sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
e91a8fd095f41dbd7502465c2e0b985fb76232083ba1b74b58b72a30ae5ad477 | MATLAB | 1,100 | 36 | function [channelNumber] = plx_ad_resolve_chennel(filename, channel)
% plx_ad_resolve_chennel(filename, channel): returns .plx file raw a/d channel number for the specified channel name
%
% [channelNumber] = plx_ad_resolve_chennel(filename, channel)
%
% INPUT:
% filename - .plx file name
% channel - 0-based channel... |
8d7f23d5d7e75136b25af7bd7862c1a0289c0ace36718a4e120d0d3a4b2c7897 | MATLAB | 1,101 | 40 | function varargout = offset(varargin)
% file_array's offset property
% For getting the value
% dat = offset(obj)
%
% For setting the value
% obj = offset(obj,dat)
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: offset... |
eac56433bdfe6fec618daa17c1afefa9220136f3a18e84ec305c652ec6bfb0ec | MATLAB | 1,102 | 47 | function W = pnmfeu(X, r, max_iter, tol)
%
% compute PNMF based on Euclidean distance
% input:
% X nonnegative data input (m times n)
% r number of PNMF components
% max_iter maximum number of iterations (defaut 5000)
% tol convergence tolerance (default 1e-5)
% output:
% W ... |
a459f2ed8ce48895c0f2a7c296fc4004c6677a5f1c3c8dbb4e5e3c2485dc5340 | MATLAB | 1,103 | 44 | function [gm]=geometricMean(v)
% geometricMean of vector v
% for example
% v=[1,2,3,NaN];
% [gm]=geometricMean(v)
%%%%
% Copyright (C) <2012> <Yifeng Li>
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software ... |
88fc21b15200030b576acda0c8afd31bf3f8eeb433e12504402356b9de4ecc8f | MATLAB | 1,104 | 34 | %PERCENTILE: The kth percentile Pk is that value of X, say Xk, which
% corresponds to a cumulative frequency of Nk/100. ( cited from
% Eric W. Weisstein. "Percentile." From MathWorld--A Wolfram Web
% Resource. http://mathworld.wolfram.com/Percentile.html )
%
% Usage: Pk = percentile(X, Nk);
%
% In which, X can ... |
4804227e7955de0eb71bd7b32d6a4c63d188d4b7afdec5dce96d7817210e3b38 | MATLAB | 1,106 | 39 | function [x,obj] = hillclimber2c(DD, x, varargin)
%HILLCLIMBER Performs hillclimbing using initial solution
%
% function [x, obj] = hillclimber(DD, x, varargin)
%
%
%
% This file is part of the Matlab Toolbox for Dimensionality Reduction.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are... |
0cfb1389d6d6a43becfdb6ba4419e5c5158786099e049e4d19ddb984ab0520c1 | MATLAB | 1,108 | 39 | function [ERR, TBL] = export_features(handles, batchmode)
warning off
curclass = get(handles.popupmenu1,'Value');
filename = sprintf('%s_A%g_Features', handles.params.TrainParam.SAV.matname, handles.curranal);
[nlabels, nmodal] = size(handles.visdata_table);
if strcmp(handles.modeflag,'regression')
ModeStr = 'Rg... |
36fcea3177088080f486b26f8a61c4e6cc1be642bc36fddddc2b032ea9e437ab | MATLAB | 1,108 | 40 | function CutterOption_CreateClustersFromTFiles(self)
% find T files
[fn, fd] = uigetfile('*.t', 'T Files to get from', '*.t','MultiSelect', 'on');
if isempty(fn)
return;
else
if ~iscell(fn)
fn = {fn};
end
self.StoreUndo('CreateClustersFromTFiles');
% get timestamps
MCD = MClust.Get... |
6238519378558162f76a52dd3d77b44b256924f9f69a1b60d5e41d08a1dc1c88 | MATLAB | 1,109 | 40 | % fit 2D gaussian to cell with lam pixel weights
function params = fitMVGaus(iy, ix, lam0, thres)
% normalize pixel weigths
lam = lam0;
% iteratively fit the Guassian, excluding outliers
for k = 1:5
lam = lam / sum(lam);
mu = [sum(lam.*iy) sum(lam.*ix)];
xydist = bsxfun(@minus, [iy i... |
065779e50e6f3328dbdd5dc7886eb02616f6c426ad7011f10ebc10defe4af2ef | MATLAB | 1,112 | 46 | function fn = FindFile(globfn, varargin)
% fn = FindFile(globfn, parameters)
%
% Finds a single file that match a wildcard input globfn.
% Based on matlab's dir function.
% Can searche all directories under the current directory.
%
% INPUTS
% globfn -- filename to search for (you can use '*',
% but... |
5a021d1e35ee3434557576505fbbe27a751c0c0079c4efae3d7d1a6c6c56f5d7 | MATLAB | 1,113 | 32 | % SB2_SIGMOID Generic sigmoid function for SPARSEBAYES computations
%
% Y = SB2_SIGMOID(X)
%
% Implements the function f(x) = 1 / (1+exp(-x))
%
%
% Copyright 2009, Vector Anomaly Ltd
%
% This file is part of the SPARSEBAYES library for Matlab (V2.0).
