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github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-8/mlclass-ex7-008/mlclass-ex7/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | marclamberti/mooc-machine-learning-master | submit.m | .m | mooc-machine-learning-master/Week-9/mlclass-ex8-008/mlclass-ex8/submit.m | 17,515 | utf_8 | 2949fbde41e47f99c42171e2e0a39efc | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-9/mlclass-ex8-008/mlclass-ex8/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | marclamberti/mooc-machine-learning-master | submit.m | .m | mooc-machine-learning-master/Week-3/mlclass-ex2-008/mlclass-ex2/submit.m | 17,086 | utf_8 | 7b02ce6b9daa919a9a66ef0adb401b07 | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-3/mlclass-ex2-008/mlclass-ex2/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | marclamberti/mooc-machine-learning-master | submit.m | .m | mooc-machine-learning-master/Week-5/mlclass-ex4-008/mlclass-ex4/submit.m | 17,129 | utf_8 | 917c487f37cf14037c77e3c57ad78ce1 | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-5/mlclass-ex4-008/mlclass-ex4/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | marclamberti/mooc-machine-learning-master | submit.m | .m | mooc-machine-learning-master/Week-4/mlclass-ex3-008/mlclass-ex3/submit.m | 17,041 | utf_8 | 07a62d95df0814b4ffbc6c2f4b433e22 | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-4/mlclass-ex3-008/mlclass-ex3/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | marclamberti/mooc-machine-learning-master | submit.m | .m | mooc-machine-learning-master/Week-1-2/mlclass-ex1-008/mlclass-ex1/submit.m | 17,317 | utf_8 | 14dfeccc6eb749406cb5d77fabb6bf47 | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-1-2/mlclass-ex1-008/mlclass-ex1/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | marclamberti/mooc-machine-learning-master | submit.m | .m | mooc-machine-learning-master/Week-7/mlclass-ex6-008/mlclass-ex6/submit.m | 16,836 | utf_8 | d4c87e5dbf32a81bdaf04fd017fe4cb3 | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
github | marclamberti/mooc-machine-learning-master | porterStemmer.m | .m | mooc-machine-learning-master/Week-7/mlclass-ex6-008/mlclass-ex6/porterStemmer.m | 9,902 | utf_8 | 7ed5acd925808fde342fc72bd62ebc4d | function stem = porterStemmer(inString)
% Applies the Porter Stemming algorithm as presented in the following
% paper:
% Porter, 1980, An algorithm for suffix stripping, Program, Vol. 14,
% no. 3, pp 130-137
% Original code modeled after the C version provided at:
% http://www.tartarus.org/~martin/PorterStemmer/c.tx... |
github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-7/mlclass-ex6-008/mlclass-ex6/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | marclamberti/mooc-machine-learning-master | submit.m | .m | mooc-machine-learning-master/Week-6/mlclass-ex5-008/mlclass-ex5/submit.m | 17,211 | utf_8 | 057662350ffa8db95583373185a26a6b | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
github | marclamberti/mooc-machine-learning-master | submitWeb.m | .m | mooc-machine-learning-master/Week-6/mlclass-ex5-008/mlclass-ex5/submitWeb.m | 827 | utf_8 | bfb2fa08cac9d8d797e3071d3fdd7ca1 | % submitWeb Creates files from your code and output for web submission.
%
% If the submit function does not work for you, use the web-submission mechanism.
% Call this function to produce a file for the part you wish to submit. Then,
% submit the file to the class servers using the "Web Submission" button on ... |
github | davidnbresch/climada_module_salvador_demo-master | climada_measure_viewer.m | .m | climada_module_salvador_demo-master/code/climada_measure_viewer.m | 55,232 | utf_8 | 54ee33b6d80813d23407af7d7dcccf91 | function varargout = climada_measure_viewer(varargin)
% climada measure
% MODULE:
% core
% NAME:
% climada_measure_viewer
% PURPOSE:
% plots entities, assets and damage
% climada_measure_viewer, by itself, creates a new climada_measure_viewer or raises the existing
% singleton*.
%
% H = climada_me... |
github | lamilami/openmovement-master | OMX_readFile.m | .m | openmovement-master/Software/Analysis/Matlab/OMX_readFile.m | 21,297 | utf_8 | ac7a6818625180357606bc18d4684b7c | function data = OMX_readFile(filename, varargin)
%
% NOTES:
% * This version defaults to reading just the accelerometer values.
% * The gyroscope/magnetometer data can be read when given the options: 'modality', [1, 1, 1]
% * Stepped data can be read given the options: 'step', 100
% ... |
github | lamilami/openmovement-master | resampleACC.m | .m | openmovement-master/Software/Analysis/Matlab/resampleACC.m | 992 | utf_8 | fd5f513c57872c11df4d9451ce6f5f6d | % Load CWA file with optional re-sampling.
% Returns tri-axial data with the format: [timestamp x y z] in units of 'g'
%
% Example:
%
% % Load CWA file re-sampled at 100Hz
% Fs = 100;
% data = AX3_readFile('CWA-DATA.CWA');
% data.ACC = resampleACC(data, Fs);
%
function D = resampleACC(data, interpRate)
... |
github | lamilami/openmovement-master | AX3_readFile.m | .m | openmovement-master/Software/Analysis/Matlab/AX3_readFile.m | 17,262 | utf_8 | 32881d84ae6978308d60502f0569cf3a | function data = AX3_readFile(filename, varargin)
%
% DATA = AX3_readFile(FILENAME, [OPTIONS])
%
% Reads in binary file as produced by AX3 accelerometer. Returns a
% struct filled with data from different modalities (ACC, LIGHT,
% TEMP). Relies on two external mex-functions (parseValueBlo... |
github | lamilami/openmovement-master | epochs.m | .m | openmovement-master/Software/Analysis/Matlab/epochs.m | 966 | utf_8 | afa1d4145d2ad851c907af35595cbeb2 | % Calculate epochs of the specified bucket size.
