sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ba71e0168b5291b49f67607406852977653d597cf531ed9bd491ab2f1ab54397 | MATLAB | 3,642 | 99 | function [subj pathfilename] = move_pattern_to_hd(subj,patname,varargin)
% Moves the pattern MAT to the hard disk
%
% [SUBJ PATHFILENAME] = MOVE_PATTERN_TO_HD(SUBJ,PATNAME,...)
%
% Saves the pattern MAT field as a file, and removes the mat field
% from the pattern cell, to save hard disk space. It also adds a field
% ... |
3142ae1a3aa51642d3460737fb81d3f30bf1d8c61f5cbb6a23d3a8c752581a3a | MATLAB | 3,645 | 145 | function [errmsgs warnmsgs] = unit_create_spatial_avg_pat(varargin)
% USAGE :[ERRMSGS WARNMSGS] = TEST_CREATE_SPATIAL_AVG_PAT(...)
%
% This is a script that tests the spatial averaging functionality.
%
% INPUT ARGUMENTS:
%
% STDOUT (optional, default = true) If true, prints errors and
% warnings to screen as they occ... |
d3b0072ce5c1e555a6d45438a0e10f7837d0d6a8ef19b872411789e8c6133d27 | MATLAB | 3,646 | 106 | % Preprocessing unit test
%
% average_samples
tol = 10e-10;
N = 256;
X = randn(N,1);
% Get default parameters
pparam = mv_get_preprocess_param('average_samples');
%% if a class has less than group_size samples, it should disappear from the averaged sample
pparam.group_size = 5;
clabel = ones(N,1);
clabel(N-30:end)... |
732c4a049bcc8961ef59a5e3f51a5014723915a37aa6a258136d3954cdfd5285 | MATLAB | 3,651 | 137 | % This file is part of the Matlab Toolbox for Dimensionality Reduction v0.7.2b.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are free to use, change, or redistribute this code in any way you
% want for non-commercial purposes. However, it is appreciated if you
% maintain the name of th... |
b87c227716cfbe4a978f0cbe0070a1df4b8a63e657f4d9ea87cd0e6241d9fea2 | MATLAB | 3,655 | 130 | %% Resonance analysis single files (raw nwb files)
fn= '/Volumes/Expansion/Ephys from 226/H23.29.244.01_6 /H23.29.244.11.01.01.nwb';
nwb = NWBfile(fn,[{'CHIRP'}]);
%% Zorg dat hiervoor de traces individueel al bekeken zijn of ze vergelijkbaar zijn
%(indien niet, geen average trace nemen)
% Bij errors 'expected in... |
311cf240903e3c8e4a456b8d69437f90b27463d09324abab6d02a6a0158a9f10 | MATLAB | 3,658 | 78 | %Estimates flicker modulation of single units, using PSTH plots an circular statistics.
%2024/02/25
function modulation_singleunits(fnames)
%CONTINUE WORKING ON THIS...
%SHOW VISUAL AND AUDIO RESPONSE FOR SAME UNIT, OR SHOW A SUBSET OF
%CONDITIONS FOR SAME UNIT, SO READER CAN COMPARE. MOREOVER, RANDOM SHO... |
ec678869af4850ffb63c0376e8f21184430bc9e6cff035fc5e6e899d69607f8b | MATLAB | 3,660 | 116 | function h = plot(this, varargin)
%PLOT plot an ACTI object
%
% $Author: Peng Li
% $Date: Dec 02, 2020
%
% axes
if nargin == 2
if isa(varargin{1}, 'actigraphy2')
if isempty(findobj('Tag', 'actigraphyFig'))
h = actigraphy2(this);
else
h = varargin{1};
... |
2f7d176a61562287f69d659b8d7e77ad946ebcf4bea8db22664d82f3c57a80c9 | MATLAB | 3,662 | 125 | function [modelToLoadFolder] = downlaodModelResultsImages(resultsPath,isCorrectAspectRatio2To1,outputFolder,scaleBar)
% This function downloads test and train images from aws. Saves locally for
% further analysis
% INPUTS:
% resultsPath - path to model result, get using s3GetPathToModelResult
% isCorrectAspect... |
405189cabd512ec744d7526f26239b9d8a55c10f1a863c7f00487e590a4d70f6 | MATLAB | 3,662 | 117 | function [subj] = create_thresh_mask(subj,map_patin,new_maskname,thresh,varargin)
% Create a boolean mask by thresholding a statmap
%
% SUBJ = CREATE_THRESH_MASK(SUBJ,MAP_PATIN,NEW_MASKNAME,THRESH,VARARGIN)
%
% Adds the following objects:
% - mask object OR mask group (if PATGROUP == true)
%
% Takes the MAP_PATIN stat... |
37cb8416b80a7e7a1629dc82d2987d0a8bc68a9442bf035c33f98fb9a239301f | MATLAB | 3,663 | 81 | function [G,h] = build_G_h_quadratic2d(A,delta_b,transformationModel)
% BUILD_G_H_QUADRATIC2D Builds the equation system G*p = h
%
% [G,h] = build_G_h_quadratic2d(A,delta_b,transformationModel)
%
% INPUT ARGUMENTS
% A - A = [A22 A21]
% [A12 A11]
% delta_b -... |
38754174501ce58f73638277521e9019fdd791866c16889583cc8d72cac703ae | MATLAB | 3,664 | 116 | function [t_cluster, clusters] = find_significant_cluster(data, tail)
% function [t_cluster, clusters] = find_significant_cluster(data, tail)
%
% Find clusters of subsequent time points with above-chance reconstruction
% accuracy based on t-tests.
%
% Input:
% - data: 2-D data array, 1st dimension are subjects and ... |
3651e3da02b2a02d3255dfdf9ef432f25d09bdf63e7afdfdaf5bec596c88e6c0 | MATLAB | 3,667 | 62 | %Plots PSDs along with occluded condition, for all electrodes, and saves figure.
%2024/02/25
function plot_depthelectrode_occluded(PSD_results,outputFolder)
depth_electrodes=extract_clinLFP_labels(PSD_results.label); %organize electrode contacts by detph electrode
fig=[];
for i=1:length(depth_electrod... |
8c6f0de39982528ee8b222c5086b2d4229fd46f856b8467577212a1eb30b4471 | MATLAB | 3,667 | 76 | % Fit a utility logit choice model for binary risky choice data
%
% 'type' : String input indicating the model to fit. One of 'E','R','W','H'
% 'E' : Expected Utility Theory: U = p * A^alpha.