%
% SPARSEBAYES is free software; you can redistribute it and/or m... |
784b19305e85de0e8bf63375ddec0c78f1c77626778caeedb7565d0a4abc41bd | MATLAB | 1,114 | 30 | function IN = nk_PerfANOVAObjOld(Y, IN)
global VERBOSE
[~,n] = size(Y);
%IN.p = zeros(n,1);
%IN.F = zeros(n,1);
%IN.R2 = zeros(n,1);
if VERBOSE, fprintf('\t running ANOVA on %g variables ',n); end
IN.beta = pinv(IN.X)*Y;
% here we use a pseudoinverse:
% X is rank deficient, i.e. regressors are not independent, since ... |
03c6f0ba3ca583a091497993d3757b4a4a0e2b839887c3888f9f00ec5082a4dd | MATLAB | 1,116 | 25 |
function SVR_NFolds_Sort_Permutation_Sub(Subjects_Data_Path, Subjects_Scores, FoldQuantity, Pre_Method, C_Range, ResultantFolder)
%
% Sub-function for the SVR_NFolds_Sort_Permutation.m
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Written by Zaixu Cui: zaixucui@gmail.com;
% ... |
2aa5cc6e637a2f390046e4fd4c15afc06e56b16c3241fcedb3a712f17d28ed60 | MATLAB | 1,117 | 33 | function [X, W, mu_X] = prewhiten(X)
%PREWHITEN Performs prewhitening of a dataset X
%
% [X, W, mu_X] = prewhiten(X)
%
% Performs prewhitening of the dataset X. Prewhitening concentrates the main
% variance in the data in a relatively small number of dimensions, and
% removes all first-order structure from the data.... |
9b77913073470978c375259ec5f3314e41c4e0497aa29c32d4f3f4d2ace4393d | MATLAB | 1,117 | 27 | function runConcatStep6(path)
%% Pipeline for the proper concatenation of miniscope data across sessions
% Developed by Daniel Almeida Filho July/2020 (SilvaLab - UCLA)
% If you have any questions, please send an email to
% almeidafilhodg@ucla.edu
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
0292d8156d335807d0ade6bf0136ddd1411fd43c42de886ef7e0f1f4c285fb9a | MATLAB | 1,119 | 38 | function op = prox_nnl1( q )
%PROX_NNL1 non-negative L1 norm.
% OP = PROX_L1( q ) implements the nonsmooth function
% OP(X) = norm(q.*X,1), OP(X)>=0
% Q is optional; if omitted, Q=1 is assumed. But if Q is supplied,
% then it must be a positive real scalar (or must be same size as X).
%
% Update Fe... |
7379348c89256afdeeea9384139dcab3dc42a8b4cde4908655c5d4371c3b5554 | MATLAB | 1,122 | 35 | function [ wY, wYnew, wYoocv ] = nk_WeightData(W, TRd, CVd, OOCVd, SelectFlag, ScaleFlag)
wYnew = []; wYoocv = [];
if ~exist('ScaleFlag','var'), ScaleFlag = false; end
if size(W,2) == 1, W = W'; end
switch SelectFlag
case 1
ind = W~=0;
fprintf(' Selecting %g non-zero voxels ...', sum(ind))
... |
32b91cda49285aafebeea0013531c73d3d6e6871b134c08f5ece4d2913ec5121 | MATLAB | 1,123 | 38 | function [channelNumber] = plx_event_resolve_channel(filename, channel)
% plx_event_resolve_channel(filename, channel): returns .plx file event channel number for the specified channel name
%
% [channelNumber] = plx_event_resolve_channel(filename, channel)
%
% INPUT:
% filename - if empty string, will use File Open d... |
876238c5c9dc9243b2c35e29b43d57771b72cfeb7a6bb50111e62bc5162ad791 | MATLAB | 1,123 | 27 | function [sY, IN] = nk_PerfDiscretizeObj(Y, IN)
% =========================================================================
% FORMAT [dY, IN] = nk_PerfDiscretizeObj(Y, IN)
% =========================================================================
% Do one of the following to digitize feature matrix Y
%
% Either:
% Dis... |
54f9ec8453a74358a639ddb7667ef333b27fc634e63f1107681a91a9f0b654f5 | MATLAB | 1,124 | 40 | clear;clc;
%This produces 4 .mat files.
% 1. Dynamics_Outputs_*: Contains the variables required for analysis in
% 'Nonergodicity and Simpson's paradox in neurocognitive dynamics of cognitive control'
% 2. SummaryAll_cog_prad_*: Detailed summaries from JAGS output required for analysis in
%'Computational Model... |
be4cb22808c3ed104b90a40a97a1934d66418c39ee55dc520c59258e75c8ecd1 | MATLAB | 1,124 | 37 | function params = fitted_params_from_posterior(self,xyz_mode)
% feather.fitted_params returns the maximum likelihood fitted parameters
% This function returns the parameter value corresponding to the maximum
% value of the posterior density. This value reflects the entire distribution
% and should be more stable (... |
fb972351b8065a141b82e2c62d72648d4ce1e7ee439e0ea61300c7c17c83c2a9 | MATLAB | 1,126 | 33 | function [S,C,L] = small_world_ness(A,LR,CR,FLAG)
% SMALL_WORLD_NESS computes small-world-ness of graph
% [S,C,L] = SMALL_WORLD_NESS(A,LR,CR,FLAG) computes small-world-ness score S of
% graph described by adjacency matrix A, given mean shortest path
% length LR and mean clustering coefficient CR averaged over a random... |
4ea0a0afb00a5bc18d31ddc450c78ad7a217490b2eadf22ab40fd6072f298e46 | MATLAB | 1,127 | 29 | function datacontainer = nk_LoadLinkedData(datacontainer, varind)
global VERBOSE
if iscell(datacontainer.Y)
for i=1:numel(varind)
if ischar(datacontainer.Y{varind(i)})
if exist(datacontainer.Y{i},"file")
fprintf('\nLoading data file %s into modality #%g', datacontainer.Y{varind... |
bb5a7ee2b2439decf63bb48af1f914e5489b7a0f1aaa03257460200bf5371858 | MATLAB | 1,127 | 37 | %==========================================================================
%FORMAT feats = nk_RSS(Y, P, transp)
%==========================================================================
%Performs random subspace sampling
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%(c) Nikolaos Koutso... |
6dbfaed5865ec6a1494f80092c0ab52a5aed3728c070b1eade7041f12ecd1b46 | MATLAB | 1,128 | 37 | function X = multi_transpose (X)
% Multi-task cell array transpose.
%
%% INPUT
% X: {n1 * n2} * t - input matrix
%
%% OUTPUT
% X: {n2 * n1} * t - transpose every matrix in the cells.
%
%% LICENSE
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Pu... |
646c14b9ff3de46dbbd435f759b4cc0257e994e2b98c4865a2d249fb10f64298 | MATLAB | 1,129 | 44 | function distplot(y,cutoff,class,nid)
%DISTPLOT plots the vector y versus the index.
% At the height of the cutoff value a red vertical line is plotted.