%
% Example:
%
% % Load CWA file re-sampled at 100Hz
% Fs = 100;
% data = resampleCWA('CWA-DATA.CWA', Fs);
%
% % HP-Filtered SVM-1
% svm = SVM(data, Fs, 1);
%
% % Convert to 60 second epochs (sum of absolute SVM-1 values)
% epochSVM = epochs(abs(svm), 60 * F... |
github | lamilami/openmovement-master | SVM.m | .m | openmovement-master/Software/Analysis/Matlab/SVM.m | 1,277 | utf_8 | 34760145d18804d9c9278ecd964e2981 | % Calculate SVM-1, with optional HP-filter
% Assumes tri-axial data with the format: [timestamp x y z] in units of 'g'
%
% Example:
%
% % Load CWA file re-sampled at 100Hz
% Fs = 100;
% data = resampleCWA('CWA-DATA.CWA', Fs);
%
% % HP-Filtered SVM-1
% svm = SVM(data, Fs, 1);
%
% % Convert to 60 second epoc... |
github | lamilami/openmovement-master | resampleCWA.m | .m | openmovement-master/Software/Analysis/Matlab/resampleCWA.m | 709 | utf_8 | a1b0224306ad1fc11c21a4c088a1b9ec | % Load CWA file with optional re-sampling.
% Returns tri-axial data with the format: [timestamp x y z] in units of 'g'
%
% Example:
%
% % Load CWA file re-sampled at 100Hz
% Fs = 100;
% data = resampleCWA('CWA-DATA.CWA', Fs);
%
function D = resampleCWA(filename, interpRate)
fprintf('\treading file inform... |
github | lamilami/openmovement-master | findHoles.m | .m | openmovement-master/Software/Analysis/Matlab/old/findHoles.m | 1,916 | utf_8 | 1b67c555615418202111e3f0afc0f648 | % Copyright (c) 2009-2013, Newcastle University, UK.
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% 1. Redistributions of source code must retain the above copyright notice,
% this list ... |
github | lamilami/openmovement-master | interpolateElan.m | .m | openmovement-master/Software/Analysis/Matlab/old/interpolateElan.m | 2,568 | utf_8 | 5eed817372fb8f52cfecde62c7e60618 | % Copyright (c) 2009-2013, Newcastle University, UK.
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% 1. Redistributions of source code must retain the above copyright notice,
% this list ... |
github | lamilami/openmovement-master | findWET_energy.m | .m | openmovement-master/Software/ThirdParty/OMPA/findWET_energy.m | 1,537 | utf_8 | 66f7fc4e8fe35347ae4defa4b300ef01 | % WET - Work Energy Theorem
% Notes: Uses the equation:
% kcals = counts * 0.0000191 * mass
% where kcals = Total calories for a single epoch
% counts = count level for single epoch
%
% Input: mass = body mass in Kg
% data = triaxial accelerometer data in row-wise fashi... |
github | lamilami/openmovement-master | findPA.m | .m | openmovement-master/Software/ThirdParty/OMPA/findPA.m | 15,606 | utf_8 | 1ca38106394f2a71d5b7372062d3370d | % Copyright (c) 2009-2012, Newcastle University, UK.
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% 1. Redistributions of source code must retain the above copyright notice,
% this list of c... |
github | lamilami/openmovement-master | defaultMetaAX3.m | .m | openmovement-master/Software/ThirdParty/OMPA/defaultMetaAX3.m | 3,865 | utf_8 | 3c122757c4f4043c6def9518c29ca837 | % Copyright (c) 2009-2012, Newcastle University, UK.
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% 1. Redistributions of source code must retain the above copyright notice,
% this list ... |
github | lamilami/openmovement-master | findSigEnergy.m | .m | openmovement-master/Software/ThirdParty/OMPA/findSigEnergy.m | 993 | utf_8 | 53d90f333159ed83c6dd033980106f46 | % Notes: Finds Signal Energy using a sliding window approach.
%
% Input Takes in triaxial accelerometer data in row-wise fashion.
% Assumes Col(1) is the time base and calculates fs from this at a constant
% rate
% E.g each row has a t(col1), xaxis(col2), yaxis(col3), zaxis(col4)% O... |
github | lamilami/openmovement-master | findPA_usesVarArgin.m | .m | openmovement-master/Software/ThirdParty/OMPA/findPA_usesVarArgin.m | 7,772 | utf_8 | f5eee5d67fe5f8124946e92962dd06d4 | % Copyright (c) 2009-2012, Newcastle University, UK.
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% 1. Redistributions of source code must retain the above copyright notice,
% this list ... |
github | lamilami/openmovement-master | findgps.m | .m | openmovement-master/Software/ThirdParty/OMPA/findgps.m | 1,210 | utf_8 | b0c009ff7ea4b826950efc2f27a97c65 | % Notes: Finds the ammount of g's per second based.
% Input: data = Takes in triaxial accelerometer data in row-wise fashion.
