sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f33369555af85487d8b1811d0d656e46d7b307c0f0801afa65a91353f3084224 | MATLAB | 1,151 | 31 | function run_tier3()
%% run_tier3()
%
% Description: runs the Tier-3 toolbox-dependent regression matrix
% (test/tier3_matrix/) against the real dataset configured via
% sepiatest.get_real_dataset(). Rows requiring an unavailable toolbox, or
% missing a real dataset/reference, are skipped (not failed). Errors
% (non-ze... |
0439d22cd23c5de7c424eb6e24249e76646c02e180ab844cafd40831dfc465b8 | MATLAB | 1,152 | 38 | function y = vl_nncrop(x, crop, dzdy, inputSize)
%VL_NNCROP CNN crop.
% Y = VL_NNCROP(X, CROP) crops the input X spatially. CROP specifies the
% amount of cropping as [TOP, BOTTOM, LEFT, RIGHT].
%
% DZDX = VL_NNCROP(X, CROP, DZDY) computes the derivative DZDX of the
% function projected on the output derivative... |
c01634f4c3f3858674042f3ebb90494ef4dfb943518540201b7cb6d0e4fb22fa | MATLAB | 1,154 | 45 | function [ params ] = nmri_get_modality_params( params, mod_type )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
% check if we have a specific subfield
if (isfield(params,mod_type))
params_b=params.(mod_type);
params_a=rmfield(params,mod_type);
% will use the versatible update... |
b4ebd1903896cce89aa5dad9d8f6808a05e0dbd9b51e79916fec3179ddf3964b | MATLAB | 1,155 | 31 | function [m,dm] = meanWSPC(d, hyp, x)
% Weighted Sum of Projected Cosines or Random Kitchen Sink features.
%
% This function represents the feature function of a zero mean GP with
% stationary covariance function. See the paper "Sparse spectrum GP regression"
% by Lazaro-Gredilla et al., JMLR, 2010 for details.
%
% m... |
7cf9cfc1fbe6d2db56eccf9fb8a916f94c450982f6978f636590de5dccbdc189 | MATLAB | 1,157 | 51 | function [SNRmean, STD, E] = sero_srr_snr_check_invivo(fn_nii, fn_fit, fn_xps, fn_msk, do_t1)
% function SNR = sero_srr_snr_check_invivo(fn_nii, fn_fit, fn_xps, fn_msk, do_t1)
%read files
I = mdm_nii_read(fn_nii); I = abs(I);
xps = load(fn_xps);
P = mdm_nii_read(fn_fit);
S0 = P(:,:,:,1);
M = mdm_nii_read(fn_ms... |
ce5e724c96e6cc4d06675bcec9b4c31595c7a515ccbdfb78d88bcaed70757f65 | MATLAB | 1,157 | 35 | %{
preprocess.CirclesLookup (computed) # my newest table
# add primary key here
-> preprocess.CircleRadii
-----
# add additional attributes
width : smallint # width of the reactangle over which the map is
# created
height : smallint # height of rectangle
base... |
d5d92f5353543171a403407ff8543789254bc719e345307f9247ea52f3f13d80 | MATLAB | 1,157 | 23 | % reward_time=[time2uL time5uL time7uL time10uL time15uL] （The length of water supply for different amounts of water）
% reward_time2= Actual water supply sequence（Random order）
reward_order=[find(reward_time2==reward_time(1)) find(reward_time2==reward_time(2)) find(reward_time2==reward_time(3)) find(rew... |
fbd1c4e68e4897254632c83dc24bc878dcf89fecda87226e994c2b2689be5557 | MATLAB | 1,157 | 39 | clear, clc,
% set simulation metadata
T = 1000; % # of time steps
V.dt = 1/8; % time step size
% initialize params
P.a = 1; % observation scale
P.b = 0; % observation bias
tau = 1.5; % decay time constant
P.gam = 1-V.dt/tau; % C(t) = gam*C(t-1)
P.lam = 0.1; % firing rate = lam/dt
P... |
254de6c7717a7e3775052dec2d6175db22d51696f1350f499954531c2673884c | MATLAB | 1,158 | 56 | function Q = qGetQ( R )
% qGetQ: converts 3x3 rotation matrix into equivalent quaternion
% Q = qGetQ( R );
[r,c] = size( R );
if( r ~= 3 | c ~= 3 )
fprintf( 'R must be a 3x3 matrix\n\r' );
return;
end
% [ Rxx, Rxy, Rxz ] = R(1,1:3);
% [ Ryx, Ryy, Ryz ] = R(2,1:3);
% [ Rzx, Rzy, Rzz ] = R(3,1:3);
Rxx = R(1,1... |
814ec9c546f65c7ff82c4c069bc86f3b25f0ddaf5f90ed362cad76c363e552c3 | MATLAB | 1,158 | 44 | function SortCalls(hObject, eventdata, handles, sort_type, show_waitbar, select_added)
% Sort current file by score
set(handles.hFig, 'pointer', 'watch')
if nargin < 5
show_waitbar = 1;
end
if nargin < 6
select_added = 0;
end
if show_waitbar
h = waitbar(0,'Sorting...');
end
switch sort_type
case 'score'... |
96c4440763528107f5e30a96fe407881feb435acf17055b2c5a2514ff9ac2bb2 | MATLAB | 1,158 | 20 | %{
vis.FancyBar (manual) # Moving Bar stimulus that keeps the size and speed of the bar constant relative to the mouse’s perspective.
-> vis.Condition
---
pre_blank : double # (s) blank period preceding trials
luminance : float # (cd/m... |
db1f5ba39b8c5043e7d5a83abf084d0c81623933adab5d6da38c1258b4b3885a | MATLAB | 1,158 | 36 | function xyzvox = meta_get_voxel_coords(DB,contrastnumber,V,maskdata)
% Given a) x,y,z fields in DB, 2) 3-D mask data; and 3) a contrast number indexed in DB.Contrast,
% return voxel coordinates xyzvox of in-mask coordinate points.
%
% xyzvox = meta_get_voxel_coords(DB,contrastnumber,V,maskdata)
% See meta_prob_activat... |
452589ba8cf215ea0cc27cc649b215377c7fee880421fc96756b4563cba4a65a | MATLAB | 1,159 | 33 | function ProcessData_ExtendedData8(datadir, savedir, codedir)
%ProcessData_ExtendedData8 - Process raw data saved under datadir such that it can be plotted by PlotExtendedData8.
