sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
22528988046e5475fd9cc2bcbf1ebf67c37ec0676acb96c0a3f00f6c09ebfc92 | MATLAB | 1,459 | 50 | function plotArrayFileResults(AD)
if isstring(AD)
AD = load(ADfilename,'-mat');
end
nS = AD.inputs.nS;
nD = AD.inputs.nD;
minRhoOpt = AD.inputs.minRhoOpt;
maxRho = AD.inputs.maxRho;
% %############################################################
%Head Model info
%Load GM and scalp pos
load([pathnameHeadModel '/G... |
aee8b2ff052adfa6364d5ac5e921d3eb98d63e0dc5e725de473abff342a2c035 | MATLAB | 1,459 | 44 | function [index, rank] = sqi_level_crossing(x, th1, th2, varargin)
% sqi_level_crossing - Signal quality index based on the percentage of samples exceeding upper and lower thresholds.
%
% Usage:
% [index, rank] = sqi_level_crossing(x, th1, th2, ranking_mode)
%
% Inputs:
% x: Input signal matrix with dimensio... |
00bb24fe577161ba09a9be0a2f7562af962e8efba431e62008f5c3b0daae5c0f | MATLAB | 1,460 | 36 | if exist('RoA_POS','var')
aremerged=true; % Are there already colocated cells
else
aremerged=false; % Are there already colocated cells
end
[CM,ColorIndx]=Color_Selector(Names_Conditions);
plot_cdf_cell(RoA_ALL,Names_Conditions,CM(ColorIndx,:));
xlabel('RoA')
plot_cdf_cell(ISIs_ALL,Names_Conditions,CM(C... |
3a370cffc15ca81b7b712aa9fac8987affa18fbd78b702a2f075a2809b1f03db | MATLAB | 1,460 | 38 | function plot_junction(ax,x,y,vector_angles)
vector_angles = sort(vector_angles);
angle_diffs = [diff(vector_angles), 2*pi - (vector_angles(end) - vector_angles(1))];
Alpha = 0.5;
CM = [0.8,0,0 ; 0,0.8,0 ; 0,0,0.8 ; lines(5)];
CM = CM(1:length(vector_angles), :);
[~, angle_diffs_sort_indices] = sor... |
c7bcea75ec2559dbc29b6c489bfec15a5b071207903f5e978b118a4c775bc743 | MATLAB | 1,460 | 84 | function [Montage,pos,lbl] = ReadSXYZ(fname)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
[fid,message] = fopen(fname,'rt');
if fid == -1
errordlg(message,'Read SXYZ File');
Montage = [];
return;
end
l = fgets(fid);
[params,pcount] = sscanf(l... |
e2b0a25d37ac2c8e1c3ef7b954a7359c318982ad0ab789e19e8dd2ff26d87e75 | MATLAB | 1,460 | 64 | % Test the instantaneous correlation of different signals
% Reza Sameni
clc
clear;
close all;
N = 1000;
fs = 1000;
n = 0:N-1;
x = sin(2*pi*n*10/fs);
y = sin(2*pi*n*33/fs);
z = [x y];
zz = z + .05*randn(size(z));
zz = [zz randn(1,1000) zz ];
% % % load sampledata x fs
% % % zz = x(1,:);
tau = 0:199;
t = (0:length(zz... |
0cf7d8ee5c84056a70b6e3095ad2bd773172c146d40d5cafaa66f192de4f7476 | MATLAB | 1,461 | 55 | function plotAGDiff_MSPoI(AM,Lab_idx,NodeName,atlas,options,savepath,save)
atlas_name = options.atlas{atlas};
%close all
for reg = 1:length(AM)%3
f = figure;%(com);
CF = AM{reg};
AM_diff = CF(:,:,2) - CF(:,:,1);
% Pr = Lab_idx{gI}; if partition for each group
Pr =... |
47fc92650b2e4096788ad578e0ab0af63c974fc4582756bafc73d97d625291b9 | MATLAB | 1,461 | 45 | % The script plots the neural and behavioural data contained in a .h5 file
% of the repository in the form of a raster plot
% authors: Francesco E. Vaccari
% date: 10/2022
clear all; clc; close all;
addpath('supportFunctions')
currentFolder = pwd;
parentFolder = fileparts(fileparts(currentFolder));
[filename,path_... |
65c9e5ec4c716120f3f2087c5702645142fb56d9e879458c889dbaa79c7e359f | MATLAB | 1,462 | 41 | % function cluster_combineCoils(reconParsFile)
load(reconParsFile)
run([RETROMOCOBOX_PATH '/addRetroMoCoBoxToPath.m']);
% run([MIRT_PATH '/setup.m']);
addpath(SPM_PATH);
tempDir = fileparts(reconParsFile); % tempDir itself wasn't actually saved explicitly before...
all_ims = complex(zeros(Hxyz(1),Hxyz(2),Hxyz(3),nE... |
629b26f3c8328152deb9fef37bc59c397e817b17d54675b310c6b651a10a25e1 | MATLAB | 1,464 | 43 | pathnameLoad = '/Users/sabri/Documents/code/ArrayDesigner/ArrayDesigner/HeadModels/MNI152_LowRes/';
% Load GM surface mesh to get n of voxels
load(fullfile(pathnameLoad,'GMSurfaceMesh.mat'))
nVoxels = size(GMSurfaceMesh.node,1);
% Read idx file - each row contains the number of voxels with significant
% values for ea... |
0ff980ecfc636bdfcab67d6d88618c3d39f107d120408647d72c01407813b095 | MATLAB | 1,466 | 50 | %% Load initial state from data for the large network
% Input: Inifile: Filename, string
% N_E/I: Number of neurons used here.
