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|---|---|---|---|---|---|---|---|---|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/5 bias vs variance linear regression/ex5/lib/jsonlab/loadubjson.m
| 15,574 |
utf_8
|
5974e78e71b81b1e0f76123784b951a4
|
function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a UBJSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.IntEndian [B|L]: specify the endianness of the integer fields
% in the UBJSON input data. B - Big-Endian format for
% integers (as required in the UBJSON specification);
% L - input integer fields are in Little-Endian order.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% obj=struct('string','value','array',[1 2 3]);
% ubjdata=saveubjson('obj',obj);
% dat=loadubjson(ubjdata)
% dat=loadubjson(['examples' filesep 'example1.ubj'])
% dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken fileendian systemendian
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
fileendian=upper(jsonopt('IntEndian','B',opt));
[os,maxelem,systemendian]=computer;
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
%%
function newdata=parse_collection(id,data,obj)
if(jsoncount>0 && exist('data','var'))
if(~iscell(data))
newdata=cell(1);
newdata{1}=data;
data=newdata;
end
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=double(data(j).x0x5F_ArraySize_);
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1); % TODO
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
count=double(parse_number());
end
if next_char ~= '}'
num=0;
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
%parse_char(':');
val = parse_value(varargin{:});
num=num+1;
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}' || (count>=0 && num>=count)
break;
end
%parse_char(',');
end
end
if(count==-1)
parse_char('}');
end
%%-------------------------------------------------------------------------
function [cid,len]=elem_info(type)
id=strfind('iUIlLdD',type);
dataclass={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
if(id>0)
cid=dataclass{id};
len=bytelen(id);
else
error_pos('unsupported type at position %d');
end
%%-------------------------------------------------------------------------
function [data adv]=parse_block(type,count,varargin)
global pos inStr isoct fileendian systemendian
[cid,len]=elem_info(type);
datastr=inStr(pos:pos+len*count-1);
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
id=strfind('iUIlLdD',type);
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,cid));
end
data=typecast(newdata,cid);
adv=double(len*count);
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim=[];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1);
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
if(next_char=='[')
dim=parse_array(varargin{:});
count=prod(double(dim));
else
count=double(parse_number());
end
end
if(~isempty(type))
if(count>=0)
[object adv]=parse_block(type,count,varargin{:});
if(~isempty(dim))
object=reshape(object,dim);
end
pos=pos+adv;
return;
else
endpos=matching_bracket(inStr,pos);
[cid,len]=elem_info(type);
count=(endpos-pos)/len;
[object adv]=parse_block(type,count,varargin{:});
pos=pos+adv;
parse_char(']');
return;
end
end
if next_char ~= ']'
while 1
val = parse_value(varargin{:});
object{end+1} = val;
if next_char == ']'
break;
end
%parse_char(',');
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
if(count==-1)
parse_char(']');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr esc index_esc len_esc
% len, ns = length(inStr), keyboard
type=inStr(pos);
if type ~= 'S' && type ~= 'C' && type ~= 'H'
error_pos('String starting with S expected at position %d');
else
pos = pos + 1;
end
if(type == 'C')
str=inStr(pos);
pos=pos+1;
return;
end
bytelen=double(parse_number());
if(length(inStr)>=pos+bytelen-1)
str=inStr(pos:pos+bytelen-1);
pos=pos+bytelen;
else
error_pos('End of file while expecting end of inStr');
end
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct fileendian systemendian
id=strfind('iUIlLdD',inStr(pos));
if(isempty(id))
error_pos('expecting a number at position %d');
end
type={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
datastr=inStr(pos+1:pos+bytelen(id));
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,type{id}));
end
num=typecast(newdata,type{id});
pos = pos + bytelen(id)+1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
switch(inStr(pos))
case {'S','C','H'}
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'i','U','I','l','L','d','D'}
val = parse_number(varargin{:});
return;
case 'T'
val = true;
pos = pos + 1;
return;
case 'F'
val = false;
pos = pos + 1;
return;
case {'Z','N'}
val = [];
pos = pos + 1;
return;
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos e1l e1r maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
saveubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/5 bias vs variance linear regression/ex5/lib/jsonlab/saveubjson.m
| 16,123 |
utf_8
|
61d4f51010aedbf97753396f5d2d9ec0
|
function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/17
%
% $Id: saveubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array)
% filename: a string for the file name to save the output UBJSON data
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [1|0]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSON='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a binary string in the UBJSON format (see http://ubjson.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% saveubjson('jsonmesh',jsonmesh)
% saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
json=obj2ubjson(rootname,obj,rootlevel,opt);
if(~rootisarray)
json=['{' json '}'];
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=[jsonp '(' json ')'];
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2ubjson(name,item,level,varargin)
if(iscell(item))
txt=cell2ubjson(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2ubjson(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2ubjson(name,item,level,varargin{:});
else
txt=mat2ubjson(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2ubjson(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item); % let's handle 1D cell first
if(len>1)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) '[']; name='';
else
txt='[';
end
elseif(len==0)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) 'Z']; name='';
else
txt='Z';
end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
txt=[txt obj2ubjson(name,item{i,j},level+(len>1),varargin{:})];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=struct2ubjson(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=[txt S_(checkname(name,varargin{:})) '{'];
else
txt=[txt '{'];
end
if(~isempty(names))
for e=1:length(names)
txt=[txt obj2ubjson(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:})];
end
end
txt=[txt '}'];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=str2ubjson(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
val=item(e,:);
if(len==1)
obj=['' S_(checkname(name,varargin{:})) '' '',S_(val),''];
if(isempty(name)) obj=['',S_(val),'']; end
txt=[txt,'',obj];
else
txt=[txt,'',['',S_(val),'']];
end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=mat2ubjson(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) || jsonopt('ArrayToStruct',0,varargin{:}))
cid=I_(uint32(max(size(item))));
if(isempty(name))
txt=['{' S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1)) ];
else
if(isempty(item))
txt=[S_(checkname(name,varargin{:})),'Z'];
return;
else
txt=[S_(checkname(name,varargin{:})),'{',S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1))];
end
end
else
if(isempty(name))
txt=matdata2ubjson(item,level+1,varargin{:});
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
numtxt=regexprep(regexprep(matdata2ubjson(item,level+1,varargin{:}),'^\[',''),']','');
txt=[S_(checkname(name,varargin{:})) numtxt];
else
txt=[S_(checkname(name,varargin{:})),matdata2ubjson(item,level+1,varargin{:})];
end
end
return;
end
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=[txt,S_('_ArrayIsComplex_'),'T'];
end
txt=[txt,S_('_ArrayIsSparse_'),'T'];
if(size(item,1)==1)
% Row vector, store only column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([iy(:),data'],level+2,varargin{:})];
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,data],level+2,varargin{:})];
else
% General case, store row and column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,iy,data],level+2,varargin{:})];
end
else
if(isreal(item))
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson(item(:)',level+2,varargin{:})];
else
txt=[txt,S_('_ArrayIsComplex_'),'T'];
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([real(item(:)) imag(item(:))],level+2,varargin{:})];
end
end
txt=[txt,'}'];
%%-------------------------------------------------------------------------
function txt=matdata2ubjson(mat,level,varargin)
if(isempty(mat))
txt='Z';
return;
end
if(size(mat,1)==1)
level=level-1;
end
type='';
hasnegtive=(mat<0);
if(isa(mat,'integer') || isinteger(mat) || (isfloat(mat) && all(mod(mat(:),1) == 0)))
if(isempty(hasnegtive))
if(max(mat(:))<=2^8)
type='U';
end
end
if(isempty(type))
% todo - need to consider negative ones separately
id= histc(abs(max(mat(:))),[0 2^7 2^15 2^31 2^63]);
if(isempty(find(id)))
error('high-precision data is not yet supported');
end
key='iIlL';
type=key(find(id));
end
txt=[I_a(mat(:),type,size(mat))];
elseif(islogical(mat))
logicalval='FT';
if(numel(mat)==1)
txt=logicalval(mat+1);
else
txt=['[$U#' I_a(size(mat),'l') typecast(swapbytes(uint8(mat(:)')),'uint8')];
end
else
if(numel(mat)==1)
txt=['[' D_(mat) ']'];
else
txt=D_a(mat(:),'D',size(mat));
end
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function val=S_(str)
if(length(str)==1)
val=['C' str];
else
val=['S' I_(int32(length(str))) str];
end
%%-------------------------------------------------------------------------
function val=I_(num)
if(~isinteger(num))
error('input is not an integer');
end
if(num>=0 && num<255)
val=['U' data2byte(swapbytes(cast(num,'uint8')),'uint8')];
return;
end
key='iIlL';
cid={'int8','int16','int32','int64'};
for i=1:4
if((num>0 && num<2^(i*8-1)) || (num<0 && num>=-2^(i*8-1)))
val=[key(i) data2byte(swapbytes(cast(num,cid{i})),'uint8')];
return;
end
end
error('unsupported integer');
%%-------------------------------------------------------------------------
function val=D_(num)
if(~isfloat(num))
error('input is not a float');
end
if(isa(num,'single'))
val=['d' data2byte(num,'uint8')];
else
val=['D' data2byte(num,'uint8')];
end
%%-------------------------------------------------------------------------
function data=I_a(num,type,dim,format)
id=find(ismember('iUIlL',type));
if(id==0)
error('unsupported integer array');
end
% based on UBJSON specs, all integer types are stored in big endian format
if(id==1)
data=data2byte(swapbytes(int8(num)),'uint8');
blen=1;
elseif(id==2)
data=data2byte(swapbytes(uint8(num)),'uint8');
blen=1;
elseif(id==3)
data=data2byte(swapbytes(int16(num)),'uint8');
blen=2;
elseif(id==4)
data=data2byte(swapbytes(int32(num)),'uint8');
blen=4;
elseif(id==5)
data=data2byte(swapbytes(int64(num)),'uint8');
blen=8;
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/blen)) data(:)'];
end
data=['[' data(:)'];
else
data=reshape(data,blen,numel(data)/blen);
data(2:blen+1,:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function data=D_a(num,type,dim,format)
id=find(ismember('dD',type));
if(id==0)
error('unsupported float array');
end
if(id==1)
data=data2byte(single(num),'uint8');
elseif(id==2)
data=data2byte(double(num),'uint8');
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/(id*4))) data(:)'];
end
data=['[' data];
else
data=reshape(data,(id*4),length(data)/(id*4));
data(2:(id*4+1),:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function bytes=data2byte(varargin)
bytes=typecast(varargin{:});
bytes=bytes(:)';
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submit.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/3 neural nets/ex3/submit.m
| 1,567 |
utf_8
|
1dba733a05282b2db9f2284548483b81
|
function submit()
addpath('./lib');
conf.assignmentSlug = 'multi-class-classification-and-neural-networks';
conf.itemName = 'Multi-class Classification and Neural Networks';
conf.partArrays = { ...
{ ...
'1', ...
{ 'lrCostFunction.m' }, ...
'Regularized Logistic Regression', ...
}, ...
{ ...
'2', ...
{ 'oneVsAll.m' }, ...
'One-vs-All Classifier Training', ...
}, ...
{ ...
'3', ...
{ 'predictOneVsAll.m' }, ...
'One-vs-All Classifier Prediction', ...
}, ...
{ ...
'4', ...
{ 'predict.m' }, ...
'Neural Network Prediction Function' ...
}, ...
};
conf.output = @output;
submitWithConfiguration(conf);
end
function out = output(partId, auxdata)
% Random Test Cases
X = [ones(20,1) (exp(1) * sin(1:1:20))' (exp(0.5) * cos(1:1:20))'];
y = sin(X(:,1) + X(:,2)) > 0;
Xm = [ -1 -1 ; -1 -2 ; -2 -1 ; -2 -2 ; ...
1 1 ; 1 2 ; 2 1 ; 2 2 ; ...
-1 1 ; -1 2 ; -2 1 ; -2 2 ; ...
1 -1 ; 1 -2 ; -2 -1 ; -2 -2 ];
ym = [ 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 ]';
t1 = sin(reshape(1:2:24, 4, 3));
t2 = cos(reshape(1:2:40, 4, 5));
if partId == '1'
[J, grad] = lrCostFunction([0.25 0.5 -0.5]', X, y, 0.1);
out = sprintf('%0.5f ', J);
out = [out sprintf('%0.5f ', grad)];
elseif partId == '2'
out = sprintf('%0.5f ', oneVsAll(Xm, ym, 4, 0.1));
elseif partId == '3'
out = sprintf('%0.5f ', predictOneVsAll(t1, Xm));
elseif partId == '4'
out = sprintf('%0.5f ', predict(t1, t2, Xm));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submitWithConfiguration.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/3 neural nets/ex3/lib/submitWithConfiguration.m
| 3,926 |
utf_8
|
f889a7cf3dc6c1c2877566d38df1bec8
|
function submitWithConfiguration(conf)
% Note: has the "certificate" patch from Liran for Windows-like systems
addpath('./lib/jsonlab');
%keyboard
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = promptToken('', '', tokenFile);
end
if isempty(token)
fprintf('!! Submission Cancelled\n');
return
end
try
response = submitParts(conf, email, token, parts);
catch
e = lasterror();
fprintf( ...
'!! Submission failed: unexpected error: %s\n', ...
e.message);
fprintf('!! Please try again later.\n');
return
end
if isfield(response, 'errorMessage')
fprintf('!! Submission failed: %s\n', response.errorMessage);
else
showFeedback(parts, response);
save(tokenFile, 'email', 'token');
end
end
function [email token] = promptToken(email, existingToken, tokenFile)
if (~isempty(email) && ~isempty(existingToken))
prompt = sprintf( ...
'Use token from last successful submission (%s)? (Y/n): ', ...
email);
reenter = input(prompt, 's');
if (isempty(reenter) || reenter(1) == 'Y' || reenter(1) == 'y')
token = existingToken;
return;
else
delete(tokenFile);
end
end
email = input('Login (email address): ', 's');
token = input('Token: ', 's');
end
function isValid = isValidPartOptionIndex(partOptions, i)
isValid = (~isempty(i)) && (1 <= i) && (i <= numel(partOptions));
end
function response = submitParts(conf, email, token, parts)
body = makePostBody(conf, email, token, parts);
submissionUrl = submissionUrl();
params = {'jsonBody', body};
%responseBody = urlread(submissionUrl, 'post', params);
[code, responseBody] = system(sprintf('echo jsonBody=%s | curl -k -X POST -d @- %s', body, submissionUrl));
response = loadjson(responseBody);
end
function body = makePostBody(conf, email, token, parts)
bodyStruct.assignmentSlug = conf.assignmentSlug;
bodyStruct.submitterEmail = email;
bodyStruct.secret = token;
bodyStruct.parts = makePartsStruct(conf, parts);
opt.Compact = 1;
body = savejson('', bodyStruct, opt);
end
function partsStruct = makePartsStruct(conf, parts)
for part = parts
partId = part{:}.id;
fieldName = makeValidFieldName(partId);
outputStruct.output = conf.output(partId);
partsStruct.(fieldName) = outputStruct;
end
end
function [parts] = parts(conf)
parts = {};
for partArray = conf.partArrays
part.id = partArray{:}{1};
part.sourceFiles = partArray{:}{2};
part.name = partArray{:}{3};
parts{end + 1} = part;
end
end
function showFeedback(parts, response)
fprintf('== \n');
fprintf('== %43s | %9s | %-s\n', 'Part Name', 'Score', 'Feedback');
fprintf('== %43s | %9s | %-s\n', '---------', '-----', '--------');
for part = parts
score = '';
partFeedback = '';
partFeedback = response.partFeedbacks.(makeValidFieldName(part{:}.id));
partEvaluation = response.partEvaluations.(makeValidFieldName(part{:}.id));
score = sprintf('%d / %3d', partEvaluation.score, partEvaluation.maxScore);
fprintf('== %43s | %9s | %-s\n', part{:}.name, score, partFeedback);
end
evaluation = response.evaluation;
totalScore = sprintf('%d / %d', evaluation.score, evaluation.maxScore);
fprintf('== --------------------------------\n');
fprintf('== %43s | %9s | %-s\n', '', totalScore, '');
fprintf('== \n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Service configuration
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function submissionUrl = submissionUrl()
submissionUrl = 'https://www-origin.coursera.org/api/onDemandProgrammingImmediateFormSubmissions.v1';
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
savejson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/3 neural nets/ex3/lib/jsonlab/savejson.m
| 17,462 |
utf_8
|
861b534fc35ffe982b53ca3ca83143bf
|
function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09
%
% $Id: savejson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array).
% filename: a string for the file name to save the output JSON data.
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.FloatFormat ['%.10g'|string]: format to show each numeric element
% of a 1D/2D array;
% opt.ArrayIndent [1|0]: if 1, output explicit data array with
% precedent indentation; if 0, no indentation
% opt.ArrayToStruct[0|1]: when set to 0, savejson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [0|1]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, savejson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.Inf ['"$1_Inf_"'|string]: a customized regular expression pattern
% to represent +/-Inf. The matched pattern is '([-+]*)Inf'
% and $1 represents the sign. For those who want to use
% 1e999 to represent Inf, they can set opt.Inf to '$11e999'
% opt.NaN ['"_NaN_"'|string]: a customized regular expression pattern
% to represent NaN
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSONP='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
% opt.SaveBinary [0|1]: 1 - save the JSON file in binary mode; 0 - text mode.
% opt.Compact [0|1]: 1- out compact JSON format (remove all newlines and tabs)
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a string in the JSON format (see http://json.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% savejson('jmesh',jsonmesh)
% savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
whitespaces=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
if(jsonopt('Compact',0,opt)==1)
whitespaces=struct('tab','','newline','','sep',',');
end
if(~isfield(opt,'whitespaces_'))
opt.whitespaces_=whitespaces;
end
nl=whitespaces.newline;
json=obj2json(rootname,obj,rootlevel,opt);
if(rootisarray)
json=sprintf('%s%s',json,nl);
else
json=sprintf('{%s%s%s}\n',nl,json,nl);
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=sprintf('%s(%s);%s',jsonp,json,nl);
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
if(jsonopt('SaveBinary',0,opt)==1)
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
else
fid = fopen(opt.FileName, 'wt');
fwrite(fid,json,'char');
end
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2json(name,item,level,varargin)
if(iscell(item))
txt=cell2json(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2json(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2json(name,item,level,varargin{:});
else
txt=mat2json(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2json(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=jsonopt('whitespaces_',struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n')),varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
nl=ws.newline;
if(len>1)
if(~isempty(name))
txt=sprintf('%s"%s": [%s',padding0, checkname(name,varargin{:}),nl); name='';
else
txt=sprintf('%s[%s',padding0,nl);
end
elseif(len==0)
if(~isempty(name))
txt=sprintf('%s"%s": []',padding0, checkname(name,varargin{:})); name='';
else
txt=sprintf('%s[]',padding0);
end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
txt=sprintf('%s%s',txt,obj2json(name,item{i,j},level+(dim(1)>1)+1,varargin{:}));
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
%if(j==dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=struct2json(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
padding1=repmat(ws.tab,1,level+(dim(1)>1)+(len>1));
nl=ws.newline;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding0,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding0,nl); end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=sprintf('%s%s"%s": {%s',txt,padding1, checkname(name,varargin{:}),nl);
else
txt=sprintf('%s%s{%s',txt,padding1,nl);
end
if(~isempty(names))
for e=1:length(names)
txt=sprintf('%s%s',txt,obj2json(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:}));
if(e<length(names)) txt=sprintf('%s%s',txt,','); end
txt=sprintf('%s%s',txt,nl);
end
end
txt=sprintf('%s%s}',txt,padding1);
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=str2json(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding1,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding1,nl); end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
if(isoct)
val=regexprep(item(e,:),'\\','\\');
val=regexprep(val,'"','\"');
val=regexprep(val,'^"','\"');
else
val=regexprep(item(e,:),'\\','\\\\');
val=regexprep(val,'"','\\"');
val=regexprep(val,'^"','\\"');
end
val=escapejsonstring(val);
if(len==1)
obj=['"' checkname(name,varargin{:}) '": ' '"',val,'"'];
if(isempty(name)) obj=['"',val,'"']; end
txt=sprintf('%s%s%s%s',txt,padding1,obj);
else
txt=sprintf('%s%s%s%s',txt,padding0,['"',val,'"']);
end
if(e==len) sep=''; end
txt=sprintf('%s%s',txt,sep);
end
if(len>1) txt=sprintf('%s%s%s%s',txt,nl,padding1,']'); end
%%-------------------------------------------------------------------------
function txt=mat2json(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) ||jsonopt('ArrayToStruct',0,varargin{:}))
if(isempty(name))
txt=sprintf('%s{%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
else
txt=sprintf('%s"%s": {%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,checkname(name,varargin{:}),nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
end
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1 && level>0)
numtxt=regexprep(regexprep(matdata2json(item,level+1,varargin{:}),'^\[',''),']','');
else
numtxt=matdata2json(item,level+1,varargin{:});
end
if(isempty(name))
txt=sprintf('%s%s',padding1,numtxt);
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
else
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
end
end
return;
end
dataformat='%s%s%s%s%s';
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsSparse_": ','1', sep);
if(size(item,1)==1)
% Row vector, store only column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([iy(:),data'],level+2,varargin{:}), nl);
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,data],level+2,varargin{:}), nl);
else
% General case, store row and column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,iy,data],level+2,varargin{:}), nl);
end
else
if(isreal(item))
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json(item(:)',level+2,varargin{:}), nl);
else
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([real(item(:)) imag(item(:))],level+2,varargin{:}), nl);
end
end
txt=sprintf('%s%s%s',txt,padding1,'}');
%%-------------------------------------------------------------------------
function txt=matdata2json(mat,level,varargin)
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
tab=ws.tab;
nl=ws.newline;
if(size(mat,1)==1)
pre='';
post='';
level=level-1;
else
pre=sprintf('[%s',nl);
post=sprintf('%s%s]',nl,repmat(tab,1,level-1));
end
if(isempty(mat))
txt='null';
return;
end
floatformat=jsonopt('FloatFormat','%.10g',varargin{:});
%if(numel(mat)>1)
formatstr=['[' repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf('],%s',nl)]];
%else
% formatstr=[repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf(',\n')]];
%end
if(nargin>=2 && size(mat,1)>1 && jsonopt('ArrayIndent',1,varargin{:})==1)
formatstr=[repmat(tab,1,level) formatstr];
end
txt=sprintf(formatstr,mat');
txt(end-length(nl):end)=[];
if(islogical(mat) && jsonopt('ParseLogical',0,varargin{:})==1)
txt=regexprep(txt,'1','true');
txt=regexprep(txt,'0','false');
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],\n['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
txt=[pre txt post];
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function newstr=escapejsonstring(str)
newstr=str;
isoct=exist('OCTAVE_VERSION','builtin');
if(isoct)
vv=sscanf(OCTAVE_VERSION,'%f');
if(vv(1)>=3.8) isoct=0; end
end
if(isoct)
escapechars={'\a','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},escapechars{i});
end
else
escapechars={'\a','\b','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},regexprep(escapechars{i},'\\','\\\\'));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/3 neural nets/ex3/lib/jsonlab/loadjson.m
| 18,884 |
ibm852
|
d21f0844f91f2dbb9ea8df00eda346ca
|
function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% Nedialko Krouchev: http://www.mathworks.com/matlabcentral/fileexchange/25713
% created on 2009/11/02
% François Glineur: http://www.mathworks.com/matlabcentral/fileexchange/23393
% created on 2009/03/22
% Joel Feenstra:
% http://www.mathworks.com/matlabcentral/fileexchange/20565
% created on 2008/07/03
%
% $Id: loadjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a JSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.FastArrayParser [1|0 or integer]: if set to 1, use a
% speed-optimized array parser when loading an
% array object. The fast array parser may
% collapse block arrays into a single large
% array similar to rules defined in cell2mat; 0 to
% use a legacy parser; if set to a larger-than-1
% value, this option will specify the minimum
% dimension to enable the fast array parser. For
% example, if the input is a 3D array, setting
% FastArrayParser to 1 will return a 3D array;
% setting to 2 will return a cell array of 2D
% arrays; setting to 3 will return to a 2D cell
% array of 1D vectors; setting to 4 will return a
% 3D cell array.
% opt.ShowProgress [0|1]: if set to 1, loadjson displays a progress bar.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
% dat=loadjson(['examples' filesep 'example1.json'])
% dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
if(jsonopt('ShowProgress',0,opt)==1)
opt.progressbar_=waitbar(0,'loading ...');
end
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
if(isfield(opt,'progressbar_'))
close(opt.progressbar_);
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=data(j).x0x5F_ArraySize_;
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
if next_char ~= '}'
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
parse_char(':');
val = parse_value(varargin{:});
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}'
break;
end
parse_char(',');
end
end
parse_char('}');
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim2=[];
arraydepth=jsonopt('JSONLAB_ArrayDepth_',1,varargin{:});
pbar=jsonopt('progressbar_',-1,varargin{:});
if next_char ~= ']'
if(jsonopt('FastArrayParser',1,varargin{:})>=1 && arraydepth>=jsonopt('FastArrayParser',1,varargin{:}))
[endpos, e1l, e1r, maxlevel]=matching_bracket(inStr,pos);
arraystr=['[' inStr(pos:endpos)];
arraystr=regexprep(arraystr,'"_NaN_"','NaN');
arraystr=regexprep(arraystr,'"([-+]*)_Inf_"','$1Inf');
arraystr(arraystr==sprintf('\n'))=[];
arraystr(arraystr==sprintf('\r'))=[];
%arraystr=regexprep(arraystr,'\s*,',','); % this is slow,sometimes needed
if(~isempty(e1l) && ~isempty(e1r)) % the array is in 2D or higher D
astr=inStr((e1l+1):(e1r-1));
astr=regexprep(astr,'"_NaN_"','NaN');
astr=regexprep(astr,'"([-+]*)_Inf_"','$1Inf');
astr(astr==sprintf('\n'))=[];
astr(astr==sprintf('\r'))=[];
astr(astr==' ')='';
if(isempty(find(astr=='[', 1))) % array is 2D
dim2=length(sscanf(astr,'%f,',[1 inf]));
end
else % array is 1D
astr=arraystr(2:end-1);
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',[1,inf]);
if(nextidx>=length(astr)-1)
object=obj;
pos=endpos;
parse_char(']');
return;
end
end
if(~isempty(dim2))
astr=arraystr;
astr(astr=='[')='';
astr(astr==']')='';
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',inf);
if(nextidx>=length(astr)-1)
object=reshape(obj,dim2,numel(obj)/dim2)';
pos=endpos;
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
return;
end
end
arraystr=regexprep(arraystr,'\]\s*,','];');
else
arraystr='[';
end
try
if(isoct && regexp(arraystr,'"','once'))
error('Octave eval can produce empty cells for JSON-like input');
end
object=eval(arraystr);
pos=endpos;
catch
while 1
newopt=varargin2struct(varargin{:},'JSONLAB_ArrayDepth_',arraydepth+1);
val = parse_value(newopt);
object{end+1} = val;
if next_char == ']'
break;
end
parse_char(',');
end
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr len esc index_esc len_esc
% len, ns = length(inStr), keyboard
if inStr(pos) ~= '"'
error_pos('String starting with " expected at position %d');
else
pos = pos + 1;
end
str = '';
while pos <= len
while index_esc <= len_esc && esc(index_esc) < pos
index_esc = index_esc + 1;
end
if index_esc > len_esc
str = [str inStr(pos:len)];
pos = len + 1;
break;
else
str = [str inStr(pos:esc(index_esc)-1)];
pos = esc(index_esc);
end
nstr = length(str); switch inStr(pos)
case '"'
pos = pos + 1;
if(~isempty(str))
if(strcmp(str,'_Inf_'))
str=Inf;
elseif(strcmp(str,'-_Inf_'))
str=-Inf;
elseif(strcmp(str,'_NaN_'))
str=NaN;
end
end
return;
case '\'
if pos+1 > len
error_pos('End of file reached right after escape character');
end
pos = pos + 1;
switch inStr(pos)
case {'"' '\' '/'}
str(nstr+1) = inStr(pos);
pos = pos + 1;
case {'b' 'f' 'n' 'r' 't'}
str(nstr+1) = sprintf(['\' inStr(pos)]);
pos = pos + 1;
case 'u'
if pos+4 > len
error_pos('End of file reached in escaped unicode character');
end
str(nstr+(1:6)) = inStr(pos-1:pos+4);
pos = pos + 5;
end
otherwise % should never happen
str(nstr+1) = inStr(pos), keyboard
pos = pos + 1;
end
end
error_pos('End of file while expecting end of inStr');
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct
currstr=inStr(pos:end);
numstr=0;
if(isoct~=0)
numstr=regexp(currstr,'^\s*-?(?:0|[1-9]\d*)(?:\.\d+)?(?:[eE][+\-]?\d+)?','end');
[num, one] = sscanf(currstr, '%f', 1);
delta=numstr+1;
else
[num, one, err, delta] = sscanf(currstr, '%f', 1);
if ~isempty(err)
error_pos('Error reading number at position %d');
end
end
pos = pos + delta-1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
pbar=jsonopt('progressbar_',-1,varargin{:});
if(pbar>0)
waitbar(pos/len,pbar,'loading ...');
end
switch(inStr(pos))
case '"'
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'-','0','1','2','3','4','5','6','7','8','9'}
val = parse_number(varargin{:});
return;
case 't'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'true')
val = true;
pos = pos + 4;
return;
end
case 'f'
if pos+4 <= len && strcmpi(inStr(pos:pos+4), 'false')
val = false;
pos = pos + 5;
return;
end
case 'n'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'null')
val = [];
pos = pos + 4;
return;
end
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
% Hard to believe but sprintf("%X") is broken in Octave 4.0.0
% str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
str=sprintf('x0x%s_%s',xxNumToHexStr(char(str(1))),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos, e1l, e1r, maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/3 neural nets/ex3/lib/jsonlab/loadubjson.m
| 15,574 |
utf_8
|
5974e78e71b81b1e0f76123784b951a4
|
function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a UBJSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.IntEndian [B|L]: specify the endianness of the integer fields
% in the UBJSON input data. B - Big-Endian format for
% integers (as required in the UBJSON specification);
% L - input integer fields are in Little-Endian order.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% obj=struct('string','value','array',[1 2 3]);
% ubjdata=saveubjson('obj',obj);
% dat=loadubjson(ubjdata)
% dat=loadubjson(['examples' filesep 'example1.ubj'])
% dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken fileendian systemendian
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
fileendian=upper(jsonopt('IntEndian','B',opt));
[os,maxelem,systemendian]=computer;
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
%%
function newdata=parse_collection(id,data,obj)
if(jsoncount>0 && exist('data','var'))
if(~iscell(data))
newdata=cell(1);
newdata{1}=data;
data=newdata;
end
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=double(data(j).x0x5F_ArraySize_);
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1); % TODO
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
count=double(parse_number());
end
if next_char ~= '}'
num=0;
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
%parse_char(':');
val = parse_value(varargin{:});
num=num+1;
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}' || (count>=0 && num>=count)
break;
end
%parse_char(',');
end
end
if(count==-1)
parse_char('}');
end
%%-------------------------------------------------------------------------
function [cid,len]=elem_info(type)
id=strfind('iUIlLdD',type);
dataclass={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
if(id>0)
cid=dataclass{id};
len=bytelen(id);
else
error_pos('unsupported type at position %d');
end
%%-------------------------------------------------------------------------
function [data adv]=parse_block(type,count,varargin)
global pos inStr isoct fileendian systemendian
[cid,len]=elem_info(type);
datastr=inStr(pos:pos+len*count-1);
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
id=strfind('iUIlLdD',type);
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,cid));
end
data=typecast(newdata,cid);
adv=double(len*count);
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim=[];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1);
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
if(next_char=='[')
dim=parse_array(varargin{:});
count=prod(double(dim));
else
count=double(parse_number());
end
end
if(~isempty(type))
if(count>=0)
[object adv]=parse_block(type,count,varargin{:});
if(~isempty(dim))
object=reshape(object,dim);
end
pos=pos+adv;
return;
else
endpos=matching_bracket(inStr,pos);
[cid,len]=elem_info(type);
count=(endpos-pos)/len;
[object adv]=parse_block(type,count,varargin{:});
pos=pos+adv;
parse_char(']');
return;
end
end
if next_char ~= ']'
while 1
val = parse_value(varargin{:});
object{end+1} = val;
if next_char == ']'
break;
end
%parse_char(',');
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
if(count==-1)
parse_char(']');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr esc index_esc len_esc
% len, ns = length(inStr), keyboard
type=inStr(pos);
if type ~= 'S' && type ~= 'C' && type ~= 'H'
error_pos('String starting with S expected at position %d');
else
pos = pos + 1;
end
if(type == 'C')
str=inStr(pos);
pos=pos+1;
return;
end
bytelen=double(parse_number());
if(length(inStr)>=pos+bytelen-1)
str=inStr(pos:pos+bytelen-1);
pos=pos+bytelen;
else
error_pos('End of file while expecting end of inStr');
end
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct fileendian systemendian
id=strfind('iUIlLdD',inStr(pos));
if(isempty(id))
error_pos('expecting a number at position %d');
end
type={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
datastr=inStr(pos+1:pos+bytelen(id));
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,type{id}));
end
num=typecast(newdata,type{id});
pos = pos + bytelen(id)+1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
switch(inStr(pos))
case {'S','C','H'}
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'i','U','I','l','L','d','D'}
val = parse_number(varargin{:});
return;
case 'T'
val = true;
pos = pos + 1;
return;
case 'F'
val = false;
pos = pos + 1;
return;
case {'Z','N'}
val = [];
pos = pos + 1;
return;
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos e1l e1r maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
saveubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/3 neural nets/ex3/lib/jsonlab/saveubjson.m
| 16,123 |
utf_8
|
61d4f51010aedbf97753396f5d2d9ec0
|
function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/17
%
% $Id: saveubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array)
% filename: a string for the file name to save the output UBJSON data
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [1|0]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSON='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a binary string in the UBJSON format (see http://ubjson.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% saveubjson('jsonmesh',jsonmesh)
% saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
json=obj2ubjson(rootname,obj,rootlevel,opt);
if(~rootisarray)
json=['{' json '}'];
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=[jsonp '(' json ')'];
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2ubjson(name,item,level,varargin)
if(iscell(item))
txt=cell2ubjson(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2ubjson(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2ubjson(name,item,level,varargin{:});
else
txt=mat2ubjson(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2ubjson(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item); % let's handle 1D cell first
if(len>1)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) '[']; name='';
else
txt='[';
end
elseif(len==0)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) 'Z']; name='';
else
txt='Z';
end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
txt=[txt obj2ubjson(name,item{i,j},level+(len>1),varargin{:})];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=struct2ubjson(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=[txt S_(checkname(name,varargin{:})) '{'];
else
txt=[txt '{'];
end
if(~isempty(names))
for e=1:length(names)
txt=[txt obj2ubjson(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:})];
end
end
txt=[txt '}'];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=str2ubjson(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
val=item(e,:);
if(len==1)
obj=['' S_(checkname(name,varargin{:})) '' '',S_(val),''];
if(isempty(name)) obj=['',S_(val),'']; end
txt=[txt,'',obj];
else
txt=[txt,'',['',S_(val),'']];
end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=mat2ubjson(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) || jsonopt('ArrayToStruct',0,varargin{:}))
cid=I_(uint32(max(size(item))));
if(isempty(name))
txt=['{' S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1)) ];
else
if(isempty(item))
txt=[S_(checkname(name,varargin{:})),'Z'];
return;
else
txt=[S_(checkname(name,varargin{:})),'{',S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1))];
end
end
else
if(isempty(name))
txt=matdata2ubjson(item,level+1,varargin{:});
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
numtxt=regexprep(regexprep(matdata2ubjson(item,level+1,varargin{:}),'^\[',''),']','');
txt=[S_(checkname(name,varargin{:})) numtxt];
else
txt=[S_(checkname(name,varargin{:})),matdata2ubjson(item,level+1,varargin{:})];
end
end
return;
end
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=[txt,S_('_ArrayIsComplex_'),'T'];
end
txt=[txt,S_('_ArrayIsSparse_'),'T'];
if(size(item,1)==1)
% Row vector, store only column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([iy(:),data'],level+2,varargin{:})];
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,data],level+2,varargin{:})];
else
% General case, store row and column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,iy,data],level+2,varargin{:})];
end
else
if(isreal(item))
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson(item(:)',level+2,varargin{:})];
else
txt=[txt,S_('_ArrayIsComplex_'),'T'];
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([real(item(:)) imag(item(:))],level+2,varargin{:})];
end
end
txt=[txt,'}'];
%%-------------------------------------------------------------------------
function txt=matdata2ubjson(mat,level,varargin)
if(isempty(mat))
txt='Z';
return;
end
if(size(mat,1)==1)
level=level-1;
end
type='';
hasnegtive=(mat<0);
if(isa(mat,'integer') || isinteger(mat) || (isfloat(mat) && all(mod(mat(:),1) == 0)))
if(isempty(hasnegtive))
if(max(mat(:))<=2^8)
type='U';
end
end
if(isempty(type))
% todo - need to consider negative ones separately
id= histc(abs(max(mat(:))),[0 2^7 2^15 2^31 2^63]);
if(isempty(find(id)))
error('high-precision data is not yet supported');
end
key='iIlL';
type=key(find(id));
end
txt=[I_a(mat(:),type,size(mat))];
elseif(islogical(mat))
logicalval='FT';
if(numel(mat)==1)
txt=logicalval(mat+1);
else
txt=['[$U#' I_a(size(mat),'l') typecast(swapbytes(uint8(mat(:)')),'uint8')];
end
else
if(numel(mat)==1)
txt=['[' D_(mat) ']'];
else
txt=D_a(mat(:),'D',size(mat));
end
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function val=S_(str)
if(length(str)==1)
val=['C' str];
else
val=['S' I_(int32(length(str))) str];
end
%%-------------------------------------------------------------------------
function val=I_(num)
if(~isinteger(num))
error('input is not an integer');
end
if(num>=0 && num<255)
val=['U' data2byte(swapbytes(cast(num,'uint8')),'uint8')];
return;
end
key='iIlL';
cid={'int8','int16','int32','int64'};
for i=1:4
if((num>0 && num<2^(i*8-1)) || (num<0 && num>=-2^(i*8-1)))
val=[key(i) data2byte(swapbytes(cast(num,cid{i})),'uint8')];
return;
end
end
error('unsupported integer');
%%-------------------------------------------------------------------------
function val=D_(num)
if(~isfloat(num))
error('input is not a float');
end
if(isa(num,'single'))
val=['d' data2byte(num,'uint8')];
else
val=['D' data2byte(num,'uint8')];
end
%%-------------------------------------------------------------------------
function data=I_a(num,type,dim,format)
id=find(ismember('iUIlL',type));
if(id==0)
error('unsupported integer array');
end
% based on UBJSON specs, all integer types are stored in big endian format
if(id==1)
data=data2byte(swapbytes(int8(num)),'uint8');
blen=1;
elseif(id==2)
data=data2byte(swapbytes(uint8(num)),'uint8');
blen=1;
elseif(id==3)
data=data2byte(swapbytes(int16(num)),'uint8');
blen=2;
elseif(id==4)
data=data2byte(swapbytes(int32(num)),'uint8');
blen=4;
elseif(id==5)
data=data2byte(swapbytes(int64(num)),'uint8');
blen=8;
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/blen)) data(:)'];
end
data=['[' data(:)'];
else
data=reshape(data,blen,numel(data)/blen);
data(2:blen+1,:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function data=D_a(num,type,dim,format)
id=find(ismember('dD',type));
if(id==0)
error('unsupported float array');
end
if(id==1)
data=data2byte(single(num),'uint8');
elseif(id==2)
data=data2byte(double(num),'uint8');
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/(id*4))) data(:)'];
end
data=['[' data];
else
data=reshape(data,(id*4),length(data)/(id*4));
data(2:(id*4+1),:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function bytes=data2byte(varargin)
bytes=typecast(varargin{:});
bytes=bytes(:)';
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submit.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/8 Anomaly detection and recommender system/ex8/submit.m
| 2,064 |
utf_8
|
7c4fcf60df3a7e09d05a74f7772fed3b
|
function submit()
addpath('./lib');
conf.assignmentSlug = 'anomaly-detection-and-recommender-systems';
conf.itemName = 'Anomaly Detection and Recommender Systems';
conf.partArrays = { ...
{ ...
'1', ...
{ 'estimateGaussian.m' }, ...
'Estimate Gaussian Parameters', ...
}, ...
{ ...
'2', ...
{ 'selectThreshold.m' }, ...
'Select Threshold', ...
}, ...
{ ...
'3', ...
{ 'cofiCostFunc.m' }, ...
'Collaborative Filtering Cost', ...
}, ...
{ ...
'4', ...
{ 'cofiCostFunc.m' }, ...
'Collaborative Filtering Gradient', ...
}, ...
{ ...
'5', ...
{ 'cofiCostFunc.m' }, ...
'Regularized Cost', ...
}, ...
{ ...
'6', ...
{ 'cofiCostFunc.m' }, ...
'Regularized Gradient', ...
}, ...
};
conf.output = @output;
submitWithConfiguration(conf);
end
function out = output(partId, auxstring)
% Random Test Cases
n_u = 3; n_m = 4; n = 5;
X = reshape(sin(1:n_m*n), n_m, n);
Theta = reshape(cos(1:n_u*n), n_u, n);
Y = reshape(sin(1:2:2*n_m*n_u), n_m, n_u);
R = Y > 0.5;
pval = [abs(Y(:)) ; 0.001; 1];
yval = [R(:) ; 1; 0];
params = [X(:); Theta(:)];
if partId == '1'
[mu sigma2] = estimateGaussian(X);
out = sprintf('%0.5f ', [mu(:); sigma2(:)]);
elseif partId == '2'
[bestEpsilon bestF1] = selectThreshold(yval, pval);
out = sprintf('%0.5f ', [bestEpsilon(:); bestF1(:)]);
elseif partId == '3'
[J] = cofiCostFunc(params, Y, R, n_u, n_m, ...
n, 0);
out = sprintf('%0.5f ', J(:));
elseif partId == '4'
[J, grad] = cofiCostFunc(params, Y, R, n_u, n_m, ...
n, 0);
out = sprintf('%0.5f ', grad(:));
elseif partId == '5'
[J] = cofiCostFunc(params, Y, R, n_u, n_m, ...
n, 1.5);
out = sprintf('%0.5f ', J(:));
elseif partId == '6'
[J, grad] = cofiCostFunc(params, Y, R, n_u, n_m, ...
n, 1.5);
out = sprintf('%0.5f ', grad(:));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submitWithConfiguration.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/8 Anomaly detection and recommender system/ex8/lib/submitWithConfiguration.m
| 3,926 |
utf_8
|
f889a7cf3dc6c1c2877566d38df1bec8
|
function submitWithConfiguration(conf)
% Note: has the "certificate" patch from Liran for Windows-like systems
addpath('./lib/jsonlab');
%keyboard
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = promptToken('', '', tokenFile);
end
if isempty(token)
fprintf('!! Submission Cancelled\n');
return
end
try
response = submitParts(conf, email, token, parts);
catch
e = lasterror();
fprintf( ...
'!! Submission failed: unexpected error: %s\n', ...
e.message);
fprintf('!! Please try again later.\n');
return
end
if isfield(response, 'errorMessage')
fprintf('!! Submission failed: %s\n', response.errorMessage);
else
showFeedback(parts, response);
save(tokenFile, 'email', 'token');
end
end
function [email token] = promptToken(email, existingToken, tokenFile)
if (~isempty(email) && ~isempty(existingToken))
prompt = sprintf( ...
'Use token from last successful submission (%s)? (Y/n): ', ...
email);
reenter = input(prompt, 's');
if (isempty(reenter) || reenter(1) == 'Y' || reenter(1) == 'y')
token = existingToken;
return;
else
delete(tokenFile);
end
end
email = input('Login (email address): ', 's');
token = input('Token: ', 's');
end
function isValid = isValidPartOptionIndex(partOptions, i)
isValid = (~isempty(i)) && (1 <= i) && (i <= numel(partOptions));
end
function response = submitParts(conf, email, token, parts)
body = makePostBody(conf, email, token, parts);
submissionUrl = submissionUrl();
params = {'jsonBody', body};
%responseBody = urlread(submissionUrl, 'post', params);
[code, responseBody] = system(sprintf('echo jsonBody=%s | curl -k -X POST -d @- %s', body, submissionUrl));
response = loadjson(responseBody);
end
function body = makePostBody(conf, email, token, parts)
bodyStruct.assignmentSlug = conf.assignmentSlug;
bodyStruct.submitterEmail = email;
bodyStruct.secret = token;
bodyStruct.parts = makePartsStruct(conf, parts);
opt.Compact = 1;
body = savejson('', bodyStruct, opt);
end
function partsStruct = makePartsStruct(conf, parts)
for part = parts
partId = part{:}.id;
fieldName = makeValidFieldName(partId);
outputStruct.output = conf.output(partId);
partsStruct.(fieldName) = outputStruct;
end
end
function [parts] = parts(conf)
parts = {};
for partArray = conf.partArrays
part.id = partArray{:}{1};
part.sourceFiles = partArray{:}{2};
part.name = partArray{:}{3};
parts{end + 1} = part;
end
end
function showFeedback(parts, response)
fprintf('== \n');
fprintf('== %43s | %9s | %-s\n', 'Part Name', 'Score', 'Feedback');
fprintf('== %43s | %9s | %-s\n', '---------', '-----', '--------');
for part = parts
score = '';
partFeedback = '';
partFeedback = response.partFeedbacks.(makeValidFieldName(part{:}.id));
partEvaluation = response.partEvaluations.(makeValidFieldName(part{:}.id));
score = sprintf('%d / %3d', partEvaluation.score, partEvaluation.maxScore);
fprintf('== %43s | %9s | %-s\n', part{:}.name, score, partFeedback);
end
evaluation = response.evaluation;
totalScore = sprintf('%d / %d', evaluation.score, evaluation.maxScore);
fprintf('== --------------------------------\n');
fprintf('== %43s | %9s | %-s\n', '', totalScore, '');
fprintf('== \n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Service configuration
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function submissionUrl = submissionUrl()
submissionUrl = 'https://www-origin.coursera.org/api/onDemandProgrammingImmediateFormSubmissions.v1';
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
savejson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/8 Anomaly detection and recommender system/ex8/lib/jsonlab/savejson.m
| 17,462 |
utf_8
|
861b534fc35ffe982b53ca3ca83143bf
|
function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09
%
% $Id: savejson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array).
% filename: a string for the file name to save the output JSON data.
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.FloatFormat ['%.10g'|string]: format to show each numeric element
% of a 1D/2D array;
% opt.ArrayIndent [1|0]: if 1, output explicit data array with
% precedent indentation; if 0, no indentation
% opt.ArrayToStruct[0|1]: when set to 0, savejson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [0|1]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, savejson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.Inf ['"$1_Inf_"'|string]: a customized regular expression pattern
% to represent +/-Inf. The matched pattern is '([-+]*)Inf'
% and $1 represents the sign. For those who want to use
% 1e999 to represent Inf, they can set opt.Inf to '$11e999'
% opt.NaN ['"_NaN_"'|string]: a customized regular expression pattern
% to represent NaN
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSONP='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
% opt.SaveBinary [0|1]: 1 - save the JSON file in binary mode; 0 - text mode.
% opt.Compact [0|1]: 1- out compact JSON format (remove all newlines and tabs)
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a string in the JSON format (see http://json.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% savejson('jmesh',jsonmesh)
% savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
whitespaces=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
if(jsonopt('Compact',0,opt)==1)
whitespaces=struct('tab','','newline','','sep',',');
end
if(~isfield(opt,'whitespaces_'))
opt.whitespaces_=whitespaces;
end
nl=whitespaces.newline;
json=obj2json(rootname,obj,rootlevel,opt);
if(rootisarray)
json=sprintf('%s%s',json,nl);
else
json=sprintf('{%s%s%s}\n',nl,json,nl);
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=sprintf('%s(%s);%s',jsonp,json,nl);
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
if(jsonopt('SaveBinary',0,opt)==1)
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
else
fid = fopen(opt.FileName, 'wt');
fwrite(fid,json,'char');
end
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2json(name,item,level,varargin)
if(iscell(item))
txt=cell2json(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2json(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2json(name,item,level,varargin{:});
else
txt=mat2json(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2json(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=jsonopt('whitespaces_',struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n')),varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
nl=ws.newline;
if(len>1)
if(~isempty(name))
txt=sprintf('%s"%s": [%s',padding0, checkname(name,varargin{:}),nl); name='';
else
txt=sprintf('%s[%s',padding0,nl);
end
elseif(len==0)
if(~isempty(name))
txt=sprintf('%s"%s": []',padding0, checkname(name,varargin{:})); name='';
else
txt=sprintf('%s[]',padding0);
end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
txt=sprintf('%s%s',txt,obj2json(name,item{i,j},level+(dim(1)>1)+1,varargin{:}));
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
%if(j==dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=struct2json(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
padding1=repmat(ws.tab,1,level+(dim(1)>1)+(len>1));
nl=ws.newline;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding0,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding0,nl); end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=sprintf('%s%s"%s": {%s',txt,padding1, checkname(name,varargin{:}),nl);
else
txt=sprintf('%s%s{%s',txt,padding1,nl);
end
if(~isempty(names))
for e=1:length(names)
txt=sprintf('%s%s',txt,obj2json(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:}));
if(e<length(names)) txt=sprintf('%s%s',txt,','); end
txt=sprintf('%s%s',txt,nl);
end
end
txt=sprintf('%s%s}',txt,padding1);
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=str2json(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding1,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding1,nl); end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
if(isoct)
val=regexprep(item(e,:),'\\','\\');
val=regexprep(val,'"','\"');
val=regexprep(val,'^"','\"');
else
val=regexprep(item(e,:),'\\','\\\\');
val=regexprep(val,'"','\\"');
val=regexprep(val,'^"','\\"');
end
val=escapejsonstring(val);
if(len==1)
obj=['"' checkname(name,varargin{:}) '": ' '"',val,'"'];
if(isempty(name)) obj=['"',val,'"']; end
txt=sprintf('%s%s%s%s',txt,padding1,obj);
else
txt=sprintf('%s%s%s%s',txt,padding0,['"',val,'"']);
end
if(e==len) sep=''; end
txt=sprintf('%s%s',txt,sep);
end
if(len>1) txt=sprintf('%s%s%s%s',txt,nl,padding1,']'); end
%%-------------------------------------------------------------------------
function txt=mat2json(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) ||jsonopt('ArrayToStruct',0,varargin{:}))
if(isempty(name))
txt=sprintf('%s{%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
else
txt=sprintf('%s"%s": {%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,checkname(name,varargin{:}),nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
end
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1 && level>0)
numtxt=regexprep(regexprep(matdata2json(item,level+1,varargin{:}),'^\[',''),']','');
else
numtxt=matdata2json(item,level+1,varargin{:});
end
if(isempty(name))
txt=sprintf('%s%s',padding1,numtxt);
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
else
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
end
end
return;
end
dataformat='%s%s%s%s%s';
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsSparse_": ','1', sep);
if(size(item,1)==1)
% Row vector, store only column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([iy(:),data'],level+2,varargin{:}), nl);
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,data],level+2,varargin{:}), nl);
else
% General case, store row and column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,iy,data],level+2,varargin{:}), nl);
end
else
if(isreal(item))
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json(item(:)',level+2,varargin{:}), nl);
else
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([real(item(:)) imag(item(:))],level+2,varargin{:}), nl);
end
end
txt=sprintf('%s%s%s',txt,padding1,'}');
%%-------------------------------------------------------------------------
function txt=matdata2json(mat,level,varargin)
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
tab=ws.tab;
nl=ws.newline;
if(size(mat,1)==1)
pre='';
post='';
level=level-1;
else
pre=sprintf('[%s',nl);
post=sprintf('%s%s]',nl,repmat(tab,1,level-1));
end
if(isempty(mat))
txt='null';
return;
end
floatformat=jsonopt('FloatFormat','%.10g',varargin{:});
%if(numel(mat)>1)
formatstr=['[' repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf('],%s',nl)]];
%else
% formatstr=[repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf(',\n')]];
%end
if(nargin>=2 && size(mat,1)>1 && jsonopt('ArrayIndent',1,varargin{:})==1)
formatstr=[repmat(tab,1,level) formatstr];
end
txt=sprintf(formatstr,mat');
txt(end-length(nl):end)=[];
if(islogical(mat) && jsonopt('ParseLogical',0,varargin{:})==1)
txt=regexprep(txt,'1','true');
txt=regexprep(txt,'0','false');
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],\n['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
txt=[pre txt post];
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function newstr=escapejsonstring(str)
newstr=str;
isoct=exist('OCTAVE_VERSION','builtin');
if(isoct)
vv=sscanf(OCTAVE_VERSION,'%f');
if(vv(1)>=3.8) isoct=0; end
end
if(isoct)
escapechars={'\a','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},escapechars{i});
end
else
escapechars={'\a','\b','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},regexprep(escapechars{i},'\\','\\\\'));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/8 Anomaly detection and recommender system/ex8/lib/jsonlab/loadjson.m
| 18,884 |
ibm852
|
d21f0844f91f2dbb9ea8df00eda346ca
|
function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% Nedialko Krouchev: http://www.mathworks.com/matlabcentral/fileexchange/25713
% created on 2009/11/02
% François Glineur: http://www.mathworks.com/matlabcentral/fileexchange/23393
% created on 2009/03/22
% Joel Feenstra:
% http://www.mathworks.com/matlabcentral/fileexchange/20565
% created on 2008/07/03
%
% $Id: loadjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a JSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.FastArrayParser [1|0 or integer]: if set to 1, use a
% speed-optimized array parser when loading an
% array object. The fast array parser may
% collapse block arrays into a single large
% array similar to rules defined in cell2mat; 0 to
% use a legacy parser; if set to a larger-than-1
% value, this option will specify the minimum
% dimension to enable the fast array parser. For
% example, if the input is a 3D array, setting
% FastArrayParser to 1 will return a 3D array;
% setting to 2 will return a cell array of 2D
% arrays; setting to 3 will return to a 2D cell
% array of 1D vectors; setting to 4 will return a
% 3D cell array.
% opt.ShowProgress [0|1]: if set to 1, loadjson displays a progress bar.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
% dat=loadjson(['examples' filesep 'example1.json'])
% dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
if(jsonopt('ShowProgress',0,opt)==1)
opt.progressbar_=waitbar(0,'loading ...');
end
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
if(isfield(opt,'progressbar_'))
close(opt.progressbar_);
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=data(j).x0x5F_ArraySize_;
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
if next_char ~= '}'
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
parse_char(':');
val = parse_value(varargin{:});
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}'
break;
end
parse_char(',');
end
end
parse_char('}');
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim2=[];
arraydepth=jsonopt('JSONLAB_ArrayDepth_',1,varargin{:});
pbar=jsonopt('progressbar_',-1,varargin{:});
if next_char ~= ']'
if(jsonopt('FastArrayParser',1,varargin{:})>=1 && arraydepth>=jsonopt('FastArrayParser',1,varargin{:}))
[endpos, e1l, e1r, maxlevel]=matching_bracket(inStr,pos);
arraystr=['[' inStr(pos:endpos)];
arraystr=regexprep(arraystr,'"_NaN_"','NaN');
arraystr=regexprep(arraystr,'"([-+]*)_Inf_"','$1Inf');
arraystr(arraystr==sprintf('\n'))=[];
arraystr(arraystr==sprintf('\r'))=[];
%arraystr=regexprep(arraystr,'\s*,',','); % this is slow,sometimes needed
if(~isempty(e1l) && ~isempty(e1r)) % the array is in 2D or higher D
astr=inStr((e1l+1):(e1r-1));
astr=regexprep(astr,'"_NaN_"','NaN');
astr=regexprep(astr,'"([-+]*)_Inf_"','$1Inf');
astr(astr==sprintf('\n'))=[];
astr(astr==sprintf('\r'))=[];
astr(astr==' ')='';
if(isempty(find(astr=='[', 1))) % array is 2D
dim2=length(sscanf(astr,'%f,',[1 inf]));
end
else % array is 1D
astr=arraystr(2:end-1);
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',[1,inf]);
if(nextidx>=length(astr)-1)
object=obj;
pos=endpos;
parse_char(']');
return;
end
end
if(~isempty(dim2))
astr=arraystr;
astr(astr=='[')='';
astr(astr==']')='';
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',inf);
if(nextidx>=length(astr)-1)
object=reshape(obj,dim2,numel(obj)/dim2)';
pos=endpos;
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
return;
end
end
arraystr=regexprep(arraystr,'\]\s*,','];');
else
arraystr='[';
end
try
if(isoct && regexp(arraystr,'"','once'))
error('Octave eval can produce empty cells for JSON-like input');
end
object=eval(arraystr);
pos=endpos;
catch
while 1
newopt=varargin2struct(varargin{:},'JSONLAB_ArrayDepth_',arraydepth+1);
val = parse_value(newopt);
object{end+1} = val;
if next_char == ']'
break;
end
parse_char(',');
end
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr len esc index_esc len_esc
% len, ns = length(inStr), keyboard
if inStr(pos) ~= '"'
error_pos('String starting with " expected at position %d');
else
pos = pos + 1;
end
str = '';
while pos <= len
while index_esc <= len_esc && esc(index_esc) < pos
index_esc = index_esc + 1;
end
if index_esc > len_esc
str = [str inStr(pos:len)];
pos = len + 1;
break;
else
str = [str inStr(pos:esc(index_esc)-1)];
pos = esc(index_esc);
end
nstr = length(str); switch inStr(pos)
case '"'
pos = pos + 1;
if(~isempty(str))
if(strcmp(str,'_Inf_'))
str=Inf;
elseif(strcmp(str,'-_Inf_'))
str=-Inf;
elseif(strcmp(str,'_NaN_'))
str=NaN;
end
end
return;
case '\'
if pos+1 > len
error_pos('End of file reached right after escape character');
end
pos = pos + 1;
switch inStr(pos)
case {'"' '\' '/'}
str(nstr+1) = inStr(pos);
pos = pos + 1;
case {'b' 'f' 'n' 'r' 't'}
str(nstr+1) = sprintf(['\' inStr(pos)]);
pos = pos + 1;
case 'u'
if pos+4 > len
error_pos('End of file reached in escaped unicode character');
end
str(nstr+(1:6)) = inStr(pos-1:pos+4);
pos = pos + 5;
end
otherwise % should never happen
str(nstr+1) = inStr(pos), keyboard
pos = pos + 1;
end
end
error_pos('End of file while expecting end of inStr');
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct
currstr=inStr(pos:end);
numstr=0;
if(isoct~=0)
numstr=regexp(currstr,'^\s*-?(?:0|[1-9]\d*)(?:\.\d+)?(?:[eE][+\-]?\d+)?','end');
[num, one] = sscanf(currstr, '%f', 1);
delta=numstr+1;
else
[num, one, err, delta] = sscanf(currstr, '%f', 1);
if ~isempty(err)
error_pos('Error reading number at position %d');
end
end
pos = pos + delta-1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
pbar=jsonopt('progressbar_',-1,varargin{:});
if(pbar>0)
waitbar(pos/len,pbar,'loading ...');
end
switch(inStr(pos))
case '"'
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'-','0','1','2','3','4','5','6','7','8','9'}
val = parse_number(varargin{:});
return;
case 't'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'true')
val = true;
pos = pos + 4;
return;
end
case 'f'
if pos+4 <= len && strcmpi(inStr(pos:pos+4), 'false')
val = false;
pos = pos + 5;
return;
end
case 'n'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'null')
val = [];
pos = pos + 4;
return;
end
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
% Hard to believe but sprintf("%X") is broken in Octave 4.0.0
% str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
str=sprintf('x0x%s_%s',xxNumToHexStr(char(str(1))),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos, e1l, e1r, maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/8 Anomaly detection and recommender system/ex8/lib/jsonlab/loadubjson.m
| 15,574 |
utf_8
|
5974e78e71b81b1e0f76123784b951a4
|
function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a UBJSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.IntEndian [B|L]: specify the endianness of the integer fields
% in the UBJSON input data. B - Big-Endian format for
% integers (as required in the UBJSON specification);
% L - input integer fields are in Little-Endian order.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% obj=struct('string','value','array',[1 2 3]);
% ubjdata=saveubjson('obj',obj);
% dat=loadubjson(ubjdata)
% dat=loadubjson(['examples' filesep 'example1.ubj'])
% dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken fileendian systemendian
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
fileendian=upper(jsonopt('IntEndian','B',opt));
[os,maxelem,systemendian]=computer;
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
%%
function newdata=parse_collection(id,data,obj)
if(jsoncount>0 && exist('data','var'))
if(~iscell(data))
newdata=cell(1);
newdata{1}=data;
data=newdata;
end
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=double(data(j).x0x5F_ArraySize_);
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1); % TODO
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
count=double(parse_number());
end
if next_char ~= '}'
num=0;
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
%parse_char(':');
val = parse_value(varargin{:});
num=num+1;
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}' || (count>=0 && num>=count)
break;
end
%parse_char(',');
end
end
if(count==-1)
parse_char('}');
end
%%-------------------------------------------------------------------------
function [cid,len]=elem_info(type)
id=strfind('iUIlLdD',type);
dataclass={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
if(id>0)
cid=dataclass{id};
len=bytelen(id);
else
error_pos('unsupported type at position %d');
end
%%-------------------------------------------------------------------------
function [data adv]=parse_block(type,count,varargin)
global pos inStr isoct fileendian systemendian
[cid,len]=elem_info(type);
datastr=inStr(pos:pos+len*count-1);
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
id=strfind('iUIlLdD',type);
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,cid));
end
data=typecast(newdata,cid);
adv=double(len*count);
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim=[];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1);
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
if(next_char=='[')
dim=parse_array(varargin{:});
count=prod(double(dim));
else
count=double(parse_number());
end
end
if(~isempty(type))
if(count>=0)
[object adv]=parse_block(type,count,varargin{:});
if(~isempty(dim))
object=reshape(object,dim);
end
pos=pos+adv;
return;
else
endpos=matching_bracket(inStr,pos);
[cid,len]=elem_info(type);
count=(endpos-pos)/len;
[object adv]=parse_block(type,count,varargin{:});
pos=pos+adv;
parse_char(']');
return;
end
end
if next_char ~= ']'
while 1
val = parse_value(varargin{:});
object{end+1} = val;
if next_char == ']'
break;
end
%parse_char(',');
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
if(count==-1)
parse_char(']');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr esc index_esc len_esc
% len, ns = length(inStr), keyboard
type=inStr(pos);
if type ~= 'S' && type ~= 'C' && type ~= 'H'
error_pos('String starting with S expected at position %d');
else
pos = pos + 1;
end
if(type == 'C')
str=inStr(pos);
pos=pos+1;
return;
end
bytelen=double(parse_number());
if(length(inStr)>=pos+bytelen-1)
str=inStr(pos:pos+bytelen-1);
pos=pos+bytelen;
else
error_pos('End of file while expecting end of inStr');
end
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct fileendian systemendian
id=strfind('iUIlLdD',inStr(pos));
if(isempty(id))
error_pos('expecting a number at position %d');
end
type={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
datastr=inStr(pos+1:pos+bytelen(id));
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,type{id}));
end
num=typecast(newdata,type{id});
pos = pos + bytelen(id)+1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
switch(inStr(pos))
case {'S','C','H'}
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'i','U','I','l','L','d','D'}
val = parse_number(varargin{:});
return;
case 'T'
val = true;
pos = pos + 1;
return;
case 'F'
val = false;
pos = pos + 1;
return;
case {'Z','N'}
val = [];
pos = pos + 1;
return;
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos e1l e1r maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
saveubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/8 Anomaly detection and recommender system/ex8/lib/jsonlab/saveubjson.m
| 16,123 |
utf_8
|
61d4f51010aedbf97753396f5d2d9ec0
|
function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/17
%
% $Id: saveubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array)
% filename: a string for the file name to save the output UBJSON data
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [1|0]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSON='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a binary string in the UBJSON format (see http://ubjson.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% saveubjson('jsonmesh',jsonmesh)
% saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
json=obj2ubjson(rootname,obj,rootlevel,opt);
if(~rootisarray)
json=['{' json '}'];
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=[jsonp '(' json ')'];
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2ubjson(name,item,level,varargin)
if(iscell(item))
txt=cell2ubjson(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2ubjson(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2ubjson(name,item,level,varargin{:});
else
txt=mat2ubjson(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2ubjson(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item); % let's handle 1D cell first
if(len>1)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) '[']; name='';
else
txt='[';
end
elseif(len==0)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) 'Z']; name='';
else
txt='Z';
end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
txt=[txt obj2ubjson(name,item{i,j},level+(len>1),varargin{:})];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=struct2ubjson(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=[txt S_(checkname(name,varargin{:})) '{'];
else
txt=[txt '{'];
end
if(~isempty(names))
for e=1:length(names)
txt=[txt obj2ubjson(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:})];
end
end
txt=[txt '}'];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=str2ubjson(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
val=item(e,:);
if(len==1)
obj=['' S_(checkname(name,varargin{:})) '' '',S_(val),''];
if(isempty(name)) obj=['',S_(val),'']; end
txt=[txt,'',obj];
else
txt=[txt,'',['',S_(val),'']];
end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=mat2ubjson(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) || jsonopt('ArrayToStruct',0,varargin{:}))
cid=I_(uint32(max(size(item))));
if(isempty(name))
txt=['{' S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1)) ];
else
if(isempty(item))
txt=[S_(checkname(name,varargin{:})),'Z'];
return;
else
txt=[S_(checkname(name,varargin{:})),'{',S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1))];
end
end
else
if(isempty(name))
txt=matdata2ubjson(item,level+1,varargin{:});
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
numtxt=regexprep(regexprep(matdata2ubjson(item,level+1,varargin{:}),'^\[',''),']','');
txt=[S_(checkname(name,varargin{:})) numtxt];
else
txt=[S_(checkname(name,varargin{:})),matdata2ubjson(item,level+1,varargin{:})];
end
end
return;
end
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=[txt,S_('_ArrayIsComplex_'),'T'];
end
txt=[txt,S_('_ArrayIsSparse_'),'T'];
if(size(item,1)==1)
% Row vector, store only column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([iy(:),data'],level+2,varargin{:})];
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,data],level+2,varargin{:})];
else
% General case, store row and column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,iy,data],level+2,varargin{:})];
end
else
if(isreal(item))
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson(item(:)',level+2,varargin{:})];
else
txt=[txt,S_('_ArrayIsComplex_'),'T'];
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([real(item(:)) imag(item(:))],level+2,varargin{:})];
end
end
txt=[txt,'}'];
%%-------------------------------------------------------------------------
function txt=matdata2ubjson(mat,level,varargin)
if(isempty(mat))
txt='Z';
return;
end
if(size(mat,1)==1)
level=level-1;
end
type='';
hasnegtive=(mat<0);
if(isa(mat,'integer') || isinteger(mat) || (isfloat(mat) && all(mod(mat(:),1) == 0)))
if(isempty(hasnegtive))
if(max(mat(:))<=2^8)
type='U';
end
end
if(isempty(type))
% todo - need to consider negative ones separately
id= histc(abs(max(mat(:))),[0 2^7 2^15 2^31 2^63]);
if(isempty(find(id)))
error('high-precision data is not yet supported');
end
key='iIlL';
type=key(find(id));
end
txt=[I_a(mat(:),type,size(mat))];
elseif(islogical(mat))
logicalval='FT';
if(numel(mat)==1)
txt=logicalval(mat+1);
else
txt=['[$U#' I_a(size(mat),'l') typecast(swapbytes(uint8(mat(:)')),'uint8')];
end
else
if(numel(mat)==1)
txt=['[' D_(mat) ']'];
else
txt=D_a(mat(:),'D',size(mat));
end
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function val=S_(str)
if(length(str)==1)
val=['C' str];
else
val=['S' I_(int32(length(str))) str];
end
%%-------------------------------------------------------------------------
function val=I_(num)
if(~isinteger(num))
error('input is not an integer');
end
if(num>=0 && num<255)
val=['U' data2byte(swapbytes(cast(num,'uint8')),'uint8')];
return;
end
key='iIlL';
cid={'int8','int16','int32','int64'};
for i=1:4
if((num>0 && num<2^(i*8-1)) || (num<0 && num>=-2^(i*8-1)))
val=[key(i) data2byte(swapbytes(cast(num,cid{i})),'uint8')];
return;
end
end
error('unsupported integer');
%%-------------------------------------------------------------------------
function val=D_(num)
if(~isfloat(num))
error('input is not a float');
end
if(isa(num,'single'))
val=['d' data2byte(num,'uint8')];
else
val=['D' data2byte(num,'uint8')];
end
%%-------------------------------------------------------------------------
function data=I_a(num,type,dim,format)
id=find(ismember('iUIlL',type));
if(id==0)
error('unsupported integer array');
end
% based on UBJSON specs, all integer types are stored in big endian format
if(id==1)
data=data2byte(swapbytes(int8(num)),'uint8');
blen=1;
elseif(id==2)
data=data2byte(swapbytes(uint8(num)),'uint8');
blen=1;
elseif(id==3)
data=data2byte(swapbytes(int16(num)),'uint8');
blen=2;
elseif(id==4)
data=data2byte(swapbytes(int32(num)),'uint8');
blen=4;
elseif(id==5)
data=data2byte(swapbytes(int64(num)),'uint8');
blen=8;
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/blen)) data(:)'];
end
data=['[' data(:)'];
else
data=reshape(data,blen,numel(data)/blen);
data(2:blen+1,:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function data=D_a(num,type,dim,format)
id=find(ismember('dD',type));
if(id==0)
error('unsupported float array');
end
if(id==1)
data=data2byte(single(num),'uint8');
elseif(id==2)
data=data2byte(double(num),'uint8');
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/(id*4))) data(:)'];
end
data=['[' data];
else
data=reshape(data,(id*4),length(data)/(id*4));
data(2:(id*4+1),:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function bytes=data2byte(varargin)
bytes=typecast(varargin{:});
bytes=bytes(:)';
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submit.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/6 support vector machines/ex6/submit.m
| 1,318 |
utf_8
|
bfa0b4ffb8a7854d8e84276e91818107
|
function submit()
addpath('./lib');
conf.assignmentSlug = 'support-vector-machines';
conf.itemName = 'Support Vector Machines';
conf.partArrays = { ...
{ ...
'1', ...
{ 'gaussianKernel.m' }, ...
'Gaussian Kernel', ...
}, ...
{ ...
'2', ...
{ 'dataset3Params.m' }, ...
'Parameters (C, sigma) for Dataset 3', ...
}, ...
{ ...
'3', ...
{ 'processEmail.m' }, ...
'Email Preprocessing', ...
}, ...
{ ...
'4', ...
{ 'emailFeatures.m' }, ...
'Email Feature Extraction', ...
}, ...
};
conf.output = @output;
submitWithConfiguration(conf);
end
function out = output(partId, auxstring)
% Random Test Cases
x1 = sin(1:10)';
x2 = cos(1:10)';
ec = 'the quick brown fox jumped over the lazy dog';
wi = 1 + abs(round(x1 * 1863));
wi = [wi ; wi];
if partId == '1'
sim = gaussianKernel(x1, x2, 2);
out = sprintf('%0.5f ', sim);
elseif partId == '2'
load('ex6data3.mat');
[C, sigma] = dataset3Params(X, y, Xval, yval);
out = sprintf('%0.5f ', C);
out = [out sprintf('%0.5f ', sigma)];
elseif partId == '3'
word_indices = processEmail(ec);
out = sprintf('%d ', word_indices);
elseif partId == '4'
x = emailFeatures(wi);
out = sprintf('%d ', x);
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
porterStemmer.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/6 support vector machines/ex6/porterStemmer.m
| 9,902 |
utf_8
|
7ed5acd925808fde342fc72bd62ebc4d
|
function stem = porterStemmer(inString)
% Applies the Porter Stemming algorithm as presented in the following
% paper:
% Porter, 1980, An algorithm for suffix stripping, Program, Vol. 14,
% no. 3, pp 130-137
% Original code modeled after the C version provided at:
% http://www.tartarus.org/~martin/PorterStemmer/c.txt
% The main part of the stemming algorithm starts here. b is an array of
% characters, holding the word to be stemmed. The letters are in b[k0],
% b[k0+1] ending at b[k]. In fact k0 = 1 in this demo program (since
% matlab begins indexing by 1 instead of 0). k is readjusted downwards as
% the stemming progresses. Zero termination is not in fact used in the
% algorithm.
% To call this function, use the string to be stemmed as the input
% argument. This function returns the stemmed word as a string.
% Lower-case string
inString = lower(inString);
global j;
b = inString;
k = length(b);
k0 = 1;
j = k;
% With this if statement, strings of length 1 or 2 don't go through the
% stemming process. Remove this conditional to match the published
% algorithm.
stem = b;
if k > 2
% Output displays per step are commented out.
%disp(sprintf('Word to stem: %s', b));
x = step1ab(b, k, k0);
%disp(sprintf('Steps 1A and B yield: %s', x{1}));
x = step1c(x{1}, x{2}, k0);
%disp(sprintf('Step 1C yields: %s', x{1}));
x = step2(x{1}, x{2}, k0);
%disp(sprintf('Step 2 yields: %s', x{1}));
x = step3(x{1}, x{2}, k0);
%disp(sprintf('Step 3 yields: %s', x{1}));
x = step4(x{1}, x{2}, k0);
%disp(sprintf('Step 4 yields: %s', x{1}));
x = step5(x{1}, x{2}, k0);
%disp(sprintf('Step 5 yields: %s', x{1}));
stem = x{1};
end
% cons(j) is TRUE <=> b[j] is a consonant.
function c = cons(i, b, k0)
c = true;
switch(b(i))
case {'a', 'e', 'i', 'o', 'u'}
c = false;
case 'y'
if i == k0
c = true;
else
c = ~cons(i - 1, b, k0);
end
end
% mseq() measures the number of consonant sequences between k0 and j. If
% c is a consonant sequence and v a vowel sequence, and <..> indicates
% arbitrary presence,
% <c><v> gives 0
% <c>vc<v> gives 1
% <c>vcvc<v> gives 2
% <c>vcvcvc<v> gives 3
% ....
function n = measure(b, k0)
global j;
n = 0;
i = k0;
while true
if i > j
return
end
if ~cons(i, b, k0)
break;
end
i = i + 1;
end
i = i + 1;
while true
while true
if i > j
return
end
if cons(i, b, k0)
break;
end
i = i + 1;
end
i = i + 1;
n = n + 1;
while true
if i > j
return
end
if ~cons(i, b, k0)
break;
end
i = i + 1;
end
i = i + 1;
end
% vowelinstem() is TRUE <=> k0,...j contains a vowel
function vis = vowelinstem(b, k0)
global j;
for i = k0:j,
if ~cons(i, b, k0)
vis = true;
return
end
end
vis = false;
%doublec(i) is TRUE <=> i,(i-1) contain a double consonant.
function dc = doublec(i, b, k0)
if i < k0+1
dc = false;
return
end
if b(i) ~= b(i-1)
dc = false;
return
end
dc = cons(i, b, k0);
% cvc(j) is TRUE <=> j-2,j-1,j has the form consonant - vowel - consonant
% and also if the second c is not w,x or y. this is used when trying to
% restore an e at the end of a short word. e.g.
%
% cav(e), lov(e), hop(e), crim(e), but
% snow, box, tray.
function c1 = cvc(i, b, k0)
if ((i < (k0+2)) || ~cons(i, b, k0) || cons(i-1, b, k0) || ~cons(i-2, b, k0))
c1 = false;
else
if (b(i) == 'w' || b(i) == 'x' || b(i) == 'y')
c1 = false;
return
end
c1 = true;
end
% ends(s) is TRUE <=> k0,...k ends with the string s.
function s = ends(str, b, k)
global j;
if (str(length(str)) ~= b(k))
s = false;
return
end % tiny speed-up
if (length(str) > k)
s = false;
return
end
if strcmp(b(k-length(str)+1:k), str)
s = true;
j = k - length(str);
return
else
s = false;
end
% setto(s) sets (j+1),...k to the characters in the string s, readjusting
% k accordingly.
function so = setto(s, b, k)
global j;
for i = j+1:(j+length(s))
b(i) = s(i-j);
end
if k > j+length(s)
b((j+length(s)+1):k) = '';
end
k = length(b);
so = {b, k};
% rs(s) is used further down.
% [Note: possible null/value for r if rs is called]
function r = rs(str, b, k, k0)
r = {b, k};
if measure(b, k0) > 0
r = setto(str, b, k);
end
% step1ab() gets rid of plurals and -ed or -ing. e.g.
% caresses -> caress
% ponies -> poni
% ties -> ti
% caress -> caress
% cats -> cat
% feed -> feed
% agreed -> agree
% disabled -> disable
% matting -> mat
% mating -> mate
% meeting -> meet
% milling -> mill
% messing -> mess
% meetings -> meet
function s1ab = step1ab(b, k, k0)
global j;
if b(k) == 's'
if ends('sses', b, k)
k = k-2;
elseif ends('ies', b, k)
retVal = setto('i', b, k);
b = retVal{1};
k = retVal{2};
elseif (b(k-1) ~= 's')
k = k-1;
end
end
if ends('eed', b, k)
if measure(b, k0) > 0;
k = k-1;
end
elseif (ends('ed', b, k) || ends('ing', b, k)) && vowelinstem(b, k0)
k = j;
retVal = {b, k};
if ends('at', b, k)
retVal = setto('ate', b(k0:k), k);
elseif ends('bl', b, k)
retVal = setto('ble', b(k0:k), k);
elseif ends('iz', b, k)
retVal = setto('ize', b(k0:k), k);
elseif doublec(k, b, k0)
retVal = {b, k-1};
if b(retVal{2}) == 'l' || b(retVal{2}) == 's' || ...
b(retVal{2}) == 'z'
retVal = {retVal{1}, retVal{2}+1};
end
elseif measure(b, k0) == 1 && cvc(k, b, k0)
retVal = setto('e', b(k0:k), k);
end
k = retVal{2};
b = retVal{1}(k0:k);
end
j = k;
s1ab = {b(k0:k), k};
% step1c() turns terminal y to i when there is another vowel in the stem.
function s1c = step1c(b, k, k0)
global j;
if ends('y', b, k) && vowelinstem(b, k0)
b(k) = 'i';
end
j = k;
s1c = {b, k};
% step2() maps double suffices to single ones. so -ization ( = -ize plus
% -ation) maps to -ize etc. note that the string before the suffix must give
% m() > 0.
function s2 = step2(b, k, k0)
global j;
s2 = {b, k};
switch b(k-1)
case {'a'}
if ends('ational', b, k) s2 = rs('ate', b, k, k0);
elseif ends('tional', b, k) s2 = rs('tion', b, k, k0); end;
case {'c'}
if ends('enci', b, k) s2 = rs('ence', b, k, k0);
elseif ends('anci', b, k) s2 = rs('ance', b, k, k0); end;
case {'e'}
if ends('izer', b, k) s2 = rs('ize', b, k, k0); end;
case {'l'}
if ends('bli', b, k) s2 = rs('ble', b, k, k0);
elseif ends('alli', b, k) s2 = rs('al', b, k, k0);
elseif ends('entli', b, k) s2 = rs('ent', b, k, k0);
elseif ends('eli', b, k) s2 = rs('e', b, k, k0);
elseif ends('ousli', b, k) s2 = rs('ous', b, k, k0); end;
case {'o'}
if ends('ization', b, k) s2 = rs('ize', b, k, k0);
elseif ends('ation', b, k) s2 = rs('ate', b, k, k0);
elseif ends('ator', b, k) s2 = rs('ate', b, k, k0); end;
case {'s'}
if ends('alism', b, k) s2 = rs('al', b, k, k0);
elseif ends('iveness', b, k) s2 = rs('ive', b, k, k0);
elseif ends('fulness', b, k) s2 = rs('ful', b, k, k0);
elseif ends('ousness', b, k) s2 = rs('ous', b, k, k0); end;
case {'t'}
if ends('aliti', b, k) s2 = rs('al', b, k, k0);
elseif ends('iviti', b, k) s2 = rs('ive', b, k, k0);
elseif ends('biliti', b, k) s2 = rs('ble', b, k, k0); end;
case {'g'}
if ends('logi', b, k) s2 = rs('log', b, k, k0); end;
end
j = s2{2};
% step3() deals with -ic-, -full, -ness etc. similar strategy to step2.
function s3 = step3(b, k, k0)
global j;
s3 = {b, k};
switch b(k)
case {'e'}
if ends('icate', b, k) s3 = rs('ic', b, k, k0);
elseif ends('ative', b, k) s3 = rs('', b, k, k0);
elseif ends('alize', b, k) s3 = rs('al', b, k, k0); end;
case {'i'}
if ends('iciti', b, k) s3 = rs('ic', b, k, k0); end;
case {'l'}
if ends('ical', b, k) s3 = rs('ic', b, k, k0);
elseif ends('ful', b, k) s3 = rs('', b, k, k0); end;
case {'s'}
if ends('ness', b, k) s3 = rs('', b, k, k0); end;
end
j = s3{2};
% step4() takes off -ant, -ence etc., in context <c>vcvc<v>.
function s4 = step4(b, k, k0)
global j;
switch b(k-1)
case {'a'}
if ends('al', b, k) end;
case {'c'}
if ends('ance', b, k)
elseif ends('ence', b, k) end;
case {'e'}
if ends('er', b, k) end;
case {'i'}
if ends('ic', b, k) end;
case {'l'}
if ends('able', b, k)
elseif ends('ible', b, k) end;
case {'n'}
if ends('ant', b, k)
elseif ends('ement', b, k)
elseif ends('ment', b, k)
elseif ends('ent', b, k) end;
case {'o'}
if ends('ion', b, k)
if j == 0
elseif ~(strcmp(b(j),'s') || strcmp(b(j),'t'))
j = k;
end
elseif ends('ou', b, k) end;
case {'s'}
if ends('ism', b, k) end;
case {'t'}
if ends('ate', b, k)
elseif ends('iti', b, k) end;
case {'u'}
if ends('ous', b, k) end;
case {'v'}
if ends('ive', b, k) end;
case {'z'}
if ends('ize', b, k) end;
end
if measure(b, k0) > 1
s4 = {b(k0:j), j};
else
s4 = {b(k0:k), k};
end
% step5() removes a final -e if m() > 1, and changes -ll to -l if m() > 1.
function s5 = step5(b, k, k0)
global j;
j = k;
if b(k) == 'e'
a = measure(b, k0);
if (a > 1) || ((a == 1) && ~cvc(k-1, b, k0))
k = k-1;
end
end
if (b(k) == 'l') && doublec(k, b, k0) && (measure(b, k0) > 1)
k = k-1;
end
s5 = {b(k0:k), k};
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submitWithConfiguration.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/6 support vector machines/ex6/lib/submitWithConfiguration.m
| 3,926 |
utf_8
|
f889a7cf3dc6c1c2877566d38df1bec8
|
function submitWithConfiguration(conf)
% Note: has the "certificate" patch from Liran for Windows-like systems
addpath('./lib/jsonlab');
%keyboard
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = promptToken('', '', tokenFile);
end
if isempty(token)
fprintf('!! Submission Cancelled\n');
return
end
try
response = submitParts(conf, email, token, parts);
catch
e = lasterror();
fprintf( ...
'!! Submission failed: unexpected error: %s\n', ...
e.message);
fprintf('!! Please try again later.\n');
return
end
if isfield(response, 'errorMessage')
fprintf('!! Submission failed: %s\n', response.errorMessage);
else
showFeedback(parts, response);
save(tokenFile, 'email', 'token');
end
end
function [email token] = promptToken(email, existingToken, tokenFile)
if (~isempty(email) && ~isempty(existingToken))
prompt = sprintf( ...
'Use token from last successful submission (%s)? (Y/n): ', ...
email);
reenter = input(prompt, 's');
if (isempty(reenter) || reenter(1) == 'Y' || reenter(1) == 'y')
token = existingToken;
return;
else
delete(tokenFile);
end
end
email = input('Login (email address): ', 's');
token = input('Token: ', 's');
end
function isValid = isValidPartOptionIndex(partOptions, i)
isValid = (~isempty(i)) && (1 <= i) && (i <= numel(partOptions));
end
function response = submitParts(conf, email, token, parts)
body = makePostBody(conf, email, token, parts);
submissionUrl = submissionUrl();
params = {'jsonBody', body};
%responseBody = urlread(submissionUrl, 'post', params);
[code, responseBody] = system(sprintf('echo jsonBody=%s | curl -k -X POST -d @- %s', body, submissionUrl));
response = loadjson(responseBody);
end
function body = makePostBody(conf, email, token, parts)
bodyStruct.assignmentSlug = conf.assignmentSlug;
bodyStruct.submitterEmail = email;
bodyStruct.secret = token;
bodyStruct.parts = makePartsStruct(conf, parts);
opt.Compact = 1;
body = savejson('', bodyStruct, opt);
end
function partsStruct = makePartsStruct(conf, parts)
for part = parts
partId = part{:}.id;
fieldName = makeValidFieldName(partId);
outputStruct.output = conf.output(partId);
partsStruct.(fieldName) = outputStruct;
end
end
function [parts] = parts(conf)
parts = {};
for partArray = conf.partArrays
part.id = partArray{:}{1};
part.sourceFiles = partArray{:}{2};
part.name = partArray{:}{3};
parts{end + 1} = part;
end
end
function showFeedback(parts, response)
fprintf('== \n');
fprintf('== %43s | %9s | %-s\n', 'Part Name', 'Score', 'Feedback');
fprintf('== %43s | %9s | %-s\n', '---------', '-----', '--------');
for part = parts
score = '';
partFeedback = '';
partFeedback = response.partFeedbacks.(makeValidFieldName(part{:}.id));
partEvaluation = response.partEvaluations.(makeValidFieldName(part{:}.id));
score = sprintf('%d / %3d', partEvaluation.score, partEvaluation.maxScore);
fprintf('== %43s | %9s | %-s\n', part{:}.name, score, partFeedback);
end
evaluation = response.evaluation;
totalScore = sprintf('%d / %d', evaluation.score, evaluation.maxScore);
fprintf('== --------------------------------\n');
fprintf('== %43s | %9s | %-s\n', '', totalScore, '');
fprintf('== \n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Service configuration
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function submissionUrl = submissionUrl()
submissionUrl = 'https://www-origin.coursera.org/api/onDemandProgrammingImmediateFormSubmissions.v1';
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
savejson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/6 support vector machines/ex6/lib/jsonlab/savejson.m
| 17,462 |
utf_8
|
861b534fc35ffe982b53ca3ca83143bf
|
function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09
%
% $Id: savejson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array).
% filename: a string for the file name to save the output JSON data.
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.FloatFormat ['%.10g'|string]: format to show each numeric element
% of a 1D/2D array;
% opt.ArrayIndent [1|0]: if 1, output explicit data array with
% precedent indentation; if 0, no indentation
% opt.ArrayToStruct[0|1]: when set to 0, savejson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [0|1]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, savejson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.Inf ['"$1_Inf_"'|string]: a customized regular expression pattern
% to represent +/-Inf. The matched pattern is '([-+]*)Inf'
% and $1 represents the sign. For those who want to use
% 1e999 to represent Inf, they can set opt.Inf to '$11e999'
% opt.NaN ['"_NaN_"'|string]: a customized regular expression pattern
% to represent NaN
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSONP='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
% opt.SaveBinary [0|1]: 1 - save the JSON file in binary mode; 0 - text mode.
