sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
bb281d565b69634e56b3002dd2f1dcb678af5f9283f027daacdb5895bc0f751d | MATLAB | 1,186 | 46 | function [x,error]=SolveMA57m(A,b)
%% Calls solver function that uses MA57 subroutines
% from Central Laboratory
% of the Research Councils
% ALL USE IS SUBJECT TO LICENCE. For full details of a UK ACADEMIC
% Licence, see http://hsl.rl.ac.uk/acuk/cou.html
% Uses matrices in sparse component format: ... |
f0ce73f071699db2ca45da696b5861e7c3a9fa098e054da118151112d41f7547 | MATLAB | 1,187 | 45 | function plot_potential_along_fascicle(model, iFasc, iAS)
%PLOT_ACTIVATING_FUNCTION Summary of this function goes here
% Detailed explanation goes here
[~, ~, ~, fascIdsByAs, activeSites, ~, ~, cross_pl] = import_nerve(model, 'hide_plots');
assert(fascIdsByAs(iAS, iFasc), 'This fascicle is not reached by this... |
bebbaf837ded83c0d8dfb146c8635f72e0d7386197cfc0cfde74f232e248ad2b | MATLAB | 1,188 | 39 | function self = TrainNetwork(self)
isTrn = self.ClipTable.Set == categorical({'Train'});
trnSeqT = SplitClipDataIntoSequences(self, self.ClipTable(isTrn, :));
trainFeats = TransposeCellArrayElements(trnSeqT.Features);
trnLabels = DeepActionProject.GetLabelsFromTable(trnSeqT);
trainLabels = TransposeCellArrayElements... |
ee4e19f14e7999e193da4404a656845ec019d9612a53e712286b5c5e73be8ec7 | MATLAB | 1,188 | 54 | function calculatePitch
%
% This function selects the hold time from a range of possible times
%
% Required gf parameters:
% pitchMin
% pitchMax
% pitchSteps
% pInd
%
% Parameters generated:
% pitch
global gf
if gf.pitchMin ~= gf.pitchMax,
% Linerarly spaced array of times from min to max (dB)
gf... |
0a516a3f45ff070862055ec90350b2e5f20fd4c33f37eca36522a43cb6bb05da | MATLAB | 1,189 | 38 | function design = designMatrix_discriminant(cfg0, group)
% [design] = designMatrix_dummy(cfg, G)
% Returns a design matrix using discriminant coding for two groups.
%
% G Array of length N, where N is the number of trials, that contains the group each trial
% belongs to, as identified by ... |
50a867728bb67b9319edce931dc37bc171bb01439952a5c552f3f5c61226855f | MATLAB | 1,189 | 37 | function c = ss_censored( spikes, use )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% ss_censored - wrapper for censored.m
%
% Usage:
% c = ss_censored( spikes, use )
%
% Description:
% Estimates the percent of a cluster that is lost due to censoring.
% See censored.m for mor... |
6467f7261703c259befd13cc8603bd6f21cba765f10b329c5ad9aac3ff6e9d42 | MATLAB | 1,189 | 39 | %% Get spike and stimulus onset vectors for use with NeuroExplorer
% from block currently selected in DB_Browser
ids = getpref('DB_BROWSER_SELECTION');
units = mym(['SELECT u.id,c.target,CONCAT(c.target,c.channel,p.class,u.id) AS name ', ...
'FROM units u ', ...
'INNER JOIN channels... |
88d806754ebab14f7ed9648b65fc528c3736474604f751c0ccbac3c353a55ea5 | MATLAB | 1,190 | 24 | function [ROIs] = chord_ROIs()
%CHORD_ROIS ROIs used for the chord diagrams
ROIs.beta = {'PFC', 'OFC', 'ACC_area24', 'agranularIns_bin', ...
'dAIC_custom_bin_agranTrim', 'Idys','Idfm_custom_bin', 'S2', 'S1',...
'thalamus_ohne_genicula', 'hypothalamus', 'amygdala', 'putamen', ...
'PAG', 'PBC'};
ROIs.regionIn... |
6362deba06ae434eedcc440c2f0ebd9d7392fbba1836ab400a5d9792c9577046 | MATLAB | 1,193 | 47 | function plot_potential_cross(model, iAS, plotArgs)
arguments
model Model
iAS (1,1)
plotArgs.?CrossPlotProps;
plotArgs.LabelAS = true;
plotArgs.clabel = 'Normalized Potential';
plotArgs.z = NaN;
end
[epi, endo, elec, fascIdsByAs, activeSites] = ...
import_nerve(model, 'hide... |
19e8abb6aa6c7c13f85efdbebd879827ef36a33845c3c652dfd64e29a7c5c5e6 | MATLAB | 1,194 | 49 | clc; clear; close all;
Fig8d=figure();
Ntrials=20000; %number of learning cycles
xax=1:1:Ntrials;
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
Results1=zeros(N_mu,Ntrials); % total number of spikes
Results2=zeros(N_mu,Ntrials); % ns1+ns2 ns1: pattern 1 ns2: ... |
523050b88a69728438a77622edc6c3459fc5d03977bd547376b11c31b7d471c2 | MATLAB | 1,194 | 51 | function motif_class = network_motif_classification_3D(x1, x2, y1, y2, t1, t2)
vec1 = [x1,y1];
vec2 = [x2,y2];
vec0 = [0,0];
list_vec = [x1, x2, y1, y2, t1, t2];
if t1 < t2
x1_new = x1;
x2_new = x2;
y1_new = y1;
y2_new = y2;
t1_new = t1;
... |
7194a8a500ae429de61e04cd1ee1600a45fcee8afe2ac41fe511abd9f1318392 | MATLAB | 1,196 | 38 | function fnames = export_active_sites(model)
[~, activeSites] = load_active_sites(model.paths);
FEM = [];
log = model.getLogger('electrode');
fnames = cell(1, numel(activeSites));
for iAS = 1:numel(activeSites)
fnames{iAS} = fullfile(model.paths.elec, sprintf('AS%d.stl', iAS));
if isfile(fnames{iAS})
... |
9b5d252d514d1ee7b60c4a4b57c3d267c61dfb10e4889124f7299d240b8b8b9c | MATLAB | 1,198 | 54 | %% 2 Rotate all images into proper plane
% Does not do any fine adjustments to individual brains
%
% DJS 11/28/2016
rootPath = 'D:\DataProcessing\';
cd(rootPath);
addpath H:\DataProcessing\PREPROC
P = getFiles;
% P = P(cellfun(@isempty,strfind(P,'VOI'))); % hide directory
%%
% approximate transformations determi... |
9cb6e2753acf6ba01832a4d78d06e2aa302f1dcb103ad515be899f0a8db87ec3 | MATLAB | 1,198 | 53 | %% Response Latency
RCode = NHP_decodeResponseCode([Data.ResponseCode]);
Angle = [Data.Behavior_Speaker_Angle];
uAngle = unique(Angle);
rl = cell(size(uAngle));
for i = 1:length(uAngle)
ind = uAngle(i) == Angle;
ind = ind & ~(RCode.Abort | RCode.NoResponse);
rl{i} = [Data(ind).Behavior_RespLat... |
cbfb3063501e6c1b78d2226682db2aec0d79b220ee2769e54a8fa43b5d7f1428 | MATLAB | 1,198 | 26 | % GUI Layout Toolbox
% Version 2.3.9 (R2024a) 05-Jul-2024
%
% Panels
% uix.Panel - arrange a single element inside a standard panel
% uix.CardPanel - show one element from a list
% uix.BoxPanel - arrange a single element inside a panel with a boxed title
% uix.TabPanel - arrange... |
1c7e39eefc39e4bfd415a2b7180ddc8a31ef9a084003a207f1462dcfc7bab110 | MATLAB | 1,199 | 68 | function [CN,R] = f_CN_corr_aprox(CIJ,nterms)
% Approximation of CN using Barnett et al.
