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github
ojwoodford/ojwul-master
vl_mser.m
.m
ojwul-master/features/vlfeat/vl_mser.m
3,185
utf_8
3f713cf370e5d15b71f6f7b90dd91390
% VL_MSER Maximally Stable Extremal Regions % R=VL_MSER(I) computes the Maximally Stable Extremal Regions (MSER) % [1] of image I with stability threshold DELTA. I is any array of % class UINT8. R is a vector of region seeds. % % A (maximally stable) extremal region is just a connected component % of one of the level sets of the image I. An extremal region can % be recovered from a seed X as the connected component of the level % set {Y: I(Y) <= I(X)} which contains the pixel o index X. % % The function supports images of arbitrary dimension D. % % [R,F]=VL_MSER(...) also returns ellipsoids F fitted to the regions. % Each column of F describes an ellipsoid; F(1:D,i) is the center of % the elliposid and F(D:end,i) are the independent elements of the % co-variance matrix of the ellipsoid. % % Ellipsoids are computed according to the same reference frame of I % seen as a matrix. This means that the first coordinate spans the % first dimension of I. % % Notice that for 2-D images usually the opposite convention is used % (i.e. the first coordinate is the x-axis, which corresponds to the % column index). Thus, if the function VL_PLOTFRAME() is used to plot % the ellipses, the frames F should be `transposed' as in F = F([2 % 1 5 4 3],:). VL_ERTR() exists for this purpose. % % VL_MSER(I,'Option'[,Value]...) accepts the following options % % Delta:: 5 % Set the DELTA parameter of the VL_MSER algorithm. Roughly % speaking, the stability of a region is the relative variation % of the region area when the intensity is changed of +/- % Delta/2. % % MaxArea:: 0.75 % Set the maximum area (volume) of the regions relative to % the image domain area (volume). % % MinArea:: 3/npixels % Set the minimum area (volume) of the regions relative to % the image domain area (volume). % % MaxVariation:: 0.25 % Set the maximum variation (absolute stability score) of the % regions. % % MinDiversity:: 0.2 % Set the minimum diversity of the region. When the relative % area variation of two nested regions is below this threshold, % then only the most stable one is selected. % % BrightOnDark:: 1 % Detect bright-on-dark MSERs. This corresponds to MSERs of the % inverted image. % % DarkOnBright:: 1 % Detect dark-on-bright MSERs. This corresponds to MSERs of the % original image. % % Verbose:: % Be verbose. % % REFERENCES % [1] J. Matas, O. Chum, M. Urban, and T. Pajdla, "Robust wide % baseline stereo from maximally stable extremal regions," in % Proc. BMVC, 2002. % % See also: VL_HELP(). % AUTORIGHTS % Copyright (C) 2007-10 Andrea Vedaldi and Brian Fulkerson % % This file is part of VLFeat, available under the terms of the % GNU GPLv2, or (at your option) any later version. function varargout = vl_mser(varargin) base = '../private/vlfeat'; sourceList = {['-I' base], 'vl_mser.c', [base '/vl/mser.c'], [base '/vl/generic.c'], [base '/vl/host.c'], [base '/vl/random.c']}; % Cell array of source files [varargout{1:nargout}] = compile(varargin{:}); % Compilation happens here return
github
ojwoodford/ojwul-master
vl_sift.m
.m
ojwul-master/features/vlfeat/vl_sift.m
3,096
utf_8
27d8451c04817442563daeb990c87b58
% VL_SIFT Scale-Invariant Feature Transform % F = VL_SIFT(I) computes the SIFT frames [1] (keypoints) F of the % image I. I is a gray-scale image in single precision. Each column % of F is a feature frame and has the format [X;Y;S;TH], where X,Y % is the (fractional) center of the frame, S is the scale and TH is % the orientation (in radians). % % [F,D] = VL_SIFT(I) computes the SIFT descriptors [1] as well. Each % column of D is the descriptor of the corresponding frame in F. A % descriptor is a 128-dimensional vector of class UINT8. % % VL_SIFT() accepts the following options: % % Octaves:: [maximum possible] % Set the number of octave of the DoG scale space. % % Levels:: [3] % Set the number of levels per octave of the DoG scale space. % % FirstOctave:: [0] % Set the index of the first octave of the DoG scale space. % % PeakThresh:: [0] % Set the peak selection threshold. % % EdgeThresh:: [10] % Set the non-edge selection threshold. % % NormThresh:: [-inf] % Set the minimum l2-norm of the descriptors before % normalization. Descriptors below the threshold are set to zero. % % Magnif:: [3] % Set the descriptor magnification factor. The scale of the % keypoint is multiplied by this factor to obtain the width (in % pixels) of the spatial bins. For instance, if there are there % are 4 spatial bins along each spatial direction, the % ``side'' of the descriptor is approximatively 4 * MAGNIF. % % WindowSize:: [2] % Set the variance of the Gaussian window that determines the % descriptor support. It is expressend in units of spatial % bins. % % Frames:: [not specified] % If specified, set the frames to use (bypass the detector). If % frames are not passed in order of increasing scale, they are % re-orderded. % % Orientations:: % If specified, compute the orietantions of the frames overriding % the orientation specified by the 'Frames' option. % % Verbose:: % If specfified, be verbose (may be repeated to increase the % verbosity level). % % REFERENCES % % [1] D. G. Lowe, Distinctive image features from scale-invariant % keypoints. IJCV, vol. 2, no. 60, pp. 91-110, 2004. % % See also:: VL_HELP(), VL_UBCMATCH(), VL_DSIFT(). % AUTORIGHTS % Copyright (C) 2007-10 Andrea Vedaldi and Brian Fulkerson % % This file is part of VLFeat, available under the terms of the % GNU GPLv2, or (at your option) any later version. function varargout = vl_sift(varargin) base = '../private/vlfeat'; if ismember(computer('arch'), {'maca64'}) sourceList = {['-I' base], 'vl_sift.c', [base '/vl/sift.c'], [base '/vl/generic.c'], [base '/vl/host.c'], [base '/vl/imopv.c'], [base '/vl/random.c']}; % Cell array of source files else sourceList = {['-I' base], '-D__SSE2__', 'vl_sift.c', [base '/vl/sift.c'], [base '/vl/generic.c'], [base '/vl/host.c'], [base '/vl/imopv.c'], [base '/vl/imopv_sse2.c'], [base '/vl/random.c']}; % Cell array of source files end [varargout{1:nargout}] = compile(varargin{:}); % Compilation happens here return
github
ojwoodford/ojwul-master
vl_siftdescriptor.m
.m
ojwul-master/features/vlfeat/vl_siftdescriptor.m
2,682
utf_8
0753efd3f2ffd45604b62f2aec10d0e5
% VL_SIFTDESCRIPTOR Raw SIFT descriptor % D = VL_SIFTDESCRIPTOR(GRAD, F) calculates the SIFT descriptors of % the keypoints F on the pre-processed image GRAD. GRAD is a 2xMxN % array. The first layer GRAD(1,:,:) contains the modulus of % gradient of the original image modulus. The second layer % GRAD(2,:,:) contains the gradient angle (measured in radians, % clockwise, starting from the X axis -- this assumes that the Y % axis points down). The matrix F contains one column per keypoint % with the X, Y, SGIMA and ANLGE parameters. % % In order to match the standard SIFT descriptor, the gradient GRAD % should be calculated after mapping the image to the keypoint % scale. This is obtained by smoothing the image by a a Gaussian % kernel of variance equal to the scale of the keypoint. % Additionaly, SIFT assumes that the input image is pre-smoothed at % scale 0.5 (this roughly compensates for the effect of the CCD % integrators), so the amount of smoothing that needs to be applied % is slightly less. The following code computes a standard SIFT % descriptor by using VL_SIFTDESCRIPTOR(): % % I_ = vl_imsmooth(im2double(I), sqrt(f(3)^2 - 0.5^2)) ; % [Ix, Iy] = vl_grad(I_) ; % mod = sqrt(Ix.^2 + Iy.^2) ; % ang = atan2(Iy,Ix) ; % grd = shiftdim(cat(3,mod,ang),2) ; % grd = single(grd) ; % d = vl_siftdescriptor(grd, f) ; % % Remark:: The above fragment generates results which are very close % but not identical to the output of VL_SIFT() as the latter % samples the scale space at finite steps. % % Remark:: For object categorization is sometimes useful to compute % SIFT descriptors without smoothing the image. % % Options: % % Magnif [3]:: % Magnification factor (see VL_SIFT()). % % See also:: VL_SIFT(), VL_HELP(). % AUTORIGHTS % Copyright (C) 2007-10 Andrea Vedaldi and Brian Fulkerson % % This file is part of VLFeat, available under the terms of the % GNU GPLv2, or (at your option) any later version. function varargout = vl_siftdescriptor(varargin) base = '../private/vlfeat'; if ismember(computer('arch'), {'maca64'}) sourceList = {['-I' base], 'vl_siftdescriptor.c', [base '/vl/sift.c'], [base '/vl/generic.c'], [base '/vl/host.c'], [base '/vl/imopv.c'], [base '/vl/random.c']}; % Cell array of source files else sourceList = {['-I' base], '-D__SSE2__', 'vl_siftdescriptor.c', [base '/vl/sift.c'], [base '/vl/generic.c'], [base '/vl/host.c'], [base '/vl/imopv.c'], [base '/vl/imopv_sse2.c'], [base '/vl/random.c']}; % Cell array of source files end [varargout{1:nargout}] = compile(varargin{:}); % Compilation happens here return
github
ojwoodford/ojwul-master
vl_hog.m
.m
ojwul-master/features/vlfeat/vl_hog.m
2,429
utf_8
ad12f0d85adb05c48fae844aac4c4fd5
% VL_HOG Compute HOG features % HOG = VL_HOG(IM, CELLSIZE) computes the HOG features for image IM % and the specified CELLSIZE. IM can be either grayscale or colour % in SINGLE storage class. HOG is an array of cells: its number % of columns is approximately the number of columns of IM divided % by CELLSIZE and the same for the number of rows. The third % dimension spans the feature components. % % PERM = VL_HOG('permutation') returns the left-right permutation % to apply to each HOG cell to flip it. % % IMAGE = VL_HOG('render', HOG) returns an IMAGE containing an % iconic representation of the array of cells HOG. % % Options: % % Variant:: 'UoCTTI' % Choose a HOG variant: 'UoCTTI' or 'DalalTriggs'. % % NumOrientations:: 9 % Choose a number of undirected orientations in the orientation % histograms. The angle [0,pi) is divided in to NumOrientation % equal parts. % % DirectedPolarField:: % By specifying this flag the image IM is interpreted as samples % from a 2D vector field specified by their argument IM(:,:,2) and % modulus IM(:,:,1). % % UndirectedPolarField:: % Same as above, but wraps angles in [0,pi). % % BilinearOrientations:: % This flags activates the use of bilinear interpolation to assign % orientations to bins. This produces a smoother feature, but is % not some other implementations (e.g. UoCTTI). % % Example:: computing and visualizing HOG features % hog = vl_hog(im2single(im)) ; % compute HOG features % % See also: <a href="matlab:vl_help('hog')">HOG fundamentals</a>, % VL_HELP(). % Author: Andrea Vedaldi % Copyright (C) 2012-13 Andrea Vedaldi. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). function varargout = vl_hog(varargin) base = '../private/vlfeat'; if ismember(computer('arch'), {'maca64'}) sourceList = {['-I' base], 'vl_hog.c', [base '/vl/hog.c'], [base '/vl/generic.c'], [base '/vl/host.c'], [base '/vl/imopv.c'], [base '/vl/random.c']}; % Cell array of source files else sourceList = {['-I' base], '-D__SSE2__', 'vl_hog.c', [base '/vl/hog.c'], [base '/vl/generic.c'], [base '/vl/host.c'], [base '/vl/imopv.c'], [base '/vl/imopv_sse2.c'], [base '/vl/random.c']}; % Cell array of source files end [varargout{1:nargout}] = compile(varargin{:}); % Compilation happens here return
github
monark12/Machine-Learning-Coursera-master
submit.m
.m
Machine-Learning-Coursera-master/machine-learning-ex2/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
monark12/Machine-Learning-Coursera-master
submitWithConfiguration.m
.m
Machine-Learning-Coursera-master/machine-learning-ex2/ex2/lib/submitWithConfiguration.m
3,734
utf_8
84d9a81848f6d00a7aff4f79bdbb6049
function submitWithConfiguration(conf) addpath('./lib/jsonlab'); 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); 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
monark12/Machine-Learning-Coursera-master
savejson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex2/ex2/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
monark12/Machine-Learning-Coursera-master
loadjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex2/ex2/lib/jsonlab/loadjson.m
18,732
ibm852
ab98cf173af2d50bbe8da4d6db252a20
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($1))}_','once'); else str=sprintf('x0x%X_%s',char(str(1)),str(2:end)); end end if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end if(~isoct) str=regexprep(str,'([^0-9A-Za-z_])','_0x${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
monark12/Machine-Learning-Coursera-master
loadubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex2/ex2/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
monark12/Machine-Learning-Coursera-master
saveubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex2/ex2/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
monark12/Machine-Learning-Coursera-master
submit.m
.m
Machine-Learning-Coursera-master/machine-learning-ex4/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
monark12/Machine-Learning-Coursera-master
submitWithConfiguration.m
.m
Machine-Learning-Coursera-master/machine-learning-ex4/ex4/lib/submitWithConfiguration.m
3,734
utf_8
84d9a81848f6d00a7aff4f79bdbb6049
function submitWithConfiguration(conf) addpath('./lib/jsonlab'); 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); 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
monark12/Machine-Learning-Coursera-master
savejson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex4/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
monark12/Machine-Learning-Coursera-master
loadjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex4/ex4/lib/jsonlab/loadjson.m
18,732
ibm852
ab98cf173af2d50bbe8da4d6db252a20
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($1))}_','once'); else str=sprintf('x0x%X_%s',char(str(1)),str(2:end)); end end if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end if(~isoct) str=regexprep(str,'([^0-9A-Za-z_])','_0x${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
monark12/Machine-Learning-Coursera-master
loadubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex4/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
monark12/Machine-Learning-Coursera-master
saveubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex4/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
monark12/Machine-Learning-Coursera-master
submit.m
.m
Machine-Learning-Coursera-master/machine-learning-ex6/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
monark12/Machine-Learning-Coursera-master
porterStemmer.m
.m
Machine-Learning-Coursera-master/machine-learning-ex6/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
monark12/Machine-Learning-Coursera-master
submitWithConfiguration.m
.m
Machine-Learning-Coursera-master/machine-learning-ex6/ex6/lib/submitWithConfiguration.m
3,734
utf_8
84d9a81848f6d00a7aff4f79bdbb6049
function submitWithConfiguration(conf) addpath('./lib/jsonlab'); 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); 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
monark12/Machine-Learning-Coursera-master
savejson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex6/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
monark12/Machine-Learning-Coursera-master
loadjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex6/ex6/lib/jsonlab/loadjson.m
18,732
ibm852
ab98cf173af2d50bbe8da4d6db252a20
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($1))}_','once'); else str=sprintf('x0x%X_%s',char(str(1)),str(2:end)); end end if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end if(~isoct) str=regexprep(str,'([^0-9A-Za-z_])','_0x${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
monark12/Machine-Learning-Coursera-master
loadubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex6/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
monark12/Machine-Learning-Coursera-master
saveubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex6/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
monark12/Machine-Learning-Coursera-master
submit.m
.m
Machine-Learning-Coursera-master/machine-learning-ex7/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
monark12/Machine-Learning-Coursera-master
submitWithConfiguration.m
.m
Machine-Learning-Coursera-master/machine-learning-ex7/ex7/lib/submitWithConfiguration.m
3,734
utf_8
84d9a81848f6d00a7aff4f79bdbb6049
function submitWithConfiguration(conf) addpath('./lib/jsonlab'); 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); 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
monark12/Machine-Learning-Coursera-master
savejson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex7/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
monark12/Machine-Learning-Coursera-master
loadjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex7/ex7/lib/jsonlab/loadjson.m
18,732
ibm852
ab98cf173af2d50bbe8da4d6db252a20
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($1))}_','once'); else str=sprintf('x0x%X_%s',char(str(1)),str(2:end)); end end if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end if(~isoct) str=regexprep(str,'([^0-9A-Za-z_])','_0x${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
monark12/Machine-Learning-Coursera-master
loadubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex7/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
monark12/Machine-Learning-Coursera-master
saveubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex7/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
monark12/Machine-Learning-Coursera-master
submit.m
.m
Machine-Learning-Coursera-master/machine-learning-ex5/ex5/submit.m
1,765
utf_8
b1804fe5854d9744dca981d250eda251
function submit() addpath('./lib'); conf.assignmentSlug = 'regularized-linear-regression-and-bias-variance'; conf.itemName = 'Regularized Linear Regression and Bias/Variance'; conf.partArrays = { ... { ... '1', ... { 'linearRegCostFunction.m' }, ... 'Regularized Linear Regression Cost Function', ... }, ... { ... '2', ... { 'linearRegCostFunction.m' }, ... 'Regularized Linear Regression Gradient', ... }, ... { ... '3', ... { 'learningCurve.m' }, ... 'Learning Curve', ... }, ... { ... '4', ... { 'polyFeatures.m' }, ... 'Polynomial Feature Mapping', ... }, ... { ... '5', ... { 'validationCurve.m' }, ... 'Validation Curve', ... }, ... }; conf.output = @output; submitWithConfiguration(conf); end function out = output(partId, auxstring) % Random Test Cases X = [ones(10,1) sin(1:1.5:15)' cos(1:1.5:15)']; y = sin(1:3:30)'; Xval = [ones(10,1) sin(0:1.5:14)' cos(0:1.5:14)']; yval = sin(1:10)'; if partId == '1' [J] = linearRegCostFunction(X, y, [0.1 0.2 0.3]', 0.5); out = sprintf('%0.5f ', J); elseif partId == '2' [J, grad] = linearRegCostFunction(X, y, [0.1 0.2 0.3]', 0.5); out = sprintf('%0.5f ', grad); elseif partId == '3' [error_train, error_val] = ... learningCurve(X, y, Xval, yval, 1); out = sprintf('%0.5f ', [error_train(:); error_val(:)]); elseif partId == '4' [X_poly] = polyFeatures(X(2,:)', 8); out = sprintf('%0.5f ', X_poly); elseif partId == '5' [lambda_vec, error_train, error_val] = ... validationCurve(X, y, Xval, yval); out = sprintf('%0.5f ', ... [lambda_vec(:); error_train(:); error_val(:)]); end end
github
monark12/Machine-Learning-Coursera-master
submitWithConfiguration.m
.m
Machine-Learning-Coursera-master/machine-learning-ex5/ex5/lib/submitWithConfiguration.m
3,734
utf_8
84d9a81848f6d00a7aff4f79bdbb6049
function submitWithConfiguration(conf) addpath('./lib/jsonlab'); 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); 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
monark12/Machine-Learning-Coursera-master
savejson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex5/ex5/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
monark12/Machine-Learning-Coursera-master
loadjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex5/ex5/lib/jsonlab/loadjson.m
18,732
ibm852
ab98cf173af2d50bbe8da4d6db252a20
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($1))}_','once'); else str=sprintf('x0x%X_%s',char(str(1)),str(2:end)); end end if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end if(~isoct) str=regexprep(str,'([^0-9A-Za-z_])','_0x${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
monark12/Machine-Learning-Coursera-master
loadubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex5/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
monark12/Machine-Learning-Coursera-master
saveubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex5/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
monark12/Machine-Learning-Coursera-master
submit.m
.m
Machine-Learning-Coursera-master/machine-learning-ex3/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
monark12/Machine-Learning-Coursera-master
submitWithConfiguration.m
.m
Machine-Learning-Coursera-master/machine-learning-ex3/ex3/lib/submitWithConfiguration.m
3,734
utf_8
84d9a81848f6d00a7aff4f79bdbb6049
function submitWithConfiguration(conf) addpath('./lib/jsonlab'); 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); 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
monark12/Machine-Learning-Coursera-master
savejson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex3/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
monark12/Machine-Learning-Coursera-master
loadjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex3/ex3/lib/jsonlab/loadjson.m
18,732
ibm852
ab98cf173af2d50bbe8da4d6db252a20
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($1))}_','once'); else str=sprintf('x0x%X_%s',char(str(1)),str(2:end)); end end if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end if(~isoct) str=regexprep(str,'([^0-9A-Za-z_])','_0x${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
monark12/Machine-Learning-Coursera-master
loadubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex3/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
monark12/Machine-Learning-Coursera-master
saveubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex3/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
monark12/Machine-Learning-Coursera-master
submit.m
.m
Machine-Learning-Coursera-master/machine-learning-ex1/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
monark12/Machine-Learning-Coursera-master
submitWithConfiguration.m
.m
Machine-Learning-Coursera-master/machine-learning-ex1/ex1/lib/submitWithConfiguration.m
3,734
utf_8
84d9a81848f6d00a7aff4f79bdbb6049
function submitWithConfiguration(conf) addpath('./lib/jsonlab'); 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); 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
monark12/Machine-Learning-Coursera-master
savejson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex1/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
monark12/Machine-Learning-Coursera-master
loadjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex1/ex1/lib/jsonlab/loadjson.m
18,732
ibm852
ab98cf173af2d50bbe8da4d6db252a20
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($1))}_','once'); else str=sprintf('x0x%X_%s',char(str(1)),str(2:end)); end end if(isempty(regexp(str,'[^0-9A-Za-z_]', 'once' ))) return; end if(~isoct) str=regexprep(str,'([^0-9A-Za-z_])','_0x${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
monark12/Machine-Learning-Coursera-master
loadubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex1/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
monark12/Machine-Learning-Coursera-master
saveubjson.m
.m
Machine-Learning-Coursera-master/machine-learning-ex1/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
ee368/EE368-Android-Samples-master
vl_compile.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/vl_compile.m
5,060
utf_8
978f5189bb9b2a16db3368891f79aaa6
function vl_compile(compiler) % VL_COMPILE Compile VLFeat MEX files % VL_COMPILE() uses MEX() to compile VLFeat MEX files. This command % works only under Windows and is used to re-build problematic % binaries. The preferred method of compiling VLFeat on both UNIX % and Windows is through the provided Makefiles. % % VL_COMPILE() only compiles the MEX files and assumes that the % VLFeat DLL (i.e. the file VLFEATROOT/bin/win{32,64}/vl.dll) has % already been built. This file is built by the Makefiles. % % By default VL_COMPILE() assumes that Visual C++ is the active % MATLAB compiler. VL_COMPILE('lcc') assumes that the active % compiler is LCC instead (see MEX -SETUP). Unfortunately LCC does % not seem to be able to compile the latest versions of VLFeat due % to bugs in the support of 64-bit integers. Therefore it is % recommended to use Visual C++ instead. % % See also: VL_NOPREFIX(), VL_HELP(). % Authors: Andrea Vedadli, Jonghyun Choi % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). if nargin < 1, compiler = 'visualc' ; end switch lower(compiler) case 'visualc' fprintf('%s: assuming that Visual C++ is the active compiler\n', mfilename) ; useLcc = false ; case 'lcc' fprintf('%s: assuming that LCC is the active compiler\n', mfilename) ; warning('LCC may fail to compile VLFeat. See help vl_compile.') ; useLcc = true ; otherwise error('Unknown compiler ''%s''.', compiler) end vlDir = vl_root ; toolboxDir = fullfile(vlDir, 'toolbox') ; switch computer case 'PCWIN' fprintf('%s: compiling for PCWIN (32 bit)\n', mfilename); mexwDir = fullfile(toolboxDir, 'mex', 'mexw32') ; binwDir = fullfile(vlDir, 'bin', 'win32') ; case 'PCWIN64' fprintf('%s: compiling for PCWIN64 (64 bit)\n', mfilename); mexwDir = fullfile(toolboxDir, 'mex', 'mexw64') ; binwDir = fullfile(vlDir, 'bin', 'win64') ; otherwise error('The architecture is neither PCWIN nor PCWIN64. See help vl_compile.') ; end impLibPath = fullfile(binwDir, 'vl.lib') ; libDir = fullfile(binwDir, 'vl.dll') ; mkd(mexwDir) ; % find the subdirectories of toolbox that we should process subDirs = dir(toolboxDir) ; subDirs = subDirs([subDirs.isdir]) ; discard = regexp({subDirs.name}, '^(.|..|noprefix|mex.*)$', 'start') ; keep = cellfun('isempty', discard) ; subDirs = subDirs(keep) ; subDirs = {subDirs.name} ; % Copy support files ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ if ~exist(fullfile(binwDir, 'vl.dll')) error('The VLFeat DLL (%s) could not be found. See help vl_compile.', ... fullfile(binwDir, 'vl.dll')) ; end tmp = dir(fullfile(binwDir, '*.dll')) ; supportFileNames = {tmp.name} ; for fi = 1:length(supportFileNames) name = supportFileNames{fi} ; cp(fullfile(binwDir, name), ... fullfile(mexwDir, name) ) ; end % Ensure implib for LCC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ if useLcc lccImpLibDir = fullfile(mexwDir, 'lcc') ; lccImpLibPath = fullfile(lccImpLibDir, 'VL.lib') ; lccRoot = fullfile(matlabroot, 'sys', 'lcc', 'bin') ; lccImpExePath = fullfile(lccRoot, 'lcc_implib.exe') ; mkd(lccImpLibDir) ; cp(fullfile(binwDir, 'vl.dll'), fullfile(lccImpLibDir, 'vl.dll')) ; cmd = ['"' lccImpExePath '"', ' -u ', '"' fullfile(lccImpLibDir, 'vl.dll') '"'] ; fprintf('Running:\n> %s\n', cmd) ; curPath = pwd ; try cd(lccImpLibDir) ; [d,w] = system(cmd) ; if d, error(w); end cd(curPath) ; catch cd(curPath) ; error(lasterr) ; end end % Compile each mex file ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ for i = 1:length(subDirs) thisDir = fullfile(toolboxDir, subDirs{i}) ; fileNames = ls(fullfile(thisDir, '*.c')); for f = 1:size(fileNames,1) fileName = fileNames(f, :) ; sp = strfind(fileName, ' '); if length(sp) > 0, fileName = fileName(1:sp-1); end filePath = fullfile(thisDir, fileName); fprintf('MEX %s\n', filePath); dot = strfind(fileName, '.'); mexFile = fullfile(mexwDir, [fileName(1:dot) 'dll']); if exist(mexFile) delete(mexFile) end cmd = {['-I' toolboxDir], ... ['-I' vlDir], ... '-O', ... '-outdir', mexwDir, ... filePath } ; if useLcc cmd{end+1} = lccImpLibPath ; else cmd{end+1} = impLibPath ; end mex(cmd{:}) ; end end % -------------------------------------------------------------------- function cp(src,dst) % -------------------------------------------------------------------- if ~exist(dst,'file') fprintf('Copying ''%s'' to ''%s''.\n', src,dst) ; copyfile(src,dst) ; end % -------------------------------------------------------------------- function mkd(dst) % -------------------------------------------------------------------- if ~exist(dst, 'dir') fprintf('Creating directory ''%s''.', dst) ; mkdir(dst) ; end
github
ee368/EE368-Android-Samples-master
vl_noprefix.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/vl_noprefix.m
1,875
utf_8
97d8755f0ba139ac1304bc423d3d86d3
function vl_noprefix % VL_NOPREFIX Create a prefix-less version of VLFeat commands % VL_NOPREFIX() creats prefix-less stubs for VLFeat functions % (e.g. SIFT for VL_SIFT). This function is seldom used as the stubs % are included in the VLFeat binary distribution anyways. Moreover, % on UNIX platforms, the stubs are generally constructed by the % Makefile. % % See also: VL_COMPILE(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). root = fileparts(which(mfilename)) ; list = listMFilesX(root); outDir = fullfile(root, 'noprefix') ; if ~exist(outDir, 'dir') mkdir(outDir) ; end for li = 1:length(list) name = list(li).name(1:end-2) ; % remove .m nname = name(4:end) ; % remove vl_ stubPath = fullfile(outDir, [nname '.m']) ; fout = fopen(stubPath, 'w') ; fprintf('Creating stub %s for %s\n', stubPath, nname) ; fprintf(fout, 'function varargout = %s(varargin)\n', nname) ; fprintf(fout, '%% %s Stub for %s\n', upper(nname), upper(name)) ; fprintf(fout, '[varargout{1:nargout}] = %s(varargin{:})\n', name) ; fclose(fout) ; end end function list = listMFilesX(root) list = struct('name', {}, 'path', {}) ; files = dir(root) ; for fi = 1:length(files) name = files(fi).name ; if files(fi).isdir if any(regexp(name, '^(\.|\.\.|noprefix)$')) continue ; else tmp = listMFilesX(fullfile(root, name)) ; list = [list, tmp] ; end end if any(regexp(name, '^vl_(demo|test).*m$')) continue ; elseif any(regexp(name, '^vl_(demo|setup|compile|help|root|noprefix)\.m$')) continue ; elseif any(regexp(name, '\.m$')) list(end+1) = struct(... 'name', {name}, ... 'path', {fullfile(root, name)}) ; end end end
github
ee368/EE368-Android-Samples-master
vl_override.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/misc/vl_override.m
4,654
utf_8
e233d2ecaeb68f56034a976060c594c5
function config = vl_override(config,update,varargin) % VL_OVERRIDE Override structure subset % CONFIG = VL_OVERRIDE(CONFIG, UPDATE) copies recursively the fileds % of the structure UPDATE to the corresponding fields of the % struture CONFIG. % % Usually CONFIG is interpreted as a list of paramters with their % default values and UPDATE as a list of new paramete values. % % VL_OVERRIDE(..., 'Warn') prints a warning message whenever: (i) % UPDATE has a field not found in CONFIG, or (ii) non-leaf values of % CONFIG are overwritten. % % VL_OVERRIDE(..., 'Skip') skips fields of UPDATE that are not found % in CONFIG instead of copying them. % % VL_OVERRIDE(..., 'CaseI') matches field names in a % case-insensitive manner. % % Remark:: % Fields are copied at the deepest possible level. For instance, % if CONFIG has fields A.B.C1=1 and A.B.C2=2, and if UPDATE is the % structure A.B.C1=3, then VL_OVERRIDE() returns a strucuture with % fields A.B.C1=3, A.B.C2=2. By contrast, if UPDATE is the % structure A.B=4, then the field A.B is copied, and VL_OVERRIDE() % returns the structure A.B=4 (specifying 'Warn' would warn about % the fact that the substructure B.C1, B.C2 is being deleted). % % Remark:: % Two fields are matched if they correspond exactly. Specifically, % two fileds A(IA).(FA) and B(IA).FB of two struct arrays A and B % match if, and only if, (i) A and B have the same dimensions, % (ii) IA == IB, and (iii) FA == FB. % % See also: VL_ARGPARSE(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). warn = false ; skip = false ; err = false ; casei = false ; if length(varargin) == 1 & ~ischar(varargin{1}) % legacy warn = 1 ; end if ~warn & length(varargin) > 0 for i=1:length(varargin) switch lower(varargin{i}) case 'warn' warn = true ; case 'skip' skip = true ; case 'err' err = true ; case 'argparse' argparse = true ; case 'casei' casei = true ; otherwise error(sprintf('Unknown option ''%s''.',varargin{i})) ; end end end % if CONFIG is not a struct array just copy UPDATE verbatim if ~isstruct(config) config = update ; return ; end % if CONFIG is a struct array but UPDATE is not, no match can be % established and we simply copy UPDATE verbatim if ~isstruct(update) config = update ; return ; end % if CONFIG and UPDATE are both struct arrays, but have different % dimensions then nom atch can be established and we simply copy % UPDATE verbatim if numel(update) ~= numel(config) config = update ; return ; end % if CONFIG and UPDATE are both struct arrays of the same % dimension, we override recursively each field for idx=1:numel(update) fields = fieldnames(update) ; for i = 1:length(fields) updateFieldName = fields{i} ; if casei configFieldName = findFieldI(config, updateFieldName) ; else configFieldName = findField(config, updateFieldName) ; end if ~isempty(configFieldName) config(idx).(configFieldName) = ... vl_override(config(idx).(configFieldName), ... update(idx).(updateFieldName)) ; else if warn warning(sprintf('copied field ''%s'' which is in UPDATE but not in CONFIG', ... updateFieldName)) ; end if err error(sprintf('The field ''%s'' is in UPDATE but not in CONFIG', ... updateFieldName)) ; end if skip if warn warning(sprintf('skipping field ''%s'' which is in UPDATE but not in CONFIG', ... updateFieldName)) ; end continue ; end config(idx).(updateFieldName) = update(idx).(updateFieldName) ; end end end % -------------------------------------------------------------------- function field = findFieldI(S, matchField) % -------------------------------------------------------------------- field = '' ; fieldNames = fieldnames(S) ; for fi=1:length(fieldNames) if strcmpi(fieldNames{fi}, matchField) field = fieldNames{fi} ; end end % -------------------------------------------------------------------- function field = findField(S, matchField) % -------------------------------------------------------------------- field = '' ; fieldNames = fieldnames(S) ; for fi=1:length(fieldNames) if strcmp(fieldNames{fi}, matchField) field = fieldNames{fi} ; end end
github
ee368/EE368-Android-Samples-master
vl_quickvis.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/quickshift/vl_quickvis.m
3,696
utf_8
27f199dad4c5b9c192a5dd3abc59f9da
function [Iedge dists map gaps] = vl_quickvis(I, ratio, kernelsize, maxdist, maxcuts) % VL_QUICKVIS Create an edge image from a Quickshift segmentation. % IEDGE = VL_QUICKVIS(I, RATIO, KERNELSIZE, MAXDIST, MAXCUTS) creates an edge % stability image from a Quickshift segmentation. RATIO controls the tradeoff % between color consistency and spatial consistency (See VL_QUICKSEG) and % KERNELSIZE controls the bandwidth of the density estimator (See VL_QUICKSEG, % VL_QUICKSHIFT). MAXDIST is the maximum distance between neighbors which % increase the density. % % VL_QUICKVIS takes at most MAXCUTS thresholds less than MAXDIST, forming at % most MAXCUTS segmentations. The edges between regions in each of these % segmentations are labeled in IEDGE, where the label corresponds to the % largest DIST which preserves the edge. % % [IEDGE,DISTS] = VL_QUICKVIS(I, RATIO, KERNELSIZE, MAXDIST, MAXCUTS) also % returns the DIST thresholds that were chosen. % % IEDGE = VL_QUICKVIS(I, RATIO, KERNELSIZE, DISTS) will use the DISTS % specified % % [IEDGE,DISTS,MAP,GAPS] = VL_QUICKVIS(I, RATIO, KERNELSIZE, MAXDIST, MAXCUTS) % also returns the MAP and GAPS from VL_QUICKSHIFT. % % See Also: VL_QUICKSHIFT(), VL_QUICKSEG(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). if nargin == 4 dists = maxdist; maxdist = max(dists); [Iseg labels map gaps E] = vl_quickseg(I, ratio, kernelsize, maxdist); else [Iseg labels map gaps E] = vl_quickseg(I, ratio, kernelsize, maxdist); dists = unique(floor(gaps(:))); dists = dists(2:end-1); % remove the inf thresh and the lowest level thresh if length(dists) > maxcuts ind = round(linspace(1,length(dists), maxcuts)); dists = dists(ind); end end [Iedge dists] = mapvis(map, gaps, dists); function [Iedge dists] = mapvis(map, gaps, maxdist, maxcuts) % MAPVIS Create an edge image from a Quickshift segmentation. % IEDGE = MAPVIS(MAP, GAPS, MAXDIST, MAXCUTS) creates an edge % stability image from a Quickshift segmentation. MAXDIST is the maximum % distance between neighbors which increase the density. % % MAPVIS takes at most MAXCUTS thresholds less than MAXDIST, forming at most % MAXCUTS segmentations. The edges between regions in each of these % segmentations are labeled in IEDGE, where the label corresponds to the % largest DIST which preserves the edge. % % [IEDGE,DISTS] = MAPVIS(MAP, GAPS, MAXDIST, MAXCUTS) also returns the DIST % thresholds that were chosen. % % IEDGE = MAPVIS(MAP, GAPS, DISTS) will use the DISTS specified % % See Also: VL_QUICKVIS, VL_QUICKSHIFT, VL_QUICKSEG if nargin == 3 dists = maxdist; maxdist = max(dists); else dists = unique(floor(gaps(:))); dists = dists(2:end-1); % remove the inf thresh and the lowest level thresh % throw away min region size instead of maxdist? ind = find(dists < maxdist); dists = dists(ind); if length(dists) > maxcuts ind = round(linspace(1,length(dists), maxcuts)); dists = dists(ind); end end Iedge = zeros(size(map)); for i = 1:length(dists) s = find(gaps >= dists(i)); mapdist = map; mapdist(s) = s; [mapped labels] = vl_flatmap(mapdist); fprintf('%d/%d %d regions\n', i, length(dists), length(unique(mapped))) borders = getborders(mapped); Iedge(borders) = dists(i); %Iedge(borders) = Iedge(borders) + 1; %Iedge(borders) = i; end %%%%%%%%% GETBORDERS function borders = getborders(map) dx = conv2(map, [-1 1], 'same'); dy = conv2(map, [-1 1]', 'same'); borders = find(dx ~= 0 | dy ~= 0);
github
ee368/EE368-Android-Samples-master
vl_demo_aib.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/demo/vl_demo_aib.m
2,928
utf_8
590c6db09451ea608d87bfd094662cac
function vl_demo_aib % VL_DEMO_AIB Test Agglomerative Information Bottleneck (AIB) D = 4 ; K = 20 ; randn('state',0) ; rand('state',0) ; X1 = randn(2,300) ; X1(1,:) = X1(1,:) + 2 ; X2 = randn(2,300) ; X2(1,:) = X2(1,:) - 2 ; X3 = randn(2,300) ; X3(2,:) = X3(2,:) + 2 ; figure(1) ; clf ; hold on ; vl_plotframe(X1,'color','r') ; vl_plotframe(X2,'color','g') ; vl_plotframe(X3,'color','b') ; axis equal ; xlim([-4 4]); ylim([-4 4]); axis off ; rectangle('position',D*[-1 -1 2 2]) vl_demo_print('aib_basic_data', .6) ; C = 1:K*K ; Pcx = zeros(3,K*K) ; f1 = quantize(X1,D,K) ; f2 = quantize(X2,D,K) ; f3 = quantize(X3,D,K) ; Pcx(1,:) = vl_binsum(Pcx(1,:), ones(size(f1)), f1) ; Pcx(2,:) = vl_binsum(Pcx(2,:), ones(size(f2)), f2) ; Pcx(3,:) = vl_binsum(Pcx(3,:), ones(size(f3)), f3) ; Pcx = Pcx / sum(Pcx(:)) ; [parents, cost] = vl_aib(Pcx) ; cutsize = [K*K, 10, 3, 2, 1] ; for i=1:length(cutsize) [cut,map,short] = vl_aibcut(parents, cutsize(i)) ; parents_cut(short > 0) = parents(short(short > 0)) ; C = short(1:K*K+1) ; [drop1,drop2,C] = unique(C) ; figure(i+1) ; clf ; plotquantization(D,K,C) ; hold on ; %plottree(D,K,parents_cut) ; axis equal ; axis off ; title(sprintf('%d clusters', cutsize(i))) ; vl_demo_print(sprintf('aib_basic_clust_%d',i),.6) ; end % -------------------------------------------------------------------- function f = quantize(X,D,K) % -------------------------------------------------------------------- d = 2*D / K ; j = round((X(1,:) + D) / d) ; i = round((X(2,:) + D) / d) ; j = max(min(j,K),1) ; i = max(min(i,K),1) ; f = sub2ind([K K],i,j) ; % -------------------------------------------------------------------- function [i,j] = plotquantization(D,K,C) % -------------------------------------------------------------------- hold on ; cl = [[.3 .3 .3] ; .5*hsv(max(C)-1)+.5] ; d = 2*D / K ; for i=0:K-1 for j=0:K-1 patch(d*(j+[0 1 1 0])-D, ... d*(i+[0 0 1 1])-D, ... cl(C(j*K+i+1),:)) ; end end % -------------------------------------------------------------------- function h = plottree(D,K,parents) % -------------------------------------------------------------------- d = 2*D / K ; C = zeros(2,2*K*K-1)+NaN ; N = zeros(1,2*K*K-1) ; for i=0:K-1 for j=0:K-1 C(:,j*K+i+1) = [d*j-D; d*i-D]+d/2 ; N(:,j*K+i+1) = 1 ; end end for i=1:length(parents) p = parents(i) ; if p==0, continue ; end; if all(isnan(C(:,i))), continue; end if all(isnan(C(:,p))) C(:,p) = C(:,i) / N(i) ; else C(:,p) = C(:,p) + C(:,i) / N(i) ; end N(p) = N(p) + 1 ; end C(1,:) = C(1,:) ./ N ; C(2,:) = C(2,:) ./ N ; xt = zeros(3, 2*length(parents)-1)+NaN ; yt = zeros(3, 2*length(parents)-1)+NaN ; for i=1:length(parents) p = parents(i) ; if p==0, continue ; end; xt(1,i) = C(1,i) ; xt(2,i) = C(1,p) ; yt(1,i) = C(2,i) ; yt(2,i) = C(2,p) ; end h=line(xt(:),yt(:),'linestyle','-','marker','.','linewidth',3) ;
github
ee368/EE368-Android-Samples-master
vl_demo_alldist.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/demo/vl_demo_alldist.m
5,460
utf_8
6d008a64d93445b9d7199b55d58db7eb
function vl_demo_alldist % numRepetitions = 3 ; numDimensions = 1000 ; numSamplesRange = [300] ; settingsRange = {{'alldist2', 'double', 'l2', }, ... {'alldist', 'double', 'l2', 'nosimd'}, ... {'alldist', 'double', 'l2' }, ... {'alldist2', 'single', 'l2', }, ... {'alldist', 'single', 'l2', 'nosimd'}, ... {'alldist', 'single', 'l2' }, ... {'alldist2', 'double', 'l1', }, ... {'alldist', 'double', 'l1', 'nosimd'}, ... {'alldist', 'double', 'l1' }, ... {'alldist2', 'single', 'l1', }, ... {'alldist', 'single', 'l1', 'nosimd'}, ... {'alldist', 'single', 'l1' }, ... {'alldist2', 'double', 'chi2', }, ... {'alldist', 'double', 'chi2', 'nosimd'}, ... {'alldist', 'double', 'chi2' }, ... {'alldist2', 'single', 'chi2', }, ... {'alldist', 'single', 'chi2', 'nosimd'}, ... {'alldist', 'single', 'chi2' }, ... {'alldist2', 'double', 'hell', }, ... {'alldist', 'double', 'hell', 'nosimd'}, ... {'alldist', 'double', 'hell' }, ... {'alldist2', 'single', 'hell', }, ... {'alldist', 'single', 'hell', 'nosimd'}, ... {'alldist', 'single', 'hell' }, ... {'alldist2', 'double', 'kl2', }, ... {'alldist', 'double', 'kl2', 'nosimd'}, ... {'alldist', 'double', 'kl2' }, ... {'alldist2', 'single', 'kl2', }, ... {'alldist', 'single', 'kl2', 'nosimd'}, ... {'alldist', 'single', 'kl2' }, ... {'alldist2', 'double', 'kl1', }, ... {'alldist', 'double', 'kl1', 'nosimd'}, ... {'alldist', 'double', 'kl1' }, ... {'alldist2', 'single', 'kl1', }, ... {'alldist', 'single', 'kl1', 'nosimd'}, ... {'alldist', 'single', 'kl1' }, ... {'alldist2', 'double', 'kchi2', }, ... {'alldist', 'double', 'kchi2', 'nosimd'}, ... {'alldist', 'double', 'kchi2' }, ... {'alldist2', 'single', 'kchi2', }, ... {'alldist', 'single', 'kchi2', 'nosimd'}, ... {'alldist', 'single', 'kchi2' }, ... {'alldist2', 'double', 'khell', }, ... {'alldist', 'double', 'khell', 'nosimd'}, ... {'alldist', 'double', 'khell' }, ... {'alldist2', 'single', 'khell', }, ... {'alldist', 'single', 'khell', 'nosimd'}, ... {'alldist', 'single', 'khell' }, ... } ; %settingsRange = settingsRange(end-5:end) ; styles = {} ; for marker={'x','+','.','*','o'} for color={'r','g','b','k','y'} styles{end+1} = {'color', char(color), 'marker', char(marker)} ; end end for ni=1:length(numSamplesRange) for ti=1:length(settingsRange) tocs = [] ; for ri=1:numRepetitions rand('state',ri) ; randn('state',ri) ; numSamples = numSamplesRange(ni) ; settings = settingsRange{ti} ; [tocs(end+1), D] = run_experiment(numDimensions, ... numSamples, ... settings) ; end means(ni,ti) = mean(tocs) ; stds(ni,ti) = std(tocs) ; if mod(ti-1,3) == 0 D0 = D ; else err = max(abs(D(:)-D0(:))) ; fprintf('err %f\n', err) ; if err > 1, keyboard ; end end end end if 0 figure(1) ; clf ; hold on ; numStyles = length(styles) ; for ti=1:length(settingsRange) si = mod(ti - 1, numStyles) + 1 ; h(ti) = plot(numSamplesRange, means(:,ti), styles{si}{:}) ; leg{ti} = sprintf('%s ', settingsRange{ti}{:}) ; errorbar(numSamplesRange, means(:,ti), stds(:,ti), 'linestyle', 'none') ; end end for ti=1:length(settingsRange) leg{ti} = sprintf('%s ', settingsRange{ti}{:}) ; end figure(1) ; clf ; barh(means(end,:)) ; set(gca,'ytick', 1:length(leg), 'yticklabel', leg,'ydir','reverse') ; xlabel('Time [s]') ; function [elaps, D] = run_experiment(numDimensions, numSamples, settings) distType = 'l2' ; algType = 'alldist' ; classType = 'double' ; useSimd = true ; for si=1:length(settings) arg = settings{si} ; switch arg case {'l1', 'l2', 'chi2', 'hell', 'kl2', 'kl1', 'kchi2', 'khell'} distType = arg ; case {'alldist', 'alldist2'} algType = arg ; case {'single', 'double'} classType = arg ; case 'simd' useSimd = true ; case 'nosimd' useSimd = false ; otherwise assert(false) ; end end X = rand(numDimensions, numSamples) ; X(X < .3) = 0 ; switch classType case 'double' case 'single' X = single(X) ; end vl_simdctrl(double(useSimd)) ; switch algType case 'alldist' tic ; D = vl_alldist(X, distType) ; elaps = toc ; case 'alldist2' tic ; D = vl_alldist2(X, distType) ; elaps = toc ; end
github
ee368/EE368-Android-Samples-master
vl_demo_kdtree_sift.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/demo/vl_demo_kdtree_sift.m
6,822
utf_8
191589ff45e0f5cdb79b1eed1b1bb906
