sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
463ff451f11455e5cc32b2c93830ffac34a06a957a6109aa9be8b4b3160ee32e | MATLAB | 581 | 23 | function [pID,pN] = rst_FDR(p,alpha)
%
% p - vector of p-values
% alpha - False Discovery Rate level
%
% pID - p-value threshold based on independence or positive dependence
% pN - "Nonparametric" (any covariance structure) p-value threshold
%_______________________________________________________________________... |
cca3042f5b0b92884aeb8f0ca18641bf382db81c3b8d5dcca43ed34d0412b783 | MATLAB | 582 | 21 | data = clusters.all_gm;
figure
counts = 0;
for m = 1:size(data ,3)
for j = 1:size(data ,2)
counts = counts + 1;
for i = 1:size(data ,1)
aic(i, counts) = data{i,j,m}.AIC;
end
end
end
plot(aic, 'LineWidth', 1.5)
title( 'AIC For Various $k$ and $\Sigma$ Choices','Interpreter',... |
43e5e17d90e902acbf79e165f2297a0a09b5e9719a518fae791507899441f71c | MATLAB | 584 | 18 | load('./dataset.txt'); %matrice dei dati
featuresIndex = 1:10; %prime 10 variabili
dataSet = [ dataset(:,featuresIndex) dataset(:,end) ]; %una parte per l-analisi, l-atltro eliminato
[getSet, skipSet] = dataSetSplit(dataSet, 98);
dataSet = getSet;
[dataSet vMin vMax ] = dataSetNormalize(dataSet, 0.1, 0.9,1... |
5495c21759c52feec70e13ff3583a428c03114ddb5b946276a925871ba8435f1 | MATLAB | 584 | 15 | %% Get Input for the current time bin...
% Input: Events: Event matrix N*X. Entries are the event time for each
% neuron (indexed by row number)
% TimeN: Number of time bin
% dt: timestep
% N: Number of E or I neurons
% STASHED!!!
function InputVec = GetInputFromSeries(Events,TimeN,dt,N)
... |
c205398e5c45963eb7dbfc7b4e06113cb9048b0e63818701fc383a602e102857 | MATLAB | 584 | 18 | %plot of the 2 components of the 3-way PCA
function twocomponents(x,k)
figure
color=['r' 'g' 'b'];
[o,v]=size(x);
h=plot(x(:,1),x(:,2),'.');
set(h,'color',color(k))
set(gca,'XLim',[(min(x(:,1))-(0.05*(max(x(:,1))-min(x(:,1))))) (max(x(:,1))+(0.05*(max(x(:,1))-min(x(:,1)))))]);
set(gca,'YLim',[(min(x(:,2))-(0.05*(max(x(... |
e3a4880891208d994f9cd3692cbb4264225f5399480175487c5bc681aa0a3cf4 | MATLAB | 584 | 21 | function [ av_x,av_no_x ] = get_t2_avoid_trials_x(p, traces, evs, bvs, tis, speed_control)
%% calc scale factors per subject
for sub = 1:p.nSubjects
all_tr = cat(2,traces{sub,:});
vars(sub) = nanstd(all_tr(:));
end
scale_factors = 1./(vars / max(vars));
for sub = 1:p.nSubjects
... |
1574b103e1d12ee903db183211072737e1b6a34468f810834a918f18b75239be | MATLAB | 586 | 17 | function ok = sysCheck()
%SYSCHECK Check for required toolboxes
ok = 1;
boxen = {'Signal', 'Image', 'Statistics'};
reqs = cellfun(@(b) logical(license('test', [b '_Toolbox'])), boxen);
if ~all(reqs)
errmsg = ['You are missing the following toolboxes: ', strjoin(boxen(~reqs), ', ')];
... |
530f5b3fa5761e99649e02a429b10cb6beb416f58edd67941c17011274626cdb | MATLAB | 586 | 24 | function h = plot_line_edge(ax,x,y,W)
% x = 0:0.1:10;
% y = sin(x);
xd = gradient(x);
yd = gradient(y);
Lxy = (xd.^2 + yd.^2).^0.5;
xd = W .* (xd ./ Lxy);
yd = W .* (yd ./ Lxy);
R1 = rotz(90);
R2 = rotz(-90);
Edges1_XY = R1(1:2,1:2) * [xd ; yd];
Edges2_XY = R2(1:2,1:2) * [xd... |
2a2a33a9228616cb6871b3f3ed31ba747c7a1a70ad26b6e552baffebbe8fc8b6 | MATLAB | 587 | 30 | function [numberOfNeurons] = nonNEU (neuron, pathname, filename)
[filename, pathname] = uigetfile({'*.jpg;*.tiff;*.bmp;*.png;*.gif','All Images Files'}, 'Pick an image','Multiselect','on')
nu=length(filename)
numberOfNeurons = zeros(nu, 1);
if iscell(filename)==1
for k = 1:nu
slice=imread... |
a4a50eae84618e2f2224f1744fab701c6be33875b227fce29824613331dfd5ba | MATLAB | 587 | 21 | function AddTableRowHTML(obj, row, style, lastrow)
% A member function of HTMLGenerator for adding rows to an HTML table
% Reza Sameni, Sep 2020
% The open-source electrophysiological toolbox (OSET)
% www.oset.ir
%
if(obj.fid)
fprintf(obj.fid, '\n\t\t\t\t<tr>');
for k = 1 : length(row)
if(style{k} == 'H... |
3e340fd35fdff02be45cfdad6c3b52e5c7e0f556406266f8cb1a9d218d474d2a | MATLAB | 588 | 21 | function stationarity = moduleStationarity(S, c)
%% parameter and output
% stationarity: stationarity of community c in S_pxT
% S: overall community structure
% c: index of the community of interest
tS = S;
tS(tS~=c) = 0;
tS(tS~=0) = 1;
existIdx = any(tS);
tMin = find(existIdx,1,'first');
tMax ... |
a5340f4c954673ff0aab82d10e0862a545bfe399c2cbd69a8bfa00ba3067be3f | MATLAB | 588 | 22 | function reorderClusters(obj, by)
%REORDERCLUSTERS Reorder clusters by centroids
if nargin < 2
by = 'clusterSites';
end
argsort = obj.hClust.orderClusters(by);
if issorted(argsort)
jrclust.utils.qMsgBox('Clusters already in order');
return;
else
nChanged = sum(a... |
1368b29e00a357be9275f342cb7f8e442c8ada24840cce9a7e9214488ceebeda | MATLAB | 589 | 25 | function y = fatrix2_do_forw(ob, x)
%function y = fatrix2_do_forw(A, x)
%|
%| implement 'forw' function: A * x
%| in array mode, accounting for idiag, odiag, scale
x = fatrix2_apply_diag(x, ob.idiag); % [idim *L]
y = ob.handle_forw(ob.arg, x); % [odim *L]
y = fatrix2_apply_diag(y, ob.odiag); % [odim *L]
if ~isequal(... |
37a72c74a123517ccf8eee04d18a203a42485d5b394e4f6adee7fe674a7c1f62 | MATLAB | 589 | 30 | function [ output_args ] = compareMovies(start,stop,FPS,varargin)
nMov = length(varargin);
x = ceil(nMov/3);
y = ceil(nMov/x);
f = figure('WindowStyle','normal','Position',[100,200,y*500,x*400]);
cvals = [];
for i = 1:nMov
cvals(i,1) = min(varargin{i}(:));
cvals(i,2) = max(varargin{i}(:));
end
%cvals = [.3 .7... |
1d2324276c3798865b31c15be249cba308b54fa4126436d14d97599f22960449 | MATLAB | 590 | 17 | function multiple_boxplot_vec(dataVec,groupIdx,xlab,M)
% data is a cell matrix of MxL where in each element there is a array of N
% length. M is how many data for the same group, L, how many groups.
