sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
7e0b431563420516b46a37b0422f7ac2f1bedc686b3d7be78ab633ccf052a7f4 | MATLAB | 6,090 | 127 | function out = nk_mapY2Struct(mapY, permutefl)
if ~exist('permutefl','var') || isempty(permutefl), permutefl = true; end
global FUSION
switch FUSION.flag
case {0,1,3}
out = mapY;
case 2 % Concatenate modality structure into single multi-modal structure
nvar ... |
d10bfad0b7a9635da138b64512632339cc6e95b0790fe28f362b6237f66cbc18 | MATLAB | 6,105 | 165 | <<<<<<< HEAD
function y = base64decode(x)
%BASE64DECODE Perform base64 decoding on a string.
%
% BASE64DECODE(STR) decodes the given base64 string STR.
%
% Any character not part of the 65-character base64 subset set is silently
% ignored.
%
% This function is used to decode strings from the Base64 enco... |
6d5e9699648d9b8df95357f51a713955086fa1f28801d44113886d68e08e25fb | MATLAB | 6,114 | 216 | function hdr = load_nifti_hdr(niftifile)
% hdr = load_nifti_hdr(niftifile)
%
% Changes units to mm and msec.
% Creates hdr.sform and hdr.qform with the matrices in them.
% Creates hdr.vox2ras based on sform if valid, then qform.
% Does not and will not handle compressed. Compression is handled
% in load_nifti.m, which ... |
a452c9b1c01d262ed10d14680bc3dab7c4bca3dee14819604c4b0584a7538012 | MATLAB | 6,135 | 179 | function [opt_hE, opt_E, opt_F, opt_D] = nk_CVMax(E, L, EnsStrat)
global BATCH MODEFL VERBOSE
ind0 = L~=0; E = E(ind0,:); L=L(ind0);
[m,k] = size(E);
% Compute initial ensemble performance
if EnsStrat.Metric == 2, T = sign(E); else T = E; end
opt_hE = nk_EnsPerf(E, L); orig_hE = opt_hE;
opt_D = nk_Entropy(T,[-1 1], ... |
6b3d0bd8849c60db29d08fa3efae46e960ae631f31957d102c2771b49a598f2f | MATLAB | 6,149 | 207 | function all_resppred_map(EventTypes_all,EventTypes)
% ALL_RESPPRED_MAP Maps units with all types of behaviorally relevant activity
% ALL_RESPPRED_MAP(EventTypes_all,EventTypes) draws a map where each type
% of responsive/ predictive unit is presented (rows). Each column represents a
% type of behaviorall... |
7d1e529dcf6ee9aac28d60bf5cf8f27bf6394333fdbf9d283b30243f2b0ee4e2 | MATLAB | 6,154 | 198 | % =========================================================================
% FORMAT function [Z, R] = nk_AdjForCovarsUsingLocalModels (SY, S, Sid, TY, T, Tid, ...
% tolvec, numsel, wins, act)
% =========================================================================
% pe... |
ebf2b8735c55105632e2b2618731712cbaee5200e410430ac88c577a8827e598 | MATLAB | 6,178 | 132 | function [MultiGroupSelection, MultiBinBind] = nk_MultiBinBind(GD, label, f, d, curlabel)
global CV RFE
%%%% PREPARATIONS %%%%
ngroups = numel(unique(label(~isnan(label))));
nclass = length(CV.class{1,1});
[CV1perms, CV1folds] = size(CV.cvin{f,d}.TrainInd);
TsXdims =... |
d08e1de39d240c8f668a275cf90396a2e159cbf3b546b6e68b8b8ece1c4964c5 | MATLAB | 6,190 | 153 | function find_dominant_freq_bands(sess2analyse,fr_names,freq_bands,chanmean,subregion)
%FIND_DOMINANT_FREQ_BANDS Selects dominant freuency within band limits
% FIND_DOMINANT_FREQ_BANDS(sess2analyse,fr_names,freq_bands,chanmean,subregion)
% - loads full-epoch normalized, epoched time-frequency data
% ... |
3751ec06b76373ec4da45a1a771ebb1f807d816fed4af7c1857be72fdf142334 | MATLAB | 6,193 | 195 | function [x, infos] = ns_nmf(V, rank, in_options)
% Nonsmooth nonnegative matrix factorization (nsNMF)
%
% The problem of interest is defined as
%
% min || V - W*S*H ||_F^2,
%
% or
%
% min D(V||W*S*H),
%
% where
% {V, W, S, H} > 0.
%
% Given a non-negative matrix V, f... |
81132118d30c0e28bac1997203ecda577e54d27b5f60041ad984049ad6275ec4 | MATLAB | 6,194 | 150 | function [ STANDARD, act ] = nk_Standardize_config(STANDARD, parentstr, defaultsfl)
global NM
methodarr = {'standardization using median','standardization using mean','mean-centering','l1-median centering','qn-standardization','sn-standardization'};
sIND = []; dIND = []; WINSOPT = []; IQRFUN = 1; ZeroOut = 1; CALIBUSE... |
a4283ba7ac973841558f42e1318578d7e129aa015b15d5fa0fb773c622a0e3d6 | MATLAB | 6,198 | 208 | function [Y,numIter,tElapsed,finalResidual]=vsmftest(testSet,outTrain)
% Versatile NMF to test samples
% Definition:
% [A,Y,AtA,numIter,tElapsed,finalResidual]=vsmf(X,k)
% [A,Y,AtA,numIter,tElapsed,finalResidual]=vsmf(X,k,option)
% X: matrix, dataset to factorize, each column is a sample, and each row is a feat... |
d7b7867a24d0d1c67cbcf7a8a2cfb449d719f9a94d91a8d4272dd452b18f9212 | MATLAB | 6,200 | 219 | % SB2_POSTERIORMODE Posterior mode-finder for the SPARSEBAYES algorithm
%
% [MU, U, BETA, LIKELIHOODMODE, BADHESS] = ...