%
% Required input arguments:
% y : the vector to be plotted
% cutoff : a cutoff value
%
% Optional input arguments:
% class : the class of the y-vector ... |
dd1f2eb1b5062f0c738ecbcbdaf3cbb88a44aa51859b034e92eb7ce4602bf808 | MATLAB | 1,130 | 37 | % op_arr = DR_movavg(ip_arr, window, stepping, SR, mov_key)
% Input parameters:
% ip_arr: m * n array
% window: length of window in sec.
% stepping: the next window is step sec. after ini. time of this window
% SR: sampling rate
% mov_key: the column of time point
% Output parameters:
% op_a... |
0f775528672d9515598d810cd7586351af6e7ab6dd922e09db6525be6d780ddc | MATLAB | 1,131 | 47 | function wcoh_fig(wc,phL,t,f,coi,varargin)
%WCOH_FIG Wavelet coherence map.
% WCOH_FIG(wc,phL,t,f,coi) draws wav-coherence map.
%
% Input parameters:
% WC MxN matrix of MSWC values. 1D: frequency, 2D: time
% phL MxN matrix of MSWC phase lag values. 1D: frequency, 2D: time
% t 1xN time vec... |
9dac5b8b814c8ac1cbaccc113a3e4b02e1be085ff31b1a947b44d7661fd24b37 | MATLAB | 1,131 | 31 | function msPlayVidObj(vidObj,downSamp,columnCorrect, align, dFF, overlay)
%MSPLAYVIDOBJ Summary of this function goes here
% Detailed explanation goes here
hSmall = fspecial('average', 2);
for frameNum=1:downSamp:vidObj.numFrames
frame = msReadFrame(vidObj,frameNum,columnCorrect,align,dFF);
... |
f614545bda35a41e9be764e4f5e739f6db1a318011830233bfb13fea60892609 | MATLAB | 1,131 | 28 | function mripy_merge_asc(lh, rh, output)
%MRIPY_MERGE_ASC Merge FS/SUMA surfaces (left and right hemisphere) in *.asc format.
% Note that vertices indexing is zero-based and continuous.
%
% References
% 1. https://github.com/PyMVPA/PyMVPA/blob/master/mvpa2/tests/test_surfing_afni.py
% 2. http://www.pymvpa.org/g... |
ee976370c0c780f8da41eb80c2571ed4f74d385e4876374659eee4454872c1ff | MATLAB | 1,132 | 52 | function X = mask(tsa, t0, t1, masking)
%
% mTSD = ctsd/Mask(tsd, t0, t1, masking)
%
% INPUTS:
% X = ctsd object
% t0 = sets of start times
% t1 = sets of end times
% masking = 1=NaN times inside trial pairs, 0=NaN times outside trial
% pairs (default = 1)
% NOTE: must be SAME units as tsd!
%
%... |
cfed2d032e5b5bfccba5e840ee6db29578e20a80438afea1037e09ac85c54266 | MATLAB | 1,133 | 28 | function [wave] = PL2Waves(filename, channel, unit)
% PL2Waves( filename, channel, unit ): read spike timestamps and waveforms from a .pl2 file
% returns waveform values in millivolts
%
% wave = PL2Waves( filename, channel, unit )
% wave = PL2Waves( filename, 'SPK01', 1 );
% wave = PL2Waves( filename, 2,... |
dfb409e71442c12ade5b1d154a554c8070445a28b026bb1877aa6ef152dd9760 | MATLAB | 1,135 | 51 | load faces.mat;
X = X / 255;
disp 'Press any key to show example faces in the input dataset.';
pause;
ShowNMFBasis(X(1:20:2000,:)', 32, 32, 2, true);
disp 'Press any key to run the PNMF algorithm based on the Euclidean distance.';
disp ' W = pnmfeu(X'', 16)'
pause;
W = pnmfeu(X', 16);
disp 'Learning is finished.... |
63f70e01d3af456d6e97d77059edc7a0a85f498f44b21337a57a0397b2faf570 | MATLAB | 1,136 | 34 | function dir_srand=dir_generate_srand(s1,ntry)
% Syntax:
% dir_srand=dir_generate_srand(s1)
% s1 - the adjacency matrix of a directed network
% ntry - (optional) the number of rewiring steps. If none is given ntry=4*(# of edges in the network)
% Output: dir_srand - the adjacency matrix of a randomized network with t... |
a447c460dcc24d622a8fd3d4b33b31bd03e9149917ca41f5656cc203a391d824 | MATLAB | 1,136 | 40 | function [wave,f] = eegwavelet2(dat,sr)
%EEGWAVELET Wavelet calculation.
% [wav,F] = EEGWAVELET(DATA,SR) performs wavelet calculation on
% input EEG data (DATA) sampled at SR sampling rate. Complex wavelet coefficients
% and scale vector (F) are returned. DATA is first
% standardized. A minimal interesti... |
3a7a9f9a1ae62c4e68701174b8e2cd60ea5c43f22f69c33b5b77a9e1c5fb8704 | MATLAB | 1,140 | 51 | function Projection3(self)
% Recalculate Projection (self)
% Projection plan 3
%
% Modified from Jadin Jackson's original code.
