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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | pmoulos/gene-armada-master | selectFilesAffy.m | .m | gene-armada-master/InputOutput/selectFilesAffy.m | 2,217 | utf_8 | 4ccc41acfbefaf577af0fe1099a4a9c4 | function [exprp,cdfname,celpathnames,cdfpath,Datatable]=selectFilesAffy(names)
%
% selectFileAffy creates the exprp cell, which contains the filenames for all slides.
% It serves as slide unique identifier for the rest of the analysis
%
% Find experiments directory
currentWD=cd;
dirname=uigetdir('C:\','Sel... |
github | pmoulos/gene-armada-master | readIllumina.m | .m | gene-armada-master/InputOutput/readIllumina.m | 4,836 | utf_8 | d19df8d62ca55ae9bcb4114eb5221967 | function [datstruct,expinfo,attributes]=readIllumina(filename,h,instr)
if nargin<2
h=[];
instr={''};
end
if nargin<3
instr={''};
end
% Read data with specialized Illumina function... for memory, read first headers to select
str1=['Reading data from file : ',filename];
instr=[instr;str1];
upda... |
github | pmoulos/gene-armada-master | exportNormAffy.m | .m | gene-armada-master/InputOutput/exportNormAffy.m | 103,482 | utf_8 | 4833fb744639873e98c51a47dca89cf6 | function [headers,finaldata] = exportNormAffy(exprp,DataCellNormLo,gnID,names,fcinds,opts,filename,prin)
% This function works as a helper for ARMADA to export files. The variable opts
% contains certain export option fields (sse code of ExportDEEditor). When I find some
% time, I will write a complete help.
% op... |
github | pmoulos/gene-armada-master | myimageneread.m | .m | gene-armada-master/InputOutput/myimageneread.m | 7,397 | utf_8 | 92321d1532f881ef27f7f569b338983c | function output = myimageneread(filename,varargin)
%IMAGENEREAD reads ImaGene Results Format files.
%
% IMAGENEDATA = IMAGENEREAD(FILE) reads in ImaGene results format data
% from FILE and creates a structure IMAGENEDATA, containing these fields:
% Header
% Data
% Blocks
% ... |
github | pmoulos/gene-armada-master | Affy2Struct.m | .m | gene-armada-master/InputOutput/Affy2Struct.m | 3,608 | utf_8 | ec4aa74fae31268ff705d940fc5c0a1d | % function [datstruct]=Affy2Struct(celfile,celpath,cdffile,cdfpath)
function datstruct = Affy2Struct(celfile,cdfpath)
%
% Read Affymetrix data in a MATLAB structure
% For internal use
% Please use CREATEDATSTRUCTAFFY for importing data in ARMADA
%
% Read data...
affydata=affyread(celfile,cdfpath);
% Co... |
github | pmoulos/gene-armada-master | exportNorm.m | .m | gene-armada-master/InputOutput/exportNorm.m | 25,051 | utf_8 | 41990367225d8ed9fb940008a382eea1 | function exportNorm(exprp,exptab,DataCellNormLo,gnID,names,fcinds,opts,filename)
% This function works as a helper for ARMADA to export files. The variable opts
% contains certain export option fields (sse code of ExportDEEditor). When I find some
% time, I will write a complete help.
% opts.outtype='text' for ta... |
github | pmoulos/gene-armada-master | agferead.m | .m | gene-armada-master/InputOutput/agferead.m | 7,249 | utf_8 | 9c81de5231926322bba3577e91aa0a57 | function outStruct = agferead(filename)
%AGFEREAD reads Agilent Feature Extraction Format files.
%
% AGFEDATA = AGFEREAD(FILE) reads in Agilent Feature Extraction format data
% from FILE and creates a structure AGFEDATA, containing these fields:
% Header
% Stats
% Columns
% ... |
github | pmoulos/gene-armada-master | TabDelim2Struct.m | .m | gene-armada-master/InputOutput/TabDelim2Struct.m | 10,686 | utf_8 | fcb7852976662c25fd814accc9c7dc62 | function output = TabDelim2Struct(filename,cols,allcolnames)
nfcols=length(allcolnames);
frmt=cell(1,nfcols);
colnames=cell(1,nfcols);
for i=1:nfcols
frmt{i}='%*s'; % Fill with a general skip format
end
if all(cols==0)
uiwait(errordlg('You must specify the column numbers of the files to be read',...... |
github | pmoulos/gene-armada-master | annotateGeneLists.m | .m | gene-armada-master/InputOutput/annotateGeneLists.m | 24,647 | utf_8 | 046267e568ec6089e9960fda65941c54 | function annotateGeneLists(flist,fann,unidg,unida,anncols)
% Function to add annotation element to an output file of ARMADA
% flist : the gene list file (Excel or tab delimited)
% fann : the file that contains the annotation elements (Excel or tab delimited)
% unidg : the unique identifier of genes in the ... |
github | pmoulos/gene-armada-master | selectFiles.m | .m | gene-armada-master/InputOutput/selectFiles.m | 6,811 | utf_8 | 63e50b66b45f0869f15cd6d323bd2c75 | function [exprp,Datatable,pathnames]=selectFiles(t,imgsw,names)
%
% Inputstxt creates the exprp cell, which contains the filenames for all slides.
% It serves as slide unique identifier for the rest of the analysis
%
% Find experiments directory
currentWD = cd;
dirname = uigetdir('C:\','Select your Experim... |
github | pmoulos/gene-armada-master | gprread.m | .m | gene-armada-master/InputOutput/gprread.m | 9,956 | utf_8 | 4a022ac651e72e00e7ac33871d965de6 | function output = gprread(filename,varargin)
%GPRREAD reads GenePix Results Format (GPR) files.
%
% GPRDATA = GPRREAD(FILE) reads in GenePix results format data from FILE
% and creates a structure GPRDATA, containing these fields:
% Header
% Data
% Blocks
% Columns
% ... |
github | pmoulos/gene-armada-master | exportDEfinalAffyTCA.m | .m | gene-armada-master/InputOutput/exportDEfinalAffyTCA.m | 110,022 | utf_8 | b1706dae1622281c8d409fd26aff04b8 | function [headers,finaldata] = exportDEfinalAffyTCA(exprp,names,DataCellNormLo,DataCellStat,tind,opts,filename,prin)
% This function works as a helper for ARMADA to export files. The variable opts
% contains certain export option fields (sse code of ExportDEEditor). When I find some
% time, I will write a complete... |
github | pmoulos/gene-armada-master | excelread.m | .m | gene-armada-master/InputOutput/excelread.m | 10,141 | utf_8 | 2fb2e486892ab3a70a5d9d7b407f966b | function output = excelread(filename,colnums)
%
% Function to read column delimited files (already manipulated outputs from an image
% analysis software). The user must specify certain columns to keep through a GUI. If any
% of the data that the user is prompted to supply does not exist, the user must leave the
... |
github | pmoulos/gene-armada-master | GetColumnsUI.m | .m | gene-armada-master/InputOutput/GetColumnsUI.m | 15,050 | utf_8 | 073f31f751bae4cf850cc44c3b2ede2e | function varargout = GetColumnsUI(varargin)
% GETCOLUMNSUI M-file for GetColumnsUI.fig
% GETCOLUMNSUI, by itself, creates a new GETCOLUMNSUI or raises the existing
% singleton*.
