sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
d68c5cc8324ada8436a0831de52a23d742cd7ab75dfdda51659d907317cf6cd7 | MATLAB | 2,086 | 65 | function [ellapsed, difference] = wait2( timeout, flushevents)
%WAIT waits for a specified duration in milliseconds
%
% Syntax: WAIT(timeout);
% Syntax: WAIT(timeout, flushevents);
%
% Inputs:
% timeout, the timeout to wait in milliseconds
% the variable timeout has to be numeric, scalar and real
% flush... |
9abe77da7b964a075dd9ed9726cb40f5df5bcac54680a82f7d6a6ff82bb72ffc | MATLAB | 2,087 | 72 | function plotJointKinematicsCVPCA(lossTests)
% Pair plot of cvPCA results
% Figure
fig;
axis off
hold on;
% Params
colors = turbo(size(lossTests,1));
markers = {'s', 'x', '+', '*', 'o'};
% Loop over mice
for mouseN = 1:size(lossTests,1)
% Angles
mouseLoss = lossTests(mouseN,:,1);
[mouseBestA, mouseB... |
3ce8b5de1dc8c87b86f1b309a93c80f66787bc178afd8aaae10f08922f171d2c | MATLAB | 2,089 | 80 | function fear_icaReacCCG_NREM(basename,varargin)
% basename='~/data/Fear/triple/achel180320/achel180320';
load([basename '.basicMetaData.mat']);
fprintf('start %s\n%s loading data for %s \n', mfilename, datestr(now), basicMetaData.SessionName)
load([basename '.Sleepstate.states.mat'])
load([basename '.sessions.events.... |
72e1deb14737882d4e0613aeeb2b8dab1ea9dafffab6a588bf1d44b592830d46 | MATLAB | 2,089 | 61 | function count = fwriteVAXG(fid, A, precision)
% FWRITEVAXG(FID, A , PRECISION) writes the elements of 'A' to the
% specified file in VAXG format, translating MATLAB ® values to the specified
% precision. COUNT is the number of elements successfully written.
%
% FID is an integer file identifier obtained from ... |
41347cc45d7050f99b1a378a3a8c178f3c863c001e79382db3e95fcf9ebd15ae | MATLAB | 2,091 | 52 | function out = BF_SignChange(y,doFind)
% BF_SignChange Where a data vector changes sign
%
%---INPUTS:
% y, the input vector
% doFind, (i) 0: returns a logical vector with 1s where the input changes sign
% (ii) 1: returns a vector of indicies of where the input vector changes
% sign
% -----... |
96369f876c54606ae627895e40dd4ee2de2612d6b708dc8a1a7ba87a0658d4f2 | MATLAB | 2,091 | 59 | function [iProcessingStep, dirProcessing] = ...
find_max_processing_step(this)
% Returns maximum processing step that has been done for this object (via
% folder structure, even if current object is at an earlier processing
% step)
%
% Y = MrSeries()
% Y.find_max_processing_step(inputs)
%
% This is a method of ... |
e22a4b4b66d1540697600345e61037d541a007a12d68ef996a838f216ba60d93 | MATLAB | 2,092 | 59 | function [] = load_tracks()
%load_tracks Load X/Y tracking data
% Function that imports manual worm coordinates generated in FIJI and
% collated in a series of .xslx tabs. Tab names must match info.wormUIDs.
global info
global dat
%% Import tracks
% Updated for single camera configuration
[dat.Xvals.Pixels, dat.... |
4f17ec44768c339da9a4621804baf287504a12b006ce9bb26429aad4f3a87063 | MATLAB | 2,093 | 56 | function PostHocDenoising_Callback(hObject, eventdata, handles)
% This function uses a convolutional neural network, trained in
% "TrainPostHocDenoiser_Callback.m", to seperate noise from USVs.
% Load the network
[FileName,PathName] = uigetfile(fullfile(handles.data.squeakfolder,'Denoising Network','*.mat'),'Select D... |
cb037000153c302421c6c308c270690e17f21f10026287bceab44d0f7b6475f2 | MATLAB | 2,093 | 56 | function results = analysis01D(config)
% Runs analysis 01D: Initialise a large population of (neuromorphic)
% reservoirs, evaluate their performance nTest times, and test the
% following hypothesis: Is the probability of a successful prediction,
% given that the prediction was emergent, higher than the marginal
% pro... |
dd7a683ed6d634c3afd2d818e609e74c6775471f08d13c8a6ff81735b6c55a82 | MATLAB | 2,094 | 61 | function newPosition = tapas_uniqc_convert_montage_position_to_selection(montagePosition, ...
montageSize, dimInfoSelection, selectionIndexArray)
% Converts (mouse) position in montage into x,y,z selection of plotted data
%
% newPosition = tapas_uniqc_convert_montage_position_to_selection(montagePosition, ...
% ... |
181af8b6a7040ed65e3cadd17436d2611f3a22beb8f6c365f1a8aef2c974830b | MATLAB | 2,095 | 48 | function params = sero_pulseq_InitialiseParameters_v2(varargin)
% pulseq_InitialiseParameters: Initialize and pack pulse sequence parameters
% with default values that can be overridden by user input.
% Example usage: pulseq_InitialiseParameters('FOV', 50e-3)
% Set default parameter values
defa... |
54ab0354d059a7c3ab075f3d7ef63c3b92c4ac9544ea3d0411169ac033b3acc6 | MATLAB | 2,095 | 57 | function BF_ResetSeed(resetHow)
% BF_ResetSeed Reset the random seed generator in Matlab
%
% Allows functions using random numbers to produce repeatable results with a
% consistent syntax.
