sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
405d0609f1544b80c32809856a240fcc2d3d0e01b386aac42ae6be80292a1eca | MATLAB | 1,283 | 43 | % test function for Generalized Singular Value Decomposition
%
% Open Source Electrophysiological Toolbox, version 3.14, June 2019
% Released under the GNU General Public License
% Copyright (C) 2019 Reza Sameni
% reza.sameni@gmail.com
% This program is free software; you can redistribute it and/or modify it
% under ... |
0aca666d972ec61cb61511f2a13d61eee3c080ca7187b4bda36d7f921992ed4b | MATLAB | 1,285 | 47 | function distance = euclidean_dist(x,y)
%EUCLIDEAN_DIST Euclidean distance between two points in Cartesian coordinates
%
%Syntax
% distance = euclidean_dist(x,y);
%
%Description
% DISTANCE = EUCLIDEAN_DIST(X,Y) sets DISTANCE to be the Euclidean distance
% between the two points X and Y.
%
% The arguments X and Y must b... |
b43f9e6815952f9a781a87c57d8b5ab5d75e097d95372d92cbe0a26a2ff39d62 | MATLAB | 1,286 | 64 | 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... |
2a6d535a9da283de2e0c586c26c72d3b167ae1be84cf91da43a1229d0070ad4c | MATLAB | 1,287 | 32 | %function [mrVpp1, mrVpp2] = getSpikeCov(sampledSpikes, iSite)
function [mrVpp1, mrVpp2] = getSpikeCov(hClust, sampledSpikes, iSite)
%GETSPIKECOV Compute covariance feature for a subset of spikes
hCfg = hClust.hCfg;
spikeSites = hClust.spikeSites;
spikesFilt = hClust.spikesFilt;
nSpikes = numel(sam... |
eb38823d59024926df6cee4bd0e837d89ddd081ece65bfec2473e36fe67adea0 | MATLAB | 1,288 | 39 | function y = bp_filter_complex_ma_fixed_tap(x, w0, N)
% bp_filter_complex_ma_fixed_tap - Complex frequency domain first-order
% moving average bandpass filter with a fixed tap
%
% y = bp_filter_complex_ma_fixed_tap(x, w0, N)
% A complex domain moving average bandpass filter.
%
% Inputs:
% x: input data... |
f0647b9ad177c5ff1c5dd7e1e8b72d54289ff72ff2dbd0982147e272208e26df | MATLAB | 1,291 | 40 | function EEG = remove_noise(EEG, Cuts_Filepath)
% from EEGLAB structured data, looks for corresponding .mat file where
% manual scoring of noise output was saved (in /Cleaning/Cuts/) as a TMPREJ
% array, which is a n x (2+3+ # channels) matrix. The first two columns are
% the start and end timepoints of the artefact.
... |
141e245043fbaed2901cdd6b31164d869c4b0a3487f47e625b44227c00e3c718 | MATLAB | 1,292 | 28 | function [proj1, proj2, proj3] = pcProjectSpikes(sampledWindows, prVecs1, prVecs2, prVecs3)
%PCPROJECTSPIKES Project selected spikes onto 1st, 2nd, 3rd principal components
% input: sampledWindows is nSamples x nSpikes x nSites
% input: prVecs{1,2,3} is nSamples x nSites
% output: proj{1,2,3} is... |
aa9310dd3a588396ef1308d4869d36a7f6dd22aee7c7aed93cf61c1f87fcb028 | MATLAB | 1,292 | 50 |
%datasetName = 'MNIST';
datasetName = 'CIFAR';
%datasetName = 'CIFAR-100';
%datasetName = 'SVHN';
kWorkspaceFolder = fullfile('/media/sergeyd/OS/Users/sergeyd/Workspaces', datasetName);
errfile = fullfile(kWorkspaceFolder, 'final-last', 'noise0.2.mat');
load(errfile, 'errors', 'stdev');
clear LineSpec;
LineSpec{1} =... |
a9cce336e672cb9864494a44939401cc8fd01b783e9a8b751b61be46cdc4533a | MATLAB | 1,293 | 42 | function [SIGNALS,r,H,W,RADroi,fs]=FluorescenceSignalsCSV(NumberofSplits,FN,PathName,r)
RADroi={};
%% Load Data *********************************************************
% For each CONDITION and VIDEO
[X,fs]=readdeltaFzero([PathName,FN{1}]);
[C,F]=size(X);
if C>F
X=X';
[C,F]=size(X);
disp('Transposed to Cel... |
4b2f545dbf9151de76105692fdf6b3941bbc4fe3a21e52de8b8ec184b0d8fc1f | MATLAB | 1,295 | 45 | function area = area_of_collar(dim, a_top, a_bot)
%AREA_OF_COLLAR Area of spherical collar
%
%Syntax
% area = area_of_collar(dim, a_top, a_bot);
%
%Description
% AREA = AREA_OF_COLLAR(dim, A_TOP, A_BOT) sets AREA to be the area of
% an S^dim spherical collar specified by A_TOP, A_BOT, where
% A_TOP is top (smaller) sp... |
ff597405841336b45f9809df2c3b4541aac347adff5063e9f2c4405e208d7574 | MATLAB | 1,295 | 54 | function lambda = findlambda(X,numspikes,fs)
%FINDLAMBDA get thresholding parameter for specified number of spikes
%
% Input parameters:
% X : SocialSparsity neighborhood
% numspikes : Number of spikes
% fs : Sampling frequency
%
%
% Description:
% findlamda(X,numspikes,fs) fi... |
3997e3c61c0ed5f97c7c572e5d0bb93ded92f836dd14e3d9efc3dc9c5e4024e8 | MATLAB | 1,296 | 33 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This script simulates the effect of different doses and duration of neoadjuvant treatment
% on primary and secondary tumor kinetics
% It generates the plots of Figure 3
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
94f2fb8b98e38596a82723f34d0f10593e6ce48ed9149f593f69e78338abfd8a | MATLAB | 1,297 | 52 | function [links,weights]=minimal_spanning_tree(d)
% [links,weights]=minimal_spanning_tree(distance_matrix/weights)
%
% Prim's algorithm for constructing the Minimal-Spanning Tree (MST)
% from a given symmetric distance/similarity matrix
%The input matrix must be a mapping from weight to distance. For
% ins... |
