sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e833cfb631113df53a16f490a8ecd80ffb955b3049544779818b15fd8552de5e | MATLAB | 5,192 | 144 | %%
clear all
close all
run(['..' filesep 'def_local'])
addpath(path_fieldtrip)
ft_defaults
if ~exist(preproc_path, 'dir')
mkdir(preproc_path)
end
%%
manualRej = 0; % set flag to 1 in order to perform manual artefact rejection
if manualRej ~=1
fprintf('Manual artifact rejection switched off...\n ... load... |
fc927a5b53ed64f7b2fea8e1c7625b106cb59853326f940782873aa929b4f3bf | MATLAB | 5,194 | 143 | function step3bb_plot_validation_fmri_meg_combo(bids_dir, varargin)
%% Function that plots the results of the combination analysis between fMRI and MEG
% we are taking the univariate activation in V1 and FFA and use the
% time-resolved MEG data to predict these
%
% @ Lina Teichmann, 2022
%
%... |
5c5f1b34f39bacf48e6482a46350453c7c485e0d8b1cd0ddc7119e491ab8968d | MATLAB | 5,195 | 181 |
%function FM_sweep_testing()
% close all;
% Define RCX file
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\Sandbox\KP\AM_jitter_Macro.rcx';
%Load in speaker calibration file
pn = 'C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrations\';
fn = 'rig1012-CeilingB_Noise_Mar072016.cal';
fidx=1;
% [fn,... |
56fe4192a17091b5e996eab402fb8995e6062a857fb9ab7b7ef1f3896f6d2bf8 | MATLAB | 5,200 | 204 | function [rectx,recty,area,perimeter] = minboundrect(x,y,metric)
% minboundrect: Compute the minimal bounding rectangle of points in the plane
% usage: [rectx,recty,area,perimeter] = minboundrect(x,y,metric)
%
% arguments: (input)
% x,y - vectors of points, describing points in the plane as
% (x,y) pairs. x and... |
08acd30316cf012435dc676660633292a1c1b27f3e05efe2f24aedda3e8e1713 | MATLAB | 5,201 | 132 | function [db,P] = processData_paper(db,P,recompute)
if ~exist('recompute','var')
recompute = 0;
end
% clean fields in case
fnames = fieldnames(db);
db = rmfield(db,fnames(contains(fnames,'Data')));
P.bins = P.proc.window(1)+P.proc.binSize/2:P.proc.binSize:P.proc.window(2);
P.nBins... |
96aacffb024ae3c3f0f1760c62ecd9214e03205d5dffa1a61f364a2758651657 | MATLAB | 5,204 | 208 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% read in proc spreadsheet
% filename = [ DD_PROC '/MamiNum_corrected_proc.txt' ] ;
% ssheet = readtable(filename,'Delimiter','\t') ;
%
% animal_names = regexprep(ssheet.file_prefix,'... |
8211f924978a452c7a2fd8339c3f83781d0869981c0f1b3282e3e63aea67e7e5 | MATLAB | 5,205 | 197 | function [w, infos] = fista(problem, options)
% Fast iterative soft (shrinkage)-thresholding algorithm (FISTA) for LASSO problem.
%
% Inputs:
% problem function (cost/grad/hess)
% options options
% Output:
% w solution of w
% infos information
%
% This file is part of Spa... |
5d7f9eed40dc10082d25e935a0ef6421a87711c8f0adf1209b72c35b02fac60e | MATLAB | 5,209 | 207 | function concat_temperature_csv_files(file_path)
% Build cooling record
% Add temperature to each trial
% Add label (bilateral, right, left)
% Request source directory from user
if nargin == 0
file_path = uigetdir();
end
% Load files
files = dir( fullfile( file_path, '*.csv'));
T = [];
% For... |
8d54b5b6571b7735a603fc9531f017ccec4d6ad875825e11649b12f42406257d | MATLAB | 5,217 | 220 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
VIZIT = 0 %#ok<NOPTS>
%% big loop
for tDx = 1:length(THRDENS)
%%
filename = [ DD_INTERM '/con_mat_gn_repani_stack_thr' num2str(THRDENS(tDx)) '_.mat' ] ;
ll = load(filename) ;
c_aCon... |
5e326442402e0d204185b84671d048ea8a9d05da2b3dfdc1846b083df5681c8b | MATLAB | 5,218 | 118 | function compare_fasc_recruitment()
model1 = select_and_load_model();
model2 = select_and_load_model();
Q = 0:120;
[recrAbsPerAS_1, recrNormPerAS_1, numFiberPerFasc_1, ...
activeSites_1, fascicles_legend_1] = load_recr(model1, Q);
[recrAbsPerAS_2, recrNormPerAS_2, numFiberPerFasc_2, ...
activeSites_2... |
c7508c6af76181e4fd84933907f352c47dbb08024f0e32e928479af7d4c7df33 | MATLAB | 5,219 | 132 | %% %%%%%% PREAMBLE %%%%%%
clear
Target = 'LONG';
warning ('off')
if ispc
pat = 'C:\Analysis\AssemblyAnalysis\raw\';
addpath(genpath('C:\Users\ad15419\Dropbox\MATLAB\PC MATLAB Path\AssemblyCode\Eleonora\Mic\programs'))
else
path(path,'/panfs/panasas01/phph/ad15419/MATLAB')
addpath(genpath('/... |
cc657996f7cc1ebf0964b8a11227ca44911c548a7c5f39283057249bcb7ba1df | MATLAB | 5,219 | 163 | function [NextTrialID,LastTrialID,Next_trial_type] = ...
passive_trialselect_SanesLab(TRIALS,remind_row,...
trial_type_ind,LastTrialID)
%[NextTrialID,LastTrialID,Next_trial_type] =
% aversive_trialselect_SanesLab(TRIALS,remind_row,...
% trial_type_ind,LastTrialID)
%
%Custom function for SanesLab epsych
%
%S... |
62d7de14fecebca79714eab4db04e36a75e919f60d4b1f52cb147b84875069e5 | MATLAB | 5,220 | 109 | % ----------------------------------------------------------------------
% out = simPalamedes(stairParams,obsParams,simParams)
% ----------------------------------------------------------------------
%
% Purpose: Simulate (modified) Palamedes titration procedures.