%
%---INPUTS:
% resetHow, one of:
% 'default' -- reset to the Mersenne Twister with seed 0
% 'none' -- don... |
93d4c1130f87a054290be692ed5e01aaf096f7731ae5f6097bb9cfdefaee3c7e | MATLAB | 2,095 | 58 | function [hdr] = read_brainstorm_header(filename)
% READ_BRAINSTORM_HEADER reads the header information from .EEG files
% that have been generated by the Nihon Kohden system. The function
% constitutes a wrapper around BrainStorm3 functionalities
%
% Use as
% [hdr] = read_brainstorm_header(filename)
%
% See also ... |
3da2e747e847798c19cd27920b7215a7ff427a66e15e25ccfedd56e08db98723 | MATLAB | 2,096 | 75 | function [ h ] = tapas_rdcm_get_convolution_bm(options)
% [ h ] = tapas_rdcm_get_convolution_bm(options)
%
% Creates a fixed hemodynamic response function (HRF) by convolving a single
% event (impulse) with the standard Balloon model from DCM.
%
% Input:
% options - options structure with relevant informa... |
c45e0b36a2779d55ad16848383a914f808da1eff3337f0f31a63b26c7a1cc1c5 | MATLAB | 2,096 | 42 | function updateCSVstatusInGui(app, groupNameBeginsWnumber, groupNameContainsSpecial, allDIVisValid, groupNameIllegal)
%UPDATECSVSTATUSINGU Update the text field in GUI based on whether the CSV
%pass all the checks
if groupNameBeginsWnumber
app.MEANAPStatusTextArea.Value = [app.MEANAPStatusTextArea.Value; .... |
23924546a63fcd19a3bd7bbbbd4bdd5c6e723db6ca28ae5327950be291d0cbf6 | MATLAB | 2,097 | 55 | % ERRORDLG2 - Makes a popup dialog box with the specified message and (optional)
% title.
%
% Usage:
% errordlg2(Prompt, Title);
%
% Example:
% errordlg2('Explanation of error','title of error');
%
% Input:
% Prompt - A text string explaining why the user is seeing this error message.
% Title ... |
f958e641fbb45599c69885c9ff28e99f5a116b2c6fc6897b40b5dc5e891e34de | MATLAB | 2,097 | 48 | %% Spike code to find the mid point of spikes
% Created by Aaron Choong and Jesslyn Sutanti
% Last modified 10/8/2017
% Supervised by Kostas, Yan & Masoud
function [spikes_index] = spike_detection(spike_data,threshold)
%% This spike code finds the mid point of the spikes instead of the peaks
% Faster computatio... |
2e5ecbc7b406f58de6f6d4f714a3f53ba127143e7c0effa84bc2fecc147dd6fb | MATLAB | 2,098 | 75 | %{
map.Masks (imported) #
-> map.Area
---
mask : mediumblob # area mask
%}
classdef Masks < dj.Relvar & dj.AutoPopulate
properties
popRel = (map.Area)
end
methods (Access=protected)
function makeTuples(obj,key)
pat... |
c3a98eae9ca0d98101b3e22437219bfbc58b7bab61c27a5ca3920ddb4ac2bd90 | MATLAB | 2,098 | 80 | function obj = init_model(obj)
D = prod(obj.lat);
% ----
% mean
% ----
format = brca.format.auto(obj.mu0);
if ~isfinite(obj.nm0)
obj.mu = obj.mu0;
else
if format.numel(obj.mu0) == 1
obj.mu = obj.format.allocate(obj.lat);
obj.mu = obj.format.write(obj... |
e7e05b66ebec797c9fcb431c80c89a8640996c23133e737a4f639b782e57235f | MATLAB | 2,098 | 90 | function [a, b] = isintent(this,intent)
% Correspondance between fieldnames and NIfTI intents
% FORMAT ind = isintent(this,intent)
% this - GIfTI object
% intent - fieldnames
% a - indices of found intent(s)
% b - indices of dataarrays of found intent(s)
%____________________________________________... |
330aab85f9a01364a86da3c97d78b7a58267a319766d2a4897ef8903f5554bcf | MATLAB | 2,099 | 69 | function tapas_hmm_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);
%
% --------------------------------------------------------------------------------------------------
% Copyr... |
bbc4b5ec1c70f66335d06b698518018b1c3e52d62517e81534f9ccc2109445da | MATLAB | 2,100 | 46 | function [numStrides,numValidStrides, percValid, percThresh] = validStrides(EEG_block, gait_event_order,gait_timeNextHs)
gait_event = gait_event_order{1};
timeNextHs = gait_timeNextHs*EEG_block.srate;
idxHS = find(strcmp({EEG_block.event.type}, gait_event));
%check whether threshold crossings were marked
if isf... |
ec5bea3b7f52e63ac82f6af31f20d28b3a45d67db995d728e89be3d3a61eaa77 | MATLAB | 2,100 | 56 | function y = block_geometric_median(X,blocksize,varargin)
% Calculate a blockwise geometric median (faster and less memory-intensive
% than the regular geom_median function).
%
% This statistic is not robust to artifacts that persist over a duration that
% is significantly shorter than the blocksize.
%
% In:
% X : t... |
383efef3cd704736a06ca94c2e51448415601d19a15fc3af2d7e1a66e60c3ad1 | MATLAB | 2,101 | 66 | function SaveEvents(filename,events,varargin)
%SaveEvents - Write events to file.
