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github
|
Sinan81/PSAT-master
|
fm_threed.m
|
.m
|
PSAT-master/psat-oct/psat/fm_threed.m
| 11,096 |
utf_8
|
a9f48ea419066334caf6e7e619ec2e0b
|
function varargout = fm_threed(varargin)
% FM_THREED create GUI for network visualisations
%
% HDL = FM_THREED()
%
%Author: Federico Milano
%Date: 21-Aug-2007
%Version: 1.0.0
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2019 Federico Milano
global Settings Theme Varout Path Fig File CPF OPF
% check for data file
if isempty(File.data)
fm_disp('Set a data file for running sparse matrix visualisation.',2)
return
end
% check for initial power flow solution
if ~Settings.init
fm_disp('Solve base case power flow...')
Settings.show = 0;
fm_set('lf')
Settings.show = 1;
if ~Settings.init, return, end
end
if nargin
if ~ishandle(Fig.threed), return, end
hdl1 = findobj(Fig.threed,'Tag','PopupMenu1');
hdl2 = findobj(Fig.threed,'Tag','PopupMenu2');
value1 = get(hdl1,'Value');
value2 = get(hdl2,'Value');
switch varargin{1}
case 'update'
hdl3 = findobj(Fig.threed,'Tag','MenuCaxis');
if value2 == 1
set(hdl3,'Enable','on')
else
set(hdl3,'Enable','off')
end
if (value2 == 6 || value2 == 7) && ~OPF.init
fm_disp(['Run OPF before displaying Locational Marginal ' ...
'Prices'],2)
set(hdl2,'Value',1)
set(hdl3,'Enable','on')
return
end
fm_simrep('DrawModel',value1,value2,0)
case 'init'
Varout.movie = getframe(findobj(Fig.threed,'Tag','Axes1'));
hdl = findobj(Fig.threed,'Tag','Axes1');
togglecontrols(Fig.threed,'off')
case 'newframe'
fm_simrep('DrawModel',value1,value2,1)
case 'finish'
togglecontrols(Fig.threed,'on')
case 'movie'
if isempty(Varout.movie), return, end
axes(findobj(Fig.threed,'Tag','Axes1'));
xlabel('')
%axes('Position',[0 0 1 1])
if Settings.init > 1 && ~CPF.init
fps = round(length(Varout.movie)/(Settings.tf-Settings.t0));
if ~fps, fps = 12; end
movie(Varout.movie,1,fps)
else
movie(Varout.movie)
end
case 'savemovie'
if isempty(Varout.movie), return, end
cd(Path.data)
filedata = strrep(File.data,'@ ','');
filedata = strrep(filedata,'(mdl)','_mdl');
mov = VideoWriter(filedata);
open(mov);
writeVideo(mov, Varout.movie);
close(mov);
cd(Path.local)
case 'openmovie'
[filename, pathname] = uigetfile('*.avi', 'Pick an AVI-file');
if ~pathname, return, end
cd(pathname)
Varout.movie = aviread(filename);
cd(Path.local)
case 'setcaxis'
switch get(gcbo,'Checked')
case 'on'
set(gcbo,'Checked','off')
Varout.caxis = 0;
case 'off'
set(gcbo,'Checked','on')
Varout.caxis = 1;
end
fm_simrep('DrawModel',value1,value2,0)
case 'printfig'
togglecontrols(Fig.threed,'off')
cd(Path.data)
filedata = strrep(File.data,'@ ','');
filedata = strrep(filedata,'(mdl)','_mdl');
print(Fig.threed,'-dpng',filedata)
cd(Path.local)
togglecontrols(Fig.threed,'on')
end
return
end
if ishandle(Fig.threed), figure(Fig.threed), return, end
maps = {'jet';'hot';'gray';'bone';'copper';'pink';
'hsv';'cool';'autumn';'spring';'winter';'summer'};
h0 = figure('Color',Theme.color01, ...
'Units', 'normalized', ...
'CreateFcn','Fig.threed = gcf;', ...
'DeleteFcn','Fig.threed = -1; rotate3d off', ...
'FileName','fm_threed', ...
'MenuBar','none', ...
'Name','Network Visualisation', ...
'NumberTitle','off', ...
'PaperPosition',[18 180 576 432], ...
'PaperUnits','points', ...
'Position',sizefig(0.666,0.74), ...
'Resize','on', ...
'ToolBar','none');
% Menu File
h1 = uimenu('Parent',h0, ...
'Label','File', ...
'Tag','MenuFile');
h2 = uimenu('Parent',h1, ...
'Callback','fm_threed openmovie', ...
'Label', 'Open movie', ...
'Tag','OpenMovie', ...
'Accelerator','o');
h2 = uimenu('Parent',h1, ...
'Callback','fm_threed savemovie', ...
'Label', 'Save movie', ...
'Tag','SaveMovie', ...
'Accelerator','s');
h2 = uimenu('Parent',h1, ...
'Callback','fm_threed printfig', ...
'Label', 'Save frame', ...
'Tag','PrintFig', ...
'Accelerator','p');
h2 = uimenu('Parent',h1, ...
'Callback','close(gcf)', ...
'Label','Close', ...
'Tag','FileClose', ...
'Separator','on', ...
'Accelerator','q');
% Menu Edit
h1 = uimenu('Parent',h0, ...
'Label','Edit', ...
'Tag','MenuEdit');
h2 = uimenu('Parent',h1, ...
'Callback','fm_threed update', ...
'Label', 'Update', ...
'Accelerator','u', ...
'Tag','MenuUpdate');
h2 = uimenu('Parent',h1, ...
'Callback','fm_threed movie', ...
'Label', 'Play movie', ...
'Accelerator','m', ...
'Tag','MenuPlay');
% Menu View
h1 = uimenu('Parent',h0, ...
'Label','View', ...
'Tag','MenuView');
h2 = uimenu('Parent',h1, ...
'Callback','fm_threed setcaxis', ...
'Label', 'Use voltage limits', ...
'Accelerator','v', ...
'Tag','MenuCaxis');
if Varout.caxis
set(h1,'Checked','on')
else
set(h1,'Checked','off')
end
h2 = uimenu('Parent',h1, ...
'Label', 'Transparency', ...
'Tag','MenuTransparency', ...
'Separator','on');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(1), Varout.alpha = 1;', ...
'Label','None', ...
'Tag','alpha1', ...
'Accelerator','0');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.9), Varout.alpha = 0.9;', ...
'Label','alpha = 0.9', ...
'Tag','alpha1', ...
'Accelerator','9');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.8), Varout.alpha = 0.8;', ...
'Label','alpha = 0.8', ...
'Tag','alpha1', ...
'Accelerator','8');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.7), Varout.alpha = 0.7;', ...
'Label','alpha = 0.7', ...
'Tag','alpha1', ...
'Accelerator','7');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.6), Varout.alpha = 0.6;', ...
'Label','alpha = 0.6', ...
'Tag','alpha1', ...
'Accelerator','6');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.5), Varout.alpha = 0.5;', ...
'Label','alpha = 0.5', ...
'Tag','alpha1', ...
'Accelerator','5');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.4), Varout.alpha = 0.4;', ...
'Label','alpha = 0.4', ...
'Tag','alpha1', ...
'Accelerator','4');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.3), Varout.alpha = 0.3;', ...
'Label','alpha = 0.3', ...
'Tag','alpha1', ...
'Accelerator','3');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.2), Varout.alpha = 0.2;', ...
'Label','alpha = 0.2', ...
'Tag','alpha1', ...
'Accelerator','2');
h3 = uimenu('Parent',h2, ...
'Callback','alpha(0.1), Varout.alpha = 0.1;', ...
'Label','alpha = 0.1', ...
'Tag','alpha1', ...
'Accelerator','1');
%fm_set colormap
h1 = axes('Parent',h0, ...
'Box','on', ...
'CameraUpVector',[0 1 0], ...
'CameraUpVectorMode','manual', ...
'Color',Theme.color11, ...
'Position',[0.09 0.152 0.85 0.779], ...
'Tag','Axes1', ...
'XColor',[0 0 0], ...
'YColor',[0 0 0], ...
'ZColor',[0 0 0]);
set(h0,'UserData',h1);
h1 = uicontrol('Parent',h0, ...
'CData',fm_mat('threed_matlab'), ...
'BackgroundColor',Theme.color02, ...
'Units', 'normalized', ...
'Callback','fm_threed update', ...
'Position',[0.673 0.0185 0.06 0.08], ...
'TooltipString','Update', ...
'Tag','Pushbutton1');
h1 = uicontrol('Parent',h0, ...
'CData',fm_mat('threed_movie'), ...
'BackgroundColor',Theme.color02, ...
'Units', 'normalized', ...
'Callback','fm_threed movie', ...
'Position',[0.673+0.0650 0.0185 0.06 0.08], ...
'TooltipString','Play Movie', ...
'Tag','Pushbutton2');
h1 = uicontrol('Parent',h0, ...
'BackgroundColor',Theme.color02, ...
'Units', 'normalized', ...
'Callback','close(gcf)', ...
'Position',[0.82 0.044 0.121 0.052], ...
'String','Close', ...
'Tag','Pushbutton3');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'Callback','String = get(gcbo,''String''); eval([''colormap '',String{get(gcbo,''Value'')}]);', ...
'BackgroundColor',Theme.color04, ...
'Position',[0.488 0.041 0.157 0.056], ...
'String',maps, ...
'Style','popupmenu', ...
'Tag','PopupMenu1', ...
'Value',1);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'Callback','fm_threed update', ...
'BackgroundColor',Theme.color04, ...
'Position',[0.27 0.041 0.187 0.056], ...
'String',{'Voltage Magnitudes','Voltage Angles', ...
'Line Flows','Gen. Rotor Angles', ...
'Gen. Rotor Speeds','LMPs','NCPs'}, ...
'Style','popupmenu', ...
'Tag','PopupMenu2', ...
'Value',1);
x = 0.02;
y = 0.05;
% Frame and push buttons for axis manipulation
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'ForegroundColor',Theme.color03, ...
'Position',[0.0726-x 0.0638-y 0.2000 0.0893], ...
'Style','frame', ...
'Tag','Frame2');
h1 = uicontrol('Parent',h0, ...
'CData',fm_mat('mat_rotate'), ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback','rotate3d(gcf), , if(get(gcbo,''Value'')), set(findobj(gcf,''Tag'',''toggle7''),''Value'',0), zoom(gcf,''off''), end', ...
'Position',[0.0776-x 0.0685-y 0.0600 0.0800], ...
'TooltipString','Rotate graph', ...
'Style','togglebutton', ...
'Tag','toggle5');
h1 = uicontrol('Parent',h0, ...
'CData',fm_mat('mat_grid'), ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback','grid(get(Fig.threed,''UserData''))', ...
'Position',[0.1426-x 0.0685-y 0.0600 0.0800], ...
'TooltipString','Grid', ...
'Style','togglebutton', ...
'Tag','toggle6');
h1 = uicontrol('Parent',h0, ...
'CData',fm_mat('mat_zoomxy'), ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback','zoom, if(get(gcbo,''Value'')), set(findobj(gcf,''Tag'',''toggle5''),''Value'',0), rotate3d(gcf,''off''), end', ...
'Position',[0.2076-x 0.0685-y 0.0600 0.0800], ...
'TooltipString','Zoom', ...
'Style','togglebutton', ...
'Tag','toggle7');
if nargout > 0, fig = h0; end
function togglecontrols(fig,flag)
hdl(1) = findobj(fig,'Tag','PopupMenu1');
hdl(2) = findobj(fig,'Tag','PopupMenu2');
hdl(3) = findobj(fig,'Tag','Frame2');
hdl(4) = findobj(fig,'Tag','toggle5');
hdl(5) = findobj(fig,'Tag','toggle6');
hdl(6) = findobj(fig,'Tag','toggle7');
hdl(7) = findobj(fig,'Tag','Pushbutton1');
hdl(8) = findobj(fig,'Tag','Pushbutton2');
hdl(9) = findobj(fig,'Tag','Pushbutton3');
set(hdl,'Visible',flag)
|
github
|
Sinan81/PSAT-master
|
fm_dirset.m
|
.m
|
PSAT-master/psat-oct/psat/fm_dirset.m
| 30,919 |
utf_8
|
5fd21968fdac71735d7ea592d1e51a8e
|
function varargout = fm_dirset(type)
% FM_DIRSET define settings and actions for the data format
% conversion GUI
%
% FM_DIRSET(TYPE)
% TYPE action indentifier
%
%see also FM_DIR
%
%Author: Federico Milano
%Date: 11-Nov-2002
%Update: 05-Jul-2003
%Update: 31-Jul-2003
%Update: 07-Oct-2003
%Version: 1.1.0
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2019 Federico Milano
global Path Fig Settings Theme
if ishandle(Fig.dir)
hdl = findobj(Fig.dir,'Tag','PopupMenu1');
formato = get(hdl,'Value');
hdl_dir = findobj(Fig.dir,'Tag','EditText1');
folder1 = get(hdl_dir,'String');
if ischar(folder1) && isdir(folder1), cd(folder1), end
end
% codes:
IEEE = 1;
PSAT = 2;
PSATPERT = 3;
PSATMDL = 4;
CYME = 5;
MATPOWER = 6;
PST = 7;
EPRI = 8;
PSSE = 9;
PSAP = 10;
EUROSTAG = 11;
TH = 12;
CESI = 13;
VST = 14;
SIMPOW = 15;
NEPLAN = 16;
DIGSILENT = 17;
POWERWORLD = 18;
PET = 19;
FLOWDEMO = 20;
GEEPC = 21;
CHAPMAN = 22;
UCTE = 23;
PCFLO = 24;
WEBFLOW = 25;
IPSS = 26;
CEPEL = 27;
ODM = 28;
REDS = 29;
VITRUVIO = 30; % all files
switch type
case 'formatlist'
formati = cell(VITRUVIO,1);
formati{IEEE} = 'IEEE CDF (.dat, .txt, .cf)';
formati{CYME} = 'CYME (.nnd, .sf)';
formati{MATPOWER} = 'MatPower (.m)';
formati{PSAT} = 'PSAT data (.m)';
formati{PSATPERT} = 'PSAT pert. (.m)';
formati{PSATMDL} = 'PSAT Simulink (.mdl)';
formati{PST} = 'PST (.m)';
formati{EPRI} = 'EPRI (.wsc, .txt, .dat)';
formati{PSSE} = 'PSS/E (.raw)';
formati{PSAP} = 'PSAP (.dat)';
formati{EUROSTAG} = 'Eurostag (.dat)';
formati{TH} = 'TH (.dat)';
formati{CESI} = 'CESI - INPTC1 (.dat)';
formati{VST} = 'VST (.dat)';
formati{SIMPOW} = 'SIMPOW (.optpow)';
formati{NEPLAN} = 'NEPLAN (.ndt)';
formati{DIGSILENT} = 'DigSilent (.dgs)';
formati{POWERWORLD} = 'PowerWorld (.aux)';
formati{PET} = 'PET (.pet)';
formati{FLOWDEMO} = 'Flowdemo.net (.fdn)';
formati{GEEPC} = 'GE format (.epc)';
formati{CHAPMAN} = 'Chapman format';
formati{UCTE} = 'UCTE format';
formati{PCFLO} = 'PCFLO format';
formati{WEBFLOW} = 'WebFlow format';
formati{IPSS} = 'InterPSS format (.ipss)';
formati{CEPEL} = 'CEPEL format (.txt)';
formati{ODM} = 'ODM format (.odm, .xml)';
formati{REDS} = 'REDS format (.pos)';
formati{VITRUVIO} = 'All Files (*.*)';
varargout(1) = {formati};
%==================================================================
case 'changedir'
hdl = findobj(Fig.dir,'Tag','Listbox1');
cdir = get(hdl,'String');
ndir = get(hdl,'Value');
namedir = cdir{ndir(1),1};
switch namedir
case '..'
eval('cd ..');
case '.'
if ~isempty(dir(namedir))
cd(namedir);
end
case '[ * DATA * ]'
if isempty(Path.data), return, end
cd(Path.data)
case '[ * PERT * ]'
if isempty(Path.pert), return, end
cd(Path.pert)
case '[ * LOCAL * ]'
if isempty(Path.local), return, end
cd(Path.local)
case '[ * PSAT * ]'
if isempty(Path.psat), return, end
cd(Path.psat)
otherwise
cd(namedir)
end
a = dir;
numdir = find([a.isdir] == 1);
cdir = {a(numdir).name}';
cdir(strmatch('.',cdir)) = [];
cdir(strmatch('@',cdir)) = [];
set(hdl,'ListboxTop',1,'String',[{'.'; '..'};cdir;get(hdl,'UserData')],'Value',1);
hdl = findobj(Fig.dir,'Tag','EditText1');
set(hdl,'String',pwd);
set(Fig.dir,'UserData',pwd);
hdl = findobj(Fig.dir,'Tag','Listbox2');
hdlf = findobj(Fig.dir,'Tag','PopupMenu1');
cfile = uform(get(hdlf,'Value'));
if isempty(cfile)
cfile = 'empty';
else
cfile = sort(cfile);
end
set(hdl,'ListboxTop',1,'String',cfile,'Value',1);
%==================================================================
case 'chformat'
if ~ishandle(Fig.dir), return; end
if ~strcmp(get(Fig.dir, 'Type'), 'figure'), return; end
hdlf = findobj(Fig.dir,'Tag','PopupMenu1');
formato = get(hdlf,'Value');
if ~length(formato)
formato = 1
end
% display(formato)
hdl = findobj(Fig.dir,'Tag','Listbox2');
hdla = findobj(Fig.dir,'Tag','Axes1');
hdlc = findobj(Fig.dir,'Tag','Pushbutton1');
hdl1 = findobj(Fig.dir,'Tag','CheckboxSilent');
hdl2 = findobj(Fig.dir,'Tag','Checkbox2');
hdl4 = findobj(Fig.dir,'Tag','StaticText2');
hdlp = findobj(Fig.dir,'Tag','PushbuttonPreview');
cfile = uform(formato);
switch int32(formato)
case IEEE, file = 'ieee';
case CYME, file = 'cyme';
case MATPOWER, file = 'pserc';
case PSAT, file = 'psatdata';
case PSATPERT, file = 'psatpert';
case PSATMDL, file = 'simulink';
case PST, file = 'cherry';
case EPRI, file = 'epri';
case PSSE, file = 'pti';
case PSAP, file = 'pjm';
case EUROSTAG, file = 'eurostag';
case TH, file = 'th';
case CESI, file = 'cesi';
case VST, file = 'cepe';
case SIMPOW, file = 'simpow';
case NEPLAN, file = 'neplan';
case DIGSILENT, file = 'digsilent';
case POWERWORLD, file = 'powerworld';
case PET, file = 'pet';
case FLOWDEMO, file = 'eeh';
case GEEPC, file = 'ge';
case CHAPMAN, file = 'chapman';
case UCTE, file = 'ucte';
case PCFLO, file = 'pcflo';
case WEBFLOW, file = 'webflow';
case IPSS, file = 'ipss';
case CEPEL, file = 'cepel';
case ODM, file = 'odm';
case REDS, file = 'reds';
case VITRUVIO, file = 'vitruvio';
end
switch formato
case VITRUVIO,
if ~get(hdlf,'UserData'), set(hdlc,'Enable','off'), end
set(hdl1,'Enable','off')
set(hdl2,'Enable','off')
set(hdl4,'Enable','off')
case PSAT,
set(hdlc,'Enable','on')
set(hdl1,'Enable','off')
if ~get(hdlf,'UserData'), set(hdl2,'Enable','on'), end
if ~get(hdlf,'UserData'), set(hdl4,'Enable','on'), end
case PSATPERT,
if ~get(hdlf,'UserData'), set(hdlc,'Enable','off'), end
set(hdl1,'Enable','off')
set(hdl2,'Enable','off')
set(hdl4,'Enable','off')
case {NEPLAN,CESI}
set(hdlc,'Enable','on')
set(hdl1,'Enable','on')
set(hdl2,'Enable','off')
set(hdl4,'Enable','off')
otherwise % all other formats
set(hdlc,'Enable','on')
set(hdl1,'Enable','off')
set(hdl2,'Enable','off')
set(hdl4,'Enable','off')
end
if formato == PSATMDL
set(hdlp,'Enable','on')
set(hdlp,'Visible','on')
else
set(hdlp,'Enable','off')
set(hdlp,'Visible','off')
end
a = imread([Path.images,'logo_',file,'.jpg'],'jpg');
[yl,xl,zl] = size(a);
set(Fig.dir,'Units','pixels')
figdim = get(Fig.dir,'Position');
% the following if-block is needed for some issues on Matlab R2008a
if figdim(3) < 1
if strcmp(get(0,'Units'),'pixels')
ssize = get(0,'ScreenSize');
figdim(3) = ssize(3)*figdim(3);
figdim(4) = ssize(4)*figdim(4);
else
set(0,'Units','pixels')
ssize = get(0,'ScreenSize');
figdim(3) = ssize(3)*figdim(3);
figdim(4) = ssize(4)*figdim(4);
end
end
set(Fig.dir,'Units','normalized')
dimx = figdim(3)*0.2616;
dimy = figdim(4)*0.3468;
rl = xl/yl;
if dimx > xl && dimy > yl
xd = xl/figdim(3);
yd = yl/figdim(4);
set(hdla,'Position',[0.8358-xd/2, 0.5722-yd/2, xd, yd]);
elseif xl > yl
xd = 0.2616;
yd = 0.3468/rl;
set(hdla,'Position',[0.7050, 0.5722-0.1734/rl, xd, yd]);
else
xd = 0.2616*rl;
yd = 0.3468;
set(hdla,'Position',[0.8358-0.1308*rl, 0.3988, xd, yd]);
end
xd = round(xd*figdim(3));
yd = round(yd*figdim(4));
%disp([xl yl xd yd])
if xd ~= xl && yd ~= yl
try
if Settings.hostver >= 7.04
a = imresize(a,[yd xd],'bilinear');
else
a = imresize(a,[yd xd],'bilinear',11);
end
catch
% imresize is not available!!!
end
end
set(hdla,'XLim',[0.5 xd+0.5],'YLim',[0.5 yd+0.5]);
if Settings.hostver < 8.04
if length(get(hdla,'Children')) > 1
h2 = image( ...
'Parent',hdla, ...
'CData',a, ...
'Erase','none', ...
'Tag','Axes1Image1', ...
'XData',[1 xd], ...
'YData',[1 yd]);
else
set(get(hdla,'Children'),'CData',a,'XData',[1 xd],'YData',[1 yd]);
end
else
if length(get(hdla,'Children')) > 1
set(hdla, 'XDir', 'reverse');
h2 = image( ...
'Parent',hdla, ...
'CData',flipud(a), ...
'Erase','none', ...
'Tag','Axes1Image1', ...
'XData',[1 xd], ...
'YData',[1 yd]);
else
set(hdla, 'XDir', 'reverse');
set(get(hdla,'Children'), ...
'CData',flipud(a), ...
'XData',[1 xd], ...
'YData',[1 yd])
end
end
set(hdla,'XTick',[],'XTickLabel','','XColor',Theme.color01);
set(hdla,'YTick',[],'YTickLabel','','YColor',Theme.color01);
if ispc, set(hdla,'XColor',[126 157 185]/255,'YColor',[126 157 185]/255), end
if isempty(cfile), cfile = 'empty'; else, cfile = sort(cfile); end
set(hdl,'ListboxTop',1,'String',cfile,'Value',1);
Settings.format = formato;
%==================================================================
case 'editinit'
if ~isempty(Path.temp)
try
cd(Path.temp);
catch
% nothing to do
end
elseif ~isempty(Path.data)
try
cd(Path.data);
catch
% nothing to do
end
end
set(gcbo,'String',pwd)
set(gcf,'UserData',pwd);
%==================================================================
case 'dirinit'
devices = getdevices;
devices{end+1,1} = '[ * DATA * ]';
devices{end+1,1} = '[ * PERT * ]';
devices{end+1,1} = '[ * LOCAL * ]';
devices{end+1,1} = '[ * PSAT * ]';
set(gcbo,'UserData',devices)
cd(get(gcf,'UserData'))
a = dir;
numdir = find([a.isdir] == 1);
if isempty(numdir)
cdir = {' '};
else
cdir = {a(numdir).name}';
cdir(strmatch('.',cdir)) = [];
cdir(strmatch('@',cdir)) = [];
end
set(findobj(Fig.dir,'Tag','Listbox1'),'ListboxTop',1, ...
'String',[{'.';'..'}; cdir; devices],'Value',1);
%==================================================================
case 'dirsel'
%values = get(gcbo,'Value');
%set(gcbo,'Value',values(end));
if strcmp(get(Fig.dir,'SelectionType'),'open')
cd(Path.local)
fm_dirset('changedir');
end
%==================================================================
case 'diredit'
hdl = findobj(Fig.dir,'Tag','EditText1');
cartella = get(hdl,'String');
try
cd(cartella);
hdl = findobj(Fig.dir,'Tag','Listbox1');
a = dir;
cdir = {'.';'..'};
numdir = find([a.isdir] == 1);
j = 2;
for i = 1:length(numdir)
if ~strcmp(a(numdir(i)).name(1),'.') && isunix
j = j + 1;
cdir{j,1} = a(numdir(i)).name;
end
end
if isempty(cdir),
cdir = ' ';
else,
cdir = sort(cdir);
end
set(hdl,'ListboxTop',1,'String',[cdir;get(hdl,'UserData')],'Value',1);
hdl = findobj(Fig.dir,'Tag','Listbox2');
cfile = uform(formato);
if isempty(cfile),
cfile = 'empty';
else,
cfile = sort(cfile);
end
set(hdl,'ListboxTop',1,'String',cfile,'Value',1);
set(Fig.dir,'UserData',cartella);
catch
fm_disp(lasterr,2)
set(hdl_dir,'String',get(Fig.dir,'UserData'));
end
%==================================================================
case 'getfolder'
pathname = get(Fig.dir,'UserData');
cartella = uigetdir(pathname);
if cartella
hdl = findobj(Fig.dir,'Tag','EditText1');
set(hdl,'String',cartella);
cd(Path.local)
fm_dirset('diredit');
end
%==================================================================
case 'convert'
hdl = findobj(Fig.dir,'Tag','Listbox2');
numfile = get(hdl,'Value');
nomefile = get(hdl,'String');
if ~iscell(nomefile),
nomefile = cellstr(nomefile);
end
hdl = findobj(Fig.dir,'Tag','PopupMenu1');
if numfile == 1 && strcmp(nomefile{1},'empty')
fm_disp('Current folder does not contain files in the selected format.',2)
cd(Path.local)
return
end
% if coverting a PSAT file, get destination format
hdlpsat = findobj(Fig.dir,'Tag','Checkbox2');
convpsat = get(hdlpsat,'Value');
for i = 1:length(numfile)
lasterr('');
filename = nomefile{numfile(i),1};
check = 0;
switch get(hdl,'Value')
case IEEE
check = fm_perl('IEEE CDF','ieee2psat',filename);
case CYME
check = fm_perl('CYME','cyme2psat',filename);
case MATPOWER
check = matpower2psat(filename,pwd);
case PSAT
switch convpsat
case 1, check = psat2ieee(filename,pwd);
case 2, check = psat2epri(filename,pwd);
case 3, check = psat2odm(filename,pwd);
end
case PSATMDL
first = double(filename(1));
if first <= 57 && first >= 48
copyfile(filename,['d',filename])
filename = ['d',filename];
fm_disp(['Use modified file name <',filename,'>'])
end
check = sim2psat(filename,pwd);
case PSATPERT
fm_disp('No filter is associated with pertubation files.')
case PST
check = pst2psat(filename,pwd);
case EPRI
check = fm_perl('WSCC','epri2psat',filename);
case PSSE
check = fm_perl('PSS/E','psse2psat',filename);
case PSAP
check = fm_perl('PSAP','psap2psat',filename);
case EUROSTAG
check = fm_perl('EUROSTAG','eurostag2psat',filename);
case TH,
check = fm_perl('TH','th2psat',filename);
case CESI,
check = fm_perl('CESI','inptc12psat',filename);
case VST
check = fm_perl('VST','vst2psat',filename);
case SIMPOW
check = fm_perl('SIMPOW','simpow2psat',filename);
case NEPLAN
check = fm_perl('NEPLAN','neplan2psat',filename);
case DIGSILENT
check = fm_perl('DIGSILENT','digsilent2psat',filename);
case POWERWORLD
check = fm_perl('PowerWorld','pwrworld2psat',filename);
case PET
fm_choice('Filter for PET data format has not been implemeted yet',2)
break
case FLOWDEMO
check = fm_perl('FlowDemo.net','flowdemo2psat',filename);
case GEEPC
check = fm_perl('GE','ge2psat',filename);
case CHAPMAN
check = fm_perl('Chapman','chapman2psat',filename);
case UCTE
check = fm_perl('UCTE','ucte2psat',filename);
case PCFLO
check = fm_perl('PCFLO','pcflo2psat',filename);
case WEBFLOW
check = fm_perl('WebFlow','webflow2psat',filename);
case CEPEL
check = fm_perl('CEPEL','cepel2psat',filename);
case ODM
check = fm_perl('ODM','odm2psat',filename);
case REDS
check = fm_perl('REDS','reds2psat',filename);
case IPSS
if ~isempty(strfind(filename,'.ipssdat'))
check = fm_perl('InterPSS','ipssdat2psat',filename);
else
check = fm_perl('InterPSS','ipss2psat',filename);
end
case VITRUVIO % All files
fm_disp('Select a Data Format for running the conversion.')
end
if ~check && ~isempty(lasterr), fm_disp(lasterr), end
end
if nargout, varargout{1} = check; end
%==================================================================
case 'openfile'
global File
Path.temp = 0;
File.temp = '';
hdl = findobj(Fig.dir,'Tag','Listbox2');
numfile = get(hdl,'Value');
nomefile = get(hdl,'String');
if ~iscell(nomefile),
nomefile = cellstr(nomefile);
end
if numfile == 1 && strcmp(nomefile{1},'empty')
fm_disp('Current folder does not contain files in the selected data format.',2)
cd(Path.local)
close(Fig.dir)
return
end
hdl = findobj(Fig.dir,'Tag','PopupMenu1');
type = get(hdl,'Value');
if type == PSAT || type == PSATPERT || type == VITRUVIO
check = 1;
else
cd(Path.local)
check = fm_dirset('convert');
end
if ~check
fm_disp('Data conversion failed.',2)
return
end
% determine file name
namefile = nomefile{numfile};
switch type
case {PSAT,PSATPERT,PSATMDL,VITRUVIO}
% nothing to do!
case PCFLO
namefile = regexprep([namefile,'.m'],'^bdat\.','','ignorecase');
namefile = regexprep(['d_',namefile],'^d*_*','d_');
namefile = regexprep(namefile,'[^\w\.]','_');
case PST
namefile = strrep(namefile,'.m','_pst.m');
if ~strcmp(namefile(1), 'd'); namefile = ['d_',namefile]; end
case MATPOWER
extension = findstr(namefile,'.');
namefile = ['d_',namefile(1:extension(end)-1),'.m'];
otherwise
namefile = regexprep(['d_',namefile],'^d*_*','d_');
namefile = regexprep(namefile,'^d_d','d_');
namefile = regexprep(namefile,'^d__','d_');
namefile = regexprep(namefile,'[^\w\.]','_');
namefile = regexprep(namefile,'\..+$','.m');
end
Path.temp = get(Fig.dir,'UserData');
if ~strcmp(Path.temp(end),filesep)
Path.temp = [Path.temp,filesep];
end
File.temp = namefile;
close(Fig.dir)
%==================================================================
case 'cancel'
Path.temp = 0;
File.temp = '';
close(Fig.dir)
%==================================================================
case 'preview'
global File
% check whether the selected file is a Simulink model
hdl = findobj(Fig.dir,'Tag','PopupMenu1');
type = get(hdl,'Value');
if type ~= PSATMDL
cd(Path.local)
return
end
% get the name of the Simulink model
hdl = findobj(Fig.dir,'Tag','Listbox2');
numfile = get(hdl,'Value');
if length(numfile) > 1
numfile = numfile(1);
temp = get(hdl,'String');
namefile = temp{numfile};
else
files = get(hdl,'String');
if iscell(files)
namefile = files{numfile};
else
namefile = files;
end
end
% make sure that the file name does not start with a number
first = double(namefile(1));
if first <= 57 && first >= 48
copyfile(namefile,['d',namefile])
namefile = ['d',namefile];
end
oldpath = Path.data;
oldfile = File.data;
Path.data = pwd;
File.data = [namefile(1:end-4),'(mdl)'];
hdla = findobj(Fig.dir,'Tag','Axes1');
lasterr('')
try
fm_simrep('DrawModel',0,0,0)
catch
disp(' ')
fm_disp('* * * The model likely refers to an old PSAT/Simulink library.')
fm_disp(' Load and update the model before trying to preview it.')
fm_dirset chformat
return
end
%set(hdla,'XLimMode','auto')
%set(hdla,'YLimMode','auto')
x_lim = get(hdla,'XLim');
y_lim = get(hdla,'YLim');
xl = x_lim(2)-x_lim(1);
yl = y_lim(2)-y_lim(1);
set(Fig.dir,'Units','pixels')
figdim = get(Fig.dir,'Position');
set(Fig.dir,'Units','normalized')
dimx = figdim(3)*0.2616;
dimy = figdim(4)*0.3468;
rl = xl/yl;
if dimx > xl && dimy > yl
xd = xl/figdim(3);
yd = yl/figdim(4);
set(hdla,'Position',[0.8358-xd/2, 0.5722-yd/2, xd, yd]);
elseif xl > yl
xd = 0.2616;
yd = 0.3468/rl;
set(hdla,'Position',[0.7050, 0.5722-0.1734/rl, xd, yd]);
else
xd = 0.2616*rl;
yd = 0.3468;
set(hdla,'Position',[0.8358-0.1308*rl, 0.3988, xd, yd]);
end
Path.data = oldpath;
File.data = oldfile;
%==================================================================
case 'view'
hdl = findobj(Fig.dir,'Tag','Listbox2');
numfile = get(hdl,'Value');
nomefile = get(hdl,'String');
if ~iscell(nomefile), nomefile = cellstr(nomefile); end
if strcmp(nomefile{1},'empty')
fm_disp('Folder is empty or does not contain files in the selected data format',2)
cd(Path.local)
return
end
for i = 1:length(numfile)
ext = lower(nomefile{numfile(i),1}(end-2:end));
idx = findstr(ext,'.');
if ~isempty(idx)
ext = ext(idx(end)+1:end);
end
file = nomefile{numfile(i),1};
try
switch ext
case 'mdl'
open_system(file)
case 'pdf',
switch computer
case 'GLNX86', eval(['! xpdf ',file, ' &']),
case 'PCWIN', eval(['! acroread ',file, ' &'])
otherwise 'SOL2', eval(['! acroread ',file, ' &'])
end
case '.ps'
switch computer
case 'GLNX86', eval(['! gsview ',file, ' &']),
case 'PCWIN', eval(['! gsview ',file, ' &'])
otherwise, eval(['! ghostview ',file, ' &'])
end
case 'eps'
switch computer
case 'GLNX86', eval(['! gsview ',file, ' &']),
case 'PCWIN', eval(['! gsview ',file, ' &'])
otherwise, eval(['! ghostview ',file, ' &'])
end
case 'doc'
switch computer
case 'GLNX86', eval(['! AbiWord ',file, ' &']),
case 'PCWIN', eval(['! WINWORD ',file, ' &'])
otherwise, fm_disp('Unknown viewer on this platform for file "',file,'"')
end
case 'ppt'
switch computer
case 'GLNX86', eval(['! AbiWord ',file, ' &']),
case 'PCWIN', eval(['! POWERPNT ',file, ' &'])
otherwise, fm_disp('Unknown viewer on this platform for file "',file,'"')
end
case 'dvi'
switch computer
case 'GLNX86', eval(['! xdvi ',file, ' &']),
case 'PCWIN', fm_disp('Unknown viewer on this platform for file "',file,'"')
otherwise, eval(['! xdvi ',file, ' &'])
end
case 'jpg', fm_iview(file)
case 'tif', fm_iview(file)
case 'gif', fm_iview(file)
case 'bmp', fm_iview(file)
case 'png', fm_iview(file)
case 'hdf', fm_iview(file)
case 'pcx', fm_iview(file)
case 'xwd', fm_iview(file)
case 'ico', fm_iview(file)
case 'cur', fm_iview(file)
otherwise, fm_text(13,file)
end
catch
fm_disp(['Error in opeining file "',file,'": ',lasterr])
end
end
end
cd(Path.local)
%===================================================================
function cfile = uform(formato)
% codes
IEEE = 1;
PSAT = 2;
PSATPERT = 3;
PSATMDL = 4;
CYME = 5;
MATPOWER = 6;
PST = 7;
EPRI = 8;
PSSE = 9;
PSAP = 10;
EUROSTAG = 11;
TH = 12;
CESI = 13;
VST = 14;
SIMPOW = 15;
NEPLAN = 16;
DIGSILENT = 17;
POWERWORLD = 18;
PET = 19;
FLOWDEMO = 20;
GEEPC = 21;
CHAPMAN = 22;
UCTE = 23;
PCFLO = 24;
WEBFLOW = 25;
IPSS = 26;
CEPEL = 27;
ODM = 28;
REDS = 29;
VITRUVIO = 30; % all files
a = dir;
numfile = find([a.isdir] == 0);
jfile = 1;
cfile = [];
for i = 1:length(numfile)
nomefile = a(numfile(i)).name;
lfile = length(nomefile);
add_file = 0;
% display(formato)
switch int32(formato)
case IEEE
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'dat') || strcmpi(extent,'txt') || ...
strcmpi(extent,'.cf'),
if isfile(nomefile,'BUS DATA FOLLOW',20)
add_file = 1;
end
end
case CYME
extent1 = nomefile(max(1,lfile-3):lfile);
extent2 = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent1,'.nnd') || strcmpi(extent2,'.sf')
add_file = 1;
end
case MATPOWER
extent = nomefile(lfile);
if strcmpi(extent,'m')
if isfile(nomefile,'baseMVA',5), add_file = 1; end
end
case PSAT
extent = nomefile(lfile);
if strcmpi(extent,'m')
if strcmp(nomefile(1),'d')
add_file = 1;
elseif isfile(nomefile,'Bus.con',50)
add_file = 1;
end
end
case PSATPERT
extent = nomefile(lfile);
if strcmpi(extent,'m')
if strcmp(nomefile(1),'p')
add_file = 1;
elseif isfile(nomefile,'(t)',5)
add_file = 1;
end
end
case PSATMDL
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'mdl')
if strcmpi(nomefile,'fm_lib.mdl')
add_file = 0;
%elseif strcmp(nomefile(1),'d')
% add_file = 1;
%elseif isfile(nomefile,'PSATblock',1000) %% THIS IS TOO SLOW!!
% add_file = 1;
else
add_file = 1;
end
end
case PST
extent = nomefile(lfile);
if strcmpi(extent,'m') && strcmp(nomefile(1),'d')
if isfile(nomefile,'bus = [',50), add_file = 1; end
if ~add_file
if isfile(nomefile,'bus=',50), add_file = 1; end
end
end
case EPRI
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'wsc') || strcmpi(extent,'txt') || ...
strcmpi(extent,'dat')
if isfile(nomefile,'HDG',15)
add_file = 1;
elseif isfile(nomefile,'/NETWORK_DATA\',20)
add_file = 1;
end
end
case PSSE
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'raw'),
fid = fopen(nomefile, 'rt');
sline = fgets(fid);
out = 0;
if isempty(sline), sline = ' 2'; end
if sline == -1; sline = ' 2'; end
if length(sline) == 1; sline = [sline,' ']; end
if isempty(str2num(sline(1:4))), sline = ' 2'; end
if str2num(sline(1:2)) == 0 || str2num(sline(1:2)) == 1
out = 1;
end
if strcmp(sline(1:3),'001'), out = 0; end
count = fclose(fid);
if out, add_file = 1; end
end
case PSAP
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'dat'),
fid = fopen(nomefile, 'rt');
sline = fgets(fid);
count = fclose(fid);
if strfind(sline,'1'), add_file = 1; end
end
case EUROSTAG
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'dat'),
if isfile(nomefile,'HEADER ',20), add_file = 1; end
end
case TH
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'dat'),
if isfile(nomefile,'SYSBASE',50) || ...
isfile(nomefile,'THLINE',50)
add_file = 1;
end
end
case CESI
extent = nomefile(max(1,lfile-2):lfile);
if strcmpi(extent,'dat'),
if isfile(nomefile,'VNOM',25), add_file = 1; end
end
case VST
extent = nomefile(max(1,lfile-7):lfile);
if strcmpi(extent,'_vst.dat'), add_file = 1; end
case SIMPOW
extent = nomefile(max(1,lfile-6):lfile);
%if strcmpi(extent,'.optpow') || strcmpi(extent,'.dynpow')
if strcmpi(extent,'.optpow'), add_file = 1; end
case IPSS
extent1 = nomefile(max(1,lfile-7):lfile);
extent2 = nomefile(max(1,lfile-4):lfile);
if strcmpi(extent1,'.ipssdat') || strcmpi(extent2,'.ipss')
add_file = 1;
end
case NEPLAN
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.ndt'), add_file = 1; end
case ODM
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.odm'), add_file = 1; end
if strcmpi(extent,'.xml')
if isfile(nomefile,'PSSStudyCase',10), add_file = 1; end
end
case DIGSILENT
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.dgs'), add_file = 1; end
case POWERWORLD
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.aux'), add_file = 1; end
case PET
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.pet'), add_file = 1; end
case FLOWDEMO
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.fdn'), add_file = 1; end
case CHAPMAN
if isempty(findstr(nomefile,'.')),
if isfile(nomefile,'SYSTEM',10), add_file = 1; end
end
case UCTE
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.uct'), add_file = 1; end
case REDS
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.pos')
if isfile(nomefile,'.PU',10), add_file = 1; end
end
case PCFLO
if strmatch('bdat.',lower(nomefile)), add_file = 1; end
case WEBFLOW
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.txt')
if isfile(nomefile,'BQ',10)
add_file = 1;
end
end
case CEPEL
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.txt')
if isfile(nomefile,'TITU',5)
add_file = 1;
end
end
case GEEPC
extent = nomefile(max(1,lfile-3):lfile);
if strcmpi(extent,'.epc'), add_file = 1; end
otherwise % all files
% add only files that do not begin with a dot that are
% hidden files on UNIX systems
if ~(strcmp(nomefile(1),'.') && isunix)
add_file = 1;
end
end
if add_file, cfile{jfile,1} = a(numfile(i)).name; jfile = jfile + 1; end
end
%============================================================================
function out = isfile(file,stringa,nrow)
% checking the first nrow to figure out the data format
out = 0;
[fid, message] = fopen(file, 'rt');
if ~isempty(message)
fm_disp(['While inspecting the current folder, ', ...
'error found in file "',file,'". ',message])
return
end
n_row = 0;
while 1
sline = fgets(fid);
n_row = n_row + 1;
if ~isempty(sline), if sline == -1, break; end, end
vec = strfind(sline,stringa);
if ~isempty(vec), out = 1; break, end
if n_row == nrow, break, end
end
count = fclose(fid);
%============================================================================
function devices = getdevices
if isunix
devices = {'/'};
else
devices = {'a:\'};
ndev = 1;
for i = 99:122
device_name = [char(i),':\'];
%if exist(device_name) == 7
if ~isempty(dir(device_name))
ndev = ndev + 1;
devices{ndev,1} = device_name;
end
end
end
%============================================================================
function check = fm_perl(program_name,filter_name,file_name)
global Path Fig
cmd = [Path.filters,filter_name];
% last minute option for certain filters
hdl = findobj(Fig.dir,'Tag','CheckboxSilent');
if ~get(hdl,'Value')
switch program_name
case 'CESI'
[add_file,add_path] = uigetfile('*.dat','Select COLAS ADD file');
if strcmp(add_path,[pwd,filesep])
file_name = ['-a" "',add_file,'" "',file_name];
elseif add_path == 0
% no COLAS ADD file
else
% COLAS ADD file is not in the current folder
fm_disp(['* * COLAS ADD file must be in the same folder as base ' ...
'data file.'])
end
case 'NEPLAN'
[add_file,add_path] = uigetfile('*.edt','Select EDT file');
if strcmp(add_path,[pwd,filesep])
file_name = ['-a" "',add_file,'" "',file_name];
elseif add_path == 0
% no NEPLAN EDT file
else
% NEPLAN EDT file is not in the current folder
fm_disp(['* * NEPLAN EDT file must be in the same folder as NDT ' ...
'file.'])
end
case 'SIMPOW'
[add_file,add_path] = uigetfile('*.dynpow','Select DYNPOW file');
if strcmp(add_path,[pwd,filesep])
file_name = [file_name,'" "',add_file];
elseif add_path == 0
% no DYNPOW file
file_name = ['-n" "',file_name];
else
file_name = [file_name,'" "',add_path,filesep,add_file];
end
otherwise
% nothing to do
end
end
% verbose conversion
hdl = findobj(Fig.dir,'Tag','CheckboxVerbose');
if get(hdl,'Value')
file_name = ['-v" "',file_name];
end
if ispc
cmdString = ['"',Path.filters,filter_name,'" "',file_name,'"'];
else
cmdString = [filter_name,' "',file_name,'"'];
end
% Execute Perl script
errTxtNoPerl = 'Unable to find Perl executable.';
if isempty(cmdString)
% nothing to do ...
elseif ispc % PC
perlCmd = fullfile(matlabroot, 'sys\perl\win32\bin\');
cmdString = ['perl ' cmdString];
perlCmd = ['set PATH=',perlCmd, ';%PATH%&' cmdString];
[status, results] = dos(perlCmd);
else % UNIX
[status, perlCmd] = unix('which perl');
if (status == 0)
[status, results] = unix(cmdString);
else
error(errTxtNoPerl);
end
end
fm_disp(results)
check = ~status;
|
github
|
Sinan81/PSAT-master
|
fm_input.m
|
.m
|
PSAT-master/psat-oct/psat/fm_input.m
| 13,124 |
utf_8
|
a4a7b367ecb64f3f86fd6e1ea1f62c27
|
function Answer = fm_input(Prompt, Title, NumLines, DefAns,Resize)
%INPUTDLG Input dialog box.
% Answer = INPUTDLG(Prompt) creates a modal dialog box that returns
% user input for multiple prompts in the cell array Answer. Prompt
% is a cell array containing the Prompt strings.
%
% INPUTDLG uses WAITFOR to suspend execution until the user responds.
%
% Answer = INPUTDLG(Prompt,Title) specifies the Title for the dialog.
%
% Answer = INPUTDLG(Prompt,Title,LineNo) specifies the number of lines
% for each answer in LineNo. LineNo may be a constant value or a
% column vector having one element per Prompt that specifies how many
% lines per input. LineNo may also be a matrix where the first
% column specifies how many rows for the input field and the second
% column specifies how many columns wide the input field should be.
%
% Answer = INPUTDLG(Prompt,Title,LineNo,DefAns) specifies the default
% answer to display for each Prompt. DefAns must contain the same
% number of elements as Prompt and must be a cell array.
%
% Answer = INPUTDLG(Prompt,Title,LineNo,DefAns,AddOpts) specifies whether
% the dialog may be resized or not. Acceptable values for AddOpts are
% 'on' or 'off'. If the dialog can be resized, then the dialog is
% not modal.
%
% AddOpts may also be a data structure with fields Resize,
% WindowStyle and Interpreter. Resize may be 'on' or 'off'.
% WindowStyle may be 'modal' or 'normal' and Interpreter may be
% 'tex' or 'none'. The interpreter applies to the prompt strings.
%
% Examples:
%
% prompt={'Enter the matrix size for x^2:','Enter the colormap name:'};
% def={'20','hsv'};
% dlgTitle='Input for Peaks function';
% lineNo=1;
% answer=fm_input(prompt,dlgTitle,lineNo,def);
%
% AddOpts.Resize='on';
% AddOpts.WindowStyle='normal';
% AddOpts.Interpreter='tex';
% answer=fm_input(prompt,dlgTitle,lineNo,def,AddOpts);
%
% See also TEXTWRAP, QUESTDLG, WAITFOR.
% Loren Dean May 24, 1995.
% Copyright 1998-2001 The MathWorks, Inc.
% $Revision: 1.57 $
%
%Modified by: Federico Milano
%Date: 11-Nov-2002
%Version: 1.0.0
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
global Settings
Black =[0 0 0 ]/255;
LightGray =[192 192 192 ]/255;
LightGray2 =[160 160 164 ]/255;
MediumGray =[128 128 128 ]/255;
White =[255 255 255 ]/255;
%%%%%%%%%%%%%%%%%%%%
%%% Nargin Check %%%
%%%%%%%%%%%%%%%%%%%%
if nargin == 1 && nargout == 0,
if strcmp(Prompt,'InputDlgResizeCB'),
LocalResizeFcn(gcbf)
return
end
end
error(nargchk(1,5,nargin));
if Settings.hostver > 6, error(nargoutchk(1,1,nargout)); end
if nargin==1,
Title=' ';
end
if nargin<=2, NumLines=1;end
if ~iscell(Prompt),
Prompt={Prompt};
end
NumQuest=prod(size(Prompt));
if nargin<=3,
DefAns=cell(NumQuest,1);
for lp=1:NumQuest, DefAns{lp}=''; end
end
WindowStyle='modal';
Interpreter='none';
if nargin<=4,
Resize = 'off';
end
if nargin==5 && isstruct(Resize),
Interpreter=Resize.Interpreter;
WindowStyle=Resize.WindowStyle;
Resize=Resize.Resize;
end
if strcmp(Resize,'on'),
WindowStyle='normal';
end
% Backwards Compatibility
if ischar(NumLines),
warning(['Please see the INPUTDLG help for correct input syntax.' 10 ...
' OKCallback no longer supported.' ]);
NumLines=1;
end
[rw,cl]=size(NumLines);
OneVect = ones(NumQuest,1);
if (rw == 1 && cl == 2)
NumLines=NumLines(OneVect,:);
elseif (rw == 1 && cl == 1)
NumLines=NumLines(OneVect);
elseif (rw == 1 && cl == NumQuest)
NumLines = NumLines';
elseif rw ~= NumQuest || cl > 2,
error('NumLines size is incorrect.')
end
if ~iscell(DefAns),
error('Default Answer must be a cell array in INPUTDLG.');
end
%%%%%%%%%%%%%%%%%%%%%%%
%%% Create InputFig %%%
%%%%%%%%%%%%%%%%%%%%%%%
FigWidth=300;FigHeight=100;
FigPos(3:4)=[FigWidth FigHeight];
FigColor=get(0,'Defaultuicontrolbackgroundcolor');
TextForeground = Black;
if sum(abs(TextForeground - FigColor)) < 1
TextForeground = White;
end
InputFig=dialog( ...
'Visible' ,'off' , ...
'Name' ,Title , ...
'Pointer' ,'arrow' , ...
'Units' ,'points' , ...
'UserData' ,'' , ...
'Tag' ,Title , ...
'HandleVisibility','on' , ...
'Color' ,FigColor , ...
'NextPlot' ,'add' , ...
'WindowStyle' ,WindowStyle, ...
'Resize' ,Resize ...
);
%%%%%%%%%%%%%%%%%%%%%
%%% Set Positions %%%
%%%%%%%%%%%%%%%%%%%%%
DefOffset=5;
SmallOffset=2;
DefBtnWidth=50;
BtnHeight=20;
BtnYOffset=DefOffset;
BtnFontSize=get(0,'FactoryUIControlFontSize');
BtnWidth=DefBtnWidth;
TextInfo.Units ='points' ;
TextInfo.FontSize =BtnFontSize;
TextInfo.HorizontalAlignment='left' ;
TextInfo.HandleVisibility ='callback' ;
StInfo=TextInfo;
StInfo.Style ='text' ;
StInfo.BackgroundColor =FigColor;
StInfo.ForegroundColor =TextForeground ;
TextInfo.VerticalAlignment='bottom';
EdInfo=StInfo;
EdInfo.Style='edit';
EdInfo.BackgroundColor=White;
BtnInfo=StInfo;
BtnInfo.Style='pushbutton';
BtnInfo.HorizontalAlignment='center';
% Determine # of lines for all Prompts
ExtControl=uicontrol(StInfo, ...
'String' ,'' , ...
'Position' ,[DefOffset DefOffset ...
0.96*(FigWidth-2*DefOffset) BtnHeight ...
] , ...
'Visible' ,'off' ...
);
WrapQuest=cell(NumQuest,1);
QuestPos=zeros(NumQuest,4);
for ExtLp=1:NumQuest,
if size(NumLines,2)==2
[WrapQuest{ExtLp},QuestPos(ExtLp,1:4)]= ...
textwrap(ExtControl,Prompt(ExtLp),NumLines(ExtLp,2));
else,
[WrapQuest{ExtLp},QuestPos(ExtLp,1:4)]= ...
textwrap(ExtControl,Prompt(ExtLp),80);
end
end % for ExtLp
delete(ExtControl);
QuestHeight=QuestPos(:,4);
TxtHeight=QuestHeight(1)/size(WrapQuest{1,1},1);
EditHeight=TxtHeight*NumLines(:,1);
EditHeight(NumLines(:,1)==1)=EditHeight(NumLines(:,1)==1)+4;
FigHeight=(NumQuest+2)*DefOffset + ...
BtnHeight+sum(EditHeight) + ...
sum(QuestHeight);
TxtXOffset=DefOffset;
TxtWidth=FigWidth-2*DefOffset;
QuestYOffset=zeros(NumQuest,1);
EditYOffset=zeros(NumQuest,1);
QuestYOffset(1)=FigHeight-DefOffset-QuestHeight(1);
EditYOffset(1)=QuestYOffset(1)-EditHeight(1);% -SmallOffset;
for YOffLp=2:NumQuest,
QuestYOffset(YOffLp)=EditYOffset(YOffLp-1)-QuestHeight(YOffLp)-DefOffset;
EditYOffset(YOffLp)=QuestYOffset(YOffLp)-EditHeight(YOffLp); %-SmallOffset;
end % for YOffLp
QuestHandle=[];
EditHandle=[];
FigWidth =1;
AxesHandle=axes('Parent',InputFig,'Position',[0 0 1 1],'Visible','off');
for lp=1:NumQuest,
QuestTag=['Prompt' num2str(lp)];
EditTag=['Edit' num2str(lp)];
if ~ischar(DefAns{lp}),
delete(InputFig);
error('Default answers must be strings in INPUTDLG.');
end
QuestHandle(lp)=text('Parent',AxesHandle, ...
TextInfo , ...
'Position' ,[ TxtXOffset QuestYOffset(lp)], ...
'String' ,WrapQuest{lp} , ...
'Color' ,TextForeground , ...
'Interpreter',Interpreter , ...
'Tag' ,QuestTag ...
);
EditHandle(lp)=uicontrol(InputFig ,EdInfo , ...
'Max' ,NumLines(lp,1) , ...
'Position' ,[ TxtXOffset EditYOffset(lp) ...
TxtWidth EditHeight(lp) ...
] , ...
'String' ,DefAns{lp} , ...
'Tag' ,QuestTag ...
);
if size(NumLines,2) == 2,
set(EditHandle(lp),'String',char(ones(1,NumLines(lp,2))*'x'));
Extent = get(EditHandle(lp),'Extent');
NewPos = [TxtXOffset EditYOffset(lp) Extent(3) EditHeight(lp) ];
NewPos1= [TxtXOffset QuestYOffset(lp)];
set(EditHandle(lp),'Position',NewPos,'String',DefAns{lp})
set(QuestHandle(lp),'Position',NewPos1)
FigWidth=max(FigWidth,Extent(3)+2*DefOffset);
else
FigWidth=max(175,TxtWidth+2*DefOffset);
end
end % for lp
FigPos=get(InputFig,'Position');
Temp=get(0,'Units');
set(0,'Units','points');
ScreenSize=get(0,'ScreenSize');
set(0,'Units',Temp);
FigWidth=max(FigWidth,2*(BtnWidth+DefOffset)+DefOffset);
FigPos(1)=(ScreenSize(3)-FigWidth)/2;
FigPos(2)=(ScreenSize(4)-FigHeight)/2;
FigPos(3)=FigWidth;
FigPos(4)=FigHeight;
set(InputFig,'Position',FigPos);
CBString='set(gcbf,''UserData'',''Cancel'');uiresume';
CancelHandle=uicontrol(InputFig , ...
BtnInfo , ...
'Position' ,[FigWidth-BtnWidth-DefOffset DefOffset ...
BtnWidth BtnHeight ...
] , ...
'String' ,'Cancel' , ...
'Callback' ,CBString , ...
'Tag' ,'Cancel' ...
);
CBString='set(gcbf,''UserData'',''OK'');uiresume';
OKHandle=uicontrol(InputFig , ...
BtnInfo , ...
'Position' ,[ FigWidth-2*BtnWidth-2*DefOffset DefOffset ...
BtnWidth BtnHeight ...
] , ...
'String' ,'OK' , ...
'Callback' ,CBString , ...
'Tag' ,'OK' ...
);
Data.OKHandle = OKHandle;
Data.CancelHandle = CancelHandle;
Data.EditHandles = EditHandle;
Data.QuestHandles = QuestHandle;
Data.LineInfo = NumLines;
Data.ButtonWidth = BtnWidth;
Data.ButtonHeight = BtnHeight;
Data.EditHeight = TxtHeight+4;
Data.Offset = DefOffset;
set(InputFig ,'Visible','on','UserData',Data);
% This drawnow is a hack to work around a bug
drawnow
set(findall(InputFig),'Units','normalized','HandleVisibility','callback');
set(InputFig,'Units','points')
try
uiwait(InputFig);
catch
delete(InputFig);
end
TempHide=get(0,'ShowHiddenHandles');
set(0,'ShowHiddenHandles','on');
if any(get(0,'Children')==InputFig),
Answer={};
if strcmp(get(InputFig,'UserData'),'OK'),
Answer=cell(NumQuest,1);
for lp=1:NumQuest,
Answer(lp)=get(EditHandle(lp),{'String'});
end % for
end % if strcmp
delete(InputFig);
else,
Answer={};
end % if any
set(0,'ShowHiddenHandles',TempHide);
function LocalResizeFcn(FigHandle)
Data=get(FigHandle,'UserData');
%Data.ButtonHandles = [ OKHandles CancelHandle];
%Data.EditHandles = EditHandle;
%Data.QuestHandles = QuestHandle;
%Data.LineInfo = NumLines;
%Data.ButtonWidth = BtnWidth;
%Data.ButtonHeight = BtnHeight;
%Data.EditHeight = TxtHeight;
set(findall(FigHandle),'Units','points');
FigPos = get(FigHandle,'Position');
FigWidth = FigPos(3); FigHeight = FigPos(4);
OKPos = [ FigWidth-Data.ButtonWidth-Data.Offset Data.Offset ...
Data.ButtonWidth Data.ButtonHeight ];
CancelPos =[Data.Offset Data.Offset Data.ButtonWidth Data.ButtonHeight];
set(Data.OKHandle,'Position',OKPos);
set(Data.CancelHandle,'Position',CancelPos);
% Determine the height of all question fields
YPos = sum(OKPos(1,[2 4]))+Data.Offset;
QuestPos = get(Data.QuestHandles,{'Extent'});
QuestPos = cat(1,QuestPos{:});
QuestPos(:,1) = Data.Offset;
RemainingFigHeight = FigHeight - YPos - sum(QuestPos(:,4)) - ...
Data.Offset - size(Data.LineInfo,1)*Data.Offset;
Num1Liners = length(find(Data.LineInfo(:,1)==1));
RemainingFigHeight = RemainingFigHeight - ...
Num1Liners*Data.EditHeight;
Not1Liners = find(Data.LineInfo(:,1)~=1);
%Scale the 1 liner heights appropriately with remaining fig height
TotalLines = sum(Data.LineInfo(Not1Liners,1));
% Loop over each quest/text pair
for lp = 1:length(Data.QuestHandles),
CurPos = get(Data.EditHandles(lp),'Position');
NewPos = [Data.Offset YPos CurPos(3) Data.EditHeight ];
if Data.LineInfo(lp,1) ~= 1,
NewPos(4) = RemainingFigHeight*Data.NumLines(lp,1)/TotalLines;
end
set(Data.EditHandles(lp),'Position',NewPos)
YPos = sum(NewPos(1,[2 4]));
QuestPos(lp,2) = YPos;QuestPos(lp,3) = NewPos(3);
set(Data.QuestHandles(lp),'Position',QuestPos(lp,:));
YPos = sum(QuestPos(lp,[2 4]))+Data.Offset;
end
if YPos>FigHeight - Data.Offset,
FigHeight = YPos+Data.Offset;
FigPos(4)=FigHeight;
set(FigHandle,'Position',FigPos);
drawnow
end
set(FigHandle,'ResizeFcn','fm_input InputDlgResizeCB');
set(findall(FigHandle),'Units','normalized')
|
github
|
Sinan81/PSAT-master
|
zbuildpi.m
|
.m
|
PSAT-master/psat-oct/psat/zbuildpi.m
| 3,207 |
utf_8
|
77e32ffc8651729d7ba2a3fb4c88cb6c
|
% This program forms the complex bus impedance matrix by the method
% of building algorithm. Bus zero is taken as reference.
% This program is compatible with power flow data.
% Copyright (C) 1998 by H. Saadat.
function [Zbus, linedata] = zbuildpi(linedata, gendata, yload)
% gendata generator data syn.con
ng = length(gendata(:,1));
nlg = gendata(:,1);
nrg = zeros(size(gendata(:,1)));
zg = gendata(:,7) + j*gendata(:,6);
nl = linedata(:,1);
nr = linedata(:,2);
R = linedata(:,8);
X = linedata(:,9);
ZB = R + j*X;
nbr = length(linedata(:,1));
nbus = max(max(nl), max(nr));
nc = length(linedata(1,:));
BC = 0.5*linedata(:,10);
yc = zeros(nbus,1);
nlc = zeros(nbus,1);
nrc = zeros(nbus,1);
for n = 1:nbus
yc(n) = 0;
nlc(n) = 0;
nrc(n) = n;
for k = 1:nbr
if nl(k) == n || nr(k) == n
yc(n) = yc(n) + j*BC(k);
end
end
end
if exist('yload') == 1
yload = yload.';
yc = yc + yload;
end
m = 0;
havecc = 0; % have cc ?
for n = 1:nbus
if abs(yc(n)) ~=0
m = m + 1;
nlcc(m) = nlc(n);
nrcc(m) = nrc(n);
zc(m) = 1/yc(n);
havecc = 1;
end
end
if havecc == 1
nlcc = nlcc';
nrcc = nrcc';
zc = zc.';
nl = [nlg; nlcc; nl];
nr = [nrg; nrcc; nr];
ZB = [zg; zc; ZB];
else
nl = [nlg; nl];
nr = [nrg; nr];
ZB = [zg; ZB];
end
% standard line data consist of line generator capacitor of line model and load
linedata = [nl nr real(ZB) imag(ZB)];
nbr = length(nl);
Zbus = zeros(nbus, nbus);
tree = 0; %%%%new
% Adding a branch from a new bus to reference bus 0
for I = 1:nbr
ntree(I) = 1;
if nl(I) == 0 || nr(I) == 0
if nl(I) == 0
n = nr(I);
elseif nr(I) == 0
n = nl(I);
end
if abs(Zbus(n, n)) == 0
Zbus(n,n) = ZB(I);
tree = tree+1; %%new
else
Zbus(n,n) = Zbus(n,n)*ZB(I)/(Zbus(n,n) + ZB(I));
end
ntree(I) = 2;
end
end
% Adding a branch from new bus to an existing bus
while tree < nbus %%% new
for n = 1:nbus
nadd = 1;
if abs(Zbus(n,n)) == 0
for I = 1:nbr
if nadd == 1
if nl(I) == n || nr(I) == n
if nl(I) == n
k = nr(I);
elseif nr(I) == n
k = nl(I);
end
if abs(Zbus(k,k)) ~= 0
for m = 1:nbus
if m ~= n
Zbus(m,n) = Zbus(m,k);
Zbus(n,m) = Zbus(m,k);
end
end
Zbus(n,n) = Zbus(k,k) + ZB(I);
tree=tree+1; %%new
nadd = 2;
ntree(I) = 2;
end
end
end
end
end
end
end %%%%%%new
% Adding a link between two old buses
for n = 1:nbus
for I = 1:nbr
if ntree(I) == 1
if nl(I) == n || nr(I) == n
if nl(I) == n
k = nr(I);
elseif nr(I) == n
k = nl(I);
end
DM = Zbus(n,n) + Zbus(k,k) + ZB(I) - 2*Zbus(n,k);
for jj = 1:nbus
AP = Zbus(jj,n) - Zbus(jj,k);
for kk = 1:nbus
AT = Zbus(n,kk) - Zbus(k, kk);
DELZ(jj,kk) = AP*AT/DM;
end
end
Zbus = Zbus - DELZ;
ntree(I) = 2;
end
end
end
end
disp('end of zbus build')
|
github
|
Sinan81/PSAT-master
|
fm_gams.m
|
.m
|
PSAT-master/psat-oct/psat/fm_gams.m
| 45,016 |
utf_8
|
37a2129685b6794bad0fe98843d008ce
|
function fm_gams
% FM_GAMS initialize and call GAMS to solve
% several kind of Market Clearing Mechanisms
%
% FM_GAMS
%
%GAMS settings are stored in the structure GAMS, with
%the following fields:
%
% METHOD 1 -> simple auction
% 2 -> linear OPF (DC power flow)
% 3 -> nonlinear OPF (AC power flow)
% 4 -> nonlinear VSC-OPF
% 5 -> maximum loading condition
% 6 -> continuation OPF
%
% TYPE 1 -> single period auction
% 2 -> multi period auction
% 3 -> VSC single period auction
% 4 -> VSC multi period auction
%
%see also FM_GAMS.GMS, FM_GAMSFIG and
%structures CPF and OPF for futher settings
%
%Author: Federico Milano
%Date: 29-Jan-2003
%Update: 01-Feb-2003
%Update: 06-Feb-2003
%Version: 1.0.2
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2019 Federico Milano
global DAE OPF CPF GAMS Bus File clpsat
global Path Settings Snapshot Varname
global PV PQ SW Line Shunt jay Varout
global Supply Demand Rmpl Rmpg Ypdp
[u,w] = system('gams');
if u
fm_disp('GAMS is not properly installed on your system.',2)
return
end
if ~autorun('PSAT-GAMS Interface',0)
return
end
if DAE.n
fm_disp(['Dynamic data are not supported within the PSAT-GAMS interface.'],2)
return
end
if ~Supply.n,
fm_disp(['Supply data have to be specified before in order to ', ...
'run PSAT-GAMS interface'],2)
return
end
if ~Demand.n,
if GAMS.basepg && ~clpsat.init
Settings.ok = 0;
uiwait(fm_choice(['Exclude (recommended) base generator powers?']))
GAMS.basepg = ~Settings.ok;
end
noDem = 1;
Demand = add_demand(Demand,'dummy');
else
noDem = 0;
end
length(Snapshot.y);
if ~GAMS.basepl
buspl = Snapshot(1).Pl;
busql = Snapshot(1).Ql;
Bus.Pl(:) = 0;
Bus.Ql(:) = 0;
PQ = pqzero_pq(PQ,'all');
end
if ~GAMS.basepg
ploss = Snapshot(1).Ploss;
Snapshot(1).Ploss = 0;
buspg = Snapshot(1).Pg;
busqg = Snapshot(1).Qg;
Bus.Pg(:) = 0;
Bus.Qg(:) = 0;
SW = swzero_sw(SW,'all');
PV = pvzero_pv(PV,'all');
end
fm_disp
fm_disp('---------------------------------------------------------')
fm_disp(' PSAT-GAMS Interface')
fm_disp('---------------------------------------------------------')
fm_disp
tic
method = GAMS.method;
modelstat = 0;
solvestat = 0;
type = GAMS.type;
omega = GAMS.omega;
if GAMS.method == 6 && GAMS.type ~= 1
fm_disp(['WARNING: Continuation OPF can be run only with Single' ...
' Period Auctions.'])
fm_disp('Voltage Stability Constrained OPF will be solved.')
method = 4;
end
if GAMS.method == 6 && GAMS.flow ~= 1
fm_disp(['WARNING: Continuation OPF can be run only with Current ' ...
'Limits.'])
fm_disp('Current limits in transmission lines will be used.')
GAMS.flow = 1;
end
if GAMS.type == 3 && GAMS.method ~= 4
fm_disp(['WARNING: Pareto Set Single Period Auction can be run ' ...
'only for VSC-OPF.'])
fm_disp( ' Single Period Auction will be solved.')
fm_disp
type = 1;
end
if GAMS.type == 3 && length(GAMS.omega) == 1
fm_disp(['WARNING: Weighting factor is scalar. ', ...
'Single Period Auction will be solved.'])
fm_disp
type = 1;
end
if GAMS.type == 1 && length(GAMS.omega) > 1
fm_disp(['WARNING: Weighting factor is a vector. ', ...
'First omega entry will be used.'])
fm_disp
omega = omega(1);
end
if ~rem(GAMS.type,2) && ~Rmpg.n
type = 1;
fm_disp(['WARNING: No Ramping data were found. ', ...
'Single Period Auction will be solved.'])
fm_disp
end
if GAMS.type == 2 && Rmpg.n && ~Ypdp.n
type = 4;
fm_disp(['WARNING: No Power Demand Profile was found. Single ' ...
'Period Auction with Unit Commitment will be solved.'])
fm_disp
end
% resetting time vector in case of previous time simulations
if type == 3, Varout.t = []; end
switch method
case 1, fm_disp(' Simple Auction')
case 2, fm_disp(' Market Clearing Mechanism')
case 3, fm_disp(' Standard OPF')
case 4, fm_disp(' Voltage Stability Constrained OPF')
case 5, fm_disp(' Maximum Loading Condition')
case 6, fm_disp(' Continuation OPF')
case 7, fm_disp(' Congestion Management')
end
switch type
case 1, fm_disp(' Single-Period Auction')
case 2, fm_disp(' Multi-Period Auction')
case 3, fm_disp(' Pareto Set Single-Period Auction')
case 4, fm_disp(' Single-Period Auction with Unit Commitment')
end
if (GAMS.flatstart || isempty(Snapshot)) && GAMS.method > 2
DAE.y(Bus.a) = getzeros_bus(Bus);
DAE.y(Bus.v) = getones_bus(Bus);
else
DAE.y = Snapshot(1).y;
end
% ------------------------------------------------------------
% Parameter definition
% ------------------------------------------------------------
% dimensions
nBus = int2str(Bus.n);
nQg = int2str(PV.n+SW.n);
nBusref = int2str(SW.refbus);
[nSW,SW_idx,ksw] = gams_sw(SW);
[nPV,PV_idx,kpv] = gams_pv(PV);
[nLine,L,Li,Lj,Gh,Bh,Ghc,Bhc] = gams_line(Line,method);
[Gh,Bh,Ghc,Bhc] = gams_shunt(Shunt,method,Gh,Bh,Ghc,Bhc);
[nPd,Pd_idx,D] = gams_demand(Demand);
[nPs,Ps_idx,S] = gams_supply(Supply,type);
[nH,Ch] = gams_ypdp(Ypdp,type);
% indexes
iBPs = Supply.bus;
iBPd = Demand.bus;
iBQg = [SW.bus; PV.bus];
% Fixed powers
Pg0 = Bus.Pg;
Pl0 = Bus.Pl;
Ql0 = Bus.Ql;
% Generator reactive powers and associated limits
Qg0 = getzeros_bus(Bus);
Qg0(iBQg) = Bus.Qg(iBQg);
[Qgmax,Qgmin] = fm_qlim('all');
% Voltage limits
V0 = DAE.y(Bus.v);
t0 = DAE.y(Bus.a);
[Vmax,Vmin] = fm_vlim(1.5,0.2);
% ------------------------------------------------------------
% Data structures
% ------------------------------------------------------------
X.val = [V0,t0,Pg0,Qg0,Pl0,Ql0,Qgmax,Qgmin,Vmax,Vmin,ksw,kpv];
lambda.val = [GAMS.lmin(1),GAMS.lmax(1),GAMS.omega(1),GAMS.line];
X.labels = {cellstr(num2str(Bus.a)), ...
{'V0','t0','Pg0','Qg0','Pl0','Ql0', ...
'Qgmax','Qgmin','Vmax','Vmin','ksw','kpv'}};
lambda.labels = {'lmin','lmax','omega','line'};
X.name = 'X';
lambda.name = 'lambda';
% ------------------------------------------------------------
% Launch GAMS solver
% ------------------------------------------------------------
control = int2str(method);
flow = int2str(GAMS.flow);
currentpath = pwd;
file = 'fm_gams';
if ~rem(type,2)
file = [file,'2'];
end
if GAMS.libinclude
file = [file,' ',GAMS.ldir];
end
if clpsat.init || ispc, cd(Path.psat), end
switch control
% ------------------------------------------------------------------
case '1' % S I M P L E A U C T I O N
% ------------------------------------------------------------------
if type == 1 % Single Period Auction
[Ps,Pd,MCP,modelstat,solvestat] = psatgams(file,nBus,nLine,nPs,nPd,nSW,nPV, ...
nBusref,control,flow,S,D,X);
[Pij,Pji,Qg] = updatePF(Pd,Ps,iBQg);
elseif ~rem(type,2) % Single/Multi Period Auction with UC
[Ps,Pd,MCP,modelstat,solvestat] = psatgams(file,nBus,nLine,nPs,nPd,nSW,nPV, ...
nBusref,nH,control,flow,S,D,X,Ch);
numh = size(MCP,1);
a = zeros(numh,Bus.n);
V = zeros(numh,Bus.n);
Qg = zeros(numh,Bus.n);
Pij = zeros(numh,Line.n);
Qij = zeros(numh,Line.n);
for i = 1:numh
[Piji,Pjii,Qgi] = updatePF(Pd(i,:)',Ps(i,:)',iBQg);
a(i,:) = [DAE.y(Bus.a)]';
V(i,:) = [DAE.y(Bus.v)]';
Pij(i,:) = Piji';
Pji(i,:) = Pjii';
Qg(i,iBQg) = Qgi';
end
ro = MCP*ones(1,Bus.n);
end
% ------------------------------------------------------------------
case '2' % M A R K E T C L E A R I N G M E C H A N I S M
% ------------------------------------------------------------------
if type == 1 % Single Period Auction
[Ps,Pd,MCP,modelstat,solvestat] = psatgams(file,nBus, ...
nLine,nPs,nPd,nSW,nPV,nBusref,control, ...
flow,Gh,Bh,Li,Lj,Ps_idx,Pd_idx,SW_idx,PV_idx, ...
S,D,X,L);
[Pij,Pji,Qg] = updatePF(Pd,Ps,iBQg);
elseif ~rem(type,2) % Single/Multi Period Auction with UC
[Ps,Pd,MCP,modelstat,solvestat] = psatgams(file,nBus, ...
nLine,nPs,nPd,nSW,nPV,nBusref,nH,control, ...
flow,Gh,Bh,Li,Lj,Ps_idx,Pd_idx,SW_idx,PV_idx, ...
S,D,X,L,Ch);
numh = size(MCP,1);
a = zeros(numh,Bus.n);
V = zeros(numh,Bus.n);
Qg = zeros(numh,Bus.n);
Pij = zeros(numh,Line.n);
Qij = zeros(numh,Line.n);
for i = 1:numh
[Piji,Pjii,Qgi] = updatePF(Pd(i,:)',Ps(i,:)',iBQg);
a(i,:) = [DAE.y(Bus.a)]';
V(i,:) = [DAE.y(Bus.v)]';
Pij(i,:) = Piji';
Pji(i,:) = Pjii';
Qg(i,iBQg) = Qgi';
end
ro = MCP;
end
% ------------------------------------------------------------------
case '3' % S T A N D A R D O P T I M A L P O W E R F L O W
% ------------------------------------------------------------------
if type == 1 % Single Period Auction
[Ps,Pd,V,a,Qg,ro,Pij,Pji,mV,mFij,mFji,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nSW,nPV,nBusref,control, ...
flow,Gh,Bh,Li,Lj,Ps_idx,Pd_idx,S,D,X,L);
NCP = compNCP(V,a,mV,mFij,mFji);
elseif ~rem(type,2) % Single/Multi Period Auction with UC
[Ps,Pd,V,a,Qg,ro,Pij,Pji,mV,mFij,mFji,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nSW,nPV,nBusref,nH,control, ...
flow,Gh,Bh,Li,Lj,Ps_idx,Pd_idx,S,D,X,L,Ch);
NCP = zeros(length(Ps(:,1)),Bus.n);
for i = 1:length(Ps(:,1))
NCPi = compNCP(V(i,:)',a(i,:)',mV(i,:)',mFij(i,:)',mFji(i,:)');
NCP(i,:) = NCPi';
end
end
% ------------------------------------------------------------------
case '7' % C O N G E S T I O N M A N A G E M E N T
% ------------------------------------------------------------------
%lambda_values = [0.0:0.01:0.61];
%n_lambda = length(lambda_values);
%GAMS.dpgup = zeros(Supply.n,n_lambda);
%GAMS.dpgdw = zeros(Supply.n,n_lambda);
%GAMS.dpdup = zeros(Demand.n,n_lambda);
%GAMS.dpddw = zeros(Demand.n,n_lambda);
%for i = 1:length(lambda_values)
%lambda.val(1) = lambda_values(i);
iteration = 0;
idx_gen = zeros(Supply.n,1);
Psc_idx = Ps_idx;
Psm_idx = zeros(Bus.n,Supply.n);
while 1
[Ps,Pd,dPSup,dPSdw,dPDup,dPDdw,V,a,Qg,ro,Pij,Pji,mV,mFij,mFji, ...
lambdac,kg,Vc,ac,Qgc,Pijc,Pjic,Pceq,lambdam,modelstat,solvestat] = ...
psatgams('fm_cong',nBus,nLine,nPs,nPd,nBusref,nSW,nPV,control,flow, ...
Gh,Bh,Ghc,Bhc,Li,Lj,Ps_idx,Psc_idx,Psm_idx,Pd_idx, ...
SW_idx,PV_idx,S,D,X,L,lambda);
iteration = iteration + 1;
if iteration > 10
fm_disp('* * * Maximum number of iteration with no convergence!')
break
end
idx = psupper_supply(Supply,(1+lambdac+kg)*Ps);
if sum(idx_gen(idx)) == length(idx)
fm_disp(['* * * iter = ',num2str(iteration), ...
', #viol., ',num2str(length(find(idx_gen))), ...
' lambda = ', num2str(lambdac), ...
' kg = ', num2str(kg)])
break
else
% loop until there are no violations of power supply limits
idx_gen(idx) = 1;
fm_disp(['* * * iter = ',num2str(iteration),', #viol. = ', ...
num2str(length(idx)),', lambda = ', ...
num2str(lambdac),' kg = ', num2str(kg)])
drawnow;
Psc_idx = psidx_supply(Supply,~idx_gen);
Psm_idx = psidx_supply(Supply,idx_gen);
end
end
%GAMS.dpgup(:,i) = dPSup;
%GAMS.dpgdw(:,i) = dPSdw;
%GAMS.dpdup(:,i) = dPDup;
%GAMS.dpddw(:,i) = dPDdw;
%if ~rem(i,10), disp(['Current lambda = ',num2str(lambda_values(i))]),end
%end
%GAMS.lvals = lambda_values;
NCP = compNCP(V,a,mV,mFij,mFji);
% ------------------------------------------------------------------
case '4' % V O L T A G E S T A B I L I T Y C O N S T R A I N E D
% O P T I M A L P O W E R F L O W
% ------------------------------------------------------------------
if type == 1 % Single Period Auction
[Ps,Pd,V,a,Qg,ro,Pij,Pji,mV,mFij,mFji, ...
lambdac,kg,Vc,ac,Qgc,Pijc,Pjic,Pceq,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nBusref,nSW,nPV,control,flow, ...
Gh,Bh,Ghc,Bhc,Li,Lj,Ps_idx,Pd_idx,SW_idx,PV_idx,S,D,X,L,lambda);
NCP = compNCP(V,a,mV,mFij,mFji);
elseif ~rem(type,2) % Single/Multi Period Auction with UC
[Ps,Pd,V,a,Qg,ro,Pij,Pji,mV,mFij,mFji, ...
lambdac,kg,Vc,ac,Qgc,Pijc,Pjic,Pceq,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nBusref,nH,control,flow, ...
Gh,Bh,Ghc,Bhc,Li,Lj,Ps_idx,Pd_idx,S,D,X,L,lambda,Ch);
NCP = zeros(length(lambdac),Bus.n);
for i = 1:length(lambdac)
NCPi = compNCP(V(i,:)',a(i,:)',mV(i,:)',mFij(i,:)',mFji(i,:)');
NCP(i,:) = NCPi';
end
elseif type == 3 % Pareto Set Single Period Auction
fm_disp
for i = 1:length(omega)
fm_disp(sprintf(' VSC-OPF #%d, %3.1f%% - omega: %5.4f', ...
i,100*i/length(omega),omega(i)))
lambda.val = [GAMS.lmin(1),GAMS.lmax(1),omega(i),GAMS.line];
[Psi,Pdi,Vi,ai,Qgi,roi,Piji,Pjii,mV,mFij,mFji, ...
lambdaci,kgi,Vci,aci,Qgci,Pijci,Pjici,Pceq,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nBusref,nSW,nPV,control,flow, ...
Gh,Bh,Ghc,Bhc,Li,Lj,Ps_idx,Pd_idx,SW_idx,PV_idx, ...
S,D,X,L,lambda);
gams_mstat(modelstat)
gams_sstat(solvestat)
Ps(i,:) = Psi';
Pd(i,:) = Pdi';
V(i,:) = Vi';
a(i,:) = ai';
Qg(i,:) = Qgi';
ro(i,:) = roi';
Pij(i,:) = Piji';
Pji(i,:) = Pjii';
lambdac(i,:) = lambdaci';
kg(i,:) = kgi';
Vc(i,:) = Vci';
ac(i,:) = aci';
Qgc(i,:) = Qgci';
Pijc(i,:) = Pijci';
Pjic(i,:) = Pjici';
NCPi = compNCP(Vi,ai,mV,mFij,mFji);
NCP(i,:) = NCPi';
end
fm_disp
end
% ------------------------------------------------------------------
case '5' % M A X I M U M L O A D I N G C O N D I T I O N
% ------------------------------------------------------------------
if type == 1 % Single Period Auction
[Ps,Pd,V,a,Qg,ro,Pij,Pji,lambdac,kg,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nSW,nPV,nBusref, ...
control,flow,Gh,Bh,Li,Lj,Ps_idx,Pd_idx, ...
SW_idx,PV_idx,S,D,X,L);
elseif ~rem(type,2) % Single/Multi Period Auction with UC
[Ps,Pd,V,a,Qg,ro,Pij,Pji,lambdac,kg,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nSW,nPV,nBusref,nH, ...
control,flow,Gh,Bh,Li,Lj,Ps_idx,Pd_idx,SW_idx, ...
PV_idx,S,D,X,L,Ch);
end
% ------------------------------------------------------------------
case '6' % C O N T I N U A T I O N
% O P T I M A L P O W E R F L O W
% ------------------------------------------------------------------
initial_time = clock;
if type == 1 % single period OPF, no discrete variables
% number of steps
i = 0;
last_point = 0;
% initial lambda = 0. Base case has to be feasible
lmin = 0;
lmax = 0;
Lambda = lmin;
% save actual CPF settings
CPF_old = CPF;
%CPF.nump = 50;
CPF.show = 0;
CPF.type = 3;
CPF.sbus = 0;
CPF.vlim = 1;
CPF.ilim = 1;
CPF.qlim = 1;
CPF.init = 0;
CPF.step = 0.25;
control = '6';
% save actual power flow data
% ------------------------------------------------------
snappg = Snapshot(1).Pg;
%Snapshot(1).Pg = [];
Bus_old = Bus;
% defining voltage limits
[Vmax,Vmin] = fm_vlim(1.2,0.8);
fm_disp
stop_opf = 0;
while 1
% OPF step
% ------------------------------------------------------
i = i + 1;
fm_disp(sprintf('Continuation OPF #%d, lambda_c = %5.4f', ...
i,lmin))
lambda.val = [lmin,lmax,0,GAMS.line];
% call GAMS
[Psi,Pdi,Vi,ai,Qgi,roi,Piji,Pjii,mV,mFij,mFji, ...
lambdaci,kgi,Vci,aci,Qgci,Pijci,Pjici,mPceq,ml,modelstat,solvestat] = ...
psatgams(file,nBus,nLine,nPs,nPd,nBusref,nSW,nPV,control,flow, ...
