sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
03153aa944a0ce397776831ae64726670830ae1a876511f63011d4358b264bb6 | MATLAB | 2,179 | 62 | function x = ecg_gen_from_phase(params, phase)
% ecg_gen_from_phase - Synthetic ECG generator using a Gaussian mixture model.
%
% Syntax:
% x = ecg_gen_from_phase(params, phase)
%
% Inputs:
% params: A vector of length 3*L, where L is the number of Gaussian kernels structured as follows:
% - a... |
b5b5bb2c71ddcfc51238c336aa2876dc54cd3a6a70cab838375a1621d9cc966b | MATLAB | 2,179 | 83 | %% compare baseline form all_ints_data
clc
clear
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\eopn3')
all_ints_data = importdata("all_ints_data_eopn3.mat");
all_ints_data_control = importdata("all_ints_data_control.mat");
%%
baseline = baseline_form_all_ints_data(all_ints_data);
low_baselin... |
e6a654ccaa3aeca2f243897f570e0fcbac9001d7d745481dbd7080256794ec8d | MATLAB | 2,179 | 73 | function graph_est = fdr_est(kappa_post, fdr)
%%
%Input
%%kappa_post: a RxRxSxnsims array of the shrinkage coeficients
%%1/(1+lambda_ijs*tau_s)
%%fdr: real between 0 and 1, desired false discovery rate
%Output
%%graph_est: a RxRxS array of indicator variables for selection
kappa_thresh = squeeze(median(median(median(... |
36472a9473f75fff36d6108016497ae1526bf4cbfde845b66574de6265d87374 | MATLAB | 2,180 | 84 | %%
%% i/o args
% output args:
% PSTH
% z-scored PSTH
% ?reliability
% plotHandle
% input args:
% stimulus trial event times (on + off times)
% blank trial event times
% spike times
spikeTimes = unitex.spiketimes.*1000;
statTrials = tsd(cellfun(@(x) prop(x<3)>=0.8 & mean(x)<0.5, {tsd.WheelSpeed}));
statTrials_blan... |
aa600d9027918ab28b329fb20930a83182dde2b69ff9cd4ae58d541ecc7372a0 | MATLAB | 2,180 | 79 | function peak_VE_evoked(sub,ses,project_dir)
restoredefaultpath
% close all
clc
% project_dir = 'R:\DRS-KidsOPM\Paediatric_OPM_Notts_AdultData\';
%
% sub = '001';
% ses = '001';
run = 'run-001';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
datadir = [project_dir,'Data',file... |
a83a9d6cb1815f2984447e1b403442e656ba2589083e5906f16d451b24988fbf | MATLAB | 2,181 | 69 | function result = verLessThan(toolboxstr, verstr)
%verLessThan Compare version of toolbox to specified version string.
% verLessThan(TOOLBOX_DIR, VERSION) returns true if the version of
% the toolbox specified by the string TOOLBOX_DIR is older than the
% version specified by the string VERSION, and false otherwi... |
f837f9aa000593997bd4b4b665f8d5c04fc1858db9f292d9e41536740bc4cff6 | MATLAB | 2,181 | 48 | %% Calculate response stats
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\DREEDDS_VS_dreadds before\new_IR_calculations\IE cells')
% T2 = T(find(contains(T.tags, ["dreadds before", "dreadds after"])),:);
clear
clc
T = importdata('IE_CELLS_table.mat');
T2 = T(find(contains(T.tags, ["dreadds before", "d... |
1381efc0699a7eec76e84bca01c1c7bda19e45c16ac72fdd1ff63b67f3da5776 | MATLAB | 2,182 | 79 | function zn = nufft_interp_zn(alist, N, J, K, func, Nmid)
%function zn = nufft_interp_zn(alist, N, J, K, func, Nmid)
%|
%| Compute the "zn" terms for a conventional "shift-invariant" interpolator
%| as described in T-SP paper. Needed for error analysis and for user-
%| defined kernels since I don't provide a means to... |
41c557fe291b56f09fd49140cceaaaf0159f6db2c2d827c373d706630f3a753f | MATLAB | 2,182 | 41 | function Locs1 = Trace_Peak_Analysis(Workspace,Step_Params,s,v,Scores,ImSize)
% This function find peaks in the convolution function.
% It uses the skeleton constraint to filter out peaks that are too far, and to sort those that satisfy the condition.
L = Step_Params.Scan_Length;
Locs1 = [];
Trace_Skel_Max_D... |
92b71116bcb3a6b1053e037d29cb8afbbbdfaa01ad60f4319f9e6500b1f14686 | MATLAB | 2,182 | 63 | function PCA20200117
path=['C:\Users\C238\Desktop\CheetahWRLV20180729Part1'];
cd(path)
LS1=ls;
% MaxA1Rt DiffMaxMinR MaxZR A1RtStepFreq
% MaxA2Lt DiffMaxMinL MaxZL A2LtStepFreq
%
TouchIndexMatrix=[];
for i=1:length(LS1(:,1))
trimFolder1=strtrim(LS1(i,:));
if ~strcmp(trimFolder1,'.') &... |
c3a8b82c9eabe34106a4878e48b294e0ac9e7c6d2ac9bf1dde11cb2135cb4083 | MATLAB | 2,182 | 45 | function [prVecs1, prVecs2] = getPVClusters(hClust, sites, iCluster, jCluster)
%GETPVCLUSTERS Compute principal vectors on sites from one or two clusters
% input: sites, a vector of site indices
% input: iCluster, primary cluster ID of interest
% input: jCluster, optional, secondary cluster ID ... |
f255b493757f517b0a2ca21f015e7133a3e77053cbf01eea81cc8b86c9b21174 | MATLAB | 2,189 | 69 | function [valindSQI, indSQI] = SQI1(x, peaks)
%
% [valindSQI, indSQI] = SQI1(x, peaks)
% Channel selection based on Pseudo-periodicity
