sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c5344bbb2ebb8af84b1b262a8807f1b996d7bfc9b54fdf8972a0c9b8059140dd | MATLAB | 3,184 | 99 | function [urlConnection,errorid,errormsg] = plugin_urlreadwrite(fcn,urlChar)
%URLREADWRITE A helper function for URLREAD and URLWRITE.
% Adapted by A. Delorme from
% Matthew J. Simoneau, June 2005
% Copyright 1984-2011 The MathWorks, Inc.
% $Revision: 1.1.6.7 $ $Date: 2011/10/22 22:05:21 $
% Default output a... |
f99dce584a186e9d2dae4e4ff885f449801627ee885c26e3d1316e431de23f83 | MATLAB | 3,184 | 87 | function str = mean2str(m,s,n,varargin)
%mean2str - Convert mean or median and SEM (or confidence interval) to string.
%
% USAGE
%
% s = mean2str(m,s,n,<options>)
%
% m mean or median
% s standard error (see <a href="matlab:help sem">sem</a> or <a href="matlab:help semedian">semedia... |
2227f35ff26f18c629fd2594c67fab8be90487eca7892988fe0b1fd4a07f5e46 | MATLAB | 3,185 | 109 | function [cost, info, x, A] = test22(n)
% Test for the preconditioner support of RCG and RTR.
%
%
% This file is part of Manopt: www.manopt.org.
% Original author: Nicolas Boumal, Dec. 30, 2012.
% Contributors:
% Change log:
clc;
% reset(RandStream.getDefaultStream);
% randnfoo = randn(123456, 1); %#ok... |
3f27e3f7ff232cf9e03df65f285d8cf42f34983abbbf7a258f86c523ce6e435d | MATLAB | 3,186 | 88 | function task_clean_b(sii, PATH, cfg)
% Further clean ICA decomposed data by only rejecting eye and muscle ICs
% >.9 % (IClabel default)
% with single subject ICA decomposed EEG data PATHIN named file_in
%
% INPUT
% - sii: vector of subject IDs to be processed
% - PATH: structure with all paths leading to diff... |
7bef68cd3f1d377b3a212f319b5e71a75b7698974249f44afd6af587741bcc8a | MATLAB | 3,189 | 103 | function [pval,perlow] = uncertainty_exploratory(all_SU, all_index, all_S)
%% christine's version of MLB
alignto = {'Rew'};
for m = 1:5
map1{m} = [];
map2{m} = [];
end
ul = .8; % probability for mix block
ll = .05; %probability for adapt block
params = [1, 1.2, 0.8, .3, 1];
ctr1 = 0;
ctr2 = 0;
for yy = 1:length... |
c1b3ca0b47a770f04e93ed73bc8ed22d6e25474c31455e10d143608b6258793b | MATLAB | 3,189 | 121 | function mat2nii(img,file_name,varargin)
%Writes an image intensity matrix to an nii file
%Input: image matrix in either matrix or vectorized form and nii file name
%Optional inputs: image dimensions vector, data precision and reference volume
%Image dimensions are required if image matrix is vectorized
%Default ... |
0dd3b18f8865d4354893ea4c58710627e7181dfb6884fea2d967e34cd3ccc82b | MATLAB | 3,190 | 97 | % pop_firpmord() - Estimate Parks-McClellan filter order and weights
%
% Usage:
% >> [m, wtpass, wtstop] = pop_firpmord(f, a); % pop-up window mode
% >> [m, wtpass, wtstop] = pop_firpmord(f, a, dev);
% >> [m, wtpass, wtstop] = pop_firpmord(f, a, dev, fs);
%
% Inputs:
% f - vector frequency band edges
% ... |
0415d7d05eb6fd46b07282eadf00cf0454bc21ba6a22aa1e89c4235414381673 | MATLAB | 3,191 | 102 | sig_time_points = find(true_size_sig_mask(4,:) == 1);
for i = 1:length(bc_corrected_pupil);
temp_amplitudes = bc_corrected_pupil(i,sig_time_points);
mean_amp(i) = mean(temp_amplitudes,'omitnan');
temp_amplitudes = [];
end
Y = mean_amp';
formula = 'Y ~ 1 + cohMatrix + condition_Matrix +(1|subje... |
d94a8c64d10da231161788877a0caf2672e0592777e22467f323736f1dcceb1b | MATLAB | 3,191 | 82 | % BIDS_WRITEELECTRODEFILE - write electrodes.tsv and coordsystem.json from single EEG dataset
%
% Usage:
% bids_writeelectrodefile(EEG, fileOut, flagExport)
%
% Inputs:
% 'EEG' - [struct] the EEG structure
% 'fileOut' - [string] filepath of the desired output location with file basename
% e.... |
9ce72426bb2f469474caa4211eb1eea4469e6b9be7ecbdc3220bd99635716195 | MATLAB | 3,193 | 58 | % EEG_HELPHELP - How to use EEGLAB help.
%
% EEGLAB MENU:
% Each EEGLAB menu item calls a Matlab function from the commandline. If this
% function pops up a graphic interface window, the figure title usually
% contains the name of the function that the window will call. EEGLAB help
% files are thus simply the colle... |
0694a97ae4f7c758b136a08d1e3848c61168eb2be46401da053cdd4b0195bead | MATLAB | 3,194 | 115 | function fh = tapas_physio_plot_retroicor_regressors(R, order, ...
hasCardiacData, hasRespData, verbose)
% Plots RETROICOR regressors split into cardiac/resp and interaction
%
% fh = tapas_physio_plot_retroicor_regressors(R, order)
%
% IN
% R [nVolumes, nRegressors] physiological nuisance regressor
% ... |
281459e8533dd04fcd7eb88849ab5a2cc2a0b1b040bc6f8164c77a92292ee9e9 | MATLAB | 3,197 | 109 | function [] = PlotFigure1(datadir, codedir)
%PlotFigure1 - Plots Figure 1. Must be run after ProcessData_Figure1.