%
% USAGE
%
% SaveEvents(filename,events,options)
%
% filename event file name
% events event data
% <options> optional list of property-value pairs (see table below)
%
% ===============================... |
8e16c7778ccb90087e734b00625f33ab5ceccf507f3cc039187a554bf86192b1 | MATLAB | 2,101 | 46 | function [fileNameSourceArray, fileNameTargetArray, ...
fileNameSourceMovedArray, fileNameTargetMovedArray] = tapas_uniqc_move_with_hdr(...
fileNameSourceArray, fileNameTargetArray)
% Moves given files; for .nii (nifti-) files, also moves .mat-header,
% if existing; for given .img (analyze) files, also moves .h... |
1c31ef97fa29efdab18590c22f8598e4d1a5df1c583816484726de74061b3f9b | MATLAB | 2,102 | 87 | function out = meta_chi2_matrix(dat,w)
w = w ./ mean(w);
myalpha = .05;
[N,npairs] = size(dat);
[rows,cols,ncorr] = corrcoef_indices(npairs);
str = sprintf('Computing differences among correlations %04d',0); fprintf(1,str);
chi2 = zeros(ncorr,1);
chi2p = zeros(ncorr,1);
diffr = zeros(ncor... |
a96f7f6f9277435b8a3baa1ba6c9d5d06f83735d74ca755c142bec971eea04b6 | MATLAB | 2,102 | 67 | function coords = getNodeCoords(adjM, Params)
%GETNODECOORDS Summary of this function goes here
% Detailed explanation goes here
if strcmp(Params.nodeLayout, 'force')
% Create a graph object from the adjacency matrix
G = graph(adjM, 'lower');
% Use layout to get coordinates without plottin... |
54112ccd253512d8128f57be0fb34bb04740476e3bad49ecf107b4b9d39c1ae4 | MATLAB | 2,104 | 81 | function y = binomcdf(x,n,p)
%BINOCDF Binomial cumulative distribution function.
% Y=BINOMCDF(X,N,P) returns the binomial cumulative distribution
% function with parameters N and P at the values in X.
%
% The size of Y is the common size of the input arguments. A scalar input
% functions as a constant matrix ... |
1ce5d27c7a1629a4794dce88a5c4ce60b0c3d32b9b9291a3be2ad46461a740bc | MATLAB | 2,106 | 76 | function I=processvarargin(I,D)
%function I2=processvarargin(I,D)
%
%PURPOSE
%
%Subfunction of various functions in Icasso.
%
%INPUT
%
% I (cell array) input {'id1' value1 'id2' value2 ...}
% D (cell array) defaults {'id1 value1 'id2' value2 'id3' value3 ...}
%
%OUTPUT
%
% I2 (cell array) combination of inputs I and de... |
43f21b0179dba158e8b14c32d1986e50fc9c36a962754289a60cb96e6d790932 | MATLAB | 2,106 | 60 | function Model=modelMANOVA(Fa,Fb,varargin);
% function Model=modelMANOVA(Fa,Fb,varargin)
% This function generates the RDM model for a fully-crossed MANOVA design (2-factorial).
% INPUT:
% Fa: a nConditions column-vector, indicating the assignment of condition k to
% level A
% Fb: a nConditions column-vector,... |
d3a6c6c98f342f788861dea4d1cdd4663296eeaae1641d0fcc9a001a767e888e | MATLAB | 2,106 | 81 | function [stimind,causal_ind,covops] = stimulusInfo(stim,covname)
%grabs index and information about a covariate in stim
%useful for removing, merging, etc.
%important sizing information
if isempty(stim.TDcausalvec)
ntdc = 0;
ntdac = 0;
else
ntdc = sum(stim.TDcausalvec(1,:)); %number time-dep. causal st... |
5dee0e3ac8d51834619b2da9efbdf6727173893d4464e6b5776f9d64e72057de | MATLAB | 2,107 | 93 | function [tx,ty,T] = pred_time_index(x,parm)
% Time index for delay embedding prediction
% [tx,ty,T] = pred_time_index(x,parm)
% --- Input
% x : Input data : Xdim x Tsample x Ntrial
% parm : Time delay embedding parameter
% parm.Tau = Lag time
% parm.Dtau = Number of embedding dimension
% parm.Tpr... |
f3e0aa7309d080284c660c599931c9f0142f22c7be5666513c73bc95696739fc | MATLAB | 2,107 | 64 | % RMSAVE - return the RMS in each channel, epoch
%
% Usage:
% >> ave = rmsave(data,frames);
% Copyright (C) Scott Makeig, CNL/Salk Institute, La Jolla, 9/98
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, wit... |
53dee0fae2df97596e9973d8158bd149272f53ac11cfbc3461d4907bbb61a41b | MATLAB | 2,108 | 59 | function [basefun,basefunst] = chooseBasis_ofc(ops)
%CHOOSEBASIS_OFC: a wrapper function around chooseBasis for ofc studies
%length of history filter in timesteps,
lh = ops.lh; %length history filter. a 1.2 s filter
ls = ops.ls; %length stimulus filter. a 1.s s filter.
dim = ops.dim; %dim hist basis
dimst = ops.dimst... |
86f34261519e7520a4792725823aeb0cbbe5a05f39cbcd536fe3a275a7ee0833 | MATLAB | 2,108 | 71 | function c = tapas_rs_belief_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the 'belief' response model according to:
%
% Vossel, S.*, Mathys, C.*, Daunizeau, J., Bauer, M., Driver, J., Friston, K. J., and Stephan, K. E.
% (... |
df816e7c3435cd144d10f5653f482dedf0c764a78d979c8e0427ce9ece3cc52e | MATLAB | 2,108 | 56 | % setdiff_bc - setdiff backward compatible with Matlab versions prior to 2013a
% Copyright (C) 2013 Arnaud Delorme
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provide... |
55f360d5dfe96854405b2e96bd7c464f7abb58f9d5dfc1babba8d54d1a067a8d | MATLAB | 2,110 | 67 | function [phase,amplitude,unwrapped] = Phase(samples,times)
%Phase - Compute instantaneous phase in signal.
%
% Compute instantaneous phase (wrapped and unwrapped) and amplitude
% in signal, using the Hilbert transform of the signal.
