sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3a8e008431e9c70a89b54d94f2a465042906b26272ad5d8812c449fb6629cfc6 | MATLAB | 2,904 | 96 | function handles = plotFilledArea(x, y, varargin)
% PLOTFILLEDAREA Plot filled area under curve
%
% Syntax:
% h = plotFilledArea(x, y)
% h = plotFilledArea(x, y, 'Name', Value, ...)
%
% Description:
% Creates a filled area plot from baseline to curve.
%
% Inputs:
% x - X values (vector)
% y - Y values (vector... |
79a723d208520748372518ee51b3bfbdb402ab48ff1e8507aa215d48d0baaa7d | MATLAB | 2,904 | 98 | function FigureS9(datadir, codedir)
%FigureS9 - Inferential model identifies mistaken inferences during mixed
% blocks across rats
% datadir = directory of dataset
% codedir = director of code
%% Set up paths
s = pathsep;
pathStr = [s, path, s];
onPath = contains(pathStr,...
codedir, 'IgnoreCase', ispc);
i... |
71ee5629fcb6268187dede01bb09b6a3b20bd1219fe321cf650a1d9127357acd | MATLAB | 2,905 | 55 | % Session data handling functions for FMAToolbox.
%
% FMAToolbox provides a number of functions to handle data files stored
% in the open and hardware-independent <a href="http://neuroscope.sourceforge.net/UserManual/data-files.html">formats</a> used by <a href="http://klusters.sourceforge.net">Klusters</a>, <a href="h... |
8659e36a3992adfee5ed914c25734fc5bec93bafdbe5f1ae028dc150b36cb849 | MATLAB | 2,905 | 85 | function [vertices,faces] = freesurfer_read_ascii(file)
% freesurfer_read_ascii - Read FreeSurfer tesselation (.txt)
%
% [vertices,faces] = freesurfer_read_ascii(file)
%
% This function will load an ascii file that contains a one
% line specification of the number of vertices and faces,
% followed by rows of vertex poi... |
557d2447e4be65640acde895067521e78047da1b1bef1a1167af5f4683649c20 | MATLAB | 2,908 | 79 | % EEG_CACHE - Store data in cache with hashcode
%
% >> [cache data] = eeg_cache(cache, hashcode, data);
%
% Inputs:
% cache - Cell array containing cached data
% hashcode - MD5 hashcode
%
% Optional input:
% data - This can be anything
%
% Outputs:
% cache - Updated cache information
% dat... |
7ddd1b70ea77d9cfff7a052394364130971b521c43a73b25398ac66687880bd9 | MATLAB | 2,908 | 81 | classdef nnloss < nntest
properties (TestParameter)
loss = {...
'classerror', 'log', 'softmaxlog', 'mhinge', 'mshinge', ...
'binaryerror', 'binarylog', 'logistic', 'hinge'}
weighed = {false, true}
end
properties
x
end
methods
function [x,c,dzdy,instanceWeights] = getx(test,loss)
... |
db78fe0d4a3e56fd0d9447f5c5118033fbc9c5479cd79fde49bdab0cd107474a | MATLAB | 2,908 | 56 | function [finalgradientval, gradientdiff, sum_down, sum_up, count_down, count_up, mingradientval, maxgradientval, startgradientval] = quant_specific_linear(xvals)
%% quant_specific_linear includes additional analyses for single-worm linear assays.
global info
global vals
B = ~isnan(xvals);
Indices = arrayfun(@(x) find... |
a3a53f10dc2f8b5d7f177b33d8739e64a6a9b2273012a1d57da3736579af587e | MATLAB | 2,909 | 109 | function th = threshold_for_far(target_far,hsi,det_img,filt,params)
% th = threshold_for_far(target_far,hsi,det_img,filt,params)
%
% finds the threshold for a given false alarm rate in the detector output image (det_img)
%
% 2/9/2013 - Taylor Glenn - tcg@cise.ufl.edu
if ~exist('params','var') || isempty(params)
... |
7c778a0d307b8d55b06949ce8819426dd4c313dbe8f1fcaea670b97acbff3b93 | MATLAB | 2,910 | 79 | %% get_set_swismwi_swi_2dhamming(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 sh... |
e4dd709c6fc0f55c7418af00853d003368fd2929fdf75815e737afa24fb0c5cd | MATLAB | 2,910 | 79 | %% get_set_swismwi_swi_2dhamming(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 sh... |
3aa71609c581179ae13a0b393a9b266bde6f22d8d6ad3f71d565e58975f88d18 | MATLAB | 2,911 | 119 | addpath("~/ER_Ca_rot/networkSpreadFVM-main/scripts/");
addpath("~/ER_Ca_rot/networkSpreadFVM-main/examples/");
dirname = "~/ER_Ca_rot/networkSpreadFVM-main/examples/Kd_op/Output";
%filen= strings(5,51);
ar = [0, 1.089, 2.178, 2.755, 4.356]; %diffusion constants
ar1 = [-13.815, -13.539, -13.262, -12.986, -12.710, -12.43... |
7c90b6a217e2b6e262793d3f7354e20289abf65a5e0e7103404e2907aaa282f9 | MATLAB | 2,912 | 126 | %% %%%%% PHYSIO (just modify/hack physioinspections.m)
% create physio inspection figures
types = {'puls' 'resp'};
for qq=1:length(types)
typ = types{qq};
alldata = {};
for subjix=1
for sess=25
for runix=1:14
file0 = sprintf('~/nsd/nsddata_timeseries/ppdata/subj%02d/physio/physio_session%02d_ru... |
d1edb3555717abbd6bc58c4765a38d599d06975c64ea7e394c90ee938d3779ef | MATLAB | 2,912 | 82 | function varargout = preTrialSetup(varargin)