% opt.Compact [0|1]: 1- out compact JSON format (remove all newlines and tabs)
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a string in the JSON format (see http://json.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% savejson('jmesh',jsonmesh)
% savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
whitespaces=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
if(jsonopt('Compact',0,opt)==1)
whitespaces=struct('tab','','newline','','sep',',');
end
if(~isfield(opt,'whitespaces_'))
opt.whitespaces_=whitespaces;
end
nl=whitespaces.newline;
json=obj2json(rootname,obj,rootlevel,opt);
if(rootisarray)
json=sprintf('%s%s',json,nl);
else
json=sprintf('{%s%s%s}\n',nl,json,nl);
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=sprintf('%s(%s);%s',jsonp,json,nl);
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
if(jsonopt('SaveBinary',0,opt)==1)
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
else
fid = fopen(opt.FileName, 'wt');
fwrite(fid,json,'char');
end
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2json(name,item,level,varargin)
if(iscell(item))
txt=cell2json(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2json(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2json(name,item,level,varargin{:});
else
txt=mat2json(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2json(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=jsonopt('whitespaces_',struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n')),varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
nl=ws.newline;
if(len>1)
if(~isempty(name))
txt=sprintf('%s"%s": [%s',padding0, checkname(name,varargin{:}),nl); name='';
else
txt=sprintf('%s[%s',padding0,nl);
end
elseif(len==0)
if(~isempty(name))
txt=sprintf('%s"%s": []',padding0, checkname(name,varargin{:})); name='';
else
txt=sprintf('%s[]',padding0);
end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
txt=sprintf('%s%s',txt,obj2json(name,item{i,j},level+(dim(1)>1)+1,varargin{:}));
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
%if(j==dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=struct2json(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
padding1=repmat(ws.tab,1,level+(dim(1)>1)+(len>1));
nl=ws.newline;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding0,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding0,nl); end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=sprintf('%s%s"%s": {%s',txt,padding1, checkname(name,varargin{:}),nl);
else
txt=sprintf('%s%s{%s',txt,padding1,nl);
end
if(~isempty(names))
for e=1:length(names)
txt=sprintf('%s%s',txt,obj2json(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:}));
if(e<length(names)) txt=sprintf('%s%s',txt,','); end
txt=sprintf('%s%s',txt,nl);
end
end
txt=sprintf('%s%s}',txt,padding1);
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=str2json(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding1,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding1,nl); end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
if(isoct)
val=regexprep(item(e,:),'\\','\\');
val=regexprep(val,'"','\"');
val=regexprep(val,'^"','\"');
else
val=regexprep(item(e,:),'\\','\\\\');
val=regexprep(val,'"','\\"');
val=regexprep(val,'^"','\\"');
end
val=escapejsonstring(val);
if(len==1)
obj=['"' checkname(name,varargin{:}) '": ' '"',val,'"'];
if(isempty(name)) obj=['"',val,'"']; end
txt=sprintf('%s%s%s%s',txt,padding1,obj);
else
txt=sprintf('%s%s%s%s',txt,padding0,['"',val,'"']);
end
if(e==len) sep=''; end
txt=sprintf('%s%s',txt,sep);
end
if(len>1) txt=sprintf('%s%s%s%s',txt,nl,padding1,']'); end
%%-------------------------------------------------------------------------
function txt=mat2json(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) ||jsonopt('ArrayToStruct',0,varargin{:}))
if(isempty(name))
txt=sprintf('%s{%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
else
txt=sprintf('%s"%s": {%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,checkname(name,varargin{:}),nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
end
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1 && level>0)
numtxt=regexprep(regexprep(matdata2json(item,level+1,varargin{:}),'^\[',''),']','');
else
numtxt=matdata2json(item,level+1,varargin{:});
end
if(isempty(name))
txt=sprintf('%s%s',padding1,numtxt);
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
else
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
end
end
return;
end
dataformat='%s%s%s%s%s';
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsSparse_": ','1', sep);
if(size(item,1)==1)
% Row vector, store only column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([iy(:),data'],level+2,varargin{:}), nl);
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,data],level+2,varargin{:}), nl);
else
% General case, store row and column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,iy,data],level+2,varargin{:}), nl);
end
else
if(isreal(item))
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json(item(:)',level+2,varargin{:}), nl);
else
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([real(item(:)) imag(item(:))],level+2,varargin{:}), nl);
end
end
txt=sprintf('%s%s%s',txt,padding1,'}');
%%-------------------------------------------------------------------------
function txt=matdata2json(mat,level,varargin)
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
tab=ws.tab;
nl=ws.newline;
if(size(mat,1)==1)
pre='';
post='';
level=level-1;
else
pre=sprintf('[%s',nl);
post=sprintf('%s%s]',nl,repmat(tab,1,level-1));
end
if(isempty(mat))
txt='null';
return;
end
floatformat=jsonopt('FloatFormat','%.10g',varargin{:});
%if(numel(mat)>1)
formatstr=['[' repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf('],%s',nl)]];
%else
% formatstr=[repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf(',\n')]];
%end
if(nargin>=2 && size(mat,1)>1 && jsonopt('ArrayIndent',1,varargin{:})==1)
formatstr=[repmat(tab,1,level) formatstr];
end
txt=sprintf(formatstr,mat');
txt(end-length(nl):end)=[];
if(islogical(mat) && jsonopt('ParseLogical',0,varargin{:})==1)
txt=regexprep(txt,'1','true');
txt=regexprep(txt,'0','false');
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],\n['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
txt=[pre txt post];
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function newstr=escapejsonstring(str)
newstr=str;
isoct=exist('OCTAVE_VERSION','builtin');
if(isoct)
vv=sscanf(OCTAVE_VERSION,'%f');
if(vv(1)>=3.8) isoct=0; end
end
if(isoct)
escapechars={'\a','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},escapechars{i});
end
else
escapechars={'\a','\b','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},regexprep(escapechars{i},'\\','\\\\'));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/6 support vector machines/ex6/lib/jsonlab/loadjson.m
| 18,884 |
ibm852
|
d21f0844f91f2dbb9ea8df00eda346ca
|
function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% Nedialko Krouchev: http://www.mathworks.com/matlabcentral/fileexchange/25713
% created on 2009/11/02
% François Glineur: http://www.mathworks.com/matlabcentral/fileexchange/23393
% created on 2009/03/22
% Joel Feenstra:
% http://www.mathworks.com/matlabcentral/fileexchange/20565
% created on 2008/07/03
%
% $Id: loadjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a JSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.FastArrayParser [1|0 or integer]: if set to 1, use a
% speed-optimized array parser when loading an
% array object. The fast array parser may
% collapse block arrays into a single large
% array similar to rules defined in cell2mat; 0 to
% use a legacy parser; if set to a larger-than-1
% value, this option will specify the minimum
% dimension to enable the fast array parser. For
% example, if the input is a 3D array, setting
% FastArrayParser to 1 will return a 3D array;
% setting to 2 will return a cell array of 2D
% arrays; setting to 3 will return to a 2D cell
% array of 1D vectors; setting to 4 will return a
% 3D cell array.
% opt.ShowProgress [0|1]: if set to 1, loadjson displays a progress bar.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
% dat=loadjson(['examples' filesep 'example1.json'])
% dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
if(jsonopt('ShowProgress',0,opt)==1)
opt.progressbar_=waitbar(0,'loading ...');
end
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
if(isfield(opt,'progressbar_'))
close(opt.progressbar_);
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=data(j).x0x5F_ArraySize_;
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
if next_char ~= '}'
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
parse_char(':');
val = parse_value(varargin{:});
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}'
break;
end
parse_char(',');
end
end
parse_char('}');
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim2=[];
arraydepth=jsonopt('JSONLAB_ArrayDepth_',1,varargin{:});
pbar=jsonopt('progressbar_',-1,varargin{:});
if next_char ~= ']'
if(jsonopt('FastArrayParser',1,varargin{:})>=1 && arraydepth>=jsonopt('FastArrayParser',1,varargin{:}))
[endpos, e1l, e1r, maxlevel]=matching_bracket(inStr,pos);
arraystr=['[' inStr(pos:endpos)];
arraystr=regexprep(arraystr,'"_NaN_"','NaN');
arraystr=regexprep(arraystr,'"([-+]*)_Inf_"','$1Inf');
arraystr(arraystr==sprintf('\n'))=[];
arraystr(arraystr==sprintf('\r'))=[];
%arraystr=regexprep(arraystr,'\s*,',','); % this is slow,sometimes needed
if(~isempty(e1l) && ~isempty(e1r)) % the array is in 2D or higher D
astr=inStr((e1l+1):(e1r-1));
astr=regexprep(astr,'"_NaN_"','NaN');
astr=regexprep(astr,'"([-+]*)_Inf_"','$1Inf');
astr(astr==sprintf('\n'))=[];
astr(astr==sprintf('\r'))=[];
astr(astr==' ')='';
if(isempty(find(astr=='[', 1))) % array is 2D
dim2=length(sscanf(astr,'%f,',[1 inf]));
end
else % array is 1D
astr=arraystr(2:end-1);
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',[1,inf]);
if(nextidx>=length(astr)-1)
object=obj;
pos=endpos;
parse_char(']');
return;
end
end
if(~isempty(dim2))
astr=arraystr;
astr(astr=='[')='';
astr(astr==']')='';
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',inf);
if(nextidx>=length(astr)-1)
object=reshape(obj,dim2,numel(obj)/dim2)';
pos=endpos;
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
return;
end
end
arraystr=regexprep(arraystr,'\]\s*,','];');
else
arraystr='[';
end
try
if(isoct && regexp(arraystr,'"','once'))
error('Octave eval can produce empty cells for JSON-like input');
end
object=eval(arraystr);
pos=endpos;
catch
while 1
newopt=varargin2struct(varargin{:},'JSONLAB_ArrayDepth_',arraydepth+1);
val = parse_value(newopt);
object{end+1} = val;
if next_char == ']'
break;
end
parse_char(',');
end
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr len esc index_esc len_esc
% len, ns = length(inStr), keyboard
if inStr(pos) ~= '"'
error_pos('String starting with " expected at position %d');
else
pos = pos + 1;
end
str = '';
while pos <= len
while index_esc <= len_esc && esc(index_esc) < pos
index_esc = index_esc + 1;
end
if index_esc > len_esc
str = [str inStr(pos:len)];
pos = len + 1;
break;
else
str = [str inStr(pos:esc(index_esc)-1)];
pos = esc(index_esc);
end
nstr = length(str); switch inStr(pos)
case '"'
pos = pos + 1;
if(~isempty(str))
if(strcmp(str,'_Inf_'))
str=Inf;
elseif(strcmp(str,'-_Inf_'))
str=-Inf;
elseif(strcmp(str,'_NaN_'))
str=NaN;
end
end
return;
case '\'
if pos+1 > len
error_pos('End of file reached right after escape character');
end
pos = pos + 1;
switch inStr(pos)
case {'"' '\' '/'}
str(nstr+1) = inStr(pos);
pos = pos + 1;
case {'b' 'f' 'n' 'r' 't'}
str(nstr+1) = sprintf(['\' inStr(pos)]);
pos = pos + 1;
case 'u'
if pos+4 > len
error_pos('End of file reached in escaped unicode character');
end
str(nstr+(1:6)) = inStr(pos-1:pos+4);
pos = pos + 5;
end
otherwise % should never happen
str(nstr+1) = inStr(pos), keyboard
pos = pos + 1;
end
end
error_pos('End of file while expecting end of inStr');
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct
currstr=inStr(pos:end);
numstr=0;
if(isoct~=0)
numstr=regexp(currstr,'^\s*-?(?:0|[1-9]\d*)(?:\.\d+)?(?:[eE][+\-]?\d+)?','end');
[num, one] = sscanf(currstr, '%f', 1);
delta=numstr+1;
else
[num, one, err, delta] = sscanf(currstr, '%f', 1);
if ~isempty(err)
error_pos('Error reading number at position %d');
end
end
pos = pos + delta-1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
pbar=jsonopt('progressbar_',-1,varargin{:});
if(pbar>0)
waitbar(pos/len,pbar,'loading ...');
end
switch(inStr(pos))
case '"'
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'-','0','1','2','3','4','5','6','7','8','9'}
val = parse_number(varargin{:});
return;
case 't'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'true')
val = true;
pos = pos + 4;
return;
end
case 'f'
if pos+4 <= len && strcmpi(inStr(pos:pos+4), 'false')
val = false;
pos = pos + 5;
return;
end
case 'n'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'null')
val = [];
pos = pos + 4;
return;
end
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
% Hard to believe but sprintf("%X") is broken in Octave 4.0.0
% str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
str=sprintf('x0x%s_%s',xxNumToHexStr(char(str(1))),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos, e1l, e1r, maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/6 support vector machines/ex6/lib/jsonlab/loadubjson.m
| 15,574 |
utf_8
|
5974e78e71b81b1e0f76123784b951a4
|
function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a UBJSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.IntEndian [B|L]: specify the endianness of the integer fields
% in the UBJSON input data. B - Big-Endian format for
% integers (as required in the UBJSON specification);
% L - input integer fields are in Little-Endian order.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% obj=struct('string','value','array',[1 2 3]);
% ubjdata=saveubjson('obj',obj);
% dat=loadubjson(ubjdata)
% dat=loadubjson(['examples' filesep 'example1.ubj'])
% dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken fileendian systemendian
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
fileendian=upper(jsonopt('IntEndian','B',opt));
[os,maxelem,systemendian]=computer;
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
%%
function newdata=parse_collection(id,data,obj)
if(jsoncount>0 && exist('data','var'))
if(~iscell(data))
newdata=cell(1);
newdata{1}=data;
data=newdata;
end
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=double(data(j).x0x5F_ArraySize_);
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1); % TODO
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
count=double(parse_number());
end
if next_char ~= '}'
num=0;
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
%parse_char(':');
val = parse_value(varargin{:});
num=num+1;
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}' || (count>=0 && num>=count)
break;
end
%parse_char(',');
end
end
if(count==-1)
parse_char('}');
end
%%-------------------------------------------------------------------------
function [cid,len]=elem_info(type)
id=strfind('iUIlLdD',type);
dataclass={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
if(id>0)
cid=dataclass{id};
len=bytelen(id);
else
error_pos('unsupported type at position %d');
end
%%-------------------------------------------------------------------------
function [data adv]=parse_block(type,count,varargin)
global pos inStr isoct fileendian systemendian
[cid,len]=elem_info(type);
datastr=inStr(pos:pos+len*count-1);
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
id=strfind('iUIlLdD',type);
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,cid));
end
data=typecast(newdata,cid);
adv=double(len*count);
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim=[];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1);
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
if(next_char=='[')
dim=parse_array(varargin{:});
count=prod(double(dim));
else
count=double(parse_number());
end
end
if(~isempty(type))
if(count>=0)
[object adv]=parse_block(type,count,varargin{:});
if(~isempty(dim))
object=reshape(object,dim);
end
pos=pos+adv;
return;
else
endpos=matching_bracket(inStr,pos);
[cid,len]=elem_info(type);
count=(endpos-pos)/len;
[object adv]=parse_block(type,count,varargin{:});
pos=pos+adv;
parse_char(']');
return;
end
end
if next_char ~= ']'
while 1
val = parse_value(varargin{:});
object{end+1} = val;
if next_char == ']'
break;
end
%parse_char(',');
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
if(count==-1)
parse_char(']');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr esc index_esc len_esc
% len, ns = length(inStr), keyboard
type=inStr(pos);
if type ~= 'S' && type ~= 'C' && type ~= 'H'
error_pos('String starting with S expected at position %d');
else
pos = pos + 1;
end
if(type == 'C')
str=inStr(pos);
pos=pos+1;
return;
end
bytelen=double(parse_number());
if(length(inStr)>=pos+bytelen-1)
str=inStr(pos:pos+bytelen-1);
pos=pos+bytelen;
else
error_pos('End of file while expecting end of inStr');
end
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct fileendian systemendian
id=strfind('iUIlLdD',inStr(pos));
if(isempty(id))
error_pos('expecting a number at position %d');
end
type={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
datastr=inStr(pos+1:pos+bytelen(id));
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,type{id}));
end
num=typecast(newdata,type{id});
pos = pos + bytelen(id)+1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
switch(inStr(pos))
case {'S','C','H'}
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'i','U','I','l','L','d','D'}
val = parse_number(varargin{:});
return;
case 'T'
val = true;
pos = pos + 1;
return;
case 'F'
val = false;
pos = pos + 1;
return;
case {'Z','N'}
val = [];
pos = pos + 1;
return;
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos e1l e1r maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
saveubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/6 support vector machines/ex6/lib/jsonlab/saveubjson.m
| 16,123 |
utf_8
|
61d4f51010aedbf97753396f5d2d9ec0
|
function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/17
%
% $Id: saveubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array)
% filename: a string for the file name to save the output UBJSON data
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [1|0]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSON='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a binary string in the UBJSON format (see http://ubjson.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% saveubjson('jsonmesh',jsonmesh)
% saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
json=obj2ubjson(rootname,obj,rootlevel,opt);
if(~rootisarray)
json=['{' json '}'];
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=[jsonp '(' json ')'];
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2ubjson(name,item,level,varargin)
if(iscell(item))
txt=cell2ubjson(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2ubjson(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2ubjson(name,item,level,varargin{:});
else
txt=mat2ubjson(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2ubjson(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item); % let's handle 1D cell first
if(len>1)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) '[']; name='';
else
txt='[';
end
elseif(len==0)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) 'Z']; name='';
else
txt='Z';
end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
txt=[txt obj2ubjson(name,item{i,j},level+(len>1),varargin{:})];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=struct2ubjson(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=[txt S_(checkname(name,varargin{:})) '{'];
else
txt=[txt '{'];
end
if(~isempty(names))
for e=1:length(names)
txt=[txt obj2ubjson(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:})];
end
end
txt=[txt '}'];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=str2ubjson(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
val=item(e,:);
if(len==1)
obj=['' S_(checkname(name,varargin{:})) '' '',S_(val),''];
if(isempty(name)) obj=['',S_(val),'']; end
txt=[txt,'',obj];
else
txt=[txt,'',['',S_(val),'']];
end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=mat2ubjson(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) || jsonopt('ArrayToStruct',0,varargin{:}))
cid=I_(uint32(max(size(item))));
if(isempty(name))
txt=['{' S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1)) ];
else
if(isempty(item))
txt=[S_(checkname(name,varargin{:})),'Z'];
return;
else
txt=[S_(checkname(name,varargin{:})),'{',S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1))];
end
end
else
if(isempty(name))
txt=matdata2ubjson(item,level+1,varargin{:});
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
numtxt=regexprep(regexprep(matdata2ubjson(item,level+1,varargin{:}),'^\[',''),']','');
txt=[S_(checkname(name,varargin{:})) numtxt];
else
txt=[S_(checkname(name,varargin{:})),matdata2ubjson(item,level+1,varargin{:})];
end
end
return;
end
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=[txt,S_('_ArrayIsComplex_'),'T'];
end
txt=[txt,S_('_ArrayIsSparse_'),'T'];
if(size(item,1)==1)
% Row vector, store only column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([iy(:),data'],level+2,varargin{:})];
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,data],level+2,varargin{:})];
else
% General case, store row and column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,iy,data],level+2,varargin{:})];
end
else
if(isreal(item))
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson(item(:)',level+2,varargin{:})];
else
txt=[txt,S_('_ArrayIsComplex_'),'T'];
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([real(item(:)) imag(item(:))],level+2,varargin{:})];
end
end
txt=[txt,'}'];
%%-------------------------------------------------------------------------
function txt=matdata2ubjson(mat,level,varargin)
if(isempty(mat))
txt='Z';
return;
end
if(size(mat,1)==1)
level=level-1;
end
type='';
hasnegtive=(mat<0);
if(isa(mat,'integer') || isinteger(mat) || (isfloat(mat) && all(mod(mat(:),1) == 0)))
if(isempty(hasnegtive))
if(max(mat(:))<=2^8)
type='U';
end
end
if(isempty(type))
% todo - need to consider negative ones separately
id= histc(abs(max(mat(:))),[0 2^7 2^15 2^31 2^63]);
if(isempty(find(id)))
error('high-precision data is not yet supported');
end
key='iIlL';
type=key(find(id));
end
txt=[I_a(mat(:),type,size(mat))];
elseif(islogical(mat))
logicalval='FT';
if(numel(mat)==1)
txt=logicalval(mat+1);
else
txt=['[$U#' I_a(size(mat),'l') typecast(swapbytes(uint8(mat(:)')),'uint8')];
end
else
if(numel(mat)==1)
txt=['[' D_(mat) ']'];
else
txt=D_a(mat(:),'D',size(mat));
end
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function val=S_(str)
if(length(str)==1)
val=['C' str];
else
val=['S' I_(int32(length(str))) str];
end
%%-------------------------------------------------------------------------
function val=I_(num)
if(~isinteger(num))
error('input is not an integer');
end
if(num>=0 && num<255)
val=['U' data2byte(swapbytes(cast(num,'uint8')),'uint8')];
return;
end
key='iIlL';
cid={'int8','int16','int32','int64'};
for i=1:4
if((num>0 && num<2^(i*8-1)) || (num<0 && num>=-2^(i*8-1)))
val=[key(i) data2byte(swapbytes(cast(num,cid{i})),'uint8')];
return;
end
end
error('unsupported integer');
%%-------------------------------------------------------------------------
function val=D_(num)
if(~isfloat(num))
error('input is not a float');
end
if(isa(num,'single'))
val=['d' data2byte(num,'uint8')];
else
val=['D' data2byte(num,'uint8')];
end
%%-------------------------------------------------------------------------
function data=I_a(num,type,dim,format)
id=find(ismember('iUIlL',type));
if(id==0)
error('unsupported integer array');
end
% based on UBJSON specs, all integer types are stored in big endian format
if(id==1)
data=data2byte(swapbytes(int8(num)),'uint8');
blen=1;
elseif(id==2)
data=data2byte(swapbytes(uint8(num)),'uint8');
blen=1;
elseif(id==3)
data=data2byte(swapbytes(int16(num)),'uint8');
blen=2;
elseif(id==4)
data=data2byte(swapbytes(int32(num)),'uint8');
blen=4;
elseif(id==5)
data=data2byte(swapbytes(int64(num)),'uint8');
blen=8;
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/blen)) data(:)'];
end
data=['[' data(:)'];
else
data=reshape(data,blen,numel(data)/blen);
data(2:blen+1,:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function data=D_a(num,type,dim,format)
id=find(ismember('dD',type));
if(id==0)
error('unsupported float array');
end
if(id==1)
data=data2byte(single(num),'uint8');
elseif(id==2)
data=data2byte(double(num),'uint8');
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/(id*4))) data(:)'];
end
data=['[' data];
else
data=reshape(data,(id*4),length(data)/(id*4));
data(2:(id*4+1),:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function bytes=data2byte(varargin)
bytes=typecast(varargin{:});
bytes=bytes(:)';
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submit.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/4 neural nets/ex4/submit.m
| 1,635 |
utf_8
|
ae9c236c78f9b5b09db8fbc2052990fc
|
function submit()
addpath('./lib');
conf.assignmentSlug = 'neural-network-learning';
conf.itemName = 'Neural Networks Learning';
conf.partArrays = { ...
{ ...
'1', ...
{ 'nnCostFunction.m' }, ...
'Feedforward and Cost Function', ...
}, ...
{ ...
'2', ...
{ 'nnCostFunction.m' }, ...
'Regularized Cost Function', ...
}, ...
{ ...
'3', ...
{ 'sigmoidGradient.m' }, ...
'Sigmoid Gradient', ...
}, ...
{ ...
'4', ...
{ 'nnCostFunction.m' }, ...
'Neural Network Gradient (Backpropagation)', ...
}, ...
{ ...
'5', ...
{ 'nnCostFunction.m' }, ...
'Regularized Gradient', ...
}, ...
};
conf.output = @output;
submitWithConfiguration(conf);
end
function out = output(partId, auxstring)
% Random Test Cases
X = reshape(3 * sin(1:1:30), 3, 10);
Xm = reshape(sin(1:32), 16, 2) / 5;
ym = 1 + mod(1:16,4)';
t1 = sin(reshape(1:2:24, 4, 3));
t2 = cos(reshape(1:2:40, 4, 5));
t = [t1(:) ; t2(:)];
if partId == '1'
[J] = nnCostFunction(t, 2, 4, 4, Xm, ym, 0);
out = sprintf('%0.5f ', J);
elseif partId == '2'
[J] = nnCostFunction(t, 2, 4, 4, Xm, ym, 1.5);
out = sprintf('%0.5f ', J);
elseif partId == '3'
out = sprintf('%0.5f ', sigmoidGradient(X));
elseif partId == '4'
[J, grad] = nnCostFunction(t, 2, 4, 4, Xm, ym, 0);
out = sprintf('%0.5f ', J);
out = [out sprintf('%0.5f ', grad)];
elseif partId == '5'
[J, grad] = nnCostFunction(t, 2, 4, 4, Xm, ym, 1.5);
out = sprintf('%0.5f ', J);
out = [out sprintf('%0.5f ', grad)];
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submitWithConfiguration.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/4 neural nets/ex4/lib/submitWithConfiguration.m
| 3,926 |
utf_8
|
f889a7cf3dc6c1c2877566d38df1bec8
|
function submitWithConfiguration(conf)
% Note: has the "certificate" patch from Liran for Windows-like systems
addpath('./lib/jsonlab');
%keyboard
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = promptToken('', '', tokenFile);
end
if isempty(token)
fprintf('!! Submission Cancelled\n');
return
end
try
response = submitParts(conf, email, token, parts);
catch
e = lasterror();
fprintf( ...
'!! Submission failed: unexpected error: %s\n', ...
e.message);
fprintf('!! Please try again later.\n');
return
end
if isfield(response, 'errorMessage')
fprintf('!! Submission failed: %s\n', response.errorMessage);
else
showFeedback(parts, response);
save(tokenFile, 'email', 'token');
end
end
function [email token] = promptToken(email, existingToken, tokenFile)
if (~isempty(email) && ~isempty(existingToken))
prompt = sprintf( ...
'Use token from last successful submission (%s)? (Y/n): ', ...
email);
reenter = input(prompt, 's');
if (isempty(reenter) || reenter(1) == 'Y' || reenter(1) == 'y')
token = existingToken;
return;
else
delete(tokenFile);
end
end
email = input('Login (email address): ', 's');
token = input('Token: ', 's');
end
function isValid = isValidPartOptionIndex(partOptions, i)
isValid = (~isempty(i)) && (1 <= i) && (i <= numel(partOptions));
end
function response = submitParts(conf, email, token, parts)
body = makePostBody(conf, email, token, parts);
submissionUrl = submissionUrl();
params = {'jsonBody', body};
%responseBody = urlread(submissionUrl, 'post', params);
[code, responseBody] = system(sprintf('echo jsonBody=%s | curl -k -X POST -d @- %s', body, submissionUrl));
response = loadjson(responseBody);
end
function body = makePostBody(conf, email, token, parts)
bodyStruct.assignmentSlug = conf.assignmentSlug;
bodyStruct.submitterEmail = email;
bodyStruct.secret = token;
bodyStruct.parts = makePartsStruct(conf, parts);
opt.Compact = 1;
body = savejson('', bodyStruct, opt);
end
function partsStruct = makePartsStruct(conf, parts)
for part = parts
partId = part{:}.id;
fieldName = makeValidFieldName(partId);
outputStruct.output = conf.output(partId);
partsStruct.(fieldName) = outputStruct;
end
end
function [parts] = parts(conf)
parts = {};
for partArray = conf.partArrays
part.id = partArray{:}{1};
part.sourceFiles = partArray{:}{2};
part.name = partArray{:}{3};
parts{end + 1} = part;
end
end
function showFeedback(parts, response)
fprintf('== \n');
fprintf('== %43s | %9s | %-s\n', 'Part Name', 'Score', 'Feedback');
fprintf('== %43s | %9s | %-s\n', '---------', '-----', '--------');
for part = parts
score = '';
partFeedback = '';
partFeedback = response.partFeedbacks.(makeValidFieldName(part{:}.id));
partEvaluation = response.partEvaluations.(makeValidFieldName(part{:}.id));
score = sprintf('%d / %3d', partEvaluation.score, partEvaluation.maxScore);
fprintf('== %43s | %9s | %-s\n', part{:}.name, score, partFeedback);
end
evaluation = response.evaluation;
totalScore = sprintf('%d / %d', evaluation.score, evaluation.maxScore);
fprintf('== --------------------------------\n');
fprintf('== %43s | %9s | %-s\n', '', totalScore, '');
fprintf('== \n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Service configuration
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function submissionUrl = submissionUrl()
submissionUrl = 'https://www-origin.coursera.org/api/onDemandProgrammingImmediateFormSubmissions.v1';
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
savejson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/4 neural nets/ex4/lib/jsonlab/savejson.m
| 17,462 |
utf_8
|
861b534fc35ffe982b53ca3ca83143bf
|
function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09
%
% $Id: savejson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array).
% filename: a string for the file name to save the output JSON data.
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.FloatFormat ['%.10g'|string]: format to show each numeric element
% of a 1D/2D array;
% opt.ArrayIndent [1|0]: if 1, output explicit data array with
% precedent indentation; if 0, no indentation
% opt.ArrayToStruct[0|1]: when set to 0, savejson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [0|1]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, savejson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.Inf ['"$1_Inf_"'|string]: a customized regular expression pattern
% to represent +/-Inf. The matched pattern is '([-+]*)Inf'
% and $1 represents the sign. For those who want to use
% 1e999 to represent Inf, they can set opt.Inf to '$11e999'
% opt.NaN ['"_NaN_"'|string]: a customized regular expression pattern
% to represent NaN
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSONP='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
% opt.SaveBinary [0|1]: 1 - save the JSON file in binary mode; 0 - text mode.
% opt.Compact [0|1]: 1- out compact JSON format (remove all newlines and tabs)
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a string in the JSON format (see http://json.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% savejson('jmesh',jsonmesh)
% savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
whitespaces=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
if(jsonopt('Compact',0,opt)==1)
whitespaces=struct('tab','','newline','','sep',',');
end
if(~isfield(opt,'whitespaces_'))
opt.whitespaces_=whitespaces;
end
nl=whitespaces.newline;
json=obj2json(rootname,obj,rootlevel,opt);
if(rootisarray)
json=sprintf('%s%s',json,nl);
else
json=sprintf('{%s%s%s}\n',nl,json,nl);
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=sprintf('%s(%s);%s',jsonp,json,nl);
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
if(jsonopt('SaveBinary',0,opt)==1)
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
else
fid = fopen(opt.FileName, 'wt');
fwrite(fid,json,'char');
end
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2json(name,item,level,varargin)
if(iscell(item))
txt=cell2json(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2json(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2json(name,item,level,varargin{:});
else
txt=mat2json(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2json(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=jsonopt('whitespaces_',struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n')),varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
nl=ws.newline;
if(len>1)
if(~isempty(name))
txt=sprintf('%s"%s": [%s',padding0, checkname(name,varargin{:}),nl); name='';
else
txt=sprintf('%s[%s',padding0,nl);
end
elseif(len==0)
if(~isempty(name))
txt=sprintf('%s"%s": []',padding0, checkname(name,varargin{:})); name='';
else
txt=sprintf('%s[]',padding0);
end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
txt=sprintf('%s%s',txt,obj2json(name,item{i,j},level+(dim(1)>1)+1,varargin{:}));
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
%if(j==dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=struct2json(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
padding1=repmat(ws.tab,1,level+(dim(1)>1)+(len>1));
nl=ws.newline;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding0,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding0,nl); end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=sprintf('%s%s"%s": {%s',txt,padding1, checkname(name,varargin{:}),nl);
else
txt=sprintf('%s%s{%s',txt,padding1,nl);
end
if(~isempty(names))
for e=1:length(names)
txt=sprintf('%s%s',txt,obj2json(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:}));
if(e<length(names)) txt=sprintf('%s%s',txt,','); end
txt=sprintf('%s%s',txt,nl);
end
end
txt=sprintf('%s%s}',txt,padding1);
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=str2json(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding1,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding1,nl); end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
if(isoct)
val=regexprep(item(e,:),'\\','\\');
val=regexprep(val,'"','\"');
val=regexprep(val,'^"','\"');
else
val=regexprep(item(e,:),'\\','\\\\');
val=regexprep(val,'"','\\"');
val=regexprep(val,'^"','\\"');
end
val=escapejsonstring(val);
if(len==1)
obj=['"' checkname(name,varargin{:}) '": ' '"',val,'"'];
if(isempty(name)) obj=['"',val,'"']; end
txt=sprintf('%s%s%s%s',txt,padding1,obj);
else
txt=sprintf('%s%s%s%s',txt,padding0,['"',val,'"']);
end
if(e==len) sep=''; end
txt=sprintf('%s%s',txt,sep);
end
if(len>1) txt=sprintf('%s%s%s%s',txt,nl,padding1,']'); end
%%-------------------------------------------------------------------------
function txt=mat2json(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) ||jsonopt('ArrayToStruct',0,varargin{:}))
if(isempty(name))
txt=sprintf('%s{%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
else
txt=sprintf('%s"%s": {%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,checkname(name,varargin{:}),nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
end
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1 && level>0)
numtxt=regexprep(regexprep(matdata2json(item,level+1,varargin{:}),'^\[',''),']','');
else
numtxt=matdata2json(item,level+1,varargin{:});
end
if(isempty(name))
txt=sprintf('%s%s',padding1,numtxt);
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
else
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
end
end
return;
end
dataformat='%s%s%s%s%s';
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsSparse_": ','1', sep);
if(size(item,1)==1)
% Row vector, store only column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([iy(:),data'],level+2,varargin{:}), nl);
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,data],level+2,varargin{:}), nl);
else
% General case, store row and column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,iy,data],level+2,varargin{:}), nl);
end
else
if(isreal(item))
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json(item(:)',level+2,varargin{:}), nl);
else
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([real(item(:)) imag(item(:))],level+2,varargin{:}), nl);
end
end
txt=sprintf('%s%s%s',txt,padding1,'}');
%%-------------------------------------------------------------------------
function txt=matdata2json(mat,level,varargin)
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
tab=ws.tab;
nl=ws.newline;
if(size(mat,1)==1)
pre='';
post='';
level=level-1;
else
pre=sprintf('[%s',nl);
post=sprintf('%s%s]',nl,repmat(tab,1,level-1));
end
if(isempty(mat))
txt='null';
return;
end
floatformat=jsonopt('FloatFormat','%.10g',varargin{:});
%if(numel(mat)>1)
formatstr=['[' repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf('],%s',nl)]];
%else
% formatstr=[repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf(',\n')]];
%end
if(nargin>=2 && size(mat,1)>1 && jsonopt('ArrayIndent',1,varargin{:})==1)
formatstr=[repmat(tab,1,level) formatstr];
end
txt=sprintf(formatstr,mat');
txt(end-length(nl):end)=[];
if(islogical(mat) && jsonopt('ParseLogical',0,varargin{:})==1)
txt=regexprep(txt,'1','true');
txt=regexprep(txt,'0','false');
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],\n['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
txt=[pre txt post];
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function newstr=escapejsonstring(str)
newstr=str;
isoct=exist('OCTAVE_VERSION','builtin');
if(isoct)
vv=sscanf(OCTAVE_VERSION,'%f');
if(vv(1)>=3.8) isoct=0; end
end
if(isoct)
escapechars={'\a','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},escapechars{i});
end
else
escapechars={'\a','\b','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},regexprep(escapechars{i},'\\','\\\\'));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/4 neural nets/ex4/lib/jsonlab/loadjson.m
| 18,884 |
ibm852
|
d21f0844f91f2dbb9ea8df00eda346ca
|
function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% Nedialko Krouchev: http://www.mathworks.com/matlabcentral/fileexchange/25713
% created on 2009/11/02
% François Glineur: http://www.mathworks.com/matlabcentral/fileexchange/23393
% created on 2009/03/22
% Joel Feenstra:
% http://www.mathworks.com/matlabcentral/fileexchange/20565
% created on 2008/07/03
%
% $Id: loadjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a JSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.FastArrayParser [1|0 or integer]: if set to 1, use a
% speed-optimized array parser when loading an
% array object. The fast array parser may
% collapse block arrays into a single large
% array similar to rules defined in cell2mat; 0 to
% use a legacy parser; if set to a larger-than-1
% value, this option will specify the minimum
% dimension to enable the fast array parser. For
% example, if the input is a 3D array, setting
% FastArrayParser to 1 will return a 3D array;
% setting to 2 will return a cell array of 2D
% arrays; setting to 3 will return to a 2D cell
% array of 1D vectors; setting to 4 will return a
% 3D cell array.
% opt.ShowProgress [0|1]: if set to 1, loadjson displays a progress bar.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
% dat=loadjson(['examples' filesep 'example1.json'])
% dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
if(jsonopt('ShowProgress',0,opt)==1)
opt.progressbar_=waitbar(0,'loading ...');
end
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
if(isfield(opt,'progressbar_'))
close(opt.progressbar_);
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=data(j).x0x5F_ArraySize_;
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
if next_char ~= '}'
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
parse_char(':');
val = parse_value(varargin{:});
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}'
break;
end
parse_char(',');
end
end
parse_char('}');
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim2=[];
arraydepth=jsonopt('JSONLAB_ArrayDepth_',1,varargin{:});
pbar=jsonopt('progressbar_',-1,varargin{:});
if next_char ~= ']'
if(jsonopt('FastArrayParser',1,varargin{:})>=1 && arraydepth>=jsonopt('FastArrayParser',1,varargin{:}))
[endpos, e1l, e1r, maxlevel]=matching_bracket(inStr,pos);
arraystr=['[' inStr(pos:endpos)];
arraystr=regexprep(arraystr,'"_NaN_"','NaN');
arraystr=regexprep(arraystr,'"([-+]*)_Inf_"','$1Inf');
arraystr(arraystr==sprintf('\n'))=[];
arraystr(arraystr==sprintf('\r'))=[];
%arraystr=regexprep(arraystr,'\s*,',','); % this is slow,sometimes needed
if(~isempty(e1l) && ~isempty(e1r)) % the array is in 2D or higher D
astr=inStr((e1l+1):(e1r-1));
astr=regexprep(astr,'"_NaN_"','NaN');
astr=regexprep(astr,'"([-+]*)_Inf_"','$1Inf');
astr(astr==sprintf('\n'))=[];
astr(astr==sprintf('\r'))=[];
astr(astr==' ')='';
if(isempty(find(astr=='[', 1))) % array is 2D
dim2=length(sscanf(astr,'%f,',[1 inf]));
end
else % array is 1D
astr=arraystr(2:end-1);
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',[1,inf]);
if(nextidx>=length(astr)-1)
object=obj;
pos=endpos;
parse_char(']');
return;
end
end
if(~isempty(dim2))
astr=arraystr;
astr(astr=='[')='';
astr(astr==']')='';
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',inf);
if(nextidx>=length(astr)-1)
object=reshape(obj,dim2,numel(obj)/dim2)';
pos=endpos;
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
return;
end
end
arraystr=regexprep(arraystr,'\]\s*,','];');
else
arraystr='[';
end
try
if(isoct && regexp(arraystr,'"','once'))
error('Octave eval can produce empty cells for JSON-like input');
end
object=eval(arraystr);
pos=endpos;
catch
while 1
newopt=varargin2struct(varargin{:},'JSONLAB_ArrayDepth_',arraydepth+1);
val = parse_value(newopt);
object{end+1} = val;
if next_char == ']'
break;
end
parse_char(',');
end
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr len esc index_esc len_esc
% len, ns = length(inStr), keyboard
if inStr(pos) ~= '"'
error_pos('String starting with " expected at position %d');
else
pos = pos + 1;
end
str = '';
while pos <= len
while index_esc <= len_esc && esc(index_esc) < pos
index_esc = index_esc + 1;
end
if index_esc > len_esc
str = [str inStr(pos:len)];
pos = len + 1;
break;
else
str = [str inStr(pos:esc(index_esc)-1)];
pos = esc(index_esc);
end
nstr = length(str); switch inStr(pos)
case '"'
pos = pos + 1;
if(~isempty(str))
if(strcmp(str,'_Inf_'))
str=Inf;
elseif(strcmp(str,'-_Inf_'))
str=-Inf;
elseif(strcmp(str,'_NaN_'))
str=NaN;
end
end
return;
case '\'
if pos+1 > len
error_pos('End of file reached right after escape character');
end
pos = pos + 1;
switch inStr(pos)
case {'"' '\' '/'}
str(nstr+1) = inStr(pos);
pos = pos + 1;
case {'b' 'f' 'n' 'r' 't'}
str(nstr+1) = sprintf(['\' inStr(pos)]);
pos = pos + 1;
case 'u'
if pos+4 > len
error_pos('End of file reached in escaped unicode character');
end
str(nstr+(1:6)) = inStr(pos-1:pos+4);
pos = pos + 5;
end
otherwise % should never happen
str(nstr+1) = inStr(pos), keyboard
pos = pos + 1;
end
end
error_pos('End of file while expecting end of inStr');
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct
currstr=inStr(pos:end);
numstr=0;
if(isoct~=0)
numstr=regexp(currstr,'^\s*-?(?:0|[1-9]\d*)(?:\.\d+)?(?:[eE][+\-]?\d+)?','end');
[num, one] = sscanf(currstr, '%f', 1);
delta=numstr+1;
else
[num, one, err, delta] = sscanf(currstr, '%f', 1);
if ~isempty(err)
error_pos('Error reading number at position %d');
end
end
pos = pos + delta-1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
pbar=jsonopt('progressbar_',-1,varargin{:});
if(pbar>0)
waitbar(pos/len,pbar,'loading ...');
end
switch(inStr(pos))
case '"'
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'-','0','1','2','3','4','5','6','7','8','9'}
val = parse_number(varargin{:});
return;
case 't'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'true')
val = true;
pos = pos + 4;
return;
end
case 'f'
if pos+4 <= len && strcmpi(inStr(pos:pos+4), 'false')
val = false;
pos = pos + 5;
return;
end
case 'n'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'null')
val = [];
pos = pos + 4;
return;
end
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
% Hard to believe but sprintf("%X") is broken in Octave 4.0.0
% str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
str=sprintf('x0x%s_%s',xxNumToHexStr(char(str(1))),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos, e1l, e1r, maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/4 neural nets/ex4/lib/jsonlab/loadubjson.m
| 15,574 |
utf_8
|
5974e78e71b81b1e0f76123784b951a4
|
function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a UBJSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.IntEndian [B|L]: specify the endianness of the integer fields
% in the UBJSON input data. B - Big-Endian format for
% integers (as required in the UBJSON specification);
% L - input integer fields are in Little-Endian order.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% obj=struct('string','value','array',[1 2 3]);
% ubjdata=saveubjson('obj',obj);
% dat=loadubjson(ubjdata)
% dat=loadubjson(['examples' filesep 'example1.ubj'])
% dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken fileendian systemendian
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
fileendian=upper(jsonopt('IntEndian','B',opt));
[os,maxelem,systemendian]=computer;
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
%%
function newdata=parse_collection(id,data,obj)
if(jsoncount>0 && exist('data','var'))
if(~iscell(data))
newdata=cell(1);
newdata{1}=data;
data=newdata;
end
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=double(data(j).x0x5F_ArraySize_);
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1); % TODO
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
count=double(parse_number());
end
if next_char ~= '}'
num=0;
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
%parse_char(':');
val = parse_value(varargin{:});
num=num+1;
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}' || (count>=0 && num>=count)
break;
end
%parse_char(',');
end
end
if(count==-1)
parse_char('}');
end
%%-------------------------------------------------------------------------
function [cid,len]=elem_info(type)
id=strfind('iUIlLdD',type);
dataclass={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
if(id>0)
cid=dataclass{id};
len=bytelen(id);
else
error_pos('unsupported type at position %d');
end
%%-------------------------------------------------------------------------
function [data adv]=parse_block(type,count,varargin)
global pos inStr isoct fileendian systemendian
[cid,len]=elem_info(type);
datastr=inStr(pos:pos+len*count-1);
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
id=strfind('iUIlLdD',type);
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,cid));
end
data=typecast(newdata,cid);
adv=double(len*count);
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim=[];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1);
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
if(next_char=='[')
dim=parse_array(varargin{:});
count=prod(double(dim));
else
count=double(parse_number());
end
end
if(~isempty(type))
if(count>=0)
[object adv]=parse_block(type,count,varargin{:});
if(~isempty(dim))
object=reshape(object,dim);
end
pos=pos+adv;
return;
else
endpos=matching_bracket(inStr,pos);
[cid,len]=elem_info(type);
count=(endpos-pos)/len;
[object adv]=parse_block(type,count,varargin{:});
pos=pos+adv;
parse_char(']');
return;
end
end
if next_char ~= ']'
while 1
val = parse_value(varargin{:});
object{end+1} = val;
if next_char == ']'
break;
end
%parse_char(',');
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
if(count==-1)
parse_char(']');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr esc index_esc len_esc
% len, ns = length(inStr), keyboard
type=inStr(pos);
if type ~= 'S' && type ~= 'C' && type ~= 'H'
error_pos('String starting with S expected at position %d');
else
pos = pos + 1;
end
if(type == 'C')
str=inStr(pos);
pos=pos+1;
return;
end
bytelen=double(parse_number());
if(length(inStr)>=pos+bytelen-1)
str=inStr(pos:pos+bytelen-1);
pos=pos+bytelen;
else
error_pos('End of file while expecting end of inStr');
end
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct fileendian systemendian
id=strfind('iUIlLdD',inStr(pos));
if(isempty(id))
error_pos('expecting a number at position %d');
end
type={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
datastr=inStr(pos+1:pos+bytelen(id));
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,type{id}));
end
num=typecast(newdata,type{id});
pos = pos + bytelen(id)+1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
switch(inStr(pos))
case {'S','C','H'}
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'i','U','I','l','L','d','D'}
val = parse_number(varargin{:});
return;
case 'T'
val = true;
pos = pos + 1;
return;
case 'F'
val = false;
pos = pos + 1;
return;
case {'Z','N'}
val = [];
pos = pos + 1;
return;
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos e1l e1r maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
saveubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/4 neural nets/ex4/lib/jsonlab/saveubjson.m
| 16,123 |
utf_8
|
61d4f51010aedbf97753396f5d2d9ec0
|
function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/17
%
% $Id: saveubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array)
% filename: a string for the file name to save the output UBJSON data
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [1|0]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSON='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a binary string in the UBJSON format (see http://ubjson.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% saveubjson('jsonmesh',jsonmesh)
% saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
json=obj2ubjson(rootname,obj,rootlevel,opt);
if(~rootisarray)
json=['{' json '}'];
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=[jsonp '(' json ')'];
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2ubjson(name,item,level,varargin)
if(iscell(item))
txt=cell2ubjson(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2ubjson(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2ubjson(name,item,level,varargin{:});
else
txt=mat2ubjson(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2ubjson(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item); % let's handle 1D cell first
if(len>1)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) '[']; name='';
else
txt='[';
end
elseif(len==0)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) 'Z']; name='';
else
txt='Z';
end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
txt=[txt obj2ubjson(name,item{i,j},level+(len>1),varargin{:})];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=struct2ubjson(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=[txt S_(checkname(name,varargin{:})) '{'];
else
txt=[txt '{'];
end
if(~isempty(names))
for e=1:length(names)
txt=[txt obj2ubjson(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:})];
end
end
txt=[txt '}'];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=str2ubjson(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
val=item(e,:);
if(len==1)
obj=['' S_(checkname(name,varargin{:})) '' '',S_(val),''];
if(isempty(name)) obj=['',S_(val),'']; end
txt=[txt,'',obj];
else
txt=[txt,'',['',S_(val),'']];
end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=mat2ubjson(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) || jsonopt('ArrayToStruct',0,varargin{:}))
cid=I_(uint32(max(size(item))));
if(isempty(name))
txt=['{' S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1)) ];
else
if(isempty(item))
txt=[S_(checkname(name,varargin{:})),'Z'];
return;
else
txt=[S_(checkname(name,varargin{:})),'{',S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1))];
end
end
else
if(isempty(name))
txt=matdata2ubjson(item,level+1,varargin{:});
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
numtxt=regexprep(regexprep(matdata2ubjson(item,level+1,varargin{:}),'^\[',''),']','');
txt=[S_(checkname(name,varargin{:})) numtxt];
else
txt=[S_(checkname(name,varargin{:})),matdata2ubjson(item,level+1,varargin{:})];
end
end
return;
end
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=[txt,S_('_ArrayIsComplex_'),'T'];
end
txt=[txt,S_('_ArrayIsSparse_'),'T'];
if(size(item,1)==1)
% Row vector, store only column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([iy(:),data'],level+2,varargin{:})];
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,data],level+2,varargin{:})];
else
% General case, store row and column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,iy,data],level+2,varargin{:})];
end
else
if(isreal(item))
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson(item(:)',level+2,varargin{:})];
else
txt=[txt,S_('_ArrayIsComplex_'),'T'];
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([real(item(:)) imag(item(:))],level+2,varargin{:})];
end
end
txt=[txt,'}'];
%%-------------------------------------------------------------------------
function txt=matdata2ubjson(mat,level,varargin)
if(isempty(mat))
txt='Z';
return;
end
if(size(mat,1)==1)
level=level-1;
end
type='';
hasnegtive=(mat<0);
if(isa(mat,'integer') || isinteger(mat) || (isfloat(mat) && all(mod(mat(:),1) == 0)))
if(isempty(hasnegtive))
if(max(mat(:))<=2^8)
type='U';
end
end
if(isempty(type))
% todo - need to consider negative ones separately
id= histc(abs(max(mat(:))),[0 2^7 2^15 2^31 2^63]);
if(isempty(find(id)))
error('high-precision data is not yet supported');
end
key='iIlL';
type=key(find(id));
end
txt=[I_a(mat(:),type,size(mat))];
elseif(islogical(mat))
logicalval='FT';
if(numel(mat)==1)
txt=logicalval(mat+1);
else
txt=['[$U#' I_a(size(mat),'l') typecast(swapbytes(uint8(mat(:)')),'uint8')];
end
else
if(numel(mat)==1)
txt=['[' D_(mat) ']'];
else
txt=D_a(mat(:),'D',size(mat));
end
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function val=S_(str)
if(length(str)==1)
val=['C' str];
else
val=['S' I_(int32(length(str))) str];
end
%%-------------------------------------------------------------------------
function val=I_(num)
if(~isinteger(num))
error('input is not an integer');
end
if(num>=0 && num<255)
val=['U' data2byte(swapbytes(cast(num,'uint8')),'uint8')];
return;
end
key='iIlL';
cid={'int8','int16','int32','int64'};
for i=1:4
if((num>0 && num<2^(i*8-1)) || (num<0 && num>=-2^(i*8-1)))
val=[key(i) data2byte(swapbytes(cast(num,cid{i})),'uint8')];
return;
end
end
error('unsupported integer');
%%-------------------------------------------------------------------------
function val=D_(num)
if(~isfloat(num))
error('input is not a float');
end
if(isa(num,'single'))
val=['d' data2byte(num,'uint8')];
else
val=['D' data2byte(num,'uint8')];
end
%%-------------------------------------------------------------------------
function data=I_a(num,type,dim,format)
id=find(ismember('iUIlL',type));
if(id==0)
error('unsupported integer array');
end
% based on UBJSON specs, all integer types are stored in big endian format
if(id==1)
data=data2byte(swapbytes(int8(num)),'uint8');
blen=1;
elseif(id==2)
data=data2byte(swapbytes(uint8(num)),'uint8');
blen=1;
elseif(id==3)
data=data2byte(swapbytes(int16(num)),'uint8');
blen=2;
elseif(id==4)
data=data2byte(swapbytes(int32(num)),'uint8');
blen=4;
elseif(id==5)
data=data2byte(swapbytes(int64(num)),'uint8');
blen=8;
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/blen)) data(:)'];
end
data=['[' data(:)'];
else
data=reshape(data,blen,numel(data)/blen);
data(2:blen+1,:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function data=D_a(num,type,dim,format)
id=find(ismember('dD',type));
if(id==0)
error('unsupported float array');
end
if(id==1)
data=data2byte(single(num),'uint8');
elseif(id==2)
data=data2byte(double(num),'uint8');
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/(id*4))) data(:)'];
end
data=['[' data];
else
data=reshape(data,(id*4),length(data)/(id*4));
data(2:(id*4+1),:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function bytes=data2byte(varargin)
bytes=typecast(varargin{:});
bytes=bytes(:)';
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submit.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/2 Logistic Regression/ex2/submit.m
| 1,605 |
utf_8
|
9b63d386e9bd7bcca66b1a3d2fa37579
|
function submit()
addpath('./lib');
conf.assignmentSlug = 'logistic-regression';
conf.itemName = 'Logistic Regression';
conf.partArrays = { ...
{ ...
'1', ...
{ 'sigmoid.m' }, ...
'Sigmoid Function', ...
}, ...
{ ...
'2', ...
{ 'costFunction.m' }, ...
'Logistic Regression Cost', ...
}, ...
{ ...
'3', ...
{ 'costFunction.m' }, ...
'Logistic Regression Gradient', ...
}, ...
{ ...
'4', ...
{ 'predict.m' }, ...
'Predict', ...
}, ...
{ ...
'5', ...
{ 'costFunctionReg.m' }, ...
'Regularized Logistic Regression Cost', ...
}, ...
{ ...
'6', ...
{ 'costFunctionReg.m' }, ...
'Regularized Logistic Regression Gradient', ...
}, ...
};
conf.output = @output;
submitWithConfiguration(conf);
end
function out = output(partId, auxstring)
% Random Test Cases
X = [ones(20,1) (exp(1) * sin(1:1:20))' (exp(0.5) * cos(1:1:20))'];
y = sin(X(:,1) + X(:,2)) > 0;
if partId == '1'
out = sprintf('%0.5f ', sigmoid(X));
elseif partId == '2'
out = sprintf('%0.5f ', costFunction([0.25 0.5 -0.5]', X, y));
elseif partId == '3'
[cost, grad] = costFunction([0.25 0.5 -0.5]', X, y);
out = sprintf('%0.5f ', grad);
elseif partId == '4'
out = sprintf('%0.5f ', predict([0.25 0.5 -0.5]', X));
elseif partId == '5'
out = sprintf('%0.5f ', costFunctionReg([0.25 0.5 -0.5]', X, y, 0.1));
elseif partId == '6'
[cost, grad] = costFunctionReg([0.25 0.5 -0.5]', X, y, 0.1);
out = sprintf('%0.5f ', grad);
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submit.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/1 Linear Regression with Multiple Variables/ex1/submit.m
| 1,876 |
utf_8
|
8d1c467b830a89c187c05b121cb8fbfd
|
function submit()
addpath('./lib');
conf.assignmentSlug = 'linear-regression';
conf.itemName = 'Linear Regression with Multiple Variables';
conf.partArrays = { ...
{ ...
'1', ...
{ 'warmUpExercise.m' }, ...
'Warm-up Exercise', ...
}, ...
{ ...
'2', ...
{ 'computeCost.m' }, ...
'Computing Cost (for One Variable)', ...
}, ...
{ ...
'3', ...
{ 'gradientDescent.m' }, ...
'Gradient Descent (for One Variable)', ...
}, ...
{ ...
'4', ...
{ 'featureNormalize.m' }, ...
'Feature Normalization', ...
}, ...
{ ...
'5', ...
{ 'computeCostMulti.m' }, ...
'Computing Cost (for Multiple Variables)', ...
}, ...
{ ...
'6', ...
{ 'gradientDescentMulti.m' }, ...
'Gradient Descent (for Multiple Variables)', ...
}, ...
{ ...
'7', ...
{ 'normalEqn.m' }, ...
'Normal Equations', ...
}, ...
};
conf.output = @output;
submitWithConfiguration(conf);
end
function out = output(partId)
% Random Test Cases
X1 = [ones(20,1) (exp(1) + exp(2) * (0.1:0.1:2))'];
Y1 = X1(:,2) + sin(X1(:,1)) + cos(X1(:,2));
X2 = [X1 X1(:,2).^0.5 X1(:,2).^0.25];
Y2 = Y1.^0.5 + Y1;
if partId == '1'
out = sprintf('%0.5f ', warmUpExercise());
elseif partId == '2'
out = sprintf('%0.5f ', computeCost(X1, Y1, [0.5 -0.5]'));
elseif partId == '3'
out = sprintf('%0.5f ', gradientDescent(X1, Y1, [0.5 -0.5]', 0.01, 10));
elseif partId == '4'
out = sprintf('%0.5f ', featureNormalize(X2(:,2:4)));
elseif partId == '5'
out = sprintf('%0.5f ', computeCostMulti(X2, Y2, [0.1 0.2 0.3 0.4]'));
elseif partId == '6'
out = sprintf('%0.5f ', gradientDescentMulti(X2, Y2, [-0.1 -0.2 -0.3 -0.4]', 0.01, 10));
elseif partId == '7'
out = sprintf('%0.5f ', normalEqn(X2, Y2));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submitWithConfiguration.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/1 Linear Regression with Multiple Variables/ex1/lib/submitWithConfiguration.m
| 3,926 |
utf_8
|
f889a7cf3dc6c1c2877566d38df1bec8
|
function submitWithConfiguration(conf)
% Note: has the "certificate" patch from Liran for Windows-like systems
addpath('./lib/jsonlab');
%keyboard
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = promptToken('', '', tokenFile);
end
if isempty(token)
fprintf('!! Submission Cancelled\n');
return
end
try
response = submitParts(conf, email, token, parts);
catch
e = lasterror();
fprintf( ...
'!! Submission failed: unexpected error: %s\n', ...
e.message);
fprintf('!! Please try again later.\n');
return
end
if isfield(response, 'errorMessage')
fprintf('!! Submission failed: %s\n', response.errorMessage);
else
showFeedback(parts, response);
save(tokenFile, 'email', 'token');
end
end
function [email token] = promptToken(email, existingToken, tokenFile)
if (~isempty(email) && ~isempty(existingToken))
prompt = sprintf( ...
'Use token from last successful submission (%s)? (Y/n): ', ...
email);
reenter = input(prompt, 's');
if (isempty(reenter) || reenter(1) == 'Y' || reenter(1) == 'y')
token = existingToken;
return;
else
delete(tokenFile);
end
end
email = input('Login (email address): ', 's');
token = input('Token: ', 's');
end
function isValid = isValidPartOptionIndex(partOptions, i)
isValid = (~isempty(i)) && (1 <= i) && (i <= numel(partOptions));
end
function response = submitParts(conf, email, token, parts)
body = makePostBody(conf, email, token, parts);
submissionUrl = submissionUrl();
params = {'jsonBody', body};
%responseBody = urlread(submissionUrl, 'post', params);
[code, responseBody] = system(sprintf('echo jsonBody=%s | curl -k -X POST -d @- %s', body, submissionUrl));
response = loadjson(responseBody);
end
function body = makePostBody(conf, email, token, parts)
bodyStruct.assignmentSlug = conf.assignmentSlug;
bodyStruct.submitterEmail = email;
bodyStruct.secret = token;
bodyStruct.parts = makePartsStruct(conf, parts);
opt.Compact = 1;
body = savejson('', bodyStruct, opt);
end
function partsStruct = makePartsStruct(conf, parts)
for part = parts
partId = part{:}.id;
fieldName = makeValidFieldName(partId);
outputStruct.output = conf.output(partId);
partsStruct.(fieldName) = outputStruct;
end
end
function [parts] = parts(conf)
parts = {};
for partArray = conf.partArrays
part.id = partArray{:}{1};
part.sourceFiles = partArray{:}{2};
part.name = partArray{:}{3};
parts{end + 1} = part;
end
end
function showFeedback(parts, response)
fprintf('== \n');
fprintf('== %43s | %9s | %-s\n', 'Part Name', 'Score', 'Feedback');
fprintf('== %43s | %9s | %-s\n', '---------', '-----', '--------');
for part = parts
score = '';
partFeedback = '';
partFeedback = response.partFeedbacks.(makeValidFieldName(part{:}.id));
partEvaluation = response.partEvaluations.(makeValidFieldName(part{:}.id));
score = sprintf('%d / %3d', partEvaluation.score, partEvaluation.maxScore);
fprintf('== %43s | %9s | %-s\n', part{:}.name, score, partFeedback);
end
evaluation = response.evaluation;
totalScore = sprintf('%d / %d', evaluation.score, evaluation.maxScore);
fprintf('== --------------------------------\n');
fprintf('== %43s | %9s | %-s\n', '', totalScore, '');
fprintf('== \n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Service configuration
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function submissionUrl = submissionUrl()
submissionUrl = 'https://www-origin.coursera.org/api/onDemandProgrammingImmediateFormSubmissions.v1';
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
savejson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/1 Linear Regression with Multiple Variables/ex1/lib/jsonlab/savejson.m
| 17,462 |
utf_8
|
861b534fc35ffe982b53ca3ca83143bf
|
function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09
%
% $Id: savejson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array).
% filename: a string for the file name to save the output JSON data.
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.FloatFormat ['%.10g'|string]: format to show each numeric element
% of a 1D/2D array;
% opt.ArrayIndent [1|0]: if 1, output explicit data array with
% precedent indentation; if 0, no indentation
% opt.ArrayToStruct[0|1]: when set to 0, savejson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [0|1]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, savejson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.Inf ['"$1_Inf_"'|string]: a customized regular expression pattern
% to represent +/-Inf. The matched pattern is '([-+]*)Inf'
% and $1 represents the sign. For those who want to use
% 1e999 to represent Inf, they can set opt.Inf to '$11e999'
% opt.NaN ['"_NaN_"'|string]: a customized regular expression pattern
% to represent NaN
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSONP='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
% opt.SaveBinary [0|1]: 1 - save the JSON file in binary mode; 0 - text mode.
% opt.Compact [0|1]: 1- out compact JSON format (remove all newlines and tabs)
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a string in the JSON format (see http://json.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% savejson('jmesh',jsonmesh)
% savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
whitespaces=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
if(jsonopt('Compact',0,opt)==1)
whitespaces=struct('tab','','newline','','sep',',');
end
if(~isfield(opt,'whitespaces_'))
opt.whitespaces_=whitespaces;
end
nl=whitespaces.newline;
json=obj2json(rootname,obj,rootlevel,opt);
if(rootisarray)
json=sprintf('%s%s',json,nl);
else
json=sprintf('{%s%s%s}\n',nl,json,nl);
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=sprintf('%s(%s);%s',jsonp,json,nl);
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
if(jsonopt('SaveBinary',0,opt)==1)
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
else
fid = fopen(opt.FileName, 'wt');
fwrite(fid,json,'char');
end
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2json(name,item,level,varargin)
if(iscell(item))
txt=cell2json(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2json(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2json(name,item,level,varargin{:});
else
txt=mat2json(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2json(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=jsonopt('whitespaces_',struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n')),varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
nl=ws.newline;
if(len>1)
if(~isempty(name))
txt=sprintf('%s"%s": [%s',padding0, checkname(name,varargin{:}),nl); name='';
else
txt=sprintf('%s[%s',padding0,nl);
end
elseif(len==0)
if(~isempty(name))
txt=sprintf('%s"%s": []',padding0, checkname(name,varargin{:})); name='';
else
txt=sprintf('%s[]',padding0);
end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
txt=sprintf('%s%s',txt,obj2json(name,item{i,j},level+(dim(1)>1)+1,varargin{:}));
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
%if(j==dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=struct2json(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
padding1=repmat(ws.tab,1,level+(dim(1)>1)+(len>1));
nl=ws.newline;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding0,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding0,nl); end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=sprintf('%s%s"%s": {%s',txt,padding1, checkname(name,varargin{:}),nl);
else
txt=sprintf('%s%s{%s',txt,padding1,nl);
end
if(~isempty(names))
for e=1:length(names)
txt=sprintf('%s%s',txt,obj2json(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:}));
if(e<length(names)) txt=sprintf('%s%s',txt,','); end
txt=sprintf('%s%s',txt,nl);
end
end
txt=sprintf('%s%s}',txt,padding1);
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=str2json(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding1,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding1,nl); end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
if(isoct)
val=regexprep(item(e,:),'\\','\\');
val=regexprep(val,'"','\"');
val=regexprep(val,'^"','\"');
else
val=regexprep(item(e,:),'\\','\\\\');
val=regexprep(val,'"','\\"');
val=regexprep(val,'^"','\\"');
end
val=escapejsonstring(val);
if(len==1)
obj=['"' checkname(name,varargin{:}) '": ' '"',val,'"'];
if(isempty(name)) obj=['"',val,'"']; end
txt=sprintf('%s%s%s%s',txt,padding1,obj);
else
txt=sprintf('%s%s%s%s',txt,padding0,['"',val,'"']);
end
if(e==len) sep=''; end
txt=sprintf('%s%s',txt,sep);
end
if(len>1) txt=sprintf('%s%s%s%s',txt,nl,padding1,']'); end
%%-------------------------------------------------------------------------
function txt=mat2json(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) ||jsonopt('ArrayToStruct',0,varargin{:}))
if(isempty(name))
txt=sprintf('%s{%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
else
txt=sprintf('%s"%s": {%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,checkname(name,varargin{:}),nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
end
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1 && level>0)
numtxt=regexprep(regexprep(matdata2json(item,level+1,varargin{:}),'^\[',''),']','');
else
numtxt=matdata2json(item,level+1,varargin{:});
end
if(isempty(name))
txt=sprintf('%s%s',padding1,numtxt);
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
else
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
end
end
return;
end
dataformat='%s%s%s%s%s';
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsSparse_": ','1', sep);
if(size(item,1)==1)
% Row vector, store only column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([iy(:),data'],level+2,varargin{:}), nl);
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,data],level+2,varargin{:}), nl);
else
% General case, store row and column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,iy,data],level+2,varargin{:}), nl);
end
else
if(isreal(item))
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json(item(:)',level+2,varargin{:}), nl);
else
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([real(item(:)) imag(item(:))],level+2,varargin{:}), nl);
end
end
txt=sprintf('%s%s%s',txt,padding1,'}');
%%-------------------------------------------------------------------------
function txt=matdata2json(mat,level,varargin)
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
tab=ws.tab;
nl=ws.newline;
if(size(mat,1)==1)
pre='';
post='';
level=level-1;
else
pre=sprintf('[%s',nl);
post=sprintf('%s%s]',nl,repmat(tab,1,level-1));
end
if(isempty(mat))
txt='null';
return;
end
floatformat=jsonopt('FloatFormat','%.10g',varargin{:});
%if(numel(mat)>1)
formatstr=['[' repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf('],%s',nl)]];
%else
% formatstr=[repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf(',\n')]];
%end
if(nargin>=2 && size(mat,1)>1 && jsonopt('ArrayIndent',1,varargin{:})==1)
formatstr=[repmat(tab,1,level) formatstr];
end
txt=sprintf(formatstr,mat');
txt(end-length(nl):end)=[];
if(islogical(mat) && jsonopt('ParseLogical',0,varargin{:})==1)
txt=regexprep(txt,'1','true');
txt=regexprep(txt,'0','false');
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],\n['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
txt=[pre txt post];
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function newstr=escapejsonstring(str)
newstr=str;
isoct=exist('OCTAVE_VERSION','builtin');
if(isoct)
vv=sscanf(OCTAVE_VERSION,'%f');
if(vv(1)>=3.8) isoct=0; end
end
if(isoct)
escapechars={'\a','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},escapechars{i});
end
else
escapechars={'\a','\b','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},regexprep(escapechars{i},'\\','\\\\'));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/1 Linear Regression with Multiple Variables/ex1/lib/jsonlab/loadjson.m
| 18,884 |
ibm852
|
d21f0844f91f2dbb9ea8df00eda346ca
|
function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% Nedialko Krouchev: http://www.mathworks.com/matlabcentral/fileexchange/25713
% created on 2009/11/02
% François Glineur: http://www.mathworks.com/matlabcentral/fileexchange/23393
% created on 2009/03/22
% Joel Feenstra:
% http://www.mathworks.com/matlabcentral/fileexchange/20565
% created on 2008/07/03
%
% $Id: loadjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a JSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.FastArrayParser [1|0 or integer]: if set to 1, use a
% speed-optimized array parser when loading an
% array object. The fast array parser may
% collapse block arrays into a single large
% array similar to rules defined in cell2mat; 0 to
% use a legacy parser; if set to a larger-than-1
% value, this option will specify the minimum
% dimension to enable the fast array parser. For
% example, if the input is a 3D array, setting
% FastArrayParser to 1 will return a 3D array;
% setting to 2 will return a cell array of 2D
% arrays; setting to 3 will return to a 2D cell
% array of 1D vectors; setting to 4 will return a
% 3D cell array.
% opt.ShowProgress [0|1]: if set to 1, loadjson displays a progress bar.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
% dat=loadjson(['examples' filesep 'example1.json'])
% dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
if(jsonopt('ShowProgress',0,opt)==1)
opt.progressbar_=waitbar(0,'loading ...');
end
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
if(isfield(opt,'progressbar_'))
close(opt.progressbar_);
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=data(j).x0x5F_ArraySize_;
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
if next_char ~= '}'
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
parse_char(':');
val = parse_value(varargin{:});
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}'
break;
end
parse_char(',');
end
end
parse_char('}');
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim2=[];
arraydepth=jsonopt('JSONLAB_ArrayDepth_',1,varargin{:});
pbar=jsonopt('progressbar_',-1,varargin{:});
if next_char ~= ']'
if(jsonopt('FastArrayParser',1,varargin{:})>=1 && arraydepth>=jsonopt('FastArrayParser',1,varargin{:}))
[endpos, e1l, e1r, maxlevel]=matching_bracket(inStr,pos);
arraystr=['[' inStr(pos:endpos)];
arraystr=regexprep(arraystr,'"_NaN_"','NaN');
arraystr=regexprep(arraystr,'"([-+]*)_Inf_"','$1Inf');
arraystr(arraystr==sprintf('\n'))=[];
arraystr(arraystr==sprintf('\r'))=[];
%arraystr=regexprep(arraystr,'\s*,',','); % this is slow,sometimes needed
if(~isempty(e1l) && ~isempty(e1r)) % the array is in 2D or higher D
astr=inStr((e1l+1):(e1r-1));
astr=regexprep(astr,'"_NaN_"','NaN');
astr=regexprep(astr,'"([-+]*)_Inf_"','$1Inf');
astr(astr==sprintf('\n'))=[];
astr(astr==sprintf('\r'))=[];
astr(astr==' ')='';
if(isempty(find(astr=='[', 1))) % array is 2D
dim2=length(sscanf(astr,'%f,',[1 inf]));
end
else % array is 1D
astr=arraystr(2:end-1);
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',[1,inf]);
if(nextidx>=length(astr)-1)
object=obj;
pos=endpos;
parse_char(']');
return;
end
end
if(~isempty(dim2))
astr=arraystr;
astr(astr=='[')='';
astr(astr==']')='';
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',inf);
if(nextidx>=length(astr)-1)
object=reshape(obj,dim2,numel(obj)/dim2)';
pos=endpos;
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
return;
end
end
arraystr=regexprep(arraystr,'\]\s*,','];');
else
arraystr='[';
end
try
if(isoct && regexp(arraystr,'"','once'))
error('Octave eval can produce empty cells for JSON-like input');
end
object=eval(arraystr);
pos=endpos;
catch
while 1
newopt=varargin2struct(varargin{:},'JSONLAB_ArrayDepth_',arraydepth+1);
val = parse_value(newopt);
object{end+1} = val;
if next_char == ']'
break;
end
parse_char(',');
end
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr len esc index_esc len_esc
% len, ns = length(inStr), keyboard
if inStr(pos) ~= '"'
error_pos('String starting with " expected at position %d');
else
pos = pos + 1;
end
str = '';
while pos <= len
while index_esc <= len_esc && esc(index_esc) < pos
index_esc = index_esc + 1;
end
if index_esc > len_esc
str = [str inStr(pos:len)];
pos = len + 1;
break;
else
str = [str inStr(pos:esc(index_esc)-1)];
pos = esc(index_esc);
end
nstr = length(str); switch inStr(pos)
case '"'
pos = pos + 1;
if(~isempty(str))
if(strcmp(str,'_Inf_'))
str=Inf;
elseif(strcmp(str,'-_Inf_'))
str=-Inf;
elseif(strcmp(str,'_NaN_'))
str=NaN;
end
end
return;
case '\'
if pos+1 > len
error_pos('End of file reached right after escape character');
end
pos = pos + 1;
switch inStr(pos)
case {'"' '\' '/'}
str(nstr+1) = inStr(pos);
pos = pos + 1;
case {'b' 'f' 'n' 'r' 't'}
str(nstr+1) = sprintf(['\' inStr(pos)]);
pos = pos + 1;
case 'u'
if pos+4 > len
error_pos('End of file reached in escaped unicode character');
end
str(nstr+(1:6)) = inStr(pos-1:pos+4);
pos = pos + 5;
end
otherwise % should never happen
str(nstr+1) = inStr(pos), keyboard
pos = pos + 1;
end
end
error_pos('End of file while expecting end of inStr');
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct
currstr=inStr(pos:end);
numstr=0;
if(isoct~=0)
numstr=regexp(currstr,'^\s*-?(?:0|[1-9]\d*)(?:\.\d+)?(?:[eE][+\-]?\d+)?','end');
[num, one] = sscanf(currstr, '%f', 1);
delta=numstr+1;
else
[num, one, err, delta] = sscanf(currstr, '%f', 1);
if ~isempty(err)
error_pos('Error reading number at position %d');
end
end
pos = pos + delta-1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
pbar=jsonopt('progressbar_',-1,varargin{:});
if(pbar>0)
waitbar(pos/len,pbar,'loading ...');
end
switch(inStr(pos))
case '"'
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'-','0','1','2','3','4','5','6','7','8','9'}
val = parse_number(varargin{:});
return;
case 't'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'true')
val = true;
pos = pos + 4;
return;
end
case 'f'
if pos+4 <= len && strcmpi(inStr(pos:pos+4), 'false')
val = false;
pos = pos + 5;
return;
end
case 'n'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'null')
val = [];
pos = pos + 4;
return;
end
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
% Hard to believe but sprintf("%X") is broken in Octave 4.0.0
% str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
str=sprintf('x0x%s_%s',xxNumToHexStr(char(str(1))),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos, e1l, e1r, maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/1 Linear Regression with Multiple Variables/ex1/lib/jsonlab/loadubjson.m
| 15,574 |
utf_8
|
5974e78e71b81b1e0f76123784b951a4
|
function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a UBJSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.IntEndian [B|L]: specify the endianness of the integer fields
% in the UBJSON input data. B - Big-Endian format for
% integers (as required in the UBJSON specification);
% L - input integer fields are in Little-Endian order.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% obj=struct('string','value','array',[1 2 3]);
% ubjdata=saveubjson('obj',obj);
% dat=loadubjson(ubjdata)
% dat=loadubjson(['examples' filesep 'example1.ubj'])
% dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken fileendian systemendian
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
fileendian=upper(jsonopt('IntEndian','B',opt));
[os,maxelem,systemendian]=computer;
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
%%
function newdata=parse_collection(id,data,obj)
if(jsoncount>0 && exist('data','var'))
if(~iscell(data))
newdata=cell(1);
newdata{1}=data;
data=newdata;
end
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=double(data(j).x0x5F_ArraySize_);
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1); % TODO
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
count=double(parse_number());
end
if next_char ~= '}'
num=0;
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
%parse_char(':');
val = parse_value(varargin{:});
num=num+1;
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}' || (count>=0 && num>=count)
break;
end
%parse_char(',');
end
end
if(count==-1)
parse_char('}');
end
%%-------------------------------------------------------------------------
function [cid,len]=elem_info(type)
id=strfind('iUIlLdD',type);
dataclass={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
if(id>0)
cid=dataclass{id};
len=bytelen(id);
else
error_pos('unsupported type at position %d');
end
%%-------------------------------------------------------------------------
function [data adv]=parse_block(type,count,varargin)
global pos inStr isoct fileendian systemendian
[cid,len]=elem_info(type);
datastr=inStr(pos:pos+len*count-1);
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
id=strfind('iUIlLdD',type);
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,cid));
end
data=typecast(newdata,cid);
adv=double(len*count);
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim=[];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1);
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
if(next_char=='[')
dim=parse_array(varargin{:});
count=prod(double(dim));
else
count=double(parse_number());
end
end
if(~isempty(type))
if(count>=0)
[object adv]=parse_block(type,count,varargin{:});
if(~isempty(dim))
object=reshape(object,dim);
end
pos=pos+adv;
return;
else
endpos=matching_bracket(inStr,pos);
[cid,len]=elem_info(type);
count=(endpos-pos)/len;
[object adv]=parse_block(type,count,varargin{:});
pos=pos+adv;
parse_char(']');
return;
end
end
if next_char ~= ']'
while 1
val = parse_value(varargin{:});
object{end+1} = val;
if next_char == ']'
break;
end
%parse_char(',');
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
if(count==-1)
parse_char(']');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr esc index_esc len_esc
% len, ns = length(inStr), keyboard
type=inStr(pos);
if type ~= 'S' && type ~= 'C' && type ~= 'H'
error_pos('String starting with S expected at position %d');
else
pos = pos + 1;
end
if(type == 'C')
str=inStr(pos);
pos=pos+1;
return;
end
bytelen=double(parse_number());
if(length(inStr)>=pos+bytelen-1)
str=inStr(pos:pos+bytelen-1);
pos=pos+bytelen;
else
error_pos('End of file while expecting end of inStr');
end
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct fileendian systemendian
id=strfind('iUIlLdD',inStr(pos));
if(isempty(id))
error_pos('expecting a number at position %d');
end
type={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
datastr=inStr(pos+1:pos+bytelen(id));
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,type{id}));
end
num=typecast(newdata,type{id});
pos = pos + bytelen(id)+1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
switch(inStr(pos))
case {'S','C','H'}
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'i','U','I','l','L','d','D'}
val = parse_number(varargin{:});
return;
case 'T'
val = true;
pos = pos + 1;
return;
case 'F'
val = false;
pos = pos + 1;
return;
case {'Z','N'}
val = [];
pos = pos + 1;
return;
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos e1l e1r maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
saveubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/1 Linear Regression with Multiple Variables/ex1/lib/jsonlab/saveubjson.m
| 16,123 |
utf_8
|
61d4f51010aedbf97753396f5d2d9ec0
|
function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/17
%
% $Id: saveubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array)
% filename: a string for the file name to save the output UBJSON data
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [1|0]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSON='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a binary string in the UBJSON format (see http://ubjson.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% saveubjson('jsonmesh',jsonmesh)
% saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
json=obj2ubjson(rootname,obj,rootlevel,opt);
if(~rootisarray)
json=['{' json '}'];
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=[jsonp '(' json ')'];
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2ubjson(name,item,level,varargin)
if(iscell(item))
txt=cell2ubjson(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2ubjson(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2ubjson(name,item,level,varargin{:});
else
txt=mat2ubjson(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2ubjson(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item); % let's handle 1D cell first
if(len>1)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) '[']; name='';
else
txt='[';
end
elseif(len==0)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) 'Z']; name='';
else
txt='Z';
end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
txt=[txt obj2ubjson(name,item{i,j},level+(len>1),varargin{:})];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=struct2ubjson(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=[txt S_(checkname(name,varargin{:})) '{'];
else
txt=[txt '{'];
end
if(~isempty(names))
for e=1:length(names)
txt=[txt obj2ubjson(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:})];
end
end
txt=[txt '}'];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=str2ubjson(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
val=item(e,:);
if(len==1)
obj=['' S_(checkname(name,varargin{:})) '' '',S_(val),''];
if(isempty(name)) obj=['',S_(val),'']; end
txt=[txt,'',obj];
else
txt=[txt,'',['',S_(val),'']];
end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=mat2ubjson(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) || jsonopt('ArrayToStruct',0,varargin{:}))
cid=I_(uint32(max(size(item))));
if(isempty(name))
txt=['{' S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1)) ];
else
if(isempty(item))
txt=[S_(checkname(name,varargin{:})),'Z'];
return;
else
txt=[S_(checkname(name,varargin{:})),'{',S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1))];
end
end
else
if(isempty(name))
txt=matdata2ubjson(item,level+1,varargin{:});
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
numtxt=regexprep(regexprep(matdata2ubjson(item,level+1,varargin{:}),'^\[',''),']','');
txt=[S_(checkname(name,varargin{:})) numtxt];
else
txt=[S_(checkname(name,varargin{:})),matdata2ubjson(item,level+1,varargin{:})];
end
end
return;
end
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=[txt,S_('_ArrayIsComplex_'),'T'];
end
txt=[txt,S_('_ArrayIsSparse_'),'T'];
if(size(item,1)==1)
% Row vector, store only column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([iy(:),data'],level+2,varargin{:})];
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,data],level+2,varargin{:})];
else
% General case, store row and column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,iy,data],level+2,varargin{:})];
end
else
if(isreal(item))
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson(item(:)',level+2,varargin{:})];
else
txt=[txt,S_('_ArrayIsComplex_'),'T'];
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([real(item(:)) imag(item(:))],level+2,varargin{:})];
end
end
txt=[txt,'}'];
%%-------------------------------------------------------------------------
function txt=matdata2ubjson(mat,level,varargin)
if(isempty(mat))
txt='Z';
return;
end
if(size(mat,1)==1)
level=level-1;
end
type='';
hasnegtive=(mat<0);
if(isa(mat,'integer') || isinteger(mat) || (isfloat(mat) && all(mod(mat(:),1) == 0)))
if(isempty(hasnegtive))
if(max(mat(:))<=2^8)
type='U';
end
end
if(isempty(type))
% todo - need to consider negative ones separately
id= histc(abs(max(mat(:))),[0 2^7 2^15 2^31 2^63]);
if(isempty(find(id)))
error('high-precision data is not yet supported');
end
key='iIlL';
type=key(find(id));
end
txt=[I_a(mat(:),type,size(mat))];
elseif(islogical(mat))
logicalval='FT';
if(numel(mat)==1)
txt=logicalval(mat+1);
else
txt=['[$U#' I_a(size(mat),'l') typecast(swapbytes(uint8(mat(:)')),'uint8')];
end
else
if(numel(mat)==1)
txt=['[' D_(mat) ']'];
else
txt=D_a(mat(:),'D',size(mat));
end
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function val=S_(str)
if(length(str)==1)
val=['C' str];
else
val=['S' I_(int32(length(str))) str];
end
%%-------------------------------------------------------------------------
function val=I_(num)
if(~isinteger(num))
error('input is not an integer');
end
if(num>=0 && num<255)
val=['U' data2byte(swapbytes(cast(num,'uint8')),'uint8')];
return;
end
key='iIlL';
cid={'int8','int16','int32','int64'};
for i=1:4
if((num>0 && num<2^(i*8-1)) || (num<0 && num>=-2^(i*8-1)))
val=[key(i) data2byte(swapbytes(cast(num,cid{i})),'uint8')];
return;
end
end
error('unsupported integer');
%%-------------------------------------------------------------------------
function val=D_(num)
if(~isfloat(num))
error('input is not a float');
end
if(isa(num,'single'))
val=['d' data2byte(num,'uint8')];
else
val=['D' data2byte(num,'uint8')];
end
%%-------------------------------------------------------------------------
function data=I_a(num,type,dim,format)
id=find(ismember('iUIlL',type));
if(id==0)
error('unsupported integer array');
end
% based on UBJSON specs, all integer types are stored in big endian format
if(id==1)
data=data2byte(swapbytes(int8(num)),'uint8');
blen=1;
elseif(id==2)
data=data2byte(swapbytes(uint8(num)),'uint8');
blen=1;
elseif(id==3)
data=data2byte(swapbytes(int16(num)),'uint8');
blen=2;
elseif(id==4)
data=data2byte(swapbytes(int32(num)),'uint8');
blen=4;
elseif(id==5)
data=data2byte(swapbytes(int64(num)),'uint8');
blen=8;
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/blen)) data(:)'];
end
data=['[' data(:)'];
else
data=reshape(data,blen,numel(data)/blen);
data(2:blen+1,:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function data=D_a(num,type,dim,format)
id=find(ismember('dD',type));
if(id==0)
error('unsupported float array');
end
if(id==1)
data=data2byte(single(num),'uint8');
elseif(id==2)
data=data2byte(double(num),'uint8');
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/(id*4))) data(:)'];
end
data=['[' data];
else
data=reshape(data,(id*4),length(data)/(id*4));
data(2:(id*4+1),:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function bytes=data2byte(varargin)
bytes=typecast(varargin{:});
bytes=bytes(:)';
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submit.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/7 K-means clustering and PCA/ex7/submit.m
| 1,438 |
utf_8
|
665ea5906aad3ccfd94e33a40c58e2ce
|
function submit()
addpath('./lib');
conf.assignmentSlug = 'k-means-clustering-and-pca';
conf.itemName = 'K-Means Clustering and PCA';
conf.partArrays = { ...
{ ...
'1', ...
{ 'findClosestCentroids.m' }, ...
'Find Closest Centroids (k-Means)', ...
}, ...
{ ...
'2', ...
{ 'computeCentroids.m' }, ...
'Compute Centroid Means (k-Means)', ...
}, ...
{ ...
'3', ...
{ 'pca.m' }, ...
'PCA', ...
}, ...
{ ...
'4', ...
{ 'projectData.m' }, ...
'Project Data (PCA)', ...
}, ...
{ ...
'5', ...
{ 'recoverData.m' }, ...
'Recover Data (PCA)', ...
}, ...
};
conf.output = @output;
submitWithConfiguration(conf);
end
function out = output(partId, auxstring)
% Random Test Cases
X = reshape(sin(1:165), 15, 11);
Z = reshape(cos(1:121), 11, 11);
C = Z(1:5, :);
idx = (1 + mod(1:15, 3))';
if partId == '1'
idx = findClosestCentroids(X, C);
out = sprintf('%0.5f ', idx(:));
elseif partId == '2'
centroids = computeCentroids(X, idx, 3);
out = sprintf('%0.5f ', centroids(:));
elseif partId == '3'
[U, S] = pca(X);
out = sprintf('%0.5f ', abs([U(:); S(:)]));
elseif partId == '4'
X_proj = projectData(X, Z, 5);
out = sprintf('%0.5f ', X_proj(:));
elseif partId == '5'
X_rec = recoverData(X(:,1:5), Z, 5);
out = sprintf('%0.5f ', X_rec(:));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
submitWithConfiguration.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/7 K-means clustering and PCA/ex7/lib/submitWithConfiguration.m
| 3,926 |
utf_8
|
f889a7cf3dc6c1c2877566d38df1bec8
|
function submitWithConfiguration(conf)
% Note: has the "certificate" patch from Liran for Windows-like systems
addpath('./lib/jsonlab');
%keyboard
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = promptToken('', '', tokenFile);
end
if isempty(token)
fprintf('!! Submission Cancelled\n');
return
end
try
response = submitParts(conf, email, token, parts);
catch
e = lasterror();
fprintf( ...
'!! Submission failed: unexpected error: %s\n', ...
e.message);
fprintf('!! Please try again later.\n');
return
end
if isfield(response, 'errorMessage')
fprintf('!! Submission failed: %s\n', response.errorMessage);
else
showFeedback(parts, response);
save(tokenFile, 'email', 'token');
end
end
function [email token] = promptToken(email, existingToken, tokenFile)
if (~isempty(email) && ~isempty(existingToken))
prompt = sprintf( ...
'Use token from last successful submission (%s)? (Y/n): ', ...
email);
reenter = input(prompt, 's');
if (isempty(reenter) || reenter(1) == 'Y' || reenter(1) == 'y')
token = existingToken;
return;
else
delete(tokenFile);
end
end
email = input('Login (email address): ', 's');
token = input('Token: ', 's');
end
function isValid = isValidPartOptionIndex(partOptions, i)
isValid = (~isempty(i)) && (1 <= i) && (i <= numel(partOptions));
end
function response = submitParts(conf, email, token, parts)
body = makePostBody(conf, email, token, parts);
submissionUrl = submissionUrl();
params = {'jsonBody', body};
%responseBody = urlread(submissionUrl, 'post', params);
[code, responseBody] = system(sprintf('echo jsonBody=%s | curl -k -X POST -d @- %s', body, submissionUrl));
response = loadjson(responseBody);
end
function body = makePostBody(conf, email, token, parts)
bodyStruct.assignmentSlug = conf.assignmentSlug;
bodyStruct.submitterEmail = email;
bodyStruct.secret = token;
bodyStruct.parts = makePartsStruct(conf, parts);
opt.Compact = 1;
body = savejson('', bodyStruct, opt);
end
function partsStruct = makePartsStruct(conf, parts)
for part = parts
partId = part{:}.id;
fieldName = makeValidFieldName(partId);
outputStruct.output = conf.output(partId);
partsStruct.(fieldName) = outputStruct;
end
end
function [parts] = parts(conf)
parts = {};
for partArray = conf.partArrays
part.id = partArray{:}{1};
part.sourceFiles = partArray{:}{2};
part.name = partArray{:}{3};
parts{end + 1} = part;
end
end
function showFeedback(parts, response)
fprintf('== \n');
fprintf('== %43s | %9s | %-s\n', 'Part Name', 'Score', 'Feedback');
fprintf('== %43s | %9s | %-s\n', '---------', '-----', '--------');
for part = parts
score = '';
partFeedback = '';
partFeedback = response.partFeedbacks.(makeValidFieldName(part{:}.id));
partEvaluation = response.partEvaluations.(makeValidFieldName(part{:}.id));
score = sprintf('%d / %3d', partEvaluation.score, partEvaluation.maxScore);
fprintf('== %43s | %9s | %-s\n', part{:}.name, score, partFeedback);
end
evaluation = response.evaluation;
totalScore = sprintf('%d / %d', evaluation.score, evaluation.maxScore);
fprintf('== --------------------------------\n');
fprintf('== %43s | %9s | %-s\n', '', totalScore, '');
fprintf('== \n');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Service configuration
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function submissionUrl = submissionUrl()
submissionUrl = 'https://www-origin.coursera.org/api/onDemandProgrammingImmediateFormSubmissions.v1';
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
savejson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/7 K-means clustering and PCA/ex7/lib/jsonlab/savejson.m
| 17,462 |
utf_8
|
861b534fc35ffe982b53ca3ca83143bf
|
function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09
%
% $Id: savejson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array).
% filename: a string for the file name to save the output JSON data.
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.FloatFormat ['%.10g'|string]: format to show each numeric element
% of a 1D/2D array;
% opt.ArrayIndent [1|0]: if 1, output explicit data array with
% precedent indentation; if 0, no indentation
% opt.ArrayToStruct[0|1]: when set to 0, savejson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [0|1]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, savejson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.Inf ['"$1_Inf_"'|string]: a customized regular expression pattern
% to represent +/-Inf. The matched pattern is '([-+]*)Inf'
% and $1 represents the sign. For those who want to use
% 1e999 to represent Inf, they can set opt.Inf to '$11e999'
% opt.NaN ['"_NaN_"'|string]: a customized regular expression pattern
% to represent NaN
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSONP='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
% opt.SaveBinary [0|1]: 1 - save the JSON file in binary mode; 0 - text mode.