% FC is computed using Galan's linear model
% References
% L. Barnett, C. L. Buckley and S. Bullock (2009) %
% R. F. Galan, plos one (2008)
if nargin < 2
nterms = 5;
end
N = size(CIJ,1... |
b61e1a22a4d6082e428e516b6ce0e1866d33a6b4363f748175d23b63ebcc22f8 | MATLAB | 1,200 | 37 | % PURPOSE: pins figures to the light theme.
%
% FORMAT:
%
% erplab_lighttheme(fig)
%
% INPUT
%
% fig - figure handle, or array of figure handles
%
%
% ERPLAB's windows are laid out for a light background and many of their
% colours are set explicitly, so a dark desktop leaves dark text on dark
% panels in some pl... |
f9be377d2a352fca5f1e6fa87db8a916eb07c39bd27e9a17cee646e2fd2083cd | MATLAB | 1,201 | 42 |
function BetaWeights_bin = f_decoding_betaweights(mdl,nDecoders,method,nBins)
% ddd=0;
% for iiii = 1:nDecoders
% for j = iiii+1:nDecoders
% ddd = ddd+1;
% BetaWeights_bin(ddd,:) = mdl.Coeffs(iiii,j).Linear;
% end
% end
if method==1%% SVM%%GH August 2025
if nBins > 2
... |
15fa1b8a82f5627d61d12b8913c1ffaaae7bd2ff5f843177c08c2c6b311206ee | MATLAB | 1,202 | 48 | function [scaled_expectation,expectation, p] = theoretical_expectation_2D(raster, neuron_window, time_window)
motif_order = [
1
2
3
2
3
2
3
3
3
3
3
3
3
... |
053bdad6041f3e927eb65a91fb7bf0bae804190495217688c59523adf0da2367 | MATLAB | 1,203 | 35 | % part of https://github.com/LudgerS/MRSartifactRemoval
%
% modified from A. Weideman's code
% http://appliedmaths.sun.ac.za/~weideman/research/cef.html
% which is based on J.A.C. Weideman, "Computation of the Complex Error
% Function", SIAM J. Numer. Anal., Vol. 31, pp. 1497-1518 (1994)
%
% computes w(z) = exp(-z^2... |
1f56dd841cac40fdae5bc09f3e174c124323d06c1674b884743d3665cdd9385a | MATLAB | 1,204 | 32 | function PhotodiodeMarker(win,seton)
% PhotodiodeMarker(win,seton)
%
% Simple helper function that sets up bottom-right corner of window (win)
% to activate a photodiode. This function should be the last command
% called just before 'flipping' so it is on top.
%
% If seton is true, then the bottom-right corner... |
ec12f0a85155b3ddaad94ecfefc2fac16ad3a43b89076e608f7859eb12d749bd | MATLAB | 1,205 | 37 | function out=TPPreviewImageFunctionListGetCache(filename)
% TPPREVIEWIMAGEFUNCTIONLISTGETCACHE - Get preview image parameters to the cache
%
% OUT=TPPREVIEWIMAGEFUNCTIONLISTGETCACHE(FILENAME)
%
% Gets the TPPreviewImageFunctionList data from the TPPreviewImageCache global variable for the
% filename FILENAME. If tha... |
9146ad502b4cc53c1e86a32e99792eca5e2f1e0e33228150310b1a802d281de9 | MATLAB | 1,206 | 38 | function Xhat = decode_LDA(cfg0, decoder, Y)
% [Xhat] = decode_LDA(cfg, decoder, Y)
% Decodes data using a linear discriminant analysis decoder as obtained from
% an appropriate training function, e.g. train_LDA.
%
% decoder The decoder as obtained from an appropriate training function.
%
% Y ... |
7eb5f1307a745296ad8d045226b88bc6268b67667191e1896a33b84f38aa087d | MATLAB | 1,209 | 33 | % Package GMLM_dmc for dimensionality reduction of neural data.
%
% References
% Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
% decisions in parietal cortex reflects long-term training history.
% bioRxiv
%
% Copyright (c) 2021 Kenneth Latimer
%
% This software is distributed unde... |
ee3d4bb420a5e8207c4ed8f62cc83a23b67131337e5be9b634082c78d75644a8 | MATLAB | 1,211 | 47 | function r = DB_AddResearcher(conn)
myms(['CREATE TABLE IF NOT EXISTS db_util.researchers (' ...
'initials VARCHAR(3) NOT NULL, ', ...
'researcher VARCHAR(45) NOT NULL, ', ...
'email VARCHAR(45) NULL, ', ...
'UNIQUE INDEX initials_UNIQUE (initials ASC), ', ...