%
% H = GETCOLUMNSUI returns the handle to a new GETCOLUMNSUI or the handle to
% the existing singleton*.
%
% ... |
github | pmoulos/gene-armada-master | ilmnbsread.m | .m | gene-armada-master/InputOutput/ilmnbsread.m | 8,957 | utf_8 | 4b98c7fa000ebe322be34e97191ab781 | function output = ilmnbsread(filename,varargin)
%ILMNBSREAD reads data exported from Illumina BeadStudio.
%
% ILMNSTRUCT = ILMNBSREAD(FILE) reads tab-delimited or comma-separated
% expression data exported from Illumina BeadStudio from FILE and creates
% a structure ILMNSTRUCT, containing these fields:
% ... |
github | pmoulos/gene-armada-master | exportDEfinalAffy.m | .m | gene-armada-master/InputOutput/exportDEfinalAffy.m | 109,718 | utf_8 | 2d0ee1bdb7fb89dec37664cd22a5aa3f | function [headers,finaldata] = exportDEfinalAffy(exprp,DataCellNormLo,DataCellStat,fcinds,opts,filename,prin)
% This function works as a helper for ARMADA to export files. The variable opts
% contains certain export option fields (sse code of ExportDEEditor). When I find some
% time, I will write a complete help.
... |
github | pmoulos/gene-armada-master | plotMABeforeAfter.m | .m | gene-armada-master/Ploting/plotMABeforeAfter.m | 37,177 | utf_8 | 2d90a2cb3ee80db5ccb1067cf73196c9 | function [hpbefore,hpafter] = plotMABeforeAfter(inten,lograt,logratnorm,logratsmth,varargin)
% Count is a variable to help when this function is called multiple times from ARMADA.
% It helps naming handle objects and distinguishing them with the find function
% Set def... |
github | pmoulos/gene-armada-master | createRawImage.m | .m | gene-armada-master/Ploting/createRawImage.m | 5,812 | utf_8 | c39b583815e97846a73c3778fd3c25bf | function him = createRawImage(stru,attrib,ax)
flag=false;
if nargin<3
flag=true;
figure;
ax=axes;
end
% Perform a check in case a subgrid part of the array is black
zeroind=find(attrib.Indices==0);
if ~isempty(zeroind)
attrib.Indices(zeroind)=1;
end
% Determine whether affymetrix or no... |
github | pmoulos/gene-armada-master | mymaimage3D.m | .m | gene-armada-master/Ploting/mymaimage3D.m | 12,070 | utf_8 | 2001f33bba84663043c90efa04b85e82 | function [hOut,hLines] = mymaimage3D(maStruct,attrib,field,varargin)
%MAIMAGE displays a spatial image of microarray data.
%
% MAIMAGE(X,FIELD) displays an image of field FIELD from
% microarray data structure X. Clicking on the image displays a data tip
% showing the value and ID, if known, for a particul... |
github | pmoulos/gene-armada-master | plotMAXY.m | .m | gene-armada-master/Ploting/plotMAXY.m | 2,182 | utf_8 | e1f2608f0360bdae73f61b0832750b99 | function plotMAXY(x,opts,colnams,sup)
if nargin<3
m=size(x,2);
colnams=cell(1,m);
for i=1:m
colnams{i}=['Sample ',num2str(i)];
end
end
if nargin<4
sup='';
end
x=affytransform(x,opts);
n=size(x,2);
mn=nanmean(x);
md=nanmedian(x);
st=nanstd(x);
iq=iqr(x);
[l,b,w,h]=createG... |
github | pmoulos/gene-armada-master | plotExprProfileMulti.m | .m | gene-armada-master/Ploting/plotExprProfileMulti.m | 6,868 | utf_8 | da1249443f78be00d1d10ecc1bb38176 | function hp = plotExprProfileMulti(x,y,varargin)
% Supposing that figure handle is supplied here by the main program
% Defaults
labels='';
titre='Expression Profile';
leg=false;
multicol=false;
xc=x(:);
condnames=cellstr(num2str(xc));
cntrd=false;
% Check various input arguments
if length(varargin)>1
... |
github | pmoulos/gene-armada-master | mymaimage.m | .m | gene-armada-master/Ploting/mymaimage.m | 12,754 | utf_8 | 57409e874495ea18f08d7612be89b7da | function [hOut,hLines] = mymaimage(maStruct,attrib,field,varargin)
%MAIMAGE displays a spatial image of microarray data.
%
% MAIMAGE(X,FIELD) displays an image of field FIELD from
% microarray data structure X. Clicking on the image displays a data tip
% showing the value and ID, if known, for a particular... |
github | pmoulos/gene-armada-master | plotExprProfile.m | .m | gene-armada-master/Ploting/plotExprProfile.m | 6,748 | utf_8 | f364f62d9ae973c7a3f624587c3c616d | function hp = plotExprProfile(x,y,varargin)
% Input y is a matrix of expression data
% Defaults
labels='';
titre='Expression Profile';
leg=false;
multicol=true;
xc=x(:);
condnames=cellstr(num2str(xc));
cntrd=false;
% Check various input arguments
if length(varargin)>1
if rem(nargin,2)~=0
... |
github | pmoulos/gene-armada-master | createRawNormImage.m | .m | gene-armada-master/Ploting/createRawNormImage.m | 5,136 | utf_8 | 7e1f6f8e891f2a3755a810eed0ba5028 | function him = createRawNormImage(stru,attrib,ndata,dim,ax)
flag=false;
if nargin<4
dim=1;
flag=true;
figure;
ax=axes;
elseif nargin<5
flag=true;
figure;
ax=axes;
end
% Perform a check in case a subgrid part of the array is black
zeroind=find(attrib.Indices==0);
if ~isempty... |
github | pmoulos/gene-armada-master | plotMANormSub.m | .m | gene-armada-master/Ploting/plotMANormSub.m | 6,978 | utf_8 | 67fc115e06ae712213f8130a635644ea | function hp = plotMANormSub(areas,inten,logratnorm,titre,disfcline,fc,labels)
% Check various inputs
if nargin<4
titre='';
disfcline=false;
fc=[];
labels='';
elseif nargin<5
disfcline=false;
fc=[];
labels='';
elseif nargin<6
if disfcline
fc=2;
else
fc... |
github | pmoulos/gene-armada-master | plotMASub.m | .m | gene-armada-master/Ploting/plotMASub.m | 4,241 | utf_8 | 12b31225a6df8cedb342ed9e81e139e9 | function hp = plotMASub(areas,inten,lograt,logratsmth,titre,discurve,disfcline,fc,labels)
% Check various inputs
if nargin<5
titre='';
discurve=false;
disfcline=false;
fc=[];
labels='';
elseif nargin<6
discurve=false;
disfcline=false;
fc=[];
labels='';
elseif nargin<7
... |
github | pmoulos/gene-armada-master | plotVolcano.m | .m | gene-armada-master/Ploting/plotVolcano.m | 41,671 | utf_8 | 7eee4fc5d5d19c6fac6c179b6a3c9395 | function hp = plotVolcano(logtreated,logcontrol,pval,varargin)
%
% PropertyName PropertyValue
% -----------------------------------------------------------------------------
% DisplayPLine Display p-value cut of line or not.
