sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
d310ecb751820c5a82a9dba03fbd5c783f4a3c7c852acc2c8a5b64e9171533d6 | MATLAB | 6,471 | 186 | function [pntr, trir, texr] = refine(pnt, tri, method, texture, varargin)
% REFINE a 3D surface that is described by a triangulation
%
% Use as
% [pnt, tri] = refine(pnt, tri)
% [pnt, tri] = refine(pnt, tri, 'banks')
% [pnt, tri] = refine(pnt, tri, 'updown', numtri)
% [pnt, tri, text... |
329b28bd94ef5692d48485bef09894f9b8f80c8c74ab8f4ef7a51046b545170a | MATLAB | 6,473 | 227 | % rd_analyzeTADetectDiscrimGroupBehav.m
%% setup
exptDir = pathToExpt;
% subjects = {'rd','lr','mj','af','xw'};
% startRuns = [211, 211, 221, 221, 221];
subjects = {'mj'};
startRuns = 1;
nSubjects = numel(subjects);
%% load data
for iSubject = 1:nSubjects
sessionDir = subjects{iSubject};
behavDir = sprint... |
c4dafb6da58d699c913dc0e587b382cbbc4efaac8515f245f2a310c50d9a2cc1 | MATLAB | 6,474 | 162 | function ft_trackusage(event, varargin)
% FT_TRACKUSAGE tracks the usage of specific FieldTrip components using a central
% tracking server. This involves sending a small snippet of information to the
% server. Tracking is only used to gather data on the usage of the FieldTrip
% toolbox, to get information on the numb... |
eff5f151ff34000a7b3cf896ed9ec0f84d9783766c063b596c027e868e8eba0c | MATLAB | 6,474 | 195 | function gprDemoMarglik()
% Make figure 5.5 of Rasmussen and Williams book
%PMTKauthor Carl Rasmussen
hhh=figure(1)
clf
set(gca,'FontSize',22)
n = 7;
rand('state',28);
randn('state',28);
xs = 15*(rand(n,1)-0.5);
K = inline('exp(-0.5*(repmat(p'',size(q))-repmat(q,size(p''))).^2)');
fs = chol(K(xs,xs)+0.01*eye(n))'*ran... |
ae45a33e44e390cd04bf642ba1b22e511d3c988e8fcd6a28aca47ecf0ce6b272 | MATLAB | 6,475 | 189 | function M = grassmanncomplexfactory(n, p, k)
% Returns a manifold struct to optimize over the set of subspaces in C^n.
%
% function M = grassmanncomplexfactory(n, p)
% function M = grassmanncomplexfactory(n, p, k)
%
% Complex Grassmann manifold: each point on this manifold is a collection
% of k vector subspace... |
afbb800acc4d7a1f88bed41e97a7d8c2d6bf264e53b27916eeacb7352f8b13bd | MATLAB | 6,475 | 223 | function [asens, afiducials] = ft_average_sens(sens, varargin)
% FT_AVERAGE_SENS computes average sensor array from a series of input
% arrays. Corresponding average fiducials can also be computed (optional)
%
% Use as
% [asens, afid] = ft_average_sens(sens)
% where sens is a 1xN structure array containing N sensor ... |
23a0edad77c717a70fabe3fa4a73189ee86160ad96594bcb6a95c44a5a6b591c | MATLAB | 6,476 | 166 | function DecodeAnalysisAction(AllTrialData,Labels,DecodeLabels,TimeWindow,OutDir,Tag,varargin)
% Plots confusion matrix (decode analysis) for decoding each (relevant)
% condition.
% [~,PThresh] = Utilities.ProcVarargin(varargin,'PThresh',0.001);
[~,PThresh] = Utilities.ProcVarargin(varargin,'PThresh','fdr');
[... |
aeb62456dd7138ee965e176ff2b09fd92d13aceb65feefbf9f42283207a119c9 | MATLAB | 6,478 | 152 |
ind = 1;
data = dir('/DATAPOOL/ERRORMONITORING/SEM_mri_data/P*');
%%
for i = 1:size(data,1)
runs = [1:7];
SPM_file = [data(i).folder, '/', data(i).name, '/mri/SEM_', data(i).name, '/nifti/GLM/SPM.mat'];
SPM = load(SPM_file);
SPM = SPM.SPM;
errorCorr_conWeights = zeros(1,length(SPM.x... |
5acd8ec99fce66019c1e573ff6719f48f8ba307b43936a3495e06657c81b7eb1 | MATLAB | 6,480 | 183 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% creates self.n_channels new axes, assuming that
% the GUI has no already-existing axes or
% ass... |
6d747319c81307e181cc89c91fed5d4c348757ef9931af40752045fba6c98898 | MATLAB | 6,481 | 245 | function [data] = fiff_setup_read_raw(fname,allow_maxshield)
%
% [data] = fiff_setup_read_raw(fname,allow_maxshield)
%
% Read information about raw data file
%
% fname Name of the file to read
% allow_maxshield Accept unprocessed MaxShield data
%
%
% Author : Matti Hamalainen, MGH Martinos Center
%... |
f8fee325ad57032ed5e4638954200e33e8d14865e6e96b3918a5b28c11824fae | MATLAB | 6,484 | 209 | function [Gx, Gy, Gz] = imgradientxyz(I, method)
%IMGRADIENTXYZ Find the directional gradients of a volume.
% [Gx, Gy, Gz] = IMGRADIENTXYZ(V) takes a grayscale or binary volume V
% as input and returns the gradient along the X axis, Gx, the Y axis, Gy
% and the Z axis, Gz. X axis points in the direction of increa... |
1837f06715511062f1fef67db311928675b919ff50fa6018d54c0657ea8fc2eb | MATLAB | 6,486 | 180 | function [parhat,Q,parerr,nll] = ECMEtdr(stopmode,stopcrit,pars0,Ai,Xi,r,ni,zetai,xbari,Ybar,Xzetai0)
% [parhat,Q,parerr] = EMtdr_Slamb(stopmode,stopcrit,pars0,Ai,Ri,zzi,r,ni)
% Function to perform expectation maximization to estimate time-varying
% basis functions and independant noise variance for the MBTDR model.