function vl_demo_kdtree_sift % VL_DEMO_KDTREE_SIFT % Demonstrates the use of a kd-tree forest to match SIFT % features. If FLANN is present, this function runs a comparison % against it. % AUTORIGHS rand('state',0) ; randn('state',0); do_median = 0 ; do_mean = 1 ; % try to setup flann if ~exist('flann_search', 'file') if exist(fullfile(vl_root, 'opt', 'flann', 'build', 'matlab')) addpath(fullfile(vl_root, 'opt', 'flann', 'build', 'matlab')) ; end end do_flann = exist('nearest_neighbors') == 3 ; if ~do_flann warning('FLANN not found. Comparison disabled.') ; end maxNumComparisonsRange = [1 10 50 100 200 300 400] ; numTreesRange = [1 2 5 10] ; % get data (SIFT features) im1 = imread(fullfile(vl_root, 'data', 'a.jpg')) ; im2 = imread(fullfile(vl_root, 'data', 'b.jpg')) ; im1 = single(rgb2gray(im1)) ; im2 = single(rgb2gray(im2)) ; [f1,d1] = vl_sift(im1,'firstoctave',-1,'floatdescriptors','verbose') ; [f2,d2] = vl_sift(im2,'firstoctave',-1,'floatdescriptors','verbose') ; % add some noise to make matches unique d1 = single(d1) + rand(size(d1)) ; d2 = single(d2) + rand(size(d2)) ; % match exhaustively to get the ground truth elapsedDirect = tic ; D = vl_alldist(d1,d2) ; [drop, best] = min(D, [], 1) ; elapsedDirect = toc(elapsedDirect) ; for ti=1:length(numTreesRange) for vi=1:length(maxNumComparisonsRange) v = maxNumComparisonsRange(vi) ; t = numTreesRange(ti) ; if do_median tic ; kdtree = vl_kdtreebuild(d1, ... 'verbose', ... 'thresholdmethod', 'median', ... 'numtrees', t) ; [i, d] = vl_kdtreequery(kdtree, d1, d2, ... 'verbose', ... 'maxcomparisons',v) ; elapsedKD_median(vi,ti) = toc ; errors_median(vi,ti) = sum(double(i) ~= best) / length(best) ; errorsD_median(vi,ti) = mean(abs(d - drop) ./ drop) ; end if do_mean tic ; kdtree = vl_kdtreebuild(d1, ... 'verbose', ... 'thresholdmethod', 'mean', ... 'numtrees', t) ; %kdtree = readflann(kdtree, '/tmp/flann.txt') ; %checkx(kdtree, d1, 1, 1) ; [i, d] = vl_kdtreequery(kdtree, d1, d2, ... 'verbose', ... 'maxcomparisons', v) ; elapsedKD_mean(vi,ti) = toc ; errors_mean(vi,ti) = sum(double(i) ~= best) / length(best) ; errorsD_mean(vi,ti) = mean(abs(d - drop) ./ drop) ; end if do_flann tic ; [i, d] = flann_search(d1, d2, 1, struct('algorithm','kdtree', ... 'trees', t, ... 'checks', v)); ifla = i ; elapsedKD_flann(vi,ti) = toc; errors_flann(vi,ti) = sum(i ~= best) / length(best) ; errorsD_flann(vi,ti) = mean(abs(d - drop) ./ drop) ; end end end figure(1) ; clf ; leg = {} ; hnd = [] ; sty = {{'color','r'},{'color','g'},... {'color','b'},{'color','c'},... {'color','k'}} ; for ti=1:length(numTreesRange) s = sty{mod(ti,length(sty))+1} ; if do_median h1=loglog(elapsedDirect ./ elapsedKD_median(:,ti),100*errors_median(:,ti),'-*',s{:}) ; hold on ; leg{end+1} = sprintf('VLFeat median (%d tr.)', numTreesRange(ti)) ; hnd(end+1) = h1 ; end if do_mean h2=loglog(elapsedDirect ./ elapsedKD_mean(:,ti), 100*errors_mean(:,ti), '-o',s{:}) ; hold on ; leg{end+1} = sprintf('VLFeat (%d tr.)', numTreesRange(ti)) ; hnd(end+1) = h2 ; end if do_flann h3=loglog(elapsedDirect ./ elapsedKD_flann(:,ti), 100*errors_flann(:,ti), '+--',s{:}) ; hold on ; leg{end+1} = sprintf('FLANN (%d tr.)', numTreesRange(ti)) ; hnd(end+1) = h3 ; end end set([hnd], 'linewidth', 2) ; xlabel('speedup over linear search (log times)') ; ylabel('percentage of incorrect matches (%)') ; h=legend(hnd, leg{:}, 'location', 'southeast') ; set(h,'fontsize',8) ; grid on ; axis square ; vl_demo_print('kdtree_sift_incorrect',.6) ; figure(2) ; clf ; leg = {} ; hnd = [] ; for ti=1:length(numTreesRange) s = sty{mod(ti,length(sty))+1} ; if do_median h1=loglog(elapsedDirect ./ elapsedKD_median(:,ti),100*errorsD_median(:,ti),'*-',s{:}) ; hold on ; leg{end+1} = sprintf('VLFeat median (%d tr.)', numTreesRange(ti)) ; hnd(end+1) = h1 ; end if do_mean h2=loglog(elapsedDirect ./ elapsedKD_mean(:,ti), 100*errorsD_mean(:,ti), 'o-',s{:}) ; hold on ; leg{end+1} = sprintf('VLFeat (%d tr.)', numTreesRange(ti)) ; hnd(end+1) = h2 ; end if do_flann h3=loglog(elapsedDirect ./ elapsedKD_flann(:,ti), 100*errorsD_flann(:,ti), '+--',s{:}) ; hold on ; leg{end+1} = sprintf('FLANN (%d tr.)', numTreesRange(ti)) ; hnd(end+1) = h3 ; end end set([hnd], 'linewidth', 2) ; xlabel('speedup over linear search (log times)') ; ylabel('relative overestimation of minmium distannce (%)') ; h=legend(hnd, leg{:}, 'location', 'southeast') ; set(h,'fontsize',8) ; grid on ; axis square ; vl_demo_print('kdtree_sift_distortion',.6) ; % -------------------------------------------------------------------- function checkx(kdtree, X, t, n, mib, mab) % -------------------------------------------------------------------- if nargin <= 4 mib = -inf * ones(size(X,1),1) ; mab = +inf * ones(size(X,1),1) ; end lc = kdtree.trees(t).nodes.lowerChild(n) ; uc = kdtree.trees(t).nodes.upperChild(n) ; if lc < 0 for i=-lc:-uc-1 di = kdtree.trees(t).dataIndex(i) ; if any(X(:,di) > mab) error('a') ; end if any(X(:,di) < mib) error('b') ; end end return end i = kdtree.trees(t).nodes.splitDimension(n) ; v = kdtree.trees(t).nodes.splitThreshold(n) ; mab_ = mab ; mab_(i) = min(mab(i), v) ; checkx(kdtree, X, t, lc, mib, mab_) ; mib_ = mib ; mib_(i) = max(mib(i), v) ; checkx(kdtree, X, t, uc, mib_, mab) ; % -------------------------------------------------------------------- function kdtree = readflann(kdtree, path) % -------------------------------------------------------------------- data = textread(path)' ; for i=1:size(data,2) nodeIds = data(1,:) ; ni = find(nodeIds == data(1,i)) ; if ~isnan(data(2,i)) % internal node li = find(nodeIds == data(4,i)) ; ri = find(nodeIds == data(5,i)) ; kdtree.trees(1).nodes.lowerChild(ni) = int32(li) ; kdtree.trees(1).nodes.upperChild(ni) = int32(ri) ; kdtree.trees(1).nodes.splitThreshold(ni) = single(data(2,i)) ; kdtree.trees(1).nodes.splitDimension(ni) = single(data(3,i)+1) ; else di = data(3,i) + 1 ; kdtree.trees(1).nodes.lowerChild(ni) = int32(- di) ; kdtree.trees(1).nodes.upperChild(ni) = int32(- di - 1) ; end kdtree.trees(1).dataIndex = uint32(1:kdtree.numData) ; end
github
ee368/EE368-Android-Samples-master
vl_tpsu.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/imop/vl_tpsu.m
1,755
utf_8
09f36e1a707c069b375eb2817d0e5f13
function [U,dU,delta]=vl_tpsu(X,Y) % VL_TPSU Compute the U matrix of a thin-plate spline transformation % U=VL_TPSU(X,Y) returns the matrix % % [ U(|X(:,1) - Y(:,1)|) ... U(|X(:,1) - Y(:,N)|) ] % [ ] % [ U(|X(:,M) - Y(:,1)|) ... U(|X(:,M) - Y(:,N)|) ] % % where X is a 2xM matrix and Y a 2xN matrix of points and U(r) is % the opposite -r^2 log(r^2) of the radial basis function of the % thin plate spline specified by X and Y. % % [U,dU]=vl_tpsu(x,y) returns the derivatives of the columns of U with % respect to the parameters Y. The derivatives are arranged in a % Mx2xN array, one layer per column of U. % % See also: VL_TPS(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). if exist('tpsumx') U = tpsumx(X,Y) ; else M=size(X,2) ; N=size(Y,2) ; % Faster than repmat, but still fairly slow r2 = ... (X( ones(N,1), :)' - Y( ones(1,M), :)).^2 + ... (X( 1+ones(N,1), :)' - Y(1+ones(1,M), :)).^2 ; U = - rb(r2) ; end if nargout > 1 M=size(X,2) ; N=size(Y,2) ; dx = X( ones(N,1), :)' - Y( ones(1,M), :) ; dy = X(1+ones(N,1), :)' - Y(1+ones(1,M), :) ; r2 = (dx.^2 + dy.^2) ; r = sqrt(r2) ; coeff = drb(r)./(r+eps) ; dU = reshape( [coeff .* dx ; coeff .* dy], M, 2, N) ; end % The radial basis function function y = rb(r2) y = zeros(size(r2)) ; sel = find(r2 ~= 0) ; y(sel) = - r2(sel) .* log(r2(sel)) ; % The derivative of the radial basis function function y = drb(r) y = zeros(size(r)) ; sel = find(r ~= 0) ; y(sel) = - 4 * r(sel) .* log(r(sel)) - 2 * r(sel) ;
github
ee368/EE368-Android-Samples-master
vl_xyz2lab.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/imop/vl_xyz2lab.m
1,570
utf_8
09f95a6f9ae19c22486ec1157357f0e3
function J=vl_xyz2lab(I,il) % VL_XYZ2LAB Convert XYZ color space to LAB % J = VL_XYZ2LAB(I) converts the image from XYZ format to LAB format. % % VL_XYZ2LAB(I,IL) uses one of the illuminants A, B, C, E, D50, D55, % D65, D75, D93. The default illuminatn is E. % % See also: VL_XYZ2LUV(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). if nargin < 2 il='E' ; end switch lower(il) case 'a' xw = 0.4476 ; yw = 0.4074 ; case 'b' xw = 0.3324 ; yw = 0.3474 ; case 'c' xw = 0.3101 ; yw = 0.3162 ; case 'e' xw = 1/3 ; yw = 1/3 ; case 'd50' xw = 0.3457 ; yw = 0.3585 ; case 'd55' xw = 0.3324 ; yw = 0.3474 ; case 'd65' xw = 0.312713 ; yw = 0.329016 ; case 'd75' xw = 0.299 ; yw = 0.3149 ; case 'd93' xw = 0.2848 ; yw = 0.2932 ; end J=zeros(size(I)) ; % Reference white Yw = 1.0 ; Xw = xw/yw ; Zw = (1-xw-yw)/yw * Yw ; % XYZ components X = I(:,:,1) ; Y = I(:,:,2) ; Z = I(:,:,3) ; x = X/Xw ; y = Y/Yw ; z = Z/Zw ; L = 116 * f(y) - 16 ; a = 500*(f(x) - f(y)) ; b = 200*(f(y) - f(z)) ; J = cat(3,L,a,b) ; % -------------------------------------------------------------------- function b=f(a) % -------------------------------------------------------------------- sp = find(a > 0.00856) ; sm = find(a <= 0.00856) ; k = 903.3 ; b=zeros(size(a)) ; b(sp) = a(sp).^(1/3) ; b(sm) = (k*a(sm) + 16)/116 ;
github
ee368/EE368-Android-Samples-master
vl_test_twister.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_twister.m
1,162
utf_8
1ae9040a416db503ad73600f081d096b
function results = vl_test_twister(varargin) % VL_TEST_TWISTER vl_test_init ; function test_illegal_args() vl_assert_exception(@() vl_twister(-1), 'vl:invalidArgument') ; vl_assert_exception(@() vl_twister(1, -1), 'vl:invalidArgument') ; vl_assert_exception(@() vl_twister([1, -1]), 'vl:invalidArgument') ; function test_seed_by_scalar() rand('twister',1) ; a = rand ; vl_twister('state',1) ; b = vl_twister ; vl_assert_equal(a,b,'seed by scalar + VL_TWISTER()') ; function test_get_set_state() rand('twister',1) ; a = rand('twister') ; vl_twister('state',1) ; b = vl_twister('state') ; vl_assert_equal(a,b,'read state') ; a(1) = a(1) + 1 ; vl_twister('state',a) ; b = vl_twister('state') ; vl_assert_equal(a,b,'set state') ; function test_multi_dimensions() b = rand('twister') ; rand('twister',b) ; vl_twister('state',b) ; a=rand([1 2 3 4 5]) ; b=vl_twister([1 2 3 4 5]) ; vl_assert_equal(a,b,'VL_TWISTER([M N P ...])') ; function test_multi_multi_args() a=rand(1, 2, 3, 4, 5) ; b=vl_twister(1, 2, 3, 4, 5) ; vl_assert_equal(a,b,'VL_TWISTER(M, N, P, ...)') ; function test_square() a=rand(10) ; b=vl_twister(10) ; vl_assert_equal(a,b,'VL_TWISTER(N)') ;
github
ee368/EE368-Android-Samples-master
vl_test_kdtree.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_kdtree.m
2,448
utf_8
66f429ff8286089a34c193d7d3f9f016
function results = vl_test_kdtree(varargin) % VL_TEST_KDTREE vl_test_init ; function s = setup() randn('state',0) ; s.X = single(randn(10, 1000)) ; s.Q = single(randn(10, 10)) ; function test_nearest(s) for tmethod = {'median', 'mean'} for type = {@single, @double} conv = type{1} ; tmethod = char(tmethod) ; X = conv(s.X) ; Q = conv(s.Q) ; tree = vl_kdtreebuild(X,'ThresholdMethod', tmethod) ; [nn, d2] = vl_kdtreequery(tree, X,Q) ; D2 = vl_alldist2(X, Q, 'l2') ; [d2_, nn_] = min(D2) ; vl_assert_equal(... nn,uint32(nn_),... 'incorrect nns: type=%s th. method=%s', func2str(conv), tmethod) ; vl_assert_almost_equal(... d2,d2_,... 'incorrect distances: type=%s th. method=%s', func2str(conv), tmethod) ; end end function test_nearests(s) numNeighbors = 7 ; tree = vl_kdtreebuild(s.X) ; [nn, d2] = vl_kdtreequery(tree, s.X, s.Q, ... 'numNeighbors', numNeighbors) ; D2 = vl_alldist2(s.X, s.Q, 'l2') ; [d2_, nn_] = sort(D2) ; d2_ = d2_(1:numNeighbors, :) ; nn_ = nn_(1:numNeighbors, :) ; vl_assert_equal(nn,uint32(nn_)) ; vl_assert_almost_equal(d2,d2_) ; function test_ann(s) vl_twister('state', 1) ; numNeighbors = 7 ; maxComparisons = numNeighbors * 50 ; tree = vl_kdtreebuild(s.X) ; [nn, d2] = vl_kdtreequery(tree, s.X, s.Q, ... 'numNeighbors', numNeighbors, ... 'maxComparisons', maxComparisons) ; D2 = vl_alldist2(s.X, s.Q, 'l2') ; [d2_, nn_] = sort(D2) ; d2_ = d2_(1:numNeighbors, :) ; nn_ = nn_(1:numNeighbors, :) ; for i=1:size(s.Q,2) overlap = numel(intersect(nn(:,i), nn_(:,i))) / ... numel(union(nn(:,i), nn_(:,i))) ; assert(overlap > 0.6, 'ANN did not return enough correct nearest neighbors') ; end function test_ann_forest(s) vl_twister('state', 1) ; numNeighbors = 7 ; maxComparisons = numNeighbors * 25 ; numTrees = 5 ; tree = vl_kdtreebuild(s.X, 'numTrees', 5) ; [nn, d2] = vl_kdtreequery(tree, s.X, s.Q, ... 'numNeighbors', numNeighbors, ... 'maxComparisons', maxComparisons) ; D2 = vl_alldist2(s.X, s.Q, 'l2') ; [d2_, nn_] = sort(D2) ; d2_ = d2_(1:numNeighbors, :) ; nn_ = nn_(1:numNeighbors, :) ; for i=1:size(s.Q,2) overlap = numel(intersect(nn(:,i), nn_(:,i))) / ... numel(union(nn(:,i), nn_(:,i))) ; assert(overlap > 0.6, 'ANN did not return enough correct nearest neighbors') ; end
github
ee368/EE368-Android-Samples-master
vl_test_imwbackward.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_imwbackward.m
514
utf_8
33baa0784c8f6f785a2951d7f1b49199
function results = vl_test_imwbackward(varargin) % VL_TEST_IMWBACKWARD vl_test_init ; function s = setup() s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ; function test_identity(s) xr = 1:size(s.I,2) ; yr = 1:size(s.I,1) ; [x,y] = meshgrid(xr,yr) ; vl_assert_almost_equal(s.I, vl_imwbackward(xr,yr,s.I,x,y)) ; function test_invalid_args(s) xr = 1:size(s.I,2) ; yr = 1:size(s.I,1) ; [x,y] = meshgrid(xr,yr) ; vl_assert_exception(@() vl_imwbackward(xr,yr,single(s.I),x,y), 'vl:invalidArgument') ;
github
ee368/EE368-Android-Samples-master
vl_test_pegasos.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_pegasos.m
2,852
utf_8
45a09a3bfefa3facd439fefbb7f1a903
function results = vl_test_pegasos(varargin) % VL_TEST_KDTREE vl_test_init ; function s = setup() randn('state',0) ; s.biasMultiplier = 10 ; s.lambda = 0.01 ; Np = 10 ; Nn = 10 ; Xp = diag([1 3])*randn(2, Np) ; Xn = diag([1 3])*randn(2, Nn) ; Xp(1,:) = Xp(1,:) + 2 + 1 ; Xn(1,:) = Xn(1,:) - 2 + 1 ; s.X = [Xp Xn] ; s.y = [ones(1,Np) -ones(1,Nn)] ; %s.w = exact_solver(s.X, s.y, s.lambda, s.biasMultiplier) s.w = [1.181106685845652 ; 0.098478251033487 ; -0.154057992404545 ] ; function test_problem_1(s) for conv = {@single,@double} vl_twister('state',0) ; conv = conv{1} ; w = vl_pegasos(conv(s.X), int8(s.y), s.lambda, ... 'NumIterations', 100000, ... 'BiasMultiplier', s.biasMultiplier, ... 'Preconditioner', conv([1 1 .1])) ; vl_assert_almost_equal(w, conv(s.w), 0.1) ; end function test_continue_training(s) for conv = {@single,@double} conv = conv{1} ; vl_twister('state',0) ; w = vl_pegasos(conv(s.X), int8(s.y), s.lambda, ... 'NumIterations', 3000, ... 'BiasMultiplier', s.biasMultiplier) ; vl_twister('state',0) ; w1 = vl_pegasos(conv(s.X), int8(s.y), s.lambda, ... 'StartingIteration', 1, ... 'NumIterations', 1500, ... 'BiasMultiplier', s.biasMultiplier) ; w2 = vl_pegasos(conv(s.X), int8(s.y), s.lambda, ... 'StartingIteration', 1501, ... 'StartingModel', w1, ... 'NumIterations', 1500, ... 'BiasMultiplier', s.biasMultiplier) ; vl_assert_almost_equal(w,w2,1e-7) ; end function test_continue_training_with_perm(s) perm = uint32(randperm(size(s.X,2))) ; for conv = {@single,@double} conv = conv{1} ; vl_twister('state',0) ; w = vl_pegasos(conv(s.X), int8(s.y), s.lambda, ... 'NumIterations', 3000, ... 'BiasMultiplier', s.biasMultiplier, ... 'Permutation', perm) ; vl_twister('state',0) ; w1 = vl_pegasos(conv(s.X), int8(s.y), s.lambda, ... 'StartingIteration', 1, ... 'NumIterations', 1500, ... 'BiasMultiplier', s.biasMultiplier, ... 'Permutation', perm) ; w2 = vl_pegasos(conv(s.X), int8(s.y), s.lambda, ... 'StartingIteration', 1501, ... 'StartingModel', w1, ... 'NumIterations', 1500, ... 'BiasMultiplier', s.biasMultiplier, ... 'Permutation', perm) ; vl_assert_almost_equal(w,w2,1e-7) ; end function w = exact_solver(X, y, lambda, biasMultiplier) N = size(X,2) ; model = svmtrain(y', [(1:N)' X'*X], sprintf(' -c %f -t 4 ', 1/(lambda*N))) ; w = X(:,model.SVs) * model.sv_coef ; w(3) = - model.rho / biasMultiplier ; format long ; disp('model w:') disp(w)
github
ee368/EE368-Android-Samples-master
vl_test_alphanum.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_alphanum.m
1,624
utf_8
2da2b768c2d0f86d699b8f31614aa424
function results = vl_test_alphanum(varargin) % VL_TEST_ALPHANUM vl_test_init ; function s = setup() s.strings = ... {'1000X Radonius Maximus','10X Radonius','200X Radonius','20X Radonius','20X Radonius Prime','30X Radonius','40X Radonius','Allegia 50 Clasteron','Allegia 500 Clasteron','Allegia 50B Clasteron','Allegia 51 Clasteron','Allegia 6R Clasteron','Alpha 100','Alpha 2','Alpha 200','Alpha 2A','Alpha 2A-8000','Alpha 2A-900','Callisto Morphamax','Callisto Morphamax 500','Callisto Morphamax 5000','Callisto Morphamax 600','Callisto Morphamax 6000 SE','Callisto Morphamax 6000 SE2','Callisto Morphamax 700','Callisto Morphamax 7000','Xiph Xlater 10000','Xiph Xlater 2000','Xiph Xlater 300','Xiph Xlater 40','Xiph Xlater 5','Xiph Xlater 50','Xiph Xlater 500','Xiph Xlater 5000','Xiph Xlater 58'} ; s.sortedStrings = ... {'10X Radonius','20X Radonius','20X Radonius Prime','30X Radonius','40X Radonius','200X Radonius','1000X Radonius Maximus','Allegia 6R Clasteron','Allegia 50 Clasteron','Allegia 50B Clasteron','Allegia 51 Clasteron','Allegia 500 Clasteron','Alpha 2','Alpha 2A','Alpha 2A-900','Alpha 2A-8000','Alpha 100','Alpha 200','Callisto Morphamax','Callisto Morphamax 500','Callisto Morphamax 600','Callisto Morphamax 700','Callisto Morphamax 5000','Callisto Morphamax 6000 SE','Callisto Morphamax 6000 SE2','Callisto Morphamax 7000','Xiph Xlater 5','Xiph Xlater 40','Xiph Xlater 50','Xiph Xlater 58','Xiph Xlater 300','Xiph Xlater 500','Xiph Xlater 2000','Xiph Xlater 5000','Xiph Xlater 10000'} ; function test_basic(s) sorted = vl_alphanum(s.strings) ; assert(isequal(sorted,s.sortedStrings)) ;
github
ee368/EE368-Android-Samples-master
vl_test_imintegral.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_imintegral.m
1,429
utf_8
4750f04ab0ac9fc4f55df2c8583e5498
function results = vl_test_imintegral(varargin) % VL_TEST_IMINTEGRAL vl_test_init ; function state = setup() state.I = ones(5,6) ; state.correct = [ 1 2 3 4 5 6 ; 2 4 6 8 10 12 ; 3 6 9 12 15 18 ; 4 8 12 16 20 24 ; 5 10 15 20 25 30 ; ] ; function test_matlab_equivalent(s) vl_assert_equal(slow_imintegral(s.I), s.correct) ; function test_basic(s) vl_assert_equal(vl_imintegral(s.I), s.correct) ; function test_multi_dimensional(s) vl_assert_equal(vl_imintegral(repmat(s.I, [1 1 3])), ... repmat(s.correct, [1 1 3])) ; function test_random(s) numTests = 50 ; for i = 1:numTests I = rand(5) ; vl_assert_almost_equal(vl_imintegral(s.I), ... slow_imintegral(s.I)) ; end function test_datatypes(s) vl_assert_equal(single(vl_imintegral(s.I)), single(s.correct)) ; vl_assert_equal(double(vl_imintegral(s.I)), double(s.correct)) ; vl_assert_equal(uint32(vl_imintegral(s.I)), uint32(s.correct)) ; vl_assert_equal(int32(vl_imintegral(s.I)), int32(s.correct)) ; vl_assert_equal(int32(vl_imintegral(-s.I)), -int32(s.correct)) ; function integral = slow_imintegral(I) integral = zeros(size(I)); for k = 1:size(I,3) for r = 1:size(I,1) for c = 1:size(I,2) integral(r,c,k) = sum(sum(I(1:r,1:c,k))); end end end
github
ee368/EE368-Android-Samples-master
vl_test_sift.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_sift.m
1,318
utf_8
806c61f9db9f2ebb1d649c9bfcf3dc0a
function results = vl_test_sift(varargin) % VL_TEST_SIFT vl_test_init ; function s = setup() s.I = im2single(imread(fullfile(vl_root,'data','box.pgm'))) ; [s.ubc.f, s.ubc.d] = ... vl_ubcread(fullfile(vl_root,'data','box.sift')) ; function test_ubc_descriptor(s) err = [] ; [f, d] = vl_sift(s.I,... 'firstoctave', -1, ... 'frames', s.ubc.f) ; D2 = vl_alldist(f, s.ubc.f) ; [drop, perm] = min(D2) ; f = f(:,perm) ; d = d(:,perm) ; error = mean(sqrt(sum((single(s.ubc.d) - single(d)).^2))) ... / mean(sqrt(sum(single(s.ubc.d).^2))) ; assert(error < 0.1, ... 'sift descriptor did not produce desctiptors similar to UBC ones') ; function test_ubc_detector(s) [f, d] = vl_sift(s.I,... 'firstoctave', -1, ... 'peakthresh', .01, ... 'edgethresh', 10) ; s.ubc.f(4,:) = mod(s.ubc.f(4,:), 2*pi) ; f(4,:) = mod(f(4,:), 2*pi) ; % scale the components so that 1 pixel erro in x,y,z is equal to a % 10-th of angle. S = diag([1 1 1 20/pi]); D2 = vl_alldist(S * s.ubc.f, S * f) ; [d2,perm] = sort(min(D2)) ; error = sqrt(d2) ; quant80 = round(.8 * size(f,2)) ; % check for less than one pixel error at 80% quantile assert(error(quant80) < 1, ... 'sift detector did not produce enough keypoints similar to UBC ones') ;
github
ee368/EE368-Android-Samples-master
vl_test_binsum.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_binsum.m
1,301
utf_8
5bbd389cbc4d997e413d809fe4efda6d
function results = vl_test_binsum(varargin) % VL_TEST_BINSUM vl_test_init ; function test_three_args() vl_assert_almost_equal(... vl_binsum([0 0], 1, 2), [0 1]) ; vl_assert_almost_equal(... vl_binsum([1 7], -1, 1), [0 7]) ; vl_assert_almost_equal(... vl_binsum([1 7], -1, [1 2 2 2 2 2 2 2]), [0 0]) ; function test_four_args() vl_assert_almost_equal(... vl_binsum(eye(3), [1 1 1], [1 2 3], 1), 2*eye(3)) ; vl_assert_almost_equal(... vl_binsum(eye(3), [1 1 1]', [1 2 3]', 2), 2*eye(3)) ; vl_assert_almost_equal(... vl_binsum(eye(3), 1, [1 2 3], 1), 2*eye(3)) ; vl_assert_almost_equal(... vl_binsum(eye(3), 1, [1 2 3]', 2), 2*eye(3)) ; function test_3d_one() Z = zeros(3,3,3) ; B = 3*ones(3,1,3) ; R = Z ; R(:,3,:) = 17 ; vl_assert_almost_equal(... vl_binsum(Z, 17, B, 2), R) ; function test_3d_two() Z = zeros(3,3,3) ; B = 3*ones(3,3,1) ; X = zeros(3,3,1) ; X(:,:,1) = 17 ; R = Z ; R(:,:,3) = 17 ; vl_assert_almost_equal(... vl_binsum(Z, X, B, 3), R) ; function test_storage_classes() types = {@double, @single, @int64, @uint64, ... @int32, @uint32, @int16, @uint16, ... @int8, @uint8} ; for a = types a = a{1} ; for b = types b = b{1} ; vl_assert_almost_equal(... vl_binsum(a(eye(3)), a([1 1 1]), b([1 2 3]), 1), a(2*eye(3))) ; end end
github
ee368/EE368-Android-Samples-master
vl_test_lbp.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_lbp.m
1,056
utf_8
3b5cca50109af84014e56a4280a3352a
function results = vl_test_lbp(varargin) % VL_TEST_TWISTER vl_test_init ; function test_one_on() I = {} ; I{1} = [0 0 0 ; 0 0 1 ; 0 0 0] ; I{2} = [0 0 0 ; 0 0 0 ; 0 0 1] ; I{3} = [0 0 0 ; 0 0 0 ; 0 1 0] ; I{4} = [0 0 0 ; 0 0 0 ; 1 0 0] ; I{5} = [0 0 0 ; 1 0 0 ; 0 0 0] ; I{6} = [1 0 0 ; 0 0 0 ; 0 0 0] ; I{7} = [0 1 0 ; 0 0 0 ; 0 0 0] ; I{8} = [0 0 1 ; 0 0 0 ; 0 0 0] ; for j=0:7 h = vl_lbp(single(I{j+1}), 3) ; h = find(squeeze(h)) ; vl_assert_equal(h, j * 7 + 1) ; end function test_two_on() I = {} ; I{1} = [0 0 0 ; 0 0 1 ; 0 0 1] ; I{2} = [0 0 0 ; 0 0 0 ; 0 1 1] ; I{3} = [0 0 0 ; 0 0 0 ; 1 1 0] ; I{4} = [0 0 0 ; 1 0 0 ; 1 0 0] ; I{5} = [1 0 0 ; 1 0 0 ; 0 0 0] ; I{6} = [1 1 0 ; 0 0 0 ; 0 0 0] ; I{7} = [0 1 1 ; 0 0 0 ; 0 0 0] ; I{8} = [0 0 1 ; 0 0 1 ; 0 0 0] ; for j=0:7 h = vl_lbp(single(I{j+1}), 3) ; h = find(squeeze(h)) ; vl_assert_equal(h, j * 7 + 2) ; end function test_fliplr() randn('state',0) ; I = randn(256,256,1,'single') ; f = vl_lbp(fliplr(I), 8) ; f_ = vl_lbpfliplr(vl_lbp(I, 8)) ; vl_assert_almost_equal(f,f_,1e-3) ;
github
ee368/EE368-Android-Samples-master
vl_test_colsubset.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_colsubset.m
828
utf_8
be0c080007445b36333b863326fb0f15