% INPUTS:
% datadir - Directory where output from ProcessData_Figure1 was saved
% codedir - Directory of code (e.g., published/dynamic_learning_rate/)
%% Set Path and Load Data
s = pathsep;
pathStr = ... |
8ed7967b9922d30ae3ef3a692fe420e239903cc09efbb53cf5d5e8be6c2b013b | MATLAB | 3,197 | 106 | function shuffled = shuffle(x,method)
%shuffle Shuffles raster data using various different methods
% Shuffles spike data (0 or 1) using three differnt methods
% assumes rows are individual cells and columns are time frames
%
% 'frames' - shuffles the frames in time, maintains activity pattern of
% each frame
%
% 'tim... |
54805243c60fab89d1c339b039512bfcb2de9b38bb14cdd614092f5d32644f7b | MATLAB | 3,199 | 83 | function distance = Distance(positions,reference,varargin)
%Distance - Compute instantaneous distance to a reference point.
%
% USAGE
%
% distance = Distance(positions,reference,<options>)
%
% positions position <a href="matlab:help samples">samples</a>
% reference reference point (same coordinates... |
8b7b46593fa555adda383e7641ef91c29cf7dbba107ef5d506773f3c3c886935 | MATLAB | 3,199 | 106 | function [patchHandles textHandles] = hlp_vrect(x, varargin)
% Tim Mullen, 2011, SCCN/INC/UCSD
g = finputcheck(varargin, ...
{'yscale' 'real' [] 1; ... % vertical scaling (relative to ylimits)
'dock' 'string' {'bottom','top','none'} 'top'; ... % whether to 'd... |
da8e308ed7a058ec33debdf0596c96f551d1bd7185faf9484e098307c033c2dc | MATLAB | 3,199 | 56 | %-----------------------------------------------------------------------
% Job saved on 22-Jul-2024 11:54:27 by cfg_util (rev $Rev: 7345 $)
% spm SPM - SPM12 (7771)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
%% load libraries, I think
run('set_library_paths.... |
188909a0816d4170aab06142a725be638e6ba8065478904a9741d154b459c438 | MATLAB | 3,200 | 74 | classdef McsSegmentStream < McsHDF5.McsStream
% Holds the contents of a SegmentStream, either spike data or averages
%
% (c) 2016 by Multi Channel Systems MCS GmbH
properties (SetAccess = protected)
% (struct) Information about the source channel(s) of the segment.
% Same as the McsAnal... |
26c6d292458e61b1b98a8908f1ded2739072df352e20e27b98161277d2924292 | MATLAB | 3,200 | 103 | %% io_writelcmBASIS
% This function creates a LCM usable .BASIS file from an Osprey Basisset.
% MMs are not included in the output
%
%
% USAGE:
% RF=io_writelcmBASIS(in,outfile,vendor,resample);
%
% INPUT: in = Osprey BASIS file
% outfile = path and name of the LCModel .BASIS file
... |
fd3d45857729bb9441ecd40f749e4d9ebb8d106200176dfd55de996ea1c13e55 | MATLAB | 3,201 | 101 | function [ax,h]=suplabel(text,whichLabel,supAxes)
% PLaces text as a title, xlabel, or ylabel on a group of subplots.
% Returns a handle to the label and a handle to the axis.
% [ax,h]=suplabel(text,whichLabel,supAxes)
% returns handles to both the axis and the label.
% ax=suplabel(text,whichLabel,supAxes)
% returns ... |
cf9a871344f4c642b613eb84e46b797433c1cad1d9569616ca0e60b167aa7bc7 | MATLAB | 3,202 | 96 | function [C2 thetaout] = mahiem_trialwise2(dat,theta,thetabasis,foldvar,inclusion,covtime,exclusion,recenter)
% [C2 thetaout] = mahiem_trialwise2(dat,theta,thetabasis,foldvar,inclusion,covtime,exclusion,recenter)
if nargin < 3
thetabasis = -pi:pi/8:(pi-pi/8);
end
thetabasis = thetabasis(:); %make sure the... |
7180212d1383c18e5a5d00a564620d21421e997ac0f64e8394b08cc7c61a8eb2 | MATLAB | 3,205 | 80 | function out = MF_AR_arcov(y, p)
% MF_AR_arcov Fits an AR model of a given order, p.
%
% Uses arcov code from Matlab's Signal Processing Toolbox.
%
% ---INPUTS:
% y, the input time series
% p, the AR model order
%
% ---OUTPUTS: include the parameters of the fitted model, the variance estimate
% of a white noise inpu... |
2a6069a2382b850481ac999f34a473d76601880b1970e16dc1d311b42de7fb07 | MATLAB | 3,206 | 120 | function [WTOpt, WTMdl, BlkInf, Belief, Prior, Kappa] =...
GenerateSynthData_Bayes(params, ratTrial,...
noise_arg, gen_arg, noise_params)
%GenerateSynthData_Bayes - generates synthetic wait times
%for optimal Bayes model.
% Inputs:
% params - Parameter vector. [kappa_mi, kappa_hi, kappa_lo, D, lambda]
% ... |
6c835f47043165602f42a216170a62bad33a15bc29b0c2588720a0d4188b1df8 | MATLAB | 3,206 | 106 | function shuffled = shuffle(x,method)
%shuffle Shuffles raster data using various different methods
% Shuffles spike data (0 or 1) using three differnt methods
% assumes rows are individual cells and columns are time frames
%
% 'frames' - shuffles the frames in time, maintains activity pattern of
% each frame
%
% 'tim... |
28e3b3c05702883eb82492c7c13808a509084b0b5460f8e164be1dde9d681824 | MATLAB | 3,207 | 88 | function [newvol,newvolsize] = changevolumeres(vol,volsize,newdim,wantlabel)
% function [newvol,newvolsize] = changevolumeres(vol,volsize,newdim,wantlabel)
%
% <vol> is a matrix X x Y x Z. All dimensions must be > 1.
