sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b5de14e2de3f0bd74a8352f4701eaa4f14a3b8e9788b504691df2bd4164e8c7f | MATLAB | 10,240 | 253 | function recruitment(model)
format longeng;
simStart = tic;
log = model.getLogger('recruitment');
%% Parameters
MRG = model.load_MRG_coeff();
nbNod = model.params.nbNod;
nbSeg = model.params.nbSeg;
start = model.params.start;
stimDur = model.params.stimDur;
deltaQnC = model.params.deltaQnC;
qMaxnC = model.... |
5a69e245c1bd5572fa1b99ee80506d48ab6d02bfce25564e6e71b62b7eac0a23 | MATLAB | 10,245 | 269 | function step3g_validation_pairwise_decoding_mds(bids_dir, toolbox_dir, varargin)
%% Making an MDS plot for some image categories
%
%
% @ Lina Teichmann, 2022
%
% Usage:
% step3g_validation_pairwise_decoding_mds(bids_dir, ...)
%
% Inputs:
% bids_dir path to the bids... |
326dfbdc9e79596ec6080b7769a71fb9e15d3060434abfa95a425018df45e17e | MATLAB | 10,249 | 354 | % Figure Fig6_abcd
% Code to generate SUA examples V1 and V6
% (revised version, plotting sorted raster)
% load data
addpath data CircStat2012a
load('Fig6_abcd_data','tr', 'cfg', 'clu','wfm', 'templates', 'winv')
% %%%% Examples for paper:
% cfg.sessionID = 564;
% cfg.cluIDList = [20 70 195 122 ];
% cfg.stimTime = 0... |
f704f65ae5a0dd884da32e57cc2e6eadf5e717ee4700b44eb7b8c05c30feebd6 | MATLAB | 10,261 | 273 | clear
Delays_ = {'Short','Medium','Long'};
Delays__ = [4,8,16];
Target = 'LONG';
offset = [-5 5];
plotOnline = false;
bw=0.05;
clear Av
warning ('off')
if ispc
pat = 'C:\Analysis\AssemblyAnalysis\raw';
else
pat = '/Volumes/HDD2/DNMTP/raw';
end
cd(pat)
fileList=dir(sprintf('allTimestamps%s*%s*.... |
4f2b345288607c374c4d034b8abc2bdc78c0a4170434e0fac110e8f1ca9f6e8a | MATLAB | 10,300 | 225 | %% setupHMCparams returns default setup for HMC
% inputs (optional):
% nWarmup (default = 25000) : number of warmup samples (to be discarded later)
% nSamples (default = 50000) : number of samples to take post warmup
% debugSettings (default = false) : if true, changes settings for a debug run (fe... |
28d5eaa6e6106a83075d84a8edf1fa9887f0bececd56f8b8f893d52647ea127b | MATLAB | 10,306 | 329 | function varargout = AMRate_tuning_gui(varargin)
% BASIC_CHARACTERIZATION MATLAB code for basic_characterization.fig
% BASIC_CHARACTERIZATION, by itself, creates a new BASIC_CHARACTERIZATION or raises the existing
% singleton*.
%
% H = BASIC_CHARACTERIZATION returns the handle to a new BASIC_CHARACTERIZA... |
c8a3290770d28637dd210f8935c021acd624fad028a056a223753bc6b80aee6f | MATLAB | 10,311 | 256 | function Ve_rec=anesthesia_fieldmodel(p,mu,LRposition)
%% field model simulation
% input parameters: mu is the long range strength
% p is the anesthetic degree
% structure LRposition has two subfields: 'linkout' and 'receive'
% both LRposition.linkout and LRposition.receive are N x 2 matrices
% they are the outgoing ... |
10523df91c0a30e643061d0e5dd65c1f69aa0c219371dab4e7faef5d46e91bc2 | MATLAB | 10,340 | 199 | %%%%%%%%%%this script produces masked images for objects bring handled by
%%%%%%%%%%hands.This script also visualizes the output
%%%%%%%%%%%%%%%%%%%% images written to the output directory.
%%%%%%%% Comment out all imshow() statements if you want to speedup the
%%%%%%%% execution of this script.%%%%%%%%%%%%%%%%%... |
08860e5eace43c5149df92e1a3df2cca1837d5dddb3908c79591ed6fe3cb2de4 | MATLAB | 10,342 | 277 | function Model_test_Noise(p1,p2)
%p1: seed for random number and p1=1:1:\mu. There are \mu independent simulations
%p2: pattern length. p2=1 is for 50 ms; p2=2 is for 100 ms; p2=3 is for 300 ms
rng(10+(p1-1)*1e7);
%There are 3 steps in this program.
%%Step 1: removing spikes
%%Step 2: jittering s... |
c9ca9d88876882ddb23383d826e2247e1d9607a7c3ed34d25e86752649c89312 | MATLAB | 10,348 | 280 | % A property editor for custom objects.
% The property editor combines a dropdown list that the contains object
% instances with a property grid that lets the user inspect and modify
% the property values of the selected instance.
%
% See also: PropertyGrid
% Copyright 2008-2010 Levente Hunyadi
classdef Proper... |
bed74b8a80c726fa28451daef18bd6fde5a54ee29e090ae753f9b44ad510ba31 | MATLAB | 10,391 | 287 | function varargout = insertcodeatTTLGUI(varargin)
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @insertcodeatTTLGUI_OpeningFcn, ...
