sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0b30b5088b0e01eba281ee5773963b36e3ec9709c6081f08e402b2b71274d6b3 | MATLAB | 1,100 | 35 | function [AutoCo]=AutoCorr(Array,duration,Direction)%binÍhistOtÌש³iªj
%¼ûüÌêASÌÅdurationÌ·³ÉÈéæ¤ÉµÄ¢éB
Array(Array==0)=[];%Excel©çf[^ð¼ÉÁÄ«Ä¢éêA0ÅßçêÄ¢é±Æª é
Array=sort(Array);
AutoCo=[];
if Direction==1 %Ðûü
for n=1:length(Array... |
4c217bf8a0c41be93216c3a23f884993a5d2f05901688a49e9014e859f2b8667 | MATLAB | 1,100 | 24 | function meanfigure
cd('C:\Users\C238\Desktop\touchcellLtRt_matsuda');
load('FiringRate_TouchCountData.mat');
RtRepeat5TouchSpike4FR_BinMeanArray=[];
RtRepeat5TouchSpike4FR_BinStdArray=[];
RtRepeat5TouchSpike4FR_BinArray
for d=1:5
RtRepeat5TouchSpike4FR_BinMeanArray=[RtRepeat5TouchSpike4FR_BinMeanArray mea... |
177dd839c0083ec02e84c7b4941776ded9217b6255338f889fed2344e7daa4fa | MATLAB | 1,101 | 27 | function phase = phase_shifter(phasein, teta)
% phase_shifter - Phase shifter; used for shifting the ECG phase signal
%
% Usage:
% phase = phase_shifter(phasein, teta)
%
% Inputs:
% phasein: Calculated ECG phase
% teta: Desired phase shift. teta>0 and teta<0 corresponds with phase leads and phase lags, re... |
96a457d033ff2d8a3fe7986d0b156f4f635de40f16a6e15f256b915cebee8f40 | MATLAB | 1,101 | 30 | % Authors : Simon Wadle 2019-2023
%function corrects movement by utilizing the NormCorr Package
function motion_corrected_data = NormCorrWidefield(Yf)
gcp;
addpath('NoRMCorre');
%Yf = read_file(name,1,200);
Yf = single(Yf);
[d1,d2,~] = size(Yf);
%% perform some sort of deblurring/high pass filtering
gSig = 7;
gSiz = ... |
0b786f93a1c258c7397fdc06079885132aa03330be522a1aceb13e8cfcd0fd01 | MATLAB | 1,102 | 43 | function FourierfunctionAC
%UNTITLED2 ±ÌÖÌTvð±±ÉLq
% Ú×à¾ð±±ÉLq
global ACresult ACresultW fname tfile AAC figAC
bin=500;
figAC=figure;
subplot(2,1,1);
plot(linspace(1,5000,bin),ACresult,'color','k');hold on
plot(linspace(1,5000,bin),ACresultW,'color','b');
ylabel(['AC'])
M=mean(ACres... |
549ea70e6d9179dee875b69e17aa6797c160dfa8a271820cfbf3e4396804f765 | MATLAB | 1,102 | 26 | function [zProb, zGenProb] = mean_center_timescore(ProbAll, GenProb, PreserveDim)
% [zProb, zGenProb] = mean_center_timescore(ProbAll, GenProb, PreserveDim)
% GenProb is a P x 2 matrix, with the first column indicating the mean
% general probability of an event, and the second column the standard
% deviation. This func... |
56a3bc4034348bceeb6958986ae6a212a3519b54d9bb45c6db91cd8cfba198c8 | MATLAB | 1,102 | 34 | function [spiketimes, trials, groups, trialStarts] = createExampleData
% createExampleData Generate random spike times for testing spikeRasterPlot
% [times, trials, groups, starts] = createExampleData() Generate a random
% spike times for two neurons across 20 trials.
% Copyright 2020-2021 The MathWorks, Inc.
% Creat... |
07f5fd1c1d5312d749bc5102a1f479dbdbc3a4d89ffc6e02103c5ce11b4b6421 | MATLAB | 1,103 | 47 | function DB=hbf_BEMOperatorsB_Linear(meshes,coils)
% HBF_BEMOPERATORS_B_LINEAR make DB matrices for linear-basis BEM
%
% DB=HBF_BEMOPERATORS_B_LINEAR(meshes,coils)
% meshes: BEM geometry, [N x 1] cell array of hbf structs
% coils: coil description, hbf struct
%
% DB: DB matrices in [N x 1] cell array
%
% v160229... |
521736a9b58357d6088272a46fb751eb0c35de6e3e9e94344df01670dfa414b8 | MATLAB | 1,103 | 28 | function [Segments,Traced_Segments] = Trace_Short_Segments(Data)
Min_Segment_Length = Data.Parameters.Tracing.Min_Segment_Length;
[Im_Rows,Im_Cols] = size(Data.Info.Files(1).Raw_Image); % TODO: this is already computed in the parent function.
