sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
1780160cca6916aba3c0fec8b6c64c3e049926e9e5604cc084b2e3455c7970c4 | MATLAB | 4,671 | 111 | function out = Pyramid_astro_threshold_Is_impulse
out{1} = @init;
out{2} = @fun_eval;
out{3} = [];
out{4} = [];
out{5} = [];
out{6} = [];
out{7} = [];
out{8} = [];
out{9} = [];
out{10}= @Iast;
out{11}= @ip_fback;
% --------------------------------------------------------------------------
function dydt = fun_eval(t,km... |
d2d6c609b87db5488480c5e98ffa6056899556febd6e10e0079a8b6cd95d58bb | MATLAB | 4,674 | 131 | function MBmodel = optimiseMBparams_homeostaticExcitation(MBmodel, PNactivity)
%% this is the "blue model"
DEBUG = true;
sigmoid_factor = 1.;
Sigmoid_derivative = @(x) exp(-x./sigmoid_factor)./((1.+exp(-x./sigmoid_factor)).^2) ;
Sigmoid = @(x) 1./(1.+exp(-x./sigmoid_factor)) ;
n = MBmodel.nKCs;
m = MBmodel.nPNs;
the... |
f99815d1e1dd58deb2ad34545fe447a10dc760c38ff7a8262aec46b565c1985f | MATLAB | 4,688 | 119 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% dictionary_learn_script.m
% This scrips it an example script for basic sparse dictionary learning
% based on the Olshausen and Field, 1997 paper 'Sparse Coding with... |
73bd9908c7a14b9c15e8f32c11ca4f777bab1a034c2a12b5ab90bca293421ba2 | MATLAB | 4,695 | 173 | function outpict = picdynamics(inpict,G,linetime,rangemode,mode)
% PICDYNAMICS(INPICT, {G}, {RANGEMODE}, {MODE})
% performs LTI system response simulation on the rows of INPICT
% used with imblend() to effect analog crt drive defect emulation
%
% INPICT is a single-frame image of any standard image clas... |
de8e32e25b644691876c044755c6bdaf6d912b00dc5f6f98dc9f1dea7f4d8444 | MATLAB | 4,695 | 96 | %% LME analysis for first two bins
cd D:\ES_data_Hannah\for_stats
temp = dir('*'); % assuming 3 directories
for i=1:length(temp)
if temp(i).isdir == 1 & length(temp(i).name) > 3
cd(temp(i).name)
load for_stats.mat
load for_stats_expquarter.mat
load for_stats_subject.mat
... |
083547fb035931206aa20a4754f1556563357e2117f37f9d11a319a8e5268e78 | MATLAB | 4,697 | 133 | function[stats] = simple_Wilcoxon_test_analysis(save_path,grouping_variable,group_names,dependent_variable,y_label,fig_title,fig_name)
fontsize_text = 16;
fontsize_title = 20;
order_v = {char(group_names(1)),char(group_names(2))};
grouping_variable = categorical(table2array(grouping_variable),order_v);
depen... |
7552ab5a22f1d6dd4795e8ef5db5b48d0b4ae298d028e4b9f4a217aa1f7ccf15 | MATLAB | 4,702 | 154 | function [outnii, outFile] = add_qform(dataIn, outFile, force_flag)
% Adds qform (Quaternion) parameters to nifti header. The parameters are defined to match sform
% matrix. This function is intended to be used with NIFTI1 files/structs with NIFTI1_XFORM_CODE set
% to NIFTI_XFORM_SCANNER_ANAT (sform_code = 1; qform_cod... |
d4b163fc45f312844980a68b5c1f16d7281bea82af3e3641df536531931f5054 | MATLAB | 4,707 | 102 | function [S,t,f,Serr]=mtspecgramc(data,movingwin,params)
% Multi-taper time-frequency spectrum - continuous process
%
% Usage:
% [S,t,f,Serr]=mtspecgramc(data,movingwin,params)
% Input:
% Note units have to be consistent. Thus, if movingwin is in seconds, Fs
% has to be in Hz. see chronux.m for more information.
% ... |
b3ad4796297324fd0dbb4c1b9f24f0bec65fb3444e3c6e9f1497380bc6902e20 | MATLAB | 4,711 | 140 | function outpict = addborder(inpict,width,varargin)
% ADDBORDER(INPICT, {WIDTH}, {COLOR}, {KEYS})
% ADDBORDER(INPICT, {WIDTH}, {EDGETYPE})
% Add a colored border to an image. I find that the syntax and flexibility
% makes addborder far more convenient than PADARRAY.
%
% INPICT is an I/IA/RGB/RGBA/R... |
34cdc4ea2597aedf3de9776ab88fdae2767d73c959234a9c3841d6f031eccfb3 | MATLAB | 4,717 | 85 | function wrong_markers = verifymarkers(cfg, MuseStruct)
% Use as :
% wrong_markers = verifymarkers(cfg, MuseStruct)
%
% verifymarkers check the marker list for the 2 kinds of Muse markers :
% - for "one-off" markers, it verifies that there are no __START__ markers
% associated
% - for start/end markers, it ... |
596661b56b25506bac9c2b88c0db6378b4a6c7a740281559e2a11d0f3e7bf839 | MATLAB | 4,724 | 129 | function result=psignifitCore(data,options)
% this is the Core processing of psignifit, call the frontend psignifit!
%function result=psignifitCore(data,options)
% Data nx3 matrix with values [x, percCorrect, NTrials]
%
% sigmoid should be a handle to a function, which accepts
% X,parameters as inputs and gives back a ... |
1b35f05320757793843f20d5e5f143beb95fb86dbf6c48c106e95e3bcc553297 | MATLAB | 4,738 | 93 | function data=rmlinesc(data,params,p,plt,f0)
% removes significant sine waves from data (continuous data).
%
% Usage: data=rmlinesc(data,params,p,plt,f0)
%
% Inputs:
% Note that units of Fs, fpass have to be consistent.
% data (data in [N,C] i.e. time x channels/trials or a single vector) - required.
% ... |
183f6d0aca9ff3ec72e3219e6ef1ff29602540d0598885a3ac1b643a2be3db4b | MATLAB | 4,744 | 137 | function [FFT] = FFTtrials(cfg, force, LFP)
%
% Use as :
% [FFT] = FFTtrials(cfg, force, LFP)
%
% The LFP argument is optional. If LFP is not in the input, then it is
% loaded with the function readLFP.m.
