sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
54866269320d15af9870b491e1bc5ad2767dd3155c0722662757d35ac63c26ca | MATLAB | 5,115 | 145 | function M = stiefelcomplexfactory(n, p, k)
% Returns a manifold struct. to optimize over complex orthonormal matrices.
%
% function M = stiefelcomplexfactory(n, p)
% function M = stiefelcomplexfactory(n, p, k)
%
% The complex Stiefel manifold is the set of complex orthonormal nxp
% matrices. If k is larger than 1, thi... |
26001c532f9e5a57998225f48a0fe817c923472ca968d3707998825125992190 | MATLAB | 5,147 | 184 | function [electrode_data, electrode_labels] = electrodes_from_csv(file, kwargs)
%
% electrodes_from_csv
%
% Reads a set of electrodes from a CSV file into a format that can be stored
% into the central struct of Zeffiro Interface. The CSV file should contain a
% header row with the titles
%
% x, y, z [, label] [, inn... |
75c991240f407cbf177cf12d039211c6cec95b2973eb23ef574daf548a5c72c5 | MATLAB | 5,152 | 134 | function [vecSpikeCh,vecSpikeT,intTotT] = DP_DetectSpikes(matData, sP, vecChanMap)
%DP_DetectSpikes Performs fast GPU-accelerated thresholded-spike detection
% [vecSpikeCh,vecSpikeT,intTotT] = DP_DetectSpikes(matData, sP, vecChanMap)
%
%input:
% - matData [Ch x T]: gpuArray [Channel by Timepoint] data matrix
% - ... |
48e58c0e98926f0f301c4a3b5dc708b3048dff82f0962e3b0dc329b222e3f2c2 | MATLAB | 5,176 | 168 | function M = unitaryfactory(n, k)
% Returns a manifold structure to optimize over unitary matrices.
%
% function M = unitaryfactory(n)
% function M = unitaryfactory(n, k)
%
% Unitary group: deals with arrays U of size n x n x k (or n x n if k = 1,
% which is the default) such that each n x n matrix is unitary, that is... |
9789c18fc82f6b69063862a49775c7c1ff0747f877af9a9369265e36c5075ff1 | MATLAB | 5,185 | 138 |
function [SSW] = detect_SSW_Carrier(signals,OPTIONS)
% signals.data is a Ntrials x Ntime (IN MICRO VOLTS)
% signas.fs is the sampling rate
% OPTIONS.Sleep contains the parameters for the SSW detection
% output:
% SSW ----- .marker{i} ---.nsamp : table [start end] (samples in the data)
% .P... |
25a7550dc9653f1ee3e34c4618c5aafd6cd3d17dac564403374734784c682234 | MATLAB | 5,189 | 120 | %% Sample script to set up the parameters object.
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% Copyright (C) 2023 Joseph T. Lizier
% Distribu... |
31b6ff445ea43e69a80affd44470712789bf71545153b9089629c6817194a1c9 | MATLAB | 5,190 | 159 | %% process HCP data with Brainstorm
hcp_dir = '/path/to/megdata/and/results/';
reports_dir = strcat(hcp_dir, 'brainstormReports/');
loadedsubj = load(fullfile(hcp_dir, 'myMEGList.mat'));
subjList = split(loadedsubj.myMEG, '_');
subjList = subjList(:,2);
channels = load(fullfile(hcp_dir, 'myMEGbadChannels'));
badChann... |
c563c9f5501a843755b8b3a0e8d2c271eebae62c74b43e0957689d361ed45221 | MATLAB | 5,191 | 178 | function M = fixedrankMNquotientfactory(m, n, k)
% Manifold of m-by-n matrices of rank k with two factor quotient geometry.
%
% function M = fixedrankMNquotientfactory(m, n, k)
%
% This follows the quotient geometry described in the following paper:
% P.-A. Absil, L. Amodei and G. Meyer,
% "Two Newton methods on the ma... |
0a5f07203ce982dd009cf7e4e42a380591bfacda6c76182f6a786ec4515a7ce2 | MATLAB | 5,195 | 130 | % Define preprocessing and brain features parameters
%
% Cristina Gil, TUM, 10.06.2022
function params = define_params(fname)
%% Read json file with all the parameters
if isempty(fname)
fname = 'params_example.json';
end
fid = fopen(fname);
raw = fread(fid,inf);
str = char(raw');
fclose(fid);
params =... |
d4f91afbe3e23d8a73dc7f5bb134e977d4f76588ef6094cba3f1a145aee7915b | MATLAB | 5,197 | 141 | function zef_ES_plot_error_chart(varargin)
switch nargin
case {0, 1}
if nargin == 0
zef = evalin('base','zef');
warning('ZI: No zef were called as an input argument.')
