plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | TadaoYamaoka/caffe-master | classification_demo.m | .m | caffe-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | frkngrpnr/lapfi-master | LAPFI_align_w_IntraFace.m | .m | lapfi-master/helpers/LAPFI_align_w_IntraFace.m | 12,886 | utf_8 | 29ca0d5d1f0653bf2029d002b0aacd31 | function [alignment] = LAPFI_align_w_IntraFace(inpath, outpath)
%% This code uses the IntraFace library in order to align faces.
% inpath should contain videos, outpath will have .mat files that contain
% aligned videos.
% alignment will be a struct with fields:
% data : Nx1 cell
% label : Nx1
alignment.meta... |
github | frkngrpnr/lapfi-master | fg_normalizeData.m | .m | lapfi-master/helpers/fg_normalizeData.m | 6,663 | utf_8 | 6295d6c33d72a6a801f90276169268a7 | function [ntraindata, norm_model, ntestdata] = fg_normalizeData(traindata, normtype, testdata, verbose)
% [ntraindata, norm_model, ntestdata] = fg_normalizeData(traindata, 'MMN', testdata, 1);
% or
% [data, norm_model] = fg_normalizeData(data, 'MMN');
% or for test data:
% [ntestdata] = fg_normalizeData(testdata,... |
github | frkngrpnr/lapfi-master | LAPFI_attach_labels_val.m | .m | lapfi-master/IO/LAPFI_attach_labels_val.m | 2,196 | utf_8 | f5c62df50249249301783e62de7c65d0 | function [ldset] = LAPFI_attach_labels(dset, gt_train)
if nargin<2, gt_train = evalin('base','gt_train'); end
labelnames = {'ValueExtraversion', 'ValueAgreeableness', 'ValueConscientiousness', 'ValueNeurotisicm', 'ValueOpenness'};
ldset = dset;
% also attach subject_ids
N = size(dset.data,1);
ldset.subject_id = c... |
github | frkngrpnr/lapfi-master | LAPFI_attach_labels.m | .m | lapfi-master/IO/LAPFI_attach_labels.m | 2,232 | utf_8 | 20677650f70b5cfd778e876f5964e25b | function [ldset] = LAPFI_attach_labels(dset, gt_train)
if nargin<2, gt_train = evalin('base','gt_train'); end
labelnames = {'ValueExtraversion', 'ValueAgreeableness', 'ValueConscientiousness', 'ValueNeurotisicm', 'ValueOpenness'};
ldset = dset;
% also attach subject_ids
N = size(dset.data,1);
ldset.subject_id = c... |
github | frkngrpnr/lapfi-master | LAPFI_extract_video_TOP_features.m | .m | lapfi-master/feature_extraction/LAPFI_extract_video_TOP_features.m | 3,361 | utf_8 | cefb49a2caa53651bb19c68e883ab29e | function [fset] = LAPFI_extract_video_TOP_features(inpath, feature_name, feature_params)
% inpath folder will have .mat files with aligned videos in them
% for LGBP-TOP, you need to have the VLFeat library installed.
%% Input validation
extra_params={}; if nargin<3, feature_params = []; end
feature_name = upper(fe... |
github | frkngrpnr/lapfi-master | LAPFI_extract_frame_features.m | .m | lapfi-master/feature_extraction/LAPFI_extract_frame_features.m | 4,255 | utf_8 | 7afe6ddeccd33fb8b1921dbec05c8e16 | function [no_output] = LAPFI_extract_frame_features(inpath, outpath, feature_name, feature_params, extra_params)
% This code extracts frame-level features from aligned videos.
%% Parameters:
% inpath is a folder with .mat files that contain the aligned videos.
% outpath will have .mat files with the same names, con... |
github | frkngrpnr/lapfi-master | LAPFI_extract_scene_features.m | .m | lapfi-master/feature_extraction/LAPFI_extract_scene_features.m | 4,288 | utf_8 | b5f560846f922ab6f81c02915493ae5b | function [fset] = LAPFI_extract_scene_features(inpath, outpath, feature_name, feature_params, extra_params)
% inpath folder will have the original .mp4 files
%% Input validation
if nargin<5, extra_params={}; end
if nargin<3, feature_params = []; end
bss = '\';
feature_name = upper(feature_name);
if strcmp(feat... |
github | frkngrpnr/lapfi-master | video_to_lgbp_top_2015.m | .m | lapfi-master/feature_extraction/video_to_lgbp_top_2015.m | 1,209 | utf_8 | a66a2303ba8575cdb2c3a094f4354a97 | function [lgbp_top] = video_to_lgbp_top_2015(vid,gfb)
%% Inputs :
% vid is a matrix [I x F]
% I : image size (=w*h)
% F : number of frames
%% Outputs :
% lgbptop is a 174 (3*58) x 18 matrix, where each column is the LBP-TOP of
% a gabor video, and we have 18 different gabor videos per video.
lgbp_top=[];
S =... |
github | frkngrpnr/lapfi-master | elm_kernel.m | .m | lapfi-master/modeling/ELM/Kernel Version/elm_kernel.m | 7,935 | utf_8 | aec630d7d9ea4b192774e673e1101375 | function [TrainingTime, TestingTime, TrainingAccuracy, TestingAccuracy,TY, Omega_train, Omega_test] = elm_kernel(TrainingData, TestData, TrainingLabels, TestLabels, Elm_Type, Regularization_coefficient, Kernel_type, Kernel_para)
% Usage: elm(TrainingData_File, TestingData_File, Elm_Type, NumberofHiddenNeurons, Activ... |
github | Raknoche/MyCode-master | Submit_KrypCal_to_LUG.m | .m | MyCode-master/CodeForLUX/Matlab/Submit_KrypCal_to_LUG.m | 6,542 | utf_8 | 25b4a635bbb0bf80f9006219b64bc2be | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function runs KrypCal on all of the data in a given directory.
