sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5b1be4073a6f48beb2ce185296732482066533793450ea72917c76fea91f5db9 | MATLAB | 8,048 | 243 | %% MVGC statistics demo
%
% Demonstrates MVGC toolbox time series statistical and spectral analysis tools.
%
%% References
%
% [1] L. Barnett and A. K. Seth,
% <http://www.sciencedirect.com/science/article/pii/S0165027013003701 The MVGC
% Multivariate Granger Causality Toolbox: A New Approach to Granger-causal
% In... |
52a4b9eaee4f8d4f49f50e7cbaadec2ba7d48b81b2282ed93aad991be98b138a | MATLAB | 8,057 | 253 | classdef CalRig < handle
properties (Abstract)
nviews
viewNames % [nviews]. cellstr viewnames
%viewRois % [nviews x 4]. viewRois(iView,:) gives [xlo xhi ylo yhi]
end
properties
sourceFile = '';
end
methods (Abstract)
% iView1: view index for anchor point
% xy1: [2]. [x y] v... |
34db62848a4ad4fcfa0eb458c69e7e729748d0be141316e0e7522376e557e155 | MATLAB | 8,059 | 174 | function [theCovariables] = y_RegressOutImgCovariates(DataDir,CovariablesDef,Postfix,MaskFilename, ImgCovModel)
% FORMAT y_RegressOutImgCovariates(DataDir,CovariablesDef,Postfix,MaskFilename, ImgCovModel)
% Input:
% DataDir - where the 3d+time dataset stay, and there should be 3d EPI functional image files.... |
18ed4b6d9a0c84cf3eabd39c4f7a1752c7d23bd314e330efaa184f238d676b99 | MATLAB | 8,060 | 201 | % Second-kind integral equation on the unit sphere, Laplace double-layer.
%
% This is the same as IE_SPHERE1 but using HIFIE3X.
%
% Inputs (defaults are used if not provided or set empty):
%
% - N: minimum number of triangles from subdivision (default: N = 20480)
% - NQUAD: 1D quadrature order (default: NQUAD = 4)
... |
3d350557745df10f53421958556dc0a8e4f9ba4e3b29200125991147593c8dbf | MATLAB | 8,061 | 145 | [OS,dc,compName,MatlabVersion,MatlabVersionYear,ScreenSize]=WhereAmIRunning(0);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for RecordingNum=1:size(Recording,2)
SaveName=Recording(RecordingNum).SaveName;
StackSaveName=Recording(Recording... |
5c687f37505fb217263feb016a1bfd9f32b6f0ba3a5d255c358f94dd54fbb55c | MATLAB | 8,063 | 188 | function h_loadQCamImg3(handles)
global h_img3;
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
channelToLoadOpt = get(handles.channelToLoadForQCam,'value');
if channelToLoadOpt==1
fileType = '*.fig';% 1 = red, reference
[fname,pname] = uigetfile(fileType,'Se... |
907344803dd1753be041273703ce367e4bf96f7299476cb00c9421436726e939 | MATLAB | 8,065 | 218 | function CBIG_KRDNN_train_valid_krr(setup_file, lambda_set)
% CBIG_KRDNN_train_valid_krr(setup_file, lambda_set)
%
% This function runs kernel ridge regression algorithm on training and
% validation data.
%
% Inputs:
% - setup_file
% Path of the setup file (.txt file).
% setup_file has the following fields:
... |
a98589c75dd8cdbfac744bf01a75096eca04c9033949b6126aaf9eb743c53c14 | MATLAB | 8,065 | 254 | %% set up paths
JAABAcodedir = '/groups/branson/home/bransonk/behavioranalysis/code/Jdetect/Jdetect';
labelfiles = {
'/tier2/hantman/Jay/videos/M186hm4dBPN/labeler/M186hm4dBPN_manualEndpoint1stCNO.lbl'
'/tier2/hantman/Jay/videos/M186hm4dBPN/labeler/M186hm4dBPN_manualEndpoint2ndCNO.lbl'
'/tier2/hantman/Jay/videos... |
0b3cb063b7f7127036abda2ab949144eb46bd97ac0f13fe18ea67f367e8e1653 | MATLAB | 8,074 | 234 | function r = ttest2Struct(x_c,x_p,varargin)
% varargin -> all the params for ttest2 function
% additional params:
% AlphaFDR -> value for the FDR threshold
% SplitNegPos -> averages x and y across rows and performs two t-Tests:
% one for the elements in which: mean(x,1) - mean(y,1) >= 0; and ... |
5cfa1c5222c5b975eb097163657de8aa95200e9c1fe39aff4bcb88c53cec4956 | MATLAB | 8,079 | 220 | %% Statistical analyses for HbO (main findings)
%% to compare correct condition and baseline
% define representative value
clear all
load incongruent_allsub_2probe_final.mat
load congruent_allsub_2probe_final.mat
% for congruent condition
N_sub = length(congruent_allsub_2probe_final);
N_chan = size(congruent_allsub_2p... |
abbee076df064ec1dc902d3c4d65ad04a993ce34230aa44d940d0935136ae2e9 | MATLAB | 8,083 | 251 | function [pdf, sigma] = circ_ksdensity(T, ti, method, sigma)
%CIRC_KSDENSITY Probability density function of circular data.
%
% -------------
% INPUT
% -------------
% T - circular data values, n-by-1 vector
% ti - vector location in angles of even-spaced points where
% the pdf is to be computed (1:360 for example... |
df3130a4d04016673afe2e760963315431eabf74735b0c47dc8ed9ae6d8433d4 | MATLAB | 8,089 | 245 | %% This code plots an example newtork figure
% plotNetSchematics.m
%
addpath(fullfile("..", "..", "src"))
Config = utils.setConfig;
% Parameters and create network
analysisParam.figSettings = 'manuscript'; % standard, manuscript, poster
analysisParam.plotLegends = 1;
analysisParam.tSNESeed = 1234;
%% Create network... |
75dee5ab49d824ffe5413fba372c145f77126434abe56fdc976390fcf95d448e | MATLAB | 8,094 | 302 | function [dip,xl,xu, ifault, gcm, lcm, mn, mj] = hartigansdiptest_ss(xpdf)
% function [dip,xl,xu, ifault, gcm, lcm, mn, mj]=HartigansDipTest(xpdf)
%
% This is a direct translation by F. Mechler (August 27 2002)
% into MATLAB from the original FORTRAN code of Hartigan's Subroutine DIPTST algorithm
% Ref: Algorithm AS ... |
9d138f172c8e53b4e4a69beaad12e46de346452ea3657fe8dbd87c403394138d | MATLAB | 8,096 | 150 | %% Description
% In this example, simulation of fluorescence (luminescence) is shown. The
% test geometry is a fluorescing cylinder in which excitation light is
% predominantly absorbed embedded in a block of medium in which
% fluorescence light is predominantly absorbed. The geometry is illuminated
% with an infinite ... |
a1b0573d4c36a5c8257d41c9da9b594ed9dcf047e0a8b57837d43495efe93c44 | MATLAB | 8,096 | 212 |
% Calculating Correspondences
% This is the code that calculates the keypoints and descriptors at
% varying scale levels
%
% INPUTS:
% moving_run: which expeirment do you want to warp accordingly?