%... |
de84119171d5642c018a9be2120a471b9baf5a61052814e602d48affd885feff | MATLAB | 6,487 | 189 | function FilterLabChart(datFile, varargin)
% hard-coded parameters
bytesPerSample = 2;
wname = 'db4'; % specifies Daubechies(4) wavelet filter
% set default values for varargs
maxLevel = 6; % This sets the (high-pass) cutoff frequency for wavelet filtering.
% cutoff frequency = Fs/(2^(maxLevel+1)) ... |
d6fd65a1f36bce0584e0bcd32badbb939c784268ece7ccf7ede330d143b26532 | MATLAB | 6,489 | 153 | % Noam Saadon-Grosman
% August 2020
% This code computes laterality in each vertex of each subject in each
% stimulus direction that passed the threshold for significant
% somatosensory response. Laterality is defined as the normalized difference
%between contralateral and ipsilateral response
% The output stract... |
6a693103b684417b396ac226d9fd86ad5db526ad896e66ad59e78802760797ba | MATLAB | 6,490 | 136 | function [Data, VoxelSize, FileList, Header] = y_ReadAll(InputName)
%function [Data, VoxelSize, FileList, Header] = y_ReadAll(InputName)
% Read NIfTI or GIfTI files or DPABINet Matrix files in all kinds of input formats.
% ------------------------------------------------------------------------
% Input:
% InputName - C... |
963e78bca009b0ca70890ad49ca78ef6cf41e18b5348dd5e5887a1e842165026 | MATLAB | 6,491 | 226 | function out = scatplot(x,y,method,radius,N,n,po,ms)
% Scatter plot with color indicating data density
%
% USAGE:
% out = scatplot(x,y,method,radius,N,n,po,ms)
% out = scatplot(x,y,dd)
%
% DESCRIPTION:
% Draws a scatter plot with a colorscale
% representing the data density computed
% using three ... |
92ed35e10ee9dcb76b16f9554f78704b805d71b08dbce0224a6bd0dbf4298a5e | MATLAB | 6,496 | 117 | clc
format compact;
FLIM_main_folders = 'Q:\TBI\LiveData_Injury_2022\FLIM_results\';
ShortNames = {'R1_6hr','R1_24hr','R1_72hr','R2_72hr','R2_24hr','R2_6hr'}; % 'R2_24hr_crash' contains no FLIM.
FLIM_Results_folders = {[FLIM_main_folders,'1stRound\6hr_NAM6_06.15.22'],...
[FLIM_main_folders,'1stRound\24hr_NAM6_... |
886955963472a9634a4b38f69210b9425120b97c78e7bbaeca91168669dff594 | MATLAB | 6,497 | 173 | function [errors, warnings] = debugDemos(subFolder, exclusions)
% Run PMTK3 demos hiding all figures and demo output - displays a report
% This function keeps running even if a demo fails.
%% Input
%
% subFolder - all demos are run by default unless a demo subfolder is
% specified, e.g. Markov_models
%
% ... |
1436d3b712dc316f4ec287e0baad26843a8b78c3f14818a0e54936a15bb93c2b | MATLAB | 6,499 | 170 | function [y, lambda, info] = hessianextreme(problem, x, side, y0, options, storedb, key)
% Compute an extreme eigenvector / eigenvalue of the Hessian of a problem.
%
% [u, lambda, info] = hessianextreme(problem, x)
% [u, lambda, info] = hessianextreme(problem, x, side)
% [u, lambda, info] = hessianextreme(problem,... |
334ca27501f1b7f42bc142a968b955ad85f768f8f7d62a8ec4828742ad0aed73 | MATLAB | 6,500 | 218 | function y_ClusterReport(data,head,ClusterConnectivityCriterion)
% Generate the report of the thresholded clusters.
% Based on CUI Xu's xjview. (http://www.alivelearn.net/xjview/)
% Revised by YAN Chao-Gan and ZHU Wei-Xuan 20091108: suitable for different Cluster Connectivity Criterion: surface connected, edge conne... |
906441b75ddce96142cf68c101223f4f0174042fe43be15dd77b3a714403cac2 | MATLAB | 6,510 | 221 | function A = convnfft(A, B, shape, dims, options)
% CONVNFFT FFT-BASED N-dimensional convolution.
% C = CONVNFFT(A, B) performs the N-dimensional convolution of
% matrices A and B. If nak = size(A,k) and nbk = size(B,k), then
% size(C,k) = max([nak+nbk-1,nak,nbk]);
%
% C = CONVNFFT(A, B, SHAPE) controls... |
cdf4984fecb913b72ed1111374e8fe19529fe62f3b53f4c8b32245346769cb82 | MATLAB | 6,510 | 219 | function han = showvc_prog_plain(loc,tri,view_dir,para);
% Guido Nolte, Stefan Haufe
cmap=1;
voxelkont=0;
colorbars=1;
alphaclimPolicy = 'none';
alpha_const = 1;
if nargin>3
if isfield(para, 'alpha_const')
alpha_const = para.alpha_const;
end
if isfield(para,'voxelfield')
voxelfield=para.voxelfield;... |
2b1ffcf4e50dae2150f2afe0768a75383f0e398888794c83780e655eb11bf44d | MATLAB | 6,514 | 122 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
15aa4c76daa376ef1861a44a705990e7b82aa70800d3aa2fdf665eaf9fd2c3d6 | MATLAB | 6,517 | 169 | function [trialData] = read_sbin_data(filename, hdr, begtrial, endtrial, chanindx)
% READ_SBIN_DATA reads the data from an EGI segmented simple binary format file
%
% Use as
% [trialData] = read_sbin_data(filename, hdr, begtrial, endtrial, chanindx)
% with
% filename name of the input file
% hdr ... |
b4392b4181cb532ad4a17b2ba153b409cf193f9d1c0d4f184fee4d67456dcfbf | MATLAB | 6,519 | 129 | function [Lipofuscin_container, Bright755_container, Cell_NoLipo_container] = generate_Lipo_Apoptotic_RemovalMask(roi_names, file_identifiers, image_array, Masks)
% Two levels of Lipo removal, >0.8 for Lipo, <0.02 for EV
Lipofuscin_container = containers.Map;
Cell_NoLipo_container = containers.Map;
Brig... |
dce6167ac988dd94dc30b9cb9fc6db77d728c512e1235fdc701cf3861944a52e | MATLAB | 6,519 | 172 | % Five-point stencil on the unit square, variable-coefficient Poisson equation,
% Dirichlet boundary conditions.