% INPUTS:
% datadir - Local directory where 'Golden_Nature/RawData_ExtendedData8.mat' from Zenodo was saved
% codedir - Local directory wh... |
96a7fa769ed0eb1dda970a91aedce717ad7300d72477e055b43ad6399e489fbe | MATLAB | 1,160 | 55 | function V=surfing_afni2spmvol(I)
% returns an affine matrix for an AFNI brik similar to SPM
%
% V=SURFING_AFNI_AFFINEMATRIX(INFO)
% INPUT:
% INFO: Info brik as returned by BrikInfo (or a filename of an AFNI brik)
% OUTPUT:
% V: struct with the following fields:
% V.mat: 4x4 affine transformation matrix, ... |
b03b54cedd1d76e6ca4faf910dfe457554413843d7cf7c01562a381c5efbf936 | MATLAB | 1,160 | 38 | function this = set_from_geometry4D(this, geometry)
% Updates affine transformation from read-in MrImageGeometry
%
% Y = MrAffineTransformation()
% Y.set_from_geometry4D(geometry)
%
% This is a method of class MrAffineTransformation.
%
% IN
% geometry MrImageGeometry
% OUT
%
% EXAMPLE
% set_from_geometry... |
dd1e608d71d6cf23f09832b92e346553c7ed9d8b8a184e5919a008fce1c3fe35 | MATLAB | 1,160 | 33 | n = 3;
M = rotationsfactory(n, 1);
A = randn(n);
problem.cost = @(X) .5*norm(X-A, 'fro')^2 + trace(X) + cos(X(1, 1));
Z = zeros(n); Z(1, 1) = 1;
problem.egrad = @(X) X-A + eye(n) - sin(X(1, 1))*Z;
at = @(M, i, j) M(i, j);
problem.ehess = @(X, Sdot) X*Sdot - cos(X(1, 1))*at(X*Sdot, 1, 1)*Z;
M.exp = M.retr_qr; % check*... |
f8c6e73c660779e527e237b4e595aac8f6a693f62069369020f70ae44b38bb30 | MATLAB | 1,160 | 27 | function logical = IntervalsIntersect(intervals1, intervals2)
% This function returns a logical vector the size of intervals1, with ones
% if any portion of intervals2 is present in the respective interval1.
%
% This can be useful if, for example, you want to have the identity of
% the windows intervals1 which conta... |
160f88ea8c585a10289a40a1ea3eed15bca392902ffe919e6844bd5b093f4f8b | MATLAB | 1,161 | 49 | % op_rmempty.m
% Georg Oeltzschner, Johns Hopkins University 2018.
%
% USAGE:
% [out]=op_rmempty(in);
%
% DESCRIPTION:
% Removes empty FIDs (for example in Philips *_ref.sdat files).
%
% INPUTS:
% in = input data in matlab structure format.
%
% OUTPUTS:
% out = Output dataset
function [out]=op_rmempty... |
1f3bdaa722b0cd174aeab2b9210161251d3939da6da52935aa576e26e0a8d590 | MATLAB | 1,161 | 43 | function phiBC = cellBoundary1D(phi, BC)
% This function calculates the value of the boundary cells and add them
% to the variable phi of size (1 .. Nx)
% the output includes the boundary is of the size (1..Nx+2)
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Al... |
c5302e05cd196cc5e4ea66700dc93a7e1f9678b33bacfaed3375404b6e2ec1ce | MATLAB | 1,161 | 42 | function [ft,tBreak]=essential_distMinAnglePair_ftFromQ(t,Q1,Q2,varargin)
kFlip=1;
term='both';
ivarargin=1;
while(ivarargin<=length(varargin))
switch(lower(varargin{ivarargin}))
case 'kflip'
ivarargin=ivarargin+1;
kFlip=varargin{ivarargin};
case 'term'
ivarargin... |
1ac44cbfaf8832c14d773e2341c275da366a22640312ad14f8d8fc32834eb6e7 | MATLAB | 1,162 | 25 | function eletrodesLines=choosingTHeElectrodes()
channelsLabel ={'Fp1','AF7','AF3','F1','TP9','F5h','F7','FT7','FC5h','PO9','FC1','C1','C3','C5','T7','TP7','CP5','CP3','CP1','P1','I1','P5h','P7','P9','PO7','PO3','O1','Iz','Oz','POz','Pz','CPz','Fpz','Fp2','AF8','AF4','AFz','Fz','F2','TP10','F6h','F8','FT8','FC6h','... |
679ff2c9e139bda3649fa66ed9edcb5c4544714ce2a3b7bdd8a076e8ea558172 | MATLAB | 1,162 | 38 | %Hamming distance. LC Dec 2013 Calcula la distancia de Hamming entre todos
%los picos.
%La distancia de Hamming entre dos cadenas del mismo
%tamanhio esta definida como el numero de elementos diferentes en cada
%posicion de ambos arreglos. Un arreglo binario de longitud n puede ser
%visto como un vector de n dimensione... |
860569a4522b6c8c81f7d648f530695f9173500a48ab4845c0384c8c37aae4a8 | MATLAB | 1,162 | 39 | function [mapALL]=sh_TTLPowerMap(mov,TTL,freqRange,Fs,Nttl)
mov=double(mov);
mov=sh_Standardize(mov);
% find the 0 before 0-1 transition
[idxBehP,~]=find(diff(TTL) == 1); %Baseline
[idxBehN,~]=find(diff(TTL) == -1); %Baseline
n=length(idxBehP);
onT=(idxBehN(1)-idxBehP(1)+1);
deadT=(idxBehP(2)-idxBehN(1)+1);
fprint... |
eb030ee91e8dc2f5c3d1dc3e1d3063144c8120f1b58d78057ef0155d2ebae0a2 | MATLAB | 1,162 | 29 | function storage = DBExternalStoragePath
%DBExternalStoragePath - Get path for database external storage space.
%
% This is an 'internal' function used by FMAToolbox. You should not need
% to use it, unless you are developping new functions for this toolbox.