% 'R' : Classic Risk-Return Model (aka Mean-Variance Model): U = EV - b * Var.
% 'W' : Elke Weber's Coeffic... |
44b14e6ed2ea5c7ae1ad60da78bb83d42acf46d267791b7254fd53a865f62f3a | MATLAB | 3,670 | 89 | function univ_pe_1st()
cfg = load('neurovar_cfg.mat').cfg;
for i_sub = 1:44
fprintf(strcat('1st Level PEs Sub_', string(i_sub),'\n'));
pipeline_dir = fullfile(cfg.global.deriv_dir, 'univ_pe_1st',...
strcat('sub-',sprintf('%02d',i_sub)));
mkdir(pipeline_dir);
mult_cond_dir = fullfile(pip... |
d294038a96cabc14cb7d232ba385e01ef19903bc952ac44be25bd3f613403a14 | MATLAB | 3,671 | 112 | function this = cosinorActi(this)
%COSINORACTI Perform cosinor analysis on an ACTI object
% based on cosinor class methods
%
% $Author: Peng Li
% $Date: Nov 11, 2022
%
period = this.CosinorInfo.HarmonicsInHour;
minLen = this.CosinorInfo.MinimumLengthInDays;
alpha = this.CosinorInfo.CIAlpha;
epoch ... |
9cd8a2d0e3976ef65541cfc885877d708d463a87a942ca4d5b9408ddaef26bc7 | MATLAB | 3,675 | 121 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This code generates a kymograph.
%
% @v = the video
% @rect = specifies the area in the video that should be analyzed.
% @startTimeMin = the minute at which the kymograph should start. Decimals
% permitted.
% @endTimeMin = the minute at which the kymograph should end. May... |
ab40207d72ba944ddb404c6bca5a0e00e96ded53b2ef5c99ccade984336e6424 | MATLAB | 3,676 | 166 | function [mu, Kappa, pval, Rmean, delta, sigma,confDw,confUp] = CircularMean(theta,varargin)
% [theta, Kappa, pval, Rmean, delta] = CircularMean(t) ciricualr mean, dispersion
% and significance of a circular datasets
%
% INPUTS:
% t: a column vector of angles (in radians) or a n x p matrix, n: samples /
% p:variables... |
c36aa5e4e756a6d40f52ef8d2c9195e37c3240725dad8d8c48a12fbbbaa7241e | MATLAB | 3,676 | 112 | %% Bar Plot of d' and LR Bias (Pooled + JK errorbars)
data_path = 'E:\Adi\Copy_of_V4_FEF_Project\Code_Plotting\data';
functions_path = 'E:\Adi\Copy_of_V4_FEF_Project\Code_Plotting\functions';
addpath(functions_path);
addpath(data_path)
%% Initialize variables
par_all = cell(1,2);
par_all_mi = cell(1,2);
... |
c79fb5c9fbb1e68edcb93c74e7bf3e3f268ef060e49358286783613048933619 | MATLAB | 3,676 | 68 | function PlotTSMean_PreVPost_ChooseStat( TS_mean_preVpost, TS_idx, TITLE, YLABEL, YLIMS, stdOrsem, STAT )
% Michelle Cahill 20200601
%PlotTSMean_PreVPost plots the mean value of each t-series pre-stim and
% post-stim & the mean+-std or +- sem of all t-series. A paired t-test is carried
% out for identified pre/... |
243c64399ca1ef9e4f06b71bdd0fb2c8aa87ae804713d293e4aef4911d057b7e | MATLAB | 3,678 | 134 | function this = qc(this)
%QC qc an ACTI object
%
% $Author: Peng Li
% $Date: Feb 07, 2022
% $Modif.: Aug 13, 2025
% output data length in day
%
len = length(this.Data);
qcMessage = "";
% check data length
len_in_day = len * this.Epoch / 3600 / 24;
%% 1: consistant off-wrist during ni... |
ab5fe28a4b2eec06060898ee76853f97d3a6fb13c4d8a64452ecebb3ebe6f017 | MATLAB | 3,679 | 95 | function [bincountmatrix, channel_Out, xbin_ISI,keep_times]= create_conduction_time_histogram_210712( folder_name, length_rec_sec)
%Edit made to original: added output channel name
channel_Out=[];
%Creates conduction time histogram for matched units present in
%matching_table_wNMI present in folder indicated by fold... |
5f250f1d5bfdf9a4aefff5dd5c5d41bcadc8aeba78156cc47699abfdbd327d08 | MATLAB | 3,689 | 141 | %% Replicate result from Zhang et al:
%%% Zhang S, Liu Z, Grant A, Keupp J, Lenkinski RE, Vinogradov E.
%%% Balanced Steady-State Free Precession (bSSFP) from an effective field
%%% perspective: Application to the detection of chemical exchange (bSSFPX).
%%% J. Magn. Reson. 2017;275:55?67.
addpath(genpath('li... |
70f2bbda226ca926c8c8933a29e8b904b05f9ef8df83aae82cd83a483773aec1 | MATLAB | 3,702 | 77 | function [A,h] = build_A_h_2d(dphi,cert,phiGrad,transformatioinModel)
% BUILD_A_H_LINEAR2D Builds the equation system A*p = h
%
% INPUT ARGUMENTS
% dphi - Phase-difference
% cert - Certainty
% phiGrad - Phase gradient
% transformationModel - Transformation model (transl... |
176a7091eb330443a9da153a62fdab54c5bf9e2d0bfcd1ae080e93462c47690c | MATLAB | 3,705 | 99 | function Image5and6_SingleCellsWithFlow_and_WithFlowColoredByDirection(imageExportFolder, fileParams, flowFigureImageParams, numA, imageAshow, vxMatShowA, vyMatShowA, relMatShowA, numMicrons, imageNumber)
%% Import parameters
% File Params
pxPerMicron = fileParams.pxPerMicron;
% Flow Figure Params
frameNum = flowFigu... |
25808c2ad0367bf2e081e6c23b57eb67ecbb90c0926249fb8c54b1a3362a1f22 | MATLAB | 3,707 | 128 | function [omega, tbl, pVals] = calOmegaSquare(response,labels,labelNames, varargin)
p = inputParser;
defaultPartial = false;
addOptional(p,'partial',defaultPartial,@islogical);
defaultSstype = 2;
addOptional(p,'sstype',defaultSstype,@isnumeric);
defaultIncludeTime = true;
addOptional(p,'includeTime',defaultIncludeT... |
9473230cd132405e1e199874204b0c85cdc4eb30f663c7a2d372659260c297ee | MATLAB | 3,708 | 124 | function [perfmet] = perfmet_maxclass(acts,targs,scratchpad,varargin)
% This is the most basic performance metric.