% All three inputs are required to run a si... |
88903c2d48483b7624d6392f967e6e8de60228201040127549580c7d53e79caa | MATLAB | 5,233 | 110 | function [CVE, pClass1,CVEunits,pClassunits] =DecodeCVEdistance(FR,evt0,reg)
% Leave-one out cross-validation error (CVE) Decoder
%
% (c) 2014, Daniel Durstewitz, Dept. Theoretical Neuroscience, CIMH
% Mannheim/ Heidelberg University
% Edited by Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
... |
4fb2a978bf80ac638bad3861b3e0f0245978dfdcbb3942107c4608c56854af9f | MATLAB | 5,237 | 209 |
%function FM_sweep_testing()
close all;
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\KP\circuit_wav_stim_data.rcx';
% handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\KP\FM_sweep_test_manualcircuit.rcx';
%Load in speaker calibration file
% [fn,pn,fidx] = uigetfile('C:\gits\eps... |
bf5c4bc51dcc1f260a79c565d2fbffa1968d8368733de596628ac44512bae42b | MATLAB | 5,255 | 46 | function out = qtipm_mcheck(model,D0)
% function qtipm_mcheck()
%
% checks if condition (m-) is satisfied using SDP
%
% assumes model is [28,nvox]
nvox = size(model,2);
% get d and c and change units
d = arrayfun(@(i)convert_1x6_to_3x3(model(2:7,i).*1e9), 1:nvox, 'UniformOutput', false);
c = arrayfun(@(i)convert_1x21... |
37b995ca630b9dcc911121ae23aee20497999736e17797f9055f894c5860f03d | MATLAB | 5,256 | 174 | function varargout = f_change_chan_name_GUI(varargin)
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @f_change_chan_name_GUI_OpeningFcn, ...
'gui_OutputFcn', @f_change_chan_name_GU... |
b579d1654c1c2e4b30be334383ac85b3674a837aedefdbb287438d29aa8a3b8e | MATLAB | 5,259 | 96 | %% Model based on
% Model : PMSM Field Oriented Control
% Description : Set Parameters for PMSM Field Oriented Control
% File name : mcb_pmsm_foc_sensorless_f28069MLaunchPad_datascript.m
%% Gather the dataset
%data = out.simout.signals.values; put in command window, then save array
%%... |
c6a4eeaefc4393b5afd810e58f618ec0757b36fb59f7700554bf7c86fbab7008 | MATLAB | 5,294 | 147 | function [dr] = tpdriftcheck(dirname, channel, searchx, searchy, refdirname, refsearchx, refsearchy, howoften, avgframes, brightnesscorrect, roicorrect,subtractmean,brightnessartifact,writeit, doplotit)
% TPDRIFTCHECK - Checks two-photon data for drift
%
% [DR] = TPDRIFTCHECK(DIRNAME,CHANNEL,SEARCHX, SEARCHY,
% ... |
51966a9e827987bd47367eb7a0e64e9925b6d5c4e2f5e6b4a0780b36f188745e | MATLAB | 5,300 | 177 | function RUNTIME = ep_TimerFcn_RunTime_SanesLab_aversive(RUNTIME, AX)
%RUNTIME = ep_TimerFcn_RunTime_SanesLab(RUNTIME, AX)
%
%Custom function for SanesLab epsych
%
%Controls the timer box figure during runtime.Currently supports aversive
%and appetitive go-nogo GUIs (Aversive_detection_GUI.m and
%Appetitive_detecti... |
ad7e5a1a69060218eb37e894b1e728b25d537bf16b17ee514bee30a9af819778 | MATLAB | 5,303 | 158 | function [varargout] = BernoulliNoJump(s, priorpA, method, MemParam, OutPut, prior_data)
% Ideal Observer that estimates the probability (frequency) generating
% the observed outcomes.
%
% Usage:
% [MAP, ...
% m_hat, ...
% s_hat, ...
% pmY, ...
% ] = BernoulliNoJump(s, priorpA, method, MemParam, OutPut)
%
%... |
7d1a54fa6c64f23288f2da4172997fbae025dcccd0dd16e0fd87b404f96091bb | MATLAB | 5,304 | 111 | %% GMLM.computeMAPevidenceOptimization
% optimizes the log-evidence (plus log hyperprior) of the GMLM using quasi-newton optimization & Laplace approximation for the evidence
%
% inputs:
% params_init (OPTIONAL) :a param struct of the initial value of the optimization. If not given or empty, a random initiali... |
c0ea61f42efab6fed4bd267721f013f98eab4a4e375be6ac69e4b61d791b69f5 | MATLAB | 5,306 | 177 |
%%ERPbindata contains the values for each point and it should be is column
%%vector. e.g., ERPbindata = [1 2 4 5 3 2 5 6 3 2 5 6 6 ....]
%%Time indexes for each time point e.g., timesrange =
%%[-199.21875,-195.3125,-191.40625,-187.5,-183.59375,-179.6875,-175.78125,-171.875,-167.96875,....]
%%if sampling rate is 256
... |
d75d9d06abe4e793304ca9a5490b9ac40ccf014a35cfc6e77ba3f2cee031a462 | MATLAB | 5,309 | 178 |
% PURPOSE : form the time points based on the defined time range and xtick range;
%
% FORMAT :
%
% [xtick_time, bindata] = f_get_erp_xticklabel_time(ERP, timerange,xtickrange)
%
%
% INPUTS :
%ERP - ERP structures (ERPsets)
%timerange - time range where we want to display the wave e.g., [-200 800]... |
0242a630e92a5cc1d5108699f95d2b48f5e6ca5341dae24d55a58981b4bb98cc | MATLAB | 5,317 | 191 |
%function FM_sweep_testing()
% close all;
% Define RCX file
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\Sandbox\KP\AM_jitter.rcx';
%Load in speaker calibration file
pn = 'C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrations\';
fn = 'rig1012-CeilingB_Noise_Mar072016.cal';
fidx=1;
% [fn,pn,fid... |
57fca51ce514b4179c354eedffe68879a62f2eb01f226b5dd10e954b41215f67 | MATLAB | 5,323 | 133 | % ========================================================================
function [tsp,sps,Itot,Istm] = run_sim(glmprs,verbose)
% [tsp,sps,Itot,Istm] = run_sim(glmprs,verbose)
%
% Compute ongoing activity (multi-cell) coupled-glm.
