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values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | sheldona/hessianIK-master | emptySkeleton.m | .m | hessianIK-master/matlab/HDM05-Parser/parser/emptySkeleton.m | 2,792 | utf_8 | 269e811e8abce591c94074b36eeba9aa | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | emptySkeletonNode.m | .m | hessianIK-master/matlab/HDM05-Parser/parser/emptySkeletonNode.m | 2,036 | utf_8 | 5f2126b69ec37eb46b000e2c8f162a24 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | amc_to_matrix.m | .m | hessianIK-master/matlab/HDM05-Parser/parser/ASFAMCparser/amc_to_matrix.m | 2,554 | utf_8 | b1cf288c34613efe546bd9409ebb7ae7 | % Reads data from an AMC motion file into a Matlab matrix variable.
% AMC file has to be in the AMC format used in the online CMU motion capture library.
% number of dimensions = number of columns = 62
% function D = amc_to_matrix(fname)
% fname = name of disk input file, in AMC format
% Example:
% D = amc_to_matrix(f... |
github | sheldona/hessianIK-master | matrix_to_amc.m | .m | hessianIK-master/matlab/HDM05-Parser/parser/ASFAMCparser/matrix_to_amc.m | 2,157 | utf_8 | 54cc2acc388d5a139ee98e11ff0745c4 | % Writes motion data from matrix D to an AMC file on disk.
% The ACM format is the format used in the CMU online motion capture database
% function [] = matrix_to_amc(fname, D)
% fname = output disk file name for AMC file
% D = input Matlab data matrix
% Example:
% matrix_to_amc('running1.amc', D)
%
%
% Jernej Barbic
... |
github | sheldona/hessianIK-master | filterR4.m | .m | hessianIK-master/matlab/HDM05-Parser/quaternions/filterR4.m | 2,139 | utf_8 | 9c7df4fc6f448e66036bb7397f11e78e | function [Y,t] = filterR4(varargin)
% Y = filterR4(w,X,step,padding_method)
% Filters curves embedded in the unit quaternion sphere with a sliding window.
% Simply views quats as 4D data without additional structure and renormalizes
% to S^3 after filtering
%
% Input: w, weight vector
% X, 4xN matrix of in... |
github | sheldona/hessianIK-master | new_animate.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/new_animate.m | 4,443 | utf_8 | 7c2a0775e942d33be94bf604b50913e4 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | coordsDiscNormal.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/coordsDiscNormal.m | 2,544 | utf_8 | ef826401167a9e0fcb50a9677d3e8573 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | coordsCappedCylinder.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/coordsCappedCylinder.m | 4,089 | utf_8 | 90bc8049364cd8f5a2b1163f35b9475f | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | old_createPlaneNormal.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/old_createPlaneNormal.m | 1,183 | utf_8 | b97f43b934cb7043af84fe9ae222d544 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animateGUI.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animateGUI.m | 13,691 | utf_8 | 5739395d8d277eb8131b34cd31154869 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | saveCamera.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/saveCamera.m | 1,684 | utf_8 | 7749a04b6cedd203283a11fafe2214e5 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | gramschmidt.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/gramschmidt.m | 1,318 | utf_8 | 3407cb5995f0348fefd4819b84082843 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | coordsGridDiscNormal.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/coordsGridDiscNormal.m | 2,922 | utf_8 | d2f60be72f8b308194ab808ee1b48fbb | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | resumeAnimation.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/resumeAnimation.m | 2,150 | utf_8 | 42f8280c765992e5a383c09d67f18409 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animate_sound.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animate_sound.m | 4,499 | utf_8 | 01e75d42c480e6a8ca1ba1846c3f6e77 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | emptyVarsGlobalAnimStruct.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/emptyVarsGlobalAnimStruct.m | 3,735 | utf_8 | 4f769d2096aef0f6b1b3368c3a991162 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animate_showFrame.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animate_showFrame.m | 6,254 | utf_8 | 559c1de0a69ae55a7b39a19bbdbea997 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | showTracePoses.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/showTracePoses.m | 2,166 | utf_8 | 22106722235c86ca330051e8c0791b28 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | params_planePointNormal.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/params_planePointNormal.m | 2,782 | utf_8 | ea22c0084f199090b885985a7baf6db8 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | new_animate_showFrame.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/new_animate_showFrame.m | 7,936 | utf_8 | 54cf87ae23a8624ff5da8c91f5b5f896 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | new_animate_initGraphics.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/new_animate_initGraphics.m | 8,957 | utf_8 | 98c0162f25275bc385e84a3284063b25 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | createSkeletonLines.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/createSkeletonLines.m | 3,310 | utf_8 | 81475446626b2907be67cac6c5a709b9 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | addAnimatedPatches.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/addAnimatedPatches.m | 1,890 | utf_8 | 18c8bb64181343ef5a4cab9f8ca774a8 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animatedPatchStruct.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animatedPatchStruct.m | 1,159 | utf_8 | c015eeaf7e0b0c68bfc3831e5392eb8c | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | updateAnimationSlider.