sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
15d30f66861315253a9b191f300d40e9297b72e13604bdffaec0e322f54060a6 | MATLAB | 6,116 | 155 | % This script accurately computes and displays electric fields sampled on
% a cross-section (sagittal plane) via the FMM method with accurate neighbor integration
%
% Copyright SNM/WAW 2017-2020
%% Load/prepare data
planeABCD = [1 0 0 X]; % Equation of the plane of the cross-section (for neighbor trian... |
8529b5da583c64fcb4875d66031d6ab5e7fd2aad0efaff878221855ddbc67eb8 | MATLAB | 6,119 | 185 | % function f_GetIIRFilter.m
%
% This function returns an IIR filter
%
% Parameters:
%
% ps_SampleRate: The sample rate of the signal to be filtered
%
% ps_CutFreqs: A vector or a scalar containing the cut frequencies
%
% ps_Order: The order of the filter
%
% pstr_Type: Set empty ([]) for a pass-band filter, 'low'... |
9eac9b6eeca14cfa2f5a9a02e4a6ab048f474adeab75b1326eb838e17b004d84 | MATLAB | 6,122 | 161 |
switch Analysis_Type
case 'SingleWindow'
for idxArea = 1:length(cfg.aROI)
figure; idx_boxes = ceil(length(idxE)/2);
for idxEpoch = idxE
Epoch = idxEpoch;
Predictors = Spike_Data{3}{idxEpoch};
for idxPredictor = 1:length(Pre... |
300c542f7a418f8dd0f4e2e6d8ce7a1c1efb20de0feb5d3d7343b3ac6da7b41f | MATLAB | 6,125 | 227 | function out = delta2chi_nSFCRL2(params)
% out = delta2chi_nSFCRL1(params)
% delta2chi_nSFCRL1
% Ref: Bao et al, IEEE TMI, 2016 35(9):2040-50
% Chen et al, J Neurosci Res, 2019, 97:467:479
% Milovic, MRM, 2018, 80:814–821 (FANSI)
% FANSI toolbox: https://gitlab.com/cmilovic/FANSI-toolbox
%
% Authors: ... |
9560e4a09e47f64236e8cfe982d1eaef95a7de97c6fd405ae292ecd9762f877b | MATLAB | 6,125 | 198 | function err = MRIwrite(mri,fstring,datatype)
% err = MRIwrite(mri,fstring,datatype)
%
% Writes an MRI volume based on the fstring. fstring can be:
% 1. MGH file. Eg, f.mgh or f.mgz
% 2. BHDR file Eg, f.bhdr. Result will be written to a bfloat
% volume, eg f_000.bfloat.
% 3. NIFIT file, Eg, f.nii, f.nii.gz (unco... |
a743d703785fa6d71c57ec31d0fe84d09193b6fb70851c411e53710215f5f053 | MATLAB | 6,125 | 216 | function hdr = load_nifti_hdr(niftifile)
% hdr = load_nifti_hdr(niftifile)
%
% Changes units to mm and msec.
% Creates hdr.sform and hdr.qform with the matrices in them.
% Creates hdr.vox2ras based on sform if valid, then qform.
% Does not and will not handle compressed. Compression is handled
% in load_nifti.m, which ... |
0ba01d6fa654369b60dce5df89d46155d25a758e10d764b06ac2ce7ee9e6223b | MATLAB | 6,130 | 130 | function [transition_graph,normalized_adj_matrix, adj_matrix, adj_matrix_duration_occupied, behavioral_ratios] = BehavioralTransitionGraph(Tracks, number_of_behaviors, plotting, ratio_included)
% Generates a normalized adjacency matrix from tracks
% the generated adjacency matrix has "from" columns and "to" row... |
74aeb00f1ad8a9eb9243cb2ce38d3dad16450226542187fa7adc4c6f771a8e9b | MATLAB | 6,130 | 187 | % plotAvgContParamEphys_fly.m
%
% Function to plot output of getCorrelationEphysContParam_cond_all() as
% average across flies and/or individual flies
% Spike rate on x, behavior on y
%
% INPUTS:
% datDir - path to folder containing savePCAinterpStepParam() output files
% avg - 'mean' or 'median' for which type of... |
d885b802521c2b637213294ed216cffc8859fdca26ca4b40d9d434af8d8e21e8 | MATLAB | 6,134 | 170 | function [result] = ml_egomaps_compute_with_egotable(...
animal_pos_x_cm, animal_pos_y_cm, animal_facing_angle_deg, ...
cell_activation, ...
ARENA_WIDTH_CM, ARENA_HEIGHT_CM, RADIUS_CM, EGOMAPS_CM_PER_BIN, EgoTable, showAnimation)
%DISCRETIZATION_SCALE_FACTOR = 100;
% EgoTable = ml_egomaps_compute_s... |
60ce7e7da6509a25d8e498aa4c6315736cb12056e0eabfdb80450a38a5d9ed8d | MATLAB | 6,138 | 227 | tic
%% open/read file and set up Environment
%clear;clc;close all
activateCEDS64
% Wavelength
WAVELENGTH = 1999;
file = 'Z:\1_Maxwell_Gagnon\RuthProjectData\01_10_18\apples.smr';
fhand1 = CEDS64Open(file);
%% Read Channel information
load('jan12Workspace.mat')
% sineWave channel (8)
%[ ~, sineWave, ~ ] = CEDS64Re... |
281919cd210fce99f8df87847b2a1888dbe9b14cb8c7ff5b9109a0a42e5e8e27 | MATLAB | 6,139 | 208 | function handles = fix_FixTrackFlies(flies,f0,f1,handles)
% track multiple flies
% splintered from fixerrorsgui 6/23/12 JAB
guidata(handles.figure1,handles);
MINPRIOR = .01;
se = strel('disk',1);
nflies = length(flies);
mu0 = zeros(nflies,2);
S0 = zeros([2,2,nflies]);
priors0 = zeros(1,nflies);
for i = 1:nflies,
fl... |
4a081cb097d4cb611e193868fd8c14ed1b9c2c7be9ffd843d759e67390eca977 | MATLAB | 6,139 | 143 | function [ pM_A,pM_V,pC1_givSASV,sHatAMAP,sHatVMAP,pC1MAP] = ...