Gh,Bh,Ghc,Bhc,Li,Lj,Ps_idx,Pd_idx,SW_idx,PV_idx,S,D,X,L,lambda);
gams_mstat(modelstat)
gams_sstat(solvestat)
Lambda(i,1) = lambdaci;
Ps(i,:) = Psi';
Pd(i,:) = Pdi';
V(i,:) = Vi';
a(i,:) = ai';
Qg(i,:) = Qgi';
ro(i,:) = roi';
Pij(i,:) = Piji';
Pji(i,:) = Pjii';
lambdac(i,:) = lambdaci;
kg(i,:) = kgi;
Vc(i,:) = Vci';
ac(i,:) = aci';
Qgc(i,:) = Qgci';
Pijc(i,:) = Pijci';
Pjic(i,:) = Pjici';
NCPi = compNCP(Vi,ai,mV,mFij,mFji);
NCP(i,:) = NCPi';
ML(i,1) = ml;
% check consistency of the solution (LMP > 0)
if modelstat > 3 %min(abs(roi)) < 1e-5
fm_disp('Unfeasible OPF solution. Discarding last solution.')
Lambda(end) = [];
Ps(end,:) = [];
Pd(end,:) = [];
V(end,:) = [];
a(end,:) = [];
Qg(end,:) = [];
ro(end,:) = [];
Pij(end,:) = [];
Pji(end,:) = [];
lambdac(end) = [];
kg(end) = [];
Vc(end,:) = [];
ac(end,:) = [];
Qgc(end,:) = [];
Pijc(end,:) = [];
Pjic(end,:) = [];
NCP(end,:) = [];
ML(end) = [];
lambdaci = lambdac(end,:);
break
end
% ------------------------------------------------------
% Bid variations to allow loading parameter increase
%
% d mu_Pceq_i
% D P_i = -sign(P_i) -------------
% d mu_lambda
%
% where:
%
% P_i = power bid i
% mu_Pceq_i = Lagrangian multiplier of critical PF eq. i
% mu_lambda = Lagrangian multiplier of lambda
% ------------------------------------------------------
delta = 0.05;
while 1
if abs(ml) > 1e-5
deltaPd = ml./mPceq(Demand.bus)/(1+lambdaci);
deltaPs = -ml./mPceq(Supply.bus)/(1+lambdaci+kgi);
delta_max = norm([deltaPs; deltaPd]);
if delta_max == 0, delta_max = 1; end
deltaPd = deltaPd/delta_max;
deltaPs = deltaPs/delta_max;
else
deltaPd = zeros(Demand.n,1);
deltaPs = zeros(Supply.n,1);
end
%ml
%mPceq
%delta_max = max(norm([deltaPs; deltaPd]));
%if delta_max == 0, delta_max = 1; end
DPs(i,:) = deltaPs'/Settings.mva;
DPd(i,:) = deltaPd'/Settings.mva;
Pdi = pdbound_demand(Demand,Pd(i,:)' + delta*deltaPd.*Pd(i,:)');
Psi = psbound_supply(Supply,Ps(i,:)' + delta*deltaPs.*Ps(i,:)');
% CPF step
% ------------------------------------------------------
if GAMS.basepl
PQ = pqreset_pq(PQ,'all');
PV = pvreset_pv(PV,'all');
SW = swreset_sw(SW,'all');
Snapshot(1).Pg = snappg;
else
PQ = pqzero_pq(PQ,'all');
PV = pvzero_pv(PV,'all');
SW = swzero_sw(SW,'all');
Snapshot(1).Pg = getzeros_bus(Bus);
end
Demand = pset_demand(Demand,Pdi);
pqsum_demand(Demand,1);
Supply = pset_supply(Supply,Psi);
pgsum_supply(Supply,1);
swsum_supply(Supply,1);
DAE.y(Bus.a) = aci;
DAE.y(Bus.v) = Vci;
PV = setvg_pv(PV,'all',DAE.y(PV.vbus));
SW = setvg_sw(SW,'all',DAE.y(SW.vbus));
DAE.x = Snapshot(1).x;
Bus.Pg = Bus_old.Pg;
Bus.Qg = Bus_old.Qg;
Bus.Pl = Bus_old.Pl;
Bus.Ql = Bus_old.Ql;
% avoid aborting CPF routine due to limits
% ------------------------------------------------------
% voltage limits
Vbus = DAE.y(Bus.v);
idx = find(abs(Vbus-Vmax) < CPF.tolv | Vbus > Vmax);
if ~isempty(idx)
DAE.y(idx+Bus.n) = Vmax(idx)-1e-6-CPF.tolv;
end
idx = find(abs(Vbus-Vmin) < CPF.tolv | Vbus < Vmin);
if ~isempty(idx)
DAE.y(idx+Bus.n) = Vmin(idx)+1e-6+CPF.tolv;
end
CPF.kg = 0;
CPF.lambda = 1; %lambdaci + 1;
CPF.linit = 1+lambdaci*0.25;
CPF.init = 0;
% set contingency for CPF analysis
if GAMS.line
status = Line.u(GAMS.line);
Line = setstatus_line(Line,GAMS.line,0);
end
% ---------------------------------------------
% call continuation power flow routine
fm_cpf('gams');
%CPF.lambda = CPF.lambda + 1;
% ---------------------------------------------
% reset admittance line
if GAMS.line
Line = setstatus_line(Line,GAMS.line,status);
end
if isempty(CPF.lambda)
fm_disp([' * CPF solution: <empty>'])
elseif isnan(CPF.lambda)
fm_disp([' * CPF solution: <NaN>'])
else
fm_disp([' * CPF solution: ',num2str(CPF.lambda-1)])
end
if isnan(CPF.lambda)
stop_opf = 1;
break
end
if isempty(CPF.lambda)
stop_opf = 1;
break
end
if CPF.lambda ~= lambdaci
CPF.lambda = CPF.lambda - 0.995;
end
if CPF.lambda < lambdaci && abs(ml) <= 1e-5
ml = 0;
CPF.lambda = lmin+1e-5;
end
if CPF.lambda < lmin && abs(ml) > 1e-5
fm_disp([' * Decrease Delta Ps and Delta Pd'])
delta = 0.5*delta;
if delta < 5e-8
fm_disp([' * CPF method cannot find a higher lambda'])
stop_opf = 1;
break
end
repeat_cpf = 1;
else
repeat_cpf = 0;
end
% maximum lambda increment
if (CPF.lambda - lmin) > 0.025 % && (abs(ml) > 1e-5 || CPF.lambda > 0.6)
fm_disp(['lambda critical = ',num2str(CPF.lambda)])
fm_disp(['Limit lambda increment to threshold (0.025)'])
CPF.lambda = lmin + 0.025;
end
% stopping criterion
% ------------------------------------------------------
if last_point
fm_disp('Reached maximum lambda.')
if CPF.lambda > lmin
fm_disp('Desired maximum lambda is not critical.')
end
stop_opf = 1;
break
end
if i >= CPF.nump
fm_disp('Reached maximum # of continuation steps.')
stop_opf = 1;
break
end
if CPF.lambda >= GAMS.lmax
CPF.lambda = GAMS.lmax;
last_point = 1;
end
if CPF.lambda == 0
fm_disp('Base case solution is likely unfeasible.')
stop_opf = 1;
break
end
if abs(lmin-CPF.lambda) < 1e-5
%fm_disp(['||lambda(i+1) - lambda(i)|| = ', ...
% num2str(abs(lmin-CPF.lambda))])
fm_disp('Lambda increment is lower than the desired tolerance.')
stop_opf = 1;
break
elseif ~repeat_cpf
if abs(ml) < 1e-5
lmin = CPF.lambda+0.001;
lmax = CPF.lambda+0.001;
else
lmin = CPF.lambda;
lmax = CPF.lambda;
end
break
end
end
%end
if stop_opf, break, end
end
% restore original data and settings
% --------------------------------------------------------
DAE.y = Snapshot(1).y;
Snapshot(1).Pg = snappg;
Bus.Pg = Bus_old.Pg;
Bus.Qg = Bus_old.Qg;
Bus.Pl = Bus_old.Pl;
Bus.Ql = Bus_old.Ql;
PV = restore_pv(PV);
SW = restore_sw(SW);
PQ = pqreset_pq(PQ,'all');
CPF = CPF_old;
CPF.init = 4;
Varout.t = [];
Varout.vars = [];
fm_disp
% uncomment to plot [dP/d lambda] instead of [P]
%Ps = DPs;
%Pd = DPd;
else
fm_disp('Continuation OPF not implemented yet...')
cd(currentpath)
return
end
end
% -------------------------------------------------------------------
% Output
% -------------------------------------------------------------------
MVA = Settings.mva;
TPQ = MVA*totp_pq(PQ);
% character for backslash
bslash = char(92);
if GAMS.method == 6, type = 3; end
if type == 2 || type == 3
switch GAMS.flow
case 0, flow = 'I_';
case 1, flow = 'I_';
case 2, flow = 'P_';
case 3, flow = 'S_';
end
Lf = cellstr(num2str(Line.fr));
Lt = cellstr(num2str(Line.to));
TD = MVA*sum(Pd')';
if type == 2
TD = MVA*sum(Pd,2);
TTL = TD + TPQ*Ch.val';
TL = MVA*sum(Ps')' + MVA*sum(Bus.Pg)*Ch.val' - TTL;
TBL = TL - MVA*Snapshot(1).Ploss*Ch.val';
for i = 1:size(Ps,1)
PG(i,:) = full(sparse(1,iBPs,Ps(i,:),1,Bus.n)+Ch.val(i)*Bus.Pg')*MVA;
end
for i = 1:size(Pd,1)
PL(i,:) = full(sparse(1,iBPd,Pd(i,:),1,Bus.n)+Ch.val(i)*Bus.Pl')*MVA;
end
elseif type == 3
TTL = TD + TPQ;
TL = MVA*sum(Ps')' + MVA*sum(Bus.Pg) - TTL;
TBL = TL - MVA*Snapshot(1).Ploss;
for i = 1:size(Ps,1)
PG(i,:) = full(sparse(1,iBPs,Ps(i,:),1,Bus.n)+Bus.Pg')*MVA;
end
for i = 1:size(Pd,1)
PL(i,:) = full(sparse(1,iBPd,Pd(i,:),1,Bus.n)+Bus.Pl')*MVA;
end
end
PayS = -PG.*ro;
PayD = PL.*ro;
ISO = sum(PayS')'+sum(PayD')';
if GAMS.method == 4 || GAMS.method == 6
MLC = TTL.*(1+lambdac);
elseif GAMS.method == 5
MLC = TTL.*lambdac;
end
Varname.uvars = fm_strjoin('PS_',{Bus.names{Supply.bus}}');
Varname.uvars = [Varname.uvars;fm_strjoin('PD_',{Bus.names{Demand.bus}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('PG_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('PL_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('Pay_S_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('Pay_D_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('theta_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('V_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('Qg_',{Bus.names{iBQg}}')];
if GAMS.method > 2 && GAMS.method ~= 5
Varname.uvars = [Varname.uvars;fm_strjoin('LMP_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('NCP_',{Bus.names{:}}')];
elseif GAMS.method == 2
Varname.uvars = [Varname.uvars;fm_strjoin('LMP_',{Bus.names{:}}')];
elseif GAMS.method == 5
Varname.uvars = [Varname.uvars;fm_strjoin(bslash,'rho_',{Bus.names{:}}')];
else
Varname.uvars = [Varname.uvars;{'MCP'}];
end
Varname.uvars = [Varname.uvars;fm_strjoin(flow,Lf,'-',Lt)];
Varname.uvars = [Varname.uvars;fm_strjoin(flow,Lt,'-',Lf)];
Varname.uvars = [Varname.uvars;{'Total Demand';'TTL';'Total Losses'; ...
'Total Bid Losses';'IMO Pay'}];
if GAMS.method >= 4
Varname.uvars = [Varname.uvars;{'MLC'}];
Varname.uvars = [Varname.uvars;{'ALC'}];
end
Varname.fvars = fm_strjoin('P_{S',{Bus.names{Supply.bus}}','}');
Varname.fvars = [Varname.fvars;fm_strjoin('P_{D',{Bus.names{Demand.bus}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('P_{G',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('P_{L',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('Pay_{S',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('Pay_{D',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin(bslash,'theta_{',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('V_{',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('Q_{g',{Bus.names{iBQg}}','}')];
if GAMS.method > 2 && GAMS.method ~= 5
Varname.fvars = [Varname.fvars;fm_strjoin('LMP_{',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('NCP_{',{Bus.names{:}}','}')];
elseif GAMS.method == 2
Varname.fvars = [Varname.fvars;fm_strjoin('LMP_{',{Bus.names{:}}','}')];
elseif GAMS.method == 5
Varname.fvars = [Varname.fvars;fm_strjoin(bslash,'rho_',{Bus.names{:}}')];
else
Varname.fvars = [Varname.fvars;{'MCP'}];
end
Varname.fvars = [Varname.fvars;fm_strjoin(flow,'{',Lf,'-',Lt,'}')];
Varname.fvars = [Varname.fvars;fm_strjoin(flow,'{',Lt,'-',Lf,'}')];
Varname.fvars = [Varname.fvars;{'Total Demand';'TTL';'Total Losses'; ...
'Total Bid Losses';'IMO Pay'}];
if GAMS.method >= 4
Varname.fvars = [Varname.fvars;{'MLC'}];
Varname.fvars = [Varname.fvars;{'ALC'}];
end
switch GAMS.method
case 3 % OPF
Varout.vars = [Ps*MVA,Pd*MVA,PG,PL,PayS,PayD,a,V,Qg(:,iBQg)*MVA, ...
ro,NCP,Pij,Pji,TD,TTL,TL,TBL,ISO];
case {4,6} % VSC-OPF
Varname.uvars = [Varname.uvars;{'lambda_c';'kg_c'}];
Varname.uvars = [Varname.uvars;fm_strjoin('thetac_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('Vc_',{Bus.names{:}}')];
Varname.uvars = [Varname.uvars;fm_strjoin('Qgc_',{Bus.names{iBQg}}')];
Varname.uvars = [Varname.uvars;fm_strjoin(flow,'c',Lf,'-',Lt)];
Varname.uvars = [Varname.uvars;fm_strjoin(flow,'c',Lt,'-',Lf)];
Varname.fvars = [Varname.fvars;{[bslash,'lambda_c'];'k_g_c'}];
Varname.fvars = [Varname.fvars;fm_strjoin(bslash,'theta_{c',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('V_{c',{Bus.names{:}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin('Q_{gc',{Bus.names{iBQg}}','}')];
Varname.fvars = [Varname.fvars;fm_strjoin(flow,'{c',Lf,'-',Lt,'}')];
Varname.fvars = [Varname.fvars;fm_strjoin(flow,'{c',Lt,'-',Lf,'}')];
Varout.vars = [Ps*MVA,Pd*MVA,PG,PL,PayS,PayD,a,V,Qg(:,iBQg)*MVA, ...
ro,NCP,Pij,Pji,TD,TTL,TL,TBL,ISO,MLC,MLC-TTL,lambdac,kg, ...
ac,Vc,Qgc(:,iBQg)*MVA,Pijc,Pjic];
case 5 % MLC
Varname.uvars = [Varname.uvars;{'lambda_c';'kg_c'}];
Varname.fvars = [Varname.fvars;{bslash,'lambda_c';'k_g_c'}];
Varout.vars = [Ps*MVA,Pd*MVA,PG,PL,PayS,PayD,a,V,Qg(:,iBQg)*MVA, ...
ro,Pij,Pji,TD,TTL,TL,TBL,ISO,MLC,lambdac,kg];
otherwise % SA and MCM
Varout.vars = [Ps*MVA,Pd*MVA,PG,PL,PayS,PayD,a,V,Qg(:,iBQg)*MVA, ...
MCP,Pij,Pji,TD,TTL,TL,TBL,ISO];
end
if GAMS.method == 6 % Continuation OPF
Settings.xlabel = [bslash,'lambda (loading parameter)'];
Varout.t = Lambda';
elseif type == 2 % Multi Period Auction
Varout.vars = Varout.vars([2:end],:);
Settings.xlabel = 'hour [h]';
Varout.t = [1:Ypdp.len]';
elseif type == 3 % Pareto Set Single Period Auction
Settings.xlabel = [bslash,'omega (weighting factor)'];
Varout.t = GAMS.omega';
end
Varout.idx = [1:length(Varout.vars(1,:))];
fm_disp(' ---------------------------------------------------------------')
fm_disp([' Check file ',Path.psat,'fm_gams.lst for GAMS report.'])
if strcmp(control,'6')
fm_disp([' PSAT-GAMS Optimization Routine completed in ', ...
num2str(etime(clock,initial_time)),' s'])
else
fm_disp([' PSAT-GAMS Optimization Routine completed in ',num2str(toc),' s'])
end
Demand = restore_demand(Demand);
if ~GAMS.basepl
Bus.Pl = buspl;
Bus.Ql = busql;
PQ = pqreset_pq(PQ,'all');
end
if ~GAMS.basepg
Snapshot(1).Ploss = ploss;
Bus.Pg = buspg;
Bus.Qg = busqg;
PV = pvreset_pv(PV,'all');
end
% restore original bus power injections
Bus.Pg = Snapshot(1).Pg;
Bus.Qg = Snapshot(1).Qg;
Bus.Pl = Snapshot(1).Pl;
Bus.Ql = Snapshot(1).Ql;
return
end
if type == 4
Ps = Ps(2,:)';
Pd = Pd(2,:)';
V = V(2,:)';
a = a(2,:)';
Qg = Qg(2,iBQg)';
Pij = Pij(2,:)';
Pji = Pji(2,:)';
if GAMS.method <= 2
MCP = MCP(2,:);
end
if GAMS.method >= 3
ro = ro(2,:)';
if GAMS.method ~= 5
NCP = NCP(2,:)';
end
end
if GAMS.method == 4 || GAMS.method == 6
Vc = Vc(2,:)';
ac = ac(2,:)';
Qgc = Qgc(2,iBQg)';
Pijc = Pijc(2,:)';
Pjic = Pjic(2,:)';
end
if GAMS.method >= 4
lambdac = lambdac(2);
kg = kg(2);
end
end
Demand = pset_demand(Demand,Pd);
Supply = pset_supply(Supply,Ps);
if GAMS.method == 4 || GAMS.method == 6
DAE.y(Bus.a) = ac;
DAE.y(Bus.v) = Vc;
Line = gcall_line(Line);
glfpc = Line.p;
glfqc = Line.q;
end
if GAMS.method >= 3
DAE.y(Bus.a) = a;
DAE.y(Bus.v) = V;
Line = gcall_line(Line);
Qg = Qg(iBQg);
end
if GAMS.method == 1
ro = MCP*getones_bus(Bus);
end
if GAMS.method == 2
[rows,cols] = size(MCP);
if rows == 1,
ro = MCP';
else
ro = MCP;
end
end
Qgmin = Qgmin(iBQg);
Qgmax = Qgmax(iBQg);
if GAMS.basepl
PG = full((sparse(iBPs,1,Ps,Bus.n,1)+Bus.Pg)*MVA);
PL = full((sparse(iBPd,1,Pd,Bus.n,1)+Bus.Pl)*MVA);
else
PG = full(sparse(iBPs,1,Ps,Bus.n,1)*MVA);
PL = full(sparse(iBPd,1,Pd,Bus.n,1)*MVA);
end
QG = full(sparse(iBQg,1,Qg,Bus.n,1)*MVA);
QL = full((sparse(iBPd,1,Pd.*tanphi_demand(Demand),Bus.n,1)+Bus.Ql)*MVA);
PayS = -ro(Bus.a).*PG;
PayD = ro(Bus.a).*PL;
ISOPay = -sum(ro(Bus.a).*Line.p*MVA);
if (Settings.showlf || GAMS.show) && clpsat.showopf
fm_disp
fm_disp(' Power Supplies')
fm_disp(' ---------------------------------------------------------------')
[Psmax,Psmin] = plim_supply(Supply);
if GAMS.method == 7
fm_disp({'Bus','Ps','Ps max','Ps min','dPs_up','dPs_dw'})
fm_disp({'<i>','[MW]','[MW]','[MW]','[MW]','[MW]'})
fm_disp([getidx_bus(Bus,Supply.bus),Ps*MVA,Psmax*MVA,Psmin*MVA,dPSup*MVA,dPSdw*MVA])
else
fm_disp({'Bus','Ps','Ps max','Ps min'})
fm_disp({'<i>','[MW]','[MW]','[MW]'})
fm_disp([getidx_bus(Bus,Supply.bus),Ps*MVA,Psmax*MVA,Psmin*MVA])
end
fm_disp
fm_disp(' Power Demands')
fm_disp(' ---------------------------------------------------------------')
[Pdmax,Pdmin] = plim_demand(Demand);
if GAMS.method == 7
fm_disp({'Bus','Pd','Pd max','Pd min','dPd_up','dPd_dw'})
fm_disp({'<i>','[MW]','[MW]','[MW]'})
fm_disp([getidx_bus(Bus,Demand.bus),Pd*MVA,Pdmax*MVA,Pdmin*MVA,dPDup*MVA,dPDdw*MVA])
else
fm_disp({'Bus','Pd','Pd max','Pd min'})
fm_disp({'<i>','[MW]','[MW]','[MW]'})
fm_disp([getidx_bus(Bus,Demand.bus),Pd*MVA,Pdmax*MVA,Pdmin*MVA])
end
fm_disp
fm_disp(' Generator Reactive Powers')
fm_disp(' ---------------------------------------------------------------')
if GAMS.method == 4 || GAMS.method == 6
fm_disp({'Bus','Qg','Qgc','Qg max','Qg min'})
fm_disp({'<i>','[MVar]','[MVar]','[MVar]','[MVar]'})
fm_disp([getidx_bus(Bus,iBQg),Qg*MVA,Qgc(iBQg)*MVA,Qgmax*MVA,Qgmin*MVA])
else
fm_disp({'Bus','Qg','Qg max','Qg min'})
fm_disp({'<i>','[MVar]','[MVar]','[MVar]'})
fm_disp([getidx_bus(Bus,iBQg),Qg*MVA,Qgmax*MVA,Qgmin*MVA])
end
fm_disp
fm_disp(' Power Flow Solution')
fm_disp([' ----------------------------------------------------' ...
'-----------'])
fm_disp({'Bus','V','theta','PG','PL','QG','QL'})
fm_disp({'<i>','[p.u.]','[rad]','[MW]','[MW]','[MVar]','[MVar]'})
fm_disp([getidx_bus(Bus,0),DAE.y(Bus.v),DAE.y(Bus.a),PG,PL,QG,QL])
fm_disp
fm_disp(' Prices and Pays')
fm_disp([' ----------------------------------------------------' ...
'-----------'])
if GAMS.method == 3 || GAMS.method == 4 || GAMS.method == 6
fm_disp({'Bus','LMP','NCP','Pay S','Pay D'})
fm_disp({'<i>','[$/MWh]','[$/MWh]','[$/h]','[$/h]'})
fm_disp([getidx_bus(Bus,0),ro(Bus.a), NCP, PayS, PayD])
else
fm_disp({'Bus','LMP','Pay S','Pay D'})
fm_disp({'<i>','[$/MWh]','[$/h]','[$/h]'})
fm_disp([getidx_bus(Bus,0),ro(Bus.a), PayS, PayD])
end
if GAMS.method == 4 || GAMS.method == 6
fm_disp
fm_disp(' "Critical" Power Flow Solution')
fm_disp(' ---------------------------------------------------------------')
fm_disp({'Bus','Vc','thetac','PGc','PLc','QGc','QLc'})
fm_disp({'<i>','[p.u.]','[rad]','[MW]','[MW]','[MVar]', ...
'[MVar]'})
PG = (1+lambdac+kg)*PG;
PL = (1+lambdac)*PL;
QL = (1+lambdac)*QL;
fm_disp([getidx_bus(Bus,0),Vc,ac,PG,PL,Qgc*MVA,QL])
end
fm_disp
if GAMS.flow
fm_disp(' Flows on Transmission Lines')
fm_disp(' ---------------------------------------------------------------')
switch GAMS.flow
case 1,
fm_disp({'From Bus','To Bus','Iij','Iijmax', ...
'Iij margin','Iji','Ijimax','Iji margin'},1)
case 2,
fm_disp({'From Bus','To Bus','Pij','Pijmax', ...
'Pij margin','Pji','Pjimax','Pji margin'},1)
case 3,
fm_disp({'From Bus','To Bus','Sij','Sijmax', ...
'Sij margin','Sji','Sjimax','Sji margin'},1)
end
fm_disp({'<i>','<j>','[p.u.]','[p.u.]', ...
'[p.u.]','[p.u.]','[p.u.]','[p.u.]'})
fm_disp([Line.fr, Line.to,Pij, ...
L.val(:,5),abs((-abs(Pij)+L.val(:,5))), ...
Pji,L.val(:,5),abs((-abs(Pji)+L.val(:,5)))])
fm_disp
else
fm_disp('Flow limits are disabled.')
end
if GAMS.method == 4 || GAMS.method == 6
fm_disp(' Flows on Transmission Lines of the "Critical" System')
fm_disp(' ---------------------------------------------------------------')
switch GAMS.flow
case 1,
fm_disp({'From Bus','To Bus','Iijc','Iijcmax', ...
'Iijc margin','Ijic','Ijicmax','Ijic margin'})
case 2,
fm_disp({'From Bus','To Bus','Pijc','Pijcmax', ...
'Pijc margin','Pjic','Pjicmax','Pjic margin'})
case 3,
fm_disp({'From Bus','To Bus','Sijc','Sijcmax', ...
'Sijc margin','Sjic','Sjicmax',['Sjic margin']})
end
fm_disp({'<i>','<j>','[p.u.]','[p.u.]', ...
'[p.u.]','[p.u.]','[p.u.]','[p.u.]'})
if GAMS.flow
fm_disp([Line.fr, Line.to,Pijc, ...
L.val(:,5),abs((-abs(Pijc)+L.val(:,5))), ...
Pjic,L.val(:,5),abs((-abs(Pjic)+L.val(:,5)))])
fm_disp
end
end
fm_disp
fm_disp(' Totals')
fm_disp(' ---------------------------------------------------------------')
if GAMS.method >= 4,
fm_disp([' omega = ',num2str(omega(1))])
fm_disp([' lambda_c = ',num2str(lambdac),' [p.u.]'])
fm_disp([' kg = ',num2str(kg),' [p.u.]'])
end
if GAMS.method == 1
fm_disp([' Market Clearing Price = ',num2str(MCP),' [$/MWh]'])
end
total_loss = 1e-5*round(sum(Line.p)*1e5)*MVA;
bid_loss = 1e-5*round((sum(Line.p)-Snapshot(1).Ploss)*1e5)*MVA;
fm_disp([' Total Losses = ',num2str(total_loss),' [MW]'])
fm_disp([' Bid Losses = ',num2str(bid_loss),' [MW]'])
fm_disp([' Total demand = ',num2str(sum(Pd)*MVA),' [MW]'])
fm_disp([' Total Transaction Level = ', ...
fvar(sum(Pd)*MVA+TPQ,8),' [MW]']);
if GAMS.method == 4 || GAMS.method == 6
fm_disp([' Maximum Loading Condition = ', ...
fvar((1+lambdac)*(sum(Pd)*MVA+TPQ),8),' [MW]']);
fm_disp([' Available Loading Capability = ', ...
fvar(lambdac*(sum(Pd)*MVA+TPQ),8),' [MW]']);
end
if GAMS.method == 5
fm_disp([' Maximum Loading Condition = ', ...
fvar(lambdac*(sum(Pd)*MVA+TPQ),8),' [MW]']);
end
fm_disp([' IMO Pay = ',num2str(ISOPay),' [$/h]']);
fm_disp
end
fm_disp(' ---------------------------------------------------------------')
fm_disp([' Check file ',Path.psat,'fm_gams.lst for GAMS report.'])
gams_mstat(modelstat)
gams_sstat(solvestat)
if strcmp(control,'6')
fm_disp([' PSAT-GAMS Optimization Routine completed in ', ...
num2str(etime(clock,initial_time)),' s'])
else
fm_disp([' PSAT-GAMS Optimization Routine completed in ',num2str(toc),' s'])
end
if noDem, Demand = restore_demand(Demand); end
if ~GAMS.basepl
Bus.Pl = buspl;
Bus.Ql = busql;
PQ = pqreset_pq(PQ,'all');
end
if ~GAMS.basepg
Snapshot(1).Ploss = ploss;
Bus.Pg = buspg;
Bus.Qg = busqg;
PV = pvreset_pv(PV,'all');
end
% restore original bus power injections
Bus.Pg = Snapshot(1).Pg;
Bus.Qg = Snapshot(1).Qg;
Bus.Pl = Snapshot(1).Pl;
Bus.Ql = Snapshot(1).Ql;
% ===============================================================
function [Pij,Pji,Qg] = updatePF(Pd,Ps,iBQg)
% Power FLow Solution with the current simple auction solution
% ===============================================================
global Settings Bus Line PQ PV SW Demand Supply GAMS
Busold = Bus;
Demand = pset_demand(Demand,Pd);
Supply = pset_supply(Supply,Ps);
pg = SW.pg;
pqsum_demand(Demand,1);
pgsum_supply(Supply,1);
show_old = Settings.show;
Settings.show = 0;
Settings.locksnap = 1;
fm_spf
Settings.locksnap = 0;
Settings.show = show_old;
[Pij,Pji] = flows_line(Line,max(GAMS.flow,1));
Qg = Bus.Qg(iBQg);
Bus = Busold;
SW = setpg_sw(SW,'all',pg);
PQ = restore_pq(PQ);
PV = pvreset_pv(PV,'all');
% ==========================================================================
function NCP = compNCP(V,a,mV,mFij,mFji)
% Nodal Congestion Prices
% ==========================================================================
global DAE SW GAMS Line Bus
yold = DAE.y;
Gyold = DAE.Gy;
DAE.y(Bus.a) = a;
DAE.y(Bus.v) = V;
Gycall_line(Line)
fm_setgy(SW.refbus)
[Fij,Jij,Fji,Jji] = fjh2_line(Line,max(GAMS.flow,1));
dH_dtV = Jij'*mFij + Jji'*mFji + [getzeros_bus(Bus);mV];
dH_dtV(SW.refbus,:) = 0;
NCP = DAE.Gy'\dH_dtV;
NCP = NCP(Bus.a);
DAE.y = yold;
DAE.Gy = Gyold;
% ==========================================================================
function varargout = psatgams(varargin)
% PSAT-GAMS interface
% ==========================================================================
global Settings Path
% writing GAMS input data
%---------------------------------------------------------------------
fid1 = fopen('psatglobs.gms','wt+');
fid2 = fopen('psatdata.gms','wt+');
fprintf(fid2,'%s\n','$onempty');
for i = 2:nargin
if ischar(varargin{i})
fprintf(fid1,'$setglobal %s ''%s''\n',inputname(i), ...
varargin{i});
elseif isnumeric(varargin{i})
fprintf(fid2,'$kill %s\n',inputname(i));
if length(varargin{i}) == 1
fprintf(fid2,'scalar %s /%f/;\n',inputname(i),varargin{i});
else
fprintf(fid2,'parameter %s /\n',inputname(i));
[x,y,v] = find(varargin{i});
fprintf(fid2,'%d.%d %f\n',[x y v]');
fprintf(fid2,'/;\n');
end
elseif isstruct(varargin{i})
labels = varargin{i}.labels;
fprintf(fid2,'$kill %s\n',varargin{i}.name);
fprintf(fid2,'parameter %s /\n',varargin{i}.name);
[x,y,v] = find(varargin{i}.val);
if iscell(labels{1})
%a = fm_strjoin(labels{1}(x),'.',labels{2}(y)',[blanks(length(x))',num2str(v)]);
%fprintf(fid2,'%s\n',a{:});
for j = 1:length(x)
fprintf(fid2,'%s.%s %f\n',labels{1}{x(j)},labels{2}{y(j)},v(j));
end
else
for j = 1:length(x)
fprintf(fid2,'%s %f\n',labels{y(j)},v(j));
end
end
fprintf(fid2,'/;\n');
end
end
fprintf(fid2,'%s\n','$offempty');
fclose(fid1);
fclose(fid2);
% Lauching GAMS
%---------------------------------------------------------------------
status = 0;
t0 = clock;
%disp(['gams ',varargin{1},' -error=PSAT'])
[status,result] = system(['gams ',varargin{1}]);
fm_disp([' GAMS routine completed in ',num2str(etime(clock,t0)),' s'])
if status
fm_disp(result)
return
end
% Reading GAMS output
%---------------------------------------------------------------------
nout = 0;
EPS = eps;
clear psatsol
psatsol
if nout < nargout
for i = nout+1:nargout
varargout{i} = [];
end
end
if nout > nargout
varargout(nargout+1:nout) = [];
end
%---------------------------------------------------------------------
function gams_mstat(status)
if isempty(status), return, end
switch status
case 0, fm_disp(' GAMS model status: not available')
case 1, fm_disp(' GAMS model status: optimal')
case 2, fm_disp(' GAMS model status: locally optimal')
case 3, fm_disp(' GAMS model status: unbounded')
case 4, fm_disp(' GAMS model status: infeasible')
case 5, fm_disp(' GAMS model status: locally infeasible')
case 6, fm_disp(' GAMS model status: intermediate infeasible')
case 7, fm_disp(' GAMS model status: intermediate non-optimal')
case 8, fm_disp(' GAMS model status: integer solution')
case 9, fm_disp(' GAMS model status: intermediate non-integer')
case 10, fm_disp(' GAMS model status: integer infeasible')
case 11, fm_disp(' GAMS model status: ???')
case 12, fm_disp(' GAMS model status: error unknown')
case 13, fm_disp(' GAMS model status: error no solution')
otherwise, fm_disp(' GAMS model status: unknown model status')
end
%---------------------------------------------------------------------
function gams_sstat(status)
if isempty(status), return, end
switch status
case 0, fm_disp(' GAMS solver status: not available')
case 1, fm_disp(' GAMS solver status: normal completion')
case 2, fm_disp(' GAMS solver status: iteration interrupt')
case 3, fm_disp(' GAMS solver status: resource interrupt')
case 4, fm_disp(' GAMS solver status: terminated by solver')
case 5, fm_disp(' GAMS solver status: evaluation error limit')
case 6, fm_disp(' GAMS solver status: unknown')
case 7, fm_disp(' GAMS solver status: ???')
case 8, fm_disp(' GAMS solver status: error preprocessor error')
case 9, fm_disp(' GAMS solver status: error setup failure')
case 10, fm_disp(' GAMS solver status: error solver failure')
case 11, fm_disp(' GAMS solver status: error internal solver error')
case 12, fm_disp(' GAMS solver status: error post-processor error')
case 13, fm_disp(' GAMS solver status: error system failure')
otherwise, fm_disp(' GAMS solver status: unknown solver status')
end
|
github
|
Sinan81/PSAT-master
|
fm_build.m
|
.m
|
PSAT-master/psat-oct/psat/fm_build.m
| 25,468 |
utf_8
|
688cdaed0380b34975aab856abfbaf9e
|
function fm_build
%FM_BUILD build new component functions (Symbolic Toolbox is needed)
%
%FM_BUILD
%
%see also FM_MAKE FM_COMPONENT
%
%Author: Federico Milano
%Date: 11-Nov-2002
%Update: 19-Dec-2003
%Version: 1.0.1
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2019 Federico Milano
global Comp Settings Fig Path
global Algeb Buses Initl Param Servc State
% ***********************************************************************
% some control variables
error_v = [];
lasterr('');
null = '0';
% useful strings
c_name = Comp.name;
c_name(1) = upper(c_name(1));
% variable arrays
state_vect = varvect(State.name, ' ');
algeb_vect = varvect(Algeb.name, ' ');
param_vect = varvect(Param.name, ' ');
initl_vect = varvect(Initl.name, ' ');
servc_vect = varvect(Servc.name, ' ');
pq_Servc = 0;
% equation arrays
servc_eq = varvect(Servc.eq,'; ');
state_eq = varvect(State.eq,'; ');
algeb_eq = varvect(Algeb.eq,'; ');
% ********************************************************************************
% check equations
if State.neq > 0
state_check = strmatch('null',State.eq,'exact');
if state_check
error_v = [error_v; ...
fm_strjoin('Differential equation for "', ...
State.eqidx(state_check), ...
'" has not been defined.')];
end
end
if Servc.neq > 0
servc_foo = fm_strjoin(Servc.type,Servc.eq);
servc_check = strmatch('Innernull',servc_foo,'exact');
servc_check = [servc_check; strmatch('Outputnull',servc_foo,'exact')];
if servc_check
error_v = [error_v; ...
fm_strjoin('Service equation for "', ...
Servc.eqidx(servc_check), ...
'" has not been defined.')];
end
end
% ********************************************************************************
% check variable usage
servc_idx = [strmatch('Inner',Servc.type); strmatch('Output',Servc.type)];
total_var = [State.name; Algeb.name; Servc.eqidx(servc_idx); Param.name; Initl.name];
total_eqn = [' ',servc_eq,' ',state_eq,' ',algeb_eq,' ',varvect(State.time,'*'),' '];
for i = 1:length(total_var)
idx = findstr(total_eqn,total_var{i});
if isempty(idx)
error_v{end+1,1} = ['The variable "',total_var{i},'" is not used in any equation.'];
else
before = total_eqn(idx-1);
after = total_eqn(idx+length(total_var{i}));
check = 1;
for j = 1:length(idx)
a = double(after(j)); b = double(before(j));
a1 = ~isletter(after(j)); a2 = (a ~= 95); a3 = (a > 57 || a < 48);
b1 = ~isletter(before(j)); b2 = (b ~= 95); b3 = (b > 57 || b < 48);
if a1 && a2 && a3 && b1 && b2 && b3, check = 0; break, end
end
if check
error_v{end+1,1} = ['The variable "',total_var{i}, ...
'" is not used in any equation.'];
end
end
end
% ********************************************************************************
% symbolic variables
try
if state_vect, eval(['syms ',state_vect]), end
if algeb_vect, eval(['syms ',algeb_vect]), end
if param_vect, eval(['syms ',param_vect]), end
if servc_vect, eval(['syms ',servc_vect]), end
if initl_vect, eval(['syms ',initl_vect]), end
% compute Jacobians matrices (Maple Symbolic Toolbox)
if ~isempty(state_eq)
if ~isempty(state_vect)
eval(['Fx = jacobian([',state_eq, '],[', state_vect, ']);']);
end
if ~isempty(algeb_vect)
eval(['Fy = jacobian([',state_eq, '],[', algeb_vect, ']);']);
end
if ~isempty(servc_vect)
eval(['Fz = jacobian([',state_eq, '],[', servc_vect, ']);']);
end
if pq_Servc
eval(['Fpq = jacobian([',state_eq, '],[', pq_vect, ']);']);
end
end
if ~isempty(algeb_eq)
if ~isempty(state_vect)
eval(['Gx = jacobian([',algeb_eq, '],[', state_vect, ']);']);
end
if ~isempty(algeb_vect)
eval(['Gy = jacobian([',algeb_eq, '],[', algeb_vect, ']);']);
end
if ~isempty(servc_vect)
eval(['Gz = jacobian([',algeb_eq, '],[', servc_vect, ']);']);
end
if pq_Servc
eval(['Gpq = jacobian([',alg_eqeb, '],[', pq_vect, ']);']);
end
end
if ~isempty(servc_eq)
if ~isempty(state_vect)
eval(['Zx = jacobian([',servc_eq, '],[', state_vect, ']);']);
end
if ~isempty(algeb_vect)
eval(['Zy = jacobian([',servc_eq, '],[', algeb_vect, ']);']);
end
if ~isempty(servc_vect)
eval(['Zz = jacobian([',servc_eq, '],[', servc_vect, ']);']);
end
if pq_Servc
eval(['Zpq = jacobian([',servc_eq, '],[', pq_vect, ']);']);
end
end
end
% ********************************************************************************
% check synthax of equations
for i = 1:State.neq
try
eval([State.eq{i,1},';'])
catch
error_v{end+1,1} = [lasterr, ' (In differential equation "', ...
State.eq{i,1}, '")'];
end
try
eval([State.init{i,1},';'])
catch
error_v{end+1,1} = [lasterr, ' (In state variable "', ...
State.name{i,1}, '" initialization expression)'];
end
state_init{i,1} = vectorize(State.init{i,1});
end
for i = 1:Algeb.neq
try
eval([Algeb.eq{i,1},';'])
catch
error_v{end+1,1} = [lasterr, ' (In algebraic equation "', ...
State.eq{i,1}, '")'];
end
end
for j = 1:Servc.neq
try
eval([Servc.eq{i,1},';'])
catch
error_v{end+1,1} = [lasterr, ' (In service equation "', ...
Servc.eqidx{i,1}, '")'];
end
end
% check component name
if isempty(Comp.name)
error_v{end+1,1} = 'Component name is empty.';
return
end
% ********************************************************************************
% display errors
if ~isempty(error_v)
error_v = fm_strjoin('Error#',num2str([1:length(error_v)]'),': ',error_v);
error_v = [{['REPORT OF ERRORS ENCOUNTERED WHILE BUILDING ', ...
'NEW COMPONENT "',Comp.name,'.m"']}; error_v];
error_v{end+1,1} = ['BUILDING NEW COMPONENT FILE "', ...
Comp.name,'.m" FAILED'];
fm_disp
fm_disp(error_v{1:end-1})
fm_disp(['BUILDING NEW COMPONENT FILE "',Comp.name,'.m" FAILED'])
fm_update
set(findobj(Fig.update,'Tag','Listbox1'),'String',error_v, ...
'BackgroundColor','w', ...
'ForegroundColor','r', ...
'Enable','inactive', ...
'max',2, ...
'Value',[]);
set(findobj(Fig.update,'Tag','Pushbutton2'),'Enable','off');
return
end
% ***********************************************************************
% check for previous versions
a = what(Path.psat);
olderfile = strmatch(['fm_',Comp.name,'.m'],a.m,'exact');
if ~isempty(olderfile)
uiwait(fm_choice(['Overwrite Existing File "fm_',Comp.name,'.m" ?']));
if ~Settings.ok, return, end
end
% ***********************************************************************
% open new component file
fid = fopen([Path.psat, 'fm_', Comp.name,'.m'], 'wt');
if fid == -1
fm_disp(['Cannot open file fm_',Comp.name,'. Check permissions'])
return
end
fprintf(fid, ['function fm_', Comp.name, '(flag)']);
% write help of the function
if isempty(Comp.descr)
Comp.descr = ['Algebraic Differential Equation ', ...
Comp.name, '.m'];
end
fprintf(fid, ['\n\n%%FM_', upper(Comp.name),' defines ',Comp.descr]);
% ********************************************************************
% data format .con
fprintf(fid, ['\n%%\n%%Data Format ', c_name, '.con:']);
fprintf(fid, '\n%% col #%d: Bus %d number',[1:Buses.n;1:Buses.n]);
idx_inn = strmatch('Inner', Servc.type, 'exact');
idx_inp = strmatch('Input', Servc.type, 'exact');
idx_out = strmatch('Output', Servc.type, 'exact');
fprintf(fid, '\n%% col #%d: Power rate [MVA]',Buses.n+1);
fprintf(fid, '\n%% col #%d: Bus %d Voltage Rate [kV]', ...
[Buses.n+1+[1:Buses.n];1:Buses.n]);
fprintf(fid, '\n%% col #%d: Frequency rate [Hz]',2*Buses.n+2);
inip = 2*Buses.n+3;
endp = 2*Buses.n+2+Param.n;
pidx = inip:endp;
for i=1:length(pidx)
fprintf(fid, '\n%% col #%d: %s %s [%s]', ...
pidx(i),Param.name{i},Param.descr{i},Param.unit{i});
end
x_max = [1:State.n];
if State.n
x_idx = strmatch('None',State.limit(:,1),'exact');
x_max(x_idx) = [];
end
x_min = [1:State.n];
if State.n
x_idx = strmatch('None',State.limit(:,2),'exact');
x_min(x_idx) = [];
end
n_xmax = length(x_max); n_xmin = length(x_min);
for i=1:n_xmax
fprintf(fid,'\n%% col #%d: %s',endp+i, ...
State.limit{x_max(i),1});
end
for i=1:n_xmin
fprintf(fid,'\n%% col #%d: %s',endp+n_xmax+i, ...
State.limit{x_min(i),1});
end
s_max = [1:Servc.neq];
if Servc.n
s_idx = strmatch('None',Servc.limit(:,1),'exact');
s_max(s_idx) = [];
end
s_min = [1:Servc.neq];
if Servc.n
s_idx = strmatch('None',Servc.limit(:,2),'exact');
s_min(s_idx) = [];
end
n_smax = length(s_max); n_smin = length(s_min);
for i=1:n_smax
fprintf(fid,'\n%% col #%d: %s', ...
endp+n_xmax+n_xmin+i,Servc.limit{s_max(i),1});
end
for i=1:n_smin
fprintf(fid,'\n%% col #%d: %s', ...
endp+n_xmax+n_xmin+n_smax+i,Servc.limit{s_min(i),1});
end
okdata = 0;
nidx = 0;
if ~isempty(idx_inn) || ~isempty(idx_out)
okdata = 1;
end
if Initl.n || okdata
fprintf(fid, ['\n%% \n%%Data Structure: ', c_name, '.dat:']);
end
for i=1:Initl.n
fprintf(fid,'\n%% col #%d: %s', i,Initl.name{i});
end
if okdata
nidx = length(idx_inn)+length(idx_out);
iidx = [idx_inn;idx_out];
for i=1:nidx
fprintf(fid,'\n%% col #%d: %s', ...
Initl.n+i,Servc.eqidx{iidx(i)});
end
end
% function calls
fprintf(fid, ['\n%% \n%%FM_', upper(Comp.name),'(FLAG)']);
if Comp.init
fprintf(fid, ['\n%% FLAG = 0 -> initialization']);
end
if ~isempty(algeb_eq)
fprintf(fid, ['\n%% FLAG = 1 -> algebraic equations']);
fprintf(fid, ['\n%% FLAG = 2 -> algebraic Jacobians']);
end
if ~isempty(state_eq);
fprintf(fid, ['\n%% FLAG = 3 -> differential equations']);
fprintf(fid, ['\n%% FLAG = 4 -> state Jacobians']);
end
if n_xmax || n_xmin > 0
fprintf(fid, ['\n%% FLAG = 5 -> non-windup limiters)']);
end
fprintf(fid, '\n%% \n%%Author: File automatically generated by PSAT');
fprintf(fid, '\n%%Date: %s',date);
% global variables
fprintf(fid, ['\n\nglobal ',c_name,' DAE Bus Settings']);
% ************************************************************************
% general settings
fprintf(fid, '\n');
for i=1:State.n
fprintf(fid,'\n%s = DAE.x(%s.%s);',State.name{i},c_name, ...
State.name{i});
end
if Algeb.n
idx_v = strmatch('V',Algeb.name);
idx_a = strmatch('t',Algeb.name);
if idx_v
num_v = strrep(Algeb.name(idx_v),'V','');
if Buses.n == 1
fprintf(fid,'\n%s = DAE.y(%s.bus+Bus.n);', ...
Algeb.name{idx_v},c_name);
else
for i=1:length(idx_v)
fprintf(fid,'\n%s = DAE.y(%s.bus%s+Bus.n);', ...
Algeb.name{idx_v(i)},c_name,num_v{i});
end
end
end
if idx_a
num_a = strrep(Algeb.name(idx_a),'theta','');
if Buses.n == 1
fprintf(fid,'\n%s = DAE.y(%s.bus);', ...
Algeb.name{idx_a},c_name);
else
for i=1:length(idx_a)
fprintf(fid,'\n%s = DAE.y(%s.bus%s);', ...
Algeb.name{idx_a(i)},c_name,num_a{i});
end
end
end
end
for i=1:Param.n
fprintf(fid,'\n%s = %s.con(:,%d);',Param.name{i},c_name,pidx(i));
end
for i=1:n_xmax,
fprintf(fid,'\n%s = %s.con(:,%d);',State.limit{x_max(i),1}, ...
c_name,endp+i);
end
for i=1:n_xmin,
fprintf(fid,'\n%s = %s.con(:,%d);',State.limit{x_min(i),2}, ...
c_name,endp+n_xmax+i);
end
for i=1:n_smax,
fprintf(fid,'\n%s = %s.con(:,%d);',Servc.limit{s_max(i),1}, ...
c_name,endp+n_xmax+n_xmin+i);
end
for i=1:n_smin,
fprintf(fid,'\n%s = %s.con(:,%d);',Servc.limit{s_min(i),2}, ...
c_name,endp+n_xmax+n_xmin+n_smax+i);
end
for i=1:Initl.n,
fprintf(fid,'\n%s = %s.dat(:,%d);',Initl.name{i},c_name,i);
end
for i=1:nidx,
fprintf(fid,'\n%s = %s.dat(:,%d);',Servc.eqidx{iidx(i)},c_name, ...
Initl.n+i);
end
% **********************************************************************
% initialization
if Comp.init
fprintf(fid, '\n\nswitch flag\n case 0 %% initialization');
msg = ['Component'];
idx_T = [1:State.n];
idx = strmatch('None',State.time,'exact');
idx_T(idx) = [];
if idx_T
fprintf(fid,'\n\n %%check time constants');
end
for i=1:length(idx_T),
fprintf(fid,['\n idx = find(%s == 0);\n if idx\n ', ...
Comp.name,'warn(idx, ''Time constant %s ', ...
'cannot be zero. %s = 0.001 s will be used.''),\n ' ...
'end'],State.time{idx_T(i)}, ...
State.time{idx_T(i)},State.time{idx_T(i)});
fprintf(fid,'\n %s.con(idx,%d) = 0.001;', ...
c_name,pidx(strmatch(State.time{idx_T(i)}, ...
Param.name,'exact')));
end
fprintf(fid,'\n\n %%variable initialization');
for i=1:State.n,
fprintf(fid,'\n DAE.x(%s.%s) = %s;',c_name,State.name{i},state_init{i});
fprintf(fid,'\n %s = DAE.x(%s.%s);',State.name{i},c_name,State.name{i});
end
for i=1:nidx,
fprintf(fid,'\n %s.dat(:,%d) = %s;',Initl.n+i,c_name,vectorize(Servc.eq{i}));
fprintf(fid,'\n %s = %s.dat(:,%d);',Servc.eqidx{iidx(i)},c_name,Initl.n+i);
end
for i=1:Initl.n
fprintf(fid,'\n %s.dat(:,%d) = %s;',c_name,i, ...
strrep(Initl.name{i},'_0',''));
end
fprintf(fid,'\n\n %%check limits');
for i=1:n_xmax
fprintf(fid,['\n idx = find(%s > %s_max); if idx, ', ...
Comp.name,'warn(idx, '' State variable %s ', ...
'is over its maximum limit.''), end'], ...
State.name{x_max(i)},State.name{x_max(i)}, ...
State.name{x_max(i)});
end
for i=1:n_xmin
fprintf(fid,['\n idx = find(%s < %s_min); if idx, ', ...
Comp.name,'warn(idx, '' State variable %s ', ...
'is under its minimum limit.''), end'], ...
State.name{x_min(i)},State.name{x_min(i)}, ...
State.name{x_min(i)});
end
for i=1:n_smax
fprintf(fid,['\n idx = find(%s > %s_max); if idx, ', ...
Comp.name,'warn(idx, '' State variable %s ', ...
'is over its maximum limit.''), end'], ...
Servc.name{s_max(i)},Servc.name{s_max(i)}, ...
Servc.name{s_max(i)});
end
for i=1:n_smin
fprintf(fid,['\n idx = find(%s < %s_min); if idx, ', ...
Comp.name,'warn(idx, '' State variable %s ', ...
'is under its minimum limit.''), end'], ...
Servc.name{s_min(i)},Servc.name{s_min(i)}, ...
Servc.name{s_min(i)});
end
fprintf(fid,['\n fm_disp(''Initialization of ',c_name, ...
'components completed.'')\n']);
end
% **********************************************************************
% algebraic equations
if ~isempty(algeb_eq)
if Comp.init
fprintf(fid, '\n case 1 %% algebraic equations\n');
else
fprintf(fid, '\n\nswitch flag\n case 1 %% algebraic equations\n');
end
end
aidx = [1:Algeb.neq];
idx = strmatch('null',Algeb.eq);
aidx(idx) = [];
idx = strmatch('0',Algeb.eq);
aidx(idx) = [];
for i = 1:length(aidx)
if Buses.n == 1
a1 = '';
else
a1 = num2str(ceil(aidx(i)/2));
end
if rem(aidx(i),2)
fprintf(fid,'\n DAE.g = DAE.g + sparse(%s.bus%s,1,%s,DAE.m,1);', ...
c_name,a1,vectorize(Algeb.eq{aidx(i)}));
else
fprintf(fid,'\n DAE.g = DAE.g + sparse(%s.bus%s+Bus.n,1,%s,DAE.m,1);', ...
c_name,a1,vectorize(Algeb.eq{aidx(i)}));
end
end
% ********************************************************************
% algebraic Jacobians
% substitution of inner service variables
for j = 1:5
for i = 1:Servc.neq
if strcmp(Servc.type{i},'Inner') && ~strcmp(Servc.eq{i},'null')
state_eq = strrep(state_eq,Servc.eqidx{i},['(',Servc.eq{i},')']);
algeb_eq = strrep(algeb_eq,Servc.eqidx{i},['(',Servc.eq{i},')']);
servc_eq = strrep(servc_eq,Servc.eqidx{i},['(',Servc.eq{i},')']);
end
end
end
if ~isempty(algeb_eq)
fprintf(fid, '\n\n case 2 %% algebraic Jacobians\n');
end
eqformat = '\n DAE.J%d%d = DAE.J%d%d + sparse(%s.bus%s,%s.bus%s,%s,Bus.n,Bus.n);';
for j = 1:length(aidx)
i = aidx(j);
a1 = 2-rem(i,2);
if Buses.n == 1
a2 = '';
else
a2 = num2str(ceil(i/2));
end
for h = 1:Algeb.n
type = Algeb.name{h,1};
if strcmp(type(1), 'V');
a3 = 2;
if Buses.n == 1
a4 = '';
else
a4 = type(2:length(type));
end
elseif strcmp(type(1:5), 'theta');
a3 = 1;
if Buses.n == 1
a4 = '';
else
a4 = type(6:length(type));
end
end
if ~strcmp(char(Gy(i,h)),'0')
fprintf(fid,eqformat,a1,a3,a1,a3,c_name,a2,c_name,a4, ...
vectorize(char(Gy(i,h))));
end
end
end
% check limits in case of state variable dependancies
Temp = 0;
for i = 1:Servc.neq; Temp = ~strcmp(Servc.limit{i},'None'); break; end
S = 0;
if Temp
for i = 1:Servc.neq; S = ~strcmp(Servc.type{i},'Input'); break; end
end
if S
fprintf(fid,'\n');
for i = 1:length(Servc.eqidx)
s_var = Servc.eqidx{i};
for k = 1:Servc.neq; if strcmp(s_var,Servc.name{k}); break; end; end
if ~strcmp(Servc.type{k},'Input') && ~isempty(findstr(algeb_eq,s_var))
a = strcmp(Servc.limit{k,1},'None');
b = strcmp(Servc.limit{k,2},'None');
if ~a || ~b
fprintf(fid, ['\n if (']);
if ~a
fprintf(fid,[Servc.name{k},'(i) <= ',Servc.name{k},'_max(i)']);
else
fprintf(fid,'(');
end
if ~a && ~b
fprintf(fid,' || '); end
if ~b
fprintf(fid,[Servc.name{k},'(i) >= ',Servc.name{k},'_min(i))']);
else
fprintf(fid,')');
end
fprintf(fid,'\n end');
end
end
end
end
% *********************************************************************
% differential & service equations
if ~isempty(state_eq)
if Comp.init || ~isempty(algeb_eq)
fprintf(fid, '\n\n case 3 %% differential equations\n');
else
fprintf(fid, '\n\nswitch flag\n case 3 %% differential equations\n');
end
end
for i = 1:Servc.neq
Temp = Servc.type{i};
if strcmp(Temp,'Inner')
s_eq = vectorize(Servc.eq{i});
fprintf(fid,['\n ',Servc.name{i},' = ',s_eq,';']);
if ~strcmp(Servc.limit{i,1},'None')
fprintf(fid, ['\n ',Servc.name{i}, ...
' = min(',Servc.name{i},',',Servc.name{i},'_max);']);
end
if ~strcmp(Servc.limit{i,2},'None')
fprintf(fid, ['\n ',Servc.name{i}, ...
' = max(',Servc.name{i},',',Servc.name{i},'_min);']);
end
end
end
for i = 1:State.n
if strcmp(State.nodyn{i},'Yes')
fprintf(fid, ['\n no_dyn_',State.name{i},' = find(',State.time{i},' == 0);']);
fprintf(fid, ['\n ', State.time{i}, '(no_dyn_',State.name{i},') = 1;']);
end
if strcmp(State.time{i},'None')
s_eq = vectorize(State.eq{i});
else
s_eq = vectorize(['(',State.eq{i},')/',State.time{i}]);
end
fprintf(fid, ['\n DAE.f(',c_name,'.',State.name{i},') = ',s_eq,';']);
if strcmp(State.nodyn{i},'Yes')
fprintf(fid, ['\n DAE.f(',c_name,'.',State.name{i},'(no_dyn_',State.name{i},')) = 0;']);
end
end
if State.n > 0; if strcmp(State.nodyn{State.n},'Yes'); fprintf(fid, '\n'); end; end
% set hard limits
fprintf(fid,'\n %% non-windoup limits');
limfor1 = '\n idx = find(%s >= %s_max && DAE.f(%s) > 0);';
limfor2 = '\n if idx, DAE.f(%s(idx)) = 0; end';
limfor3 = '\n DAE.x(%s) = min(%s,%s_max);';
limfor4 = '\n idx = find(%s <= %s_min && DAE.f(%s) < 0);';
limfor5 = '\n DAE.x(%s) = max(%s,%s_min);';
for i = 1:State.n
varidx = [c_name,'.',State.name{i}];
a = strcmp(State.limit{i,1},'None');
if ~a
fprintf(fid,limfor1,State.name{i},State.name{i},varidx);
fprintf(fid,limfor2,State.name{i});
fprintf(fid,limfor3,varidx,State.name{i},State.name{i});
end
b = strcmp(State.limit{i,2},'None');
if ~b
fprintf(fid,limfor4,State.name{i},State.name{i},varidx);
fprintf(fid,limfor2,State.name{i});
fprintf(fid,limfor5,varidx,State.name{i},State.name{i});
end
end
fprintf(fid, '\n');
numdata = Initl.n;
for i = 1:Servc.neq
Temp = Servc.type{i};
if okdata && strcmp(Temp,'Inner')
numdata = numdata + 1;
fprintf(fid,['\n ',c_name,'.dat(:,',int2str(numdata),') = ', Servc.name{i},';']);
elseif strcmp(Temp,'Output')
numdata = numdata + 1;
s_eq = vectorize(Servc.eq{i});
TempT = [c_name,'.dat(:,',int2str(numdata),')'];
fprintf(fid,['\n ',TempT,' = ',s_eq,';']);
zz = ['z(',Servc.name{i},'_',Comp.name,'_idx)'];
if ~strcmp(Servc.limit{i,1},'None')
fprintf(fid, ['\n ',TempT,' = min(',TempT,',',Servc.name{i},'_max);']);
end
if ~strcmp(Servc.limit{i,2},'None')
fprintf(fid, ['\n ',TempT,' = max(',TempT,',',Servc.name{i},'_min);']);
end
fprintf(fid,['\n ',zz,' = ',zz,' + ',TempT,';']);
end
end
fprintf(fid, '\n');
% *********************************************************************
% state variable Jacobians
if ~isempty(state_eq)
fprintf(fid, '\n\n case 4 %% state variable Jacobians\n');
end
% DAE.Fx
for j = 1:State.n
if strcmp(State.nodyn{j},'Yes')
fprintf(fid, ['\n no_dyn_',State.name{j},' = find(',State.time{j},' == 0);']);
fprintf(fid, ['\n ', State.time{j}, '(no_dyn_',State.name{j},') = 1;']);
end
end
fprintf(fid, '\n');
if State.n, fprintf(fid,'\n %% DAE.Fx'); end
fxformat = '\n DAE.Fx = DAE.Fx + sparse(%s,%s,%s,DAE.n,DAE.n);';
for j = 1:State.n
x_idx1 = [c_name,'.',State.name{j}];
for i = 1:State.n
x_idx2 = [c_name,'.',State.name{i}];
if strcmp(State.time{j},'None') && ~strcmp(char(Fx(j,i)),'0')
fxexp = vectorize(char(Fx(j,i)));
else
fxexp = ['(',vectorize(char(Fx(j,i))),')./',State.time{j}];
end
if ~strcmp(fxexp,['(0)./',State.time{j}])
fprintf(fid,fxformat,x_idx1,x_idx2,fxexp);
end
end
end
fprintf(fid,'\n');
% DAE.Fy
if State.n && Algeb.n, fprintf(fid,'\n %% DAE.Fy'); end
fyformat = '\n DAE.Fy = DAE.Fy + sparse(%s,%s,%s,DAE.n,DAE.m);';
for j = 1:State.n
x_idx1 = [c_name,'.',State.name{j}];
for i = 1:Algeb.n
type = Algeb.name{i};
if strcmp(type(1),'V')
if Buses.n == 1
x_idx2 = [c_name,'.bus','','+Bus.n'];
else
x_idx2 = [c_name,'.bus',type(2:length(type)),'+Bus.n'];
end
elseif strcmp(type(1:5),'theta')
if Buses.n == 1
x_idx2 = [c_name,'.bus',''];
else
x_idx2 = [c_name,'.bus',type(6:length(type))];
end
end
if strcmp(State.time{j},'None') && ~strcmp(char(Fy(j,i)),'0')
fyexp = vectorize(char(Fy(j,i)));
else
fyexp = ['(',vectorize(char(Fy(j,i))),')./',State.time{j}];
end
if ~strcmp(fyexp,['(0)./',State.time{j}])
fprintf(fid,fyformat,x_idx1,x_idx2,fyexp);
end
end
end
fprintf(fid,'\n');
% DAE.Gx
if State.n && Algeb.n, fprintf(fid,'\n %% DAE.Gx'); end
gxformat = '\n DAE.Gx = DAE.Gx + sparse(%s,%s,%s,DAE.m,DAE.n);';
for j = 1:Algeb.neq
if ~strcmp(Algeb.eq{1},'null')
type = Algeb.eqidx{j,1};
if strcmp(type(1),'P')
if Buses.n == 1
a_idx = [c_name,'.bus',''];
else
a_idx = [c_name,'.bus',type(2:length(type))];
end
elseif strcmp(type(1),'Q')
if Buses.n == 1
a_idx = [c_name,'.bus','','+Bus.n'];
else
a_idx = [c_name,'.bus',type(2:length(type)),'+Bus.n'];
end
end
for h = 1:State.n
x_idx = [c_name,'.',State.name{h}];
algexp = vectorize(char(Gx(j,h)));
if ~strcmp(algexp,'0')
fprintf(fid,gxformat,a_idx,x_idx,algexp);
end
end
end
end
%if State.n > 0, fprintf(fid, ['\n\n end']); end
% ***************************************************************
% non-windup limiters
if n_xmax || n_xmin
fprintf(fid, '\n\n case 5 %% non-windup limiters\n');
for i = 1:State.n
M = ~strcmp(State.limit{i,1},'None');
m = ~strcmp(State.limit{i,2},'None');
if M || m
fprintf(fid, ['\n idx = find((']);
if M, fprintf(fid,'%s >= %s_max',State.name{i},State.name{i}); end
if M && m; fprintf(fid,' || '); end
if m, fprintf(fid,'%s <= %s_min',State.name{i},State.name{i}); end
fprintf(fid,[') && DAE.f(',c_name,'.%s) == 0);'],State.name{i});
fprintf(fid, '\n if ~isempty(idx)');
fprintf(fid,['\n k = ',c_name,'.%s(idx);'],State.name{i});
fprintf(fid,['\n DAE.tn(k) = 0;']);
fprintf(fid,['\n DAE.Ac(:,k) = 0;']);
fprintf(fid,['\n DAE.Ac(k,:) = 0;']);
fprintf(fid,['\n DAE.Ac = DAE.Ac - sparse(k,k,1,DAE.m+DAE.n,DAE.m+DAE.n);']);
fprintf(fid,['\n end']);
end
end
end
fprintf(fid, '\n\nend\n');
% *******************************************************************
% warning message function
fprintf(fid,'\n\n%% -------------------------------------------------------------------');
fprintf(fid,'\n%% function for creating warning messages');
fprintf(fid,['\nfunction ',Comp.name,'warn(idx, msg)']);
%fprintf(fid,['\nglobal ',c_name]);
fprintf(fid,['\nfm_disp(fm_strjoin(''Warning: ',upper(Comp.name),' #'',int2str(idx),msg))']);
% close component file and return
fclose(fid);
fm_choice(['Function "fm_',Comp.name,'" built.'],2)
% ****************************************************************
function vect = varvect(vect,sep)
n = length(sep)-1;
if iscell(vect)
vect = fm_strjoin(vect,'#');
vect = strrep([vect{:}],'#',sep);
vect(end-n:end) = [];
end
|
github
|
Sinan81/PSAT-master
|
symfault.m
|
.m
|
PSAT-master/psat-oct/psat/symfault.m
| 4,578 |
utf_8
|
7a0f660fadb898109463adb029ac24ae
|
% The program symfault is designed for the balanced three-phase
% fault analysis of a power system network. The program requires
% the bus impedance matrix Zbus. Zbus may be defined by the
% user, obtained by the inversion of Ybus or it may be
% determined either from the function Zbus = zbuild(zdata)
% or the function Zbus = zbuildpi(linedata, gendata, yload).
% The program prompts the user to enter the faulted bus number
% and the fault impedance Zf. The prefault bus voltages are
% defined by the reserved Vector V. The array V may be defined or
% it is returned from the power flow programs lfgauss, lfnewton,
% decouple or perturb. If V does not exist the prefault bus voltages
% are automatically set to 1.0 per unit. The program obtains the
% total fault current, the postfault bus voltages and line currents.
%
% Copyright (C) 1998 H. Saadat
function symfault(zdata, Zbus, V)
fm_var
if ~autorun('Short Circuit Analysis',0)
return
end
if isempty(Fault.con)
fm_disp('No fault found', 2)
return
end
zdata = Line.con;
[Zbus, zdata]= zbuildpi(zdata, Syn.con);
nl = zdata(:,1);
nr = zdata(:,2);
R = zdata(:,3);
X = zdata(:,4);
nc = length(zdata(1,:));
if nc > 4
BC = zdata(:,11);
elseif nc == 4
BC = zeros(length(zdata(:,1)), 1);
end
ZB = R + j*X
nbr = length(zdata(:,1));
nbus = max(max(nl), max(nr));
if exist('V') == 1
if length(V) == nbus
V0 = V;
end
else
V0 = ones(nbus, 1) + j*zeros(nbus, 1);
end
fprintf('\nThree-phase balanced fault analysis \n')
for ff = 1:Fault.n
nf = Fault.bus(ff);
fprintf('Faulted bus No. = %g \n', nf)
fprintf('\n Fault Impedance Zf = R + j*X = ')
Zf = Fault.con(ff,7) + j*Fault.con(ff,8);
fprintf('%8.5f + j(%8.5f) \n', real(Zf), imag(Zf))
fprintf('Balanced three-phase fault at bus No. %g\n', nf)
If = V0(nf)/(Zf + Zbus(nf, nf));
Ifm = abs(If);
Ifmang = angle(If)*180/pi;
fprintf('Total fault current = %8.4f per unit \n\n', Ifm)
fprintf('Bus Voltages during fault in per unit \n\n')
fprintf(' Bus Voltage Angle\n')
fprintf(' No. Magnitude degrees\n')
for n = 1:nbus
if n == nf
Vf(nf) = V0(nf)*Zf/(Zf + Zbus(nf,nf));
Vfm = abs(Vf(nf));
angv = angle(Vf(nf))*180/pi;
else
Vf(n) = V0(n) - V0(n)*Zbus(n,nf)/(Zf + Zbus(nf,nf));
Vfm = abs(Vf(n));
angv=angle(Vf(n))*180/pi;
end
fprintf(' %4g', n), fprintf('%13.4f', Vfm),fprintf('%13.4f\n', angv)
end
fprintf(' \n')
fprintf('Line currents for fault at bus No. %g\n\n', nf)
fprintf(' From To Current Angle\n')
fprintf(' Bus Bus Magnitude degrees\n')
for n = 1:nbus
%Ign=0;
for I = 1:nbr
if nl(I) == n || nr(I) == n
if nl(I) == n
k = nr(I);
elseif nr(I) == n
k = nl(I);
end
if k==0
Ink = (V0(n) - Vf(n))/ZB(I);
Inkm = abs(Ink);
th = angle(Ink);
%if th <= 0
if real(Ink) > 0
fprintf(' G '), fprintf('%7g',n), fprintf('%12.4f', Inkm)
fprintf('%12.4f\n', th*180/pi)
elseif real(Ink) ==0 && imag(Ink) < 0
fprintf(' G '), fprintf('%7g',n), fprintf('%12.4f', Inkm)
fprintf('%12.4f\n', th*180/pi)
end
Ign = Ink;
elseif k ~= 0
Ink = (Vf(n) - Vf(k))/ZB(I)+BC(I)*Vf(n);
%Ink = (Vf(n) - Vf(k))/ZB(I);
Inkm = abs(Ink); th=angle(Ink);
%Ign=Ign+Ink;
%if th <= 0
if real(Ink) > 0
fprintf('%7g', n)
fprintf('%10g', k),
fprintf('%12.4f', Inkm)
fprintf('%12.4f\n', th*180/pi)
elseif real(Ink) ==0 && imag(Ink) < 0
fprintf('%7g', n)
fprintf('%10g', k),
fprintf('%12.4f', Inkm)
fprintf('%12.4f\n', th*180/pi)
end
end
end
end
if n == nf % show Fault Current
fprintf('%7g',n)
fprintf(' F')
fprintf('%12.4f', Ifm)
fprintf('%12.4f\n', Ifmang)
end
end
resp=0;
%while strcmp(resp, 'n')~=1 && strcmp(resp, 'N')~=1 && strcmp(resp, 'y')~=1 && strcmp(resp, 'Y')~=1
%resp = input('Another fault location? Enter ''y'' or ''n'' within single quote -> ');
%if strcmp(resp, 'n')~=1 && strcmp(resp, 'N')~=1 && strcmp(resp, 'y')~=1 && strcmp(resp, 'Y')~=1
%fprintf('\n Incorrect reply, try again \n\n'), end
%end
%if resp == 'y' || resp == 'Y'
nf = 999;
%else
ff = 0;
%end
end % end for while
fm_disp(['Finished "',filedata,'"']),
|
github
|
Sinan81/PSAT-master
|
fm_plot.m
|
.m
|
PSAT-master/psat-oct/psat/fm_plot.m
| 30,010 |
utf_8
|
916052824f8021af416d6d8bd704c7d7
|
function fm_plot(flag)
% FM_PLOT plot results of Continuation Power Flow,
% Optimal Power Flow and Time Domain
% Simulations.
%
% FM_PLOT(FLAG)
% FLAG 0 -> create variable list
% 1 -> plot selected variables
% 2 -> save graph
% 3 -> set layout
%
%Author: Federico Milano
%Date: 11-Nov-2002
%Update: 25-Feb-2003
%Update: 26-Jan-2005
%Version: 1.0.2
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2019 Federico Milano
global DAE Bus Syn Settings Fig Snapshot Hdl CPF Theme
global Varout Varname Path File OPF Line Mass SSR Pmu
%hdls = get(Fig.plot, 'Children')
%display(hdls)
hdlfig = findobj(Fig.plot, 'Tag','Axes1');
hdlfig2 = findobj(Fig.plot, 'Tag','Axes2');
Hdl_grid = findobj(Fig.plot,'Tag','Checkbox1');
Hdl_legend = findobj(Fig.plot,'Tag','Checkbox2');
Hdl_listvar = findobj(Fig.plot,'Tag','Listbox1');
Hdl_listplot = findobj(Fig.plot,'Tag','Listbox2');
Hdl_tipoplot = findobj(Fig.plot,'Tag','PopupMenu1');
Hdl_angref = findobj(Fig.plot,'Tag','PopupMenu2');
Hdl_snap = findobj(Fig.plot,'Tag','Radiobutton1');
hdl_zoom1 = findobj(Fig.plot,'Tag','Pushbutton12');
hdl_zoom2 = findobj(Fig.plot,'Tag','Pushbutton11');
hdl_zoom3 = findobj(Fig.plot,'Tag','Pushbutton4');
hdl_x = findobj(Fig.plot,'Tag','Pushbutton9');
hdl_y = findobj(Fig.plot,'Tag','Pushbutton5');
hdl_xy = findobj(Fig.plot,'Tag','Pushbutton10');
switch flag
case 'exporttext', % output data as plain text file
flag = 'plotvars';
out_matlab = 0;
out_mtv = 0;
out_text = 1;
case 'exportmtv', % output data as plain text file
flag = 'plotvars';
out_matlab = 0;
out_mtv = 1;
out_text = 0;
case 'exportscript', % output data as plain text file
flag = 'plotvars';
out_matlab = 1;
out_mtv = 0;
out_text = 0;
otherwise
out_matlab = 0;
out_mtv = 0;
out_text = 0;
end
switch flag
case 'initlist'
if ~strcmp(get(Fig.plot,'UserData'),File.modify)
set(Hdl_listvar, ...
'String',enum(Varname.uvars(Varout.idx)), ...
'Value',1);
if Settings.hostver < 8.04
set(Fig.plot,'DefaultAxesColorOrder',Settings.color, ...
'DefaultAxesLineStyle','-');
end
end
set(Fig.plot,'UserData',File.modify)
Varname.pos = 1;
case 'initxlabel'
first = strrep(Settings.xlabel,'\','');
hdl = findobj(Fig.plot,'Tag','Listbox1');
stringa = get(hdl,'String');
hdl = findobj(Fig.plot,'Tag','PopupMenu3');
if ~isempty(stringa)
set(hdl,'String',[{first}; stringa],'Enable','on','Value',1)
end
case 'plotvars'
if isempty(Varout.t)
fm_disp('Plotting Utilities: No data available for plotting.')
return
end
if isempty(Varname.pos)
fm_disp('Plotting Utilities: Select variables to be plotted.')
return
end
nB = Bus.n;
nD = DAE.n;
Value = get(Hdl_listvar,'Value');
if isempty(Value), return, end
hdlfig = findobj(Fig.plot, 'Tag', 'Axes1');
AxesFont = get(hdlfig,'FontName');
%AxesColor = get(hdlfig,'Color');
%if ~length(AxesColor)
AxesColor = [1, 1, 1];
%end
AxesWeight = get(hdlfig,'FontWeight');
AxesAngle = get(hdlfig,'FontAngle');
AxesSize = get(hdlfig,'FontSize');
AxesUnits = get(hdlfig,'FontUnits');
plot_snap = get(Hdl_snap,'Value');
snap_idx = zeros(length(Snapshot),1);
if plot_snap && ~OPF.init
for i = 1:length(Snapshot);
a = find(Varout.t == Snapshot(i).time);
if isempty(a)
fm_disp('Plotting utilities: Snapshots do not match current simulation data',2)
Hdl_rad1 = findobj(gcf,'Tag','Radiobutton1');
set(Hdl_rad1,'Value',0);
plot_snap = 0;
break
else
snap_idx(i) = a;
end
end
end
legenda = Varname.fvars(Varout.idx(Value(Varname.pos)));
leg_value = get(Hdl_legend,'Value');
hdlab = findobj(Fig.plot,'Tag','PopupMenu3');
AbValue = get(hdlab,'Value');
Y = Varout.vars(:,Value);
if isempty(Y), return, end
% set angle unit
if Settings.usedegree
kdx = get_angle_idx(Value);
Y(:,kdx) = 180*Y(:,kdx)/pi;
end
% set rotor speed unit and values
if Settings.usehertz || Settings.userelspeed
kdx = get_rotor_idx(Value);
if Settings.userelspeed
Y(:,kdx) = Y(:,kdx)-1;
end
if Settings.usehertz
Y(:,kdx) = Settings.freq*Y(:,kdx);
end
end
% set reference angle
if ~OPF.init
ang_idx = get(Hdl_angref,'Value')-1;
if ~ang_idx
angolo = zeros(length(Varout.t),1);
else
ref_idx = get(Hdl_angref,'UserData');
ang_ref = ref_idx(ang_idx);
angolo = Varout.vars(:,ang_ref);
end
for i = 1:length(Value)
kk = Varout.idx(Value(i));
if isdelta_syn(Syn,kk) || isdelta_mass(Mass,kk) || isdelta_ssr(SSR,kk) || isdelta_pmu(Pmu,kk)
Y(:,i) = Y(:,i) - angolo;
elseif kk >= nD+1 && kk <= nD+nB
Y(:,i) = Y(:,i) - angolo;
end
end
end
hdlnorm = findobj(Fig.plot,'Tag','NormSij');
if strcmp(get(hdlnorm,'Checked'),'on')
for i = 1:length(Value)
kk = Varout.idx(Value(i));
Y(:,i) = isflow_line(Line,Y(:,i),kk);
end
end
if AbValue == 1
X = Varout.t;
else
X = Varout.vars(:,AbValue-1);
% set angle unit
check = get_angle_idx(AbValue-1);
if Settings.usedegree && ~isempty(check)
X = 180*X/pi;
end
% set rotor speed unit and values
if Settings.usehertz || Settings.userelspeed
check = get_rotor_idx(AbValue-1);
if Settings.userelspeed && check
X = X-1;
end
if Settings.usehertz && check
X = Settings.freq*X;
end
end
end
tipoplot = get(Hdl_tipoplot,'Value');
if out_text
plainfile = fm_filenum('txt');
fid = fopen([Path.data,plainfile,'.txt'],'wt');
if fid == -1
fm_disp('Cannot open file. Data not saved.')
return
end
fprintf(fid,'C Legend:\n');
fprintf(fid,'C %s, ',Settings.xlabel);
for i = 1:size(Y,2)
fprintf(fid,'%s, ',legenda{i});
end
fprintf(fid,'\nC Data:\n');
fprintf(fid,[repmat('%8.5f ',1,1+size(Y,2)),'\n'],[X,Y]');
fclose(fid);
fm_disp(['Data exported to plain text file "',plainfile,'.txt"'])
end
if out_mtv
plainfile = fm_filenum('mtv');
fid = fopen([Path.data,plainfile,'.mtv'],'wt');
if fid == -1
fm_disp('Cannot open file. Data not saved.')
return
end
%fprintf(fid,'$ DATA=CURVE2D\n');
fprintf(fid,'%% xlabel = "%s"\n',Settings.xlabel);
if min(X) < max(X)
fprintf(fid,'%% xmin = %8.5f\n',min(X));
fprintf(fid,'%% xmax = %8.5f\n',max(X));
end
fprintf(fid,'\n');
if tipoplot == 3 || tipoplot == 6
fm_disp('MTV format does not support numbered plots.')
end
for i = 1:size(Y,2)
labelmtv = strrep(legenda{i},'{','');
labelmtv = strrep(labelmtv,'}','');
labelmtv = strrep(labelmtv,'_',' ');
labelmtv = strrep(labelmtv,'\','');
fprintf(fid,'%% linelabel="%s"\n',labelmtv);
switch tipoplot
case 2
linetype = rem(i-1,10)+1;
linecolor = 1;
markertype = 0;
markercolor = 1;
case 4
linetype = 1;
linecolor = 1;
markertype = rem(i-1,13)+1;
markercolor = 1;
case 5
linetype = 1;
linecolor = rem(i-1,10)+1;
markertype = rem(i-1,13)+1;
markercolor = linecolor;
otherwise
linetype = 1;
linecolor = rem(i-1,10)+1;
markertype = 0;
markercolor = 1;
end
fprintf(fid,'%% linetype=%d linecolor=%d markertype=%d markercolor=%d\n', ...
linetype,linecolor,markertype,markercolor);
fprintf(fid,'%8.5f %8.5f\n',[X,Y(:,i)]');
fprintf(fid,'\n');
end
fclose(fid);
fm_disp(['Data exported to MTV plot file "',plainfile,'.mtv"'])
end
if out_matlab
plainfile = fm_filenum('m');
fid = fopen([Path.data,plainfile,'.m'],'wt');
if fid == -1
fm_disp('Cannot open file. Data not saved.')
return
end
fprintf(fid,'x_label = ''%s'';\n',Settings.xlabel);
fprintf(fid,'\nvar_legend = {');
for i = 1:size(Y,2)-1
fprintf(fid,'''%s'', ',legenda{i});
end
fprintf(fid,'''%s''};\n',legenda{end});
fprintf(fid,'\noutput_data = [ ...\n');
fprintf(fid,[repmat('%8.5f ',1,1+size(Y,2)),';\n'], ...
[X(1:end-1),Y(1:end-1,:)]');
fprintf(fid,[repmat('%8.5f ',1,1+size(Y,2)),'];\n'], ...
[X(end),Y(end,:)]');
fclose(fid);
fm_disp(['Data exported to plain text file "',plainfile,'.m"'])
end
set(Fig.plot,'CurrentAxes',hdlfig);
plot(X,Y(:,Varname.pos));
set(hdlfig, 'Tag', 'Axes1')
if AbValue == 1
xlabel(Settings.xlabel);
else
xlabel(Varname.fvars{Varout.idx(AbValue-1)});
end
if min(X) < max(X)
set(hdlfig,'XLim',[min(X),max(X)])
end
%legend
if leg_value == 1 || Settings.hostver >= 7
if Settings.hostver >= 8.04
hleg = legend(legenda, 'Location', 'northeast');
else
hleg = legend(legenda, 0);
end
Hdl.legend = hleg;
set(hleg,'Color',AxesColor)
hchild = get(hleg,'Child');
if ishandle(hchild)
set(hchild(end), ...
'FontName',AxesFont, ...
'FontWeight',AxesWeight, ...
'FontAngle',AxesAngle)
end
end
hdlfig = findobj(Fig.plot, 'Tag', 'Axes1');
% display(hdlfig)
% axes(hdlfig)
if tipoplot == 3 || tipoplot == 6
[quanti,tanti] = size(Y);
colori = get(gcf,'DefaultAxesColorOrder');
for i = 1:tanti
if plot_snap
sequenza = snap_idx;
else
tmin = min(X);
tmax = max(X);
deltat = (tmax-tmin)/5;
tmin = tmin + i*(tmax-tmin)/43;
seqt = tmin:deltat:tmax;
for j = 1:length(seqt),
[valt, sequenza(j)] = min(abs(X-seqt(j)));
end
end
hdl = text(X(sequenza),Y(sequenza,i),num2str(Varname.pos(i)));
if tipoplot == 6,
set(hdl,'Color',colori(rem(i-1,7)+1,:));
end
end
if leg_value == 1 || Settings.hostver >= 7
hdl = findobj(Fig.plot,'Tag','legend');
%get(hdl)
oldh = gca;
set(gca,'HandleVisibility','off')
set(hdl,'Interruptible','on')
h = findobj(hdl,'Type','line');
%get(hdl)
for i = 1:tanti
j = i*2;
xdata = get(h(j),'XData');
ydata = get(h(j),'YData');
htext = text((xdata(2)-xdata(1))/2,ydata(1), ...
int2str(tanti-i+1));
set(htext,'Color',get(h(j),'Color'));
end
set(oldh,'HandleVisibility','on')
set(Fig.plot,'CurrentAxes',oldh);
end
elseif tipoplot == 4 || tipoplot == 5
[quanti,tanti] = size(Y);
hold on
simboli = {'o';'s';'d';'v';'^';'<';'>';'x'};
colori = get(Fig.plot,'DefaultAxesColorOrder');
for i = 1:tanti
if plot_snap
sequenza = snap_idx;
if tanti == 1 && CPF.init
y1 = get(hdlfig,'YLim');
yoff = 0.05*(y1(2)-y1(1));
for hh = 1:length(sequenza)
text(X(sequenza(hh)), ...
