sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
57a1c4eca05a7fa3b2ef2a9d9ff70669d882bd42332ca72d2a459c0f6828a0ee | MATLAB | 1,117 | 49 | function [fitresult, gof,output] = createSplineFit(timeStamps, trace)
%CREATEFIT1(TIME,TEST)
% Create a fit.
% plotFigure
% Data for 'untitled fit 1' fit:
% X Input : time
% Y Output: test
% Output:
% fitresult : a fit object representing the fit.
% gof : structure with goodness-of fit info.
%
% ... |
d8231e9f9baa3dedae41099a50ee65a879b29873ae0d2683ad342c230bd5aee7 | MATLAB | 1,117 | 32 | function h = plotvert(vert,ptcolor,varargin)
% function h = plotvert(vert,pointcolor,vertices[opt],lncolor [opt])
%
% draws lines optionally, if you specify verties list and linecolor
h(1) = plot3(vert(1),vert(2),vert(3),ptcolor,'MarkerSize',4,'MarkerFaceColor',ptcolor(1));
if nargin > 3
vertices = varargin{1};
lnco... |
e67f4d7d2dffa2a7c9a2c765b8c54e86cf679a30fb44be75f1f87ce9b36312f0 | MATLAB | 1,117 | 42 | %% relPath = get_relative_source_path(baseDir, fullPath)
%
% Input
% --------------
% baseDir : the output directory the JSON sidecar will live in
% fullPath : full filename of a source (input) file
%
% Output
% --------------
% relPath : fullPath expressed relative to baseDir when possible,
% ... |
d8ea2abbcc4dcfdde1dc431eb1d06e6ace1a97397d8f468e311383f813e72aae | MATLAB | 1,118 | 40 | function [T,rez] = estimate_snr(rez,T)
[~,~, U, ~] = SVD_template(T,3,rez.ops.Chan_criteria);
[~,~,Nclust] = size(T);
[Chan] = Chan_cluster2(U,Nclust,rez.ops.Chan_criteria);
sigma = rez.sigdata;
mu = rez.mudata;
Nbatch = length(sigma);
nt0 = rez.ops.nt0;
th = rez.ops.snr_th;
snr_coeff_batch = zero... |
4cdbf38f18d35bc737a056756003edc6eb095e1e139e8f2d3410d0cc1313880d | MATLAB | 1,119 | 34 | function [w, g_sqr] = rmsprop(w, g_sqr, grad, opts, lr)
%RMSPROP
% Example RMSProp solver, for use with CNN_TRAIN and CNN_TRAIN_DAG.
%
% Set the initial learning rate for RMSProp in the options for
% CNN_TRAIN and CNN_TRAIN_DAG. Note that a learning rate that works for
% SGD may be inappropriate for RMSProp; th... |
299fc8225a8b48ff124a3a6e7838136ad84c15db04fe9f6964df0f885a983078 | MATLAB | 1,120 | 28 | function res = search(varargin)
% Special keyword to declare parameter values to search over.
% search(x,y,z,...) or search([x,y,z,....]) or search({x,y,z,...}) expresses
% a parameter range (i.e. set of possible parameter values, to be searched for) in a grid search.
%
% Note:
% search() may also be nested ins... |
76c9546c264e5ced13071e08105c6b575be29f8cb57a43bfea61fc071ff33be2 | MATLAB | 1,120 | 34 | function A = suma_stitch(imaname)
% A function to put together a series of suma recorder images
% Very crude, only for the intrepid.
% Example: A = suma_stitch('imageseries_');
%The would be the images as spat out by the recorder window after
% a suma 'r' key stroke with SUMA_SnapshotOverSampling > 1
figure(1); clf
[e... |
b04c378d8e622dfa6f2cffb81cb1a9f7b3fe48349d294c62e7817c0e9a3944e8 | MATLAB | 1,120 | 37 | function exportTrials(params, trials2export)
% exports trials from trigger analysis
% exports selected channels (selCh_H_resp) & header structure H
% (c) Jiri, Mar21 - for bachelors at CVUT
%% trials
trials = struct;
trials.data = trials2export.data;
trials.time = trials2export.time;
trials.labels = trials2export.lab... |
9f270786f8f31cef7abb086c31318c47559fedef9cf55a6c0b29b903ca8b530a | MATLAB | 1,121 | 38 | function MultiRunCalc(type)
f1 = uigetdir([],'select one folder') ;
ListSubj = uigetfile('.txt') ;
f3 = uigetdir([],'select output folder') ;
f1list = dir(f1) ;
Subj = importdata(ListSubj); % no '_Run*' in the list name
for i = 1 : length(Subj)
csubj = 0 ;
mkdir([f3,filesep,Subj{i}]) ;
for j = 3 : length(f... |
a884c42292856baa3baed39f9e3e42adbb464f4f6c4b63ede3536ccd10bf9901 | MATLAB | 1,121 | 33 | function getTriggers_locaVisu_stimuliTypes(params)
% determines trials which contained the selected keyword (in params.thisCategory)
% saves result into respective column of 'trials_events' in each sessionCacheFile
% - rows = trials
% - values = zeros (event not found) and ones (event found)
% (c) Jiri, Mar16
dis... |
b80d7cf1fbbd3be6b8431e036a0ee90b3b7cadb149d9639d072b8313a00f2236 | MATLAB | 1,121 | 41 | function [output]=bpFilter2D(input,low,high,varargin)
options.parallel=true;
%% UPDATE OPTIONS
if nargin>=4
options=getOptions(options,varargin);
end
stack=double(input);
fwhm_scaling=2*sqrt(2*log(2));
output=stack;
sz=size(stack);
if length(sz)==2
sz=[sz,1];
end
if options.parallel
parfor ii=1:sz(3)
... |
c234aad56e69101e571d0d4a59b531be1d5e51bbd9561632f853f4c0f2c262df | MATLAB | 1,121 | 42 | function [ptheta] = tapas_sem_mixed_prepare_ptheta(ptheta, theta, pars)
%% Thin layer of preparations for the hierarchical model.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
% Number of parameter data sets.