%
% [thisEvent, thisFixation, cfg] = postInitializatinSetup(cfg, iBlock, iEvent)
%
%
% (C) Copyright 2020 CPP visual motion localizer developers
% generic function to prepare some structure before each trial
[cfg, iBlock, iEvent] = deal(varargin... |
3228d9193eb6feb4a467c1b7743bb32e411beac7de7d6a1f30598ff067469fe0 | MATLAB | 2,913 | 71 | clear all
close all
clc
exp_root = 'C:\Users\User\Documents\fMRI_EXP\';
more_code = fullfile(exp_root, 'cells_data_muller');
data_folder = fullfile(more_code, 'wetransfer_neil-s-data_2023-09-25_1057');
addpath(genpath(more_code));
addpath(genpath(data_folder));
%load('grid_animal4.mat')
load('grid_animal3.mat')
num_g... |
a040cffa07c2d76dc9fe833db8ce0323d59ea16c8bdf682ab05e26d83f85fbfc | MATLAB | 2,913 | 64 | function subtypes=graphical_model_prediction(subtypes_model,P_training, P, dHausdorff, K, thd, alpha)
% predict the subtype membership for the new data
N = length(subtypes_model);
D = ones(1,N)*inf;
x=1;
for y=1:N
% compare the temporal orders
[~,sortedindexY] = sort(cell2mat(P_training{y,1}(:,4)),... |
8bdea27b9e415bbd28d1b3f0e7b019a36b196849b3720af9b6ae81adef5f8dfa | MATLAB | 2,916 | 75 | function yBin = BF_Binarize(y,binarizeHow)
% BF_Binarize Converts an input vector into a binarized version
% ------------------------------------------------------------------------------
% Copyright (C) 2013-2026, Ben D. Fulcher <ben.d.fulcher@gmail.com>,
% <http://www.benfulcher.com>
%
% If you use this code for ... |
a349b2aa449bcf6c6146a003eaf2278e89d4a6ce58a6a8719cb52b6362909fd2 | MATLAB | 2,916 | 76 | function [readyParams] = check_MLparams(params,defaultParams)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% check_MLparams checks parameters provided and returns default parameter
% for an ML algorithm using a structure including default parameters. It
% also throws warning messages if a... |
a5215d2d08218fa26459264073eddb208ca12599059dede8dacd054266f2a3b6 | MATLAB | 2,916 | 71 | function [bestParam,bestParamScore,bestParamIdx] = bayesOpt(objFun,...
data,paramGrid,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% bayesOpt performs bayesian optimization over parameters provided.
%
% Arguments:
% objFun = Objective function (e.g., estimator).
% data =... |
e5bdf2517cc4e54c09337bc1add792a19239f8be6afb56b12588fa3be74b9ac6 | MATLAB | 2,916 | 91 | % GETALLMENUS - get all submenus of a window or a menu and return
% a tree.
%
% Usage:
% >> [tree nb] = getallmenus( handler );
%
% Inputs:
% handler - handler of the window or of a menu
%
% Outputs:
% tree - text output
% nb - number of elements in the tree
%
% Author: Arnaud ... |
94d4f2e2bb6705f7f7fc5f1b5c74f7b7b3cad404ba1b96520301183614d38505 | MATLAB | 2,917 | 83 | function data = GetSpikeWaveforms(unit,varargin)
%GetSpikeWaveforms - Get spike waveforms.
%
% USAGE
%
% waveforms = GetSpikeWaveforms(unit,<options>)
%
% unit [electrode group,cluster] pair
% <options> optional list of property-value pairs (see table below)
%
% ============================... |
9ca55f32225a85d7b8515e8935dad43a845bc536343a4a2a3d2e75bf576029fa | MATLAB | 2,917 | 89 | function PlotCSD(csd,varargin)
%PlotCSD - Plot current source density.
%
% USAGE
%
% PlotCSD(csd,<options>)
%
% csd current source density <a href="matlab:help samples">samples</a> (see <a href="matlab:help CSD">CSD</a>)
% <options> optional list of property-value pairs (see table below)
%
% ... |
7b7946415a83a9ab02d9a717597d4bd4d673784780b28d0c8bcd574f8f61b8b4 | MATLAB | 2,918 | 96 | % function [lik,likv] = hmm_cl(X,T,K,Mu,Cov,P,Pi);
%
% Calculate Likelihood for 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
% Mu - mean vectors
% Cov - output covariance matrix (full, tied across states)
% P - state transi... |
c4f08c0fbca514a4d0adc310701bdefbfffa62c303d851495244dfbb9f1dae34 | MATLAB | 2,918 | 64 | % This is an example code that shows how to export and import back data for manual adjustment of human Neuropixels recordings
% with Blender, following by adjusting the ap.bin data accroding to manual
% annotation.
lfp_data_file = '{your data path}\data_file.lfp.bin';
ap_data_file = '{your data path}\data_file.ap.bin... |
d6871b51cf3693d78641dd9ec6cb153c6cfa122958db4fd5ca9960cc2c8a30e5 | MATLAB | 2,918 | 118 | function [lEvec,rEvec,Evals,xtras] = epca(varargin)
% Return the first p eigenvectors and eigenvalues.
%
% Usage:
% [lEvec,rEvec,Evals,xtras] = epca(X,p,dim,norm)
%
% Inputs:
% X : 2D array
% p : Number of eigenvectors and eigenvalues to be
% returned.
% dim : Dimension used for mean-centering.