% <volsize> is a 3-element vector with the voxel size
% <newdim> is the desired matrix dimensions
% <w... |
2829013f867f1c6de587e20b3821a78983a700175757ba689cb9038d39751d25 | MATLAB | 3,209 | 68 | % turn off advanced expression facilities and load a dataset
exp_eval(Set(@disable_expressions,1))
eeg = io_loadset('data:/christian/Demo/imag.vhdr');
% run a filter on some data with some arguments using positional syntax (rest using defaults)
eeg = flt_fir(eeg, [], [5 10 25 30], 'bandpass');
% run a filter on some ... |
4a16bf47f2708462810cd9eb9a1000d0b883f6c06153b0cce6e04010598171d9 | MATLAB | 3,209 | 102 | function interpolated = fillnans(matrix,coefficients)
% coeffifcients are vertical and horizontal kernel size (like in Smooth):
% how much should each dimension weigh in the interpolation?
% This function is an usage of John D'Errico's method 2 in
% INPAINT_NANS (dowloaded from FileExchange on 01/02/2016)
% e-mail ad... |
78b417d098fed79835b587b8b60d72624daaa238bea191b7d1ead6c8efde17f9 | MATLAB | 3,211 | 125 | function simulate_DA_release
%Dopamine simulation for Golden et al. (Figure 5g-h).
T = -.05:.001:.100; %time vector
tstart = find(T==0);
rew = 1:3;
mycolors = [0 0 1; .55 0 .8; 1 0 0];
gammas = [.7 .85]; %terms specifying reuptake
timeStepS = 0.001;
durationS = .015;
ntrials = 500;
evoked_FRs = [0 1.5 3]; %evoked DA ... |
b442148c0924d64534019dfa99f513e6e123ad17434e83ba9c18aaa7648e305b | MATLAB | 3,211 | 94 | function outputImage = reslice(this, targetGeometry, varargin)
% Reslices nD MrImage in 4D chuncks via SPM functionality
%
% Y = MrImage()
% rY = Y.reslice(targetGeometry, 'splitDimLabels', ...
% 'echo', 'splitComplex', 'ri')
%
% This is a method of class MrImage.
%
% IN
% targetGeometry object of MrImageGeome... |
31dbfcdde3a2fb2c1743cecf999ea6ea7f433c3566ca9e98a06a63dfd858e319 | MATLAB | 3,212 | 51 | %-----------------------------------------------------------------------
% Job saved on 14-Jul-2014 18:18:40 by cfg_util (rev $Rev$)
% spm SPM - SPM12b (5672)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
matlabbatch{1}.spm.spatial.preproc.channel.vols = {'/Use... |
ac3ec38366dfeb06536fccdc86840f5b437f292d9a0dfeaa2f10602e788c10ca | MATLAB | 3,212 | 117 | % HELPFOREXE - Write help files for exe version
%
% Usage:
% histtoexe( mfile, folder)
%
% Inputs:
% mfile - [cell of string] Matlab files with help message
% folder - [string] Output folder
%
% Output:
% text files name help_"mfile".m
%
% Author: Arnaud Delorme, 2006
%
% See also: EEGLAB
% Copyright (C) 200... |
08dded5cfe45782d64f602b3d81eb9a5d555aaef72898e9f7f7657de114e86e0 | MATLAB | 3,213 | 89 | function grp_out_dist = init_sd_param(infnames,outfname)
%% LOAD DATASET
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
grp_out_dist=[];
for i=1:length(infnames);
infnames{i}
%Load the .set file (this will need to be BIDS data file format compliant)
EEG = pop_loadset('filename'... |
981c0b4e9a32557e29592bb011aa3476d97600c31560b4c933a9c7fdf5a1b727 | MATLAB | 3,213 | 90 | function [output, outputPrxDst, outputD2S, outputRes, outputWc, outputWa] = loadDecode(dataPath, mouse, session, kinematicField, neuralField, fitModels)
% Runs all decoding model configurations for one dataset, for specified
% data fields
if nargin < 6
fitModels = [1,1,1,1,1,1]; % fit all 6 model configurations
en... |
c342013d1adb0d5fe7b483172692943d0481cef2163907140b94bc5c600c88cd | MATLAB | 3,214 | 135 | %% [r2s,t2s,m0] = R2star_NLLS(img,te,mask,isParallel,NUM_MAGN)
%
% Input
% --------------
% img : multiecho images, time in last dimension
% te : echo times
% mask : signal mask
% isParallel : parallel computing (i.e. parfor)
% NUM_MAGN : no. of phase-corrupted echoes
%
% Output
% ... |
29228b81063968ae3b89e98bf0c9af0c24c4376c9c36121eee26cfb00ae2f84d | MATLAB | 3,215 | 108 | %firws() - Designs windowed sinc type I linear phase FIR filter
%
% Usage:
% >> b = firws(m, f);
% >> b = firws(m, f, w);
% >> b = firws(m, f, t);
% >> b = firws(m, f, t, w);
%
% Inputs:
% m - filter order (mandatory even)
% f - vector or scalar of cutoff frequency/ies (-6 dB;
% pi rad / sample)
%
% O... |
a3407ab46e31961984ca3c5649b65c0697bcb709a59e5ad4c72396e38feb569d | MATLAB | 3,215 | 100 | clc;
clear;
atlas = cifti_read('C:\Users\lihon\Desktop\abcd_study\atlas\Schaefer\Schaefer2018_400Parcels_17Networks_order.dlabel.nii');
atlas_parcel = atlas.cdata;
atlas_label = unique(atlas_parcel(atlas_parcel>0));
num_parcel = length(atlas_label);
% load regional brain development (RBD) index patterns
K = 3;
cen_... |
ae5ebc4bde2c34bdf45835d8e321fefe4fb7097702d0c6aa4c0d92eaa231c028 | MATLAB | 3,215 | 84 | % POP_AVEREF - Convert an EEG dataset to average reference.
% This function is obsolete. See POP_REREF instead.
%
% Usage:
% >> EEGOUT = pop_averef( EEG );
%
% Author: Arnaud Delorme, CNL / Salk Institute, 22 March 2002
%
% See also: EEGLAB, REREF, AVEREF
% Copyright (C) 22 March 2002 Arnaud Delor... |
0ba28321ed8bdd86cf8fafe9689a842a3349c720546000ad022e23b1e5b15358 | MATLAB | 3,216 | 94 | function [K,dK] = covScale(cov, lsf, hyp, x, z)
% covScale - compose a covariance function as a scaled version of another
% one to model functions of the form f(x) = sf(x) f0(x), where sf(x) is a
% scaling function determining the function's standard deviation given f0(x)
% is normalised.