nvals = size(ptheta.jm, 1);
ndims = ptheta.ndims;
npars = nvals / ndims;
assert(floor(npars) == npars,... |
16e79261d7b89169e157c08524cb2e2c5259fe01951156fc0bb4fdf7b8aa728c | MATLAB | 1,122 | 40 | function [posterior] = tapas_mcmc_estimate(data, model, inference)
%% Estimate a model specified.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
nfuncs = numel(inference.sampling_methods);
[states] = inference.initialize_states(data, model, inference);
[state] = inference.initialize_state(data, model, inference);... |
5f289ec4e68ecc0b0c37e9829ff98b78c3bc22e1e19b2874a0e1a4bd1d74b4e8 | MATLAB | 1,124 | 53 | function weighted_sum_image(P,Pout,w)
%weighted_sum_image(input file names,output file name);
%
% Creates a weighted sum of images based on weights for each image
%
% weighted_sum_image(DB.PP,'Activation.img',DB.studyweight);
switch spm('Ver')
case 'SPM2'
% spm_defaults is a script
disp('WARNING: s... |
b95f5afd7aefdc0e4b1995fd96c3fe7b873a8b1661251d87183ddc55c3959435 | MATLAB | 1,124 | 30 | % disp() - This file overrides disp with our custom logging function
% use logging_override_disp to disable or enable this, do not add
% this folder to path directly
% Usage:
% >> disp(data)
%
% Inputs:
% data - The data to display formatted
% matlog - a Matlab and Octave compatible logging libra... |
ef48bb90cce4068ba3bf22b93b862839d23335003056eac2e71b4416790d8a77 | MATLAB | 1,124 | 53 | function [map]=sh_PowerMap(movie, freqrange,fs)
options.plot=false; % RC
if freqrange(2)==inf
band=[1 4;...
5 9;...
10 24;...
25 50;...
51 110;...
120 fs/2-1];
nFB=6;[i,j]=find(band>(fs/2-1));
if ~isempty(i)
jj=find(j==2,1,'first');
nFB=i(j... |
f1e769e2f987e349d6d29f20be4483015df43cdb23391e854f1d122c3fb215bb | MATLAB | 1,124 | 32 | %% key = sepiatest.unwrap_method_toolbox_key(unwrapMethod)
%
% Description: maps a phase-unwrapping method name (as it appears in
% methodUnwrapName, sepia_universal_variables.m) to the field name in
% sepiatest.discover_toolboxes()'s output struct that gates whether it
% can run on this machine. See sepiatest.qsm_meth... |
68a7e302ef1c236673286e39a3763df851ccee7b408d3697f8d1030cdad69a7f | MATLAB | 1,125 | 33 | function Q = DK_theilerQ(x)
% DK_theilerQ Computes Theiler's Q statistic
%
% theilerQ calculates Q=<(x_t + x_{t+1})^3> normalized by <x^2>^{3/2}
% on a vector x
%
% ------------------------------------------------------------------------------
% Copyright (C) 1996, D. Kaplan <kaplan@macalester.edu>
%
% This function is... |
25058d5aa2f05d79b25858d29ec888b710e443cc9209afd98a3528d2523d69f9 | MATLAB | 1,126 | 34 | function cnn_imagenet_minimal()
% CNN_IMAGENET_MINIMAL Minimalistic demonstration of how to run an ImageNet CNN model
% Setup MatConvNet.
run(fullfile(fileparts(mfilename('fullpath')), ...
'..', '..', 'matlab', 'vl_setupnn.m')) ;
% Download a pre-trained CNN from the web.
if ~exist('imagenet-vgg-f.mat', 'file')
... |
377b2a59aa2022e38b12ce5d28fb44fed0e37d5fb9f23887e5ef24bbd426b6e6 | MATLAB | 1,126 | 36 |
function save4Dnii(nii,V,filename)
% nii: 4D or 3D matrix to save.
% V: either an SPM structure or just the output of spm_vols - i.e a
% structure with NIFTI header information.
if ndims(nii) == 3
T = 1; % no 4th dimension
elseif ndims(nii) == 4
T = size(nii,4);
end
if isempty(V)
dim = [size(nii,1),si... |
3dbcc295d70c123a705004685e170c1225abe95905f317420309b12e7e3eab5c | MATLAB | 1,126 | 42 | function this = plot(this, module, varargin)
% Plots different aspects of MrSeries using MrImage-plot functions
%
% Y = MrSeries()
% Y.plot(inputs)
%
% This is a method of class MrSeries.
%
% IN
%
% OUT
%
% EXAMPLE
% plot
%
% See also MrSeries
% Author: Saskia Klein & Lars Kasper
% Created: 2014-07-08
% Cop... |
4955845e10afc3f6eb6eba3fff74c30ab616fe72f2565849c287ac84a1580240 | MATLAB | 1,126 | 34 | function [rawdata, header] = readforcecurve_3_4_15 (filename)
%% OPEN THE FILE
forcefile=fopen(filename{1,1});
%% count the number of headerlines
headerline_index = 1;
headerline_counter = 0;
while headerline_index == 1
headerindicator = textscan(forcefile, '%c%*[^\n]', 1);
if strcmp(headerindicato... |
85fefa52f68872ec1c3b5623908ce2e6ecc1b23cc454edf1a69edcef93ab17bd | MATLAB | 1,126 | 40 | function [shuffleDist, trueDiff, pvals, trueParams] =...
myLambdaShuffleTest(dataLo, dataHi, nPerms, twin)
niters = 10;
xs = -(twin-10):(twin-10);
% myNorm = @(x) x-mean(x(1:twin));
myNorm = @(x) x;
[group1Params, group2Params] = deal(nan(size(dataLo, 1), 4));
dataAll = [dataLo; dataHi];
dataAll = dataAll(:, 11... |
d3ab0fa09db92606bb7908584bf28c1d745bee26a8ee371211180eb842180571 | MATLAB | 1,126 | 51 | function [ace_out] = ace_ss_detector(hsi_img,tgt_sigs,mask)
%
%function [ace_out] = ace_ss_detector(hsi_img,tgt_sigs,mask)
%
% Adaptive Cosine/Coherence Estimator - Subspace Formulation
%
% inputs:
% hsi_image - n_row x n_col x n_band hyperspectral image
% tgt_sigs - target signatures (n_band x M - column vector)
% ... |
1cd720c961e2002e985418f2e72fccdc553059005d39b7d35100a083d05a9d11 | MATLAB | 1,127 | 32 | function [ModelOutput] = fit_LCModelParamsToModel(fitParams)
% This function returns the complete fit, the baseline, the residual,
% individual contributions from each basis function, the data that are
% being fit, and the frequency axis.