% EEDly, IEDly, EIDly: logical, if these delay mats will be used
% Output: InE/I: Adjusted initial conditions for E/I cells
% DlyMat: Delay Mats used
function [InE, In... |
2e4fccf884268ab561ac00b2343f1888db62471e4550fa39da074faf144cda4c | MATLAB | 1,466 | 65 | % test scatter plot assymetry effect on ICA
% Reza Sameni, Copyright 2005
%
clear;
close all;
t = [0:.001:16*pi 0];
N = length(t);
%r = ceil(t/pi/2).*sin(2.001*t).^3;% + sin(5.00*t).^5;% + .01*rand(size(t)); % + sin(t)
r = sin(2.00*t).^4;% + sin(5.00*t).^5;% + .01*rand(size(t)); % + sin(t)
[x,y] = pol2ca... |
e6716904fed2e2e78292ff22eb7e91827a9551acde8b6729717cbcce737172d7 | MATLAB | 1,467 | 39 | function data = processRestOnsetOffset(data,params)
%Process Rest Onset and Offset Data
%
% data = processRestOnsetOffset(data,params)
%
% Description: This function takes a data structure with velocity traces,
% onset and offset indicies, and fiber photometry data and aligns
% photometry to rest onset a... |
163218b8aec45bed6f54104c6497c38779927a7600b85ef973e03582cd883f11 | MATLAB | 1,469 | 55 | function boxplot_pairwise(y, colors)
% y: 2D matrix (each dataset in each column)
% colors: color to be used, N*3 matrix, each color in each row
% example
% y = rand(100,2); % one pair of y values
% boxplot_pairwise(y);
% y = {rand(100,2), rand(50, 2)+1}; % multiple pairs of y values
% boxplot_pairwise(y);
if narg... |
b0b275fc8d14564518209ec1b5b89dbe4a33a02e2ac4088c86ce9ab7ec92fbc7 | MATLAB | 1,469 | 47 | function angle = ideal_collar_angle(dim,N)
%IDEAL_COLLAR_ANGLE The ideal angle for spherical collars of an EQ partition
%
%Syntax
% angle = ideal_collar_angle(dim,N);
%
%Description
% ANGLE = IDEAL_COLLAR_ANGLE(dim,N) sets ANGLE to the ideal angle for the
% spherical collars of an EQ partition of the unit sphere S^dim... |
ee23b148b228d6154d1476249e6fd1942b26de722aed157f36cfd58026983a25 | MATLAB | 1,470 | 49 | function Stats = paired_ttest_topography(Data1, Data2, Chanlocs, CLims, StatParameters, PlotProps)
% Stats = paired_ttest_topography(Data1, Data2, Chanlocs, CLims, StatParameters, PlotProps)
%
% plots the t-values (color) and significant channels (white dots) of
% Data2 vs Data1 using chART plots.
% Data are P x Ch mat... |
c59aff63abf3e12a0638c46261d7b59f214d03f3a925ba9096290541871b821e | MATLAB | 1,472 | 57 | function [X,w,bin,fitin] = alasso(X,y,Xtest,ytest,alph,stnd,lam,gam,regp,parallel)
%regp = 'largest'; % could also be smallest, largest, or middle
if isempty(alph)
alph = 0.001; % was 0.01
end
if isempty(gam)
gam = 1;
end
if isempty(stnd)
stnd = true;
end
if isempty(lam)
[~,~,lam] = defLam(X,y,alph,stnd... |
cbac8148af85ff3eeece9ce99ba9ef4fb1c7c79e1bfbb6be29ef199c518a4359 | MATLAB | 1,472 | 57 | function [yy, criterion] = PeriodicDeflDecompositionWDEN(dat, Itr, MM, T0, T1, TPTR, SORH, SCAL, NDEN, WNAME)
%
% [yy criterion] = PeriodicDeflDecompositionWDEN(dat, Itr, MM, T0, T1, TPTR, SORH, SCAL, NDEN, WNAME)
% (maternal) cardiac signal supression by deflation using periodic component
% analysis and wavelet shrink... |
06781aa06864b60dc52a1d6cf673b33cb071edaf5afde5eb39dfbf05abb654f9 | MATLAB | 1,473 | 39 | function data = JT_processRestOnsetOffset(data,params)
%Process Rest Onset and Offset Data
%
% data = processRestOnsetOffset(data,params)
%
% Description: This function takes a data structure with velocity traces,
% onset and offset indicies, and fiber photometry data and aligns
% photometry to rest onse... |
037a48209524193aa835a4bc04f2e2de186065621b56d5796a4fdefad64d27a0 | MATLAB | 1,475 | 58 | function errorbar_with_fitcurve(x, y, curves,colors)
% x: cell or 1D array, datapoints on the x axis
% Y: cell or 2D array (dataset arranged as column), datapoints on the y
% axis
% colors: color to be used, N*3 matrix, each color in each row
% example:
% x = [1:20]';
% y = cell(1,2);
% for i = 1:20
% y{1} = [y{1}... |
19600c97a7dc869004aa47f830b60cdc9cb1c57f5b35dda29b07b0a1688cb75b | MATLAB | 1,475 | 59 | function fid_corr = LineShapeCorrect(fid,mConAmpCor,mSPhase,mT2used,sw,traf_flag)
% Applies amp and phase corrections to fid from water only signal
% Also applies traf filter to fid
% Assumes files already added (or a single file)
% FID data is dcy
% Amplitude corr is mConAmpCor; phase correction (to be added)is... |
1fb60aa8594c65f4744041320722e1e8646a11ccd8c31f7d70da570147b04438 | MATLAB | 1,476 | 41 | function sampledWindows = getSampledWindows(hClust, sampledSpikes, sites, showRaw)
%GETSAMPLEDWINDOWS
% input: sampledSpikes, a vector of spike indices
% input: sites, a vector of site indices
% input: showRaw, bool, a flag use raw waveforms if true (else filtered)
% output: sampledWindo... |
bf7638de1897d45ce69bfe7e1e09b05a97321df7b59b7778432f7b8f89813e0e | MATLAB | 1,476 | 70 | %% Ch2
close all
% clear all
idx = 4;
path = 'E:\data\DNAnanopore\030223\cell4_acsf_qx314';
filename = sprintf('230303_001.sealtest.%d.wcp', idx(1));
out=import_wcp(fullfile(path, filename),'debug');
n_channel = out.channel_no;
n_recording = length(out.rec_index);
dt = out.T(2)-out.T(1); % sample time in s
Im... |
23fd84457644748280b13ab5c78670f18f9e308e1bfe69bc3c49e628e3f93a3e | MATLAB | 1,477 | 46 | function S = metaToStruct(filename)