% Files are skipped if they already have IQs on the LUG.
%
% Inputs:
% - user_name - Username for the LUG entr... |
github | Raknoche/MyCode-master | ApplyCorrections.m | .m | MyCode-master/CodeForLUX/Matlab/ApplyCorrections.m | 17,433 | utf_8 | 066af3c46f6fa01700f7ab06c2db8944 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function queries the LUG to find and apply the appropriate XY, and Z corrections
% for the dataset being processed. This runs as part of the DP framework, and produces
% a number of co... |
github | Raknoche/MyCode-master | KrypCal.m | .m | MyCode-master/CodeForLUX/Matlab/KrypCal.m | 135,496 | utf_8 | 613352dffc7da3419a052c740cdc7964 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ____ ____ _____ _____ _____ _____ _____ ____ ____
%| | | | ___|\ \ |\ \ / /| ___|\ \ ___|\... |
github | Raknoche/MyCode-master | calcnbins.m | .m | MyCode-master/CodeForLUX/Matlab/MyScripts/KrypCal_FieldEffectMeasurements/TritiumMethod/libNEST_CH3TModel/landau_fit/calcnbins.m | 3,239 | utf_8 | 5797fcc3c5ca9ac3618bb4e8f0861962 |
function nbins = calcnbins(x, method, minimum, maximum)
error(nargchk(1, 4, nargin));
if ~isnumeric(x) && ~islogical(x)
error('calcnbins:invalidX', 'The X argument must be numeric or logical.')
end
if ~isreal(x)
x = real(x);
warning('calcnbins:complexX', 'Imaginary parts of X will be ignored.');
end
% ... |
github | Raknoche/MyCode-master | landau_.m | .m | MyCode-master/CodeForLUX/Matlab/MyScripts/KrypCal_FieldEffectMeasurements/TritiumMethod/libNEST_CH3TModel/landau_fit/landau_.m | 2,355 | utf_8 | 6ea5b8b23f9673e7029592674b64a0fe |
function y=landau_(x,mpv,sigma,norm)
p1 = [0.4259894875,-0.1249762550, 0.03984243700, -0.006298287635, 0.001511162253];
q1 = [1.0 ,-0.3388260629, 0.09594393323, -0.01608042283, 0.003778942063];
p2 = [0.1788541609, 0.1173957403, 0.01488850518, -0.001394989411, 0.0001283617211];
q2 = [1.0 , 0.742... |
github | Raknoche/MyCode-master | MeasureS1aS1b3DDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureS1aS1b3DDep.m | 5,309 | utf_8 | 46308765dfd0cb16437f62a558c7b487 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces three dimensional maps of the S1a, S1b, and S1a/S1b means
%
% Inputs:
% - s1ab_x - S1a/S1b x position after golden selection
% - s1ab_y ... |
github | Raknoche/MyCode-master | RemoveFieldDependence_3D.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/RemoveFieldDependence_3D.m | 3,449 | utf_8 | 303486dafd74b8e8d529a6174e1b8a56 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces field removal (3D dependence) matrices for Kr83m S1 and S2 data.
% Note this will ONLY work for Kr83m, and not for other sources
%
% Inputs:
% - s1ab_xyz_xbins -... |
github | Raknoche/MyCode-master | EstimateField.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/EstimateField.m | 4,765 | utf_8 | f13eed97df68033610fdff5f2177f01b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function takes s2radius and s2drift inputs in the form of 1D vectors. It
% uses Scott Hertel's field simulation to determine the field at the location of each data point.
% The output of this funct... |
github | Raknoche/MyCode-master | RemoveFieldDependence_1D.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/RemoveFieldDependence_1D.m | 1,775 | utf_8 | 526a40051ff1f29980ac8df806f0d507 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces field removal (Z dependence only) matrices for Kr83m S1 and S2 data.
% Note this will ONLY work for Kr83m, and not for other sources
%
% Inputs:
% - s1ab_P ... |
github | Raknoche/MyCode-master | RK_1DCubicInterp_LinearExtrap.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/RK_1DCubicInterp_LinearExtrap.m | 3,729 | utf_8 | f30d11485c1dee003bb72f0b384a1550 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function does 1D cubic interpolation within the bounds of the map,
% and linear extrapolation based on the first/last 20% of the map
%
% Inputs:
% - X - X bins of the map
%... |
github | Raknoche/MyCode-master | MeasureS2PulseWidthXYDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureS2PulseWidthXYDep.m | 2,953 | utf_8 | 0c3605c5fc766f84dd7a3ea3145979e3 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces XY dependence maps of the S2 Pulse width
%
% Inputs:
% - s2x - X position of events after golden selection
% - s2y - Y position of ev... |
github | Raknoche/MyCode-master | KrypCal_S1_3D.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/KrypCal_S1_3D.m | 19,156 | utf_8 | 9f26905525fe71a9afe099f26922db3a | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces XYZ dependence maps of the S1 signal and directly submits
% the result to the LUG.
