sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
056e9fc9761b535ac2245eae06af7f0d6bc34b8cc5ac3765898b2ed8fc63698d | MATLAB | 3,780 | 86 | function Points = Find_Distance_From_Midline(Points,Axes,Scale_Factor,Step)
% This function computes the signed distance of each point from the midline.
% Dorsal is defined as positive distance and ventral as negative.
% The midline points are given from head to tail.
% Step=1 indicates that the other axes (besid... |
fa5e4ffe032072e6b61490f80bfd7acb764182608c93431cb21c3393948f99e8 | MATLAB | 3,783 | 83 | function [tapers,pad,Fs,fpass,err,trialave,params]=getparams(params)
% Helper function to convert structure params to variables used by the
% various routines - also performs checks to ensure that parameters are
% defined; returns default values if they are not defined.
%
% Usage: [tapers,pad,Fs,fpass,err,trialave,para... |
f4f170813e556003e2842ea7cc6f6bf191761ee7b3063d67775bbe77cc7436f2 | MATLAB | 3,785 | 121 | function result = savepathonly(outputfile)
%SAVEPATHONLY Save the current MATLAB path to the file pathdef.m
%
% SAVEPATHONLY saves the current MATLAB path to the current pathdef.m file.
%
% SAVEPATHONLY(OUTPUTFILE) saves the current MATLAB path to the
% file specified by OUTPUTFILE.
%
% This is essentially a pa... |
5e1bd7154fc217458b6f682607b5ee97663854319be287d518c165c4e9426c01 | MATLAB | 3,786 | 136 |
[cols,alpha] = chooseColors;
%% plot removal from time dependent decoders
for config = 1:4
figure('Position',[100 100 300 300])
hold on
% set lims and labels
xlim([0 21])
set(gca,'XTick',[0 5 10 15 20])
set(gca,'XTickLabel',-3:1)
xlabel('Time (s)')
ylabel('Accuracy (%)')
% indi... |
8d543601aa082f6a10c7da566feecc970e37ef5755319f7558ac3de4919d758d | MATLAB | 3,786 | 130 | function [inspk] = wave_features(spikes,par)
%Calculates the spike features
scales = par.scales;
feature = par.features;
nspk = size(spikes,1);
ls = size(spikes,2);
if strcmp(par.max_inputs,'all')
par.max_inputs = ls;
elseif par.max_inputs < 1
par.max_inputs = ceil(par.max_inputs*ls);
end
% CALCULATES FEATURE... |
db6715d9760df5523ee9364c355082b35c95d7a5e9922e9a0a9c9f2f8fc7a575 | MATLAB | 3,786 | 92 | function [y_med, y_mean] = ecg_den_wavelet(x, varargin)
% ecg_den_wavelet - A wavelet-based ECG denoiser using majority voting or
% averaging between multiple wavelet denoising configurations.
%
% Syntax:
% [y_med, y_mean] = ecg_den_wavelet(x)
% [y_med, y_mean] = ecg_den_wavelet(x, params)
%
% Inputs:
% x: Matr... |
4c80682577801dadfcae61ab2ef4cbf2964a993b522642e290b3d3644e08b4bd | MATLAB | 3,790 | 130 | function [Cell]=mnl_CalculateSomaValues(Cell,Scale,cData,BkgMean)
%% Step 1 - Get the voxels involved in each soma
dim=size(cData);
Scount=size(Cell,2);
for i=1:Scount
NumPoints=size(Cell(i).dxyz,1);
for j=1:NumPoints
%Convert the surface points to voxels
dxyz(j,1)=round(Cell(i).dxyz(j,1));
... |
dd7d5615d5160afc22b9f79f5921c9f3105963a56bae13139581ef09b57140c0 | MATLAB | 3,791 | 113 | function structGAM=pyGAM2struct(pGAM)
stats=struct(pGAM.statistics_);
stats.pseudo_r2=struct(stats.pseudo_r2);
% stats.cov=double(stats.cov);
stats.GCV=[];
stats.cov=[];
stats.edof_per_coef=[];%struct(stats.edof_per_coef);
stats.m_features=int64(stats.m_features);
stats.n_samples=int64(stats.n_samples);
stats.... |
e09d8aba64a301267ca4303421d2d8f27a57011862c5184eae3f33e15e453efb | MATLAB | 3,792 | 130 | function [s_cap,n_regions] = eq_caps(dim,N)
%EQ_CAPS Partition a sphere into to nested spherical caps
%
%Syntax
% [s_cap,n_regions] = eq_caps(dim,N);
%
%Description
% [S_CAP,N_REGIONS] = EQ_CAPS(dim,N) does the following:
% 1) partitions the unit sphere S^dim into a list of spherical caps of
% increasing colatitude ... |
3f2b9d04f9dd5f7133aad97938f908c6f8a7de35d298d5787883cee84692b896 | MATLAB | 3,793 | 143 | function xlswritefig(hFig,filename,sheetname,xlcell)
% XLSWRITEFIG Write a MATLAB figure to an Excel spreadsheet
%
% xlswritefig(hFig,filename,sheetname,xlcell)
%
% All inputs are optional:
%
% hFig: Handle to MATLAB figure. If empty, current figure is
% exported
% filename (string) Nam... |
991685bf654e7a937befc8bf2945b55c90c85d09bc57f04c5b8657afde56ac07 | MATLAB | 3,794 | 139 | % Simulated scatter plots and ICA
%
clear;
close all;
a = 2;
b = 2;
% t = asin(1/b) + [0:.01:18*pi 0];
% t = asin(1/b) + [0:.01:2*pi 0];
t = 0:.01:20*pi;
N = length(t);
r = a * (1-b*sin(t));% + .2*randn(1,length(t));
[x,y] = pol2cart(t,r);
z = 2*cos(t);
% z = t/10;
A0 = [-1 1 -2; 1 1 1; -.2 1 1];
x... |
3810acf5f13595daebbc371d8d37a99607d2ac459207d3e574af0b9f7ab9a269 | MATLAB | 3,796 | 100 | function varargout = wave_clus_aux1(varargin)
% WAVE_CLUS_AUX1 M-file for wave_clus_aux.fig
% WAVE_CLUS_AUX, by itself, creates a new WAVE_CLUS_AUX or raises the existing
% singleton*.