% ... |
github | pmoulos/gene-armada-master | plotGeneric.m | .m | gene-armada-master/Ploting/plotGeneric.m | 28,375 | utf_8 | 7c712aa5e6dd0432d9501b95b136e93c | function hp = plotGeneric(x,y,varargin)
% Count is a variable to help when this function is called multiple times from ARMADA.
% It helps naming handle objects and distinguishing them with the find function
% Set defaults
titre='Generic Plot';
xtitre='X';
ytitre='Y';
discutline=false;
logscale=false;
disco... |
github | pmoulos/gene-armada-master | plotMANorm.m | .m | gene-armada-master/Ploting/plotMANorm.m | 26,882 | utf_8 | b9d20e444adce433eb3222c937bf1800 | function hp = plotMANorm(inten,logratnorm,varargin)
% Count is a variable to help when this function is called multiple times from ARMADA.
% It helps naming handle objects and distinguishing them with the find function
% Set defaults
titre='MA Plot';
disfcline=false;
fc=[];
labels='';
affyvalstruct=[];
cou... |
github | pmoulos/gene-armada-master | createDataImage.m | .m | gene-armada-master/Ploting/createDataImage.m | 3,623 | utf_8 | 2b1a8f09985bdb6a6fb920396367845a | function him = createDataImage(datamat,labels,colnames,ax)
flag=false;
if nargin<2
labels={};
colnames={};
end
if nargin<3
colnames={};
end
if nargin<4
flag=true;
figure;
ax=axes;
end
datamat(isinf(datamat))=NaN;
datamat(isnan(datamat))=0;
if flag
him=imagesc(datamat);... |
github | pmoulos/gene-armada-master | createRawImageNoGrid.m | .m | gene-armada-master/Ploting/createRawImageNoGrid.m | 3,868 | utf_8 | a2608e94ed388243212d97537753681b | function him = createRawImageNoGrid(gmat,rmat,labels,colnames,ax)
flag=false;
if nargin<5
flag=true;
figure;
ax=axes;
end
% Scale data (not by max, each column by each max)
sgmat=zeros(size(gmat));
srmat=zeros(size(rmat));
for i=1:size(gmat,2)
sgmat(:,i)=gmat(:,i)/max(gmat(:,i));
end
if... |
github | pmoulos/gene-armada-master | myheatmap.m | .m | gene-armada-master/Ploting/myheatmap.m | 7,786 | utf_8 | 92506bcd0645d44d4a23daf7b06dd2ec | function him = myheatmap(datamat,varargin)
% Set defaults
clusters=[];
hier=false;
hierparams.pdist='euclidean';
hierparams.linkage='average';
hierparams.dimension=1;
cmap='redgreenfixed';
cmapden=64;
scalerows=false;
scalecolumns=false;
scalecolors=false;
labels={};
colnames={};
titre=false;
% Check... |
github | pmoulos/gene-armada-master | plotMA.m | .m | gene-armada-master/Ploting/plotMA.m | 13,201 | utf_8 | a48fd2b1f6bc2b38953ddcc52d98a1e1 | function hp = plotMA(inten,lograt,logratsmth,varargin)
% Count is a variable to help when this function is called multiple times from ARMADA.
% It helps naming handle objects and distinguishing them with the find function
% Set defaults
titre='MA Plot';
discurve=false;
disfcline=false;
fc=[];
labels='';
co... |
github | pmoulos/gene-armada-master | checkboxBad.m | .m | gene-armada-master/Filtering/checkboxBad.m | 6,364 | utf_8 | 1dbd1a4a40088371197b0e48c69283d0 | function varargout = checkboxBad(varargin)
%CHECKBOXBAD M-file for checkboxBad.fig
% CHECKBOXBAD, by itself, creates a new CHECKBOXBAD or raises the existing
% singleton*.
%
% H = CHECKBOXBAD returns the handle to a new CHECKBOXBADNEW or the handle to
% the existing singleton*.
%
% CHECKBOXBAD(... |
github | pmoulos/gene-armada-master | FilterGenesAffy.m | .m | gene-armada-master/Filtering/FilterGenesAffy.m | 26,655 | utf_8 | efb43e1f220cce6c5f6a3f59e1a14f98 | function [DataCellNormLo,TotalBadpoints] = FilterGenesAffy(datstruct,DataCellNormLo,cdffile,varargin)
% Function to apply several quality filters in Affymetrix data
% Set defaults
mas5opts={0.05,0.015,[0.04 0.06]}; % {alpha, tau, limits}
margasabs=false; % Marginal as absent from MAS5 calls
i... |
github | pmoulos/gene-armada-master | FilterGenesIllu.m | .m | gene-armada-master/Filtering/FilterGenesIllu.m | 24,764 | utf_8 | 6757b103d8534c4aa362083817dd3ef4 | function [DataCellNormLo,TotalBadpoints] = FilterGenesIllu(datstruct,DataCellNormLo,varargin)
% Function to apply several quality filters in Illumina data
% Set defaults
pset=[0.98 0.99]; % Limits for present/marginal/absent
margasabs=false; % Marginal as absent from MAS5 calls
invert=false; % Invert d... |
github | pmoulos/gene-armada-master | FindBadpoints.m | .m | gene-armada-master/Filtering/FindBadpoints.m | 38,478 | utf_8 | ebd36e994edafa6ab96a6e2bfc3abf0e | function [exptab,TotalBadpoints] = FindBadpoints(datstruct,t,exprp,imgsw,backCor,...
filMet,noiseParam,doreptest,meanOrMedian,...
reptest,pval,dishis,pbp,condnames,uori,htext)
... |
github | pmoulos/gene-armada-master | TimeCourseANOVAEditor.m | .m | gene-armada-master/Statistics/TimeCourseANOVAEditor.m | 7,585 | utf_8 | 693860cc7d24df44d45a5d8dbfeac6e9 | function varargout = TimeCourseANOVAEditor(varargin)
% TIMECOURSEANOVAEDITOR M-file for TimeCourseANOVAEditor.fig
% TIMECOURSEANOVAEDITOR, by itself, creates a new TIMECOURSEANOVAEDITOR or raises the existing
% singleton*.