%
% Optional:
% xlab is a cell array of strings of length L with the names of each
% group
%
% Mlab is a cell arr... |
8a901e618aa381c08d67877a725ebfd74d8df342c11bdd621c2aba1a2147d9c9 | MATLAB | 590 | 27 | function f = correct_fid_lana(f)
for k = 1:length(f)
fid = f(k).water_ref.fid;
sw = f(k).spectrum.SW_h;
np=size(fid,1);
timeD=transpose(0:1/sw:(np)*1/sw-1/sw);
RtermLor=exp(-timeD/0.15);
ywat = transpose(fid);
[mConAmpCor mSPhase mT2used] = LineShapeExtract(ywat,sw);
fidcor = transpose(LineSh... |
3295e146beaa3956bfc0801d26aca1d9b42fd9df273d26ea6925a0a9a6391be6 | MATLAB | 591 | 27 | function sn(data,filename,voxdims, origin)
% function sn(data,filename,voxdims,origin)
%
% Save a nifti file with an empty header
if nargin < 3
voxdims = [1 1 1];
end
if nargin < 4
szData = size(data);
switch length(szData)
case {3,4,5}
origin = szData(1:3)/2+1;
cas... |
5ec1120e23730fa0522f174fb7aad8710a0b80bff249e7fab31d9a959c1c4c71 | MATLAB | 591 | 26 | function [quantized, gain, bias] = approximate_quantizer(data, gain_mode, bias_mode)
switch bias_mode
case 'zero'
bias = 0;
case 'mean'
bias = mean(data(:));
case 'median'
bias = median(data(:));
otherwise
error('Undefined bias calculation mode.');
end
data = data - bia... |
a6fbe40fd567ccb1d601b7596d477e3672952897f1826b6330e832bd6ea7ab5a | MATLAB | 591 | 15 | function check_single_channel_detection(EEGBroadband, EEGNarrowband, ChannelIdx, CriteriaSet)
DataBroadband = EEGBroadband.data(ChannelIdx, :);
DataNarrowband = EEGNarrowband.data(ChannelIdx, :);
SampleRate =EEGBroadband.srate;
Cycles = cycy.detect_cycles(DataBroadband, DataNarrowband);
AugmentedCycles = cycy.measur... |
22a0c80acd2a276d824d5b859f192ff0898e8a38c835457eea2ee687f32769de | MATLAB | 592 | 21 | function auto_derived(app)
%AUTO_DERIVED Summary of this function goes here
% Detailed explanation goes here
if ~isempty(app.data)
if isempty(app.burst_ints)
[~, idx] = max(vertcat(app.data.tic_multipl));
bords = [app.data(idx).ts(1), app.data(idx).ts(2)];
app.burst_ints = struct('name','... |
6e167993442687e51d99e30ea9997caba72b0a96b27b9ea892ed2e5bb2d1ded3 | MATLAB | 592 | 28 | function moveback(hax_or_h,h)
% function moveback([hax],h)
% move h back by one
if nargin < 2 || isempty(hax_or_h)
h = hax_or_h;
hax = gca;
else
hax = hax_or_h;
end
axkids = get(hax,'Children');
n_axkids = length(axkids);
for i=1:n_axkids
if axkids(i)==h
ih=i;
break;
end
end
if isempty(... |
e85cd39adc3da83ea592390c0b25febb54d4e8737b5eb9c22557bdb62f375e4a | MATLAB | 592 | 22 | function updateSubset(obj, showSubset, silent)
%UPDATESUBSET Update the subset of units to show
if nargin < 3
silent = 0;
end
showSubset = intersect(1:obj.hClust.nClusters, showSubset);
if isempty(showSubset) && ~silent
jrclust.utils.qMsgBox('Subset is empty; selecting all units');
showSubset = obj.showSu... |
2e7ec3082828da419361a3c1895ceb548bd452e1af91876c7bb471993b335bb7 | MATLAB | 593 | 21 | function vals = linmap(vals, oldLim, newLim)
%LINMAP Rescale vals occurring within oldLim to newLim, saturating at
%the boundaries
if numel(oldLim) == 1
oldLim = abs(oldLim)*[-1, 1];
end
% saturate at the boundaries
vals(vals > oldLim(2)) = oldLim(2);
vals(vals < oldLim(1)) = oldLim... |
55bda8c3cb84a28c995ea0a3854059d07fd72b8cc08a1c7e61b1a3396aac4697 | MATLAB | 593 | 18 | function [ql,qu]=rst_idealf(x)
% Compute the ideal fourths for data in x
% The estimate of the interquartile range is:
% IQR=qu-ql;
% Adapted from Rand Wilcox's idealf R function, described in
% Rand Wilcox, Introduction to Robust Estimation & Hypothesis Testing, 3rd
% edition, Academic Press, Elsevier, 2012
% Cyril P... |
e91f90c925c2c76d2be56735369cb15e6b55f80db9cedd03619d85415485224f | MATLAB | 593 | 41 | function fo=add_zer_line(f,fac)
lb=2;
lineposition = -4.7; %-4.65;
lineposition = -4.65;%4.65;
fo =f;
for nf = 1:length(f)
spec = f(nf).spectrum;
t=[0:spec.dw:(spec.np-1)*spec.dw]';
fid = f(nf).fid;
sfrq = spec.cenfreq;
ns = size(fid,2)/2;
if ns<1
fid2 = fid;
else
fid1 = fid(:,1:ns... |
f5870773fc088a52243d1ae23a1b87a9efc676ea2240f2007cd4ab79a2bca41f | MATLAB | 596 | 19 | function auto_bp(app)
%auto_Bb checks if bb is already detected and runs if
%not
% Detailed explanation goes here
if isempty(app.bp_res)
[data,ts,~, ~] = current_signal(app, app.settings.channel_idx.bldp);
data = lowpass(data,3,1/ts(1));
[ footIndex, systolicIndex, notchIndex, dicroticIndex ] = ...