%
% This file is part of EpiCode, see
% http://www.github.com/stephenwhitmarsh/EpiCode for documentation... |
b3fce2ebfabbea2c3b09cce322cd6420d8a3bb8c3f8d09899a81d1d1183226bf | MATLAB | 4,764 | 148 | classdef OpenExLive < handle
%OpenExLive TDT online data streamer.
% obj = OpenExLive() connects to TTank server and opens currently
% recording block in Workbench
%
% obj.data reference to all available data from block
% obj.update get latest data from current block
% obj.TT ... |
2c9568e55b607b76364f5ea4af8409b5f4684309c0be5083d316fd577231cb48 | MATLAB | 4,769 | 90 | function [ColorPalette] = ColorScheme(num)
%% Color Scheme
% Liz's Color Palette
% Purple: 8338EC [131, 56, 236]
% Yellow: FFBE0B [255, 190, 11]
% Orange: FB5607 [251, 86, 7]
% Magenta: FF006E [255, 0, 110]
% Pink: FF9DA4 [255, 157, 164]
% Electric purple: F700FF [247, 0, 255]
% Blue: 0080FF [0, 128, 255]... |
7ef711463282ff8b41e6687dbe277ef679200ffd95c3b415f885bacc97a2dd47 | MATLAB | 4,769 | 130 | function sub_fold = CBIG_cross_validation_data_split( subject_list, family_csv, ...
subject_header, family_header, num_folds, seed, outdir, delimiter )
% sub_fold = CBIG_cross_validation_data_split( subject_list, family_csv, ...
% subject_header, family_header, num_folds, seed, outdir, delimiter )
%
% This fu... |
61babfc32850e08bc02de1bc48c79e74dc992b01e2bc6d51c85a1a0d3a12febf | MATLAB | 4,771 | 157 | %% TIFFSAVE() Saves a TIFF stack.
%
% Usage:
% tiffsave(outputPath, image, tags)
%
% tags should be a struct; if it has more than one item, the first one will
% be used as a template.
%
function tiffsave(outputPath, image, varargin)
% Parse optional arguments
iArg = 1;
if ~is... |
7669dbf1614f99a2c13fc06f6535afc917e54e966e499a3c1f7f1025df0924a0 | MATLAB | 4,775 | 124 | function [vertices, faces] = fs_read_surf(fname)
% freesurfer_read_surf - FreeSurfer I/O function to read a surface file
%
% !!! Modified by D. S. Schwarzkopf (15/09/2012) - removed output messages !!!
%
% [vertices, faces] = freesurfer_read_surf(fname)
%
% Reads the vertex coordinates (mm) and face lists from... |
3aa4b75802bb723441eeb05a0102986817657aaaaac9b5b9fbeadc4e417791e3 | MATLAB | 4,776 | 161 | function mpict = linedither(inpict,varargin)
% LINEDITHER(INPICT, {OPTIONS})
% Quirky multilevel dither consisting of variable density line segments
% As the purpose of this function is image degradation, accuracy is moot.
%
% INPICT is a 2-D intensity image. RGB images will be converted to grayscale.
... |
a9afa3ab756a170527f2c2f8329fde3e190acad82af9ff0f1b79a8a0c1764a0d | MATLAB | 4,789 | 104 | function [S,t,f,R,Serr]=mtspecgrampb(data,movingwin,params,fscorr)
% Multi-taper time-frequency spectrum - binned point process
%
% Usage:
%
% [S,t,f,R,Serr]=mtspecgrampb(data,movingwin,params,fscorr)
% Input:
% data (in form samples x channels/trials or single vector) -- required
% movingwin ... |
82e73b87cff78558c922d5df2caaa6f39b719d47e4b775c6083310001fdf3a21 | MATLAB | 4,795 | 152 | function [S] = mt_dtft_gram(lfps, fs, time_window, time_step, freq, TW, n_tapers)
% MULTI-TAPER DISCRETE-TIME-FOURIER-TRANSFORM SPECTROGRAM:
% Compute a time-frequency plot using a DTFT with a multipaer method.
%
% Input:
% lfps = lfp signals (trials x samples)
% fs = lfp sampling rate (kHz).
% ti... |
5a083cd3efb8d823a068e0478c0a923c049e810b6a688c971af4e504c8848ed6 | MATLAB | 4,805 | 186 | function outpict = randlines(size,dim,varargin)
% RANDLINES(SIZE, DIM, {OPTIONS})
% generates image fields of random lines of various type
%
% SIZE is a 2-element vector specifying the output image dimensions
% DIM specifies the line orientation
% 1 produces vertical stripes
% 2 produces horizont... |
133c59ecb7d4ea4fbce345661680a48fd4de9534117f6cf65fa4ab31c0bdd33e | MATLAB | 4,807 | 101 | function [datafit,Amps,freqs,Fval,sig]=fitlinesc(data,params,p,plt,f0)
% fits significant sine waves to data (continuous data).
%
% Usage: [datafit,Amps,freqs,Fval,sig]=fitlinesc(data,params,p,plt,f0)
%
% Inputs:
% Note that units of Fs, fpass have to be consistent.