%
% USAGE:
% [ModelOutput] = fit_LCModelParamsToModel(fitParams)
%
... |
a639709eb11cc98f628a210e037122ed51c3f43e0c43fd6b4d70c5c60b7ffd0f | MATLAB | 1,127 | 41 | %% function fiter = computeFiter(s,shat,NUM_MAGN)
% s - measured signal
% shat - simulated signal
% NUM_GAGN - no. of phase corrupted echoes:
% NUM_MAGN=0 : complex fitting
% NUM_MAGN=length(s) : magnitude fitting
% NUM_MAGN (0,length(s)) : mixed fitting
%
% Description: Compute the fitter for lsqnonlin
%
% Kwok-s... |
fb4f400d9f274ad53ba91aa3ac4e52cf0e42b5e9e9fee70188956a9afd433071 | MATLAB | 1,127 | 25 | function c = BrainNet_GenColormap(Nmax,Nmin,Pmin,Pmax,original_color_map)
if isempty(original_color_map)
original_color_map = jet;
end
color_length = length(original_color_map);
if color_length < 64
original_color_map = interp1(linspace(1,64,10),original_color_map,1:64,'nearest');
color_length ... |
83aca161b9ad634317d4ba949e08f1cfb320a05c5268dcf10880e57bae85e990 | MATLAB | 1,128 | 30 | function eta_matrix = eta_calc_pair(zmapa, zmapb)
if length(size(zmapa)) > 2 || length(size(zmapb)) > 2 || size(zmapa, 1) <= 1 || size(zmapb, 1) <= 1
error('inputs must be column vectors or 2D matrices');
end
m = size(zmapa, 2);
n = size(zmapb, 2);
eta_matrix = zeros(m, n, 'singl... |
19c477d41395941b7e70c45dd0a832208f8af43a428db05f8616d7c552b22834 | MATLAB | 1,129 | 36 | function label_AA = msSEI_get_label_AA(brainAtlas)
% returns labels of anatomic area atlas (e.g. Yeo7)
% (c) Jiri, Nov23
label_AA_yeo7 = {
'Visual', 'VIS';
'Dorsal Attention', 'DAN';
'Somatomotor', 'SMT';
'Ventral Attention','VAN';
'Frontoparietal', 'FPN';
'Limbic', ... |
9852a30f8a2588cde21b4267653a6f53d38ac2e7033d16cc4cd5cb67a5d25723 | MATLAB | 1,130 | 40 | function [Pr, prMax] = placeBayes(Cr, rateMap, binLength)
%function out = placeBayes1(Cr, rateMap, binLength)
% Inputs:
% Cr = [nTemporalBin X nCell] matrix of binned firing rates
% rateMap = [nSpatialBin X nCell] firing rate 'template'
% binLength = scalar of the duration of the bins in 'Cr'
% Outputs:
% Pr = [nTempor... |
f1408f377fa97855aeaddda9b48f6a15d0d8c3bb475e29769894bd0abd269524 | MATLAB | 1,130 | 62 | function [err, g, b] = TellAfniCheck (w)
%
% [err, g, b] = TellAfniCheck (w)
%
%Purpose:
% Parses AFNI's returned string from plugout_drive
%
%
%Input Parameters:
% w the string output by plugout_drive
%
%
%Output Parameters:
% err : 0 No Problem
% : N N Problems
% g : Number of OK tokens
% b : N... |
1ea272ef27737d609408521b705b51feef39fed5ba45c145c0c529c1aead8a2e | MATLAB | 1,131 | 39 | function this = save(this, fileName)
% saves object as struct (to be readable if code is not in path or
% outdated) in .mat-file , variable named 'objectAsStruct'
%
% Y = MrCopyData()
% Y.save(fileName)
%
% This is a method of class MrCopyData.
%
% IN
%
% OUT
%
% EXAMPLE
% save
%
% See also MrCopyData MrCopyDa... |
359db6f6b8359e4d49fe7fa88fd81b0c28eea4a9df640282a2c64c7447810b13 | MATLAB | 1,131 | 37 | function fout = mrvWaitbar(x,varargin)
% mrVista wrapper for waitbar
% fout = mrvWaitbar(x, varargin)
%
% The purpose of the wrapper is to check whether VISTA preferences for
% 'verbose' are set to true or false, and if false, then to skip calling
% the waitbar.
%
% EXAMPLE 1
% setpref('VISTA', 'verbose', true);
% fou... |
db76b974edb3ae7ba79288447c5106274d15369c3173728d05ad876d0a260851 | MATLAB | 1,131 | 41 | %% get_set_bfr_lbv(h,mode,input)
%
% Input
% --------------
% h : structure contains all handles of SEPIA
% mode : 'set' - extract information from GUI to config file
% 'get' - extract information from config file to GUI
% input : if mode is 'set' then input should be fid
% ... |
f19e38ea7083302b768f22afed43e380fbcf3a797ec858eb8c64c81dc1774bcc | MATLAB | 1,131 | 42 | % op_addNoise.m
% Jamie Near, McGill University 2014.
%
% USAGE:
% [out,noise]=op_addNoise(in,sdnoise,noise);
%
% DESCRIPTION:
% Add noise to a spectrum (useful for generating simulated data). Normally
% distributed random noise is added to both the real and imaginary parts of
% the data. Real and imaginary noise p... |
440e5fd27af042951ecb0706a18871dfaf5f89f540992ab3ef614ad37c606eec | MATLAB | 1,132 | 30 | function runScript = naj_scriptModified(scriptName, outputFile)
% check whether output file exists, if so, only run script if it has
% been modified in the meantime
% also check scripts that are being called!