computeRespDistrib_factModel(pCommon, muP,sigP,sigA,sigV,sigA_d,sigV_d,lapse,k,eta,param)
% computes the binomial distribution for unity response and multinomial
% distribution for A location judgement given parameters of the causal
% inference mo... |
8ade16dd781474dfe7aec255734cd282cb285613098a0451dbf0646fdc7e035b | MATLAB | 6,139 | 171 | function [y,yy,nremove,scores]=nt_zapline_plus(x,fline,nremove,p,plotflag)
%[y,yy]=nt_zapline(x,fline,nremove,p,plotflag) - remove power line artifact
%
% y: denoised data
% yy: artifact
% nremove: adaptive nremove result
% score: score of the components on which the adaptive algorithm is based
%
% x: data
% flin... |
5891b826a22cc78ab8743ad06c19c3e6ed27f6f50d632dd264c0ce128d76d5e2 | MATLAB | 6,142 | 143 | function mltp_plot_placemaps(obj, session)
tFileFilenamePrefixes = session.getTFilesFilenamePrefixes();
numCells = length(tFileFilenamePrefixes);
for iCell = 1:numCells
fnPrefix = tFileFilenamePrefixes{iCell};
% We need to know which trials belong to each context.
cmap ... |
7ac15b2c5d6a41f69f04fa235859a4e62abc8f5dc0eb4f7ad290ca4cf188e958 | MATLAB | 6,145 | 183 | % f_findHFOxSTF.m [As a part of HFO Detection Project]
% Written by:
% Miguel G. Navarrete Mejia
% Electrical Engineering MS candidate
% UNIVERSIDAD DE LOS ANDES
% Colombia, 2012
% mnavarretem@gmail.com
function m_HFOEvents = f_findHFOxHIL(pstr_SignalPath,ps_SignalIdx,st_DatA,...
... |
5cb829608caa65faf26f3d8d36acc99062547e7ac7f9eb865414b0a229fb7422 | MATLAB | 6,152 | 198 | function decoding_movement_direction_all_sessions(Sessions,Areas,threshold,Ndir,k_fold,Nrep)
%% decoding_movement_direction_all_sessions predicts the movement direction bin and angle from the preparatory neural activity
%
% INPUTS
%
% Sessions: cell array containing the names of the sessions to be analysed.
% e.g {'MC_... |
71e02dda06cfd6d4826df082bc3c0381c15569300d3d64ec8d8f438ae0d891cd | MATLAB | 6,159 | 166 | % go through 1_Maxwell_Gagnon and then ProjectData_Testing
% in each folder in this directory (i.e. Delta7, Delta7-Gen)
% - FOR each folder in Delta7
% - open the .xlsx file that matches the name of the folder
% - onto the final destination .xlsx file do what is done
% - open the .mat file that matches the nam... |
b5a91ae375ba3de5b8a19b74f07a220e79c9411a20ba510dd9ab74b022b834ee | MATLAB | 6,162 | 225 | clear all
close all
%addpath('../lib/') %add the lib to path, wherever you have put it.
%note all "melting" steps have been performed already and the outputs are
%saved in the data folder. This script is only collating the information
%and plotting it and running stats.
%setup basic definitions:
lrstr='lr';
pathcolo... |
25d612aa66eb9ab35659d2b9f0b033b761dd4bd72b6932a9e34797e7c035910a | MATLAB | 6,171 | 163 | function [ ] = getVIF(dicomdir,workingDir,concentrationmap1File,concentrationmap2File,fastdceFile,sequencenameFast,MP2RAGE_postcontrast1File,MP2RAGE_postcontrast2File,hematocrit,fastLookUpTableFile)
cd(workingDir)
% retrieve the exact timepoints of the mri scans using the dicominformation
[intervalFast,kcenter_timepo... |
ab3fb95b79d826b5300bf3a9301d46766e288135a85b2a79ecd0d94b9bf68044 | MATLAB | 6,171 | 163 | %% write_mff_event.m
% Matlab File
% author Colin Davey
% date 3/2/2012, 4/15/2014
% Copyright 2012, 2014 EGI. All rights reserved.
%
% Writes an events structure (as described at
% http://fieldtrip.fcdonders.nl/reference/ft_read_event) to an event-track
% file in an existing MFF file (filePath).
%
% filePath... |
bb629435b207fb5821bbea9ea1baf6c654576f66750397c4a81ad0276ab8aa6d | MATLAB | 6,174 | 186 | #!/bin/bash
#SBATCH --time=360:00:00
#SBATCH --job-name=ALLtrainByRep
#SBATCH --mail-type=END
#SBATCH --mail-user=
#SBATCH --mem=3G
#SBATCH --cpus-per-task=2
#SBATCH --array=1-15
#SBATCH --output=outputs/ALLtrainByRep_A%A_%a.out
#SBATCH --error=outputs/ALLtrainByRep_A%A_%a.err
#Load Matlab 2017a module
ml MATLAB
ml li... |
540dfb82854d9677387e74718af4ced4c1c44b8e0415a8076b5973c67cc6ab25 | MATLAB | 6,178 | 204 | function [] = ExtDataFig03_AveTimeCourse_OptStim_Song
% Code for plotting the time course of and the proportions of pulse and sine song in Extended Data Fig. 3a,h.
GT = 'dPR1NP'; % Extended Data Fig. 3a
% GT = 'TN1SGNP'; % Extended Data Fig. 3h
switch GT
case 'dPR1NP'
CellFlagNonTrans = [1,1,0,1,1,1,1,1,1... |
43ecccb653305083b872e99c8d3206747154d55d05be3000c27b436adbe8a9f8 | MATLAB | 6,181 | 207 | %% average weights plotting
figure('Position',[1200 300 500 500])
subplot(3,1,1)
plot(ff_vect(1,:),'x');
if num_columns == 2
hold on
plot(ff_vect1(1,:),'x');
end
xlabel('Trial Number');
ylabel('Mean FF Weight');
subplot(3,1,2)
plot(rec_vect(1,:),'x');
if num_columns == 2
hold on
plot(rec_v... |
1ff4df17a6860a28abab044dcf21ed31346f202527a3196906cdb0f59cc8b80e | MATLAB | 6,183 | 190 | function aedes_helpabout()
% AEDES_HELPABOUT - Show Aedes About dialog
%
%
% Synopsis:
%
% Description:
%
% Examples:
%
% See also:
% AEDES
% This function is a part of Aedes - A graphical tool for analyzing
% medical images
%
% Copyright (C) 2006 Juha-Pekka Niskanen <Juha-Pekka.Niskanen@uku.fi>
%
% Depar... |
69f67b16ac913df44e6b71821e3cb99d4246570c5c69ffa3ce24ca39ba8f5f8a | MATLAB | 6,202 | 199 | function findmagscaleVel
% Updated 2/23/15 HP
% Simplest version of calibration: fit sine wave to VOR stimulus for both
% video and magnet channels, scale so the gains are the same.
