sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
62bae92563635497ddbbb30f52779b6eeea66ce95ec3d7cee1c46562d4f2019b | MATLAB | 4,264 | 171 | function RDMs = averageRDMs_subjectSession(varargin)
% RDMs = averageRDMs_subjectSession(RDMs): returns the input unchanged (no
% operation). RDMs = averageRDMs_subjectSession(RDMs, 'subject'): computes
% the subject-averaged RDMs. RDMs = averageRDMs_subjectSession(RDMs,
% 'session') RDMs = averageRDMs_subjectSession(R... |
63a888300e42e047a150688b1292358a0b83bd897d69e36dd7a02fae494952fa | MATLAB | 4,264 | 101 | %% TestBFRMatrix - Tier 3 real-dataset background-field-removal method regression matrix
%
% Mirrors TestQSMMatrix.m: runs the one-stop SEPIA pipeline on a real
% dataset once per background-field-removal method in methodBFRName
% (sepia_universal_variables.m), holding phase unwrapping ('None') and
% QSM dipole inversi... |
01012cbcaf795b655a904e650bd33d7ef1a9028791133c45e9915bc565e81c77 | MATLAB | 4,265 | 103 | function [realignedImage, realignmentParameters] = realign(this, varargin)
% Realigns all 3D images in 4D data to each other using SPM's realign...
% estimate+rewrite functionality; interfaces all options of spm_realign
%
% Y = MrImageSpm4D()
% [realignedImage, realignmentParameters] = Y.realign(...
% 'spmPar... |
3276e7ab4483972944d40cbefb49577a0b8084bc353cd7439e890095e4c05fb3 | MATLAB | 4,265 | 113 | % EEGDRAWG - subroutine used by EEGPLOTGOLD to plot data.
%
% Author: Colin Humphries, CNL, Salk Institute, La Jolla, 7/96
% Copyright (C) Colin Humphries, CNL, Salk Institute 7/96 from EEGPLOT
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in... |
d576b83182ebeda53873f2451e1b9b0ec12cfaa32b79ae55240842a4a1b2df4e | MATLAB | 4,266 | 123 | function MS = createMesh3D(varargin)
% MeshStructure = buildMesh3D(Nx, Ny, Nz, Width, Height, Depth)
% builds a uniform 3D mesh:
% Nx is the number of cells in x (horizontal) direction
% Ny is the number of cells in y (vertical) direction
% Nz is the number of cells in z (perpendicular) direction
% Lx is the domain len... |
ed46116c91189b3afa017bdc6d74dbd4d9a6f5a54a377504ebaad4bbba39e523 | MATLAB | 4,267 | 119 | %% get_set_qsm_heidi(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
... |
859ada67a484a18dc084c7b6c47077c88bb6ac72380825d30fa86e0fa97e1082 | MATLAB | 4,268 | 98 | function [varargout] = likPoisson(link, hyp, y, mu, s2, inf, i)
% likPoisson - Poisson likelihood function for count data y. The expression for
% the likelihood is
% likPoisson(f) = mu^y * exp(-mu) / y! with mean=variance=mu
% where mu = g(f) is the Poisson intensity, f is a
% Gaussian process, y is the non-negativ... |
3b293cca9d66df507e55447bdb77b0e3dcdeb51a996d1a05cd1d9d0eaff820bc | MATLAB | 4,270 | 175 | function [Xi,alltasknms,condf,allti,testfield,prop_by_condition,num_by_condition] = Meta_Task_Indicator(DB,varargin)
% [Xi,alltasknms,condf,allti,testfield,prop_by_condition,num_by_condition] = Meta_Task_Indicator(DB,[data])
%
% Get task indicators and number / proportion of activating contrasts from DB
%
% needs to se... |
2a47424e109bb3890010d4b40a06cf3bd99c984a314b1721f509b3502b16cbba | MATLAB | 4,271 | 105 | function hessfd = getHessianFD(problem, x, d, storedb, key)
% Computes an approx. of the Hessian w/ finite differences of the gradient.
%
% function hessfd = getHessianFD(problem, x, d)
% function hessfd = getHessianFD(problem, x, d, storedb)
% function hessfd = getHessianFD(problem, x, d, storedb, key)
%
% Returns a f... |
4e090b4671acfe9e45ba4533fba0da9bd7d5fdbd8690b0bf71bc2828db8eae7d | MATLAB | 4,275 | 117 | %% MOTION CORRECTION SCRIPT
close all
clear all
% fname = 'Z:\Scanbox\Data\rbp6_3\20210707_rbp6_3\20210707_rbp6_3_000_004';
Directory = 'Z:\Scanbox\Data';
cases = {'rbp6_3'; 'rbp10'; 'rbp11'; 'rbp12'; 'rbp13'; 'rbp16'};
% MC_values = cell(6, 6);
%
% x_y_coord = cell(6, 6);
load('Z:\CLOOSE_benchmark_tests\MC\MC_v... |
258f1aa7290558dca6ccee77f6a8af75dd1c3ce941aa262fb26956cac8e388d5 | MATLAB | 4,276 | 135 | function stats = anova2_repmeas(Y,S,F1,F2,FACTNAMES)
%
% function stats = anova2_repmeas(Y,S,F1,F2,FACTNAMES)
%
% Two-factor, within-subject repeated measures ANOVA.
% For designs with two within-subject factors.