%
% Inputs:
% - s1_phe_both - S1 pulse areas (with both arrays) after gold... |
github | Raknoche/MyCode-master | MeasureS1aS1bXYDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureS1aS1bXYDep.m | 4,474 | utf_8 | 2922f1e2fbcc3567d578e6509c67f17e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces XY dependence maps of the S1a, S1b, and S1a/S1b means
%
% Inputs:
% - s1ab_x - S1a/S1b X coordinates after golden selection
% - s1ab_y - S1... |
github | Raknoche/MyCode-master | MeasurePulseAreaZDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasurePulseAreaZDep.m | 3,402 | utf_8 | 950d653cddd0c5c21c81383057620685 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function measures the Z dependence of a pulse area RQ
%
% Inputs:
% - bin_min - Minimum of the histograms used during Gaussian fitting
% - bin_max - Maximum of... |
github | Raknoche/MyCode-master | MeasureSEXYDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureSEXYDep.m | 5,834 | utf_8 | 66e52f6d1e15e00ffcf02311b18c0405 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces XY dependence maps of the single electron size
%
% Inputs:
% - SE_pulse_area - Single electron pulse areas after golden selection
% - SE_x - Sin... |
github | Raknoche/MyCode-master | ProducePulseAreaXYNorms.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/ProducePulseAreaXYNorms.m | 1,790 | utf_8 | 1a0f018ff6537e5a0bb4e952202d5d2c | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces XY normalization maps from XY pulse area mean maps
%
% Inputs:
% - xbins - 1xN vector defining x binning of XY means map
% - ybins - 1xM vect... |
github | Raknoche/MyCode-master | GetGoldenCuts.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/GetGoldenCuts.m | 2,860 | utf_8 | 53d1e717bcdc3841e68288bfb7532db5 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces golden event selection cuts between S1 and S2 area bounds
%
% Inputs:
% - d - the data structure to be analysed.
% - s1area_bound_min - Minimum S1 s... |
github | Raknoche/MyCode-master | MeasurePulseAreaXYDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasurePulseAreaXYDep.m | 3,890 | utf_8 | d7b13fd6cb068ca0516369f48242fed0 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces XY dependence maps of the given pulse area
%
% Inputs:
% - bin_min - Minimum range of the Gaussian fit histograms
% - bin_max - Maximum range... |
github | Raknoche/MyCode-master | rkploterr.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/rkploterr.m | 4,782 | utf_8 | 117dfb4bcc5ccb284fc264f9b6ca4720 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function edits the standard ploterr code so that it is easier to plot. Errorbars
% no longer have horizontal lines, horizontal error bars are now an option, and each point
% is consider... |
github | Raknoche/MyCode-master | MeasureS1aS1bZDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureS1aS1bZDep.m | 3,739 | utf_8 | a40e4433b87bbc7b17f5d6ce5f239f63 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces Z dependence maps and polynomial fits for the S1a, S1b, and S1a/S1b means
%
% Inputs:
% - det_edge - Edge of the drift time histogram (typically 330 uSec in Run0... |
github | Raknoche/MyCode-master | MeasureSESize.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureSESize.m | 2,991 | utf_8 | 1da8ffe49925b0f548f95a2e0aa9d5ac | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function fits a skew Gaussian to a single electron pulse area histogram
%
% Inputs:
% - SE_hist_binning - Binning to use in the histogram
% - SE_pulse_area - Single electron pulse... |
github | Raknoche/MyCode-master | GetS1aS1bCuts.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/GetS1aS1bCuts.m | 1,288 | utf_8 | ce852387c54cd66990a1c8781010d764 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces golden event selection cuts for Kr S1a and S1b pulses
%
% Inputs:
% - d - the data structure to be analysed.
% - s1_single_cut - Golden event cu... |
github | Raknoche/MyCode-master | GetS1aS1bFiducialCuts.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/GetS1aS1bFiducialCuts.m | 2,642 | utf_8 | 5a746e422252eb9c308a71688bc96b3c | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces fiducial volume cuts for Kr S1a and S1b pulses
%
% Inputs:
% - s1ab_z - S1a/S1b z coordinates after golden cut is applied
% - s2radius - S1a/S1b... |
github | Raknoche/MyCode-master | MeasureS2PulseWidthZDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureS2PulseWidthZDep.m | 3,023 | utf_8 | b1286cf2150b88f5d07b609502f84029 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces Z dependence maps of the S2 pulse width
%
% Inputs:
% - s2_width - S2 Width RQ after golden selection
% - drift_time - Drift time after g... |
github | Raknoche/MyCode-master | MeasureS1aS1bRvZDep.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/MeasureS1aS1bRvZDep.m | 4,885 | utf_8 | b4c707c64470f3335348cfea4a6bec50 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces two dimensional R^2 v Z maps of the S1a, S1b, and S1a/S1b means
%
% Inputs:
% - s1ab_radius - S1a/S1b radius after golden selection
% - s1ab_z ... |
github | Raknoche/MyCode-master | GetSECuts.m | .m | MyCode-master/CodeForLUX/Matlab/MyFunctions/GetSECuts.m | 1,116 | utf_8 | f55ff4d6f831b7ac8088faa1207c3005 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Purpose:
% This function produces single electron selection cuts from golden S1 and S2 events
%
% Inputs:
% - d - the data structure to be analysed.