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/updateAnimationSlider.m | 1,053 | utf_8 | a26b08cbee39ea5f869d6928c9c46ba4 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | createAnimatedPatches.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/createAnimatedPatches.m | 15,395 | utf_8 | 7eeb9dd84191ba1db207f0a95d3b56cf | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | showTrajectory.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/showTrajectory.m | 1,785 | utf_8 | eb709c8dee65d22c7c903f044f51bb29 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animate_initGraphics.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animate_initGraphics.m | 9,209 | utf_8 | cd70562b00aa2a26dee089385ac74678 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | params_planePointNormal_hipMiddle.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/params_planePointNormal_hipMiddle.m | 1,872 | utf_8 | 3f364fb83a64507cc42a47f8213efe4e | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animateD.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animateD.m | 1,263 | utf_8 | 3f8a0b3675cad9797f6e4718f617edeb | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | params_planePointNormal_yAxis.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/params_planePointNormal_yAxis.m | 1,638 | utf_8 | 0fc5e348ac7026a527e959b2667201e8 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | createGroundPlane.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/createGroundPlane.m | 2,338 | utf_8 | 91b0ef6feeb2d3bc384ee3701473cc4f | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | clearTracePoses.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/clearTracePoses.m | 1,489 | utf_8 | 6c8fe077512099e2b252b07c469a1c78 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | pauseAnimation.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/pauseAnimation.m | 1,015 | utf_8 | 6561afbd29136530c0772b4648470d34 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | params_planePointPoint.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/params_planePointPoint.m | 2,899 | utf_8 | 9d0bac1f2b300efaa7b0c654811de25f | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animate.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animate.m | 4,493 | utf_8 | 482def7e4bca1a7f821115e5c91c42a3 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | params_cappedCylinder.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/params_cappedCylinder.m | 1,264 | utf_8 | 102ad0b5fdbea7ea428a807018e318f8 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | animateVideo.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/animateVideo.m | 6,406 | utf_8 | f882dde25749bf606e027581e06f1121 | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | sheldona/hessianIK-master | params_point.m | .m | hessianIK-master/matlab/HDM05-Parser/animate/params_point.m | 991 | utf_8 | 7c22edf392e740c65f2843d490b0affa | % This code belongs to the HDM05 mocap database which can be obtained
% from the website http://www.mpi-inf.mpg.de/resources/HDM05 .
%
% If you use and publish results based on this code and data, please
% cite the following technical report:
%
% @techreport{MuellerRCEKW07_HDM05-Docu,
% author = {Meinard M{\"u}ll... |
github | aman432/Spam-Classifier-master | submit.m | .m | Spam-Classifier-master/Spam/submit.m | 1,318 | utf_8 | bfa0b4ffb8a7854d8e84276e91818107 | function submit()
addpath('./lib');
conf.assignmentSlug = 'support-vector-machines';
conf.itemName = 'Support Vector Machines';
conf.partArrays = { ...
{ ...
'1', ...
{ 'gaussianKernel.m' }, ...
'Gaussian Kernel', ...
}, ...
{ ...
'2', ...
{ 'dataset3Params.m' }, ...
... |
github | aman432/Spam-Classifier-master | porterStemmer.m | .m | Spam-Classifier-master/Spam/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 | aman432/Spam-Classifier-master | submitWithConfiguration.m | .m | Spam-Classifier-master/Spam/lib/submitWithConfiguration.m | 5,562 | utf_8 | 4ac719ea6570ac228ea6c7a9c919e3f5 | function submitWithConfiguration(conf)
addpath('./lib/jsonlab');
parts = parts(conf);
fprintf('== Submitting solutions | %s...\n', conf.itemName);
tokenFile = 'token.mat';
if exist(tokenFile, 'file')
load(tokenFile);
[email token] = promptToken(email, token, tokenFile);
else
[email token] = p... |
github | aman432/Spam-Classifier-master | savejson.m | .m | Spam-Classifier-master/Spam/lib/jsonlab/savejson.m | 17,462 | utf_8 | 861b534fc35ffe982b53ca3ca83143bf | function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fa... |
github | aman432/Spam-Classifier-master | loadjson.m | .m | Spam-Classifier-master/Spam/lib/jsonlab/loadjson.m | 18,732 | ibm852 | ab98cf173af2d50bbe8da4d6db252a20 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% ... |
github | aman432/Spam-Classifier-master | loadubjson.m | .m | Spam-Classifier-master/Spam/lib/jsonlab/loadubjson.m | 15,574 | utf_8 | 5974e78e71b81b1e0f76123784b951a4 | function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id: loadubjson.m 460 2015-01-... |
github | aman432/Spam-Classifier-master | saveubjson.m | .m | Spam-Classifier-master/Spam/lib/jsonlab/saveubjson.m | 16,123 | utf_8 | 61d4f51010aedbf97753396f5d2d9ec0 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
github | sovandas/Modulation-Testing-Tool-master | parameterEdit.m | .m | Modulation-Testing-Tool-master/SISO OFDM/parameterEdit.m | 4,564 | utf_8 | 74f2193b03e8af2a1f406a0056e10c89 | function varargout = parameterEdit(varargin)
% PARAMETEREDIT MATLAB code for parameterEdit.fig
% PARAMETEREDIT, by itself, creates a new PARAMETEREDIT or raises the existing
% singleton*.