% ... |
ef405b6e0f24b52bcd82c1128c7974b49b785bad0ad109c0daf05b1b4ff0c958 | MATLAB | 2,919 | 109 | function afni_niml_test_io(fns)
% simple test function for i/o capabilities of afni_niml_{read,parse,print,write}
%
% AFNI_NIML_TEST_IO(FNS), where FNS is a cell with filenames, reads each of
% the files indicated in FNS, tests whether parsing and printing are
% reverse operations, and writes the files to a new file. I... |
89d23e69278a0f84b8fc2b419cf06296144e4f97f28a4d585e6ccb4dcfc6ff09 | MATLAB | 2,920 | 97 | function getTriggers_emoReco_objectEmotion(params)
% determines & saves trigger times and class labels
% (c) Jiri, Mar16
display([' - finding events for: ' params.thisCategory]);
%% per session: load trials, find events and save
for sess = 1:size(params.storage.sessionCacheFiles,2)
% load trials
clear t... |
e1caf0b9a5e594151a1688f9e5d96dd849a13c988417d9040e61d2ccaf3cf815 | MATLAB | 2,921 | 62 | function start_cat(NiiFile, atlas, Template)
%
% Input: NiiFile <string> fullpath to T1 MRI image to be segmented.
% atlas <string> fullpath to cortical atlas used by CAT12.
% Template <string> fullpath to prior probability distribution
% template used ... |
49069d5517ec277153a45e06c4f0cba65da9174092e8d3ac9c63fa39efc40915 | MATLAB | 2,923 | 126 | function vl_simplenn_diagnose(net, res)
%VL_SIMPLENN_DIAGNOSE Plot diagnostic information on a SimpleNN network.
% VL_SIMPLENN_DIAGNOSE(NET, RES) plots in the current window
% the average, maximum, and miminum element for all the filters
% and biases in the network NET. If RES is also provided, it will
% plot ... |
44b98ea19c233790a9ce8c7def6ee081fa28065ddb41f1e21002eb4dfb43fb52 | MATLAB | 2,924 | 95 | function varargout = opensignals_txt(filename, hdr, begsample, endsample, chanindx)
% OPENSIGNALS_TXT reads time series data from a Bitalino OpenSignals txt file
%
% Use as
% hdr = opensignals_txt(filename);
% dat = opensignals_txt(filename, hdr, begsample, endsample, chanindx);
% evt = opensignals_txt(filename,... |
5e71c7975487aad6e6f3139c5e8ecc3160f31af9b490f52698a80dc4f100d329 | MATLAB | 2,925 | 81 | function str = fixname(str, version)
% FIXNAME changes all inappropriate characters in a string into '_'
% so that it can be used as a filename or as a field name in a structure.
% If the string begins with a digit, an 'x' is prepended.
%
% Use as
% str = fixname(str)
%
% MATLAB 2014a introduces the matlab.lang.make... |
b99619739bbc463ef479470a14ae22d797a90bd4f826dd85f500020b9fa65b27 | MATLAB | 2,925 | 94 | function B = ar_mls(TS,p)
% [Y,B,Z,E] = CBIG_RL2017_ar_mls(TS,p)
% This function identifies an autoregressive (AR) model from multivariate time series using the multivariate least square approach
% Input
% 'TS' original time course encoded in a matrix of size (T=number of time points,k=number of variables... |
ed3265bac66d2074be618803a2d4e0a49791398c83cdd96a3ab7620cf69d4963 | MATLAB | 2,926 | 106 | function diplayDesign(cfg, displayFigs)
%
% diplayDesign(cfg, displayFigs)
%
%
% (C) Copyright 2020 CPP visual motion localizer developers
%% Visualize the design matrix
if displayFigs
close all;
figure(1);
% Shows blocks (static and motion) and events (motion dir... |
05ad7b590f42cc9173cbbfc415f51a4ddf23208f011839ecd5c9bcb98d9f7e52 | MATLAB | 2,927 | 61 | function K = apxSparse(cov, xu, hyp, x, z)
% apxSparse - Covariance function for sparse approximations.
%
% This is a special covariance function which handles some non-standard
% requirements of sparse covariances
% 1) it holds the inducing inputs in xu, and
% 2) it returns covariances for prediction purposes.... |
13f90a55f068ed0826a3d267f77a2896435803843ec72b5b99bba56c55e7b7af | MATLAB | 2,927 | 76 | function firstlevel_decision()
% Representative integrated decision model for Figure 4.
% Loads archived multi-condition files and removes Miss/empty conditions.
%% USER SETTINGS
rootDir = 'D:\path\to\MRI_project';
condDir = 'D:\path\to\conditions_mat';
spmDir = 'C:\path\to\spm';
subName='sub-001';
emID='em0001';
nR... |
20ecf103ca64d7b05939075e5920c07c64e7a3c95e5613c0953738108f3a8628 | MATLAB | 2,927 | 101 |
% This code acquires significantly related genes with MFC using PLS
ROI = {'A1C'
'DFC'
'IPC'
'ITC'
'M1C'
'MFC'
'OFC'
'S1C'
'STC'
'V1C'
'VFC'};
Gene_expr_pre = readmatrix('./data/gene_expression.csv');
load('./data/Gene_label.mat')
load('./data/MFC.mat')
genes=Gene_label; % this needs to be imported first
geneindex... |
c80a41c8ac19a8baa42d283f74a6befbb5e7bbbe91db557556308034cd37218e | MATLAB | 2,927 | 119 | function [D,x0, side] = axons_setup(axons, lawname, k)
% author : Tom Mingasson
% axonsSetup creates a randomly generated axon gamma or lognormal distribution and initilialize axons positions in a square area defined by its length 'side'.
% diameters distribution under a gamma or lognormal law
D = samplingHastingsMet... |
6956dccfbda6bb99aa3df548d2bb284790682e4b61862c4df4f457eec5e58253 | MATLAB | 2,929 | 113 | function plot_fig4h(datadir)
% Plot reward port nose poke probability during the delay period
% during mixed block. N = 16 rats.