% Assumes Col(1) is the time base and calculates fs from this at a constant
% rate
% E.g each row has a t(col1), xaxis(col2), yaxis(... |
github | lamilami/openmovement-master | findVM_energy.m | .m | openmovement-master/Software/ThirdParty/OMPA/findVM_energy.m | 939 | utf_8 | 2f1745be2633be9cecd6f93da351f560 | % VM - Vector Magnitude
% Validated by Freedson 2010 for epoch counts > 2453
% Uses the equation:
% kcals = scale * (0.00097*SVM +(0.08793 * mass) - 5.01582)
% where kcals = Total calories for a single epoch
% counts = count level for single epoch
% mass = body mass in Kg
% scale = Epoch peri... |
github | lamilami/openmovement-master | SetMeta.m | .m | openmovement-master/Software/ThirdParty/OMPA/SetMeta.m | 245 | utf_8 | 1bc718a0296f5a4e3378cd164f70f1a7 | %% Takes input meta-data from a FileInfo Object read from a Device
%% and enters it into a existing structure.
function SetMeta(input,output)
{
%some code goes here to overwrite output's existing parameters with
%those of inputs.
} |
github | lamilami/openmovement-master | summarizeData.m | .m | openmovement-master/Software/ThirdParty/OMPA/summarizeData.m | 3,660 | utf_8 | cb990666db60ce85fbe196f0a2cb2795 |
%Epoch length must be specified as: secs,mins,hours,days
function SummarizedData = summarizeData(EpochLength,data)
startTime = data(2,1); %start at second time stamp as problem sometimes with 1st one...
stopTime = data(end,1);
if(strcmpi(EpochLength,'secs'))
%secs - each row is a second so no need to find index... |
github | lamilami/openmovement-master | findPAEE_energy.m | .m | openmovement-master/Software/ThirdParty/OMPA/findPAEE_energy.m | 3,040 | utf_8 | 203d0bf29e3f98f349e556001d0108ce | % PAEE - Physical Activity Energy Expendiature
% Notes: Uses the techniques described in
% http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3146494/
%
% Input: mass = body mass in Kg
% data = triaxial accelerometer data in row-wise fashion.
% E.g each row has an time(col1), xaxis(col2),... |
github | lamilami/openmovement-master | findSVM.m | .m | openmovement-master/Software/ThirdParty/OMPA/findSVM.m | 358 | utf_8 | 1cf8766f8f837cb8082801e55bef98c5 | % Notes: Finds the standard vector magnitude of an input matrix.
% Input: Takes in triaxial accelerometer data in row-wise fashion.
% E.g each row has an xaxis(col1), yaxis(col2), zaxis(col3)
% Output: Standard vector mag (not removeing gravity component)
function svm=findSVM(xyz)
svm = sqrt(xyz(:,1... |
github | lamilami/openmovement-master | findEnergy.m | .m | openmovement-master/Software/ThirdParty/OMPA/findEnergy.m | 401 | utf_8 | 43000a0935dfafd5a4d0ff43252fe749 | % input xyz - x y and z data in g
% input sampleFreq in Hz
% output Energy as sliding window implementation
function energy = findEnergy(xyz,sampleFreq)
if (size(xyz) < sampleFreq)
fprintf('Not enough data. SVM must be larger than sample Freq\r\n');
end
wl = sampleFreq/2;
for i = 1:len... |
github | lamilami/openmovement-master | findPA_win32.m | .m | openmovement-master/Software/ThirdParty/OMPA/findPA_win32.m | 3,572 | utf_8 | 1c0537e6a84a12299347262fcb43e781 | % Copyright (c) 2009-2012, Newcastle University, UK.
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% 1. Redistributions of source code must retain the above copyright notice,
% this list ... |
github | lamilami/openmovement-master | findPAIT.m | .m | openmovement-master/Software/ThirdParty/OMPA/findPAIT.m | 4,644 | utf_8 | 6e43c1b380bf1b9f3208d8911382d5aa | % PAIT - Physical Activity Intensity Time Estimation
% Notes: Uses the techniques described in
% http://www.geneactiv.co.uk/media/1677/esliger_et_al_2011.pdf
%
% Input: data = triaxial accelerometer data in row-wise fashion.
% E.g each row has an time(col1), xaxis(col2), yaxis(col3), ... |
github | lamilami/openmovement-master | findVMC_energy.m | .m | openmovement-master/Software/ThirdParty/OMPA/findVMC_energy.m | 929 | utf_8 | 2936315b3cb55f2c59b7c011422cd042 | % VMC_WET - Vector Magnitude, Work Energy Theorem Combined
% Uses VMC where 60 sec epoch counts > 2453 and WET <=2453
% where kcals = Total calories for a single epoch
% counts = count level for single epoch
% mass = body mass in Kg
% scale = Epoch period (s) / 60
%
% Input: mass = body ma... |
github | duijnhouwer/DPX-master | dpxStimOccluders.m | .m | DPX-master/dpxStimuli/@dpxStimOccluders/dpxStimOccluders.m | 7,640 | utf_8 | f66fed17cbde37b42236cb9010c9979c | classdef dpxStimOccluders < dpxAbstractVisualStim
%DPXOCCLUDERS Summary of this class goes here
% Detailed explanation goes here
% DOES NOT WORK
properties (Access=public)
NReps=10;
PicsPerBlock=5;
NrBars=4;
barConfig='even';
disparityFrac... |
github | duijnhouwer/DPX-master | dpxStimImage.m | .m | DPX-master/dpxStimuli/@dpxStimImage/dpxStimImage.m | 6,323 | utf_8 | bac9d6287604f4511ca8c9268d9c3b29 | classdef dpxStimImage < dpxAbstractVisualStim
properties (Access=public)
RGBA=[0 0 255 255];
mode='Encode'
NrBars=4;
HorDisp=0;
BarConfig='even'
stimLoc=0;
stimList;
picNum;
inputFolder;
scale=1;
dots=[];
... |
github | duijnhouwer/DPX-master | dpxStimRotCylinder.m | .m | DPX-master/dpxStimuli/@dpxStimRotCylinder/dpxStimRotCylinder.m | 11,955 | utf_8 | 929939fdad3e85ffc9807aae1a2ac36e | classdef dpxStimRotCylinder < dpxAbstractVisualStim