%
% H = PARAMETEREDIT returns the handle to a new PARAMETEREDIT or the handle to
% the existing singleton*.
%
% ... |
github | sovandas/Modulation-Testing-Tool-master | parameterEdit.m | .m | Modulation-Testing-Tool-master/SM OFDM/parameterEdit.m | 4,564 | utf_8 | 74f2193b03e8af2a1f406a0056e10c89 | function varargout = parameterEdit(varargin)
% PARAMETEREDIT MATLAB code for parameterEdit.fig
% PARAMETEREDIT, by itself, creates a new PARAMETEREDIT or raises the existing
% singleton*.
%
% H = PARAMETEREDIT returns the handle to a new PARAMETEREDIT or the handle to
% the existing singleton*.
%
% ... |
github | sovandas/Modulation-Testing-Tool-master | SM_test_est_with_ch_est_adaptive_modulation.m | .m | Modulation-Testing-Tool-master/SM OFDM/SM_test_est_with_ch_est_adaptive_modulation.m | 12,232 | utf_8 | c59725a94507e3d8a4fac3a01f0ebde3 |
function [BER, BER_SM, BER_QAM, channel, estimated_channel, estimated_SNR, fitted_SNR] = SM_test_est_with_ch_est_adaptive_modulation(input_from_diode_ch1, input_from_diode_ch2, qam_dco_ch1, qam_dco_ch2, SM_bits, M, P, Frames, Nfft, cp_length, omitted_carriers, preamble_length, offset, frame_eq_mult, samples_per_symbol... |
github | sovandas/Modulation-Testing-Tool-master | parameterEdit.m | .m | Modulation-Testing-Tool-master/MIMO OFDM/parameterEdit.m | 4,564 | utf_8 | 74f2193b03e8af2a1f406a0056e10c89 | function varargout = parameterEdit(varargin)
% PARAMETEREDIT MATLAB code for parameterEdit.fig
% PARAMETEREDIT, by itself, creates a new PARAMETEREDIT or raises the existing
% singleton*.
%
% H = PARAMETEREDIT returns the handle to a new PARAMETEREDIT or the handle to
% the existing singleton*.
%
% ... |
github | sovandas/Modulation-Testing-Tool-master | MIMO_test_est_with_ch_est_adaptive_modulation.m | .m | Modulation-Testing-Tool-master/MIMO OFDM/MIMO_test_est_with_ch_est_adaptive_modulation.m | 14,887 | utf_8 | dc04eabf4637c5a652f42d0a115cb9f9 |
function [BER, BER_QAM1, BER_QAM2, channel, estimated_channel, SNR1, SNR2] = MIMO_test_est_with_ch_est_adaptive_modulation(input_from_diode_ch1, input_from_diode_ch2, qam_dco_ch1, qam_dco_ch2, M, P, Frames, Nfft, cp_length, omitted_carriers, preamble_length, offset, frame_eq_mult, samples_per_symbol, filter_type, roll... |
github | sqjin/scEpath-master | clusteringCells.m | .m | scEpath-master/clusteringCells.m | 4,523 | utf_8 | 855d58cac5df9078e81f48eb4516b78c | function [y, S] = clusteringCells(data,networkIfo,C,clusterRange,showFigure)
% perform unsupervised clustering of single cell data
% Inputs:
% data: single cell data (rows are genes and columns are cells)
% networkIfo: network information for the constructed gene-gene network
% C: number of clusters, by d... |
github | sqjin/scEpath-master | constructingNetwork.m | .m | scEpath-master/constructingNetwork.m | 4,418 | utf_8 | 07b464ae3eba9965f313e9cab6e15ed9 | function networkIfo = constructingNetwork(data,quick_construct,thresh,thresh_percent,showFigure,fig_width,fig_height)
% construct a gene-gene co-expression network
% Inputs:
% data: single cell data (rows are cells and columns are genes)
% quick_construct: default=0,the network will be constructed by choosing... |
github | sqjin/scEpath-master | optimal_SVHT_coef.m | .m | scEpath-master/optimal_SVHT_coef.m | 4,578 | utf_8 | 601f5430e4282be5998f855bc038b18f | function coef = optimal_SVHT_coef(beta, sigma_known)
% function omega = optimal_SVHT_coef(beta, sigma_known)
%
% Coefficient determining optimal location of Hard Threshold for Matrix
% Denoising by Singular Values Hard Thresholding when noise level is known or
% unknown.
%
% See D. L. Donoho and M. Gavish, "The Opti... |
github | sqjin/scEpath-master | distinguishable_colors.m | .m | scEpath-master/enternal/distinguishable_colors.m | 5,753 | utf_8 | 57960cf5d13cead2f1e291d1288bccb2 | function colors = distinguishable_colors(n_colors,bg,func)
% DISTINGUISHABLE_COLORS: pick colors that are maximally perceptually distinct
%
% When plotting a set of lines, you may want to distinguish them by color.