%
% USAGE
%
% [phase,amplitude,unwrapped] = Phase(samples,times)
%
% samples ... |
8e2a42f5265d898e05a3981deee348a7c0f8accab72ab9f5eac79e2350f6ea9d | MATLAB | 2,110 | 57 | function c = tapas_squared_pe_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuraton for the squared-prediction error optimization of perceptual parameters
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
e6e687563b2b93798fffa421ca42f4a5aefad13da641597f0d2688a00b5ce4a1 | MATLAB | 2,110 | 36 | function excel_Callback(hObject, eventdata, handles)
function t = loop_calls(Calls, hc,includereject,waitbar_text,handles,call_file, audioReader)
exceltable = [{'File'} {'ID'} {'Label'} {'Accepted'} {'Score'} {'Begin Time (s)'} {'End Time (s)'} {'Call Length (s)'} {'Principal Frequency (kHz)'} {'Low Fr... |
e3343b83a7f32462542542c2a5d4bf4c539a3fbd2f233a978564e230a096900d | MATLAB | 2,111 | 62 | function adjM = get_sttc(spikeTimes, lag_ms, duration_s, method, use_c_code)
% Description: calculates pairwise correlation between pairs of neurons
% using spike time tiling coefficient
%
% See the original paper:
% https://www.ncbi.nlm.nih.gov/pubmed/25339742
%----------
% Parameters
% spikeTimes - [n x... |
987ab3b630287c8e94f5ed6e5e923b0e76b62928f4562af0eb365acf96ef2d94 | MATLAB | 2,112 | 83 | function [out] = osp_SenseUnfolding(in,SENSE)
Voxels=2;
%%
Navg = in.sz(in.dims.averages);
if in.dims.subSpecs ~= 0
NsubSpec = in.sz(in.dims.subSpecs);
fids = zeros(in.sz(in.dims.t),in.sz(in.dims.averages),in.sz(in.dims.subSpecs),Voxels);
for ll = 1:Navg
for mm = 1:NsubSpec
fids(:... |
45cebf71ae9f910ae30d8f4b9b478368cf09ef13992a835b094d3a0b350554e8 | MATLAB | 2,114 | 56 | % recursively get the list of Matlab file in
% a given directory
%
% A. Delorme, 2017
% Copyright (C) A. Delorme, 2017
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted pr... |
a69017f94516c6f33145702f5c2b44229d28c4a0cc6d1f7e0b38869cfb0cf569 | MATLAB | 2,114 | 56 | % RESHAPE - reshape of memory mapped underlying array
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, Nov. 2008
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with o... |
10370691d4b9dc86f78147480c39bf4d3be3c2b72e527e91cbb057ffdeda3e47 | MATLAB | 2,115 | 64 | function [ ] = tapas_huge_compile( )
% Compile integrator for DCM fMRI forward model. This function assumes that
% source code file 'tapas_huge_int_euler.c' is in the same folder as this
% function and places the compiled mex-file in the same folder. Running
% this function requires a C compiler to be installed. For mo... |
18111462bd1a6e072c27c5122de4603eaccddb9b52d3382e9c11342e46127fa6 | MATLAB | 2,115 | 56 | % ismember_bc - ismember backward compatible with Matlab versions prior to 2013a
% Copyright (C) 2013 Arnaud Delorme
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provi... |
4f8996132b000f3766202e4c5ed4ea1e53777a27c8bcea477435c57dbfa45163 | MATLAB | 2,115 | 90 | function DB = Meta_Prune(DB,include)
% DB = Meta_Prune(DB,include)
%
% Prunes database given an indicator vector of points (peaks) to include
% Includes only contrasts for which ALL peaks are included!
% Thus, if any peaks are excluded, the whole contrast is excluded.
%
% Called in Meta_Select_Contrasts and Meta_Logis... |
136650d86b30469ee5b377b04925c1ff5e11f46df819a70f330242d3b3d53ee9 | MATLAB | 2,116 | 71 | function call_copy_withLabels(xstring, ystring)
a = gca;
f = gcf;
cm=get(f,'colormap');
cf=get(f,'color');
% mousepos = get(gcf,'CurrentPoint');
set(f,'units','pixel')
set(a,'units','pixel')
posA = get(a,'Position');
posF = get(f,'Position');
set(f,'units','normalized')
set(a,'units','normalized')
posAn = get(a,'Posi... |
d9ddd6b861a1eacee33f415854465d437b8315a97c11be02a9aec71fe91b83c0 | MATLAB | 2,116 | 71 | function c = tapas_rs_surprise_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the 'surprise' response model according to:
%
% Vossel, S.*, Mathys, C.*, Daunizeau, J., Bauer, M., Driver, J., Friston, K. J., and Stephan, K. E.... |
869ada29816fa6a3e443606c276c8fdaa741c504ecf64012feb0fe9f4ddf422a | MATLAB | 2,117 | 77 | function this = load(this, fileName)
% Loads Geometry info from affine image header (.nii/.hdr/.img) or Philips
% (par/rec)
%
% NOTE: .mat-header files (for 4D niftis) are ignored, since the same voxel
% position is assumed in each volume for MrImage
%
% geom = MrImageGeometry()
% geom.load(fileName)
%
% This... |
6dbc5e9744811650f73a924f52bd8fca6329b72b0216ba4d40d5b9ac1c18ed97 | MATLAB | 2,118 | 53 | function args = hlp_struct2varargin(struc,varargin)
% Convert a struct into a sequence of name-value pairs; inverse to hlp_varargin2struct.
% Args = hlp_struct2varargin(Struct,Options...)
%
% In:
% Struct: a 1x1 structure array
% Options: optional name-value pairs;
% 'suppress': suppress the output names... |
9f553415f15bbe06d73e6215a0dc7395452598758e1d1cd62d181507c2964de2 | MATLAB | 2,118 | 59 | function download_tMPPCA_toolbox()
% Check whether Tensor-MP-PCA (https://github.com/Neurophysics-CFIN/Tensor-MP-PCA)
% is available on the path; if not, download it into SEPIA_HOME/external/
% and add it to the path.
%
% Unlike FANSI/HEIDI, Tensor-MP-PCA needs no SpecifyToolboxesDirectory.m
% entry - its location is a... |
bdc323a143c05511448e276aa192810fc67d1eabbc53b3a2bdd3ddb1aeea423b | MATLAB | 2,119 | 76 | function out = study_table(study,varargin)
% function out = study_table(study,varargin)
%
% prints a table of studies; input the study variable, and input columns, in order
% columns with ones and zeros are converted to X's or blanks.