%
% [PERFMET] = PERFMET_MAXCLASS(ACTS,TARGS,SCRATCHPAD,...)
%
% The classifier is considered to guess correctly if its maximally
% active row (the unit that it guessed) corresponds to the most active
% ro... |
21edf6aff0145a15648fbc4f727806b319a8da5698f88ca959882801e5442a0f | MATLAB | 3,715 | 86 | % function p = stats_permutation(n_correct,reference,tail)
%
% Function to calculate p-value for a permutation test.
% The permutation sample needs to have been calculated already, e.g. using
% make_design_permutation.m
% The minimal p-value provided by this function is 1/(n+1) where n is the
% number of existin... |
173074ad1a2529def2dd55b792f4145bdad7c1ffd7cb931251b3d9eef75a212a | MATLAB | 3,720 | 124 | function chk = testfun(fnh)
% Test function for NATSORT, NATSORTFILES, and NATSORTROWS. Do not call!
%
% (c) 2012-2022 Stephen Cobeldick
%
% See also NATSORT_TEST NATSORTFILES_TEST NATSORTROWS_TEST
chk = @nestfun;
wrn = warning('off','SC:natsort:rgx:SanityCheck');
itr = 0;
cnt = 0;
if feature('hotlinks')
... |
54fce581c255f5271a3aa9d2b325283fed58c2e53eed0cddb3cb761d4f24dd47 | MATLAB | 3,722 | 115 | %DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by sampling X at equal intervals and then
% generating target data by computing SIN(2*PI*X) and adding Gaussian
% noise. A 2-layer ne... |
4c80fce35f8b24e812b251aff71ca74638e20d224c2a724bc2aa73413a8cbf0f | MATLAB | 3,726 | 104 | function ttest_to_bar_210226(table1,table2,ttable)
% Assumes tables 1 and 2 are already organized
% IMPORTANT NOTE: UP AND DOWN REGULATION WERE SWITCHED DURING CREATION,
% NAMES IN SAVED PICTURES SWITCHED BUT VARIABLES HAVE NOT BEEN
if all(~ismember({'Electrode Pairs','Spike Area','Conduction Time','Unit Pairs','Direc... |
1cdcb0d201706a9e75409d470c383728513f569d42be0ab9011af7b9b2893947 | MATLAB | 3,729 | 114 | function yOCT2Dicom (data, filepath, dimensions, c)
%This function saves a grayscale version of data to a Dicom stack file.
%Dimensions are (z,x) and each frame is y
%INPUTS
% data - scan data (dimensions are (z,x,y)
% filpath - filepath of output Dicom file (including 'name.dcm')
% dimensions - describing the in... |
1c05efaedc1b28def1246414846b3285b01328077bae6ca52430e4ac6b66d77d | MATLAB | 3,733 | 112 | function RasterPlot(S, varargin)
% RasterPlot(S, height, bar, tstart, tend)
%
% Plot spike trains as rasters.
% INPUT:
% S: tsdArray of ts objects, spike trains
% OPTIONS:
% Height: the height allocated to each cell (includes spacing), default 1
% BarFraction: the fraction of height occupied by a cell, default 0.8
% ... |
4f93af2ff86d999279ea073dc512f6f89e49827b97b3130dc1eabe8e67491b57 | MATLAB | 3,738 | 128 | function [r_CI, m_CI, k_CI] = ME_vMMM_CI(y, r_est, m_est, k_est, m, alpha)
% _
% Confidence Intervals for a von Mises Mixture Model using Wilks's Theorem
% FORMAT [r_CI, m_CI, k_CI] = ME_vMMM_CI(y, r_est, m_est, k_est, m, alpha)
%
% y - an N x 1 vector of angles (domain: -pi <= y_i <= +pi)
% r_est - a 1 x... |
80ac8ff91921e6e9a69a2f9d8e52b986b788050834c7eb89f9b65b5749c6750a | MATLAB | 3,740 | 126 | %
Resps = [];
Typs = [];
for i = 1:7
for j = 1:5
ids = gtyp == i & gsiz == 1 & gfrq == j;
if j == 1
ncel = sum(ids);
cresp = nan(ncel, 5);
end
cresp(:, j) = y(ids);
end
Resps = [Resps; cresp];
Typs = [Typs; i*ones(ncel, 1)];
end
ke... |
1c32fe1f5a297da37cc8ba0feeca9ce599d483433e0c757271230c5a5f7caab5 | MATLAB | 3,741 | 126 | %% Wave Clus Output Plotting
% load both the raw data and times files manually
%this is for wells
%clc
%close all
%% loading
current_program=dbstack();
current_program=current_program.name;
% load spike dyn from folder above current in dir
spike_dyn_path=fullfile('..\','well_spike_dynamics_table*.mat');
dir_spike_dyn=... |
18a685157fca1e82445a2a3de852ef9a875be470b8fb281e69460c9240441700 | MATLAB | 3,742 | 112 | %ACTIGRAPHY2
%
% Descriptions tba
%
% $Author: Peng Li, Ph.D.
% $Date: Jan 01, 2022
%
% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
% (C) Peng Li 2019 -
% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
%
classdef actigraphy2 < handle
... |
25debdf4fd2ed52329124b503fc91c6d8ff19c4a0125930f0eac836efc868ac5 | MATLAB | 3,744 | 103 | function model = pp_realign(sub_id, p)
% function model = pp_realign(sub_id, p)
%
% Runs SPM realignment (i.e. head motion correction) on unprocessed fMRI
% images.
%
% Input:
% - sub_id: ID of the current subject.
% - p: Structure with analysis parameters.