%
% This is basically the same as FD_SQUARE1 but with a variable quantized high-
% contrast random coefficient field that makes the problem especially ill-
% conditioned.
%
% Inputs (defaults are used if not... |
8dee71198f627aad0beadb262ff4e3daeb1b869531d3b79df3e9c54694b009a8 | MATLAB | 6,520 | 174 | function varargout = DPABI_ConcordanceSelect_Surf(varargin)
% DPABI_CONCORDANCESELECT MATLAB code for DPABI_ConcordanceSelect.fig
% DPABI_CONCORDANCESELECT, by itself, creates a new DPABI_CONCORDANCESELECT or raises the existing
% singleton*.
%
% H = DPABI_CONCORDANCESELECT returns the handle to a new DP... |
be70551c842092e3f61b4f45f97596e3f2194fbd1ffc125f26581e62ecb0d149 | MATLAB | 6,521 | 211 | % Demo for DCM for fMRI (distributed responses)
% This demo inverts the DCM for fMRI model, which contains the ballon model
% as a generalized observation function (not affected by stochastic
% innovations).
close all
clear variables
%-----------------------------------------------------------
%-------------- DCM mod... |
e613ad6570e132e5dc7225427ba77b7fa241a295e20a65768a89da666128f66a | MATLAB | 6,521 | 177 | function Y=ms_bandpass_filter(X,opts)
%MS_FILTER - Bandpass filter using smooth roll-offs in Fourier space
%
%Consider using mscmd_bandpass_filter
%
% Syntax: [Y] = ms_bandpass_filter(X,opts)
%
% Inputs:
% X - MxN array of raw data
% opts.samplefreq - the sampling frequency corresponding to X, e.g.
% ... |
4da020dea5c5973f8754420f84a138dc705d76f0e70fd284848272c924cfbe61 | MATLAB | 6,524 | 129 | function [CPup,CPdwn,Wup,Wdwn,rb,rp,ra] = pkoffon(T,pl,MinNum,gran,crit,S,fig)
% The complement to the pkonoff function; this finds the loci of pauses in
% responding (step-like reductions and resumptions in the rate of responding)
% Computes estimates of the onset and offsets of the pauses and the
% weight of the evid... |
cfc9084a8db7ebb81a1e238ccbfbd381b4956fb6f8bb0d139cbe3105890942e8 | MATLAB | 6,527 | 173 | function [imdata] = synapse_properties_multiplexed_nopw(params,fovid,nsynapses)
% This function extracts multiplexed synapse features (e.g. volume, number
% of puncta for each channel WITHOUT pairwise data (much faster) from cropped synaptic ROIs with multiple channels
%
%Extract parameters
parent = params.parentfold... |
5aa411fd8c708ad8026e2c5976bd09ff41a077a35fd78858b70fc0e4413fa99b | MATLAB | 6,529 | 258 | clc;clear all;close all
V = BrikLoad ('ambmc_ori_100+orig');
LABEL = BrikLoad ('Allen_label_AMBMC_R+orig');
LABEL_L= BrikLoad ('Allen_label_AMBMC_L+orig');
LABEL_L(LABEL_L~=0)= LABEL_L(LABEL_L~=0)+865;
LABEL=LABEL+LABEL_L;
V=reshape(mapminmax(V(:)',0,1),size(V));
az=90;el=90;
T = readtable('labels.txt');
... |
3595afb3f0db54e66f735f0429730baa463183c5b6c0ef0cf17879e3ecad29a5 | MATLAB | 6,530 | 192 | function [DAT,H1]=openedf(FILENAME)
% EDF=openedf(FILENAME)
% Opens an EDF File (European Data Format for Biosignals) in MATLAB (R)
% <A HREF="http://www.medfac.leidenuniv.nl/neurology/knf/kemp/edf.htm">About EDF</A>
% Copyright (C) 1997-1998 by Alois Schloegl
% a.schloegl@ieee.org
% Ver 2.20 18.Aug.1998
% ... |
8ee3056bb13ec0964549e7001a5e77b62a071a012ce2f55eecf6398145f188b5 | MATLAB | 6,539 | 208 | function CrossCorrLimitedConditions(OutDir,Tag,varargin)
% Plots confusion matrix (decode analysis) for decoding each (relevant)
% condition.
% [~,PThresh] = Utilities.ProcVarargin(varargin,'PThresh',0.001);
[~,Pmethod] = Utilities.ProcVarargin(varargin,'Pmethod','fdr');
[varargin,saveFig]=Utilities.ProcVararg... |
0152a1a616050553c2a8688bd180bbef3da73fc8ee386219576be9e3ac05c58c | MATLAB | 6,541 | 218 | % pop_filterp
%
% PURPOSE : Filters ERP data
%
% FORMAT :
%
% >> ERP= pop_filterp( ERP, chanArray, highpasscutoff, lowpasscutoff,
% filterorder, typefilter, removemean );
%
% EXAMPLE :
%
% >> ERP = pop_filterp( ERP,1:16, 1, 40, 25, 'fir', 0 );
%
% INPUTS :
%
% ERP - input ERPset
% chanArray - channel(... |
3f6b74bd162827ff823beb3bfb7fe53730a60e04c3dafe8de3996cf879641c58 | MATLAB | 6,545 | 361 | clear
clc
% This M-file creates an animation of individual muscles as well as the equivalent muscles.
f = 0;
cmap = [[0 1 0]; [0 0 1]; [0 1 1]; ...
[0.4940 0.1840 0.5560]; [0.4660 0.6740 0.1880]; ...