%
% Parameters:
% Y dependent variable (numeric) in a column vector
% S grouping va... |
a3bc099e460ce74481af73d0cc37e1eb627fe8c37dbc56b4f2e1fed2a5c2b7e5 | MATLAB | 4,276 | 131 | function data = eventLockData(R, M, eventName, tPts, rois)
% data = eventLockData(R, M, eventName, tPts)
% data = eventLockData(R, M, eventName, tPts, rois)
%
% Resample deconvolved calcium events into a new time base. For example,
% instead of having a time base that's set inconveniently to 32.17 ms by
% our scan rat... |
b6b641cef837b6681a5bc58e1a7414cf71591204fb8c51d45f8d0579b92190ac | MATLAB | 4,276 | 130 | function [str,H,p,STATS,stars] = ttest_nice(a,b,type,plotFlag,fontsize4text,printOutFlag,statsInTitleFlag,inputNames)
if ~exist('plotFlag','var') || isempty(plotFlag)
plotFlag = 0;
end
if ~exist('printOutFlag','var') || isempty(printOutFlag)
printOutFlag = 1;
end
if ~exist('statsInTitleFlag','var') || isempty(stat... |
c57882c404bbeb920be35d83c3f5bd34a1112b149640a0a00272b805039bdbe5 | MATLAB | 4,279 | 106 | function tapas_hgf_binary_condhalluc_plotTraj(r)
% Plots the estimated or generated trajectories for the binary HGF perceptual model
% Usage example: est = tapas_fitModel(responses, inputs); tapas_hgf_binary_plotTraj(est);
%
% --------------------------------------------------------------------------------------------... |
a66ca725b97242e8668b96820e48cf7ae7093db5ecf6b20f8356ca194b20e735 | MATLAB | 4,281 | 101 | %% Encasing.m
% Written by Julia Becker January 2020. Minor edits Alex Winkel
% Instructions: copy this file from the GIT folder to somewhere else (e.g.
% a folder in the Matlab path), then edit the varibles ui2 to ui7. Run the
% script and choose an over-arching folder - it will search for subfolders
% called '... |
b8ec58ebb15ddde34f5a6edea6fecfddb03c3177ce536265b0044b3cc22ea031 | MATLAB | 4,281 | 124 | function run_booteffectsize_examples
%RUN_BOOTEFFECTSIZE_EXAMPLES Run bootstrapped effect size examples.
% Generates random multivariate data for 2 samples X and Y. Each sample
% has 20 variables, each with a mean value of 0, except for the first 10
% variables of Y which have a mean value of -1. Each variable h... |
fc3e86b42be74ecda9e7a1d33d90da3763d86edad89ea6b9fd14f73f6fc787f8 | MATLAB | 4,281 | 118 | function [dcurve_mag_clust1_avg,dcurve_eig_clust1_avg,length_x1]=diversity_curve(M,dsym,L,VoxelSize,Avg_mag,Avg_eig)
% This srcipt computes the diversity curve for each streamline
% The are all in cropped space
% The gradient magnitude is symmetrized
% Load the group everaged eigenmap and gradient magnitude
[~,avg_m... |
7c3fe7016fafea930cec31b727f33899833cc3e69ad0059461cb2c6a982481d9 | MATLAB | 4,282 | 141 | %% Morris screening
% Author: MJ Colebank
% Last edited: 3/10/2022
%
% THIS CODE COMES WITH NO GUARANTEES
clc; clear;
%%
Qdat = dlmread('DP1_inflow.dat');
% inflow_param = Qdat(13:end,:);
% get_inflow(Qdat,16385,inflow_param);
dlmwrite('inflow.dat',Qdat,'delimiter','\t')
load ('DP1_opt.mat');
param_values = x.*sc;
%%... |
1dba5faa5344a73984ebba52e1fda950e752ed6041b9395e4f23249290b2ebad | MATLAB | 4,286 | 57 | function current_results_out = outputHNMPAResults(current_results,csv_outdir,modality,roiType,resultsCell)
current_results_out = current_results;
struct_string = [modality '_' roiType];
% current_results = outputHNMPAResults(current_results,'IVIM',roiType,{bval_arr,dwi_arr,[f_arr;D_arr;Dx_arr;s0_arr]... |
8a96a956b60164df7a11c82ecf1e5524ecf0e47b0e90db7c2d67824994b773b4 | MATLAB | 4,287 | 138 | function [X,a]=indicatorMatrix(what,c)
% function X=indicatorMatrix(what,c)
% Makes a indicator Matrix for the classes in c
% INPUT:
% what : gives the type of indicator matrix that is needed
% 'identity' : a regressor for each category
% 'identity_p' : a regressor for each category, except for... |
29cc49e810ef50e1c50b871b04e55ad49559da88c1bbacbf90f39ea37d8470b2 | MATLAB | 4,288 | 126 | % exp 1 uses 6 pcs and 0.035 on the global centroid clustering
% exp 2 uses 6 pcs and 0.022 on the global centroid clustering
% exp 3 uses 5 pcs and 0.015 on the global centroid clustering and manual
% exp 4 uses 5 pcs and 0.015 on the global centroid clustering and manual
% selection
%% Testing centroid detecting with... |
62478660978830d3ae5610da7d8fadcf6f9a759c94b41e9429dca417811f664b | MATLAB | 4,289 | 113 | function brain = getBrainData(params, plotInfo)
% loads 3D brain volume (MRI, CT, anatomic areas, ...) = brain
% interpolates
% SPM package MUST be included in Matlab path
% (c) Jiri, Jan17
% old implementation (as of Nov21), use: brainVolumes_load.m
%% defaults
if ~isfield(plotInfo, 'plottingStyle')
plotInfo.plo... |
9d8ae86710c6ff1ded88edfa96f8da99c1a6b763ea472867212d10c4e0654e50 | MATLAB | 4,289 | 134 | % Script for WMH segmentation using LST toolbox in SPM
% Youjie Wang, 2025-08-31.
% Dependencies:
% - SPM12
% - LST (https://www.applied-statistics.de/lst.html)
clear;
FLAIR_path = '/this/is/for/nipype/flair';
T1w_path = '/this/is/for/nipype/t1w'; % can be empty ''
threshold = '/this/is/for/nipype/threshold';
output... |
0c8e80874395068b8d6184539ba89c3bd98ca41be6f27cd959111f17bcdb4eb7 | MATLAB | 4,290 | 100 | %% h = sepia_handle_panel_qsm_FANSI(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global structure contains all new and other hand... |
1c0bb13f28e9f2252ec7f61cd983974d4f4e369d4cd80208c182a5b79180d5d8 | MATLAB | 4,291 | 132 | function [y1, y2] = vl_nnpdist(x, x0, p, varargin)
%VL_NNPDIST CNN p-distance from target.