%METATOSTRUCT read a SpikeGLX meta file and convert to struct
[status, cmdout] = system(sprintf('file %s', filename));
% check given file is a text file
if status == 0
assert(any(strfind(lower(cmdout), 'text')), '''%s'' is not a text file', filename);
els... |
5d11f54172b042773bfbc9df2e0504ca5db928e1fb03c56da29fa5999795326f | MATLAB | 1,477 | 45 | function info = mmil_csv2struct(fname,parseflag,separator,quote)
%function info = mmil_csv2struct(fname,[parseflag],[separator],[quote])
%
% Required Input:
% fname: input file name
%
% Optional Input:
% parseflag: [0|1] whether to parse strings for arrays and matrices
% {default = 1}
% separator: separator be... |
b986ba22743b0a5c8307a3c72976cd07fdd2b9abab2810bfa5823d28fcac6d65 | MATLAB | 1,477 | 58 | % Gets line from time accumlating function of activity
%
% CumCAG=p(1)+p(2)*T+W
% Where:
% p: linear fit coeficients
% T: time in seconds [s]
% W: residue
%
% Input
% R: Matrix of activity (cells x frames)
% fs: sampling frequency
% TotalSum (optional)
% Output
% p(1)scalar slope of the line p(2): scalar y-in... |
980e57cde74bf31269ff6d0d148298e0dbc53ff05ef60180b17357528d13079a | MATLAB | 1,478 | 59 | function Plot_AG_MSPoI(options,AM,Lab_idx,NodeName,atlas,ResPath,save)
%gr = options.var_gr;
gr = options.grlabel;
atlas_name = options.atlas{atlas};
fg = 0;
for gI = 1:2%length(gr)
for Reg = 1:length(AM)
fg = fg + 1;
f = figure;
CF = AM{Reg}(:,:,gI);
... |
32af2639014eae481818a5f0740da97626c0a98cf652160e09e18b836051a1e1 | MATLAB | 1,479 | 55 | function [NewDesign,iDesign,CondIndices,DoF2] = Ragu_SortOutWithinDesign(Design,TwoLevels)
if (size(Design,1) == 1 || TwoLevels == false) % Make it a dummy two factorial if it isn't
Design(2,:) = 1;
end
% Find the original labels
OrgLabelsL1 = unique(Design(1,~isnan(Design(1,:))));
OrgLabelsL2 = unique(Design(2,... |
3e8060bceeb93226f395f42a585055b9de8aaefcc66d27924088c143a54d9cdd | MATLAB | 1,479 | 53 | function playMovieCutout(movieCutout, traceCutout, cellOutline, neighborOutlines )
% resize movie cutout (was compressed to save memory)
movieCutout = imresize(movieCutout,2);
% set display params
windowSpace = 20;
windowTime = 20;
waitTime = 1/(windowTime);
% set color values
... |
9497b6f5b24e1e0fec3ea6d2b3d7584af514f77c661626d3982640ac43a6822d | MATLAB | 1,480 | 41 | function spikeData = findPeaks(obj, spikeData)
%FINDPEAKS Detect or import spike peaks
samplesFilt = spikeData.samplesFilt;
keepMe = spikeData.keepMe;
spikeTimes = spikeData.spikeTimes;
spikeSites = spikeData.spikeSites;
siteThresh = spikeData.siteThresh;
nPadPre = spikeData.nPadPre;
nPa... |
5512bfe2a60318d55b19358219d7a50a3852f019462fbd6954657581ade70cde | MATLAB | 1,482 | 46 | function A = getSensitivityMap(array,posScalp,nS,minRho,maxRho,pathnameHeadModel,pathnameWeights)
%Load PMDF weights
PMDFweighting = load(pathnameWeights);
nD = length(array)-nS;
srcs = array(1:nS);
dets = array(nS+1:end);
%Load PMDFs of the channels of the AD array
pathnameMSHS = getMSHSpath(pathnameHeadModel);
loa... |
6ec7ba704d22fe5fc6d18e825d2dbee78c313bb4eea804b3223ed5c66f8d8989 | MATLAB | 1,484 | 51 | function min_dist = point_set_min_dist(points)
%POINT_SET_MIN_DIST Minimum distance between points of a point set
%
%Syntax
% min_dist = point_set_min_dist(points);
%
%Description
% MIN_DIST = POINT_SET_MIN_DIST(POINTS) sets MIN_DIST to be the minimum
% Euclidean distance between points of the point set POINTS.
%
% PO... |
c1b70fcee4586db74f8d3988a4223f4e94d122b36148d715cc9b7bb892e5adcf | MATLAB | 1,486 | 41 | function index = nearest_neighbor(x,vectors,maxdist,varargin)
% function index = nearest_neigbor(x,vectors,maxdist,pointdist*,pointlimit*,k*)
% x is a row vector
% pointdist (optional) - vector of standard deviations
% pointlimit (optional) - upper bound on number of points outside pointdist
% k (optional) - number of ... |
40b99af3f40e54504794d8190827333cd8f1b3d6b8e0772cf146828ed23d8154 | MATLAB | 1,489 | 50 | function s = cart2polar2(x)
%CART2POLAR2 Convert from Cartesian to spherical coordinates on sphere S^2
%
%Syntax
% s = cart2polar2(x);
%
%Description
% S = CART2POLAR2(X) sets S to be the spherical polar coordinates of the points
% represented by the Cartesian coordinates X:
% S = [phi;theta]: phi in [0, 2*pi), theta i... |
9ab96c7d4be6c92d11c1fe06816fd39ca50df78f0cb9945b2ccf7149bb32a0e9 | MATLAB | 1,492 | 45 | function [choosecolor_SAVE] = photomplotColor(setupParam,numgroups)
%%
if nargin<2
numgroups = 0;
end
comparisonType = setupParam.comparisonType;
if comparisonType == 1
choosecolor = {'k' '#61e15e' '#51c54f' '#41a940' '#328d32' '#227023' '#125414' '#023805'}; %green gradient
elseif comparisonType == 2
... |
14745e1d5f3ad647d8e6fe8bc5f97e5a7583ff38aed9bda01ec352a1daf26670 | MATLAB | 1,493 | 31 | function [kdata_simMotion, st] = apply_2DsimulatedMotion(kdata_in,mpars)
[Nx, Ny] = size(kdata_in);
Npars = size(mpars,2);
alignMats = zeros(4,4,Npars);
this_mpars = mpars;
for iT = 1:Npars
alignMats(1:3,1:3,iT) = euler2rmat(0,0,this_mpars(3,iT));
alignMats(1:2,4,iT) = this_mpars(1:2,iT);
end
alignMats(4,4,:) ... |
5a29867832e9d13927b8c10ee9b0e65ad56c5acd97b0951db3f79fe749e867f4 | MATLAB | 1,493 | 74 | %% Histamine firing function.
