sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
655e2925c5554808ec1d1e178980a15990f51945850db7472966486ac678d53f | MATLAB | 6,568 | 201 | %IM2GIF Convert a multiframe image to an animated GIF file
%
% Examples:
% im2gif infile
% im2gif infile outfile
% im2gif(A, outfile)
% im2gif(..., '-nocrop')
% im2gif(..., '-nodither')
% im2gif(..., '-ncolors', n)
% im2gif(..., '-loops', n)
% im2gif(..., '-delay', n)
%
% This function converts a mu... |
70117497e91f3935ef7e39bc3871f8fe6e650d480dda2bee13a337267ce0c37f | MATLAB | 6,569 | 153 | % STD_PREPARE_NEIGHBORS - prepare Fieldtrip channel neighbor structure.
% Only prepare the structure if necessary based
% on statistical options in STUDY.etc.statistics.
% Use the 'force' option to force preparing the
% ... |
614664a984b7021f9af9d3922c5e308f43ac0b7fa3bc17bcd2982c4177f8cd28 | MATLAB | 6,572 | 221 | % Bang et al (2020) Private-public mappings in human prefrontal cortex
%
% Reproduces Figure 2
%
% Visualises behavioural data for fMRI session and performs associated
% regression analyses
%
% Statistical tests can be reproduced by applying one-sample t-tests to
% regression betas: e.g. [H,P,CI,STATS]= ttest(beta.con... |
d8393e67437b939389cb1a31a082318e52f5bf88f215777cf3f9a602f38af241 | MATLAB | 6,573 | 261 | function Mn = powermanifold(M, n)
% Returns a structure describing a power manifold M^n = M x M x ... x M.
%
% function Mn = powermanifold(M, n)
%
% Input: a manifold structure M and an integer n >= 1.
%
% Output: a manifold structure Mn representing M x ... x M (n copies of M)
% with the metric of M extended element-... |
72ebdb6da4e1a9190fc0e7dde18ca667614f2c1429e241e204413e40c35bb19f | MATLAB | 6,574 | 274 | function [ err ] = mmwrite(filename,A,comment,field,precision)
%
% Function: mmwrite(filename,A,comment,field,precision)
%
% Writes the sparse or dense matrix A to a Matrix Market (MM)
% formatted file.
%
% Required arguments:
%
% filename - destination file
%
% A - sp... |
829177dff56a9c972c6cbc33ab1f0950a0e98885c08098a07fb333bdfc7aa93b | MATLAB | 6,577 | 159 | function [BASISdiff] = osp_addDiffMMPeaks(BASISdiff,BASISoff,fitOpts)
n = BASISdiff.n;
sw = BASISdiff.spectralwidth;
Bo = BASISdiff.Bo;
centerFreq = BASISdiff.centerFreq;
% The amplitude and FWHM values are determined as for the LCModel and
% TARQUIN algorithms (see Wilson et al., MRM 2011).
... |
0910cb5073c3edf9abd110d937948260c83171ce479554a76310ea2e8ec9cf85 | MATLAB | 6,581 | 159 | function sii = task_gaitERSP_cluster(PATH, cfg, fieldName)
PATHIN = PATH.ICAdecomp;
PATHOUT = PATH.(fieldName);
% load clustered study
[STUDY ALLEEG] = pop_loadstudy('filename', [cfg.study_name, '_',fieldName, '.study'], 'filepath', PATHOUT);
CURRENTSTUDY = 1; EEG = ALLEEG; CURRENTSET = [1:length(EEG)];
% ide... |
e4d9c9dce11148e95a0eae75ad8a8d68deb5307cd92f5aeb68489615171462e8 | MATLAB | 6,583 | 113 | % check folder
eeglab
if ~exist('n400.study', 'file')
error([ 'You must change the path to the folder containing the data to run this script' 10 ...
'Download the data from https://eeglab.org/tutorials/tutorial_data.html (5 subject study)' ]);
else
filepath = fileparts(which('n400.study'));
end
%% impo... |
927e4c827048dc62186aa11b3ba4a50da781c7c73dae2382c7b4e10f20331453 | MATLAB | 6,584 | 176 | function res = permutation_null_brain(img_data, geneset, expressions, gene_symbols, background)
% PERMUTATION_NULL_BRAIN(...) performs permutation testing to examine
% whether imaging profiles associate with gene expression profiles, based
% on the null-brain model (where random genes were selected from
% brain-expres... |
55f728101fb8c89519edcbdf89f744d873f261c1ec8b82f0d12f3ea291ab0591 | MATLAB | 6,585 | 185 | function net = cnn_imagenet_deploy(net)
%CNN_IMAGENET_DEPLOY Deploy a CNN
isDag = isa(net, 'dagnn.DagNN') ;
if isDag
dagRemoveLayersOfType(net, 'dagnn.Loss') ;
dagRemoveLayersOfType(net, 'dagnn.DropOut') ;
else
net = simpleRemoveLayersOfType(net, 'softmaxloss') ;
net = simpleRemoveLayersOfType(net, 'dropout')... |
77b3531f164c55be6fa85badf0a9483421e326bf66117f45d4534a2f36a43f9a | MATLAB | 6,589 | 217 | function detectTTLpulses(basicMetaData,varargin)
paramNames={'fileType','lfpFile','samplingRate','nCh','nSample',...
'bufferSize','threshold','minInterval','minDuration',...
'evtFileName','saveFileName','chList','chName','detectionintervals',...
'varName'};
%default values
p... |
50e261473f4273a31726dc4bd1c102b82abb0f6860ecf590dabb7c27cd50cf21 | MATLAB | 6,590 | 176 | function verify_cli()
% verify_cli is a test script to validate run_NBSPredict_cli function.