384032d9b7e68ace912345826b311b8c1e669a3dec5151134a0a9b49d561472a | MATLAB | 1,298 | 43 | function [BurstMask, ReferenceMask] = mask_bursts(EEGData, Bursts)
% creates a matrix the size of the data in EEG, with values of the data
% only during the bursts
BurstMask = nan(size(EEGData));
% identify location of bursts
if isfield(Bursts, 'ClusterStart')
Starts = [Bursts.ClusterStarts];
Ends = [Bursts.C... |
b37a1b7a625e6927b3e5f714f10d3bbe0f675802f5e3823b9a17adfe3645b50b | MATLAB | 1,300 | 51 | function fname = abcd_check_eprime_encoding(fname,outdir,forceflag)
%function fname = abcd_check_eprime_encoding(fname,[outdir],[forceflag])
%
% Purpose: check whether eprime file is plain text or unicode UTF-16
% and if so, convert to ASCII
%
% Required parameters:
% fname: full path name of eprime output file
%
%... |
2c66fdca7544a6c5dafbac2a1c1d75c0430c25a04414c14111c77cec280d6d1d | MATLAB | 1,301 | 52 | function out = euler2rmat(phi, theta, psi)
if nargin==1
eMat = phi;
nT = size(eMat,2);
else
nT = 1;
end
out = zeros(3,3,nT);
for iT = 1:nT
if nT > 1
phi = eMat(1,iT)*pi/180; theta = eMat(2,iT)*pi/180; psi = eMat(3,iT)*pi/180;
else
phi = phi*pi/180; theta = theta*pi/180; ... |
c0eb26002354ba57907608f57f4bb08ad7c566aa898879ed999934354f5a9890 | MATLAB | 1,301 | 48 | function output_path = createFolderIfNoExist(varargin)
%createIfNecessary: Creates a folder if it doesn't exist
%
% This function creates a folder if it does not exist. In addition it can
% be used to:
% - construct the path of the folder
% - construct the path to a file, ensuring that the folder path t... |
54ae4ca0065c57653b4b50932220e0ad316d0733f8e987a6b425ee0681318a8a | MATLAB | 1,304 | 39 | clear all
% this script contains code to reproduce Figure 1f
%% load data
% drag and drop corresponding file (S1 Data)
%% data content description
% IHC contains GFAP fluorescence values across various cortical ROIs
% column 1: animal id
% column 2: ROI location (slide)
% column 3: GFAP fluroescence
... |
89beac0d3b33c04304283ac05ecf0ca73b38abb6df8189aa46461ae165d69009 | MATLAB | 1,304 | 46 | %Threshold setting and selection of the sufficient correlations for the visualisation
clear row
clear col
clear source
clear target
%% eliminates self connections
for t = 1 : length(cross)
cross(t,t) = 0;
end
%% eliminate NaN values
cross(find(isnan(cross)))=0;
%% REMOVE ARTEFACTED CHANNELS
% artefacted_channels... |
ecb7631cce092d638c8304fe89242cc8178f09354473e67b6cd34f0fac10a9e4 | MATLAB | 1,304 | 41 | function md = info()
%INFO Get JRCLUST repository metadata
fid = fopen(fullfile(jrclust.utils.basedir(), 'json', 'jrc.json'), 'r', 'n', 'UTF-8');
fstr = fread(fid, '*char')';
fclose(fid);
md = jsondecode(fstr);
hash = gitHash();
if ~isempty(hash)
md.version.commitHash = hash;
e... |
18ca8391c16005802e04dfab4f780f73810b197415517b753e279526eac73bb9 | MATLAB | 1,306 | 35 | function h = CorrCoefFig(FrETemp, FrITemp, mVETemp, mVITemp)
h = figure('Name','Correlation');
subplot 231;
scatter(FrETemp, mVETemp, 0.1, 'r.','MarkerFaceAlpha',.2,'MarkerEdgeAlpha',.2);
Corr1 = corrcoef(FrETemp, mVETemp);
title(sprintf('Corr = %.2f', Corr1(2,1)))
xlabel('FrE');ylabel('mVE')
subplot 232;
scatter(... |
b2ad01248ff83f474336e30fcd77082f055a6d1c0fcbeb210131f727ed8cb981 | MATLAB | 1,306 | 34 | function [FiltData, Filter] = lowpass_filter(Data, SampleRate, PassbandFrequency, ...
StopbandFrequency, DesignMethod, PassbandRipple, StopbandAttenuation)
arguments
Data
SampleRate (1, 1) {mustBePositive}
PassbandFrequency (1, 1) {mustBePositive}
StopbandFrequency (1, 1) {mustBePositive} = Passband... |
8becaaf00ea0168d742aa7245bc1a0ed6bd3880fda5f19d5680c6287446f54b2 | MATLAB | 1,308 | 39 | function auto_min_vent(app)
if ~isnan(app.settings.channel_idx.res_flow)
if isempty(find(contains(vertcat(app.data.name),'min. vent.')))
[data,ts,~, ~] = current_signal(app, app.settings.channel_idx.res_flow);
t= ts(1):ts(1):ts(2);
sig_p = data;
sig_p(sig_p<0) = 0;
sig_n = d... |
6a31d3245ea4d8daee165a117460522a5ed7759d74ff22d080db64d8b5e5e3ba | MATLAB | 1,309 | 54 | function update_signal_popup(app)
%UPATE_SIGNAL_POPUP updates the selection options for all popup menues
%for the selection of specific signals. to be called after calulation of
%derived signals
% Detailed explanation goes here
if ~isempty(app.data)
name = vertcat(app.data.name);
if length(app.data) < 2
... |
8df5a50203a65dc60c872fc65c2557ab1ad3720026a256f9d02ef7d2452987f5 | MATLAB | 1,309 | 62 |
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'filters.mat');
load(fpath,'filters')
sub = 1;
%%
randIdx = randperm(size(filters{sub},3));
fr1 = max(filters{sub}(:,:,randIdx(1:10)),[],3);
fr2 = max(filters{sub}(:,:,randIdx(11:20)),[],3);
fr_fil1 = apply_lowpass(p,fr1);
fr_fil2 = apply_lowpass(p,fr2);
%%
p =... |
bc7e7ff13643fd5eb885502c6ffa78cc5da57fb1295e6e4f017e42ec28822bd7 | MATLAB | 1,309 | 35 | function [absS_out,F_out,msT_out,nsamp_window_out,nsamp_frame_advance_out] = ...
my_specgram(y,msToffset,fs,ms_framespec,nfft,yes_preemph,yes_plot)
% function [[absS],[F],[msT],[nsamp_window],[nsamp_frame_advance]] = ...