% Copyright (C) 2016-2023 by Michaël Zugaro
%
% This pro... |
067cc3a6da437c118fccd107c5367b883f99fdcb3700f0ef118535ed097daece | MATLAB | 1,163 | 37 | function simpleVP(x,vp,edgeColor,faceColor,lineColor,width,type,rawRad,jitter)
if ~exist('width','var') || isempty(width)
width = 0.8;
end
if ~exist('type','var')
type='';
end
if ~exist('rawRad','var')
rawRad=[];
end
if ~exist('jitter','var')||isempty(j... |
292cf0e605f7e5fd8b0d4faddcf1c38bdbc20bbdbd09720106d51ca69c4e23f1 | MATLAB | 1,163 | 35 | function [logp, yhat, res] = tapas_bayes_optimal_binary(r, infStates, ptrans)
% Calculates the log-probabilities of the inputs given the current prediction
%
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2012-2016 Christoph Mathys, TNU, UZH & ETHZ
%... |
518f4498bf0c1017abca358169d4b89369c976ff980a9962591523c5b33cb6ec | MATLAB | 1,163 | 47 | function nsd_savenifti(data,res,file0,tr,origin)
% function nsd_savenifti(data,res,file0,tr,origin)
%
% <data> is X x Y x Z x D (where D >= 1) with volume data
% for one or more datasets. Can be of a specific format
% like 'double' or 'int16'.
% <res> is [A B C] in millimeters for the voxel size
% <file0> is the ... |
0e789e744101ee59d59e0151ba388fcc93877ea7ea6fea6ec0dcd9a4eeda18fc | MATLAB | 1,164 | 43 | function [ mi ] = GaussianMI(X, Y)
%%GAUSSIANMI Mutual information between Gaussian variables
% I = GAUSSIANMI(X, Y) calculates the mutual information between matrices X
% and Y, assuming they are jointly Gaussian distributed. Matrices must be
% of size [T, Dx] and [T, Dy] respectively, where Dx,Dy are the ... |
202861326aaf8f98754712681c517e96cc0074a720d37b108da0e9b9f1095e0f | MATLAB | 1,164 | 46 | % op_fddccorr.m
% Jamie Near, McGill University 2014.
%
% USAGE:
% out=op_fddccorr(in,npts);
%
% DESCRIPTION:
% Correct and DC offset in the frequency domain. This is equivalent to a
% vertical shift in the frequency domain. The required vertical shift is
% calculated by taking the average of the first and last "NP... |
e26f508be804f67c24e1d6a2e7034d02a49a0802a87122e3da65f11b4a91906a | MATLAB | 1,164 | 30 | %% HECPredictiveScripts
resultPath = 'D:\Data\Lobster\EventClassificationResult_4C_Predictive_NonOverlap';
filelist = dir(resultPath);
sessionPaths = regexp({filelist.name},'^HEC_Predictive.*.mat','match');
sessionPaths = sessionPaths(~cellfun('isempty',sessionPaths));
sessionPaths = fliplr(sessionPaths);
midpoints =... |
1200e01fa9300c84a0b5a59e747aa3a92cd890f6b936f0d721cf634a0d087418 | MATLAB | 1,165 | 53 | function [image] = create_slice(domain,BV,WM,occupancy,slice_ind)
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
i = slice_ind;
dx = 1; %slice thickness
%%Create image
wm_slice = squeeze(sum(WM(:,i-dx:i+dx,:),2));
bv_slice = squeeze(sum(BV(:,i-dx:i+dx,:),2));
brain_slice = ... |
7bfd3a67381d9d1bc1c6692afedcfcbada77fef50a1ae0f03ef79777e7c5a3f1 | MATLAB | 1,165 | 16 | % EEG_OPTIONS - eeglab option script
%
% Note: DO NOT EDIT, instead use POP_EDITOPTIONS or the menu
% /File/Maximize memory in EEGLAB gui
% STUDY options (set these checkboxes if you intend to work with studies)
option_storedisk = 0 ; % If set, keep at most one dataset in memory. This allows processing hundreds... |
9f8002d1b5b77f281e0c0e6f5d31591976f689190f224580916a8bddfb53d880 | MATLAB | 1,165 | 34 | function varargout = covRQiso(varargin)
% Wrapper for Rational Quadratic covariance function covRQ.m.
%
% Rational Quadratic covariance function with isotropic distance measure. The
% covariance function is parameterized as:
%
% k(x,z) = sf^2 * [1 + (x-z)'*inv(P)*(x-z)/(2*alpha)]^(-alpha)
%
% where the P matrix is ell... |
83fb4025b75dc91b60db4641d8e301031931609718f8c1160384c8965c58fd6d | MATLAB | 1,166 | 53 | %% getM(Ciclo)
%
% Obtiene la matriz de un ciclo
%
% Ciclo = string
%
% NOTA: el ciclo debe terminar en el vértice donde comienza.
%
% Ejemplo,
% Ciclo="abcabcdabaa"
%
% 1 2 3 4
%
% Matriz = 1 | 1 1 2 0|
% 2 | 1 0 2 0|
% 3 | 1 0 0... |
941ddf61a0842641e14f44e80c8832d198434019db9f4cad133d6aace89e8f10 | MATLAB | 1,166 | 46 | function [ITIacrossrats, ITIbins_density] =...