%
% The covariance function i... |
a74edf43bfe981cb6dfb3b557426089b2df1221eb43f3363c575806b34b35dea | MATLAB | 3,217 | 75 | function r=raeSpearmanCorr(x,y,toleratedStandardError)
% This function computes the "random-among-equals" Spearman correlation
% (RAE-Spearman r), which is the Pearson correlation applied to ranks with
% random ranks assigned to sets of entries in either variable that have
% equal values. In case there are no ties, th... |
bacd4e238b2b38c4c3c33b442a1e2e92d66e2c4523bff68d1f4a634dad973531 | MATLAB | 3,217 | 127 | function phiBC = cellBoundary3D(phi, BC)
% function phiBC = cellBoundary2D(MeshStructure, BC, phi)
% It creates the matrix of coefficient based on the BC structure provided
% by the user. It also generates the right hand side vector of the linear
% system of equations
%
% SYNOPSIS:
% phiBC = cellBoundary2D(MeshStruct... |
7a8c966aaca34fbcb808b0a87ac43e4da94368f4eb46af9427a3e11cf1db1d9e | MATLAB | 3,218 | 88 | function CS=surfing_nodeidxs2coords(cs1,cs2,idxs,linedef)
% maps vertex indices from two surfaces to coordinates
%
% CS=SURFING_NODEIDXS2COORD(C1,C2,IDXS,LINEDEF)
% INPUTS:
% C1,C2: 3xN coordinates for N nodes for the two surfaces.
% OPTIONAL INPUT
% IDXS: Px1 node indices to be used (default: all nodes)
%... |
ddd5d77d7acbc45517d6da87ad36dddbc54faa42ecd5dccb43318f0fd406c5c2 | MATLAB | 3,218 | 101 | function [ax,h]=suplabel(text,whichLabel,supAxes)
% PLaces text as a title, xlabel, or ylabel on a group of subplots.
% Returns a handle to the label and a handle to the axis.
% [ax,h]=suplabel(text,whichLabel,supAxes)
% returns handles to both the axis and the label.
% ax=suplabel(text,whichLabel,supAxes)
% returns ... |
fe5ed7bd48c865ae283bb23da18ed16ec72039f2f9f669007e5378d21274672a | MATLAB | 3,218 | 120 | function [WTOpt, WTMdl, BlkInf, Belief, Prior, Kappa] =...
GenerateSynthData_Bayes_BeliefState(params, ratTrial,...
noise_arg, gen_arg, noise_params)
%GenerateSynthData_Bayes_subopt_onlylambda - generates synthetic wait times
%for optimal Bayes model.
% Inputs:
% params - Parameter vector. [kappa_mi, kappa_hi... |
5c2913b85d367d1a59a4238921cf252d510737f17e1b028ebe2bd6ada7979e68 | MATLAB | 3,219 | 100 | function Y_rgb = sd_slice_to_rgb(Y, layer, settings)
% SD_SLICE_TO_RGB Converts 2D slice data to 3D RGB color coding
%
% DESCRIPTION
% This function uses the pr_scaletocmap function, which is part of SPM's
% slover toolbox, to convert image data to RGB color using the color coding
% scheme specified in the layer's co... |
204254afeaa00325a6b62d727c6df47bcbefbba7cd6077c196b6c6da88381c49 | MATLAB | 3,220 | 43 | matlabbatch{1}.spm.tools.physio.save_dir = {'physio_out'};
matlabbatch{1}.spm.tools.physio.write_bids.bids_step = 4;
matlabbatch{1}.spm.tools.physio.write_bids.bids_dir = {''};
matlabbatch{1}.spm.tools.physio.write_bids.bids_prefix = 'sub-control01_task-YOURTASK_run-1';
matlabbatch{1}.spm.tools.physio.log_files.vendor ... |
3928431f2364b47eb930f69938783d685c91c623bfa178348f33e566e865c658 | MATLAB | 3,222 | 94 | function grad = getPartialGradient(problem, x, I, storedb, key)
% Computes the gradient of a subset of terms in the cost function at x.
%
% function grad = getPartialGradient(problem, x, I)
% function grad = getPartialGradient(problem, x, I, storedb)
% function grad = getPartialGradient(problem, x, I, storedb, key)
%
%... |
4262b7b4c293a145b3b51b3b6393ea1ca77a182e7e9bf82244740955986b0fba | MATLAB | 3,223 | 68 | %% Scripts to calculate spectral entropy in different frequency bands
% Eline Schaft, 2025
% Code corresponding to Schaft et al. - Spectral Entropy Variability of
% intra-operative electrocorticography predicts outcome after epilepsy
% surgery in people with focal cortical dysplasia.
%% Set paths
addpath('\path... |
f146a48e7ffc4159e8bab2f7aa1eb8c5a603bb54946b58fc260df61db11b5705 | MATLAB | 3,223 | 118 | %% chi = NDI(localField,mask,voxelSize,varargin)
%
% Usage: chi = NDI(localField,mask,voxelSize,'b0dir',B0_dir,'weight',weight,...
% 'iteration',200,'stepsize',1,'tolerance',0.5);
%
% Input
% --------------
% localField : local (tissue) field
% mask : signal mask
% voxelSize : spatial ... |
57d655aab3e1095e92d7bfae01a7efc8a105b6266ce5628f708780df2e41016d | MATLAB | 3,226 | 80 | % Compute empirical p-vals under the null hypothesis that observed samples
% come from a given surrogate distribution. P-values for Type I error in
% rejecting the null hypothesis are obtained by finding the proportion of
% samples in the distribution that
% (a) are larger than the observed sample (one-sided test)
% (b... |
5985377e4207ec740f248f89355a1da520eb25f7b55d34b5f3b070a9ac29fdfc | MATLAB | 3,226 | 76 | %{
# quantal size in images
-> preprocess.Prepare
-> preprocess.Channel
-> preprocess.Slice
---
min_intensity : int # max value in movie
max_intensity : int # max value in movie
intensities : longblob # intensities... |
cd6b47ea76cb2fef7b024394a25e042e3a45fc746d3761c3a42a4a95e569daf3 | MATLAB | 3,226 | 84 | function [X, info] = dominant_invariant_subspace_complex(A, p)
% Returns a unitary basis of the dominant invariant p-subspace of A.