... |
60319e1261fe412e0c66c9aed6ed061d091a1399f38acf14988f52b360ab8825 | MATLAB | 597 | 25 | function [W, lambda] = orthogonal_gevd(A, B)
if size(A, 1) ~= size(A, 2) || size(B, 1) ~= size(B, 2) || size(A, 1) ~= size(B, 1)
error('A and B must be square matrices of the same size')
end
n = size(A, 1);
W = zeros(n);
lambda = zeros(n, 1);
A_proj = A;
B_proj = B;
for k = 1 : n
[v, lambda(k)] = eigs(A_pro... |
9a44050eeb6587d109cf85e9a29d5df16df14c131570478cf7482a7324aceb6b | MATLAB | 597 | 24 | function pars = mats2pars(Amats, doInv)
% Convert affine matrices to rigid-body motion parameters
if nargin < 2
doInv = 0;
end
pars = zeros(6,size(Amats,3));
for iV = 1:size(pars,2)
if doInv==0
thesepars = spm_imatrix(Amats(:,:,iV));
elseif doInv==1
thesepars = spm_imatrix(inv(Amats(... |
d9fea7f8746bcedb719309515ba94bb1ee1ed42d9371cef26071c187589c74ac | MATLAB | 597 | 14 | function [ms_frame,ms_frame_advance,nsamps_frame,nsamps_frame_advance] = get_ms_framespec(ms_framespec,fs)
if length(ms_framespec) == 2
ms_frame = ms_framespec(1); ms_frame_advance = ms_framespec(2);
else
all_ms_framespecs = get_all_ms_framespecs();
idx = strmatch(ms_framespec,all_ms_framespecs.name);
if isemp... |
d6e033defdf985e718f24af289e820f28ac171bba584b95337bf15db8eee9ea7 | MATLAB | 598 | 27 | function [H, overlap] = overlapCI(means, CIs)
nVals = numel(means);
if nVals ~= numel(CIs)
error('must provide equal number of means and CIs')
end
overlap = nan(nVals);
H = overlap;
for ival1 = 1:numel(means)
for ival2 = ival1+1:numel(means)
temp_means = means([ival1,ival2]);
temp_... |
10c9ec9ffef322bfc2d21137d234f2effaf6764d9374746c5cb07306f0595cb4 | MATLAB | 602 | 17 | % function that builds a table to save ti as CSV
% from several data cells of Raster Features
% Input
% RASTER_NAME: cell with ExpIDs
% RASTER_FEATURES: cell of rastrfeatures
% Names_Conditions: cell of Condition Names
function TableFeatures=maketableraster(RASTER_NAMES,RASTER_FEATURES,Names_Conditi... |
31c9dfb98f911b8443b917053f896be961443eb52c71783a7954d87f1fdc9cb1 | MATLAB | 602 | 21 | function movie = cropMovie(movie,zeroMask)
% crops movie (i.e. sets borders to zero), such that every row or column that
% is zero because of motion correction for some frame is set to zero for
% all frames
[N, S, W, E] = getCropCoords( zeroMask );
% getCropCoords gives the values that are included in the... |
b28e9297ad639af595520384dc75ee4fe3ccc2ca849010dfd53c392f50ecf2e9 | MATLAB | 603 | 30 | function F=get_files_recursif(in_dir)
F=[];
for nbdir =1:size(in_dir,1)
cur_dir = deblank(in_dir(nbdir,:));
DD = dir(cur_dir);
DD=DD(3:end);
for i=1:size(DD,1)
if ( DD(i).isdir )
F = [F;get_files_recursif( fullfile(cur_dir,DD(i).name) )];
else
[pathstr,filename,ext] = fileparts(DD(... |
d985d5b8b5547f646dcddbd45a9480251a303e32779781eacd1bf9186bbe8455 | MATLAB | 603 | 18 | function [fs,dyename,NV,NC]=ExperimentSize(NumberofVideos,FN)
%% Read Sampling Frequency
fs=NaN; % To read fs to get into the following loop:
NV=1;
while isnan(fs) % Interface error user reading fs
fs = inputdlg('Sampling Frequency [Hz] : ',...
'Frames per Second or', [1 75]);
fs = str2double(f... |
6c759f86081022146189541e343168fa8abce3f88a37cb966b7285efea6973b3 | MATLAB | 604 | 17 | function beat_spk_lag = get_spike_lag(spike_ts, spike_clust,spike_use, hb_ts, beats_use, int_idx)
spike_ts = spike_ts/1000;
num_clus = max(spike_clust);
spks = {};
spike_use = spike_use(:,int_idx);
hb_ts = hb_ts(beats_use(:,int_idx));
for i = 1 : length(hb_ts)
spks{1,i} = spike_ts(spike_ts>=(hb_ts(i)-0.5) & spike... |
7fef112bee2c800f9964c936c67725743be7a21acbbee1dc98fe87d621df629b | MATLAB | 604 | 4 | function [PeakToPeak_corrected, PeakToPeak_differences, matched_peaks_indexes, smoothed_matched_output] = SMFPeakDetector(x, matched_template, type, wlen, PP_diff_wlen, PP_diff_th, average_peak_det_rate, fs)
% SMFPeakDetector has been deprecated. Use peak_det_matched_filter_pwr_env instead.
warning('SMFPeakDetector ha... |
14c506b04ff13a539950bef3594eb7453a19d06a81ea44486078db66b0f20a1c | MATLAB | 605 | 19 | function index = ML_gaussian(x,mu,inv_sigma)
% function index = ML_gaussian(x,mu,sigma)
% x is a vector drawn from some multivariate gaussian
% mu(i,:) is the mean of the ith Gaussian
% sigma(:,:,i) is the covariance of the ith Gaussian
%
% Returns the index of the Gaussian with the highest value of p(x).