% It tests input validations, required parameter check, default overrides,
% and backward compatibility with pre-built config files.
fprintf('===============================================\n');
fprintf(' Starting run_NBSPre... |
5978cf63ecef2fca1f6a1ab15e615d8b2cf54db9cb84b23f615ac20688a3b161 | MATLAB | 6,595 | 194 | function [out_proj,variance_proj,cfg] = mante_proj(dat,cfg)
% [out_proj,variance_proj,cfg] = mante_proj(dat,cfg)
if nargin < 2
help mante_proj
error('missing input arguments!')
end
ntrl = size(dat,1); % number of timepoints
nsens = size(dat,2); % number of M/EEG sensors
ntime = size(dat... |
78b8d3545d4b8cd42f07ec10d838b99897d3fe72128dd6312919828f4638aeeb | MATLAB | 6,596 | 167 | function out = PD_PeriodicityWang(y)
% PD_PeriodicityWang Periodicity extraction measure of Wang et al. (2007)
%
% Implements an idea based on the periodicity extraction measure proposed in:
%
% "Structure-based Statistical Features and Multivariate Time Series Clustering"
% X. Wang and A. Wirth and L. Wang
% Sevent... |
d258a5d54954b8924ab114f6678aa5763fe20edb2ae4081495481bf30f5c7a63 | MATLAB | 6,596 | 207 | function shuffle_icaReacCCG_dropEvt_cueRet(basename)
tempIdx=2;
[rootPath,sesName,~]=fileparts(basename);
fprintf('%s load files for %s\n',datestr(now),sesName);
temp=matfile(fullfile(rootPath,'data',[sesName '-icaReac.mat']));
icaReac=temp.icaReac(1,tempIdx);
load(fullfile(rootPath,'data',[sesName '.sleepstate.sta... |
efd8a7504516a7dd34a39b224e81b480e4a99503d841409c8d00ae7decc3c86d | MATLAB | 6,596 | 172 | function plot_example_choice_mode_activity_RNN
close all
clear all
clc
% Plot choice mode activity of RNNs with distractors.
rng(0)
% Set parameters for example RNNs.
RNN_variable = get_example_choice_mode_activity_RNN;
% Control.
left_choice_mode_std_norm = RNN_variable.control.choice_mode.left_choice_mode_std_n... |
5dccd2fdd0e350b646213813c4153d1e260c5f12f7f5e18ba8d7576cb589e22e | MATLAB | 6,597 | 213 | %% mapVBVD - a short Tutorial
% Philipp Ehses <philipp.ehses@tuebingen.mpg.de>
% Created: September 2016
%% Parse twix file
% The basic idea of mapVBVD is to divide reading the data into two parts:
% First, parsing the twix file and saving all relevant information from the
% 'measurement data headers' (mdh) for each a... |
e6798a95b4ec27c05722afdf2dc27d426fa50401fe703a68079bb1752da3e28e | MATLAB | 6,601 | 170 | % plot accuracies
% NOTE THE ORDER OF SUBJECTS IN ALL THE TABLES
subList ={'001','002','003','004','005','006','007','008',...
'009','010','011',...
'013','014','015','016','017',...
'pil001','pil002','pil004','pil005'};
vis =readtable("visAccu.xlsx");
hu =readtable("ha... |
78966ed1327e1bda802d9afdc75a2cc2d87a5f4a39eb7a983877f25bd59d4a0f | MATLAB | 6,603 | 196 | function fear_getHFO_spike_PETH(basename)
% basename='~/data/Fear/triple/innis190601/innis190601';
load([basename '.basicMetaData.mat'])
if ~exist([basicMetaData.Basename '.amyHFO.events.mat'],'file')
warning('hfoTrigHist.mat was not generated since %s not found',[basicMetaData.Basename '.amyHFO.events.mat'])
... |
838caee8df0dd2a41e8c4fff84b0039f07cb025e49e2a76db45b36143d8cf79a | MATLAB | 6,603 | 189 | function [C2,cfg] = mahal_lin_trialwise(dat,theta,cfg)
% [C2,cfg] = mahal_lin_trialwise(dat,theta,cfg)
% authors: M Stokes, E Spaak, N Myers
if nargin < 2
help mahal_lin_trialwise
error('missing input arguments!')
end
ntrl = size(dat,1); % number of timepoints
nsens = size(dat,2); % n... |
2935eede3e03da5d379ff3d31a9eb54ef921dc6e7f95694fc4011deb67ae45df | MATLAB | 6,604 | 139 | %% BipolarCorr = BipolarEddyCorrect(Bipolar,unwrap)
%
% Input
% --------------
% bipolarCplxME : complex-valued multi-echo GRE data with bipolar readout
% unwrap : phase unwrapped method (optional)
%
% Output
% --------------
% bipolarCorr : eddy current corrected data
% FIT3D : bipolar readout induced... |
d1ace5ba5812eba672f7485bdb2fe524b688ac286c16e6790730cba0908205e5 | MATLAB | 6,610 | 149 | function out = SP_SpectralTimeFreq(y, numWindows)
% SP_SpectralTimeFreq Time-varying spectral statistics from a spectrogram.
%
% SP_Summaries computes statistics from a single, static spectral estimate of
% the whole time series. This function instead divides the series into
% overlapping windows and tracks how the sp... |
952776a68ff4dcb2a0504589a2ca2667a8282af2fa93a9894e4e39cd947c7a2f | MATLAB | 6,613 | 219 | function [lambda,p,ci,stats,tbl,dist] = permumanova1(x,group,varargin)
%PERMUMANOVA1 Permutation-based one-way multivariate ANOVA and rank MANOVA.
% LAMBDA = PERMUMANOVA1(X,GROUP) performs a permutation-based one-way
% multivariate analysis of variance (MANOVA) for comparing the means of
% two or more groups of... |
119f1597ee042a94dfa3b847b4a77193df0762e3b90ec48aa455af23cc7ec2f1 | MATLAB | 6,617 | 153 | function TS_Init(INP_ts,whatFeatureSet,beVocal,outputFile)
% TS_Init Produces a formatted HCTSA .mat file from input files
%
%---EXAMPLE USAGE:
% Initiate an HCTSA.mat file on a custom time-series dataset using the hctsa
% feature library, using a formatted input file, 'my_TS_INP_file.mat'
% >> TS_Init('my_TS_INP_file... |
cb51053178f53ebe62ed3fa5a506937878c5bb1a80ac49c2652a0730cd5818b1 | MATLAB | 6,617 | 214 | %RadialMazeVisits - Compute distribution of successive visits in radial maze.