% SB2_POSTERIORMODE(LIKELIHOOD,BASIS,TARGETS,ALPHA,MU,ITSMAX,OPTIONS)
%
% OUTPUT ARGUMENTS:
%
% MU Parameter values at the mode
% U Cholesky factor of the covariance at the mode
% BETA V... |
529483a21b9e9dce18032c977ce117e3cfede788777c3143544dfddfc1ba826e | MATLAB | 6,212 | 106 | clear; % Clear workspace variables
clc; % Clear command window
% Initialize a tracking table to store step names and counts
stepTracking = table('Size', [0 2], ...
'VariableTypes', {'string', 'double'}, ...
'VariableNames', {'Step', 'ItemCount'});
%% First Step: Data Combining and Cleaning Based... |
e4e5fdbb5cbfe079fad3da664a8507e9d46a9511df9bba0295b76b9c8c1bdec0 | MATLAB | 6,222 | 181 | function ProceduralPolarGratingDemo(color1,color2,baseColor)
% ProceduralPolarGratingDemo() -- demo polar grating procedural shader
% stimuli, the shader is based on the colour grating shader, see
% ProceduralColorGratingDemo for details.
%
% History:
% 20/05/2021 initial version (Junxiang Luo)
if ~exist('color1','var... |
2b18d5b7d8d7c4583422152e94b3941c2c3a3d984647b6f13e8e54a8a4033277 | MATLAB | 6,257 | 253 | <<<<<<< HEAD
function r = save_mgh(vol, fname, M, mr_parms)
%
% save_mgh(vol,fname, M, <mr_parms>);
%
% M is the 4x4 vox2ras transform such that
% y(i1,i2,i3), xyz = M*[i1 i2 i3 1] where the
% indicies are 0-based
%
% mr_parms = [tr flipangle te ti]
%
% See also: load_mgh, vox2ras_0to1
%
%
%
% save_mg... |
c73733f18eba597fda1cf615c57a28ebfdd6174ce1a8e74d54dbe1ee38ab133f | MATLAB | 6,272 | 184 | classdef reduced_ly < bt.model.template
% This model is set up to fit t0 keeping the prior fixed if the alpha peak is not present
% Note that prepare_for_fit must be used before spectrum() can be used
% Uniform priors and DB initial fit
% Note that this does sum over k
properties
kmax
k0
k2u
k2_volconduct... |
0491a5e250da7d60dcffa902305ba923e15de9cd3dc14e9fe43281d38e3c6ebe | MATLAB | 6,281 | 187 | function [r_p,wat_pup,ftm,mu,bestmod,mufit,kappafit,pfit] = ...
PC_figstat3(sp_hilb,smwin,act_cellid,event,figdir,isplot,fignm,plottype, components)
%PC_FIGSTAT3 Population phase histogram plot with statistics
%
% Input parameters:
% SP_HILB vector of complex or numeric values;
% ... |
e6f0257c7e47cee4621126ccdddee5195b0e49a0a7b9391f61d065402532c5a6 | MATLAB | 6,283 | 237 | %% FUNCTION Least_CFGLasso
% Fused Group Lasso Progression Model with Least Squares Loss.
%
%% OBJECTIVE
% argmin_W { sum_i^t (0.5 * norm (Y{i} - X{i}' * W(:, i))^2)
% + rho1 * \|W\|_1 + rho2 * \|W*R\|_1 +
% + rho3 * \|W\|_{2,1} }
% where
% rho1: sparse.
% rho2: fused Lasso.
% rho3: L... |
58f6866a5c876bd61d6184c5512facdd0c0606ee660d1dac309cbce3015b935d | MATLAB | 6,297 | 239 | %% FUNCTION Least_Weight1FGLasso
% Weighted Fused Group Lasso with Least Squares Loss.
%
%% OBJECTIVE
% argmin_W { \sum_i^t (0.5 * norm (Y{i} - X{i}' * W(:, i))^2)
% + \sum_i^d rho1{i} * \|W(i, :)\|_1
% + rho2 * \|W*R\|_1
% }
% rho1: reweighted Lasso sparse.
% rho2: fused Lasso.
%... |
a8940cbecd267fe5f5570a3ff7e733e7d2d54d27f7e5e53e0f90018b081d421b | MATLAB | 6,300 | 194 | % to verify if triggers are detected and filter and epoch raw data
% subject-wise analysis
% subject = 'annesh'; % 10th block for Annesh has missed a trigger
function preprocess (subject)
for w = 1:15 % w = blocks
close all;
clear trigger_data;
clear filtered_data;
clear image_data1;
... |
803c3d4bdbf61541b9e924acc0f9810792fb9276768d9624f7ad2dd1a0644f8f | MATLAB | 6,304 | 217 | function [x,y,z,info]=csdp(At,b,c,K,pars)
% CSDP Uses CSDP to solve a problem in SeDuMi format
%
% [x,y,z,info]=csdp(At,b,c,K,pars)
%
% Uses CSDP to solve a problem in SeDuMi format.
%
% Input:
% At, b, c, K SDP problem in SeDuMi format.
% pars CSDP parameters (optional parameter.)
%
% Ou... |
6f9e337676380e35fdf01cb2106ca7e4b839e3dd2f76df81a53f4c12e6c7ac05 | MATLAB | 6,312 | 175 | function [D, I] = TransferModality2NM(D, I, varind)
% Write IO data to D
if (~isfield(I,'oocvflag') || ~I.oocvflag) && isfield(I,'modeflag'), D.modeflag = I.modeflag; end
if isfield(I,'Y')
% Check whether multiple modalities have to be imported
if iscell(I.Y)
nM = numel(I.Y)-1; m = size(I.Y{1},1)... |
35f1f4d049f7a3c8e4731b2363c93e8e15f58ce9152777ebeb501047fa25769e | MATLAB | 6,318 | 189 | classdef ManualCutter < MClust.Cutter
% ManualCutter
properties (Constant)
nStepToAutosave = 10;
maxUndoRedo = 10;
end
properties
% --- windows
% --- process
Autosave = MClust.ManualCutter.nStepToAutosave; % countdown, when reaches 0 autosaves
... |
82b84c696e48b6479dac077b14aeb9507e28760fe44eafca272386a0c1510870 | MATLAB | 6,326 | 190 | function [x, infos] = nmf_sparse_mu(V, rank, in_options)
% Sparse Multiplicative upates (MU) for non-negative matrix factorization with orthogonalization (Orth-NMF).