'PRIMARY KEY (re... |
78e431eb2f27166631c471c1a63ac96fc9744649a7f15b531d59a3eb8abba3dd | MATLAB | 1,212 | 33 | function [newtimes,frame2dirnum] = tpcorrecttptimes(params, dirname)
% TPCORRECTTPTIMES - Corrects time for twophoton files
% (This is the Generic version, so it just returns the 2P parameter times)
%
% [FRAMETIMES,FRAME2DIRNUM] = ...
% TPCORRECTTPTIMES({PARAMSTRUCT}, DIRNAME)
%
% PARAMSTRUCT should be a cel... |
9e58b2e8ccad742ed8813512f2989f4efa597c588cd03034de3505a6aaf5b606 | MATLAB | 1,212 | 35 | % defualt params and upper/lower bounds for the Liley model
param.he_rest = -70;
param.hi_rest = -70;
param.Nee_beta = 4000;
param.Nei_beta = 3034;
param.Nie_beta = 536;
param.Nii_beta = 536;
param.Gamma_e = 0.4;
param.Gamma_i = 0.8;
param.gamma_e = 0.3;
param.gamma_i = 0.065;
param.Tau_e = 10;
param.Tau_i... |
a3e6a70a276398272601bc55212893acfe02a1c6163776b7a81f11422dbcc5a4 | MATLAB | 1,212 | 39 | function self = GenerateClipPredictions(self)
% Generate predicted labels for each clip
if self.VerboseLevel > 0
fprintf('Generating clip predictions... ')
end
mbSize = self.ConfigFile.GetParams('PredictionMiniBatchSize');
seqT = SplitClipDataIntoSequences(self, self.ClipTable);
features = TransposeCellArrayElem... |
c5a5f60feff3ef12725962cadde9a2513df21d25b6eb2f6d73f7f18e9fdf2caa | MATLAB | 1,212 | 42 | function [N_points,v,N_faces,f,c,c2,Tpsi,DTpsi]=readelmer(name)
fileID = fopen(name,'r');
%Read number of points
format='%s %f %s';
data = textscan(fileID,format,1,'HeaderLines',4,'Delimiter',' ','CollectOutput',1);
N_points=data{1,2};
%save points
format=' %f %f %f';
data= textscan(fileID,format,N_points,'... |
0be568d4aed74109aecfb75d421ba61bf81331183000f0cb5d6404faf4089e7e | MATLAB | 1,213 | 37 | %%
clear all
close all
run(['..' filesep 'def_local'])
addpath(path_fieldtrip)
ft_defaults
%%
load wsws_badComps_train
allfiles = {'405','406','407','408','409','410','411','412','413','414',...
'415','416','417','418','419','420','421','422','423'};
for n=1:length(allfiles)
%%% load training data & compo... |
dba83e5c3d1ca949ff23d9fc420b3440ae2fd3ba8fa257bcc2b9134785b607b3 | MATLAB | 1,213 | 52 | % Weighted clustering coefficient
% Source: Barrat, The architecture of complex weighted networks
% INPUTS: weighted adjacency matrix
% OUTPUTs: vector of node weighted clustering coefficients
% Other routines used: degrees.m, kneighbors.m
function wC=weighted_clust_coeff(adj)
deg=sum(adj);
n=size(adj,1); % number o... |
8e4ac102ddfcc442c91cfd4b7d193eb33d75130c49272ea1bc8ddc1e91ce1ecb | MATLAB | 1,218 | 36 | function t = bids_tsv_nan2na(t)
%
% function t = bids_tsv_nan2na(t)
%
% function replaces NaN in a table with n/a
%
% Tables entried may have NaN for missing values, but should be written as
% a n/a in the bids .tsv file. Therefore, this function replaces all NaNs
% in a table with n/a.
%
%
% Dora Hermes, 2017
% get ... |
763a2acac11d4d0d12ac6c2595abafbce7e00c3b08107f16a8f5d6a87e70c458 | MATLAB | 1,220 | 74 | clear
close all
clc
tic
%% Parameters definition
alpha = 1; %1;
sigma = 1;
dt = 0.2;
W = load('W.dat');
N = sqrt(size(W,1));
%% Numerical integration of the dynamical equations
T = 20000; % number of time points
x = zeros(N^2,T);
x(:,1) = randn(N^2,1)*dt;
noise = randn(N^2,T);
fo... |
8572dcf2884b061d3d5781daec12655c92d7a52072802e23fe520d0e39ef696d | MATLAB | 1,220 | 39 | function [class_contribution,class_count,contribution]= triple_correlation_class_contributions_2D_periodic(arr, neuron_window, time_window)
class_contribution = zeros(1,14);
class_count = zeros(1,14);
max_time_lag = ceil((time_window / 2));
[N_neurons, N_times] = size(arr);
for n1 = -floor((ne... |
97734999668ffb40df78a151a9e2a57b63b67769095350b7597e0c98a2dd6a0c | MATLAB | 1,220 | 35 | % Find handle graphics object with user data check.
% Retrieves those handle graphics objects (HGOs) that have the specified
% Tag property and whose UserData property satisfies the given predicate.