%
% H = WAVE_CLUS_AUX returns the handle to a new WAVE_CLUS_AUX or the handle to
% the existing singleton*.
%
% ... |
377a86a18e34c5eef7d9b817a9376c39d21296efe4345e28f6fcf06f135af5f8 | MATLAB | 3,797 | 111 | % Control script to get info on bursts occurance in time relative to single
% peaks (Hung / Bernardi method).
clear
clc
% close all
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Parameters
P = analysisParameters();
Participants = P.Participants;
Sessions = P.Sessions;
Paths = P.Pat... |
1e1bb70a25e386c4cf8cf0d90bc65b09bf7a3e7ca3fc4bc2d6e5ba5b4207adb9 | MATLAB | 3,799 | 137 | function ha = plotFitPars(fitPars,t,climsXYZ,climsRTP,isVertical)
% function ha = plotFitPars(fitPars,t,climsXYZ,climsRTP,isVertical)
%
% 16/3/16 - Added a little trick so that 'isVertical' can also be of the
% form [handle1 handle2] for the two subplots to plot into
%
% 16/6/23 - New hack so that if 'isVertical' is a ... |
e9f58cb170e7d967631ee03ae22e1f5850b086d34c330d6874e1c618c14b0ef8 | MATLAB | 3,799 | 100 | function varargout = wave_clus_aux2(varargin)
% WAVE_CLUS_AUX1 M-file for wave_clus_aux.fig
% WAVE_CLUS_AUX, by itself, creates a new WAVE_CLUS_AUX or raises the existing
% singleton*.
%
% H = WAVE_CLUS_AUX returns the handle to a new WAVE_CLUS_AUX or the handle to
% the existing singleton*.
%
% ... |
c94512c14e26dde12061265db21921cde09e48944140a437d941895da4e44671 | MATLAB | 3,800 | 100 | function varargout = wave_clus_aux5(varargin)
% WAVE_CLUS_AUX1 M-file for wave_clus_aux.fig
% WAVE_CLUS_AUX, by itself, creates a new WAVE_CLUS_AUX or raises the existing
% singleton*.
%
% H = WAVE_CLUS_AUX returns the handle to a new WAVE_CLUS_AUX or the handle to
% the existing singleton*.
%
% ... |
772d2e507e1d694ba6d415791a9759d251f8f1238984d16f3497a076e3780609 | MATLAB | 3,801 | 127 | function hb_res = hb_det_2(varargin)%ecg, threshold, inverse, bp, use_bp)
%HB_DET_2 Summary of this function goes here
% Detailed explanation goes here
ecg = varargin{1};
threshold = varargin{2};
inverse = varargin{3};
if length(varargin) > 3
bp = varargin{4};
use_bp = varargin{5};
if isempty(bp)
... |
8374fcbfccf6244fc8e7e37683e7d58f6ebeeba85f5186e4353f16231c5fdd05 | MATLAB | 3,801 | 100 | function varargout = wave_clus_aux4(varargin)
% WAVE_CLUS_AUX1 M-file for wave_clus_aux.fig
% WAVE_CLUS_AUX, by itself, creates a new WAVE_CLUS_AUX or raises the existing
% singleton*.
%
% H = WAVE_CLUS_AUX returns the handle to a new WAVE_CLUS_AUX or the handle to
% the existing singleton*.
%
% ... |
c900b3af9f13a1d16d15fee5c3217b8019ba883d1243f593dcb4d0a33732641c | MATLAB | 3,801 | 100 | function varargout = wave_clus_aux3(varargin)
% WAVE_CLUS_AUX1 M-file for wave_clus_aux.fig
% WAVE_CLUS_AUX, by itself, creates a new WAVE_CLUS_AUX or raises the existing
% singleton*.
%
% H = WAVE_CLUS_AUX returns the handle to a new WAVE_CLUS_AUX or the handle to
% the existing singleton*.
%
% ... |
1827c2918df8dbfcc30e0c08a07a37321c027390be03aec1620d2b83e520f291 | MATLAB | 3,802 | 96 | function Bursts = detect_bursts(EEGBroadband, ChannelIndex, EEGNarrowbands,...
NarrowbandRanges, CriteriaSets, KeepTimepoints)
arguments
EEGBroadband struct
ChannelIndex (1,1) {mustBeInteger, mustBePositive}
EEGNarrowbands struct
NarrowbandRanges struct
CriteriaSets struct
KeepTimepoints = o... |
e6f385a97ae589975d321d7bc15ad43cf6ddd19884a60e5d48242f1a3c5d8da7 | MATLAB | 3,803 | 100 | function E=efficiency_wei(Gw,local)
%EFFICIENCY_WEI Global efficiency, local efficiency.
%
% Eglob = efficiency_wei(Gw);
% Eloc = efficiency_wei(Gw,1);
%
% The global efficiency is the average of inverse shortest path length,
% and is inversely related to the characteristic path length.
%
% The ... |
572005ab9599002efb685d7aa8987c4caa748fcc0cf27399b0b9573debc05a1c | MATLAB | 3,804 | 84 | function [lead_fields,UnitMDip] = Forward_OPM_single_sphere_XYZ_dir(x,y,z,slots_all,normal_unit,sphere_origin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
mean_sphere_origin = sphere_origin;
%% number of channels
Nch = size(slots_all,1);
%% voxel position in CTF and in metres
vox_pos_ctf... |
f02086f2d1e711b1ac338960ecd0ee56ff66f2da568790a12994d8d5171951f4 | MATLAB | 3,805 | 93 | clear
clc
%%
% Needs to be in D:\Data\IR data Shira_May_14_2022
windows = {40:50, 40:60, 40:45, 40:55, 65:125, 75:125, 85:125, 95:125, 100:130, 140:150, 140:160, 140:155};
relevant_windows = [1, 5, 10];
win = ["early"; "steady"; "off"];
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the lo... |
3937ed28a57b09c9f263d09c8184b8983137e7dd02c96c5be9aabb83eced5ad5 | MATLAB | 3,807 | 118 | function Y = timelag(X,lags,time_window)
% Take an input matrix, X, and create multiple time-lagged versions of the
% the matrix.