[0.3010 0.7450 0.9330]; [0.6350 0.0780 0.1840]; [1 0 1]; [0.75, 0.75, 0]];
figure(3)
pause(2)
for ... |
e6b282c25af4c5bcac57eee471ff32c6fdd448442f13aeac974fcd8432512a29 | MATLAB | 6,546 | 152 | clear;clc;close
rdfile='Data_exp2.xlsx'; % File for reading data
rdrange='A3:P642'; % Range for reading data
wrfile='Results_exp2.xlsx'; % File for writing results
wrsheet = 'Each participant'; % Sheet for writing results
wrrange1='E2'; % Range for writing TSs
wrrange2='E4'; % Range for writing results
n_... |
601ea44b205a92178447968e9609f855814ec03d8329f7c8d41a015b99605c6c | MATLAB | 6,548 | 137 | clear variables
close all
%% Ensure you stay in the directory of this script as it's running (leave as is)
current_file_name = matlab.desktop.editor.getActiveFilename;
pathstr = fileparts(current_file_name);
cd(pathstr)
% Ensure you can access functions related to the image generator
addpath(pwd)
addpath(... |
8e28c116c1043f5910256562ec982cea3dbbdb15e0d0e54be972ce769c3571bb | MATLAB | 6,551 | 172 | function [trialData] = read_sbin_data(filename, hdr, begtrial, endtrial, chanindx)
% READ_SBIN_DATA reads the data from an EGI segmented simple binary format file
%
% Use as
% [trialData] = read_sbin_data(filename, hdr, begtrial, endtrial, chanindx)
% with
% filename name of the input file
% hdr ... |
448586719d7fd35b00872e3f222af7004d62200ef28c5e7044214e5b10d55987 | MATLAB | 6,555 | 170 | function varargout = FlySongSettings(varargin)
% FLYSONGSETTINGS MATLAB code for FlySongSettings.fig
% FLYSONGSETTINGS, by itself, creates a new FLYSONGSETTINGS or raises the existing
% singleton*.
%
% H = FLYSONGSETTINGS returns the handle to a new FLYSONGSETTINGS or the handle to
... |
12d64fa4fe2db3e30225938f3cd53284c8ec9a61860b44cfd67f9e28ab0640c2 | MATLAB | 6,556 | 135 | % Get paramters
% Edited by Jerry Liu, 09/20/2022
function Parameter = GetParameter_220919(HCstim,savePath)
% this function get the suitable parameters for analysis. call this
% function before implementing the analysis and pass the output struct
% as an argument to functions that need it. if you are to ch... |
7363cccd2318315082f12db3b993b52e037431de9b6c2b8986e4b4f54ac61d45 | MATLAB | 6,556 | 217 | % visualize_distortions
%
%
% A script to run in conjunction with calib_gui in TOOLBOX_calib to plot
% the distortion models.
%
% This is a slightly modified version of the script plot_CCT_distortion.m written by Mr. Oshel
% Thank you Mr. Oshel for your contribution!
[mx,my] = meshgrid(0:nx/20:(nx-1),0:ny/20:(ny-1));... |
1b66fa99350feead8201a5be028bb24bfd0346e6193981ff6bd1dc278a0eeb98 | MATLAB | 6,561 | 158 | function [Q, dQ] = Q_TDR(par_new,par_old,Ai,Ri,zzi,r,ni,alpha)
% Unpack parameters
P = length(r); % number of regressors
T = length(Ri(:,1))/P; % number of time bins
TP = T*P;
rtot = sum(r); % sum of ranks
n = length(ni); % number neurons
lambinew = par_new(1:n);
snew = par_new(n+1:end);
lambiold = par_old(1:n);
sold... |
c347db5244e3f69535272d7520f43256d30fee939f30275ad0423b0653252e81 | MATLAB | 6,561 | 147 | function Step4c_DynamicFC(config, pid, visitnum)
%
% Step4c_DynamicFC calculates specified functional connectivity metric
% across a series of sliding windows, thereby returning dynamic functional
% connectivity rather than static (i.e., 1 value for connectivity between
% pairwise ROIs).
%
% INPUTS:
% > config:
%... |
297468169675971612b3b3ca1b3f94749f234a9f33bc6d65fe8c4681a5596487 | MATLAB | 6,563 | 227 | classdef CropInfo < handle
% Note on 'roi', 'posn', and cropping
%
% roi
% This refers to an APT-style roi. This is [xlo xhi ylo yhi] with integer
% values. In normal situations, we will want positive integer values,
% which are also <= the image size. We call these rois 'proper rois'.
%
% We imag... |
977a9fd006023f536116fd38c44ea21e7d424322845c8d2bcb60acd3a0bff8b5 | MATLAB | 6,563 | 168 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
82488e2d7b2be4fea33512a2d77a121cca2e61e0da296aa6319fa6012b8c1ffa | MATLAB | 6,565 | 180 | % Underdetermined least squares on the unit square, regularized Laplace kernel.
%
% This is like ULS_SQUARE1 except now we use regularized Laplace sources to
% match against data on a quasi-uniform grid. This seems to better match the
% expected asymptotics for method-of-fundamental-solutions problems.
%
% Inputs (defa... |
7b5f6a6b0b9231b520b2a9f2452856ff014dd07c8890b7aef600d36036a767e7 | MATLAB | 6,572 | 252 | function CBH = cbfit(varargin)
%CBFIT Draws a colorbar with specific color bands between its ticks.