'gui_OutputFcn', @insertcodeatTTLGUI_OutputFc... |
b1bcf33ef367408bcb40d629a0f68e54f93d8ea8b7e5dfdaedba9942d5d45abf | MATLAB | 10,417 | 282 | function f = MakeONFilter(Type,Par)
% MakeONFilter -- Generate Orthonormal QMF Filter for Wavelet Transform
% Usage
% qmf = MakeONFilter(Type,Par)
% Inputs
% Type string, 'Haar', 'Beylkin', 'Coiflet', 'Daubechies',
% 'Symmlet', 'Vaidyanathan','Battle'
% Par integer, it is a parameter re... |
53923e496d0232c54aa497e2c36f585a319422ea62f0be2092f37af32965855e | MATLAB | 10,430 | 181 | % CREATE HEATMAP %
function h = bst_ast_display_heatmap(heatmap_data, mapMax, mapMin, title, bad_channels_to_be_removed, output_channel_names, all_condition_labels, heatmap_blocker, remove_trial_thresh, sort_type)
%if heatmap_blocker == 1, do not block channels
%if heatmap_blocker == 2, do block channels
%i... |
9b56ba86e414c444cd641cf5bb9859f65a94993db8c52409c8f57e3a8e0e45a1 | MATLAB | 10,432 | 360 | %
% Author: Javier Lopez-Calderon & Steven Luck & Guanghui ZHANG
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009 & 2022
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% Copyright (C) 2008 Javier Lopez-Calderon & Steven Luck,
% Center for Mind and Brain, Univer... |
0f6e6381813a3530bc86e07aa7026b8662440440744d62a9e755100978b3b681 | MATLAB | 10,437 | 370 | function varargout = DRAFT_Headtracker_Behavior(varargin)
% DRAFT_HEADTRACKER_BEHAVIOR MATLAB code for DRAFT_Headtracker_Behavior.fig
% DRAFT_HEADTRACKER_BEHAVIOR, by itself, creates a new DRAFT_HEADTRACKER_BEHAVIOR or raises the existing
% singleton*.
%
% H = DRAFT_HEADTRACKER_BEHAVIOR returns the handl... |
043ef458ceeeb314cf7f66c11fe6505e55f03fb0af57f27c877511c818f6a3ae | MATLAB | 10,446 | 261 | function [data, t,frametimes, roidata] = tpreadlsdata(dirname, intervals, pixelinds, mode, channel)
% TPREADLSDATA - Reads twophon linescan data
%
% [DATA, T] = TPREADLSDATA(DIRNAME, INTERVALS, PIXELINDS, MODE)
%
% Reads data blocks from PrairieView record. TPREADDATA
% allows the user to request data in specific ... |
26e33f9332fce73e111d38be48a2a1260cd68f2c4b46921bcb410f5d18df750f | MATLAB | 10,495 | 344 | clear all
doSave = 1;
twoStepPaths=vertcat([1,2,4], [1,3,4], [1,2,1], [1,3,1],...
[2,1,3], [2,4,3], [2,1,2], [2,4,2],...
[3,1,2], [3,4,2], [3,1,3], [3,4,3],...
[4,3,1], [4,2,1], [4,2,4], [4,3,4]);
oneStepPaths = vertcat([1,2,2], [1,3,3],...
[2,1,1], [2,4,4],...
[3,1,1], [3,4,4],...
[4,3,3], [4... |
6ec4f991b4c3756cb0f94c29a14e6e659f1ad391185cc9f0dde7724ab3dc112f | MATLAB | 10,499 | 247 | function [CBF] = cr_patchwise_analysis(phase_patch, pos, PowerSpec, check, CBF)
% In this function, a gradient map is calculated for a static phase.
% From this gradient map, both the wave direction and wavelength will be
% calculated and plotted.
% Credits go to Stephan Bialonski for writing the codes to determine t... |
aa883285e30e9a84e52982be505b62ebe460411e3ca167011a59ce96b60d72b6 | MATLAB | 10,515 | 314 | function FIGURE_NozzlePerformance
% This function plots some specific results for the performance of
% homogenised models for activation travelling through a nozzle-type
% structure
% Specify the type of homogenisation for which results are plotted
homog_type = 'linear';
% Specify the results to plot (varying... |
8b1fdfa061888bf8d4051770b5fe8bed1950a5c1bb1e7f45190ea4240fa74321 | MATLAB | 10,577 | 345 | clear all
addpath('/media/spare_tire/hammer/space0/model/nz_goals/mg_backup') %JWB 6/29/22
doSave = 0;
twoStepPaths=vertcat([1,2,4], [1,3,4], [1,2,1], [1,3,1],...
[2,1,3], [2,4,3], [2,1,2], [2,4,2],...
[3,1,2], [3,4,2], [3,1,3], [3,4,3],...
[4,3,1], [4,2,1], [4,2,4], [4,3,4]);
oneStepPaths = vertcat([1,2,... |
5b84c183d79c3ecd9c1ac6ffb007f03001330cd23777d877aa454b18ab080b52 | MATLAB | 10,589 | 242 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Target = 'LONG';
Areas = {'PFC','HP','Joint'};
TimeSpan = 4;
bw=0.05;
tlimsAll = [-5 5];
tbAll = tlimsAll(1):bw:tlimsAll(2);%0:bw:2*sum(abs(tlimsAll));
maxRange=20; % Upper limit of assembly size to explore
noTrials = 5; % How many ... |
e04e8e45dfc5dd4593c54f2e0eba2b175b2b5d032e8d2fc895d4e4cc585624ba | MATLAB | 10,637 | 223 | %%changed by GH Oct 2023 when developing EStudio toolbox
% POP_EEGPLOT - Visually inspect EEG data using a scrolling display.
% Perform rejection or marking for rejection of visually
% (and/or previously) selected data portions (i.e., stretches
% of continuous data... |
f1b8ce4813beb3d0ae18fbca3ce0bfd7ab1298d721999f8a40072b2fc4e3d210 | MATLAB | 10,658 | 326 | function [Regions,RgMeans] = lme_mass_RgGrow(SphSurf,Re,Theta,maskvtx,nst,prc)
% [Regions,RgMeans] = lme_mass_RgGrow(SphSurf,Re,Theta,maskvtx,nst,prc)
%
% This function implements a region growing algorithm along the spherical
% surface to find homogeneous regions comprising locations with similar
% covariance compo... |
da2aac231cd1333bddfae4627cb92c9364fed6394d210031523d66cc61cac1b8 | MATLAB | 10,672 | 326 |
function epData = reformat_tank_data_kp(BLKS,FIX_BLOCK)
%reformat_tank_data
% Function to reformat and save ephys data from epsych program.