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to download can
% be found in README.
load(fullfile(datadir, 'data-published/ratlist.mat'), 'ratList');
pokeProb = cell... |
ad42835d6c7036e3f69d08fb5fae1201e7f7239a56aeee45628319c9d1d8a608 | MATLAB | 2,931 | 81 | function LOCS = tapas_physio_create_LOCS_from_VOLLOCS(VOLLOCS, t, sqpar)
% Compute slice scan events as locations in time vector (LOCS) from volume
% scan locations and sequence parameters (TR, nSlices)
%
% LOCS = tapas_physio_create_LOCS_from_VOLLOCS(VOLLOCS, t, sqpar);
%
%
% IN
% NOTE: The detailed description of a... |
fa02584492d97470c3d263d0662b92a8133589f219022d9428c1e5628e5cc731 | MATLAB | 2,932 | 71 | function c = tapas_softmax_binary_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the softmax observation model for binary responses
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
e43a92ea679c0eb7b3a8aa7432537fec309fe343669bb870721aac9c4602fe7b | MATLAB | 2,933 | 59 | function Er = pipelineCompareDynamicEnergyAfterShuffle(time_series, control_node, window_size, r_time)
% Pipeline of Compare dynamic control energy before and after shuffle
% dynamicMiniEnergy to calculate the control energy.
% This pipeline include:
% 1. random select the start point and final point
% ... |
e4f36f0d46f71adc4705107474178b9bcb499fe27c8dd0a1b39215b51633f564 | MATLAB | 2,934 | 85 | function [logp, yhat, res] = tapas_logrt_linear_whatworld(r, infStates, ptrans)
% Calculates the log-probability of log-reaction times y (in units of log-ms) according to the
% linear log-RT model developed with Louise Marshall and Sven Bestmann
%
% ----------------------------------------------------------------------... |
fe951863c0ad86823a76cab22dc0e7f89aaa24a9a8001534b6827dfe8780803a | MATLAB | 2,935 | 72 | function ppc = PPC(phases,input2)
%PPC - compute Pairwise Phase Consistency across spikes
%
% ppc = PPC(phases) computes the Pairwise Phase Consistency as defined by
% Vinck, Wingerden, Womelsdorf, Fries, Pennartz (2010, NeuroImage)
% ppc = PPC(phases,trialID) computes P(hat)2 Pairwise Phase Consistency
% as define... |
1de5c37d239606e49b768fb92a8343abddc7cdda003d79578ebc3f9410a52032 | MATLAB | 2,936 | 102 | function M = centeredmatrixfactory(m, n, rows_or_cols)
% Linear manifold struct. for optimization over matrices with centered cols
%
% function M = centeredmatrixfactory(m, n)
% function M = centeredmatrixfactory(m, n, 'cols')
% function M = centeredmatrixfactory(m, n, 'rows')
%
% Returns M, a structure for Manopt desc... |
b17ae588502f1e60c83005af4a8fb7504d800b5e3998bec93bb2a911957a22df | MATLAB | 2,937 | 112 | function [pval, k, K] = circ_kuipertest(alpha1, alpha2, res, vis_on)
% [pval, k, K] = circ_kuipertest(sample1, sample2, res, vis_on)
%
% The Kuiper two-sample test tests whether the two samples differ
% significantly.The difference can be in any property, such as mean
% location and dispersion. It is a circula... |
f7b2ad04110502de86e4283a12f7a43f5b364a84d509971906950716ef75be6e | MATLAB | 2,937 | 66 | function [brainVolumes, mni_vox] = brainVolumes_chSpec(params, struct_plotBrain, channelStruct, fixedVols, inds_vol, groupInfo)
% updates/loads channel-specific brain volumes for slices plotting (defined for each channel separately)
% updates if fixedVols{vol}.loaded = 0
% input:
% - params struct
% - struct_plotBr... |
3fe06de660cf1641ca3172a0fef6a38440014f2de6ff78bbb99c7171bd90da2a | MATLAB | 2,938 | 80 | function out = ST_FitPolynomial(y, k)
% ST_FitPolynomial Goodness of a polynomial fit to a time series
%
% Usually kind of a stupid thing to do with a time series, but it's sometimes
% somehow informative for time series with large trends.
%
% ---INPUTS:
% y, the input time series.
% k, the order of the polynomial to... |
613b0459f78f1cee7d3f2ec4bb9789e16e42da6cf4b3b3f4f98dc2206b06240e | MATLAB | 2,938 | 82 | function data = check_workspace(wp_dir)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% check_workspace checks if the workspace directory contains all necessary
% files
%
% Arguments:
% wp_dir: Workspace directory
%
% Output:
% data: Structure containing the paths of the files
%
% Exam... |
6f5c3d35cab76ccd282bb034bf48bd4bb1b5d7b7756defdccad34324579944ac | MATLAB | 2,938 | 100 | function tapas_hhmm_binary_displayResults(r)
% Displays results estimated by fitModel for the hmm perceptual model in the binary case
% Usage: est = fitModel(responses, inputs); hmm_binary_displayResults(est);
%
% --------------------------------------------------------------------------------------------------
% Copy... |
9ea6863cccd0ab02bc8cd42267951bcefef738cb2ef8035044bb083096c77103 | MATLAB | 2,938 | 93 | function [MRSCont] = OspreyRebase(MRSCont)
%% [MRSCont] = OspreyRebase(MRSCont)
% This function allows you to rebase your derviatives folder and files in
% case you have processed them on another machine
%
% USAGE:
% MRSCont = OspreyRebase(MRSCont);
%
% INPUTS:
% MRSCont = Osprey MRS data contai... |
f878f8b1d33516452ed44ad491bde31df3c646b7b98bb78bae717f285974bdb7 | MATLAB | 2,939 | 82 | function physio = tapas_physio_prepend_absolute_paths(physio)
% prepend absolute paths for file names, in particular save_dir; creates
% save_dir, if necessary
%
% physio = tapas_physio_prepend_absolute_paths(physio)
%
% IN
%
% OUT
%
% EXAMPLE
% tapas_physio_prepend_absolute_paths
%
% See also
% Author: Lars Kas... |
9225c5c5b8d1cc03288979b7491d3fd9b59da969a43ddaa647a3a38e035abe42 | MATLAB | 2,940 | 89 | function f = constructbutterfilter3D(matrixsize,cutoff,order,mode)
% function f = constructbutterfilter3D(matrixsize,cutoff,order,mode)
%
% <matrixsize> is [A B C] with the dimensions of the 3D volume
% <cutoff> is a 3-element cell vector with each element being:
% A means low-pass filter cutoff (in cycles per field... |
f6090b0c90d71979a110ebb5df409670803074f619825f6a87381a76b039d0e3 | MATLAB | 2,940 | 81 | function s = hlp_handleerror(e,level)
% Displays a formatted error message for some error object, including a full stack trace.