%
% In order to detect stereotypic egocentric strategies that a rat could employ to
% solve a radial maze task, this function determines the distribution (over trials)
% of successive arm visits: if the rat does follow an egocentric strateg... |
4df0b0f5964eb77d46c892988d512d1558c3d88a0901bee1acc484a784d03edd | MATLAB | 6,618 | 209 | %
% Regress photoplethysmography data from the fNIRS signal.
%
% Parameters
% ----------
% participant: integral number
% Participant to process.
% type: "HbO" or "HHb"
% Type of data
%
% Outputs
% -------
% The outputs are saved as .csv files.
%
% Author
% -------
% Ségolène M. R. Guérin
% March 11, 2025
% URePS... |
905d4c63e0c42e2c24fdee84952139cf837047ea9df76a60d1f235c43e9d625b | MATLAB | 6,622 | 178 | function [rvt, verbose] = tapas_physio_rvt_hilbert(fr, t, sample_points, verbose)
% Computes respiratory volume per unit time (RVT) from filtered time series
%
% RVT is computed by calculating the instantaneous amplitude / frequency
% of the breathing signal via the Hilbert transform, as proposed by
% Harrison et al.
%... |
e81befdc7002ece7af38d2335194ee6a559bf223d26b0bfc880a8e0327b2f5c9 | MATLAB | 6,622 | 172 | function positions = GetPositions(varargin)
%GetPositions - Get position samples.
%
% USAGE
%
% positions = GetPositions(<options>)
%
% <options> optional list of property-value pairs (see table below)
%
% =========================================================================
% Properties Valu... |
5b3d21134b48649b6d0930577b25c3d3b35411f4882231b652288a13ed4a4002 | MATLAB | 6,627 | 198 | clear all
close all
clc
% Calculates subspace generalization between simulated voxels.
% Each voxel is an average over simulated grid cells according to their
% phase. grid cells with closer phases are averaged within the same voxels.
global dv_voxels r_voxel a_noise
exp_root = 'C:\Users\User\Documents\fMRI_EXP\';
... |
0ecd75ab149cbe9deb42008f9335b4e34bd88c597903a4ced191081aa3d078a5 | MATLAB | 6,630 | 216 | function M = obliquecomplexfactory(n, m, transposed)
% Returns a manifold struct defining complex matrices w/ unit-norm columns.
%
% function M = obliquecomplexfactory(n, m)
% function M = obliquecomplexfactory(n, m, transposed)
%
% Oblique manifold: deals with complex matrices of size n x m such that
% each column has... |
d7d14e1246cadbb0eabc165395bc643bd15e8c47d5dbc90f940422db0fc99a87 | MATLAB | 6,631 | 177 | function info = step1RunSearchlightProprioception(opt)
% Step 1 : running searchlight (SL)
% get the smoothing parameter for 4D map
funcFWHM = opt.funcFWHM;
% set output folder/name
savefileMat = fullfile(opt.pathOutput, ...
[opt.taskName, ...
'_SL_Prop... |
38108600c239731699f033f195dff15f21ff91f0ab316cfeac059be6b2fc322b | MATLAB | 6,632 | 177 | function info = step1RunSearchlightAcrossHandAnat(opt)
% Step 1 : running searchlight (SL)
% get the smoothing parameter for 4D map
funcFWHM = opt.funcFWHM;
% set output folder/name
savefileMat = fullfile(opt.pathOutput, ...
[opt.taskName, ...
'_SL_Acro... |
b3705301b565a3653236e6ef7dbe3b3f4166ecf2812100e2bab9331b7a2839a7 | MATLAB | 6,634 | 226 | function out = io_loadspec_lcmraw(rawFile)
%% LCMparam = io_loadspec_lcmraw(rawFile)
% This function reads a LCModel-formatted .RAW file.
%
% USAGE:
% LCMparam = osp_readlcm_raw(rawFile)
%
% INPUTS:
% rawFile = LCModel .RAW data file
%
% OUTPUTS:
% % out = Input dataset in FID-A s... |
0d8a1b6a3e6f566fba939b3336076c5cffdc6bf2798c2e66e119821fb423ce8c | MATLAB | 6,637 | 177 | function info = step1RunSearchlightAcrossHandExt(opt)
% Step 1 : running searchlight (SL)
% get the smoothing parameter for 4D map
funcFWHM = opt.funcFWHM;
% set output folder/name
savefileMat = fullfile(opt.pathOutputTemp, ...
[opt.taskName, ...
'_SL_A... |
4bf56479c738a34449971690ae455c26a81be68063171fdf6e981897af63593d | MATLAB | 6,637 | 212 | function [newcl,DB] = database2clusters(db_mat,clusters,mydist)
% function [newcl,DB] = database2clusters(db_mat,clusters,mydist)
%
% tor wager
%
% This function turns a database file (stored as variables in a .mat file)
% as created with read_database.m
% into a clusters structure, by finding the points
% that fall wi... |
a6b087349854a21d3231ce171721ad1e6681f26efc53f2cb60c57883340a0201 | MATLAB | 6,638 | 109 | clc
clear all
close all
whicheye = input('Please enter left or right to choose eye: ','s')
rawfilepath = input('Enter raw_data location(such as /home/raw_data): ', 's');
processedpath = input('Enter processed_data location(such as /home/processed_data): ', 's');
% whicheye = 'left'; % choose which eye to start tracking... |
b32356e5b1980dc6e72a264f0708ca8e71b3d57bcc0eedbe97171bebe47174d0 | MATLAB | 6,638 | 197 | % openbdf() - Opens an BDF File (European Data Format for Biosignals) in MATLAB (R)
%
% Usage:
% >> EDF=openedf(FILENAME)
%
% Note: About EDF -> www.biosemi.com/faq/file_format.htm
%
% Author: Alois Schloegl, 5.Nov.1998
%
% See also: readedf()
% Copyright (C) 1997-1998 by Alois Schloegl
% a.schloegl@ieee.org
% ... |
5ed7d87a285f52d7ec9130117d525489b623bf1df4526a11eaf09711a6714b69 | MATLAB | 6,639 | 152 | % INSTALL Installs the hctsa code package from scratch.