N = size(mu... |
4c604cadd28efa6ef1c13d14a39aff497638ffd3f7ca06a25f38507adcb295e0 | MATLAB | 605 | 19 | function [ F, pValue, df1_total, df2_total] = granger_causality_group( X, Y, maxLag)
[n, m] = size(X);
SSR_Y_Total = 0;
SSR_XY_Total = 0;
df1_total = 0;
df2_total = 0;
for i = 1:m
[~,~,SSR_Y, SSR_XY, df1, df2] = granger_causality(X(:,i), Y(:,i), maxLag);
SSR_Y_Total = SSR_Y_Total + SSR_Y;
SSR_XY_To... |
a6654902a13d9aa25f68583dcf0572de4e6d7552e4616d8af48099e0932db78f | MATLAB | 605 | 21 | function updateProjection(obj, proj)
%UPDATEPROJECTION Update the feature projection
try
obj.hCfg.dispFeature = proj;
catch
obj.hCfg.dispFeature = 'vpp';
end
% set menu items checked or unchecked where appropriate
hProjMenu = obj.hMenus('ProjMenu');
for i = 1:numel(hProjMenu... |
23404e6d0ce87cb24c7057c0ca5e0eebd09d1ecd90d591533317fd6e7c68bc39 | MATLAB | 606 | 12 | function all_ms_framespecs = get_all_ms_framespecs()
i = 0;
i = i + 1; name{i} = 'less narrowband'; ms_frame(i) = 18; ms_frame_advance(i) = 1.5;
i = i + 1; name{i} = 'narrowband'; ms_frame(i) = 36; ms_frame_advance(i) = 3;
i = i + 1; name{i} = 'more narrowband'; ms_frame(i) = 72; ms_frame_advance(i) = 3;
i = i + ... |
564514ec9ad0281deb39ef7f6cc9139d705f4ce2be17ac79719269dafc57268c | MATLAB | 606 | 28 | %% load movies
thisSub = 13;
ses = 1;
% preprocessed
movPath = fullfile(p.rootDir,'miniscope', ['subject' num2str(thisSub)],['session' num2str(ses)],'preprocessed','preprocessedMovie.h5');
movie = loadMovie(movPath,1,150);
% no lowpass
movPath = 'G:\E7_2DAA\results\preprocessedMovie_no_lowpass.h5';
movie_nl = loadMov... |
b5c97ae12cbb8a3da02e2aa8f63d9fc93f34bb745f4623f50fb586dd47070fe7 | MATLAB | 606 | 25 | function res = endSession(obj)
%ENDSESSION Finish curating and return results
if obj.isWorking
dlgAns = questdlg('An operation is in progress. Really quit?', 'Operation in progress', 'No');
if ~strcmp(dlgAns, 'Yes')
return;
end
end
obj.isEnding = 1;
if nargout ==... |
99ddc4c7bc50c83978a8e3a2db8f999fd01dc0e009ae07ebc57552ea81516a04 | MATLAB | 607 | 19 | function criteriaset_diagnostics(Diagnostics)
CriteriaLabels = fieldnames(Diagnostics);
isUnique = contains(CriteriaLabels, 'Unique');
CriteriaLabelsUnique = CriteriaLabels(isUnique);
CriteriaLabelsUnique = replace(CriteriaLabelsUnique, 'Unique', '');
CriteriaLabels(isUnique) = [];
Diagnostics = cell2mat(struct2cell(... |
89d2037271da76e8ec1fcb1740b44f8e0d88015d2b9afd42ce06d2b04f077f01 | MATLAB | 608 | 19 | function [weights, trainerr] = cnntrain(layers, weights_in, params, train_x, train_y, type)
if (length(size(train_x)) == 3)
% insert singletone maps index
train_x = permute(train_x, [1 2 4 3]);
end;
tic;
if (strcmp(type, 'cpu') || strcmp(type, 'gpu'))
[weights, trainerr] = cnntrain_mex(layers, weights_in, para... |
8339e4dbacc5a9f60be0740efe4f2320fe881fa896a4bdf29c805beca2932b01 | MATLAB | 609 | 29 | function surf_jet
%SURF_JET Set up extreme color values using COLORMAP JET
%
%Syntax
% surf_jet
% Copyright 2004-2005 Paul Leopardi for the University of New South Wales.
% $Revision 1.10 $ $Date 2005-06-01 $
% Documentation files renamed
% $Revision 1.00 $ $Date 2005-02-12 $
%
% For licensing, see COPYING.
% For refe... |
92fc8cb60f79773d64d2f3b18597dd76d61240b67693051451b23ead67b9f1b0 | MATLAB | 609 | 34 | clear
close all
mat_file_after_converting ={
% 'HB329.mat';
% 'HB330.mat';
% 'HB438.mat';
% 'HB593.mat';
% 'HB594.mat';
% 'HB597.mat';
'HB442.mat';
'HB328.mat';
};
tubemap_folder_list ={
% 'HB329/';
% 'HB330/';
% 'HB438/';
% 'HB593/';
% 'HB594... |
9cf4709ca2ec5652c39aa54b7524dc79bced287a209d38b0c57cfa51a987c49a | MATLAB | 609 | 28 | function angle = calculate_ecg_angle(A, B)
% function angle = calculate_ecg_angle(A, B)
% Formula: atan2(A, B) (degree)
% Computes the angle (in degrees) between two ECG signal components
%
% Inputs:
% A: numerator component
% B: denominator component
%
% Outputs:
% ang... |
cd8de25178de4feae4405eb9e49a7f651f502f1b3a975128fd32c42805565874 | MATLAB | 609 | 19 | %Shinjini Kundu (c) 2022
function [average, lowerCI, upperCI] = classification_compute_CI(vector,T)
%computes confidence interval for a vector assuming normal approximation of the binomal
%inputs: vector the vector of values
%outputs: mean mean
% lowerCI lower range of the 95% con... |
ede2e8e8dc62623fedd37fe2aaf42ec438562fc22e62d2216c932f52e4e8a327 | MATLAB | 609 | 23 | options.color_area = [0.85, 0.85, 0.85];
line_style_MFS = '-o';
hf = figure(4);
clf
ha = axes();
h = plot(1, 1, '-', 'Linewidth', 2);
h.Visible = 'off';
hold on
h = plot(1, 1, line_style_MFS, 'Linewidth', 2);
h.Visible = 'off';
patch = fill(...
[0.2, 0.6, 0.6, 0.2],...
