sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ed7b9ee29f43d248306079e60267a8827590ebdafda49dbf75171ad35a483cd4 | MATLAB | 588 | 26 | function b2 = FitVMLikelihood(data)
%% choose initial parameters
[mu, k, p] = MixedVonMisesFit(data);
p1 = p;
p2 = 1-p;
p3 = 0;
b = [mu; k; p1; p2; p3];
%% fit data
options = optimoptions('fminunc', 'GradObj', 'on');
b2 = fminunc(@(b) VMMix_logF(data, b), b, options);
%% plot fit
% figure;
% plot histogram
numBins... |
020350882bb57250ece16cee1214af70f8d78eb4d44c74695133a282add53318 | MATLAB | 589 | 20 | function p = MD_unipdf(x, a, b)
% _
% Probability Density Function for a Continuous Uniform Distribution
% FORMAT p = MD_unipdf(x, a, b)
%
% x - an N x 1 vector of values (domain: a <= x_i <= b)
% a - a scalar, the lower end of the uniform distribution
% b - a scalar, the upper end of the uniform distribut... |
02c66e42da3f087d306fc12a16cf6a490c7048371f773fbee291bd3bfdd35091 | MATLAB | 589 | 24 | function PrairieLinkPlayer()
% Lloyd Russell 2017
% displays the raw data saved by PraireLinkRawDataStream for quick inspection
% choose file
[FileName, PathName] = uigetfile('*.bin');
FullPath = [PathName filesep FileName];
cd(PathName)
% read data
data = PrairieLink_ReadRawFile(FullPath);
NumFrames = siz... |
d483100961026d65bdc9aa5863fb74ff442337af3030ee16ba916f9310aee09d | MATLAB | 589 | 18 | sources_table = abannotate_get_sources;
parcellated_data_path = 'pls_ukb_bootstrap_schaefer100_df.csv'
parcellated_data = csvread(parcellated_data_path);
opt.n_nulls = 1000;
opt.atlas = 'Schaefer'
opt.phenotype_data = parcellated_data;
opt.GCEA.correlation_method = 'Spearman'
% Cell type analysis
opt.analysis_name ... |
b5e36702ed9573c40e0a1a79713613ca6bbf13784043b2e6b92cb69b0293cf12 | MATLAB | 590 | 22 | function [x] = shuffle_channels( x )
% *WAVE*
%
% SHUFFLE CHANNELS randomizes the spatial position of channels in a
% datacube, so that any spatial autocorrelation
% is destroyed while leaving the temporal
% structure intact
%
% INPUT:
... |
06d98fbe0cb1707e551cbd0dfe8ae120a6ff7df1cc4fa0cf18a4814436f0526d | MATLAB | 592 | 20 | function [r,p_val] = NB_corr(data,raster_params,directions, ind)
spikes =[];
RTs =[];
boolFail = [data.trials.fail];
[~,match_d] = getDirections (data);
% substract RT average in direction to reduce directional variance
for d = 1:length(directions)
inx = intersect(ind, find ((~boolFail)...
& match_d == dir... |
a63631cbbeeba1d8215e72573e816b7900ecf2656ba135a37e23ebc11aa2ba10 | MATLAB | 592 | 18 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : CHATENET Louis
% Date : 24/05/2018
% Updated : 30/05/2018
% Version : V2.0
%
% Description : AMPA current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Isyn, r] = IsynAMPA3(dt... |
c9136d0cad38afa572f816722e3e16e26938b474f918bff9839e8f6ff2b9fc4c | MATLAB | 592 | 36 | function [eigvec, eigval, eigval_full] = eig1(A, c, isMax, isSym)
if nargin < 2
c = size(A,1);
isMax = 1;
isSym = 1;
elseif c > size(A,1)
c = size(A,1);
end;
if nargin < 3
isMax = 1;
isSym = 1;
end;
if nargin < 4
isSym = 1;
end;
if isSym == 1
A = max(A,A');
end;
... |
9de5a41a2825f1baa0aac3dcc5d60a1054e7a24c0a4b498b17671a9c688dcde2 | MATLAB | 593 | 22 | function cluster_frequency_rejection_211021(folder_address,rec_leng)
cap_freq=10;
max_clus_size=cap_freq*rec_leng;
cd(folder_address)
times_dir=dir('times_*.mat');
times_name=string({times_dir.name});
for i=1:length(times_name)
load(times_name(i))
num_classes=max(cluster_class(:,1));
for j=1:num_classes
... |
ab2ddfbd4d8436da3c011bcada56030c4db3785314d09f45625aa3e4a36992e0 | MATLAB | 593 | 17 | function plot_handles = assignColorsToLines(plot_handles, color_map_matrix, color_field_name)
% this will work with bar handles if the color field name is provided
% ('FaceColor')
if size(color_map_matrix, 1) < length(plot_handles)
error('color map matrix should be a Nx3 matrix of rgb colors, with N >= length(plot_... |
cd8f2270f20601b287440ae570ee729df793370cd2dd6dfdeb0b8eba7f47aaaf | MATLAB | 593 | 43 | function [bias1] = CrossCorrBias2(Sdata, nbins, binsize)
n_cells = length(Sdata);
bias = ones(n_cells,n_cells) * NaN;
for i = 1:n_cells
for j = 1:i-1
[Crp{i,j}, B] = CrossCorr(Data(Sdata{i}), Data(Sdata{j}),...
binsize, nbins);
if(sum(Crp{i,j}) == 0)
birp = 0;
else
birp = ... |
0f85186f0f5de94b5eaa1c0e654638b0c6ab2f04a155317338ae6e3169830c46 | MATLAB | 594 | 21 | function [old_dirs,old_stps,Hdiag] = lbfgsUpdate(y,s,corrections,debug,old_dirs,old_stps,Hdiag)
ys = y'*s;
if ys > 1e-10
numCorrections = size(old_dirs,2);
if numCorrections < corrections
% Full Update
old_dirs(:,numCorrections+1) = s;
old_stps(:,numCorrections+1) = y;
else
%... |
a52eec970d285aff33b50a679123f5722cbb999252eaac6f5bcb2c9d6186155b | MATLAB | 594 | 21 | function [rho,phi] = cart2poln(data)
% [rho,phi] = cart2poln(DATA)
% transforms the p samples of cartesian N-dimensional data (Data is a p-by-n matrix) into spherical coordinates (N-sphere)
% rho is a vector of length p, phi a matrix of angular values of size p x n-1
% Adrien Peyrache, 2013
squared = data.*data;
N... |
5987a9052168b75688ebadd635b5dafbf4909cfe8f4e311b2f54ef47023bda92 | MATLAB | 595 | 17 | % Equivalent to typing 'summarize(subj)'. For lazy people.