% hlp_handleerror(Error, Indent)
%
% In:
% Error : error object, as received from lasterror or via a catch clause
% (if omitted, lasterror is used)
% Indent : optional inden... |
7c9bf7b5ddcaa3c5decb4db0ea5a1fb0b98eaa3192d2ad554a75f2e188882325 | MATLAB | 2,941 | 82 | function transform_to_ctf(input_img)
%
% Input: input_img <string> fullpath to T1 MRI image to be segmented
%
% This function transforms all coordinate system depending results of this
% segmentaion pipeline into the ctf coordinate system. It does the follwoing:
% 1. Reads fiducials from nonlinear alignement.
%... |
39058a158a5f8f12a57cb0dea2c768cb8e451a2abf348a20d485a97a0d2587fa | MATLAB | 2,943 | 126 | function [pt,st] = contingency_table(varargin)
% function [pt,st] = contingency_table(varargin)
%
% makes 2-way contingency tables for pairs of variables
% varargin arguments are variables
% vars must be column cell array vectors containing strings
%
% pt: Table of point (coordinate) counts
% st: Table of unique study... |
47c4a2097bcd745b51c91877b05ba40751939b9db0828cd609ce865cf258d4a2 | MATLAB | 2,943 | 85 | function compile_all
% Compile all EIF normalization MEX files into sim_script/mex
% Folder layout (relative to this script):
% sim_script/
% compile_all.m
% mex/ (created if missing)
% src/
% common/ (EIF_common.c, EIF_common.h)
% variants/ (multiple EIF_normalizat... |
aadc46f4d721f0b28e6b59b16a137de77ae3b5b47588801a16fdf2f93229e847 | MATLAB | 2,943 | 98 | function output = cvClassifier(data, nFolds, nPartitions, type, reg)
% The fraction test is 1/nPartitions * 100, for 5 partitions 20% of the
% trials are held out in each model fit, making the cross validation an
% 80/20 split
if nargin < 2
% With nFolds and nPartitions at default, 10 models will be fit
nFol... |
ebbe64133db9c8db6ac81153347f1b3dd4893902c9a7d723c0750c2da1851664 | MATLAB | 2,943 | 72 | function plot(recording,cfg,varargin)
% Plot the contents of a McsCmosRecording object
%
% function plot(recording,cfg,varargin)
%
% Input:
% recording - A McsCmosRecording object
%
% cfg - Either empty (for default parameters) or a structure with
% (some of) the following f... |
a00eb80f0e79a0ef20ef71ca8ee500a2ee568867941000c0bb64ca658cfe7c26 | MATLAB | 2,944 | 112 | %% Colormaps that are pretty awesome: DEMO1
% this is an exampe of 4 colormaps that are being considered as the default
% colormap in python's matplotlib lybrary.
%
% All of them look quite good and they dont have any official name, so at
% the moment they are A,B,C,D.
%
% colormaps from https://github.com/bids/... |
a64978d33386b52a97624a33636c3a98f07a6bdab166d9a7b6d1fcd337252fd4 | MATLAB | 2,945 | 113 | % op_takeextra.m
% Jamie Near, McGill University 2014.
%
% USAGE:
% out=op_takesubspec(in,index);
%
% DESCRIPTION:
% Extract the subspectra with indices corresponding to the 'index' input
% array.
%
% INPUTS:
% in = input data in matlab structure format.
% index = vector indicating the indices of the subspectr... |
42d3c493498149d113e7badfd679772cfedb004e6c44cfb4be50392f8fe3fab6 | MATLAB | 2,946 | 92 | % this script looks at prffloc screening...
% ranks the 14 subjects according to BOLD...
% and boil it down to one number per subject.
% visual inspection of variance explained [make sure they look sane]
cd /Users/kendrick/sessions/nsd/
open */analyzePRF_prf_figures/R2.png
open */GLM*figures/FinalModel.png
% make... |
60ca8442baa01f8ca519ceb2e25582c03c0c29dbe9287b4eb7949120c9a8de00 | MATLAB | 2,946 | 79 | function [fList,isFine] = tapas_diagnose_file(fileNames,filterNames,notifyMultipleOccurences)
% TAPAS_DIAGNOSE_FILE Checks if file uses functions which are overloaded
%
% IN
% fileName [character vector of cell array of character vectors]
% The file names to be checked.
%
% OUT
% fList Filtered list of... |
aa5de0e260216b9f667c0c0c07507fe8995f44b89913fe89775dcf38740a6c48 | MATLAB | 2,948 | 94 | function out = nsamdf_nonlinear_measure(data,fs,winLenRel,shiftLenRel,lagRel,degree,doPlot)
% nsamdf_nonlinear_measure computes the nonlinearity measure L through nsAMDF
% (nonlinear average magnitude difference function), developed by:
%
% Ozkurt et al. (2020), "Identification of nonlinear features in cortical and
% s... |
1252ec13f5fcd7da27295781080a21ab84f097ff6d6fac40050c171a877d3ea0 | MATLAB | 2,949 | 67 | function fake_output = mmx(varargin)
%MMX - Multithreaded matrix operations on N-D matrices
% MMX treats an N-D matrix of double precision values as a set of pages
% of 2D matrices, and performs various matrix operations on those pages.