% - s1_single_cut - 10xN Golde... |
github | zeroc-ice/ice-debian-packaging-main | removeFolderFromPath.m | .m | ice-debian-packaging-main/matlab/toolbox/removeFolderFromPath.m | 296 | utf_8 | f3ff894d79494ecc72e480101a64bf5f | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function removeFolderFromPath(p)
try
fprintf(1, 'Removing toolxbox folder from path... ');
rmpath(p);
savepath();
fprintf(1, 'ok\n');
exit(0);
catch e
fprintf(1, 'failed\n%s', getReport(e));
exit(1);
end
end
|
github | zeroc-ice/ice-debian-packaging-main | addFolderToPath.m | .m | ice-debian-packaging-main/matlab/toolbox/addFolderToPath.m | 288 | utf_8 | 5722423101ec86eed73270675157460d | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function addFolderToPath(f)
try
fprintf(1, 'Adding toolxbox folder to path... ');
addpath(f);
savepath();
fprintf(1, 'ok\n');
exit(0);
catch e
fprintf(1, 'failed\n%s', getReport(e));
exit(1);
end
end
|
github | zeroc-ice/ice-debian-packaging-main | buildToolbox.m | .m | ice-debian-packaging-main/matlab/toolbox/buildToolbox.m | 1,017 | utf_8 | b1d4be5a2e5c664100f6a47ddb74ec65 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function buildToolbox(iceVersion)
rootDir = fileparts(mfilename('fullpath'));
packageDir = fullfile(rootDir, 'build');
projectFile = fullfile(rootDir, 'toolbox.prj');
if isunix
os = 'linux';
else
os = 'win';
end
try
fprintf(1, 'Building ... |
github | zeroc-ice/ice-debian-packaging-main | runTest.m | .m | ice-debian-packaging-main/matlab/test/lib/runTest.m | 821 | utf_8 | 14d34cd75ead8ea5cda970be686b9ca6 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function runTest(varargin)
if length(varargin) == 0
fprintf('testdir argument required\n');
exit(1);
end
testdir = varargin{1};
varargin(1) = []; % Removes first argument.
libsubdir = varargin{1};
varargin(1) = []; % Removes ... |
github | zeroc-ice/ice-debian-packaging-main | LocalTests.m | .m | ice-debian-packaging-main/matlab/test/Ice/objects/LocalTests.m | 38,325 | utf_8 | 59160cd39eb9c39c7599968eeac067db | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
%
% These tests exercise some corner cases of the mapping.
%
classdef LocalTests
methods(Static)
function localTests(helper)
import LocalTest.*;
communicator = helper.communicator();
props = communicator.getProperties... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/objects/Client.m | 1,561 | utf_8 | bf50b1f63fe342bcc280ef610bc182b9 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
properties = helper.createTestProperties(args);
properties.setProperty('Ice.Warn.Connections', '0');
comm... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/optional/Client.m | 452 | utf_8 | 1403fa71d428924795f74e72e3859efd | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
initial = AllTes... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/proxy/Client.m | 453 | utf_8 | ef0ebbe57e11a1f2345664cb71ffb293 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
myClass = AllTe... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/binding/Client.m | 418 | utf_8 | 0789c019951da5a790060612771eb0b2 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
AllTests.allTest... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/facets/Client.m | 440 | utf_8 | 0b3a1c86beafc348cd86888302a6eb28 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
g = AllTests.all... |
github | zeroc-ice/ice-debian-packaging-main | OnewaysAMI.m | .m | ice-debian-packaging-main/matlab/test/Ice/operations/OnewaysAMI.m | 1,333 | utf_8 | 78f1729ca4fc6e3d5eec57546fdc6022 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
classdef OnewaysAMI
methods(Static)
function onewaysAMI(p)
import Test.*;
p = p.ice_oneway();
call(p, 'ice_ping');
try
p.ice_isAAsync(MyClassPrx.ice_staticId());
catch ex
... |
github | zeroc-ice/ice-debian-packaging-main | TwowaysAMI.m | .m | ice-debian-packaging-main/matlab/test/Ice/operations/TwowaysAMI.m | 45,096 | utf_8 | 480d313f8964844db4ab4f0d76da9543 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
classdef TwowaysAMI
methods(Static)
function twowaysAMI(helper, p)
import Test.*;
call(p, 'ice_ping');
b = call(p, 'ice_isA', MyClassPrx.ice_staticId());
assert(b);
id = call(p, 'ice_id');
... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/operations/Client.m | 1,014 | utf_8 | 0aea5303975d94af71c9152f0c8c5188 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
properties = helper.createTestProperties(args);
properties.setProperty('Ice.ThreadPool.Client.Size', '2');
... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/ami/Client.m | 783 | utf_8 | 96830c9a0ce17297fc09e967aebbb844 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
properties = helper.createTestProperties(args);
properties.setProperty('Ice.Warn.AMICallback', '0');
prop... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/slicing/objects/Client.m | 446 | utf_8 | 91cfab5e1fc1e8ece6eacfdd91f571e7 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
test = AllTests.... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/slicing/exceptions/Client.m | 446 | utf_8 | 91cfab5e1fc1e8ece6eacfdd91f571e7 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
test = AllTests.... |
github | zeroc-ice/ice-debian-packaging-main | AllTests.m | .m | ice-debian-packaging-main/matlab/test/Ice/info/AllTests.m | 6,945 | utf_8 | c5e4176da9158e9dd0365e2d79e20970 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
classdef AllTests
methods(Static)
function allTests(helper)
import Test.*;
communicator = helper.communicator();
fprintf('testing proxy endpoint information... ');
p1 = communicator.stringToProxy(...
... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/info/Client.m | 418 | utf_8 | 0789c019951da5a790060612771eb0b2 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
AllTests.allTest... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/defaultValue/Client.m | 418 | utf_8 | 0789c019951da5a790060612771eb0b2 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
AllTests.allTest... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/enums/Client.m | 446 | utf_8 | 91cfab5e1fc1e8ece6eacfdd91f571e7 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
test = AllTests.... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/timeout/Client.m | 922 | utf_8 | daa6f315e5a6a7e6b8b908b9fc4a200f | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
properties = helper.createTestProperties(args);
%
% For this test, we want to disable retries.