vec = zef_ES_table(zef.y_ES_interval);
[sr, sc] = zef_ES_objective_function(zef);
el... |
2a3002fbbd9e58000de3fec170702d7c33125b044f112cfc5126e9b87e117c59 | MATLAB | 5,209 | 126 | function events = custardWrapper( timing, fluo_matrix, params_in, detailed )
% params_in contains multiple sets of custard parameters
% timing 1 x npoints
% fluo nROIs x npoints
% params_in, detailed structure with params for multiple runs
% detailed, flag for showing details of custard algorithm
detailFlag=false;
if ... |
8cbc00f5aff9193bcd9cf468f8f1acf79fd6a470c947d223ed276d44b72d4d56 | MATLAB | 5,216 | 120 | %% Script to set up the parameters object for the figure 4a experiment (d=2, c=0.5, various p).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% ... |
a58af094e0050117fa8958c3d0c2ef5008b7f0fd2f5071bfd501eba47f51421c | MATLAB | 5,253 | 120 | %% Script to set up the parameters object for the figure 4f experiment (d=4, c=1.0, various p).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% ... |
5dc1c56ade6cac45088f9b2dd32211e08fd8d0687b9e25de4be10bdfa6ab4510 | MATLAB | 5,260 | 109 | zef.h_ES_parameter_table.Data = cell(0);
if ismember(zef.ES_opt_solver, 1)
zef.h_ES_opt_method.Items = zef.ES_opt_method_list([1 3 4]);
zef.h_ES_opt_method.ItemsData = [1 3 4];
zef.h_ES_opt_algorithm.Items = zef.ES_opt_algorithm_list([2 3]);
zef.h_ES_opt_algorithm.ItemsData = [2 3];
... |
3c255fcf0df515b4460e52d6acc8af898df9d552bf4775e8dbeb28054316ba05 | MATLAB | 5,264 | 186 | function [p,info] = erp_clusterperm_TANOVA(obj,design,varargin)
% Perform cluster permutation TANOVA analysis
%% Check inputs
% Check multiple conditions appear in the data
if length(obj.conditionlabels) == 1
error('The cohort structure must contain multiple conditions');
end
% Get pairs of conditions -... |
84cea43fe4ea56fad58c81da21cac106c2fd6caa270363a1467c02b831e75d94 | MATLAB | 5,268 | 186 | function[s,t,E] = sta(data_spk,data_lfp,smp,plt,w,T,D,err)
% Spike Triggered Average
% Usage: [s,t,E] = sta(data_spk,data_lfp,smp,plt,w,T,D,err)
%
% Inputs
%
% Note that all times... |
084fa175c62dd690c8715486628296aa7082b3d45e0332143374814c730b3a90 | MATLAB | 5,280 | 154 | function low_rank_tensor_completion_embedded()
% Given partial observation of a low rank tensor (possibly including noise),
% attempts to complete it.
%
% function low_rank_tensor_completion_embedded()
%
% NOTE: Tensor Toolbox version 2.6 or higher is required for this factory:
% see https://www.tensortoolbox.org/ or h... |
fc9b681f25dc9cc166facbe52fd6fe330cba272f33429bb1ffe360d3cefde0ac | MATLAB | 5,287 | 146 | function hessfun = approxhessianFD(problem, options)
% Hessian approx. fnctn handle based on finite differences of the gradient.
%
% function hessfun = approxhessianFD(problem)
% function hessfun = approxhessianFD(problem, options)
%
% Input:
%
% A Manopt problem structure (already containing the manifold and enough
% ... |
9face11ac15b741ae2a18bb9ec296a244b6acfed04fb54a97b9fc59b1415b79c | MATLAB | 5,298 | 120 | %% Script to set up the parameters object for the figure 4c experiment (d=8, c=0.5, various p).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% ... |
15cc4dfd440c1d222daf5aec5659237598ef63464e95f21aaf76db37adc9c030 | MATLAB | 5,299 | 121 | %% Script to set up the parameters object for the figure 4a experiment (d=2, c=0.5, various p).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% ... |
8ded7fde07ae11e3c8f147ba076564a4880eb409719617f244c657f939efc0de | MATLAB | 5,299 | 121 | %% Script to set up the parameters object for the figure 4b experiment (d=4, c=0.5, various p).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% ... |
b4c8d54f9ff98b59d12571723ba5178dfcb688174a59ec42e68f0060e39dafa9 | MATLAB | 5,299 | 121 | %% Script to set up the parameters object for the figure 4e experiment (d=4, c=1.0, various p).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% ... |
f18a53b28312b99366ed8530a3d90882007b3267122f1fb0704311a42ab66b01 | MATLAB | 5,299 | 121 | %% Script to set up the parameters object for the figure 4d experiment (d=4, c=0.1, various p).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
% ... |
add92506051e13d8e42de25e2e2eb8462bb5bf4e5734ef6c9ed1ba2eb97bd438 | MATLAB | 5,304 | 156 | function M = multinomialfactory(n, m)
% Manifold of n-by-m column-stochastic matrices with positive entries.
%
% function M = multinomialfactory(n)
% function M = multinomialfactory(n, m)
%
% The returned structure M is a Manopt manifold structure to optimize over
% the set of n-by-m matrices with (strictly) positive e... |
e222bc4f138e88a914f036907997f263106028e470c21e3f99e16483ca5795dc | MATLAB | 5,324 | 63 | function update_ensemble_eval_text(app)
%% Documentation Contents
% Darik O'Neil 05/11/2022
% Function to update Eval text
%% Function Contents
%duplicate to be safe, vad for memory tho
%bring results into caller memory
%set value
v = app.StimulusEV.Value;
dataset = app.ViewEnsPerfButtonGroup.SelectedObject.Text;... |
3154c0c187104130d757d84f189b1097d9692e50179d3d7bd4fba88c387acd8f | MATLAB | 5,328 | 176 | function visualize_segmentation(stats, imdb, net, opts)
epoch = stats.epoch;
plotErrors(opts, epoch, stats, false);
drawConfusionMatrix(opts, stats);
showImages(imdb, net, opts);
% print to disk
if(opts.savePlots)
print(opts.vis.hnd_loss, sprintf('%s/summary.pdf',opts.expDir), '-dpdf')... |
8b502aec30ed5e557d600ac5b48242642ff93fc4e1d440140785efabda14307e | MATLAB | 5,329 | 156 | function [tuda,Gamma,encmodel,decmodel] = tudasparsify(X,Y,T,tuda,...
Gamma,temp_sparsity,spatial_sparsity,doplot)
% Given an estimation of a TUDA model and the corresponding model time
% courses Gamma, this function creates sparse estimates of the decoding models.