%
% H = TIMECOURSEANOVAEDITOR returns the handle to a new TIMECOURSEANOVAEDIT... |
github | pmoulos/gene-armada-master | FCMClustering.m | .m | gene-armada-master/Statistics/FCMClustering.m | 13,063 | utf_8 | a423d9f4135ca422e7c6e817a114e428 | function [FinalTable,clusters,pIndex,centroids,u,group] = FCMClustering(DataCellStat,k,varargin)
%
% Fuzzy C-Means Clustering and formation of Clusters for significant genes
%
% Implemented for ARMADA GUI
%
% Usage: FinalTable = ExpHClustering(DataCellStat,k,varargin)
%
% Arguments:
% DataCellStat : A cell a... |
github | pmoulos/gene-armada-master | tunelda.m | .m | gene-armada-master/Statistics/tunelda.m | 25,439 | utf_8 | d6593ff5ef931ef8eb4ba605db533984 | function tunelda(data,clg,varargin)
%
% Function to perform tuning (and evaluation) of discriminant analysis classifier given
% data matrix and class vectors. This function uses classify and crossvalind. For further
% help please see help on the functions classify and crossvalind of the Bioinformatics
% and St... |
github | pmoulos/gene-armada-master | ExpHClustering.m | .m | gene-armada-master/Statistics/ExpHClustering.m | 15,063 | utf_8 | 5394475f1ca0c89c98ced066528cf770 | function [FinalTable,clusters,pIndex,fig] = ExpHClustering(DataCellStat,varargin)
%
% Hierarchical Clustering and formation of Clusters for significant genes
%
% Available linkage algorithms: single, average, complete
% Available distance algorithms: euclidean, standardized euclidean, Pearson correlation,
% M... |
github | pmoulos/gene-armada-master | tuneknn.m | .m | gene-armada-master/Statistics/tuneknn.m | 28,147 | utf_8 | 20648830c1d55cd2608dc70f24f65bbf | function tuneknn(data,clg,varargin)
%
% Function to perform tuning (and evaluation) of knn classifier given data matrix and
% class vectors. This function uses knnclassify and crossvalind. For further help please
% see help on the functions knnclassify and crossvalind of the Bioinformatics Toolbox.
%
% TUNEKNN... |
github | pmoulos/gene-armada-master | FilterReplicates.m | .m | gene-armada-master/Statistics/FilterReplicates.m | 19,334 | utf_8 | 81804ef69781543117d0b2bc80d0ffa1 | function DataCellFiltered = FilterReplicates(DataCellNormLo,t,gnID,varargin)
%
% Gene filtering before statistical selection, MAD Centering and data averaging for
% filtered missing values based on the Trust Factor
%
% Cut off genes for all experiments which have no data in all replicates
% Replace every gene/e... |
github | pmoulos/gene-armada-master | imputeAndScale.m | .m | gene-armada-master/Statistics/imputeAndScale.m | 4,879 | utf_8 | 491332349c7dc0f6a3f8435be414af88 | function [outdata,aftermeans] = imputeAndScale(indata,when,scale,scaleopts,impt,imptopts)
% indata are in the main format of ARMADA. A cell with as many subcells as the number
% of conditions. The subcells are one matrix with number of columns equal to the number of
% replicates for one condition
if nargin<2
... |
github | pmoulos/gene-armada-master | GapStatistic.m | .m | gene-armada-master/Statistics/GapStatistic.m | 33,480 | utf_8 | d73ddea97cb14bf4f9eea244a2d54346 | function [bestk,gapk,sk] = GapStatistic(DataCellStat,ks,varargin)
%
% Calculation of Gap statistic for the estimation of the optimum number of clusters (based
% on the paper of Tibshirani et al., 2001).
%
% GAPSTAT calculates the optimal number of clusters based on the intra-cluster distances
% measured by spec... |
github | pmoulos/gene-armada-master | QuantileProps.m | .m | gene-armada-master/Statistics/QuantileProps.m | 4,770 | utf_8 | 12d21e8b752152ca89812abf94408f38 | function varargout = QuantileProps(varargin)
% QUANTILEPROPS M-file for QuantileProps.fig
% QUANTILEPROPS, by itself, creates a new QUANTILEPROPS or raises the existing
% singleton*.
%
% H = QUANTILEPROPS returns the handle to a new QUANTILEPROPS or the handle to
% the existing singleton*.
%
... |
github | pmoulos/gene-armada-master | kNNImputeProps.m | .m | gene-armada-master/Statistics/kNNImputeProps.m | 10,989 | utf_8 | cf0e7e50c39dc479bb0fba82fe493fd1 | function varargout = kNNImputeProps(varargin)
% KNNIMPUTEPROPS M-file for kNNImputeProps.fig
% KNNIMPUTEPROPS, by itself, creates a new KNNIMPUTEPROPS or raises the existing
% singleton*.
%
% H = KNNIMPUTEPROPS returns the handle to a new KNNIMPUTEPROPS or the handle to
% the existing singleto... |
github | pmoulos/gene-armada-master | tunesvm.m | .m | gene-armada-master/Statistics/tunesvm.m | 38,172 | utf_8 | b030e99a87337c571251a8e07c26294e | function tunesvm(data,clg,varargin)
%
% Function to perform tuning (and evaluation) of suport vector machines classifier given
% data matrix and class vectors. This function uses the OSU SVM Toolbox
% (http://sourceforge.net/projects/svm/) and the function crossvlind. For further help
% please see help of the ... |
github | pmoulos/gene-armada-master | StatisticalTest.m | .m | gene-armada-master/Statistics/StatisticalTest.m | 13,800 | utf_8 | 58441b943e584a225c290e797cee92c8 | function DataCellStat = StatisticalTest(DataCellFiltered,t,group,slcstatest,multcorr,thecut,tcaninds,htext)
%
% Statistical selection procedure: calculate p-values per gene
% Available statistical tests are Kruskal-Wallis and ANOVA-1way
%
% User does not interact with the command window
%
% Usage: DataCellStat... |
github | pmoulos/gene-armada-master | MAS5Calls.m | .m | gene-armada-master/Statistics/MAS5Calls.m | 10,830 | utf_8 | 15fe85966e0f7c59b67e647db0c80195 | function [calls, pvals] = MAS5Calls(datstruct,cdffile,varargin)
%
% This function calculates present calls for Affymetrix chips which are stored in the
% structure datstruct and more specifically in the filed 'Intensity'. The input variable
% datstruct has a format that is supported by ARMADA. For more informatio... |
github | pmoulos/gene-armada-master | mafdr.m | .m | gene-armada-master/Matlab Altered/mafdr.m | 13,811 | utf_8 | afbf2c8ae10f43243a0d6e1e92a9e4f2 | function [fdr, q, pi0, rs] = mafdr(p, varargin)
%MAFDR estimates false discovery rates (FDR) of multiple hypotheses testing
% of gene expression data from a microarray experiment.
%
% FDR = MAFDR(P) computes the FDR from the p-values P of the hypotheses
% tests of gene expression data obtained by a microarray ... |
github | pmoulos/gene-armada-master | mapcaplot.m | .m | gene-armada-master/Matlab Altered/mapcaplot.m | 27,638 | utf_8 | e9bc9dd5f24526d9536867351bbd52b8 | function output = mapcaplot(varargin)
%MAPCAPLOT creates a Principal Component plot of expression profile data.