Segments = Data.Segments;
Traced_Segments = zeros(1,numel(Segments... |
c772b9abd586879f9e11953b2a81db75589dbe92862c248bfee319d7cd68851e | MATLAB | 1,103 | 33 | function y = HRSmoother(x, ExcludedHR, wlen, varargin)
%
% HR = HRSmoother(x, ExcludedHR, wlen, RefLevel),
% Heart rate smoothing
%
% Open Source ECG Toolbox, version 2.1, September 2010
% Released under the GNU General Public License
% Copyright (C) 2010 Reza Sameni
% Shiraz University, Shiraz, Iran
% reza.s... |
8c19438cb5b683550723de24addd87a23423a9242094a32a0933dc2afeac2df7 | MATLAB | 1,106 | 51 | function NosePokeDrinkAnalysis
close all
cd('C:\Users\B133_2\Desktop\NosePokeData');
for N=2:7
% FileName='101_180119'
% FileName=[int2str(N),'01_180119'];
FileName=[int2str(N),'_180406'];
eval(['load ',FileName,'.mat -ascii;']);
eval(['data=X',FileName,';']);
StartTime=data(1,2);
StopTime=data(1,... |
145da494dfe4ff4a6dbaab8a79d9c9029c262f85d46eff5deadbbdca051c8593 | MATLAB | 1,107 | 59 | function [o no]=get_subdir_regex(indir,reg_ex,varargin)
if ~exist('indir'), indir=pwd;end
if ~exist('reg_ex'), reg_ex=('graphically');end
if length(varargin)>0
o = get_subdir_regex(indir,reg_ex);
for ka=1:length(varargin)
o = get_subdir_regex(o,varargin{ka});
end
return
end
if ~iscell(indir), indir={indi... |
48997ea91e4b9620b0b2917ae9a5d389b0ebcd38d2390240260ebd5b4f0c7231 | MATLAB | 1,107 | 48 | function mnl_InsertProgressTrackerInLoops(i,n)
%Inputs
% i=the current number
% n=the total number of loops to do
persistent i_prev_prct;
PcValue=(i/n)*100;
rPcValue=round(PcValue,1);
if rPcValue==100 && i<n
PcValue=99.9;
else
PcValue=rPcValue;
end
msg=sprintf('%s\n','Percent Complete...');
%% Print message... |
e55441cfc8d1a385a978008f45380dd309c99f4d07d8cb29053a6e6bd2b3d9e5 | MATLAB | 1,111 | 20 | function [ShiftedArray]=ShiftArray(Array,TurnMarkerTime)
% global OneTurnTime
Array(Array==0)=[];%Excel©çf[^ð¼ÉÁÄ«Ä¢éêA0ÅßçêÄ¢é±Æª é
%ArrayðTurnMarkerÅØèæÁÄ
ShiftedArray=[];
for n=1:length(TurnMarkerTime)-1
tempArray=Array(Array>TurnMarkerTime(n)&Array<Tu... |
1a7127a7f7c16f7f5cefbe0f73399f1a385c7690c057abfbf096585ddfad5aca | MATLAB | 1,112 | 54 | % fastICA test
% Reza Sameni, 2005
close all;
% teta = -4*pi:.01:4*pi;
% r = 1*sin(5*teta).^9 + 1*sin(teta);
% [s1,s2] = pol2cart(teta,r);
% N = length(teta);
Wp = .2;
Ws = .25;
Rp = .5;
Rs = 60;
[N, Wn] = ellipord(Wp, Ws, Rp, Rs);
[B,A] = ellip(N,Rp,Rs,Wn);
N = 1000;
n = 0:N-1;
s1 = sin(2*pi*.003*n).^2;
s2 = 1*on... |
52600d12ee5cd36d04547e2a25f0211aa347b3c627fe9e50b2cd8454ea226afb | MATLAB | 1,112 | 26 | close all
clear all; clc;
s = load('peak_distanse_control_before.mat');
m = load('peak_distanse_control_after_saline.mat');
l = load('peak_distanse_control_after_hcl.mat');
dis_before = s.peak_dis;
dis_after_saline = m.peak_dis;
dis_after_hcl = l.peak_dis;
bin_edges = 0:0.001:0.2;
figure
histogram((dis_be... |
c14b7d213b5165cb3af0bbfbbf70aa7b732cecb7fb351ee8714389d63e29c72a | MATLAB | 1,112 | 36 | %Shinjini Kundu (c) 2015
function [ B,T ] = Gen_Stack( IMAGES )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
slices = size(IMAGES{1,1},3);
for k = 1:slices
BIG = [];
MEAN = [];
for i = 1:size(IMAGES,1)
BIG1 = []; MEAN1 = [];
center_image ... |
b6565bc4f83928bcc6a493fed2212cb1289735ce883ef770eb2a5584dd47371f | MATLAB | 1,113 | 52 | % test fetal ECG preprocessing
% Reza Sameni
% July 2018
% Revised:
% Oct 2020: obsolate psd replaced by pwelch
clc
clear;
close all;
load('FOETAL_ECG.dat'); data = FOETAL_ECG(:,2:end)'; clear FOETAL_ECG; fs = 250;
% load patient165_s0323lre; data = data(:, 2:6)'; fs = 1000;
N = size(data, 2);
% make the data no... |
cfa44660186abe2071e5f992d1995a55ab616efab4ed56792865a1a74ed4ce4f | MATLAB | 1,113 | 41 | function argpair = fatrix2_construct_args(ob, varargin)
%function argpair = fatrix2_construct_args(ob, options)
%|
%| Given a fatrix2_block object, return a cell array of name, value pairs
%| such that the object could be re-constructed by
%| ob = fatrix2(argpair{:})
%| This is useful for constructing variations of th... |
1ee6b5f113404306b9cdc79400799551437378c7f9b2c64f8bfaa1a520b84e7f | MATLAB | 1,114 | 27 | function proj = templateFeaturesBySpike(obj, spikes, sites)
%TEMPLATEFEATURESBYSPIKE Get template features features for selected spikes on given
%sites
nSites = numel(sites);
nSpikes = numel(spikes);
proj = zeros(nSites, nSpikes);
iFeatures = obj.templateFeatures(:, spikes);
uniqueTemplates... |
3db745a0d68987c2b362614dfb8aa397f5858159531568284ee4e2b741d21db7 | MATLAB | 1,114 | 37 | % Function to re-label hebbian sequence
% Input
% labels: Vector sequence of neural ensemble instances
% HebbSequence Vector of Ensembles Sequence
% mode: 'sequence','2-freq'
% Output
% relabels resorted sequence of neural ensemble instances
function relabel=relabel_ensembles(labelsEns,HebbSequenc... |
ea7d1fdf0d05fbe807170a9dacae8db664be6d742bad5a0044fdf8a71ddc5b17 | MATLAB | 1,114 | 37 | addpath('functions');
addpath('demo_data')
addpath('perturbation')
addpath(genpath('results_figures\sp_results'))
load('patient_data.mat');
% 1 is a seizure-free case, 2 is a non-seizure-free case
% patient_number = 1 % Uncomment this line if running script from here
patient = patient(patient_number);
%% Un... |
968c1ac72b8db1415ae2b45424151a034ff9932c06220692d76b69cccca731af | MATLAB | 1,117 | 37 | function [Centroids,AllPoints,RealClusterIDs] = mnl_GenerateDemoClusters_2d
Centroids=[1 2;1 8;2 2;3 8;4 1;4 5;4 6;7 1;8 4;9 7];
szCent=size(Centroids);
NumPointsPerClust=25;
AllPoints=nan(szCent(1)*NumPointsPerClust,szCent(2));
RealClusterIDs=nan(szCent(1)*NumPointsPerClust,1);
NoiseSpread=0.333;
for i=1:szCent
tP... |
833ab5428920b2953125f56c80ad371ec6264ab7b6d1123a159c708b60b9751e | MATLAB | 1,118 | 36 | function points = centres_of_regions(regions)
%CENTRES_OF_REGIONS Centre points of given regions
%
% points = centres_of_regions(regions);
% Copyright 2004-2005 Paul Leopardi for the University of New South Wales.