% This is done:
% - Temporally: after fitting a Ga... |
e59ad4c99db1f2f549926fba44f5419a4009678c4554c875cba06ac64f78ed6d | MATLAB | 5,334 | 108 | classdef SolverSGDM_conv5 < nnet.internal.cnn.solver.Solver
% ====================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn\+nnet\+internal\+cnn\+solver
% ====================================================
% SolverSGDM Stochastic gradien... |
f1d36e2c5b4256ffdd6738f383818a986ba88e97fd937e87234c57356a9698fb | MATLAB | 5,334 | 108 | classdef SolverSGDM_conv5 < nnet.internal.cnn.solver.Solver
% ====================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn\+nnet\+internal\+cnn\+solver
% ====================================================
% SolverSGDM Stochastic gradien... |
47138d11a26abb63c09e686d0af98061d79cb24c2dd2e0d8bf67bc7b53e98202 | MATLAB | 5,352 | 168 | function M = stiefelstackedfactory(m, d, k)
% Stiefel(k, d)^m, represented as matrices of size m*d-by-k.
%
% function M = stiefelstackedfactory(m, d, k)
%
% Points on this manifold are matrices Y of size n x k, with n = m*d.
% Y is thought of as m matrices of size d x k each, stacked on top of each
% other. Call them Y... |
a965e6fbe011370c23d89da9cce713954b57b0f48fb626c3d776ba93db98a9dd | MATLAB | 5,355 | 172 | clear
Data_path = '/media/ravinderjit/Data_Drive/Data/BehaviorData/IACbehavior/';
Fig_path = '/media/ravinderjit/Data_Drive/Data/Figures/DynBin/';
sqtone = load([Data_path 'IACsquareTone_Processed.mat']);
oscor = load([Data_path 'OSCORfmThresh_processed.mat']);
oscor_white = load([Data_path 'OSCORwhite_processed.mat'... |
6868bf6feebb4293db6e244794742545a949d3d21c47af3c6fa3881ae7761e63 | MATLAB | 5,357 | 142 | %This is the startup function for KF app.
%Beamformer, inverse_tools, zef_KF_start
function zef = zef_kf_open_window(zef)
if nargin == 0
zef = evalin('base','zef');
end
zef.KF = zef_kf_app;
zef.KF.filter_type.Items = {'No standardization' 'EnKF' 'Spatiotemporal standardization' 'Spatial standardization' 'Doub... |
c20a9f53a004e3a10c9c2bbb549ccdc979c6a3bfd871f2aa40ca8d0e87d97664 | MATLAB | 5,366 | 121 | %% Script to set up the parameters object for the figure 1 experiment (d=4, c=0.5, various p, L).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
... |
8a54c0029b25dee9913911c7579ce88a06bc9b70cee0732904f444e1ec8aca02 | MATLAB | 5,374 | 130 | function data = load_preprocessed_data(params,bidsID)
if exist(fullfile(params.PreprocessedDataPath,bidsID,'eeg',[bidsID '_eeg.mat']),'file')
load(fullfile(params.PreprocessedDataPath,bidsID,'eeg',[bidsID '_eeg.mat']),'data');
else
% Load data
ses ='';
if contains(bidsID,'_')
bidsparts = strspl... |
5829b6e6b2aef9d15113eedd98e604ec9c627812daebda3e59edc0b6aad9992a | MATLAB | 5,382 | 235 | function [rmse_l, rmse_c, rmse_m, rmse_i, t] = func_train_val(n, train_t, reset_t, noise_level, bias)
dt=0.01;
input_infor={'xy', 'qdt'};
dim_in=length(input_infor) * 4;
dim_out=2;
m1=1;m2=1;
l1=0.5;l2=0.5;
lc1=0.25;lc2=0.25;
I1=0.03;I2=0.03;
properties=[m1, m2, l1, l2, lc1, lc2, I1, I2];
val_t=500;
% prepare for t... |
f693dd6a79e65bed03247d1a24198351fcb7f71f33319765eff6442d05be27b2 | MATLAB | 5,384 | 177 | %% Copyright © 2025- Joonas Lahtinen
function [z_vec, self] = invert(self, f, L, procFile, source_direction_mode, source_positions, opts)
%
% invert
%
% Builds a reconstruction of source dipoles from a given lead field with
% the Kalman filtering method.
%
% Inputs:
%
% - self
%... |
59c41a244f351c5b220f8a9304b2a72b49a00044ba6ec0909cc75732d310ccde | MATLAB | 5,387 | 168 | function [h_cone_field, h_streamline, h_colorbar] = zef_plot_cone_field(zef, h_axes, varargin)
if eval('zef.cone_draw') || eval('zef.streamline_draw')
rec_ind = 1;
position_case = 1;
if not(isempty(varargin))
rec_ind = varargin{1};
if length(varargin) > 1
position_case = vararg... |
63ccbbec99cc2a798529dc1726fcb30ddc04ef66543091cb21a6b4b435127a02 | MATLAB | 5,390 | 146 | function [zef] = zef_KF(zef, q_value)
% Optimal q_value as parameter
%% Initial parameters
snr_val = zef.inv_snr;
pm_val = zef.inv_prior_over_measurement_db;
amplitude_db = zef.inv_amplitude_db;
pm_val = pm_val - amplitude_db;
std_lhood = 10^(-snr_val/20);
sampling_freq = zef.inv_sampling_frequency;
high_pass = zef.inv... |
0403f59a5da3b4046e30ac7295eee664e200f8d30a67d744c3d6541104d70230 | MATLAB | 5,395 | 216 | function zeffiro_setup ( kwargs )
%
% zeffiro_setup ( kwargs )
%
% Downloads dependencies specified in the .gitmodules file into the external/
% folder and calls their installation scripts.