% my_specgram(y,msToffset,fs,ms_framespec,nfft,yes_preemph,yes_plot)
if nargin < 2 || isem... |
54cfc3d907737e7e2bab86dc638b1573906e6527787983fae82818f1352bf581 | MATLAB | 1,310 | 48 | % Expand a multiple-scan NIFTI file into multiple single-scan NIFTI files
%
% Usage: expand_nii_scan(multi_scan_filename, [img_idx], [path_to_save])
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
%
function expand_nii_scan(filename, img_idx, newpath)
... |
e4982181fed711ad9d1adc8f0fcd4c6c580101865562d4570ea83410b9518144 | MATLAB | 1,310 | 54 | % 1-d example of leslie greengard's gaussian kernel-based nufft
% (type 2)
R = 4; % oversampling ratio
Msp = 12; % spreading parameter - the number of neighbors to spread
% to in each direction
M = 512; % dimension of uniform grid on which we evaluate nufft
tau = 1/M/M*pi/R/(R-0.5)*Msp;
Mr = R*M;
% precompu... |
e2c5699e4c50d73905f180ace5e69f9856a74e73ecd8abb654a520ccde295422 | MATLAB | 1,311 | 47 | function [currenttitle_SAVE] = photomplotTitle(ST,plotvarname)
if contains(ST,'Raw')
currenttitle.ST = 'Raw';
elseif contains(ST,'Recentered')
currenttitle.ST = 'Re-Centered';
elseif contains(ST,'DecayAdj')
if contains(ST,'Exp')
currenttitle.ST = 'Reference Adjusted (Exp Fit)';
elseif contains... |
51a8660e4a20dfe96e5d6f8cd64bac30e2da5225ec01c2b5db1c19a7fb08a636 | MATLAB | 1,312 | 48 | function mergeSelected(obj)
%MERGESELECTED Merge a pair of clusters
if obj.isWorking
jrclust.utils.qMsgBox('An operation is in progress.');
return;
end
if numel(obj.selected) < 2
return;
end
iCluster = min(obj.selected);
jCluster = max(obj.selected);
obj.isWork... |
f1321e4c0b5fad3baba5b9a4eef56b1b87ab8a8ec99aeeb7663d0b65e04d2091 | MATLAB | 1,313 | 39 | %This script calculates the percentiles of each cell in order to extract a
%baseline for behavioral data when running hte averageAllCellsFunction
%script.
function [baseline] = calculatePercentileBaselineFunct(data, threshold, raw)
% data = mouseData;
% threshold = 25; %what percentile should be used as the cuto... |
13f152c83699329bb809c8d793bfa5dc190b378318da69e72a4da3674c9f2ef1 | MATLAB | 1,315 | 78 | function [T2b T2csf Ab Acsf sujet] = find_T2_hipo(fi)
int_field = 'integral_real_fit_all';
int_field = 'integral_fid_abs';
int_field = 'integral_fid_cor_abs';
do_plot=1
for k = 1:(length(fi)/8)
tk=1;
for tt = ((k-1)*8+1):k*8
T2(tk,k) = getfield(fi(tt),int_field);
TE(tk,k) = fi(tt).TE./1000;
sujet{k}... |
7d02f5cb40521dfb154f80141f9397ae38820d8557e5e3aad737851e48bb501b | MATLAB | 1,315 | 43 | function [peaks, r] = peak_det_matched_filter_robust(ref, fs, h, fmax, varargin)
% peak_det_matched_filter_robust: R-peak detector based on a matched filter
%
% Syntax: [peaks, r] = peak_det_matched_filter_robust(ref, fs, h, fmax, itr)
%
% Inputs:
% ref: Vector of input data.
% fs: Sampling rate.
% h: ... |
f57c1734604ab9d729b1c37969f41fa1ef53f81bbcfdb1f1ae65e80ba3d9f935 | MATLAB | 1,315 | 45 | %% venn diagram
% create the relevant table
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
%%
total = [];
early = [];
late = [];
late_ir = [];
ear... |
c4a909b068d00ff82855daafbda4245d926192521434778881c48589e7e3770c | MATLAB | 1,316 | 39 | function my_colormap(cmap_spec,yes_reversed,thresh_gray,max_gray)
% function my_colormap([cmap_spec],[yes_reversed],[thresh_gray],[max_gray])
if nargin < 1 || isempty(cmap_spec), cmap_spec = 'default'; end
if nargin < 2 || isempty(yes_reversed), yes_reversed = 0; end
if nargin < 3 || isempty(thresh_gray), thresh_gray ... |
feef462f084b92b7369f40b09e97adfdd4907d03df05e24fc96c51af89df3f10 | MATLAB | 1,317 | 35 | % Funtion that read list of coordinates only from Nth row
% Text files UTF-8 w/BOM (Byte Order Mark).
% Input
% N: row where coordinates starts
% Output
% XY: coordintas x and y columns
function XY = readXYfromCSV(filename,startRow)
delimiter = ',';
% startRow = 2;
endRow = inf;
XY=[];
%% Format string for each li... |
8d868df020cf90b2d32dfbf8b021fa8cd9135470ba2db1acdbc5856b0abdcc53 | MATLAB | 1,318 | 39 | function restoreHistory(obj, entryIndex)
%RESTOREHISTORY Restore a position in hClust history
if entryIndex <= obj.hClust.nEdits
if isprop(obj.hCfg, 'testRun') && obj.hCfg.testRun
dlgAns = 'Yes';
else
qstring = 'This operation is irreversible. Continue?';
dlgA... |
390ce0ed9635626f64225ded1d77cc002b30d39d62df763db041b92c5ad635fa | MATLAB | 1,321 | 60 | % An implementation of Jacobi's algorithm for symmetric matrix
% diagonalization: The classical Jacobi algorithm.
% Ref: Golub, Gene H., and Charles F. Van Loan. Matrix computations.