%
% SYNTAX:
% cbfit
% cbfit(NBANDS) % May be LBANDS instead of NBANDS
% cbfit(NBANDS,CENTER)
% cbfit(...,MODE)
% cbfit(...,OPT)
% cbfit(CBH,.... |
4a0afa2a2363cfb601ba3d2ded9ff6b0452b802610dbc92413644e0491511bc6 | MATLAB | 6,573 | 251 | function mne_baby_meg_dig_trig(infile,outfile,threshold,invert,include,want_eeg)
%
% function mne_baby_meg_dig_trig(infile,outfile,threshold,invert,want_eeg);
%
% Read and write raw data in 60-sec blocks
%
%
% Author : Matti Hamalainen, MGH Martinos Center
% License : BSD 3-clause
%
global FIFF;
if isempty(FIFF)... |
6de35bbb5ca2d218aebc74bec97ec6fcb09e7ed33641786ee913f4553f3d7ad1 | MATLAB | 6,574 | 165 | function [ctxidx, hpidx] = matchidx_acrossep_singleday(animaldir, animalprefix, day, exclude_list)
eps = 2:2:16;% RUN Epochs
%%
tetinfo = loaddatastruct(animaldir, animalprefix, 'tetinfo');
cell = loaddatastruct(animaldir,animalprefix,'cellinfo');
spks = loaddatastruct(animaldir, animalprefix, 'spikes', day); % get sp... |
b32655a36b8f1c136ae68a85fbc63ec0034850ec301df8d6fd214a3d66d37fde | MATLAB | 6,577 | 295 | % compute f(x) = max_i w_i Gauss(x | mu(i), Sigma(i))
% Code based on
%http://staff.itee.uq.edu.au/marcusg/msg.html
function maxGMMplot()
rng(42) % seed
params = initialize (2, 20, 5, -5, 10, 0.8);
plotlandscape (5, -5, 50, params);
end
function params = initialize(dimension,nGaussian,upper,lower,globalvalue,rat... |
d2127076fed8cfcb06189d6bf5a845aa50145b6878df139a6fe8b7e481112726 | MATLAB | 6,577 | 175 | % Plot normalized ITPC TS by att w shaded error bars
%% Settings
titleVis = 0; % if title vis off, then will plot for appropriate manuscript size
showN = 1; % show n = X annotation
figFormat = 'svg'; % svg
plotErrorBars = 1; % turn off for subject-level plots
restrictYLim = 0; % turn on for group-level manuscript... |
3a17701148b9b2689c6fcd11b42f2b0fec53ccfbdeb859365995022e640236a9 | MATLAB | 6,578 | 212 | function varargout = DPARSF_ROI_Template(varargin)
% DPARSF_ROI_TEMPLATE MATLAB code for DPARSF_ROI_Template.fig
% DPARSF_ROI_TEMPLATE, by itself, creates a new DPARSF_ROI_TEMPLATE or raises the existing
% singleton*.
%
% H = DPARSF_ROI_TEMPLATE returns the handle to a new DPARSF_ROI_TEMPLATE or the hand... |
2f5582cc0526c9686d46a738e554b9fe63c3343752a216bf5c3fbcebc7760ee7 | MATLAB | 6,579 | 123 | function gm = fitgmdist2(X, k, varargin)
%FITGMDIST Fit a Gaussian mixture distribution to data.
% GM = FITGMDIST(X,K) fits a Gaussian mixture distribution with K
% components to the data in X. X is an N-by-D matrix. Rows of X
% correspond to observations; columns correspond to variables. FITGMDIST
% fits the... |
8a48945a8e177d70239705ba2ad56e76362f038b408d5b50195b1a602ba0f6ef | MATLAB | 6,580 | 131 | function BSC_LSA(stat_path,sots_path,exp_folder,N,TR,model,q_level,ground_truth)
% ========================================================================
% Ruslan Masharipov, October, 2023
% email: ruslan.s.masharipov@gmail.com
% ========================================================================
tic
% Number... |
10366d522f1da45a3febfd02bb3c33762412e36fa239524615c5e65d2e512fb5 | MATLAB | 6,582 | 163 | function [all] = VBA_classification_display(all)
% displays the results of VBA_classification
% function [all] = VBA_classification_display(all)
% Note: inputs to VBA_classification_display.m are outputs of
% VBA_classification.m.
% IN:
% - pv: cross-validation p-value
% - df: effective degees of freedom of the t- ... |
1981eb00befa4ca5543f86c1df9c0d567134d63dd60d566c9987c87294e1fd85 | MATLAB | 6,583 | 195 | function [tfr,t,f,wt]=tfrscalo(X,time,wave,fmin,fmax,N,trace);
%TFRSCALO Scalogram, for Morlet or Mexican hat wavelet.
% [TFR,T,F,WT]=TFRSCALO(X,T,WAVE,FMIN,FMAX,N,TRACE) computes
% the scalogram (squared magnitude of a continuous wavelet
% transform).
%
% X : signal (in time) to be analyzed (Nx=length(X)). Its
% ... |
e9d8461990eb8f62ba421531f475e01ed954cd268f2db88ba5e73b9750af7d91 | MATLAB | 6,583 | 248 | function [model, errors] = rbmFit(X, numhid, varargin)
% Fit a bernoulli-bernoulli RBM to binary data
% optionally with class labels
%
%INPUTS:
%X ... N*d matrix, entries in [0,1]
%numhid ... number of hidden units
%
%
%OPTIONAL INPUTS (specified as name value pairs *or in struct*)
%y ... |
ed5f640f89503dacedeb23e9ef823b135abbe08cc0c45301af2406167487a385 | MATLAB | 6,583 | 143 | %% Efficient subpixel image registration by cross-correlation.
% Registers two images (2-D rigid translation) within a fraction
% of a pixel specified by the user. Instead of computing a zero-padded FFT
% (fast Fourier transform), this code uses selective upsampling by a
% matrix-multiply DFT (discrete FT) to drama... |
630b0f15aee4c8517916dc7a8b70220d1b76e89f3b6700657dc89952bb25d0cc | MATLAB | 6,588 | 131 | function [grid_tags, palm_seg_present, dors_seg_present] = GetSegmentLabels(SurveyStruct, ChannelMap, pbt_regions, dbt_regions, method, orig_size)
if nargin == 5
orig_size = [1200, 1050];
end
% Tags for palmar and dorsum
grid_locations = ChannelMap.ChannelNumbers(ChannelMap.IsSensory);
[grid... |
9aaef7b6f02419208d70990f53de32c73de515eeba1b16f4b89da5f1dec229b4 | MATLAB | 6,590 | 230 | function varargout = tracking( varargin )
%tracking Track anonymized usage data
%
% tracking(p,v,id) tracks usage to the property p for the product version
% v and identifier id. No personally identifiable information is tracked.