MCD = MClust.GetData();
nFeatures = length(self.Features);
% --------------------------
% Find points in n-dimensions
C1 = self.PrimaryCluster;
C2 = self.SecondaryCluster;
FD = nan(nFeat... |
f4f5a96806e0fd1876903c848ab52c6d719ddcbc0b36c8aadd7476bd4ed7e09a | MATLAB | 1,141 | 50 | function [str,n_pars] = nk_ConcatParamstr(param, longflg)
str = []; if ~exist('longflg','var') || isempty(longflg), longflg = 0; end
n_pars = numel(param);
if longflg
for i=1:n_pars
str = conv_param(param(i),str);
end
else
if n_pars > 1
str = sprintf('%g Params: ',n_pars);
str = sp... |
039730ff6ea373676a4462fc46b27b77df9124e8f4d43b6d3c39adbe2fad3323 | MATLAB | 1,142 | 29 | % script to test the adjustment to combat
%matlab
p=10000;
n=10;
batch = [1 1 1 1 1 2 2 2 2 2]; %Batch variable for the scanner id
dat = randn(p,n); %Random data matrix
%and let simulate an age and disease variable:
age = [82 70 68 66 80 69 72 76 74 80]'; % Continuous variable
disease = [1 2 1 2 1 2 1 2 1 2]'; % Cat... |
0c88d48209f990fdf0686efa1a9bb2efb37221f744b7ea5022b7d5e19aa2de31 | MATLAB | 1,143 | 55 | function D = EuDist2(fea_a,fea_b,bSqrt)
% Euclidean Distance matrix
% D = EuDist(fea_a,fea_b)
% fea_a: nSample_a * nFeature
% fea_b: nSample_b * nFeature
% D: nSample_a * nSample_a
% or nSample_a * nSample_b
if ~exist('bSqrt','var')
bSqrt = 1;
end
if (~exist('fea_b','var')) | isempty(f... |
37550da1ca1a2099e071e893d25482d2e5894f215999bfac8a024edeee880e3a | MATLAB | 1,144 | 30 | function [ nexFile ] = nexAddNeuron( nexFile, timestamps, name )
% [nexFile] = nexAddNeuron( nexFile, timestamps, name ) -- adds a neuron
% to nexFile data structure
%
% INPUT:
% nexFile - nex file data structure created in nexCreateFileData
% timestamps - vector of neuron timestamps in seconds
% nam... |
226f1d0cff6f19c894db59847e92946e5c0dc9fdaa9f366fa220f86ca5944644 | MATLAB | 1,145 | 34 | %% add path
CNMF_dir = fileparts(which('cnmfe_setup.m'));
addpath(fullfile(CNMF_dir, 'ca_source_extraction'));
addpath(genpath(fullfile(CNMF_dir, 'ca_source_extraction', 'utilities')));
addpath(genpath(fullfile(CNMF_dir, 'ca_source_extraction', 'endoscope')));
addpath(fullfile(CNMF_dir, 'GUI'));
addpath(fullfile(CNMF_d... |
be504b98383e11c24aaf42de8d5efcfd7a0f63121a748841ac4dd7c1bb8b7247 | MATLAB | 1,145 | 45 | function C = nk_CalcSpatConst(Y,Vm)
indvol=[];
% Read brainmask into vector format
for sl=1:Vm.dim(3)
% read mask
M = spm_matrix([0 0 sl 0 0 0 1 1 1]);
%M1 = Vm.mat\V.mat\M;
mask_slice = spm_slice_vol(Vm,M,Vm.dim(1:2),1);
ind0 = find(mask_slice > 0.5);
ind = ind0 + (sl - 1)*prod(Vm.dim(1:2));... |
d116084bf221ec008df2bb9955f0d6a39afa535348c24dff7ac719a09e3ad361 | MATLAB | 1,145 | 25 | % 20160415 CRM
% 20180502 SK: modified to read in label names from a text file
% if 'options.labelfile' is 'none', label names default to numerical
addpath('../calcFD')
sample = 'IXI';
subjectpath = sprintf('~/path/to/data/%s/surf/',sample);
subjects = {'.'};
options.alg = 'd... |
77137b7887ca045a8394d893bbad81309c4c03100e88514bc792c91835f542c1 | MATLAB | 1,147 | 37 | function F = setPapertoFigPos(F)
% This function change's the paper size of a figure to match
% the space the figure takes up on the page. This is mainly
% since it allows you to set the 'position' argument to the
% desired size and then have the resulting ps/eps/pdfs come out
% without a bunch of whitespace.
%________... |
21c3650c7576adc076f6075f5edf3fffdc4cea4d5ae466180e2abc4282a3ec5e | MATLAB | 1,148 | 34 | % =========================================================================
% FORMAT param = BAC2(expected, predicted)
% =========================================================================
% Compute Balanced Accuracy of classification
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% (... |
55bc225490909c70f2140bbce59c970e31b925e2b7f3337a4679f9a1dd8ed56b | MATLAB | 1,150 | 54 | function out = fixTrailing(in,varargin)
p = inputParser;
p.addRequired('in',@(x) exist(x,'file'));
p.addParameter('delimiter','\t');
p.addParameter('out','');
p.parse(in,varargin{:});
inputs = p.Results;
% setup output
if isempty(inputs.out)
[fpath,fname,fext] = fileparts(in);
inputs.out = fullfile(fpath,[fname... |
0bb9f0402a88fb82973d37f44533647d37ad486ee4c603e8dd8f7a69dee766ce | MATLAB | 1,154 | 30 | function [ad] = PL2AdSpan(filename, channel, startCount, endCount)
% PL2AdSpan(filename, channel, startCount, endCount): read a span of a/d data from a .pl2 file
% returns a/d values in millivolts
%
% examples:
%
% ad = PL2AdSpan(filename, channel, startCount, endCount)
% ad = PL2AdSpan(filename, 48, 1, ... |
591ba159c1f52448863d74f28cad29139e6ba396fa02b4fc2c26c3181c9d9976 | MATLAB | 1,158 | 22 | % This make.m is for MATLAB and OCTAVE under Windows, Mac, and Unix
function make()
try
% This part is for OCTAVE
if(exist('OCTAVE_VERSION', 'builtin'))
mex libsvmread.c
mex libsvmwrite.c
mex -I.. train_liblin244.c linear_model_matlab.c ../linear.cpp ../newton.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ... |
e37e8c364f980acbaf4ab7f6f5ef8f71de19aa24322df6aeef87ca630bb708a9 | MATLAB | 1,159 | 29 | % CL Septembre 2022, landelle.caroline@gmail.com // caroline.landelle@mcgill.ca