Y(sequenza(hh),Varname.pos(i))+yoff, ...
Snapshot(hh).name)
end
end
else
tmin = min(X);
tmax = max(X);
deltat = (tmax-tmin)/5;
tmin = tmin + i*(tmax-tmin)/43;
seqt = tmin:deltat:tmax;
for j = 1:length(seqt),
[valt, sequenza(j)] = min(abs(X-seqt(j)));
end
end
set(hdlfig,'LineStyle',simboli{rem(i-1,8)+1}, 'Tag', 'Axes1');
hmarker = plot(X(sequenza),Y(sequenza,Varname.pos(i)));
set(hmarker,'MarkerSize',7,'MarkerFaceColor',AxesColor);
if tipoplot == 5,
set(hmarker,'Color',colori(rem(i-1,7)+1,:));
end
end
hold off;
if leg_value == 1 || Settings.hostver >= 7
hdl = findobj(Fig.plot,'Tag','legend');
set(Fig.plot,'CurrentAxes',hdl);
h = findobj(hdl,'Type','line');
for i = 1:tanti
j = i*2;
xdata = get(h(j),'XData');
ydata = get(h(j),'YData');
set(hdl,'LineStyle',simboli{rem(tanti-i,8)+1});
if Settings.hostver >= 7
hmarker = plot(hdl,(xdata(2)-xdata(1))/1.2,ydata(1));
else
hmarker = plot((xdata(2)-xdata(1))/1.2,ydata(1));
end
set(hmarker,'MarkerSize',7, ...
'Color',get(h(j),'Color'), ...
'MarkerFaceColor',AxesColor);
end
set(Fig.plot,'CurrentAxes',hdlfig);
end
end
if get(Hdl_grid,'Value'); grid on; end
if ~get(Hdl_legend,'Value') && Settings.hostver >= 7 && Settings.hostver < 8.04
legend(findobj(Fig.plot,'Tag','Axes1'),'hide')
end
set(get(hdlfig,'XLabel'), ...
'FontName',AxesFont, ...
'FontWeight',AxesWeight, ...
'FontAngle',AxesAngle, ...
'FontSize',AxesSize, ...
'FontUnits',AxesUnits)
set(hdlfig, ...
'FontName',AxesFont, ...
'Color',AxesColor, ...
'FontWeight',AxesWeight, ...
'FontAngle',AxesAngle, ...
'FontSize',AxesSize, ...
'FontUnits',AxesUnits, ...
'Tag','Axes1')
if ishandle(Fig.line), fm_plot('createlinelist'), end
if get(hdl_x, 'Value'), fm_plot('axesx'), end
if get(hdl_y, 'Value'), fm_plot('axesy'), end
if get(hdl_xy,'Value'), fm_plot('axesxy'), end
fm_plot plotvlims
fm_plot plotslims
set(hdlfig,'Position',[0.09 0.4050 0.4754 0.5000], 'Tag', 'Axes1')
%display('ciao')
%display(hdlfig)
case 'export' % export the figure to file
tag = get(gcbo,'Tag');
axs_pos = get(Hdl.axesplot,'Position');
fig_pos = get(Fig.plot,'Position');
pap_pos = get(Fig.plot,'PaperPosition');
pap_siz = get(Fig.plot,'PaperSize');
leg_value = get(Hdl_legend,'Value');
if leg_value
pos_leg = get(Hdl.legend,'Position');
end
shrink = 0.8; % axes scale factor
set(Hdl.axesplot,'Position',[0.13 0.11 0.855 0.875])
set(Fig.plot,'Position',[fig_pos(1), fig_pos(2), ...
fig_pos(3)*shrink, fig_pos(4)*shrink])
if leg_value
pos_leg2(1) = 0.13 + 0.855*(pos_leg(1) - axs_pos(1))/axs_pos(3);
pos_leg2(2) = 0.11 + 0.875*(pos_leg(2) - axs_pos(2))/axs_pos(4);
pos_leg2(3) = pos_leg(3)*0.855/axs_pos(3);
pos_leg2(4) = pos_leg(4)*0.875/axs_pos(4);
set(Hdl.legend,'Position',pos_leg2);
if pos_leg2(1)+pos_leg2(3) > 0.985
Resize = (pos_leg2(1)+pos_leg2(3))/0.985;
fig_pos2 = [0.13 0.11 0.855 0.875];
fig_pos2(3) = fig_pos2(3)/Resize;
fig_pos2(1) = fig_pos2(1)/Resize;
pos_leg2(3) = pos_leg2(3)/Resize;
pos_leg2(1) = pos_leg2(1)/Resize;
set(Hdl.axesplot,'Position',fig_pos2)
set(Hdl.legend,'Position',pos_leg2)
end
end
if Settings.hostver > 5.03,
set(Fig.plot,'PaperSize',[pap_siz(1)*shrink, pap_siz(2)*shrink])
end
ppos(3) = pap_pos(3)*shrink;
ppos(4) = pap_pos(4)*shrink;
ppos(1) = (pap_siz(1)-ppos(3))/2;
ppos(2) = (pap_siz(2)-ppos(4))/2;
set(Fig.plot,'PaperPosition',ppos)
ax2_pos = get(Hdl.axeslogo,'Position');
set(Hdl.axeslogo,'Position',[10 10 0.2 0.2]);
Hdl_all = get(Fig.plot,'Children');
idx = find(Hdl_all==Hdl.axesplot);
if idx, Hdl_all(idx) = []; end
idx = find(Hdl_all==Hdl.axeslogo);
if idx, Hdl_all(idx) = []; end
if leg_value,
idx = find(Hdl_all==Hdl.legend);
if idx, Hdl_all(idx) = []; end
end
set(Hdl_all,'Visible','off');
lastwarn('')
switch tag
case 'PushEPS'
nomefile = fm_filenum('eps');
print(Fig.plot,'-depsc',[Path.data,nomefile])
set(hdlfig,'Position',axs_pos);
set(hdlfig2,'Position',ax2_pos);
set(Fig.plot,'Position',fig_pos)
set(Fig.plot,'PaperPosition',pap_pos)
if Settings.hostver > 5.03,
set(Fig.plot,'PaperSize',pap_siz)
end
set(Hdl_all,'Visible','on');
if leg_value
set(Hdl.legend,'Position',pos_leg);
end
case 'PushMeta'
print(Fig.plot,'-dmeta')
set(hdlfig,'Position',axs_pos);
set(hdlfig2,'Position',ax2_pos);
set(Fig.plot,'Position',fig_pos)
set(Fig.plot,'PaperPosition',pap_pos)
if Settings.hostver > 5.03,
set(Fig.plot,'PaperSize',pap_siz)
end
set(Hdl_all,'Visible','on');
if leg_value
set(Hdl.legend,'Position',pos_leg);
end
case 'PushFig'
figplot = Fig.plot;
Fig.plot = -1;
try
figpos = get(0,'factoryFigurePosition');
axspos = get(0,'factoryAxesPosition');
figunit = get(0,'factoryFigureUnits');
axsunit = get(0,'factoryAxesUnits');
catch
figpos = [100 100 660 520];
axspos = [0.1300 0.1100 0.7750 0.8150];
figunit = 'pixels';
axsunit = 'normalized';
end
set(figplot, ...
'Units',figunit, ...
'Position',figpos, ...
'Menubar','figure', ...
'Name','', ...
'NumberTitle','on', ...
'CreateFcn','', ...
'DeleteFcn','', ...
'UserData',[], ...
'FileName','')
set(Hdl.axesplot,'Color',[1 1 1],'Units',axsunit,'Position',axspos)
if leg_value
set(Hdl.legend,'Color',[1 1 1])
end
delete(Hdl_all)
delete(hdlfig2)
fm_plotfig
figure(figplot)
end
if ~isempty(lastwarn) && ~strcmp(lastwarn,'File not found or permission denied')
fm_disp(lastwarn,2),
end
case 'plottypes'
tipoplot = get(Hdl_tipoplot,'Value');
if Settings.hostver < 8.04
switch tipoplot
case 1,
set(Fig.plot, ...
'DefaultAxesColorOrder',Settings.color, ...
'DefaultAxesLineStyleOrder','-');
case 2,
set(Fig.plot, ...
'DefaultAxesColorOrder',[ 0 0 0 ], ...
'DefaultAxesLineStyleOrder','-|-.|--|:');
case 3,
set(Fig.plot, ...
'DefaultAxesColorOrder',[ 0 0 0 ], ...
'DefaultAxesLineStyleOrder','-');
case 4,
set(Fig.plot, ...
'DefaultAxesColorOrder',[ 0 0 0 ], ...
'DefaultAxesLineStyleOrder','-');
otherwise,
set(Fig.plot, ...
'DefaultAxesColorOrder',Settings.color, ...
'DefaultAxesLineStyleOrder','-');
end
else
switch tipoplot
case 1,
set(Fig.plot, ...
'DefaultAxesColorOrder',Settings.color, ...
'DefaultAxesLineStyleOrder','-');
otherwise,
set(Fig.plot, ...
'DefaultAxesColorOrder',[ 0 0 0 ], ...
'DefaultAxesLineStyleOrder','-|-.|--|:');
end
end
fm_plot('plotvars')
case 'editvarname'
value = get(Hdl_listplot,'Value');
if ~isempty(get(Hdl_listplot,'String'))
valori = get(Hdl_listvar,'Value');
val = valori(Varname.pos(value));
stringa = Varname.fvars(Varname.idx);
nomeattuale = popupstr(Hdl_listplot);
idx = findstr(nomeattuale,']');
nomeattuale = nomeattuale(idx+2:end);
nomenuovo = fm_input('Input Formatted Text:', ...
'Legend Name',1,{stringa{val}});
if isempty(nomenuovo),
return,
end
Varname.fvars{Varname.idx(val)} = nomenuovo{1};
set(Fig.plot,'UserData',stringa);
fm_disp(['Formatted text of variable "', ...
nomeattuale,'" has been changed in "', ...
nomenuovo{1},'"'])
else
fm_disp('No variable selected')
end
case 'zoomy'
zoom yon
set(Fig.plot,'WindowButtonMotionFcn','fm_plot motion');
set(hdl_zoom1,'Value',0);
set(hdl_zoom2,'Value',0);
if get(hdl_zoom3,'Value')
Settings.zoom = 'zoom yon';
else
Settings.zoom = '';
zoom off
end
case 'axesy'
if get(hdl_x,'Value')
set(hdl_x,'Value',0)
delete(findobj(allchild(hdlfig),'UserData','x axis'))
end
if get(hdl_xy,'Value')
set(hdl_xy,'Value',0)
delete(findobj(allchild(hdlfig),'UserData','x axis'))
delete(findobj(allchild(hdlfig),'UserData','y axis'))
end
value = get(gcbo,'Value');
if value
ylim = get(hdlfig,'YLim');
hold on
h = plot([0 0],[ylim(1), ylim(2)],'k:');
set(h,'UserData','y axis')
hold off
else
hdl_child = allchild(hdlfig);
delete(findobj(hdl_child,'UserData','y axis'))
end
if ishandle(Fig.line), fm_plot('createlinelist'), end
case 'axescolor'
currentColor = get(hdlfig,'Color');
c = uisetcolor(currentColor);
if ~isequal(c,currentColor)
set(hdlfig,'Color',c)
hdl_line = findobj(allchild(hdlfig),'Type','line');
set(hdl_line,'MarkerFaceColor',c)
hlegend = findobj(Fig.plot,'Tag','legend');
set(hlegend,'Color',c)
end
case 'axesx'
if get(hdl_y,'Value')
set(hdl_y,'Value',0)
delete(findobj(allchild(hdlfig),'UserData','y axis'))
end
if get(hdl_xy,'Value')
set(hdl_xy,'Value',0)
delete(findobj(allchild(hdlfig),'UserData','y axis'))
delete(findobj(allchild(hdlfig),'UserData','x axis'))
end
value = get(gcbo,'Value');
if value
xlim = get(hdlfig,'XLim');
hold on
h = plot([xlim(1), xlim(2)], [0, 0],'k:');
set(h,'UserData','x axis')
hold off
else
hdl_child = allchild(hdlfig);
delete(findobj(hdl_child,'UserData','x axis'))
end
if ishandle(Fig.line), fm_plot('createlinelist'), end
case 'axesxy'
if get(hdl_x,'Value')
set(hdl_x,'Value',0)
delete(findobj(allchild(hdlfig),'UserData','x axis'))
end
if get(hdl_y,'Value')
set(hdl_y,'Value',0)
delete(findobj(allchild(hdlfig),'UserData','y axis'))
end
value = get(gcbo,'Value');
if value
xlim = get(hdlfig,'XLim');
ylim = get(hdlfig,'YLim');
hold on
h = plot([xlim(1), xlim(2)], [0, 0],'k:');
set(h,'UserData','x axis')
h = plot([0, 0],[ylim(1), ylim(2)],'k:');
set(h,'UserData','y axis')
hold off
else
hdl_child = allchild(hdlfig);
try
delete(findobj(hdl_child,'UserData','x axis'))
catch
% nothing to do
end
try
delete(findobj(hdl_child,'UserData','y axis'))
catch
% nothing to do
end
end
if ishandle(Fig.line), fm_plot('createlinelist'), end
case 'zoomx'
zoom xon
set(Fig.plot,'WindowButtonMotionFcn','fm_plot motion');
set(hdl_zoom1,'Value',0);
set(hdl_zoom3,'Value',0);
if get(hdl_zoom2,'Value')
Settings.zoom = 'zoom xon';
else
Settings.zoom = '';
zoom off
end
case 'zoomxy'
zoom on
set(Fig.plot,'WindowButtonMotionFcn','fm_plot motion');
set(hdl_zoom2,'Value',0);
set(hdl_zoom3,'Value',0);
if get(hdl_zoom1,'Value')
Settings.zoom = 'zoom on';
else
Settings.zoom = '';
zoom off
end
case 'moveup'
value = get(Hdl_listplot,'Value');
NameString = get(Hdl_listplot,'String');
Value = 1:length(NameString);
if value > 1
dummy = Varname.pos(value);
Varname.pos(value) = Varname.pos(value-1);
Varname.pos(value-1) = dummy;
dummy = Value(value);
Value(value) = Value(value-1);
Value(value-1) = dummy;
set(Hdl_listplot, ...
'String',NameString(Value), ...
'Value',value-1);
end
case 'movedown'
value = get(Hdl_listplot,'Value');
NameString = get(Hdl_listplot,'String');
Value = 1:length(NameString);
if value < length(Varname.pos) && ~isempty(NameString)
dummy = Varname.pos(value);
Varname.pos(value) = Varname.pos(value+1);
Varname.pos(value+1) = dummy;
dummy = Value(value);
Value(value) = Value(value+1);
Value(value+1) = dummy;
set(Hdl_listplot, ...
'String',NameString(Value), ...
'Value',value+1);
end
case 'togglegrid'
if get(gcbo,'Value')
grid on
else
grid off
end
case 'togglelegend'
if Settings.hostver >= 8.04
% axes(findobj(Fig.plot, 'Tag', 'Axes1'))
legend toggle
elseif Settings.hostver >= 7
legend(findobj(Fig.plot,'Tag','Axes1'),'toggle')
else
onoff = {'off','on'};
if strcmp(get(gcbo,'Tag'),'PushLegend')
set(Hdl_legend,'Value',~get(Hdl_legend,'Value'))
set(gcbo,'Checked',onoff{get(Hdl_legend,'Value')+1})
value = get(Hdl_legend,'Value');
else
hdl = findobj(Fig.plot,'Tag','PushLegend');
set(hdl,'Checked',onoff{get(gcbo,'Value')+1})
value = get(gcbo,'Value');
end
if value
fm_plot('plotvars')
else
legend off
end
end
case 'listvars'
Value = get(Hdl_listvar,'Value');
if isempty(Value), return, end
NameString = get(Hdl_listvar,'String');
if isempty(NameString), return, end
set(Hdl_listplot,'String',NameString(Value));
set(Hdl_listplot,'Value',1);
Varname.pos = 1:length(Value);
if strcmp(get(Fig.plot,'SelectionType'),'open'),
fm_plot('plotvars')
end
case 'listlines'
hdl = findobj(Fig.line,'Tag','Listbox1');
Value = get(hdl,'Value');
hdl_line = get(Fig.line,'UserData');
hdl_line = hdl_line(end:-1:1);
fm_linedlg(hdl_line(Value))
case 'createlinelist'
hdl_line = findobj(allchild(hdlfig),'Type','line');
variabili = get(Hdl_listplot,'String');
set(Fig.line,'UserData',hdl_line);
hdl_list = findobj(Fig.line,'Tag','Listbox1');
line_string = cell(length(hdl_line),1);
hdl_line = hdl_line(end:-1:1);
for i = 1:length(hdl_line)
if strcmp(get(hdl_line(i),'UserData'),'x axis')
line_string{i,1} = ['x axis ',fvar(i,4)];
elseif strcmp(get(hdl_line(i),'UserData'),'y axis')
line_string{i,1} = ['y axis ',fvar(i,4)];
elseif i <= length(variabili)
line_string{i,1} = ['line ',fvar(i,4),variabili{i}];
else
line_string{i,1} = ['symbol ',fvar(i,4), ...
variabili{i-length(variabili)}];
end
end
set(hdl_list,'String',line_string,'Value',1);
case 'axesprops'
fm_axesdlg(hdlfig)
case 'textprops'
TextProp = uisetfont;
if isstruct(TextProp)
set(hdlfig,TextProp)
set(get(hdlfig,'XLabel'),TextProp)
set(get(hdlfig,'YLabel'),TextProp)
set(get(hdlfig,'Title'),TextProp)
if get(Hdl_legend,'Value')
hlegend = findobj(Fig.plot,'Tag','legend');
hchild = get(hlegend,'Child');
set(hchild(end), ...
'FontName',TextProp.FontName, ...
'FontWeight', TextProp.FontWeight, ...
'FontAngle',TextProp.FontAngle)
end
end
case 'setxlabel'
value = get(gcbo,'Value');
set(gcbo,'Value',value(end))
if strcmp(get(Fig.plot,'SelectionType'),'open')
fm_plot('plotvars')
end
case 'setangles'
[idx,kdx] = get_angle_idx;
set(gcbo,'String',[{'None'}; Varname.uvars(idx)],'UserData',kdx)
case 'limits'
status = get(gcbo,'Checked');
switch status
case 'on'
set(gcbo,'Checked','off')
case 'off'
set(gcbo,'Checked','on')
end
fm_plot plotvars
case 'usedegrees'
status = get(gcbo,'Checked');
switch status
case 'on'
Settings.usedegree = 0;
set(gcbo,'Checked','off')
case 'off'
Settings.usedegree = 1;
set(gcbo,'Checked','on')
end
fm_plot plotvars
case 'usehertzs'
status = get(gcbo,'Checked');
switch status
case 'on'
Settings.usehertz = 0;
set(gcbo,'Checked','off')
case 'off'
Settings.usehertz = 1;
set(gcbo,'Checked','on')
end
fm_plot plotvars
case 'userelspeeds'
status = get(gcbo,'Checked');
switch status
case 'on'
Settings.userelspeed = 0;
set(gcbo,'Checked','off')
case 'off'
Settings.userelspeed = 1;
set(gcbo,'Checked','on')
end
fm_plot plotvars
case 'plotvlims'
hdl = findobj(Fig.plot,'Tag','PlotVLim');
value = get(hdl,'Checked');
if ~strcmp(value,'on'), return, end
xlimits = get(hdlfig,'XLim');
hold on
plot(hdlfig,[xlimits(1) xlimits(2)],[0.9 0.9],'k:')
plot(hdlfig,[xlimits(1) xlimits(2)],[1.1 1.1],'k:')
hold off
case 'plotslims'
hdl = findobj(Fig.plot,'Tag','NormSij');
value = get(hdl,'Checked');
if ~strcmp(value,'on'), return, end
xlimits = get(hdlfig,'XLim');
hold on
plot(hdlfig,[xlimits(1) xlimits(2)],[1.0 1.0],'k:')
hold off
case 'lowestv'
idx = find(Varname.idx > DAE.n+Bus.n && Varname.idx <= DAE.n+2*Bus.n);
if isempty(idx), return, end
out = Varout.vars(:,idx);
vals = min(out,[],1);
[y,jdx] = sort(vals);
if length(jdx) > 3, jdx = jdx(1:3); end
set(Hdl_listvar,'Value',idx(jdx));
fm_plot listvars
fm_plot plotvars
case 'highestv'
idx = find(Varname.idx > DAE.n+Bus.n && Varname.idx <= DAE.n+2*Bus.n);
if isempty(idx), return, end
out = Varout.vars(:,idx);
vals = max(out,[],1);
[y,jdx] = sort(vals,2,'descend');
if length(jdx) > 3, jdx = jdx(1:3); end
set(Hdl_listvar,'Value',idx(jdx));
fm_plot listvars
fm_plot plotvars
case 'highests'
values = highests_line(Line);
if isempty(values), return, end
set(Hdl_listvar,'Value',values);
fm_plot listvars
fm_plot plotvars
end
if ~isempty(Settings.zoom), eval(Settings.zoom), end
% ------------------------------------------------------------------------
% Some useful functions
% -----------------------------------------------------------------------
function stringa = enum(stringa)
for i = 1:length(stringa),
stringa{i} = ['[',int2str(i),'] ',stringa{i}];
end
function kdx = get_rotor_idx(idx)
global DAE Syn COI Cswt Dfig Ddsg Busfreq Mass SSR Tg
kdx = [];
for i = 1:length(idx)
kkk = idx(i);
if kkk > DAE.n+DAE.m
break
elseif kkk <= DAE.n
if isomega_syn(Syn,kkk) || isomega_cswt(Cswt,kkk) || isomega_dfig(Dfig,kkk) ...
|| isomega_ddsg(Ddsg,kkk) || isomega_mass(Mass,kkk) || isomega_ssr(SSR,kkk) ...
|| isomega_busfreq(Busfreq)
kdx = [kdx, i];
end
elseif isomega_coi(COI,kkk) || isomega_tg(Tg,kkk)
kdx = [kdx, i];
end
end
function varargout = get_angle_idx(varargin)
global Varout DAE Syn Bus COI Mass SSR Phs Svc Cswt Ddsg Dfig Pmu Hvdc
idx = [];
kdx = [];
if ~nargin
varidx = Varout.idx;
else
varidx = varargin{1};
end
for i = 1:length(varidx)
kkk = varidx(i);
if kkk > DAE.n+DAE.m
break
elseif kkk <= DAE.n
if isdelta_syn(Syn,kkk) || isdelta_mass(Mass,kkk) || isdelta_ssr(SSR,kkk) ...
|| isdelta_phs(Phs,kkk) || isdelta_svc(Svc,kkk) || isdelta_cswt(Cswt,kkk) ...
|| isdelta_ddsg(Ddsg,kkk) || isdelta_dfig(Dfig,kkk) || isdelta_pmu(Pmu,kkk)
idx = [idx, kkk];
kdx = [kdx, i];
end
elseif kkk > DAE.n && kkk <= DAE.n+Bus.n
idx = [idx, kkk];
kdx = [kdx, i];
elseif isdelta_coi(COI,kkk) || isdelta_hvdc(Hvdc,kkk)
idx = [idx, kkk];
kdx = [kdx, i];
end
end
switch nargout
case 1
varargout{1} = kdx;
case 2
varargout{1} = idx;
varargout{2} = kdx;
end
|
github
|
Sinan81/PSAT-master
|
fm_uwfig.m
|
.m
|
PSAT-master/psat-oct/psat/fm_uwfig.m
| 36,174 |
utf_8
|
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function fig = fm_uwfig(varargin)
% FM_UWFIG create GUI for PSAT/UWPFLOW interface.
%
% FIG = FM_UWFIG
%
%see UWPFLOW structure for settings
%
%Author: Federico Milano
%Date: 31-Mar-2003
%Version: 1.0.0
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2019 Federico Milano
global Settings Path PQ UWPFLOW GAMS Theme Fig Hdl History
% initialize UWPFLOW.opt, if necessary
fm_uwpflow('init')
% check for options
if nargin, checkon(varargin{1}), return, end
% do not redraw figure if open
if ishandle(Fig.uwpflow), figure(Fig.uwpflow), return, end
[u,w] = system('uwpflow');
if isempty(strmatch('UW Continuation Power Flow',w))
uiwait(fm_choice('UWPFLOW is not properly installed on your system.',2))
return
end
% constants and lists
D = 0.9394;
dy = 0.025;
dx = (D-4*dy)/3;
x1 = 0.0329 + dy;
x2 = 0.0329 + 2*dy + dx;
x3 = 0.0329 + 3*dy + 2*dx;
methods = {'[ ] Power Flow';
'[-c] Continuation Method';
'[-C] Direct Method';
'[-H] Parameterized CM'};
output = {'.k'; '.v'; '.w'; '.pf'; '.jac'; '.cf'; '.cpf';
'.mis'; '.var'; '.log'; '.oh'; '.vp'; '.gen'; '.ini';
'.poc'; '.ntv'};
output = fm_strjoin(UWPFLOW.file,output);
if PQ.n
PQbuses = fm_strjoin('PQ_',num2str(PQ.bus));
if PQ.n < UWPFLOW.opt.B.num, UWPFLOW.opt.B.num = 1; end
if PQ.n < UWPFLOW.opt.f.num, UWPFLOW.opt.f.num = 1; end
if PQ.n < UWPFLOW.opt.one.num, UWPFLOW.opt.one.num = 1; end
else
PQbuses = {'<none>'};
end
if strcmp(Settings.platform,'MAC')
aligntxt = 'center';
dm = 0.0075;
else
aligntxt = 'left';
dm = 0;
end
h0 = figure('Units','normalized', ...
'Color',Theme.color02, ...
'Colormap',[], ...
'CreateFcn', 'Fig.uwpflow = gcf;', ...
'DeleteFcn', 'Fig.uwpflow = -1;', ...
'MenuBar','none', ...
'Name','PSAT-UWPFLOW', ...
'NumberTitle','off', ...
'PaperPosition',[18 180 576 432], ...
'PaperUnits','points', ...
'Position',sizefig(1.2*0.5645,1.1*0.8451), ...
'Resize','on', ...
'ToolBar','none', ...
'FileName','fm_uwfig');
fm_set colormap
% Menu File
h1 = uimenu('Parent',h0, ...
'Label','File', ...
'Tag','MenuFile');
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwpflow view', ...
'Label','View UWPFLOW Input/Output files', ...
'Tag','OTV', ...
'Accelerator','g');
h2 = uimenu('Parent',h1, ...
'Callback','close(gcf)', ...
'Label','Exit', ...
'Tag','NetSett', ...
'Accelerator','x', ...
'Separator','on');
% Menu Edit
h1 = uimenu('Parent',h0, ...
'Label','Edit', ...
'Tag','MenuEdit');
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwpflow makecom', ...
'Label','Create UWPFLOW command line', ...
'Tag','ToolUWcom', ...
'Accelerator','c');
h2 = uimenu('Parent',h1, ...
'Callback','fm_setting', ...
'Label','General Settings', ...
'Tag','ToolSett', ...
'Separator', 'on', ...
'Accelerator','s');
% Menu Run
h1 = uimenu('Parent',h0, ...
'Label','Run', ...
'Tag','MenuRun');
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwpflow uwrun', ...
'Label','Run UWPFLOW', ...
'Tag','ToolOPFSett', ...
'Accelerator','z');
% Menu Options
h1 = uimenu('Parent',h0, ...
'Label','Options', ...
'Tag','MenuOpt');
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig a', ...
'Label','[-a] No tap/angle limit control', ...
'Tag','aopt', ...
'Checked',onoff(UWPFLOW.opt.a.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig A', ...
'Label','[-A] No intercahnge area control', ...
'Tag','Aopt', ...
'Checked',onoff(UWPFLOW.opt.A.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig b', ...
'Label','[-b] No interchange area control', ...
'Tag','bopt', ...
'Checked',onoff(UWPFLOW.opt.b.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig d', ...
'Label','[-d] Generate debug output', ...
'Tag','dopt', ...
'Checked',onoff(UWPFLOW.opt.d.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig g', ...
'Label','[-g] Force Qg to 0 (IEEE CDF)', ...
'Tag','gopt', ...
'Checked',onoff(UWPFLOW.opt.g.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig G', ...
'Label','[-G] Turn off ac device recovery', ...
'Tag','Gopt', ...
'Checked',onoff(UWPFLOW.opt.G.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig n', ...
'Label','[-n] Turn off all ac limits', ...
'Tag','nopt', ...
'Checked',onoff(UWPFLOW.opt.n.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig N', ...
'Label','[-N] Turn off all ac system controls', ...
'Tag','Nopt', ...
'Checked',onoff(UWPFLOW.opt.N.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig p', ...
'Label','[-p] Turn off P/Q limits in reg. transf.', ...
'Tag','popt', ...
'Checked',onoff(UWPFLOW.opt.p.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig P', ...
'Label','[-P] Turn off P/Q control by reg. transf.', ...
'Tag','Popt', ...
'Checked',onoff(UWPFLOW.opt.P.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig q', ...
'Label','[-q] Turn off Q limits in PV buses', ...
'Tag','qopt', ...
'Checked',onoff(UWPFLOW.opt.q.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig qx', ...
'Label','[-qx] Turn off V limits in BX buses', ...
'Tag','qxopt', ...
'Checked',onoff(UWPFLOW.opt.qx.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig qz', ...
'Label','[-qz] Turn off Q limits in BZ buses', ...
'Tag','qzopt', ...
'Checked',onoff(UWPFLOW.opt.qz.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig Q', ...
'Label','[-Q] Turn off remote Vg control', ...
'Tag','Qopt', ...
'Checked',onoff(UWPFLOW.opt.Q.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig QX', ...
'Label','[-QX] Turn off remote Vg control in BX buses', ...
'Tag','QXopt', ...
'Checked',onoff(UWPFLOW.opt.QX.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig r', ...
'Label','[-r] Turn off V limits in reg. tranf. and PV buses', ...
'Tag','ropt', ...
'Checked',onoff(UWPFLOW.opt.r.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig R', ...
'Label','[-R] Turn off V control by reg. transf.', ...
'Tag','Ropt', ...
'Checked',onoff(UWPFLOW.opt.R.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig s', ...
'Label','[-s] Suppress ASCII output file', ...
'Tag','sopt', ...
'Checked',onoff(UWPFLOW.opt.s.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig x', ...
'Label','[-x] Use single slack bus', ...
'Tag','xopt', ...
'Checked',onoff(UWPFLOW.opt.x.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig X', ...
'Label','[-X] Turn off max Pg limits', ...
'Tag','Xopt', ...
'Checked',onoff(UWPFLOW.opt.X.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig four', ...
'Label','[-4] Turn off Eq limits in all gen.', ...
'Tag','fouropt', ...
'Checked',onoff(UWPFLOW.opt.four.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig five', ...
'Label','[-5] Turn off Ia limits in all gen.', ...
'Tag','fiveopt', ...
'Checked',onoff(UWPFLOW.opt.five.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig seven', ...
'Label','[-7] Enforce Vmax and Vmin', ...
'Tag','sevenopt', ...
'Checked',onoff(UWPFLOW.opt.seven.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig eight', ...
'Label','[-8] Enforce Imax limits', ...
'Tag','eightopt', ...
'Checked',onoff(UWPFLOW.opt.eight.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig nine', ...
'Label','[-9] Do not enforce gen. Smax limits', ...
'Tag','nineopt', ...
'Checked',onoff(UWPFLOW.opt.nine.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig bound', ...
'Label','[-#] Use secondary voltage control', ...
'Tag','boundopt', ...
'Checked',onoff(UWPFLOW.opt.bound.status));
% Menu Output files
h1 = uimenu('Parent',h0, ...
'Label','Output', ...
'Tag','MenuOut');
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig E', ...
'Label','[-E] Print PoC right e-vector', ...
'Tag','eopt', ...
'Checked',onoff(UWPFLOW.opt.E.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig j', ...
'Label','[-j] Write Jacobian matrix (2n+1)x(2n+1)', ...
'Tag','eopt', ...
'Checked',onoff(UWPFLOW.opt.j.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig J', ...
'Label','[-J] Write Jacobian matrix (2n)x(2n)', ...
'Tag','eopt', ...
'Checked',onoff(UWPFLOW.opt.j.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig E', ...
'Label','[-E] Print PoC right e-vector', ...
'Tag','eopt', ...
'Checked',onoff(UWPFLOW.opt.E.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig l', ...
'Label','[-l] Write standard error output', ...
'Tag','lopt', ...
'Checked',onoff(UWPFLOW.opt.l.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig w', ...
'Label','[-w] Write solution in IEEE CARD format', ...
'Tag','wopt', ...
'Checked',onoff(UWPFLOW.opt.w.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig W', ...
'Label','[-W] Write solution in IEEE TAPE format', ...
'Tag','wopt', ...
'Checked',onoff(UWPFLOW.opt.W.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig y', ...
'Label','[-y] Print left e-vector of smallest |e-value|', ...
'Tag','yopt', ...
'Checked',onoff(UWPFLOW.opt.y.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig Y', ...
'Label','[-Y] Print right e-vector of smallest |e-value|', ...
'Tag','Yopt', ...
'Checked',onoff(UWPFLOW.opt.Y.status));
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwfig Z', ...
'Label','[-Z] Print normalized tangent vector', ...
'Tag','Zopt', ...
'Checked',onoff(UWPFLOW.opt.Z.status));
% Menu Preferences
h1 = uimenu('Parent',h0, ...
'Label','Preferences', ...
'Tag','MenuPref');
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwpflow filename', ...
'Label','Modify input/output file name', ...
'Tag','OTV', ...
'Accelerator','e');
h2 = uimenu('Parent',h1, ...
'Callback','fm_tviewer', ...
'Label','Select Text Viewer', ...
'Tag','tvopt', ...
'Separator', 'on', ...
'Accelerator','t');
% Menu Help
h1 = uimenu('Parent',h0, ...
'Label','Help', ...
'Tag','MenuHelp');
h2 = uimenu('Parent',h1, ...
'Callback','fm_uwpflow help', ...
'Label','UWPFLOW help', ...
'Accelerator','h', ...
'Tag','UWHelp');
h2 = uimenu('Parent',h1, ...
'Callback','web(''http://thunderbox.uwaterloo.ca/~claudio/software/pflow.html'');', ...
'Label','UWPFLOW website', ...
'Accelerator','w', ...
'Tag','UWLink');
% Frame
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'ForegroundColor',Theme.color03, ...
'Position',[0.0329 0.1399 0.9394 0.8405], ...
'Style','frame', ...
'Tag','Frame1');
% List Boxes
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig B', ...
'HorizontalAlignment','left', ...
'Position',[x3 0.9199 dx 0.0339], ...
'String','[-B] Bus for fixed voltage:', ...
'Style','checkbox', ...
'Tag','Check_B', ...
'Value', UWPFLOW.opt.B.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.B.num = get(gcbo,''Value''); UWPFLOW.opt.B.num = UWPFLOW.opt.B.num(end); set(gcbo,''Value'',UWPFLOW.opt.B.num)', ...
'Enable', onoff(UWPFLOW.opt.B.status), ...
'FontName', Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'ListboxTop',UWPFLOW.opt.B.num, ...
'Max', 100, ...
'Position',[x3 0.7439 dx 0.1595], ...
'String',PQbuses, ...
'Style','listbox', ...
'Tag','Edit_B', ...
'Value',UWPFLOW.opt.B.num);
dyy = 0.015;
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig f', ...
'HorizontalAlignment','left', ...
'Position',[x3 0.6835+dyy dx 0.0339], ...
'String','[-f] Bus for SF, VSF and TG:', ...
'Style','checkbox', ...
'Tag','Check_f', ...
'Value', UWPFLOW.opt.f.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.f.num = get(gcbo,''Value''); UWPFLOW.opt.f.num = UWPFLOW.opt.f.num(end); set(gcbo,''Value'',UWPFLOW.opt.f.num)', ...
'Enable', onoff(UWPFLOW.opt.f.status), ...
'FontName', Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'ListboxTop',UWPFLOW.opt.f.num, ...
'Max', 100, ...
'Position',[x3 0.5076+dyy dx 0.1595], ...
'String',PQbuses, ...
'Style','listbox', ...
'Tag','Edit_f', ...
'Value',UWPFLOW.opt.f.num);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig one', ...
'HorizontalAlignment','left', ...
'Position',[x3 0.4471+2*dyy dx 0.0339], ...
'String','[-1] Bus for test functions:', ...
'Style','checkbox', ...
'Tag','Check_one', ...
'Value', UWPFLOW.opt.one.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.one.num = get(gcbo,''Value''); UWPFLOW.opt.one.num = UWPFLOW.opt.one.num(end); set(gcbo,''Value'',UWPFLOW.opt.one.num)', ...
'Enable', onoff(UWPFLOW.opt.one.status), ...
'FontName', Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'ListboxTop',UWPFLOW.opt.one.num, ...
'Max', 100, ...
'Position',[x3 0.2712+2*dyy dx 0.1595], ...
'String',PQbuses, ...
'Style','listbox', ...
'Tag','Edit_one', ...
'Value',UWPFLOW.opt.one.num);
% Popup Menus
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwpflow methods', ...
'FontName', Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment','left', ...
'Position',[x2 0.2712+2*dyy dx 0.0308], ...
'String',methods, ...
'Style','popupmenu', ...
'Tag','PopupMenuMethod', ...
'Value',UWPFLOW.method);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'HorizontalAlignment','left', ...
'Position',[x2 0.305+2*dyy dx 0.0308], ...
'String','Solver method:', ...
'Style','text', ...
'Tag','StaticText12');
h1 = uicontrol('Parent', h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', '', ...
'FontName', Theme.font01, ...
'HorizontalAlignment','left', ...
'Position',[x1 0.2712+2*dyy dx 0.0308], ...
'String',output, ...
'Style','popupmenu', ...
'Tag','PopupUWFile', ...
'Value',1);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'HorizontalAlignment','left', ...
'Position',[x1 0.305+2*dyy dx 0.0308], ...
'String','UWPFLOW input/output file:', ...
'Style','text', ...
'Tag','StaticText11');
% Pushbuttons
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color03, ...
'Callback','fm_uwpflow uwrun', ...
'FontWeight','bold', ...
'ForegroundColor',Theme.color09, ...
'Position',[x1 0.1576-2*dm dx 0.045+2*dm], ...
'String','Run UWPFLOW', ...
'Tag','Pushbutton1');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback','close(gcf)', ...
'Position',[x3 0.1576-2*dm dx 0.045+2*dm], ...
'String','Close', ...
'Tag','Pushbutton2');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback','fm_uwpflow view', ...
'Position',[x2 0.1576-2*dm dx 0.045+2*dm], ...
'String','View Input/Output File', ...
'Tag','Pushbutton3');
% UWPFLOW Command Line
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback','UWPFLOW.command = get(gcbo,''String'');', ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x1 0.225 x3+dx-x1 0.0308+dm], ...
'Style','edit', ...
'String', UWPFLOW.command, ...
'Tag','EditCom');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'HorizontalAlignment','left', ...
'Position',[x1 0.225+0.0308+dm dx 0.0308], ...
'String','Command Line:', ...
'Style','text', ...
'Tag','TextCom');
% Parameters (left column)
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.F.num = fval(gcbo,UWPFLOW.opt.F.num);', ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'Enable', onoff(UWPFLOW.opt.F.status), ...
'HorizontalAlignment',aligntxt, ...
'Position',[x1 0.8731 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.F.num), ...
'Tag','Edit_F');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig F', ...
'HorizontalAlignment','left', ...
'Position',[x1 0.9199 dx 0.0339], ...
'String','[-F] Stability/sparsity [0,1]', ...
'Style','checkbox', ...
'Tag','Check_F', ...
'Value', UWPFLOW.opt.F.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.t.num = fval(gcbo,UWPFLOW.opt.t.num)', ...
'Enable', onoff(UWPFLOW.opt.t.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x1 0.7764 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.t.num), ...
'Tag','Edit_t');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'Callback', 'fm_uwfig t', ...
'BackgroundColor',Theme.color02, ...
'HorizontalAlignment','left', ...
'Position',[x1 0.8232 dx 0.0339], ...
'String','[-t] Iteration mismatch tol.', ...
'Style','checkbox', ...
'Tag','Check_t', ...
'Value', UWPFLOW.opt.t.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback','UWPFLOW.opt.o.num = fval(gcbo,UWPFLOW.opt.o.num);', ...
'Enable', onoff(UWPFLOW.opt.o.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x1 0.6798 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.o.num), ...
'Tag','Edit_o');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig o', ...
'HorizontalAlignment','left', ...
'Position',[x1 0.7266 dx 0.0339], ...
'String','[-o] Limit control tol.', ...
'Style','checkbox', ...
'Tag','Check_o', ...
'Value', UWPFLOW.opt.o.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.L.num = fval(gcbo,UWPFLOW.opt.L.num);', ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'Enable', onoff(UWPFLOW.opt.L.status), ...
'HorizontalAlignment',aligntxt, ...
'Position',[x1 0.5831 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.L.num), ...
'Tag','Edit_L');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig L', ...
'HorizontalAlignment','left', ...
'Position',[x1 0.6299 dx 0.0339], ...
'String','[-L] Initial loading factor', ...
'Style','checkbox', ...
'Tag','Check_L', ...
'Value', UWPFLOW.opt.L.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.O.num = fval(gcbo,UWPFLOW.opt.O.num)', ...
'Enable', onoff(UWPFLOW.opt.O.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x1 0.4865 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.O.num), ...
'Tag','Edit_O');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'Callback', 'fm_uwfig O', ...
'BackgroundColor',Theme.color02, ...
'HorizontalAlignment','left', ...
'Position',[x1 0.5333 dx 0.0339], ...
'String','[-O] ac/dc TEF digits [6-10]', ...
'Style','checkbox', ...
'Tag','Check_O', ...
'Value', UWPFLOW.opt.O.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback','UWPFLOW.opt.S.num = fval(gcbo,UWPFLOW.opt.S.num);', ...
'Enable', onoff(UWPFLOW.opt.S.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x1 0.3898 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.S.num), ...
'Tag','Edit_S');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig S', ...
'HorizontalAlignment','left', ...
'Position',[x1 0.4366 dx 0.0339], ...
'String','[-S] Max. loading factor [0,1]', ...
'Style','checkbox', ...
'Tag','Check_S', ...
'Value', UWPFLOW.opt.S.status);
% Parameters (middle column)
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.k.num = fval(gcbo,UWPFLOW.opt.k.num);', ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'Enable', onoff(UWPFLOW.opt.k.status), ...
'HorizontalAlignment',aligntxt, ...
'Position',[x2 0.8731 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.k.num), ...
'Tag','Edit_k');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig k', ...
'HorizontalAlignment','left', ...
'Position',[x2 0.9199 dx 0.0339], ...
'String','[-k] Loading factor increment', ...
'Style','checkbox', ...
'Tag','Check_k', ...
'Value', UWPFLOW.opt.k.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.u.num = fval(gcbo,UWPFLOW.opt.u.num)', ...
'Enable', onoff(UWPFLOW.opt.u.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x2 0.7764 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.u.num), ...
'Tag','Edit_u');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'Callback', 'fm_uwfig u', ...
'BackgroundColor',Theme.color02, ...
'HorizontalAlignment','left', ...
'Position',[x2 0.8232 dx 0.0339], ...
'String','[-u] Reduce eq. tol. [0,0.2]', ...
'Style','checkbox', ...
'Tag','Check_u', ...
'Value', UWPFLOW.opt.u.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback','UWPFLOW.opt.U.num = fval(gcbo,UWPFLOW.opt.U.num);', ...
'Enable', onoff(UWPFLOW.opt.U.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x2 0.6798 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.U.num), ...
'Tag','Edit_U');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig U', ...
'HorizontalAlignment','left', ...
'Position',[x2 0.7266 dx 0.0339], ...
'String','[-U] Step # for sys. red. [2,100]', ...
'Style','checkbox', ...
'Tag','Check_U', ...
'Value', UWPFLOW.opt.U.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.v.num = fval(gcbo,UWPFLOW.opt.v.num);', ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'Enable', onoff(UWPFLOW.opt.v.status), ...
'HorizontalAlignment',aligntxt, ...
'Position',[x2 0.5831 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.v.num), ...
'Tag','Edit_v');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig v', ...
'HorizontalAlignment','left', ...
'Position',[x2 0.6299 dx 0.0339], ...
'String','[-v] PQ bus voltage magnitude', ...
'Style','checkbox', ...
'Tag','Check_v', ...
'Value', UWPFLOW.opt.v.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback', 'UWPFLOW.opt.z.num = fval(gcbo,UWPFLOW.opt.z.num)', ...
'Enable', onoff(UWPFLOW.opt.z.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x2 0.4865 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.z.num), ...
'Tag','Edit_z');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'Callback', 'fm_uwfig z', ...
'BackgroundColor',Theme.color02, ...
'HorizontalAlignment','left', ...
'Position',[x2 0.5333 dx 0.0339], ...
'String','[-z] Max. # of CM steps', ...
'Style','checkbox', ...
'Tag','Check_z', ...
'Value', UWPFLOW.opt.z.status);
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color04, ...
'Callback','UWPFLOW.opt.two.num = fval(gcbo,UWPFLOW.opt.two.num);', ...
'Enable', onoff(UWPFLOW.opt.two.status), ...
'FontName',Theme.font01, ...
'ForegroundColor',Theme.color05, ...
'HorizontalAlignment',aligntxt, ...
'Position',[x2 0.3898 dx 0.0308+dm], ...
'Style','edit', ...
'String', num2str(UWPFLOW.opt.two.num), ...
'Tag','Edit_two');
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'Callback', 'fm_uwfig two', ...
'HorizontalAlignment','left', ...
'Position',[x2 0.4366 dx 0.0339], ...
'String','[-2] Step # for dir. change', ...
'Style','checkbox', ...
'Tag','Check_two', ...
'Value', UWPFLOW.opt.two.status);
% Banner
h1 = axes('Parent',h0, ...
'Box','on', ...
'CameraUpVector',[0 1 0], ...
'Color',Theme.color04, ...
'ColorOrder',Settings.color, ...
'Layer','top', ...
'Position',[0.0329 0.0169 0.8*0.1540 0.8*0.1371], ...
'Tag','Axes1', ...
'XColor',Theme.color02, ...
'XLim',[0.5 100.5], ...
'XLimMode','manual', ...
'XTick',[], ...
'YColor',Theme.color02, ...
'YDir','reverse', ...
'YLim',[0.5 100.5], ...
'YLimMode','manual', ...
'YTick',[], ...
'ZColor',[0 0 0]);
if Settings.hostver < 8.04
h2 = image('Parent',h1, ...
'CData',fm_mat('logo_psat'), ...
'Tag','Axes1Image1', ...
'XData',[1 101], ...
'YData',[1 101]);
else
h2 = image('Parent',h1, ...
'CData',flipud(fliplr(fm_mat('logo_psat'))), ...
'Tag','Axes1Image1', ...
'XData',[1 101], ...
'YData',[1 101]);
end
h1 = axes('Parent',h0, ...
'Box','on', ...
'CameraUpVector',[0 1 0], ...
'Color',Theme.color02, ...
'ColorOrder',Settings.color, ...
'Layer','top', ...
'Position',[0.8491 0.0169 0.8*0.1540 0.8*0.1371], ...
'Tag','Axes1', ...
'XColor',Theme.color02, ...
'XLim',[0.5 100.5], ...
'XLimMode','manual', ...
'XTick',[], ...
'YColor',Theme.color02, ...
'YDir','reverse', ...
'YLim',[0.5 100.5], ...
'YLimMode','manual', ...
'YTick',[], ...
'ZColor',[0 0 0]);
if Settings.hostver < 8.04
h2 = image('Parent',h1, ...
'CData',fm_mat('logo_uwpflow'), ...
'Tag','Axes1Image1', ...
'XData',[1 101], ...
'YData',[1 101]);
else
h2 = image('Parent',h1, ...
'CData',flipud(fliplr(fm_mat('logo_uwpflow'))), ...
'Tag','Axes1Image1', ...
'XData',[1 101], ...
'YData',[1 101]);
end
h1 = uicontrol('Parent',h0, ...
'Units', 'normalized', ...
'BackgroundColor',Theme.color02, ...
'ForegroundColor', [0 0 1], ...
'FontSize', 12, ...
'FontName', 'Times', ...
'FontWeight', 'bold', ...
'FontAngle', 'italic',...
'Position',[0.2915 0.0516 0.4221 0.0355], ...
'String','PSAT-UWPFLOW Interface', ...
'Style','text', ...
'Tag','StaticText3');
if nargout > 0, fig = h0; end
% ---------------------------------------------------------
function output = onoff(input)
if input, output = 'on'; else, output = 'off'; end
% ---------------------------------------------------------
function checkon(field)
global UWPFLOW Fig
if isfield(UWPFLOW.opt,field)
a = getfield(UWPFLOW.opt,field);
a.status = ~a.status;
UWPFLOW.opt = setfield(UWPFLOW.opt,field,a);
try % strcmp(get(gcbo,'Style'),'checkbox')
set(gcbo,'Value',a.status)
hdl = findobj(Fig.uwpflow,'Tag',['Edit_',field]);
set(hdl,'Enable',onoff(a.status))
catch
set(gcbo,'Checked',onoff(a.status))
end
end
|
github
|
Sinan81/PSAT-master
|
sim2psat.m
|
.m
|
PSAT-master/psat-oct/psat/filters/sim2psat.m
| 29,948 |
utf_8
|
eaf79c62c1825a9a71b6f65fe0cb7b15
|
function check_model = sim2psat(varargin)
% SIM2PSAT convert Simulink models into PSAT data files
%
% CHECK = SIM2PSAT
% CHECK = 0 conversion failed
% CHECK = 1 conversion completed
%
%see also FM_LIB, FM_SIMREP, FM_SIMSET
%
%Author: Federico Milano
%Date: 01-Jan-2006
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2009 Federico Milano
global File Fig Settings Hdl Path Theme History
if ~nargin
File_Data = File.data;
Path_Data = Path.data;
else
File_Data = varargin{1};
Path_Data = varargin{2};
end
if ~strcmp(Path_Data(end),filesep)
Path_Data = [Path_Data,filesep];
end
check_model = 1;
fm_disp
fm_disp('Simulink Model Conversion');
fm_disp(['Simulink File <',File_Data,'>.']);
% component names
% NB. 'Varname' must be the last element
Compnames = {'Bus','Line','Shunt','Breaker', ...
'Fault','SW','PV','PQ','PQgen', ...
'Mn','Pl','Fl','Lines','Twt','Syn', ...
'Ind','Mot','Ltc','Thload','Tg','Exc', ...
'Pss','Oxl','Hvdc','Svc','Tcsc', ...
'Statcom','Sssc','Upfc','Mass','SSR', ...
'Tap','Demand','Supply','Rsrv','Rmpg', ...
'Rmpl','Vltn','Ypdp','Sofc','Cac','Spv','Spq', ...
'Cluster','Exload','Phs','Cswt','Dfig', ...
'Ddsg','Wind','Busfreq','Pmu','Jimma', ...
'Mixload','Pod','Areas','Regions','Varname'};
lasterr('');
for i = 1:length(Compnames),
eval([Compnames{i}, ' = [];']);
end
tipi = length(Compnames)-1;
% constants used in the component masks
% ----------------------------------------------------------------
on = 1;
off = 0;
omega = 1;
power = 2;
voltage = 3;
monday = 1;
tuesday = 2;
wednesday = 3;
thursday = 4;
friday = 5;
saturday = 6;
sunday = 7;
winter_week_day = 1;
winter_week_end = 2;
summer_week_day = 3;
summer_week_end = 4;
spring_fall_week_day = 5;
spring_fall_week_end = 6;
measurements = 1;
weibull = 2;
composite = 3;
mexican_hat = 4;
Bus_V = 1;
Line_P_from_bus = 2;
Line_P_to_bus = 3;
Line_I_from_bus = 4;
Line_I_to_bus = 5;
Line_Q_from_bus = 6;
Line_Q_to_bus = 7;
in = 1;
out = 1;
ins = 1;
ous = 1;
constant_voltage = 1;
constant_reactance = 2;
constant_power = 3;
constant_line_power = 1;
constant_angle = 2;
SVC_control = 1;
TCSC_control = 2;
STATCOM_control = 3;
SSSC_control = 4;
UPFC_control = 5;
Xc = 1;
Alpha = 2;
constant_admittance = 1;
constant_power_flow = 2;
Current_control = 1;
Power_control = 2;
Voltage_control = 3;
% loading Simulink model
% ----------------------------------------------------------------
File_Data = strrep(File_Data,'(mdl)','');
File_Data = strrep(File_Data,'.mdl','');
fm_disp('Loading Simulink Model')
%cd(Path_Data);
open_sys = find_system('type','block_diagram');
OpenModel = sum(strcmp(open_sys,File_Data));
if OpenModel
cur_sys = get_param(File_Data,'Handle');
else
localpath = pwd;
cd(Path_Data)
if exist(File_Data,'file') ~= 4
fm_disp(['File <',File_Data,'> is not a Simulink model.'],2)
check_model = 0;
return
end
warning('off', 'Simulink:Engine:InvalidDomainRegistrationKey');
cur_sys = load_system(File_Data);
cd(localpath)
end
% open status bar
fm_bar open
% load block and mask properties
% ----------------------------------------------------------------
fm_disp(' * * *')
fm_disp('Check model version and blocks ...')
SimUpdate(cur_sys)
Settings.mv = str2num(get_param(cur_sys,'ModelVersion'));
blocks = find_system(cur_sys,'Type','block');
if strcmp(get_param(cur_sys,'Open'),'on')
hilite_system(cur_sys,'none')
end
masks = get_param(blocks,'MaskType');
nblock = length(blocks);
tipi3 = 1/(tipi + 1 + 2*nblock);
fm_bar([1e-3,tipi3])
fm_disp(' * * *')
fm_disp('Statistics ...')
vector = zeros(13,1);
vector(1) = length(find_system(blocks,'Description','Connection'));
vector(2) = length(find_system(blocks,'Description','Power Flow'));
vector(3) = length(find_system(blocks,'Description','OPF & CPF'));
vector(4) = length(find_system(blocks,'Description','Faults & Breakers'));
vector(5) = length(find_system(blocks,'Description','Loads'));
vector(6) = length(find_system(blocks,'Description','Machines'));
vector(7) = length(find_system(blocks,'Description','ULTC'));
vector(8) = length(find_system(blocks,'Description','Controls'));
vector(9) = length(find_system(blocks,'Description','FACTS'));
vector(10) = length(find_system(blocks,'Description','Sparse Dynamic Component'));
vector(11) = length(find_system(blocks,'Description','Wind Turbines'));
vector(12) = length(find_system(blocks,'Description','Measurements'));
dispno(vector(1),'Connections')
dispno(vector(2),'Power Flow Components')
dispno(vector(3),'OPF & CPF Components')
dispno(vector(4),'Faults & Breakers')
dispno(vector(5),'Special Loads')
dispno(vector(6),'Machines')
dispno(vector(7),'Regulating Transformers')
dispno(vector(8),'Controls')
dispno(vector(9),'FACTS')
dispno(vector(10),'Spare Dynamic Components')
dispno(vector(11),'Wind Power Components')
dispno(vector(12),'Measurement Components')
% component data matrices
% ----------------------------------------------------------------
fm_disp(' * * *')
fm_disp('Definition of component data ...')
kinds = zeros(length(Compnames),1);
idx_old = 0;
for i = 1:nblock
tipo = masks{i};
idx = strmatch(tipo,Compnames,'exact');
if ~isempty(idx)
kinds(idx) = kinds(idx)+1;
sidx = num2str(kinds(idx));
if idx ~= idx_old
idx_old = idx;
fm_disp(['Data "',tipo,'.con"'])
end
comp_data = get_param(blocks(i),'MaskVariables');
comp_value = get_param(blocks(i),'MaskValueString');
valori = strrep(['[',comp_value,']'],'|',',');
indici = comp_data;
if strmatch(indici,'pxq=@1;','exact')
indici = ':';
else
indici = ['[',indici,']'];
indici = strrep(indici,'x',':');
indici = strrep(indici,'p','');
indici = strrep(indici,'_',' ');
indici = strrep(indici,'q','');
end
indici = regexprep(indici,'=@([0-9]*);',' ');
try
eval([tipo,'(',sidx,',',indici,') = ',valori,';']);
catch
%[tipo,'(',sidx,',',indici,') = ',valori,';']
fm_disp(['Error: ',tipo,' block <', ...
get_param(blocks(i),'Name'), ...
'> has a wrong number of data.'],2)
hilite_system(blocks(i),'default')
eval([tipo,'(',sidx,',',indici,') = 0;']);
end
set_param(blocks(i),'UserData',sidx);
end
if ~rem(i,5), fm_bar([(i-1)*tipi3,i*tipi3]), end
end
% "Bus" number
% ----------------------------------------------------------------
busidx = find(strcmp(masks,'Bus'));
busname = get_param(blocks(busidx),'Name');
Bus_n = length(busidx);
Bus(:,1) = [1:Bus_n]';
fm_disp(' * * *')
fm_disp('Definition of system connections ...')
for i = 1:nblock
if isempty(masks{i}), continue, end
if strcmp(get_param(blocks(i),'Description'),'Connection')
continue
end
rowno = get_param(blocks(i),'UserData');
% define connections
switch masks{i}
case {'Exc','Tg','Mass'}
Destin = {'Syn'};
dst = 1; posdst = 1;
Source = '';
src = []; possrc = [];
case {'Pss','Oxl'}
Destin = {'Exc'};
dst = 1; posdst = 1;
Source = '';
src = []; possrc = [];
case 'Rmpg'
Destin = {'Supply'};
dst = 1; posdst = 1;
Source = '';
src = []; possrc = [];
case 'Rmpl'
Destin = '';
dst = []; posdst = [];
Source = {'Demand'};
src = 1; possrc = 1;
case 'Breaker'
Destin = {'Bus'};
dst = 2; posdst = 2;
Source = {'Line'};
src = 1; possrc = 1;
case 'Pod'
Destin = {'Statcom','Sssc','Svc','Upfc','Tcsc','Dfig'};
dst = 2; posdst = 2;
MaskValues = get_param(blocks(i),'MaskValues');
if strcmp(MaskValues{1},'Bus_V')
Source = {'Bus'};
else
Source = {'Line'};
end
src = 1; possrc = 1;
case 'Cluster'
Source = {'Cac'};
src = 1; possrc = 1;
Destin = {'Exc','Svc'};
dst = 2; posdst = 2;
case {'PV','SW','Supply','Rsrv','Rmpg','Vltn', ...
'SSR','Sofc','PQgen','Syn','Supply','Spv','Spq'}
Destin = {'Bus'};
dst = 1; posdst = 1;
Source = '';
src = []; possrc = [];
case {'Line','Lines','Phs','RLC','Hvdc'}
Destin = {'Bus'};
dst = 2; posdst = 2;
Source = {'Bus'};
src = 1; possrc = 1;
case {'Sssc','Upfc','Tcsc'}
Destin = '';
dst = []; posdst = [];
Source = {'Line'};
src = 1; possrc = 1;
case 'Ltc'
MaskValues = get_param(blocks(i),'MaskValues');
if strcmp(MaskValues{3},'3')
Destin = {'Bus'};
dst = 3; posdst = 2;
Source = {'Bus'};
src = [1 2]; possrc = [15 1];
else
Destin = {'Bus'};
dst = 2; posdst = 2;
Source = {'Bus'};
src = 1; possrc = 1;
end
case {'Cswt','Dfig','Ddsg'}
Destin = {'Bus'};
dst = 2; posdst = 1;
Source = {'Wind'};
src = 1; possrc = 2;
case 'Twt'
Destin = {'Bus'};
dst = [2 3]; posdst = [2 3];
Source = {'Bus'};
src = 1; possrc = 1;
%case {'SAE1','SAE2','SAE3'}
% Source = {'Bus'};
% src = [1 2]; possrc = [1 2];
% Destin = '';
% dst = []; posdst = [];
case {'Ypdp','Wind','Varname'}
Source = '';
src = []; possrc = [];
Destin = '';
dst = []; posdst = [];
case {'Areas','Regions'}
Source = '';
src = []; possrc = [];
MaskValues = get_param(blocks(i),'MaskValues');
if strcmp(MaskValues{1},'1')
Destin = {'Bus'};
dst = 1; posdst = 2;
else
Destin = '';
dst = []; posdst = [];
end
otherwise
Destin = '';
dst = []; posdst = [];
Source = {'Bus'};
src = 1; possrc = 1;
end
% find connections
for j = 1:length(dst)
block2_handle = SeekDstBlock(blocks(i),Destin,dst(j));
busno = get_param(block2_handle,'UserData');
eval([masks{i},'(',rowno,',',num2str(posdst(j)),') = ',busno,';']);
if strcmp(masks(i),'Cluster')
switch get_param(block2_handle,'MaskType')
case 'Exc', ctype = '1';
case 'Svc', ctype = '2';
end
eval([masks{i},'(',rowno,',3) = ',ctype,';']);
end
if strcmp(masks(i),'Pod')
switch get_param(block2_handle,'MaskType')
case 'Svc', ctype = '1';
case 'Tcsc', ctype = '2';
case 'Statcom', ctype = '3';
case 'Sssc', ctype = '4';
case 'Upfc', ctype = '5';
case 'Dfig', ctype = '6';
end
eval([masks{i},'(',rowno,',4) = ',ctype,';']);
end
end
for j = 1:length(src)
block2_handle = SeekSrcBlock(blocks(i),Source,src(j));
busno = get_param(block2_handle,'UserData');
eval([masks{i},'(',rowno,',',num2str(possrc(j)),') = ',busno,';']);
end
fm_bar([(nblock+i-1)*tipi3,(nblock+i)*tipi3])
end
fm_disp(' * * *')
% writing data file
idx1 = strmatch('Definition of component data ...',History.text);
idx2 = strmatch('Definition of system connections ...',History.text);
idx3 = strmatch('Error:',History.text);
if isempty(idx3), idx3 = 0; end
if idx3(end) > idx1(end)
if idx3(end) > idx2(end),
message = 'Simulink model is not well-formed (check links).';
end
if find(idx3 < idx2(end) & idx3 > idx1(end)),
message = ['Component data are not well-formed (check ' ...
'masks).'];
end
else
File_Data = [File_Data,'_mdl'];
[fid, message] = fopen([Path_Data,File_Data,'.m'], 'wt');
end
if ~isempty(message),
if strcmp(message, ...
['Sorry. No help in figuring out the problem ...']),
fm_disp(['Most likely the folder "',Path_Data, ...
'" is read only. Try to change the permission.'])
else
fm_disp(['Failed conversion from Simulink model: ',message],2)
end
if ishandle(Fig.main)
set(Fig.main,'Pointer','arrow');
delete(Hdl.bar); Hdl.bar = 0;
set(Hdl.frame,'Visible','on');
set(Hdl.text,'Visible','on');
end
check_model = 0;
return
else
fm_disp('Writing Data File',1)
end
fm_bar([(2*nblock)*tipi3,(2*nblock+1)*tipi3])
for j = 1:length(Compnames)-1
values = eval(Compnames{j});
if ~isempty(values)
count = fprintf(fid,'%s.con = [ ... \n',Compnames{j});
for i = 1:length(values(:,1))
count = fprintf(fid,[' ',regexprep(num2str(values(i,:)),'\s*',' '),';\n']);
end
count = fprintf(fid,' ];\n\n');
end
fm_bar([(2*nblock+j-1)*tipi3,(2*nblock+j)*tipi3])
end
% count = fprintf(fid, 'Bus.names = {... \n ');
% for i = 1:Bus_n-1
% namebus = strrep(busname{i,1},char(10),' ');
% count = fprintf(fid, ['''',namebus,'''; ']);
% if rem(i,5) == 0; count = fprintf(fid,'\n '); end
% end
% if iscell(busname)
% namebus = strrep(busname{length(busname),1},char(10),' ');
% count = fprintf(fid, ['''',namebus,'''};\n\n']);
% else
% namebus = strrep(busname,char(10),' ');
% count = fprintf(fid, ['''',namebus,'''};\n\n']);
% end
WriteNames(fid,'Bus',busname);
areaidx = find(strcmp(masks,'Areas'));
areaname = get_param(blocks(areaidx),'Name');
WriteNames(fid,'Areas',areaname);
zoneidx = find(strcmp(masks,'Regions'));
zonename = get_param(blocks(zoneidx),'Name');
WriteNames(fid,'Regions',zonename);
% print indexes of variables to be plotted
if ~isempty(Varname)
count = fprintf(fid, 'Varname.idx = [... \n');
nidx = length(Varname);
count = fprintf(fid,'%5d; %5d; %5d; %5d; %5d; %5d; %5d;\n',Varname);
if rem(nidx,7) ~= 0,
count = fprintf(fid,'\n');
end
count = fprintf(fid,' ];\n');
end
% closing data file
count = fclose(fid);
exist(File_Data);
% closing Simulink model
if ~OpenModel && ~strcmp(get_param(cur_sys,'Dirty'),'on')
close_system(cur_sys);
end
fm_disp(['Construction of Data File <',File_Data,'.m> completed.'])
% close status bar
fm_bar close
% last operations
% cd(Path.local);
if Settings.beep, beep, end
if ~nargin, File.data = [File_Data(1:end-4),'(mdl)']; end
%------------------------------------------------------------------
function dispno(num,msg)
%------------------------------------------------------------------
if num, fm_disp([msg,': #',num2str(num),'#']), end
%------------------------------------------------------------------
function block_name = MaskType(block_handle)
%------------------------------------------------------------------
block_name = get_param(block_handle,'MaskType');
if isempty(block_name)
block_name = get_param(block_handle,'BlockType');
end
if isempty(block_name)
hilite_system(block_handle)
block_name = 'Error';
return
end
if iscell(block_name)
block_name = block_name{1};
end
%------------------------------------------------------------------
function hdl2 = SeekDstBlock(hdl1,name2,pos)
%------------------------------------------------------------------
ports = get_param(hdl1,'PortConnectivity');
if length(ports) < pos
SimWarnMsg(hdl1,'has the wrong number of ports')
hdl2 = hdl1; % to avoid errors in evaluating UserData
return
end
handles = [ports.DstBlock];
try
idx = find(strcmp({ports.Type},'RConn1'));
if isempty(idx), idx = pos; end
if idx(pos) ~= pos
hdl2 = ports(idx(pos)).DstBlock;
else
hdl2 = handles(pos);
end
catch
hdl2 = ports(pos).DstBlock;
end
hdl0 = hdl1;
while 1
switch MaskType(hdl2)
case name2
break
case 'Outport'
port_no = str2num(get_param(hdl2,'Port'));
ports = get_param(hdl2,'PortConnectivity');
hdl0 = hdl2;
hdl2 = ports(port_no).DstBlock;
case 'PMIOPort'
port_no = str2num(get_param(hdl2,'Port'));
ports = get_param(hdl2,'PortConnectivity');
hdl0 = hdl2;
hdl2 = ports(port_no).DstBlock;
case 'SubSystem'
ports = get_param(hdl2,'PortConnectivity');
port_no = num2str(find([ports(:).SrcBlock] == hdl1));
if isempty(port_no)
port_no = num2str(find([ports(:).DstBlock] == hdl1));
end
hdl0 = hdl2;
hdl2 = find_system(hdl2,'SearchDepth',1,'Port',port_no);
case 'Goto'
tag = get_param(hdl2,'GotoTag');
name = find_system(gcs,'BlockType','From','GotoTag',tag);
from = get_param(name{1},'Handle');
ports = get_param(from,'PortConnectivity');
hdl0 = hdl2;
hdl2 = ports(1).DstBlock;
case 'Link'
ports = get_param(hdl2,'PortConnectivity');
if sum(strcmp(MaskType(hdl1),{'Pod','Cluster'}))
if strcmp(ports(3).DstBlock,'Bus')
hdl0 = hdl2;
hdl2 = ports(2).DstBlock; % Input Port
else
hdl0 = hdl2;
hdl2 = ports(3).DstBlock; % Output Port
end
elseif strcmp(MaskType(hdl0),MaskType(ports(2).DstBlock))
hdl0 = hdl2;
hdl2 = ports(3).DstBlock; % Output Port
else
hdl0 = hdl2;
hdl2 = ports(2).DstBlock; % Input Port
end
case 'Line'
switch MaskType(hdl1)
case {'Breaker','Upfc','Tcsc','Sssc'}
hdl0 = hdl2;
hdl2 = SeekSrcBlock(hdl1,'Bus',1);
otherwise
SimWarnMsg(hdl1,'cannot be connected to',hdl2)
end
break
case {'Breaker','Sssc','Upfc','Tcsc','Mass'}
ports = get_param(hdl2,'PortConnectivity');
hdl_temp = hdl0;
hdl0 = hdl2;
hdl2 = ports(2).DstBlock; % Output Port
if hdl2 == hdl_temp
hdl2 = ports(1).DstBlock; % Output Port
end
case 'Link2'
ports = get_param(hdl2,'PortConnectivity');
hdl0 = hdl2;
hdl2 = ports(3).DstBlock; % Output Port
case 'Error'
SimWarnMsg(hdl1,'is badly connected')
hdl0 = hdl2;
hdl2 = hdl1; % to avoid errors in evaluating UserData
break
otherwise
SimWarnMsg(hdl1,'cannot be connected to',hdl2)
break
end
end
%------------------------------------------------------------------
function hdl2 = SeekSrcBlock(hdl1,name2,pos)
%------------------------------------------------------------------
ports = get_param(hdl1,'PortConnectivity');
if length(ports) < pos
SimWarnMsg(hdl1,'has the wrong number of ports')
hdl2 = hdl1; % to avoid errors in evaluating UserData
return
end
switch ports(pos).Type
case {'1','enable'}
hdl2 = ports(pos).SrcBlock;
otherwise
hdl2 = ports(pos).DstBlock;
end
hdl0 = hdl1;
while 1
switch MaskType(hdl2)
case name2
break
case 'Inport'
port_no = str2num(get_param(hdl2,'Port'));
ports = get_param(hdl2,'PortConnectivity');
hdl0 = hdl2;
hdl2 = ports(port_no).SrcBlock;
case 'PMIOPort'
port_no = str2num(get_param(hdl2,'Port'));
ports = get_param(hdl2,'PortConnectivity');
hdl0 = hdl2;
hdl2 = ports(port_no).DstBlock;
case 'SubSystem'
ports = get_param(hdl2,'PortConnectivity');
port_no = num2str(find([ports(:).DstBlock] == hdl1));
hdl0 = hdl2;
hdl2 = find_system(hdl2,'SearchDepth',1,'Port',port_no);
case 'From'
tag = get_param(hdl2,'GotoTag');
name = find_system(gcs,'BlockType','Goto','GotoTag',tag)
goto = get_param(name{1},'Handle');
ports = get_param(goto,'PortConnectivity');
hdl0 = hdl2;
hdl2 = ports(1).SrcBlock;
case 'Link'
ports = get_param(hdl2,'PortConnectivity');
if strcmp(MaskType(hdl0),MaskType(ports(2).DstBlock))
hdl0 = hdl2;
hdl2 = ports(3).DstBlock; % Output Port
else
hdl0 = hdl2;
hdl2 = ports(2).DstBlock; % Input Port
end
case 'Bus'
switch MaskType(hdl1)
case {'Breaker','Sssc','Upfc','Tcsc'}
hdl0 = hdl2;
hdl2 = SeekDstBlock(hdl1,'Line',2);
otherwise
SimWarnMsg(hdl1,'cannot be connected to',hdl2)
end
break
case {'Breaker','Sssc','Upfc','Tcsc'}
ports = get_param(hdl2,'PortConnectivity');
hdl_temp = hdl0;
hdl0 = hdl2;
hdl2 = ports(1).DstBlock; % Output Port
if hdl2 == hdl_temp
hdl2 = ports(2).DstBlock; % Output Port
end
case 'Link2'
ports = get_param(hdl2,'PortConnectivity');
hdl0 = hdl2;
if strcmp(MaskType(hdl1),'Pod')
if strcmp(MaskType(ports(2).DstBlock),name2)
hdl2 = ports(2).DstBlock; % Input Port
break
elseif strcmp(MaskType(ports(3).DstBlock),name2)
hdl2 = ports(3).DstBlock; % Output Port
break
else
% try to follow one path (50% likely to succeed)
hdl2 = ports(3).DstBlock; % Output Port
end
else
hdl2 = ports(2).DstBlock; % Input Port
end
case 'Error'
SimWarnMsg(hdl1,'is badly connected')
hdl0 = hdl2;
hdl2 = hdl1; % to avoid errors in evaluating UserData
break
otherwise
SimWarnMsg(hdl1,'cannot be connected to',hdl2)
break
end
end
%------------------------------------------------------------------
function SimWarnMsg(varargin)
%------------------------------------------------------------------
handle1 = varargin{1};
msg = varargin{2};
hilite_system(handle1,'default')
name1 = get_param(handle1,'Name');
if nargin == 2
fm_disp(['Error: Block <',name1,'> ',msg,'.'])
elseif nargin == 3
handle2 = varargin{3};
name2 = get_param(handle2,'Name');
fm_disp(['Error: Block <',name1,'> ',msg,' block <',name2,'>.'])
end
%------------------------------------------------------------------
function WriteNames(fid,type,names)
%------------------------------------------------------------------
if isempty(names), return, end
n = length(names);
count = fprintf(fid, [type,'.names = {... \n ']);
for i = 1:n-1
name = strrep(names{i,1},char(10),' ');
count = fprintf(fid, ['''',name,'''; ']);
if rem(i,5) == 0; count = fprintf(fid,'\n '); end
end
if iscell(names)
name = strrep(names{n,1},char(10),' ');
count = fprintf(fid, ['''',name,'''};\n\n']);
else
name = strrep(names,char(10),' ');
count = fprintf(fid, ['''',name,'''};\n\n']);
end
%------------------------------------------------------------------
function SimUpdate(sys)
%------------------------------------------------------------------
global Settings
sys = getfullname(sys);
hilite_system(sys,'none')
block = find_system(sys,'Type','block');
mask = get_param(block,'MaskType');
nblock = length(block);
% check if all blocks belong to the PSAT Library
Tags = get_param(block,'Tag');
BlockTypes = get_param(block,'BlockType');
idx = ones(nblock,1);
idx(strmatch('PSATblock',Tags,'exact')) = 0;
idx(strmatch('SubSystem',BlockTypes,'exact')) = 0;
idx(strmatch('PMIOPort',BlockTypes,'exact')) = 0;
if sum(idx)
idx = find(idx);
fm_disp(fm_strjoin('* * Warning: Block <',get_param(block(idx),'Name'), ...
'> does not belong to the PSAT Simulink Library.'))
Settings.ok = 0;
uiwait(fm_choice(['Some blocks do not seem to belong to the ', ...
'PSAT library, but could be old blocks. ', ...
'Do you want to fix them?']))
if Settings.ok
for iii = 1:length(idx)
blocktype = mask{idx(iii)};
if isempty(blocktype)
blocktype = get_param(block{idx(iii)},'BlockType');
end
switch blocktype
case {'Bus','Link','Goto','From'}
prop = 'Connection';
case {'Supply','Demand','Rmpg','Rrsv','Vltn','Rmpl','Ypdp'}
prop = 'OPF & CPF';
case {'Breaker','Fault'}
prop = 'Faults & Breakers';
case 'Busfreq'
prop = 'Measurements';
case {'Mn','Pl','Thload','Fl','Exload'}
prop = 'Loads';
case {'Syn','Ind','Mot'}
prop = 'Machines';
case {'Ltc','Tap'}
prop = 'ULTC';
case 'Phs'
prop = 'Phase Shifter';
case {'Tg','Exc','Cac','Cluster','Pss','Oxl'}
prop = 'Controls';
case {'Statcom','Upfc','Svc','Hvdc','Tcsc','Sssc'}
prop = 'FACTS';
case {'Dfig','Cswt','Ddsg'}
prop = 'Wind Turbines';
case {'Sofc','SSR','RLC','Mass','Spv','Spq'}
prop = 'Sparse Dynamic Component';
%case {'SAE1','SAE2','SAE3'}
% prop = 'SAE';
otherwise
prop = 'Power Flow';
end
set_param(block{idx(iii)}, ...
'Tag','PSATblock', ...
'Description',prop)
end
save_system(sys);
end
else
fm_disp(' ')
fm_disp('* * All blocks belong to the PSAT-Simulink Library.')
end
% check for old models
slackbus = find_system(sys,'MaskType','SW');
ports = get_param(slackbus,'Ports');
if isempty(ports)
fm_disp('* * * Error: No Slack bus found!')
pvbus = find_system(sys,'MaskType','PV');
ports = get_param(pvbus,'Ports');
end
if isempty(ports)
check = 1;
fm_disp('* * Error: No connections found!')
elseif iscell(ports)
check = sum(ports{1});
elseif isnumeric(ports)
check = sum(ports);
end
% check if model needs to be updated
if ~check
disp(' ')
fm_disp('* * Warning: The model refers to an old PSAT-Simulink')
fm_disp(' library. PSAT will try to update models.')
disp(' ')
Settings.ok = 0;
uiwait(fm_choice(['The model refers to an old PSAT-Simulink ' ...
'library. Update?'],1))
if ~Settings.ok, return, end
else
return
end
load_system('fm_lib');
open_system(sys);
for i = 1:nblock
% fix source block if it has changed
try
source = get_param(block{i},'SourceBlock');
switch source
case 'fm_lib/Power Flow/Transf5'
set_param(block{i},'SourceBlock','fm_lib/Power Flow/Twt')
case ['fm_lib/Wind',char(10),'Turbines/Cswt1']
set_param(block{i},'SourceBlock',['fm_lib/Wind',char(10),'Turbines/Cswt'])
case ['fm_lib/Wind',char(10),'Turbines/Dfig1']
set_param(block{i},'SourceBlock',['fm_lib/Wind',char(10),'Turbines/Ddsg'])
case ['fm_lib/Wind',char(10),'Turbines/Dfig2']
set_param(block{i},'SourceBlock',['fm_lib/Wind',char(10),'Turbines/Dfig'])
case ['fm_lib/Wind',char(10),'Turbines/Wind1']
set_param(block{i},'SourceBlock',['fm_lib/Wind',char(10),'Turbines/Wind'])
case 'fm_lib/Power Flow/Extra Line'
set_param(block{i},'SourceBlock','fm_lib/Power Flow/Lines')
case 'fm_lib/Power Flow/PQ1'
set_param(block{i},'SourceBlock','fm_lib/Power Flow/PQgen')
case 'fm_lib/Machines/Gen'
set_param(block{i},'SourceBlock','fm_lib/Machines/Syn')
case 'fm_lib/ULTC/LTC'
set_param(block{i},'SourceBlock','fm_lib/ULTC/Ltc')
case 'fm_lib/ULTC/OLTC'
set_param(block{i},'SourceBlock','fm_lib/ULTC/Tap')
case 'fm_lib/ULTC/PHS'
set_param(block{i},'SourceBlock','fm_lib/ULTC/Phs')
case 'fm_lib/Others/SOFC'
set_param(block{i},'SourceBlock','fm_lib/Others/Sofc')
case 'fm_lib/Others/SSR'
set_param(block{i},'SourceBlock','fm_lib/Others/Ssr')
case 'fm_lib/Measurements/SPV'
set_param(block{i},'SourceBlock','fm_lib/Others/Spv')
case 'fm_lib/Measurements/SPQ'
set_param(block{i},'SourceBlock','fm_lib/Others/Spq')
case 'fm_lib/Measurements/PMU'
set_param(block{i},'SourceBlock','fm_lib/Measurements/Pmu')
case 'fm_lib/Loads/FDL'
set_param(block{i},'SourceBlock','fm_lib/Loads/Fl')
case 'fm_lib/Loads/LRL'
set_param(block{i},'SourceBlock','fm_lib/Loads/Exload')
case 'fm_lib/Loads/TCL'
set_param(block{i},'SourceBlock','fm_lib/Loads/Thload')
case 'fm_lib/Loads/Mixed'
set_param(block{i},'SourceBlock','fm_lib/Loads/Mixload')
case 'fm_lib/Loads/VDL'
set_param(block{i},'SourceBlock','fm_lib/Loads/Mn')
case 'fm_lib/Loads/ZIP'
set_param(block{i},'SourceBlock','fm_lib/Loads/Pl')
case 'fm_lib/FACTS/HVDC'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Hvdc')
case 'fm_lib/FACTS/SSSC'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Sssc')
case 'fm_lib/FACTS/SVC (1)'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Svc')
case 'fm_lib/FACTS/SVC (2)'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Svc2')
case 'fm_lib/FACTS/StatCom'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Statcom')
case 'fm_lib/FACTS/TCSC (1)'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Tcsc')
case 'fm_lib/FACTS/TCSC (2)'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Tcsc2')
case 'fm_lib/FACTS/UPFC'
set_param(block{i},'SourceBlock','fm_lib/FACTS/Upfc')
case 'fm_lib/Connections/Link'
set_param(block{i},'SourceBlock','fm_lib/Connections/Link1')
case 'fm_lib/OPF & CPF/RMPG'
set_param(block{i},'SourceBlock','fm_lib/OPF & CPF/Rmpg')
case 'fm_lib/OPF & CPF/RMPL'
set_param(block{i},'SourceBlock','fm_lib/OPF & CPF/Rmpl')
case 'fm_lib/OPF & CPF/RSRV'
set_param(block{i},'SourceBlock','fm_lib/OPF & CPF/Rsrv')
case 'fm_lib/OPF & CPF/VLTN'
set_param(block{i},'SourceBlock','fm_lib/OPF & CPF/Vltn')
case 'fm_lib/OPF & CPF/YPDP'
set_param(block{i},'SourceBlock','fm_lib/OPF & CPF/Ypdp')
case 'fm_lib/OPF & CPF/YPDP1'
set_param(block{i},'SourceBlock','fm_lib/OPF & CPF/Ypdp1')
case 'fm_lib/Controls/AVR'
set_param(block{i},'SourceBlock','fm_lib/Controls/Exc')
case 'fm_lib/Controls/TG'
set_param(block{i},'SourceBlock','fm_lib/Controls/Tg')
case 'fm_lib/Controls/SSCL'
set_param(block{i},'SourceBlock','fm_lib/Controls/Pod')
case 'fm_lib/Controls/OXL'
set_param(block{i},'SourceBlock','fm_lib/Controls/Oxl')
case 'fm_lib/Controls/PSS'
set_param(block{i},'SourceBlock','fm_lib/Controls/Pss')
case 'fm_lib/Controls/CAC'
set_param(block{i},'SourceBlock','fm_lib/Controls/Cac')
case 'fm_lib/Controls/Shaft'
set_param(block{i},'SourceBlock','fm_lib/Others/Mass')
end
mask{i} = get_param(block{i},'MaskType');
catch
% the source block has not changed
end
switch mask{i}
case {'Bus','Link','Line','Lines','Breaker','Twt' ...
'Phs','Tcsc','Sssc','Upfc','Hvdc','Dfig', ...
'Cswt','Ddsg','RLC','PV','SW','PQgen','Spv','Spq', ...
'Rmpg','Rsrv','Vltn','Wind','Sofc','Ssr', ...
'PQ','Shunt','Rmpl','Fault','Mn','Pl','Ind','Mot', ...
'Fl','Exload','Mixload','Thload','Jimma','Tap', ...
'Svc','Statcom','Busfreq','Pmu','Supply', ...
'Demand','Syn','Ltc','SAE1','SAE2','SAE3', ...