% MMX uses multithreading over the higher dimensions to achieve good
% ... |
37ca8f8286a8ef26431c155c26ba40d496768cfa9a64f27761b196a0c80b3e43 | MATLAB | 2,949 | 96 | function [ output_args ] = estimateGraphCommunityStructure( graph , opts )
%ESTIMATEGRAPHCOMMUNITYSTRUCTURE( graph , opts ) Wrapper function for the
%'estimate' function to run the Marko-Chain-Monte-Carlo procedure for
%estimating community structure.
%
% INPUT:
% graph [graph]: undirected, unweigted graph
% opts... |
8957ad718410021a1925cbf3261e0b39b7951e3938ec2d8343802dca994a4fbe | MATLAB | 2,949 | 101 | % fir_filterdcpadded() - Pad data with DC constant and filter
%
% Usage:
% >> data = fir_filterdcpadded(b, a, data, causal, usefftfilt);
%
% Inputs:
% b - vector of filter coefficients
% a - 1
% data - raw data (times x chans)
% causal - boolean perform causal filtering... |
b5e75ee1701b830ed793c049c7dbe948ff524120bec11fcbf93073b3e72fae68 | MATLAB | 2,949 | 88 | %% h = sepia_handle_panel_Utility(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% hFig : handle of the GUI
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global structu... |
bda6aba316274cf4e71e0f795be6ffb457088daa3cd549733da2131f012ffcce | MATLAB | 2,949 | 100 | function [onset, duration] = doAuditoryMotion(cfg, thisEvent)
% Play the auditopry stimulation of moving in 4 directions or static noise bursts
%
% DIRECTIONS
% 0=Right; 90=Up; 180=Left; 270=down; -1 static
%
% Input:
% - cfg: PTB/machine configurations returned by setParameters and init... |
cfb4d899e4d6f163be892225977eb66d46c7e30735d4928f5b659bc3906b828d | MATLAB | 2,949 | 82 | function [data2, length_dupl] = RemoveDuplicates(data) % by Julia Becker, 01/04/2020 % JB 19/11/2021, debugged
%REMOVEDUPLICATES Handles curves from identical x/y position
% Finds repeat measurements and keeps highest force one
%% Do all of the below individually for each experimental folder
folder = unique(dat... |
a72976dc371f1d1a6801f99291d7707f70a6344ef38c8f99526bcb0194c9126e | MATLAB | 2,951 | 92 | function index2centrotype=icassoIdx2Centrotype(sR,mode,P)
%function index2centrotype=icassoIdx2Centrotype(sR,mode,P)
%
%PURPOSE
%
%To compute the index to centrotype of
%estimate-clusters. Centrotype is an estimate close to the centroid
%of the estimate-cluster. (see help in function centrotype for an
%exact definition... |
1612324003b3bff4c4ff196bc7498200a9abf953cf578ff07489cd50de5f5744 | MATLAB | 2,952 | 67 | classdef McsCmosDataSource < handle
% Stores the contents of a generic data source for CMOS-MEA files.
%
% This should only be used if a data source of unknown type is used. It
% reads all datasets in the data source, so it should not be used if the
% datasets are very large!
%
% (c) 2017 by Multi Channel Syste... |
2b0ab46005a1be6e6208254ddc6d4b341d89f35dcb717797fd8a0c8e6879e1ed | MATLAB | 2,952 | 84 | function out = DN_HistogramMode(y, numBins, doSimple, doPlot)
% DN_HistogramMode Mode of a data vector.
%
% Measures the mode of the data vector using histograms with a given number
% of bins.
%
% ---INPUTS:
%
% y, the input data vector.
% numBins, the number of bins to use in the histogram.
% doSimple, whether to... |
a55f0556e12227125e1ff01f58247dc18b9c9b86aa7d83e46528b57d6b3288a0 | MATLAB | 2,953 | 87 | % firwsord() - Estimate windowed sinc FIR filter order depending on
% window type and requested transition band width
%
% Usage:
% >> [m, dev] = firwsord(wtype, fs, df);
% >> m = firwsord('kaiser', fs, df, dev);
%
% Inputs:
% wtype - char array window type. 'rectangular', 'hann', 'hamming',
% ... |
077390ea929bb2369b74185010aae1db5012aa4aac7fb92c5f68f27320b0e80b | MATLAB | 2,956 | 78 | function [] = Crawler ()
%% Get user to select the files to be analyzed.