%
% Uses time rescaling to sample conditionally Poisson process
% For speed, ma... |
1eff02c187d2b8984f1acc3ba31f8ead34f54a77fc3ff355d83c4d7154f5dfa4 | MATLAB | 5,331 | 161 | function oimg = readTIFstack(path)
% Copyright (c) 2012, YoonOh Tak
% 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 cop... |
a7364cdbbc74b4bddd55bbfe1f8e29571c113b280cc5744d89dc467b86acbfe9 | MATLAB | 5,339 | 114 | function [ev_half,z,p] = plotPredSingleTrial(predDat,mainFigP)
%% Plot single trials
% Parameters -- should be inputs!!
k2plt = 1;
trials2plt(1,:) = [4 5 6]; % videos
trials2plt(2,:) = [1 1 1]; % repeats
% what stimuli
idxstimsubset = [];
for idx = 1:numel(mainFigP.stimsubset)
... |
6d6a386a00d58722f337ee6378f96adda7a35e5893202856ca6ab23616da6e51 | MATLAB | 5,340 | 175 | % Function for calculating spike-triggered average. Also generates the
% plus/minus average
% Arguments:
% file_id: patient ID + recording number
% llfp_type: whitened or unwhitened
% seizure_onset, seizure_end: start and stop times of seizure within recording
% clip_length: length of STA clip to be calculated in... |
91ab3fb2f1148c3b1a1d1ea3800a315eb902953f31e34c03c55a50c81a429a55 | MATLAB | 5,352 | 210 | function [M,xp,yp,A,B,Base] = Cart2Pixel(Q,A,B)
% [M,xp,yp,A,B,Base] = Cart2Pixel(Q,A,B)
%
% Q.data should be in no_of_genes x no_of_samples format
%
% Q.Method
% n=10;
% x = randn(n,1);
% y = randn(n,1);
% Method = 1) kpca for kernel pca
% or 2) tSNE for t-Distributed Stochastic Neighbor Embedding
% or 3... |
131ff0c73529de6fb805bb95ab09fc2a2b4e692acd9a6a9514fec8269b64e522 | MATLAB | 5,353 | 139 | function segments = cross_section(V, F, z_cross, z_step, roundPrec, ...
live_plot)
% IMPORT_ENDO_GEOM Extract the list of non ordered segments obtained from
% the crosection the geometry composed by F facets and V vertices.
%
% [segments] = cross_... |
8c10a86a6a8cf70724dc79b773b006569fec9c4682fc6789c94757d73d3cee97 | MATLAB | 5,357 | 171 | % PURPOSE : subroutine for pop_export2text
%
% FORMAT :
%
% serror = mvpc2text(ERP, filename, time, timeunit, transpose,DecodingUnit,precision)
%
%
% INPUTS :
%
% MVPC - MVPCset (ERPLAB structure)
% filename - filename of outputted file
% time' - 1=include time values; 0=don't include tim... |
76829037a1146fcbdf34b719483fa5bd87ff9e5762e3845c270e1c11b3fc88fb | MATLAB | 5,359 | 103 | %% GMLM.computeMAP
% optimizes the log-posterior of the GMLM given fixed hyperparameters using quasi-newton optimization
%
% inputs:
% params_init (REQUIRED) :a param struct of the initial value of the optimization.
%
% optional key/value pairs
%
% alternating_opt (true/false; default = false... |
8a641a659a3a79ee07466f99d4d5befa98cab85f481f07d694ef65ffea07b48b | MATLAB | 5,365 | 168 | function TRIALS = TrialFcn_IncrReward_LOMBER(TRIALS)
% TRIALS = TrialFcn_IncrReward_LOMBER(TRIALS)
%
% Custom trial selection function for increasing reward size for
% consecutive hits on a 2AFC task. Misses reset the reward size to minimum
% specified amount.
%
% Strategy: Count the number of recent hits and update ... |
ec45bcbdb086ec23085dcb2f704756ab6a16e495247e12a616dc68a0f84ec88e | MATLAB | 5,365 | 186 |
%function FM_sweep_testing()
% close all;
% Define RCX file
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\Sandbox\KP\AM_jitter_Macro_DurTest.rcx';
%Load in speaker calibration file
pn = 'C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrations\';
fn = 'rig1012-CeilingB_Noise_Mar072016.cal';
fidx=1... |
5b781095809378a8fd4e3175aafe908de3ce82b6dda2a4d1cbdcf459a9ab76dd | MATLAB | 5,371 | 171 | % PURPOSE: updates ERPset menu
%
% Format
%
% updatemenuerp(ALLERP, overw)
%
% INPUT:
%
% ALLERP - structure containing multiple ERPsets
% overw - overwrite erpset menu? 0=no; 1=yes; -1=delete
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% Un... |
4f53c7391c44bb016a94414bfdf494dcea0bf2526d9a8bcd0bf701eb0c4c7c9f | MATLAB | 5,377 | 179 | %BLP_rev_Fig2_FreezingCalc
%NG...
clear all
animalN = 1; %1-8, blpgfp 1,2,3
FC = 0; % 0:Retrieval; 1:FC;
%Thres=6200000;
Thres=1.8;
%load Thres
switch animalN
case 1 %blpretroarch2
if FC == 1
cd('.\Data\blpgfp2\blpgfp2_s01_fc\video\')
folderN='blpgfp2_s01_fc';
elseif FC == 0
cd('.\Data\blpgf... |
543c4a227ece912a7dd2ba731d9dd332c9d6d82c3ec5bbdee6d9bbbab56af1af | MATLAB | 5,390 | 190 | function model = qtipm_data2fit_SDPdcmSL(model,signal,bten,varargin)
% function qtipm_data2fit_SDPdcmSL()
%
% flag is for define output size:
% flag = 1 -> m is [nvox*28,1] (default);
% flag = 0 -> m is [28,nvox]
nmeas = size(bten,1);
% retrieve optio... |
ebb0da74ee97c56f585bae0680bd97a3b48e15bc1f8ec58da81065156cc1ac57 | MATLAB | 5,390 | 148 | function step3e_validation_pairwise_decoding1854(bids_dir, toolbox_dir, participant, blocknr, n_blocks)
%% Function to run pairwise decoding analysis for the 1854 object classes
%
% @ Lina Teichmann, 2022
%
% Usage:
% step3d_validation_pairwise_decoding200(bids_dir,participant, ...)