%
% Fahimeh Jamshidian Tehrani,
% jamshidian.t@cse.shirazu.ac.ir,
% fahimeh.jt@gmail.com
% February 2020
%
% input:
% x: input JADE component of fetal ECG record
% peaks: R-peak imp... |
09998f1e3d34c50939308b094fc7b4d3082511c39c3731faf88d24654233f973 | MATLAB | 2,191 | 83 | % Function that Detects Calcium Transients
% from onset spikes and denoised fluorescence signal
% Input
% R: Raster Matrix: Cells x Frames
% XEST: Denoised Fluo Signals
% Output
% NoT Number of Transient per Cell
% ITI Inter Transient Interval units:[samples]
% LT Latency Transient ... |
e5fe343495ecf49da29db8c4ed320e90a33dee31724497be9bd8c7ea1c3270f5 | MATLAB | 2,191 | 58 | function [ProcessedEventWindowData_SAVE,varnamesDATA_SAVE] = relativeBLperZscoreV2(ProcessedEventWindowData,EventWindowDts,varnames,varnamesDATA,setupParam)
ST1 = {'Raw'; 'Recentered'; 'DecayAdj';};
inUseST = fieldnames(ProcessedEventWindowData);
STidx = zeros(1,numel(ST1));
for i = 1:numel(ST1)
if ismembe... |
188e6317860c80439a332c52fefe662265f56e3b165c03f68780f654fc1752c8 | MATLAB | 2,193 | 71 | function gui_sc (action)
%
% This file is used by FASTICAG
% This file holds the callbacks for save-dialog
% 5.6.1999
% Hugo Gävert
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Global variables
% Handle to the window
global hf_FastICA_Save;
% Handles to some of ... |
803fe87dfb687cad6c1eb526434f413a90c937a48b5d80a4e4a5237d74cba49a | MATLAB | 2,196 | 108 | % kalman filter of rossel system signals sample entropy
clear all
close all
% Data Sampling Rate: 100 Hz
fs = 100;
% Generate rossel signals
a=0.38;
b=0.2;
c=5.7;
x(1)=1;
y(1)=0;
z(1)=0;
h=0.01;
for i=1:50000
K1=-(y(i)+z(i));
L1=x(i)+a*y(i);
M1=b+x(i)*z(i)-c*z(i);
K2=-((y(i)+h/2... |
a3ebbbc4e6532cd82dc186c94c1ece0962c0c101535b5684f255e8009305e924 | MATLAB | 2,197 | 71 | % do basic decoding for 4 different settings:
% neural vs. speed
% a/e vs. iti
clear
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'allData.mat');
load(fpath,'evs','tis','bvs','traces')
[cols,alpha] = chooseColors;
%%
fpath = fullfile(p.data_dir,'av_vs_iti');
saveFigs = 1;
saveData = 1;
aa_sessions = 3:9;
n_... |
4295fb60cc091141de457c04ca2b32feeb98e00ef71f1c29b1c93450d053112c | MATLAB | 2,200 | 58 | function [ nexFile ] = nexAddMarker( nexFile, timestamps, fieldName, fieldValues, name )
% [nexFile] = nexAddMarker( nexFile, timestamps, name ) -- adds a marker event
% (series of timestamps with string tags) to nexFile data structure.
% In general, each marker timestamp can have several ta... |
b90c5d62cfbd2206b923ec9261647866663215bc38fd7f811416512ec514efac | MATLAB | 2,200 | 116 | %%%%% Neuron Parameters %%%%%%
C=50;
k_input=1.;
v_rest=-80.;
v_t=-20.;
c=-55.;
v_peak=40.;
a=0.01;
b=-20.;
d=150.;
noise=0;
R=100;
%%%%% Synapse Parameter %%%%%%
tau_s=20;
Apostpre=1;
%%%%%% Simulation Parameters %%%%%
T=300;
dt=0.01;
t_vect=0:dt:T;
n_times=length(t_vect);
ve=zeros(1,n_times);
we=zeros(1,n_times);
... |
21c2bf3c9b604d2bd63784607f8bd5d58cfaee02df5cf417f24ae145385e8cfe | MATLAB | 2,201 | 48 | function import_exp_data(csvfile)
%% Import experiment metadata from experiments.csv
% Read csv file and write experiment details to data structure.
%
% This function depends on a file experiments.csv which contains metadata
% from all relevant experiments, retrieved from connectivity.brain-map.org.
% FormatSp... |
ec45f315d5e147886259cf3fec4fc23b5a99ab4c19eabc7bde056381c54a1e36 | MATLAB | 2,201 | 78 | %Copyright (C) 2019, Adria Tauste Campo
%Contact details: adria.tauste@gmail.com
%Copyright (C) 2079, Jiantao Jiao
% DESCRIPTION: Function CTWAlgorithm outputs the universal sequential probability
% assignments given by CTW method.
function [Px_record ]= ctwalgorithm_M(x,Nx,D,Temps)
%function Px_record = ctwalgorithm... |
6c8f692575617fb5a0824503c852bac1645ac8d644299b4a99b9dd07b010a05e | MATLAB | 2,202 | 87 | function CellCounter20190710
cd('C:\Users\C238\Desktop\CheetahWRLV20180729\119\2017-6-7_20-8-33 11901-51\11931_170607_98___Classify');
LS=ls;
Rtcount1=0;
Ltcount1=0;
RLtcount1=0;
Doncount1=0;
Woncount1=0;
Woffcount1=0;
Rtcount2=0;
Ltcount2=0;
RLtcount2=0;
Doncount2=0;
Woncount2=0;
Woffcount2=0;
R... |
635b7c8576253b9173d19fa537ba426f9cb7aec54990c1ebb75da38625e9ff95 | MATLAB | 2,204 | 73 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Expand an image as per the Gaussian Pyramid.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function IResult = GPExpand(I,newdim)
Wt = [0.0500 0.2500 0.4000 0.2500 0.0500];
dim = size(I);
% newdim = zeros(1,3);
% newdim(1) = dim(1); newdim(2) = dim(2); newdim(3) =... |
5c245a66f803777530d7993856c9dde9e2f5eccadf4d08aa82e49d397dbc496c | MATLAB | 2,205 | 84 | function [results]...