function results = vl_test_colsubset(varargin) % VL_TEST_COLSUBSET vl_test_init ; function s = setup() s.x = [5 2 3 6 4 7 1 9 8 0] ; function test_beginning(s) vl_assert_equal(1:5, vl_colsubset(1:10, 5, 'beginning')) ; vl_assert_equal(1:5, vl_colsubset(1:10, .5, 'beginning')) ; function test_ending(s) vl_assert_equal(6:10, vl_colsubset(1:10, 5, 'ending')) ; vl_assert_equal(6:10, vl_colsubset(1:10, .5, 'ending')) ; function test_largest(s) vl_assert_equal([5 6 7 9 8], vl_colsubset(s.x, 5, 'largest')) ; vl_assert_equal([5 6 7 9 8], vl_colsubset(s.x, .5, 'largest')) ; function test_smallest(s) vl_assert_equal([2 3 4 1 0], vl_colsubset(s.x, 5, 'smallest')) ; vl_assert_equal([2 3 4 1 0], vl_colsubset(s.x, .5, 'smallest')) ; function test_random(s) assert(numel(intersect(s.x, vl_colsubset(s.x, 5, 'random'))) == 5) ;
github
ee368/EE368-Android-Samples-master
vl_test_alldist.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_alldist.m
2,373
utf_8
9ea1a36c97fe715dfa2b8693876808ff
function results = vl_test_alldist(varargin) % VL_TEST_ALLDIST vl_test_init ; function s = setup() vl_twister('state', 0) ; s.X = 3.1 * vl_twister(10,10) ; s.Y = 4.7 * vl_twister(10,7) ; function test_null_args(s) vl_assert_equal(... vl_alldist(zeros(15,12), zeros(15,0), 'kl2'), ... zeros(12,0)) ; vl_assert_equal(... vl_alldist(zeros(15,0), zeros(15,0), 'kl2'), ... zeros(0,0)) ; vl_assert_equal(... vl_alldist(zeros(15,0), zeros(15,12), 'kl2'), ... zeros(0,12)) ; vl_assert_equal(... vl_alldist(zeros(0,15), zeros(0,12), 'kl2'), ... zeros(15,12)) ; function test_self(s) vl_assert_almost_equal(... vl_alldist(s.X, 'kl2'), ... makedist(@(x,y) x*y, s.X, s.X), ... 1e-6) ; function test_distances(s) dists = {'chi2', 'l2', 'l1', 'hell', 'js', ... 'kchi2', 'kl2', 'kl1', 'khell', 'kjs'} ; distsEquiv = { ... @(x,y) (x-y)^2 / (x + y), ... @(x,y) (x-y)^2, ... @(x,y) abs(x-y), ... @(x,y) (sqrt(x) - sqrt(y))^2, ... @(x,y) x - x .* log2(1 + y/x) + y - y .* log2(1 + x/y), ... @(x,y) 2 * (x*y) / (x + y), ... @(x,y) x*y, ... @(x,y) min(x,y), ... @(x,y) sqrt(x.*y), ... @(x,y) .5 * (x .* log2(1 + y/x) + y .* log2(1 + x/y))} ; types = {'single', 'double'} ; for simd = [0 1] for d = 1:length(dists) for t = 1:length(types) vl_simdctrl(simd) ; X = feval(str2func(types{t}), s.X) ; Y = feval(str2func(types{t}), s.Y) ; vl_assert_almost_equal(... vl_alldist(X,Y,dists{d}), ... makedist(distsEquiv{d},X,Y), ... 1e-4, ... 'alldist failed for dist=%s type=%s simd=%d', ... dists{d}, ... types{t}, ... simd) ; end end end function test_distance_kernel_pairs(s) dists = {'chi2', 'l2', 'l1', 'hell', 'js'} ; for d = 1:length(dists) dist = char(dists{d}) ; X = s.X ; Y = s.Y ; ker = ['k' dist] ; kxx = vl_alldist(X,X,ker) ; kyy = vl_alldist(Y,Y,ker) ; kxy = vl_alldist(X,Y,ker) ; kxx = repmat(diag(kxx), 1, size(s.Y,2)) ; kyy = repmat(diag(kyy), 1, size(s.X,1))' ; d2 = vl_alldist(X,Y,dist) ; vl_assert_almost_equal(d2, kxx + kyy - 2 * kxy, '1e-6') ; end function D = makedist(cmp,X,Y) [d,m] = size(X) ; [d,n] = size(Y) ; D = zeros(m,n) ; for i = 1:m for j = 1:n acc = 0 ; for k = 1:d acc = acc + cmp(X(k,i),Y(k,j)) ; end D(i,j) = acc ; end end conv = str2func(class(X)) ; D = conv(D) ;
github
ee368/EE368-Android-Samples-master
vl_test_grad.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_grad.m
434
utf_8
4d03eb33a6a4f68659f868da95930ffb
function results = vl_test_grad(varargin) % VL_TEST_GRAD vl_test_init ; function s = setup() s.I = rand(150,253) ; s.I_small = rand(2,2) ; function test_equiv(s) vl_assert_equal(gradient(s.I), vl_grad(s.I)) ; function test_equiv_small(s) vl_assert_equal(gradient(s.I_small), vl_grad(s.I_small)) ; function test_equiv_forward(s) Ix = diff(s.I,2,1) ; Iy = diff(s.I,2,1) ; vl_assert_equal(gradient(s.I_small), vl_grad(s.I_small)) ;
github
ee368/EE368-Android-Samples-master
vl_test_whistc.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_whistc.m
1,384
utf_8
81c446d35c82957659840ab2a579ec2c
function results = vl_test_whistc(varargin) % VL_TEST_WHISTC vl_test_init ; function test_acc() x = ones(1, 10) ; e = 1 ; o = 1:10 ; vl_assert_equal(vl_whistc(x, o, e), 55) ; function test_basic() x = 1:10 ; e = 1:10 ; o = ones(1, 10) ; vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ; x = linspace(-1,11,100) ; o = ones(size(x)) ; vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ; function test_multidim() x = rand(10, 20, 30) ; e = linspace(0,1,10) ; o = ones(size(x)) ; vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ; vl_assert_equal(histc(x, e, 1), vl_whistc(x, o, e, 1)) ; vl_assert_equal(histc(x, e, 2), vl_whistc(x, o, e, 2)) ; vl_assert_equal(histc(x, e, 3), vl_whistc(x, o, e, 3)) ; function test_nan() x = rand(10, 20, 30) ; e = linspace(0,1,10) ; o = ones(size(x)) ; x(1:7:end) = NaN ; vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ; vl_assert_equal(histc(x, e, 1), vl_whistc(x, o, e, 1)) ; vl_assert_equal(histc(x, e, 2), vl_whistc(x, o, e, 2)) ; vl_assert_equal(histc(x, e, 3), vl_whistc(x, o, e, 3)) ; function test_no_edges() x = rand(10, 20, 30) ; o = ones(size(x)) ; vl_assert_equal(histc(1, []), vl_whistc(1, 1, [])) ; vl_assert_equal(histc(x, []), vl_whistc(x, o, [])) ; vl_assert_equal(histc(x, [], 1), vl_whistc(x, o, [], 1)) ; vl_assert_equal(histc(x, [], 2), vl_whistc(x, o, [], 2)) ; vl_assert_equal(histc(x, [], 3), vl_whistc(x, o, [], 3)) ;
github
ee368/EE368-Android-Samples-master
vl_test_dsift.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_dsift.m
2,048
utf_8
fbbfb16d5a21936c1862d9551f657ccc
function results = vl_test_dsift(varargin) % VL_TEST_DSIFT vl_test_init ; function s = setup() I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ; s.I = rgb2gray(single(I)) ; function test_fast_slow(s) binSize = 4 ; % bin size in pixels magnif = 3 ; % bin size / keypoint scale scale = binSize / magnif ; windowSize = 5 ; [f, d] = vl_dsift(vl_imsmooth(s.I, sqrt(scale.^2 - .25)), ... 'size', binSize, ... 'step', 10, ... 'bounds', [20,20,210,140], ... 'windowsize', windowSize, ... 'floatdescriptors') ; [f_, d_] = vl_dsift(vl_imsmooth(s.I, sqrt(scale.^2 - .25)), ... 'size', binSize, ... 'step', 10, ... 'bounds', [20,20,210,140], ... 'windowsize', windowSize, ... 'floatdescriptors', ... 'fast') ; error = std(d_(:) - d(:)) / std(d(:)) ; assert(error < 0.1, 'dsift fast approximation not close') ; function test_sift(s) binSize = 4 ; % bin size in pixels magnif = 3 ; % bin size / keypoint scale scale = binSize / magnif ; windowSizeRange = [1 1.2 5] ; for wi = 1:length(windowSizeRange) windowSize = windowSizeRange(wi) ; [f, d] = vl_dsift(vl_imsmooth(s.I, sqrt(scale.^2 - .25)), ... 'size', binSize, ... 'step', 10, ... 'bounds', [20,20,210,140], ... 'windowsize', windowSize, ... 'floatdescriptors') ; numKeys = size(f, 2) ; f_ = [f ; ones(1, numKeys) * scale ; zeros(1, numKeys)] ; [f_, d_] = vl_sift(s.I, ... 'magnif', magnif, ... 'frames', f_, ... 'firstoctave', -1, ... 'levels', 5, ... 'floatdescriptors', ... 'windowsize', windowSize) ; error = std(d_(:) - d(:)) / std(d(:)) ; assert(error < 0.1, 'dsift and sift equivalence') ; end
github
ee368/EE368-Android-Samples-master
vl_test_imsmooth.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_imsmooth.m
1,837
utf_8
718235242cad61c9804ba5e881c22f59
function results = vl_test_imsmooth(varargin) % VL_TEST_IMSMOOTH vl_test_init ; function s = setup() I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ; I = max(min(vl_imdown(I),1),0) ; s.I = single(I) ; function test_pad_by_continuity(s) % Convolving a constant signal padded with continuity does not change % the signal. I = ones(3) ; for ker = {'triangular', 'gaussian'} ker = char(ker) ; J = vl_imsmooth(I, 2, ... 'kernel', ker, ... 'padding', 'continuity') ; vl_assert_almost_equal(J, I, 1e-4, ... 'padding by continutiy with kernel = %s', ker) ; end function test_kernels(s) for ker = {'triangular', 'gaussian'} ker = char(ker) ; for type = {@single, @double} for simd = [0 1] for sigma = [1 2 7] for step = [1 2 3] vl_simdctrl(simd) ; conv = type{1} ; g = equivalent_kernel(ker, sigma) ; J = vl_imsmooth(conv(s.I), sigma, ... 'kernel', ker, ... 'padding', 'zero', ... 'subsample', step) ; J_ = conv(convolve(s.I, g, step)) ; vl_assert_almost_equal(J, J_, 1e-4, ... 'kernel=%s sigma=%f step=%d simd=%d', ... ker, sigma, step, simd) ; end end end end end function g = equivalent_kernel(ker, sigma) switch ker case 'gaussian' W = ceil(4*sigma) ; g = exp(-.5*((-W:W)/(sigma+eps)).^2) ; case 'triangular' W = max(round(sigma),1) ; g = W - abs(-W+1:W-1) ; end g = g / sum(g) ; function I = convolve(I, g, step) if strcmp(class(I),'single') g = single(g) ; else g = double(g) ; end for k=1:size(I,3) I(:,:,k) = conv2(g,g,I(:,:,k),'same'); end I = I(1:step:end,1:step:end,:) ;
github
ee368/EE368-Android-Samples-master
vl_test_phow.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_phow.m
549
utf_8
f761a3bb218af855986263c67b2da411
function results = vl_test_phow(varargin) % VL_TEST_PHOPW vl_test_init ; function s = setup() s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ; s.I = single(s.I) ; function test_gray(s) [f,d] = vl_phow(s.I, 'color', 'gray') ; assert(size(d,1) == 128) ; function test_rgb(s) [f,d] = vl_phow(s.I, 'color', 'rgb') ; assert(size(d,1) == 128*3) ; function test_hsv(s) [f,d] = vl_phow(s.I, 'color', 'hsv') ; assert(size(d,1) == 128*3) ; function test_opponent(s) [f,d] = vl_phow(s.I, 'color', 'opponent') ; assert(size(d,1) == 128*3) ;
github
ee368/EE368-Android-Samples-master
vl_test_kmeans.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_kmeans.m
2,788
utf_8
14374b7dbae832fc3509e02caf00cdf5
function results = vl_test_kmeans(varargin) % VL_TEST_KMEANS % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). vl_test_init ; function s = setup() randn('state',0) ; s.X = randn(128, 100) ; function test_basic(s) [centers, assignments, en] = vl_kmeans(s.X, 10, 'NumRepetitions', 10) ; [centers_, assignments_, en_] = simpleKMeans(s.X, 10) ; assert(en_ <= 1.1 * en, 'vl_kmeans did not optimize enough') ; function test_algorithms(s) distances = {'l1', 'l2'} ; dataTypes = {'single','double'} ; for dataType = dataTypes for distance = distances distance = char(distance) ; conversion = str2func(char(dataType)) ; X = conversion(s.X) ; vl_twister('state',0) ; [centers, assignments, en] = vl_kmeans(X, 10, ... 'NumRepetitions', 1, ... 'MaxNumIterations', 10, ... 'Algorithm', 'Lloyd', ... 'Distance', distance) ; vl_twister('state',0) ; [centers_, assignments_, en_] = vl_kmeans(X, 10, ... 'NumRepetitions', 1, ... 'MaxNumIterations', 10, ... 'Algorithm', 'Elkan', ... 'Distance', distance) ; vl_assert_almost_equal(centers, centers_, 1e-5) ; vl_assert_almost_equal(assignments, assignments_, 1e-5) ; vl_assert_almost_equal(en, en_, 1e-5) ; end end function test_patterns(s) distances = {'l1', 'l2'} ; dataTypes = {'single','double'} ; for dataType = dataTypes for distance = distances distance = char(distance) ; conversion = str2func(char(dataType)) ; data = [1 1 0 0 ; 1 0 1 0] ; data = conversion(data) ; [centers, assignments, en] = vl_kmeans(data, 4, ... 'NumRepetitions', 100, ... 'Distance', distance) ; assert(isempty(setdiff(data', centers', 'rows'))) ; end end function [centers, assignments, en] = simpleKMeans(X, numCenters) [dimension, numData] = size(X) ; centers = randn(dimension, numCenters) ; for iter = 1:10 [dists, assignments] = min(vl_alldist(centers, X)) ; en = sum(dists) ; centers = [zeros(dimension, numCenters) ; ones(1, numCenters)] ; centers = vl_binsum(centers, ... [X ; ones(1,numData)], ... repmat(assignments, dimension+1, 1), 2) ; centers = centers(1:end-1, :) ./ repmat(centers(end,:), dimension, 1) ; end
github
ee368/EE368-Android-Samples-master
vl_test_imarray.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_imarray.m
795
utf_8
c5e6a5aa8c2e63e248814f5bd89832a8
function results = vl_test_imarray(varargin) % VL_TEST_IMARRAY vl_test_init ; function test_movie_rgb(s) A = rand(23,15,3,4) ; B = vl_imarray(A,'movie',true) ; function test_movie_indexed(s) cmap = get(0,'DefaultFigureColormap') ; A = uint8(size(cmap,1)*rand(23,15,4)) ; A = min(A,size(cmap,1)-1) ; B = vl_imarray(A,'movie',true) ; function test_movie_gray_indexed(s) A = uint8(255*rand(23,15,4)) ; B = vl_imarray(A,'movie',true,'cmap',gray(256)) ; for k=1:size(A,3) vl_assert_equal(squeeze(A(:,:,k)), ... frame2im(B(k))) ; end function test_basic(s) M = 3 ; N = 4 ; width = 32 ; height = 15 ; for i=1:M for j=1:N A{i,j} = rand(width,height) ; end end A1 = A'; A1 = cat(3,A1{:}) ; A2 = cell2mat(A) ; B = vl_imarray(A1, 'layout', [M N]) ; vl_assert_equal(A2,B) ;
github
ee368/EE368-Android-Samples-master
vl_test_homkermap.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_homkermap.m
1,903
utf_8
c157052bf4213793a961bde1f73fb307
function results = vl_test_homkermap(varargin) % VL_TEST_HOMKERMAP vl_test_init ; function check_ker(ker, n, window, period) args = {n, ker, 'window', window} ; if nargin > 3 args = {args{:}, 'period', period} ; end x = [-1 -.5 0 .5 1] ; y = linspace(0,2,100) ; for conv = {@single, @double} x = feval(conv{1}, x) ; y = feval(conv{1}, y) ; sx = sign(x) ; sy = sign(y) ; psix = vl_homkermap(x, args{:}) ; psiy = vl_homkermap(y, args{:}) ; k = vl_alldist(psix,psiy,'kl2') ; k_ = (sx'*sy) .* vl_alldist(sx.*x,sy.*y,ker) ; vl_assert_almost_equal(k, k_, 2e-2) ; end function test_uniform_kchi2(), check_ker('kchi2', 3, 'uniform', 15) ; function test_uniform_kjs(), check_ker('kjs', 3, 'uniform', 15) ; function test_uniform_kl1(), check_ker('kl1', 29, 'uniform', 15) ; function test_rect_kchi2(), check_ker('kchi2', 3, 'rectangular', 15) ; function test_rect_kjs(), check_ker('kjs', 3, 'rectangular', 15) ; function test_rect_kl1(), check_ker('kl1', 29, 'rectangular', 10) ; function test_auto_uniform_kchi2(),check_ker('kchi2', 3, 'uniform') ; function test_auto_uniform_kjs(), check_ker('kjs', 3, 'uniform') ; function test_auto_uniform_kl1(), check_ker('kl1', 25, 'uniform') ; function test_auto_rect_kchi2(), check_ker('kchi2', 3, 'rectangular') ; function test_auto_rect_kjs(), check_ker('kjs', 3, 'rectangular') ; function test_auto_rect_kl1(), check_ker('kl1', 25, 'rectangular') ; function test_gamma() x = linspace(0,1,20) ; for gamma = linspace(.2,2,10) k = vl_alldist(x, 'kchi2') .* (x'*x + 1e-12).^((gamma-1)/2) ; psix = vl_homkermap(x, 3, 'kchi2', 'gamma', gamma) ; assert(norm(k - psix'*psix) < 1e-2) ; end function test_negative() x = linspace(-1,1,20) ; k = vl_alldist(abs(x), 'kchi2') .* (sign(x)'*sign(x)) ; psix = vl_homkermap(x, 3, 'kchi2') ; assert(norm(k - psix'*psix) < 1e-2) ;
github
ee368/EE368-Android-Samples-master
vl_test_slic.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_slic.m
229
utf_8
42c827b383cca74cae2540e5da870bbf
function results = vl_test_slic(varargin) % VL_TEST_SLIC vl_test_init ; function s = setup() s.im = im2single(imread(fullfile(vl_root,'data','a.jpg'))) ; function test_slic(s) segmentation = vl_slic(s.im, 10, 0.1, 'verbose') ;
github
ee368/EE368-Android-Samples-master
vl_test_imdisttf.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_imdisttf.m
1,885
utf_8
ae921197988abeb984cbcdf9eaf80e77
function results = vl_test_imdisttf(varargin) % VL_TEST_DISTTF vl_test_init ; function test_basic() for conv = {@single, @double} conv = conv{1} ; I = conv([0 0 0 ; 0 -2 0 ; 0 0 0]) ; D = vl_imdisttf(I); assert(isequal(D, conv(- [0 1 0 ; 1 2 1 ; 0 1 0]))) ; I(2,2) = -3 ; [D,map] = vl_imdisttf(I) ; assert(isequal(D, conv(-1 - [0 1 0 ; 1 2 1 ; 0 1 0]))) ; assert(isequal(map, 5 * ones(3))) ; end function test_1x1() assert(isequal(1, vl_imdisttf(1))) ; function test_rand() I = rand(13,31) ; for t=1:4 param = [rand randn rand randn] ; [D0,map0] = imdisttf_equiv(I,param) ; [D,map] = vl_imdisttf(I,param) ; vl_assert_almost_equal(D,D0,1e-10) assert(isequal(map,map0)) ; end function test_param() I = zeros(3,4) ; I(1,1) = -1 ; [D,map] = vl_imdisttf(I,[1 0 1 0]); assert(isequal(-[1 0 0 0 ; 0 0 0 0 ; 0 0 0 0 ;], D)) ; D0 = -[1 .9 .6 .1 ; 0 0 0 0 ; 0 0 0 0 ;] ; [D,map] = vl_imdisttf(I,[.1 0 1 0]); vl_assert_almost_equal(D,D0,1e-10); D0 = -[1 .9 .6 .1 ; .9 .8 .5 0 ; .6 .5 .2 0 ;] ; [D,map] = vl_imdisttf(I,[.1 0 .1 0]); vl_assert_almost_equal(D,D0,1e-10); D0 = -[.9 1 .9 .6 ; .8 .9 .8 .5 ; .5 .6 .5 .2 ; ] ; [D,map] = vl_imdisttf(I,[.1 1 .1 0]); vl_assert_almost_equal(D,D0,1e-10); function test_special() I = rand(13,31) -.5 ; D = vl_imdisttf(I, [0 0 1e5 0]) ; vl_assert_almost_equal(D(:,1),min(I,[],2),1e-10); D = vl_imdisttf(I, [1e5 0 0 0]) ; vl_assert_almost_equal(D(1,:),min(I,[],1),1e-10); function [D,map]=imdisttf_equiv(I,param) D = inf + zeros(size(I)) ; map = zeros(size(I)) ; ur = 1:size(D,2) ; vr = 1:size(D,1) ; [u,v] = meshgrid(ur,vr) ; for v_=vr for u_=ur E = I(v_,u_) + ... param(1) * (u - u_ - param(2)).^2 + ... param(3) * (v - v_ - param(4)).^2 ; map(E < D) = sub2ind(size(I),v_,u_) ; D = min(D,E) ; end end
github
ee368/EE368-Android-Samples-master
vl_test_argparse.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_argparse.m
795
utf_8
e72185b27206d0ee1dfdc19fe77a5be6
function results = vl_test_argparse(varargin) % VL_TEST_ARGPARSE vl_test_init ; function test_basic() opts.field1 = 1 ; opts.field2 = 2 ; opts.field3 = 3 ; opts_ = opts ; opts_.field1 = 3 ; opts_.field2 = 10 ; opts = vl_argparse(opts, {'field2', 10, 'field1', 3}) ; assert(isequal(opts, opts_)) ; opts_.field1 = 9 ; opts = vl_argparse(opts, {'field1', 4, 'field1', 9}) ; assert(isequal(opts, opts_)) ; function test_error() opts.field1 = 1 ; try opts = vl_argparse(opts, {'field2', 5}) ; catch e return ; end assert(false) ; function test_leftovers() opts1.field1 = 1 ; opts2.field2 = 1 ; opts1_.field1 = 2 ; opts2_.field2 = 2 ; [opts1,args] = vl_argparse(opts1, {'field1', 2, 'field2', 2}) ; opts2 = vl_argparse(opts2, args) ; assert(isequal(opts1,opts1_), isequal(opts2,opts2_)) ;
github
ee368/EE368-Android-Samples-master
vl_test_binsearch.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/xtest/vl_test_binsearch.m
1,339
utf_8
85dc020adce3f228fe7dfb24cf3acc63
function results = vl_test_binsearch(varargin) % VL_TEST_BINSEARCH vl_test_init ; function test_inf_bins() x = [-inf -1 0 1 +inf] ; vl_assert_equal(vl_binsearch([], x), [0 0 0 0 0]) ; vl_assert_equal(vl_binsearch([-inf 0], x), [1 1 2 2 2]) ; vl_assert_equal(vl_binsearch([-inf], x), [1 1 1 1 1]) ; vl_assert_equal(vl_binsearch([-inf +inf], x), [1 1 1 1 2]) ; function test_empty() vl_assert_equal(vl_binsearch([], []), []) ; function test_bnd() vl_assert_equal(vl_binsearch([], [1]), [0]) ; vl_assert_equal(vl_binsearch([], [-inf]), [0]) ; vl_assert_equal(vl_binsearch([], [+inf]), [0]) ; vl_assert_equal(vl_binsearch([1], [.9]), [0]) ; vl_assert_equal(vl_binsearch([1], [1]), [1]) ; vl_assert_equal(vl_binsearch([1], [-inf]), [0]) ; vl_assert_equal(vl_binsearch([1], [+inf]), [1]) ; function test_basic() vl_assert_equal(vl_binsearch(-10:10, -10:10), 1:21) ; vl_assert_equal(vl_binsearch(-10:10, -11:10), 0:21) ; vl_assert_equal(vl_binsearch(-10:10, [-inf, -11:10, +inf]), [0 0:21 21]) ; function test_frac() vl_assert_equal(vl_binsearch(1:10, 1:.5:10), floor(1:.5:10)) vl_assert_equal(vl_binsearch(1:10, fliplr(1:.5:10)), ... fliplr(floor(1:.5:10))) ; function test_array() a = reshape(1:100,10,10) ; b = reshape(1:.5:100.5, 2, []) ; c = floor(b) ; vl_assert_equal(vl_binsearch(a,b), c) ;
github
ee368/EE368-Android-Samples-master
vl_plotframe.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/plotop/vl_plotframe.m
5,410
utf_8
8c48bac1c5d80dba361b67cd135103d9
function h=vl_plotframe(frames,varargin) % VL_PLOTFRAME Plot feature frame % VL_PLOTFRAME(FRAME) plots the frames FRAME. Frames are attributed % image regions (as, for example, extracted by a feature detector). A % frame is a vector of D=2,3,..,6 real numbers, depending on its % class. VL_PLOTFRAME() supports the following classes: % % * POINTS % + FRAME(1:2) coordinates % % * CIRCLES % + FRAME(1:2) center % + FRAME(3) radius % % * ORIENTED CIRCLES % + FRAME(1:2) center % + FRAME(3) radius % + FRAME(4) orientation % % * ELLIPSES % + FRAME(1:2) center % + FRAME(3:5) S11, S12, S22 such that ELLIPSE = {x: x' inv(S) x = 1}. % % * ORIENTED ELLIPSES % + FRAME(1:2) center % + FRAME(3:6) stacking of A such that ELLIPSE = {A x : |x| = 1} % % H=VL_PLOTFRAME(...) returns the handle of the graphical object % representing the frames. % % VL_PLOTFRAME(FRAMES) where FRAMES is a matrix whose column are FRAME % vectors plots all frames simultaneously. Using this call is much % faster than calling VL_PLOTFRAME() for each frame. % % VL_PLOTFRAME(FRAMES,...) passes any extra argument to the underlying % plot function. The first optional argument can be a line % specification string such as the one used by PLOT(). % % See also: VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). % number of vertices drawn for each frame np = 40 ; lineprop = {} ; if length(varargin) > 0 lineprop = vl_linespec2prop(varargin{1}) ; lineprop = {lineprop{:}, varargin{2:end}} ; end % -------------------------------------------------------------------- % Handle various frame classes % -------------------------------------------------------------------- % if just a vector, make sure it is column if(min(size(frames))==1) frames = frames(:) ; end [D,K] = size(frames) ; zero_dimensional = D==2 ; % just points? if zero_dimensional h = plot(frames(1,:),frames(2,:),'g.',lineprop{:}) ; return ; end % reduce all other cases to ellipses/oriented ellipses frames = frame2oell(frames) ; do_arrows = (D==4 || D==6) ; % -------------------------------------------------------------------- % Draw % -------------------------------------------------------------------- K = size(frames,2) ; thr = linspace(0,2*pi,np) ; % allx and ally are nan separated lists of the vertices describing the % boundary of the frames allx = nan*ones(1, np*K+(K-1)) ; ally = nan*ones(1, np*K+(K-1)) ; if do_arrows % allxf and allyf are nan separated lists of the vertices of the allxf = nan*ones(1, 3*K) ; allyf = nan*ones(1, 3*K) ; end % vertices around a unit circle Xp = [cos(thr) ; sin(thr) ;] ; for k=1:K % frame center xc = frames(1,k) ; yc = frames(2,k) ; % frame matrix A = reshape(frames(3:6,k),2,2) ; % vertices along the boundary X = A * Xp ; X(1,:) = X(1,:) + xc ; X(2,:) = X(2,:) + yc ; % store allx((k-1)*(np+1) + (1:np)) = X(1,:) ; ally((k-1)*(np+1) + (1:np)) = X(2,:) ; if do_arrows allxf((k-1)*3 + (1:2)) = xc + [0 A(1,1)] ; allyf((k-1)*3 + (1:2)) = yc + [0 A(2,1)] ; end end if do_arrows h = line([allx nan allxf], ... [ally nan allyf], ... 'Color','g','LineWidth',3, ... lineprop{:}) ; else h = line(allx, ally, ... 'Color','g','LineWidth',3, ... lineprop{:}) ; end % -------------------------------------------------------------------- function eframes = frame2oell(frames) % FRAMES2OELL Convert generic frame to oriented ellipse % EFRAMES = FRAME2OELL(FRAMES) converts the frames FRAMES to % oriented ellipses EFRAMES. This is useful because many tasks are % almost equivalent for all kind of regions and are immediately % reduced to the most general case. % % Determine the kind of frames % [D,K] = size(frames) ; switch D case 2 kind = 'point' ; case 3 kind = 'disk' ; case 4 kind = 'odisk' ; case 5 kind = 'ellipse' ; case 6 kind = 'oellipse' ; otherwise error(['FRAMES format is unknown']) ; end eframes = zeros(6,K) ; % % Do converison % switch kind case 'point' eframes(1:2,:) = frames(1:2,:) ; case 'disk' eframes(1:2,:) = frames(1:2,:) ; eframes(3,:) = frames(3,:) ; eframes(6,:) = frames(3,:) ; case 'odisk' r = frames(3,:) ; c = r.*cos(frames(4,:)) ; s = r.*sin(frames(4,:)) ; eframes(1:2,:) = frames(1:2,:) ; eframes(3:6,:) = [c ; s ; -s ; c] ; case 'ellipse' eframes(1:2,:) = frames(1:2,:) ; eframes(3:6,:) = mapFromS(frames(3:5,:)) ; case 'oellipse' eframes = frames ; end % -------------------------------------------------------------------- function A = mapFromS(S) % -------------------------------------------------------------------- % Returns the (stacking of the) 2x2 matrix A that maps the unit circle % into the ellipses satisfying the equation x' inv(S) x = 1. Here S % is a stacked covariance matrix, with elements S11, S12 and S22. tmp = sqrt(S(3,:)) + eps ; A(1,:) = sqrt(S(1,:).*S(3,:) - S(2,:).^2) ./ tmp ; A(2,:) = zeros(1,length(tmp)); A(3,:) = S(2,:) ./ tmp ; A(4,:) = tmp ;