% $Revision 1.10 $ $Date 2005-06-01 $
% Documentation files renamed
% $Revision 1.00 $ $Date 2005-02-12 $... |
773f4d42b64516392f25b39f1d42801675baf0b7ea9d6b9736a610b0153b27d7 | MATLAB | 1,119 | 37 | function Trials = load_task_output(Participants, Sessions, Task, Paths, RerunAnalysis)
% single function to load main outcomes for PVT and LAT.
% LAT types are Lapses, Late, and Correct Responses.
% PVT types are Lapses (<.5), Correct Responses and Bugs.
% From Lapses-Causes.
TaskDataDir = fullfile(Paths.AnalyzedData,... |
aa584913736742af3dd92efa4434640fdc064308775625900711885530a0f9ae | MATLAB | 1,119 | 33 | function [mesh,success]=hbf_CorrectTriangleOrientation(mesh)
%HBF_CORRECTTRIANGLEORIENTATION checks orientation of triangles and
% corrects it to CCW (works only in the simplest case).
%
%[mesh_out,success]=HBF_CORRECTTRIANGLEORIENTATION(mesh_in)
% mesh_in: the mesh to be checked/corrected; hbf struct for triangle ... |
b348fce461894facea48bd69234309cd9b2f52155f3add5e0ed0e192d26a4d1a | MATLAB | 1,119 | 33 | function success = revert(obj, revertTo)
%REVERT Summary of this function goes here
success = revert@jrclust.interfaces.Clustering(obj, revertTo);
if success
good = find(obj.clusterCenters > 0);
% find both empty cluster centers and centers that don't belong to
% this cluster
... |
b2c5a889daf09091c1a4d83bdf3b5d2bab590156e493f59cd9674dbbc14ed710 | MATLAB | 1,120 | 43 | classdef comments_comparison < handle
%
% Class:
% adi.file_comparison.comments_comparison
properties
n_comments1
n_comments2
%Comments in 1 only
%Comments in 2 only
%----------------------------------------------------
%ID:
... |
d022c966b093453a441ad2d0c379e26d04eb12ae5165aad1a4dcf9dd7f94f392 | MATLAB | 1,120 | 29 | % function to idnetify if a neural ensembles is a subset
% from another neural ensemble
% Input:
% NeuroVectors: Matrix where 1 is for active Neuron Index
% Ouput
% EnsemblesIndx: Columns of Ensembles which belong to Other:
% [i,j]: ith ensemble is member of the jth ensemble
function Ensemble... |
e51058c08c36a1ee4426dfb2eb2dfd3d5611f8328da25e2fd9661b614ffb6179 | MATLAB | 1,120 | 34 | clc;clear;
load 'gradient1-3 data'
load 'subject infomation'
nsubs = 1790;
nROIs = 1533;
%%
%**********************************************step1 : Caculate Global Dispersion
for i=1:nsubs
cen1 = median(gradientAll1(i,:));
cen2 = median(gradientAll2(i,:));
cen3 = median(... |
f0ddf354bc424475c493f047e4d14739ef6d03de320a8f9264ab89896e42694c | MATLAB | 1,121 | 30 | % Function to denoise signal bye wavelet analysys
% It use the 'sym8' and the degree increases
% until the autocorrelation finds a local minimum
% Input:
% xd: signal
% Ouput
% xdenoised: denoised signal
% noisex: noise=xd-xdenoised
function [xdenoised,noisex]=mini_denoise(xd)
dbw=1; % Degree (Or... |
1bb8918bd7a7463190dd670751aae73311dca8b869dc0796704e7d00c654f187 | MATLAB | 1,122 | 61 | %% plot_LFP from all channels LFPs
clc
clear
load("E:\PFC\LFP\all_locations\all_chennels_each_eria.mat")
plot_example_lfp = 0;
%%
fields = fieldnames(all_channels_LFPs);
for i = 1:length(fields)
figure
T = all_channels_LFPs.(fields{i});
for w = 1:size(T,1)
for j = 1:size(T,2)
T2(w, j,:... |
27356a430c1b922a1db5b424a2b9be175b52b1fd80041bd3dfeb4a2f1479a66a | MATLAB | 1,122 | 33 | function [h,CV] = benhoch(p,FDR)
% [h,CV] = benhoch(p,FDR)
% Benjamini-Hochberg Procedure to address false discovery rate (FDR)
%
% INPUT VARIABLES
% p : vector of individual p-values
% FDR : false discovery rate (default = 0.05)
%
% OUTPUT VARIABLE
% h : Benjamini-Hochberg adjusted hypothesis test
... |
11db9e4e215b7d6311990652e532b5e051d71dd8a20ef2da677cb17170469f3e | MATLAB | 1,123 | 40 | % here we further analyze how consistent the neural dynamics of individual
% subjects is with the found joint one
clear
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'allData.mat');
load(fpath,'evs','tis','bvs','traces')
%%
fpath = fullfile(p.data_dir,'dr_validation');
saveData = 1;
saveFigs = 1;
n_rep = 80;... |
a092db1cf443bad52e3d3dc9680f113fa8913655bcb4e6ec9e84c43b0e2c1658 | MATLAB | 1,124 | 43 | % HMM batch processing example by Yunxiang Zhang (yxzhang@gmail.com)
%last updated Nov 12th, 2021
path = '/Users/brunger/Dropbox/archive/programs/single_molecule/HMMbatchscript/examples/film2';
%% Find smm files
cd(path);
matfiles = dir(fullfile(path, '*.txt'));
nfiles = length(matfiles);
disp(nfiles);
for... |
b4011d838759b9df74671142372247038abcbf358391b7cd2650387bc69dd920 | MATLAB | 1,124 | 26 | function plot_line_arrow_therapy(ax, t_start, t_end, plot_line_t_start)
font = 18;
axes(ax)
y_lim = get(ax, 'YLim');
if exist('t_start', 'var') && ~isempty(t_start)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Lines
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
ec7592a5ccb661bd60773c2c302fabb69ac66f4bbb036b1513252b2da029d9a6 | MATLAB | 1,124 | 46 | function [] = plotCORR(val1, val2, label, stim, COPE_texts, color)
% This code is to plot the correlation between two groups
%
%
% inputs:
% val1:
% val2:
% label:
% stim:
% COPE_texts:
% flag:
%
%
% by Hiro Taiyo Hamada, 2020/12/17,
clear COPE; close all;
count = 1;
n1 = length(val1);
index = find(~is... |
f2e7548f3cf5fc04a8461cf9f3549d55a1f0f9c8de4b075a999f148432e196d4 | MATLAB | 1,124 | 43 | % A test script for warping_transform function
clear; close all; clc
% Example 1:
% Generate warping matrix using quadratic interpolation
in_len = 50;
out_len = 57;
interp_order = 2;
M = warping_transform_col(in_len, out_len, interp_order);
% Example 2:
% Define input and output knot points
% in_knots = [1, 50, 100, ... |
7b6d6afa58bf32765b7a793b78d9877d5c3e958bc2795a7f986c5b549e49b155 | MATLAB | 1,127 | 44 | % Make Line Sequence a Vector of Values of Dsicrete Onset Times
% Input
% Onsets x values
% yvalues y values
% varargin if any intervals (optional)
% Output
% xseq
function [xseq,yseq]=makelineseq(Onsets,yvalues,varargin)
% If there are Intervals
if ~isempty(varargin)
IntervalsX=vara... |
20fea6d32bf368d48ae82c79567d8d887ce0a28efa1346df17c5136201b996a2 | MATLAB | 1,129 | 27 | function [f,findx]=getfgrid(Fs,nfft,fpass)
% Helper function that gets the frequency grid associated with a given fft based computation
% Called by spectral estimation routines to generate the frequency axes
% Usage: [f,findx]=getfgrid(Fs,nfft,fpass)
% Inputs:
% Fs (sampling frequency associated with the data)-... |
60e8a654b010bc5fc84f0214ae88f373ab2c75ac876a17172d9f22bdbc2e1a8d | MATLAB | 1,129 | 1 | function [tv,g]=rst_tvar(x,percent)
% function [tv]=tvar(x,percent)
% Returns the estimated squared standard error of the trimmed mean of x.