%
% Parameters:
% X: matrix
% A matrix of size (M x C) where M is the number of samples
% and where C is the number of channels
% lags: vector
% A vector of length L wher... |
d806b9619bace806897c54d1e8642dc349a85a7d6bb3a41aa95c59f0b53b5b3b | MATLAB | 3,807 | 154 | function [AAAt_ECGpeak222 AAAt_BPfoot222 AAAt_footIndex222]=riallinea_BP_ECG_v04(AAAt_ECGpeak,AAAt_BPfoot,AAAt_footIndex)
% figure
AAAt_ECGpeak1=unique(AAAt_ECGpeak);
AAAt_BPfoot1=unique(AAAt_BPfoot);
AAAt_footIndex1=unique(AAAt_footIndex);
if AAAt_BPfoot1(1)>AAAt_ECGpeak1(2)
AAAt_ECGpeak1(1)=[];
end
imin3=dif... |
0d6121e3b38a0d3734d66f3a46fb2cd7c11b5453d9803a7b204c62251f8572e9 | MATLAB | 3,811 | 89 | function MSN20200107
global dpath3
%
% trimtfile=strtrim(tfile);
Old=cd;
cd(dpath3)
LS=ls;
for i=1:length(LS(:,1)) % Sc#_SS_##.t@t@Cðñ·
trimFL=strtrim(LS(i,:));
if length(trimFL)>4 && strcmp(trimFL(end-1:end),'.t');
trimtfile=strtrim(trimFL);
nttfile=[trimtfile(1:3),'.nt... |
8f223414cf3c88f18538de057d36866e65b639e4b81d6e443cd353fefff35854 | MATLAB | 3,811 | 111 | % "example_nufft1_reverse.m"
% This m-file is an example of applying the NUFFT method "in reverse,"
% meaning that you have a nonuniformly-sampled signal spectrum in hand
% and you want to try to "compute its inverse Fourier transform"
% to get uniform set of signal samples. In the nomenclature of the 1999
% SIAM J Sc... |
a602aecb7d6fce1b7970be46bd0b43f3fc602be615a78932d8f156d4a6b25aa3 | MATLAB | 3,811 | 109 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Software developed by Javier Lucas-Romero
% July 2023
% This is the master script for the execution of ASTA3.
% The purpose of this software is to provide a user-friendly tool to
% classify the different firing patt... |
99e8cc05851004cb77f724e216033228d8825f8278c137372cdaaa9d20094e4c | MATLAB | 3,813 | 130 | function [Cell]=mnl_CalculateSomaValues_v2(Cell,Scale,cData,BkgMean)
%% Step 1 - Get the voxels involved in each soma
dim=size(cData);
Scount=size(Cell,2);
for i=1:Scount
NumPoints=size(Cell(i).dxyz,1);
for j=1:NumPoints
%Convert the surface points to voxels
dxyz(j,1)=round(Cell(i).dxyz(j,1));
... |
6cb29cf69d83daa240977d11b5bf25c0a76203b362f931ded24cd51d527e041c | MATLAB | 3,814 | 110 | function ThreePhaseSpike320190516
%¶«Ì^b`ÌÔÌDZÅE^b`ª Á½©Ì¶«Ì^b`ÔÅDZÅXpCNª Á½©
% global
cd('C:\Users\C238\Desktop\CheetahWRLV20180729\119\2017-6-7_20-8-33 11901-51');
dpath=('C:\Users\C238\Desktop\CheetahWRLV20180729\119\2017-6-7_20-8-33 11901-51\');
dpath3=('C:\Users\C2... |
7ac5a1d0439d41af3f26809e2925cfefc67a650ea0162fe4b6b2f8adee2e23db | MATLAB | 3,814 | 106 | function CV=carspls_mccv(X,y,A,N,method,num,selectLV,originalVersion)
%+++ Cross validation of CARS, at each iteration, CARS is run on sub-training
% data and tested on the lef-out test samples. Repeat N times, and
% record the times each variable is selected, say z. So the selection
% frequency can then be c... |
8b900ef3e0701aa1694702828bfef7d9f7314505a035bc02d828e71d17658e2f | MATLAB | 3,815 | 114 | %% Plotting States Colors *********************************************
% Requeriment:
% Plot Raster
% Input
%
% labels_frames: Ensemble Labels in each frame
% signif_frames: Significative Coactivity Frames
% ColorState: Color of The Ensembles
% Experiment: Raster Concatenated and Ensemble Sorted
% fs... |
97c82310a19a181020c6c2c9d275bb57f80a8a145a4bbbc0577487db90cec122 | MATLAB | 3,816 | 107 | clear
clc
%%
% Needs to be in D:\Data\IR data Shira_May_14_2022
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
for i = 1:length(datafile)
load(datafile... |
80b7b029cf88671dfcbf904e572f50c25a70b031255096da189257e626bc088d | MATLAB | 3,825 | 72 | % Computes the metastatic mass via a first order quadrature
% Growth PT follows model growth_model_PT (with parameters param_PT)
% Growth of Mets follows model growth_model_met (with parameter set param)
% flagNb = 0 or 1 depending on whether we want the number of mets to be
% computed or not
% Model is designed to be... |
2d1b6b928c844a76c995923eadb6432533093f50957309aadd5e86ed9049088f | MATLAB | 3,830 | 94 | function [FD,RMS,FD_outliers,RMS_outliers] = spmup_FD(varargin)
% simple routine that computes framewise displacement as a sum (FD) and RMS
% Power et al. (2012) doi:10.1016/j.neuroimage.2011.10.018
% Power et al. (2014) doi:10.1016/j.neuroimage.2013.08.048
%
% FORMAT: [FD,RMS,FD_outliers,RMS_outliers] = spmup_FD
%... |
5c4edf6da5605d30ff1d68738e7556504fdce7d2d4a3b833b3c59a06d800e140 | MATLAB | 3,830 | 166 | clear all
close all
sigma=0.5;
Veq=-76.72;
Vth=-39.51;
Vr=-41.70;
tau=11.85;
Vsp=-20;
R=118.5;
C=0.098;
tau_Ref=0.1;
P=10;
taus=20;
epsilon=0.02;
Areward=0.9;
Apostpre=1;
Aprepost=-1;
N_pres=1000;
dt=0.1;
% Coeffs=1;
PLOTS=1;
% ncoeffs=50;
% Coeffs=linspace(0.11,7,ncoeffs);
Coeff=3/7;
wmax=0.2;
wmin=0;
%%%% ... |
adf552db8b9b383a714a5f6bc36a2c775115d22d2915104dca11f6e2427db191 | MATLAB | 3,834 | 96 | function layers = backward(layers, params)
n = numel(layers);
batchsize = size(layers{1}.a, 4);
for l = n : -1 : 1
if strcmp(layers{l}.type, 'c') || strcmp(layers{l}.type, 'f')
if strcmp(layers{l}.function, 'soft') % for softmax
if (~strcmp(params.lossfun, 'logreg'))