get_ITIbins(ratlist, Bstruct, numbins)
%Use mixed blocks and violations only
%input
%ratlist
%numbins: number of bins to sort all ITIs into
ITIs_rats = cell(length(ratlist), 1);
numbins_vector = linspace(1,numbins,numbins);
for rat = 1:length(ratlist) ... |
a76ac9752e2d2e716e7f708062c49da22619add7dc583e841db28f5c9dbb3e7f | MATLAB | 1,166 | 21 | %{
# Dot stimulus, for receptive field mapping
-> vis.Condition
---
rng_seed : blob # RNG seed
luminance : float # cd/m^2
contrast : float # Michelson's 0-1
bg_color : smal... |
daf661aa7bdb1dac2800ccc449d4d8bbcfc25daa73b2b8af9a51f6ebbbdfef59 | MATLAB | 1,166 | 38 | function X = tapas_uniqc_flip_compatible(X, dim)
% For older Matlab versions (<2013b), this redirects tapas_uniqc_flip_compatible to flip_compatibledim
%
% X = tapas_uniqc_flip_compatible(X, dim)
%
% IN
% X N-d matrix
% dim dimension which shall be flip_compatibleped (i.e. element indices changed
% ... |
5d638c18ed55674326b6990dbc78143e2eb98ce0b4e37c952583cdb8b49bfa3d | MATLAB | 1,167 | 29 | function Model=features2ModelRDMs(features,varargin);
% function RDMs=rsa_features2ModelRDMs({Feature1,'name1',Feature2,'name2'},options);
% generates a Model structure from features
% for parametric analysis of RDMs
Opt.dissimilarity='LDC'; % Could be covariance
import rsa.*;
Opt=getUserOptions(varargin,O... |
6cf17d9739ac9701c5a2c3233d49dae35e1817a06e23f1ea16b45aaf797fb403 | MATLAB | 1,167 | 36 | function varargout = compute_mRCVscore(truePredLabels, metric)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% compute_mRCVscore computes mean repeated CV scores using given
% true and predicted labels.
%
% Arguments:
% truePredLabels = Cell containing true and predicted labels obtaine... |
ab27178ea3b7542d907ac24c6ffb020a99e7642fdbe5788a10dcdd0a95482efe | MATLAB | 1,167 | 34 | %This code will generate a csv file with the global component gs_sd or estimated_drowsiness value of
%the 543 subjects
%Author: Kim Kundert-Obando for questions please reach out to me at k.rogge.obando@gmail.com
%Load subject list
subj= readtable('/data1/neurdylab/datasets/nki_rockland/vigilance_analysis/great_HR_su... |
b2ce6b942d1e9c6ae62c604910a77f93c780c3b59d570e5a0f528b07aa15e410 | MATLAB | 1,167 | 31 | function resizedWeight = ART_Add_New_Category(weight, input)
% ART_Add_New_Category Adds a new category to the given weight matrix.
% RESIZEDWEIGHT = ART_Add_New_Category(WEIGHT)
% This function returns a new weight matrix which is identical to the
% given weight matrix except that it contains one more cate... |
b7939b18e8537617ef21e186354a8fcfc820f063a4c6449f472f283859f41b27 | MATLAB | 1,167 | 45 | %io_writesdat.m
%Georg Oeltzschner, Johns Hopkins University 2019.
%
% USAGE:
% RF=io_writesdat(in,outfile);
%
% DESCRIPTION:
% Takes MRS data in matlab structure format and writes it to a SDAT file
% that can be read by LCModel.
%
% INPUTS:
% in = input data in matlab structure format.
% sdatFile = Desired... |
f04787f99beec9717f35b74bab27f579d0454e449a9f04bf655e158b713bb90f | MATLAB | 1,167 | 48 | function [hout]=bandwidth_SJ(xi,K)
%
% Bandwidth selection with Sheater and Jones(1991)
% and Wand and Jones (1995) pp.74-75
syms uh
if K=='norm'
fk=1/sqrt(2*pi)*exp(-0.5*uh^2);
interK1=-inf;interK2=inf;
elseif K=='biwt'
fk=15/16*(1-uh^2)^2;
interK1=-1;interK2=1;
elseif K=='expn'
... |
e2b61b022dc796cfbad64020014904314ff74c2d72c5ea8b27b8671801f517de | MATLAB | 1,168 | 54 | function [xopt, Y] = hyperbolic_frechet_mean_computation(n, N)
% This is an example of how to use the hyperbolic manifold factory to
% compute the Frechet mean of points.
% This file is part of Manopt: www.manopt.org.
% Original author: Bamdev Mishra, Nov. 2, 2018
% Contributors:
% Change log:
if ~exist('n', 'var') |... |
6fb6fddfdb1daecca7e6f0ce9daafeddebd3dfa4d56ee81d8135df407c6c68e1 | MATLAB | 1,169 | 31 | function [values] = modal_control(A)
% FUNCTION:
% Returns values of MODAL CONTROLLABILITY for each node in a
% network, given the adjacency matrix for that network. Modal
% controllability indicates the ability of that node to steer the
% system into difficult-to-reach states, given inp... |
d2514ae57af2491a0aa45e402399f020998eae9025d9329f09fa94039e28b8cf | MATLAB | 1,170 | 37 | function [ S_index_query ] = sindex_query( query,tf_idf_Rasterbin,Rasterbin )
%Busca los vectores de query en el diccionario de Rasterbin
%Para buscar los que pertenecen a un estado dado
%query=Rasterbin(:,Pk_edos(find(Pk_edos(:,edo)>0),edo));
%Normalizo query tf-idf
[sis_cti sis_pools]=size(query);
tf_query=zeros(si... |
2bb79c618c912e1d2402eee2a2235bd5853a331325bdc3a292abd905d6c93ae5 | MATLAB | 1,171 | 46 | function Xtensor = tucker2multiarray(X)
% Converts a 3d Tucker form tensor to a multiarray.
%
% function Xtensor = tucker2multiarray(X)
%
% X has fields U1, U2, U3, and G.
%
% The matrices U1 (n1-by-r1), U2 (n2-by-r2) and U3 (n3-by-r3) are
% orthogonal matrices.
% G (r1-by-r2-by-r3) is a multidimensional array.
%
% See... |
7d7f538041ad42b0cc70d898447ad3734ae959565fe1581373574cdc18544ac3 | MATLAB | 1,171 | 53 | function fn = tapas_uniqc_get_fig_name(fh, isSaveCompatible)
% Automatically creates reasonable figure name based on Name, suptitle or axis
% title
%
% fn = tapas_uniqc_get_fig_name(fh)
% IN
% fh figure handle (default gcf)
% isSaveCompatible {0} set to 1 to remove blanks, slashes, colons
... |
922ef012447413b4dca7a76dce0c08fe07f2e134810358b9a9aba61afe57614b | MATLAB | 1,171 | 37 | % conf_dist: confidence response probabilities for -6,-5,...,-1,1,2,..,6
% (those probabilioties must sum to 1)
% noise_std: std of noise.