% JHU Press, 1996, Sec 8.4
%
% Reza Sameni 3/1/2019
% email: reza.sameni@gmail.com
%
function testJacobiDiagonalization02
clc;
clear;
clo... |
40faec838f7309e6808e70b924bae831139ecdfd85f9e0bd3f268af30723e4ab | MATLAB | 1,322 | 47 | function ob = subsasgn(ob, sub, arg)
%function ob = subsasgn(ob, sub, arg)
% method for "ob.sub = arg" etc.
% caution: reassigning dimensions (.idim .odim .imask .omask) is dangerous!
if ~streq(sub(1).type, '.')
fail('only "ob.field = value" is supported')
end
% trick: for struct.sub = object
% e.g., A.arg.field = ... |
e52871b4a0a53b7ddf75e1569a8b79bf684ed6ba09b9c72dd62c88a8428bdaa0 | MATLAB | 1,324 | 50 | function []=mnl_CumulativePlot(varargin)
%mnl_CumulativePlot is designed to plot cumulative distribution plots of
%multiple groups to compare the differences in the spread of the data.
%Inputs
%The data needs to be arranged into different columns - the sorting is
%done automatically (This is Name1 and Name2)
cmap=col... |
1a6b4c672065542159e1c61be6f798f79abbc4d9bcd7dcaa160778b79573ca8b | MATLAB | 1,325 | 42 | function cost = van_rossum(st1,st2,tau,Fs)
%van_rossum - Get van rossum spike distance cost
%
% Usage:
% [cost] = van_rossum(st1,st2,tau,Fs)
%
% Description: This function takes two spike trains as an input,
% convolves them with an exponential kernel to obtain a continuous
% representation of th... |
2a37080a354d08debd6fca53170ae3178bd010987beb5953e515ccd29cb9b50f | MATLAB | 1,325 | 50 | function []=mnl_CumulativePlot3(varargin)
%mnl_CumulativePlot is designed to plot cumulative distribution plots of
%multiple groups to compare the differences in the spread of the data.
%Inputs
%The data needs to be arranged into different columns - the sorting is
%done automatically (This is Name1 and Name2)
cmap=co... |
b510de92d2b28fafac3e7ec4cfa625cac19902d17546c25439a41295c40b7774 | MATLAB | 1,327 | 49 | function [proj_a,proj_e,ve,d_primes] = project_tavs_onto_coding_dims(dims,av_trials,err_trials)
n_dims = size(dims,2);
% concat a and e trial averages to build coding space
t_avs_a = nanmean(av_trials,3);
t_avs_e = nanmean(err_trials,3);
y_ld = cat(2,t_avs_a,t_avs_e)';
y_ld = y_ld - me... |
80d60d788ecc8b35a5f543c6c7bd580a6101d7fb595f2e9f83d00fcd6d530822 | MATLAB | 1,328 | 60 | % Sample code for active noise cancellation from ECG signals
%
% Reza Sameni (C)
% Email: rsameni@shirazu.ac.ir
% Web: www.sameni.info
%
% Created May 2007
% Modified June 2018
clc;
clear;
close all;
load('SampleECG128Hz');
fs = 128;
ECG = y(:,2)';
N = length(ECG);
n = (0:N-1);
% Adding noise
rr = ... |
1638963208b3189557f4b6a55d100bd6f1ecc0cab750c854479ab43417e94e86 | MATLAB | 1,329 | 33 | clc;clear;
load 'gradient1-3 data'
load 'subject information'
nsubs = 1790;
network = importdata('von Economo index');
withinDispersion = zeros(1790,1533);
withinDispersion_mean = zeros(7,1790);
%%
%**********************************************step1 : Caculate Within Dispersion
for i = 1:nsubs
fo... |
406d841855336334ad5b135e5ae4fc449b8e6b2ecfcaac314f1ca130cea06113 | MATLAB | 1,330 | 38 | function [RTStruct, Means, Quantile99, Quantile01] = assemble_reaction_times(Trials, Participants, Sessions, SessionLabels)
% from a table of all trials, gets reaction times into struct needed for
% overlapping flame plot.
% Sessions can be either a structure, like Struct.BL = {'BaselinePre',
% 'BaselinePost'}; or just... |
c87b0903619d3e2055b0daf8b2a48ac97c030e3d5f6293cc00241f6de8633cb6 | MATLAB | 1,330 | 29 | function data = data_dsRateDivisible(data)
%Validate whether signal is divisible by downsampling rate, will be false
%if wavesurfer crashed during recording
%
% data = data_dsRateDivisible(data)
%
% Anya Krok, September 2022
%
thisLength = length(data.acq.time); % Length of signal that was acquired
... |
125280d381c6081e734b76778b291cdcb51275f9eca9c954af88243209f2b2db | MATLAB | 1,332 | 27 | % 测试文件夹中所有的CPL或者XPL图片
clc
clear
load E:\SemanticSegmentation_Scale\CPL\GTruth_Revolve_1433.mat;
load E:\SemanticSegmentation_Scale\Results\CPL_ResNet50_Class_No_Attention\trainedNet_resnet50.mat;
InputPicBG='E:\CPL_XPL_MULI\A\*.png';% 背景原图的存放位置里的tif文件
InputPicPath='E:\CPL_XPL_MULI\A\';% 背景原图的存放位置
SavePathName='E... |
49f7dce63d86798f6f964f41cbda372c0c2fbd9bc024b27dc2e70bbfb1e0340a | MATLAB | 1,332 | 38 | function eventMat = alignTrace2Event(trace,eventTimes,tBefore,tAfter,nSamp)
%alignTrace2Event - Align time series traces to event times
%
% Usage:
% eventMat = alignTrace2Event(trace,eventTimes,tBefore,tAfter,nSamp)
%
% Description: This function creates a matrix of time series data
% aligned to even... |
9147ecff627ffc41ec06841893fc6b1643edd4f764820e9bd9aaef2cd7931ac5 | MATLAB | 1,332 | 52 | function [ Vec,eigval ] = PLDA(Data,Labels,Alpha,nPLDA)
%Penalized LDA
% Detailed explanation goes here
%Input:
%Data = The data matrix each column represents one sample
%Labels= Labels corresponding the data matrix
%Alpha = The weight of PCA in (LDA+Alpha*PCA);
%nPLDA = Number of PLDA directions
%Output:
%PLDA:... |
fae6efd77470d257276c9d381ce59fcf3c781c8a777721f0b2d8aa2cf5960c83 | MATLAB | 1,332 | 33 | % Wrapper script to turn parcellation files into FreeSurfer annotation
% files. Then you can calculate surface area of parcellations!