layers{l}.d = softder(layers{l... |
c8ca6772d405e5ab89a068247d70fc10c9b1f4918ff328cafe914fb917d3ea1d | MATLAB | 3,839 | 107 | % function [mrFet12_, viSpk12_, n1_, n2_, viiSpk12_ord_] = fet12_site_(trFet_spk, S0, P, iSite, vlRedo_spk)
function [siteFeatures, spikes, n1, n2, spikeOrder] = getSiteFeatures(spikeFeatures, site, spikeData, hCfg)
%GETSITEFEATURES Get features occurring on primary and secondary (optionally tertiary) sites
[si... |
82256fa703715c062dc6ebb46a5270de36a231742778ba9854a753e99e105d36 | MATLAB | 3,840 | 99 | function [y, W, A, B, C, lambda] = nonstationary_component_analysis(x, I, J, varargin)
% nonstationary_component_analysis - Nonstationary Component Analysis (NSCA)
% algorithm to extract temporal nonstationarities from multichannel data
%
% Usage:
% [y, W, A, B, C, lambda] = nonstationary_component_analysis(x,... |
7ea52a749685c632eff4e9ddbfdb2c6191cfb9cba51468b431a7bd821c7bf73b | MATLAB | 3,841 | 102 | function MakeMultimerNet_Group20160520
%MakeMultimerProb20160517.m(Exp=5Ìêj
%MakeMultimerProb20160526.miExp=10Ìêj
%Éæèêv²ÆÉt@Cðì¬
%»êðp¢ÄMultimerConProbAllt@Cð쬷éBMatching10ñ̪۶³êéB
%MakeMultimerNet_Group20160520.mÅlbg[Nì¬
%â`q»... |
ff3b8553f3945a852e1267092aee0aa5e28da41fa4457f24ef99d6d81a13e7c8 | MATLAB | 3,845 | 112 | % This script saves time series per subject per region of interest (ROI)
% into a file called `subject_region_timeseries.csv`.
%
% The stimulation protocol can be found in the `.tsv` files, in the `func`
% folder of the raw data.
%
% The stimulation parameters are:
%
% TODO: check this because the length is either s... |
e74343c1444b80c3a71db14e5d164b014dac7641450a2352e949e14dcd9a0386 | MATLAB | 3,847 | 105 | % Test script for SpatioTemporalInnovationsFilterDesigner, which estimates an innovations filter from ensembles of multichannel random
% processes.
%
% The Open-Source Electrophysiological Toolbox (OSET)
% https://github.com/alphanumericslab/OSET
% Reza Sameni, Feb 2023
close all
clear
clc
case_study = 'EEG'; % 'EEG'... |
191a5e833603c0a68df2906ce9654398a9765ac26c3cb360bcfcf1cded76aecc | MATLAB | 3,848 | 95 | clc
clear
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
%%
windows = {40:50,65:125,140:150};
all_sugnificnt_cells = [];
all_p_val = [];
for z = 1:length(wi... |
7b7f736916ff4e4a95d77cf456eee4a22708c097f3b6a944eb42238255203986 | MATLAB | 3,849 | 97 | clear all
close all
clc
constants;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Load parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
import_data;
import_covariates;
folder_fit = './fit_PT_met_SAEM';
[param_inds, param_ind_d] = compute_param_inds(... |
3dccc7042cf9e0f6a3a2ac82aa0d583e510e23302271a444d01ddda6f7c7b39f | MATLAB | 3,850 | 98 | function Data = Classify_PVD_Points(Data,Clusters_Struct)
% TODO: move to parameters file:
X_Min_Max = [-2,2];
Y_Min_Max = [-1,1];
XFunc = @(x) rescale(x,X_Min_Max(1),X_Min_Max(2),'InputMin',-pi/2,'InputMax',pi/2);
YFunc = @(y) rescale(y,Y_Min_Max(1),Y_Min_Max(2),'InputMin',0,'InputMax',pi/2);
Classific... |
7ec0b312ad0765a0b4fc052da4c5e2b236f0b16df259a7ded313ff37ed1cb7d1 | MATLAB | 3,855 | 105 | close all
clear
clc
% Convert all dat files in bash using this command: find ./*/ -type f -execdir wfdb2mat -r {} \;
% datafilepath = '../../../../DataFiles/physionet.org/files/ptbdb/1.0.0/';
% directory_list = dir([datafilepath 'patient*']);
%
% filelist = dir(fullfile([datafilepath, '**/*lr*.mat'])); % get list o... |
188db4d23d2e6a2fa125a8b8f38488d8d68bd50387ce01ec93c14e1458de33e6 | MATLAB | 3,857 | 135 | function varargout = stlreadNonCleaning(file)
% STLREAD imports geometry from an STL file into MATLAB.
% FV = STLREAD(FILENAME) imports triangular faces from the ASCII or binary
% STL file idicated by FILENAME, and returns the patch struct FV, with fields
% 'faces' and 'vertices'.
%
% [F,V] = STLREAD(FILENA... |
ca2b2adffc17dbe8b96213d07efa5a94935e4bea8efe4fef0551642ef2ffc828 | MATLAB | 3,858 | 104 | %% caculate parameters from all data (baseline)
clear
clc
ploting =1 ;
window = 2; %(on, sus, off)
sus_window = 65:125;
%%
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file... |
b1e374b8839a33b66e02930dbdd3ef3003c902b319025d2ab77c1be570d40717 | MATLAB | 3,859 | 143 | % read .COORD file and plot data
% PGH Oct 2001
function lcmodelresults=readcoord(filename)
% define output structure for results
%lcmodelresults=struct('spectrumppm',0,'spectrumdata',0,'spectrumfit',0,'spectrumbasl',0,'metabconc',0,'linewidth',0,'SN',0);
%lcmodelresults.metabconc=struct('name',0,'relconc',0,'abscon... |
3cecfe54dc13385a31d742691a4dcf93d7c7982011734e7362805e04dd232713 | MATLAB | 3,865 | 137 | function SpikeArray1=GetSpikeAll(dpath,fname)
global StartTime FinishTime dpath3
% StartTime
% FinishTime
DurationB=FinishTime-StartTime;
CurrentPath=pwd;
% cd C:\Users\B133\Desktop\WR_LVdata\6721_160218
% load 6721_160218.mat
% % % cd C:\Users\B133\Desktop\CheetahData
%dpath='C:\Documents and Settin... |
372a756cb4f4cb9596b7050d3c21f455cae7cd700ee4ba60edfade3a80ecf089 | MATLAB | 3,867 | 143 | function [a r phi zm] = circ_plot(alpha, format, formats, varargin)
%
% r = circ_plot(alpha, ...)