% data (data in [N,C] i.e. time x cha... |
92d28d38a3c664e0f5e73eadcddfe2594d628ab8a7f4d4bc5d65a8d22fc3692d | MATLAB | 4,815 | 123 | function phasePairLFP(suffix)
% Phase Pair LFP:
% LFP-LFP Pairwise Phase Consistency
%
% Read parameters
Params = read_params(suffix);
freq = Params.freq_start_1 : Params.freq_step_1 : Params.freq_end_1;
time_window = Params.time_1;
time_step = time_window / 4;
TW = Params.freq_star... |
9327c4b513d0f8524bd6fcf04ede0c463324d123909990b97da2976c2a4a084a | MATLAB | 4,816 | 145 | function [O_new,Spacing]=refine_grid(O_trans,Spacing,sizeI)
% Refine image transformation grid of 1D b-splines with use of spliting matrix
%
% Msplit=(1/8)*[4 4 0 0;
% 1 6 1 0;
% 0 4 4 0;
% 0 1 6 1;
% 0 0 4 4];
%
% [O_new,Spacing] = r... |
c50887d5e43ab19a50a91f3b9da295663f0daaa19b2e2f923ddddee836d506dd | MATLAB | 4,820 | 156 | function [outpict T] = histeqtool(inpict,mode,varargin)
% OUTPICT = HISTEQTOOL(INPICT,MODE,{EXTRAARGS})
% [OUTPICT TF] = HISTEQTOOL(INPICT,MODE,{EXTRAARGS})
% Simple wrapper tool for histeqFB() and adapthisteqFB() for simplified use
% on both I and RGB images. This makes it simpler to apply these tools to
% ... |
6de5ddc7be7a684128c42b1c0caae10c959698ea783554a6225c298804b37260 | MATLAB | 4,821 | 115 | function kernel = CBIG_crossvalid_kernel_with_scale(data_KbyS1, data_KbyS2, index_S1, index_S2, type, scale)
% kernel = CBIG_crossvalid_kernel_with_scale(data_KbyS1, data_KbyS2, index_S1, index_S2, type, scale)
%
% This function calculates the kernel matrix between subjects from two sets
% (e.g. training set and tes... |
cc8b112c932954db60ef26fd2843f04e15a5f1117caf7d4b9fbf8a3a1e0d0408 | MATLAB | 4,821 | 104 | function [S,t,f,R,Serr]=mtspecgrampt(data,movingwin,params,fscorr)
% Multi-taper time-frequency spectrum - point process times
%
% Usage:
%
% [S,t,f,R,Serr]=mtspecgrampt(data,movingwin,params,fscorr)
% Input:
% data (structure array of spike times with dimension channels/trials;
% also ... |
a4c61e75b2deb9988f7a2dd266441ca753b539807a19dffebcdbda7aeaf8c0bf | MATLAB | 4,822 | 94 | function Handle=getSigmoidHandle(options)
% creates a function handle to a specific sigmoid
%function Handle=getSigmoidHandle(options)
% This function creates a function handle to the sigmoid specified by its
% name in options.sigmoidName.
% Additional parameter is the options.widthalpha which specifies the
% scaling ... |
7c6358bb0120f92293eaaacf9ee8b26aa8f413a07d40186293bb11375ef63d65 | MATLAB | 4,830 | 137 | function nt_idx_disp(name,field,explainflag)
%nt_idx_disp(name,field,explainflag) - display contents of index file
%
% name: name of file
% field: field to display in detail
% explainflag: if true, explain contents of each field
%
% NoiseTools
nt_greetings;
if nargin<1; name=pwd; end
if nargin<2; field=[]; end
if n... |
8a8c0018b15462d8c8a6d5283fc29df29be385524b6dc50a6fbd872d71f00332 | MATLAB | 4,834 | 135 | function[OPS_dataset_pos] = format_OPS_results(settings,pos_idx,phase)
% [OPS_dataset_pos] = format_OPS_results(settings,pos_idx,phase)
% Summarises OPS results in a table
%
% inputs:
% settings - Analysis and experimental settings
% pos_idx - Position number to analyse
% phase - 'test' or 'training'
%
% out... |
c203d9012baafdb1beeeaf6c2c76e8f8310b6fac8b7259fffbaa22f169b18636 | MATLAB | 4,834 | 134 | function [TFR] = TFRtrials(cfg, force, Trialdata)
% This file is part of EpiCode, see
% http://www.github.com/stephenwhitmarsh/EpiCode for documentation and details.
%
% EpiCode is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the... |
4c165c18ab9d7702653100b922120328b11242e2ef0b05c53f3a71474c0b396f | MATLAB | 4,836 | 139 | function [confC,phistd,Cerr]=coherr(C,J1,J2,err,trialave,numsp1,numsp2)
% Function to compute lower and upper confidence intervals on the coherency
% given the tapered fourier transforms, errchk, trialave.
%
% Usage: [confC,phistd,Cerr]=coherr(C,J1,J2,err,trialave,numsp1,numsp2)
% Inputs:
% C - coherence
% J1,J2 -... |
0fbf9bc79d82a75ea155c804903da9b0403ec97b498a58e01ca1e48f6b784d10 | MATLAB | 4,855 | 170 | %% Zoom into the specified region of a given axes
% focus()
% focus(precision)
% focus([min, max], [axis = 'x'])
% focus([xMin, xMax], [yMin, yMax])
% focus(handle, ...)
%
function [varargout] = focus(varargin)
%----- Default values
handles = [];
precision = 2;
%----- ... |
00d025bcb50c3ef265defdaffe1c2ced90cb8f03333d154c8abf51099c3a3baf | MATLAB | 4,859 | 103 | function [sens, regu, noise_cov] = morse_estimate_sensitivities(ref, PAD, PPIparams)
%**************************************************************************
%
% morse_estimate_sensitivities
% input ref: data for sensitivity estimation post apodisation
% [RO, PE1, PE2, N_coils]
% ... |
da5d999bb3e459ccef532350662c6c6814e5bf36ca257d571632be9c38fd5943 | MATLAB | 4,878 | 135 | % SVReg: Surface-Constrained Volumetric Registration
% Copyright (C) 2019 The Regents of the University of California and the University of Southern California
% Created by Anand A. Joshi, Chitresh Bhushan, David W. Shattuck, Richard M. Leahy
%
% This program is free software; you can redistribute it and/or
% modi... |
bb7373a7aa77ee4f744b5a7fbe923b2fe082d0e0ce486dd560268533cad598b4 | MATLAB | 4,907 | 113 | function [ancova_models,indx_all] = generate_ancova_spectral_data(EEG_integrals_am,EEG_integrals_nam, participant, indx_all, ancova_models, options)
%% Creates a placeholder cell with the datasets of all participants for plotting of results
%
% **Usage:** [all_data,indx] = generate_spectral_data(EEG_integrals_am,EEG_in... |
4b81f8c43e5fb9773c2837c3b8417259ee9fd24e503b93c38581da28a5b8829a | MATLAB | 4,922 | 124 | function [newPhi, newVarBound] = ...
CBIG_AuthorTopic_ComputeVariationalTerm__N_tc(params, newPhi, ...
newVarBound, varBoundFlag)
% [newPhi, newVarBound] = ...