github
ee368/EE368-Android-Samples-master
vl_roc.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/plotop/vl_roc.m
6,848
utf_8
3d7ed746da2d3f389ad56c8e36f006d7
function [tpr,tnr,info] = vl_roc(labels, scores, varargin) % VL_ROC Compute ROC curve % [TP,TN] = VL_ROC(LABELS, SCORES) computes the receiver operating % characteristic (ROC curve). LABELS are the ground thruth labels (+1 % or -1) and SCORE is the scores assigned to them by a classifier % (higher scores correspond to positive labels). % % [TP,TN] are the true positive and true negative rates for % incereasing values of the decision threshold. % % Set the zero the lables of samples to ignore in the evaluation. % % Set to -INF the score of samples which are never retrieved. In % this case the PR curve will have maximum recall < 1. % % [TP,TN,INFO] = VL_ROC(...) returns the following additional % information: % % INFO.EER:: Equal error rate. % INFO.AUC:: Area under the VL_ROC (AUC). % INFO.UR:: Uniform prior best op point rate. % INFO.UT:: Uniform prior best op point threhsold. % INFO.NR:: Natural prior best op point rate. % INFO.NT:: Natural prior best op point threshold. % % VL_ROC(...) with no output arguments plots the VL_ROC diagram in % the current axis. % % About the ROC curve:: % Consider a classifier that predicts as positive all lables Y % whose SCORE is not smaller than a threshold S. The ROC curve % represents the performance of such classifier as the threshold S % is changed. Define % % P = num. of positive samples, % N = num. of negative samples, % % and for each threshold S % % TP(S) = num. of samples that are correctly classified as positive, % TN(S) = num. of samples that are correctly classified as negative, % FP(S) = num. of samples that are incorrectly classified as positive, % FN(S) = num. of samples that are incorrectly classified as negative. % % Consider also the rates: % % TPR = TP(S) / P, FNR = FN(S) / P, % TNR = TN(S) / N, FPR = FP(S) / N, % % and notice that by definition % % P = TP(S) + FN(S) , N = TN(S) + FP(S), % 1 = TPR(S) + FNR(S), 1 = TNR(S) + FPR(S). % % The ROC curve is the parametric curve (TPR(S), TNR(S)) obtained % as the classifier threshold S is varied from -INF to +INF. The % TPR is also known as recall (see VL_PR()). % % The ROC curve is contained in the square with vertices (0,0) The % (average) ROC curve of a random classifier is a line which % connects (1,0) and (0,1). % % The ROC curve is independent of the prior probability of the % labels (i.e. of P/(P+N) and N/(P+N)). % % An OPERATING POINT is a point on the ROC curve corresponding to % a certain threshold S. Each operating point corresponds to % minimizing the empirical 01 error of the classifier for given % prior probabilty of the labels. VL_ROC() computes the following % operating points: % % Natural operating point:: Assumes P[Y=+1] = P / (P + N). % Uniform operating point:: Assumes P[Y=+1] = 1/2. % % VL_ROC() acccepts the following options: % % Plot:: [] % Setting this option turns on plotting. Set to 'TrueNegative' or % 'TN' to plot TP(S) (recall) vs. TN(S). Set to 'FalseNegative' or % 'FN' to plot TP(S) (recall) vs. FP(S) = 1 - TN(S). % % See also: VL_PR(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). opts.plot = [] ; opts = vl_argparse(opts, varargin) ; % make row vectors labels = labels(:)' ; scores = scores(:)' ; % sort by descending scores [scores, perm] = sort(scores, 'descend') ; labels = labels(perm) ; % assume that data with -INF score is never retrieved stop = max(find(scores > -inf)) ; % Compute number of true positives, false positives, and overall % peositives. Note that labels==0 don't increase any of the counts. tp = [0 cumsum(labels(1:stop) > 0)] ; fp = [0 cumsum(labels(1:stop) < 0)] ; p = sum(labels > 0) ; n = sum(labels < 0) ; % compute the rates tpr = tp / (p + eps) ; fpr = fp / (n + eps) ; fnr = 1 - tpr ; tnr = 1 - fpr ; % -------------------------------------------------------------------- % Additional info % -------------------------------------------------------------------- if nargout > 0 | nargout == 0 % equal error rate i1 = max(find(tpr >= tnr)) ; i2 = max(find(tnr >= tpr)) ; eer = 1 - max(tnr(i1), tpr(i2)) ; % uniform prior and natural prior operating points [drop, upoint] = max(tpr * .5 + tnr * .5) ; [drop, npoint] = max(tpr * p + tnr * n) ; % uniform prior and natural prior operationg points rates and thresholds ur = tpr(upoint) * .5 + tnr(upoint) * .5 ; nr = tpr(npoint) * p/(p+n) + tnr(npoint) * n/(p+n) ; scores_ = [-inf, scores] ; ut = scores_(upoint) ; nt = scores_(npoint) ; % area area = sum((tnr(1:end-1)+tnr(2:end)) .* diff(tpr))/2 ; info.eer = eer ; info.auc = area ; info.ut = ut ; info.ur = ur ; info.nt = nt ; info.nr = nr ; end % -------------------------------------------------------------------- % Plot % -------------------------------------------------------------------- if ~isempty(opts.plot) || (nargout == 0) if isempty(opts.plot), opts.plot = 'tn' ; end cla ; hold on ; switch lower(opts.plot) case {'truenegatives', 'tn'} plot(tnr, tpr, 'b', 'linewidth', 2) ; spline((1-eer) * [0 1 1], (1-eer) * [1 1 0], 'r--') ; spline(tnr(upoint) * [0 1 1], tpr(upoint) * [1 1 0], 'g--') ; spline(tnr(npoint) * [0 1 1], tpr(npoint) * [1 1 0], 'k--') ; spline([0 1], [1 0], 'b:', 'linewidth', 2) ; spline([0 1], [0 1], 'y--', 'linewidth', 1) ; xlabel('true negative rate') ; ylabel('true positve rate (recall)') ; case {'falsepositives', 'fp'} plot(fpr, tpr, 'b', 'linewidth', 2) ; spline(eer * [0 1 1], (1-eer) * [1 1 0], 'r--') ; spline((1-tnr(upoint)) * [0 1 1], tpr(upoint) * [1 1 0], 'g--') ; spline((1-tnr(npoint)) * [0 1 1], tpr(npoint) * [1 1 0], 'k--') ; spline([1 0], [1 0], 'b:', 'linewidth', 2) ; spline([1 0], [0 1], 'y--', 'linewidth', 1) ; xlabel('false positive rate') ; ylabel('true positve rate (recall)') ; otherwise error('Invalid argument %s for option PLOT.', opts.plot); end grid on ; xlim([0 1]) ; ylim([0 1]) ; axis square ; title(sprintf('ROC (AUC = %.3g)', area), 'interpreter', 'none') ; legend('ROC', ... sprintf('eer %.3g %%', 100 * eer), ... sprintf('op. unif. %.3g %%', 100 * ur), ... sprintf('op. nat. %.3g %%', 100 * nr), ... 'ROC rand.', 'Location', 'SouthWest') ; end function h = spline(x,y,spec,varargin) prop = vl_linespec2prop(spec) ; h = line(x,y,prop{:},varargin{:}) ;
github
ee368/EE368-Android-Samples-master
vl_click.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/plotop/vl_click.m
2,661
utf_8
6982e869cf80da57fdf68f5ebcd05a86
function P = vl_click(N,varargin) ; % VL_CLICK Click a point % P=VL_CLICK() let the user click a point in the current figure and % returns its coordinates in P. P is a two dimensiona vectors where % P(1) is the point X-coordinate and P(2) the point Y-coordinate. The % user can abort the operation by pressing any key, in which case the % empty matrix is returned. % % P=VL_CLICK(N) lets the user select N points in a row. The user can % stop inserting points by pressing any key, in which case the % partial list is returned. % % VL_CLICK() accepts the following options: % % PlotMarker:: [0] % Plot a marker as points are selected. The markers are deleted on % exiting the function. % % See also: VL_CLICKPOINT(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). plot_marker = 0 ; for k=1:2:length(varargin) switch lower(varargin{k}) case 'plotmarker' plot_marker = varargin{k+1} ; otherwise error(['Uknown option ''', varargin{k}, '''.']) ; end end if nargin < 1 N=1; end % -------------------------------------------------------------------- % Do job % -------------------------------------------------------------------- fig = gcf ; is_hold = ishold ; hold on ; bhandler = get(fig,'WindowButtonDownFcn') ; khandler = get(fig,'KeyPressFcn') ; pointer = get(fig,'Pointer') ; set(fig,'WindowButtonDownFcn',@click_handler) ; set(fig,'KeyPressFcn',@key_handler) ; set(fig,'Pointer','crosshair') ; P=[] ; h=[] ; data.exit=0; guidata(fig,data) ; while size(P,2) < N uiwait(fig) ; data = guidata(fig) ; if(data.exit) break ; end P = [P data.P] ; if( plot_marker ) h=[h plot(data.P(1),data.P(2),'rx')] ; end end if ~is_hold hold off ; end if( plot_marker ) pause(.1); delete(h) ; end set(fig,'WindowButtonDownFcn',bhandler) ; set(fig,'KeyPressFcn',khandler) ; set(fig,'Pointer',pointer) ; % ==================================================================== function click_handler(obj,event) % -------------------------------------------------------------------- data = guidata(gcbo) ; P = get(gca, 'CurrentPoint') ; P = [P(1,1); P(1,2)] ; data.P = P ; guidata(obj,data) ; uiresume(gcbo) ; % ==================================================================== function key_handler(obj,event) % -------------------------------------------------------------------- data = guidata(gcbo) ; data.exit = 1 ; guidata(obj,data) ; uiresume(gcbo) ;
github
ee368/EE368-Android-Samples-master
vl_ubcread.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/sift/vl_ubcread.m
3,015
utf_8
e8ddd3ecd87e76b6c738ba153fef050f
function [f,d] = vl_ubcread(file, varargin) % SIFTREAD Read Lowe's SIFT implementation data files % [F,D] = VL_UBCREAD(FILE) reads the frames F and the descriptors D % from FILE in UBC (Lowe's original implementation of SIFT) format % and returns F and D as defined by VL_SIFT(). % % VL_UBCREAD(FILE, 'FORMAT', 'OXFORD') assumes the format used by % Oxford VGG implementations . % % See also: VL_SIFT(), VL_HELP(). % Authors: Andrea Vedaldi % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). opts.verbosity = 0 ; opts.format = 'ubc' ; opts = vl_argparse(opts, varargin) ; g = fopen(file, 'r'); if g == -1 error(['Could not open file ''', file, '''.']) ; end [header, count] = fscanf(g, '%d', [1 2]) ; if count ~= 2 error('Invalid keypoint file header.'); end switch opts.format case 'ubc' numKeypoints = header(1) ; descrLen = header(2) ; case 'oxford' numKeypoints = header(2) ; descrLen = header(1) ; otherwise error('Unknown format ''%s''.', opts.format) ; end if(opts.verbosity > 0) fprintf('%d keypoints, %d descriptor length.\n', numKeypoints, descrLen) ; end %creates two output matrices switch opts.format case 'ubc' P = zeros(4,numKeypoints) ; case 'oxford' P = zeros(5,numKeypoints) ; end L = zeros(descrLen, numKeypoints) ; %parse tmp.key for k = 1:numKeypoints switch opts.format case 'ubc' % Record format: i,j,s,th [record, count] = fscanf(g, '%f', [1 4]) ; if count ~= 4 error(... sprintf('Invalid keypoint file (parsing keypoint %d, frame part)',k) ); end P(:,k) = record(:) ; case 'oxford' % Record format: x, y, a, b, c such that x' [a b ; b c] x = 1 [record, count] = fscanf(g, '%f', [1 5]) ; if count ~= 5 error(... sprintf('Invalid keypoint file (parsing keypoint %d, frame part)',k) ); end P(:,k) = record(:) ; end % Record format: descriptor [record, count] = fscanf(g, '%d', [1 descrLen]) ; if count ~= descrLen error(... sprintf('Invalid keypoint file (parsing keypoint %d, descriptor part)',k) ); end L(:,k) = record(:) ; end fclose(g) ; switch opts.format case 'ubc' P(1:2,:) = flipud(P(1:2,:)) + 1 ; % i,j -> x,y f=[ P(1:2,:) ; P(3,:) ; -P(4,:) ] ; d=uint8(L) ; p=[1 2 3 4 5 6 7 8] ; q=[1 8 7 6 5 4 3 2] ; for j=0:3 for i=0:3 d(8*(i+4*j)+p,:) = d(8*(i+4*j)+q,:) ; end end case 'oxford' P(1:2,:) = P(1:2,:) + 1 ; % matlab origin f = P ; f(3:5,:) = inv2x2(f(3:5,:)) ; d = uint8(L) ; end % -------------------------------------------------------------------- function S = inv2x2(C) % -------------------------------------------------------------------- den = C(1,:) .* C(3,:) - C(2,:) .* C(2,:) ; S = [C(3,:) ; -C(2,:) ; C(1,:)] ./ den([1 1 1], :) ;
github
ee368/EE368-Android-Samples-master
vl_plotsiftdescriptor.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/sift/vl_plotsiftdescriptor.m
4,348
utf_8
b9a98b0c298fa249fb5fcd1314762b88
function h=vl_plotsiftdescriptor(d,f,varargin) % VL_PLOTSIFTDESCRIPTOR Plot SIFT descriptor % VL_PLOTSIFTDESCRIPTOR(D) plots the SIFT descriptors D, stored as % columns of the matrix D. D has the same format used by VL_SIFT(). % % VL_PLOTSIFTDESCRIPTOR(D,F) plots the SIFT descriptors warped to % the SIFT frames F, specified as columns of the matrix F. F has the % same format used by VL_SIFT(). % % H=VL_PLOTSIFTDESCRIPTOR(...) returns the handle H to the line drawing % representing the descriptors. % % REMARK. By default, the function assumes descriptors with 4x4 % spatial bins and 8 orientation bins (Lowe's default.) % % The function supports the following options % % NumSpatialBins:: [4] % Number of spatial bins in each spatial direction. % % NumOrientBins:: [8] % Number of orientation bis. % % Magnif:: [3] % Magnification factor. % % See also: VL_SIFT(), VL_PLOTFRAME(), VL_HELP(). % Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. % All rights reserved. % % This file is part of the VLFeat library and is made available under % the terms of the BSD license (see the COPYING file). magnif = 3.0 ; NBP = 4 ; NBO = 8 ; maxv = 0 ; if nargin > 1 if ~ isnumeric(f) error('F must be a numeric type (use [] to leave it unspecified)') ; end end for k=1:2:length(varargin) opt=lower(varargin{k}) ; arg=varargin{k+1} ; switch opt case 'numspatialbins' NBP = arg ; case 'numorientbins' NBO = arg ; case 'magnif' magnif = arg ; case 'maxv' maxv = arg ; otherwise error(sprintf('Unknown option ''%s''', opt)) ; end end % -------------------------------------------------------------------- % Check the arguments % -------------------------------------------------------------------- if(size(d,1) ~= NBP*NBP*NBO) error('The number of rows of D does not match the geometry of the descriptor') ; end if nargin > 1 if (~isempty(f) & size(f,1) < 2 | size(f,1) > 4) error('F should be a 2xK, 3xK, 4xK matrix or the empty matrix'); end if size(f,1) == 2 f = [f; 10 * ones(1, size(f,2)) ; 0 * zeros(1, size(f,2))] ; end if size(f,1) == 3 f = [f; 0 * zeros(1, size(f,2))] ; end if(~isempty(f) & size(f,2) ~= size(d,2)) error('D and F have incompatible dimension') ; end end % Descriptors are often non-double numeric arrays d = double(d) ; K = size(d,2) ; if nargin < 2 | isempty(f) f = repmat([0;0;1;0],1,K) ; end % -------------------------------------------------------------------- % Do the job % -------------------------------------------------------------------- xall=[] ; yall=[] ; for k=1:K SBP = magnif * f(3,k) ; th=f(4,k) ; c=cos(th) ; s=sin(th) ; [x,y] = render_descr(d(:,k), NBP, NBO, maxv) ; xall = [xall SBP*(c*x-s*y)+f(1,k)] ; yall = [yall SBP*(s*x+c*y)+f(2,k)] ; end h=line(xall,yall) ; % -------------------------------------------------------------------- function [x,y] = render_descr(d, BP, BO, maxv) % -------------------------------------------------------------------- [x,y] = meshgrid(-BP/2:BP/2,-BP/2:BP/2) ; % Rescale d so that the biggest peak fits inside the bin diagram if maxv d = 0.4 * d / maxv ; else d = 0.4 * d / max(d(:)+eps) ; end % We have BP*BP bins to plot. Here are the centers: xc = x(1:end-1,1:end-1) + 0.5 ; yc = y(1:end-1,1:end-1) + 0.5 ; % We scramble the the centers to have the in row major order % (descriptor convention). xc = xc' ; yc = yc' ; % Each spatial bin contains a star with BO tips xc = repmat(xc(:)',BO,1) ; yc = repmat(yc(:)',BO,1) ; % Do the stars th=linspace(0,2*pi,BO+1) ; th=th(1:end-1) ; xd = repmat(cos(th), 1, BP*BP) ; yd = repmat(sin(th), 1, BP*BP) ; xd = xd .* d(:)' ; yd = yd .* d(:)' ; % Re-arrange in sequential order the lines to draw nans = NaN * ones(1,BP^2*BO) ; x1 = xc(:)' ; y1 = yc(:)' ; x2 = x1 + xd ; y2 = y1 + yd ; xstars = [x1;x2;nans] ; ystars = [y1;y2;nans] ; % Horizontal lines of the grid nans = NaN * ones(1,BP+1); xh = [x(:,1)' ; x(:,end)' ; nans] ; yh = [y(:,1)' ; y(:,end)' ; nans] ; % Verical lines of the grid xv = [x(1,:) ; x(end,:) ; nans] ; yv = [y(1,:) ; y(end,:) ; nans] ; x=[xstars(:)' xh(:)' xv(:)'] ; y=[ystars(:)' yh(:)' yv(:)'] ;
github
ee368/EE368-Android-Samples-master
vl_test_twister.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_twister.m
1,166
utf_8
1e18a0b343ffe164ec9c941e18575c05
function vl_test_twister % VL_TEST_TWISTER % test seed by scalar rand('twister',1) ; a = rand ; vl_twister('state',1) ; b = vl_twister ; check(a,b,'twister: seed by scalar + VL_TWISTER()') ; % read state rand('twister') ; a = rand('twister') ; vl_twister('state') ; b = vl_twister('state') ; check(a,b,'twister: read state') ; % set state a(1) = a(1)+1 ; rand('twister',a) ; b = rand('twister') ; check(a,b,'twister: set state') ; % VL_TWISTER([M N P ...]) rand('twister',b) ; vl_twister('state',b) ; a=rand([1 2 3 4 5]) ; b=vl_twister([1 2 3 4 5]) ; check(a,b,'twister: VL_TWISTER([M N P ...])') ; % VL_TWISTER(M, N, P ...) a=rand(1, 2, 3, 4, 5) ; b=vl_twister(1, 2, 3, 4, 5) ; check(a,b,'twister: VL_TWISTER(M, N, P, ...)') ; % VL_TWISTER(M, N, P ...) a=rand(1, 2, 3, 4, 5) ; b=vl_twister(1, 2, 3, 4, 5) ; check(a,b,'twister: VL_TWISTER(M, N, P, ...)') ; % VL_TWISTER(N) a=rand(10) ; b=vl_twister(10) ; check(a,b,'twister: VL_TWISTER(N)') ; % --------------------------------------------------------------- function check(a,b,msg) fprintf('test: %-40s ... ', msg) ; if isequal(a,b) fprintf('ok.\n') ; else fprintf('!!!! FAIL !!!!\n') ; keyboard end
github
ee368/EE368-Android-Samples-master
vl_test_imintegral.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_imintegral.m
1,257
utf_8
d5ad8d073e99ff451cc1b692da99ec6d
function vl_test_imintegral I = ones(5,6); correct = [1 2 3 4 5 6; 2 4 6 8 10 12; 3 6 9 12 15 18; 4 8 12 16 20 24; 5 10 15 20 25 30;]; if ~all(all(slow_imintegral(I) == correct)) fprintf('test_imintegral: FAIL slow ones test\n'); keyboard; end if ~all(all(vl_imintegral(I) == correct)) fprintf('test_imintegral: FAIL ones test\n'); keyboard; end I = repmat(ones(5,6), [1 1 3]); integral = vl_imintegral(I); if ~all(all(all(integral == repmat(correct,[1 1 3])))) fprintf('test_imintegral: FAIL multidimensional ones test\n'); keyboard; end ntest = 50; for i = 1:ntest I = rand(5); integral = vl_imintegral(I); slow_integral = slow_imintegral(I); err = abs(integral - slow_integral); if max(err(:)) > 0.00001 fprintf('test_imintegral: FAIL random test\n'); keyboard; end end fprintf('test_imintegral: passed.\n'); % The slow but obvious way function integral = slow_imintegral(I) integral = zeros(size(I)); for k = 1:size(I,3) for r = 1:size(I,1) for c = 1:size(I,2) integral(r,c,k) = sum(sum(I(1:r,1:c,k))); end end end
github
ee368/EE368-Android-Samples-master
vl_test_sift.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_sift.m
1,849
utf_8
cfae71614a40aebf645eb42102ca53f3
function vl_test_sift % VL_TEST_SIFT Test VL_SIFT implementation(s) I = vl_test_pattern(101); % run various instances of the code [a0,b0] = vl_sift(single(I),'verbose','peaktresh',0,'levels',4) ; [a1,b1] = cmd_sift(I,'--first-octave=0 --peak-tresh=0 --levels=4') ; [a2,b2] = cmd_sift(I,'--first-octave=0',1) ; [a3,b3] = vl_sift(single(I),'verbose','frames',a0) ; figure(1) ; clf ; colormap gray ; imagesc(I) ; hold on ; h=vl_plotsiftdescriptor(b0,a0) ; set(h,'color','g','linewidth',6) ; h=vl_plotsiftdescriptor(b1,a1) ; set(h,'color','b','linewidth',4) ; h=vl_plotsiftdescriptor(b2,a2) ; set(h,'color','r','linewidth',2) ; h=vl_plotsiftdescriptor(b3,a3) ; set(h,'color','y','linewidth',1) ; title('Same descriptor computed in four ways') ; %disp([a0 a1 a2 a3]) ; % -------------------------------------------------------------------- function [a,b]=cmd_sift(I,param,do_read) % -------------------------------------------------------------------- switch mexext case 'mexmac' arch = 'mac/sift' ; case 'mexmaci' arch = 'maci/sift' ; case 'mexglx' arch = 'glx/sift' ; case 'dll' ; arch = 'w32\sift.exe' ; end pfx = fullfile(vl_root,'results') ; if ~ exist(pfx, 'dir') mkdir(pfx) ; end pfx_sift_cmd = fullfile(vlfeat_root,'bin',arch) ; pfx_im = fullfile(pfx,'autotest.pgm') ; pfx_d = fullfile(pfx,'autotest.descr') ; pfx_f = fullfile(pfx,'autotest.frame') ; imwrite(uint8(I), pfx_im) ; str = [pfx_sift_cmd, ' ', param, ' ', ... ' --descriptors=', pfx_d, ..., ' --frames=', pfx_f, ..., ' -v -v ' pfx_im] ; if (nargin > 2) str = [str ' --read-frames=' pfx_f] ; end fprintf('> %s\n',str) ; [err,msg] = system(str) ; if (err), error(msg) ; end fprintf(msg) ; a = load(pfx_f,'-ASCII')' ; b = load(pfx_d,'-ASCII')' ; if ~isempty(a), a(1:2,:) = a(1:2,:) + 1 ; end
github
ee368/EE368-Android-Samples-master
vl_test_binsum.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_binsum.m
1,030
utf_8
c69da861d697e8228e243a385f5ba545
function vl_test_binsum % VL_TEST_BINSUM Test VL_BINSUM function testh({[0 0], 1, 2}, [0 1] ) ; testh({[1 7], -1, 1}, [0 7] ) ; testh({[1 7], -1, [1 2 2 2 2 2 2 2]}, [0 0] ) ; testh({eye(3), [1 1 1], [1 2 3], 1 }, 2*eye(3)) ; testh({eye(3), [1 1 1]', [1 2 3]', 2 }, 2*eye(3)) ; testh({eye(3), 1, [1 2 3], 1 }, 2*eye(3)) ; testh({eye(3), 1, [1 2 3]', 2 }, 2*eye(3)) ; Z = zeros(3,3,3) ; B = 3*ones(3,1,3) ; R = Z ; R(:,3,:) = 17 ; testh({Z, 17, B, 2}, R) ; Z = zeros(3,3,3) ; B = 3*ones(3,3,1) ; X = zeros(3,3,1) ; X(:,:,1) = 17 ; R = Z ; R(:,:,3) = 17 ; testh({Z, X, B, 3}, R) ; function testh(args, H_) H__ = vl_binsum(args{:}) ; if any(any(any(H_ ~= H__))) fprintf('H:\n') ; disp(args{1}); fprintf('X:\n') ; disp(args{2}); fprintf('B:\n') ; disp(args{3}); if length(args) > 3, fprintf('d:\n') ; disp(args{4}) ; end fprintf('R computed:\n') ; disp(H__) ; fprintf('R correct:\n') ; disp(H_) ; error('vl_binsum regression test failed') ; end
github
ee368/EE368-Android-Samples-master
vl_test_imsmooth.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_imsmooth.m
1,566