% criteria: the 11 confidence criterions that account for the confidence
% distribution given the noist
function criteria=my_confidence_criteria(conf_dist, noise_std,stimuli)... |
92dbb8893ec8e79782a047ff1fc948af2c0137cc0e8a66731e88dab31f1f17ec | MATLAB | 1,171 | 44 | function [u,xpdf,ypdf,xcdf,ycdf,h] = d_pdf(vec,crit_p,varargin)
% [u,xpdf,ypdf,xcdf,ycdf,h] = d_pdf(vec,crit_p,[opt] plot, [opt] figure handles)
%
% vec vector of values with unknown distribution
% crit_p p value at which to make height threshold (e.g., .05)
% plot Optional. 0 = none, 1 = pdf, 2 = pdf + ... |
9a5aa1c6f7007b74ad4d91f9cb3dce1d2a4bf701ad2ad437dfe51cffadf87301 | MATLAB | 1,171 | 39 | function eeglabciplot(lower,upper,x,colour, alphaval)
% eeglabciplot(lower,upper)
% eeglabciplot(lower,upper,x)
% eeglabciplot(lower,upper,x,colour)
%
% Plots a shaded region on a graph between specified lower and upper confidence intervals (L and U).
% l and u must be vectors of the same length.
% Uses the 'fil... |
bb828c1891fa0f4741342af5b4e82be67334e6f50321a1b260e1c6d23caebbd2 | MATLAB | 1,171 | 39 | % Regularization Enabled Sophisticated Harmonic Artifact Reduction for Phase data (RESHARP)
% RDF = RESHARP(iFreq, Mask,matrix_size,voxel_size, radius,alpha)
%
% output
% RDF - the relative difference field, or local field
%
% input
% iFreq - the unwrapped field map
% Mask - a binary 3D matrix denoting th... |
317128c58d93c536ebefd4b24831eedce62ba08104bd223b33c8eb38a85e95f3 | MATLAB | 1,172 | 32 | function i_aa = assign_ch2aa(chnlStruct_H, cytoarchAreas, subjTag, chnlNum)
% converts channel topology to (larger) anatomical areas 'aa'
% input: channel info from header H = H.channel(N)
% output: vektor of AA indices
% (c) Jiri, Jun17
if nargin < 4, chnlNum = 0; end
if nargin < 3, subjTag = 'noName'; end
%% defin... |
5090a6f87007bb4246138c81c07d8e7c1d08f7b7357669eef0e39d7fa75eddb1 | MATLAB | 1,173 | 40 | function [ H ] = tapas_rdcm_spm_logdet(C)
% returns the log of the determinant of positive semi-definite matrix C
% FORMAT [H] = spm_logdet(C)
% H = log(det(C))
%
% spm_logdet is a computationally efficient operator that can deal with
% sparse matrices
%__________________________________________________________________... |
87a536d314ad495ddf8cb12a1cd539983aec010d0109d9a36a133112de2b13c7 | MATLAB | 1,173 | 38 | classdef MaxAbsScaler < baseScaler
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MaxAbsScaler scales data by its maximum value.
%
% Parameters:
% data: Input data to be scaled.
%
% Attributes:
% maxAbs: Absolute maximum value.
%
% Example:
... |
9db4ed216d74a494eadf3d73f1471f86f92ef54db241cd74f75d8671937c4d04 | MATLAB | 1,173 | 45 | function [posterior] = tapas_mcmc_blocked_estimate(data, model, inference)
%% Estimate a model specified.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
nfuncs = numel(inference.sampling_methods);
nmeta = numel(inference.metasampling_methods);
[states] = inference.initialize_states(data, model, inference);
[stat... |
e75eb46ba8ac1be1d62a5883c0d0d73709a231201434c2082889fe287e9d6a68 | MATLAB | 1,173 | 45 | function [M_out, RHS_out] = maskCells(meshstruct, M, RHS, cellIndex, cellValue)
% This function masks the specified cells by giving them a constant value.
% It modifies the matrix of coefficient and the RHS vector
%
% SYNOPSIS:
% [M_out, RHS_out] = maskCells(meshstruct, M, RHS, cellIndex, cellValue)
%
% PARAMETERS:
%... |
67a1fc2cab259b211343a78ca45d29d0107428eb4d74c3cdd54778c8bbf53206 | MATLAB | 1,174 | 38 | function[PreFix] = osp_generate_SubjectAndSessionPrefix(Name,kk)
%% function[PreFix] = osp_RemoveSuffix(Name)
% Function to add subject and session filenames while respecting key-value pairs
% as defined in BIDs specification.
try
subs = num2str([contains(Name,{'sub'},'IgnoreCase',true) contains(Name,'S'+ digitsPa... |
5cb987ae811527c81c3d393a98de79de38feb7a86bbfcd24c179689c44ef4791 | MATLAB | 1,176 | 40 | function y = tapas_condhalluc_obs3_sim(r, infStates, p)
% Simulates responses according to the condhalluc_obs model
%
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2020 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, whic... |
4efed97d72f7aa3fd55145cb61b52b126c9f6a90b69bbd382093995db6e01706 | MATLAB | 1,177 | 29 | function [homerPruneMat, sciAvgs, pspAvgs, motionWindows] = updateQualityMetrics(nirs, qualityMatrices, nsub, homerPruneMat, sciAvgs, pspAvgs, motionWindows, saveFlags, params)
% Updates the quality metrics matrices with data from the current subject,
% including SCI averages, PSP averages, and motion window info... |
a1549d8dcdba63040c09a15dcd332e04ff1d21580acb4158e398707313168a01 | MATLAB | 1,178 | 44 | function freesurfer_asc_averagesurfaces(fnout,varargin)
% take the average of a number of freesurfer ASCII surface files
%
% freesurfer_asc_averagesurfaces(FNOUT,FNIN1,FNIN2,...)