% (not implemented yet; everything must be cell arrays of strings now)
%
% study is a... |
be77858205a415012909405adfacdbdbf7cd20c382cfa0c209f071745d7a8234 | MATLAB | 2,119 | 61 | function [group,threshold,em] = Otsu(vector)
% The Otsu method for splitting data into two groups for 1 dimensional data.
% This is somewhat equivalent to kmeans(vector,2), but while the kmeans implementation
% finds a local minimum and may therefore produce different results each time,
% the Otsu implementation is gu... |
beda2c49751191c7f1a25d9b15ba24837a64a5d23c1ddfc474459c6703a1d389 | MATLAB | 2,119 | 69 | function indexFoundPattern = tapas_physio_find_string(stringArray, searchPattern, isExact)
% Finds a string pattern in a cell of strings and returns found cell indices
%
% NOTE: this function behaves the same as find should behave
%
% indexFoundPattern = find_string(stringArray, searchPattern, isExact)
%
% IN
% ... |
f4d07f898da5e78fa5e06dcdada7a24a94f32d2f6651b94808ccbcfce870d7a7 | MATLAB | 2,119 | 67 | function [this, argsUnused] = update(this, varargin)
% updates Geometry directly or computes given new FOV/resolution/nVoxels or whole affineTransformation
%
% Y = MrImageGeometry()
% Y.update('FOV_mm', FOV_mm, 'resolution_mm', resolution_mm, ...
% 'nVoxels', nVoxels, 'affineMatrix', affineMatrix, ...
% ... |
4e68c86730f28a43906f8c3b6fe2a42af424c2771571ba6119347d8c9feaa35d | MATLAB | 2,120 | 75 | function [RegisteredImage,MOVINGREG] = registerImages(MOVING,FIXED)
%registerImages Register grayscale images using auto-generated code from Registration Estimator app.
% [MOVINGREG] = registerImages(MOVING,FIXED) Register grayscale images
% MOVING and FIXED using auto-generated code from the Registration
% Estimat... |
5e1dca8c412b6593da918cdf62fed07cb672f019665d076c04625eb17658759c | MATLAB | 2,120 | 85 | function W = fast_ica(x,pcomponents,nit)
% Originally written by the Finish (Aapo) team;
% Modified by the PIB team in Aug. 21, 2007
% PIB - Biological Information Processing Lab - UFMA - Brazil
% Modified by Vítor Lopes dos Santos Aug. 2011.
if nargin < 3, nit=100; end
% fprintf ('Removing mean...\n');
%----------... |
6f52350014de89000753706b2cdcd7a6bb948853554e234a3b59983dc46045a5 | MATLAB | 2,120 | 71 | function c = tapas_rs_precision_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the 'precision' response model according to:
%
% Vossel, S.*, Mathys, C.*, Daunizeau, J., Bauer, M., Driver, J., Friston, K. J., and Stephan, K. ... |
c25063016699f4d9094cf37fa31da424fd77efc81f4f4ad1245e07e08a9bf20d | MATLAB | 2,120 | 49 | function DBCreateTables(database)
%DBCreateTables - Create tables in existing database.
%
% Create figure and variable tables in an existing database. If you
% have admin rights to the database server, use <a href="matlab:help DBCreate">DBCreate</a> instead.
% Otherwise ask the DBA to create an empty database with the... |
512e098db89e7fd967734f926912c214c45aac837e6a8d35f57aff23d07b7450 | MATLAB | 2,121 | 62 | function [encoderNet, decoderNet] = VAE_model()
latentDim = 32;
imageSize = [128, 128, 1];
encoderLG = layerGraph([
imageInputLayer(imageSize,'Name','input_encoder','Normalization','none')
convolution2dLayer(3, 8, 'Padding','same', 'Stride', 2, 'Name', 'conv1')
batchNormalizationLayer('Name', 'bnorm... |
5fc6c480e674c95954afb0882c716b5c5cf2b20ac467e0bf91fa5857c368ac97 | MATLAB | 2,121 | 56 | % unique_bc - unique backward compatible with Matlab versions prior to 2013a
% Copyright (C) 2013 Arnaud Delorme
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided ... |
9808542ccd5b6838663e190c5c4ceeac3dc601f33e4122860e3914893b59b4c0 | MATLAB | 2,121 | 68 | function [M,stderr,V,grpids] = means(X,grps)
% MEANS: Means, standard errors and variances. For column vectors, means(x)
% returns the mean value. For matrices or row vectors, means(x) is a
% row vector containing the mean value of each column. The basic
% difference from the Matlab funct... |
8d579f8f1e6e12b362abb86f6cf8323a5b6ac5067e6b37d98d6550286ccacca8 | MATLAB | 2,122 | 67 | function [config] = tapas_get_config(tpath)
%% Loads the configuration of the project.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
fname = fullfile(tpath, 'config.static.ini');
config = ini2struct(fname);
fname = fullfile(tpath, 'config.ini');
tc = ini2struct(fname);
tf = fields(tc);
for i = 1:numel(tf)
... |
ec653ab0f18f3fd20aae1a703a85af4ce899e5a6aaf361645fa3172d0c8434e1 | MATLAB | 2,122 | 54 | function SupervisedClassification_Callback(hObject, eventdata, handles)
% This function uses a convolutional neural network, trained in
% "TrainSupervisedClassifier_Callback.m", to classify USVs.