%
% Assumes ind_parcellation output from Kong2019 CBIG pipeline.
% Written by M. Peterson, Nielsen Brain and Behavior Lab
%To run:
% 1. Claim computing resources using salloc (ex: `sa... |
46d0e2b2008bf8027ac46949c568362dd1e2c73d074ac6a9a243466fa8fd409b | MATLAB | 1,333 | 72 | function med = circ_median(alpha,dim)
%
% med = circ_median(alpha)
% Computes the median direction for circular data.
%
% Input:
% alpha sample of angles in radians
% [dim compute along this dimension, default is 1, must
% be either 1 or 2 for circ_median]
%
% Output:
% mu median directio... |
debd04112d7dc422c5f796d394080d66384618bc34da442e5ba6eae4bd72257a | MATLAB | 1,333 | 30 | function [samplesOut, keepMe] = filterSamples(obj, samplesIn, samplesPre, samplesPost)
%FILTERSAMPLES Denoise and filter raw samples, apply CAR
samplesIn = [samplesPre; samplesIn; samplesPost];
if obj.hCfg.fftThresh > 0
samplesIn = jrclust.filters.fftClean(samplesIn, obj.hCfg.fftThresh, obj.hCfg);
... |
449af2cdaf0e213b8b1a174652915da984da455e9737bedef3def7bfa9c0c8ef | MATLAB | 1,334 | 52 | function ss = outer_sum(xx,yy)
%|function ss = outer_sum(xx,yy)
%|
%| compute an "outer sum" x + y'
%| that is analogous to the "outer product" x * y'
%|
%| in
%| xx [nx 1]
%| yy [1 ny]
%| more generally: xx [(dim)] + yy [L,1] -> xx [(dim) LL]
%| out
%| ss [nx ny] ss(i,j) = xx(i) + yy(j)
%|
%| Copyright 2001, Jeff F... |
bdb13fec8979550adbe06c7e33fb2be34607c86761e145913825d596040cc13d | MATLAB | 1,335 | 48 | function output = XxRotate3D(inArray, angle, zx_aspratio, varargin)
%rotate3D rotate a 3D array by "angle" around the 1st dimension (y axis)
% angle: angle in degrees to be rotated; in terms of physical geometry
% zx_aspratio: ratio of z step size over x-y pixel size
% [Ny, Nx, Nz] = size(inArray);
% inArray = imr... |
1c4c78465eb917af7eb07f21c50923ba5fbaf312dcdf86af84383789787756b2 | MATLAB | 1,336 | 40 | function my_colormap(cmap_spec,yes_reversed,thresh_gray,max_gray)
% function my_colormap([cmap_spec],[yes_reversed],[thresh_gray],[max_gray])
if nargin < 1 || isempty(cmap_spec), cmap_spec = 'default'; end
if nargin < 2 || isempty(yes_reversed), yes_reversed = 0; end
if nargin < 3 || isempty(thresh_gray), thresh_gray ... |
64064c65689a7a6156a58301a44b6f917fbeaa14c596568c611498af6a17c28a | MATLAB | 1,336 | 37 | %number of cross validation iterations
function cross_validation_script(features,label)
T = 1000; %number of cross-validation iterations
%cluster
for j = 1:T
[accuracy, kappa, sensitivity, specificity, w, alpha, actual, predicted] = PLDA_knn_CV(features, label+2, 1, 3,'features', j); %run this on the
... |
7ef0f9d8bf54ac3bc2ffc15fe99e984279b2b929b887a55d9969bcba33f168e8 | MATLAB | 1,337 | 66 | function [vtx, vty, vtz] = dipolefangrid(rx,ry,rz,theta_t)
sizr = size(rx);
% GRIDS
% Get back R and unit vectors from passed grid
R = sqrt(rx.^2 + ry.^2 + rz.^2); %calculate |r| at each point
%getting normal vectors
erx = rx./R;
ery = ry./R;
erz = rz./R;
%Get theta and phi for each point in grid
theta = acos(rz./... |
7573ccaad7969292d81757a8bb54c0903c6318682ed5f7ae936ae6c5cc865441 | MATLAB | 1,339 | 43 | function outTable = flexibleTableRead(filename)
%% Notes
% this function is designed primarily for csv files produced by bonsai
% datatype is assumed to be numeric except for the last column which is
% assumed to be a timestmap
% filename = 'X:\ibn-vision\DATA\SUBJECTS\M23002\SDTraining\230313\TrialParams2023-03-13T... |
63f4b0c00431096ca44aef1aad4bdc248525fb326502d78a95d7795cde9dbd52 | MATLAB | 1,340 | 44 | classdef (Hidden) mat_file_h < handle
%
% Class:
% adi.mat_file_h
properties
m %Handle to the file.
end
methods
function obj = mat_file_h(file_path,varargin)
%
% obj = adi.mat_file_h(file_path,varargin)
%
% Optional I... |
ad32a409ac5ba4e6e1b58e5c4aa1fc1e6e18a6be0208443260bee379fe19bd4d | MATLAB | 1,342 | 42 |
% plots the distribution of confidence values for each eye and each
% participant so I can chose which eye to use for each recording. Ideally,
% each histogram should show mostly 1s, and some 0s. The more uniform the
% distrinution, the worst the eye quality. In a csv, save which eye had the
% best distribution.