[name, pathstr] = uigetfile('*.xlsx', 'MultiSelect','on');
if isequal(name,0)
error('User canceled analysis session');
elseif length(name) == 1
error('User selected only one file, please use the normal WormTacker3000 for this.');
else
... |
0ac139bda6c2f886ba3149a2a280f94640f2cffb857c2ff11c1e99ca54fd0fce | MATLAB | 2,956 | 80 | % FDR - compute false detection rate mask
%
% Usage:
% >> [p_fdr, p_masked] = fdr( pvals, alpha);
%
% Inputs:
% pvals - vector or array of p-values
% alpha - threshold value (non-corrected). If no alpha is given
% each p-value is used as its own alpha and FDR corrected
% array is retur... |
01fcf074c43270625fa19dc39a2ddcac19924b7864c64ca20e4c7a0e16bc8aa3 | MATLAB | 2,957 | 61 | function [b_orig, b_anti, b_orig_norm,b_anti_norm] = er_pac_3(data,fs,segleng,segshift,epleng,filt)
% Estimates PAC using bispectra assuming that data is 6 channels 3 pcs of first roi and second roi
% b_orig: uncorrected bispectrum
% b_anti: anti-symmetrized bispectrum
% b_orig_norm: uncorrected bicoherence
% b_anti... |
14fe48e36a992fe286b16f7155270feabebbc5aaa1a6dc7d0f74a805a7e4c5ab | MATLAB | 2,957 | 108 | function [Out] = GetSignedBias(sn)
Azimuths = [-75:15:75];
for idx = 1:length(Azimuths)
TargetAzimuth = Azimuths(idx);
% --- lp
ResponseAzimuths = sn.lp_Azi(:,idx);
nTrials = length(ResponseAzimuths);
nTrialsHalf = nTrials * 0.5;
n1 = nTrials/2; % last idx of first half of trials
n2 ... |
fbd90042d538825207b2a3de8907a4d4caa31263f774bf58e5961d6f7faec780 | MATLAB | 2,957 | 121 | %% TE = readTE_JSON(filenames)
%
% Input
% --------------
% filenames : json file fullname(s)
%
% Output
% --------------
% TE : echo times
%
% Description:
%
% Kwok-shing Chan @ DCCN
% k.chan@donders.ru.nl
% Date created: 13 June 2018
% Date modified: 12 April 2019
%
%
function [TE] = readTE_JSON(filena... |
18430d1b51bb30da0ec0322e39e6719251fd799105e21c6e570139929fcb096e | MATLAB | 2,958 | 82 | function [K,dK] = covGabor(mode, hyp, x, z)
% Gabor covariance function with length scale ell and period p. The
% covariance function is parameterized as:
%
% k(x,z) = h(x-z), h(t) = exp(-sum(t.^2./(2*ell.^2)))*cos(2*pi*sum(t./p)).
%
% The hyperparameters are:
%
% hyp = [ hyp_ell
% hyp_p ]
%
% We offer thr... |
260afcccb6a844602e221b5f58f396c3f610ee00f49addd2c3750ffbd20ffc5e | MATLAB | 2,959 | 86 | % simulationOptions_demo
%
% This function is used to make a simulationOptions struct for use in the
% simulation part of the demo. The options should be set to personal
% preference.
%
% Cai Wingfield 7-2010
%__________________________________________________________________________
% Copyright (C) 2010 Medical Resea... |
46a2858984e220a2e9770d4e8a4e55fc0bd8c5ba332fb66e3d40d183206eee3c | MATLAB | 2,959 | 81 | function [cs,index] = sort_nat(c,mode)
%sort_nat: Natural order sort of cell array of strings.
% usage: [S,INDEX] = sort_nat(C)
%
% where,
% C is a cell array (vector) of strings to be sorted.
% S is C, sorted in natural order.
% INDEX is the sort order such that S = C(INDEX);
%
% Natural order sorting sorts ... |
d5569ca36bc752845c9230a53ea7a0eb86df8e7d716aa21c90f8aa17ca7fd75f | MATLAB | 2,961 | 91 | function [iti,iti_npv,iti_pv,startTime] = getITI(S)
% Calculates inter-trial interval and start time for each trial in a
% session. SSS 05/2020
%INPUTS:
% S = screened sessions from get_data (using poolRats to screen for
% current criteria 05/2020)
%OUTPUTS:
% iti = cell for each session containing the ITI ... |
5c795839cf6a12b840b501bb029f7b23a47d54acc374c473214e74caec981fc4 | MATLAB | 2,962 | 88 | function [y,dzdg,dzdb] = vl_nnbnorm_old(x,g,b,varargin)
% VL_NNBNORM CNN batch normalisation
% Y = VL_NNBNORM(X,G,B) computes the batch normalization of the
% input X. This is defined as:
%
% Y(i,j,k,t) = G(k) * (X(i,j,k,t) - mu(k)) / sigma(k) + B(k)
%
% where
%
% mu(k) = mean_ijt X(i,j,k,t),
% si... |
5efed1d0e9e85789fc59c9026e7f30b47b50c872cf8de946695b1ea6eabf83c1 | MATLAB | 2,962 | 77 | % STD_CHECKCONSIST - Create channel groups for plotting.
%
% Usage:
% >> boolval = std_checkconsist(STUDY, 'uniform', 'condition');
% >> boolval = std_checkconsist(STUDY, 'uniform', 'group');
% Inputs:
% STUDY - EEGLAB STUDY set comprising some or all of the EEG datasets i... |
ca1d543a66d4358143036837c42702b7a0f866ae61e5a7d7765d2ead9b58745d | MATLAB | 2,962 | 70 | function [indices,values] = FindClosest(reference, query, mode)
%FindClosest - field the indices of a reference vector closest to a query vector
% Look up a query vector in a reference vector, and for each value in
% the query vector, return the index of the closest value in the
% reference vector.
%
% USAGE
%
% ... |
3059548863da2a9823e950976f89f87bc79fce10922d6ee92ce17c339ca4d91c | MATLAB | 2,963 | 76 | function cm_data=fake_parula(m)
cm = [[0.2081, 0.1663, 0.5292],
[0.2116238095, 0.1897809524, 0.5776761905],
[0.212252381, 0.2137714286, 0.6269714286],
[0.2081, 0.2386, 0.6770857143],
[0.1959047619, 0.2644571429, 0.7279],
[0.1707285714, 0.2919380952, 0.779247619],
[0.1252714286, 0.3242428571, 0.8302714286... |
f054ba402b09ce58f7d27b93729d165d67074a96d4023d7118806e6c5cf0147a | MATLAB | 2,963 | 91 | function [file] = read_ctf_ascii(filename)
% READ_CTF_ASCII reads general data from an CTF configuration file
%
% The file should be formatted like
% Group
% {
% item1 : value1a value1b value1c
% item2 : value2a value2b value2c
% item3 : value3a value3b value3c
% item4 : value4a value4b value... |
9d75c96b0574fe24e35de76e332ba22a304d57946248831c5db9af4b427c8807 | MATLAB | 2,964 | 84 | function tapas_init(varargin)
% Initialize TAPAS and print a message in the console
%
% If no argument is given, all toolboxes are initialized.