%
% Output:
% - model: Structure with all SPM settings ... |
59ce94a91ee88901121beb517a9ea7e5da9c90242362de680bc09c7b1ac32a13 | MATLAB | 3,745 | 132 | rng(42)
tol = 10e-10;
nsamples = 100;
nfeatures = 10;
nclasses = 2;
prop = [];
scale = 1;
do_plot = 0;
[X, clabel] = simulate_gaussian_data(nsamples, nfeatures, nclasses, prop, scale, do_plot);
%% BINOMIAL: accuracy = 0.5 should give p=0.5 when N uneven
cfg = [];
cfg.test = 'binomial';
% create fake result
resul... |
e95e909a00bd7c2f89e1f2c5fc92206e137162490fcdc6041e25c7937cc6b5a2 | MATLAB | 3,751 | 133 | function fig = plot_transients_fragments(step1, step2, Eventname)
i1 = step2.(Eventname).i1;
i2 = step2.(Eventname).i2;
D = step2.(Eventname).D;
x = step2.(Eventname).x;
zscored = step2.(Eventname).transients_PETA.zscored_matrix;
baseline_period_start_msec = step2.(Eventname).baseline_period_start_msec;
baseline_perio... |
ca36881c0a62d693824b79d1a17244c91bf062023610fc32e6c8030c4a4c4e5e | MATLAB | 3,756 | 110 | function [OCTSystem, OCTSystemManufacturer] = yOCTLoadInterfFromFile_WhatOCTSystemIsIt(inputDataFolder)
%This function goes to inputDataFolder and figures out which OCT system is
%it (from the OCT systems that are supported by this code package)
%% Input checks
%Modify for compatability, this function works even ... |
c7158ebaf4eea4fbcfbcb8460a4eb19b7a676997532fe54522739194247a2550 | MATLAB | 3,758 | 113 | function [interferogram, apodization,prof] = yOCTLoadInterfFromFile_WasatchData(varargin)
%Interface implementation of yOCTLoadInterfFromFile. See help yOCTLoadInterfFromFile
% OUTPUTS:
% - interferogram - interferogram data, apodization corrected.
% Dimensions order (lambda,x,y,AScanAvg,BScanAvg).
% ... |
002a676e246d2beabc44d74e4ed5bd319cd41ef0c0d4b0ca92ab40444070ec1d | MATLAB | 3,759 | 131 | function [dimensions] = yOCTLoadInterfFromFile_WasatchHeader(inputDataFolder)
%This function loads dimensions structure from xml header
% INPUTS:
% - inputDataFolder - OCT folder with header.xml file
%% Figure Out basic Parameters
if (awsIsAWSPath(inputDataFolder))
%Load Data from AWS
awsSetCredentia... |
0081446e1ad8fb8b19b444c6a509f316b5d9e0dd2d12baf44f5368cdc6b3f4e8 | MATLAB | 3,763 | 85 | function [ks_stats_D, surr_a_est] = computeKSStatSurrogateData(a_hat, x_min, x_max_val, n_total, n_tail, emp_bins, num_surr)
% generate surrogate datasets and measure the KS statistic between model
% and surrogate dataset
% ks_stats_D: over power law only (eqn 3.9)
% ks_stats_Surr: over entire region
% tail_bins are t... |
68610b9db528206243f9bac872a8000772b978346a7bf2296694fa5909edfd25 | MATLAB | 3,764 | 123 | %$Release 4.0
% Copyright (c) 2005, Massachusetts General Hospital
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without modification,
% are permitted provided that the following conditions are met:
%
% Redistributions of source code must retain the above copyright notice, thi... |
ae5d98dea8f0b149ea44f2cbb6afb339bd560a468efc02651590331ae1ce526d | MATLAB | 3,768 | 74 | %This function creates simulated 40Hz flicker data based on the SPEP
%response and the superposition hypothesis.
%NEED TO ADJUST DATA VARIABLE SO THAT ITS FIELDS MATCH THE KINDS OF FIELDS
%WE GET FOR FLICKER FIELDTRIP DATA.
%2024/02/25
function superposition_modeling_data(fnames)
%fetch data:
load(fnames.... |
145ae3f0c1af0dba9f2da138c3630f17abfc505835063d40e69886c8cfac2042 | MATLAB | 3,769 | 68 | function plot_heat_maps(Dataset,geno_names,rec_type,events_names,events_plot)
Xnew = -(40*10):1:(60*10);
for gg=1:1:length(geno_names) %loop on genotypes
for rr=1:1:length(rec_type) %loop on eat or run sessions
figure('Name',[geno_names{gg},': Rep. trials ',rec_type{rr}])
%align trials to door open... |
2d3010f4254adeb9aff77387eee572cf2fdaa1f5f590b0be317da573a92a7eb9 | MATLAB | 3,771 | 129 | %% Recalculate the repeat reliability and the shuffle value
Diameter = 150;
dids = find(ismember(ROITable(:, 8), Diameter));
ndids = length(dids);
nFz = size(DMat, 2);
Quals = nan(ndids, nFz);
rQuals = nan(ndids, nFz);
Qualtyp = nan(ndids, 1);
mPhis = nan(ndids, nFz);
stda = std(DMat(:));
rng('shuffle');
for... |
1c470744146af23f1848dbd24be758717d6123df6b098ab1bb418d68a0443694 | MATLAB | 3,772 | 121 | function [fh, rasterAx, histAx, matVal] = ImagePETH(S, center, TStart, TEnd, varargin)
% Displays a PETH/raster plot-like for continuous data.
%
% USAGE:
% [fh, rasterAx, histAx] = RasterPETH_c(S, center, TStart, TEnd, 'ParameterName','Value')
%
% RasterPETH_c creates a raster plot, triggered on different... |
617e8549d75de010ef6c850a23394f323d2e03b2a7b88ffa5faf0816e9c23047 | MATLAB | 3,773 | 98 | % About
%
% Descriptions tba
%
% $Author: Peng Li, Ph.D.
% $Date: May 16, 2018
% $Modif.: Nov 15, 2022
% Oct 15, 2025
% simply and adjust layout
%
% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
% (C) Peng Li 2016 -
% +++... |
ffd8357e9306289eef35324b5690a990b8d73af8b78b428559e1b4243f8a2e14 | MATLAB | 3,779 | 161 | function [errmsgs warnmsgs] = unit_statmap_xcorr(varargin)
% [ERRMSGS WARNMSGS] = UNIT_STATMAP_XCORR(type)
%
% This is a script that tests the cross correlation statmap.
%
% INPUT ARGUMENTS:
%
% STDOUT (optional, default = true) If true, prints errors and
% warnings to screen as they occur.