%
% Program prompts user to select TANK, then cycles through each BLOCK,
% calls TDT2mat (@DJS) to reformat tank data to a matlab struct, then
% saves as a -mat file in... |
0f7e925045cb9a1ad4c12d18b5e8de333fa28a4738b6944c75f1a3a4e8499ed5 | MATLAB | 10,675 | 377 | % PURPOSE : Save MVPC (.mvpc) file.
%
% FORMAT :
%
% >> [MVPC] = pop_savemymvpc(MVPC, parameters);
%
% INPUTS :
%
% MVPC - Multivariate Pattern Classification (MVPC) structure
%
% The available input parameters are as follows:
% 'mvpcname' - mvpc name to be saved
% 'filen... |
da4dd9dc0750a69ef39e7537e5054f78e3423d038629f7594e1ab9601de96f14 | MATLAB | 10,685 | 272 | %% Independent sample t-test
sFilesB = db_template('importfile');
jj = 1; conlab = '04'; sFiles_in = sFiles_4;
% Process: FT t-test unequal fdr [1000ms] H0:(A=B), H1:(A<>B)
bst_process('CallProcess', 'process_ft_sourcestatistics_edit', sFiles_in, sFilesB, ...
'timewindow', [1, 1], ...
'scoutsel', ... |
efb6346e6f0b03fbce93a2d6ba6772fb0bb0840d1fc9c15d2ab2eb564429fb4a | MATLAB | 10,692 | 257 | %this is a program that calculates response to the first encounter with the stimulus
%for DL, DM and CB. Choose DLDMCB_trial1_comp. Created by Haleh Fotowat
clearvars
close all
path=uigetdir;
cd(path)
filename_b1=dir('2*_b.mat')
filename_s1=dir('2*_s.mat')
%DL: type 1, DM: type 2, CB: type 3
Stim_type_all=zeros(1,lengt... |
42a8b2a59a6071842c16f885bcb9cba40c0b0c8035fb60610a5de502de9c19d6 | MATLAB | 10,701 | 260 | % Metadata on a single property.
% This class is used to provide type and shape information, initial value,
% categorization, and context-sensitive help when a property is added as a
% field to a property grid.
%
% See also: PropertyGrid, PropertyType
% Copyright 2010 Levente Hunyadi
classdef PropertyGridField... |
c7f6aa636fcc7f9d7f4c5de38e2db481f9ca2716385bca5b22898c6bd8dc5fd1 | MATLAB | 10,701 | 268 | function Model_Learning_2_em(p1,p2)
%p1: seed for random number and p1=1:1:\mu. There are \mu independent simulations
%p2: p2=1 is for 50 ms;
rng(10+(p1-1)*1e6);
%There are four steps in this program.
%%Step 1: There is no embedded pattern in afferents for 2000 learning cycles.
%%Step 2: There are tw... |
b38ee7ac3e60169edadd5060cbf982260716b9dafd3592bbc5fea8c3e6a93e3c | MATLAB | 10,715 | 268 | function [resp] = tptuningcurve(dirname, channel, paramname, pixels, plotit, names, trials, tint,sptint, blst, basemeth)
% TPTUNINGCURVE - Tuning curve for PrairieView two-photon data
%
% RESPS = TPTUNINGCURVE(DIRNAME, CHANNEL, PARAMETER, PIXELS_OR_DATA, PLOTIT, NAMES,
% [TRIALS], [T0 T1],[SP0 SP1],BLANKS... |
6f6e64a92ef723ead57ba1a84eca6b8f4f6b8ef6db804d8d80f11be1d6ab8b01 | MATLAB | 10,729 | 275 | %sets up network for small 6-state environment simulation
% Testing modifications to 'find next state' components after April '17 cleanup.
% among other things, changed proxPast learning rule to be oscillatory and
% cleaned up plot method.
NEW_NETWORK=1;
if NEW_NETWORK
%clear all
NEW_NETWORK=1;
else
n.res... |
634c487867ac798a238ec3102be804d30622fb8c520442dafc6167a45d6b8101 | MATLAB | 10,735 | 309 | function varargout = f_ERP_meas_basecorr(varargin)
% F_ERP_MEAS_BASECORR MATLAB code for f_ERP_meas_basecorr.fig
% F_ERP_MEAS_BASECORR, by itself, creates a new F_ERP_MEAS_BASECORR or raises the existing
% singleton*.
%
% H = F_ERP_MEAS_BASECORR returns the handle to a new F_ERP_MEAS_BASECORR or the hand... |
e00b62403bc4fad983dd1376832ffef7bac27b7dc594ac2daa5a629cd87d41cc | MATLAB | 10,743 | 323 | function offlineSpikeDetect(tank,block,plxdir,sevName,nsamps,shadow,thrMult,minSpikes,Hd)
% offlineSpikeDetect(tank,block,plxdir,sevName,nsamps,shadow,thrMult,minSpikes,Hd)
%
% Offline spike detection from TDT Streamed data
%
% 1. Retrieve streamed data associated with the tank's block.
% 2. Use acausal filter (filtfil... |
4af5dde32dad0bfec27a53266e5c3aef806b407c1e6c3f6001620cfe81c160cf | MATLAB | 10,764 | 282 | function sliderFigure( h, margin, th, yar )
% SliderFigure tool by Hill DN - 07/12/2010
%
% sliderFigure - Allows user to scale and scroll through all axes on a figure
%
% Usage:
% sliderFigure( h, margin, toolbar, yar )
%
% Description:
% Call sliderFigure to add scroll bars and a toolbar with zoom control
%... |
a277389b8ac0ae9fd9c78454385de2e9e554625330c94715ecf0026de3e54e78 | MATLAB | 10,770 | 364 | function vol = ldrb_main_original(config)
% Laplace–Dirichlet Rule-Based (LDRB) algorithm for ventricular fibers
% from Bayer 2012: https://doi.org/10.1007/s10439-012-0593-5
% (see algorithm "DefineFibers" in the supplement)
% This function can be applied to BI- and ONE-ventricular geometries.
if ~isfield(config,'sou... |
59cd5b013b0c2d1c21e5afde3ef9ae15a1ced11acbf0f21b8ec3d401c044d16a | MATLAB | 10,802 | 223 | function spikes = ss_kmeans(spikes, options)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% ss_kmeans - K-means clustering.