%
... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/exceptions/Client.m | 635 | utf_8 | 6c9a089cf83ee04647f8aa3b32592d2a | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
properties = helper.createTestProperties(args);
properties.setProperty('Ice.Warn.Connections', '0');
prop... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/acm/Client.m | 534 | utf_8 | 482e84c629eff62bf472841d58f2e8b7 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
properties = helper.createTestProperties(args);
properties.setProperty('Ice.Warn.Connections', '0');
comm... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Ice/inheritance/Client.m | 452 | utf_8 | 1403fa71d428924795f74e72e3859efd | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
initial = AllTes... |
github | zeroc-ice/ice-debian-packaging-main | Client.m | .m | ice-debian-packaging-main/matlab/test/Slice/escape/Client.m | 418 | utf_8 | 0789c019951da5a790060612771eb0b2 | %
% Copyright (c) ZeroC, Inc. All rights reserved.
%
function client(args)
addpath('generated');
if ~libisloaded('ice')
loadlibrary('ice', @iceproto)
end
helper = TestHelper();
communicator = helper.initialize(args);
cleanup = onCleanup(@() communicator.destroy());
AllTests.allTest... |
github | SatStressGUI/SatStressGUI-master | afunc.m | .m | SatStressGUI-master/Contents/Resources/lib/python2.5/scipy/io/matlab/tests/afunc.m | 198 | utf_8 | 001c8b39c33bf4f7513b2e87a13478f2 | function [a, b] = afunc(c, d)
% A function
a = c + 1;
b = d + 10;
function [a, b] = afunc(c, d)
% A function
a = c + 1;
b = d + 10;
function [a, b] = afunc(c, d)
% A function
a = c + 1;
b = d + 10;
|
github | zclhit/DIP_project2_HIT-master | appendimages.m | .m | DIP_project2_HIT-master/appendimages.m | 461 | utf_8 | a7ad42558236d4f7bd90dc6e72631d54 | % im = appendimages(image1, image2)
%
% Return a new image that appends the two images side-by-side.
function im = appendimages(image1, image2)
% Select the image with the fewest rows and fill in enough empty rows
% to make it the same height as the other image.
rows1 = size(image1,1);
rows2 = size(image2,1);
if (... |
github | zclhit/DIP_project2_HIT-master | showkeys.m | .m | DIP_project2_HIT-master/showkeys.m | 1,699 | utf_8 | 4e67466c0fd7739350cb2af5767e10a4 | % showkeys(image, locs)
%
% This function displays an image with SIFT keypoints overlayed.
% Input parameters:
% image: the file name for the image (grayscale)
% locs: matrix in which each row gives a keypoint location (row,
% column, scale, orientation)
function showkeys(image, locs)
disp('Drawin... |
github | zclhit/DIP_project2_HIT-master | sift.m | .m | DIP_project2_HIT-master/sift.m | 2,568 | utf_8 | b611da51b9aff52e6139dcf866ad2128 | % [image, descriptors, locs] = sift(imageFile)
%
% This function reads an image and returns its SIFT keypoints.
% Input parameters:
% imageFile: the file name for the image.
%
% Returned:
% image: the image array in double format
% descriptors: a K-by-128 matrix, where each row gives an invariant
% ... |
github | zclhit/DIP_project2_HIT-master | match.m | .m | DIP_project2_HIT-master/match.m | 1,992 | utf_8 | 428cfc56368b130ec14df9462dc5640b | % num = match(image1, image2)
%
% This function reads two images, finds their SIFT features, and
% displays lines connecting the matched keypoints. A match is accepted
% only if its distance is less than distRatio times the distance to the
% second closest match.
% It returns the number of matches displayed.
%
%... |
github | shaohuawan/py-faster-rcnn-master | voc_eval.m | .m | py-faster-rcnn-master/lib/datasets/VOCdevkit-matlab-wrapper/voc_eval.m | 1,332 | utf_8 | 3ee1d5373b091ae4ab79d26ab657c962 | function res = voc_eval(path, comp_id, test_set, output_dir)
VOCopts = get_voc_opts(path);
VOCopts.testset = test_set;
for i = 1:length(VOCopts.classes)
cls = VOCopts.classes{i};
res(i) = voc_eval_cls(cls, VOCopts, comp_id, output_dir);
end
fprintf('\n~~~~~~~~~~~~~~~~~~~~\n');
fprintf('Results:\n');
aps = [res(:... |
github | infant-cognition-tampere/saccademodel-m-master | utils.m | .m | saccademodel-m-master/utils.m | 1,434 | utf_8 | c69038ad92e3dc8b88f5499e1da09b92 | function x = utils
% Google: matlab call local functions using function handles
x.colsBeforeTime = @selectColsBeforeTime;
x.colsAfterTime = @selectColsAfterTime;
x.firstCols = @selectFirstCols;
x.lastCols = @selectLastCols;
x.colsTimeToTime = @selectColsTimeToTime;
end
function Y = selectColsBe... |
github | cswluo/CSAEs-master | TiedRecstConvNets.m | .m | CSAEs-master/TiedRecstConvNets.m | 4,508 | utf_8 | 036caa8df6eac82ae1135a9a37cb76c6 | function [dkernels, hbias, obias, params, decoder, rerror] = TiedRecstConvNets(X, acttype, dkernels,...
hbias, obias, params, stride, varargin)
if nargin == 9
tiedflag = varargin{1};
nneighbors = varargin{2};
elseif nargin == 8
tiedflag = varargin{1};
nneighbors = 5;... |
github | cswluo/CSAEs-master | PreprocessingCaltech.m | .m | CSAEs-master/utils/PreprocessingCaltech.m | 3,672 | utf_8 | f268a142a216c08d76c41cc842e4b88c | function PreprocessingCaltech(src,dst)
fSize = 7;
kernel = make_kernel(fSize);
maxImSize = 102;
subfolders = dir(src);
for i = 1:length(subfolders)
if ~strcmp(subfolders(i).name, '.') & ~strcmp(subfolders(i).name, '..')