% x must be a vector. If x is empty, then NaN is returned.
% percent must be a number between 0 and 100
%
% The trimmed variance is calculated from the winsorized variance, vw,
%... |
813044f81dd56ba124f37f1148c32c29bb7f11f2280a1c3cec61b67c6db74ca8 | MATLAB | 1,129 | 39 | % Authors : Simon Wadle 2019-2023
%function reads coordinates from PrarieView log files and gives x, y
%coordinates in MATLAB format
function coordinates = read_coordinates_from_txt_file(txt_filename)
fid = fopen(txt_filename);
information = fscanf(fid, '%s');
fclose(fid);
x_idxs = strfind(information, 'x'... |
3082e3b84a220f2d288311938222fb6e38efd48d83026ba96a5f0ceb3025f8b4 | MATLAB | 1,131 | 34 | % Feature Extraction
% Input
% xdenoised: clean signal (by wavelet analysis)
% noisex: noise(by wavelet analysis)
% Output
% SkewSignal: Skewness from denoised signal
% SkewNoise: Skewness from noise
% SNRbyWT: Signal Noise Ratio [dB]
% ABratio: Max Peaks Aplitudes Ratio
function [SkewSig... |
9d07ed6eb0cb563539650fca05add7592812cf7af5b7ca0868756172cd3feb60 | MATLAB | 1,131 | 38 | function out = perlinNoise1D(Npts,weights)
% function out = perlinNoise1D(Npts,weights)
%
% I first heard about 'Perlin noise' from the MRF Nature paper
% (www.nature.com/articles/nature11971). I then made this Matlab code by
% translating the pseudo-code from http://freespace.virgin.net/hugo.elias/models/m_perlin.htm
... |
94995b71bc7fe8470a4c964d399fc9f435c99823a39a9588df26a8c5396c5614 | MATLAB | 1,132 | 49 | % A test script to extract R-peaks from sample records of the PTB-XL
% dataset
close all
clear
clc
data_path = '../sample-data/ptb-xl/*.mat'; % set data path
fs = 500; % set sampling frequency
data_list = dir(data_path);
for k = 1 : length(data_list)
fname = fullfile(data_list(k).folder, data_list(k).name);
... |
b5a1357e7e106c2d1a08fbc20b75bfc4d0b718afc5d03bb311699379da77c7d7 | MATLAB | 1,132 | 38 | % This function Retrieves inter events interval & event duration
% Input
% r: vector of ones that indicate the events
% Output
% IEI: inter events intervals
% ED: events duration
function [IEI,ED]=interval_duration_events(r)
% Setup
IEI=[];
ED=[];
if ~isempty(r(r>0))
dr=diff(r);
% +dr -> start Interv... |
60a2ae361a064c3328aa9eb6c9d39dc96998d4907a61e8ff39cd9e99786c2ec0 | MATLAB | 1,133 | 33 | %%devide_cells_by_aria
clear
clc
%%
%save only Intensity encoding + IR
[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(da... |
9b02b5318a48f478aa43bd53cdb9cceef33c31621adb01b345f1cfb4f56d41d2 | MATLAB | 1,133 | 92 | %% Initial conditions
P_I4_0 = 0;
A_I4_0 = 0.05;
P_I3_anterior_0 = 0;
A_I3_anterior_0 = 0.05;
T_I3_0 = 0.05;
A_I3_0 = 0.05;
T_I2_0 = 0.05;
A_I2_0 = 0.05;
T_hinge_0 = 0;
A_hinge_0 = 0.05;
x_h_0 = 0;
% x_g_0 = 0.1;
x_g_0 = 0.4;
%% inital neural states
% CBI2
V_CBI2_0 = -60; % mV
% CBI3
V_CBI3_0 = -60; % mV
% CBI4
... |
8d339dd0c4ae5965447c9558d99d949051e521fd1097129948c67513a163a0bb | MATLAB | 1,134 | 33 | function scrollplotdemo
% Created by Steven Lord, slord@mathworks.com
% Uploaded to MATLAB Central
% http://www.mathworks.com/matlabcentral
% 7 May 2002
%
% Permission is granted to adapt this code for your own use.
% However, if it is reposted this message must be intact.
% Generate and plot data
x=0:1e-2:2*pi;
y=sin(... |
28594a533147030de321f36ad63f86587cbb95d48bb54e27c79f3f4b60e6b72d | MATLAB | 1,137 | 54 | function k0 = nufft_offset(om, J, K)
%function k0 = nufft_offset(om, J, K)
%|
%| offset for NUFFT
%| in
%| om [M,1] omega (radians), typically in [-pi, pi) (not essential!)