%
% OUTPUT ARGUMENTS:
%
%... |
310274208e68f9aab87a3b49ca6c183df77631cdd4ab31b5c579436270babec7 | MATLAB | 3,780 | 90 | function ms = msGenerateVideoObj(dirName, filePrefix)
%MSGENERATEMS Summary of this function goes here
% Detailed explanation goes here
MAXFRAMESPERFILE = 1000; %This is set in the miniscope control software
% find avi and dat files
aviFiles = dir([dirName filesep '*.avi']);
datFiles = dir([dirN... |
80c664c8b102a1cb0b86fea0e68b5727c00978e0deed4c058abef44e1567a485 | MATLAB | 3,780 | 45 | matlabbatch{1}.spm.tools.beamforming.data.dir = {'D:\home\Data\4AshO\Phantom_Images'};
matlabbatch{1}.spm.tools.beamforming.data.D = {'D:\home\Data\4AshO\ROI_sim.mat'};
% 'efROI_tsss_sphere_einner_rsss_spmeeg_uespmeeg_phantom090715_BrainampDBS_20150709_11.mat']};
matlabbatch{1}.spm.tools.beamforming.data.val = 1;
ma... |
31374acd1f6fd926be25c2545dc5adae95ec99941365114e5e8ba6b0a2bc920f | MATLAB | 3,784 | 146 |
clear
[task_info,supPath,~,task_DB_path] = loadDBAndSpecifyDataPaths('Vermis');
EPOCH = 'targetMovementOnset';
DIRECIONS = 0:45:315;
PROBABILITIES = [25,75];
PLOT_CELL = false;
TASK = "saccade";
req_params = reqParamsEffectSize(TASK);
%req_params.cell_type = {'BG msn'};
lines = findLinesInDB (task_info, req_params);... |
ce93d44cd7ac8f87494bf2638db788a2a4e2901ba4227ba9cd0001ccb0b81b04 | MATLAB | 3,785 | 83 | % This script is a template that can be used for a decoding analysis on
% brain image data. It is for people who have betas available from an
% SPM.mat and want to automatically extract the relevant images used for
% classification, as well as corresponding labels and decoding chunk numbers
% (e.g. run numbers). ... |
308d2b9cb65551e2b844f49f3b2639ff5129337a3b32d6ec1bf30e799ed4c4bd | MATLAB | 3,789 | 130 | function DisplayVisualization(Y, C, marker_size, class_names, font_size, fig_width,augmented, show_legend)
% Display 2-D scatter-plot
%
% DisplayVisualization(Y, C)
% DisplayVisualization(Y, C, marker_size)
% DisplayVisualization(Y, C, marker_size, class_names, font_size)
% DisplayVisualization(Y, C, mark... |
34731c28bb8d1546e0c1db17ba4b855f768b10d6be37c328e5abb7b57344a21c | MATLAB | 3,791 | 89 | function [BEH] = getBehavior_eegCAT(dir,fin,model)
%% Read Behavioral data
filename = fullfile(dir.dir, strcat('BEHdata-',fin, '.mat'));
fprintf(' Load File: %s\n', filename);
load(filename,'BEHdata');
filename2 = fullfile(dir.dir_fits ,strcat('sim-', model, '-',fin, '.mat'));
fprintf(' Load File: %s\n', filename... |
e174aeea328dab8888b417bf128ae305672deaf6617553e4041677685733f7ac | MATLAB | 3,794 | 143 | function barerr(x, y, e, varargin)
% BARERR - Bar graph with error bars and significance marks.
%
% Usage:
%
% barerr(x, y, e, ...)
% barerr(x, y, e, 'p_vals', p, ...)
%
% BARERR will plot a bar graph with error bars and (optionally)
% significance asterisks indicating that a given bar is
% statistically significan... |
6fc5e4803425e549580955cb6aa584e41e059f50c357f177debb9cc5f67e0570 | MATLAB | 3,796 | 84 | %% Extract frequency information
% Perform time frequency calculation
% Check if variable Exclusion_Info exists already. If yes, load it.
if exist([output_dir output_specific 'Exclusion_Info.mat']) == 2
load([output_dir output_specific 'Exclusion_Info'],'Exclusion_Info');
end
for s=1:length(subject_list... |
336045aa2a24c75112dfb3d84d94ad547886c4771d3d53289e4e8f48f0592072 | MATLAB | 3,800 | 92 | function output=process_MF_data(tracedata,filter_parameter)
minPhot=filter_parameter.minPhot;
maxPhot=filter_parameter.maxPhot;
minStepSize=filter_parameter.minStepSize;
photsmW=9;
resulttable=[];SBR=[];accepted=0;rejected=0; %initialize arrays and counters
for m=1:length(tracedata)
%calculate SCE and fi... |
f4871dcd3118202d24cd6161c441c004cf61ee9af70619320bb681d78e355e12 | MATLAB | 3,800 | 115 | function [subj] = average_object(subj,objtype,objname,labels_name,varargin)
% Averages together all the sets of TRs with the same LABELS identifier
%
% [SUBJ] = AVERAGE_OBJECT(SUBJ,OBJTYPE,OBJNAME,LABELS_NAME,...)