% opt.Compact [0|1]: 1- out compact JSON format (remove all newlines and tabs)
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a string in the JSON format (see http://json.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% savejson('jmesh',jsonmesh)
% savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
whitespaces=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
if(jsonopt('Compact',0,opt)==1)
whitespaces=struct('tab','','newline','','sep',',');
end
if(~isfield(opt,'whitespaces_'))
opt.whitespaces_=whitespaces;
end
nl=whitespaces.newline;
json=obj2json(rootname,obj,rootlevel,opt);
if(rootisarray)
json=sprintf('%s%s',json,nl);
else
json=sprintf('{%s%s%s}\n',nl,json,nl);
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=sprintf('%s(%s);%s',jsonp,json,nl);
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
if(jsonopt('SaveBinary',0,opt)==1)
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
else
fid = fopen(opt.FileName, 'wt');
fwrite(fid,json,'char');
end
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2json(name,item,level,varargin)
if(iscell(item))
txt=cell2json(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2json(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2json(name,item,level,varargin{:});
else
txt=mat2json(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2json(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=jsonopt('whitespaces_',struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n')),varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
nl=ws.newline;
if(len>1)
if(~isempty(name))
txt=sprintf('%s"%s": [%s',padding0, checkname(name,varargin{:}),nl); name='';
else
txt=sprintf('%s[%s',padding0,nl);
end
elseif(len==0)
if(~isempty(name))
txt=sprintf('%s"%s": []',padding0, checkname(name,varargin{:})); name='';
else
txt=sprintf('%s[]',padding0);
end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
txt=sprintf('%s%s',txt,obj2json(name,item{i,j},level+(dim(1)>1)+1,varargin{:}));
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
%if(j==dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=struct2json(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding0=repmat(ws.tab,1,level);
padding2=repmat(ws.tab,1,level+1);
padding1=repmat(ws.tab,1,level+(dim(1)>1)+(len>1));
nl=ws.newline;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding0,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding0,nl); end
end
for j=1:dim(2)
if(dim(1)>1) txt=sprintf('%s%s[%s',txt,padding2,nl); end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=sprintf('%s%s"%s": {%s',txt,padding1, checkname(name,varargin{:}),nl);
else
txt=sprintf('%s%s{%s',txt,padding1,nl);
end
if(~isempty(names))
for e=1:length(names)
txt=sprintf('%s%s',txt,obj2json(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:}));
if(e<length(names)) txt=sprintf('%s%s',txt,','); end
txt=sprintf('%s%s',txt,nl);
end
end
txt=sprintf('%s%s}',txt,padding1);
if(i<dim(1)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(dim(1)>1) txt=sprintf('%s%s%s]',txt,nl,padding2); end
if(j<dim(2)) txt=sprintf('%s%s',txt,sprintf(',%s',nl)); end
end
if(len>1) txt=sprintf('%s%s%s]',txt,nl,padding0); end
%%-------------------------------------------------------------------------
function txt=str2json(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(~isempty(name))
if(len>1) txt=sprintf('%s"%s": [%s',padding1,checkname(name,varargin{:}),nl); end
else
if(len>1) txt=sprintf('%s[%s',padding1,nl); end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
if(isoct)
val=regexprep(item(e,:),'\\','\\');
val=regexprep(val,'"','\"');
val=regexprep(val,'^"','\"');
else
val=regexprep(item(e,:),'\\','\\\\');
val=regexprep(val,'"','\\"');
val=regexprep(val,'^"','\\"');
end
val=escapejsonstring(val);
if(len==1)
obj=['"' checkname(name,varargin{:}) '": ' '"',val,'"'];
if(isempty(name)) obj=['"',val,'"']; end
txt=sprintf('%s%s%s%s',txt,padding1,obj);
else
txt=sprintf('%s%s%s%s',txt,padding0,['"',val,'"']);
end
if(e==len) sep=''; end
txt=sprintf('%s%s',txt,sep);
end
if(len>1) txt=sprintf('%s%s%s%s',txt,nl,padding1,']'); end
%%-------------------------------------------------------------------------
function txt=mat2json(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
padding1=repmat(ws.tab,1,level);
padding0=repmat(ws.tab,1,level+1);
nl=ws.newline;
sep=ws.sep;
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) ||jsonopt('ArrayToStruct',0,varargin{:}))
if(isempty(name))
txt=sprintf('%s{%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
else
txt=sprintf('%s"%s": {%s%s"_ArrayType_": "%s",%s%s"_ArraySize_": %s,%s',...
padding1,checkname(name,varargin{:}),nl,padding0,class(item),nl,padding0,regexprep(mat2str(size(item)),'\s+',','),nl);
end
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1 && level>0)
numtxt=regexprep(regexprep(matdata2json(item,level+1,varargin{:}),'^\[',''),']','');
else
numtxt=matdata2json(item,level+1,varargin{:});
end
if(isempty(name))
txt=sprintf('%s%s',padding1,numtxt);
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
else
txt=sprintf('%s"%s": %s',padding1,checkname(name,varargin{:}),numtxt);
end
end
return;
end
dataformat='%s%s%s%s%s';
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
end
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsSparse_": ','1', sep);
if(size(item,1)==1)
% Row vector, store only column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([iy(:),data'],level+2,varargin{:}), nl);
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,data],level+2,varargin{:}), nl);
else
% General case, store row and column indices.
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([ix,iy,data],level+2,varargin{:}), nl);
end
else
if(isreal(item))
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json(item(:)',level+2,varargin{:}), nl);
else
txt=sprintf(dataformat,txt,padding0,'"_ArrayIsComplex_": ','1', sep);
txt=sprintf(dataformat,txt,padding0,'"_ArrayData_": ',...
matdata2json([real(item(:)) imag(item(:))],level+2,varargin{:}), nl);
end
end
txt=sprintf('%s%s%s',txt,padding1,'}');
%%-------------------------------------------------------------------------
function txt=matdata2json(mat,level,varargin)
ws=struct('tab',sprintf('\t'),'newline',sprintf('\n'),'sep',sprintf(',\n'));
ws=jsonopt('whitespaces_',ws,varargin{:});
tab=ws.tab;
nl=ws.newline;
if(size(mat,1)==1)
pre='';
post='';
level=level-1;
else
pre=sprintf('[%s',nl);
post=sprintf('%s%s]',nl,repmat(tab,1,level-1));
end
if(isempty(mat))
txt='null';
return;
end
floatformat=jsonopt('FloatFormat','%.10g',varargin{:});
%if(numel(mat)>1)
formatstr=['[' repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf('],%s',nl)]];
%else
% formatstr=[repmat([floatformat ','],1,size(mat,2)-1) [floatformat sprintf(',\n')]];
%end
if(nargin>=2 && size(mat,1)>1 && jsonopt('ArrayIndent',1,varargin{:})==1)
formatstr=[repmat(tab,1,level) formatstr];
end
txt=sprintf(formatstr,mat');
txt(end-length(nl):end)=[];
if(islogical(mat) && jsonopt('ParseLogical',0,varargin{:})==1)
txt=regexprep(txt,'1','true');
txt=regexprep(txt,'0','false');
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],\n['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
txt=[pre txt post];
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function newstr=escapejsonstring(str)
newstr=str;
isoct=exist('OCTAVE_VERSION','builtin');
if(isoct)
vv=sscanf(OCTAVE_VERSION,'%f');
if(vv(1)>=3.8) isoct=0; end
end
if(isoct)
escapechars={'\a','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},escapechars{i});
end
else
escapechars={'\a','\b','\f','\n','\r','\t','\v'};
for i=1:length(escapechars);
newstr=regexprep(newstr,escapechars{i},regexprep(escapechars{i},'\\','\\\\'));
end
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/7 K-means clustering and PCA/ex7/lib/jsonlab/loadjson.m
| 18,884 |
ibm852
|
d21f0844f91f2dbb9ea8df00eda346ca
|
function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% Nedialko Krouchev: http://www.mathworks.com/matlabcentral/fileexchange/25713
% created on 2009/11/02
% François Glineur: http://www.mathworks.com/matlabcentral/fileexchange/23393
% created on 2009/03/22
% Joel Feenstra:
% http://www.mathworks.com/matlabcentral/fileexchange/20565
% created on 2008/07/03
%
% $Id: loadjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a JSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.FastArrayParser [1|0 or integer]: if set to 1, use a
% speed-optimized array parser when loading an
% array object. The fast array parser may
% collapse block arrays into a single large
% array similar to rules defined in cell2mat; 0 to
% use a legacy parser; if set to a larger-than-1
% value, this option will specify the minimum
% dimension to enable the fast array parser. For
% example, if the input is a 3D array, setting
% FastArrayParser to 1 will return a 3D array;
% setting to 2 will return a cell array of 2D
% arrays; setting to 3 will return to a 2D cell
% array of 1D vectors; setting to 4 will return a
% 3D cell array.
% opt.ShowProgress [0|1]: if set to 1, loadjson displays a progress bar.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
% dat=loadjson(['examples' filesep 'example1.json'])
% dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
if(jsonopt('ShowProgress',0,opt)==1)
opt.progressbar_=waitbar(0,'loading ...');
end
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
if(isfield(opt,'progressbar_'))
close(opt.progressbar_);
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=data(j).x0x5F_ArraySize_;
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
if next_char ~= '}'
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
parse_char(':');
val = parse_value(varargin{:});
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}'
break;
end
parse_char(',');
end
end
parse_char('}');
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim2=[];
arraydepth=jsonopt('JSONLAB_ArrayDepth_',1,varargin{:});
pbar=jsonopt('progressbar_',-1,varargin{:});
if next_char ~= ']'
if(jsonopt('FastArrayParser',1,varargin{:})>=1 && arraydepth>=jsonopt('FastArrayParser',1,varargin{:}))
[endpos, e1l, e1r, maxlevel]=matching_bracket(inStr,pos);
arraystr=['[' inStr(pos:endpos)];
arraystr=regexprep(arraystr,'"_NaN_"','NaN');
arraystr=regexprep(arraystr,'"([-+]*)_Inf_"','$1Inf');
arraystr(arraystr==sprintf('\n'))=[];
arraystr(arraystr==sprintf('\r'))=[];
%arraystr=regexprep(arraystr,'\s*,',','); % this is slow,sometimes needed
if(~isempty(e1l) && ~isempty(e1r)) % the array is in 2D or higher D
astr=inStr((e1l+1):(e1r-1));
astr=regexprep(astr,'"_NaN_"','NaN');
astr=regexprep(astr,'"([-+]*)_Inf_"','$1Inf');
astr(astr==sprintf('\n'))=[];
astr(astr==sprintf('\r'))=[];
astr(astr==' ')='';
if(isempty(find(astr=='[', 1))) % array is 2D
dim2=length(sscanf(astr,'%f,',[1 inf]));
end
else % array is 1D
astr=arraystr(2:end-1);
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',[1,inf]);
if(nextidx>=length(astr)-1)
object=obj;
pos=endpos;
parse_char(']');
return;
end
end
if(~isempty(dim2))
astr=arraystr;
astr(astr=='[')='';
astr(astr==']')='';
astr(astr==' ')='';
[obj, count, errmsg, nextidx]=sscanf(astr,'%f,',inf);
if(nextidx>=length(astr)-1)
object=reshape(obj,dim2,numel(obj)/dim2)';
pos=endpos;
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
return;
end
end
arraystr=regexprep(arraystr,'\]\s*,','];');
else
arraystr='[';
end
try
if(isoct && regexp(arraystr,'"','once'))
error('Octave eval can produce empty cells for JSON-like input');
end
object=eval(arraystr);
pos=endpos;
catch
while 1
newopt=varargin2struct(varargin{:},'JSONLAB_ArrayDepth_',arraydepth+1);
val = parse_value(newopt);
object{end+1} = val;
if next_char == ']'
break;
end
parse_char(',');
end
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
parse_char(']');
if(pbar>0)
waitbar(pos/length(inStr),pbar,'loading ...');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr len esc index_esc len_esc
% len, ns = length(inStr), keyboard
if inStr(pos) ~= '"'
error_pos('String starting with " expected at position %d');
else
pos = pos + 1;
end
str = '';
while pos <= len
while index_esc <= len_esc && esc(index_esc) < pos
index_esc = index_esc + 1;
end
if index_esc > len_esc
str = [str inStr(pos:len)];
pos = len + 1;
break;
else
str = [str inStr(pos:esc(index_esc)-1)];
pos = esc(index_esc);
end
nstr = length(str); switch inStr(pos)
case '"'
pos = pos + 1;
if(~isempty(str))
if(strcmp(str,'_Inf_'))
str=Inf;
elseif(strcmp(str,'-_Inf_'))
str=-Inf;
elseif(strcmp(str,'_NaN_'))
str=NaN;
end
end
return;
case '\'
if pos+1 > len
error_pos('End of file reached right after escape character');
end
pos = pos + 1;
switch inStr(pos)
case {'"' '\' '/'}
str(nstr+1) = inStr(pos);
pos = pos + 1;
case {'b' 'f' 'n' 'r' 't'}
str(nstr+1) = sprintf(['\' inStr(pos)]);
pos = pos + 1;
case 'u'
if pos+4 > len
error_pos('End of file reached in escaped unicode character');
end
str(nstr+(1:6)) = inStr(pos-1:pos+4);
pos = pos + 5;
end
otherwise % should never happen
str(nstr+1) = inStr(pos), keyboard
pos = pos + 1;
end
end
error_pos('End of file while expecting end of inStr');
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct
currstr=inStr(pos:end);
numstr=0;
if(isoct~=0)
numstr=regexp(currstr,'^\s*-?(?:0|[1-9]\d*)(?:\.\d+)?(?:[eE][+\-]?\d+)?','end');
[num, one] = sscanf(currstr, '%f', 1);
delta=numstr+1;
else
[num, one, err, delta] = sscanf(currstr, '%f', 1);
if ~isempty(err)
error_pos('Error reading number at position %d');
end
end
pos = pos + delta-1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
pbar=jsonopt('progressbar_',-1,varargin{:});
if(pbar>0)
waitbar(pos/len,pbar,'loading ...');
end
switch(inStr(pos))
case '"'
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'-','0','1','2','3','4','5','6','7','8','9'}
val = parse_number(varargin{:});
return;
case 't'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'true')
val = true;
pos = pos + 4;
return;
end
case 'f'
if pos+4 <= len && strcmpi(inStr(pos:pos+4), 'false')
val = false;
pos = pos + 5;
return;
end
case 'n'
if pos+3 <= len && strcmpi(inStr(pos:pos+3), 'null')
val = [];
pos = pos + 4;
return;
end
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
% Hard to believe but sprintf("%X") is broken in Octave 4.0.0
% str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
str=sprintf('x0x%s_%s',xxNumToHexStr(char(str(1))),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos, e1l, e1r, maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
loadubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/7 K-means clustering and PCA/ex7/lib/jsonlab/loadubjson.m
| 15,574 |
utf_8
|
5974e78e71b81b1e0f76123784b951a4
|
function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% fname: input file name, if fname contains "{}" or "[]", fname
% will be interpreted as a UBJSON string
% opt: a struct to store parsing options, opt can be replaced by
% a list of ('param',value) pairs - the param string is equivallent
% to a field in opt. opt can have the following
% fields (first in [.|.] is the default)
%
% opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
% for each element of the JSON data, and group
% arrays based on the cell2mat rules.
% opt.IntEndian [B|L]: specify the endianness of the integer fields
% in the UBJSON input data. B - Big-Endian format for
% integers (as required in the UBJSON specification);
% L - input integer fields are in Little-Endian order.
%
% output:
% dat: a cell array, where {...} blocks are converted into cell arrays,
% and [...] are converted to arrays
%
% examples:
% obj=struct('string','value','array',[1 2 3]);
% ubjdata=saveubjson('obj',obj);
% dat=loadubjson(ubjdata)
% dat=loadubjson(['examples' filesep 'example1.ubj'])
% dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
global pos inStr len esc index_esc len_esc isoct arraytoken fileendian systemendian
if(regexp(fname,'[\{\}\]\[]','once'))
string=fname;
elseif(exist(fname,'file'))
fid = fopen(fname,'rb');
string = fread(fid,inf,'uint8=>char')';
fclose(fid);
else
error('input file does not exist');
end
pos = 1; len = length(string); inStr = string;
isoct=exist('OCTAVE_VERSION','builtin');
arraytoken=find(inStr=='[' | inStr==']' | inStr=='"');
jstr=regexprep(inStr,'\\\\',' ');
escquote=regexp(jstr,'\\"');
arraytoken=sort([arraytoken escquote]);
% String delimiters and escape chars identified to improve speed:
esc = find(inStr=='"' | inStr=='\' ); % comparable to: regexp(inStr, '["\\]');
index_esc = 1; len_esc = length(esc);
opt=varargin2struct(varargin{:});
fileendian=upper(jsonopt('IntEndian','B',opt));
[os,maxelem,systemendian]=computer;
jsoncount=1;
while pos <= len
switch(next_char)
case '{'
data{jsoncount} = parse_object(opt);
case '['
data{jsoncount} = parse_array(opt);
otherwise
error_pos('Outer level structure must be an object or an array');
end
jsoncount=jsoncount+1;
end % while
jsoncount=length(data);
if(jsoncount==1 && iscell(data))
data=data{1};
end
if(~isempty(data))
if(isstruct(data)) % data can be a struct array
data=jstruct2array(data);
elseif(iscell(data))
data=jcell2array(data);
end
end
%%
function newdata=parse_collection(id,data,obj)
if(jsoncount>0 && exist('data','var'))
if(~iscell(data))
newdata=cell(1);
newdata{1}=data;
data=newdata;
end
end
%%
function newdata=jcell2array(data)
len=length(data);
newdata=data;
for i=1:len
if(isstruct(data{i}))
newdata{i}=jstruct2array(data{i});
elseif(iscell(data{i}))
newdata{i}=jcell2array(data{i});
end
end
%%-------------------------------------------------------------------------
function newdata=jstruct2array(data)
fn=fieldnames(data);
newdata=data;
len=length(data);
for i=1:length(fn) % depth-first
for j=1:len
if(isstruct(getfield(data(j),fn{i})))
newdata(j)=setfield(newdata(j),fn{i},jstruct2array(getfield(data(j),fn{i})));
end
end
end
if(~isempty(strmatch('x0x5F_ArrayType_',fn)) && ~isempty(strmatch('x0x5F_ArrayData_',fn)))
newdata=cell(len,1);
for j=1:len
ndata=cast(data(j).x0x5F_ArrayData_,data(j).x0x5F_ArrayType_);
iscpx=0;
if(~isempty(strmatch('x0x5F_ArrayIsComplex_',fn)))
if(data(j).x0x5F_ArrayIsComplex_)
iscpx=1;
end
end
if(~isempty(strmatch('x0x5F_ArrayIsSparse_',fn)))
if(data(j).x0x5F_ArrayIsSparse_)
if(~isempty(strmatch('x0x5F_ArraySize_',fn)))
dim=double(data(j).x0x5F_ArraySize_);
if(iscpx && size(ndata,2)==4-any(dim==1))
ndata(:,end-1)=complex(ndata(:,end-1),ndata(:,end));
end
if isempty(ndata)
% All-zeros sparse
ndata=sparse(dim(1),prod(dim(2:end)));
elseif dim(1)==1
% Sparse row vector
ndata=sparse(1,ndata(:,1),ndata(:,2),dim(1),prod(dim(2:end)));
elseif dim(2)==1
% Sparse column vector
ndata=sparse(ndata(:,1),1,ndata(:,2),dim(1),prod(dim(2:end)));
else
% Generic sparse array.
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3),dim(1),prod(dim(2:end)));
end
else
if(iscpx && size(ndata,2)==4)
ndata(:,3)=complex(ndata(:,3),ndata(:,4));
end
ndata=sparse(ndata(:,1),ndata(:,2),ndata(:,3));
end
end
elseif(~isempty(strmatch('x0x5F_ArraySize_',fn)))
if(iscpx && size(ndata,2)==2)
ndata=complex(ndata(:,1),ndata(:,2));
end
ndata=reshape(ndata(:),data(j).x0x5F_ArraySize_);
end
newdata{j}=ndata;
end
if(len==1)
newdata=newdata{1};
end
end
%%-------------------------------------------------------------------------
function object = parse_object(varargin)
parse_char('{');
object = [];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1); % TODO
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
count=double(parse_number());
end
if next_char ~= '}'
num=0;
while 1
str = parseStr(varargin{:});
if isempty(str)
error_pos('Name of value at position %d cannot be empty');
end
%parse_char(':');
val = parse_value(varargin{:});
num=num+1;
eval( sprintf( 'object.%s = val;', valid_field(str) ) );
if next_char == '}' || (count>=0 && num>=count)
break;
end
%parse_char(',');
end
end
if(count==-1)
parse_char('}');
end
%%-------------------------------------------------------------------------
function [cid,len]=elem_info(type)
id=strfind('iUIlLdD',type);
dataclass={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
if(id>0)
cid=dataclass{id};
len=bytelen(id);
else
error_pos('unsupported type at position %d');
end
%%-------------------------------------------------------------------------
function [data adv]=parse_block(type,count,varargin)
global pos inStr isoct fileendian systemendian
[cid,len]=elem_info(type);
datastr=inStr(pos:pos+len*count-1);
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
id=strfind('iUIlLdD',type);
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,cid));
end
data=typecast(newdata,cid);
adv=double(len*count);
%%-------------------------------------------------------------------------
function object = parse_array(varargin) % JSON array is written in row-major order
global pos inStr isoct
parse_char('[');
object = cell(0, 1);
dim=[];
type='';
count=-1;
if(next_char == '$')
type=inStr(pos+1);
pos=pos+2;
end
if(next_char == '#')
pos=pos+1;
if(next_char=='[')
dim=parse_array(varargin{:});
count=prod(double(dim));
else
count=double(parse_number());
end
end
if(~isempty(type))
if(count>=0)
[object adv]=parse_block(type,count,varargin{:});
if(~isempty(dim))
object=reshape(object,dim);
end
pos=pos+adv;
return;
else
endpos=matching_bracket(inStr,pos);
[cid,len]=elem_info(type);
count=(endpos-pos)/len;
[object adv]=parse_block(type,count,varargin{:});
pos=pos+adv;
parse_char(']');
return;
end
end
if next_char ~= ']'
while 1
val = parse_value(varargin{:});
object{end+1} = val;
if next_char == ']'
break;
end
%parse_char(',');
end
end
if(jsonopt('SimplifyCell',0,varargin{:})==1)
try
oldobj=object;
object=cell2mat(object')';
if(iscell(oldobj) && isstruct(object) && numel(object)>1 && jsonopt('SimplifyCellArray',1,varargin{:})==0)
object=oldobj;
elseif(size(object,1)>1 && ndims(object)==2)
object=object';
end
catch
end
end
if(count==-1)
parse_char(']');
end
%%-------------------------------------------------------------------------
function parse_char(c)
global pos inStr len
skip_whitespace;
if pos > len || inStr(pos) ~= c
error_pos(sprintf('Expected %c at position %%d', c));
else
pos = pos + 1;
skip_whitespace;
end
%%-------------------------------------------------------------------------
function c = next_char
global pos inStr len
skip_whitespace;
if pos > len
c = [];
else
c = inStr(pos);
end
%%-------------------------------------------------------------------------
function skip_whitespace
global pos inStr len
while pos <= len && isspace(inStr(pos))
pos = pos + 1;
end
%%-------------------------------------------------------------------------
function str = parseStr(varargin)
global pos inStr esc index_esc len_esc
% len, ns = length(inStr), keyboard
type=inStr(pos);
if type ~= 'S' && type ~= 'C' && type ~= 'H'
error_pos('String starting with S expected at position %d');
else
pos = pos + 1;
end
if(type == 'C')
str=inStr(pos);
pos=pos+1;
return;
end
bytelen=double(parse_number());
if(length(inStr)>=pos+bytelen-1)
str=inStr(pos:pos+bytelen-1);
pos=pos+bytelen;
else
error_pos('End of file while expecting end of inStr');
end
%%-------------------------------------------------------------------------
function num = parse_number(varargin)
global pos inStr len isoct fileendian systemendian
id=strfind('iUIlLdD',inStr(pos));
if(isempty(id))
error_pos('expecting a number at position %d');
end
type={'int8','uint8','int16','int32','int64','single','double'};
bytelen=[1,1,2,4,8,4,8];
datastr=inStr(pos+1:pos+bytelen(id));
if(isoct)
newdata=int8(datastr);
else
newdata=uint8(datastr);
end
if(id<=5 && fileendian~=systemendian)
newdata=swapbytes(typecast(newdata,type{id}));
end
num=typecast(newdata,type{id});
pos = pos + bytelen(id)+1;
%%-------------------------------------------------------------------------
function val = parse_value(varargin)
global pos inStr len
true = 1; false = 0;
switch(inStr(pos))
case {'S','C','H'}
val = parseStr(varargin{:});
return;
case '['
val = parse_array(varargin{:});
return;
case '{'
val = parse_object(varargin{:});
if isstruct(val)
if(~isempty(strmatch('x0x5F_ArrayType_',fieldnames(val), 'exact')))
val=jstruct2array(val);
end
elseif isempty(val)
val = struct;
end
return;
case {'i','U','I','l','L','d','D'}
val = parse_number(varargin{:});
return;
case 'T'
val = true;
pos = pos + 1;
return;
case 'F'
val = false;
pos = pos + 1;
return;
case {'Z','N'}
val = [];
pos = pos + 1;
return;
end
error_pos('Value expected at position %d');
%%-------------------------------------------------------------------------
function error_pos(msg)
global pos inStr len
poShow = max(min([pos-15 pos-1 pos pos+20],len),1);
if poShow(3) == poShow(2)
poShow(3:4) = poShow(2)+[0 -1]; % display nothing after
end
msg = [sprintf(msg, pos) ': ' ...
inStr(poShow(1):poShow(2)) '<error>' inStr(poShow(3):poShow(4)) ];
error( ['JSONparser:invalidFormat: ' msg] );
%%-------------------------------------------------------------------------
function str = valid_field(str)
global isoct
% From MATLAB doc: field names must begin with a letter, which may be
% followed by any combination of letters, digits, and underscores.
% Invalid characters will be converted to underscores, and the prefix
% "x0x[Hex code]_" will be added if the first character is not a letter.
pos=regexp(str,'^[^A-Za-z]','once');
if(~isempty(pos))
if(~isoct)
str=regexprep(str,'^([^A-Za-z])','x0x${sprintf(''%X'',unicode2native($1))}_','once');
else
str=sprintf('x0x%X_%s',char(str(1)),str(2:end));
end
end
if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end
if(~isoct)
str=regexprep(str,'([^0-9A-Za-z_])','_0x${sprintf(''%X'',unicode2native($1))}_');
else
pos=regexp(str,'[^0-9A-Za-z_]');
if(isempty(pos)) return; end
str0=str;
pos0=[0 pos(:)' length(str)];
str='';
for i=1:length(pos)
str=[str str0(pos0(i)+1:pos(i)-1) sprintf('_0x%X_',str0(pos(i)))];
end
if(pos(end)~=length(str))
str=[str str0(pos0(end-1)+1:pos0(end))];
end
end
%str(~isletter(str) & ~('0' <= str & str <= '9')) = '_';
%%-------------------------------------------------------------------------
function endpos = matching_quote(str,pos)
len=length(str);
while(pos<len)
if(str(pos)=='"')
if(~(pos>1 && str(pos-1)=='\'))
endpos=pos;
return;
end
end
pos=pos+1;
end
error('unmatched quotation mark');
%%-------------------------------------------------------------------------
function [endpos e1l e1r maxlevel] = matching_bracket(str,pos)
global arraytoken
level=1;
maxlevel=level;
endpos=0;
bpos=arraytoken(arraytoken>=pos);
tokens=str(bpos);
len=length(tokens);
pos=1;
e1l=[];
e1r=[];
while(pos<=len)
c=tokens(pos);
if(c==']')
level=level-1;
if(isempty(e1r)) e1r=bpos(pos); end
if(level==0)
endpos=bpos(pos);
return
end
end
if(c=='[')
if(isempty(e1l)) e1l=bpos(pos); end
level=level+1;
maxlevel=max(maxlevel,level);
end
if(c=='"')
pos=matching_quote(tokens,pos+1);
end
pos=pos+1;
end
if(endpos==0)
error('unmatched "]"');
end
|
github
|
kartik-nighania/Coursera-Machine-Learning-Course-by-Stanford-master
|
saveubjson.m
|
.m
|
Coursera-Machine-Learning-Course-by-Stanford-master/7 K-means clustering and PCA/ex7/lib/jsonlab/saveubjson.m
| 16,123 |
utf_8
|
61d4f51010aedbf97753396f5d2d9ec0
|
function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author: Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/17
%
% $Id: saveubjson.m 460 2015-01-03 00:30:45Z fangq $
%
% input:
% rootname: the name of the root-object, when set to '', the root name
% is ignored, however, when opt.ForceRootName is set to 1 (see below),
% the MATLAB variable name will be used as the root name.
% obj: a MATLAB object (array, cell, cell array, struct, struct array)
% filename: a string for the file name to save the output UBJSON data
% opt: a struct for additional options, ignore to use default values.
% opt can have the following fields (first in [.|.] is the default)
%
% opt.FileName [''|string]: a file name to save the output JSON data
% opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
% array in JSON array format; if sets to 1, an
% array will be shown as a struct with fields
% "_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
% sparse arrays, the non-zero elements will be
% saved to _ArrayData_ field in triplet-format i.e.
% (ix,iy,val) and "_ArrayIsSparse_" will be added
% with a value of 1; for a complex array, the
% _ArrayData_ array will include two columns
% (4 for sparse) to record the real and imaginary
% parts, and also "_ArrayIsComplex_":1 is added.
% opt.ParseLogical [1|0]: if this is set to 1, logical array elem
% will use true/false rather than 1/0.
% opt.NoRowBracket [1|0]: if this is set to 1, arrays with a single
% numerical element will be shown without a square
% bracket, unless it is the root object; if 0, square
% brackets are forced for any numerical arrays.
% opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
% will use the name of the passed obj variable as the
% root object name; if obj is an expression and
% does not have a name, 'root' will be used; if this
% is set to 0 and rootname is empty, the root level
% will be merged down to the lower level.
% opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
% for example, if opt.JSON='foo', the JSON data is
% wrapped inside a function call as 'foo(...);'
% opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
% back to the string form
%
% opt can be replaced by a list of ('param',value) pairs. The param
% string is equivallent to a field in opt and is case sensitive.
% output:
% json: a binary string in the UBJSON format (see http://ubjson.org)
%
% examples:
% jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
% 'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
% 'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
% 2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
% 'MeshCreator','FangQ','MeshTitle','T6 Cube',...
% 'SpecialData',[nan, inf, -inf]);
% saveubjson('jsonmesh',jsonmesh)
% saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
%
% license:
% BSD, see LICENSE_BSD.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
if(nargin==1)
varname=inputname(1);
obj=rootname;
if(isempty(varname))
varname='root';
end
rootname=varname;
else
varname=inputname(2);
end
if(length(varargin)==1 && ischar(varargin{1}))
opt=struct('FileName',varargin{1});
else
opt=varargin2struct(varargin{:});
end
opt.IsOctave=exist('OCTAVE_VERSION','builtin');
rootisarray=0;
rootlevel=1;
forceroot=jsonopt('ForceRootName',0,opt);
if((isnumeric(obj) || islogical(obj) || ischar(obj) || isstruct(obj) || iscell(obj)) && isempty(rootname) && forceroot==0)
rootisarray=1;
rootlevel=0;
else
if(isempty(rootname))
rootname=varname;
end
end
if((isstruct(obj) || iscell(obj))&& isempty(rootname) && forceroot)
rootname='root';
end
json=obj2ubjson(rootname,obj,rootlevel,opt);
if(~rootisarray)
json=['{' json '}'];
end
jsonp=jsonopt('JSONP','',opt);
if(~isempty(jsonp))
json=[jsonp '(' json ')'];
end
% save to a file if FileName is set, suggested by Patrick Rapin
if(~isempty(jsonopt('FileName','',opt)))
fid = fopen(opt.FileName, 'wb');
fwrite(fid,json);
fclose(fid);
end
%%-------------------------------------------------------------------------
function txt=obj2ubjson(name,item,level,varargin)
if(iscell(item))
txt=cell2ubjson(name,item,level,varargin{:});
elseif(isstruct(item))
txt=struct2ubjson(name,item,level,varargin{:});
elseif(ischar(item))
txt=str2ubjson(name,item,level,varargin{:});
else
txt=mat2ubjson(name,item,level,varargin{:});
end
%%-------------------------------------------------------------------------
function txt=cell2ubjson(name,item,level,varargin)
txt='';
if(~iscell(item))
error('input is not a cell');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item); % let's handle 1D cell first
if(len>1)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) '[']; name='';
else
txt='[';
end
elseif(len==0)
if(~isempty(name))
txt=[S_(checkname(name,varargin{:})) 'Z']; name='';
else
txt='Z';
end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
txt=[txt obj2ubjson(name,item{i,j},level+(len>1),varargin{:})];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=struct2ubjson(name,item,level,varargin)
txt='';
if(~isstruct(item))
error('input is not a struct');
end
dim=size(item);
if(ndims(squeeze(item))>2) % for 3D or higher dimensions, flatten to 2D for now
item=reshape(item,dim(1),numel(item)/dim(1));
dim=size(item);
end
len=numel(item);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
for j=1:dim(2)
if(dim(1)>1) txt=[txt '[']; end
for i=1:dim(1)
names = fieldnames(item(i,j));
if(~isempty(name) && len==1)
txt=[txt S_(checkname(name,varargin{:})) '{'];
else
txt=[txt '{'];
end
if(~isempty(names))
for e=1:length(names)
txt=[txt obj2ubjson(names{e},getfield(item(i,j),...
names{e}),level+(dim(1)>1)+1+(len>1),varargin{:})];
end
end
txt=[txt '}'];
end
if(dim(1)>1) txt=[txt ']']; end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=str2ubjson(name,item,level,varargin)
txt='';
if(~ischar(item))
error('input is not a string');
end
item=reshape(item, max(size(item),[1 0]));
len=size(item,1);
if(~isempty(name))
if(len>1) txt=[S_(checkname(name,varargin{:})) '[']; end
else
if(len>1) txt='['; end
end
isoct=jsonopt('IsOctave',0,varargin{:});
for e=1:len
val=item(e,:);
if(len==1)
obj=['' S_(checkname(name,varargin{:})) '' '',S_(val),''];
if(isempty(name)) obj=['',S_(val),'']; end
txt=[txt,'',obj];
else
txt=[txt,'',['',S_(val),'']];
end
end
if(len>1) txt=[txt ']']; end
%%-------------------------------------------------------------------------
function txt=mat2ubjson(name,item,level,varargin)
if(~isnumeric(item) && ~islogical(item))
error('input is not an array');
end
if(length(size(item))>2 || issparse(item) || ~isreal(item) || ...
isempty(item) || jsonopt('ArrayToStruct',0,varargin{:}))
cid=I_(uint32(max(size(item))));
if(isempty(name))
txt=['{' S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1)) ];
else
if(isempty(item))
txt=[S_(checkname(name,varargin{:})),'Z'];
return;
else
txt=[S_(checkname(name,varargin{:})),'{',S_('_ArrayType_'),S_(class(item)),S_('_ArraySize_'),I_a(size(item),cid(1))];
end
end
else
if(isempty(name))
txt=matdata2ubjson(item,level+1,varargin{:});
else
if(numel(item)==1 && jsonopt('NoRowBracket',1,varargin{:})==1)
numtxt=regexprep(regexprep(matdata2ubjson(item,level+1,varargin{:}),'^\[',''),']','');
txt=[S_(checkname(name,varargin{:})) numtxt];
else
txt=[S_(checkname(name,varargin{:})),matdata2ubjson(item,level+1,varargin{:})];
end
end
return;
end
if(issparse(item))
[ix,iy]=find(item);
data=full(item(find(item)));
if(~isreal(item))
data=[real(data(:)),imag(data(:))];
if(size(item,1)==1)
% Kludge to have data's 'transposedness' match item's.
% (Necessary for complex row vector handling below.)
data=data';
end
txt=[txt,S_('_ArrayIsComplex_'),'T'];
end
txt=[txt,S_('_ArrayIsSparse_'),'T'];
if(size(item,1)==1)
% Row vector, store only column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([iy(:),data'],level+2,varargin{:})];
elseif(size(item,2)==1)
% Column vector, store only row indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,data],level+2,varargin{:})];
else
% General case, store row and column indices.
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([ix,iy,data],level+2,varargin{:})];
end
else
if(isreal(item))
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson(item(:)',level+2,varargin{:})];
else
txt=[txt,S_('_ArrayIsComplex_'),'T'];
txt=[txt,S_('_ArrayData_'),...
matdata2ubjson([real(item(:)) imag(item(:))],level+2,varargin{:})];
end
end
txt=[txt,'}'];
%%-------------------------------------------------------------------------
function txt=matdata2ubjson(mat,level,varargin)
if(isempty(mat))
txt='Z';
return;
end
if(size(mat,1)==1)
level=level-1;
end
type='';
hasnegtive=(mat<0);
if(isa(mat,'integer') || isinteger(mat) || (isfloat(mat) && all(mod(mat(:),1) == 0)))
if(isempty(hasnegtive))
if(max(mat(:))<=2^8)
type='U';
end
end
if(isempty(type))
% todo - need to consider negative ones separately
id= histc(abs(max(mat(:))),[0 2^7 2^15 2^31 2^63]);
if(isempty(find(id)))
error('high-precision data is not yet supported');
end
key='iIlL';
type=key(find(id));
end
txt=[I_a(mat(:),type,size(mat))];
elseif(islogical(mat))
logicalval='FT';
if(numel(mat)==1)
txt=logicalval(mat+1);
else
txt=['[$U#' I_a(size(mat),'l') typecast(swapbytes(uint8(mat(:)')),'uint8')];
end
else
if(numel(mat)==1)
txt=['[' D_(mat) ']'];
else
txt=D_a(mat(:),'D',size(mat));
end
end
%txt=regexprep(mat2str(mat),'\s+',',');
%txt=regexprep(txt,';',sprintf('],['));
% if(nargin>=2 && size(mat,1)>1)
% txt=regexprep(txt,'\[',[repmat(sprintf('\t'),1,level) '[']);
% end
if(any(isinf(mat(:))))
txt=regexprep(txt,'([-+]*)Inf',jsonopt('Inf','"$1_Inf_"',varargin{:}));
end
if(any(isnan(mat(:))))
txt=regexprep(txt,'NaN',jsonopt('NaN','"_NaN_"',varargin{:}));
end
%%-------------------------------------------------------------------------
function newname=checkname(name,varargin)
isunpack=jsonopt('UnpackHex',1,varargin{:});
newname=name;
if(isempty(regexp(name,'0x([0-9a-fA-F]+)_','once')))
return
end
if(isunpack)
isoct=jsonopt('IsOctave',0,varargin{:});
if(~isoct)
newname=regexprep(name,'(^x|_){1}0x([0-9a-fA-F]+)_','${native2unicode(hex2dec($2))}');
else
pos=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','start');
pend=regexp(name,'(^x|_){1}0x([0-9a-fA-F]+)_','end');
if(isempty(pos)) return; end
str0=name;
pos0=[0 pend(:)' length(name)];
newname='';
for i=1:length(pos)
newname=[newname str0(pos0(i)+1:pos(i)-1) char(hex2dec(str0(pos(i)+3:pend(i)-1)))];
end
if(pos(end)~=length(name))
newname=[newname str0(pos0(end-1)+1:pos0(end))];
end
end
end
%%-------------------------------------------------------------------------
function val=S_(str)
if(length(str)==1)
val=['C' str];
else
val=['S' I_(int32(length(str))) str];
end
%%-------------------------------------------------------------------------
function val=I_(num)
if(~isinteger(num))
error('input is not an integer');
end
if(num>=0 && num<255)
val=['U' data2byte(swapbytes(cast(num,'uint8')),'uint8')];
return;
end
key='iIlL';
cid={'int8','int16','int32','int64'};
for i=1:4
if((num>0 && num<2^(i*8-1)) || (num<0 && num>=-2^(i*8-1)))
val=[key(i) data2byte(swapbytes(cast(num,cid{i})),'uint8')];
return;
end
end
error('unsupported integer');
%%-------------------------------------------------------------------------
function val=D_(num)
if(~isfloat(num))
error('input is not a float');
end
if(isa(num,'single'))
val=['d' data2byte(num,'uint8')];
else
val=['D' data2byte(num,'uint8')];
end
%%-------------------------------------------------------------------------
function data=I_a(num,type,dim,format)
id=find(ismember('iUIlL',type));
if(id==0)
error('unsupported integer array');
end
% based on UBJSON specs, all integer types are stored in big endian format
if(id==1)
data=data2byte(swapbytes(int8(num)),'uint8');
blen=1;
elseif(id==2)
data=data2byte(swapbytes(uint8(num)),'uint8');
blen=1;
elseif(id==3)
data=data2byte(swapbytes(int16(num)),'uint8');
blen=2;
elseif(id==4)
data=data2byte(swapbytes(int32(num)),'uint8');
blen=4;
elseif(id==5)
data=data2byte(swapbytes(int64(num)),'uint8');
blen=8;
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/blen)) data(:)'];
end
data=['[' data(:)'];
else
data=reshape(data,blen,numel(data)/blen);
data(2:blen+1,:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function data=D_a(num,type,dim,format)
id=find(ismember('dD',type));
if(id==0)
error('unsupported float array');
end
if(id==1)
data=data2byte(single(num),'uint8');
elseif(id==2)
data=data2byte(double(num),'uint8');
end
if(nargin>=3 && length(dim)>=2 && prod(dim)~=dim(2))
format='opt';
end
if((nargin<4 || strcmp(format,'opt')) && numel(num)>1)
if(nargin>=3 && (length(dim)==1 || (length(dim)>=2 && prod(dim)~=dim(2))))
cid=I_(uint32(max(dim)));
data=['$' type '#' I_a(dim,cid(1)) data(:)'];
else
data=['$' type '#' I_(int32(numel(data)/(id*4))) data(:)'];
end
data=['[' data];
else
data=reshape(data,(id*4),length(data)/(id*4));
data(2:(id*4+1),:)=data;
data(1,:)=type;
data=data(:)';
data=['[' data(:)' ']'];
end
%%-------------------------------------------------------------------------
function bytes=data2byte(varargin)
bytes=typecast(varargin{:});
bytes=bytes(:)';
|
github
|
nagadomi/caffe-master
|
classification_demo.m
|
.m
|
caffe-master/matlab/demo/classification_demo.m
| 5,412 |
utf_8
|
8f46deabe6cde287c4759f3bc8b7f819
|
function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% ****************************************************************************
% For detailed documentation and usage on Caffe's Matlab interface, please
% refer to Caffe Interface Tutorial at
% http://caffe.berkeleyvision.org/tutorial/interfaces.html#matlab
% ****************************************************************************
%
% input
% im color image as uint8 HxWx3
% use_gpu 1 to use the GPU, 0 to use the CPU
%
% output
% scores 1000-dimensional ILSVRC score vector
% maxlabel the label of the highest score
%
% You may need to do the following before you start matlab:
% $ export LD_LIBRARY_PATH=/opt/intel/mkl/lib/intel64:/usr/local/cuda-5.5/lib64
% $ export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libstdc++.so.6
% Or the equivalent based on where things are installed on your system
%
% Usage:
% im = imread('../../examples/images/cat.jpg');
% scores = classification_demo(im, 1);
% [score, class] = max(scores);
% Five things to be aware of:
% caffe uses row-major order
% matlab uses column-major order
% caffe uses BGR color channel order
% matlab uses RGB color channel order
% images need to have the data mean subtracted
% Data coming in from matlab needs to be in the order
% [width, height, channels, images]
% where width is the fastest dimension.
% Here is the rough matlab for putting image data into the correct
% format in W x H x C with BGR channels:
% % permute channels from RGB to BGR
% im_data = im(:, :, [3, 2, 1]);
% % flip width and height to make width the fastest dimension
% im_data = permute(im_data, [2, 1, 3]);
% % convert from uint8 to single
% im_data = single(im_data);
% % reshape to a fixed size (e.g., 227x227).
% im_data = imresize(im_data, [IMAGE_DIM IMAGE_DIM], 'bilinear');
% % subtract mean_data (already in W x H x C with BGR channels)
% im_data = im_data - mean_data;
% If you have multiple images, cat them with cat(4, ...)
% Add caffe/matlab to you Matlab search PATH to use matcaffe
if exist('../+caffe', 'dir')
addpath('..');
else
error('Please run this demo from caffe/matlab/demo');
end
% Set caffe mode
if exist('use_gpu', 'var') && use_gpu
caffe.set_mode_gpu();
gpu_id = 0; % we will use the first gpu in this demo
caffe.set_device(gpu_id);
else
caffe.set_mode_cpu();
end
% Initialize the network using BVLC CaffeNet for image classification
% Weights (parameter) file needs to be downloaded from Model Zoo.
model_dir = '../../models/bvlc_reference_caffenet/';
net_model = [model_dir 'deploy.prototxt'];
net_weights = [model_dir 'bvlc_reference_caffenet.caffemodel'];
phase = 'test'; % run with phase test (so that dropout isn't applied)
if ~exist(net_weights, 'file')
error('Please download CaffeNet from Model Zoo before you run this demo');
end
% Initialize a network
net = caffe.Net(net_model, net_weights, phase);
if nargin < 1
% For demo purposes we will use the cat image
fprintf('using caffe/examples/images/cat.jpg as input image\n');
im = imread('../../examples/images/cat.jpg');
end
% prepare oversampled input
% input_data is Height x Width x Channel x Num
tic;
input_data = {prepare_image(im)};
toc;
% do forward pass to get scores
% scores are now Channels x Num, where Channels == 1000
tic;
% The net forward function. It takes in a cell array of N-D arrays
% (where N == 4 here) containing data of input blob(s) and outputs a cell
% array containing data from output blob(s)
scores = net.forward(input_data);
toc;
scores = scores{1};
scores = mean(scores, 2); % take average scores over 10 crops
[~, maxlabel] = max(scores);
% call caffe.reset_all() to reset caffe
caffe.reset_all();
% ------------------------------------------------------------------------
function crops_data = prepare_image(im)
% ------------------------------------------------------------------------
% caffe/matlab/+caffe/imagenet/ilsvrc_2012_mean.mat contains mean_data that
% is already in W x H x C with BGR channels
d = load('../+caffe/imagenet/ilsvrc_2012_mean.mat');
mean_data = d.mean_data;
IMAGE_DIM = 256;
CROPPED_DIM = 227;
% Convert an image returned by Matlab's imread to im_data in caffe's data
% format: W x H x C with BGR channels
im_data = im(:, :, [3, 2, 1]); % permute channels from RGB to BGR
im_data = permute(im_data, [2, 1, 3]); % flip width and height
im_data = single(im_data); % convert from uint8 to single
im_data = imresize(im_data, [IMAGE_DIM IMAGE_DIM], 'bilinear'); % resize im_data
im_data = im_data - mean_data; % subtract mean_data (already in W x H x C, BGR)
% oversample (4 corners, center, and their x-axis flips)
crops_data = zeros(CROPPED_DIM, CROPPED_DIM, 3, 10, 'single');
indices = [0 IMAGE_DIM-CROPPED_DIM] + 1;
n = 1;
for i = indices
for j = indices
crops_data(:, :, :, n) = im_data(i:i+CROPPED_DIM-1, j:j+CROPPED_DIM-1, :);
crops_data(:, :, :, n+5) = crops_data(end:-1:1, :, :, n);
n = n + 1;
end
end
center = floor(indices(2) / 2) + 1;
crops_data(:,:,:,5) = ...
im_data(center:center+CROPPED_DIM-1,center:center+CROPPED_DIM-1,:);
crops_data(:,:,:,10) = crops_data(end:-1:1, :, :, 5);
|
github
|
gylee1103/ELDNet-master
|
classification_demo.m
|
.m
|
ELDNet-master/caffe/matlab/demo/classification_demo.m
| 5,412 |
utf_8
|
8f46deabe6cde287c4759f3bc8b7f819
|
function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% ****************************************************************************
% For detailed documentation and usage on Caffe's Matlab interface, please
% refer to Caffe Interface Tutorial at
% http://caffe.berkeleyvision.org/tutorial/interfaces.html#matlab
% ****************************************************************************
%
% input
% im color image as uint8 HxWx3
% use_gpu 1 to use the GPU, 0 to use the CPU
%
% output
% scores 1000-dimensional ILSVRC score vector
% maxlabel the label of the highest score
%
% You may need to do the following before you start matlab:
% $ export LD_LIBRARY_PATH=/opt/intel/mkl/lib/intel64:/usr/local/cuda-5.5/lib64
% $ export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libstdc++.so.6
% Or the equivalent based on where things are installed on your system
%
% Usage:
% im = imread('../../examples/images/cat.jpg');
% scores = classification_demo(im, 1);
% [score, class] = max(scores);
% Five things to be aware of:
% caffe uses row-major order
% matlab uses column-major order
% caffe uses BGR color channel order
% matlab uses RGB color channel order
% images need to have the data mean subtracted
% Data coming in from matlab needs to be in the order
% [width, height, channels, images]
% where width is the fastest dimension.
% Here is the rough matlab for putting image data into the correct
% format in W x H x C with BGR channels:
% % permute channels from RGB to BGR
% im_data = im(:, :, [3, 2, 1]);
% % flip width and height to make width the fastest dimension
% im_data = permute(im_data, [2, 1, 3]);
% % convert from uint8 to single
% im_data = single(im_data);
% % reshape to a fixed size (e.g., 227x227).
% im_data = imresize(im_data, [IMAGE_DIM IMAGE_DIM], 'bilinear');
% % subtract mean_data (already in W x H x C with BGR channels)
% im_data = im_data - mean_data;
% If you have multiple images, cat them with cat(4, ...)
% Add caffe/matlab to you Matlab search PATH to use matcaffe
if exist('../+caffe', 'dir')
addpath('..');
else
error('Please run this demo from caffe/matlab/demo');
end
% Set caffe mode
if exist('use_gpu', 'var') && use_gpu
caffe.set_mode_gpu();
gpu_id = 0; % we will use the first gpu in this demo
caffe.set_device(gpu_id);
else
caffe.set_mode_cpu();
end
% Initialize the network using BVLC CaffeNet for image classification
% Weights (parameter) file needs to be downloaded from Model Zoo.
model_dir = '../../models/bvlc_reference_caffenet/';
net_model = [model_dir 'deploy.prototxt'];
net_weights = [model_dir 'bvlc_reference_caffenet.caffemodel'];
phase = 'test'; % run with phase test (so that dropout isn't applied)
if ~exist(net_weights, 'file')
error('Please download CaffeNet from Model Zoo before you run this demo');
end
% Initialize a network
net = caffe.Net(net_model, net_weights, phase);
if nargin < 1
% For demo purposes we will use the cat image
fprintf('using caffe/examples/images/cat.jpg as input image\n');
im = imread('../../examples/images/cat.jpg');
end
% prepare oversampled input
% input_data is Height x Width x Channel x Num
tic;
input_data = {prepare_image(im)};
toc;
% do forward pass to get scores
% scores are now Channels x Num, where Channels == 1000
tic;
% The net forward function. It takes in a cell array of N-D arrays
% (where N == 4 here) containing data of input blob(s) and outputs a cell
% array containing data from output blob(s)
scores = net.forward(input_data);
toc;
scores = scores{1};
scores = mean(scores, 2); % take average scores over 10 crops
[~, maxlabel] = max(scores);
% call caffe.reset_all() to reset caffe
caffe.reset_all();
% ------------------------------------------------------------------------
function crops_data = prepare_image(im)
% ------------------------------------------------------------------------
% caffe/matlab/+caffe/imagenet/ilsvrc_2012_mean.mat contains mean_data that
% is already in W x H x C with BGR channels
d = load('../+caffe/imagenet/ilsvrc_2012_mean.mat');
mean_data = d.mean_data;
IMAGE_DIM = 256;
CROPPED_DIM = 227;
% Convert an image returned by Matlab's imread to im_data in caffe's data
% format: W x H x C with BGR channels
im_data = im(:, :, [3, 2, 1]); % permute channels from RGB to BGR
im_data = permute(im_data, [2, 1, 3]); % flip width and height
im_data = single(im_data); % convert from uint8 to single
im_data = imresize(im_data, [IMAGE_DIM IMAGE_DIM], 'bilinear'); % resize im_data
im_data = im_data - mean_data; % subtract mean_data (already in W x H x C, BGR)
% oversample (4 corners, center, and their x-axis flips)
crops_data = zeros(CROPPED_DIM, CROPPED_DIM, 3, 10, 'single');
indices = [0 IMAGE_DIM-CROPPED_DIM] + 1;
n = 1;
for i = indices
for j = indices
crops_data(:, :, :, n) = im_data(i:i+CROPPED_DIM-1, j:j+CROPPED_DIM-1, :);
crops_data(:, :, :, n+5) = crops_data(end:-1:1, :, :, n);
n = n + 1;
end
end
center = floor(indices(2) / 2) + 1;
crops_data(:,:,:,5) = ...
im_data(center:center+CROPPED_DIM-1,center:center+CROPPED_DIM-1,:);
crops_data(:,:,:,10) = crops_data(end:-1:1, :, :, 5);
|
github
|
fasiha/cython-demo-master
|
numpyToMat.m
|
.m
|
cython-demo-master/numpyToMat.m
| 731 |
utf_8
|
00738f0f052d887028420010b8a9316e
|
% Taken from answer by Jim Hokanson
% http://www.mathworks.com/matlabcentral/answers/157347-convert-python-numpy-array-to-double
% if a simple list would be like this:
% means = cellfun( @double, cell(ms))
function data = numpyToMat(x)
data_size = cell2mat(cell(x.shape));
% if empty array
if data_size == 0
data = [];
return
end
data_row = double(py.array.array('d', py.numpy.nditer(x, pyargs('order', 'F')))); % Add order='F' to get data in column-major order (as in Fortran 'F' and Matlab
if length(data_size) > 1
data = reshape(data_row, data_size); % No need for transpose, since we're retrieving the data in column major order
else
data = data_row;
end
|
github
|
golnazghiasi/cofw68-benchmark-master
|
VisualizeLocalizationRes.m
|
.m
|
cofw68-benchmark-master/VisualizeLocalizationRes.m
| 3,332 |
utf_8
|
20529c5f9a701993d9c0971e566211bd
|
function [] = VisualizeLocalizationRes( ...
boxes, pts_name, occ_name, test, testname, figdir, ...
crop_images, show_groundtruth, show_keypoint_num, errors, ...
draw_line_between_gt_det, method_name, max_to_show)
if(~exist('max_to_show', 'var') || max_to_show > length(test))
max_to_show = length(test);
end
fprintf(['Visualizing landmark localization predication of first %d images' ...
' for %s method ...\n'], max_to_show, method_name);
save_res = fullfile(figdir, method_name);
if(~exist(save_res, 'dir'))
mkdir(save_res);
end
for i = 1 : max_to_show
if(isempty(boxes{i}))
im = imread(test(i).im);
clf; imagesc(im); axis off; axis image; hold on;
if isfield(test(i), 'bbox')
bbox = test(i).bbox;
[im, offset] = CropImage(im, bbox, 0);
clf; imagesc(im); axis off; axis image; hold on;
end
continue;
end
pts_gt = test(i).pts;
if isfield(test(i), 'occ') && ~isempty(test(i).occ)
occ_gt = test(i).occ;
else
occ_gt = zeros(1, size(pts_gt, 1));
end
im = imread(test(i).im);
b = boxes{i}(1);
pts_det = getfield(b, pts_name);
occ_det = getfield(b, occ_name);
if crop_images
if isfield(test(i), 'bbox')
bbox = test(i).bbox;
[im, offset] = CropImage(im, bbox, 0.3);
else
bbox = [min(pts_gt(:, 1)), min(pts_gt(:, 2)), ...
max(pts_gt(:, 1)), max(pts_gt(:, 2))];
[im, offset] = CropImage(im, bbox, 0.3);
end
pts_gt(:, 1) = pts_gt(:, 1) - offset(1);
pts_gt(:, 2) = pts_gt(:, 2) - offset(2);
pts_det(:, 1) = pts_det(:, 1) - offset(1);
pts_det(:, 2) = pts_det(:, 2) - offset(2);
end
clf; imagesc(im); axis off; axis image; hold on;
if(size(im, 3) == 1)
colormap(gray);
end
plot(pts_det(occ_det == 0, 1), pts_det(occ_det == 0, 2), '.g', ...
'MarkerSize', 20);
plot(pts_det(occ_det == 1, 1), pts_det(occ_det == 1, 2), '.r', ...
'MarkerSize', 20);
if show_keypoint_num
ShowKeypointNums(pts_det, 'k');
end
if show_groundtruth
plot(pts_gt(occ_gt == 0, 1), pts_gt(occ_gt == 0, 2), '.b', ...
'MarkerSize', 20);
plot(pts_gt(occ_gt == 1, 1), pts_gt(occ_gt == 1, 2), '.m', ...
'MarkerSize', 20);
if show_keypoint_num
ShowKeypointNums(pts_gt, 'm');
end
end
if draw_line_between_gt_det
for k = 1 : size(pts_gt, 1)
plot([pts_gt(k, 1) pts_det(k, 1)], [pts_gt(k, 2) pts_det(k, 2)], 'g');
end
end
title(sprintf('%.3f', errors(i)));
pause;
%export_fig(fullfile(save_res, num2str(i)), '-pdf');
end
function [im, offset] = CropImage(im, box, pad_ratio)
% Crops image around the bounding box.
pad = pad_ratio * ((box(3) - box(1) + 1) + (box(4) - box(2) + 1));
x1 = max(1, round(box(1) - pad));
y1 = max(1, round(box(2) - pad));
x2 = min(size(im, 2), round(box(3) + pad));
y2 = min(size(im, 1), round(box(4) + pad));
im = im(y1:y2, x1:x2, :);
offset(1) = x1 -1;
offset(2) = y1 -1;
function ShowKeypointNums(pts, color)
for i = 1 : size(pts, 1)
text(pts(i, 1), pts(i, 2), num2str(i), 'Color', color, 'FontSize', 10);
end
|
github
|
golnazghiasi/cofw68-benchmark-master
|
distinguishable_colors.m
|
.m
|
cofw68-benchmark-master/distinguishable_colors.m
| 5,753 |
utf_8
|
57960cf5d13cead2f1e291d1288bccb2
|
function colors = distinguishable_colors(n_colors,bg,func)
% DISTINGUISHABLE_COLORS: pick colors that are maximally perceptually distinct
%
% When plotting a set of lines, you may want to distinguish them by color.
% By default, Matlab chooses a small set of colors and cycles among them,
% and so if you have more than a few lines there will be confusion about
% which line is which. To fix this problem, one would want to be able to
% pick a much larger set of distinct colors, where the number of colors
% equals or exceeds the number of lines you want to plot. Because our
% ability to distinguish among colors has limits, one should choose these
% colors to be "maximally perceptually distinguishable."
%
% This function generates a set of colors which are distinguishable
% by reference to the "Lab" color space, which more closely matches
% human color perception than RGB. Given an initial large list of possible
% colors, it iteratively chooses the entry in the list that is farthest (in
% Lab space) from all previously-chosen entries. While this "greedy"
% algorithm does not yield a global maximum, it is simple and efficient.
% Moreover, the sequence of colors is consistent no matter how many you
% request, which facilitates the users' ability to learn the color order
% and avoids major changes in the appearance of plots when adding or
% removing lines.
%
% Syntax:
% colors = distinguishable_colors(n_colors)
% Specify the number of colors you want as a scalar, n_colors. This will
% generate an n_colors-by-3 matrix, each row representing an RGB
% color triple. If you don't precisely know how many you will need in
% advance, there is no harm (other than execution time) in specifying
% slightly more than you think you will need.
%
% colors = distinguishable_colors(n_colors,bg)
% This syntax allows you to specify the background color, to make sure that
% your colors are also distinguishable from the background. Default value
% is white. bg may be specified as an RGB triple or as one of the standard
% "ColorSpec" strings. You can even specify multiple colors:
% bg = {'w','k'}
% or
% bg = [1 1 1; 0 0 0]
% will only produce colors that are distinguishable from both white and
% black.
%
% colors = distinguishable_colors(n_colors,bg,rgb2labfunc)
% By default, distinguishable_colors uses the image processing toolbox's
% color conversion functions makecform and applycform. Alternatively, you
% can supply your own color conversion function.
%
% Example:
% c = distinguishable_colors(25);
% figure
% image(reshape(c,[1 size(c)]))
%
% Example using the file exchange's 'colorspace':
% func = @(x) colorspace('RGB->Lab',x);
% c = distinguishable_colors(25,'w',func);
% Copyright 2010-2011 by Timothy E. Holy
% Parse the inputs
if (nargin < 2)
bg = [1 1 1]; % default white background
else
if iscell(bg)
% User specified a list of colors as a cell aray
bgc = bg;
for i = 1:length(bgc)
bgc{i} = parsecolor(bgc{i});
end
bg = cat(1,bgc{:});
else
% User specified a numeric array of colors (n-by-3)
bg = parsecolor(bg);
end
end
% Generate a sizable number of RGB triples. This represents our space of
% possible choices. By starting in RGB space, we ensure that all of the
% colors can be generated by the monitor.
n_grid = 30; % number of grid divisions along each axis in RGB space
x = linspace(0,1,n_grid);
[R,G,B] = ndgrid(x,x,x);
rgb = [R(:) G(:) B(:)];
if (n_colors > size(rgb,1)/3)
error('You can''t readily distinguish that many colors');
end
% Convert to Lab color space, which more closely represents human
% perception
if (nargin > 2)
lab = func(rgb);
bglab = func(bg);
else
C = makecform('srgb2lab');
lab = applycform(rgb,C);
bglab = applycform(bg,C);
end
% If the user specified multiple background colors, compute distances
% from the candidate colors to the background colors
mindist2 = inf(size(rgb,1),1);
for i = 1:size(bglab,1)-1
dX = bsxfun(@minus,lab,bglab(i,:)); % displacement all colors from bg
dist2 = sum(dX.^2,2); % square distance
mindist2 = min(dist2,mindist2); % dist2 to closest previously-chosen color
end
% Iteratively pick the color that maximizes the distance to the nearest
% already-picked color
colors = zeros(n_colors,3);
lastlab = bglab(end,:); % initialize by making the "previous" color equal to background
for i = 1:n_colors
dX = bsxfun(@minus,lab,lastlab); % displacement of last from all colors on list
dist2 = sum(dX.^2,2); % square distance
mindist2 = min(dist2,mindist2); % dist2 to closest previously-chosen color
[~,index] = max(mindist2); % find the entry farthest from all previously-chosen colors
colors(i,:) = rgb(index,:); % save for output
lastlab = lab(index,:); % prepare for next iteration
end
end
function c = parsecolor(s)
if ischar(s)
c = colorstr2rgb(s);
elseif isnumeric(s) && size(s,2) == 3
c = s;
else
error('MATLAB:InvalidColorSpec','Color specification cannot be parsed.');
end
end
function c = colorstr2rgb(c)
% Convert a color string to an RGB value.
% This is cribbed from Matlab's whitebg function.
% Why don't they make this a stand-alone function?
rgbspec = [1 0 0;0 1 0;0 0 1;1 1 1;0 1 1;1 0 1;1 1 0;0 0 0];
cspec = 'rgbwcmyk';
k = find(cspec==c(1));
if isempty(k)
error('MATLAB:InvalidColorString','Unknown color string.');
end
if k~=3 || length(c)==1,
c = rgbspec(k,:);
elseif length(c)>2,
if strcmpi(c(1:3),'bla')
c = [0 0 0];
elseif strcmpi(c(1:3),'blu')
c = [0 0 1];
else
error('MATLAB:UnknownColorString', 'Unknown color string.');
end
end
end
|
github
|
sunhongfu/scripts-master
|
load_nii_ext.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_nii_ext.m
| 5,544 |
utf_8
|
09a2960b9d48f4b0363d5065f1780cbd
|
% Load NIFTI header extension after its header is loaded using load_nii_hdr.
%
% Usage: ext = load_nii_ext(filename)
%
% filename - NIFTI file name.
%
% Returned values:
%
% ext - Structure of NIFTI header extension, which includes num_ext,
% and all the extended header sections in the header extension.
% Each extended header section will have its esize, ecode, and
% edata, where edata can be plain text, xml, or any raw data
% that was saved in the extended header section.
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function ext = load_nii_ext(filename)
if ~exist('filename','var'),
error('Usage: ext = load_nii_ext(filename)');
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
elseif strcmp(filename(end-6:end), '.img.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.hdr.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.hdr.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.img.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.nii.gz')
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename = gunzip(filename, tmpDir);
filename = char(filename); % convert from cell to string
end
end
machine = 'ieee-le';
new_ext = 0;
if findstr('.nii',filename) & strcmp(filename(end-3:end), '.nii')
new_ext = 1;
filename(end-3:end)='';
end
if findstr('.hdr',filename) & strcmp(filename(end-3:end), '.hdr')
filename(end-3:end)='';
end
if findstr('.img',filename) & strcmp(filename(end-3:end), '.img')
filename(end-3:end)='';
end
if new_ext
fn = sprintf('%s.nii',filename);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.nii".', filename);
error(msg);
end
else
fn = sprintf('%s.hdr',filename);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.hdr".', filename);
error(msg);
end
end
fid = fopen(fn,'r',machine);
vox_offset = 0;
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
fseek(fid,0,'bof');
if fread(fid,1,'int32') == 348
if new_ext
fseek(fid,108,'bof');
vox_offset = fread(fid,1,'float32');
end
ext = read_extension(fid, vox_offset);
fclose(fid);
else
fclose(fid);
% first try reading the opposite endian to 'machine'
%
switch machine,
case 'ieee-le', machine = 'ieee-be';
case 'ieee-be', machine = 'ieee-le';
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
fseek(fid,0,'bof');
if fread(fid,1,'int32') ~= 348
% Now throw an error
%
msg = sprintf('File "%s" is corrupted.',fn);
error(msg);
end
if new_ext
fseek(fid,108,'bof');
vox_offset = fread(fid,1,'float32');
end
ext = read_extension(fid, vox_offset);
fclose(fid);
end
end
end
% Clean up after gunzip
%
if exist('gzFileName', 'var')
rmdir(tmpDir,'s');
end
return % load_nii_ext
%---------------------------------------------------------------------
function ext = read_extension(fid, vox_offset)
ext = [];
if vox_offset
end_of_ext = vox_offset;
else
fseek(fid, 0, 'eof');
end_of_ext = ftell(fid);
end
if end_of_ext > 352
fseek(fid, 348, 'bof');
ext.extension = fread(fid,4)';
end
if isempty(ext) | ext.extension(1) == 0
ext = [];
return;
end
i = 1;
while(ftell(fid) < end_of_ext)
ext.section(i).esize = fread(fid,1,'int32');
ext.section(i).ecode = fread(fid,1,'int32');
ext.section(i).edata = char(fread(fid,ext.section(i).esize-8)');
i = i + 1;
end
ext.num_ext = length(ext.section);
return % read_extension
|
github
|
sunhongfu/scripts-master
|
rri_orient.m
|
.m
|
scripts-master/cs-phase/_src/_nii/rri_orient.m
| 2,357 |
utf_8
|
e1b7cfcaf2517b7887ac6e02d9ab504d
|
% Convert image of different orientations to standard Analyze orientation
%
% Usage: nii = rri_orient(nii);
% Jimmy Shen ([email protected]), 26-APR-04
%___________________________________________________________________
function [nii, orient, pattern] = rri_orient(nii, varargin)
if nargin > 1
pattern = varargin{1};
else
pattern = [];
end
if(nargin > 2)
orient = varargin{2};
if(length(find(orient>6)) || length(find(orient<1))) %value checking
orient=[1 2 3]; %set to default if bogus values set
end
else
orient = [1 2 3];
end
dim = double(nii.hdr.dime.dim([2:4]));
if ~isempty(pattern) & ~isequal(length(pattern), prod(dim))
return;
end
% get orient of the current image
%
if isequal(orient, [1 2 3])
orient = rri_orient_ui;
pause(.1);
end
% no need for conversion
%
if isequal(orient, [1 2 3])
return;
end
if isempty(pattern)
pattern = 1:prod(dim);
end
pattern = reshape(pattern, dim);
img = nii.img;
% calculate after flip orient
%
rot_orient = mod(orient + 2, 3) + 1;
% do flip:
%
flip_orient = orient - rot_orient;
for i = 1:3
if flip_orient(i)
pattern = flipdim(pattern, i);
img = flipdim(img, i);
end
end
% get index of orient (do inverse)
%
[tmp rot_orient] = sort(rot_orient);
% do rotation:
%
pattern = permute(pattern, rot_orient);
img = permute(img, [rot_orient 4 5 6]);
% rotate resolution, or 'dim'
%
new_dim = nii.hdr.dime.dim([2:4]);
new_dim = new_dim(rot_orient);
nii.hdr.dime.dim([2:4]) = new_dim;
% rotate voxel_size, or 'pixdim'
%
tmp = nii.hdr.dime.pixdim([2:4]);
tmp = tmp(rot_orient);
nii.hdr.dime.pixdim([2:4]) = tmp;
% re-calculate originator
%
tmp = nii.hdr.hist.originator([1:3]);
tmp = tmp(rot_orient);
flip_orient = flip_orient(rot_orient);
for i = 1:3
if flip_orient(i) & ~isequal(double(tmp(i)), 0)
tmp(i) = int16(double(new_dim(i)) - double(tmp(i)) + 1);
end
end
nii.hdr.hist.originator([1:3]) = tmp;
nii.img = img;
pattern = pattern(:);
return; % rri_orient
|
github
|
sunhongfu/scripts-master
|
save_untouch0_nii_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_untouch0_nii_hdr.m
| 8,813 |
utf_8
|
a0a201073cb18f09b62842e94094c451
|
% internal function
% - Jimmy Shen ([email protected])
function save_nii_hdr(hdr, fid)
if ~isequal(hdr.hk.sizeof_hdr,348),
error('hdr.hk.sizeof_hdr must be 348.');
end
write_header(hdr, fid);
return; % save_nii_hdr
%---------------------------------------------------------------------
function write_header(hdr, fid)
% Original header structures
% struct dsr /* dsr = hdr */
% {
% struct header_key hk; /* 0 + 40 */
% struct image_dimension dime; /* 40 + 108 */
% struct data_history hist; /* 148 + 200 */
% }; /* total= 348 bytes*/
header_key(fid, hdr.hk);
image_dimension(fid, hdr.dime);
data_history(fid, hdr.hist);
% check the file size is 348 bytes
%
fbytes = ftell(fid);
if ~isequal(fbytes,348),
msg = sprintf('Header size is not 348 bytes.');
warning(msg);
end
return; % write_header
%---------------------------------------------------------------------
function header_key(fid, hk)
fseek(fid,0,'bof');
% Original header structures
% struct header_key /* header key */
% { /* off + size */
% int sizeof_hdr /* 0 + 4 */
% char data_type[10]; /* 4 + 10 */
% char db_name[18]; /* 14 + 18 */
% int extents; /* 32 + 4 */
% short int session_error; /* 36 + 2 */
% char regular; /* 38 + 1 */
% char hkey_un0; /* 39 + 1 */
% }; /* total=40 bytes */
fwrite(fid, hk.sizeof_hdr(1), 'int32'); % must be 348.
% data_type = sprintf('%-10s',hk.data_type); % ensure it is 10 chars from left
% fwrite(fid, data_type(1:10), 'uchar');
pad = zeros(1, 10-length(hk.data_type));
hk.data_type = [hk.data_type char(pad)];
fwrite(fid, hk.data_type(1:10), 'uchar');
% db_name = sprintf('%-18s', hk.db_name); % ensure it is 18 chars from left
% fwrite(fid, db_name(1:18), 'uchar');
pad = zeros(1, 18-length(hk.db_name));
hk.db_name = [hk.db_name char(pad)];
fwrite(fid, hk.db_name(1:18), 'uchar');
fwrite(fid, hk.extents(1), 'int32');
fwrite(fid, hk.session_error(1), 'int16');
fwrite(fid, hk.regular(1), 'uchar');
fwrite(fid, hk.hkey_un0(1), 'uchar');
return; % header_key
%---------------------------------------------------------------------
function image_dimension(fid, dime)
%struct image_dimension
% { /* off + size */
% short int dim[8]; /* 0 + 16 */
% char vox_units[4]; /* 16 + 4 */
% char cal_units[8]; /* 20 + 8 */
% short int unused1; /* 28 + 2 */
% short int datatype; /* 30 + 2 */
% short int bitpix; /* 32 + 2 */
% short int dim_un0; /* 34 + 2 */
% float pixdim[8]; /* 36 + 32 */
% /*
% pixdim[] specifies the voxel dimensions:
% pixdim[1] - voxel width
% pixdim[2] - voxel height
% pixdim[3] - interslice distance
% ..etc
% */
% float vox_offset; /* 68 + 4 */
% float roi_scale; /* 72 + 4 */
% float funused1; /* 76 + 4 */
% float funused2; /* 80 + 4 */
% float cal_max; /* 84 + 4 */
% float cal_min; /* 88 + 4 */
% int compressed; /* 92 + 4 */
% int verified; /* 96 + 4 */
% int glmax; /* 100 + 4 */
% int glmin; /* 104 + 4 */
% }; /* total=108 bytes */
fwrite(fid, dime.dim(1:8), 'int16');
pad = zeros(1, 4-length(dime.vox_units));
dime.vox_units = [dime.vox_units char(pad)];
fwrite(fid, dime.vox_units(1:4), 'uchar');
pad = zeros(1, 8-length(dime.cal_units));
dime.cal_units = [dime.cal_units char(pad)];
fwrite(fid, dime.cal_units(1:8), 'uchar');
fwrite(fid, dime.unused1(1), 'int16');
fwrite(fid, dime.datatype(1), 'int16');
fwrite(fid, dime.bitpix(1), 'int16');
fwrite(fid, dime.dim_un0(1), 'int16');
fwrite(fid, dime.pixdim(1:8), 'float32');
fwrite(fid, dime.vox_offset(1), 'float32');
fwrite(fid, dime.roi_scale(1), 'float32');
fwrite(fid, dime.funused1(1), 'float32');
fwrite(fid, dime.funused2(1), 'float32');
fwrite(fid, dime.cal_max(1), 'float32');
fwrite(fid, dime.cal_min(1), 'float32');
fwrite(fid, dime.compressed(1), 'int32');
fwrite(fid, dime.verified(1), 'int32');
fwrite(fid, dime.glmax(1), 'int32');
fwrite(fid, dime.glmin(1), 'int32');
return; % image_dimension
%---------------------------------------------------------------------
function data_history(fid, hist)
% Original header structures - ANALYZE 7.5
%struct data_history
% { /* off + size */
% char descrip[80]; /* 0 + 80 */
% char aux_file[24]; /* 80 + 24 */
% char orient; /* 104 + 1 */
% char originator[10]; /* 105 + 10 */
% char generated[10]; /* 115 + 10 */
% char scannum[10]; /* 125 + 10 */
% char patient_id[10]; /* 135 + 10 */
% char exp_date[10]; /* 145 + 10 */
% char exp_time[10]; /* 155 + 10 */
% char hist_un0[3]; /* 165 + 3 */
% int views /* 168 + 4 */
% int vols_added; /* 172 + 4 */
% int start_field; /* 176 + 4 */
% int field_skip; /* 180 + 4 */
% int omax; /* 184 + 4 */
% int omin; /* 188 + 4 */
% int smax; /* 192 + 4 */
% int smin; /* 196 + 4 */
% }; /* total=200 bytes */
% descrip = sprintf('%-80s', hist.descrip); % 80 chars from left
% fwrite(fid, descrip(1:80), 'uchar');
pad = zeros(1, 80-length(hist.descrip));
hist.descrip = [hist.descrip char(pad)];
fwrite(fid, hist.descrip(1:80), 'uchar');
% aux_file = sprintf('%-24s', hist.aux_file); % 24 chars from left
% fwrite(fid, aux_file(1:24), 'uchar');
pad = zeros(1, 24-length(hist.aux_file));
hist.aux_file = [hist.aux_file char(pad)];
fwrite(fid, hist.aux_file(1:24), 'uchar');
fwrite(fid, hist.orient(1), 'uchar');
fwrite(fid, hist.originator(1:5), 'int16');
pad = zeros(1, 10-length(hist.generated));
hist.generated = [hist.generated char(pad)];
fwrite(fid, hist.generated(1:10), 'uchar');
pad = zeros(1, 10-length(hist.scannum));
hist.scannum = [hist.scannum char(pad)];
fwrite(fid, hist.scannum(1:10), 'uchar');
pad = zeros(1, 10-length(hist.patient_id));
hist.patient_id = [hist.patient_id char(pad)];
fwrite(fid, hist.patient_id(1:10), 'uchar');
pad = zeros(1, 10-length(hist.exp_date));
hist.exp_date = [hist.exp_date char(pad)];
fwrite(fid, hist.exp_date(1:10), 'uchar');
pad = zeros(1, 10-length(hist.exp_time));
hist.exp_time = [hist.exp_time char(pad)];
fwrite(fid, hist.exp_time(1:10), 'uchar');
pad = zeros(1, 3-length(hist.hist_un0));
hist.hist_un0 = [hist.hist_un0 char(pad)];
fwrite(fid, hist.hist_un0(1:3), 'uchar');
fwrite(fid, hist.views(1), 'int32');
fwrite(fid, hist.vols_added(1), 'int32');
fwrite(fid, hist.start_field(1),'int32');
fwrite(fid, hist.field_skip(1), 'int32');
fwrite(fid, hist.omax(1), 'int32');
fwrite(fid, hist.omin(1), 'int32');
fwrite(fid, hist.smax(1), 'int32');
fwrite(fid, hist.smin(1), 'int32');
return; % data_history
|
github
|
sunhongfu/scripts-master
|
rri_zoom_menu.m
|
.m
|
scripts-master/cs-phase/_src/_nii/rri_zoom_menu.m
| 770 |
utf_8
|
f0bae2b3d88fd719c47fd467e867e19f
|
% Imbed a zoom menu to any figure.
%
% Usage: rri_zoom_menu(fig);
%
% - Jimmy Shen ([email protected])
%
%--------------------------------------------------------------------
function menu_hdl = rri_zoom_menu(fig)
if isnumeric(fig)
menu_hdl = uimenu('Parent',fig, ...
'Label','Zoom on', ...
'Userdata', 1, ...
'Callback','rri_zoom_menu(''zoom'');');
return;
end
zoom_on_state = get(gcbo,'Userdata');
if (zoom_on_state == 1)
zoom on;
set(gcbo,'Userdata',0,'Label','Zoom off');
set(gcbf,'pointer','crosshair');
else
zoom off;
set(gcbo,'Userdata',1,'Label','Zoom on');
set(gcbf,'pointer','arrow');
end
return % rri_zoom_menu
|
github
|
sunhongfu/scripts-master
|
rri_select_file.m
|
.m
|
scripts-master/cs-phase/_src/_nii/rri_select_file.m
| 17,235 |
utf_8
|
0e0b14435a670dd8805aa514f7dbb6bb
|
function [selected_file, selected_path] = rri_select_file(varargin)
%
% USAGE: [selected_file, selected_path] = ...
% rri_select_file(dir_name, fig_title)
%
% Allow user to select a file from a list of Matlab competible
% file format
%
% Example:
%
% [selected_file, selected_path] = ...
% rri_select_file('/usr','Select Data File');
%
% See Also RRI_GETFILES
% -- Created June 2001 by Wilkin Chau, Rotman Research Institute
%
% use rri_select_file to open & save Matlab recognized format
% -- Modified Dec 2002 by Jimmy Shen, Rotman Research Institute
%
if nargin == 0 | ischar(varargin{1}) % create rri_select_file figure
dir_name = '';
fig_title = 'Select a File';
if nargin > 0
dir_name = varargin{1};
end
if nargin > 1
fig_title = varargin{2};
end
Init(fig_title,dir_name);
uiwait; % wait for user finish
selected_path = getappdata(gcf,'SelectedDirectory');
selected_file = getappdata(gcf,'SelectedFile');
cd (getappdata(gcf,'StartDirectory'));
close(gcf);
return;
end;
% clear the message line,
%
h = findobj(gcf,'Tag','MessageLine');
set(h,'String','');
action = varargin{1}{1};
% change 'File format':
% update 'Files' & 'File selection' based on file pattern
%
if strcmp(action,'EditFilter'),
EditFilter;
% run delete_fig when figure is closing
%
elseif strcmp(action,'delete_fig'),
delete_fig;
% select 'Directories':
% go into the selected dir
% update 'Files' & 'File selection' based on file pattern
%
elseif strcmp(action,'select_dir'),
select_dir;
% select 'Files':
% update 'File selection'
%
elseif strcmp(action,'select_file'),
select_file;
% change 'File selection':
% if it is a file, select that,
% if it is more than a file (*), select those,
% if it is a directory, select based on file pattern
%
elseif strcmp(action,'EditSelection'),
EditSelection;
% clicked 'Select'
%
elseif strcmp(action,'DONE_BUTTON_PRESSED'),
h = findobj(gcf,'Tag','SelectionEdit');
[filepath,filename,fileext] = fileparts(get(h,'String'));
if isempty(filepath) | isempty(filename) | isempty(fileext)
setappdata(gcf,'SelectedDirectory',[]);
setappdata(gcf,'SelectedFile',[]);
else
if ~strcmp(filepath(end),filesep) % not end with filesep
filepath = [filepath filesep]; % add a filesep to filepath
end
setappdata(gcf,'SelectedDirectory',filepath);
setappdata(gcf,'SelectedFile',[filename fileext]);
end
if getappdata(gcf,'ready') % ready to exit
uiresume;
end
% clicked 'cancel'
%
elseif strcmp(action,'CANCEL_BUTTON_PRESSED'),
setappdata(gcf,'SelectedDirectory',[]);
setappdata(gcf,'SelectedFile',[]);
set(findobj(gcf,'Tag','FileList'),'String','');
uiresume;
end;
return;
% --------------------------------------------------------------------
function Init(fig_title,dir_name),
StartDirectory = pwd;
if isempty(StartDirectory),
StartDirectory = filesep;
end;
filter_disp = {'JPEG image (*.jpg)', ...
'TIFF image, compressed (*.tif)', ...
'EPS Level 1 (*.eps)', ...
'Adobe Illustrator 88 (*.ai)', ...
'Enhanced metafile (*.emf)', ...
'Matlab Figure (*.fig)', ...
'Matlab M-file (*.m)', ...
'Portable bitmap (*.pbm)', ...
'Paintbrush 24-bit (*.pcx)', ...
'Portable Graymap (*.pgm)', ...
'Portable Network Graphics (*.png)', ...
'Portable Pixmap (*.ppm)', ...
};
filter_string = {'*.jpg', ...
'*.tif', ...
'*.eps', ...
'*.ai', ...
'*.emf', ...
'*.fig', ...
'*.m', ...
'*.pbm', ...
'*.pcx', ...
'*.pgm', ...
'*.png', ...
'*.ppm', ...
};
% filter_disp = char(filter_disp);
filter_string = char(filter_string);
margine = 0.05;
line_height = 0.07;
char_height = line_height*0.8;
save_setting_status = 'on';
rri_select_file_pos = [];
try
load('pls_profile');
catch
end
if ~isempty(rri_select_file_pos) & strcmp(save_setting_status,'on')
pos = rri_select_file_pos;
else
w = 0.4;
h = 0.6;
x = (1-w)/2;
y = (1-h)/2;
pos = [x y w h];
end
h0 = figure('parent',0, 'Color',[0.8 0.8 0.8], ...
'Units','normal', ...
'Name',fig_title, ...
'NumberTitle','off', ...
'MenuBar','none', ...
'Position', pos, ...
'deleteFcn','rri_select_file({''delete_fig''});', ...
'WindowStyle', 'modal', ...
'Tag','GetFilesFigure', ...
'ToolBar','none');
x = margine;
y = 1 - 1*line_height - margine;
w = 1-2*x;
h = char_height;
pos = [x y w h];
h1 = uicontrol('Parent',h0, ... % Filter Label
'Style','text', ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'fontunit','normal', ...
'FontSize',0.5, ...
'HorizontalAlignment','left', ...
'Position', pos, ...
'String','Choose one of the file format:', ...
'Tag','FilterLabel');
y = 1 - 2*line_height - margine + line_height*0.2;
w = 1-2*x;
pos = [x y w h];
h_filter = uicontrol('Parent',h0, ... % Filter list
'Style','popupmenu', ...
'Units','normal', ...
'BackgroundColor',[1 1 1], ...
'fontunit','normal', ...
'FontSize',0.5, ...
'HorizontalAlignment','left', ...
'Position', pos, ...
'String', filter_disp, ...
'user', filter_string, ...
'value', 1, ...
'Callback','rri_select_file({''EditFilter''});', ...
'Tag','FilterEdit');
y = 1 - 3*line_height - margine;
w = 0.5 - x - margine/2;
pos = [x y w h];
h1 = uicontrol('Parent',h0, ... % Directory Label
'Style','text', ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'fontunit','normal', ...
'FontSize',0.5, ...
'HorizontalAlignment','left', ...
'ListboxTop',0, ...
'Position', pos, ...
'String','Directories', ...
'Tag','DirectoryLabel');
x = 0.5;
y = 1 - 3*line_height - margine;
w = 0.5 - margine;
pos = [x y w h];
h1 = uicontrol('Parent',h0, ... % File Label
'Style','text', ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'fontunit','normal', ...
'FontSize',0.5, ...
'HorizontalAlignment','left', ...
'ListboxTop',0, ...
'Position', pos, ...
'String','Files', ...
'Tag','FileLabel');
x = margine;
y = 4*line_height + margine;
w = 0.5 - x - margine/2;
h = 1 - 7*line_height - 2*margine;
pos = [x y w h];
h_dir = uicontrol('Parent',h0, ... % Directory Listbox
'Style','listbox', ...
'Units','normal', ...
'fontunit','normal', ...
'FontSize',0.08, ...
'HorizontalAlignment','left', ...
'Interruptible', 'off', ...
'ListboxTop',1, ...
'Position', pos, ...
'String', '', ...
'Callback','rri_select_file({''select_dir''});', ...
'Tag','DirectoryList');
x = 0.5;
y = 4*line_height + margine;
w = 0.5 - margine;
h = 1 - 7*line_height - 2*margine;
pos = [x y w h];
h_file = uicontrol('Parent',h0, ... % File Listbox
'Style','listbox', ...
'Units','normal', ...
'fontunit','normal', ...
'FontSize',0.08, ...
'HorizontalAlignment','left', ...
'ListboxTop',1, ...
'Position', pos, ...
'String', '', ...
'Callback','rri_select_file({''select_file''});', ...
'Tag','FileList');
x = margine;
y = 3*line_height + margine - line_height*0.2;
w = 1-2*x;
h = char_height;
pos = [x y w h];
h1 = uicontrol('Parent',h0, ... % Selection Label
'Style','text', ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'fontunit','normal', ...
'FontSize',0.5, ...
'HorizontalAlignment','left', ...
'Position', pos, ...
'String','File you selected:', ...
'Tag','SelectionLabel');
y = 2*line_height + margine;
w = 1-2*x;
pos = [x y w h];
h_select = uicontrol('Parent',h0, ... % Selection Edit
'Style','edit', ...
'Units','normal', ...
'BackgroundColor',[1 1 1], ...
'fontunit','normal', ...
'FontSize',0.5, ...
'HorizontalAlignment','left', ...
'Position', pos, ...
'String', '', ...
'Callback','rri_select_file({''EditSelection''});', ...
'Tag','SelectionEdit');
x = 2*margine;
y = line_height/2 + margine;
w = 0.2;
h = line_height;
pos = [x y w h];
h_done = uicontrol('Parent',h0, ... % DONE
'Units','normal', ...
'fontunit','normal', ...
'FontSize',0.5, ...
'ListboxTop',0, ...
'Position', pos, ...
'HorizontalAlignment','center', ...
'String','Save', ... % 'Select', ...
'Callback','rri_select_file({''DONE_BUTTON_PRESSED''});', ...
'Tag','DONEButton');
x = 1 - x - w;
pos = [x y w h];
h_cancel = uicontrol('Parent',h0, ... % CANCEL
'Units','normal', ...
'fontunit','normal', ...
'FontSize',0.5, ...
'ListboxTop',0, ...
'Position', pos, ...
'HorizontalAlignment','center', ...
'String','Cancel', ...
'Callback','rri_select_file({''CANCEL_BUTTON_PRESSED''});', ...
'Tag','CANCELButton');
if isempty(dir_name)
dir_name = StartDirectory;
end
set(h_select,'string',dir_name);
filter_select = get(h_filter,'value');
filter_pattern = filter_string(filter_select,:);
setappdata(gcf,'FilterPattern',deblank(filter_pattern));
setappdata(gcf,'filter_string',filter_string);
setappdata(gcf,'h_filter', h_filter);
setappdata(gcf,'h_dir', h_dir);
setappdata(gcf,'h_file', h_file);
setappdata(gcf,'h_select', h_select);
setappdata(gcf,'h_done', h_done);
setappdata(gcf,'h_cancel', h_cancel);
setappdata(gcf,'StartDirectory',StartDirectory);
EditSelection;
h_file = getappdata(gcf,'h_file');
if isempty(get(h_file,'string'))
setappdata(gcf,'ready',0);
else
setappdata(gcf,'ready',1);
end
return; % Init
% called by all the actions, to update 'Directories' or 'Files'
% based on filter_pattern. Select first file in filelist.