%
% r = tracking(...) returns the server response r, fo... |
ce921265b405593f578ca6ff45517b8067ede05e7a4478e8104b47f4291ad27d | MATLAB | 6,590 | 187 | %% Plot results of varyDecodeParam.m
% plotVariedDecodeParam.m
%
%% Choose which varied decode parameter result to analyze
% Creates Figure 4—figure supplement 2
% Decoding "mainPaperGrid" with 25 random subset replicates at each point
variedDecodeFilename = 'grid_2023-07-22T14-50variedDecode2023-09-10T21-04.mat';
... |
4769ebee12d5a9c18e6347664db27304365595fec79a452b1c58ebad84d4ead4 | MATLAB | 6,593 | 191 | %% Initialise plot parameters
function pp = InitPlotParams()
% Return struct with plotting parameters to allow for consistent style
% across figures
% ==== Input ===
% none
% === Output ===
% plot parameters: pp = struct with fields
% - color_xhat = RGB color for xhat
% ... |
7547c39564d513ca46c3ed612195a46e3a6a7ab28566a56d0fd8c1033e260ca4 | MATLAB | 6,593 | 230 | %% load weight matrix and declare layer type
% lay is layer in network - 0, 1, or 2
% load the corresponding weights - here all weights are random
% also load the corresponding input
lay = 0;
switch lay
case(0)
weights = cell(1);
for i = 1:8
for j = 1:8
weight... |
53935a19e1b703e79f8e90973475d24f24dbcdabe379520850396a32755af8d0 | MATLAB | 6,594 | 224 | function [asens, afiducials] = ft_average_sens(sens, varargin)
% FT_AVERAGE_SENS computes average sensor array from a series of input
% arrays. Corresponding average fiducials can also be computed (optional)
%
% Use as
% [asens, afid] = ft_average_sens(sens)
% where sens is a 1xN structure array containing N sensor ... |
4158ae26eadef73bbc2690c34d26f9ecbdb0c7131d4080744f0006d2d914d7aa | MATLAB | 6,597 | 127 | clear;
clc;
%% This script used to perform generalized PPI derived from Go trials
% Set up path
Para.rootdir = 'W:\All_IMAGEN_DATA\imaging\SST_spm_first_level_GT'; % SPM first level path
Para.opdir = 'W:\gPPI_Shen_GT'; % output path
Para.Maskdir = 'W:\Shen268_ROIs';% ROI mask path including 268 regions nfiti data
P... |
992491e968d32606b32cc361f1def69e867d3ed7f3ddde1aabda28931a1943e6 | MATLAB | 6,604 | 195 | %% significance
%
% Statistical significance adjusted for multiple hypotheses
%
% <matlab:open('significance.m') code>
%
%% Syntax
%
% sig = significance(pval,alpha,correction)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% pval multi-trial time ... |
90b737e5af261e900e2a6c51b9c683da401acbbd26864cebad382d9c73d753b4 | MATLAB | 6,606 | 192 | function [DAT,H1]=openedf(FILENAME)
% EDF=openedf(FILENAME)
% Opens an EDF File (European Data Format for Biosignals) in MATLAB (R)
% <A HREF="http://www.medfac.leidenuniv.nl/neurology/knf/kemp/edf.htm">About EDF</A>
% Copyright (C) 1997-1998 by Alois Schloegl
% a.schloegl@ieee.org
% Ver 2.20 18.Aug.1998
% ... |
123830d567947610ee52a9308638a9a24218f9b4861d0bb2d1c27d13000c78fc | MATLAB | 6,608 | 175 | % Noam Saadon-Grosman
% August 2020
% This code computes selectivity in each vertex of each subject in each
% stimulus direction that passed the threshold for significant
% somatosensory response. Selectivity is defined as 1/standard deviation of
% a Gaussian fitted to the response Event Related Averaging. The out... |
9c457391daa7a6496426a9cf3636bbc1919f82a40dfcb81fb315505d1124b717 | MATLAB | 6,611 | 253 | function [ fv, normals, name ] = read_stl( file, A, v )
% Modified by William Warriner 22 Aug 2019
% from READ_stl by Adam H. Aitkenhead
% Inputs:
% - @file, a string containing the path to the desired STL file.
% - @format, optional, default "auto", a string containing one of "ascii",
% "auto", or "binary". The str... |
a57c1fa40f617f67c6e6717973ecaa154f18cb153c85c081c72a2b2b1e276579 | MATLAB | 6,611 | 207 | function [P,Uinit,output] = cp_als(X,R,varargin)
%CP_ALS Compute a CP decomposition of any type of tensor.
%
% P = CP_ALS(X,R) computes an estimate of the best rank-R
% CP model of a tensor X using an alternating least-squares
% algorithm. The input X can be a tensor, sptensor, ktensor, or
% ttensor. The resul... |
d861977327621301ea0da530bec05d0614868f0fd565c6db1d7da30456d904dd | MATLAB | 6,612 | 194 | % ========================================================================
% TMFC analysis for event-related design
% Requires SPM12 (v7771)
%
% Beta-Series Correlations based on Fractional Ridge Regression (BSC-FRR)
% requires GLMsingle toolbox (https://github.com/cvnlab/GLMsingle)
%
% ================================... |
13b422530719f08ede7ac9737fed72af62f212d72293889b878f64569f2144e1 | MATLAB | 6,613 | 241 | function [ events auxwaves auxdata ] = wlProc_doSegmentAndParamExtract( ...
wavedata, samprate, bpfband, segconfig, paramconfig, wantmultithread)
% function [ events auxwaves auxdata ] = wlProc_doSegmentAndParamExtract( ...
% wavedata, samprate, bpfband, segconfig, paramconfig, wantmultithread)
%
% This function p... |
bcbc3b689d55be4c9b48249476d33cbedb596512318df6be490df6d222a08c06 | MATLAB | 6,617 | 154 |
function [r, LB, UB, F, df1, df2, p] = ICC(M, type, alpha, r0)
% Intraclass correlation
% [r, LB, UB, F, df1, df2, p] = ICC(M, type, alpha, r0)
%
% M is matrix of observations. Each row is an object of measurement and
% each column is a judge or measurement.
%
% 'type' is a string that can be one of th... |
3078d18938dcc0b8171e2cc7b3157b16147f42c498f19c85db2698bc54ed0816 | MATLAB | 6,619 | 168 | function [U] = emfmm3d(eps,zk,srcinfo,targ,ifE,ifcurlE,ifdivE)
% EMFMM3D FMM in 3D for Maxwell (frequency-domain electromagnetic) kernels.
%
% U = emfmm3d(eps,zk,srcinfo,targ,ifE,ifcurlE,ifdivE)
%
% Frequency-domain Maxwell FMM in R^3: evaluate all pairwise particle
% interactions (ignoring self-interactions) and
... |
487798cffc504367a7741919f483856616a24082f85a91cce8496ab9a58eb9c3 | MATLAB | 6,620 | 194 |
%% This code is used for creating timeseries and averages following processing on the FlyDisco pipeline
%Inputs -
%Conditions: dirs containing expdirs for each experimental type. I
%sorted the expdirs by genotype.