% VL_NNPDIST(X, X0, P) computes the P distance raised of each feature
% vector in X to the corresponding feature vector in X0:
%
% Y(i,j,1) = (SUM_d (X(i,j,d) - X0(i,j,d))^P)^(1/P)
%
% X0 should have the same size as X;... |
5319560ae5301a1dbd7ea7deaf4e6e58de82d9e6f39d12a6f366750147fe4e0c | MATLAB | 4,292 | 112 | function [dataheat, ind_lim] = get_norm_rsc_simfile(sim_file, ind_lim)
% GET_NORM_RSC_SIMFILE
% Syntax:
% [dataheat, ind_lim] = get_norm_rsc_simfile(sim_file, ind_lim)
% Description:
% From a simulation file and its *_1/*_2 siblings, compute per-neuron
% ratio (rate_1+rate_2)/rate_3, select neurons within percent... |
555e436244bd6279fdcb644b72873cc638f8b3651cd36a3e9059e7863da43846 | MATLAB | 4,292 | 132 | function [opts, args] = vl_argparse(opts, args, varargin)
%VL_ARGPARSE Parse list of parameter-value pairs.
% OPTS = VL_ARGPARSE(OPTS, ARGS) updates the structure OPTS based on
% the specified parameter-value pairs ARGS={PAR1, VAL1, ... PARN,
% VALN}. If a parameter PAR cannot be matched to any of the fields
% ... |
440b4a48c4b9a42b2dd380e487373e0021413a5433d1a7814df4ca1fc91acbc2 | MATLAB | 4,293 | 145 | %%
Phantom.fslow = .64;
Phantom.finter = .29;
Phantom.ffast = .10;
Phantom.Dslow = .0015;
Phantom.Dinter = .0052;
Phantom.Dfast = .08;
Phantom.S0 = 184;
ffast = Phantom.ffast;
% T1_tissue = 900:20:1700; % 900 to 1700
% T1_blood = 1500:20:2100; % 1500 to 2100
% T2_tissue = 70:10:90; % 50 to 90
% T2_blood = 220:... |
dd163b9ee65a73f07df549a312d9eae3d48ea32a56f813f318ebf4165e83a972 | MATLAB | 4,293 | 132 | function [y1, y2] = vl_nnpdist(x, x0, p, varargin)
%VL_NNPDIST CNN p-distance from target.
% VL_NNPDIST(X, X0, P) computes the P distance raised of each feature
% vector in X to the corresponding feature vector in X0:
%
% Y(i,j,1) = (SUM_d (X(i,j,d) - X0(i,j,d))^P)^(1/P)
%
% X0 should have the same size as X;... |
011758ac207cc7e86fd806f9aebc127ced6bd4e990d51851ef2781f98424c5c0 | MATLAB | 4,295 | 149 | function [output]=runEXTRACT(h5Path,varargin)
%% OPTIONS
options.diary=true;
options.plotFigure=true;
options.diary_name='diary';
options.verbose=true;
options.frameRange=[];
options.polarityGEVI='pos'; % 'neg' 'dual'
options.rank=100;
options.binning=[];
options.partition=[1 1];
options.cellRadius=20;
%% UPDATE OP... |
22fd1de6fb2f08636d0bd47605dd927a40b43ba9c367de44b6e501d62f1cddef | MATLAB | 4,295 | 128 | function autoqc_nsd_grandfinale(glmdirname,curix)
% setup
nsdsetup;
alltempfiles = {};
switch glmdirname
case {'glmdata' 'glmdataLOW'}
if isequal(glmdirname,'glmdata')
min0 = -620;
else
min0 = -340;
end
% what is the 1-index of the max nsd session we have?
if ~exist('curix','var') || isempty(cur... |
267fc133c2adf02d1789d0f8427ec61dd871ec9b59c50a85c6f47668528177eb | MATLAB | 4,297 | 108 | %% %%%%%%%% Generate maps of floc results
% define
resultsdir = [nsd_datalocation '/ppdata/subj%02d/func1mm/'];
files = ... % 1 is R2, 2 is mean, 3-7 is domain [t], 8-17 is subdomain [t], 18-22 is domain [a], 23-32 is subdomain [a], 33 is all betas
...% name fname mgz name color r... |
c6a15a3ac35c377eb2c8b6799ffcfa99b88622415f880cd3a743c06f518be28f | MATLAB | 4,298 | 128 | %% Place to save reduced data structures
YOURDATAPATH = '';
savePath = [YOURDATAPATH '/' 'locked' '/'];
%% Individual datasets
mouseInfoAll = {{'cfa17', '200825'}, ...
{'cfa17', '200827'}, ...
{'cfa19', '200820'}, ...
{'cfa19', '200826'}, ...
{'cfa20', '201114'}, ...
{'cfa20', '201118'}, ...
{'... |
bdd33d07305efa75423c2d1b5e930edf996022c3f78b749f0f2837b2b6e35179 | MATLAB | 4,302 | 121 | function [ EEGOUT, command ] = pop_cwregression( EEG ,varargin)
% UNTITLED1 Summary of this function goes here
% Detailed explanation goes here
command='';
% keyboard;
if numel(varargin)==0
% probably can be removed..
% cfg.cwregression.srate = EEG.srate; %srate=1000;
% cfg.cwregression.wi... |
3d9d10e1d627e8db131f9f1ee220b504b19afb13db7f73ec71038f2cbf952b22 | MATLAB | 4,303 | 96 | function PseudoTransmit_GroupAverage(myelinRCFile, avgPTFieldFile, ReferenceValOutFile)
%asymmetry stuff is only for display, moved to phase 4 to simplify
%"Orig Myelin"
MyelinMap = cifti_read(myelinRCFile);
AvgPTField = cifti_read(avgPTFieldFile);
[leftmyelin leftroi] = cifti_struct_dense... |
cd1c2182ef0985d3e408c9b9d86d2f24464df77e26f991c16e486db7c4d66939 | MATLAB | 4,303 | 124 | % ENTROPY_REJ - calculation of entropy of a 1D, 2D or 3D array and
% rejection of odd last dimension values of the input data array
% using the discrete entropy of the values in that dimension
% (and using the probability distribution of all columns).