%| J # of neighbors used for NUFFT interpolation
%| K FFT size
%|
%| out
%| k0 [M,1] prepared for mod(k0 + [1:J], K) (+ 1 for matlab)
%|
%| Copy... |
341d9d6e877e775a691b40334f5a1954372e90959a0e51342bf3866c907290da | MATLAB | 1,139 | 30 | function [mappedX, W, mu_X] = prewhiten_2(X)
%PREWHITEN Performs prewhitening of a dataset X
%
% [X, W, mu_X] = prewhiten(X)
%
% Performs prewhitening of the dataset X. Prewhitening concentrates the main
% variance in the data in a relatively small number of dimensions, and
% removes all first-order structure... |
dacf7583a37c7d93faa507bc7679e875035ac93b0f0d31973c71a3b01263d516 | MATLAB | 1,141 | 37 | classdef I2_Hill_Type_Muscle_Model
properties
I2_struct
end
methods
function obj = I2_Hill_Type_Muscle_Model()
obj.I2_struct.tau=2.45;
obj.I2_struct.beta=0.703;
obj.I2_struct.a0=0.165;
obj.I2_struct.g_scale=2.0;
... |
0003179a221e5a343f8fe7e131456a77f62cebdf66d817b6281919fca7bd0a21 | MATLAB | 1,143 | 31 | % Function to plto conout of probabilities
function plot_multiclass(x1Grid,x2Grid,PosteriorRegion,CMprobs,Xpca,ONEpca,...
TWOpca,Y,CM,ColorIndx,BestKernel,AccuracySVM,Yclass)
fprintf('>>Plotting regions: ... ')
MissClassifed=find(Yclass~=Y);
figure;
contourf(x1Grid,x2Grid,...
reshape(max(PosteriorRegion... |
8db4e53786906a3009924fad6569751d086e095db6e6a694228c11213e1b8ce2 | MATLAB | 1,143 | 49 | close all;
clear;
clc;
% parameters
path = 'E:\Sameni\Projects\Seizure\Dog_1\';
subject = 'Dog_1';
number = 4;
% mode = 'interictal';
mode = 'preictal';
ch = 1:16; % desired channels
time = [5 10]*60; % in seconds
nfft = 10000 - 1;
SpectralWinLen = 10; % in seconds
SpectralOverlapPercentage = 50; % [0 99]
% load sign... |
9e4a85fba5923ca128ef3697f165c1f5a4cbe3b8c487245690f2a75dc1921be3 | MATLAB | 1,143 | 34 | function [latency, peak, first_peak, f1] = lfp_latency(LFP, ploting)
%% LFP LATENCY
% calcualte peak/ first time fr crosses 1std form baseline
delay = 3116;
fr = 1000; %hz
[peak_val, peak] = max(abs(LFP(delay:end)));
t = (1:length(LFP))/1000 - delay/fr;
b_std = std(LFP(1:3000)); %baseline std
latency = find(abs(LFP(de... |
3ab76f043a63a2d53676d63138e07ca2aa0e5b359cce686b71c6c75b67f3ffea | MATLAB | 1,145 | 32 | %% Iterations of LDE: Use precomputed function to determine output of a cell type
% Input: L4EmeshX, L4ImeshY Domain of precomputed functions
% LDEFrfunc_Subf Functions of all input type for certain cell
% population
% L4EUse,L4IUse All input L4E L4I
% LDEUse Just fo... |
412512c2178aac5cf4ea91d38ed8b983868908380f0753ac33aa1a8361944ccc | MATLAB | 1,145 | 46 | function handle = XxWriteMRC_BigEndian(handle, image, header)
% disp('write position')
position=ftell(handle);
% dataclass=class(image);
switch header(4)
case 6
dataclass='uint16';
case 4
dataclass='complex';
case 2
dataclass='single';
end
if position==-1
fprintf('Invalid MR... |
951040ddf9689223a2472b32eff60f58560f83ae2cb735745d6c7a456b7a7d91 | MATLAB | 1,150 | 33 | function [ data_st, hilbert_params ] = sigproc_perform_hilbert_transform( data_st, hilbert_params )
% sigproc_perform_hilbert_transform performs hilbert transform
% Usage :
% [ data_st ] = sigproc_perform_hilbert_transform( data_st )
% [ data_st, hilbert_params ] = sigproc_perform_hilbert_transform( data_st, hilber... |
aa1dd5a9f26256ae53ef4104a0b69e79848d9ec4eff5908852fa71169cb3f3a1 | MATLAB | 1,151 | 1 | function filteredArray = gaussianFilter(array, sigma)
% Filter an vector with a gaussian of specified width
% Returned vector has the same length as the input vector
% Total area is preserved, edge effects are eliminated
bins = length(array);
if (bins == 0)
filteredArray = [];
return;
end
if (sigma <= 0)
filteredAr... |
d55eb577762f06f5ea454fb61ab5d3d265fe82f21e72a8111f542be9395463f0 | MATLAB | 1,151 | 40 | function Fig_similarity_10000(VI_sim,tot_VI,NC,savefig)
close all
f = figure;
plot(VI_sim(:,1),'o','LineWidth',2,...
'MarkerEdgeColor','k',...
'MarkerFaceColor','b',...
'MarkerSize',10); hold on
plot(VI_sim(:,2),'o','LineWidth',2,...
'MarkerEdgeColor','k',...
'M... |
f1ef8f5fd155782eec3acd6a6b1fab7757e2dc2760daa0f5316f77051170fe58 | MATLAB | 1,151 | 39 | function cellids = select_pv_cells(cellids)
%SELECT_PV_CELLS Select VP neurons from CellBase.
% SELECT_PV_CELLS(CELLIDS) selects parvalbumin(+) (PV-)cells that are from
% CELLIDS (default, all cell IDs in CellBase). Well-isolated units
% (ID > 20, L_ratio < 0.15) are returned.
%
% See also PV_PAVLOVIA... |
7a56d0b33eba4d6b8ea3c3118c449f96222555cefaa3b57c16e9e3dd592ffd88 | MATLAB | 1,152 | 33 | function [ nexFile ] = nexAddEvent( nexFile, timestamps, name )
% [nexFile] = nexAddEvent( nexFile, timestamps, name ) -- adds an event
% (series of timestamps) to nexFile data structure
%
% INPUT:
% nexFile - nex file data structure created in nexCreateFileData
% timestamps - vector of event tim... |
415a613d548b78dbceed2df0d4391c90b998a8112495d50d2008ae49005aa6f9 | MATLAB | 1,153 | 42 | function [nnode, ind, offset] = DOTHUB_nearestNode(point,nodes)
%This function outputs the node (1x3) present in the list nodes (Mx3) that is closest
%to the 3D location specified by point (1x3) and the offset in whatever
%dimensions are provided.