% Units in events/h.
%
function f = fireha(t, i_factor) %Repeated stim.
n=length(t);
r = 150;
repeat_time = 60*10;
t_start = 5;
t_flip = 7;
t_end = 15;
basal = 1;
b = 2;
max_f = 10;
stim_boolean = 0;
if stim_boolean == 0
for i=1:n
f(i) = basal.*i_factor;
end
f(f... |
6eee53bff0deec06a38277415894c6e0771bd3164a7730c42e33d3e97251817a | MATLAB | 1,493 | 45 | function data = processCC(data,params)
%Process Cross-Correlations
%
% [data] = processCC(data,params)
%
% Description: This function is designed to process the cross correlation between fiber photometry
% traces and velocity data. The parameters for the analysis are found in the params
% structure, whi... |
1a3c336a8233ae82b77aac54c263c6e4e0964e124ce90328c60ba0bdbcfaa050 | MATLAB | 1,494 | 28 | constants;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Same growth for the primary tumor and the metastases
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
SameGrowth.model = @(param, time) model_burden_nb_PT(...
[param(1), param(2:3)],... % m... |
5460c160382b48f5d21749aebcffdfc84e550593d746ca6f26eaa8bf20befec7 | MATLAB | 1,494 | 46 | %% Reproduce Fig. 1e from deposited dataset
% David Wolf, 11/2023
%
%% load dataset
clear; clc;
% paths need to be updated
load('C:\Users\David\Documents\GitHub\OXT-Wolf\data\Fig1_AON_data.mat');
addpath(genpath('C:\Users\David\Documents\GitHub\OXT-Wolf\'));
% the data.(odor) contains the binned spike counts (100 ... |
7aa0c04981bf8d763a6ba117ade121af88cc029d44735c21f25edc2f9b2ab833 | MATLAB | 1,494 | 65 | function varargout = plot(varargin)
% plot method for GIfTI objects
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
% Guillaume Flandin
% $Id: plot.m 7381 2018-07-25 10:27:54Z guillaume $
% if ishandle(varargin{1})
% ... |
0e27b794368752e0ce06861b8d47b86d4d4958e28716596b7dfb756cb2352879 | MATLAB | 1,496 | 41 | %% Sort the cells according to the sortWindow and graph
function sortAllCellsGraphFunct(traces, sortWindow, clims, binLengthStart, binLengthEnd, behaviorName, treatment)
% traces = allTracesNull; %data to analyze
% sortWindow = [50 60]; %what sample window should use to sort cell activity, activity is averaged an... |
983deffd42e7de75f20074368b211cf12bc56b0de2a103f2382669ce9add7a16 | MATLAB | 1,496 | 40 | function Plot_Brains_AG_MSPoI_1b(FinalRepPar,nodes_name,nodes_coord,at,options)
gr = options.grlabel;
for n = 1:length(nodes_name)
Name = nodes_name(n);
NodeName(n,:) = string(Name);
end
%============== PLOT BRAINS====================
% TO save data
cd /netapp/vol7_u923/SEME/SE... |
9c15f61e5a9587ba9ab2265e1ca9e936dba7ad3e91f8d24cc98a1229588a2141 | MATLAB | 1,496 | 40 | %plot_basline_per_clsuter_clsuters only for phb
[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)
%%
NDs = [10 8 6 4 3 2 1];
if ~iscell(file)
file{1} = file;
end
baselines = [];
clusters = [];
for i ... |
00103e88234403362be875b2adbe2a3477026d17f82e800a82184c1c0fe0af02 | MATLAB | 1,497 | 63 | function paths_out = fullfile(root,paths_in)
%fullfile Appends paths to a root path
%
% paths_out = sl.dir.fullfile(root,paths_in)
%
% Performs the equivalent of fullfile() on each root/pathsIn pair. It
% tries to accomplish this in the quickest way possible.
%
% Inputs:
% -------
% root : (string), root p... |
984c5824a0645df93c86c3940dea9669363c79e971d4b88dfd250b0792666c14 | MATLAB | 1,497 | 49 | function [Signal, t] = eeg(AperiodicParameters, PeriodicParameters, ...
Duration, SampleRate, WelchWindow, highpass, lowpass)
arguments
AperiodicParameters = struct();
PeriodicParameters = struct();
Duration = 20;
SampleRate = 250;
WelchWindow = 4;
highpass = .8;
lowpass = 45;
end
% Ape... |
fa042733225faa74a9f9c1837be150454de3cfe0c0b13dffe86902947bc86020 | MATLAB | 1,498 | 41 | % Model Multiclass SVM Classification binary complete
% Input:
% Xpca: Data matrix
% ONEpca: Column i-th of Xpca
% TWOpca: Column j-th of Xpca
% Y: labels
% template: Kernel SVM template
% labelconditions: Cell of strings
% Nsim: ... |
6bd970d7cb405b398a814fc599b659936b365d0dba8c57c1bb8acb4e312d1b83 | MATLAB | 1,499 | 44 | function [nrgSig_adapt_model,ts_adapt,sys,f] = adaptation_analysis(sigma,d,a,downsam,nTR)
%sigma = noise param
% d = adaptation param in equation of model
% downsam = play around with downsampling data
sys = StochasticWilsonWTA_Tash_Sigmoid_adapt(sigma,d,a); %change d params. as adaptati... |
f29a61b2764b6fedf33de7d0c05be891afff481ae9d3c34683d9033b99c5f9ec | MATLAB | 1,499 | 42 | function Pixels_List = Order_Connected_Pixels(Im_BW,P0,P1)
% This function gets a binary image and two [x,y] coordinates (P0,P1).
% It returns an ordered list of the coordinates of the 1-pixels ("white").
% The ordering is according to the connectivity, starting from P0.
% P1 is used for directionality to account... |
597ea4fbbf4d0447ab8c9c2486c62c9c27972bda8fab9e064c460613c733d5d6 | MATLAB | 1,502 | 31 | %--------------------------------------------------------
%HeRA default settings
%--------------------------------------------------------
hera_def.pulsefile_extension = 'puls';
hera_def.prepeak = 5000;
hera_def.prepeakdelay = 2; %Number of samples delay in peak detection of scanner
hera_def.samplerate... |
c646ac408304a6ef879c56bb40d71b7c2055d01a571cc727e0c03e9fa747e0a2 | MATLAB | 1,502 | 82 | function A=readmda(fname)
%READMDA - read the contents of a .mda file. MDA stands for
%multi-dimensional array.