%
% Usage:
% spikes = ss_kmeans(spikes, options)
%
% Description:
% Performs k-means clustering on the (M x N) matrix SPIKES.WAVEFORMS and stores the
% r... |
78d9baafaf5332fdc7e18588f0f52f51101084364f049015a10cd2720f33cd15 | MATLAB | 10,819 | 360 | % PURPOSE : Creates and modifies channels using any algebraic expression (MATLAB arithmetic operators)
% running over the channels in the current ERP structure.
%
% FORMAT :
%
% ERP = pop_erpchanoperator( ERP, formulas )
%
% INPUTS :
%
% ERP - input ERPset
% formulas - expression for new ... |
1ae584471570e03c6d578aa4d5d0eb37d3caa86a1464594e0e13d5b2b50d5bd8 | MATLAB | 10,831 | 169 | %
% Extract the latencies and (relative) number of N1s between one stimulated ROI and a response ROI
% [out] = ccep_N1sBetweenRegions(ccepData, roiStim, roiResp)
%
% ccepData = ...
% roiStim = An array of Destrieux codes that defines the ROI in which stimulation... |
675312e092aabf1117462b7cef26ee2c3ae286c852c4e4d46c27339482094450 | MATLAB | 10,837 | 318 | function varargout = ccep_peakfinder(x0, sel, thresh, extrema, includeEndpoints, interpolate)
%PEAKFINDER Noise tolerant fast peak finding algorithm
% INPUTS:
% x0 - A real vector from the maxima will be found (required)
% sel - The amount above surrounding data for a peak to be,
% identified (d... |
4fe230beeeeaa7c2f0761cf0d969a36411a1e031c90f828ac8ebe82614fa4588 | MATLAB | 10,839 | 273 | function analyzetpstack_slicelist(command, thestackname, thefig, arg4)
if nargin==0, % it is a callback
h1 = gcbf;
analyzetpstack_slicelist(gcbo);
return;
end;
if nargin>=3, % then is command w/ fig as 3rd arg
fig = thefig;
ud = get(fig,'userdata');
stackname = get(findobj(fig,'Tag','stacknameEdit'),'... |
895a719db47e02907fee4b3748af5cb7148854f11f02111f55d18664b697b326 | MATLAB | 10,851 | 246 | function [u,A] = TVRegDiff( data, iter, alph, u0, scale, ep, dx, plotflag, diagflag )
% u = TVRegDiff( data, iter, alph, u0, scale, ep, dx, plotflag, diagflag );
% u = tvdiff( e, dx, iter, ep, alph );
% Rick Chartrand (rickc@lanl.gov), Apr. 10, 2011
% Please cite Rick Chartrand, "Numerical differentiation of noisy,
% n... |
bb30e74451c57bfdc36253d5a76660b82f5a773154b4861c58708f0184abd162 | MATLAB | 10,852 | 376 | function varargout = H2OPassive_GUI(varargin)
% GUI for passive trial presentation, while animal drinks from spout.
%
%To do:
%
% KP Nov 6 2016, based on Aversive_detection_GUI by ML Caras
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_S... |
ad36ddc6280af885eb0a71d5849e8f6576d3e2e914e912685a4898f97578bf56 | MATLAB | 10,862 | 295 | function [] = axescenter(ax)
% AXESCENTER locates axes in the center instead of at the edges.
% AXESCENTER(AX) puts axes in the center of axes AX. If AX is not
% supplied, the current axes is assumed. Many of the standard properties
% manipulated through the command line will also work when the axes are in
% the... |
a7ed0063d3685b4aa5b24e84c729c092ecc5bd1122cc4749ceaf43d0f354bfe2 | MATLAB | 10,867 | 263 | % PURPOSE: subroutine of pop_geterpvalues.m
%
% Format
%
% A = areaerp(data, fs, latsam, op, coi)
%
% or
%
% [A L] = areaerp(data, fs,latsam, op, coi)
%
% where
%
% data - input array of data
% fs - sampling frequency
% latsam - integration limits in samples. Two values for fixed integration l... |
d8fae75a6aad30f9dc9ffd7a768b11030ddcc4aa70f13e9d772ec570c96cc9b4 | MATLAB | 10,871 | 379 | %% EXPERIMENT 1: REVERSAL LEARNING
% This code is to replicate the first experiment of Favila et al (in
% revision). The code runs n reinforcement learning agents in a two phase task. In the first
% phase agents have to learn to perform sequence Left-Right and in the
% second phase the contingency is reverse to Rig... |
45f1d5bf01c64d462d7d3b4a917be5599ad26ee85e6af8da6cbdd14744e6b15d | MATLAB | 10,874 | 294 | function [xVi, mask,F,Eh,Ch,Cm] = spm_est_non_sphericity(SPM)
% Non-sphericity estimation using ReML
% FORMAT [xVi, mask] = spm_est_non_sphericity(SPM)
%
% Required fields of SPM structure (see spm_spm):
% SPM.xY.VY - nScan x 1 struct array of file handles
% SPM.xX - structure containing design matrix information... |
fadfcb3bd26a496b72aec864042b37ded45c2492e522003d2f1f4b27d6cfdc26 | MATLAB | 10,887 | 357 | % PURPOSE : Averages across MVPCsets (grand average)
%
% FORMAT :
%
% MVPC = pop_mvpcaverager( ALLMVPC , Parameters);
%
%
% INPUTS :
%
% ALLMVPC - structure array of MVPC structures (MVPCsets)
%
% The available parameters are as follows:
%
% 'Mvpcsets' - index(es) pointing to MVPC ... |
7b23d6b997c48f8ebf407ed4ca4eaa529ae2cb75d4fc385217cd0e7c827cfebd | MATLAB | 10,898 | 291 | %% regularized Horseshoe prior for rank reduction and shrinkage
% Combining ideas from
%
% Chakraborty, Antik, Anirban Bhattacharya, and Bani K. Mallick. "Bayesian sparse multiple regression for simultaneous rank reduction and variable selection." Biometrika 107.1 (2020): 205-221.