%Inputs (point,nodes) : the single point and the list of nodes
%Output... |
e60778d92b7d261b486afb2e07154675f575a4d00cd31c93e9c4f6cacdf867cd | MATLAB | 1,153 | 39 | %% Modify rate map
% CurrentFrE: The rough ratemap
% ConvMat: Convolution kernel
% CurrentBlowupModi: Blowup mat. Should be same dim of CurrentFrE. We get
% rid of where blowup is true
% CurrentsteadyModi: Steady mat. Should be same dim of CurrentFrE. We get
% rid of where steady is false.
% Output: FringMap
function ... |
9c92ecb4acad797cedd0f6d83b4b9d39f286e7e737911956311c2b6d008c7319 | MATLAB | 1,154 | 49 | function [numberOfNeurons] = editor_precount (neuron, pathname, filename)
if isempty(lasterror) == 0 %c'è errore
[filename, pathname] = uigetfile({'*.jpg;*.tif;*.bmp;*.png;*.gif','All Image Files'}, 'Pick an image');
str = strcat(pathname, filename); %complete directory
neuron = ... |
4dc6b2a73bd30f56b4b06ba620e85ab7dfe806e7dccb514b15421b7d472fe2a2 | MATLAB | 1,159 | 38 | function expanded_region = expand_region_for_diam(region)
%EXPAND_REGION_FOR_DIAM The set of 2^d vertices of a region
%
% Expand a region from the 2 vertex definition to the set of 2^dim vertices
% of the pseudo-region of a region, so that the Euclidean diameter of a region
% is approximated by the diameter of this se... |
5bc8c0d7cd77c482740fd2e9cd907cd456b5c7d6afa1c8a26d1de3fc40137d97 | MATLAB | 1,160 | 40 | function [windows, timeRanges] = extractWindows(obj, samplesIn, spikeTimes, spikeSites, fRaw)
%EXTRACTWINDOWS Isolate windows around spiking events from matrix of samples
% returns nSamples x nSpikes x nSites
if nargin < 4
spikeSites = [];
end
if nargin < 5
fRaw = 0;
end
i... |
9ffa657048fcff3279cd8c40ebe3883d3d1c44cb23fed1656e258ab96c6f5335 | MATLAB | 1,161 | 46 | function lineplot_with_shaded_errorbar(x, y, 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 = [1:10]';
% y = cell(1,2);
% for i = 1:20
% y{1} = [y{1}... |
e70115121f8d176e4f8e4c35732dc20821bfbe4db8e7b32c15686fc990235984 | MATLAB | 1,161 | 29 | function [trainedClassifier, validationAccuracy] = trainClassifierview(trainingData, responseData)
% Create an SVM template for classification
template = templateSVM(...
'KernelFunction', 'linear', ...
'PolynomialOrder', [], ...
'KernelScale', 'auto', ...
'BoxConstraint', 1, ...
... |
2f96f2fa5261bfa0d16588ead7176c2c281e5e5ba439591e88c061fc0488140d | MATLAB | 1,162 | 30 | function [fBeads]=mnl_RemoveBeadsOnEdge(Beads,dim)
%NB Remember that I've already switched the X and Y axes so dim(2) is the
%image X and dim(1) is the image Y
szB=size(Beads,2);
n=1;
r=1;
for i=1:szB
Xpos=Beads(i).BeadCentre(1);
Ypos=Beads(i).BeadCentre(2);
Zpos=Beads(i).BeadCentre(3);
Xsize=Beads(i).B... |
3b35d7116c1ecf2b658a9e532dcd0fc400bf88eeffc477acbc332d2a8c74368c | MATLAB | 1,163 | 48 | function [alpha, beta, ok] = nufft_alpha(N, J, K, alpha, beta)
%function [alpha, beta, ok] = nufft_alpha(N, J, K, alpha, beta)
%|
%| Determine alpha and beta, as associated with the scaling factors
%| for min-max interpolation, from arguments.
%|
%| in
%| alpha [L,1] Fourier series coefficients of scaling factors
%| ... |
5a8761a7c02ec3525ba6b2140fe961283699943423b6cc8421ed838eb289dfd2 | MATLAB | 1,163 | 46 | function data = load_data(session, channel, unit)
% Load data
%
% Parameters
% ----------
% - session: scalar
% Session number with format: yymmdd
% - channel: scalar
% Channel number
% - unit: scalar
% Unit number
%
% Returns
% -------
% - STIM: boolean arr... |
e6da14f3e3b62b36dbefe4031b885cb0a744ea1d2173db4f213e2ed7b7f93586 | MATLAB | 1,163 | 48 | function fr0 = get_fr0(session, channel, unit, fold)
% Get firing rate of null model
%
% Parameters
% ----------
%
% - fold: integer scalar
% Fold number
%
% Returns
% -------
% - fr0: scalar
% null firing rate
r = get_resp(session, channel, unit, fold);
tri... |
dd0fea3fff41c5b3bfe35ec856fd97ab30259a37863cecf8209e7b150f424756 | MATLAB | 1,164 | 19 | function [NoiseIm] = MakeCheckNoiseFun(ImWidth,ConInc,CheckSize);
% [NoiseIm] = MakeCheckNoiseFun(ImWidth,ConInc,CheckSize);
% function to draw a patch of random noise 'checks' with a given balance between black and white in the image
% needs inputs of ImWidth (image width in pixels), ConInc (the contrast increment ap... |
e90b9b2c5c19d120daa1fd24fcfe51adaf9069f9c3deb417ab78c25465c68781 | MATLAB | 1,164 | 40 | function data = calcLickLatency(data)
%calcLickLatency - Calculate lick latency
%
% Usage:
% data = calcLickLatency(data)
%
% Description: This function find the first lick onset after the reward
% delivery and calculates the latency / delivery from the delivery of a
% reward to consumption
%
... |
da3c1ac311089f1ba1a5a42dd575346bab966df9dd66806fd72c1470ef566712 | MATLAB | 1,166 | 48 | function mmil_write_value(fid,value)
%function mmil_write_value(fid,value)
%
% Purpose: writes a value to open file specified by fid
% handles multiple data types, including vectors and cell arrays
%
% Created: 02/25/11 by Don Hagler
% Prev Mod: 10/07/13 by Don Hagler
% Last Mod: 07/02/19 by Feng Xue
%
if isfloat(v... |
14f13e5caaf073eb80c994269f00cf3152c1c1e47a9e708707fcac7e909c3726 | MATLAB | 1,167 | 30 | %Author: Tatjana Schmitt, 2019-2023
function edges_turning_points_maps = edges_turning_points(BF, radial_vectors_mean_BF_smoothed, borders)