%
% See http://magland.github.io//articles/mda-format/
%
% Syntax: A=readmda(fname)
%
% Inputs:
% fname - path to the .mda file
%
% Outputs:
% A - the multi-dimensional array
%
% Other m-files required:... |
cfc6ccf7d1ef2951f459c4168c645d6f649b855bd36452724ebdb3f1173ef52d | MATLAB | 1,502 | 46 | %
% Test program for phase shifting function.
%
% Dependencies: The baseline wander and ECG filtering toolboxes of the Open Source ECG Toolbox
%
% Open Source ECG Toolbox, version 1.0, November 2006
% Released under the GNU General Public License
% Copyright (C) 2006 Reza Sameni
% Sharif University of Technolo... |
ddb743a4fdb89c6391e338f5b63c56610992bcbeba0f6b8d5cc2c02ab2e1ff29 | MATLAB | 1,502 | 52 | function [icasig, W]=milca(x,P,kneig,algo,harm,finetune)
% Mutual Information based Least Dependent Component Analysis
%References:
% H. Stogbauer, A. Kraskov, S. A. Astakhov, P.Grassberger,
% Phys. Rev. E 70 (6) 066123, 2004
% A. Kraskov, H. Stogbauer, P. Grassberger,
% Phys. Rev. E 69 (6) 066138, 2004
% Output... |
22cde6051aeb054cb0ba097092c6795023168fcb779f67212c3c824b66573682 | MATLAB | 1,504 | 43 | %% Finding df/f using linear regression - least square fitting model
function [dF, baseline] = linregFP(iso,sig,prc)
% Description: This function will find the baseline of a signal by applying
% a linear least-squares fit between the two timeseries (that is, the
% isosbestic control signal values were the independe... |
80492d59749b0c1c322528f400da9f5a0168fe72217d5de21f9ddfdaeca5ba6d | MATLAB | 1,504 | 38 |
function [positions, EXITFLAG] = fiducial_det_lsim(data, ecg_rpeaks_index, fs, varargin)
% FIDUCIAL_DET_LSIM (DEPRECATED) ECG fiducial points detector based on LSIM
%
% [positions, EXITFLAG] = fiducial_det_lsim(data, ecg_rpeaks_index, fs, varargin)
%
% This function is deprecated and kept only for backward compa... |
0ff4a4c879aa0ff5277b9078bf89eb593aceab839ab6cf177371e844c3dc8671 | MATLAB | 1,505 | 47 | function [map, delay_bases, time_bases] = decide_bases(session, channel, unit, sigma)
% Decide about resolution of bases
%
% Parameters
% ----------
% - session: scalar
% Session number with format: yymmdd
% - channel: scalar
% Channel number
% - sigma: scalar
% S... |
5d162e309964e66c4b95ae33084e62642b730b42167a03b644d63e88ce269d14 | MATLAB | 1,505 | 49 | function Bursts = classify_bursts_shape(Bursts)
% categorizes bursts based on their average shape
% Types: Sw = sawtooth, Mu = mu wave, NM = notched mu, Sq = square, Tr =
% triangle, Sn = sinusoid
% Part of Matcycle 2022, by Sophia Snipes.
DRSYM_Threshold = .15; % this is deviation from .5
TPSYM_Threshold = .1;
Square... |
7e80c7e1f9f9485f8d4a8c86c168ce2fd392df1ea23f6fb31cf88676f7f34300 | MATLAB | 1,506 | 96 | % Created By: Ashlee Liao (ashleel@andrew.cmu.edu)
% Created: 17 February 2021
% Last Edited: 8 December 2022
% Last Edited By: V. Webster-Wood (vwebster@andrew.cmu.edu)
% Run this file to set up some forces/parameters to complement
% ModularAplysia_1282022_withSNS.slx
%close all
%clear all
%clc
%% Spring Parameters... |
624e332bba3c50c89705074bd984e2ab18ac01e1709098d82aaeda42b30e5ce9 | MATLAB | 1,508 | 39 | %% add togethter meny WF files
clear
clc
[filename, 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)
%%
all_CTP = [];
for i = 1:2:(length(filename))
load(filename{i})
'exp_num'
filename{i... |
38d660a7489d03a57297d4837fbca230614e029aa6e6497f6f62915333b87cf2 | MATLAB | 1,510 | 62 | function gym()
gym = struct;
gym.vertices = ...
[0 0 0;
0 0 0.20000000298023224;
0 0 0.60500001907348633;
0 -0 1.0059999942779541;
0 -0 1.4049999713897705;
0 1.17 0;
0 1.17 0.20000199973583221;
0 1.17 0.60500001907348633;
0 1.17 1.00600019693374634;
0 1.17 1.4049999713897705;
0.600000023... |
951a8e0b9418abcd94b766c0075bf34a0092058cb939446abc5a5a6a259aceb4 | MATLAB | 1,510 | 48 | function hirarcial_ex(N, dont_use_pca, CTP, parameter_names, i, XT)
% use hirarcial
% Load the data matrix X
% Normalize the data
X = XT{:, N{i}};
X_norm = normalize(X);
% Apply PCA to reduce dimensionality
[coeff,score,latent] = pca(X_norm);
% Find the most significant PCs
cumulative_variance = cumsum(lat... |
2ae2e43275f921c3a49503093dc9a62c04c2a4379488750ed18d8a68040bca6d | MATLAB | 1,512 | 30 | % reject_cnt() - works the same way as EEGLAB Plot - Channel activations (pop_eegplot)
% except for saving the rejected period limits in a .mat file
% with the same name as the original set
% see 'winrej' parameter in eegplot.m
% The original file r... |
a213d467bac30477b0be73e80d5df7d8da43ce856a36fcc26c491bcc54e81b46 | MATLAB | 1,512 | 49 | function sRes = sort(obj)
%SORT Cluster detected spikes
if isempty(obj.res)
obj.loadFiles();
end
obj.isSort = 1;
if ~isfield(obj.res, 'spikeTimes') || isempty(obj.res.spikeTimes)
error('no spikes to sort');
end
if ~isfield(obj.res, 'spikeFeatures')
dlgAns = questdlg... |
be9fa4946f256bb859d986f419821d30d454eeb3457551628715b64ecc392f4e | MATLAB | 1,512 | 50 | function [trans_data] = prepare_data_task_decoding_iti(p, traces, evs, bvs, tis, speed_control)
%% calc scale factors per subject
for sub = 1:p.nSubjects
all_tr = cat(2,traces{sub,:});
vars(sub) = nanstd(all_tr(:));
end
scale_factors = 1./(vars / max(vars));
for sub = 1:p.nSubject... |
e3379bfa777e1269b4e2720e676b9c35e38802504ff02589ab8bfb325e2a62f6 | MATLAB | 1,512 | 34 | function WaterMarkTurn=WaterMark(WaterOnArray, WaterOffArray, StartTime, FinishTime, TurnMarkerTime, OneTurnTime)
%StartTime©çFinishTimeÌÔÌAÅÌTurnMarkerTime©çÅãÌTurnMarkerTimeÜÅÌ
ÌÝðZoB
global DrName %WaterOnArray WaterOffArray StartTime FinishTime TurnMarkerTime OneTurnTime
TurnMar... |
5ed2af0e439cc2e673c8c9583ed69971248f108c866c00e7c3de2e42f2213ffe | MATLAB | 1,514 | 40 | function generatemaps(outfile,thr)
% This function constructs multiple networks with varying parameters. For
% each projection type, an adjacency matrix is created with. For various
% threshold values, distance matrices are computed from this matrix.