%
%---INPUTS:
% silentInstall, (binary) set true to run non-interactively (no 'Press any
% key to continue' prompts), e.g., for scripted/CI installs.
% Defaults to false.
% ----------------------------------------------------------... |
60391af50cfe528c99eb946b55c2d7b7117c1c6ac6905523a2ba54cd3e422af0 | MATLAB | 6,640 | 193 | function metrics = evalRegQualityMetrics(frameFixed, frameRegistered, varargin)
% Evaluation of the image registration performance between two images,
% frameMoving and frameFixed.
%
% SYNTAX:
% metrics= evalRegQualityMetrics(frameFixed, frameRegistered)
% metrics= evalRegQualityMetrics(frameFixed, frameRegistered, 'Ba... |
76c746ecea0d264fb0960eb69cdc76fe0596132b4d9ead09a247a99837be5ed6 | MATLAB | 6,650 | 197 | function plotFigure4_TCA(ephysPath, codePath, processedEphysPath)
% Plot figure 4. Process and plot heatmat of neural responses based on TCA model
% Process and plot responses to 20ul trials pre- and post-incongruent trial
% by TCA cluster
s = pathsep;
pathStr = [s, path, s];
onPath = contains(pathStr,...
codePat... |
2ae5b88f61e5e80cf866b18331786394aa3a63777ab3770ff5cdc480a6e18155 | MATLAB | 6,651 | 174 | function [density,xdata,sampleinfo] = support_func_event_density(trl,ttime,twin,tstep)
%% ########################################################################
% - Plot density of events
% #########################################################################
% Determine density of events per twin [s]
%
% -------... |
4b6bb315df1d9caefd5b1f1342a9598aaee70e820a68a016cfe67957430380f2 | MATLAB | 6,652 | 168 | function [ClusteringData, clustAssign, freqRange, maxDuration, spectrogramOptions] = CreateClusteringData(handles, varargin)
%% This function prepares data for clustering
% For each file selected, create a cell array with the image, and contour
% of calls where Calls.Accept == 1
p = inputParser;
addParameter(p,'forClu... |
c70394c1977dca8337c3e6f15c256d9d583d98dedae65148a4314f9340f76782 | MATLAB | 6,654 | 140 | function rawConvertFunc(HomeDir, raw_file_dir, batch_csv_fname, autofill_div, autofill_genotype, genotype, fs)
% Parameters
% ----------
% HomeDir :
% raw_file_dir :
% batch_csv_fname :
% autofill_div :
% autofill_genotype :
% genotype :
% fs : int
% sampling frequency of your recording (Hz)
% Use this scr... |
bc8a8e4a20789decc18925925a7317c97e807c2f8224921523795bd9815c8fb7 | MATLAB | 6,655 | 173 | %% raincloud_plot - plots a combination of half-violin, boxplot, and raw
% datapoints (1d scatter).
% Use as h = raincloud_plot(X), where X is a data vector is a cell array of handles for the various figure parts.
% Seee below for optional inputs.
% Based on https://micahallen.org/2018/03/15/introducing-raincloud-plot... |
d22bc6dc27ff48172a924e81c7f77801e33033f82e074590a52d1c84ab3a856f | MATLAB | 6,658 | 119 | %% outputFileList = construct_output_filename(outputDir, ouputPrefix, outputSufffix)
%
% Input
% --------------
% outputDir : output directory
% ouputPrefix : output filename prefix
%
% Output
% --------------
% outputFileList: structure contains all output filenames
%
% Kwok-shing Chan @ DCCN
% kwokshing.chan@do... |
c31fd4de60d068bb54fe2ebc912d5df06ae1efaaad62061c370210c35e690188 | MATLAB | 6,660 | 190 | function dm = mask2density(mask,radius,varargin)
% function dm = mask2density(mask,radius,[opt] searchmask, [opt] sphere_vol)
%
% mask is the mask with ones where activation points are
% radius is in voxels
%
% optional arguments:
% 1 searchmask
% searchmask is the whole brain search space [optional]
% Mas... |
24452cded4a15e3740112cb6f723913b143a77b3536860cd64f98d16a80c8751 | MATLAB | 6,661 | 130 | function results = assembly_patterns(SpikeCount,opts)
% Patterns = assembly_patterns(Activitymatrix,opts): extracts assembly patterns from the spike matrix.
%
% Description of inputs:
% Activitymatrix: spike matrix. Rows represent neurons, columns represent time bins. Thus, each element of the matrix carries the spi... |
075791a579d77a57204170fd2129d544a90b0254565047575dd4ff44e65b183e | MATLAB | 6,664 | 137 | function [ons_secs, VOLLOCS, LOCS, verbose] = tapas_physio_create_scan_timing(...
log_files, scan_timing, ons_secs, verbose)
% Extracts slice and volume scan onsets (triggers) from different vendor formats
%
% [ons_secs, VOLLOCS, LOCS, verbose] = tapas_physio_create_scan_timing(...
% log_files, scan_t... |
48d422a5af111fc85e89d5fbb438f40abd2e8b78bea9cf41c76a22a31e364fa9 | MATLAB | 6,669 | 160 | function burstData = singleChannelBurstDetection(raster, N, samplingRate, isiThreshold)
% singleChannelBurstDetection Get bursts within channels using Bakkum method
% INPUTS
% -----------
% raster : T x N matrix
% number of time samples (T) x number of units (N) binary spike matrix
% N : int
% minimum number of ... |
747f059ad5010b716e5f7a610ed2964da2801c749f629c583a09d3ac6c3669b3 | MATLAB | 6,669 | 188 | function output = targetClassifier(data, config)
% Params
nFolds = 1;
nPartitions = 5;
% Fit on only time period after cue
fitBins = find(ismember(config.tPts, 50:config.postT));
predictors = getPredictors(data, 'data', [], fitBins);
% Fit
output = cvClassifier(predictors, nFolds, nPartitions, config.type);
% Save ... |
815914b24a28ca6be57d0995c33881815425b6a5f05591952199884601b210b3 | MATLAB | 6,672 | 176 | function spindles = FindSpindles(filtered,varargin)
%FindSpindles - Find thalamo-cortical spindles (9-17Hz oscillations).