% OUTPUTS:
% no variables. All outputs saved to params.registeredImagesDir
%
% Author: Daniel Goodwin dgoodwin208@gmail.co... |
ec3aab2faae3d2db4b2c850926f283452b4d8785b515ebb41f95c82d8447bcc2 | MATLAB | 8,096 | 266 | function [Results]=SUA_BayesModel4Format(AllTrialData,Phase,unit,timeWindow,opts)
%%(AllTrialData,Phase,unit,timeWindow,opts)
% unit=[1 50 1];
% % Phase='Go1';
% timeWindow=[.5 1];
% opts.BaselinePhase='CueTarget'
model= 'FR~Condition';
LabelOrder={'Pinch' 'Press' 'Rub' 'Tap'};
cTrialData=Analyze.S... |
afb7a10f04ccbcef2523c4088b4f650a8c3794d12ff2bf63694d25363a57b82d | MATLAB | 8,099 | 200 | % function ConvertLocations ( ReadFileName, WriteFileName, eegLabels )
%
% This routine converts between *.ced and *.locs (EEGlab) and *.csd (CSD
% toolbox) electrode location ASCII text files by rotating the spherical
% angle theta +90 or -90 degrees.
%
% Usage: function ConvertLocations ( ReadFileName, WriteFi... |
10974b0961b0ff1c7964371b6b12a33e967fbd1c428f9b9027d6e5310bb19c17 | MATLAB | 8,101 | 100 | clear;clc;close all
ROOTPATH = strcat(NoveltySU.utils.getRootDirPath(mfilename("fullpath"), 4), "Data\Processed Data\");
cd(NoveltySU.utils.getRootDirPath(mfilename("fullpath"), 2))
protStr = "1000-ms Sound reward";
temp = NoveltySU.utils.dirItem(strcat(ROOTPATH, protStr), "spkData.mat");
popRes = cell2mat(cellfun... |
3c2d422a3205560407b4de98f68b76fd3285b02e8ea95623f89ce763d48e5815 | MATLAB | 8,101 | 147 | % align ImageArray and keep result in ImageArray_Reg
%[ImageArrayReg_AllImages DeltaX_First DeltaY_First MaxValue_First BoutonArray] = ReadGoodImages_LapseRegXY_ArrayRegIndBoutSel_Crop_Fine_DifFirst([StackSaveName,StackSaveNameSuffix], StackFileName, GoodImages, FilterSize, FilterSigma, AlignRegion, MaxShiftX, MaxShift... |
e99f144256881ceb4ec769b1f040eb841238e8e6d96a7dc03b61003c8995b5ae | MATLAB | 8,102 | 259 | function cb=colorbarZN(varargin)
%COLORBAR Display color bar (color scale)
% COLORBAR appends a colorbar to the current axes in the default (right)
% location
%
% COLORBAR('peer',AX) creates a colorbar associated with axes AX
% instead of the current axes.
%
% COLORBAR(...,LOCATION) appends a colorbar in the ... |
09cf127d5bb3974c3f501b21c96b2b2cda0dd376a449a2e1ee922d67cd6af843 | MATLAB | 8,103 | 148 | % SPIKE COUNT FOR BAYESIAN DECODING
% INPUTS:
% place fields: matrix or []. Place fields that want to be used as a template in the decoding. If empty, it will load place fields for the whole session (extracted_place_fields_BAYESIAN.mat)
% start_time & end_time: single value, vector or []. Might want to enter start and ... |
0a08a1139477e5d42468af6c3027732e2b30599bde2e23189dc48601a01b1446 | MATLAB | 8,106 | 224 | % Address the basic question, when x is the salient category, what
% percentage of units are tuned to x.
function PlotAnalysisThroughTime(config,varargin)
[varargin,DateName] = Utilities.ProcVarargin(varargin,'DateName',[]);
if strcmp(mfilename,'') || nargin==0
opts=Analyze.Libet.Config_BasicLinear... |
7d8da4e9112e9f823bebb37d3f0dc89c0cb8a2cef2b970364764ccad5ee6c606 | MATLAB | 8,107 | 187 | function plot_badtimesegments(params,EEG,single_path)
% ,total_recording_length
% Recording ids
s_ids = cellfun(@(x) regexp(x,'.*(?=_eeg.set)','match','lineanchors'),{EEG.filename});
etc = {EEG.etc};
srates = {EEG.srate};
shapesrates = size(srates );
disp(['srates size£º', num2str(shapesrates )]);
disp(['srates £º', ... |
edb1c4c37e7f1a39928fb401b801b135bc107fe5145b6b01f0d9a25161df2d8b | MATLAB | 8,108 | 180 | function y_GroupAnalysis_PermutationTest_Image(DependentVolume,Predictor,OutputName,MaskFile,CovVolume,Contrast,TF_Flag,IsOutputResidual,Header,PALMSettings)
% function y_GroupAnalysis_PermutationTest_Image(DependentVolume,Predictor,OutputName,MaskFile,CovVolume,Contrast,TF_Flag,IsOutputResidual,Header,PALMSettings)
... |
f0f983bb67c14ed4d7d2c874f86fb4a54e076db20af2f743b1710259a3fd2dc7 | MATLAB | 8,109 | 231 | function [n, fn] = dimlength(data, seldim, fld)
% DIMLENGTH(DATA, SELDIM, FLD) is a helper function to obtain n, the number
% of elements along dimension seldim from the appropriate field from the
% input data containing functional data.