[0, 0, 0.5, 0.5],...
options... |
7a9987a241e6065791881733708379cae5f41d82a331f74e5836cbb00b151201 | MATLAB | 610 | 19 | function [ql,qu]=idealf(x)
% [ql,qu]=idealf(x)
% Compute the ideal fourths for data in x
% The estimate of the interquartile range is:
% IQR=qu-ql;
% Adapted from Rand Wilcox's idealf R function, described in
% Rand Wilcox, Introduction to Robust Estimation & Hypothesis Testing, 3rd
% edition, Academic Press, Elsevier,... |
70c8d4ac8b93e26d65dffd8e54fe6a72952552814034344c55e447fab6f3c47c | MATLAB | 612 | 20 | %%
clear
[file, path] = uigetfile('*.mat');%When the user clicks the load data button, a window should open to enable the user to select a file.
datafile = fullfile(path, file); %save path
load(datafile)
cd(path)
close all
clc
%%
for x = 1:size(clusters.mean, 1)
all_data = [];
clusters_name = ['cluster_' num2st... |
7619b1db0d99a3b84fbbff4f342153762596158218704647b2f061c4b07497b8 | MATLAB | 612 | 18 | function [ica_filters, ica_traces] = compute_ica_pairs(spatial, temporal, S, height ,width, ica_W)
% Compute ICA pairs
ica_traces = ica_W*diag(S)*temporal;
ica_filters = ica_W*spatial;
% Format the ICA dimensions for output
ica_traces = ica_traces'; % [time x IC]
ica_filters = reshape(ica_filters, size(ica_W,... |
ae88f6dd2cad259c2b4096ca71a74d2f6d667aeb3824baf28c23de50473838af | MATLAB | 612 | 17 | function [out, lims] = zeroCrop(data)
% up to 3D, crop out edge zeros
lims.xMin = find(any(any(data(:,:,:,1),2),3),1,'first');
lims.xMax = find(any(any(data(:,:,:,1),2),3),1,'last');
lims.yMin = find(squeeze(any(any(data(:,:,:,1),1),3)),1,'first');
lims.yMax = find(squeeze(any(any(data(:,:,:,1),1),3)),1,'last');
lim... |
0ac6b0e2b6e48c2223a66031a900e06d4a619742d6751e35a074962c3bd6ceb6 | MATLAB | 613 | 19 | %split before and after
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
for i = 1:length(datafile)
load(datafile{1,i});
if iscell(all_data)... |
da49f51ab59c4d104a49ae62cd220f6d8f22a403fd30e554a76ab916d47600cd | MATLAB | 613 | 18 | function [ traces ] = fix_traces_2daa( traces )
% fix for M11S7 (dropped frames 2 times -> add nans)
% recording xml file indicates dropped frames:
% 46357 - 46369
% 46480 - 46491
% insert one big nan block (also take out frames between the 2 drops)
% recording is good until first drop: 1:1159... |
f0dbc7f8c7ee790d6ad1e7c9d3901e69274cb5caa95beafd3d74a5575d5a3887 | MATLAB | 613 | 20 | function [stderrmean] = SEM(signal,dimension)
% Created by: Anya Krok
% Created on: 26 June 2018
% Description: calculate standard error of mean
%
% [sem] = SEM(signal,dimension)
%
% INPUT
% signal: matrix to analyze
% dimension: 1 or 2
% if dim = 1, then SEM returns row vector containing SEM of t... |
e08be4878049129f0e0040c6027b08a61a4f6d7d8fd96d85ba9f2f7da3f495f9 | MATLAB | 614 | 26 | function dspPMapColorbar(LevelList)
cla
nNegContours = sum(LevelList < 0);
nPosContours = sum(LevelList > 0) ;
axis([0 (nNegContours+nPosContours) 0 1]);
for i = 1:nNegContours
colc = (i-1) / nNegContours;
col = [colc colc 1];
patch([i-1 i i i-1],[0 0 1 1],col);
end
for j = ... |
94b9251e350f8ba55341c620699dc3cad9aeb0cfe3b46bc4cabf48cb730d5dc9 | MATLAB | 615 | 14 | global Vinj V0 gamma
Vinj = 1; % (mm^3)
lambda_iv = 0.837; %(day^-1) based on in vitro fit to the average
DT_invitro = log(2)/lambda_iv*24; % (hours)
convPhotCell = 10; % 1 cell \simeq convPhotCEll photons/seconds
convPhotMm = convPhotCell*1e6; % 1 mm3 \simeq convPhotMm photons/seconds
phot2cell = @(x... |
89382e4bcf7a256b5696ff9cc9ba7f51e05d5858a774f48e547b99e3427ef85f | MATLAB | 616 | 20 | function [stderrmean] = SEM(signal,dimension)
% Created by: Anya Krok
% Created on: 26 June 2018
% Description: calculate standard error of mean
%
% [sem] = SEM(signal,dimension)
%
% INPUT
% signal: matrix to analyze
% dimension: 1 or 2
% if dim = 1, then SEM returns row vector containing SEM of t... |
1a52f482366b66c38af079292a9e184d50dd06c80ec4687794ed3ab0aade5435 | MATLAB | 618 | 18 | function [spikeWindows, indices] = interpWindows(spikeWindows, nIterp)
%INTERPWINDOWS Interpolate windows subpixel-wise using FFT method
if nIterp <= 1
return;
end
nSamples = size(spikeWindows, 1);
% interpolation done on first non-singleton dimension but we assume
% columnwise; force w... |
72a57dcf53fea2c0c57a56f5af32b47b6d2162744b4b81c8b1949cff4cc6ce71 | MATLAB | 618 | 24 | function mmil_struct2csv(info,fname,separator)
%function mmil_struct2csv(info,fname,[separator])
%
% Required Input:
% info: struct array
% fname: output file name
%
% Optional Input:
% separator: separator between columns
% {default: ','}
%
% Created: 10/17/14 by Don Hagler
% Prev Mod: 01/30/15 by Don Hagler
... |
858f4c2548772e07e175b79cda903e3f60e5fa29f26ea23cdc08f419b8c8d674 | MATLAB | 618 | 22 | function auto_derived(app)
%AUTO_DERIVED Summary of this function goes here
% Detailed explanation goes here
if ~isempty(app.data)
if isempty(app.burst_ints)
[~, idx] = max(vertcat(app.data.tic_multipl));
[~,ts,~, ~] = current_signal(app, idx);
bords = [ts(1), ts(2)-ts(1)];
app.bu... |
887e2e980591f57ce981cc00f29d298d25110b44e19e2322f6e3659dbd0676e6 | MATLAB | 618 | 15 | %% Example 1: Visualize neural states with DataHigh
% The dataset corresponds to Section 3.1 in the DataHigh JNE paper.