properties (Access=public)
dotsPerSqrDeg=10;
rotSpeedDeg=120;
disparityFrac=1;
sideToDraw='front'; % 'front','back','both'
dotRGBA1frac=[1 1 1 1];
dotRGBA2frac=[0 0 0 1];
axis='hori';
d... |
github | duijnhouwer/DPX-master | dpxRespContiMouse.m | .m | DPX-master/dpxResponses/@dpxRespContiMouse/dpxRespContiMouse.m | 3,460 | utf_8 | 32e596d5b5e41f1900e738700237de74 | classdef dpxRespContiMouse < dpxAbstractResp
properties (Access=public)
mouseId=[];
defaultX;
defaultY;
doReset;
end
properties (Access=protected)
nrTotalSamples;
nrSamplesTaken;
startTime;
end
methods (Access=public)
function R=dp... |
github | duijnhouwer/DPX-master | rdFixDataTrialStructBug.m | .m | DPX-master/dpxTools/rdFixDataTrialStructBug.m | 1,014 | utf_8 | 8af2f2d418953f324e430ca448c7c2b0 | function rdFixDataTrialStructBug
files=dpxUIgetfiles;
for i=1:numel(files)
load(files{i});
[didfix,newdata]=fix(data);
if didfix
save([files{i} 'BACKUP'],'data');
data=newdata;
save(files{i},'data');
else
disp(['[rdF... |
github | duijnhouwer/DPX-master | dpxdToolRenameFields.m | .m | DPX-master/dpxTools/dpxdToolRenameFields.m | 7,898 | utf_8 | 3d7fba017f5e7ecb0fede722429da216 | function dpxdToolRenameFields(old,new)
% dpxdToolRenameFields(old,new)
%
% Rename structure fields in DPXDs. A file selector will open. old and new
% are string or a cell array of strings corresponding to the old and the
% new fieldnames. If old and new are cell-arrays, they should be of ... |
github | duijnhouwer/DPX-master | dpxToolStimWindowGui.m | .m | DPX-master/dpxTools/dpxToolStimWindowGui/dpxToolStimWindowGui.m | 8,837 | utf_8 | 42442265bc4bb762237719076c9c1967 | function varargout = dpxToolStimWindowGui(varargin)
% dpxToolStimWindowGui
% Jacob 2014-05-29
% Type dpxToolStimWindowGui and press Help button for instructions.
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Sin... |
github | duijnhouwer/DPX-master | dpxToolCommentEditor.m | .m | DPX-master/dpxTools/dpxToolCommentEditor/dpxToolCommentEditor.m | 12,746 | utf_8 | 1d1d1f0c2594638dd95e3d1f3eb00614 | function varargout = dpxToolCommentEditor(varargin)
% DPXTOOLCOMMENTEDITOR MATLAB code for dpxToolCommentEditor.fig
% DPXTOOLCOMMENTEDITOR, by itself, creates a new DPXTOOLCOMMENTEDITOR or raises the existing
% singleton*.
%
% H = DPXTOOLCOMMENTEDITOR returns the handle to a new DPXTO... |
github | duijnhouwer/DPX-master | gridfit.m | .m | DPX-master/dpxTools/@dpxToolsHalfDomeWarp/private/gridfit.m | 34,995 | utf_8 | e58c0dba921cb156ee39a27dd18a4d1c | function [zgrid,xgrid,ygrid] = gridfit(x,y,z,xnodes,ynodes,varargin)
% gridfit: estimates a surface on a 2d grid, based on scattered data
% Replicates are allowed. All methods extrapolate to the grid
% boundaries. Gridfit uses a modified ridge estimator to
% generate the surface, where the bi... |
github | duijnhouwer/DPX-master | jdRearProjectionCam.m | .m | DPX-master/extra/jdRearProjectionCam.m | 4,448 | utf_8 | 910d6db04a2661d28b45f36a29504b0b | function jdRearProjectionCam
maxHz=3;
cam=selectCam();
if isempty(cam)
return;
end
hFig=figure(666);
set(hFig,'menubar','none','name',mfilename,'NumberTitle','off');
image(fliplr(snapshot(cam)));
set(gca,'Units','normalized','position',[0 0 1 1]);
axis equal o... |
github | duijnhouwer/DPX-master | jdSpeedContrast.m | .m | DPX-master/extra/jdSpeedContrast.m | 15,820 | utf_8 | 59a5946cc2f1f2304d7775abd04d3a04 |
function jdSpeedContrast
% plotExample;
global fitopts
models={'EoffIsMinusIoff'};%,'EoffZero'}%,''};EoffZero EoffIsMinusIoff OneOffOneSig
for i=1:numel(models)
fitopts=models{i};
M.(fitopts)=[ KrekelbergVanWezelAlbright2006 ]; % packHunterBorn2005 rodmanAlbright1987 KrekelbergVan... |
github | duijnhouwer/DPX-master | jdSpeedContrastNew.m | .m | DPX-master/extra/jdSpeedContrastNew.m | 16,950 | utf_8 | de53a8ce1d9c806f44fb49667af0978c | function jdSpeedContrast
global fitopts
global fitcounter
global plotfitcounter
fitcounter=0;
plotfitcounter=0;
% models={'IoffIsNegXoff','XoffZero','IoffZero'}%'XoffIoff'};
models={'IoffIsNegXoff'}%,'XoffIoff'}%'XoffIoff'};
%%
global rodAlb;
rodAlb=fals... |
github | duijnhouwer/DPX-master | jdMovieRandomDots.m | .m | DPX-master/extra/jdMovieRandomDots.m | 11,342 | utf_8 | 7ab25a4f6291f59c512c47e93fcbc5e9 | function jdMovieRandomDots(varargin)
% jdMovieRandomDots(varargin)
% Function to generate animated random dot movies
%
% EXAMPLE:
% % A 4-second movie of a 3.5-pixels per frame leftward grating:
% jdMovieRandomDots('dX',-3.5,'frHz',30,'frN',120)
%
% See also: jdMovieT... |
github | duijnhouwer/DPX-master | jdMovieGrating.m | .m | DPX-master/extra/jdMovieGrating.m | 4,017 | utf_8 | d3e5ff35c5a93d4cdf8862c9e6aa148d | function jdMovieGrating(varargin)
% jdMovieGrating(varargin)
% Function to generate animated grating movies
%
% EXAMPLE:
% % A 4-second movie of a 3.5-pixels per frame left-up grating:
% jdMovieGrating('pxPerFr',3.5,'aDeg',135,'frHz',30,'frN',120)
%
% Jacob Duijnhouwe... |
github | duijnhouwer/DPX-master | rankcorr.m | .m | DPX-master/extra/@circular/rankcorr.m | 2,736 | utf_8 | b200b63cef1facf5594ee466d78ee474 | function [r,p,U] = rankcorr(c1,c2);
% Rank correlation coefficients for two sets of circular data or for circular and linear data.