folder_flag = subfolders(i).isdir;
if fo... |
github | cswluo/CSAEs-master | make_kernel.m | .m | CSAEs-master/utils/make_kernel.m | 549 | utf_8 | c81443b7331df8a266ad98168cd5fb1e | % make Gaussian kernel to be used as weighted window in the local
% normalization of the images in the C101.
function k = make_kernel(sz)
% sz is the size of the kernel: sz x sz
% k is the kernel
x = - floor(sz/2) : 1 : floor(sz/2);
s = sz/4; % standard deviation (width) of kernel
k1 = exp(- (x./s).^2);
k = k1' * k1;... |
github | cswluo/CSAEs-master | DisplayWeights.m | .m | CSAEs-master/utils/DisplayWeights.m | 3,403 | utf_8 | 712836284abc3b335d342060a0e77e6f | function DisplayWeights(ae, varargin)
if nargin == 3
hierFlag = varargin{1};
net_type = varargin{2};
else
hierFlag = 0;
net_type = 'ae';
end
t = 10;
if hierFlag % unsuprevise for deep layer
W = {};
for i = 1:le... |
github | cswluo/CSAEs-master | random_patches.m | .m | CSAEs-master/utils/random_patches.m | 8,662 | utf_8 | 2435f2b24eadd8e8a6f1f7511187786b | % random sample patches from Berkley training set
function [varargout] = random_patches(varargin)
if nargin < 4
img_dir = 'D:\BaiduDrive\My Database\Images\Berkerly\BSR\BSDS500\data\images\train'; % Berkley training set
num_patches = 100000;
patch_size = 16;
datasetName = [];... |
github | cswluo/CSAEs-master | convnet_maxpool.m | .m | CSAEs-master/utils/maxpooling/convnet_maxpool.m | 3,481 | utf_8 | a7388e01649873ea10c1d50f4c18b5a5 | % convnet_maxpool
% Copyright (C) 2013 KyungHyun Cho
%
%This program is free software; you can redistribute it and/or
%modify it under the terms of the GNU General Public License
%as published by the Free Software Foundation; either version 2
%of the License, or (at your option) any later version.
%
%This program is di... |
github | cswluo/CSAEs-master | AveReconstError.m | .m | CSAEs-master/AssitFunc/AveReconstError.m | 3,436 | utf_8 | 3223c9ebeaba57af5e3e9daee8153137 | function aveError = AveReconstError(xtrain, poolstride, vneighbors, varargin)
if nargin < 4
error('Must specify the location of learned kernels.\n');
else
kerlocations = varargin{1};
end
load(kerlocations);
numTrains = size(xtrain,2);
imgsize = repmat(sqrt(size(xtrain,1)),1,2);
if numTrains > 500... |
github | cswluo/CSAEs-master | cnn_test.m | .m | CSAEs-master/CNN/cnn_test.m | 2,315 | utf_8 | e6c201027c7937f96e2b74bf7a494901 | function [info] = cnn_test(net, xtest, ytest, varargin)
opts.batchSize = 256 ;
opts.useGpu = false ;
opts.errorType = 'multiclass' ;
opts.expDir = 'data/exp' ;
opts.test = [] ;
opts.imgsize = [];
opts.conserveMemory = true ;
opts.sync = true ;
opts.prefetch = false ;
opts = vl_argparse(opts, varargin) ;
imgsize ... |
github | cswluo/CSAEs-master | cnn_trainval.m | .m | CSAEs-master/CNN/cnn_trainval.m | 9,441 | utf_8 | 9138347390c1b5788d24d17fb84e1baf | function [net,info] = cnn_trainval(net, xtrain, ytrain, xval, yval, varargin)
opts.datainfo.datasetName = [];
opts.datainfo.numClass = 10;
opts.datainfo.imgsize = [];
opts.datainfo.trNum = 30;
opts.datainfo.train = [] ;
opts.datainfo.val = [] ;
opts.numEpochs = 300 ;
opts.batchSize = 256 ;
opts.useGpu = false ;
opts.... |
github | cswluo/CSAEs-master | cnn_train.m | .m | CSAEs-master/CNN/cnn_train.m | 7,372 | utf_8 | 231790cc22f0728b8379e85d0ec9c5fa | function [net,info] = cnn_train(net, xtrain, ytrain, varargin)
opts.datainfo.datasetName = [];
opts.datainfo.numClass = 10;
opts.datainfo.imgsize = [];
opts.datainfo.trNum = 30;
opts.datainfo.train = [] ;
opts.numEpochs = 300 ;
opts.batchSize = 256 ;
opts.useGpu = false ;
opts.weightDecay = 0.0005 ;
opts.momentum = 0... |
github | cswluo/CSAEs-master | cnn_trainval_mnist.m | .m | CSAEs-master/MNIST/cnn_trainval_mnist.m | 9,201 | utf_8 | 3ac30c2ef6b2e9a949142136b48f8dd9 | function [net,info] = cnn_trainval_mnist(net, xtrain, ytrain, xval, yval, varargin)
opts.datainfo.datasetName = [];
opts.datainfo.numClass = 10;
opts.datainfo.imgsize = [];
opts.datainfo.train = [] ;
opts.datainfo.val = [] ;
opts.numEpochs = 300 ;
opts.batchSize = 256 ;
opts.useGpu = false ;
opts.weightDecay = 0.0005... |
github | cswluo/CSAEs-master | cnn_train_mnist.m | .m | CSAEs-master/MNIST/cnn_train_mnist.m | 7,408 | utf_8 | 6dee0f3f86e17152fac33bca72d4c6a0 | function [net,info] = cnn_train_mnist(net, xtrain, ytrain, varargin)
opts.datainfo.datasetName = [];
opts.datainfo.numClass = 10;
opts.datainfo.imgsize = [];
opts.datainfo.trNum = 30;
opts.datainfo.train = [] ;
opts.numEpochs = 300 ;
opts.batchSize = 256 ;
opts.useGpu = false ;
opts.weightDecay = 0.0005 ;
opts.moment... |
github | Diti24/opticspy-master | getRefractiveIndex.m | .m | opticspy-master/ray_tracing/glass_function/getRefractiveIndex.m | 1,047 | utf_8 | cd680e605de793869ddb9cbfc6f92f9c | # This file is part of PyTMM.