close all;
magthresh = 5; % 15
vidthresh = 100; % 100
freq = 1;
%% Load magnet
pathname = cd;
[~, filenameroot]= fileparts(pathname);
f... |
5bbd489081d68808be324733abeb481f7345e1f9f705699bb55735189d142f79 | MATLAB | 6,209 | 181 | function[data,h]=SONGetADCMarkerChannel(fid, chan, varargin)
% SONGETADCMARKERCHANNEL reads an ADCMark channel from a SON file.
%
% [DATA {, HEADER}]=SONGETADCMARKERCHANNEL(FID, CHAN{, START{, STOP{, OPTIONS}}})
% FID is the matlab file handle, CHAN is the channel number (1=max)
%
% [DATA, HEADER]=SONGETADCMARKER... |
4403e452243f501f32739debb5e98d91a01a24552ee711575d0d573d44b009bf | MATLAB | 6,220 | 166 | % preprocessIInj.m
%
% Function for processing current injection from iInj field of ephysData
% Extracts start and end times of each iInj step as well as its amplitude.
% Also, logical for iInj step or not. And original iInj vector.
% For steps of 0 pA, uses known duration of time between steps to estimate
% when thi... |
ed9fd9d26d9b6f67a96d3b480dafbe6f9fa62f1031ce0cfd6ff51c71956233f8 | MATLAB | 6,225 | 191 | % Starburst Algorithm
%
% This source code is part of the starburst algorithm.
% Starburst algorithm is free; 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 vers... |
c062d7f53aed65a8401f4fdfa805da8d8b10fcd17c4f4bcc2d7b36a8d90903b8 | MATLAB | 6,226 | 209 | function encoder = trainEncoder(images, varargin)
% TRAINENCODER Train image encoder: BoVW, VLAD, FV
% ENCODER = TRAINENCOER(IMAGES) trains a BoVW encoder from the
% specified list of images IMAGES.
%
% TRAINENCODER(..., 'OPT', VAL, ...) accepts the following options:
%
% Type:: 'bovw'
% Bag of visual wor... |
b4ed917fa7bc202d7909149360f727e688562ba557cbcf547fe177b9f80ba07a | MATLAB | 6,229 | 173 | function [x, fmax, nf] = nmsmax(fun, x, stopit, savit, varargin)
%NMSMAX Nelder-Mead simplex method for direct search optimization.
% [x, fmax, nf] = NMSMAX(FUN, x0, STOPIT, SAVIT) attempts to
% maximize the function FUN, using the starting vector x0.
% The Nelder-Mead direct search method is used... |
106af6e4b492d0abfa2e89e3d4a7749c0f7a20a356c337fd78a9e43537ba3277 | MATLAB | 6,231 | 209 | function Dvec = movingslopeCausal(vec,supportlength,modelorder,dt)
% movingslope: estimate local slope for a sequence of points, using a sliding window
% usage: Dvec = movingslope(vec)
% usage: Dvec = movingslope(vec,supportlength)
% usage: Dvec = movingslope(vec,supportlength,modelorder)
% usage: Dvec = movingslope(ve... |
910b238e171121c6b8e239cfee20fda3b4b5f0186f149feb874e65c4a38ff981 | MATLAB | 6,231 | 171 | %% CLEANING UP
clear all;close all;clc
%% DEPENDENCIES SPECIFICATION
% DATA PATH SPECIFICATION
ToolsPath = '/home/guille/GitHub/SoO/Tools';
DataPath = '/media/guille/DADES/DADES/PhysioNet/QTDB/manual0';
% Wavedet codes
addpath([ToolsPath filesep 'BSB' filesep 'WAVEDET' filesep '... |
a0423d5ffff5172213eb6cbfb49ec42d12e14b6dd8781815e723117afd86377a | MATLAB | 6,232 | 292 | %
% Draw and print one scatter plot.
%
% PARAMETERS
% s (n*4) One row per network; columns: X, Y, FORMAT, WEIGHTS.
% kind What is plotted (only used for printing)
% class Only used for the filename
% type One letter plot type:
% a Abbreviations, colors by format
% b Bare - only black point frame. No labels. Squa... |
ce91946832030d897ee9eee3ac44cbcf55d479be87702e51edd1850e856e8fa8 | MATLAB | 6,233 | 166 | function [trackParams, frameData] = eyeAnalysis_APP(app, trackParams)
%% Parameters & Prep
a = 0:.1:2*pi;
the = linspace(0,2*pi,100);
lastGoodFrame = 1;
%% Get Images
disp('Opening Images...')
tic
[ImageStack, n_images] = getImageStack(['img', num2str(trackParams.cam), '.tiff']);
toc
%% Pre-process Images
disp('Prep... |
58e3cce0da1facbd2dcadc19858792594e0f4df82f41978f40fb7fc1de9f0b69 | MATLAB | 6,236 | 210 | % createEphysLegTrackFictracMovie.m
%
% Quick and dirty script to generate movie showing ephys recording, FicTrac
% variables, leg movie, leg tracking (overlaid on movie and with leg
% positions. Starts from raw data.