%
% Input arguments:
% fcn:
% a predicate (a function that returns a logical value) to test against
% the HG... |
28fbf0a02af8e40bb54fae515e5c7d27d3df1a9108706ea0009cd77a5aa7a28c | MATLAB | 1,221 | 41 | function [ IDs ] = ReadIDsFromFile( filename, endpoint )
%READLOCATIONSFROMFILE Read locations from a tab-delimited text file
IDs = [];
if ~exist(filename, 'file')
disp(['Input file does not exist: ' filename]);
return;
end
fileID = fopen(filename);
%Figure out the directory th... |
b2fb3e7dd91817bce0cb2b2615a4a32baea6efbc855ac148a6425e684e78844b | MATLAB | 1,225 | 22 | function cr = emptycellrec
% ANALYZETPSTACK_EMPTYCELLREC - Return an empty cell record
%
% Returns a structure with the following fields (each empty, ready for filling):
%
% DIRNAME : The dirname where the cell was first identified
% pixelinds : The pixelinds of the cell within... |
dfe64296b1082518f49c376c2bc4c92744fe75d75b62004c454c1be46a9bf45d | MATLAB | 1,227 | 53 | function BEST = combineBESTbins(BEST,new_bins,new_labels)
n_bins = length(new_bins);
BEST.nbin = n_bins;
BEST.bindesc = new_labels;
BEST.original_bin = {}; %erase due to new BEST being combined
new_binwise_data = struct();
n_trials_per_bin = NaN(1,numel(new_bins));
%% combine bins
for b = 1:n_bins
se... |
fb82aed140c6a44056de3448abf76be1924e3ded749cc68507f2e2605ba70987 | MATLAB | 1,228 | 38 | % Downsample signal by given factor by taking average of factor # of
% neighboring samples
%
% Last update: October 24, 2018 (SL)
function signals_downsampled = downsample_by_average(signals, downsample_factor)
n_signals = size(signals,1); % Number of signals fed in argument
n_samples = size(signals,2); ... |
e5fc3954674d7fd194ff3a614f4a9a9300798b66583f1e57e8a182f57dd0677c | MATLAB | 1,229 | 46 | function varargout = TDT_BlockSelect(tank,varargin)
% varargout = TDT_BlockSelect(tank,varargin)
%
% Optional Input Parameters:
% 'SelectionMode' ... 'multiple' or 'single' (default)
% 'Name' ... dialog title
% 'OKString'
% 'CancelString'
% 'TankList' ... option... |
7721929df2f5723d78459998ccd63667585a992417ded94dbb4346ce2538ef9a | MATLAB | 1,231 | 41 | function SaturMap = Saturation(X,gray)
% Determines saturated pixels as those having a peak value (must be over
% 250) and a neighboring pixel of equal value
% X grayscale or color image with pixels in range 0-255
% SaturMap binary matrix, 0 - saturated pixels
% gray in case of 'gray' saturated pixels in... |
004f48711c0bb3f26dcef110b7eef5297002c9adb1ed3f453a14e9bc3ea13b9f | MATLAB | 1,233 | 46 | function [p alpha] = circ_vmpdf(alpha, thetahat, kappa)
% [p alpha] = circ_vmpdf(alpha, w, p)
% Computes the circular von Mises pdf with preferred direction thetahat
% and concentration kappa at each of the angles in alpha
%
% The vmpdf is given by f(phi) =
% (1/(2pi*I0(kappa))*exp(kappa*cos(phi-thetahat)
%
%... |
54de89708e7c2bf60b43a4c3bc05c4b18b2ace564b29376e18bff79e348382c9 | MATLAB | 1,238 | 45 | function [ VOrigin, VOne, VTwo ] = FindIntersectingEdges( TriDistToPlane, Epsilon )
%Figure out if we have two points above or below the plane
Above = TriDistToPlane - Epsilon > 0;
Below = TriDistToPlane + Epsilon < 0;
Zero = abs(TriDistToPlane) <= Epsilon;
if(sum(Above) > 1)
VOrigin = find(... |
3b5ab5afbf10c0536298c835d3581766eb2beee97f6b82257b746ee2df572340 | MATLAB | 1,241 | 38 | function [dr] = driftcorrectls(orig_imag, linescanpoints, linescandata, searchX, searchY, brightnesscorrect);
% driftcorrect -- the correction of the original image
% driftcorrect_ls -- the correction of the line scans
usemse = 1;
imsize = size(orig_imag);
imscan = NaN(length(searchX)*length(searchY)... |
69c71aee9c23427b25924b3ff4f9a852278ac74a64027e217f462cf44d1ae5ac | MATLAB | 1,242 | 49 | function SetTwoPhotonConfiguration(platform, synchronization)
% SETTWOPHOTONCONFIGURATION - Sets configuration for TWOPHOTON analysis
%
% SETTWOPHOTONCONFIGURATION(PLATFORM, SYNCHRONIZATION)
%
% Sets the 2-photon configuration, so the system knows what
% microscope and synchronization method the user is using.
%
% ... |
55068dccf9e178294ee310f562562678965971a5c04baee216c7891ea83ed281 | MATLAB | 1,245 | 41 | function fnames = load_stl(model, object)
arguments
model (1,1) Model
object (1,:) char
end
switch object
case 'epi'
fnames = load_or_export(model, model.paths.epi, 'epineurium', false);
case 'endo'
fnames = load_or_export(model, model.paths.endo, 'endoneurium', true);
case... |
41df94b4f9a7eb12cb8ee13e20d32998950957a46f09919bb70d4388ef9d874d | MATLAB | 1,246 | 47 | function [delays,valAtDelay, valAt0] = plotCrossCorrelogram(xc,lags)
nMice = numel(xc);
% get the average across mice--interpolate in case not all the same time
% bins?
% take the first one as reference
delays = nan(1,nMice);
valAtDelay = nan(1,nMice);
valAt0 = nan(1,nMice);
lagsRef = ... |
4dab6f6fdb12abf954d47813a6c5a6318666063cd3c75298e67b2712499740a0 | MATLAB | 1,247 | 54 | function out = analyzetpstack_drift_devs_menu(command, uihandle, inputs)
out = [];
switch lower(command),
case 'init',
dd = analyzetpstack_drift_devices('Get');
ad = analyzetpstack_active_drift_devices('Get');
ud = {[] [] []};
str = {'Drift Correction','Update this list','-----'};
ud{end+1} = [];
str... |
249b706095b9b7971abebe6b46653ae812cae5cc5c73ac336fee72b7ddf8415d | MATLAB | 1,248 | 46 | %% Modify Atlas to place space between ROIs to avoid partial volume effects
scaleFactor = 2;
Patlas = 'D:\ownCloud\PROJECTS\MRI\TPM_Catlas_Slicer4\CombinedAreas.nii';
Vatlas = spm_vol(Patlas);
Yatlas = uint8(spm_read_vols(Vatlas));
fprintf('Upsampling volume...')