%
% Use als
% [n, fn] = dimlength(data, seldim, fld)
%
% It can be called with ... |
47d228a8ad5b8941fc3f6eb1a103f908b8e9c2311fbd2fc2ab777b44cc72b48b | MATLAB | 8,111 | 312 | function COR = cor_stata(COR,cfg)
% v.0.0.4
% <*LAN)<]
%
% Compute basic statistic of COR structure. (non parametric)
% with differente subjet in COR.OTHER.subject or COR.OTHER.sujeto
%
% cfg.analysis={ ... } % analsis to compute between different estimuli
% 'correct' % proporcion of creec... |
561b861b18c7bb9315963d427b5d767f6612f42b1358e1519da583526404aba2 | MATLAB | 8,114 | 214 | function hText = xticklabel_rotate(XTick,rot,varargin)
%hText = xticklabel_rotate(XTick,rot,XTickLabel,varargin) Rotate XTickLabel
%
% Syntax: xticklabel_rotate
%
% Input:
% {opt} XTick - vector array of XTick positions & values (numeric)
% uses current XTick values or XTick... |
a5f7838d58d1413d0c6759b17add4ba0e31aceb817c3efa205f9d58faf987f29 | MATLAB | 8,114 | 227 | function [ ] = viewTimeCourses( output_dir )
close all;
if ~exist('output_dir', 'var')
output_dir = uigetdir('please choose output directory');
end
%% load files
load(fullfile(output_dir,'TCA.mat'));
load(fullfile(output_dir,'images.mat'));
%%create TCA triplet
triplet_fig = makeTCATriplet(TCA.blue_dimension, ... |
e161dfc4380dffc370273a807ea145f804cef3ec84a8d21518f13fe9d8dcd07a | MATLAB | 8,119 | 228 | function varargout = w_FDRCorrection(varargin)
% W_FDRCORRECTION MATLAB code for w_FDRCorrection.fig
% W_FDRCORRECTION, by itself, creates a new W_FDRCORRECTION or raises the existing
% singleton*.
%
% H = W_FDRCORRECTION returns the handle to a new W_FDRCORRECTION or the handle to
% the existing si... |
449bfa6ad8ebf001e154bcd8f89905f9c2f5be7231632de5ffb019c7eda1a5c9 | MATLAB | 8,121 | 232 | function [grandavg] = ft_sourcegrandaverage(cfg, varargin)
% FT_SOURCEGRANDAVERAGE averages source reconstructions over either multiple
% subjects or conditions. It computes the average and variance for all
% known source parameters. The output can be used in FT_SOURCESTATISTICS
% with the method 'parametric'.
%
% Alt... |
687f2f781c095b5cc8fce0d2ffa431221268eb68862503420cd8b32c45124af2 | MATLAB | 8,126 | 170 | % Time-Frequency Toolbox.
% Version 1.0 January 1996
% Copyright (c) 1994-96 by CNRS (France) - RICE University (USA).
%
% Signal Generation Files
%
% sigmerge - Add two signals with given energy ratio in dB.
%
% Choice of the Instantaneous Amplitude
% amexpo1s - Generate one-sided exponential amplitude modulatio... |
c1744cb4e5a5e27d5a47c03286b072f40c3ad42a6deec1e0fbddc1a057285d78 | MATLAB | 8,126 | 253 | function varargout=wtc(x,y,varargin)
%% Wavelet coherence
%
% USAGE: [Rsq,period,scale,coi,sig95]=wtc(x,y,[,settings])
%
%
% Settings: Pad: pad the time series with zeros?
% . Dj: Octaves per scale (default: '1/12')
% . S0: Minimum scale
% . J1: Total number of scales
% . Mother: Mothe... |
7882f23f5c45472178e0969585812a0e3409d0fe3d4ba1922b171bdcdced3859 | MATLAB | 8,129 | 241 | function [xBF] = spm_get_bf(xBF)
% Fill in basis function structure
% FORMAT [xBF] = spm_get_bf(xBF)
%
% xBF.dt - time bin length {seconds}
% xBF.name - description of basis functions specified
% 'hrf'
% 'hrf (with time derivative)'
% 'hrf (with time and dispers... |
493cb5a1c6bc9d7e28c3763143bd3f78530c3515751fdb584c000b298cfd26a2 | MATLAB | 8,131 | 214 | classdef SuhDbmSplitter < SuhSplitter
properties(Constant)
MEX_FILE='mexSptxDbm';
MEX_CPP_FOLDER='eppCpp_files';
end
methods(Static)
function ok=Build
%This invokes your C++ compiler to build a Mac or Windows MEX
%file for modal separatrix algori... |
1d58562fc530aaff6462cabd563d2223d12f643125097017d95e49ef57d764b2 | MATLAB | 8,136 | 311 | function [dip,xl,xu, ifault, gcm, lcm, mn, mj] = bz_hartigansdiptest(xpdf)
% USAGE
% [dip,xl,xu, ifault, gcm, lcm, mn, mj]=HartigansDipTest(xpdf)
%
% INPUTS
%
%
%
%
% OUTPUTS
%
%
% DESCRIPTION
%
% This is a direct translation by F. Mechler (August 27 2002)
% into MATLAB from the original FORTRAN code of Hartigan's Subr... |
b9c7bec09423d6068ba555543a6352a7ca15ae0bfdf1649c795308bf7a126e0a | MATLAB | 8,138 | 306 | function [x,fval,exitflag,output] = fminsearchbnd(fun,x0,LB,UB,options,varargin)
% FMINSEARCHBND: FMINSEARCH, but with bound constraints by transformation
% usage: x=FMINSEARCHBND(fun,x0)
% usage: x=FMINSEARCHBND(fun,x0,LB)
% usage: x=FMINSEARCHBND(fun,x0,LB,UB)
% usage: x=FMINSEARCHBND(fun,x0,LB,UB,options)
% usage: x... |
a86bb1b8db6afaa63f36f47a7cbe5be7a90392906599adbdd77edae45be45583 | MATLAB | 8,144 | 297 | function [minx, fminx, num_eval, flag, last_prt] = ...
simplex(func,nx,scalev,ss_dim,setorder,minx,num_eval,...