% Made 10/28/22 - for 2022 pizza talks
%%
pDataFilePath = ['/Users/hyang/Dropbox (HMS)/EphysAnaly... |
e6132938f3e0dba5fac024205a83631b67bcdef8841a077fec78ef39f7caae69 | MATLAB | 6,237 | 193 | function [red_wavelength_stack,Fall,redcell_vect_init,wsFall] = load_reg_tif_wavelength_rev(info)
% Function that loads the Fall.mat files from functional data, redcell-only
% suite2p,and wavelength series suite2p. Also loads the reg_tif generated
% by suite2p for the wavelength series
%INPUTS:
% info: structure ... |
a6c444bd6d598758db4fd72ea1ff3c4ec2cbedf503ebe1ada277b0a0feb082ba | MATLAB | 6,240 | 163 | function[partialcorr_results] = get_partialcorr(combined_info)
%%load data
dff = combined_info.dff;
decon = combined_info.deconv;
%%get forward, reverse, left, right velocity
velocity = combined_info.velocity;
[roll_pos,roll_neg, pitch_pos, pitch_neg, yaw_pos, yaw_neg] = separate_velocity_channels(velocity);
% roll_... |
edea13b3da95eb21aad1d41523eead73bec3a1964386703b7574208aefd37c41 | MATLAB | 6,249 | 125 | function adj_mat = sampSmallWorldMat(N_node, K_conn, beta, varargin)
% adj_mat = sampSmallWorldMat(N_nodes, K_conn, beta {rand_opt, self_ex,
% n_locs})
%
% Create a random small-world graph using the Watts-Strogatz model for
% small world graphs. There... |
4fb33551f17d00f0bb7c37d082fa93efcb44516ae3053eb5ae3d7e0815f922f3 | MATLAB | 6,250 | 182 | % pcaCompStepParams.m
%
% Function that takes in two sets of step parameters, performs PCA on each,
% and compares the two against each other.
% Operates on output from saveBallLegStepParamCond_bouts() or
% saveLegStepParamCond_bouts(). One point per turn bout
%
% INPUTS:
% set1 - struct of first set of step params... |
f6edf40ad4b6f96d4e09a3162e64066ee0eb8878e59bec3a490e40fa85397108 | MATLAB | 6,253 | 143 | % visstimUserPrompts.m
%
% Function to wrap all the user prompts to get the input parameters for
% presenting visual stimuli (on the G3 arena system)
%
% INPUTS:
% settings - struct of ephys setup settings, from ephysSettings()
%
% OUTPUTS:
% visstimParams - struct with fields containing all parameters:
% vi... |
49ea6c1ac7e6b7795c8f016b8c7d6884a5fdc1f56b0f271a5234479c2e1641a2 | MATLAB | 6,259 | 167 | function handles = find_parcellated_paths(handles)
fs=filesep;
ix_surv=find(or(handles.mc.surv_ix(:,1),handles.mc.surv_ix(:,2)));
n=size(ix_surv,1);
parcel_names=cell(n,1);
mismatch_frames=zeros(n,1);
parcels_that_mismatch=cell(n,1);
parcels_per_study=zeros(n,1);
%% Promt user to ignore validation of frame count per pa... |
4570cfdcfcc27346d0bd2d8d839c5aba79d425e36f1865f2943b097c9c0a2d31 | MATLAB | 6,268 | 222 | clc
clear
% This code requires the MATLAB Neural Network and Deep Learning Toolbox
% Packages.
% This code develops and compares the different neural network (NN)
% architectures considered for modeling any generic nonlinear dynamic data.
% The candidate network models considered in this code for comparison a... |
ee9a7ea0379620420689f856b4b538892e17ec946235ccea53f23f5a0c7601f3 | MATLAB | 6,284 | 191 | %% function to run pairwise comparision and one-sample t-test
% against zero and plot all results into the same plot
% function [handles] = perm_multcompare(condA, condB, nperms, ...
% clusteralpha, alpha, xaxis, plotcolors,...
% conditionnames, ax1, markSize, LfontSiz,... |
5842b15a26a80da039638799ac5f88328eee45d45f7cb9a76ff4aa5fcb8bc7a5 | MATLAB | 6,286 | 200 | function [Acc_per_cv,error_angle,error_angle_bin]=decoding_movement_direction(coeff,direction,s_angle,neural_activity,colour_dir,k_fold,Nrep,shuffle,do_plot)
%% decoding_movement_direction train a Naive Bayes model to decode the movement direction from the preparatory neural activity
%
% Model is k-fold cross-validated... |
a33737240b125003e2666c8d4a9e2b6460d62fc32ec52c1f468022493184a2b2 | MATLAB | 6,294 | 223 | function cross_whisker_adaptation(fig5)
av_unit=1;
ff=dir('*.mat*');
Nsessions=size(ff,1);
percentile_FR=0.95;
window=100;
nunits=33;
first_FR=nan(nunits,2);
h_pred1=nan(nunits,1);
p_pred1=nan(nunits,1);
WSAI=nan(nunits,1);
samples=zeros(Nsessions,1);
%% Define population FR per mouse
mouse_id=zeros(Nsessions,1);
... |
bc6d341bf0b88c064a48d46770b62bad3a33d2097fe6b8572bd8de3ad985537c | MATLAB | 6,294 | 122 | function [LNPStats, meanLEDPower, stdLEDPower] = FitLNP(Tracks,parameters,cross_valdiation)
%FitLNP takes in tracks and outputs the parameters of the LNP
% Detailed explanation goes here
numbins = 10;
if nargin<3
cross_valdiation = false;
end
seconds_before = parameters.BTA_seconds_b... |
352c2d7ab565f199f1ca687d02ae6aa18b652b6536deef3b0b47133fec395b08 | MATLAB | 6,295 | 152 | %% windowed SD %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
windowLen = 100;
windowedSDFig = figure();
for k = 1:size(segMat_405_Control, 1)
moveSTDsegMat_405_Control(k,:) = movstd(segMat_405_Control(k,:), windowLen);
moveSTDsegMat_472_GCaMP(k,:) = movstd(segMat_472_GCaMP(k,:), windowLen);
... |
44784569f80dc0c1adf19ea87ebd4d2e040d0bd66e958dfa4c164dc1b4cc4c4c | MATLAB | 6,296 | 120 | %% calculates gradient refractive index in lens based on reference region, axial displacement and reflectivity
close all
n0=1;
nc=1.375; % cornea refractive index
na=1.33; % aqueous humor refractive index
nl=1.41; % lens average refractive index
complx1=complx1_aligned; % complx1_aligned = complex OCT matrix, pre-pr... |
4869242f235ebbbd268cfc87c397bd71e62411b57a927c48df73f3bbee8fed31 | MATLAB | 6,297 | 229 | %
% Generate the plots relative to one decomposition for one network.