'Exc','Tg','Sscl','Cac','Oxl','Pss','Cluster'}
cloneblock(block{i},sys)
end
end
lines = find_system(sys,'FindAll','on','type','line');
for i = 1:length(lines)
points = get_param(lines(i),'Points');
parent = get_param(lines(i),'Parent');
delete_line(parent,points(1,:));
try
add_line(parent,points);
catch
fm_disp(['* * Connection line ',num2str(i),' could not be replaced.'])
end
end
uiwait(fm_choice('Now please take a moment to doublecheck connections...',2))
fm_disp(' ')
fm_disp(['* * Update of model <',sys,'> completed.'])
|
github
|
Sinan81/PSAT-master
|
psat2epri.m
|
.m
|
PSAT-master/psat-oct/psat/filters/psat2epri.m
| 10,049 |
utf_8
|
fd2ab45d2c3ab7faff9a51b6be3ac9d2
|
function check = psat2epri(filename, pathname)
% PSAT2EPRI converts PSAT data file into EPRI Data Format
%
% CHECK = PSAT2EPRI(FILENAME,PATHNAME)
% FILENAME name of the file to be converted
% PATHNAME path of the file to be converted
%
% CHECK = 1 conversion completed
% CHECK = 0 problem encountered (no data file created)
%
%Author: Federico Milano
%Date: 06-Oct-2003
%Version: 1.0.0
%
%E-mail: [email protected]
%Web-site: faraday1.ucd.ie/psat.html
%
% Copyright (C) 2002-2009 Federico Milano
global DAE Varname Settings
DAE_old = DAE;
Varname_old = Varname;
Settings_old = Settings;
if strcmp(pathname(end),filesep)
pathname = pathname(1:end-1);
end
if ~strcmp(pathname,pwd)
cd(pathname)
end
fm_disp
fm_disp(['Opening PSAT file "',filename,'"...'])
% General Settings
% -----------------------------------------------------------
check = 1;
b128 = [blanks(128),'\n'];
b12 = blanks(12);
% Defining local data structures
% -----------------------------------------------------------
Bus = BUclass;
Twt = TWclass;
Line = LNclass;
Shunt = SHclass;
SW = SWclass;
PV = PVclass;
PQ = PQclass;
PQgen = PQclass;
Ltc = LTclass;
Phs = PHclass;
% Reading Data from PSAT Data File
% -----------------------------------------------------------
a = exist(filename);
if a == 2,
eval(filename(1:end-2))
else,
fm_disp(['File "',filename,'" not found or not an m-file'],2)
check = 0;
return
end
% Completing data settings
% -----------------------------------------------------------
Bus = setup_bus(Bus);
Line = setup_line(Line,Bus);
Twt = setup_twt(Twt,Bus,Line);
Shunt = setup_shunt(Shunt,Bus);
PV = setup_pv(PV,Bus);
SW = setup_sw(SW,Bus,PV);
PQ = setup_pq(PQ,Bus);
PQgen = setup_pq(PQgen,Bus);
PQ = addgen_pq(PQ,PQgen,Bus);
Ltc = setup_ltc(Ltc,Bus);
Phs = setup_phs(Phs,Bus);
% Opening File
% -----------------------------------------------------------
newfile = [filename(1:end-2),'.wsc'];
fm_disp(['Writing WSCC file "',newfile,'"...'])
fid = fopen([pathname,filesep, newfile], 'wt');
comment = ['C\nC',repmat('*',1,79),'\nC\n'];
count = fprintf(fid,comment);
% Header and Title
% -----------------------------------------------------------
count = fprintf(fid,'HDG\n');
count = fprintf(fid,['PSAT ARCHIVE\n']);
count = fprintf(fid,[num2str(Bus.n),'-Bus ', ...
num2str(Line.n),'-Line System\n']);
count = fprintf(fid,[date,'\n']);
count = fprintf(fid,'BAS\n');
count = fprintf(fid,comment);
% Bus Data
% -----------------------------------------------------------
% Section Start card
idxPV = [];
idxPQ = [];
idxSW = [];
idxSH = [];
Busnames = cell(Bus.n,1);
% Scan each bus for data
for i = 1:Bus.n
% the following lines ensure that bus names
% are unique and with no repetitions
busname = Bus.names{i};
if length(busname) > 8,
busname = busname([1:8]);
end
idx = strmatch(busname,Bus.names);
if length(idx) > 1
idx = find(idx == i);
nn = length(num2str(idx));
busname([(end-idx+1):end]) = num2str(idx);
end
busname = [busname,blanks(8)];
busname = busname([1:8]);
Busnames{i,1} = busname;
count = fprintf(fid,'B');
idxPV = findbus_pv(PV,i);
idxPQ = findbus_pq(PQ,i);
idxSW = findbus_sw(SW,i);
if ~isempty(Shunt.con)
idxSH = find(Shunt.bus == i);
end
% Bus type
if ~isempty(idxSW)
count = fprintf(fid,'S ');
slackname = busname;
slackkV = Bus.con(i,2);
slackang = SW.con(idxSW,5);
elseif ~isempty(idxPV)
if PV.con(idxPV,6) == 0 && PV.con(idxPV,7) == 0
count = fprintf(fid,'E ');
else
count = fprintf(fid,'Q ');
end
elseif ~isempty(idxPQ)
if PQ.con(idxPQ,6) == 0 && PQ.con(idxPQ,7) == 0
count = fprintf(fid,' ');
else
count = fprintf(fid,'V ');
PQ.con(idxPQ,4) = PQ.con(idxPQ,4);
PQ.con(idxPQ,5) = PQ.con(idxPQ,5);
end
else
count = fprintf(fid,' ');
end
% Bus name, voltage rate and zone
kV = Bus.con(i,2);
count = fprintf(fid,['%s',tr(kV,4),' '],busname,kV);
% Load powers
if ~isempty(idxPQ)
P = PQ.con(idxPQ,4)*PQ.con(idxPQ,2);
Q = PQ.con(idxPQ,5)*PQ.con(idxPQ,2);
count = fprintf(fid,[tr(P,5),tr(Q,5)],P,Q);
else
count = fprintf(fid,blanks(10));
end
% Shunts
if ~isempty(idxSH)
G = Shunt.con(idxSH,5)*Shunt.con(idxSH,2)/(Shunt.con(idxSH,3)^2);
B = Shunt.con(idxSH,6)*Shunt.con(idxSH,2)/(Shunt.con(idxSH,3)^2);
count = fprintf(fid,[tr(G,4),tr(B,4)],G,B);
else
count = fprintf(fid,blanks(8));
end
% Generator powers and limits
if ~isempty(idxPV)
PM = PV.con(idxPV,2);
Pg = PV.con(idxPV,4)*PV.con(idxPV,2);
count = fprintf(fid,[tr(PM,4),tr(Pg,5)],PM,Pg);
if PV.con(idxPV,6) ~= 0 || PV.con(idxPV,7) ~= 0
QM = PV.con(idxPV,6)*PV.con(idxPV,2);
Qm = PV.con(idxPV,7)*PV.con(idxPV,2);
if QM < Qm
dummy = QM;
QM = Qm;
Qm = dummy;
end
count = fprintf(fid,[tr(QM,5),tr(Qm,5)],QM,Qm);
else
count = fprintf(fid,blanks(10));
end
elseif ~isempty(idxSW)
PM = SW.con(idxSW,2);
Pg = SW.con(idxSW,10)*SW.con(idxSW,2);
count = fprintf(fid,[tr(PM,4),tr(Pg,5)],PM,Pg);
if SW.con(idxSW,6) ~= 0 || SW.con(idxSW,7) ~= 0
QM = SW.con(idxSW,6)*SW.con(idxSW,2);
Qm = SW.con(idxSW,7)*SW.con(idxSW,2);
if QM < Qm
dummy = QM;
QM = Qm;
Qm = dummy;
end
count = fprintf(fid,[tr(QM,5),tr(Qm,5)],QM,Qm);
else
count = fprintf(fid,blanks(10));
end
else
count = fprintf(fid,blanks(19));
end
% Desired or maximum voltage
if ~isempty(idxPV)
count = fprintf(fid,'%-4.2f',PV.con(idxPV,5));
elseif ~isempty(idxSW)
count = fprintf(fid,'%-4.2f',SW.con(idxSW,4));
elseif ~isempty(idxPQ)
if PQ.con(idxPQ,6) ~= 0
count = fprintf(fid,'%-4.2f',PQ.con(idxPQ,6));
else
count = fprintf(fid,blanks(4));
end
else
count = fprintf(fid,blanks(4));
end
% Minimum voltage
if ~isempty(idxPQ)
if PQ.con(idxPQ,7) ~= 0
count = fprintf(fid,'%-4.2f',PQ.con(idxPQ,7));
else
count = fprintf(fid,blanks(4));
end
else
count = fprintf(fid,blanks(4));
end
% Remote name, kV and %Q are not Used by PSAT
% ...
% End of line
count = fprintf(fid,'\n');
end
count = fprintf(fid,comment);
% Line and transformer data
% -----------------------------------------------------------
% Scan each line for data
for i = 1:Line.n
m = Line.con(i,1);
n = Line.con(i,2);
if Line.con(i,7)
count = fprintf(fid,'T ');
else
count = fprintf(fid,'L ');
end
count = fprintf(fid,'%s',Busnames{m});
count = fprintf(fid,tr(Bus.con(m,2),4),Bus.con(m,2));
count = fprintf(fid,' %s',Busnames{n});
count = fprintf(fid,tr(Bus.con(n,2),4),Bus.con(n,2));
if Line.con(i,7)
In = Line.con(i,3);
else
In = Line.con(i,3)*1e3/Line.con(i,4)/sqrt(3);
end
count = fprintf(fid,[' ',tr(In,4)],In);
R = Line.con(i,8);
X = Line.con(i,9);
B = Line.con(i,10)/2;
count = fprintf(fid,' %-6.4f%-6.4f%-6.4f%-6.4f',R,X,0.0,B);
if Line.con(i,7)
if Line.con(i,11)
T = Line.con(i,11)*Line.con(i,4);
count = fprintf(fid,'%-5.2f',T);
T = Line.con(i,4)/Line.con(i,7);
count = fprintf(fid,'%-5.2f',T);
end
else
if Line.con(i,6)
% conversion to miles
L = Line.con(i,6)*0.621371;
count = fprintf(fid,tr(L,4),L);
end
end
count = fprintf(fid,'\n');
end
% End line data
count = fprintf(fid,comment);
% Regulating Transformer Data
% -----------------------------------------------------------
for i = 1:Ltc.n
switch Ltc.con(i,16)
case 1, count = fprintf(fid,'R ');
case 2, count = fprintf(fid,'RQ ');
case 3, count = fprintf(fid,'R ');
end
m = Ltc.bus1(i);
n = Ltc.bus2(i);
k = Ltc.busc;
count = fprintf(fid,'%s',Busnames{m});
count = fprintf(fid,tr(Bus.con(m,2),4),Bus.con(m,2));
count = fprintf(fid,' %s',Busnames{n});
count = fprintf(fid,tr(Bus.con(n,2),4),Bus.con(n,2));
count = fprintf(fid,'%s',Busnames{k});
count = fprintf(fid,tr(Bus.con(k,2),4),Bus.con(k,2));
count = fprintf(fid,'%-5.2f%-5.2f', ...
Ltc.con(i,9)*Bus.con(m,2), ...
Ltc.con(i,10)*Bus.con(m,2));
if Ltc.con(i,11)
ntap = (Ltc.con(i,9)-Ltc.con(i,10))/Ltc.con(i,11);
else
ntap = 11;
end
count = fprintf(fid,tr(ntap,2),ntap);
if Ltc.con(i,16) == 2
count = fprintf(fid,tr(Ltc.con(i,12),5),Ltc.con(i,12));
end
end
for i = 1:Phs.n
count = fprintf(fid,'RP ');
m = Phs.bus1(i);
n = Phs.bus2(i);
count = fprintf(fid,'%s',Busnames{m});
count = fprintf(fid,tr(Bus.con(m,2),4),Bus.con(m,2));
count = fprintf(fid,' %s',Busnames{n});
count = fprintf(fid,tr(Bus.con(n,2),4),Bus.con(n,2));
count = fprintf(fid,'%s',Busnames{n});
count = fprintf(fid,tr(Bus.con(n,2),4),Bus.con(n,2));
count = fprintf(fid,'%-5.2f%-5.2f', ...
Phs.con(i,13)*180/pi, ...
Phs.con(i,14)*180/pi);
count = fprintf(fid,'%d',11);
count = fprintf(fid,tr(Phs.con(i,10),5),Phs.con(i,10));
end
if Ltc.n || Phs.n
% End of regulating transformer data
count = fprintf(fid,comment);
end
% Area Data
% -----------------------------------------------------------
% ... PSAT does not currently support areas ...
% Solution control data
% -----------------------------------------------------------
count = fprintf(fid,['SOL',blanks(20)]);
count = fprintf(fid,'%-5i ',Settings.lfmit);
count = fprintf(fid,'%s',slackname);
count = fprintf(fid,tr(slackkV,4),slackkV);
count = fprintf(fid,' %-10.4f\n',slackang);
% Closing the file
% -----------------------------------------------------------
count = fprintf(fid,'ZZ\n');
count = fprintf(fid,'END\n');
fclose(fid);
DAE = DAE_old;
Varname = Varname_old;
Settings = Settings_old;
fm_disp('Conversion completed.')
if Settings.beep, beep, end
% -----------------------------------------------------------
function string = tr(value,n)
threshold = 10^(n-2);
if value >= threshold || value < 0
string = '0';
else
string = '1';
end
string = ['%-',num2str(n),'.',string,'f'];
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
add_path.m
|
.m
|
Closed-Null-Geodesics-2D-master/add_path.m
| 644 |
utf_8
|
b693c741666d3c95b8f19581f1d83c7c
|
%------------------------------------Set path
function add_path
fp = mfilename('fullpath');
rootdir = fileparts(fp);
p{1} = fullfile(rootdir,'data');
p{2} = fullfile(rootdir,'doc');
p{3} = fullfile(rootdir,'Main');
p{4} = fullfile(rootdir,'Subfunctions');
for i = 1:4
addpath(rootdir,p{i});
end
%------------------------------------
fprintf('----------------------------*---------------------------------\n');
fprintf('data,...doc,...Main,...Subfunctions,...All paths have been added');
fprintf('\n')
fprintf('----------------------------*---------------------------------\n');
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
PlotOutmost.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/PlotOutmost.m
| 2,786 |
utf_8
|
c4ea33d3292589c47e67d3f2ecedd59a
|
% function PlotOutmost(xLcOutM,yLcOutM,LamLcOutM,lamV,x_g,y_g,lam2)
% Input arguments:
% xLcOutM : x-component of the outermost closed null-geodesics
% yLcOutM : x-component of the outermost closed null-geodesics
% LamLcOutM : \lambda values of the outermost closed null-geodesics
% lamV,lamV,x_g,y_g,lam2 : see step 1
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function PlotOutmost(xLcOutM,yLcOutM,LamLcOutM,lamV,x_g,y_g,lam2)
if ~isempty(LamLcOutM) % If there are closed null-geodesics
% Colormap encoding different \lambda values
cmap = jet(length(lamV));
% Plot properties
AxthicksFnt = 15;
fontsizeaxlab = 15;
% Initialize the figure with the FTLE plot
figure('units','normalized','outerposition',[0 0 .5 .5]);
imagesc(x_g,y_g,log(lam2)/30/2);shading interp
set(gca,'FontSize',AxthicksFnt,'fontWeight','normal')
hold on
set(gca,'YDir','normal')
set(gcf,'color','w');
axis equal
xlabel('$$Lon [^{\circ}]$$','Interpreter','latex','FontWeight','bold','FontSize',fontsizeaxlab);
ylabel('$$Lat [^{\circ}]$$','Interpreter','latex','FontWeight','bold','FontSize',fontsizeaxlab);
axis equal tight
colormap(gca,'gray')
hhF=colorbar(gca);
hhF.Location='westOutside';
hhF.FontSize=fontsizeaxlab;
set(get(hhF,'xlabel'),'string','$$FTLE$$','Interpreter','latex','FontWeight','normal');
% Plot outermost Closed null-geodesics
for kkmuv=1:1:length(LamLcOutM)
Lamidx=find(lamV==LamLcOutM(kkmuv));
xlc=xLcOutM{kkmuv};
ylc=yLcOutM{kkmuv};
hold on
plot(xlc,ylc,'color',cmap(Lamidx,:),'linewidth',2.5);
end
axis equal tight
% Add a second colorbar encoding the different \lambda values
ax1 = gca;
ax1_pos = ax1.Position; % position of first axes
ax2 = axes('Position',ax1_pos,...
'XAxisLocation','bottom',...
'YAxisLocation','left',...
'Color','none');
hhF2 = colorbar(ax2,'eastOutside');
hhF2.FontSize = AxthicksFnt;
set(get(hhF2,'xlabel'),'string','$$\lambda$$','Interpreter','latex','FontWeight','normal');
colormap(ax2,'jet')
hhF2.Ticks=linspace(0,1,3);
hhF2.XTickLabel={'0.9';'1';'1.1'};
set(ax2,'xtick',[])
set(ax2,'ytick',[])
set(ax2, 'visible', 'off') ;
end
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
Phi_prime.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/Phi_prime.m
| 2,243 |
utf_8
|
3c5f187b58b0314eee6b9906f4ae3a7e
|
%% References:
%[1] Mattia Serra and George Haller, "Efficient Computation of Null-Geodesic with
% Applications to Coherent Vortex Detection", sumbitted, (2016).
%%
% [phiPrGr,C22mC11Gr,C12Gr]=Phi_prime(C11,C11x1,C11x2,C12,C12x1,C12x2,C22,C22x1,C22x2,x1_g,x2_g)
% Input arguments:
% Cij : ij entries of the C strain tensor
% Cijx1 : x1-derivatice of the Cij entry
% Cijx2 : x2-derivatice of the Cij entry
% x1_g : x1 component of the spatial grid
% x2_g : x2 component of the spatial grid
% Output argument:
% C22mC11Gr: gridded interpolant object for C22(x,y)-C11(x,y)
% C12Gr : gridded interpolant object for C12(x,y)
% phiPrGr : gridded interpolant object for \phi'(x,\phi)
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function [phiPrGr,C22mC11Gr,C12Gr]=Phi_prime(C11,C11x1,C11x2,C12,C12x1,C12x2,C22,C22x1,C22x2,x1_g,x2_g)
%Define the \phi component of the spatial grid
phi_g = linspace(0,2*pi,180);
% Constract 3D arrays to build the gridded interpolant for \phi'
C113df = repmat(C11,1,1,numel(phi_g));
C123df = repmat(C12,1,1,numel(phi_g));
C223df = repmat(C22,1,1,numel(phi_g));
C11x3d = repmat(C11x1,1,1,numel(phi_g));
C11y3d = repmat(C11x2,1,1,numel(phi_g));
C12x3d = repmat(C12x1,1,1,numel(phi_g));
C12y3d = repmat(C12x2,1,1,numel(phi_g));
C22x3d = repmat(C22x1,1,1,numel(phi_g));
C22y3d = repmat(C22x2,1,1,numel(phi_g));
[~,~,Z3d]=meshgrid(x1_g,x2_g,phi_g);
% phi' (cf. eq. (38) of [1])
phiPr = -((C11x3d.*cos(Z3d)+C11y3d.*sin(Z3d)).*cos(Z3d).^2+(C12x3d.*cos(Z3d)+C12y3d.*sin(Z3d)).*sin(2*Z3d)+(C22x3d.*cos(Z3d)+C22y3d.*sin(Z3d)).*sin(Z3d).^2)./(sin(2*Z3d).*(C223df-C113df)+2*cos(2*Z3d).*C123df);
phiPrGr = griddedInterpolant ({x1_g,x2_g,phi_g},permute(phiPr,[2 1 3]),'linear');
% Compute the (x)-dependent functions needed to define the domain of
% existence V (cf. eq. (37) of [1]) of the reduced 3D null-geodesic flow (cf. eq. (38) of [1]).
C22mC11Gr = griddedInterpolant ({x1_g,x2_g},permute(C22-C11,[2 1]),'linear');
C12Gr = griddedInterpolant ({x1_g,x2_g},permute(C12,[2 1]),'linear');
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
FindOutermost.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/FindOutermost.m
| 2,834 |
utf_8
|
803304c13610eb9655ad4a5d39d10c44
|
%% References:
%[1] Mattia Serra and George Haller, "Efficient Computation of Null-Geodesic with
% Applications to Coherent Vortex Detection", sumbitted, (2016).
%%
% function [xLcOutM,yLcOutM,LamLcOutM]=FindOutermost(xPsol,yPsol,lamV,sVec);
% Input arguments:
% x1Psol : x1-component of closed null-geodesics
% x2Psol : x2-component of closed null-geodesics
% lamV : see steps 0-1
% sVec : see step 3
% Output arguments:
% xLcOutM : x1-component of the outermost closed null-geodesics
% yLcOutM : x2-component of the outermost closed null-geodesics
% LamLcOutM : \lambda values corresponding to the outermost closed null-geodesics
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function [xLcOutM,yLcOutM,LamLcOutM]=FindOutermost(xPsol,yPsol,lamV,sVec)
NMaxPts=length(sVec);
xlcEx=[];ylcEx=[];lamfin=[];xcPos=[];ycPos=[];AreaLc=[];
for kkmuv=1:1:length(lamV)
%save all the final curves in a cell
xxapp=xPsol{kkmuv};
yyapp=yPsol{kkmuv};
if ~isempty(xxapp)
for kkc=1:size(xxapp,2)
xlc=xxapp(~isnan(xxapp(:,kkc)),kkc);
ylc=yyapp(~isnan(yyapp(:,kkc)),kkc);
%close the curve
xlc(end)=xlc(1); ylc(end)=ylc(1);
%compute the area
Alc = polyarea(xlc,ylc);
xlcEx=[xlcEx,[xlc(:);nan(NMaxPts-length(xlc),1)]];
ylcEx=[ylcEx,[ylc(:);nan(NMaxPts-length(xlc),1)]];
xCentLc=mean(xlc);yCentLc=mean(ylc);
xcPos=[xcPos,xCentLc];ycPos=[ycPos,yCentLc];
AreaLc=[AreaLc,Alc];
lamfin=[lamfin,lamV(kkmuv)];
end
end
end
% Sort the Lc in decreasing Area
[~,ind]=sort(AreaLc,'descend');
AreaLc=AreaLc(ind);
xcPos=xcPos(ind);ycPos=ycPos(ind);
xlcEx=xlcEx(:,ind);ylcEx=ylcEx(:,ind);lamfin=lamfin(ind);
% Extract the outermost
toDel=[];
MatCheck=nan(size(xlcEx,2),size(xlcEx,2));
for kkmuv=1:1:size(xlcEx,2)
xxapp=xlcEx(~isnan(xlcEx(:,kkmuv)),kkmuv);
yyapp=ylcEx(~isnan(ylcEx(:,kkmuv)),kkmuv);
in=inpolygon(xcPos,ycPos,xxapp,yyapp);
MatCheck(kkmuv,:)=in;
end
for kkmuv=1:1:size(MatCheck,2)
vettIdx=kkmuv+1:length(AreaLc);
VettMat=MatCheck(kkmuv,kkmuv+1:size(MatCheck,2));
ToDelvett=vettIdx(VettMat==1);
toDel=[toDel,ToDelvett];
end
toDel=unique(toDel);
xlcEx(:,toDel)=[];
ylcEx(:,toDel)=[];
lamfin(toDel)=[];
% Store the outermost closed null-geodesic
xLcOutM=cell(1,size(xlcEx,2));
yLcOutM=cell(1,size(xlcEx,2));
LamLcOutM=nan(1,size(xlcEx,2));
for kkpl=1:size(xlcEx,2)
LamLcOutM(kkpl)=lamfin(kkpl);
xLcOutM{kkpl}=xlcEx(~isnan(xlcEx(:,kkpl)),kkpl);
yLcOutM{kkpl}=ylcEx(~isnan(xlcEx(:,kkpl)),kkpl);
end
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
FindClosedNullGeod.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/FindClosedNullGeod.m
| 3,053 |
utf_8
|
e648b671dcb8d9222859dbc53f0cb579
|
%% References:
%[1] Mattia Serra and George Haller, "Efficient Computation of Null-Geodesic with
% Applications to Coherent Vortex Detection", sumbitted, (2016).
%%
% function [x1Psol,x2Psol]=FindClosedNullGeod(C22mC11Gr,C12Gr,phiPrGr,x1_g,x2_g,lamV,sVec,options);
% Input arguments:
% C22mC11Gr, C12Gr, phiPrGr : see step 2
% x1_g, x2_g, lamV : see steps 0-1
% sVec, options : see step 3
% NCores : Number of cores for Parallel computing
% Output arguments:
% x1Psol : x1-component of closed null-geodesics
% x2Psol : x2-component of closed null-geodesics
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function [x1Psol,x2Psol]=FindClosedNullGeod(C22mC11Gr,C12Gr,phiPrGr,x0lam,y0lam,phi0lam,x1_g,x2_g,lamV,sVec,options,NCores);
% Initialize the variables containing the periodic solutions of the
% initial value problem
x1Psol = cell(1,length(lamV));
x2Psol = x1Psol;
phiPsol = x1Psol;
% Define the limits of the (x-y) domain to stop particles at the
% boundary
x1_glim = [min(x1_g),max(x1_g)];
x2_glim = [min(x2_g),max(x2_g)];
tic
% Compute closed orbits of the Initial Value Problem (cf. eqs. (38-39) of [1])
for kklam = 1:1:length(lamV)
kklam
% Extract the r0_lam for the current value of \lambda
x0 = x0lam{kklam};
y0 = y0lam{kklam};
phi0 = phi0lam{kklam};
lam=lamV(kklam);
%% Opening MATLAB Pool %%
Np=size(x0,1);
cpu_num = min(NCores,Np);
id = ceil( linspace(0,Np,cpu_num+1) );
poolobj = gcp('nocreate'); % If no pool, do not create new one.
if isempty(poolobj) % if parpool is not open
parpool('local',cpu_num)
elseif (~isempty(poolobj)) && (poolobj.NumWorkers~=cpu_num) % if parpool is not consistent with cpu_num
delete(gcp)
parpool('local',cpu_num)
end
%% Integrate the ODE (38) in [1]
tic
spmd
Range = id(labindex)+1:id(labindex+1);
Z0loc = [x0(Range);y0(Range);phi0(Range)];
[~,xxfTot,yyfTot,zzfTot] = Advect_r(phiPrGr,C22mC11Gr,C12Gr,x1_glim,x2_glim,sVec,Z0loc,options);
end
toc
% Put the trajectories of ODE (38) in matrix form
X_Vf = cat(2,xxfTot{:});
Y_Vf = cat(2,yyfTot{:});
Z_Vf = cat(2,zzfTot{:});
%Warning in case of dimensionality mismatch
if size(X_Vf,2)~=length(x0)
disp('smpd dim. mismatch')
end
% Find periodic solutions
[X1lco,X2lco,philco] = PeriodicSolutions(X_Vf,Y_Vf,Z_Vf);
% Final curves in a cell
x1Psol{kklam} = X1lco;
x2Psol{kklam} = X2lco;
phiPsol{kklam} = philco;
end
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
Advect_r.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/Advect_r.m
| 2,455 |
utf_8
|
978d0c7efae18777e437ca0a4f95e6a9
|
%% References:
%[1] Mattia Serra and George Haller, "Efficient Computation of Null-Geodesic with
% Applications to Coherent Vortex Detection", sumbitted, (2016).
%%
% function [~,xxx,yyy,zzz]=Advect_r(phiPrGr,C22mC11Gr,C12Gr,x_glim,y_glim,sVec,Z0,options)
% Input arguments:
% C22mC11Gr, C12Gr, phiPrGr : see step 2
% x1_glim, x2_glim, : domain limits to stop particles if they
% reach the boundaries
% sVec, options : see step 3
% Z0 : Initial conditions
% Output arguments:
% xxx : x1-component of trajectories of the ODE (38) in [1]
% yyy : x2-component of trajectories of the ODE (38) in [1]
% zzz : \phi-component of trajectories of the ODE (38) in [1]
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function [Time,xxx,yyy,zzz] = Advect_r(phiPrGr,C22mC11Gr,C12Gr,x1_glim,x2_glim,sVec,Z0,options)
% Shared variables
x1m = x1_glim(1);
x1M = x1_glim(2);
x2m = x2_glim(1);
x2M = x2_glim(2);
Np = numel(Z0)/3;
% Ode solver
[Time,XXXpartcl] = ode45(@(t,zVec)r_prime(zVec),sVec,Z0,options);
%% Function to evaluate r'(s) (cf. ODE (38) in [1])
function V_intrp = r_prime(zVecs)
XXxx=zVecs(1:Np);
YYyy=zVecs(1+Np:2*Np);
ZZzz=zVecs(1+2*Np:3*Np);
% Freeze particles at the boundaries of the doamin or when the ODE
% (38) is not defined
Bll=1+0*XXxx;
Bll(XXxx>x1M)=0;Bll(XXxx<x1m)=0;
Bll(YYyy>x2M)=0;Bll(YYyy<x2m)=0;
% Freeze particles at the boundaries of the domain of definition V (cf eq. (37) of [1]) of
% the ODE (38) of [1].
% Domain of existence
DoE=2*C12Gr(XXxx,YYyy).*cos(2*ZZzz)+sin(2*ZZzz).*C22mC11Gr(XXxx,YYyy);
Bll(abs(DoE)<1e-2)=0;
% Evaluate r'(s)
utemp_scp=cos(ZZzz);
vtemp_scp=sin(ZZzz);
wtemp_scp=phiPrGr(XXxx,YYyy,ZZzz);
Norma=sqrt(utemp_scp.^2+vtemp_scp.^2+wtemp_scp.^2);
V_intrp=[utemp_scp./Norma.*Bll;vtemp_scp./Norma.*Bll;wtemp_scp./Norma.*Bll];
end
xxx=XXXpartcl(:,1:Np);
yyy=XXXpartcl(:,1+Np:2*Np);
zzz=XXXpartcl(:,1+2*Np:3*Np);
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
r0_lam.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/r0_lam.m
| 2,234 |
utf_8
|
1be846cd61314ab3dd3afb6f7a3c7d25
|
%% References:
%[1] Mattia Serra and George Haller, "Efficient Computation of Null-Geodesic with
% Applications to Coherent Vortex Detection", sumbitted, (2016).
%%
% function [x0lam,y0lam,phi0lam]=r0_lam(lamV,C11,C12,C22,x_g,y_g)
% Input arguments:
% lamV : Desired set of \lambda values
% Cij : ij entries of the C strain tensor
% x_g : x component of the spatial grid
% y_g : y component of the spatial grid
% Output arguments:
% x0lam: x-coordinates of r0_lam
% y0lam: y-coordinates of r0_lam
% phi0lam: phi-coordinates of r0_lam
%Note: This function returns the intial condition r0_lam for any value of
%phi0 \in [0,2\pi). Since this choice is arbitrary, in [1]
%we picked phi0=0, leading to the simplified formula (39) in [1].
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function [x0lam,y0lam,phi0lam]=r0_lam(lamV,C11,C12,C22,x_g,y_g)
%Define the initial \phi value: \phi_0 (cf. Fig. 2 of [1])
phi0 = 0;
% Initialize the output variables
x0lam = cell(1,length(lamV));
y0lam = x0lam;
phi0lam = x0lam;
% Compute the initial conditions r0_\lambda for different values of \lambda
for kkmu = 1:length(lamV)
lam = (lamV(kkmu));
ZeroSet = (cos(phi0))^2*C11+sin(2*phi0)*C12+(sin(phi0))^2*C22-lam^2;
%Discard the points where out of the domain of existence V (cf. eq. (37) of [1])
DoE = 2*C12.*cos(2*phi0)+sin(2*phi0).*(C22-C11);
ZeroSet(abs(DoE)<1e-2) = nan;
% Extract the x_0(\lambda,\phi_0) (cf. Fig. 2b or eq.(39) of [1])
CC = contourc(x_g,y_g,ZeroSet,[0,0]);
ss = getcontourlines(CC);
XXvTzero = [];
YYvTzero = [];
for kkk=1:size(ss,2)
XXvTzero = [XXvTzero;(ss(kkk).x)'];
YYvTzero = [YYvTzero;(ss(kkk).y)'];
end
ZZvTzero = phi0+0*XXvTzero;
% Cell variables containing the x,y,\phi coordinates of \lambda-dependent zero level set
x0lam{kkmu} = XXvTzero;
y0lam{kkmu} = YYvTzero;
phi0lam{kkmu} = ZZvTzero;
end
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
PeriodicSolutions.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/PeriodicSolutions.m
| 5,724 |
utf_8
|
89699760a218aea7448fc5c4c93964b2
|
%% References:
%[1] Mattia Serra and George Haller, "Efficient Computation of Null-Geodesic with
% Applications to Coherent Vortex Detection", sumbitted, (2016).
%%
% function [X1lco,X2lco,philco]=PeriodicSolutions(X_Vf,Y_Vf,Z_Vf)
% Input arguments:
% X_Vf : x1-component of the trajectories of the ODE (38) in [1]
% Y_Vf : x2-component of the trajectories of the ODE (38) in [1]
% Z_Vf : \phi-component of the trajectories of the ODE (38) in [1]
% Output arguments:
% X1lco : x1-component of periodic solutions of ODE (38) in [1]
% X2lco : x2-component of periodic solutions of ODE (38) in [1]
% philco : \phi-component of periodic solutions of ODE (38) in [1]
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function [X1lco,X2lco,philco] = PeriodicSolutions(X_Vf,Y_Vf,Z_Vf)
X1lco=[];X2lco=[];philco=[];
% Topological condition: discard the traject that have no Z values close to abs(2*pi)
MaxPerCol=max(abs(Z_Vf));
MinZVal=0.95*2*pi;
X_Vf=X_Vf(:,MaxPerCol>MinZVal);
Y_Vf=Y_Vf(:,MaxPerCol>MinZVal);
Z_Vf=Z_Vf(:,MaxPerCol>MinZVal);
% C^1 distance
distance2d02pi=sqrt((repmat(X_Vf(1,:),size(X_Vf,1),1)-X_Vf).^2+(repmat(Y_Vf(1,:),size(Y_Vf,1),1)-Y_Vf).^2+(abs(repmat(Z_Vf(1,:),size(Z_Vf,1),1)-Z_Vf)-2*pi).^2);
% Avoid to get the first points
ReturnDist=2*1e-2; % Avoid to scan all the set of initial conditions to find closed null-geodesics
distance2d02pi(abs(Z_Vf)<0.8*2*pi)=nan;
[valret,indrw]=min(distance2d02pi);
indrw(valret>ReturnDist)=[];
X_Vf(:,valret>ReturnDist)=[];
Y_Vf(:,valret>ReturnDist)=[];
Z_Vf(:,valret>ReturnDist)=[];
valret(valret>ReturnDist)=[];
% Set to nan the points following the closest one
for kkss=1:length(indrw)
X_Vf(indrw(kkss)+1:end,kkss)=nan;
Y_Vf(indrw(kkss)+1:end,kkss)=nan;
Z_Vf(indrw(kkss)+1:end,kkss)=nan;
end
[~,ind]=sort(valret,'ascend');
indrw=indrw(ind);
xIn=X_Vf(1,:);
yIn=Y_Vf(1,:);
MatrixFin=[];
% Filter the ones which do not have a change of spiraling
InDist=0.1; % Avoid to scan all the set of initial conditions to find the 2 closest initial conditions to the current initial point contained in the set
for kkh=1:length(ind)
indFull=[];
ind12=[];sign12=0;
%analyze each trajectory
x00=X_Vf(1,ind(kkh));y00=Y_Vf(1,ind(kkh));
%find the 2 closest initial conditions on the initial set
AlNorDir=mod(atan2((Y_Vf(2,ind(kkh))-y00),(X_Vf(2,ind(kkh))-x00))+pi/2,2*pi);
distan=sqrt((xIn-x00).^2+(yIn-y00).^2);
[vald,indd]=sort(distan,'ascend');
indd(vald>InDist)=[];
vald(vald>InDist)=[];
indd(vald==0)=[];
vald(vald==0)=[];
if ~isempty(indd)
xn=xIn(indd(1:end));yn=yIn(indd(1:end));
AlneighDir=mod(atan2((yn-y00),(xn-x00)),2*pi);
dotpr=[cos(AlNorDir) sin(AlNorDir)]*[cos(AlneighDir);sin(AlneighDir)];
Boolsd=0*AlneighDir-1;
Boolsd(AlneighDir>AlNorDir+pi/2)=1;
ind12=[ind12;indd(1)];
sign12=(Boolsd(1));
sign12Bool=sign12*Boolsd;
[~,inddd]=find(sign12Bool<0);
if ~isempty(inddd)
ind12=[ind12;indd(inddd(1))];
end
if length(ind12)==2
indFull=[ind12(1);ind(kkh);ind12(2)];
% Check the change of spiraling
Matr=[];
spiral=[];
dist=[];
for kkcs=1:length(indFull)
indcol=indFull(kkcs);
InN1=length(X_Vf(~isnan(X_Vf(:,indcol)),indcol));
AlNorDircon=mod(atan2((Y_Vf(2,indcol)-Y_Vf(1,indcol)),(X_Vf(2,indcol)-X_Vf(1,indcol)))+pi/2,2*pi);
AlneighDircon=mod(atan2((Y_Vf(InN1,indcol)-Y_Vf(1,indcol)),(X_Vf(InN1,indcol)-X_Vf(1,indcol))),2*pi);
AlneighAbsDist=sqrt((Y_Vf(InN1,indcol)-Y_Vf(1,indcol)).^2+(X_Vf(InN1,indcol)-X_Vf(1,indcol)).^2);
spiral=[spiral;-sign([cos(AlNorDircon) sin(AlNorDircon)]*[cos(AlneighDircon);sin(AlneighDircon)])];
% Distance projected along the local normal
locDistVec=AlneighAbsDist*[cos(AlneighDircon),sin(AlneighDircon)];
ProjVectDist=locDistVec*[cos(AlNorDircon);sin(AlNorDircon)];
dist=[dist;abs(ProjVectDist)];
end
Matr=[indFull,spiral,dist];
% If there is a change of spiraling, take the selected point with
% min return distance
if Matr(1,2)*Matr(2,2)<0 | Matr(3,2)*Matr(2,2)<0
MatrixFin=[MatrixFin;Matr(2,:)];
end
end
end
end
if ~isempty(MatrixFin)
MatrixFinal=MatrixFin;
[~,indddd]=sort(MatrixFinal(:,1),'ascend');
MatrixFinal=MatrixFinal(indddd,:);
Idxtodel=[];
for kk=1:size(MatrixFinal,1)-1
if abs(MatrixFinal(kk+1,1)-MatrixFinal(kk,1))==1 %if they are consecutive IC discard the one with max return distance (this avoids to have the same null-geodesic twice)
[~,idistc]=max(MatrixFinal(kk:kk+1,end));
if idistc==2
Idxtodel=[Idxtodel;kk+1];
else
Idxtodel=[Idxtodel;kk];
end
end
end
MatrixFinal(Idxtodel,:)=[];
indFFin=MatrixFinal(:,1);
X1lco=X_Vf(:,indFFin);
X2lco=Y_Vf(:,indFFin);
philco=Z_Vf(:,indFFin);
% Final closed null-geodesics
for kk=1:size(X1lco,2)-1
x1=X1lco(~isnan(X1lco(:,kk)),kk);
x2=X2lco(~isnan(X2lco(:,kk)),kk);
x1(end)=x1(1);x2(end)=x2(1);
X1lco(~isnan(X1lco(:,kk)),kk)=x1;
X2lco(~isnan(X2lco(:,kk)),kk)=x2;
end
end
end
|
github
|
haller-group/Closed-Null-Geodesics-2D-master
|
PlotAllClosedNullGeodesics.m
|
.m
|
Closed-Null-Geodesics-2D-master/Subfunctions/PlotAllClosedNullGeodesics.m
| 2,577 |
utf_8
|
265d9d1e1e7298b68083091ccc61ebb6
|
% function PlotAllClosedNullGeodesics(x1Psol,x2Psol,x1_g,x2_g,lamV,lam2)
% Input arguments:
% lamV : Desired set of \lambda values
% phi0 : initial \phi value (cf. Fig. 2 of [1])
% CGij : ij entries of the CG strain tensor
% x1_g : x1 component of the spatial grid
% x2_g : x2 component of the spatial grid
%--------------------------------------------------------------------------
% Author: Mattia Serra [email protected]
% http://www.zfm.ethz.ch/~serra/
%--------------------------------------------------------------------------
function PlotAllClosedNullGeodesics(x1Psol,x2Psol,x1_g,x2_g,lamV,lam2)
% Colormap encoding different \lambda values
cmap = jet(length(lamV));
% Plot properties
AxthicksFnt = 15;
fontsizeaxlab = 15;
if ~isempty(x1Psol) % If there are closed null-geodesics
% Initialize the figure with the FTLE plot
figure('units','normalized','outerposition',[0 0 .5 .5]);
imagesc(x1_g,x2_g,log(lam2)/30/2);shading interp
set(gca,'FontSize',AxthicksFnt,'fontWeight','normal')
hold on
set(gca,'YDir','normal')
set(gcf,'color','w');
axis equal
xlabel('$$Lon [^{\circ}]$$','Interpreter','latex','FontWeight','bold','FontSize',fontsizeaxlab);
ylabel('$$Lat [^{\circ}]$$','Interpreter','latex','FontWeight','bold','FontSize',fontsizeaxlab);
axis equal tight
colormap(gca,'gray')
hhF=colorbar(gca);
hhF.Location='westOutside';
hhF.FontSize=fontsizeaxlab;
set(get(hhF,'xlabel'),'string','$$FTLE$$','Interpreter','latex','FontWeight','normal');
for kkmuv=1:1:length(lamV)
xxapp=x1Psol{kkmuv};
yyapp=x2Psol{kkmuv};
if ~isempty(xxapp)
for kkc=1:size(xxapp,2)
xlc=xxapp(~isnan(xxapp(:,kkc)),kkc);
ylc=yyapp(~isnan(yyapp(:,kkc)),kkc);
hold on
plot(xlc,ylc,'color',cmap(kkmuv,:),'linewidth',2.5)
end
end
end
axis equal tight
%add a second colorbar for the \lambda values
ax1=gca;
ax1_pos = ax1.Position;
ax2 = axes('Position',ax1_pos,...
'XAxisLocation','bottom',...
'YAxisLocation','left',...
'Color','none');
hhF2 = colorbar(ax2,'eastOutside')
hhF2.FontSize=AxthicksFnt;
set(get(hhF2,'xlabel'),'string','$$\lambda$$','Interpreter','latex','FontWeight','normal');
colormap(ax2,'jet')
hhF2.Ticks=linspace(0,1,3);
hhF2.XTickLabel={'0.9';'1';'1.1'};
set(ax2,'xtick',[])
set(ax2,'ytick',[])
set(ax2, 'visible', 'off') ;
end
end
|
github
|
PrincetonUniversity/3D3A-SABRE-Toolkit-master
|
SABRE_SphericalHarmonic.m
|
.m
|
3D3A-SABRE-Toolkit-master/SABRE_SphericalHarmonic.m
| 3,326 |
utf_8
|
8364057f4d5325bc0be08b1baff9b0ca
|
function Y = SABRE_SphericalHarmonic(L, R)
%SABRE_SphericalHarmonic Real-valued spherical harmonic function for ambiX.
% Y = SABRE_SphericalHarmonic(L,R) computes the real-valued, SN3D
% normalized spherical harmonics, up to order L and for positions R,
% used in the ambiX plugins. The ambiX spherical harmonic convention
% is described by Nachbar et al. [1] and Kronlachner [2].
%
% Note:
% L must be a scalar.
% R may be a P-by-3 matrix of directions, where each row is a
% Cartesian vector.
% Y will be a (L + 1)^2-by-P matrix.
% ==============================================================================
% This file is part of the 3D3A SABRE Toolkit.
%
% Joseph G. Tylka <[email protected]>
% 3D Audio and Applied Acoustics (3D3A) Laboratory
% Princeton University, Princeton, New Jersey 08544, USA
%
% MIT License
%
% Copyright (c) 2017 Princeton University
%
% Permission is hereby granted, free of charge, to any person obtaining a copy
% of this software and associated documentation files (the "Software"), to deal
% in the Software without restriction, including without limitation the rights
% to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
% copies of the Software, and to permit persons to whom the Software is
% furnished to do so, subject to the following conditions:
%
% The above copyright notice and this permission notice shall be included in all
% copies or substantial portions of the Software.
%
% THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
% IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
% FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
% AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
% LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
% OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
% SOFTWARE.
% ==============================================================================
% Needs at least 2 input arguments
if nargin < 2
error('Not enough input arguments.');
end
% Compute spherical harmonic matrix
Y = zeros((L + 1)^2, size(R,1));
for l = 0:L
for m = -l:l
acn = l*(l + 1) + m;
Y(acn + 1,:) = ambiXsphericalHarmonic(l, m, R);
end
end
end
function Y = ambiXsphericalHarmonic(l,m,r)
% Needs at least 3 input arguments
if nargin < 3
error('Not enough input arguments.');
end
if (l >= 0) && (abs(m) <= l)
if isvector(r)
[AZIM,ELEV,~] = cart2sph(r(1),r(2),r(3));
else
[AZIM,ELEV,~] = cart2sph(r(:,1),r(:,2),r(:,3));
end
% Compute normalization term
Nlm = ambiXnormalization(l,abs(m));
% Compute elevation term
Pl = legendre(l, sin(ELEV));
Plm = Pl(abs(m) + 1,:).';
% Compute azimuth term
if m >= 0
Tm = cos(m * AZIM);
else % m < 0
Tm = sin(abs(m) * AZIM);
end
Y = Nlm*Plm.*Tm;
else
warning('Invalid order and degree.');
Y = 0;
end
end
function Nlm = ambiXnormalization(l,m)
Nlm = ((-1)^m)*sqrt((2-(~m))/(4*pi)).*sqrt(factorial(l-m)./factorial(l+m));
% Includes Condon-Shortley phase ((-1)^m) to cancel it in the Legendre term.
end
|
github
|
PrincetonUniversity/3D3A-SABRE-Toolkit-master
|
SABRE_InterpolateHRTFs.m
|
.m
|
3D3A-SABRE-Toolkit-master/SABRE_InterpolateHRTFs.m
| 7,851 |
utf_8
|
21888ca5a9f7b7c50fb72a87ae244f1e
|
function [hrirL, hrirR, desiredGrid] = SABRE_InterpolateHRTFs(hrirDataL, hrirDataR, measuredGrid, varargin)
%SABRE_InterpolateHRTFs Interpolate measured HRTFs to a desired grid.
% [XL, XR, RD] = SABRE_InterpolateHRTFs(HL, HR, RM, RD) returns HRIRs XL
% and XR for the desired positions RD, given input HRIRs HL and HR
% that are measured at positions RM. The returned HRIRs are the
% 'nearest neighbors,' computed by finding the nearest point on the
% measured grid to each point on the desired grid and returning the
% corresponding measured HRIRs.
%
% [XL, XR, RD] = SABRE_InterpolateHRTFs(HL, HR, RM, RD, METHOD) uses one
% of the following interpolation methods:
% 'nearest' - Nearest neighbor interpolation (default)
% 'natural' - Natural neighbor interpolation
% 'linear' - Linear interpolation
% 'sh' - Spherical-harmonic interpolation
%
% [XL, XR, RD] = SABRE_InterpolateHRTFs(HL, HR, RM, RD, METHOD, DOMAIN)
% performs interpolation in either of the following domains:
% 'time' - Averages time-aligned impulse responses (default)
% 'frequency' - Averages magnitude spectra in dB and computes
% minimum-phase impulse responses
%
% [XL, XR, RD] = SABRE_InterpolateHRTFs(HL, HR, RM, RD, METHOD, DOMAIN, THRESHOLD)
% limits interpolation to only those desired grid positions that are
% at least THRESHOLD degrees away from the nearest measurement
% position. Within the THRESHOLD, nearest-neighbor interpolation is
% used.
%
% [XL, XR, RD] = SABRE_InterpolateHRTFs(HL, HR, RM, CONFIG) interpolates
% the measured HRIRs using specified CONFIG settings.
%
% See also SABRE_LoadHRTFs, SABRE_RemoveHRTFDelays, SABRE_AddHRTFDelays.
% ==============================================================================
% This file is part of the 3D3A SABRE Toolkit.
%
% Joseph G. Tylka <[email protected]>
% 3D Audio and Applied Acoustics (3D3A) Laboratory
% Princeton University, Princeton, New Jersey 08544, USA
%
% MIT License
%
% Copyright (c) 2017 Princeton University
%
% Permission is hereby granted, free of charge, to any person obtaining a copy
% of this software and associated documentation files (the "Software"), to deal
% in the Software without restriction, including without limitation the rights
% to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
% copies of the Software, and to permit persons to whom the Software is
% furnished to do so, subject to the following conditions:
%
% The above copyright notice and this permission notice shall be included in all
% copies or substantial portions of the Software.
%
% THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
% IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
% FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
% AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
% LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
% OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
% SOFTWARE.
% ==============================================================================
narginchk(4,7);
if nargin == 4 && isstruct(varargin{1})
config = varargin{1};
else
if nargin >= 4
config.interpolation_grid = varargin{1};
end
if nargin >= 5
config.interpolation_method = varargin{2};
end
if nargin >= 6
config.interpolation_domain = varargin{3};
end
if nargin == 7
config.interpolation_threshold = varargin{4};
end
end
if ~isfield(config,'interpolation_method')
config.interpolation_method = 'nearest';
end
if ~isfield(config,'interpolation_domain')
config.interpolation_domain = 'time';
end
if ~isfield(config,'interpolation_threshold')
config.interpolation_threshold = 0;
end
desiredGrid = config.interpolation_grid;
hrirLen = size(hrirDataL,1);
numDirs = size(desiredGrid,1);
numMeas = size(measuredGrid,1);
hrirL = zeros(hrirLen, numDirs);
hrirR = zeros(hrirLen, numDirs);
% Normalize vectors to be on unit sphere
desiredGrid = desiredGrid ./(sqrt(dot(desiredGrid ,desiredGrid ,2))*ones(1,size(desiredGrid ,2)));
measuredGrid = measuredGrid./(sqrt(dot(measuredGrid,measuredGrid,2))*ones(1,size(measuredGrid,2)));
switch lower(config.interpolation_method)
case 'nearest' % Find nearest measured HRTFs
for ii = 1:numDirs
distVec = sqrt(sum((measuredGrid - ones(numMeas,1)*desiredGrid(ii,:)).^2,2));
indx = find(distVec == min(distVec),1,'first');
hrirL(:,ii) = hrirDataL(:,indx);
hrirR(:,ii) = hrirDataR(:,indx);
desiredGrid(ii,:) = measuredGrid(indx,:);
end
case {'natural','linear','sh'} % Interpolate HRTFs
w = interpWeights(measuredGrid, desiredGrid, lower(config.interpolation_method));
% Apply interpolation threshold
interpNeeded = ~zeros(1,numDirs); % for logical indexing of which positions need interpolation
for ii = 1:numDirs
distVec = sqrt(sum((measuredGrid - ones(numMeas,1)*desiredGrid(ii,:)).^2,2));
indx = find(distVec == min(distVec),1,'first');
angDist = acosd(dot(measuredGrid(indx,:),desiredGrid(ii,:),2));
if angDist < config.interpolation_threshold
interpNeeded(ii) = false; % prevent overwriting below
% Copy measurements directly
hrirL(:,ii) = hrirDataL(:,indx);
hrirR(:,ii) = hrirDataR(:,indx);
desiredGrid(ii,:) = measuredGrid(indx,:);
end
end
[irL, irR, dL, dR, d0] = SABRE_RemoveHRTFDelays(hrirDataL, hrirDataR);
dLi = dL*w(:,interpNeeded);
dRi = dR*w(:,interpNeeded);
switch lower(config.interpolation_domain)
case 'time'
irLi = irL*w(:,interpNeeded);
irRi = irR*w(:,interpNeeded);
case 'frequency'
HdBL = mag2db(abs(fft(hrirDataL,hrirLen,1)));
HdBR = mag2db(abs(fft(hrirDataR,hrirLen,1)));
irLi = minimumPhase(ifft(db2mag(HdBL*w(:,interpNeeded)),hrirLen,1,'symmetric'));
irRi = minimumPhase(ifft(db2mag(HdBR*w(:,interpNeeded)),hrirLen,1,'symmetric'));
dLi = dLi + d0;
dRi = dRi + d0;
end
[hrirL(:,interpNeeded), hrirR(:,interpNeeded)] = SABRE_AddHRTFDelays(irLi, irRi, dLi, dRi);
% TODO: Add other interpolation methods here...
end
end
function w = interpWeights(posIn,posOut,METHOD,OPTION)
narginchk(2,4);
if nargin < 3
METHOD = 'linear';
end
if strcmpi(METHOD,'sh')
if nargin < 4 || isempty(OPTION)
maxOrder = 4;
else
maxOrder = OPTION;
end
YmatrixIn = SABRE_SphericalHarmonic(maxOrder, posIn);
YmatrixOut = SABRE_SphericalHarmonic(maxOrder, posOut);
w = YmatrixIn\YmatrixOut; % numPosIn-by-numPosOut
else
numPosIn = size(posIn,1);
numPosOut = size(posOut,1);
w = zeros(numPosIn,numPosOut);
for jj = 1:numPosOut
[y, p, ~] = cart2sph(posOut(jj,1),posOut(jj,2),posOut(jj,3));
Rz = [cos(y) -sin(y) 0; sin(y) cos(y) 0; 0 0 1];
Ry = [cos(p) 0 -sin(p); 0 1 0; sin(p) 0 cos(p)];
posInR = posIn*Rz*Ry;
[posInS(:,1),posInS(:,2),~] = cart2sph(posInR(:,1),posInR(:,2),posInR(:,3));
% Get "impulse responses" of interpolation function
for ii = 1:numPosIn
v = zeros(numPosIn,1);
v(ii) = 1;
F = scatteredInterpolant(posInS,v,METHOD);
w(ii,jj) = F([0 0]);
end
end
end
end
|
github
|
kohpangwei/data-poisoning-release-master
|
upperBoundTrue.m
|
.m
|
data-poisoning-release-master/matlab/upperBoundTrue.m
| 6,944 |
utf_8
|
212d5d2bb6860fc19366e570c83dd283
|
% G, Constraint are yalmip data for debugging
function [G, Constraint, val, X_eps, probs_eps] = upperBoundTrue(X_train, y_train, theta, bias, probs, mus, epsilon, r_slab, r_sphere, randomize, solver)
% we don't have a good way of splitting u pthe probabilities, so let's
% just do it randomly
if randomize
probs_eps = gamrnd([probs(1) probs(1) probs(2) probs(2)], 1);
probs_eps = epsilon * probs_eps / sum(probs_eps);
else
% this heuristic choice also works well
probs_eps = epsilon * [probs(1) 0 probs(2) 0];
end
% who are the relevant players?
% x_a^+, x_b^+, x_a^-, x_b^-
% mu^+, mu^-, theta
Norms = [norm(mus(:,1),2); norm(mus(:,2),2); norm(theta,2)];
%Norms
%D = eig(mus' * mus);
%D
M_m = [mus(:,1)/Norms(1) mus(:,2)/Norms(2) theta/Norms(3)];
G_m = M_m' * M_m;
%E = eig(G_m);
%E
%G_o = sdpvar(4,4);
%G_s = sdpvar(4,3);
%G = [G_o G_s; G_s' G_m];
G = sdpvar(7,7);
%Slack = 1e-5 * diag([1 1 1 1 1 1 1]);
Constraint = [G >= 0; G(5:7,5:7) == G_m];
e_ap = [1;0;0;0;0;0;0]; % x_a^+; this one is a support vector
e_bp = [0;1;0;0;0;0;0]; % x_b^+; this one is not a support vector
e_am = [0;0;1;0;0;0;0]; % x_a^-
e_bm = [0;0;0;1;0;0;0]; % x_b^-
e_up = [0;0;0;0;Norms(1);0;0]; % mu^+
e_um = [0;0;0;0;0;Norms(2);0]; % mu^-
e_th = [0;0;0;0;0;0;Norms(3)]; % theta
mu_pp = (probs(1) * e_up + probs_eps(1) * e_ap + probs_eps(2) * e_bp) / (probs(1) + probs_eps(1) + probs_eps(2)); %mu_poisoned^+
mu_mp = (probs(2) * e_um + probs_eps(3) * e_am + probs_eps(4) * e_bm) / (probs(2) + probs_eps(3) + probs_eps(4)); %mu_poisoned^-
% add inner product constraint
Constraint = [Constraint;
1 - (e_ap' * G * e_th + bias) >= 0; % i.e., 1 - <x_a^+, theta> >= 0
%1 - (e_bp' * G * e_th + bias) <= 0;
1 + (e_am' * G * e_th + bias) >= 0];
%1 + (e_bm' * G * e_th + bias) <= 0];
% add sphere constraints
Constraint = [Constraint;
(e_ap - mu_pp)' * G * (e_ap - mu_pp) <= r_sphere(1)^2; % i.e., <x_a^+ - mu_poisoned^+, x_a^+ - mu_poisoned^+ > <= r_sphere^2
(e_bp - mu_pp)' * G * (e_bp - mu_pp) <= r_sphere(1)^2;
(e_am - mu_mp)' * G * (e_am - mu_mp) <= r_sphere(2)^2;
(e_bm - mu_mp)' * G * (e_bm - mu_mp) <= r_sphere(2)^2];
% add slab constraints
dist_sq = norm(mus(:,1) - mus(:,2),2)^2;
s1 = sdpvar; s2 = sdpvar; s3 = sdpvar; s4 = sdpvar;
Constraint = [Constraint;
s1 == ((e_ap - mu_pp)' * G * (mu_pp - mu_mp));
s2 == ((e_bp - mu_pp)' * G * (mu_pp - mu_mp));
s3 == ((e_am - mu_mp)' * G * (mu_pp - mu_mp));
s4 == ((e_bm - mu_mp)' * G * (mu_pp - mu_mp));
s1^2 <= (r_slab(1)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp);
s2^2 <= (r_slab(1)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp);
s3^2 <= (r_slab(2)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp);
s4^2 <= (r_slab(2)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp)];
%((e_ap - mu_pp)' * G * (mu_pp - mu_mp))^2 <= (r_slab(1)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp);
%((e_bp - mu_pp)' * G * (mu_pp - mu_mp))^2 <= (r_slab(1)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp);
%((e_am - mu_mp)' * G * (mu_pp - mu_mp))^2 <= (r_slab(2)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp);
%((e_bm - mu_mp)' * G * (mu_pp - mu_mp))^2 <= (r_slab(2)^2/dist_sq) * (mu_pp - mu_mp)' * G * (mu_pp - mu_mp)];
%-r_slab(1) <= (e_ap - mu_pp)' * G * (mu_pp - mu_mp) <= r_slab(1); % i.e., -r_slab <= <x_a^+ - mu_poisoned^+, mu_poisoned^+ - mu_poisoned^_ > <= r_slab
%-r_slab(1) <= (e_bp - mu_pp)' * G * (mu_pp - mu_mp) <= r_slab(1);
%-r_slab(2) <= (e_am - mu_mp)' * G * (mu_pp - mu_mp) <= r_slab(2);
%-r_slab(2) <= (e_bm - mu_mp)' * G * (mu_pp - mu_mp) <= r_slab(2)];
Objective = probs_eps(1) * (1 - (e_ap' * G * e_th + bias)) + probs_eps(3) * (1 + (e_am' * G * e_th + bias)); % loss on the support vectors x_a^+ and x_a^-
opts = sdpsettings('verbose', 0, 'showprogress', 0, 'solver', solver, 'cachesolvers', 1);
optimize(Constraint, -Objective, opts);
val = double(Objective);
fprintf(1, 'value = %.4f \t (eps = [%.3f %.3f %.3f %.3f])\n', val, probs_eps(1), probs_eps(2), probs_eps(3), probs_eps(4));
%[~, L0] = nabla_Loss(X_train, y_train, theta);
%fprintf(1, 'upper bound: %.4f (all) | %.4f (L0) | %.4f (val)\n', L0 + val, L0, val);
G_d = double(G); %X_eps' * X_eps;
errIn = norm(G_d(5:7,5:7) - G_m, 'inf');
if errIn > 1e-4
fprintf(1, 'errIn = %.5f, skipping...\n', errIn);
X_eps = [mus(:,1) mus(:,1) mus(:,2) mus(:,2)];
G_feas = [X_eps M_m]' * [X_eps M_m];
assign(G, G_feas);
check(Constraint);
val = 1e3;
return;
end
if nargout > 3
X_eps = extractVecs(double(G), G_m, M_m); %[mus theta]);
G_approx = X_eps' * X_eps;
% check constraints
feas_sphere = [ (e_ap - mu_pp)' * G_approx * (e_ap - mu_pp) / r_sphere(1)^2;
(e_bp - mu_pp)' * G_approx * (e_bp - mu_pp) / r_sphere(1)^2;
(e_am - mu_mp)' * G_approx * (e_am - mu_mp) / r_sphere(2)^2;
(e_bm - mu_mp)' * G_approx * (e_bm - mu_mp) / r_sphere(2)^2];
%feas_slab = [ abs((e_ap - mu_pp)' * G_approx * (mu_pp - mu_mp)) / r_slab(1);
% abs((e_bp - mu_pp)' * G_approx * (mu_pp - mu_mp)) / r_slab(1);
% abs((e_am - mu_mp)' * G_approx * (mu_pp - mu_mp)) / r_slab(2);
% abs((e_bm - mu_mp)' * G_approx * (mu_pp - mu_mp)) / r_slab(2)];
feas_slab = [ ((e_ap - mu_pp)' * G_approx * (mu_pp - mu_mp))^2 / ((r_slab(1)^2/dist_sq) * (mu_pp - mu_mp)' * G_approx * (mu_pp - mu_mp));
((e_bp - mu_pp)' * G_approx * (mu_pp - mu_mp))^2 / ((r_slab(1)^2/dist_sq) * (mu_pp - mu_mp)' * G_approx * (mu_pp - mu_mp));
((e_am - mu_mp)' * G_approx * (mu_pp - mu_mp))^2 / ((r_slab(2)^2/dist_sq) * (mu_pp - mu_mp)' * G_approx * (mu_pp - mu_mp));
((e_bm - mu_mp)' * G_approx * (mu_pp - mu_mp))^2 / ((r_slab(2)^2/dist_sq) * (mu_pp - mu_mp)' * G_approx * (mu_pp - mu_mp))];
fprintf(1, 'feasibility: %.3f %.3f %.3f %.3f (sphere) | %.3f %.3f %.3f %.3f (slab)\n', ...
feas_sphere(1), feas_sphere(2), feas_sphere(3), feas_sphere(4), ...
feas_slab(1), feas_slab(2), feas_slab(3), feas_slab(4));
X_eps = X_eps(:,1:4);
end
end
|
github
|
kohpangwei/data-poisoning-release-master
|
extractVecs.m
|
.m
|
data-poisoning-release-master/matlab/extractVecs.m
| 1,607 |
utf_8
|
6ed8c565810c85c34eda832eb00d180a
|
function V_full = extractVecs(G_full, G_partial, V_partial)
% G_full is Graham matrix of inner products
% G_partial is lower-right corner of G
% V_partial is collection of vectors realizing G_partial
n_full = size(G_full, 1);
assert(n_full == size(G_full, 2));
n_partial = size(G_partial, 1);
n_missing = n_full - n_partial;
assert(n_partial == size(G_partial, 2));
assert(n_partial == size(V_partial, 2));
d = size(V_partial, 1);
[Proj_half, ~] = svd_lr(V_partial, 1e-6);
G_11 = G_full(1:n_missing,1:n_missing);
G_12 = G_full(1:n_missing,n_missing+1:n_full);
G_22 = G_full(n_missing+1:n_full,n_missing+1:n_full);
[U_22, D_22] = eig_lr(G_22, 1e-6);
Gp_12 = G_12 * U_22;
Gp_22_pinv_sqrt = sqrt(inv(D_22));
Gp_schur_sqrt = Gp_12 * Gp_22_pinv_sqrt;
Bp = Gp_schur_sqrt * Gp_22_pinv_sqrt';
AAt = (G_11 - (Gp_schur_sqrt * Gp_schur_sqrt'));
[U_a, D_a] = eig(AAt);
A = U_a * sqrt(max(D_a,0));
basis = randn(d,n_missing);
basis = basis - Proj_half * (Proj_half' * basis);
[basis, ~] = qr(basis, 0);
V_missing = basis * A' + V_partial * U_22 * Bp';
V_full = [V_missing V_partial];
err = norm(G_full - (V_full'*V_full), 'inf');
fprintf(1, 'err: %.4f\n', err);
end
function [U,D] = svd_lr(A, tol)
[U,D,~] = svd(A, 'econ');
active = diag(D) > tol*max(D(:));
U = U(:,active);
D = D(active,active);
end
function [U,D] = eig_lr(A, tol)
[U,D] = eig((A+A')/2);
active = diag(D)>tol*max(D(:));
U = U(:, active);
D = D(active,active);
end
|
github
|
aharley/segaware-master
|
classification_demo.m
|
.m
|
segaware-master/caffe/matlab/demo/classification_demo.m
| 5,412 |
utf_8
|
8f46deabe6cde287c4759f3bc8b7f819
|
function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% ****************************************************************************
% For detailed documentation and usage on Caffe's Matlab interface, please
% refer to Caffe Interface Tutorial at
% http://caffe.berkeleyvision.org/tutorial/interfaces.html#matlab
% ****************************************************************************
%
% input
% im color image as uint8 HxWx3
% use_gpu 1 to use the GPU, 0 to use the CPU
%
% output
% scores 1000-dimensional ILSVRC score vector
% maxlabel the label of the highest score
%
% You may need to do the following before you start matlab:
% $ export LD_LIBRARY_PATH=/opt/intel/mkl/lib/intel64:/usr/local/cuda-5.5/lib64
% $ export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libstdc++.so.6
% Or the equivalent based on where things are installed on your system
%
% Usage:
% im = imread('../../examples/images/cat.jpg');
% scores = classification_demo(im, 1);
% [score, class] = max(scores);
% Five things to be aware of:
% caffe uses row-major order
% matlab uses column-major order
% caffe uses BGR color channel order
% matlab uses RGB color channel order
% images need to have the data mean subtracted
% Data coming in from matlab needs to be in the order
% [width, height, channels, images]
% where width is the fastest dimension.
% Here is the rough matlab for putting image data into the correct
% format in W x H x C with BGR channels:
% % permute channels from RGB to BGR
% im_data = im(:, :, [3, 2, 1]);
% % flip width and height to make width the fastest dimension
% im_data = permute(im_data, [2, 1, 3]);
% % convert from uint8 to single
% im_data = single(im_data);
% % reshape to a fixed size (e.g., 227x227).
% im_data = imresize(im_data, [IMAGE_DIM IMAGE_DIM], 'bilinear');
% % subtract mean_data (already in W x H x C with BGR channels)
% im_data = im_data - mean_data;
% If you have multiple images, cat them with cat(4, ...)
% Add caffe/matlab to you Matlab search PATH to use matcaffe
if exist('../+caffe', 'dir')
addpath('..');
else
error('Please run this demo from caffe/matlab/demo');
end
% Set caffe mode
if exist('use_gpu', 'var') && use_gpu
caffe.set_mode_gpu();
gpu_id = 0; % we will use the first gpu in this demo
caffe.set_device(gpu_id);
else
caffe.set_mode_cpu();
end
% Initialize the network using BVLC CaffeNet for image classification
% Weights (parameter) file needs to be downloaded from Model Zoo.
model_dir = '../../models/bvlc_reference_caffenet/';
net_model = [model_dir 'deploy.prototxt'];
net_weights = [model_dir 'bvlc_reference_caffenet.caffemodel'];
phase = 'test'; % run with phase test (so that dropout isn't applied)
if ~exist(net_weights, 'file')
error('Please download CaffeNet from Model Zoo before you run this demo');
end
% Initialize a network
net = caffe.Net(net_model, net_weights, phase);
if nargin < 1
% For demo purposes we will use the cat image
fprintf('using caffe/examples/images/cat.jpg as input image\n');
im = imread('../../examples/images/cat.jpg');
end
% prepare oversampled input
% input_data is Height x Width x Channel x Num
tic;
input_data = {prepare_image(im)};
toc;
% do forward pass to get scores
% scores are now Channels x Num, where Channels == 1000
tic;
% The net forward function. It takes in a cell array of N-D arrays
% (where N == 4 here) containing data of input blob(s) and outputs a cell
% array containing data from output blob(s)
scores = net.forward(input_data);
toc;
scores = scores{1};
scores = mean(scores, 2); % take average scores over 10 crops
[~, maxlabel] = max(scores);
% call caffe.reset_all() to reset caffe
caffe.reset_all();
% ------------------------------------------------------------------------
function crops_data = prepare_image(im)
% ------------------------------------------------------------------------
% caffe/matlab/+caffe/imagenet/ilsvrc_2012_mean.mat contains mean_data that
% is already in W x H x C with BGR channels
d = load('../+caffe/imagenet/ilsvrc_2012_mean.mat');
mean_data = d.mean_data;
IMAGE_DIM = 256;
CROPPED_DIM = 227;
% Convert an image returned by Matlab's imread to im_data in caffe's data
% format: W x H x C with BGR channels
im_data = im(:, :, [3, 2, 1]); % permute channels from RGB to BGR
im_data = permute(im_data, [2, 1, 3]); % flip width and height
im_data = single(im_data); % convert from uint8 to single
im_data = imresize(im_data, [IMAGE_DIM IMAGE_DIM], 'bilinear'); % resize im_data
im_data = im_data - mean_data; % subtract mean_data (already in W x H x C, BGR)
% oversample (4 corners, center, and their x-axis flips)
crops_data = zeros(CROPPED_DIM, CROPPED_DIM, 3, 10, 'single');
indices = [0 IMAGE_DIM-CROPPED_DIM] + 1;
n = 1;
for i = indices
for j = indices
crops_data(:, :, :, n) = im_data(i:i+CROPPED_DIM-1, j:j+CROPPED_DIM-1, :);
crops_data(:, :, :, n+5) = crops_data(end:-1:1, :, :, n);
n = n + 1;
end
end
center = floor(indices(2) / 2) + 1;
crops_data(:,:,:,5) = ...
im_data(center:center+CROPPED_DIM-1,center:center+CROPPED_DIM-1,:);
crops_data(:,:,:,10) = crops_data(end:-1:1, :, :, 5);
|
github
|
aharley/segaware-master
|
MyVOCevalseg.m
|
.m
|
segaware-master/caffe/matlab/my_script/MyVOCevalseg.m
| 4,625 |
utf_8
|
128c24319d520c2576168d1cf17e068f
|
%VOCEVALSEG Evaluates a set of segmentation results.
% VOCEVALSEG(VOCopts,ID); prints out the per class and overall
% segmentation accuracies. Accuracies are given using the intersection/union
% metric:
% true positives / (true positives + false positives + false negatives)
%
% [ACCURACIES,AVACC,CONF] = VOCEVALSEG(VOCopts,ID) returns the per class
% percentage ACCURACIES, the average accuracy AVACC and the confusion
% matrix CONF.
%
% [ACCURACIES,AVACC,CONF,RAWCOUNTS] = VOCEVALSEG(VOCopts,ID) also returns
% the unnormalised confusion matrix, which contains raw pixel counts.
function [accuracies,avacc,conf,rawcounts] = MyVOCevalseg(VOCopts,id)
% image test set
[gtids,t]=textread(sprintf(VOCopts.seg.imgsetpath,VOCopts.testset),'%s %d');
% number of labels = number of classes plus one for the background
num = VOCopts.nclasses+1;
confcounts = zeros(num);
count=0;
num_missing_img = 0;
tic;
for i=1:length(gtids)
% display progress
if toc>1
fprintf('test confusion: %d/%d\n',i,length(gtids));
drawnow;
tic;
end
imname = gtids{i};
% ground truth label file
gtfile = sprintf(VOCopts.seg.clsimgpath,imname);
[gtim,map] = imread(gtfile);
gtim = double(gtim);
% results file
resfile = sprintf(VOCopts.seg.clsrespath,id,VOCopts.testset,imname);
try
[resim,map] = imread(resfile);
catch err
num_missing_img = num_missing_img + 1;
%fprintf(1, 'Fail to read %s\n', resfile);
continue;
end
resim = double(resim);
% Check validity of results image
maxlabel = max(resim(:));
if (maxlabel>VOCopts.nclasses),
error('Results image ''%s'' has out of range value %d (the value should be <= %d)',imname,maxlabel,VOCopts.nclasses);
end
szgtim = size(gtim); szresim = size(resim);
if any(szgtim~=szresim)
error('Results image ''%s'' is the wrong size, was %d x %d, should be %d x %d.',imname,szresim(1),szresim(2),szgtim(1),szgtim(2));
end
%pixel locations to include in computation
locs = gtim<255;
% joint histogram
sumim = 1+gtim+resim*num;
hs = histc(sumim(locs),1:num*num);
count = count + numel(find(locs));
confcounts(:) = confcounts(:) + hs(:);
end
if (num_missing_img > 0)
fprintf(1, 'WARNING: There are %d missing results!\n', num_missing_img);
end
% confusion matrix - first index is true label, second is inferred label
%conf = zeros(num);
conf = 100*confcounts./repmat(1E-20+sum(confcounts,2),[1 size(confcounts,2)]);
rawcounts = confcounts;
% Pixel Accuracy
overall_acc = 100*sum(diag(confcounts)) / sum(confcounts(:));
fprintf('Percentage of pixels correctly labelled overall: %6.3f%%\n',overall_acc);
% Class Accuracy
class_acc = zeros(1, num);
class_count = 0;
fprintf('Accuracy for each class (pixel accuracy)\n');
for i = 1 : num
denom = sum(confcounts(i, :));
if (denom == 0)
denom = 1;
end
class_acc(i) = 100 * confcounts(i, i) / denom;
if i == 1
clname = 'background';
else
clname = VOCopts.classes{i-1};
end
if ~strcmp(clname, 'void')
class_count = class_count + 1;
fprintf(' %14s: %6.3f%%\n', clname, class_acc(i));
end
end
fprintf('-------------------------\n');
avg_class_acc = sum(class_acc) / class_count;
fprintf('Mean Class Accuracy: %6.3f%%\n', avg_class_acc);
% Pixel IOU
accuracies = zeros(VOCopts.nclasses,1);
fprintf('Accuracy for each class (intersection/union measure)\n');
real_class_count = 0;
for j=1:num
gtj=sum(confcounts(j,:));
resj=sum(confcounts(:,j));
gtjresj=confcounts(j,j);
% The accuracy is: true positive / (true positive + false positive + false negative)
% which is equivalent to the following percentage:
denom = (gtj+resj-gtjresj);
if denom == 0
denom = 1;
end
accuracies(j)=100*gtjresj/denom;
clname = 'background';
if (j>1), clname = VOCopts.classes{j-1};end;
if ~strcmp(clname, 'void')
real_class_count = real_class_count + 1;
else
if denom ~= 1
fprintf(1, 'WARNING: this void class has denom = %d\n', denom);
end
end
if ~strcmp(clname, 'void')
fprintf(' %14s: %6.3f%%\n',clname,accuracies(j));
end
end
%accuracies = accuracies(1:end);
%avacc = mean(accuracies);
avacc = sum(accuracies) / real_class_count;
fprintf('-------------------------\n');
fprintf('Average accuracy: %6.3f%%\n',avacc);
|
github
|
aharley/segaware-master
|
MyVOCevalsegBoundary.m
|
.m
|
segaware-master/caffe/matlab/my_script/MyVOCevalsegBoundary.m
| 4,415 |
utf_8
|
1b648714e61bafba7c08a8ce5824b105
|
%VOCEVALSEG Evaluates a set of segmentation results.
% VOCEVALSEG(VOCopts,ID); prints out the per class and overall
% segmentation accuracies. Accuracies are given using the intersection/union
% metric:
% true positives / (true positives + false positives + false negatives)
%
% [ACCURACIES,AVACC,CONF] = VOCEVALSEG(VOCopts,ID) returns the per class
% percentage ACCURACIES, the average accuracy AVACC and the confusion
% matrix CONF.
%
% [ACCURACIES,AVACC,CONF,RAWCOUNTS] = VOCEVALSEG(VOCopts,ID) also returns
% the unnormalised confusion matrix, which contains raw pixel counts.
function [accuracies,avacc,conf,rawcounts, overall_acc, avg_class_acc] = MyVOCevalsegBoundary(VOCopts, id, w)
% get structural element
st_w = 2*w + 1;
se = strel('square', st_w);
% image test set
fn = sprintf(VOCopts.seg.imgsetpath,VOCopts.testset);
fid = fopen(fn, 'r');
gtids = textscan(fid, '%s');
gtids = gtids{1};
fclose(fid);
%[gtids,t]=textread(sprintf(VOCopts.seg.imgsetpath,VOCopts.testset),'%s %d');
% number of labels = number of classes plus one for the background
num = VOCopts.nclasses+1;
confcounts = zeros(num);
count=0;
tic;
for i=1:length(gtids)
% display progress
if toc>1
fprintf('test confusion: %d/%d\n',i,length(gtids));
drawnow;
tic;
end
imname = gtids{i};
% ground truth label file
gtfile = sprintf(VOCopts.seg.clsimgpath,imname);
[gtim,map] = imread(gtfile);
gtim = double(gtim);
% results file
resfile = sprintf(VOCopts.seg.clsrespath,id,VOCopts.testset,imname);
try
[resim,map] = imread(resfile);
catch err
fprintf(1, 'Fail to read %s\n', resfile);
continue;
end
resim = double(resim);
% Check validity of results image
maxlabel = max(resim(:));
if (maxlabel>VOCopts.nclasses),
error('Results image ''%s'' has out of range value %d (the value should be <= %d)',imname,maxlabel,VOCopts.nclasses);
end
szgtim = size(gtim); szresim = size(resim);
if any(szgtim~=szresim)
error('Results image ''%s'' is the wrong size, was %d x %d, should be %d x %d.',imname,szresim(1),szresim(2),szgtim(1),szgtim(2));
end
% dilate gt
binary_gt = gtim == 255;
dilate_gt = imdilate(binary_gt, se);
target_gt = dilate_gt & (gtim~=255);
%pixel locations to include in computation
locs = target_gt;
%locs = gtim<255;
% joint histogram
sumim = 1+gtim+resim*num;
hs = histc(sumim(locs),1:num*num);
count = count + numel(find(locs));
confcounts(:) = confcounts(:) + hs(:);
end
% confusion matrix - first index is true label, second is inferred label
%conf = zeros(num);
conf = 100*confcounts./repmat(1E-20+sum(confcounts,2),[1 size(confcounts,2)]);
rawcounts = confcounts;
% Pixel Accuracy
overall_acc = 100*sum(diag(confcounts)) / sum(confcounts(:));
fprintf('Percentage of pixels correctly labelled overall: %6.3f%%\n',overall_acc);
% Class Accuracy
class_acc = zeros(1, num);
class_count = 0;
fprintf('Accuracy for each class (pixel accuracy)\n');
for i = 1 : num
denom = sum(confcounts(i, :));
if (denom == 0)
denom = 1;
else
class_count = class_count + 1;
end
class_acc(i) = 100 * confcounts(i, i) / denom;
if i == 1
clname = 'background';
else
clname = VOCopts.classes{i-1};
end
fprintf(' %14s: %6.3f%%\n', clname, class_acc(i));
end
fprintf('-------------------------\n');
avg_class_acc = sum(class_acc) / class_count;
fprintf('Mean Class Accuracy: %6.3f%%\n', avg_class_acc);
% Pixel IOU
accuracies = zeros(VOCopts.nclasses,1);
fprintf('Accuracy for each class (intersection/union measure)\n');
for j=1:num
gtj=sum(confcounts(j,:));
resj=sum(confcounts(:,j));
gtjresj=confcounts(j,j);
% The accuracy is: true positive / (true positive + false positive + false negative)
% which is equivalent to the following percentage:
accuracies(j)=100*gtjresj/(gtj+resj-gtjresj);
clname = 'background';
if (j>1), clname = VOCopts.classes{j-1};end;
fprintf(' %14s: %6.3f%%\n',clname,accuracies(j));
end
accuracies = accuracies(1:end);
avacc = mean(accuracies);
fprintf('-------------------------\n');
fprintf('Average accuracy: %6.3f%%\n',avacc);
|
github
|
aharley/segaware-master
|
MyVOCevalseg.m
|
.m
|
segaware-master/scripts/segaware/matlab/eval/MyVOCevalseg.m
| 4,821 |
utf_8
|
e2ba8ed0ce8588906a6c63e3a76eb9b2
|
%VOCEVALSEG Evaluates a set of segmentation results.
% VOCEVALSEG(VOCopts,ID); prints out the per class and overall
% segmentation accuracies. Accuracies are given using the intersection/union
% metric:
% true positives / (true positives + false positives + false negatives)
%
% [ACCURACIES,AVACC,CONF] = VOCEVALSEG(VOCopts,ID) returns the per class
% percentage ACCURACIES, the average accuracy AVACC and the confusion
% matrix CONF.