% CBIG_AuthorTopic_ComputeVariationalTerm__N_tc(params, newPhi, ...
% newVarBound, varBoundFlag)
%
% Compute the expectation and variance of the count N_{.t... |
005c45549bc9a679f656f3162a094d335cafdb0020157f789581cbcd1ce1bc9a | MATLAB | 4,923 | 88 |
%% Setting parameters
function [config] = seg_setparams(config)
if ismac
error('Platform not supported')
elseif isunix
rootpath_analysis = '/network/lustre/iss01/charpier/analyses/stephen.whitmarsh';
rootpath_data = '/network/lustre/iss01/epimicro/patients/raw';
os = 'unix'; ... |
ec13c516f1c41f5aee0e899f5918f00d13febf6c1df5b0cb727cb60988cfc02a | MATLAB | 4,923 | 136 | function MBmodel = optimiseMBparams_homeostaticThreshold(MBmodel, PNactivity)
%% this is the "magenta model"
DEBUG = true;
% sigmoid_factor = -0.9;
% Sigmoid_derivative = @(x) exp(-sigmoid_factor.*x)./((1.+exp(-sigmoid_factor.*x)).^2) ;
% Sigmoid = @(x) 1./(1.+exp(-sigmoid_factor.*x)) ;
sigmoid_factor = 1.;
Sigmoid_der... |
47a30d282803e1c809e06060ae4c9ede4b9b26afc1d84844578288547e013bf0 | MATLAB | 4,924 | 153 | function A = catstruct(varargin)
% CATSTRUCT Concatenate or merge structures with different fieldnames
% X = CATSTRUCT(S1,S2,S3,...) merges the structures S1, S2, S3 ...
% into one new structure X. X contains all fields present in the various
% structures. An example:
%
% A.name = 'Me' ;
% B.income = 99... |
4b161d10931bba79415504666effffb94d1d2269a9ea8f3433a141b0c3d20aeb | MATLAB | 4,944 | 122 | function [y_resid_perfold] = CBIG_crossvalid_regress_covariates_from_y( ...
y_in, regressors, sub_fold, outdir, outstem)
% [y_resid_perfold] = CBIG_crossvalid_regress_covariates_from_y( ...
% y_in, regressors, sub_fold, outdir, outstem)
%
% This function regress the "regressors" from the target variables "y_i... |
5247449348ea8c8f2149063195661a3e20391fd87a38b74edf255330b19811fe | MATLAB | 4,952 | 134 | function data = TDTdigitalfilter(data, STREAM, FC, varargin)
%TDTDIGITALFILTER applies a digital filter to continuous data
% data = TDTdigitalfilter(DATA, STREAM, FC, 'parameter', 'value', ... ),
% where DATA is the output of TDTbin2mat, STREAM is the name of the
% stream store to filter, FC is the cutoff freque... |
004c8028a4769ad73ca5e564734c5a2037f48820e542de3a90023c3fe784fc10 | MATLAB | 4,958 | 147 | function [trajectory, trials] = cpm_td_learning(freeparams, fixedparams, data)
% Simulation configs, file for handling of paths to toolboxes.
% ---------------------------------------------------------------------
% Copyright (C) 2023 Simon R. Steinkamp, Iyadh Chaker
% This program is free software: you... |
ae0cac2040604311f1b6d8a9def4690151f45ab0be9261389ee762febb6e36ed | MATLAB | 4,962 | 133 | function [y] = CBIG_read_y_from_csv( csv_files, subject_header, y_names, y_types, subject_list, outname, delimiter )
% [y] = CBIG_read_y_from_csv( csv_files, subject_header, y_names, y_types, subject_list, outname, delimiter )
%
% This function reads y (i.e. the target variables to predict, e.g.
% behaviors, disease ... |
f63a040abc01651d2b322a68710c737286def186d021ae2f5580b6c3bfbb608b | MATLAB | 4,979 | 154 | function S07_layer_x_cross_validation(subject, game, DQN, reg_parameter)
root_path = 'YOUR_DATA_PATH';
main_dir = strcat(subject, '/', game) ;
sess_no = 5;
GLM_name = 'GLMs_Layer_x';
lambda_seq = reg_parameter;
load(strcat(root_path, main_dir, '/GLMs/GLM_empty/SPM.mat'));
beta_template_nii = load_nii(strcat(root_... |
090b8809e66332539b486e76543fab324fc18acd810ce401578024fb879aad73 | MATLAB | 4,983 | 219 | function outpict = displace(inpict,amount,varargin)
% DISPLACE(INPICT, AMOUNT, {OPTIONS})
% Apply pixel displacement map(s)
%
% INPICT is an I/RGB image of any standard image class
% AMOUNT is a 2-element vector specifying maximal displacements
% for X and Y directions ([maxx maxy])
% OPTIONS are ke... |
a8a800d920f0b9db536ecb8557973b2edf5ed33c5d48337d056cec9a2075ff92 | MATLAB | 5,018 | 96 |
%% Euclidian distance for hierarchical clustering
% eucD = pdist(LFP_concatinated_z,'seuclidean');
% eucD = pdist(shifted_clean_z,@naneucdist); % method to allow nans
%
% [Y,stress,disparities] = mdscale(eucD,3,'Criterion','sstress');
... |
fe7e978f2c4dee825c131648b2c80b6b1d15d31508c012da966997e522dab086 | MATLAB | 5,018 | 171 | %
% BDP BrainSuite Diffusion Pipeline
%
% Copyright (C) 2019 The Regents of the University of California and
% the University of Southern California
%
% Created by Chitresh Bhushan, Divya Varadarajan, Justin P. Haldar, Anand A. Joshi,
% David W. Shattuck, and Richard M. Leahy
%
% This program is free sof... |
8cc47aaa394a82b4b0df66938d51fdfc5c314d52bf75d32e0b70eef114d60d25 | MATLAB | 5,019 | 160 | function outpict = morphops(inpict,se,mode)
% OUTPICT=MORPHOPS(INPICT,SE,MODE)
% Perform the selected morphological operation on an image.