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released under
% the GPL. See http://www.csbmb.princeton.edu/mvpa for more
% information.
%
% The Princeton MVPA toolbox is avail... |
dd9c9ec015e0372a746c203bf7ffc8fa19d1f86e6f6a1eab0b4726fb3845b591 | MATLAB | 598 | 20 | raster_params.allign_to = 'cue';
raster_params.cue_time = 500;
raster_params.time_before = 300;
raster_params.time_after = 700;
raster_params.smoothing_margins = 0;
raster_params.bin_size = 10;
raster_params.plot_cell = 1;
%% cells that are simple random noise
for t = 1:length(data1.trials)
data1.trials(t).spi... |
d10bab1da2d8600b47884c8e59361bbccd5890ea63264e490bbac63ee38f6161 | MATLAB | 599 | 25 | function dirNode(treeHandle, topFolder, varargin)
% DIRNODE generate parent node and walk subfolders (1 level) to create
% child nodes to parent node treeHandle
%
% VARARGIN
% context menu: Open
%
% $Author: Peng Li
% $Date: Mar. 22, 2021
%
% root node
[~, f] = fileparts(topFolder);
rnode... |
3a0365ef47d0b1e344afbafb0972d8f279e8c06011ed5201606ef0e3a345a53e | MATLAB | 600 | 18 | % figure for IZ param ranges
ranges=[0.62 0.98; 0.004 0.005; -23.77 11.69; 3 119; 118 131; -62.65 -58.53; ...
-43.6 -43.52; 7.85 11.48; -52.68 -49.52];
for i=1:9
r1=ranges(i,1); r2=ranges(i,2);
data_range = linspace(r1, r2, 10);
s_plot = subplot(9, 1, i);
plot(s_plot,data_range,1)
%xlim([r1 r2... |
4acb562911bf82a688282c9137705978b45638913158f849aae4bfeaa6abe554 | MATLAB | 600 | 35 | function r = Rate(S0,varargin)
% Returns a vector containing the time of the last event of each tsd
%
% USAGE:
% eno = Start(tsa,is)
%
% INPUTS:
% tsa - a tsdArray
% is - an intervalSet
%
% OUTPUT:
% eno - an vector of time
% copyright (c) 2009 Adrien Peyrache adrien.peyrache@gmail.com
r = [... |
0bf1ffc2a2495932e4fb7e9c9d9a964110a6bee6a453b7ff9e6005c1a9bacd4c | MATLAB | 601 | 25 | function [ripTsd ripEp] = LoadRipples(fbasename,varargin);
% Load ripple times from a .sts.RIPPLES file
%
% USAGE:
% [ripTsd ripEp] = LoadRipples(fbasename);
%
% INPUT:
% fbasename: session file basename
%
% OUTPUT:
% ripTsd: a tsd of ripple times
% ripEp: a intervalSet of ripple events (beginnings and en... |
522efc8de22a7bae8dc1958aa4918aea07595ac73ee7b72c3a74cfda7a62eba4 | MATLAB | 601 | 10 |
function add_scale_bars(ax,quantity_xaxis,quantity_yaxis,shift_from_origin)
%x scale bar:
disp(['x scale bar is ' num2str(quantity_xaxis)]);
annotation('line',[ax.Position(1) ax.Position(1)+(quantity_xaxis*ax.Position(3))/range(ax.XLim)]-shift_from_origin,[ax.Position(2) ax.Position(2)]-shift_from_origin,'... |
1fca852a7c9c30de9a17020f9e2a559657b870c1245780ee533255fe5642be98 | MATLAB | 602 | 26 | function [xf] = generate_damped_sin( dt, T, frequency, tau, phase_angle )
% *WAVE*
%
% GENERATE DAMPED SINE WAVE TEST DATA generates a simple test damped sine wave for
% use with the functions in WAVE
%
%
% INPUT
% dt - timestep
% T - epoch length (s)
% frequency - frequen... |
3f1544fd6003ce715c970fa965cd612cabc5c81bc5c144ea657ab8c6d52ad5e3 | MATLAB | 602 | 21 | function y = linef(lambda, fn, x, d, varargin)
%LINEF Calculate function value along a line.
%
% Description
% LINEF(LAMBDA, FN, X, D) calculates the value of the function FN at
% the point X+LAMBDA*D. Here X is a row vector and LAMBDA is a scalar.
%
% LINEF(LAMBDA, FN, X, D, P1, P2, ...) allows additional arguments t... |
7613b16172d73b2da81927242eeaf6ebc679137ea13e92e1157fdf608cff8b13 | MATLAB | 602 | 19 | function [z] = cellcat(dim, x, y)
% [Z] = CELLCAT(DIM, X, Y) outputs cell-array Z with the same dimensionality as X and Y
% Each cell in Z contains a concatenation of the corresponding arrays in X and Y,
% along dimension DIM
%
% X (and Y) should be linear cell-array(s) of matrices for which the number of rows (if di... |
5b72bb44b5ab356735f622cc32274b9f89374c01dabde40129ce8acd0d66299b | MATLAB | 604 | 18 | function start_eyetracker(Experiment)
if strcmp(Experiment.Mode.eyetracking,'Yes')
% start recording eye position (preceded by a short pause so that
% the tracker can finish the mode transition)
% The paramerters for the 'StartRecording' call controls the
% file_samples, file_events, link_sample... |
f78d209015f16b9913c6f7c998d12b14a2f24e0696a96daeec0029218e1f5e86 | MATLAB | 604 | 28 | function [xo] = notch_filter_matrix(x, f1, f2, filter_order, Fs)
% *WAVE*
%
% NOTCH FILTER notch filter a datacube between frequencies f1 and f2
%
% INPUT:
% x - datacube (r,c,t)
% f1 - low frequency for notch
% f2 - high frequency
% filter_order - filter order ( x2 for bandpass filter )
% Fs - sampling frequency
... |
9f1c83d4d77a74050bae255dcb72731044ad7a8d0c37aa59f329dc02a024e8c6 | MATLAB | 605 | 29 | function [allBins, Std_mean, Std_median] = VF_weighted_Std(Quiver)
% input Quiver to weigh the std (column 9) by the occupancy in each bin
% (column 7)
% output for weighted average and median std
% output for all std values for new histogram plot
if isempty(Quiver) == 0
Std = Quiver(:,9);
Occ = Quiv... |
a0cf42c5460b44ef4def74af069f91f16dfa2a857f7ec7e812c72aec8771ad47 | MATLAB | 605 | 28 | %% Run PLS analysis %%
%% Read in data and functions
workdir='';
addpath(genpath('/dagher/dagher11/filip/Obesity_maps/scripts/'));
addpath(genpath('/dagher/dagher11/filip/Obesity_maps/data/'));
addpath(genpath('/dagher/dagher11/filip/Obesity_maps/data_old/'));
BMI='UKBB_CT_DKT_LHRH';
nsynth='Nsynth_DKT_thickness_LHR... |
25cfbd318b355a8dad3cb81e29b301af87f3620c99fb268773f1e9d378a0388e | MATLAB | 606 | 25 | function s = times(a,b)
% Overload of the .* operator
%
% USAGE:
% s = times(a,b)
%
% the .* operaetor is defined to return a tsd with same timestamps and
% data that are the difference of the data. Returns error if timestamps of the
% two object don't coincide
% copyright (c) 2004 Francesco P. Bat... |
106bede143a9d04a118690f10272e171cc78cae28e0698f8ef618277f5e35b5e | MATLAB | 608 | 23 | function [c] = sompak(net)
%SOMPAK Combines node weights into one weights matrix.