pass,last_prt,call_string,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10)
%
% SIMPLEX - simplex implements the Nelder-Mead simplex method to minimize
% func on a subspace. It is intended for use as a routine for t... |
253d52bc39d9f2c0a3bd01ccaa76ea3f041f1ec6305b594f48d43c52ec091a43 | MATLAB | 8,146 | 130 | %% 共空间模式 | common spatial patterns (CSP) 不可在main中调用，仅可单独使用
%% one vs one Multiclass or two-classes 白化法
% how：N个类别中任意两个做CSP，共得到CN2=N*(N-1)/2个投影矩阵，对每个投影矩阵取最佳的2m个方向（前后各m个），特征矩阵为2m*N*(N-1)/2=m*N*(N-1)维
% 优点：每次计算CSP投影矩阵时，2个类别都是单纯的类别，更容易找到两类差别最大的投影方向
% 缺点：N类需要计算CN2个投影矩阵，N很大时，计算量会大大增加
% 注意：在计算CSP投影矩阵时，并非使用整个trial，而是将trial划分出... |
fc04f7a0bed15350f272a343128fcb7cbfe0b9a8bc351bb7e3411ade4f15b82b | MATLAB | 8,148 | 201 | %% Imports
addpath("HelperFunctions")
load(fullfile(DataPath, 'ForceEquiv_Pitt.mat')) % Pitt mech amp
load(fullfile(DataPath, "ForceEquiv_UC.mat")) % Mech amp est
load(fullfile(DataPath, "ForceEquiv_Control.mat")) % Mech amp est
% Plotting setup
SetFont('Arial', 9)
scatter_size = 30;
line_width = 1.5;
force_ratio = 0.... |
029253772b05361dd0d1c7c94a34e5737af8cf20eaaee03b8ad386c192d39a1e | MATLAB | 8,153 | 269 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function [epo] = srmr_prepro_latepotentials_esg(subject, condition, is_restcontrol, new_ref, srmr_nr)
%% prepro ESG with broadband filtering (loop 6 with different filtering)
% load ecg-clean ESG data
% filtering from 0.5-400 Hz + 50 Hz notch
% epoch
% remove bad channels
... |
caa3f50ea611d4e2039bd78edef842390be275c14501c90f7fc4cde209318eeb | MATLAB | 8,158 | 196 | % PopulateResponseVariables.m
% Sarah West
% 6/6/22
% Run with RunAnalysis, on each mouse. Not doing anything fancy with the
% input loops because this is a very specific use-case function.
function [parameters] = PopulateResponseVariables(parameters)
MessageToUser('Populating ', parameters);
% If verticall... |
e5fb4dc0ecd86c80fb3baff4bc0bfa02a61b8bccee3aa36dff859b5469fa77fe | MATLAB | 8,158 | 323 | function x = build_matrix_regressors(behav,ephys)
% x = build_regressor_matrix(behav)
%
% This function generates the matrix of regressors used to compute
% the pulse-evoked and other kernels describing neural activity.
%
% GLOBAL VARIABLES: this function assumes the definition of global
% variable "glm" that defines ... |
7645d2f61cf065cddf85a37da288b7889dc3ee5f2083e0507a7abeac0af26f28 | MATLAB | 8,164 | 194 | function [] = proportion_of_unique_place_fields(folders,option,method)
load('Tables\subsets_of_cells.mat')
total_number{1}(1:3) = 0;
total_number{2}(1:3) = 0;
for nfolder = 1:length(folders) % Get total number of replay events
for nshuffle = 1:2 % 1 is original and 2 is global remapped
session_total_numb... |
844c61fcc1ddbdd9890ef5ead91f30fdabbf3c4e6834f65c5bccd2f9eb9d639c | MATLAB | 8,164 | 321 | % Field Trip-related test scripts - Synthetic FT data - Plotting
%
%
% Includes.
% FIXME - Assume init has already been called.
%
%
% Configuration.
% Scatter-plot ranges.
plotband = [ 0.5 * bandtheta(1) 1.5*bandgamma(2) ];
plotdur = [ 0 7 ];
plotamp = [ 1e-2 10 ];
% FIXME - Expand ranges, in case of plotting ... |
d31b7485bdbb5b7bc025946a54f22f19a9a2a38ce30652bbb5d19a23f0cb938e | MATLAB | 8,167 | 180 | function [H,Ip] = imagesAlign( I, Iref, varargin )
% Fast and robust estimation of homography relating two images.
%
% The algorithm for image alignment is a simple but effective variant of
% the inverse compositional algorithm. For a thorough overview, see:
% "Lucas-kanade 20 years on A unifying framework,"
% S. B... |
7461877cae5b3b7ad5ab877166f8ea25229561acc24b8b05d94a11fab8750207 | MATLAB | 8,170 | 272 | function [tfr,t,f]=tfrspbk(X,time,K,nh0,ng0,fmin,fmax,N,trace);
%TFRSPBK Smoothed Pseudo K-Bertrand time-frequency distribution.
% [TFR,T,F]=TFRSPBK(X,T,K,NH0,NG0,FMIN,FMAX,N,TRACE)
% generates the auto- or cross- Smoothed Pseudo K-Bertrand
% distribution.
%
% X : signal (in time) to be analyzed. If X=[X1 X2], TFRSPB... |
1af9cdb20a73aa65ef8b2dc6062c3b6d89b1fdcc2f3a6cac9be5011630166e10 | MATLAB | 8,171 | 182 | function decRes = summary_decoding_results(p)
%
% - This code is written for summarizing multiple ROI decoding analysis.
%
%
% called from emotion2020_analysis_BATCH
%
%% setting for ensemble decoders
thval = 0.095; % threshold for ROI selection
nAllrois = length(p.roiDescrip);
%% construct ensemble decoder
for scori... |
b3acae74e1ed321cb65bd3894bf7205a4b4994ecca67e0b98dcae969e12a9a4d | MATLAB | 8,177 | 233 | % Example 2
% Script #2
%
% Script_02_IMAP_Beta_v2_2c.m
%
% This script reads measured values froma a spreadsheet previously created
% by script #1 (Script_01_IMAP_Beta_v2_2c.m), and then it
% generates violin plots.