%
% INPUT
% - scriptName - [string] fullfile of script that should be checked
% - outputFile - [cel... |
79772968b30391c0210e0c685b2077e637344f5c41203ee681c9e1b777e6c72c | MATLAB | 1,132 | 41 | function [major,minor,patchnum,extra]=iso2meshver
%
% [major,minor,patchnum,extra]=iso2meshver
% or
% v=iso2meshver
%
% get the version number of iso2mesh toolbox
%
% author: Qianqian Fang, <q.fang at neu.edu>
%
% output:
% if you ask for a single output:
% v: a string denotes the current version number; t... |
d3bf51c8880326c6b84b61e187a16ea6b53219d822a978532867fdb39b212365 | MATLAB | 1,132 | 43 | %% str_new = remove_bids_key(str,key)
%
% Input
% --------------
% str : BIDS compatible filename
% key : key to be removed, string
%
% Output
% --------------
% str_new : new filename without the specified key
%
% Description: remove a specific key from BIDS compatible filename
%
% Kwok-shing... |
755c13e97676a45652f38ef90b4680ce9c0bf20c4c08a651be587a69970f72bc | MATLAB | 1,133 | 35 | function [ par ] = tapas_rdcm_ep2par(Ep)
% [ par ] = tapas_rdcm_ep2par(Ep)
%
% Vectorizes Ep structure
%
% Input:
% Ep - parameter structure
%
% Output:
% par - vectorized version of parameters
%
% ----------------------------------------------------------------------
%
% Authors: Stefan... |
be444503818bc6fee5d6e14d5136111fd812f87ff28918958ef127b7ef254020 | MATLAB | 1,133 | 36 | function kinematicsAll = loadMultilockKinematicsAll(datasets, dataPath)
% Loads multiple datasets, locks the kinematics and creates a single data
% struct combining across trials
kinematicsAll = [];
for dataset = datasets
mouse = dataset{1}{1};
session = dataset{1}{2};
% Load and lock
kinemat... |
ee43f960f66de83545a2c17ba7b7a5302232512d9e5e0b96e7616a7431562d54 | MATLAB | 1,133 | 41 | %function perf =projeval(x,v,m,c,f)
function perf = projeval(result,param)
%projeval(result.PCAproj.P,result.PCAproj.vp,param.m,param.c,result.data.f);
x = result.proj.P;
v = result.proj.vp;
m = param.m;
c = param.c;
f = result.data.f;
%calculation of the membership
for j = 1 : c, % for all clu... |
bfd704f13bcc38105e8d43d6a821adb51c6c87f77ca1c461514695b970171a35 | MATLAB | 1,134 | 49 | function [e1] = tripleErrorBars(av, er, col, barwidth, linewidth, middle_bar)
% Takes a mean, its error(s) and plot error bars with a particular style
% % % for testing___________________
% clear all
% close all
% clc
% load 'scatdistTestData.mat'
% col=4;
% vec=vecs{col};
% av=mean(vec);
% stdvec=std(vec);
% er=stdv... |
c8d3608a54af5acde428d28314be371b8112f8dee6c9b32f5e39e8a10c07701b | MATLAB | 1,134 | 40 | function recastMrImage = recast_as_MrImage(this)
% recasts an MrImageSpm4D as a 4D MrImage, changes available methods etc.
%
% Y = MrImageSpm4D()
% YasMrImage = Y.recast_as_MrImage()
%
% This is a method of class MrImageSpm4D.
%
% IN
%
% OUT
%
% EXAMPLE
% recast_as_MrImage
%
% See also MrImageSpm4D
% Author: ... |
d8fded099073e79659c2214094ae88a3adc7ead3293dad5536e97d38dc3b2011 | MATLAB | 1,134 | 33 | function val = littleendian
% LITTLEENDIAN returns 1 (true) on a little endian machine, e.g. with an
% Intel or AMD, or 0 (false) otherwise
%
% Example
% if (littleendian)
% % do something, e.g. swap some bytes
% end
%
% See also BIGENDIAN, SWAPBYTES, TYPECAST
% Copyrigth (C) 2007, Robert Oostenveld
%
% This... |
1b3e4e4fcd3fb386ede8cbb3ef2742cd30ba2556c8a2f31f737ab916660495eb | MATLAB | 1,135 | 46 | function cr = pwidentification(simmat, labels)
% pwidentification Perform pairwise identification from similarity matrix
%
% Inputs:
%
% - simmat : Similarity matrix [pred x correct]
% - labels : Index matrix
%
% Outputs:
%
% - cr : Correct rate
%
%
% Author: Tomoyasu Horikawa <horikawa-t@atr.jp>, Shuntaro C. Aok... |
e6fd68f779c34e1f827d4c3d8334b97627fdb81330744b6f5c432ed52dbef039 | MATLAB | 1,135 | 48 | function [model] = tapas_sem_hier_prepare_model(data, model, inference)
%%
%
% Input
%
% Output
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
model.graph{1}.htheta.model = ...
tapas_sem_hier_prepare_ptheta(model.graph{1}.htheta.model);
nc = size(model.graph{2}.htheta.T, 2);
ns = numel(data);
... |
3f6481f99d83e3bc5c317a5ac881bf3adfb4d6da994fd3eb15dcbc9ba3674646 | MATLAB | 1,136 | 39 | function [this, saveFileNameArray] = save(this, varargin)
% Saves data to file(s), depending on which loop-dimensions have been
% selected
%
% Y = MrDataNd()
% Y.save('fileName', fileName, 'splitDims', 'unset')
%
% This is a method of class MrDataNd.
%
% IN
%
% OUT
%
% EXAMPLE
% save
%
% See also MrDataNd MrDat... |
773df83a76200bd5c991f8c6431d91bc34a38463b859bb966df34983efbf58e0 | MATLAB | 1,136 | 39 | function [] = create_parallelPool(numCores)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% create_parallelPool creates a parallel processing pool using given number
% of CPU cores.
%
% Arguments:
% numCores = Number of CPU cores to use
%
% Last edited by Emin Serin, 26.02.2022
%
%%%%%%... |
dfd111f31c82e633ecc55ac55b7d82092e59c7a691d407f37714927cfbaaa843 | MATLAB | 1,136 | 39 | function [sel, mobj] = get_properties_to_update(obj)
% Returns all properties which are mutable for update, cloning etc.
% (and the metaobject of property information)
%
% Y = MrCopyData()
% [sel, mobj] = Y.get_properties_to_update()
%
% This is a method of class MrCopyData.