cle... |
88bc2f16a23ae9a20d9d1445ddbefda1e6cd7939354d038933f570ef576799e3 | MATLAB | 1,343 | 51 | function MSPoI_analysis2(AG,Par,idxNE,idxEX,options,atlas,Nbr_Regim,respath)
atlas_name = options.atlas{atlas};
DiffAG_All = []; DiffAG_pos = []; DiffAG_neg = []; Total_sim = [];Dis = [];
for rg = 1:Nbr_Regim
All_P = Par.MSPoI.Par{rg};
for gI = 1:2%gr
... |
70017de800609ba184cbed64740bec395c7a9f4cee2cd315fcc2208b51fa565f | MATLAB | 1,344 | 55 | function ob = Gblock(ob, nblock, varargin)
%function ob = Gblock(ob, nblock, varargin)
%|
%| Create "block" fatrix (blocks of rows) for block-based methods like OSEM
%| option:
%| 'idiag' [idim] optional input diagonal scaling matrix
%| 'odiag' [odim] optional output diagonal scaling matrix
arg.idiag = [];
arg.odiag ... |
087b609647d2b0d7894685343d703f283d0f7beac8eaf07585369622143de55a | MATLAB | 1,345 | 51 | function Fourierfunction(CCresultDrinkOn)
%UNTITLED2 ±ÌÖÌTvð±±ÉLq
% Ú×à¾ð±±ÉLq
global fname tfile TotalTime ADon figWon MaxADon MaxZ MaxA1Rt_count render
bin=500;
% M=mean(CCresultDrinkOn);
if render == 1
figWon=figure;
subplot(2,1,1);
plot(linspace(1,2000,bin),CCresultD... |
3c243c12e314f4ccea72d840a66bbb9efc7528e71cbf9394e8270bd80b17a538 | MATLAB | 1,347 | 44 | function coeff = eq_vertex_diam_coeff(dim,N)
%EQ_VERTEX_DIAM_COEFF Coefficient of maximum vertex diameter of EQ partition
%
%Syntax
% coeff = eq_vertex_diam_coeff(dim,N);
%
%Description
% COEFF = EQ_VERTEX_DIAM_COEFF(dim,N) does the following:
% 1) uses the recursive zonal equal area sphere partitioning algorithm to
... |
7a44a89566944bf43ea698a9b4ceb12a7bb4e02acac115708fc629ed3dcb5707 | MATLAB | 1,347 | 41 | % Function to extract general features of the raster
% Input
% R: Matrix of the Raster of dims: Cell x Frames
% Output
% Descriptive Features:
% Descriptive.AN: Active Neurons
% Descriptive.eAC % of Active Cells
% Descriptive.DurAc Time of Activity (minutes)
% Descriptive.CAG ... |
9de4524e5ecf14f675156a20b36f2fd3dfcda9d5d5736221159e3f244890f16a | MATLAB | 1,348 | 33 | function spike_res_out = sel_spikes(spike_res_in, ts, burst_ints)
%SEL_SPIKES Summary of this function goes here
% Detailed explanation goes here
spike_res_in.use_spikes = [];
spike_res_out = spike_res_in;
ts_msna = ts(1) : ts(1) : ts(2);
spike_res_out.use_spikes(1:length(spike_res_in.spike_idx),1) = ones(size(spi... |
4fa3ba23f1d74b158831d82ba772de9388d26d0a33fe31202db8700d332870e5 | MATLAB | 1,349 | 43 | function power_without_bursts(DataBroadband, SampleRate, Bursts, CleanTimepoints)
arguments
DataBroadband
SampleRate
Bursts
CleanTimepoints = ones(size(DataBroadband));
end
DataBroadband(~CleanTimepoints) = nan;
% plot power spectrum of channel
[PowerBroadband, Frequencies] = cycy.utils.compute_power(DataBroadband, S... |
93b16464738ddd6f0a6e407d679a72b4f96c300969d3e2b82923cd564f1ff86a | MATLAB | 1,349 | 38 | function [mean_proj,dim_vars,dim_ves] = ...
analyze_dims_over_sessions_iti(p,av_trials_all,err_trials_all,trans_data_all,trans_data_err_all,dims,q,trial_idx_ses)
n_dims = size(dims,2);
% analyze summary dims over sessions
% - calc mean projections for a and e per session
% - quantify VE usi... |
bbfb47016366d82cc2f8b8409342c301028c165274ff4a2cfe2bb046a1a37c7f | MATLAB | 1,349 | 37 | function [Xroi, unROI, id] = roiBin(X,roi)
% Gets the mean of roi voxels as defined in unROI within the X matrix of
% brain data.
%
% Inputs------------------------------------------------------------------
% X: brain data, where rows are subjects and columns are features or
% voxels. Here, we assume the val... |
dba053c5625ce57bc5f2799c84bb5faf6b89d4e4b8333c1b563e378b481213db | MATLAB | 1,351 | 36 | function [test_indices, train_indices] = crossvalpartitionDBP(N, n_folds)
% crossvalpartitionDBP: Partition data into training and testing sets for cross-validation.
%
% INPUTS:
% - N: Total number of data points.
% - n_folds: Number of cross-validation folds.
%
% OUTPUTS:
% - test_indices: ... |
e336fd8dc19b799c63c6879ad97818c2beb179413f7fd44404e0b33adeb22190 | MATLAB | 1,351 | 52 | function mnl_PlotClustersFromMultipleClusters(efPxTrace,Cmap,FinalClusterIDs)
figure('Name','Clusters Per Section')
szT=length(efPxTrace);
ImNum=nan(szT,1);
for i=1:szT
ImNum(i)=efPxTrace(i).ImageNum;
end
nCol=max(ImNum);
for i=1:szT
subplot(1,nCol,ImNum(i))
Scale=efPxTrace(i).Scale;
TracePoints=efPxTra... |
d1c36d9bda90f826b2d49c0c8fd7395e05a55ca0baffdf209b7c3f08993e160b | MATLAB | 1,352 | 41 | function []=mnl_TracesChannelMIPs_TracesAndSomas(dim,efPxTrace,Somas,BkgMean,MaxValues)
%function that creates normalised MIPs for each channel based on the values
%from the trace extraction
% Inputs
% dim - dimensions of the original image [x y c z]
% data - the image matrix
% BkgMean - the background values to sub... |
d64132b0728352fbf47c788b82b1d77ab0f33ccff78ebd685b550672d9d8e31f | MATLAB | 1,353 | 48 | % rotate (and flip ICs)
% varargin: Mirind: true for flip, false for not flip
% Abanden the move for every field: just do one field at a time.