=Call_Function(TC, X, S, burnin, nmc, seed)
%% Inputs:
% Y_file :
% Set seed
rng(seed)
%% Call Function Implementation
% Add paths to data
%addpath 'MCMC_Folder'
data.TC = TC;
data.X = X;
% Get the dimensions
p = size(data.TC,2);
T = size(data.TC,1);
base_prob = .5;
alpha_0 = log(base... |
b5af811e9e3b0bc368f4f058b55654d37193059b533e514a6b58c0bbd86bb36c | MATLAB | 2,205 | 70 | % test the Spikes and Bumps phenomenon in ICA using real fetal ECG data
% Reza Sameni, Copyright 2006
% Modified June 2018
clear;
close all;
load LTE07102005_40s.txt -mat;
data = LOUETTE_40s';clear LOUETTE_40s
fs = 1000;
% Keep the follwoing lines if you want to repeat the same results again
randn('seed', 1);
rand(... |
15d6d676546025f3af10749aa88e210456fd6e659e1f1a654ffc7707f00f4d46 | MATLAB | 2,206 | 79 | clear
clc
[file, path] = uigetfile('*.mat','MultiSelect','off');%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
load(datafile)
close all
w = 2; %window to use (on, sustaneid, off)
%%
n = fieldnames(clusters.clu... |
e04ab0dfe9c2d08363be602c3e6e2d0492f11a859374aadf0ced793cde480d79 | MATLAB | 2,210 | 83 | %%
clear
dataset_list = ["leuven", "oxford"];
T_subjectCharacteristics = table;
for dataset_counter = 1 : length(dataset_list)
dataset = dataset_list(dataset_counter);
input_folder = '../data/';
input_file = strcat('data_', dataset, '.csv');
output_folder = '../results/';
if ~exist(output_f... |
236c86666720401cc556181b40691cf7b3b2050bbf41ad5b762b642146cf0e5c | MATLAB | 2,212 | 80 | % Plots two time-dependent data sets on two axes. Typically made for
% primary tumor and metastases
function [AX, hPT, hMet] = plot_data_global_conv_unit(...
index_postresection,...
time_PT,...
PT,...
time_met,...
met,...
axisS,...
conv_unit_PT,...
conv_unit_met,...
styleS)
if nargin... |
8980784788cdaf0e3d0e9e896b0a4e6da93133a5ac31dcb23fc178e41f473d2c | MATLAB | 2,212 | 102 | function [regout,CI,pboot,p] = rst_pbCIreg(a,b,nboot,alpha,mu)
% function [regout,CI,pboot,p] = pbCIreg(a,b,nboot,alpha,mu)
%
% Compute a percentile bootstrap confidence interval
% of the linear regression outputs using OLS
%
% INPUTS:
% a (vector of predictor)
% b (vector of response)
% ... |
68425e0fd54749483be31f4a56c9547c89bbdb3586d46a28da382275bfa63277 | MATLAB | 2,213 | 38 | function paths = Choose_Paths(Step_Parameters,Parameters1)
% Curve Fitting:
fitobject = fit(Step_Parameters.Step_Routes(:,3),Step_Parameters.Step_Routes(:,2),'smoothingspline','SmoothingParam',Parameters1.Auto_Tracing_Parameters.Step_Smoothing_Parameter);
% fitobject = fit(Step_Parameters.Step_Routes(:,3)-Step_Par... |
ad44f4d126590f563e5926cb0692df00e8619b360a747cbb632953e883af684b | MATLAB | 2,214 | 57 | function [unmixData]=sf_unmixing_20xG_3HyD_220823ref(fn)
% load xycz image
[Data,Scale,dim,metadata]=mnl_Load4Dimage;
for i=1:size(Data, 3)
Data_ch(i).Data=Data(:,:,i,:);
Data_ch(i).Data=squeeze(Data_ch(i).Data);
Data_ch(i).Data=double(Data_ch(i).Data);
end
%% Reference matrises for 20xG 3HyD prot... |
569c9d0239ea84a26b5314f90243b87fe76c89c6ae6017a4c2a79083a69cef9c | MATLAB | 2,218 | 69 | function test_multi_lead_ecg_viewers
% A script for testing different ECG viewer functions
%
% Usage:
% testMultiLeadECGPlotter
%
% Revision History:
% 2023: First release
%
% Reza Sameni, 2023
% The Open-Source Electrophysiological Toolbox
% https://github.com/alphanumericslab/OSET
close all
clear
clc
% Define th... |
7a37d23dd008fcfb0765f8a7961addf3f119a4ac00453c109341f06ea97d5ef5 | MATLAB | 2,218 | 121 | function [ellisx,ellisy,rmax,xo,yo]=clust(y,n1,n2,prob,IXi,IYi,in,de);
% y=yy, componenti principali
% n1=t1, estemità inf asse x
% n2=t2,
m=mean(y);
xo=m(1);yo=m(2);
ss=cov(y);
s=inv(ss);
count=1;ellisx=[];ellisy=[];
%calcolo delle distanze fra i punti rispetto al centroide dell' ellisse
j=sqrt(-1);
AA=y(:... |
fb6038f75e5d6163362e1e310b939c104d22ff6ebe4ecb8c51ec3be934ad03ea | MATLAB | 2,218 | 65 | function PV_lightpsth_colored(cellids, impdir, resdir)
% PV_LIGHTPSTH_COLORED Population PSTH of light-aligned PSTH.
% PV_LIGHTPSTH_COLORED(CELLIDS, IMPDIR, RESDIR) calculates adaptive PSTH
% (see DAPSTH) aligned to light pulse onset using all pulses of the most
% efficient stimulation frequency. PSTHs are... |
5d21d7dc1e3557fe79d0e75d2a2576750ce13e4b0e248d77fce2de45dce34179 | MATLAB | 2,222 | 65 | %VOT method
%Shinjini Kundu (c) 2015
function [ f1t,f2t,f3t,I0_recon,Ierror,flag ] = compVOTGradients( f1,f2,f3,I0,I1,lambda )
%Computes the gradients required in Kundu et al's variation optimization approach
%inputs: f1,f2,f3 current deformation fields
% I0,I1 original images
% ... |
820a5767b22b919663468d275d7f85a650eed8dc6e59cf5ac4323e06b472f17f | MATLAB | 2,222 | 65 | classdef PoissonIndependentDecoder
% Object to perform basic decoding
properties
tuningAxes; % cell array of tuning axes
tuningDims;
tuning; % struct array (cells) with tuning field
allTuning
bias; % sum of all tuning for all cells
end
meth... |
ceec97b917939690e1e63a634464bea9368135786077e6e52cb45c71b7a7a975 | MATLAB | 2,222 | 68 | function [peaks, peak_indexes] = peak_det_amp_threshold(x, ff, th, varargin)
% peak_det_amp_threshold - R-peak detector based on max search and level thresholding
%
% Syntax: [peaks, peak_indexes] = peak_det_amp_threshold(x, ff, th, varargin)
%
% Inputs:
% x: Vector of input data.