% INPUTS:
% FNOUT: surface output file name
% FNIN*: surface input file name
%
%
surffns=varargin;
surfcount=numel(surffns);
% l... |
dcdf7141baccb4cc91c745b35d1f609ae49a5f0354f00c5ea4b3dd6567868204 | MATLAB | 1,178 | 51 | function [slt, W] = sero_pulseq_seq2sliceThickness(seq, dz)
% function [slt, W] = sero_pulseq_seq2sliceThickness(seq, dz)
nEvents = numel(seq.blockEvents);
Lib = {'initialized'};
c = 1;
for i = 1:nEvents
cEvent = seq.blockEvents{i};
if cEvent(2) && cEvent(5) && cEvent(7)
block = seq.getBlock(i);
... |
489342c2e238aa7ed0a82ad3bb3a5643f7f78f81fec7ac1c7fd76ba685bfa402 | MATLAB | 1,179 | 27 | function [pvec, pstruct] = tapas_hgf_binary_mab_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2013 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, which is released under the terms of the GNU General Pub... |
58b8d182f34b86e74afcc73b1c7090b8eca8b0fc008ecfa2c55b9014d0367c3b | MATLAB | 1,179 | 51 | function phi = solveExplicitPDE(phi_old, dt, RHS, BC, varargin)
% phi = solveExplicitPDE(phi_old, dt, RHS, BC, varargin)
% SolveExplicitPDE solves for the new value of variable \phi in an explicit
% discretization scheme: \phi_new = \phi_old + dt/ * RHS
% the real equation is d\phi/dt=RHS
% The code calculates the new ... |
a78787ef594b4c2a694f38cc527ffd75b52bcacf7bc0af5800561e19ad0ae527 | MATLAB | 1,179 | 31 | function dist = distancetosurface(coords,vertices)
% Won't work unless all vertices are on the actual surface!
%
% This function is old and may work for its intended purpose,
% but it is not a general function for calculating distance from a set of
% surface vertices. therefore, use dist_to_surface.m
for i = 1:size(c... |
64246d2b583150dbfdc90bf699803c39fb60acff2cc90383600b74d2972ff383 | MATLAB | 1,180 | 37 | function [Opt] = Args_to_opts(Opt, autoconvert, varargin)
% Convert arguments to items in the Opt structure
% This ability should be particularly useful for creating compiled
% functions in Matlab, where there is no desktop environment to set
% variables before running a program
% the compiled program should take a var... |
7b4af3bd03673470012565b53031d58771718e21b7b6bc8f75e55eb1495efc98 | MATLAB | 1,181 | 33 | function varargout = preSaveSetup(varargin)
%
% thisEvent = postInitializatinSetup(thisEvent, thisFixation, iBlock, iEvent, ...
% duration, onset, cfg, logFile)
%
%
% (C) Copyright 2020 CPP visual motion localizer developers
% generic function to prepare s... |
e4d87763332f96e3edd01ce52392bbc3ff87eaf6dcbf372c72f27ea2e7b9e8e9 | MATLAB | 1,181 | 39 | function [K,dK] = covRQ(mode, par, hyp, varargin)
% Rational Quadratic covariance function.
% The covariance function is parameterized as:
%
% k(x,z) = [1 + maha(x,z)/(2*alpha)]^(-alpha)
%
% where maha(x,z) is a Mahalanobis distance and alpha is the shape parameter
% for the RQ covariance. The hyperparameters are:
%
%... |
ef1840e5262b6af8bccd78a3494875154e7d604a9f8ea2b9e95862f8fb0cc9d1 | MATLAB | 1,181 | 40 | % pnt = [-2,-2,-4,1;-2,2,-4,1;2,2,-4,1;2,-2,-4,1;...
% -2,-2,-8,1;-2,2,-8,1;2,2,-8,1;2,-2,-8,1]';
% F = 200;
% N = 40;
% a = -(F+N)/(F-N);
% b = -2*F*N/(F-N);
% thx = 0;
% thy = 0;
% thz = 0;
%
% for k = 1:1
% thx = 1/180*pi;
% thy = thy+1/180*pi;
% Rx = [1,0,0,0;0,cos(-thx),-sin(-thx),0;0,sin(-thx),c... |
215889db7d91392e92b64ca757f1545d6dae233eed3b85a52c7b2acc68fd99d2 | MATLAB | 1,182 | 44 | function figHandle = plotStimHeatmapWmetric(nodeMetric, vrange, cmap, cmapLabel, stimInfo, patternID, figHandle)
%PLOTSTIMHEATMAP Summary of this function goes here
% Detailed explanation goes here
if ~exist('figHandle', 'var')
figHandle = figure();
elseif ~isgraphics(figHandle)
figHandle = figure();
end
... |
73d9d52403404e47c52e3e0f3b0582b78852ee5d78fc8f364ab1c3669b13481c | MATLAB | 1,182 | 43 | function faceGrad = gradientTerm3D(phi)
% this function calculates the gradient of a variable in x and y direction
% it checks for the availability of the ghost variables and use them, otherwise
% estimate them, assuming a zero gradient on the boundaries
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
%... |
3726786cb5505bf5e74fe0e9dc2ea9d3f2d20f7d8a6102698f0047bda6782444 | MATLAB | 1,183 | 34 | function getTriggers_stimuliTypes(params)
% determines trials which contained the selected keyword (in params.thisCategory)
% MUST match trials 'tr' with the same keyword in trials(tr).stim_type
% saves result into respective column of 'trials_events' in each sessionCacheFile
% - rows = trials
% - values = zeros (e... |
493598b409e3bc6d6177ab08d9b55e5f97ae0495f5a5609a791f0666e869f679 | MATLAB | 1,183 | 39 | function [hi, lo, mix, all] = iticurves_SS(A, postUnrewArg)
%Get ITIs for each block. Applies threshold to filter out top 1% of ITIs
l = A.ITI;
postunrew = [0; ~A.hits(1:end-1)]; % post unrewarded trials (Hit = 0)
if postUnrewArg
% Pull Post-unrewarded Latency
usethese = ~isnan(l) & postunrew;
else
us... |
7c16ece989bc9e3c4992255fbcea0e45bfef1a7db8b493be00574dc3b96d59da | MATLAB | 1,183 | 29 | function su_hdr = GE_readHeaderSuite(fid, byte_align)
%
% su_hdr = GE_readHeaderSuite(fid, byte_align)
%
% Loads the suite header from the file with filed id fid
% and returns it as a structure.