%
% INPUT
% c1 = Circular data
% c2 = Circular data object or linear data in a vector.
%
% OUTPUT
% r = The correlation coefficient.
% p = The p-value associated with the... |
github | duijnhouwer/DPX-master | bin.m | .m | DPX-master/extra/@circular/bin.m | 3,754 | utf_8 | cbea47972ec8a1eda5daf4e89e496b5c |
function [cN,cM,cE,binidx]=bin(c,varargin)
% function [cN,cM,cE,binidx]=bin(c,varargin)
%
% Bin the observations in circular object bins, calculating the number of
% observations per bin, their means, and there error ranges (std, sem).
%
% INPUT
% c: circular object containing the observations to bin
% ... |
github | duijnhouwer/DPX-master | vonmisesfit.m | .m | DPX-master/extra/@circular/vonmisesfit.m | 8,193 | utf_8 | 786711cc57ce092bf4b9f27223f20967 | function [vmf, est, estci, r2, ftest, residual]=vonmisesfit(c,varargin)
% Fit a Von Mises-based model to the circular object c using nlinfit. The
% fit model is a Von Mises curve spanned between the range of 0 and 1,
% multiplied by a gain and shifted by an offset. Sine skew is optional.
%
% INPUT
% c: circul... |
github | duijnhouwer/DPX-master | istuned.m | .m | DPX-master/extra/@circular/istuned.m | 2,646 | utf_8 | 4deef37e64419bb491fab35cdaa1c4aa | function [tuned tunestruct]=istuned(c,varargin)
% Determine whether circular object c exhibits tuning by fitting a scaled
% and offset Von Mises to the data. The curve is considered tuned if the
% confidence intervals of the gain and the concentration parameter kappa do
% not contain zero. In addition, the model ... |
github | duijnhouwer/DPX-master | circular.m | .m | DPX-master/extra/@circular/circular.m | 4,165 | utf_8 | 1abe282a77db38f951e36475f23abdbf | function c= circular(x,y,units,axial)
% Constructor for the circular class. This class encapsulates the properties of
% circular data. It provides methods of descriptive statistics as well as methods
% for hypothesis testing. See @circular/docs/usage.pdf for a brief introduction or
% @circular/docs/reference.pdf fo... |
github | duijnhouwer/DPX-master | test.m | .m | DPX-master/extra/@circular/docs/test.m | 6,188 | utf_8 | 1baea988240b904e901d7b21eb29e0c1 | function test(in)
% This script tests most of the methods of the @Cricular class with examples
% given in Batschelet1981.
% The name of the test is given, followed by two columns of numbers. On the left
% is what the Circular Toolbox calculated, on the right is the value given in
% Batschelet. Note that someti... |
github | duijnhouwer/DPX-master | jdAdelsonBergenFig16.m | .m | DPX-master/extra/jdAdelsonBergen/jdAdelsonBergenFig16.m | 1,213 | utf_8 | baf9a9b67cd02902c1841b94a5a5a5d2 | function jdAdelsonBergenFig16
load('\\vision\dfs\home\jacob\My Documents\MATLAB\DPX\extra\jdAdelsonBergen\@jdAdelsonBergen\private\AB16.mat');
dpxFindFig('Phi');
XT=stim;
plotStage4(XT);
dpxFindFig('Static')
XT=stim;
for t=1:4:size(XT,1)-3
XT(t:t+3,:)=circshift(XT... |
github | duijnhouwer/DPX-master | dpxDisplayText.m | .m | DPX-master/dpxCore/base/dpxDisplayText.m | 5,147 | utf_8 | 92d1eb0491ec4403a1f1273fecad92c6 | function escPressed=dpxDisplayText(windowPtr,text,varargin)
% escPressed=dpxDisplayText(windowPtr,text,varargin)
%
% EXAMPLES:
%
% Display 'Press a key' that fades in 1 s and that fades out and
% continues the after a key press and release
% dpxDisplayText(windowPtr,'Press a key' ,'fa... |
github | duijnhouwer/DPX-master | dpxVersion.m | .m | DPX-master/dpxCore/base/dpxVersion.m | 3,000 | utf_8 | 9df26d2fe659450187fb07e5ea904a0e | function revisionNr=dpxVersion(varargin)
% revisionNr=dpxVersion(varargin)
%
% dpxVersion('svncompare',false,'offerupdate',false)
% returns current local DPX revision
%
% dpxVersion('svncompare',true,'offerupdate',false)
% returns current local DPX revision and notif... |
github | duijnhouwer/DPX-master | dpxMergeStructs.m | .m | DPX-master/dpxCore/base/dpxMergeStructs.m | 3,769 | utf_8 | dd392554d42c3cb7cba1fc1a78e1a688 | function u=dpxMergeStructs(s,str)
% U=dpxMergeStructs(S,[STR])
% Merge the structures in cell-array of structures S,
% Either all structures need to have with unique fieldnames, or make them
% unique in one of three ways:
% 1 provide unique labels in cell-array of strings STR. If the last
... |
github | duijnhouwer/DPX-master | dpxSeconds2readable.m | .m | DPX-master/dpxCore/base/dpxSeconds2readable.m | 1,365 | utf_8 | 486ff2364274bcbe5a2a934ff771257b | function [str]=dpxSeconds2readable(seconds,format)
% str=seconds2readable(seconds,format)
% Return a legible time format string.