%
% See https://compmem.princeton.edu/mvpa_docs/TutorialAvg
%
% Adds the following objects:
% -... |
a9a4af57971fec67847b5514f327a26d7c095234e3d7eeaf0ba95c885ddcab30 | MATLAB | 3,808 | 112 | function test_suite = test_parse_filename %#ok<*STOUT>
try % assignment of 'localfunctions' is necessary in Matlab >= 2016
test_functions = localfunctions(); %#ok<*NASGU>
catch % no problem; early Matlab versions can use initTestSuite fine
end
initTestSuite;
end
function test_parse_filename_warnings()
s... |
0b13a27b4a0323ba3538e70ff2fa0c34351eb38ef5c9012ad4e185902f14f404 | MATLAB | 3,814 | 98 | function this = addSingleGap(this, actigraphy, singleGap)
% ADDSINGLEGAP Adds a new gap to ACTIGRAPHY and return the updated .Gap
% property
%
% $Author: Peng Li
% $Date: Feb 19, 2026
% $Modif.: Feb 20, 2026
% Add internal verification of SINGLEGAP validity
% Mar 10, 2026
% ... |
641d572652b4481b955ca42767579b2202b4f70707fa826d9def7aba2d4d7703 | MATLAB | 3,817 | 109 | function [L,weights] = CrossValidationCrossCorrPrediction_Cells(qPre,qPost,sPost,binT,ep)
% [L,params] = CrossValidationCrossCorrPrediction_Cells(qPre,qPost,sPost,ep)
%
% computes the loglikelihood prediction of an ensemble of target spike trains given another ensemble of (predictor) spike trains
% The prediction is ... |
816de8763f480b7ec9ab7bcd79d1826de7686fc7be4e9f37bf9c61c4c6a6f90e | MATLAB | 3,819 | 126 | %% CLEAR AND INITIALIZE
clear;close all;clc;tic;
sfreq = 10;
% DEFINE INPUTS AND OUTPUTS
params.analysis_folder = 'E:\NAS_SD\SuiviClient\Triffilieff\2023\Analyses\RWD_Anna\Exp1';
results_folder = [params.analysis_folder filesep 'RESULTS'];
load([results_folder filesep 'RESULTS.mat']);
%% OVERWRITE ANALYSIS PARAMETER... |
99dc34ad00d765faf3552177579e18e59bb635167648e87a2b12b2928beb6d9e | MATLAB | 3,820 | 90 | function PlotCurrentTracks(tracks, frameNum, trackColor, lineWidth, frameFlip, varargin)
if isempty(varargin)
%% Whole Image Plotting
trackIDs = unique(tracks(tracks(:, 3) == frameNum, 4));
for trackIdx = 1:length(trackIDs)
currTrack = tracks(tracks(:, 4) == trackIDs(trackIdx), :);
currTrack... |
deb1638bbd28196bf3616f55e7124204651c228dae603da85dc9bb13270cf73a | MATLAB | 3,820 | 111 | function fw_simBEH(dir,fin,model,options)
%load behavioral data
load(fullfile(dir.dir,strcat('BEHdata-',fin,'.mat')),'BEHdata');
%load fits
load(fullfile(dir.dir_fits,strcat('fit-', model, '-', fin, '.mat')),'results');
%build parameter structure (taken from Gershman example)
% [~,~,f] = defineModel_eegCAT(model);
[... |
4c7c3636e0fcdd12b229303d48d978dfd456c67319f958d8fcc33cc830e7fac8 | MATLAB | 3,821 | 118 |
%% Add path
addpath(genpath('../../Ionnic Channel'),genpath('../../Tools'), genpath('../../Synapses'), genpath('../../Datas'));
%% Import data from neuron (FS)
dt = 2^-5;
Vmem = -30:dt:60;
l_V = length(Vmem);
Invtaum_simp = @(v) cosh(1.32+0.04105*v)/(0.08938 + 0.0289*cos... |
5abb62add1a5250ec3cccb558f08746134f8f401765a75235cdefe5e93a64327 | MATLAB | 3,822 | 185 | function [S0, F] = SIMLR_Large_Scale(X, c, k, ifimpute,normalize)
%%%
if nargin==2
k=10;
ifimpute = 0;
normalize = 0;
end
if nargin==3
ifimpute = 0;
normalize = 0;
end
if nargin==4
normalize = 0;
end
if ifimpute
X = X';
[I,J] = find(X==0);
Xmean = mean(X);
X(sub2ind(size(X),... |
bd463f77e806ce7b938b2b74eb16505f6a5ae66d4e45eb81b8121d94121e474a | MATLAB | 3,822 | 114 | function [pparam, X, clabel] = mv_preprocess_average_samples(pparam, X, clabel)
% Splits samples of the same class into groups and then replaces the data by
% the averages within each group. This increases SNR and reduces the sample
% size. This approach has been explored by Cichy and Pantazis (2017).
%
% Note: this a... |
8b2be41e09293a64877df9f01b8efa57688879a451b06d5e2650e27a2d1f631e | MATLAB | 3,828 | 86 | %Segments and preprocessed LFP from spep task.
%2024/02/25
function spep_preproc(fnames)
%load data:
load(fnames.trials_filename);
%organize trial data into fieldtrip format:
analysis_trials=[trials.clinrecording.trials_timestamps(1,1) trials.clinrecording.trials_timestamps(end,end)];
analysis_tri... |
3d1747b7c3e076ee4908c5991ce13c4ba5d5f05c3d3a2ade11f765e1394f7104 | MATLAB | 3,829 | 102 | function out=pkfnd(im,th,sz)
% finds local maxima in an image to pixel level accuracy.
% this provides a rough guess of particle
% centers to be used by cntrd.m. Inspired by the lmx subroutine of Grier
% and Crocker's feature.pro
% INPUTS:
% im: image to process, particle should be bright spots on dark backgroun... |
1685fa3f4f4ac72ba429af51f0ada7c981943e276c454483ddc6b048c51b02da | MATLAB | 3,830 | 110 | function [] = mom_write_minc1_matlab(hdr,vol)
% Write a MINC1 file in Octave
% To learn more about the MINC format :
% http://en.wikibooks.org/wiki/MINC
%
% SYNTAX:
% [] = MOM_WRITE_MINC1_MATLAB(HDR,VOL)
%
% INPUTS:
% HDR (structure) The header of a MINC1 file (see MINC_READ)
% HDR.FILE_NAME is the name of th... |
702b8c85915769d5e4a98df80d55512265be6e8b2ec97b264680d06a793a0851 | MATLAB | 3,832 | 62 | %Performs analysis on the persistence of oscillatory activity following offset of flicker stimulus.
%Requirements:
%MATLAB version 2021b or later because of the pyrunfile function.
%Python. To make sure have proper python version/environment, type in: pyversion(<path to proper python.exe file>).
%2024/02/25
function e... |
6e0f3cbb9da983d3ccdcefb63076addd896cbcbc9fcce36c9bb43f1994f2e68a | MATLAB | 3,838 | 45 | %-----------------------------------------------------------------------
% Job saved on 20-May-2023 23:13:37 by cfg_util (rev $Rev: 8183 $)
% spm SPM - SPM12 (12.6)
% cfg_basicio BasicIO - Unknown
%-----------------------------------------------------------------------
matlabbatch{1}.spm.tools.beamforming.data.dir = {'... |
f3232483251c103234820343cb7516432c8752469e7cc5186ce57b48cee51a58 | MATLAB | 3,841 | 163 | function [S, E, M] = findSpindles(EEG, DetectThreshold, LimitThreshold, varargin)
% [S, E, M] = findRipples(Filt_EEG, DetectThreshold, LimitThreshold, varargin)
%
% INPUTS:
% Filt_EEG: EEG tsd
% DetectThreshold: Threshold for detection of ripples
% LimitThreshold: Threshold for finding the ripple boundaries
%
% PAR... |
3ae8660c44a93f1ab7c44538c2aad40badcdc4caaaf4ddd2fe847d6fdd17306b | MATLAB | 3,843 | 102 | function out=pkfnd2(im,binaryImage,sz)
% finds local maxima in an image to pixel level accuracy.