function [LDEequvUse] = HCRot_Rec(LDEequv,rotID,N_HCOutX,N_HCOutY,NPixX,NPixY, varargin)
if ~isempty(varargin)
Mirind = varargin{1};
else
Mirind = false;
end
if Mirind
... |
4c8d15a54e44531cba5ea1f2bd005eff25c6538e78a417c77226921d63d6030e | MATLAB | 1,355 | 48 | function [Data,Scale,dim,metadata]=mnl_Load4Dimage
%Function to load the image, and relevant OME metadata using bfopen
% Outputs
% Data - The image as a matrix (x*y*c*z)
% Scale - the size of a voxel (x*y*z)
% dim - the dimensions of the image
% metadata - the OME metadata
file=bfopen;
series1=file{1, 1};
metadata=fil... |
87aeff595ecf1183bd4038c83a62aed31c590c40cf6e777abd5503a631ef88df | MATLAB | 1,355 | 50 | function gscatter3b(x,y,z,group,clr,sym,siz,doleg,xnam,ynam,znam)
%GSCATTER3B 3D Scatter plot with grouping variable
% gscatter3(x,y,z,group,clr,sym,siz,doleg,xnam,ynam,znam)
% Designed to work in the exactly same fashion as statistics toolbox's
% gscatter. Differently from GSCATTER3, this function requires t... |
977fb494e8f53c76324803cc1b88a94793d042ed1481579dcac145da402fe81e | MATLAB | 1,355 | 39 | function targetcount(h,data)
%% Draw bar plot with number of structures targeted
% autocorrelatemap() and crosscorrelatemaps() depend on this function.
load('structures','groups');
subplot(h);
% Create plot with double y-axes
ax = plotyy(0,0,0,0);
hold(ax(1),'on');
hold(ax(2),'on');
gr = length(groups.name);... |
6b1efaec2a161b8eb6c8fa7e1d1c67fa0124053a76aeddb3fc5f67debd7bba1c | MATLAB | 1,357 | 36 | function Modo=SelectMode()
%% Initialize Figure
global Modo;
Modo='none';
fprintf('\n>>Select FinderSpiker mode:')
IntroFig=figure('DockCOntrols','off','MenuBar','none', 'NumberTitle',...
'off','ToolBar','none','Units','normalized','Position',...
[0.3 0.3 0.4 0.25],'Name','FinderSpiker.CalciumImaging','Visible'... |
7427be721c42848bfe80c62ed32575996be742f29cdba0a69c8e35d159a4eb7a | MATLAB | 1,358 | 35 | function R = rotation_matrix_3d(theta_x, theta_y, theta_z)
% rotation_matrix_3d - Generate a 3D rotation matrix.
%
% Syntax:
% R = rotation_matrix_3d(theta_x, theta_y, theta_z)
%
% Inputs:
% theta_x: Rotation angle around the x-axis or in y-z plane (in radians)
% theta_y: Rotation angle around the y-axis ... |
888e1b5e3a5a0a85c8f484a542caa15e466dba5a27eb28214a00e807a1cc6132 | MATLAB | 1,358 | 33 | function [ ripple_info, lfp_st, ripple_st ] = ripple_detection_single_dataset( data_st )
% Usage:
% [ ripple_info, lfp_st, ripple_st ] = ripple_detection_single_dataset( data_st )
% Input:
% data_st bipolar signals from hippocampus
%
% Output:
% ripple_info ripple timing of each channel stored in ... |
8adcdc4e3a5d75ad9df9ded3edc1ab4edb7e3e96b54eaec3c97e1f101eb3c32b | MATLAB | 1,358 | 41 | function splitCluster(obj, iCluster, unitPart)
%SPLITCLUSTER Split off a cluster given retained spikes
if obj.isWorking
jrclust.utils.qMsgBox('An operation is in progress.');
return;
end
if isempty(unitPart) || ~iscell(unitPart) || any(cellfun(@isempty, unitPart))
return;
... |
8d070683de86900c4645e9b9843ca23f80965afe25ce8fa8828c37d40000c46c | MATLAB | 1,359 | 63 | function R = rot3(axis, angle)
%ROT3 R^3 rotation about a coordinate axis
%
%Syntax
% R = rot3(axis, angle);
%
%Description
% R = ROT3(AXIS, ANGLE) sets R to be the 3 by 3 rotation matrix corresponding to
% AXIS and ANGLE. Use this to create rotation matrices from Euler angles.
%
% AXIS must be 1, 2, or 3.
% ANGLE must... |
71beae2e786179a437b39730093dc166e7ffc9bba6b329a0edc8cbe1c745a1c6 | MATLAB | 1,362 | 52 | function rotation = s2_offset(points_1)
%S2_OFFSET Experimental offset rotation of S^2
%
%Syntax
% rotation = s2_offset(points_1);
%
%Description
% ROTATION = S2_OFFSET(POINTS_1) sets ROTATION to be an R^3 rotation matrix which
% rotates the north pole of S^2 to a point specified by the points of POINTS_1.
%
% POINTS_1... |
8d46b113785ce0d5cf0ccf087ee04421924c18e93778eea8428fb0a81627ddf5 | MATLAB | 1,362 | 56 | function []=mnl_MakeMaxNormalisedMIPs(Data,n)
sz=size(Data);
NumChan=sz(3);
NumStacks=sz(4);
NumVx=sz(1)*sz(2)*NumStacks;
for i=1:NumChan
%Make a single z stack for the colour
tData=nan(sz(1),sz(2),sz(4));
for j=1:sz(4)
tData(:,:,j)=Data(:,:,i,j);
end
%Find the Nth percentile
Data2=resh... |
998b93eeb806cb8776357f13264c624ed881b776cb0ee42513c8a49dcb144276 | MATLAB | 1,363 | 38 | function [binary w] = threshold_pro(w, p)
% proportional thresholding
%
% This function "thresholds" the connectivity matrix by preserving a
% proportion p (0<p<1) of the strongest weights. All other weights, and
% all weights on the main diagonal (self-self connections) are set to 0.
%
%INPUTS: W = we... |
d520fd92f9495f8b6d9e632381d4a7c6d2e68ee5e28459c089469984b3e097a7 | MATLAB | 1,364 | 47 | function [avgc,maxc,nc] = macromap(map,nodes)
% Create a network based on connectivity between hyperstructures, e.g.
% isocortex, hypothalamus, etc. Projection values are either the mean
% (avgc) or max (maxc) of connections between two groups, or the number of
% connections (nc).
%
% [avgc,maxc,nc] = macromap(m... |
32027ec04d4a3f8fdc9594150e69e0efb036987700ced8d87b5b0b7b96d50c19 | MATLAB | 1,365 | 27 | cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\effect size\f2\n')
x = importdata("IE_cells.mat")
%%
x1 = x;
x1 = sortrows(x1,"main_structure")
x1.struct_number = grp2idx(x1.main_structure);
stats = mes1way(x1.response,'eta2','group',x1.struct_number)
%% post hoc
%% IL vs PL
stats = mes(x1.response... |
4357ae9be3e8c594633f9019609770f67798c21e64c219f8c5858dc06f50fa00 | MATLAB | 1,366 | 41 | function Plot_continuous_data(xf_detect, sr_sub,handles)
% Function that plot the segment of continuous data.