%
% The problem of interest is defined as
%
% min || V - WH ||_F^2 + lambda*sum(sum(H)),
%
% or
%
% min D(V||W*H) + lambda*... |
f02abe2d87f9676bb60b306d8f74c4d6c7cab34912057f826aba6e425b53175b | MATLAB | 6,327 | 172 | function [testExtr,outTest,time]=featureExtrationTest(trainSet,testSet,outTrain)
% map the test/unknown data into the feature space produced by function "featureExtractionTrain".
% testSet: matrix, each column is a test/unknown sample.
% outTrain: the output of "featureExtractionTrain" function.
% testExtr: the test/un... |
20d4db0d55cc481afcfd8d2d13becf85f85d3c9e2e8451cab866796d1bbb7109 | MATLAB | 6,330 | 116 | function handles = load_OOCV(handles, oocv)
cnt=1; l = handles.selLabel.Value;
% Loop through all OOCV containers
for n = 1: numel(oocv)
% If analysis has been applied to OOCV container, retrieve predictions
% and prepare export tables
if ~isempty(oocv{n})
handles.OOCV(cnt).num = n;
ha... |
a16ea6fba6c8c419f8db78cc37d9c234819e43b4af4569f21143a847bba1d587 | MATLAB | 6,330 | 159 | %% Brainstorm Post-processing Batch (Subject 01–20)
%% ===== USER SETTINGS (modify before running) =====
data_dir = '/path/to/ds004995';
eeglab_dir = fullfile(data_dir, 'derivatives', 'eeglab');
reports_dir = '/path/to/reports';
subjects = 1:20;
% ===================================================
sFiles = [... |
0384d7d8930ee0c26db2cdfb54ebd9532082deaa97b7eb858ec77a154e9e5644 | MATLAB | 6,331 | 180 | classdef (Abstract) template < matlab.mixin.Copyable
% These properties are SetAccess protected to ensure that the MCMC functions
% are properly independent of the choice of model
properties(SetAccess = protected) % Public access, but can only be edited via the interface
name
n_params
param_names
param_... |
29a976b4c35d8fdbd01a781b835cdb1a1970e805feee3d51ab29337bd200f513 | MATLAB | 6,335 | 129 | function [REMVARCOMP, PX] = nk_Remvarcomp_config(NM, varind, REMVARCOMP, PX, parentstr)
[m, ~] = size(NM.Y{varind});
corrmeth = 1;
corrthresh = 0.5;
corrcrit = 'corr';
varop = 'gt';
recon = 2;
varops = {'gt','ge','lt','le'};
recons = {'yes', 'no'};
corrmeths = {'Pearson','Spearman','ANOVA'};
corrcrits = {'corr','p... |
3798c60f1d3ff7cd96af3dd8dc5665d653ecc688c05cc63105a507ea932707e0 | MATLAB | 6,346 | 153 | % =========================================================================
% = MULTI-GROUP CLASSIFICATION PLOTS =
% =========================================================================
function handles = display_multiclassplot(handles)
axes(handles.axes1);
%uistack(handles.ax... |
d0cd1704051ac4aa8d5a51d7cebba582cbc11b2aef2bca9986f9bd020d0af232 | MATLAB | 6,357 | 202 | function [x, infos] = smu_nmf(V, rank, in_options)
% Stochastic multiplicative update for non-negative matrix factorization (SMU-NMF) algorithm.
%
% Inputs:
% matrix V
% rank rank
% options options
% Output:
% w solution of w
% infos information
%
%
% Cr... |
c34699c4785211a88cc2e7c96d688f48a8a65e8123b5ddf30868346f895e9435 | MATLAB | 6,365 | 162 | function [MULTI, act] = nk_Multi_config(MULTI, defaultfl, parentstr)
% function res = nk_MULTI_config(res)
%
% Setup parameters for multi-group classification
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% (c) N. Koutsouleris 04/2015
global NM
if ~exist('defaultfl','var') || isempty(defa... |
870cdd56413f6e4734ede6979f79848853c1c65b96c40d215477613868b2bccf | MATLAB | 6,368 | 101 | function VTBL = create_visdata_tables(v, VTBL, ind, act)
if ~exist('act','var') || isempty(act)
error('Action string is required')
elseif strcmp(act,'reorder') && ( (~exist('VTBL','var') || isempty(VTBL)) || (~exist('ind','var') || isempty(ind)) )
error('Table data or sorting vector missing')
end
switch act
... |
2f6c97559eac9ed0090029067da5462da88f140f7b4870fe24f64cc0f371cf85 | MATLAB | 6,372 | 166 | function [Emtx_all] = gen_mussel_encodemtx(sentiv_map, grp_idx, header, varargin)
%function [Emtx_all] = gen_mussel_encodemtx(sentiv_map, grp_idx, header, varargin)
%
% Wei-Tang Chang, UNC-Chapel Hill
% May 28, 2019
%
% Usage : generate the encoding matrix of MUSSEL
% Input arguments:
% sentiv_map: the sensitivity... |
411c194ea4525076266e54dfa7830cbd8f532f094ad65a3f02daa8a311b66a42 | MATLAB | 6,389 | 177 | function TE = PD_nosyncTE(Results,interp)
%PD_nosyncTE extracts behavioral information of behavioral analysis
% PD_nosyncTE(Results,ifinterp) extracts behavioral information from
% RESULTS struct (data provided by the SSRT task algorithm, see Task_SSRT.m). Event timestamps
% are NOT SYNCHRONIZED with EEG dat... |
5a7f0e3637a07bde9b5dd3053f10b38e5a46c94711a5ce4126df9d7073cf15e6 | MATLAB | 6,389 | 90 | function ProcessedData = removeJunkRecordings(a,sw,plxFileName,ProcessedData)
% This function allows the user to delete recording segments that should not be part of the anaysis
% For example, if life support was being connected during the first few minutes of the recording,
% or if life support failed at the record... |
a98074db12abe57a930b62944a1a55cbed1d1f6d4312c5760ad9ec7ac25d64fb | MATLAB | 6,393 | 192 | function obj = subsasgn(obj,subs,dat)
% Overloaded subsasgn function for file_array objects
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: subsasgn.m 7147 2017-08-03 14:07:01Z spm $
if isempty(subs), return; end
%... |
b8239f818577840a5d82237d0765cc278c3206d4846890dceb4288b7c4b756a6 | MATLAB | 6,399 | 156 | %% ================================================================
% Script: consistency_variability_analysis.m
% Purpose:
% Assess cross-subject consistency (MSC dataset) and inter-individual
% variability (HCP dataset) of FOCA matrices.