%
% Example:
% h=tic; pause(2);
% fprintf('Example finished in %s\n',seconds2readable(toc(h)));
%
% Jacob 2011-10-18
seconds=round(seconds);
if nargin==1
format='shorte... |
github | duijnhouwer/DPX-master | dpxFlattenStruct.m | .m | DPX-master/dpxCore/base/dpxFlattenStruct.m | 883 | utf_8 | 873d8db8c1e2fdcb142ee22c2e405661 | function f=dpxFlattenStruct(s)
% f=dpxFlattenStruct(s)
%
% Flatten a nested structure ('.' levels replaced by '_')
% Jacob, 2014-05-26
%
% EXAMPLE
% s.a=1;
% s.b.a=2;
% s.b.b=3;
% s.c.a.a=4;
% s.cheese='yummie';
% f=dpxFlattenStru... |
github | duijnhouwer/DPX-master | dpxDispFancy.m | .m | DPX-master/dpxCore/base/dpxDispFancy.m | 29,958 | utf_8 | a066806ced649a8f54f98b856e239989 | function dpxDispFancy(msg,symbol,nh,nv,textStyle,borderStyle)
% dpxDispFancy(msg,symbol,nh,nv,textStyle,borderStyle)
%
% Display a string in a fancy color and with a fancy border.
%
% INPUT:
% msg: String String to disply fancyly
% symbol: String repeated in border (Default:... |
github | duijnhouwer/DPX-master | dpxGetSetables.m | .m | DPX-master/dpxCore/base/dpxGetSetables.m | 1,113 | utf_8 | 34f08a86896f8d3612ccc4d341c05cf2 | function s=dpxGetSetables(obj)
% Like get(obj) but only fields with get AND set access are returned
% Jacob 20140528
fields=dpxWhichSetFields(obj);
for i=1:numel(fields)
s.(fields{i})=obj.(fields{i});
end
end
% --- HELP FUNCTIONS ---------------------------------------------------... |
github | duijnhouwer/DPX-master | dpxMeanUnequalLengthVectors.m | .m | DPX-master/dpxCore/base/dpxMeanUnequalLengthVectors.m | 5,085 | utf_8 | 0a16eb3bb48c74035d3d2b98750f0ffb | function [m,n,s,md]=dpxMeanUnequalLengthVectors(c,varargin)
% function [m,n,s,md]=dpxMeanUnequalLengthVectors(c,weights) get the
% mean 1D vector of a bunch of 1D numerical vectors in cell array c.
% They can be of unequal length (that's the purpose of this function).
% Another useful feature ... |
github | duijnhouwer/DPX-master | dpxSegmentTimeSeries.m | .m | DPX-master/dpxCore/base/analysis/dpxSegmentTimeSeries.m | 2,183 | utf_8 | dc661b32d21a2cd189829831e0856fa7 | function [Ys,Ts]=dpxSegmentTimeSeries(varargin)
% Cut an array into pieces defined by start and stop moments in
% seconds.
% Jacob Duijnhouwer, 2014-08-29
p = inputParser;
p.addParamValue('timeseries',[],@isnumeric);
p.addParamValue('timestamps',[],@isnumeric);
p.addParamV... |
github | duijnhouwer/DPX-master | dpxdIs.m | .m | DPX-master/dpxCore/base/analysis/dpxd/dpxdIs.m | 3,002 | utf_8 | c2ddfdb20f9e38830ec59152cec7457a | function [b,err]=dpxdIs(T,varargin)
% [b,err]=dpxdIs(T,varargin)
%
% Returns boolean B to indicate if T is a DPXD.
%
% Optional output argument err contains a string that explains why T is
% not a DPXD.
%
% A DPXD is a structure whose members have equal numbers of elements ... |
github | duijnhouwer/DPX-master | dpxdLoad.m | .m | DPX-master/dpxCore/base/analysis/dpxd/dpxdLoad.m | 5,487 | utf_8 | bbb677e90dbf0471a1b84edb874118c0 | function [DPXD,auxData]=dpxdLoad(filename,varargin)
% [dpxd,theRest]=dpxdLoad(filename,varargin)
% Load a DPX-data file.