%
% Inputs:
%
% - kwargs.submodules = string([])
%
% This column vector of submodule names specifies, which submodules listed in... |
02b8fb7f8de8089fca3184fb9ece9d40d64a2ce92ac04750ae899dc6f9589158 | MATLAB | 5,424 | 216 | function [Model] = estimate_shape(data, parm)
% training shape parameter using training data
%
% data.y = observed spike data with noise
% data.t = sample time [sec]
% data.fs = sampling rate for observed data [Hz]
%
% parm.fs =sampling rate for observed data [Hz]
% parm.fs_est =estimation freq [Hz]... |
1d1111fea68cbba9ca1aeb692079a63487b6b524db850a702c5b4c85aef27634 | MATLAB | 5,426 | 121 |
%--------------------------------------------------------------------------------
% This demo is included in
% Reverse engineering neural networks to characterise their cost functions
% Takuya Isomura, Karl Friston
%
% Copyright (C) 2020 Takuya Isomura
% (RIKEN Center for Brain Science)
%
% 2020-05-08
%---------------... |
138133fec1794886fc953061f25175730b76646cf0b74c0668163b66a0ecf4ea | MATLAB | 5,435 | 144 | function nodes = zef_inflate_surfaces(zef, nodes, tetra, domain_labels)
if isempty(zef)
zef = evalin('base','zef');
end
waitbar_opened = 0;
if evalin('caller','exist(''h'')')
if evalin('caller','isvalid(h)')
h = evalin('caller','h');
else
h = zef_waitbar([0 0], [1 1],'Inflating.');
... |
e60d69b0ccf94b650447d21aa01207adf03abda53a16c5b64284bcc36da7926b | MATLAB | 5,448 | 121 | %% Script to set up the parameters object for the figure 1 experiment (d=4, c=0.5, various p, L).
% You can not only assign values here, but have differential processing
% (e.g. to do different things on your desktop or cluster).
% Required members are described as they appear below.
%
%% Linear Sync Toolkit (linsync)
... |
dcabf1ed00a6f007811906937a9a729d97788f423301fee92d3e3dc21291c699 | MATLAB | 5,454 | 145 | function [matW, dblMSE, intRankT, sSuppOut, intOutputFlag] = doRRR_CV(matX, matY, intRankT, intFoldK, dblLambda, matB, matCov)
%doRRR_CV Performed CV reduced rank multivariate regression.
% [matW, dblMSE, intRankT, sSuppOut] = doRRR_CV(matX, matY, intRankT=min(R,S), intFoldK=10, dblLambda=0, [matB], [matCov])
% ... |
417c6625c0333d88bd2c19c2042a4c7fce62ab6876eae2cd2a93889aa1500d4e | MATLAB | 5,465 | 166 | function ETP_AutoSettings(hObject,eventdata)
%get globals
global sETP;
global sFigETP;
global ETP_Fit;
%% check bounds
intTempAvg = str2double(sFigETP.sHandles.TempAvg.String);
if ~isnumeric(intTempAvg) || intTempAvg < 1
sFigETP.sHandles.TempAvg.String = '1';
elseif intTempAvg > sETP.intS
sFigETP.sHandl... |
f7cff0b7e0778a7089ae34071bf6f619fa19176007a00230d6dc67a2a2034e6f | MATLAB | 5,486 | 119 | clear all
Fig_path = '/media/ravinderjit/Data_Drive/Data/Figures/DynBin/';
Subjects = [{'S001'},{'S132'},{'S205'},{'S206'},{'S207'},{'S208'},{'S203'},{'S204'},{'S211'}];
Data_path = '/media/ravinderjit/Data_Drive/Data/BehaviorData/IACbehavior/';
responseTracks = {};
for i =1:numel(Subjects)
ThisData = load([... |
936d583aa7801e602203beb11e723a1949d171aaa7b69ef487da8e42d7edc848 | MATLAB | 5,505 | 152 | function [cellHandles,sOut] = doPEP2(vecTrace1,vecTrace2,vecOn,sEvents)
%doPEP2 Performs Peri-Event Plot of 2 supplied traces
%syntax: [cellHandles,sOut] = doPEP2(vecTrace1,vecTrace2,vecOn,sEvents)
% input:
% - sEvents, structure containing the following fields:
% - handleFig; handle to figure
% - vecOn; vector... |
a916350cfa1a587914033c68701d53385e1c146aeb01a79407b640763883f185 | MATLAB | 5,515 | 153 | function [h_contour,h_text] = zef_plot_contour(zef,rel_val,surf_func,triangles,nodes,varargin)
if not(eval('zef.show_contour_text'))
h_text = [];
end
n_iter = eval('zef.contour_n_smoothing');
line_width = eval('zef.contour_line_width');
c_lim = zef.h_axes1.CLim;
if not(isempty(varargin))
if not(isempty(vararg... |
7f1fb142f28c79f37aa1fd9d6d045d4091d573f3a0866c146457bd027cc139c8 | MATLAB | 5,517 | 117 | function update_params(app)
% access parameters and instance a new copy since matlab does'nt do memory
% references????
params = app.params;
% always validate
params.ignore_dataset_ = true;
params = parameterize(params);
params.ignore_dataset_ = false;
app.params = params;
% GENERAL
app.ShuffleDataEditField.Value =... |
e2cd2a778316061b5a260296ac37b7c6a3ee594fe099c2d36bbf89376871226c | MATLAB | 5,520 | 163 | function [opt,delta,stats,fh] = sw_run_delta_LFP(varargin)
% [rip] = run_ripple_LFP(dat, opt)
% top level function to perform ripple detection
% inputs:
% 1) dat - data input which can be either
% a) string dat='C:/lfpdata/rec001.ncs' or
% b) data structure with the following... |
9644afab339c526ad94f9ddc546b0676af1fb4a4df0b3552b42197870fb024ed | MATLAB | 5,526 | 91 | % clean_rawdata(): a wrapper for EEGLAB to call Christian's clean_artifacts.