%
% Description
% C = SOMPAK(NET) takes a SOM data structure NET and combines the node
% weights into a matrix of centres C where each row represents the node
% vector.
%
% The ordering of the parameters in W is defined by the indexing of... |
70d77cf77232bb085154e30296b3ef663ff19411b7b2d9234ef2d473e8da03a1 | MATLAB | 610 | 17 | function CalculateDifferenceImage(exportFolder, diffImageParams, origImage, smoothImage)
% Params
corrThresh = diffImageParams.corrThresh;
% Calculate Difference Image
% corrPeaks = GetCorrPeaks(smoothImage, corrThresh);
corrPeaks = 3 + zeros(30, 1);
origDiffImage = CreateFinalImage(origImage, corrPeaks);
smoothDiffIm... |
a7fe517d5ba0c5ea09080cd52d6b2bb8ffdf38de2a5d701e897235e70a71dd77 | MATLAB | 610 | 36 | function C = ReactCC(X, Y)
% C = ReactCC(X, Y)
%
% coompute the correlation coefficient between matching columns in the
% matrices X and Y, taking care of NaNs
if any(size(X) ~= size(Y))
error('X and Y must have same size');
end
mk = zeros(size(X));
mk(find(isnan(X .* Y))) = NaN;
X = X + mk;
Y = ... |
f90e6b4c9364748eabf5694346aa845f65047666eeca5e184c924777dcd4c71c | MATLAB | 610 | 39 | function r = MatrixCorrCoef(A, B)
% r = MatrixCorrCoef(A, B)
%
% Computes the correlation coefficient between the vectors of the
% off-diagonal elements of the square matrices A and B
% INPUTS
% A, B: two square matrices of the same size
% OUTPUTS
% r: the correlation coefficient
% batta 2000
[N, N1] = size(A);
if ... |
1453648eb79af7bf66fa0c2aaa0d569c5bcdb37131f6fcef49211f9bc14439b2 | MATLAB | 611 | 15 | function [sectionPaths, sectionNames, sectionRootFolder] = s3GetAllSlidesOfSubject(subjectPath)
%This function returns all slides owned by a subject
sectionRootFolder = awsModifyPathForCompetability([subjectPath '/Slides/']);
[sectionNames, sectionPaths] = awsls(sectionRootFolder);
isFolder = cellfun(@(x)(contain... |
6eb8816d6c6aa3184405931d5b837caf749340934bf32b9b21b02873df57ef61 | MATLAB | 611 | 18 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : BEAUBOIS Romain
% Date : 30/03/2020
% Updated : 30/03/2020
% Version : V2.0
%
% Description : GABAa current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Isyn, r] = IsynGABAa3(... |
bb31d97874fd9105edfee3535c07574a68d70b93ea52856f56b58462e8f28589 | MATLAB | 612 | 28 | function [cmds, errs, msgs] = gitSubmodulesUpdate(repo, options, preview)
cmds = {};
currdir = pwd;
if ~exist('repo','var') || isempty(repo)
repo = [pwd, '/'];
end
if ~exist('options','var')
options = 'init';
end
if ~exist('preview','var')
preview = false;
end
repoFull = filesepStandard_startup(repo,'fu... |
bf684cdb84c5d7ca7f665076d65e30d1ac69c7c7eb66db7aefaa7068afcf7cc6 | MATLAB | 612 | 23 | function boxplot_r_jin(Perm_r,corr_r,Ylabel,pic_size,output_path)
figure;
[B,I] = sort(corr_r(:,1),'ascend');
Perm_r_new = Perm_r(I,:);
Ylabel_new = Ylabel(I)
boxplot(Perm_r_new','Orientation','horizontal','Whisker',3,'color',[137 137 137]/255)
set(gca,'FontSize',18);
set(gca,'LineWidth',3);
set(findobj(gca,'type','l... |
333e0943f4e6b9ebcff8caa246b65d5f228c85961e4d84c843cd6665afadab55 | MATLAB | 615 | 14 | function decoding_out = RFEselect_test(labels_test,vectors_test,cfg,model)
switch lower(cfg.decoding.method)
case 'classification'
[predicted_labels accuracy decision_values] = svmpredict(labels_test,vectors_test,model,cfg.decoding.test.classification.model_parameters);
case 'regression'
... |
47c5d1667fe4390408e82d3e80326fb7a3ff708f38aac58adfb8cf55732f78ee | MATLAB | 615 | 26 | function [bsResult] = bootstrap_analysis(data,n1,repeatNum)
%BOOTSTRAP_ANALYSIS ´Ë´¦ÏÔʾÓйش˺¯ÊýµÄÕªÒª
% ´Ë´¦ÏÔʾÏêϸ˵Ã÷
% if ndims(data) > 1
% disp('Input data for bootstrap analysis must have only 1 dimension!')