%
% function X = dominant_invariant_subspace(A, p)
%
% Input: A complex, Hermitian matrix A of size nxn and an integer p < n.
% Output: A complex, unitary matrix X of size nxp such that tr... |
48ca5e7561736959da4ba88f8d2adfe4de98dc221e92f90053c489323233d134 | MATLAB | 3,227 | 89 | function pathOut = tapas_uniqc_get_path(folder)
% Returns absolute paths for given folder
%
% pathOut = tapas_uniqc_get_path(folder)
%
% IN
% folder default: 'code'; returns full path of given folder within
% UniQC Repository
% options:
% 'code'
% 'utils'... |
032b30d8d30450fdc28aebc7cc9489992e3c61ff1b9ef017445f54d86f192d34 | MATLAB | 3,229 | 89 | function x = arg_extract(args,names,position,default)
% Extract arguments from Args; simple version, see notes.
% Value = arg_extract(Args,Names,Position,Default)
%
% In:
% Args : the varargin of the calling function
%
% Names : name by which the argument is referenced, or a cell array of names
%
% Position: the ... |
7174c9c8820e8dc0da0633bbd960f4e6e07760004e73f03f0000fbb0969e8c17 | MATLAB | 3,229 | 86 | %% read csv file
fileName = fullfile('data', 'Data S1.csv');
rawDataTable = readtable(fileName); % load Excel file
[input.Odor, ~, input.indOdor] = unique(rawDataTable.Odor, 'stable'); %ORN name
input.ORN = rawDataTable.Properties.VariableNames(4:end);
input.concList = rawDataTable.Concentration;
input.expID = raw... |
7f60155ca59759816586aeef64b7148f74aceee61a939dc4da95aa2abad0b18b | MATLAB | 3,230 | 82 | function plot(frameStream,cfg,varargin)
% Plot the contents of a McsFrameStream object.
%
% function plot(frameStream,cfg,varargin)
%
% Produces plots of the individual FrameDataEntities (one figure per
% entity).
%
% Input:
%
% frameStream - A McsFrameStream object
%
% cfg - Either ... |
dca9d1f2d368c23ac246d63f2f5c24dfddfbc5568a5f37c932fb3d4dff3a7a57 | MATLAB | 3,230 | 94 | %%
clear all
load fig3Fdata
cccc = get_seaborn;
f = figure('Position',[680 558 540 420]);
H1 = cplot(selected_resp_times,patwise_context_decoding,{'color',cccc{3}});
hold on,plot([-2000 1000],[.2 .2],'k--')
H2 = cplot(selected_resp_times,patwise_im1_decoding,{'color',cccc{8}});
H3 = cplot(selected_resp_times,pa... |
e1fb263fdc0789f88de45ba2bf831e991403c522fe96846405e100e45ba7580e | MATLAB | 3,230 | 120 | %% draw a regular polygon to approximate a circle:
nside=5;
pgon = nsidedpoly(nside);
%%
model = createpde("thermal","transient")
%%
model = createpde;
g = geometryFromEdges(model,@circleg);
pdegplot(model)
%%
mesh = generateMesh(model)
% ----------------
%% Create a decomposed geometry matrix, with line segments gi... |
d8a8c3c1e44107f4d1ab17d9d06b8ee67ebc7db835bef08830aabd2b5910bcb9 | MATLAB | 3,231 | 118 | function [dp,dpshuff,dp_raw] = dprime(hmat,mask1,mask2,varargin)
%dprime: discriminability in firing rate between two conditions
%
%INPUTS:
% hmat: (ns, nt) heatmat for a single neuron.ns trials. nt time points
% mask1: (ns,1) boolean for condition 1. true if trial satistfies cond.
% mask2: similarly to mask1. Ty... |
012c5f2097cd2ceb1f44e24916e3f5f157a2ce02cfa4ee1e3e820328b86cf906 | MATLAB | 3,232 | 90 | function this = load(this, fileName, varargin)
% loads object from struct in .mat-file, different variable names possible
%
%
% Y = MrCopyData()
% Y.load(filName)
% Y.load(filName, variableName)
%
% Options for variable name
% 1) variableName is given in varargin - load if available
% 2a) no variableName is... |
a7ab85c5d9a2c3065e0b8d56fb1448bbb452f7676c6a9d3a065a77646a3e24ee | MATLAB | 3,232 | 96 | function [stim_new] = add_covariate(cnew,stim_old,covops)
%adds a covariate to an existin stimulus sctruct
%inputs: cnew: new test covariate. size ntest x nt (if timde dep),
% or ntest x 1 if a constant covariate
% stim_old: old stim structure for testing/training data
% covops: options for c... |
34eadab30d5c8083b0d9a2832f8b542144ffe30119323c72646d0cc1ebcc155f | MATLAB | 3,236 | 115 | function PlotCCG(t,ccg,varargin)
%PlotCCG - Plot auto/cross-correlograms of point processes.
%
% USAGE
%
% PlotCCG(t,ccg)
%
% t time bins obtained using <a href="matlab:help CCG">CCG</a>
% ccg data obtained using <a href="matlab:help CCG">CCG</a>
% <options> optional list of p... |
fd7edc97502b14fb72a89c7608970a9a1a2aa99553683d9ef90e9f342570d016 | MATLAB | 3,237 | 73 | %{
# pixelwise cosine fit to directional responses
-> tuning.OriMapy
---
cos2_amp : longblob # dF/F at preferred direction
cos2_r2 : longblob # fraction of variance explained (after gaussinization)
cos2_fp : longblob ... |
9071f48e9d7ddbaea264c72898ecf25a1192d72a01ac70fb746877da3bf3416e | MATLAB | 3,238 | 108 | function [rows, cols, entries, rep, field, symm] = mminfo(filename)
%
% function [rows, cols, entries, rep, field, symmetry] = mminfo(filename)
%
% Reads the contents of the Matrix Market file 'filename'
% and extracts size and storage information.