utf_8
27ae6791e4ca852539a031b78ae7a00b
function vl_test_imsmooth I = im2double(imread('data/spots.jpg')) ; I = max(min(imresize(I,2),1),0) ; I = single(I) ; global fign ; fign = 1 ; step = 1 ; ker = 'gaussian' ; testmany(I,'triangular',1) ; testmany(I,'triangular',2) ; testmany(I,'gaussian',1) ; testmany(I,'gaussian',2) ; function testmany(I,ker,step) global fign ; sigmar = [0, 1, 10, 100] ; for sigma = sigmar [I1,I2,I3] = testone(I,ker,sigma,step) ; compare(fign,I1,I2,I3,sprintf('%s, sigma %g, sub. step %d', ker, sigma, step)) ; fign=fign+1 ; end function I=icut(I) I=min(max(I,0),1) ; function [I1,I2,I3]=testone(I,ker,sigma,step) switch ker case 'gaussian' W = ceil(4*sigma) ; g = exp(-.5*((-W:W)/(sigma+eps)).^2) ; case 'triangular' W = max(round(sigma),1) ; g = W - abs(-W+1:W-1) ; end g = g / sum(g) ; I1 = imconv(I,g) ; I1 = I1(1:step:end,1:step:end,:) ; I2 = vl_imsmooth(I,sigma,'kernel',ker,'padding','zero', 'verbose','subsample',step) ; I3 = vl_imsmooth(I,sigma,'kernel',ker,'padding','continuity','verbose','subsample',step) ; function compare(n,I1,I2,I3,tit) figure(n) ; clf ; colormap gray ; subplot(1,3,1) ; axis equal ; imagesc(icut(I1)) ; axis off ; title('Matlab zeropad') ; subplot(1,3,2) ; axis equal ; imagesc(abs(I1-I2)) ; axis off ; title('matlab - imsmooth') ; subplot(1,3,3) ; axis equal ; imagesc(icut(I3)) ; axis off ; title('vl_imsmooth contpad') ; set(n,'name',tit) ; function I=imconv(I,g) if strcmp(class(I),'single') g = single(g) ; else g = double(g) ; end for k=1:size(I,3) I(:,:,k) = conv2(g,g,I(:,:,k),'same'); end
github
ee368/EE368-Android-Samples-master
vl_test_hikmeans.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_hikmeans.m
2,037
utf_8
f57532e5de667fbe2f6cb9c714f20457
function vl_test_hikmeans % VL_TEST_HIKMEANS Test VL_HIKMEANS function K = 2; nleaves = 2; data = uint8(rand(2,100)*255); [tree,A] = vl_hikmeans(data,K,nleaves,'verbose','verbose'); %keyboard; K = 3 ; nleaves = 100 ; data = uint8(rand(2,1000) * 255) ; datat = uint8(rand(2,10000)* 255) ; [tree,A] = vl_hikmeans(data,K,nleaves,'verbose', 'verbose') ; AT = vl_hikmeanspush(tree,datat,'verbose','verbose') ; %keyboard figure(1) ; clf ; plottree(tree) ; axis off ; axis equal ; xlim([0 255]) ; ylim([0 255]) ; vl_demo_print('hikmeans-tree') ; figure(2) ; clf ; hold on ; hold on ; cl = get(gca,'ColorOrder') ; ncl = size(cl,1) ; for k=1:K*K sel=find(A(end,:)==k) ; plot(data(1,sel),data(2,sel), '.','Color',cl(mod(k,ncl)+1,:)) ; sel=find(AT(end,:)==k) ; plot(datat(1,sel),datat(2,sel),'+','Color',cl(mod(k,ncl)+1,:)) ; end h=plottree(tree) ; set(h,'LineWidth',4) ; axis off ; axis equal ; xlim([0 255]) ; ylim([0 255]) ; vl_demo_print('hikmeans-clusters') ; % -------------------------------------------------------------------- function h=plottree(tree) % -------------------------------------------------------------------- % PLOTTRE Plot hierarchical K-means tree % PLOTTREE(TREE) plots a tree generated by HIKMEASN(). % % See also:VL_HIKMEANS(). x1=[] ; x2=[] ; for c=1:size(tree.centers,2) [x1p x2p]=xplot(tree.centers(:,c), tree.sub(c)) ; x1 = [x1 x1p] ; x2 = [x2 x2p] ; end h=line(x1(:),x2(:)) ; % -------------------------------------------------------------------- function [x1,x2]=xplot(X,tree) % -------------------------------------------------------------------- x1=[] ; x2=[] ; if(~isstruct(tree)), return ; end ; C = size(tree.centers,2) ; x1 = [double(X(1))*ones(1,C); double(tree.centers(1,:)); nan*ones(1,C)] ; x2 = [double(X(2))*ones(1,C); double(tree.centers(2,:)); nan*ones(1,C)] ; if(any(x1>300)), keyboard ;end if ~isempty(tree.sub) for c=1:C [x1p x2p]=xplot(tree.centers(:,c), tree.sub(c)) ; x1 = [x1 x1p] ; x2 = [x2 x2p] ; end end
github
ee368/EE368-Android-Samples-master
vl_test_homkmap.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_homkmap.m
1,493
utf_8
a78c933efd15a4279e2724ba4441ad76
function vl_test_homkmap x = 2.^(-12:.1:0) ; L = .3 ; n = 4 ; V = vl_homkmap(x, n, L, 'kchi2') ; V_ = featureMap('chi2', n, L, x, 1) ; V V_ figure(1) ; clf ; subplot(1,2,1) ; semilogx(x,V_','-') ; hold on ; semilogy(x,V','--') ; subplot(1,2,2); plot(x,V_','-') ; hold on ; plot(x,V','--') ; function psi = featureMap(kappa, n, L, x, g) if nargin < 5, g = 1 ; end if isstr(kappa) switch kappa case 'inters' kappa = @(lambda) 2/pi * 1 ./ (1 + 4 * lambda.^2) ; case 'chi2' kappa = @(lambda) sech(pi * lambda) ; otherwise error('Unknown kernel') ; end end l = (1:n) * L ; skp0 = sqrt(L) * sqrt(kappa(0)) ; s2kp = sqrt(2*L) * sqrt(kappa(l)) ; [d, M] = size(x) ; sz = 1 + 2*n ; psi = zeros(d * sz, M) ; % do this in blocks to avoid using too much memory br = [1:ceil(2e6 / d):M, M+1] ; if br(end) < M, br(end+1) = M ; end for bi = 1:length(br)-1 sel = br(bi) : br(bi+1)-1 ; %sqx = sqrt(x(:, sel)) ; sqx = x(:, sel).^(g/2) ; lgx = log(x(:, sel) + eps) ; psi(1:d, sel) = skp0 * sqx ; for i=1:n llgx = l(i) * lgx ; psi(2*d*(i-1) + d + (1:d), sel) = s2kp(i) * cos(llgx) .* sqx ; psi(2*d*(i-1) + 2*d + (1:d), sel) = s2kp(i) * sin(llgx) .* sqx ; end end % sanity check if 0 for j = 1:M for i = 1:d psi_((i-1)*sz + (1:sz), j) = ... sqrt(x(i,j)) * [ ... skp0, ... s2kp .* cos(l * log(x(i,j))), ... s2kp .* sin(l * log(x(i,j))) ]' ; end end %keyboard psi = psi_ ; end
github
ee368/EE368-Android-Samples-master
vl_test_aibhist.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_aibhist.m
2,263
utf_8
d46c6fa557ab0d00e465eaedd060add9
% VL_TEST_AIBHIST function vl_test_aibhist D = 4 ; K = 20 ; randn('state',0) ; rand('state',0) ; X1 = randn(2,300) ; X1(1,:) = X1(1,:) + 2 ; X2 = randn(2,300) ; X2(1,:) = X2(1,:) - 2 ; X3 = randn(2,300) ; X3(2,:) = X3(2,:) + 2 ; C = 1:K*K ; Pcx = zeros(3,K*K) ; f1 = quantize(X1,D,K) ; f2 = quantize(X2,D,K) ; f3 = quantize(X3,D,K) ; Pcx(1,:) = vl_binsum(Pcx(1,:), ones(size(f1)), f1) ; Pcx(2,:) = vl_binsum(Pcx(2,:), ones(size(f2)), f2) ; Pcx(3,:) = vl_binsum(Pcx(3,:), ones(size(f3)), f3) ; Pcx = Pcx / sum(Pcx(:)) ; [parents_, cost_] = vl_aib(Pcx) ; [parents, cost ] = vl_aib(Pcx,'clusternull') ; % find a null node for testing purposes anull = min(find(parents_==0)) ; f1 = [f1 repmat(anull,1,10)] ; figure(100); clf ; subplot(1,2,1) ; hold on ; plot(parents_, 'r.-') ; plot(parents, 'g') ; legend('signal null', 'cluster null') ; subplot(1,2,2) ; hold on ; plot(cost_, 'r.-') ; plot(cost, 'g') ; legend('signal null', 'cluster null') ; range = [1 10 K*K-10 K*K] ; for c=1:length(range) cut_size = range(c) ; % compare two methods of getting the same cut histogram [cut_,map_] = vl_aibcut(parents_, cut_size) ; hist_ = vl_aibcuthist(map_, f1, 'nulls', 'append') ; histtree_ = vl_aibhist(parents_, f1) ; thist_ = histtree_(cut_) ; [cut,map] = vl_aibcut(parents, cut_size) ; hist = vl_aibcuthist(map, f1, 'nulls', 'append') ; histtree = vl_aibhist(parents, f1) ; thist = histtree(cut) ; figure(100 + c) ; clf ; subplot(2,2,1) ; hold on ; plot(hist_,'g.-') ; plot(thist_,'r') ; legend('cut+cuthist', 'hist+cut') ; title('vl_aibcuthist vs aibhist'); subplot(2,2,2) ; hold on ; plot(histtree_) ; title('aibtree') ; subplot(2,2,3) ; hold on ; plot(hist,'g.-') ; plot(thist,'r') ; legend('cut+cuthist', 'hist+cut') ; title('vl_aibcuthist vs vl_aibhist (clust null)'); subplot(2,2,4) ; hold on ; plot(histtree) ; title('aibtree (clust null)') ; end % -------------------------------------------------------------------- function f = quantize(X,D,K) % -------------------------------------------------------------------- d = 2*D / K ; j = round((X(1,:) + D) / d) ; i = round((X(2,:) + D) / d) ; j = max(min(j,K),1) ; i = max(min(i,K),1) ; f = sub2ind([K K],i,j) ;
github
ee368/EE368-Android-Samples-master
vl_test_ikmeans.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/toolbox/test/vl_test_ikmeans.m
1,552
utf_8
1d5747a991a0d81ed4f7a2c90cd2a213
function vl_test_ikmeans % VL_TEST_IKMEANS Test VL_IKMEANS function fprintf('test_ikmeans: Testing VL_IKMEANS and IKMEANSPUSH\n') % ----------------------------------------------------------------------- fprintf('test_ikmeans: Testing Lloyd algorithm\n') K = 3 ; data = uint8(rand(2,1000) * 255) ; datat = uint8(rand(2,10000)* 255) ; [C,A] = vl_ikmeans(data,K,'verbose') ; [AT] = vl_ikmeanspush(datat,C,'verbose') ; figure(1) ; clf ; hold on ; plot_partition(data, datat, C, A, AT) ; title('vl_ikmeans (Lloyd algorithm)') ; vl_demo_print('ikmeans_lloyd') ; % ----------------------------------------------------------------------- fprintf('test_ikmeans: Testing Elkan algorithm\n') [C,A] = vl_ikmeans(data,K,'verbose','method','elkan') ; [AT] = vl_ikmeanspush(datat,C,'verbose','method','elkan') ; figure(2) ; clf ; hold on ; plot_partition(data, datat, C, A, AT) ; title('vl_ikmeans (Elkan algorithm)') ; vl_demo_print('ikmeans_elkan') ; % ----------------------------------------------------------------------- function plot_partition(data, datat, C, A, AT) % ----------------------------------------------------------------------- K = size(C,2) ; cl = get(gca,'ColorOrder') ; ncl = size(cl,1) ; for k=1:K sel = find(A == k) ; selt = find(AT == k) ; vl_plotframe(data(:,sel), '.','Color',cl(mod(k,ncl)+1,:)) ; vl_plotframe(datat(:,selt),'+','Color',cl(mod(k,ncl)+1,:)) ; end plot(C(1,:),C(2,:),'ko','markersize',10','linewidth',6) ; plot(C(1,:),C(2,:),'yo','markersize',10','linewidth',1) ; axis off ; axis equal ;
github
ee368/EE368-Android-Samples-master
phow_caltech101.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/apps/phow_caltech101.m
11,269
utf_8
91ef403a7a3865b32e7a5673350fec49
function phow_caltech101 % PHOW_CALTECH101 Image classification in the Caltech-101 dataset % This program demonstrates how to use VLFeat to construct an image % classifier on the Caltech-101 data. The classifier uses PHOW % features (dense SIFT), spatial histograms of visual words, and a % Chi2 SVM. To speedup computation it uses VLFeat fast dense SIFT, % kd-trees, and homogeneous kernel map. The program also % demonstrates VLFeat PEGASOS SVM solver, although for this small % dataset other solvers such as LIBLINEAR can be more efficient. % % By default 15 training images are used, which should result in % about 64% performance (a good performance considering that only a % single feature type is being used). % % Call PHOW_CALTECH101 to train and test a classifier on a small % subset of the Caltech-101 data. Note that the program % automatically downloads a copy of the Caltech-101 data from the % Internet if it cannot find a local copy. % % Edit the PHOW_CALTECH101 file to change the program configuration. % % To run on the entire dataset change CONF.TINYPROBLEM to FALSE. % % The Caltech-101 data is saved into CONF.CALDIR, which defaults to % 'data/caltech-101'. Change this path to the desired location, for % instance to point to an existing copy of the Caltech-101 data. % % The program can also be used to train a model on custom data by % pointing CONF.CALDIR to it. Just create a subdirectory for each % class and put the training images there. Make sure to adjust % CONF.NUMTRAIN accordingly. % % Intermediate files are stored in the directory CONF.DATADIR. All % such files begin with the prefix CONF.PREFIX, which can be changed % to test different parameter settings without overriding previous % results. % % The program saves the trained model in % <CONF.DATADIR>/<CONF.PREFIX>-model.mat. This model can be used to % test novel images independently of the Caltech data. % % load('data/baseline-model.mat') ; # change to the model path % label = model.classify(model, im) ; % % AUTORIGHTS conf.calDir = 'data/caltech-101' ; conf.dataDir = 'data/' ; conf.autoDownloadData = true ; conf.numTrain = 15 ; conf.numTest = 15 ; conf.numClasses = 102 ; conf.numWords = 600 ; conf.numSpatialX = [2 4] ; conf.numSpatialY = [2 4] ; conf.quantizer = 'kdtree' ; conf.svm.C = 10 ; conf.svm.solver = 'pegasos' ; conf.svm.biasMultiplier = 1 ; conf.phowOpts = {'Step', 3} ; conf.clobber = false ; conf.tinyProblem = true ; conf.prefix = 'baseline' ; conf.randSeed = 1 ; if conf.tinyProblem conf.prefix = 'tiny' ; conf.numClasses = 5 ; conf.numSpatialX = 2 ; conf.numSpatialY = 2 ; conf.numWords = 300 ; conf.phowOpts = {'Verbose', 2, 'Sizes', 7, 'Step', 5} ; end conf.vocabPath = fullfile(conf.dataDir, [conf.prefix '-vocab.mat']) ; conf.histPath = fullfile(conf.dataDir, [conf.prefix '-hists.mat']) ; conf.modelPath = fullfile(conf.dataDir, [conf.prefix '-model.mat']) ; conf.resultPath = fullfile(conf.dataDir, [conf.prefix '-result']) ; randn('state',conf.randSeed) ; rand('state',conf.randSeed) ; vl_twister('state',conf.randSeed) ; % -------------------------------------------------------------------- % Download Caltech-101 data % -------------------------------------------------------------------- if ~exist(conf.calDir, 'dir') || ... (~exist(fullfile(conf.calDir, 'airplanes'),'dir') && ... ~exist(fullfile(conf.calDir, '101_ObjectCategories', 'airplanes'))) if ~conf.autoDownloadData error(... ['Caltech-101 data not found. ' ... 'Set conf.autoDownloadData=true to download the required data.']) ; end vl_xmkdir(conf.calDir) ; calUrl = ['http://www.vision.caltech.edu/Image_Datasets/' ... 'Caltech101/101_ObjectCategories.tar.gz'] ; fprintf('Downloading Caltech-101 data to ''%s''. This will take a while.', conf.calDir) ; untar(calUrl, conf.calDir) ; end if ~exist(fullfile(conf.calDir, 'airplanes'),'dir') conf.calDir = fullfile(conf.calDir, '101_ObjectCategories') ; end % -------------------------------------------------------------------- % Setup data % -------------------------------------------------------------------- classes = dir(conf.calDir) ; classes = classes([classes.isdir]) ; classes = {classes(3:conf.numClasses+2).name} ; images = {} ; imageClass = {} ; for ci = 1:length(classes) ims = dir(fullfile(conf.calDir, classes{ci}, '*.jpg'))' ; ims = vl_colsubset(ims, conf.numTrain + conf.numTest) ; ims = cellfun(@(x)fullfile(classes{ci},x),{ims.name},'UniformOutput',false) ; images = {images{:}, ims{:}} ; imageClass{end+1} = ci * ones(1,length(ims)) ; end selTrain = find(mod(0:length(images)-1, conf.numTrain+conf.numTest) < conf.numTrain) ; selTest = setdiff(1:length(images), selTrain) ; imageClass = cat(2, imageClass{:}) ; model.classes = classes ; model.phowOpts = conf.phowOpts ; model.numSpatialX = conf.numSpatialX ; model.numSpatialY = conf.numSpatialY ; model.quantizer = conf.quantizer ; model.vocab = [] ; model.w = [] ; model.b = [] ; model.classify = @classify ; % -------------------------------------------------------------------- % Train vocabulary % -------------------------------------------------------------------- if ~exist(conf.vocabPath) || conf.clobber % Get some PHOW descriptors to train the dictionary selTrainFeats = vl_colsubset(selTrain, 30) ; descrs = {} ; %for ii = 1:length(selTrainFeats) parfor ii = 1:length(selTrainFeats) im = imread(fullfile(conf.calDir, images{selTrainFeats(ii)})) ; im = standarizeImage(im) ; [drop, descrs{ii}] = vl_phow(im, model.phowOpts{:}) ; end descrs = vl_colsubset(cat(2, descrs{:}), 10e4) ; descrs = single(descrs) ; % Quantize the descriptors to get the visual words vocab = vl_kmeans(descrs, conf.numWords, 'verbose', 'algorithm', 'elkan') ; save(conf.vocabPath, 'vocab') ; else load(conf.vocabPath) ; end model.vocab = vocab ; if strcmp(model.quantizer, 'kdtree') model.kdtree = vl_kdtreebuild(vocab) ; end % -------------------------------------------------------------------- % Compute spatial histograms % -------------------------------------------------------------------- if ~exist(conf.histPath) || conf.clobber hists = {} ; parfor ii = 1:length(images) % for ii = 1:length(images) fprintf('Processing %s (%.2f %%)\n', images{ii}, 100 * ii / length(images)) ; im = imread(fullfile(conf.calDir, images{ii})) ; hists{ii} = getImageDescriptor(model, im); end hists = cat(2, hists{:}) ; save(conf.histPath, 'hists') ; else load(conf.histPath) ; end % -------------------------------------------------------------------- % Compute feature map % -------------------------------------------------------------------- psix = vl_homkermap(hists, 1, 'kchi2', 'gamma', .5) ; % -------------------------------------------------------------------- % Train SVM % -------------------------------------------------------------------- if ~exist(conf.modelPath) || conf.clobber switch conf.svm.solver case 'pegasos' lambda = 1 / (conf.svm.C * length(selTrain)) ; w = [] ; % for ci = 1:length(classes) parfor ci = 1:length(classes) perm = randperm(length(selTrain)) ; fprintf('Training model for class %s\n', classes{ci}) ; y = 2 * (imageClass(selTrain) == ci) - 1 ; w(:,ci) = vl_pegasos(psix(:,selTrain(perm)), ... int8(y(perm)), lambda, ... 'NumIterations', 50/lambda, ... 'BiasMultiplier', conf.svm.biasMultiplier) ; end case 'liblinear' svm = train(imageClass(selTrain)', ... sparse(double(psix(:,selTrain))), ... sprintf(' -s 3 -B %f -c %f', ... conf.svm.biasMultiplier, conf.svm.C), ... 'col') ; w = svm.w' ; end model.b = conf.svm.biasMultiplier * w(end, :) ; model.w = w(1:end-1, :) ; save(conf.modelPath, 'model') ; else load(conf.modelPath) ; end % -------------------------------------------------------------------- % Test SVM and evaluate % -------------------------------------------------------------------- % Estimate the class of the test images scores = model.w' * psix + model.b' * ones(1,size(psix,2)) ; [drop, imageEstClass] = max(scores, [], 1) ; % Compute the confusion matrix idx = sub2ind([length(classes), length(classes)], ... imageClass(selTest), imageEstClass(selTest)) ; confus = zeros(length(classes)) ; confus = vl_binsum(confus, ones(size(idx)), idx) ; % Plots figure(1) ; clf; subplot(1,2,1) ; imagesc(scores(:,[selTrain selTest])) ; title('Scores') ; set(gca, 'ytick', 1:length(classes), 'yticklabel', classes) ; subplot(1,2,2) ; imagesc(confus) ; title(sprintf('Confusion matrix (%.2f %% accuracy)', ... 100 * mean(diag(confus)/conf.numTest) )) ; print('-depsc2', [conf.resultPath '.ps']) ; save([conf.resultPath '.mat'], 'confus', 'conf') ; % ------------------------------------------------------------------------- function im = standarizeImage(im) % ------------------------------------------------------------------------- im = im2single(im) ; if size(im,1) > 480, im = imresize(im, [480 NaN]) ; end % ------------------------------------------------------------------------- function hist = getImageDescriptor(model, im) % ------------------------------------------------------------------------- im = standarizeImage(im) ; width = size(im,2) ; height = size(im,1) ; numWords = size(model.vocab, 2) ; % get PHOW features [frames, descrs] = vl_phow(im, model.phowOpts{:}) ; % quantize appearance switch model.quantizer case 'vq' [drop, binsa] = min(vl_alldist(model.vocab, single(descrs)), [], 1) ; case 'kdtree' binsa = double(vl_kdtreequery(model.kdtree, model.vocab, ... single(descrs), ... 'MaxComparisons', 15)) ; end for i = 1:length(model.numSpatialX) binsx = vl_binsearch(linspace(1,width,model.numSpatialX(i)+1), frames(1,:)) ; binsy = vl_binsearch(linspace(1,height,model.numSpatialY(i)+1), frames(2,:)) ; % combined quantization bins = sub2ind([model.numSpatialY(i), model.numSpatialX(i), numWords], ... binsy,binsx,binsa) ; hist = zeros(model.numSpatialY(i) * model.numSpatialX(i) * numWords, 1) ; hist = vl_binsum(hist, ones(size(bins)), bins) ; hists{i} = single(hist / sum(hist)) ; end hist = cat(1,hists{:}) ; hist = hist / sum(hist) ; % ------------------------------------------------------------------------- function [className, score] = classify(model, im) % ------------------------------------------------------------------------- hist = getImageDescriptor(model, im) ; psix = vl_homkermap(hist, 1, .7, 'kchi2') ; scores = model.w' * psix + model.b' ; [score, best] = max(scores) ; className = model.classes{best} ;
github
ee368/EE368-Android-Samples-master
sift_mosaic.m
.m
EE368-Android-Samples-master/Tutorial3/ServerCode/vlfeat-0.9.14/apps/sift_mosaic.m
4,621
utf_8
8fa3ad91b401b8f2400fb65944c79712
function mosaic = sift_mosaic(im1, im2) % SIFT_MOSAIC Demonstrates matching two images using SIFT and RANSAC % % SIFT_MOSAIC demonstrates matching two images based on SIFT % features and RANSAC and computing their mosaic. % % SIFT_MOSAIC by itself runs the algorithm on two standard test % images. Use SIFT_MOSAIC(IM1,IM2) to compute the mosaic of two % custom images IM1 and IM2. % AUTORIGHTS if nargin == 0 im1 = imread(fullfile(vl_root, 'data', 'river1.jpg')) ; im2 = imread(fullfile(vl_root, 'data', 'river2.jpg')) ; end % make single im1 = im2single(im1) ; im2 = im2single(im2) ; % make grayscale if size(im1,3) > 1, im1g = rgb2gray(im1) ; else im1g = im1 ; end if size(im2,3) > 1, im2g = rgb2gray(im2) ; else im2g = im2 ; end % -------------------------------------------------------------------- % SIFT matches % -------------------------------------------------------------------- [f1,d1] = vl_sift(im1g) ; [f2,d2] = vl_sift(im2g) ; [matches, scores] = vl_ubcmatch(d1,d2) ; numMatches = size(matches,2) ; X1 = f1(1:2,matches(1,:)) ; X1(3,:) = 1 ; X2 = f2(1:2,matches(2,:)) ; X2(3,:) = 1 ; % -------------------------------------------------------------------- % RANSAC with homography model % -------------------------------------------------------------------- clear H score ok ; for t = 1:100 % estimate homograpyh subset = vl_colsubset(1:numMatches, 4) ; A = [] ; for i = subset A = cat(1, A, kron(X1(:,i)', vl_hat(X2(:,i)))) ; end [U,S,V] = svd(A) ; H{t} = reshape(V(:,9),3,3) ; % score homography X2_ = H{t} * X1 ; du = X2_(1,:)./X2_(3,:) - X2(1,:)./X2(3,:) ; dv = X2_(2,:)./X2_(3,:) - X2(2,:)./X2(3,:) ; ok{t} = (du.*du + dv.*dv) < 6*6 ; score(t) = sum(ok{t}) ; end [score, best] = max(score) ; H = H{best} ; ok = ok{best} ; % -------------------------------------------------------------------- % Optional refinement % -------------------------------------------------------------------- function err = residual(H) u = H(1) * X1(1,ok) + H(4) * X1(2,ok) + H(7) ; v = H(2) * X1(1,ok) + H(5) * X1(2,ok) + H(8) ; d = H(3) * X1(1,ok) + H(6) * X1(2,ok) + 1 ; du = X2(1,ok) - u ./ d ; dv = X2(2,ok) - v ./ d ; err = sum(du.*du + dv.*dv) ; end if exist('fminsearch') == 2 H = H / H(3,3) ; opts = optimset('Display', 'none', 'TolFun', 1e-8, 'TolX', 1e-8) ; H(1:8) = fminsearch(@residual, H(1:8)', opts) ; else warning('Refinement disabled as fminsearch was not found.') ; end % -------------------------------------------------------------------- % Show matches % -------------------------------------------------------------------- dh1 = max(size(im2,1)-size(im1,1),0) ; dh2 = max(size(im1,1)-size(im2,1),0) ; figure(1) ; clf ; subplot(2,1,1) ; imagesc([padarray(im1,dh1,'post') padarray(im2,dh2,'post')]) ; o = size(im1,2) ; line([f1(1,matches(1,:));f2(1,matches(2,:))+o], ... [f1(2,matches(1,:));f2(2,matches(2,:))]) ; title(sprintf('%d tentative matches', numMatches)) ; axis image off ; subplot(2,1,2) ; imagesc([padarray(im1,dh1,'post') padarray(im2,dh2,'post')]) ; o = size(im1,2) ; line([f1(1,matches(1,ok));f2(1,matches(2,ok))+o], ... [f1(2,matches(1,ok));f2(2,matches(2,ok))]) ; title(sprintf('%d (%.2f%%) inliner matches out of %d', ... sum(ok), ... 100*sum(ok)/numMatches, ... numMatches)) ; axis image off ; drawnow ; % -------------------------------------------------------------------- % Mosaic % -------------------------------------------------------------------- box2 = [1 size(im2,2) size(im2,2) 1 ; 1 1 size(im2,1) size(im2,1) ; 1 1 1 1 ] ; box2_ = inv(H) * box2 ; box2_(1,:) = box2_(1,:) ./ box2_(3,:) ; box2_(2,:) = box2_(2,:) ./ box2_(3,:) ; ur = min([1 box2_(1,:)]):max([size(im1,2) box2_(1,:)]) ; vr = min([1 box2_(2,:)]):max([size(im1,1) box2_(2,:)]) ; [u,v] = meshgrid(ur,vr) ; im1_ = vl_imwbackward(im2double(im1),u,v) ; z_ = H(3,1) * u + H(3,2) * v + H(3,3) ; u_ = (H(1,1) * u + H(1,2) * v + H(1,3)) ./ z_ ; v_ = (H(2,1) * u + H(2,2) * v + H(2,3)) ./ z_ ; im2_ = vl_imwbackward(im2double(im2),u_,v_) ; mass = ~isnan(im1_) + ~isnan(im2_) ; im1_(isnan(im1_)) = 0 ; im2_(isnan(im2_)) = 0 ; mosaic = (im1_ + im2_) ./ mass ; figure(2) ; clf ; imagesc(mosaic) ; axis image off ; title('Mosaic') ; if nargout == 0, clear mosaic ; end end