%Behaviors: scores files from the classifier used
%Pre: number of frames that is the pre-stimulus perio... |
ce04e090c1a225e00fc512e5431f3c0d85bc43e56b6f3293f7d4a6fa01c21a4b | MATLAB | 6,621 | 144 | % This code cleans up the seizure data from noisy artefacts and selects the
% components that are relevant to seizure (those that demonstrate
% correlation with seizure onset time).
% data_noise Sohrabpour
% 1/9/2018
clear all; close all; clc
% This part of the code was to load the data for our data base. We... |
bd380c58f1286d9b2b02517661c04c07b79a7a6f844f334d4ddcf8f2afa82389 | MATLAB | 6,622 | 260 | function [hfigs,savenames,errprctiles] = PlotWorstLandmarkErrorOverX(varargin)
[errprctiles,gtdata,nets,legendnames,colors,colorfracprcs,exptype,...
n_train,...
conddata,labeltypes,datatypes,...
maxerr,prcs,...
statname,...
hfigs,figpos,savedir,savenames,dosavefig,xl,savekey] = myparse(varargin,'errprctiles'... |
2e2e918756bde7b6421e7cd7d76584019217ac4bfab0c5a1eb218b427cb5589c | MATLAB | 6,623 | 129 | function [Cms,AcqTms,FinDif,USsToAcq,TrlsToAcq,TmToSig,M,FinDifLstN,FinCSpkrate] = ...
Cums(tsd,CSon,CSoff,UScode,PkCode,Sesstart,LstN,fig)
if nargin<8
fig = false;
end
Cms = nan(length(tsd),19); % intitializing output
Cms(:,1) = tsd(:,1); % cumulative time in context in col 1
LVus = tsd(:,2) == UScode; % flags... |
34ec676a556d909aa98dd8c7c3510d641df60fba23ad5418fb175af30f29acaf | MATLAB | 6,623 | 194 | function EEG = detect_spindles(EEG,PARAM)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Detect Spindles in EEG data
%
% INPUT: EEG = EEGLab structure
% PARAM = structure of parameters (see below)
%
% OUTPUT: EEG = same structure with spindle markers (EEG.event)
%
% Auth... |
6e89d9d92b879f11e1a2c5790b91f32d1c28fdcfc5b9ce9818ebd6bbb90e39aa | MATLAB | 6,623 | 173 | function DecodeAnalysis(AllTrialData,Labels,DecodeLabels,TimeWindow,OutDir,Tag,varargin)
% Plots confusion matrix (decode analysis) for decoding each (relevant)
% condition.
% [~,PThresh] = Utilities.ProcVarargin(varargin,'PThresh',0.001);
[~,PThresh] = Utilities.ProcVarargin(varargin,'PThresh','fdr');
[~,NIte... |
6f76cffc2ed974080c460c2ccfd79e94092b3bb4ce619d9d0425892f7a66bae9 | MATLAB | 6,623 | 149 | function Cfg = y_GetTRInfo(Cfg,WorkingDir,SubjectListFile,StartingDirName)
% function Cfg = y_GetTRInfo(Cfg,WorkingDir,SubjectListFile,StartingDirName)
% Generate TRInfo.tsv
% Input:
% Cfg - the parameters for auto data processing.
% WorkingDir - Define the working directory to replace the one defined in Cf... |
59fd3a7b15d73ca8ae804b84dede9b5a0a99b9fef9f2e411b38890127d2a82b7 | MATLAB | 6,624 | 192 | function [score splitVal] = Bimodality(dat,varargin)
showPlot = false;
nBins = 100;
quantRange = [0.01 0.99];
smoothFactor = 5;
minSampPerBin = 5;
if length(dat) < minSampPerBin
score = 0;
splitVal = nan;
return
end
for i = 1:2:length(varargin)
switch lower(varargin{i})
case 'showplot'
... |
7719cf9f3e98f18ee41c7f9f310e77c552a79c26f2ed1cd5b33ca33de723b00d | MATLAB | 6,628 | 200 | function [all] = VBA_classification(X,y,k,verbose,options,sparse)
% performs binary classification using VBA
% function [pv,stat,df,all] = VBA_classification(X,y,k,verbose,options)
% In brief, this function fits the following logistic regresion model:
% p(y=1) = s(X*beta)
% where y is the binary data, s is the standa... |
1854a921c72a9c1962aa1c1ae6f74ad6a99e495efa16460b5bafd8d00fc07864 | MATLAB | 6,631 | 154 | function [Obj,Dims] = NETCDFload(filename,flags,varargin)
%% NETCDFLOAD
% Obj = NETCDFload(filename,'all') reads the SOFA object OBJ with all data from
% a SOFA file.
%
% Obj = NETCDFload(filename,'nodata') ignores the Data. variables while
% reading.
%
% Obj = NETCDFload(filename,[START COUNT],partialDim) re... |
73d420528e4abb7a63edba9027206502b28f7352ae30275ede80e5320a6f71e3 | MATLAB | 6,632 | 171 | function edited = PulseTrainSettings(pulseTrainDetector, varargin)
handles.detector = pulseTrainDetector;
handles.reporters = pulseTrainDetector.controller.reporters;
if isempty(handles.reporters)
msgbox('You must find or import pulses before you can detect pulse trains.', 'Pulse Train Detector... |
3afc421a7a61a560e2a1ae3d3afe6d27ee1adb5328578aa3b0adb86bc271f8e3 | MATLAB | 6,633 | 179 | % Covariance matrix on the unit cube, squared exponential kernel.
%
% This is basically the 3D analogue of COV_SQUARE1.
%
% Inputs (defaults are used if not provided or set empty):
%
% - N: number of points in each dimension (default: N = 32)
% - OCC: tree occupancy parameter (default: OCC = 512)
% - P: cube root... |
4c4b7e3869aba506158d9dcf110567b58b591f9203c73a020aa7d9ea490f1136 | MATLAB | 6,634 | 186 | function CM=nfoldxval( data, IDX, clfInit, clfparams, ...
types, ignoreT, fname, show )
% Runs n-fold cross validation on data with a given classifier.