% return
% end
if nargin < 3
repeatNum = 1000;
end
bsResult.repeatNum... |
a7f888ce3d98c172526c5428ea8c2a4abf5ccc1cf769f56c7ebe383ff8550b62 | MATLAB | 615 | 17 | function filtered_exptracelist=merge_and_filter_short_links_s(tracklist,segmentlists_time,segmentlists,length_filter,tmax_local)
fet=1;
filtered_exptracelist=[];
for tracklist_id=1:numel(tracklist)
new_track=NaN.*ones(1,tmax_local);
for segment_id=tracklist{tracklist_id}
start_time=(segmentlists... |
cf342f9831c9d386c9a88e305b900c52295b641caff3a42b92e7780053552f41 | MATLAB | 615 | 17 | function filtered_exptracelist=merge_and_filter_short_links(tracklist,segmentlists_time,segmentlists,length_filter)
global maxtime
fet=1;
filtered_exptracelist=[];
for tracklist_id=1:numel(tracklist)
new_track=NaN.*ones(1,maxtime);
for segment_id=tracklist{tracklist_id}
start_time=(segmentlists_t... |
5437a0f74a718a92277540e87f25654b85f6d91ffaa0c54b0ec84530e03cc95c | MATLAB | 616 | 16 | function [LABELS] = MultiLineLabels(LabelMatrix)
%MultiLineLabels takes a cell array of labels (columns are different
%labels, rows will be different lines of the labels) and converts it into
%individual labels
BaseString = '%s';
AdditionalString = '\\newline%s';
AddStringRep = repmat(AdditionalString, 1, size(... |
9c6eb9bc863d11003a177d0ef0d0a1269298f7dc52cf37faf4e13bcb40bb77fe | MATLAB | 617 | 24 | clear
[task_info,supPath,~,task_DB_path] = loadDBAndSpecifyDataPaths('Vermis');
req_params.grade = 7;
req_params.cell_type = {'SNR'};
req_params.num_trials = 50;
req_params.ID = 4000:5000;
req_params.task = {'choice|saccade_8_dir_75and25|pursuit_8_dir_75and25'};
lines = findLinesInDB(task_info, req_params);
median(... |
2d004396099415c83f3075f2990ddc7d9f82d47ca4756a7a523bca86c8f28cc6 | MATLAB | 618 | 29 | function h = histp(x, xmin, xmax, nbins)
%HISTP Histogram estimate of 1-dimensional probability distribution.
%
% Description
%
% HISTP(X, XMIN, XMAX, NBINS) takes a column vector X of data values
% and generates a normalized histogram plot of the distribution. The
% histogram has NBINS bins lying in the range XMIN t... |
6590eb36315babdeff5968dde15c57b1f34ad71b18a3d12c13a446e719c5dd29 | MATLAB | 618 | 19 | function [selected_Traj, sample_idx] = SubsampleTraj(Traj, k)
% subsamples the same number k of trajectories for each session
% if there are less than k traj in the session it will take all trajs
numTrials = size(Traj,1);
if numTrials < k
selected_Traj = Traj;
sample_i... |
91c83370ebba860a3c6e010aebde40a61bbe94c2990e8fa128723935edc04591 | MATLAB | 618 | 24 | function [logalpha1,loglik1] = VBHMMforward(v,phghm,ph1,logOutput)
T = size(v,2);
H = size(logOutput,1);
logalpha1 = zeros(H,T);
for h = 1:H
logalpha1(h,1) = logOutput(h,1) + log(ph1(h)) +1e-100; % eps
end
for t = 2:T
phatvgh1 = zeros(H,1);
for h = 1:H
phatvgh1(h) = exp(logOutput(h,t)) + 1e-100;... |
0543269184ea99feab662ca1b82bd5eebd1d1265942847ceaa9db21e52439dc0 | MATLAB | 622 | 26 | function [states, stateCell] = estimateStatesByVitterbi(data,model,logOutProbs)
Wa = model.Wa;
Wa = Wa';
K = size(Wa,1);
Aest = Wa./repmat(sum(Wa,2),1,K);
Aest = Aest';
Wpi = model.Wpi;
piest = Wpi./sum(Wpi);
nSubjs = length(data);
states = [];
for ns = 1:nSubjs
[M,T] = size(data{ns});
pvgh = zeros(K,T);
... |
2925a39538f2c9cc39082d2cd296a7164bd54efd4bc2dd59c8e42e10fb9218a6 | MATLAB | 623 | 30 | function combineFiles(filepathname)
[~, savename] = fileparts(filepathname);
PFs = 0:.1:1;
clear E K1 K0 K2
for ii = 1:length(PFs)
try
D = load(fullfile(filepathname, sprintf('%s_%gPF.mat', savename, PFs(ii))));
catch
continue;
end
K1(ii) = D.K1;
K0(ii) = D.K0;
K2(ii) = D... |
6fa2909f699f6bf3ef10790134b1505655125e1438a10f10ce42a2a77f021fa9 | MATLAB | 623 | 23 | function net = somunpak(net, w)
%SOMUNPAK Replaces node weights in SOM.
%
% Description
% NET = SOMUNPAK(NET, W) takes a SOM data structure NET and weight
% matrix W (each node represented by a row) and puts the nodes back
% into the multi-dimensional array NET.MAP.