%
% IN
%
% OUT
%
% EXAMPLE
% get_prope... |
e491a7a58da42910ca5eb609512c66804800878e405b369cab906cbc96191802 | MATLAB | 1,137 | 28 | function candoit = canGetSqrtPrecon(problem)
% Checks whether a square root of preconditioner was specified in problem.
%
% function candoit = canGetSqrtPrecon(problem)
%
% Returns true if the problem structure allows for applying the square root
% of a preconditioner to tangent vectors at a given point. The square roo... |
08a1f686ad1cddc24517d2f345aadc2f9de6459e1fc262de2dab02569e56666b | MATLAB | 1,138 | 10 | %Graphic interface builder functions (guifunc folder):
% <a href="matlab:helpwin errordlg2">errordlg2</a> - Makes a popup dialog box with the specified message and (optional)...
% <a href="matlab:helpwin finputcheck">finputcheck</a> - Check Matlab function {'key','value'} input argument pairs...
%... |
f8c9667f30162d1b1cd83c8964b659dbc1abe07ff1ca5818e4043f5602fdd58d | MATLAB | 1,138 | 52 | %isastring - Test if parameter is an (admissible) character string.
%
% USAGE
%
% test = isastring(x,string1,string2,...)
%
% x item to test
% string1... optional list of admissible strings
%
% SEE ALSO
%
% See also isdmatrix, isdvector, isdscalar, isimatrix, isivector, isiscalar,
% is... |
4271c721eb3848954a3ff38572c8d005e1dad13bfec34bbba013d84cb8ecf0bc | MATLAB | 1,139 | 51 | function varargout=sigstar_vertical(xpos, p)
% Adds a vertical significance bar at xpos
% Anne Urai, 2015
hold on
% determine the y positions for this xpos
h = findobj(gca,'Type','line');
x=get(h,'Xdata');
y=get(h,'Ydata');
ymin = min([y{1}(floor(xpos)) y{2}(floor(xpos))]);
ymax = max([y{1}(floor(xpos)) y{2}(floor(... |
93c75f70b4804d817a9c27fdebbfaf983f06b080715639744ff4da3a481505c7 | MATLAB | 1,139 | 42 | function G_rewired = rewireNetwork(G, p)
%REWIRENETWORK Summary of this function goes here
% G : network adjacency matrix
% p : re-wiring probability
% select edges to replace
numNodes = size(G, 1);
edgePairs = nchoosek(1:numNodes, 2);
edgePairIdx = 1:length(edgePairs);
edgePairIdxRandomised = edgePairIdx(randpe... |
db7548c8bd11140913b2311b1dceee99e66291e78c57a30d8d0574c5cb70a7f0 | MATLAB | 1,139 | 34 | %{
aod_monet.DriftResponse (computed) # calcium responses to drift trials
-> aod_monet.DriftResponseSet
-> aod_monet.DriftTrial
-> aodpre.Trace
-----
response: float # averaged response
%}
classdef DriftResponse < dj.Relvar
methods
function makeTuples(self, key)
disp 'preparing traces...'
... |
f2272f3ba17d0f1c7c9edcbc5de2ee0397cb5bc6a893252345241f6f06dc7fd5 | MATLAB | 1,139 | 37 | function [ y ] = tapas_huge_logit( x )
% Numerical stable calculation of logit function.
%
% INPUTS:
% x - Array of double.
%
% OUTPUTS:
% y - logit of x.
%
% Author: Yu Yao (yao@biomed.ee.ethz.ch)
% Copyright (C) 2019 Translational Neuromodeling Unit
% Institute for Biomedical Engineering,
%... |
0cf5ef7587fce4327b57b12e58a5c07b8ce19610405b568866eee6431da8e2fc | MATLAB | 1,140 | 42 | function [B1vector Intensity Signal]=B1mappingSa2RAGElookuptable(nimage, MPRAGE_tr ,invtimesAB,flipangleABdegree,nZslices,FLASH_tr,varargin)
% usage
% [B1map]=B1mappingSa2RAGE(Rationii,nimage,MPRAGE_tr,invtimesAB,flipangleABdegree,nZslices,FLASH_tr,varargin)
% varargin{1} is a phase image
%varargin{2} is the T1averag... |
5266c95d3b85b4b941ebcf42a01e965801313f22d8a76fb9f9e9909785a434ab | MATLAB | 1,140 | 41 | function generate_manopt_reference(target_html_dir_relative_to_manopt_root)
% This code assumes it's run from its own directory; could be improved
% using mfilename('fullpath') and pwd() for example.
% Add m2html tool to the Matlab path
cd m2html/;
addpath(pwd());
cd ..;
% Go back to... |
6e1bcaf5919cef53c04942342a3d8c955e459f9cc3a830ac723d6c7d32ef7aff | MATLAB | 1,140 | 26 | function checkIfAnySpikes(spikeTimes, ExpName)
spikeDetectionMethodUsed = fieldnames(spikeTimes{1});
all_method_spikes_detected = 0;
for nmethod = 1:length(spikeDetectionMethodUsed)
methodName = spikeDetectionMethodUsed{nmethod};
method_detected_spikes = 0;
for channel = 1:length(... |
0ffe9dc2e106dbfa064b7f6ff0caa01aad7c365de4ef52a3a8f8997ea843b893 | MATLAB | 1,141 | 39 | function c = tapas_quasinewton_optim_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the Broyden, Fletcher, Goldfarb and Shanno (BFGS)
% quasi-Newton optimization algorithm
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
1844c5f8cb7e3cf48826a56a15df8049e7c69ee24cc2fa6200d2d7630cf9ca3c | MATLAB | 1,141 | 40 | function cols=RDMcolormap
% this function provides a convenient colormap for visualizing
% dissimilarity matrices. it goes from blue to yellow and has grey for
% intermediate values.
%__________________________________________________________________________
% Copyright (C) 2012 Medical Research Council
import rsa.*
i... |
4bc6987d59790d503817461ac40b95e7207481926f28f3ca16fbf75f3b6b2dec | MATLAB | 1,141 | 35 | function getTriggers_emoReco_button(params)
% finds events when subject pressed a button on a joystick to indicate hirs choice:
% left (=L), right (=R) or nothing (=n.a.)