% ff: Approximate ECG beat-rate in... |
ed47b5d74794443daedd6bd338d1d100434a3bd15b3b3856e8c9ac9cec06222c | MATLAB | 2,222 | 85 | function [bin thres mdegree]=threslold_mean_degree(graph,kk)
% THRESHOLD_MEAN_DEGREE Mean Degree thresholding
%
% [bin threshold degree]=threslold_mean_degree(graph,kk)
%
% This function thresholds the connectivity matrix by absolute weight
% magnitude. All weights below the given threshold, and all w... |
72098495432179be2126b782080286144b894425c2df5ff024cc92b2291b9214 | MATLAB | 2,225 | 42 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [pops_PT, pops_met] = simulate_pop_PT_met(...
temps_PT,...
temps_met,...
model_PT_f,...
model_met_f,... % suffix 'met' is employed for clarity but should be 'met_PT' as the model and parameters deal wit... |
79f7793ac13ea0286c604bc60f0c0b12080144222f2ed0ebe79f699efb75c804 | MATLAB | 2,227 | 63 | function [Tr_sig, loc] = sig_trend(sig)
%
% [Tr_sig, loc] = sig_trend(sig)
%
% *************************************************************************
% * Calculating the trend of a signal using local minima *
% *************************************************************************
%
% Usage: ... |
e1f57538ff008a1beb74db41e287c12558d620b9487229300ea07805c4216836 | MATLAB | 2,228 | 86 | function c = get_water_content_tour(cmet)
marsbar('on');
pp.verbose=0;
anat_dir = '/home/romain/data/spectro/tourette/anat';
%suj_dir = get_subdir_regex(anat_dir,'rett')
c=cmet;
for npol = 1:length(cmet)
suj = cmet(npol).suj;
for ns = 1:length(suj)
sujname = suj{ns};
if findstr(sujname,'_sujet_'... |
5354bd6e7e87c4e7cac8412514d429b73d2dd968ff393405b867be4bbbbc1c87 | MATLAB | 2,229 | 71 | %% calculate Magnitude index
%% load all data files
clear
clc
[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
%% calulate
count = 0;
window_names = {'ON', 'S... |
3233cceb31e3583fe8bd7083373ff6b176024549a768700a9e3a3d8a616f3b19 | MATLAB | 2,231 | 70 | % Solve the RED problem
% min 1/(2*sigma_w^2)*\|b-|Ax|\|^2+lambda/2x'*(x-f(x)) where f(x)
% is a denoiser
% using the solver FASTA.
%
% Inputs:
% A : A matrix or function handle
% At : The adjoint/transpose of A
% b : A column vector of measurements
% x0 : Initial guess of s... |
c9fe076f2591bbebbfd6bb80f73b5776b37767642ea91c337e617d1b270950a6 | MATLAB | 2,231 | 42 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [pops_PT, pops_met] = simulate_pop_PT_met(...
temps_PT,...
temps_met,...
model_PT_f,...
model_met_f,... % suffix 'met' is employed for clarity but should be 'met_PT' as the model and parameters deal wit... |
1254c336c7601fa44f9ecaa8e50805de58f9ec4e4a8a0aa598b15d394adc1a13 | MATLAB | 2,232 | 73 | function Image= Test_Image_Color(I)
[x,y] = size(I);
Image = zeros(x,y,3);
for i = 1:x
for j = 1:y
if I(i,j) == 1
Image(i,j,1) = 0;
Image(i,j,2) = 0.4824;
Image(i,j,3) = 0.7412;
elseif I(i,j) == 2
Image(i,j,1) = 0.8500;
Image(i,j... |
7a18029624d62f5125862947b52f316526e3c742f730da8442467bc5c8de2688 | MATLAB | 2,232 | 60 | % Function that make Hierarchichal Cluster
% from Matrix Activity
% Input
% Raster: Matrix Cells x Frames
% CAG Threshold: Scalar
% Simmilaarity Method : 'hamming', etc
% Ouput
% R_Analysis Output Strcuture Output
function R_Analysis = get_ensembles_manual(R,CAGth,SimMethod)
ActiveCells= sum(R,2);
% GET ... |
c8ffc702f8b406e357efd0fa4803100ff83b9190b8e997861255ec59d35722fc | MATLAB | 2,232 | 62 | function sampledWindows = getSpikeWindows(obj, spikes, sites, useRaw, useVolt)
%GETSPIKEWINDOWS
% input: spikes, a vector of spike indices
% input: sites, a vector of site indices
% input: useRaw, bool, a flag use raw waveforms if true (else filtered)
% input: useVolt, bool, a flag to u... |
7b941aa5871cbd80d893bf5389967d96276ce78dab7838ab7a1b19d1842d1dd3 | MATLAB | 2,235 | 61 |
function [dip, p_value, xlow,xup]=HartigansDipSignifTest(xpdf,nboot)
%
% % function [dip,p_value,xlow,xup]=HartigansDipSignifTest(xpdf,nboot)
% %
% % calculates Hartigan's DIP statistic and its significance for the empirical p.d.f XPDF (vector of sample values)
% % This routine calls the matlab routine 'HartigansD... |
8ffcbaa65288275bcd94e18d02c601068d920009a78c443b1ae635c50e538dad | MATLAB | 2,235 | 60 | % Script to Load & Process Calcium Fluorescence Signals (ImPatch Experiments)
% It detects Calcium Transients from VIDEOS of a single slice (EXPERIMENT)
% Sugggested Directorie's Strcuture:
% NAME_EXPERIMENT/ {VIDEOS & Coordinates from fSIENN):
% Input (same directory):
% Coordinates:
% ALL (XY).csv Coordinat... |
c49452f26b3eb14d183dd0fa03a3d3fb852dcc6ce7c1e4d1338e2f19649381a9 | MATLAB | 2,236 | 89 | function [diff,CI,p,sig] = rst_pbvar(data1,data2)
%[diff,CI,P,SIG] = pbvar(data1,data2)
%PBVAR - percentile bootstrap test to compare the variances of 2
%independent groups
% 2 tailed bootstrap test based on the estimation of H1, the
% hypothesis of an experimental effect. nboot the number of bootstrap
% samples = 600.... |
be9c7634201c8c2f6f430d9040eb4eb2f5c2f7e31fa96b733abca79c1ee09c63 | MATLAB | 2,238 | 67 | function computeCentroids(obj, updateMe)
%COMPUTEPOSITIONS determine cluster position from spike position
if nargin < 2 || isempty(obj.clusterCentroids)
updateMe = [];
end
if isempty(updateMe)
centroids = zeros(obj.nClusters, 2);
clusters_ = 1:obj.nClusters;
else % selective... |