[FileName,PathName] = uigetfile(fullfile(handles.data.squeakfolder,'Clustering Models','*.mat'),'Select Network');
net = l... |
ef60c58252be8c5c717517bc58bda288342965e674cd6e11adc823a2963cea28 | MATLAB | 2,122 | 105 | function linearModelExamples
% % Linear model call format
%
%
% % Build data
% rng(555),
% n=10;
% R=rand(n,5);
% R(:,3)=R(:,3)+1;
%
% X=repmat(1:5,size(R,1),1);
% lemmings=R(:);
% group=X(:);
%
% clf
%
% % We can call notBoxPlot with just X and Y
% subplot(2,2,1)
% notBoxPlot(lemmings,group,'jitter',0.75)
% grid on... |
87a7c4b32a6f16b590536b6b4940f0ee4fddaa8a8b03fd62c5af46875cfc0c5e | MATLAB | 2,123 | 70 | function processDPrime(ephysPath, codePath, savePath)
% Compute the discriminability index for large versus small volume rewards
% in mixed blocks for each cell in the recorded area of interest
%INPUTS:
% ephysPath = local path to ephys folder downloaded from zenodo for the
% recording area you want to analyz... |
c4537d42a32a2bf1115ec37444fab88a5ebc219a98e0c392339f6926933c0b50 | MATLAB | 2,123 | 73 | function [K,dK] = covULL(hyp, x, z)
% covULL Stationary covariance function for underdamped linear Langevin process
%
% [K,dK] = covULL(hyp, x, z)
%
% where the hyperparameters are:
%
% hyp = [ log(mu)
% log(omega)
% log(a) ]
%
% The covariance is obtained by filtering white noise through an underda... |
e8e072aa1022ab3215c8af76483760785bc2c4fb96229192b4e697408906f306 | MATLAB | 2,124 | 66 | function plot(evtStream,cfg,varargin)
% Plot the contents of a McsEventStream object.
%
% function plot(evtStream,cfg,varargin)
%
% Produces a plot in which the time stamp of each event is shown as a line
% on a time scale.
%
% Input:
%
% evtStream - A McsEventStream object
%
% cfg - Re... |
35e9f3cbca0f288cdcf76821e61f8f03209c066eb7606da1788bf0c2362a98fa | MATLAB | 2,125 | 40 | % noise_std a 1*2 vec with noise std for players 1 and 2
% Dyad_acc:51 (player 1 'ready made increasing mean') * 51
% (player 2 'ready made increasing mean')* 8 (Gaussian increasing mean).
function output = calc_landscape(noise_std, ready_made_conf_dist, stimuli);
conf_mean_vec= 1:.1:6;
Dyad_acc=zeros(length(con... |
831b43b45a4d687e28c0a65c09ea00604b265ec582bf4372957589e7da1068d4 | MATLAB | 2,125 | 72 | function [file] = read_bti_ascii(filename)
% READ_BTI_ASCII reads general data from a BTI configuration file
%
% The file should be formatted like
% Group:
% item1 : value1a value1b value1c
% item2 : value2a value2b value2c
% item3 : value3a value3b value3c
% item4 : value4a value4b value4c
%
%... |
93220d00fc506c150acddd1a778da37305313582ba82b1ab8467d357360c44f7 | MATLAB | 2,125 | 65 | % Test point by point conductance computation, in a 2D vector example
% Author: Aina Frau-Pascual
% Input image
im = zeros(3) + 0.0;
im(1, :) = 0.8;
im(:, 1) = 0.8;
im(:,:,2) = 1 - im(:,:,1);
im(im==1) = 0;
% Construct mesh structure
Lx = size(im, 1); % domain length
Nx = size(im, 1); % number of cells
Ly = size(im,... |
04b7ce579f691cd5e8f6180b54b70aa034635a7351bc51fd3fa70a9e8d90ef81 | MATLAB | 2,126 | 65 | % Continuous Tone Controlled by Mouse Movement
% Move your cursor horizontally in the figure to change the tone frequency.
% Define a global variable to hold the current frequency.
global currentFreq;
currentFreq = 200; % Start at 200 Hz
% Audio parameters
fs = 44100; % Sampling rate in Hz
dt = 0.05; % ... |
068aa76f37f141aa23f9866211e61a985dcb5376cb3a4427249b2cd7f905fb99 | MATLAB | 2,126 | 47 | % eegplugin_clean_rawdata() - a wrapper to plug-in Christian's clean_artifact() into EEGLAB. .
%
% Usage:
% >> eegplugin_firstPassOutlierTrimmer(fig,try_strings,catch_strings);
%
% see also: clean_artifacts
% Author: Makoto Miyakoshi and Christian Kothe, SCCN,INC,UCSD 2013
% History:
% 05/13/2014 ver 0.30 by Chri... |
c0284b20f6af6b17ba938f46d50b3223481ed026f96b4f25dd9af0979577cc2e | MATLAB | 2,126 | 72 | % SPM ReML overiew
% _
% This script plots several variants for the variance components used
% in restricted maximum likelihood estimation (ReML) in SPM.
%
% Joram Soch, MPI Leipzig <soch@cbs.mpg.de>
% 2023-09-06, 12:30: first version
clear
close all
% specify covariances
n = 5;
p = 0.4;
TR= 2.1;
Q = cell(4,2);
Q{1... |
7056c50adf2c02b336f19f2dba43c52d2f3f63dfc063bb8a67650651327cfb18 | MATLAB | 2,127 | 63 | function this = load(this, fileName, varargin)
% Loads MrSeries from given folder or loads image files (.nii etc.) into MrSeries.data
%
% Y = MrSeries()
% Y.load(fileName)
%
% This is a method of class MrSeries.