%
% This is a passthrough to the IPT functions imdilate(), imerode(), imopen(), imclose(),
% imtophat(), and imbothat(), with internal fallback implementations to help r... |
98b02ec0a7bb0730f95333a941daefbefbc36035dbb58174ddedd8fa662242cc | MATLAB | 5,036 | 161 | function Srf = spm_prf_import_surface(glm_dir, struct_img, surf_dir, hemi)
% Imports Freesurfer surfaces to Matlab (SamSrf format)
%
% glm_dir - directory containing SPM.mat
% struct_img - filename of the subject's structural MRI
% surf_dir - directory containing Freesurfer surfaces
% hemi - ... |
4943346ad9fdab0c58aa15734b62e4c24c74370594811d60e92c6170075dee85 | MATLAB | 5,037 | 114 | function [micromed_markers, stim_micro_aligned] = alignstimdata(cfg,varargin)
if nargin > 0
if nargin > 1
micromed_markers = varargin{1};
markerdat_micro = varargin{2};
end
else
fprintf('Not enough input arguments!');
end
fname_output = fullfile(cfg.datasavedir,'aligned_stim_marke... |
dc5167eb9c41375d24ae9a2e43012556b72d19958f5f93338dd8980fb9405a1a | MATLAB | 5,052 | 150 | % This script provides a synthetic max-statistics example for the optimized
% C++ MEX implementation of continuous/continuous mutual information.
%
% The direct native entrypoint is:
% I = info_cc_slice_cpp(X, Xdim, Y, Ntrl, Nthread)
%
% This script uses cell mode - cells are delimited by %% lines and can
% be run wi... |
4ffcbc5adadb642d2f417f9e376e53a08b14451d9bd973572e53ff15cc0af176 | MATLAB | 5,072 | 169 | clear
close
%% SETTING
run('./../init.m')
hls = Pyramid_only;
f = hls{2};
OPTIONS = odeset('RelTol',1e-6);
dt = 0.01;
transient = 3000; % transient period
T = 3300; % total timespan length
t = 0:dt:T;
IC = [-60,-60,0.5,0.9,0.001,0.01,0.06,0.01]; % initial conditions
%% GRID
% Load fold curve
PATH = './..... |
9298753870c2bbbbda4d4d61de14c4eada158e43d23d3b432fc7402e17b70ccf | MATLAB | 5,074 | 193 | function y=nt_mfilt(x,M,B,A,expand)
%y=nt_mfilt(x,M,B,A,expand) - multichannel filter
%
% y: filtered data
%
% x: data to filter (time X channel)
% M: multichannel impulse response (ichannel X ochannel X lag)
% B, A: bank of filters
% expand: if true output 3D matrix, one band per page (else add)
%
% Output is ... |
2deacd1f85455b982d0fa4fa4ab1cadab323786e71a7ff738fe7f3da1756787b | MATLAB | 5,086 | 207 | % Load NIFTI header extension after its header is loaded using load_nii_hdr.
%
% Usage: ext = load_nii_ext(filename)
%
% filename - NIFTI file name.
%
% Returned values:
%
% ext - Structure of NIFTI header extension, which includes num_ext,
% and all the extended header sections in the header extension.
% ... |
6b8019ad1ec1945ff478fbaeb20998b4e9e5f1230114f32d3449d59352bce2d3 | MATLAB | 5,088 | 147 | function varargout = imcropFB(varargin)
% OUTPICT=IMCROPFB(INPICT,RECT)
% OUTPICT=IMCROPFB(X,Y,INPICT,RECT)
% Crop an image array.
%
% This is a passthrough to the IPT function imcrop(), with an internal
% fallback implementation to help remove the dependency of MIMT tools on the
% Image Processing Toolbo... |
f78d02bea2222709f229ad258c6d04b6be71c386cde99151a90af0e028fae147 | MATLAB | 5,098 | 164 | function [p,h,p_3d,h_3d,lme] = stats_SAP(results_folder, results_to_plot, biom_1, biom_2, biom_set_folder,name, coloc)
alldata = 0;
shapiro = 0; % to check for normality and deide on the test accordingly
mixed_effects = 1;
rem_outliers = 1;
tech_rep = 0;
AB =1;
nonparam = 0; % to impose non parametric test
t_test = ... |
15f8db072afc2068623172bcf1fd7673f926ad6deba804674e7dcc54536cc082 | MATLAB | 5,099 | 143 | function CBIG_compute_multiKRR_PFM(feature_file, multiKRR_dir, sub_fold_file, score_ind, outstem, outdir)
% CBIG_compute_multiKRR_PFM(feature_file, multiKRR_dir, sub_fold_file, score_ind, outstem, outdir)
%
% This function computes the predictive network features of multi-kernel
% ridge regression (under <CBIG_CODE_DI... |
4e117476627e7f49bfe8dd16bd8135a92b532cbbd77f4761fd28eef503aa04d8 | MATLAB | 5,100 | 87 | %% change dir %%
cd ~/Projects/pacman/behavioral_analyses/matlab_helpers
%% BJH021 table
bjh21 = load('~/Projects/knight_server/remote/WashU/data/_VERA/VERA_BJH021/BJH021_MNI_brain.mat')
bjh21_table = table(repmat({'BJH021'}, length(bjh21.electrodeNames), 1), bjh21.electrodeNames, bjh21.tala.electrodes(:,1), bjh21.ta... |
b54024b2d2bd25d7a40a1998aed90d57cfa7c9e1466cf8c54a6aa2999b5dc893 | MATLAB | 5,109 | 160 | %% FP_Part1.m
%
% Fiber Photometry Analysis - Part 1
%
% It is recommended that users read through the documentation in full
% prior to using this analysis. This applies to each section in the code
%
% All outputs are accessed through the structure element "FP" in the
% MATLAB ... |
41242cdb1347d2aea0439d1a49b81fc958febf35fc813c8aad96097aa19491a7 | MATLAB | 5,122 | 125 | function [psth trialspx] = mpsth(spxtimes,trigtimes,varargin)
% [psth trialspx] = mpsth(spxtimes,trigtimes,varargin)
% function generates a peri-stimulus time histogram (psth) with time base in column 1 and histogram in column 2
% in addition, function returns spike timestamps relative to trigger times
% IMPORTANT: all... |
5a7ee473830b874ac438f3ced80ddc231faa2908c790385661995c2327e8c38d | MATLAB | 5,123 | 152 | function G = G_matrices_3D(kCal, N1, N2, N3, tau, U, varargin)
% Function that calculates the G(x) matrices directly without calculating
% H(x) first.