% (c) Jiri, Mar16
display([' - finding events for: ' params.thisCategory]);
%% per session: load trials, find events and save
for sess = 1:size(... |
aa9180dd2b8a6b82fc68dccc1cd2e9000ee032bf64ae79d2a3501bed6cf218ea | MATLAB | 1,141 | 41 | function RDMs=squareRDMs(RDMs_ltv)
% converts set of row-vector RDMs_ltv to square form (despite being
% rows, RDMs are stacked along the 3rd dimension, just as square RDMs
% would be. this avoids ambiguity when the RDMs_ltv is square and could
% be either a single RDM or a number of vectorized RDMs.)
% RDMs may be bar... |
693ca085f880d0586fca7950d830148ba2c1b5f714833896c7fcc3ec7a0f8690 | MATLAB | 1,142 | 57 | function [llh] = tapas_mdlinear_hier_llh(data, theta, ptheta)
%% Likelihood of the nodes of a linear multivariate model with diagonal
% precisions on each parameter.
%
% It is the likelihood of
%
% p(y|x, beta, pi) = N(y - x*b, 1/pi)
%
% Note that this is a multivariate regression problem, so beta is a matrix
% in w... |
6e2679cfc28721b44c31d1cb3f4e1a3038d72523a737da885d42c7f2ee9a5dd1 | MATLAB | 1,142 | 28 | function [values] = ave_control(A)
% FUNCTION:
% Returns values of AVERAGE CONTROLLABILITY for each node in a
% network, given the adjacency matrix for that network. Average
% controllability measures the ease by which input at that node can
% steer the system into many easily-reachable ... |
951a138c263406964ee9c5d40b3f5eace776fd177907df45060a700ff6364190 | MATLAB | 1,142 | 59 | function [c] = ROIcol(i,nc, verb)
% [c] = ROIcol(i,nc);
% returns a color from an ROI colormap.
% useful for autocoloring of multiplots
% i: index of color, starts at 1
% nc: number of colors in map. Default is 32.
% larger numbers cause longer delays at map generation.
% returns
% c: The color RGB triplets... |
a92d39cbdc13145a930a2ae40d05d7c16e58df4ad6a285c0bd0e3c42da34f906 | MATLAB | 1,142 | 40 | function [fitresult, gof] = createSpikeFit(tsFit, toFit)
%CREATEFIT(TSFIT,TOFIT)
% Create a fit.
%
% Data for 'untitled fit 1' fit:
% X Input : tsFit
% Y Output: toFit
% Output:
% fitresult : a fit object representing the fit.
% gof : structure with goodness-of fit info.
%
% See also FIT, CFIT, ... |
3777b9756d4d160a1ccca905921914f9d7f1dad94ae8e242e573ddbccdc12a06 | MATLAB | 1,143 | 25 | % I need a model that has different rhos for gain trials than loss trials.
% I don't think that this implementation of prospecet theory gives me that.
c1 = 10;
c2 = 5;
p1 = 0.5;
rho = 0;
alpha = 1;%.7; % alpha is the weight of the probability
u_CARA = @(c, rho) (rho ~= 0) .* (1 - exp(-rho .* c)) ./ ( rho + (rho... |
72b44f3ceb8ba9d6d76708c43d4341d021e7572aea26a4b32a05d1b0acaa99ae | MATLAB | 1,143 | 54 | function [model, param] = tapas_sem_identify_model(fllh)
%% Identifies the model from the likelihood function.
%
% Input
% fllh -- Funcion handle with the likelihood of the model
% Output
% model -- String. Name of the model (seria or prosa).
% param -- String. Name of the parametri... |
d46dccf4e9ee67cb1557ac47c917e2ccef2b50ae419592da1144c806b1242117 | MATLAB | 1,143 | 37 | % setup
nsdsetup;
% find all DWI preprocessed results
files0 = matchfiles(sprintf('~/nsd/nsddata_diffusion/ppdata/subj*/run*/dwi/dwi.nii.gz'));
assert(length(files0)==8*2);
% load in the data
allvols = {};
for zz=1:length(files0)
a1 = load_untouch_nii(files0{zz}) % img: [320x320x320x98 single] for Run 1
% avera... |
f747bef7118ad9c8395629b5eeb0a607bedacfa29fdf8111d598dddbc8c620c9 | MATLAB | 1,143 | 33 | function [m,dm] = meanPow(d, mean, hyp, x)
% meanPow - compose a mean function as the power of another mean function m0.
%
% m(x) = m_0(x) ^ d
%
% If the degree d is not a strictly positive integer, we use
% m(x) = sign(m_0(x)) * abs(m_0(x)) ^ d
% to stay within the reals
%
% The hyperparameter is:
%
% hyp = [ hyp_m0... |
7e193056b9539bfaa2a90ef169017de045efaee8e7efb3c46d5ae9f1d71c0ae5 | MATLAB | 1,144 | 64 | function [state] = tapas_mcmc_meta_adaptive_ti(data, model, inference, ...
state, states, si)
%%
%
% Input
%
% Output
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
if state.nsample > inference.nburnin || mod(si, inference.ndiag)
return;
end
% Number of subjects and chains
[ns, nc] = size... |
82b85406a48ec7b05ce399c404a2fde920868eb4102a09524ea78a7f80ef8163 | MATLAB | 1,144 | 41 |
% Simulate
t=0:1/Fs:23389/Fs;
signal=sin(2*pi*t*10)+1*randn(1,length(t));
reference=2*sin(2*pi*t*10)+0.1*randn(1,length(t));
% plot(signal, reference)
win=[0.5 1 2];
for iWin=1:length(win)
[output]=pieceWiseUnmixing( reference,signal, Fs, 'umxMethod','pca','window',win(iWin));
a_pca(iWin,:)=output.coefficient;
[outp... |
82d9828d0ada608d54fee76d7c25ba0e6c9343e239a5dd166887ab2b1d7a996a | MATLAB | 1,144 | 39 | function [m,dm] = meanPoly(d, hyp, x)
% meanPoly - compose a mean function as a polynomial.
%
% The degree d has to be a strictly positive integer.