%
% The ordering of the parameters in W is defined by... |
57fe2b15fef9a18c90e684f38ba559a0bc3ce752f88834f1ae01ac8c1f0852b4 | MATLAB | 624 | 14 | %%
%% Script to load spike firing times for a cell
%% c_ts: firing times, root.cel_x{1,1}: spike x coordinates,
%% root.cel_y{1,1}: spike y coordinates
%% reference: https://github.com/hasselmonians/CMBHOME/wiki/Tutorial-2:-Apply-an-epoch-and-get-theta-signal
%%
function pos=load_and_format_spikes(file_to_reformat... |
9a485c165355aab440440f82e40961be64128f1765aa43eaca86858edcf53497 | MATLAB | 624 | 29 | function L = CrossValidationSpatialCheck(S,lambda,x1,x2,X,Y,ep)
nbEp = 10;
epV = regIntervals(ep,nbEp);
L = zeros(nbEp,1);
for ii=1:nbEp
ix = (1:nbEp);
ix(ii)=[];
testEp = epV{ii};
trainingEp = epV{ix(1)};
for jj=2:nbEp-1
trainingEp = union(trainingEp,epV{ix(jj)});
trainingEp... |
6a75dc401b89158da08850967ede263208e06d0e22e890ad00d1c6067c33fa79 | MATLAB | 625 | 16 | % @author Farad Khoyratee
% @date 16 Apr 2019
% @copyright
% SPDX-FileCopyrightText: © 2021 Farad Khoyratee <farad.khoyratee@gmail.com>
% SPDX-License-Identifier: GPL-3.0-or-later
function simplified_rV2= simplified_rV2(v, rpre, dt)
inf = (2^-1)*tanh(-(2^-6 + 2^-7)*v-1.404)+0.5193;
% tau = ((-0... |
4f24c6395296bade0213f7c26a004331c4614e23eeae37f9747fa492b9585b6c | MATLAB | 626 | 35 | function t = compatible_ts(tsa, tsb, tl)
% Tells whether two tsd's have the same timestamps, within relative tolerance
%
% USAGE:
% t = compatible_ts(tsa, tsb, tol)
%
% INPUTS:
% tsa,tsb: two tsd to compare
% tol: tolerance (default 0)
%
% OUPUTS:
% t: scalar value
%
% copyright (c) 2004 France... |
f2e1e41e2a448758501d947774f0c9a439df679dced2d5e0f93d4ea8b1f80de1 | MATLAB | 626 | 28 | function PoSubPaper_GetTCxcorrs
load(fullfile('Analysis','HdTuning_moveEp'));
smoothTC = 3; % smoothing of tuning curves (3 used in Duszkiewicz et al., 2024)
hAll = hAll(:,:,smoothTC+1);
if size(hAll,1) > 360
hAll = hAll(1:end-1,:);
end
[bins,totC] = size(hAll);
allPairs = nchoosek(1:totC,2);
% calc... |
16ac952077c37d6cd1f6d2d9825ae8ce55cb7a92cf9439ef3ae98bdf60631dc0 | MATLAB | 627 | 28 | function [xo] = bandpass_filter_matrix(x, f1, f2, filter_order, Fs)
% *WAVE*
%
% BANDPASS FILTER MATRIX filter a matrix between frequencies f1 and f2
%
% INPUT:
% x - matrix (r,t)
% f1 - low-frequency cutoff
% f2 - high-frequency cutoff
% filter_order - filter order (N.B. doubled for forward-reverse filter)
% Fs - sa... |
64f55f13cdc47b320dc52eb7f692a01232851166496586459b5b286b58973a78 | MATLAB | 629 | 22 | function plottracks_s
global ax
global text_spot_num
global framenum
global A_time_s
global plotted_neurons
global neurons_tmp_unsorted_s
a=1;
try
delete(plotted_neurons);
end
plotted_neurons=[];
for i=1:numel(A_time_s{framenum})
if ~isempty(A_time_s{framenum}(i).color)
hold on
pl... |
bc5c45dae2e0e432bd4d03c5a75263e63600fda3296a849a7b29ae291b289850 | MATLAB | 630 | 31 | function s = vertcat(a, b, varargin);
% Vertical concatenation of TSDs (overload of the [a; b] operator)
%
% USAGE:
% tso = vertcat(tsa, tsb, ...)
%
% arguments must be all tsd, the cat function is used
% copyright (c) 2004 Francesco P. Battaglia
% This software is released under the GNU GPL
% www.g... |
c8dff001feef67f7f8e46e1032bf691c5a1c673d7d27a9234381456698809e8f | MATLAB | 630 | 21 | %returns timestamps of trials in a cell array
%
%stimuliTimestamps: first column is begin timestamp, second column is end
%timestamp of trial
%
%returns a cell array of trials
%
%urut/may04
function [trials, indsAll, indsOrigPerTrial] = getTimestampsOfTrials(timestampsOfCell, stimuliTimestamps )
timestampsOfCell = tim... |
6cc7f37ddddab8cbaff11ac16e99ee41d0159cc7157b28d8987f02dc2a2f4cc1 | MATLAB | 631 | 24 | function run_all_unittests()
% Call this function to execute all unit tests contained in this
% subfolder.
global FAIL_COUNT
FAIL_COUNT = 0;
path = fileparts(mfilename('fullpath'));
% Find all other unit tests in unittest subfolder
unittests = dir([path filesep 'unittest_*.m']);
% Execture every unit test
for uu=1:... |
a2c7935344fed3e3b67bbd47d980bf38ddb41d2c9a0397b697686f26e0f854d6 | MATLAB | 631 | 21 | % reshape index from (chn x cond x conc) to just chn
% mlList is list of all (chn x cond x cond) and can be found in dcAvg.measurementList
% give list of conds, find all chn indx and conc belonging to cond list
function [reshapeIdx] = reshapeIdxByCond(condList,numConds,mlList)
numConc = 3;
numChns = size(mlList,2)/(... |
ba5cd2f828cb032c83de730fb0c3af4a546251097aa28c6e160460d59aa641dd | MATLAB | 631 | 16 | function ml = GetMeasurementList(handles)
global maingui
ml = [];
datatype = GetDatatype(handles);
if datatype == maingui.buttonVals.RAW || datatype == maingui.buttonVals.OD
ml = maingui.dataTree.currElem.GetMeasurementList('matrix', 1, 'raw');
elseif datatype == maingui.buttonVals.CONC
ml = maingui.dat... |
8b3c21fdfec23fa7886fe51b3c2fc604f3ba5fb873bca581cd56b16391cdac4e | MATLAB | 632 | 30 | function [activitymap2] = activity_map3(activitymap1,opt)
%ACTIVITY_MAP2 ´Ë´¦ÏÔʾÓйش˺¯ÊýµÄÕªÒª
% Generate mean activity maps for multiple neurons, with peaks in
% temporal sequence
% Opt == 1, peak values are normalized to 1
% Opt == 0, peak values are not normalized
[M1,B1] = max(activitymap1,[],2... |
8532e9ea355f184739245cb1159c00c2e3d54d663e064dc14158960d508ae32e | MATLAB | 633 | 19 | function analyse_behavior(p)
% Analyse the behavioral data of the MRI experiment by fitting a von Mises
% mixture model (vMMM) on the response errors. The main parameter of
% interest is the 'kappa'-parameter, which controls the dispersion of the
% fitted distribution and is therefore a measure of beahvioral precision... |
e63639ca7644ad28e9e32b233f167c6cadc74ce8264bc9a26a88dea5813d5652 | MATLAB | 633 | 16 | writeNPY(FL_CAM.times, 'fl_cam.npy')
writeNPY(Lft_ex.values, 'lft_ex.npy')
writeNPY(Lft_PPL.values, 'lft_ppl.npy')
writeNPY(Lft_whsk.values, 'lft_whisk.npy')
%writeNPY(Lick.values, 'lick.npy')
writeNPY(LPup_FC.times, 'lpup_fc.npy')
writeNPY(NI_PZO.values, 'ni_pzo.npy')
writeNPY(P_diode.values, 'p_diode.npy')
wr... |
0382c9df7ca84271fc5756ac6c76d046b290f07a26214a6a86eb01076be73cbe | MATLAB | 634 | 30 | function [activitymap2] = activity_map2(activitymap1,opt)
%ACTIVITY_MAP2 ´Ë´¦ÏÔʾÓйش˺¯ÊýµÄÕªÒª
% Generate mean activity maps for multiple neurons, with peaks in
% temporal sequence
% Opt == 0, peak values are normalized to 1
% Opt == 1, peak values are not normalized
[M1,B1] = max(activitymap1,[],2... |
2102850fc1e3515a09019c7c35869b6ae7ced0cb3c1dc2abfd51345026aebeea | MATLAB | 634 | 19 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : CHATENET Louis
% Date : 24/05/2018
% Updated : 30/05/2018
% Version : V2.0
%
% Description : AMPA current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Isyn, r, T] = IsynAMPAV... |
3f59d7f1c6232061eb3acfd16bb2f2946d54040de74ee9e7514b24400db6a220 | MATLAB | 634 | 20 | function wasSet = setVariblesFromJenkins()
% This function looks in the base workspace for varibles that where set by
% Jenkins. These vaibles have the name "name_" (underscore at the end), and
% set name = name_
% returns true if any varible was set, false otherwise.