% Each datapoint represents a trial. Trials are separated into seven
% different reach directions (colors). The space was reduced
% from 61 neurons to 7 latent dimensions with factor analysis... |
831ce06e2b557534848c0c1e2e0d31cb7a8a50883d0bf1c19e8c88eebf4eb5a7 | MATLAB | 619 | 20 | clear
close all
clc
fname = 'ICARE_0097_20000102_185034_segment';
load(fname, 'signal', 'sampling_rate', 'channel_names');
signal = signal(:, 1:10000);
save('sample.mat', 'signal', 'sampling_rate', 'channel_names');
% Save the raw data matrix in CSV format
fout_csv = 'sample_raw.csv';
writematrix(signal', fout_csv)... |
0bdba8b123dd9faa0ee6c34666d0166e352c834c73e0580a25fe6cc8cebc3f41 | MATLAB | 620 | 22 | function syn = getsynapses(map,threshold)
%% Use the getpaths() function on a binarized map.
% Use getpaths() on a binarized map to get the minimal number of synapses
% between any two nodes i and j.
%
% syn = getsynapses(map,thr)
%
% Input:
% map: projections matrix (uni- or bilateral)
% threshold: for filt... |
a6a6c72e14c581fdaf32f61505a77911889fb46633a729d43ef88bf7fe336912 | MATLAB | 620 | 15 | function [hp] = drawTransformedBat(posBat, orientBat, batFaces, batVertices)
batVerticesRot = ( rotz( orientBat(3) ) *roty( orientBat(2) ) * rotx( orientBat(1) ) * batVertices' )';
batVerticesTrans = ( batVerticesRot' + posBat )';
drawTriad( posBat, orientBat, 0.10 );
hp = patch('faces', batFaces,... |
a99782cede95937ff97d66218acb10d8acd393b45d7c4ba6f19f4273e23b6327 | MATLAB | 620 | 28 | function [h] = seplot3(dt,data,color,ebars)
%[h] = splot(dt,data,color,ebars)
if(nargin<4)
ebars = 0;
end
if(nargin<3)
color = 'b';
end
if(numel(dt)==1)
t = dt*(1:size(data,2));
else
t = dt;
end
h = plot(t,nanmean(dat... |
756f989166f48525fd22cbd5170457849b09e2e91be5a3759a5ca7170c17930d | MATLAB | 621 | 4 | function [penalty_factor, cc, ee, L_curveC, L_curveE] = OptimalSmoothnessFactor(xx, bb, ss, mode, SmoothnessFactor, penalty_factor0, signorm, ACCURACY, MAX_ITERATION, FORGETTING_FACTOR, LCurveSweepLength, LCurveSweepFator)
% OptimalSmoothnessFactor has been deprecated. Use optimal_smoothness_factor instead.
warning('Op... |
771683d9429f89d36e1b95224ee7146af3dec32646b4aeeae88067a0c41e9b59 | MATLAB | 621 | 25 | function path_out = filepartsx(file_or_folder_path,N)
%filepartsx Applies fileparts() function numerous times
%
% path_out = sl.dir.filepartsx(file_or_folder_path,N)
%
% Small function to help clean up stripping of the path.
%
% INPUTS:
% -------
% file_or_folder_path : path to file or folder
% N ... |
8844b264190d0cf3db82229d86280776cebd3adc5b238d714fcd1e80852df15e | MATLAB | 621 | 23 | function auto_derived(app)
%AUTO_DERIVED Summary of this function goes here
% Detailed explanation goes here
if ~isempty(app.data)
if isempty(app.burst_ints)
[~, idx] = max(vertcat(app.data.tic_multipl));
[~,ts,~, ~] = current_signal(app, idx);
bords = [ts(1), ts(2)-ts(1)];
app.bu... |
10f204e3da802293a59edd1af537cb0ed85c3aed6b3c385edd411e426e105be4 | MATLAB | 622 | 18 | function check_WC_params(par)
if isfield(par,'features') && strcmp('features','wav')
if isfield(par,'scales')&& isfield(par,'par.w_post') && isfield(par,'par.w_pre')
L = wmaxlev(par.w_pre+par.w_post,'haar');
if L<scale
error('[par.scale] exceeds maximum wavelet decomposition level... |
71bdeb3a599834ff22dc8001f719ad846d6adef3014427b212c1d83a49fdf2d9 | MATLAB | 623 | 17 | function [Rep_part,Diag_Par,SIM,ML_rep_part,consensus_idx,ML_rep_part_ALL,ALL_consensus_idx] = Analyse_MSP(S)
D = squeeze(mode(S,2)); % group partition for each ML partition
[Rep_part, consensus_simm, pairwise_simm,consensus_idx,ALL_consensus_idx] = Find_Consensus_VIn(D);
SIM.Consensus = Rep_pa... |
8c308284cd5aae351c2b65e844fa52d377094b1ef1c0ae14a977d2634642951e | MATLAB | 623 | 23 | function XxPSFGenerator(dxy,dz,SizeXY,SizeZ,lamd,NA,RI,FileName)
dk = 2*pi/dxy/SizeXY;
kx = (-(SizeXY-1)/2:1:(SizeXY-1)/2)*dk;
[kx,ky] = meshgrid(kx,kx);
kr_sq = kx.^2+ky.^2;
z = (-(SizeZ-1)/2:1:(SizeZ-1)/2)*dz;
PupilMask = (kr_sq<=(2*pi/lamd*NA)^2);
kz = sqrt((2*pi/lamd*RI)^2-kr_sq).*PupilMask;
for ii = 1:SizeZ
... |
e3cdd353a2b190e58be845e3ef1b39dd645cf24867fca26c66a5666166164cbc | MATLAB | 623 | 23 | function dist=JSDiv(P,Q)
% Jensen-Shannon divergence of two probability distributions
% dist = JSD(P,Q) Kullback-Leibler divergence of two discrete probability
% distributions
% P and Q are automatically normalised to have the sum of one on rows
% have the length of one at each
% P = n x nbins
% Q = 1 x n... |
06a13ec9945a3bdcc63a919342049ee97d36b40467126acfbcb208ea1fdf6c5a | MATLAB | 624 | 13 | function stop = makeLogVertAx(state, whichAx)
stop = false; % The function has to return a value.