%
% m(x) = sum_i=1..D sum_j=1..d a_ij * x_i^j
%
% The hyperparameter is:
%
% hyp = [ a_11
% a_21
% ..
% a_D1
% a_12
% a_22
% ... |
99ebea01bcf32969fba5fe1b46ea016c29dbcbe8e90f7ec86b2de494379c132b | MATLAB | 1,144 | 28 | function [lp,dlp] = priorT(mu,s2,nu,x)
% Univariate Student's t hyperparameter prior distribution.
% Compute log-likelihood and its derivative or draw a random sample.
% The prior distribution is parameterized as:
%
% p(x) = ( 1 + (x-mu)^2/(s2*(nu-2)) )^(-(nu+1)/2) / Z, where
% Z = gamma(nu/2) * sqrt(pi*... |
00862beae9ab773fcc88b82e8cc54ebffe4b0828323d8675358ea2f21fcf1686 | MATLAB | 1,145 | 32 | function plot_pc_init(PC,Nchan,i)
figure;
ki =0;
for k=1:Nchan
subplot(Nchan,3,1+ki)
plot(squeeze(PC(k,1,:)),squeeze(PC(k,2,:)),'*')
title(['Cluster:', num2str(i)]);
ylabel('PC2')
xlabel('PC1')
xlim([min(squeeze(PC(k,1,:))) max(squeeze(... |
670662cb2bbce9d9e367ca3dfe9f9e9606768af8cab82131e4a7c9e4a1f2bae4 | MATLAB | 1,146 | 44 | %% B0_dir = get_B0_dir_from_nifti(nii)
%
% Input
% --------------
% nii : NIfTI format structure from load_untouch_nii.m
% B0_dir : default B0 direction (optional, default in z-direction [0;0;1])
%
% Output
% --------------
% B0_dir : main magnetic field direction with respect to imaging
% ... |
9ef206c6880305b53216bc7246c8ae96c197232ef3af45dd18ec5a9c822012bb | MATLAB | 1,146 | 52 | function [out err] = semangle(in,sens);
% MEANANGLE will calculate the mean of a set of angles (in degrees) based
% on polar considerations.
%
% Usage: [out] = meanangle(in,dim)
%
% in is a vector or matrix of angles (in degrees)
% out is the mean of these angles along the dimension dim
%
% If dim is not specified, th... |
c28fa908a81bb830aa63f093dfb6600b8f7d9834cd379ec035a4e1440e921585 | MATLAB | 1,146 | 48 | function [llh] = tapas_mdlinear_llh(data, theta, ptheta)
%% Likelihood function of a multivariate linear model where we assume that
% the covariances are diagonal.
%
% This is the likelihood of a Gamma Gauss model % of the form
%
% p(beta| beta0, pe)p(pe) = N(beta; X*beta0, 1/pe) Gamma(pe; a, b)
%
% Note thet beta is ... |
c7dd3b1fa2e909fdf3042c9e9c3c469f901a462752cfe9af5aee110d0802129e | MATLAB | 1,146 | 44 | function [ptheta] = tapas_sem_multiv_prepare_ptheta(ptheta, theta, pars)
%% Thin layer of preparations for the hierarchical model.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
% Number of parameter data sets.
nvals = size(ptheta.jm, 1);
ndims = ptheta.ndims;
npars = nvals / ndims;
assert(floor(npars) == npars... |
d07bfc5633437fe59647df10c1a8bfe10be9b6a199511b0b619fee8a890a23f7 | MATLAB | 1,146 | 38 | function namesMatlabbatchMethods = get_all_matlabbatch_methods(this)
% Returns cell of string identifiers of all methods using a matlabbatch
%
% Y = MrSeries()
% Y.get_all_matlabbatch_methods()
%
% This is a method of class MrSeries.
%
% IN
%
% OUT
% nameMatlabbatchMethods cell(1,nMethods) of string identifiers ... |
d820a259a3ea3e5e02ea294be101e726879b7c599b41db9f8c7465472bee6f0a | MATLAB | 1,146 | 61 | function [sigma,mu,A]=mygaussfit(x,y,h,optionStab)
%
% [sigma,mu,A]=mygaussfit(x,y)
% [sigma,mu,A]=mygaussfit(x,y,h)
%
% this function is doing fit to the function
% y=A * exp( -(x-mu)^2 / (2*sigma^2) )
%
% the fitting is been done by a polyfit
% the lan of the data.
%
% h is the threshold which is the fraction
% from... |
ff8b24894aa5708ada147f0cf819fcbb6528a1e2c2f84643f4fe7bcb8c6e93a8 | MATLAB | 1,146 | 39 | function crc = neuralynx_crc(dat, dim)
% NEURALYNX_CRC computes a cyclic redundancy check
%
% Use as
% crc = neuralynx_crc(dat)
%
% Note that the CRC is computed along the first dimension.
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the docum... |
3e793eb66a84d43428fc189213f261855cce9bf6240833eaebdd838901345e6c | MATLAB | 1,147 | 27 | function [pvec, pstruct] = tapas_ehgf_binary_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2012-2020 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, which is released under the terms of the GNU General P... |
6c3922247d3484132a08ac07a0fa66aa6b4ff403afccf997a8aef7ce6718497e | MATLAB | 1,147 | 39 | function y = tapas_condhalluc_obs2_sim(r, infStates, p)
% Simulates responses according to the condhalluc_obs model
%
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2016 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, whic... |
afa942d34482934af39952fb97aaf04a631e6c2e74b6a1ab7b513fa70e49e957 | MATLAB | 1,147 | 37 | function y=surfing_uniqueidxsperrow(x)
% returns unique indices per row
%
% UNIQUEIDXS=SURFING_UNIQUEIDXSPERROW(IDXS)
%
% INPUT:
% IDXS: NxP matrix, for N rows with P indices each.