%
% Input parameters:
% --kCal: N1_cal x N2_cal x N3_cal x Nc block of calibration data,
% where N1_cal, N2_cal, and N3_cal are the dimensio... |
7c62a2fa350bc2d8a0d917c82cfbc65ed6118915b3814c8682d5bac66e83e371 | MATLAB | 5,130 | 98 |
% done for rodents 1 to 7
% writemusemarkerfiles do not work for brainvision data (because there is an other format of Muse marker file (.vmrk))
% config = dtx_setparams_probe_spikes;
config = wod_setparams;
pat_list = 4:length(config);
torename = {};%{'Baseline_Start', 'Analysis_Start'}; %{old1, new1; old2, new2;... |
483e8c27924e7b70355b96a0ea078ac08055b3e846eab0f75596b1c3c0eb4cf0 | MATLAB | 5,136 | 146 | function varargout=wt(d,varargin)
%% Continous Wavelet Transform
% Creates a figure of wavelet power in units of
% normalized variance.
%
% USAGE: [wave,period,scale,coi,sig95]=wt(d[,params])
%
% d: a time series
% wave: the wavelet transform of d
% period: a vector of "Fourier" periods associated with wave
% scale: a ... |
6f8c5f5e81aee3e665d6099d8a5f6f2df2b3070bd39ae7a9e56c8e0114de155d | MATLAB | 5,143 | 143 | % Pipeline to analyse OPS data %%
% Author: Maria Garcia - 31/05/2024 (V1)
clear all
close all
settings.experiment = "TI_AD-Hipp2"; % Either "TI_AD-Hipp2" or "pilot"
%% Define steps to run
%%%%%%% Test steps %%%%%%%
detect_object = 1;
analyse_OPS_data = 1;
format_OPS_data = 1;
get_OPS_graphs = 1;
%%%... |
89241eecc35672c809b9805790c324f2c479ff8b2a8d0738f2850cbf05d4852a | MATLAB | 5,146 | 205 | function [fft_data,varargout] = TDTfft(data, channel, varargin)
%TDTFFT performs a frequency analysis of the data stream
% [fft_data, fft_freq] = TDTfft(DATA, CHANNEL), where DATA is a stream
% from the output of TDT2mat and CHANNEL is an integer.
%
% fft_data contains power spectrum array
% fft_freq co... |
faed1b8f65cd90af815a22d4610d77ea865eb4cecb1c194e0e7eb9f8b1677999 | MATLAB | 5,149 | 157 | function [results_col] = compute_colocalisation(mask_1, mask_2, biom_1, biom_2,fname, repeat, results_folder)
close_figs = 1;
coloc_per_cell = 1;
count_coloc = 0;
%% Load image
% fpath = fullfile(files(idx).folder, files(idx).name);
% biom_ch_1 = find_channel_img(biom_1);
% % [img_1] = load_channel_images(fpath, biom... |
cb0283481b2cd807a5e738cad7e5d13fbcfbf72d852ce605c712579f22bc44d7 | MATLAB | 5,157 | 141 | function [vol1_new, vol2_new, X_grid, Y_grid, Z_grid, res, G_new] = reslice_vol_same_grid(v1, v2, res, method, outFile1, outFile2, gz)
% Reslice/Resamples v1 and v2 on the same grid point. (v1, v2 should be registered together)
% v1, v2 - nii structure or nifti file
% res - resolution in mm of target output image
% ... |
71d5ed8ff7a48d180bfe18b6123b8d4b6865f1dacbbb37090d78d1fa404dbc2b | MATLAB | 5,159 | 175 | function kbboxplot(paramArray, varargin)
% KBBOXPLOT - Draws multiple stylized boxplots with explicitly defined parameters,
% mimicking the style of MATLAB's boxchart.
%
% Inputs:
% paramArray - struct array, each with fields:
% bottomWhisker, bottomBox, bottomNotch, median,
% topNotch, topBox... |
6910d6c6b8e9dce44327cf86745d3091bf2dfb86a42e28f18b96faab897cc41d | MATLAB | 5,166 | 196 | function varargout=shadedErrorBar(x,y,errBar,varargin)
% generate continuous error bar area around a line plot
%
% function H=shadedErrorBar(x,y,errBar, ...)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
%
% Inputs (required)
% x - vec... |
c29ec0e191b14dd1f5f0f75d22836f81cf9c2f92912f66d4113cbdbd68dd4540 | MATLAB | 5,186 | 130 | %
% BDP BrainSuite Diffusion Pipeline
%
% Copyright (C) 2019 The Regents of the University of California and
% the University of Southern California
%
% Created by Chitresh Bhushan, Divya Varadarajan, Justin P. Haldar, Anand A. Joshi,
% David W. Shattuck, and Richard M. Leahy
%
% This program is free sof... |
f4a05c0b7a5769be2563d3fe0db95fda120ed02fb716ff71c064008f75bbf164 | MATLAB | 5,207 | 132 | function [newPhi, newVarBound] = ...
CBIG_AuthorTopic_ComputeVariationalTerm__N_cv(params, newPhi, ...
newVarBound, varBoundFlag)
% [newPhi, newVarBound] = ...
% CBIG_AuthorTopic_ComputeVariationalTerm__N_cv(params, newPhi, ...
% newVarBound, varBoundFlag)
%
% Compute the expectation and variance of the count
%... |
15e76df546d5d83e5d92dd8778b0c6b61fa4e6462d64f9b618b961a6620e456e | MATLAB | 5,216 | 120 | function [sdf kernel] = msdf(psth,ftype,w,varargin)
% [sdf kernel] = msdf(psth,ftype,w,varargin)
% make spike density function
% filters a psth generated from mpsth with a Gaussian or exponential kernel to yield an SDF
% note: bin size of psth should be 1 ms!