[Xq,Yq,Zq] = meshgrid(1:1/scaleFactor:size(Yatlas,1),... |
4c0f9b2dd0e248b4acf7374be75fedba92f99016957af8eff682130a45a5f3d1 | MATLAB | 1,248 | 51 | function [delayEmbeddedData, embeddedTime] = delayEmbed(data, numDelays, deltaT, useDerivatives, dontFlip)
if ~exist('useDerivatives') || isempty(useDerivatives)
useDerivatives = 1;
end
if ~exist('dontFlip') || isempty(dontFlip)
dontFlip = 0;
end
if numDelays == 0 || deltaT... |
cd4570c527f964048ceaf7d1af60ab8ea08e4358c99a59f16fe6b5b2929f76fc | MATLAB | 1,248 | 52 | function func_SaveModels(Parm)
% Save model files to folder: DeepInsight3D_pkg/Models/...
model = load('model.mat')
netName = Parm.NetName;
cd DeepResults
net = load(model.fileName);
cd ../
FileRun = Parm.FileRun;
Stages = Parm.Stage;
Ask = Parm.SaveModels;
if strcmp(Parm.PATH{1}(end),'/')==0
Parm.PATH{1} = [... |
12f58453b665a5cf15a1b1e37c9746aebbe560601031f20390d0403ed0d176f7 | MATLAB | 1,249 | 47 | function embed = doDiffusionMap(W,n_template,n_components)
fprintf('- diffusion map embedding\n')
alpha = 0.5;
diffusion_time = 1;
n = size(W,1);
fprintf('- normalize\n')
d_alpha = spdiags(sum(W,2).^-alpha, 0, speye(n));
L_alpha = d_alpha * W * d_alpha;
fprintf('- laplacian\n')
d_alpha = spdiags(sum(L_... |
296f1b861096b756a6293c865f0d9f4b38a039edf61a2084d160b7c953550cd2 | MATLAB | 1,249 | 27 | function [Subject_Details_subset]=Select_cohort_subset(Subject_Details,AnalParams)
% From a full cohort of data, selects a subset of data with the same number of datasets per age bin
%
% INPUTS:
% - Subject_Details: structure of demographic information for the analysis cohort
% - AnalParams: structure con... |
8ddfa615f6546c1d9813b6bd6e3b803c62610d6776039142045c465ada3e3b1f | MATLAB | 1,249 | 38 | function data = ecog_notch(data,srate,notch_freq)
% data = ecog_notch(data,srate)
% notch filter data around 60Hz, 120Hz and 180Hz
% data is time X electrodes
%
% DH 2018
if notch_freq==60
% 5th order butterworth notch filter, [low/(samplerate/2) high/(samplerate/2)]
[n1_b, n1_a]=butter(5,2*[59 61]/srate,'st... |
ac460d27cb0b3f17a78766b81fd5562d19e764413c750c81413e269108813268 | MATLAB | 1,252 | 42 | function [ scale ] = FetchScale(Server, Port, Database)
%FetchData - Collect scale from a database. Returns struct
% with XScale, XUnits, ..., ZUnits fields
javaaddpath('.\sqljdbc4.jar');
ConnString = ['jdbc:sqlserver://' Server ':' num2str(Port) ';database=' Database];
disp(['Connection string: ' C... |
4833303fd14a277eb442fe2d2524099761acbb1a58b1f2c37571216be1e9dcc6 | MATLAB | 1,253 | 31 | function [pe_results] = create_peInput(input_data, timestamps, input_window, framerate)
% Reformats input_data data to make compatible with pe_Plot class (object) handle
% Splits up full traces into peri-event sweeps. Each sweep contains the
% flourescence values within the given time-window (-window through +windo... |
6550522fdffeb9e8f69bd055ff22ef50ff47b5c2b147e7bbeff0aedb4ecdf657 | MATLAB | 1,253 | 54 | function celllist = analyzetpstack_draw_devs_menu(command, uihandle, inputs)
celllist = [];
switch lower(command),
case 'init',
dd = analyzetpstack_draw_devices('Get');
ad = analyzetpstack_active_draw_devices('Get');
ud = {[] [] []};
str = {'Autodraw/import cells','Update this list','-----'};
ud{end+1}... |
f7f67972d25001c987bd3a56a2250b9af261b4aadb947059954637cd68f7be8e | MATLAB | 1,254 | 41 | function [ algs ] = solver_list(category)
% Return list of solvers.
%
% Inputs:
% category category to be returned.
% Output:
% algs list of solvers in the category
%
% This file is part of SparseGDLibrary.
%
% Created by H.Kasai on Apr. 25, 2017
% supported algorithms by SparseGDLibrary
... |
d3b7ee36f2b13fb3f75a4c87acec7181acf9490ed708b5d73d13e5fc65467e99 | MATLAB | 1,255 | 42 | function tpexper2text(expername)
% TPEXPER2TEXT - Convert raw output of 2-photon experiment to text
%
% TPEXPER2TEXT(EXPERNAME)
%
% Convert all analzed raw data to text format, where EXPERNAME is the
% name of the experiment directory to be converted.
%
% The data must first have been analyzed with analyzetpstack... |
489890f4fd1ef47f1cc85dd83d29879a2a69ae733149d1f4d9c8c22822bf47fb | MATLAB | 1,256 | 51 | %% 4A Clean up mask
P = spm_select(1,'image','Select T1...');
if isempty(P), return; end
Pm = spm_select(1,'image','Select Mask...',{},fullfile(fileparts(P),'VOI'));
Po = MySPM_BatchMasking2(P,Pm);
% Try to do some additional cleanup on the mask
V = spm_vol(char(Po));
Y = spm_read_vols(V);
Yf = logical(entropyfilt(... |
cc1467e225be99654c8feff2dc9d87ea3de0d10b2361fe85a6dfd940280d63da | MATLAB | 1,256 | 41 | function [hr,pval,CI] = SStat_HR(x1,x2,stats)
% [hr,pval,CI] = SStat_HR(x1,x2,stats)
%
% Hazard ratio estimate for Cox models.
%
% Input
%
% x1: Row vector with the covariate values for the first group.
% x2: Row vector with the covariate values for the second group.