%
% USAGE
%
% spindles = FindSpindles(filtered,<options>)
%
% filtered spindle-band filtered LFP <a href="matlab:help samples">samples</a> (one channel). This must
% ... |
028bbfb78550f18a581aca828c0fb2fe02419bffcd012999c721fbdc8c980823 | MATLAB | 6,678 | 169 | function saveNetMet(ExpName, Params)
%SAVENETMET Summary of this function goes here
% Parameters
% ----------
% ExpName : str
% Name of experiment file
% Params : struct
% Parameter structure used in MEANAP
% Output
% -------
% None
%% groups and DIV
Grps = Params.GrpNm;
AgeDiv = Params.DivNm;
%% Varia... |
137447324c43e3056fef8b51a176677972630e56edbf89fb8f966874425e39a9 | MATLAB | 6,678 | 232 | function [Cs, sall] = rgbdectohex (Mrgb,strg, prompt)
%
% Mode 1:
% [Cs, sall] = rgbdectohex (Mrgb,[string])
% Mode 2:
% rgbdectohex
% Mode 3:
% Mrgb = rgbdectohex (sall)
%
% Mode 1:
%This function takes as an input the rgb matrix Mrgb (size is Nx3)
% where each row represents the rgb gun values ... |
b1cbae4aa28ac178fc4903063d25433ac679eab25d241cdce785255bf64cbc8b | MATLAB | 6,685 | 188 | function [r, LB, UB, F, df1, df2, p] = ICC(M, type, alpha, r0)
% Intraclass correlation
% [r, LB, UB, F, df1, df2, p] = ICC(M, type, alpha, r0)
%
% M is matrix of observations. Each row is an object of measurement and
% each column is a judge or measurement.
%
% 'type' is a string that can be one of the ... |
b7ae5fafc2ade483484e009aac3be56b219ec16c74071c87d1c412fa1619ef49 | MATLAB | 6,685 | 160 | function task_GA_gaitERSP_cluster(sii,PATH, cfg, fieldName)
PATHIN = PATH.ICAdecomp;
PATHOUT = PATH.(fieldName);
% load clustered study
[STUDY ALLEEG] = pop_loadstudy('filename', [cfg.study_name, '_',fieldName, '.study'], 'filepath', PATHOUT);
CURRENTSTUDY = 1; EEG = ALLEEG; CURRENTSET = [1:length(EEG)];
% id... |
ec8da1bd679119e67450bd0fe26ef0f0b92829841cddf0cdbbe09cfaf6b18d06 | MATLAB | 6,688 | 208 | % CART2TOPO - convert xyz-cartesian channel coordinates
% to polar TOPOPLOT coordinates. Input data
% are points on a sphere centered at (0,0,0)
% or at optional input 'center'. This function
% is now DEPRECATED! See Important warning below.
%
% Usage: >> [th r]... |
7f44d0ef385f1494f10f07274a4ef671e8a876fbe5b227188c6453a363c412ab | MATLAB | 6,690 | 140 | classdef MrImageGeometry < MrCopyData
% Geometry properties of MrImage, in particular for operations on niftis
% Provides full voxel to world mapping, i.e. affine transformation
% Including rotation/translation/voxel scaling
%
%
% EXAMPLE
% MrImageGeometry
%
% See also MrImage ta... |
f5ccd884a92870b5ca83a6d6060fe9adede87ddaeef1457c7af5740f75be2f67 | MATLAB | 6,690 | 235 | % this script builds a bunch of connected reservoirs
% representing a meshing of a polygonal region
% ----------------
%% Create a decomposed geometry matrix, with line segments giving boundary of polygon
% documented here:
% https://www.mathworks.com/help/pde/ug/create-geometry-at-the-command-line.html
% set up th... |
1a51272dd03eb25443e9cf625f3ac217448ff95db8819e2318fe5a5f2decdecf | MATLAB | 6,691 | 156 | function [mouse_position,chamber_frames,chamber_masks,cup_centroids,...
mouse_bodyparts,juv_bodyparts,juv_presence_frames] = proc_dlc_data(this_file,this_session_type,frame_size)
%% get mouse position, chamber masks, and cup positions from DLC result file
% ZZ 2022
[dlc_vars,chamber_names] = set_dlc_vars(this_s... |
67082d9a75dad00b7794bca77d867526dd3b073b0f6b3ac49aa5023c070309d0 | MATLAB | 6,697 | 139 | function [ens_seq,maxcor,templates,core_cells,clust_out,pars] = neuronRaster2EnsRaster(spktimes,filename,pars)
%
% [ens_seq,templates,clust_out] = neuronRaster2EnsRaster(spktimes,pars)
%
% Generates ensemble raster (N_ens x T) from neuron raster (N_neu x T),
% whose timestamps are contained on the cell array spktimes.
... |
981901d1331f1b95036e5d1d0f776cb081eedaa22265cc7e78ac5d25aac0ed96 | MATLAB | 6,697 | 199 | function plotFigureS7_TCAsupp(ephysPath, codePath, processedOFCPath)
% Plot TCA error and model, incongruent respones for LED on and LED off
%INPUTS:
% ephysPath = local path to ephys data downloaded from zenodo
% processedEphysPath = local path to saved incongruent response data from
% running processEphys... |
1911932886d3c122c0b8b01132ee92790d2f8d38adda6bcab945161cc6f4b515 | MATLAB | 6,698 | 159 | function yth = SB_CoarseGrain(y, howtocg, numGroups)
% SB_CoarseGrain Coarse-grains a continuous time series to a discrete alphabet.
%
% ---INPUTS:
% howtocg, the method of coarse-graining:
% (i) 'quantile': an equiprobable alphabet by the value of each point
% (ii) 'diff': as 'quantile', but applied to t... |
4d279ef62755e8f9265518da2edc9d63920f5c4c6700e1367488d76f1c5897da | MATLAB | 6,700 | 197 | function A0_RSA_YuModel(subject_id, model_lib_path, varargin)
% RSA_ANALYSIS_OPTIMIZED - Optimized multi-model RSA analysis
%
% Syntax:
% rsa_analysis_optimized(subject_id, model_lib_path)
% rsa_analysis_optimized(subject_id, model_lib_path, 'ParameterName', ParameterValue)
%
% Input Arguments:
% subject_id ... |
8b19abe8fff9dacbd5b2ff8224871d0e597f0c7197c9eb0e1f6d50f706a9a566 | MATLAB | 6,709 | 154 | function hyp = MF_GP_LearnHyperp(t, y, covFunc, meanFunc, likFunc, infAlg, nfevals, hyp)
% MF_GP_LearnHyperp Learns Gaussian Process hyperparameters for a time series
%
% Used by main Gaussian Process model fitting operations.