%
% IN
% fileName
% '.mat',
% 'nii',
% '.img'/'.hdr'
% ... |
da9c4258d339c3c34863b6ded59b9aa8802a963176fc41bb9ad2672b4188edf0 | MATLAB | 2,127 | 82 | function varargout=checkRAM()
% Checking amount of available RAM on the computer (in bytes)
% SYNTAX
% checkRAM() - prints the information about the RAM into the command line
% [availableRAM,summary]= checkRAM()
%
% INPUTS:
% - noinputts
%
% OUTPUTS:
% - availableRAM - available RAM in bytes
% - summary - structure co... |
e6f31cb25c02d4b8185032bf62593898e7c693c30ce121d41a3d8274799996bc | MATLAB | 2,127 | 68 | function corrMat=RDMCorrMat(RDMs,figPlotSpec,type)
% USAGE
% corrMat=RDMCorrMat(RDMs[,figPlotSpec])
%
% FUNCTION
% returns and optionally displays the correlation matrix (spearman) of a set
% of RDMs (can be square or upper triangle form and wrapped or bare).
%
% 08-2011 CW: slight modifications for how nans are handle... |
242e13f10ce8c7bc030221a9da6f344f173f2b1156d8c48c003bc294e2d7f517 | MATLAB | 2,128 | 56 | % union_bc - union backward compatible with Matlab versions prior to 2013a
% Copyright (C) 2013 Arnaud Delorme
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided th... |
2a150a49e90a79e80357e8b4ee4231f915977c6569c882f039bb53bc627492f5 | MATLAB | 2,128 | 58 | clear all;
clc;
% % Add software, add DPABI before spm
if ismac
addpath(genpath(fullfile('..', 'DPABI_V8.1_240101')));
addpath(genpath(fullfile('..', 'REST_V1.8_130615')));
addpath(fullfile('..', 'spm'));
elseif ispc
addpath(genpath(fullfile('..', 'DPABI_V8.1_240101')));
addpath(genpath(fullfile('.... |
e264663a77b3bd64cd35865416af91e9163b4661dc04cabef458329cbd777985 | MATLAB | 2,128 | 58 | clear all;
clc;
% % Add software, add DPABI before spm
if ismac
addpath(genpath(fullfile('..', 'DPABI_V8.1_240101')));
addpath(genpath(fullfile('..', 'REST_V1.8_130615')));
addpath(fullfile('..', 'spm'));
elseif ispc
addpath(genpath(fullfile('..', 'DPABI_V8.1_240101')));
addpath(genpath(fullfile('.... |
ffe4d7294f1af8f47a9b757c9c390ddc0503e9a87fd79c7e87af2a0202552188 | MATLAB | 2,128 | 58 | clear all;
clc;
% % Add software, add DPABI before spm
if ismac
addpath(genpath(fullfile('..', 'DPABI_V8.1_240101')));
addpath(genpath(fullfile('..', 'REST_V1.8_130615')));
addpath(fullfile('..', 'spm'));
elseif ispc
addpath(genpath(fullfile('..', 'DPABI_V8.1_240101')));
addpath(genpath(fullfile('.... |
37788f2d7aa8b254a9b2c62cda8ac2544abf31fe54c5a29093fb45dfa564e838 | MATLAB | 2,129 | 57 | function cmdString = tapas_physio_create_spm_toolbox_link(pathPhysIO)
% Creates a symbolik link of PhysIO/code folder to subfolder SPM/toolbox/PhysIO
% to make toolbox visible to SPM Batch editor
%
% tapas_physio_create_spm_toolbox_link()
%
% IN
%
% OUT
% cmdString string of executed command
%
% EXAMPLE
% tapas... |
76f43fa2c3728c7d7ef04aebdbcc758d5e289fc6ac4162733aa58313268c098a | MATLAB | 2,129 | 78 | function plot_fig3d_right(datadir)
% Plot z-scored rat trial initiation time and model simulation regressed
% against reward offers in the last 15 trials. For visualization, only 7
% trials are shown. N = 10 rats.
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to download can
% be found in README.... |
78d8a14ca3d9b2984e92804b3ec242b3f699f9103bd7db658ea07201226482b8 | MATLAB | 2,129 | 66 | function BrainNet_GenSurface(filename,outputfilename,threshold)
% BrainNet Viewer, a graph-based brain network mapping tool, by Mingrui Xia
% Function to generate surface file from Nifti mask
%-----------------------------------------------------------
% Copyright(c) 2015
% State Key Laboratory of Cognitive Neuros... |
3b7edb3aed1667f9ac099c038b18b3304fdc8544d2230510b10ad988a5f3e28a | MATLAB | 2,130 | 75 | %isivector - Test if parameter is a vector of integers satisfying an optional list of tests.
%
% USAGE
%
% test = isivector(x,test1,test2,...)
%
% x parameter to test
% test1... optional list of additional tests (see examples below)
%
% EXAMPLES
%
% % Test if x is a vector of doubles
% ... |
4503b204d3fe4634cfe4c10bda0fb37b5b14c999cce10c11db461bbec7b32c47 | MATLAB | 2,130 | 60 | function ResampleBinary(inputName,outputName,nChannels,up,down)
%ResampleBinary - Resample binary data file.
%
% Resample binary data file, e.g. create LFP file from raw data file.
%
% USAGE
%
% ResampleBinary(inputName,outputName,nChannels,up,down)
%
% inputName binary input file
% outputName binar... |
6f342a63525216d5aa052ddd82792d83655425513cedd3a0085af3a06dcc4bab | MATLAB | 2,130 | 65 | function varargout = ft_warning(varargin)
% FT_WARNING prints a warning message on screen, depending on the verbosity
% settings of the calling high-level FieldTrip function. This function works
% similar to the standard WARNING function, but also features the "once" mode.
%
% Use as
% ft_warning(...)