% stats: Structure containing statistiscs obtained w... |
3e03435a0b48c3fd157c0ac3fa753496d8c48efd3eb81a765611e8858d77d05a | MATLAB | 1,261 | 40 | function [ hubresil, hubresilarea, resiljac, resilvar, orighub ] = ...
hub_resilience(mat,distmat,hubmethod,Nreps)
% the probability that hubs remain after 100% rewire
n = size(mat,1) ;
% enfore und
mat = (mat + mat') ./ 2 ;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% original h... |
dae004ea89f5181f22af5627945b459b4d1c1cb58b8693a4d73b3fc5591f53ec | MATLAB | 1,261 | 48 | % 5. Use Coregistration of masked T1 to Template brain to finish reorientation
P = spm_select(1,'image','Select masked T1...',{},pwd,'^m.*');
fprintf(2,'***** ENSURE THE ORIGIN OF THE IMAGE IS NEAR ANTERIOR COMMISURE **********\n')
fprintf(2,'***** IF THE T1 NEEDS ADJUSTMENT, THEN BE SURE TO APPLY REORIENTATION T... |
e6f14f2ce4b990ea9d0e961aac95520b854ebb0c2f94a40a4c3634d9e491357c | MATLAB | 1,261 | 38 |
function Spikes = pp_save_manual_sort(Pname,subject,session,Spikes,channel,spikes )
%
% pp_save_manual_sort( subject, session, Spikes, channel, spikes )
% Incorporates the manual changes from splitmerge tool into the Spikes
% struct, changes flag to indicate channel has been sorted, and saves
% the updated f... |
9c74c5478da934c736031b78de56a410e281cdf9651387229a20b92f5f002a93 | MATLAB | 1,263 | 51 | %% Extract LFP signal
% Filter continuously sampled data for low-frequency LFPs and downsample
%
% Filter properties: Bandpass [1 200] Hz
% Downsample from raw data rate (~25 kHz) to ~1000 Hz
%
% DJS 5/2016
tank = 'D:\Data Tanks\CHRONIC_EPHYS_TANKS\HANSOLO_20160426';
blocks = TDT2mat(tank);
plxdir = 'D:\DataProcessi... |
c906e8940f9289d28271c4f6cd1d745e7d40a940500152d9808b2521d6118a02 | MATLAB | 1,263 | 50 |
function [Exist,ExistIndex] = f_existvector(TotalVector,SmallVector)
Exist = 0;%%1.There exists some elements in SmallVector which donot belong to TotalVector.
ExistIndex = [];
if nargin < 1
help f_existvector
return;
end
if nargin < 2
msgboxText = ['There should be two inputs'];
error('prog:inpu... |
0c5b14e8f36749ffad1c387952214d62c56f1221499957f58bb86d892e23aecf | MATLAB | 1,267 | 25 | function [x,y] = findintersection(L1,L2)
% findintersection is a function for finding the intersection point of two lines (vectors)
% Inputs into this function are coordinates of two lines (vectors)
% Line1 = [(x11,y11);(x12,y12)] and line2=[(x21,y21);(x22,y22)]
% Example1 [xintersect yintersect] = findintersecti... |
bd065108e32b209bf6a3ffb641467773bda9563f9368b36e16f99ea714e620d4 | MATLAB | 1,267 | 67 | classdef visedconfig_obj
properties
%vised options
pop_gui='on'
data_type=''
chan_index=[]
event_type={}
winrej_marks_labels={}
quick_evtmk=''
quick_evtrm='off'
quick_chanflag='off'
chan_marks_struct=[]
... |
687515770d977f3c76bde3aeefee66f2f9ce45fca20829d29520381a7cf81539 | MATLAB | 1,271 | 34 | function [results] = scaleDWB3(results, params, couplingGroup, precomputedPortion)
% i.i.d non-mean Gaussian over spike history coefficients & constant
K = size(params.B,1);
if(~isempty(results.dW) && isfield(results, "dH") && ~isempty(results.dH))
w_mu_idx = 1;
dW = double(results.dW);
results.dH(w_m... |
7262af8dbc0eacba5865c5e5b9a81f60515cc3526e056feeab5ac1dbf02f782a | MATLAB | 1,271 | 39 | %this is a program that generates trial averages and forms clusters based
%on that/Select folder TwoEyeAnalysis/ISI20/LXLXCXCX. Created by Haleh Fotowat.
close all
clearvars
path=uigetdir;
cd(path)
%read the pooled clustering data
load('LXLXCXCX_HA.mat')
stim_type_cnt=4;
repse=10;
per2p=1.06295;
ISI=20;
f0=round(ISI/(... |
d753f96661fc623fd6200da77de4e51cd505fea38a24b5aa4ce0b2afe322b6c7 | MATLAB | 1,271 | 49 |
function estudio_warning(Messagestr,titleName)
if nargin<1
help estudio_warning
return
end
if nargin<2
titleName = '';
end
if isempty(Messagestr)
help estudio_warning
return
end
FontSizeDefault = f_get_default_fontsize();
try
[version reldate,ColorB_def,ColorF_def,errorColorF_def] = geter... |
4c73688b88a98a3a0f33f4862571ba22e5af781f96a9d4d9daa90064e2136264 | MATLAB | 1,272 | 73 | %% Noise-Flash Temporal Slewing
%
% Daniel.Stolzberg@gmail.com 2016
sca
FlashDur = 0.1; % flash duration (seconds)
ITI = 2; % inter-trigger interval (seconds)
FlashOnColor = 1; % flash intensity [0 1]
FlashOffColor = 0; % flash intensity [0 1]
NFlashes = 425; % number of flashes
FlashDelay ... |
43fcbdaafe9053c191bcd9cc40a8a9d7a1a7825560d20f7c83b3aef506f63991 | MATLAB | 1,273 | 36 | function reassignments = sort_assignments(assignments)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/08/2010
%
% sort_assignments - renumber cluster identities based on size of cluster
%
% Usage:
% reassignments = sort_assignments(assignments)
%
% Description:
% Takes a list of assignment numbers an... |
1448d3b28cc1f5240ebf5ef6968859e108e52a7af744603108e4450a5dd6d6d9 | MATLAB | 1,275 | 56 | function calculateHoldTimes
%
% This function selects the hold time from a range of possible times
%
% Required gf parameters:
% holdMin
% holdMax
% holdSteps
% holdIndii
%
% Parameters generated:
% holdRange
% holdInd
% holdTime
% holdSamples
global gf
% Linerarly spaced array of times from min to m... |
dff8e0ae6fd7209855eda8781d2dfad4bc1dde9de34da5c10d6d8862a4883fd3 | MATLAB | 1,275 | 53 | % STRAIGHT LINE DEVIATION
function sld = straightLineDeviation(subject,trial,dataType)
if dataType==0
global blacklist filtered time MVCs;
elseif dataType==1
global blacklistLeft filteredLeft timeLeft MVCsLeft;
blacklist = blacklistLeft;
filtered = filteredLeft;
time = timeLeft;
MVCs = MVCsLeft... |
74db380b67e993fef95a69897ba6e371f6c0c515fdcd9353b68640e6ddeacc87 | MATLAB | 1,276 | 40 | function DA = TDT_SetupDA(varargin)
% DA = TDT_SetupDA(tank);
% DA = TDT_SetupDA(tank,server);
%
% The TDT TDevAcc activex control is used to interface with running OpenEx
%
% Initialize TDT TDevAcc activex control in invisible window and return
% handle to control (DA), registered tanks, and a handle to the i... |
2370c4dfe62b9e10a27f449f052b891f67b3703d47d0a8c5f84bab6999b40f1d | MATLAB | 1,277 | 37 | classdef CrossEntropyRegression < nnet.layer.RegressionLayer
properties
% Vector of weights corresponding to the classes in the training
% data
ClassWeights
end
methods
function layer = CrossEntropyRegression(name, classWeights)
layer.Name = name... |
3018546cf7ef9163dd14ee9dc695e13b8b4fbe9636f3d86cf35ad8309a7bd010 | MATLAB | 1,277 | 70 | % FORMAT:
%
% sampval = sample_to_ms(timesam, fs,EpochStart, rounding)
%
% INPUTS:
%
% timesam - time value in time samples
% fs - sampling rate (in Hz)
%
%
% Optional inputs:
%
% rounding - 1 means round the result {default}, 0 means do not round
% EpochStart - the left interval of epoch/... |
961ddc6915e60de77a11c4563ebd83572b10024d90a254b9b6868b38d4d39229 | MATLAB | 1,277 | 39 | function fs_write_fstats(fstats,mri,fname,data_type)
% fs_write_fstats(fstats,mri,fname,data_type)
%
% Writes F-statistic or p-value or Freesurfer significance maps to Freesurfer's
% .mgh or .mgz data file. This can be useful for visualization and post-processing
% in Freesurfer.