%
% Usage:
% >> EEG = clean_rawdata(EEG, arg_flatline, arg_highpass, arg_channel, arg_noisy, arg_burst, arg_window)
%
% ------------------ below is from clean_artifacts -----------------------
%
% This function removes flatline channels, lo... |
1446162f881ba8598132c0a6640d3263ecaaa8d5f82ca3f97aef2fba86c55599 | MATLAB | 5,540 | 162 | function [GMModel,GMModelDipoles] = zef_GMMcluster
h = zef_waitbar(0,1,['Gaussian mixature model.']);
%Options
options = statset('MaxIter',evalin('base','zef.GMMcluster_MaxIter'));
if evalin('base','zef.GMMcluster_covtype')==1
Sigma = 'full';
else
Sigma = 'diagonal';
end
if evalin('base','zef.GMMcluster_covid... |
496a061490646b518d5f187eaefc62eeccb567ddabd9c8329aa6b7c7e672a5cf | MATLAB | 5,541 | 157 | function [C, Q] = procCosp(DATA, WINDOW_TYPE, WINDOW_SIZE, OVERLAP, FREQUENCY_RANGE, PHASE_CORRECTION)
% [C, Q] = procCosp(DATA, WINDOW_TYPE, WINDOW_SIZE, OVERLAP, FREQUENCY_RANGE)
%
% This function computes cospectra and quadrature spectra on multivariate
% data using Welch's method. For a better estimation, each... |
c5f9d6a0d5efbf724b91cc944bd4c96676f5680c8d25c53d458101c9d5280ca4 | MATLAB | 5,554 | 130 | clear
clc
scale_factor = 16;%ͼÏñÔÚ¼ÆËãµÄʱºòµÄËõ·Å´óС8 12 32(´óͼ) 2»ò3£¨Ð¡Í¼µ½´óͼ£© 5.12 ´óͼ12 8²»ÐÐ 16
stack_img_dir = 'E:\Zhu\myownex\ETreg\img\TOM\stack\result\';
ava_img_dir = 'E:\Zhu\myownex\ETreg\img\TOM\stack\ava\';
file_name = dir(stack_img_dir);
num_stack = length(file_name) - 2;
%% ÇóstackµÄ¾ù... |
29c52ae466217e38843d4bcea4f7832c54c445aa778177a428780ea500251270 | MATLAB | 5,556 | 125 | function Fun_ExportTimeSpentTC(Path, Subject, ScoringPerFileTC,...
ScoringMappingForVS, SleepFragTC, NumOfTimePoints, TimeBin,...
EpochLength, NumberOfFilesPerSubject, FileNamesForSubjects)
%% Written and updated by M. Nollet (Aug 2023)
%
% Function to be used to export sleep architecture and sleep fragme... |
6e51928e432f06bc37841b965e80346ec448c3d19cabdbb767067f69ebd532ad | MATLAB | 5,556 | 195 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [nodes, nodes_b, tetra, johtavuus_ind, surface_triangles,name_tags] = zef_fem_mesh(void)
void = [];
h = zef_waitbar(0,1,'Initial mesh.');
mesh_res = evalin('base','zef.mesh_resolution');
re... |
0a1df762e1459c4fa424c3edef0d11c8d85f6ae6c4bc4f7d3de01c66f2043630 | MATLAB | 5,563 | 139 | function [Y_pred, loglikelihoodX] = LDApredict(model,Gamma,X,classification,intercept)
% For an inferred LDA model and state timecourses, computes the
% likelihood manifold in X space and computes the likelihood function for
% each class of labels.
if nargin<4
classification=true;
end
if nargin<5
intercept=true... |
b8b80e10c61f4350b1076d54c62abd7ed5b7f5827b6b8e1264f2e5d930f720b1 | MATLAB | 5,565 | 176 | % This is a template script that runs the HMM on a fictional fMRI data set
% using a number of different settings, involving how many PCA components we use to
% describe the data, and how many HMM states we set up for the HMM inference.
% It assumes that there are 2 different
% conditions (for example rest and some t... |
8c9c98839f9afa72f74dd9619e64b31e018c21f0f1b45963c410b22a5918315b | MATLAB | 5,584 | 152 | function [opt, rip, stats, fh] = sw_run_ripple_LFP(varargin)
% [rip] = sw_ripple_LFP(dat, opt)
% top level function to perform ripple detection
% inputs:
% dat - data input which can be either
% a) string with path/file.dat or
% b) a data structure with the following fields:
... |
3da8ea9fdd5005bc3403017fee0644eedba47800d12bbdadcf887e5f6d3ce8b0 | MATLAB | 5,585 | 150 | function h = image3(im,ij2xyz,handle)
% Display a 2-D image in Matlab xyz 3-D space
% h = image3(C, IJ2XYZ, handle)
%
% C is an image, encoded with scalars or rgb-values, i.e. the dimensions of
% C are either N x M or N x M x 3. Scalars correspond to indices in the
% current colormap and rgb-values should be within the... |
211a5b12c598ae1f9a36e296affeb1050fd8fd6d03791d73b6bff7b8dc08938a | MATLAB | 5,594 | 119 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef_plot_hyperprior
axes(evalin('base','zef.h_axes1'));
cla(evalin('base','zef.h_axes1'));
tail_length = evalin('base','zef.inv_hyperprior_tail_length_db');
snr_val = evalin('base','zef.inv_... |
c3f713ba7b4106cb15f4c5ba0a285f56105438fa83b77166f87448e4d4bc6847 | MATLAB | 5,607 | 152 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
parameters;
nodes = load([torre_dir '/system_data/nodes_' int2str(system_setting_index) '.dat']);
tetrahedra = load([torre_dir '/system_data/tetrahedra_' int2str(system_setting_index) '.dat']);
... |
dd0fce2b5fdb8fbc4e7d8f64f0fa846d3feeae95fd33198a9585b48284faf565 | MATLAB | 5,620 | 253 | function plotting_simulations
addpath('./scripts');
outdirpath = './output_dir';
%% plotting AI
regime_type = 'AI';
plotting_helper0(regime_type, outdirpath);
%% plotting BS
regime_type = 'BS';
plotting_helper0(regime_type, outdirpath);
%% plotting SZ
regime_type = 'SZ';
plotting_helper0(regime_type, outdirpath);
... |
8d5475b7fce3a2af5cc994df2e8a26f61f8f297ec5411cc29a0a9f708e7682b3 | MATLAB | 5,626 | 182 | % sobi() - Second Order Blind Identification (SOBI) by joint diagonalization of
% correlation matrices. THIS CODE ASSUMES TEMPORALLY CORRELATED SIGNALS,
% and uses correlations across times in performing the signal separation.