%
% Usage:
% >> [entropy r... |
6787ff616b30c12ef6447d2af75e05ce3f60a38c4e2a4567d9921e71ec4d8114 | MATLAB | 4,304 | 171 | function test_suite = test_checkParameters %#ok<*STOUT>
% (C) Copyright 2021 CPP visual motion localizer developers
try % assignment of 'localfunctions' is necessary in Matlab >= 2016
test_functions = localfunctions(); %#ok<*NASGU>
catch % no problem; early Matlab versions can use initTestSuite fine... |
e4dcc8a0e2adbe6f518759c82bf1e21ddbd0478b1a4092f65c0e869ec1f3f9a7 | MATLAB | 4,305 | 119 | function F = spm_Fcdf(x,v,w)
% Cumulative Distribution Function (CDF) of F (Fisher-Snedecor) distribution
% FORMAT F = spm_Fpdf(x,df)
% FORMAT F = spm_Fpdf(x,v,w)
%
% x - F-variate (F has range [0,Inf) )
% df - Degrees of freedom, concatenated along last dimension
% Eg. Scalar (or column vector) v & w. Then df=... |
0cdd3db10fc52e38853b742e79fed1cd8f956fe7dd7ddcda237de89f1fc710aa | MATLAB | 4,306 | 107 | % EEG_DIPSELECT - select component dipoles from an EEG dataset with
% reisdual variance (rv) less than a selected threshold
% and equivalent dipole location inside the brain volume.
% Usage:
% >> selctedComponents = eeg_dipselect(EEG, rvThreshold, selectionType, depthThreshold)
%... |
293cfb4fb60bc7a55b97aeafa7bdb4f7e99326984bffb169d49312a69246ef97 | MATLAB | 4,309 | 135 | function [result] = fit_happy_model_basic(mtx,happyscore,constant)
%assumes that each row of the cell array is a different subject
rptfit = 5; %repeat N times jittering the betas
tempf=fieldnames(mtx);
for n=1:length(tempf), eval(sprintf('mtx.%s=double(mtx.%s);',tempf{n},tempf{n})); end;
data = mtx;
data.happyscore =... |
4eaaed04ba69a6ea8fa22a58c17fbd267f0b619326a864882204a1aa5e4df825 | MATLAB | 4,309 | 171 | function [incong_offer, incong_rew, incong_opt, cong_offer, ...
cong_rew, cong_opt] = getIncongruentTrials(S)
% find incongruent trials
bchange = diff(S.Block);
allChange = find(bchange);
ltom = find(bchange == -2)+1; %first mixed trial post low
ltom_incong_offer = nan(size(ltom));
ltom_incong_rew = nan(size(ltom)... |
1ca0fb2144e2c58f2d38db73c18622a700e892a5e892f0c497a2a22234ea6b40 | MATLAB | 4,310 | 100 | %% h = sepia_handle_panel_swismwi_SWI_2DHamming(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global structure contains all new an... |
2845b919b0fd63a08d409601c76a66c2ae4b7753b1a034aa3aba87d68a5a1007 | MATLAB | 4,310 | 170 | function Pipeline_plotPatchData(params)
% This function plots data acquired from whole cell recordings and
% simultaneous voltage imaging of single neurons
sm = 1;
analysisDir = getAnalysisDir(params);
ExpInfoFn = getFileName(params, 'ExpInfo');
tsFn = getFileName(params, 'TS');
wsFn = getFileName(params, 'WSData');... |
f4a3f2252a26d820734d0b0302fedb0f7c5d1bb6ca34b242a38d5952d86f3fc5 | MATLAB | 4,311 | 110 | function out = MF_StateSpaceCompOrder(y, maxOrder)
% MF_StateSpaceCompOrder Change in goodness of fit across different state space models.
%
% Fits state space models using n4sid (from Matlab's System Identification
% Toolbox) of orders 1, 2, ..., maxOrder and returns statistics on how the
% goodness of fit changes ... |
5b456a5f6968162f325e8d00b0644b818cc8aef5031cb464a701d842b73a65fd | MATLAB | 4,312 | 104 | % This MATLAB script can be used to reproduce the result of EEG spectral power increase and decrease
%
% Please download BBCItoolbox to 'MyToolboxDir'
% Please download dataset to 'NirsMyDataDir' and 'EegMyDataDir'
% The authors would be grateful if published reports of research using this code
% (or a modified version... |
7ba55c4d28dd0830fb557f5303ae2cb1610a0a250d8b26ee85114674e48030d6 | MATLAB | 4,312 | 144 | function tapas_uniqc_new_struct(varargin)
% Creates a new script (e.g. tests/examples) including header.
% tapas_uniqc_new_struct(funname) opens the editor and pastes the content
% of a user-defined template into the file funname.m.
%
% Example
% tapas_uniqc_new_struct myscript
% OR
% tapas_un... |
ee6d3b547073e472fc88d7c1409a7d6dcdd16e3a33f49ee154c20ffadac533b7 | MATLAB | 4,313 | 146 | function [nTestFailed,nTestTotal] = tapas_test(toolboxes,level)
% TAPAS_TEST Run tests of TAPAS toolboxes
%
% IN
% toolboxes
% Names of toolboxes to test (including their dependencies)-
% If empty, all toolboxes are used.
% level
% Detail of the test (per toolbox).
% 0: Rough... |
b976dcfd0ca936cae4bd5d107c6e814de3208d96a723b0b103315d8ce1ac98bb | MATLAB | 4,314 | 108 | function filter = tapas_physio_gui_filter()
% Creates sub-part for preproc filter options in Batch Editor GUI
%
% tapas_physio_gui_filter
%
%
% See also
% Author: Lars Kasper
% Created: 2019-07-05
% Copyright (C) 2019 Institute for Biomedical Engineering
% University of Zurich and ETH Zurich
... |
e8e1ad0531edc01727543521c7cd215bab39dc1aa18acba21c52895b632a97d2 | MATLAB | 4,314 | 132 | function [mesh] = prepare_mesh_iso2mesh(seg, tissue, maxvoxelvol, dofix, ...
downsample)
%
% Input: seg <nx x ny x nz matrix> segmented MRI scan
% tissue <list> of tissue types, e.g. {'brain', 'skull', 'scalp'},
% or something lik... |
d321240254601349c0f0df59ac3ce79a726748bc07309f313d2049f274061f86 | MATLAB | 4,315 | 141 | function [fet_proc,fet,fet_sem,fet_legend,fet_inds,xvec] =...
createFeatures_ofc(ops)
%generates features from OFC data.