%
% In the case of coordinate matrices, entries refer... |
a12751957f0a219c75f87f39d46bf578cc05a292932a82681a8e1ef17e28cb50 | MATLAB | 3,238 | 66 | function preprocess_nsd_TOF(subjix)
% function preprocess_nsd_TOF(subjix)
%
% <subjix> is 1-8
%
% Use ANTS to use a BSplineSyN to match the TOF image
% to the T1 1.0-mm resolution. We use some carefully crafted parameters.
%
% We then create a final 0.5-mm TOF image and some other resolutions (0.8 mm, 1.0 mm).
%
% No... |
49dd230bdccee295b3a451ce152709fafb011f9a557878ce59a5dd03667845b0 | MATLAB | 3,242 | 77 | %{
tuning.Cos2Map (computed) # pixelwise cosine fit to directional responses
-> tuning.OriMap
---
cos2_amp : longblob # dF/F at preferred direction
cos2_r2 : longblob # fraction of variance explained (after gaussinization)
cos2_fp ... |
f2de26505d9f46ac410245f7acea7a9ae80a065d024f2dea28465ae31edae436 | MATLAB | 3,242 | 104 | function analyzebehavior_prf_visualize(ppdirs,outputdir)
% load
alldata = {};
for p=1:length(ppdirs)
alldata{p} = load([ppdirs{p} '/behavioralresults_prf.mat']);
end
% internal constants
expectedtriggers = 188;
% look at tricky trigger stuff
totaln = [];
mdf = [];
realstart = [];
for p=1:length(ppdirs)
for q=1:l... |
1d79ad19aa5e393edb157f0b71ff134be160bf6e1d55c5ebbf1a6b2620801dde | MATLAB | 3,243 | 97 | function rebuild(obj)
%REBUILD Rebuild the internal data structures of a DagNN object
% REBUILD(obj) rebuilds the internal data structures
% of the DagNN obj. It is an helper function used internally
% to update the network when layers are added or removed.
varFanIn = zeros(1, numel(obj.vars)) ;
varFanOut = zero... |
d4364c867ea5a2b1311c44098a884e2d5bccd471d701eda1b10892b9c6bf8e91 | MATLAB | 3,243 | 104 | function check_func_imgs(func_imgs)
% _
% Checks functional image files before or after preprocessing
% FORMAT check_func_imgs(func_imgs)
%
% func_imgs - an R x 1 cell array where each entry is the
% filepath to a 4D NIfTI filepath from one run
%
% FORMAT check_func_imgs(func_imgs) loads the imag... |
022bf01d02ebbae18dfad6478452045ab5e66cdb8ac5c8b183aafc4e6df403f7 | MATLAB | 3,244 | 102 | function MS = createMesh2D(varargin)
% MeshStructure = buildMesh2D(Nx, Ny, Lx, Ly)
% MeshStructure = buildMesh2D(facelocationX, facelocationY)
% builds a uniform 2D mesh:
% Nx is the number of cells in x (horizontal) direction
% Ny is the number of cells in y (vertical) direction
% Lx is the domain length in x directio... |
85e9c1947e6e9a05a8a5402e125f64eb96b22bb91b6e3495d162d7f2f1305b54 | MATLAB | 3,244 | 102 | function m = Bright(n,varargin)
%Bright - Bright colormap (similar to HSV or JET, but brighter).
%
% USAGE
%
% m = Bright(n,<options>)
%
% n optional number of rows in output matrix (default = 100)
% <options> optional list of property-value pairs (see table below)
%
% ==================... |
8d80f6fd59859eab80fa2d6615f54512696e17871efb39803631365fbe4a8e7d | MATLAB | 3,244 | 90 | %% Testing the ensembles detection method using subsampling
% 1.- Generating synthetic data
T = 50000;% recording time
N = 300; % number of neuron
nens = 10; % number of ensembles
fr = 0.2; % maximal neuron firing rate
ncellsperens = repmat(N*0.05,[1 nens]); % cells per ensemble
ntimesperens = repmat((0.7)/nens,[1 nens... |
a763270db1921e1b2bfe8d69fc69e2ede97aafb3d7f0c5fbcd2be00a2367c49b | MATLAB | 3,244 | 97 | function [correlation,x,y] = tapas_physio_corrcoef12(x,y, isZtransformed,precisionThreshold)
% computes correlation coefficient (i.e. entry (1,2) of correlation matrix)
% quickly between two time series
% The speed-up is mainly due to in-line re-implementation of costly
% statistical functions, i.e. mean, std, cov, and... |
a81523980d1768bc43071d012fc34fd7de492cd8765e1f635730627829887f71 | MATLAB | 3,244 | 98 | % ICAACT - compute ICA activation waveforms = weights*sphere*(data-meandata)
%
% Usage: >> [activations] = icaact(data,weights,datamean);
%
% Inputs:
% data = input data (chans,frames)
% weights = unmixing matrix (RUNICA weights*sphere)
% datamean = 0 or mean(data') (default 0);
%
% Note: If datame... |
09080624077c43fb89eb1634b1a1f759c6bd613cdfe19f94b4a12b83fcd4b1df | MATLAB | 3,246 | 90 | function [sensorDataSumGPU, p_max_all_cut, target_point] = forwardSimulation(medium, Element, sim_vol, kgrid, sensor, input_args)
%% Forward Simulation - Single Emission, Single Focusing
% One transmit with all array elements focusing at a single target point
Nx = kgrid.Nx;
Ny = kgrid.Ny;
Nz = kgrid.Nz;
% Element pos... |
3cf4da40843565b70974edab479451d03ebd39dbf4c68cda652e75240520a742 | MATLAB | 3,246 | 75 | function output = loadAllUnitData()
%% LoadAllUnitData
% Load all unit data with corresponding behavior data
%% Define table variable for output
output = table('Size',[0, 9],'VariableTypes',["string", "string", "string", "double", "cell", "cell", "cell", "cell", "cell"],...