%
% Description:
% - Part I: MSC dataset — compute pairwise correl... |
80d96b48c8c729d5d9cbcaac8d7ddcf9c1190b12f2a400c9e52de9a795e7dc26 | MATLAB | 6,402 | 200 | function palm_miscwrite(varargin)
% Write various scalar data formats based on the struct X.
%
% palm_miscwrite(X);
%
% See 'palm_miscread.m' for a description of the contents of X.
%
% _____________________________________
% Anderson M. Winkler
% FMRIB / University of Oxford
% Aug/2013
% http://brainder.org
% - - -... |
5684f26398475a40bd98f261a18344d6ee8bf69f853acfc61a577fcf228fa447 | MATLAB | 6,407 | 143 | function mtSVMs_wOptNcv_1vO_insula_linear_domain_m2(task_id)
% For Discovery job
% Toolbox
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modules/MediationToolbox'));
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modules/Neuroimaging_Pattern_Masks'));
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modu... |
6e8a48c7df2509b6ce80158f364b4e43bf75351c0c7141935940d06bce6a4cb8 | MATLAB | 6,413 | 202 | classdef KKCluster < MClust.ClusterTypes.DisplayableCluster
%
% Cluster type for KlustaKwik selection cutter
%
% This is an unmodifiable displayable cluster, that remembers
% whether it should be kept or not.
%
% Because the spikelist cannot change, it remembers its
% averagewaveform
p... |
7846b1aa6709ec28512ee04e987016413e698b63db68b8509e07151fde036068 | MATLAB | 6,413 | 189 | function mappedX = cfa(X, no_dims, no_analyzers, no_iterations)
%CFA Performs manifold charting on dataset X
%
% mappedX = cfa(X, no_dims, no_analyzers, no_iterations)
%
% Performs manifold charting on dataset X to reduce its dimensionality to
% no_dims dimensions. The variable no_analyzers determines the number of
... |
00c469ae039703016a44b0a52c42eb2b53778112cfa0f4f8ab9f0c798d9f7f25 | MATLAB | 6,435 | 185 | function NMFBicHeatMap(Xout,Aout,Yout,indACluster,indYCluster,k,option)
% Draw the heatmap for the result of biclustering
% Usuage:
% NMFBicHeatMap(Xout,Aout,Yout,indACluster,indYCluster,k)
% NMFBicHeatMap(Xout,Aout,Yout,indACluster,indYCluster,k,option)
% Xout: matrix, the same as the output "Xout" of function "biClus... |
37ee7a2177d7959b746a9c85c74acee9280cbbe7ea595894a87460ba94b05ca6 | MATLAB | 6,438 | 185 | function varargout = nk_main(varargin)
% NK_MAIN MATLAB code for nk_main.fig
% NK_MAIN, by itself, creates a new NK_MAIN or raises the existing
% singleton*.
%
% H = NK_MAIN returns the handle to a new NK_MAIN or the handle to
% the existing singleton*.
%
% NK_MAIN('CALLBACK',hObject,eventData,... |
67ebff7d9ec72a473909e6dd05240d721f9d2190ef6410efd2e385e2edb20619 | MATLAB | 6,440 | 220 | function [ x, f_x, output ] = pnopt_sparsa( smoothF, nonsmoothF, x, options )
% pnopt_sparsa : Structured reconstruction by separable approximation (SpaRSA)
%
% $Revision: 0.8.0 $ $Date: 2012/12/01 $
%
REVISION = '$Revision: 0.8.0$';
DATE = '$Date: Dec. 01, 2012$';
REVISION = REVISION(11:end-1);
DATE = DATE(... |
6b3eee00eb9c14d969435b8a271e6f08ae25f467d3bbafa069a126a694c15718 | MATLAB | 6,453 | 207 | %% run_oracle_val_sweeps.m
% Hyperparameter sweeps for VMD, SSA, DWT, and optionally CEEMDAN on bench_val.
%
% For each method & configuration:
% - decompose N_tune validation samples,
% - oracle-reconstruct to the clean target,
% - store per-sample RMSE / RRMSE / PCC,
% - compute mean / std summaries,
% - me... |
1903cde876b3254ae0747a148b6837cfeeb01300fbbe99cae0e21ff9e9f9bfdc | MATLAB | 6,465 | 229 | function [init_factors, init_factors_opts] = generate_init_factors(V, rank, options)
% V = WH + R
m = size(V, 1);
n = size(V, 2);
init_factors_opts = [];
%% generate W and H
generate_wh_init = true;
if isfield(options, 'x_init')
if isfield(options.x_init, 'W'... |
8c9a9d785df4d32ea63877bc877c95fc9dc8762c5488e46ff33cb12ee1391866 | MATLAB | 6,472 | 203 | function [x, infos] = symm_newton(V, rank, in_options)
% Symmetric non-negative matrix factorization by Newton's method (Symm Newton).
%
% The problem of interest is defined as
%
% min || V - WH ||_F^2,
% where
% {V, W, H} >= 0, and W is close to H'.