% Plotting routines for circular data.
%
% Input:
% alpha sample of angles in radians
% [format specifies style of plot
% pretty, histogram, density, []
% [formats standard matlab stri... |
e49c57e9c37d93bd5120a40466b928949077156143bce846d741a7a8de6d2caf | MATLAB | 3,869 | 96 | %% Figure 4A
load(fullfile(pwd, 'stat', 'Figure4A.mat'))
addpath(genpath(fullfile(pwd, 'plotting')))
colors = [[0, 0, 0]; [1, 0, 0]];
boxplot_pairwise(Rin, colors);
%% Figure 4C
load(fullfile(pwd, 'stat', 'Figure4C.mat'))
ft = fittype('d+b/(1+exp(-(x-a)/k))', 'independent', 'x');
curves{1} = fit([2:8]', mean(spike_prop... |
1c9cb30cf6729f1867821c87a65da1904684c09079a663765056f480fd2fc617 | MATLAB | 3,873 | 105 | function stat_PERMS_MSPoI_Mikael(ResPath,atlas,NodeName,savepath)
% Concatenate permutations
atlas_name = atlas;
numper = 10000;
numruns = 50;
Pval = []; Pair_diff_pos = {}; Pair_diff_neg = {}; Dissidents = {};
for reg = 1:3
TS_all = []; D_pos = []; D_neg = []; Diss = []... |
cc0bd8591163bf3e2e2ca219061277b1e733621e3658a8450cc103f788835eee | MATLAB | 3,875 | 134 | % - use joint results and apply to single session
% - rerun preprocessing without lowpass filter and compare
% - define circle around centroid
% - define cell area using threshold
% - take cell out of circle -> ring
% - correlate ring vs. cell (original / thresholded)
%%
clear
p = params_2DAA;
saveFig = 1;
data_path... |
4df3b26eb2c0bbdf18d5d6f06bc6d955d47ae62f2b983e7424fa0c78f20ac805 | MATLAB | 3,876 | 100 | %{
----------------------------------------------------------------------------
Analyzing behavioral data
At least for the correct rate
----------------------------------------------------------------------------
%}
function Figure2d_Dual_RL_analysis_220314_para_all_220909_2
close all
analysis_folder = {
... |
a28dd98de62274d59cc90481bb16853fc99c370ca1678c71d57e4d0f868f8009 | MATLAB | 3,876 | 103 | function [weights, trainerr] = cnntrain_norm_mat(layers, weights, train_x, train_y, params)
params = setparams(params);
assert(length(layers) == 3);
assert(length(weights) == 3);
layers{1} = cnnsetup(layers{1}, 0);
layers{1} = setweights(layers{1}, weights{1});
layers{2} = cnnsetup(layers{2}, 0);
layers{3} = cnnset... |
44ad8b6d3efa7d6b978a35be5cde7886201f8e713e08520b833fae1900bb1595 | MATLAB | 3,878 | 109 | function splitDat(totalChan,timeWin,chan2pull,Fs,memToUse)
%splitDat - Split Dat Files
%
% Usage:
% splitDat(totalChan,timeWin,chan2pull,Fs,memToUse)
% splitDat(totalChan,{},chan2pull,Fs,memToUse) - If splitting channels over entire recording
% splitDat(totalChan,{t,'end'},chan2pull,Fs,memToUs... |
4d79b4a14949c5b2c9f0d99b4dfc9cf8747566c5d4286948c06b522e74f5b426 | MATLAB | 3,879 | 129 | %% Figure 2 plots
clear all
close all
%read raw data
por_data = xlsread('POR_data.xlsx','B2:AA23');
[~,odor_data] = xlsread('POR_data.xlsx','B25:AA46');
[~,gender_data] = xlsread('POR_data.xlsx','B47:AA47');
odors = {'hex','hex01','hex10','iaa','2oct','ani','hxa','gua','bza',...
'cit','neem','gar','chex','l... |
a11d40549735b7db72e687ae469121be121ea99817b67de785197f318841bf4b | MATLAB | 3,882 | 85 | function [data] = createDataStruct(wsData,animalName,expDate)
%%Create Data Structure from WaveSurfer to MAT function
%
% [data] = createDataStruct(wsData,animalName,expDate)
%
% Description: This file takes a data structure generated from the
% extractH5_WS function and it organizes the acquired traces int... |
c4ef6fc5658194839b80f91fcadd7895b93fa2d974e4b81b8b568cda716e0b56 | MATLAB | 3,883 | 91 | % This script demonstrates how the burst detection works for multiple
% channels.