%
% --------------------------------------------------------------------
function update_dirlist;
filter_path = getappdata(gcf,'curr_dir');
filter_pattern = getappdata(gcf,'FilterPattern');
if exist(filter_pattern) == 2 % user input specific filename
is_single_file = 1; % need manually take path out later
else
is_single_file = 0;
end
% take the file path out from filter_pattern
%
[fpath fname fext] = fileparts(filter_pattern);
filter_pattern = [fname fext];
dir_struct = dir(filter_path);
if isempty(dir_struct)
msg = 'ERROR: Directory not found!';
uiwait(msgbox(msg,'File Selection Error','modal'));
return;
end;
old_pointer = get(gcf,'Pointer');
set(gcf,'Pointer','watch');
dir_list = dir_struct(find([dir_struct.isdir] == 1));
[sorted_dir_names,sorted_dir_index] = sortrows({dir_list.name}');
dir_struct = dir([filter_path filesep filter_pattern]);
if isempty(dir_struct)
sorted_file_names = [];
else
file_list = dir_struct(find([dir_struct.isdir] == 0));
if is_single_file % take out path
tmp = file_list.name;
[fpath fname fext] = fileparts(tmp);
file_list.name = [fname fext];
end
[sorted_file_names,sorted_file_index] = sortrows({file_list.name}');
end;
disp_dir_names = []; % if need full path, use this
% instead of sorted_dir_names
for i=1:length(sorted_dir_names)
tmp = [filter_path filesep sorted_dir_names{i}];
disp_dir_names = [disp_dir_names {tmp}];
end
h = findobj(gcf,'Tag','DirectoryList');
set(h,'String',sorted_dir_names,'Value',1);
h = findobj(gcf,'Tag','FileList');
set(h,'String',sorted_file_names,'value',1);
h_select = getappdata(gcf,'h_select');
if strcmp(filter_path(end),filesep) % filepath end with filesep
filter_path = filter_path(1:end-1); % take filesep out
end
if isempty(sorted_file_names)
set(h_select,'string',[filter_path filesep]);
else
set(h_select,'string',[filter_path filesep sorted_file_names{1}]);
end
set(gcf,'Pointer',old_pointer);
return; % update_dirlist
% change 'File format':
% update 'Files' & 'File selection' based on file pattern
%
% --------------------------------------------------------------------
function EditFilter()
filter_select = get(gcbo,'value');
filter_string = getappdata(gcf,'filter_string');
filter_pattern = filter_string(filter_select,:);
filter_path = getappdata(gcf,'curr_dir');
% update filter_pattern
setappdata(gcf,'FilterPattern',deblank(filter_pattern));
if isempty(filter_path),
filter_path = filesep;
end;
update_dirlist;
h_file = getappdata(gcf,'h_file');
if isempty(get(h_file,'string'))
setappdata(gcf,'ready',0);
else
setappdata(gcf,'ready',1);
end
return; % EditFilter
% select 'Directories':
% go into the selected dir
% update 'Files' & 'File selection' based on file pattern
%
% --------------------------------------------------------------------
function select_dir()
listed_dir = get(gcbo,'String');
selected_dir_idx = get(gcbo,'Value');
selected_dir = listed_dir{selected_dir_idx};
curr_dir = getappdata(gcf,'curr_dir');
% update the selection box
%
try
cd ([curr_dir filesep selected_dir]);
catch
msg = 'ERROR: Cannot access directory';
uiwait(msgbox(msg,'File Selection Error','modal'));
return;
end;
if isempty(pwd)
curr_dir = filesep;
else
curr_dir = pwd;
end;
setappdata(gcf,'curr_dir',curr_dir);
update_dirlist;
h_file = getappdata(gcf,'h_file');
if isempty(get(h_file,'string'))
setappdata(gcf,'ready',0);
else
setappdata(gcf,'ready',1);
end
return; % select_dir
% select 'Files':
% update 'File selection'
%
% --------------------------------------------------------------------
function select_file()
setappdata(gcf,'ready',1);
listed_file = get(gcbo,'String');
selected_file_idx = get(gcbo,'Value');
selected_file = listed_file{selected_file_idx};
curr_dir = getappdata(gcf,'curr_dir');
if strcmp(curr_dir(end),filesep) % filepath end with filesep
curr_dir = curr_dir(1:end-1); % take filesep out
end
h_select = getappdata(gcf,'h_select');
set(h_select,'string',[curr_dir filesep selected_file]);
return; % select_file
% change 'File selection':
% if it is a file, select that,
% if it is more than a file (*), select those,
% if it is a directory, select based on file pattern
%
% --------------------------------------------------------------------
function EditSelection()
filter_string = getappdata(gcf,'filter_string');
h_select = getappdata(gcf,'h_select');
selected_file = get(h_select,'string');
if exist(selected_file) == 7 % if user enter a dir
setappdata(gcf,'ready',0);
setappdata(gcf,'curr_dir',selected_file); % get new dir
update_dirlist;
else
setappdata(gcf,'ready',1);
[fpath fname fext]= fileparts(selected_file);
if exist(fpath) ~=7 % fpath is not a dir
setappdata(gcf,'ready',0);
msg = 'ERROR: Cannot access directory';
uiwait(msgbox(msg,'File Selection Error','modal'));
end
% if the file format user entered is not supported by matlab
if isempty(strmatch(['*',fext],filter_string,'exact'))
setappdata(gcf,'ready',0);
msg = 'ERROR: File format is not supported by Matlab.';
uiwait(msgbox(msg,'File Selection Error','modal'));
end
end
return; % EditSelection
% --------------------------------------------------------------------
function delete_fig()
try
load('pls_profile');
pls_profile = which('pls_profile.mat');
rri_select_file_pos = get(gcbf,'position');
save(pls_profile, '-append', 'rri_select_file_pos');
catch
end
return;
|
github
|
sunhongfu/scripts-master
|
clip_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/clip_nii.m
| 3,421 |
utf_8
|
19da887808bddae362df38b0e9f35076
|
% CLIP_NII: Clip the NIfTI volume from any of the 6 sides
%
% Usage: nii = clip_nii(nii, [option])
%
% Inputs:
%
% nii - NIfTI volume.
%
% option - struct instructing how many voxel to be cut from which side.
%
% option.cut_from_L = ( number of voxel )
% option.cut_from_R = ( number of voxel )
% option.cut_from_P = ( number of voxel )
% option.cut_from_A = ( number of voxel )
% option.cut_from_I = ( number of voxel )
% option.cut_from_S = ( number of voxel )
%
% Options description in detail:
% ==============================
%
% cut_from_L: Number of voxels from Left side will be clipped.
%
% cut_from_R: Number of voxels from Right side will be clipped.
%
% cut_from_P: Number of voxels from Posterior side will be clipped.
%
% cut_from_A: Number of voxels from Anterior side will be clipped.
%
% cut_from_I: Number of voxels from Inferior side will be clipped.
%
% cut_from_S: Number of voxels from Superior side will be clipped.
%
% NIfTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function nii = clip_nii(nii, opt)
dims = abs(nii.hdr.dime.dim(2:4));
origin = abs(nii.hdr.hist.originator(1:3));
if isempty(origin) | all(origin == 0) % according to SPM
origin = round((dims+1)/2);
end
cut_from_L = 0;
cut_from_R = 0;
cut_from_P = 0;
cut_from_A = 0;
cut_from_I = 0;
cut_from_S = 0;
if nargin > 1 & ~isempty(opt)
if ~isstruct(opt)
error('option argument should be a struct');
end
if isfield(opt,'cut_from_L')
cut_from_L = round(opt.cut_from_L);
if cut_from_L >= origin(1) | cut_from_L < 0
error('cut_from_L cannot be negative or cut beyond originator');
end
end
if isfield(opt,'cut_from_P')
cut_from_P = round(opt.cut_from_P);
if cut_from_P >= origin(2) | cut_from_P < 0
error('cut_from_P cannot be negative or cut beyond originator');
end
end
if isfield(opt,'cut_from_I')
cut_from_I = round(opt.cut_from_I);
if cut_from_I >= origin(3) | cut_from_I < 0
error('cut_from_I cannot be negative or cut beyond originator');
end
end
if isfield(opt,'cut_from_R')
cut_from_R = round(opt.cut_from_R);
if cut_from_R > dims(1)-origin(1) | cut_from_R < 0
error('cut_from_R cannot be negative or cut beyond originator');
end
end
if isfield(opt,'cut_from_A')
cut_from_A = round(opt.cut_from_A);
if cut_from_A > dims(2)-origin(2) | cut_from_A < 0
error('cut_from_A cannot be negative or cut beyond originator');
end
end
if isfield(opt,'cut_from_S')
cut_from_S = round(opt.cut_from_S);
if cut_from_S > dims(3)-origin(3) | cut_from_S < 0
error('cut_from_S cannot be negative or cut beyond originator');
end
end
end
nii = make_nii(nii.img( (cut_from_L+1) : (dims(1)-cut_from_R), ...
(cut_from_P+1) : (dims(2)-cut_from_A), ...
(cut_from_I+1) : (dims(3)-cut_from_S), ...
:,:,:,:,:), nii.hdr.dime.pixdim(2:4), ...
[origin(1)-cut_from_L origin(2)-cut_from_P origin(3)-cut_from_I], ...
nii.hdr.dime.datatype, nii.hdr.hist.descrip);
return;
|
github
|
sunhongfu/scripts-master
|
affine.m
|
.m
|
scripts-master/cs-phase/_src/_nii/affine.m
| 16,664 |
utf_8
|
419b609560eb98534c0e32cc4506cc7f
|
% Using 2D or 3D affine matrix to rotate, translate, scale, reflect and
% shear a 2D image or 3D volume. 2D image is represented by a 2D matrix,
% 3D volume is represented by a 3D matrix, and data type can be real
% integer or floating-point.
%
% You may notice that MATLAB has a function called 'imtransform.m' for
% 2D spatial transformation. However, keep in mind that 'imtransform.m'
% assumes y for the 1st dimension, and x for the 2nd dimension. They are
% equivalent otherwise.
%
% In addition, if you adjust the 'new_elem_size' parameter, this 'affine.m'
% is equivalent to 'interp2.m' for 2D image, and equivalent to 'interp3.m'
% for 3D volume.
%
% Usage: [new_img new_M] = ...
% affine(old_img, old_M, [new_elem_size], [verbose], [bg], [method]);
%
% old_img - original 2D image or 3D volume. We assume x for the 1st
% dimension, y for the 2nd dimension, and z for the 3rd
% dimension.
%
% old_M - a 3x3 2D affine matrix for 2D image, or a 4x4 3D affine
% matrix for 3D volume. We assume x for the 1st dimension,
% y for the 2nd dimension, and z for the 3rd dimension.
%
% new_elem_size (optional) - size of voxel along x y z direction for
% a transformed 3D volume, or size of pixel along x y for
% a transformed 2D image. We assume x for the 1st dimension
% y for the 2nd dimension, and z for the 3rd dimension.
% 'new_elem_size' is 1 if it is default or empty.
%
% You can increase its value to decrease the resampling rate,
% and make the 2D image or 3D volume more coarse. It works
% just like 'interp3'.
%
% verbose (optional) - 1, 0
% 1: show transforming progress in percentage
% 2: progress will not be displayed
% 'verbose' is 1 if it is default or empty.
%
% bg (optional) - background voxel intensity in any extra corner that
% is caused by the interpolation. 0 in most cases. If it is
% default or empty, 'bg' will be the average of two corner
% voxel intensities in original data.
%
% method (optional) - 1, 2, or 3
% 1: for Trilinear interpolation
% 2: for Nearest Neighbor interpolation
% 3: for Fischer's Bresenham interpolation
% 'method' is 1 if it is default or empty.
%
% new_img - transformed 2D image or 3D volume
%
% new_M - transformed affine matrix
%
% Example 1 (3D rotation):
% load mri.mat; old_img = double(squeeze(D));
% old_M = [0.88 0.5 3 -90; -0.5 0.88 3 -126; 0 0 2 -72; 0 0 0 1];
% new_img = affine(old_img, old_M, 2);
% [x y z] = meshgrid(1:128,1:128,1:27);
% sz = size(new_img);
% [x1 y1 z1] = meshgrid(1:sz(2),1:sz(1),1:sz(3));
% figure; slice(x, y, z, old_img, 64, 64, 13.5);
% shading flat; colormap(map); view(-66, 66);
% figure; slice(x1, y1, z1, new_img, sz(1)/2, sz(2)/2, sz(3)/2);
% shading flat; colormap(map); view(-66, 66);
%
% Example 2 (2D interpolation):
% load mri.mat; old_img=D(:,:,1,13)';
% old_M = [1 0 0; 0 1 0; 0 0 1];
% new_img = affine(old_img, old_M, [.2 .4]);
% figure; image(old_img); colormap(map);
% figure; image(new_img); colormap(map);
%
% This program is inspired by:
% SPM5 Software from Wellcome Trust Centre for Neuroimaging
% http://www.fil.ion.ucl.ac.uk/spm/software
% Fischer, J., A. del Rio (2004). A Fast Method for Applying Rigid
% Transformations to Volume Data, WSCG2004 Conference.
% http://wscg.zcu.cz/wscg2004/Papers_2004_Short/M19.pdf
%
% - Jimmy Shen ([email protected])
%
function [new_img, new_M] = affine(old_img, old_M, new_elem_size, verbose, bg, method)
if ~exist('old_img','var') | ~exist('old_M','var')
error('Usage: [new_img new_M] = affine(old_img, old_M, [new_elem_size], [verbose], [bg], [method]);');
end
if ndims(old_img) == 3
if ~isequal(size(old_M),[4 4])
error('old_M should be a 4x4 affine matrix for 3D volume.');
end
elseif ndims(old_img) == 2
if ~isequal(size(old_M),[3 3])
error('old_M should be a 3x3 affine matrix for 2D image.');
end
else
error('old_img should be either 2D image or 3D volume.');
end
if ~exist('new_elem_size','var') | isempty(new_elem_size)
new_elem_size = [1 1 1];
elseif length(new_elem_size) < 2
new_elem_size = new_elem_size(1)*ones(1,3);
elseif length(new_elem_size) < 3
new_elem_size = [new_elem_size(:); 1]';
end
if ~exist('method','var') | isempty(method)
method = 1;
elseif ~exist('bresenham_line3d.m','file') & method == 3
error([char(10) char(10) 'Please download 3D Bresenham''s line generation program from:' char(10) char(10) 'http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=21057' char(10) char(10) 'to test Fischer''s Bresenham interpolation method.' char(10) char(10)]);
end
% Make compatible to MATLAB earlier than version 7 (R14), which
% can only perform arithmetic on double data type
%
old_img = double(old_img);
old_dim = size(old_img);
if ~exist('bg','var') | isempty(bg)
bg = mean([old_img(1) old_img(end)]);
end
if ~exist('verbose','var') | isempty(verbose)
verbose = 1;
end
if ndims(old_img) == 2
old_dim(3) = 1;
old_M = old_M(:, [1 2 3 3]);
old_M = old_M([1 2 3 3], :);
old_M(3,:) = [0 0 1 0];
old_M(:,3) = [0 0 1 0]';
end
% Vertices of img in voxel
%
XYZvox = [ 1 1 1
1 1 old_dim(3)
1 old_dim(2) 1
1 old_dim(2) old_dim(3)
old_dim(1) 1 1
old_dim(1) 1 old_dim(3)
old_dim(1) old_dim(2) 1
old_dim(1) old_dim(2) old_dim(3) ]';
old_R = old_M(1:3,1:3);
old_T = old_M(1:3,4);
% Vertices of img in millimeter
%
XYZmm = old_R*(XYZvox-1) + repmat(old_T, [1, 8]);
% Make scale of new_M according to new_elem_size
%
new_M = diag([new_elem_size 1]);
% Make translation so minimum vertex is moved to [1,1,1]
%
new_M(1:3,4) = round( min(XYZmm,[],2) );
% New dimensions will be the maximum vertices in XYZ direction (dim_vox)
% i.e. compute dim_vox via dim_mm = R*(dim_vox-1)+T
% where, dim_mm = round(max(XYZmm,[],2));
%
new_dim = ceil(new_M(1:3,1:3) \ ( round(max(XYZmm,[],2))-new_M(1:3,4) )+1)';
% Initialize new_img with new_dim
%
new_img = zeros(new_dim(1:3));
% Mask out any changes from Z axis of transformed volume, since we
% will traverse it voxel by voxel below. We will only apply unit
% increment of mask_Z(3,4) to simulate the cursor movement
%
% i.e. we will use mask_Z * new_XYZvox to replace new_XYZvox
%
mask_Z = diag(ones(1,4));
mask_Z(3,3) = 0;
% It will be easier to do the interpolation if we invert the process
% by not traversing the original volume. Instead, we traverse the
% transformed volume, and backproject each voxel in the transformed
% volume back into the original volume. If the backprojected voxel
% in original volume is within its boundary, the intensity of that
% voxel can be used by the cursor location in the transformed volume.
%
% First, we traverse along Z axis of transformed volume voxel by voxel
%
for z = 1:new_dim(3)
if verbose & ~mod(z,10)
fprintf('%.2f percent is done.\n', 100*z/new_dim(3));
end
% We need to find out the mapping from voxel in the transformed
% volume (new_XYZvox) to voxel in the original volume (old_XYZvox)
%
% The following equation works, because they all equal to XYZmm:
% new_R*(new_XYZvox-1) + new_T == old_R*(old_XYZvox-1) + old_T
%
% We can use modified new_M1 & old_M1 to substitute new_M & old_M
% new_M1 * new_XYZvox == old_M1 * old_XYZvox
%
% where: M1 = M; M1(:,4) = M(:,4) - sum(M(:,1:3),2);
% and: M(:,4) == [T; 1] == sum(M1,2)
%
% Therefore: old_XYZvox = old_M1 \ new_M1 * new_XYZvox;
%
% Since we are traverse Z axis, and new_XYZvox is replaced
% by mask_Z * new_XYZvox, the above formula can be rewritten
% as: old_XYZvox = old_M1 \ new_M1 * mask_Z * new_XYZvox;
%
% i.e. we find the mapping from new_XYZvox to old_XYZvox:
% M = old_M1 \ new_M1 * mask_Z;
%
% First, compute modified old_M1 & new_M1
%
old_M1 = old_M; old_M1(:,4) = old_M(:,4) - sum(old_M(:,1:3),2);
new_M1 = new_M; new_M1(:,4) = new_M(:,4) - sum(new_M(:,1:3),2);
% Then, apply unit increment of mask_Z(3,4) to simulate the
% cursor movement
%
mask_Z(3,4) = z;
% Here is the mapping from new_XYZvox to old_XYZvox
%
M = old_M1 \ new_M1 * mask_Z;
switch method
case 1
new_img(:,:,z) = trilinear(old_img, new_dim, old_dim, M, bg);
case 2
new_img(:,:,z) = nearest_neighbor(old_img, new_dim, old_dim, M, bg);
case 3
new_img(:,:,z) = bresenham(old_img, new_dim, old_dim, M, bg);
end
end; % for z
if ndims(old_img) == 2
new_M(3,:) = [];
new_M(:,3) = [];
end
return; % affine
%--------------------------------------------------------------------
function img_slice = trilinear(img, dim1, dim2, M, bg)
img_slice = zeros(dim1(1:2));
TINY = 5e-2; % tolerance
% Dimension of transformed 3D volume
%
xdim1 = dim1(1);
ydim1 = dim1(2);
% Dimension of original 3D volume
%
xdim2 = dim2(1);
ydim2 = dim2(2);
zdim2 = dim2(3);
% initialize new_Y accumulation
%
Y2X = 0;
Y2Y = 0;
Y2Z = 0;
for y = 1:ydim1
% increment of new_Y accumulation
%
Y2X = Y2X + M(1,2); % new_Y to old_X
Y2Y = Y2Y + M(2,2); % new_Y to old_Y
Y2Z = Y2Z + M(3,2); % new_Y to old_Z
% backproject new_Y accumulation and translation to old_XYZ
%
old_X = Y2X + M(1,4);
old_Y = Y2Y + M(2,4);
old_Z = Y2Z + M(3,4);
for x = 1:xdim1
% accumulate the increment of new_X, and apply it
% to the backprojected old_XYZ
%
old_X = M(1,1) + old_X ;
old_Y = M(2,1) + old_Y ;
old_Z = M(3,1) + old_Z ;
% within boundary of original image
%
if ( old_X > 1-TINY & old_X < xdim2+TINY & ...
old_Y > 1-TINY & old_Y < ydim2+TINY & ...
old_Z > 1-TINY & old_Z < zdim2+TINY )
% Calculate distance of old_XYZ to its neighbors for
% weighted intensity average
%
dx = old_X - floor(old_X);
dy = old_Y - floor(old_Y);
dz = old_Z - floor(old_Z);
x000 = floor(old_X);
x100 = x000 + 1;
if floor(old_X) < 1
x000 = 1;
x100 = x000;
elseif floor(old_X) > xdim2-1
x000 = xdim2;
x100 = x000;
end
x010 = x000;
x001 = x000;
x011 = x000;
x110 = x100;
x101 = x100;
x111 = x100;
y000 = floor(old_Y);
y010 = y000 + 1;
if floor(old_Y) < 1
y000 = 1;
y100 = y000;
elseif floor(old_Y) > ydim2-1
y000 = ydim2;
y010 = y000;
end
y100 = y000;
y001 = y000;
y101 = y000;
y110 = y010;
y011 = y010;
y111 = y010;
z000 = floor(old_Z);
z001 = z000 + 1;
if floor(old_Z) < 1
z000 = 1;
z001 = z000;
elseif floor(old_Z) > zdim2-1
z000 = zdim2;
z001 = z000;
end
z100 = z000;
z010 = z000;
z110 = z000;
z101 = z001;
z011 = z001;
z111 = z001;
x010 = x000;
x001 = x000;
x011 = x000;
x110 = x100;
x101 = x100;
x111 = x100;
v000 = double(img(x000, y000, z000));
v010 = double(img(x010, y010, z010));
v001 = double(img(x001, y001, z001));
v011 = double(img(x011, y011, z011));
v100 = double(img(x100, y100, z100));
v110 = double(img(x110, y110, z110));
v101 = double(img(x101, y101, z101));
v111 = double(img(x111, y111, z111));
img_slice(x,y) = v000*(1-dx)*(1-dy)*(1-dz) + ...
v010*(1-dx)*dy*(1-dz) + ...
v001*(1-dx)*(1-dy)*dz + ...
v011*(1-dx)*dy*dz + ...
v100*dx*(1-dy)*(1-dz) + ...
v110*dx*dy*(1-dz) + ...
v101*dx*(1-dy)*dz + ...
v111*dx*dy*dz;
else
img_slice(x,y) = bg;
end % if boundary
end % for x
end % for y
return; % trilinear
%--------------------------------------------------------------------
function img_slice = nearest_neighbor(img, dim1, dim2, M, bg)
img_slice = zeros(dim1(1:2));
% Dimension of transformed 3D volume
%
xdim1 = dim1(1);
ydim1 = dim1(2);
% Dimension of original 3D volume
%
xdim2 = dim2(1);
ydim2 = dim2(2);
zdim2 = dim2(3);
% initialize new_Y accumulation
%
Y2X = 0;
Y2Y = 0;
Y2Z = 0;
for y = 1:ydim1
% increment of new_Y accumulation
%
Y2X = Y2X + M(1,2); % new_Y to old_X
Y2Y = Y2Y + M(2,2); % new_Y to old_Y
Y2Z = Y2Z + M(3,2); % new_Y to old_Z
% backproject new_Y accumulation and translation to old_XYZ
%
old_X = Y2X + M(1,4);
old_Y = Y2Y + M(2,4);
old_Z = Y2Z + M(3,4);
for x = 1:xdim1
% accumulate the increment of new_X and apply it
% to the backprojected old_XYZ
%
old_X = M(1,1) + old_X ;
old_Y = M(2,1) + old_Y ;
old_Z = M(3,1) + old_Z ;
xi = round(old_X);
yi = round(old_Y);
zi = round(old_Z);
% within boundary of original image
%
if ( xi >= 1 & xi <= xdim2 & ...
yi >= 1 & yi <= ydim2 & ...
zi >= 1 & zi <= zdim2 )
img_slice(x,y) = img(xi,yi,zi);
else
img_slice(x,y) = bg;
end % if boundary
end % for x
end % for y
return; % nearest_neighbor
%--------------------------------------------------------------------
function img_slice = bresenham(img, dim1, dim2, M, bg)
img_slice = zeros(dim1(1:2));
% Dimension of transformed 3D volume
%
xdim1 = dim1(1);
ydim1 = dim1(2);
% Dimension of original 3D volume
%
xdim2 = dim2(1);
ydim2 = dim2(2);
zdim2 = dim2(3);
for y = 1:ydim1
start_old_XYZ = round(M*[0 y 0 1]');
end_old_XYZ = round(M*[xdim1 y 0 1]');
[X Y Z] = bresenham_line3d(start_old_XYZ, end_old_XYZ);
% line error correction
%
% del = end_old_XYZ - start_old_XYZ;
% del_dom = max(del);
% idx_dom = find(del==del_dom);
% idx_dom = idx_dom(1);
% idx_other = [1 2 3];
% idx_other(idx_dom) = [];
%del_x1 = del(idx_other(1));
% del_x2 = del(idx_other(2));
% line_slope = sqrt((del_x1/del_dom)^2 + (del_x2/del_dom)^2 + 1);
% line_error = line_slope - 1;
% line error correction removed because it is too slow
for x = 1:xdim1
% rescale ratio
%
i = round(x * length(X) / xdim1);
if i < 1
i = 1;
elseif i > length(X)
i = length(X);
end
xi = X(i);
yi = Y(i);
zi = Z(i);
% within boundary of the old XYZ space
%
if ( xi >= 1 & xi <= xdim2 & ...
yi >= 1 & yi <= ydim2 & ...
zi >= 1 & zi <= zdim2 )
img_slice(x,y) = img(xi,yi,zi);
% if line_error > 1
% x = x + 1;
% if x <= xdim1
% img_slice(x,y) = img(xi,yi,zi);
% line_error = line_slope - 1;
% end
% end % if line_error
% line error correction removed because it is too slow
else
img_slice(x,y) = bg;
end % if boundary
end % for x
end % for y
return; % bresenham
|
github
|
sunhongfu/scripts-master
|
load_untouch_nii_img.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_untouch_nii_img.m
| 15,224 |
utf_8
|
46fb6696904467f1848e2882cd7a72f6
|
% internal function
% - Jimmy Shen ([email protected])
function [img,hdr] = load_untouch_nii_img(hdr,filetype,fileprefix,machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB,slice_idx)
if ~exist('hdr','var') | ~exist('filetype','var') | ~exist('fileprefix','var') | ~exist('machine','var')
error('Usage: [img,hdr] = load_nii_img(hdr,filetype,fileprefix,machine,[img_idx],[dim5_idx],[dim6_idx],[dim7_idx],[old_RGB],[slice_idx]);');
end
if ~exist('img_idx','var') | isempty(img_idx) | hdr.dime.dim(5)<1
img_idx = [];
end
if ~exist('dim5_idx','var') | isempty(dim5_idx) | hdr.dime.dim(6)<1
dim5_idx = [];
end
if ~exist('dim6_idx','var') | isempty(dim6_idx) | hdr.dime.dim(7)<1
dim6_idx = [];
end
if ~exist('dim7_idx','var') | isempty(dim7_idx) | hdr.dime.dim(8)<1
dim7_idx = [];
end
if ~exist('old_RGB','var') | isempty(old_RGB)
old_RGB = 0;
end
if ~exist('slice_idx','var') | isempty(slice_idx) | hdr.dime.dim(4)<1
slice_idx = [];
end
% check img_idx
%
if ~isempty(img_idx) & ~isnumeric(img_idx)
error('"img_idx" should be a numerical array.');
end
if length(unique(img_idx)) ~= length(img_idx)
error('Duplicate image index in "img_idx"');
end
if ~isempty(img_idx) & (min(img_idx) < 1 | max(img_idx) > hdr.dime.dim(5))
max_range = hdr.dime.dim(5);
if max_range == 1
error(['"img_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"img_idx" should be an integer within the range of [' range '].']);
end
end
% check dim5_idx
%
if ~isempty(dim5_idx) & ~isnumeric(dim5_idx)
error('"dim5_idx" should be a numerical array.');
end
if length(unique(dim5_idx)) ~= length(dim5_idx)
error('Duplicate index in "dim5_idx"');
end
if ~isempty(dim5_idx) & (min(dim5_idx) < 1 | max(dim5_idx) > hdr.dime.dim(6))
max_range = hdr.dime.dim(6);
if max_range == 1
error(['"dim5_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim5_idx" should be an integer within the range of [' range '].']);
end
end
% check dim6_idx
%
if ~isempty(dim6_idx) & ~isnumeric(dim6_idx)
error('"dim6_idx" should be a numerical array.');
end
if length(unique(dim6_idx)) ~= length(dim6_idx)
error('Duplicate index in "dim6_idx"');
end
if ~isempty(dim6_idx) & (min(dim6_idx) < 1 | max(dim6_idx) > hdr.dime.dim(7))
max_range = hdr.dime.dim(7);
if max_range == 1
error(['"dim6_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim6_idx" should be an integer within the range of [' range '].']);
end
end
% check dim7_idx
%
if ~isempty(dim7_idx) & ~isnumeric(dim7_idx)
error('"dim7_idx" should be a numerical array.');
end
if length(unique(dim7_idx)) ~= length(dim7_idx)
error('Duplicate index in "dim7_idx"');
end
if ~isempty(dim7_idx) & (min(dim7_idx) < 1 | max(dim7_idx) > hdr.dime.dim(8))
max_range = hdr.dime.dim(8);
if max_range == 1
error(['"dim7_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim7_idx" should be an integer within the range of [' range '].']);
end
end
% check slice_idx
%
if ~isempty(slice_idx) & ~isnumeric(slice_idx)
error('"slice_idx" should be a numerical array.');
end
if length(unique(slice_idx)) ~= length(slice_idx)
error('Duplicate index in "slice_idx"');
end
if ~isempty(slice_idx) & (min(slice_idx) < 1 | max(slice_idx) > hdr.dime.dim(4))
max_range = hdr.dime.dim(4);
if max_range == 1
error(['"slice_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"slice_idx" should be an integer within the range of [' range '].']);
end
end
[img,hdr] = read_image(hdr,filetype,fileprefix,machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB,slice_idx);
return % load_nii_img
%---------------------------------------------------------------------
function [img,hdr] = read_image(hdr,filetype,fileprefix,machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB,slice_idx)
switch filetype
case {0, 1}
fn = [fileprefix '.img'];
case 2
fn = [fileprefix '.nii'];
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
end
% Set bitpix according to datatype
%
% /*Acceptable values for datatype are*/
%
% 0 None (Unknown bit per voxel) % DT_NONE, DT_UNKNOWN
% 1 Binary (ubit1, bitpix=1) % DT_BINARY
% 2 Unsigned char (uchar or uint8, bitpix=8) % DT_UINT8, NIFTI_TYPE_UINT8
% 4 Signed short (int16, bitpix=16) % DT_INT16, NIFTI_TYPE_INT16
% 8 Signed integer (int32, bitpix=32) % DT_INT32, NIFTI_TYPE_INT32
% 16 Floating point (single or float32, bitpix=32) % DT_FLOAT32, NIFTI_TYPE_FLOAT32
% 32 Complex, 2 float32 (Use float32, bitpix=64) % DT_COMPLEX64, NIFTI_TYPE_COMPLEX64
% 64 Double precision (double or float64, bitpix=64) % DT_FLOAT64, NIFTI_TYPE_FLOAT64
% 128 uint8 RGB (Use uint8, bitpix=24) % DT_RGB24, NIFTI_TYPE_RGB24
% 256 Signed char (schar or int8, bitpix=8) % DT_INT8, NIFTI_TYPE_INT8
% 511 Single RGB (Use float32, bitpix=96) % DT_RGB96, NIFTI_TYPE_RGB96
% 512 Unsigned short (uint16, bitpix=16) % DT_UNINT16, NIFTI_TYPE_UNINT16
% 768 Unsigned integer (uint32, bitpix=32) % DT_UNINT32, NIFTI_TYPE_UNINT32
% 1024 Signed long long (int64, bitpix=64) % DT_INT64, NIFTI_TYPE_INT64
% 1280 Unsigned long long (uint64, bitpix=64) % DT_UINT64, NIFTI_TYPE_UINT64
% 1536 Long double, float128 (Unsupported, bitpix=128) % DT_FLOAT128, NIFTI_TYPE_FLOAT128
% 1792 Complex128, 2 float64 (Use float64, bitpix=128) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
% 2048 Complex256, 2 float128 (Unsupported, bitpix=256) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
%
switch hdr.dime.datatype
case 1,
hdr.dime.bitpix = 1; precision = 'ubit1';
case 2,
hdr.dime.bitpix = 8; precision = 'uint8';
case 4,
hdr.dime.bitpix = 16; precision = 'int16';
case 8,
hdr.dime.bitpix = 32; precision = 'int32';
case 16,
hdr.dime.bitpix = 32; precision = 'float32';
case 32,
hdr.dime.bitpix = 64; precision = 'float32';
case 64,
hdr.dime.bitpix = 64; precision = 'float64';
case 128,
hdr.dime.bitpix = 24; precision = 'uint8';
case 256
hdr.dime.bitpix = 8; precision = 'int8';
case 511
hdr.dime.bitpix = 96; precision = 'float32';
case 512
hdr.dime.bitpix = 16; precision = 'uint16';
case 768
hdr.dime.bitpix = 32; precision = 'uint32';
case 1024
hdr.dime.bitpix = 64; precision = 'int64';
case 1280
hdr.dime.bitpix = 64; precision = 'uint64';
case 1792,
hdr.dime.bitpix = 128; precision = 'float64';
otherwise
error('This datatype is not supported');
end
tmp = hdr.dime.dim(2:end);
tmp(find(tmp < 1)) = 1;
hdr.dime.dim(2:end) = tmp;
% move pointer to the start of image block
%
switch filetype
case {0, 1}
fseek(fid, 0, 'bof');
case 2
fseek(fid, hdr.dime.vox_offset, 'bof');
end
% Load whole image block for old Analyze format or binary image;
% otherwise, load images that are specified in img_idx, dim5_idx,
% dim6_idx, and dim7_idx
%
% For binary image, we have to read all because pos can not be
% seeked in bit and can not be calculated the way below.
%
if hdr.dime.datatype == 1 | isequal(hdr.dime.dim(4:8),ones(1,5)) | ...
(isempty(img_idx) & isempty(dim5_idx) & isempty(dim6_idx) & isempty(dim7_idx) & isempty(slice_idx))
% For each frame, precision of value will be read
% in img_siz times, where img_siz is only the
% dimension size of an image, not the byte storage
% size of an image.
%
img_siz = prod(hdr.dime.dim(2:8));
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img_siz = img_siz * 2;
end
%MPH: For RGB24, voxel values include 3 separate color planes
%
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
img_siz = img_siz * 3;
end
img = fread(fid, img_siz, sprintf('*%s',precision));
d1 = hdr.dime.dim(2);
d2 = hdr.dime.dim(3);
d3 = hdr.dime.dim(4);
d4 = hdr.dime.dim(5);
d5 = hdr.dime.dim(6);
d6 = hdr.dime.dim(7);
d7 = hdr.dime.dim(8);
if isempty(slice_idx)
slice_idx = 1:d3;
end
if isempty(img_idx)
img_idx = 1:d4;
end
if isempty(dim5_idx)
dim5_idx = 1:d5;
end
if isempty(dim6_idx)
dim6_idx = 1:d6;
end
if isempty(dim7_idx)
dim7_idx = 1:d7;
end
else
d1 = hdr.dime.dim(2);
d2 = hdr.dime.dim(3);
d3 = hdr.dime.dim(4);
d4 = hdr.dime.dim(5);
d5 = hdr.dime.dim(6);
d6 = hdr.dime.dim(7);
d7 = hdr.dime.dim(8);
if isempty(slice_idx)
slice_idx = 1:d3;
end
if isempty(img_idx)
img_idx = 1:d4;
end
if isempty(dim5_idx)
dim5_idx = 1:d5;
end
if isempty(dim6_idx)
dim6_idx = 1:d6;
end
if isempty(dim7_idx)
dim7_idx = 1:d7;
end
%ROMAN: begin
roman = 1;
if(roman)
% compute size of one slice
%
img_siz = prod(hdr.dime.dim(2:3));
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img_siz = img_siz * 2;
end
%MPH: For RGB24, voxel values include 3 separate color planes
%
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
img_siz = img_siz * 3;
end
% preallocate img
img = zeros(img_siz, length(slice_idx)*length(img_idx)*length(dim5_idx)*length(dim6_idx)*length(dim7_idx) );
currentIndex = 1;
else
img = [];
end; %if(roman)
% ROMAN: end
for i7=1:length(dim7_idx)
for i6=1:length(dim6_idx)
for i5=1:length(dim5_idx)
for t=1:length(img_idx)
for s=1:length(slice_idx)
% Position is seeked in bytes. To convert dimension size
% to byte storage size, hdr.dime.bitpix/8 will be
% applied.
%
pos = sub2ind([d1 d2 d3 d4 d5 d6 d7], 1, 1, slice_idx(s), ...
img_idx(t), dim5_idx(i5),dim6_idx(i6),dim7_idx(i7)) -1;
pos = pos * hdr.dime.bitpix/8;
% ROMAN: begin
if(roman)
% do nothing
else
img_siz = prod(hdr.dime.dim(2:3));
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img_siz = img_siz * 2;
end
%MPH: For RGB24, voxel values include 3 separate color planes
%
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
img_siz = img_siz * 3;
end
end; % if (roman)
% ROMAN: end
if filetype == 2
fseek(fid, pos + hdr.dime.vox_offset, 'bof');
else
fseek(fid, pos, 'bof');
end
% For each frame, fread will read precision of value
% in img_siz times
%
% ROMAN: begin
if(roman)
img(:,currentIndex) = fread(fid, img_siz, sprintf('*%s',precision));
currentIndex = currentIndex +1;
else
img = [img fread(fid, img_siz, sprintf('*%s',precision))];
end; %if(roman)
% ROMAN: end
end
end
end
end
end
end
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img = reshape(img, [2, length(img)/2]);
img = complex(img(1,:)', img(2,:)');
end
fclose(fid);
% Update the global min and max values
%
hdr.dime.glmax = double(max(img(:)));
hdr.dime.glmin = double(min(img(:)));
% old_RGB treat RGB slice by slice, now it is treated voxel by voxel
%
if old_RGB & hdr.dime.datatype == 128 & hdr.dime.bitpix == 24
% remove squeeze
img = (reshape(img, [hdr.dime.dim(2:3) 3 length(slice_idx) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
img = permute(img, [1 2 4 3 5 6 7 8]);
elseif hdr.dime.datatype == 128 & hdr.dime.bitpix == 24
% remove squeeze
img = (reshape(img, [3 hdr.dime.dim(2:3) length(slice_idx) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
img = permute(img, [2 3 4 1 5 6 7 8]);
elseif hdr.dime.datatype == 511 & hdr.dime.bitpix == 96
img = double(img(:));
img = single((img - min(img))/(max(img) - min(img)));
% remove squeeze
img = (reshape(img, [3 hdr.dime.dim(2:3) length(slice_idx) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
img = permute(img, [2 3 4 1 5 6 7 8]);
else
% remove squeeze
img = (reshape(img, [hdr.dime.dim(2:3) length(slice_idx) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
end
if ~isempty(slice_idx)
hdr.dime.dim(4) = length(slice_idx);
end
if ~isempty(img_idx)
hdr.dime.dim(5) = length(img_idx);
end
if ~isempty(dim5_idx)
hdr.dime.dim(6) = length(dim5_idx);
end
if ~isempty(dim6_idx)
hdr.dime.dim(7) = length(dim6_idx);
end
if ~isempty(dim7_idx)
hdr.dime.dim(8) = length(dim7_idx);
end
return % read_image
|
github
|
sunhongfu/scripts-master
|
load_untouch_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_untouch_nii.m
| 6,373 |
utf_8
|
303eb6438d7d37e2144d554504fbdf54
|
% Load NIFTI or ANALYZE dataset, but not applying any appropriate affine
% geometric transform or voxel intensity scaling.
%
% Although according to NIFTI website, all those header information are
% supposed to be applied to the loaded NIFTI image, there are some
% situations that people do want to leave the original NIFTI header and
% data untouched. They will probably just use MATLAB to do certain image
% processing regardless of image orientation, and to save data back with
% the same NIfTI header.
%
% Since this program is only served for those situations, please use it
% together with "save_untouch_nii.m", and do not use "save_nii.m" or
% "view_nii.m" for the data that is loaded by "load_untouch_nii.m". For
% normal situation, you should use "load_nii.m" instead.
%
% Usage: nii = load_untouch_nii(filename, [img_idx], [dim5_idx], [dim6_idx], ...
% [dim7_idx], [old_RGB], [slice_idx])
%
% filename - NIFTI or ANALYZE file name.
%
% img_idx (optional) - a numerical array of image volume indices.
% Only the specified volumes will be loaded. All available image
% volumes will be loaded, if it is default or empty.
%
% The number of images scans can be obtained from get_nii_frame.m,
% or simply: hdr.dime.dim(5).
%
% dim5_idx (optional) - a numerical array of 5th dimension indices.
% Only the specified range will be loaded. All available range
% will be loaded, if it is default or empty.
%
% dim6_idx (optional) - a numerical array of 6th dimension indices.
% Only the specified range will be loaded. All available range
% will be loaded, if it is default or empty.
%
% dim7_idx (optional) - a numerical array of 7th dimension indices.
% Only the specified range will be loaded. All available range
% will be loaded, if it is default or empty.
%
% old_RGB (optional) - a scale number to tell difference of new RGB24
% from old RGB24. New RGB24 uses RGB triple sequentially for each
% voxel, like [R1 G1 B1 R2 G2 B2 ...]. Analyze 6.0 from AnalyzeDirect
% uses old RGB24, in a way like [R1 R2 ... G1 G2 ... B1 B2 ...] for
% each slices. If the image that you view is garbled, try to set
% old_RGB variable to 1 and try again, because it could be in
% old RGB24. It will be set to 0, if it is default or empty.
%
% slice_idx (optional) - a numerical array of image slice indices.
% Only the specified slices will be loaded. All available image
% slices will be loaded, if it is default or empty.
%
% Returned values:
%
% nii structure:
%
% hdr - struct with NIFTI header fields.
%
% filetype - Analyze format .hdr/.img (0);
% NIFTI .hdr/.img (1);
% NIFTI .nii (2)
%
% fileprefix - NIFTI filename without extension.
%
% machine - machine string variable.
%
% img - 3D (or 4D) matrix of NIFTI data.
%
% - Jimmy Shen ([email protected])
%
function nii = load_untouch_nii(filename, img_idx, dim5_idx, dim6_idx, dim7_idx, ...
old_RGB, slice_idx)
if ~exist('filename','var')
error('Usage: nii = load_untouch_nii(filename, [img_idx], [dim5_idx], [dim6_idx], [dim7_idx], [old_RGB], [slice_idx])');
end
if ~exist('img_idx','var') | isempty(img_idx)
img_idx = [];
end
if ~exist('dim5_idx','var') | isempty(dim5_idx)
dim5_idx = [];
end
if ~exist('dim6_idx','var') | isempty(dim6_idx)
dim6_idx = [];
end
if ~exist('dim7_idx','var') | isempty(dim7_idx)
dim7_idx = [];
end
if ~exist('old_RGB','var') | isempty(old_RGB)
old_RGB = 0;
end
if ~exist('slice_idx','var') | isempty(slice_idx)
slice_idx = [];
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
elseif strcmp(filename(end-6:end), '.img.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.hdr.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.hdr.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.img.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.nii.gz')
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename = gunzip(filename, tmpDir);
filename = char(filename); % convert from cell to string
end
end
% Read the dataset header
%
[nii.hdr,nii.filetype,nii.fileprefix,nii.machine] = load_nii_hdr(filename);
if nii.filetype == 0
nii.hdr = load_untouch0_nii_hdr(nii.fileprefix,nii.machine);
nii.ext = [];
else
nii.hdr = load_untouch_nii_hdr(nii.fileprefix,nii.machine,nii.filetype);
% Read the header extension
%
nii.ext = load_nii_ext(filename);
end
% Read the dataset body
%
[nii.img,nii.hdr] = load_untouch_nii_img(nii.hdr,nii.filetype,nii.fileprefix, ...
nii.machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB,slice_idx);
% Perform some of sform/qform transform
%
% nii = xform_nii(nii, tolerance, preferredForm);
nii.untouch = 1;
% Clean up after gunzip
%
if exist('gzFileName', 'var')
% fix fileprefix so it doesn't point to temp location
%
nii.fileprefix = gzFileName(1:end-7);
rmdir(tmpDir,'s');
end
return % load_untouch_nii
|
github
|
sunhongfu/scripts-master
|
collapse_nii_scan.m
|
.m
|
scripts-master/cs-phase/_src/_nii/collapse_nii_scan.m
| 7,038 |
utf_8
|
2d30d10b884719503df2974ff39b7093
|
% Collapse multiple single-scan NIFTI files into a multiple-scan NIFTI file
%
% Usage: collapse_nii_scan(scan_file_pattern, [collapsed_fileprefix], [scan_file_folder])
%
% Here, scan_file_pattern should look like: 'myscan_0*.img'
% If collapsed_fileprefix is omit, 'multi_scan' will be used
% If scan_file_folder is omit, current file folder will be used
%
% The order of volumes in the collapsed file will be the order of
% corresponding filenames for those selected scan files.
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function collapse_nii_scan(scan_pattern, fileprefix, scan_path)
if ~exist('fileprefix','var')
fileprefix = 'multi_scan';
else
[tmp fileprefix] = fileparts(fileprefix);
end
if ~exist('scan_path','var'), scan_path = pwd; end
pnfn = fullfile(scan_path, scan_pattern);
file_lst = dir(pnfn);
flist = {file_lst.name};
flist = flist(:);
filename = flist{1};
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
else
gzFile = 1;
end
else
if ~strcmp(filename(end-3:end), '.img') & ...
~strcmp(filename(end-3:end), '.hdr') & ...
~strcmp(filename(end-3:end), '.nii')
error('Please check filename.');
end
end
nii = load_untouch_nii(fullfile(scan_path,filename));
nii.hdr.dime.dim(5) = length(flist);
if nii.hdr.dime.dim(1) < 4
nii.hdr.dime.dim(1) = 4;
end
hdr = nii.hdr;
filetype = nii.filetype;
if isfield(nii,'ext') & ~isempty(nii.ext)
ext = nii.ext;
[ext, esize_total] = verify_nii_ext(ext);
else
ext = [];
end
switch double(hdr.dime.datatype),
case 1,
hdr.dime.bitpix = int16(1 ); precision = 'ubit1';
case 2,
hdr.dime.bitpix = int16(8 ); precision = 'uint8';
case 4,
hdr.dime.bitpix = int16(16); precision = 'int16';
case 8,
hdr.dime.bitpix = int16(32); precision = 'int32';
case 16,
hdr.dime.bitpix = int16(32); precision = 'float32';
case 32,
hdr.dime.bitpix = int16(64); precision = 'float32';
case 64,
hdr.dime.bitpix = int16(64); precision = 'float64';
case 128,
hdr.dime.bitpix = int16(24); precision = 'uint8';
case 256
hdr.dime.bitpix = int16(8 ); precision = 'int8';
case 512
hdr.dime.bitpix = int16(16); precision = 'uint16';
case 768
hdr.dime.bitpix = int16(32); precision = 'uint32';
case 1024
hdr.dime.bitpix = int16(64); precision = 'int64';
case 1280
hdr.dime.bitpix = int16(64); precision = 'uint64';
case 1792,
hdr.dime.bitpix = int16(128); precision = 'float64';
otherwise
error('This datatype is not supported');
end
if filetype == 2
fid = fopen(sprintf('%s.nii',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.nii.',fileprefix);
error(msg);
end
hdr.dime.vox_offset = 352;
if ~isempty(ext)
hdr.dime.vox_offset = hdr.dime.vox_offset + esize_total;
end
hdr.hist.magic = 'n+1';
save_untouch_nii_hdr(hdr, fid);
if ~isempty(ext)
save_nii_ext(ext, fid);
end
elseif filetype == 1
fid = fopen(sprintf('%s.hdr',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.hdr.',fileprefix);
error(msg);
end
hdr.dime.vox_offset = 0;
hdr.hist.magic = 'ni1';
save_untouch_nii_hdr(hdr, fid);
if ~isempty(ext)
save_nii_ext(ext, fid);
end
fclose(fid);
fid = fopen(sprintf('%s.img',fileprefix),'w');
else
fid = fopen(sprintf('%s.hdr',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.hdr.',fileprefix);
error(msg);
end
save_untouch0_nii_hdr(hdr, fid);
fclose(fid);
fid = fopen(sprintf('%s.img',fileprefix),'w');
end
if filetype == 2 & isempty(ext)
skip_bytes = double(hdr.dime.vox_offset) - 348;
else
skip_bytes = 0;
end
if skip_bytes
fwrite(fid, zeros(1,skip_bytes), 'uint8');
end
glmax = -inf;
glmin = inf;
for i = 1:length(flist)
nii = load_untouch_nii(fullfile(scan_path,flist{i}));
if double(hdr.dime.datatype) == 128
% RGB planes are expected to be in the 4th dimension of nii.img
%
if(size(nii.img,4)~=3)
error(['The NII structure does not appear to have 3 RGB color planes in the 4th dimension']);
end
nii.img = permute(nii.img, [4 1 2 3 5 6 7 8]);
end
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
real_img = real(nii.img(:))';
nii.img = imag(nii.img(:))';
nii.img = [real_img; nii.img];
end
if nii.hdr.dime.glmax > glmax
glmax = nii.hdr.dime.glmax;
end
if nii.hdr.dime.glmin < glmin
glmin = nii.hdr.dime.glmin;
end
fwrite(fid, nii.img, precision);
end
hdr.dime.glmax = round(glmax);
hdr.dime.glmin = round(glmin);
if filetype == 2
fseek(fid, 140, 'bof');
fwrite(fid, hdr.dime.glmax, 'int32');
fwrite(fid, hdr.dime.glmin, 'int32');
elseif filetype == 1
fid2 = fopen(sprintf('%s.hdr',fileprefix),'w');
if fid2 < 0,
msg = sprintf('Cannot open file %s.hdr.',fileprefix);
error(msg);
end
save_untouch_nii_hdr(hdr, fid2);
if ~isempty(ext)
save_nii_ext(ext, fid2);
end
fclose(fid2);
else
fid2 = fopen(sprintf('%s.hdr',fileprefix),'w');
if fid2 < 0,
msg = sprintf('Cannot open file %s.hdr.',fileprefix);
error(msg);
end
save_untouch0_nii_hdr(hdr, fid2);
fclose(fid2);
end
fclose(fid);
% gzip output file if requested
%
if exist('gzFile', 'var')
if filetype == 1
gzip([fileprefix, '.img']);
delete([fileprefix, '.img']);
gzip([fileprefix, '.hdr']);
delete([fileprefix, '.hdr']);
elseif filetype == 2
gzip([fileprefix, '.nii']);
delete([fileprefix, '.nii']);
end;
end;
return; % collapse_nii_scan
|
github
|
sunhongfu/scripts-master
|
rri_orient_ui.m
|
.m
|
scripts-master/cs-phase/_src/_nii/rri_orient_ui.m
| 5,635 |
utf_8
|
3361ce417798ffe2c6b53cf194b2a146
|
% Return orientation of the current image:
% orient is orientation 1x3 matrix, in that:
% Three elements represent: [x y z]
% Element value: 1 - Left to Right; 2 - Posterior to Anterior;
% 3 - Inferior to Superior; 4 - Right to Left;
% 5 - Anterior to Posterior; 6 - Superior to Inferior;
% e.g.:
% Standard RAS Orientation: [1 2 3]
% Standard RHOS Orientation: [2 4 3]
% Jimmy Shen ([email protected]), 26-APR-04
%
function orient = rri_orient_ui(varargin)
if nargin == 0
init;
orient_ui_fig = gcf;
uiwait; % wait for user finish
orient = getappdata(gcf, 'orient');
if isempty(orient)
orient = [1 2 3];
end
if ishandle(orient_ui_fig)
close(gcf);
end
return;
end
action = varargin{1};
if strcmp(action, 'done')
click_done;
elseif strcmp(action, 'cancel')
uiresume;
end
return; % rri_orient_ui
%----------------------------------------------------------------------
function init
save_setting_status = 'on';
rri_orient_pos = [];
try
load('pls_profile');
catch
end
try
load('rri_pos_profile');
catch
end
if ~isempty(rri_orient_pos) & strcmp(save_setting_status,'on')
pos = rri_orient_pos;
else
w = 0.35;
h = 0.4;
x = (1-w)/2;
y = (1-h)/2;
pos = [x y w h];
end
handles.figure = figure('Color',[0.8 0.8 0.8], ...
'Units','normal', ...
'Name', 'Convert to standard RAS orientation', ...
'NumberTitle','off', ...
'MenuBar','none', ...
'Position',pos, ...
'WindowStyle', 'normal', ...
'ToolBar','none');
h0 = handles.figure;
Font.FontUnits = 'point';
Font.FontSize = 12;
margin = .1;
line_num = 6;
line_ht = (1 - margin*2) / line_num;
x = margin;
y = 1 - margin - line_ht;
w = 1 - margin * 2;
h = line_ht * .7;
pos = [x y w h];
handles.Ttit = uicontrol('parent', h0, ...
'style','text', ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','left',...
'background', [0.8 0.8 0.8], ...
'string', 'Please input orientation of the current image:');
y = y - line_ht;
w = .2;
pos = [x y w h];
handles.Tx_orient = uicontrol('parent', h0, ...
'style','text', ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','left',...
'background', [0.8 0.8 0.8], ...
'string', 'X Axes:');
y = y - line_ht;
pos = [x y w h];
handles.Ty_orient = uicontrol('parent', h0, ...
'style','text', ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','left',...
'background', [0.8 0.8 0.8], ...
'string', 'Y Axes:');
y = y - line_ht;
pos = [x y w h];
handles.Tz_orient = uicontrol('parent', h0, ...
'style','text', ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','left',...
'background', [0.8 0.8 0.8], ...
'string', 'Z Axes:');
choice = { 'From Left to Right', 'From Posterior to Anterior', ...
'From Inferior to Superior', 'From Right to Left', ...
'From Anterior to Posterior', 'From Superior to Inferior' };
y = 1 - margin - line_ht;
y = y - line_ht;
w = 1 - margin - x - w;
x = 1 - margin - w;
pos = [x y w h];
handles.x_orient = uicontrol('parent', h0, ...
'style','popupmenu', ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','left',...
'string', choice, ...
'value', 1, ...
'background', [1 1 1]);
y = y - line_ht;
pos = [x y w h];
handles.y_orient = uicontrol('parent', h0, ...
'style','popupmenu', ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','left',...
'string', choice, ...
'value', 2, ...
'background', [1 1 1]);
y = y - line_ht;
pos = [x y w h];
handles.z_orient = uicontrol('parent', h0, ...
'style','popupmenu', ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','left',...
'string', choice, ...
'value', 3, ...
'background', [1 1 1]);
x = margin;
y = y - line_ht * 1.5;
w = .3;
pos = [x y w h];
handles.done = uicontrol('parent', h0, ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','center',...
'callback', 'rri_orient_ui(''done'');', ...
'string', 'Done');
x = 1 - margin - w;
pos = [x y w h];
handles.cancel = uicontrol('parent', h0, ...
'unit', 'normal', ...
Font, ...
'Position',pos, ...
'HorizontalAlignment','center',...
'callback', 'rri_orient_ui(''cancel'');', ...
'string', 'Cancel');
setappdata(h0, 'handles', handles);
setappdata(h0, 'orient', [1 2 3]);
return; % init
%----------------------------------------------------------------------
function click_done
handles = getappdata(gcf, 'handles');
x_orient = get(handles.x_orient, 'value');
y_orient = get(handles.y_orient, 'value');
z_orient = get(handles.z_orient, 'value');
orient = [x_orient y_orient z_orient];
test_orient = [orient, orient + 3];
test_orient = mod(test_orient, 3);
if length(unique(test_orient)) ~= 3
msgbox('Please don''t choose same or opposite direction','Error','modal');
return;
end
setappdata(gcf, 'orient', [x_orient y_orient z_orient]);
uiresume;
return; % click_done
|
github
|
sunhongfu/scripts-master
|
load_untouch0_nii_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_untouch0_nii_hdr.m
| 8,293 |
utf_8
|
d823050e9ba931a2ba7f9d9a3893d2d1
|
% internal function
% - Jimmy Shen ([email protected])
function hdr = load_nii_hdr(fileprefix, machine)
fn = sprintf('%s.hdr',fileprefix);
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
fseek(fid,0,'bof');
hdr = read_header(fid);
fclose(fid);
end
return % load_nii_hdr
%---------------------------------------------------------------------
function [ dsr ] = read_header(fid)
% Original header structures
% struct dsr
% {
% struct header_key hk; /* 0 + 40 */
% struct image_dimension dime; /* 40 + 108 */
% struct data_history hist; /* 148 + 200 */
% }; /* total= 348 bytes*/
dsr.hk = header_key(fid);
dsr.dime = image_dimension(fid);
dsr.hist = data_history(fid);
return % read_header
%---------------------------------------------------------------------
function [ hk ] = header_key(fid)
fseek(fid,0,'bof');
% Original header structures
% struct header_key /* header key */
% { /* off + size */
% int sizeof_hdr /* 0 + 4 */
% char data_type[10]; /* 4 + 10 */
% char db_name[18]; /* 14 + 18 */
% int extents; /* 32 + 4 */
% short int session_error; /* 36 + 2 */
% char regular; /* 38 + 1 */
% char hkey_un0; /* 39 + 1 */
% }; /* total=40 bytes */
%
% int sizeof_header Should be 348.
% char regular Must be 'r' to indicate that all images and
% volumes are the same size.
v6 = version;
if str2num(v6(1))<6
directchar = '*char';
else
directchar = 'uchar=>char';
end
hk.sizeof_hdr = fread(fid, 1,'int32')'; % should be 348!
hk.data_type = deblank(fread(fid,10,directchar)');
hk.db_name = deblank(fread(fid,18,directchar)');
hk.extents = fread(fid, 1,'int32')';
hk.session_error = fread(fid, 1,'int16')';
hk.regular = fread(fid, 1,directchar)';
hk.hkey_un0 = fread(fid, 1,directchar)';
return % header_key
%---------------------------------------------------------------------
function [ dime ] = image_dimension(fid)
%struct image_dimension
% { /* off + size */
% short int dim[8]; /* 0 + 16 */
% /*
% dim[0] Number of dimensions in database; usually 4.
% dim[1] Image X dimension; number of *pixels* in an image row.
% dim[2] Image Y dimension; number of *pixel rows* in slice.
% dim[3] Volume Z dimension; number of *slices* in a volume.
% dim[4] Time points; number of volumes in database
% */
% char vox_units[4]; /* 16 + 4 */
% char cal_units[8]; /* 20 + 8 */
% short int unused1; /* 28 + 2 */
% short int datatype; /* 30 + 2 */
% short int bitpix; /* 32 + 2 */
% short int dim_un0; /* 34 + 2 */
% float pixdim[8]; /* 36 + 32 */
% /*
% pixdim[] specifies the voxel dimensions:
% pixdim[1] - voxel width, mm
% pixdim[2] - voxel height, mm
% pixdim[3] - slice thickness, mm
% pixdim[4] - volume timing, in msec
% ..etc
% */
% float vox_offset; /* 68 + 4 */
% float roi_scale; /* 72 + 4 */
% float funused1; /* 76 + 4 */
% float funused2; /* 80 + 4 */
% float cal_max; /* 84 + 4 */
% float cal_min; /* 88 + 4 */
% int compressed; /* 92 + 4 */
% int verified; /* 96 + 4 */
% int glmax; /* 100 + 4 */
% int glmin; /* 104 + 4 */
% }; /* total=108 bytes */
v6 = version;
if str2num(v6(1))<6
directchar = '*char';
else
directchar = 'uchar=>char';
end
dime.dim = fread(fid,8,'int16')';
dime.vox_units = deblank(fread(fid,4,directchar)');
dime.cal_units = deblank(fread(fid,8,directchar)');
dime.unused1 = fread(fid,1,'int16')';
dime.datatype = fread(fid,1,'int16')';
dime.bitpix = fread(fid,1,'int16')';
dime.dim_un0 = fread(fid,1,'int16')';
dime.pixdim = fread(fid,8,'float32')';
dime.vox_offset = fread(fid,1,'float32')';
dime.roi_scale = fread(fid,1,'float32')';
dime.funused1 = fread(fid,1,'float32')';
dime.funused2 = fread(fid,1,'float32')';
dime.cal_max = fread(fid,1,'float32')';
dime.cal_min = fread(fid,1,'float32')';
dime.compressed = fread(fid,1,'int32')';
dime.verified = fread(fid,1,'int32')';
dime.glmax = fread(fid,1,'int32')';
dime.glmin = fread(fid,1,'int32')';
return % image_dimension
%---------------------------------------------------------------------
function [ hist ] = data_history(fid)
%struct data_history
% { /* off + size */
% char descrip[80]; /* 0 + 80 */
% char aux_file[24]; /* 80 + 24 */
% char orient; /* 104 + 1 */
% char originator[10]; /* 105 + 10 */
% char generated[10]; /* 115 + 10 */
% char scannum[10]; /* 125 + 10 */
% char patient_id[10]; /* 135 + 10 */
% char exp_date[10]; /* 145 + 10 */
% char exp_time[10]; /* 155 + 10 */
% char hist_un0[3]; /* 165 + 3 */
% int views /* 168 + 4 */
% int vols_added; /* 172 + 4 */
% int start_field; /* 176 + 4 */
% int field_skip; /* 180 + 4 */
% int omax; /* 184 + 4 */
% int omin; /* 188 + 4 */
% int smax; /* 192 + 4 */
% int smin; /* 196 + 4 */
% }; /* total=200 bytes */
v6 = version;
if str2num(v6(1))<6
directchar = '*char';
else
directchar = 'uchar=>char';
end
hist.descrip = deblank(fread(fid,80,directchar)');
hist.aux_file = deblank(fread(fid,24,directchar)');
hist.orient = fread(fid, 1,'char')';
hist.originator = fread(fid, 5,'int16')';
hist.generated = deblank(fread(fid,10,directchar)');
hist.scannum = deblank(fread(fid,10,directchar)');
hist.patient_id = deblank(fread(fid,10,directchar)');
hist.exp_date = deblank(fread(fid,10,directchar)');
hist.exp_time = deblank(fread(fid,10,directchar)');
hist.hist_un0 = deblank(fread(fid, 3,directchar)');
hist.views = fread(fid, 1,'int32')';
hist.vols_added = fread(fid, 1,'int32')';
hist.start_field = fread(fid, 1,'int32')';
hist.field_skip = fread(fid, 1,'int32')';
hist.omax = fread(fid, 1,'int32')';
hist.omin = fread(fid, 1,'int32')';
hist.smax = fread(fid, 1,'int32')';
hist.smin = fread(fid, 1,'int32')';
return % data_history
|
github
|
sunhongfu/scripts-master
|
load_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_nii.m
| 7,006 |
utf_8
|
71beffc9e2b0c7e14c2f8dc8adbadbf1
|
% Load NIFTI or ANALYZE dataset. Support both *.nii and *.hdr/*.img
% file extension. If file extension is not provided, *.hdr/*.img will
% be used as default.
%
% A subset of NIFTI transform is included. For non-orthogonal rotation,
% shearing etc., please use 'reslice_nii.m' to reslice the NIFTI file.
% It will not cause negative effect, as long as you remember not to do
% slice time correction after reslicing the NIFTI file. Output variable
% nii will be in RAS orientation, i.e. X axis from Left to Right,
% Y axis from Posterior to Anterior, and Z axis from Inferior to
% Superior.
%
% Usage: nii = load_nii(filename, [img_idx], [dim5_idx], [dim6_idx], ...
% [dim7_idx], [old_RGB], [tolerance], [preferredForm])
%
% filename - NIFTI or ANALYZE file name.
%
% img_idx (optional) - a numerical array of 4th dimension indices,
% which is the indices of image scan volume. The number of images
% scan volumes can be obtained from get_nii_frame.m, or simply
% hdr.dime.dim(5). Only the specified volumes will be loaded.
% All available image volumes will be loaded, if it is default or
% empty.
%
% dim5_idx (optional) - a numerical array of 5th dimension indices.
% Only the specified range will be loaded. All available range
% will be loaded, if it is default or empty.
%
% dim6_idx (optional) - a numerical array of 6th dimension indices.
% Only the specified range will be loaded. All available range
% will be loaded, if it is default or empty.
%
% dim7_idx (optional) - a numerical array of 7th dimension indices.
% Only the specified range will be loaded. All available range
% will be loaded, if it is default or empty.
%
% old_RGB (optional) - a scale number to tell difference of new RGB24
% from old RGB24. New RGB24 uses RGB triple sequentially for each
% voxel, like [R1 G1 B1 R2 G2 B2 ...]. Analyze 6.0 from AnalyzeDirect
% uses old RGB24, in a way like [R1 R2 ... G1 G2 ... B1 B2 ...] for
% each slices. If the image that you view is garbled, try to set
% old_RGB variable to 1 and try again, because it could be in
% old RGB24. It will be set to 0, if it is default or empty.
%
% tolerance (optional) - distortion allowed in the loaded image for any
% non-orthogonal rotation or shearing of NIfTI affine matrix. If
% you set 'tolerance' to 0, it means that you do not allow any
% distortion. If you set 'tolerance' to 1, it means that you do
% not care any distortion. The image will fail to be loaded if it
% can not be tolerated. The tolerance will be set to 0.1 (10%), if
% it is default or empty.
%
% preferredForm (optional) - selects which transformation from voxels
% to RAS coordinates; values are s,q,S,Q. Lower case s,q indicate
% "prefer sform or qform, but use others if preferred not present".
% Upper case indicate the program is forced to use the specificied
% tranform or fail loading. 'preferredForm' will be 's', if it is
% default or empty. - Jeff Gunter
%
% Returned values:
%
% nii structure:
%
% hdr - struct with NIFTI header fields.
%
% filetype - Analyze format .hdr/.img (0);
% NIFTI .hdr/.img (1);
% NIFTI .nii (2)
%
% fileprefix - NIFTI filename without extension.
%
% machine - machine string variable.
%
% img - 3D (or 4D) matrix of NIFTI data.
%
% original - the original header before any affine transform.
%
% Part of this file is copied and modified from:
% http://www.mathworks.com/matlabcentral/fileexchange/1878-mri-analyze-tools
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function nii = load_nii(filename, img_idx, dim5_idx, dim6_idx, dim7_idx, ...
old_RGB, tolerance, preferredForm)
if ~exist('filename','var')
error('Usage: nii = load_nii(filename, [img_idx], [dim5_idx], [dim6_idx], [dim7_idx], [old_RGB], [tolerance], [preferredForm])');
end
if ~exist('img_idx','var') | isempty(img_idx)
img_idx = [];
end
if ~exist('dim5_idx','var') | isempty(dim5_idx)
dim5_idx = [];
end
if ~exist('dim6_idx','var') | isempty(dim6_idx)
dim6_idx = [];
end
if ~exist('dim7_idx','var') | isempty(dim7_idx)
dim7_idx = [];
end
if ~exist('old_RGB','var') | isempty(old_RGB)
old_RGB = 0;
end
if ~exist('tolerance','var') | isempty(tolerance)
tolerance = 0.1; % 10 percent
end
if ~exist('preferredForm','var') | isempty(preferredForm)
preferredForm= 's'; % Jeff
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
elseif strcmp(filename(end-6:end), '.img.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.hdr.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.hdr.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.img.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.nii.gz')
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename = gunzip(filename, tmpDir);
filename = char(filename); % convert from cell to string
end
end
% Read the dataset header
%
[nii.hdr,nii.filetype,nii.fileprefix,nii.machine] = load_nii_hdr(filename);
% Read the header extension
%
% nii.ext = load_nii_ext(filename);
% Read the dataset body
%
[nii.img,nii.hdr] = load_nii_img(nii.hdr,nii.filetype,nii.fileprefix, ...
nii.machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB);
% Perform some of sform/qform transform
%
nii = xform_nii(nii, tolerance, preferredForm);
% Clean up after gunzip
%
if exist('gzFileName', 'var')
% fix fileprefix so it doesn't point to temp location
%
nii.fileprefix = gzFileName(1:end-7);
rmdir(tmpDir,'s');
end
return % load_nii
|
github
|
sunhongfu/scripts-master
|
unxform_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/unxform_nii.m
| 1,221 |
utf_8
|
ff8be64760837046b931857d59ca304e
|
% Undo the flipping and rotations performed by xform_nii; spit back only
% the raw img data block. Initial cut will only deal with 3D volumes
% strongly assume we have called xform_nii to write down the steps used
% in xform_nii.
%
% Usage: a = load_nii('original_name');
% manipulate a.img to make array b;
%
% if you use unxform_nii to un-tranform the image (img) data
% block, then nii.original.hdr is the corresponding header.
%
% nii.original.img = unxform_nii(a, b);
% save_nii(nii.original,'newname');
%
% Where, 'newname' is created with data in the same space as the
% original_name data
%
% - Jeff Gunter, 26-JUN-06
%
function outblock = unxform_nii(nii, inblock)
if isempty(nii.hdr.hist.rot_orient)
outblock=inblock;
else
[dummy unrotate_orient] = sort(nii.hdr.hist.rot_orient);
outblock = permute(inblock, unrotate_orient);
end
if ~isempty(nii.hdr.hist.flip_orient)
flip_orient = nii.hdr.hist.flip_orient(unrotate_orient);
for i = 1:3
if flip_orient(i)
outblock = flipdim(outblock, i);
end
end
end;
return;
|
github
|
sunhongfu/scripts-master
|
load_untouch_nii_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_untouch_nii_hdr.m
| 8,739 |
utf_8
|
eb068c88e2b7bb518ea557d0734bc65d
|
% internal function
% - Jimmy Shen ([email protected])
function hdr = load_nii_hdr(fileprefix, machine, filetype)
if filetype == 2
fn = sprintf('%s.nii',fileprefix);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.nii".', fileprefix);
error(msg);
end
else
fn = sprintf('%s.hdr',fileprefix);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.hdr".', fileprefix);
error(msg);
end
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
fseek(fid,0,'bof');
hdr = read_header(fid);
fclose(fid);
end
return % load_nii_hdr
%---------------------------------------------------------------------
function [ dsr ] = read_header(fid)
% Original header structures
% struct dsr
% {
% struct header_key hk; /* 0 + 40 */
% struct image_dimension dime; /* 40 + 108 */
% struct data_history hist; /* 148 + 200 */
% }; /* total= 348 bytes*/
dsr.hk = header_key(fid);
dsr.dime = image_dimension(fid);
dsr.hist = data_history(fid);
% For Analyze data format
%
if ~strcmp(dsr.hist.magic, 'n+1') & ~strcmp(dsr.hist.magic, 'ni1')
dsr.hist.qform_code = 0;
dsr.hist.sform_code = 0;
end
return % read_header
%---------------------------------------------------------------------
function [ hk ] = header_key(fid)
fseek(fid,0,'bof');
% Original header structures
% struct header_key /* header key */
% { /* off + size */
% int sizeof_hdr /* 0 + 4 */
% char data_type[10]; /* 4 + 10 */
% char db_name[18]; /* 14 + 18 */
% int extents; /* 32 + 4 */
% short int session_error; /* 36 + 2 */
% char regular; /* 38 + 1 */
% char dim_info; % char hkey_un0; /* 39 + 1 */
% }; /* total=40 bytes */
%
% int sizeof_header Should be 348.
% char regular Must be 'r' to indicate that all images and
% volumes are the same size.
v6 = version;
if str2num(v6(1))<6
directchar = '*char';
else
directchar = 'uchar=>char';
end
hk.sizeof_hdr = fread(fid, 1,'int32')'; % should be 348!
hk.data_type = deblank(fread(fid,10,directchar)');
hk.db_name = deblank(fread(fid,18,directchar)');
hk.extents = fread(fid, 1,'int32')';
hk.session_error = fread(fid, 1,'int16')';
hk.regular = fread(fid, 1,directchar)';
hk.dim_info = fread(fid, 1,'uchar')';
return % header_key
%---------------------------------------------------------------------
function [ dime ] = image_dimension(fid)
% Original header structures
% struct image_dimension
% { /* off + size */
% short int dim[8]; /* 0 + 16 */
% /*
% dim[0] Number of dimensions in database; usually 4.
% dim[1] Image X dimension; number of *pixels* in an image row.
% dim[2] Image Y dimension; number of *pixel rows* in slice.
% dim[3] Volume Z dimension; number of *slices* in a volume.
% dim[4] Time points; number of volumes in database
% */
% float intent_p1; % char vox_units[4]; /* 16 + 4 */
% float intent_p2; % char cal_units[8]; /* 20 + 4 */
% float intent_p3; % char cal_units[8]; /* 24 + 4 */
% short int intent_code; % short int unused1; /* 28 + 2 */
% short int datatype; /* 30 + 2 */
% short int bitpix; /* 32 + 2 */
% short int slice_start; % short int dim_un0; /* 34 + 2 */
% float pixdim[8]; /* 36 + 32 */
% /*
% pixdim[] specifies the voxel dimensions:
% pixdim[1] - voxel width, mm
% pixdim[2] - voxel height, mm
% pixdim[3] - slice thickness, mm
% pixdim[4] - volume timing, in msec
% ..etc
% */
% float vox_offset; /* 68 + 4 */
% float scl_slope; % float roi_scale; /* 72 + 4 */
% float scl_inter; % float funused1; /* 76 + 4 */
% short slice_end; % float funused2; /* 80 + 2 */
% char slice_code; % float funused2; /* 82 + 1 */
% char xyzt_units; % float funused2; /* 83 + 1 */
% float cal_max; /* 84 + 4 */
% float cal_min; /* 88 + 4 */
% float slice_duration; % int compressed; /* 92 + 4 */
% float toffset; % int verified; /* 96 + 4 */
% int glmax; /* 100 + 4 */
% int glmin; /* 104 + 4 */
% }; /* total=108 bytes */
dime.dim = fread(fid,8,'int16')';
dime.intent_p1 = fread(fid,1,'float32')';
dime.intent_p2 = fread(fid,1,'float32')';
dime.intent_p3 = fread(fid,1,'float32')';
dime.intent_code = fread(fid,1,'int16')';
dime.datatype = fread(fid,1,'int16')';
dime.bitpix = fread(fid,1,'int16')';
dime.slice_start = fread(fid,1,'int16')';
dime.pixdim = fread(fid,8,'float32')';
dime.vox_offset = fread(fid,1,'float32')';
dime.scl_slope = fread(fid,1,'float32')';
dime.scl_inter = fread(fid,1,'float32')';
dime.slice_end = fread(fid,1,'int16')';
dime.slice_code = fread(fid,1,'uchar')';
dime.xyzt_units = fread(fid,1,'uchar')';
dime.cal_max = fread(fid,1,'float32')';
dime.cal_min = fread(fid,1,'float32')';
dime.slice_duration = fread(fid,1,'float32')';
dime.toffset = fread(fid,1,'float32')';
dime.glmax = fread(fid,1,'int32')';
dime.glmin = fread(fid,1,'int32')';
return % image_dimension
%---------------------------------------------------------------------
function [ hist ] = data_history(fid)
% Original header structures
% struct data_history
% { /* off + size */
% char descrip[80]; /* 0 + 80 */
% char aux_file[24]; /* 80 + 24 */
% short int qform_code; /* 104 + 2 */
% short int sform_code; /* 106 + 2 */
% float quatern_b; /* 108 + 4 */
% float quatern_c; /* 112 + 4 */
% float quatern_d; /* 116 + 4 */
% float qoffset_x; /* 120 + 4 */
% float qoffset_y; /* 124 + 4 */
% float qoffset_z; /* 128 + 4 */
% float srow_x[4]; /* 132 + 16 */
% float srow_y[4]; /* 148 + 16 */
% float srow_z[4]; /* 164 + 16 */
% char intent_name[16]; /* 180 + 16 */
% char magic[4]; % int smin; /* 196 + 4 */
% }; /* total=200 bytes */
v6 = version;
if str2num(v6(1))<6
directchar = '*char';
else
directchar = 'uchar=>char';
end
hist.descrip = deblank(fread(fid,80,directchar)');
hist.aux_file = deblank(fread(fid,24,directchar)');
hist.qform_code = fread(fid,1,'int16')';
hist.sform_code = fread(fid,1,'int16')';
hist.quatern_b = fread(fid,1,'float32')';
hist.quatern_c = fread(fid,1,'float32')';
hist.quatern_d = fread(fid,1,'float32')';
hist.qoffset_x = fread(fid,1,'float32')';
hist.qoffset_y = fread(fid,1,'float32')';
hist.qoffset_z = fread(fid,1,'float32')';
hist.srow_x = fread(fid,4,'float32')';
hist.srow_y = fread(fid,4,'float32')';
hist.srow_z = fread(fid,4,'float32')';
hist.intent_name = deblank(fread(fid,16,directchar)');
hist.magic = deblank(fread(fid,4,directchar)');
return % data_history
|
github
|
sunhongfu/scripts-master
|
save_nii_ext.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_nii_ext.m
| 1,015 |
utf_8
|
db919f3a7a4b2f64dae641b1e97fa4a0
|
% Save NIFTI header extension.
%
% Usage: save_nii_ext(ext, fid)
%
% ext - struct with NIFTI header extension fields.
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function save_nii_ext(ext, fid)
if ~exist('ext','var') | ~exist('fid','var')
error('Usage: save_nii_ext(ext, fid)');
end
if ~isfield(ext,'extension') | ~isfield(ext,'section') | ~isfield(ext,'num_ext')
error('Wrong header extension');
end
write_ext(ext, fid);
return; % save_nii_ext
%---------------------------------------------------------------------
function write_ext(ext, fid)
fwrite(fid, ext.extension, 'uchar');
for i=1:ext.num_ext
fwrite(fid, ext.section(i).esize, 'int32');
fwrite(fid, ext.section(i).ecode, 'int32');
fwrite(fid, ext.section(i).edata, 'uchar');
end
return; % write_ext
|
github
|
sunhongfu/scripts-master
|
view_nii_menu.m
|
.m
|
scripts-master/cs-phase/_src/_nii/view_nii_menu.m
| 14,895 |
utf_8
|
d81fb80884a14ae659630258fbc330bc
|
% Imbed Zoom, Interp, and Info menu to view_nii window.
%
% Usage: view_nii_menu(fig);
%
% - Jimmy Shen ([email protected])
%
%--------------------------------------------------------------------
function menu_hdl = view_nii_menu(fig, varargin)
if isnumeric(fig)
menu_hdl = init(fig);
return;
end
menu_hdl = [];
switch fig
case 'interp'
if nargin > 1
fig = varargin{1};
else
fig = gcbf;
end
nii_menu = getappdata(fig, 'nii_menu');
interp_on_state = get(nii_menu.Minterp,'Userdata');
if (interp_on_state == 1)
opt.useinterp = 1;
view_nii(fig,opt);
set(nii_menu.Minterp,'Userdata',0,'Label','Interp off');
reset_zoom(fig);
else
opt.useinterp = 0;
view_nii(fig,opt);
set(nii_menu.Minterp,'Userdata',1,'Label','Interp on');
reset_zoom(fig);
end
case 'reset_zoom'
if nargin > 1
fig = varargin{1};
else
fig = gcbf;
end
reset_zoom(fig);
case 'orient'
orient;
case 'editvox'
editvox;
case 'img_info'
img_info;
case 'img_hist'
img_hist;
case 'save_disp'
save_disp;
end
return % view_nii_menu
%--------------------------------------------------------------------
function menu_hdl = init(fig)
% search for edit, view menu
%
nii_menu.Mfile = [];
nii_menu.Medit = [];
nii_menu.Mview = [];
menuitems = findobj(fig, 'type', 'uimenu');
for i=1:length(menuitems)
filelabel = get(menuitems(i),'label');
if strcmpi(strrep(filelabel, '&', ''), 'file')
nii_menu.Mfile = menuitems(i);
end
editlabel = get(menuitems(i),'label');
if strcmpi(strrep(editlabel, '&', ''), 'edit')
nii_menu.Medit = menuitems(i);
end
viewlabel = get(menuitems(i),'label');
if strcmpi(strrep(viewlabel, '&', ''), 'view')
nii_menu.Mview = menuitems(i);
end
end
set(fig, 'menubar', 'none');
if isempty(nii_menu.Mfile)
nii_menu.Mfile = uimenu('Parent',fig, ...
'Label','File');
nii_menu.Mfile_save = uimenu('Parent',nii_menu.Mfile, ...
'Label','Save displayed image as ...', ...
'Callback','view_nii_menu(''save_disp'');');
else
nii_menu.Mfile_save = uimenu('Parent',nii_menu.Mfile, ...
'Label','Save displayed image as ...', ...
'separator','on', ...
'Callback','view_nii_menu(''save_disp'');');
end
if isempty(nii_menu.Medit)
nii_menu.Medit = uimenu('Parent',fig, ...
'Label','Edit');
nii_menu.Medit_orient = uimenu('Parent',nii_menu.Medit, ...
'Label','Convert to RAS orientation', ...
'Callback','view_nii_menu(''orient'');');
nii_menu.Medit_editvox = uimenu('Parent',nii_menu.Medit, ...
'Label','Edit voxel value at crosshair', ...
'Callback','view_nii_menu(''editvox'');');
else
nii_menu.Medit_orient = uimenu('Parent',nii_menu.Medit, ...
'Label','Convert to RAS orientation', ...
'separator','on', ...
'Callback','view_nii_menu(''orient'');');
nii_menu.Medit_editvox = uimenu('Parent',nii_menu.Medit, ...
'Label','Edit voxel value at crosshair', ...
'Callback','view_nii_menu(''editvox'');');
end
if isempty(nii_menu.Mview)
nii_menu.Mview = uimenu('Parent',fig, ...
'Label','View');
nii_menu.Mview_info = uimenu('Parent',nii_menu.Mview, ...
'Label','Image Information', ...
'Callback','view_nii_menu(''img_info'');');
nii_menu.Mview_info = uimenu('Parent',nii_menu.Mview, ...
'Label','Volume Histogram', ...
'Callback','view_nii_menu(''img_hist'');');
else
nii_menu.Mview_info = uimenu('Parent',nii_menu.Mview, ...
'Label','Image Information', ...
'separator','on', ...
'Callback','view_nii_menu(''img_info'');');
nii_menu.Mview_info = uimenu('Parent',nii_menu.Mview, ...
'Label','Volume Histogram', ...
'Callback','view_nii_menu(''img_hist'');');
end
nii_menu.Mzoom = rri_zoom_menu(fig);
nii_menu.Minterp = uimenu('Parent',fig, ...
'Label','Interp on', ...
'Userdata', 1, ...
'Callback','view_nii_menu(''interp'');');
setappdata(fig,'nii_menu',nii_menu);
menu_hdl = nii_menu.Minterp;
return % init
%----------------------------------------------------------------
function reset_zoom(fig)
old_handle_vis = get(fig, 'HandleVisibility');
set(fig, 'HandleVisibility', 'on');
nii_view = getappdata(fig, 'nii_view');
nii_menu = getappdata(fig, 'nii_menu');
set(nii_menu.Mzoom,'Userdata',1,'Label','Zoom on');
set(fig,'pointer','arrow');
zoom off;
axes(nii_view.handles.axial_axes);
setappdata(get(gca,'zlabel'), 'ZOOMAxesData', ...
[get(gca, 'xlim') get(gca, 'ylim')])
% zoom reset;
% zoom getlimits;
zoom out;
axes(nii_view.handles.coronal_axes);
setappdata(get(gca,'zlabel'), 'ZOOMAxesData', ...
[get(gca, 'xlim') get(gca, 'ylim')])
% zoom reset;
% zoom getlimits;
zoom out;
axes(nii_view.handles.sagittal_axes);
setappdata(get(gca,'zlabel'), 'ZOOMAxesData', ...
[get(gca, 'xlim') get(gca, 'ylim')])
% zoom reset;
% zoom getlimits;
zoom out;
set(fig, 'HandleVisibility', old_handle_vis);
return; % reset_zoom
%----------------------------------------------------------------
function img_info
nii_view = getappdata(gcbf, 'nii_view');
hdr = nii_view.nii.hdr;
max_value = num2str(double(max(nii_view.nii.img(:))));
min_value = num2str(double(min(nii_view.nii.img(:))));
dim = sprintf('%d %d %d', double(hdr.dime.dim(2:4)));
vox = sprintf('%.3f %.3f %.3f', double(hdr.dime.pixdim(2:4)));
if double(hdr.dime.datatype) == 1
type = '1-bit binary';
elseif double(hdr.dime.datatype) == 2
type = '8-bit unsigned integer';
elseif double(hdr.dime.datatype) == 4
type = '16-bit signed integer';
elseif double(hdr.dime.datatype) == 8
type = '32-bit signed integer';
elseif double(hdr.dime.datatype) == 16
type = '32-bit single float';
elseif double(hdr.dime.datatype) == 64
type = '64-bit double precision';
elseif double(hdr.dime.datatype) == 128
type = '24-bit RGB true color';
elseif double(hdr.dime.datatype) == 256
type = '8-bit signed integer';
elseif double(hdr.dime.datatype) == 511
type = '96-bit RGB true color';
elseif double(hdr.dime.datatype) == 512
type = '16-bit unsigned integer';
elseif double(hdr.dime.datatype) == 768
type = '32-bit unsigned integer';
elseif double(hdr.dime.datatype) == 1024
type = '64-bit signed integer';
elseif double(hdr.dime.datatype) == 1280
type = '64-bit unsigned integer';
end
msg = {};
msg = [msg {''}];
msg = [msg {['Dimension: [', dim, ']']}];
msg = [msg {''}];
msg = [msg {['Voxel Size: [', vox, ']']}];
msg = [msg {''}];
msg = [msg {['Data Type: [', type, ']']}];
msg = [msg {''}];
msg = [msg {['Max Value: [', max_value, ']']}];
msg = [msg {''}];
msg = [msg {['Min Value: [', min_value, ']']}];
msg = [msg {''}];
if isfield(nii_view.nii, 'fileprefix')
if isfield(nii_view.nii, 'filetype') & nii_view.nii.filetype == 2
msg = [msg {['File Name: [', nii_view.nii.fileprefix, '.nii]']}];
msg = [msg {''}];
elseif isfield(nii_view.nii, 'filetype')
msg = [msg {['File Name: [', nii_view.nii.fileprefix, '.img]']}];
msg = [msg {''}];
else
msg = [msg {['File Prefix: [', nii_view.nii.fileprefix, ']']}];
msg = [msg {''}];
end
end
h = msgbox(msg, 'Image Information', 'modal');
set(h,'color',[1 1 1]);
return; % img_info
%----------------------------------------------------------------
function orient
fig = gcbf;
nii_view = getappdata(fig, 'nii_view');
nii = nii_view.nii;
if ~isempty(nii_view.bgimg)
msg = 'You can not modify an overlay image';
h = msgbox(msg, 'Error', 'modal');
return;
end
old_pointer = get(fig,'Pointer');
set(fig,'Pointer','watch');
[nii orient] = rri_orient(nii);
if isequal(orient, [1 2 3]) % do nothing
set(fig,'Pointer',old_pointer);
return;
end
oldopt = view_nii(fig);
opt.command = 'updatenii';
opt.usecolorbar = oldopt.usecolorbar;
opt.usepanel = oldopt.usepanel;
opt.usecrosshair = oldopt.usecrosshair;
opt.usestretch = oldopt.usestretch;
opt.useimagesc = oldopt.useimagesc;
opt.useinterp = oldopt.useinterp;
opt.setarea = oldopt.area;
opt.setunit = oldopt.unit;
opt.setviewpoint = oldopt.viewpoint;
opt.setscanid = oldopt.scanid;
opt.setcbarminmax = oldopt.cbarminmax;
opt.setcolorindex = oldopt.colorindex;
opt.setcolormap = oldopt.colormap;
opt.setcolorlevel = oldopt.colorlevel;
if isfield(oldopt,'highcolor')
opt.sethighcolor = oldopt.highcolor;
end
view_nii(fig, nii, opt);
set(fig,'Pointer',old_pointer);
reset_zoom(fig);
return; % orient
%----------------------------------------------------------------
function editvox
fig = gcbf;
nii_view = getappdata(fig, 'nii_view');
if ~isempty(nii_view.bgimg)
msg = 'You can not modify an overlay image';
h = msgbox(msg, 'Error', 'modal');
return;
end
nii = nii_view.nii;
oldopt = view_nii(fig);
sag = nii_view.imgXYZ.vox(1);
cor = nii_view.imgXYZ.vox(2);
axi = nii_view.imgXYZ.vox(3);
if nii_view.nii.hdr.dime.datatype == 128
imgvalue = [double(nii.img(sag,cor,axi,1,nii_view.scanid)) double(nii.img(sag,cor,axi,2,nii_view.scanid)) double(nii.img(sag,cor,axi,3,nii_view.scanid))];
init_val = sprintf('%7.4g %7.4g %7.4g',imgvalue);
elseif nii_view.nii.hdr.dime.datatype == 511
R = double(nii.img(sag,cor,axi,1,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
G = double(nii.img(sag,cor,axi,2,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
B = double(nii.img(sag,cor,axi,3,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
imgvalue = [R G B];
init_val = sprintf('%7.4g %7.4g %7.4g',imgvalue);
else
imgvalue = double(nii.img(sag,cor,axi,nii_view.scanid));
init_val = sprintf('%.6g',imgvalue);
end
old_pointer = get(fig,'Pointer');
set(fig,'Pointer','watch');
repeat = 1;
while repeat
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
init_val = inputdlg({'Replace the current voxel values with 3 new numbers:'}, ...