#
# PyTMM is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# PyTMM is distributed in t... |
github | geez0x1/CompliantJointToolbox-master | cjtExamples.m | .m | CompliantJointToolbox-master/cjtExamples.m | 13,133 | utf_8 | 3a2ce07301a269a87263305529975955 | function cjtExamples
% CJTEXAMPLES Compliant Joint Toolbox Examples GUI
%
% This file implements a graphical user interface that allows to explore
% the Matlab and Simulink examples provided with the Compliant Joint
% Toolbox.
%
% Author::
% Joern Malzahn
% Wesley Roozing
%
% See also genericJoint.
% C... |
github | geez0x1/CompliantJointToolbox-master | toggleMaskFields.m | .m | CompliantJointToolbox-master/lib/include/toggleMaskFields.m | 3,399 | utf_8 | 2a5bae78487d9116efe67c46515fe9b6 | % TOGGLEMASKFIELDS Enable/disable mask fields based on the settings of checkboxes
% (supports multiple fields by using a cell for the 'fields' argument).
%
% toggleMaskFields( blockH, checkbox, fields [, onDirection ])
%
% Inputs::
%
% blockH: handle to the Simulink block under consideration
% checkbox: handle ... |
github | geez0x1/CompliantJointToolbox-master | getDynamicsMatrices.m | .m | CompliantJointToolbox-master/templates/getDynamicsMatrices.m | 1,557 | utf_8 | 539f5abf3221ba07ed03199878adfa2b | %%GETDYNAMICSMATRICES Template for obtaining state space matrices for the linear dynamics.
%%
%% [A, B, C, D, I, R, K] = jointObj.getDynamicsMatrices
%%
%% jointObj is the instance of the joint class object for which this
%% function has been called.
%%
%% Outputs::
%%
%%
%% A: System matrix
%% B: Input matrix
%% ... |
github | geez0x1/CompliantJointToolbox-master | constructor.m | .m | CompliantJointToolbox-master/templates/constructor.m | 1,511 | utf_8 | c871dca3608702fa840946fb4361b64b | %%CONSTRUCTOR Template for joint class constructor
%%
%% Author::
%% Joern Malzahn
%% Wesley Roozing
%%
%% See also genericJoint, jointBuilder, getNonlinearDynamics.
%% Copyright (C) 2016, by Joern Malzahn, Wesley Roozing
%%
%% This file has been generated with the Compliant Joint Toolbox (CJT).
%%
%% CJT is free so... |
github | geez0x1/CompliantJointToolbox-master | electric_dyn_zero_inductance.m | .m | CompliantJointToolbox-master/model/electrical/electric_dyn_zero_inductance.m | 2,251 | utf_8 | 3abde2c7d40cd39816863342d22a3327 | %ELECTRIC_DYN_ZERO_INDUCTANCE Get linear dynamics matrices for the
%electrical subsystem when inductance can be ignored
%
% [A, B, C, D] = electric_dyn(jointObj)
%
% jointObj is the instance of the joint class object for which this
% function has been called. Alternatively, it can be called for joints
% which we... |
github | geez0x1/CompliantJointToolbox-master | electric_dyn_dq.m | .m | CompliantJointToolbox-master/model/electrical/electric_dyn_dq.m | 3,744 | utf_8 | bf7f7edc727c3f46a5373f24b314dc7c | %ELECTRIC_DYN_DQ Get compute nonlinear dynamics for the electrical
%subsystem with a d-q axis current model
%
% [x_dot, tau_m] = electric_dyn_dq(jointObj, x, u)
%
% Inputs::
% jointObj: instance of the joint class object for which this function
% has been called.