% Thus, estimated time delayed covariance matrices must be no... |
ff553bbf912542f994453cdf5b1d38bf5a8bc8e45f510e1840ea4b17d4a6ea23 | MATLAB | 5,631 | 152 | function [contacts, sensor_info, triangle_ind] = zef_get_strip_contacts(contact_index,strip_struct,zef,domain_type,global_index)
if nargin < 4
domain_type = 'model_geometry';
end
if nargin < 5
global_index = [];
end
contacts = [];
sensor_info = struct;
triangle_ind = [];
sensor_info.strip_id = strip_struct.s... |
2592e5506eaa5f1e909e82c95e6902dba48c8c3f708398bfbe97d62cd539da50 | MATLAB | 5,679 | 172 | function [C,hmm] = hmmtestretest(data,T,options)
%
% Test the reliability of the solutions across repetitions of the HMM
% inference. Runs are aligned using the Hungarian algorithm and compared
% for each subject/segment (each element of T). The compared metric is the
% amount of agreement between the state time course... |
98585b5ae68e402f37c14356c414cd0a253c9f711d5c03cdb6d7fe8000474af7 | MATLAB | 5,708 | 114 | classdef SolverSGDM_conv3_LRC < nnet.internal.cnn.solver.Solver
% ====================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn\+nnet\+internal\+cnn\+solver
% ====================================================
% SolverSGDM Stochastic gra... |
dc0381f4f0c164f9017bfe1f4c687772ded21b7bad47618fb4f357eea0c38d15 | MATLAB | 5,708 | 114 | classdef SolverSGDM_conv3_LRC < nnet.internal.cnn.solver.Solver
% ====================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn\+nnet\+internal\+cnn\+solver
% ====================================================
% SolverSGDM Stochastic gra... |
d253e6aa723845308b7720632a2e762b9dfddf30fbe3b9ad97fda78599bd6e4d | MATLAB | 5,718 | 172 | function [CIN]=dat2mat(file);
%
% loads events from a jAER .dat/.aedat file.
% allAddr are int16 raw addresses.
% allTs are int32 timestamps (1 us tick).
% noarg invocations open file browser dialog (in the case of no input argument)
% directly create vars allAddr, allTs in
% base workspace (in the case of no output ar... |
1a1d505617008a1b1db4727dcceb4cf085470b1143308895ca6edb36097046aa | MATLAB | 5,737 | 234 | function [G, interpolation_positions] = zef_st_venant_interpolation( ...
p_nodes, ...
p_tetrahedra, ...
p_brain_inds, ...
p_intended_source_inds, ...
p_nearest_neighbour_inds, ...
p_regparam ...
)
% Documentation
%
% Produces an interpolation matrix G in a tetrahedral finite element mesh
% ... |
aac2055ae420dbb8580ec636e91168f1fdfb62b889804af13fc90d868c8a90f2 | MATLAB | 5,748 | 128 | function detection = ferrarelli_spindle_detection(C3,fs,stage_file)
% FERRARELLI Detect sleep spindles using the Ferrarelli algorithm.
% Ferrarelli et al. "Reduced Sleep Spindle Activity in Schizophrenia
% Patients", Am J Psychiatry 164, 2007, pp 483-492
%
% Input is recorded EEG for a whole night of sleep (any channel... |
f5a9ea8526c73f68264b3931f427ebb7ecd68af1404b7f4f61077680b4151277 | MATLAB | 5,749 | 143 | %% initialize
clear; clc;
currentPath = pwd;
cd ../temp
load('tempFileForAnalysis.mat');
cd(pathBIDS);
cd derivatives
pathDeriv = pwd;
cd(pathDeriv);
cd('spm-preproc'); % For saving preprocessed file from SPM
pathPrepFile = pwd;
prepSubjFolders = dir('sub*');
cd(pathDeriv);
cd('behavior');
pathBehav = pwd;
load('be... |
6f80c2b6eab5f19ac719f2d87470fd2d2f772770f0708658cdf06dc6057bb627 | MATLAB | 5,759 | 197 |
%% plot both size distributions in one graph
figureHandle=figure;
set(gcf,'units','centimeters','position',[4,4,8,12.2])
load('kesten_workspace.mat')
%% Intrinsic dists
in_inds=[3,4,5];
all_lims=[-3,0.3 ; 0, 0.01 ; 0 ,1];
positions_X=([0.25, 2.25, 4.25, 6.25]);
positions_Y=([10.25, 8.25, 6.25, 4.2... |
5faf29382f87d87758d394e3a05c3dc457b31d098fbd15dc7e25cd35799e9d00 | MATLAB | 5,803 | 201 | function [ electrode_data, electrode_labels ] = electrodes_from_dat(file, kwargs)
%
% electrodes_from_dat
%
% Imports a set of electrodes and their (optional) labels from a given text
% file. Throws an error if the given file could not be read.
%
% Inputs:
%
% - file (1,1) string { mustBeFile }
%
% The text file that... |
6339b1164e59beeacc391aa90433b1c4f974249be06846d61c05e6898e239cb4 | MATLAB | 5,807 | 179 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [z,reconstruction_information] = zef_mcmc(zef)
inverse_gamma_ind = [1:4];
gamma_ind = [5:10];
h = zef_waitbar(0,1,['MCMC sampling.']);
[s_ind_1] = unique(eval('zef.source_interpolation_ind{1}... |
fd7b509e676a2129d736cf001ffd227f691152e7771b8005fcdea58ffaeed976 | MATLAB | 5,810 | 231 | function projection_points_in_DSP = DPalgo_optimal_trajectory_withnan(DS_plane_feat, baby_data_feat_withnan, radius)
% To find the optimal projection of the data points onto the model
% [K^+]_{Buffer}-[O_2]_{Buffer} plane.