354b91fcb03ac454982981adef6bfb68c266bfbc00f31e808c77bdb64a442444 | MATLAB | 2,239 | 99 | function ff = embed(x, mask, varargin)
%function ff = embed(x, mask, varargin)
%| embed x in nonzero elements of (logical) mask
%| in
%| x [np (L)] the "nonzero" pixels (lexicographically stacked)
%| mask [(Nd)] logical array, np = sum(mask)
%| option
%| '*dim' {0|1} 0: [(N) (L)] (default); 1: return [(N) *L]
%| out... |
0e2bcae9a9bdfed56c993ddafbe102c45e5d8ab99bbceb8508a8324056e25250 | MATLAB | 2,241 | 42 | function matlabbatch = spmup_get_FM_workflow(type)
% routine to get the SPM batch workflow for FieldMaps
%
% FORMAT matlabbatch = get_FM_workflow(type)
%
% INPUT type can be 'phasediff' or 'phase&mag'
% OUTPUT matlabbatch is a structure pre-filled with SPM options
%
% Cyril Pernet & Remi Gau
% -----------------------... |
f21f99b39a60f26dde003de8d7673275f16fe8c75e776bea229c53ec61782c73 | MATLAB | 2,241 | 55 | function success = exportQualityScores(obj, zeroIndex, fGui)
%EXPORTQUALITYSCORES Export cluster quality scores to CSV
if nargin < 2
zeroIndex = 0;
end
if nargin < 3
fGui = 0;
end
ID = (1:obj.nClusters)';
centerSite = obj.clusterSites(:) - double(zeroIndex);
nSpikes = ob... |
6dc66bc1bff7df2cb782509e3a529457aa790a7449afe067bb7706f8d6136bc7 | MATLAB | 2,243 | 74 | function [Sig2NoisePeak]=mnl_EvaluateCumulativeSignal2Noise(Noise,Signal,ChanNum)
%mnl_EvaluateCumulativeSignal2Noise is designed to evaluate where the
%difference is between two different distributions of different sample
%sizes. It then plots several graphs to visualise the differences
%Inputs
% Noise - Single colum... |
e7110a93ac035b605824d1a965966355d786023de0931f2f8a19b5d5623d6fdf | MATLAB | 2,243 | 67 | function [ lfp_signal ] = ripple_detection_preprocess( data_st )
% Usage:
% [ lfp_signal ] = ripple_detection_preprocess( data_st )
% Input:
% data_st bipolar signals
% Output:
% lfp_signal
% .lfp_st Signal with power line noise removed by preprocessing
% .ripple_st 70-180Hz filte... |
a178b6e2a647c2f990f9daa197c5b700fbc8950e52846f7a08c3aecd6ce7546b | MATLAB | 2,244 | 53 | function build_database
%% Download and import Allen Mouse Brain Connectivity Atlas
% 1. Import experiments.csv into MATLAB
% 2. Download AMBCA XML files.
% 3. Import in MATLAB and save as .mat files.
% 4. Define network nodes from injection sites: only structures that are
% the injection site in at least one exp... |
37b17d9ae2db506904c66c14fc3047f3f448937f17da84720f9342c39a30277e | MATLAB | 2,246 | 85 | % test_linear_phase_equalizer_design.m
% Design and visualize a linear phase equalizer filter
%
% Reza Sameni, 2024
% The Open-Source Electrophysiological Toolbox
% https://github.com/alphanumericslab/OSET
% Context: let's say we have a signal with spectrum S_source(f), which we
% want to equalize to a target s... |
8dfe0c53bea10871c25e27f615a496199f370d1c20c74e78c5914b231469eacd | MATLAB | 2,246 | 73 | %
% Test program for Kalman notch filter
%
% Dependencies: The baseline wander toolbox of the Open Source ECG Toolbox
%
% Open Source ECG Toolbox, version 1.0, October 2007
% Released under the GNU General Public License
% Copyright (C) 2007 Reza Sameni
% Sharif University of Technology, Tehran, Iran -- GIPSA-... |
0dc4949d56706a0f0bd0e5fd16f42c2d79316a0f52d1987ac7a9f08bcc7b3773 | MATLAB | 2,248 | 69 | function install(pddir)
%INSTALL Install toolbox directories.
% INSTALL is an easy to use installation program for toolboxes.
% It installs toolbox directories when run from the base directory
% of a toolbox. A file "info.ins" created by MAKEINSTALL must exist
% in this directory.
% Example of usage:
%
% ... |
729a0d7a42942345eac770396505840a9d504c269abd61c5a63c0bd7bc2e4412 | MATLAB | 2,251 | 66 | % create psth vector from all data
%% load all data files
clear
clc
[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
%% calulate
count = 0;
nds = [10,8,6,4,3,... |
b17b0b225aecfd006ab274501c761518b541fcc3ee8522a245f8e71fa3392787 | MATLAB | 2,251 | 66 | function [ Thresh, error_subspace ] = Calculate_Alpha( FINAL_FEATS, labels, Curveoption )
%This piece of code runs the PLDA function with different values of alpha
%and plots two error curves
%The projection metric distance of two consequent subspaces
%written originally by Soheil Kolouri, modified by Shinjini Kund... |
c2afb1f808e0ada2877e3527bb7a6532179547dc062ade1d169c3aff102c1600 | MATLAB | 2,251 | 65 | function [onsetsFinal, offsetsFinal] = JT_getOnsetOffset(signal, ampThreshold, minBelowTime, minAboveTime, behFlag)
% [onsetsFinal, offsetsFinal] = getOnsetOffset(signal, ampThreshold, minBelowTime, minAboveTime, behFlag)
%
% Summary: This function determines the indices of onsets and offsets
% for a movement bo... |
d65bcf739f007a6baaabeda2993ba142e47a94c3d786fc8ffa4b65a2e6b7a453 | MATLAB | 2,254 | 86 | function plot_AG_sigVals(FS,AG,FRP,NodeName,atlas,options,savepath,save)
% before plot_AG_trans_MSPoI_Mikael.m
atlas_name = options.atlas{atlas};
fg = 0;
for cm = 1:3
fg = fg + 1;
fig = figure;
CF = AG{cm};
AM_diff = CF(:,:,2) - CF(:,:,1);
sig_AG = FS.RES... |
7b97f07d59f10b4d004e4aedd00d3c95c342aaafd69f24607a9cd3ff615fb683 | MATLAB | 2,255 | 79 | function nuisances = spmup_nuisance(fmridata, whitematter, csf)
% Routine to compute nuisance regressors from White matter and CSF masks.