%
% PARAMETERS
% $network Internal name of network
% $decomposition Internal name of decomposition
%
% INPUT FILES
% dat/decomposition.$decomposition.$network.mat
%
% OUTPUT FILES
% plot/decomposition.{...}.$decomposition.$network.eps
%
color... |
962b38f5caaef7545971b7d66f57af6e8ecb37b463e0dd70f778184230e7401c | MATLAB | 6,303 | 173 | % run2PExpt.m
%
% Top level function for running experiments on the updated 2P deux
% two-photon scope.
% Sets up folder structure for organizing data (date/fly/fov/trial),
% prompts for experimental condition and runs it.
%
% USE: run2PExpt()
%
% Created: 7/27/18
% Updated: 7/31/18 - HHY
%
function run2PExpt()
... |
f7adb5ff02333ac61ba430299663a9dae814f97c61fa8d5d008b4a83d98f8b91 | MATLAB | 6,304 | 135 | function run_tracker(videos_struct, options, input_calibration_file_name, vinfo_or_video_file_name)
% Deal with options argument
if nargin < 2 || isempty(options) ,
options = [] ;
end
options = sanitize_tracker_options(options);
% Set display variables
do_use_display = options.isdispla... |
468ecc85281488bc22f3237b2690b134469142b465064079239331fbd4cfa95b | MATLAB | 6,310 | 113 | function [UMparam, UniqueIDConversion, MatchTable, WaveformInfo] = RunUnitMatch(Params)
%% UnitMatch Parameters
% Use some bombcell parameters
if Params.RunQualityMetrics
paramBC = bc_qualityParamValuesForUnitMatch;
UMparam.sampleamount = paramBC.nRawSpikesToExtract; %500; % Nr. waveforms to include
UMpar... |
e3c282d81675eaddf02c77f558e12a4694826886d0a4389a6b75f8a56cff43b1 | MATLAB | 6,311 | 139 | %% DEMO UNIT MATCH
% Example data can be found here: https://doi.org/10.6084/m9.figshare.24305758.v1
%% README
% UnitMatch matches neurons within and across days using only their spatiotemporal waveforms.
% To run, it needs a folder called 'RawWaveforms' for each recording, where there should be a NPY file for eve... |
50ce33925f58a865906e9692caea7e55a0a351c828d125ab62ea90cbfb4df2ee | MATLAB | 6,321 | 150 | % Analysis LFP from ExtractData/ using NeuroView 1.3.0
% analysis three type of activities: Spontaneouspain, Groom, Move..
% no active means NoSpontaneouspain, NoGroom, NoMove..
Basepath='ExtractData';
eventtype={'Spontaneousnopain','Spontaneouspain'};
filelist=dir(Basepath);
PSDparams=PowerSpectralDensity.getParams();... |
4be5f8589f091f2481f32b28d7c052d3fc670f8771372bf63da8fe58d5705e0d | MATLAB | 6,328 | 89 | % SON32
%
% Files
% son32 - Prototype file. Create structures to define interfaces found in 'matlab'.
% SONAppID - sets or gets the creator lable from a SON file
% SONBlocks - returns the number of blocks written to disk for the channel
% SONBookFileSpace - Allocates di... |
53e596851803df43945afc5e199a2a90900d7385031002e68ca3a0bb3417b1f8 | MATLAB | 6,333 | 168 | % skip subjects to form subgroups
% SI Table 4, 10, 11, 14
%
% 2023-10-13 Jonathan Wirsich
%select table: options: 'SITable_4', 'SITable_10', 'SITable_11', 'SITable_14_HS', 'SITable_14_noHS'
select_table = 'SITable_4';
[confs, confs_label, groups, eeg_conn_types, bands, atlases, serialized_path] = init_serialized_conf... |
4dd86f18961574626955c2a8c1646dcf9f62a543f3bd71c11b6797fce93b7270 | MATLAB | 6,337 | 232 | function [omitH, omitCenters, eye_pos_filt, eye_vel_pfilt] = desaccadeVel_B(data, samplerate, freq, presaccade, postsaccade, thresh)
% STEP 1: LOW PASS ON POSITION
% N = 4;
% fc = 15;
% [bb,aa] = butter(N, fc/samplerate, 'low');
% eye_pos_filt = filtfilt(bb,aa,data);
eye_pos_filt = data;
% STEP 2: CALC VEL - use H... |
36414a720503f7de9819d4199027867ab49e2062fa044fc42fcb4881fb448b03 | MATLAB | 6,347 | 174 | function cfg_artifacts=st_event_tables_to_array(cfg_artifacts)
% ST_EVENT_TABLES_TO_ARRAY converts continuous artifacts (as detected by ST_RUN_DETECTOR_SET) to segment-based artifact grids
%
% Use as:
% cfg=st_event_tables_to_array(cfg)
%
% Required configuration parameters (all automatically supplied by ST... |
5199d1546f07331d74e0d70ed3500fb0c5a35b75c637f927fee187435340a031 | MATLAB | 6,351 | 198 | %% generate the nii data of connectivity for two-way ranova
%% each nii contain data:3(icc type)
%% do two-way ranova in MRM toolbox
%% the file sort in MRM is: smo_dbm, smo_vbm, no_smo_dbm, no_smo_vbm
%% do the post hoc with paired t test
%% para
load('Sub_matrix_str_DBM.mat')
data.no_smo_dbm = mean(sub_matrix_no_smo,... |
a3b95a67833188e98ece56b4c66e551474dcc72d387e91200a191c04b8ff24a6 | MATLAB | 6,353 | 184 | % function [results] = figureS1_loc(data_dir, id, data, read_from_xlsx)
% this function creates full rasterplots for location cells
%
% parameters
% data_dir (str): path to source_data directory
% id (int): 1 or 2, since there are 2 units of each type
% (responding to items or l... |
21ec6e922ca050b3d3541dcc76c517177fc35771a70d989fa1bc0cdd2ed1a3cb | MATLAB | 6,355 | 185 | function grandaverage(data_timelock, type, condition, group)
%% GRANDAVERAGE
% Computes the block average over multiple participants for a given
% condition and visualizes this in multiple plots and videos.