%
% ----------------------------------------------------------------------
% ... |
a9179a16892d8af654e192d365ce5bb9ec9e485b348251a0231607d41be1465d | MATLAB | 8,180 | 247 | function write_wobj(OBJ,fullfilename)
% Write objects to a Wavefront OBJ file
%
% write_wobj(OBJ,filename);
%
% OBJ struct containing:
%
% OBJ.vertices : Vertices coordinates
% OBJ.vertices_texture: Texture coordinates
% OBJ.vertices_normal : Normal vectors
% OBJ.vertices_point : Vertice data used for point... |
837198a681ba0bb0e4207879eedb4f048b3f506d563e89308bc5b543702e40dd | MATLAB | 8,181 | 150 | % align ImageArray and keep result in ImageArray_Reg
%[ImageArrayReg_AllImages DeltaX_First DeltaY_First MaxValue_First BoutonArray] = ReadGoodImages_LapseRegXY_ArrayRegIndBoutSel_Crop_Fine_DifFirst([StackSaveName,StackSaveNameSuffix], StackFileName, GoodImages, FilterSize, FilterSigma, AlignRegion, MaxShiftX, MaxShift... |
ff5dd4cf9efa75b8566b4a844dc860bf22555cc5de6b6394333ae6309787c454 | MATLAB | 8,183 | 251 | function [H, Z, S, psi] = sfactorization_wilson(S,freq,Niterations,tol,fb,init,checkflag,stabilityfix)
% SFACTORIZATION_WILSON performs multivariate non-parametric spectral factorization on
% cross-spectra, based on Wilson's algorithm.
%
% Usage : [H, Z, S, psi] = sfactorization_wilson(S,freq);
%
% Inputs : S (1-side... |
92f142e6d7248b7c80ba5c4b59d8e4c022d50ec9dedefe876caa5aaa36ebc560 | MATLAB | 8,184 | 172 | classdef CBIG_preproc_single_subject_unit_test < matlab.unittest.TestCase
%
% Target project:
% CBIG_fMRI_Preproc2016
%
% Case design:
% CBIG_fMRI_Preproc2016 already have unit tests, here we
% call its "single_subject" unit test and automatically
% make j... |
edf072857632297614085e075a14de796471fdf9644d23ba13efbfeadb68c268 | MATLAB | 8,184 | 214 | function [U,varargout] = hfmm3d(eps,zk,srcinfo,pg,varargin)
% HFMM3D FMM in 3D for Helmholtz (acoustic frequency-domain) kernel.
%
% [U,varargout] = hfmm3d(eps,zk,srcinfo,pg,varargin)
%
% Helmholtz FMM in R^3: evaluate all pairwise particle
% interactions (ignoring self-interactions) and possibly
% interactions w... |
873278b80d5c777e7009b718a5a7face0b4a4b956fb9f67d46d1adedd5e85d90 | MATLAB | 8,185 | 160 | %% Create HBM2024 table
% _________________________________________________________________________
%
% Robert Dahnke & Polona Kalc
% Structural Brain Mapping Group (https://neuro-jena.github.io)
% Departments of Neurology and Psychiatry
% Jena University Hospital
% _____________________________________________________... |
985ae9cffd73382d2deb6cb1b4d36476e125d17b196784913c0132f2997fdbfa | MATLAB | 8,187 | 247 | function CBIG_KRDNN_regress_from_behaviour(setup_file)
% CBIG_KRDNN_regress_from_behaviour(setup_file)
%
% This function regress age, gender and motion from the behavioral measures.
% For age and gender, we did not regress out any thing.
%
% Inputs:
% - setup_file
% Path of the setup file (.txt file).
% set... |
212852892d042f73319ba1afd0468e536e68da3aa2ccbe16c75ac5215100ccd5 | MATLAB | 8,192 | 201 | clear
close all
clc
load experimentalData.mat
num_mats = 1; % Number of measurement matrices
num_runs = 10; % Number of runs per measurement
num_images = 8;
image_names = {'Parrots', 'barbara', 'boats','house','foreman', 'cameraman', 'lena256'};
% image_names = {'Parrots'};
% image_names = {'Monarch'};
output_folder_0... |
cab148e77a4eeb274a3d0d854d95d5a9ab63eb38f5b23e49ead36ff4fe5c80b7 | MATLAB | 8,192 | 140 | %% Description
% Here we show an example of how to model fluence rate dependent optical
% properties. We have a beam of light incident exactly on the interface
% between two saturable absorber materials. Material 1 has an absorption
% coefficient that reduces with fluence rate, while for material 2 both the
% absorptio... |
d5dbe1dae2713ab30841bc62f4c7ac8d22de4ad02f61d1ad2b831eaa591e4414 | MATLAB | 8,192 | 189 | function [times, chans] = ms_detect3(X,opts)
%MS_DETECT3 - Detect super-threshold events in a raw/preprocessed dataset
%
%Consider using mscmd_detect
%
% Syntax: [times, chans] = ms_detect3(X,opts)
%
% Inputs:
% X - MxN array of raw or preprocessed data (M channels by N timepoints)
% opts.detect_interval - minim... |
0e08adb88330605a75102e1fa3442cc0c3a224562539e49e7742cc0d172289fa | MATLAB | 8,195 | 250 | function [out] = RFT_main(X,options,verbose)
% applies RFT to an input 1D-field X sampled on a regular lattice
% function [out] = RFT_main(X,options,verbose)
% RFT (Random Field Theory) allows one to derive the FWE-corrected p-values
% on some topological features of the field (e.g., local peaks and
% upcrossing thresh... |
732838c6df33107c6553bc94a426ee0da474fe4ed005d21affdd58f68957083d | MATLAB | 8,197 | 404 | % merges all .crabsort files and returns spike time info
function data = consolidate(varargin)
% options and defaults
options.DataDir = pwd;
options.dt = 1e-3; % 1 ms
options.nerves = {};
options.neurons = {};
options.stack = false;
options.DataFun = {};
options.ChunkSize = NaN; % seconds
% validate and accept opt... |
27875f95ba85e4e5943a36079aca09cbc96e442481e10fc749e42078a84913e4 | MATLAB | 8,199 | 210 | %Purpose: Implement Hungarian Matching Algorithm for MSHBM and k-means parcellations
%parcellations.
%Inputs: MSHBM and k-means parcellations (run directly following
%parcellation BEFORE visualization)
%Outputs: Individual parcellations with matched values (e.g., network 1 is the same across parcellation methods.
%
%... |
5eef7ed96de2d4871075c6ea3f5fcd208d2dfcee045d5f8a144f029f9d68c13b | MATLAB | 8,200 | 250 | function [simulated] = ft_dipolesimulation(cfg)
% FT_DIPOLESIMULATION computes the field or potential of a simulated dipole
% and returns a datastructure identical to the FT_PREPROCESSING function.