'Edit voxel value at crosshair', 1, {num2str(init_val)});
else
init_val = inputdlg({'Replace the current voxel value with 1 new number:'}, ...
'Edit voxel value at crosshair', 1, {num2str(init_val)});
end
if isempty(init_val)
set(fig,'Pointer',old_pointer);
return
end
imgvalue = str2num(init_val{1});
if ( (nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511) ...
& length(imgvalue) ~= 3 ) | ...
( (nii_view.nii.hdr.dime.datatype ~= 128 & nii_view.nii.hdr.dime.datatype ~= 511) ...
& length(imgvalue) ~= 1 )
% do nothing
else
repeat = 0;
end
end
if nii_view.nii.hdr.dime.datatype == 128
nii.img(sag,cor,axi,1,nii_view.scanid) = imgvalue(1);
nii.img(sag,cor,axi,2,nii_view.scanid) = imgvalue(2);
nii.img(sag,cor,axi,3,nii_view.scanid) = imgvalue(3);
elseif nii_view.nii.hdr.dime.datatype == 511
nii.img(sag,cor,axi,1,nii_view.scanid) = (imgvalue(1) - nii_view.nii.hdr.dime.glmin) ...
/ (nii_view.nii.hdr.dime.glmax - nii_view.nii.hdr.dime.glmin);
nii.img(sag,cor,axi,2,nii_view.scanid) = (imgvalue(2) - nii_view.nii.hdr.dime.glmin) ...
/ (nii_view.nii.hdr.dime.glmax - nii_view.nii.hdr.dime.glmin);
nii.img(sag,cor,axi,3,nii_view.scanid) = (imgvalue(3) - nii_view.nii.hdr.dime.glmin) ...
/ (nii_view.nii.hdr.dime.glmax - nii_view.nii.hdr.dime.glmin);
else
nii.img(sag,cor,axi,nii_view.scanid) = imgvalue;
end
opt.command = 'updatenii';
opt.usecolorbar = oldopt.usecolorbar;
opt.usepanel = oldopt.usepanel;
opt.usecrosshair = oldopt.usecrosshair;
opt.usestretch = oldopt.usestretch;
opt.useimagesc = oldopt.useimagesc;
opt.useinterp = oldopt.useinterp;
opt.setarea = oldopt.area;
opt.setunit = oldopt.unit;
opt.setviewpoint = oldopt.viewpoint;
opt.setscanid = oldopt.scanid;
opt.setcbarminmax = oldopt.cbarminmax;
opt.setcolorindex = oldopt.colorindex;
opt.setcolormap = oldopt.colormap;
opt.setcolorlevel = oldopt.colorlevel;
if isfield(oldopt,'highcolor')
opt.sethighcolor = oldopt.highcolor;
end
view_nii(fig, nii, opt);
set(fig,'Pointer',old_pointer);
reset_zoom(fig);
return; % editvox
%----------------------------------------------------------------
function save_disp
[filename pathname] = uiputfile('*.*', 'Save displayed image as (*.nii or *.img)');
if isequal(filename,0) | isequal(pathname,0)
return;
else
out_imgfile = fullfile(pathname, filename); % original image file
end
old_pointer = get(gcbf,'Pointer');
set(gcbf,'Pointer','watch');
nii_view = getappdata(gcbf, 'nii_view');
nii = nii_view.nii;
try
save_nii(nii, out_imgfile);
catch
msg = 'File can not be saved.';
msgbox(msg, 'File write error', 'modal');
end
set(gcbf,'Pointer',old_pointer);
return; % save_disp
%----------------------------------------------------------------
function img_hist
nii_view = getappdata(gcbf, 'nii_view');
N = hist(double(nii_view.nii.img(:)),256);
x = linspace(double(min(nii_view.nii.img(:))), double(max(nii_view.nii.img(:))), 256);
figure;bar(x,N);
set(gcf, 'number', 'off', 'name', 'Volume Histogram');
set(gcf, 'windowstyle', 'modal'); % no zoom ...
xspan = max(x) - min(x) + 1;
yspan = max(N) + 1;
set(gca, 'xlim', [min(x)-xspan/20, max(x)+xspan/20]);
set(gca, 'ylim', [-yspan/20, max(N)+yspan/20]);
return; % img_hist
|
github
|
sunhongfu/scripts-master
|
save_untouch_header_only.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_untouch_header_only.m
| 2,203 |
utf_8
|
6622b1835d5ad8ce504298473ab7684f
|
% This function is only used to save Analyze or NIfTI header that is
% ended with .hdr and loaded by load_untouch_header_only.m. If you
% have NIfTI file that is ended with .nii and you want to change its
% header only, you can use load_untouch_nii / save_untouch_nii pair.
%
% Usage: save_untouch_header_only(hdr, new_header_file_name)
%
% hdr - struct with NIfTI / Analyze header fields, which is obtained from:
% hdr = load_untouch_header_only(original_header_file_name)
%
% new_header_file_name - NIfTI / Analyze header name ended with .hdr.
% You can either copy original.img(.gz) to new.img(.gz) manually,
% or simply input original.hdr(.gz) in save_untouch_header_only.m
% to overwrite the original header.
%
% - Jimmy Shen ([email protected])
%
function save_untouch_header_only(hdr, filename)
if ~exist('hdr','var') | isempty(hdr) | ~exist('filename','var') | isempty(filename)
error('Usage: save_untouch_header_only(hdr, filename)');
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.hdr.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
else
gzFile = 1;
filename = filename(1:end-3);
end
end
[p,f] = fileparts(filename);
fileprefix = fullfile(p, f);
write_hdr(hdr, fileprefix);
% gzip output file if requested
%
if exist('gzFile', 'var')
gzip([fileprefix, '.hdr']);
delete([fileprefix, '.hdr']);
end;
return % save_untouch_header_only
%-----------------------------------------------------------------------------------
function write_hdr(hdr, fileprefix)
fid = fopen(sprintf('%s.hdr',fileprefix),'w');
if isfield(hdr.hist,'magic')
save_untouch_nii_hdr(hdr, fid);
else
save_untouch0_nii_hdr(hdr, fid);
end
fclose(fid);
return % write_hdr
|
github
|
sunhongfu/scripts-master
|
pad_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/pad_nii.m
| 3,854 |
utf_8
|
a38d813f9f822362d873bc92725f565b
|
% PAD_NII: Pad the NIfTI volume from any of the 6 sides
%
% Usage: nii = pad_nii(nii, [option])
%
% Inputs:
%
% nii - NIfTI volume.
%
% option - struct instructing how many voxel to be padded from which side.
%
% option.pad_from_L = ( number of voxel )
% option.pad_from_R = ( number of voxel )
% option.pad_from_P = ( number of voxel )
% option.pad_from_A = ( number of voxel )
% option.pad_from_I = ( number of voxel )
% option.pad_from_S = ( number of voxel )
% option.bg = [0]
%
% Options description in detail:
% ==============================
%
% pad_from_L: Number of voxels from Left side will be padded.
%
% pad_from_R: Number of voxels from Right side will be padded.
%
% pad_from_P: Number of voxels from Posterior side will be padded.
%
% pad_from_A: Number of voxels from Anterior side will be padded.
%
% pad_from_I: Number of voxels from Inferior side will be padded.
%
% pad_from_S: Number of voxels from Superior side will be padded.
%
% bg: Background intensity, which is 0 by default.
%
% NIfTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function nii = pad_nii(nii, opt)
dims = abs(nii.hdr.dime.dim(2:4));
origin = abs(nii.hdr.hist.originator(1:3));
if isempty(origin) | all(origin == 0) % according to SPM
origin = round((dims+1)/2);
end
pad_from_L = 0;
pad_from_R = 0;
pad_from_P = 0;
pad_from_A = 0;
pad_from_I = 0;
pad_from_S = 0;
bg = 0;
if nargin > 1 & ~isempty(opt)
if ~isstruct(opt)
error('option argument should be a struct');
end
if isfield(opt,'pad_from_L')
pad_from_L = round(opt.pad_from_L);
if pad_from_L >= origin(1) | pad_from_L < 0
error('pad_from_L cannot be negative');
end
end
if isfield(opt,'pad_from_P')
pad_from_P = round(opt.pad_from_P);
if pad_from_P >= origin(2) | pad_from_P < 0
error('pad_from_P cannot be negative');
end
end
if isfield(opt,'pad_from_I')
pad_from_I = round(opt.pad_from_I);
if pad_from_I >= origin(3) | pad_from_I < 0
error('pad_from_I cannot be negative');
end
end
if isfield(opt,'pad_from_R')
pad_from_R = round(opt.pad_from_R);
if pad_from_R > dims(1)-origin(1) | pad_from_R < 0
error('pad_from_R cannot be negative');
end
end
if isfield(opt,'pad_from_A')
pad_from_A = round(opt.pad_from_A);
if pad_from_A > dims(2)-origin(2) | pad_from_A < 0
error('pad_from_A cannot be negative');
end
end
if isfield(opt,'pad_from_S')
pad_from_S = round(opt.pad_from_S);
if pad_from_S > dims(3)-origin(3) | pad_from_S < 0
error('pad_from_S cannot be negative');
end
end
if isfield(opt,'bg')
bg = opt.bg;
end
end
blk = bg * ones( pad_from_L, dims(2), dims(3) );
nii.img = cat(1, blk, nii.img);
blk = bg * ones( pad_from_R, dims(2), dims(3) );
nii.img = cat(1, nii.img, blk);
dims = size(nii.img);
blk = bg * ones( dims(1), pad_from_P, dims(3) );
nii.img = cat(2, blk, nii.img);
blk = bg * ones( dims(1), pad_from_A, dims(3) );
nii.img = cat(2, nii.img, blk);
dims = size(nii.img);
blk = bg * ones( dims(1), dims(2), pad_from_I );
nii.img = cat(3, blk, nii.img);
blk = bg * ones( dims(1), dims(2), pad_from_S );
nii.img = cat(3, nii.img, blk);
nii = make_nii(nii.img, nii.hdr.dime.pixdim(2:4), ...
[origin(1)+pad_from_L origin(2)+pad_from_P origin(3)+pad_from_I], ...
nii.hdr.dime.datatype, nii.hdr.hist.descrip);
return;
|
github
|
sunhongfu/scripts-master
|
load_nii_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_nii_hdr.m
| 10,311 |
utf_8
|
ef81f82b43da4fbd79a9de1787b5ae22
|
% internal function
% - Jimmy Shen ([email protected])
function [hdr, filetype, fileprefix, machine] = load_nii_hdr(fileprefix)
if ~exist('fileprefix','var'),
error('Usage: [hdr, filetype, fileprefix, machine] = load_nii_hdr(filename)');
end
machine = 'ieee-le';
new_ext = 0;
if findstr('.nii',fileprefix) & strcmp(fileprefix(end-3:end), '.nii')
new_ext = 1;
fileprefix(end-3:end)='';
end
if findstr('.hdr',fileprefix) & strcmp(fileprefix(end-3:end), '.hdr')
fileprefix(end-3:end)='';
end
if findstr('.img',fileprefix) & strcmp(fileprefix(end-3:end), '.img')
fileprefix(end-3:end)='';
end
if new_ext
fn = sprintf('%s.nii',fileprefix);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.nii".', fileprefix);
error(msg);
end
else
fn = sprintf('%s.hdr',fileprefix);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.hdr".', fileprefix);
error(msg);
end
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
fseek(fid,0,'bof');
if fread(fid,1,'int32') == 348
hdr = read_header(fid);
fclose(fid);
else
fclose(fid);
% first try reading the opposite endian to 'machine'
%
switch machine,
case 'ieee-le', machine = 'ieee-be';
case 'ieee-be', machine = 'ieee-le';
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
fseek(fid,0,'bof');
if fread(fid,1,'int32') ~= 348
% Now throw an error
%
msg = sprintf('File "%s" is corrupted.',fn);
error(msg);
end
hdr = read_header(fid);
fclose(fid);
end
end
end
if strcmp(hdr.hist.magic, 'n+1')
filetype = 2;
elseif strcmp(hdr.hist.magic, 'ni1')
filetype = 1;
else
filetype = 0;
end
return % load_nii_hdr
%---------------------------------------------------------------------
function [ dsr ] = read_header(fid)
% Original header structures
% struct dsr
% {
% struct header_key hk; /* 0 + 40 */
% struct image_dimension dime; /* 40 + 108 */
% struct data_history hist; /* 148 + 200 */
% }; /* total= 348 bytes*/
dsr.hk = header_key(fid);
dsr.dime = image_dimension(fid);
dsr.hist = data_history(fid);
% For Analyze data format
%
if ~strcmp(dsr.hist.magic, 'n+1') & ~strcmp(dsr.hist.magic, 'ni1')
dsr.hist.qform_code = 0;
dsr.hist.sform_code = 0;
end
return % read_header
%---------------------------------------------------------------------
function [ hk ] = header_key(fid)
fseek(fid,0,'bof');
% Original header structures
% struct header_key /* header key */
% { /* off + size */
% int sizeof_hdr /* 0 + 4 */
% char data_type[10]; /* 4 + 10 */
% char db_name[18]; /* 14 + 18 */
% int extents; /* 32 + 4 */
% short int session_error; /* 36 + 2 */
% char regular; /* 38 + 1 */
% char dim_info; % char hkey_un0; /* 39 + 1 */
% }; /* total=40 bytes */
%
% int sizeof_header Should be 348.
% char regular Must be 'r' to indicate that all images and
% volumes are the same size.
v6 = version;
if str2num(v6(1))<6
directchar = '*char';
else
directchar = 'uchar=>char';
end
hk.sizeof_hdr = fread(fid, 1,'int32')'; % should be 348!
hk.data_type = deblank(fread(fid,10,directchar)');
hk.db_name = deblank(fread(fid,18,directchar)');
hk.extents = fread(fid, 1,'int32')';
hk.session_error = fread(fid, 1,'int16')';
hk.regular = fread(fid, 1,directchar)';
hk.dim_info = fread(fid, 1,'uchar')';
return % header_key
%---------------------------------------------------------------------
function [ dime ] = image_dimension(fid)
% Original header structures
% struct image_dimension
% { /* off + size */
% short int dim[8]; /* 0 + 16 */
% /*
% dim[0] Number of dimensions in database; usually 4.
% dim[1] Image X dimension; number of *pixels* in an image row.
% dim[2] Image Y dimension; number of *pixel rows* in slice.
% dim[3] Volume Z dimension; number of *slices* in a volume.
% dim[4] Time points; number of volumes in database
% */
% float intent_p1; % char vox_units[4]; /* 16 + 4 */
% float intent_p2; % char cal_units[8]; /* 20 + 4 */
% float intent_p3; % char cal_units[8]; /* 24 + 4 */
% short int intent_code; % short int unused1; /* 28 + 2 */
% short int datatype; /* 30 + 2 */
% short int bitpix; /* 32 + 2 */
% short int slice_start; % short int dim_un0; /* 34 + 2 */
% float pixdim[8]; /* 36 + 32 */
% /*
% pixdim[] specifies the voxel dimensions:
% pixdim[1] - voxel width, mm
% pixdim[2] - voxel height, mm
% pixdim[3] - slice thickness, mm
% pixdim[4] - volume timing, in msec
% ..etc
% */
% float vox_offset; /* 68 + 4 */
% float scl_slope; % float roi_scale; /* 72 + 4 */
% float scl_inter; % float funused1; /* 76 + 4 */
% short slice_end; % float funused2; /* 80 + 2 */
% char slice_code; % float funused2; /* 82 + 1 */
% char xyzt_units; % float funused2; /* 83 + 1 */
% float cal_max; /* 84 + 4 */
% float cal_min; /* 88 + 4 */
% float slice_duration; % int compressed; /* 92 + 4 */
% float toffset; % int verified; /* 96 + 4 */
% int glmax; /* 100 + 4 */
% int glmin; /* 104 + 4 */
% }; /* total=108 bytes */
dime.dim = fread(fid,8,'int16')';
dime.intent_p1 = fread(fid,1,'float32')';
dime.intent_p2 = fread(fid,1,'float32')';
dime.intent_p3 = fread(fid,1,'float32')';
dime.intent_code = fread(fid,1,'int16')';
dime.datatype = fread(fid,1,'int16')';
dime.bitpix = fread(fid,1,'int16')';
dime.slice_start = fread(fid,1,'int16')';
dime.pixdim = fread(fid,8,'float32')';
dime.vox_offset = fread(fid,1,'float32')';
dime.scl_slope = fread(fid,1,'float32')';
dime.scl_inter = fread(fid,1,'float32')';
dime.slice_end = fread(fid,1,'int16')';
dime.slice_code = fread(fid,1,'uchar')';
dime.xyzt_units = fread(fid,1,'uchar')';
dime.cal_max = fread(fid,1,'float32')';
dime.cal_min = fread(fid,1,'float32')';
dime.slice_duration = fread(fid,1,'float32')';
dime.toffset = fread(fid,1,'float32')';
dime.glmax = fread(fid,1,'int32')';
dime.glmin = fread(fid,1,'int32')';
return % image_dimension
%---------------------------------------------------------------------
function [ hist ] = data_history(fid)
% Original header structures
% struct data_history
% { /* off + size */
% char descrip[80]; /* 0 + 80 */
% char aux_file[24]; /* 80 + 24 */
% short int qform_code; /* 104 + 2 */
% short int sform_code; /* 106 + 2 */
% float quatern_b; /* 108 + 4 */
% float quatern_c; /* 112 + 4 */
% float quatern_d; /* 116 + 4 */
% float qoffset_x; /* 120 + 4 */
% float qoffset_y; /* 124 + 4 */
% float qoffset_z; /* 128 + 4 */
% float srow_x[4]; /* 132 + 16 */
% float srow_y[4]; /* 148 + 16 */
% float srow_z[4]; /* 164 + 16 */
% char intent_name[16]; /* 180 + 16 */
% char magic[4]; % int smin; /* 196 + 4 */
% }; /* total=200 bytes */
v6 = version;
if str2num(v6(1))<6
directchar = '*char';
else
directchar = 'uchar=>char';
end
hist.descrip = deblank(fread(fid,80,directchar)');
hist.aux_file = deblank(fread(fid,24,directchar)');
hist.qform_code = fread(fid,1,'int16')';
hist.sform_code = fread(fid,1,'int16')';
hist.quatern_b = fread(fid,1,'float32')';
hist.quatern_c = fread(fid,1,'float32')';
hist.quatern_d = fread(fid,1,'float32')';
hist.qoffset_x = fread(fid,1,'float32')';
hist.qoffset_y = fread(fid,1,'float32')';
hist.qoffset_z = fread(fid,1,'float32')';
hist.srow_x = fread(fid,4,'float32')';
hist.srow_y = fread(fid,4,'float32')';
hist.srow_z = fread(fid,4,'float32')';
hist.intent_name = deblank(fread(fid,16,directchar)');
hist.magic = deblank(fread(fid,4,directchar)');
fseek(fid,253,'bof');
hist.originator = fread(fid, 5,'int16')';
return % data_history
|
github
|
sunhongfu/scripts-master
|
save_untouch_slice.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_untouch_slice.m
| 20,263 |
utf_8
|
833f175c0298d11697418454a03993db
|
% Save back to the original image with a portion of slices that was
% loaded by "load_untouch_nii". You can process those slices matrix
% in any way, as long as their dimension is not altered.
%
% Usage: save_untouch_slice(slice, filename, ...
% slice_idx, [img_idx], [dim5_idx], [dim6_idx], [dim7_idx])
%
% slice - a portion of slices that was loaded by "load_untouch_nii".
% This should be a numeric matrix (i.e. only the .img field in the
% loaded structure)
%
% filename - NIfTI or ANALYZE file name.
%
% slice_idx (depending on slice size) - a numerical array of image
% slice indices, which should be the same as that you entered
% in "load_untouch_nii" command.
%
% img_idx (depending on slice size) - a numerical array of image
% volume indices, which should be the same as that you entered
% in "load_untouch_nii" command.
%
% dim5_idx (depending on slice size) - a numerical array of 5th
% dimension indices, which should be the same as that you entered
% in "load_untouch_nii" command.
%
% dim6_idx (depending on slice size) - a numerical array of 6th
% dimension indices, which should be the same as that you entered
% in "load_untouch_nii" command.
%
% dim7_idx (depending on slice size) - a numerical array of 7th
% dimension indices, which should be the same as that you entered
% in "load_untouch_nii" command.
%
% Example:
% nii = load_nii('avg152T1_LR_nifti.nii');
% save_nii(nii, 'test.nii');
% view_nii(nii);
% nii = load_untouch_nii('test.nii','','','','','',[40 51:53]);
% nii.img = ones(91,109,4)*122;
% save_untouch_slice(nii.img, 'test.nii', [40 51:52]);
% nii = load_nii('test.nii');
% view_nii(nii);
%
% - Jimmy Shen ([email protected])
%
function save_untouch_slice(slice, filename, slice_idx, img_idx, dim5_idx, dim6_idx, dim7_idx)
if ~exist('slice','var') | ~isnumeric(slice)
msg = [char(10) '"slice" argument should be a portion of slices that was loaded' char(10)];
msg = [msg 'by "load_untouch_nii.m". This should be a numeric matrix (i.e.' char(10)];
msg = [msg 'only the .img field in the loaded structure).'];
error(msg);
end
if ~exist('filename','var') | ~exist(filename,'file')
error('In order to save back, original NIfTI or ANALYZE file must exist.');
end
if ~exist('slice_idx','var') | isempty(slice_idx) | ~isequal(size(slice,3),length(slice_idx))
msg = [char(10) '"slice_idx" is a numerical array of image slice indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
if ~exist('img_idx','var') | isempty(img_idx)
img_idx = [];
if ~isequal(size(slice,4),1)
msg = [char(10) '"img_idx" is a numerical array of image volume indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
elseif ~isequal(size(slice,4),length(img_idx))
msg = [char(10) '"img_idx" is a numerical array of image volume indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
if ~exist('dim5_idx','var') | isempty(dim5_idx)
dim5_idx = [];
if ~isequal(size(slice,5),1)
msg = [char(10) '"dim5_idx" is a numerical array of 5th dimension indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
elseif ~isequal(size(slice,5),length(img_idx))
msg = [char(10) '"img_idx" is a numerical array of 5th dimension indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
if ~exist('dim6_idx','var') | isempty(dim6_idx)
dim6_idx = [];
if ~isequal(size(slice,6),1)
msg = [char(10) '"dim6_idx" is a numerical array of 6th dimension indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
elseif ~isequal(size(slice,6),length(img_idx))
msg = [char(10) '"img_idx" is a numerical array of 6th dimension indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
if ~exist('dim7_idx','var') | isempty(dim7_idx)
dim7_idx = [];
if ~isequal(size(slice,7),1)
msg = [char(10) '"dim7_idx" is a numerical array of 7th dimension indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
elseif ~isequal(size(slice,7),length(img_idx))
msg = [char(10) '"img_idx" is a numerical array of 7th dimension indices, which' char(10)];
msg = [msg 'should be the same as that you entered in "load_untouch_nii.m"' char(10)];
msg = [msg 'command.'];
error(msg);
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
elseif strcmp(filename(end-6:end), '.img.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.hdr.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.hdr.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.img.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.nii.gz')
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename = gunzip(filename, tmpDir);
filename = char(filename); % convert from cell to string
end
end
% Read the dataset header
%
[nii.hdr,nii.filetype,nii.fileprefix,nii.machine] = load_nii_hdr(filename);
if nii.filetype == 0
nii.hdr = load_untouch0_nii_hdr(nii.fileprefix,nii.machine);
else
nii.hdr = load_untouch_nii_hdr(nii.fileprefix,nii.machine,nii.filetype);
end
% Clean up after gunzip
%
if exist('gzFileName', 'var')
% fix fileprefix so it doesn't point to temp location
%
nii.fileprefix = gzFileName(1:end-7);
% rmdir(tmpDir,'s');
end
[p,f] = fileparts(filename);
fileprefix = fullfile(p, f);
% fileprefix = nii.fileprefix;
filetype = nii.filetype;
if ~isequal( nii.hdr.dime.dim(2:3), [size(slice,1),size(slice,2)] )
msg = [char(10) 'The first two dimensions of slice matrix should be the same as' char(10)];
msg = [msg 'the first two dimensions of image loaded by "load_untouch_nii".'];
error(msg);
end
% Save the dataset body
%
save_untouch_slice_img(slice, nii.hdr, filetype, fileprefix, ...
nii.machine, slice_idx,img_idx,dim5_idx,dim6_idx,dim7_idx);
% gzip output file if requested
%
if exist('gzFileName', 'var')
[p,f] = fileparts(gzFileName);
if filetype == 1
gzip([fileprefix, '.img']);
delete([fileprefix, '.img']);
movefile([fileprefix, '.img.gz']);
gzip([fileprefix, '.hdr']);
delete([fileprefix, '.hdr']);
movefile([fileprefix, '.hdr.gz']);
elseif filetype == 2
gzip([fileprefix, '.nii']);
delete([fileprefix, '.nii']);
movefile([fileprefix, '.nii.gz']);
end;
rmdir(tmpDir,'s');
end;
return % save_untouch_slice
%--------------------------------------------------------------------------
function save_untouch_slice_img(slice,hdr,filetype,fileprefix,machine,slice_idx,img_idx,dim5_idx,dim6_idx,dim7_idx)
if ~exist('hdr','var') | ~exist('filetype','var') | ~exist('fileprefix','var') | ~exist('machine','var')
error('Usage: save_untouch_slice_img(slice,hdr,filetype,fileprefix,machine,slice_idx,[img_idx],[dim5_idx],[dim6_idx],[dim7_idx]);');
end
if ~exist('slice_idx','var') | isempty(slice_idx) | hdr.dime.dim(4)<1
slice_idx = [];
end
if ~exist('img_idx','var') | isempty(img_idx) | hdr.dime.dim(5)<1
img_idx = [];
end
if ~exist('dim5_idx','var') | isempty(dim5_idx) | hdr.dime.dim(6)<1
dim5_idx = [];
end
if ~exist('dim6_idx','var') | isempty(dim6_idx) | hdr.dime.dim(7)<1
dim6_idx = [];
end
if ~exist('dim7_idx','var') | isempty(dim7_idx) | hdr.dime.dim(8)<1
dim7_idx = [];
end
% check img_idx
%
if ~isempty(img_idx) & ~isnumeric(img_idx)
error('"img_idx" should be a numerical array.');
end
if length(unique(img_idx)) ~= length(img_idx)
error('Duplicate image index in "img_idx"');
end
if ~isempty(img_idx) & (min(img_idx) < 1 | max(img_idx) > hdr.dime.dim(5))
max_range = hdr.dime.dim(5);
if max_range == 1
error(['"img_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"img_idx" should be an integer within the range of [' range '].']);
end
end
% check dim5_idx
%
if ~isempty(dim5_idx) & ~isnumeric(dim5_idx)
error('"dim5_idx" should be a numerical array.');
end
if length(unique(dim5_idx)) ~= length(dim5_idx)
error('Duplicate index in "dim5_idx"');
end
if ~isempty(dim5_idx) & (min(dim5_idx) < 1 | max(dim5_idx) > hdr.dime.dim(6))
max_range = hdr.dime.dim(6);
if max_range == 1
error(['"dim5_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim5_idx" should be an integer within the range of [' range '].']);
end
end
% check dim6_idx
%
if ~isempty(dim6_idx) & ~isnumeric(dim6_idx)
error('"dim6_idx" should be a numerical array.');
end
if length(unique(dim6_idx)) ~= length(dim6_idx)
error('Duplicate index in "dim6_idx"');
end
if ~isempty(dim6_idx) & (min(dim6_idx) < 1 | max(dim6_idx) > hdr.dime.dim(7))
max_range = hdr.dime.dim(7);
if max_range == 1
error(['"dim6_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim6_idx" should be an integer within the range of [' range '].']);
end
end
% check dim7_idx
%
if ~isempty(dim7_idx) & ~isnumeric(dim7_idx)
error('"dim7_idx" should be a numerical array.');
end
if length(unique(dim7_idx)) ~= length(dim7_idx)
error('Duplicate index in "dim7_idx"');
end
if ~isempty(dim7_idx) & (min(dim7_idx) < 1 | max(dim7_idx) > hdr.dime.dim(8))
max_range = hdr.dime.dim(8);
if max_range == 1
error(['"dim7_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim7_idx" should be an integer within the range of [' range '].']);
end
end
% check slice_idx
%
if ~isempty(slice_idx) & ~isnumeric(slice_idx)
error('"slice_idx" should be a numerical array.');
end
if length(unique(slice_idx)) ~= length(slice_idx)
error('Duplicate index in "slice_idx"');
end
if ~isempty(slice_idx) & (min(slice_idx) < 1 | max(slice_idx) > hdr.dime.dim(4))
max_range = hdr.dime.dim(4);
if max_range == 1
error(['"slice_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"slice_idx" should be an integer within the range of [' range '].']);
end
end
write_image(slice,hdr,filetype,fileprefix,machine,slice_idx,img_idx,dim5_idx,dim6_idx,dim7_idx);
return % save_untouch_slice_img
%---------------------------------------------------------------------
function write_image(slice,hdr,filetype,fileprefix,machine,slice_idx,img_idx,dim5_idx,dim6_idx,dim7_idx)
if filetype == 2
fid = fopen(sprintf('%s.nii',fileprefix),'r+');
if fid < 0,
msg = sprintf('Cannot open file %s.nii.',fileprefix);
error(msg);
end
else
fid = fopen(sprintf('%s.img',fileprefix),'r+');
if fid < 0,
msg = sprintf('Cannot open file %s.img.',fileprefix);
error(msg);
end
end
% Set bitpix according to datatype
%
% /*Acceptable values for datatype are*/
%
% 0 None (Unknown bit per voxel) % DT_NONE, DT_UNKNOWN
% 1 Binary (ubit1, bitpix=1) % DT_BINARY
% 2 Unsigned char (uchar or uint8, bitpix=8) % DT_UINT8, NIFTI_TYPE_UINT8
% 4 Signed short (int16, bitpix=16) % DT_INT16, NIFTI_TYPE_INT16
% 8 Signed integer (int32, bitpix=32) % DT_INT32, NIFTI_TYPE_INT32
% 16 Floating point (single or float32, bitpix=32) % DT_FLOAT32, NIFTI_TYPE_FLOAT32
% 32 Complex, 2 float32 (Use float32, bitpix=64) % DT_COMPLEX64, NIFTI_TYPE_COMPLEX64
% 64 Double precision (double or float64, bitpix=64) % DT_FLOAT64, NIFTI_TYPE_FLOAT64
% 128 uint8 RGB (Use uint8, bitpix=24) % DT_RGB24, NIFTI_TYPE_RGB24
% 256 Signed char (schar or int8, bitpix=8) % DT_INT8, NIFTI_TYPE_INT8
% 511 Single RGB (Use float32, bitpix=96) % DT_RGB96, NIFTI_TYPE_RGB96
% 512 Unsigned short (uint16, bitpix=16) % DT_UNINT16, NIFTI_TYPE_UNINT16
% 768 Unsigned integer (uint32, bitpix=32) % DT_UNINT32, NIFTI_TYPE_UNINT32
% 1024 Signed long long (int64, bitpix=64) % DT_INT64, NIFTI_TYPE_INT64
% 1280 Unsigned long long (uint64, bitpix=64) % DT_UINT64, NIFTI_TYPE_UINT64
% 1536 Long double, float128 (Unsupported, bitpix=128) % DT_FLOAT128, NIFTI_TYPE_FLOAT128
% 1792 Complex128, 2 float64 (Use float64, bitpix=128) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
% 2048 Complex256, 2 float128 (Unsupported, bitpix=256) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
%
switch hdr.dime.datatype
case 2,
hdr.dime.bitpix = 8; precision = 'uint8';
case 4,
hdr.dime.bitpix = 16; precision = 'int16';
case 8,
hdr.dime.bitpix = 32; precision = 'int32';
case 16,
hdr.dime.bitpix = 32; precision = 'float32';
case 64,
hdr.dime.bitpix = 64; precision = 'float64';
case 128,
hdr.dime.bitpix = 24; precision = 'uint8';
case 256
hdr.dime.bitpix = 8; precision = 'int8';
case 511
hdr.dime.bitpix = 96; precision = 'float32';
case 512
hdr.dime.bitpix = 16; precision = 'uint16';
case 768
hdr.dime.bitpix = 32; precision = 'uint32';
case 1024
hdr.dime.bitpix = 64; precision = 'int64';
case 1280
hdr.dime.bitpix = 64; precision = 'uint64';
otherwise
error('This datatype is not supported');
end
hdr.dime.dim(find(hdr.dime.dim < 1)) = 1;
% move pointer to the start of image block
%
switch filetype
case {0, 1}
fseek(fid, 0, 'bof');
case 2
fseek(fid, hdr.dime.vox_offset, 'bof');
end
if hdr.dime.datatype == 1 | isequal(hdr.dime.dim(4:8),ones(1,5)) | ...
(isempty(img_idx) & isempty(dim5_idx) & isempty(dim6_idx) & isempty(dim7_idx) & isempty(slice_idx))
msg = [char(10) char(10) ' "save_untouch_slice" is used to save back to the original image a' char(10)];
msg = [msg ' portion of slices that were loaded by "load_untouch_nii". You can' char(10)];
msg = [msg ' process those slices matrix in any way, as long as their dimension' char(10)];
msg = [msg ' is not changed.'];
error(msg);
else
d1 = hdr.dime.dim(2);
d2 = hdr.dime.dim(3);
d3 = hdr.dime.dim(4);
d4 = hdr.dime.dim(5);
d5 = hdr.dime.dim(6);
d6 = hdr.dime.dim(7);
d7 = hdr.dime.dim(8);
if isempty(slice_idx)
slice_idx = 1:d3;
end
if isempty(img_idx)
img_idx = 1:d4;
end
if isempty(dim5_idx)
dim5_idx = 1:d5;
end
if isempty(dim6_idx)
dim6_idx = 1:d6;
end
if isempty(dim7_idx)
dim7_idx = 1:d7;
end
%ROMAN: begin
roman = 1;
if(roman)
% compute size of one slice
%
img_siz = prod(hdr.dime.dim(2:3));
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img_siz = img_siz * 2;
end
%MPH: For RGB24, voxel values include 3 separate color planes
%
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
img_siz = img_siz * 3;
end
end; %if(roman)
% ROMAN: end
for i7=1:length(dim7_idx)
for i6=1:length(dim6_idx)
for i5=1:length(dim5_idx)
for t=1:length(img_idx)
for s=1:length(slice_idx)
% Position is seeked in bytes. To convert dimension size
% to byte storage size, hdr.dime.bitpix/8 will be
% applied.
%
pos = sub2ind([d1 d2 d3 d4 d5 d6 d7], 1, 1, slice_idx(s), ...
img_idx(t), dim5_idx(i5),dim6_idx(i6),dim7_idx(i7)) -1;
pos = pos * hdr.dime.bitpix/8;
% ROMAN: begin
if(roman)
% do nothing
else
img_siz = prod(hdr.dime.dim(2:3));
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img_siz = img_siz * 2;
end
%MPH: For RGB24, voxel values include 3 separate color planes
%
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
img_siz = img_siz * 3;
end
end; % if (roman)
% ROMAN: end
if filetype == 2
fseek(fid, pos + hdr.dime.vox_offset, 'bof');
else
fseek(fid, pos, 'bof');
end
% For each frame, fwrite will write precision of value
% in img_siz times
%
fwrite(fid, slice(:,:,s,t,i5,i6,i7), sprintf('*%s',precision));
end
end
end
end
end
end
fclose(fid);
return % write_image
|
github
|
sunhongfu/scripts-master
|
load_nii_img.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_nii_img.m
| 12,720 |
utf_8
|
5670adb84a76f241bd221003bee8187d
|
% internal function
% - Jimmy Shen ([email protected])
function [img,hdr] = load_nii_img(hdr,filetype,fileprefix,machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB)
if ~exist('hdr','var') | ~exist('filetype','var') | ~exist('fileprefix','var') | ~exist('machine','var')
error('Usage: [img,hdr] = load_nii_img(hdr,filetype,fileprefix,machine,[img_idx],[dim5_idx],[dim6_idx],[dim7_idx],[old_RGB]);');
end
if ~exist('img_idx','var') | isempty(img_idx) | hdr.dime.dim(5)<1
img_idx = [];
end
if ~exist('dim5_idx','var') | isempty(dim5_idx) | hdr.dime.dim(6)<1
dim5_idx = [];
end
if ~exist('dim6_idx','var') | isempty(dim6_idx) | hdr.dime.dim(7)<1
dim6_idx = [];
end
if ~exist('dim7_idx','var') | isempty(dim7_idx) | hdr.dime.dim(8)<1
dim7_idx = [];
end
if ~exist('old_RGB','var') | isempty(old_RGB)
old_RGB = 0;
end
% check img_idx
%
if ~isempty(img_idx) & ~isnumeric(img_idx)
error('"img_idx" should be a numerical array.');
end
if length(unique(img_idx)) ~= length(img_idx)
error('Duplicate image index in "img_idx"');
end
if ~isempty(img_idx) & (min(img_idx) < 1 | max(img_idx) > hdr.dime.dim(5))
max_range = hdr.dime.dim(5);
if max_range == 1
error(['"img_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"img_idx" should be an integer within the range of [' range '].']);
end
end
% check dim5_idx
%
if ~isempty(dim5_idx) & ~isnumeric(dim5_idx)
error('"dim5_idx" should be a numerical array.');
end
if length(unique(dim5_idx)) ~= length(dim5_idx)
error('Duplicate index in "dim5_idx"');
end
if ~isempty(dim5_idx) & (min(dim5_idx) < 1 | max(dim5_idx) > hdr.dime.dim(6))
max_range = hdr.dime.dim(6);
if max_range == 1
error(['"dim5_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim5_idx" should be an integer within the range of [' range '].']);
end
end
% check dim6_idx
%
if ~isempty(dim6_idx) & ~isnumeric(dim6_idx)
error('"dim6_idx" should be a numerical array.');
end
if length(unique(dim6_idx)) ~= length(dim6_idx)
error('Duplicate index in "dim6_idx"');
end
if ~isempty(dim6_idx) & (min(dim6_idx) < 1 | max(dim6_idx) > hdr.dime.dim(7))
max_range = hdr.dime.dim(7);
if max_range == 1
error(['"dim6_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim6_idx" should be an integer within the range of [' range '].']);
end
end
% check dim7_idx
%
if ~isempty(dim7_idx) & ~isnumeric(dim7_idx)
error('"dim7_idx" should be a numerical array.');
end
if length(unique(dim7_idx)) ~= length(dim7_idx)
error('Duplicate index in "dim7_idx"');
end
if ~isempty(dim7_idx) & (min(dim7_idx) < 1 | max(dim7_idx) > hdr.dime.dim(8))
max_range = hdr.dime.dim(8);
if max_range == 1
error(['"dim7_idx" should be 1.']);
else
range = ['1 ' num2str(max_range)];
error(['"dim7_idx" should be an integer within the range of [' range '].']);
end
end
[img,hdr] = read_image(hdr,filetype,fileprefix,machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB);
return % load_nii_img
%---------------------------------------------------------------------
function [img,hdr] = read_image(hdr,filetype,fileprefix,machine,img_idx,dim5_idx,dim6_idx,dim7_idx,old_RGB)
switch filetype
case {0, 1}
fn = [fileprefix '.img'];
case 2
fn = [fileprefix '.nii'];
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
end
% Set bitpix according to datatype
%
% /*Acceptable values for datatype are*/
%
% 0 None (Unknown bit per voxel) % DT_NONE, DT_UNKNOWN
% 1 Binary (ubit1, bitpix=1) % DT_BINARY
% 2 Unsigned char (uchar or uint8, bitpix=8) % DT_UINT8, NIFTI_TYPE_UINT8
% 4 Signed short (int16, bitpix=16) % DT_INT16, NIFTI_TYPE_INT16
% 8 Signed integer (int32, bitpix=32) % DT_INT32, NIFTI_TYPE_INT32
% 16 Floating point (single or float32, bitpix=32) % DT_FLOAT32, NIFTI_TYPE_FLOAT32
% 32 Complex, 2 float32 (Use float32, bitpix=64) % DT_COMPLEX64, NIFTI_TYPE_COMPLEX64
% 64 Double precision (double or float64, bitpix=64) % DT_FLOAT64, NIFTI_TYPE_FLOAT64
% 128 uint8 RGB (Use uint8, bitpix=24) % DT_RGB24, NIFTI_TYPE_RGB24
% 256 Signed char (schar or int8, bitpix=8) % DT_INT8, NIFTI_TYPE_INT8
% 511 Single RGB (Use float32, bitpix=96) % DT_RGB96, NIFTI_TYPE_RGB96
% 512 Unsigned short (uint16, bitpix=16) % DT_UNINT16, NIFTI_TYPE_UNINT16
% 768 Unsigned integer (uint32, bitpix=32) % DT_UNINT32, NIFTI_TYPE_UNINT32
% 1024 Signed long long (int64, bitpix=64) % DT_INT64, NIFTI_TYPE_INT64
% 1280 Unsigned long long (uint64, bitpix=64) % DT_UINT64, NIFTI_TYPE_UINT64
% 1536 Long double, float128 (Unsupported, bitpix=128) % DT_FLOAT128, NIFTI_TYPE_FLOAT128
% 1792 Complex128, 2 float64 (Use float64, bitpix=128) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
% 2048 Complex256, 2 float128 (Unsupported, bitpix=256) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
%
switch hdr.dime.datatype
case 1,
hdr.dime.bitpix = 1; precision = 'ubit1';
case 2,
hdr.dime.bitpix = 8; precision = 'uint8';
case 4,
hdr.dime.bitpix = 16; precision = 'int16';
case 8,
hdr.dime.bitpix = 32; precision = 'int32';
case 16,
hdr.dime.bitpix = 32; precision = 'float32';
case 32,
hdr.dime.bitpix = 64; precision = 'float32';
case 64,
hdr.dime.bitpix = 64; precision = 'float64';
case 128,
hdr.dime.bitpix = 24; precision = 'uint8';
case 256
hdr.dime.bitpix = 8; precision = 'int8';
case 511
hdr.dime.bitpix = 96; precision = 'float32';
case 512
hdr.dime.bitpix = 16; precision = 'uint16';
case 768
hdr.dime.bitpix = 32; precision = 'uint32';
case 1024
hdr.dime.bitpix = 64; precision = 'int64';
case 1280
hdr.dime.bitpix = 64; precision = 'uint64';
case 1792,
hdr.dime.bitpix = 128; precision = 'float64';
otherwise
error('This datatype is not supported');
end
hdr.dime.dim(find(hdr.dime.dim < 1)) = 1;
% move pointer to the start of image block
%
switch filetype
case {0, 1}
fseek(fid, 0, 'bof');
case 2
fseek(fid, hdr.dime.vox_offset, 'bof');
end
% Load whole image block for old Analyze format or binary image;
% otherwise, load images that are specified in img_idx, dim5_idx,
% dim6_idx, and dim7_idx
%
% For binary image, we have to read all because pos can not be
% seeked in bit and can not be calculated the way below.
%
if hdr.dime.datatype == 1 | isequal(hdr.dime.dim(5:8),ones(1,4)) | ...
(isempty(img_idx) & isempty(dim5_idx) & isempty(dim6_idx) & isempty(dim7_idx))
% For each frame, precision of value will be read
% in img_siz times, where img_siz is only the
% dimension size of an image, not the byte storage
% size of an image.
%
img_siz = prod(hdr.dime.dim(2:8));
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img_siz = img_siz * 2;
end
%MPH: For RGB24, voxel values include 3 separate color planes
%
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
img_siz = img_siz * 3;
end
img = fread(fid, img_siz, sprintf('*%s',precision));
d1 = hdr.dime.dim(2);
d2 = hdr.dime.dim(3);
d3 = hdr.dime.dim(4);
d4 = hdr.dime.dim(5);
d5 = hdr.dime.dim(6);
d6 = hdr.dime.dim(7);
d7 = hdr.dime.dim(8);
if isempty(img_idx)
img_idx = 1:d4;
end
if isempty(dim5_idx)
dim5_idx = 1:d5;
end
if isempty(dim6_idx)
dim6_idx = 1:d6;
end
if isempty(dim7_idx)
dim7_idx = 1:d7;
end
else
d1 = hdr.dime.dim(2);
d2 = hdr.dime.dim(3);
d3 = hdr.dime.dim(4);
d4 = hdr.dime.dim(5);
d5 = hdr.dime.dim(6);
d6 = hdr.dime.dim(7);
d7 = hdr.dime.dim(8);
if isempty(img_idx)
img_idx = 1:d4;
end
if isempty(dim5_idx)
dim5_idx = 1:d5;
end
if isempty(dim6_idx)
dim6_idx = 1:d6;
end
if isempty(dim7_idx)
dim7_idx = 1:d7;
end
% compute size of one image
%
img_siz = prod(hdr.dime.dim(2:4));
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img_siz = img_siz * 2;
end
%MPH: For RGB24, voxel values include 3 separate color planes
%
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
img_siz = img_siz * 3;
end
% preallocate img
img = zeros(img_siz, length(img_idx)*length(dim5_idx)*length(dim6_idx)*length(dim7_idx) );
currentIndex = 1;
for i7=1:length(dim7_idx)
for i6=1:length(dim6_idx)
for i5=1:length(dim5_idx)
for t=1:length(img_idx)
% Position is seeked in bytes. To convert dimension size
% to byte storage size, hdr.dime.bitpix/8 will be
% applied.
%
pos = sub2ind([d1 d2 d3 d4 d5 d6 d7], 1, 1, 1, ...
img_idx(t), dim5_idx(i5),dim6_idx(i6),dim7_idx(i7)) -1;
pos = pos * hdr.dime.bitpix/8;
if filetype == 2
fseek(fid, pos + hdr.dime.vox_offset, 'bof');
else
fseek(fid, pos, 'bof');
end
% For each frame, fread will read precision of value
% in img_siz times
%
img(:,currentIndex) = fread(fid, img_siz, sprintf('*%s',precision));
currentIndex = currentIndex +1;
end
end
end
end
end
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
img = reshape(img, [2, length(img)/2]);
img = complex(img(1,:)', img(2,:)');
end
fclose(fid);
% Update the global min and max values
%
hdr.dime.glmax = double(max(img(:)));
hdr.dime.glmin = double(min(img(:)));
% old_RGB treat RGB slice by slice, now it is treated voxel by voxel
%
if old_RGB & hdr.dime.datatype == 128 & hdr.dime.bitpix == 24
% remove squeeze
img = (reshape(img, [hdr.dime.dim(2:3) 3 hdr.dime.dim(4) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
img = permute(img, [1 2 4 3 5 6 7 8]);
elseif hdr.dime.datatype == 128 & hdr.dime.bitpix == 24
% remove squeeze
img = (reshape(img, [3 hdr.dime.dim(2:4) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
img = permute(img, [2 3 4 1 5 6 7 8]);
elseif hdr.dime.datatype == 511 & hdr.dime.bitpix == 96
img = double(img(:));
img = single((img - min(img))/(max(img) - min(img)));
% remove squeeze
img = (reshape(img, [3 hdr.dime.dim(2:4) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
img = permute(img, [2 3 4 1 5 6 7 8]);
else
% remove squeeze
img = (reshape(img, [hdr.dime.dim(2:4) length(img_idx) length(dim5_idx) length(dim6_idx) length(dim7_idx)]));
end
if ~isempty(img_idx)
hdr.dime.dim(5) = length(img_idx);
end
if ~isempty(dim5_idx)
hdr.dime.dim(6) = length(dim5_idx);
end
if ~isempty(dim6_idx)
hdr.dime.dim(7) = length(dim6_idx);
end
if ~isempty(dim7_idx)
hdr.dime.dim(8) = length(dim7_idx);
end
return % read_image
|
github
|
sunhongfu/scripts-master
|
bresenham_line3d.m
|
.m
|
scripts-master/cs-phase/_src/_nii/bresenham_line3d.m
| 4,682 |
utf_8
|
f2e52d1f3ac9779b22baf3bb4d2ac201
|
% Generate X Y Z coordinates of a 3D Bresenham's line between
% two given points.
%
% A very useful application of this algorithm can be found in the
% implementation of Fischer's Bresenham interpolation method in my
% another program that can rotate three dimensional image volume
% with an affine matrix:
% http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=21080
%
% Usage: [X Y Z] = bresenham_line3d(P1, P2, [precision]);
%
% P1 - vector for Point1, where P1 = [x1 y1 z1]
%
% P2 - vector for Point2, where P2 = [x2 y2 z2]
%
% precision (optional) - Although according to Bresenham's line
% algorithm, point coordinates x1 y1 z1 and x2 y2 z2 should
% be integer numbers, this program extends its limit to all
% real numbers. If any of them are floating numbers, you
% should specify how many digits of decimal that you would
% like to preserve. Be aware that the length of output X Y
% Z coordinates will increase in 10 times for each decimal
% digit that you want to preserve. By default, the precision
% is 0, which means that they will be rounded to the nearest
% integer.
%
% X - a set of x coordinates on Bresenham's line
%
% Y - a set of y coordinates on Bresenham's line
%
% Z - a set of z coordinates on Bresenham's line
%
% Therefore, all points in XYZ set (i.e. P(i) = [X(i) Y(i) Z(i)])
% will constitute the Bresenham's line between P1 and P1.
%
% Example:
% P1 = [12 37 6]; P2 = [46 3 35];
% [X Y Z] = bresenham_line3d(P1, P2);
% figure; plot3(X,Y,Z,'s','markerface','b');
%
% This program is ported to MATLAB from:
%
% B.Pendleton. line3d - 3D Bresenham's (a 3D line drawing algorithm)
% ftp://ftp.isc.org/pub/usenet/comp.sources.unix/volume26/line3d, 1992
%
% Which is also referenced by:
%
% Fischer, J., A. del Rio (2004). A Fast Method for Applying Rigid
% Transformations to Volume Data, WSCG2004 Conference.
% http://wscg.zcu.cz/wscg2004/Papers_2004_Short/M19.pdf
%
% - Jimmy Shen ([email protected])
%
function [X,Y,Z] = bresenham_line3d(P1, P2, precision)
if ~exist('precision','var') | isempty(precision) | round(precision) == 0
precision = 0;
P1 = round(P1);
P2 = round(P2);
else
precision = round(precision);
P1 = round(P1*(10^precision));
P2 = round(P2*(10^precision));
end
d = max(abs(P2-P1)+1);
X = zeros(1, d);
Y = zeros(1, d);
Z = zeros(1, d);
x1 = P1(1);
y1 = P1(2);
z1 = P1(3);
x2 = P2(1);
y2 = P2(2);
z2 = P2(3);
dx = x2 - x1;
dy = y2 - y1;
dz = z2 - z1;
ax = abs(dx)*2;
ay = abs(dy)*2;
az = abs(dz)*2;
sx = sign(dx);
sy = sign(dy);
sz = sign(dz);
x = x1;
y = y1;
z = z1;
idx = 1;
if(ax>=max(ay,az)) % x dominant
yd = ay - ax/2;
zd = az - ax/2;
while(1)
X(idx) = x;
Y(idx) = y;
Z(idx) = z;
idx = idx + 1;
if(x == x2) % end
break;
end
if(yd >= 0) % move along y
y = y + sy;
yd = yd - ax;
end
if(zd >= 0) % move along z
z = z + sz;
zd = zd - ax;
end
x = x + sx; % move along x
yd = yd + ay;
zd = zd + az;
end
elseif(ay>=max(ax,az)) % y dominant
xd = ax - ay/2;
zd = az - ay/2;
while(1)
X(idx) = x;
Y(idx) = y;
Z(idx) = z;
idx = idx + 1;
if(y == y2) % end
break;
end
if(xd >= 0) % move along x
x = x + sx;
xd = xd - ay;
end
if(zd >= 0) % move along z
z = z + sz;
zd = zd - ay;
end
y = y + sy; % move along y
xd = xd + ax;
zd = zd + az;
end
elseif(az>=max(ax,ay)) % z dominant
xd = ax - az/2;
yd = ay - az/2;
while(1)
X(idx) = x;
Y(idx) = y;
Z(idx) = z;
idx = idx + 1;
if(z == z2) % end
break;
end
if(xd >= 0) % move along x
x = x + sx;
xd = xd - az;
end
if(yd >= 0) % move along y
y = y + sy;
yd = yd - az;
end
z = z + sz; % move along z
xd = xd + ax;
yd = yd + ay;
end
end
if precision ~= 0
X = X/(10^precision);
Y = Y/(10^precision);
Z = Z/(10^precision);
end
return; % bresenham_line3d
|
github
|
sunhongfu/scripts-master
|
make_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/make_nii.m
| 7,105 |
utf_8
|
6b1565392965b164217621e71d213ddd
|
% Make NIfTI structure specified by an N-D matrix. Usually, N is 3 for
% 3D matrix [x y z], or 4 for 4D matrix with time series [x y z t].
% Optional parameters can also be included, such as: voxel_size,
% origin, datatype, and description.
%
% Once the NIfTI structure is made, it can be saved into NIfTI file
% using "save_nii" command (for more detail, type: help save_nii).
%
% Usage: nii = make_nii(img, [voxel_size], [origin], [datatype], [description])
%
% Where:
%
% img: Usually, img is a 3D matrix [x y z], or a 4D
% matrix with time series [x y z t]. However,
% NIfTI allows a maximum of 7D matrix. When the
% image is in RGB format, make sure that the size
% of 4th dimension is always 3 (i.e. [R G B]). In
% that case, make sure that you must specify RGB
% datatype, which is either 128 or 511.
%
% voxel_size (optional): Voxel size in millimeter for each
% dimension. Default is [1 1 1].
%
% origin (optional): The AC origin. Default is [0 0 0].
%
% datatype (optional): Storage data type:
% 2 - uint8, 4 - int16, 8 - int32, 16 - float32,
% 32 - complex64, 64 - float64, 128 - RGB24,
% 256 - int8, 511 - RGB96, 512 - uint16,
% 768 - uint32, 1792 - complex128
% Default will use the data type of 'img' matrix
% For RGB image, you must specify it to either 128
% or 511.
%
% description (optional): Description of data. Default is ''.
%
% e.g.:
% origin = [33 44 13]; datatype = 64;
% nii = make_nii(img, [], origin, datatype); % default voxel_size
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function nii = make_nii(varargin)
nii.img = varargin{1};
dims = size(nii.img);
dims = [length(dims) dims ones(1,8)];
dims = dims(1:8);
voxel_size = [0 ones(1,7)];
origin = zeros(1,5);
descrip = '';
switch class(nii.img)
case 'uint8'
datatype = 2;
case 'int16'
datatype = 4;
case 'int32'
datatype = 8;
case 'single'
if isreal(nii.img)
datatype = 16;
else
datatype = 32;
end
case 'double'
if isreal(nii.img)
datatype = 64;
else
datatype = 1792;
end
case 'int8'
datatype = 256;
case 'uint16'
datatype = 512;
case 'uint32'
datatype = 768;
otherwise
error('Datatype is not supported by make_nii.');
end
if nargin > 1 & ~isempty(varargin{2})
voxel_size(2:4) = double(varargin{2});
end
if nargin > 2 & ~isempty(varargin{3})
origin(1:3) = double(varargin{3});
end
if nargin > 3 & ~isempty(varargin{4})
datatype = double(varargin{4});
if datatype == 128 | datatype == 511
dims(5) = [];
dims(1) = dims(1) - 1;
dims = [dims 1];
end
end
if nargin > 4 & ~isempty(varargin{5})
descrip = varargin{5};
end
if ndims(nii.img) > 7
error('NIfTI only allows a maximum of 7 Dimension matrix.');
end
maxval = round(double(max(nii.img(:))));
minval = round(double(min(nii.img(:))));
nii.hdr = make_header(dims, voxel_size, origin, datatype, ...
descrip, maxval, minval);
switch nii.hdr.dime.datatype
case 2
nii.img = uint8(nii.img);
case 4
nii.img = int16(nii.img);
case 8
nii.img = int32(nii.img);
case 16
nii.img = single(nii.img);
case 32
nii.img = single(nii.img);
case 64
nii.img = double(nii.img);
case 128
nii.img = uint8(nii.img);
case 256
nii.img = int8(nii.img);
case 511
img = double(nii.img(:));
img = single((img - min(img))/(max(img) - min(img)));
nii.img = reshape(img, size(nii.img));
nii.hdr.dime.glmax = double(max(img));
nii.hdr.dime.glmin = double(min(img));
case 512
nii.img = uint16(nii.img);
case 768
nii.img = uint32(nii.img);
case 1792
nii.img = double(nii.img);
otherwise
error('Datatype is not supported by make_nii.');
end
return; % make_nii
%---------------------------------------------------------------------
function hdr = make_header(dims, voxel_size, origin, datatype, ...
descrip, maxval, minval)
hdr.hk = header_key;
hdr.dime = image_dimension(dims, voxel_size, datatype, maxval, minval);
hdr.hist = data_history(origin, descrip);
return; % make_header
%---------------------------------------------------------------------
function hk = header_key
hk.sizeof_hdr = 348; % must be 348!
hk.data_type = '';
hk.db_name = '';
hk.extents = 0;
hk.session_error = 0;
hk.regular = 'r';
hk.dim_info = 0;
return; % header_key
%---------------------------------------------------------------------
function dime = image_dimension(dims, voxel_size, datatype, maxval, minval)
dime.dim = dims;
dime.intent_p1 = 0;
dime.intent_p2 = 0;
dime.intent_p3 = 0;
dime.intent_code = 0;
dime.datatype = datatype;
switch dime.datatype
case 2,
dime.bitpix = 8; precision = 'uint8';
case 4,
dime.bitpix = 16; precision = 'int16';
case 8,
dime.bitpix = 32; precision = 'int32';
case 16,
dime.bitpix = 32; precision = 'float32';
case 32,
dime.bitpix = 64; precision = 'float32';
case 64,
dime.bitpix = 64; precision = 'float64';
case 128
dime.bitpix = 24; precision = 'uint8';
case 256
dime.bitpix = 8; precision = 'int8';
case 511
dime.bitpix = 96; precision = 'float32';
case 512
dime.bitpix = 16; precision = 'uint16';
case 768
dime.bitpix = 32; precision = 'uint32';
case 1792,
dime.bitpix = 128; precision = 'float64';
otherwise
error('Datatype is not supported by make_nii.');
end
dime.slice_start = 0;
dime.pixdim = voxel_size;
dime.vox_offset = 0;
dime.scl_slope = 0;
dime.scl_inter = 0;
dime.slice_end = 0;
dime.slice_code = 0;
dime.xyzt_units = 0;
dime.cal_max = 0;
dime.cal_min = 0;
dime.slice_duration = 0;
dime.toffset = 0;
dime.glmax = maxval;
dime.glmin = minval;
return; % image_dimension
%---------------------------------------------------------------------
function hist = data_history(origin, descrip)
hist.descrip = descrip;
hist.aux_file = 'none';
hist.qform_code = 0;
hist.sform_code = 0;
hist.quatern_b = 0;
hist.quatern_c = 0;
hist.quatern_d = 0;
hist.qoffset_x = 0;
hist.qoffset_y = 0;
hist.qoffset_z = 0;
hist.srow_x = zeros(1,4);
hist.srow_y = zeros(1,4);
hist.srow_z = zeros(1,4);
hist.intent_name = '';
hist.magic = '';
hist.originator = origin;
return; % data_history
|
github
|
sunhongfu/scripts-master
|
verify_nii_ext.m
|
.m
|
scripts-master/cs-phase/_src/_nii/verify_nii_ext.m
| 1,721 |
utf_8
|
0339aeb8d7286e4f08165c9eeeb4c2cd
|
% Verify NIFTI header extension to make sure that each extension section
% must be an integer multiple of 16 byte long that includes the first 8
% bytes of esize and ecode. If the length of extension section is not the
% above mentioned case, edata should be padded with all 0.
%
% Usage: [ext, esize_total] = verify_nii_ext(ext)
%
% ext - Structure of NIFTI header extension, which includes num_ext,
% and all the extended header sections in the header extension.
% Each extended header section will have its esize, ecode, and
% edata, where edata can be plain text, xml, or any raw data
% that was saved in the extended header section.
%
% esize_total - Sum of all esize variable in all header sections.
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function [ext, esize_total] = verify_nii_ext(ext)
if ~isfield(ext, 'section')
error('Incorrect NIFTI header extension structure.');
elseif ~isfield(ext, 'num_ext')
ext.num_ext = length(ext.section);
elseif ~isfield(ext, 'extension')
ext.extension = [1 0 0 0];
end
esize_total = 0;
for i=1:ext.num_ext
if ~isfield(ext.section(i), 'ecode') | ~isfield(ext.section(i), 'edata')
error('Incorrect NIFTI header extension structure.');
end
ext.section(i).esize = ceil((length(ext.section(i).edata)+8)/16)*16;
ext.section(i).edata = ...
[ext.section(i).edata ...
zeros(1,ext.section(i).esize-length(ext.section(i).edata)-8)];
esize_total = esize_total + ext.section(i).esize;
end
return % verify_nii_ext
|
github
|
sunhongfu/scripts-master
|
get_nii_frame.m
|
.m
|
scripts-master/cs-phase/_src/_nii/get_nii_frame.m
| 4,497 |
utf_8
|
cc9b1b92f34e5ae67dc34c35a5174c75
|
% Return time frame of a NIFTI dataset. Support both *.nii and
% *.hdr/*.img file extension. If file extension is not provided,
% *.hdr/*.img will be used as default.
%
% It is a lightweighted "load_nii_hdr", and is equivalent to
% hdr.dime.dim(5)
%
% Usage: [ total_scan ] = get_nii_frame(filename)
%
% filename - NIFTI file name.
%
% Returned values:
%
% total_scan - total number of image scans for the time frame
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function [ total_scan ] = get_nii_frame(filename)
if ~exist('filename','var'),
error('Usage: [ total_scan ] = get_nii_frame(filename)');
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
elseif strcmp(filename(end-6:end), '.img.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.hdr.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.hdr.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.img.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.nii.gz')
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename = gunzip(filename, tmpDir);
filename = char(filename); % convert from cell to string
end
end
fileprefix = filename;
machine = 'ieee-le';
new_ext = 0;
if findstr('.nii',fileprefix) & strcmp(fileprefix(end-3:end), '.nii')
new_ext = 1;
fileprefix(end-3:end)='';
end
if findstr('.hdr',fileprefix) & strcmp(fileprefix(end-3:end), '.hdr')
fileprefix(end-3:end)='';
end
if findstr('.img',fileprefix) & strcmp(fileprefix(end-3:end), '.img')
fileprefix(end-3:end)='';
end
if new_ext
fn = sprintf('%s.nii',fileprefix);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.nii".', fileprefix);
error(msg);
end
else
fn = sprintf('%s.hdr',fileprefix);
if ~exist(fn)
msg = sprintf('Cannot find file "%s.hdr".', fileprefix);
error(msg);
end
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
hdr = read_header(fid);
fclose(fid);
end
if hdr.sizeof_hdr ~= 348
% first try reading the opposite endian to 'machine'
switch machine,
case 'ieee-le', machine = 'ieee-be';
case 'ieee-be', machine = 'ieee-le';
end
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
hdr = read_header(fid);
fclose(fid);
end
end
if hdr.sizeof_hdr ~= 348
% Now throw an error
msg = sprintf('File "%s" is corrupted.',fn);
error(msg);
end
total_scan = hdr.dim(5);
% Clean up after gunzip
%
if exist('gzFileName', 'var')
rmdir(tmpDir,'s');
end
return; % get_nii_frame
%---------------------------------------------------------------------
function [ dsr ] = read_header(fid)
fseek(fid,0,'bof');
dsr.sizeof_hdr = fread(fid,1,'int32')'; % should be 348!
fseek(fid,40,'bof');
dsr.dim = fread(fid,8,'int16')';
return; % read_header
|
github
|
sunhongfu/scripts-master
|
flip_lr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/flip_lr.m
| 3,568 |
utf_8
|
d95b62698d44a65a3c2f02fbabc632ac
|
% When you load any ANALYZE or NIfTI file with 'load_nii.m', and view
% it with 'view_nii.m', you may find that the image is L-R flipped.
% This is because of the confusion of radiological and neurological
% convention in the medical image before NIfTI format is adopted. You
% can find more details from:
%
% http://www.rotman-baycrest.on.ca/~jimmy/UseANALYZE.htm
%
% Sometime, people even want to convert RAS (standard orientation) back
% to LAS orientation to satisfy the legend programs or processes. This
% program is only written for those purpose. So PLEASE BE VERY CAUTIOUS
% WHEN USING THIS 'FLIP_LR.M' PROGRAM.
%
% With 'flip_lr.m', you can convert any ANALYZE or NIfTI (no matter
% 3D or 4D) file to a flipped NIfTI file. This is implemented simply
% by flipping the affine matrix in the NIfTI header. Since the L-R
% orientation is determined there, so the image will be flipped.
%
% Usage: flip_lr(original_fn, flipped_fn, [old_RGB],[tolerance],[preferredForm])
%
% original_fn - filename of the original ANALYZE or NIfTI (3D or 4D) file
%
% flipped_fn - filename of the L-R flipped NIfTI file
%
% old_RGB (optional) - a scale number to tell difference of new RGB24
% from old RGB24. New RGB24 uses RGB triple sequentially for each
% voxel, like [R1 G1 B1 R2 G2 B2 ...]. Analyze 6.0 from AnalyzeDirect
% uses old RGB24, in a way like [R1 R2 ... G1 G2 ... B1 B2 ...] for
% each slices. If the image that you view is garbled, try to set
% old_RGB variable to 1 and try again, because it could be in
% old RGB24. It will be set to 0, if it is default or empty.
%
% tolerance (optional) - distortion allowed for non-orthogonal rotation
% or shearing in NIfTI affine matrix. It will be set to 0.1 (10%),
% if it is default or empty.
%
% preferredForm (optional) - selects which transformation from voxels
% to RAS coordinates; values are s,q,S,Q. Lower case s,q indicate
% "prefer sform or qform, but use others if preferred not present".
% Upper case indicate the program is forced to use the specificied
% tranform or fail loading. 'preferredForm' will be 's', if it is
% default or empty. - Jeff Gunter
%
% Example: flip_lr('avg152T1_LR_nifti.nii', 'flipped_lr.nii');
% flip_lr('avg152T1_RL_nifti.nii', 'flipped_rl.nii');
%
% You will find that 'avg152T1_LR_nifti.nii' and 'avg152T1_RL_nifti.nii'
% are the same, and 'flipped_lr.nii' and 'flipped_rl.nii' are also the
% the same, but they are L-R flipped from 'avg152T1_*'.
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function flip_lr(original_fn, flipped_fn, old_RGB, tolerance, preferredForm)
if ~exist('original_fn','var') | ~exist('flipped_fn','var')
error('Usage: flip_lr(original_fn, flipped_fn, [old_RGB],[tolerance])');
end
if ~exist('old_RGB','var') | isempty(old_RGB)
old_RGB = 0;
end
if ~exist('tolerance','var') | isempty(tolerance)
tolerance = 0.1;
end
if ~exist('preferredForm','var') | isempty(preferredForm)
preferredForm= 's'; % Jeff
end
nii = load_nii(original_fn, [], [], [], [], old_RGB, tolerance, preferredForm);
M = diag(nii.hdr.dime.pixdim(2:5));
M(1:3,4) = -M(1:3,1:3)*(nii.hdr.hist.originator(1:3)-1)';
M(1,:) = -1*M(1,:);
nii.hdr.hist.sform_code = 1;
nii.hdr.hist.srow_x = M(1,:);
nii.hdr.hist.srow_y = M(2,:);
nii.hdr.hist.srow_z = M(3,:);
save_nii(nii, flipped_fn);
return; % flip_lr
|
github
|
sunhongfu/scripts-master
|
save_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_nii.m
| 9,690 |
utf_8
|
ed292054cab74afaf953455bfbc200aa
|
% Save NIFTI dataset. Support both *.nii and *.hdr/*.img file extension.
% If file extension is not provided, *.hdr/*.img will be used as default.
%
% Usage: save_nii(nii, filename, [old_RGB])
%
% nii.hdr - struct with NIFTI header fields (from load_nii.m or make_nii.m)
%
% nii.img - 3D (or 4D) matrix of NIFTI data.
%
% filename - NIFTI file name.
%
% old_RGB - an optional boolean variable to handle special RGB data
% sequence [R1 R2 ... G1 G2 ... B1 B2 ...] that is used only by
% AnalyzeDirect (Analyze Software). Since both NIfTI and Analyze
% file format use RGB triple [R1 G1 B1 R2 G2 B2 ...] sequentially
% for each voxel, this variable is set to FALSE by default. If you
% would like the saved image only to be opened by AnalyzeDirect
% Software, set old_RGB to TRUE (or 1). It will be set to 0, if it
% is default or empty.
%
% Tip: to change the data type, set nii.hdr.dime.datatype,
% and nii.hdr.dime.bitpix to:
%
% 0 None (Unknown bit per voxel) % DT_NONE, DT_UNKNOWN
% 1 Binary (ubit1, bitpix=1) % DT_BINARY
% 2 Unsigned char (uchar or uint8, bitpix=8) % DT_UINT8, NIFTI_TYPE_UINT8
% 4 Signed short (int16, bitpix=16) % DT_INT16, NIFTI_TYPE_INT16
% 8 Signed integer (int32, bitpix=32) % DT_INT32, NIFTI_TYPE_INT32
% 16 Floating point (single or float32, bitpix=32) % DT_FLOAT32, NIFTI_TYPE_FLOAT32
% 32 Complex, 2 float32 (Use float32, bitpix=64) % DT_COMPLEX64, NIFTI_TYPE_COMPLEX64
% 64 Double precision (double or float64, bitpix=64) % DT_FLOAT64, NIFTI_TYPE_FLOAT64
% 128 uint RGB (Use uint8, bitpix=24) % DT_RGB24, NIFTI_TYPE_RGB24
% 256 Signed char (schar or int8, bitpix=8) % DT_INT8, NIFTI_TYPE_INT8
% 511 Single RGB (Use float32, bitpix=96) % DT_RGB96, NIFTI_TYPE_RGB96
% 512 Unsigned short (uint16, bitpix=16) % DT_UNINT16, NIFTI_TYPE_UNINT16
% 768 Unsigned integer (uint32, bitpix=32) % DT_UNINT32, NIFTI_TYPE_UNINT32
% 1024 Signed long long (int64, bitpix=64) % DT_INT64, NIFTI_TYPE_INT64
% 1280 Unsigned long long (uint64, bitpix=64) % DT_UINT64, NIFTI_TYPE_UINT64
% 1536 Long double, float128 (Unsupported, bitpix=128) % DT_FLOAT128, NIFTI_TYPE_FLOAT128
% 1792 Complex128, 2 float64 (Use float64, bitpix=128) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
% 2048 Complex256, 2 float128 (Unsupported, bitpix=256) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
%
% Part of this file is copied and modified from:
% http://www.mathworks.com/matlabcentral/fileexchange/1878-mri-analyze-tools
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
% - "old_RGB" related codes in "save_nii.m" are added by Mike Harms (2006.06.28)
%
function save_nii(nii, fileprefix, old_RGB)
if ~exist('nii','var') | isempty(nii) | ~isfield(nii,'hdr') | ...
~isfield(nii,'img') | ~exist('fileprefix','var') | isempty(fileprefix)
error('Usage: save_nii(nii, filename, [old_RGB])');
end
if isfield(nii,'untouch') & nii.untouch == 1
error('Usage: please use ''save_untouch_nii.m'' for the untouched structure.');
end
if ~exist('old_RGB','var') | isempty(old_RGB)
old_RGB = 0;
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(fileprefix) > 2 & strcmp(fileprefix(end-2:end), '.gz')
if ~strcmp(fileprefix(end-6:end), '.img.gz') & ...
~strcmp(fileprefix(end-6:end), '.hdr.gz') & ...
~strcmp(fileprefix(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
else
gzFile = 1;
fileprefix = fileprefix(1:end-3);
end
end
filetype = 1;
% Note: fileprefix is actually the filename you want to save
%
if findstr('.nii',fileprefix) & strcmp(fileprefix(end-3:end), '.nii')
filetype = 2;
fileprefix(end-3:end)='';
end
if findstr('.hdr',fileprefix) & strcmp(fileprefix(end-3:end), '.hdr')
fileprefix(end-3:end)='';
end
if findstr('.img',fileprefix) & strcmp(fileprefix(end-3:end), '.img')
fileprefix(end-3:end)='';
end
write_nii(nii, filetype, fileprefix, old_RGB);
% gzip output file if requested
%
if exist('gzFile', 'var')
if filetype == 1
gzip([fileprefix, '.img']);
delete([fileprefix, '.img']);
gzip([fileprefix, '.hdr']);
delete([fileprefix, '.hdr']);
elseif filetype == 2
gzip([fileprefix, '.nii']);
delete([fileprefix, '.nii']);
end;
end;
if filetype == 1
% So earlier versions of SPM can also open it with correct originator
%
M=[[diag(nii.hdr.dime.pixdim(2:4)) -[nii.hdr.hist.originator(1:3).*nii.hdr.dime.pixdim(2:4)]'];[0 0 0 1]];
save([fileprefix '.mat'], 'M');
end
return % save_nii
%-----------------------------------------------------------------------------------
function write_nii(nii, filetype, fileprefix, old_RGB)
hdr = nii.hdr;
if isfield(nii,'ext') & ~isempty(nii.ext)
ext = nii.ext;
[ext, esize_total] = verify_nii_ext(ext);
else
ext = [];
end
switch double(hdr.dime.datatype),
case 1,
hdr.dime.bitpix = int16(1 ); precision = 'ubit1';
case 2,
hdr.dime.bitpix = int16(8 ); precision = 'uint8';
case 4,
hdr.dime.bitpix = int16(16); precision = 'int16';
case 8,
hdr.dime.bitpix = int16(32); precision = 'int32';
case 16,
hdr.dime.bitpix = int16(32); precision = 'float32';
case 32,
hdr.dime.bitpix = int16(64); precision = 'float32';
case 64,
hdr.dime.bitpix = int16(64); precision = 'float64';
case 128,
hdr.dime.bitpix = int16(24); precision = 'uint8';
case 256
hdr.dime.bitpix = int16(8 ); precision = 'int8';
case 511,
hdr.dime.bitpix = int16(96); precision = 'float32';
case 512
hdr.dime.bitpix = int16(16); precision = 'uint16';
case 768
hdr.dime.bitpix = int16(32); precision = 'uint32';
case 1024
hdr.dime.bitpix = int16(64); precision = 'int64';
case 1280
hdr.dime.bitpix = int16(64); precision = 'uint64';
case 1792,
hdr.dime.bitpix = int16(128); precision = 'float64';
otherwise
error('This datatype is not supported');
end
hdr.dime.glmax = round(double(max(nii.img(:))));
hdr.dime.glmin = round(double(min(nii.img(:))));
if filetype == 2
fid = fopen(sprintf('%s.nii',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.nii.',fileprefix);
error(msg);
end
hdr.dime.vox_offset = 352;
if ~isempty(ext)
hdr.dime.vox_offset = hdr.dime.vox_offset + esize_total;
end
hdr.hist.magic = 'n+1';
save_nii_hdr(hdr, fid);
if ~isempty(ext)
save_nii_ext(ext, fid);
end
else
fid = fopen(sprintf('%s.hdr',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.hdr.',fileprefix);
error(msg);
end
hdr.dime.vox_offset = 0;
hdr.hist.magic = 'ni1';
save_nii_hdr(hdr, fid);
if ~isempty(ext)
save_nii_ext(ext, fid);
end
fclose(fid);
fid = fopen(sprintf('%s.img',fileprefix),'w');
end
ScanDim = double(hdr.dime.dim(5)); % t
SliceDim = double(hdr.dime.dim(4)); % z
RowDim = double(hdr.dime.dim(3)); % y
PixelDim = double(hdr.dime.dim(2)); % x
SliceSz = double(hdr.dime.pixdim(4));
RowSz = double(hdr.dime.pixdim(3));
PixelSz = double(hdr.dime.pixdim(2));
x = 1:PixelDim;
if filetype == 2 & isempty(ext)
skip_bytes = double(hdr.dime.vox_offset) - 348;
else
skip_bytes = 0;
end
if double(hdr.dime.datatype) == 128
% RGB planes are expected to be in the 4th dimension of nii.img
%
if(size(nii.img,4)~=3)
error(['The NII structure does not appear to have 3 RGB color planes in the 4th dimension']);
end
if old_RGB
nii.img = permute(nii.img, [1 2 4 3 5 6 7 8]);
else
nii.img = permute(nii.img, [4 1 2 3 5 6 7 8]);
end
end
if double(hdr.dime.datatype) == 511
% RGB planes are expected to be in the 4th dimension of nii.img
%
if(size(nii.img,4)~=3)
error(['The NII structure does not appear to have 3 RGB color planes in the 4th dimension']);
end
if old_RGB
nii.img = permute(nii.img, [1 2 4 3 5 6 7 8]);
else
nii.img = permute(nii.img, [4 1 2 3 5 6 7 8]);
end
end
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
real_img = real(nii.img(:))';
nii.img = imag(nii.img(:))';
nii.img = [real_img; nii.img];
end
if skip_bytes
fwrite(fid, zeros(1,skip_bytes), 'uint8');
end
fwrite(fid, nii.img, precision);
% fwrite(fid, nii.img, precision, skip_bytes); % error using skip
fclose(fid);
return; % write_nii
|
github
|
sunhongfu/scripts-master
|
rri_file_menu.m
|
.m
|
scripts-master/cs-phase/_src/_nii/rri_file_menu.m
| 4,153 |
utf_8
|
c9faa3905c642854eeed98ab8b02998e
|
% Imbed a file menu to any figure. If file menu exist, it will append
% to the existing file menu. This file menu includes: Copy to clipboard,
% print, save, close etc.
%
% Usage: rri_file_menu(fig);
%
% rri_file_menu(fig,0) means no 'Close' menu.
%
% - Jimmy Shen ([email protected])
%
%--------------------------------------------------------------------
function rri_file_menu(action, varargin)
if isnumeric(action)
fig = action;
action = 'init';
end
% clear the message line,
%
h = findobj(gcf,'Tag','MessageLine');
set(h,'String','');
if ~strcmp(action, 'init')
set(gcbf, 'InvertHardcopy','off');
% set(gcbf, 'PaperPositionMode','auto');
end
switch action
case {'init'}
if nargin > 1
init(fig, 1); % no 'close' menu
else
init(fig, 0);
end
case {'print_fig'}
printdlg(gcbf);
case {'copy_fig'}
copy_fig;
case {'export_fig'}
export_fig;
end
return % rri_file_menu
%------------------------------------------------
%
% Create (or append) File menu
%
function init(fig, no_close)
% search for file menu
%
h_file = [];
menuitems = findobj(fig, 'type', 'uimenu');
for i=1:length(menuitems)
filelabel = get(menuitems(i),'label');
if strcmpi(strrep(filelabel, '&', ''), 'file')
h_file = menuitems(i);
break;
end
end
set(fig, 'menubar', 'none');
if isempty(h_file)
if isempty(menuitems)
h_file = uimenu('parent', fig, 'label', 'File');
else
h_file = uimenu('parent', fig, 'label', 'Copy Figure');
end
h1 = uimenu('parent', h_file, ...
'callback','rri_file_menu(''copy_fig'');', ...
'label','Copy to Clipboard');
else
h1 = uimenu('parent', h_file, ...
'callback','rri_file_menu(''copy_fig'');', ...
'separator','on', ...
'label','Copy to Clipboard');
end
h2 = uimenu(h_file, ...
'callback','pagesetupdlg(gcbf);', ...
'label','Page Setup...');
h2 = uimenu(h_file, ...
'callback','printpreview(gcbf);', ...
'label','Print Preview...');
h2 = uimenu('parent', h_file, ...
'callback','printdlg(gcbf);', ...
'label','Print Figure ...');
h2 = uimenu('parent', h_file, ...
'callback','rri_file_menu(''export_fig'');', ...
'label','Save Figure ...');
arch = computer;
if ~strcmpi(arch(1:2),'PC')
set(h1, 'enable', 'off');
end
if ~no_close
h1 = uimenu('parent', h_file, ...
'callback','close(gcbf);', ...
'separator','on', ...
'label','Close');
end
return; % init
%------------------------------------------------
%
% Copy to clipboard
%
function copy_fig
arch = computer;
if(~strcmpi(arch(1:2),'PC'))
error('copy to clipboard can only be used under MS Windows');
return;
end
print -noui -dbitmap;
return % copy_fig
%------------------------------------------------
%
% Save as an image file
%
function export_fig
curr = pwd;
if isempty(curr)
curr = filesep;
end
[selected_file, selected_path] = rri_select_file(curr,'Save As');
if isempty(selected_file) | isempty(selected_path)
return;
end
filename = [selected_path selected_file];
if(exist(filename,'file')==2) % file exist
dlg_title = 'Confirm File Overwrite';
msg = ['File ',filename,' exist. Are you sure you want to overwrite it?'];
response = questdlg(msg,dlg_title,'Yes','No','Yes');
if(strcmp(response,'No'))
return;
end
end
old_pointer = get(gcbf,'pointer');
set(gcbf,'pointer','watch');
try
saveas(gcbf,filename);
catch
msg = 'ERROR: Cannot save file';
set(findobj(gcf,'Tag','MessageLine'),'String',msg);
end
set(gcbf,'pointer',old_pointer);
return; % export_fig
|
github
|
sunhongfu/scripts-master
|
reslice_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/reslice_nii.m
| 10,138 |
utf_8
|
ea18d2f994fd5d9989449feaced1e4dd
|
% The basic application of the 'reslice_nii.m' program is to perform
% any 3D affine transform defined by a NIfTI format image.
%
% In addition, the 'reslice_nii.m' program can also be applied to
% generate an isotropic image from either a NIfTI format image or
% an ANALYZE format image.
%
% The resliced NIfTI file will always be in RAS orientation.
%
% This program only supports real integer or floating-point data type.
% For other data type, the program will exit with an error message
% "Transform of this NIFTI data is not supported by the program".
%
% Usage: reslice_nii(old_fn, new_fn, [voxel_size], [verbose], [bg], ...
% [method], [img_idx], [preferredForm]);
%
% old_fn - filename for original NIfTI file
%
% new_fn - filename for resliced NIfTI file
%
% voxel_size (optional) - size of a voxel in millimeter along x y z
% direction for resliced NIfTI file. 'voxel_size' will use
% the minimum voxel_size in original NIfTI header,
% if it is default or empty.
%
% verbose (optional) - 1, 0
% 1: show transforming progress in percentage
% 2: progress will not be displayed
% 'verbose' is 1 if it is default or empty.
%
% bg (optional) - background voxel intensity in any extra corner that
% is caused by 3D interpolation. 0 in most cases. 'bg'
% will be the average of two corner voxel intensities
% in original image volume, if it is default or empty.
%
% method (optional) - 1, 2, or 3
% 1: for Trilinear interpolation
% 2: for Nearest Neighbor interpolation
% 3: for Fischer's Bresenham interpolation
% 'method' is 1 if it is default or empty.
%
% img_idx (optional) - a numerical array of image volume indices. Only
% the specified volumes will be loaded. All available image
% volumes will be loaded, if it is default or empty.
%
% The number of images scans can be obtained from get_nii_frame.m,
% or simply: hdr.dime.dim(5).
%
% preferredForm (optional) - selects which transformation from voxels
% to RAS coordinates; values are s,q,S,Q. Lower case s,q indicate
% "prefer sform or qform, but use others if preferred not present".
% Upper case indicate the program is forced to use the specificied
% tranform or fail loading. 'preferredForm' will be 's', if it is
% default or empty. - Jeff Gunter
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function reslice_nii(old_fn, new_fn, voxel_size, verbose, bg, method, img_idx, preferredForm)
if ~exist('old_fn','var') | ~exist('new_fn','var')
error('Usage: reslice_nii(old_fn, new_fn, [voxel_size], [verbose], [bg], [method], [img_idx])');
end
if ~exist('method','var') | isempty(method)
method = 1;
end
if ~exist('img_idx','var') | isempty(img_idx)
img_idx = [];
end
if ~exist('verbose','var') | isempty(verbose)
verbose = 1;
end
if ~exist('preferredForm','var') | isempty(preferredForm)
preferredForm= 's'; % Jeff
end
nii = load_nii_no_xform(old_fn, img_idx, 0, preferredForm);
if ~ismember(nii.hdr.dime.datatype, [2,4,8,16,64,256,512,768])
error('Transform of this NIFTI data is not supported by the program.');
end
if ~exist('voxel_size','var') | isempty(voxel_size)
voxel_size = abs(min(nii.hdr.dime.pixdim(2:4)))*ones(1,3);
elseif length(voxel_size) < 3
voxel_size = abs(voxel_size(1))*ones(1,3);
end
if ~exist('bg','var') | isempty(bg)
bg = mean([nii.img(1) nii.img(end)]);
end
old_M = nii.hdr.hist.old_affine;
if nii.hdr.dime.dim(5) > 1
for i = 1:nii.hdr.dime.dim(5)
if verbose
fprintf('Reslicing %d of %d volumes.\n', i, nii.hdr.dime.dim(5));
end
[img(:,:,:,i) M] = ...
affine(nii.img(:,:,:,i), old_M, voxel_size, verbose, bg, method);
end
else
[img M] = affine(nii.img, old_M, voxel_size, verbose, bg, method);
end
new_dim = size(img);
nii.img = img;
nii.hdr.dime.dim(2:4) = new_dim(1:3);
nii.hdr.dime.datatype = 16;
nii.hdr.dime.bitpix = 32;
nii.hdr.dime.pixdim(2:4) = voxel_size(:)';
nii.hdr.dime.glmax = max(img(:));
nii.hdr.dime.glmin = min(img(:));
nii.hdr.hist.qform_code = 0;
nii.hdr.hist.sform_code = 1;
nii.hdr.hist.srow_x = M(1,:);
nii.hdr.hist.srow_y = M(2,:);
nii.hdr.hist.srow_z = M(3,:);
nii.hdr.hist.new_affine = M;
save_nii(nii, new_fn);
return; % reslice_nii
%--------------------------------------------------------------------
function [nii] = load_nii_no_xform(filename, img_idx, old_RGB, preferredForm)
if ~exist('filename','var'),
error('Usage: [nii] = load_nii(filename, [img_idx], [old_RGB])');
end
if ~exist('img_idx','var'), img_idx = []; end
if ~exist('old_RGB','var'), old_RGB = 0; end
if ~exist('preferredForm','var'), preferredForm= 's'; end % Jeff
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
elseif strcmp(filename(end-6:end), '.img.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.hdr.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.hdr.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.img.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.nii.gz')
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename = gunzip(filename, tmpDir);
filename = char(filename); % convert from cell to string
end
end
% Read the dataset header
%
[nii.hdr,nii.filetype,nii.fileprefix,nii.machine] = load_nii_hdr(filename);
% Read the header extension
%
% nii.ext = load_nii_ext(filename);
% Read the dataset body
%
[nii.img,nii.hdr] = ...
load_nii_img(nii.hdr,nii.filetype,nii.fileprefix,nii.machine,img_idx,'','','',old_RGB);
% Perform some of sform/qform transform
%
% nii = xform_nii(nii, preferredForm);
% Clean up after gunzip
%
if exist('gzFileName', 'var')
% fix fileprefix so it doesn't point to temp location
%
nii.fileprefix = gzFileName(1:end-7);
rmdir(tmpDir,'s');
end
hdr = nii.hdr;
% NIFTI can have both sform and qform transform. This program
% will check sform_code prior to qform_code by default.