% Only do this once, following the 1st iteration
if state.Iteration == 1
% Get handles to "Training Progress" figures:
hF = findall(0,'type','figure','Tag','NNET_CNN_TRAININGPLOT_UIFIGURE');
... |
493547bec3aa9604bdf112403842bff682c1b02a109dcfa413271ed833f1bc45 | MATLAB | 624 | 19 | %% Function that simulates the injection of FMH into the peritoneum.
%t_start is the time for the first dose, and t_repeat is the repetition
%time in hours. inj_time is time that the injection lasts. Output units in ug/h.
function f = FMH_inj(t, t_start, t_repeat, q)
inj_time = 1/3600;
n=length(t);
for i=1:n
... |
6c4c810b37afbf6217b4543ebd1b5afccd6c6e23c0e09f3d776a2412521ea945 | MATLAB | 624 | 15 | cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\effect size\figure 1\1i')
g = importdata("side_per_session_data.mat")
%% transient
sample1 = g.mean_is_responsive(ismember(g.side,'R'),1)
sample2 = g.mean_is_responsive(ismember(g.side,'L'),1)
[p, observeddifference, effectsize] = permutationTest(sample1,... |
9954feb3f5a234af0f104ad399a1e1955da05cae60c29bec35f38e77bc3d571b | MATLAB | 624 | 14 | function D = Get_Linearity(XY)
% XY = [Np x 2].
v1 = XY(1,:); % Head point. [1 x 2].
v2 = XY(end,:); % Tail point. [1 x 2].
a = v1 - v2;
b = XY(2:end-1,:) - v2;
d = vecnorm(cross(repmat(a,size(b,1),1),b,2),2,2) / norm(a); % Distance from line. Row-wise cross and norm. d = norm(cross(a,b),2) / norm(a);
d1 =... |
2fc9cddc285b64162181c4eed5bbbf67a1633a22d92349babe42e2e3ab990d93 | MATLAB | 625 | 21 | function H = Hindex_distribution(ntcells,taggedcells)
%HINDEX_DISTRIBUTION Plot H-index distribution.
% H = HINDEX_DISTRIBUTION(NTCELLS,TCELLS) plots tagging (H-) index
% distribution for a population of tagged (TCELLS) and non-tagged cells
% (NTCELLS).
%
% See also SALT.
% Balazs Hangya
% hangy... |
3304dc11166c2e8c5f325a55365dfd11e80f8006d54f2f22d1768e4482916925 | MATLAB | 625 | 19 | %This script will make a "Matched" variable, which contains both the name
%of the docking event from red (aka channel 2/right) channel and the time of
%fusion from the green (aka channel 1/left) channel.
Matched={}
MatchedTime=[]
for i=1:length(confirmedHits2);
idx=find(strcmp({confirmedHits.name}, confirmedHits2(i... |
184789d59911bb69e7d7a3dacee18bd56fec933bd44889b20fcededdd7c09976 | MATLAB | 626 | 26 | function toggleRaw(obj, hMenu)
%TOGGLERAW Toggle raw waveform display
showRaw = ~obj.hCfg.showRaw;
if obj.hasFig('FigWav')
hFigWav = obj.hFigs('FigWav');
hFigWav.wait(1);
end
if showRaw && isempty(obj.hClust.meanWfGlobalRaw)
obj.hClust.computeMeanWaveforms([], 1);
end
... |
3952d21710c7bea7cf6bb7717c6c52e032aa8a478f995c4ceb5bce2e9d3861a7 | MATLAB | 626 | 14 | % Input
% Rclustens: Cells x Frames
% SimMethod: 'hamming', etc'
% DistThreshold: Maximum Threshold (at least half of neurons)
% Ouput
% NonSimilarVectors: Frames with Vectos non similar
% MaxDistanceIV: Maximum Distance Intra Vectors
function [NonSimilarIV,MaxDistanceIV]=nonsimilarframes(Rclustens,SimMethod... |
592162efc555549b0abf59053ebe312f878a3fb16d6c980988bcfeb788fc6491 | MATLAB | 626 | 21 | function [option_names,option_values] = make_option_specs(varargin)
%MAKE_OPTION_SPECS Separate keys and values from key-value pairs.
if mod(nargin,2)
error('Must have even number of args (args are key/value pairs)');
end
nopts = nargin/2;
option_names = cell(1,nopts);
option_values = cell(1,nopts);
for iopt = ... |
9b4323cced3756ecef442d39c4de435cae149a025217f44746f0843e21208527 | MATLAB | 626 | 22 | function showmeyourraster(R,Indexes,fs,NSECONDS,NameOutRaster)
fprintf('>>Raster Animation Starting:\n')
v = VideoWriter([NameOutRaster,'.avi']);
% Plot Raster
Plot_Raster_Ensembles(R(Indexes,:),fs,1,[1:numel(Indexes)])
FigRaster=gcf;
%CAGAxis=FigRaster.Children(1);
RasterAxis=FigRaster.Children(2);
% Showtime raster
R... |
f9d6f7bfa3aae8734296019dcf7f05ad8eb8490d05e9308d6ab4f8d712480e8d | MATLAB | 626 | 26 | function [ d ] = Projection_metric( A,B )
%This function calculates the projection metric based on the principal
%angles between the columns of matrix A and B
%Input:
% A: Orthonormal matrix N*M
% B: Orthonormal matrix N*M
%Output:
% d: Distnace between column spaces of A and B
%Author:
% Soheil... |
2c279a73e315ba5b3d7f521e675e6b5d7d9b53a268059c0efb3150fb7ba24ead | MATLAB | 627 | 26 | function A = shrink(A, sc, st)
for d = 1 : length(size(A))
ind = [];
for i = 1 : sc(d) - st(d)
ind = [ind; sc(d)+i : sc(d) : size(A, d)];
end;
newind = ind-sc(d)+st(d);
if (d == 1)
A(newind, :, :, :) = A(newind, :, :, :) + A(ind, :, :, :);
A(ind, :, :, :) = [];
elseif (d == 2)
A(:, newind, ... |
9dd8babdd5e35b3494b0d1840ad331cc51050d1eb9348166fc73f41245f161eb | MATLAB | 628 | 26 | % Shinjini Kundu (c) 2014
% Transport-Based Morphometry project (TBM)
function [I_out]=gen_pdf(I_in,dc,phi)
%Preprocessing of 3D image
%Inputs: I_in 3D input image
% dc a positive constant
% phi kernel for filtering image
%
%Outputs: I_out 3D output image
I = m... |
b0fd3cd128515e71cd65d8a525237545fb4fd189650d20219b8754f06b6b700f | MATLAB | 629 | 17 | % Authors : Simon Wadle 2019-2023