% Masks are thresholded at 70%, the time series extracted, detrended (2nd
% order polynomial) and averaged
%
% FORMAT: nuisances = spmup_nuisance(fmridata, whitematter, csf)
%
% IMP... |
89dbabd10b265393a6fee8831e1521f0c1d1158a94a40a157fb52bd8956b8c2f | MATLAB | 2,255 | 79 | % load aligned cell maps and quantify MSE
clear
p = params_2DAA;
%% load maps
for sub = 1:p.nSubjects
for ses = 1:p.nSessions
thisSub = p.subjects(sub);
fpath = fullfile(p.rootDir,'miniscope', ['subject' num2str(thisSub)],['session' num2str(ses)],'extracted','cellMap.mat');
load(fpath)
... |
0e200bf3568d7ebbe6cfdcb5414c572b22de453b8d2b09a0108e9e403d18b144 | MATLAB | 2,256 | 77 | function x = nufft_adj_single(X, st)
%|function x = nufft_adj_single(X, st)
%| Apply adjoint of d-dimensional NUFFT to spectrum vector(s) X
%| in
%| X [M,(L)]
%| st structure precomputed by nufft_init()
%| out
%| x [(Nd),(L)] signal(s)/image(s)
%|
%| Copyright 2003-6-1, Jeff Fessler, University of Michigan
%
% - Da... |
f325fbbdf030946a8a62fc2d0bcc17d316a2c19310af147c1bbab89cf112130b | MATLAB | 2,259 | 129 | function c1 = correct_result(c1,c2,field_list,fielnamcor)
divide=0;
if ~exist('c2')
c2=c1;
end
if ~exist('fielnamcor')
fielnamcor = 'cor_all';
end
correct_only_with_mean=0;
if iscell(c1)
for k=1:length(c1)
field_list = find_metab_list(fieldnames(c1{k}));
c1{k} = correct_result(c1{k},c2,fiel... |
51d8fec3b761350370d782ae6875165cf1c8942408f33dd7b1803ec0fc6bf46c | MATLAB | 2,264 | 80 | function rasterplot2(times,numtrials,triallen,offset,varargin)
nin=nargin;
%%%%%%%%%%%%%% Plot variables %%%%%%%%%%%%%%
plotwidth=0.01; % spike thickness
plotcolor='k'; % spike color
trialgap= 1; % distance between trials
defaultfs=15000; % default sampling rate
showtimescale=1; % display timescale
... |
9e2d4e9566584391a6e344788d943eb8fb4ecd37b143c223a1e68848ba8b4cb0 | MATLAB | 2,264 | 78 | % 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,... |
1f55a6f54f6ab66a2a049e8588da4c59690ee1f663ec48b1605cdd3a826f4676 | MATLAB | 2,265 | 58 | function FRA_analysis_subfields(FRA_file_input, genotype)
% Authors: Simon Wadle & Tatjana Schmitt, 2019-2023
% this function sorts FRA parameter on a subfield-specific basis
% gets called by 'pipeline_complete_SPLanalysis_awake_FMR1.m'
for j = 1:2
if j == 1
[path, name, ext] = fileparts(FRA_file_in... |
5fffa0c67a27f72657133e3cb79ba652d9858143fb9ab1b034bbb5ad21e781c7 | MATLAB | 2,265 | 48 | function success = commit(obj, spikeClusters, metadata, msg)
%COMMIT Commit a modification of clustering to history log
%% first run parent class commit method
success = commit@jrclust.interfaces.Clustering(obj, spikeClusters, metadata, msg);
%% then update template similarity scores
if success
... |
822c27c85730ba9daf767d95ae3c337d0b951701cab72edc6d33fd97aae9c7a8 | MATLAB | 2,265 | 107 | clear all
close all
clc
load('nn.mat')
r_on = scatterplot(results(1,:),results(2,:));
r_on_shuffled = scatterplot(results(1,:),results(3,:));
load('nn_OFF.mat')
r_off = scatterplot(results(1,:),results(2,:));
r_off_shuffled = scatterplot(results(1,:),results(3,:));
%%
clear all
clc
%colormap defin... |
bec56fb3b6ff7b30bc4f51a4cf0c387ea359bbd35fe239203ce33a192231d3f7 | MATLAB | 2,266 | 88 | function x = newfft_approx_adj(st, X, om)
%function x = newfft_approx_adj(st, X, om)
%|
%| Adjoint of (approximate) NUFFT
%|
%| in
%| st structure precomputed by nufft_init()
%| X [M (L)]
%| om [M 1] optional frequency vector (default: st.om)
%|
%| out
%| x [(Nd) (L)] signal(s)/image(s)
%|
%| Copyright 2003-6-1, Je... |
24ba5f4ead1cb7268067cd0d109b67224e0746af8d0623891f799dfaecdf8a0b | MATLAB | 2,267 | 51 | function repeat_heatmap
%%% gt3Ælt2Ìdevideq[g}bvÌðÍ
%%% devideÌq[g}bvð½Ïª1ÉÈéæ¤ÉW»µÄàÆÌFigureÉã«·évO
path = 'C:\Users\C238\Desktop\touchcellLtRt_Hirokane';
savepath = 'C:\Users\C238\Desktop\Rhythm';
patternnum = 1;
for i=1:82 %»ê¼êÌ×EÅCe[V... |
e926aea8b837179293f072e38e3b6c819293a95c57f42ea4efb7cb8dc17e1b4e | MATLAB | 2,268 | 88 | function [tf, frex] = wavecwt(signal, srate, frange, ncycles, nsteps)
% This function performs a highly customizable complex morlet wavelet transform.