%
% In... |
6a5f37a304da676ce1ea475ebb4e2787f422052922b795c2786f9d39641e5f89 | MATLAB | 5,393 | 133 | function [r, beta_map, predicted_labels, p] = svr_cross_predict (train_data, train_labels, test_data, test_labels, clipping)
% predict the scores using linear support vector regression
% INPUTS:
% data (#observations x #features) -- data matrix (ROI or voxelwise)
% labels -- scores to predict (i.e. values of depend... |
8bd10aaf0af8f6d0c34834dff49c622dcfd129397efa4c04d29df22dd6723df6 | MATLAB | 5,394 | 166 | function handles = updateFArate_SanesLab(handles,variables,FAind,NOGOind,f)
%handles = updateFArate_SanesLab(handles,variables,FAind,NOGOind,f)
%
%Custom function for SanesLab epsych
%
%This function calculates and displays the FA rate. FA rate can be
%calculated for individual NOGO trial types separately, or as an agg... |
6dc726c63345c1983554ddaf024ea31ffa7714d1bf7c4589a839936153c7739a | MATLAB | 5,402 | 195 | function [w, infos] = cd_lasso_elasticnet(problem, options)
% Coordinate descent algorithm for LASSO problem.
%
% Inputs:
% problem function (cost/grad/hess)
% options options
% Output:
% w solution of w
% infos information
%
% This file is part of SparseGDLibrary.
%
% Cr... |
835c443a483809cd4f1965843d82b6912f2d3462ce36f641fe29b3b8f603f426 | MATLAB | 5,421 | 145 | function [M, L, Y, C] = lmnn(X, labels)
%LMNN Learns a metric using large-margin nearest neighbor metric learning
%
% [M, L, Y, C] = lmnn(X, labels)
%
% The function uses large-margin nearest neighbor (LMNN) metric learning to
% learn a metric on the data set specified by the NxD matrix X and the
% corresponding Nx1 ... |
85bb0143f4662d9ef6abcfbceb7cab62c76a958152f7e35b219a261ef9a7fc8f | MATLAB | 5,425 | 172 | function [schedule,fail] = ep_AddTrial(schedule,varargin)
% [schedule,fail] = ep_AddTrial(schedule,varargin)
%
% INPUTS: schedule should be empty or the returned structure from a
% previous call to this function.
% varargin inputs can be specified as follows:
%
% Define stimuli to use in schedule... |
cfbaa087e890c1b3dd177834bf55e6df3979e1fe64c4a7c771505b8cca710d48 | MATLAB | 5,429 | 195 | function [w, infos] = shooting_grouplasso(problem, options)
% Shooting algorithm for Group LASSO problem.
%
% Inputs:
% problem function (cost/grad/hess)
% options options
% Output:
% w solution of w
% infos information
%
% This file is part of SparseGDLibrary.
%
% Refere... |
3931076b7b510f7b9518e9d2aa16c9a6e323de68894ac6813d27f663335d63cb | MATLAB | 5,431 | 160 | function [sacc] = detectSaccEp(EYESeSc)
%detectSacc Detects saccades based on velocity in epoched data
% Detailed explanation goes here
% EYESeSc: Offset corrected eye signal (x and y) in degress of visual angle
pxPerDeg = 27.854; % pixels per degree of visual angle at the center
Fs = 1000; % 1kHz sampling rat... |
9fb046740833c8508a814daacaad9f39ccffe7b1720e22c1179cf8cbfa0d0db4 | MATLAB | 5,436 | 177 | function RUNTIME = ep_TimerFcn_RunTime_SanesLab_v2(RUNTIME, AX)
%RUNTIME = ep_TimerFcn_RunTime_SanesLab_v2(RUNTIME, AX)
%
%Custom function for SanesLab epsych
%
%Controls the timer box figure during runtime.Currently supports aversive
%and appetitive go-nogo GUIs (Aversive_detection_GUI.m and
%Appetitive_detection_... |
0671202e4db1b31935692bdeb405d9c4eaf5b0fb3ac1f9a9c1112f4eb8c24e5d | MATLAB | 5,438 | 84 | % NEED TO CHECK IF CORRECT (MODIFIED IT FOR THIS TASK
%
% ASK ANNABELLE IF WAY WE HAVE THIS RANDOMIZATION ORGANIZED OK
%
% study_conditions = PSEUDORANDOMIZATION(conditions,repeat_limit,number_trials_per_condition)
%
% Randomizes trials in a way that does not repeat a trial of a given
% condition quality (for ex. moda... |
9ddd9437ad3ee1c054d61d814d26d965552821808ac29362ea46837cfa67b6c9 | MATLAB | 5,439 | 133 | clear all
close all
target= 'Task';
if ispc
home = 'C:\'; % [getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\Sleep'];
elseif ismac
path(path,'/Users/aleksanderdomanski/Documents/Bristol_work/assembly_analysis/MichalDataAna')
home = getenv('HOME');
cd ([home '... |
bf665daa693d1643b56c3ee92a418741d86b4cf25a195acf160b91df7479e0f0 | MATLAB | 5,445 | 287 | % two variable examples
%% RDN
Pxxy = zeros(2,2,2);
Pxxy(1,1,1) = 0.5;
Pxxy(2,2,2) = 0.5;
fprintf(1,'RDN\n')
compare(lattice2d(),Pxxy);
%% W&B FIGURE 4A
Pxxy = zeros(2,2,3);
Pxxy(1,1,1) = 1/3;
Pxxy(1,2,2) = 1/3;
Pxxy(2,1,3) = 1/3;
fprintf(1,'Williams and Beer Fig 4A\n')
compare(lattice2d(),Pxxy);
%% W&B FIGURE 4B
... |
822070addcb237b98e5786721ead355638cdf996458879471bf17a4536def3c4 | MATLAB | 5,448 | 165 | function [reg_corner,rho_c,eta_c,reg_param] = l_curve_modified(U,sm,b,method,plotCorner,L,V)
%L_CURVE Plot the L-curve and find its "corner".