% Toolbox required: Matlab, SPM12
%%
function Norm=Norm_dartel(dartel_template,filename_DeformField,i_file,SPM_Dir,resolution)
%______________________________________________________________________
%% Initialization
%________________... |
40c6efa683e81c742ec59d51eefe84488b318e77ae1117a6b8362ccbda2ad5ad | MATLAB | 1,161 | 39 | % authors: Ioannis Psorakis psorakis@gmail.com, Theodoros Damoulas theo@dcs.gla.ac.uk
% Copyright NCR, 2009
%
% Use of this code is subject to the Terms and Conditions of the Research License Agreement,
% agreed to when this code was downloaded, and a copy of which is available at
% http://www.dcs.gla.ac.... |
bf2972ab3e70ef15290e172ec118919a190093ac9cdf6e9847757e73f00fc50d | MATLAB | 1,161 | 37 | function [sY, IN] = cv_graph_PerfSparsityThres(Y, IN)
% =========================================================================
% FORMAT function [sY, IN] = nk_PerfElimZeroObj(Y, IN)
% =========================================================================
% Remove features with zero-variance, and ANY Infs and NaNs... |
199eda7b719a69a751daf52297ba138913c9657a9942414be48df9a67b032049 | MATLAB | 1,163 | 34 | % =========================================================================
% FORMAT param = BAC(expected, predicted)
% =========================================================================
% Compute Balanced Accuracy of classification
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% (c... |
e935b047dd278d9173f8cf43827beb171652a2451d59ac5751e2372f22b8b2c7 | MATLAB | 1,166 | 42 | function varargout = dim(varargin)
% file_array's dimension property
% For getting the value
% dat = dim(obj)
%
% For setting the value
% obj = dim(obj,dat)
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: dim.m 7147 2... |
3d7c4398fefd23fb7c2a56a1908f8eebcd020fccfb9dc5396a8372c3722c22f9 | MATLAB | 1,167 | 44 | classdef NRadioSwitch < handle
properties
buttongroup; % group for set
buttonElements; % individual buttons
end
methods
function self = NRadioSwitch(buttonNames, varargin)
nButtons = length(buttonNames);
self.buttongroup = feval(@uibuttongroup, varargin{:});
set(self.buttongroup, 'Units', 'Normali... |
7e1104fce9d989362ec92797dce89b1a0c3e93e26f3c0c7c1325f57a2e7e77d1 | MATLAB | 1,167 | 53 | function [inputMap] = mbm_read_map(mapList)
% Read the gifti or mgh maps from the file paths.
%
%% Input:
% mapList - Cell array of character vectors.
% - Each array element contains the path to an input
% anatomical map in a gifti or mgh file.
%
%% Output:
% inputMap - Matrix of ro... |
85cda1568c9f3d3f1c665e6c69c14d814372750e6b1538850db2e3508a5a7b8f | MATLAB | 1,168 | 27 | %% prepare_workspace_example.m
% Example template for preparing the workspace before building the benchmark.
%
% Replace the placeholder loading code below with your own data-loading
% pipeline. The benchmark builder expects the following variables in the
% MATLAB workspace:
%
% EEG_all_epochs : [N_eeg x T_src] clean... |
bb9a3bb0c3787d9b159428c58de92681608d6e506b6d87cfcaa92241b8dad03e | MATLAB | 1,168 | 37 | function path = retrieve_shortest_path(s,t,hops,Pmat)
% RETRIEVE_SHORTEST_PATH Retrieval of shortest path
%
% This function finds the sequence of nodes that comprise the shortest
% path between a given source and target node.
%
% Inputs:
% s,
% Source node: i.e. node where the shortest path... |
ce7afe3b609f7390ff5f10f6b78b1408b883f39dcab134492d8e8345a459bfd6 | MATLAB | 1,170 | 33 | function IN = nk_PerfANOVAObjNew(Y, IN)
global VERBOSE
[~,n] = size(Y);
%IN.p = zeros(n,1);
%IN.F = zeros(n,1);
%IN.R2 = zeros(n,1);
if VERBOSE, fprintf('\t running ANOVA on %g variables ',n); end
notnan = sum(isnan(Y),2)==0;
X = IN.X(notnan,:); Y=Y(notnan,:);
IN.beta = pinv(X)*Y;
% here we use a pseudoinverse:
% X ... |
ae152230159d8c7e84f02aaf068c395141ff4c05f4d857fcfad4dc7acd2e78df | MATLAB | 1,171 | 43 | % authors: Ioannis Psorakis psorakis@gmail.com, Theodoros Damoulas
% theo@dcs.gla.ac.uk
% Copyright NCR, 2009
%
% Use of this code is subject to the Terms and Conditions of the Research License Agreement,
% agreed to when this code was downloaded, and a copy of which is available at
% http://www.dcs.gla.ac.... |
b6e9774ee62077d848cf97cfc48f1d5951d1d619b9be5c3838d1e93871c352f3 | MATLAB | 1,172 | 34 | function testClassPredicted=getLabel(Y)
% obtain class labels from Y, called by logistic regression
% for example
% Y, n by k matrix, it can be posterior probability
% testClassPredicted: n by 1 vector, intiger, each element is from {1,2,...,k}
%%%%
% Copyright (C) <2012> <Yifeng Li>
%
% This program is free software... |
e79d33f02e636f92770fe587a616f4e74a86e760bb9d4a7743b7dc31fca1177e | MATLAB | 1,172 | 43 | function result=adm(x)
%ADM is a scale estimator given by the Average Distance to the Median.
% It is defined as
% adm(x) = ave(|x_i - med(x)|)
% If x is a matrix, the scale estimate is computed on the columns of x. The
% result is then a row vector. If x is a row or a column vector,
% the output is a scalar.