%
% Input
% fstats: Structure obtai... |
bea50f73e8647c8285e56fcfdba3e17b88784865817743532782edbb14de9794 | MATLAB | 1,277 | 52 | %% Update Bits# mode
s1 = serial('COM5');
fopen(s1);
fprintf(s1,['#monoPlusPlus' 13]);
fclose(s1);
delete(s1);
clear s1
%%
PsychImaging('PrepareConfiguration');
PsychImaging('AddTask', 'General', 'FloatPoint32BitIfPossible');
PsychImaging('AddTask', 'General', 'EnableBits++Mono++Output');
% PsychImaging('AddTask', ... |
a20607fc1d27a129350ee6e74f385aff4203ee7bba7d60b1215dd327ae103525 | MATLAB | 1,279 | 42 | function Q = StructureMeasure(prediction,GT)
% StructureMeasure computes the similarity between the foreground map and
% ground truth(as proposed in "Structure-measure: A new way to evaluate
% foreground maps" [Deng-Ping Fan et. al - ICCV 2017])
% Usage:
% Q = StructureMeasure(prediction,GT)
% Input:
% prediction -... |
c45e80afc5981cd30d59be232704d685e5661c811415c78ef874c94f4fdb15ee | MATLAB | 1,280 | 48 | function m = dist_mean(val, pgrid, doWarning)
% Compute the mean (m) of a probability distribution (val) over a discrete
% grid (pgrid).
%
% Usage:
% m = dist_mean(val, pgrid, doWarning)
%
% NB: doWarning: 1 allow a warning message on whether the distribution is
% normalized to sum to 1 (default: 0)
%
% Copyright ... |
df96419603bf25c33a0fb8f4f66eb71fa9cb4eb5e2ce29d92fe661c675c04739 | MATLAB | 1,282 | 45 | function annotT = BehaviorArrayToCategorical(annotT)
% If input is a single array
if any(strcmpi('Frame', annotT.Properties.VariableNames))
annotT = SingleArrayToCategorical(annotT);
% If input is a table of clips
else
initCatBehav = cell(size(annotT, 1), 1);
if any(strcmp('Labels', annotT.Properties.... |
2774bc4ebbd078b51b370cb84a5333b07a95047160eb0ec7014a217cb0a1b6c0 | MATLAB | 1,284 | 52 | %=====================================================
% FileName: extract_bin_image.m
% Designby: Zhe
% Modified: 11/4/2021
% Describe: Extract all frames of images from TIFF and store in image.bin
%==========================================================================
clear variables;
file_path = "/media/blairl... |
50a39e2de78ecf9d6604cc78cd1b1180f78aed2227478b4f8ce59030225ee015 | MATLAB | 1,284 | 50 | function [Q]= original_WFb(FG,GT)
% WFb Compute the Weighted F-beta measure (as proposed in "How to Evaluate
% Foreground Maps?" [Margolin et. al - CVPR'14])
% Usage:
% Q = FbW(FG,GT)
% Input:
% FG - Binary/Non binary foreground map with values in the range [0 1]. Type: double.
% GT - Binary ground truth. Type: log... |
e9f3d9aa0d2d943ad327f0e3fd51ce9c4764a0bf0362ec28e5d7394bb74d4a87 | MATLAB | 1,285 | 45 | %% Master Script for Vector Strength plots
clear all
clc
root = 'C:\Data\Daniela\ACV_Water\PCF_Males_TP2\';
dirAnaly = 'C:\Data\Daniela\ACV_Water\PCF_Males_TP2\angHeadCircAnaly\'; % where to save the analyzed data
dirAng = [root 'vid_Angles\'];
% Select and parse video files
[files, dirAng] = uig... |
f960e2f2dcc484238bb0f4be349294005df909712d633dc13ac58612423731c2 | MATLAB | 1,287 | 36 | function params=tpreadconfig( tpdirname )
%TPREADCONFIG read twophoton experiment config file
%
% PARAMS = TPREADCONFIG(TPDIRNAME)
%
% Reads the parameters from the 2-photon data directory
% TPDIRNAME. TPDIRNAME should be a full path to the 2-photon directory.