%
% [ACCURACIES,AVACC,CONF,RAWCOUNTS] = VOCEVALSEG(VOCopts,ID) also returns
% the unnormalised confusion matrix, which contains raw pixel counts.
function [accuracies,avacc,conf,rawcounts] = MyVOCevalseg(VOCopts,id)
% image test set
[gtids,t]=textread(sprintf(VOCopts.seg.imgsetpath,VOCopts.testset),'%s %d');
% number of labels = number of classes plus one for the background
num = VOCopts.nclasses+1;
confcounts = zeros(num);
count=0;
num_missing_img = 0;
tic;
for i=1:length(gtids)
% display progress
if toc>1
fprintf('test confusion: %d/%d\n',i,length(gtids));
drawnow;
tic;
end
imname = gtids{i};
% ground truth label file
gtfile = sprintf(VOCopts.seg.clsimgpath,imname);
[gtim,map] = imread(gtfile);
gtim = double(gtim);
%fprintf([VOCopts.seg.clsimgpath '\n'],imname)
% results file
%fprintf(VOCopts.seg.clsrespath,id,VOCopts.testset,imname);
%fprintf('\n');
resfile = sprintf(VOCopts.seg.clsrespath,id,VOCopts.testset,imname);
%fprintf([VOCopts.seg.clsrespath '\n'],id,VOCopts.testset,imname);
try
[resim,map] = imread(resfile);
catch err
num_missing_img = num_missing_img + 1;
%fprintf(1, 'Fail to read %s\n', resfile);
continue;
end
resim = double(resim);
% Check validity of results image
maxlabel = max(resim(:));
if (maxlabel>VOCopts.nclasses),
error('Results image ''%s'' has out of range value %d (the value should be <= %d)',imname,maxlabel,VOCopts.nclasses);
end
szgtim = size(gtim); szresim = size(resim);
if any(szgtim~=szresim)
error('Results image ''%s'' is the wrong size, was %d x %d, should be %d x %d.',imname,szresim(1),szresim(2),szgtim(1),szgtim(2));
end
%pixel locations to include in computation
locs = gtim<255;
% joint histogram
sumim = 1+gtim+resim*num;
hs = histc(sumim(locs),1:num*num);
count = count + numel(find(locs));
confcounts(:) = confcounts(:) + hs(:);
end
if (num_missing_img > 0)
fprintf(1, 'WARNING: There are %d missing results!\n', num_missing_img);
end
% confusion matrix - first index is true label, second is inferred label
%conf = zeros(num);
conf = 100*confcounts./repmat(1E-20+sum(confcounts,2),[1 size(confcounts,2)]);
rawcounts = confcounts;
% Pixel Accuracy
overall_acc = 100*sum(diag(confcounts)) / sum(confcounts(:));
fprintf('Percentage of pixels correctly labelled overall: %6.3f%%\n',overall_acc);
% Class Accuracy
class_acc = zeros(1, num);
class_count = 0;
fprintf('Accuracy for each class (pixel accuracy)\n');
for i = 1 : num
denom = sum(confcounts(i, :));
if (denom == 0)
denom = 1;
end
class_acc(i) = 100 * confcounts(i, i) / denom;
if i == 1
clname = 'background';
else
clname = VOCopts.classes{i-1};
end
if ~strcmp(clname, 'void')
class_count = class_count + 1;
fprintf(' %14s: %6.3f%%\n', clname, class_acc(i));
end
end
fprintf('-------------------------\n');
avg_class_acc = sum(class_acc) / class_count;
fprintf('Mean Class Accuracy: %6.3f%%\n', avg_class_acc);
% Pixel IOU
accuracies = zeros(VOCopts.nclasses,1);
fprintf('Accuracy for each class (intersection/union measure)\n');
real_class_count = 0;
for j=1:num
gtj=sum(confcounts(j,:));
resj=sum(confcounts(:,j));
gtjresj=confcounts(j,j);
% The accuracy is: true positive / (true positive + false positive + false negative)
% which is equivalent to the following percentage:
denom = (gtj+resj-gtjresj);
if denom == 0
denom = 1;
end
accuracies(j)=100*gtjresj/denom;
clname = 'background';
if (j>1), clname = VOCopts.classes{j-1};end;
if ~strcmp(clname, 'void')
real_class_count = real_class_count + 1;
else
if denom ~= 1
fprintf(1, 'WARNING: this void class has denom = %d\n', denom);
end
end
if ~strcmp(clname, 'void')
fprintf(' %14s: %6.3f%%\n',clname,accuracies(j));
end
end
%accuracies = accuracies(1:end);
%avacc = mean(accuracies);
avacc = sum(accuracies) / real_class_count;
fprintf('-------------------------\n');
fprintf('Average accuracy: %6.3f%%\n',avacc);
|
github
|
Unisens/unisensMatlabTools-master
|
unisensBin2Csv.m
|
.m
|
unisensMatlabTools-master/unisensBin2Csv.m
| 5,391 |
utf_8
|
02ce00d793b19e479aaa3464084aa4f4
|
function unisensBin2Csv(path, keepSensorScaling, new_path)
%UNISENSBIN2CSV convert unisens dataset with bin entries to dataset with csv entries
% Converts all unisens signal entries from binary format (*.bin) to csv format (*.csv)
% Copyright 2017 movisens GmbH
addUnisensJar();
if nargin==0 || nargin>3
error('unisensTools:missingArugments','Wrong number of Arguments.\nUsage:\nunisensBin2Csv(''path_to_unisens_bin_dataset\'') \nunisensBin2Csv(''path_to_unisens_bin_dataset\'', ''path_to_new_unisens_csv_dataset\'')');
end
if nargin ==1
keepSensorScaling=true;
new_path = [path '_csv'];
end
if nargin ==2
new_path = [path '_csv'];
end
%open unisens dataset
j_unisensFactory = org.unisens.UnisensFactoryBuilder.createFactory();
j_unisens = j_unisensFactory.createUnisens(path);
%create new unisens dataset
j_unisens_new = j_unisensFactory.createUnisens(new_path);
%set comment
j_unisens_new.setComment([char(j_unisens.getComment()) ' Converted by unisensBin2Csv().']);
%copy custom attibutes
j_custom_attributes = j_unisens.getCustomAttributes();
j_key_iterator = j_custom_attributes.keySet().iterator();
while( j_key_iterator. hasNext() )
j_key = j_key_iterator.next();
j_unisens_new.addCustomAttribute(j_key,j_custom_attributes.get(j_key));
end
%copy context information
j_context = j_unisens.getContext();
if ~isempty(j_context)
j_unisens_new.createContext(j_context.getSchemaUrl());
copyfile([path filesep 'context.xml'],new_path);
end
%set measurement id
measurement_id = j_unisens.getMeasurementId();
if ~isempty(measurement_id)
j_unisens_new.setMeasurementId(j_unisens.getMeasurementId());
end
%set duration in [s]
j_unisens_new.setDuration(j_unisens.getDuration());
%set timestamp in [s]
j_timestamp_start = j_unisens.getTimestampStart();
if ~isempty(j_timestamp_start)
j_unisens_new.setTimestampStart(j_timestamp_start);
end
%loop over all timed entries (signal, values and event entries)
j_entries = j_unisens.getEntries();
nEntries = j_entries.size();
for i = 0:nEntries-1
j_entry = j_entries.get(i);
entry_class_name= j_entry.getClass.toString;
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%here we go
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl'))
%signalEntry
signal_entry_convert(j_entry, j_unisens_new, keepSensorScaling);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl'))
%valuesEntry
values_entry_copy(j_entry, j_unisens_new);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%eventEntry
event_entry_copy(j_entry, j_unisens_new);
end
elseif (strcmp(entry_class_name, 'class org.unisens.ri.CustomEntryImpl'))
%customEntry
disp('Crop not possible for custom Entries');
end
end
%copy groups
j_groups = j_unisens.getGroups();
nGroups = j_groups.size();
for i = 0:nGroups-1
j_group = j_groups.get(i);
j_group_cropped = j_unisens_new.createGroup(j_group.getId());
j_group_entries = j_group.getEntries();
nEntries = j_group.size();
for j = 0:nEntries
j_group_cropped.addEntry(j_unisens_new.getEntry(j_group_entries.get(j).getId()));
end
end
%unisens speichern
j_unisens_new.save();
j_unisens_new.closeAll();
j_unisens.closeAll();
end
function signal_entry_convert(j_entry, j_unisens_new, keepSensorScaling)
%copy entry information
newId = strrep(char(j_entry.getId()),'bin','csv');
if keepSensorScaling==true
j_entry_new=j_unisens_new.createSignalEntry(newId, j_entry.getChannelNames, j_entry.getDataType() , j_entry.getSampleRate());
j_entry_new.setLsbValue(j_entry.getLsbValue());
j_entry_new.setBaseline(j_entry.getBaseline());
else
j_entry_new=j_unisens_new.createSignalEntry(newId, j_entry.getChannelNames, org.unisens.DataType.DOUBLE , j_entry.getSampleRate());
end
j_entry_new.setFileFormat(j_entry_new.createCsvFileFormat());
j_entry_new.setComment(j_entry.getComment());
j_entry_new.setContentClass(j_entry.getContentClass());
j_entry_new.setUnit(j_entry.getUnit());
%copy data piecewise
position = 0;
total = j_entry.getCount();
while (position < total)
if (total - position > 1000000)
count = 1000000;
else
count = total - position;
end
if keepSensorScaling==true
data = j_entry.read(position, count);
else
data = j_entry.readScaled(position, count);
end
j_entry_new.append(data);
position = position + count;
end
end
function values_entry_copy(j_entry, j_unisens_new)
j_entry_new=j_unisens_new.addEntry(j_entry.clone(),true);
end
function event_entry_copy(j_entry, j_unisens_new)
j_entry_new=j_unisens_new.addEntry(j_entry.clone(),true);
end
|
github
|
Unisens/unisensMatlabTools-master
|
unisensAddZerosEnd.m
|
.m
|
unisensMatlabTools-master/unisensAddZerosEnd.m
| 7,664 |
utf_8
|
c567890472a5e0394fdfe8d1e7a8fa5d
|
function unisensAddZerosEnd(path, new_path, addZeros_samplerate, end_samplestamp)
%UNISENSADDZEROSEND adds zeros to the end of a unisens dataset
% Copyright 2020 movisens GmbH, Germany
addZeros_end_time = end_samplestamp / addZeros_samplerate;
%open unisens dataset
j_unisensFactory = org.unisens.UnisensFactoryBuilder.createFactory();
j_unisens = j_unisensFactory.createUnisens(path);
%check if unisens dataset is long enough
if ~durationOk(j_unisens, end_samplestamp / addZeros_samplerate)
warning(['Unisens Dataset ' path ' is too long.']);
end
%create new unisens dataset
j_unisens_addZeros = j_unisensFactory.createUnisens(new_path);
%set comment
j_unisens_addZeros.setComment([char(j_unisens.getComment()) ' Zeros added by addZerosEnd(). Small jitter possible']);
%copy custom attibutes
j_custom_attributes = j_unisens.getCustomAttributes();
j_key_iterator = j_custom_attributes.keySet().iterator();
while( j_key_iterator. hasNext() )
j_key = j_key_iterator.next();
j_unisens_addZeros.addCustomAttribute(j_key,j_custom_attributes.get(j_key));
end
%copy context information
j_context = j_unisens.getContext();
if ~isempty(j_context)
j_unisens_addZeros.createContext(j_context.getSchemaUrl());
copyfile([path filesep 'context.xml'],new_path);
end
%set measurement id
measurement_id = j_unisens.getMeasurementId();
if ~isempty(measurement_id)
j_unisens_addZeros.setMeasurementId(j_unisens.getMeasurementId());
end
%loop over all timed entries (signal, values and event entries)
j_entries = j_unisens.getEntries();
nEntries = j_entries.size();
for i = 0:nEntries-1
j_entry = j_entries.get(i);
entry_class_name= j_entry.getClass.toString;
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%here we go
entry_samplerate= j_entries.get(i).getSampleRate();
entry_samplestamp_end = addZeros_end_time * entry_samplerate;
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl'))
%signalEntry
signal_entry_addZeros(j_entry, j_unisens_addZeros, entry_samplestamp_end);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl'))
%valuesEntry
%values_entry_addZeros(j_entry, j_unisens_addZeros, entry_samplestamp_end);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%eventEntry
event_entry_addZeros(j_entry, j_unisens_addZeros, entry_samplestamp_end);
end
elseif (strcmp(entry_class_name, 'class org.unisens.ri.CustomEntryImpl'))
%customEntry
disp('Add zeros not possible for custom Entries');
end
end
%set new duration in [s]
%TODO duration will be changed to double?
j_unisens_addZeros.setDuration(addZeros_end_time)
%set timesamtp start if available
if ~isempty(j_unisens.getTimestampStart())
j_unisens_addZeros.setTimestampStart(j_unisens.getTimestampStart());
end
%copy groups
j_groups = j_unisens.getGroups();
nGroups = j_groups.size();
for i = 0:nGroups-1
j_group = j_groups.get(i);
j_group_addZeros = j_unisens_addZeros.createGroup(j_group.getId());
j_group_entries = j_group.getEntries();
nEntries = j_group.size();
for j = 0:nEntries
j_group_addZeros.addEntry(j_unisens_addZeros.getEntry(j_group_entries.get(j).getId()));
end
end
%unisens speichern
j_unisens_addZeros.save();
j_unisens_addZeros.closeAll();
j_unisens.closeAll();
end
function signal_entry_addZeros(j_entry, j_unisens_addZeros, samplestamp_end)
%copy entry information
j_entry_addZeros=j_unisens_addZeros.addEntry(j_entry.clone(),false);
%copy data piecewise
position = 1;
channels = 1;
while (position < samplestamp_end)
if (samplestamp_end - position > 1000000)
count = 1000000;
else
count = samplestamp_end - position;
end
data = j_entry.read(position, count);
if ~isempty(data)
channels = size(data,2);
j_entry_addZeros.append(data);
if int64(length(data)) < int64(count)
j_entry_addZeros.append(zeros(int64(count-length(data)),int64(channels),lower(char(j_entry.getDataType))));
end
else
j_entry_addZeros.append(zeros(int64(count),int64(channels),lower(char(j_entry.getDataType))));
end
position = position + count;
end
end
function values_entry_addZeros(j_entry, j_unisens_addZeros, samplestamp_end)
j_entry_addZeros=j_unisens_addZeros.addEntry(j_entry.clone(),false);
%copy values with timeshifted samplestamp
while (true)
j_values = j_entry.read(100000);
nValues = j_values.size();
if nValues==0
break;
end
%TODO use arrayList of values for speed, add funtion to unisens
%library
for i=1:nValues
j_value=j_values(i);
if ~isempty(j_value)
samplestamp = j_value.getSampleStamp();
if (samplestamp <=samplestamp_end)
%TODO deep copy needed?
j_value.setSamplestamp(j_value.getSamplestamp());
%j_value_addZeros = Value(j_value.getSamplestamp(), j_value.getData());
j_entry_addZeros.append(j_value);
else
%break if first value is outside region
break;
end
else
break;
end
end
end
end
function event_entry_addZeros(j_entry, j_unisens_addZeros, samplestamp_end)
j_unisens_addZeros=j_unisens_addZeros.addEntry(j_entry.clone(),false);
%copy eventy with timeshifted samplestamp
while (true)
j_events = j_entry.read(100000);
nEvents = j_events.size();
if nEvents==0
break;
end
j_event_iterator = j_events.iterator();
addZerosEvents = java.util.ArrayList();
while (j_event_iterator.hasNext())
j_event=j_event_iterator.next();
samplestamp = j_event.getSamplestamp();
if (samplestamp <=samplestamp_end)
%TODO deep copy needed?
%j_unisens_addZeros = org.unisens.Event(j_event.getSamplestamp(), j_event.getType(),j_event.getComment());
j_event.setSamplestamp(j_event.getSamplestamp());
addZerosEvents.add(j_event);
else
%break if first event is outside region
break;
end
end
j_unisens_addZeros.append(addZerosEvents);
end
end
function result = durationOk(j_unisens, newDuration)
j_entries = j_unisens.getEntries();
nEntries = j_entries.size();
allDurations = [];
for i = 0:nEntries-1
j_entry = j_entries.get(i);
entry_class_name= j_entry.getClass.toString;
if strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl')
nSamples=j_entry.getCount();
sampleRate = j_entry.getSampleRate();
allDurations=[allDurations nSamples/sampleRate];
end
end
result = min(allDurations) < newDuration;
end
|
github
|
Unisens/unisensMatlabTools-master
|
unisensCsv2Bin.m
|
.m
|
unisensMatlabTools-master/unisensCsv2Bin.m
| 4,937 |
utf_8
|
93aaf329972417ca112b688c76105878
|
function unisensCsv2Bin(path, new_path)
%UNISENSCSV2BIN convert unisens dataset with csv entries to dataset with bin entries
% Converts all unisens signal entries from csv format (*.csv) to bin format (*.bin).
% Event entries and values entries are not affected
% Copyright 2017 movisens GmbH
addUnisensJar();
if nargin==0 || nargin>2
error('unisensTools:missingArugments','Wrong number of Arguments.\nUsage:\nunisensCsv2Bin(''path_to_unisens_bin_dataset\'') \nunisensBin2Csv(''path_to_unisens_bin_dataset\'', ''path_to_new_unisens_csv_dataset\'')');
end
if nargin ==1
new_path = [path '_bin'];
end
%open unisens dataset
j_unisensFactory = org.unisens.UnisensFactoryBuilder.createFactory();
j_unisens = j_unisensFactory.createUnisens(path);
%create new unisens dataset
j_unisens_new = j_unisensFactory.createUnisens(new_path);
%set comment
j_unisens_new.setComment([char(j_unisens.getComment()) ' Converted by unisensCsv2Bin().']);
%copy custom attibutes
j_custom_attributes = j_unisens.getCustomAttributes();
j_key_iterator = j_custom_attributes.keySet().iterator();
while( j_key_iterator. hasNext() )
j_key = j_key_iterator.next();
j_unisens_new.addCustomAttribute(j_key,j_custom_attributes.get(j_key));
end
%copy context information
j_context = j_unisens.getContext();
if ~isempty(j_context)
j_unisens_new.createContext(j_context.getSchemaUrl());
copyfile([path filesep 'context.xml'],new_path);
end
%set measurement id
measurement_id = j_unisens.getMeasurementId();
if ~isempty(measurement_id)
j_unisens_new.setMeasurementId(j_unisens.getMeasurementId());
end
%set duration in [s]
j_unisens_new.setDuration(j_unisens.getDuration());
%set timestamp in [s]
j_timestamp_start = j_unisens.getTimestampStart();
if ~isempty(j_timestamp_start)
j_unisens_new.setTimestampStart(j_timestamp_start);
end
%loop over all timed entries (signal, values and event entries)
j_entries = j_unisens.getEntries();
nEntries = j_entries.size();
for i = 0:nEntries-1
j_entry = j_entries.get(i);
entry_class_name= j_entry.getClass.toString;
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%here we go
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl'))
%signalEntry
signal_entry_convert(j_entry, j_unisens_new);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl'))
%valuesEntry
values_entry_copy(j_entry, j_unisens_new);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%eventEntry
event_entry_copy(j_entry, j_unisens_new);
end
elseif (strcmp(entry_class_name, 'class org.unisens.ri.CustomEntryImpl'))
%customEntry
disp('Crop not possible for custom Entries');
end
end
%copy groups
j_groups = j_unisens.getGroups();
nGroups = j_groups.size();
for i = 0:nGroups-1
j_group = j_groups.get(i);
j_group_cropped = j_unisens_new.createGroup(j_group.getId());
j_group_entries = j_group.getEntries();
nEntries = j_group.size();
for j = 0:nEntries
j_group_cropped.addEntry(j_unisens_new.getEntry(j_group_entries.get(j).getId()));
end
end
%unisens speichern
j_unisens_new.save();
j_unisens_new.closeAll();
j_unisens.closeAll();
end
function signal_entry_convert(j_entry, j_unisens_new)
%copy entry information
newId = strrep(char(j_entry.getId()),'csv','bin');
j_entry_new=j_unisens_new.createSignalEntry(newId, j_entry.getChannelNames, org.unisens.DataType.DOUBLE , j_entry.getSampleRate());
j_entry_new.setFileFormat(j_entry_new.createBinFileFormat());
j_entry_new.setComment(j_entry.getComment());
j_entry_new.setContentClass(j_entry.getContentClass());
j_entry_new.setUnit(j_entry.getUnit());
%copy data piecewise
position = 0;
total = j_entry.getCount();
while (position < total)
if (total - position > 1000000)
count = 1000000;
else
count = total - position;
end
data = j_entry.readScaled(position, count);
j_entry_new.append(data);
position = position + count;
end
end
function values_entry_copy(j_entry, j_unisens_new)
j_entry_new=j_unisens_new.addEntry(j_entry.clone(),true);
end
function event_entry_copy(j_entry, j_unisens_new)
j_entry_new=j_unisens_new.addEntry(j_entry.clone(),true);
end
|
github
|
Unisens/unisensMatlabTools-master
|
unisensCrop.m
|
.m
|
unisensMatlabTools-master/unisensCrop.m
| 8,048 |
utf_8
|
f40ca68854d3743c34c1e1cdd289865a
|
function unisensCrop(path, new_path, crop_samplerate, start_samplestamp, end_samplestamp)
%UNISENSCROP crop a unisens dataset to a specified region
% Copyright 2017 movisens GmbH, Germany
crop_start_time = start_samplestamp / crop_samplerate;
crop_end_time = end_samplestamp / crop_samplerate;
%check if crop_end_time is smaller than crop_start_time
if start_samplestamp > end_samplestamp
error('crop end is smaller than crop start');
end
%open unisens dataset
j_unisensFactory = org.unisens.UnisensFactoryBuilder.createFactory();
j_unisens = j_unisensFactory.createUnisens(path);
%check if unisens dataset is long enough
if ~durationOk(j_unisens, end_samplestamp / crop_samplerate)
warning(['Unisens Dataset ' path ' is not long enough.']);
end
%create new unisens dataset
j_unisens_cropped = j_unisensFactory.createUnisens(new_path);
%set comment
j_unisens_cropped.setComment([char(j_unisens.getComment()) ' Cropped by unisensCrop(). Small jitter possible']);
%copy custom attibutes
j_custom_attributes = j_unisens.getCustomAttributes();
j_key_iterator = j_custom_attributes.keySet().iterator();
while( j_key_iterator. hasNext() )
j_key = j_key_iterator.next();
j_unisens_cropped.addCustomAttribute(j_key,j_custom_attributes.get(j_key));
end
%copy context information
j_context = j_unisens.getContext();
if ~isempty(j_context)
j_unisens_cropped.createContext(j_context.getSchemaUrl());
copyfile([path filesep 'context.xml'],new_path);
end
%set measurement id
measurement_id = j_unisens.getMeasurementId();
if ~isempty(measurement_id)
j_unisens_cropped.setMeasurementId(j_unisens.getMeasurementId());
end
%loop over all timed entries (signal, values and event entries)
j_entries = j_unisens.getEntries();
nEntries = j_entries.size();
for i = 0:nEntries-1
j_entry = j_entries.get(i);
entry_class_name= j_entry.getClass.toString;
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl')) || ...
(strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%here we go
entry_samplerate= j_entries.get(i).getSampleRate();
entry_samplestamp_start = crop_start_time * entry_samplerate;
entry_samplestamp_end = crop_end_time * entry_samplerate;
if (strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl'))
%signalEntry
signal_entry_crop(j_entry, j_unisens_cropped, entry_samplestamp_start, entry_samplestamp_end);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.ValuesEntryImpl'))
%valuesEntry
%values_entry_crop(j_entry, j_unisens_cropped, entry_samplestamp_start, entry_samplestamp_end);
elseif (strcmp(entry_class_name, 'class org.unisens.ri.EventEntryImpl'))
%eventEntry
event_entry_crop(j_entry, j_unisens_cropped, entry_samplestamp_start, entry_samplestamp_end);
end
elseif (strcmp(entry_class_name, 'class org.unisens.ri.CustomEntryImpl'))
%customEntry
disp('Crop not possible for custom Entries');
end
end
%set new duration in [s]
%TODO duration will be changed to double?
j_unisens_cropped.setDuration(crop_end_time-crop_start_time)
%set new timesamtp start if available
j_timestamp_start = j_unisens.getTimestampStart();
if ~isempty(j_timestamp_start)
j_unisens_cropped.setTimestampStart(java.util.Date(j_timestamp_start.getTime() + (crop_start_time*1000)));
end
%copy groups
j_groups = j_unisens.getGroups();
nGroups = j_groups.size();
for i = 0:nGroups-1
j_group = j_groups.get(i);
j_group_cropped = j_unisens_cropped.createGroup(j_group.getId());
j_group_entries = j_group.getEntries();
nEntries = j_group.size();
for j = 0:nEntries
j_group_cropped.addEntry(j_unisens_cropped.getEntry(j_group_entries.get(j).getId()));
end
end
%unisens speichern
j_unisens_cropped.save();
j_unisens_cropped.closeAll();
j_unisens.closeAll();
end
function signal_entry_crop(j_entry, j_unisens_cropped, samplestamp_start, samplestamp_end)
%copy entry information
j_entry_cropped=j_unisens_cropped.addEntry(j_entry.clone(),false);
%copy data piecewise
position = samplestamp_start;
while (position < samplestamp_end)
if (samplestamp_end - position > 1000000)
count = 1000000;
else
count = samplestamp_end - position;
end
data = j_entry.read(position, count);
if ~isempty(data)
j_entry_cropped.append(data);
end
position = position + count;
end
end
function values_entry_crop(j_entry, j_unisens_cropped, samplestamp_start, samplestamp_end)
j_entry_cropped=j_unisens_cropped.addEntry(j_entry.clone(),false);
%copy values with timeshifted samplestamp
while (true)
j_values = j_entry.read(100000);
nValues = j_values.size();
if nValues==0
break;
end
%TODO use arrayList of values for speed, add funtion to unisens
%library
for i=1:nValues
j_value=j_values(i);
if ~isempty(j_value)
samplestamp = j_value.getSampleStamp();
if (samplestamp > samplestamp_start)
if (samplestamp <=samplestamp_end)
%TODO deep copy needed?
j_value.setSamplestamp(j_value.getSamplestamp()-samplestamp_start);
%j_value_cropped = Value(j_value.getSamplestamp()-samplestamp_start, j_value.getData());
j_entry_cropped.append(j_value);
else
%break if first value is outside crop region
break;
end
end
else
break;
end
end
end
end
function event_entry_crop(j_entry, j_unisens_cropped, samplestamp_start, samplestamp_end)
j_entry_cropped=j_unisens_cropped.addEntry(j_entry.clone(),false);
%copy eventy with timeshifted samplestamp
while (true)
j_events = j_entry.read(100000);
nEvents = j_events.size();
if nEvents==0
break;
end
j_event_iterator = j_events.iterator();
croppedEvents = java.util.ArrayList();
while (j_event_iterator.hasNext())
j_event=j_event_iterator.next();
samplestamp = j_event.getSamplestamp();
if (samplestamp > samplestamp_start)
if (samplestamp <=samplestamp_end)
%TODO deep copy needed?
%j_event_cropped = org.unisens.Event(j_event.getSamplestamp()-samplestamp_start, j_event.getType(),j_event.getComment());
j_event.setSamplestamp(j_event.getSamplestamp()-samplestamp_start);
croppedEvents.add(j_event);
else
%break if first event is outside crop region
break;
end
end
end
j_entry_cropped.append(croppedEvents);
end
end
function result = durationOk(j_unisens, minDuration)
j_entries = j_unisens.getEntries();
nEntries = j_entries.size();
allDurations = [];
for i = 0:nEntries-1
j_entry = j_entries.get(i);
entry_class_name= j_entry.getClass.toString;
if strcmp(entry_class_name, 'class org.unisens.ri.SignalEntryImpl')
nSamples=j_entry.getCount();
sampleRate = j_entry.getSampleRate();
allDurations=[allDurations nSamples/sampleRate];
end
end
result = min(allDurations) > minDuration;
end
|
github
|
lightyears1998/a-gzhu-coder-master
|
figure.m
|
.m
|
a-gzhu-coder-master/period/freshman/物理实验/变温粘滞系数的测定/figure.m
| 473 |
utf_8
|
66121fba75c6072fcbef078143902f7f
|
% 变温粘滞系数 Figure %
nw = [.548, .469, .343, .222, .182];
t = [ 30, 35, 40, 45, 50];
function rslt = fun(var, data)
rslt = var(1) * exp(-var(2) * data);
endfunction
var0 = [0 0];
P = lsqcurvefit(@fun, var0, t, nw);
graphics_toolkit("gnuplot");
figure();
hold on;
grid off;
axis([25, 55, 0, 0.6]);
plot(t, nw, '+', 'MarkerSize', 12);
plot([25:1:55], fun(P, [25:1:55]), 'LineWidth', 5);
print('figure.png', '-dpng');
hold off;
|
github
|
vitoruapt/lartkv5-master
|
matlab2opencv.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/matlab2opencv.m
| 1,002 |
utf_8
|
faa2274109d4211d124825eeac37a400
|
%creates yaml file from matlab var, so it can be loaded by opencv
function matlab2opencv( variable, fileName, flag)
[rows cols] = size(variable);
% Beware of Matlab's linear indexing
variable = variable';
% Write mode as default
if ( ~exist('flag','var') )
flag = 'w';
end
if ( ~exist(fileName,'file') || flag == 'w' )
% New file or write mode specified
file = fopen( fileName, 'w');
fprintf( file, '%%YAML:1.0\n');
else
% Append mode
file = fopen( fileName, 'a');
end
% Write variable header
fprintf( file, ' %s: !!opencv-matrix\n', inputname(1));
fprintf( file, ' rows: %d\n', rows);
fprintf( file, ' cols: %d\n', cols);
fprintf( file, ' dt: f\n');
fprintf( file, ' data: [ ');
% Write variable data
for i=1:rows*cols
fprintf( file, '%.6f', variable(i));
if (i == rows*cols), break, end
fprintf( file, ', ');
if mod(i+1,4) == 0
fprintf( file, '\n ');
end
end
fprintf( file, ']\n');
fclose(file);
|
github
|
vitoruapt/lartkv5-master
|
show_labels.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/show_labels.m
| 1,338 |
utf_8
|
ab280e637c4213c23d1ea1b9786aec23
|
%compare the labels created by the three evaluators with, also plotting the
%final tag, for illustrative purposes only.
%input must be xx files
function [] = plot_labels(test)
features = test(:,5:end);
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
% Create figure
F = figure('position',[360 260 900 600]);
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',1.5);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
%%%%%%%%%%% pro plot %%%%%%%%%%
gd_class = test(:,2);
bad_tag = test(gd_class == 1,1);
H = figure;
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);
%axis equal;
axis tight;
ax_x = get(H, 'xlim');
ax_y = get(H, 'ylim');
box on;
set(gca,'XTickLabel',[]);
%set(gca,'YTickLabel',[]);
ylabel('pro');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
github
|
vitoruapt/lartkv5-master
|
relative_velocities.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/relative_velocities.m
| 901 |
utf_8
|
f9ecea158bfff8175dccdbc6bb95383f
|
%compute relative velocities, decomposing original feature that was scalar
%only, requires target_velocity, relative_velocity and relative_heading
function [rel_vx rel_vy] = relative_velocities(dataset)
tgt_v = dataset(:,3);
rel_v = dataset(:,4);
rel_h = dataset(:,5);
%recompute robot velocity
robot_v = rel_v + tgt_v;
%sin an cos of relative angle (heading)
sin_v = sin(rel_h);
cos_v = cos(rel_h);
%compute target vel wrt robot frame
tgt_vx = tgt_v.*cos_v;
tgt_vy = tgt_v.*sin_v;
%compute relative vel wrt robot frame
rel_vx = tgt_vx - robot_v;
rel_vy = tgt_vy;
%rel_vx = tgt_v.*cos(rel_h) - (rel_v + tgt_v);
%for comparison with rel_v from dataset
%rel_v = sqrt(((robotv-tgt_vx).^2)+(tgt_vy).^2);
% figure,hold
% plot(rel_v,'b')
% plot(abs(dataset(:,4)),'r')
% plot(tgt_vx,'m')
% plot(tgt_vy,'c')
% plot(sin_v,'k')
% plot(cos_v,'y')
%
% delta = abs(dataset(:,4))-rel_v;
%plot(delta,'go')
end
|
github
|
vitoruapt/lartkv5-master
|
plot_class_error.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/plot_class_error.m
| 942 |
utf_8
|
293c87fc993554746f6e4632eebf2aec
|
%show the error in classification as a graph, for all the test set, shown
%in the x axis, input is a matrix copied from excel, containing the value
%of the errors, but could come directly from evaluate_model function. it
%has been done this way because excel already had all the errors in tables.
function [] = plot_class_error(input)
F = figure; hold;
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',2);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
plot(input(1,:),'bs-','color',[1 0.82 0.13]);
plot(input(2,:),'md-','color',[1 0.26 0.06]);
plot(input(3,:),'ko-','color',[0 0.27 0.53]);
label = {'st04','st08','gd02','gd06','as02','as03',...
'fr04','nm05','nm03','od01','od10','total'};
axis tight, grid on;
set(gcf,'position',[175 338 1000 300]);
set(gca,'ylim',[0 0.4]);
set(gca,'xtick',1:12)
set(gca,'XTickLabel',label);
legend('false good','false bad','false total','location','eastoutside');
|
github
|
vitoruapt/lartkv5-master
|
show_thresholds.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/show_thresholds.m
| 943 |
utf_8
|
7bdaa72b918d819190140d9908221b5d
|
%create linear variation of features to find what are the thresholds
%used by the classifier on each feature, receive as argument the classifier
%and the dimension to evaluate
function []=show_thresholds(model,dim)
clear new_model;
clear j; j=1; clear test_thresh;
% test_thresh = zeros(401,9);
test_thresh(:,1) = 1:401;
% second column is tag, does not matter here.
test_thresh(:,3) = -10:0.05:10; %1 velocity
% test_thresh(:,4) = -10:0.05:10; %2 lat disp.
% test_thresh(:,5) = -pi:0.0157:pi; %3 rel head.
% test_thresh(:,6) = -pi:0.0157:pi; %4 angle
% test_thresh(:,7) = -10:0.05:10; %5 dist
% test_thresh(:,8) = -10:0.05:10; %6 rel vx
% test_thresh(:,9) = -10:0.05:10; %7 rel vy
%
% test_thresh(:,10:23) = 0;
% for ii=10:23
% test_thresh(:,ii) = -10:0.05:10;
% end
for i=1:length(model)
if model(i).dimension == dim
new_model(j)=model(i);
j=j+1;
end
end
evaluate_model_single(new_model,test_thresh);
end
|
github
|
vitoruapt/lartkv5-master
|
compare_classifiers.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/compare_classifiers.m
| 3,391 |
utf_8
|
49da591a25df76b44b60c94c25ddbf32
|
% i think this was created to comparte an adaboost classificer with
% a neural network classifier
%test neural network
function [] = compare_classifiers(model,net,test)
%prepare the data
features = test(:,3:7);
input_val = features';
target_val = test(:,2)';
target_val(2,find(target_val == 0)) = 1; %for ann
test(test(:,2)==0,2)=-1; %for ada: transform from 0 to -1
gd_class = test(:,2); %second column has leader tag
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
%%%%%%%%%%%%% ANN Classifier %%%%%%%%%%
% Test the Network
outputs = net(input_val);
% binarize classification = good/bad
ann_class = round(outputs(2,:));
%diferences = abs(test_class - gd_class);
differences = abs(target_val(2,:) - ann_class);
error = length(find(differences == 1));
error_ratio = error / length(differences);
ann_string = ...
sprintf('NeuralNet Classification. error:%.2f',error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%% Adaboost Classifier %%%%%%%%%%
% Classify the features with the trained model
if(isstruct(model))
%classic adaboost
ada_class = adaboost('apply',features, model);
else
%matlab adaboost
ada_class = predict(model, features);
end
diferences = abs(ada_class - gd_class);
error = length(find(diferences == 2));
error_ratio = error / length(diferences);
ada_string = ...
sprintf('Adaboost Classification. error:%.2f',error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% groundtruth plot %%%%%%%%%%
bad_tag = test(gd_class == 1,1);
% Show groundtruth
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',2);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
set(H,'position',[740 110 550 550]);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
subplot(3,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
vel = plot(time,features(:,1),'b');
vld = plot(time,features(:,2),'m');
hdd = plot(time,features(:,3),'k');
ang = plot(time,features(:,4),'g');
dst = plot(time,features(:,5),'y');
l_handle = legend([vel, vld, hdd, ang, dst],...
'vel','vel diff','head diff','angle', 'distance');
set(l_handle,'orientation','horizontal',...
'Position',[0.12 0.0 0.8 0.05]);
axis tight;
set(gca,'XTickLabel',[]);
title('Ground Truth','FontWeight','bold');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% neural net plot %%%%%%%%%%%
bad_tag = test(ann_class == 0,1);
% Show classification
subplot(3,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b');
plot(time,features(:,2),'m');
plot(time,features(:,3),'k');
plot(time,features(:,4),'g');
plot(time,features(:,5),'y');
axis tight;
set(gca,'XTickLabel',[]);
title(ann_string,'FontWeight','bold');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% Adaboost plot %%%%%%%%%%%%%
bad_tag = test(ada_class == 1,1);
% Show classification
subplot(3,1,3), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b');
plot(time,features(:,2),'m');
plot(time,features(:,3),'k');
plot(time,features(:,4),'g');
plot(time,features(:,5),'y');
axis tight;
title(ada_string,'FontWeight','bold');
|
github
|
vitoruapt/lartkv5-master
|
train_net.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/train_net.m
| 907 |
utf_8
|
0d219bb6a1a146ccf798b6ec9b25b86f
|
%train neural network
% function [net] = train_net(inputs,targets)
function [net] = train_net(train_set,n_neurons)
inputs = train_set(:,3:end);
targets = train_set(:,2);
targets(targets==0,2)=1;
% Solve a Pattern Recognition Problem with a Neural Network
inputs = inputs';
targets = targets';
% Create a Pattern Recognition Network
hiddenLayerSize = n_neurons;%[10,10];
net = patternnet(hiddenLayerSize);
%net.performParam.regularization = 0.1;
% net.trainFcn = 'trainbr';
net.trainParam.max_fail = 100;
% Setup Division of Data for Training, Validation, Testing
%net.divideFcn = 'dividetrain'
net.divideFcn = 'divideind';
net.divideParam.testInd = [];
net.divideParam.trainInd = 1:8504;
net.divideParam.valInd = 8505:10196;
% net.divideparam.trainratio = 85/100;
% net.divideparam.valratio = 10/100;
% net.divideparam.testratio = 5/100;
% Train the Network
[net,tr] = train(net,inputs,targets);
|
github
|
vitoruapt/lartkv5-master
|
test_net.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/test_net.m
| 3,230 |
utf_8
|
8dc4a43efed1f2b19867805d622306f8
|
%test neural network
function [] = test_net(net,test_set)
for number = 1:length(test_set)
test = test_set(number).set;
name = test_set(number).name;
%prepare the data
features = test(:,3:end);
input_val = features';
target_val = test(:,2)';
target_val(2,target_val == 0) = 1;
gt_class = test(:,2); %second column has leader tag
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
% Test the Network
outputs = net(input_val);
%errors = gsubtract(y_val',outputs);
%performance = perform(net,y_val',outputs)
classes = round(outputs(2,:));
%classes = vec2ind(outputs) - 1;
%%%%% debug plot %%%%%%
% figure, hold;
% plot(target_val','o');
% plot(outputs(1,:),'k');
% plot(outputs(2,:),'r');
% plot(classes,'y');
%diferences = abs(test_class - gd_class);
% differences = abs(target_val(2,:)-classes);
% error = length(find(differences == 1));
% error_ratio = error / length(differences);
% title_string = ...
% sprintf('NeuralNet Classification. error:%.2f',error_ratio);
differences = classes - target_val(2,:);
false_bad = length(find(differences == -1));
false_good = length(find(differences == 1));
false_total = false_bad + false_good;
false_bad_ratio = false_bad / length(differences);
false_good_ratio = false_good / length(differences);
false_bad_ratio = round(false_bad_ratio*100)/100;
false_good_ratio = round(false_good_ratio*100)/100;
error_ratio = false_bad_ratio + false_good_ratio;
title_string = ...
sprintf('false good:%.2f, false bad:%.2f, total error:%.2f',...
false_good_ratio, false_bad_ratio, error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% groundtruth plot %%%%%%%%%%
bad_tag = test(gt_class == 1,1);
% Show groundtruth
figure;
subplot(2,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
%axis equal;
axis tight;
title(['test:' name ' ' 'ground truth']);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% classification plot %%%%%%%
bad_tag = test(classes == 0,1);
% Show classification
subplot(2,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
plot(time,outputs(1,:),'bo');
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
%axis equal;
axis tight;
title(title_string);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
end
|
github
|
vitoruapt/lartkv5-master
|
evaluate_model_single.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/evaluate_model_single.m
| 3,609 |
utf_8
|
b86fe2360a8aafd9d15d87f1c08468b1
|
%evaluates adaboost classifier, comparing groundtruth
%with class output, may receive a single dataset or a structure of them,
%create plots comparing ground truth and classification, also prints error
%of false good, false bad and false total
function [] = evaluate_model(model,test_set)
if size(test_set,1)~=1
temp = test_set;
clear test_set;
test_set.set = temp;
test_set.name = 'single';
end
for number = 1:length(test_set)
test = test_set(number).set;
name = test_set(number).name;
%prepare the data
features = test(:,3:end);
test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test(:,2); %second column has leader tag [-1 good / 1 bad]
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
tic
% Classify the features with the trained model
if(isstruct(model))
%classic adaboost
test_class=adaboost('apply',features, model);
else
%matlab adaboost
test_class=predict(model, features);
end
toc
differences = test_class - gd_class;
false_bad = length(find(differences == 2));
false_good = length(find(differences == -2));
false_total = false_bad + false_good;
false_bad_ratio = false_bad / length(differences);
false_good_ratio = false_good / length(differences);
false_bad_ratio = round(false_bad_ratio*100)/100;
false_good_ratio = round(false_good_ratio*100)/100;
error_ratio = false_bad_ratio + false_good_ratio;
title_string = ...
sprintf('false good:%.2f, false bad:%.2f, total error:%.2f',...
false_good_ratio, false_bad_ratio, error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% target plot %%%%%%%%%%%%%%%
bad_tag = test(gd_class == 1,1);
% Show the data
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',2);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
subplot(2,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
axis tight; %axis equal
title(['test:' name ' ' 'ground truth']);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Show result
bad_tag = test(test_class == 1,1);
% Show the data
subplot(2,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
axis tight; %axis equal;
title(title_string);
end
end
function large_markers
tmp_l = legend('velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(tmp_l,'visible','off')
xlabel('t(s)');
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
%set(ax2,'position',get(ax1,'position'));
hL = legend(ax2,'velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(ax2,'visible','off')
axis(ax1, 'tight');
%set(gcf,'position',[200 200 800 400]);
end
|
github
|
vitoruapt/lartkv5-master
|
adaboost_vs_ann.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/adaboost_vs_ann.m
| 1,794 |
utf_8
|
2b9a6ca896a568cbfad96012f03beb47
|
%compare the labels created by the three evaluators with, also plotting the
%final tag, for illustrative purposes only.
function [] = adaboost_vs_ann()
% Create figure
% F = figure('position',[360 260 750 600]);
F = figure('position',[360 260 750 500]);
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',1.5);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
%%%%%%%%%%% false good %%%%%%%%%%
% FG = subplot(3,1,1,'position',[0.065 0.70 0.90 0.20]);
FG = subplot(3,1,1,'position',[0.075 0.65 0.90 0.25]);
hold on; grid on;
set(gca,'xtick',1:12);
set(FG,'xlim',[1 12]);
set(FG,'ylim',[0 0.4]);
ax_x = get(FG, 'xlim');
ax_y = get(FG, 'ylim');
box on;
set(gca,'XTickLabel',[]);
ylabel('false good');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%% false bad %%%%%%%%%%
% FB = subplot(3,1,2,'position',[0.065 0.4125 0.90 0.20]);
FB = subplot(3,1,2,'position',[0.075 0.36 0.90 0.25]);
hold on; grid on;
set(gca,'xtick',1:12);
set(FB,'xlim',ax_x);
set(FB,'ylim',ax_y);
set(gca,'XTickLabel',[]);
box on;
ylabel('false bad');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%% false total %%%%%%%%%%
FT = subplot(3,1,3,'position',[0.075 0.066 0.90 0.25]);
hold on; grid on;
set(gca,'xtick',1:12);
set(FT,'xlim',ax_x);
set(FT,'ylim',ax_y);
box on;
label = {'st04','st08','gd02','gd06','as02','as03',...
'fr04','nm05','nm03','od01','od10','total'};
set(gca,'XTickLabel',label);
ylabel('false total');
large_markers
%%%%%%%%%%%%%%%%%%%%%%%%
end
function large_markers
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'r','linewidth',10,'parent',ax2);
hL = legend(ax2,'AdaBoost','ANN','location','eastOutside');
set(hL,'orientation', 'horizontal');
set(hL,'position', [0.37 0.92 0.25 0.05]);
set(ax2,'visible','off')
axis(ax1, 'tight');
end
|
github
|
vitoruapt/lartkv5-master
|
train_adaboost.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/train_adaboost.m
| 5,522 |
utf_8
|
2362578a48eadb03855f3d3a151234ea
|
%trains an adaboost classifier, input is training set, and iterations are
%the max number of weak classifiers allowed
function [classestimate,model,feat_of_wc] = train_adaboost(data,iterations)
%train adaboost classifier downloaded from internet
%features:
% 3: target velocity
% 4: lateral displacement (former relative velocity)
% 5: heading difference
% 6: angle between robot head and target pos
% 7: distance
% 8: relative velocity x
% 9: relative velocity y
datafeatures = data(:,3:end);
% data classification
data(data(:,2)==0,2)=-1; %transform from 0 to -1
dataclass = data(:,2); %second column has leader tag
% Use Adaboost to make a classifier
[classestimate,model]=adaboost('train',datafeatures,dataclass,iterations);
% Show the error verus number of weak classifiers
error=zeros(1,length(model));
feat_of_wc = zeros(1,length(model));
cont_ratio = zeros(1,size(datafeatures,2));
for i=1:length(model)
error(i)=model(i).error;
feature_id = model(i).dimension;
feat_of_wc(i) = feature_id;
cont_ratio(feature_id)=cont_ratio(feature_id)+model(i).alpha;
end
cont_ratio = cont_ratio./sum(cont_ratio);
fh1 = figure;
set(fh1,'defaultlinelinewidth',3);
set(fh1,'defaultaxeslinewidth',2);
set(fh1,'defaulttextfontsize',12);
set(fh1,'defaultaxesfontsize',12);
set(fh1,'position',[480 210 800 400]);
hold, title('Classification error versus number of weak classifiers');
plot(error);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
fh2 = figure;
set(fh2,'defaultlinelinewidth',3);
set(fh2,'defaultaxeslinewidth',2);
set(fh2,'defaulttextfontsize',12);
set(fh2,'defaultaxesfontsize',12);
set(fh2,'position',[ 679 106 600 400]);
hold, title('Features');
% [H,X] = hist(feat_of_wc,1:size(datafeatures,2));
[H,X] = hist(feat_of_wc,1:size(datafeatures,2));
a = [H;X]';
a(:,3) = a(:,1)/length(feat_of_wc);
sortrows(a)
cm = jet(length(X));
for i=1:length(X)
h=bar(X(i),H(i));
set(h,'facecolor',cm(i,:));
end
ylabel('weak classifiers');
set(gca,'XTickLabel',[]);
axis tight;
% legend('velocity',...
% 'lateral displacement',...
% 'relative heading',...
% 'angle','distance',...
% 'relative vel. x',...
% 'relative vel. y',...
% 'location','eastOutside');
legend('mean target vel.',...
'mean lat. displ.',...
'mean rel. head.',...
'mean angle',...
'mean distance',...
'mean relative vel. x',...
'mean relative vel. y',...
'Location','eastOutside')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
fh3 = figure;
set(fh3,'defaultlinelinewidth',3);
set(fh3,'defaultaxeslinewidth',2);
set(fh3,'defaulttextfontsize',12);
set(fh3,'defaultaxesfontsize',12);
set(fh3,'position',[ 679 106 600 400]);
hold,
title({'Features Contribution Ratio';...
sprintf('(number of weak classifiers = %i)',length(feat_of_wc))})
%X = 1:length(cont_ratio);
H = cont_ratio;
cm = jet(length(X));
for i=1:length(X)
h2=bar(X(i),H(i));
set(h2,'facecolor',cm(i,:));
end
ylabel('contribution ratio');
set(gca,'XTick',1:21);
set(gcf,'position',[250 100 1200 500]);
axis tight;
set(gca,'YLim',[0 0.25]);
grid;
legend('1. lateral displ.',...
'2. rel. heading',...
'3. angle',...
'4. distance',...
'5. stdv distance',...
'Location','eastOutside');
legend('1. target velocity',...
'2. lateral displ.',...
'3. rel. heading',...
'4. angle',...
'5. distance',...
'6. relative vel. x',...
'7. relative vel. y',...
'8. stdv target vel.',...
'9. stdv lateral displ.',...
'10. stdv rel. head.',...
'11. stdv angle',...
'12. stdv distance',...
'13. stdv relative vel. x',...
'Location','eastOutside');
% if (length(H)~=length(X))
% X = [1 round(X)]
% end
a = [H;X]';
sortrows(a)
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% legend('1. target velocity',...
% '2. lateral displ.',...
% '3. rel. heading',...
% '4. angle',...
% '5. distance',...
% '6. relative vel. x',...
% '7. relative vel. y',...
% '8. \Delta target vel.',...
% '9. \Delta lateral displ.',...
% '10. \Delta rel. head.',...
% '11. \Delta angle',...
% '12. \Delta distance',...
% '13. \Delta relative vel. x',...
% '14. \Delta relative vel. y',...
% '15. stdv target vel.',...
% '16. stdv lateral displ.',...
% '17. stdv rel. head.',...
% '18. stdv angle',...
% '19. stdv distance',...
% '20. stdv relative vel. x',...
% '21. stdv relative vel. y',...
% 'Location','eastOutside');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Training results
% Show results
% blue=datafeatures(classestimate==-1,:); red=datafeatures(classestimate==1,:);
% I=zeros(161,161);
% for i=1:length(model)
% if(model(i).dimension==1)
% if(model(i).direction==1), rec=[-80 -80 80+model(i).threshold 160];
% else rec=[model(i).threshold -80 80-model(i).threshold 160 ];
% end
% else
% if(model(i).direction==1), rec=[-80 -80 160 80+model(i).threshold];
% else rec=[-80 model(i).threshold 160 80-model(i).threshold];
% end
% end
% rec=round(rec);
% y=rec(1)+81:rec(1)+81+rec(3); x=rec(2)+81:rec(2)+81+rec(4);
% I=I-model(i).alpha; I(x,y)=I(x,y)+2*model(i).alpha;
% end
% subplot(2,2,2), imshow(I,[]); colorbar; axis xy;
% colormap('jet'), hold on
% plot(blue(:,1)+81,blue(:,2)+81,'bo');
% plot(red(:,1)+81,red(:,2)+81,'ro');
% title('Training Data classified with adaboost model');
|
github
|
vitoruapt/lartkv5-master
|
leader_features.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/leader_features.m
| 3,099 |
utf_8
|
55c282a169e38696d0583e4ede61126d
|
%extract features from chosen target and
%stores it in a matlab variable (proc_target)
%must pass as arguments the name of the file, generated by ROS
%log file from process_target, and the id of the desired subject
function [proc_target]=leader_features(file,target_id)
% input file format:
% 1: id
% 2: good/bad tag
% 3: time
% 4: pos x
% 5: pos y
% 6: vel
% 7: theta
% 8: pos diff
% 9: head diff
%10: angle 2 robot
%11: velocity diff
%printf("%d,%d,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f\n",
% target_id, badLeader, time_elapsed.toSec(),
% target_x, target_y, target_vel, target_theta,
% position_diff, heading_diff, angle_to_robot, velocity_diff);
% output file format:
% 1: time
% 2: good/bad tag
% 3: mean vel 1
% 4: mean vel diff 2
% 5: mean head diff 3
% 6: angle 2 robot 4
% 7: mean dist 2 robot 5
%initialize vars
begin_sweep = 1;
end_sweep = 1;
counter = 1;
mean_fig = figure; hold on; grid on;
%load and rearrange targets file
list = load(file);
range = max(list(:,1)) + 2;
cm = jet(range);
figure,hold;
for i = 1:length(list);
if(list(i,1)==-1)
plot3(list(i,4),list(i,5),list(i,3),'bo');
elseif(list(i,1)==target_id)
plot3(list(i,4),list(i,5),list(i,3),'ro');
end
end
list = sortrows(list);
% separate target from robot
while counter < length(list)
while list(begin_sweep,1) == list(end_sweep,1)
end_sweep = end_sweep + 1;
counter = counter + 1;
if counter > length(list)
break
end
end
%only pick one target, according to input of function
switch list(begin_sweep,1)
case -1
robot = list(begin_sweep:end_sweep-1,:);
case target_id
target = list(begin_sweep:end_sweep-1,:);
end
begin_sweep = end_sweep;
end
% filter data
proc_target(length(target),7) = 0;
proc_target(:,1) = target(:,3);
proc_target(:,2) = target(:,2);
proc_target(:,3) = target(:,6); %vel
proc_target(:,4) = target(:,11); %vel diff
proc_target(:,5) = target(:,9); %head diff
proc_target(:,6) = target(:,10); %angle 2 robot
proc_target(:,7) = target(:,8); %pos diff (dist)
%%%%%%%%% PLOTTING %%%%%%%%%%%%
%plot good/bad leader index
tag = find(diff(proc_target(:,2)));
figure(mean_fig);
plot(proc_target(:,1),proc_target(:,3),'b-');
plot(proc_target(:,1),proc_target(:,4),'r-');
plot(proc_target(:,1),proc_target(:,5),'k-');
plot(proc_target(:,1),proc_target(:,6),'g-');
plot(proc_target(:,1),proc_target(:,7),'y-');
legend('vel','vel diff','head diff','angle', 'distance',...
'Location','NorthWest');
title('mean features from target 2 robot');
if ~isempty(tag)
line([proc_target(tag,1) proc_target(tag,1)],[0 5])
end
figure(mean_fig);
plot(proc_target(:,1),proc_target(:,3),'bo');
plot(proc_target(:,1),proc_target(:,4),'ro');
plot(proc_target(:,1),proc_target(:,5),'ko');
plot(proc_target(:,1),proc_target(:,6),'go');
plot(proc_target(:,1),proc_target(:,7),'yo');
legend('vel','vel diff','head diff','angle', 'distance',...
'Location','NorthWest');
|
github
|
vitoruapt/lartkv5-master
|
plot_labels.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/plot_labels.m
| 4,314 |
utf_8
|
ebee9d9693bb54f2e92624c850c4223d
|
%compare the labels created by the three evaluators with, also plotting the
%final tag, for illustrative purposes only.
function [] = plot_labels(test,final_tag)
features = test(:,5:end);
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
% Create figure
F = figure('position',[360 260 900 600]);
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',1.5);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
%%%%%%%%%%% pro plot %%%%%%%%%%
gd_class = test(:,2);
bad_tag = test(gd_class == 1,1);
H = subplot(3,1,1,'position',[0.065 0.70 0.70 0.20]);
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);
%axis equal;
axis tight;
ax_x = get(H, 'xlim');
ax_y = get(H, 'ylim');
box on;
set(gca,'XTickLabel',[]);
%set(gca,'YTickLabel',[]);
ylabel('pro');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%% rich plot %%%%%%%%%%
gd_class = test(:,3); %rich tag
bad_tag = test(gd_class == 1,1);
% Show the data
I = subplot(3,1,2,'position',[0.065 0.4125 0.70 0.20]);
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);
%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
set(gca,'XTickLabel',[]);
box on;
%set(gca,'YTickLabel',[]);
ylabel('rich');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%% jor plot %%%%%%%%%%
gd_class = test(:,4); %jorge_tag
bad_tag = test(gd_class == 1,1);
% Show the data
I = subplot(3,1,3,'position',[0.065 0.1250 0.70 0.20]);
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
box on;
xlabel('t(s)');
%set(gca,'YTickLabel',[]);
ylabel('jor');
large_markers
%%%%%%%%%%%%%%%%%%%%%%%%%%%
p_tag = test(diff(test(:,2))==1,1);
r_tag = test(diff(test(:,3))==1,1);
j_tag = test(diff(test(:,4))==1,1);
[p_tag r_tag j_tag]
%%%%%%%%%%%%%%%%%%%%%%%%
end
function large_markers
xlabel('t(s)');
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
plot(0,0,'color',[0.7 0.7 0.7],'linewidth',10,'parent',ax2);
% hL = legend(ax2,'velocity','rel velocity',...
% 'rel heading','angle','distance','bad leader region',...
% 'final tag',...
% 'location','eastOutside');
hL = legend(ax2,'velocity (m/s)','lateral disp. (m)',...
'relative head. (rad)','angle (rad)','distance (m)',...
'relative vel. x (m/s)','relative vel. y (m/s)','cropped region',...
'location','eastOutside');
set(hL,'position', [0.80 0.35 0.15 0.30]);
set(ax2,'visible','off')
axis(ax1, 'tight');
end
|
github
|
vitoruapt/lartkv5-master
|
plot_test2.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/plot_test2.m
| 2,313 |
utf_8
|
968d8618023c1cc38d47190720487c42
|
%used in do_tag to show comparison between labels
function [] = plot_test2(test_a)
features = test_a(:,5:end);
%test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test_a(:,2); %second column has leader tag
low_plot = min(min(features));
up_plot = max(max(features));
time = test_a(:,1);
bad_tag = test_a(gd_class == 1,1);
% Show the data
F = figure;
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',2);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
H = subplot(3,1,1); hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[0.5 0.5 0.5]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
%axis equal;
axis tight;
ax_x = get(H, 'xlim');
ax_y = get(H, 'ylim');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
features = test_a(:,5:end);
%test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test_a(:,3); %rich tag
low_plot = min(min(features));
up_plot = max(max(features));
time = test_a(:,1);
bad_tag = test_a(gd_class == 1,1);
% Show the data
I = subplot(3,1,2); hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[0.5 0.5 0.5]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
features = test_a(:,5:end);
%test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test_a(:,4); %jorge_tag
low_plot = min(min(features));
up_plot = max(max(features));
time = test_a(:,1);
bad_tag = test_a(gd_class == 1,1);
% Show the data
I = subplot(3,1,3); hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[0.5 0.5 0.5]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
xlabel('t(s)');
%%%%%%%%%%%%%%%%%%%%%%%%%%%
p_tag = test_a(diff(test_a(:,2))==1,1);
r_tag = test_a(diff(test_a(:,3))==1,1);
j_tag = test_a(diff(test_a(:,4))==1,1);
[p_tag r_tag j_tag]
|
github
|
vitoruapt/lartkv5-master
|
enhance_features.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/enhance_features.m
| 4,253 |
utf_8
|
891a77b7a8827b581b59f2bf33af6c4e
|
%compute new features based on existing ones
%
% derivatives from position 10 to 16
% standard deviation, based on winsize, position 17 to 23
% mean, based on winsize, position 24 to 30
%
% in final part, must uncomment the desired set, using only portions of
% the features computed, eliminating features with reduced contribution
% for example
%
%
% 3 velocity
% 4 lateral displacement
% 5 relative heading
% 6 angle 2 robot
% 7 distance
% 8 relative velocity x
% 9 relative velocity y
function new_features = enhance_features(input_features)
new_features = input_features;
% diff part
new_features(2:end,10) = diff(input_features(:,3));
new_features(2:end,11) = diff(input_features(:,4));
new_features(2:end,12) = diff(input_features(:,5));
new_features(2:end,13) = diff(input_features(:,6));
new_features(2:end,14) = diff(input_features(:,7));
new_features(2:end,15) = diff(input_features(:,8));
new_features(2:end,16) = diff(input_features(:,9));
new_features(1,10) = new_features(2,10);
new_features(1,11) = new_features(2,11);
new_features(1,12) = new_features(2,12);
new_features(1,13) = new_features(2,13);
new_features(1,14) = new_features(2,14);
new_features(1,15) = new_features(2,15);
new_features(1,16) = new_features(2,16);
% mean and stdv part
for i = 1:length(input_features)
winsize = 30;
while(i-winsize <= 0) %not enough past info
winsize = winsize - 1;
end
% stdv part
new_features(i,17) = std(input_features(i-winsize:i,3)); %std vel
new_features(i,18) = std(input_features(i-winsize:i,4)); %std lat. disp.
new_features(i,19) = std(input_features(i-winsize:i,5)); %std rel. head.
new_features(i,20) = std(input_features(i-winsize:i,6)); %std angle 2 robot
new_features(i,21) = std(input_features(i-winsize:i,7)); %std dist
new_features(i,22) = std(input_features(i-winsize:i,8)); %std rel v x
new_features(i,23) = std(input_features(i-winsize:i,8)); %std rel v y
% mean part
new_features(i,24) = mean(input_features(i-winsize:i,3)); %mean vel
new_features(i,25) = mean(input_features(i-winsize:i,4)); %mean lat. disp.
new_features(i,26) = mean(input_features(i-winsize:i,5)); %mean rel. head
new_features(i,27) = mean(input_features(i-winsize:i,6)); %mean angle 2 robot
new_features(i,28) = mean(input_features(i-winsize:i,7)); %mean dist
new_features(i,29) = mean(input_features(i-winsize:i,8)); %mean rel v x
new_features(i,30) = mean(input_features(i-winsize:i,9)); %mean rel v y
end
% %test single feature thresholds
% new_features = [new_features(:,1:2)...
% new_features(:,7)];
%test integration with opencv adaboost
% new_features = [new_features(:,1:2)...
% new_features(:,3:7)];
% %test vel, lat dist., dist
% new_features = [new_features(:,1:2)...
% new_features(:,3)...
% new_features(:,4)...
% new_features(:,7)...
% ];
% %reduced4 (lat. displ., dist., stdv distance)
% new_features = [new_features(:,1:2)...
% new_features(:,4)...
% new_features(:,7)...
% new_features(:,21)...
% ];
% %reduced3 ODNM (minus relvx, relvy, stdv ld, stdv dist)
% new_features = [new_features(:,1:2)...
% new_features(:,3:7)...
% ];
% %reduced3 (lat. displ., rel. heading, angle, dist. stdv distance)
% new_features = [new_features(:,1:2)...
% new_features(:,4:7)...
% new_features(:,21)...
% ];
%reduced2 == ODNM
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)...
% new_features(:,17)...
% new_features(:,21)...
% ];
% %reduced1 (no diff, no stdv rel_v_y)
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)...
% new_features(:,17:22)...
% ];
% %train complete
new_features = [new_features(:,1:2)...
new_features(:,3:9)...
new_features(:,10:16)...
new_features(:,17:23)...
];
% %train no diff
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)...
% new_features(:,17:23)...
% ];
%with mean
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)... %kf output
% new_features(:,10:16)... %diff
% new_features(:,17:23)... %stdv
% new_features(:,24:30)... %mean
% ];
%only one
% new_features = [new_features(:,1:2)...
% new_features(:,3)];
|
github
|
vitoruapt/lartkv5-master
|
new_features.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/new_features.m
| 263 |
utf_8
|
64fbb408c530fb0bd97e9027cb513024
|
%decompose relative velocity in x and y, compute lateral displacement
function [out]=new_features(in)
out = in;
[rel_vel_x rel_vel_y] = relative_velocities(in);
out(:,8) = rel_vel_x;
out(:,9) = rel_vel_y;
out(:,4) = sin(in(:,6)).*in(:,7); %put ld in place of rv
|
github
|
vitoruapt/lartkv5-master
|
crop_features.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/crop_features.m
| 1,981 |
utf_8
|
a3fc318bef5c147ab0e5fb5c62756f4f
|
%crop variable containing leader features
%so transitory measurments from beginning and
%end can be removed
%inputs:
%in_data : input data
%x1: inferior crop limit
%x2: superior crop limit
function [out_data] = crop_features(in_data,x1,x2)
% Show the data
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',1.5);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
hold on, grid on; title('Cropped Fatures');
set(gcf,'position',[200 200 800 300]);
[val1 ind1] = min(abs(in_data(:,1)-x1));
[val2 ind2] = min(abs(in_data(:,1)-x2));
top = max(max(in_data(:,3:9)));
bottom = min(min(in_data(:,3:9)));
patch([x1 x1 x2 x2],...
[bottom top top bottom],...
[0.7 0.7 0.7]);%,'faceAlpha',0.5);
plot(in_data(:,1),in_data(:,3),'bo');
plot(in_data(:,1),in_data(:,4),'co');
plot(in_data(:,1),in_data(:,5),'ko');
plot(in_data(:,1),in_data(:,6),'go');
plot(in_data(:,1),in_data(:,7),'yo');
plot(in_data(:,1),in_data(:,8),'mo');
plot(in_data(:,1),in_data(:,9),'o','color',[0.5 0 0]);
legend('vel','vel diff','head diff','angle', 'dist diff',...
'Location','eastOutside');
xlabel('t(s)');
axis tight;
out_data = in_data(ind1:ind2,:);
%large markers
ax1 = gca;
ax2 = axes('position',get(ax1,'position'));
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
plot(0,0,'color',[0.7 0.7 0.7],'linewidth',10,'parent',ax2);
%set(ax2,'position',get(ax1,'position'));
HL = legend(ax2,'velocity (m/s)','lateral disp. (m)',...
'relative head. (rad)','angle (rad)','distance (m)',...
'relative vel. x (m/s)','relative vel. y (m/s)','cropped region',...
'location','eastOutside');
set(HL,'position',[0.7650 0.35 0.23 0.37]);
set(ax2,'visible','off')
%axis(ax1, 'tight');
|
github
|
vitoruapt/lartkv5-master
|
do_tag.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/do_tag.m
| 1,227 |
utf_8
|
19d31561f6a92e6f273b5b9fa70294a9
|
%new tag and shift time
%as tests have different initial times, this function put all of them
%in the same reference frame. the offsets are computed based on the
%recorded images, because they have the correct time
%first the tags are obatined using rxbag, then the first image of each
%bag is compared wrt their clock stamp, the difference is the offset
%normally the problem that created this differences has been solved,
%and this would not be required for new bags and tests
function [new_var] = do_tag(input_var, pro_tag, rich_tag, jor_tag,offset,off_j)
%shift
i = diff(input_var(:,2))==1;
old_time = input_var(i,1);
if(isempty(old_time))
time_diff = pro_tag;
else
time_diff = pro_tag - old_time;
end
new_var = input_var;
new_var(:,1) = new_var(:,1) + time_diff;
%new tag rich
[val pos] = min(abs(new_var(:,1) - (rich_tag -offset)));
class_rich = zeros(length(input_var),1);
class_rich(pos:end)=1;
if(rich_tag==99)
class_rich(end)=0;
end
%new tag jor
[val pos] = min(abs(new_var(:,1) - (jor_tag -offset-off_j)));
class_jor = zeros(length(input_var),1);
class_jor(pos:end)=1;
if(rich_tag==99)
class_jor(end)=0;
end
new_var = [new_var(:,1:2) class_rich class_jor new_var(:,3:end)];
plot_test2(new_var);
|
github
|
vitoruapt/lartkv5-master
|
evaluate_model.m
|
.m
|
lartkv5-master/src/utils/human_leader/matlab/evaluate_model.m
| 5,501 |
utf_8
|
ecf0d85ca58f00874687aa0be33c94df
|
%evaluates adaboost classifier, comparing groundtruth
%with class output, may receive a single dataset or a structure of them,
%create plots comparing ground truth and classification, also prints error
%of false good, false bad and false total
function [] = evaluate_model(model,test_set)
if size(test_set,1)~=1
temp = test_set;
clear test_set;
test_set.set = temp;
test_set.name = 'single';
end
for number = 1:length(test_set)
test = test_set(number).set;
name = test_set(number).name;
%prepare the data
features = test(:,3:end);
test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test(:,2); %second column has leader tag [-1 good / 1 bad]
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
tic
% Classify the features with the trained model
if(isstruct(model))
%classic adaboost
test_class=adaboost('apply',features, model);
else
%matlab adaboost
test_class=predict(model, features);
end
toc
differences = test_class - gd_class;
false_bad = length(find(differences == 2));
false_good = length(find(differences == -2));
false_total = false_bad + false_good;
false_bad_ratio = false_bad / length(differences);
false_good_ratio = false_good / length(differences);
% error_ratio = false_total / length(differences);
false_bad_ratio = round(false_bad_ratio*100)/100;
false_good_ratio = round(false_good_ratio*100)/100;
error_ratio = false_bad_ratio + false_good_ratio;
% error_ratio = round(error_ratio*100)/100;
title_string = ...
sprintf('false good:%.2f, false bad:%.2f, total error:%.2f',...
false_good_ratio, false_bad_ratio, error_ratio);
%title_string = ['test:' name ' ' title_string];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% target plot %%%%%%%%%%%%%%%
bad_tag = test(gd_class == 1,1);
% Show the data
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',2);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
subplot(2,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'color',[0.5 0 0]);
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
axis tight; %axis equal
title(['test:' name ' ' 'ground truth']);
% large_markers;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Show result
bad_tag = test(test_class == 1,1);
% Show the data
subplot(2,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'color',[0.5 0 0]);
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
axis tight; %axis equal;
title(title_string);
% large_markers;
end
%set(gcf,'position',[200 200 800 400]);
score(length(test_class)-1)=0;
for i=1:length(test_class)
if test_class(i)==-1
vote = 0.01;
else
vote = -0.5;
end
score(i+1) = score(i) + vote;
if score(i+1) > 1
score(i+1) = 1;
elseif score(i+1) < -0.1
score(i+1) = -0.1;
end
end
X = figure; hold;
set(X,'position',[200 400 800 300]);
set(X,'defaultlinelinewidth',3);
set(X,'defaultaxeslinewidth',2);
set(X,'defaulttextfontsize',12);
set(X,'defaultaxesfontsize',12);
line([bad_tag bad_tag],[-0.1 1],'Color',[1 0 0.1]);
score = score(1:end-1);
sc = plot(time,score);
l1 = line([time(1) time(end)],[0 0],'Color',[1 0 0.1]);
l2 = line([time(1) time(end)],[0 0],'Color',[0 0 0]);
legend([l1, sc, l2],'bad leader','leader score','threshold',...
'location','eastoutside');
axis tight;
xlabel('time (s)'), ylabel('score');
end
function large_markers
tmp_l = legend('velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(tmp_l,'visible','off')
xlabel('t(s)');
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
%set(ax2,'position',get(ax1,'position'));
hL = legend(ax2,'velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(ax2,'visible','off')
axis(ax1, 'tight');
%set(gcf,'position',[200 200 800 400]);
end
|
github
|
vitoruapt/lartkv5-master
|
show_labels.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/show_labels.m
| 1,338 |
utf_8
|
ab280e637c4213c23d1ea1b9786aec23
|
%compare the labels created by the three evaluators with, also plotting the
%final tag, for illustrative purposes only.
%input must be xx files
function [] = plot_labels(test)
features = test(:,5:end);
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
% Create figure
F = figure('position',[360 260 900 600]);
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',1.5);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
%%%%%%%%%%% pro plot %%%%%%%%%%
gd_class = test(:,2);
bad_tag = test(gd_class == 1,1);
H = figure;
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);
%axis equal;
axis tight;
ax_x = get(H, 'xlim');
ax_y = get(H, 'ylim');
box on;
set(gca,'XTickLabel',[]);
%set(gca,'YTickLabel',[]);
ylabel('pro');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
github
|
vitoruapt/lartkv5-master
|
show_thresholds.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/show_thresholds.m
| 943 |
utf_8
|
7bdaa72b918d819190140d9908221b5d
|
%create linear variation of features to find what are the thresholds
%used by the classifier on each feature, receive as argument the classifier
%and the dimension to evaluate
function []=show_thresholds(model,dim)
clear new_model;
clear j; j=1; clear test_thresh;
% test_thresh = zeros(401,9);
test_thresh(:,1) = 1:401;
% second column is tag, does not matter here.
test_thresh(:,3) = -10:0.05:10; %1 velocity
% test_thresh(:,4) = -10:0.05:10; %2 lat disp.
% test_thresh(:,5) = -pi:0.0157:pi; %3 rel head.
% test_thresh(:,6) = -pi:0.0157:pi; %4 angle
% test_thresh(:,7) = -10:0.05:10; %5 dist
% test_thresh(:,8) = -10:0.05:10; %6 rel vx
% test_thresh(:,9) = -10:0.05:10; %7 rel vy
%
% test_thresh(:,10:23) = 0;
% for ii=10:23
% test_thresh(:,ii) = -10:0.05:10;
% end
for i=1:length(model)
if model(i).dimension == dim
new_model(j)=model(i);
j=j+1;
end
end
evaluate_model_single(new_model,test_thresh);
end
|
github
|
vitoruapt/lartkv5-master
|
compare_classifiers.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/compare_classifiers.m
| 3,391 |
utf_8
|
49da591a25df76b44b60c94c25ddbf32
|
% i think this was created to comparte an adaboost classificer with
% a neural network classifier
%test neural network
function [] = compare_classifiers(model,net,test)
%prepare the data
features = test(:,3:7);
input_val = features';
target_val = test(:,2)';
target_val(2,find(target_val == 0)) = 1; %for ann
test(test(:,2)==0,2)=-1; %for ada: transform from 0 to -1
gd_class = test(:,2); %second column has leader tag
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
%%%%%%%%%%%%% ANN Classifier %%%%%%%%%%
% Test the Network
outputs = net(input_val);
% binarize classification = good/bad
ann_class = round(outputs(2,:));
%diferences = abs(test_class - gd_class);
differences = abs(target_val(2,:) - ann_class);
error = length(find(differences == 1));
error_ratio = error / length(differences);
ann_string = ...
sprintf('NeuralNet Classification. error:%.2f',error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%% Adaboost Classifier %%%%%%%%%%
% Classify the features with the trained model
if(isstruct(model))
%classic adaboost
ada_class = adaboost('apply',features, model);
else
%matlab adaboost
ada_class = predict(model, features);
end
diferences = abs(ada_class - gd_class);
error = length(find(diferences == 2));
error_ratio = error / length(diferences);
ada_string = ...
sprintf('Adaboost Classification. error:%.2f',error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% groundtruth plot %%%%%%%%%%
bad_tag = test(gd_class == 1,1);
% Show groundtruth
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',2);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
set(H,'position',[740 110 550 550]);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
subplot(3,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
vel = plot(time,features(:,1),'b');
vld = plot(time,features(:,2),'m');
hdd = plot(time,features(:,3),'k');
ang = plot(time,features(:,4),'g');
dst = plot(time,features(:,5),'y');
l_handle = legend([vel, vld, hdd, ang, dst],...
'vel','vel diff','head diff','angle', 'distance');
set(l_handle,'orientation','horizontal',...
'Position',[0.12 0.0 0.8 0.05]);
axis tight;
set(gca,'XTickLabel',[]);
title('Ground Truth','FontWeight','bold');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% neural net plot %%%%%%%%%%%
bad_tag = test(ann_class == 0,1);
% Show classification
subplot(3,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b');
plot(time,features(:,2),'m');
plot(time,features(:,3),'k');
plot(time,features(:,4),'g');
plot(time,features(:,5),'y');
axis tight;
set(gca,'XTickLabel',[]);
title(ann_string,'FontWeight','bold');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% Adaboost plot %%%%%%%%%%%%%
bad_tag = test(ada_class == 1,1);
% Show classification
subplot(3,1,3), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b');
plot(time,features(:,2),'m');
plot(time,features(:,3),'k');
plot(time,features(:,4),'g');
plot(time,features(:,5),'y');
axis tight;
title(ada_string,'FontWeight','bold');
|
github
|
vitoruapt/lartkv5-master
|
train_net.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/train_net.m
| 907 |
utf_8
|
0d219bb6a1a146ccf798b6ec9b25b86f
|
%train neural network
% function [net] = train_net(inputs,targets)
function [net] = train_net(train_set,n_neurons)
inputs = train_set(:,3:end);
targets = train_set(:,2);
targets(targets==0,2)=1;
% Solve a Pattern Recognition Problem with a Neural Network
inputs = inputs';
targets = targets';
% Create a Pattern Recognition Network
hiddenLayerSize = n_neurons;%[10,10];
net = patternnet(hiddenLayerSize);
%net.performParam.regularization = 0.1;
% net.trainFcn = 'trainbr';
net.trainParam.max_fail = 100;
% Setup Division of Data for Training, Validation, Testing
%net.divideFcn = 'dividetrain'
net.divideFcn = 'divideind';
net.divideParam.testInd = [];
net.divideParam.trainInd = 1:8504;
net.divideParam.valInd = 8505:10196;
% net.divideparam.trainratio = 85/100;
% net.divideparam.valratio = 10/100;
% net.divideparam.testratio = 5/100;
% Train the Network
[net,tr] = train(net,inputs,targets);
|
github
|
vitoruapt/lartkv5-master
|
test_net.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/test_net.m
| 3,230 |
utf_8
|
8dc4a43efed1f2b19867805d622306f8
|
%test neural network
function [] = test_net(net,test_set)
for number = 1:length(test_set)
test = test_set(number).set;
name = test_set(number).name;
%prepare the data
features = test(:,3:end);
input_val = features';
target_val = test(:,2)';
target_val(2,target_val == 0) = 1;
gt_class = test(:,2); %second column has leader tag
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
% Test the Network
outputs = net(input_val);
%errors = gsubtract(y_val',outputs);
%performance = perform(net,y_val',outputs)
classes = round(outputs(2,:));
%classes = vec2ind(outputs) - 1;
%%%%% debug plot %%%%%%
% figure, hold;
% plot(target_val','o');
% plot(outputs(1,:),'k');
% plot(outputs(2,:),'r');
% plot(classes,'y');
%diferences = abs(test_class - gd_class);
% differences = abs(target_val(2,:)-classes);
% error = length(find(differences == 1));
% error_ratio = error / length(differences);
% title_string = ...
% sprintf('NeuralNet Classification. error:%.2f',error_ratio);
differences = classes - target_val(2,:);
false_bad = length(find(differences == -1));
false_good = length(find(differences == 1));
false_total = false_bad + false_good;
false_bad_ratio = false_bad / length(differences);
false_good_ratio = false_good / length(differences);
false_bad_ratio = round(false_bad_ratio*100)/100;
false_good_ratio = round(false_good_ratio*100)/100;
error_ratio = false_bad_ratio + false_good_ratio;
title_string = ...
sprintf('false good:%.2f, false bad:%.2f, total error:%.2f',...
false_good_ratio, false_bad_ratio, error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% groundtruth plot %%%%%%%%%%
bad_tag = test(gt_class == 1,1);
% Show groundtruth
figure;
subplot(2,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
%axis equal;
axis tight;
title(['test:' name ' ' 'ground truth']);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% classification plot %%%%%%%
bad_tag = test(classes == 0,1);
% Show classification
subplot(2,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
plot(time,outputs(1,:),'bo');
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
%axis equal;
axis tight;
title(title_string);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
end
|
github
|
vitoruapt/lartkv5-master
|
evaluate_model_single.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/evaluate_model_single.m
| 3,609 |
utf_8
|
b86fe2360a8aafd9d15d87f1c08468b1
|
%evaluates adaboost classifier, comparing groundtruth
%with class output, may receive a single dataset or a structure of them,
%create plots comparing ground truth and classification, also prints error
%of false good, false bad and false total
function [] = evaluate_model(model,test_set)
if size(test_set,1)~=1
temp = test_set;
clear test_set;
test_set.set = temp;
test_set.name = 'single';
end
for number = 1:length(test_set)
test = test_set(number).set;
name = test_set(number).name;
%prepare the data
features = test(:,3:end);
test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test(:,2); %second column has leader tag [-1 good / 1 bad]
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
tic
% Classify the features with the trained model
if(isstruct(model))
%classic adaboost
test_class=adaboost('apply',features, model);
else
%matlab adaboost
test_class=predict(model, features);
end
toc
differences = test_class - gd_class;
false_bad = length(find(differences == 2));
false_good = length(find(differences == -2));
false_total = false_bad + false_good;
false_bad_ratio = false_bad / length(differences);
false_good_ratio = false_good / length(differences);
false_bad_ratio = round(false_bad_ratio*100)/100;
false_good_ratio = round(false_good_ratio*100)/100;
error_ratio = false_bad_ratio + false_good_ratio;
title_string = ...
sprintf('false good:%.2f, false bad:%.2f, total error:%.2f',...
false_good_ratio, false_bad_ratio, error_ratio);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% target plot %%%%%%%%%%%%%%%
bad_tag = test(gd_class == 1,1);
% Show the data
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',2);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
subplot(2,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
axis tight; %axis equal
title(['test:' name ' ' 'ground truth']);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Show result
bad_tag = test(test_class == 1,1);
% Show the data
subplot(2,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
axis tight; %axis equal;
title(title_string);
end
end
function large_markers
tmp_l = legend('velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(tmp_l,'visible','off')
xlabel('t(s)');
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
%set(ax2,'position',get(ax1,'position'));
hL = legend(ax2,'velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(ax2,'visible','off')
axis(ax1, 'tight');
%set(gcf,'position',[200 200 800 400]);
end
|
github
|
vitoruapt/lartkv5-master
|
train_adaboost.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/train_adaboost.m
| 5,522 |
utf_8
|
2362578a48eadb03855f3d3a151234ea
|
%trains an adaboost classifier, input is training set, and iterations are
%the max number of weak classifiers allowed
function [classestimate,model,feat_of_wc] = train_adaboost(data,iterations)
%train adaboost classifier downloaded from internet
%features:
% 3: target velocity
% 4: lateral displacement (former relative velocity)
% 5: heading difference
% 6: angle between robot head and target pos
% 7: distance
% 8: relative velocity x
% 9: relative velocity y
datafeatures = data(:,3:end);
% data classification
data(data(:,2)==0,2)=-1; %transform from 0 to -1
dataclass = data(:,2); %second column has leader tag
% Use Adaboost to make a classifier
[classestimate,model]=adaboost('train',datafeatures,dataclass,iterations);
% Show the error verus number of weak classifiers
error=zeros(1,length(model));
feat_of_wc = zeros(1,length(model));
cont_ratio = zeros(1,size(datafeatures,2));
for i=1:length(model)
error(i)=model(i).error;
feature_id = model(i).dimension;
feat_of_wc(i) = feature_id;
cont_ratio(feature_id)=cont_ratio(feature_id)+model(i).alpha;
end
cont_ratio = cont_ratio./sum(cont_ratio);
fh1 = figure;
set(fh1,'defaultlinelinewidth',3);
set(fh1,'defaultaxeslinewidth',2);
set(fh1,'defaulttextfontsize',12);
set(fh1,'defaultaxesfontsize',12);
set(fh1,'position',[480 210 800 400]);
hold, title('Classification error versus number of weak classifiers');
plot(error);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
fh2 = figure;
set(fh2,'defaultlinelinewidth',3);
set(fh2,'defaultaxeslinewidth',2);
set(fh2,'defaulttextfontsize',12);
set(fh2,'defaultaxesfontsize',12);
set(fh2,'position',[ 679 106 600 400]);
hold, title('Features');
% [H,X] = hist(feat_of_wc,1:size(datafeatures,2));
[H,X] = hist(feat_of_wc,1:size(datafeatures,2));
a = [H;X]';
a(:,3) = a(:,1)/length(feat_of_wc);
sortrows(a)
cm = jet(length(X));
for i=1:length(X)
h=bar(X(i),H(i));
set(h,'facecolor',cm(i,:));
end
ylabel('weak classifiers');
set(gca,'XTickLabel',[]);
axis tight;
% legend('velocity',...
% 'lateral displacement',...
% 'relative heading',...
% 'angle','distance',...
% 'relative vel. x',...
% 'relative vel. y',...
% 'location','eastOutside');
legend('mean target vel.',...
'mean lat. displ.',...
'mean rel. head.',...
'mean angle',...
'mean distance',...
'mean relative vel. x',...
'mean relative vel. y',...
'Location','eastOutside')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
fh3 = figure;
set(fh3,'defaultlinelinewidth',3);
set(fh3,'defaultaxeslinewidth',2);
set(fh3,'defaulttextfontsize',12);
set(fh3,'defaultaxesfontsize',12);
set(fh3,'position',[ 679 106 600 400]);
hold,
title({'Features Contribution Ratio';...
sprintf('(number of weak classifiers = %i)',length(feat_of_wc))})
%X = 1:length(cont_ratio);
H = cont_ratio;
cm = jet(length(X));
for i=1:length(X)
h2=bar(X(i),H(i));
set(h2,'facecolor',cm(i,:));
end
ylabel('contribution ratio');
set(gca,'XTick',1:21);
set(gcf,'position',[250 100 1200 500]);
axis tight;
set(gca,'YLim',[0 0.25]);
grid;
legend('1. lateral displ.',...
'2. rel. heading',...
'3. angle',...
'4. distance',...
'5. stdv distance',...
'Location','eastOutside');
legend('1. target velocity',...
'2. lateral displ.',...
'3. rel. heading',...
'4. angle',...
'5. distance',...
'6. relative vel. x',...
'7. relative vel. y',...
'8. stdv target vel.',...
'9. stdv lateral displ.',...
'10. stdv rel. head.',...
'11. stdv angle',...
'12. stdv distance',...
'13. stdv relative vel. x',...
'Location','eastOutside');
% if (length(H)~=length(X))
% X = [1 round(X)]
% end
a = [H;X]';
sortrows(a)
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% legend('1. target velocity',...
% '2. lateral displ.',...
% '3. rel. heading',...
% '4. angle',...
% '5. distance',...
% '6. relative vel. x',...
% '7. relative vel. y',...
% '8. \Delta target vel.',...
% '9. \Delta lateral displ.',...
% '10. \Delta rel. head.',...
% '11. \Delta angle',...
% '12. \Delta distance',...
% '13. \Delta relative vel. x',...
% '14. \Delta relative vel. y',...
% '15. stdv target vel.',...
% '16. stdv lateral displ.',...
% '17. stdv rel. head.',...
% '18. stdv angle',...
% '19. stdv distance',...
% '20. stdv relative vel. x',...
% '21. stdv relative vel. y',...