% By default, Matlab chooses a small set of colors and cycles among them,
% and so if you have more than ... |
github | sqjin/scEpath-master | SIMLR_LARGE.m | .m | scEpath-master/enternal/SIMLR/src/SIMLR_LARGE.m | 3,824 | utf_8 | d93d9e5fe003f6e721edf44251075283 | function [S0, F] = SIMLR_LARGE(X, c, k, ifimpute,normalize)
%%%
if nargin==2
k=10;
ifimpute = 0;
normalize = 0;
end
if nargin==3
ifimpute = 0;
normalize = 0;
end
if nargin==4
normalize = 0;
end
if ifimpute
X = X';
[I,J] = find(X==0);
Xmean = mean(X);
X(sub2ind(size(X),I,J)) ... |
github | sqjin/scEpath-master | fast_pca.m | .m | scEpath-master/enternal/SIMLR/src/fast_pca.m | 997 | utf_8 | faf27f941117e07978072249dcc5a39d | function X = fast_pca(in_X, K)
in_X = in_X - repmat(mean(in_X),size(in_X,1),1);
[U, S, ~] = rsvd(in_X, K);
K = min(size(S,2),K);
X = U(:,1:K)*diag(sqrt(diag(S(1:K,1:K))));
X = X./repmat(sqrt(sum(X.*X,2)),1,K);
end
function [U,S,V] = rsvd(A,K)
%--------------------------------------------------------------------------... |
github | sqjin/scEpath-master | L2_distance_1.m | .m | scEpath-master/enternal/SIMLR/src/L2_distance_1.m | 508 | utf_8 | 163a4a02852578aabe7c4660b447694b | % compute squared Euclidean distance
% ||A-B||^2 = ||A||^2 + ||B||^2 - 2*A'*B
function d = L2_distance_1(a,b)
% a,b: two matrices. each column is a data
% d: distance matrix of a and b
if (size(a,1) == 1)
a = [a; zeros(1,size(a,2))];
b = [b; zeros(1,size(b,2))];
end
aa=sum(a.*a); bb=sum(b.*b); ... |
github | sqjin/scEpath-master | colorspace.m | .m | scEpath-master/enternal/SIMLR/src/colorspace.m | 16,178 | utf_8 | 2ca0aee9ae4d0f5c12a7028c45ef2b8d | function varargout = colorspace(Conversion,varargin)
%COLORSPACE Transform a color image between color representations.
% B = COLORSPACE(S,A) transforms the color representation of image A
% where S is a string specifying the conversion. The input array A
% should be a real full double array of size Mx3 or MxN... |
github | sqjin/scEpath-master | litekmeans.m | .m | scEpath-master/enternal/SIMLR/src/litekmeans.m | 16,583 | utf_8 | b74ab36bf2876c2205b06e5bb554d8d8 | function [label, center, bCon, sumD, D] = litekmeans(X, k, varargin)
%LITEKMEANS K-means clustering, accelerated by matlab matrix operations.
%
% label = LITEKMEANS(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... |
github | sqjin/scEpath-master | SIMLR.m | .m | scEpath-master/enternal/SIMLR/src/SIMLR.m | 9,303 | utf_8 | 7913f20bdbdf908c5366ae37d193da4d | function [y, S, F, ydata,alphaK,timeOurs,converge,LF] = SIMLR(X, c, k, ifimpute,normalize)
%%%
if nargin==2
k=10;
ifimpute = 0;
normalize = 0;
end
if nargin==3
ifimpute = 0;
normalize = 0;
end
if nargin==4
normalize = 0;
end
if ifimpute
X = X';
[I,J] = find(X==0);
Xmean = mean(X... |
github | sqjin/scEpath-master | SIMLR_embedding_tsne.m | .m | scEpath-master/enternal/SIMLR/src/SIMLR_embedding_tsne.m | 2,427 | utf_8 | 3e805cd1014ff2298086d18d9910a372 | function Y = SIMLR_embedding_tsne(P, do_init,DD, Y0)
%%%compute 2-D coordinates by approximae t-SNE
%
% Y = SIMLR_embedding_tsne(P, do_init)
%
% Input:
% P: N x N, pairwise (sparse) similarities or network (weighted) adjacency matrix
% do_init: boolean, do over-attraction initialization or not, default=false
... |
github | Shenc0411/CS445-master | mask2chain.m | .m | CS445-master/mp3/mask2chain.m | 15,323 | utf_8 | 816e13d1228586bd4c7115c9c3075203 | function [x, y] = mask2chain_tmp(mask)
crack_img = seg2cracks(double(mask));
fragments = cracks2fragments(crack_img, mask, 1);
x = round(fragments{1}(:, 1));
y = round(fragments{1}(:, 2));
% x = fragments{1}(:, 1);
% y = fragments{1}(:, 2);
[gy, gx] = gradient(double(mask));
epix = (gy.^2+gx.^2>0) & mask;
e = y + (x-... |
github | Shenc0411/CS445-master | auto_homography.m | .m | CS445-master/mp5/auto_homography.m | 1,604 | utf_8 | 43e69b60910b0e8336b4ed782d13dcaa | function H=auto_homography(Ia,Ib)
% Computes a homography that maps points from Ia to Ib
%
% Input: Ia and Ib are images
% Output: H is the homography
%