%
% If user specifys "preferredForm", user can then choose the
% priority. - Jeff
%
useForm=[]; % Jeff
if isequal(preferredForm,'S')
if isequal(hdr.hist.sform_code,0)
error('User requires sform, sform not set in header');
else
useForm='s';
end
end % Jeff
if isequal(preferredForm,'Q')
if isequal(hdr.hist.qform_code,0)
error('User requires sform, sform not set in header');
else
useForm='q';
end
end % Jeff
if isequal(preferredForm,'s')
if hdr.hist.sform_code > 0
useForm='s';
elseif hdr.hist.qform_code > 0
useForm='q';
end
end % Jeff
if isequal(preferredForm,'q')
if hdr.hist.qform_code > 0
useForm='q';
elseif hdr.hist.sform_code > 0
useForm='s';
end
end % Jeff
if isequal(useForm,'s')
R = [hdr.hist.srow_x(1:3)
hdr.hist.srow_y(1:3)
hdr.hist.srow_z(1:3)];
T = [hdr.hist.srow_x(4)
hdr.hist.srow_y(4)
hdr.hist.srow_z(4)];
nii.hdr.hist.old_affine = [ [R;[0 0 0]] [T;1] ];
elseif isequal(useForm,'q')
b = hdr.hist.quatern_b;
c = hdr.hist.quatern_c;
d = hdr.hist.quatern_d;
if 1.0-(b*b+c*c+d*d) < 0
if abs(1.0-(b*b+c*c+d*d)) < 1e-5
a = 0;
else
error('Incorrect quaternion values in this NIFTI data.');
end
else
a = sqrt(1.0-(b*b+c*c+d*d));
end
qfac = hdr.dime.pixdim(1);
i = hdr.dime.pixdim(2);
j = hdr.dime.pixdim(3);
k = qfac * hdr.dime.pixdim(4);
R = [a*a+b*b-c*c-d*d 2*b*c-2*a*d 2*b*d+2*a*c
2*b*c+2*a*d a*a+c*c-b*b-d*d 2*c*d-2*a*b
2*b*d-2*a*c 2*c*d+2*a*b a*a+d*d-c*c-b*b];
T = [hdr.hist.qoffset_x
hdr.hist.qoffset_y
hdr.hist.qoffset_z];
nii.hdr.hist.old_affine = [ [R * diag([i j k]);[0 0 0]] [T;1] ];
elseif nii.filetype == 0 & exist([nii.fileprefix '.mat'],'file')
load([nii.fileprefix '.mat']); % old SPM affine matrix
R=M(1:3,1:3);
T=M(1:3,4);
T=R*ones(3,1)+T;
M(1:3,4)=T;
nii.hdr.hist.old_affine = M;
else
M = diag(hdr.dime.pixdim(2:5));
M(1:3,4) = -M(1:3,1:3)*(hdr.hist.originator(1:3)-1)';
M(4,4) = 1;
nii.hdr.hist.old_affine = M;
end
return % load_nii_no_xform
|
github
|
sunhongfu/scripts-master
|
save_untouch_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_untouch_nii.m
| 6,726 |
utf_8
|
cb98e2799abc112dca5b10078bde09bf
|
% Save NIFTI or ANALYZE dataset that is loaded by "load_untouch_nii.m".
% The output image format and file extension will be the same as the
% input one (NIFTI.nii, NIFTI.img or ANALYZE.img). Therefore, any file
% extension that you specified will be ignored.
%
% Usage: save_untouch_nii(nii, filename)
%
% nii - nii structure that is loaded by "load_untouch_nii.m"
%
% filename - NIFTI or ANALYZE file name.
%
% - Jimmy Shen ([email protected])
%
function save_untouch_nii(nii, filename)
if ~exist('nii','var') | isempty(nii) | ~isfield(nii,'hdr') | ...
~isfield(nii,'img') | ~exist('filename','var') | isempty(filename)
error('Usage: save_untouch_nii(nii, filename)');
end
if ~isfield(nii,'untouch') | nii.untouch == 0
error('Usage: please use ''save_nii.m'' for the modified structure.');
end
if isfield(nii.hdr.hist,'magic') & strcmp(nii.hdr.hist.magic(1:3),'ni1')
filetype = 1;
elseif isfield(nii.hdr.hist,'magic') & strcmp(nii.hdr.hist.magic(1:3),'n+1')
filetype = 2;
else
filetype = 0;
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
else
gzFile = 1;
filename = filename(1:end-3);
end
end
[p,f] = fileparts(filename);
fileprefix = fullfile(p, f);
write_nii(nii, filetype, fileprefix);
% gzip output file if requested
%
if exist('gzFile', 'var')
if filetype == 1
gzip([fileprefix, '.img']);
delete([fileprefix, '.img']);
gzip([fileprefix, '.hdr']);
delete([fileprefix, '.hdr']);
elseif filetype == 2
gzip([fileprefix, '.nii']);
delete([fileprefix, '.nii']);
end;
end;
% % So earlier versions of SPM can also open it with correct originator
% %
% if filetype == 0
% M=[[diag(nii.hdr.dime.pixdim(2:4)) -[nii.hdr.hist.originator(1:3).*nii.hdr.dime.pixdim(2:4)]'];[0 0 0 1]];
% save(fileprefix, 'M');
% elseif filetype == 1
% M=[];
% save(fileprefix, 'M');
%end
return % save_untouch_nii
%-----------------------------------------------------------------------------------
function write_nii(nii, filetype, fileprefix)
hdr = nii.hdr;
if isfield(nii,'ext') & ~isempty(nii.ext)
ext = nii.ext;
[ext, esize_total] = verify_nii_ext(ext);
else
ext = [];
end
switch double(hdr.dime.datatype),
case 1,
hdr.dime.bitpix = int16(1 ); precision = 'ubit1';
case 2,
hdr.dime.bitpix = int16(8 ); precision = 'uint8';
case 4,
hdr.dime.bitpix = int16(16); precision = 'int16';
case 8,
hdr.dime.bitpix = int16(32); precision = 'int32';
case 16,
hdr.dime.bitpix = int16(32); precision = 'float32';
case 32,
hdr.dime.bitpix = int16(64); precision = 'float32';
case 64,
hdr.dime.bitpix = int16(64); precision = 'float64';
case 128,
hdr.dime.bitpix = int16(24); precision = 'uint8';
case 256
hdr.dime.bitpix = int16(8 ); precision = 'int8';
case 512
hdr.dime.bitpix = int16(16); precision = 'uint16';
case 768
hdr.dime.bitpix = int16(32); precision = 'uint32';
case 1024
hdr.dime.bitpix = int16(64); precision = 'int64';
case 1280
hdr.dime.bitpix = int16(64); precision = 'uint64';
case 1792,
hdr.dime.bitpix = int16(128); precision = 'float64';
otherwise
error('This datatype is not supported');
end
% hdr.dime.glmax = round(double(max(nii.img(:))));
% hdr.dime.glmin = round(double(min(nii.img(:))));
if filetype == 2
fid = fopen(sprintf('%s.nii',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.nii.',fileprefix);
error(msg);
end
hdr.dime.vox_offset = 352;
if ~isempty(ext)
hdr.dime.vox_offset = hdr.dime.vox_offset + esize_total;
end
hdr.hist.magic = 'n+1';
save_untouch_nii_hdr(hdr, fid);
if ~isempty(ext)
save_nii_ext(ext, fid);
end
elseif filetype == 1
fid = fopen(sprintf('%s.hdr',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.hdr.',fileprefix);
error(msg);
end
hdr.dime.vox_offset = 0;
hdr.hist.magic = 'ni1';
save_untouch_nii_hdr(hdr, fid);
if ~isempty(ext)
save_nii_ext(ext, fid);
end
fclose(fid);
fid = fopen(sprintf('%s.img',fileprefix),'w');
else
fid = fopen(sprintf('%s.hdr',fileprefix),'w');
if fid < 0,
msg = sprintf('Cannot open file %s.hdr.',fileprefix);
error(msg);
end
save_untouch0_nii_hdr(hdr, fid);
fclose(fid);
fid = fopen(sprintf('%s.img',fileprefix),'w');
end
ScanDim = double(hdr.dime.dim(5)); % t
SliceDim = double(hdr.dime.dim(4)); % z
RowDim = double(hdr.dime.dim(3)); % y
PixelDim = double(hdr.dime.dim(2)); % x
SliceSz = double(hdr.dime.pixdim(4));
RowSz = double(hdr.dime.pixdim(3));
PixelSz = double(hdr.dime.pixdim(2));
x = 1:PixelDim;
if filetype == 2 & isempty(ext)
skip_bytes = double(hdr.dime.vox_offset) - 348;
else
skip_bytes = 0;
end
if double(hdr.dime.datatype) == 128
% RGB planes are expected to be in the 4th dimension of nii.img
%
if(size(nii.img,4)~=3)
error(['The NII structure does not appear to have 3 RGB color planes in the 4th dimension']);
end
nii.img = permute(nii.img, [4 1 2 3 5 6 7 8]);
end
% For complex float32 or complex float64, voxel values
% include [real, imag]
%
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792
real_img = real(nii.img(:))';
nii.img = imag(nii.img(:))';
nii.img = [real_img; nii.img];
end
if skip_bytes
fwrite(fid, zeros(1,skip_bytes), 'uint8');
end
fwrite(fid, nii.img, precision);
% fwrite(fid, nii.img, precision, skip_bytes); % error using skip
fclose(fid);
return; % write_nii
|
github
|
sunhongfu/scripts-master
|
view_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/view_nii.m
| 144,481 |
utf_8
|
8ea68ec34d3a6bec721497afb56cfb54
|
% VIEW_NII: Create or update a 3-View (Front, Top, Side) of the
% brain data that is specified by nii structure
%
% Usage: status = view_nii([h], nii, [option]) or
% status = view_nii(h, [option])
%
% Where, h is the figure on which the 3-View will be plotted;
% nii is the brain data in NIFTI format;
% option is a struct that configures the view plotted, can be:
%
% option.command = 'init'
% option.command = 'update'
% option.command = 'clearnii'
% option.command = 'updatenii'
% option.command = 'updateimg' (nii is nii.img here)
%
% option.usecolorbar = 0 | [1]
% option.usepanel = 0 | [1]
% option.usecrosshair = 0 | [1]
% option.usestretch = 0 | [1]
% option.useimagesc = 0 | [1]
% option.useinterp = [0] | 1
%
% option.setarea = [x y w h] | [0.05 0.05 0.9 0.9]
% option.setunit = ['vox'] | 'mm'
% option.setviewpoint = [x y z] | [origin]
% option.setscanid = [t] | [1]
% option.setcrosshaircolor = [r g b] | [1 0 0]
% option.setcolorindex = From 1 to 9 (default is 2 or 3)
% option.setcolormap = (Mx3 matrix, 0 <= val <= 1)
% option.setcolorlevel = No more than 256 (default 256)
% option.sethighcolor = []
% option.setcbarminmax = []
% option.setvalue = []
% option.glblocminmax = []
% option.setbuttondown = ''
% option.setcomplex = [0] | 1 | 2
%
% Options description in detail:
% ==============================
%
% 1. command: A char string that can control program.
%
% init: If option.command='init', the program will display
% a 3-View plot on the figure specified by figure h
% or on a new figure. If there is already a 3-View
% plot on the figure, please use option.command =
% 'updatenii' (see detail below); otherwise, the
% new 3-View plot will superimpose on the old one.
% If there is no option provided, the program will
% assume that this is an initial plot. If the figure
% handle is omitted, the program knows that it is
% an initial plot.
%
% update: If there is no command specified, and a figure
% handle of the existing 3-View plot is provided,
% the program will choose option.command='update'
% to update the 3-View plot with some new option
% items.
%
% clearnii: Clear 3-View plot on specific figure
%
% updatenii: If a new nii is going to be loaded on a fig
% that has already 3-View plot on it, use this
% command to clear existing 3-View plot, and then
% display with new nii. So, the new nii will not
% superimpose on the existing one. All options
% for 'init' can be used for 'updatenii'.
%
% updateimg: If a new 3D matrix with the same dimension
% is going to be loaded, option.command='updateimg'
% can be used as a light-weighted 'updatenii, since
% it only updates the 3 slices with new values.
% inputing argument nii should be a 3D matrix
% (nii.img) instead of nii struct. No other option
% should be used together with 'updateimg' to keep
% this command as simple as possible.
%
%
% 2. usecolorbar: If specified and usecolorbar=0, the program
% will not include the colorbar in plot area; otherwise,
% a colorbar will be included in plot area.
%
% 3. usepanel: If specified and usepanel=0, the control panel
% at lower right cornor will be invisible; otherwise,
% it will be visible.
%
% 4. usecrosshair: If specified and usecrosshair=0, the crosshair
% will be invisible; otherwise, it will be visible.
%
% 5. usestretch: If specified and usestretch=0, the 3 slices will
% not be stretched, and will be displayed according to
% the actual voxel size; otherwise, the 3 slices will be
% stretched to the edge.
%
% 6. useimagesc: If specified and useimagesc=0, images data will
% be used directly to match the colormap (like 'image'
% command); otherwise, image data will be scaled to full
% colormap with 'imagesc' command in Matlab.
%
% 7. useinterp: If specified and useinterp=1, the image will be
% displayed using interpolation. Otherwise, it will be
% displayed like mosaic, and each tile stands for a
% pixel. This option does not apply to 'setvalue' option
% is set.
%
%
% 8. setarea: 3-View plot will be displayed on this specific
% region. If it is not specified, program will set the
% plot area to [0.05 0.05 0.9 0.9].
%
% 9. setunit: It can be specified to setunit='voxel' or 'mm'
% and the view will change the axes unit of [X Y Z]
% accordingly.
%
% 10. setviewpoint: If specified, [X Y Z] values will be used
% to set the viewpoint of 3-View plot.
%
% 11. setscanid: If specified, [t] value will be used to display
% the specified image scan in NIFTI data.
%
% 12. setcrosshaircolor: If specified, [r g b] value will be used
% for Crosshair Color. Otherwise, red will be the default.
%
% 13. setcolorindex: If specified, the 3-View will choose the
% following colormap: 2 - Bipolar; 3 - Gray; 4 - Jet;
% 5 - Cool; 6 - Bone; 7 - Hot; 8 - Copper; 9 - Pink;
% If not specified, it will choose 3 - Gray if all data
% values are not less than 0; otherwise, it will choose
% 2 - Bipolar if there is value less than 0. (Contrast
% control can only apply to 3 - Gray colormap.
%
% 14. setcolormap: 3-View plot will use it as a customized colormap.
% It is a 3-column matrix with value between 0 and 1. If
% using MS-Windows version of Matlab, the number of rows
% can not be more than 256, because of Matlab limitation.
% When colormap is used, setcolorlevel option will be
% disabled automatically.
%
% 15. setcolorlevel: If specified (must be no more than 256, and
% cannot be used for customized colormap), row number of
% colormap will be squeezed down to this level; otherwise,
% it will assume that setcolorlevel=256.
%
% 16. sethighcolor: If specified, program will squeeze down the
% colormap, and allocate sethighcolor (an Mx3 matrix)
% to high-end portion of the colormap. The sum of M and
% setcolorlevel should be less than 256. If setcolormap
% option is used, sethighcolor will be inserted on top
% of the setcolormap, and the setcolorlevel option will
% be disabled automatically.
%
% 17. setcbarminmax: if specified, the [min max] will be used to
% set the min and max of the colorbar, which does not
% include any data for highcolor.
%
% 18. setvalue: If specified, setvalue.val (with the same size as
% the source data on solution points) in the source area
% setvalue.idx will be superimposed on the current nii
% image. So, the size of setvalue.val should be equal to
% the size of setvalue.idx. To use this feature, it needs
% single or double nii structure for background image.
%
% 19. glblocminmax: If specified, pgm will use glblocminmax to
% calculate the colormap, instead of minmax of image.
%
% 20. setbuttondown: If specified, pgm will evaluate the command
% after a click or slide action is invoked to the new
% view point.
%
% 21. setcomplex: This option will decide how complex data to be
% displayed: 0 - Real part of complex data; 1 - Imaginary
% part of complex data; 2 - Modulus (magnitude) of complex
% data; If not specified, it will be set to 0 (Real part
% of complex data as default option. This option only apply
% when option.command is set to 'init or 'updatenii'.
%
%
% Additional Options for 'update' command:
% =======================================
%
% option.enablecursormove = [1] | 0
% option.enableviewpoint = 0 | [1]
% option.enableorigin = 0 | [1]
% option.enableunit = 0 | [1]
% option.enablecrosshair = 0 | [1]
% option.enablehistogram = 0 | [1]
% option.enablecolormap = 0 | [1]
% option.enablecontrast = 0 | [1]
% option.enablebrightness = 0 | [1]
% option.enableslider = 0 | [1]
% option.enabledirlabel = 0 | [1]
%
%
% e.g.:
% nii = load_nii('T1'); % T1.img/hdr
% view_nii(nii);
%
% or
%
% h = figure('unit','normal','pos', [0.18 0.08 0.64 0.85]);
% opt.setarea = [0.05 0.05 0.9 0.9];
% view_nii(h, nii, opt);
%
%
% Part of this file is copied and modified from:
% http://www.mathworks.com/matlabcentral/fileexchange/1878-mri-analyze-tools
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function status = view_nii(varargin)
if nargin < 1
error('Please check inputs using ''help view_nii''');
end;
nii = '';
opt = '';
command = '';
usecolorbar = [];
usepanel = [];
usecrosshair = '';
usestretch = [];
useimagesc = [];
useinterp = [];
setarea = [];
setunit = '';
setviewpoint = [];
setscanid = [];
setcrosshaircolor = [];
setcolorindex = '';
setcolormap = 'NA';
setcolorlevel = [];
sethighcolor = 'NA';
setcbarminmax = [];
setvalue = [];
glblocminmax = [];
setbuttondown = '';
setcomplex = 0;
status = [];
if ishandle(varargin{1}) % plot on top of this figure
fig = varargin{1};
if nargin < 2
command = 'update'; % just to get 3-View status
end
if nargin == 2
if ~isstruct(varargin{2})
error('2nd parameter should be either nii struct or option struct');
end
opt = varargin{2};
if isfield(opt,'hdr') & isfield(opt,'img')
nii = opt;
elseif isfield(opt, 'command') & (strcmpi(opt.command,'init') ...
| strcmpi(opt.command,'updatenii') ...
| strcmpi(opt.command,'updateimg') )
error('Option here cannot contain "init", "updatenii", or "updateimg" comand');
end
end
if nargin == 3
nii = varargin{2};
opt = varargin{3};
if ~isstruct(opt)
error('3rd parameter should be option struct');
end
if ~isfield(opt,'command') | ~strcmpi(opt.command,'updateimg')
if ~isstruct(nii) | ~isfield(nii,'hdr') | ~isfield(nii,'img')
error('2nd parameter should be nii struct');
end
if isfield(nii,'untouch') & nii.untouch == 1
error('Usage: please use ''load_nii.m'' to load the structure.');
end
end
end
set(fig, 'menubar', 'none');
elseif ischar(varargin{1}) % call back by event
command = lower(varargin{1});
fig = gcbf;
else % start nii with a new figure
nii = varargin{1};
if ~isstruct(nii) | ~isfield(nii,'hdr') | ~isfield(nii,'img')
error('1st parameter should be either a figure handle or nii struct');
end
if isfield(nii,'untouch') & nii.untouch == 1
error('Usage: please use ''load_nii.m'' to load the structure.');
end
if nargin > 1
opt = varargin{2};
if isfield(opt, 'command') & ~strcmpi(opt.command,'init')
error('Option here must use "init" comand');
end
end
command = 'init';
fig = figure('unit','normal','position',[0.15 0.08 0.70 0.85]);
view_nii_menu(fig);
rri_file_menu(fig);
end
if ~isempty(opt)
if isfield(opt,'command')
command = lower(opt.command);
end
if isempty(command)
command = 'update';
end
if isfield(opt,'usecolorbar')
usecolorbar = opt.usecolorbar;
end
if isfield(opt,'usepanel')
usepanel = opt.usepanel;
end
if isfield(opt,'usecrosshair')
usecrosshair = opt.usecrosshair;
end
if isfield(opt,'usestretch')
usestretch = opt.usestretch;
end
if isfield(opt,'useimagesc')
useimagesc = opt.useimagesc;
end
if isfield(opt,'useinterp')
useinterp = opt.useinterp;
end
if isfield(opt,'setarea')
setarea = opt.setarea;
end
if isfield(opt,'setunit')
setunit = opt.setunit;
end
if isfield(opt,'setviewpoint')
setviewpoint = opt.setviewpoint;
end
if isfield(opt,'setscanid')
setscanid = opt.setscanid;
end
if isfield(opt,'setcrosshaircolor')
setcrosshaircolor = opt.setcrosshaircolor;
if ~isempty(setcrosshaircolor) & (~isnumeric(setcrosshaircolor) | ~isequal(size(setcrosshaircolor),[1 3]) | min(setcrosshaircolor(:))<0 | max(setcrosshaircolor(:))>1)
error('Crosshair Color should be a 1x3 matrix with value between 0 and 1');
end
end
if isfield(opt,'setcolorindex')
setcolorindex = round(opt.setcolorindex);
if ~isnumeric(setcolorindex) | setcolorindex < 1 | setcolorindex > 9
error('Colorindex should be a number between 1 and 9');
end
end
if isfield(opt,'setcolormap')
setcolormap = opt.setcolormap;
if ~isempty(setcolormap) & (~isnumeric(setcolormap) | size(setcolormap,2) ~= 3 | min(setcolormap(:))<0 | max(setcolormap(:))>1)
error('Colormap should be a Mx3 matrix with value between 0 and 1');
end
end
if isfield(opt,'setcolorlevel')
setcolorlevel = round(opt.setcolorlevel);
if ~isnumeric(setcolorlevel) | setcolorlevel > 256 | setcolorlevel < 1
error('Colorlevel should be a number between 1 and 256');
end
end
if isfield(opt,'sethighcolor')
sethighcolor = opt.sethighcolor;
if ~isempty(sethighcolor) & (~isnumeric(sethighcolor) | size(sethighcolor,2) ~= 3 | min(sethighcolor(:))<0 | max(sethighcolor(:))>1)
error('Highcolor should be a Mx3 matrix with value between 0 and 1');
end
end
if isfield(opt,'setcbarminmax')
setcbarminmax = opt.setcbarminmax;
if isempty(setcbarminmax) | ~isnumeric(setcbarminmax) | length(setcbarminmax) ~= 2
error('Colorbar MinMax should contain 2 values: [min max]');
end
end
if isfield(opt,'setvalue')
setvalue = opt.setvalue;
if isempty(setvalue) | ~isstruct(setvalue) | ...
~isfield(opt.setvalue,'idx') | ~isfield(opt.setvalue,'val')
error('setvalue should be a struct contains idx and val');
end
if length(opt.setvalue.idx(:)) ~= length(opt.setvalue.val(:))
error('length of idx and val fields should be the same');
end
if ~strcmpi(class(opt.setvalue.idx),'single')
opt.setvalue.idx = single(opt.setvalue.idx);
end
if ~strcmpi(class(opt.setvalue.val),'single')
opt.setvalue.val = single(opt.setvalue.val);
end
end
if isfield(opt,'glblocminmax')
glblocminmax = opt.glblocminmax;
end
if isfield(opt,'setbuttondown')
setbuttondown = opt.setbuttondown;
end
if isfield(opt,'setcomplex')
setcomplex = opt.setcomplex;
end
end
switch command
case {'init'}
set(fig, 'InvertHardcopy','off');
set(fig, 'PaperPositionMode','auto');
fig = init(nii, fig, setarea, setunit, setviewpoint, setscanid, setbuttondown, ...
setcolorindex, setcolormap, setcolorlevel, sethighcolor, setcbarminmax, ...
usecolorbar, usepanel, usecrosshair, usestretch, useimagesc, useinterp, ...
setvalue, glblocminmax, setcrosshaircolor, setcomplex);
% get status
%
status = get_status(fig);
case {'update'}
nii_view = getappdata(fig,'nii_view');
h = fig;
if isempty(nii_view)
error('The figure should already contain a 3-View plot.');
end
if ~isempty(opt)
% Order of the following update matters.
%
update_shape(h, setarea, usecolorbar, usestretch, useimagesc);
update_useinterp(h, useinterp);
update_useimagesc(h, useimagesc);
update_usepanel(h, usepanel);
update_colorindex(h, setcolorindex);
update_colormap(h, setcolormap);
update_highcolor(h, sethighcolor, setcolorlevel);
update_cbarminmax(h, setcbarminmax);
update_unit(h, setunit);
update_viewpoint(h, setviewpoint);
update_scanid(h, setscanid);
update_buttondown(h, setbuttondown);
update_crosshaircolor(h, setcrosshaircolor);
update_usecrosshair(h, usecrosshair);
% Enable/Disable object
%
update_enable(h, opt);
end
% get status
%
status = get_status(h);
case {'updateimg'}
if ~exist('nii','var')
msg = sprintf('Please input a 3D matrix brain data');
error(msg);
end
% Note: nii is not nii, nii should be a 3D matrix here
%
if ~isnumeric(nii)
msg = sprintf('2nd parameter should be a 3D matrix, not nii struct');
error(msg);
end
nii_view = getappdata(fig,'nii_view');
if isempty(nii_view)
error('The figure should already contain a 3-View plot.');
end
img = nii;
update_img(img, fig, opt);
% get status
%
status = get_status(fig);
case {'updatenii'}
nii_view = getappdata(fig,'nii_view');
if isempty(nii_view)
error('The figure should already contain a 3-View plot.');
end
if ~isstruct(nii) | ~isfield(nii,'hdr') | ~isfield(nii,'img')
error('2nd parameter should be nii struct');
end
if isfield(nii,'untouch') & nii.untouch == 1
error('Usage: please use ''load_nii.m'' to load the structure.');
end
opt.command = 'clearnii';
view_nii(fig, opt);
opt.command = 'init';
view_nii(fig, nii, opt);
% get status
%
status = get_status(fig);
case {'clearnii'}
nii_view = getappdata(fig,'nii_view');
handles = struct2cell(nii_view.handles);
for i=1:length(handles)
if ishandle(handles{i}) % in case already del by parent
delete(handles{i});
end
end
rmappdata(fig,'nii_view');
buttonmotion = get(fig,'windowbuttonmotion');
mymotion = '; view_nii(''move_cursor'');';
buttonmotion = strrep(buttonmotion, mymotion, '');
set(fig, 'windowbuttonmotion', buttonmotion);
case {'axial_image','coronal_image','sagittal_image'}
switch command
case 'axial_image', view = 'axi'; axi = 0; cor = 1; sag = 1;
case 'coronal_image', view = 'cor'; axi = 1; cor = 0; sag = 1;
case 'sagittal_image', view = 'sag'; axi = 1; cor = 1; sag = 0;
end
nii_view = getappdata(fig,'nii_view');
nii_view = get_slice_position(nii_view,view);
if isfield(nii_view, 'disp')
img = nii_view.disp;
else
img = nii_view.nii.img;
end
% CData must be double() for Matlab 6.5 for Windows
%
if axi,
if isfield(nii_view.handles,'axial_bg') & ~isempty(nii_view.handles.axial_bg) & nii_view.useinterp
Saxi = squeeze(nii_view.bgimg(:,:,nii_view.slices.axi));
set(nii_view.handles.axial_bg,'CData',double(Saxi)');
end
if isfield(nii_view.handles,'axial_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Saxi = squeeze(img(:,:,nii_view.slices.axi,:,nii_view.scanid));
Saxi = permute(Saxi, [2 1 3]);
else
Saxi = squeeze(img(:,:,nii_view.slices.axi,nii_view.scanid));
Saxi = Saxi';
end
set(nii_view.handles.axial_image,'CData',double(Saxi));
end
if isfield(nii_view.handles,'axial_slider'),
set(nii_view.handles.axial_slider,'Value',nii_view.slices.axi);
end;
end
if cor,
if isfield(nii_view.handles,'coronal_bg') & ~isempty(nii_view.handles.coronal_bg) & nii_view.useinterp
Scor = squeeze(nii_view.bgimg(:,nii_view.slices.cor,:));
set(nii_view.handles.coronal_bg,'CData',double(Scor)');
end
if isfield(nii_view.handles,'coronal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Scor = squeeze(img(:,nii_view.slices.cor,:,:,nii_view.scanid));
Scor = permute(Scor, [2 1 3]);
else
Scor = squeeze(img(:,nii_view.slices.cor,:,nii_view.scanid));
Scor = Scor';
end
set(nii_view.handles.coronal_image,'CData',double(Scor));
end
if isfield(nii_view.handles,'coronal_slider'),
slider_val = nii_view.dims(2) - nii_view.slices.cor + 1;
set(nii_view.handles.coronal_slider,'Value',slider_val);
end;
end;
if sag,
if isfield(nii_view.handles,'sagittal_bg') & ~isempty(nii_view.handles.sagittal_bg) & nii_view.useinterp
Ssag = squeeze(nii_view.bgimg(nii_view.slices.sag,:,:));
set(nii_view.handles.sagittal_bg,'CData',double(Ssag)');
end
if isfield(nii_view.handles,'sagittal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Ssag = squeeze(img(nii_view.slices.sag,:,:,:,nii_view.scanid));
Ssag = permute(Ssag, [2 1 3]);
else
Ssag = squeeze(img(nii_view.slices.sag,:,:,nii_view.scanid));
Ssag = Ssag';
end
set(nii_view.handles.sagittal_image,'CData',double(Ssag));
end
if isfield(nii_view.handles,'sagittal_slider'),
set(nii_view.handles.sagittal_slider,'Value',nii_view.slices.sag);
end;
end;
update_nii_view(nii_view);
if ~isempty(nii_view.buttondown)
eval(nii_view.buttondown);
end
case {'axial_slider','coronal_slider','sagittal_slider'},
switch command
case 'axial_slider', view = 'axi'; axi = 1; cor = 0; sag = 0;
case 'coronal_slider', view = 'cor'; axi = 0; cor = 1; sag = 0;
case 'sagittal_slider', view = 'sag'; axi = 0; cor = 0; sag = 1;
end
nii_view = getappdata(fig,'nii_view');
nii_view = get_slider_position(nii_view);
if isfield(nii_view, 'disp')
img = nii_view.disp;
else
img = nii_view.nii.img;
end
if axi,
if isfield(nii_view.handles,'axial_bg') & ~isempty(nii_view.handles.axial_bg) & nii_view.useinterp
Saxi = squeeze(nii_view.bgimg(:,:,nii_view.slices.axi));
set(nii_view.handles.axial_bg,'CData',double(Saxi)');
end
if isfield(nii_view.handles,'axial_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Saxi = squeeze(img(:,:,nii_view.slices.axi,:,nii_view.scanid));
Saxi = permute(Saxi, [2 1 3]);
else
Saxi = squeeze(img(:,:,nii_view.slices.axi,nii_view.scanid));
Saxi = Saxi';
end
set(nii_view.handles.axial_image,'CData',double(Saxi));
end
if isfield(nii_view.handles,'axial_slider'),
set(nii_view.handles.axial_slider,'Value',nii_view.slices.axi);
end
end
if cor,
if isfield(nii_view.handles,'coronal_bg') & ~isempty(nii_view.handles.coronal_bg) & nii_view.useinterp
Scor = squeeze(nii_view.bgimg(:,nii_view.slices.cor,:));
set(nii_view.handles.coronal_bg,'CData',double(Scor)');
end
if isfield(nii_view.handles,'coronal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Scor = squeeze(img(:,nii_view.slices.cor,:,:,nii_view.scanid));
Scor = permute(Scor, [2 1 3]);
else
Scor = squeeze(img(:,nii_view.slices.cor,:,nii_view.scanid));
Scor = Scor';
end
set(nii_view.handles.coronal_image,'CData',double(Scor));
end
if isfield(nii_view.handles,'coronal_slider'),
slider_val = nii_view.dims(2) - nii_view.slices.cor + 1;
set(nii_view.handles.coronal_slider,'Value',slider_val);
end
end
if sag,
if isfield(nii_view.handles,'sagittal_bg') & ~isempty(nii_view.handles.sagittal_bg) & nii_view.useinterp
Ssag = squeeze(nii_view.bgimg(nii_view.slices.sag,:,:));
set(nii_view.handles.sagittal_bg,'CData',double(Ssag)');
end
if isfield(nii_view.handles,'sagittal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Ssag = squeeze(img(nii_view.slices.sag,:,:,:,nii_view.scanid));
Ssag = permute(Ssag, [2 1 3]);
else
Ssag = squeeze(img(nii_view.slices.sag,:,:,nii_view.scanid));
Ssag = Ssag';
end
set(nii_view.handles.sagittal_image,'CData',double(Ssag));
end
if isfield(nii_view.handles,'sagittal_slider'),
set(nii_view.handles.sagittal_slider,'Value',nii_view.slices.sag);
end
end
update_nii_view(nii_view);
if ~isempty(nii_view.buttondown)
eval(nii_view.buttondown);
end
case {'impos_edit'}
nii_view = getappdata(fig,'nii_view');
impos = str2num(get(nii_view.handles.impos,'string'));
if isfield(nii_view, 'disp')
img = nii_view.disp;
else
img = nii_view.nii.img;
end
if isempty(impos) | ~all(size(impos) == [1 3])
msg = 'Please use 3 numbers to represent X,Y and Z';
msgbox(msg,'Error');
return;
end
slices.sag = round(impos(1));
slices.cor = round(impos(2));
slices.axi = round(impos(3));
nii_view = convert2voxel(nii_view,slices);
nii_view = check_slices(nii_view);
impos(1) = nii_view.slices.sag;
impos(2) = nii_view.dims(2) - nii_view.slices.cor + 1;
impos(3) = nii_view.slices.axi;
if isfield(nii_view.handles,'sagittal_slider'),
set(nii_view.handles.sagittal_slider,'Value',impos(1));
end
if isfield(nii_view.handles,'coronal_slider'),
set(nii_view.handles.coronal_slider,'Value',impos(2));
end
if isfield(nii_view.handles,'axial_slider'),
set(nii_view.handles.axial_slider,'Value',impos(3));
end
nii_view = get_slider_position(nii_view);
update_nii_view(nii_view);
if isfield(nii_view.handles,'axial_bg') & ~isempty(nii_view.handles.axial_bg) & nii_view.useinterp
Saxi = squeeze(nii_view.bgimg(:,:,nii_view.slices.axi));
set(nii_view.handles.axial_bg,'CData',double(Saxi)');
end
if isfield(nii_view.handles,'axial_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Saxi = squeeze(img(:,:,nii_view.slices.axi,:,nii_view.scanid));
Saxi = permute(Saxi, [2 1 3]);
else
Saxi = squeeze(img(:,:,nii_view.slices.axi,nii_view.scanid));
Saxi = Saxi';
end
set(nii_view.handles.axial_image,'CData',double(Saxi));
end
if isfield(nii_view.handles,'axial_slider'),
set(nii_view.handles.axial_slider,'Value',nii_view.slices.axi);
end
if isfield(nii_view.handles,'coronal_bg') & ~isempty(nii_view.handles.coronal_bg) & nii_view.useinterp
Scor = squeeze(nii_view.bgimg(:,nii_view.slices.cor,:));
set(nii_view.handles.coronal_bg,'CData',double(Scor)');
end
if isfield(nii_view.handles,'coronal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Scor = squeeze(img(:,nii_view.slices.cor,:,:,nii_view.scanid));
Scor = permute(Scor, [2 1 3]);
else
Scor = squeeze(img(:,nii_view.slices.cor,:,nii_view.scanid));
Scor = Scor';
end
set(nii_view.handles.coronal_image,'CData',double(Scor));
end
if isfield(nii_view.handles,'coronal_slider'),
slider_val = nii_view.dims(2) - nii_view.slices.cor + 1;
set(nii_view.handles.coronal_slider,'Value',slider_val);
end
if isfield(nii_view.handles,'sagittal_bg') & ~isempty(nii_view.handles.sagittal_bg) & nii_view.useinterp
Ssag = squeeze(nii_view.bgimg(nii_view.slices.sag,:,:));
set(nii_view.handles.sagittal_bg,'CData',double(Ssag)');
end
if isfield(nii_view.handles,'sagittal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Ssag = squeeze(img(nii_view.slices.sag,:,:,:,nii_view.scanid));
Ssag = permute(Ssag, [2 1 3]);
else
Ssag = squeeze(img(nii_view.slices.sag,:,:,nii_view.scanid));
Ssag = Ssag';
end
set(nii_view.handles.sagittal_image,'CData',double(Ssag));
end
if isfield(nii_view.handles,'sagittal_slider'),
set(nii_view.handles.sagittal_slider,'Value',nii_view.slices.sag);
end
axes(nii_view.handles.axial_axes);
axes(nii_view.handles.coronal_axes);
axes(nii_view.handles.sagittal_axes);
if ~isempty(nii_view.buttondown)
eval(nii_view.buttondown);
end
case 'coordinates',
nii_view = getappdata(fig,'nii_view');
set_image_value(nii_view);
case 'crosshair',
nii_view = getappdata(fig,'nii_view');
if get(nii_view.handles.xhair,'value') == 2 % off
set(nii_view.axi_xhair.lx,'visible','off');
set(nii_view.axi_xhair.ly,'visible','off');
set(nii_view.cor_xhair.lx,'visible','off');
set(nii_view.cor_xhair.ly,'visible','off');
set(nii_view.sag_xhair.lx,'visible','off');
set(nii_view.sag_xhair.ly,'visible','off');
else
set(nii_view.axi_xhair.lx,'visible','on');
set(nii_view.axi_xhair.ly,'visible','on');
set(nii_view.cor_xhair.lx,'visible','on');
set(nii_view.cor_xhair.ly,'visible','on');
set(nii_view.sag_xhair.lx,'visible','on');
set(nii_view.sag_xhair.ly,'visible','on');
set(nii_view.handles.axial_axes,'selected','on');
set(nii_view.handles.axial_axes,'selected','off');
set(nii_view.handles.coronal_axes,'selected','on');
set(nii_view.handles.coronal_axes,'selected','off');
set(nii_view.handles.sagittal_axes,'selected','on');
set(nii_view.handles.sagittal_axes,'selected','off');
end
case 'xhair_color',
old_color = get(gcbo,'user');
new_color = uisetcolor(old_color);
update_crosshaircolor(fig, new_color);
case {'color','contrast_def'}
nii_view = getappdata(fig,'nii_view');
if nii_view.numscan == 1
if get(nii_view.handles.colorindex,'value') == 2
set(nii_view.handles.contrast,'value',128);
elseif get(nii_view.handles.colorindex,'value') == 3
set(nii_view.handles.contrast,'value',1);
end
end
[custom_color_map, custom_colorindex] = change_colormap(fig);
if strcmpi(command, 'color')
setcolorlevel = nii_view.colorlevel;
if ~isempty(custom_color_map) % isfield(nii_view, 'color_map')
setcolormap = custom_color_map; % nii_view.color_map;
else
setcolormap = [];
end
if isfield(nii_view, 'highcolor')
sethighcolor = nii_view.highcolor;
else
sethighcolor = [];
end
redraw_cbar(fig, setcolorlevel, setcolormap, sethighcolor);
if nii_view.numscan == 1 & ...
(custom_colorindex < 2 | custom_colorindex > 3)
contrastopt.enablecontrast = 0;
else
contrastopt.enablecontrast = 1;
end
update_enable(fig, contrastopt);
end
case {'neg_color','brightness','contrast'}
change_colormap(fig);
case {'brightness_def'}
nii_view = getappdata(fig,'nii_view');
set(nii_view.handles.brightness,'value',0);
change_colormap(fig);
case 'hist_plot'
hist_plot(fig);
case 'hist_eq'
hist_eq(fig);
case 'move_cursor'
move_cursor(fig);
case 'edit_change_scan'
change_scan('edit_change_scan');
case 'slider_change_scan'
change_scan('slider_change_scan');
end
return; % view_nii
%----------------------------------------------------------------
function fig = init(nii, fig, area, setunit, setviewpoint, setscanid, buttondown, ...
colorindex, color_map, colorlevel, highcolor, cbarminmax, ...
usecolorbar, usepanel, usecrosshair, usestretch, useimagesc, ...
useinterp, setvalue, glblocminmax, setcrosshaircolor, ...
setcomplex)
% Support data type COMPLEX64 & COMPLEX128
%
if nii.hdr.dime.datatype == 32 | nii.hdr.dime.datatype == 1792
switch setcomplex,
case 0,
nii.img = real(nii.img);
case 1,
nii.img = imag(nii.img);
case 2,
if isa(nii.img, 'double')
nii.img = abs(double(nii.img));
else
nii.img = single(abs(double(nii.img)));
end
end
end
if isempty(area)
area = [0.05 0.05 0.9 0.9];
end
if isempty(setscanid)
setscanid = 1;
else
setscanid = round(setscanid);
if setscanid < 1
setscanid = 1;
end
if setscanid > nii.hdr.dime.dim(5)
setscanid = nii.hdr.dime.dim(5);
end
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
usecolorbar = 0;
elseif isempty(usecolorbar)
usecolorbar = 1;
end
if isempty(usepanel)
usepanel = 1;
end
if isempty(usestretch)
usestretch = 1;
end
if isempty(useimagesc)
useimagesc = 1;
end
if isempty(useinterp)
useinterp = 0;
end
if isempty(colorindex)
tmp = min(nii.img(:,:,:,setscanid));
if min(tmp(:)) < 0
colorindex = 2;
setcrosshaircolor = [1 1 0];
else
colorindex = 3;
end
end
if isempty(color_map) | ischar(color_map)
color_map = [];
else
colorindex = 1;
end
bgimg = [];
if ~isempty(glblocminmax)
minvalue = glblocminmax(1);
maxvalue = glblocminmax(2);
else
minvalue = nii.img(:,:,:,setscanid);
minvalue = double(minvalue(:));
minvalue = min(minvalue(~isnan(minvalue)));
maxvalue = nii.img(:,:,:,setscanid);
maxvalue = double(maxvalue(:));
maxvalue = max(maxvalue(~isnan(maxvalue)));
end
if ~isempty(setvalue)
if ~isempty(glblocminmax)
minvalue = glblocminmax(1);
maxvalue = glblocminmax(2);
else
minvalue = double(min(setvalue.val));
maxvalue = double(max(setvalue.val));
end
bgimg = double(nii.img);
minbg = double(min(bgimg(:)));
maxbg = double(max(bgimg(:)));
bgimg = scale_in(bgimg, minbg, maxbg, 55) + 200; % scale to 201~256
% 56 level for brain structure
%
% highcolor = [zeros(1,3);gray(55)];
highcolor = gray(56);
cbarminmax = [minvalue maxvalue];
if useinterp
% scale signal data to 1~200
%
nii.img = repmat(nan, size(nii.img));
nii.img(setvalue.idx) = setvalue.val;
% 200 level for source image
%
bgimg = single(scale_out(bgimg, cbarminmax(1), cbarminmax(2), 199));
else
bgimg(setvalue.idx) = NaN;
minbg = double(min(bgimg(:)));
maxbg = double(max(bgimg(:)));
bgimg(setvalue.idx) = minbg;
% bgimg must be normalized to [201 256]
%
bgimg = 55 * (bgimg-min(bgimg(:))) / (max(bgimg(:))-min(bgimg(:))) + 201;
bgimg(setvalue.idx) = 0;
% scale signal data to 1~200
%
nii.img = zeros(size(nii.img));
nii.img(setvalue.idx) = scale_in(setvalue.val, minvalue, maxvalue, 199);
nii.img = nii.img + bgimg;
bgimg = [];
nii.img = scale_out(nii.img, cbarminmax(1), cbarminmax(2), 199);
minvalue = double(nii.img(:));
minvalue = min(minvalue(~isnan(minvalue)));
maxvalue = double(nii.img(:));
maxvalue = max(maxvalue(~isnan(maxvalue)));
if ~isempty(glblocminmax) % maxvalue is gray
minvalue = glblocminmax(1);
end
end
colorindex = 2;
setcrosshaircolor = [1 1 0];
end
if isempty(highcolor) | ischar(highcolor)
highcolor = [];
num_highcolor = 0;
else
num_highcolor = size(highcolor,1);
end
if isempty(colorlevel)
colorlevel = 256 - num_highcolor;
end
if usecolorbar
cbar_area = area;
cbar_area(1) = area(1) + area(3)*0.93;
cbar_area(3) = area(3)*0.04;
area(3) = area(3)*0.9; % 90% used for main axes
else
cbar_area = [];
end
% init color (gray) scaling to make sure the slice clim take the
% global clim [min(nii.img(:)) max(nii.img(:))]
%
if isempty(bgimg)
clim = [minvalue maxvalue];
else
clim = [minvalue double(max(bgimg(:)))];
end
if clim(1) == clim(2)
clim(2) = clim(1) + 0.000001;
end
if isempty(cbarminmax)
cbarminmax = [minvalue maxvalue];
end
xdim = size(nii.img, 1);
ydim = size(nii.img, 2);
zdim = size(nii.img, 3);
dims = [xdim ydim zdim];
voxel_size = abs(nii.hdr.dime.pixdim(2:4)); % vol in mm
if any(voxel_size <= 0)
voxel_size(find(voxel_size <= 0)) = 1;
end
origin = abs(nii.hdr.hist.originator(1:3));
if isempty(origin) | all(origin == 0) % according to SPM
origin = (dims+1)/2;
end;
origin = round(origin);
if any(origin > dims) % simulate fMRI
origin(find(origin > dims)) = dims(find(origin > dims));
end
if any(origin <= 0)
origin(find(origin <= 0)) = 1;
end
nii_view.dims = dims;
nii_view.voxel_size = voxel_size;
nii_view.origin = origin;
nii_view.slices.sag = 1;
nii_view.slices.cor = 1;
nii_view.slices.axi = 1;
if xdim > 1, nii_view.slices.sag = origin(1); end
if ydim > 1, nii_view.slices.cor = origin(2); end
if zdim > 1, nii_view.slices.axi = origin(3); end
nii_view.area = area;
nii_view.fig = fig;
nii_view.nii = nii; % image data
nii_view.bgimg = bgimg; % background
nii_view.setvalue = setvalue;
nii_view.minvalue = minvalue;
nii_view.maxvalue = maxvalue;
nii_view.numscan = nii.hdr.dime.dim(5);
nii_view.scanid = setscanid;
Font.FontUnits = 'point';
Font.FontSize = 12;
% create axes for colorbar
%
[cbar_axes cbarminmax_axes] = create_cbar_axes(fig, cbar_area);
if isempty(cbar_area)
nii_view.cbar_area = [];
else
nii_view.cbar_area = cbar_area;
end
% create axes for top/front/side view
%
vol_size = voxel_size .* dims;
[top_ax, front_ax, side_ax] ...
= create_ax(fig, area, vol_size, usestretch);
top_pos = get(top_ax,'position');
front_pos = get(front_ax,'position');
side_pos = get(side_ax,'position');
% Sagittal Slider
%
x = side_pos(1);
y = top_pos(2) + top_pos(4);
w = side_pos(3);
h = (front_pos(2) - y) / 2;
y = y + h;
pos = [x y w h];
if xdim > 1,
slider_step(1) = 1/(xdim);
slider_step(2) = 1.00001/(xdim);
handles.sagittal_slider = uicontrol('Parent',fig, ...
'Style','slider','Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment','center',...
'BackgroundColor',[0.5 0.5 0.5],'ForegroundColor',[0 0 0],...
'BusyAction','queue',...
'TooltipString','Sagittal slice navigation',...
'Min',1,'Max',xdim,'SliderStep',slider_step, ...
'Value',nii_view.slices.sag,...
'Callback','view_nii(''sagittal_slider'');');
set(handles.sagittal_slider,'position',pos); % linux66
end
% Coronal Slider
%
x = top_pos(1);
y = top_pos(2) + top_pos(4);
w = top_pos(3);
h = (front_pos(2) - y) / 2;
y = y + h;
pos = [x y w h];
if ydim > 1,
slider_step(1) = 1/(ydim);
slider_step(2) = 1.00001/(ydim);
slider_val = nii_view.dims(2) - nii_view.slices.cor + 1;
handles.coronal_slider = uicontrol('Parent',fig, ...
'Style','slider','Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment','center',...
'BackgroundColor',[0.5 0.5 0.5],'ForegroundColor',[0 0 0],...
'BusyAction','queue',...
'TooltipString','Coronal slice navigation',...
'Min',1,'Max',ydim,'SliderStep',slider_step, ...
'Value',slider_val,...
'Callback','view_nii(''coronal_slider'');');
set(handles.coronal_slider,'position',pos); % linux66
end
% Axial Slider
%
% x = front_pos(1) + front_pos(3);
% y = front_pos(2);
% w = side_pos(1) - x;
% h = front_pos(4);
x = top_pos(1);
y = area(2);
w = top_pos(3);
h = top_pos(2) - y;
pos = [x y w h];
if zdim > 1,
slider_step(1) = 1/(zdim);
slider_step(2) = 1.00001/(zdim);
handles.axial_slider = uicontrol('Parent',fig, ...
'Style','slider','Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment','center',...
'BackgroundColor',[0.5 0.5 0.5],'ForegroundColor',[0 0 0],...
'BusyAction','queue',...
'TooltipString','Axial slice navigation',...
'Min',1,'Max',zdim,'SliderStep',slider_step, ...
'Value',nii_view.slices.axi,...
'Callback','view_nii(''axial_slider'');');
set(handles.axial_slider,'position',pos); % linux66
end
% plot info view
%
% info_pos = [side_pos([1,3]); top_pos([2,4])];
% info_pos = info_pos(:);
gap = side_pos(1)-(top_pos(1)+top_pos(3));
info_pos(1) = side_pos(1) + gap;
info_pos(2) = area(2);
info_pos(3) = side_pos(3) - gap;
info_pos(4) = top_pos(2) + top_pos(4) - area(2) - gap;
num_inputline = 10;
inputline_space =info_pos(4) / num_inputline;
% for any info_area change, update_usestretch should also be changed
% Image Intensity Value at Cursor
%
x = info_pos(1);
y = info_pos(2);
w = info_pos(3)*0.5;
h = inputline_space*0.6;
pos = [x y w h];
handles.Timvalcur = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Value at cursor:');
if usepanel
set(handles.Timvalcur, 'visible', 'on');
end
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.imvalcur = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'right',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String',' ');
if usepanel
set(handles.imvalcur, 'visible', 'on');
end
% Position at Cursor
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.Timposcur = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','[X Y Z] at cursor:');
if usepanel
set(handles.Timposcur, 'visible', 'on');
end
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.imposcur = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'right',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String',' ','Value',[0 0 0]);
if usepanel
set(handles.imposcur, 'visible', 'on');
end
% Image Intensity Value at Mouse Click
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.Timval = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Value at crosshair:');
if usepanel
set(handles.Timval, 'visible', 'on');
end
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.imval = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'right',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String',' ');
if usepanel
set(handles.imval, 'visible', 'on');
end
% Viewpoint Position at Mouse Click
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.Timpos = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','[X Y Z] at crosshair:');
if usepanel
set(handles.Timpos, 'visible', 'on');
end
x = x + w + 0.005;
y = y - 0.008;
w = info_pos(3)*0.5;
h = inputline_space*0.9;
pos = [x y w h];
handles.impos = uicontrol('Parent',fig,'Style','edit', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'right',...
'BackgroundColor', [1 1 1], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'Callback','view_nii(''impos_edit'');', ...
'TooltipString','Viewpoint Location in Axes Unit', ...
'visible','off', ...
'String',' ','Value',[0 0 0]);
if usepanel
set(handles.impos, 'visible', 'on');
end
% Origin Position
%
x = info_pos(1);
y = y + inputline_space*1.2;
w = info_pos(3)*0.5;
h = inputline_space*0.6;
pos = [x y w h];
handles.Torigin = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','[X Y Z] at origin:');
if usepanel
set(handles.Torigin, 'visible', 'on');
end
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.origin = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'right',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String',' ','Value',[0 0 0]);
if usepanel
set(handles.origin, 'visible', 'on');
end
if 0
% Voxel Unit
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
handles.Tcoord = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Axes Unit:');
if usepanel
set(handles.Tcoord, 'visible', 'on');
end
x = x + w + 0.005;
w = info_pos(3)*0.5 - 0.005;
pos = [x y w h];
Font.FontSize = 8;
handles.coord = uicontrol('Parent',fig,'Style','popupmenu', ...
'Units','Normalized', Font, ...
'Position',pos, ...
'BackgroundColor', [1 1 1], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'TooltipString','Choose Voxel or Millimeter',...
'String',{'Voxel','Millimeter'},...
'visible','off', ...
'Callback','view_nii(''coordinates'');');
% 'TooltipString','Choose Voxel, MNI or Talairach Coordinates',...
% 'String',{'Voxel','MNI (mm)','Talairach (mm)'},...
Font.FontSize = 12;
if usepanel
set(handles.coord, 'visible', 'on');
end
end
% Crosshair
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.4;
pos = [x y w h];
handles.Txhair = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Crosshair:');
if usepanel
set(handles.Txhair, 'visible', 'on');
end
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.2;
h = inputline_space*0.7;
pos = [x y w h];
Font.FontSize = 8;
handles.xhair_color = uicontrol('Parent',fig,'Style','push', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'TooltipString','Crosshair Color',...
'User',[1 0 0],...
'String','Color',...
'visible','off', ...
'Callback','view_nii(''xhair_color'');');
if usepanel
set(handles.xhair_color, 'visible', 'on');
end
x = info_pos(1) + info_pos(3)*0.7;
w = info_pos(3)*0.3;
pos = [x y w h];
handles.xhair = uicontrol('Parent',fig,'Style','popupmenu', ...
'Units','Normalized', Font, ...
'Position',pos, ...
'BackgroundColor', [1 1 1], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'TooltipString','Display or Hide Crosshair',...
'String',{'On','Off'},...
'visible','off', ...
'Callback','view_nii(''crosshair'');');
if usepanel
set(handles.xhair, 'visible', 'on');
end
% Histogram & Color
%
x = info_pos(1);
w = info_pos(3)*0.45;
h = inputline_space * 1.5;
pos = [x, y+inputline_space*0.9, w, h];
handles.hist_frame = uicontrol('Parent',fig, ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'Position',pos, ...
'visible','off', ...
'Style','frame');
if usepanel
% set(handles.hist_frame, 'visible', 'on');
end
handles.coord_frame = uicontrol('Parent',fig, ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'Position',pos, ...
'visible','off', ...
'Style','frame');
if usepanel
set(handles.coord_frame, 'visible', 'on');
end
x = info_pos(1) + info_pos(3)*0.475;
w = info_pos(3)*0.525;
h = inputline_space * 1.5;
pos = [x, y+inputline_space*0.9, w, h];
handles.color_frame = uicontrol('Parent',fig, ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'Position',pos, ...
'visible','off', ...
'Style','frame');
if usepanel
set(handles.color_frame, 'visible', 'on');
end
x = info_pos(1) + info_pos(3)*0.025;
y = y + inputline_space*1.2;
w = info_pos(3)*0.2;
h = inputline_space*0.7;
pos = [x y w h];
Font.FontSize = 8;
handles.hist_eq = uicontrol('Parent',fig,'Style','toggle', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'TooltipString','Histogram Equalization',...
'String','Hist EQ',...
'visible','off', ...
'Callback','view_nii(''hist_eq'');');
if usepanel
% set(handles.hist_eq, 'visible', 'on');
end
x = x + w;
w = info_pos(3)*0.2;
pos = [x y w h];
handles.hist_plot = uicontrol('Parent',fig,'Style','push', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'TooltipString','Histogram Plot',...
'String','Hist Plot',...
'visible','off', ...
'Callback','view_nii(''hist_plot'');');
if usepanel
% set(handles.hist_plot, 'visible', 'on');
end
x = info_pos(1) + info_pos(3)*0.025;
w = info_pos(3)*0.4;
pos = [x y w h];
handles.coord = uicontrol('Parent',fig,'Style','popupmenu', ...
'Units','Normalized', Font, ...
'Position',pos, ...
'BackgroundColor', [1 1 1], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'TooltipString','Choose Voxel or Millimeter',...
'String',{'Voxel','Millimeter'},...
'visible','off', ...
'Callback','view_nii(''coordinates'');');
% 'TooltipString','Choose Voxel, MNI or Talairach Coordinates',...
% 'String',{'Voxel','MNI (mm)','Talairach (mm)'},...
if usepanel
set(handles.coord, 'visible', 'on');
end
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.2;
pos = [x y w h];
handles.neg_color = uicontrol('Parent',fig,'Style','toggle', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'TooltipString','Negative Colormap',...
'String','Negative',...
'visible','off', ...
'Callback','view_nii(''neg_color'');');
if usepanel
set(handles.neg_color, 'visible', 'on');
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
set(handles.neg_color, 'enable', 'off');
end
x = info_pos(1) + info_pos(3)*0.7;
w = info_pos(3)*0.275;
pos = [x y w h];
handles.colorindex = uicontrol('Parent',fig,'Style','popupmenu', ...
'Units','Normalized', Font, ...
'Position',pos, ...
'BackgroundColor', [1 1 1], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'TooltipString','Change Colormap',...
'String',{'Custom','Bipolar','Gray','Jet','Cool','Bone','Hot','Copper','Pink'},...
'value', colorindex, ...
'visible','off', ...
'Callback','view_nii(''color'');');
if usepanel
set(handles.colorindex, 'visible', 'on');
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
set(handles.colorindex, 'enable', 'off');
end
x = info_pos(1) + info_pos(3)*0.1;
y = y + inputline_space;
w = info_pos(3)*0.28;
h = inputline_space*0.6;
pos = [x y w h];
Font.FontSize = 8;
handles.Thist = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Histogram');
handles.Tcoord = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Axes Unit');
if usepanel
% set(handles.Thist, 'visible', 'on');
set(handles.Tcoord, 'visible', 'on');
end
x = info_pos(1) + info_pos(3)*0.60;
w = info_pos(3)*0.28;
pos = [x y w h];
handles.Tcolor = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Colormap');
if usepanel
set(handles.Tcolor, 'visible', 'on');
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
set(handles.Tcolor, 'enable', 'off');
end
% Contrast Frame
%
x = info_pos(1);
w = info_pos(3)*0.45;
h = inputline_space * 2;
pos = [x, y+inputline_space*0.8, w, h];
handles.contrast_frame = uicontrol('Parent',fig, ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'Position',pos, ...
'visible','off', ...
'Style','frame');
if usepanel
set(handles.contrast_frame, 'visible', 'on');
end
if colorindex < 2 | colorindex > 3
set(handles.contrast_frame, 'visible', 'off');
end
% Brightness Frame
%
x = info_pos(1) + info_pos(3)*0.475;
w = info_pos(3)*0.525;
pos = [x, y+inputline_space*0.8, w, h];
handles.brightness_frame = uicontrol('Parent',fig, ...
'Units','normal', ...
'BackgroundColor',[0.8 0.8 0.8], ...
'Position',pos, ...
'visible','off', ...
'Style','frame');
if usepanel
set(handles.brightness_frame, 'visible', 'on');
end
% Contrast
%
x = info_pos(1) + info_pos(3)*0.025;
y = y + inputline_space;
w = info_pos(3)*0.4;
h = inputline_space*0.6;
pos = [x y w h];
Font.FontSize = 12;
slider_step(1) = 5/255;
slider_step(2) = 5.00001/255;
handles.contrast = uicontrol('Parent',fig, ...
'Style','slider','Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor',[0.5 0.5 0.5],'ForegroundColor',[0 0 0],...
'BusyAction','queue',...
'TooltipString','Change contrast',...
'Min',1,'Max',256,'SliderStep',slider_step, ...
'Value',1, ...
'visible','off', ...
'Callback','view_nii(''contrast'');');
if usepanel
set(handles.contrast, 'visible', 'on');
end
if (nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511) & nii_view.numscan <= 1
set(handles.contrast, 'enable', 'off');
end
if nii_view.numscan > 1
set(handles.contrast, 'min', 1, 'max', nii_view.numscan, ...
'sliderstep',[1/(nii_view.numscan-1) 1.00001/(nii_view.numscan-1)], ...
'Callback', 'view_nii(''slider_change_scan'');');
elseif colorindex < 2 | colorindex > 3
set(handles.contrast, 'visible', 'off');
elseif colorindex == 2
set(handles.contrast,'value',128);
end
set(handles.contrast,'position',pos); % linux66
% Brightness
%
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.475;
pos = [x y w h];
Font.FontSize = 12;
slider_step(1) = 1/50;
slider_step(2) = 1.00001/50;
handles.brightness = uicontrol('Parent',fig, ...
'Style','slider','Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor',[0.5 0.5 0.5],'ForegroundColor',[0 0 0],...
'BusyAction','queue',...
'TooltipString','Change brightness',...
'Min',-1,'Max',1,'SliderStep',slider_step, ...
'Value',0, ...
'visible','off', ...
'Callback','view_nii(''brightness'');');
if usepanel
set(handles.brightness, 'visible', 'on');
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
set(handles.brightness, 'enable', 'off');
end
set(handles.brightness,'position',pos); % linux66
% Contrast text/def
%
x = info_pos(1) + info_pos(3)*0.025;
y = y + inputline_space;
w = info_pos(3)*0.22;
pos = [x y w h];
handles.Tcontrast = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Contrast:');
if usepanel
set(handles.Tcontrast, 'visible', 'on');
end
if (nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511) & nii_view.numscan <= 1
set(handles.Tcontrast, 'enable', 'off');
end
if nii_view.numscan > 1
set(handles.Tcontrast, 'string', 'Scan ID:');
set(handles.contrast, 'TooltipString', 'Change Scan ID');
elseif colorindex < 2 | colorindex > 3
set(handles.Tcontrast, 'visible', 'off');
end
x = x + w;
w = info_pos(3)*0.18;
pos = [x y w h];
Font.FontSize = 8;
handles.contrast_def = uicontrol('Parent',fig,'Style','push', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'TooltipString','Restore initial contrast',...
'String','Reset',...
'visible','off', ...
'Callback','view_nii(''contrast_def'');');
if usepanel
set(handles.contrast_def, 'visible', 'on');
end
if (nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511) & nii_view.numscan <= 1
set(handles.contrast_def, 'enable', 'off');
end
if nii_view.numscan > 1
set(handles.contrast_def, 'style', 'edit', 'background', 'w', ...
'TooltipString','Scan (or volume) index in the time series',...
'string', '1', 'Callback', 'view_nii(''edit_change_scan'');');
elseif colorindex < 2 | colorindex > 3
set(handles.contrast_def, 'visible', 'off');
end
% Brightness text/def
%
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.295;
pos = [x y w h];
Font.FontSize = 12;
handles.Tbrightness = uicontrol('Parent',fig,'Style','text', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'left',...
'BackgroundColor', [0.8 0.8 0.8], 'ForegroundColor', [0 0 0],...
'BusyAction','queue',...
'visible','off', ...
'String','Brightness:');
if usepanel
set(handles.Tbrightness, 'visible', 'on');
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
set(handles.Tbrightness, 'enable', 'off');
end
x = x + w;
w = info_pos(3)*0.18;
pos = [x y w h];
Font.FontSize = 8;
handles.brightness_def = uicontrol('Parent',fig,'Style','push', ...
'Units','Normalized', Font, ...
'Position',pos, 'HorizontalAlignment', 'center',...
'TooltipString','Restore initial brightness',...
'String','Reset',...
'visible','off', ...
'Callback','view_nii(''brightness_def'');');
if usepanel
set(handles.brightness_def, 'visible', 'on');
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
set(handles.brightness_def, 'enable', 'off');
end
% init image handles
%
handles.axial_image = [];
handles.coronal_image = [];
handles.sagittal_image = [];
% plot axial view
%
if ~isempty(nii_view.bgimg)
bg_slice = squeeze(bgimg(:,:,nii_view.slices.axi));
h1 = plot_view(fig, xdim, ydim, top_ax, bg_slice', clim, cbarminmax, ...
handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, useinterp, nii_view.numscan);
handles.axial_bg = h1;
else
handles.axial_bg = [];
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
img_slice = squeeze(nii.img(:,:,nii_view.slices.axi,:,setscanid));
img_slice = permute(img_slice, [2 1 3]);
else
img_slice = squeeze(nii.img(:,:,nii_view.slices.axi,setscanid));
img_slice = img_slice';
end
h1 = plot_view(fig, xdim, ydim, top_ax, img_slice, clim, cbarminmax, ...
handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, useinterp, nii_view.numscan);
set(h1,'buttondown','view_nii(''axial_image'');');
handles.axial_image = h1;
handles.axial_axes = top_ax;
if size(img_slice,1) == 1 | size(img_slice,2) == 1
set(top_ax,'visible','off');
if isfield(handles,'sagittal_slider') & ishandle(handles.sagittal_slider)
set(handles.sagittal_slider, 'visible', 'off');
end
if isfield(handles,'coronal_slider') & ishandle(handles.coronal_slider)
set(handles.coronal_slider, 'visible', 'off');
end
if isfield(handles,'axial_slider') & ishandle(handles.axial_slider)
set(handles.axial_slider, 'visible', 'off');
end
end
% plot coronal view
%
if ~isempty(nii_view.bgimg)
bg_slice = squeeze(bgimg(:,nii_view.slices.cor,:));
h1 = plot_view(fig, xdim, zdim, front_ax, bg_slice', clim, cbarminmax, ...
handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, useinterp, nii_view.numscan);
handles.coronal_bg = h1;
else
handles.coronal_bg = [];
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
img_slice = squeeze(nii.img(:,nii_view.slices.cor,:,:,setscanid));
img_slice = permute(img_slice, [2 1 3]);
else
img_slice = squeeze(nii.img(:,nii_view.slices.cor,:,setscanid));
img_slice = img_slice';
end
h1 = plot_view(fig, xdim, zdim, front_ax, img_slice, clim, cbarminmax, ...
handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, useinterp, nii_view.numscan);
set(h1,'buttondown','view_nii(''coronal_image'');');
handles.coronal_image = h1;
handles.coronal_axes = front_ax;
if size(img_slice,1) == 1 | size(img_slice,2) == 1
set(front_ax,'visible','off');
if isfield(handles,'sagittal_slider') & ishandle(handles.sagittal_slider)
set(handles.sagittal_slider, 'visible', 'off');
end
if isfield(handles,'coronal_slider') & ishandle(handles.coronal_slider)
set(handles.coronal_slider, 'visible', 'off');
end
if isfield(handles,'axial_slider') & ishandle(handles.axial_slider)
set(handles.axial_slider, 'visible', 'off');
end
end
% plot sagittal view
%
if ~isempty(nii_view.bgimg)
bg_slice = squeeze(bgimg(nii_view.slices.sag,:,:));
h1 = plot_view(fig, ydim, zdim, side_ax, bg_slice', clim, cbarminmax, ...
handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, useinterp, nii_view.numscan);
handles.sagittal_bg = h1;
else
handles.sagittal_bg = [];
end
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
img_slice = squeeze(nii.img(nii_view.slices.sag,:,:,:,setscanid));
img_slice = permute(img_slice, [2 1 3]);
else
img_slice = squeeze(nii.img(nii_view.slices.sag,:,:,setscanid));
img_slice = img_slice';
end
h1 = plot_view(fig, ydim, zdim, side_ax, img_slice, clim, cbarminmax, ...
handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, useinterp, nii_view.numscan);
set(h1,'buttondown','view_nii(''sagittal_image'');');
set(side_ax,'Xdir', 'reverse');
handles.sagittal_image = h1;
handles.sagittal_axes = side_ax;
if size(img_slice,1) == 1 | size(img_slice,2) == 1
set(side_ax,'visible','off');
if isfield(handles,'sagittal_slider') & ishandle(handles.sagittal_slider)
set(handles.sagittal_slider, 'visible', 'off');
end
if isfield(handles,'coronal_slider') & ishandle(handles.coronal_slider)
set(handles.coronal_slider, 'visible', 'off');
end
if isfield(handles,'axial_slider') & ishandle(handles.axial_slider)
set(handles.axial_slider, 'visible', 'off');
end
end
[top1_label, top2_label, side1_label, side2_label] = ...
dir_label(fig, top_ax, front_ax, side_ax);
% store label handles
%
handles.top1_label = top1_label;
handles.top2_label = top2_label;
handles.side1_label = side1_label;
handles.side2_label = side2_label;
% plot colorbar
%
if ~isempty(cbar_axes) & ~isempty(cbarminmax_axes)
if 0
if isempty(color_map)
level = colorlevel + num_highcolor;
else
level = size([color_map; highcolor], 1);
end
end
if isempty(color_map)
level = colorlevel;
else
level = size([color_map], 1);
end
niiclass = class(nii.img);
h1 = plot_cbar(fig, cbar_axes, cbarminmax_axes, cbarminmax, ...
level, handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, niiclass, nii_view.numscan);
handles.cbar_image = h1;
handles.cbar_axes = cbar_axes;
handles.cbarminmax_axes = cbarminmax_axes;
end
nii_view.handles = handles; % store handles
nii_view.usepanel = usepanel; % whole panel at low right cornor
nii_view.usestretch = usestretch; % stretch display of voxel_size
nii_view.useinterp = useinterp; % use interpolation
nii_view.colorindex = colorindex; % store colorindex variable
nii_view.buttondown = buttondown; % command after button down click
nii_view.cbarminmax = cbarminmax; % store min max value for colorbar
set_coordinates(nii_view,useinterp); % coord unit
if ~isfield(nii_view, 'axi_xhair') | ...
~isfield(nii_view, 'cor_xhair') | ...
~isfield(nii_view, 'sag_xhair')
nii_view.axi_xhair = []; % top cross hair
nii_view.cor_xhair = []; % front cross hair
nii_view.sag_xhair = []; % side cross hair
end
if ~isempty(color_map)
nii_view.color_map = color_map;
end
if ~isempty(colorlevel)
nii_view.colorlevel = colorlevel;
end
if ~isempty(highcolor)
nii_view.highcolor = highcolor;
end
update_nii_view(nii_view);
if ~isempty(setunit)
update_unit(fig, setunit);
end
if ~isempty(setviewpoint)
update_viewpoint(fig, setviewpoint);
end
if ~isempty(setcrosshaircolor)
update_crosshaircolor(fig, setcrosshaircolor);
end
if ~isempty(usecrosshair)
update_usecrosshair(fig, usecrosshair);
end
nii_menu = getappdata(fig, 'nii_menu');
if ~isempty(nii_menu)
if nii.hdr.dime.datatype == 128 | nii.hdr.dime.datatype == 511
set(nii_menu.Minterp,'Userdata',1,'Label','Interp on','enable','off');
elseif useinterp
set(nii_menu.Minterp,'Userdata',0,'Label','Interp off');
else
set(nii_menu.Minterp,'Userdata',1,'Label','Interp on');
end
end
windowbuttonmotion = get(fig, 'windowbuttonmotion');
windowbuttonmotion = [windowbuttonmotion '; view_nii(''move_cursor'');'];
set(fig, 'windowbuttonmotion', windowbuttonmotion);
return; % init
%----------------------------------------------------------------
function fig = update_img(img, fig, opt)
nii_menu = getappdata(fig,'nii_menu');
if ~isempty(nii_menu)
set(nii_menu.Mzoom,'Userdata',1,'Label','Zoom on');
set(fig,'pointer','arrow');
zoom off;
end
nii_view = getappdata(fig,'nii_view');
change_interp = 0;
if isfield(opt, 'useinterp') & opt.useinterp ~= nii_view.useinterp
nii_view.useinterp = opt.useinterp;
change_interp = 1;
end
setscanid = 1;
if isfield(opt, 'setscanid')
setscanid = round(opt.setscanid);
if setscanid < 1
setscanid = 1;
end
if setscanid > nii_view.numscan
setscanid = nii_view.numscan;
end
end
if isfield(opt, 'glblocminmax') & ~isempty(opt.glblocminmax)
minvalue = opt.glblocminmax(1);
maxvalue = opt.glblocminmax(2);
else
minvalue = img(:,:,:,setscanid);
minvalue = double(minvalue(:));
minvalue = min(minvalue(~isnan(minvalue)));
maxvalue = img(:,:,:,setscanid);
maxvalue = double(maxvalue(:));
maxvalue = max(maxvalue(~isnan(maxvalue)));
end
if isfield(opt, 'setvalue')
setvalue = opt.setvalue;
if isfield(opt, 'glblocminmax') & ~isempty(opt.glblocminmax)
minvalue = opt.glblocminmax(1);
maxvalue = opt.glblocminmax(2);
else
minvalue = double(min(setvalue.val));
maxvalue = double(max(setvalue.val));
end
bgimg = double(img);
minbg = double(min(bgimg(:)));
maxbg = double(max(bgimg(:)));
bgimg = scale_in(bgimg, minbg, maxbg, 55) + 200; % scale to 201~256
cbarminmax = [minvalue maxvalue];
if nii_view.useinterp
% scale signal data to 1~200
%
img = repmat(nan, size(img));
img(setvalue.idx) = setvalue.val;
% 200 level for source image
%
bgimg = single(scale_out(bgimg, cbarminmax(1), cbarminmax(2), 199));
else
bgimg(setvalue.idx) = NaN;
minbg = double(min(bgimg(:)));
maxbg = double(max(bgimg(:)));
bgimg(setvalue.idx) = minbg;
% bgimg must be normalized to [201 256]
%
bgimg = 55 * (bgimg-min(bgimg(:))) / (max(bgimg(:))-min(bgimg(:))) + 201;
bgimg(setvalue.idx) = 0;
% scale signal data to 1~200
%
img = zeros(size(img));
img(setvalue.idx) = scale_in(setvalue.val, minvalue, maxvalue, 199);
img = img + bgimg;
bgimg = [];
img = scale_out(img, cbarminmax(1), cbarminmax(2), 199);
minvalue = double(min(img(:)));
maxvalue = double(max(img(:)));
if isfield(opt,'glblocminmax') & ~isempty(opt.glblocminmax)
minvalue = opt.glblocminmax(1);
end
end
nii_view.bgimg = bgimg;
nii_view.setvalue = setvalue;
else
cbarminmax = [minvalue maxvalue];
end
update_cbarminmax(fig, cbarminmax);
nii_view.cbarminmax = cbarminmax;
nii_view.nii.img = img;
nii_view.minvalue = minvalue;
nii_view.maxvalue = maxvalue;
nii_view.scanid = setscanid;
change_colormap(fig);
% init color (gray) scaling to make sure the slice clim take the
% global clim [min(nii.img(:)) max(nii.img(:))]
%
if isempty(nii_view.bgimg)
clim = [minvalue maxvalue];
else
clim = [minvalue double(max(nii_view.bgimg(:)))];
end
if clim(1) == clim(2)
clim(2) = clim(1) + 0.000001;
end
if strcmpi(get(nii_view.handles.axial_image,'cdatamapping'), 'direct')
useimagesc = 0;
else
useimagesc = 1;
end
if ~isempty(nii_view.bgimg) % with interpolation
Saxi = squeeze(nii_view.bgimg(:,:,nii_view.slices.axi));
if isfield(nii_view.handles,'axial_bg') & ~isempty(nii_view.handles.axial_bg)
set(nii_view.handles.axial_bg,'CData',double(Saxi)');
else
axes(nii_view.handles.axial_axes);
if useimagesc
nii_view.handles.axial_bg = surface(zeros(size(Saxi')),double(Saxi'),'edgecolor','none','facecolor','interp');
else
nii_view.handles.axial_bg = surface(zeros(size(Saxi')),double(Saxi'),'cdatamapping','direct','edgecolor','none','facecolor','interp');
end
order = get(gca,'child');
order(find(order == nii_view.handles.axial_bg)) = [];
order = [order; nii_view.handles.axial_bg];
set(gca, 'child', order);
end
end
if isfield(nii_view.handles,'axial_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Saxi = squeeze(nii_view.nii.img(:,:,nii_view.slices.axi,:,setscanid));
Saxi = permute(Saxi, [2 1 3]);
else
Saxi = squeeze(nii_view.nii.img(:,:,nii_view.slices.axi,setscanid));
Saxi = Saxi';
end
set(nii_view.handles.axial_image,'CData',double(Saxi));
end
set(nii_view.handles.axial_axes,'CLim',clim);
if ~isempty(nii_view.bgimg)
Scor = squeeze(nii_view.bgimg(:,nii_view.slices.cor,:));
if isfield(nii_view.handles,'coronal_bg') & ~isempty(nii_view.handles.coronal_bg)
set(nii_view.handles.coronal_bg,'CData',double(Scor)');
else
axes(nii_view.handles.coronal_axes);
if useimagesc
nii_view.handles.coronal_bg = surface(zeros(size(Scor')),double(Scor'),'edgecolor','none','facecolor','interp');
else
nii_view.handles.coronal_bg = surface(zeros(size(Scor')),double(Scor'),'cdatamapping','direct','edgecolor','none','facecolor','interp');
end
order = get(gca,'child');
order(find(order == nii_view.handles.coronal_bg)) = [];
order = [order; nii_view.handles.coronal_bg];
set(gca, 'child', order);
end
end
if isfield(nii_view.handles,'coronal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Scor = squeeze(nii_view.nii.img(:,nii_view.slices.cor,:,:,setscanid));
Scor = permute(Scor, [2 1 3]);
else
Scor = squeeze(nii_view.nii.img(:,nii_view.slices.cor,:,setscanid));
Scor = Scor';
end
set(nii_view.handles.coronal_image,'CData',double(Scor));
end
set(nii_view.handles.coronal_axes,'CLim',clim);
if ~isempty(nii_view.bgimg)
Ssag = squeeze(nii_view.bgimg(nii_view.slices.sag,:,:));
if isfield(nii_view.handles,'sagittal_bg') & ~isempty(nii_view.handles.sagittal_bg)
set(nii_view.handles.sagittal_bg,'CData',double(Ssag)');
else
axes(nii_view.handles.sagittal_axes);
if useimagesc
nii_view.handles.sagittal_bg = surface(zeros(size(Ssag')),double(Ssag'),'edgecolor','none','facecolor','interp');
else
nii_view.handles.sagittal_bg = surface(zeros(size(Ssag')),double(Ssag'),'cdatamapping','direct','edgecolor','none','facecolor','interp');
end
order = get(gca,'child');
order(find(order == nii_view.handles.sagittal_bg)) = [];
order = [order; nii_view.handles.sagittal_bg];
set(gca, 'child', order);
end
end
if isfield(nii_view.handles,'sagittal_image'),
if nii_view.nii.hdr.dime.datatype == 128 | nii_view.nii.hdr.dime.datatype == 511
Ssag = squeeze(nii_view.nii.img(nii_view.slices.sag,:,:,:,setscanid));
Ssag = permute(Ssag, [2 1 3]);
else
Ssag = squeeze(nii_view.nii.img(nii_view.slices.sag,:,:,setscanid));
Ssag = Ssag';
end
set(nii_view.handles.sagittal_image,'CData',double(Ssag));
end
set(nii_view.handles.sagittal_axes,'CLim',clim);
update_nii_view(nii_view);
if isfield(opt, 'setvalue')
if ~isfield(nii_view,'highcolor') | ~isequal(size(nii_view.highcolor),[56 3])
% 55 level for brain structure (paded 0 for highcolor level 1, i.e. normal level 201, to make 56 highcolor)
%
update_highcolor(fig, [zeros(1,3);gray(55)], []);
end
if nii_view.colorindex ~= 2
update_colorindex(fig, 2);
end
old_color = get(nii_view.handles.xhair_color,'user');
if isequal(old_color, [1 0 0])
update_crosshaircolor(fig, [1 1 0]);
end
% if change_interp
% update_useinterp(fig, nii_view.useinterp);
% end
end
if change_interp
update_useinterp(fig, nii_view.useinterp);
end
return; % update_img
%----------------------------------------------------------------
function [top_pos, front_pos, side_pos] = ...
axes_pos(fig,area,vol_size,usestretch)
set(fig,'unit','pixel');
fig_pos = get(fig,'position');
gap_x = 15/fig_pos(3); % width of vertical scrollbar
gap_y = 15/fig_pos(4); % width of horizontal scrollbar
a = (area(3) - gap_x * 1.3) * fig_pos(3) / (vol_size(1) + vol_size(2)); % no crosshair lost in zoom
b = (area(4) - gap_y * 3) * fig_pos(4) / (vol_size(2) + vol_size(3));
c = min([a b]); % make sure 'ax' is inside 'area'
top_w = vol_size(1) * c / fig_pos(3);
side_w = vol_size(2) * c / fig_pos(3);
top_h = vol_size(2) * c / fig_pos(4);
side_h = vol_size(3) * c / fig_pos(4);
side_x = area(1) + top_w + gap_x * 1.3; % no crosshair lost in zoom
side_y = area(2) + top_h + gap_y * 3;
if usestretch
if a > b % top touched ceiling, use b
d = (area(3) - gap_x * 1.3) / (top_w + side_w); % no crosshair lost in zoom
top_w = top_w * d;
side_w = side_w * d;
side_x = area(1) + top_w + gap_x * 1.3; % no crosshair lost in zoom
else
d = (area(4) - gap_y * 3) / (top_h + side_h);
top_h = top_h * d;
side_h = side_h * d;
side_y = area(2) + top_h + gap_y * 3;
end
end
top_pos = [area(1) area(2)+gap_y top_w top_h];
front_pos = [area(1) side_y top_w side_h];
side_pos = [side_x side_y side_w side_h];
set(fig,'unit','normal');
return; % axes_pos
%----------------------------------------------------------------
function [top_ax, front_ax, side_ax] ...
= create_ax(fig, area, vol_size, usestretch)
cur_fig = gcf; % save h_wait fig
figure(fig);
[top_pos, front_pos, side_pos] = ...
axes_pos(fig,area,vol_size,usestretch);
nii_view = getappdata(fig, 'nii_view');
if isempty(nii_view)
top_ax = axes('position', top_pos);
front_ax = axes('position', front_pos);
side_ax = axes('position', side_pos);
else
top_ax = nii_view.handles.axial_axes;
front_ax = nii_view.handles.coronal_axes;
side_ax = nii_view.handles.sagittal_axes;
set(top_ax, 'position', top_pos);
set(front_ax, 'position', front_pos);
set(side_ax, 'position', side_pos);
end
figure(cur_fig);
return; % create_ax
%----------------------------------------------------------------
function [cbar_axes, cbarminmax_axes] = create_cbar_axes(fig, cbar_area, nii_view)
if isempty(cbar_area) % without_cbar
cbar_axes = [];
cbarminmax_axes = [];
return;
end
cur_fig = gcf; % save h_wait fig
figure(fig);
if ~exist('nii_view', 'var')
nii_view = getappdata(fig, 'nii_view');
end
if isempty(nii_view) | ~isfield(nii_view.handles,'cbar_axes') | isempty(nii_view.handles.cbar_axes)
cbarminmax_axes = axes('position', cbar_area);
cbar_axes = axes('position', cbar_area);
else
cbarminmax_axes = nii_view.handles.cbarminmax_axes;
cbar_axes = nii_view.handles.cbar_axes;
set(cbarminmax_axes, 'position', cbar_area);
set(cbar_axes, 'position', cbar_area);
end
figure(cur_fig);
return; % create_cbar_axes
%----------------------------------------------------------------
function h1 = plot_view(fig, x, y, img_ax, img_slice, clim, ...
cbarminmax, handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, useinterp, numscan)
h1 = [];
if x > 1 & y > 1,
axes(img_ax);
nii_view = getappdata(fig, 'nii_view');
if isempty(nii_view)
% set colormap first
%
nii.handles = handles;
nii.handles.axial_axes = img_ax;
nii.colorindex = colorindex;
nii.color_map = color_map;
nii.colorlevel = colorlevel;
nii.highcolor = highcolor;
nii.numscan = numscan;
change_colormap(fig, nii, colorindex, cbarminmax);
if useinterp
if useimagesc
h1 = surface(zeros(size(img_slice)),double(img_slice),'edgecolor','none','facecolor','interp');
else
h1 = surface(zeros(size(img_slice)),double(img_slice),'cdatamapping','direct','edgecolor','none','facecolor','interp');
end
set(gca,'clim',clim);
else
if useimagesc
h1 = imagesc(img_slice,clim);
else
h1 = image(img_slice);
end
set(gca,'clim',clim);
end
else
h1 = nii_view.handles.axial_image;
if ~isequal(get(h1,'parent'), img_ax)
h1 = nii_view.handles.coronal_image;
end
if ~isequal(get(h1,'parent'), img_ax)
h1 = nii_view.handles.sagittal_image;
end
set(h1, 'cdata', double(img_slice));
set(h1, 'xdata', 1:size(img_slice,2));
set(h1, 'ydata', 1:size(img_slice,1));
end
set(img_ax,'YDir','normal','XLimMode','manual','YLimMode','manual',...
'ClimMode','manual','visible','off', ...
'xtick',[],'ytick',[], 'clim', clim);
end
return; % plot_view
%----------------------------------------------------------------
function h1 = plot_cbar(fig, cbar_axes, cbarminmax_axes, cbarminmax, ...
level, handles, useimagesc, colorindex, color_map, ...
colorlevel, highcolor, niiclass, numscan, nii_view)
cbar_image = [1:level]';
% In a uint8 or uint16 indexed image, 0 points to the first row
% in the colormap
%
if 0 % strcmpi(niiclass,'uint8') | strcmpi(niiclass,'uint16')
% we use single for display anyway
ylim = [0, level-1];
else
ylim = [1, level];
end
axes(cbarminmax_axes);
plot([0 0], cbarminmax, 'w');
axis tight;
set(cbarminmax_axes,'YDir','normal', ...
'XLimMode','manual','YLimMode','manual','YColor',[0 0 0], ...
'XColor',[0 0 0],'xtick',[],'YAxisLocation','right');
ylimb = get(cbarminmax_axes,'ylim');
ytickb = get(cbarminmax_axes,'ytick');
ytick=(ylim(2)-ylim(1))*(ytickb-ylimb(1))/(ylimb(2)-ylimb(1))+ylim(1);
axes(cbar_axes);
if ~exist('nii_view', 'var')
nii_view = getappdata(fig, 'nii_view');
end
if isempty(nii_view) | ~isfield(nii_view.handles,'cbar_image') | isempty(nii_view.handles.cbar_image)
% set colormap first
%
nii.handles = handles;
nii.colorindex = colorindex;
nii.color_map = color_map;
nii.colorlevel = colorlevel;
nii.highcolor = highcolor;
nii.numscan = numscan;
change_colormap(fig, nii, colorindex, cbarminmax);
h1 = image([0,1], [ylim(1),ylim(2)], cbar_image);
else
h1 = nii_view.handles.cbar_image;
set(h1, 'cdata', double(cbar_image));
end
set(cbar_axes,'YDir','normal','XLimMode','manual', ...
'YLimMode','manual','YColor',[0 0 0],'XColor',[0 0 0],'xtick',[], ...
'YAxisLocation','right','ylim',ylim,'ytick',ytick,'yticklabel','');
return; % plot_cbar
%----------------------------------------------------------------
function set_coordinates(nii_view,useinterp)
imgPlim.vox = nii_view.dims;
imgNlim.vox = [1 1 1];
if useinterp
xdata_ax = [imgNlim.vox(1) imgPlim.vox(1)];
ydata_ax = [imgNlim.vox(2) imgPlim.vox(2)];
zdata_ax = [imgNlim.vox(3) imgPlim.vox(3)];
else
xdata_ax = [imgNlim.vox(1)-0.5 imgPlim.vox(1)+0.5];
ydata_ax = [imgNlim.vox(2)-0.5 imgPlim.vox(2)+0.5];
zdata_ax = [imgNlim.vox(3)-0.5 imgPlim.vox(3)+0.5];
end
if isfield(nii_view.handles,'axial_image') & ~isempty(nii_view.handles.axial_image)
set(nii_view.handles.axial_axes,'Xlim',xdata_ax);
set(nii_view.handles.axial_axes,'Ylim',ydata_ax);
end;
if isfield(nii_view.handles,'coronal_image') & ~isempty(nii_view.handles.coronal_image)
set(nii_view.handles.coronal_axes,'Xlim',xdata_ax);
set(nii_view.handles.coronal_axes,'Ylim',zdata_ax);
end;
if isfield(nii_view.handles,'sagittal_image') & ~isempty(nii_view.handles.sagittal_image)
set(nii_view.handles.sagittal_axes,'Xlim',ydata_ax);
set(nii_view.handles.sagittal_axes,'Ylim',zdata_ax);
end;
return % set_coordinates
%----------------------------------------------------------------
function set_image_value(nii_view),
% get coordinates of selected voxel and the image intensity there
%
sag = round(nii_view.slices.sag);
cor = round(nii_view.slices.cor);
axi = round(nii_view.slices.axi);
if 0 % isfield(nii_view, 'disp')
img = nii_view.disp;
else
img = nii_view.nii.img;
end
if nii_view.nii.hdr.dime.datatype == 128
imgvalue = [double(img(sag,cor,axi,1,nii_view.scanid)) double(img(sag,cor,axi,2,nii_view.scanid)) double(img(sag,cor,axi,3,nii_view.scanid))];
set(nii_view.handles.imval,'Value',imgvalue);
set(nii_view.handles.imval,'String',sprintf('%7.4g %7.4g %7.4g',imgvalue));
elseif nii_view.nii.hdr.dime.datatype == 511
R = double(img(sag,cor,axi,1,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
G = double(img(sag,cor,axi,2,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
B = double(img(sag,cor,axi,3,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
imgvalue = [double(img(sag,cor,axi,1,nii_view.scanid)) double(img(sag,cor,axi,2,nii_view.scanid)) double(img(sag,cor,axi,3,nii_view.scanid))];
set(nii_view.handles.imval,'Value',imgvalue);
imgvalue = [R G B];
set(nii_view.handles.imval,'String',sprintf('%7.4g %7.4g %7.4g',imgvalue));
else
imgvalue = double(img(sag,cor,axi,nii_view.scanid));
set(nii_view.handles.imval,'Value',imgvalue);
if isnan(imgvalue) | imgvalue > nii_view.cbarminmax(2)
imgvalue = 0;
end
set(nii_view.handles.imval,'String',sprintf('%.6g',imgvalue));
end
% Now update the coordinates of the selected voxel
nii_view = update_imgXYZ(nii_view);
if get(nii_view.handles.coord,'value') == 1,
sag = nii_view.imgXYZ.vox(1);
cor = nii_view.imgXYZ.vox(2);
axi = nii_view.imgXYZ.vox(3);
org = nii_view.origin;
elseif get(nii_view.handles.coord,'value') == 2,
sag = nii_view.imgXYZ.mm(1);
cor = nii_view.imgXYZ.mm(2);
axi = nii_view.imgXYZ.mm(3);
org = [0 0 0];
elseif get(nii_view.handles.coord,'value') == 3,
sag = nii_view.imgXYZ.tal(1);
cor = nii_view.imgXYZ.tal(2);
axi = nii_view.imgXYZ.tal(3);
org = [0 0 0];
end
set(nii_view.handles.impos,'Value',[sag,cor,axi]);
if get(nii_view.handles.coord,'value') == 1,
string = sprintf('%7.0f %7.0f %7.0f',sag,cor,axi);
org_str = sprintf('%7.0f %7.0f %7.0f', org(1), org(2), org(3));
else
string = sprintf('%7.1f %7.1f %7.1f',sag,cor,axi);
org_str = sprintf('%7.1f %7.1f %7.1f', org(1), org(2), org(3));
end;
set(nii_view.handles.impos,'String',string);
set(nii_view.handles.origin, 'string', org_str);
return % set_image_value
%----------------------------------------------------------------
function nii_view = get_slice_position(nii_view,view),
% obtain slices that is in correct unit, then update slices
%
slices = nii_view.slices;
switch view,
case 'sag',
currentpoint = get(nii_view.handles.sagittal_axes,'CurrentPoint');
slices.cor = currentpoint(1,1);
slices.axi = currentpoint(1,2);
case 'cor',
currentpoint = get(nii_view.handles.coronal_axes,'CurrentPoint');
slices.sag = currentpoint(1,1);
slices.axi = currentpoint(1,2);
case 'axi',
currentpoint = get(nii_view.handles.axial_axes,'CurrentPoint');
slices.sag = currentpoint(1,1);
slices.cor = currentpoint(1,2);
end
% update nii_view.slices with the updated slices
%
nii_view.slices.axi = round(slices.axi);
nii_view.slices.cor = round(slices.cor);
nii_view.slices.sag = round(slices.sag);
return % get_slice_position
%----------------------------------------------------------------
function nii_view = get_slider_position(nii_view),
[nii_view.slices.sag,nii_view.slices.cor,nii_view.slices.axi] = deal(0);
if isfield(nii_view.handles,'sagittal_slider'),
if ishandle(nii_view.handles.sagittal_slider),
nii_view.slices.sag = ...
round(get(nii_view.handles.sagittal_slider,'Value'));
end
end
if isfield(nii_view.handles,'coronal_slider'),
if ishandle(nii_view.handles.coronal_slider),
nii_view.slices.cor = ...
round(nii_view.dims(2) - ...
get(nii_view.handles.coronal_slider,'Value') + 1);
end
end
if isfield(nii_view.handles,'axial_slider'),
if ishandle(nii_view.handles.axial_slider),
nii_view.slices.axi = ...
round(get(nii_view.handles.axial_slider,'Value'));
end
end
nii_view = check_slices(nii_view);
return % get_slider_position
%----------------------------------------------------------------
function nii_view = update_imgXYZ(nii_view),
nii_view.imgXYZ.vox = ...