%
% MANDATORY ARGUMENTS
% psth 2-column vector with ti... |
c4f6b9abcf5ec192e66e7e8589b839326c1e96edfd9a893a6b22423165bc006f | MATLAB | 5,216 | 157 | function wtcsig=wtcsignif(mccount,ar1,dt,n,pad,dj,s0,j1,mother,cutoff)
% Wavelet Coherence Significance Calculation (Monte Carlo)
%
% wtcsig=wtcsignif(mccount,ar1,dt,n,pad,dj,s0,j1,mother,cutoff)
%
% mccount: number of time series generations in the monte carlo run (the greater the better)
% ar1: a vector containing th... |
0d815659580f13c74a98a9d4d094f7bae7d86d3023b6e49a2dd4dccf13508b15 | MATLAB | 5,226 | 113 | function [session, init_params] = preprocessingParams(session, clip, stc)
% Generate data structures of vistasoft parameters for preprocessing
%
% INPUTS
% 1) session: name of session to analyze (string)
% 2) clip: number of TRs to clip from beginnning of each run (int)
% 3) stc: flag controlling slice time correction ... |
34211f17eca4a44e9d2e21a8bcbf134887774c340c332f58e2467360ec799ddc | MATLAB | 5,226 | 151 | function outpict = rgb2husl(inpict,varargin)
% RGB2HUSL(INPICT,{MODE})
% converts an RGB input image to HUSL (human-friendly HSL), which is an adaptation
% of LCH with normalized chroma. This is particularly useful for tasks such as
% avoiding out-of-gamut values when rotating hue at high chroma. ... |
1c775bb9fb80965a7c50c1e5f6acd43db9d625a39150f585be22ba3a68f90a04 | MATLAB | 5,235 | 143 | function write_brainvision_eeg(filename, hdr, dat, event)
% WRITE_BRAINVISION_EEG exports continuous EEG data to a BrainVision *.eeg
% and corresponding *.vhdr file. The samples in the exported file are
% multiplexed and stored in ieee-le float32 format.
%
% Use as
% write_brainvision_eeg(filename, hdr, dat, evt)
%
... |
8c3e814f3b2df04a92feb72a9eb6c90104da77821d52f2ccd9b24e4a3ffc6aea | MATLAB | 5,235 | 91 | function [dat_micro] = readMicroFs(cfg,MuseStruct_micro)
fname = fullfile(cfg.datasavedir,['data_aligned_microFs_',cfg.label,'.mat']);
if exist(fname,'file') && cfg.force == false
fprintf('Loading precomputed data: %s \n',fname);
load(fname,'dat_micro');
else
trialcount = 1; % to have a continuo... |
67af5f3ed76790d85b70be09d9833ff55a4e0727f0e8ac2a0c562fd294cefc03 | MATLAB | 5,239 | 146 | function outpict = genknit(bgcolor,rowcolors,nloops,varargin)
% OUTPICT = GENKNIT(BGCOLOR,FGCOLOR,NLOOPS,{OPTIONS})
% A novelty function to generate images of interlocking (knit) curves.
% This was originally written to answer a forum question and really doesn't have
% much purpose beyond demonstrating compositing... |
bf93f5f7a3c26e58ec83b131fcdfcee1f65eaa4fd30c61fda6fe3f2cfc955855 | MATLAB | 5,240 | 97 | %% main script to identify cells that are tuned to heading-direction
% define folders
folders = strings(9,2);
rootdir = "G:\CA1 miniscope data\";
folders(:,1) = ["\M119\TrainingD11\" "\M120\TrainingD11\" "\M292\TrainingD6\" "\M319\TrainingD7\" "\M210\TrainingD17\" ...
"\M231\TrainingD9\" "\M314\Training_Sep... |
d6f4fa0a2cb72c31f58650b972fe9edf9e83115a5bfb8748e46797c40465c616 | MATLAB | 5,242 | 91 | function [dat_micro] = readMicroFs_spikes(cfg,MuseStruct_micro)
fname = fullfile(cfg.datasavedir,['data_aligned_microFs_',cfg.label,'.mat']);
if exist(fname,'file') && cfg.force == false
fprintf('Loading precomputed data: %s \n',fname);
load(fname,'dat_micro');
else
trialcount = 1; % to have a c... |
b88720e76aeb0ebc687a5f4793b32260c789fd158556da8a8165c0a5c36c8f24 | MATLAB | 5,245 | 142 | function [y,idx,w]=nt_tsr_nodemean(x,ref,shifts,wx,wref,keep,thresh)
%[y,idx,w]=nt_tsr_nodemean(x,ref,shifts,wx,wref,keep,thresh) - time-shift regression (TSPCA)
%
% y: denoised data
% idx: x(idx) is aligned with y
% w: weights applied by tsr
%
% x: data to denoise (time * channels * trials)
% ref: reference (ti... |
020c61e1dd12896236230e91ab890640df677e81a7b5d0499bbf7380f8e62d76 | MATLAB | 5,246 | 141 | %
% BDP BrainSuite Diffusion Pipeline
%
% Copyright (C) 2019 The Regents of the University of California and
% the University of Southern California
%
% Created by Chitresh Bhushan, Divya Varadarajan, Justin P. Haldar, Anand A. Joshi,
% David W. Shattuck, and Richard M. Leahy
%
% This program is free sof... |
0cc0b8f80a7c76dedfcdf5e21dd1f37c806f1aff62e875715270b690a0d33f43 | MATLAB | 5,246 | 177 | function y=nt_sparse_filter(x,T,A)
%y=nt_sparse_filter(x,T,A) - convolve multichannel data with sparse impulse response
%
% y: result
%
% x: data to convolve (columnwise)
% T: times of non-zero samples of IR (can be fractionnary)
% A: amplitude of non-zero samples of IR (default: all 1)
%
% T and A together describ... |
8aa92fe5b8edc7d14155a12ee7fbb8156885f0441d4bbb2542d8db8af2413063 | MATLAB | 5,247 | 80 | function [config] = hspike_setparams_temp
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% [config] = hspike_setparams
%
% This function outputs all the settings of a study, to be defined below
%
% Note the consideration of the operating system, because the pointers to
% the file server is... |
8c336c445c7769fb761f70cacdd78969b67c5d2d4db64c2d5c915f3368e66991 | MATLAB | 5,251 | 154 | function CBIG_AuthorTopic_PreprocessExpDataFromText(textDataPath, ...
dataDir, binarySmoothKernelRad)
% CBIG_AuthorTopic_PreprocessExpDataFromText(textDataPath, ...