% with argume... |
a4e2c836edcdd9b1276a4f68303f9cf5d7a86fd498939f3cad1040d624395465 | MATLAB | 2,130 | 80 | function prob=pca_dim(lambda,N);
% PCA_DIM Automatic choice of dimensionality for PCA
%
% Laplace approximation and subsequernt simplifications to the
% posterior probability of the Data being generated from hidden var's
% of dimensionality k
% Methods described in
% Thomas Minka:
% Au... |
ce9fa8bf6a44e7778622c927f96a114dc9dec7d7fe71d273b98cf9721c621cdf | MATLAB | 2,130 | 61 | function unit = ft_estimate_units(size)
% FT_ESTIMATE_UNITS tries to determine the units of a geometrical object by
% looking at its size and by relating this to the approximate size of the
% human head according to the following table:
% from 0.050 to 0.500 -> meter
% from 0.500 to 5.000 -> decimeter
% fr... |
de3eb5fb88e0bd8dad8a8aedbe9ee4411f936f2490a607ceaf3b03ef621342a1 | MATLAB | 2,130 | 70 | function [model,IDmap] = runTCA(data,R,titles,plotArg)
% converts data matrix to tensor object then finds the model with the
% lowest error for the provided rank. Plots model
%Does not remove neurons with neuron factors of 0 at this stage
%INPUTS:
% data = data matrix created in time__Tensor
% R = number of compo... |
e0ad8ea2e1e982e0f644cbaaf9402bcf7bf2711f19ede5782d3d33001b4b3785 | MATLAB | 2,130 | 48 | % Wakeman & Henson Data analysis: Extract EEG data and import events and channel location
% Data available at https://sccn.ucsd.edu/eeglab/download/ds000117_sub-01.zip
% (subject 1 of https://nemar.org/dataexplorer/detail?dataset_id=ds000117)
%
% EEGLAB plugin/extensions required
% - File-io
% - Fieldtrip
% - bids-matl... |
5ce04357174a4da36e052ab697a3c2d17ca68e4c7a27f0e18d2b8b93f3879a0e | MATLAB | 2,132 | 52 | %{
stack.StackInfo (imported) # header information
-> experiment.Stack
---
nchannels : tinyint # number of recorded channels
nslices : int # number of slices
frames_per_slice : int # number of fra... |
dc332658e75d14e84f68e2ef2eaef06be6109608c5299dea250828664c3343ad | MATLAB | 2,132 | 91 | function plot_fig2g(datadir)
% Plot event-aligned ACh responses (baseline corrected), split by relevant
% conditions at each event, averaged across rats (N = 10).
% 1. Offer Cue: volume
% 2. Reward Port On: side
% 3. Reward Cue: delay
% 4. Reward Delivery: delay
% 5. Opt Out: side
%
% INPUTS
% datadir: file path of dat... |
c9a3c4d671fadda9465bf708dac1372f605a8871131022cc73a89ba7b36a2f7f | MATLAB | 2,133 | 54 | function herr = plot4BarsWithDots(plotdat,colormat,plot_sig,plot_sig_diff,plot_exact)
if nargin<5
plot_exact=true;
end
if nargin<4
plot_sig_diff=true;
end
if nargin<3
plot_sig=true;
end
hold on
nt = size(plotdat,2);
nx = size(plotdat,1);
mubar = mean(... |
cbf07411ea3b6c598a8b74b40087bbed78d60e1aff033948c5b19c34c1deb40a | MATLAB | 2,133 | 55 | function output = decodeWiener(kinematics, neurons, tPts, ROIs, lags, kinematicField, neuralField)
% Fit a lagged Wiener filter model with specified lags
% lags must contain 0
% Note tPts argument instead of tBins, tPts is integer values of time
% points, ie -100:10:400
% For the first submission we fit RADICaL to the... |
d140806f99585771f5f1409d94ed5780d287d1915ff8ce5d727170f62d0fe9fc | MATLAB | 2,133 | 54 | function [S, f] = calculateSegmentSpectrum(data, lineNoise)
% Multi-taper segmented spectrum for a univariate continuous process
%
% Usage:
% [S, f] = calculateSegmentSpectrum(data, lineNoise)
%
% Parameters:
% data (single channel) -- required
% lineNoise structure with various parameters set
%
% ... |
d2b38c7b97aec1d835df4e92d522791606924d3a16038772776063f7a84c5d93 | MATLAB | 2,133 | 53 | % RSPFUNC - sub-function used by RSGET
%
% Usage: res = rspfunc(pval, l, rval)
%
% Input:
% pval - p-value to optimize
% l - [l1 l2 l3 l4] l-values for Ramberg-Schmeiser distribution
% rval - expected r-value
%
% Output:
% res - residual
%
% Author: Arnaud Delorme, SCCN, 2003
%
% See also: RSGET
%
% Referen... |
673b26599ce4768b40ebc3154bd7ff99e698a5c9674f0845255919b728f6fdcf | MATLAB | 2,135 | 60 | function patchMatchCost_group(thisSubj,subject_list,dInput1, dInput2, fileDir)
load(subject_list)
Patch1 = strcat(fileDir, thisSubj,'/',thisSubj,'_Patch_RH.mat');
if exist(Patch1,'file')
A1 = load(Patch1);
load(dInput1);
C = cell(1,length(subject_list));
outputCost = strcat(fileDir, thisSubj,'/',thisSu... |
bfc024ae7359550d4dd89382274c76a56ccf211ac1e2905d2f887360f0ad2ce4 | MATLAB | 2,135 | 58 | % GETTEMPFOLDER - return the temporary folder
%
% Usage: >> folder = gettempfolder;
%
% Output: a string containing the folder if a temporary folder can be found.
% Empty if the folder cannot be found.
%
% Author: Arnaud Delorme, SCCN, UCSD, 2012
%
% Copyright (C) Arnaud Delorme
% This file is part of EEGLAB,... |
d4c2f9f57f229574eb6b38d7533a4f5c6ee8324a10a089a84360955ae2a33d09 | MATLAB | 2,135 | 53 | function [m,dm] = meanGPexact(mean,cov,x,y, hypz,z)
% Mean function being the predictive mean of a GP model:
%
% mu(z) = posterior mean of GP at location z as given by
% mu(z) = gp(hyp,@infExact,mean,cov,@likGauss,x,y, z) where
% hyp.mean = hyp_mean; hyp.lik = log(sn); hyp.cov = hyp.cov;
%
% The hyperparameters are:
%... |
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