clear
clc
close all
%% load the EEG data
load("C:\Users\colas\Code\Matcycle\example_data\EEGbroadband.mat", "EEGbroadband")
% EEG data needs to be a structure with fields "data" (channels x time
% array), "srate" (sampling rate), and... |
5fa31f03e4e0b2629dd8f36d884e95ce6570860fc0e1c7be208d136e189c441a | MATLAB | 3,884 | 125 | close all;
clear;
clc;
resultfname = 'testICASubspaceAngles02.txt';
% parameters
subject = {'Dog_1', 'Dog_2', 'Dog_3', 'Dog_4', 'Dog_5', 'Patient_1', 'Patient_2'};
f0 = 60; % powerline frequency Hz
Q = 30; % notch filter Q-factor
% wlen = [0.5 1.0 3.0 5.0 10.0]; % energy window lengths in seconds
drop = 200; % remove ... |
a7793542ef00777255f9fc71be55ee769a2fb207c4aa46c79e547556e63610c5 | MATLAB | 3,890 | 85 | %% Process Parameters for Photometry Analysis
%Created By: Pratik Mistry
%Created On: 31 January 2019
%Edited On: 26 September 2019
%
%Description: This is a script with different variables whose values can be
%adjusted depending on the photometry signal that is being processed. The
%name of this file can and sh... |
56b0bebaf1772a99eec810a37f5a41b8cc2597ee8705787d5eee8ccf63d7f021 | MATLAB | 3,891 | 129 | function hb_res = hb_det_2(varargin)%ecg, threshold, inverse, bp, use_bp)
%HB_DET_2 Summary of this function goes here
% Detailed explanation goes here
ecg = varargin{1};
threshold = varargin{2};
inverse = varargin{3};
if length(varargin) > 3
bp = varargin{4};
use_bp = varargin{5};
if isempty(bp)
... |
7f4f9444bf1689614245f46060e8f754bafa0b853095f971b828c0175dde2e9b | MATLAB | 3,891 | 138 | clear
clc
close all
Info = analysisParameters();
Paths = Info.Paths;
Bands = Info.Narrowbands;
BandLabels = fieldnames(Bands);
%%%% Choose a file
%%%%
%%%%
Task = 'PVT'; % Game, Standing, Fixation
Session = 'Session2Beam';
Participant = 'P04'; % P03 has almost no oscillations, P15 has tons
%%%%
%%%%
%%%%
Source = fu... |
55f4db5cea841ffa53451d877b264cadbbfe0a8dd01bb179ac5db9845f3af301 | MATLAB | 3,892 | 92 | % Rockland dataset
% http://fcon_1000.projects.nitrc.org/indi/enhanced/
%
% Data contains TR 645 and TR 1400 acquisitions using a ON/OFF checkerboard protocol. This is a subset (50)
% of participants, the full dataset has hundreds of participants and lots of different scan modalities / experimental tasks.
%% Set Pat... |
47804b240498c3a7918a44444718bac13757832127f5e653f2335dd8885026ee | MATLAB | 3,894 | 161 | function [mov rest start_end_mov peaks_mov start_end_rest peaks_rest locs amp_mov ]=movrestepoch(TrackingData)
%%
% This function processes tracking data (assumes sampling rate 60 Hz) to extract movement and resting epochs.
% The function returns various statistics related to the movement and resting data.
% mov= mo... |
f4097fd3c59e814b68f9cfc30c4a8c286764c53d363041a6d6015dddc833ca0c | MATLAB | 3,894 | 111 | % Using eyetracking data, identify when participants had eyes open or
% closed.
clear
clc
close all
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% load in and set parameters for analysis
Tasks = {'PVT', 'LAT'};
RerunAnalysis = true;
PupilDetectionMethodType = '2d c++'; % either 2D or... |
ce04bc926bba434b6511427957bef63b93e6832969608eca0884568d728a79a1 | MATLAB | 3,896 | 110 | function [lambda, AIC, MDL, NEW, ENSTh, ENS, fhand] = dimension_estimation(x, noisevar, varargin)
% Estimates the dimensions of the signal space from noisy data
%
% Syntax:
% [lambda, AIC, MDL, NEW, ENSTh, ENS, fhand] = dimension_estimation(x, noisevar, flagplot)
%
% Inputs:
% x - Input data matrix (L x N), where L... |
f48a45aceb4eee0180f7a40f6519880b635031583fb2926e558d5aff20f4ece5 | MATLAB | 3,896 | 150 |
function [pi_0_ehmm , coupling_tetha_ehmm , transition_ehmm ,ehmm_gmm_para, index_matrix ] = chmm_cartesian_product( pi_0_chmm , transition_chmm ,chmm_gmm_para )
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Converting CHMM to equivale... |
2af2e08308e9254300b3c3fd7dde79ce667417fb7367403c60c007ee5ae94bb7 | MATLAB | 3,897 | 118 | function probe = loadProbe(probeFile)
%LOADPROBE Load a probe file
try % first try to load probe from mat file
pstr = load(probeFile, '-mat');
catch
pstr = jrclust.utils.mToStruct(probeFile);
end
probe = struct();
% exactly one of 'channels' or 'siteMap'
if isfield(pstr, 'c... |
2cd3080ab0377008d295d97eb31dd26764b3432813cf7bdfb3d6066d108990e1 | MATLAB | 3,899 | 113 | clear;
close all;
cd 'C:\Users\Admin\Git\repo\ZS-DeconvNet\Python_MATLAB_Codes\data_augment_recorrupt_matlab'; % change this path to your cloned path
addpath(genpath('./XxUtils'));
addpath(genpath('./GenData4ZS-DeconvNet-SIM'));
% It should be noted that, the raw data loading code of this demo is based on the file str... |
92966a020ef201e88554e91730a47e40aefa875859555068f93a5831141cd23a | MATLAB | 3,899 | 102 | clc
clear
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
%%
windows = {40:50, 40:60, 40:45, 40:55, 65:125, 75:125, 85:125, 95:125, 100:130, 140:150, 140:160... |
507422253220528a26b8a9fc1d50e40844d0097e8a59290d38f378b725e5203d | MATLAB | 3,900 | 77 | function Workspace1 = Segments_Orientation(Workspace1)
% Make a list of the coordinates of the 1st and last primary branches:
Vxy1 = [[Workspace1.Branches(1).Rectangles(:).X]',[Workspace1.Branches(1).Rectangles(:).Y]'];
Vxy2 = [[Workspace1.Branches(2).Rectangles(:).X]',[Workspace1.Branches(2).Rectangles(:).Y]'];... |
35aaef950bfb27febf6561a771f5fc2ca159e01ddba275accf448af7ab6c092d | MATLAB | 3,901 | 107 |
%% loading data
load('dataFig2AB.mat');
load('dataFig2CD.mat');
%% Fig 2AB
figure(21); clf; set(gcf,'Position',[50,10,400,840]);
% V-I curve
subplot(2,1,1); cla; hold on; xl=[-0.55,1.05]; yl=[-93,-27];
plot(amps/1000,potentialP,'-','color',[0.0,0.4,0.0]);
plot(amps/1000,potentialA,'-','color',[0.0,0.0,0.... |
e9de2dc832be13389a3d4a6968cbe9f16a88b2c74a045edfa1632564c77fae7c | MATLAB | 3,901 | 118 | %% LDE iteration w/o figures
% Output: Iteration firing maps, and L1 diff norm
% Outflag: 'f(xn)' or 'xn'
function [LDERepFinal,L2DiffNorm,L2DiffNormNeib,L2Diameter,LDEequv] = ...