%
% Previous to this step, we perform feature normalization (for both DS_plane
% and baby_data) b... |
a9155ac6388fe6c6acb177b85f0f1af00b5e33a97a7e6baea01a35ab0848fe10 | MATLAB | 5,836 | 157 | function [stepsize, newx, newkey, lsstats] = ...
linesearch_adaptive(problem, x, d, f0, df0, options, storedb, key)
% Adaptive line search algorithm (step size selection) for descent methods.
%
% function [stepsize, newx, newkey, lsstats] =
% linesearch_adaptive(problem, x, d, f0, df0, options, storedb, key)
... |
67b8e7cc1a911b26e2e8e8bca142ccdc5bc204f87957b7cb973ef4dd801dd7e1 | MATLAB | 5,842 | 112 |
function [forward_pressure, backward_pressure, forward_velocity, backward_velocity, intensities] = zef_nse_separate_waves_roi(zef, nse_field)
roi_ind = zef_nse_roi_ind(zef,nse_field);
dir_aux = zef_nse_vel_dir(zef,nse_field);
% [~, dir_aux] = zef_nse_mean_velocity_roi(zef,nse_field);
n_time = length(zef.nse_field.bp_... |
f8f3e782b065aa5cb2f2f05a0b4dabee07d02d343238c9203acb8073a313594d | MATLAB | 5,855 | 174 | %% Fieldtrip preprocessing of data
% NOTE: This script does not contain any tutorials for +microstate toolbox,
% and is just used for pre-processing the data. For the tutorial on
% +microstate, see the script example_script_EEGcanonicalmaps.m
%
% This script follows the Fieldtrip tutorial for resting-state data
... |
f336912283db3ee3d961815a42ba10d34ea97fdcfe945c5bb036e29aa47befcc | MATLAB | 5,858 | 194 | function [C,A,e,Av] = corrStaticFC (data,T,options,use_pca)
% When running the HMM on fMRI data (with order=0, i.e. a Gaussian
% distribution with mean and covariance),
% it can happen that states are assigned to entire subjects
% with not much switching between states. This happens typically when the
% static functio... |
b22f68b4528c7dd8f27affa0c9dab6b54e2517f05e29a909493e2578109d4c71 | MATLAB | 5,888 | 123 | function [coupling] = structure_function_coupling(subject)
% The purpose of this script is to compute the structure-function coupling
% based on the correlational approach, on each HCP subject's brain region.
%
% Requirements:
% 1. Download the gifti and cifti-matlab toolboxes. Instructions can be found in:
% https://... |
3556bf4e1aa7d3e5da6c82aa9ccf3285415197e0a090adb45663cc6f5a5bf40b | MATLAB | 5,894 | 178 | function sClustered = getPreProClustering(sFile,sRP)
%% get paths & files
strTempDirSSD = sRP.strTempPath;
strPathToConfigFile = sRP.strConfigFilePath;
strConfigFileName = sRP.strConfigFileName;
strDataDir = sFile.sEphysAp.folder;
strDataFile = sFile.sEphysAp.name;
strNiqdName = sFile.sMeta.strNidqName;
... |
91a2bde6b9fd7b6b919b1eaaf58ba1f8bc1b2d8e0ece588b23dceac20630211d | MATLAB | 5,908 | 118 | %This is the startup script for beamformer app. One must add this as launch
%script to zeffiro_plugins file:
%Beamformer, inverse_tools, zef_beamformer_start
function zef = zef_beamformer_window(zef)
zef.beamformer = zef_beamformer_app;
%_ Names of methods that are included in app _
zef_bf_names = {'Linearly constrai... |
74b611be471464c90f96a19fa893241153c8a9033b71eed2287b01c777dcab63 | MATLAB | 5,916 | 120 | function zef = zef_electrode_strip_multiple_probe(zef)
clear strip_struct
orientation(1,:) = 1/norm(zef.strip_struct.dir_vec(1,:))*zef.strip_struct.dir_vec(1,:);
orientation(2,:) = 1/norm(zef.strip_struct.dir_vec(2,:))*zef.strip_struct.dir_vec(2,:);
position(1,:) = zef.strip_struct.center_point(1,:) - 4*zef.strip_stru... |
f586262e9edef620fd13bf16f345241f809be1d9fb95e6e4a2b4cc18cd1e2660 | MATLAB | 5,924 | 74 | function [W Ms crit]=uwedge_c(M,W_est0);
%
% Uniformly Weighted Exhaustive Diagonalization using Gauss itEration (U-WEDGE)
% for complex-valued matrices (not necessarily symmetric).
... |
65453980ab1ed89f103bee4f044698e3a6f0a26a721c1b5d8e364fd13b0e5e2e | MATLAB | 5,932 | 127 | function [empiricalCovarianceProjected] = empiricalCovariancesProjected(C, discreteTime, S, dt)
%
% Returns an empirical measurement of the covariance in the space orthogonal to the zero mode psi_0=[1 1 1 ... 1]
% for either continuous time Ornstein-Uhelnbeck or discrete time AR
% dynamics as required.
%
% There was... |
5fb5cec0c06a332e55a72b43eb709e495fbb08a6936b0f930aeffa2f18769e38 | MATLAB | 5,937 | 245 | function Mn = powermanifold(M, n)
% Returns a structure describing a power manifold M^n = M x M x ... x M.
%
% function Mn = powermanifold(M, n)
%
% Input: a manifold structure M and an integer n >= 1.