%
% Piironen, Juho, and Aki Vehta... |
444bcb7e9fa1f4839019041dfdbb1ef2f2fd779c8d44fbbcff2d674763752c6f | MATLAB | 10,903 | 252 | %% Characterize all trials by their respective task type.
% The user can decide whether to analyse all trials, all pairs of trials,
% or the first pair of trials.
% Copyright (C) 2022 Richard Hugh Moulton
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Gene... |
9488f1f06fbe31eeeafb578aaa257cd2c810029b3021b29ef41060415c306769 | MATLAB | 10,919 | 309 | %Author: Guanghui ZHANG--zhang.guanghui@foxmail.com
%Center for Mind and Brain
%University of California, Davis
%Davis, CA, USA
%Feb. 2022
% ERPLAB Studio
function S_out = f_baseline_geterpvalues(varargin)
%%Get the parameters for pop_geterpvalues used in the last time.
def_erpvalue = erpworkingmemory('pop_geterpv... |
3d42c9129f6ec34f5c65ea44aae0f6e076bd507702ff7405eece98dfa77b997c | MATLAB | 10,945 | 300 | function varargout = analyzetpstack_previewimage(command, thestackname, thefig, arg4)
if nargin==0, % it is a callback
h1 = gcbf;
analyzetpstack_slicelist(gcbo);
return;
end;
if nargin>=3, % then is command w/ fig as 3rd arg
fig = thefig;
ud = get(fig,'userdata');
stackname = get(findobj(fig,'Tag','st... |
03c47530e115417875b32a8924aca87ea2c5c9c6a9dcdff6e3b74e766bfa970d | MATLAB | 10,975 | 302 | function setemailGUI(varargin)
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @setemailGUI_OpeningFcn, ...
'gui_OutputFcn', @setemailGUI_Outp... |
bf6cea8f231e5fb7808c4d39ff282ea545a6c136becb3dba513b611014eec667 | MATLAB | 11,035 | 337 | function varargout = csd_generate(varargin)
% CSD_GENERATE MATLAB code for csd_generate.fig
% CSD_GENERATE, by itself, creates a new CSD_GENERATE or raises the existing
% singleton*.
%
% H = CSD_GENERATE returns the handle to a new CSD_GENERATE or the handle to
% the existing singleton*.
%
% CS... |
cd7ea4cb1f11734a2357df12dbe5bd6fa377e2432f2d2bc5b8ff91afec56aca7 | MATLAB | 11,041 | 263 | %% Preamble, get file list
clear all; close all
set(0,'DefaultFigureWindowStyle','docked')
flags.plotIndividualChanges = false;
% pat{1} - % location of the processed assembly memberships
% pat{2} - % location of raw spike times
if ispc
% pat{1} = 'C:\Analysis\AssemblyAnalysis\Sleep\Decoding vs flanki... |
80dd8181dd2da8e3fe55715eda6b7519d99121933132929b7cd8536b621fc839 | MATLAB | 11,045 | 460 | clearvars
setUpPaths
%%
for len=1:23
processData
fs=29.133;
NewTime = -1/fs*60:1/fs:1/fs*100;
TIO = NewTime >0.250 & NewTime <1.000;
baseTIO = NewTime>-.1 & NewTime<0;
trials=StoreType==1;
ind1 =trials & NewSupriseStore1==0;
ind2= trials &NewSupris... |
96a98f80c5df3d4b2d40282da466b2250ebf523c2a631d5adb4f096c406d6ec1 | MATLAB | 11,107 | 301 | % demo_002 fields of the options struct - Which options can one set?
% This demo explains all fields of the options struct, e.g. which options
% you can set for the fitting process as a user.
% to have some data we use the data from demo_001
data = [...
0.0010, 45.0000, 90.0000;...
0.0015, 50.0000, ... |
43c52f04dd497ed02f6fd122aa05230048795e81040a57d24a89018f9dc77a9a | MATLAB | 11,175 | 224 | %
% Retrieve the distance in subject native space (mm) between end-point ROIs given specific tracts
% [distance] = ccep_retrieveInterROIDistance(gPial, hemi, fibers, idx, subjectFsFolder, roi1, roi2, allowIntraROI, elecPositions, trcLineEnds, extLines)
%
% gPial = ...
% hemi = w... |
1cf2e8abe5bb5cfb56c6c467a55d8bdf48d198e78caa1a65c0b9b23c22247789 | MATLAB | 11,180 | 293 | clear all
close all
target= 'LONG';
if ispc
home = 'C:\'; % [getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\raw\KDE_bins\'];
elseif ismac
path(path,'/Users/aleksanderdomanski/Documents/Bristol_work/assembly_analysis/MichalDataAna')
home = getenv('HOME');
cd ([home '/... |
a07d6d8a7ec7fd79c27f968fa8b15660a6c32974d693e43caf9a1db258b670d7 | MATLAB | 11,203 | 179 | %%This function is to create ERP Tab
% Author: Guanghui Zhang, David Garrett & Steve J. Luck
% Center for Mind and Brain
% University of California, Davis
% Davis, CA
% 2022-2025
function EStudio_gui_erp_totl = EStudio_ERP_Tab(EStudio_gui_erp_totl,ColorB_def)
if isempty(ColorB_def)
ColorB_def = [0.7020 0.77 0... |
a50ac33a7b805145ed31a35a1497b9ff36cd5cffc3f5522691398ce53ff82f45 | MATLAB | 11,203 | 313 | % From MAT LAB File Exchange
% (https://www.mathworks.com/matlabcentral/fileexchange/66493-alexhenderson-cividis)
%
% ALEX HENDERSON - CIVIDIS
function cm_data = cividis(m)
% cividis Perceptually uniform colormap (blue-yellow)
%
% Syntax
% cm_data = cividis();
% cm_data = cividis(m);
%
% Description
% cm_data =... |
0ef2f3245223b23afb4c5469d4fdf6c7729fa9f0f863e4b71490957a33f47daf | MATLAB | 11,204 | 318 | %
% Under construction...Sorry.