%
% [reg_corner,rho,eta,reg_param] =
% l_curve(U,s,b,method)
% l_curve(U,sm,b,method) , sm = [sigma,mu]
% l_curve(U,s,b,metho... |
7c26102f77a80aedd37bd405256396583e8c3ea0dffd7cda75b0320aced9ece1 | MATLAB | 5,450 | 163 | % Quality control Q6
% Plot time series from fMRI images and head motion
% Show their correlations before and after preprocessing
% Xin Di, July 13, 2022
clear
subjfolder = dir('F:\fMRI_QC\fmri-open-qc-rest_bias_corrected\sub*');
subjfolder = subjfolder([1:89 91:end]); % subji 90 CSF mask empty
figure('position',[10... |
a5711f48e24abbf4968628f20b0153e898e99b79f582d5232b34f4329e6bd424 | MATLAB | 5,481 | 193 | function [realpos realneg]=get_cluster_permutation(data,montecarloalpha,clusteralpha,npermutation,sTime,averageelecFlag,dataPerm)
% Input
% - data: cell array (1 cell per condition: channels * times * subjects
% - montecarloalpha
% - clusteralpha
% - npermutation
% - sTime
% - averageelecFlag
Ncond=size(data,2);... |
9066d9a319a9ca2a09ba826dd853c7254c6426fedfbf79c20d17bd5abc109d2a | MATLAB | 5,499 | 166 | function EEG = ve_update(EEG)
udf=get(gcbf,'userdata');
if isfield(udf,'urdata');
EEG.data=get(findobj('tag','eegaxis','parent',gcbf), 'userdata');
end
if isfield(udf, 'eventupdate');
for i=1:length(udf.eventupdate);
if strcmp(udf.eventupdate(i).proc, 'new');
eventindex=length(EEG.event)+... |
f5812c31d9808a76422dc1e9b3de77a8b6cf9982906ff728e44e2b5cf6001aaa | MATLAB | 5,512 | 208 | function [w, infos] = admm_trace_norm(problem, options)
% The alternating direction method of multipliers (ADMM) algorithm for
% minimization problem with trace norm.
%
% Inputs:
% problem function (cost/grad/hess)
% options options
% Output:
% w solution of w
% infos inf... |
2e1c0e1555b2f98b6497ff9271b79074ca70a04148342068b19ba2cabf25d73d | MATLAB | 5,515 | 238 | function varargout = Joystick2AFC_TRAINING(varargin)
% Joystick2AFC_TRAINING
%
% Simple GUI for training Left/Right movements on a Joystick
%
% Daniel.Stolzberg@gmail.com 2016
% Last Modified by GUIDE v2.5 31-Jan-2016 22:30:20
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name'... |
408e654f12f8aa1d32fcf3f4835718c3f017404f7632076608d9ce74600666ca | MATLAB | 5,522 | 157 | % red: 165, 33, 32
clear
mainDir = fullfile('/Users/karimia/code/mvgc_grangercausality/Data/RectalDistension', 'Means');
animalDirStruct = dir(mainDir);
% remove '.' and '..' dirs
animalNames= {animalDirStruct(3:end).name}';
assert(~any(contains(animalNames,'.')));
numAnimals = length(animalNames);
% Generate voiNames... |
d1f238bb5bad68dbff83540697b6455b90123112b950c162e8c758aa8560eb32 | MATLAB | 5,525 | 164 | function [hubs,hubfrag,hubprob,hubdista,susceptind] = ...
hub_fragility_volatility(mat,distmat,hubmethod,Nreps,proprand,altdist)
% from Gollo2018, get measures of hub fagility and measure the volatility
% of the hub distance embedding
%
% INPUTS:
% mat: connectivity data
% distmat: dis... |
f0d926c9f60b943e56156907309944eaf4e320e76652126176d9e47f4a84e4be | MATLAB | 5,542 | 184 | function [u, v, convergenceLoop] = opticalFlowStep(im1, im2, ...
nanIndices, surroundLocs, alpha, beta,...
showFlag, u0, v0, im0, im3, angleFlag)
% Find the optical flow U, V between two images IM1 and IM2 from a video
% sequence.
%
% Rory Townsend, Aug 2017
% rory.townsend@sydney.edu.au
%% Fixed point iterati... |
e00e5b85c5aac2df88937c86f25b803035ffa12bdb26b93a44b2ede4b476e33e | MATLAB | 5,545 | 207 | function Investigating_model_simulation_waveforms
% Script recreates Figure 3 from the manuscript. This compares the wHVG from a
% segment of model time series obtained using each optimisation method. We note, pseduo data is
% applied for this script, and hence small devations from the data
% in the paper will be... |
e596a7e315098a4cf0064b99b1bb51e8dc2d644033f432ddd4e12d1c845eb3f3 | MATLAB | 5,545 | 99 |
function spikes = ss_default_params(Fs, varargin )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% ss_default_params - initializes a spikes object with the default
% parameters
%
% Usage:
% spikes = ss_default_params(Fs, varargin )
%
% Description:
%... |
ca2b575aa589a42506c46c87ffcecf4497b5e2f3a79d38301c83faa2f415eb88 | MATLAB | 5,549 | 207 | % PURPOSE : Clears MVPCset(s) from MVPC menu
%
% FORMAT :
%
% >> ALLMVPC = pop_deletemvpc( ALLMVPC, index);
%
% EXAMPLE :
%
% >> ALLMVPC = pop_deletbestset( ALLMVPC, [3 5]);
%
% INPUTS :
%
% ALLERP - Includes all MVPCsets in workspace
% Index - MVPCset(s) that you want to clear from the workspace
%
% OUTP... |
303dd46b38fef66b95726de6b3360dd42e873751a305cb453ba503ec20a4b17e | MATLAB | 5,559 | 117 | function FEM = mesh_FEM(model)
log = model.getLogger('mesh');
meshedPathLegacy = [get_conf().solutionsDir model.baseName '_mesh.mph'];
if isfile(meshedPathLegacy)
assert(~isfile(model.paths.mesh));
log.info('%s moved to %s...', meshedPathLegacy, model.paths.mesh);
movefile(meshedPathLegacy, model.pa... |
f0cf8e461c808044629bb7494046de506c8fc3cd714ad27383f6f8e96c4c7814 | MATLAB | 5,562 | 195 | %quick and dirty tool for plotting out HMC sample progress
% I didn't document this well, but it's not super imporant
% This prints out stuff I want for the DMC task GMLM, but not every GMLM
function [] = plotSamples(obj, samples, metrics, paramStruct, sample)
clf;
TotalSamples = size(samples.W, 2);
if(nargin < 4 || i... |
04fa30774a38c0182fb5f62ef5c21948cb9bee600e9bb63f02f8e096c1331bbf | MATLAB | 5,566 | 223 | function analyzetpstack_newautofilledstack(ds)
% ANALYZETPSTACK_NEWAUTOFILLEDSTACK - Create an autofilled analyzetpstack record
%
% ANALYZETPSTACK_NEWAUTOFILLEDSTACK(DS)
%
% This function takes as input a DIRSTRUCT object for the directory of interest,
% and prompts the user to help 'auto-fill' the stack.