% Note: to use H in maketform, use maketform('projective', H')
% Computes correspondences and matches
[fa,da] = vl_sift(im2single(rgb2gray(Ia))) ;
[fb,db] = vl_sift(i... |
github | Shenc0411/CS445-master | vl_compile.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/vl_compile.m | 5,060 | utf_8 | 978f5189bb9b2a16db3368891f79aaa6 | function vl_compile(compiler)
% VL_COMPILE Compile VLFeat MEX files
% VL_COMPILE() uses MEX() to compile VLFeat MEX files. This command
% works only under Windows and is used to re-build problematic
% binaries. The preferred method of compiling VLFeat on both UNIX
% and Windows is through the provided Makefile... |
github | Shenc0411/CS445-master | vl_noprefix.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/vl_noprefix.m | 1,875 | utf_8 | 97d8755f0ba139ac1304bc423d3d86d3 | function vl_noprefix
% VL_NOPREFIX Create a prefix-less version of VLFeat commands
% VL_NOPREFIX() creats prefix-less stubs for VLFeat functions
% (e.g. SIFT for VL_SIFT). This function is seldom used as the stubs
% are included in the VLFeat binary distribution anyways. Moreover,
% on UNIX platforms, the stub... |
github | Shenc0411/CS445-master | vl_pegasos.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/misc/vl_pegasos.m | 2,837 | utf_8 | d5e0915c439ece94eb5597a07090b67d | % VL_PEGASOS [deprecated]
% VL_PEGASOS is deprecated. Please use VL_SVMTRAIN() instead.
function [w b info] = vl_pegasos(X,Y,LAMBDA, varargin)
% Verbose not supported
if (sum(strcmpi('Verbose',varargin)))
varargin(find(strcmpi('Verbose',varargin),1))=[];
fprintf('Option VERBOSE is no longer supported.\n');
en... |
github | Shenc0411/CS445-master | vl_svmpegasos.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/misc/vl_svmpegasos.m | 1,178 | utf_8 | 009c2a2b87a375d529ed1a4dbe3af59f | % VL_SVMPEGASOS [deprecated]
% VL_SVMPEGASOS is deprecated. Please use VL_SVMTRAIN() instead.
function [w b info] = vl_svmpegasos(DATA,LAMBDA, varargin)
% Verbose not supported
if (sum(strcmpi('Verbose',varargin)))
varargin(find(strcmpi('Verbose',varargin),1))=[];
fprintf('Option VERBOSE is no longer suppor... |
github | Shenc0411/CS445-master | vl_override.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/misc/vl_override.m | 4,654 | utf_8 | e233d2ecaeb68f56034a976060c594c5 | function config = vl_override(config,update,varargin)
% VL_OVERRIDE Override structure subset
% CONFIG = VL_OVERRIDE(CONFIG, UPDATE) copies recursively the fileds
% of the structure UPDATE to the corresponding fields of the
% struture CONFIG.
%
% Usually CONFIG is interpreted as a list of paramters with their
... |
github | Shenc0411/CS445-master | vl_quickvis.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/quickshift/vl_quickvis.m | 3,696 | utf_8 | 27f199dad4c5b9c192a5dd3abc59f9da | function [Iedge dists map gaps] = vl_quickvis(I, ratio, kernelsize, maxdist, maxcuts)
% VL_QUICKVIS Create an edge image from a Quickshift segmentation.
% IEDGE = VL_QUICKVIS(I, RATIO, KERNELSIZE, MAXDIST, MAXCUTS) creates an edge
% stability image from a Quickshift segmentation. RATIO controls the tradeoff
% bet... |
github | Shenc0411/CS445-master | vl_demo_aib.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/demo/vl_demo_aib.m | 2,928 | utf_8 | 590c6db09451ea608d87bfd094662cac | function vl_demo_aib
% VL_DEMO_AIB Test Agglomerative Information Bottleneck (AIB)
D = 4 ;
K = 20 ;
randn('state',0) ;
rand('state',0) ;
X1 = randn(2,300) ; X1(1,:) = X1(1,:) + 2 ;
X2 = randn(2,300) ; X2(1,:) = X2(1,:) - 2 ;
X3 = randn(2,300) ; X3(2,:) = X3(2,:) + 2 ;
figure(1) ; clf ; hold on ;
vl_plotframe(X... |
github | Shenc0411/CS445-master | vl_demo_alldist.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/demo/vl_demo_alldist.m | 5,460 | utf_8 | 6d008a64d93445b9d7199b55d58db7eb | function vl_demo_alldist
%
numRepetitions = 3 ;
numDimensions = 1000 ;
numSamplesRange = [300] ;
settingsRange = {{'alldist2', 'double', 'l2', }, ...
{'alldist', 'double', 'l2', 'nosimd'}, ...
{'alldist', 'double', 'l2' }, ...