[nii_view.slices.sag,nii_view.slices.cor,nii_view.slices.axi];
nii_view.imgXYZ.mm = ...
(nii_view.imgXYZ.vox - nii_view.origin) .* nii_view.voxel_size;
% nii_view.imgXYZ.tal = mni2tal(nii_view.imgXYZ.mni);
return % update_imgXYZ
%----------------------------------------------------------------
function nii_view = convert2voxel(nii_view,slices),
if get(nii_view.handles.coord,'value') == 1,
% [slices.axi, slices.cor, slices.sag] are in vox
%
nii_view.slices.axi = round(slices.axi);
nii_view.slices.cor = round(slices.cor);
nii_view.slices.sag = round(slices.sag);
elseif get(nii_view.handles.coord,'value') == 2,
% [slices.axi, slices.cor, slices.sag] are in mm
%
xpix = nii_view.voxel_size(1);
ypix = nii_view.voxel_size(2);
zpix = nii_view.voxel_size(3);
nii_view.slices.axi = round(slices.axi / zpix + nii_view.origin(3));
nii_view.slices.cor = round(slices.cor / ypix + nii_view.origin(2));
nii_view.slices.sag = round(slices.sag / xpix + nii_view.origin(1));
elseif get(nii_view.handles.coord,'value') == 3,
% [slices.axi, slices.cor, slices.sag] are in talairach
%
xpix = nii_view.voxel_size(1);
ypix = nii_view.voxel_size(2);
zpix = nii_view.voxel_size(3);
xyz_tal = [slices.sag, slices.cor, slices.axi];
xyz_mni = tal2mni(xyz_tal);
nii_view.slices.axi = round(xyz_mni(3) / zpix + nii_view.origin(3));
nii_view.slices.cor = round(xyz_mni(2) / ypix + nii_view.origin(2));
nii_view.slices.sag = round(xyz_mni(1) / xpix + nii_view.origin(1));
end
return % convert2voxel
%----------------------------------------------------------------
function nii_view = check_slices(nii_view),
img = nii_view.nii.img;
[ SagSize, CorSize, AxiSize, TimeSize ] = size(img);
if nii_view.slices.sag > SagSize, nii_view.slices.sag = SagSize; end;
if nii_view.slices.sag < 1, nii_view.slices.sag = 1; end;
if nii_view.slices.cor > CorSize, nii_view.slices.cor = CorSize; end;
if nii_view.slices.cor < 1, nii_view.slices.cor = 1; end;
if nii_view.slices.axi > AxiSize, nii_view.slices.axi = AxiSize; end;
if nii_view.slices.axi < 1, nii_view.slices.axi = 1; end;
if nii_view.scanid > TimeSize, nii_view.scanid = TimeSize; end;
if nii_view.scanid < 1, nii_view.scanid = 1; end;
return % check_slices
%----------------------------------------------------------------
%
% keep this function small, since it will be called for every click
%
function nii_view = update_nii_view(nii_view)
% add imgXYZ into nii_view struct
%
nii_view = check_slices(nii_view);
nii_view = update_imgXYZ(nii_view);
% update xhair
%
p_axi = nii_view.imgXYZ.vox([1 2]);
p_cor = nii_view.imgXYZ.vox([1 3]);
p_sag = nii_view.imgXYZ.vox([2 3]);
nii_view.axi_xhair = ...
rri_xhair(p_axi, nii_view.axi_xhair, nii_view.handles.axial_axes);
nii_view.cor_xhair = ...
rri_xhair(p_cor, nii_view.cor_xhair, nii_view.handles.coronal_axes);
nii_view.sag_xhair = ...
rri_xhair(p_sag, nii_view.sag_xhair, nii_view.handles.sagittal_axes);
setappdata(nii_view.fig, 'nii_view', nii_view);
set_image_value(nii_view);
return; % update_nii_view
%----------------------------------------------------------------
function hist_plot(fig)
nii_view = getappdata(fig,'nii_view');
if isfield(nii_view, 'disp')
img = nii_view.disp;
else
img = nii_view.nii.img;
end
img = double(img(:));
if length(unique(round(img))) == length(unique(img))
is_integer = 1;
range = max(img) - min(img) + 1;
figure; hist(img, range);
set(gca, 'xlim', [-range/5, max(img)]);
else
is_integer = 0;
figure; hist(img);
end
xlabel('Voxel Intensity');
ylabel('Voxel Numbers for Each Intensity');
set(gcf, 'NumberTitle','off','Name','Histogram Plot');
return; % hist_plot
%----------------------------------------------------------------
function hist_eq(fig)
nii_view = getappdata(fig,'nii_view');
old_pointer = get(fig,'Pointer');
set(fig,'Pointer','watch');
if get(nii_view.handles.hist_eq,'value')
max_img = double(max(nii_view.nii.img(:)));
tmp = double(nii_view.nii.img) / max_img; % normalize for histeq
tmp = histeq(tmp(:));
nii_view.disp = reshape(tmp, size(nii_view.nii.img));
min_disp = min(nii_view.disp(:));
nii_view.disp = (nii_view.disp - min_disp); % range having eq hist
nii_view.disp = nii_view.disp * max_img / max(nii_view.disp(:));
nii_view.disp = single(nii_view.disp);
else
if isfield(nii_view, 'disp')
nii_view.disp = nii_view.nii.img;
else
set(fig,'Pointer',old_pointer);
return;
end
end
% update axial view
%
img_slice = squeeze(double(nii_view.disp(:,:,nii_view.slices.axi)));
h1 = nii_view.handles.axial_image;
set(h1, 'cdata', double(img_slice)');
% update coronal view
%
img_slice = squeeze(double(nii_view.disp(:,nii_view.slices.cor,:)));
h1 = nii_view.handles.coronal_image;
set(h1, 'cdata', double(img_slice)');
% update sagittal view
%
img_slice = squeeze(double(nii_view.disp(nii_view.slices.sag,:,:)));
h1 = nii_view.handles.sagittal_image;
set(h1, 'cdata', double(img_slice)');
% remove disp field if un-check 'histeq' button
%
if ~get(nii_view.handles.hist_eq,'value') & isfield(nii_view, 'disp')
nii_view = rmfield(nii_view, 'disp');
end
update_nii_view(nii_view);
set(fig,'Pointer',old_pointer);
return; % hist_eq
%----------------------------------------------------------------
function [top1_label, top2_label, side1_label, side2_label] = ...
dir_label(fig, top_ax, front_ax, side_ax)
nii_view = getappdata(fig,'nii_view');
top_pos = get(top_ax,'position');
front_pos = get(front_ax,'position');
side_pos = get(side_ax,'position');
top_gap_x = (side_pos(1)-top_pos(1)-top_pos(3)) / (2*top_pos(3));
top_gap_y = (front_pos(2)-top_pos(2)-top_pos(4)) / (2*top_pos(4));
side_gap_x = (side_pos(1)-top_pos(1)-top_pos(3)) / (2*side_pos(3));
side_gap_y = (front_pos(2)-top_pos(2)-top_pos(4)) / (2*side_pos(4));
top1_label_pos = [0, 1]; % rot0
top2_label_pos = [1, 0]; % rot90
side1_label_pos = [1, - side_gap_y]; % rot0
side2_label_pos = [0, 0]; % rot90
if isempty(nii_view)
axes(top_ax);
top1_label = text(double(top1_label_pos(1)),double(top1_label_pos(2)), ...
'== X =>', ...
'vertical', 'bottom', ...
'unit', 'normal', 'fontsize', 8);
axes(top_ax);
top2_label = text(double(top2_label_pos(1)),double(top2_label_pos(2)), ...
'== Y =>', ...
'rotation', 90, 'vertical', 'top', ...
'unit', 'normal', 'fontsize', 8);
axes(side_ax);
side1_label = text(double(side1_label_pos(1)),double(side1_label_pos(2)), ...
'<= Y ==', ...
'horizontal', 'right', 'vertical', 'top', ...
'unit', 'normal', 'fontsize', 8);
axes(side_ax);
side2_label = text(double(side2_label_pos(1)),double(side2_label_pos(2)), ...
'== Z =>', ...
'rotation', 90, 'vertical', 'bottom', ...
'unit', 'normal', 'fontsize', 8);
else
top1_label = nii_view.handles.top1_label;
top2_label = nii_view.handles.top2_label;
side1_label = nii_view.handles.side1_label;
side2_label = nii_view.handles.side2_label;
set(top1_label, 'position', [top1_label_pos 0]);
set(top2_label, 'position', [top2_label_pos 0]);
set(side1_label, 'position', [side1_label_pos 0]);
set(side2_label, 'position', [side2_label_pos 0]);
end
return; % dir_label
%----------------------------------------------------------------
function update_enable(h, opt);
nii_view = getappdata(h,'nii_view');
handles = nii_view.handles;
if isfield(opt,'enablecursormove')
if opt.enablecursormove
v = 'on';
else
v = 'off';
end
set(handles.Timposcur, 'visible', v);
set(handles.imposcur, 'visible', v);
set(handles.Timvalcur, 'visible', v);
set(handles.imvalcur, 'visible', v);
end
if isfield(opt,'enableviewpoint')
if opt.enableviewpoint
v = 'on';
else
v = 'off';
end
set(handles.Timpos, 'visible', v);
set(handles.impos, 'visible', v);
set(handles.Timval, 'visible', v);
set(handles.imval, 'visible', v);
end
if isfield(opt,'enableorigin')
if opt.enableorigin
v = 'on';
else
v = 'off';
end
set(handles.Torigin, 'visible', v);
set(handles.origin, 'visible', v);
end
if isfield(opt,'enableunit')
if opt.enableunit
v = 'on';
else
v = 'off';
end
set(handles.Tcoord, 'visible', v);
set(handles.coord_frame, 'visible', v);
set(handles.coord, 'visible', v);
end
if isfield(opt,'enablecrosshair')
if opt.enablecrosshair
v = 'on';
else
v = 'off';
end
set(handles.Txhair, 'visible', v);
set(handles.xhair_color, 'visible', v);
set(handles.xhair, 'visible', v);
end
if isfield(opt,'enablehistogram')
if opt.enablehistogram
v = 'on';
vv = 'off';
else
v = 'off';
vv = 'on';
end
set(handles.Tcoord, 'visible', vv);
set(handles.coord_frame, 'visible', vv);
set(handles.coord, 'visible', vv);
set(handles.Thist, 'visible', v);
set(handles.hist_frame, 'visible', v);
set(handles.hist_eq, 'visible', v);
set(handles.hist_plot, 'visible', v);
end
if isfield(opt,'enablecolormap')
if opt.enablecolormap
v = 'on';
else
v = 'off';
end
set(handles.Tcolor, 'visible', v);
set(handles.color_frame, 'visible', v);
set(handles.neg_color, 'visible', v);
set(handles.colorindex, 'visible', v);
end
if isfield(opt,'enablecontrast')
if opt.enablecontrast
v = 'on';
else
v = 'off';
end
set(handles.Tcontrast, 'visible', v);
set(handles.contrast_frame, 'visible', v);
set(handles.contrast_def, 'visible', v);
set(handles.contrast, 'visible', v);
end
if isfield(opt,'enablebrightness')
if opt.enablebrightness
v = 'on';
else
v = 'off';
end
set(handles.Tbrightness, 'visible', v);
set(handles.brightness_frame, 'visible', v);
set(handles.brightness_def, 'visible', v);
set(handles.brightness, 'visible', v);
end
if isfield(opt,'enabledirlabel')
if opt.enabledirlabel
v = 'on';
else
v = 'off';
end
set(handles.top1_label, 'visible', v);
set(handles.top2_label, 'visible', v);
set(handles.side1_label, 'visible', v);
set(handles.side2_label, 'visible', v);
end
if isfield(opt,'enableslider')
if opt.enableslider
v = 'on';
else
v = 'off';
end
if isfield(handles,'sagittal_slider') & ishandle(handles.sagittal_slider)
set(handles.sagittal_slider, 'visible', v);
end
if isfield(handles,'coronal_slider') & ishandle(handles.coronal_slider)
set(handles.coronal_slider, 'visible', v);
end
if isfield(handles,'axial_slider') & ishandle(handles.axial_slider)
set(handles.axial_slider, 'visible', v);
end
end
return; % update_enable
%----------------------------------------------------------------
function update_usepanel(fig, usepanel)
if isempty(usepanel)
return;
end
if usepanel
opt.enablecursormove = 1;
opt.enableviewpoint = 1;
opt.enableorigin = 1;
opt.enableunit = 1;
opt.enablecrosshair = 1;
% opt.enablehistogram = 1;
opt.enablecolormap = 1;
opt.enablecontrast = 1;
opt.enablebrightness = 1;
else
opt.enablecursormove = 0;
opt.enableviewpoint = 0;
opt.enableorigin = 0;
opt.enableunit = 0;
opt.enablecrosshair = 0;
% opt.enablehistogram = 0;
opt.enablecolormap = 0;
opt.enablecontrast = 0;
opt.enablebrightness = 0;
end
update_enable(fig, opt);
nii_view = getappdata(fig,'nii_view');
nii_view.usepanel = usepanel;
setappdata(fig,'nii_view',nii_view);
return; % update_usepanel
%----------------------------------------------------------------
function update_usecrosshair(fig, usecrosshair)
if isempty(usecrosshair)
return;
end
if usecrosshair
v=1;
else
v=2;
end
nii_view = getappdata(fig,'nii_view');
set(nii_view.handles.xhair,'value',v);
opt.command = 'crosshair';
view_nii(fig, opt);
return; % update_usecrosshair
%----------------------------------------------------------------
function update_usestretch(fig, usestretch)
nii_view = getappdata(fig,'nii_view');
handles = nii_view.handles;
fig = nii_view.fig;
area = nii_view.area;
vol_size = nii_view.voxel_size .* nii_view.dims;
% Three Axes & label
%
[top_ax, front_ax, side_ax] = ...
create_ax(fig, area, vol_size, usestretch);
dir_label(fig, top_ax, front_ax, side_ax);
top_pos = get(top_ax,'position');
front_pos = get(front_ax,'position');
side_pos = get(side_ax,'position');
% Sagittal Slider
%
x = side_pos(1);
y = top_pos(2) + top_pos(4);
w = side_pos(3);
h = (front_pos(2) - y) / 2;
y = y + h;
pos = [x y w h];
if isfield(handles,'sagittal_slider') & ishandle(handles.sagittal_slider)
set(handles.sagittal_slider,'position',pos);
end
% Coronal Slider
%
x = top_pos(1);
y = top_pos(2) + top_pos(4);
w = top_pos(3);
h = (front_pos(2) - y) / 2;
y = y + h;
pos = [x y w h];
if isfield(handles,'coronal_slider') & ishandle(handles.coronal_slider)
set(handles.coronal_slider,'position',pos);
end
% Axial Slider
%
x = top_pos(1);
y = area(2);
w = top_pos(3);
h = top_pos(2) - y;
pos = [x y w h];
if isfield(handles,'axial_slider') & ishandle(handles.axial_slider)
set(handles.axial_slider,'position',pos);
end
% plot info view
%
% info_pos = [side_pos([1,3]); top_pos([2,4])];
% info_pos = info_pos(:);
gap = side_pos(1)-(top_pos(1)+top_pos(3));
info_pos(1) = side_pos(1) + gap;
info_pos(2) = area(2);
info_pos(3) = side_pos(3) - gap;
info_pos(4) = top_pos(2) + top_pos(4) - area(2) - gap;
num_inputline = 10;
inputline_space =info_pos(4) / num_inputline;
% Image Intensity Value at Cursor
%
x = info_pos(1);
y = info_pos(2);
w = info_pos(3)*0.5;
h = inputline_space*0.6;
pos = [x y w h];
set(handles.Timvalcur,'position',pos);
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.imvalcur,'position',pos);
% Position at Cursor
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.Timposcur,'position',pos);
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.imposcur,'position',pos);
% Image Intensity Value at Mouse Click
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.Timval,'position',pos);
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.imval,'position',pos);
% Viewpoint Position at Mouse Click
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.Timpos,'position',pos);
x = x + w + 0.005;
y = y - 0.008;
w = info_pos(3)*0.5;
h = inputline_space*0.9;
pos = [x y w h];
set(handles.impos,'position',pos);
% Origin Position
%
x = info_pos(1);
y = y + inputline_space*1.2;
w = info_pos(3)*0.5;
h = inputline_space*0.6;
pos = [x y w h];
set(handles.Torigin,'position',pos);
x = x + w;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.origin,'position',pos);
if 0
% Axes Unit
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.5;
pos = [x y w h];
set(handles.Tcoord,'position',pos);
x = x + w + 0.005;
w = info_pos(3)*0.5 - 0.005;
pos = [x y w h];
set(handles.coord,'position',pos);
end
% Crosshair
%
x = info_pos(1);
y = y + inputline_space;
w = info_pos(3)*0.4;
pos = [x y w h];
set(handles.Txhair,'position',pos);
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.2;
h = inputline_space*0.7;
pos = [x y w h];
set(handles.xhair_color,'position',pos);
x = info_pos(1) + info_pos(3)*0.7;
w = info_pos(3)*0.3;
pos = [x y w h];
set(handles.xhair,'position',pos);
% Histogram & Color
%
x = info_pos(1);
w = info_pos(3)*0.45;
h = inputline_space * 1.5;
pos = [x, y+inputline_space*0.9, w, h];
set(handles.hist_frame,'position',pos);
set(handles.coord_frame,'position',pos);
x = info_pos(1) + info_pos(3)*0.475;
w = info_pos(3)*0.525;
h = inputline_space * 1.5;
pos = [x, y+inputline_space*0.9, w, h];
set(handles.color_frame,'position',pos);
x = info_pos(1) + info_pos(3)*0.025;
y = y + inputline_space*1.2;
w = info_pos(3)*0.2;
h = inputline_space*0.7;
pos = [x y w h];
set(handles.hist_eq,'position',pos);
x = x + w;
w = info_pos(3)*0.2;
pos = [x y w h];
set(handles.hist_plot,'position',pos);
x = info_pos(1) + info_pos(3)*0.025;
w = info_pos(3)*0.4;
pos = [x y w h];
set(handles.coord,'position',pos);
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.2;
pos = [x y w h];
set(handles.neg_color,'position',pos);
x = info_pos(1) + info_pos(3)*0.7;
w = info_pos(3)*0.275;
pos = [x y w h];
set(handles.colorindex,'position',pos);
x = info_pos(1) + info_pos(3)*0.1;
y = y + inputline_space;
w = info_pos(3)*0.28;
h = inputline_space*0.6;
pos = [x y w h];
set(handles.Thist,'position',pos);
set(handles.Tcoord,'position',pos);
x = info_pos(1) + info_pos(3)*0.60;
w = info_pos(3)*0.28;
pos = [x y w h];
set(handles.Tcolor,'position',pos);
% Contrast Frame
%
x = info_pos(1);
w = info_pos(3)*0.45;
h = inputline_space * 2;
pos = [x, y+inputline_space*0.8, w, h];
set(handles.contrast_frame,'position',pos);
% Brightness Frame
%
x = info_pos(1) + info_pos(3)*0.475;
w = info_pos(3)*0.525;
pos = [x, y+inputline_space*0.8, w, h];
set(handles.brightness_frame,'position',pos);
% Contrast
%
x = info_pos(1) + info_pos(3)*0.025;
y = y + inputline_space;
w = info_pos(3)*0.4;
h = inputline_space*0.6;
pos = [x y w h];
set(handles.contrast,'position',pos);
% Brightness
%
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.475;
pos = [x y w h];
set(handles.brightness,'position',pos);
% Contrast text/def
%
x = info_pos(1) + info_pos(3)*0.025;
y = y + inputline_space;
w = info_pos(3)*0.22;
pos = [x y w h];
set(handles.Tcontrast,'position',pos);
x = x + w;
w = info_pos(3)*0.18;
pos = [x y w h];
set(handles.contrast_def,'position',pos);
% Brightness text/def
%
x = info_pos(1) + info_pos(3)*0.5;
w = info_pos(3)*0.295;
pos = [x y w h];
set(handles.Tbrightness,'position',pos);
x = x + w;
w = info_pos(3)*0.18;
pos = [x y w h];
set(handles.brightness_def,'position',pos);
return; % update_usestretch
%----------------------------------------------------------------
function update_useinterp(fig, useinterp)
if isempty(useinterp)
return;
end
nii_menu = getappdata(fig, 'nii_menu');
if ~isempty(nii_menu)
if get(nii_menu.Minterp,'user')
set(nii_menu.Minterp,'Userdata',0,'Label','Interp off');
else
set(nii_menu.Minterp,'Userdata',1,'Label','Interp on');
end
end
nii_view = getappdata(fig, 'nii_view');
nii_view.useinterp = useinterp;
if ~isempty(nii_view.handles.axial_image)
if strcmpi(get(nii_view.handles.axial_image,'cdatamapping'), 'direct')
useimagesc = 0;
else
useimagesc = 1;
end
elseif ~isempty(nii_view.handles.coronal_image)
if strcmpi(get(nii_view.handles.coronal_image,'cdatamapping'), 'direct')
useimagesc = 0;
else
useimagesc = 1;
end
else
if strcmpi(get(nii_view.handles.sagittal_image,'cdatamapping'), 'direct')
useimagesc = 0;
else
useimagesc = 1;
end
end
if ~isempty(nii_view.handles.axial_image)
img_slice = get(nii_view.handles.axial_image, 'cdata');
delete(nii_view.handles.axial_image);
axes(nii_view.handles.axial_axes);
clim = get(gca,'clim');
if useinterp
if useimagesc
nii_view.handles.axial_image = surface(zeros(size(img_slice)),double(img_slice),'edgecolor','none','facecolor','interp');
else
nii_view.handles.axial_image = surface(zeros(size(img_slice)),double(img_slice),'cdatamapping','direct','edgecolor','none','facecolor','interp');
end
else
if useimagesc
nii_view.handles.axial_image = imagesc('cdata',img_slice);
else
nii_view.handles.axial_image = image('cdata',img_slice);
end
end
set(gca,'clim',clim);
order = get(gca,'child');
order(find(order == nii_view.handles.axial_image)) = [];
order = [order; nii_view.handles.axial_image];
if isfield(nii_view.handles,'axial_bg') & ~isempty(nii_view.handles.axial_bg)
order(find(order == nii_view.handles.axial_bg)) = [];
order = [order; nii_view.handles.axial_bg];
end
set(gca, 'child', order);
if ~useinterp
if isfield(nii_view.handles,'axial_bg') & ~isempty(nii_view.handles.axial_bg)
delete(nii_view.handles.axial_bg);
nii_view.handles.axial_bg = [];
end
end
set(nii_view.handles.axial_image,'buttondown','view_nii(''axial_image'');');
end
if ~isempty(nii_view.handles.coronal_image)
img_slice = get(nii_view.handles.coronal_image, 'cdata');
delete(nii_view.handles.coronal_image);
axes(nii_view.handles.coronal_axes);
clim = get(gca,'clim');
if useinterp
if useimagesc
nii_view.handles.coronal_image = surface(zeros(size(img_slice)),double(img_slice),'edgecolor','none','facecolor','interp');
else
nii_view.handles.coronal_image = surface(zeros(size(img_slice)),double(img_slice),'cdatamapping','direct','edgecolor','none','facecolor','interp');
end
else
if useimagesc
nii_view.handles.coronal_image = imagesc('cdata',img_slice);
else
nii_view.handles.coronal_image = image('cdata',img_slice);
end
end
set(gca,'clim',clim);
order = get(gca,'child');
order(find(order == nii_view.handles.coronal_image)) = [];
order = [order; nii_view.handles.coronal_image];
if isfield(nii_view.handles,'coronal_bg') & ~isempty(nii_view.handles.coronal_bg)
order(find(order == nii_view.handles.coronal_bg)) = [];
order = [order; nii_view.handles.coronal_bg];
end
set(gca, 'child', order);
if ~useinterp
if isfield(nii_view.handles,'coronal_bg') & ~isempty(nii_view.handles.coronal_bg)
delete(nii_view.handles.coronal_bg);
nii_view.handles.coronal_bg = [];
end
end
set(nii_view.handles.coronal_image,'buttondown','view_nii(''coronal_image'');');
end
if ~isempty(nii_view.handles.sagittal_image)
img_slice = get(nii_view.handles.sagittal_image, 'cdata');
delete(nii_view.handles.sagittal_image);
axes(nii_view.handles.sagittal_axes);
clim = get(gca,'clim');
if useinterp
if useimagesc
nii_view.handles.sagittal_image = surface(zeros(size(img_slice)),double(img_slice),'edgecolor','none','facecolor','interp');
else
nii_view.handles.sagittal_image = surface(zeros(size(img_slice)),double(img_slice),'cdatamapping','direct','edgecolor','none','facecolor','interp');
end
else
if useimagesc
nii_view.handles.sagittal_image = imagesc('cdata',img_slice);
else
nii_view.handles.sagittal_image = image('cdata',img_slice);
end
end
set(gca,'clim',clim);
order = get(gca,'child');
order(find(order == nii_view.handles.sagittal_image)) = [];
order = [order; nii_view.handles.sagittal_image];
if isfield(nii_view.handles,'sagittal_bg') & ~isempty(nii_view.handles.sagittal_bg)
order(find(order == nii_view.handles.sagittal_bg)) = [];
order = [order; nii_view.handles.sagittal_bg];
end
set(gca, 'child', order);
if ~useinterp
if isfield(nii_view.handles,'sagittal_bg') & ~isempty(nii_view.handles.sagittal_bg)
delete(nii_view.handles.sagittal_bg);
nii_view.handles.sagittal_bg = [];
end
end
set(nii_view.handles.sagittal_image,'buttondown','view_nii(''sagittal_image'');');
end
if ~useinterp
nii_view.bgimg = [];
end
set_coordinates(nii_view,useinterp);
setappdata(fig, 'nii_view', nii_view);
return; % update_useinterp
%----------------------------------------------------------------
function update_useimagesc(fig, useimagesc)
if isempty(useimagesc)
return;
end
if useimagesc
v='scaled';
else
v='direct';
end
nii_view = getappdata(fig,'nii_view');
handles = nii_view.handles;
if isfield(handles,'cbar_image') & ishandle(handles.cbar_image)
% set(handles.cbar_image,'cdatamapping',v);
end
set(handles.axial_image,'cdatamapping',v);
set(handles.coronal_image,'cdatamapping',v);
set(handles.sagittal_image,'cdatamapping',v);
return; % update_useimagesc
%----------------------------------------------------------------
function update_shape(fig, area, usecolorbar, usestretch, useimagesc)
nii_view = getappdata(fig,'nii_view');
if isempty(usestretch) % no change, get usestretch
stretchchange = 0;
usestretch = nii_view.usestretch;
else % change, set usestretch
stretchchange = 1;
nii_view.usestretch = usestretch;
end
if isempty(area) % no change, get area
areachange = 0;
area = nii_view.area;
elseif ~isempty(nii_view.cbar_area) % change, set area & cbar_area
areachange = 1;
cbar_area = area;
cbar_area(1) = area(1) + area(3)*0.93;
cbar_area(3) = area(3)*0.04;
area(3) = area(3)*0.9; % 90% used for main axes
[cbar_axes cbarminmax_axes] = create_cbar_axes(fig, cbar_area);
nii_view.area = area;
nii_view.cbar_area = cbar_area;
else % change, set area only
areachange = 1;
nii_view.area = area;
end
% Add colorbar
%
if ~isempty(usecolorbar) & usecolorbar & isempty(nii_view.cbar_area)
colorbarchange = 1;
cbar_area = area;
cbar_area(1) = area(1) + area(3)*0.93;
cbar_area(3) = area(3)*0.04;
area(3) = area(3)*0.9; % 90% used for main axes
% create axes for colorbar
%
[cbar_axes cbarminmax_axes] = create_cbar_axes(fig, cbar_area);
nii_view.area = area;
nii_view.cbar_area = cbar_area;
% useimagesc follows axial image
%
if isempty(useimagesc)
if strcmpi(get(nii_view.handles.axial_image,'cdatamap'),'scaled')
useimagesc = 1;
else
useimagesc = 0;
end
end
if isfield(nii_view, 'highcolor') & ~isempty(highcolor)
num_highcolor = size(nii_view.highcolor,1);
else
num_highcolor = 0;
end
if isfield(nii_view, 'colorlevel') & ~isempty(nii_view.colorlevel)
colorlevel = nii_view.colorlevel;
else
colorlevel = 256 - num_highcolor;
end
if isfield(nii_view, 'color_map')
color_map = nii_view.color_map;
else
color_map = [];
end
if isfield(nii_view, 'highcolor')
highcolor = nii_view.highcolor;
else
highcolor = [];
end
% plot colorbar
%
if 0
if isempty(color_map)
level = colorlevel + num_highcolor;
else
level = size([color_map; highcolor], 1);
end
end
if isempty(color_map)
level = colorlevel;
else
level = size([color_map], 1);
end
cbar_image = [1:level]';
niiclass = class(nii_view.nii.img);
h1 = plot_cbar(fig, cbar_axes, cbarminmax_axes, nii_view.cbarminmax, ...
level, nii_view.handles, useimagesc, nii_view.colorindex, ...
color_map, colorlevel, highcolor, niiclass, nii_view.numscan);
nii_view.handles.cbar_image = h1;
nii_view.handles.cbar_axes = cbar_axes;
nii_view.handles.cbarminmax_axes = cbar_axes;
% remove colorbar
%
elseif ~isempty(usecolorbar) & ~usecolorbar & ~isempty(nii_view.cbar_area)
colorbarchange = 1;
area(3) = area(3) / 0.9;
nii_view.area = area;
nii_view.cbar_area = [];
nii_view.handles = rmfield(nii_view.handles,'cbar_image');
delete(nii_view.handles.cbarminmax_axes);
nii_view.handles = rmfield(nii_view.handles,'cbarminmax_axes');
delete(nii_view.handles.cbar_axes);
nii_view.handles = rmfield(nii_view.handles,'cbar_axes');
else
colorbarchange = 0;
end
if colorbarchange | stretchchange | areachange
setappdata(fig,'nii_view',nii_view);
update_usestretch(fig, usestretch);
end
return; % update_shape
%----------------------------------------------------------------
function update_unit(fig, setunit)
if isempty(setunit)
return;
end
if strcmpi(setunit,'mm') | strcmpi(setunit,'millimeter') | strcmpi(setunit,'mni')
v = 2;
% elseif strcmpi(setunit,'tal') | strcmpi(setunit,'talairach')
% v = 3;
elseif strcmpi(setunit,'vox') | strcmpi(setunit,'voxel')
v = 1;
else
v = 1;
end
nii_view = getappdata(fig,'nii_view');
set(nii_view.handles.coord, 'value', v);
set_image_value(nii_view);
return; % update_unit
%----------------------------------------------------------------
function update_viewpoint(fig, setviewpoint)
if isempty(setviewpoint)
return;
end
nii_view = getappdata(fig,'nii_view');
if length(setviewpoint) ~= 3
error('Viewpoint position should contain [x y z]');
end
set(nii_view.handles.impos,'string',num2str(setviewpoint));
opt.command = 'impos_edit';
view_nii(fig, opt);
set(nii_view.handles.axial_axes,'selected','on');
set(nii_view.handles.axial_axes,'selected','off');
set(nii_view.handles.coronal_axes,'selected','on');
set(nii_view.handles.coronal_axes,'selected','off');
set(nii_view.handles.sagittal_axes,'selected','on');
set(nii_view.handles.sagittal_axes,'selected','off');
return; % update_viewpoint
%----------------------------------------------------------------
function update_scanid(fig, setscanid)
if isempty(setscanid)
return;
end
nii_view = getappdata(fig,'nii_view');
if setscanid < 1
setscanid = 1;
end
if setscanid > nii_view.numscan
setscanid = nii_view.numscan;
end
set(nii_view.handles.contrast_def,'string',num2str(setscanid));
set(nii_view.handles.contrast,'value',setscanid);
opt.command = 'updateimg';
opt.setscanid = setscanid;
view_nii(fig, nii_view.nii.img, opt);
return; % update_scanid
%----------------------------------------------------------------
function update_crosshaircolor(fig, new_color)
if isempty(new_color)
return;
end
nii_view = getappdata(fig,'nii_view');
xhair_color = nii_view.handles.xhair_color;
set(xhair_color,'user',new_color);
set(nii_view.axi_xhair.lx,'color',new_color);
set(nii_view.axi_xhair.ly,'color',new_color);
set(nii_view.cor_xhair.lx,'color',new_color);
set(nii_view.cor_xhair.ly,'color',new_color);
set(nii_view.sag_xhair.lx,'color',new_color);
set(nii_view.sag_xhair.ly,'color',new_color);
return; % update_crosshaircolor
%----------------------------------------------------------------
function update_colorindex(fig, colorindex)
if isempty(colorindex)
return;
end
nii_view = getappdata(fig,'nii_view');
nii_view.colorindex = colorindex;
setappdata(fig, 'nii_view', nii_view);
set(nii_view.handles.colorindex,'value',colorindex);
opt.command = 'color';
view_nii(fig, opt);
return; % update_colorindex
%----------------------------------------------------------------
function redraw_cbar(fig, colorlevel, color_map, highcolor)
nii_view = getappdata(fig,'nii_view');
if isempty(nii_view.cbar_area)
return;
end
colorindex = nii_view.colorindex;
if isempty(highcolor)
num_highcolor = 0;
else
num_highcolor = size(highcolor,1);
end
if isempty(colorlevel)
colorlevel=256;
end
if colorindex == 1
colorlevel = size(color_map, 1);
end
% level = colorlevel + num_highcolor;
level = colorlevel;
cbar_image = [1:level]';
cbar_area = nii_view.cbar_area;
% useimagesc follows axial image
%
if strcmpi(get(nii_view.handles.axial_image,'cdatamap'),'scaled')
useimagesc = 1;
else
useimagesc = 0;
end
niiclass = class(nii_view.nii.img);
delete(nii_view.handles.cbar_image);
delete(nii_view.handles.cbar_axes);
delete(nii_view.handles.cbarminmax_axes);
[nii_view.handles.cbar_axes nii_view.handles.cbarminmax_axes] = ...
create_cbar_axes(fig, cbar_area, []);
nii_view.handles.cbar_image = plot_cbar(fig, ...
nii_view.handles.cbar_axes, nii_view.handles.cbarminmax_axes, ...
nii_view.cbarminmax, level, nii_view.handles, useimagesc, ...
colorindex, color_map, colorlevel, highcolor, niiclass, ...
nii_view.numscan, []);
setappdata(fig, 'nii_view', nii_view);
return; % redraw_cbar
%----------------------------------------------------------------
function update_buttondown(fig, setbuttondown)
if isempty(setbuttondown)
return;
end
nii_view = getappdata(fig,'nii_view');
nii_view.buttondown = setbuttondown;
setappdata(fig, 'nii_view', nii_view);
return; % update_buttondown
%----------------------------------------------------------------
function update_cbarminmax(fig, cbarminmax)
if isempty(cbarminmax)
return;
end
nii_view = getappdata(fig, 'nii_view');
if ~isfield(nii_view.handles, 'cbarminmax_axes')
return;
end
nii_view.cbarminmax = cbarminmax;
setappdata(fig, 'nii_view', nii_view);
axes(nii_view.handles.cbarminmax_axes);
plot([0 0], cbarminmax, 'w');
axis tight;
set(nii_view.handles.cbarminmax_axes,'YDir','normal', ...
'XLimMode','manual','YLimMode','manual','YColor',[0 0 0], ...
'XColor',[0 0 0],'xtick',[],'YAxisLocation','right');
ylim = get(nii_view.handles.cbar_axes,'ylim');
ylimb = get(nii_view.handles.cbarminmax_axes,'ylim');
ytickb = get(nii_view.handles.cbarminmax_axes,'ytick');
ytick=(ylim(2)-ylim(1))*(ytickb-ylimb(1))/(ylimb(2)-ylimb(1))+ylim(1);
axes(nii_view.handles.cbar_axes);
set(nii_view.handles.cbar_axes,'YDir','normal','XLimMode','manual', ...
'YLimMode','manual','YColor',[0 0 0],'XColor',[0 0 0],'xtick',[], ...
'YAxisLocation','right','ylim',ylim,'ytick',ytick,'yticklabel','');
return; % update_cbarminmax
%----------------------------------------------------------------
function update_highcolor(fig, highcolor, colorlevel)
nii_view = getappdata(fig,'nii_view');
if ischar(highcolor) & (isempty(colorlevel) | nii_view.colorindex == 1)
return;
end
if ~ischar(highcolor)
nii_view.highcolor = highcolor;
if isempty(highcolor)
nii_view = rmfield(nii_view, 'highcolor');
end
else
highcolor = [];
end
if isempty(colorlevel) | nii_view.colorindex == 1
nii_view.colorlevel = nii_view.colorlevel - size(highcolor,1);
else
nii_view.colorlevel = colorlevel;
end
setappdata(fig, 'nii_view', nii_view);
if isfield(nii_view,'color_map')
color_map = nii_view.color_map;
else
color_map = [];
end
redraw_cbar(fig, nii_view.colorlevel, color_map, highcolor);
change_colormap(fig);
return; % update_highcolor
%----------------------------------------------------------------
function update_colormap(fig, color_map)
if ischar(color_map)
return;
end
nii_view = getappdata(fig,'nii_view');
nii = nii_view.nii;
minvalue = nii_view.minvalue;
if isempty(color_map)
if minvalue < 0
colorindex = 2;
else
colorindex = 3;
end
nii_view = rmfield(nii_view, 'color_map');
setappdata(fig,'nii_view',nii_view);
update_colorindex(fig, colorindex);
return;
else
colorindex = 1;
nii_view.color_map = color_map;
nii_view.colorindex = colorindex;
setappdata(fig,'nii_view',nii_view);
set(nii_view.handles.colorindex,'value',colorindex);
end
colorlevel = nii_view.colorlevel;
if isfield(nii_view, 'highcolor')
highcolor = nii_view.highcolor;
else
highcolor = [];
end
redraw_cbar(fig, colorlevel, color_map, highcolor);
change_colormap(fig);
opt.enablecontrast = 0;
update_enable(fig, opt);
return; % update_colormap
%----------------------------------------------------------------
function status = get_status(h);
nii_view = getappdata(h,'nii_view');
status.fig = h;
status.area = nii_view.area;
if isempty(nii_view.cbar_area)
status.usecolorbar = 0;
else
status.usecolorbar = 1;
width = status.area(3) / 0.9;
status.area(3) = width;
end
if strcmpi(get(nii_view.handles.imval,'visible'), 'on')
status.usepanel = 1;
else
status.usepanel = 0;
end
if get(nii_view.handles.xhair,'value') == 1
status.usecrosshair = 1;
else
status.usecrosshair = 0;
end
status.usestretch = nii_view.usestretch;
if strcmpi(get(nii_view.handles.axial_image,'cdatamapping'), 'direct')
status.useimagesc = 0;
else
status.useimagesc = 1;
end
status.useinterp = nii_view.useinterp;
if get(nii_view.handles.coord,'value') == 1
status.unit = 'vox';
elseif get(nii_view.handles.coord,'value') == 2
status.unit = 'mm';
elseif get(nii_view.handles.coord,'value') == 3
status.unit = 'tal';
end
status.viewpoint = get(nii_view.handles.impos,'value');
status.scanid = nii_view.scanid;
status.intensity = get(nii_view.handles.imval,'value');
status.colorindex = get(nii_view.handles.colorindex,'value');
if isfield(nii_view,'color_map')
status.colormap = nii_view.color_map;
else
status.colormap = [];
end
status.colorlevel = nii_view.colorlevel;
if isfield(nii_view,'highcolor')
status.highcolor = nii_view.highcolor;
else
status.highcolor = [];
end
status.cbarminmax = nii_view.cbarminmax;
status.buttondown = nii_view.buttondown;
return; % get_status
%----------------------------------------------------------------
function [custom_color_map, colorindex] ...
= change_colormap(fig, nii, colorindex, cbarminmax)
custom_color_map = [];
if ~exist('nii', 'var')
nii_view = getappdata(fig,'nii_view');
else
nii_view = nii;
end
if ~exist('colorindex', 'var')
colorindex = get(nii_view.handles.colorindex,'value');
end
if ~exist('cbarminmax', 'var')
cbarminmax = nii_view.cbarminmax;
end
if isfield(nii_view, 'highcolor') & ~isempty(nii_view.highcolor)
highcolor = nii_view.highcolor;
num_highcolor = size(highcolor,1);
else
highcolor = [];
num_highcolor = 0;
end
% if isfield(nii_view, 'colorlevel') & ~isempty(nii_view.colorlevel)
if nii_view.colorlevel < 256
num_color = nii_view.colorlevel;
else
num_color = 256 - num_highcolor;
end
contrast = [];
if colorindex == 3 % for gray
if nii_view.numscan > 1
contrast = 1;
else
contrast = (num_color-1)*(get(nii_view.handles.contrast,'value')-1)/255+1;
contrast = floor(contrast);
end
elseif colorindex == 2 % for bipolar
if nii_view.numscan > 1
contrast = 128;
else
contrast = get(nii_view.handles.contrast,'value');
end
end
if isfield(nii_view,'color_map') & ~isempty(nii_view.color_map)
color_map = nii_view.color_map;
custom_color_map = color_map;
elseif colorindex == 1
[f p] = uigetfile('*.txt', 'Input colormap text file');
if p==0
colorindex = nii_view.colorindex;
set(nii_view.handles.colorindex,'value',colorindex);
return;
end;
try
custom_color_map = load(fullfile(p,f));
loadfail = 0;
catch
loadfail = 1;
end
if loadfail | isempty(custom_color_map) | size(custom_color_map,2)~=3 ...
| min(custom_color_map(:)) < 0 | max(custom_color_map(:)) > 1
msg = 'Colormap should be a Mx3 matrix with value between 0 and 1';
msgbox(msg,'Error in colormap file');
colorindex = nii_view.colorindex;
set(nii_view.handles.colorindex,'value',colorindex);
return;
end
color_map = custom_color_map;
nii_view.color_map = color_map;
end
switch colorindex
case {2}
color_map = bipolar(num_color, cbarminmax(1), cbarminmax(2), contrast);
case {3}
color_map = gray(num_color - contrast + 1);
case {4}
color_map = jet(num_color);
case {5}
color_map = cool(num_color);
case {6}
color_map = bone(num_color);
case {7}
color_map = hot(num_color);
case {8}
color_map = copper(num_color);
case {9}
color_map = pink(num_color);
end
nii_view.colorindex = colorindex;
if ~exist('nii', 'var')
setappdata(fig,'nii_view',nii_view);
end
if colorindex == 3
color_map = [zeros(contrast,3); color_map(2:end,:)];
end
if get(nii_view.handles.neg_color,'value') & isempty(highcolor)
color_map = flipud(color_map);
elseif get(nii_view.handles.neg_color,'value') & ~isempty(highcolor)
highcolor = flipud(highcolor);
end
brightness = get(nii_view.handles.brightness,'value');
color_map = brighten(color_map, brightness);
color_map = [color_map; highcolor];
set(fig, 'colormap', color_map);
return; % change_colormap
%----------------------------------------------------------------
function move_cursor(fig)
nii_view = getappdata(fig, 'nii_view');
if isempty(nii_view)
return;
end
axi = get(nii_view.handles.axial_axes, 'pos');
cor = get(nii_view.handles.coronal_axes, 'pos');
sag = get(nii_view.handles.sagittal_axes, 'pos');
curr = get(fig, 'currentpoint');
if curr(1) >= axi(1) & curr(1) <= axi(1)+axi(3) & ...
curr(2) >= axi(2) & curr(2) <= axi(2)+axi(4)
curr = get(nii_view.handles.axial_axes, 'current');
sag = curr(1,1);
cor = curr(1,2);
axi = nii_view.slices.axi;
elseif curr(1) >= cor(1) & curr(1) <= cor(1)+cor(3) & ...
curr(2) >= cor(2) & curr(2) <= cor(2)+cor(4)
curr = get(nii_view.handles.coronal_axes, 'current');
sag = curr(1,1);
cor = nii_view.slices.cor;
axi = curr(1,2);
elseif curr(1) >= sag(1) & curr(1) <= sag(1)+sag(3) & ...
curr(2) >= sag(2) & curr(2) <= sag(2)+sag(4)
curr = get(nii_view.handles.sagittal_axes, 'current');
sag = nii_view.slices.sag;
cor = curr(1,1);
axi = curr(1,2);
else
set(nii_view.handles.imvalcur,'String',' ');
set(nii_view.handles.imposcur,'String',' ');
return;
end
sag = round(sag);
cor = round(cor);
axi = round(axi);
if sag < 1
sag = 1;
elseif sag > nii_view.dims(1)
sag = nii_view.dims(1);
end
if cor < 1
cor = 1;
elseif cor > nii_view.dims(2)
cor = nii_view.dims(2);
end
if axi < 1
axi = 1;
elseif axi > nii_view.dims(3)
axi = nii_view.dims(3);
end
if 0 % isfield(nii_view, 'disp')
img = nii_view.disp;
else
img = nii_view.nii.img;
end
if nii_view.nii.hdr.dime.datatype == 128
imgvalue = [double(img(sag,cor,axi,1,nii_view.scanid)) double(img(sag,cor,axi,2,nii_view.scanid)) double(img(sag,cor,axi,3,nii_view.scanid))];
set(nii_view.handles.imvalcur,'String',sprintf('%7.4g %7.4g %7.4g',imgvalue));
elseif nii_view.nii.hdr.dime.datatype == 511
R = double(img(sag,cor,axi,1,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
G = double(img(sag,cor,axi,2,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
B = double(img(sag,cor,axi,3,nii_view.scanid)) * (nii_view.nii.hdr.dime.glmax - ...
nii_view.nii.hdr.dime.glmin) + nii_view.nii.hdr.dime.glmin;
imgvalue = [R G B];
set(nii_view.handles.imvalcur,'String',sprintf('%7.4g %7.4g %7.4g',imgvalue));
else
imgvalue = double(img(sag,cor,axi,nii_view.scanid));
if isnan(imgvalue) | imgvalue > nii_view.cbarminmax(2)
imgvalue = 0;
end
set(nii_view.handles.imvalcur,'String',sprintf('%.6g',imgvalue));
end
nii_view.slices.sag = sag;
nii_view.slices.cor = cor;
nii_view.slices.axi = axi;
nii_view = update_imgXYZ(nii_view);
if get(nii_view.handles.coord,'value') == 1,
sag = nii_view.imgXYZ.vox(1);
cor = nii_view.imgXYZ.vox(2);
axi = nii_view.imgXYZ.vox(3);
elseif get(nii_view.handles.coord,'value') == 2,
sag = nii_view.imgXYZ.mm(1);
cor = nii_view.imgXYZ.mm(2);
axi = nii_view.imgXYZ.mm(3);
elseif get(nii_view.handles.coord,'value') == 3,
sag = nii_view.imgXYZ.tal(1);
cor = nii_view.imgXYZ.tal(2);
axi = nii_view.imgXYZ.tal(3);
end
if get(nii_view.handles.coord,'value') == 1,
string = sprintf('%7.0f %7.0f %7.0f',sag,cor,axi);
else
string = sprintf('%7.1f %7.1f %7.1f',sag,cor,axi);
end;
set(nii_view.handles.imposcur,'String',string);
return; % move_cursor
%----------------------------------------------------------------
function change_scan(hdl_str)
fig = gcbf;
nii_view = getappdata(fig,'nii_view');
if strcmpi(hdl_str, 'edit_change_scan') % edit
hdl = nii_view.handles.contrast_def;
setscanid = round(str2num(get(hdl, 'string')));
else % slider
hdl = nii_view.handles.contrast;
setscanid = round(get(hdl, 'value'));
end
update_scanid(fig, setscanid);
return; % change_scan
%----------------------------------------------------------------
function val = scale_in(val, minval, maxval, range)
% scale value into range
%
val = range*(double(val)-double(minval))/(double(maxval)-double(minval))+1;
return; % scale_in
%----------------------------------------------------------------
function val = scale_out(val, minval, maxval, range)
% according to [minval maxval] and range of color levels (e.g. 199)
% scale val back from any thing between 1~256 to a small number that
% is corresonding to [minval maxval].
%
val = (double(val)-1)*(double(maxval)-double(minval))/range+double(minval);
return; % scale_out
|
github
|
sunhongfu/scripts-master
|
mat_into_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/mat_into_hdr.m
| 2,691 |
utf_8
|
847d96698f45f7c5e7decbb3a0c3187f
|
%MAT_INTO_HDR The old versions of SPM (any version before SPM5) store
% an affine matrix of the SPM Reoriented image into a matlab file
% (.mat extension). The file name of this SPM matlab file is the
% same as the SPM Reoriented image file (.img/.hdr extension).
%
% This program will convert the ANALYZE 7.5 SPM Reoriented image
% file into NIfTI format, and integrate the affine matrix in the
% SPM matlab file into its header file (.hdr extension).
%
% WARNING: Before you run this program, please save the header
% file (.hdr extension) into another file name or into another
% folder location, because all header files (.hdr extension)
% will be overwritten after they are converted into NIfTI
% format.
%
% Usage: mat_into_hdr(filename);
%
% filename: file name(s) with .hdr or .mat file extension, like:
% '*.hdr', or '*.mat', or a single .hdr or .mat file.
% e.g. mat_into_hdr('T1.hdr')
% mat_into_hdr('*.mat')
%
% - Jimmy Shen ([email protected])
%
%-------------------------------------------------------------------------
function mat_into_hdr(files)
pn = fileparts(files);
file_lst = dir(files);
file_lst = {file_lst.name};
file1 = file_lst{1};
[p n e]= fileparts(file1);
for i=1:length(file_lst)
[p n e]= fileparts(file_lst{i});
disp(['working on file ', num2str(i) ,' of ', num2str(length(file_lst)), ': ', n,e]);
process=1;
if isequal(e,'.hdr')
mat=fullfile(pn, [n,'.mat']);
hdr=fullfile(pn, file_lst{i});
if ~exist(mat,'file')
warning(['Cannot find file "',mat , '". File "', n, e, '" will not be processed.']);
process=0;
end
elseif isequal(e,'.mat')
hdr=fullfile(pn, [n,'.hdr']);
mat=fullfile(pn, file_lst{i});
if ~exist(hdr,'file')
warning(['Can not find file "',hdr , '". File "', n, e, '" will not be processed.']);
process=0;
end
else
warning(['Input file must have .mat or .hdr extension. File "', n, e, '" will not be processed.']);
process=0;
end
if process
load(mat);
R=M(1:3,1:3);
T=M(1:3,4);
T=R*ones(3,1)+T;
M(1:3,4)=T;
[h filetype fileprefix machine]=load_nii_hdr(hdr);
h.hist.qform_code=0;
h.hist.sform_code=1;
h.hist.srow_x=M(1,:);
h.hist.srow_y=M(2,:);
h.hist.srow_z=M(3,:);
h.hist.magic='ni1';
fid = fopen(hdr,'w',machine);
save_nii_hdr(h,fid);
fclose(fid);
end
end
return; % mat_into_hdr
|
github
|
sunhongfu/scripts-master
|
xform_nii.m
|
.m
|
scripts-master/cs-phase/_src/_nii/xform_nii.m
| 18,628 |
utf_8
|
e39c421e7f117cbc81c56e9d023774a3
|
% internal function
% 'xform_nii.m' is an internal function called by "load_nii.m", so
% you do not need run this program by yourself. It does simplified
% NIfTI sform/qform affine transform, and supports some of the
% affine transforms, including translation, reflection, and
% orthogonal rotation (N*90 degree).
%
% For other affine transforms, e.g. any degree rotation, shearing
% etc. you will have to use the included 'reslice_nii.m' program
% to reslice the image volume. 'reslice_nii.m' is not called by
% any other program, and you have to run 'reslice_nii.m' explicitly
% for those NIfTI files that you want to reslice them.
%
% Since 'xform_nii.m' does not involve any interpolation or any
% slice change, the original image volume is supposed to be
% untouched, although it is translated, reflected, or even
% orthogonally rotated, based on the affine matrix in the
% NIfTI header.
%
% However, the affine matrix in the header of a lot NIfTI files
% contain slightly non-orthogonal rotation. Therefore, optional
% input parameter 'tolerance' is used to allow some distortion
% in the loaded image for any non-orthogonal rotation or shearing
% of NIfTI affine matrix. If you set 'tolerance' to 0, it means
% that you do not allow any distortion. If you set 'tolerance' to
% 1, it means that you do not care any distortion. The image will
% fail to be loaded if it can not be tolerated. The tolerance will
% be set to 0.1 (10%), if it is default or empty.
%
% Because 'reslice_nii.m' has to perform 3D interpolation, it can
% be slow depending on image size and affine matrix in the header.
%
% After you perform the affine transform, the 'nii' structure
% generated from 'xform_nii.m' or new NIfTI file created from
% 'reslice_nii.m' will be in RAS orientation, i.e. X axis from
% Left to Right, Y axis from Posterior to Anterior, and Z axis
% from Inferior to Superior.
%
% NOTE: This function should be called immediately after load_nii.
%
% Usage: [ nii ] = xform_nii(nii, [tolerance], [preferredForm])
%
% nii - NIFTI structure (returned from load_nii)
%
% tolerance (optional) - distortion allowed for non-orthogonal rotation
% or shearing in NIfTI affine matrix. It will be set to 0.1 (10%),
% if it is default or empty.
%
% preferredForm (optional) - selects which transformation from voxels
% to RAS coordinates; values are s,q,S,Q. Lower case s,q indicate
% "prefer sform or qform, but use others if preferred not present".
% Upper case indicate the program is forced to use the specificied
% tranform or fail loading. 'preferredForm' will be 's', if it is
% default or empty. - Jeff Gunter
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function nii = xform_nii(nii, tolerance, preferredForm)
% save a copy of the header as it was loaded. This is the
% header before any sform, qform manipulation is done.
%
nii.original.hdr = nii.hdr;
if ~exist('tolerance','var') | isempty(tolerance)
tolerance = 0.1;
elseif(tolerance<=0)
tolerance = eps;
end
if ~exist('preferredForm','var') | isempty(preferredForm)
preferredForm= 's'; % Jeff
end
% if scl_slope field is nonzero, then each voxel value in the
% dataset should be scaled as: y = scl_slope * x + scl_inter
% I bring it here because hdr will be modified by change_hdr.
%
if nii.hdr.dime.scl_slope ~= 0 & ...
ismember(nii.hdr.dime.datatype, [2,4,8,16,64,256,512,768]) & ...
(nii.hdr.dime.scl_slope ~= 1 | nii.hdr.dime.scl_inter ~= 0)
nii.img = ...
nii.hdr.dime.scl_slope * double(nii.img) + nii.hdr.dime.scl_inter;
if nii.hdr.dime.datatype == 64
nii.hdr.dime.datatype = 64;
nii.hdr.dime.bitpix = 64;
else
nii.img = single(nii.img);
nii.hdr.dime.datatype = 16;
nii.hdr.dime.bitpix = 32;
end
nii.hdr.dime.glmax = max(double(nii.img(:)));
nii.hdr.dime.glmin = min(double(nii.img(:)));
% set scale to non-use, because it is applied in xform_nii
%
nii.hdr.dime.scl_slope = 0;
end
% However, the scaling is to be ignored if datatype is DT_RGB24.
% If datatype is a complex type, then the scaling is to be applied
% to both the real and imaginary parts.
%
if nii.hdr.dime.scl_slope ~= 0 & ...
ismember(nii.hdr.dime.datatype, [32,1792])
nii.img = ...
nii.hdr.dime.scl_slope * double(nii.img) + nii.hdr.dime.scl_inter;
if nii.hdr.dime.datatype == 32
nii.img = single(nii.img);
end
nii.hdr.dime.glmax = max(double(nii.img(:)));
nii.hdr.dime.glmin = min(double(nii.img(:)));
% set scale to non-use, because it is applied in xform_nii
%
nii.hdr.dime.scl_slope = 0;
end
% There is no need for this program to transform Analyze data
%
if nii.filetype == 0 & exist([nii.fileprefix '.mat'],'file')
load([nii.fileprefix '.mat']); % old SPM affine matrix
R=M(1:3,1:3);
T=M(1:3,4);
T=R*ones(3,1)+T;
M(1:3,4)=T;
nii.hdr.hist.qform_code=0;
nii.hdr.hist.sform_code=1;
nii.hdr.hist.srow_x=M(1,:);
nii.hdr.hist.srow_y=M(2,:);
nii.hdr.hist.srow_z=M(3,:);
elseif nii.filetype == 0
nii.hdr.hist.rot_orient = [];
nii.hdr.hist.flip_orient = [];
return; % no sform/qform for Analyze format
end
hdr = nii.hdr;
[hdr,orient]=change_hdr(hdr,tolerance,preferredForm);
% flip and/or rotate image data
%
if ~isequal(orient, [1 2 3])
old_dim = hdr.dime.dim([2:4]);
% More than 1 time frame
%
if ndims(nii.img) > 3
pattern = 1:prod(old_dim);
else
pattern = [];
end
if ~isempty(pattern)
pattern = reshape(pattern, old_dim);
end
% calculate for rotation after flip
%
rot_orient = mod(orient + 2, 3) + 1;
% do flip:
%
flip_orient = orient - rot_orient;
for i = 1:3
if flip_orient(i)
if ~isempty(pattern)
pattern = flipdim(pattern, i);
else
nii.img = flipdim(nii.img, i);
end
end
end
% get index of orient (rotate inversely)
%
[tmp rot_orient] = sort(rot_orient);
new_dim = old_dim;
new_dim = new_dim(rot_orient);
hdr.dime.dim([2:4]) = new_dim;
new_pixdim = hdr.dime.pixdim([2:4]);
new_pixdim = new_pixdim(rot_orient);
hdr.dime.pixdim([2:4]) = new_pixdim;
% re-calculate originator
%
tmp = hdr.hist.originator([1:3]);
tmp = tmp(rot_orient);
flip_orient = flip_orient(rot_orient);
for i = 1:3
if flip_orient(i) & ~isequal(tmp(i), 0)
tmp(i) = new_dim(i) - tmp(i) + 1;
end
end
hdr.hist.originator([1:3]) = tmp;
hdr.hist.rot_orient = rot_orient;
hdr.hist.flip_orient = flip_orient;
% do rotation:
%
if ~isempty(pattern)
pattern = permute(pattern, rot_orient);
pattern = pattern(:);
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792 | ...
hdr.dime.datatype == 128 | hdr.dime.datatype == 511
tmp = reshape(nii.img(:,:,:,1), [prod(new_dim) hdr.dime.dim(5:8)]);
tmp = tmp(pattern, :);
nii.img(:,:,:,1) = reshape(tmp, [new_dim hdr.dime.dim(5:8)]);
tmp = reshape(nii.img(:,:,:,2), [prod(new_dim) hdr.dime.dim(5:8)]);
tmp = tmp(pattern, :);
nii.img(:,:,:,2) = reshape(tmp, [new_dim hdr.dime.dim(5:8)]);
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
tmp = reshape(nii.img(:,:,:,3), [prod(new_dim) hdr.dime.dim(5:8)]);
tmp = tmp(pattern, :);
nii.img(:,:,:,3) = reshape(tmp, [new_dim hdr.dime.dim(5:8)]);
end
else
nii.img = reshape(nii.img, [prod(new_dim) hdr.dime.dim(5:8)]);
nii.img = nii.img(pattern, :);
nii.img = reshape(nii.img, [new_dim hdr.dime.dim(5:8)]);
end
else
if hdr.dime.datatype == 32 | hdr.dime.datatype == 1792 | ...
hdr.dime.datatype == 128 | hdr.dime.datatype == 511
nii.img(:,:,:,1) = permute(nii.img(:,:,:,1), rot_orient);
nii.img(:,:,:,2) = permute(nii.img(:,:,:,2), rot_orient);
if hdr.dime.datatype == 128 | hdr.dime.datatype == 511
nii.img(:,:,:,3) = permute(nii.img(:,:,:,3), rot_orient);
end
else
nii.img = permute(nii.img, rot_orient);
end
end
else
hdr.hist.rot_orient = [];
hdr.hist.flip_orient = [];
end
nii.hdr = hdr;
return; % xform_nii
%-----------------------------------------------------------------------
function [hdr, orient] = change_hdr(hdr, tolerance, preferredForm)
orient = [1 2 3];
affine_transform = 1;
% NIFTI can have both sform and qform transform. This program
% will check sform_code prior to qform_code by default.
%
% If user specifys "preferredForm", user can then choose the
% priority. - Jeff
%
useForm=[]; % Jeff
if isequal(preferredForm,'S')
if isequal(hdr.hist.sform_code,0)
error('User requires sform, sform not set in header');
else
useForm='s';
end
end % Jeff
if isequal(preferredForm,'Q')
if isequal(hdr.hist.qform_code,0)
error('User requires qform, qform not set in header');
else
useForm='q';
end
end % Jeff
if isequal(preferredForm,'s')
if hdr.hist.sform_code > 0
useForm='s';
elseif hdr.hist.qform_code > 0
useForm='q';
end
end % Jeff
if isequal(preferredForm,'q')
if hdr.hist.qform_code > 0
useForm='q';
elseif hdr.hist.sform_code > 0
useForm='s';
end
end % Jeff
if isequal(useForm,'s')
R = [hdr.hist.srow_x(1:3)
hdr.hist.srow_y(1:3)
hdr.hist.srow_z(1:3)];
T = [hdr.hist.srow_x(4)
hdr.hist.srow_y(4)
hdr.hist.srow_z(4)];
if det(R) == 0 | ~isequal(R(find(R)), sum(R)')
hdr.hist.old_affine = [ [R;[0 0 0]] [T;1] ];
R_sort = sort(abs(R(:)));
R( find( abs(R) < tolerance*min(R_sort(end-2:end)) ) ) = 0;
hdr.hist.new_affine = [ [R;[0 0 0]] [T;1] ];
if det(R) == 0 | ~isequal(R(find(R)), sum(R)')
msg = [char(10) char(10) ' Non-orthogonal rotation or shearing '];
msg = [msg 'found inside the affine matrix' char(10)];
msg = [msg ' in this NIfTI file. You have 3 options:' char(10) char(10)];
msg = [msg ' 1. Using included ''reslice_nii.m'' program to reslice the NIfTI' char(10)];
msg = [msg ' file. I strongly recommand this, because it will not cause' char(10)];
msg = [msg ' negative effect, as long as you remember not to do slice' char(10)];
msg = [msg ' time correction after using ''reslice_nii.m''.' char(10) char(10)];
msg = [msg ' 2. Using included ''load_untouch_nii.m'' program to load image' char(10)];
msg = [msg ' without applying any affine geometric transformation or' char(10)];
msg = [msg ' voxel intensity scaling. This is only for people who want' char(10)];
msg = [msg ' to do some image processing regardless of image orientation' char(10)];
msg = [msg ' and to save data back with the same NIfTI header.' char(10) char(10)];
msg = [msg ' 3. Increasing the tolerance to allow more distortion in loaded' char(10)];
msg = [msg ' image, but I don''t suggest this.' char(10) char(10)];
msg = [msg ' To get help, please type:' char(10) char(10) ' help reslice_nii.m' char(10)];
msg = [msg ' help load_untouch_nii.m' char(10) ' help load_nii.m'];
error(msg);
end
end
elseif isequal(useForm,'q')
b = hdr.hist.quatern_b;
c = hdr.hist.quatern_c;
d = hdr.hist.quatern_d;
if 1.0-(b*b+c*c+d*d) < 0
if abs(1.0-(b*b+c*c+d*d)) < 1e-5
a = 0;
else
error('Incorrect quaternion values in this NIFTI data.');
end
else
a = sqrt(1.0-(b*b+c*c+d*d));
end
qfac = hdr.dime.pixdim(1);
if qfac==0, qfac = 1; end
i = hdr.dime.pixdim(2);
j = hdr.dime.pixdim(3);
k = qfac * hdr.dime.pixdim(4);
R = [a*a+b*b-c*c-d*d 2*b*c-2*a*d 2*b*d+2*a*c
2*b*c+2*a*d a*a+c*c-b*b-d*d 2*c*d-2*a*b
2*b*d-2*a*c 2*c*d+2*a*b a*a+d*d-c*c-b*b];
T = [hdr.hist.qoffset_x
hdr.hist.qoffset_y
hdr.hist.qoffset_z];
% qforms are expected to generate rotation matrices R which are
% det(R) = 1; we'll make sure that happens.
%
% now we make the same checks as were done above for sform data
% BUT we do it on a transform that is in terms of voxels not mm;
% after we figure out the angles and squash them to closest
% rectilinear direction. After that, the voxel sizes are then
% added.
%
% This part is modified by Jeff Gunter.
%
if det(R) == 0 | ~isequal(R(find(R)), sum(R)')
% det(R) == 0 is not a common trigger for this ---
% R(find(R)) is a list of non-zero elements in R; if that
% is straight (not oblique) then it should be the same as
% columnwise summation. Could just as well have checked the
% lengths of R(find(R)) and sum(R)' (which should be 3)
%
hdr.hist.old_affine = [ [R * diag([i j k]);[0 0 0]] [T;1] ];
R_sort = sort(abs(R(:)));
R( find( abs(R) < tolerance*min(R_sort(end-2:end)) ) ) = 0;
R = R * diag([i j k]);
hdr.hist.new_affine = [ [R;[0 0 0]] [T;1] ];
if det(R) == 0 | ~isequal(R(find(R)), sum(R)')
msg = [char(10) char(10) ' Non-orthogonal rotation or shearing '];
msg = [msg 'found inside the affine matrix' char(10)];
msg = [msg ' in this NIfTI file. You have 3 options:' char(10) char(10)];
msg = [msg ' 1. Using included ''reslice_nii.m'' program to reslice the NIfTI' char(10)];
msg = [msg ' file. I strongly recommand this, because it will not cause' char(10)];
msg = [msg ' negative effect, as long as you remember not to do slice' char(10)];
msg = [msg ' time correction after using ''reslice_nii.m''.' char(10) char(10)];
msg = [msg ' 2. Using included ''load_untouch_nii.m'' program to load image' char(10)];
msg = [msg ' without applying any affine geometric transformation or' char(10)];
msg = [msg ' voxel intensity scaling. This is only for people who want' char(10)];
msg = [msg ' to do some image processing regardless of image orientation' char(10)];
msg = [msg ' and to save data back with the same NIfTI header.' char(10) char(10)];
msg = [msg ' 3. Increasing the tolerance to allow more distortion in loaded' char(10)];
msg = [msg ' image, but I don''t suggest this.' char(10) char(10)];
msg = [msg ' To get help, please type:' char(10) char(10) ' help reslice_nii.m' char(10)];
msg = [msg ' help load_untouch_nii.m' char(10) ' help load_nii.m'];
error(msg);
end
else
R = R * diag([i j k]);
end % 1st det(R)
else
affine_transform = 0; % no sform or qform transform
end
if affine_transform == 1
voxel_size = abs(sum(R,1));
inv_R = inv(R);
originator = inv_R*(-T)+1;
orient = get_orient(inv_R);
% modify pixdim and originator
%
hdr.dime.pixdim(2:4) = voxel_size;
hdr.hist.originator(1:3) = originator;
% set sform or qform to non-use, because they have been
% applied in xform_nii
%
hdr.hist.qform_code = 0;
hdr.hist.sform_code = 0;
end
% apply space_unit to pixdim if not 1 (mm)
%
space_unit = get_units(hdr);
if space_unit ~= 1
hdr.dime.pixdim(2:4) = hdr.dime.pixdim(2:4) * space_unit;
% set space_unit of xyzt_units to millimeter, because
% voxel_size has been re-scaled
%
hdr.dime.xyzt_units = char(bitset(hdr.dime.xyzt_units,1,0));
hdr.dime.xyzt_units = char(bitset(hdr.dime.xyzt_units,2,1));
hdr.dime.xyzt_units = char(bitset(hdr.dime.xyzt_units,3,0));
end
hdr.dime.pixdim = abs(hdr.dime.pixdim);
return; % change_hdr
%-----------------------------------------------------------------------
function orient = get_orient(R)
orient = [];
for i = 1:3
switch find(R(i,:)) * sign(sum(R(i,:)))
case 1
orient = [orient 1]; % Left to Right
case 2
orient = [orient 2]; % Posterior to Anterior
case 3
orient = [orient 3]; % Inferior to Superior
case -1
orient = [orient 4]; % Right to Left
case -2
orient = [orient 5]; % Anterior to Posterior
case -3
orient = [orient 6]; % Superior to Inferior
end
end
return; % get_orient
%-----------------------------------------------------------------------
function [space_unit, time_unit] = get_units(hdr)
switch bitand(hdr.dime.xyzt_units, 7) % mask with 0x07
case 1
space_unit = 1e+3; % meter, m
case 3
space_unit = 1e-3; % micrometer, um
otherwise
space_unit = 1; % millimeter, mm
end
switch bitand(hdr.dime.xyzt_units, 56) % mask with 0x38
case 16
time_unit = 1e-3; % millisecond, ms
case 24
time_unit = 1e-6; % microsecond, us
otherwise
time_unit = 1; % second, s
end
return; % get_units
|
github
|
sunhongfu/scripts-master
|
make_ana.m
|
.m
|
scripts-master/cs-phase/_src/_nii/make_ana.m
| 5,665 |
utf_8
|
37d574b277823f941138c9548127d720
|
% Make ANALYZE 7.5 data structure specified by a 3D or 4D matrix.
% Optional parameters can also be included, such as: voxel_size,
% origin, datatype, and description.
%
% Once the ANALYZE structure is made, it can be saved into ANALYZE 7.5
% format data file using "save_untouch_nii" command (for more detail,
% type: help save_untouch_nii).
%
% Usage: ana = make_ana(img, [voxel_size], [origin], [datatype], [description])
%
% Where:
%
% img: a 3D matrix [x y z], or a 4D matrix with time
% series [x y z t]. When image is in RGB format,
% make sure that the size of 4th dimension is
% always 3 (i.e. [R G B]). In that case, make
% sure that you must specify RGB datatype to 128.
%
% voxel_size (optional): Voxel size in millimeter for each
% dimension. Default is [1 1 1].
%
% origin (optional): The AC origin. Default is [0 0 0].
%
% datatype (optional): Storage data type:
% 2 - uint8, 4 - int16, 8 - int32, 16 - float32,
% 64 - float64, 128 - RGB24
% Default will use the data type of 'img' matrix
% For RGB image, you must specify it to 128.
%
% description (optional): Description of data. Default is ''.
%
% e.g.:
% origin = [33 44 13]; datatype = 64;
% ana = make_ana(img, [], origin, datatype); % default voxel_size
%
% ANALYZE 7.5 format: http://www.rotman-baycrest.on.ca/~jimmy/ANALYZE75.pdf
%
% - Jimmy Shen ([email protected])
%
function ana = make_ana(varargin)
ana.img = varargin{1};
dims = size(ana.img);
dims = [4 dims ones(1,8)];
dims = dims(1:8);
voxel_size = [0 ones(1,3) zeros(1,4)];
origin = zeros(1,5);
descrip = '';
switch class(ana.img)
case 'uint8'
datatype = 2;
case 'int16'
datatype = 4;
case 'int32'
datatype = 8;
case 'single'
datatype = 16;
case 'double'
datatype = 64;
otherwise
error('Datatype is not supported by make_ana.');
end
if nargin > 1 & ~isempty(varargin{2})
voxel_size(2:4) = double(varargin{2});
end
if nargin > 2 & ~isempty(varargin{3})
origin(1:3) = double(varargin{3});
end
if nargin > 3 & ~isempty(varargin{4})
datatype = double(varargin{4});
if datatype == 128 | datatype == 511
dims(5) = [];
dims = [dims 1];
end
end
if nargin > 4 & ~isempty(varargin{5})
descrip = varargin{5};
end
if ndims(ana.img) > 4
error('NIfTI only allows a maximum of 4 Dimension matrix.');
end
maxval = round(double(max(ana.img(:))));
minval = round(double(min(ana.img(:))));
ana.hdr = make_header(dims, voxel_size, origin, datatype, ...
descrip, maxval, minval);
ana.filetype = 0;
ana.ext = [];
ana.untouch = 1;
switch ana.hdr.dime.datatype
case 2
ana.img = uint8(ana.img);
case 4
ana.img = int16(ana.img);
case 8
ana.img = int32(ana.img);
case 16
ana.img = single(ana.img);
case 64
ana.img = double(ana.img);
case 128
ana.img = uint8(ana.img);
otherwise
error('Datatype is not supported by make_ana.');
end
return; % make_ana
%---------------------------------------------------------------------
function hdr = make_header(dims, voxel_size, origin, datatype, ...
descrip, maxval, minval)
hdr.hk = header_key;
hdr.dime = image_dimension(dims, voxel_size, datatype, maxval, minval);
hdr.hist = data_history(origin, descrip);
return; % make_header
%---------------------------------------------------------------------
function hk = header_key
hk.sizeof_hdr = 348; % must be 348!
hk.data_type = '';
hk.db_name = '';
hk.extents = 0;
hk.session_error = 0;
hk.regular = 'r';
hk.hkey_un0 = '0';
return; % header_key
%---------------------------------------------------------------------
function dime = image_dimension(dims, voxel_size, datatype, maxval, minval)
dime.dim = dims;
dime.vox_units = 'mm';
dime.cal_units = '';
dime.unused1 = 0;
dime.datatype = datatype;
switch dime.datatype
case 2,
dime.bitpix = 8; precision = 'uint8';
case 4,
dime.bitpix = 16; precision = 'int16';
case 8,
dime.bitpix = 32; precision = 'int32';
case 16,
dime.bitpix = 32; precision = 'float32';
case 64,
dime.bitpix = 64; precision = 'float64';
case 128
dime.bitpix = 24; precision = 'uint8';
otherwise
error('Datatype is not supported by make_ana.');
end
dime.dim_un0 = 0;
dime.pixdim = voxel_size;
dime.vox_offset = 0;
dime.roi_scale = 1;
dime.funused1 = 0;
dime.funused2 = 0;
dime.cal_max = 0;
dime.cal_min = 0;
dime.compressed = 0;
dime.verified = 0;
dime.glmax = maxval;
dime.glmin = minval;
return; % image_dimension
%---------------------------------------------------------------------
function hist = data_history(origin, descrip)
hist.descrip = descrip;
hist.aux_file = 'none';
hist.orient = 0;
hist.originator = origin;
hist.generated = '';
hist.scannum = '';
hist.patient_id = '';
hist.exp_date = '';
hist.exp_time = '';
hist.hist_un0 = '';
hist.views = 0;
hist.vols_added = 0;
hist.start_field = 0;
hist.field_skip = 0;
hist.omax = 0;
hist.omin = 0;
hist.smax = 0;
hist.smin = 0;
return; % data_history
|
github
|
sunhongfu/scripts-master
|
extra_nii_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/extra_nii_hdr.m
| 8,085 |
utf_8
|
4f76a8a66736025a0acf3efa15a2d2aa
|
% Decode extra NIFTI header information into hdr.extra
%
% Usage: hdr = extra_nii_hdr(hdr)
%
% hdr can be obtained from load_nii_hdr
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function hdr = extra_nii_hdr(hdr)
switch hdr.dime.datatype
case 1
extra.NIFTI_DATATYPES = 'DT_BINARY';
case 2
extra.NIFTI_DATATYPES = 'DT_UINT8';
case 4
extra.NIFTI_DATATYPES = 'DT_INT16';
case 8
extra.NIFTI_DATATYPES = 'DT_INT32';
case 16
extra.NIFTI_DATATYPES = 'DT_FLOAT32';
case 32
extra.NIFTI_DATATYPES = 'DT_COMPLEX64';
case 64
extra.NIFTI_DATATYPES = 'DT_FLOAT64';
case 128
extra.NIFTI_DATATYPES = 'DT_RGB24';
case 256
extra.NIFTI_DATATYPES = 'DT_INT8';
case 512
extra.NIFTI_DATATYPES = 'DT_UINT16';
case 768
extra.NIFTI_DATATYPES = 'DT_UINT32';
case 1024
extra.NIFTI_DATATYPES = 'DT_INT64';
case 1280
extra.NIFTI_DATATYPES = 'DT_UINT64';
case 1536
extra.NIFTI_DATATYPES = 'DT_FLOAT128';
case 1792
extra.NIFTI_DATATYPES = 'DT_COMPLEX128';
case 2048
extra.NIFTI_DATATYPES = 'DT_COMPLEX256';
otherwise
extra.NIFTI_DATATYPES = 'DT_UNKNOWN';
end
switch hdr.dime.intent_code
case 2
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_CORREL';
case 3
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_TTEST';
case 4
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_FTEST';
case 5
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_ZSCORE';
case 6
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_CHISQ';
case 7
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_BETA';
case 8
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_BINOM';
case 9
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_GAMMA';
case 10
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_POISSON';
case 11
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_NORMAL';
case 12
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_FTEST_NONC';
case 13
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_CHISQ_NONC';
case 14
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_LOGISTIC';
case 15
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_LAPLACE';
case 16
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_UNIFORM';
case 17
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_TTEST_NONC';
case 18
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_WEIBULL';
case 19
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_CHI';
case 20
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_INVGAUSS';
case 21
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_EXTVAL';
case 22
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_PVAL';
case 23
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_LOGPVAL';
case 24
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_LOG10PVAL';
case 1001
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_ESTIMATE';
case 1002
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_LABEL';
case 1003
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_NEURONAME';
case 1004
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_GENMATRIX';
case 1005
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_SYMMATRIX';
case 1006
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_DISPVECT';
case 1007
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_VECTOR';
case 1008
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_POINTSET';
case 1009
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_TRIANGLE';
case 1010
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_QUATERNION';
case 1011
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_DIMLESS';
otherwise
extra.NIFTI_INTENT_CODES = 'NIFTI_INTENT_NONE';
end
extra.NIFTI_INTENT_NAMES = hdr.hist.intent_name;
if hdr.hist.sform_code > 0
switch hdr.hist.sform_code
case 1
extra.NIFTI_SFORM_CODES = 'NIFTI_XFORM_SCANNER_ANAT';
case 2
extra.NIFTI_SFORM_CODES = 'NIFTI_XFORM_ALIGNED_ANAT';
case 3
extra.NIFTI_SFORM_CODES = 'NIFTI_XFORM_TALAIRACH';
case 4
extra.NIFTI_SFORM_CODES = 'NIFTI_XFORM_MNI_152';
otherwise
extra.NIFTI_SFORM_CODES = 'NIFTI_XFORM_UNKNOWN';
end
extra.NIFTI_QFORM_CODES = 'NIFTI_XFORM_UNKNOWN';
elseif hdr.hist.qform_code > 0
extra.NIFTI_SFORM_CODES = 'NIFTI_XFORM_UNKNOWN';
switch hdr.hist.qform_code
case 1
extra.NIFTI_QFORM_CODES = 'NIFTI_XFORM_SCANNER_ANAT';
case 2
extra.NIFTI_QFORM_CODES = 'NIFTI_XFORM_ALIGNED_ANAT';
case 3
extra.NIFTI_QFORM_CODES = 'NIFTI_XFORM_TALAIRACH';
case 4
extra.NIFTI_QFORM_CODES = 'NIFTI_XFORM_MNI_152';
otherwise
extra.NIFTI_QFORM_CODES = 'NIFTI_XFORM_UNKNOWN';
end
else
extra.NIFTI_SFORM_CODES = 'NIFTI_XFORM_UNKNOWN';
extra.NIFTI_QFORM_CODES = 'NIFTI_XFORM_UNKNOWN';
end
switch bitand(hdr.dime.xyzt_units, 7) % mask with 0x07
case 1
extra.NIFTI_SPACE_UNIT = 'NIFTI_UNITS_METER';
case 2
extra.NIFTI_SPACE_UNIT = 'NIFTI_UNITS_MM'; % millimeter
case 3
extra.NIFTI_SPACE_UNIT = 'NIFTI_UNITS_MICRO';
otherwise
extra.NIFTI_SPACE_UNIT = 'NIFTI_UNITS_UNKNOWN';
end
switch bitand(hdr.dime.xyzt_units, 56) % mask with 0x38
case 8
extra.NIFTI_TIME_UNIT = 'NIFTI_UNITS_SEC';
case 16
extra.NIFTI_TIME_UNIT = 'NIFTI_UNITS_MSEC';
case 24
extra.NIFTI_TIME_UNIT = 'NIFTI_UNITS_USEC'; % microsecond
otherwise
extra.NIFTI_TIME_UNIT = 'NIFTI_UNITS_UNKNOWN';
end
switch hdr.dime.xyzt_units
case 32
extra.NIFTI_SPECTRAL_UNIT = 'NIFTI_UNITS_HZ';
case 40
extra.NIFTI_SPECTRAL_UNIT = 'NIFTI_UNITS_PPM'; % part per million
case 48
extra.NIFTI_SPECTRAL_UNIT = 'NIFTI_UNITS_RADS'; % radians per second
otherwise
extra.NIFTI_SPECTRAL_UNIT = 'NIFTI_UNITS_UNKNOWN';
end
% MRI-specific spatial and temporal information
%
dim_info = hdr.hk.dim_info;
extra.NIFTI_FREQ_DIM = bitand(dim_info, 3);
extra.NIFTI_PHASE_DIM = bitand(bitshift(dim_info, -2), 3);
extra.NIFTI_SLICE_DIM = bitand(bitshift(dim_info, -4), 3);
% Check slice code
%
switch hdr.dime.slice_code
case 1
extra.NIFTI_SLICE_ORDER = 'NIFTI_SLICE_SEQ_INC'; % sequential increasing
case 2
extra.NIFTI_SLICE_ORDER = 'NIFTI_SLICE_SEQ_DEC'; % sequential decreasing
case 3
extra.NIFTI_SLICE_ORDER = 'NIFTI_SLICE_ALT_INC'; % alternating increasing
case 4
extra.NIFTI_SLICE_ORDER = 'NIFTI_SLICE_ALT_DEC'; % alternating decreasing
case 5
extra.NIFTI_SLICE_ORDER = 'NIFTI_SLICE_ALT_INC2'; % ALT_INC # 2
case 6
extra.NIFTI_SLICE_ORDER = 'NIFTI_SLICE_ALT_DEC2'; % ALT_DEC # 2
otherwise
extra.NIFTI_SLICE_ORDER = 'NIFTI_SLICE_UNKNOWN';
end
% Check NIFTI version
%
if ~isempty(hdr.hist.magic) & strcmp(hdr.hist.magic(1),'n') & ...
( strcmp(hdr.hist.magic(2),'i') | strcmp(hdr.hist.magic(2),'+') ) & ...
str2num(hdr.hist.magic(3)) >= 1 & str2num(hdr.hist.magic(3)) <= 9
extra.NIFTI_VERSION = str2num(hdr.hist.magic(3));
else
extra.NIFTI_VERSION = 0;
end
% Check if data stored in the same file (*.nii) or separate
% files (*.hdr/*.img)
%
if isempty(hdr.hist.magic)
extra.NIFTI_ONEFILE = 0;
else
extra.NIFTI_ONEFILE = strcmp(hdr.hist.magic(2), '+');
end
% Swap has been taken care of by checking whether sizeof_hdr is
% 348 (machine is 'ieee-le' or 'ieee-be' etc)
%
% extra.NIFTI_NEEDS_SWAP = (hdr.dime.dim(1) < 0 | hdr.dime.dim(1) > 7);
% Check NIFTI header struct contains a 5th (vector) dimension
%
if hdr.dime.dim(1) > 4 & hdr.dime.dim(6) > 1
extra.NIFTI_5TH_DIM = hdr.dime.dim(6);
else
extra.NIFTI_5TH_DIM = 0;
end
hdr.extra = extra;
return; % extra_nii_hdr
|
github
|
sunhongfu/scripts-master
|
rri_xhair.m
|
.m
|
scripts-master/cs-phase/_src/_nii/rri_xhair.m
| 2,300 |
utf_8
|
95954b8cd43e01fba5c4b2f335be1780
|
% rri_xhair: create a pair of full_cross_hair at point [x y] in
% axes h_ax, and return xhair struct
%
% Usage: xhair = rri_xhair([x y], xhair, h_ax);
%
% If omit xhair, rri_xhair will create a pair of xhair; otherwise,
% rri_xhair will update the xhair. If omit h_ax, current axes will
% be used.
%
% 24-nov-2003 jimmy ([email protected])
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function xhair = rri_xhair(varargin)
if nargin == 0
error('Please enter a point position as first argument');
return;
end
if nargin > 0
p = varargin{1};
if ~isnumeric(p) | length(p) ~= 2
error('Invalid point position');
return;
else
xhair = [];
end
end
if nargin > 1
xhair = varargin{2};
if ~isempty(xhair)
if ~isstruct(xhair)
error('Invalid xhair struct');
return;
elseif ~isfield(xhair,'lx') | ~isfield(xhair,'ly')
error('Invalid xhair struct');
return;
elseif ~ishandle(xhair.lx) | ~ishandle(xhair.ly)
error('Invalid xhair struct');
return;
end
lx = xhair.lx;
ly = xhair.ly;
else
lx = [];
ly = [];
end
end
if nargin > 2
h_ax = varargin{3};
if ~ishandle(h_ax)
error('Invalid axes handle');
return;
elseif ~strcmp(lower(get(h_ax,'type')), 'axes')
error('Invalid axes handle');
return;
end
else
h_ax = gca;
end
x_range = get(h_ax,'xlim');
y_range = get(h_ax,'ylim');
if ~isempty(xhair)
set(lx, 'ydata', [p(2) p(2)]);
set(ly, 'xdata', [p(1) p(1)]);
set(h_ax, 'selected', 'on');
set(h_ax, 'selected', 'off');
else
figure(get(h_ax,'parent'));
axes(h_ax);
xhair.lx = line('xdata', x_range, 'ydata', [p(2) p(2)], ...
'zdata', [11 11], 'color', [1 0 0], 'hittest', 'off');
xhair.ly = line('xdata', [p(1) p(1)], 'ydata', y_range, ...