%
% The u... |
0cd8a6c2b77d01340f905ac0bc2d14d4c6f309f5f474e53695a614f1e8dca3ea | MATLAB | 5,572 | 183 | function handles = updateTrialHistory_SanesLab(handles,variables,reminders,HITind,FAind,GOind)
%handles = updateTrialHistory_SanesLab(handles,variables,reminders,HITind,FAind,GOind)
%
%Custom function for SanesLab epsych
%
%This function updates the GUI Trial History Table. For each GO trial type,
%d' values are calcul... |
3eaa15beba44dd0b05d03dae8b0d7c29e5cd9f6b44166e676473a9af31e719d1 | MATLAB | 5,590 | 157 | clc; clear all; close all
subjects = [3 4 5 6 7 8 9 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33];
%subjects = [3 4 5 6 7 8 11 12 13 14 15 16 17 18 19 20 21 22 23 24 26 27 28 29 30 31 32 33];
%subjects = [3 8 11 12 13 17 19 20 22 23 24 27 30 32 33];
%subjects = [4 5 6 7 9 14 15 16 18 21 25 26 2... |
1a3b52e26e3731cbda49fd95ae2ae6943c969e000d1436ed51cfe9234a611349 | MATLAB | 5,591 | 160 | clear all;
close all;
%Prepare_Data with DeepInsight
%
%Description of Datasets
% 1. dataset1.mat is RNA-seq (1.5GB)
% 2. dataset2.mat is ringnorm-DELVE (560KB)
% 3. dataset3.mat is vowels (3.6MB)
% 4. dataset4.mat is Madelon (2.1MB)
% 5. dataset5.mat is Relathe (696KB)
%Parm.fid=fopen('Results.txt','a+');
Parm.Metho... |
86964ec302347c15482a131d9885f84aeaa4af22c6ff89f5aed11cebabb54b08 | MATLAB | 5,600 | 160 | %%
clear all
close all
run(['..' filesep 'def_local'])
addpath(path_figs)
timeCol=17;
%% Loop on subjects
subj_name=405:425;
ns=0;
for nS=1:length(subj_name)
%%% load data
behav_name=dir([behav_path filesep 'SWS_NVS_results_S' num2str(subj_name(nS)) '*.mat']);
if isempty(behav_name)
fprintf('..... |
e73281e9faae82ef9fa5e764ae3d80f17dfadaefc118cf69187e897d224eaae7 | MATLAB | 5,601 | 163 | function varargout = testFigure(varargin)
% TESTFIGURE MATLAB code for testFigure.fig
% TESTFIGURE, by itself, creates a new TESTFIGURE or raises the existing
% singleton*.
%
% H = TESTFIGURE returns the handle to a new TESTFIGURE or the handle to
% the existing singleton*.
%
% TESTFIGURE('CALL... |
96dd25b6b623cc7274eb47f693334ef48377903225ef6a8691795104702730a0 | MATLAB | 5,602 | 126 | function [quant,p,quant_sing] = plotPredResults(pred,sideTransec)
if ~exist('sideTransec','var')
sideTransec = -ones(1,numel(pred.ypred_test));
end
ypred_test = pred.ypred_test;
predP = pred.predP;
getQuant = predP.getQuant;
%%
fnames = fieldnames(ypred_test);
for... |
18c51f89095658458a42514310c97b4aeffc021ac75eac6946d5d0d277977fdd | MATLAB | 5,607 | 207 | % PURPOSE : Clears BESTset(s) for BESTset menu
%
% FORMAT :
%
% >> ALLBEST = pop_deletebestset( ALLBEST, index);
%
% EXAMPLE :
%
% >> ALLBEST = pop_deletbestset( ALLBEST, [3 5]);
%
% INPUTS :
%
% ALLERP - Includes all BESTsets in workspace
% Index - BESTset(s) that you want to clear from the workspace
%
%... |
1d28d28914f92251ae7b166fa7f72d578d1d501e21e726c832ec719eed58d216 | MATLAB | 5,616 | 174 | %% %%%%%% PREAMBLE %%%%%%
clear
TaskOnly = true;
Epochs = {'PreSleep','Task','PostSleep'};
Epoch_ = 'PreSleep';
Target = 'LONG';
warning ('off')
if ispc
pat = 'C:\Analysis\AssemblyAnalysis\raw\';
addpath(genpath('C:\Users\ad15419\Dropbox\MATLAB\PC MATLAB Path\AssemblyCode\Eleonora\Mic\programs')... |
3077e071d876ae67f333fd56ed4fae4b6c5df624b1c174a447641a7c665085a4 | MATLAB | 5,618 | 196 | function [ outStruct ] = SpherePatch( numPts, radius, varargin)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
FlipZ = false;
optargin = size(varargin,2);
if(optargin == 0)
axis = [0 0 1];
hemisphere = False;
elseif(optargin == 1)
axis = varar... |
176eb632c25f07d1de624b30a61ebbda9d7b269eef361e4c5fdf3324b5a51d0d | MATLAB | 5,634 | 142 | % Prototype function for calculating smoothed estimates of firing rate by
% optimised kernel density smoothing. Also contains a bloc of code to calculate FR for error trials.