%
% MAPCAPLOT(DATA) creates 2D scatter plots of the principal component scores
% of DATA. The scores used for the x and y data are selected from popup
% menus, below each scatter plot.
%
% Onc... |
github | pmoulos/gene-armada-master | affyprobeseqread.m | .m | gene-armada-master/Matlab Altered/affyprobeseqread.m | 11,234 | utf_8 | 250b5d4308d9750879e7e8506f7aca65 | function S = affyprobeseqread(seqfile, cdf, varargin)
%AFFYPROBESEQREAD reads a data file describing the probe sequences on an
% Affymetrix GeneChip.
%
% S = AFFYPROBESEQREAD(SEQFILE, CDF) reads the probe sequence data file,
% SEQFILE, of an Affymetrix GeneChip, and creates a structure, S. CDF can
% be a s... |
github | pmoulos/gene-armada-master | marunmed.m | .m | gene-armada-master/Matlab Altered/marunmed.m | 4,155 | utf_8 | 0cbd902d01bce1f1866105edb9407829 | function c = marunmed(x,y,k)
%MARUNMED One dimensional running median smoother.
% Y = MARUNMED(X,Y, K) computes the running median of order K.
% K - integer width of median window, Default K = 3.
% For K odd, Y(n) is the median of X( n-(K-1)/2 : n+(K-1)/2 ).
% For K even, Y(n) is the median of X( n-K/2 : ... |
github | pmoulos/gene-armada-master | myclustergram.m | .m | gene-armada-master/Matlab Altered/myclustergram.m | 35,220 | utf_8 | 481b7d1193423f8a27a92d015f2b7dfd | function varargout = myclustergram(data,varargin)
%CLUSTERGRAM creates a dendrogram and heat map on the same figure.
%
% CLUSTERGRAM(DATA) creates a dendrogram and heat map from DATA using
% hierarchical clustering with Euclidean distance metric and average
% linkage used to generate the hierarchical tree. T... |
github | pmoulos/gene-armada-master | masmooth.m | .m | gene-armada-master/Matlab Altered/masmooth.m | 25,645 | utf_8 | 6d6c7fb7ffb8590c215dca5cf0c72c9e | function c = masmooth(x,y,span,method,iter,weighting)
%MASMOOTH Helper function for MALOWESS AND MSLOWESS
% Smoothes data using Robust or Non-robust Lowess smoother or with the
% Savitzky-Golay smoother.
%
% Usage: Z = masmooth(X,Y,span,method,iter,weighting)
% Z = masmooth(X,Y,span,'sgolay',degree)
%... |
github | pmoulos/gene-armada-master | mainvarsetnorm.m | .m | gene-armada-master/Matlab Altered/mainvarsetnorm.m | 12,667 | utf_8 | d8b974fdc780bfca5c9f76a3cb5ff981 | function [normY iset iYS] = mainvarsetnorm(X, Y, varargin)
%MAINVARSETNORM performs rank invariant set normalization.
%
% NORMY = MAINVARSETNORM(X,Y), where X and Y correspond to expression values.
% X and Y values are ranked separately. The invariant ranks are selected by
% proportional rank difference bel... |
github | pmoulos/gene-armada-master | myaffyread.m | .m | gene-armada-master/Matlab Altered/myaffyread.m | 7,966 | utf_8 | 51691b84abe284cc287feaee1f257473 | function affystruct = affyread(filename,libdir,noLibCheck)
%AFFYREAD reads Affymetrix GeneChip data files.
%
% AFFYDATA = AFFYREAD(FILE) reads the Affymetrix data file, FILE, and
% creates a structure, AFFYDATA. AFFYREAD can read DAT, EXP, CEL, CHP,
% CDF and GIN files.
%
% AFFYDATA = AFFYREAD(FILE,LIBDI... |
github | pmoulos/gene-armada-master | knnclassify.m | .m | gene-armada-master/Matlab Altered/knnclassify.m | 12,079 | utf_8 | 61068efac88fa62e0d35e299b08daefe | function outClass = knnclassify(sample, TRAIN, group, K, distance,rule)
%KNNCLASSIFY classifies data using the nearest-neighbor method
%
% CLASS = KNNCLASSIFY(SAMPLE,TRAINING,GROUP) classifies each row of the
% data in SAMPLE into one of the groups in TRAINING using the nearest-
% neighbor method. SAMPLE and... |
github | pmoulos/gene-armada-master | statdisptable.m | .m | gene-armada-master/Matlab Altered/statdisptable.m | 7,137 | utf_8 | 51eb3855ec146b36d9ceaebef99c028d | function figh=statdisptable(tbl,maintitle,header,footer,digits,infigh,pfigh,varargin)
%STATDISPTABLE Display a table for the Statistics Toolbox
%
% Utility function used by other functions to display tables
% Author: Tom Lane, 8-20-99
% Copyright 1993-2003 The MathWorks, Inc.
% $Revision: 1.9 $ $Dat... |
github | pmoulos/gene-armada-master | linkage.m | .m | gene-armada-master/Matlab Altered/linkage.m | 9,472 | utf_8 | 4882d1c846b66fb261d0b44f7f5eb44d | function Z = linkage(Y, method, pdistArg)
%LINKAGE Create hierarchical cluster tree.
% Z = LINKAGE(Y) creates a hierarchical cluster tree, using the single
% linkage algorithm. The input Y is a distance matrix such as is
% generated by PDIST. Y may also be a more general dissimilarity
% matrix conforming... |
github | pmoulos/gene-armada-master | dendrogram.m | .m | gene-armada-master/Matlab Altered/dendrogram.m | 13,267 | utf_8 | c00ef0b278b60253bde1041a2fabe6de | function [h,T,perm] = dendrogram(Z,varargin)
%DENDROGRAM Generate dendrogram plot.
% DENDROGRAM(Z) generates a dendrogram plot of the hierarchical binary
% cluster tree represented by Z. Z is an (M-1)-by-3 matrix, generated by
% the LINKAGE function, where M is the number of objects in the original
% data... |
github | pmoulos/gene-armada-master | marunmean.m | .m | gene-armada-master/Matlab Altered/marunmean.m | 4,150 | utf_8 | d790c95899f2d0633883474260000f21 | function c = marunmean(x,y,k)
%MARUNMED One dimensional running median smoother.
% Y = MARUNMED(X,Y, K) computes the running median of order K.
% K - integer width of median window, Default K = 3.
% For K odd, Y(n) is the median of X( n-(K-1)/2 : n+(K-1)/2 ).
% For K even, Y(n) is the median of X( n-K/2 :... |
github | pmoulos/gene-armada-master | affyinvarsetnorm.m | .m | gene-armada-master/Matlab Altered/affyinvarsetnorm.m | 18,997 | utf_8 | 84961a4d7e681e0280aaf3efad67e949 | function [normalizedData, medStruct] = affyinvarsetnorm(values,varargin)
%AFFYINVARSETNORM performs rank invariant normalization of probe intensities
% from multiple Affymetrix DAT or CEL files.