% If you want to initialize only certain toolboxes, use their
% names as arguments, i.e. tapas_init('hgf') for the HGF-toolbox.
% Dependent TAPAS toolboxes will be initial... |
9503d8d20edfe8c1abe8a29f9395bb794f94fc0a512443333a6196751590c0ef | MATLAB | 2,966 | 79 | % EEG_MERGECHAN - merge channel structure while preserving channel
% order
%
% >> mergelocs = eeg_mergechan(locs1, locs2);
%
% Inputs:
% locs1 - EEGLAB channel location structure
% locs2 - second EEGLAB channel location structure
%
% Output:
% mergelocs - merged channel location ... |
e8a9a5b910f774cc0b01ebd49a88951d153f1981ff6360e5fec5b0bc936faa6b | MATLAB | 2,966 | 76 | function [selectionImage, selectionIndexArray, unusedVarargin] = select(this, varargin)
% Prototype for select-method of n-dimensional image data using dimInfo
%
% Y = MrImage()
% selectionImage = Y.select('type', 'index'/'label', 'invert', true/false, ...
% 'removeDims', true/false
% 'di... |
fc38f1a6950b95dcf464081de6aa436b083d39fe78164ca9b635e54eb69c1387 | MATLAB | 2,967 | 85 | function [varargout] = simulateClusteredfMRIData_fullBrain(simulationOptions)
%
% this function simulates fMRI data with a categorical effect inserted at a
% specified location. The remaining regions contain noise that is temporally
% and spatially smooth yet lacks any particular categorical structure.
% the size of th... |
044b1757a8a436391af2aa30c815b265f6a9d7ed835653094a35185fda6a07c9 | MATLAB | 2,968 | 94 | function costs = surfprofile(problem, x, d1, d2, t1, t2)
% Plot the cost function as a surface over a 2-dimensional subspace.
%
% function surfprofile(problem, x, d1, d2, t1, t2)
% function costs = surfprofile(problem, x, d1, d2, t1, t2)
%
% Evaluates the cost function at points
%
% gamma(t1, t2) = exponential_x(t1*d... |
649f9ed420afadff2aca56185b81f6dc7dca566d2bca77a81b691b16f733faa3 | MATLAB | 2,968 | 68 | disp('See http://www.gaussianprocess.org/gpml/code/matlab/doc/ for details.')
clear all, close all, write_fig = 0; N = 30;
sd = 3; rand('seed',sd), randn('seed',sd) % set a seed for reproducability
liktyp = input('Which likelihood?\n (g)aussian, (l)ogistic: ','s');
a = 0.3; b = 1.2; f = @(x) a*x + b + sin(x); ... |
b0ef4997d1dc9c185409bda236cb199a0cbe6e47bafc1a6acb11ef9119cd2132 | MATLAB | 2,968 | 102 | function imdb = cnn_setup_data_voc07_ssw(varargin)
%CNN_SETUP_DATE_VOC07_SSW Setup PASCAL VOC 2007 data with precomputed SSW proposals
%
% Copyright (C) 2016 Hakan Bilen.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file)... |
3d808433bfda9a010937e651c3d9f56d7677f441d74bbc0ee2d25b14e446001b | MATLAB | 2,970 | 82 | function parameters = LoadParameters(filename)
%LoadParameters - Load parameters from an XML file.
%
% USAGE
%
% parameters = LoadParameters(filename)
%
% filename parameter file name
% Copyright (C) 2004-2018 by Michaël Zugaro
%
% This program is free software; you can redistribute it and/or modify... |
2ac3f5af4e5490cbac678dda4cfccea662d51618603261cdc85dcfce017f7bdd | MATLAB | 2,971 | 85 | %{
preprocess.ManualSegment (imported) # manual 2d cell segmentation$
-> preprocess.PrepareGalvoMotion
---
mask : longblob # binary 4-connected mask image segmenting the aligned image
segment_ts=CURRENT_TIMESTAMP: timestamp # automatic
%}
classdef Manua... |
8e47d3e229b70938f059b664e0c4b23e462d4d27e5106082ffc41878a7603c65 | MATLAB | 2,971 | 102 | function [result] = fit_happy_model_partnerRPE(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.happysc... |
f136de8d3b4be709c20dbd9f1aeedabbe6df883c2639c611efeed92e344f97e5 | MATLAB | 2,972 | 85 | function [spikeTrain, filtTrace, threshold] = ...
detectSpikesThreshold(trace, multiplier, refPeriod, fs, filterFlag, absoluteThreshold, ...
threshold_calculation_window)
% Description:
% Threshold-based spike detection
% INPUT:
% trace: [n x 1] raw or filtered voltage trace
% multiplier: [scalar] thres... |
6d49d15f51b3a22f08138057446198e8f9b9700c091c3d6ee0a841ce7929e333 | MATLAB | 2,973 | 77 | % Main script for generating Economo-Koskinas cortical parcellation
% annotation files and resampling them from fsaverage5 to fsaverage
% using FreeSurfer
%
% Reference:
% Lee H, ..., Huang S, Communications Biology, 2026
%
% Requirements:
% - FreeSurfer installed and configured
% - FreeSurfer fsaverage and fsaverage5 ... |
207b7497018e992cc1b14ee6314d9d06a73044d19776b41144184b17132f5af4 | MATLAB | 2,974 | 102 | function [result] = fit_happy_model_partnerRPE(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.happysc... |
131d5de21b2386a69716f559a3daf8253c7b54658033b6c62e434204da26f361 | MATLAB | 2,975 | 97 | function [Xlsq, Xhub, D] = test04(n, m)
% function [Xlsq Xhub D] = test04(n, m)
% All intputs are optional.
%
% Crude formulation of the photometric stereo problem to experiment with
% product manifolds: we are looking for two sets of normal vectors in R^3,
% more precisely, we work on the product OB(3, m) x OB(3, n).
... |
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