%
% generatemaps(outfile, [thr])
%
% Input:
% outfile: file... |
a1eae119904d7cc040c15bc15252b224acb744ada9f18e97af2c486dff19c4fd | MATLAB | 1,515 | 47 | function E=efficiency(G,local)
%Global and local efficiency for binary undirected graph G.
%
%Eglob=efficiency(G); outputs the inverse distance matrix: the mean of this
%matrix (excluding main diagonal) is equivalent to the global efficiency.
%
%Eloc=efficiency(G,1); outputs individual nodal local efficiency.
%F... |
973d510f013b1616eedd63b2bb8190045920ddce58956e4ca58a00edc80a46e5 | MATLAB | 1,516 | 44 | % Funtion that estimates the coefficients of Auto Regressive Process
% Input
% XD: Matrix of signals: Signals x Samples
% p: Order of Linear Predictor Coefficients (FIR-filter)
% fs: sampling frequency @ Hz
% L: Duration of Response in Seconds
% taus_0: initial taus of the AR(p) proces... |
8583504ff17a8a52a012a16728927d3c41afb451216d692d3ec3c7d7bc9b3c81 | MATLAB | 1,518 | 26 | cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\effect size\f6\c')
x = importdata("responsive_with_response_parameters_and_tags.mat")
%%
x1 = sortrows(x,"tag")
x1 = x1(find(~isnan(x1.magnitude)),:)
x1.struct_number = grp2idx(x1.tag);
stats = mes1way(x1.magnitude,'eta2','group',x1.struct_number)
%% ... |
0436fe2eeb7ff5a2fbff4c33ef9850e611bdb41ad77c03b24e21319648087f27 | MATLAB | 1,519 | 55 | function [lmxo,lmno,lms] = defLam(X,y,alpha,stnd,lmx,lmn,lamRatio,lst,ln,logPref)
%logPref = 'smaller';
if isempty(stnd)
stnd = true;
end
if isempty(lamRatio)
lamRatio = 1e-4;
end
if isempty(lst)
lst = 'log';
end
if isempty(ln)
ln = 100;
end
if ~isempty(X) && ~isempty(y) % if X and y are not empty we a... |
1fd5a97a625e408a21dc9d228537b74b4940244450c1c60e7f9bf6897d5c6d19 | MATLAB | 1,519 | 33 | % Funtion to get Odd Matrix from
% Input
% isSIGNALS: detected signals with Ca++ Transients Automatically
% notSIGNALS: retected signals Automatically
% Global Input
% indxSIGNALSOK: true signals with Ca++ Transients
% SIGNALS: Original Raw Data
% Output
% OddsMatrix: Cell Of Structure Matrix f... |
67352b9a0444b7fe914c493cb009b633128ca4778401c2b9786209103edacefb | MATLAB | 1,519 | 41 | %% Plot Data
clear all;
[FPfiles,FPpath] = uigetfile('*.mat','Select FP Files to Analyze','MultiSelect','On');
if isempty(FPfiles)
fprintf('No Files Selected');
else
if (~iscell(FPfiles))
FPfiles = {FPfiles};
end
nFiles = length(FPfiles);
[analysisOpt,ind] = listdlg('PromptString',... |
040c8652cccf7d18c1f63427da8ca19f7f85ed5036e940a4e2a65af1f8cf288f | MATLAB | 1,520 | 39 | function [ang, theta_min, theta_max, theta_mean, theta_med] = column_subspace_angle(A, B)
% column_subspace_angle - Compute angle between the column subspaces of matrices A and B.
%
% Syntax: [ang, theta_min, theta_max, theta_mean, theta_med] = column_subspace_angle(A, B)
%
% Inputs:
% A: Matrix A with dimensio... |
561bc63c3a06c8afba56b0028137c19a9eafb50be7c15f6ca1b3dec04a1b325d | MATLAB | 1,522 | 42 | data = clusters.cluster_cells.cluster_2{15}.intensities;
%%
%bin and interpulate
plot(data(1).psth.mean)
%%
for i = 1:clusters.num_of_cells(2)
psth = clusters.cluster_cells.cluster_2{i}.intensities(1).psth.mean;
interpulated_psth(i, :) = bin_psth(psth, 5);
mximum_psth(i) = max(abs(interpulated_psth(i, :... |
60daf3e78851764e6040480ad1a57e506aa3fad5df62caae04f04631151051cc | MATLAB | 1,525 | 40 | function y = tikhonov_regularization(x, diff_order_or_filter_coefs, lambda)
% tikhonov_regularization - Tikhonov Regularization.
%
% Syntax: y = tikhonov_regularization(x, diff_order_or_filter_coefs, lambda)
%
% Inputs:
% x: Input signal (Channels x Time).