% Written Tylor J Harlow 9/12/2023 - tylor.harlow@uconn.edu
%
% adapted from code by Michael X Cohen
% "A better way to define and describe Morlet wavelets for ti... |
3780d58e97ec1fa869239716967ffc4ecbdfe628c0464741f747871353ce649a | MATLAB | 2,269 | 76 | function strval = field2str(val)
%FIELD2STR Convert a value to a canonical string representation
switch class(val)
case {'int', 'int16', 'int32', 'uint16', 'uint32', 'logical'}
formatstr = '%d';
case 'double'
if numel(val) == 1 && val == floor(val) % integer
... |
15cdbe5719076b8d2b5d2d2c8811833da08c003ac1a6f4476ef005f18677c5a1 | MATLAB | 2,270 | 68 | % ecg_gen_twa Test Script
%
% This script demonstrates the usage of the ecg_gen_twa function to generate
% synthetic ECG signals with T-wave alternans (TWA) using the warping
% transformation from the phase domain.
%
% Revision History:
% 2023: First release.
%
% Reza Sameni, 2023
% The Open-Source Electrophysiologic... |
e460ceae431d107dca9d29e8d83b29e181c99c1938e3d38237bcde59745cbd30 | MATLAB | 2,271 | 72 | %% Script to concatenate Network Features: NetFeat Files
% Makes a TABLE of Different and MULTIPLE Network Features
%% Setup
% Initial:
clear; close all; clc;
Load_Default_Directories;
fprintf('>It merges tables created in Make_Statistics_Gephi_Features in one single table\n')
runs=1; % Runs Counter
FEATS={... |
f09525d1642846101f3b6717a43d7d131f512b6838e1f41f90f9a9b9b383b1e8 | MATLAB | 2,273 | 62 | % function cluster_combineCoils(reconParsFile)
load(reconParsFile)
run([RETROMOCOBOX_PATH '/addRetroMoCoBoxToPath.m']);
% run([MIRT_PATH '/setup.m']);
addpath(SPM_PATH);
% parfor doesn't like some stuff... have to make it clear that they are
% variables by setting them equal to themselves...!
tempGRAPPAreconFile = t... |
55fd6a9ba4074627a346160e1f6d4230516eadd6fb7385e90d7aa956c0befdfd | MATLAB | 2,274 | 72 | function [tmean,tmCIlo,tmCIhi,df,se,p,Ty] = rst_trimci(x,percent,alpha,out,mu)
% function [tm,tmCIlo,tmCIhi,g,se,p,Ty] = trimci(x,percent,alpha,out,mu)
% Returns the 1-alpha confidence interval of the trimmed mean.
%
% INPUTS:
% x - vector
% percent - percentage of trimming, default = 20
% alp... |
f98e6fc0d8b6d2e17d3d4e4ab285154b9f745afcfa1b33c70296fdb48aa2c2d3 | MATLAB | 2,274 | 83 | % nufft_tune_gauss
% tune the FWHM for gaussian interpolation in 1D NUFFT
% to minimize the worst-case error
if ~isvar('err_gauss')
N = 2^8;
K_N = 2; % oversampling factor
Jlist = [2:16];
Plist = linspace(0.2, 0.4, 101); % sig = parameter * sqrt(J)
rlist = [0:20]'/40; % fractions of gamma
err_gauss.zn = ze... |
bec1fd91024931447d5f6562e77ab6eb7b3d9f721dc6d83607f02c191d104af2 | MATLAB | 2,275 | 73 | % 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 Neuroscie... |
22ebce3df7274a834c308c03bbcd80afb8319535ec2b9143bdf030794abc6175 | MATLAB | 2,278 | 97 | clearvars -except ONimageS OFFimageS refpic Error CC
%% Calculate SRsp
CC1 = CC;%total;
NF=size(ONimageS,1);
rep = size(ONimageS,2);
currRsp = zeros(CC1.NumObjects,NF,rep);
for ci=1:CC1.NumObjects
bw5=zeros(512,512);
bw6=zeros(512,512);
area = mean(refpic(CC1.PixelIdxList{ci}));
... |
8a42e2dee10fc94708800c69c31f73d0cbeccaa74eb1b9ffdc0bc992e4b77637 | MATLAB | 2,278 | 88 | function [energy,min_dist] = point_set_energy_dist(points,s)
%POINT_SET_ENERGY_DIST Energy and minimum distance of a point set
%
%Syntax
% [energy,min_dist] = point_set_energy_dist(points,s);
%
%Description
% [ENERGY,MIN_DIST] = POINT_SET_ENERGY_DIST(POINTS,s) sets ENERGY to be the
% energy of the r^(-s) potential on t... |
bb37913567be1cf3e04408384fb531ce5b5d166a52bfd605fa87cb3decee6b2f | MATLAB | 2,278 | 48 | % 计算Label图片中各类矿物组分的占比
clc
clear
pixel_num = zeros(1,14);
x = 224;
y = 224;
InputPicBG = 'E:\SemanticSegmentation_Scale\NET_Muli_CPL_XPL_All\Revolve_Pxds_Test\*.png';% 背景原图的存放位置里的tif文件
InputPicPath = 'E:\SemanticSegmentation_Scale\NET_Muli_CPL_XPL_All\Revolve_Pxds_Test\';% 背景原图的存放位置
FilePic=dir(InputPicBG);% 找到文... |
670e8c550a0e88be60c326e029b0cf81acb6f11fa67555be0856eb9677bd529e | MATLAB | 2,283 | 55 | function [xd yd delta deltaCI] = rst_shifthd(x,y,nboot,plotshift)
% [xd yd delta deltaCI] = shifthd(x,y,nboot,plotshift)
% SHIFTHD computes the 95% simultaneous confidence intervals
% for the difference between the deciles of two independent groups
% using the Harrell-Davis estimate
% See Wilcox p.151-155
%
% GAR, U... |
b031d07b2def8178d4cddd8e11665b41f4419fc91a83fa3e55222847c499f024 | MATLAB | 2,283 | 53 | % Function to extract network parameters from tables
%
function [TotalTable,DATAnet]=TableNetwork(ExsitFeature,GEPHIDATA,EXPLIST,Names_Conditions,ActualFeature)
TotalTable=table;
DATAnet={};
% ALLpreActive=cell(NE,NC);
fprintf('>>Reading data for table: \n')
n=1;
while sum(ExsitFeature(:))>0
% No empty Table
i... |
8fb3e7c37febcc9d6c70932897ed167dcc9f6287643bb0e22135cec77f14426f | MATLAB | 2,284 | 49 | % TrimmedFilter has been deprecated. Use trimmed_filter.cpp instead.
error('TrimmedFilter has been deprecated. Use trimmed_filter.cpp instead.');
% y = TrimmedFilter(x,type,L,k,h),
% y = TrimmedFilter(x,type,L,k,l,h),
%
% A moving average, median, or trimmed mean filter.