%The running history of the many
%types investigated, but pulled and made on the fly
% includes preprocessing steps such as denoising via PCA
%% load data and siz... |
3085ea1a3bd509611818d750035b8e560842dff3804e05970e779c1869873a6d | MATLAB | 4,316 | 87 | % this script generates, for all subjects, a depiction of tsnr results for one run.
% this includes tsnr related stuff (i.e. mean and valid).
% define
massiveim = [];
for subjix=1:8
sessix = 20;
runix = 1;
% setup
dirs0 = nsdallsessfun2(subjix);
ppdir = regexprep(dirs0{sessix},'rawdata','ppdata');
% loa... |
6179534f0fa9410aecf2874a354e5c2e364c3dbd9c723118688119051423598f | MATLAB | 4,317 | 109 | % Bonferroni-Holm (1979) correction for multiple comparisons. This is a
% sequentially rejective version of the simple Bonferroni correction for multiple
% comparisons and strongly controls the family-wise error rate at level alpha.
%
% It works as follows:
% 1) All p-values are sorted in order of smallest to largest.... |
d22fbad0e6e52dba7f6a368f2b99fc93bf2cb97c5e68883407feda71303177a5 | MATLAB | 4,318 | 116 | function BF_AnnotateRect(featureVector,groupLabels,cfnParams,colors,ax,underOrLeft)
% BF_AnnotateRect Annotates rectangles under distributions for group classification
%
%---INPUTS:
% whatCfn, the classification method to use
% featureVector, the values given to each observation
% groupLabels, the class labels assigned... |
48ad221ae8aa793b9bfa918c327fa7ce4c4e784032dacae6d8c609ec577d6a18 | MATLAB | 4,319 | 155 | function [value] = test21(epsilon, A, B, C, D)
% test for complex sphere
% See notes October 11, 2012.
%
% fzero(@(x) test21(x), [.1 1]) searches the value of epsilon such that we
% barely destabilize the system with a norm epsilon perturbation.
%
% This file is part of Manopt: www.manopt.org.
% Original author: Nicol... |
f377a53e95ca8be4286715e1b6c59b68a47e70271d89f4d901c70737c40e0850 | MATLAB | 4,319 | 118 | % Script demo_change_geometry
% How to change the gemetry parameters (shift, rot, zoom, shear) in
% MrImageGeometry or MrDimInfo (axis-parallel shift and zoom only)
%
% demo_change_geometry
%
%
% See also
% Author: Saskia Bollmann & Lars Kasper
% Created: 2019-12-03
% Copyright (C) 2019 Institute for Biomedical ... |
dc68824e348b64a1159ad31ed7a377ecbba287c876aad62ba38c304fa765857e | MATLAB | 4,320 | 155 | function coactPaper_figureS09()
labelWeight=true;
labelCase=false;
labelSize=9;
letGapX=5;
letGapY=6;
fontsize=6;
close all
fh=initFig('width',8.9,'height',3,'font','Arial','fontsize',fontsize);
x=18;
y=2;
panel_01(x,y,fontsize);
drawnow();
end
%%
function panel_01(x,y,fs)
width=20;
height=18;
xGap=14;
cellInfo=po... |
f341d4d97c1440f764c0ac6d57442500efd83e98bf941a79336ea2f644333431 | MATLAB | 4,320 | 102 | function f = TS_PlotLowDim(whatData,whatAlgorithm,showDist,annotateParams,cfnParams)
% TS_PlotLowDim 2-dim feature-based representation of a time-series dataset
%
% The low-dimensional representation is computed using PCA by default.
%
%---INPUTS:
% whatData, the hctsa data file (or structure) to use (input to TS_Loa... |
43707643c44f0431063b99c82c4c89e014d3dd16941fa7a7f32d9474fac9a3cb | MATLAB | 4,322 | 139 | %Detrend - Detrend signal.
%
% USAGE
%
% [detrended,model] = Detrend(samples,<options>)
%
% samples <a href="matlab:help samples">samples</a> to detrend
% <options> optional list of property-value pairs (see table below)
%
% ======================================================================... |
b02c8576dc8a3749a3237308743e0eb6caec669ecd688f9bc830e21bf3f230a9 | MATLAB | 4,323 | 127 | classdef nnconvt < nntest
properties (TestParameter)
depth = {1 2 3}
numImages = {1 2 3 4}
numFilters = {1 2 3}
upx = {1 2 3}
upy = {1 2 3}
padx1 = {1 2 3}
padx2 = {1 2 3}
pady1 = {1 2 3}
pady2 = {1 2 3}
up = {1 2}
fsx = {1 2}
crop = {1 2 3 4 5 6 7 8}
numGroups = {1... |
802aaf4855c614caf95d603445361405bdf043ee6fb2cfae17b5fded7111c3f1 | MATLAB | 4,324 | 112 | function f = ba_interp3_wrapper(vol,coords,interptype)
% function f = ba_interp3_wrapper(vol,coords,interptype)
%
% <vol> is a 3D matrix (can be complex-valued)
% <coords> is 3 x N with the matrix coordinates to interpolate at.
% one or more of the entries can be NaN.
% <interptype> (optional) is 'nearest' | 'linear... |
7030ac74f3142f184af8b1de7645eacc98ed0406e64add7f2b0aec72f1562c43 | MATLAB | 4,328 | 89 |
% Copyright 2025 Laura Schmid
% Permission is hereby granted, free of charge, to any person obtaining a
% copy of this software and associated documentation files (the
% “Software”), to deal in the Software without restriction, including
% without limitation the rights to use, copy, modify, merge, publish,
% distribu... |
28c0201728edee698e0c229ac89c3998233711d5a357a2a04f7d679cb640ceb1 | MATLAB | 4,330 | 119 | % Seed ROI to Cortex PAC Analysis
% This script computes phase-amplitude coupling (PAC) between a seed region of interest (ROI)
% and multiple cortical ROIs using bispectral analysis.