% 'Location','eastOutside');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Training results
% Show results
% blue=datafeatures(classestimate==-1,:); red=datafeatures(classestimate==1,:);
% I=zeros(161,161);
% for i=1:length(model)
% if(model(i).dimension==1)
% if(model(i).direction==1), rec=[-80 -80 80+model(i).threshold 160];
% else rec=[model(i).threshold -80 80-model(i).threshold 160 ];
% end
% else
% if(model(i).direction==1), rec=[-80 -80 160 80+model(i).threshold];
% else rec=[-80 model(i).threshold 160 80-model(i).threshold];
% end
% end
% rec=round(rec);
% y=rec(1)+81:rec(1)+81+rec(3); x=rec(2)+81:rec(2)+81+rec(4);
% I=I-model(i).alpha; I(x,y)=I(x,y)+2*model(i).alpha;
% end
% subplot(2,2,2), imshow(I,[]); colorbar; axis xy;
% colormap('jet'), hold on
% plot(blue(:,1)+81,blue(:,2)+81,'bo');
% plot(red(:,1)+81,red(:,2)+81,'ro');
% title('Training Data classified with adaboost model');
|
github
|
vitoruapt/lartkv5-master
|
leader_features.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/leader_features.m
| 4,394 |
utf_8
|
c2c7a6b0afe6ec5c38886b61eda5b343
|
%extract features from chosen target and
%stores it in a matlab variable (proc_target)
%must pass as arguments the name of the file, generated by ROS
%log file from process_target, and the id of the desired subject
%function [robot,proc_target]=leader_features(file,target_id)
function [proc_target]=leader_features(file,target_id)
% input file format:
% 1: id
% 2: good/bad tag
% 3: time
% 4: pos x
% 5: pos y
% 6: vel
% 7: theta
% 8: pos diff
% 9: head diff
%10: angle 2 robot
%11: velocity diff
%printf("%d,%d,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f\n",
% target_id, badLeader, time_elapsed.toSec(),
% target_x, target_y, target_vel, target_theta,
% position_diff, heading_diff, angle_to_robot, velocity_diff);
% output file format:
% 1: time
% 2: good/bad tag
% 3: mean vel 1
% 4: mean vel diff 2
% 5: mean head diff 3
% 6: angle 2 robot 4
% 7: mean dist 2 robot 5
%initialize vars
begin_sweep = 1;
end_sweep = 1;
counter = 1;
mean_fig = figure; hold on; grid on;
%load and rearrange targets file
list = load(file);
range = max(list(:,1)) + 2;
cm = jet(range);
figure,hold; %axis square;
for i = 1:length(list);
if(list(i,1)==-1)
plot3(list(i,4),list(i,5),list(i,3),'bo');
% plot3(list(i,4),list(i,5),list(i,3),'o','color',cm((list(i,1)+2),:));
elseif(list(i,1)==target_id)
plot3(list(i,4),list(i,5),list(i,3),'ro');
end
end
%axis equal;
list = sortrows(list);
% separate target from robot
while counter < length(list)
while list(begin_sweep,1) == list(end_sweep,1)
end_sweep = end_sweep + 1;
counter = counter + 1;
if counter > length(list)
break
end
end
%only pick one target, according to input of function
switch list(begin_sweep,1)
case -1
robot = list(begin_sweep:end_sweep-1,:);
case target_id
target = list(begin_sweep:end_sweep-1,:);
end
begin_sweep = end_sweep;
end
% filter data
proc_target(length(target),7) = 0;
proc_target(:,1) = target(:,3);
proc_target(:,2) = target(:,2);
proc_target(:,6) = target(:,10); %angle 2 robot
proc_target(:,3) = target(:,6); %vel
proc_target(:,4) = target(:,11); %vel diff
proc_target(:,5) = target(:,9); %head diff
proc_target(:,6) = target(:,10); %angle 2 robot
proc_target(:,7) = target(:,8); %pos diff (dist)
% for i=1:length(target)
% winsize = 50;
% while(i-winsize <= 0) %not enough past info
% winsize = winsize - 1;
% end
% proc_target(i,3) = mean(target(i-winsize:i,6)); %vel
% proc_target(i,4) = mean(target(i-winsize:i,11)); %vel diff
% proc_target(i,5) = mean(target(i-winsize:i,9)); %head diff
% %proc_target(i,6) = mean(target(i-winsize:i,10)); %angle 2 robot
% proc_target(i,7) = mean(target(i-winsize:i,8)); %pos diff (dist)
% end
%%%%%%%%% PLOTTING %%%%%%%%%%%%
%removing angle jump
% robot(:,7) = unwrap(robot(:,7));
% robot(:,9) = unwrap(robot(:,9));
% robot(:,10) = unwrap(robot(:,10));
% target(:,7) = unwrap(target(:,7));
% target(:,9) = unwrap(target(:,9));
% target(:,10) = unwrap(target(:,10));
%proc_target(:,5) = unwrap(proc_target(:,5));
%proc_target(:,6) = unwrap(proc_target(:,6));
% if(max(proc_target(:,5)>pi))
% proc_target(:,5) = proc_target(:,5) - 2*pi;
% elseif(min(proc_target(:,5)<-pi))
% proc_target(:,5) = proc_target(:,5) + 2*pi;
% end
%plot good/bad leader index
tag = find(diff(proc_target(:,2)));
figure(mean_fig);
plot(proc_target(:,1),proc_target(:,3),'b-');
plot(proc_target(:,1),proc_target(:,4),'r-');
plot(proc_target(:,1),proc_target(:,5),'k-');
plot(proc_target(:,1),proc_target(:,6),'g-');
plot(proc_target(:,1),proc_target(:,7),'y-');
legend('vel','vel diff','head diff','angle', 'distance',...
'Location','NorthWest');
title('mean features from target 2 robot');
if ~isempty(tag)
line([proc_target(tag,1) proc_target(tag,1)],[0 5])
%plot(proc_target(tag,1),0:0.1:5);
end
%proc_target = crop_features(proc_target);
figure(mean_fig);
plot(proc_target(:,1),proc_target(:,3),'bo');
plot(proc_target(:,1),proc_target(:,4),'ro');
plot(proc_target(:,1),proc_target(:,5),'ko');
plot(proc_target(:,1),proc_target(:,6),'go');
plot(proc_target(:,1),proc_target(:,7),'yo');
legend('vel','vel diff','head diff','angle', 'distance',...
'Location','NorthWest');
|
github
|
vitoruapt/lartkv5-master
|
plot_labels.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/plot_labels.m
| 4,314 |
utf_8
|
ebee9d9693bb54f2e92624c850c4223d
|
%compare the labels created by the three evaluators with, also plotting the
%final tag, for illustrative purposes only.
function [] = plot_labels(test,final_tag)
features = test(:,5:end);
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
% Create figure
F = figure('position',[360 260 900 600]);
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',1.5);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
%%%%%%%%%%% pro plot %%%%%%%%%%
gd_class = test(:,2);
bad_tag = test(gd_class == 1,1);
H = subplot(3,1,1,'position',[0.065 0.70 0.70 0.20]);
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);
%axis equal;
axis tight;
ax_x = get(H, 'xlim');
ax_y = get(H, 'ylim');
box on;
set(gca,'XTickLabel',[]);
%set(gca,'YTickLabel',[]);
ylabel('pro');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%% rich plot %%%%%%%%%%
gd_class = test(:,3); %rich tag
bad_tag = test(gd_class == 1,1);
% Show the data
I = subplot(3,1,2,'position',[0.065 0.4125 0.70 0.20]);
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);
%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
set(gca,'XTickLabel',[]);
box on;
%set(gca,'YTickLabel',[]);
ylabel('rich');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%% jor plot %%%%%%%%%%
gd_class = test(:,4); %jorge_tag
bad_tag = test(gd_class == 1,1);
% Show the data
I = subplot(3,1,3,'position',[0.065 0.1250 0.70 0.20]);
hold on, grid on;
if ~isempty(bad_tag)
left = bad_tag(1);
right = bad_tag(end);
top = up_plot;
bottom = low_plot;
patch([left left right right],...
[bottom top top bottom],...
[0.7 0.7 0.7],...
'FaceAlpha',0.5);
line([final_tag final_tag],...
[bottom top],...
'color',[1 0 0]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'.','color',[0.7 0 0]);%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
box on;
xlabel('t(s)');
%set(gca,'YTickLabel',[]);
ylabel('jor');
large_markers
%%%%%%%%%%%%%%%%%%%%%%%%%%%
p_tag = test(diff(test(:,2))==1,1);
r_tag = test(diff(test(:,3))==1,1);
j_tag = test(diff(test(:,4))==1,1);
[p_tag r_tag j_tag]
%%%%%%%%%%%%%%%%%%%%%%%%
end
function large_markers
xlabel('t(s)');
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
plot(0,0,'color',[0.7 0.7 0.7],'linewidth',10,'parent',ax2);
% hL = legend(ax2,'velocity','rel velocity',...
% 'rel heading','angle','distance','bad leader region',...
% 'final tag',...
% 'location','eastOutside');
hL = legend(ax2,'velocity (m/s)','lateral disp. (m)',...
'relative head. (rad)','angle (rad)','distance (m)',...
'relative vel. x (m/s)','relative vel. y (m/s)','cropped region',...
'location','eastOutside');
set(hL,'position', [0.80 0.35 0.15 0.30]);
set(ax2,'visible','off')
axis(ax1, 'tight');
end
|
github
|
vitoruapt/lartkv5-master
|
plot_test2.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/plot_test2.m
| 2,313 |
utf_8
|
968d8618023c1cc38d47190720487c42
|
%used in do_tag to show comparison between labels
function [] = plot_test2(test_a)
features = test_a(:,5:end);
%test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test_a(:,2); %second column has leader tag
low_plot = min(min(features));
up_plot = max(max(features));
time = test_a(:,1);
bad_tag = test_a(gd_class == 1,1);
% Show the data
F = figure;
set(F,'defaultlinelinewidth',3);
set(F,'defaultaxeslinewidth',2);
set(F,'defaulttextfontsize',12);
set(F,'defaultaxesfontsize',12);
H = subplot(3,1,1); hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[0.5 0.5 0.5]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
%axis equal;
axis tight;
ax_x = get(H, 'xlim');
ax_y = get(H, 'ylim');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
features = test_a(:,5:end);
%test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test_a(:,3); %rich tag
low_plot = min(min(features));
up_plot = max(max(features));
time = test_a(:,1);
bad_tag = test_a(gd_class == 1,1);
% Show the data
I = subplot(3,1,2); hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[0.5 0.5 0.5]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
features = test_a(:,5:end);
%test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test_a(:,4); %jorge_tag
low_plot = min(min(features));
up_plot = max(max(features));
time = test_a(:,1);
bad_tag = test_a(gd_class == 1,1);
% Show the data
I = subplot(3,1,3); hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[0.5 0.5 0.5]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'m.');
plot(time,features(:,3),'k.');
plot(time,features(:,4),'g.');
plot(time,features(:,5),'y.');
%axis equal;
axis tight;
set(I,'xlim',ax_x);
set(I,'ylim',ax_y);
xlabel('t(s)');
%%%%%%%%%%%%%%%%%%%%%%%%%%%
p_tag = test_a(diff(test_a(:,2))==1,1);
r_tag = test_a(diff(test_a(:,3))==1,1);
j_tag = test_a(diff(test_a(:,4))==1,1);
[p_tag r_tag j_tag]
|
github
|
vitoruapt/lartkv5-master
|
enhance_features.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/enhance_features.m
| 4,253 |
utf_8
|
891a77b7a8827b581b59f2bf33af6c4e
|
%compute new features based on existing ones
%
% derivatives from position 10 to 16
% standard deviation, based on winsize, position 17 to 23
% mean, based on winsize, position 24 to 30
%
% in final part, must uncomment the desired set, using only portions of
% the features computed, eliminating features with reduced contribution
% for example
%
%
% 3 velocity
% 4 lateral displacement
% 5 relative heading
% 6 angle 2 robot
% 7 distance
% 8 relative velocity x
% 9 relative velocity y
function new_features = enhance_features(input_features)
new_features = input_features;
% diff part
new_features(2:end,10) = diff(input_features(:,3));
new_features(2:end,11) = diff(input_features(:,4));
new_features(2:end,12) = diff(input_features(:,5));
new_features(2:end,13) = diff(input_features(:,6));
new_features(2:end,14) = diff(input_features(:,7));
new_features(2:end,15) = diff(input_features(:,8));
new_features(2:end,16) = diff(input_features(:,9));
new_features(1,10) = new_features(2,10);
new_features(1,11) = new_features(2,11);
new_features(1,12) = new_features(2,12);
new_features(1,13) = new_features(2,13);
new_features(1,14) = new_features(2,14);
new_features(1,15) = new_features(2,15);
new_features(1,16) = new_features(2,16);
% mean and stdv part
for i = 1:length(input_features)
winsize = 30;
while(i-winsize <= 0) %not enough past info
winsize = winsize - 1;
end
% stdv part
new_features(i,17) = std(input_features(i-winsize:i,3)); %std vel
new_features(i,18) = std(input_features(i-winsize:i,4)); %std lat. disp.
new_features(i,19) = std(input_features(i-winsize:i,5)); %std rel. head.
new_features(i,20) = std(input_features(i-winsize:i,6)); %std angle 2 robot
new_features(i,21) = std(input_features(i-winsize:i,7)); %std dist
new_features(i,22) = std(input_features(i-winsize:i,8)); %std rel v x
new_features(i,23) = std(input_features(i-winsize:i,8)); %std rel v y
% mean part
new_features(i,24) = mean(input_features(i-winsize:i,3)); %mean vel
new_features(i,25) = mean(input_features(i-winsize:i,4)); %mean lat. disp.
new_features(i,26) = mean(input_features(i-winsize:i,5)); %mean rel. head
new_features(i,27) = mean(input_features(i-winsize:i,6)); %mean angle 2 robot
new_features(i,28) = mean(input_features(i-winsize:i,7)); %mean dist
new_features(i,29) = mean(input_features(i-winsize:i,8)); %mean rel v x
new_features(i,30) = mean(input_features(i-winsize:i,9)); %mean rel v y
end
% %test single feature thresholds
% new_features = [new_features(:,1:2)...
% new_features(:,7)];
%test integration with opencv adaboost
% new_features = [new_features(:,1:2)...
% new_features(:,3:7)];
% %test vel, lat dist., dist
% new_features = [new_features(:,1:2)...
% new_features(:,3)...
% new_features(:,4)...
% new_features(:,7)...
% ];
% %reduced4 (lat. displ., dist., stdv distance)
% new_features = [new_features(:,1:2)...
% new_features(:,4)...
% new_features(:,7)...
% new_features(:,21)...
% ];
% %reduced3 ODNM (minus relvx, relvy, stdv ld, stdv dist)
% new_features = [new_features(:,1:2)...
% new_features(:,3:7)...
% ];
% %reduced3 (lat. displ., rel. heading, angle, dist. stdv distance)
% new_features = [new_features(:,1:2)...
% new_features(:,4:7)...
% new_features(:,21)...
% ];
%reduced2 == ODNM
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)...
% new_features(:,17)...
% new_features(:,21)...
% ];
% %reduced1 (no diff, no stdv rel_v_y)
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)...
% new_features(:,17:22)...
% ];
% %train complete
new_features = [new_features(:,1:2)...
new_features(:,3:9)...
new_features(:,10:16)...
new_features(:,17:23)...
];
% %train no diff
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)...
% new_features(:,17:23)...
% ];
%with mean
% new_features = [new_features(:,1:2)...
% new_features(:,3:9)... %kf output
% new_features(:,10:16)... %diff
% new_features(:,17:23)... %stdv
% new_features(:,24:30)... %mean
% ];
%only one
% new_features = [new_features(:,1:2)...
% new_features(:,3)];
|
github
|
vitoruapt/lartkv5-master
|
new_features.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/new_features.m
| 263 |
utf_8
|
64fbb408c530fb0bd97e9027cb513024
|
%decompose relative velocity in x and y, compute lateral displacement
function [out]=new_features(in)
out = in;
[rel_vel_x rel_vel_y] = relative_velocities(in);
out(:,8) = rel_vel_x;
out(:,9) = rel_vel_y;
out(:,4) = sin(in(:,6)).*in(:,7); %put ld in place of rv
|
github
|
vitoruapt/lartkv5-master
|
crop_features.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/crop_features.m
| 1,981 |
utf_8
|
a3fc318bef5c147ab0e5fb5c62756f4f
|
%crop variable containing leader features
%so transitory measurments from beginning and
%end can be removed
%inputs:
%in_data : input data
%x1: inferior crop limit
%x2: superior crop limit
function [out_data] = crop_features(in_data,x1,x2)
% Show the data
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',1.5);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
hold on, grid on; title('Cropped Fatures');
set(gcf,'position',[200 200 800 300]);
[val1 ind1] = min(abs(in_data(:,1)-x1));
[val2 ind2] = min(abs(in_data(:,1)-x2));
top = max(max(in_data(:,3:9)));
bottom = min(min(in_data(:,3:9)));
patch([x1 x1 x2 x2],...
[bottom top top bottom],...
[0.7 0.7 0.7]);%,'faceAlpha',0.5);
plot(in_data(:,1),in_data(:,3),'bo');
plot(in_data(:,1),in_data(:,4),'co');
plot(in_data(:,1),in_data(:,5),'ko');
plot(in_data(:,1),in_data(:,6),'go');
plot(in_data(:,1),in_data(:,7),'yo');
plot(in_data(:,1),in_data(:,8),'mo');
plot(in_data(:,1),in_data(:,9),'o','color',[0.5 0 0]);
legend('vel','vel diff','head diff','angle', 'dist diff',...
'Location','eastOutside');
xlabel('t(s)');
axis tight;
out_data = in_data(ind1:ind2,:);
%large markers
ax1 = gca;
ax2 = axes('position',get(ax1,'position'));
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
plot(0,0,'color',[0.7 0.7 0.7],'linewidth',10,'parent',ax2);
%set(ax2,'position',get(ax1,'position'));
HL = legend(ax2,'velocity (m/s)','lateral disp. (m)',...
'relative head. (rad)','angle (rad)','distance (m)',...
'relative vel. x (m/s)','relative vel. y (m/s)','cropped region',...
'location','eastOutside');
set(HL,'position',[0.7650 0.35 0.23 0.37]);
set(ax2,'visible','off')
%axis(ax1, 'tight');
|
github
|
vitoruapt/lartkv5-master
|
evaluate_model.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/evaluate_model.m
| 5,501 |
utf_8
|
ecf0d85ca58f00874687aa0be33c94df
|
%evaluates adaboost classifier, comparing groundtruth
%with class output, may receive a single dataset or a structure of them,
%create plots comparing ground truth and classification, also prints error
%of false good, false bad and false total
function [] = evaluate_model(model,test_set)
if size(test_set,1)~=1
temp = test_set;
clear test_set;
test_set.set = temp;
test_set.name = 'single';
end
for number = 1:length(test_set)
test = test_set(number).set;
name = test_set(number).name;
%prepare the data
features = test(:,3:end);
test(test(:,2)==0,2)=-1; %transform from 0 to -1
gd_class = test(:,2); %second column has leader tag [-1 good / 1 bad]
%for plot purposes
low_plot = min(min(features));
up_plot = max(max(features));
time = test(:,1);
tic
% Classify the features with the trained model
if(isstruct(model))
%classic adaboost
test_class=adaboost('apply',features, model);
else
%matlab adaboost
test_class=predict(model, features);
end
toc
differences = test_class - gd_class;
false_bad = length(find(differences == 2));
false_good = length(find(differences == -2));
false_total = false_bad + false_good;
false_bad_ratio = false_bad / length(differences);
false_good_ratio = false_good / length(differences);
% error_ratio = false_total / length(differences);
false_bad_ratio = round(false_bad_ratio*100)/100;
false_good_ratio = round(false_good_ratio*100)/100;
error_ratio = false_bad_ratio + false_good_ratio;
% error_ratio = round(error_ratio*100)/100;
title_string = ...
sprintf('false good:%.2f, false bad:%.2f, total error:%.2f',...
false_good_ratio, false_bad_ratio, error_ratio);
%title_string = ['test:' name ' ' title_string];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% target plot %%%%%%%%%%%%%%%
bad_tag = test(gd_class == 1,1);
% Show the data
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',2);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
subplot(2,1,1), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'color',[0.5 0 0]);
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
axis tight; %axis equal
title(['test:' name ' ' 'ground truth']);
% large_markers;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Show result
bad_tag = test(test_class == 1,1);
% Show the data
subplot(2,1,2), hold on, grid on;
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
plot(time,features(:,1),'b.');
plot(time,features(:,2),'c.');
plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
% plot(time,features(:,6),'m.');
% plot(time,features(:,7),'color',[0.5 0 0]);
%legend('vel','vel diff','head diff','angle', 'distance',...
% 'Location','NorthWest');
axis tight; %axis equal;
title(title_string);
% large_markers;
end
%set(gcf,'position',[200 200 800 400]);
score(length(test_class)-1)=0;
for i=1:length(test_class)
if test_class(i)==-1
vote = 0.01;
else
vote = -0.5;
end
score(i+1) = score(i) + vote;
if score(i+1) > 1
score(i+1) = 1;
elseif score(i+1) < -0.1
score(i+1) = -0.1;
end
end
X = figure; hold;
set(X,'position',[200 400 800 300]);
set(X,'defaultlinelinewidth',3);
set(X,'defaultaxeslinewidth',2);
set(X,'defaulttextfontsize',12);
set(X,'defaultaxesfontsize',12);
line([bad_tag bad_tag],[-0.1 1],'Color',[1 0 0.1]);
score = score(1:end-1);
sc = plot(time,score);
l1 = line([time(1) time(end)],[0 0],'Color',[1 0 0.1]);
l2 = line([time(1) time(end)],[0 0],'Color',[0 0 0]);
legend([l1, sc, l2],'bad leader','leader score','threshold',...
'location','eastoutside');
axis tight;
xlabel('time (s)'), ylabel('score');
end
function large_markers
tmp_l = legend('velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(tmp_l,'visible','off')
xlabel('t(s)');
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
%set(ax2,'position',get(ax1,'position'));
hL = legend(ax2,'velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(ax2,'visible','off')
axis(ax1, 'tight');
%set(gcf,'position',[200 200 800 400]);
end
|
github
|
vitoruapt/lartkv5-master
|
ros_interface.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/old/ros_interface.m
| 1,701 |
utf_8
|
84fa1bd62878c2e5189bebed40138987
|
%interface with ros, receives a feature message and
%apply classifier, then outputs a new message with
%the classification
function []=ros_subscriber(model)
% create a publisher for a geometry_msgs/Pose message
pub_process = geometry_msgs_Pose(...
'connect','publisher','subscribe_to_matlab','pose');
% create a subscriber for a geometry_msgs/Twist message
sub_process = geometry_msgs_PoseWithCovariance(...
'connect','subscriber','publish_to_matlab','PoseWithCovariance');
% create an empty messages structure
out_msg = geometry_msgs_Pose('empty');
in_msg = geometry_msgs_PoseWithCovariance('empty');
% read a message and print to screen
while (1)
in_msg = geometry_msgs_PoseWithCovariance('read', sub_process, 100);
if ~isempty(in_msg)
tic
%info is being passed in the covariance struct
x_pos = in_msg.pose.position.x;
y_pos = in_msg.pose.position.y;
id = in_msg.pose.position.z;
sample = [in_msg.covariance(1) ...
in_msg.covariance(2) ...
in_msg.covariance(3) ...
in_msg.covariance(4) ...
in_msg.covariance(5)];
if(isstruct(model))
%to be used with classic adaboost
%quality = ada_classify(sample,model);
quality = adaboost('apply', sample, model);
else
%to be used with adaboost from matlab
quality = predict(model,sample);
end
out_msg.position.x = x_pos;
out_msg.position.y = y_pos;
out_msg.position.z = quality;
out_msg.orientation.x = id;
geometry_msgs_Pose('send', pub_process, out_msg);
toc
end
end
|
github
|
vitoruapt/lartkv5-master
|
plot_test.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/old/plot_test.m
| 2,514 |
utf_8
|
4802dbf48aec6bab59fcfc490193758f
|
%compares pro tag before and after shift,
function [] = plot_test(test_set)
features = test_set(:,3:end);
good_tag = test_set(:,2); %second column has leader tag
bad_tag = test_set(good_tag == 1,1);
low_plot = min(min(features));
up_plot = max(max(features));
time = test_set(:,1);
% Show the data
H = figure;
set(H,'defaultlinelinewidth',3);
set(H,'defaultaxeslinewidth',2);
set(H,'defaulttextfontsize',12);
set(H,'defaultaxesfontsize',12);
hold on, grid on; title('Features over time');
if ~isempty(bad_tag)
line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
end
v = plot(time,features(:,1),'b.'); %velocity
ld = plot(time,features(:,2),'c.'); %lateral displacement
rh = plot(time,features(:,3),'k.'); %heading diff
a = plot(time,features(:,4),'g.'); %angle to robot
d = plot(time,features(:,5),'y.'); %distance
rv_x = plot(time,-features(:,6),'m.'); %relative velocity x
rv_y = plot(time,features(:,7),'color',[0.5 0 0]); %relative velocity y
legend([v,ld,rh,a,d,rv_x,rv_y],'velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
xlabel('t(s)');
%large markers
ax1 = gca;
ax2 = axes;
hold;
plot(0,0,'b','linewidth',10,'parent',ax2);
plot(0,0,'c','linewidth',10,'parent',ax2);
plot(0,0,'k','linewidth',10,'parent',ax2);
plot(0,0,'g','linewidth',10,'parent',ax2);
plot(0,0,'y','linewidth',10,'parent',ax2);
plot(0,0,'m','linewidth',10,'parent',ax2);
plot(0,0,'color',[0.5 0 0],'linewidth',10,'parent',ax2);
%set(ax2,'position',get(ax1,'position'));
legend(ax2,'velocity','lateral displacement',...
'relative heading','angle','distance',...
'relative vel. x','relative vel. y',...
'location','eastOutside');
set(ax2,'visible','off')
axis(ax1, 'tight');
set(gcf,'position',[200 200 800 400]);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% features = test_b(:,5:end);
% %test(test(:,2)==0,2)=-1; %transform from 0 to -1
% gd_class = test_b(:,2); %rich tag
% low_plot = min(min(features));
% up_plot = max(max(features));
% time = test_b(:,1);
%
% bad_tag = test_b(gd_class == 1,1);
%
% % Show the data
% I = subplot(2,1,2); hold on, grid on;
% if ~isempty(bad_tag)
% line([bad_tag bad_tag],[low_plot up_plot],'Color',[1 0 0.1]);
% end
% plot(time,features(:,1),'b.');
% plot(time,features(:,2),'m.');
% plot(time,features(:,3),'k.');
% plot(time,features(:,4),'g.');
% plot(time,features(:,5),'y.');
% %axis equal;
% axis tight;
% %set(I,'xlim',ax_x);
% set(I,'ylim',ax_y);
|
github
|
vitoruapt/lartkv5-master
|
test_ensemble.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/old/test_ensemble.m
| 219 |
utf_8
|
2057f682ef3cecaa6ab5d76aa489ef52
|
%test different 4 situations with classifier
function [] = test_ensemble(model,stopped,good,aside,far)
evaluate_model(model,stopped);
evaluate_model(model,good);
evaluate_model(model,aside);
evaluate_model(model,far);
|
github
|
vitoruapt/lartkv5-master
|
ros_ann.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/old/ros_ann.m
| 1,651 |
utf_8
|
87dfddc5f632bdf0e31bf7bf52a2a6bc
|
%interface with ros, receives a feature message and
%apply classifier, then outputs a new message with
%the classification
function []=ros_subscriber(model)
% create a publisher for a geometry_msgs/Pose message
pub_process = geometry_msgs_Pose(...
'connect','publisher','subscribe_to_matlab','pose');
% create a subscriber for a geometry_msgs/Twist message
sub_process = geometry_msgs_PoseWithCovariance(...
'connect','subscriber','publish_to_matlab','PoseWithCovariance');
% create an empty messages structure
out_msg = geometry_msgs_Pose('empty');
in_msg = geometry_msgs_PoseWithCovariance('empty');
% read a message and print to screen
while (1)
in_msg = geometry_msgs_PoseWithCovariance('read', sub_process, 100);
if ~isempty(in_msg)
%info is being passed in the covariance struct
x_pos = in_msg.pose.position.x;
y_pos = in_msg.pose.position.y;
id = in_msg.pose.position.z;
sample = [in_msg.covariance(1) ...
in_msg.covariance(2) ...
in_msg.covariance(3) ...
in_msg.covariance(4) ...
in_msg.covariance(5)];
quality = model(sample');
%round to 1 or 0
quality = round(quality(2,:));
%ros expects -1 good / 1 bad
switch quality
case 1
quality = -1;
case 0
quality = 1;
end
out_msg.position.x = x_pos;
out_msg.position.y = y_pos;
out_msg.position.z = quality;
out_msg.orientation.x = id;
geometry_msgs_Pose('send', pub_process, out_msg);
end
end
|
github
|
vitoruapt/lartkv5-master
|
do_transition.m
|
.m
|
lartkv5-master/src/utils/process_target/matlab/old/do_transition.m
| 245 |
utf_8
|
9c9e7c379455091aff623a8171bc64f3
|
%back tagging, never used
function out = do_transition(in)
out = in;
tag_i = find(diff(in(:,2))==1);
timestep = mean(diff(in(:,1)));
window = 1;
steps = round(window/timestep);
trans_i = tag_i - steps;
out(:,2)=0;
out(trans_i:tag_i,2)=1;
end
|
github
|
vitoruapt/lartkv5-master
|
pdftops.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/pdftops.m
| 3,077 |
utf_8
|
8dff856e4b450072050d8aa571d1a08e
|
function varargout = pdftops(cmd)
%PDFTOPS Calls a local pdftops executable with the input command
%
% Example:
% [status result] = pdftops(cmd)
%
% Attempts to locate a pdftops executable, finally asking the user to
% specify the directory pdftops was installed into. The resulting path is
% stored for future reference.
%
% Once found, the executable is called with the input command string.
%
% This function requires that you have pdftops (from the Xpdf package)
% installed on your system. You can download this from:
% http://www.foolabs.com/xpdf
%
% IN:
% cmd - Command string to be passed into pdftops.
%
% OUT:
% status - 0 iff command ran without problem.
% result - Output from pdftops.
% Copyright: Oliver Woodford, 2009-2010
% Thanks to Jonas Dorn for the fix for the title of the uigetdir window on
% Mac OS.
% Thanks to Christoph Hertel for pointing out a bug in check_xpdf_path
% under linux.
% 23/01/2014 - Add full path to pdftops.txt in warning.
% Call pdftops
[varargout{1:nargout}] = system(sprintf('"%s" %s', xpdf_path, cmd));
end
function path_ = xpdf_path
% Return a valid path
% Start with the currently set path
path_ = user_string('pdftops');
% Check the path works
if check_xpdf_path(path_)
return
end
% Check whether the binary is on the path
if ispc
bin = 'pdftops.exe';
else
bin = 'pdftops';
end
if check_store_xpdf_path(bin)
path_ = bin;
return
end
% Search the obvious places
if ispc
path_ = 'C:\Program Files\xpdf\pdftops.exe';
else
path_ = '/usr/local/bin/pdftops';
end
if check_store_xpdf_path(path_)
return
end
% Ask the user to enter the path
while 1
if strncmp(computer,'MAC',3) % Is a Mac
% Give separate warning as the uigetdir dialogue box doesn't have a
% title
uiwait(warndlg('Pdftops not found. Please locate the program, or install xpdf-tools from http://users.phg-online.de/tk/MOSXS/.'))
end
base = uigetdir('/', 'Pdftops not found. Please locate the program.');
if isequal(base, 0)
% User hit cancel or closed window
break;
end
base = [base filesep];
bin_dir = {'', ['bin' filesep], ['lib' filesep]};
for a = 1:numel(bin_dir)
path_ = [base bin_dir{a} bin];
if exist(path_, 'file') == 2
break;
end
end
if check_store_xpdf_path(path_)
return
end
end
error('pdftops executable not found.');
end
function good = check_store_xpdf_path(path_)
% Check the path is valid
good = check_xpdf_path(path_);
if ~good
return
end
% Update the current default path to the path found
if ~user_string('pdftops', path_)
warning('Path to pdftops executable could not be saved. Enter it manually in %s.', fullfile(fileparts(which('user_string.m')), '.ignore', 'pdftops.txt'));
return
end
end
function good = check_xpdf_path(path_)
% Check the path is valid
[good, message] = system(sprintf('"%s" -h', path_));
% system returns good = 1 even when the command runs
% Look for something distinct in the help text
good = ~isempty(strfind(message, 'PostScript'));
end
|
github
|
vitoruapt/lartkv5-master
|
crop_borders.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/crop_borders.m
| 1,669 |
utf_8
|
725f526e7270a9b417300035d8748a9c
|
%CROP_BORDERS Crop the borders of an image or stack of images
%
% [B, v] = crop_borders(A, bcol, [padding])
%
%IN:
% A - HxWxCxN stack of images.
% bcol - Cx1 background colour vector.
% padding - scalar indicating how many pixels padding to have. Default: 0.
%
%OUT:
% B - JxKxCxN cropped stack of images.
% v - 1x4 vector of start and end indices for first two dimensions, s.t.
% B = A(v(1):v(2),v(3):v(4),:,:).
function [A, v] = crop_borders(A, bcol, padding)
if nargin < 3
padding = 0;
end
[h, w, c, n] = size(A);
if isscalar(bcol)
bcol = bcol(ones(c, 1));
end
bail = false;
for l = 1:w
for a = 1:c
if ~all(col(A(:,l,a,:)) == bcol(a))
bail = true;
break;
end
end
if bail
break;
end
end
bcol = A(ceil(end/2),w,:,1);
bail = false;
for r = w:-1:l
for a = 1:c
if ~all(col(A(:,r,a,:)) == bcol(a))
bail = true;
break;
end
end
if bail
break;
end
end
bcol = A(1,ceil(end/2),:,1);
bail = false;
for t = 1:h
for a = 1:c
if ~all(col(A(t,:,a,:)) == bcol(a))
bail = true;
break;
end
end
if bail
break;
end
end
bcol = A(h,ceil(end/2),:,1);
bail = false;
for b = h:-1:t
for a = 1:c
if ~all(col(A(b,:,a,:)) == bcol(a))
bail = true;
break;
end
end
if bail
break;
end
end
% Crop the background, leaving one boundary pixel to avoid bleeding on resize
v = [max(t-padding, 1) min(b+padding, h) max(l-padding, 1) min(r+padding, w)];
A = A(v(1):v(2),v(3):v(4),:,:);
end
function A = col(A)
A = A(:);
end
|
github
|
vitoruapt/lartkv5-master
|
isolate_axes.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/isolate_axes.m
| 3,668 |
utf_8
|
e2dce471e433886fcb87f9dcb284a2cb
|
%ISOLATE_AXES Isolate the specified axes in a figure on their own
%
% Examples:
% fh = isolate_axes(ah)
% fh = isolate_axes(ah, vis)
%
% This function will create a new figure containing the axes/uipanels
% specified, and also their associated legends and colorbars. The objects
% specified must all be in the same figure, but they will generally only be
% a subset of the objects in the figure.
%
% IN:
% ah - An array of axes and uipanel handles, which must come from the
% same figure.
% vis - A boolean indicating whether the new figure should be visible.
% Default: false.
%
% OUT:
% fh - The handle of the created figure.
% Copyright (C) Oliver Woodford 2011-2013
% Thank you to Rosella Blatt for reporting a bug to do with axes in GUIs
% 16/3/2012 Moved copyfig to its own function. Thanks to Bob Fratantonio
% for pointing out that the function is also used in export_fig.m.
% 12/12/12 - Add support for isolating uipanels. Thanks to michael for
% suggesting it.
% 08/10/13 - Bug fix to allchildren suggested by Will Grant (many thanks!).
% 05/12/13 - Bug fix to axes having different units. Thanks to Remington
% Reid for reporting the issue.
function fh = isolate_axes(ah, vis)
% Make sure we have an array of handles
if ~all(ishandle(ah))
error('ah must be an array of handles');
end
% Check that the handles are all for axes or uipanels, and are all in the same figure
fh = ancestor(ah(1), 'figure');
nAx = numel(ah);
for a = 1:nAx
if ~ismember(get(ah(a), 'Type'), {'axes', 'uipanel'})
error('All handles must be axes or uipanel handles.');
end
if ~isequal(ancestor(ah(a), 'figure'), fh)
error('Axes must all come from the same figure.');
end
end
% Tag the objects so we can find them in the copy
old_tag = get(ah, 'Tag');
if nAx == 1
old_tag = {old_tag};
end
set(ah, 'Tag', 'ObjectToCopy');
% Create a new figure exactly the same as the old one
fh = copyfig(fh); %copyobj(fh, 0);
if nargin < 2 || ~vis
set(fh, 'Visible', 'off');
end
% Reset the object tags
for a = 1:nAx
set(ah(a), 'Tag', old_tag{a});
end
% Find the objects to save
ah = findall(fh, 'Tag', 'ObjectToCopy');
if numel(ah) ~= nAx
close(fh);
error('Incorrect number of objects found.');
end
% Set the axes tags to what they should be
for a = 1:nAx
set(ah(a), 'Tag', old_tag{a});
end
% Keep any legends and colorbars which overlap the subplots
lh = findall(fh, 'Type', 'axes', '-and', {'Tag', 'legend', '-or', 'Tag', 'Colorbar'});
nLeg = numel(lh);
if nLeg > 0
set([ah(:); lh(:)], 'Units', 'normalized');
ax_pos = get(ah, 'OuterPosition');
if nAx > 1
ax_pos = cell2mat(ax_pos(:));
end
ax_pos(:,3:4) = ax_pos(:,3:4) + ax_pos(:,1:2);
leg_pos = get(lh, 'OuterPosition');
if nLeg > 1;
leg_pos = cell2mat(leg_pos);
end
leg_pos(:,3:4) = leg_pos(:,3:4) + leg_pos(:,1:2);
ax_pos = shiftdim(ax_pos, -1);
% Overlap test
M = bsxfun(@lt, leg_pos(:,1), ax_pos(:,:,3)) & ...
bsxfun(@lt, leg_pos(:,2), ax_pos(:,:,4)) & ...
bsxfun(@gt, leg_pos(:,3), ax_pos(:,:,1)) & ...
bsxfun(@gt, leg_pos(:,4), ax_pos(:,:,2));
ah = [ah; lh(any(M, 2))];
end
% Get all the objects in the figure
axs = findall(fh);
% Delete everything except for the input objects and associated items
delete(axs(~ismember(axs, [ah; allchildren(ah); allancestors(ah)])));
end
function ah = allchildren(ah)
ah = findall(ah);
if iscell(ah)
ah = cell2mat(ah);
end
ah = ah(:);
end
function ph = allancestors(ah)
ph = [];
for a = 1:numel(ah)
h = get(ah(a), 'parent');
while h ~= 0
ph = [ph; h];
h = get(h, 'parent');
end
end
end
|
github
|
vitoruapt/lartkv5-master
|
im2gif.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/im2gif.m
| 6,048 |
utf_8
|
5a7437140f8d013158a195de1e372737
|
%IM2GIF Convert a multiframe image to an animated GIF file
%
% Examples:
% im2gif infile
% im2gif infile outfile
% im2gif(A, outfile)
% im2gif(..., '-nocrop')
% im2gif(..., '-nodither')
% im2gif(..., '-ncolors', n)
% im2gif(..., '-loops', n)
% im2gif(..., '-delay', n)
%
% This function converts a multiframe image to an animated GIF.
%
% To create an animation from a series of figures, export to a multiframe
% TIFF file using export_fig, then convert to a GIF, as follows:
%
% for a = 2 .^ (3:6)
% peaks(a);
% export_fig test.tif -nocrop -append
% end
% im2gif('test.tif', '-delay', 0.5);
%
%IN:
% infile - string containing the name of the input image.
% outfile - string containing the name of the output image (must have the
% .gif extension). Default: infile, with .gif extension.
% A - HxWxCxN array of input images, stacked along fourth dimension, to
% be converted to gif.
% -nocrop - option indicating that the borders of the output are not to
% be cropped.
% -nodither - option indicating that dithering is not to be used when
% converting the image.
% -ncolors - option pair, the value of which indicates the maximum number
% of colors the GIF can have. This can also be a quantization
% tolerance, between 0 and 1. Default/maximum: 256.
% -loops - option pair, the value of which gives the number of times the
% animation is to be looped. Default: 65535.
% -delay - option pair, the value of which gives the time, in seconds,
% between frames. Default: 1/15.
% Copyright (C) Oliver Woodford 2011
function im2gif(A, varargin)
% Parse the input arguments
[A, options] = parse_args(A, varargin{:});
if options.crop ~= 0
% Crop
A = crop_borders(A, A(ceil(end/2),1,:,1));
end
% Convert to indexed image
[h, w, c, n] = size(A);
A = reshape(permute(A, [1 2 4 3]), h, w*n, c);
map = unique(reshape(A, h*w*n, c), 'rows');
if size(map, 1) > 256
dither_str = {'dither', 'nodither'};
dither_str = dither_str{1+(options.dither==0)};
if options.ncolors <= 1
[B, map] = rgb2ind(A, options.ncolors, dither_str);
if size(map, 1) > 256
[B, map] = rgb2ind(A, 256, dither_str);
end
else
[B, map] = rgb2ind(A, min(round(options.ncolors), 256), dither_str);
end
else
if max(map(:)) > 1
map = double(map) / 255;
A = double(A) / 255;
end
B = rgb2ind(im2double(A), map);
end
B = reshape(B, h, w, 1, n);
% Bug fix to rgb2ind
map(B(1)+1,:) = im2double(A(1,1,:));
% Save as a gif
imwrite(B, map, options.outfile, 'LoopCount', round(options.loops(1)), 'DelayTime', options.delay);
end
%% Parse the input arguments
function [A, options] = parse_args(A, varargin)
% Set the defaults
options = struct('outfile', '', ...
'dither', true, ...
'crop', true, ...
'ncolors', 256, ...
'loops', 65535, ...
'delay', 1/15);
% Go through the arguments
a = 0;
n = numel(varargin);
while a < n
a = a + 1;
if ischar(varargin{a}) && ~isempty(varargin{a})
if varargin{a}(1) == '-'
opt = lower(varargin{a}(2:end));
switch opt
case 'nocrop'
options.crop = false;
case 'nodither'
options.dither = false;
otherwise
if ~isfield(options, opt)
error('Option %s not recognized', varargin{a});
end
a = a + 1;
if ischar(varargin{a}) && ~ischar(options.(opt))
options.(opt) = str2double(varargin{a});
else
options.(opt) = varargin{a};
end
end
else
options.outfile = varargin{a};
end
end
end
if isempty(options.outfile)
if ~ischar(A)
error('No output filename given.');
end
% Generate the output filename from the input filename
[path, outfile] = fileparts(A);
options.outfile = fullfile(path, [outfile '.gif']);
end
if ischar(A)
% Read in the image
A = imread_rgb(A);
end
end
%% Read image to uint8 rgb array
function [A, alpha] = imread_rgb(name)
% Get file info
info = imfinfo(name);
% Special case formats
switch lower(info(1).Format)
case 'gif'
[A, map] = imread(name, 'frames', 'all');
if ~isempty(map)
map = uint8(map * 256 - 0.5); % Convert to uint8 for storage
A = reshape(map(uint32(A)+1,:), [size(A) size(map, 2)]); % Assume indexed from 0
A = permute(A, [1 2 5 4 3]);
end
case {'tif', 'tiff'}
A = cell(numel(info), 1);
for a = 1:numel(A)
[A{a}, map] = imread(name, 'Index', a, 'Info', info);
if ~isempty(map)
map = uint8(map * 256 - 0.5); % Convert to uint8 for storage
A{a} = reshape(map(uint32(A{a})+1,:), [size(A) size(map, 2)]); % Assume indexed from 0
end
if size(A{a}, 3) == 4
% TIFF in CMYK colourspace - convert to RGB
if isfloat(A{a})
A{a} = A{a} * 255;
else
A{a} = single(A{a});
end
A{a} = 255 - A{a};
A{a}(:,:,4) = A{a}(:,:,4) / 255;
A{a} = uint8(A(:,:,1:3) .* A{a}(:,:,[4 4 4]));
end
end
A = cat(4, A{:});
otherwise
[A, map, alpha] = imread(name);
A = A(:,:,:,1); % Keep only first frame of multi-frame files
if ~isempty(map)
map = uint8(map * 256 - 0.5); % Convert to uint8 for storage
A = reshape(map(uint32(A)+1,:), [size(A) size(map, 2)]); % Assume indexed from 0
elseif size(A, 3) == 4
% Assume 4th channel is an alpha matte
alpha = A(:,:,4);
A = A(:,:,1:3);
end
end
end
|
github
|
vitoruapt/lartkv5-master
|
read_write_entire_textfile.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/read_write_entire_textfile.m
| 924 |
utf_8
|
779e56972f5d9778c40dee98ddbd677e
|
%READ_WRITE_ENTIRE_TEXTFILE Read or write a whole text file to/from memory
%
% Read or write an entire text file to/from memory, without leaving the
% file open if an error occurs.
%
% Reading:
% fstrm = read_write_entire_textfile(fname)
% Writing:
% read_write_entire_textfile(fname, fstrm)
%
%IN:
% fname - Pathname of text file to be read in.
% fstrm - String to be written to the file, including carriage returns.
%
%OUT:
% fstrm - String read from the file. If an fstrm input is given the
% output is the same as that input.
function fstrm = read_write_entire_textfile(fname, fstrm)
modes = {'rt', 'wt'};
writing = nargin > 1;
fh = fopen(fname, modes{1+writing});
if fh == -1
error('Unable to open file %s.', fname);
end
try
if writing
fwrite(fh, fstrm, 'char*1');
else
fstrm = fread(fh, '*char')';
end
catch ex
fclose(fh);
rethrow(ex);
end
fclose(fh);
end
|
github
|
vitoruapt/lartkv5-master
|
pdf2eps.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/pdf2eps.m
| 1,471 |
utf_8
|
a1f41f0c7713c73886a2323e53ed982b
|
%PDF2EPS Convert a pdf file to eps format using pdftops
%
% Examples:
% pdf2eps source dest
%
% This function converts a pdf file to eps format.
%
% This function requires that you have pdftops, from the Xpdf suite of
% functions, installed on your system. This can be downloaded from:
% http://www.foolabs.com/xpdf
%
%IN:
% source - filename of the source pdf file to convert. The filename is
% assumed to already have the extension ".pdf".
% dest - filename of the destination eps file. The filename is assumed to
% already have the extension ".eps".
% Copyright (C) Oliver Woodford 2009-2010
% Thanks to Aldebaro Klautau for reporting a bug when saving to
% non-existant directories.
function pdf2eps(source, dest)
% Construct the options string for pdftops
options = ['-q -paper match -eps -level2 "' source '" "' dest '"'];
% Convert to eps using pdftops
[status, message] = pdftops(options);
% Check for error
if status
% Report error
if isempty(message)
error('Unable to generate eps. Check destination directory is writable.');
else
error(message);
end
end
% Fix the DSC error created by pdftops
fid = fopen(dest, 'r+');
if fid == -1
% Cannot open the file
return
end
fgetl(fid); % Get the first line
str = fgetl(fid); % Get the second line
if strcmp(str(1:min(13, end)), '% Produced by')
fseek(fid, -numel(str)-1, 'cof');
fwrite(fid, '%'); % Turn ' ' into '%'
end
fclose(fid);
end
|
github
|
vitoruapt/lartkv5-master
|
print2array.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/print2array.m
| 6,273 |
utf_8
|
c2feb752d8836426a74edd9357f1ff17
|
%PRINT2ARRAY Exports a figure to an image array
%
% Examples:
% A = print2array
% A = print2array(figure_handle)
% A = print2array(figure_handle, resolution)
% A = print2array(figure_handle, resolution, renderer)
% [A bcol] = print2array(...)
%
% This function outputs a bitmap image of the given figure, at the desired
% resolution.
%
% If renderer is '-painters' then ghostcript needs to be installed. This
% can be downloaded from: http://www.ghostscript.com
%
% IN:
% figure_handle - The handle of the figure to be exported. Default: gcf.
% resolution - Resolution of the output, as a factor of screen
% resolution. Default: 1.
% renderer - string containing the renderer paramater to be passed to
% print. Default: '-opengl'.
%
% OUT:
% A - MxNx3 uint8 image of the figure.
% bcol - 1x3 uint8 vector of the background color
% Copyright (C) Oliver Woodford 2008-2012
% 05/09/11: Set EraseModes to normal when using opengl or zbuffer
% renderers. Thanks to Pawel Kocieniewski for reporting the
% issue.
% 21/09/11: Bug fix: unit8 -> uint8! Thanks to Tobias Lamour for reporting
% the issue.
% 14/11/11: Bug fix: stop using hardcopy(), as it interfered with figure
% size and erasemode settings. Makes it a bit slower, but more
% reliable. Thanks to Phil Trinh and Meelis Lootus for reporting
% the issues.
% 09/12/11: Pass font path to ghostscript.
% 27/01/12: Bug fix affecting painters rendering tall figures. Thanks to
% Ken Campbell for reporting it.
% 03/04/12: Bug fix to median input. Thanks to Andy Matthews for reporting
% it.
% 26/10/12: Set PaperOrientation to portrait. Thanks to Michael Watts for
% reporting the issue.
function [A, bcol] = print2array(fig, res, renderer)
% Generate default input arguments, if needed
if nargin < 2
res = 1;
if nargin < 1
fig = gcf;
end
end
% Warn if output is large
old_mode = get(fig, 'Units');
set(fig, 'Units', 'pixels');
px = get(fig, 'Position');
set(fig, 'Units', old_mode);
npx = prod(px(3:4)*res)/1e6;
if npx > 30
% 30M pixels or larger!
warning('MATLAB:LargeImage', 'print2array generating a %.1fM pixel image. This could be slow and might also cause memory problems.', npx);
end
% Retrieve the background colour
bcol = get(fig, 'Color');
% Set the resolution parameter
res_str = ['-r' num2str(ceil(get(0, 'ScreenPixelsPerInch')*res))];
% Generate temporary file name
tmp_nam = [tempname '.tif'];
if nargin > 2 && strcmp(renderer, '-painters')
% Print to eps file
tmp_eps = [tempname '.eps'];
print2eps(tmp_eps, fig, 0, renderer, '-loose');
try
% Initialize the command to export to tiff using ghostscript
cmd_str = ['-dEPSCrop -q -dNOPAUSE -dBATCH ' res_str ' -sDEVICE=tiff24nc'];
% Set the font path
fp = font_path();
if ~isempty(fp)
cmd_str = [cmd_str ' -sFONTPATH="' fp '"'];
end
% Add the filenames
cmd_str = [cmd_str ' -sOutputFile="' tmp_nam '" "' tmp_eps '"'];
% Execute the ghostscript command
ghostscript(cmd_str);
catch me
% Delete the intermediate file
delete(tmp_eps);
rethrow(me);
end
% Delete the intermediate file
delete(tmp_eps);
% Read in the generated bitmap
A = imread(tmp_nam);
% Delete the temporary bitmap file
delete(tmp_nam);
% Set border pixels to the correct colour
if isequal(bcol, 'none')
bcol = [];
elseif isequal(bcol, [1 1 1])
bcol = uint8([255 255 255]);
else
for l = 1:size(A, 2)
if ~all(reshape(A(:,l,:) == 255, [], 1))
break;
end
end
for r = size(A, 2):-1:l
if ~all(reshape(A(:,r,:) == 255, [], 1))
break;
end
end
for t = 1:size(A, 1)
if ~all(reshape(A(t,:,:) == 255, [], 1))
break;
end
end
for b = size(A, 1):-1:t
if ~all(reshape(A(b,:,:) == 255, [], 1))
break;
end
end
bcol = uint8(median(single([reshape(A(:,[l r],:), [], size(A, 3)); reshape(A([t b],:,:), [], size(A, 3))]), 1));
for c = 1:size(A, 3)
A(:,[1:l-1, r+1:end],c) = bcol(c);
A([1:t-1, b+1:end],:,c) = bcol(c);
end
end
else
if nargin < 3
renderer = '-opengl';
end
err = false;
% Set paper size
old_pos_mode = get(fig, 'PaperPositionMode');
old_orientation = get(fig, 'PaperOrientation');
set(fig, 'PaperPositionMode', 'auto', 'PaperOrientation', 'portrait');
try
% Print to tiff file
print(fig, renderer, res_str, '-dtiff', tmp_nam);
% Read in the printed file
A = imread(tmp_nam);
% Delete the temporary file
delete(tmp_nam);
catch ex
err = true;
end
% Reset paper size
set(fig, 'PaperPositionMode', old_pos_mode, 'PaperOrientation', old_orientation);
% Throw any error that occurred
if err
rethrow(ex);
end
% Set the background color
if isequal(bcol, 'none')
bcol = [];
else
bcol = bcol * 255;
if isequal(bcol, round(bcol))
bcol = uint8(bcol);
else
bcol = squeeze(A(1,1,:));
end
end
end
% Check the output size is correct
if isequal(res, round(res))
px = [px([4 3])*res 3];
if ~isequal(size(A), px)
% Correct the output size
A = A(1:min(end,px(1)),1:min(end,px(2)),:);
end
end
end
% Function to return (and create, where necessary) the font path
function fp = font_path()
fp = user_string('gs_font_path');
if ~isempty(fp)
return
end
% Create the path
% Start with the default path
fp = getenv('GS_FONTPATH');
% Add on the typical directories for a given OS
if ispc
if ~isempty(fp)
fp = [fp ';'];
end
fp = [fp getenv('WINDIR') filesep 'Fonts'];
else
if ~isempty(fp)
fp = [fp ':'];
end
fp = [fp '/usr/share/fonts:/usr/local/share/fonts:/usr/share/fonts/X11:/usr/local/share/fonts/X11:/usr/share/fonts/truetype:/usr/local/share/fonts/truetype'];
end
user_string('gs_font_path', fp);
end
|
github
|
vitoruapt/lartkv5-master
|
append_pdfs.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/append_pdfs.m
| 2,010 |
utf_8
|
1034abde9642693c404671ff1c693a22
|
%APPEND_PDFS Appends/concatenates multiple PDF files
%
% Example:
% append_pdfs(output, input1, input2, ...)
% append_pdfs(output, input_list{:})
% append_pdfs test.pdf temp1.pdf temp2.pdf
%
% This function appends multiple PDF files to an existing PDF file, or
% concatenates them into a PDF file if the output file doesn't yet exist.
%
% This function requires that you have ghostscript installed on your
% system. Ghostscript can be downloaded from: http://www.ghostscript.com
%
% IN:
% output - string of output file name (including the extension, .pdf).
% If it exists it is appended to; if not, it is created.
% input1 - string of an input file name (including the extension, .pdf).
% All input files are appended in order.
% input_list - cell array list of input file name strings. All input
% files are appended in order.
% Copyright: Oliver Woodford, 2011
% Thanks to Reinhard Knoll for pointing out that appending multiple pdfs in
% one go is much faster than appending them one at a time.
% Thanks to Michael Teo for reporting the issue of a too long command line.
% Issue resolved on 5/5/2011, by passing gs a command file.
% Thanks to Martin Wittmann for pointing out the quality issue when
% appending multiple bitmaps.
% Issue resolved (to best of my ability) 1/6/2011, using the prepress
% setting
function append_pdfs(varargin)
% Are we appending or creating a new file
append = exist(varargin{1}, 'file') == 2;
if append
output = [tempname '.pdf'];
else
output = varargin{1};
varargin = varargin(2:end);
end
% Create the command file
cmdfile = [tempname '.txt'];
fh = fopen(cmdfile, 'w');
fprintf(fh, '-q -dNOPAUSE -dBATCH -sDEVICE=pdfwrite -dPDFSETTINGS=/prepress -sOutputFile="%s" -f', output);
fprintf(fh, ' "%s"', varargin{:});
fclose(fh);
% Call ghostscript
ghostscript(['@"' cmdfile '"']);
% Delete the command file
delete(cmdfile);
% Rename the file if needed
if append
movefile(output, varargin{1});
end
end
|
github
|
vitoruapt/lartkv5-master
|
using_hg2.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/using_hg2.m
| 365 |
utf_8
|
6a7f56042fda1873d8225eb3ec1cc197
|
%USING_HG2 Determine if the HG2 graphics pipeline is used
%
% tf = using_hg2(fig)
%
%IN:
% fig - handle to the figure in question.
%
%OUT:
% tf - boolean indicating whether the HG2 graphics pipeline is being used
% (true) or not (false).
function tf = using_hg2(fig)
try
tf = ~graphicsversion(fig, 'handlegraphics');
catch
tf = false;
end
end
|
github
|
vitoruapt/lartkv5-master
|
eps2pdf.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/eps2pdf.m
| 5,009 |
utf_8
|
5658b3d96232e138be7fd49693d88453
|
%EPS2PDF Convert an eps file to pdf format using ghostscript
%
% Examples:
% eps2pdf source dest
% eps2pdf(source, dest, crop)
% eps2pdf(source, dest, crop, append)
% eps2pdf(source, dest, crop, append, gray)
% eps2pdf(source, dest, crop, append, gray, quality)
%
% This function converts an eps file to pdf format. The output can be
% optionally cropped and also converted to grayscale. If the output pdf
% file already exists then the eps file can optionally be appended as a new
% page on the end of the eps file. The level of bitmap compression can also
% optionally be set.
%
% This function requires that you have ghostscript installed on your
% system. Ghostscript can be downloaded from: http://www.ghostscript.com
%
%IN:
% source - filename of the source eps file to convert. The filename is
% assumed to already have the extension ".eps".
% dest - filename of the destination pdf file. The filename is assumed to
% already have the extension ".pdf".
% crop - boolean indicating whether to crop the borders off the pdf.
% Default: true.
% append - boolean indicating whether the eps should be appended to the
% end of the pdf as a new page (if the pdf exists already).
% Default: false.
% gray - boolean indicating whether the output pdf should be grayscale or
% not. Default: false.
% quality - scalar indicating the level of image bitmap quality to
% output. A larger value gives a higher quality. quality > 100
% gives lossless output. Default: ghostscript prepress default.
% Copyright (C) Oliver Woodford 2009-2011
% Suggestion of appending pdf files provided by Matt C at:
% http://www.mathworks.com/matlabcentral/fileexchange/23629
% Thank you to Fabio Viola for pointing out compression artifacts, leading
% to the quality setting.
% Thank you to Scott for pointing out the subsampling of very small images,
% which was fixed for lossless compression settings.
% 9/12/2011 Pass font path to ghostscript.
function eps2pdf(source, dest, crop, append, gray, quality)
% Intialise the options string for ghostscript
options = ['-q -dNOPAUSE -dBATCH -sDEVICE=pdfwrite -dPDFSETTINGS=/prepress -sOutputFile="' dest '"'];
% Set crop option
if nargin < 3 || crop
options = [options ' -dEPSCrop'];
end
% Set the font path
fp = font_path();
if ~isempty(fp)
options = [options ' -sFONTPATH="' fp '"'];
end
% Set the grayscale option
if nargin > 4 && gray
options = [options ' -sColorConversionStrategy=Gray -dProcessColorModel=/DeviceGray'];
end
% Set the bitmap quality
if nargin > 5 && ~isempty(quality)
options = [options ' -dAutoFilterColorImages=false -dAutoFilterGrayImages=false'];
if quality > 100
options = [options ' -dColorImageFilter=/FlateEncode -dGrayImageFilter=/FlateEncode -c ".setpdfwrite << /ColorImageDownsampleThreshold 10 /GrayImageDownsampleThreshold 10 >> setdistillerparams"'];
else
options = [options ' -dColorImageFilter=/DCTEncode -dGrayImageFilter=/DCTEncode'];
v = 1 + (quality < 80);
quality = 1 - quality / 100;
s = sprintf('<< /QFactor %.2f /Blend 1 /HSample [%d 1 1 %d] /VSample [%d 1 1 %d] >>', quality, v, v, v, v);
options = sprintf('%s -c ".setpdfwrite << /ColorImageDict %s /GrayImageDict %s >> setdistillerparams"', options, s, s);
end
end
% Check if the output file exists
if nargin > 3 && append && exist(dest, 'file') == 2
% File exists - append current figure to the end
tmp_nam = tempname;
% Copy the file
copyfile(dest, tmp_nam);
% Add the output file names
options = [options ' -f "' tmp_nam '" "' source '"'];
try
% Convert to pdf using ghostscript
[status, message] = ghostscript(options);
catch me
% Delete the intermediate file
delete(tmp_nam);
rethrow(me);
end
% Delete the intermediate file
delete(tmp_nam);
else
% File doesn't exist or should be over-written
% Add the output file names
options = [options ' -f "' source '"'];
% Convert to pdf using ghostscript
[status, message] = ghostscript(options);
end
% Check for error
if status
% Report error
if isempty(message)
error('Unable to generate pdf. Check destination directory is writable.');
else
error(message);
end
end
end
% Function to return (and create, where necessary) the font path
function fp = font_path()
fp = user_string('gs_font_path');
if ~isempty(fp)
return
end
% Create the path
% Start with the default path
fp = getenv('GS_FONTPATH');
% Add on the typical directories for a given OS
if ispc
if ~isempty(fp)
fp = [fp ';'];
end
fp = [fp getenv('WINDIR') filesep 'Fonts'];
else
if ~isempty(fp)
fp = [fp ':'];
end
fp = [fp '/usr/share/fonts:/usr/local/share/fonts:/usr/share/fonts/X11:/usr/local/share/fonts/X11:/usr/share/fonts/truetype:/usr/local/share/fonts/truetype'];
end
user_string('gs_font_path', fp);
end
|
github
|
vitoruapt/lartkv5-master
|
copyfig.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/copyfig.m
| 812 |
utf_8
|
b6b1fa9a9351df33ae0d42056c3df40a
|
%COPYFIG Create a copy of a figure, without changing the figure
%
% Examples:
% fh_new = copyfig(fh_old)
%
% This function will create a copy of a figure, but not change the figure,
% as copyobj sometimes does, e.g. by changing legends.
%
% IN:
% fh_old - The handle of the figure to be copied. Default: gcf.
%
% OUT:
% fh_new - The handle of the created figure.
% Copyright (C) Oliver Woodford 2012
function fh = copyfig(fh)
% Set the default
if nargin == 0
fh = gcf;
end
% Is there a legend?
if isempty(findall(fh, 'Type', 'axes', 'Tag', 'legend'))
% Safe to copy using copyobj
fh = copyobj(fh, 0);
else
% copyobj will change the figure, so save and then load it instead
tmp_nam = [tempname '.fig'];
hgsave(fh, tmp_nam);
fh = hgload(tmp_nam);
delete(tmp_nam);
end
end
|
github
|
vitoruapt/lartkv5-master
|
user_string.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/user_string.m
| 2,460 |
utf_8
|
e8aa836a5140410546fceccb4cca47aa
|
%USER_STRING Get/set a user specific string
%
% Examples:
% string = user_string(string_name)
% saved = user_string(string_name, new_string)
%
% Function to get and set a string in a system or user specific file. This
% enables, for example, system specific paths to binaries to be saved.
%
% IN:
% string_name - String containing the name of the string required. The
% string is extracted from a file called (string_name).txt,
% stored in the same directory as user_string.m.
% new_string - The new string to be saved under the name given by
% string_name.
%
% OUT:
% string - The currently saved string. Default: ''.
% saved - Boolean indicating whether the save was succesful
% Copyright (C) Oliver Woodford 2011-2013
% This method of saving paths avoids changing .m files which might be in a
% version control system. Instead it saves the user dependent paths in
% separate files with a .txt extension, which need not be checked in to
% the version control system. Thank you to Jonas Dorn for suggesting this
% approach.
% 10/01/2013 - Access files in text, not binary mode, as latter can cause
% errors. Thanks to Christian for pointing this out.
function string = user_string(string_name, string)
if ~ischar(string_name)
error('string_name must be a string.');
end
% Create the full filename
string_name = fullfile(fileparts(mfilename('fullpath')), '.ignore', [string_name '.txt']);
if nargin > 1
% Set string
if ~ischar(string)
error('new_string must be a string.');
end
% Make sure the save directory exists
dname = fileparts(string_name);
if ~exist(dname, 'dir')
% Create the directory
try
if ~mkdir(dname)
string = false;
return
end
catch
string = false;
return
end
% Make it hidden
try
fileattrib(dname, '+h');
catch
end
end
% Write the file
fid = fopen(string_name, 'wt');
if fid == -1
string = false;
return
end
try
fprintf(fid, '%s', string);
catch
fclose(fid);
string = false;
return
end
fclose(fid);
string = true;
else
% Get string
fid = fopen(string_name, 'rt');
if fid == -1
string = '';
return
end
string = fgetl(fid);
fclose(fid);
end
end
|
github
|
vitoruapt/lartkv5-master
|
export_fig.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/export_fig.m
| 29,720 |
utf_8
|
923dcc1ad89f1381ee70abbf422b20a5
|
%EXPORT_FIG Exports figures suitable for publication
%
% Examples:
% im = export_fig
% [im alpha] = export_fig
% export_fig filename
% export_fig filename -format1 -format2
% export_fig ... -nocrop
% export_fig ... -transparent
% export_fig ... -native
% export_fig ... -m<val>
% export_fig ... -r<val>
% export_fig ... -a<val>
% export_fig ... -q<val>
% export_fig ... -p<val>
% export_fig ... -<renderer>
% export_fig ... -<colorspace>
% export_fig ... -append
% export_fig ... -bookmark
% export_fig(..., handle)
%
% This function saves a figure or single axes to one or more vector and/or
% bitmap file formats, and/or outputs a rasterized version to the
% workspace, with the following properties:
% - Figure/axes reproduced as it appears on screen
% - Cropped borders (optional)
% - Embedded fonts (vector formats)
% - Improved line and grid line styles
% - Anti-aliased graphics (bitmap formats)
% - Render images at native resolution (optional for bitmap formats)
% - Transparent background supported (pdf, eps, png)
% - Semi-transparent patch objects supported (png only)
% - RGB, CMYK or grayscale output (CMYK only with pdf, eps, tiff)
% - Variable image compression, including lossless (pdf, eps, jpg)
% - Optionally append to file (pdf, tiff)
% - Vector formats: pdf, eps
% - Bitmap formats: png, tiff, jpg, bmp, export to workspace
%
% This function is especially suited to exporting figures for use in
% publications and presentations, because of the high quality and
% portability of media produced.
%
% Note that the background color and figure dimensions are reproduced
% (the latter approximately, and ignoring cropping & magnification) in the
% output file. For transparent background (and semi-transparent patch
% objects), use the -transparent option or set the figure 'Color' property
% to 'none'. To make axes transparent set the axes 'Color' property to
% 'none'. Pdf, eps and png are the only file formats to support a
% transparent background, whilst the png format alone supports transparency
% of patch objects.
%
% The choice of renderer (opengl, zbuffer or painters) has a large impact
% on the quality of output. Whilst the default value (opengl for bitmaps,
% painters for vector formats) generally gives good results, if you aren't
% satisfied then try another renderer. Notes: 1) For vector formats (eps,
% pdf), only painters generates vector graphics. 2) For bitmaps, only
% opengl can render transparent patch objects correctly. 3) For bitmaps,
% only painters will correctly scale line dash and dot lengths when
% magnifying or anti-aliasing. 4) Fonts may be substitued with Courier when
% using painters.
%
% When exporting to vector format (pdf & eps) and bitmap format using the
% painters renderer, this function requires that ghostscript is installed
% on your system. You can download this from:
% http://www.ghostscript.com
% When exporting to eps it additionally requires pdftops, from the Xpdf
% suite of functions. You can download this from:
% http://www.foolabs.com/xpdf
%
%IN:
% filename - string containing the name (optionally including full or
% relative path) of the file the figure is to be saved as. If
% a path is not specified, the figure is saved in the current
% directory. If no name and no output arguments are specified,
% the default name, 'export_fig_out', is used. If neither a
% file extension nor a format are specified, a ".png" is added
% and the figure saved in that format.
% -format1, -format2, etc. - strings containing the extensions of the
% file formats the figure is to be saved as.
% Valid options are: '-pdf', '-eps', '-png',
% '-tif', '-jpg' and '-bmp'. All combinations
% of formats are valid.
% -nocrop - option indicating that the borders of the output are not to
% be cropped.
% -transparent - option indicating that the figure background is to be
% made transparent (png, pdf and eps output only).
% -m<val> - option where val indicates the factor to magnify the
% on-screen figure pixel dimensions by when generating bitmap
% outputs. Default: '-m1'.
% -r<val> - option val indicates the resolution (in pixels per inch) to
% export bitmap and vector outputs at, keeping the dimensions
% of the on-screen figure. Default: '-r864' (for vector output
% only). Note that the -m option overides the -r option for
% bitmap outputs only.
% -native - option indicating that the output resolution (when outputting
% a bitmap format) should be such that the vertical resolution
% of the first suitable image found in the figure is at the
% native resolution of that image. To specify a particular
% image to use, give it the tag 'export_fig_native'. Notes:
% This overrides any value set with the -m and -r options. It
% also assumes that the image is displayed front-to-parallel
% with the screen. The output resolution is approximate and
% should not be relied upon. Anti-aliasing can have adverse
% effects on image quality (disable with the -a1 option).
% -a1, -a2, -a3, -a4 - option indicating the amount of anti-aliasing to
% use for bitmap outputs. '-a1' means no anti-
% aliasing; '-a4' is the maximum amount (default).
% -<renderer> - option to force a particular renderer (painters, opengl
% or zbuffer) to be used over the default: opengl for
% bitmaps; painters for vector formats.
% -<colorspace> - option indicating which colorspace color figures should
% be saved in: RGB (default), CMYK or gray. CMYK is only
% supported in pdf, eps and tiff output.
% -q<val> - option to vary bitmap image quality (in pdf, eps and jpg
% files only). Larger val, in the range 0-100, gives higher
% quality/lower compression. val > 100 gives lossless
% compression. Default: '-q95' for jpg, ghostscript prepress
% default for pdf & eps. Note: lossless compression can
% sometimes give a smaller file size than the default lossy
% compression, depending on the type of images.
% -p<val> - option to add a border of width val to eps and pdf files,
% where val is in units of the intermediate eps file. Default:
% 0 (i.e. no padding).
% -append - option indicating that if the file (pdfs only) already
% exists, the figure is to be appended as a new page, instead
% of being overwritten (default).
% -bookmark - option to indicate that a bookmark with the name of the
% figure is to be created in the output file (pdf only).
% handle - The handle of the figure, axes or uipanels (can be an array of
% handles, but the objects must be in the same figure) to be
% saved. Default: gcf.
%
%OUT:
% im - MxNxC uint8 image array of the figure.
% alpha - MxN single array of alphamatte values in range [0,1], for the
% case when the background is transparent.
%
% Some helpful examples and tips can be found at:
% https://github.com/ojwoodford/export_fig
%
% See also PRINT, SAVEAS.
% Copyright (C) Oliver Woodford 2008-2014
% The idea of using ghostscript is inspired by Peder Axensten's SAVEFIG
% (fex id: 10889) which is itself inspired by EPS2PDF (fex id: 5782).
% The idea for using pdftops came from the MATLAB newsgroup (id: 168171).
% The idea of editing the EPS file to change line styles comes from Jiro
% Doke's FIXPSLINESTYLE (fex id: 17928).
% The idea of changing dash length with line width came from comments on
% fex id: 5743, but the implementation is mine :)
% The idea of anti-aliasing bitmaps came from Anders Brun's MYAA (fex id:
% 20979).
% The idea of appending figures in pdfs came from Matt C in comments on the
% FEX (id: 23629)
% Thanks to Roland Martin for pointing out the colour MATLAB
% bug/feature with colorbar axes and transparent backgrounds.
% Thanks also to Andrew Matthews for describing a bug to do with the figure
% size changing in -nodisplay mode. I couldn't reproduce it, but included a
% fix anyway.
% Thanks to Tammy Threadgill for reporting a bug where an axes is not
% isolated from gui objects.
% 23/02/12: Ensure that axes limits don't change during printing
% 14/03/12: Fix bug in fixing the axes limits (thanks to Tobias Lamour for
% reporting it).
% 02/05/12: Incorporate patch of Petr Nechaev (many thanks), enabling
% bookmarking of figures in pdf files.
% 09/05/12: Incorporate patch of Arcelia Arrieta (many thanks), to keep
% tick marks fixed.
% 12/12/12: Add support for isolating uipanels. Thanks to michael for
% suggesting it.
% 25/09/13: Add support for changing resolution in vector formats. Thanks
% to Jan Jaap Meijer for suggesting it.
% 07/05/14: Add support for '~' at start of path. Thanks to Sally Warner
% for suggesting it.
function [im, alpha] = export_fig(varargin)
% Make sure the figure is rendered correctly _now_ so that properties like
% axes limits are up-to-date.
drawnow;
% Parse the input arguments
[fig, options] = parse_args(nargout, varargin{:});
% Isolate the subplot, if it is one
cls = all(ismember(get(fig, 'Type'), {'axes', 'uipanel'}));
if cls
% Given handles of one or more axes, so isolate them from the rest
fig = isolate_axes(fig);
else
% Check we have a figure
if ~isequal(get(fig, 'Type'), 'figure');
error('Handle must be that of a figure, axes or uipanel');
end
% Get the old InvertHardcopy mode
old_mode = get(fig, 'InvertHardcopy');
end
% Hack the font units where necessary (due to a font rendering bug in
% print?). This may not work perfectly in all cases. Also it can change the
% figure layout if reverted, so use a copy.
magnify = options.magnify * options.aa_factor;
if isbitmap(options) && magnify ~= 1
fontu = findobj(fig, 'FontUnits', 'normalized');
if ~isempty(fontu)
% Some normalized font units found
if ~cls
fig = copyfig(fig);
set(fig, 'Visible', 'off');
fontu = findobj(fig, 'FontUnits', 'normalized');
cls = true;
end
set(fontu, 'FontUnits', 'points');
end
end
% MATLAB "feature": axes limits and tick marks can change when printing
Hlims = findall(fig, 'Type', 'axes');
if ~cls
% Record the old axes limit and tick modes
Xlims = make_cell(get(Hlims, 'XLimMode'));
Ylims = make_cell(get(Hlims, 'YLimMode'));
Zlims = make_cell(get(Hlims, 'ZLimMode'));
Xtick = make_cell(get(Hlims, 'XTickMode'));
Ytick = make_cell(get(Hlims, 'YTickMode'));
Ztick = make_cell(get(Hlims, 'ZTickMode'));
end
% Set all axes limit and tick modes to manual, so the limits and ticks can't change
set(Hlims, 'XLimMode', 'manual', 'YLimMode', 'manual', 'ZLimMode', 'manual');
set_tick_mode(Hlims, 'X');
set_tick_mode(Hlims, 'Y');
set_tick_mode(Hlims, 'Z');
% Set to print exactly what is there
set(fig, 'InvertHardcopy', 'off');
% Set the renderer
switch options.renderer
case 1
renderer = '-opengl';
case 2
renderer = '-zbuffer';
case 3
renderer = '-painters';
otherwise
renderer = '-opengl'; % Default for bitmaps
end
% Do the bitmap formats first
if isbitmap(options)
% Get the background colour
if options.transparent && (options.png || options.alpha)
% Get out an alpha channel
% MATLAB "feature": black colorbar axes can change to white and vice versa!
hCB = findobj(fig, 'Type', 'axes', 'Tag', 'Colorbar');
if isempty(hCB)
yCol = [];
xCol = [];
else
yCol = get(hCB, 'YColor');
xCol = get(hCB, 'XColor');
if iscell(yCol)
yCol = cell2mat(yCol);
xCol = cell2mat(xCol);
end
yCol = sum(yCol, 2);
xCol = sum(xCol, 2);
end
% MATLAB "feature": apparently figure size can change when changing
% colour in -nodisplay mode
pos = get(fig, 'Position');
% Set the background colour to black, and set size in case it was
% changed internally
tcol = get(fig, 'Color');
set(fig, 'Color', 'k', 'Position', pos);
% Correct the colorbar axes colours
set(hCB(yCol==0), 'YColor', [0 0 0]);
set(hCB(xCol==0), 'XColor', [0 0 0]);
% Print large version to array
B = print2array(fig, magnify, renderer);
% Downscale the image
B = downsize(single(B), options.aa_factor);
% Set background to white (and set size)
set(fig, 'Color', 'w', 'Position', pos);
% Correct the colorbar axes colours
set(hCB(yCol==3), 'YColor', [1 1 1]);
set(hCB(xCol==3), 'XColor', [1 1 1]);
% Print large version to array
A = print2array(fig, magnify, renderer);
% Downscale the image
A = downsize(single(A), options.aa_factor);
% Set the background colour (and size) back to normal
set(fig, 'Color', tcol, 'Position', pos);
% Compute the alpha map
alpha = round(sum(B - A, 3)) / (255 * 3) + 1;
A = alpha;
A(A==0) = 1;
A = B ./ A(:,:,[1 1 1]);
clear B
% Convert to greyscale
if options.colourspace == 2
A = rgb2grey(A);
end
A = uint8(A);
% Crop the background
if options.crop
[alpha, v] = crop_borders(alpha, 0, 1);
A = A(v(1):v(2),v(3):v(4),:);
end
if options.png
% Compute the resolution
res = options.magnify * get(0, 'ScreenPixelsPerInch') / 25.4e-3;
% Save the png
imwrite(A, [options.name '.png'], 'Alpha', double(alpha), 'ResolutionUnit', 'meter', 'XResolution', res, 'YResolution', res);
% Clear the png bit
options.png = false;
end
% Return only one channel for greyscale
if isbitmap(options)
A = check_greyscale(A);
end
if options.alpha
% Store the image
im = A;
% Clear the alpha bit
options.alpha = false;
end
% Get the non-alpha image
if isbitmap(options)
alph = alpha(:,:,ones(1, size(A, 3)));
A = uint8(single(A) .* alph + 255 * (1 - alph));
clear alph
end
if options.im
% Store the new image
im = A;
end
else
% Print large version to array
if options.transparent
% MATLAB "feature": apparently figure size can change when changing
% colour in -nodisplay mode
pos = get(fig, 'Position');
tcol = get(fig, 'Color');
set(fig, 'Color', 'w', 'Position', pos);
A = print2array(fig, magnify, renderer);
set(fig, 'Color', tcol, 'Position', pos);
tcol = 255;
else
[A, tcol] = print2array(fig, magnify, renderer);
end
% Crop the background
if options.crop
A = crop_borders(A, tcol, 1);
end
% Downscale the image
A = downsize(A, options.aa_factor);
if options.colourspace == 2
% Convert to greyscale
A = rgb2grey(A);
else
% Return only one channel for greyscale
A = check_greyscale(A);
end
% Outputs
if options.im
im = A;
end
if options.alpha
im = A;
alpha = zeros(size(A, 1), size(A, 2), 'single');
end
end
% Save the images
if options.png
res = options.magnify * get(0, 'ScreenPixelsPerInch') / 25.4e-3;
imwrite(A, [options.name '.png'], 'ResolutionUnit', 'meter', 'XResolution', res, 'YResolution', res);
end
if options.bmp
imwrite(A, [options.name '.bmp']);
end
% Save jpeg with given quality
if options.jpg
quality = options.quality;
if isempty(quality)
quality = 95;
end
if quality > 100
imwrite(A, [options.name '.jpg'], 'Mode', 'lossless');
else
imwrite(A, [options.name '.jpg'], 'Quality', quality);
end
end
% Save tif images in cmyk if wanted (and possible)
if options.tif
if options.colourspace == 1 && size(A, 3) == 3
A = double(255 - A);
K = min(A, [], 3);
K_ = 255 ./ max(255 - K, 1);
C = (A(:,:,1) - K) .* K_;
M = (A(:,:,2) - K) .* K_;
Y = (A(:,:,3) - K) .* K_;
A = uint8(cat(3, C, M, Y, K));
clear C M Y K K_
end
append_mode = {'overwrite', 'append'};
imwrite(A, [options.name '.tif'], 'Resolution', options.magnify*get(0, 'ScreenPixelsPerInch'), 'WriteMode', append_mode{options.append+1});
end
end
% Now do the vector formats
if isvector(options)
% Set the default renderer to painters
if ~options.renderer
renderer = '-painters';
end
% Generate some filenames
tmp_nam = [tempname '.eps'];
if options.pdf
pdf_nam = [options.name '.pdf'];
else
pdf_nam = [tempname '.pdf'];
end
% Generate the options for print
p2eArgs = {renderer, sprintf('-r%d', options.resolution)};
if options.colourspace == 1
p2eArgs = [p2eArgs {'-cmyk'}];
end
if ~options.crop
p2eArgs = [p2eArgs {'-loose'}];
end
try
% Generate an eps
print2eps(tmp_nam, fig, options.bb_padding, p2eArgs{:});
% Remove the background, if desired
if options.transparent && ~isequal(get(fig, 'Color'), 'none')
eps_remove_background(tmp_nam, 1 + using_hg2(fig));
end
% Add a bookmark to the PDF if desired
if options.bookmark
fig_nam = get(fig, 'Name');
if isempty(fig_nam)
warning('export_fig:EmptyBookmark', 'Bookmark requested for figure with no name. Bookmark will be empty.');
end
add_bookmark(tmp_nam, fig_nam);
end
% Generate a pdf
eps2pdf(tmp_nam, pdf_nam, 1, options.append, options.colourspace==2, options.quality);
catch ex
% Delete the eps
delete(tmp_nam);
rethrow(ex);
end
% Delete the eps
delete(tmp_nam);
if options.eps
try
% Generate an eps from the pdf
pdf2eps(pdf_nam, [options.name '.eps']);
catch ex
if ~options.pdf
% Delete the pdf
delete(pdf_nam);
end
rethrow(ex);
end
if ~options.pdf
% Delete the pdf
delete(pdf_nam);
end
end
end
if cls
% Close the created figure
close(fig);
else
% Reset the hardcopy mode
set(fig, 'InvertHardcopy', old_mode);
% Reset the axes limit and tick modes
for a = 1:numel(Hlims)
set(Hlims(a), 'XLimMode', Xlims{a}, 'YLimMode', Ylims{a}, 'ZLimMode', Zlims{a}, 'XTickMode', Xtick{a}, 'YTickMode', Ytick{a}, 'ZTickMode', Ztick{a});
end
end
end
function [fig, options] = parse_args(nout, varargin)
% Parse the input arguments
% Set the defaults
fig = get(0, 'CurrentFigure');
options = struct('name', 'export_fig_out', ...
'crop', true, ...
'transparent', false, ...
'renderer', 0, ... % 0: default, 1: OpenGL, 2: ZBuffer, 3: Painters
'pdf', false, ...
'eps', false, ...
'png', false, ...
'tif', false, ...
'jpg', false, ...
'bmp', false, ...
'colourspace', 0, ... % 0: RGB/gray, 1: CMYK, 2: gray
'append', false, ...
'im', nout == 1, ...
'alpha', nout == 2, ...
'aa_factor', 0, ...
'bb_padding', 0, ...
'magnify', [], ...
'resolution', [], ...
'bookmark', false, ...