%
% Output: a manifold structure Mn representing M x ... x M (n copies of M)
% with the metric of M extended element-... |
18c8f78c902e6308b41562715ded1933a4a487506776ac47bbe2c2285aea0c0e | MATLAB | 5,942 | 183 | function [fe,ll] = hmmfe(data,T,hmm,Gamma,Xi,preproc,grouping)
% Computes the Free Energy of an HMM
%
% INPUT
% data observations, either a struct with X (time series) and C (classes, optional)
% or just a matrix containing the time series
% T length of series
% hmm ... |
1a99edc1a8db1ddd937fd6ecd354b5407feeb5668dfa6e26af2756aeb6fdaef8 | MATLAB | 5,942 | 137 | function sLocCh = getBrainAreasPerChannel(varIn,tv,av,st,boolCalcDistToBound)
%getBrainAreasPerChannel Retrieves brain area for each channel using Allen Brain Atlas
% sLocCh = getBrainAreasPerChannel(varIn,tv,av,st,boolCalcDistToBound)
%
%Input can be sAP structure, sFile structure, sProbeCoords structure or a pr... |
3654761a7e5c47d3e10e4916c9716f556fbd6b4eb9ef217eb98f56a702a26e69 | MATLAB | 5,943 | 148 | % Code used in Vidaurre et al. (2018) Cerebral Cortex
%
% Detailed documentation and further examples can be found in:
% https://github.com/OHBA-analysis/HMM-MAR
% This pipeline must be adapted to your particular configuration of files.
%%%%%%%%%%%%%%%%%%%%%%%%%
%% Setup
DO_PLOT = 1;
mydir = '/home/diegov/MATLAB/';
ad... |
a11d293947ecfe2da9fcdc646e6539df80ba689d1b14b5365bd186e4ab9ffc6a | MATLAB | 5,944 | 159 |
%--------------------------------------------------------------------------------
% This demo is included in
% Reverse engineering neural networks to characterise their cost functions
% Takuya Isomura, Karl Friston
%
% Copyright (C) 2020 Takuya Isomura
% (RIKEN Center for Brain Science)
%
% 2020-05-08
%---------------... |
46a7bb85dcf709ad8ce755d2976061a51895eb52669097c83b0ab545471d0ca3 | MATLAB | 5,967 | 119 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if zef.mlapp == 1
zef.preconditioner = get(zef.h_as_opt_1,'Value');
zef.preconditioner_tolerance = str2num(get(zef.h_as_opt_2,'Value'));
zef.smoothing_steps_surf = str2num(get(zef.h_as_opt_... |
3dccfe8b9233d933c1a2dffbff6b9f1ea66dd731f878e8bd0cd39f19e2f7f7a2 | MATLAB | 5,968 | 139 | %% Result 2 : Long-Range Connections Integrate Global Features (Figure 3)
%% Generate dataset
if ~exist('IMAGE_mod')
tic
disp('generating modified MNIST ...(~ 30 sec)')
[IMAGE_mod,LABEL_mod] = fun_generate_mMNIST(numTrain_mod);
toc
end
%% Show dataset
disp('Showing stimulus (Classs X Exampl... |
1360d27766658aeacc150bfed2f97ad1a3aee248f6e1ad8167043d99f0fb7aea | MATLAB | 5,978 | 197 | function [s_roi, roi_specs] = zef_ROI_finder(source_positions, roi_specs)
%beware: this function only moves s_p to the nearest source point if
%the roi is completely empty, therefore if the roi is not empty, there is
%not necessarily a source at the exact center
s_p = roi_specs.roi_center;
radius = roi_specs.rad... |
accefadf16609cd47b19303894d6167339e504ce8af34f59247986cee15bd646 | MATLAB | 5,979 | 185 | function [Gamma,vpath,error,Ypred] = tudadecode(X,Y,T,tuda,new_experiment,parallel_trials)
% Having estimated the TUDA model (i.e. the corresponding decoding models)
% in the same or a different data set, this function finds the model time
% courses (with no re-estimation of the decoding parameters)
%
% INPUT
% X: Bra... |
741f1eb22f1214d90381006f1d51133391a69e9975827578c12f09b3e1bace16 | MATLAB | 6,009 | 154 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [z,reconstruction_information] = exp_ias_iteration(void)
h = zef_waitbar(0,1,['IAS MAP iteration.']);
hyper_type = evalin('base','zef.exp_ias_hyper_type');
n_ias_map_iter = evalin('base','zef... |
c9ea343bcab9843d6a7c5392c860ed76d469c53744efd99ed6bc2a328f049ec3 | MATLAB | 6,014 | 147 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if zef.save_switch == 1
if not(isequal(zef.file,0));
zef.save_file = zef.file;
zef.save_file_path = zef.file_path;
zef_close_tools;
zef_close_figs;
zef_data ... |
a9ee345e65c7f6209ddb0dd048cfded2fc351c25cf003fba3a1d22e021cf60f4 | MATLAB | 6,022 | 184 | classdef BeamformerInverter < inverse.CommonInverseParameters & handle
%
% BeamformerInverter
%
% A class which defines the properties needed for different types of
% beamforming, and the method itself.
%
properties
%
%The inverse algorithm used. The options are currently:... |
45a1e4708f4debe6c7023cbd5f57679587685c74d15dec35aafb235c1e5b93a5 | MATLAB | 6,035 | 228 | %% Copyright © 2025- Joonas Lahtinen
function [z_vec, self] = invert(self, f, L, procFile, source_direction_mode, source_positions, opts)
%
% invert
%
% Builds a reconstruction of source dipoles from a given lead field with
% the CSM method.
%
% Inputs:
%
% - self
%
% An ... |
47e885bc8cfdc6244b2db70f6a9277e4c8a4102db6bf39a6a64a4c10c4223933 | MATLAB | 6,043 | 146 | %This function plot intensity as curves or histograms depending on is the
%ground truth setted or not.
function zef_plot_source_intensity
%Get needed variables
if str2num(evalin('base','zef.find_synth_source.h_plot_switch.Value')) == 1
name_label = evalin('base','zef.find_synth_source.h_source_list.Data(zef.find_s... |
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