% The results are saved for each subject in a specified directory.
resultsDir = [main_path 'Results/source/']; % Directory containing s... |
469cbaecc08604c86468dedcc2be58d67ae8691658e39fdc8b8603198ab33f88 | MATLAB | 4,330 | 133 | function rgb_map = getColorMap(cTag, nRows)
% based on 'cTag', returns nRows x 3 RGB colormap
% (c) Jiri, Mar13
%% how many rows?
if nargin < 2
nRows = 256;
end
%% select colormap
switch cTag
case 'bwr'
N = ceil(nRows/4)-1;
rgb_bw = cat(2, linspace(0,1,N)', linspace(0,1,N)',ones(N,1));
... |
4a2cd1acfe5e52bf6eb741c79746f8c6fcfb0f9f9e1e8ac8f11fece4ee99052e | MATLAB | 4,333 | 137 | function stats = CalculateStats(I,windowsize,noverlap,nfft,SampleRate,Box,EntropyThreshold,AmplitudeThreshold,verbose)
if nargin <= 8
verbose = 1;
end
%% Ridge Detection
% Calculate entropy at each time point
stats.Entropy = geomean(I,1) ./ mean(I,1);
stats.Entropy = smooth(stats.Entropy,0.1,'rlowess')';
if Ampl... |
515e6776f6fd43a4dea42a6e65cd37175b9912b893d8a14cc20b4bd868fe3be3 | MATLAB | 4,334 | 120 | classdef McsVideo < handle
%UNTITLED Summary of this class goes here
% Detailed explanation goes here
properties %(Access = private)
playing = 0;
environment = [];
imageCube = [];
framerate = [];
curFrame = 1;
framehandl... |
73739d1ea8b63d608f5d2a3a0b930b2dcd0f5445fef641ec41279512c27fe859 | MATLAB | 4,335 | 109 | % logging_log() - logging_log logs messages if required by the current_level
% or LOG_LEVEL current_level superceeds log_level. if neither
% are set 'NOTICE' is used levels are ERROR, WARN, NOTICE,
% INFO, DEBUG from least verbose to most by default warning
% ... |
90c5d9e9195038451967eb91a18959a62432a1ce1ea205321a47d8b36e19a58f | MATLAB | 4,335 | 112 | function [FIT3D,Residuals,b]=PolyFit(Data3D,Mask,order);
dim=size(Data3D);
%% for volume fitting
Indices = find(Mask(:,:,:));
[x1,y1,z1]=ind2sub(size(Data3D(:,:,:)),Indices);
% x1 = cast(x1,'like',Data3D);
% y1 = cast(y1,'like',Data3D);
% z1 = cast(z1,'like',Data3D);
R=Data3D(Indices);
... |
6e4f915f6d831618eec07790e83b2a51c534b92bee81388a260a43d3b9daf78e | MATLAB | 4,340 | 148 | function plot_fig3d_left(datadir)
% Plot dopamine AUC at the offer cue (0-0.5 s) and model predicted RPE
% regressed against reward offers in the last 15 trials during mixed
% blocks. For visualization, only 7 trials back are shown. N = 10 rats.
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to do... |
12d54c1f7daab13812c3d2fa9f4dc72940fbb92b44f1e3dac6d27345f08598e6 | MATLAB | 4,341 | 148 | %% load in mesh output by fortran file
meshfile = '../../networkFVMsims/test/circpolyresv.mesh.txt'
MSH = MeshObj(meshfile);
%% load snapshots
snapfile = '../../networkFVMsims/test/circpolyresv.snap.txt';
[fields,snaptimes,vels] = loadSnapshotFVM(snapfile);
%% plot field on triangular mesh
% for this to work, n... |
4768a431deef76f4622df4f9d5f3c6613ba01c57cb237f2ea0abcd31c6ad299d | MATLAB | 4,341 | 105 | % REJTREND - detect linear trends in EEG activity and reject the
% epoched trials based on the accuracy of the linear
% fit.
% Usage:
% >> [rej rejE] = rejtrend( signal, winsize, maxslope, minR, step);
%
% Inputs:
% signal - 3 dimensional signal (channels x frames x trials)
%... |
df4f95d65fcf3d08f6746d191a1666779810b935b6aefbeb37a97687dda4c281 | MATLAB | 4,341 | 124 | % SPEC - power spectrum. This function replaces PSD function if the signal
% processing toolbox is not present. It uses the TIMEF function.
%
% Usage:
% >> [power freqs] = spec(X);
% >> [power freqs] = spec(X, nfft, fs, win, overlap);
%
% Inputs:
% X - data
% nfft - zero padding to length nfft... |
19498be5c52e1265419799ac5e5508389ace101ffc8ea5074bb6a4c38f0c893d | MATLAB | 4,345 | 156 | function test19()
% Test for complexcircle geometry (Phaseless signal reconstruction)
% Based on formulation by Waldspurger, d'Aspremont and Mallat, 2012, eq (4)
%
% This file is part of Manopt: www.manopt.org.
% Original author: Nicolas Boumal, Dec. 30, 2012.
% Contributors:
% Change log:
reset(RandStream.get... |
bdb430a339bf53cae02882c5ad4735b719b923056983686f8abd55ac3b54f569 | MATLAB | 4,345 | 112 | % SETFONT - Change all the fonts properties of a figure.
%
% Usage:
% >> newdata = setfont( handle, 'key', 'val');
% >> [newdata chlab] = setfont( handle, 'key' , 'val', ... );
% >> [newdata chlab] = setfont( handle, 'handletype', handletypevalue, 'key' , 'val', ... );
%
% Inputs:
% handle - [gcf,gca] ... |
3469d611a816e8ef79358d665020e85e3b38501fc5bb574d9a2f39eace09f5f7 | MATLAB | 4,346 | 129 | %{
# Optical Flow for all frames using Lucas-Kanade method
-> movies.OpticFlowOpt
-> stimulus.MovieClip
---
orientation : mediumblob # mean phase angle of optical flow
magnitude : mediumblob # Magnitude of optical flow
%}
classdef OpticFlowFine < dj.Computed
properties
keySour... |
2805cbf0db93108c575e733e0a301fd279967c4632637497eaf2b82aa8ac2915 | MATLAB | 4,347 | 148 | function nmri_check_seg(subject)
%nmri_check_seg(subject)
%
% Function to visually check (and edit if needed) the segmented MRI that
% is the basis for the headmodel step.