{'alldist2', 's... |
github | Shenc0411/CS445-master | vl_demo_ikmeans.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/demo/vl_demo_ikmeans.m | 774 | utf_8 | 17ff0bb7259d390fb4f91ea937ba7de0 | function vl_demo_ikmeans()
% VL_DEMO_IKMEANS
numData = 10000 ;
dimension = 2 ;
data = uint8(255*rand(dimension,numData)) ;
numClusters = 3^3 ;
[centers, assignments] = vl_ikmeans(data, numClusters);
figure(1) ; clf ; axis off ;
plotClusters(data, centers, assignments) ;
vl_demo_print('ikmeans_2d',0.6);
[tree, assig... |
github | Shenc0411/CS445-master | vl_demo_svm.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/demo/vl_demo_svm.m | 1,235 | utf_8 | 7cf6b3504e4fc2cbd10ff3fec6e331a7 | % VL_DEMO_SVM Demo: SVM: 2D linear learning
function vl_demo_svm
y=[];X=[];
% Load training data X and their labels y
load('vl_demo_svm_data.mat')
Xp = X(:,y==1);
Xn = X(:,y==-1);
figure
plot(Xn(1,:),Xn(2,:),'*r')
hold on
plot(Xp(1,:),Xp(2,:),'*b')
axis equal ;
vl_demo_print('svm_training') ;
% Parameters
lambda =... |
github | Shenc0411/CS445-master | vl_demo_kdtree_sift.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/demo/vl_demo_kdtree_sift.m | 6,832 | utf_8 | e676f80ac330a351f0110533c6ebba89 | function vl_demo_kdtree_sift
% VL_DEMO_KDTREE_SIFT
% Demonstrates the use of a kd-tree forest to match SIFT
% features. If FLANN is present, this function runs a comparison
% against it.
% AUTORIGHS
rand('state',0) ;
randn('state',0);
do_median = 0 ;
do_mean = 1 ;
% try to setup flann
if ~exist('flann_search'... |
github | Shenc0411/CS445-master | vl_impattern.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/imop/vl_impattern.m | 6,876 | utf_8 | 1716a4d107f0186be3d11c647bc628ce | function im = vl_impattern(varargin)
% VL_IMPATTERN Generate an image from a stock pattern
% IM=VLPATTERN(NAME) returns an instance of the specified
% pattern. These stock patterns are useful for testing algoirthms.
%
% All generated patterns are returned as an image of class
% DOUBLE. Both gray-scale and colou... |
github | Shenc0411/CS445-master | vl_tpsu.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/imop/vl_tpsu.m | 1,755 | utf_8 | 09f36e1a707c069b375eb2817d0e5f13 | function [U,dU,delta]=vl_tpsu(X,Y)
% VL_TPSU Compute the U matrix of a thin-plate spline transformation
% U=VL_TPSU(X,Y) returns the matrix
%
% [ U(|X(:,1) - Y(:,1)|) ... U(|X(:,1) - Y(:,N)|) ]
% [ ]
% [ U(|X(:,M) - Y(:,1)|) ... U(|X(:,M) - Y(:,N)|) ]
%
% where X... |
github | Shenc0411/CS445-master | vl_xyz2lab.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/imop/vl_xyz2lab.m | 1,570 | utf_8 | 09f95a6f9ae19c22486ec1157357f0e3 | function J=vl_xyz2lab(I,il)
% VL_XYZ2LAB Convert XYZ color space to LAB
% J = VL_XYZ2LAB(I) converts the image from XYZ format to LAB format.
%
% VL_XYZ2LAB(I,IL) uses one of the illuminants A, B, C, E, D50, D55,
% D65, D75, D93. The default illuminatn is E.
%
% See also: VL_XYZ2LUV(), VL_HELP().
% Copyright ... |
github | Shenc0411/CS445-master | vl_test_gmm.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_gmm.m | 1,332 | utf_8 | 76782cae6c98781c6c38d4cbf5549d94 | function results = vl_test_gmm(varargin)
% VL_TEST_GMM
% Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
vl_test_init ;
end
function s = setup()
randn('st... |
github | Shenc0411/CS445-master | vl_test_twister.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_twister.m | 1,251 | utf_8 | 2bfb5a30cbd6df6ac80c66b73f8646da | function results = vl_test_twister(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_illegal_args()
vl_assert_exception(@() vl_twister(-1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister(1, -1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister([1, -1]), 'vl:invalidArgument') ;
function te... |
github | Shenc0411/CS445-master | vl_test_kdtree.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_kdtree.m | 2,449 | utf_8 | 9d7ad2b435a88c22084b38e5eb5f9eb9 | function results = vl_test_kdtree(varargin)
% VL_TEST_KDTREE
vl_test_init ;
function s = setup()
randn('state',0) ;
s.X = single(randn(10, 1000)) ;
s.Q = single(randn(10, 10)) ;
function test_nearest(s)
for tmethod = {'median', 'mean'}
for type = {@single, @double}
conv = type{1} ;
tmethod = char(tmethod) ;... |
github | Shenc0411/CS445-master | vl_test_imwbackward.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_imwbackward.m | 514 | utf_8 | 33baa0784c8f6f785a2951d7f1b49199 | function results = vl_test_imwbackward(varargin)
% VL_TEST_IMWBACKWARD
vl_test_init ;
function s = setup()
s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
function test_identity(s)
xr = 1:size(s.I,2) ;
yr = 1:size(s.I,1) ;
[x,y] = meshgrid(xr,yr) ;
vl_assert_almost_equal(s.I, vl_imwbackward(xr,yr,s.I,... |
github | Shenc0411/CS445-master | vl_test_alphanum.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_alphanum.m | 1,624 | utf_8 | 2da2b768c2d0f86d699b8f31614aa424 | function results = vl_test_alphanum(varargin)
% VL_TEST_ALPHANUM
vl_test_init ;
function s = setup()
s.strings = ...