%
% DPXD files are simply MAT files, so they can be loaded with
% load(filename)
% But that would instantiate the DPXD struct with whatever name it was saved
%... |
github | duijnhouwer/DPX-master | dpxdMerge.m | .m | DPX-master/dpxCore/base/analysis/dpxd/dpxdMerge.m | 6,309 | utf_8 | 1d6db9c2d6158f25b9a8292da6e604b9 | function M=dpxdMerge(T,varargin)
% Merge the DPXDs in cell array T into one DPXD M. All DPXDs in T
% must be compatible, i.e., have the same fields.
% 2012-10-12: T can also be a regular array of DPXDs, does not need
% to be a cell (only works for DPXD-structs with identical fields)
% 201... |
github | duijnhouwer/DPX-master | dpxdMergeGUI.m | .m | DPX-master/dpxCore/base/analysis/dpxd/dpxdMergeGUI/dpxdMergeGUI.m | 12,458 | utf_8 | 702ef6e4e622d8885251e15d0645e05f | function varargout = dpxdMergeGUI(varargin)
% Tool to merge datafiles using a GUI
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @dpxdMergeGUI_OpeningFcn, ...
'gui_OutputFcn', @dpxdMergeGUI_OutputFcn, ...... |
github | duijnhouwer/DPX-master | dpxUIgetFiles.m | .m | DPX-master/dpxCore/base/analysis/filestuff/dpxUIgetfiles/dpxUIgetFiles.m | 12,030 | utf_8 | eb46aa99a76322fd0afda7efadd47bbc | function varargout = dpxUIgetFiles(varargin)
% dpxUIgetFiles
%
% GUI to select multiple files from multiple directories. It is possible to select
% files from folder including subfolder, filter on extention, and use
% simple inclusion and exclusion filtering on filenames.
%
% EXAMPLE:
... |
github | duijnhouwer/DPX-master | dpxBayesPhysV1.m | .m | DPX-master/dpxCore/base/analysis/curvefit/dpxBayesPhysV1.m | 4,183 | utf_8 | ea298d96cee6ba52c0a63e9457faf4ee | function bayesphys=dpxBayesPhysV1(varargin)
% First check if bayesphys_V1 is on the path;
if ~exist('tc_sample','file') || ~exist('compute_bf.m','file')
error('errortag:bla',strcat('dpxBayesPhysV1 requires the bayesphys_v1 toolkit\n',...
'You can download it from this page:\n',...
... |
github | duijnhouwer/DPX-master | struct2batch.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/struct2batch.m | 3,297 | utf_8 | 1ff49d1563b868c677f105aafc989aa6 | function string = struct2batch(s)
% STRUCT2BATCH converts from a MATLAB struct to a batch string
%
% B = STRUCT2BATCH(S) converts the 1x1 struct S into the "batch string"
% format required by PSIGNIFIT. Keys (struct field names) are prefixed
% with # on a new line, and values are separated from keys by whites... |
github | duijnhouwer/DPX-master | batch2struct.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/batch2struct.m | 2,398 | utf_8 | b1cb550f693549d142074d10acf98837 | function s = batch2struct(string)
% BATCH2STRUCT converts from a batch string to a MATLAB struct
%
% S = BATCH2STRUCT(B) returns a 1x1 struct.
% The input is in the "batch string" format required by PSIGNIFIT:
% keys (which become struct field names) are prefixed with # (each key
% must also be the first wo... |
github | duijnhouwer/DPX-master | psychostats.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/psychostats.m | 15,101 | utf_8 | 6695376f042a6d8c90dc9a35ae1ac1c7 | function [sOut, figHandle]= psychostats(dat, p, R, stats, statsSim, sfp, optIn)
% PSYCHOSTATS assesses goodness-of-fit for models of psychophysical data
%
% S = PSYCHOSTATS(DAT, P_MODEL [, R]) conducts goodness-of-fit tests on the
% model that predicts probabilities P_MODEL for the experiment that pro... |
github | duijnhouwer/DPX-master | deviance.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/deviance.m | 2,609 | utf_8 | 2a9d474ea88954301d0cd2523d964abe | function [D, residuals, p] = deviance(shape, params, x, y, n)
% [D RESIDUALS p] = DEVIANCE(SHAPE, PARAMS, DAT)
% [D RESIDUALS p] = DEVIANCE(SHAPE, PARAMS, x, y, n)
%
% DAT is a standard 3- or 4- column data matrix.
% Cases are taken row-by-row: each of the arguments
% PARAMS, x, y and n may have a single row, or mu... |
github | duijnhouwer/DPX-master | psychoplot.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/psychoplot.m | 5,512 | utf_8 | 2a74b12ea1c944c1decf7efcb9cbc5fd | function hOut = psychoplot(varargin)
% H = PSYCHOPLOT([DAT, ] [INFO, ] [plotPropName, plotPropValue, ...])
%
% INFO can be a cell vector, containing up to 6 arguments in the following order:
% {SHAPE, PARAMS, TH_EST, TH_LIMS, TH_WORST, LEVELS}
% Arguments may be omitted from the end, or passed as empty: []
%
% Al... |
github | duijnhouwer/DPX-master | psychreport.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/psychreport.m | 7,765 | utf_8 | 3e5116660a6fd0c2bacf6ea401ff8f9f | function [strOut] = psychreport(sIn, varargin)
% PSYCHREPORT text reporting of PFIT results
%
% PSYCHREPORT(S), where S is the STRUCT output from PFIT,
% produces a text report of the results. If an output argument
% is not requested, then the string is displayed on the terminal.
%
% Additional options s... |
github | duijnhouwer/DPX-master | pfit.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/pfit.m | 20,215 | utf_8 | df88e73944eaab706f7a20be40d660a6 | function [s, sFull, str] = pfit(varargin)
% PFIT fitting, bootstrapping, goodness-of-fit and sensitivity analysis
%
% PFIT(DAT [, plot option][, fitting options...])