% Wraps around FSLeyes for the editing and deals with updating the
% mri_seg.mat if needed
% check for fsleyes
[cstat,cout]=system('whic... |
7c18ebd95db5ec7d1f675209675a356a23664201dbe34e98753102c41fa9ac56 | MATLAB | 4,349 | 96 | function plot3B()
%% b
% Pooled context (green) or
% stimulus (red) decoding accuracies from context (left) and stimulus (right)
% neurons, for cross-validation or generalization across pictures (red), contexts
% (green) and serial picture positions (blue).
load fig3Bdata.mat
YP=0.2... |
cd49fe7e6181e0b1c26057f42fbe319319558b2b298de9c885e89c82f255efc1 | MATLAB | 4,349 | 98 | % STD_MERGECLUST - Commandline function, to merge several clusters.
% Usage:
% >> [STUDY] = std_mergeclust(STUDY, ALLEEG, mrg_cls, name);
% Inputs:
% STUDY - EEGLAB STUDY set comprising some or all of the EEG datasets in ALLEEG.
% ALLEEG - global EEGLAB vector of EEG struct... |
d0dc2340de4c6a83e0430e6c88559deab05ed3deefa3b5a312cae38639d8d7a8 | MATLAB | 4,350 | 103 | % IMAGESCLOGY - make an imagesc(0) plot with log y-axis values (ala SEMILOGY)
%
% Usage: >> imagesclogy(times,freqs,data);
% Usage: >> imagesclogy(times,freqs,data,clim,xticks,yticks,'key','val',...);
%
% Inputs:
% times = vector of x-axis values
% freqs = vector of y-axis values (LOG spaced)
% data = matrix o... |
d7c3ac1d0038350f729afe84ee23f8cee3a8b9f7ff369f51185ae3198ff9e7f0 | MATLAB | 4,351 | 126 | function tileCoef = sttc_m(N1v, N2v, dtv, Time, spike_times_1, spike_times_2)
%sttc calculates the spike timing tiling coefficient
% Originally written in C by Cutts and Eglen
% https://github.com/CCutts/Detecting_pairwise_correlations_in_spike_trains/blob/master/spike_time_tiling_coefficient.c
% See their 2014 p... |
e263f3e59eb0aa26598e504cdadebd49e9aa866ffaed715dccbd4fde192cac55 | MATLAB | 4,351 | 175 | function [Mu, Cov, P, Pi, LL] = ZG_hmm(X,T,K,cyc,tol)
% Gaussian Observation Hidden Markov Model
%
% X - N x p data matrix
% T - length of each sequence (N must evenly divide by T, default T=N)
% K - number of states (default 2)
% cyc - maximum number of cycles of Baum-Welch (default 100)
% tol - termination tolerance ... |
26f36eaf184f1f9fdd5eb01829a11ddd1a32b804d4e346f78f1cb76c1aa1b006 | MATLAB | 4,352 | 117 | function opt=defaultOpt(optIn,defVal,defRange,strictClass)
%function opt=defaultOpt(optIn,defVal,defRange,strictClass)
%
% This takes in a option flag structure [optIn] and the default
% values of each of the fields [defVal]. It will set the option
% fields to the default value when the field in [optIn] does not
% exis... |
c9d1c0c109d249dd5d6b79ca2f56761cdac951646e691c54dc0a8c1b79a289df | MATLAB | 4,357 | 130 | function run_permuranova2_examples
%RUN_PERMURANOVA2_EXAMPLES Run two-way permutation RM ANOVA examples.
% Generates random 3D repeated-measures data (Subjects x Factor A x
% Factor B). Factor A has 2 levels and Factor B has 3 levels. Main
% effects and an interaction effect are injected along with a subject
% ... |
bfa8c759990bd015009f726f9a13eaf7775b46123cdd6211ff3dacbc6a0c1074 | MATLAB | 4,359 | 98 | %% %%%%%%%% Generate maps of prf results
% define
resultsdir = [nsd_datalocation '/ppdata/subj%02d/func1mm/'];
files = ...
...% name fname mgz name color range color map transform function circular
{ ...
{'R2' 'prfR2' 'prfR2' [0 1] ... |
592330f3ca5bb4fd56be8cd98abab869ca4d00e0bed196cad5aa63d1c725092d | MATLAB | 4,361 | 135 | function DebugBatch(mfile,bfile,item,varargin)
%DebugBatch - Help debug a batch job.
%
% This function can be used to help debug a batch. It retrieves the parameters
% corresponding to the required item from the batch file, and either starts
% the batch function with these parameters in debug mode, or simply assign... |
c8bc3ed091865053c810c3e9c99f44f17c3caf19fbbdd9a30db460c9d9692335 | MATLAB | 4,363 | 120 | function ch2roi_plot_AUC_allFB_allROI(GRUP, groupInfo)
% plots AUC (area under the curve), or sum in certain time window, for
% - clz 1 vs. baseline
% - clz 2 vs. baseline
% - clz 1 vs. clz 2
% (c) Jiri, Jun23
%% settings: AUC
if ~isfield(groupInfo, 'AUC_settings')
groupInfo.AUC_settings.baselineWindow =... |
b0dbba322077877e1379aa9a7a632c3b9773158f9153d012255ba9496da43fcf | MATLAB | 4,365 | 163 | function varargout=shadedErrorBar(x,y,errBar,lineProps,transparent)
% function H=shadedErrorBar(x,y,errBar,lineProps,transparent)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
% Inputs
% x - vector of x values [optional, can be left em... |
4562717ad53fb609b313ad1cd374e378385f41c2e36f42fa5c8cdb74b0e73eee | MATLAB | 4,366 | 118 | function x = gen_gamma_integer_array(alpha, theta, L, N)
% ATTTREC_GENERATE_GAMMA_INTEGER_ARRAY Allocate N integers via Gamma-proportional rounding.