%
% Given a symmetric non-negative mat... |
b4028a65f3fd3ab04a5e4fca02915fb30c0c32fcbaf5608d827243e5f8320aae | MATLAB | 6,477 | 206 | tic
subj = 's36';
ExpDate = '061130';
MainDIR = ['~/liang/' subj '_' ExpDate '/'];
% subj = 's31';
% ExpDate = '061020';
% MainDIR = ['~/liang/' subj '_' ExpDate '/'];
SR = 500; %sampling rate of EEG when RECORDING
A=[];
B=[];
C=[];
D=[];
E=[];
F=[];
A3=[];
A4=[];
A = importdata([MainDIR subj '_' Exp... |
2f9f2dbe1b1af906f75f3581e734146788aa5d508f49ebaf4f293b7007d83b06 | MATLAB | 6,483 | 164 | function [ GD, MD ] = nk_MLOptimizer_ParamAnnealer(GD, MD, DISP, Ps, Params_desc, mapY, algostr, f, d, npreml, nclass, batchflag, combcell)
% =========================================================================
% FORMAT [ GD, MD ] = nk_MLOptimizer_ParamAnnealer(GD, MD, DISP, Ps, ...
% Par... |
4d78c3648b2cf146bf975a4a7818502826f93670caeb6d937ae75d85284fe779 | MATLAB | 6,488 | 180 | % Convert a native Python variable to an equivalent native MATLAB variable.
% {{{ code/matlab_py/py2mat.m
% This code accompanies the book _Python for MATLAB Development:
% Extend MATLAB with 300,000+ Modules from the Python Package Index_
% ISBN 978-1-4842-7222-0 | ISBN 978-1-4842-7223-7 (eBook)
% DOI 10.1007/978-1-... |
b8314c7a4bcc4f914a73db41b3900f5ba1d3c0a97d9e6a741f2543bf8b5adbb5 | MATLAB | 6,494 | 198 | function [A,W] = fcn_preserve_degseq_lengthdist(A,Dist,nbins,nswap)
% [A,W] = fcn_preserve_degseq_lengthdist(A,Dist,nbins,nswap) takes a
% weighted, connectivity matrix, A, and Euclidean/fiber length matrix,
% Dist, and generates a randomized network with:
% 1) exactly the same degree sequence
% 2) approximately the sa... |
c636a7688654245a1d1b7f95711a62d3634f6ff6e03e81dab3073044713296d0 | MATLAB | 6,496 | 194 | classdef reduced < bt.model.template
% This model is set up to fit t0 keeping the prior fixed if the alpha peak is not present
% Note that prepare_for_fit must be used before spectrum() can be used
% Uniform priors and DB initial fit
% Note that this does sum over k
properties
kmax
k0
k2u
k2_volconduct
... |
d123c759dad3b2ce852b7b78d9ac4e025fd07dfef8aa01d0fb7a5510f4c584e2 | MATLAB | 6,499 | 242 | %% FUNCTION Least_Weight2FGLasso
% Weighted Fused Group Lasso and Weighted Lasso with Least Squares Loss .
%
%% OBJECTIVE
% argmin_W { \sum_i^t (0.5 * norm (Y{i} - X{i}' * W(:, i))^2)
% + \sum_{i=1}^d rho1{i} * \|W(i, :)\|_1
% + \sum_{i=1}^d rho2{i} \sum_{j=1}^{t-1}* \|W(i, j) - W(i, j+1)\... |
6326b3b401be35ee981e695753dea17f292bb3f63e0b386d8f819570bd4b3c44 | MATLAB | 6,508 | 165 | % ========================================================================
%> @class OptickaGUITest
%> @brief Class-based unit tests for the opticka GUI wrapper.
%>
%> Opens the opticka GUI, loads a protocol from CoreProtocols, configures
%> a dummy iRec eyetracker, sets nBlocks, and runs a behavioural task
%> using xd... |
c2c3395457465cd704ba6e0fea68b9e33c61eb0c93e3312ef984151e63df2f17 | MATLAB | 6,511 | 247 | %% FUNCTION Least_TGL
% Temporal Group Lasso Progression Model with Least Squares Loss.
%
%% OBJECTIVE
% argmin_W { sum_i^t (0.5 * norm (Y{i} - X{i}' * W(:, i))^2)
% + rho1 * \|W\|_2^2 + rho2 * \|W*R\|_2^2 +
% + rho3 * \|W\|_{2,1} }
%
%% R encodes smooth relationship
% R=zeros(t,t-1);R(1:(t+1):... |
cc5e1b5d4c93dcdb69e250b4d151c0280c8525847038ac667b9c6d7f3e0c9ce9 | MATLAB | 6,512 | 197 | function result = diana(x,vtype,stdize,metric,plots)
%DIANA is a divisive clustering algorithm. It returns a hierarchy of clusters.
%
% The algorithm is fully described in:
% Kaufman, L. and Rousseeuw, P.J. (1990),
% "Finding groups in data: An introduction to cluster analysis",
% Wiley-Interscience: New York (... |
045783ec6a262b8bd2ebd5fe91fde774bcddd01f45130cb679570a580a29f600 | MATLAB | 6,520 | 218 | function [x, infos] = nmf_sc(V, rank, in_options)
% Nonnegative matrix factorization with sparseness constraints (NMFsc)
%
% The problem of interest is defined as
%
% min ,
% where
% {V, W, H} > 0.
%
%
% Given a non-negative matrix V, factorized non-negative matrices {W, H} are calculated... |
c7948a204153b42ccb0e3ea492e2a1e5f889c45dc93c6a30011cb2942d22b757 | MATLAB | 6,524 | 167 | function [featmat, emptfl, nvar] = nk_GenPreprocMaster2(datid, cv, mastermat, tdir, basename, savefl, varind, varstr, concatfl, UIopt)
%
% This function assembles a bunch of paths to preprocessed data files (each file
% contains the data of a CV2 data partition) into a single master file.
% It allows to combine the pa... |
30dd53eaf9de67be29d3f73697789e720fa27d783136694368e5c9b03172dba9 | MATLAB | 6,534 | 248 | %% FUNCTION Least_SRMTL
% Sparse Structure-Regularized Learning with Least Squares Loss.
%
%% OBJECTIVE
% argmin_W { sum_i^t (0.5 * norm (Y{i} - X{i}' * W(:, i))^2)
% + rho1 * norm(W*R, 'fro')^2 + rho2 * \|W\|_1}
%
%% R encodes structure relationship
% 1)Structure order is given by using [1 -1 0 ...; 0... |
160b8c87850ba6e4f82ddf40f29ea9dae2a3f4334e00c6afeb3e04e177ade02a | MATLAB | 6,538 | 194 | function result = clara(x,kclus,vtype,stdize,metric,plots,nsamp,sampsize)
%CLARA is the 'Clustering Large Applications' clustering algorithm.