LDEIteration_16FuncMain(...
PixInptCtgrUse,LDEIni,p,Epoc,...
C_SS_mean,C_CS_mean,C_IS_mean,...
C_SC_mean,C_CC_mean,C_IC_mean... |
d74b1bdf07aeb93f01994837aa45246217e68d3d7d5c16bb2bf031e2eb2cbc48 | MATLAB | 3,904 | 139 | function [fmri_out,V4] = spmup_skip(varargin)
% routine that reads a 4D fmri data set and return a 4D set minus N initial volumes
%
% FORMAT fmri_out = spmup_skip
% fmri_out = spmup_skip(fmri_in,n,options)
%
% INPUTS fmri_in is the name of the fmri data set
% n is the nymber of initial volumes to... |
f66264f70a08f1049619d18278f9e6fb98105724327e3132fd40b89e734085ff | MATLAB | 3,907 | 121 | function [Trace]=mnl_GetNeurolucidaTraces(s)
NumTraces=size(s.mbf.tree,2);
Tree=s.mbf.tree;
nT=1; %Final Number of Fragments/Traces
counter=1;
while counter<=NumTraces
TempTrace=Tree{1,counter};
%% Are there points?
if isfield(TempTrace,'point')==1
[points,diameter]=mnl_GetPoints(TempTrace);
... |
a083e790e08009caf172b230ec01c77d78c6446df9995bceaf0a5f1d47bc3203 | MATLAB | 3,909 | 135 | % Histograms of FWF values in T1L for each MS patient
% plot showing all the histfit curves overlapped on each other
% box and whisker's plot showing the variability for all the pts
clearvars
close all
addpath(genpath('/storage/stella/MATLAB_toolboxes/'));
addpath('/storage/stella/Analysis/matlab_scripts/');
tstart ... |
d11705c8496bfc33237f86e0eb173cf0668c87b47558f56af4ee3b2e8214535b | MATLAB | 3,910 | 85 | %% This function generates arbitrary large field with lgn indexes, given a 3*3HC input
% Input: lambda_SOn_drive: LGNon input for all S cells. There should be
% three unique values
% temp: A template 1*N (same length of number of functions) that composes lambda_SOn_drive
% ... |
84c4a5b7dede19045bb7b10ca7c99d933d3c2b4991dda988278dbf6d2db8e8ab | MATLAB | 3,915 | 123 | % compare the tone component for different trial types and aligments:
% 1) avoid vs. error at tone end
% 2) avoid (action start) vs. error (tone end)
% - comparison 1 should show that in avoid trials tone singal drops early
% - comparison 2 should show that the drop is alinged between a and e
% - this will allow u... |
9521784fbb5906b691e66e213ad17140144b99316b62fc344677c1f4da5dc443 | MATLAB | 3,916 | 156 | function [res,Names,msg] = SlurpData(path,conds,directory, tp,pb)
% This function helps you to read well organized data from a directory into matlab
% PATH is a wildcart to identify the files of one condition across all
% subjects in the directory
% CONDS is a cell array containing the tags for all conditions you w... |
87dc1b88401c2b02d375544687dc3d08d913ed9f18ea4da1d74bda51601f2e86 | MATLAB | 3,919 | 177 | function go_netviewer_gray(C)
% only use to show full networks w matrtices of 1s and zeros
cLims = [0,1];
% Set the sphere widths to 1
% sphereWidths = repmat(1,78,1);
% Set them to only visible if a node survives thersholding
sphereWidths = sum(~isnan(C))*0.5;
sphereWidths = 3*sphereWidths./max(sphereWidths(:));
loa... |
16f35d43db8c8383ac8f38b4b814cafd7a0321a370d43e4e80d341eba39a7316 | MATLAB | 3,920 | 96 | function SpikeForm20191122
%CheetahWRLV20180729Part1ÉÛ¶³êÄ¢é·×ÄÌtfileÌ×EÌf[^ÉεÄHalfPeakwidthÆPeaktoTroughðvZµÄvbg
% ScNumbersÍS×EH4×EÌêÍ3D
% CellNumbersÍ×EÔA1,2,3,4...A½¾µA0à éBÇÌ×EÉàYµÈ¢L^iHj
% DataPointsÌ1³ÚÍ32_ÌdÊA2³... |
9d46c01bd5d0b08329c2bf76e21890e69bbafcf42c760a8d1e96d30b7e41e53f | MATLAB | 3,922 | 75 |
function [tr, wl, int] = mselect_wls(file)
%%%%%%%%%%%%% Loads scope files %%%%%%%%%%%%%%%%%%
[s, w] = dos('dir/B c*.txt'); %display the filenames of the txt files in the current directory that start with rs
txt = regexp(w, '.txt', 'split'); %splits the character array into cell array of strings
... |
a4ec2cd02a96a968c51fed2379bbb7de600b9ef2d219606e2ddd8708f68de464 | MATLAB | 3,922 | 78 | % ----------------------------------------------------------------------- %
% Function plot_areaerrorbar plots the mean and standard deviation of a %
% set of data filling the space between the positive and negative mean %
% error using a semi-transparent background, completely customizable. %
% ... |
22728cf5b0261c61b689da07412389e08f201e1a97398c1b1ad7d2de195f9b85 | MATLAB | 3,923 | 107 | clear
clc
%%
% Needs to be in D:\Data\IR data Shira_May_14_2022
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
for i = 1:length(datafile)
load... |
ce0732eff477d8a1982625bb46308ec6e85d7d17c29fe180241c7e11c4163d37 | MATLAB | 3,923 | 137 | function[b_model,b_ind,b_loading,exp_var] = RaguEEG_Mod_r(eeg,n_mod,reruns,max_n,flags,ProgBarAxis)
%function[b_model,b_ind,b_loading,exp_var] = RaguEEG_Mod_r(eeg,n_mod,reruns,max_n,flags)
% EEG_MOD Create the EEG model I'm working with
%
% function[b_model,b_ind,b_loading,exp_var] = eeg_mod_r(eeg,n_mod,reruns,max_n)... |
14c00147f3d4516bee188fe6402bbe7e750b5db05feceec6b8894d23283e50cb | MATLAB | 3,930 | 142 | % Simulated scatter plots and ICA
%
clear;
close all;
a = 2;
b = 2;
% t = asin(1/b) + [0:.01:18*pi 0];
% t = asin(1/b) + [0:.01:2*pi 0];
t = (0:.01:20*pi);
N = length(t);
r = a * (1-b*sin(t));% + .2*randn(1,length(t));
[x,y] = pol2cart(t,r);
% A0 = [1 1; -1 1;-.2 1];
% xyz = A0*[x;y];
x = x ... |
ccbdf46861ca80e2d606e2e3b2d05137af0ba263a8d0ebc2ed7242862a0292fe | MATLAB | 3,931 | 134 | function info = get_info()
% Get global information
%
% Returns
% -------
% - info: struct
% - width: scaler
% Width of the probes' grid
% - height: scaler
% Height of the probes' grid
% - fix: vector
% Saccade aligned presaccadic times
% - sac: vector... |
52dec9bfabcf49775518fa1f874634db7808bd972a301e1d8ce72bb821a7709a | MATLAB | 3,934 | 65 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
7937cd5c46eb901b17f909d4f3d66f0645231ef26e062af1288993f89b5f51d2 | MATLAB | 3,935 | 153 | function [bestMI, bestbin, p, SSI] = calc_MI(spikeCountCellArray, correction, optimiseBins, sigFlag, nMCSamples, nBinLim)
% 1) Choose number of bins (stimulus and response)
% - same as input, optimise to max info, pre-specified N
% 2) Compute MI using this number of bins, optional correction...