%
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created ... |
69e1208b4a1cb2cb1d7dd5239b60c53257ad665179be47d105933ef32c081657 | MATLAB | 11,216 | 338 | function varargout = csd_chan_locations(varargin)
% CSD_CHAN_LOCATIONS MATLAB code for csd_chan_locations.fig
% CSD_CHAN_LOCATIONS, by itself, creates a new CSD_CHAN_LOCATIONS or raises the existing
% singleton*.
%
% H = CSD_CHAN_LOCATIONS returns the handle to a new CSD_CHAN_LOCATIONS or the handle to
%... |
027e59bdcb6f4a88389b13b69782a3b9b7def73b2ba11784270aaf3981fe11bc | MATLAB | 11,228 | 237 | function [ypred_test, W_all] = predictComponent(db,P,predP,recompute)
%%% This function needs the glmnet-matlab repo to work (https://github.com/junyangq/glmnet-matlab)
if ~exist('recompute','var')
recompute = 0;
end
P.focusOn = predP.focusOn;
pc2predL = predP.pc2predL;
motpc2keepL =... |
2f936bd10d301ac2cebb29917d740c29baf7d700cdf6756d31647f42d12bde9b | MATLAB | 11,236 | 374 | function vol = ldrb_main_adapted(config)
% Laplace–Dirichlet Rule-Based (LDRB) algorithm for ventricular fibers
% from Bayer 2012: https://doi.org/10.1007/s10439-012-0593-5
% (see algorithm "DefineFibers" in the supplement),
%
% The original algorithm was adapted to yield a continuous and
% approximately linear rotatio... |
ca4ade7126fc5faab4b076be43ed035bec7f3e40ff8c3350e9e9870c606e4fe8 | MATLAB | 11,245 | 346 | classdef ( Hidden ) Divider < matlab.mixin.SetGet
%uix.Divider Draggable divider
%
% d = uix.Divider() creates a divider.
%
% d = uix.Divider(p1,v1,p2,v2,...) creates a divider and sets
% specified property p1 to value v1, etc.
% Copyright 2009-2024 The MathWorks, Inc.
... |
33784e8aff362fb7915239b2cee23bb73c1607e4db83f626f72923ee079a9c66 | MATLAB | 11,246 | 315 | % COLOURMAPPATH Plots the path of a colour map through colour space
%
% Usage: colourmappath(map, param_name, value, ....)
%
% Required argument:
% map - The colourmap to be plotted
%
% Optional parameter-value pairs, default values in brackets:
% 'N' - The nmber of slices through the colourspac... |
55d390e3803e5c39b227d340c4c5391fe0cdaee2801d890f3352cc9ef8300279 | MATLAB | 11,246 | 233 | restoredefaultpath
clc; clear; close all force;
data_name='ADNI';
base_path = fullfile('C:\Users\Vincent\Desktop\scratch');
out_path = fullfile(base_path, 'output'); addpath(out_path);
codes_dir = fullfile(base_path, 'ET_biomarker', 'tab_data');
sub_list_file = fullfile(codes_dir, [data_name,'_subjects.list']); % re... |
d8a908a7f83ddf8983a902211e35bbe01a2168b96da21d844f50470e3101d76e | MATLAB | 11,295 | 259 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Target = 'LONG';
Areas = {'PFC','HP','Joint'};
TimeSpan = 4;
bw=0.05;
tlimsAll = [-5 5];
tbAll = tlimsAll(1):bw:tlimsAll(2);%0:bw:2*sum(abs(tlimsAll));
maxRange = 20; % Upper limit of assembly size to explore
noTrials = 10; % How many... |
4320b80e844aaab37be9794fbc23de2556a02c04a77c1afc5049fe15003703dd | MATLAB | 11,312 | 325 | % SYNTAX
%
% >> EEG = pop_artabsth(EEG, parameters);
%
% DESCRIPTION
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% 'Twindow' - window in ms to apply this tool (start end). Example [-200 800]
% 'Threshold' - peak-to-peak threshold within the moving window (in... |
744046898ff7415870fba329dd92e73c9d751cf9536ec1a2e5b324234f0c498c | MATLAB | 11,319 | 437 | function out = FRA_Analysis(spiketimes,params,varargin)
% DB_FRA_Analysis(spiketimes,params);
% DB_FRA_Analysis(spiketimes,params,'param',value);
% out = DB_FRA_Analysis(spiketimes,params,...);
%
% Characterizes receptive field using the centroid method outlined in
% Escabi et al, 2007 Neuroscience 150:970-983. Additi... |
1799c1edb58bdb26befd75f941029e09aec72f179ff4fbc8b21401d3e6333164 | MATLAB | 11,329 | 328 | % PURPOSE : Marking epochs containing a sample to sample difference, higher than a threshold (uV/ms).
%
% FORMAT :
%
% >> EEG = pop_artdiff(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% 'Twindow' - time period (in ms) to apply ... |
38aeef8a8a29fe1760858531f4639fb30eae819ce66e4a489306ac62f83f706f | MATLAB | 11,330 | 329 | % Main execution function to keep workspace clean
% experimentalData: 2D matrix of observed values
clc;close all;
[d2,d2ri,d2ir,d2ii,dataFreq]=readpipe_2Di('alh_zf3.ft2');
observed = d2(281:2:340,2360:2:2460);
noise_floor=1.84e5;
noise_floor = noise_floor / max(observed(:));
... |
a69c158aa088c7c94561658dc367c7478fb2dfffb9a5d813415b21b799a16979 | MATLAB | 11,377 | 331 | % PURPOSE : Calculates (normalized) cross covariance between each epoch,
% at the specified channel(s), with a simulated barbed like waveform
%
% FORMAT :
%
% >> EEG = pop_artbarb(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% ... |
98d551e0c22292f9ec75b871dba85c70c7cfc3178ecb33ffba25d5cc3db33edb | MATLAB | 11,407 | 433 | function plot_gc_synthetic_network
% function plot_gc_synthetic_network
%
% Simulate toy dynamics (VAR, GLM, and GLM+calcium) on a toy network of 10
% neurons. Compute correlation, and granger causality (GC). Analyze the GC
% performance as a function of connectivity strength of the network.