%
% Use as
% data = ft_dipolesimulation(cfg)
%
% The dipoles position and orientation have to be specified with
% cfg... |
c2f98d1e3756a8fd8859aee1881fe8de50afcd87e3fea486f2e8fad834441acf | MATLAB | 8,200 | 258 | function rd_MEG_TAPilot(subjectID, run)
commandwindow
% rd_MEG_TAPilot(subjectID, run) % new input
%
% rd_MEG_TAPilot(run, stimfile)
% rd_MEG_TAPilot(3, 'taDetectDiscrim')
% MEG SSVEP left/right flicker rate x attention expt
% with exo targets
% ------
% Run time per experiment = 63 seconds
% 9 blocks with 7 s... |
af3bfe86e9410903b527b275248f80b4838ed21af586e657f460cd2be7840d37 | MATLAB | 8,201 | 299 | function hfig = ShortcutsDialog(obj)
lObj = obj.labeler_;
W = 500;
H = 800;
buttonw = 120;
sc = lObj.getShortcuts();
tags = fieldnames(sc);
edit_shortcuts_data = cell(numel(tags),3);
isvalid = false(numel(tags),1);
for i = 1:numel(tags),
[edit_shortcuts_data{i,1},isvalid(i)] = tag2desc(tags{i});
edit_shortcuts_d... |
d572fc03f08a6edda7a7afc4d0785f2b74739403181568e25482f4d1e85f806f | MATLAB | 8,205 | 286 | function hatch(obj,angle,color,style,step,width)
% HATCH Hatches a two-dimensional domain.
% Somewhat similar to the FILL command but fills the closed
% contour with hatched lines instead of uniform color.
% The boundary line(s) must be created prior to this command
% and its handle(s) specified by OB... |
c4d0e8fb2c54cf1fbced5f8a4d3d9a3ccc04b29af9b07a4bd631ac5b48e9619d | MATLAB | 8,209 | 229 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
%% SRMR1_03_groupAnalysis
% group statistics and figures
clear; clc
delete(gcp('nocreate')) % clear parallel pool
%% variables that need to be changed
% step
step_number = 14; disp(['step_number = ' step_number])
% sampling rate
sampling_rate = 1000;
% subjects
subjects... |
6ee4621e6efd124797fa761786e8212c4fde44e0e373fdd932a3ebbcfe28c7c6 | MATLAB | 8,211 | 217 | clear all
trialCOUNT = 1;
b = [0, 0.4470, 0.7410];
o = [0.8500, 0.3250, 0.0980];
y = [0.9290, 0.6940, 0.1250];
p = [0.4940, 0.1840, 0.5560];
g = [0.4660, 0.6740, 0.1880];
a = [0.3010, 0.7450, 0.9330];
r = [0.6350, 0.0780, 0.1840];
external_stimulation = 3; %0: neither CS nor US; 1: only CS; 2: only US; 3: US+CS
cond... |
d482ce21d4de9efc7afbea9ab405b9e35742ba9f00f097e264a2ff7bee58f029 | MATLAB | 8,214 | 259 | function meg_Fig5a_bootstrappedFFT
% function meg_Fig5a_bootstrappedFFT
% see meg_fftPlayground for full figs
% also makes supplemental Fig 2 (set timeOI to 'baseline')
%% Figure settings
titleVis = 0; % if title vis off, then will plot for appropriate manuscript size
showN = 1; % show n = X annotation
figFormat =... |
2e54f5f532f67f88cff1866e39708d5b7a63db020a3771721c876172dc05e65e | MATLAB | 8,215 | 255 | classdef Jab < handle
% .jab files
methods (Static)
function J = load(jabfile)
% J = load(jabfile)
%
% J: Modernized Macguffin object
assert(ischar(jabfile) && exist(jabfile,'file')==2,...
'Cannot find jabfile ''%s''.',jabfile);
J = loadAnonymous(jabfile);
i... |
d745f02d196125734130d59764da70179c5b2543d0a466fed4532da82f99b608 | MATLAB | 8,215 | 274 | %% CLUSTER ANALYSIS
% Peak location- start by map of responses
% find segments for words/non vs noise
DIRcluster=[DIRresults, '/cluster_analysis'];
mkdir(DIRcluster)
task_offset = xlsread([DIRscript, '/event_file_name_sound_offset_BOTH.xlsx'],1,'AJ3:AK590');
xbee_offset = 34;
wordle = [];
max_value = 10;
min_value = ... |
4ed1f0967b3ff9871f7ef30dbda3a33668cca003382c76f43176f6db5814ea85 | MATLAB | 8,218 | 235 | function [] = randnetPreplay(modelParam, network, V_m, G_in, network_spike_sequences, varargin)
% plots.randnetPreplay(modelParam, network, V_m, G_var(ithTest).G_in, network_spike_sequences)
%
% Plots basic simulation results from randnet.m
%
% Inputs:
% - modelParam: the model parameter structure
% - network: the ... |
6a2914b24034896e72d52a9e9d45679ace88ca0dfdef595092d70d80cdff4924 | MATLAB | 8,220 | 230 | function [data] = ft_determine_coordsys(data, varargin)
% FT_DETERMINE_COORDSYS plots a geometrical object, allowing you to perform
% a visual check on the coordinatesystem, the units and on the anatomical
% labels for the coordinate system axes.
%
% Use as
% [dataout] = ft_determine_coordsys(datain, ...)
% where th... |
c72c936e4faa285d4baf26f38487b0af28c5cdecc3b63cb86c3fb17145e69168 | MATLAB | 8,222 | 250 | function [freq] = ft_freqanalysis_mvar(cfg, data)
% FT_FREQANALYSIS_MVAR performs frequency analysis on
% mvar data, by fourier transformation of the coefficients. The output
% contains cross-spectral density, spectral transfer matrix, and the
% covariance of the innovation noise. The dimord = 'chan_chan(_freq)(_time)... |
7b9b6278135a73e77c5d17af969d6bb4d4ab347e304d2673863eac1e47f67225 | MATLAB | 8,229 | 249 | % Phase locking value for ripple band
mkdir([DIRresults, '/Corr']);
DIRresultsCorr = ([DIRresults, '/Corr']);
set(0,'DefaultFigureVisible','on');
for z = 1:num_groups
clear LowGammaData_70_180 smooth_envelope_70_180 CORR_data CORR_matrix phase_envelope_70_180
the_channels = (big_list_indexes{z});
size... |
fb1756c4678ab9a08938068741a0148fce77bde8114473de0a0a7e5cad3c1dfe | MATLAB | 8,230 | 235 | function [H, Z, S, psi] = sfactorization_wilson2x2(S,freq,Niterations,tol,cmbindx,fb,init,checkflag,stabilityfix)
% SFACTORIZATION_WILSON2X2 performs pairwise non-parametric spectral factorization on
% cross-spectra, based on Wilson's algorithm.