'VariableNames', ["Subject", "Session", ... |
4b0c29b3a3c6df2b344f116b3bf6d9ea4b5b19cfef332b3b8a9d2e5ccc545f6b | MATLAB | 3,247 | 127 | % test the ICLabel EEGLAB plugin
function run_tests()
%% set up
% load test data
EEG = pop_loadset('tests/eeglab_data.set');
% calculate sphereing matrix
try
icasphere = pca(EEG.data')';
catch
% BCILAB (unfortunately) shadows pca from the stats toolbox.
flist = which('pca.m', '-all');
fpath = flist{fi... |
0a5711596adde5b3968deb5b65bea2e931859135099822463541491194e71143 | MATLAB | 3,248 | 70 | %% cluster based rois
% follow the methods here to manually find and save your clusters
% marsbar and spm save a .mat file
% this script reads the .mat file and the base space image that you select
% manually to create rois, based on the resolution of the image you cretaed
% step 1:
% we can open marsbar and choose th... |
7db0ee453b7c60d78c894a0e558fc636c7923181aea138234cfc4b887f48e5a4 | MATLAB | 3,248 | 88 | function [Calls,audiodata,ClusteringData] = loadCallfile(filename,handles)
data = load(filename);
Calls = table();
audiodata = struct();
ClusteringData = table();
%% Unpack the data
if isfield(data, 'Calls')
Calls = data.Calls;
elseif nargout < 3 % If ClusteringData is requested, we don't need Calls
warning(... |
ace279a6dd93068d49e7c93e7b8816fd281b441cc0c0b566e000f8714bb21993 | MATLAB | 3,249 | 94 | function fear_frzTrigTripleAct_optMeanShift(basename,varargin)
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
param.binSize=0.02;
param.halfWindow=5;
param.varName='frzTrigCoactChamber';
param.saveFile=[basicMetaData.AnalysesName '-frzTr... |
b8c92e8a6da351fb3e54c7f71759694ed5a086d302642d7ca25ca0790b16ce8f | MATLAB | 3,250 | 65 | function osp_pop_whichcorrOvCorr_Call(src,~,gui)
%% osp_pop_whichcorrOvCorr_Call
% This function is triggered when the correlation overview choice popup menu is changed. It refreshes
% the figure.
%
%
% USAGE:
% osp_pop_whichcorrOvCorr_Call(src,~,gui);
%
% INPUT: src = handle of the fit tabs
% ... |
26918e1f36e8c3d3f3e834dd3a5a8e7539c1f574d712a834e54ed7cd197e271f | MATLAB | 3,252 | 89 | function c = tapas_rw_binary_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the Rescorla-Wagner (RW) learning model for binary inputs.
%
% The RW model was introduced in :
%
% Rescorla, R. A., and Wagner, A. R. (1972). "A th... |
18c7fd5dabbc6da9d0a73f80a5fde3923957dd053a10cc9dd293bebc9f04912a | MATLAB | 3,253 | 88 | function [node,elem]=meshcheckrepair(node,elem,opt,varargin)
%
% [node,elem]=meshcheckrepair(node,elem,opt)
%
% check and repair a surface mesh
%
% author: Qianqian Fang, <q.fang at neu.edu>
% date: 2008/10/10
%
% input/output:
% node: input/output, surface node list, dimension (nn,3)
% elem: input/output, s... |
9273b344af94bc6f0bd16a07eafb653728881f08a5eae33a57180a14bfa35f44 | MATLAB | 3,253 | 83 | function [nirs, windowMotion, windowTimes, windowCount, windowSizeSamples] = pruneWithCV(nirs, params, numChan, arrayChans)
% Prunes channels using coefficient of variation (CV) thresholds. Analyses
% data in windows, marks motion artifacts, and calculates CV values to
% determine which channels should be retaine... |
9d5d0288559173d16dfb9cda984566bb1488bd97a2d86917ed1d9ca4a765104a | MATLAB | 3,253 | 125 | function OUT = fuzzy_conf_cluster(im,xyz)
% OUT = fuzzy_conf_cluster(im,xyz)
%
% tor wager
%
% input:
% this function takes a set of indicator vectors (im)
% coded as 1's and 0's, and a list of varables (xyz)
%
% output:
% a permutation test for whether there are separate regions
% of the space defined by the colum... |
e1c4b0bee6b51cec7628ea32f38410d7b0ee52fda3d40d60d605b068db46b79c | MATLAB | 3,256 | 119 | function FigureS8(datadir, codedir)
%FigureS8 - Model comparison for wait times favors inferential over
% retrospective model, but does not distinguish between inferential and
% belief state models
% datadir = directory of dataset
% codedir = director of code
%% Set up paths
s = pathsep;
pathStr = [s, path, s];... |
837a8604ef6e3bce8f345fd3f1520a62a6b206813e95aa63c6aa0e9402d049bb | MATLAB | 3,257 | 92 | % checking subjects responses during the fMRI session
% both catch questions and last question in each block
clear all
close all
clc
exp_root = 'C:\Users\User\Documents\fMRI_EXP\';
data_path = fullfile(exp_root, 'alon', 'beh');
n_catch = 5;
num_subjects = 28;
num_runs = 4;
num_maps= 4;
num_blocks = 5;
all_responses ... |
311179878bb3af158ee342d5032210497e1e24f197e70fb5d768b6e4e304651f | MATLAB | 3,258 | 104 | function ft_regress_physio(input, regressor, TR, cutoff_highpass, ...
path_output, cleanup)
% Regress physio
%
% ft_regress_physio(input, regressor, TR, cutoff_highpass, ...
% path_output, cleanup)
%
% Inputs:
% input - input time series
% regressors - multiple regressors as separate columns in a ... |
9635eebc5fbfec71a7f00302b38a64cdec0fae488966eb8b71cc194aa0bd345a | MATLAB | 3,259 | 92 | function statsfun = statsfunhelper(inp1, inp2)
% Helper tool to create a statsfun for the options structure of solvers.