%
% INPUT:
% - data_timelock: cell-array with timelocked data of all participants
% (output from timelock.m)
% ... |
1eb0d8dc63f8091896131241dcf526907164c473c8ac978fa4f6c0d468ab09c3 | MATLAB | 6,359 | 200 | function outfile = heatscatter(X, Y, outpath, outname, numbins, markersize, marker, plot_colorbar, plot_lsf, xlab, ylab, title)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% heatscatter(X, Y, outpath, outname, numbins, markersize, marker, plot_colorbar, plo... |
735979f290daf0221b4af06c27d8a7ae57eec72d0a1a722cd9585ae3a1edbf08 | MATLAB | 6,363 | 135 | % icadefs() - function to read in a set of EEGLAB system-wide (i.e. lab-wide)
% or working directory-wide constants and preferences. Change the
% way these are defined in the master icadefs.m file (usually
% in dir eeglab/functions/sigprocfunc) or make a custom copy of
% ... |
65b86c5499e628f8f7dda49d4c141a46c6794a176034516d056472cddf2eddaf | MATLAB | 6,364 | 202 | function [variance,mov_distance,mov_duration,max_speed,Dur_var_exp,InnerP,InnerPdir]=embedding_dimensions_dpca(Session,Area,Ndir,Nbins,t_from,t_upto,edges_dur_bin,do_plot)
%% embedding_dimensions performs dPCA on the neural data from Session and
%% Area binning the movements into Ndir directions and Nbins durations
% T... |
70b1f9abe0582e386d4ff9936ef5b278125458e08e53bcbc146e10feec2181bd | MATLAB | 6,365 | 178 | % plotOptomotorOptoDiffFicTracChangePos_allFlies.m
%
% Function that takes outputs from extractOptomotorFicTracOptoCond_fly()
% and plots the change in FicTrac position parameters. Specifically, for
% each fly, plots the average across trials of the difference in
% cumulative position/angle between two time period... |
c05a011ae8f15eb5705ec19bb8b4477445ba3df5becaa02ea7452c152cdf5889 | MATLAB | 6,376 | 139 | classdef ElectricalSeries < types.core.TimeSeries & types.untyped.GroupClass
% ELECTRICALSERIES A time series of acquired voltage data from extracellular recordings. The data field is an int or float array storing data in volts. The first dimension should always represent time. The second dimension, if present, should ... |
1111020f4ab73e63ed7593a5170f22bc715bc83e42c411575a5b06d31e44c5b9 | MATLAB | 6,377 | 148 | function [allDS, allLMMResults, allLMMResults_model] = getDataTableAndLMMResults_stRet_matchedVoxels(projectDir,...
subjnrs, sModels, tModels, stRetParamsFlag, saveFolderNameDS)
%% Define model params
if ~exist('sModels','var') || isempty(sModels)
sModels = {'oneGaussianFit','oneGaussianFit','oneGaussianFit'};... |
57fe6399f964a30c8b00a229f8993c5d717166690142c96b6ff9805563795d22 | MATLAB | 6,379 | 251 | %% Code simulating a Perceptron-like shallow network learning to perform
% a transitive inference task. Figures resulting from this simulation and
% the related analysis provided the material to compose Fig. 3 of
% (Di Antonio et al., bioRxiv 2023, DOI: 10.1101/2023.08.03.551859).
%
% Copyright Maurizio... |
66936c5e0d71327c5249eee2f2701155632f5d7a7034ff897e3fb9fcd03f6080 | MATLAB | 6,379 | 251 | %% Code simulating a Perceptron-like shallow network learning to perform
% a transitive inference task. Figures resulting from this simulation and
% the related analysis provided the material to compose Fig. 3 of
% (Di Antonio et al., bioRxiv 2023, DOI: 10.1101/2023.08.03.551859).
%
% Copyright Maurizio... |
75d8c98d5e7251693b61cf8770ae81dd76d7c98fe2a3d7c6bc0f03b526365cf4 | MATLAB | 6,380 | 179 | function VOR_Summary_Sriram_DR1(params)
%% Prep
type = 1;% 1 == desaccaded, 2 == good cycles
load('t0_t30.mat')
%% Calculations
% Desaccaded
t0_eyeVelDes_Wmean = segObj(1).eyeVelDes * (1-segObj(1).SacFrac) + ...
segObj(2).eyeVelDes * (1-segObj(2).SacFrac) + ...
segObj(3).ey... |
ea9a0a2a41a2b77db2544c7cce16efef08f3831c03eb00be242b813b8a0bd1b4 | MATLAB | 6,383 | 200 | %% for each step parameter, plot scatter against spike rate
% subplots for each leg
% change this up to change what is being plotted
% thisStepParam = legSteps.stepLengths;
% whichParamStr = 'Step Lengths (Body Lengths)';
% thisStepParam = legSteps.stepXLengths;
% whichParamStr = 'Step X Lengths (Body Lengths)';
% s... |
447f8907f2482416b6755e2346d4ff75dc2fafe5cc7961b308414c2446f21f24 | MATLAB | 6,388 | 158 | function [order_in, order_out, frac_x] = func_SIR_adaptive_inverted(...
aij, gamma, seed)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% If you use this code, then please cite:
% 1.- Ana P. Millan, et al. "Individualized epidemic spreading models
% predict epilepsy surgery outcomes: a pseudo-pro... |
58d47c0ffc665816fa9e9ad875ec638251c35e415dc5719650843a30300f7ee0 | MATLAB | 6,390 | 129 |
Shuffle_num = 1000;
% Loop through each mouse
for m = 1:n_mice
% Loop through each field for the current mouse
for f = 1:n_field(m)
% Extract data for current mouse and field
X = CR_e_tr_all{m,f};
Y = Hit_e_tr_all{m,f};
% Iterate over blocks
for b = 1:numel(X... |
2884a5a518cac84bf5b52dca142eb8861152a0096376d0cf71bc9f6185502d30 | MATLAB | 6,393 | 166 | % preprocessFictracVidFiles.m
%
% Function to preprocess raw FicTrac video .tiff files.
% Call on date folder.
% Generates and calls powershell script for renaming .tiff files.
% Does command line call to ffmpeg to generate .mp4 video file for each
% trial with FicTrac video data.