%function writes tiff stacks faster than generic MATLAB function
function fast_tiff_export(filename, image_data)
image_data = permute(image_data, [2 1 3]);
ftif = Fast_Tiff_Write(filename);
[~, ~, frames] = size(image_data);
placeholder = ['%',num2str(floor(log10(frames))+1),'d... |
b396ddf47d302f8791f99f38e703d09480fcc333da3f895569d8e5ac6a5daec7 | MATLAB | 631 | 24 | function [fig] = plotRaster(spikeMat, tVec)
% Plot the spike matrix generated using poissonSpikeGen
%
% [] = plotRaster(spikeMat, tVec)
%
% INPUTS
% spikeMat - spike matrix, from poissonSpikeGen
% tVec - time vector, from poissonSpikeGen
%
% OUTPUTS
% fig - figure handle
%
% Anya Krok, March 2021
f... |
dc0fb004db9ac2c6be31aecfe6aaa5f1765682e25aab187e62dcfc48db747564 | MATLAB | 631 | 29 | function [EuD_all]=mnl_GroupColourEuclidean_Simplified(data)
%% Help Section
%
% Inputs
% data - data points as vector (cells*ndim)
%
% Outputs
% EuD_all - Euclidean Distance between all points
%
% Written by Marcus Leiwe, Kyushu University, 2018. If used please cite
% Sakaguchi et al 2018
%% Basic Info
sz=size(data);... |
5ce41b5937ddc57e83da9f6b058c089a9ea8ebe3ae4c9ed2c4613b99c61945bc | MATLAB | 632 | 25 | function rho = spearman_rho(deltas,zetas)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
% input params should be columns of numbers, if they are rows switch them
% to columns
if size(deltas,1) == 1
deltas = deltas';
zetas = zetas';
end
sorted = sortrows([ deltas zetas ]);
% ... |
849e368d3391eae8dd0be89d0c57f740e9fd9ee9f4ee949512b6b0adc282a2f1 | MATLAB | 632 | 13 | % - collect data per subject and session (so we can individually analyze them later)
% - av_trials
% - er_trials
% - trans_data (fastest iti transitions, used for decoding)
% - trans_data_err (random iti periods)
% - trans_data_dr (remaining iti transitions, used for definition of spd dims)
% - DR: use half ... |
cfc4e0dcbff063d5965d7dfb5af8e5d3217c9494724fd02ccfedc09630b43d32 | MATLAB | 632 | 32 | function pre = newfft_exact_p(st, om)
%function pre = newfft_exact_p(st, om)
%|
%| precomputed (large) matrix for exact forward NUFFT
if ~isvar('om') || isempty(om)
om = st.om; % default
end
if isempty(om), fail 'om or st.om required', end
dd = st.dd;
Nd = st.Nd;
n_shift = st.n_shift;
if dd > 3
fail 'only up to 3... |
764ad92fbd65de73b6881729a21d66679d12bc7ee455c78b03da38c8a09678db | MATLAB | 633 | 24 | data = all_data.cell_4.intensities;
x = data(1).intensty_data
x = x - data(1).intensty_baseline.mean
y = reshape(x,[], 1)
binned_y = bin_psth(y, 10);
%%
f4 = figure;
set(f4,'color', [1 1 1]);
set(f4,'position',[50 50 2000 250]);
plot(binned_y, 'LineWidth', 3)
hold on
for i = 1:20
% plot([30 30],[-3 8],'--k');
% ... |
a4f94c3328345e202316d395dff53a3aaf308ce6a14f1ccf947cc87b9546c7dd | MATLAB | 634 | 18 | function Experiment=getExpID(PathName)
%% Get the Experiment ID:
slashes=find(PathName=='\');
if ~isempty(slashes)
Experiment=PathName(slashes(end-1)+1:slashes(end)-1); % Experiment ID
else
Experiment=PathName(1:find(PathName=='.',1)-1);
end
Experiment(Experiment==' ')='_'; % REPLACE SpaceS with '_'
ExpIDDef{1... |
bcded33cad879df855694ab31bbf93596c8fa8437fbb3fac9b1e541158c28867 | MATLAB | 634 | 19 | %% Function that simulates the injection of escitalopram into the peritoneum.
%t_start is the time for the first dose, and t_repeat is the repetition
%time in hours. inj_time is time that the injection lasts. Output units in ug/h.
function f = SSRI_inj(t, t_start, t_repeat, q)
inj_time = 1/3600;
n=length(t);
for... |
fa90fdc6bbf3a054895304721f6af510f142fe26639e8a83795787de3fc3c519 | MATLAB | 635 | 26 | function Stats = pairedWilcoxon(Data1, Data2)
Diff = Data2-Data1;
[p,sig, stats] = signrank(Diff);
try
Stats.zval = stats.zval;
catch
warning('something weird with z-values again')
Stats.zval = stats;
end
Stats.p = p;
Stats.sig = sig;
Stats.df = numel(Diff) - nnz(isnan(Diff)) - 1;
Stats.N = Stats.df + 1;
S... |
d1af2122ffcdac684c7a43ea135c64c65fa2e3c522245a3c01e30e13e680822b | MATLAB | 637 | 40 | function [T1 S0] = find_T1(f)
for k=1:length(f)
tr(k) = f(k).TR/1000;
y1(k) = f(k).integral_real;
y2(k) = f(k).integral_real_all;
y3(k) = f(k).integral_abs;
end
[v,i] = max(tr);
v0(1) = y1(i); % S0 start point
v0(2) = 1000; % T1 start point of the fit
vE=nlinfit(tr,y1,@T1_decay,v0);
T1(1) = ... |
7c5671b640220b3e3bb7e933b74e49c46923e2173513eefd3c7c88e6af3481db | MATLAB | 639 | 23 | function [mu,F] = fcn_fastflx(S)
% computes pairwise flexibility on node x layer x repetition matrix, S
%
% inputs:
% S, node x layer x repetition matrix of community labels
%
% outputs:
% mu, node x 1 vector of average pairwise flexibility
% F, node x layer x layer x repetition dis... |
bc1606069b13a4638a9041bdca91f3b084e1d7f91821e3c9c871d082bf60cfba | MATLAB | 640 | 17 | function [filename, dirname] = selectFile(fileSpec, prompt, dirname, multiSelect)
%SELECTFILE Select a file or files via a dialog
args = {fileSpec, prompt, dirname};
if multiSelect
args = [args, {'MultiSelect', 'on'}];
end
[filename, dirname] = uigetfile(args{:});
if ~(ischar(filename) ... |
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