%
% function statsfun = statsfunhelper(name, fun)
% function statsfun = statsfunhelper(S)
%
% Usage with (name, fun):
%
% Input 1: name is a string which is a valid field name (no spaces, starts
% wit... |
980f63a8016b587a55376077ed626e4e9138168c3697fff171547568706f77f1 | MATLAB | 3,259 | 94 | function varargout = openvibe_mat(filename, hdr, begsample, endsample, chanindx)
% OPENVIBE_MAT reads EEG data from MATLAB file with OpenVibe data that was converted
% according to http://openvibe.inria.fr/converting-ov-files-to-matlab/
%
% Use as
% hdr = openvibe_mat(filename);
% dat = openvibe_mat(filename, hdr,... |
7d4e9e80df72101b3e725883ac9070dff6f75e37a4b629b315d5229fb81c87ac | MATLAB | 3,261 | 92 | function plotApertureEventHists(kinematics)
% Plot the histograms of aperture-related event timings across all mice
% Figure
[~, tl] = fig([2,1]);
% Params
liftCol = [130, 235, 118]/255;
collectCol = [72, 188, 255]/255;
extendCol = [230, 40, 151]/255;
bins = min([kinematics(find([kinematics.nPeaks] == 1)).collectTime... |
a1e42332a3db87209d819389d6b34c38606507ed5d27976fb5b801e19d28ae5f | MATLAB | 3,261 | 110 | function [d, nfnn] = MS_unfolding(y,th,de,tau)
% Estimate the minimum unfolding dimension by calculating when the
% proportion of false nearest neighbours if first below th.
%
% The number of false nearest neighbours are calculated for the
% time series y embedded in dimension de with lag tau.
%
% For each pair of valu... |
29a69bb7c1e0f0f46f6e16fe6f31ca41a986dae6b8d606a9c400bb0b49c0ee18 | MATLAB | 3,262 | 99 | % GAUSS3D - generate a 3-dimensional gaussian matrix
%
% Usage:
% >> [ gaussmatrix ] = gauss2d( nX, nY, nZ);
% >> [ gaussmatrix ] = gauss2d( nX, nY, nZ, ...
% sigmaX, sigmaY, sigmaZ, ...
% centerX, centerY, centerZ, mask)
%
% Example:
% >> gauss3d(3,3,3); ... |
91f6cc0e3d2594473ec66ddd065f5a375c320a0efa9f3cabbaff8f265baed099 | MATLAB | 3,262 | 92 | % POP_DELSET - Delete a dataset from the variable containing
% all datasets.
%
% Usage: >> ALLEEG = pop_delset(ALLEEG, indices);
%
% Inputs:
% ALLEEG - array of EEG datasets
% indices - indices of datasets to delete. None -> a pop_up window asks
% the user to choose. Index < 0 -> it'... |
173294b939a6479e09913dc385f4f6adc47a5c8f0148f29a4af51abc0b2fb03e | MATLAB | 3,263 | 77 | function outputMeasure = BF_LossFunction(yTest,yPredict,whatLoss,classLabels)
% BF_LossFunction gives a measure of classification performance
%
% All labels are expected to be integers, ranging from 1 to the total number
% of classes in the classification problem
%
%---INPUTS:
% yTest, the test set labels
% yPredict, t... |
2cfe51b2bdb9b785f8b82520204bd254ec4141de298d132dc6e6f236892303a5 | MATLAB | 3,265 | 82 | % -*- mode: matlab; -*-
% Neurophysiology Analysis Toolkit http://sourceforge.net/projects/nphys/
% Authors : Chris Higginson (original author) and Josh Tasman
% Copyright (C) 2002-2005 by the authors and the Mizumori Lab
% (at the University of Washington, Seattle)
%
% This program is free software; you ca... |
4c717c577acd74e1a694137e643e6680499a697d788353fcf7e4becebc56febf | MATLAB | 3,265 | 68 | % Optimize inducing inputs for the VFE approximation (not FITC).
%
% One can perform a gradient-based optimisation of the inducing inputs xu by
% specifying them via hyp.xu rather than through {@apxSparse,cov,xu}.
%
% An alternative way of optimising xu (in order to overcome local minima) is
% to simply compute the exp... |
a7b4469cc4c7588a1e81ac427afde00370996ea28eebbae78fef1f64119c1e71 | MATLAB | 3,265 | 105 | function ni = dtiWriteNiftiWrapper(imArray, matrixTransform, filename, sclSlope,...
description, intentName, intentCode, freqPhaseSliceDim, sliceCodeStartEndDuration, TR)
% See also niftiGetStruct and niftiCreate
% We think this should go away and be replaced by a proper niftiCreate
%
% dtiWriteNiftiWrapper (imArra... |
d0a0821ccc4698720cf2825c723b59f5f7b90810aca060e3c30131fd5b1bcd12 | MATLAB | 3,265 | 79 | %%
Bytediv = 4; %% number of bytes to average over
nn = -1 ; %% sets the tetrode you want to investigate
samplingRate = 30000;
start = 1; %% sample
stop = 900; %% sample
fac = 1.5;
min_length_of_burst = 2;
local_length = 0;
surprise_cutoff = 5;
continu... |
078020fc80663d244e2c7d56b5baf02ee7950b29cf069ae950714a1d372e0e65 | MATLAB | 3,267 | 95 | function [stepsize, newx, newkey, ssstats] = ...
stepsize_sg(problem, x, d, iter, options, storedb, key) %#ok<INUSD>
% Standard step size selection algorithm for the stochastic gradient method
%
% Given a problem structure, a point x on the manifold problem.d and a
% tangent vector d at x, produces ... |
f8c1c80e3f49b11ddd4d490acec6baeafa215816f13f49387310c06c5e0a1e0e | MATLAB | 3,267 | 84 | classdef toolsFillSmallHolesTest < matlab.unittest.TestCase
%TOOLSFILLSMALLHOLESTEST Unit tests for petraToCT.tools.fillSmallHoles.
%
% DESCRIPTION:
% Verifies that fillSmallHoles fills enclosed holes whose voxel
% count is at most ceil(radius2measure(MaximumHoleRadius, 3)) and
% lea... |
c486b1799a44b7de33bccadfbedde2fe86a6a76ff6d52daad86011698f7d2de1 | MATLAB | 3,269 | 127 | function [xvec,spikes_binned] = binspikes(spiketimes, handles, alignment,dt,tmin,tmax,wndw,varargin)
%BINSPIKES put spikes into equalbins
%
%input:
% spiketimes: long array of spike timings
%
% handles: handle of trial timings
%
% alignment: string handle for what event to be aligned
%
% dt: bin size (... |
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