%
% This code generate Fig.... |
e440f138fd486ca6e06c16750143acd5af1c46d8dc0f62587a55c034abbdec81 | MATLAB | 11,411 | 331 | % PURPOSE : Marking epochs containing a rate of change (slope) higher than given threshold (uV/ms).
%
% FORMAT :
%
% >> EEG = pop_artderiv(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% 'Twindow' - time period (in ms) to apply t... |
df3a34ddd52112bb1cafbe6715892e6b0dfa7dea21120b65005ed5704f36d89b | MATLAB | 11,416 | 484 | function varargout = ep_GenericGUI(varargin)
% ep_GenericGUI;
%
% In the ep_RunExpt GUI, click "GUI Figure" under the "Function
% Definitions" menu. This will prompt you to enter the name to this or
%
% The primary purpose of this GUI is to serve as a modifiable template for
% developing new GUIs for use with EPsych ... |
4c2e46d36875a851e95ee3d832fb0a5989335bbdba068a1b58a6623b9c2dcba3 | MATLAB | 11,431 | 330 | function [EEG,com]=pop_marks_event_gap(EEG,event_type,crit_dur_ms,new_label,new_color,varargin)
com = ''; % this initialization ensure that the function will return something
% if the user press the cancel button
% display help if not enough arguments
% ------------------------------------
if n... |
f4b93b22620272b0b24c9f2f77613d9a8248d9fb4a0ffe93202e1f67bc3ff7ba | MATLAB | 11,436 | 267 | %% %%%%%% PREAMBLE %%%%%%
Delays_ = {'Short','Medium','Long'};
Target = 'LONG';
Areas = {'PFC','HP','Joint'};
TimeSpan = 4;
bw=0.05;
tlimsAll = [-5 5];
tbAll = tlimsAll(1):bw:tlimsAll(2);%0:bw:2*sum(abs(tlimsAll));
maxRange = 20; % Upper limit of assembly size to explore
noTrials = Inf; % How many... |
8d4dc2507e7372d41de111958d414ca2a4b601e56ae02fd02351dc16844b2151 | MATLAB | 11,437 | 313 | %% KStest for PCF FH, SD, SH Only, ORCO, Males, Antennae
root = 'C:\Data\Daniela\ACV_Water\Data_Stats\';
dirAnaly = 'C:\Data\Daniela\ACV_Water\Data_Stats\KS_Test_Histograms_Last20Sec_PCF_Males_TP1_TP2\';
%% Within Conditions
% Cond 1
[h,p,ks2stat] = kstest2(HisBinProb_PCF_FH_Cond1,HisBinProb_PCF... |
701a610281e7b1be8c2b9a16f5cac76c583e99120adc55928d6d0903357b0620 | MATLAB | 11,455 | 239 | clear all
close all
target= 'PreSleep';
if ispc
home = 'C:\'; % [getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\Sleep'];
separator='\';
elseif ismac
path(path,'/Users/aleksanderdomanski/Documents/Bristol_work/assembly_analysis/MichalDataAna')
home = getenv('... |
8d393d0ca2205bb763674cbe9db1de4579b661143957184efa02442bfcc67201 | MATLAB | 11,468 | 355 | % PURPOSE : Removes ERP baseline
%
% FORMAT :
%
% ERP = pop_blcerp(ERP, 'Baseline',blc)
%
% ERP - ERPLAB structure
% blc - window for baseline correction in msec, or one of the keywords
% listed under INPUTS below
%
% Example :
% >> ERP = pop_blcerp( ERP , 'Baseline', [-100 0]);
% >> ERP = pop_blce... |
7cfc19a0c6bc0d666ffee02aeeaac43d9c349b912081aa3e0af8f9c4dee16178 | MATLAB | 11,476 | 310 | function edr = eda_edr(varargin)
% EDA_EDR Automatic Electrodermal Response (EDR) detection.
%
% Formats:
% (1) edr = EDA_EDR(eda, fs)
% (2) edr = EDA_EDR(eda, fs, thrin, opendlg)
% (3) edr = EDA_EDR(eda, fs, thrin, opendlg, plotOK)
%
% Required Input arguments:
% eda - 1-by-n vector of EDA samples
% ... |
aa4ae5d41cb2f34f3dcc028595cb7e54e57875ae94ae4160aab3fc1442b6c1c9 | MATLAB | 11,510 | 296 | function fPlotAssemActivations(Ass,plot_flag)
target = 'Homecage';
%% Optional plotting
if plot_flag
%% Plot soloists vs. choristers
figure('color','w');
cmap = {'r','g','b'};
for s = 1:length(Ass.titles)
subplot(1,2,1); hold on
bar(s,Ass.units.FractionSingleAssem(s),'EdgeColor', cmap{s},'FaceCo... |
d57a32ff3477676a6c739827f3eb1363c64b44285ba0f69ddaea164b19ba81fa | MATLAB | 11,541 | 340 | %% modified version of "2-D convolution using the FFT". Original version can be found at the following webiste.
%% http://www.mathworks.com/matlabcentral/fileexchange/31012-2-d-convolution-using-the-fft
%% Copyright (c) 2011, David Young
%% Copyright (c) 2010, David Young
%% All rights reserved.
%% Redistribution and ... |
b7fd468e10883da735351fa9cfe3052c8fac6072662fa5319ec62a8c9f25c097 | MATLAB | 11,557 | 311 | % Example plots to show various combinations of unit timestamps, firing rates, behavioural events and factor scores.