%
% Usage : [H, Z, psi] = sfactorization_wilson(S,freq);
%
% Inputs : S ... |
f491b59a38064e6d6c6d25ca3f76b235e14571001b8bcc04937a75a3040034aa | MATLAB | 8,231 | 221 | function [CellClass] = bz_CellClassification (basePath, varargin)
% Loads cell spike waveforms from the local folder, characterizes them and
% separates them into E vs I cells. Manual verification based on clickable
% gui from Shige.
%
%INPUTS
% baseName - basename of files in the local folder (default: pwd)
% 'know... |
b406c5fc2aeaf2a3041e339aace39b4e244979fb87d73a6d62c538c70ca5cf11 | MATLAB | 8,232 | 208 | function [g, region] = gradients_n(a, varargin)
%GRADIENTS_N Estimate gradients in N dimensions with Gaussian smoothing
% [G, REGION] = GRADIENTS_N(A) estimates the gradients of A using centred
% differences.
%
% A is an N-D array of class double or single. Its dimensionality D
% is given by NDIM... |
c13021f577592285161b255d9461d5c1f0b42d402e60ff098a5964a453a34e2d | MATLAB | 8,237 | 219 | classdef StandardFeatures < dspace_features.AbstractFeatures & dspace_features.AbstractHeavyFeatures
% Coordinates backed by cell array or numeric matrix. numeric types float,
% double and sparse are supported.
%
%
%
%<PRE>
% This file is part of dspace-core.
%
% Copyright (C) ... |
2534daf2f0e799d566c4b27cbff2f037c5b246fd7b70ed5d612491fad134ae06 | MATLAB | 8,238 | 195 | function glacfg = paramInitGLADpar(cfg)
% Created by Xinan Chen on 04/26/2021.
% This function returns parameters corresponding to the input 'data_name' and analysis type
% Output: 'gladcfg' := structure containing parameters for GLAD analysis
%%
glacfg.do_masked = 1;%1 if ensure everything is inside mask before sa... |
748ce7c52054a0a33fe65400828d5a30aa2dd3ce2e8b5970344b47a0c8924aa2 | MATLAB | 8,240 | 260 | function [posterior,suffStat] = VBA_GN(y,posterior,suffStat,dim,u,options,flag)
% regularized Gauss-Newton optimization of variational energies
% function [posterior,suffStat] = VBA_GN(y,posterior,suffStat,dim,u,options,flag)
%
% This function computes a gauss-Newton scheme on the variational energy of
% either hidden ... |
001e5d7085ee5a1ba98094c6903c1c6ec81a3184bca624bfacdd63de6b51af62 | MATLAB | 8,242 | 198 | % This is a demo for a source-analysis toolbox;
% you need names your EEG-electrodes and some functional
% result like a potential at a time point, a CSP-pattern,
% a cross-spectrum, etc.
%
% you can
% 1. view field and cross-spectra;
% 2. make a forward calculation
% 3. make inverse calculations (dipole fits,MUSIC,... |
cd34a64bddf24ab59a961167551a52dfb92012da246cfddfb8f2f0bc8052f074 | MATLAB | 8,245 | 197 | % Noam Saadon-Grosman
% August 2020
% This code computes the geodesic distance between each vertex to the closest vertex in area
% 3a. We use an online code (https://code.google.com/archive/p/geodesic/) to compute the distance, separately for each
% gross anatomical region. The computation is for the right and then... |
20f3333dc78214f0199291c8fc441c54490b44ae3c762e61f8dd82c242306b2c | MATLAB | 8,252 | 251 | function edited = RecordingSettings(recording, varargin)
handles.recording = recording;
isAudio = isa(handles.recording, 'AudioRecording');
isVideo = isa(handles.recording, 'VideoRecording');
if isAudio
titleString = 'Audio Settings';
fileLabel = 'Audio file:';
formatLa... |
dbc06c16631e053878bab69b05edd733dd328ee8f21b07578061675641d9cd8f | MATLAB | 8,258 | 227 | %% Hierarchical Kalman filter (HKF)
function [state, genModel] = HKF(u, z, params)
% This is an implementation of a hierarhcical Kalman filter model.
% Prior state estimation (xhat_) is computed based on actions u and the
% estimated generative model parameters Ahat and Bhat. Posterior state
% estimation (xhat) is ... |
be0416536c4c1312d031f54b7926e79530f4504af80db7466b2a4b6cdd01bb7f | MATLAB | 8,260 | 252 | function [simulated] = ft_dipolesimulation(cfg)
% FT_DIPOLESIMULATION computes the field or potential of a simulated dipole
% and returns a datastructure identical to the FT_PREPROCESSING function.