{'1000X Radonius Maximus','10X Radonius','200X Radonius','20X Radonius','20X Radonius Prime','30X Radonius','40X Radonius','Allegia 50 Clasteron','Allegia 500 Clasteron','Allegia 50B Clasteron','Al... |
github | Shenc0411/CS445-master | vl_test_printsize.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_printsize.m | 1,447 | utf_8 | 0f0b6437c648b7a2e1310900262bd765 | function results = vl_test_printsize(varargin)
% VL_TEST_PRINTSIZE
vl_test_init ;
function s = setup()
s.fig = figure(1) ;
s.usletter = [8.5, 11] ; % inches
s.a4 = [8.26772, 11.6929] ;
clf(s.fig) ; plot(1:10) ;
function teardown(s)
close(s.fig) ;
function test_basic(s)
for sigma = [1 0.5 0.2]
vl_printsize(s.fig, s... |
github | Shenc0411/CS445-master | vl_test_cummax.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_cummax.m | 838 | utf_8 | 5e98ee1681d4823f32ecc4feaa218611 | function results = vl_test_cummax(varargin)
% VL_TEST_CUMMAX
vl_test_init ;
function test_basic()
vl_assert_almost_equal(...
vl_cummax(1), 1) ;
vl_assert_almost_equal(...
vl_cummax([1 2 3 4], 2), [1 2 3 4]) ;
function test_multidim()
a = [1 2 3 4 3 2 1] ;
b = [1 2 3 4 4 4 4] ;
for k=1:6
dims = ones(1,6) ;
dim... |
github | Shenc0411/CS445-master | vl_test_imintegral.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_imintegral.m | 1,429 | utf_8 | 4750f04ab0ac9fc4f55df2c8583e5498 | function results = vl_test_imintegral(varargin)
% VL_TEST_IMINTEGRAL
vl_test_init ;
function state = setup()
state.I = ones(5,6) ;
state.correct = [ 1 2 3 4 5 6 ;
2 4 6 8 10 12 ;
3 6 9 12 15 18 ;
4 8 12 ... |
github | Shenc0411/CS445-master | vl_test_sift.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_sift.m | 1,318 | utf_8 | 806c61f9db9f2ebb1d649c9bfcf3dc0a | function results = vl_test_sift(varargin)
% VL_TEST_SIFT
vl_test_init ;
function s = setup()
s.I = im2single(imread(fullfile(vl_root,'data','box.pgm'))) ;
[s.ubc.f, s.ubc.d] = ...
vl_ubcread(fullfile(vl_root,'data','box.sift')) ;
function test_ubc_descriptor(s)
err = [] ;
[f, d] = vl_sift(s.I,...
... |
github | Shenc0411/CS445-master | vl_test_binsum.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_binsum.m | 1,377 | utf_8 | f07f0f29ba6afe0111c967ab0b353a9d | function results = vl_test_binsum(varargin)
% VL_TEST_BINSUM
vl_test_init ;
function test_three_args()
vl_assert_almost_equal(...
vl_binsum([0 0], 1, 2), [0 1]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, 1), [0 7]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, [1 2 2 2 2 2 2 2]), [0 0]) ;
function te... |
github | Shenc0411/CS445-master | vl_test_lbp.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_lbp.m | 892 | utf_8 | a79c0ce0c85e25c0b1657f3a0b499538 | function results = vl_test_lbp(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_unfiorm_lbps(s)
% enumerate the 56 uniform lbps
q = 0 ;
for i=0:7
for j=1:7
I = zeros(3) ;
p = mod(s.pixels - i + 8, 8) + 1 ;
I(p <= j) = 1 ;
f = vl_lbp(single(I), 3) ;
q = q + 1 ;
vl_assert_equal(find(f... |
github | Shenc0411/CS445-master | vl_test_colsubset.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_colsubset.m | 828 | utf_8 | be0c080007445b36333b863326fb0f15 | function results = vl_test_colsubset(varargin)
% VL_TEST_COLSUBSET
vl_test_init ;
function s = setup()
s.x = [5 2 3 6 4 7 1 9 8 0] ;
function test_beginning(s)
vl_assert_equal(1:5, vl_colsubset(1:10, 5, 'beginning')) ;
vl_assert_equal(1:5, vl_colsubset(1:10, .5, 'beginning')) ;
function test_ending(s)
vl_assert_equa... |
github | Shenc0411/CS445-master | vl_test_alldist.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_alldist.m | 2,373 | utf_8 | 9ea1a36c97fe715dfa2b8693876808ff | function results = vl_test_alldist(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist(zeros(15,12), zeros(15,0), 'kl2'), ...