%
% NORMDATA = AFFYINVARSETNORM(DATA), where the columns of DATA correspond to
% separate chips, normalizes the pro... |
github | pmoulos/gene-armada-master | invariantrankselect.m | .m | gene-armada-master/Matlab Altered/invariantrankselect.m | 5,843 | utf_8 | e15e59d364414da2622404016a19956a | function iset = invariantrankselect(baseline, data, tdLIM, stopPCN, L, iterate, adjustTD)
% INVARIANTRANKSELECT Helper function for INVARAINTSETNORM AND MAIRANKNORM Rank
% invariant selection chooses a group of points with a difference in rank below
% a given threshold.
%
% Usage: Z = invariantrankselect(X,Y,prdT... |
github | pmoulos/gene-armada-master | masmooth_timebar.m | .m | gene-armada-master/Matlab Altered/masmooth_timebar.m | 27,851 | utf_8 | 9f94524cf4a6f1d08b3780357e3e1c94 | function c = masmooth_timebar(x,y,span,method,iter,weighting)
%MASMOOTH Helper function for MALOWESS AND MSLOWESS
% Smoothes data using Robust or Non-robust Lowess smoother or with the
% Savitzky-Golay smoother.
%
% Usage: Z = masmooth(X,Y,span,method,iter,weighting)
% Z = masmooth(X,Y,span,'sgolay',de... |
github | pmoulos/gene-armada-master | knnimpute.m | .m | gene-armada-master/Matlab Altered/knnimpute.m | 8,314 | utf_8 | f61a3deaf8c954d6007624ad6bb9d6c9 | function imputed = knnimpute(data,K,varargin)
%KNNIMPUTE imputes missing data using the nearest-neighbor method
%
% KNNIMPUTE(DATA) replaces NaNs in DATA with the corresponding value from
% the nearest-neighbor column using Euclidean distance. If the nearest-
% neighbor column also contains a NaN value, then... |
github | pmoulos/gene-armada-master | grp2idx.m | .m | gene-armada-master/Matlab Altered/grp2idx.m | 2,474 | utf_8 | 9c1cd4c74cbbe7b053c2fe9d4df77854 | function [g,gn] = grp2idx(s)
% GRP2IDX Create index vector from a grouping variable.
% [G,GN]=GRP2IDX(S) creates an index vector G from the grouping
% variable S. S can be a numeric vector, a character matrix (each
% row representing a group name), or a cell array of strings stored
% as a column vector. T... |
github | pmoulos/gene-armada-master | ouitree.m | .m | gene-armada-master/Matlab Altered/ouitree.m | 11,781 | utf_8 | 4e7d83db3c64fb6bed3354cf7e8d8cad | function [tree, container] = ouitree(varargin)
% WARNING: This feature is not supported in MATLAB
% and the API and functionality may change in a future release.
% UITREE creates a uitree component with hierarchical data in a figure window.
% UITREE creates an empty uitree object with default property values in... |
github | pmoulos/gene-armada-master | kmeans.m | .m | gene-armada-master/Matlab Altered/kmeans.m | 27,928 | utf_8 | 84867378569ac3fa441faa1430a4ffca | function [idx, C, sumD, D] = kmeans(X, k, varargin)
%KMEANS K-means clustering.
% IDX = KMEANS(X, K) partitions the points in the N-by-P data matrix
% X into K clusters. This partition minimizes the sum, over all
% clusters, of the within-cluster sums of point-to-cluster-centroid
% distances. Rows of X c... |
github | pmoulos/gene-armada-master | imageDisplayParseInputs.m | .m | gene-armada-master/Matlab Altered/Image/imageDisplayParseInputs.m | 12,186 | utf_8 | 5a704cf3d49040c32d5c7c68167e90d5 | function [common_args,specific_args] = imageDisplayParseInputs(varargin)
%imageDisplayParseInputs Parse inputs for image display functions.
% [common_args,specific_args] =
% imageDisplayParseInputs(specificNames,varargin) parse inputs for image display
% functions including properties specified in property va... |
github | pmoulos/gene-armada-master | iptcheckhandle.m | .m | gene-armada-master/Matlab Altered/Image/iptcheckhandle.m | 3,618 | utf_8 | 248a5fb7dd32fc4164015124269fc49e | function iptcheckhandle(h,valid_types,function_name,variable_name,argument_position)
%IPTCHECKHANDLE Check validity of handle.
% IPTCHECKHANDLE(H,VALID_TYPES,FUNC_NAME,VAR_NAME,ARG_POS)
% checks the validity of the handle H and issues a formatted error
% message if it is invalid. H must be a handle to a sing... |
github | pmoulos/gene-armada-master | imscrollpanel.m | .m | gene-armada-master/Matlab Altered/Image/imscrollpanel.m | 38,402 | utf_8 | 7f9b09c40850d2002b4604aad6ea3dbb | function hScrollpanel = imscrollpanel(varargin)
%IMSCROLLPANEL Scroll panel for interactive image navigation.
% HPANEL = IMSCROLLPANEL(HPARENT, HIMAGE) creates a scroll panel
% containing the target image (the image to be navigated). HIMAGE
% is a handle to the target HIMAGE. HPARENT is the handle to the
% ... |
github | pmoulos/gene-armada-master | IlluminaNorm.m | .m | gene-armada-master/Normalization/IlluminaNorm.m | 3,239 | utf_8 | 31daeec65b496c8036a5fc2d4ea75956 | function [exptab,DataCellNormLo] = IlluminaNorm(datstruct,method,opts,outscale,htext)
% Function to normalize Illumina data
% method : one of 'quantile', 'rankinvariant'
% opts : options structure for each method
% htext : for ARMADA use
if nargin<2
method='quantile';
opts.usemedian=false;
op... |
github | pmoulos/gene-armada-master | AffyBackAdjust.m | .m | gene-armada-master/Normalization/AffyBackAdjust.m | 9,010 | utf_8 | cdce1d53d683e04c5d7af94c93861824 | function exptab = AffyBackAdjust(datstruct,cdffile,method,opts,htext)
% Function to background adjustment Affymetrix data
% method : one of 'rma', 'gcrma', 'plier', 'none'
% opts : options structure for each method
% htext : for ARMADA use
% Check inputs
if nargin<3
method='gcrma';
opts.optcorr=t... |
github | pmoulos/gene-armada-master | NormalizationLOAuto.m | .m | gene-armada-master/Normalization/NormalizationLOAuto.m | 20,189 | utf_8 | b10cb72d9e7e139f61d6f3d55e0a9f02 | function [DataCellNormLo,ngnID]=NormalizationLOAuto(exptab,exprp,t,s,chanInput,SP,usetimebar,gnID,...
sumprobes,sumhow,sumwhen,htext,rankopts)
%
% Global mean/median and LOWESS/LOESS normalization
%
% User does not interact with the command window
%
% Usage: ... |
github | pmoulos/gene-armada-master | NormalizationLOAutoSub.m | .m | gene-armada-master/Normalization/NormalizationLOAutoSub.m | 21,370 | utf_8 | 861dddf85c11ea3de335c91726f9b015 | function [DataCellNormLo,ngnID]=NormalizationLOAutoSub(metacords,exptab,exprp,t,imgsw,s,chanInput,SP,...
usetimebar,gnID,sumprobes,sumhow,htext)
%
% Global mean/median and LOWESS/LOESS subgrid normalization
%
% User does not interact with the command window
... |
github | pmoulos/gene-armada-master | RankInvariantOpts.m | .m | gene-armada-master/Normalization/RankInvariantOpts.m | 9,264 | utf_8 | 8402cd5228eb1e0d39f17caf5d24b950 | function varargout = RankInvariantOpts(varargin)
% RANKINVARIANTOPTS M-file for RankInvariantOpts.fig
% RANKINVARIANTOPTS, by itself, creates a new RANKINVARIANTOPTS or raises the existing
% singleton*.