%
% inputs:
% x: input vector.... |
05d32b56fabba2521630fcae7a90d17d1dc16a63cf2d9bed2717bc1f4db8a6a2 | MATLAB | 2,285 | 74 | function perturb_hopf_noisebynode_MCS(node)
load Modelling_Workspace_MCS.mat
PERTURB=0:-0.02:-0.2; % Noise protocol.
we= 0.07; %% Insert here G value from optimal MCS model fitting
ITER=10;
N=214;
a=-0.02*ones(N,2);
C=squeeze(Coptim(find(abs(WE-we)<0.0001),:,:));
TSmax=295;
NSUB=29;
TR=2; % Repetiti... |
2c206069770f26db5a49e3acd064d66df0d434d1b7e4b4f91cc15301ec77bd9a | MATLAB | 2,285 | 66 | function derived_bp_signals(app)
sys_idx = nan;
dia_idx = nan;
mea_idx = nan;
tmp = nan(1,length(app.data));
for i = 1: length(app.data)
tmp(i) = app.data(i).tic_multipl;
if strcmp (app.data(i).name,'systolic BP')
sys_idx = i;
end
if strcmp (app.data(i).name, 'diastolic BP')
dia_idx = ... |
50af04818bc18fff44af50d941f6836f9ac672a06e09718ed708b1c2cee43c54 | MATLAB | 2,285 | 73 | function [OutFeature,ndiff] = RaguMSFeatures(MSClass,n,MSFit,gfp,NoCenter)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
OutFeature = nan(size(MSClass,1),size(MSClass,2),n,6);
on = nan(size(MSClass,1),size(MSClass,2),n);
off = nan(size(MSClass,1),size(MS... |
093b6092ba2fc7fb36365174cb36bde3547b21a06516d692bcb5cc4c10bf6b51 | MATLAB | 2,286 | 82 | function coeff = point_set_energy_coeff(points,s)
%POINT_SET_ENERGY_COEFF Coefficient in expansion of energy of a point set
%
%Syntax
% coeff = point_set_energy_coeff(points,s);
%
%Description
% COEFF = POINT_SET_ENERGY_COEFF(POINTS,s) does the following:
% 1) finds the r^(-s) energy of the point set POINTS, and
% 2) ... |
2f1ad85d71948290b6e3999a4f9eb01aaa59ba96654fdddaa401b6bda7cf5839 | MATLAB | 2,286 | 56 | function [gam_grid_both, shuffle_both]=pyGAM_int_2models_shuffle(y_array_bvd,X_arrayboth_vel,x2shuffle,np,lams,shift,shuffle_number)
% pyGAM_int_2models_shuffle performs GAM analysis with shuffling for interaction models.
% This function fits GAM models, shuffles specific predictor columns,
% and evaluat... |
fc668dad475bf9c0dd36492b52173210a53673b0a2ea885500d940f6d44f4925 | MATLAB | 2,286 | 67 | function derived_bp_signals(app)
sys_idx = nan;
dia_idx = nan;
mea_idx = nan;
tmp = nan(1,length(app.data));
for i = 1: length(app.data)
tmp(i) = app.data(i).tic_multipl;
if strcmp (app.data(i).name,'systolic BP')
sys_idx = i;
end
if strcmp (app.data(i).name, 'diastolic BP')
dia_idx = ... |
43af71b358daa028877759608f51c1366d23060a7a020ea93bdc6881702cea52 | MATLAB | 2,287 | 70 | clear all, close all
% load time_data.mat
load time_measures_NaCl.mat
load time_data_NaCl.mat
%% Plot of the time oscillation, Na
f = figure(2);
f.Position = [520 20 400 850];
f.Color = [1 1 1];
t = tiledlayout(4,1,"TileSpacing","loose","Padding","loose");
% 0 Hz
ax1 = nexttile;
plot(NaCl_80mM.Time(1:3:e... |
adc6d200fb702437f3f9d7093eb43a3d3486e264f57ac4b410f3be3df3ea4545 | MATLAB | 2,288 | 68 | %
% Test program for generating single-channel ECGs with additive colored
% noise
%
% Dependencies: The synthetic ECG generator and noise generator package of
% the Open Source ECG Toolbox
%
% Open Source ECG Toolbox, version 1.0, November 2006
% Released under the GNU General Public License
% Copyright (C) ... |
13d197d0ced8add75e1c0393de7c69e36c065625315d64245ac8b4e94d55a7d4 | MATLAB | 2,293 | 59 | clear;
close all;
% Synthetic maternal parameters
params{1}.mean = [];
params{1}.std = [];
params{2}.mean = [];
params{2}.std = [];
params{3}.mean = [];
params{3}.std = [];
params{1}.theta = [-1.09 -0.83 -0.19 -.07 0 .06 0.22 1.2 1.42 1.68];
params{1}.a = [0.03 .08 -0.13 .85... |
ec690e04555c27baa08ceccb18743ce1c41027ef634eb0043eab57350a351485 | MATLAB | 2,293 | 81 | function base_path = getMyBasePath(file_name,varargin)
%getMyPath Returns base path of calling function
%
% base_path = sl.stack.getMyBasePath(*file_name,varargin)
%
% Outputs:
% --------
% base_path : path to cotaining folder of function that is calling
% this function.
%
% Inputs:
% -------
% fil... |
7f64327328ef5037ad4d5c8f46f7024d1e534123b6bf2f57a9343dd5859830b9 | MATLAB | 2,294 | 74 | function [grnnet] = load_grn_network(path_dream5,NETWORK,varargin);
% LOAD_GRN_NETWORK Load gene regulatory network of the DREAM5 challenge.
% GRNNET = LOAD_GRN_NETWORK(PATH_DREAM5,NETWORK) for path PATH_DREAM5 and index NETWORK returns
%
% GRNNET.x gene expression levels (#genes-by-#samples)
% ... |
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