%
% T... |
80a999d212b558a4ba25262d03863e61e21f45f790863b597aa13b9f971ba722 | MATLAB | 1,180 | 38 | function optionFinal=mergeOption(option,optionDefault)
% Merge two struct options into one struct
% Usage:
% optionFinal=mergeOption(option,optionDefault)
% option: struct
% optionDefault: struct
%%%%
% Copyright (C) <2012> <Yifeng Li>
%
% This program is free software: you can redistribute it and/or modify
% it unde... |
14620dce4341e2cc342ac8e28f181e622c98a99f1244ea65ba8f9be5d60c7e47 | MATLAB | 1,183 | 38 | %% FUNCTION solve_12_norm
% l1,2 norm projection
%
%% LICENSE
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
... |
2813329ea4decd6e44998719a9ee4f503f91a4ea3e8924f8cc4f71c32bc5bc9f | MATLAB | 1,188 | 44 | function create(obj,wrt)
% Create a NIFTI-1 file
% FORMAT create(obj)
% Write out the header information for the nifti object
%
% FORMAT create(obj,wrt)
% Also write out an empty image volume if wrt==1
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust C... |
eb7b0b3b589d06293b689883e3b35aa1068cf141ba9a8385dd5558381bba1b04 | MATLAB | 1,189 | 36 | function w=SW(K,trainClass)
% compute the expected distance of an image from the mass center of a class
% K: kernel matrix
% trainClass: column vector, the class labels of the samples
%%%%
% Copyright (C) <2012> <Yifeng Li>
%
% This program is free software: you can redistribute it and/or modify
% it under the terms ... |
4fcc6186301232ad52f3eca75ae3630b199a292d36f87c092794ef2eb79b183e | MATLAB | 1,190 | 41 | function D = nk_FScoreFeatRankMdIqr(Y, L, N)
% Y : Data
% L : Target Labelss
ix = unique(L);
if numel(ix) == 2
indP = L==ix(1); indM = L==ix(2);
YP = Y(indP,:); YM = Y(indM,:);
% Mean of Positive / Negative Labels
mP = nm_nanmedian(YP); mM = nm_nanmedian(YM);
% Stan... |
558937f872216e01c22af41b8cb9e6944e3e1b70496ee1e3a10ed4f9c8c8f634 | MATLAB | 1,192 | 35 | <<<<<<< HEAD
function names = fieldnames(this)
% Fieldnames method for GIfTI objects
% FORMAT names = fieldnames(this)
% this - GIfTI object
% names - field names
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
% Guill... |
fa386bc6bde379c6b50e886e9956f844d3ebccb354c6b94d9089a64f083ffa11 | MATLAB | 1,192 | 38 | function [sY, IN] = nk_PerfPLSObj(X, Y, IN)
if iscell(Y) && exist('IN','var') && ~isempty(IN)
sY = cell(1,numel(Y));
for i=1:numel(Y),
% Define active indices depending on training or testing situation
if isfield(IN,'TsInd'), IN.indY = IN.TsInd{i}; else IN.indY = []; end
sY{i} = Perf... |
60d1c39b2ebce2fd35891e346588f267758fbd20d37e1a577c38bc4847fd4524 | MATLAB | 1,193 | 48 | function W = pnmfkl(X, r, max_iter, tol)
%
% compute PNMF based on I-divergence (non-nomarlized KL-divergence)
% input:
% X nonnegative data input (m times n, non-sparse)
% r number of PNMF components
% max_iter maximum number of iterations (defaut 5000)
% tol convergence tolerance (d... |
bcbec87dbe17cd438bda86c5e93efeac15349f72f153fdb0b2a0f3535144f97c | MATLAB | 1,194 | 38 | function new_Evinxx_parts(curr_resdir,event,newpart_names,newpart_inx)
%NEW_EVINXX_PARTS Adds new fields to Evinxx struct.
% NEW_EVINXX_PARTS(curr_resdir,event,newpart_names,newpart_inx) saves
% indices of new trial sets (NEWPART_INX), intersected with indices of
% epochs aligned to EVENT. Trial/ epoch indiced are ... |
4970942621972bd929a26a89b6abde78ff8fb0f349283d7849e0dfc87e737884 | MATLAB | 1,197 | 38 | function a = state_colors(self)
% Convert the state string into a colour
state_str = self.state_str;
[~,state_names,short_mapping] = bt_utils.state_cdata;
if ~iscell(state_str)
state_str = {state_str}; % Wrap one inside the cell
end
a = ones(length(state_str),1);
for j = 1:l... |
942217bd53fb0da703911b496ab9ef5dbf25d7412aecb2a98245f3964061485c | MATLAB | 1,198 | 43 | function RedrawAxes(self, ~, ~)
MCS = MClust.GetSettings();
% Something has changed in the control window, redraw as necessary...
if self.get_redrawStatus()
% window for display
if isempty(self.CC_displayWindow) || ~ishandle(self.CC_displayWindow)
% create new drawing figure
self.CC_dis... |
319adf9e6ff78746f69669802c82558e1b1861af8694c221ca01268603842935 | MATLAB | 1,200 | 39 | function [Pred, Pro] = ...
IMRelief_Sigmoid_FastImple_Predict2(train_patterns, train_targets, test_patterns, Weight, distance, sigma)
index_1 = find(train_targets==-1);N(1) = length(index_1);
index_2 = find(train_targets==+1);N(2) = length(index_2);
patterns_1 = train_patterns(:,index_1);
patterns_2 = train_patter... |
413fd1d178267466eb1850c7a3731045f3ca30636a2a7574c308abbcb10a299b | MATLAB | 1,200 | 44 | function n = calcFD_boxcount(vol,r)
% Implementation of the 3D box-counting algorithm.
% 20151025 CRM
if length(size(vol)) < 3 | length(r) < 1
% unable to calculate any box counting
disp('Failed to count!')
n = NaN;
return;
end
dim = size(vol);
for rr = r
step = rr;
dim_r = dim / step;
%... |
717a69defcf5250cceac4c231a7cea413e7d89d68c04db08b0444415140c7c7b | MATLAB | 1,201 | 48 | function demo_face()
%
% demonstration file for NMFLibrary.
%
% This file illustrates how to use this library.
% This demonstrates multiplicative updates (MU) algorithm and
% hierarchical alternative least squares (Hierarchical ALS) algorithm.
%
% This file is part of NMFLibrary.
%
% Created by H.Kasai on Apr. 05, 20... |
06b3f17bf8259dc65cc0890919cbfa3841a54d6b45fcaa46617caeb807384d6b | MATLAB | 1,202 | 43 | function hnew = outlinebounds(hl, hp)
%OUTLINEBOUNDS Outline the patch of a boundedline
%
% hnew = outlinebounds(hl, hp)
%
% This function adds an outline to the patch objects created by
% boundedline, matching the color of the central line associated with each
% patch.