zeros(12,0)) ;
vl_assert_equa... |
github | Shenc0411/CS445-master | vl_test_ihashsum.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_ihashsum.m | 581 | utf_8 | edc283062469af62056b0782b171f5fc | function results = vl_test_ihashsum(varargin)
% VL_TEST_IHASHSUM
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(round(16*rand(2,100))) ;
sel = find(all(s.data==0)) ;
s.data(1,sel)=1 ;
function test_hash(s)
D = size(s.data,1) ;
K = 5 ;
h = zeros(1,K,'uint32') ;
id = zeros(D,K,'uint8');
next = zer... |
github | Shenc0411/CS445-master | vl_test_grad.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_grad.m | 434 | utf_8 | 4d03eb33a6a4f68659f868da95930ffb | function results = vl_test_grad(varargin)
% VL_TEST_GRAD
vl_test_init ;
function s = setup()
s.I = rand(150,253) ;
s.I_small = rand(2,2) ;
function test_equiv(s)
vl_assert_equal(gradient(s.I), vl_grad(s.I)) ;
function test_equiv_small(s)
vl_assert_equal(gradient(s.I_small), vl_grad(s.I_small)) ;
function test_equiv... |
github | Shenc0411/CS445-master | vl_test_whistc.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_whistc.m | 1,384 | utf_8 | 81c446d35c82957659840ab2a579ec2c | function results = vl_test_whistc(varargin)
% VL_TEST_WHISTC
vl_test_init ;
function test_acc()
x = ones(1, 10) ;
e = 1 ;
o = 1:10 ;
vl_assert_equal(vl_whistc(x, o, e), 55) ;
function test_basic()
x = 1:10 ;
e = 1:10 ;
o = ones(1, 10) ;
vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ;
x = linspace(-1,11,100) ;
o =... |
github | Shenc0411/CS445-master | vl_test_roc.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_roc.m | 1,019 | utf_8 | 9b2ae71c9dc3eda0fc54c65d55054d0c | function results = vl_test_roc(varargin)
% VL_TEST_ROC
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[tpr,tnr] = vl_roc(s.labels,s.scores0) ;
vl_assert_almost_equal(tpr, [0 1 2 2 2 2] / 2) ;
vl_assert_almost_equal(tnr,... |
github | Shenc0411/CS445-master | vl_test_dsift.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_dsift.m | 2,048 | utf_8 | fbbfb16d5a21936c1862d9551f657ccc | function results = vl_test_dsift(varargin)
% VL_TEST_DSIFT
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
s.I = rgb2gray(single(I)) ;
function test_fast_slow(s)
binSize = 4 ; % bin size in pixels
magnif = 3 ; % bin size / keypoint scale
scale = binSize... |
github | Shenc0411/CS445-master | vl_test_alldist2.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_alldist2.m | 2,284 | utf_8 | 89a787e3d83516653ae8d99c808b9d67 | function results = vl_test_alldist2(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
% TODO: test integer classes
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist2(zeros(15,12), zeros(15,0), 'kl2'), ...
... |
github | Shenc0411/CS445-master | vl_test_fisher.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_fisher.m | 2,097 | utf_8 | c9afd9ab635bd412cbf8be3c2d235f6b | function results = vl_test_fisher(varargin)
% VL_TEST_FISHER
vl_test_init ;
function s = setup()
randn('state',0) ;
dimension = 5 ;
numData = 21 ;
numComponents = 3 ;
s.x = randn(dimension,numData) ;
s.mu = randn(dimension,numComponents) ;
s.sigma2 = ones(dimension,numComponents) ;
s.prior = ones(1,numComponents) ;
s... |
github | Shenc0411/CS445-master | vl_test_imsmooth.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_imsmooth.m | 1,837 | utf_8 | 718235242cad61c9804ba5e881c22f59 | function results = vl_test_imsmooth(varargin)
% VL_TEST_IMSMOOTH
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
I = max(min(vl_imdown(I),1),0) ;
s.I = single(I) ;
function test_pad_by_continuity(s)
% Convolving a constant signal padded with continuity does not change... |
github | Shenc0411/CS445-master | vl_test_svmtrain.m | .m | CS445-master/mp5/vlfeat-0.9.19/toolbox/xtest/vl_test_svmtrain.m | 4,277 | utf_8 | 071b7c66191a22e8236fda16752b27aa | function results = vl_test_svmtrain(varargin)
% VL_TEST_SVMTRAIN
vl_test_init ;
end
function s = setup()
randn('state',0) ;
Np = 10 ;
Nn = 10 ;
xp = diag([1 3])*randn(2, Np) ;
xn = diag([1 3])*randn(2, Nn) ;
xp(1,:) = xp(1,:) + 2 + 1 ;
xn(1,:) = xn(1,:) - 2 + 1 ;
s.x = [xp xn] ;
s.y = [ones(1,Np) ... |
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