%
% (c) 2014 Daniel Durstewitz, Bernstein Center for Computational Neuroscience, CIMH/ Heidelberg University
% Edited by Aleksander PF Domanski P... |
02eb3de28c81d08370bf7833e3eb4c74d5c9b9036fa141b528137b198d65b37b | MATLAB | 5,643 | 138 | function [sigTissue,sigCSF,Dtissue] = estSigFracLowb(sigVals,bVals,D_CSF,opt)
%
% Estimate signal fractions of CSF and tissue assuming DTI model with 2 compartments.
% i.e., free water elimination
%
% sigVals: [N_bval * Nx * Ny * Nz] matrix
% bVals: [N_bval * 1] vector. [s/mm^2]
% D_CSF: pre... |
ee6e759ee700d78adbf57af465d1c09713c798a3bcd9b553fe9c69b447ac1295 | MATLAB | 5,658 | 119 | %% GMLM.computeMLE_crossValidated
% Fits the MLE using cross validation. Cross-validation is done over trials, not individual bins.
%
% inputs:
% foldIDs (cvparition or array of length obj.dim_M) : the folds for cross validation (K folds)
% if foldIDs is a vector, specifies the test set for ... |
b73a76568bc54c59a3fdaf61913d1b48b560f20cfa787df77bbe2086a8930dde | MATLAB | 5,667 | 115 | %% GMLM.computeMAP_crossValidated
% Fits the MAP using cross validation. Cross-validation is done over trials, not individual bins.
%
% inputs:
% foldIDs (cvparition or array of length obj.dim_M) : the folds for cross validation (K folds)
% if foldIDs is a vector, specifies the test set for ... |
188d93e80bbf58ca726274678a4ad44e7e03c54e22157c98500a644f432c14c4 | MATLAB | 5,689 | 225 | % PURPOSE: pop_duplicaterp.m
% duplicate ERPset
%
% FORMAT:
% [ERP, erpcom] = pop_duplicaterp( ERP, 'ChanArray',ChanArray, 'BinArray',BinArray,...
% 'Saveas', 'off', 'History', 'gui');
% Inputs:
%
%ERP -ERP structure
%ChanArray -index(es) of channels
%BinArray -index(es) of bins
... |
6c921fda9f728064dac10a0d20d6f3abd02d2d540690a8df02bc7cec8eea3dd0 | MATLAB | 5,689 | 213 | %% DB2STA WAV
pvar = 'BuID';
subselection = [1:12];
tadjustments = [];
fullwin = [0 0.6];
clear opts
opts.clustering_exponent = -2;
opts.unoccupied_bins_strategy = -1;
opts.metric_family = 0; % 0: Dspike; 1: Dinterval
opts.parallel = 1;
opts.possible_words = 'unique';
opts.start_time = 0;
opts.end_time = 0.6;
opts.... |
704580c4fb2504c161c0239b2ad93d3d99da2e75e58a3ec96c637f9ba243a44b | MATLAB | 5,690 | 217 | %%
%
clearvars
setUpPaths
for len=1:23
processData
%% does the modelling
n_Channels_Form=6; %number of channels in the form bank (range of pi radians) - must divide 180
Sigma_Form=30; %width of the channel (standard deviation of the Gaussian function)
recoveryRatio=1.2;%1.2;
... |
d1c17554c6ea4697133de032312996d14d990ddcd1d5416959342437e3f7be08 | MATLAB | 5,697 | 231 | function step2_crossref_temp_and_behavior(rootDir)
% Add temperature to each trial
% Add label (bilateral, right, left)
% Define paths
if nargin == 0
% rootDir = Cloudstation('Vowels\Noise\Cooling\Data');
rootDir = Cloudstation('Vowels\Spatial_Unmasking\Cooling\Data');
end
behavDir = fullfile(rootDir,'GoFer... |
6c6957111d3f5e6928002f5b182697ba6f8cdcbf2d5f1742b4141e3d5ee872ef | MATLAB | 5,698 | 111 | %% GMLM.computeMLE
% optimizes the log-likelihood of the GMLM using quasi-newton optimization
%
% inputs:
% params_init (OPTIONAL) :a param struct of the initial value of the optimization. If not given or empty, a random initialization point will be generated by GMLM.getRandomParamStruct
%
% optional ke... |
2140c39da7b567000f00f19dae1e6d20652dd0d19fc9589fbf82fe78e86ec123 | MATLAB | 5,699 | 139 | function P1vsP2 = compareAssemPatterns(P1,P2,plotYN,PermittedTransitions,RankOrder)
plotVerbose = false;
if nargin <3 || isempty(plotYN);
plotYN = true;
end
if nargin < 4 || isempty(PermittedTransitions)
PermittedTransitions = 3;
end
if nargin <5 || isempty(RankOrder);
RankOrder = true;
end
%% ... |
99a079cae83495925b72df7c4cca11876271ab7204e9c862f23ec3c8ffd393ee | MATLAB | 5,707 | 195 | % Function to calculate STA using only a subset of randomly selected
% channels.
% Arguments
% tb: table that contains all the metadata on recording files
% index: row of table to run
% llfp_type: whitened or unwhitened
% n_channels_subset: n channels to randomly select to include in STA
% clip_length: length of ST... |
70e2393344ef0e496259ce6ff0a3ce670ae12fc51393ff056346f85140fdb2d2 | MATLAB | 5,713 | 167 | function EEG=marks_epochs2continuous(EEG)
evtcount=0;
if ~isempty(EEG.event); % in case there are no events
tmp.event=EEG.event;
EEG.event=tmp.event(1);
%rejints=[];
end
sampdur=(1000/EEG.srate);%duration of each sample...
relstrtt=EEG.xmin*1000;%relative (to lock event) start time of current window...