% if byte_align = 1 then 32-bit alignment (SGI, LX2 format)
% if byte_align = 0 then 16-bit alignment (Sun, 5.X format)
%
%
%... |
f9e750f462eb6009a765cedda3ef7f260f9c3c68bbd3e100d87e166f5af88456 | MATLAB | 1,183 | 33 | % Please cite this paper if you use any component of this software:
% D. Cunefare, L. Fang, R.F. Cooper, A. Dubra, J. Carroll, S. Farsiu, "Open source software for automatic detection of cone photoreceptors in adaptive optics ophthalmoscopy using convolutional neural networks," Scientific Reports, 7, 6620, 2017.
% Re... |
404f54343c3e585431c5c466b6c665bacdfd38b8c4b58fbd1c7bbe797e88c413 | MATLAB | 1,184 | 42 | %% [file,numFiles] = get_filename_in_directory(inputDir,pattern,ext)
%
% Input
% --------------
% inputDir : input directory
% pattern : string pattern in the filename
% ext : file extension
%
% Output
% --------------
% file : structure contains all filenames with the specified
% ... |
2c168a7b312b6ddb4f7817985c0fae37cbc4163c4845fd5b1dcaa649c3174947 | MATLAB | 1,185 | 41 | % Samples - List of timestamps and corresponding values
%
% In FMAToolbox, 'samples' refer to matrices in which the first column
% contains timestamps, and subsequent columns optionally contain values
% recorded at these timestamps.
%
% (Obviously, in functions implementing statistical tests, the word 'samples'
% is us... |
9a85bc03bb76e4e3863b3e3c6b0c5a4d6c9a4e92feed8c0a6092cebeaf0d410f | MATLAB | 1,185 | 54 | %% filter's frequency response
% compares different filter responses (sgolay, butterworth lowpass)
%% settings
srate = 1200;
%% sgolay
order=2;
winLen=1.5*srate + 1; % in [s]
B=sgolay(order,winLen);
sgB = B(round(winLen/2),:);
sgA = 1;
%% butterworth
hiF = 1; % in [Hz]
Wn = hiF/(srate/2); % normalized b... |
13bbbba31efe371a7790dbe6567d6deb7f8703e53ea672bee125816dba6f7753 | MATLAB | 1,186 | 59 | function [outputArg1,outputArg2] = PlotSubjectResponses(ResponseMatrix, TitleStr)
if ~exist('TitleStr','var')
% title parameter does not exist, so default it to something
TitleStr = ' ';
end
% --- means & standard deviation per azimuth for this subject
s_responses = ResponseMatrix;
% --- vectors for ea... |
aebca21a3726208b01803aab9a17e1930eccaa8f74378c2d7143440eab9dd1f7 | MATLAB | 1,187 | 30 | function MultiRunCalc
f1 = uigetdir([],'select one folder') ;
f2 = uigetfile('.txt') ;
f3 = uigetdir([],'select output folder') ;
f1list = dir(f1) ;
f2list = dir(f2) ;
parfor i = 3 : length(f1list)
mkdir([f3,filesep,f1list(i).name]) ;
[head data1] = TMSReadNii([f1,filesep,f1list(i).name,filesep,'fundata.nii'])... |
eb82c92f1292f495e0430c7fa0697595f533ad7b76b524ec6f826798f160b51f | MATLAB | 1,187 | 34 | function getTriggers_DES_intensity(params)
% determines trials which contained the selected keyword (in params.thisCategory)
% MUST match trials 'tr' with the same keyword in trials(tr).stim_type
% saves result into respective column of 'trials_events' in each sessionCacheFile
% - rows = trials
% - values = zeros (... |
0bc34b64fd7af8b01ec923ca0bbaaa7920754cceba6e0882c8b1e539a4e2dac4 | MATLAB | 1,188 | 45 | function result = is_orthogonal_set(A)
%
% Orthogonal Sets
%
% is_orthogonal_set(A) determines if a set of vectors in Euclidean n-space
% is orthogonal. The matrix A is formed from these vectors as its columns.
% That is, the subspace spanned by the set of vectors is the column space
% of A. The value 1 is r... |
834d2008b2f9bdcf1267c472fb173dc7294edfe6d16b3e3d0bd6206c99b392a3 | MATLAB | 1,188 | 50 | function obj = init_latent(obj)
N = numel(obj.data);
% ---------------------------------------------------
% Generate random coordinates from prior distribution
% ---------------------------------------------------
Z = zeros(obj.M,numel(obj.data));
for n=1:numel(obj.data)
Z(:,n) = mv... |
0d850da3b3c8a75df05dae58a48f33be895a3c687f21e343bed461e300dfbb44 | MATLAB | 1,189 | 29 | %{
trk.EyeFrameDetection(computed) # eye frames with detected eye
->trk.EyeFrame
---
pupil_x : float # pupil x position
pupil_y : float # pupil y position
pupil_r_minor : float # pupil radius mi... |
1823b7ec85161d9a8b1df5adf0a7192437bc13a28a50c9da80b0d93c3925e45e | MATLAB | 1,190 | 39 | function report
fprintf '\nReso pipeline:\n'
r = rf.Session & 'session_date>"2016-02"';
%r = 'animal_id=8623';%r = 'animal_id=8628';
fprintf('Mice %s\n', sprintf('%d ', fetchn(common.Animal & r, 'animal_id')))
progress(pre.ScanInfo, r)
progress(pre.ScanCheck, r)
progress(pre.AlignRaster, r)
progress(pre.AlignMotion, ... |
3b29cd075e774585be595eec7eb64c4436b09dda9bf8fc4727bbb07bb1d59d40 | MATLAB | 1,190 | 29 | function setup_sepia()
% One-time setup: creates local, machine-specific copies of SEPIA's
% config files from their tracked templates, for whichever ones don't
% already exist.
thisDir = fileparts(mfilename('fullpath'));
% {template filename, local filename, message shown when it's created}
configs = { ...
'Spec... |
52302aadcf2eb171416ce6b9d81f0aee3dfe68f6255b2dae9b42e2cd12d24754 | MATLAB | 1,190 | 28 | function nodeSize = getNodeSize(z_i, nodeScaleF, Params)
%GETNODESIZE Summary of this function goes here
% Detailed explanation goes here
if isfield(Params, 'nodeScalingMethod')
if strcmp(Params.nodeScalingMethod, 'Linear')
nodeSize = max(Params.minNodeSize, z_i/nodeScaleF);
elseif strcmp(Params.nodeS... |
e95cdab88247926728fd104145a51c6e12f8b1c76aa367b32c22d0c9dcbe5ac8 | MATLAB | 1,190 | 41 | function [K,dK] = covGE(mode, par, hyp, varargin)
% Gamma Exponential covariance function.