%
% References code 'minimize' from the GAUSSIAN PROCESS REGRESSION AND
% CLASSIFICATION ... |
334b8851b51405471c07bd0db685cbd30d86dd8e73c7e94089c5369d8a0b84af | MATLAB | 6,712 | 172 | function [MRSCont] = osp_fitWater(MRSCont, kk, fitWhich)
%% [MRSCont] = LCG_fitWater(MRSCont)
% This function initializes and runs fitting of the water reference and
% short-TE water scans.
%
% USAGE:
% [MRSCont] = osp_fitWater(MRSCont, fitWhich);
%
% INPUTS:
% MRSCont = Osprey MRS data containe... |
e3489b3a0ce55bcd3d2d66faa871f95d1e042cd9e0124d2a9d7659d6dfedf9ce | MATLAB | 6,717 | 195 | function net = cnn_imagenet_init_resnet(varargin)
%CNN_IMAGENET_INIT_RESNET Initialize the ResNet-50 model for ImageNet classification
opts.classNames = {} ;
opts.classDescriptions = {} ;
opts.averageImage = zeros(3,1) ;
opts.colorDeviation = zeros(3) ;
opts.cudnnWorkspaceLimit = 1024*1024*1204 ; % 1GB
opts = vl_argp... |
edefca2da739c986085b5e68ad5b7868df93914c633fc95e5280677e4cd2a998 | MATLAB | 6,717 | 195 | function [stat,p,ci,stats,dist] = permuztest(x,m,sigma,varargin)
%PERMUZTEST Permutation-based one-sample Z-test.
% STAT = PERMUZTEST(X,M,SIGMA) performs a one-sample permutation test
% based on the Z-statistic of the null hypothesis that the data in X come
% from a distribution with mean M, and returns the test... |
c85b4b44c82ffe7b52289153df2425fe0cef2a51f116d6fd985bc03ae2dd9894 | MATLAB | 6,720 | 196 | classdef circularGraph < handle
% CIRCULARGRAPH Plot an interactive circular graph to illustrate connections in a network.
%
%% Syntax
% circularGraph(X)
% circularGraph(X,'PropertyName',propertyvalue,...)
% h = circularGraph(...)
%
%% Description
% A 'circular graph' is a visualization of a network of nodes a... |
e1d322192938ff00e335644a318884eb9b1e3ef08fad3da1707e2673df96cfe3 | MATLAB | 6,721 | 162 | %% [mask_refined,r2s,relativeResidual,gradientMagnitude,gradientStats] = MaskRefinementMacro(mask,algorParam,headerAndExtraData)
%
% Input
% --------------
% Mask : Logical brain mask to be refined
% algorParam : Struct containing the method and method specific parameters
% headerAndExtraData : St... |
80bf866772ee8a588575a397d9b3ca2ef5331bd20f269b38859c3dffca5353c2 | MATLAB | 6,722 | 205 | function fear_evtTrigIcaCoactStrength(basename,varargin)
% basename='~/data/Fear/triple/booyah180430/booyah180430';
%%
param.templateIdx=2; %id of template behavior session
param.targetIdx=3; %id of homecage session for significant selection
param.beh='nrem'; %name of behaviror type for siginificant selection : 'nrem' ... |
a6e57c8c7aaf46628149737b66a6402cbc869f46ae94b9455162db6a51f33f4c | MATLAB | 6,722 | 248 | function OUT = whole_brain_ptask_givena(OUT,varargin)
% OUT = whole_brain_ptask_givena(OUT,verbose level, mask image or threshold value(for pa_overall) )
% OUT = whole_brain_ptask_givena(OUT,2,.001)
% verbose flag
if length(varargin) > 0, vb = varargin{1};, else, vb = 1;, end
P = OUT.PP;
task_indicator = OUT.allcondin... |
1e96a1a4fb4f24e21ca212bd16fe76222557b3d333f0caf07a2505f83cddb091 | MATLAB | 6,723 | 172 | % POP_CHANSEL - pop up a graphic interface to select channels
%
% Usage:
% >> [chanlist] = pop_chansel(chanstruct); % a window pops up
% >> [chanlist strchannames cellchannames] = ...
% pop_chansel(chanstruct, 'key', 'val', ...);
%
% Inputs:
% chanstruct - channel structure. See READLOC... |
290a189468c17d5122eeff9f16a899535e94493e3851293e84a877cf41dea0f6 | MATLAB | 6,723 | 186 | function ft_block_contrast(img_input, cond_input, TR, name_output, name_sess, ...
output_folder, null_input, multi_input, cutoff_highpass, microtime_onset, hrf_cbv, ...
hrf_derivative, lowpass, cutoff_lowpass, order_lowpass)
% GLM analysis
%
% ft_block_contrast(img_input, cond_input, TR, name_output, name_sessoutput_fo... |
55415d6a54f18371833fd53193d095d12a9a3e23614a0c8b0bd6c9f6df18336a | MATLAB | 6,734 | 165 | % MMO - create a memory-mapped data class
%
% Usage:
% >> data_class = mmo(data);
%
% Inputs:
% data - input data or data file
%
% Outputs:
% data_class - output dataset class
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, Nov. 2012-
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD
%
% This file is ... |
13654192cbaece995d289e5526f07d6c8eff3256e70913ad04a1688cfa4c912a | MATLAB | 6,737 | 268 | function [xdata,ydata,Wout,Weff,Wrdn,Win,Wirr] = ...
make_train_data(parm,T,Wout,Wrdn,Win,Wirr)
% Make training and test data set
% [xdata,ydata,Wout,Weff,Wrdn,Win,Wirr] = ...