% 3) check significance... |
912ed3aeb9eb0537385e62a0a1cc16c0775b72da1d5196537a2fdd4c3bb07345 | MATLAB | 3,935 | 134 | function [ch, tim] = getkey(N,nonascii)
% GETKEY - get a keypress
% CH = GETKEY waits for a single keypress and returns the ASCII code. It
% accepts all ascii characters, including backspace (8), space (32),
% enter (13), etc, that can be typed on the keyboard.
% Non-ascii keys (ctrl, alt, ..) return a NaN. C... |
1eebc7d0f143ce25162feb462f6c3c7d878f92e7db9d883d42624df726982f8f | MATLAB | 3,941 | 102 | function computeMeanWaveforms(obj, updateMe, useRaw)
%COMPUTEMEANWAVEFORMS Compute the mean waveform for each cluster
if nargin < 2
updateMe = [];
end
if nargin < 3
useRaw = 1;
end
if isempty(obj.spikesFilt)
return;
end
useRaw = useRaw && ~isempty(obj.spikesRaw)... |
2702ac1dc98768e2dc6f232794f3d264bb4a16b0a8418b8811128d75d8de305a | MATLAB | 3,942 | 145 | % simulate effect of motion on a 2D-image
clear
close all
run('addRetroMoCoBoxToPath.m')
rng(0); % resets random number generator to get the same 'random' numbers each time code is run
% load example
image_original = imread(fullfile('images','col27_slice80.png'));
image_original = double(image_original(end:-1:1,:,... |
5d13a6751fed29bd5afec26e7e469a64a0b2cc5fefa90a97333aa7012dce7990 | MATLAB | 3,943 | 138 | function [zHits,zFA,dprime,c,cprime,beta] = rst_sdt1(varargin)
% implement signal detection theory
% based on the book Detection theory A user guide
% Authors N.A. Macmillan and C.D. Creelman
% one-interval design - two-stimuli needs to be discriminated
%
% [zHits,zFA,dprime,c,cprime,beta] = bat_sdt1(100,100,80,30,1);
... |
03b6cfe80435897f443cee119588af7315f63ce69693fc4fcc965d80cb83f6e3 | MATLAB | 3,945 | 102 | %% review 2.2;
% Simulation of cells.
% Created by Xiang Zhang, Jan., 2024.
clear;
close all;
%% parameters;
file_lists = {
'E:\Social\15028\20210405\15028-10071\PC';
'E:\Social\15029\20210420\15029-10068\PC';
'E:\Social\15030\20210420\15030-10074\PC';
'E:\Social\15032\20210407\15032-15037\PC';
'E... |
1c58bf259e3e965c5901f5c4f213a6d17ba69c3cb8e9908ae34c8823a5b682d8 | MATLAB | 3,945 | 91 | % Mapping of ICs to RSNs for neuro-dynamic-covariance project. First thrsehold the raw probability maps from the IC and RSN. Then calculate
% dices coefficient of the overlap between each IC and all RSNs, as well as the percentage of the IC mask that overlaps with each RSN (these are almost perfectly
% correlated but p... |
6ae91c189547fe1282e4cf5e3744b1c08e4d9416792fd9d88a54c71e374e185a | MATLAB | 3,947 | 102 | % ut_spmup_anatQA
%
% call spmup_anatQA testing with simulated data
% that means all the data in GM and WM masks are used corresponding to the
% values generated therein
%
% Cyril Pernet
% -------------------------------------------------------------------------
% Copyright (C) spmup team
%% load up the SPM tpm
cl... |
e297e37407b9bee86d80bb09b3726423584510dd7088d05c3630394e50c8d4fa | MATLAB | 3,948 | 114 | function untitled20190223
global ACresult ACresultW CCresultDrinkOn SpikeArray RpegTouchallWon LpegTouchallWon TurnMarkerTime RmedianPTTM RpegMedian LmedianPTTM LpegMedian...
RpNum LpNum OneTurnTime CCresultSpike RmedianPTTM LmedianPTTM pksA1 pksA2
bin1=15;
phaseR=zeros(1,bin1);
for i=1:length(RpegTouchallWo... |
fefe1a985deef45aa970744d1620e886db5fe961f813f64622d687b93e0c85a3 | MATLAB | 3,949 | 144 | %Computes gradient using second-order methods
%Shinjini Kundu (c) 2015
function [dIdx, dIdy, dIdz] = new_gradient(image, option)
%inputs: image a 3D image
% option 'first' or 'second'
% choosing 'first' is the same as the result
% ... |
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