% OUTPUT:
% UNIQUEIDXS: NxQ matrix, Q<=P, where each row contains the unique
% values in the corresponding row fro... |
f35fc5eba5b4c219776924f14ed6983419667c80babd1010fd7cca58e277653d | MATLAB | 1,147 | 29 | function FWHM_map = calculate_2D_FWHM(target_plane,target_point)
maxValue =target_plane(target_point(1), target_point(2));
row_peak = target_point(1);
col_peak = target_point(2);
FWHM_map = zeros(size(target_plane));
for view_degree = 0:359
view = pi*view_degree/180;
vector = [cos(view),sin(view)];
step_vie... |
fcc52515deceffcd69416ea879f9a9b083187c9fe33d88dfd48708b63fd88c08 | MATLAB | 1,147 | 53 | function this = save(this, filename)
% saves the data in MrRoi
%
% Y = MrRoi()
% Y.save(inputs)
%
% This is a method of class MrRoi.
%
% IN
%
% OUT
%
% EXAMPLE
% save
%
% See also MrRoi
% Author: Saskia Bollmann & Lars Kasper
% Created: 2014-11-21
% Copyright (C) 2014 Institute for Biomedical Engineering
% ... |
25113bb468156db1cb83674d074d765c8642028539a133697bd6ca7c3f9183e2 | MATLAB | 1,148 | 40 | function namesMatlabbatchMethods = get_all_matlabbatch_methods(this)
% Returns cell of string identifiers of all methods using a matlabbatch
%
% Y = MrImage()
% Y.get_all_matlabbatch_methods()
%
% This is a method of class MrImage.
%
% IN
%
% OUT
% nameMatlabbatchMethods cell(1,nMethods) of string identifiers of... |
2b5d100f4a02f9eb01aeaa2930996a6dd247167f83b76a2b7988df98ac85d205 | MATLAB | 1,148 | 46 | function opt = sero_pulseq_SERO_opt(opt)
% function opt = sero_pulseq_SERO_opt(opt)
%
% 1. Call this functions without input arguments to get default structure -
% e.g. opt = sero_pulseq_SERO_opt()
% 2. Change the options as you like
% e.g. opt.TE = 100e-3;
% 3. Call this function again with the options as input to upd... |
4746b38ac5dd532008c88bea40f6228dc8f02a4e3c59d2d271f40e86a6a2e6d7 | MATLAB | 1,148 | 61 | function [numcl,rad,nclusts] = recover_choose_radius(varargin)
% [numcl,rad,nclusts] = recover_choose_radius([plot color])
%
% input of an argument signals to plot. color = input argument
%
% tor wager
%
%
d = dir('dens*clusters.mat'); d = str2mat(d.name);
for i = 1:size(d,1),
load(deblank(d(i,:)))
numcl(i) =... |
9831010a4df60dbcdaad1956932f6acc93b0461a98d9aaf3e5d983b2af85d690 | MATLAB | 1,148 | 37 | function getTriggers_gameType(params)
% extracts only defined paradigm from each session
% based on the keyword 'gameType' which should be loaded into sessionCache
% via params.load_D
% (c) Jiri, Nov16
display([' - finding events for: ' params.thisCategory]);
%% per session: load trials, find events and save
for ses... |
bd854cfed813a764da86c03728c5f9a114d8046102892ce14d80e8e4ef2ef9c4 | MATLAB | 1,148 | 43 | for explictMexReset = [false]
% reset the same GPU device
for t = 1:6
if explictMexReset, clear mex ; end
if mod(t-1,2) == 0
disp('vl_test_gpureset: resetting GPU') ;
gpuDevice(1) ;
else
disp('vl_test_gpureset: not resetting GPU') ;
end
if t > 1, disp(a) ; end
a = gpuA... |
65fe05261279c3b0246362a2997acab4a5012cb4292249bf2f3a8765c916926e | MATLAB | 1,149 | 50 | function h = sero_pulseq_plotBlocks(seq, blockInd)
% function h = sero_pulseq_plotBlocks(seq, blockInd)
if nargin < 2 || isempty(blockInd)
blockInd = [1 numel(seq.blockEvents)];
end
[gwf, rf, dt, ti, rwf] = sero_pulseq_getBlockWaveforms(seq, blockInd);
col = pulseq_colXYZR();
tStart = sum(seq.blockDurations(1:(... |
94d603c79b11957348b053cb7ef76b3a95d492c668808cf64034c84f4b890ea2 | MATLAB | 1,149 | 36 | function p = chsqcudf(x,v)
%CHI2CDF Chi-square cumulative distribution function.
% P = CHI2CDF(X,V) returns the chi-square cumulative distribution
% function with V degrees of freedom at the values in X.
% The chi-square density function with V degrees of freedom,
% is the same as a gamma density function with ... |
a6f0bdc680c04b57b0d368db16c75bd991e35a97941b5632d86035b87ecc2f54 | MATLAB | 1,149 | 31 | function [re_ordered_corrected] = FDR_correct(uncorrected_values)
%Perform FDR correction on multiple p-values calculated from same figure
% list of uncorrected p-values is the input argument
% the function will rank order and correct scaled to the number of comparisons
% then, it re-orders the values to matc... |
b624651ba22151a34cba998a58f08f8bda4de015922954e0f2c500e3df93e48a | MATLAB | 1,149 | 28 | %{
# field-specific scan information
-> meso.ScanInfo
-> shared.Field
---
px_height : smallint # height in pixels
px_width : smallint # width in pixels
um_height : float # height in microns
um_width ... |
018ed400496f148edd9387dbafc5d1c1bb127da7eda9bf694a3dd1f688afec74 | MATLAB | 1,150 | 30 | %{
stk.StackInfo (imported) # header information
-> stk.Stack
---
nchannels : tinyint # number of recorded channels
nslices : int # number of slices (hStackManager_numSlices)
frames_per_slice : int ... |
847052dd3edd5f47c0b7e1baa5e44aa6cd8aeca86544c191b9a0f215da18900a | MATLAB | 1,150 | 27 | function [pvec, pstruct] = tapas_hgf_binary_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2012-2013 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, which is released under the terms of the GNU General Pu... |
91bac55e5bdbe8f68dac5bc7b7d21372875428c782b30945679707e3222a751d | MATLAB | 1,150 | 36 | %% addon_config
%
% Description: Addon script to incorporate new method to the SEPIA framework
%
% Kwok-shing Chan @ DCCN
% k.chan@donders.ru.nl
% Date created: 27 June 2020
% Date modified:
%
% DO NOT change the variable names, update the variable value instead
%
%% main
% This name will be used thorough the SEPIA f... |
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