% It returns a list representing a clustering of the data
% into kclus clusters following the clara algorithm which is
% designed for large data sets.
%
%The algorithm is fully ... |
fa023f06bdeb83a4b675690a8034d4d15ea4b23aa417b3773aad32415791110c | MATLAB | 6,548 | 173 | function [optparam, optind, optfound, optmodel] = nk_SimAnneal(Y, label, Ynew, labelnew, Ps, FullFeat, FullParam, ActStr)
global VERBOSE TRAINFUNC RFE
% #####################################################################
% This code does:
% 1) Feature selection using SA
% 2) This is a simple code working on 1 singl... |
14e26fc40527dca11e5f548e427872380234fefd62e18998108e91301410f4ec | MATLAB | 6,581 | 206 | function [x, infos] = spg_nmf(V, rank, in_options)
% Stochastic projected gradient for non-negative matrix factorization (SMU-NMF) algorithm.
%
% Inputs:
% matrix V
% rank rank
% options options
% Output:
% w solution of w
% infos information
%
%
% Creat... |
88f9913a8afae9fa7f971ae627335d04b275e4718e987786cb7a31afa3ff275c | MATLAB | 6,597 | 199 | %% run corrs to Day1 with same cell set, non-PreHab; by ID
clear
load('ProcessedData\tables_compiled.mat');
%% Corr to D1 no best sorting
figure,
t = tiledlayout(1,5,'TileSpacing','Compact');
D_template = tables_compiled{1,1}.Deltas;
D_template = D_template.';
trial_cutoff = 8;
within = cell(1,5);
across = c... |
0daf7420548990354e7fdc24b20ef68acd97805a0053c5a7c8b798a771b7a64f | MATLAB | 6,603 | 180 | function spike_phase_coupling_MAIN(EventTypes,SubEventTypes,rectype)
%SPIKE_PHASE_COUPLING
% Calculates the amount of coupling between spiking activity and LFP/ EEG oscillations (SPC),
% expressed in mean resultant length (MRL), for each detected unit. SPC is
% calculated in time windows around a specif... |
259de91608af99a4e710022f09cb20030b3461ce547ac65eb848ac7e2b9a2922 | MATLAB | 6,647 | 199 | % ========================================================================
%> @brief single disc stimulus, inherits from baseStimulus
%> SPOTSTIMULUS single spot stimulus, inherits from baseStimulus
%> The current properties are:
%>
%> Copyright ©2014-2022 Ian Max Andolina — released: LGPL3, see LICENCE.md
% ========... |
94f521876195577a9cafebc55fe8e262e41a35421ca88857a02b238f82738112 | MATLAB | 6,659 | 196 | %PARSEMSGPACK parses a msgpack byte buffer into Matlab data structures
% PARSEMSGPACK(BYTES)
% reads BYTES as msgpack data, and creates Matlab data structures
% from it. The number of bytes consumed by the parsemsgpack call
% is returned in the variable IDX.
% - strings are converted to strings
% - numb... |
379623b92c6f184be739f2a6468552b098af3860bff515d77b039b8556c4aa2c | MATLAB | 6,664 | 154 | function [act, RFE] = nk_RFE_config(act, TrainParam, SVM, MODEFL, MULTI, GRD, defaultsfl, parentstr)
if ~exist('defaultsfl','var') || isempty(defaultsfl), defaultsfl = 0; end
if ~isempty(act) || ~defaultsfl
if ~isfield(TrainParam,'RFE') || isempty(TrainParam.RFE)
[~, TrainParam.RFE ] = nk_RFE_config([],... |
245ee9c4bfa37df4ce0cef1ba0013438cf7534ce92a3d4dc9ca4f182c7795a0e | MATLAB | 6,670 | 169 | %% mRVM2
% 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.... |
d4953f599e497742b8c3c8e72d979945ad20833d8919364550177a077a6ab44f | MATLAB | 6,671 | 191 | classdef reduced_l < bt.model.template
% This model is set up to fit t0 keeping the prior fixed if the alpha peak is not present
% Note that prepare_for_fit must be used before spectrum() can be used
% Uniform priors and DB initial fit
%
% This model includes the factors of L in other connections
properties
km... |
e6035652197b5b1e383393f3c25cd4890b302e15ac0f398dabdea505c5057c0e | MATLAB | 6,681 | 196 | % Produce Figure 4 panels A and B
% (explore circuits of Kuramoto oscillators)
%%% comparing different circuits
clear;
Nneurons = 6; % group size.
NumSeeds = 100; % number of repetitions to do with different random seeds
%% PARAMETERS %%%%%%%%%%%%%%%%%%%%%%%%%%%
% paramater space exploration:
ScaleInput = 1; % this ... |
e9aa2ba149295cd7e7b6486ef3667bc7f943fe87c83fac47481ebc3d54bef982 | MATLAB | 6,682 | 217 | % traveling_wave_phase_mapping.m
%
% Public-friendly version of the original hybrid traveling-wave analysis.
%
% This script:
% 1. loads concatenated 4D fMRI data
% 2. trims rest periods at the beginning and end of each run
% 3. identifies tuned voxels using sinusoidal regression (R^2 threshold)
% 4. es... |
a40adebfb46451ebc0bb41e1858a0047cf7a905325c911afc9af9f4e5839f750 | MATLAB | 6,688 | 140 | %==========================================================================
%FORMAT [F, Weights, Mx] = EvalSubSpaces(Perf, strout, ...
% SubSpaceStrategy, EnsStrat, ...