'quality', []);
native = false; % Set resolution to native of an image
% Go through the other arguments
for a = 1:nargin-1
if all(ishandle(varargin{a}))
fig = varargin{a};
elseif ischar(varargin{a}) && ~isempty(varargin{a})
if varargin{a}(1) == '-'
switch lower(varargin{a}(2:end))
case 'nocrop'
options.crop = false;
case {'trans', 'transparent'}
options.transparent = true;
case 'opengl'
options.renderer = 1;
case 'zbuffer'
options.renderer = 2;
case 'painters'
options.renderer = 3;
case 'pdf'
options.pdf = true;
case 'eps'
options.eps = true;
case 'png'
options.png = true;
case {'tif', 'tiff'}
options.tif = true;
case {'jpg', 'jpeg'}
options.jpg = true;
case 'bmp'
options.bmp = true;
case 'rgb'
options.colourspace = 0;
case 'cmyk'
options.colourspace = 1;
case {'gray', 'grey'}
options.colourspace = 2;
case {'a1', 'a2', 'a3', 'a4'}
options.aa_factor = str2double(varargin{a}(3));
case 'append'
options.append = true;
case 'bookmark'
options.bookmark = true;
case 'native'
native = true;
otherwise
val = str2double(regexp(varargin{a}, '(?<=-(m|M|r|R|q|Q|p|P))-?\d*.?\d+', 'match'));
if ~isscalar(val)
error('option %s not recognised', varargin{a});
end
switch lower(varargin{a}(2))
case 'm'
options.magnify = val;
case 'r'
options.resolution = val;
case 'q'
options.quality = max(val, 0);
case 'p'
options.bb_padding = val;
end
end
else
[p, options.name, ext] = fileparts(varargin{a});
if ~isempty(p)
options.name = [p filesep options.name];
end
switch lower(ext)
case {'.tif', '.tiff'}
options.tif = true;
case {'.jpg', '.jpeg'}
options.jpg = true;
case '.png'
options.png = true;
case '.bmp'
options.bmp = true;
case '.eps'
options.eps = true;
case '.pdf'
options.pdf = true;
otherwise
options.name = varargin{a};
end
end
end
end
% Set default anti-aliasing now we know the renderer
if options.aa_factor == 0
options.aa_factor = 1 + 2 * (~(using_hg2(fig) && strcmp(get(ancestor(fig, 'figure'), 'GraphicsSmoothing'), 'on')) | (options.renderer == 3));
end
% Convert user dir '~' to full path
if numel(options.name) > 2 && options.name(1) == '~' && (options.name(2) == '/' || options.name(2) == '\')
options.name = fullfile(char(java.lang.System.getProperty('user.home')), options.name(2:end));
end
% Compute the magnification and resolution
if isempty(options.magnify)
if isempty(options.resolution)
options.magnify = 1;
options.resolution = 864;
else
options.magnify = options.resolution ./ get(0, 'ScreenPixelsPerInch');
end
elseif isempty(options.resolution)
options.resolution = 864;
end
% Check we have a figure handle
if isempty(fig)
error('No figure found');
end
% Set the default format
if ~isvector(options) && ~isbitmap(options)
options.png = true;
end
% Check whether transparent background is wanted (old way)
if isequal(get(ancestor(fig(1), 'figure'), 'Color'), 'none')
options.transparent = true;
end
% If requested, set the resolution to the native vertical resolution of the
% first suitable image found
if native && isbitmap(options)
% Find a suitable image
list = findobj(fig, 'Type', 'image', 'Tag', 'export_fig_native');
if isempty(list)
list = findobj(fig, 'Type', 'image', 'Visible', 'on');
end
for hIm = list(:)'
% Check height is >= 2
height = size(get(hIm, 'CData'), 1);
if height < 2
continue
end
% Account for the image filling only part of the axes, or vice
% versa
yl = get(hIm, 'YData');
if isscalar(yl)
yl = [yl(1)-0.5 yl(1)+height+0.5];
else
if ~diff(yl)
continue
end
yl = yl + [-0.5 0.5] * (diff(yl) / (height - 1));
end
hAx = get(hIm, 'Parent');
yl2 = get(hAx, 'YLim');
% Find the pixel height of the axes
oldUnits = get(hAx, 'Units');
set(hAx, 'Units', 'pixels');
pos = get(hAx, 'Position');
set(hAx, 'Units', oldUnits);
if ~pos(4)
continue
end
% Found a suitable image
% Account for stretch-to-fill being disabled
pbar = get(hAx, 'PlotBoxAspectRatio');
pos = min(pos(4), pbar(2)*pos(3)/pbar(1));
% Set the magnification to give native resolution
options.magnify = (height * diff(yl2)) / (pos * diff(yl));
break
end
end
end
function A = downsize(A, factor)
% Downsample an image
if factor == 1
% Nothing to do
return
end
try
% Faster, but requires image processing toolbox
A = imresize(A, 1/factor, 'bilinear');
catch
% No image processing toolbox - resize manually
% Lowpass filter - use Gaussian as is separable, so faster
% Compute the 1d Gaussian filter
filt = (-factor-1:factor+1) / (factor * 0.6);
filt = exp(-filt .* filt);
% Normalize the filter
filt = single(filt / sum(filt));
% Filter the image
padding = floor(numel(filt) / 2);
for a = 1:size(A, 3)
A(:,:,a) = conv2(filt, filt', single(A([ones(1, padding) 1:end repmat(end, 1, padding)],[ones(1, padding) 1:end repmat(end, 1, padding)],a)), 'valid');
end
% Subsample
A = A(1+floor(mod(end-1, factor)/2):factor:end,1+floor(mod(end-1, factor)/2):factor:end,:);
end
end
function A = rgb2grey(A)
A = cast(reshape(reshape(single(A), [], 3) * single([0.299; 0.587; 0.114]), size(A, 1), size(A, 2)), class(A));
end
function A = check_greyscale(A)
% Check if the image is greyscale
if size(A, 3) == 3 && ...
all(reshape(A(:,:,1) == A(:,:,2), [], 1)) && ...
all(reshape(A(:,:,2) == A(:,:,3), [], 1))
A = A(:,:,1); % Save only one channel for 8-bit output
end
end
function eps_remove_background(fname, count)
% Remove the background of an eps file
% Open the file
fh = fopen(fname, 'r+');
if fh == -1
error('Not able to open file %s.', fname);
end
% Read the file line by line
while count
% Get the next line
l = fgets(fh);
if isequal(l, -1)
break; % Quit, no rectangle found
end
% Check if the line contains the background rectangle
if isequal(regexp(l, ' *0 +0 +\d+ +\d+ +r[fe] *[\n\r]+', 'start'), 1)
% Set the line to whitespace and quit
l(1:regexp(l, '[\n\r]', 'start', 'once')-1) = ' ';
fseek(fh, -numel(l), 0);
fprintf(fh, l);
% Reduce the count
count = count - 1;
end
end
% Close the file
fclose(fh);
end
function b = isvector(options)
b = options.pdf || options.eps;
end
function b = isbitmap(options)
b = options.png || options.tif || options.jpg || options.bmp || options.im || options.alpha;
end
% Helper function
function A = make_cell(A)
if ~iscell(A)
A = {A};
end
end
function add_bookmark(fname, bookmark_text)
% Adds a bookmark to the temporary EPS file after %%EndPageSetup
% Read in the file
fh = fopen(fname, 'r');
if fh == -1
error('File %s not found.', fname);
end
try
fstrm = fread(fh, '*char')';
catch ex
fclose(fh);
rethrow(ex);
end
fclose(fh);
% Include standard pdfmark prolog to maximize compatibility
fstrm = strrep(fstrm, '%%BeginProlog', sprintf('%%%%BeginProlog\n/pdfmark where {pop} {userdict /pdfmark /cleartomark load put} ifelse'));
% Add page bookmark
fstrm = strrep(fstrm, '%%EndPageSetup', sprintf('%%%%EndPageSetup\n[ /Title (%s) /OUT pdfmark',bookmark_text));
% Write out the updated file
fh = fopen(fname, 'w');
if fh == -1
error('Unable to open %s for writing.', fname);
end
try
fwrite(fh, fstrm, 'char*1');
catch ex
fclose(fh);
rethrow(ex);
end
fclose(fh);
end
function set_tick_mode(Hlims, ax)
% Set the tick mode of linear axes to manual
% Leave log axes alone as these are tricky
M = get(Hlims, [ax 'Scale']);
if ~iscell(M)
M = {M};
end
M = cellfun(@(c) strcmp(c, 'linear'), M);
set(Hlims(M), [ax 'TickMode'], 'manual');
end
|
github
|
vitoruapt/lartkv5-master
|
ghostscript.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/ghostscript.m
| 5,009 |
utf_8
|
e93de4034ac6e4ac154729dc2c12f725
|
%GHOSTSCRIPT Calls a local GhostScript executable with the input command
%
% Example:
% [status result] = ghostscript(cmd)
%
% Attempts to locate a ghostscript executable, finally asking the user to
% specify the directory ghostcript was installed into. The resulting path
% is stored for future reference.
%
% Once found, the executable is called with the input command string.
%
% This function requires that you have Ghostscript installed on your
% system. You can download this from: http://www.ghostscript.com
%
% IN:
% cmd - Command string to be passed into ghostscript.
%
% OUT:
% status - 0 iff command ran without problem.
% result - Output from ghostscript.
% Copyright: Oliver Woodford, 2009-2013
% Thanks to Jonas Dorn for the fix for the title of the uigetdir window on
% Mac OS.
% Thanks to Nathan Childress for the fix to the default location on 64-bit
% Windows systems.
% 27/4/11 - Find 64-bit Ghostscript on Windows. Thanks to Paul Durack and
% Shaun Kline for pointing out the issue
% 4/5/11 - Thanks to David Chorlian for pointing out an alternative
% location for gs on linux.
% 12/12/12 - Add extra executable name on Windows. Thanks to Ratish
% Punnoose for highlighting the issue.
% 28/6/13 - Fix error using GS 9.07 in Linux. Many thanks to Jannick
% Steinbring for proposing the fix.
% 24/10/13 - Fix error using GS 9.07 in Linux. Many thanks to Johannes
% for the fix.
% 23/01/2014 - Add full path to ghostscript.txt in warning. Thanks to Koen
% Vermeer for raising the issue.
function varargout = ghostscript(cmd)
% Initialize any required system calls before calling ghostscript
shell_cmd = '';
if isunix
shell_cmd = 'export LD_LIBRARY_PATH=""; '; % Avoids an error on Linux with GS 9.07
end
if ismac
shell_cmd = 'export DYLD_LIBRARY_PATH=""; '; % Avoids an error on Mac with GS 9.07
end
% Call ghostscript
[varargout{1:nargout}] = system(sprintf('%s"%s" %s', shell_cmd, gs_path, cmd));
end
function path_ = gs_path
% Return a valid path
% Start with the currently set path
path_ = user_string('ghostscript');
% Check the path works
if check_gs_path(path_)
return
end
% Check whether the binary is on the path
if ispc
bin = {'gswin32c.exe', 'gswin64c.exe', 'gs'};
else
bin = {'gs'};
end
for a = 1:numel(bin)
path_ = bin{a};
if check_store_gs_path(path_)
return
end
end
% Search the obvious places
if ispc
default_location = 'C:\Program Files\gs\';
dir_list = dir(default_location);
if isempty(dir_list)
default_location = 'C:\Program Files (x86)\gs\'; % Possible location on 64-bit systems
dir_list = dir(default_location);
end
executable = {'\bin\gswin32c.exe', '\bin\gswin64c.exe'};
ver_num = 0;
% If there are multiple versions, use the newest
for a = 1:numel(dir_list)
ver_num2 = sscanf(dir_list(a).name, 'gs%g');
if ~isempty(ver_num2) && ver_num2 > ver_num
for b = 1:numel(executable)
path2 = [default_location dir_list(a).name executable{b}];
if exist(path2, 'file') == 2
path_ = path2;
ver_num = ver_num2;
end
end
end
end
if check_store_gs_path(path_)
return
end
else
executable = {'/usr/bin/gs', '/usr/local/bin/gs'};
for a = 1:numel(executable)
path_ = executable{a};
if check_store_gs_path(path_)
return
end
end
end
% Ask the user to enter the path
while 1
if strncmp(computer, 'MAC', 3) % Is a Mac
% Give separate warning as the uigetdir dialogue box doesn't have a
% title
uiwait(warndlg('Ghostscript not found. Please locate the program.'))
end
base = uigetdir('/', 'Ghostcript not found. Please locate the program.');
if isequal(base, 0)
% User hit cancel or closed window
break;
end
base = [base filesep];
bin_dir = {'', ['bin' filesep], ['lib' filesep]};
for a = 1:numel(bin_dir)
for b = 1:numel(bin)
path_ = [base bin_dir{a} bin{b}];
if exist(path_, 'file') == 2
if check_store_gs_path(path_)
return
end
end
end
end
end
error('Ghostscript not found. Have you installed it from www.ghostscript.com?');
end
function good = check_store_gs_path(path_)
% Check the path is valid
good = check_gs_path(path_);
if ~good
return
end
% Update the current default path to the path found
if ~user_string('ghostscript', path_)
warning('Path to ghostscript installation could not be saved. Enter it manually in %s.', fullfile(fileparts(which('user_string.m')), '.ignore', 'ghostscript.txt'));
return
end
end
function good = check_gs_path(path_)
% Check the path is valid
shell_cmd = '';
if ismac
shell_cmd = 'export DYLD_LIBRARY_PATH=""; '; % Avoids an error on Mac with GS 9.07
end
[good, message] = system(sprintf('%s"%s" -h', shell_cmd, path_));
good = good == 0;
end
|
github
|
vitoruapt/lartkv5-master
|
fix_lines.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/export_fig/fix_lines.m
| 5,759 |
utf_8
|
3338572f35c4669b79cc3265892d35de
|
%FIX_LINES Improves the line style of eps files generated by print
%
% Examples:
% fix_lines fname
% fix_lines fname fname2
% fstrm_out = fixlines(fstrm_in)
%
% This function improves the style of lines in eps files generated by
% MATLAB's print function, making them more similar to those seen on
% screen. Grid lines are also changed from a dashed style to a dotted
% style, for greater differentiation from dashed lines.
%
% The function also places embedded fonts after the postscript header, in
% versions of MATLAB which place the fonts first (R2006b and earlier), in
% order to allow programs such as Ghostscript to find the bounding box
% information.
%
%IN:
% fname - Name or path of source eps file.
% fname2 - Name or path of destination eps file. Default: same as fname.
% fstrm_in - File contents of a MATLAB-generated eps file.
%
%OUT:
% fstrm_out - Contents of the eps file with line styles fixed.
% Copyright: (C) Oliver Woodford, 2008-2014
% The idea of editing the EPS file to change line styles comes from Jiro
% Doke's FIXPSLINESTYLE (fex id: 17928)
% The idea of changing dash length with line width came from comments on
% fex id: 5743, but the implementation is mine :)
% Thank you to Sylvain Favrot for bringing the embedded font/bounding box
% interaction in older versions of MATLAB to my attention.
% Thank you to D Ko for bringing an error with eps files with tiff previews
% to my attention.
% Thank you to Laurence K for suggesting the check to see if the file was
% opened.
function fstrm = fix_lines(fstrm, fname2)
if nargout == 0 || nargin > 1
if nargin < 2
% Overwrite the input file
fname2 = fstrm;
end
% Read in the file
fstrm = read_write_entire_textfile(fstrm);
end
% Move any embedded fonts after the postscript header
if strcmp(fstrm(1:15), '%!PS-AdobeFont-')
% Find the start and end of the header
ind = regexp(fstrm, '[\n\r]%!PS-Adobe-');
[ind2, ind2] = regexp(fstrm, '[\n\r]%%EndComments[\n\r]+');
% Put the header first
if ~isempty(ind) && ~isempty(ind2) && ind(1) < ind2(1)
fstrm = fstrm([ind(1)+1:ind2(1) 1:ind(1) ind2(1)+1:end]);
end
end
% Make sure all line width commands come before the line style definitions,
% so that dash lengths can be based on the correct widths
% Find all line style sections
ind = [regexp(fstrm, '[\n\r]SO[\n\r]'),... % This needs to be here even though it doesn't have dots/dashes!
regexp(fstrm, '[\n\r]DO[\n\r]'),...
regexp(fstrm, '[\n\r]DA[\n\r]'),...
regexp(fstrm, '[\n\r]DD[\n\r]')];
ind = sort(ind);
% Find line width commands
[ind2, ind3] = regexp(fstrm, '[\n\r]\d* w[\n\r]');
% Go through each line style section and swap with any line width commands
% near by
b = 1;
m = numel(ind);
n = numel(ind2);
for a = 1:m
% Go forwards width commands until we pass the current line style
while b <= n && ind2(b) < ind(a)
b = b + 1;
end
if b > n
% No more width commands
break;
end
% Check we haven't gone past another line style (including SO!)
if a < m && ind2(b) > ind(a+1)
continue;
end
% Are the commands close enough to be confident we can swap them?
if (ind2(b) - ind(a)) > 8
continue;
end
% Move the line style command below the line width command
fstrm(ind(a)+1:ind3(b)) = [fstrm(ind(a)+4:ind3(b)) fstrm(ind(a)+1:ind(a)+3)];
b = b + 1;
end
% Find any grid line definitions and change to GR format
% Find the DO sections again as they may have moved
ind = int32(regexp(fstrm, '[\n\r]DO[\n\r]'));
if ~isempty(ind)
% Find all occurrences of what are believed to be axes and grid lines
ind2 = int32(regexp(fstrm, '[\n\r] *\d* *\d* *mt *\d* *\d* *L[\n\r]'));
if ~isempty(ind2)
% Now see which DO sections come just before axes and grid lines
ind2 = repmat(ind2', [1 numel(ind)]) - repmat(ind, [numel(ind2) 1]);
ind2 = any(ind2 > 0 & ind2 < 12); % 12 chars seems about right
ind = ind(ind2);
% Change any regions we believe to be grid lines to GR
fstrm(ind+1) = 'G';
fstrm(ind+2) = 'R';
end
end
% Isolate line style definition section
first_sec = strfind(fstrm, '% line types:');
[second_sec, remaining] = strtok(fstrm(first_sec+1:end), '/');
[remaining, remaining] = strtok(remaining, '%');
% Define the new styles, including the new GR format
% Dot and dash lengths have two parts: a constant amount plus a line width
% variable amount. The constant amount comes after dpi2point, and the
% variable amount comes after currentlinewidth. If you want to change
% dot/dash lengths for a one particular line style only, edit the numbers
% in the /DO (dotted lines), /DA (dashed lines), /DD (dot dash lines) and
% /GR (grid lines) lines for the style you want to change.
new_style = {'/dom { dpi2point 1 currentlinewidth 0.08 mul add mul mul } bdef',... % Dot length macro based on line width
'/dam { dpi2point 2 currentlinewidth 0.04 mul add mul mul } bdef',... % Dash length macro based on line width
'/SO { [] 0 setdash 0 setlinecap } bdef',... % Solid lines
'/DO { [1 dom 1.2 dom] 0 setdash 0 setlinecap } bdef',... % Dotted lines
'/DA { [4 dam 1.5 dam] 0 setdash 0 setlinecap } bdef',... % Dashed lines
'/DD { [1 dom 1.2 dom 4 dam 1.2 dom] 0 setdash 0 setlinecap } bdef',... % Dot dash lines
'/GR { [0 dpi2point mul 4 dpi2point mul] 0 setdash 1 setlinecap } bdef'}; % Grid lines - dot spacing remains constant
% Construct the output
fstrm = [fstrm(1:first_sec) second_sec sprintf('%s\r', new_style{:}) remaining];
% Write the output file
if nargout == 0 || nargin > 1
read_write_entire_textfile(fname2, fstrm);
end
end
|
github
|
vitoruapt/lartkv5-master
|
unbreakxaxis.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/breakxaxis/unbreakxaxis.m
| 299 |
utf_8
|
27245623b049d3a3f78c2c622c82aeae
|
function unbreakxaxis(breakInfo)
delete(breakInfo.leftAxes);
delete(breakInfo.rightAxes);
delete(breakInfo.breakAxes);
delete(breakInfo.annotationAxes);
for i = 1:numel(breakInfo.invisibleObjects)
set(breakInfo.invisibleObjects(i),'Visible','on');
end
end
|
github
|
vitoruapt/lartkv5-master
|
breakxaxis.m
|
.m
|
lartkv5-master/src/perception/pedestrians/multimodal_pedestrian_detection/matlab/breakxaxis/breakxaxis.m
| 11,663 |
utf_8
|
86d70f4a907a88c29fa10ebfec1b904b
|
% breakxaxes splits data in an axes so that data is in a left and right pane.
%
% breakXAxes(splitXLim) splitXLim is a 2 element vector containing a range
% of x values from splitXLim(1) to splitXLim(2) to remove from the axes.
% They must be within the current xLimis of the axes.
%
% breakXAxes(splitXLim,splitWidth) splitWidth is the distance to
% seperate the left and right side. Units are the same as
% get(AX,'uints') default is 0.015
%
% breakXAxes(splitXLim,splitWidth,yOverhang) yOverhang stretches the
% axis split graphic to extend past the top and bottom of the plot by
% the distance set by YOverhang. Units are the same as get(AX,'units')
% default value is 0.015
%
% breakXAxes(AX, ...) performs the operation on the axis specified by AX
%
function breakInfo = breakxaxis(varargin)
%Validate Arguements
if nargin < 1 || nargin > 4
error('Wrong number of arguements');
end
if isscalar(varargin{1}) && ishandle(varargin{1})
mainAxes = varargin{1};
argOffset = 1;
argCnt = nargin - 1;
if ~strcmp(get(mainAxes,'Type'),'axes')
error('Handle object must be Type Axes');
end
else
mainAxes = gca;
argOffset = 0;
argCnt = nargin;
end
if (strcmp(get(mainAxes,'XScale'),'log'))
error('Log X Axes are not supported');
end
if (argCnt < 3)
yOverhang = 0.015;
else
yOverhang = varargin{3 + argOffset};
if numel(yOverhang) ~= 1 || ~isreal(yOverhang) || ~isnumeric(yOverhang)
error('YOverhang must be a scalar number');
elseif (yOverhang < 0)
error('YOverhang must not be negative');
end
yOverhang = double(yOverhang);
end
if (argCnt < 2)
splitWidth = 0.015;
else
splitWidth = varargin{2 + argOffset};
if numel(yOverhang) ~= 1 || ~isreal(yOverhang) || ~isnumeric(yOverhang)
error('splitWidth must be a scalar number');
elseif (yOverhang < 0)
error('splitWidth must not be negative');
end
splitWidth = double(splitWidth);
end
splitXLim = varargin{1 + argOffset};
if numel(splitXLim) ~= 2 || ~isnumeric(splitXLim) || ~isreal(yOverhang)
error(splitXLim,'Must be a vector length 2');
end
splitXLim = double(splitXLim);
mainXLim = get(mainAxes,'XLim');
if (any(splitXLim >= mainXLim(2)) || any(splitXLim <= mainXLim(1)))
error('splitXLim must be in the range given by get(AX,''XLim'')');
end
mainPosition = get(mainAxes,'Position');
if (splitWidth > mainPosition(3) )
error('Split width is too large')
end
%We need to create 4 axes
% leftAxes - is used for the left x axis and left pane data
% rightAxes - is used to the right x axis and right pane data
% annotationAxes - is used to display the y axis and title
% breakAxes - this is an axes with the same size and position as main
% is it used to draw a seperator between the left and right side
%Grab Some Parameters from the main axis (e.g the one we are spliting)
mainXLim = get(mainAxes,'XLim');
mainYLim = get(mainAxes,'YLim');
mainPosition = get(mainAxes,'Position');
mainParent = get(mainAxes,'Parent');
mainWidth = mainPosition(3); %Positions have the format [left bottom width height]
%mainXRange = mainXLim(2) - mainXLim(1);
mainFigure = get(mainAxes,'Parent');
mainYColor = get(mainAxes,'YColor');
mainLineWidth = get(mainAxes,'LineWidth');
figureColor = get(mainFigure,'Color');
mainYTickLabelMode = get(mainAxes,'YTickLabelMode');
mainXLabel = get(mainAxes,'XLabel');
mainXDir = get(mainAxes,'XDir');
mainLayer = get(mainAxes,'Layer');
%Save Main Axis Z Order
figureChildren = get(mainFigure,'Children');
zOrder = find(figureChildren == mainAxes);
%Calculate where axesLeft and axesRight will be layed on screen
%And their respctive XLimits
leftXLimTemp = [mainXLim(1) splitXLim(1)];
rightXLimTemp = [splitXLim(2) mainXLim(2)];
leftXRangeTemp = leftXLimTemp(2) - leftXLimTemp(1);
rightXRangeTemp = rightXLimTemp(2) - rightXLimTemp(1);
leftWidthTemp = leftXRangeTemp / (leftXRangeTemp + rightXRangeTemp) * (mainWidth - splitWidth);
rightWidthTemp = rightXRangeTemp / (leftXRangeTemp + rightXRangeTemp) * (mainWidth - splitWidth);
leftStretch = (leftWidthTemp + splitWidth/2) / leftWidthTemp;
leftXRange = leftXRangeTemp * leftStretch;
leftWidth = leftWidthTemp * leftStretch;
rightStretch = (rightWidthTemp + splitWidth/2) / rightWidthTemp;
rightXRange = rightXRangeTemp * rightStretch;
rightWidth = rightWidthTemp * rightStretch;
leftXLim = [mainXLim(1) mainXLim(1)+leftXRange];
rightXLim = [mainXLim(2)-rightXRange mainXLim(2)];
if (strcmp(mainXDir, 'normal'))
leftPosition = mainPosition;
leftPosition(3) = leftWidth;
rightPosition = mainPosition;
rightPosition(1) = mainPosition(1) + leftWidth;
rightPosition(3) = rightWidth;
else
%Left Axis will actually go on the right side a vise versa
rightPosition = mainPosition;
rightPosition(3) = rightWidth;
leftPosition = mainPosition;
leftPosition(1) = mainPosition(1) + rightWidth;
leftPosition(3) = leftWidth;
end
%Create the Annotations layer, if the Layer is top, draw the axes on
%top (e.g. after) drawing the left and right pane
if strcmp(mainLayer,'bottom')
annotationAxes = CreateAnnotaionAxes(mainAxes,mainParent)
end
%Create and position the leftAxes. Remove all Y Axis Annotations, the
%title, and a potentially offensive tick mark
leftAxes = copyobj(mainAxes,mainParent);
set(leftAxes,'Position', leftPosition, ...
'XLim', leftXLim, ...
'YLim', mainYLim, ...
'YGrid' ,'off', ...
'YMinorGrid', 'off', ...
'YMinorTick','off', ...
'YTick', [], ...
'YTickLabel', [], ...
'box','off');
if strcmp(mainLayer,'bottom')
set(leftAxes,'Color','none');
end
delete(get(leftAxes,'YLabel'));
delete(get(leftAxes,'XLabel'));
delete(get(leftAxes,'Title'));
if strcmp(mainYTickLabelMode,'auto')
xTick = get(leftAxes,'XTick');
set(leftAxes,'XTick',xTick(1:(end-1)));
end
%Create and position the rightAxes. Remove all Y Axis annotations, the
%title, and a potentially offensive tick mark
rightAxes = copyobj(mainAxes,mainParent);
set(rightAxes,'Position', rightPosition, ...
'XLim', rightXLim, ...
'YLim', mainYLim, ...
'YGrid' ,'off', ...
'YMinorGrid', 'off', ...
'YMinorTick','off', ...
'YTick', [], ...
'YTickLabel', [], ...
'box','off');
if strcmp(mainLayer,'bottom')
set(rightAxes,'Color','none');
end
delete(get(rightAxes,'YLabel'));
delete(get(rightAxes,'XLabel'));
delete(get(rightAxes,'Title'));
if strcmp(mainYTickLabelMode,'auto')
xTick = get(rightAxes,'XTick');
set(rightAxes,'XTick',xTick(2:end));
end
%Create the Annotations layer, if the Layer is top, draw the axes on
%top (e.g. after) drawing the left and right pane
if strcmp(mainLayer,'top')
annotationAxes = CreateAnnotaionAxes(mainAxes,mainParent);
set(annotationAxes, 'Color','none');
end
%Create breakAxes, remove all graphics objects and hide all annotations
breakAxes = copyobj(mainAxes,mainParent);
children = get(breakAxes,'Children');
for i = 1:numel(children)
delete(children(i));
end
set(breakAxes,'Color','none');
%Stretch the breakAxes vertically to cover the horzontal axes lines
orignalUnits = get(breakAxes,'Units');
set(breakAxes,'Units','Pixel');
breakPosition = get(breakAxes,'Position');
nudgeFactor = get(breakAxes,'LineWidth');
breakPosition(4) = breakPosition(4) + nudgeFactor;
set(breakAxes,'Position',breakPosition);
set(breakAxes,'Units',orignalUnits);
%Stretch the breakAxes vertically to create an overhang for sylistic
%effect
breakPosition = get(breakAxes,'Position');
breakPosition(2) = breakPosition(2) - yOverhang;
breakPosition(4) = breakPosition(4) + 2*yOverhang;
set(breakAxes,'Position',breakPosition);
%Create a sine shaped patch to seperate the 2 sides
breakXLim = [mainPosition(1) mainPosition(1)+mainPosition(3)];
set(breakAxes,'xlim',breakXLim);
theta = linspace(0,2*pi,100);
yPoints = linspace(mainYLim(1),mainYLim(2),100);
amp = splitWidth/2 * 0.9;
xPoints1 = amp * sin(theta) + mainPosition(1) + leftWidthTemp;
xPoints2 = amp * sin(theta) + mainPosition(1) + mainPosition(3) - rightWidthTemp;
patchPointsX = [xPoints1 xPoints2(end:-1:1) xPoints1(1)];
patchPointsY = [yPoints yPoints(end:-1:1) yPoints(1)];
patch(patchPointsX,patchPointsY ,figureColor,'EdgeColor',figureColor,'Parent',breakAxes);
%Create A Line To Delineate the left and right edge of the patch
line('xData',xPoints1,'ydata',yPoints,'Parent',breakAxes,'Color',mainYColor,'LineWidth',mainLineWidth);
line('xData',xPoints2,'ydata',yPoints,'Parent',breakAxes,'Color',mainYColor,'LineWidth',mainLineWidth);
set(breakAxes,'Visible','off');
%Make the old main axes invisiable
invisibleObjects = RecursiveSetVisibleOff(mainAxes);
%Preserve the z-order of the figure
uistack([leftAxes rightAxes breakAxes annotationAxes],'down',zOrder-1)
%Set the rezise mode to position so that we can dynamically change the
%size of the figure without screwing things up
set([leftAxes rightAxes breakAxes annotationAxes],'ActivePositionProperty','Position');
%Playing with the titles labels etc can cause matlab to reposition
%the axes in some cases. Mannually force the position to be correct.
set([breakAxes annotationAxes],'Position',mainPosition);
%Save the axes so we can unbreak the axis easily
breakInfo = struct();
breakInfo.leftAxes = leftAxes;
breakInfo.rightAxes = rightAxes;
breakInfo.breakAxes = breakAxes;
breakInfo.annotationAxes = annotationAxes;
breakInfo.invisibleObjects = invisibleObjects;
end
function list = RecursiveSetVisibleOff(handle)
list = [];
list = SetVisibleOff(handle,list);
end
function list = SetVisibleOff(handle, list)
if (strcmp(get(handle,'Visible'),'on'))
set(handle,'Visible','off');
list = [list handle];
end
children = get(handle,'Children');
for i = 1:numel(children)
list = SetVisibleOff(children(i),list);
end
end
function annotationAxes = CreateAnnotaionAxes(mainAxes,mainParent)
%Create Annotation Axis, Remove graphics objects, XAxis annotations
%(except XLabel) and make background transparent
annotationAxes = copyobj(mainAxes,mainParent);
set(annotationAxes,'YLimMode','Manual');
children = get(annotationAxes,'Children');
for i = 1:numel(children)
delete(children(i));
end
%Save the xLabelpostion because it will move when we delete xAxis
%ticks
xLabel = get(annotationAxes,'XLabel');
xLabelPosition = get(xLabel,'Position');
set(annotationAxes,'XGrid' ,'off', ...
'XMinorGrid', 'off', ...
'XMinorTick','off', ...
'XTick', [], ...
'XTickLabel', []);
%Restore the pevious label postition
set(xLabel,'Position',xLabelPosition);
end
|
github
|
vitoruapt/lartkv5-master
|
ccvGetLaneDetectionStats.m
|
.m
|
lartkv5-master/src/perception/road/caltech_lanes/matlab/ccvGetLaneDetectionStats.m
| 5,767 |
utf_8
|
3b1a1bbdb2c02cde9f338e584d4523e4
|
function ccvGetLaneDetectionStats(detectionFiles, truthFiles)
% CCVGETLANEDETECTIONSTATS computes stats for the results compared to the
% ground truth
%
% INPUTS
% ------
% detectionFiles - a cell array of the detection files
% truthFiles - a cell array of the corresponding ground truth files
%
% OUTPUTS
% -------
%
% See also ccvLabel
%
% Thresholds for merging i.e. matching splines
meanDistThreshold = 15;
medianDistThreshold = 20;
% Initialize
allResults = [];
allDetectionTotal = 0;
allTruthTotal = 0;
allNumFrames = 0;
allTp = 0;
allFp = 0;
disp('------------------------------------------------------------------');
for d=1:length(detectionFiles)
%get detection and truth file
detectionFile = detectionFiles{d};
truthFile = truthFiles{d};
%load the ground truth
truths = ccvLabel('read', truthFile);
%load the detections file
detections = ccvReadLaneDetectionResultsFile(detectionFile);
%results for this file
results = [];
detectionTotal = 0;
truthTotal = 0;
numFrames = 0;
%progress index
prog = 0;
progress= '-\|/';
fprintf(1, '\n-');
%loop on results and compare splines
for i=1:length(detections)
%get frame
detectionFrame = detections(i);
detectionSplines = detectionFrame.splines;
%display progress
if mod(length(results), 10)==0
fprintf(1, '\b%s', progress(prog+1));
prog = mod(prog+1, length(progress));
end;
%get truth splines for that frame
truthFrame = ccvLabel('getFrame', truths, i);
if isempty(truthFrame), continue; end;
numFrames = numFrames + 1;
truthSplines = GetTruthSplines(truthFrame.labels);
%update totals
detectionTotal = detectionTotal + length(detectionSplines);
truthTotal = truthTotal + length(truthSplines);
%loop on these splines and compare to ground truth to get the closest
frameDetections = [];
truthDetections = zeros(1, length(truthSplines));
for j=1:length(detectionSplines)
%flag
detection = 0;
%loop on truth and get which one
k = 1;
while detection==0 && k<=length(truthSplines)
if ccvCheckMergeSplines(detectionSplines{j}, ...
truthSplines{k}, meanDistThreshold, ...
medianDistThreshold);
%not false pos
detection = 1;
truthDetections(k) = 1;
end;
%inc
k = k+1;
end; %while
%check result
result.score = detectionFrame.scores(j);
result.detection = detection;
results = [results, result];
frameDetections = [frameDetections, detection];
end; %for
%get number of missed splines
frameNumMissed = length(truthSplines) - length(find(frameDetections==1));
frameNumFalse = length(find(frameDetections==0));
end; % for i
%print out some stats
tp = length(find([results.detection]==1));
fp = length(find([results.detection]==0));
% numFrames = length(detections);
fprintf(1,'\n\n\n');
disp(sprintf('Detection File %d: %s', i, detectionFile));
disp(sprintf('Number of frames = %d', numFrames));
disp(' ');
disp(sprintf('Total detections = %d', detectionTotal));
disp(sprintf('Total truth = %d', truthTotal));
disp(' ');
disp(sprintf('Number of correct detections = %d', tp));
disp(sprintf('Number of false detections = %d', fp));
disp(' ');
disp(sprintf('Percentage of correct detections = %f', tp/truthTotal));
disp(sprintf('Percentage of false detections = %f', fp/truthTotal));
disp(' ');
disp(sprintf('False detections/frame= %f', fp/numFrames));
%put in total stats
allResults = [allResults, results];
allDetectionTotal = allDetectionTotal + detectionTotal;
allTruthTotal = allTruthTotal + truthTotal;
allNumFrames = allNumFrames + numFrames;
allTp = allTp + tp;
allFp = allFp + fp;
dResults{d} = results;
dDetectionTotal(d) = detectionTotal;
dTruthTotal(d) = truthTotal;
dNumFrames(d) = numFrames;
dTp(d) = tp;
dFp(d) = fp;
end; %for
fprintf(1,'\n\n\n');
disp('Overall results');
disp(sprintf('Number of frames = %d', allNumFrames));
disp(' ');
disp(sprintf('Total detections = %d', allDetectionTotal));
disp(sprintf('Total truth = %d', allTruthTotal));
disp(' ');
disp(sprintf('Number of correct detections = %d', allTp));
disp(sprintf('Number of false detections = %d', allFp));
disp(' ');
disp(sprintf('Percentage of correct detections = %f', allTp/allTruthTotal));
disp(sprintf('Percentage of false detections = %f', allFp/allTruthTotal));
disp(' ');
disp(sprintf('False detections/frame= %f', allFp/allNumFrames));
fprintf(1,'\n\n\n-----');
disp('Summary results');
for d=1:length(dDetectionTotal)
disp(' ');
disp(sprintf('Detection %s', detectionFile));
disp(sprintf('Total = %d', dTruthTotal(d)));
disp(sprintf('Total detections = %d', dDetectionTotal(d)));
disp(sprintf('correct detections = %.2f', 100*dTp(d)/dTruthTotal(d)));
disp(sprintf('false detections = %.2f', 100*dFp(d)/dTruthTotal(d)));
disp(sprintf('false detections / frame = %.3f', dFp(d)/dNumFrames(d)));
end;
% ---------------------------------------------------------------------------
function splines = GetTruthSplines(labels)
% returns splines in the labels as a cell array of splines
splines = {};
for i=1:length(labels)
if strcmp(labels(i).type, 'spline')
splines{end+1} = labels(i).points;
end;
end;
|
github
|
vitoruapt/lartkv5-master
|
ccvLabel.m
|
.m
|
lartkv5-master/src/perception/road/caltech_lanes/matlab/ccvLabel.m
| 9,282 |
utf_8
|
a4cfee3bd06cea44bcb2ba59e53582b8
|
function varargout = ccvLabel(f, varargin)
% CCVLABEL performs different tasks on the label structure, like creating
% new structure, adding frames, labels, ...etc.
%
% INPUTS
% ------
% f - the input function to perform
% varargin - the rest of the inputs (potentially zero)
%
% OUTPUTS
% -------
% varargout - the outputs from the selected operation
%
% See also ccvLabeler
%
% AUTHOR - Mohamed Aly <[email protected]>
% DATE - May 26, 2009
%
%check if we have a valid input function
if isempty(f) || ~exist(f, 'file'), error('Please enter a valid function'); end;
%call the function
varargout = cell(1, nargout);
[varargout{:}] = feval(f, varargin{:});
end
function ld = create()
% NEW creates a new empty structure
%
% INPUTS
% ------
%
% OUTPUTS
% -------
% ld - the output empty label data
%
ld.version = 0;
ld.source = 'image';
ld.frames = struct('frame', {}, ...
'labels', struct('points',{}, 'type',{}, 'subtype',{}, 'obj',{}));
ld.objects = struct('id',{});
end
function ld = read(fname)
% READ loads label data from a file
%
% INPUTS
% ------
% fname - the input file name
%
% OUTPUTS
% -------
% ld - the output empty label data
%
%load the file
ld = [];
try
load(fname, '-mat');
catch
return;
end;
%check version
if ~exist('ld', 'var') || ~ld.version<0
error('invalid input file');
end;
%check objects
if ~isfield(ld,'objects'), ld.objects = []; end;
end
function write(fname, ld) %#ok<INUSD>
% WRITE saves label data to a file
%
% INPUTS
% ------
% fname - the input file name
% ld - the input label data
%
% OUTPUTS
% -------
%
%load the file
save(fname, 'ld', '-mat');
end
function [obj] = createObj(objId)
% CREATEOBJ creates a new object and returns it
%
% INPUTS
% ------
% objId - the object id of the new object
%
% OUTPUTS
% -------
% obj - the new obj
%
obj = struct('id', objId);
end
function [ld, objId] = addObj(ld)
% ADDOBJ adds a new object and returns the object id
%
% INPUTS
% ------
% ld - the input label data
%
% OUTPUTS
% -------
% ld - the output label data
% objId - the id of the new object added
%
%get id of new object
objId = max([ld.objects.id]) + 1;
if isempty(objId), objId = 1; end;
%add it
ld.objects = [ld.objects createObj(objId)];
end
function ld = removeObj(ld, objId)
% REMOVEOBJ deletes an object and clears objects of every label with that
% object id
%
% INPUTS
% ------
% ld - the input label data
% objId - the id of the object to remove
%
% OUTPUTS
% -------
% ld - the output label data
%
%get index of object
objInd = find([ld.objects.id] == objId);
%make sure it's valid
if ~isempty(objInd)
%clear it
ld.objects(objInd) = [];
%update all labels with that object id, loop all frames and check
for f=1:length(ld.frames)
%reset labels with that object label
for l=1:length(ld.frames(f).labels)
if ld.frames(f).labels(l).obj == objId,
ld.frames(f).labels(l).obj = [];
end;
end;
% lbls = find([ld.frames(f).labels.obj] == objId);
% for l=lbls, ld.frames(f).labels(l).obj = []; end;
end;
end; %if
end
function [objIds] = getObjIds(ld)
% GETOBJIDS returns the object ids present
%
% INPUTS
% ------
% ld - the input label data
%
% OUTPUTS
% -------
% objIds - the list of object ids
%
%get ids of objects
objIds = [ld.objects.id];
end
function nframes = nFrames(ld)
% NFRAMES returns the number of frames
%
% INPUTS
% ------
% ld - the input label data
%
% OUTPUTS
% -------
% nframes - the number of frames
%
%get the frame
nframes = length(ld.frames);
end
function frame = getFrame(ld, frameIdx)
% GETFRAME returns the required frame
%
% INPUTS
% ------
% ld - the input label data
% frameIdx - the frame index
%
% OUTPUTS
% -------
% frame - the returned frame, which is a structure with fields
% .frame - the index or file name of the frame
% .labels - the array of labels in this frame
%
%get the frame
frame = ld.frames(frameIdx);
end
function frm = createFrame(frame, labels)
% CREATEFRAME creates a new frame
%
% INPUTS
% ------
% frame - the frame id or file name
% labels - the frame labels
%
% OUTPUTS
% -------
% frm - the output new frame
%
if nargin<1, frame = []; end;
if nargin<2, labels = createLabel(); end;
%create the new frame
frm = struct('frame',frame, 'labels',labels);
end
function [ld, frameIdx] = addFrame(ld, frame, labels)
% ADDFRAME adds a frame into the data structure
%
% INPUTS
% ------
% ld - the input label data
% frame - the frame id or file name
% labels - the frame labels
%
% OUTPUTS
% -------
% ld - the update ld structure
% frameIdx - the index of the new frame
%
if nargin<2, frame = []; end;
if nargin<3, labels = createLabel(); end;
%get the frame index
frameIdx = length(ld.frames) + 1;
%put the new frame
ld.frames(frameIdx) = createFrame(frame, labels);
end
function ld = removeFrame(ld, frameIdx)
% REMOVEFRAME removes the frame
%
% INPUTS
% ------
% ld - the input label data
% frameIdx - the frame index
%
% OUTPUTS
% -------
% ld - the update ld structure
%
%remove the frame
ld.frames(frameIdx) = [];
end
function label = createLabel(points, type, subtype, objId)
% CREATELABEL creates a new label
%
% INPUTS
% ------
% points - the points for that label
% type - the type of label
% subtype - the subtype of the label
% objId - the objId of the label
%
% OUTPUTS
% -------
% ld - the output updated label data
%
if nargin<1, points = {}; end;
if nargin<2, type = []; end;
if nargin<3, subtype = []; end;
if nargin<4, objId = []; end;
%create a new label
label = struct('points',points, 'type',type, ...
'subtype',subtype, 'obj',objId);
end
function nl = nLabels(ld, frameIdx)
% NLABELS gets the number of labels in the required frame
%
% INPUTS
% ------
% ld - the input label data
% frameIdx - the frame index
%
% OUTPUTS
% -------
% nl - the number of labels
%
nl = length(ld.frames(frameIdx).labels);
end
function [ld, lblIdx] = addLabel(ld, frameIdx, points, type, subtype, objId)
% ADDLABEL adds a new label
%
% INPUTS
% ------
% ld - the input label data
% frameIdx - the frame index
% points - the points for that label or the label structure if given
% type - the type of label
% subtype - the subtype of the label
% objId - the objId of the label
%
% OUTPUTS
% -------
% ld - the output updated label data
% lblIdx - the new label index
%
if nargin<3, points = []; end;
if nargin<4, type = []; end;
if nargin<5, subtype = []; end;
if nargin<6, objId = []; end;
%get the new label index
lblIdx = nLabels(ld, frameIdx) + 1;
%create the new label if not a struct
if isstruct(points), label = points;
else label = createLabel(points, type, subtype, objId);
end;
%add the label to the required frame
ld.frames(frameIdx).labels(lblIdx) = label;
end
function ld = updateLabel(ld, frameIdx, lblIdx, points, type, subtype, objId)
% UPDATELABEL updates an existing label
%
% INPUTS
% ------
% ld - the input label data
% frameIdx - the frame id
% lblIdx - the index of the label to change
% points - the points for that label (don't change if nan). It can also
% be a structure, in which case it is a label structure,
% so just replace it
% type - the type of label (don't change if nan)
% subtype - the subtype of the label (don't change if nan)
% objId - the objId of the label (don't change if nan)
%
% OUTPUTS
% -------
% ld - the output updated label data
%
%check if just to replace it
if nargin>=4 && isstruct(points)
label = points;
%we are passaed in independent components of the labels
else
%get the label
label = ld.frames(frameIdx).labels(lblIdx);
%update the label
if nargin>=7 && ~any(isnan(objId)), label.obj = objId; end;
if nargin>=6 && ~any(isnan(subtype)), label.subtype = subtype; end;
if nargin>=5 && ~any(isnan(type)), label.type = type ; end;
if nargin>=4 && ~any(any(isnan(points))), label.points = points; end;
end;
%put it back
ld.frames(frameIdx).labels(lblIdx) = label;
end
function label = getLabel(ld, frameIdx, lblIdx)
% GETLABEL retuns the required label
%
% INPUTS
% ------
% ld - the input label data
% frameIdx - the frame index
% lblIdx - the index of the label to return. If empty or absent, then
% return the labels in this frame
%
% OUTPUTS
% -------
% label - the returned label(s), which is a structure with fields
% .points - the label points
% .type - the label type
% .subtype - the label subtype
% .obj - the label object id
%
%get the label
if nargin<3 || isempty(lblIdx)
lblIdx = 1:length(ld.frames(frameIdx).labels);
end;
%return
label = ld.frames(frameIdx).labels(lblIdx);
end
function ld = removeLabel(ld, frameIdx, lblIdx)
% REMOVELABEL removes a label
%
% INPUTS
% ------
% ld - the input label data
% frameIdx - the frame id
% lblIdx - the index of the label to remove
%
% OUTPUTS
% -------
% ld - the output updated label data
%
%remove the label
ld.frames(frameIdx).labels(lblIdx) = [];
end
|
github
|
VIP-Group/DBP-master
|
DBP_detector_sim.m
|
.m
|
DBP-master/uplink/DBP_detector_sim.m
| 13,321 |
utf_8
|
15048a8d5848729bdbfbb43738f311f9
|
% =========================================================================
% Decentralized UPLINK simulator for the paper
% "Decentralized Baseband Processing for Massive MU-MIMO Systems"
% -------------------------------------------------------------------------
% Revision history:
%
% - aug-13-2017 v0.1 cs: simplified and commented code for GitHub
%
% -------------------------------------------------------------------------
% (c) 2017 Christoph Studer; e-mail: [email protected]
% -------------------------------------------------------------------------
% If you are using the simulator (or parts of it) for a publication, then
% you MUST cite our paper:
%
% K. Li, R. Sharan, Y. Chen, T. Goldstein, J. R. Cavallaro, and C. Studer,
% "Decentralized Baseband Processing for Massive MU-MIMO Systems",
% IEEE J. Emerging and Sel. Topics in Circuits and Systems (JETCAS)
% to appear in 2017
%
% and clearly mention this in your paper.
%=========================================================================
function res = DBP_detector_sim(varargin)
% -- set up default/custom parameters
if isempty(varargin)
disp('using default simulation settings and parameters...')
% set default simulation parameters
par.runID = 0; % simulation ID (used to reproduce results)
par.B = 128; % receive antennas
par.U = 8; % transmit antennas (set not larger than MR!)
par.mod = '16QAM'; % modulation type: 'BPSK','QPSK','16QAM','64QAM'
par.trials = 1000; % number of Monte-Carlo trials (transmissions)
par.SNRdB_list = -4:4:16; % list of SNR [dB] values to be simulated
% select data detector to be used
% centralized : `ZF`, `uMMSE', 'SIMO'
% decentralized : CG-based `DUCG_ZF`, `DUCG_MMSE`
% ADMM-based 'DZF', `DMMSE', 'DBOX'
par.detector = 'DMMSE';
par.vers = 'SxS2'; % inverse: 'UxU1', 'SxS1', 'SxS2' (only for ADMM)
par.CHEST = 'on'; % channel estimation errors 'on' or 'off'
par.plot = 'on'; % plot results? 'on' or 'off'
par.save = 'on'; % save results? 'on' or 'off'
% parameters for DBP (see paper)
par.C = 8; % number of clusters
par.maxiter = 5; % maximum algorithm iterations (for CG and ADMM)
par.rho = 7; % tuning parameter: regularizer (only for ADMM)
par.gamma = 2; % tuning parameters: step size (only for ADMM)
%
else
disp('use custom simulation settings and parameters...')
par = varargin{1}; % only argument is par structure
end
% -- initialization
% use runId random seed (enables reproducibility)
rng(par.runID);
% generate reasonable filename
par.simName = ['ERR_UL_' num2str(par.B) 'x' num2str(par.U) '_' par.mod '_' par.detector '_rho' num2str(par.rho) '_gamma' num2str(par.gamma) ]; % simulation name (used for saving results)
% set up Gray-mapped constellation alphabet (according to IEEE 802.11)
switch (par.mod)
case 'BPSK',
par.symbols = [ -1 1 ];
case 'QPSK',
par.symbols = [ -1-1i,-1+1i, ...
+1-1i,+1+1i ];
case '16QAM',
par.symbols = [ -3-3i,-3-1i,-3+3i,-3+1i, ...
-1-3i,-1-1i,-1+3i,-1+1i, ...
+3-3i,+3-1i,+3+3i,+3+1i, ...
+1-3i,+1-1i,+1+3i,+1+1i ];
case '64QAM',
par.symbols = [ -7-7i,-7-5i,-7-1i,-7-3i,-7+7i,-7+5i,-7+1i,-7+3i, ...
-5-7i,-5-5i,-5-1i,-5-3i,-5+7i,-5+5i,-5+1i,-5+3i, ...
-1-7i,-1-5i,-1-1i,-1-3i,-1+7i,-1+5i,-1+1i,-1+3i, ...
-3-7i,-3-5i,-3-1i,-3-3i,-3+7i,-3+5i,-3+1i,-3+3i, ...
+7-7i,+7-5i,+7-1i,+7-3i,+7+7i,+7+5i,+7+1i,+7+3i, ...
+5-7i,+5-5i,+5-1i,+5-3i,+5+7i,+5+5i,+5+1i,+5+3i, ...
+1-7i,+1-5i,+1-1i,+1-3i,+1+7i,+1+5i,+1+1i,+1+3i, ...
+3-7i,+3-5i,+3-1i,+3-3i,+3+7i,+3+5i,+3+1i,+3+3i ];
end
% extract average symbol energy
par.Es = mean(abs(par.symbols).^2);
% precompute bit labels
par.Q = log2(length(par.symbols)); % number of bits per symbol
par.bits = de2bi(0:length(par.symbols)-1,par.Q,'left-msb');
% track simulation time
time_elapsed = 0;
% -- start simulation
% initialize result arrays (detector x SNR)
switch (par.detector)
case {'DZF','DMMSE','DBOX','DUCG_MMSE','DUCG_ZF'}
par.distr = 1;
otherwise
par.distr = 0;
par.maxiter = 1;
end
res.par = par; % store param array
res.VER = zeros(par.maxiter,length(par.SNRdB_list)); % vector error rate
res.SER = zeros(par.maxiter,length(par.SNRdB_list)); % symbol error rate
res.BER = zeros(par.maxiter,length(par.SNRdB_list)); % bit error rate
% generate random bit stream (antenna x bit x trial)
bits = randi([0 1],par.U,par.Q,par.trials);
%initialize parameters for ADMM
% trials loop
disp('run simulation...')
tic
for t=1:par.trials
% generate transmit symbol
idx = bi2de(bits(:,:,t),'left-msb')+1;
s = par.symbols(idx).';
% generate iid Gaussian channel matrix & noise vector
n = sqrt(0.5)*(randn(par.B,1)+1i*randn(par.B,1));
H = sqrt(0.5)*(randn(par.B,par.U)+1i*randn(par.B,par.U));
NH = sqrt(0.5)*(randn(par.B,par.U)+1i*randn(par.B,par.U)); % used for CHEST
% transmit over noiseless channel (will be used later)
x = H*s;
% SNR loop
for k=1:length(par.SNRdB_list)
% compute noise variance (average SNR per receive antenna is: SNR=MT*Es/N0)
N0 = par.U*par.Es*10^(-par.SNRdB_list(k)/10);
% transmit data over noisy channel
y = x+sqrt(N0)*n;
% model channel estimation errors (CHEST)
switch (par.CHEST)
case 'on'
Hest = H + sqrt(N0/par.U/par.Es)*NH; % errors proportional to SNR
otherwise % assume perfect CSI
Hest = H;
end
% select algorithms
switch (par.detector)
case 'ZF', % zero-forcing detection
[idxhat,bithat] = ZF(par,Hest,y);
case 'MMSE', % unbiased MMSE detector
[idxhat,bithat] = MMSE(par,Hest,y,N0);
case 'SIMO', % SIMO lower bound
[idxhat,bithat] = SIMO(par,Hest,y,s); % also pass true signal
case {'DUCG_MMSE','DUCG_ZF'} % conjuage gradients
[idxhat,bithat] = DUCG(par,Hest,y,N0);
case {'DZF','DMMSE','DBOX'} % ADMM based method
[idxhat,bithat] = DU(par,Hest,y,N0);
otherwise,
error('par.detector type not defined.')
end
% -- compute error metrics
for l = 1:size(idxhat,2)
[VER,SER,BER] = getError(par,idxhat(:,l),bithat(:,:,l),idx,bits(:,:,t));
res.VER(l,k) = res.VER(l,k) + VER;
res.SER(l,k) = res.SER(l,k) + SER;
res.BER(l,k) = res.BER(l,k) + BER;
end
end % SNR loop
% keep track of simulation time
if toc>10
time=toc;
time_elapsed = time_elapsed + time;
fprintf('estimated remaining simulation time: %3.0f min.\n',time_elapsed*(par.trials/t-1)/60);
tic
end
end % trials loop
% -- normalize results
res.VER = res.VER/par.trials;
res.SER = res.SER/par.trials;
res.BER = res.BER/par.trials;
res.time_elapsed = time_elapsed + toc;
% -- save final results (par and res structure)
if strcmp(par.save,'on')
if ~exist('results','dir')
mkdir results
end
save([ 'results' filesep par.simName ],'res');
end
% -- show results (generates fairly nice Matlab plot)
if strcmp(par.plot,'on')
marker_style = {'bo-','rs--','mv-.','kp:','g*-','c>--','yx:'};
plot_list = unique(round(logspace(0,log10(par.maxiter),7)));
figure(1)
for d=1:length(plot_list)
if d==1
semilogy(par.SNRdB_list,res.BER(d,:),marker_style{d},'LineWidth',2)
hold on
else
semilogy(par.SNRdB_list,res.BER(d,:),marker_style{d},'LineWidth',2)
end
end
hold off
grid on
xlabel('average SNR per receive antenna [dB]','FontSize',12)
ylabel('uncoded bit error rate (BER)','FontSize',12)
axis([min(par.SNRdB_list) max(par.SNRdB_list) 1e-4 1])
if par.distr
l = cell(1,length(plot_list));
for i = 1:length(plot_list)
l{i} = ['Iteration ' num2str(plot_list(i))];
end
legend(l,'Fontsize',18)
end
set(gca,'FontSize',12)
end
end
% -- data detector functions
%% zero-forcing (ZF) detector
function [idxhat,bithat] = ZF(par,H,y)
xhat = H\y;
[~,idxhat] = min(abs(xhat*ones(1,length(par.symbols))-ones(par.U,1)*par.symbols).^2,[],2);
bithat = par.bits(idxhat,:);
end
%% unbiased MMSE detector (MMSE)
function [idxhat,bithat] = MMSE(par,H,y,N0)
W = (H'*H+(N0/par.Es)*eye(par.U))\(H');
xhat = W*y;
G = real(diag(W*H));
[~,idxhat] = min(abs(xhat*ones(1,length(par.symbols))-G*par.symbols).^2,[],2);
bithat = par.bits(idxhat,:);
end
%% SIMO lower bound
function [idxhat,bithat] = SIMO(par,Hest,y,sTrue)
y_tilde = y-Hest*sTrue;
% -- MMSE detection main loop
for n=1:par.U
% interference cancellation (with known data)
y_SIMO = y_tilde + Hest(:,n)*sTrue(n);
% do optimal SIMO detection for interference-free system
xhat(n,1) = Hest(:,n)'*y_SIMO/norm(Hest(:,n),2)^2;
end
[~,idxhat] = min(abs(xhat*ones(1,length(par.symbols))-ones(par.U,1)*par.symbols).^2,[],2);
bithat = par.bits(idxhat,:);
end
%% find nearest neighbors
function [idxhat,bithat] = getEstimate(par,xhat)
[~,idxhat] = min(abs(xhat*ones(1,length(par.symbols))-ones(par.U,1)*par.symbols).^2,[],2);
bithat = par.bits(idxhat,:);
end
%% get error
function [VER,SER,BER] = getError(par,idxhat,bithat,idx,bits)
err = (idx~=idxhat);
VER = any(err);
SER = sum(err)/par.U;
BER = sum(sum(bits~=bithat))/(par.U*par.Q);
end
%% ADMM-based decentralized uplink detectors
function [idxhat,bithat] = DU(par,H,y,N0)
idxhat = zeros(par.U,par.maxiter);
bithat = zeros(par.U,par.Q,par.maxiter);
lambda = zeros(par.U,par.C);
z_c = zeros(par.U,par.C);
s = zeros(par.U,1);
S = par.B/par.C;
switch (par.detector)
case 'DMMSE'
reg = par.C+N0/(par.Es*par.rho);
otherwise % Do not regularize for ZF and BOX
reg = par.C;
end
% -- preprocessing
for c=1:par.C
H_c(:,:,c) = H(S*(c-1)+1:S*c,:); %get the appropriate part of H
y_c = y(S*(c-1)+1:S*c);
switch (par.vers)
case 'SxS1'
Ainv(:,:,c) = inv(H_c(:,:,c)*H_c(:,:,c)'+eye(S)*par.rho);
y_reg(:,c) = H_c(:,:,c)'*(Ainv(:,:,c)*y_c);
case 'SxS2'
Ainv(:,:,c) = inv(H_c(:,:,c)*H_c(:,:,c)'+eye(S)*par.rho);
Gtmp = H_c(:,:,c)'*Ainv(:,:,c);
y_reg(:,c) = Gtmp*y_c;
G(:,:,c) = Gtmp*H_c(:,:,c);
case 'UxU1'
Binv(:,:,c) = inv(H_c(:,:,c)'*H_c(:,:,c)+eye(par.U)*par.rho);
y_reg(:,c) = Binv(:,:,c)*(H_c(:,:,c)'*y_c);
otherwise
error('par.vers not defined')
end
end
% -- detection loop
for l = 1:par.maxiter
for c = 1:par.C %local minimization step
switch (par.vers)
case 'SxS1'
z_c(:,c) = y_reg(:,c) + ( (s - lambda(:,c)) - H_c(:,:,c)'*(Ainv(:,:,c)*(H_c(:,:,c)*(s - lambda(:,c)))) );
case 'SxS2'
z_c(:,c) = y_reg(:,c) + ( (s - lambda(:,c)) - G(:,:,c)*(s - lambda(:,c))) ;
case 'UxU1'
z_c(:,c) = y_reg(:,c) + par.rho*(Binv(:,:,c)*(s - lambda(:,c)));
end
end
switch (par.detector)
case 'DBOX'
s = sum((z_c + lambda),2)/(reg); %global averaging step
s = projinf(par,s,max(real(par.symbols))); % experimental box regularizer
otherwise
s = sum((z_c + lambda),2)/(reg); %global averaging step
end
% update lagrange multiplier
for c = 1:par.C
lambda(:,c) = lambda(:,c) + par.gamma*(z_c(:,c) - s);
end
[idxhat(:,l),bithat(:,:,l)] = getEstimate(par,s);
end
end
% project onto alpha infinity-tilde-norm ball
function sproj = projinf(par,s,alpha)
sr = real(s);
idxr = abs(sr)>alpha;
sr(idxr) = sign(sr(idxr))*alpha;
si = imag(s);
idxi = abs(si)>alpha;
si(idxi) = sign(si(idxi))*alpha;
if strcmp(par.mod,'BPSK')
sproj = sr;
else
sproj = sr + 1i*si;
end
end % ADMM methods
%% decentralized uplink via decentralized CG
function [idxhat,bithat] = DUCG(par,H,y,N0)
% initialization
S = par.B/par.C;
H_c = zeros(S,par.U,par.C);
yMRC_c = zeros(par.U,par.C);
% distributed preprocessing (iteration 1)
for c=1:par.C
H_c(:,:,c) = H(S*(c-1)+1:S*c,:); % get the appropriate part of H
yMRC_c(:,c) = H_c(:,:,c)'*y(S*(c-1)+1:S*c); % compute local MRC
end
% centralized processing
r = sum(yMRC_c,2); % sum row-wise
p = r ;
rsold = r'*r;
x = zeros(par.U,1);
Ap_c = zeros(par.U,par.C);
% inner loop = equalization stage (iterations 2,3,...)
for l=1:par.maxiter
% decentralized matrix processing
for c=1:par.C
Ap_c(:,c) = H_c(:,:,c)'*(H_c(:,:,c)*p);
end
% centralized processing (MMSE)
switch par.detector
case 'DUCG_MMSE'
Ap = sum(Ap_c,2) + (N0/par.Es)*p;
case 'DUCG_ZF'
Ap = sum(Ap_c,2);
end
% conventional CG updates
alpha = rsold/(p'*Ap);
x = x + alpha*p;
r = r - alpha*Ap;
rsnew = r'*r;
p = r + (rsnew/rsold)*p;
rsold = rsnew;
% get estimates
[idxhat(:,l),bithat(:,:,l)] = getEstimate(par,x);
end
end % DUCG
|
github
|
VIP-Group/DBP-master
|
DBP_precoder_sim.m
|
.m
|
DBP-master/downlink/DBP_precoder_sim.m
| 10,550 |
utf_8
|
1ee2ead02cd6045fb55ef5a1f4b75d1b
|
% =========================================================================
% Decentralized DOWNLINK simulator for the paper
% "Decentralized Baseband Processing for Massive MU-MIMO Systems"
% -------------------------------------------------------------------------
% Revision history:
%
% - aug-13-2017 v0.1 cs: simplified and commented code for GitHub
%
% -------------------------------------------------------------------------
% (c) 2017 Christoph Studer; e-mail: [email protected]
% -------------------------------------------------------------------------
% If you are using the simulator (or parts of it) for a publication, then
% you MUST cite our paper:
%
% K. Li, R. Sharan, Y. Chen, T. Goldstein, J. R. Cavallaro, and C. Studer,
% "Decentralized Baseband Processing for Massive MU-MIMO Systems",
% IEEE J. Emerging and Sel. Topics in Circuits and Systems (JETCAS)
% to appear in 2017
%
% and clearly mention this in your paper.
%=========================================================================
function res = DBP_precoder_sim(varargin)
% -- set up default/custom parameters
if isempty(varargin)
disp('using default simulation settings and parameters...')
% set default simulation parameters
par.runId = 0; % simulation ID (used to reproduce results)
par.U = 8; % user antennas
par.B = 128; % BS antennas
par.mod = '16QAM'; % modulation type: 'BPSK','QPSK','16QAM','64QAM'
par.trials = 1000; % number of Monte-Carlo trials (transmissions)
par.SNRdB_list = 0:4:20; % list of SNR [dB] values to be simulated
% select precoder to be used
% centralized : `ZF`, `MRC'
% decentralized : 'DP' as described in Algorithm 3
par.precoder = 'DP'; % select precoder scheme 'MRC', ''
par.CHEST = 'on'; % channel estimation 'on' or 'off'
par.plot = 'on'; % plot results 'on' or 'off'
par.save = 'on'; % save results: 'on' or 'off'
% parameters for DBP (see paper)
par.C = 8; % number of clusters
par.vers = 'SxS1'; % inverse: 'UxU1' or 'SxS1' or 'UxU2' or 'SxS2'
par.maxiter = 5; % maximum algorithm iterations
par.rho = 1; % tuning parameter: regularizer (only for ADMM)
par.gamma = 1; % tuning parameters: step size (only for ADMM)
par.epsilon = 0.0; % precoder accuracy (0 = ZF precoding)
else
disp('use custom simulation settings and parameters...')
par = varargin{1}; % only argument is par structure
end
% -- initialization
% use runId random seed (enables reproducibility)
rng(par.runId);
% generate reasonable filename
par.simName = ['ERR_DL_' num2str(par.B) 'x' num2str(par.U) '_' par.mod '_' par.precoder '_rho' num2str(par.rho) '_gamma' num2str(par.gamma) ]; % simulation name (used for saving results)
% set up Gray-mapped constellation alphabet (according to IEEE 802.11)
switch (par.mod)
case 'BPSK',
par.symbols = [ -1 1 ];
case 'QPSK',
par.symbols = [ -1-1i,-1+1i, ...
+1-1i,+1+1i ];
case '16QAM',
par.symbols = [ -3-3i,-3-1i,-3+3i,-3+1i, ...
-1-3i,-1-1i,-1+3i,-1+1i, ...
+3-3i,+3-1i,+3+3i,+3+1i, ...
+1-3i,+1-1i,+1+3i,+1+1i ];
case '64QAM',
par.symbols = [ -7-7i,-7-5i,-7-1i,-7-3i,-7+7i,-7+5i,-7+1i,-7+3i, ...
-5-7i,-5-5i,-5-1i,-5-3i,-5+7i,-5+5i,-5+1i,-5+3i, ...
-1-7i,-1-5i,-1-1i,-1-3i,-1+7i,-1+5i,-1+1i,-1+3i, ...
-3-7i,-3-5i,-3-1i,-3-3i,-3+7i,-3+5i,-3+1i,-3+3i, ...
+7-7i,+7-5i,+7-1i,+7-3i,+7+7i,+7+5i,+7+1i,+7+3i, ...
+5-7i,+5-5i,+5-1i,+5-3i,+5+7i,+5+5i,+5+1i,+5+3i, ...
+1-7i,+1-5i,+1-1i,+1-3i,+1+7i,+1+5i,+1+1i,+1+3i, ...
+3-7i,+3-5i,+3-1i,+3-3i,+3+7i,+3+5i,+3+1i,+3+3i ];
end
% extract average symbol energy
par.Es = mean(abs(par.symbols).^2);
% normalize so that transmit vector s has unit norm
par.symbols = par.symbols/sqrt(mean(abs(par.symbols).^2))/sqrt(par.U);
% precompute bit labels
par.Q = log2(length(par.symbols)); % number of bits per symbol
par.bits = de2bi(0:length(par.symbols)-1,par.Q,'left-msb');
% track simulation time
time_elapsed = 0;
% -- start simulation
% extract cluster size
par.S = par.B/par.C; % cluster size
% initialize result arrays (detector x SNR)
if ~strcmp(par.precoder,'DP')
par.maxiter = 1;
par.distr = 0;
else
par.distr = 1;
end
res.par = par; % save parameter structure
res.VER = zeros(par.maxiter,length(par.SNRdB_list)); % vector error rate
res.SER = zeros(par.maxiter,length(par.SNRdB_list)); % symbol error rate
res.BER = zeros(par.maxiter,length(par.SNRdB_list)); % bit error rate
% generate random bit stream (antenna x bit x trial)
bits = randi([0 1],par.U,par.Q,par.trials);
% trials loop
tic
for t=1:par.trials
% generate transmit symbol
idx = bi2de(bits(:,:,t),'left-msb')+1;
s = par.symbols(idx).'; % create unit-norm transmit vector
% generate iid Gaussian channel matrix & noise vector
n = sqrt(0.5)*(randn(par.U,1)+1i*randn(par.U,1));
H = sqrt(0.5)*(randn(par.U,par.B)+1i*randn(par.U,par.B));
NH = sqrt(0.5)*(randn(par.U,par.B)+1i*randn(par.U,par.B)); % used for CHEST
% TX side processing
switch (par.precoder)
case 'ZF' % ZF beamforming
x = pinv(H)*s;
case 'MRC' % MRC beamforming
x = H'*(s./sum(abs(H).^2,2));
case 'DP' % decentralized precoding
x = DP(par,H,s);
otherwise,
error('par.precoder type not defined.')
end
% SNR loop
for k=1:length(par.SNRdB_list)
% iteration loop
for l = 1:par.maxiter
par.Ex = norm(x(:,l),2)^2;
% compute noise variance (average SNR per receive antenna is: SNR=MT*Es/N0)
N0 = par.Ex*10^(-par.SNRdB_list(k)/10);
% channel estimation (CHEST)
switch (par.CHEST)
case 'on'
Hest = H + sqrt(N0/par.Ex)*NH; % error happens in uplink
otherwise % assume perfect CHEST
Hest = H;
end
% transmit over noiseless channel
Hx = Hest*x(:,l);
% transmit data over noisy channel
y = Hx+sqrt(N0)*n;
[~,idxhat] = min(abs(y*ones(1,length(par.symbols))-ones(par.U,1)*par.symbols).^2,[],2);
bithat = par.bits(idxhat,:);
% -- compute error and complexity metrics
err = (idx~=idxhat);
res.VER(l,k) = res.VER(l,k) + any(err);
res.SER(l,k) = res.SER(l,k) + sum(err)/par.U;
res.BER(l,k) = res.BER(l,k) + sum(sum(bits(:,:,t)~=bithat))/(par.U*par.Q);
end % iteration loop
end % SNR loop
% keep track of simulation time
if toc>10
time=toc;
time_elapsed = time_elapsed + time;
fprintf('estimated remaining simulation time: %3.0f min.\n',time_elapsed*(par.trials/t-1)/60);
tic
end
end % trials loop
% normalize results
res.VER = res.VER/par.trials;
res.SER = res.SER/par.trials;
res.BER = res.BER/par.trials;
res.time_elapsed = time_elapsed + toc;
% -- save final results (res structure)
if strcmp(par.save,'on')
if ~exist('results','dir')
mkdir results
end
save([ 'results' filesep par.simName ],'res');
end
% -- show results (generates fairly nice Matlab plot)
if strcmp(par.plot,'on')
marker_style = {'bo-','rs--','mv-.','kp:','g*-','c>--','yx:'};
h=figure(1);
plot_list = unique(round(logspace(0,log10(par.maxiter),7)));
for d=1:length(plot_list)
if d==1
semilogy(par.SNRdB_list,res.SER(plot_list(d),:),marker_style{d},'LineWidth',2)
hold on
else
semilogy(par.SNRdB_list,res.SER(plot_list(d),:),marker_style{d},'LineWidth',2)
end
end
hold off
grid on
xlabel('average SNR per receive antenna [dB]','FontSize',12)
ylabel('uncoded symbol error rate (SER)','FontSize',12)
axis([min(par.SNRdB_list) max(par.SNRdB_list) 1e-4 1])
if par.distr
l = cell(1,length(plot_list));
for i = 1:length(plot_list)
l{i} = ['Iteration ' num2str(plot_list(i))];
end
legend(l,'Fontsize',18)
end
set(gca,'FontSize',12)
end
end
%% decentralized precoder
function [x] = DP(par,H,s)
% -- initialize
x = zeros(par.B,par.maxiter); % output, each column corresponds to one iteration
lambda_c = zeros(par.U,par.C);
x_c = zeros(par.S,par.C);
w_c = zeros(par.U,par.C);
Hx_c = zeros(par.U,par.C);
H_c = zeros(par.U,par.S,par.C);
% important for fast convergence (reasonable initial guess)
z_c = max(par.U/par.B,1/par.C)*s*ones(1,par.C);
% -- preprocessing
for c=1:par.C
H_c(:,:,c) = H(:,par.S*(c-1)+1:par.S*c); % get the appropriate part of H
switch par.vers
case 'SxS1'
Ainv(:,:,c) = (H_c(:,:,c)'*H_c(:,:,c) + (1/par.rho)*eye(par.S))\(H_c(:,:,c)'); % SxS inverse
case 'SxS2'
Ainv(:,:,c) = inv(H_c(:,:,c)'*H_c(:,:,c) + (1/par.rho)*eye(par.S)); % SxS inverse
case 'UxU1'
Binv(:,:,c) = H_c(:,:,c)'/(H_c(:,:,c)*H_c(:,:,c)' + (1/par.rho)*eye(par.U)); % UxU inverse
case 'UxU2'
Binv(:,:,c) = inv(H_c(:,:,c)*H_c(:,:,c)' + (1/par.rho)*eye(par.U)); % UxU inverse
otherwise
error('mode not defined')
end
end
% -- start iteration
for l = 1:par.maxiter
% cluster-wise equalization
for c=1:par.C
switch par.vers
case 'SxS1'
x_c(:,c) = Ainv(:,:,c)*(z_c(:,c) + lambda_c(:,c)); % SxS inverse
case 'SxS2'
x_c(:,c) = Ainv(:,:,c)*(H_c(:,:,c)'*(z_c(:,c) + lambda_c(:,c))); % SxS inverse
case 'UxU1'
x_c(:,c) = Binv(:,:,c)*(z_c(:,c) + lambda_c(:,c)); % UxU inverse
case 'UxU2'
x_c(:,c) = H_c(:,:,c)'*(Binv(:,:,c)*(z_c(:,c) + lambda_c(:,c))); % UxU inverse
otherwise
error('mode not defined')
end
Hx_c(:,c) = H_c(:,:,c)*x_c(:,c);
w_c(:,c) = Hx_c(:,c)-lambda_c(:,c);
end
% consensus step
w_avg = s-sum(w_c,2);
w_norm = norm(w_avg,2);
w_avg = (max(0,1-par.epsilon/w_norm)*1/par.C)*w_avg; % projection
% cluster-wise update
for c=1:par.C
z_c(:,c) = w_c(:,c)+w_avg;
lambda_c(:,c) = lambda_c(:,c) - par.gamma*(Hx_c(:,c)-z_c(:,c));
end
x(:,l) = x_c(:); % vectorize output
end
end
|
github
|
athakapo/Continuously-Informed-Heuristic-A---Optimal-path-retrieval-inside-an-unknown-environment-master
|
Continuously_Informed_Astar.m
|
.m
|
Continuously-Informed-Heuristic-A---Optimal-path-retrieval-inside-an-unknown-environment-master/Continuously_Informed_Astar.m
| 26,747 |
utf_8
|
5d783088f424b821356b527dd8560e48
|
function varargout = Continuously_Informed_Astar(varargin)
% CONTINUOUSLY_INFORMED_ASTAR MATLAB code for Continuously_Informed_Astar.fig
% CONTINUOUSLY_INFORMED_ASTAR, by itself, creates a new CONTINUOUSLY_INFORMED_ASTAR or raises the existing
% singleton*.
%
% H = CONTINUOUSLY_INFORMED_ASTAR returns the handle to a new CONTINUOUSLY_INFORMED_ASTAR or the handle to
% the existing singleton*.
%
% CONTINUOUSLY_INFORMED_ASTAR('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in CONTINUOUSLY_INFORMED_ASTAR.M with the given input arguments.
%
% CONTINUOUSLY_INFORMED_ASTAR('Property','Value',...) creates a new CONTINUOUSLY_INFORMED_ASTAR or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before Continuously_Informed_Astar_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to Continuously_Informed_Astar_OpeningFcn via varargin.
%
% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one
% instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES
% Edit the above text to modify the response to help Continuously_Informed_Astar
% Last Modified by GUIDE v2.5 01-Sep-2017 00:02:17
% Begin initialization code - DO NOT EDIT
addpath('matlabFunctions')
gui_Singleton = 0;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @Continuously_Informed_Astar_OpeningFcn, ...
'gui_OutputFcn', @Continuously_Informed_Astar_OutputFcn, ...
'gui_LayoutFcn', [] , ...
'gui_Callback', []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end
if nargout
[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT
% --- Executes just before Continuously_Informed_Astar is made visible.
function Continuously_Informed_Astar_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% varargin command line arguments to Continuously_Informed_Astar (see VARARGIN)
% Choose default command line output for Continuously_Informed_Astar
handles.weightDefaultValue = 1.2;
handles.output = hObject;
%handles.ValidExperimntSetUp = 0;
handles.times=0;
handles.stop_now = 0;
set(handles.save_button,'Enable','off')
set(handles.abort_button,'Enable','off')
set(handles.start_button,'Enable','off')
set(handles.submit_button,'Enable','on')
set(handles.weight,'Enable','off')
set(handles.weight,'String',handles.weightDefaultValue)
s = sprintf('Button tooltip line 1\nButton tooltip line 2');
set(handles.text19,'TooltipString', ['<100 and >2'])
set(handles.text20,'TooltipString', ['<70% of the total cells'])
set(handles.submit_button,'TooltipString', ['Also, renew the obstacles'' locations'])
%set(gcf,'pos',[10 10 200 50])
%set(handles.methodgroup,'SelectionChangeFcn',@methodgroup_SelectionChangeFcn);
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes Continuously_Informed_Astar wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% --- Outputs from this function are returned to the command line.
function varargout = Continuously_Informed_Astar_OutputFcn(hObject, eventdata, handles)
% varargout cell array for returning output args (see VARARGOUT);
% hObject handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Get default command line output from handles structure
varargout{1} = handles.output;
% --- Executes on button press in start_button.
function start_button_Callback(hObject, eventdata, handles)
% hObject handle to start_button (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)\
weight=handles.weightDefaultValue;
if (handles.times==1)
cla(handles.axes1,'reset');
disable(hObject, eventdata, handles);
handles=InitializeMainAxes(handles,handles.SIMULparam.gridT,...
handles.SIMULparam.goalCells,handles.SIMULparam.robotInitPos,...
handles.SIMULparam.rows,handles.SIMULparam.cols,handles.SIMULparam.sizeCell,...
handles.SIMULparam.pauseTime);
end
u = get(get(handles.methodgroup,'SelectedObject'),'Tag');
switch u
case 'CIA_button'
alg=9;
case 'A_button'
alg=1;
case 'weigted_button'
weight=str2num(get(handles.weight,'String'));
alg=8;
otherwise
alg=0;
end
disable(hObject, eventdata, handles);
set(handles.abort_button,'Enable','on')
algorithm_call(alg,weight,hObject,handles)
set(handles.abort_button,'Enable','off')
enable(hObject, eventdata, handles);
handles.times=1;
guidata(hObject, handles);
% --- Executes on button press in save_button.
function save_button_Callback(hObject, eventdata, handles)
% hObject handle to save_button (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
gridT=handles.SIMULparam.gridT;
ob=size(handles.SIMULparam.obstacles,1);
goalCells=handles.SIMULparam.goalCells;
robotInitPos=handles.SIMULparam.robotInitPos;
sizeCell=handles.SIMULparam.sizeCell;
rows=handles.SIMULparam.rows;
cols=handles.SIMULparam.cols;
obstacles=handles.SIMULparam.obstacles;
uisave({'gridT','goalCells','robotInitPos','sizeCell','rows','cols','ob',...