% dataDir, binarySmoothKernelRad)
%
% Preprocess data of activation foci's locations in text form: write the
% activation foci into 3D brain images a... |
e9bbe7e06c86a70715a95713f1b42d83462126c0d7bc475a298604ed7cbb431a | MATLAB | 5,251 | 151 | function [dz,vdz,Adz]=two_group_test_spectrum(J1,J2,p,plt,f)
% function [dz,vdz,Adz]=two_group_test_spectrum(J1,J2,p,plt,f)
% Test the null hypothesis (H0) that data sets J1, J2 in
% two conditions c1,c2 have equal population spectrum
%
% Usage:
% [dz,vdz,Adz]=two_sample_test_spectrum(J1,J2,p)
%
% Inputs:
% J1 taper... |
3ebc43020ae923213f20b2bcdd2ef1135d63a4f9e91cf51cd7f457c165a38c49 | MATLAB | 5,256 | 155 | % This script provides a synthetic max-statistics example for the optimized
% C++ MEX implementation of continuous/discrete mutual information.
%
% The direct native entrypoint is:
% I = info_cd_slice_cpp(X, Xdim, Y, Ym, Ntrl, Nthread)
%
% This script uses cell mode - cells are delimited by %% lines and can
% be run ... |
0f4a120d1785cbc39ee69757018412c77d42778c4441a56f3fcc8a933f1f557f | MATLAB | 5,270 | 81 | %-----------------------------------------------------------------------
% Job saved on 10-Oct-2023 00:29:53 by cfg_util (rev $Rev: 7345 $)
% spm SPM - SPM12 (7771)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
load('tmp_workspace_correlate_varA_varB... |
20790cc2d778d074342060470a51c1c65d94412a33a922e988fc51da4c87a93f | MATLAB | 5,278 | 82 | %-----------------------------------------------------------------------
% Job saved on 10-Oct-2023 00:29:53 by cfg_util (rev $Rev: 7345 $)
% spm SPM - SPM12 (7771)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
load('tmp_workspace_correlate_varA_varB... |
fc8d3245315c10e43ce1ca5cf99f53077342095b0558ba694a9b833e6b9fcf10 | MATLAB | 5,279 | 120 | classdef Brain3DStructureVisualizer
% Brain3DStructureVisualizer
% Static methods for visualizing 3D brain structures and spatial data.
methods (Static)
function [hAx] = imageBrainRegionalValuesIn3D(regionalValueVector,brainSpace3D,brainRegionInfo,options)
arguments
reg... |
b1bd4e37d2da92bf3013e306eb0076a952d1f5e6d5ccaab84107df8cfd982c29 | MATLAB | 5,280 | 196 | function [legend_h,object_h,plot_h,text_strings] = legappend(newStrings,varargin)
%LEGAPPEND appends new entries to the end of a legend by deleting the
%current legend and recreating a new, similar legend.
%
%% Syntax
%
% legappend('new legend entry')
% legappend('new entry 1','new entry 2',...,'new entry N')
% le... |
e57880fef1f72b13d6defe2ec0fbac85d65726693b2b10585b13fecc0cb996c1 | MATLAB | 5,299 | 171 | function legend_curate(labels, varargin)
% This function will set the appropriate color, text color, box positions,
% location, background etc. in a legend based on user input.
%
% Required parameter:
% labels : legend names
%
% Optional parameters:
% markertype : the marker type ('*... |
7f25a6633d4a2a1a2ad4e67429632e7b446bc9f7c38d71c708b118fcbfb92f08 | MATLAB | 5,314 | 130 | function MuseStruct_concat = concatenateMuseMarkers(cfg, MuseStruct, force)
%
% Use as :
% MuseStruct_concat = concatenateMuseMarkers(cfg, MuseStruct, force)
%
% concatenateMuseMarkers concatenate Muse markers over all the directories.
% This file is part of EpiCode, see
% http://www.github.com/stephenwhitmar... |
baba8115f5724d7d4e552c148a116484b18ecec3f1dc7627a256cd6c244c3397 | MATLAB | 5,314 | 190 | % Connecting parallel pool
c = parcluster;
parpool(c, 14);
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_pv_prob = 0:0.2:1;
v... |
596b4aa40046cd15895d4bfb13e29f92db875f37cf11860665127e49d7a19918 | MATLAB | 5,321 | 106 | function [S, iA] = singleGaussNeuroInfer(tau_vec, mov_vec, D, lambda_val, TOL, nonneg, S, varargin)
%function S = singleGaussNeuroInfer(tau_vec, mov_vec, D, lambda_val, TOL, nonneg, S, varargin)
% S = singleGaussNeuroInfer(tau_vec, mov_vec, D, lambda_val, TOL)
%
% Use MPC to solve the weighted LASSO problem for a sin... |
ed9ab6c3862a7094c78ba023c1ae36a3f575b86cbdf536988ea9b43820b3ad64 | MATLAB | 5,344 | 144 | function varargout = spm_prf_fcn_template(P,M,U,varargin)
% Template pRF response function. This example models neuronal
% activity as a scaled version of the inputs:
%
% z(t) = alpha * u(t)
%
% Where alpha is a parameter estimated from the data.
%
%
% Inputs:
%
% P - parameter structure
% M - model structur... |
165d4dd7339c7edf378e25c422dfd2e529926a60bb73f2286c3595ed815c3aa2 | MATLAB | 5,362 | 192 | % Connecting parallel pool
c = parcluster;
parpool(c, 14);
if not(isfolder('init_data'))
%
% Create a unique RNG stream if using poissonP or constructConnections/GJ
sc = parallel.pool.Constant(RandStream('Threefry','seed','shuffle'));
seed = sc.Value.Seed;
%}
%Sim variables
var_rep = 1:150;
var_pv_prob = 0:0.2:1;
v... |
dafdae5a4965827d3a05f8249623cdb4b7680c042dca64c046ae4819108cb6c2 | MATLAB | 5,369 | 104 | % edit_Markerfiles.m
if ispc
addpath (genpath('\\lexport\iss01.charpier\analyses\lgi1\Git-Paul\EpiCode\projects\dtx'));
addpath (genpath('\\lexport\iss01.charpier\analyses\lgi1\Git-Paul\EpiCode\shared'));
elseif isunix
addpath(genpath('/network/lustre/iss01/charpier/analyses/lgi1/Git-Paul/EpiCode/projects/... |
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