% make_train_data(parm,T,Wout,Wrdn,Win,Wirr)
% - Output
% xdata : Xdim x Tsample x Ntrial
% ydata : Ydim x Tsample x Ntrial
% Wo... |
f88466f12f5d775714647ca50bfbb9e3c1cd0d64ae734adca5b07e1d24ecb233 | MATLAB | 6,737 | 199 | function runMainFigures(varargin)
% RUNALLFIGURES Generate all figures for the normalization paper
%
% Purpose:
% Main script to generate all publication figures with proper error
% handling and progress reporting.
%
% Inputs (optional):
% 'figures' - Array of figure numbers to generate (default: 1:6)
% 'verify... |
d945fca7eb5dafffc4d81a27fa0653a1d292fb28a175f58dcec4314bcd9e197c | MATLAB | 6,739 | 198 | function [condmask,condnames] = condmaskLibrary(type,file_idx,A,ops)
%create a conditional mask library for different filtering operations
%
%Inputs:
% type: string to decide what to condition on
% file_idx: neuron index in concatenated A data structure, or index in
% fnames
% A: concatenated alldat... |
856d52cdffa1a280a33c18a56755b83cabe4dcbb7f045d9da6937d45f0097e95 | MATLAB | 6,742 | 128 | function pairwiseResults = runbehavioralanalysis(T, dependent, outputFolder)
if ~ismember(dependent, {'ACC', 'RT','BIS'})
error('Invalid dependent variable. Choose either ''ACC'', ''RT'' or ''BIS''.');
end
% Fit the linear mixed-effects model
mdl = fitlme(T, [dependent, ' ~ Condition * Age * Group + ( 1 + ... |
9d4af50d62cd40095a13e70652ac48f46954659510105dc710dfe495fb51cd30 | MATLAB | 6,743 | 208 | function shuffle_icaReacCCG_exEvt_cueRet(basename)
tempIdx=2;
[rootPath,sesName,~]=fileparts(basename);
fprintf('%s load files for %s\n',datestr(now),sesName);
temp=matfile(fullfile(rootPath,'data',[sesName '-icaReac.mat']));
icaReac=temp.icaReac(1,tempIdx);
load(fullfile(rootPath,'data',[sesName '.sleepstate.state... |
40f973cc95303958ef184f0af9e16048b6b7c4d3da481c1cb539045f65815d9b | MATLAB | 6,752 | 163 | function [comp] = ft_datatype_comp(comp, varargin)
% FT_DATATYPE_COMP describes the FieldTrip MATLAB structure for comp data
%
% The comp data structure represents time-series channel-level data that has
% been decomposed or unmixed from the channel level into its components or
% "blind sources", for example using ICA... |
d9608d4d88bd8d1c32c1989d0561e5ab7ef8cabbab4f6ec48e7a26b6d116af9d | MATLAB | 6,754 | 196 | function [highc,highe,lowc,lowe,mixc,mixe]= wt_notsided(ExpA,ConA,Raw_data,varargin)
%no side bias wt
% Inputs:
% ExpA: Opto A struct
% ConA: control A struct
% Rawdata: Both control and opto S structs
% varargin: 1 - plots each animal wt curves
for a = 1:length(ExpA)
%generate the mean wt across ... |
9b5ce14623e5a4467cf3d3c73efbf109515d73d6a5f600cd8c4db4dd288faac2 | MATLAB | 6,755 | 181 | % NEWTIMEFBASELN - Remove baseline power values for newtimef. This
% function assumes absolute power NOT log transformed power.
% This function only removes baseline. Data has to be
% averaged subsequently if necessary. This function
% works bo... |
082faa9bfacf67b2fc1daefb685396534fd0223b842318c82a70c5532bff79e5 | MATLAB | 6,759 | 208 | function cluster_manova(clusters,fnames,varargin)
% function cluster_manova(clusters,fnames,verbose)
% tor wager
%
% clusters is output of clusters2database, with all fields
% from database
% fnames is cell array of strings with names to test
% e.g., {'Rule' 'Task'}
%
% uses stats toolbox
% example: cluster_manova(... |
ec4a4938d88c4aa76585f40566be7ec188d277455b640a55c24ec4c1791fbf2a | MATLAB | 6,759 | 171 | function PlotIntervals(intervals,style,direction,opt)
%PlotIntervals - Plot lines, rectangles or bars next to an axis to show interval limits.
%
% Given a list of [start stop] intervals, draw each of them with either:
% 1. a green (red) line representing its beginning (end)
% 2. a rectangle
% 3. a bar next to the x or... |
410c239fdd134d7b09045aa076a9db198efc29e25c2c7eff4279cc138e6e6b1a | MATLAB | 6,760 | 176 | function [spectrogram,t,f] = MTPointSpectrogram(times,varargin)
%MTPointSpectrogram - Compute point process spectrogram by multi-taper estimation.
%
% The spectrogram is computed using the <a href="http://www.chronux.org">chronux</a> toolbox.
%
% USAGE
%
% [spectrogram,t,f] = MTPointSpectrogram(times,<options>)
%... |
8f96166f5733869a8953c1c66eb05366b3b3882daa03d8f4ec13ebe811440293 | MATLAB | 6,761 | 201 | %% 13.01.2025 pupil size regression analysis on stimlocked data // clean script, autoregressive model
clc
clear all
clc
load('stim_locked_data.mat')
time = -1: 0.005 : 5;
time(end) = [];
% crop pupil data (0 - 4000 ms)
% start_crop = find(time == 0);
% end_crop = find(time == 4);
%
% data_... |
1d4c01690b25ac2ee9d8ac4a71f9617c060e51fbb7750fab22f265585b6de959 | MATLAB | 6,762 | 167 | function [U, S, V, info] = truncated_svd(A, p)
% Returns an SVD decomposition of A truncated to rank p.
%
% function [U, S, V, info] = truncated_svd(A, p)
%
% Input: A real matrix A of size mxn and an integer p <= min(m, n).