%
% Use as
% data = ft_dipolesimulation(cfg)
%
% The dipoles position and orientation have to be specified with
% cfg... |
778b429dc613923e52f168a33df200261725eddd13ca77f946290601e796a98e | MATLAB | 8,262 | 246 | function [out] = VBA_spm_eeg_displayECD(Pos,Orient,Var,Names,options)
% Plot dipole positions onto the SPM canonical mesh
% FORMAT [out] = spm_eeg_displayECD(Pos,Orient,Var,Names,options)
%
% IN (admissible choices):
% - Pos: a 3xndip matrix containing the positions of the dipoles in
% the canonical frame of refere... |
a9adeb388fed74e15dcdf30e7e4cac73089ac13aafc99f7b7f47d83c77f65668 | MATLAB | 8,262 | 295 | function res = imOverlay(img, varargin)
%IMOVERLAY Add colored markers to an image (2D or 3D, grayscale or color)
%
% Usage
% OVR = imOverlay(IMG, MASK);
% OVR = imOverlay(IMG, MASK, COLOR);
% OVR = imOverlay(IMG, MASK1, COLOR1, MASK2, COLOR2...);
% OVR = imOverlay(IMG, RED, GREEN, BLUE);
%
% Description... |
cde6abd8edebf816f0b1497f2e730563d067ed3e08e4120e5983879d4932d110 | MATLAB | 8,266 | 195 | medA = load(fullfile(saveLoc, 'for_plots_mediation_norm_to_se'));
uni_s = unique({medA.leverage.signal});
labels = replace(uni_s,'w_','');
m = {medA.leverage.mediator};
s = {medA.leverage.signal};
X = nan(length(uni_s));
medCho_other_ForRatio = nan(2, 8, 8); medCho_raw_ForRatio = medCho_other_ForRatio; medR... |
b923a83a602be2a31b22027718d18cc1c8f806f78f59319078be722e64ffa4bf | MATLAB | 8,268 | 194 | function [VMHCBrain_AllWindow, zVMHCBrain_AllWindow, Header] = y_VMHC_Window(WindowSize, WindowStep, WindowType, AllVolume, OutputName, MaskData, IsNeedDetrend, Band, TR, TemporalMask, ScrubbingMethod, ScrubbingTiming, Header)
% [VMHCBrain_AllWindow, zVMHCBrain_AllWindow, Header] = y_VMHC_Window(WindowSize, WindowStep,... |
815b64c26d9c3ee01451a79d2e8e2d006383e3c7c180e6668ff993211082c6f4 | MATLAB | 8,273 | 262 | function data_to_send = loc_list_extract_features(data)
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
counter = counter+1;
data_to_send{counter} = data{i};
end
end
if exist('data_to_send','var')
f = waitbar(0,'Please Wait...');
fo... |
0ddc8e00d22f07c063a40cae62b89a600327d213e4e87eee96c43a1f5e89e505 | MATLAB | 8,275 | 236 | % function lineStyles = linspecer(N)
% https://de.mathworks.com/matlabcentral/fileexchange/42673-beautiful-and-distinguishable-line-colors-colormap
% This function creates an Nx3 array of N [R B G] colors
% These can be used to plot lots of lines with distinguishable and nice
% looking colors.
%
% lineStyles = linspec... |
25d00466136823100f249fd9e40a756e15ef3d0d0c6cf98787353691a2f187d7 | MATLAB | 8,275 | 212 | function [data] = ft_appenddata(cfg, varargin)
% FT_APPENDDATA concatenates multiple raw data structures that have been preprocessed
% separately into a single raw data structure.
%
% Use as
% data = ft_appenddata(cfg, data1, data2, data3, ...)
%
% The following configuration options are supported:
% cfg.keepsampl... |
601f2bf18d2a11e410b55aa2eb40adec29d5907cee7a20f872d9f2643e65442d | MATLAB | 8,275 | 244 | function [posterior, out] = demo_QlearningAsymmetric (data)
% // VBA toolbox //////////////////////////////////////////////////////////
%
% [posterior, out] = demo_QlearningAsymmetric ([data])
% Demo of Q-learning with asymmetric learning rates for positive and
% negative predictions errors.
%
% This demo implements th... |
56c928f876d2451c9989f48953cdd7a4501e06b3fa85bcdb97b8f8dc4acb0364 | MATLAB | 8,277 | 206 | function [cfg movement] = ft_detect_movement(cfg, data)
% FT_SACCADE_DETECTION performs micro/saccade detection on time series data
% over multiple trials
%
% Use as
% movement = ft_detect_movement(cfg, data)
%
% The input data should be organised in a structure as obtained from the
% FT_PREPROCESSING function. The ... |
19ae484c8c119bd42d7383f3bab3b08bdb0fa494fc52c426fa135ab807e7b0ee | MATLAB | 8,279 | 300 | function chewDat = ChewCheck(sesDir, varargin)
% Loads data segments on rewarded trials to look for chewing artifacts
chanName = 'ECoG1';
trNum = 1;
timeRange = [-1 20];
band1 = [100 800];
band2 = [3 8];
biteThr = 10000;
minBiteInt = 0.01;
maxBiteInt = 0.5;
minBiteDur = 0.01;
maxBiteDur = 0.5;
for i = 1 : 2 : lengt... |
9a44179df721b5775271437ec6ce45e36efd55d760b43c90edf14d597c87380b | MATLAB | 8,279 | 213 | %% Statistical analyses for HbO (main findings)
% define representative value
clear all
clc
load incongruent_allsub_2probe_final.mat
load congruent_allsub_2probe_final.mat
% exclude unusable subject data
congruent_allsub_2probe_final([6 8 14 22])=[];
incongruent_allsub_2probe_final([6 8 14 22])=[];
% for congruent co... |
d2eff7a485d1c3c5721fbd4a2b582506f307f7c5c34b0d0ac94431ddb9d07150 | MATLAB | 8,280 | 198 | function varargout = seqWriterPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow writing of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (swp=seqWriterPlugin):
% h=swp('open',h,fName,info) % Open a seq file for writing ... |
6dcd067c69319babfc6cdcdfa2cd702362accbe6d66c25632ad94d90cef0d2a8 | MATLAB | 8,281 | 239 | function res = get2DpointsFromKine(varargin)
res = struct;
[headDataFname,video1Fname,video2Fname,DEBUG,debugfig] = ...
myparse(varargin,'headDataMatFile','',...
'view1VideoFile','','view2VideoFile','',...
'debug',0,...
'debugfig',[]);
npts = 5;
%code snippet to demonstrate how to get 2D head position data ... |
c36aa5f91db9a2c894cfa616134e50ed948e1cf922ea9c7babd8e605254cdf60 | MATLAB | 8,281 | 208 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
%
% Description:
% This M-file creates MuscleMP corresponding to the muscle mechanical
% properties and musculotendon lengths in 3D and... |
38922b0abf9c9420c20832ebd56fab86abb52ca48dda3e08b140a29066316564 | MATLAB | 8,284 | 248 | function extract_replay_info_batch(folders)
shuffles={'PRE spike_train_circular_shift','PRE place_field_circular_shift','POST place bin circular shift','POST time bin circular shift','POST time bin permutation'};
% Spike shuffle
[log_odd] = extract_ground_truth_info(folders,'original','wcorr',shuffles{1},3,2.1)
cd gr... |
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