% It will try to plot a minute, maximun.
detect = handles.par.detection;
stdmin = handles.par.stdmin;
stdmax = handles.par.stdmax;
lx = length(xf_detect);
noise_std_detect = median(abs(xf_detect))/0.6745;
... |
b96d6af494de5865968090c881f7c80c351c38bbfb6c8e06622c6cdb49cad3f7 | MATLAB | 1,366 | 38 | function offset = circle_offset(n_top,n_bot,extra_twist)
%CIRCLE_OFFSET Try to maximize minimum distance of center points for S^2 collars
%
% Given n_top and n_bot, calculate an offset.
%
% The values n_top and n_bot represent the numbers of
% equally spaced points on two overlapping circles.
% The offset is given in ... |
268b2b4054f2847097798c426688f5a8626b5fa244e6fa7597e18a71f0a96d7d | MATLAB | 1,367 | 41 | function [spikeWindows, spikeTimes] = CARRealign(obj, spikeWindows, samplesIn, spikeTimes, neighbors)
%CARREALIGN Realign spike peaks after applying local CAR
if ~strcmpi(obj.hCfg.getOr('vcSpkRef', 'nmean'), 'nmean')
return;
end
% find where true peaks are not in the correct place after applyin... |
a4ba48c40a6c2b4dccfa7f1622c6866d090dc153566abdbb898abff107908d78 | MATLAB | 1,369 | 35 | function trialTimes = loadTrialFile(trialFile)
%LOADTRIALFILE Import trial times (in seconds)
trialTimes = [];
if ~exist(trialFile,'file')
warning('%s does not exist.',trialFile);
return
end
try
[~, ~, ext] = fileparts(trialFile);
if strcmpi(ext, '.mat') % use the fir... |
022ff9f3f84efc1e5024e5e41ab0f5aaefaa0eaa0ebecaec6c12db949ad78247 | MATLAB | 1,370 | 46 | function [ filters, traces ] = run_pca_ica( p,M )
%RUNPCAICA performs signal extraction using PCA and ICA
%% PCA
% perform mean subtraction for optimal PCA performance
inputMean = mean(M(:));
inputMean = cast(inputMean,class(M));
M = bsxfun(@minus,M,inputMean);
[height, width, num_frames... |
3fad2d5a75a25ce78c6e3cd64056122ca211e23c6ddc91496041c8edbdfa25a2 | MATLAB | 1,370 | 51 | function[x,nu,xp,yp] = rst_density_hist(data,units)
% simply function returning the density histogram
% function adapted from the computational statistics toolbox
% http://www.pi-sigma.info
%
% INPUT = data - vector of data to plot
% = 'units' - label for the x axis
% OUPUT x = values of each bin
% nu = ... |
e7346ea6bc31fb5dc4421b2c92c8098996ea300787ee39bc2ec2bf37501d4537 | MATLAB | 1,372 | 34 | function [data] = processCamera (data, params)
%Created By: Anya Krok
%Created On: 29 April 2021
%Description: T-Lab specific code for processing camera trigger
%signal into general T-Lab data structure
%
% [data] = processCamera (data, params)
%
% INPUT
% 'data' - T-Lab data file with data.acq.Fs and dat... |
03f951106e721ca5af1095d13081b9ee7c06d00c9d590b3c7482875d4eaa1ba1 | MATLAB | 1,373 | 52 | function Cxy = Find_CB_Center(Workspace1)
% Convert to BW and do opening & closing:
I1 = im2bw(Workspace1.Image0,Workspace1.Parameters(1).Cell_Body(1).BW_Threshold);
sec = strel('disk',ceil(Workspace1.Parameters(1).Cell_Body(1).Open_Close_Disk/Workspace1.User_Input.Scale_Factor));
% sec = strel('disk',5); % TODO:... |
350525b682c899dd609821aa0005c7747de41fc391a8ee3db68b35c1019ee984 | MATLAB | 1,373 | 41 | function [Subfolders, Datasets] = raw_data_paths(DataPath, TemplateFolder, isFullPath, IgnoreFolders)
% DataPath should indicate the folder where all the datasets are.
% TemplateFolder indicates the name of the folder that has the template
% folder structure.
% isFullPath is a boolean indicating whether to include the ... |
f31d2daba2aa60ad7a1fc0a39eff06edc7e4029887e9bec6cd3aedfbd9ac23db | MATLAB | 1,373 | 52 | function [b b0] = circ_skewness(alpha, w, dim)
% [b b0] = circ_skewness(alpha,w,dim)
% Calculates a measure of angular skewness.
%
% Input:
% alpha sample of angles
% [w weightings in case of binned angle data]
% [dim statistic computed along this dimension, 1]
%
% If dim argument i... |
9baa54ef58e162be3c541852513adcfcc83833e88a5264c04dabb19c1acc1e40 | MATLAB | 1,374 | 38 | function [blcorr, bltitre] = CREX_TF_baseline(activity, bline, choice)
% Function to carry out baseline correction method of choice on the
% time-frequency data for a single electrode.
% activity => post-stimulus time-frequency matrix (frequencyXtime). This
% could be the mean over all trials or a single trial.
% bline... |
94e09af3c1134679ebace081cada39c846099cf4414d97e678af1816df49c0eb | MATLAB | 1,375 | 31 | function [snr_median, snr_mean, mean_beat, median_beat, stacked_beats, noise_mean, noise_median] = events_snr(data, peak_indexes, beat_length, running_avg_len)
stacked_beats = event_stacker(data, peak_indexes, beat_length);
if nargin <= 3
[mean_beat, ~, median_beat, ~] = robust_weighted_average(stacked_beats);
... |
82ba94959d0a0ede11a6c6218c4672896f60365e45aedb538f9f7232ebe98b3b | MATLAB | 1,378 | 56 | function [sm_data] = gaussian_smooth_1d(data,sig,windur)
%1d gaussian smoothing function
%inputs:
% data: vector to be smoothed
% sig: sigma of gaussian kernel
% windur: number of sigma to extend kernel in either direction
%outputs:
% sm_data: smoothed data
if nargin > 2
kern_length = windur;
... |
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