% Crit, minmaxfl, AddPerf, Weighting)
%=========================... |
e240149517e59c0f4814b6910f6050dcde01e57a13d74452dfc85ad3ba1f1cbb | MATLAB | 6,695 | 288 | function [w,L] = sbmlr(x, t, w)
%
% SBMLR - sparse Bayesian multinomial logistic regression
%
% ALPHA = SBMLR(X,T) computes the weights for a sparse multinomial
% regression model, where the sparsity is obtained using Bayesian
% regularisation with a Laplace prior, as described in [1]. Here X is
% a matri... |
912beb5f63c1559d536e12d65f48afd57e54f85a4a6c84294a36fe76342326bc | MATLAB | 6,698 | 180 | function sessionStats = PopulationDistanceDirect(sigArray,sessionName,distMethod,varargin)
%% parse inputs
winID = 2:5; % default optostimulation window, from post trial start to pre dig (2:5)
%
if ~isempty(varargin)
idx = find(strncmpi(varargin,'window',3));
if ~isempty(idx)
winID = varargin{idx+1}; ... |
b52ed59b45b1b03c0d0a125e670eba09b7c8ed6156e06e18b45fcd4013b703f1 | MATLAB | 6,706 | 82 | function trials_post_rating (subject, familiarity_rating)
UM_F = [1 10 13 15 16 37 39 40 46 48 62 72 73 74 90 91 97 100 102 113 121 127 129 130 142 151 157 159 172 174 184 200 202 208 210 212 214 220 222 230 241 248 255 257 268 280 282 289 294 296 310 318 328 329 330 331 338 342 355 357 372 373 378 388 390 394 399 4... |
8a98611aab139cdac916cd96feee6e8e87051cfc0d62e6837777e2d7942be59b | MATLAB | 6,722 | 148 | function mtSVMs_wOptNcv_insula_linear_apptVSaver_domain(task_id)
% For Discovery job
% Toolbox
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modules/MediationToolbox'));
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modules/Neuroimaging_Pattern_Masks'));
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/... |
2f58a37a7ee7654d9d75fda1835d018e82eeff54c0de1102c64d843bef7ca131 | MATLAB | 6,750 | 269 | % ======================================================================
%> @brief Input Output manager, a dummy class to allow task to run without
%> strobe hardware
%>
%>
%>
%> Copyright ©2014-2022 Ian Max Andolina — released: LGPL3, see LICENCE.md
% =================================================================... |
68dcff26b9d31189cec4c88a0d740ac54e7a73e663638c46e2faa0288517f9cb | MATLAB | 6,752 | 184 | function [data, labels, covars] = nk_SynthDistkNN(realData, realLabels, realCovars, IN)
if ~exist("IN","var") || isempty(IN)
distanceMeasure = 'Euclidean';
k = 5;
numSyntheticObservations = 100;
std_flag = 2;
else
distanceMeasure = IN.distanceMeasure;
k = IN.k;
numSyntheticObservations = I... |
25040ca266e3c579c80e7bbed1f88eb7f7a9a8a06a47f7d1c52e8911aaff88cd | MATLAB | 6,763 | 170 | %% mRVM1
% 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.... |
9d846eb356742d64a8218699306d19fc6b73d2682607e5601a6d38f74ec82df8 | MATLAB | 6,768 | 223 | function result=csimpls(x,y,varargin)
%CSIMPLS performs Partial Least Squares regression using the SIMPLS
% algorithm of de Jong (1993).
%
% Reference:
% de Jong, S. (1993),
% "SIMPLS: an alternative approach to Partial Least Squares Regression",
% Chemometrics and Intelligent Laboratory Systems, 18, 251-2... |
78b28e7bbdaf453e8669406cb8c9da277f1ec6f498a089dadfecaabacc811fbb | MATLAB | 6,773 | 117 | function plotCorrelograms(Correlograms,AnalysisRegions,RecordingMetrics,ProcessedData,plotProps)
%This function plots correlogram of specific comparison vs. reference signals that are specified by the user
donePlottingCorrelograms = 0; %initialize the logical indicating whether the user is finished plotting correlo... |
6b12ce4e1419a02ff28c8977d43c9b2dbd5355f1abe7dde4a1332f61743b2852 | MATLAB | 6,779 | 181 | function param = nk_Kernel_config(param, defaultsfl, translatefl)
global DEV
if isfield(param,'kernel')
kerndef = param.kernel.kerndef;
else
kerndef = 1;
end
if ~exist('defaultsfl','var') || isempty(defaultsfl), defaultsfl=0; end
if ~exist('translatefl','var') || isempty(translatefl), translatefl=0; end
switch... |
767848def18677a01e1da33ca6e6943982fcacbb3aaef185fe90411b8f2c272a | MATLAB | 6,780 | 147 | %==========================================================================
%FORMAT o = TransferResults( I, O, Param )
%==========================================================================
%Subfunction of OptimCore
%
%Generates output array from OptimCore processing results
%%%... |
4b0191bc8be71aef5be8a9daf255a9eebeba9689d444a3ce227031794f5176fb | MATLAB | 6,802 | 193 | classdef full < bt.model.template
% This model is set up to fit t0 keeping the prior fixed if the alpha peak is not present
% Note that prepare_for_fit must be used before spectrum() can be used
% Uniform priors and DB initial fit
properties
kmax
k0
k2u
k2_volconduct
stab_gamma_prefactor
spec_gamma_pr... |
662fb26217e1cc9959290898fd2055a830719286f2423464014f8ae79fa3c00a | MATLAB | 6,815 | 154 | %% Pipeline for the proper concatenation of miniscope data across sessions
% Developed by Daniel Almeida Filho Mar/2020 (SilvaLab - UCLA)
% If you have any questions, please send an email to
% almeidafilhodg@ucla.edu
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Parameters
%%%***... |
7caa6530c1c2f3320ac6aba4b06895203eca963381e26a7d6d8d04cac6d3fa2f | MATLAB | 6,819 | 148 | function mtSVMs_wOptNcv_1vO_insula_linear_subd(task_id)
% For Discovery job
% Toolbox
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modules/MediationToolbox'));
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modules/Neuroimaging_Pattern_Masks'));
addpath(genpath('/dartfs-hpc/rc/lab/C/CANlab/modules/s... |
1604b9654b472e4f7943a0a14f6b6063fc78bd83b7fe1c02ead98e4d371c0550 | MATLAB | 6,840 | 218 | function [Weight, tElapsed] = IMRelief_Sigmoid_FastImple(patterns, targets, distance, sigma, lambda, tmax, plotfigure, verbose)
%IMRelief_Sigmoid_FastImple: fast implemetation of IMRelief_Sigmoid
%--------------------------------------------------------------------------
%INPUT:
% patterns: training data: [x1,x2,.... |
3c4940158f6a6090301957b99da70f1f8645c72b06412611b87d6489f44195d7 | MATLAB | 6,841 | 193 | classdef full_gee_extended < bt.model.template
% This model is set up to fit t0 keeping the prior fixed if the alpha peak is not present
% Note that prepare_for_fit must be used before spectrum() can be used
% Uniform priors and DB initial fit
properties
kmax
k0
k2u
k2_volconduct
stab_gamma_prefactor
... |
e869e41d326a53de8e86acc3698e5e43c03ac9fcdc1ddc34994b8fe2101c54b1 | MATLAB | 6,847 | 124 | %This script was used to make figure 1 of
%% TO RUN THIS SCRIPT...