% this provides a rough guess of particle
% centers to be used by cntrd.m. Inspired by the lmx subroutine of Grier
% and Crocker's feature.pro
% INPUTS:
% im: image to process, particle should be bright spots on dark... |
3c31d501feb5247bb52d0384435a8a6ed545955d8d33aff05695ceecffa29210 | MATLAB | 3,844 | 124 | % cd sst
% A=dir('*.jpg'); % or '*.jpg' or ...
% for n=1:length(A)
% M{n,1}=imread(A(n).name);
% end
% %
% % for i=1:length(A);
% % CB_image_names=[CB_image_names; A(i).name];
% % end
% SST_image_names=[];
% for i=1:length(A);
% SST_image_names=[SST_image_names; A(i).name];
% end
%
% % % % batchMaps=batchSali... |
62fbd8cb2f0b669f5f1776cb2dab36ec201d15c0acc9575c92775a40c9ed2fc1 | MATLAB | 3,844 | 110 | %% CLEAR AND INITIALIZE
clear;close all;clc;tic;
%% DEFINE THE STRUCTURE THAT WILL HOLD ALL THE PARAMETERS
params = [];
%% DEFINE INPUTS AND OUTPUTS
%% DEFINE INPUTS AND OUTPUTS
params.data_folder = 'E:\NAS_SD\SuiviClient\Triffilieff\2023\Data\RWD_Enrica\cohort1';
params.analysis_folder = 'E:\NAS_SD\SuiviClient\Triff... |
717e7c7a7ed883de84247f80b61359654c966e2d0c0fca8ed179911205147f2a | MATLAB | 3,850 | 98 | % This script performs multi-class searchlight decoding for the Haxby 2001
% dataset.
%
% The data is available free at http://dev.pymvpa.org/datadb/haxby2001.html
% and can be downloaded there. Accept their Terms of Use if you like to use
% the dataset.
%
% This script hase been created by just filling out the... |
fb42055992493a1990cc84bffcd308d543c32a7761fad0b42e7da7a257c793b5 | MATLAB | 3,853 | 137 | function [errmsgs warnmsgs] = unit_traintest_corr()
% [ERRMSGS WARNMSGS] = UNIT_TRAINTEST_CORR()
%
% Tests that TRAIN/TEST_CORR are working correctly.
%
% Why doesn't this use GENERIC_UNIT_CLASSIFIER???
%
% ERRMSGS = cell array holding the error strings
% describing any tests that failed. If this is empty,
% that's a ... |
b1a64ad7bc83314e499a194ba47064e412814573b7317c983d5d65c9bd4d9644 | MATLAB | 3,854 | 121 | function [fh, rasterAx, histAx] = RasterPETH(S, center, TStart, TEnd, varargin)
% Display a PETH-raster plot for discrete
%
% USAGE:
% [fh, rasterAx, histAx] = RasterPETH(S, center, TStart, TEnd, 'ParameterName','Value')
%
% RasterPETH creates a raster plot, triggered on different event times.
%
% IN... |
b4ab918fa16dd35b64bf6a915decc50f7958e18a61725d288c1811e14581c113 | MATLAB | 3,854 | 138 | function newmap = bluewhitered(m)
%BLUEWHITERED Blue, white, and red color map.
% Author: Nathan Childress (From Matlab File Exchange)
%
% BLUEWHITERED(M) returns an M-by-3 matrix containing a blue to white
% to red colormap, with white corresponding to the CAXIS value closest
% to zero. This colormap ... |
949c54886897e76025217828f0f32aada15553f3d1235d8b29218ef3e3983e23 | MATLAB | 3,855 | 112 | function [displacementField, certainty] = demons2d(moving, fixed, varargin)
% DEMONS2D Estimates a displacement field using the original demons scheme
%
% [displacementField, certainty] = demons2d(moving, fixed)
%
% INPUT ARGUMENTS
% moving - Moving iamge
% fixed - Fixed image
%
% OPTIONAL INPUT ... |
3d7413a5a5abcb7148b64363cf4294a09ad62ea2cc65c0817597a83a1c945b71 | MATLAB | 3,862 | 142 | clear; clc
[task_info,supPath] = loadDBAndSpecifyDataPaths('Vermis');
warning('off')
POPULATIONS = {'BG msn|SNR','BG msn|SNR';...
'BG msn|SNR','PC ss|CRB';...
'PC ss|CRB','PC ss|CRB'};
BIN_SIZE = 100;
DIRECTIONS = 0:45:315;
PROBABILIES = [25,75];
raster_params.time_before = 199;
raster_params.time_after = 800... |
597249950c680df1be2e3e8038e0823a95305e40c10841ea7b340f7af627a4ca | MATLAB | 3,867 | 129 | function [subj] = init_object(subj,objtype,new_objname)
% Add a new empty object
%
% [SUBJ] = INIT_OBJECT(SUBJ,OBJTYPE,NEW_OBJNAME);
%
% Update the SUBJ structure by creating a new object of type OBJTYPE
% called NEW_OBJNAME
%
% Adds the following objects:
% - object
%
% This function will initialize everything to emp... |
6d3e804e29e8a20f3a1fb8dbb5fb3497cb4bcbf357e35c9c90ed41d2b19b53ff | MATLAB | 3,867 | 95 | %
% plot raster and PSTH, grouped by multiple conditions indicated by
% different colors. Pulls together various code needed to do this with one
% simple call.
%
%
% urut/Oct'22
function [axRaster,axPSTH]=plotSpikeRaster_multiple_simplified( plotMode, offsets, limitRange_forRaster, limitRange_forPSTH, markerPos, times... |
e5f6091304956223c2e129d1cc2307e16508ead301dd6096615a02564cbf5f54 | MATLAB | 3,867 | 120 | function trial_type_list = list_all_trial_types(varargin)
%
% List all the trial_types in all the events.tsv files for a task.
%
% USAGE::
%
% trial_type_list = bids.internal.list_all_trial_types(BIDS, , ...
% task, ...