'zdata', [11 11], 'color', [1 0 0], 'hittest', 'off');
end
set(h_ax,'xlim',x_range);
set(h_ax,'ylim',y_range);
return;
|
github
|
sunhongfu/scripts-master
|
save_untouch_nii_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_untouch_nii_hdr.m
| 8,721 |
utf_8
|
0d396eaeebb6114f24d56ab74a8299cf
|
% internal function
% - Jimmy Shen ([email protected])
function save_nii_hdr(hdr, fid)
if ~isequal(hdr.hk.sizeof_hdr,348),
error('hdr.hk.sizeof_hdr must be 348.');
end
write_header(hdr, fid);
return; % save_nii_hdr
%---------------------------------------------------------------------
function write_header(hdr, fid)
% Original header structures
% struct dsr /* dsr = hdr */
% {
% struct header_key hk; /* 0 + 40 */
% struct image_dimension dime; /* 40 + 108 */
% struct data_history hist; /* 148 + 200 */
% }; /* total= 348 bytes*/
header_key(fid, hdr.hk);
image_dimension(fid, hdr.dime);
data_history(fid, hdr.hist);
% check the file size is 348 bytes
%
fbytes = ftell(fid);
if ~isequal(fbytes,348),
msg = sprintf('Header size is not 348 bytes.');
warning(msg);
end
return; % write_header
%---------------------------------------------------------------------
function header_key(fid, hk)
fseek(fid,0,'bof');
% Original header structures
% struct header_key /* header key */
% { /* off + size */
% int sizeof_hdr /* 0 + 4 */
% char data_type[10]; /* 4 + 10 */
% char db_name[18]; /* 14 + 18 */
% int extents; /* 32 + 4 */
% short int session_error; /* 36 + 2 */
% char regular; /* 38 + 1 */
% char dim_info; % char hkey_un0; /* 39 + 1 */
% }; /* total=40 bytes */
fwrite(fid, hk.sizeof_hdr(1), 'int32'); % must be 348.
% data_type = sprintf('%-10s',hk.data_type); % ensure it is 10 chars from left
% fwrite(fid, data_type(1:10), 'uchar');
pad = zeros(1, 10-length(hk.data_type));
hk.data_type = [hk.data_type char(pad)];
fwrite(fid, hk.data_type(1:10), 'uchar');
% db_name = sprintf('%-18s', hk.db_name); % ensure it is 18 chars from left
% fwrite(fid, db_name(1:18), 'uchar');
pad = zeros(1, 18-length(hk.db_name));
hk.db_name = [hk.db_name char(pad)];
fwrite(fid, hk.db_name(1:18), 'uchar');
fwrite(fid, hk.extents(1), 'int32');
fwrite(fid, hk.session_error(1), 'int16');
fwrite(fid, hk.regular(1), 'uchar'); % might be uint8
% fwrite(fid, hk.hkey_un0(1), 'uchar');
% fwrite(fid, hk.hkey_un0(1), 'uint8');
fwrite(fid, hk.dim_info(1), 'uchar');
return; % header_key
%---------------------------------------------------------------------
function image_dimension(fid, dime)
% Original header structures
% struct image_dimension
% { /* off + size */
% short int dim[8]; /* 0 + 16 */
% float intent_p1; % char vox_units[4]; /* 16 + 4 */
% float intent_p2; % char cal_units[8]; /* 20 + 4 */
% float intent_p3; % char cal_units[8]; /* 24 + 4 */
% short int intent_code; % short int unused1; /* 28 + 2 */
% short int datatype; /* 30 + 2 */
% short int bitpix; /* 32 + 2 */
% short int slice_start; % short int dim_un0; /* 34 + 2 */
% float pixdim[8]; /* 36 + 32 */
% /*
% pixdim[] specifies the voxel dimensions:
% pixdim[1] - voxel width
% pixdim[2] - voxel height
% pixdim[3] - interslice distance
% pixdim[4] - volume timing, in msec
% ..etc
% */
% float vox_offset; /* 68 + 4 */
% float scl_slope; % float roi_scale; /* 72 + 4 */
% float scl_inter; % float funused1; /* 76 + 4 */
% short slice_end; % float funused2; /* 80 + 2 */
% char slice_code; % float funused2; /* 82 + 1 */
% char xyzt_units; % float funused2; /* 83 + 1 */
% float cal_max; /* 84 + 4 */
% float cal_min; /* 88 + 4 */
% float slice_duration; % int compressed; /* 92 + 4 */
% float toffset; % int verified; /* 96 + 4 */
% int glmax; /* 100 + 4 */
% int glmin; /* 104 + 4 */
% }; /* total=108 bytes */
fwrite(fid, dime.dim(1:8), 'int16');
fwrite(fid, dime.intent_p1(1), 'float32');
fwrite(fid, dime.intent_p2(1), 'float32');
fwrite(fid, dime.intent_p3(1), 'float32');
fwrite(fid, dime.intent_code(1), 'int16');
fwrite(fid, dime.datatype(1), 'int16');
fwrite(fid, dime.bitpix(1), 'int16');
fwrite(fid, dime.slice_start(1), 'int16');
fwrite(fid, dime.pixdim(1:8), 'float32');
fwrite(fid, dime.vox_offset(1), 'float32');
fwrite(fid, dime.scl_slope(1), 'float32');
fwrite(fid, dime.scl_inter(1), 'float32');
fwrite(fid, dime.slice_end(1), 'int16');
fwrite(fid, dime.slice_code(1), 'uchar');
fwrite(fid, dime.xyzt_units(1), 'uchar');
fwrite(fid, dime.cal_max(1), 'float32');
fwrite(fid, dime.cal_min(1), 'float32');
fwrite(fid, dime.slice_duration(1), 'float32');
fwrite(fid, dime.toffset(1), 'float32');
fwrite(fid, dime.glmax(1), 'int32');
fwrite(fid, dime.glmin(1), 'int32');
return; % image_dimension
%---------------------------------------------------------------------
function data_history(fid, hist)
% Original header structures
%struct data_history
% { /* off + size */
% char descrip[80]; /* 0 + 80 */
% char aux_file[24]; /* 80 + 24 */
% short int qform_code; /* 104 + 2 */
% short int sform_code; /* 106 + 2 */
% float quatern_b; /* 108 + 4 */
% float quatern_c; /* 112 + 4 */
% float quatern_d; /* 116 + 4 */
% float qoffset_x; /* 120 + 4 */
% float qoffset_y; /* 124 + 4 */
% float qoffset_z; /* 128 + 4 */
% float srow_x[4]; /* 132 + 16 */
% float srow_y[4]; /* 148 + 16 */
% float srow_z[4]; /* 164 + 16 */
% char intent_name[16]; /* 180 + 16 */
% char magic[4]; % int smin; /* 196 + 4 */
% }; /* total=200 bytes */
% descrip = sprintf('%-80s', hist.descrip); % 80 chars from left
% fwrite(fid, descrip(1:80), 'uchar');
pad = zeros(1, 80-length(hist.descrip));
hist.descrip = [hist.descrip char(pad)];
fwrite(fid, hist.descrip(1:80), 'uchar');
% aux_file = sprintf('%-24s', hist.aux_file); % 24 chars from left
% fwrite(fid, aux_file(1:24), 'uchar');
pad = zeros(1, 24-length(hist.aux_file));
hist.aux_file = [hist.aux_file char(pad)];
fwrite(fid, hist.aux_file(1:24), 'uchar');
fwrite(fid, hist.qform_code, 'int16');
fwrite(fid, hist.sform_code, 'int16');
fwrite(fid, hist.quatern_b, 'float32');
fwrite(fid, hist.quatern_c, 'float32');
fwrite(fid, hist.quatern_d, 'float32');
fwrite(fid, hist.qoffset_x, 'float32');
fwrite(fid, hist.qoffset_y, 'float32');
fwrite(fid, hist.qoffset_z, 'float32');
fwrite(fid, hist.srow_x(1:4), 'float32');
fwrite(fid, hist.srow_y(1:4), 'float32');
fwrite(fid, hist.srow_z(1:4), 'float32');
% intent_name = sprintf('%-16s', hist.intent_name); % 16 chars from left
% fwrite(fid, intent_name(1:16), 'uchar');
pad = zeros(1, 16-length(hist.intent_name));
hist.intent_name = [hist.intent_name char(pad)];
fwrite(fid, hist.intent_name(1:16), 'uchar');
% magic = sprintf('%-4s', hist.magic); % 4 chars from left
% fwrite(fid, magic(1:4), 'uchar');
pad = zeros(1, 4-length(hist.magic));
hist.magic = [hist.magic char(pad)];
fwrite(fid, hist.magic(1:4), 'uchar');
return; % data_history
|
github
|
sunhongfu/scripts-master
|
expand_nii_scan.m
|
.m
|
scripts-master/cs-phase/_src/_nii/expand_nii_scan.m
| 1,381 |
utf_8
|
0715d668d046bcc608ea78cd0c2089bd
|
% Expand a multiple-scan NIFTI file into multiple single-scan NIFTI files
%
% Usage: expand_nii_scan(multi_scan_filename, [img_idx], [path_to_save])
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function expand_nii_scan(filename, img_idx, newpath)
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
else
gzFile = 1;
end
end
if ~exist('newpath','var') | isempty(newpath), newpath = pwd; end
if ~exist('img_idx','var') | isempty(img_idx), img_idx = 1:get_nii_frame(filename); end
for i=img_idx
nii_i = load_untouch_nii(filename, i);
fn = [nii_i.fileprefix '_' sprintf('%04d',i)];
pnfn = fullfile(newpath, fn);
if exist('gzFile', 'var')
pnfn = [pnfn '.nii.gz'];
end
save_untouch_nii(nii_i, pnfn);
end
return; % expand_nii_scan
|
github
|
sunhongfu/scripts-master
|
load_untouch_header_only.m
|
.m
|
scripts-master/cs-phase/_src/_nii/load_untouch_header_only.m
| 7,255 |
utf_8
|
f1210f851ab6610e7656121194cb5c8b
|
% Load NIfTI / Analyze header without applying any appropriate affine
% geometric transform or voxel intensity scaling. It is equivalent to
% hdr field when using load_untouch_nii to load dataset. Support both
% *.nii and *.hdr file extension. If file extension is not provided,
% *.hdr will be used as default.
%
% Usage: [header, ext, filetype, machine] = load_untouch_header_only(filename)
%
% filename - NIfTI / Analyze file name.
%
% Returned values:
%
% header - struct with NIfTI / Analyze header fields.
%
% ext - NIfTI extension if it is not empty.
%
% filetype - 0 for Analyze format (*.hdr/*.img);
% 1 for NIFTI format in 2 files (*.hdr/*.img);
% 2 for NIFTI format in 1 file (*.nii).
%
% machine - a string, see below for details. The default here is 'ieee-le'.
%
% 'native' or 'n' - local machine format - the default
% 'ieee-le' or 'l' - IEEE floating point with little-endian
% byte ordering
% 'ieee-be' or 'b' - IEEE floating point with big-endian
% byte ordering
% 'vaxd' or 'd' - VAX D floating point and VAX ordering
% 'vaxg' or 'g' - VAX G floating point and VAX ordering
% 'cray' or 'c' - Cray floating point with big-endian
% byte ordering
% 'ieee-le.l64' or 'a' - IEEE floating point with little-endian
% byte ordering and 64 bit long data type
% 'ieee-be.l64' or 's' - IEEE floating point with big-endian byte
% ordering and 64 bit long data type.
%
% Part of this file is copied and modified from:
% http://www.mathworks.com/matlabcentral/fileexchange/1878-mri-analyze-tools
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen ([email protected])
%
function [hdr, ext, filetype, machine] = load_untouch_header_only(filename)
if ~exist('filename','var')
error('Usage: [header, ext, filetype, machine] = load_untouch_header_only(filename)');
end
v = version;
% Check file extension. If .gz, unpack it into temp folder
%
if length(filename) > 2 & strcmp(filename(end-2:end), '.gz')
if ~strcmp(filename(end-6:end), '.img.gz') & ...
~strcmp(filename(end-6:end), '.hdr.gz') & ...
~strcmp(filename(end-6:end), '.nii.gz')
error('Please check filename.');
end
if str2num(v(1:3)) < 7.1 | ~usejava('jvm')
error('Please use MATLAB 7.1 (with java) and above, or run gunzip outside MATLAB.');
elseif strcmp(filename(end-6:end), '.img.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.hdr.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.hdr.gz')
filename1 = filename;
filename2 = filename;
filename2(end-6:end) = '';
filename2 = [filename2, '.img.gz'];
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename1 = gunzip(filename1, tmpDir);
filename2 = gunzip(filename2, tmpDir);
filename = char(filename1); % convert from cell to string
elseif strcmp(filename(end-6:end), '.nii.gz')
tmpDir = tempname;
mkdir(tmpDir);
gzFileName = filename;
filename = gunzip(filename, tmpDir);
filename = char(filename); % convert from cell to string
end
end
% Read the dataset header
%
[hdr, filetype, fileprefix, machine] = load_nii_hdr(filename);
if filetype == 0
hdr = load_untouch0_nii_hdr(fileprefix, machine);
ext = [];
else
hdr = load_untouch_nii_hdr(fileprefix, machine, filetype);
% Read the header extension
%
ext = load_nii_ext(filename);
end
% Set bitpix according to datatype
%
% /*Acceptable values for datatype are*/
%
% 0 None (Unknown bit per voxel) % DT_NONE, DT_UNKNOWN
% 1 Binary (ubit1, bitpix=1) % DT_BINARY
% 2 Unsigned char (uchar or uint8, bitpix=8) % DT_UINT8, NIFTI_TYPE_UINT8
% 4 Signed short (int16, bitpix=16) % DT_INT16, NIFTI_TYPE_INT16
% 8 Signed integer (int32, bitpix=32) % DT_INT32, NIFTI_TYPE_INT32
% 16 Floating point (single or float32, bitpix=32) % DT_FLOAT32, NIFTI_TYPE_FLOAT32
% 32 Complex, 2 float32 (Use float32, bitpix=64) % DT_COMPLEX64, NIFTI_TYPE_COMPLEX64
% 64 Double precision (double or float64, bitpix=64) % DT_FLOAT64, NIFTI_TYPE_FLOAT64
% 128 uint8 RGB (Use uint8, bitpix=24) % DT_RGB24, NIFTI_TYPE_RGB24
% 256 Signed char (schar or int8, bitpix=8) % DT_INT8, NIFTI_TYPE_INT8
% 511 Single RGB (Use float32, bitpix=96) % DT_RGB96, NIFTI_TYPE_RGB96
% 512 Unsigned short (uint16, bitpix=16) % DT_UNINT16, NIFTI_TYPE_UNINT16
% 768 Unsigned integer (uint32, bitpix=32) % DT_UNINT32, NIFTI_TYPE_UNINT32
% 1024 Signed long long (int64, bitpix=64) % DT_INT64, NIFTI_TYPE_INT64
% 1280 Unsigned long long (uint64, bitpix=64) % DT_UINT64, NIFTI_TYPE_UINT64
% 1536 Long double, float128 (Unsupported, bitpix=128) % DT_FLOAT128, NIFTI_TYPE_FLOAT128
% 1792 Complex128, 2 float64 (Use float64, bitpix=128) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
% 2048 Complex256, 2 float128 (Unsupported, bitpix=256) % DT_COMPLEX128, NIFTI_TYPE_COMPLEX128
%
switch hdr.dime.datatype
case 1,
hdr.dime.bitpix = 1; precision = 'ubit1';
case 2,
hdr.dime.bitpix = 8; precision = 'uint8';
case 4,
hdr.dime.bitpix = 16; precision = 'int16';
case 8,
hdr.dime.bitpix = 32; precision = 'int32';
case 16,
hdr.dime.bitpix = 32; precision = 'float32';
case 32,
hdr.dime.bitpix = 64; precision = 'float32';
case 64,
hdr.dime.bitpix = 64; precision = 'float64';
case 128,
hdr.dime.bitpix = 24; precision = 'uint8';
case 256
hdr.dime.bitpix = 8; precision = 'int8';
case 511
hdr.dime.bitpix = 96; precision = 'float32';
case 512
hdr.dime.bitpix = 16; precision = 'uint16';
case 768
hdr.dime.bitpix = 32; precision = 'uint32';
case 1024
hdr.dime.bitpix = 64; precision = 'int64';
case 1280
hdr.dime.bitpix = 64; precision = 'uint64';
case 1792,
hdr.dime.bitpix = 128; precision = 'float64';
otherwise
error('This datatype is not supported');
end
tmp = hdr.dime.dim(2:end);
tmp(find(tmp < 1)) = 1;
hdr.dime.dim(2:end) = tmp;
% Clean up after gunzip
%
if exist('gzFileName', 'var')
rmdir(tmpDir,'s');
end
return % load_untouch_header_only
|
github
|
sunhongfu/scripts-master
|
bipolar.m
|
.m
|
scripts-master/cs-phase/_src/_nii/bipolar.m
| 2,239 |
utf_8
|
c860ec93d96b6ab636c985280d79958d
|
%BIPOLAR returns an M-by-3 matrix containing a blue-red colormap, in
% in which red stands for positive, blue stands for negative,
% and white stands for 0.
%
% Usage: cmap = bipolar(M, lo, hi, contrast); or cmap = bipolar;
%
% cmap: output M-by-3 matrix for BIPOLAR colormap.
% M: number of shades in the colormap. By default, it is the
% same length as the current colormap.
% lo: the lowest value to represent.
% hi: the highest value to represent.
%
% Inspired from the LORETA PASCAL program:
% http://www.unizh.ch/keyinst/NewLORETA
%
% [email protected]
%
%----------------------------------------------------------------
function cmap = bipolar(M, lo, hi, contrast)
if ~exist('contrast','var')
contrast = 128;
end
if ~exist('lo','var')
lo = -1;
end
if ~exist('hi','var')
hi = 1;
end
if ~exist('M','var')
cmap = colormap;
M = size(cmap,1);
end
steepness = 10 ^ (1 - (contrast-1)/127);
pos_infs = 1e-99;
neg_infs = -1e-99;
doubleredc = [];
doublebluec = [];
if lo >= 0 % all positive
if lo == 0
lo = pos_infs;
end
for i=linspace(hi/M, hi, M)
t = exp(log(i/hi)*steepness);
doubleredc = [doubleredc; [(1-t)+t,(1-t)+0,(1-t)+0]];
end
cmap = doubleredc;
elseif hi <= 0 % all negative
if hi == 0
hi = neg_infs;
end
for i=linspace(abs(lo)/M, abs(lo), M)
t = exp(log(i/abs(lo))*steepness);
doublebluec = [doublebluec; [(1-t)+0,(1-t)+0,(1-t)+t]];
end
cmap = flipud(doublebluec);
else
if hi > abs(lo)
maxc = hi;
else
maxc = abs(lo);
end
for i=linspace(maxc/M, hi, round(M*hi/(hi-lo)))
t = exp(log(i/maxc)*steepness);
doubleredc = [doubleredc; [(1-t)+t,(1-t)+0,(1-t)+0]];
end
for i=linspace(maxc/M, abs(lo), round(M*abs(lo)/(hi-lo)))
t = exp(log(i/maxc)*steepness);
doublebluec = [doublebluec; [(1-t)+0,(1-t)+0,(1-t)+t]];
end
cmap = [flipud(doublebluec); doubleredc];
end
return; % bipolar
|
github
|
sunhongfu/scripts-master
|
save_nii_hdr.m
|
.m
|
scripts-master/cs-phase/_src/_nii/save_nii_hdr.m
| 9,497 |
utf_8
|
66a99df0cb0f3c1f44c6e36dcd13cddf
|
% internal function
% - Jimmy Shen ([email protected])
function save_nii_hdr(hdr, fid)
if ~exist('hdr','var') | ~exist('fid','var')
error('Usage: save_nii_hdr(hdr, fid)');
end
if ~isequal(hdr.hk.sizeof_hdr,348),
error('hdr.hk.sizeof_hdr must be 348.');
end
if hdr.hist.qform_code == 0 & hdr.hist.sform_code == 0
hdr.hist.sform_code = 1;
hdr.hist.srow_x(1) = hdr.dime.pixdim(2);
hdr.hist.srow_x(2) = 0;
hdr.hist.srow_x(3) = 0;
hdr.hist.srow_y(1) = 0;
hdr.hist.srow_y(2) = hdr.dime.pixdim(3);
hdr.hist.srow_y(3) = 0;
hdr.hist.srow_z(1) = 0;
hdr.hist.srow_z(2) = 0;
hdr.hist.srow_z(3) = hdr.dime.pixdim(4);
hdr.hist.srow_x(4) = (1-hdr.hist.originator(1))*hdr.dime.pixdim(2);
hdr.hist.srow_y(4) = (1-hdr.hist.originator(2))*hdr.dime.pixdim(3);
hdr.hist.srow_z(4) = (1-hdr.hist.originator(3))*hdr.dime.pixdim(4);
end
write_header(hdr, fid);
return; % save_nii_hdr
%---------------------------------------------------------------------
function write_header(hdr, fid)
% Original header structures
% struct dsr /* dsr = hdr */
% {
% struct header_key hk; /* 0 + 40 */
% struct image_dimension dime; /* 40 + 108 */
% struct data_history hist; /* 148 + 200 */
% }; /* total= 348 bytes*/
header_key(fid, hdr.hk);
image_dimension(fid, hdr.dime);
data_history(fid, hdr.hist);
% check the file size is 348 bytes
%
fbytes = ftell(fid);
if ~isequal(fbytes,348),
msg = sprintf('Header size is not 348 bytes.');
warning(msg);
end
return; % write_header
%---------------------------------------------------------------------
function header_key(fid, hk)
fseek(fid,0,'bof');
% Original header structures
% struct header_key /* header key */
% { /* off + size */
% int sizeof_hdr /* 0 + 4 */
% char data_type[10]; /* 4 + 10 */
% char db_name[18]; /* 14 + 18 */
% int extents; /* 32 + 4 */
% short int session_error; /* 36 + 2 */
% char regular; /* 38 + 1 */
% char dim_info; % char hkey_un0; /* 39 + 1 */
% }; /* total=40 bytes */
fwrite(fid, hk.sizeof_hdr(1), 'int32'); % must be 348.
% data_type = sprintf('%-10s',hk.data_type); % ensure it is 10 chars from left
% fwrite(fid, data_type(1:10), 'uchar');
pad = zeros(1, 10-length(hk.data_type));
hk.data_type = [hk.data_type char(pad)];
fwrite(fid, hk.data_type(1:10), 'uchar');
% db_name = sprintf('%-18s', hk.db_name); % ensure it is 18 chars from left
% fwrite(fid, db_name(1:18), 'uchar');
pad = zeros(1, 18-length(hk.db_name));
hk.db_name = [hk.db_name char(pad)];
fwrite(fid, hk.db_name(1:18), 'uchar');
fwrite(fid, hk.extents(1), 'int32');
fwrite(fid, hk.session_error(1), 'int16');
fwrite(fid, hk.regular(1), 'uchar'); % might be uint8
% fwrite(fid, hk.hkey_un0(1), 'uchar');
% fwrite(fid, hk.hkey_un0(1), 'uint8');
fwrite(fid, hk.dim_info(1), 'uchar');
return; % header_key
%---------------------------------------------------------------------
function image_dimension(fid, dime)
% Original header structures
% struct image_dimension
% { /* off + size */
% short int dim[8]; /* 0 + 16 */
% float intent_p1; % char vox_units[4]; /* 16 + 4 */
% float intent_p2; % char cal_units[8]; /* 20 + 4 */
% float intent_p3; % char cal_units[8]; /* 24 + 4 */
% short int intent_code; % short int unused1; /* 28 + 2 */
% short int datatype; /* 30 + 2 */
% short int bitpix; /* 32 + 2 */
% short int slice_start; % short int dim_un0; /* 34 + 2 */
% float pixdim[8]; /* 36 + 32 */
% /*
% pixdim[] specifies the voxel dimensions:
% pixdim[1] - voxel width
% pixdim[2] - voxel height
% pixdim[3] - interslice distance
% pixdim[4] - volume timing, in msec
% ..etc
% */
% float vox_offset; /* 68 + 4 */
% float scl_slope; % float roi_scale; /* 72 + 4 */
% float scl_inter; % float funused1; /* 76 + 4 */
% short slice_end; % float funused2; /* 80 + 2 */
% char slice_code; % float funused2; /* 82 + 1 */
% char xyzt_units; % float funused2; /* 83 + 1 */
% float cal_max; /* 84 + 4 */
% float cal_min; /* 88 + 4 */
% float slice_duration; % int compressed; /* 92 + 4 */
% float toffset; % int verified; /* 96 + 4 */
% int glmax; /* 100 + 4 */
% int glmin; /* 104 + 4 */
% }; /* total=108 bytes */
fwrite(fid, dime.dim(1:8), 'int16');
fwrite(fid, dime.intent_p1(1), 'float32');
fwrite(fid, dime.intent_p2(1), 'float32');
fwrite(fid, dime.intent_p3(1), 'float32');
fwrite(fid, dime.intent_code(1), 'int16');
fwrite(fid, dime.datatype(1), 'int16');
fwrite(fid, dime.bitpix(1), 'int16');
fwrite(fid, dime.slice_start(1), 'int16');
fwrite(fid, dime.pixdim(1:8), 'float32');
fwrite(fid, dime.vox_offset(1), 'float32');
fwrite(fid, dime.scl_slope(1), 'float32');
fwrite(fid, dime.scl_inter(1), 'float32');
fwrite(fid, dime.slice_end(1), 'int16');
fwrite(fid, dime.slice_code(1), 'uchar');
fwrite(fid, dime.xyzt_units(1), 'uchar');
fwrite(fid, dime.cal_max(1), 'float32');
fwrite(fid, dime.cal_min(1), 'float32');
fwrite(fid, dime.slice_duration(1), 'float32');
fwrite(fid, dime.toffset(1), 'float32');
fwrite(fid, dime.glmax(1), 'int32');
fwrite(fid, dime.glmin(1), 'int32');
return; % image_dimension
%---------------------------------------------------------------------
function data_history(fid, hist)
% Original header structures
%struct data_history
% { /* off + size */
% char descrip[80]; /* 0 + 80 */
% char aux_file[24]; /* 80 + 24 */
% short int qform_code; /* 104 + 2 */
% short int sform_code; /* 106 + 2 */
% float quatern_b; /* 108 + 4 */
% float quatern_c; /* 112 + 4 */
% float quatern_d; /* 116 + 4 */
% float qoffset_x; /* 120 + 4 */
% float qoffset_y; /* 124 + 4 */
% float qoffset_z; /* 128 + 4 */
% float srow_x[4]; /* 132 + 16 */
% float srow_y[4]; /* 148 + 16 */
% float srow_z[4]; /* 164 + 16 */
% char intent_name[16]; /* 180 + 16 */
% char magic[4]; % int smin; /* 196 + 4 */
% }; /* total=200 bytes */
% descrip = sprintf('%-80s', hist.descrip); % 80 chars from left
% fwrite(fid, descrip(1:80), 'uchar');
pad = zeros(1, 80-length(hist.descrip));
hist.descrip = [hist.descrip char(pad)];
fwrite(fid, hist.descrip(1:80), 'uchar');
% aux_file = sprintf('%-24s', hist.aux_file); % 24 chars from left
% fwrite(fid, aux_file(1:24), 'uchar');
pad = zeros(1, 24-length(hist.aux_file));
hist.aux_file = [hist.aux_file char(pad)];
fwrite(fid, hist.aux_file(1:24), 'uchar');
fwrite(fid, hist.qform_code, 'int16');
fwrite(fid, hist.sform_code, 'int16');
fwrite(fid, hist.quatern_b, 'float32');
fwrite(fid, hist.quatern_c, 'float32');
fwrite(fid, hist.quatern_d, 'float32');
fwrite(fid, hist.qoffset_x, 'float32');
fwrite(fid, hist.qoffset_y, 'float32');
fwrite(fid, hist.qoffset_z, 'float32');
fwrite(fid, hist.srow_x(1:4), 'float32');
fwrite(fid, hist.srow_y(1:4), 'float32');
fwrite(fid, hist.srow_z(1:4), 'float32');
% intent_name = sprintf('%-16s', hist.intent_name); % 16 chars from left
% fwrite(fid, intent_name(1:16), 'uchar');
pad = zeros(1, 16-length(hist.intent_name));
hist.intent_name = [hist.intent_name char(pad)];
fwrite(fid, hist.intent_name(1:16), 'uchar');
% magic = sprintf('%-4s', hist.magic); % 4 chars from left
% fwrite(fid, magic(1:4), 'uchar');
pad = zeros(1, 4-length(hist.magic));
hist.magic = [hist.magic char(pad)];
fwrite(fid, hist.magic(1:4), 'uchar');
return; % data_history
|
github
|
sunhongfu/scripts-master
|
pocs.m
|
.m
|
scripts-master/cs-phase/_src/_PF/pocs.m
| 32,075 |
utf_8
|
7902088f7cb0a941557fee7fc7ec700d
|
function [im, kspFull] = pocs( ksp, iter, watchProgress )
%Partial-Fourier Reconstruction with POCS
%
% [im, kspFull] = pocs( kspIn, iter, watchProgr )
%
% === Input ===
%
% kspIn: Reduced Cartesian MRI Data-Set
% Any dimension may be reduced,
% but only one reduction dim. is allowed due to Physics/Math.
%
% Allowed shapes for kspIn are...
% ... Ny x Nx
% ... Nc x Ny x Nx
% ... Nc x Ny x Nx x Nz
%
% With Nc == number of receive Channels / Coils.
%
% kspIn can either be a zero-padded array, so the partial Fourier property is obvious.
% Or kspIn can be the measured data only, then we try to find k-space centre automagically
% and create a zero-padded array with the full size, first.
% Errors are however more likely to occur in the latter case.
%
%
% iter: No. of iterations
% (optional) default: iter = 20
% Try on your own if larger iter improves your results!
%
% watchProgr: true/false; Whether the progress of the reconstruction should
% (optional) be monitored in an image window.
% In 3D data, only the central partition will be shown.
%
%
% === Output ===
%
% im: Reconstructed Images (channels not combined)
%
% kspFull: Reconstructed full k-space data
%
%
%
% === About the code ===
%
% (1) We find out whether input data is
% a) already zero-filled or
% b) the pure asymmetric dataset, only
%
% If b) is true, we zero-fill the data ourselves, which means we have to
% determine the dimension first, in which the partial Fourier reduction was done.
% We therefor find the position of the max. intensity in k-space which should
% be identical to k-space centre. If the k-space centre is different from the
% centre of the matrix, we know the partial Fourier dimension.
% We then enlarge the matrix to its desired full size and fill the new part
% with zeros.
% If a) was true, finding the partial Fourier dimension is easy:
% It is the dimension with all the zeros. :-)
%
% (2) We create one low resolution image per channel/coil:
%
% We need a symmetrically sampled part around the central k-space. Think of a
% small stripe of phase encoding lines in the central k-space.
% We only use these symmetric data (setting the rest zero) to reconstruct
% low-resolution images. In order to avoid Gibbs-Ringing, a Hamming-filter
% with the width of the stripe is multiplied with the data.
% Additionally, all the fully sampled dimensions get a Hamming filter, too,
% since we increase SNR, reduce further Gibbs-ringing and do not lose much
% resolution.
%
% (3) The phase of the low-resolution images is saved
%
% POCS uses the fact that k-space data of real objects (no imaginary part)
% have a point symmetry:
% S(-k) = S*(k) with k = (kx, ky, kz)
% Our MRI objects are always complex, but we assume that phase variations
% are due to coil sensitivities and B0-inhomgeneities,
% which are both slowly varying (no high res. required).
% Small-scale phase pertubations will decrease the reconstruction quality.
%
% (4) Reference phase is applied in image space
%
% We...
% ... transform our zero-filled data to image space (IFFT)
% ... remove the phase --> abs(image)
% ... set the phase of our reference phase map --> image .* exp(1i.*phase)
% ... transform back to k-space (FFT)
% ... re-insert the measured data (self-consistency!)
% ... goto "We..."
%
% Iterating through the above steps fills the missing k-space points
% with reasonable values.
% If the phase varies slowly and there is no aliasing, this works very well.
%
% Aliasing artifacts are very challenging for POCS.
% So try to prevent aliasing in the first place (sufficient Field of View).
% =========================================================================
% Original code by Martin Blaimer
% * changed by Uvo Hoelscher
% * changed by Michael Völker
% -- auto-detect PF dimension
% -- auto-find centre point/line/partition
% -- accept zerofilled or "pure" data
% -- for multichannel or plain 2D data (single-channel)
% -- 2D and 3D
% -- error handling
% -- comments, comments, comments
% -- added option to monitor progress
% -- moved code to seperate functions
% -- smooth transition between acquired signal and
% reconstructed data
%
% Problems? Suggestions?
% --> [email protected]
% =========================================================================
% ( ===================================================================
% Input Handling
%
if ~exist( 'ksp', 'var' ) || isempty(ksp) || ~isnumeric(ksp)
error('pocs:input', 'First input must be Cartesian k-space data.')
end
if ~exist('iter','var') || isempty(iter) || numel(iter) ~= 1 || ~isnumeric(iter)
iter = 20;
end
if ~exist('watchProgress','var') || isempty(watchProgress) || numel(watchProgress) ~= 1 || ~isfinite(watchProgress)
watchProgress = false;
else
watchProgress = logical( watchProgress );
end
Ndim = ndims( ksp );
if Ndim > 4 || Ndim < 2
error('pocs:shape','First input ''kspace'' should have one of these shapes:\n\n\t... Ny x Nx\n\t... Nc x Ny x Nx\n\t... Nc x Ny x Nx x Nz')
end
if Ndim == 2 % Ny x Nx
ksp = reshape( ksp, [1 size(ksp)] ); % 1 x Ny x Nx --> now we have one channel...
wasAddedCoilDim = true;
Ndim = 3;
else
wasAddedCoilDim = false;
end
% read the properties of the data
sz = size( ksp );
sz = sz(2:end); % the (k-)spatial size of the array (i.e. without channels)
prec = class( ksp ); % single or double precision?
% ) ===================================================================
% First: Check the sampling pattern (which parts of input are actually data?)
smplPtrn = reshape( sum(abs(ksp),1) ~= 0, sz); % Ny x Nx x Nz
% ( ===================================================================
% If input data is not yet zero-filled, do it here
%
if nnz(smplPtrn) == numel(smplPtrn) % only the sampled data were passed / |N|umber of |N|on |Z|ero elements
[ ksp, pfDim, isUpper, isLower, Nsmp ] = zerofillPFdim( ksp, wasAddedCoilDim );
sz = size( ksp );
sz = sz(2:end); % ignore channels
else
[ pfDim, isUpper, isLower, Nsmp ] = detectPFdim( smplPtrn, wasAddedCoilDim );
end
clear smplPtrn
% ) ===================================================================
if numel(sz) < 3
sz(3) = 1;
end
Ny = sz(1);
Nx = sz(2);
Nz = sz(3);
% ( ===================================================================
% Handle ugly problems.
%
if ~isUpper && ~isLower
error('pocs:UnknownErrorFound', 'I thought we are partial Fourier, but things seem to make no sense... :-(')
end
% ) ===================================================================
% =====================================================================
%
% We can now be sure to operate with zero-padded data.
%
% =====================================================================
% initialize a cell of subscripts
subs = { ':', ':', ':', ':' }; % all channels / all Ny / all Nx / all Nz
% If the first entries are zero-filled (instead of the trailing ones),
% flip the entries so we can treat them as if we pf'ed the first half of kspace.
if isLower
subs{pfDim+1} = sz(pfDim):-1:1; % ...esreveR
ksp = ksp(subs{:}); % !ecaps-k si sihT
subs{pfDim+1} = 1:sz(pfDim); % lalala, we didn't do anything...
end
% Find out which point is in the centre and which indices belong to the
% symmetrically sampled part of k-space.
[ centreLine, idxSym ] = findSymSampled( ksp, pfDim, Nsmp );
szSym = numel( idxSym ); % 2 * (Nsmp - centreLine) + 1
if isUpper
% fprintf('Using %g points around point %g\n', szSym, centreLine );
else
% fprintf('Using %g points around point %g\n', szSym, sz(pfDim)-centreLine+1 );
end
% ( ===================================================================
% build up a symmetric low-pass filter
%
filter = cast( 1, prec );
for d = 1:Ndim-1
reshRule = ones(1,Ndim); % how the filter will be reshaped
if d ~= pfDim % Each standard dimension gets a simple low-pass filter
filt1D = hamming( sz(d), 'periodic' );
else % our partial Fourier dimension gets an extra nice filter
% create a narrow filter and remove everything else
filt1D = zeros(sz(d), 1, prec); % full-size filter
tmp = hann( szSym + 2, 'symmetric' ); % a very narrow window
filt1D(idxSym) = tmp(2:end-1); % cut out the zeros at the edges (we have data there!)
% take a look:
%figure, plot(filt1D)
end
% reshape the filter according to the dimension it represents
reshRule(d+1) = sz(d);
filt1D = reshape( filt1D, reshRule );
filter = bsxfun( @times, filter, filt1D ); % iteratively build up a multidimensional filter
end
% ) ===================================================================
% Apply the low-pass filter
kspLowRes = bsxfun( @times, filter, ksp);
clear filt1D filter reshRule idxSym
% ( ===================================================================
% prerequisites prior to the iteration loop
%
% Set everything up here, do computations that you don't have
% to do in the loop, remove no longer needed variables...
%
% fftshift everything once before and after for-looping
% => less overhead during iteration
ksp = cmshiftnd( ksp, [0 sz/2] );
kspLowRes = cmshiftnd( kspLowRes, [0 sz/2] );
% reorder arrays such that the fft-dimensions come first
% => faster memory access
ksp = permute( ksp, [2 3 4 1] ); % Ny x Nx x Nz x Nc
kspLowRes = permute( kspLowRes, [2 3 4 1] ); %
subs = { subs{2}, subs{3}, subs{4}, subs{1} };
% calc. initial image and the reference phase map
im = fft( fft( fft( conj(ksp), [], 1), [], 2), [], 3); % im's phase is wrong now, but we only want it's abs() to be correct
phase = ifft(ifft(ifft( kspLowRes, [], 1), [], 2), [], 3);
phase = exp(1i * angle(phase));
% We use a trick in the loop to avoid using ifft (fft is faster).
% We only need to calculate the factor 1/N ourselves, with N = prod(sz)
phase = phase ./ prod(sz); % 1/N is absorbed inside the phase array, once
% create image with calculated phasemap from low res image
im = abs(im) .* phase;
% In the loop, we want to know where we have to copy the
% measured data to, so we set the subscript of the pf dimension
% accordingly.
% We have to do this due to the ifftshift'ing above.
tmp = false( 1, sz(pfDim));
tmp(1:Nsmp) = true;
subs{pfDim} = find(ifftshift(tmp));
% release RAM
clear tmp kspLowRes
% only keep the acquired data in memory
ksp = ksp(subs{:});
% ) ===================================================================
% Helpers for pretty-printing:
% Such a mess for such beautiful output!
b = repmat('=',1,80);
progress_str = 'starting POCS loop...';
% fprintf( '%s\n%s\n%s %s', b, b(1), b(1), progress_str )
edging = sprintf( '\n%s\n%s', b(1), b );
% fprintf( edging )
% ( ===================================================================
% iterative reconstruction POCS
%
tic
for ii = double(~watchProgress) : iter
if ii > 0
% Fourier transform the image to k-space
im = fft(fft(fft( im ,[],1),[],2),[],3); % "im" is a really bad variable name now
% but we save a lot of RAM with this
% Data Consistency:
% insert original data where we have them
im(subs{:}) = ksp; % "im" is still our reconstructed k-space signal
% Fourier transform into image domain
im = conj( im );
im = fft(fft(fft( im ,[],1),[],2),[],3); % Now, "im" is an image again.
% create image with calculated phasemap from low res image
im = abs(im) .* phase;
prevLength = numel(progress_str) + numel(edging);
t = toc;
ETA = (t./ii) * iter - t;
progress_str = sprintf( 'Iteration %g/%g, in %g s, ETA: %g s...', ii, iter, t, ETA );
% fprintf([repmat('\b',1,prevLength) '%s' '%s'], progress_str, edging );
end % if ii > 0
% a rough way to monitor the progress
%
if watchProgress
tmp = ifftshift(sqrt(sum(abs(im(:,:,1,:).^2),4))); % due to fftshift(), the 1st partition is the central one
maxRange = sort( tmp(:), 'descend' );
maxRange = maxRange( ceil(0.05 * numel(maxRange)) ); % ignore the "hottest" 5%
if ~exist('pic','var')
pic = [tmp tmp zeros(size(tmp),prec)];
diffScale = 1;
else
delta = abs( pic(:,Nx+(1:Nx)) - tmp );
diffScale = 0.5 * maxRange / median( delta(:) );
pic(:, Nx+(1:Nx)) = tmp;
pic(:,2*Nx+(1:Nx)) = diffScale * delta;
clear delta
end
figure(999)
imagesc( pic, [0 maxRange ] )
title(sprintf('\\bfiteration %g\ninitial | current | abs(previous - current) × %g', ii, diffScale ))
axis image
colormap(gray(256))
drawnow
clear tmp
%if Nz == 1 % little pause for 2D (too fast otherwise)
% pause(2 / iter)
%end
end
end % for ii = 1:iter
% fprintf([repmat('\b',1, numel(progress_str) + numel(edging)) 'POCS done! (%g s)' '%s\n\n'], t, edging );
% ) ===================================================================
clear phase pic
% ( ===================================================================
% The main part is over. Time for some thoughts.
%
% We began with a dataset that had fewer data samples than would be
% necessary for an unambiguous image reconstruction. As a consequence,
% an infinite number of images corresponds to the acquired data.
% The above iteration picks that single image whose abs() fits the data
% AND whose phase corresponds to the low-resolution phase, obtained
% using the symmetric part of the data.
%
% Viewed in k-space, there is almost always a severe edge at the border
% between acquired and interpolated data, which is due to imperfections
% in the assumptions made.
% Namely, phase often has some high frequency components which cannot be
% accounted for in the low-resolution map. Additionally, there is noise
% and we may have changing contrast or trajectory errors in our MRI
% sequence.
%
% ^
% | A A A A A A A A \
% | A A A A A A A A
% | A A A A A A A A acquired signal
% k2 | A A A A A A A A
% | A A A A A A A A /
% | I I I I I I I I \
% | I I I I I I I I interpolated data
% | I I I I I I I I /
% ----------------->
% k1
%
% Empirically, it should be wise to create a smoother transition from
% the acquired part of the signal to the interpolated data.
%
Ntrans = floor( (szSym-1)/3 ); % width of the transition zone
% Create subscripts where we intend to keep the measured data, only.
tmp = false( 1, sz(pfDim));
tmp(1:Nsmp-Ntrans) = true;
subsPure = subs;
subsPure{pfDim} = find(ifftshift(tmp));
% Create subscripts where we want to have a smooth transition between
% measured and phase-corrected data.
subsTrans = subs;
subsTrans{pfDim} = setdiff( subs{pfDim}, subsPure{pfDim} );
% build a filter for the transition:
tmp = hann( 2*Ntrans+3, 'symmetric');
filterTrans = tmp( Ntrans+3 : end-1 );
filterTrans = reshape( filterTrans, [ ones(1,pfDim-1) Ntrans 1] );
% Seperate data in unfiltered part and transition zone.
tmp = zeros( size(im), prec );
tmp(subs{:}) = ksp;
kspPure = tmp(subsPure{:});
kspTrans = tmp(subsTrans{:});
clear tmp ksp
im = fft(fft(fft( im ,[],1),[],2),[],3); % "im" becomes k-space signal, again
im(subsPure{:}) = kspPure; % strict data consistency for Nsmp-Ntrans samples
im(subsTrans{:}) = bsxfun( @times, filterTrans, kspTrans ) ...
+ bsxfun( @times, 1-filterTrans, im(subsTrans{:}) );
clear subsPure subsTrans filterTrans kspPure kspTrans
if nargout > 1
kspFull = im;
else
kspFull = double.empty([sz 0]); % kspFull exists, but no memory required
end
im = ifft(ifft(ifft( im ,[],1),[],2),[],3); % "im" is an image, again
% ) ===================================================================
% ( ===================================================================
% Undo the prerequisites (--> postrequisites???)
%
% undo the permutations
im = permute( im, [4 1 2 3] );
kspFull = permute( kspFull, [4 1 2 3] );
subs = { subs{4}, subs{1}, subs{2}, subs{3} };
% undo the fftshifts
im = cmshiftnd( im, [0 sz/2] );
kspFull = cmshiftnd( kspFull, [0 sz/2] );
% undo flipping
if isLower
subs{pfDim+1} = sz(pfDim):-1:1;
im = im(subs{:});
kspFull = kspFull(subs{:});
end
% ) ===================================================================
if wasAddedCoilDim % we initially reshaped a simple 2D raw data matrix to be of size 1 x Ny x Nx
im = reshape( im, Ny, Nx, [] );
kspFull = reshape( kspFull, Ny, Nx, [] );
end
end % of pocs()
% =========================================================================
% =
% SWAPPED CODE =
% =
% =========================================================================
function [ ksp, pfDim, isUpper, isLower, Nsmp ] = zerofillPFdim( ksp, wasAddedCoilDim )
% Only the acquired data were passed and we have to find the asymmetric
% dimension. Then we increase the size along this dimension and pad with 0.
Ndim = ndims( ksp ) - 1; % one dimension was for the channels
sz = size( ksp );
sz = sz( 2:end ); % ignore channel dimension
Nc = size( ksp, 1 );
prec = class( ksp );
% init some helper variables
pfDim = 0; % partial Fourier reduction dimension
isUpper = false;
isLower = false;
isPartialFourier = false(Ndim,1);
% ( ===============================================================
% autodetect the Partial Fourier dimension
%
for d = 1:Ndim
centre = floor( sz(d)/2 ) + 1;
tmp = squeeze( sum(abs(ksp),1) );
for d2 = 1:Ndim
if d2 ~= d
tmp = max(tmp,[],d2); % keep only the maximum of non-partial data points
end
end
[ dummy, maxPos(d) ] = max( tmp(:) ); %#ok <-- don't use "~", for compatibility
if abs(maxPos(d) - centre) >= 2 % significant asymmetry ==> partial Fourier acquisition
isPartialFourier(d) = true;
pfDim = d;
Nsmp = sz(d);
isUpper = maxPos(d) > centre; % Did we sample the upper matrix part, so the lower part is missing...
isLower = maxPos(d) < centre; % ... or are the first data points missing (e.g. asymmetric echo)?
end
end % for d = 1:Ndim
%
% ) ===== (PF dim detection) ======================================
switch nnz(isPartialFourier) % |N|umber of |N|on |Z|ero elements
case 0
error( 'pocs:NoPfDim', 'No partial Fourier dimension found.' )
case 1
% fprintf( 'Found partial Fourier along array dimension %d\n', pfDim + ~wasAddedCoilDim )
otherwise
error( 'pocs:TooManyPfDims', 'Partial Fourier only allowed in 1 dimension, but %g were found!', nnz(isPartialFourier) )
end
if pfDim == 0 % our init value above
error('zerofillPF:NoPF','No partial Fourier property found!')
end
% initialize a cell of subscripts
subs = { ':', ':', ':', ':' }; % all channels / all Ny / all Nx / all Nz
c = maxPos(pfDim);
if isUpper
sz(pfDim) = 2 * (c - mod(c,2)); % determine the blown-up size we want to achieve
subs{pfDim+1} = 1:Nsmp;
elseif isLower
sz(pfDim) = 2 * (Nsmp - c + 1);
c = floor( sz(pfDim)/2 ) + 1;
sz(pfDim) = sz(pfDim) + 2*~mod(c,2); % A hack for Stefan's data... keep an eye on this!
subs{pfDim+1} = (1:Nsmp) + (sz(pfDim)-Nsmp);
else
error( 'zerofillPF:PFdimNotClassified', 'Could not tell how partial Fourier was implemented.' )
end
% do the zerofilling
tmp = zeros( [Nc sz], prec );
tmp(subs{:}) = ksp;
ksp = tmp;
end % of zerofillPFdim()
function [ pfDim, isUpper, isLower, Nsmp ] = detectPFdim( smplPtrn, wasAddedCoilDim )
% User passed already zero-padded data. This was nice, now it's easy
% to find the partial Fourier dimension!
Ndim = ndims( smplPtrn );
sz = size( smplPtrn );
% init some helper variables
pfDim = 0; % partial Fourier reduction dimension
isUpper = false;
isLower = false;
isPartialFourier = false( Ndim, 1 );
% ( ===============================================================
% Determine if this is a zerofilled partial Fourier measurement
% and along which dimension the data is reduced.
%
% smplPtrn in Partial Fourier looks like this:
%
% ^
% | 1 1 1 1 1 1 1 1 ---> sampling pattern is the same
% | 1 1 1 1 1 1 1 1 for all k1 points
% | 1 1 1 1 1 1 1 1
% k2 | 1 1 1 1 1 1 1 1 i.e. for programming:
% | 1 1 1 1 1 1 1 1 smplPtrn == repmat( smplPtrn(:,1,1), [1 Nx Nz] )
% | O O O O O 0 0 0
% | O O O O O 0 0 0
% | O O O O O 0 0 0
% ----------------->
% k1
%
for d = 1:Ndim
subs = { ones(1,sz(d)), ... % initialize a cell of subscripts we might be interested in
ones(1,sz(d)), ...
ones(1,sz(d)) };
subs{d} = 1:sz(d); % we ask for all entries in the d'th dimension
idx_d = sub2ind( sz, subs{:} ); % convert to linear array indices
oneCol = smplPtrn( idx_d ); % one column of the d'th dimension
% create a rule how to reshape oneCol
reshRule = ones(1,Ndim);
reshRule(d) = sz(d); % e.g. reshRule = [ 1 1 128 ]
oneCol = reshape( oneCol, reshRule);
% create a rule how to replicate oneCol
repRule = sz;
repRule(d) = 1; % e.g. repRule = [ 256 256 1 ]
% Check if we get the sampling pattern again
% just by replicating oneCol along the other dimensions
isPartialFourier(d) = isequal( smplPtrn, repmat( oneCol, repRule ) );
if isPartialFourier(d)
pfDim = d;
Nsmp = nnz( oneCol ); % how many fully sampled lines do we have?
% Sampled upper or lower part of k-space matrix?
isUpper = isequal( oneCol(:).', [ true( 1,Nsmp) false(1,sz(d)-Nsmp) ]);
isLower = isequal( oneCol(:).', [ false(1,sz(d)-Nsmp) true( 1,Nsmp) ]);
end
end
% ) ===============================================================
switch nnz(isPartialFourier) % |N|umber of |N|on |Z|ero elements
case 0
error( 'pocs:NoPfDim', 'No partial Fourier dimension found.' )
case 1
% fprintf( 'Found partial Fourier along array dimension %d\n', pfDim + ~wasAddedCoilDim )
otherwise
error( 'pocs:TooManyPfDims', 'Partial Fourier only allowed in 1 dimension!' )
end
end % of detectPFdim()
function [ centreLine, idxSym ] = findSymSampled( ksp, pfDim, Nsmp )
Ndim = ndims( ksp ) - 1; % one for channels
sz = size( ksp );
sz = sz(2:end);
% autodetect the central k-space line
%if ~exist('centreLine', 'var') || isempty(centreLine)
tmp = squeeze( sum(abs(ksp),1) );
for d = 1:Ndim
if d ~= pfDim
tmp = max(tmp,[],d); % keep only the maximum of non-partial data points
end
end
[ dummy, centreLine] = max( tmp(:) ); %#ok the central line has the max intensity
%end
% calculate the size of the symmetric part and the full dataset
startSym = centreLine - (Nsmp - centreLine); % start of our symmetric sampling
endSym = centreLine + (Nsmp - centreLine); % end of symmetric part
idxSym = startSym : endSym;
if any(idxSym < 1) || any(idxSym > sz(pfDim))
error( 'pocs:BadDataProperty' , 'Symmetric part of k-space out of bounds.\nThe maximum k-space intensity is at index %g whereas it should be centred => near %g.\nThe way, zerofilling was done is probably wrong.\nCheck your input k-space.', centreLine, round(sz(pfDim)/2) )
end
end % of findSymmetricSampled()
function x = cmshiftnd( x, shifts)
%Function to circularly shift N-D arrays
if nargin < 2 || all(shifts(:) == 0)
return % no shift
end
sz = size( x );
numDims = ndims(x); % number of dimensions
idx = cell(1, numDims); % creates cell array of empty matrices,
% one cell for each dimension
for k = 1:numDims
m = sz(k);
p = ceil(shifts(k));
if p < 0
p = m + p;
end
idx{k} = [p+1:m 1:p];
end
% Use comma-separated list syntax for N-D indexing.
x = x(idx{:});
end % of cmshiftnd()
% Avoid the need for the signal toolbox and implement
% hamming() and hann() manually:
%
function w = hamming( N, symFlag )
%Hamming window
%
% w = hamming(L) returns an L-point symmetric Hamming window in the column vector w.
% L should be a positive integer.
%
% The coefficients of a Hamming window are computed from the following equation:
%
% w(n) = 0.54 + 0.46 * cos(2*pi*n/N), 0 <= n <= N
%
%
% w = hamming( L, 'symFlag') returns an L-point Hamming window using the window sampling
% specified by 'symFlag', which can be either 'periodic' or 'symmetric' (the default).
% The 'periodic' flag is useful for DFT/FFT purposes, such as in spectral analysis.
% The DFT/FFT contains an implicit periodic extension and the periodic flag enables a signal
% windowed with a periodic window to have perfect periodic extension.
% When 'periodic' is specified, hamming computes a length L+1 window and returns the first L points.
% When using windows for filter design, the 'symmetric' flag should be used.
%
% --> http://www.mathworks.de/de/help/signal/ref/hamming.html
% --> https://de.wikipedia.org/wiki/Hamming-Fenster
% implemented by [email protected], 2012
if ~exist( 'N', 'var' ) || isempty(N) || numel(N) ~= 1 || ~isnumeric(N) || ~isfinite(N) || N < 1 || floor(N) ~= N
error( 'hamming:badSize', 'Window lenght must be a positive integer.' )
end
if ~exist( 'symFlag', 'var' ) || isempty(symFlag)
symFlag = 'symmetric';
end
if N == 1
w = 1;
return
end
switch symFlag
case 'symmetric'
L = N-1;
case 'periodic'
L = N;
otherwise
error('hamming:symFlag', 'Unknown symmetry flag. Try ''symmetric'' (default) or ''periodic''.')
end
w = (0:N-1) - L/2;
w = 0.54 + 0.46 * cos(2*pi * w(:)./L);
end % of hamming()
function w = hann( N, symFlag )
%von-Hann (Hanning) window
%
% w = hann(L) returns an L-point symmetric Hann window in the column vector w.
% L must be a positive integer.
%
% The coefficients of a Hann window are computed from the following equation:
%
% w(n) = 0.5 * (1 + cos(2*pi*n/N)), 0 <= n <= N
%
% The window length is L = N+1.
%
% w = hann(L,'sflag') returns an L-point Hann window using the window sampling specified by 'sflag',
% which can be either 'periodic' or 'symmetric' (the default). The 'periodic' flag is useful for DFT/FFT purposes,
% such as in spectral analysis.
% The DFT/FFT contains an implicit periodic extension and the periodic flag enables a signal windowed
% with a periodic window to have perfect periodic extension.
% When 'periodic' is specified, hann computes a length L+1 window and returns the first L points.
% When using windows for filter design, the 'symmetric' flag should be used.
%
% --> http://www.mathworks.de/de/help/signal/ref/hann.html
% --> https://de.wikipedia.org/wiki/Hann-Fenster
% implemented by [email protected], 2012
if ~exist( 'N', 'var' ) || isempty(N) || numel(N) ~= 1 || ~isnumeric(N) || ~isfinite(N) || N < 1 || floor(N) ~= N
error( 'hann:badSize', 'Window lenght must be a positive integer.' )
end
if ~exist( 'symFlag', 'var' ) || isempty(symFlag)
symFlag = 'symmetric';
end
if N == 1
w = 1;
return
end
switch symFlag
case 'symmetric'
L = N-1;
case 'periodic'
L = N;
otherwise
error('hann:symFlag', 'Unknown symmetry flag. Try ''symmetric'' (default) or ''periodic''.')
end
w = (0:N-1) - L/2;
w = 0.5 * ( 1 + cos(2*pi * w(:)./L) );
end % of hann()
|
github
|
sunhongfu/scripts-master
|
grappa.m
|
.m
|
scripts-master/cs-phase/_src/_grappa/grappa.m
| 2,384 |
utf_8
|
ed282c80f1a0002da0cc2c40499631bd
|
% grappa.m
% [email protected]
%
% inputs:
% data - (nc, nx, ny, nz, m]) complex undersampled k-space data
% will also loop across extra dimension m
% calib - (nc, cx, cy, cz) complex calibration k-space data
% R - [Rx, Ry] or [Rx, Ry, Rz] acceleration factors
% kernel - [kx, ky] or [kx, ky, kz] kernel size
% tol - singular value cutoff threshold for kernel weight
% training, relative to s(1), defaults to pinv default
%
% output:
% recon - (nc, nx, ny, nz) complex reconstructed k-space data
function data = grappa(data, calib, ARG)
data = permute(data ,[3,1,2,4]);
calib = permute(calib,[3,1,2]);
R = ARG.iPAT.factor;
kernel = ARG.iPAT.kernel;
tol = ARG.iPAT.tol;
%% Use default pinv tolerance if not supplied
if tol > 0
pinv_reg = @(A)pinv(A, tol*norm(A,2));
else
pinv_reg = @pinv;
end
%% Determine whether this is a 1D or 2D GRAPPA problem
if numel(R) == 2
R(3) = 1;
end
if numel(kernel) == 2
kernel(3) = 1;
end
for iMe = 1:size(data,4)
%% extract one measument
tmp = squeeze(data(:,:,:,iMe));
%% Prepare masks and zero-pad data
if iMe == 1
pad = floor(R.*kernel/2);
mask = padarray(tmp~=0, [0 pad]);
end
tmp = padarray(tmp, [0 pad]);
%% Loop over all possible kernel types
for type = 1:prod(R(2:end))-1
if iMe == 1
% Collect source and target calibration points for weight estimation
[src, trg] = grappa_get_indices(kernel, true(size(calib)), pad, R, type);
% Perform weight estimation
weights(:,:,type) = calib(trg)*pinv_reg(calib(src));
end
% Collect source points in under-sampled data for weight application
[src, trg] = grappa_get_indices(kernel, mask, pad, R, type);
% Apply weights to reconstruct missing data
tmp(trg) = squeeze(weights(:,:,type))*tmp(src);
end
%% Un-pad reconstruction to get original image size back
data(:,:,:,iMe) = tmp(:,pad(1)+1:size(tmp,2)-pad(1), pad(2)+1:size(tmp,3)-pad(2), pad(3)+1:size(tmp,4)-pad(3),:);
clear tmp
end
%% Permute for compatibility with other code
data = permute(data,[2,3,1,4]);
|
github
|
sunhongfu/scripts-master
|
grappa_get_indices.m
|
.m
|
scripts-master/cs-phase/_src/_grappa/grappa_get_indices.m
| 2,774 |
utf_8
|
0692576896f6fc13f24d3be9e43c8002
|
% grappa_get_indices.m
% [email protected]
%
% inputs:
% kernel - [sx, sy, sz] kernel size in each dimension
% samp - (c, nx, ny, nz) sampling mask, true(size(calib))
% pad - [pad_x, pad_y, pad_z] size of padding in each direction
% type - (scalar, must be < R) indicates which of the R(2)*R(3)-1 kernels
% you are trying to index over
% offset - additional index offset that gets added to src,trg
%
% output:
% src - linear indices for all source points (c*sx*sy*sz, all possible targets)
% trg - linear indices for all the target points (c, all possible targets)
function [src, trg] = grappa_get_indices(kernel, samp, pad, R, type, offset)
% Offset is optional, 0 by default
if nargin < 6
offset = 0;
end
% Get dimensions
[nc,dx,dy,dz] = size(samp);
% Make sure the under-sampling is in y and z only
% There are a few things here that require that assumption
if R(1) > 1
error('x-direction must be fully sampled');
end
% Make sure the type parameter makes sense
% It should be between 1 and R(2)*R(3)-1 (inclusive)
if type > prod(R(2:3))-1
error('Type parameter is inconsistent with R');
end
% Find the limits of all possible target points given padding
kx = 1+pad(1):dx-pad(1);
ky = 1+pad(2):dy-pad(2);
kz = 1+pad(3):dz-pad(3);
%% Compute indices for a single coil
% Find relative indices for kernel SOURCE points
mask = false(dx,dy,dz);
mask(1:R(1):R(1)*kernel(1), 1:R(2):R(2)*kernel(2), 1:R(3):R(3)*kernel(3)) = true;
k_idx = reshape(find(mask),[],1);
% Find the index for the desired TARGET point (depends on type parameter)
mask = false(dx,dy,dz);
[yy,zz] = ind2sub(R(2:3),type+1);
mask(R(1)*ceil(kernel(1)/2), R(2)*(ceil(kernel(2)/2)-1)+yy, R(3)*(ceil(kernel(3)/2)-1)+zz) = true;
k_trg = reshape(find(mask),[],1);
% Subtract the target index from source indices
% to get relative linear indices for all source points
% relative to the target point (index 0, target position)
k_idx = k_idx - k_trg;
% Find all possible target indices
mask = false(dx,dy,dz);
mask(kx,ky,kz) = squeeze(circshift(samp(1,kx,ky,kz),[0 0 yy-1 zz-1]));
trg = reshape(find(mask),1,[]);
% Find all source indices associated with the target points in trg
src = bsxfun(@plus, k_idx, trg);
%% Now replicate indexing over all coils
% Final shape of trg should be (#coils, all possible target points)
trg = bsxfun(@plus, (trg-1)*nc+1, (0:nc-1)') + offset;
% Final shape of src should be (#coils*sx*sy, all possible target points)
src = bsxfun(@plus, (src(:)'-1)*nc+1, (0:nc-1)');
src = reshape(src,[], size(trg,2)) + offset;
|
github
|
sunhongfu/scripts-master
|
Gsparse.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/Gsparse.m
| 7,162 |
utf_8
|
313f033569655fb4925e3490b7ae7f5a
|
function ob = Gsparse(arg1, varargin)
%function ob = Gsparse(file.wtf | sparse | cell, options)
%
% Construct Gsparse object, either from a sparse matrix itself,
% or from the arguments that would be passed to matlab's sparse() command,
% or from an Aspire binary .wtf file.
%
% The purpose of this object is to overcome some annoying limitations of
% matlab's sparse() function and sparse datatype. In particular, this function
% allows single precision arguments (that are converted silently to doubles,
% as long as matlab continues to insist on that) instead of the useless
% error message provided by our good friends at Mathworks. And you can do
% multiplication of a Gsparse object times a non-double-precision vector
% (which is silently upgraded to doubles), which Matlab does not support.
%
% More substantively, this object also supports the "multidimensional"
% constructs needed in imaging problems. (support mask, subsets, etc.)
%
% This just uses an ordinary Matlab sparse matrix for the core!
% See Gsparse_test.m for example usage.
%
% You create an system object by calling:
% G = Gsparse(file)
% and then you can use it thereafter by typing commands like
% y = G * x.
%
% in
% arg1 char | cell | sparse sparse matrix (usual case)
% or cell array of sparse() arguments
% or filename of an aspire .wtf
% options
% mask [idim] logical support mask
% idim [1,ndim_in] input dimensions: nx,ny,nz etc.
% odim [1,ndim_out] output dimensions: nb,na etc.
% chat verbosity
%
% out
% ob [nd,np] nd = prod(odim), np = sum(mask(:))
% so it is already "masked"
%
% Copyright 2005-6-16, Jeff Fessler, The University of Michigan
if nargin == 1 & streq(arg1, 'test'), Gsparse_test, return, end
if nargin < 1, help(mfilename), error(mfilename), end
% defaults
arg.mask = [];
arg.idim = [];
arg.odim = [];
arg.chat = 0;
arg.blocks = {}; % place to store blocks of G for subset algorithms
arg = vararg_pair(arg, varargin);
if ~isempty(arg.mask) && ~islogical(arg.mask)
error 'mask must be logical'
end
%
% cell array of arguments to sparse()
%
if iscell(arg1)
if length(arg1) >= 3 % i, j, s ...
arg1{3} = double(arg1{3}); % trick: double values for s
end
arg1 = sparse(arg1{:});
end
%
% if input is an Aspire .wtf file
%
if ischar(arg1)
arg.file = arg1;
if ~isempty(arg.idim) | ~isempty(arg.odim)
error 'idim / odim should not be given for .wtf'
end
[arg.G arg.idim(1) arg.idim(2) arg.odim(1) arg.odim(2)] = ...
wtfmex('load', arg.file);
% default mask from .wtf
if isempty(arg.mask)
tmp = full(sum(arg.G) > 0);
arg.mask = reshape(tmp, arg.idim);
end
arg.G = arg.G(:,arg.mask(:));
%
% if input is a sparse matrix
%
elseif issparse(arg1)
arg.G = arg1;
if isempty(arg.idim)
if ~isempty(arg.mask)
arg.idim = size(arg.mask);
else
warning 'idim not given for sparse matrix!'
arg.idim = [size(arg.G,2) 1];
end
end
if isempty(arg.mask)
arg.mask = true(arg.idim); % default mask is all
elseif length(arg.idim) ~= ndims(arg.mask) | ...
any(arg.idim ~= size(arg.mask))
disp(arg), error 'bad mask size'
end
if isempty(arg.odim)
warning 'odim not given for sparse matrix!'
arg.odim = [size(arg.G,1) 1];
elseif prod(arg.odim) ~= size(arg.G,1)
error 'bad row dimension'
end
if sum(arg.mask(:)) ~= size(arg.G,2)
if size(arg.G,2) == numel(arg.mask)
arg.G = arg.G(:, arg.mask(:)); % trick: compact size
else
disp(arg), error 'bad G size'
end
end
else
error 'input must be cell or filename or sparse matrix'
end
%
% build Fatrix object
%
arg.nd = prod(arg.odim);
arg.np = sum(arg.mask(:));
ob = Fatrix([arg.nd arg.np], arg, 'caller', mfilename, ...
'forw', @Gsparse_forw, 'back', @Gsparse_back, ...
'block_setup', @Gsparse_block_setup, ...
'mtimes_block', @Gsparse_mtimes_block, ...
'abs', @Gsparse_abs, 'power', @Gsparse_power);
%
% Gsparse_forw(): y = G * x
%
function y = Gsparse_forw(arg, x)
% if needed, convert array to concise column
flag_array = 0;
if size(x,1) ~= arg.np
flag_array = 1;
x = reshape(x, numel(arg.mask), []); % [*N,*L]
x = x(arg.mask(:),:); % [np, *L]
end
if isa(x, 'double')
y = arg.G * x; % [nd, *L]
else
y = arg.G * double(x); % [nd, *L]
if ~issparse(y)
y = single(y);
end
end
if flag_array
y = reshaper(y, arg.odim); % [(M),*L]
end
%
% Gsparse_back(): x = G' * y
%
function x = Gsparse_back(arg, y)
flag_array = 0;
if size(y,1) ~= arg.nd
flag_array = 1;
y = reshape(y, arg.nd, []); % [nd,*L]
end
if isa(y, 'double')
x = (y' * arg.G)'; % [np,*L] trick: runs faster this way!
else
x = (double(y)' * arg.G)'; % [np,*L]
if ~issparse(x)
x = single(x);
end
end
if flag_array
x = embed(x, arg.mask); % [(N),*L]
end
%
% Gsparse_abs()
%
function ob = Gsparse_abs(ob)
ob.arg.G = abs(ob.arg.G);
%
% Gsparse_block_setup()
% Pre-construct blocks of sparse matrix so that it need not be done
% for every block access. Doubles memory.
%
function ob = Gsparse_block_setup(ob)
nb = prod(ob.arg.odim(1:end-1));
na = ob.arg.odim(end);
ob.arg.blocks = cell(ob.nblock,1);
for iblock=1:ob.nblock
ia = iblock:ob.nblock:na;
ii = outer_sum(1:nb, (ia-1)*nb);
ii = ii(:);
t = ob.arg.G(ii,:); % fix: sparse, but nzmax is too large!
[i j s] = find(t);
if iblock == 1 & length(s) ~= nzmax(t)
% persistent warned
warning 'stupid matlab sparse too big'
end
t = sparse(i, j, s, length(ii), size(ob.arg.G, 2));
ob.arg.blocks{iblock} = t;
end
%
% Gsparse_mtimes_block()
% note: this is not incredibly efficient, but it is mostly for testing anyway.
%
function y = Gsparse_mtimes_block(arg, is_transpose, x, istart, nblock)
if is_transpose
y = Gsparse_mtimes_back(arg, x, istart, nblock);
else
y = Gsparse_mtimes_forw(arg, x, istart, nblock);
end
% old slow way
%nb = prod(arg.odim(1:end-1));
%ii = outer_sum(1:nb, (ia-1)*nb);
% trick: just reuse almost everything in arg
%arg.G = arg.G(ii(:),:);
%
% Gsparse_mtimes_forw()
%
function y = Gsparse_mtimes_forw(arg, x, istart, nblock);
ia = istart:nblock:arg.odim(end); % subset over last dim
% if needed, convert array to concise column
flag_array = 0;
if size(x,1) ~= arg.np
flag_array = 1;
x = reshape(x, numel(arg.mask), []); % [*N,*L]
x = x(arg.mask(:),:); % [np,*L]
end
if isa(x, 'double')
y = arg.blocks{istart} * x; % [nd, *L]
else
y = arg.blocks{istart} * double(x); % [nd, *L]
y = single(full(y));
end
if flag_array
y = reshaper(y, [arg.odim(1:end-1) length(ia)]);
end
%
% Gsparse_mtimes_back()
%
function x = Gsparse_mtimes_back(arg, y, istart, nblock);
ia = istart:nblock:arg.odim(end); % subset over last dim
nd1 = arg.nd * length(ia) / arg.odim(end);
flag_array = 0;
if size(y,1) ~= nd1
flag_array = 1;
y = reshape(y, nd1, []); % [nd1,*L]
end
if isa(y, 'double')
x = full(y' * arg.blocks{istart})'; % [np,*L] trick: runs faster
else
x = full(double(y)' * arg.blocks{istart})'; % [np,*L]
x = single(x);
end
if flag_array
x = embed(x, arg.mask); % [(N),*L]
end
%
% Gsparse_power()
%
function ob = Gsparse_power(ob, sup)
ob.arg.G = ob.arg.G .^ sup;
% fix: this is inefficient to be working with both G and its blocks
if ~isempty(ob.nblock)
for ii=1:ob.nblock
ob.arg.blocks{ii} = ob.arg.blocks{ii} .^ sup;
end
end
|
github
|
sunhongfu/scripts-master
|
ifft_sym.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/ifft_sym.m
| 1,181 |
utf_8
|
01ebf2f01e0379ebb2d3ae4792f996f7
|
function y = ifft_sym(varargin)
%function y = ifft_sym(varargin)
% matlab 7.0 introduced a 'symmetric' option to ifft to handle
% spectra that are (circularly) hermitian symmetric (real signal).
% this glue routine is to provide backward compatibility for matlab 6.5.
% Caution: v7 ifft with 'symmetric' just uses the first half of the spectrum
% along whichever dimension is requested. Here, for pre v7, I just take
% the real part. The difference is neglible in the cases where this
% routine is expected to be used, where the spectrum should be exactly
% symmetric but has slight asymmetry due to numerical precision.
% If the spectrum is severely asymmetric, then "real(ifft())" and
% ifft(..., 'symmetric') will differ substantially. (But one should
% not call this routine in such cases.)
if ~nargin, help(mfilename), error(mfilename), end
if nargin == 1 && streq(varargin{1}, 'test'), ifft_sym_test, return, end
if is_pre_v7
y = ifft(varargin{:});
y = reale(y, 1e-11, 'prompt');
else
y = ifft(varargin{:}, 'symmetric');
end
function y = ifft_sym_test
del = 10^5*eps;
format compact
x1 = [4 2+0i*del 8 2-1i*del]
y1 = ifft(x1)
y2 = ifft_sym(x1)
x2 = fft(y2)
y1 - y2
|
github
|
sunhongfu/scripts-master
|
jf_protected_names.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/jf_protected_names.m
| 2,298 |
utf_8
|
9430f87fc9730771e794a957c0e20697
|
function pn = jf_protected_names
%|function pn = jf_protected_names
%|
%| A serious drawback of the matlab language is that it lacks
%| a protected or local namespace. Every m-file that is in the path
%| is available to all functions (except those in "private" subdirectories).
%| Users who have their own m-files that happen to have the same names as
%| any of the routines in a toolbox like this one will have problems.
%|
%| To try to overcome this limitation, I created this function in late 2009
%| to serve as a repository of simple functions.
%| To use any of these functions, one types something like
%| pn = jf_protected_names;
%| and then one can call the functions using
%| out = pn.fun(arg1, arg2, ...);
%|
%| Copyright 2009-11-21, Jeff Fessler, University of Michigan
pn = strum(struct, { ...
'struct_recurse', @jf_struct_recurse, '()';
'color_order', @jf_color_order, '()';
'diary', @jf_diary, '(file)';
'has_hct2', @jf_has_hct2, '()';
'hct_arg', @jf_hct_arg, '(cg, ig)';
'ind2sub', @jf_ind2sub, '(siz, ind)';
'mid3', @jf_mid3, '(im_3d, [dim])';
'normcdf', @jf_normcdf, '(x, mu, sigma)';
'prctile', @jf_prctile, '(x, p, [dim])';
'case', @jf_case, '(x, v0, v1, ...)';
'test', @jf_test, '()';
});
end % jf_protected_names()
% jf_case()
% its purpose is to act like the '?' operator in C
% jf_case(x, 'value if x is 0', 'value if x is 1', ...)
function out = jf_case(st, x, varargin)
if x+1 > numel(varargin)
fail('x=%d but num=%d', x, numel(varargin))
end
out = varargin{x+1};
end % jf_case()
% jf_diary()
% this version prompts if file exists!
function jf_diary(st, file)
if streq(file, 'off')
diary('off');
return
end
if exist(file, 'file')
fail 'file exists'
else
printm('starting diary for "%s"', file)
diary(file);
end
end % jf_diary()
% jf_ind2sub()
% version with a single matrix output, one dimension per column
function subs = jf_ind2sub(st, Nd, ind)
ind = ind(:);
subs = zeros(numel(ind), numel(Nd));
switch numel(Nd)
case 2
[subs(:,1) subs(:,2)] = ind2sub(Nd, ind);
case 3
[subs(:,1) subs(:,2) subs(:,3)] = ind2sub(Nd, ind);
case 4
[subs(:,1) subs(:,2) subs(:,3) subs(:,4)] = ind2sub(Nd, ind);
otherwise
fail 'not done'
end
end % jf_ind2sub()
% jf_test()
function jf_test(st, varargin)
jf_equal(st.case(1, 2, 3), 3)
end % jf_test()
|
github
|
sunhongfu/scripts-master
|
os_run.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/os_run.m
| 496 |
utf_8
|
b86b9948f9e383a3f5f8d047d0ec9ae0
|
function out = os_run(str)
%|function out = os_run(str)
%| call OS (unix only of course), check for error, optionally return output
if nargin < 1, help(mfilename), error(mfilename), end
if streq(str, 'test'), os_run_test, return, end
[s out1] = unix(str);
if s
fail('unix call failed:\n%s', str)
end
if nargout
out = out1;
end
function os_run_test
printm 'os_run test'
if ~isunix
warn 'os_run works only on unix'
return
end
out = os_run('echo 1+2 | bc');
jf_equal(out, sprintf('3\n'))
|
github
|
sunhongfu/scripts-master
|
interp1_jump.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/interp1_jump.m
| 2,280 |
utf_8
|
b183193c9190a72ea28565ea8def6dba
|
function yi = interp1_jump(xj, yj, xi, varargin)
%function yi = interp1_jump(xj, yj, xi, {arguments for interp1})
% Generalization of matlab's "interp1" to allow xj with repeated values,
% for interpolation of a function that has "jumps" (discontinuities),
% such as is caused by k-edges for mass attenuation coefficients.
% If the first option is 'monodown' then the function is expected to
% be monotone decreasing except for certain jumps that may not correspond
% to xj's with equal values.
% The (remaining) options are passed to 'interp1'.
% Copyright 2004-5-2, Jeff Fessler, The University of Michigan
if nargin == 1 && streq(xj, 'test'), interp1_jump_test, return, end
if nargin < 3, help(mfilename), error(mfilename), end
if length(xj) ~= length(yj), error 'xj and yj have different lengths', end
jjump = find(diff(xj) == 0);
if length(varargin) && streq(varargin{1}, 'monodown')
varargin = {varargin{2:end}};
yjump = find(diff(yj) > 0);
jjump = unique([jjump; yjump]);
end
npiece = 1 + length(jjump);
if npiece == 1
yi = interp1(xj, yj, xi, varargin{:});
return
end
yi = zeros(size(xi));
done = zeros(size(xi));
for ip=1:npiece
if ip == 1
jlist = [1:jjump(1)];
elseif ip == npiece
jlist = [(1+jjump(npiece-1)):length(xj)];
else
jlist = [(1+jjump(ip-1)):jjump(ip)];
end
x = xj(jlist);
y = yj(jlist);
if ip == 1
ilist = find(xi <= max(x));
elseif ip == npiece
ilist = find(min(x) <= xi);
else
ilist = find(min(x) <= xi & xi <= max(x));
end
if isempty(ilist), continue, end
if length(x) > 1
yi(ilist) = interp1(x, y, xi(ilist), varargin{:});
done(ilist) = 1;
elseif length(x) == 1
if any(x == xi(ilist))
yi(ilist) = y(x == xi(ilist));
else
warning 'bug?'
keyboard
end
end
end
% for anything left over, use linear interpolation
if any(~done)
[xj jj] = unique(xj);
yi(~done) = interp1(xj, yj(jj), xi(~done), 'linear');
end
function interp1_jump_test
x = [0 0.5 1 1 2 3 3 4 5];
%x = [0 0.5 1 1.1 2 3 3.1 4 5];
y = [1 0 0 1 1 2 1 2 2];
t = linspace(-0.5,0.5+max(x),1001);
f = interp1_jump(x, y, t, 'cubic', 'extrap');
if im
clf, subplot(211)
plot(x, y, 'o', t, f, '-')
end
x = [0:5];
y = [4 2 1 2 1 0];
f = interp1_jump(x, y, t, 'monodown', 'cubic', 'extrap');
if im
subplot(212)
plot(x, y, 'o', t, f, '-')
end
|
github
|
sunhongfu/scripts-master
|
jf_histn.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/jf_histn.m
| 2,106 |
utf_8
|
8a5e6756705f9e4c239f592b17967eed
|
function [hist center] = jf_histn(data, varargin)
%|function [hist center] = jf_histn(data, varargin)
%|
%| Fast histogram of multidimensional data for equally-spaced bins.
%| todo: use accumarray?
%|
%| in
%| data [N M] data values to be binned (M-dimensional)
%|
%| option
%| 'min' [M] minimum bin values for each dimension (left side)
%| 'max' [M] maximum bin values for each dimension (right side)
%| 'nbin' [M] # of bins for each dimension (default: 100)
%|
%| out
%| hist [[ncent]] histogram values: sum(hist(:)) = N
%| center {ncent} cell array of bin centers for each dimension
%|
%| Copyright 2010-07-31, Jeff Fessler, University of Michigan
if nargin == 1 && streq(data, 'test'), jf_histn_test, return, end
if nargin < 1, help(mfilename), error(mfilename), end
arg.min = [];
arg.max = [];
arg.nbin = [];
arg.chat = 0;
arg = vararg_pair(arg, varargin);
M = size(data,2);
if isempty(arg.nbin)
arg.nbin = 100;
end
if numel(arg.nbin) == 1
arg.nbin = arg.nbin * ones(M,1);
end
for id=1:M
tmp = data(:,id);
if isempty(arg.min)
xmin = min(tmp);
else
xmin = arg.min(id);
end
if isempty(arg.max)
xmax = max(tmp);
else
xmax = arg.max(id);
end
if xmin == xmax
if xmin == 0
xmin = -0.5;
xmax = +0.5;
else
xmin = 0.5 * xmin;
xmax = 1.5 * xmin;
end
end
K = arg.nbin(id);
tmp = (tmp - xmin) / (xmax - xmin); % [0,1]
tmp(tmp < 0) = 0;
tmp(tmp > 1) = 1;
tmp = 1 + tmp * (K-1); % [1 K]
data(:,id) = round(tmp);
if K == 1
center{id} = (xmin + xmax) / 2;
else
center{id} = linspace(xmin, xmax, K);
end
end
[hist hcent] = hist_bin_int(data);
for id=1:M
tmp = hcent{id};
K = arg.nbin(id);
if min(tmp) ~= 1 || max(tmp) ~= K
minmax(tmp)
fail 'todo'
end
end
% test routine
function jf_histn_test
randn('state', 0)
n = 1000;
sig = 5;
rho = 0.6; % correlated gaussian
Cov = sig * [1 rho; rho 1];
tmp = sqrtm(Cov)
data = randn(n, 2) * sqrtm(Cov);
nbin = [30 30]
[hist cent] = jf_histn(data, 'nbin', nbin);
[xs ys] = deal(cent{:});
if im
im plc 1 2
im(1, xs, ys, hist)
axis equal
im subplot 2
plot(data(:,1), data(:,2), '.')
axis equal
end
|
github
|
sunhongfu/scripts-master
|
jf_assert.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/jf_assert.m
| 871 |
utf_8
|
444b53c5605424b42508cd26fa0da635
|
function jf_assert(varargin)
%function jf_assert(command)
% verify that the command (evaluated within caller) returns true.
% if not, print error message.
if nargin < 1, help(mfilename), error(mfilename), end
if nargin == 1 && streq(varargin{1}, 'test'), jf_assert_test, return, end
arg = [varargin{:}]; % handle cases with spaces like 'jf_assert x == y'
[name line] = caller_name;
if isempty(name)
str = '';
else
str = sprintf(' at %d in "%s"', line, name);
end
try
tmp = evalin('caller', arg);
catch
error(['%s was unable to evaluate "%s"' str], mfilename, arg)
end
% note: use isequal, not issame!
if isscalar(tmp) && islogical(tmp)
if ~tmp
fail(['jf_assert of "%s" was untrue' str], arg)
% dbup
% dbstack
% keyboard
end
else
tmp
whos
error(['jf_assert of "%s" did not return logical scalar' str], arg)
end
function jf_assert_test
jf_assert 7 == 7
|
github
|
sunhongfu/scripts-master
|
gaussian_kernel.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/gaussian_kernel.m
| 760 |
utf_8
|
119655fccf91567673b1e3739af2b637
|
function kern = gaussian_kernel(fwhm, nk_half)
%function kern = gaussian_kernel(fwhm, nk_half)
% samples of a gaussian kernel at [-nk_half:nk_half]
% with given FWHM in pixels
% uses integral over each sample bin so that sum is very close to unity
%
% Copyright 2001-9-18, Jeff Fessler, The University of Michigan
if nargin < 1, help(mfilename), return, end
if streq(fwhm, 'test'), gaussian_kernel_test, return, end
if nargin < 2, nk_half = 2 * ceil(fwhm); end
if fwhm == 0
kern = zeros(nk_half*2+1, 1);
kern(nk_half+1) = 1;
else
sig = fwhm / sqrt(log(256));
x = [-nk_half:nk_half]';
pn = jf_protected_names;
kern = pn.normcdf(x+1/2, 0, sig) - pn.normcdf(x-1/2, 0, sig);
end
function gaussian_kernel_test
kern = gaussian_kernel(3);
plot(kern, '-o')
|
github
|
sunhongfu/scripts-master
|
fwhm_match.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/fwhm_match.m
| 1,878 |
utf_8
|
8ae6568a77739be15c5ac4afea48b4d8
|
function [fwhm_best, costs, im_best] = ...
fwhm_match(true_image, blurred_image, fwhms)
%|function [fwhm_best, costs, im_best] = ...
%| fwhm_match(true_image, blurred_image, fwhms)
%|
%| given a blurred_image of a true_image, find the FHWM of a Gaussian kernel
%| that, when convolved to the true_image, yields the smoothed image
%| that best matches blurred_image.
%|
%| the set of FWHM values given in the array fwhms is tried.
%|
%| Copyright 2001-8-30, Jeff Fessler, University of Michigan
if nargin == 1 && streq(true_image, 'test'), fwhm_match_test, return, end
if nargin < 2, help(mfilename), error(' '), end
if nargin < 3
fwhms = 0:0.5:4;
end
costs = zeros(size(fwhms));
cost_min = Inf;
for ii=1:length(fwhms)
fwhm = fwhms(ii);
kern = gaussian_kernel(fwhm);
psf = kern * kern';
tmp = conv2(true_image, psf, 'same');
costs(ii) = norm(tmp(:) - blurred_image(:)) / norm(true_image(:));
if costs(ii) < cost_min
im_best = tmp;
end
end
[dummy ibest] = min(costs);
if ibest == 1 | ibest == length(fwhms)
warning 'need wider range of fwhms'
end
fwhm_best = fwhms(ibest);
% fwhm_match_test
function fwhm_match_test
% pyramidal PSF to stress the approach
psf1 = [0:5 4:-1:0]; psf1 = psf1 / sum(psf1); psf = psf1' * psf1;
true_image = zeros(128); true_image(64:96,64:96) = 1;
blurred_image = conv2(true_image, psf, 'same');
im plc 2 2
im(1, true_image, 'True Image')
im(2, blurred_image, 'Blurred Image')
fwhms = [2:0.25:8];
[fwhm_best, costs] = fwhm_match(true_image, blurred_image, fwhms);
np = length(psf); ip = -(np-1)/2:(np-1)/2;
kern = gaussian_kernel(fwhm_best);
nk = length(kern); ik = -(nk-1)/2:(nk-1)/2;
if im
im subplot 3
plot(fwhms, costs, 'c-o', fwhm_best, min(costs), 'yx')
xlabel FWHM, ylabel Cost, title 'Cost vs FWHM'
im subplot 4
plot(ip, psf1, '-o', ik, kern(:), '-+')
xlabel pixel, title 'PSF profile: actual and Gaussian fit'
end
|
github
|
sunhongfu/scripts-master
|
fractional_delay.m
|
.m
|
scripts-master/cs-phase/_src/_NUFFT/utilities/fractional_delay.m
| 2,438 |
utf_8
|
09fad587ef6cfbb84e8a06617919b92f
|
function y = fractional_delay(x, delay)
%function y = fractional_delay(x, delay)
%
% given N samples x[n] of a real, periodic, band-limited signal x(t),
% compute sinc interpolated samples of delayed signal y(t) = x(t - delay)
% each column of x can be shifted by a different amount if delay is a vector.
% in
% x [N,L]
% delay [L]
% out
% y [N,L]
%
% see laakso:96:stu for more ideas.
%
% Copyright 2003-11-1, Jeff Fessler, The University of Michigan
% Extend to allow x to have multiple columns, 2003-11-2, Yingying Zhang.
if nargin < 1, help(mfilename), disp('Need Inputs'), error(mfilename), end
if streq(x, 'test'), fractional_delay_test, return, end
if size(x,2) ~= length(delay)
error 'Need size(x) = [N,L]; length(delay) = L'
end
dims = size(x);
N = dims(1);
L = dims(2);
if length(dims) > 2, error 'x must be 1d or 2d', end
X = fft(x); % fft of each column
% it is important to choose the k indices appropriately!
if rem(N,2) % odd
k = [-(N-1)/2:(N-1)/2]';
else
k = [-N/2:(N/2-1)]';
end
c = exp(-1i * 2*pi/N * k * delay(:)'); % [N,L] outer product
if ~rem(N,2) % even
mid = 1;
c(mid,:) = real(c(mid,:)); % this is the other key trick!
end
c = ifftshift1(c); % ifftshift differs from fftshift for odd N!
Y = X .* c;
y = ifft(Y);
%
% 1D ifftshift for each column
%
function c = ifftshift1(c)
[N,L] = size(c);
if L == 1
c = ifftshift(c); % ifftshift differs from fftshift for odd N!
else % multiple input signals
if ~rem(N,2) % even
c = c([N/2+1:end 1:N/2],:);
else % odd
c = c([(N-1)/2+1:end 1:(N-1)/2],:);
end
end
%
% self test
%
function fractional_delay_test
Nlist = [5 6];
im clf, pl=240;
for ii=1:2
N = Nlist(ii);
n = [0:(N-1)]';
xt = inline('sinc_periodic(t, N)', 't', 'N');
x = xt(n, N);
xx = [x x];
delay = [3.7; -2.2];
y = fractional_delay(xx, delay);
t = linspace(0,2*N,401);
yt1 = xt(t-delay(1),N);
yt2 = xt(t-delay(2),N);
if im
subplot(pl+0+ii), plot(t, xt(t,N), '-', n, xx(:,1), 'o')
axis([0 2*N -0.4 1.1]), title(sprintf('N=%d 1st input', N))
subplot(pl+2+ii), plot(t, xt(t,N), '-', n, xx(:,2), 'o')
axis([0 2*N -0.4 1.1]), title(sprintf('N=%d 2nd input', N))
subplot(pl+4+ii)
plot(t, yt1, '-', n, real(y(:,1)), 's', n, imag(y(:,1)), '.')
axis([0 2*N -0.4 1.1]), title(sprintf('delay=%g 1st input',delay(1)))
subplot(pl+6+ii)
plot(t, yt2, '-', n, real(y(:,2)), 's', n, imag(y(:,2)), '.')
axis([0 2*N -0.4 1.1]), title(sprintf('delay=%g 2nd input',delay(2)))
end
end
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