% FIRST RUN Main_AnalyzeRecordingData.m ON SMJM_Bicuculline.
% THEN RUN THIS SCRIPT WITHOUT CLEARING ANYTHING.
%%
%Below is copy/pasted from generateCorrelograms.m, except for the plotting.
CorrelogramBins = linspace(-plotProps.correl... |
be089ef4cfa55df7b0f3e1277972b70bc60081df0fe3f87e3a96f8787897998b | MATLAB | 6,858 | 191 | % =========================================================================
% FORMAT cv = nk_CVpartition(nperms, K, Labels, Constraint, Eq, AutoAdjust)
% =========================================================================
% This function generates nperms*K partitions of data
% using cross-validation resampling
% ... |
dc73297308792ee470af70f34fd6dfe7e1a0a6c51dc39071144e574fa6c22486 | MATLAB | 6,873 | 225 | function result = adjustedoutlyingness(x,varargin)
%ADJUSTEDOUTLYINGNESS calculates the 'Skewness-Adjusted Outlyingness'.
% The method searches for outliers in multivariate skewed data
% (thus without assuming elliptical symmetric).
% It is based on the outlyingness measure of Stahel and Donoho (1981, 1982)
% and on t... |
1ffce05f72287cf183475d0dd3b85901595753956cb992114ead1c80614a42bb | MATLAB | 6,882 | 146 | % ----------------------------------------------------------------------- %
% FUNCTION "customcolormap" defines a customized colobar given the %
% positions and the colors that are going to generate the gradients. %
% %
% Input pa... |
5310320f43cd26e03cbc39f659920b079ff4e344c4cc1ef51c88d90273bb507e | MATLAB | 6,887 | 180 | %% ================================================================
% Script: brain_axes_prediction_FOCA.m
% Purpose:
% Test whether internetwork covariance (FOCA) is shaped by
% fundamental cortical organizational features using multiple
% linear regression with 10-fold cross-validation.
%
% Descriptio... |
36c73b5ca5e9afce62e3c1d164bfb86b20090ee1073514f4ca5e0790ccf5a36c | MATLAB | 6,891 | 140 | function [act, param] = nk_Wrapper_config(act, param, SVM, MODEFL, GRD, MULTI, defaultsfl, parentstr)
%
% Defaults
% --------
% Activate feature filtering
wrappertypes = {'Greedy feature selection', ...
'Simulated Annealing', ...
'Genetic algo... |
b5aed654bc770ccef95252142e92d2cfcd7230cc004d336439600a6cf7bb4a5a | MATLAB | 6,900 | 196 | function mp2rage_run_remove_background(rmbg)
%MP2RAGE_RUN_REMOVE_BACKGROUND Executable job that removes background noise for mp2rage UNI image.
%
% Method 1:
% ---------
% Use a INV2 as pseudo mask. No user tuning required.
% Based on https:https://github.com/srikash/3dMPRAGEise.git
%
% Method 2:
% ---------
% The cor... |
2f35fb7af841ffcb13d4e223fa3469406211f78853dd7782e6b61b9f1952c2f1 | MATLAB | 6,904 | 204 | function [s, surrs, rots] = calc_eigenstrap(s, varargin)
%% CALC_EIGENSTRAP Calculate eigenstrapped surrogate maps
%% Syntax
% s = calc_eigenstrap(s, 'map', map);
% s = calc_eigenstrap(s, 'mapName', mapName);
% s = calc_eigenstrap(___, Name, Value);
% [s, surrs, rots] = calc_eigenstrap(___);
%
%
%% Descript... |
0684a8ebc0b736d640317c99874595d873a2cb87315a0fef2da2e8d6b3fdfb46 | MATLAB | 6,908 | 213 | function [sY, IN] = nk_PartialCorrelationsObj( Y, IN )
% =========================================================================
% FORMAT [sY, IN] = nk_PartialCorrelationsObj( Y, IN )
% =========================================================================
% Remove nuisance effects IN.G from Y (opt. using predefin... |
f10c871299ec60a82328140ccd05a7c3f06f7f407dc0aa1c8dbafdf10e73fed8 | MATLAB | 6,924 | 195 | classdef full_gdiff < bt.model.template
% This model is set up to fit t0 keeping the prior fixed if the alpha peak is not present
% Note that prepare_for_fit must be used before spectrum() can be used
% Uniform priors and DB initial fit
properties
kmax
k0
k2u
k2_volconduct
stab_gamma_prefactor
spec_ga... |
dd3b38507b5c02a0e6e0b2dc5091c755efe3f69c60f31a4761960ff4fc331c83 | MATLAB | 6,928 | 201 | function [Y,maskstruct,Yisvol,Yissrf,Ykindstr,Ytmp] = palm_ready(Yfile,maskstruct,opts,removecte)
% An intermediate function to read input data (-i) and
% voxelwise EVs (-evperdat).
%
% Usage:
% [Y,maskstruct] = palm_ready(Yfile,maskstruct,opts)
%
% Inputs:
% - Yfile : Filename to be read.
% - maskstruct : Mask st... |
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