% NB Feb 2016 - This is now depreciated and is obsolete, but retained for example plot purposes.
%
% Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
%% Preamble: load files
%... |
a67def460e48ec8ef9e39598d706fd05d82de176dcf548457231dc52338b0b59 | MATLAB | 11,572 | 403 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 5d
clear all; close all; clc;
Which_GLM = 3;
% 3: hv_lv, lv_hv, lv_dv, dv_lv, hv_dv, dv_hv => th... |
cde72ff8e8746584be52561e0ffa1e02e69f90f70475543c1f4041e4e0db6f51 | MATLAB | 11,581 | 450 | function DATA = SaveAMRateData2(path, subject, session, block, channel, clu)
%
% pp_plot_rasters(subject, session, channel, clu)
% Plots a raster and psth for each unique stimulus. Clu is the label
% given by UMS (not an index), found in Spikes.sorted.labels.
%
% KP, 2016-04; last updated 2016-04
%
set(0,'D... |
f937e9e57337860acb00802016192aae9be59ddf930e0c83f6034f2726e460d5 | MATLAB | 11,597 | 405 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 5b
clear all; close all; clc;
Which_GLM = 1;
% 1: HV+LV, HV-LV, D-HV => these values to predict ... |
1d0404cf77ae0da80bda20b45688ecdd8e2f4a1b325c4fa9223fa3c60e1337be | MATLAB | 11,599 | 405 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 5 - figure supplement 1b
clear all; close all; clc;
Which_GLM = 2;
% 2: HV, LV, D => these value... |
dae4813e092a46c70f3c926c68774c2c7937a75cc9152f2fba2b1ef0477ca4c4 | MATLAB | 11,601 | 405 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 5c
clear all; close all; clc;
Which_GLM = 1;
% 1: HV+LV, HV-LV, D-HV => these values to predict ... |
8baea9708998f9e54e585eaad679c48a15360cb55914ade0d9642b24298703fa | MATLAB | 11,605 | 278 | classdef MaterialManager
%MaterialManager Keeps track of all material definitions used by .obj
%files and then creates a master material file used by all
properties
MaterialsTable = java.util.Properties
end
methods
function obj = MaterialManager()
obj.Ma... |
380b4778b3cfe2e9f3e140924570031241b7f16fdc2fadf6936992a3c5b178fb | MATLAB | 11,607 | 405 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 5 - figure supplement 1
clear all; close all; clc;
Which_GLM = 2;
% 2: HV, LV, D => these values... |
c0d6cd684e68dd2f3aaaf2beeec358fd29b38616bf968dd942ec3407d27e0de4 | MATLAB | 11,618 | 405 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 5a
clear all; close all; clc;
Which_GLM = 1;
% 1: HV+LV, HV-LV, D-HV => these values to predict ... |
19b7cac1777c3c30681ce9791e8d5282c217e93a59379eb5cb667edc2575c615 | MATLAB | 11,619 | 347 |
function scatter_colormap_lin_fit(data_struct, varargin)
% Plot data points from different groups.
% used in TSL_analyze_ratings (lin fits).
%
% data_struct
% Structure array with one entry per group of data, which will be
% associated with a marker. Required fields:
% 'x' and 'y' for the data to p... |
dc8235cc36079c7c0e00b5fe4781dedc2b9c19051e7dfb360035f8edfb51ca43 | MATLAB | 11,630 | 405 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 5 - figure supplement 1a
clear all; close all; clc;
Which_GLM = 2;
% 2: HV, LV, D => these value... |
78d661bf116b0dc6d811b64bcc039424c568b85e662293ed1ade079f1d0f4266 | MATLAB | 11,654 | 201 | %
% signal=PRODUCESIGNALS(trial_duration,flicker_frequency,flicker_random,LED_duty_cycle,sound_duty_cycle,sound_frequency,type_of_burst,sample_rate)
%
% Creates visual and audio flicker signals to be sent to the NIDAQ, with given
% parameters provided in the input.
%
%
% Inputs:
%
% trial_duration: the duration of give... |
d0e0e00fd66e5e10684685fb85e9f0fec4e09c771641d4cdede2ba013bd90601 | MATLAB | 11,664 | 296 | % function DecodingDuringDelayIndividualUnits(iFile)
% if isstr(iFile)
% iFile = str2num(iFile);
% end
%% %%%%%% PREAMBLE %%%%%%
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
RunErrors = false;
tlimsShort=[0 4];
tlimsMedium=[0 8];
tlimsLong=[0 16];
tlimsShort=[-... |
f6fd4a1334dfd641059c30c03946f27085dc79052d25fa6fce2f5e0dc324864b | MATLAB | 11,665 | 272 | %% |interpclosed| documentation
% The |interpclosed| function creates piecewise polynomial fits of 2D closed
% curves given by a set of points. The function can be used to (i) return the fit
% itself; (ii) interpolate values within the curve using an arc-length
% parametrization; or (iii) return the area, perimet... |
4ab6638c5d439ed3f3a9a980db6fb06a147af8b6b7756108a6f4b6a444db0b06 | MATLAB | 11,708 | 310 | %sets up network for small 6-state environment simulation
% Testing modifications to 'find next state' components after April '17 cleanup.
% among other things, changed proxPast learning rule to be oscillatory and
% cleaned up plot method.
NEW_NETWORK=1;
if NEW_NETWORK
%clear all
NEW_NETWORK=1;
else
n.res... |
6ee36c01e624e7cd34c4b5e16f5e56080842e002fb5466e7e4376e4824130075 | MATLAB | 11,712 | 168 | restoredefaultpath
clc; clear; close all force;
data_name='ADNI';
base_path = fullfile('C:\Users\Vincent\Desktop\scratch');
out_path = fullfile(base_path, 'output'); addpath(out_path);
codes_dir = fullfile(base_path, 'ET_biomarker', 'tab_data');
sub_list_file = fullfile(codes_dir, [data_name,'_subjects.list']); % re... |
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