% ... |
4dda725cde8515a6a9f6d86df197c8ce04c756bc96bd4c3a3ed9ef6de07aacfe | MATLAB | 3,870 | 125 | % goal of this script is to run a boostrapping to estimate how much the
% variation of each block related to the total
% following by run @Response_BCPlexusComparison & @IdentifiedBCComparison
%%
[~, g] = max(SliceResp_type == BCTypes, [], 2);
%% Test Temporal distribution
nIter = 2000;
y = SimpleTemporalRio;
... |
cf9455c97e2d1f330f71a11d303786b57a5902af74ddb1500c23101d5092907f | MATLAB | 3,874 | 118 | %%
addpath('\\storage1.ris.wustl.edu\kerschensteinerd\Active\Emily\BasicFunctions');
nIter = 5000;
%%
IsEncodingSpace = 1;
if IsEncodingSpace
cResp = Y(:, 1:3);
else % []
cResp = Dfull([(1:nBC)'; remids(:)+nBC], :);
end
TypeDiff_val = nan(nType, nType);
TypeDiff_p = nan(nType, nType);
rng('shuffle... |
778f3f9aec22a7b512f8b8fe9b2257596d64ff5ccce283c90f4715bc7aaf5b94 | MATLAB | 3,880 | 73 | % Extract single HRF from dcNew variable, the output of GLM fitting function
% save to mat file.
% For experiment 08 and 10
function createSingleTrialHRF_SSBeta(sbjNum,respData,numClasses)
%saveDir = ['C:\Users\mn0mn\Documents\ResearchProjects\spatailAttentionProject\ProcessedDatafNIRS\Experiment' num2str(sbjNum)];
pr... |
794709b7262e46e684f64db1001fa3c201bc3db9e678b8828b343f95c2dbd572 | MATLAB | 3,883 | 107 | function spfOut = spfRealignToStack(varargin)
% This function takes a Single Plane Fit (spf) and realign it as best as it
% can to the stack average parameters: normal, and single pixel size.
% At the output of the process, spfOut will have the same normal as the
% stack and same pixel size.
%
% USAGE (1): Use on... |
f635ae67ba0d0b9b37fd6e083c124bd973d1add9eae32fa2095400f8360a12c0 | MATLAB | 3,883 | 60 | function [ interpulse_duration_ms, num_pulses, pulseduration_ms, uncaging_start_ms, uncaging_end_ms, uncaging_duration_ms, uncaging_frame_start, uncaging_frame_end, max_voltage ] = square_pulse_detection( r, frameRate )
%square_pulse_detection detects square pulses from a voltage recording
%(column 1: time points, co... |
b2861ab0ef4a30780a2a17e7170bd67e988aa2d9ed5f80e27f557a6e76019e44 | MATLAB | 3,886 | 118 | % This script is a demo showing some simple decoding on simulated toy data.
% The toy data are simple matlab matrices and no "real" fMRI or EEG data.
clear all
dbstop if error % if something goes wrong
fpath = fileparts(fileparts(mfilename('fullpath')));
addpath(fpath)
% initialize TDT & cfg
cfg = decoding... |
3b9d8aea6dc5d1aedcdd2e886afe24e497ad24f72e881f677892b737309d7f65 | MATLAB | 3,896 | 93 | % redefine stimulus classes into 6 diff. classes
% to be runned after generating stimuli marks from aux data in Homer3 GUI
% Combined multiple snirf files into one.
% strictly for ExperimentXXGUI folder
function redefineStimulusClassesCombined(sbjNum,rawDataFN,respData)
dir = ['C:\Users\mn0mn\Documents\ResearchProjec... |
526fa83325dc55eb2250eafc6041edc5a1c455508794feef5bee4ffe272e5e9a | MATLAB | 3,898 | 149 | %% CLEAR AND INITIALIZE
clear;close all;clc;tic;
%% DEFINE THE STRUCTURE THAT WILL HOLD ALL THE PARAMETERS
params = [];
%% DEFINE INPUTS AND OUTPUTS
params.data_folder = 'F:\Data Anna FR1 Doric old\2022-95_Pavlovien_DATA';
params.analysis_folder = 'F:\Analysis Anna FR1 Doric old\2022-95_Pavlovien_DATA';
params.figure... |
a11f456ac7f47720c9d77863c63abedc870820703dee85ec55947b9477e8f3bb | MATLAB | 3,899 | 80 | % ----------------------------------------------------------------------- %
% M U L T I P L E T E S T I N G %
% ----------------------------------------------------------------------- %
% Function 'fwer_holmbonf' computes the Holn-Bonferroni correction, also %
% known as s... |
9e5addb0495a10de910d5d1282494a5d363e09718798d1e708476d2a1bc96834 | MATLAB | 3,906 | 122 | function [subj] = load_afni_mask(subj,new_maskname,filename,varargin)
% Loads an AFNI dataset into the subj structure as a mask
%
% [SUBJ] = LOAD_AFNI_MASK(SUBJ,NEW_MASKNAME,FILENAME,...)
%
% Adds the following objects:
% - mask object called NEW_MASKNAME
%
% SUB_BRIK (optional, default = []). By default, you'll get
%... |
38a23a0c06663a5970463d8b1daa54dd8d50d16969df5019e54b1da7b2f1358d | MATLAB | 3,907 | 142 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Supp Fig9 CFstimulation"
% 3. Using ctrl+enter within each function to run each section
%% Section 1: open files
% ctrl+enter to run this section
clear
co=lines;
co(6,:)=[.5 .5 .5];
cnum=[6 2 4 5];
legendlist=[];
colorlist=[... |
1788a00ed2f6ea3c35dfc2e001d2d42addd6c24dcb96d59e86b34206eb8ed234 | MATLAB | 3,909 | 131 | function [fHandle, subplots, offsets,xlims] = plotInputsData(conds, times, ...
head, target, ipsiEye, ipsiPC, sines, light, labels, plotMeans, subplots)
d_offset = 4; % spacing between subplots
extra_offset = zeros(1,25);
extra_offset([6:13]) = 10;
extra_offset([5 8 11]) = 30;
extra_offset(14) = 40;
extra_offset([... |
5c208c661f728b175225b6f5a36ffa36fa5faaaedcff4074bab404f4c3d0de43 | MATLAB | 3,909 | 126 | function [subj betas X] = detrend_pattern(subj, patname, selname, varargin)
% DETREND_PATTERN - Remove trends from a given pattern over runs.
%
% Usage:
%
% [SUBJ BETAS X] = DETREND_PATTERN(SUBJ, PATNAME, RUNSNAME, ...)
%
% DETREND_PATTERN removes trends from the pattern PATNAME for each
% run specified in RUNSNAME. DE... |
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