% Generates powershell script and fil... |
37836d1e644c279def674e9e65872e8ee7a1f42f745dbf6615e7a8062dc27b32 | MATLAB | 6,394 | 191 | function recurrence_region_all_sessions(Sessions,Areas,threshold,Ndir,Nbins,threshold_dist)
%% recurrence_region_all_sessions defines a region of recurrence
%% for each recording and counts how many trajectories are inside this region at each moment in time
%
% INPUTS
%
% Sessions: cell array containing the names of t... |
e6957d5f817d057205cda241c26b99481d353e093f06679d12255490e63cef0b | MATLAB | 6,404 | 168 | function [f_names,f] = get_features_EEG(EEG,Fs_EEG,stages_30s,window_size)
%get_time_domain_features_EEG: This function returns the EEG features for
%the paper "Machine learning predict phenoconversion from polysomnography
%in isolated REM sleep behavior disorder". The features are calculated in
%separate windows ... |
f6d6aa75293cad81717f8404259484308792ca65712436f10a377b8702d2218d | MATLAB | 6,405 | 156 | clear;clc;
addpath('/network/lustre/iss02/home/fabien.hauw/Documents/MATLAB/spm12')
addpath(genpath('/network/lustre/iss02/home/fabien.hauw/Documents/matvol'))
addpath(genpath('/network/lustre/iss02/home/fabien.hauw/Documents/MATLAB/spm12/matlabbatch'))
D = '/network/lustre/iss02/cohen/data/Fabien_official/SYNESTHEX/... |
891c23160970cd2be5be5832a26648d1f3f560c14d3788865b4f210036856190 | MATLAB | 6,420 | 183 | %% Calculate Blood Vessel Width Based on Full-Width at Half-Maximum method
%Input: Single 8-bit tif image
%TO USE: Draw straight line perpendicular to blood vessel
%User drawn lines saved to image
%Calculates vessel width based off user defined pixel_size
%Output: Saves vessel width to excel file
%Made by Chris... |
28a0b226651a9b1305d4869d27fdf9a03d588737d93aab8d96581b6a47cb072b | MATLAB | 6,424 | 238 | % for paper "Inferring stochastic dynamics of complex systems", T.-T. Gao,
% B. Barzel, and G. Yan
clc, clf, clear, close all
%% original data
data2norm = csvread('flocks_timeseries_2dim_hf4.csv');
data2v = (data2norm(2:end,:)-data2norm(1:end-1,:))./0.01;
figure;
for i = 1:size(data2norm,2)/2
plot(data2norm(1:200... |
831a4ae05c49d5c2000719f5d7a57ce7cf4a273aa29c2a6257d2677aee1acb20 | MATLAB | 6,424 | 137 | %% Description
%{
This script depicts examplary burst events in mouse LFP signals and further
visualizes a summary of time series-based burst detection method.
%}
%% Configure Library Path
UTIL_DIR = genpath('/Users/scho/Cho2024_MouseEscapeData/utils');
addpath(UTIL_DIR);
%% Set Hyperparameters (User-Defined)
% [1] For... |
0747abe350beca324e0ca147de157c4129d8443b6d07bad71447dbc02b1d9639 | MATLAB | 6,433 | 172 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% If you use this code, then please cite:
% 1.- Ana P. Millan, et al. "Individualized epidemic spreading models
% predict epilepsy surgery outcomes: a pseudo-prospective study."
% medRxiv (2023): 2023-03. doi: https://doi.org/10.1101/2023.03.16.232873... |
b2cf70ade5d872ceb3fc07b975646a6d8a1a9c97369fa6d125a385f31f992d95 | MATLAB | 6,434 | 252 |
function runner_info=prepare_runner_test_simple(run_config)
class_info=run_config.class_info;
ds_config=[];
% set the input image scales, useful for multi-scale evaluation
run_config.input_img_scale=0.8;
run_config.gen_net_opts_fn=@gen_net_opts_model_type1;
run_config.run_evaonly=true;
ds_config.use_custom_data=... |
368c5f82992128a5d8c8c6552534ec998751d72e3abc3f778cd7d7222b361d86 | MATLAB | 6,438 | 164 | function [fraction_above_speed,p_speed,fraction_above_dist,p_dist,average_speed_bin,average_dist_bin,Distance_speed,Distance_dir_speed,Distance_dist,Distance_dir_dist,R2,power_sample]=speed_distance(Session, Area,threshold,Ndir,t_from,t_upto)
%% speed_distance compares the distance between trajectories corresponding
... |
120b5ad3bdd0f012deffe0cc4d38fc4a513b9db58fc2f5f046f849fdf9b69758 | MATLAB | 6,439 | 176 | function [frames, descrs] = vl_phow(im, varargin)
% VL_PHOW Extract PHOW features
% [FRAMES, DESCRS] = VL_PHOW(IM) extracts PHOW features [1] from the
% image IM. PHOW is simply dense SIFT applied at several resolutions. This function is a commodity interface to VL_DSIFT() and
% VL_IMSMOOTH().
%
% DESCRS has t... |
136821125da4b09fd8403dad7a7337580b5d13a1f8798bea1678481fdd77847a | MATLAB | 6,439 | 201 | % not used in paper
% Projections = {Tracks.ProjectedEigenValues};
% Projections = cellfun(@transpose, Projections, 'UniformOutput', false);
%% get the experiment folders
folders = [];
while true
if isempty(folders)
start_path = '';
else
start_path = fileparts(fullfile(folders{length(folders)}... |
c36c6c355a4ca2a8cb7159bbaf8edcc2808fc910f1281956a961d6b7c46ed8eb | MATLAB | 6,442 | 157 | function fH = plotLMMfittedRegressionSlopes(ds,lmmResults,LMMOrder, roisToPlot,cmapROIs, useSTRetParams, saveFigs, saveFigDir)
% Function to plot Linear Mixed Model fitted regression slopes (fixed and
% random subject slopes, for each condition and visual area).