%
% Input variables:
%
% hl: handles to lin... |
eed7eca36da046b860c3bdbfe18dcc61db55fff247c2e4e3fb3a564013981f7d | MATLAB | 1,204 | 39 | function plot_pred_vs_data_singleplot(predicted,data,time_stamps,datasetname)
num_tpts = length(time_stamps);
notnaninds = ~isnan(data(:,1));
data = data(notnaninds,:);
predicted = predicted(notnaninds,:);
data_vec = data(:); predicted_vec = predicted(:);
D = [predicted_vec,data_vec];
% plot_min = min(min(D));
% plot... |
88d90ad3a3058f2d88e77ede6343657a87073cd8f4b27c057d96fa1a82f2c593 | MATLAB | 1,205 | 48 | function handles = load_analysis(handles, varargin)
% Loop through input params
nVarIn = length(varargin);
for i = 1:nVarIn
if strcmpi(varargin{i}, 'Subjects')
handles.subjects = varargin{i+1};
elseif strcmpi(varargin{i}, 'Params')
handles.params = varargin{i+1};
... |
68ccf5bfae5e6b872278b82b707ebfb9e320d4534daf2216ac3a738be14529f1 | MATLAB | 1,206 | 40 | function [n_samples, n_subjects, groupnames, labelflag] = nk_DefineGroups(oocv, modeflag, n_subjects, groupnames)
switch modeflag
case 'classification'
if (~exist('groupnames','var') || isempty(groupnames))
n_samples = nk_input('# of groups?',0,'e');
else
n_samples = numel(... |
9457315ae2d029491bb96b57daed686e3b2e43df69d5b9c0b68fa3509d6ac8e9 | MATLAB | 1,207 | 37 | function net = get_net(varargin)
% net = get_net(model_file, phase_name) or
% net = get_net(model_file, weights_file, phase_name)
% Construct a net from model_file, and load weights from weights_file
% phase_name can only be 'train' or 'test'
CHECK(nargin == 2 || nargin == 3, ['usage: ' ...
'net = get_net(model_... |
f52451cdea416f9a9b49b5f47426e94c3f37478a171b02f7a708aefc176827f7 | MATLAB | 1,208 | 47 | function [d,ix] = data(tsa, tlist, varargin)
%
% [d,ix] = data(tsa)
% returns tsa.t
%
% d = data(tsa, tlist)
% returns the nearest elements to tlist in tsa
%
% d = data(tsa, tlist, parms)
% allows control of parameters through process_varargin
%
% extrapolate = nan; %% if 0 then only include tlist values such that
% ... |
1c524508829064ec40b4fae37d9f64471c405ed5e263f50dc23ab55f9b47cf4d | MATLAB | 1,215 | 46 | function R = ComputeMeanSDPerf(NM, EXT, modind, PERFCRIT)
R.PERFs=[]; cnt=1;
if ~isempty(EXT)
L = EXT.L;
P = EXT.P;
ind = EXT.ind;
nInd = numel(unique(ind));
else
L = NM.label; L(L==2)=-1;
ind = NM.TrainParam.RAND.CV2LCO.ind;
nInd = numel(unique(ind));
P = NM.analysis{modind}.GDdims{1}.... |
b7c419d8140168c6a23f74f16caf677ec8e5b76986c171160f253f0a0e446f0b | MATLAB | 1,216 | 42 | function [G, Gnames] = nk_DefineCovars_config(n_subjects_all, covars)
if exist('covars','var') && ~isempty(covars)
ncov = size(covars,2);
else
ncov = Inf;
end
G = nk_input('Covariates',0,'r',[],[n_subjects_all ncov]);
if nargout == 2
Gnames = cell(size(G,2),1);
descflag = nk_input('Define covariate ... |
cd8c24155cfac035c126db335e94dfcce5dbcf951a050530affaeb2168cb2f3f | MATLAB | 1,216 | 29 | function outputMatrix = assessCounterbalancing(conditionOrder)
% result = assessCounterbalancing(conditionOrder)
%
% This function accepts an ordered array of integers with each unique integer
% representing a different experimental condition. It assesses whether the
% sequence of conditions is counterbalanced for ser... |
170740938a24b0deb5b407963a010717cc6c1e66e5cf090f37a532a0a3016bee | MATLAB | 1,218 | 40 | function fname = mp2rage_generate_output_fname( job, suffix )
if nargin < 2
suffix = '';
end
field = ['output' suffix];
% put upstair the sub-fields
if isfield(job,'method')
fieldname = fieldnames(job.method);
fields = fieldnames(job.method.(fieldname{1}));
for f = 1 : length(fields)
job.(fie... |
a0663922b4ebf061fa53fabdcfe19e9149ddb919c5e370eba9551869069df1d7 | MATLAB | 1,219 | 58 | function C = ssa_decompose(y, L)
%SSA_DECOMPOSE Simple 1D Singular Spectrum Analysis decomposition.
% C = ssa_decompose(y, L)
%
% Inputs:
% y : 1 x T or T x 1 signal
% L : SSA window length, with 1 < L < T
%
% Output:
% C : R x T component matrix, where R = min(L, T-L+1)
%
% Each row of C is a rank-1 reconstru... |
33df5126a81d4932c35e272543da3c89480eb284c3963814a551185e8d2e411e | MATLAB | 1,222 | 45 | % eNDM
%
% Evaluate NDM predictions [y] at desired time stamps.
%
% Input:
% x0 = Initial Condition
% time_stamps = provided in units given by experiment
% C = connectivity matrix
% beta1 = diffusivity parameter
% alpha1 = linear growth/clearance term in x
... |
08b23f24f57938d44d5abf38a902a2f9afd8c8eada0bdda0874cfea0690e8248 | MATLAB | 1,223 | 50 | function [d] = data(tsa, tlist, varargin)
%
% d = data(tsa)
% returns tsa.D
%
% d = data(tsa, tlist)
% returns the nearest elements to tlist in tsa
%
% d = data(tsa, tlist, parms)
% allows control of parameters through extract_varargin
%
% extrapolate = nan; %% if 0 then only include tlist values such that
% ... |
955daa6be7fe409e46747d471135840eba5e1cc4aa4586d06275b2c88ffdded3 | MATLAB | 1,223 | 37 | function X0 = mripy_create_hpf_X0(n, RT, constant)
% Create sine wave regressors for high-pass filtering.