%
% Output:
% PARAMS.Main.Total_cycles (total number of ... |
43ba6a46013589dedbf26895befe50e6697f431c4454adb904378f1bb007e0b1 | MATLAB | 1,288 | 47 | function [c,p] = plotVersus(acc1,acc2,sideTrans,chancelevel,pltMdl,l,inSbplt)
if ~exist('pltMdl','var')
pltMdl = 0;
end
if ~exist('l','var')
l = [5 max(ceil(max([acc1(:); acc2(:)])/5)*5,30)];
end
if ~exist('inSbplt','var')
inSbplt = 0;
end
if ~inSbplt
... |
89a643fc066bd15ae431a4d8913d0f36581445e00cccdd617f4998effa5ad94e | MATLAB | 1,289 | 58 | function JS = f_JS_discr(aij,bij,nbins)
% https://github.com/aiavenak/matlab_code/blob/master/f_JS_discr.m
[d1,d2] = size(aij);
[b1,b2] = size(bij);
if (d1 == d2) && (b1 == b2)
% aij, bij are adyacency matrices
% get laplacian and eigenvalues
vaij = f_get_spectrum_lap(aij);
vbij = f_get_spectrum_lap(bi... |
b5c65d7afbe9c6200ff1fde361706d197019339bf9049ca5214654a178dcefeb | MATLAB | 1,289 | 43 | function [fitresult, gof] = createFit_fcsc_LAR(sc_avg_vec_sort, fc_avg_vec_sort, is_figures)
%NOTE: Power2. Levenbrg algorithm. LAR
%CREATEFIT(SC_AVG_VEC_SORT,FC_AVG_VEC_SORT)
% Create a fit.
%
% Data for 'untitled fit 1' fit:
% X Input : sc_avg_vec_sort
% Y Output: fc_avg_vec_sort
% Output:
% fitre... |
87d8484cd2f210af1330acbcee521ce6f4700df62d07caa7d4a02d885a4059c0 | MATLAB | 1,290 | 61 | %% Open DB_Browser GUI to retrieve selected database ids
DB_Browser;
%% Returns structure with database IDs currently selected in DB_Browser GUI
ids = getpref('DB_BROWSER_SELECTION');
%% Retrieve raw spike times from onset of recording block
spiketimes = DB_GetSpiketimes(ids.units);
%% R... |
aac2d010af57765e239f8fa66b6e8fa6112dedc85c0d4dab7362c1587828bb84 | MATLAB | 1,291 | 63 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% load up
filename = [ DD_PROC '/MamiNum_corrected_proc.txt' ] ;
ssheet = readtable(filename,'Delimiter','\t') ;
%%
species_names = readtable([ DD_RAW '/mami_species_names_v1.csv'],... |
c838c44208c686a9231f339837c29978a6e17ac1a7766f39947261772bdd4782 | MATLAB | 1,291 | 49 | function [tanks,islegacy] = CheckForTanks(parentdir)
% tanks = CheckForTanks(parentdir)
% [tanks,islegacy] = CheckForTanks(parentdir)
%
% Check some directory (parentdir) for TDT tanks
%
% islegacy can be returned as a logical vector the same size as tanks
% indicating whether or not the tank is actually a lega... |
5fcf697003b7c7d321ae63038f0d003997739507e288981218e6618114c59164 | MATLAB | 1,292 | 40 | classdef CrossPlotProps < matlab.mixin.SetGet
properties
logScale logical = false;
mode char = 'scatter'; % scatter, trisurf, griddata, or circles
shading char = 'interp'; % flat or interp, used only for trisurf
resolution (1,1) double = 10; % [um], only for griddata mode
... |
1544815f18ca105eeb7f0fff9674ba141107c74049b28e2a135b67bb3988ee0c | MATLAB | 1,294 | 47 | function lme_timePlot(time,y,ni,subjs)
% lme_timePlot(time,y,ni,subjs)
%
% Spaghetti time plot of longitudinal data.
%
% Input
% time: Time covariate.
% y: Ordered data vector (according to time for each subject).
% ni: Vector whose entries are the number of repeated measures for each
% subject in the study (ordered ac... |
9e9b6ba15bbe2bedcf38bd197613e996dc78fa163bd7a92f0c6156e003136b30 | MATLAB | 1,295 | 68 | function [t,n,b]=frame(x,y,z,vec)
% FRAME Calculate a Frenet-like frame for a polygonal space curve
% [t,n,b]=frame(x,y,z,v) returns the tangent unit vector, a normal
% and a binormal of the space curve x,y,z. The curve may be a row or
% column vector, the frame vectors are each row vectors.
%
% This function calcula... |
00aedd5dc9a7b36c7a643c11aa37a45296bcb62dd424da0b9bd9756166961d2f | MATLAB | 1,297 | 35 | function plotPerformance_SpatialMask_SNR_cdf
[dataDir, options, c, d] = import_settings()
% For each ferret
files = dir( fullfile(dataDir,'*.mat'));
for i = 1 : numel(files)
[COctrl, COcool, SPctrl, SPcool, SOctrl, SOcool] = import_data(dataDir, files(i).name);
sp = create_figure... |
6739d50ea748904e37ba305a4461faaf16c315db3512353bd5d4341eb49c0fa8 | MATLAB | 1,301 | 47 | clc; clear; close all
Fig3b = figure();
Ntrials_2 = 10000;
%Ntrials_2: number of learning cycles to learn the background containing the embedded pattern (step 2).
xax=(1:1:Ntrials_2);
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
%%%%%%%%%%%%%%%%%%%%%%%%%... |
713d08c652605dfd2e17016cb7f7a77d2fbf4a7d30887843f2b5630b680f6651 | MATLAB | 1,301 | 59 | function [outVec, outVec2] = parcellate_lab(dat,labVec,labs,funcopt)
if length(dat) ~= length(labVec)
error('data and label need to be same length')
end
if nargin < 3
labs = unique(labVec) ;
end
if nargin < 4
funcopt = 'mean' ;
end
% ensure column
if ~iscolumn(dat) || ~iscolumn(labVec) || ~iscolumn(la... |
8fe239c3fd2a9725292279ff0475d807c6706b2a225f0f9190dd448e40cdd559 | MATLAB | 1,306 | 49 |
function clipT = CollapseSequencesIntoClips(seqT)
clipNos = unique(seqT.ClipNumber);
clipT = table;
for i = 1:length(clipNos)
currClipNo = clipNos(i);
currSeqT = seqT(seqT.ClipNumber == currClipNo,:);
varNames = currSeqT.Properties.VariableNames;
currClipT = table;
for j = 1:length(varNa... |
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