github
jacksky64/imageProcessing-master
metaImageInfo.m
.m
imageProcessing-master/Matlab Slicer/imStacks/metaImageInfo.m
8,259
utf_8
769e7b03c38d70ddec2d85cd9430d077
function info = metaImageInfo(fileName, varargin) %METAIMAGEINFO Read information header of meta image data % % INFO = metaImageInfo(FILENAME) % Read and decodes the information stored in metaimage header file. % % Metaimage header files are text files containing parameters name/value % pairs in each line. % Example of header file: % ObjectType = Image % NDims = 3 % DimSize = 256 256 64 % ElementType = MET_USHORT % HeaderSize = -1 % ElementSize = 1 1 3 % ElementSpacing = 1 1 1 % ElementByteOrderMSB = False % ElementDataFile = image.raw % % For information about MetaImage Header format, see: % http://www.itk.org/Wiki/MetaIO/Documentation#Quick_Start % % Currently supported tags are: % NDims: number of dimensions % DimSize % ElementType % ElementDataFile % HeaderSize % ElementSpacing % ElementByteOrderMSB % ElementNumberOfChannels % BinaryData % BinaryDataByteOrderMSB % CompressedData % CompressedDataSize % AnatomicalOrientation % CenterOfRotation % Offset % TransformMatrix % ElementDataFile (should be the last tag in the file) % % % The values supported for 'ElementDataFile' are: % * the name of a single data file. Example: 'dataFile.raw' % * the keyword 'LIST', followed by the list of file names, one name by % line. Example: % ElementDataFile = LIST % slice-00.tif % slice-01.tif % slice-02.tif % ... % * a filename pattern, followed by three values corresponding to index % of the first slice, index of the last slice, and step between two % consecutive slices. Example: 'slice-%03d.tif 1 50 2' % * the 'LOCAL' keyword is not (yet...) supported. % % % Example % info = metaImageInfo('example.hdr'); % X = metaImageRead(info); % % % See also % metaImageRead, readstack, analyze75info % % ------ % Author: David Legland % e-mail: [email protected] % Created: 2010-01-27, using Matlab 7.9.0.529 (R2009b) % http://www.pfl-cepia.inra.fr/index.php?page=slicer % Copyright 2010 INRA - Cepia Software Platform. % HISTORY % 2011-08-17 code cleanup, better initialization of spacing %% Open info file % If the function is called without argument, open a dialog to read a file if nargin == 0 [filename, pathname] = uigetfile(... {'*.mha;*.mhd', 'Meta-Image info file (*.mha, *.mhd)'}, ... 'Open Meta-Image info file'); info = [pathname filename]; if filename == 0 return; end end % add file extension if not present ext = []; if length(fileName) > 3 ext = fileName(end-3:end); end if ~strcmp(ext, '.mhd') fileName = [fileName '.mhd']; end % get base directory path = fileparts(fileName); % open the file for reading f = fopen(fileName, 'rt'); if f == -1 error(['Could not find the file: ' fileName]); end %% Initialisations % extract key and value of current line [tag string] = splitLine(fgetl(f)); % check header file contains an image if ~strcmp(tag, 'ObjectType') || ~strcmp(string, 'Image') error('File should contain image data'); end % default values info.ObjectType = 'Image'; info.NDims = 0; info.DimSize = []; info.ElementType = 'uint8'; info.ElementDataFile = ''; % setup default values for spatial calibration info.ElementSpacing = []; info.ElementSize = []; % default optional values info.HeaderSize = 0; %% Loop over lines in the file while true % read current line, if exists line = fgetl(f); if line == -1 break end % extract key and value of current line [tag string] = splitLine(line); % extract each possible tag switch tag % First, parse required tags case 'NDims' % number of dimensions. Used for initializing data structure nd = parseInteger(string); info.NDims = nd; case 'DimSize' info.DimSize = parseIntegerVector(string); case 'ElementType' info.ElementType = string; case 'HeaderSize' info.HeaderSize = parseInteger(string); case 'ElementDataFile' info.ElementDataFile = computeDataFileName(string, f, path); % this tag is supposed to be the last one in the tag list break; % Following tags are optional, but often encountered case 'ElementSize' info.ElementSize = parseFloatVector(string); case 'ElementSpacing' info.ElementSpacing = parseFloatVector(string); case 'ElementByteOrderMSB' info.ElementByteOrderMSB = parseBoolean(string); case 'ElementNumberOfChannels' info.ElementNumberOfChannels = parseInteger(string); case 'BinaryData' info.BinaryData = parseBoolean(string); case 'BinaryDataByteOrderMSB' info.BinaryDataByteOrderMSB = parseBoolean(string); case 'CompressedData' info.CompressedData = parseBoolean(string); case 'CompressedDataSize' info.CompressedData = parseIntegerVector(string); % Some less common tags, used e.g. by Elastix case 'AnatomicalOrientation' info.AnatomicalOrientation = string; case 'CenterOfRotation' info.CenterOfRotation = parseFloatVector(string); case 'Offset' info.Offset = parseFloatVector(string); case 'TransformMatrix' info.TransformMatrix = parseFloatVector(string); % And unknown tags otherwise warning('MetaImageInfo:UnknownTag', ... ['Unknown tag in MetaImage header: ' tag]); info.(tag) = string; end end fclose(f); %% Process optional input arguments while length(varargin) > 1 info.(varargin{1}) = varargin{2}; varargin(1:2) = []; end %% Cleanup initialization if isempty(info.ElementSize) || isempty(info.ElementSpacing) if ~isempty(info.ElementSize) % init spacing from size info.ElementSpacing = info.ElementSize; elseif ~isempty(info.ElementSpacing) % init size from spacing info.ElementSize = info.ElementSpacing; else % init both spacing and size from dimension siz = ones(1, info.NDims); info.ElementSize = siz; info.ElementSpacing = siz; end end function name = computeDataFileName(string, f, path) % compute filename or file name list from pattern and current path % remove eventual trailing spaces string = strtrim(string); if strcmpi(string, 'list') % read the list of file names and add the path tline = fgetl(f); name = {}; i = 1; while ischar(tline) name{i} = fullfile(path, tline); %#ok<AGROW> i = i + 1; tline = fgetl(f); end elseif ~isempty(strfind(string, ' ')) % If filename contains spaces, it is parsed to extract indices C = textscan(string, '%s %d %d %d'); pattern = C{1}{1}; i0 = C{2}; iend = C{3}; istep = C{4}; inds = i0:istep:iend; name = cell(length(inds), 1); for i=1:length(inds) name{i} = fullfile(path, sprintf(pattern, inds(i))); end else % Simply use the string as the name of the file name = fullfile(path, string); end function [tag string] = splitLine(line) [tag remain] = strtok(line, '='); tag = strtrim(tag); string = strtrim(strtok(remain, '=')); function b = parseBoolean(string) b = strcmpi(string, 'true'); function v = parseInteger(string) v = sscanf(string, '%d'); function v = parseIntegerVector(string) v = sscanf(string, '%d', inf)'; function v = parseFloatVector(string) v = sscanf(string, '%f', inf)';
github
jacksky64/imageProcessing-master
metaImageWrite.m
.m
imageProcessing-master/Matlab Slicer/imStacks/metaImageWrite.m
7,057
utf_8
df8a6d61ef09a3a7575d62ff1765f76f
function metaImageWrite(img, fileName, varargin) %METAIMAGEWRITE Write header and data files of an image in MetaImage format % % metaImageWrite(IMG, FILENAME); % IMG is a matlab array, and FILENAME is the generic name (without % extension) of the metaimage file. % The functions tries to determine which parameters are appropriate for % the given image. % % metaImageWrite(IMG, FILENAME, INFO); % Gives an additional structure as argument, containing additional % properties. % % metaImageWrite(..., PARAM, VALUE); % Specifies additional properties as parameter key and value pairs. Case % is relevant. See http://www.itk.org/Wiki/MetaIO/Documentation for % details. % % Example % [x y z] = meshgrid(1:80, 1:80, 1:80); % img = ((x-40).^2 + (y-40).^2 + (z-40).^2)<1000; % img = uint8(img*255); % metaImageWrite(img, 'ball'); % metaImageWrite(img, 'ball.mhd'); % works also, same result % metaImageWrite(img, 'ball', 'ElementType', 'MET_USHORT', ... % 'ElementByteOrderMSB', 'True') % % See also % % % ------ % Author: David Legland % e-mail: [email protected] % Created: 2010-02-03, using Matlab 7.9.0.529 (R2009b) % http://www.pfl-cepia.inra.fr/index.php?page=slicer % Copyright 2010 INRA - Cepia Software Platform. %% Initialisations % extract meta-information info = struct; if ~isempty(varargin) var = varargin{1}; if isstruct(var) info = var; varargin(1) = []; end end % permute image dimension to use x as first index img = permute(img, [2 1 3:ndims(img)]); % extract image dimension dims = size(img); % check if image is color isColor = false; if length(dims) > 2 && dims(3) == 3 isColor = true; dims = dims([1 2 4:end]); end nd = length(dims); %% Process file names % ensure the filename has no '.mhd' extension if length(fileName) > 4 if strcmp(fileName(end-3:end), '.mhd') fileName(end-3:end) = []; end end % split filename and diectory [path, name] = fileparts(fileName); % header and binary file names headerFileName = [name '.mhd']; binaryFileName = [name '.raw']; %% Create file info structure % check main information are present if ~isfield(info, 'ObjectType') info.ObjectType = 'Image'; end if ~isfield(info, 'NDims') info.NDims = nd; end if ~isfield(info, 'DimSize') info.DimSize = dims; end if ~isfield(info, 'ElementType') info.ElementType = metaTypeToString(class(img)); end if ~isfield(info, 'ElementDataFile') info.ElementDataFile = binaryFileName; end if isColor info.ElementNumberOfChannels = 3; end % add additional varargins while length(varargin) > 1 key = varargin{1}; if ~ischar(key) error('following parameter must be a string: %s', key); end info.(key) = varargin{2}; varargin(1:2) = []; end % ensure MSB info is written for data other than 8-bits elementByteOrderDefined = isfield(info, 'ElementByteOrderMSB'); binaryDataByteOrderDefined = isfield(info, 'BinaryDataByteOrderMSB'); if ~ischar(img) && ~(elementByteOrderDefined || binaryDataByteOrderDefined) info.BinaryData = true; if ispc info.ElementByteOrderMSB = false; else info.ElementByteOrderMSB = true; end end % open file f = fopen(fullfile(path, headerFileName), 'wt'); %% write minimal information tags fprintf(f, '%s = %s\n', 'ObjectType', 'Image'); fprintf(f, '%s = %d\n', 'NDims', info.NDims); fprintf(f, '%s =%s\n', 'DimSize', ... sprintf(repmat(' %d', 1, info.NDims), info.DimSize)); fprintf(f, '%s = %s\n', 'ElementType', info.ElementType); %% write each additional tag names = fieldnames(info); for i = 1:length(names) name = names{i}; % some tags are either in the very beginning or at the end, so they are % not processed in the loop if ismember(name, {'ObjectType', 'NDims', 'DimSize', 'ElementType', ... 'ElementDataFile'}) continue; end fprintf(f, '%s = %s\n', name, convertToString(info.(name))); end %% write binary data info into header fprintf(f, '%s = %s\n', 'ElementDataFile', binaryFileName); fclose(f); %% Write binary data % Specify little- or big-endian ordering byteOrder = determineByteOrder(info); % extract data precision precision = parseMetaType(info.ElementType); % open file for binary writing f = fopen(fullfile(path, binaryFileName), 'wb'); % write image data in correct order if ~isColor % write grayscale data fwrite(f, img(:), precision, 0, byteOrder); else % first permute data to write RGB of each element, then x, y, and z data = permute(img, [3 1 2 4:ndims(img)]); fwrite(f, data(:), precision, 0, byteOrder); end % close binary file fclose(f); function type = parseMetaType(string) switch string case 'MET_UCHAR' type = 'uint8'; case 'MET_CHAR' type = 'int8'; case 'MET_USHORT' type = 'uint16'; case 'MET_SHORT' type = 'int16'; case 'MET_UINT' type = 'uint32'; case 'MET_INT' type = 'int32'; case 'MET_FLOAT' type = 'single'; case 'MET_DOUBLE' type = 'double'; otherwise error('unknown element type in metaimage header: %s', string); end function string = metaTypeToString(type) % convert a matlab class name to MetaImage Type string switch type case 'int8' string = 'MET_CHAR'; case 'uint8' string = 'MET_UCHAR'; case 'int16' string = 'MET_SHORT'; case 'uint16' string = 'MET_USHORT'; case 'int32' string = 'MET_INT'; case 'uint32' string = 'MET_UINT'; case 'single' string = 'MET_FLOAT'; case 'double' string = 'MET_DOUBLE'; otherwise error('unknown pixel type: %s', type); end function string = convertToString(data) N = length(data(:)); if ischar(data) string = data; elseif islogical(data) strings = {'false', 'true'}; pattern = ['%s' repmat(' %s', 1, N-1)]; string = sprintf(pattern, strings{data(:)+1}); elseif isinteger(data) pattern = ['%d' repmat(' %d', 1, N-1)]; string = sprintf(pattern, data(:)); elseif isfloat(data) pattern = ['%g' repmat(' %g', 1, N-1)]; string = sprintf(pattern, data(:)); else error('Unknwon type of data'); end function byteOrder = determineByteOrder(info) % default byte order given by system byteOrder = 'n'; % first check the ElementByteOrderMSB field if isfield(info, 'ElementByteOrderMSB') if info.ElementByteOrderMSB byteOrder = 'b'; else byteOrder = 'l'; end end % also check the BinaryDataByteOrderMSB field if isfield(info, 'BinaryDataByteOrderMSB') if info.BinaryDataByteOrderMSB byteOrder = 'b'; else byteOrder = 'l'; end end
github
jacksky64/imageProcessing-master
orthoSlices.m
.m
imageProcessing-master/Matlab Slicer/imStacks/orthoSlices.m
12,391
utf_8
a8b1b8223f887fe71954a2d76eb53635
function varargout = orthoSlices(img, varargin) %ORTHOSLICES Display three orthogonal slices in the same figure % % orthoSlices(IMG) % Show three orthogonal slices of the 3D image IMG in the same figure. % Each slice is displayed to occupy the maximum amount of space within % the figure, keeping same proportion between slices. % % orthoSlices(IMG, POS) % Specify the initial position of the intersection point between slices. % POS is given as [XPOS YPOS ZPOS]. % % orthoSlices(IMG, POS, SPACING) % Also specify the spacing between voxels, in [SP_X SP_Y SP_Z] order. % % orthoSlices(..., 'DisplayRange', RANGE) % Specifies the grayscale range of the data. RANGE should be a 1-by-2 row % vector containing min and max values to display. Display will be % adjusted such that min value correspond to black (value 0), and max % value correspond to white (value 255). % % orthoSlices(..., 'ColorMap', MAP) % Specifies the Colormap to display the data with. MAP should be a % 255-by-3 array. % % Examples % % Display MRI head using three orthogonal planar slices % img = analyze75read(analyze75info('brainMRI.hdr')); % figure; clf; hold on; % orthoSlices(img, [60 80 13], [1 1 2.5]); % % % Same image displayed with different grayscale calibration % img = analyze75read(analyze75info('brainMRI.hdr')); % figure; clf; hold on; % orthoSlices(img, [60 80 13], [1 1 2.5], 'displayRange', [0 90], 'lut', 'jet'); % % See also % orthoSlices3d, colormap % % % ------ % Author: David Legland % e-mail: [email protected] % Created: 2011-04-26, using Matlab 7.9.0.529 (R2009b) % Copyright 2011 INRA - Cepia Software Platform. %% Extract input arguments % get stack size (in x, y, z order) siz = stackSize(img); % extract position of middle point if ~isempty(varargin) && ~ischar(varargin{1}) pos = varargin{1}; varargin(1) = []; else % use center as default position pos = ceil(siz / 2); end % extract spacing spacing = [1 1 1]; if ~isempty(varargin) && ~ischar(varargin{1}) spacing = varargin{1}; if numel(spacing) == 1 % in case of scalar spacing, convert to row vector spacing = [1 1 1] * spacing; end varargin(1) = []; end % origin origin = [0 0 0]; % flag for displaying 3D orthodlices in lower right corner % (set to false for the moment, requires further debugging) display3d = false; % default settings for color rendering displayRange = [0 255]; lut = ''; % extract options specified by strings while length(varargin) > 1 param = varargin{1}; switch lower(param) case 'spacing' spacing = varargin{2}; case 'origin' origin = varargin{2}; case 'displayrange' displayRange = varargin{2}; case {'lut', 'colormap'} lut = varargin{2}; otherwise error(['Unknown parameter: ' param]); end varargin(1:2) = []; end %% Extract data % extract each slice sliceXY = squeeze(stackSlice(img, 3, pos(3))); sliceZY = squeeze(permute(stackSlice(img, 1, pos(1)), [2 1 3])); sliceXZ = squeeze(permute(stackSlice(img, 2, pos(2)), [2 1 3])); % If necessary, convert slice to RGB image to facilitate display if ~isempty(lut) || any(displayRange ~= [0 255]) || ~isa(img, 'uint8') sliceXY = computeSliceRGB(sliceXY, displayRange, lut); sliceZY = computeSliceRGB(sliceZY, displayRange, lut); sliceXZ = computeSliceRGB(sliceXZ, displayRange, lut); end % get spatial calibration xdata = (0:siz(1)-1) * spacing(1) + origin(1); ydata = (0:siz(2)-1) * spacing(2) + origin(2); zdata = (0:siz(3)-1) * spacing(3) + origin(3); % coordinate of reference point xPos = xdata(pos(1)); yPos = ydata(pos(2)); zPos = zdata(pos(3)); % physical extent of image in each dimension wx = xdata([1 end]); wy = ydata([1 end]); wz = zdata([1 end]); % amount of space used by each axis width1 = wx / (wx + wz); width2 = wz / (wx + wz); height1 = wy / (wy + wz); height2 = wz / (wy + wz); % refresh figure hf = gcf; clf; %% Display XY Slice % create XY axis axes('parent', hf, 'units', 'normalized', 'visible', 'off', ... 'position', [0 height2 width1 height1]); hSliceXY = imshow(sliceXY, 'xdata', xdata, 'ydata', ydata); hLineXYx = line([xdata(1) xdata(end)], [yPos yPos], 'color', 'r'); hLineXYy = line([xPos xPos], [ydata(1) ydata(end)], 'color', 'g'); % set up slice data data.handle = hSliceXY; data.fig = hf; data.dir = 3; data.dir1 = 1; data.dir2 = 2; data.index = pos(3); data.xdata = xdata; data.ydata = ydata; set(hSliceXY, 'UserData', data); % set up mouse listener set(hSliceXY, 'ButtonDownFcn', @startDragCrossLine); %% Display ZY Slice % create ZY axis axes('parent', hf, 'units', 'normalized', 'visible', 'off', ... 'position', [width1 height2 width2 height1]); hSliceZY = imshow(sliceZY, 'xdata', zdata, 'ydata', ydata); hLineZYz = line([zdata(1) zdata(end)], [yPos yPos], 'color', 'b'); hLineZYy = line([zPos zPos], [ydata(1) ydata(end)], 'color', 'g'); % set up slice data data.handle = hSliceZY; data.fig = hf; data.dir = 1; data.dir1 = 3; data.dir2 = 2; data.index = pos(1); data.xdata = zdata; data.ydata = ydata; set(hSliceZY, 'UserData', data); % set up mouse listener set(hSliceZY, 'ButtonDownFcn', @startDragCrossLine); %% Display XZ Slice % create XZ axis axes('parent', hf, 'units', 'normalized', 'visible', 'off', ... 'position', [0 0 width1 height2]); hSliceXZ = imshow(sliceXZ, 'xdata', xdata, 'ydata', zdata); hLineXZx = line([xdata(1) xdata(end)], [zPos zPos], 'color', 'r'); hLineXZz = line([xPos xPos], [zdata(1) zdata(end)], 'color', 'b'); % set up slice data data.handle = hSliceXZ; data.fig = hf; data.dir = 2; data.dir1 = 1; data.dir2 = 3; data.index = pos(2); data.xdata = xdata; data.ydata = zdata; set(hSliceXZ, 'UserData', data); % set up mouse listener set(hSliceXZ, 'ButtonDownFcn', @startDragCrossLine); %% Display Orthoslices if display3d axes('parent', hf, 'units', 'normalized', 'visible', 'off', ... 'position', [width1 0 width2 height2], ... 'ydir', 'reverse', 'zdir', 'reverse'); %#ok<UNRCH> [hSlice3dXY hSlice3dYZ hSlice3dXZ] = orthoSlices3d(img, pos); % show orthogonal lines hLine3dX = line([xdata(1) xdata(end)], [yPos yPos], [zPos zPos], 'color', 'r'); hLine3dY = line([xPos xPos], [ydata(1) ydata(end)], [zPos zPos], 'color', 'r'); hLine3dZ = line([xPos xPos], [yPos yPos], [zdata(1) zdata(end)], 'color', 'r'); view([-20 30]); axis equal; end %% Create GUI for figure % clear struct data = struct; % general data common to all displays data.img = img; data.pos = pos; % display calibration data.displayRange = displayRange; data.lut = lut; data.display3d = display3d; % spatial basis data.bases = {xdata, ydata, zdata}; % handles to image displays data.hSliceXY = hSliceXY; data.hSliceZY = hSliceZY; data.hSliceXZ = hSliceXZ; % handles to ortho lines data.hLineXYx = hLineXYx; data.hLineXYy = hLineXYy; data.hLineZYz = hLineZYz; data.hLineZYy = hLineZYy; data.hLineXZx = hLineXZx; data.hLineXZz = hLineXZz; if display3d % handles to 3D slice displays data.hSlice3dXY = hSlice3dXY; %#ok<UNRCH> data.hSlice3dYZ = hSlice3dYZ; data.hSlice3dXZ = hSlice3dXZ; % handles to 3D line separators data.hLine3dX = hLine3dX; data.hLine3dY = hLine3dY; data.hLine3dZ = hLine3dZ; end % will contain current callback object data.src = []; set(hf, 'UserData', data); if nargout > 0 varargout = {hf}; end function startDragCrossLine(src, event) %#ok<INUSD> %STARTDRAGGING One-line description here, please. % % output = startDragging(input) % % Example % startDragging % % See also % data = get(src, 'UserData'); % direction of slicing (normal to the slice) dir1 = data.dir1; dir2 = data.dir2; %disp(['Click on orthoslice - ' num2str(dir1) num2str(dir2)]); hFig = gcbf(); dataFig = get(hFig, 'UserData'); pos = dataFig.pos; point = get(gca, 'CurrentPoint'); point = point(1, 1:2); % convert indices to physical coordinates xdata = dataFig.bases{dir1}; ydata = dataFig.bases{dir2}; [mini pos(dir1)] = min((xdata - point(1)).^2); %#ok<ASGLU> [mini pos(dir2)] = min((ydata - point(2)).^2); %#ok<ASGLU> dataFig.pos = pos; dataFig.src = src; set(hFig, 'UserData', dataFig); updateDisplay(hFig); % set up listeners for figure object set(hFig, 'WindowButtonMotionFcn', @dragCrossLine); set(hFig, 'WindowButtonUpFcn', @stopDragCrossLine); function stopDragCrossLine(src, event) %#ok<INUSD> %stopDragCrossLine One-line description here, please. % % output = stopDragCrossLine(input) % % Example % stopDragCrossLine % % See also % % remove figure listeners hFig = src; set(hFig, 'WindowButtonUpFcn', ''); set(hFig, 'WindowButtonMotionFcn', ''); function dragCrossLine(src, event) %#ok<INUSD> %DRAGSLICE One-line description here, please. % % output = dragSlice(input) % % Example % dragSlice % % See also % % extract handle to image object data = get(src, 'UserData'); hImg = data.src; pos = data.pos; % position of last click point = get(gca, 'CurrentPoint'); point = point(1, 1:2); % main directions of current slice imgData = get(hImg, 'UserData'); dir1 = imgData.dir1; dir2 = imgData.dir2; % convert indices to physical coordinates xdata = data.bases{dir1}; ydata = data.bases{dir2}; [mini pos(dir1)] = min((xdata - point(1)) .^ 2); %#ok<ASGLU> [mini pos(dir2)] = min((ydata - point(2)) .^ 2); %#ok<ASGLU> % update data for current figure data.pos = pos; set(src, 'UserData', data); % redraw updateDisplay(src); function updateDisplay(hFig) % get dat of current image data = get(hFig, 'UserData'); img = data.img; pos = data.pos; displayRange = data.displayRange; lut = data.lut; % extract each slice sliceXY = squeeze(stackSlice(img, 3, pos(3))); sliceZY = squeeze(stackSlice(img, 1, pos(1))); sliceXZ = squeeze(stackSlice(img, 2, pos(2))); % If necessary, convert slice to RGB image to facilitate display if ~isempty(lut) || any(displayRange ~= [0 255]) || ~isa(img, 'uint8') sliceXY = computeSliceRGB(sliceXY, displayRange, lut); sliceZY = computeSliceRGB(sliceZY, displayRange, lut); sliceXZ = computeSliceRGB(sliceXZ, displayRange, lut); end % get spatial calibration xdata = data.bases{1}; ydata = data.bases{2}; zdata = data.bases{3}; % coordinate of reference point xpos = xdata(pos(1)); ypos = ydata(pos(2)); zpos = zdata(pos(3)); % update planar image displays buf = sliceXY; set(data.hSliceXY, 'CData', buf); if data.display3d set(data.hSlice3dXY, 'CData', buf); end buf = sliceZY; set(data.hSliceZY, 'CData', permute(buf, [2 1 3])); if data.display3d set(data.hSlice3dYZ, 'CData', buf); end buf = sliceXZ; set(data.hSliceXZ, 'CData', permute(buf, [2 1 3])); if data.display3d set(data.hSlice3dXZ, 'CData', buf); end % update position of orthogonal lines set(data.hLineXYx, 'YData', [ypos ypos]); set(data.hLineXYy, 'XData', [xpos xpos]); set(data.hLineZYz, 'YData', [ypos ypos]); set(data.hLineZYy, 'XData', [zpos zpos]); set(data.hLineXZx, 'YData', [zpos zpos]); set(data.hLineXZz, 'XData', [xpos xpos]); if data.display3d % update position of 3D orthogonal lines set(data.hLine3dX, 'YData', [ypos ypos]); set(data.hLine3dX, 'ZData', [zpos zpos]); set(data.hLine3dY, 'XData', [xpos xpos]); set(data.hLine3dY, 'ZData', [zpos zpos]); set(data.hLine3dZ, 'XData', [xpos xpos]); set(data.hLine3dZ, 'YData', [ypos ypos]); % update position of 3D slices coords = get(data.hSlice3dXY, 'ZData'); coords(:) = zpos; set(data.hSlice3dXY, 'ZData', coords); coords = get(data.hSlice3dYZ, 'XData'); coords(:) = xpos; set(data.hSlice3dYZ, 'XData', coords); coords = get(data.hSlice3dXZ, 'YData'); coords(:) = ypos; set(data.hSlice3dXZ, 'YData', coords); end