% diff_order_or_filter_coefs: Smoothness difference order (... |
b2eba5dbba9f4c5123ede553695a2ead7458cd513e17b9a324cbe3f7afd0ac22 | MATLAB | 1,525 | 48 | %load atlas
annotation_volume_location = 'C:\Users\elyashivz\Documents\analyzing_slices\annotation_volume_10um_by_index.npy';
structure_tree_location = 'C:\Users\elyashivz\Documents\analyzing_slices\structure_tree_safe_2017.csv';
if ~exist('av','var') || ~exist('st','var')
disp('loading reference atlas...')
av... |
dbad1e082faddcc7535b343cca7e11a929eb6ad3677234fbbb88e7e4650af948 | MATLAB | 1,525 | 64 | % Sample code for testing naive maternal template subtraction technique
%
% Reza Sameni (C)
% Email: rsameni@shirazu.ac.ir
% Web: www.sameni.info
%
% Crated June 2018
clc;
clear;
close all;
load('SampleFECGDaISy');
data = cell2mat(data);
fs = cell2mat(fs);
L = size(data, 1);
N = size(data, 2);
mref =... |
8d9e4f7fe9f4aacf503409eecc9b0a53c86f3c810b477f2b3d6c97dd599f7c40 | MATLAB | 1,526 | 53 | classdef (Hidden) handle_logger < handle
%
% Class:
% adi.handle_logger
%
% This is hopefully a temporary class that logs open and close
% operations.
properties
fid
end
methods
%TODO: Make private
function obj = handle_logger()
%Ca... |
8fd94071dfe9470f39326b8120475de7a5fa25d33be247afd1eccda96b2272c4 | MATLAB | 1,526 | 70 | %% this script can be used to generate coarse alignment coordinates
% we do this if the automatic alignment fails because there are
% large scale rotations or translations
%% load maps
p = params_FC;
sub = 4; % thisSub = 82
for ses = 1:p.nSessions
thisSub = p.subjects(sub);
fpath = fullfile(p.rootDir,'minisc... |
b9898f76d95b9259c3d8ee00a0f0225e47297470a8a437ee3a0bf9bec29d04d7 | MATLAB | 1,526 | 40 | clear all, close all
load time_data.mat
%% Plot time data, with Membrane off-on-off
nobio_range = (osc_sim.time > 0.2) & (osc_sim.time < 49.5);
bio_range = (osc_sim.time > 49.5) & (osc_sim.time < 100);
toxin_range = (osc_sim.time > 100);
fig = figure(1);
fig.Color = [1 1 1];
fig.Position = [0 10 600 450];
... |
ccfaba416fbcc8f89d8f01416b75e55ea9b66d35a27276cbd5ae939b5334008c | MATLAB | 1,528 | 38 | function adaptive_thresholding(stat_filename, mask_filename, spm_mat_file, con_index)
% read the data (spmT and mask), call the Gamma-Gaussian Mixture code and
% then apply this threshold to save the threasholded image with topo FDR at
% q=0.05
%
% FORMAT: adaptive_thresholding(stat_filename, mask_filename, spm_mat_fi... |
5c3f271329f793dcc56656045cb8f3ed537792ac98357387dfe2c64ed0e65715 | MATLAB | 1,530 | 48 | function [ output_args ] = runAlignment( p )
%ALIGNJOINT aligns cell maps of all sessions for each subject and saves
%registration tform
%% load maps
for sub = 1:p.nSubjects
for ses = 1:p.nSessions
thisSub = p.subjects(sub);
fpath = fullfile(p.rootDir,'miniscope', ['subject' nu... |
a1ae40f7fc458b2963ea7bbe9388973d3b80dc6449958a1bf8a45dbe5bdaf327 | MATLAB | 1,531 | 66 |
%root_dir = '/servernas/images2/romain/data/spectro/hipo/repro_study/fid_pos_nii';
anat_dir = '/home/romain/data/spectro/hipo/repro_study/anat';
coreg_inter=0;
if coreg_inter
jobs = {};
log_file='log_coreg.log';
d1 = get_subdir_regex(anat_dir,'HIPO_..$');
for nbses=1:2
if nbses==1
d2 = get_subdir_regex(anat... |
3a528b1829b4895ae1ef961b3cd9306bd0fdc80d1a20feb82569b008f4192134 | MATLAB | 1,532 | 40 | function [ nexFile ] = nexAddInterval( nexFile, intervalStarts, intervalEnds, name )
% [nexFile] = nexAddInterval( nexFile, intervalStarts, intervalEnds, name )
% -- adds an interval variable (series of intervals) to nexFile data structure
%
% INPUT:
% nexFile - nex file data structure created in n... |
f47055f28c65cdb0ee3d6697e12ec35c5d1891b78cfc5844898de2a4d93bae80 | MATLAB | 1,533 | 45 | function Bursts = detect_bursts_all_channels(EEGBroadband, EEGNarrowbands, NarrowbandRanges, ...
CriteriaSets, RunParallel, KeepTimepoints)
arguments
EEGBroadband struct
EEGNarrowbands struct
NarrowbandRanges struct
CriteriaSets struct
RunParallel logical = false
KeepTimepoints = ones(1, siz... |
54e4dd019f732b03349fafb0e7a7be37a0e7a15dd1566c96d576319d9dfe68ef | MATLAB | 1,534 | 42 | function [spikeTimes, spikeMat, tVec] = poissonSpikeGen(fr, tSim, nTrials)
% Poisson process to simulate spike train
%
% [spikeTimes, spikeMat, tVec] = poissonSpikeGen(fr, tSim, nTrials)
%
% Description: This function uses Poisson process to
% simulate spike trains that have characteristics close to real neurons... |
8fd933cfc1ccd42739543cf3da5ea2e519e7aa9e5517fa116d6a0fb4597025ea | MATLAB | 1,534 | 52 | %clculate IR for LFP
mkdir('LFP_ir')
cd('LFP_ir')
%%
time = -2.999:0.001:16.001';
binsize = 1000;
x = [15.400000000000000;14.900000000000000;14.400000000000000;13.900000000000000;12.900000000000000;11.400000000000000;9.400000000000000];
st = fieldnames(meanLFP);
for i = 1:length(st)
f1 = figure;
f1.Position = ... |
6905abcdeeef1f6352e737f59d711ada4b5976891fbb101004ed597c9efe59c3 | MATLAB | 1,535 | 49 | function out = rst_dynamicdprime(data,quantile)
% compute the dynamic d prime based on the vincentization of RT
% data is a matrix of RT (column 1) hits (column2) and stimulus codes (column3)
% quantile is the number of bin to do
% out is the result
% take stimulus info
% ---------------------
Stim = data(:,3);
% s... |
cc6ca2026c79e57db8d066853eb4b87c254016620aaa3065ec7a898ebe88952b | MATLAB | 1,535 | 43 | function [ecg, phi] = ecg_gen_gmm(phi, theta0, alpha, b, theta)
% ecg_gen_gmm - Generate synthetic ECG using a Gaussian mixture model.