% This is a non trivial implementation, but it... |
8fbcf9e2f8de4535572fb556ead23889a383d78056200beb8deca0ad61f978cc | MATLAB | 634 | 22 | function H = toHsv(data,occ,varargin)
% H = toHsv(data,occ)
% transforms matrix data into HSV image where brightness codes for values of the occ matrix
% data and occ are required to be of the same size
% H = toHsv(data,occ,[minVal maxVal])
% will normalize the values of 'data' matrix in the boundaries define by [minV... |
c02276be516317ac142cf1edaa60305757345f0d24dc5da762b28a9b1bdc902c | MATLAB | 634 | 28 | function [modRatio, prefPh, offSet, sse]= CosineFit(phase,linVar)
[estimates, model] = fitPhase(phase,linVar);
[sse, fitCurve] = model(estimates);
prefPh = estimates(3);
modRatio = estimates(2)/estimates(1);
offSet = estimates(1);
end
function [estimates, model] = fitPhase(xdata, ydata)
start_point = rand(1, 3);
... |
128d926fa99905d3402975d881a7cea4804bc5eeadcc80074604792a589ceaa7 | MATLAB | 635 | 16 | %writeNPY(FL_CAM.times, 'fl_cam.npy')
%writeNPY(Lft_ex.values, 'lft_ex.npy')
writeNPY(Lft_PPL.values, 'lft_ppl.npy')
writeNPY(Lft_Wsk.values, 'lft_whisk.npy')
writeNPY(Lick.values, 'lick.npy')
writeNPY(LPupFC.times, 'lpup_fc.npy')
%writeNPY(NI_PZO.values, 'ni_pzo.npy')
writeNPY(P_diode.values, 'p_diode.npy')
%w... |
342730f72efe2f23063d7c736d73c13c884b170ebec63fc6ffebae5e3ed943bf | MATLAB | 635 | 23 | % Sample Bullseye Creation
% Create the AHA 17-segment bullseye
figure;
c = createBullseye([0 0.5 1 0; 0.5 1 4 45; 1 1.5 6 0; 1.5 2 6 0]);
set(c,'Color','k','LineWidth',2)
% Example 1 of filling the bullseye, vector by vector
fillBullseye(rand(4,1),0.5,1,-45,315);
fillBullseye([0.25 0.35 0.25 1 0.25 0.5],1,... |
72e235254b3064f29ce48a1c7760c0eab7564501e077e572df8524cc600a1234 | MATLAB | 635 | 23 | function [thickavg, thickstd] = read_fs_thickness(fname)
% Read the ROUJ cortical thickness from Freesurfer output stat file.
% USE: [thickavg, thichstd] = read_fs_thickness(fname)
fid = fopen(fname,'r');
linenum = 53;
C = textscan(fid,'%s',1,'delimiter','\n', 'headerlines',linenum-1);
c = (C{1,1});
c = c{1};
X = spli... |
73573542ff889663dc8b6e0dca7b746c364b646c19a8e357305a23245dfa5e3b | MATLAB | 636 | 22 | function phi = angular_error(u, v)
% PHI = ANGULAR_ERROR(U, V)
%
% Compute the pointwise angular error between two velocity fields. U and V
% are supposed to be arrays of dimensions MxNx2. PHI is given in degrees.
%
% Author: Gunnar Farnebäck
% Computer Vision Laboratory
% Linköping University, Sweden
... |
88445a9604c9195e1140f9d8f380ed4e2fd60b7ad2c9f67a885d7e4bf789ed77 | MATLAB | 636 | 24 | function [response,ind,ts] = data2response(data,epoch)
BIN_SIZE = 50;
raster_params.time_before = 399;
raster_params.time_after = 1200;
raster_params.smoothing_margins = 0;
raster_params.align_to = epoch;
boolFail = [data.trials.fail] | ~[data.trials.previous_completed];
if strcmp(data.info.task,'choice')
boo... |
e63e7d46c89ce9fe36dd1493ddc8fbc661199ae2c4aa99a72bebd2ab0a1b1668 | MATLAB | 636 | 27 | function L = SpkTrainValuation(S,f,r)
% L = SpkTrainValuation(S,f,t,r)
%
% computes log-likelihood of spike train S with intensity function f.