% x: Current state vector... |
github | geez0x1/CompliantJointToolbox-master | electric_dyn.m | .m | CompliantJointToolbox-master/model/electrical/electric_dyn.m | 2,477 | utf_8 | 2e33b222a64aa9cb9ebb37254b17800e | %ELECTRIC_DYN Get linear dynamics matrices for the electrical subsystem
%
% [A, B, C, D] = electric_dyn(jointObj)
%
% jointObj is the instance of the joint class object for which this
% function has been called. Alternatively, it can be called for joints
% which were built with these dynamics as:
% [A, B, C, D] ... |
github | geez0x1/CompliantJointToolbox-master | output_fixed_rigid_gearbox.m | .m | CompliantJointToolbox-master/model/linear/output_fixed_rigid_gearbox.m | 3,586 | utf_8 | 906d14e1e80141fd96f65bcdce103b4a | %OUTPUT_FIXED_RIGID_GEARBOX Get linear dynamics matrices - output link
% fixed, gearbox rigid
%
% [A, B, C, D, I, R, K] = jointObj.output_fixed_rigid_gearbox
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
% Outputs::
% A: System matrix
% B: Input matrix
% C... |
github | geez0x1/CompliantJointToolbox-master | output_fixed.m | .m | CompliantJointToolbox-master/model/linear/output_fixed.m | 3,790 | utf_8 | a5d8937ea7218ee93e150c5076f116b9 | %OUTPUT_FIXED Get linear dynamics matrices - output link fixed
%
% [A, B, C, D, I, R, K] = jointObj.output_fixed
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
% Outputs::
% A: System matrix
% B: Input matrix
% C: Output matrix
% D: Direct Feedthrough... |
github | geez0x1/CompliantJointToolbox-master | full_dyn.m | .m | CompliantJointToolbox-master/model/linear/full_dyn.m | 3,223 | utf_8 | 717a8957a20f6f522d0bea7a0deef4f3 | %FULL_DYN Get linear dynamics matrices - default
%
% [A, B, C, D, I, R, K] = jointObj.full_dyn
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
% Outputs::
% A: System matrix
% B: Input matrix
% C: Output matrix
% D: Direct Feedthrough matrix
% I: I... |
github | geez0x1/CompliantJointToolbox-master | rigid_gearbox.m | .m | CompliantJointToolbox-master/model/linear/rigid_gearbox.m | 3,406 | utf_8 | 802f53786e2218ad127e5714838f962d | %RIGID_GEARBOX Get linear dynamics matrices - rigid gearbox
%
% [A, B, C, D, I, R, K] = jointObj.rigid_gearbox
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
% Outputs::
% A: System matrix
% B: Input matrix
% C: Output matrix
% D: Direct Feedthrough m... |
github | geez0x1/CompliantJointToolbox-master | rigid.m | .m | CompliantJointToolbox-master/model/linear/rigid.m | 2,769 | utf_8 | 225f30078a76a0fc7c71b302098c3730 | %RIGID Get linear dynamics matrices - fully rigid joint
%
% [A, B, C, D, I, R, K] = jointObj.rigid
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
% Outputs::
% A: System matrix
% B: Input matrix
% C: Output matrix
% D: Direct Feedthrough matrix
% I:... |
github | geez0x1/CompliantJointToolbox-master | coulomb.m | .m | CompliantJointToolbox-master/model/nonlinear/coulomb.m | 2,635 | utf_8 | 6c4ef6d0e0256b8c201ce39af9bcc25d | %COULOMB Calculate Coulomb friction torques
%
% [ tau, y ] = coulomb(jointObj, x)
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
%
% Inputs::
% x: state vector depending on the model type as
% x = [q_m; q_g; q_l; q_m_dot; q_g_dot, q_l_dot']; full_dyn
% x =... |
github | geez0x1/CompliantJointToolbox-master | torque_ripple.m | .m | CompliantJointToolbox-master/model/nonlinear/torque_ripple.m | 4,939 | utf_8 | ba3bb458e33818558f93c8a3b1a9d4e2 | %TORQUE_RIPPLE Calculate torque ripple torques
%
% [ tau, y ] = torque_ripple(jointObj, x)
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
%
% Inputs::
% x: state vector depending on the model type as
% x = [q_m; q_g; q_l; q_m_dot; q_g_dot, q_l_dot']; full_dyn
... |
github | geez0x1/CompliantJointToolbox-master | coulomb_asym.m | .m | CompliantJointToolbox-master/model/nonlinear/coulomb_asym.m | 3,169 | utf_8 | 300c0bffa88226385ab92f0ee4556a5d | %COULOMB_ASYM Calculate asymetric Coulomb friction torques
%
% [ tau, y ] = coulomb_asym(jointObj, x)
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
%
% Inputs::
% x: state vector depending on the model type as
% x = [q_m; q_g; q_l; q_m_dot; q_g_dot, q_l_dot'];... |
github | geez0x1/CompliantJointToolbox-master | no_nonlinear_dynamics.m | .m | CompliantJointToolbox-master/model/nonlinear/no_nonlinear_dynamics.m | 1,931 | utf_8 | 821046d6f791f0961c05915667449215 | %NONONLINEARYDNAMICS Function that returns empty tau and y of appropriate
%size, used for when a model has no nonlinear dynamics
%
% [ tau, y ] = no_nonlinear_dynamics(jointObj, x)
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
%
% Inputs::
% x: state vector depend... |
github | geez0x1/CompliantJointToolbox-master | viscous_asym.m | .m | CompliantJointToolbox-master/model/nonlinear/viscous_asym.m | 3,621 | utf_8 | cef29a60dc92ee9d7fb09600c84acc6a | %VISCOUS_ASYM Calculate asymetric viscous friction torques
%
% [ tau, y ] = viscous_asym(jointObj, x)
%
% jointObj is the instance of the joint class object for which this
% function has been called.
%
%
% Inputs::
% x: state vector depending on the model type as
% x = [q_m; q_g; q_l; q_m_dot; q_g_dot, q_l_dot'];... |
github | szokeb87/cs2005_pymc-master | sur.m | .m | cs2005_pymc-master/matlab_files_from_cogley/sur.m | 1,433 | utf_8 | 973f975e039694903c9b88488d166fc2 | % sur.m
function [theta,Vtheta,Vu] = sur(Y,X,T);
% function [theta,Vtheta,Vu] = sur(Y,X,T);
% offline 2-step SUR
% Y is a N by T matrix, with the row indicating equations, and column
% indicating time periods, i.e, column j is the observation of Y
% at time j.
% X is a tensor object, with dimension(K_... |
github | szokeb87/cs2005_pymc-master | xmat.m | .m | cs2005_pymc-master/matlab_files_from_cogley/xmat.m | 873 | utf_8 | 67199c00623a8ada4299f354cae3dbb0 | % xmat.m
% construct the (K1 +k2 +...kn) by N by T matrix X called by
% function file recadp.m
function [X] = xmat(X1,X2,X3)
% Xi is the ki by T matrix of the RHS used in equation i. K1 is the
% number of RHS varaibles, T denotes time periods
% We have to adjust X!, X2, X3 manually for different cases.
... |
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