%
% H = RANKINVARIANTOPTS returns the handle to a new RANKINVARIANTOPTS or the handle to
% ... |
github | pmoulos/gene-armada-master | AffySum.m | .m | gene-armada-master/Normalization/AffySum.m | 3,862 | utf_8 | 2a40c4bbb05e4f0f4205a66426b16d77 | function [DataCellNormLo,probesetIDs] = AffySum(exptab,cdffile,method,opts,isdone,zerohandle,htext)
% Function to background adjustment Affymetrix data
% method : one of 'quantile', 'rankinvariant'
% opts : options structure for each method
if nargin<3
method='medianpolish';
opts.output='log2';
... |
github | pmoulos/gene-armada-master | AdjNormSumAffy.m | .m | gene-armada-master/Normalization/AdjNormSumAffy.m | 17,227 | utf_8 | 79f0baf8b7301935381a3073907874d0 | % function [exptab,DataCellNormLo,probesetIDs] = AdjNormSumAffy(datstruct,cdffile,varargin)
function [DataCellNormLo,probesetIDs] = AdjNormSumAffy(datstruct,cdffile,varargin)
% Function to do everything for Affymetrix data
% Set defaults
back='rma';
backopts.method='RMA';
backopts.trunc=true;
backopts.showpl... |
github | xyang35/BurstImageDenoising-master | discretizeAndGroupImageHomography_old.m | .m | BurstImageDenoising-master/include/discretizeAndGroupImageHomography_old.m | 1,462 | utf_8 | 668419b8746d60db66ff0f69b083d949 | function homographyFlow = discretizeAndGroupImageHomography_old(homographySet, nodeRows, nodeCols, imageRows, imageCols)
% Discretize and group image node homographies to form the homography flow
homographyFlow = zeros(imageRows, imageCols, 2);
rowsPerNode = floor(imageRows / nodeRows);
colsPerNode = floor(imageCols / ... |
github | xyang35/BurstImageDenoising-master | backwardTransform_par.m | .m | BurstImageDenoising-master/include/backwardTransform_par.m | 1,225 | utf_8 | e0630a87d6d0b990cf1159fb7f9baba5 | function adjustedImage = backwardTransform_par(ori_image, homographyFlow)
% Paralleled version for backward transformation
% transforming other images to reference image
% loop in ref image space
% introduce interpolation using neighborhood pixels
parpool(4);
adjustedImage = zeros(size(ori_image));
[rows, cols, ~] = ... |
github | xyang35/BurstImageDenoising-master | refine_core.m | .m | BurstImageDenoising-master/include/refine_core.m | 2,011 | utf_8 | 22cf03ca1cd7b8e7f4ce54d90508bda5 | function homographyLevel = refine_core(homographyLevel, lambda)
MAX_ITER = 50;
[rows, cols] = size(homographyLevel);
num = rows * cols;
R = zeros(3, 3, num);
D = zeros(num, num);
count_record = zeros(num, 1);
% pre-define R, D and count_record, initialize H
for r = 1 : rows
for c = 1 : cols
cur_ind = (r... |
github | xyang35/BurstImageDenoising-master | discretizeAndGroupImageHomography.m | .m | BurstImageDenoising-master/include/discretizeAndGroupImageHomography.m | 1,467 | utf_8 | f9454d3eac8be0ff5f292fd76a836fa4 | function homographyFlow = discretizeAndGroupImageHomography(homographySet, nodeRows, nodeCols, imageRows, imageCols)
% Discretize and group image node homographies to form the homography flow
homographyFlow = zeros(imageRows, imageCols, 2);
rowsPerNode = floor(imageRows / nodeRows);
colsPerNode = floor(imageCols / node... |
github | xyang35/BurstImageDenoising-master | backwardTransform_interp.m | .m | BurstImageDenoising-master/include/backwardTransform_interp.m | 1,113 | utf_8 | a15b3c6326ddfa63d74415408d8bb5ee | function adjustedImage = backwardTransform_interp(ori_image, homographyFlow)
% Updated version for backward transformation
% transforming other images to reference image
% loop in ref image space
% introduce interpolation using neighborhood pixels
adjustedImage = zeros(size(ori_image));
[rows, cols, ~] = size(homogra... |
github | xyang35/BurstImageDenoising-master | getHomographyPyramid.m | .m | BurstImageDenoising-master/include/getHomographyPyramid.m | 4,102 | utf_8 | 2889c16547ce910fce7d0b07f017bc52 | function homographyPyramid = getHomographyPyramid(pyramid, matchedPoints1, matchedPoints2, FEATURELEVEL)
% Compute homography pyramid from matched feature points
featuredPyramid1 = getFeaturedPyramid(pyramid, matchedPoints1, matchedPoints2, FEATURELEVEL);
featuredPyramid2 = getFeaturedPyramidWithRef(pyramid, matchedPoi... |
github | hitlipan/LLCHIK-master | sp_find_sift_grid.m | .m | LLCHIK-master/sift/sp_find_sift_grid.m | 4,053 | utf_8 | 439b3883808ded16d0a8f689abc38078 | function sift_arr = sp_find_sift_grid(I, grid_x, grid_y, patch_size, sigma_edge)
% parameters
num_angles = 8;
num_bins = 4;
num_samples = num_bins * num_bins;
alpha = 9;
if nargin < 5
sigma_edge = 1;
end
angle_step = 2 * pi / num_angles;
angles = 0:angle_step:2*pi;
angles(num_angles+1) = []; % bin centers
[hgt ... |
github | hitlipan/LLCHIK-master | interKernelSum.m | .m | LLCHIK-master/compute_dic/interKernelSum.m | 526 | utf_8 | e65539dd15719a409df27230f910a107 | % one sample is a column vector
% refer to beyond the euclidean distance: ...