'obstacles'},strcat('Experiment_',num2str(cols),'x',num2str(rows),'_',num2str(ob),'_obstacles'))
guidata(hObject, handles);
function weight_Callback(hObject, eventdata, handles)
% hObject handle to weight (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of weight as text
% str2double(get(hObject,'String')) returns contents of weight as a double
weight=str2num(get(handles.weight,'String'));
if isempty(weight)
set(handles.weight,'ForegroundColor','red')
set(handles.start_button,'Enable','off')
else
set(handles.weight,'ForegroundColor','black')
if strcmp(get(handles.submit_button, 'Enable'),'on') && strcmp(get(handles.save_button, 'Enable'),'on')
set(handles.start_button,'Enable','on')
end
end
guidata(hObject, handles);
% --- Executes during object creation, after setting all properties.
function weight_CreateFcn(hObject, eventdata, handles)
% hObject handle to weight (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
% --- Executes on button press in load_button.
function load_button_Callback(hObject, eventdata, handles)
% hObject handle to load_button (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
set(handles.x_goal,'ForegroundColor','black')
set(handles.y_goal,'ForegroundColor','black')
set(handles.x_start,'ForegroundColor','black')
set(handles.y_start,'ForegroundColor','black')
set(handles.rows_size,'ForegroundColor','black')
set(handles.columns_size,'ForegroundColor','black')
set(handles.num_ob,'ForegroundColor','black')
cla(handles.axes1,'reset');
handles.times=0;
[filename pathname]=uigetfile({'*.mat','File Selector'});
fullpathname = strcat(pathname,filename);
handles.file_name=fullpathname;
load(fullpathname)
set(handles.rows_size,'String',num2str(cols))
set(handles.columns_size,'String',num2str(rows))
set(handles.x_start,'String',num2str(robotInitPos(2)))
set(handles.y_start,'String',num2str(robotInitPos(1)))
set(handles.x_goal,'String',num2str(goalCells(2)))
set(handles.y_goal,'String',num2str(goalCells(1)))
set(handles.num_ob,'String',strcat(num2str(ob)))
if ValidEnviromentalParameters(hObject, eventdata, handles)
disable(hObject, eventdata, handles);
handles = main(0,0,0,0,0,0,0,fullpathname,handles);
enable(hObject, eventdata, handles);
set(handles.save_button,'Enable','off')
end
guidata(hObject, handles);
function rows_size_Callback(hObject, eventdata, handles)
% hObject handle to rows_size (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of rows_size as text
% str2double(get(hObject,'String')) returns contents of rows_size as a double
ValidEnviromentalParameters(hObject, eventdata, handles);
guidata(hObject, handles);
% --- Executes during object creation, after setting all properties.
function rows_size_CreateFcn(hObject, eventdata, handles)
% hObject handle to rows_size (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function num_ob_Callback(hObject, eventdata, handles)
% hObject handle to num_ob (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of num_ob as text
% str2double(get(hObject,'String')) returns contents of num_ob as a double
ValidEnviromentalParameters(hObject, eventdata, handles);
guidata(hObject, handles);
% --- Executes during object creation, after setting all properties.
function num_ob_CreateFcn(hObject, eventdata, handles)
% hObject handle to num_ob (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function edit9_Callback(hObject, eventdata, handles)
% hObject handle to robot_start (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of robot_start as text
% str2double(get(hObject,'String')) returns contents of robot_start as a double
% --- Executes during object creation, after setting all properties.
function edit9_CreateFcn(hObject, eventdata, handles)
% hObject handle to robot_start (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function edit10_Callback(hObject, eventdata, handles)
% hObject handle to robot_goal (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of robot_goal as text
% str2double(get(hObject,'String')) returns contents of robot_goal as a double
% --- Executes during object creation, after setting all properties.
function edit10_CreateFcn(hObject, eventdata, handles)
% hObject handle to robot_goal (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function edit11_Callback(hObject, eventdata, handles)
% hObject handle to rows_size (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of rows_size as text
% str2double(get(hObject,'String')) returns contents of rows_size as a double
% --- Executes during object creation, after setting all properties.
function edit11_CreateFcn(hObject, eventdata, handles)
% hObject handle to rows_size (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function edit12_Callback(hObject, eventdata, handles)
% hObject handle to num_ob (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of num_ob as text
% str2double(get(hObject,'String')) returns contents of num_ob as a double
% --- Executes during object creation, after setting all properties.
function edit12_CreateFcn(hObject, eventdata, handles)
% hObject handle to num_ob (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
% --- Executes on button press in submit_butto
function submit_button_Callback(hObject, eventdata,handles)
% hObject handle to submit_button (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
handles = guidata(hObject);
cla(handles.axes1,'reset');
handles.times=0;
full_map='';
x_size=str2num(get(handles.rows_size,'String'));
y_size = str2num(get(handles.columns_size,'String'));
x_s = str2num(get(handles.x_start,'String'));
y_s = str2num(get(handles.y_start,'String'));
x_g = str2num(get(handles.x_goal,'String'));
y_g = str2num(get(handles.y_goal,'String'));
num_obstacles=str2num(get(handles.num_ob,'String'));
disable(hObject, eventdata, handles);
handles = main(x_size,y_size,x_s,y_s,x_g,y_g,num_obstacles,full_map,handles);
enable(hObject, eventdata, handles);
%handles.ValidExperimntSetUp = 1;
%set(handles.save_button,'Enable','on')
guidata(hObject, handles);
function enable(hObject, eventdata, handles)
set(handles.load_button,'Enable','on')
set(handles.submit_button,'Enable','on')
set(handles.save_button,'Enable','on')
set(handles.start_button,'Enable','on')
set(handles.rows_size,'Enable','on')
set(handles.columns_size,'Enable','on')
set(handles.x_start,'Enable','on')
set(handles.y_start,'Enable','on')
set(handles.x_goal,'Enable','on')
set(handles.y_goal,'Enable','on')
set(handles.num_ob,'Enable','on')
set(handles.CIA_button,'Enable','on')
set(handles.A_button,'Enable','on')
set(handles.weigted_button,'Enable','on')
%set(handles.weight,'Enable','on')
function disable(hObject, eventdata, handles)
set(handles.load_button,'Enable','off')
set(handles.submit_button,'Enable','off')
set(handles.save_button,'Enable','off')
set(handles.start_button,'Enable','off')
set(handles.rows_size,'Enable','off')
set(handles.columns_size,'Enable','off')
set(handles.x_start,'Enable','off')
set(handles.y_start,'Enable','off')
set(handles.x_goal,'Enable','off')
set(handles.y_goal,'Enable','off')
set(handles.num_ob,'Enable','off')
set(handles.CIA_button,'Enable','off')
set(handles.A_button,'Enable','off')
set(handles.weigted_button,'Enable','off')
%set(handles.weight,'Enable','off')
% --- Executes on button press in abort_button.
function abort_button_Callback(hObject, eventdata, handles)
% hObject handle to abort_button (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
handles.stop_now = 1;
guidata(hObject, handles); % Update handles structure
function columns_size_Callback(hObject, eventdata, handles)
% hObject handle to columns_size (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of columns_size as text
% str2double(get(hObject,'String')) returns contents of columns_size as a double
ValidEnviromentalParameters(hObject, eventdata, handles);
guidata(hObject, handles); % Update handles structure
% --- Executes during object creation, after setting all properties.
function columns_size_CreateFcn(hObject, eventdata, handles)
% hObject handle to columns_size (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function x_start_Callback(hObject, eventdata, handles)
% hObject handle to x_start (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of x_start as text
% str2double(get(hObject,'String')) returns contents of x_start as a double
ValidEnviromentalParameters(hObject, eventdata, handles);
guidata(hObject, handles); % Update handles structure
% --- Executes during object creation, after setting all properties.
function x_start_CreateFcn(hObject, eventdata, handles)
% hObject handle to x_start (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function y_start_Callback(hObject, eventdata, handles)
% hObject handle to y_start (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of y_start as text
% str2double(get(hObject,'String')) returns contents of y_start as a double
ValidEnviromentalParameters(hObject, eventdata, handles);
guidata(hObject, handles); % Update handles structure
% --- Executes during object creation, after setting all properties.
function y_start_CreateFcn(hObject, eventdata, handles)
% hObject handle to y_start (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function x_goal_Callback(hObject, eventdata, handles)
% hObject handle to x_goal (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of x_goal as text
% str2double(get(hObject,'String')) returns contents of x_goal as a double
ValidEnviromentalParameters(hObject, eventdata, handles);
guidata(hObject, handles); % Update handles structure
% --- Executes during object creation, after setting all properties.
function x_goal_CreateFcn(hObject, eventdata, handles)
% hObject handle to x_goal (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function y_goal_Callback(hObject, eventdata, handles)
% hObject handle to y_goal (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,'String') returns contents of y_goal as text
% str2double(get(hObject,'String')) returns contents of y_goal as a double
ValidEnviromentalParameters(hObject, eventdata, handles);
guidata(hObject, handles); % Update handles structure
% --- Executes during object creation, after setting all properties.
function y_goal_CreateFcn(hObject, eventdata, handles)
% hObject handle to y_goal (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
function y=ValidEnviromentalParameters(hObject, eventdata, handles)
y=0;
%handles.ValidExperimntSetUp = 0;
set(handles.save_button,'Enable','off')
maxNumOfCells = 100;
minNumOfCells = 2;
maxPerObs = 0.7;
%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%
l_xGoal = str2num(get(handles.x_goal,'String'));
l_yGoal = str2num(get(handles.y_goal,'String'));
l_xStart = str2num(get(handles.x_start,'String'));
l_yStart = str2num(get(handles.y_start,'String'));
l_rowsSize = str2num(get(handles.rows_size,'String'));
l_colsSize = str2num(get(handles.columns_size,'String'));
l_numOb = str2num(get(handles.num_ob,'String'));
set(handles.x_goal,'ForegroundColor','black')
set(handles.y_goal,'ForegroundColor','black')
set(handles.x_start,'ForegroundColor','black')
set(handles.y_start,'ForegroundColor','black')
set(handles.rows_size,'ForegroundColor','black')
set(handles.columns_size,'ForegroundColor','black')
set(handles.num_ob,'ForegroundColor','black')
if isempty(l_rowsSize) || l_rowsSize>maxNumOfCells || l_rowsSize<minNumOfCells
set(handles.rows_size,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif isempty(l_colsSize) || l_colsSize>maxNumOfCells || l_colsSize<minNumOfCells
set(handles.columns_size,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif isempty(l_xGoal) || l_xGoal<1
set(handles.x_goal,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif isempty(l_yGoal) || l_yGoal<1
set(handles.y_goal,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif isempty(l_xStart) || l_xStart<1
set(handles.x_start,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif isempty(l_yStart) || l_yStart<1
set(handles.y_start,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif l_xGoal>l_rowsSize
set(handles.rows_size,'ForegroundColor','red')
set(handles.x_goal,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif l_yGoal>l_colsSize
set(handles.columns_size,'ForegroundColor','red')
set(handles.y_goal,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif l_xStart>l_rowsSize
set(handles.rows_size,'ForegroundColor','red')
set(handles.x_start,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif l_yStart>l_colsSize
set(handles.columns_size,'ForegroundColor','red')
set(handles.y_start,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
elseif isempty(l_numOb) || l_numOb>(l_rowsSize*l_colsSize)*maxPerObs || l_numOb<0
set(handles.num_ob,'ForegroundColor','red')
set(handles.submit_button,'Enable','off')
set(handles.start_button,'Enable','off')
else
set(handles.submit_button,'Enable','on')
%set(handles.start_button,'Enable','on')
y=1;
end
guidata(hObject, handles); % Update handles structure
function methodgroup_CreateFcn(hObject, eventdata, handles)
guidata(hObject, handles);
% --- Executes when selected object is changed in methodgroup.
function methodgroup_SelectionChangedFcn(hObject, eventdata, handles)
% hObject handle to the selected object in methodgroup
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
if strcmp(get(get(handles.methodgroup,'SelectedObject'),'Tag'),'weigted_button')
set(handles.weight,'Enable','on')
else
set(handles.weight,'Enable','off')
set(handles.weight,'String',handles.weightDefaultValue)
weight_Callback(hObject, eventdata, handles)
end
guidata(hObject, handles); % Update handles structure
% --- Executes during object deletion, before destroying properties.
function CIA_button_DeleteFcn(hObject, eventdata, handles)
% hObject handle to CIA_button (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
|
github
|
athakapo/Continuously-Informed-Heuristic-A---Optimal-path-retrieval-inside-an-unknown-environment-master
|
v2struct.m
|
.m
|
Continuously-Informed-Heuristic-A---Optimal-path-retrieval-inside-an-unknown-environment-master/matlabFunctions/v2struct.m
| 15,949 |
utf_8
|
20912a1f0ff4635fa430ce427d925be3
|
%% v2struct
% v2struct Pack/Unpack Variables to/from a scalar structure.
function varargout = v2struct(varargin)
%% Description
% v2struct has dual functionality in packing & unpacking variables into structures and
% vice versa, according to the syntax and inputs.
%
% Function features:
% * Pack variables to structure with enhanced field naming
% * Pack and update variables in existing structure
% * Unpack variables from structure with enhanced variable naming
% * Unpack only specific fields in a structure to variables
% * Unpack without over writing existing variables in work space
%
% In addition to the obvious usage, this function could by highly useful for example in
% working with a function with multiple inputs. Packing variables before the call to
% the function, and unpacking it in the beginning of the function will make the function
% call shorter, more readable, and you would not have to worry about arguments order any
% more. Moreover you could leave the function as it is and you could pass same inputs to
% multiple functions, each of which will use its designated arguments placed in the
% structure.
%
%% Syntax
% Pack
% S = v2struct
% S = v2struct(x,y,z,...)
% S = v2struct(fieldNames)
% S = v2struct(A,B,C,..., fieldNames)
% S = v2struct(x,..., nameOfStruct2Update, fieldNames)
% v2struct
% v2struct(x,y,z,...)
% v2struct(fieldNames)
% v2struct(A,B,C,..., fieldNames)
% v2struct(x,..., nameOfStruct2Update, fieldNames)
%
% Unpack
% v2struct(S)
% [a,b,c,...] = v2struct(S)
% v2struct(S,fieldNames)
% [a,b,c,...] = v2struct(S,fieldNames)
%
%% Inputs & Outputs
% Pack - inputs
% x,y,z,... - any variable to pack. can be replaced by fieldNames below.
% nameOfStruct2Update - optional, name of structure to update if desired.
% fieldNames - optional, cell array of strings, which must include a cell
% with the string 'fieldNames' and must be the last input.
% Pack - outputs
% S - the packed structure. If there is no output argument then a structure named
% Sv2struct would be created in the caller workspace.
%
% Unpack - inputs
% S - name of structure to be unpacked.
% fieldNames - optional, cell array of strings, which must include a cell with the
% string 'fieldNames' and must be the last input.
% Unpack - outputs
% a,b,c,... - variables upacked from the structure.
% if there are no output arguments then variables would be created in
% the caller workspace with naming according to name of inputs.
%
%% Examples
% % see 'Usage example' section below for convenient presentation of these examples.
%
% % NOTE: whenever using filedNames cell array please note the following
% % 1. fieldNames cell array must include a cell with the string 'fieldNames'
% % 2. fieldNames cell array input must be the last input.
%
% % Pack
% x = zeros(3); x2 = ones(3); y = 'Testing123'; z = cell(2,3);
% fieldNames1 = {'fieldNames', 'x', 'y', 'z'};
% fieldNames2 = {'fieldNames', 'a', 'b', 'c'};
% fieldNames3 = {'fieldNames', 'x'};
% nameOfStruct2Update = 'S';
%
% % The four examples below return structure S with same values however the
% % structure's field names are defined differently in every syntax.
% % Example 1.
% % structure field names defined by variables names.
% S = v2struct(x,y,z)
% % Example 2.
% % structure field names defined according to the cell array fieldNames.
% % NOTE: variables with the names in fieldNames1 must exist in the caller workspace.
% S = v2struct(fieldNames1)
% % Example 3.
% % same as #1. but arguments are passed explicitly
% S = v2struct(zeros(3), 'Testing123', cell(2,3), fieldNames1)
% % Example 4.
% % field names defined by content of fieldNames2 while
% % the values are set according to the passed arguments. In this case the structure
% % S returned would be: S.a=x, S.b=y, S.c=z
% S = v2struct(x,y,z, fieldNames2)
%
% % Example 5.
% % update structure S. The fields that would be updated are according to content
% % of fieldNames3. Note that you must pass a variable with the name
% % 'nameOfStruct2Update' placed before 'fieldNames3'. This variable should contain
% % the name of the structure you want to update as a string. Also note that if you
% % set an output structure name which is different than the one stated in
% % nameOfStruct2Update a new structure would be created and the structure that was
% % meant to be updated would not get updated.
% S.oldField = 'field to be saved for future use'
% S = v2struct(x2, nameOfStruct2Update, fieldNames3)
%
% % Example 6.
% % pack all variables in caller workspace. Call without input arguments.
% S = v2struct
%
% % The following examples return the same results as the examples above but the
% % structure would be returned with the default name 'Sv2struct'. Be cautious as
% % this might lead to overriding of arguments.
% % Example 7.
% v2struct(x,y,z)
% % Example 8.
% v2struct(fieldNames1)
% % Example 9.
% v2struct(zeros(3), 'Testing123', cell(2,3), fieldNames1)
% % Example 10.
% v2struct(x,y,z, fieldNames2)
% % Example 11.
% S.oldField = 'field to be saved for future use'
% v2struct(x2, nameOfStruct2Update, fieldNames3)
% % Example 12.
% v2struct
%
% % Unpack
% clear S x x2 y z fieldNames1 fieldNames2 fieldNames3 nameOfStruct2Update
% S.x = zeros(3); S.y = 'Testing123'; S.z = cell(2,3);
% fieldNames3 = {'fieldNames','x','z'};
%
% % Example 1.
% % This example creates or overwrites variables x, y, z in the caller with the
% % contents of the corresponding named fields.
% v2struct(S)
%
% % Example 2.
% % This example assigns the contents of the fields of the scalar structure
% % S to the variables a,b,c rather than overwriting variables in the caller. If
% % there are fewer output variables than there are fields in S, the remaining fields
% % are not extracted.
% [a,b,c] = v2struct(S)
%
% % Example 3.
% % This example creates or overwrites variables x and z in the caller with the
% % contents of the corresponding named fields.
% v2struct(S, fieldNames3)
%
% % Example 4.
% % This example assigns the contents of the fields 'x' and 'z' defined by
% % fieldNames3 of the scalar structure S to the variables a and b rather than
% % overwriting variables in the caller. If there are fewer output variables than
% % there are fields in S, the remaining fields are not extracted.
% [a,b] = v2struct(S, fieldNames3)
%
% % This example unpacks variables 'y' and 'z' only without overwriting variable 'x'.
% % NOTE the addition of the field named 'avoidOverWrite' to the structure to be
% % unpacked. This is mandatory in order to make this functionality work. The
% % contents of this field can be anything, it does not matter.
% S.avoidOverWrite = '';
% x = 'do not overwrite me';
% v2struct(S)
%
%% Usage example (includes sub-functions)
% 1. run attached v2structDemo1.m file for on screen presentation of examples.
% 2. run attached v2structDemo2.m file and read comments in file for a suggestion of
% how to use v2struct in managing input to other functions with improved usability.
%
%% Revision history
% 2011-05-19, Adi N., Creation
% 2011-05-29, Adi N., Update structure added, some documentation and demo function changes
% 2011-06-02, Adi N., Fixed updating structure functionality
% 2011-06-05, Adi N., Added functionality: avoid overwritring existing variables, added
% unpacking examples to demo1 .m file.
% 2011-06-30, Adi N., fieldNames usage corrected, now must include a specific string to
% be triggered. Documentation enhanced. Code tweaked.
% 2011-07-14, Adi N., Fixed bug in packing with variables only
% 2011-08-14, Adi N., Clarified warning and error when packing/unpacking with
% fieldNames.
% 2011-09-12, Adi N., Added easy packing of all variables in caller workspace (thanks
% to Vesa Lehtinen for the suggestion), fixed bug in warning
% handling in packing case, edited comments.
%
% Inspired by the function: mmv2truct - D.C. Hanselman, University of Maine, Orono, ME
% 04469 4/28/99, 9/29/99, renamed 10/19/99 Mastering MATLAB 5, Prentice Hall,
% ISBN 0-13-858366-8
% parse input for field names
if isempty(varargin)
gotCellArrayOfStrings = false;
toUnpackRegular = false;
toUnpackFieldNames = false;
gotFieldNames = false;
else
gotCellArrayOfStrings = iscellstr(varargin{end});
toUnpackRegular = (nargin == 1) && isstruct(varargin{1});
if toUnpackRegular
fieldNames = fieldnames(varargin{1})';
nFields = length(fieldNames);
end
gotFieldNames = gotCellArrayOfStrings & any(strcmpi(varargin{end},'fieldNames'));
if gotFieldNames
fieldNamesRaw = varargin{end};
% indices of cells with actual field names, leaving out the index to 'fieldNames' cell.
indFieldNames = ~strcmpi(fieldNamesRaw,'fieldNames');
fieldNames = fieldNamesRaw(indFieldNames);
nFields = length(fieldNames);
end
toUnpackFieldNames = (nargin == 2) && isstruct(varargin{1}) && gotFieldNames;
end
% Unpack
if toUnpackRegular || toUnpackFieldNames
struct = varargin{1};
assert(isequal(length(struct),1) , 'Single input nust be a scalar structure.');
CallerWS = evalin('caller','whos'); % arguments in caller work space
% update fieldNames according to 'avoidOverWrite' flag field.
if isfield(struct,'avoidOverWrite')
indFieldNames = ~ismember(fieldNames,{CallerWS(:).name,'avoidOverWrite'});
fieldNames = fieldNames(indFieldNames);
nFields = length(fieldNames);
end
if toUnpackRegular % Unpack with regular fields order
if nargout == 0 % assign in caller
for iField = 1:nFields
assignin('caller',fieldNames{iField},struct.(fieldNames{iField}));
end
else % dump into variables
for iField = 1:nargout
varargout{iField} = struct.(fieldNames{iField});
end
end
elseif toUnpackFieldNames % Unpack with fields according to fieldNames
if nargout == 0 % assign in caller, by comparing fields to fieldNames
for iField = 1:nFields
assignin('caller',fieldNames{iField},struct.(fieldNames{iField}));
end
else % dump into variables
assert( isequal(nFields, nargout) , ['Number of output arguments',...
' does not match number of field names in cell array']);
for iField = 1:nFields
varargout{iField} = struct.(fieldNames{iField});
end
end
end
% Pack
else
% build cell array of input names
CallerWS = evalin('caller','whos');
inputNames = cell(1,nargin);
for iArgin = 1:nargin
inputNames{iArgin} = inputname(iArgin);
end
nInputs = length(inputNames);
% look for 'nameOfStruct2Update' variable and get the structure name
if ~any(strcmpi(inputNames,'nameOfStruct2Update')) % no nameOfStruct2Update
nameStructArgFound = false;
validVarargin = varargin;
else % nameOfStruct2Update found
nameStructArgFound = true;
nameStructArgLoc = strcmp(inputNames,'nameOfStruct2Update');
nameOfStruct2Update = varargin{nameStructArgLoc};
% valid varargin with just the inputs to pack and fieldNames if exists
validVarargin = varargin(~strcmpi(inputNames,'nameOfStruct2Update'));
% valid inputNames with just the inputs name to pack and fieldNames if exists
inputNames = inputNames(~strcmpi(inputNames,'nameOfStruct2Update'));
nInputs = length(inputNames);
% copy structure from caller workspace to enable its updating
if ismember(nameOfStruct2Update,{CallerWS(:).name}) % verify existance
S = evalin('caller',nameOfStruct2Update);
else
error(['Bad input. Structure named ''',nameOfStruct2Update,...
''' was not found in workspace'])
end
end
% when there is no input or the input is only variables and perhaps
% also nameOfStruct2Update
if ~gotFieldNames
% no input, pack all of variables in caller workspace
if isequal(nInputs, 0)
for iVar = 1:length(CallerWS)
S.(CallerWS(iVar).name) = evalin('caller',CallerWS(iVar).name);
end
% got input, check input names and pack
else
for iInput = 1:nInputs
if gotCellArrayOfStrings % called with a cell array of strings
errMsg = sprintf(['Bad input in cell array of strings.'...
'\nIf you want to pack (or unpack) using this cell array as'...
' designated names'...
'\nof the structure''s fields, add a cell with the string'...
' ''fieldNames'' to it.']);
else
errMsg = sprintf(['Bad input in argument no. ', int2str(iArgin),...
' - explicit argument.\n'...
'Explicit arguments can only be called along with a matching'...
'\n''fieldNames'' cell array of strings.']);
end
assert( ~isempty(inputNames{iInput}), errMsg);
S.(inputNames{iInput}) = validVarargin{iInput};
end
% issue warning for possible wrong usage when packing with an input of cell array of
% strings as the last input without it containing the string 'fieldNames'.
if gotCellArrayOfStrings
name = inputNames{end};
% input contains structure and a cell array of strings
if (nargin == 2) && isstruct(varargin{1})
msgStr = [inputNames{1},''' and ''',inputNames{2},''' were'];
% input contains any arguments with an implicit cell array of strings
else
msgStr = [name, ''' was'];
end
warnMsg = ['V2STRUCT - ''%s packed in the structure.'...
'\nTo avoid this warning do not put ''%s'' as last v2struct input.'...
'\nIf you want to pack (or unpack) using ''%s'' as designated names'...
' of the'...
'\nstructure''s fields, add a cell with the string ''fieldNames'' to'...
' ''%s''.'];
fprintf('\n')
warning('MATLAB:V2STRUCT:cellArrayOfStringNotFieldNames',warnMsg,msgStr,...
name,name,name)
end
end
% fieldNames cell array exists in input
elseif gotFieldNames
nVarToPack = length(varargin)-1-double(nameStructArgFound);
if nVarToPack == 0 % no variables to pack
for iField = 1:nFields
S.(fieldNames{iField}) = evalin('caller',fieldNames{iField});
end
% else - variables to pack exist
% check for correct number of fields vs. variables to pack
elseif ~isequal(nFields,nVarToPack)
error(['Bad input. Number of strings in fieldNames does not match',...
'number of input arguments for packing.'])
else
for iField = 1:nFields
S.(fieldNames{iField}) = validVarargin{iField};
end
end
end % if ~gotFieldNames
if nargout == 0
assignin( 'caller', 'Sv2struct',S );
else
varargout{1} = S;
end
end % if nargin
|
github
|
robical/BlindSourceSeparation-master
|
wavexread.m
|
.m
|
BlindSourceSeparation-master/wavexread.m
| 20,102 |
utf_8
|
f35f68e29ec4b1545c1597f333b27469
|
function [y,Fs,nbits,speakers] = wavexread(file,ext)
%WAVEXREAD Read Microsoft WAVE-FORMAT-EXTENSIBLE (".wav") sound file.
% Y=WAVEXREAD(FILE) reads a WAVE file specified by the string FILE,
% returning the sampled data in Y. The ".wav" extension is appended
% if no extension is given. Amplitude values are in the range [-1,+1].
%
% [Y,FS,NBITS]=WAVEXREAD(FILE) returns the sample rate (FS) in Hertz
% and the number of bits per sample (NBITS) used to encode the
% data in the file.
%
% [...]=WAVEXREAD(FILE,N) returns only the first N samples from each
% channel in the file.
% [...]=WAVEXREAD(FILE,[N1 N2]) returns only samples N1 through N2 from
% each channel in the file.
% SIZ=WAVEXREAD(FILE,'size') returns the size of the audio data contained
% in the file in place of the actual audio data, returning the
% vector SIZ=[samples channels].
%
% [Y,FS,NBITS,OPTS]=WAVEXREAD(...) returns a structure OPTS of additional
% information contained in the WAV file. The content of this
% structure differs from file to file. Typical structure fields
% include '.fmt' (audio format information) and '.info' (text
% which may describe subject title, copy right, etc.)
%
% Supports multi-channel data, with up to 32 bits per sample.
%
% NOTE: This file reader only supports Microsoft PCM data format.
% It does not support wave-list data.
%
% See also WAVEXWRITE, WAVWRITE, AUREAD, AUWRITE.
% Author: D. Orofino
% Copyright 1984-2002 The MathWorks, Inc.
% $Revision: 5.28 $ $Date: 2002/05/30 20:42:03 $
%
% Modified 2004/07/27 by Sylvain Choisel
% to handle WAVE-FORMAT-EXTENSIBLE
% Parse input arguments:
nargchk(1,2,nargin);
if nargin<2, ext=[]; end % Default - read all samples
exts = prod(size(ext)); % length of extent info
if ~strncmpi(ext,'size',exts) & (exts > 2),
error('Index range must be specified as a scalar or 2-element vector.');
end
if ~ischar(ext) & exts==1,
if ext==0,
ext='size'; % synonym for size
else
ext=[1 ext]; % Prepend start sample index
end
end
% Open WAV file:
[fid,msg] = open_wav(file);
error(msg);
% Now the file is open - wrap remaining code in try/catch so we can
% close the file if an error occurs
try
% Find the first RIFF chunk:
[riffck,msg] = find_cktype(fid,'RIFF');
%error(msg);
if ~isempty(msg),
error('Not a WAVE file.');
end
% Verify that RIFF file is WAVE data type:
msg = check_rifftype(fid,'WAVE');
error(msg);
% Find optional chunks, and don't stop till <data-ck> found:
found_data = 0;
end_of_file = 0;
opt_ck = [];
while(~end_of_file),
[ck,msg] = find_cktype(fid);
error(msg);
switch lower(ck.ID)
case 'end of file'
end_of_file = 1;
case 'fmt'
% <fmt-ck> found
[opt_ck,msg] = read_wavefmt(fid,ck,opt_ck);
error(msg);
case 'data'
% <data-ck> found:
found_data = 1;
if ~isfield(opt_ck,'fmt'),
error('Corrupt WAV file: found audio data before format information.');
end
if strncmpi(ext,'size',exts) | ...
(~isempty(ext) & all(ext==0)),
% Caller doesn't want data - just data size:
[samples,msg] = read_wavedat(ck, opt_ck.fmt, -1);
error(msg);
y = [samples opt_ck.fmt.nChannels];
else
% Read <wave-data>:
[datack,msg] = read_wavedat(ck, opt_ck.fmt, ext);
error(msg);
y = datack.Data;
end
case 'fact'
% Optional <fact-ck> found:
[opt_ck,msg] = read_factck(fid, ck, opt_ck);
error(msg);
case 'disp'
% Optional <disp-ck> found:
[opt_ck,msg] = read_dispck(fid, ck, opt_ck);
error(msg);
case 'list'
% Optional <list-ck> found:
[opt_ck, msg] = read_listck(fid, ck, opt_ck);
error(msg);
otherwise
% Skip over data in unprocessed chunks:
if rem(ck.Size,2), ck.Size=ck.Size+1; end
if(fseek(fid,ck.Size,0)==-1),
error('Incorrect chunk size information in WAV file.');
end
end
end
catch
fclose(fid);
error(lasterr);
end
fclose(fid);
% Parse structure info for return to user:
Fs = opt_ck.fmt.nSamplesPerSec;
if opt_ck.fmt.wFormatTag == 1 | opt_ck.fmt.wFormatTag == 3,
% Type 3 floating point has no nBitsPerSample field, so use
% nBlockAlign to figure out number of bits
nbits = (opt_ck.fmt.nBlockAlign / opt_ck.fmt.nChannels) * 8;
else
nbits = []; % Unknown
end
speakers=find((fliplr(dec2bin(opt_ck.fmt.dwChanelMask)-48))~=0);
% end of wavread()
% ------------------------------------------------------------------------
% Local functions:
% ------------------------------------------------------------------------
% ---------------------------------------------
% OPEN_WAV: Open a WAV file for reading
% ---------------------------------------------
function [fid,msg] = open_wav(file)
% Append .wav extension if it's missing:
[pat,nam,ext] = fileparts(file);
if isempty(ext),
file = [file '.wav'];
end
[fid,msg] = fopen(file,'rb','l'); % Little-endian
if fid == -1,
msg = 'Cannot open file.';
end
return
% ---------------------------------------------
% READ_CKINFO: Reads next RIFF chunk, but not the chunk data.
% If optional sflg is set to nonzero, reads SUBchunk info instead.
% Expects an open FID pointing to first byte of chunk header.
% Returns a new chunk structure.
% ---------------------------------------------
function [ck,msg] = read_ckinfo(fid)
msg = '';
ck.fid = fid;
ck.Data = [];
err_msg = 'Truncated chunk header found - possibly not a WAV file.';
[s,cnt] = fread(fid,4,'char');
% Do not error-out if a few (<4) trailing chars are in file
% Just return quickly:
if (cnt~=4),
if feof(fid),
% End of the file (not an error)
ck.ID = 'end of file'; % unambiguous chunk ID (>4 chars)
ck.Size = 0;
else
msg = err_msg;
end
return
end
ck.ID = deblank(setstr(s'));
% Read chunk size (skip if subchunk):
[sz,cnt] = fread(fid,1,'ulong');
if cnt~=1,
msg = err_msg;
return
end
ck.Size = sz;
return
% ---------------------------------------------
% FIND_CKTYPE: Finds a chunk with appropriate type.
% Searches from current file position specified by fid.
% Leaves file positions to data of desired chunk.
% If optional sflg is set to nonzero, finds a SUBchunk instead.
% ---------------------------------------------
function [ck,msg] = find_cktype(fid,ftype)
msg = '';
if nargin<2, ftype = ''; end
[ck,msg] = read_ckinfo(fid);
if ~isempty(msg), return; end
% Was a required chunk type specified?
if ~isempty(ftype) & ~strcmpi(ck.ID,ftype),
msg = ['<' ftype '-ck> did not appear as expected'];
end
return
% ---------------------------------------------
% CHECK_RIFFTYPE: Finds the RIFF data type.
% Searches from current file position specified by fid.
% Leaves file positions to data of desired chunk.
% ---------------------------------------------
function msg = check_rifftype(fid,ftype)
msg = '';
[rifftype,cnt] = fread(fid,4,'char');
rifftype = setstr(rifftype)';
if cnt~=4,
msg = 'Not a WAVE file.';
elseif ~strcmpi(rifftype,ftype),
msg = ['File does not contain required ''' ftype ''' data chunk.'];
end
return
% ---------------------------------------------
% READ_LISTCK: Read the FLIST chunk:
% ---------------------------------------------
function [opt_ck,msg] = read_listck(fid,ck, orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 4; % # of required bytes in <list-ck> header
msg = '';
err_msg = 'Error reading <list-ck> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <list-ck> data:
listdata = setstr(fread(fid,total_bytes,'uchar')');
listtype = lower(listdata(1:4)); % Get LIST type
listdata = listdata(5:end); % Move past INFO
if strcmp(listtype,'info'),
% Information:
while(~isempty(listdata)),
id = listdata(1:4);
switch lower(id)
case 'iart'
name = 'Artist';
case 'icmt'
name = 'Comments';
case 'icrd'
name = 'Creation date';
case 'icop'
name = ['Copy' 'right'];
case 'ieng'
name = 'Engineer';
case 'inam'
name = 'Name';
case 'iprd'
name = 'Product';
case 'isbj'
name = 'Subject';
case 'isft'
name = 'Software';
case 'isrc'
name = 'Source';
otherwise
name = id;
end
if ~isfield(opt_ck,'info'),
opt_ck.info = [];
end
len = listdata(5:8) * 2.^[0 8 16 24]';
txt = listdata(9:9+len-1);
% Fix up text: deblank, and replace CR/LR with LF
txt = deblank(txt);
idx=findstr(txt,setstr([13 10]));
txt(idx) = '';
% Store - don't include the "name" info
opt_ck.info.(lower(id)) = txt;
if rem(len,2), len=len+1; end
listdata = listdata(9+len:end);
end
else
if ~isfield(opt_ck,'list'),
opt_ck.list = [];
end
opt_ck.list.(listtype) = listdata;
end
% Skip over any unprocessed data:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - (ftell(fid) - orig_pos);
if rbytes~=0,
if (fseek(fid,rbytes,'cof')==-1),
msg = err_msg;
end
end
return
% ---------------------------------------------
% READ_DISPCK: Read the DISP chunk:
% ---------------------------------------------
function [opt_ck, msg] = read_dispck(fid,ck,orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 4; % # of required bytes in <disp-ck> header
msg = '';
err_msg = 'Error reading <disp-ck> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <disp-ck> data:
data = fread(fid,total_bytes,'uchar');
% Process data:
% First few entries are size info:
icon_data = data;
siz_info = reshape(icon_data(1:2*4),4,2)';
siz_info = siz_info*(2.^[0 8 16 24]');
is_icon = isequal(siz_info,[8;40]);
if ~is_icon,
% Not the icon:
opt_ck.disp.name = 'DisplayName';
txt = deblank(setstr(data(5:end)'));
opt_ck.disp.text = txt;
end
% Skip over any unprocessed data:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - (ftell(fid) - orig_pos);
if rbytes~=0,
if(fseek(fid,rbytes,'cof')==-1),
msg = err_msg;
end
end
return
% ---------------------------------------------
% READ_FACTCK: Read the FACT chunk:
% ---------------------------------------------
function [opt_ck,msg] = read_factck(fid,ck,orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 4; % # of required bytes in <fact-ck> header
msg = '';
err_msg = 'Error reading <fact-ck> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <fact-ck> data:
opt_ck.fact = setstr(fread(fid,total_bytes,'uchar')');
% Skip over any unprocessed data:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - (ftell(fid) - orig_pos);
if rbytes~=0,
if(fseek(fid,rbytes,'cof')==-1),
msg = err_msg;
end
end
return
% ---------------------------------------------
% READ_WAVEFMT: Read WAVE format chunk.
% Assumes fid points to the <wave-fmt> subchunk.
% Requires chunk structure to be passed, indicating
% the length of the chunk in case we don't recognize
% the format tag.
% ---------------------------------------------
function [opt_ck,msg] = read_wavefmt(fid,ck,orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 40; % # of required bytes in <wave-format> header
msg = '';
err_msg = 'Error reading <wave-fmt> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <wave-format> data:
opt_ck.fmt.wFormatTag = fread(fid,1,'ushort'); % Data encoding format
opt_ck.fmt.nChannels = fread(fid,1,'ushort'); % Number of channels
opt_ck.fmt.nSamplesPerSec = fread(fid,1,'ulong'); % Samples per second
opt_ck.fmt.nAvgBytesPerSec = fread(fid,1,'ulong'); % Avg transfer rate
opt_ck.fmt.nBlockAlign = fread(fid,1,'ushort'); % Block alignment
%sc
opt_ck.fmt.wBitsPerSample = fread(fid,1,'ushort');
opt_ck.fmt.cbSize = fread(fid,1,'ushort');
opt_ck.fmt.wValidBitsPerSample = fread(fid,1,'ushort');
opt_ck.fmt.dwChanelMask = fread(fid,1,'ulong');
opt_ck.fmt.subFormat = fread(fid,16,'uchar');
% Read format-specific info:
switch opt_ck.fmt.wFormatTag
case 1
% PCM Format:
%[opt_ck.fmt, msg] = read_fmt_pcm(fid, ck, opt_ck.fmt);
exit('Invalid extensible format');
case hex2dec('FFFE')
% [opt_ck.fmt, msg] = read_fmt_pcm(fid, ck, opt_ck.fmt);
end
% Skip over any unprocessed fmt-specific data:
%if rem(total_bytes,2), total_bytes=total_bytes+1; end
%rbytes = total_bytes - (ftell(fid) - orig_pos);
%if rbytes~=0,
% if(fseek(fid,rbytes,'cof')==-1),
% msg = err_msg;
% end
%end
return
% ---------------------------------------------
% READ_FMT_PCM: Read <PCM-format-specific> info
% ---------------------------------------------
function [fmt,msg] = read_fmt_pcm(fid, ck, fmt)
% There had better be a bits/sample field:
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 14; % # of bytes already read in <wave-format> header
msg = '';
err_msg = 'Error reading PCM <wave-fmt> chunk.';
%if (total_bytes < nbytes+2),
% msg = err_msg;
% return
%end
%[bits,cnt] = fread(fid,1,'ushort');
%nbytes=nbytes+2;
%if (cnt~=1),
% msg = err_msg;
% return
%end
%fmt.nBitsPerSample=bits;
% Are there any additional fields present?
if (total_bytes > nbytes),
% See if the "cbSize" field is present. If so, grab the data:
if (total_bytes >= nbytes+2),
% we have the cbSize ushort in the file:
[cbSize,cnt]=fread(fid,1,'ushort');
nbytes=nbytes+2;
if (cnt~=1),
msg = err_msg;
return
end
fmt.cbSize = cbSize;
end
% Simply skip any remaining stuff - we don't know what it is:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - nbytes;
if rbytes~=0,
if (fseek(fid,rbytes,'cof') == -1);
msg = err_msg;
end
end
end
return
% ---------------------------------------------
% READ_WAVEDAT: Read WAVE data chunk
% Assumes fid points to the wave-data chunk
% Requires <data-ck> and <wave-format> structures to be passed.
% Requires extraction range to be specified.
% Setting ext=[] forces ALL samples to be read. Otherwise,
% ext should be a 2-element vector specifying the first
% and last samples (per channel) to be extracted.
% Setting ext=-1 returns the number of samples per channel,
% skipping over the sample data.
% ---------------------------------------------
function [dat,msg] = read_wavedat(datack,wavefmt,ext)
% In case of unsupported data compression format:
dat = [];
fmt_msg = '';
switch wavefmt.wFormatTag
case 1
% PCM Format:
[dat,msg] = read_dat_pcm(datack,wavefmt,ext);
case 2
fmt_msg = 'Microsoft ADPCM';
case 3
% normalized floating-point
[dat,msg] = read_dat_pcm(datack,wavefmt,ext);
case 6
fmt_msg = 'CCITT a-law';
case 7
fmt_msg = 'CCITT mu-law';
case 17
fmt_msg = 'IMA ADPCM';
case 34
fmt_msg = 'DSP Group TrueSpeech TM';
case 49
fmt_msg = 'GSM 6.10';
case 50
fmt_msg = 'MSN Audio';
case 257
fmt_msg = 'IBM Mu-law';
case 258
fmt_msg = 'IBM A-law';
case 259
fmt_msg = 'IBM AVC Adaptive Differential';
case hex2dec('FFFE') %sc
% WAVE-FORMAT-EXTENSIBLE
[dat,msg] = read_dat_pcm(datack,wavefmt,ext);
otherwise
fmt_msg = ['Format #' num2str(wavefmt.wFormatTag)];
end
if ~isempty(fmt_msg),
msg = ['Data compression format (' fmt_msg ') is not supported.'];
end
return
% ---------------------------------------------
% READ_DAT_PCM: Read PCM format data from <wave-data> chunk.
% Assumes fid points to the wave-data chunk
% Requires <data-ck> and <wave-format> structures to be passed.
% Requires extraction range to be specified.
% Setting ext=[] forces ALL samples to be read. Otherwise,
% ext should be a 2-element vector specifying the first
% and last samples (per channel) to be extracted.
% Setting ext=-1 returns the number of samples per channel,
% skipping over the sample data.
% ---------------------------------------------
function [dat,msg] = read_dat_pcm(datack,wavefmt,ext)
dat = [];
msg = '';
% Determine # bytes/sample - format requires rounding
% to next integer number of bytes:
BytesPerSample = ceil(wavefmt.nBlockAlign / wavefmt.nChannels);
if (BytesPerSample == 1),
dtype='uchar'; % unsigned 8-bit
elseif (BytesPerSample == 2),
dtype='short'; % signed 16-bit
elseif (BytesPerSample == 3)
dtype='bit24'; % signed 24-bit
elseif (BytesPerSample == 4),
% 32-bit 16.8 float (type 1 - 32-bit)
% 32-bit normalized floating point
dtype = 'float';
% 32-bit 24.0 float (type 1 - 24-bit)
if wavefmt.wFormatTag ~= 3 & wavefmt.nBitsPerSample == 24,
BytesPerSample = 3;
end
else
msg = 'Cannot read PCM file formats with more than 32 bits per sample.';
return
end
total_bytes = datack.Size; % # bytes in this chunk
total_samples = total_bytes / BytesPerSample;
SamplesPerChannel = total_samples / wavefmt.nChannels;
if ~isempty(ext) & ext==-1,
% Just return the samples per channel, and fseek past data:
dat = SamplesPerChannel;
% Add in a pad-byte, if required:
total_bytes = total_bytes + rem(datack.Size,2);
if(fseek(datack.fid,total_bytes,'cof')==-1),
msg = 'Error reading PCM file format.';
end
return
end
% Determine sample range to read:
if isempty(ext),
ext = [1 SamplesPerChannel]; % Return all samples
else
if prod(size(ext))~=2,
msg = 'Sample limit vector must have 2 elements.';
return
end
if ext(1)<1 | ext(2)>SamplesPerChannel,
msg = 'Sample limits out of range.';
return
end
if ext(1)>ext(2),
msg = 'Sample limits must be given in ascending order.';
return
end
end
bytes_remaining = total_bytes; % Preset byte counter
% Skip over leading samples:
if ext(1)>1,
% Skip over leading samples, if specified:
skipcnt = BytesPerSample * (ext(1)-1) * wavefmt.nChannels;
if(fseek(datack.fid, skipcnt,'cof') == -1),
msg = 'Error reading PCM file format.';
return
end
%
% Update count of bytes remaining:
bytes_remaining = bytes_remaining - skipcnt;
end
% Read desired data:
nSPCext = ext(2)-ext(1)+1; % # samples per channel in extraction range
dat = datack; % Copy input structure to output
extSamples = wavefmt.nChannels*nSPCext;
dat.Data = fread(datack.fid, [wavefmt.nChannels nSPCext], dtype);
%
% Update count of bytes remaining:
skipcnt = BytesPerSample*nSPCext*wavefmt.nChannels;
bytes_remaining = bytes_remaining - skipcnt;
% if cnt~=extSamples, dat='Error reading file.'; return; end
% Skip over trailing samples:
if(fseek(datack.fid, BytesPerSample * ...
(SamplesPerChannel-ext(2))*wavefmt.nChannels, 'cof')==-1),
msg = 'Error reading PCM file format.';
return
end
% Update count of bytes remaining:
skipcnt = BytesPerSample*(SamplesPerChannel-ext(2))*wavefmt.nChannels;
bytes_remaining = bytes_remaining - skipcnt;
% Determine if a pad-byte is appended to data chunk,
% skipping over it if present:
if rem(datack.Size,2),
fseek(datack.fid, 1, 'cof');
end
% Rearrange data into a matrix with one channel per column:
dat.Data = dat.Data';
% Normalize data range: min will hit -1, max will not quite hit +1.
if BytesPerSample==1,
dat.Data = (dat.Data-128)/128; % [-1,1)
elseif BytesPerSample==2,
dat.Data = dat.Data/32768; % [-1,1)
elseif BytesPerSample==3,
dat.Data = dat.Data/(2^23); % [-1,1)
elseif BytesPerSample==4,
if wavefmt.wFormatTag ~= 3, % Type 3 32-bit is already normalized
dat.Data = dat.Data/32768; % [-1,1)
end
end
return
% end of wavread.m
|
github
|
robical/BlindSourceSeparation-master
|
wavexwrite.m
|
.m
|
BlindSourceSeparation-master/wavexwrite.m
| 8,855 |
utf_8
|
5e65dd381efc54d3f9865c9c79100c35
|
function wavexwrite(y,Fs,nbits,wavefile,speakers)
%WAVEXWRITE Write WAVE_FORMAT_EXTENSIBLE sound file.
% WAVEXWRITE(Y,FS,NBITS,WAVEFILE, SPEAKERS) writes data Y to a WAVEX
% file specified by the file name WAVEFILE, with a sample rate
% of FS Hz and with NBITS number of bits. NBITS must be 8, 16,
% 24, or 32. Stereo data should be specified as a matrix with two
% columns. For NBITS < 32, amplitude values outside the range
% [-1,+1] are clipped.
%
% SPEAKERS is a vector of speaker numbers
% e.g. [1,2] for stereo
% [1:5] for 5.1
% [3] for center channel
%
% WAVEXWRITE(Y,FS,WAVEFILE) assumes NBITS=16 bits.
% WAVEXWRITE(Y,WAVEFILE) assumes NBITS=16 bits and FS=44100 Hz.
%
% 8-, 16-, and 24-bit files are type 1 integer PCM. 32-bit files
% are written as type 3 normalized floating point.
%
% Modified 2004/07/27 by Sylvain Choisel
% to handle WAVE-FORMAT-EXTENSIBLE
% email: [email protected]
% Parse inputs:
error(nargchk(2,5,nargin));
if nargin < 3,
wavefile = Fs;
Fs = 44100;
nbits = 16;
elseif nargin < 4,
wavefile = nbits;
nbits = 16;
end
% If input is a vector, force it to be a column:
if ndims(y) > 2,
error('Data array cannot be an N-D array.');
end
if size(y,1)==1,
y = y(:);
end
[samples, channels] = size(y);
if nargin < 5,
speakerMask=2^channels-1;
else
if (length(speakers)~=channels)
error ('Speaker mask length must be equal to the number of channels');
end
speakerMask=sum(2.^(speakers-1));
end
% Determine number of bytes in chunks
% (not including pad bytes, if needed):
% ----------------------------------
% 'RIFF' 4 bytes
% size 4 bytes (ulong)
% 'WAVE' 4 bytes
% 'fmt ' 4 bytes
% size 4 bytes (ulong)
% <wave-format> 14 bytes
% <format_specific> 2 bytes (PCM)
% 'data' 4 bytes
% size 4 bytes (ulong)
% <wave-data> N bytes
% ----------------------------------
bytes_per_sample = ceil(nbits/8);
total_samples = samples * channels;
total_bytes = total_samples * bytes_per_sample;
riff_cksize = 4+48+total_bytes; % Don't include 'RIFF' or its size field
fmt_cksize = 40; % Don't include 'fmt ' or its size field
data_cksize = total_bytes; % Don't include 'data' or its size field
% Determine pad bytes:
data_pad = rem(data_cksize,2);
riff_cksize = riff_cksize + data_pad; % + fmt_pad, always 0
% Open file for output:
[fid,err] = OpenWaveWrite(wavefile);
error(err);
% Prepare basic chunk structure fields:
ck=[]; ck.fid=fid; ck.filename = wavefile;
% Write RIFF chunk:
ck.ID = 'RIFF';
ck.Size = riff_cksize;
error(write_ckinfo(ck));
% Write WAVE subchunk:
ck.ID = 'WAVE';
ck.Size = []; % Indicate a subchunk (no chunk size)
error(write_ckinfo(ck));
% Write <fmt-ck>:
ck.ID = 'fmt ';
ck.Size = fmt_cksize;
error(write_ckinfo(ck));
% Write <wave-format>:
fmt.filename = wavefile;
fmt.wFormatTag = hex2dec('FFFE');
fmt.nChannels = channels; % Number of channels
fmt.nSamplesPerSec = Fs; % Samples per second
fmt.nAvgBytesPerSec = channels*bytes_per_sample*Fs; % Avg transfer rate
fmt.nBlockAlign = channels*bytes_per_sample; % Block alignment
fmt.nBitsPerSample = 8*bytes_per_sample;
fmt.cbSize = 22;
fmt.wValidBitsPerSample = nbits;
fmt.dwSpkMask = speakerMask;
fmt.subFormat = [1 0 0 0 0 0 16 0 8*16 0 0 hex2dec('AA') 0 hex2dec('38') hex2dec('9B') hex2dec('71')];
error(write_wavefmt(fid,fmt));
% Write <data-ck>:
ck.ID = 'data';
ck.Size = data_cksize;
error(write_ckinfo(ck));
% Write <wave-data>, and its pad byte if needed:
error(write_wavedat(fid,fmt,y));
% Close file:
fclose(fid);
% end of wavwrite()
% ------------------------------------------------------------------------
% Private functions:
% ------------------------------------------------------------------------
% ------------------------------------------------------------------------
function [fid,err] = OpenWaveWrite(wavefile)
% OpenWaveWrite
% Open WAV file for writing.
% If filename does not contain an extension, add ".wav"
fid = [];
err = '';
if ~isstr(wavefile),
err='Wave file name must be a string.'; return;
end
% modified 27/07/2004 sc
%if isempty(findstr(wavefile,'.')),
% wavefile=[wavefile '.wav'];
%end
[pathstr,name,ext,versn]=fileparts(wavefile);
if (~strcmp(lower(ext),'.wav'))
wavefile=[wavefile '.wav'];
end
% Open file, little-endian:
[fid,err] = fopen(wavefile,'wb','l');
return
% ------------------------------------------------------------------------
function err = write_ckinfo(ck)
% WRITE_CKINFO: Writes next RIFF chunk, but not the chunk data.
% Assumes the following fields in ck:
% .fid File ID to an open file
% .ID 4-character string chunk identifier
% .Size Size of chunk (empty if subchunk)
%
%
% Expects an open FID pointing to first byte of chunk header,
% and a chunk structure.
% ck.fid, ck.ID, ck.Size, ck.Data
errmsg = ['Failed to write ' ck.ID ' chunk to WAVE file: ' ck.filename];
err = '';
if (fwrite(ck.fid, ck.ID, 'char') ~= 4),
err=errmsg; return;
end
if ~isempty(ck.Size),
% Write chunk size:
if (fwrite(ck.fid, ck.Size, 'ulong') ~= 1),
err=errmsg; return;
end
end
return
% ------------------------------------------------------------------------
function err = write_wavefmt(fid, fmt)
% WRITE_WAVEFMT: Write WAVE format chunk.
% Assumes fid points to the wave-format subchunk.
% Requires chunk structure to be passed, indicating
% the length of the chunk.
errmsg = ['Failed to write WAVE format chunk to file' fmt.filename];
err = '';
% Create <wave-format> data:
if (fwrite(fid, fmt.wFormatTag, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.nChannels, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.nSamplesPerSec, 'ulong' ) ~= 1) | ...
(fwrite(fid, fmt.nAvgBytesPerSec, 'ulong' ) ~= 1) | ...
(fwrite(fid, fmt.nBlockAlign, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.nBitsPerSample, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.cbSize, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.wValidBitsPerSample, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.dwSpkMask, 'ulong' ) ~= 1) | ...
(fwrite(fid, fmt.subFormat, 'uchar' ) ~= 16)
err=errmsg;
end
return
% -----------------------------------------------------------------------
function y = PCM_Quantize(x, fmt)
% PCM_Quantize:
% Scale and quantize input data, from [-1, +1] range to
% either an 8-, 16-, or 24-bit data range.
% Clip data to normalized range [-1,+1]:
ClipMsg = ['Data clipped during write to file:' fmt.filename];
ClipWarn = 0;
% Determine slope (m) and bias (b) for data scaling:
nbits = fmt.nBitsPerSample;
m = 2.^(nbits-1);
switch nbits
case 8,
b=128;
case {16,24},
b=0;
otherwise,
error('Invalid number of bits specified.');
end
y = round(m .* x + b);
% Determine quantized data limits, based on the
% presumed input data limits of [-1, +1]:
ylim = [-1 +1];
qlim = m * ylim + b;
qlim(2) = qlim(2)-1;
% Clip data to quantizer limits:
i = find(y < qlim(1));
if ~isempty(i),
warning(ClipMsg); ClipWarn=1;
y(i) = qlim(1);
end
i = find(y > qlim(2));
if ~isempty(i),
if ~ClipWarn, warning(ClipMsg); end
y(i) = qlim(2);
end
return
% -----------------------------------------------------------------------
function err = write_wavedat(fid,fmt,data)
% WRITE_WAVEDAT: Write WAVE data chunk
% Assumes fid points to the wave-data chunk
% Requires <wave-format> structure to be passed.
err = '';
if fmt.wFormatTag==1 | fmt.wFormatTag==3 | fmt.wFormatTag==hex2dec('FFFE'),
% PCM Format
% 32-bit Type 3 is normalized, so no scaling needed.
if fmt.nBitsPerSample ~= 32,
data = PCM_Quantize(data, fmt);
end
switch fmt.nBitsPerSample
case 8,
dtype='uchar'; % unsigned 8-bit
case 16,
dtype='short'; % signed 16-bit
case 24,
dtype='bit24'; % signed 24-bit
case 32,
dtype='float'; % normalized 32-bit floating point
otherwise,
err = 'Invalid number of bits specified.'; return;
end
% Write data, one row at a time (one sample from each channel):
[samples,channels] = size(data);
total_samples = samples*channels;
if (fwrite(fid, reshape(data',total_samples,1), dtype) ~= total_samples),
err = 'Failed to write PCM data samples.'; return;
end
% Determine # bytes/sample - format requires rounding
% to next integer number of bytes:
BytesPerSample = ceil(fmt.nBitsPerSample/8);
% Determine if a pad-byte must be appended to data chunk:
if rem(total_samples*BytesPerSample, 2) ~= 0,
fwrite(fid,0,'uchar');
end
else
% Unknown wave-format for data.
err = 'Unsupported data format.';
end
return
% end of wavwrite.m
|
github
|
robical/BlindSourceSeparation-master
|
OLAfft.m
|
.m
|
BlindSourceSeparation-master/OLAfft.m
| 1,047 |
utf_8
|
86f0ef14501a48d7746ebec4b9055b70
|
%&Implementazione STFT
%
% av=percentuale di avanzamento espressa in forma decimale es. 50%=0.5
% win=tipo di finestra
function [fourier1]=OLAfft(signal1,win,av)
durata=length(signal1); %durata segnale
pas=length(win); %durata finestra
splice1=zeros(pas,(fix(durata/(pas*av)))+1);
part1=zeros(pas,(fix(durata/(pas*av)))+1);
splice1(1:pas,1)=signal1(1:pas,1)'.*win';
part1(1:pas,1)=splice1(1:pas,1);
cicli=fix((durata-pas)/(pas/2));
for i=2:cicli;
start=1+(i-1)*(pas*av); %avanza del 50%
fin=start+pas-1;
part1(1:pas,i)=signal1(start:fin,1);
splice1(1:pas,i)=part1(1:pas,i)'.*win';
end;
resto=rem(durata,(pas*av));
fin=fix(durata/(pas*av))*(pas*av);
part1(1:pas,(fix(durata/(pas*av))-1))=[signal1(fin:durata,1); zeros((pas-resto-1),1)];
splice1(1:pas,(fix(durata/(pas*av))-1))=part1(1:pas,(fix(durata/(pas*av))-1))'.*win';
for i=1:fix(durata/(pas*av))-1;
fourier1(1:pas,i)=fftshift(fft(splice1(1:pas,i)));
end;
|
github
|
robical/BlindSourceSeparation-master
|
wavexread.m
|
.m
|
BlindSourceSeparation-master/img/Progetto/wavexread.m
| 20,102 |
utf_8
|
f35f68e29ec4b1545c1597f333b27469
|
function [y,Fs,nbits,speakers] = wavexread(file,ext)
%WAVEXREAD Read Microsoft WAVE-FORMAT-EXTENSIBLE (".wav") sound file.
% Y=WAVEXREAD(FILE) reads a WAVE file specified by the string FILE,
% returning the sampled data in Y. The ".wav" extension is appended
% if no extension is given. Amplitude values are in the range [-1,+1].
%
% [Y,FS,NBITS]=WAVEXREAD(FILE) returns the sample rate (FS) in Hertz
% and the number of bits per sample (NBITS) used to encode the
% data in the file.
%
% [...]=WAVEXREAD(FILE,N) returns only the first N samples from each
% channel in the file.
% [...]=WAVEXREAD(FILE,[N1 N2]) returns only samples N1 through N2 from
% each channel in the file.
% SIZ=WAVEXREAD(FILE,'size') returns the size of the audio data contained
% in the file in place of the actual audio data, returning the
% vector SIZ=[samples channels].
%
% [Y,FS,NBITS,OPTS]=WAVEXREAD(...) returns a structure OPTS of additional
% information contained in the WAV file. The content of this
% structure differs from file to file. Typical structure fields
% include '.fmt' (audio format information) and '.info' (text
% which may describe subject title, copy right, etc.)
%
% Supports multi-channel data, with up to 32 bits per sample.
%
% NOTE: This file reader only supports Microsoft PCM data format.
% It does not support wave-list data.
%
% See also WAVEXWRITE, WAVWRITE, AUREAD, AUWRITE.
% Author: D. Orofino
% Copyright 1984-2002 The MathWorks, Inc.
% $Revision: 5.28 $ $Date: 2002/05/30 20:42:03 $
%
% Modified 2004/07/27 by Sylvain Choisel
% to handle WAVE-FORMAT-EXTENSIBLE
% Parse input arguments:
nargchk(1,2,nargin);
if nargin<2, ext=[]; end % Default - read all samples
exts = prod(size(ext)); % length of extent info
if ~strncmpi(ext,'size',exts) & (exts > 2),
error('Index range must be specified as a scalar or 2-element vector.');
end
if ~ischar(ext) & exts==1,
if ext==0,
ext='size'; % synonym for size
else
ext=[1 ext]; % Prepend start sample index
end
end
% Open WAV file:
[fid,msg] = open_wav(file);
error(msg);
% Now the file is open - wrap remaining code in try/catch so we can
% close the file if an error occurs
try
% Find the first RIFF chunk:
[riffck,msg] = find_cktype(fid,'RIFF');
%error(msg);
if ~isempty(msg),
error('Not a WAVE file.');
end
% Verify that RIFF file is WAVE data type:
msg = check_rifftype(fid,'WAVE');
error(msg);
% Find optional chunks, and don't stop till <data-ck> found:
found_data = 0;
end_of_file = 0;
opt_ck = [];
while(~end_of_file),
[ck,msg] = find_cktype(fid);
error(msg);
switch lower(ck.ID)
case 'end of file'
end_of_file = 1;
case 'fmt'
% <fmt-ck> found
[opt_ck,msg] = read_wavefmt(fid,ck,opt_ck);
error(msg);
case 'data'
% <data-ck> found:
found_data = 1;
if ~isfield(opt_ck,'fmt'),
error('Corrupt WAV file: found audio data before format information.');
end
if strncmpi(ext,'size',exts) | ...
(~isempty(ext) & all(ext==0)),
% Caller doesn't want data - just data size:
[samples,msg] = read_wavedat(ck, opt_ck.fmt, -1);
error(msg);
y = [samples opt_ck.fmt.nChannels];
else
% Read <wave-data>:
[datack,msg] = read_wavedat(ck, opt_ck.fmt, ext);
error(msg);
y = datack.Data;
end
case 'fact'
% Optional <fact-ck> found:
[opt_ck,msg] = read_factck(fid, ck, opt_ck);
error(msg);
case 'disp'
% Optional <disp-ck> found:
[opt_ck,msg] = read_dispck(fid, ck, opt_ck);
error(msg);
case 'list'
% Optional <list-ck> found:
[opt_ck, msg] = read_listck(fid, ck, opt_ck);
error(msg);
otherwise
% Skip over data in unprocessed chunks:
if rem(ck.Size,2), ck.Size=ck.Size+1; end
if(fseek(fid,ck.Size,0)==-1),
error('Incorrect chunk size information in WAV file.');
end
end
end
catch
fclose(fid);
error(lasterr);
end
fclose(fid);
% Parse structure info for return to user:
Fs = opt_ck.fmt.nSamplesPerSec;
if opt_ck.fmt.wFormatTag == 1 | opt_ck.fmt.wFormatTag == 3,
% Type 3 floating point has no nBitsPerSample field, so use
% nBlockAlign to figure out number of bits
nbits = (opt_ck.fmt.nBlockAlign / opt_ck.fmt.nChannels) * 8;
else
nbits = []; % Unknown
end
speakers=find((fliplr(dec2bin(opt_ck.fmt.dwChanelMask)-48))~=0);
% end of wavread()
% ------------------------------------------------------------------------
% Local functions:
% ------------------------------------------------------------------------
% ---------------------------------------------
% OPEN_WAV: Open a WAV file for reading
% ---------------------------------------------
function [fid,msg] = open_wav(file)
% Append .wav extension if it's missing:
[pat,nam,ext] = fileparts(file);
if isempty(ext),
file = [file '.wav'];
end
[fid,msg] = fopen(file,'rb','l'); % Little-endian
if fid == -1,
msg = 'Cannot open file.';
end
return
% ---------------------------------------------
% READ_CKINFO: Reads next RIFF chunk, but not the chunk data.
% If optional sflg is set to nonzero, reads SUBchunk info instead.
% Expects an open FID pointing to first byte of chunk header.
% Returns a new chunk structure.
% ---------------------------------------------
function [ck,msg] = read_ckinfo(fid)
msg = '';
ck.fid = fid;
ck.Data = [];
err_msg = 'Truncated chunk header found - possibly not a WAV file.';
[s,cnt] = fread(fid,4,'char');
% Do not error-out if a few (<4) trailing chars are in file
% Just return quickly:
if (cnt~=4),
if feof(fid),
% End of the file (not an error)
ck.ID = 'end of file'; % unambiguous chunk ID (>4 chars)
ck.Size = 0;
else
msg = err_msg;
end
return
end
ck.ID = deblank(setstr(s'));
% Read chunk size (skip if subchunk):
[sz,cnt] = fread(fid,1,'ulong');
if cnt~=1,
msg = err_msg;
return
end
ck.Size = sz;
return
% ---------------------------------------------
% FIND_CKTYPE: Finds a chunk with appropriate type.
% Searches from current file position specified by fid.
% Leaves file positions to data of desired chunk.
% If optional sflg is set to nonzero, finds a SUBchunk instead.
% ---------------------------------------------
function [ck,msg] = find_cktype(fid,ftype)
msg = '';
if nargin<2, ftype = ''; end
[ck,msg] = read_ckinfo(fid);
if ~isempty(msg), return; end
% Was a required chunk type specified?
if ~isempty(ftype) & ~strcmpi(ck.ID,ftype),
msg = ['<' ftype '-ck> did not appear as expected'];
end
return
% ---------------------------------------------
% CHECK_RIFFTYPE: Finds the RIFF data type.
% Searches from current file position specified by fid.
% Leaves file positions to data of desired chunk.
% ---------------------------------------------
function msg = check_rifftype(fid,ftype)
msg = '';
[rifftype,cnt] = fread(fid,4,'char');
rifftype = setstr(rifftype)';
if cnt~=4,
msg = 'Not a WAVE file.';
elseif ~strcmpi(rifftype,ftype),
msg = ['File does not contain required ''' ftype ''' data chunk.'];
end
return
% ---------------------------------------------
% READ_LISTCK: Read the FLIST chunk:
% ---------------------------------------------
function [opt_ck,msg] = read_listck(fid,ck, orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 4; % # of required bytes in <list-ck> header
msg = '';
err_msg = 'Error reading <list-ck> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <list-ck> data:
listdata = setstr(fread(fid,total_bytes,'uchar')');
listtype = lower(listdata(1:4)); % Get LIST type
listdata = listdata(5:end); % Move past INFO
if strcmp(listtype,'info'),
% Information:
while(~isempty(listdata)),
id = listdata(1:4);
switch lower(id)
case 'iart'
name = 'Artist';
case 'icmt'
name = 'Comments';
case 'icrd'
name = 'Creation date';
case 'icop'
name = ['Copy' 'right'];
case 'ieng'
name = 'Engineer';
case 'inam'
name = 'Name';
case 'iprd'
name = 'Product';
case 'isbj'
name = 'Subject';
case 'isft'
name = 'Software';
case 'isrc'
name = 'Source';
otherwise
name = id;
end
if ~isfield(opt_ck,'info'),
opt_ck.info = [];
end
len = listdata(5:8) * 2.^[0 8 16 24]';
txt = listdata(9:9+len-1);
% Fix up text: deblank, and replace CR/LR with LF
txt = deblank(txt);
idx=findstr(txt,setstr([13 10]));
txt(idx) = '';
% Store - don't include the "name" info
opt_ck.info.(lower(id)) = txt;
if rem(len,2), len=len+1; end
listdata = listdata(9+len:end);
end
else
if ~isfield(opt_ck,'list'),
opt_ck.list = [];
end
opt_ck.list.(listtype) = listdata;
end
% Skip over any unprocessed data:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - (ftell(fid) - orig_pos);
if rbytes~=0,
if (fseek(fid,rbytes,'cof')==-1),
msg = err_msg;
end
end
return
% ---------------------------------------------
% READ_DISPCK: Read the DISP chunk:
% ---------------------------------------------
function [opt_ck, msg] = read_dispck(fid,ck,orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 4; % # of required bytes in <disp-ck> header
msg = '';
err_msg = 'Error reading <disp-ck> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <disp-ck> data:
data = fread(fid,total_bytes,'uchar');
% Process data:
% First few entries are size info:
icon_data = data;
siz_info = reshape(icon_data(1:2*4),4,2)';
siz_info = siz_info*(2.^[0 8 16 24]');
is_icon = isequal(siz_info,[8;40]);
if ~is_icon,
% Not the icon:
opt_ck.disp.name = 'DisplayName';
txt = deblank(setstr(data(5:end)'));
opt_ck.disp.text = txt;
end
% Skip over any unprocessed data:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - (ftell(fid) - orig_pos);
if rbytes~=0,
if(fseek(fid,rbytes,'cof')==-1),
msg = err_msg;
end
end
return
% ---------------------------------------------
% READ_FACTCK: Read the FACT chunk:
% ---------------------------------------------
function [opt_ck,msg] = read_factck(fid,ck,orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 4; % # of required bytes in <fact-ck> header
msg = '';
err_msg = 'Error reading <fact-ck> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <fact-ck> data:
opt_ck.fact = setstr(fread(fid,total_bytes,'uchar')');
% Skip over any unprocessed data:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - (ftell(fid) - orig_pos);
if rbytes~=0,
if(fseek(fid,rbytes,'cof')==-1),
msg = err_msg;
end
end
return
% ---------------------------------------------
% READ_WAVEFMT: Read WAVE format chunk.
% Assumes fid points to the <wave-fmt> subchunk.
% Requires chunk structure to be passed, indicating
% the length of the chunk in case we don't recognize
% the format tag.
% ---------------------------------------------
function [opt_ck,msg] = read_wavefmt(fid,ck,orig_opt_ck)
opt_ck = orig_opt_ck;
orig_pos = ftell(fid);
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 40; % # of required bytes in <wave-format> header
msg = '';
err_msg = 'Error reading <wave-fmt> chunk.';
if total_bytes < nbytes,
msg = err_msg;
return
end
% Read standard <wave-format> data:
opt_ck.fmt.wFormatTag = fread(fid,1,'ushort'); % Data encoding format
opt_ck.fmt.nChannels = fread(fid,1,'ushort'); % Number of channels
opt_ck.fmt.nSamplesPerSec = fread(fid,1,'ulong'); % Samples per second
opt_ck.fmt.nAvgBytesPerSec = fread(fid,1,'ulong'); % Avg transfer rate
opt_ck.fmt.nBlockAlign = fread(fid,1,'ushort'); % Block alignment
%sc
opt_ck.fmt.wBitsPerSample = fread(fid,1,'ushort');
opt_ck.fmt.cbSize = fread(fid,1,'ushort');
opt_ck.fmt.wValidBitsPerSample = fread(fid,1,'ushort');
opt_ck.fmt.dwChanelMask = fread(fid,1,'ulong');
opt_ck.fmt.subFormat = fread(fid,16,'uchar');
% Read format-specific info:
switch opt_ck.fmt.wFormatTag
case 1
% PCM Format:
%[opt_ck.fmt, msg] = read_fmt_pcm(fid, ck, opt_ck.fmt);
exit('Invalid extensible format');
case hex2dec('FFFE')
% [opt_ck.fmt, msg] = read_fmt_pcm(fid, ck, opt_ck.fmt);
end
% Skip over any unprocessed fmt-specific data:
%if rem(total_bytes,2), total_bytes=total_bytes+1; end
%rbytes = total_bytes - (ftell(fid) - orig_pos);
%if rbytes~=0,
% if(fseek(fid,rbytes,'cof')==-1),
% msg = err_msg;
% end
%end
return
% ---------------------------------------------
% READ_FMT_PCM: Read <PCM-format-specific> info
% ---------------------------------------------
function [fmt,msg] = read_fmt_pcm(fid, ck, fmt)
% There had better be a bits/sample field:
total_bytes = ck.Size; % # bytes in subchunk
nbytes = 14; % # of bytes already read in <wave-format> header
msg = '';
err_msg = 'Error reading PCM <wave-fmt> chunk.';
%if (total_bytes < nbytes+2),
% msg = err_msg;
% return
%end
%[bits,cnt] = fread(fid,1,'ushort');
%nbytes=nbytes+2;
%if (cnt~=1),
% msg = err_msg;
% return
%end
%fmt.nBitsPerSample=bits;
% Are there any additional fields present?
if (total_bytes > nbytes),
% See if the "cbSize" field is present. If so, grab the data:
if (total_bytes >= nbytes+2),
% we have the cbSize ushort in the file:
[cbSize,cnt]=fread(fid,1,'ushort');
nbytes=nbytes+2;
if (cnt~=1),
msg = err_msg;
return
end
fmt.cbSize = cbSize;
end
% Simply skip any remaining stuff - we don't know what it is:
if rem(total_bytes,2), total_bytes=total_bytes+1; end
rbytes = total_bytes - nbytes;
if rbytes~=0,
if (fseek(fid,rbytes,'cof') == -1);
msg = err_msg;
end
end
end
return
% ---------------------------------------------
% READ_WAVEDAT: Read WAVE data chunk
% Assumes fid points to the wave-data chunk
% Requires <data-ck> and <wave-format> structures to be passed.
% Requires extraction range to be specified.
% Setting ext=[] forces ALL samples to be read. Otherwise,
% ext should be a 2-element vector specifying the first
% and last samples (per channel) to be extracted.
% Setting ext=-1 returns the number of samples per channel,
% skipping over the sample data.
% ---------------------------------------------
function [dat,msg] = read_wavedat(datack,wavefmt,ext)
% In case of unsupported data compression format:
dat = [];
fmt_msg = '';
switch wavefmt.wFormatTag
case 1
% PCM Format:
[dat,msg] = read_dat_pcm(datack,wavefmt,ext);
case 2
fmt_msg = 'Microsoft ADPCM';
case 3
% normalized floating-point
[dat,msg] = read_dat_pcm(datack,wavefmt,ext);
case 6
fmt_msg = 'CCITT a-law';
case 7
fmt_msg = 'CCITT mu-law';
case 17
fmt_msg = 'IMA ADPCM';
case 34
fmt_msg = 'DSP Group TrueSpeech TM';
case 49
fmt_msg = 'GSM 6.10';
case 50
fmt_msg = 'MSN Audio';
case 257
fmt_msg = 'IBM Mu-law';
case 258
fmt_msg = 'IBM A-law';
case 259
fmt_msg = 'IBM AVC Adaptive Differential';
case hex2dec('FFFE') %sc
% WAVE-FORMAT-EXTENSIBLE
[dat,msg] = read_dat_pcm(datack,wavefmt,ext);
otherwise
fmt_msg = ['Format #' num2str(wavefmt.wFormatTag)];
end
if ~isempty(fmt_msg),
msg = ['Data compression format (' fmt_msg ') is not supported.'];
end
return
% ---------------------------------------------
% READ_DAT_PCM: Read PCM format data from <wave-data> chunk.
% Assumes fid points to the wave-data chunk
% Requires <data-ck> and <wave-format> structures to be passed.
% Requires extraction range to be specified.
% Setting ext=[] forces ALL samples to be read. Otherwise,
% ext should be a 2-element vector specifying the first
% and last samples (per channel) to be extracted.
% Setting ext=-1 returns the number of samples per channel,
% skipping over the sample data.
% ---------------------------------------------
function [dat,msg] = read_dat_pcm(datack,wavefmt,ext)
dat = [];
msg = '';
% Determine # bytes/sample - format requires rounding
% to next integer number of bytes:
BytesPerSample = ceil(wavefmt.nBlockAlign / wavefmt.nChannels);
if (BytesPerSample == 1),
dtype='uchar'; % unsigned 8-bit
elseif (BytesPerSample == 2),
dtype='short'; % signed 16-bit
elseif (BytesPerSample == 3)
dtype='bit24'; % signed 24-bit
elseif (BytesPerSample == 4),
% 32-bit 16.8 float (type 1 - 32-bit)
% 32-bit normalized floating point
dtype = 'float';
% 32-bit 24.0 float (type 1 - 24-bit)
if wavefmt.wFormatTag ~= 3 & wavefmt.nBitsPerSample == 24,
BytesPerSample = 3;
end
else
msg = 'Cannot read PCM file formats with more than 32 bits per sample.';
return
end
total_bytes = datack.Size; % # bytes in this chunk
total_samples = total_bytes / BytesPerSample;
SamplesPerChannel = total_samples / wavefmt.nChannels;
if ~isempty(ext) & ext==-1,
% Just return the samples per channel, and fseek past data:
dat = SamplesPerChannel;
% Add in a pad-byte, if required:
total_bytes = total_bytes + rem(datack.Size,2);
if(fseek(datack.fid,total_bytes,'cof')==-1),
msg = 'Error reading PCM file format.';
end
return
end
% Determine sample range to read:
if isempty(ext),
ext = [1 SamplesPerChannel]; % Return all samples
else
if prod(size(ext))~=2,
msg = 'Sample limit vector must have 2 elements.';
return
end
if ext(1)<1 | ext(2)>SamplesPerChannel,
msg = 'Sample limits out of range.';
return
end
if ext(1)>ext(2),
msg = 'Sample limits must be given in ascending order.';
return
end
end
bytes_remaining = total_bytes; % Preset byte counter
% Skip over leading samples:
if ext(1)>1,
% Skip over leading samples, if specified:
skipcnt = BytesPerSample * (ext(1)-1) * wavefmt.nChannels;
if(fseek(datack.fid, skipcnt,'cof') == -1),
msg = 'Error reading PCM file format.';
return
end
%
% Update count of bytes remaining:
bytes_remaining = bytes_remaining - skipcnt;
end
% Read desired data:
nSPCext = ext(2)-ext(1)+1; % # samples per channel in extraction range
dat = datack; % Copy input structure to output
extSamples = wavefmt.nChannels*nSPCext;
dat.Data = fread(datack.fid, [wavefmt.nChannels nSPCext], dtype);
%
% Update count of bytes remaining:
skipcnt = BytesPerSample*nSPCext*wavefmt.nChannels;
bytes_remaining = bytes_remaining - skipcnt;
% if cnt~=extSamples, dat='Error reading file.'; return; end
% Skip over trailing samples:
if(fseek(datack.fid, BytesPerSample * ...
(SamplesPerChannel-ext(2))*wavefmt.nChannels, 'cof')==-1),
msg = 'Error reading PCM file format.';
return
end
% Update count of bytes remaining:
skipcnt = BytesPerSample*(SamplesPerChannel-ext(2))*wavefmt.nChannels;
bytes_remaining = bytes_remaining - skipcnt;
% Determine if a pad-byte is appended to data chunk,
% skipping over it if present:
if rem(datack.Size,2),
fseek(datack.fid, 1, 'cof');
end
% Rearrange data into a matrix with one channel per column:
dat.Data = dat.Data';
% Normalize data range: min will hit -1, max will not quite hit +1.
if BytesPerSample==1,
dat.Data = (dat.Data-128)/128; % [-1,1)
elseif BytesPerSample==2,
dat.Data = dat.Data/32768; % [-1,1)
elseif BytesPerSample==3,
dat.Data = dat.Data/(2^23); % [-1,1)
elseif BytesPerSample==4,
if wavefmt.wFormatTag ~= 3, % Type 3 32-bit is already normalized
dat.Data = dat.Data/32768; % [-1,1)
end
end
return
% end of wavread.m
|
github
|
robical/BlindSourceSeparation-master
|
STFT.m
|
.m
|
BlindSourceSeparation-master/img/Progetto/STFT.m
| 560 |
utf_8
|
c29454de99da3167b1a34b11c3ac81a9
|
%STFT
% CALCOLO DEL NUMERO DI SPLICE:
% numero_splice=1+((length(signal)-length(win))/(length(win)/2))
%
%
function [trasf]=STFT(signal,win)
M=length(win);
R=M/2; %hop size del 50% (M/2)
part(1:M,1)=signal(1:M,1);
splice(1:M,1)=part(1:M,1)'.*win';
cicli=fix((length(signal)-length(win))/(length(win)/2)); %2 o 4
for i=2:cicli;
start=1+(i-1)*(R);
fin=start+length(win)-1;
part(1:M,i)=signal(start:fin,1);
splice(1:M,i)=part(1:M,i)'.*win';
end;
for i=1:(size(splice,2));
trasf(1:M,i)=fft(splice(1:M,i));
end;
|
github
|
robical/BlindSourceSeparation-master
|
wavexwrite.m
|
.m
|
BlindSourceSeparation-master/img/Progetto/wavexwrite.m
| 8,855 |
utf_8
|
5e65dd381efc54d3f9865c9c79100c35
|
function wavexwrite(y,Fs,nbits,wavefile,speakers)
%WAVEXWRITE Write WAVE_FORMAT_EXTENSIBLE sound file.
% WAVEXWRITE(Y,FS,NBITS,WAVEFILE, SPEAKERS) writes data Y to a WAVEX
% file specified by the file name WAVEFILE, with a sample rate
% of FS Hz and with NBITS number of bits. NBITS must be 8, 16,
% 24, or 32. Stereo data should be specified as a matrix with two
% columns. For NBITS < 32, amplitude values outside the range
% [-1,+1] are clipped.
%
% SPEAKERS is a vector of speaker numbers
% e.g. [1,2] for stereo
% [1:5] for 5.1
% [3] for center channel
%
% WAVEXWRITE(Y,FS,WAVEFILE) assumes NBITS=16 bits.
% WAVEXWRITE(Y,WAVEFILE) assumes NBITS=16 bits and FS=44100 Hz.
%
% 8-, 16-, and 24-bit files are type 1 integer PCM. 32-bit files
% are written as type 3 normalized floating point.
%
% Modified 2004/07/27 by Sylvain Choisel
% to handle WAVE-FORMAT-EXTENSIBLE
% email: [email protected]
% Parse inputs:
error(nargchk(2,5,nargin));
if nargin < 3,
wavefile = Fs;
Fs = 44100;
nbits = 16;
elseif nargin < 4,
wavefile = nbits;
nbits = 16;
end
% If input is a vector, force it to be a column:
if ndims(y) > 2,
error('Data array cannot be an N-D array.');
end
if size(y,1)==1,
y = y(:);
end
[samples, channels] = size(y);
if nargin < 5,
speakerMask=2^channels-1;
else
if (length(speakers)~=channels)
error ('Speaker mask length must be equal to the number of channels');
end
speakerMask=sum(2.^(speakers-1));
end
% Determine number of bytes in chunks
% (not including pad bytes, if needed):
% ----------------------------------
% 'RIFF' 4 bytes
% size 4 bytes (ulong)
% 'WAVE' 4 bytes
% 'fmt ' 4 bytes
% size 4 bytes (ulong)
% <wave-format> 14 bytes
% <format_specific> 2 bytes (PCM)
% 'data' 4 bytes
% size 4 bytes (ulong)
% <wave-data> N bytes
% ----------------------------------
bytes_per_sample = ceil(nbits/8);
total_samples = samples * channels;
total_bytes = total_samples * bytes_per_sample;
riff_cksize = 4+48+total_bytes; % Don't include 'RIFF' or its size field
fmt_cksize = 40; % Don't include 'fmt ' or its size field
data_cksize = total_bytes; % Don't include 'data' or its size field
% Determine pad bytes:
data_pad = rem(data_cksize,2);
riff_cksize = riff_cksize + data_pad; % + fmt_pad, always 0
% Open file for output:
[fid,err] = OpenWaveWrite(wavefile);
error(err);
% Prepare basic chunk structure fields:
ck=[]; ck.fid=fid; ck.filename = wavefile;
% Write RIFF chunk:
ck.ID = 'RIFF';
ck.Size = riff_cksize;
error(write_ckinfo(ck));
% Write WAVE subchunk:
ck.ID = 'WAVE';
ck.Size = []; % Indicate a subchunk (no chunk size)
error(write_ckinfo(ck));
% Write <fmt-ck>:
ck.ID = 'fmt ';
ck.Size = fmt_cksize;
error(write_ckinfo(ck));
% Write <wave-format>:
fmt.filename = wavefile;
fmt.wFormatTag = hex2dec('FFFE');
fmt.nChannels = channels; % Number of channels
fmt.nSamplesPerSec = Fs; % Samples per second
fmt.nAvgBytesPerSec = channels*bytes_per_sample*Fs; % Avg transfer rate
fmt.nBlockAlign = channels*bytes_per_sample; % Block alignment
fmt.nBitsPerSample = 8*bytes_per_sample;
fmt.cbSize = 22;
fmt.wValidBitsPerSample = nbits;
fmt.dwSpkMask = speakerMask;
fmt.subFormat = [1 0 0 0 0 0 16 0 8*16 0 0 hex2dec('AA') 0 hex2dec('38') hex2dec('9B') hex2dec('71')];
error(write_wavefmt(fid,fmt));
% Write <data-ck>:
ck.ID = 'data';
ck.Size = data_cksize;
error(write_ckinfo(ck));
% Write <wave-data>, and its pad byte if needed:
error(write_wavedat(fid,fmt,y));
% Close file:
fclose(fid);
% end of wavwrite()
% ------------------------------------------------------------------------
% Private functions:
% ------------------------------------------------------------------------
% ------------------------------------------------------------------------
function [fid,err] = OpenWaveWrite(wavefile)
% OpenWaveWrite
% Open WAV file for writing.
% If filename does not contain an extension, add ".wav"
fid = [];
err = '';
if ~isstr(wavefile),
err='Wave file name must be a string.'; return;
end
% modified 27/07/2004 sc
%if isempty(findstr(wavefile,'.')),
% wavefile=[wavefile '.wav'];
%end
[pathstr,name,ext,versn]=fileparts(wavefile);
if (~strcmp(lower(ext),'.wav'))
wavefile=[wavefile '.wav'];
end
% Open file, little-endian:
[fid,err] = fopen(wavefile,'wb','l');
return
% ------------------------------------------------------------------------
function err = write_ckinfo(ck)
% WRITE_CKINFO: Writes next RIFF chunk, but not the chunk data.
% Assumes the following fields in ck:
% .fid File ID to an open file
% .ID 4-character string chunk identifier
% .Size Size of chunk (empty if subchunk)
%
%
% Expects an open FID pointing to first byte of chunk header,
% and a chunk structure.
% ck.fid, ck.ID, ck.Size, ck.Data
errmsg = ['Failed to write ' ck.ID ' chunk to WAVE file: ' ck.filename];
err = '';
if (fwrite(ck.fid, ck.ID, 'char') ~= 4),
err=errmsg; return;
end
if ~isempty(ck.Size),
% Write chunk size:
if (fwrite(ck.fid, ck.Size, 'ulong') ~= 1),
err=errmsg; return;
end
end
return
% ------------------------------------------------------------------------
function err = write_wavefmt(fid, fmt)
% WRITE_WAVEFMT: Write WAVE format chunk.
% Assumes fid points to the wave-format subchunk.
% Requires chunk structure to be passed, indicating
% the length of the chunk.
errmsg = ['Failed to write WAVE format chunk to file' fmt.filename];
err = '';
% Create <wave-format> data:
if (fwrite(fid, fmt.wFormatTag, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.nChannels, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.nSamplesPerSec, 'ulong' ) ~= 1) | ...
(fwrite(fid, fmt.nAvgBytesPerSec, 'ulong' ) ~= 1) | ...
(fwrite(fid, fmt.nBlockAlign, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.nBitsPerSample, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.cbSize, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.wValidBitsPerSample, 'ushort') ~= 1) | ...
(fwrite(fid, fmt.dwSpkMask, 'ulong' ) ~= 1) | ...
(fwrite(fid, fmt.subFormat, 'uchar' ) ~= 16)
err=errmsg;
end
return
% -----------------------------------------------------------------------
function y = PCM_Quantize(x, fmt)
% PCM_Quantize:
% Scale and quantize input data, from [-1, +1] range to
% either an 8-, 16-, or 24-bit data range.
% Clip data to normalized range [-1,+1]:
ClipMsg = ['Data clipped during write to file:' fmt.filename];
ClipWarn = 0;
% Determine slope (m) and bias (b) for data scaling:
nbits = fmt.nBitsPerSample;
m = 2.^(nbits-1);
switch nbits
case 8,
b=128;
case {16,24},
b=0;
otherwise,
error('Invalid number of bits specified.');
end
y = round(m .* x + b);
% Determine quantized data limits, based on the
% presumed input data limits of [-1, +1]:
ylim = [-1 +1];
qlim = m * ylim + b;
qlim(2) = qlim(2)-1;
% Clip data to quantizer limits:
i = find(y < qlim(1));
if ~isempty(i),
warning(ClipMsg); ClipWarn=1;
y(i) = qlim(1);
end
i = find(y > qlim(2));
if ~isempty(i),
if ~ClipWarn, warning(ClipMsg); end
y(i) = qlim(2);
end
return
% -----------------------------------------------------------------------
function err = write_wavedat(fid,fmt,data)
% WRITE_WAVEDAT: Write WAVE data chunk
% Assumes fid points to the wave-data chunk
% Requires <wave-format> structure to be passed.
err = '';
if fmt.wFormatTag==1 | fmt.wFormatTag==3 | fmt.wFormatTag==hex2dec('FFFE'),
% PCM Format
% 32-bit Type 3 is normalized, so no scaling needed.
if fmt.nBitsPerSample ~= 32,
data = PCM_Quantize(data, fmt);
end
switch fmt.nBitsPerSample
case 8,
dtype='uchar'; % unsigned 8-bit
case 16,
dtype='short'; % signed 16-bit
case 24,
dtype='bit24'; % signed 24-bit
case 32,
dtype='float'; % normalized 32-bit floating point
otherwise,
err = 'Invalid number of bits specified.'; return;
end
% Write data, one row at a time (one sample from each channel):
[samples,channels] = size(data);
total_samples = samples*channels;
if (fwrite(fid, reshape(data',total_samples,1), dtype) ~= total_samples),
err = 'Failed to write PCM data samples.'; return;
end
% Determine # bytes/sample - format requires rounding
% to next integer number of bytes:
BytesPerSample = ceil(fmt.nBitsPerSample/8);
% Determine if a pad-byte must be appended to data chunk:
if rem(total_samples*BytesPerSample, 2) ~= 0,
fwrite(fid,0,'uchar');
end
else
% Unknown wave-format for data.
err = 'Unsupported data format.';
end
return
% end of wavwrite.m
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