%
% Syntax
% x = atttRec_generate_gamma_integer_array(alpha, theta, L, N)
%
% Description
% Draw L i.i.d. Gamma(shape=alpha, scale=theta) samples, convert them into a... |
7a7b84361f306f9822aab51fc2e9bdfecaf6362f9de207adb803957ee8f97045 | MATLAB | 4,368 | 93 | function plotHeatMap(fig, coordinates, heat, sensorDimension)
%plot all rectangles into fig onto all coordinates and sets face color to
%the value specified in heat
fig;
clf(fig);
data = guidata(fig);
%create custom grid
g_y = 0:1:sensorDimension(1)+1; % user defined grid Y [start... |
bc01bb1153c15863d2d93e4541d42e247adb3515071ce5522feebce1de0c10da | MATLAB | 4,369 | 143 | function run_permuvartest_examples
%RUN_PERMUVARTEST_EXAMPLES Run one-sample bootstrap chi-squared test examples.
% Generates random multivariate data for samples X. Each sample has 20
% variables, each with a standard deviation of 1, except for the first 10
% variables of X which have a standard deviation of 2.... |
723cd8995e4d98652bdc4cf67fda4d8c1cad149ceab75092810b5039d7698e82 | MATLAB | 4,372 | 128 | % POP_READSEGEGI - load a segmented EGI EEG file. Pop up query
% window if no arguments.
% Usage:
% >> EEG = pop_readsegegi; % a window pops up
% >> EEG = pop_readsegegi( filename ); % no pop-up window
%
% Inputs:
% filename - first EGI file name
%
% Outputs:
% EEG ... |
ce9923d42942f60e26e7de5c560813b13d63a1cbf2046e370e0e92d2f3620b5c | MATLAB | 4,372 | 153 | function plot_fig3e_right(datadir)
% Plot dopamine AUC at the offer cue (0-0.5 s) vs -delta trial initiation
% time, averaged across rats. N = 10 rats.
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to download can
% be found in README.
fname = fullfile(datadir, 'data-published/deltaITI_vs_AUC.ma... |
154f0c7b4aef3b7b8b43794d377175ec79d371a8681d2fffd0ba5e4cc318414e | MATLAB | 4,373 | 153 | function [deltaCVnLL, deltaAIC, deltaBIC, pvals, ratList] =...
model_comparison(mdl1_projectname, mdl1, mdl2_projectname, mdl2,...
nll_arg, aic_arg, bic_arg, plotarg, varargin)
% Performs model comparison. All differenes are mdl2 - mdl1.
% Inputs:
% mdl1_projectname - Project name for model 1
% mdl1 - Model... |
531ba290cd51e0390aa89558cca7158935fb16e66b90feabbfb4998325840ac9 | MATLAB | 4,373 | 110 | % Convert feature prediction results fot deep image reconstruction
%
% Output files:
%
% decodedfeatures -+- imagery --- matconvnet -+- cnn1 -+- Subject1 -+- FFA --- Mat files
% | | | |
% | | | +- LOC... |
f4b35b0ffe6d1cc0868ba0b9d59179de13ecbaa86070789fa1374be207acdb48 | MATLAB | 4,374 | 92 | %% create MT = part of hMT+ which is not MST
%this script create rois MT = part of hMT+ which is not MST by impleenting
%rhMT minus rMst
% MOST UPDATED and CORRECT feb 2024
% it is important to use these masks so that we identify the clusters which are not connected to other regions
% hMT+: from visual Motion Local... |
0565c3bf56096ed131507591728e1ee72cbeddd50367abbfe29dff833f2f1be5 | MATLAB | 4,375 | 137 | function [result] = fit_happy_model_inequalitySimple(mtx,happyscore,constant)
%assumes that each row of the cell array is a different subject
rptfit = 5; %repeat N times jittering the betas
tempf=fieldnames(mtx);
for n=1:length(tempf), eval(sprintf('mtx.%s=double(mtx.%s);',tempf{n},tempf{n})); end;
data = mtx;
data.h... |
0621fe3302c0c3ea010f0cd6a172582853b0700406c3c81e2e778d4b2a686d92 | MATLAB | 4,375 | 126 | function varargout = raster2D_ani(s0, t0, t1, Ne1)
%RASTER2D_ANI Animate a 2‑D raster from spike times.
% RASTER2D_ANI(s0, t0, t1, Ne1) animates spikes binned in 2 ms steps
% between times t0 and t1 (inclusive). If s0 has two rows, it is
% interpreted as [t; linearIndex]; if it has three rows, it is
% interpret... |
4c931fa328424f57bf067fb9f29c1aa376e4e59978c4d23daf3a591144e862dd | MATLAB | 4,375 | 137 | function obj = setup_data(obj, terms)
% obj = setup_data(obj, terms)
%
% Given a meta_dataaset object and terms, do the following:
% 1) Select contrasts and voxels that meet cutoffs
% 2) Load term text files
% 3) Select studies that involve only one term
%
%
% Parameters used, with default values from meta_dataset cons... |
5fa0548031925619826f38b98734a0855c56066dc3ee2a029084666c15da6609 | MATLAB | 4,376 | 124 | function outputImage = remove_clusters(this, varargin)
% Removes all voxel clusters within a given range of voxel counts, and/or
% a given range of percent of the area that is (approximately) filled;
% either slice-wise or volume-wise (8 or 26 neighbours) using Matlab's
% bwareaopen
%
% Y = MrImage()
% clusterRemov... |
7416d706cfe94c84d984b44c252f449cae7380922e7599754361adf821a8850d | MATLAB | 4,376 | 127 | % (C) Copyright 2020 CPP visual motion localizer developpers
function [cfg] = expDesign(cfg, displayFigs)
% Creates the sequence of blocks and the events in them
%
% The conditions are consecutive static and motion blocks
% (Gives better results than randomised).
%
% Style guide: constants are ... |
9c11169a3c2d004c68b7a8ce514b0889220718e02cb5215dfd8aeeb50d7d4036 | MATLAB | 4,376 | 126 | % FILLCURVES - fill the space between 2 curves
%
% Usage:
% h=fillcurves( Y1, Y2);
% h=fillcurves( X, Y1, Y2, color, transparent[0 to 1]);
%
% Example:
% a = rand(1, 50);
% b = rand(1, 50)+2; b(10) = NaN;
% figure; fillcurves([51:100], a, b);
%
% Author: A. Delorme, SCCN, INC, UCSD/CERCO, CNRS
% Copyright (C... |
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