% INPUTS:
% S: spike timings during test epoch
% f: a tsd describing the predicted intensity function during test epoch
% r: average firing rate during training ep... |
66771d53e2f3df2f64209c1432cb991b9b92bcf2b99fb9f85cf1241bdae74980 | MATLAB | 637 | 36 | function [tmp, mu] = covml(dat, nu, flag)
if nargin<3
flag = 0;
% flag = 0: subtract mean
% flag = 1: scatter only
end
if nargin<2
nu = 1;
% parameter for weighting function
end
[k, nobs] = size(dat);
datorig = dat;
if ~flag
mu = mean(dat,2)*ones(1,nobs);
error('not yet implemented');
else
mu ... |
1106cf85e7c77e0fd0f0ccdc51cf97c31cbfbbd7c44a38449fa5c9dbccd5e6bd | MATLAB | 638 | 27 | function s = rdivide(a,b)
% Overload of the ./ operator for two tsd objects
%
% USAGE:
% tso = rdivide(tsa,tsb)
%
% the ./ operaetor is defined to return a tsd with same timestamps and
% data that are the ratio of the data. Returns error if timestamps of the
% two object don't coincide
% copyright (... |
4a228178bd371019a1c44d1692c642dff4c548cc314445c0634e45d1fcc469aa | MATLAB | 638 | 29 | function convertpickles(varargin)
% convert fodlers and subfolders of pickles to mat files
% lloyd russell 2016
% select main directory
if ~numel(varargin)
directory = uigetdir();
else
directory = varargin{1};
end
% build file list
filelist = glob([directory filesep '**' filesep '*.pkl']);
num_files = numel(... |
499d4db65bfe4f21244c29b897465d646c6c43e488273bdecb8cc4698241e172 | MATLAB | 641 | 19 | function analyse_questionnaire(p)
% Load the data of the Vividness of Visual Imagery questionnaire (Marks,
% 1975) used for recruitment and plot the distribution of VVIQ scores. The
% upper and lower quartile of the distribution (marked in the plot) where
% used as recruitment pools for the strong and weak imagery gro... |
d19bac686034a1a797af4615918a213eea8aedb569eb0d3ec353669d2767db94 | MATLAB | 641 | 27 | function [c] = cellcovshift(x, shift, dim, flag)
% [C] = CELLCOVSHIFT(X, SHIFT, DIM) computes the covariance, across all cells
% in x along the dimension dim.
%
% X should be linear cell-array(s) of matrices for which the size in at
% least one of the dimensions is be the same for all cells
if nargin<4
flag = 1... |
26d2b815aaa9ecf952676db2ef5ee647fde149709ddc68992ef47c8da4428702 | MATLAB | 643 | 22 | function [split_stack] = split_stack(stack,nPlanes)
% Vectorised method
[nRows,nCols,nSlices] = size(stack);
slicesPerPlane = floor(nSlices/nPlanes);
nSlices = slicesPerPlane*nPlanes;
idcs = reshape(reshape([1:nSlices],nPlanes,slicesPerPlane)',[],1);
split_stack = stack(:,:,idcs);
split_stack = reshape(split... |
6fec9843ff21450f91e34c9efce8a610a87772aea3a8cdd281c27ef0468c3f67 | MATLAB | 643 | 24 | function [kden,N,K] = density_dir(CIJ)
% DENSITY_DIR Density
%
% kden = density_dir(CIJ);
% [kden,N,K] = density_dir(CIJ);
%
% Density is the fraction of present connections to possible connections.
%
% Input: CIJ, directed (weighted/binary) connection matrix
%
% Output: kden, d... |
80752b67ccf5394641b58747964bf70bbf3704408204921c098bccd61f7bfcdf | MATLAB | 643 | 21 | function [Cells] = significance_determine(DataOriginal,DataShf,thr)
%SIGNIFICANCE_DETERMINE ´Ë´¦ÏÔʾÓйش˺¯ÊýµÄÕªÒª
% DataOriginal mustbe n * 1 matrix
% DataShf mustbe n * repeatNum matrix
% Default threshold 1.65
if nargin <= 2
thr = 1.65;
end
d1 = ndims(DataShf);
data_mean =... |
35d12074a29deb219efc972df903aee25e3083b82d7ad482ac6d3de66e74847c | MATLAB | 644 | 21 | function accOut = calibAcc(accIn, para)
%CALIDACC calibrate accelerometer data based on input parameters
%
% INPUTS
% ACCIN: 3-D accelerometer data, unit g, N by 3 matrix
% PARA: Parameters for calibration
% 2 by 3 matrix
% -----... |
ad91dda80a387ffe376e79cd428777c045e44bbde81c5e0f5d685764f9d68f0a | MATLAB | 644 | 18 | writeNPY(FL_CAM.times, 'fl_cam.npy')
writeNPY(Lft_ex.values, 'lft_ex.npy')
writeNPY(Lft_PPL.values, 'lft_ppl.npy')
writeNPY(Lft_whsk.values, 'lft_whisk.npy')
writeNPY(Lick.times, 'lick.npy')
writeNPY(LPup_FC.times, 'lpup_fc.npy')
writeNPY(NI_PZO.values, 'ni_pzo.npy')
writeNPY(P_diode.values, 'p_diode.npy')
writ... |
0bb8b74020ab07a09a1b341f7122b4b145930a51ec7e51e2d4160b83ad71c584 | MATLAB | 645 | 19 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : CHATENET Louis
% Date : 24/05/2018
% Updated : 30/05/2018
% Version : V2.0
%
% Description : GABAa current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Isyn, r] = IsynGABAa2(d... |
1700b9ea06ddfd89fd5eda95a60184e5cd4b631424a97593c9c730e53c7c47e0 | MATLAB | 645 | 17 | function [estimates, model] = 1overXfit(xdata, ydata)
% Call fminsearch with a random starting point.
start_point = rand(1, 2);
model = @expfun;
estimates = fminsearch(model, start_point);
% expfun accepts curve parameters as inputs, and outputs sse,
% the sum of squares error for A * exp(-lambda * xdata) - ydata,
% a... |
3a34c3d7970ba89a9b3c397c5ab2c2ff078da884bc1db8383c8a5413e0451544 | MATLAB | 645 | 26 | %% Run PLS analysis %%
%% Read in data and functions
workdir='';
addpath(genpath('/dagher/dagher11/filip/Obesity_maps/scripts/'));
addpath(genpath('/dagher/dagher11/filip/Obesity_maps/data/'));
BMI='ABCD_CT_DKT_LH';
expr='ABCDbrainspanall'; % aba_limited_expression for UKBB and HCPA, ABCD_brainspan for ABCD, HCP_brai... |
4dd2b006a9ff49c3a23bc84df38c9b8b261aa1999fd94f6a2476600343fd8350 | MATLAB | 645 | 19 | function p = min_quadform(Qtot)
% P = MIN_QUADFORM(Qtot)
%
% Minimize quadratic forms according to equations 6.20 -- 6.24 in
% Gunnar Farnebäck's thesis "Polynomial Expansion for Orientation and
% Motion Estimation".