github
jacksky64/imageProcessing-master
metaImageRead.m
.m
imageProcessing-master/Matlab Slicer/imStacks/metaImageRead.m
5,728
utf_8
6acee507c8af1e296e6000ec8993817f
function [img info] = metaImageRead(info, varargin) %METAIMAGEREAD Read an image in MetaImage format % % IMG = metaImageRead(INFO) % Read the image IMG from data given in structure INFO. INFO is typically % returned by the metaImageInfo function. % % IMG = metaImageRead(FILENAME) % Read the image from a filename. Filename is a text file in metaimage % format. % % IMG = metaImageRead(..., PARAM, VALUE) % Specify additional parameters for reading. The parameter can % complement, or override the parameters given in info file or structure. % See the function metaImageInfo for information about supported % parameters. % % [IMG INFO] = metaImageRead(...) % Also returns the corresponding info structure associated to image IMG. % % % Example % % first load info, then load data % info = metaImageInfo('example.mhd'); % X = metaImageRead(info); % % % specify only the filename, and specify endianness % IMG = metaImageRead('filename.mhd', 'ElementByteOrderMSB', false); % % See also % metaImageInfo, readstack, analyze75info % % ------ % Author: David Legland % e-mail: [email protected] % Created: 2010-01-27, using Matlab 7.9.0.529 (R2009b) % http://www.pfl-cepia.inra.fr/index.php?page=slicer % Copyright 2010 INRA - Cepia Software Platform. %% Get info structure % default empty value to avoid errors when user cancels img = []; % If the function is called without argument, open a dialog to read a file if nargin == 0 [filename, pathname] = uigetfile(... {'*.mha;*.mhd', 'Meta-Image data file (*.mha, *.mhd)'}, ... 'Open Meta-Image data file'); info = [pathname filename]; if filename == 0 return; end end % info should be a structure. If not, assume this is name of info file if ischar(info) % read info strucure from file name info = metaImageInfo(info, varargin{:}); end if ~isstruct(info) error('First argument must be a metaimage info structure'); end %% Pre-compute variables % determines pixel type [pixelType isArrayType] = parseMetaType(info.ElementType); % determines number of channels nChannels = 1; if isfield(info, 'ElementNumberOfChannels'); nChannels = info.ElementNumberOfChannels; end if nChannels > 1 isArrayType = true; end % % in the case of array type, need number of channels % nChannels = 1; % if isArrayType % nChannels = info.ElementNumberOfChannels; % end % compute size of resulting array % (in the case of multi-channel image, use dim=3 for channel dimension). dims = info.DimSize; if isArrayType dims = [nChannels dims]; end % allocate memory for data img = zeros(dims, pixelType); % Specify little- or big-endian ordering byteOrder = determineByteOrder(info); %% Read data file(s) if ischar(info.ElementDataFile) % open data file f = fopen(info.ElementDataFile, 'rb'); if f == -1 error(['Unable to open data file: ' info.ElementDataFile]); end % skip header (defined as number of bytes) fread(f, info.HeaderSize, 'uint8'); % read binary data img(:) = fread(f, prod(dims), ['*' pixelType], byteOrder); % close file fclose(f); % convert order of elements if isArrayType % for color images, replace channel dim at third position img = permute(img, [3 2 1 4:length(dims)]); else % permute dims 1 and 2 img = permute(img, [2 1 3:length(dims)]); end elseif iscell(info.ElementDataFile) % filename is given as a cell array containing name of each file % check dimension are consistent if length(info.ElementDataFile) ~= info.DimSize(3) error('Number of files does not match image third dimension'); end % iterate over the elements in ElementDataFile, extract filename, % read image and add corresponding data to the img array. for i = 1:length(info.ElementDataFile) filename = info.ElementDataFile{i}; data = imread(filename); % use different processing for grayscale and color images if isArrayType img(:,:,:,i) = data; else img(:,:,i) = data; end end else error('Unknown type of filename'); end function [type isArray] = parseMetaType(string) % % determines if the data type is an array or a scalar % isArray = false; % ind = findstr(string, '_ARRAY'); % if ~isempty(ind) % isArray = true; % string = string(1:ind-1); % end isArray = false; % determines the base data type switch string case 'MET_UCHAR' type = 'uint8'; case 'MET_CHAR' type = 'int8'; case 'MET_USHORT' type = 'uint16'; case 'MET_SHORT' type = 'int16'; case 'MET_UINT' type = 'uint32'; case 'MET_INT' type = 'int32'; case 'MET_FLOAT' type = 'single'; case 'MET_DOUBLE' type = 'double'; otherwise error('Unknown element type in metaimage header: %s', string); end function byteOrder = determineByteOrder(info) % Return a character that can be used by fread function % default byte order given by system byteOrder = 'n'; % first check the ElementByteOrderMSB field if isfield(info, 'ElementByteOrderMSB') if info.ElementByteOrderMSB byteOrder = 'b'; else byteOrder = 'l'; end end % also check the BinaryDataByteOrderMSB field if isfield(info, 'BinaryDataByteOrderMSB') if info.BinaryDataByteOrderMSB byteOrder = 'b'; else byteOrder = 'l'; end end
github
jacksky64/imageProcessing-master
TabPanel.m
.m
imageProcessing-master/Matlab Slicer/imStacks/+uiextras/TabPanel.m
20,903
utf_8
cd35a9887b8563870e78f3635ef7341c
classdef TabPanel < uiextras.CardPanel & uiextras.DecoratedPanel %TabPanel Show one element inside a tabbed panel % % obj = uiextras.TabPanel() creates a panel with tabs along one edge % to allow selection between the different child objects contained. % % obj = uiextras.TabPanel(param,value,...) also sets one or more % property values. % % See the <a href="matlab:doc uiextras.TabPanel">documentation</a> for more detail and the list of properties. % % Examples: % >> f = figure(); % >> p = uiextras.TabPanel( 'Parent', f, 'Padding', 5 ); % >> uicontrol( 'Style', 'frame', 'Parent', p, 'Background', 'r' ); % >> uicontrol( 'Style', 'frame', 'Parent', p, 'Background', 'b' ); % >> uicontrol( 'Style', 'frame', 'Parent', p, 'Background', 'g' ); % >> p.TabNames = {'Red', 'Blue', 'Green'}; % >> p.SelectedChild = 2; % % See also: uiextras.Panel % uiextras.BoxPanel % Copyright 2009-2010 The MathWorks, Inc. % $Revision: 354 $ % $Date: 2010-11-01 10:07:13 +0000 (Mon, 01 Nov 2010) $ properties TabSize = 50 TabPosition = 'top' % which side of the contents to put the tabs [top|bottom] end % public properties properties( Dependent = true ) TabNames % The title string for each tab TabEnable = {} % The enable state of individual tabs end % dependent properties properties( SetAccess = private, GetAccess = private, Hidden = true ) Images_ = struct() TabImage_ = [] PageLabels = [] PageEnable_ = {} end % private properties methods function obj = TabPanel(varargin) % First step is to create the parent class. We pass the % arguments (if any) just incase the parent needs setting obj = [email protected]( varargin{:} ); obj = [email protected]( varargin{:} ); % Get some defaults bgcol = obj.BackgroundColor; obj.HighlightColor = ( 2*[1 1 1] + bgcol )/3; obj.ShadowColor = 0.5*bgcol; % Add a UIControl for drawing the tabs obj.TabImage_ = uicontrol( ... 'Visible', 'on', ... 'units', 'pixels', ... 'Parent', obj.UIContainer, ... 'HandleVisibility', 'off', ... 'Position', [1 1 1 1], ... 'style', 'checkbox', ... 'Tag', 'uiextras.TabPanel:TabImage'); % Make sure the images are loaded obj.reloadImages(); % Set some defaults obj.setPropertyFromDefault( 'HighlightColor' ); obj.setPropertyFromDefault( 'ShadowColor' ); obj.setPropertyFromDefault( 'TabPosition' ); obj.setPropertyFromDefault( 'TabSize' ); % Parse any input arguments if nargin>0 set( obj, varargin{:} ); end obj.redraw(); end % TabPanel end % public methods methods function set.TabSize(obj,value) obj.TabSize = value; obj.redraw(); end % set.TabSize function set.TabPosition(obj,value) if ~ischar( value ) || ~ismember( lower( value ), {'top','bottom'} ) error( 'GUILayout:InvalidPropertyValue', ... 'Property ''TabPosition'' must be ''top'' or ''bottom''.' ); end obj.TabPosition = [upper( value(1) ),lower( value(2:end) )]; obj.redraw(); end % set.TabPosition function value = get.TabNames( obj ) if isempty( obj.PageLabels ) value = {}; elseif numel( obj.PageLabels ) == 1 value = {get( obj.PageLabels, 'String' )}; else value = get( obj.PageLabels, 'String' )'; end end % get.TabNames function set.TabNames(obj,value) if ~iscell( value ) || numel( value )~=numel( obj.Children ) error( 'GUILayout:InvalidPropertyValue', ... 'Property ''TabNames'' must be a cell array of strings the same size as property ''Children''.' ) end for ii=1:numel( obj.Children ) set( obj.PageLabels(ii), 'String', value{ii} ); end end % set.TabNames function value = get.TabEnable(obj) value = obj.PageEnable_; end % get.TabEnable function set.TabEnable(obj,value) if ~iscell( value ) || numel( value )~=numel( obj.Children ) ... || any( ~ismember( lower(value), {'on','off'} ) ) error( 'GUILayout:InvalidPropertyValue', ... 'Property ''TabEnable'' must be a cell array of ''on''/''off'' the same size as property ''Children''.' ) end obj.PageEnable_ = lower( value ); if strcmpi( obj.Enable, 'on' ) obj.onEnable(); end end % set.TabEnable end % accessor methods methods ( Access = protected ) function redraw(obj) %redraw Redraw the tabs and contents % Check the object exists (may be being deleted!) if isempty(obj.TabImage_) || ~ishandle(obj.TabImage_) return; end C = obj.Children; T = obj.TabNames; % Make sure label array is right size nC = numel(C); nT = numel(T); if nC==0 || nT~=nC return end pos = getpixelposition( obj.UIContainer ); pad = obj.Padding; % Calculate the required height from the font size oldFontUnits = get( obj.PageLabels(1), 'FontUnits' ); set( obj.PageLabels(1), 'FontUnits', 'Pixels' ); fontHeightPix = get( obj.PageLabels(1), 'FontSize' ); set( obj.PageLabels(1), 'FontUnits', oldFontUnits ); tabHeight = ceil( 1.5*fontHeightPix + 4 ); % Work out where the tabs labels and contents go if strcmpi( obj.TabPosition, 'Top' ) tabPos = [1 1+pos(4)-tabHeight, pos(3), tabHeight+2]; contentPos = [pad+1 pad+1 pos(3)-2*pad pos(4)-2*pad-tabHeight]; else tabPos = [1 1, pos(3), tabHeight+2]; contentPos = [pad+1 tabHeight+pad+1 pos(3)-2*pad pos(4)-2*pad-tabHeight]; end % Shorthand for colouring things in fgCol = obj.BackgroundColor; bgCol = obj.BackgroundColor; shCol = 0.9*obj.BackgroundColor; totalWidth = round( tabPos(3)-1 ); divWidth = 8; textWidth = obj.TabSize; if textWidth<0 % This means we should fill the space textWidth = floor( (totalWidth - (nC+1)*divWidth) / nC ); end textPos = [tabPos(1:2), textWidth, tabHeight - 4]; if ~isempty( obj.SelectedChild ) % The tabs are drawn as a single image tabCData(:,:,1) = bgCol(1)*ones(20,totalWidth); tabCData(:,:,2) = bgCol(2)*ones(20,totalWidth); tabCData(:,:,3) = bgCol(3)*ones(20,totalWidth); set( obj.TabImage_, 'Position', [tabPos(1:2),totalWidth,tabHeight] ); % Use the CardLayout function to put the right child onscreen obj.showSelectedChild( contentPos ) % Now update the tab image tabCData(:,1:divWidth,:) = obj.Images_.NonNot; for ii=1:nC x = divWidth+(divWidth+textWidth)*(ii-1)+1; set( obj.PageLabels(ii), ... 'Position', textPos+[x,0,0,0] ); % BJT: Fix bug where text renders off edge of container if (textPos(1)+x >= totalWidth ) set( obj.PageLabels(ii), 'Visible', 'off' ); else set( obj.PageLabels(ii), 'Visible', 'on' ); rhs = textPos(1)+x+textPos(3); if ( rhs > totalWidth ) % Text is partially off the edge set( obj.PageLabels(ii), 'Position', textPos+[x,0,totalWidth-rhs,0] ); end end if ii==obj.SelectedChild, set( obj.PageLabels(ii), ... 'ForegroundColor', obj.ForegroundColor, ... 'BackgroundColor', fgCol); % Set the dividers to show the right image tabCData(:,x:x+textWidth-1,:) = repmat(obj.Images_.SelBack,1,textWidth); if ii==1 tabCData(:,x-divWidth:x-1,:) = obj.Images_.NonSel; else tabCData(:,x-divWidth:x-1,:) = obj.Images_.NotSel; end if ii==nC tabCData(:,x+textWidth:x+textWidth+divWidth-1,:) = obj.Images_.SelNon; else tabCData(:,x+textWidth:x+textWidth+divWidth-1,:) = obj.Images_.SelNot; end else set( obj.PageLabels(ii), ... 'ForegroundColor', 0.6*obj.ForegroundColor + 0.4*shCol, ... 'BackgroundColor', shCol ); tabCData(:,x:x+textWidth-1,:) = repmat(obj.Images_.NotBack,1,textWidth); if ii==nC tabCData(:,x+textWidth:x+textWidth+divWidth-1,:) = obj.Images_.NotNon; else tabCData(:,x+textWidth:x+textWidth+divWidth-1,:) = obj.Images_.NotNot; end end end % For % Stretch the CData to match the fontsize if tabHeight ~= 20 topbot = min( round( tabHeight/2 ), 5 ); midsz = tabHeight - 2*topbot; topData = tabCData(1:topbot,:,:); bottomData = tabCData(end-topbot+1:end,:,:); midData = repmat( tabCData(10,:,:), [midsz,1,1] ); tabCData = [ topData ; midData ; bottomData ]; end if strcmpi( obj.TabPosition, 'Top' ) set( obj.TabImage_, 'CData', tabCData ); else set( obj.TabImage_, 'CData', flipdim( tabCData, 1 ) ); end end % Make sure the text labels are top of the stack % ch = get( obj.TabContainer_, 'Children' ); % if numel( ch ) > 1 % labs = ismember( get(ch,'Style'), 'text' ); % else % labs = strcmpi( get(ch,'Style'), 'text' ); % end % set( obj.TabContainer_, 'Children', [flipud(ch(labs));ch(~labs)] ); % Note the flip is needed so that the text always redraws end % redraw function onChildAdded( obj, source, eventData ) %#ok<INUSD> %onChildAdded: Callback that fires when a child is added to a container. % Select the new addition C = obj.Children; N = numel( C ); visible = obj.Visible; title = sprintf( 'Page %d', N ); obj.PageLabels(end+1,1) = uicontrol( ... 'Visible', visible, ... 'style', 'text', ... 'enable', 'inactive', ... 'string', title, ... 'FontName', obj.FontName, ... 'FontUnits', obj.FontUnits, ... 'FontSize', obj.FontSize, ... 'FontAngle', obj.FontAngle, ... 'FontWeight', obj.FontWeight, ... 'ForegroundColor', obj.ForegroundColor, ... 'parent', obj.UIContainer, ... 'HandleVisibility', 'off', ... 'ButtonDownFcn', {@iTabClicked, obj, N}); obj.PageEnable_{1,end+1} = 'on'; if strcmpi( obj.Enable, 'off' ) set( obj.PageLabels(end), 'Enable', 'off' ); end obj.SelectedChild = N; end % onChildAdded function onChildRemoved( obj, source, eventData ) %#ok<INUSL> %onChildAdded: Callback that fires when a container child is destroyed or reparented. % If the missing child is the selected one, select something else obj.TabNames( eventData.ChildIndex ) = []; obj.PageEnable_( eventData.ChildIndex ) = []; delete( obj.PageLabels(end) ); obj.PageLabels(end) = []; if obj.SelectedChild >= eventData.ChildIndex % Changing the selection will force a redraw if isempty( obj.Children ) obj.SelectedChild = []; else obj.SelectedChild = max( 1, obj.SelectedChild - 1 ); end else % We don't need to change the selection, so explicitly % redraw obj.redraw(); end end % onChildRemoved function onBackgroundColorChanged( obj, source, eventData ) %#ok<INUSD> %onBackgroundColorChanged Callback that fires when the container background color is changed % % We need to make the panel match the container background obj.reloadImages(); obj.redraw(); end % onBackgroundColorChanged function onPanelColorChanged( obj, source, eventData ) %#ok<INUSD> % Colors have changed. This requires the images to be reset and % redrawn. obj.reloadImages(); obj.redraw(); end % onPanelColorChanged function onPanelFontChanged( obj, source, eventData ) %#ok<INUSL> % Font has changed. Since the font size and shape affects the % space available for the contents, we need to redraw. for ii=1:numel( obj.PageLabels ) set( obj.PageLabels(ii), eventData.Property, eventData.Value ); end obj.redraw(); end % onPanelFontChanged function onEnable( obj, source, eventData ) %#ok<INUSD> % We use "inactive" to be the "on" state if strcmpi( obj.Enable, 'on' ) % Take notice of the individual enable states. Where the % page is to be enabled we set the title uicontrol to be % inactive rather than on to avoid mouse-over problems. hittest = obj.PageEnable_; enable = strrep( obj.PageEnable_, 'on', 'inactive' ); for jj=1:numel( obj.PageLabels ) set( obj.PageLabels(jj), ... 'Enable', enable{jj}, ... 'HitTest', hittest{jj} ); % Since the panel as a whole is on, we may need to % switch off some children obj.helpSetChildEnable( obj.Children(jj), hittest{jj} ); end else for jj=1:numel( obj.PageLabels ) set( obj.PageLabels(jj), 'Enable', 'off', 'HitTest', 'off' ); end end end % onEnable function reloadImages( obj ) % Reload tab images % If any of the colours are not yet constructed, stop now if isempty( obj.TabImage_ ) ... || isempty( obj.HighlightColor ) ... || isempty( obj.ShadowColor ) return; end % First part of the name says which type of right-hand edge is needed % (non = no edge, not = not selected, sel = selected), second gives % left-hand obj.Images_.NonSel = iLoadIcon( 'tab_NoEdge_Selected.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.SelNon = iLoadIcon( 'tab_Selected_NoEdge.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.NonNot = iLoadIcon( 'tab_NoEdge_NotSelected.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.NotNon = iLoadIcon( 'tab_NotSelected_NoEdge.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.NotSel = iLoadIcon( 'tab_NotSelected_Selected.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.SelNot = iLoadIcon( 'tab_Selected_NotSelected.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.NotNot = iLoadIcon( 'tab_NotSelected_NotSelected.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.SelBack = iLoadIcon( 'tab_Background_Selected.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); obj.Images_.NotBack = iLoadIcon( 'tab_Background_NotSelected.png', ... obj.BackgroundColor, obj.HighlightColor, obj.ShadowColor ); end % reloadImages end % protected methods end % classdef %-------------------------------------------------------------------------% function im = iLoadIcon(imagefilename, backgroundcolor, highlightcolor, shadowcolor ) % Special image loader that turns various primary colours into background % colours. error( nargchk( 4, 4, nargin, 'struct' ) ); % Load an icon and set the transparent color this_dir = fileparts( mfilename( 'fullpath' ) ); icon_dir = fullfile( this_dir, 'Resources' ); im8 = imread( fullfile( icon_dir, imagefilename ) ); im = double(im8)/255; rows = size(im,1); cols = size(im,2); % Anything that's pure green goes to transparent f=find((im8(:,:,1)==0) & (im8(:,:,2)==255) & (im8(:,:,3)==0)); im(f) = nan; im(f + rows*cols) = nan; im(f + 2*rows*cols) = nan; % Anything pure red goes to selected background f=find((im8(:,:,1)==255) & (im8(:,:,2)==0) & (im8(:,:,3)==0)); im(f) = backgroundcolor(1); im(f + rows*cols) = backgroundcolor(2); im(f + 2*rows*cols) = backgroundcolor(3); % Anything pure blue goes to background background f=find((im8(:,:,1)==0) & (im8(:,:,2)==0) & (im8(:,:,3)==255)); im(f) = backgroundcolor(1); im(f + rows*cols) = backgroundcolor(2); im(f + 2*rows*cols) = backgroundcolor(3); % Anything pure yellow goes to deselected background f=find((im8(:,:,1)==255) & (im8(:,:,2)==255) & (im8(:,:,3)==0)); im(f) = 0.9*backgroundcolor(1); im(f + rows*cols) = 0.9*backgroundcolor(2); im(f + 2*rows*cols) = 0.9*backgroundcolor(3); % Anything pure white goes to highlight f=find((im8(:,:,1)==255) & (im8(:,:,2)==255) & (im8(:,:,3)==255)); im(f) = highlightcolor(1); im(f + rows*cols) = highlightcolor(2); im(f + 2*rows*cols) = highlightcolor(3); % Anything pure black goes to shadow f=find((im8(:,:,1)==0) & (im8(:,:,2)==0) & (im8(:,:,3)==0)); im(f) = shadowcolor(1); im(f + rows*cols) = shadowcolor(2); im(f + 2*rows*cols) = shadowcolor(3); end % iLoadIcon %-------------------------------------------------------------------------% function iTabClicked( src, evt, obj, idx ) %#ok<INUSL> % Call the user callback before selecting the tab evt = struct( ... 'Source', obj, ... 'PreviousChild', obj.SelectedChild, ... 'SelectedChild', idx ); uiextras.callCallback( obj.Callback, obj, evt ); obj.SelectedChild = idx; end % iTabClicked