%
% S = PFIT(DAT) fits a psychometric function to the data DAT and performs
% 1999 bootstrap simulations in order to estimate the variability... |
github | duijnhouwer/DPX-master | key.m | .m | DPX-master/dpxCore/base/analysis/curvefit/@dpxPsignifit/private/key.m | 15,819 | utf_8 | 8885b666dee1cd11544732536d7db26e | function hOut = key(varargin)
% KEY adds a key (otherwise referred to as a legend)
%
% HANDLE = KEY(...) creates a floating key or legend similar to MathWorks'
% LEGEND command. Only LINE objects are listed, and only if they have the
% word 'keyed' (lower case) in their 'Tag' field.
%
% The text labels for... |
github | michaelstchen/modPolyFit-master | ModPolyFit_GUI.m | .m | modPolyFit-master/ModPolyFit_GUI.m | 18,710 | utf_8 | e3a462a325a7879ac649a256cfd6d3ff | function varargout = ModPolyFit_GUI(varargin)
%MODPOLYFIT_GUI M-file for ModPolyFit_GUI.fig
% MODPOLYFIT_GUI, by itself, creates a new MODPOLYFIT_GUI or raises the existing
% singleton*.
%
% H = MODPOLYFIT_GUI returns the handle to a new MODPOLYFIT_GUI or the handle to
% the existing singleton*.
%
%... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp10VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp10VTLogitBoost.m | 1,989 | utf_8 | ed50594303aee23c5ad3c712a7af7ba4 | classdef pVbExtSamp10VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = s... |
github | pengsun/MultiClassLogitBoost-master | pSampVTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pSampVTLogitBoost.m | 1,653 | utf_8 | c7821f8fe2b87452882e68f891ac4eb6 | classdef pSampVTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = size(X,1... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp8VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp8VTLogitBoost.m | 1,730 | utf_8 | e3d26a5874a20142df21d44446b08841 | classdef pVbExtSamp8VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = si... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp9VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp9VTLogitBoost.m | 1,730 | utf_8 | 58f339b7d2fd045a85fc28895008d9b2 | classdef pVbExtSamp9VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = si... |
github | pengsun/MultiClassLogitBoost-master | pAOSOLogitBoostV2.m | .m | MultiClassLogitBoost-master/matlab/pAOSOLogitBoostV2.m | 2,497 | utf_8 | 097ac97e1f6c3122aaf1a5f4ee483cfc | classdef pAOSOLogitBoostV2
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size,...
rs,rf,wrs] = parse_input(varargin{:});
if (isempty(var_cat_mask))
n... |
github | pengsun/MultiClassLogitBoost-master | pAOSOMARTVb.m | .m | MultiClassLogitBoost-master/matlab/pAOSOMARTVb.m | 2,920 | utf_8 | f10e30e10a93fe1e0e015f471f01d26c | classdef pAOSOMARTVb
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size,...
rs,rf,wrs] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = ... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp5VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp5VTLogitBoost.m | 1,730 | utf_8 | 607b753dcc2b133cb17ebe1078844c31 | classdef pVbExtSamp5VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = si... |
github | pengsun/MultiClassLogitBoost-master | pExtSamp2VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pExtSamp2VTLogitBoost.m | 1,677 | utf_8 | a01a5cbe799f4b1d33c7e051ba79c7b6 | classdef pExtSamp2VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = size... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp13VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp13VTLogitBoost.m | 2,693 | utf_8 | 692d7a574b47d4d3dde19673e8fcc603 | classdef pVbExtSamp13VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size,...
rs,rf,rc, wrs,wrc] = parse_input(varargin{:});
if (isempty(var_cat_m... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp11VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp11VTLogitBoost.m | 2,246 | utf_8 | 756d4bfdff4e8ea520e600c71fe53fd2 | classdef pVbExtSamp11VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = s... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp14VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp14VTLogitBoost.m | 3,054 | utf_8 | 56b2561449890098625d8a5a129a49fd | classdef pVbExtSamp14VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size,...
rs,rf,rc, wrs,wrc] = parse_input(varargin{:});
if (isempty(var_cat_m... |
github | pengsun/MultiClassLogitBoost-master | pExtSampVTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pExtSampVTLogitBoost.m | 1,671 | utf_8 | 9918b1f8ba3d28d7f8076f140c40c5c6 | classdef pExtSampVTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = size(... |
github | pengsun/MultiClassLogitBoost-master | VTTCLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/VTTCLogitBoost.m | 1,487 | utf_8 | be4b9bfec757483b2a88691c6fda1f80 | classdef VTTCLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,lambda, node_size] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = size(X,1);
... |
github | pengsun/MultiClassLogitBoost-master | AOSOLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/AOSOLogitBoost.m | 1,853 | utf_8 | 12170f518e1294bfd5bae7392249d67e | classdef AOSOLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = size(X,1);
va... |
github | pengsun/MultiClassLogitBoost-master | pVbExtSamp7VTLogitBoost.m | .m | MultiClassLogitBoost-master/matlab/pVbExtSamp7VTLogitBoost.m | 1,730 | utf_8 | 5d86399efcb18be030a02f659d72da93 | classdef pVbExtSamp7VTLogitBoost
% Summary of this class goes here
% Detailed explanation goes here
properties
ptr;
end
methods
function obj = train(obj,X,Y, varargin)
[var_cat_mask,T,J,v, node_size, rs,rf,rc] = parse_input(varargin{:});
if (isempty(var_cat_mask))
nvar = si... |
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