%
% Syntax:
% [ecg, phi] = ecg_gen_gmm(phi, theta0, alpha, b, theta)
%
% Inputs:
% phi: ECG phase calculated from real ECG.
% theta0: Desired phase shift of the synthetic ... |
53f9dfaf070a53f059bf2c7bb5f8babd7fdf56c9475f078e303f464caa11fdeb | MATLAB | 1,537 | 70 | %% this script can be used to generate coarse alignment coordinates
% we do this if the automatic alignment fails because there are
% large scale rotations or translations
%% load maps
clear
p = params_2DAA;
sub = 4;
for ses = 1:p.nSessions
thisSub = p.subjects(sub);
fpath = fullfile(p.rootDir,'miniscope', ['... |
d3bb99a97216544ff4282236e7d36da17c85891a6c1ab673010ecf4c2fdc1533 | MATLAB | 1,537 | 43 | clear all
load data_oscillation.mat
%% Current oscillation
f = figure(1);
f.Position(3:4) = [540 365];
lines_width = 1.5;
ax1 = plot(i_sim.t-min(i_sim.t), i_sim.i,'Color','#F5266D','LineWidth',lines_width);
hold on
time_sel = i_meas.t > min(i_sim.t) & i_meas.t < max(i_sim.t);
set(gca,'ColorOrderIndex',1) ... |
da6d2a7a56568761e7f744729da24f2af1d84d009ae4647d93d8ad4aa64eb433 | MATLAB | 1,537 | 36 | function correlationplots(h,data)
%% Draw plots showing relative input distribution
% autocorrelatemap() and crosscorrelatemaps() depend on this function.
load('structures','groups');
axlabels1 = {data.label{1},'0.5','0','0.5',data.label{2}};
axlabels2 = {data.label{1},'0.75','0.5','0.25','0','0.25','0.5','0.75'... |
4eb7d15ceb757dbd073042508a322717b709d9e17bc0219b438ad54b48e48a87 | MATLAB | 1,540 | 53 | classdef DetectController < handle
%DETECTCONTROLLER
%% CONFIGURATION
properties (SetObservable, Transient)
hCfg; % Config object
end
properties (SetAccess=private)
errMsg;
isError;
end
properties (Access=private)
importTimes; % spike times already... |
94e10870bf5c27e8b81e62618b0e05017be0f0e486c7153c8b371dd81483881b | MATLAB | 1,540 | 79 | function [smoothedLabels,bf,org_l] = RaguSmoothLabels(V,M,b,lambda,start,stop)
% function [l,org_l] = RaguSmoothLabels(V,M,b,lambda)
%
% Where V is the voltage vector(Ne x Nt)
% M is the microstate vector(Nu x Ne)
% b is the window size
% lambda is the non-smoothness penalty factor (should be betwe... |
54d68a9cdfab85852542d8eb743483e981d8fb67763f6c23f1f8d235f84227c9 | MATLAB | 1,541 | 80 | function [FISRT LAST] = sortFirstLast(t_ECG,t_SPIKES,ind_SPIKES)
% t_ECG=t_events,
% t_SPIKES,
% ind_SPIKES=1:length(t_SPIKES);
t_CORTOpeak=t_SPIKES(ind_SPIKES)';%ECG_RESULTS.t_events; %BELT_Rpeak;
t_LUNGOpeak=t_ECG;%t_maxima(1:end);
N_ipol=50; %interpolation
%RR interval
rrint=[];
tint=[];
for i=1:length(t_CORT... |
2315ce1cbb02ca7b22690b7c8ad5afde15dabfcbae81322780c0681983deb1d9 | MATLAB | 1,542 | 56 | function result=rectify_shape(Rspimage, shape, COR_level, minvo, Rsp, Radi)
wide=512;
[I,J]=ind2sub([512,512],shape);
mI=floor(mean(I));
mJ=floor(mean(J));
I1 = max(1,mI-Radi);
centerX = mI-I1;
I2 = min(wide,mI+Radi);
J1 = max(1,mJ-Radi);
centerY = mJ-J1;
J2 = min(wide,... |
e737448ac747d49c8f46243508d2611d6492a009512b963cc7c2c5bb29227925 | MATLAB | 1,542 | 60 | function AG_MN = AG_MSpoI2(MSPoI,idxNE,idxEX,options)
% This function compute the agreement matrix acros MSPoI, for each regime
%% IF COMPUTING AG ACROSS ITERATIONS AND ACROSS SUBJECTS
AG_MN = {};
for Reg = 1:length(MSPoI.MSPoI.Par)
MLP = MSPoI.MSPoI.Par{Reg};
tot_fr = length(idxNE... |
75e0bd25e1fe17372c7e375e2fd488548bf26fc7c44635a0b4c88f01cee88805 | MATLAB | 1,543 | 44 | function ids = findexperiments(varargin)
%% Find experiments with specific conditions
% For example based on structure ID, strain or gender
%
% exp_id = findexperiments(Variable, Value, ...)
% exp_id = findexperiments('all')
%
% Input: either 'all', or a list of Variable-Value pairs where:
% Variable is an ex... |
2c201c3341eca90847d2818ee5f59062320ea02de23ad9cad3b642b95e578b2d | MATLAB | 1,545 | 72 | %kalman filter of white white noise signals sample entropy
clear all
close all
% Data Sampling Rate: 100 Hz
fs = 100;
% Generate white noise signals
EEG1 = powernoise(0, 50000,'normalize',true);
% Visualization of raw signals
EEG1=EEG1';
lenofEEG1 = length(EEG1);
tEEG = (1:length(EEG1))/fs;
subplot(311)
... |
86ad4ca965f6c4cc5c7d2ff99e3fc4830ca28223a19c080a5ad5e0764e4b278f | MATLAB | 1,545 | 44 | function success = compileCUDA(nvccPath)
%COMPILECUDA Compile CUDA codes for JRCLUST
gpuD = gpuDevice(1);
if nargin < 1
if ispc()
nvccPath = sprintf('"C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v%0.1f\\bin\\nvcc.exe"', gpuD.ToolkitVersion);
else
[ecode, ou... |
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