%
% See also: spm_filter, spm_dctmtx
% 2021-02-19: Created by qcc
global defaults
if nargin < 3
constant = 'none';
end
HParam = defaults.stats.fmri.hpf; % 128 s
k = fix(2*(n*RT)/HParam ... |
733a3e77e64364af792884aedc510e70a647866a7e9da3059c6be56186d7692d | MATLAB | 1,224 | 33 | load('N250_both.mat')
[n,c2] = size(erpval);
varNames = cell(3*2,1);
for i = 1 : 3*2
v = strcat('V',num2str(i));
varNames{i,1} = v;
end
% Create a table storing the respones
tbiases = array2table(erpval, 'VariableNames',varNames);
% Create a table reflecting the within subject factors
Fam = cell(3*2,1);... |
1d6dac2107c70995c03b0da695c13cde7503ede9f89f87d0f802b547457040e4 | MATLAB | 1,225 | 44 | function [NM, Y, oocvind, fldnam, dattype] = nk_SelectOOCVdata(NM, oocvflag, selflag, multiflag)
oocvind = []; fldnam = []; dattype = [];
if ~exist('selflag','var') || isempty(selflag), selflag = 0; end
if ~exist('multiflag','var') || isempty(multiflag), multiflag = 0; end
if ~isfield(NM,'C') && ~isfield(NM,'OOCV') &&... |
6012ffb0b8b96f750de92cfc22d2bdfc99ed93c6f62e90802a9ca2a5617d9be7 | MATLAB | 1,226 | 33 | function [local_cc, global_cc] = clustering_coefficient(A)
% A is the adjacency matrix of the graph
% Number of nodes in the graph
n = size(A, 1);
% Initialize array for local clustering coefficients
local_cc = zeros(1, n);
% Calculate local clustering coefficients
for i = 1:n... |
977f024aa4a736e6a7ccff031b4f34b0a7a8914a5cb3a3d261895277fba12dce | MATLAB | 1,227 | 37 | function v = eigenvector_centrality_und(CIJ)
%EIGENVECTOR_CENTRALITY_UND Spectral measure of centrality
%
% v = eigenvector_centrality_und(CIJ)
%
% Eigenector centrality is a self-referential measure of centrality:
% nodes have high eigenvector centrality if they connect to other nodes
% that have high e... |
5d6368b3b856990edf04de65eaa1ebf97c2bfab778f5dbb9414d5c6d03832825 | MATLAB | 1,232 | 38 | function h = stacked_bar_perc(y,barcolors,textcolor)
%STACKED_BAR_PERC Stacked bar plots with percentage
% STACKED_BAR_PERC(y,barcolors,textcolor) draws 2 groups of stacked bar plots using
% data in Y. Percentage of stacked bars of the stacked bar groups are
% displayed, aligned to the middle of each stack... |
52abb3d9ea24a520e4b4895fb1819c9147f09c4324fc2de12825b2fecc8698e4 | MATLAB | 1,233 | 32 | function load_selPager(handles, perpage)
if ~exist('perpage','var') || isempty(perpage), perpage = 50; end
if strcmp(handles.popupmenu1.String{handles.popupmenu1.Value},'Multi-group classifier')
multiflag = true;
else
multiflag = false;
end
if handles.curmodal<= size(handles.visdata,1) && handles.visdata{hand... |
86f7ddf4210780f547e56d8f2544b28850b7a602d8a4c562df9311a637f668e6 | MATLAB | 1,233 | 40 | function NM_out = train_model(NM, analind, ovrwrtfl, CV2x1, CV2x2, CV2y1, CV2y2, preprocmaster)
% %%%%%%%%%%%%%%%%%%%%%%%%% INITIALIZE NeuroMiner %%%%%%%%%%%%%%%%%%%%%%%%%
if ischar(preprocmaster) && exist(preprocmaster,'file')
preprocmat = load(preprocmaster); lfl = 2; preprocmat = preprocmat.featmat;
else
... |
4191ea81f63a77afec4a7f6e2c7e13179fde949dafadb53f39a2859204624b76 | MATLAB | 1,237 | 49 | function h = condmutualinfo(vec1,vec2,condvec)
%=========================================================
%
%This is a prog in the MutualInfo 0.9 package written by
% Hanchuan Peng.
%
%Disclaimer: The author of program is Hanchuan Peng
% at <penghanchuan@yahoo.com> and <phc@cbmv.jhu.edu>.
%
%The CopyRight is rese... |
2600e5e3e42d420ebeeb5ffecb18a71571dfa4c4a0568b4aa268bb66727f65f7 | MATLAB | 1,239 | 45 | function FindBestAxes(self)
% Finds the best pair of axes using L-ratio for one cell against the rest
% of the spikes or for two cells if two foci
axisSetX = get(self.xAxisLB, 'string'); nX = length(axisSetX);
axisSetY = get(self.yAxisLB, 'string'); nY = length(axisSetY);
bestLR = inf;
bestX = nan;
bestY = nan;
for... |
764354d3c8363c4a2ba08358679266ac987bc1d47cbcd2ae8be65e0c2d8adf53 | MATLAB | 1,245 | 48 | function [] = plx_spike_info(filename)
% plx_spike_info(filename): prints .plx file spike channel info
%
% plx_spike_info(filename)
%
% INPUT:
% filename - .plx file name. Will use file open dialog if filename is empty string
%
% OUTPUT:
% (none)
if nargin ~= 1
error 'expected 1 input argument';
end
[ filenam... |
78dda89ba1f927d50c038d3bc7d394e2a0d11e8e80fd851dcc9146f53c716700 | MATLAB | 1,245 | 38 | function [P, Ppos, nP, Pdesc] = nk_GetModelParams2(analysis, multiflag, CV2ind, curclass, curlabel )
global MULTI
Pdesc = analysis.Model.ParamDesc{curclass};
if ~exist('curclass','var') || isempty(curclass)
nclass = analysis.SVM.nclass;
P = cell(nclass,1); Ppos = cell(nclass,1); nP = zeros(nclass,1);
... |
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