%
% Qtot - A collection of quadratic forms, having the size
% HEIGTH x WIDTH x N x N.
%
% ... |
701218864f1a668fad1490b0230d265d4d0c41bcdc59598cb55e8154d1271788 | MATLAB | 645 | 23 | function x_dot = interneuron(x,K,gNa,gK,gL,C,ENa,EK,EL,I)
% SOURCE: https://doi.org/10.1023/A:1008841325921
N = length(x)/3;
V = x(1:N);
h = x(N+1:2*N);
n = x(2*N+1:end);
m = 1 ./ (1+exp(-0.08*(V+26)));
hinf = 1 ./ (1+exp(0.13*(V+38)));
tauh = 0.6 ./ (1+exp(-0.12*(V+6... |
c259170d8a3c0ec2690140776d4cd9d23c3575bd7f087fc08b509969ba189ae7 | MATLAB | 645 | 25 | function modes = gtmlmode(net, data)
%GTMLMODE Mode responsibility for data in a GTM.
%
% Description
% MODES = GTMLMODE(NET, DATA) takes a GTM structure NET, and computes
% the modes of the responsibility distributions for each data point in
% DATA. These will always lie at one of the latent space sample points
% N... |
7b501208a5d2eec4d74a9bfb531ff65721b916bd75670d911f0e2cae642e4f15 | MATLAB | 646 | 30 | % 加载预训练模型
load('trainedSVMModel.mat');
load('TRCSPFilters.mat');
% 参数设置
fs = 250;
windowLength = 1 * fs;
buffer = zeros(windowLength, nChannels);
while true
newData = getNewEEGData();
processRealTimeData(newData);
end
function processRealTimeData(newData)
buffer = [... |
a113c675caff71e433e608213cedb17c65f42c54fed3873f4f88e85d47080dc4 | MATLAB | 646 | 36 | function p = bootstrapTTest(x,y)
% https://www.youtube.com/watch?v=N4ZQQqyIf6k&ab_channel=StatQuestwithJoshStarmer
REPEATS = 10000;
t_stat = @(x) mean(x)/(std(x)/sqrt((length(x))));
if nargin==1
scores = x;
else
scores = x-y;
end
inx_nan = find(isnan(scores));
if ~isempty(inx_nan)
disp(['Remove ' num2... |
089d81de9bea2bf1731597072feb6962bdf9a3cbe80f3cfdf1f18000ba3f0d0f | MATLAB | 648 | 31 | function A = shift(O, shift, TimeUnits)
% Shifts intervalSet
%
% USAGE:
% A = shift(A, shift, TimeUnits)
%
% INPUTS:
% A - an intervalSet object
% shift - the time to shift the intervalSet of
% TimeUnits - the time units of shift
% copyright (c) 2004 Francesco P. Battaglia
% This software is relea... |
11e0ba476a1d878b9837aae93d04cb6aa74b3051e43d246ffb7a7304f76d50a8 | MATLAB | 648 | 33 | function is = timeSpan(tsa, TimeUnits)
% Returns interval spanning the duration of a TSD
%
% USAGE
% is = timeSpan(tsa)
%
% INPUTS:
% tsa - a tsd object
% TimeUnits - the time units for the result
%
% OUTPUT:
% is - intervalSet containing the timestamp
% copyright (c) 2004 Francesco P. ... |
2651e125a7fa4a0231df809c507af527c3488517a765b208ddac99f82528062f | MATLAB | 648 | 32 | function [S,Y,YS,lbfgs_start,lbfgs_end,Hdiag,skipped] = lbfgsAdd(y,s,S,Y,YS,lbfgs_start,lbfgs_end,Hdiag,useMex)
ys = y'*s;
skipped = 0;
corrections = size(S,2);
if ys > 1e-10
if lbfgs_end < corrections
lbfgs_end = lbfgs_end+1;
if lbfgs_start ~= 1
if lbfgs_start == corrections
lbfgs_start = 1;
else
lb... |
4173c67c0854547eb3d22fb10ec5a4794c04d64e81d5850dd7e7bb91780d28a7 | MATLAB | 648 | 23 | function [n] = count(x)
% Returns the number of non-zero values in X
%
% N = COUNT(X)
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released under
% the GPL. See http://www.csbmb.princeton.edu/mvpa for more
% information.
%
% The Pri... |
ae150a68b16da2bf475ef56df41cda7a4feb98715c3e54ef31b79863fdb00b8f | MATLAB | 650 | 34 | function O = subsasgn(O, S, B)
% v = subsref(O, S) deals with { } assignments
%
% O{k} = B assigns the value B to key k. If key not existing item will
% be created
% copyright (c) 2004 Francesco P. Battaglia
% This software is released under the GNU GPL
% www.gnu.org/copyleft/gpl.html
if ~strcmp(S.type,... |
546114b7d5fef1a380bbae14f717e5ce62795391c086ef6bfc4c570200b1630d | MATLAB | 651 | 21 | %% Create timeseries for turbulence
clear all
data_path='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/timeseries/preprocessing/hc_tp1_sch400/';
input_path='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/timeseries/inputs_sch400/';
fnames=dir(data_path);
fnames=fnames(~ismember({fnames.name},{'.','..'}));
for s=1:12
load(... |
c3ca2c9dedaf40651542cb94fd3d2e17e607051093a1627c2e408cb9eeda27f7 | MATLAB | 651 | 20 | function refreshPrimarySleep(this, actigraphy)
% REFRESHPRIMARYSLEEP Update primary sleep elements from ACTIGRAPHY
%
% $Author: Peng Li
% $Date: Feb 29, 2026
%
ax = actigraphy.actiAxis;
ptH = actigraphy.Decoration.YAdjust;
delete(findobj(ax, 'Tag', 'PrimaryLine'));
delete(findobj(ax, 'Tag', 'PrimaryT... |
cb71fd1d026fd4529c9c14c642bb8d96718e581c058e2bc44db115cf5875ed71 | MATLAB | 651 | 21 | %% Create timeseries for turbulence
clear all
data_path='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/timeseries/preprocessing/hc_tp2_sch400/';
input_path='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/timeseries/inputs_sch400/';
fnames=dir(data_path);
fnames=fnames(~ismember({fnames.name},{'.','..'}));
for s=1:12
load(... |
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