% To plot Figure 4B, "LMMResults" struct has fields with ... |
49b65ef4bb075d0fe0e7eb497c5674c268e23940da9fbcd514072e3a106180fa | MATLAB | 6,449 | 175 | function [filename, headerfile, datafile] = dataset2files(filename, format)
% DATASET2FILES manages the filenames for the dataset, headerfile, datafile and eventfile
% and tries to maintain a consistent mapping between them for each of the known fileformats
%
% Use as
% [filename, headerfile, datafile] = dataset2fil... |
98f3c0d099beea7faf4b849fcfd1badb034b94adcc91718172a522b3ec64e6b5 | MATLAB | 6,453 | 156 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [T, G] = compute_per_group_animal_averaged_rate_difference_histdata(SessionsToGroups, RateMatrices, perCellNormalizationMethod, perAnimalNormalizationMethod)
% 2022-02-04. This function was based off of
% compute_per... |
411c5d9f164d4fb7c25b4aa5ba8fd2405d09dca01b44dc13ef1d47efdbe65e29 | MATLAB | 6,454 | 180 | %Test FfdrGND function
%
%AUTHOR: Eric Fields
%VERSION DATE: 12 June 2020
global test_xls_output
if isempty(test_xls_output)
test_xls_output = true;
end
%Load a GND for testing
%Load a GND for testing
FMUT_dir = fileparts(fileparts(which('A_setupTest')));
load(fullfile(FMUT_dir, 'testing', 'data', 'E... |
b6680f10d73a9778adc43d92cad6fbc2a66da7c9e639db2975b006ff4f74f009 | MATLAB | 6,454 | 159 | clear;
%%% GENOME_BUILD initialization
fprintf('initializing...\n')
chr_initialization;
%%%%%%%%%%%%%%%%%%%%%%%%% SETTING PARAMETERS %%%%%%%%%%%%%%%%%%%%%%%%%%
CNV_type='Del';
GENOME_BUILD=GENOME_BUILD_19; %genome build
PATH_INPUT='../input';
PATH_OUTPUT='../output';
FILE_CASE_NAME='ASD_cnv_case.txt';
FILE_CO... |
a0732ad4c060edaa05bbaff7d6d856dc6f35361baa4aea959b6a3ffd74dff105 | MATLAB | 6,462 | 134 | function fH = plotLMMregressionSlopes_v_pRFSize_stRetParams(allLMMResults, ...
params, modelToPlot, roisToPlot, cmapROIs, saveFigs, saveFigDir)
% Function to plot LMM regression slopes against CSTfix, CSTopt, or DN-ST
% pRF size. This is a panel in Supplementary figure 9 in the paper:
% Title: Rethinking simultan... |
943a38b79201e1738185b23b15cc30eb90b5dec2a63a9fc2f2be5e1ab4d7b171 | MATLAB | 6,465 | 132 | function [fluors, opt] = preprocessing_UFARSA(opt,fluor)
% [fluors, opt] = preprocessing_UFARSA(opt,fluor)
%
% Pre-processing of the given fluorescence trace. The main steps considered
% in this function are: Normalization, Slow drifts removal, Deflections
% removal, Smoothing, and Noise level estimation.
%
% ... |
7bc0063f2056c231e7399f7e360d2a11741770efc47b9dadc7ab0e77f520280d | MATLAB | 6,469 | 172 | function results = overall_plots(results, opt)
all_participants = fieldnames(results);
map = zeros(opt.ymax-opt.ymin+1, opt.xmax-opt.xmin+1);
total_A_UL_map = map;
total_A_UL_amap = map;
total_A_HLeft_map = map;
total_A_HLeft_amap = map;
total_A_FLeft_map = map;
total_A_FLeft_ama... |
69c0a8adbdcbe9a64985d092aafcbdd738d95f9f29d13eca36f5f914c76d3508 | MATLAB | 6,472 | 227 | function [M_Ru1, M_Ru2, M_v1, M_v2] = vox2ras_rsolve(Vc_C, inPlaneRotation)
%%
%% (USE vox2ras_rsolveAA INSTEAD OF THIS METHOD!)
%%
%% NAME
%%
%% vox2ras_rsolve.m (vox2ras_r{otation matrix}solve)
%%
%% AUTHOR
%%
%% Rudolph Pienaar
%%
%% VERSION
%%
%% $Id: vox2ras_rsolve.m 8776 2013-11-14 09:04:48Z roboos $
%%
%% ... |
a548545cc3ef5af14c0fade67b0378c307161bc232cd82d212b0cc3e999e553b | MATLAB | 6,473 | 182 | function [boxes hierarchy blobStruct mergeThresholds] = BlobStruct2HierarchicalGrouping(blobStruct, neighbourMat, numInitBlobs, CalculateSimilarity)
% [boxes hierarchy blobStruct mergeThresholds] = BlobStruct2HierarchicalGrouping
% (blobStruct, neighbourMat, numInitBlobs, CalculateSimilarity)
%
% G... |
d0b1e3515e18dc337677f93a1be9712fefaf0083d76d8ebb652c70215ec47e06 | MATLAB | 6,474 | 184 | % saveStepParamPairwiseCorr_bouts.m
%
% Function that takes output from saveBallLegStepParamCond_bouts() or
% saveLegStepParamCond_bouts() and gets pairwise correlations (Pierson)
% between all specified leg step parameters (specific param, leg, step).
% Also saves all points that go into correlations.
% Select input... |
d93a9a11dbc4d0e0a724d7d7e84d139d67866512a3be3841c5896408d0b1a08e | MATLAB | 6,479 | 113 | % globals for TessData
warning off % Warning: The value of local variables may have been changed to match the globals.
% Future versions of MATLAB will require that you declare a variable to be global before you use that variable.
% > In globals (line 18)
global SearchSubFolders; % if 1, search files in all s... |
b309c9254f2baafb6f0c7e62d5a6ce3b3bb8e6cefc12b4501ca2a92f77d6938a | MATLAB | 6,485 | 174 | function h = alluvialflow(data, left_labels, right_labels, chart_title, patch_colors)
% Copyright 2018 The MathWorks, Inc.
%
% Plot an alluvial flow diagram.
% left_labels: Names of categories to flow from.
% right_labels: Names of categories to flow to.
% data: Matrix with size numel(left_labels) rows by
% ... |
6d6a12af1fd1d9da1859f6a9aab449c39f85af06cba7b9a96a18ae67e8206dbd | MATLAB | 6,493 | 123 | % function [K_LNP, K_Shuffle] = CrossValidation()
%CrossValidation compares the predicted reversal rate with a null model;
%not used in paper
% % Detailed explanation goes here
fps = 14;
number_of_trials = 100;
dt = 1/(fps*60);
training_ratio = .8;
load('reference_embedding.mat');
number_of_be... |
5f5235924b5c662676cd23046bcf004397f22ac5a11008e4f1cceb4b0d7c3d9b | MATLAB | 6,496 | 100 | % Get header of the source information
% [ Yokogawa MEG Reader toolbox for MATLAB ]
%
% brief:
% This function retrieves information of the sources in the specified file.
%
% usage:
% source = getYkgwHdrSource(filepath)
%
% arguments:
% filepath : file path
%
% return values:
% source ... |
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