% The covariance function is parameterized as:
%
% k(x,z) = exp(-r^gamma), r = maha(x,z)
%
% where maha(x,z) is a Mahalanobis distance and gamma is the shape parameter
% for the GE covariance. The hyperparameters are:
%
% hyp = ... |
1510ee626937988bf1ca7c03ecde4229d7b1ed7322c17642b41774e02d348010 | MATLAB | 1,191 | 29 | function [ output_re ] = myRescale( stimuli_time, output, output_time )
%Background:
%1, Camera is working at the limit speed, the read out time for each
%frame may vary a little bit from file to file.
%2, Input and Output are recorded from different files.
%3, The initiate of the each trial is well aligned (time poi... |
461c00c87ad9eed0a759dc2f97829e8e49df09b8c77865041b84709379e05b17 | MATLAB | 1,191 | 33 | function basename = basenameFromBasepath(basepath)
% basenameFromBasepath-gets basename from a basepath input to a function. Uses name of the last
% directory on the path to give basename. Takes care of the problem of the
% fact that if a fileseparator is on the end of the basepath, you have to
% take it off first.
%... |
a529955105d065509b10061ccf383264ee8e496a507733a7392365c073d33628 | MATLAB | 1,191 | 40 | function plot_pca(ax,pcs,ens_labs,ens_cols)
% Reference paper: Herzog et al. 2020 "Scalable and accurate automated method
% for neuronal ensemble detection in spiking neural networks"
% https://www.biorxiv.org/content/10.1101/2020.10.12.335901v1
% Rubén Herzog October 2020
cla(ax);
np = size(pcs,2);
if isempty(ens_la... |
f8d2b9adef2f585363d46cf219e437c8a6304d4c124f3e245c7dcc610455f14d | MATLAB | 1,191 | 36 | function v = makemodel(p,ng)
%MAKEMODEL Helper function to make model matrix
% P = max model term size, NG = number of grouping variables
% or
% P = vector of term codes
% We want a matrix with one row per term. Each row has a 1 for
% the variables participating in the term. There will be rows
% summing up to ... |
3073e10983c100e5d52d5777aa01c8c4e8a5fba0420ce783eb05b49260422d7e | MATLAB | 1,192 | 42 | function myelin = Restore_Oligos( ...
myelin, replacement_percentage)
% RESTORE_OLIGOS
%
% Reintroduces a proportion of previously non-active (dead)
% oligodendrocytes and restores their associated myelin to a fully
% healthy state.
%
% INPUTS:
% myelin - myelin structure containing state inform... |
f446323f907121bf86bf8078ca46469ea3dcafcfd4d11ecaa399134b6198373b | MATLAB | 1,193 | 45 | function [X_scal] = test_pretreatment(X,param)
% pretreatment for test data
%
% INPUT
% X: data matrix (samples x variables)
% param: output data structure from data_pretreatment routine
%
% OUTPUT
% X_scal: pretreated data matrix (samples x variables)
%
% version 1.0 - september 2009
% Davide Ballabio... |
f63ee430b4e8c1abe00da22c328543ff334087675302ea3e7e9c9ec4c6566c43 | MATLAB | 1,193 | 40 | function img_labels=expand(msk,img_labels,Ngh,c)
ind=find(~msk); %index of voxels in subcortical mask
ind_labels=find(img_labels);
ind_missing=setdiff(ind,ind_labels);
%%%
tmp=zeros(size(img_labels));
tmp(ind)=1:length(ind);
adj=spalloc(length(ind),length(ind),10000);
for i=1:length(ind)
[xx,yy,zz]=ind2sub(size(im... |
fdf5f73a3c603fb7a00b29b0715978ebf378bb52fefd36167ab0919044e6819a | MATLAB | 1,193 | 42 | function sero_pulseq_nii2LineProfile(niftiFile, sliceNum)
% Function allowing the user to choose a column from a nii image and
% plot the line profile of that column.
try
%Read the NIfTI image with double precision
nii = mdm_nii_read(niftiFile);
%Display the nii image
if nargin<2
%get cen... |
1ba63338414e854fac43dc7650968078b736a352b46c8a18b910a36d0d461766 | MATLAB | 1,194 | 45 | function r = celleval(f, varargin)
%FUNCEVAL calculates the value of the function f at the cell variable phi
% f must be able to accept matrices
% f: function handle
% phi: input to the function f
% r: output of the function f
% f can handle 6 input phi variables, but they should all be of the same
% class
%
% SYNOPSIS... |
4ff29852db4d6b08c27a67de4a6981a5fdeed5ed7fb5e12bcadd4dc8b2dad098 | MATLAB | 1,194 | 41 | function stats = regionprops3(this, varargin)
% Estimates properties from a binary image via connected components.
%
% Y = MrImage()
% Y.regionprops3('conn', connectivity, 'props', {'Prop1', 'Prop2'})
%
% This is a method of class MrImage.
%
% IN
%
% OUT
%
% EXAMPLE
% stats = Y.regionprops3('conn', 6, 'properties... |
a302ecde2068259bca6ec78286f18ea4e559034f0360fd57001e807a39503ae4 | MATLAB | 1,194 | 38 | function [b, er, stats] = regress_RPE_vs_rew(A, nback)
%regress model-predicted RPEs against rewards
%inputs: A struct. If you give it the S struct, will convert it to A struct.
%nback specifies number of previous trials to regress.
if isfield(A, 'pd') %if it's an S struct.
[A, ~, ~] = parse_data_from_mysql(A);
en... |
29521df43e2c5197d89c5c072d0bcc55f0b4d528f027dc6dcdf75583e45e7400 | MATLAB | 1,195 | 27 | function vectors = shuffle2(vector,nsample,window)
% Randomly shuffle "nsample" times an input vector broken into segments of
% windows and return an output matrix containing all the shuffled vectors.
% vector: 1-by-n datapoints
% nsample: the number of repetition
% window: the minimum size of the segment to be s... |
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