function dises = interKernelSum(samples, hikTables, idxes)
samples = samples + 1;
[d, n] = size(samples);
dicSize = length(hikTables);
dises = zeros(dicSize, n);
for ii = 1:dicSize
for jj = 1:d
di... |
github | hitlipan/LLCHIK-master | find_sift_grid.m | .m | LLCHIK-master/compute_dic/PG_SPBOW/find_sift_grid.m | 4,172 | utf_8 | e68f481d8cdf560b479e63c1c8677115 | function sift_arr = find_sift_grid(I, grid_x, grid_y, patch_size, sigma_edge)
% parameters
num_angles = 8;
num_bins = 4;
num_samples = num_bins * num_bins;
alpha = 9;
if nargin < 5
sigma_edge = 1;
end
angle_step = 2 * pi / num_angles;
angles = 0:angle_step:2*pi;
angles(num_angles+1) = []; % bin centers
[hgt wid... |
github | BigRedT/RGBD_Segmentation-master | generate_region_proposals.m | .m | RGBD_Segmentation-master/code/generate_region_proposals.m | 2,436 | utf_8 | f4a2bd318a1fa3ab3976b77c311852f9 | function [region_proposals, edges] = generate_region_proposals(I, params, plotFlag)
%%
% Input:
% I: w x h x 3 color image
% params: initialized in runThis
% plotFlag: [optional] set true, to visualize boxes
% Output:
% regions: [n x 7] array, each row [x1 y1 w h s x2 y2], I(y1:y2, x1:x2) i... |
github | BigRedT/RGBD_Segmentation-master | boxesEval.m | .m | RGBD_Segmentation-master/code/third_party/edge_boxes/release/boxesEval.m | 5,226 | utf_8 | d74a48569e7de4191347e67e7c4ea02b | function recall = boxesEval( varargin )
% Perform object proposal bounding box evaluation and plot results.
%
% boxesEval evaluates a set bounding box object proposals on the dataset
% specified by the 'data' parameter (which is generated by boxesData.m).
% The methods are specified by the vector 'names'. For each... |
github | BigRedT/RGBD_Segmentation-master | edgesEvalDir.m | .m | RGBD_Segmentation-master/code/third_party/edge_boxes/release/edgesEvalDir.m | 5,991 | utf_8 | bc4e65f28e28fd592f0e7886df40b820 | function varargout = edgesEvalDir( varargin )
% Calculate edge precision/recall results for directory of edge images.
%
% Enhanced replacement for boundaryBench() from BSDS500 code:
% http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/
% Uses same format for results and is fully compatible with bou... |
github | BigRedT/RGBD_Segmentation-master | edgeBoxesSweeps.m | .m | RGBD_Segmentation-master/code/third_party/edge_boxes/release/edgeBoxesSweeps.m | 3,242 | utf_8 | 914d338eaade4ff821dfe9ef9de96a8c | function edgeBoxesSweeps()
% Parameter sweeps for Edges Boxes object proposals.
%
% Running the parameter sweeps requires altering internal flags.
% The sweeps are not well documented, use at your own discretion.
%
% Structured Edge Detection Toolbox Version 3.01
% Code written by Piotr Dollar and Larry Zitnick, 2... |
github | BigRedT/RGBD_Segmentation-master | edgesTrain.m | .m | RGBD_Segmentation-master/code/third_party/edge_boxes/release/edgesTrain.m | 13,670 | utf_8 | 5251330fe91ee70d88e2919d66ff3999 | function model = edgesTrain( varargin )
% Train structured edge detector.
%
% For an introductory tutorial please see edgesDemo.m.
%
% USAGE
% opts = edgesTrain()
% model = edgesTrain( opts )
%
% INPUTS
% opts - parameters (struct or name/value pairs)
% (1) model parameters:
% .imWidth - [32] width of i... |
github | BigRedT/RGBD_Segmentation-master | spAffinities.m | .m | RGBD_Segmentation-master/code/third_party/edge_boxes/release/spAffinities.m | 4,319 | utf_8 | b2250da9ac5335d5dfcc28f819efd35e | function [A,E,U] = spAffinities( S, E, segs, nThreads )
% Compute superpixel affinities and optionally corresponding edge map.
%
% Computes an m x m affinity matrix A where A(i,j) is the affinity between
% superpixels i and j. A has values in [0,1]. Only affinities between
% spatially nearby superpixels are comput... |
github | BigRedT/RGBD_Segmentation-master | edgesSweeps.m | .m | RGBD_Segmentation-master/code/third_party/edge_boxes/release/edgesSweeps.m | 8,831 | utf_8 | c36ed011e7daa4ea08d83453e0cf8125 | function edgesSweeps()
% Parameter sweeps for structured edge detector.
%
% Running the parameter sweeps requires altering internal flags.
% The sweeps are not well documented, use at your own discretion.
%
% Structured Edge Detection Toolbox Version 3.01
% Code written by Piotr Dollar, 2014.
% Licensed under the ... |
github | BigRedT/RGBD_Segmentation-master | MRF_MAP.m | .m | RGBD_Segmentation-master/code/third_party/GMM/GMM-HMRF_v1/GMM-HMRF_v1.1/code/three-dimensional/MRF_MAP.m | 2,384 | utf_8 | 96a579a6d6901a9e706ef66eb5a23f6e | %% The MAP algorithm
%---input---------------------------------------------------------
% X: initial 3D labels
% Y: 3D image
% GMM: Gaussian mixture model parameters
% k: number of labels
% g: number of components of each GMM
% MAP_iter: maximum number of iterations of the MAP algorithm
% show_pl... |
github | BigRedT/RGBD_Segmentation-master | HMRF_EM.m | .m | RGBD_Segmentation-master/code/third_party/GMM/GMM-HMRF_v1/GMM-HMRF_v1.1/code/three-dimensional/HMRF_EM.m | 1,229 | utf_8 | 9ae1a4866c4d1a7c31fe65661377ec02 | %% The EM algorithm
%---input---------------------------------------------------------
% X: initial 2D labels
% Y: image
% GMM: Gaussian mixture model parameters
% k: number of labels
% g: number of components of each GMM
% EM_iter: maximum number of iterations of the EM algorithm
% MAP_iter: max... |
github | BigRedT/RGBD_Segmentation-master | image_kmeans.m | .m | RGBD_Segmentation-master/code/third_party/GMM/GMM-HMRF_v1/GMM-HMRF_v1.1/code/three-dimensional/image_kmeans.m | 437 | utf_8 | 920b10cd806e4eb55c2bc0ee5394da78 | %% kmeans algorithm for an image
%---input---------------------------------------------------------
% Y: 3D image
% k: number of clusters
% g: number of GMM components
%---output--------------------------------------------------------
% X: 3D labels
% GMM: Gaussian mixture model parameters
function... |
github | BigRedT/RGBD_Segmentation-master | ind2ijq.m | .m | RGBD_Segmentation-master/code/third_party/GMM/GMM-HMRF_v1/GMM-HMRF_v1.1/code/three-dimensional/ind2ijq.m | 280 | utf_8 | b8e1f1cc9a4f9c448f946de0807b9d88 | %% index to i, j and q conversion
% ind: index
% m: height of each image slice
% n: width of each image slice
% i, j, q: 3D image coordinates
function [i j q]=ind2ijq(ind,m,n)
q=floor((ind-1)/(m*n))+1;
ind=ind-(q-1)*m*n;
i=mod(ind-1,m)+1;
j=floor((ind-1)/m)+1; |
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