%size(EEG.dat... |
f2cdc1da8a8db4e94cdfa77160b73166a18d9613cbfe1b54315f986d389b4ad6 | MATLAB | 5,719 | 172 | function varargout = vhdr2mat(vhdrfile, vhdrpath, srange, chans, plotOK, saveOK)
% VHDR2MAT Convert BrainAmp Vis. Rec. (.vhdr) to Matlab (.mat) file format.
% VHDR2MAT(vhdrfile, vhdrpath)
%
% Optional inputs:
% vhdrfile - VHDR file name
% vhdrpath - VHDR path name
% srange - scalar first sample to re... |
128f7b2377b5966a34cceeb40ce11440389cbe2c7f800f5c2ab80107b8878afd | MATLAB | 5,740 | 116 | % 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
% ... |
692e69b0c624f13ad977bd32899afcaf895882eff176dd81a3e246f885a83b6b | MATLAB | 5,742 | 101 |
function spikes = ss_default_params(Fs, varargin )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% ss_default_params - initializes a spikes object with the default
% parameters
%
% Usage:
% spikes = ss_default_params(Fs, varargin )
%
% Description:
%... |
3e38f65e2a57c2192852dcfd8c7ffc6c17dfb5400c75f8b86431b37522ef3a8d | MATLAB | 5,744 | 213 | function [w, infos] = admm_lasso(problem, options)
% The alternating direction method of multipliers (ADMM) algorithm for LASSO problem.
%
% Inputs:
% problem function (cost/grad/hess)
% options options
% Output:
% w solution of w
% infos information
%
% This file is part... |
5a03cf737c49e3cc80d10ac67391493efbf30d8574a75d809644f07b3911d2d5 | MATLAB | 5,756 | 161 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
DelayTimes = [4,8,16];
Target = 'LONG';
AssemblyChoice = 2;
% 1 - lever press cutouts
% 2 - trial cutouts (cue to reward inclusive)
% 3 - continuous time
tlimsAll = [-5 5];
tlimsShort=[-4 10];
tlimsMedium=... |
df1b83d0f29aae94cba7e0b4dadee40522dcfe9b42b970440767fcbaa845f1bd | MATLAB | 5,771 | 247 | % PURPOSE: centralize ERPLAB working-memory storage and migration
%
% FORMAT:
%
% value = erplab_memory_store(kind, action, varargin)
function output = erplab_memory_store(kind, action, varargin)
output = [];
if nargin < 2
help erplab_memory_store
return
end
kind = lower(kind);
action = lower(action);
paths... |
a0a2e44f2c9cc8c7719b109479b4155d5f756ecf1f3b2835d2da257cb2955be9 | MATLAB | 5,772 | 143 | % Group analysis for single unit / assembly decoding capability, activation
% patterns for assemblies
%
% Aleksander PF Domanski PhD UoB 2016
% aleks.domanski@bristol.ac.uk
%% Preamble, get file list
clear all; close all
set(0,'DefaultFigureWindowStyle','docked')
flags.plotIndividualChanges = false;
if ispc
%... |
7d3a27d3196728917cf3d342a4a9f124c414ea3bec2d7af0a1fb110d3fff7f7b | MATLAB | 5,777 | 145 | function encodedDIOdata = BitsPlusDIO2Matrix(mask, data, command, goggle, DAC)
% encodedDIOdata = BitsPlusDIO2Matrix(mask, data, command [,goggle ,DAC]);
%
% Generates a Matlab matrix containing the magic code and data
% required to set the DIO port of CRS Bits++ box in Bits++ mode.
%
% 'mask', 'data', and 'command' ha... |
3539d90221897c786eb01b4b7c5c1242808403d610767805a576bcf6b314835d | MATLAB | 5,799 | 202 | function [stats,st] = SStat_CoxExt(sID_ext,X_ext,d_ext,t_ext,e)
% [stats,st] = SStat_CoxExt(sID_ext,X_ext,d_ext,t_ext,e)
%
% Parameter estimation for the extended Cox model. This function uses as
% input the output of SStat_X_ext but with X_ext having new time-dependent
% columns added by the user (eg. the product of ... |
b59b60cdcf6529d219419ed56e971970e3224c85f467166c1f798d3598d6f314 | MATLAB | 5,799 | 195 | function varargout = f_EEG_suffix_gui(varargin)
% F_EEG_SUFFIX_GUI MATLAB code for f_EEG_suffix_gui.fig
% F_EEG_SUFFIX_GUI, by itself, creates a new F_EEG_SUFFIX_GUI or raises the existing
% singleton*.
%
% H = F_EEG_SUFFIX_GUI returns the handle to a new F_EEG_SUFFIX_GUI or the handle to
% the exis... |
4dd31cbce8f3bcf1922da21775911e32d2fef73e36edefc932a4e64ef37d22f4 | MATLAB | 5,802 | 127 | function FIGURE_FibrePerformance
% This function plots the figure showing the performance of homogenisation
% for the different extents of homogenisation and different densities of
% fibrosis.
% Velocity measuring information
Lx = 5; % Length of fibres (cm)
start_point = 0.3; % Pro... |
4f75eeee817622e7302d1bb68bf9134b60833c2847ca088def68f70e2a5c81cf | MATLAB | 5,803 | 115 | function trial_label = AssignTrialLabel(trials,flag)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This function identifies the stimulus label
% (target/distractor/target-distractor location/euclidean distance between
% target and distractor location in trials) for the trials under trials.
% An... |
75fcdbb049c116302d13b9c536d1a3bbed9e2b0a66c407f443b9d7cd89844811 | MATLAB | 5,810 | 170 |
% Written by Sham Tlili and edited by Timothy Saunders
% Code for performing optic flow analysis
addpath('./useful_functions/')
% Defining outputs
screen_dpi = get(0, 'ScreenPixelsPerInch');
screen_display_factor = 100;
% Input and output folders and files
folder_image = './images/';
fol... |
14d7299c3c562377bcd7b79101ad756af03a0fa4eb2be1d91150e0c17f79ec48 | MATLAB | 5,820 | 168 | % PURPOSE: reads an EVENTLIST from a .xls file
%
% FORMAT:
%
% [EEG EVENTLIST] = f_readeventlist_excel(EEG, elfilename );
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Guanghui Zhang & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2024
%b8d3721ed219e65100184... |
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