%
% Given n separate labeled data sets, trains classifier using n-1 data
% sets, test on remaining one. Average results over all n such runs.
% Shows overall results... |
92337b5a8e6160c6b60c838032dafa0c860460f1f9593bc6578b3d2989502555 | MATLAB | 6,636 | 187 | %parseargs [opts] = parseargs(arguments, pairs, singles, ignore_unknowns)
%
% Variable argument parsing-- supersedes parseargs_example. This
% function is meant to be used in the context of other functions
% which have variable arguments. Typically, the function using
% variable argument parsing would be written with... |
4fd4a6067b5bd0fd7f31acc3fae2d8712e05761aeeb84e0e19f0712a54505351 | MATLAB | 6,638 | 223 | % demo of Bayesian optimization for "code breaking"
function bayesianCodeBreakerSimple()
function prior = makeCodePrior(L, A, code)
% set code(i) = 0 if unknown (uniform prior for ci)
% set code(i) in {1,..,A} to use delta function for that slot
cs = ind2subv(A*ones(1,L), 1:A^L);
... |
cc4ec2b707440e7ea257e06b25f682a32cccdd152143bcd4f5c121b457471979 | MATLAB | 6,638 | 144 | function y_IntermediateFilesOrganizer(WorkingDir,SubjectID,OutputDir)
% FORMAT y_IntermediateFilesOrganizer(WorkingDir,SubjectID,OutputDir)
% Input:
% WorkingDir - the directory contains processed data
% SubjectID - the list of subject IDs for organize. n by 1 cell
% OutputDir - the directory for saving Inte... |
16f7318d0b16584fd16eb295d60b7f69fc269bb022783eef316eba2ca5fa8d59 | MATLAB | 6,644 | 194 | function [posr, trir, texr] = refine(pos, tri, method, varargin)
% REFINE a 3D surface that is described by a triangulation
%
% Use as
% [pos, tri] = refine(pos, tri)
% [pos, tri] = refine(pos, tri, 'banks')
% [pos, tri, texture] = refine(pos, tri, 'banks', texture)
% [pos, tri] = re... |
dfd9135fd94cd73900613805ca06ee3f28f4cff14291987a079e8863fc5576c1 | MATLAB | 6,645 | 103 | % RATE REMAPPING _ POST HOC ANALYSIS PIPELINE
% get stable cells first/second half of laps, adds to subset_of_cells
get_stable_cells(folders,'wcorr');
rate_remapping_TRACK_PAIRS(folders,'wcorr');
plot_rate_remapping_NEW('subset','stable cells laps','epoch',{'PRE','POST'},...
... |
7486c525c42ace288ec3126b9afe9c4c7019c119e4819ec6ece4098feb9bdb85 | MATLAB | 6,649 | 219 | %% Overview
%
% Here we load in our source parcellated MEG data from the preprocessing stage,
% perform some normalisation and compute an Amplitude-Envelope HMM.
%
% Load in study deails
config = utils.get_studydetails;
%%
% Find preprocessed data files
datapath = fullfile( config.analysisdir,'spm_sss_processed' );
... |
f019c8ed986677cbe3ac5c9486b8bcbe18b540bba5b0c420e930e5c76b1fde16 | MATLAB | 6,649 | 254 | function hdlg = JRCBackEndSettingsDialog(obj)
lObj = obj.labeler_;
nrows = 6 + 2;
h = 30;
W = 500;
H = h*(nrows+1);
hdlg = dialog('Name','JRC Backend Settings',...
'Units','pixels','Position',[300 300 W H]);
xborder = 20;
xsep = 5;
yseprel = .025;
wquest = (W-xborder*2-xsep)*.5;
wans = (W-xborder*2-xsep)*.5;
wbu... |
647b903a5462e91f23aea9be3f7efddf2fe110051903b8c6a3697c4856b0b0b3 | MATLAB | 6,654 | 186 | % Overdetermined least squares on the unit square, thin-plate splines.
%
% This is the direct analogue of OLS_LINE for quasi-uniform points in 2D.
%
% Inputs (defaults are used if not provided or set empty):
%
% - M: number of row points (default: M = 16384)
% - N: number of column points (default: N = 8192)
% - ... |
b417f76df2df35d65123732af387445d7ea6d01223b9df59c5410820a30b06ed | MATLAB | 6,655 | 185 | % Underdetermined least squares on the unit square, Laplace kernel.
%
% This example solves an undetermined least squares problem arising from data
% fitting at random points in the unit square by Laplace kernel radial basis
% functions on an quasi-uniform grid. The matrix is rectangular (short-and-fat)
% and real; we ... |
056918b89034cfddd7ccefa9df10cea8c43037eb14c1abddc9f8bdfe9418e61e | MATLAB | 6,660 | 197 | function Results=PopAnal_FormatCorrShuffDynamic(AllTrialData,Phase,unit,timeWindow,opts)
%%
% timeWindow=[-1.5 -.5];
% Task related Firing Rate
disp(timeWindow)
%%
Conditions={ 'NancyPinchCheek','NancyPressCheek','NancyRubCheek','NancyTapCheek',...
'NancyPinchShoulder','NancyPressShoulder','NancyRubShoulder','Nan... |
62fb16a53fe0cec6faa6cf5f442b902cb4e7f1e6bb0750abb789c32a3115a46e | MATLAB | 6,661 | 209 | function [dat] = read_neuralynx_bin(filename, begsample, endsample)
% READ_NEURALYNX_BIN
%
% Use as
% hdr = read_neuralynx_bin(filename)
% or
% dat = read_neuralynx_bin(filename, begsample, endsample)
%
% This is not a formal Neuralynx file format, but at the
% F.C. Donders Centre we use it in conjunction with Ne... |
ec55a3ae34e11d9fd0dceeb5ec4690276a53e31b58c50418e26ab814aee81eba | MATLAB | 6,661 | 231 | function [ ftdata, evmatrix ] = wlSynth_genFieldTrip( ...
samprate, chancount, trialcount, trialdur, burstdefs, ...
channelratevar, channelnoisevar )
% function [ ftdata, evmatrix ] = wlSynth_genFieldTrip( ...
% samprate, chancount, trialcount, trialdur, burstdefs, ...
% channelratevar, channelnoisevar )
%
% T... |
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