% creates images for edges and turning points with 1s as borders
edges_turning_points_maps = cell(1, size(borders.turning_points,2)+1);
for j = 1:size(edges_turning_points_ma... |
62827fa95dd22ed76f053651000807f988e30a2ef68715ee5a1fa7dd38cc3cac | MATLAB | 1,167 | 50 | %% get noise Corrs
function [noiseCorr, signalCorr, totalCorr] = calc_noiseCorr(spikes1, spikes2, nShuffle)
spikes1=spikes1(:);
spikes2=spikes2(:);
if numel(spikes1)~=numel(spikes2)
error('spikes1 and spikes2 must be vectors of spike counts with equal length')
end
if nargin<3
nShuffle = numel(spikes1);
end
... |
3047c338b0c392132403a3158a617529d81c775329a0eacca66595da7d12bf84 | MATLAB | 1,169 | 51 | function fo = adjust_phase_to_first(fi)
fo = fi;
zero_filling=size(fi(1).fid,1);
NS = size(fi(1).fid,2);
pas_temps=1/fi(1).spectrum.SW_h;
ppm_center = fi(1).spectrum.ppm_center;
SW_p = fi(1).spectrum.SW_p;
f_METAB_ref = 0.9 ;
i_METAB_ref=(-(f_METAB_ref-ppm_center)*(zero_filling-1)/SW_p+(zero_filling-1)/2)+1;
fi... |
714190bc88b99282404744bfa96569f3e6e9a9f7d2f105fe875060d886869c2e | MATLAB | 1,169 | 30 | function [a, b, cPrime, totalEffect, pValueA, pValueB, pValueCPrime, pValueTotal] = mediation_analysis(X, M, Y)
% Performs a simple mediation analysis with significance testing
% X is the independent variable
% M is the mediator variable
% Y is the dependent variable
% Ensure input vectors ar... |
7cca61c26d7de5ad105e2204adf1868115c1b0229cb7d2895bdc918fe374cb40 | MATLAB | 1,169 | 36 | function [] = visualizeContrastMadinoHamada2(val1, val2, val3, texts, color)
% preparation for the
count = 1;
clear COPE
nROI = length(val1);
% blue stim control
COPE.first(count:nROI, 1) = val1;
COPE.second(count:nROI, 1) = val2;
COPE.labels(count:nROI, 1) = {'peaks of ΔCBV(Grandjean2019)'};
COPE.color(count:nROI... |
a98c35a19e67053f100e7a1c295066ebe113c044fb1bc0ba41fc6ed4867594ed | MATLAB | 1,170 | 38 | % Function that creates a Color Map for the ExperimentalConditons
% Input
% Starts a GUI to set the colors
% Ouput
% CM: Colormap
% ColorIndx: Struture with colors
function [CM,IndxColor]=Color_Selector(NamesCond)
% Colors: #################################################################
Nconditions=numel(Names... |
ef2012737809b4fb3ba554280da7846af4c58c740a31c17cf7fc6367b9e07235 | MATLAB | 1,170 | 39 | % create Gaussian model
% ------------------------------------------
% This file is part of the adaptative_threshold SPM plug-in
% Copyright (C) Cyril Pernet and Chris Gorgolewski 2012
classdef Gaussian < Distribution
properties
mu = 0
sigma = 1
sigma_sqr = 1
end
properties(Constant... |
f6d22c67d582411d74d28a62f4b4c9d5afbd48d22452cb53f0220bfb5c64891e | MATLAB | 1,170 | 39 | function [numchannels,numtimeframes,samplingrate,thedata]=opensef(openfilename)
% opensef: opens a Cartool simple EEG data file (.sef)
%
% inputs: full path and name of the file to open
%
% outputs: number of channels, number of timeframes and sampling rate as
% 1-D numeric arrays; data as a 2-D numeric array where dim... |
da90d996ac284a897d524ffded10075f61de7acb97ec5fa41cd65c7f5ee130ae | MATLAB | 1,173 | 47 | function PlotMSNFSI20200413
clear all;close all;
path=['G:\CheetahWRLV20200411'];
cd(path)
load widthPtoT
% X=[AllCellwidth.' AllCellPtoT.'];
AllCellwidth = X(:,1);
AllCellPtoT =X(:,2);
thresholdwidth=5;
thresholdPtoT=10;
[idxMSN,S1]=find(AllCellwidth>thresholdwidth & AllCellPtoT>thresholdPtoT);
[... |
e9a7070bb52aadda026a34e37860771fbfcb34e3a5c0e48f6d0260200b9cc3f6 | MATLAB | 1,173 | 34 | function c_caps = cap_colats(dim,N,c_polar,n_regions)
%CAP_COLATS Colatitudes of spherical caps enclosing cumulative sum of regions
%
% Given dim, N, c_polar and n_regions, determine c_caps,
% an increasing list of colatitudes of spherical caps which enclose the same area
% as that given by the cumulative sum of region... |
9423b84e539794fbae5ab2a164ee15cbdad648b35292b6d026e5e07b588c490d | MATLAB | 1,174 | 59 | function [x, y] = clusts4plot(p, thresh, y)
% Sets up permutation p-values to plot clusters with patch
% Inputs: p = pvalue vector
% ylim = two element vector of ylimits
%
% Written Tylor J Harlow 9/12/2023 - tylor.harlow@uconn.edu
% Orient
[r, c] = size(p);
if r > c
p = p';
end
% Get indic... |
411c0359d12bca5b0864eaac52bb63fdf392cc7808c430f65be8001bffc95322 | MATLAB | 1,176 | 39 | function [M]=mnl_PermsNoColumnBias(v,n)
% Function that works out the different combinations of selecting n values
% from vector v, regardless of order
%Inputs
% v - vector e.g. [1 2 3 4 5 6 7]
% n - number to select
%
%Outputs
% M - Matrix with all the possibilities
ap=perms(v); %All permeabilities
uap=unique(ap(:,1:... |
632a41020f06ddd0f62c1192c88210ca2c7956b08405691b4e3ec1c7b7c633e2 | MATLAB | 1,176 | 37 | clear all
close all
load Scurve_data_IV.mat
%% S-curve splitted in regions, I(V)
f = figure(1);
lines_width = 2;
plot(Scurve_sim.V(1:1000), Scurve_sim.I(1:1000),'Color','#F5266D','LineWidth',lines_width);
hold on
plot(Scurve_sim.V(1000:end), Scurve_sim.I(1000:end),'Color','#3385F5','LineWidth',lines_width);... |
9243bdccb123e1a46dd034c1696e026107047fb62bea74baa28b05f26442deec | MATLAB | 1,177 | 33 | % Copyright 2024 Eelke Spaak, Donders Institute.