% Output: An orthonormal matrix U of size mxp, an orthonormal matrix Y of
% size nxp an... |
f65b44c25263df84080e2a6b9634766ac6e1bb8b57454689354021bff2e35ffb | MATLAB | 6,762 | 158 | function [varargout] = constructRDMs(responsePatterns, betaCorrespondence, userOptions)
%
% [RDMs =] constructRDMs(responsePatterns, betaCorrespondence, userOptions)
%
% constructRDMs is a function which takes a matrix of imaging data and
% computes RDMs from it, one RDM for each ROI, subject, and scanning
% session. T... |
68f418240cb8651229ca50938444ba38eef6dd6ad653679beec99f8bd5f123fa | MATLAB | 6,765 | 174 | %A script for testing function New_HEAD
%Choose from 3 options
fprintf(1,'\n Demo for New_HEAD function.\n');
fprintf(1,' BEFORE you proceed, make sure you have no AFNI\n');
fprintf(1,' session running with the -yesplugouts option.\n');
fprintf(1,' 1- From a matlab 3 dimensional matrix, create\n');
f... |
91c055c2dd84d77806efb34349f9a9237f96ce96065648706289224797f50c15 | MATLAB | 6,769 | 151 | function out = PH_KramersMoyal(y, tau, numBins)
% PH_KramersMoyal State-dependent drift and diffusion (Kramers-Moyal coefficients).
%
% Treats the time series as a sampled Langevin process,
% dx = D1(x) dt + sqrt(2 D2(x)) dW,
% and estimates the conditional-moment (Kramers-Moyal) coefficients as a
% function of the... |
40b252ab8395468fec0e56017f750e94aed58c48d6400106a8f9f1380073884e | MATLAB | 6,770 | 180 | %% raincloud_plot - plots a combination of half-violin, boxplot, and raw
% datapoints (1d scatter).
% Use as h = raincloud_plot(X), where X is a data vector is a cell array of handles for the various figure parts.
% Seee below for optional inputs.
% Based on https://micahallen.org/2018/03/15/introducing-raincloud-plot... |
e76fd52f6a6fa8d889d67a38ceeeabd37fb6e6200489de066a8c2437cff173a3 | MATLAB | 6,772 | 161 | % POP_IMPORTEGIMAT - import EGI Matlab segmented file
%
% Usage:
% >> EEG = pop_importegimat(filename, srate, latpoint0);
%
% Inputs:
% filename - Matlab file name
% srate - sampling rate
% latpoint0 - latency in sample ms of stimulus presentation.
% When data files are exported ... |
17ce2f2b8bbc6a39373a9365f0a5d57fc337d68816384b14fa14c8cb72ffd5a2 | MATLAB | 6,777 | 186 | function create_training_images_Callback(hObject, eventdata, handles)
% hObject handle to create_training_images (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Select the files to make images from
[trainingdata, traini... |
493d53e5e877a9e5c4ca64e3a30dfea9ed060e25ea49004b2f17cd47b22cac8f | MATLAB | 6,778 | 188 | function H = calcSubspaceGener(rawData,SPM)
% rawData: raw data from searchlight
% calculate the subspace generalisation (area under the curve of explained
% variance as a function of number of EVs)
flagCal = 1; % flag whether to caclulate subspace generalisatoin, will change to 0 only if there is a problem with NaNs ... |
4ccb8ffffe5bdfab906c08f9ded7fc443148fcd5c3b778673c7319e4cd58a342 | MATLAB | 6,778 | 168 | function bids_T1B1correct_job(BIDSroot, InvEff, B1Scaling, Realign, FWHM, Target, ...
Correct, Fingerprint, B1correctM0, MP2RAGE, B1map, B1Ref, R1mapname)
% Performs the work for bids_T1B1correct()
%
% Marcel Zwiers, 20/03/2023
Debug = 0;
% Load the headers & data
B1Src = spm_vol_gz(fullfile(B1map.folder, B1m... |
99735207d074dcf5d913d1f7b8b11e0e06b8dd5a98d64344a5de41dc34d77878 | MATLAB | 6,780 | 206 | function M = fixedrankfactory_3factors(m, n, k)
% Manifold of m-by-n matrices of rank k with polar quotient geometry.
%
% function M = fixedrankfactory_3factors(m, n, k)
%
% The first-order geometry follows the balanced quotient geometry described
% in the paper,
% "Linear regression under fixed-rank constraints: a R... |
9ff25ba1e2fe8515d501e5148ee706fc4bac5c912aad2902f7bdd5e87254c983 | MATLAB | 6,790 | 144 | function [stats, stats_overview] = DescriptiveStats(data, PathName, layer_numbers) % by Julia Becker, 10/04/2020
%DESCRIPTIVESTATS
% For each condition and ROI, calculate
% - median
% - lower quartile (25th percentile)
% - upper quartile (75th percentile)
% - minimum value
% - maximum value
% - mean
%
% T... |
2b238f3094d3fbc1786016ead21eefb482cc004e47c052c571eaed7c01093062 | MATLAB | 6,802 | 148 | % (C) Copyright 2019 bidspm developers
%% analyze localizers
clear;
clc;
bidspmDir=fullfile(fileparts(mfilename('fullpath')),'..', 'lib','bidspm');
addpath(fullfile(fileparts(mfilename('fullpath')),'..', 'lib','bidspm'))
bidspm();
%changed it to absolute because there were erros.bids_dir = fullfile(fileparts(mfilen... |
9736d39cb18d8d850169fabafd8ca852141eefc61d8457c561a2543dafd87e14 | MATLAB | 6,810 | 117 | clc
clear all
close all
whicheye = input('Please enter left or right to choose eye: ','s')
rawfilepath = input('Enter raw_data location(such as /home/raw_data): ', 's');
processedpath = input('Enter processed_data location(such as /home/processed_data): ', 's');
outputFile = input('Enter output result location:','s');... |
f049a1c9200830a38502a83ec1420bf54b8ddce23a5715bcc1d04bbabc823a47 | MATLAB | 6,812 | 173 | %% statistical significance in mvpa
% non-parametric technique by combining permutations and bootstrapping
% step1:
% For each subject, the labels of the different conditions (eg. motion_vertical and motion_horizontal) were permuted,
% and the same decoding analysis was performed.
% The previous step was repeated 10... |
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