% See https://github.com/Spaak/rift-phase-and-visibility for readme/license.
% Belongs with:
% Spaak, E., Bouwkamp, F. G., & de Lange, F. P. (2024). Perceptual foundation and extension
% to phase tagging for rapid invisible frequency tagging (RIFT). Imaging Neuroscience,... |
e2113bf688bcd9be090992a2d0508423799e49ce6726d73b59451d25c0aebbe5 | MATLAB | 1,180 | 54 | function sn = nufft_scale_kb(Nd, Jd, Kd, kb_alf, kb_m)
%function sn = nufft_scale_kb(Nd, Jd, Kd, kb_alf, kb_m)
%|
%| Compute KB scaling factors for NUFFT
%|
%| in
%| N,J,K [d]
%| kb_alf [d]
%| kb_m [d]
%|
%| out
%| sn [[Nd]] scaling factors
%|
%| Copyright 2004-7-8, Jeff Fessler, University of Michigan
if nargin == ... |
98e9fd240d25e3c071f4851b55e32c56061254629a0e7e12e89c209e5f466f2a | MATLAB | 1,181 | 39 |
%Please cited this Toolbox as:
%Dimitriadis SI, Laskaris NA, Tsirka V, Vourkas V, Micheloyannis S, Fotopoulos S.
%Tracking brain dynamics via time-dependent network analysis.
%Journal of Neuroscience Methods Volume 193, Issue 1, 30 October 2010,
%Pages 145-155
%threhold schemes for graphs (especially for fun... |
af3ff3d5300d6edfda600524fd8c5afd0d013f6d75be5f2d4286de8307c4422f | MATLAB | 1,181 | 46 | function ind = ChannelIndex8(x,ff,fs,th)
% Channel selection based on peak-detection
%
% Reza Sameni
% December 2008
L1 = size(x,1);
% % % L2 = size(x,2);
% % % rng = floor(1/(2*(ff/fs)));
% prefiltering
% load FiltCoefs Num
% x = filter(Num,1,x')';
% x = x.^2; % + and - peaks are both acceptable
... |
c298d762a619a3b571bb4b693008b553cfaefce6426521a412f6f7a4efae615e | MATLAB | 1,182 | 32 | function [spikes1] = int_spikes_pol(spikes,nch,thr,par);
%Interpolates with cubic splines to improve alignment.
w_pre = par.w_pre;
w_post = par.w_post;
detect = par.detection;
int_factor = par.int_factor;
nspk = size(spikes,1);
s = 1:size(spikes,2)/nch; % length of the single spike
ints = 1/int_factor:1/int_factor:si... |
dfc77dea5d8f0be288ad385a99568fc5f8eebe589ab141a9cb503c55503a64b4 | MATLAB | 1,182 | 32 | function V = gompertz_exp_alpha0_beta(param, DT_invitro, temps, Vc, V0)
% param = [alpha_0, beta] parameters of Gompertz growth, according to
% dV/dt = (alpha_0-beta*log(V/Vc))*V
% hence alpha_ = relative growth rate at V = 1 cell (volume Vc)
% DTinvitro = doubling time in vitro in hours
DT_invitro = DT_invitr... |
ef7ebd099dd4a0e89da5f9da644dc975f91db57f2cb7a6efdd605b8cf12a5343 | MATLAB | 1,183 | 30 | function autoScaleFigTime(hFigTime, hClust, selected, iSite, channel_idx)
%AUTOSCALEFIGTIME Automatically scale features in FigTime
hCfg = hClust.hCfg;
autoscalePct = hCfg.getOr('autoscalePct', 99.5)/100;
% get display features for figTime on iSite, compute the
% autoscalePct'th quantile, set ylimi... |
1bdb2935bdb58217aaf29bf0a963b1198ae9be23982a20be093f839fbeb8ff5b | MATLAB | 1,184 | 29 | function [] = writeNex5VarHeader(fid, varHeader)
% [] = writeNex5VarHeader(fid, varHeader) -- write nex5VarHeader structure
% to the specified .nex5 file.
%
% INPUT:
% fid - file id
%
% varHeader - nex5VarHeader structure
fwrite(fid, varHeader.Type, 'int32');
fwrite(fid, varHeader.Version, '... |
6bb7930b1381379319973b5226aa53aa37866bbfb9470389d5b2d91e8dfbad7b | MATLAB | 1,184 | 43 | function state = mmil_check_nargs(nargs, expected_nargs, errorMsg)
%function mmil_check_nargs(nargs, expected_nargs, errorMsg)
%
% Purpose: to have a common function to check and handle
% this simple parameter passing check.
%
% Currently, the function compares the # of args and,
% if they are different, throws... |
afb5388e1e9699954cbcd9669645f47affd6ffd085e63bb3a054b474338bb03e | MATLAB | 1,185 | 34 | function thedata=computedataagainstref(thedata,ref)
% computedataagainstref: changes the reference of a data set
%
% inputs: data as a 2-D numeric array where dimension 1 contains the
% timeframes, dimension 2 contains the channels; ref as either a number
% (1-D numeric array) or the 'avgref' string for average referen... |
62df50ab519fc5a4d825fd731191b7c2b0407509dc45d77003f70b27cc3206d4 | MATLAB | 1,186 | 65 | clear
close all
clc
% load ECG1
% s = data;
load ECG2
s = data(:, 1:5*fs);%end);
s = LPFilter(s - LPFilter(s, 1.0/fs), 100.0/fs);
DiffOrder = 2; % smoothness constraint order greater than 1
snr = 5; % dB
nvar = var(s, [], 2)/10^(snr/10);
x = s + sqrt(nvar(:, ones(1, size(s, 2)))).*randn(size(s));
h = diff([zeros(1... |
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