sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
6138e36e7b7682a7efea4b700c2a0ce14a42a830750cba9130ecc305a0648f7b | MATLAB | 9,191 | 227 | %% Nat Comms Ictogenesis Figure 1
clear
load('20230127_PooledData.mat');
recdat = load('OP138B-210310-135833_ch2');
% Set up binning ranges
ephistbins = 1:15;
ephistedges = (1:16) - 0.5;
EXP5HZ = "B30_P5F5_";
EXP10HZ = "B30_P5F10_";
EXP20HZ = "B30_P5F20_";
rec = struct();
rec.stim5Hz = st... |
ac940d4c925222732a3ab019a5a3c7228fa5f364bce28fa10ef78c1d1fc2faed | MATLAB | 9,204 | 229 |
%--------------------------------------------------------------------------------
% utm.m
%
% This demo is included in
% Triple equivalence for the emergence of biological intelligence
% Takuya Isomura
%
% The MATLAB scripts are available at
% https://github.com/takuyaisomura/reverse_engineering
%
% Copyright (C) 2024... |
3034a42cbab2df12a0a68fdfd1809bdf8488749894d5d88d351fbe0e92d0896c | MATLAB | 9,222 | 188 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef_plot_parcellation_time_series(void)
void = [];
time_series = evalin('base','zef.parcellation_time_series');
plot_type = evalin('base','zef.parcellation_plot_type');
selected_list = evali... |
86ecd4a868294b260776a93c7b57659fd35d93e50fe76a9e0914b0224e39802a | MATLAB | 9,233 | 144 | % MAT2NLXSPIKE Exports data from Matlab into a Neuralynx NSE, NST or NTT file.
%
% Mat2NlxSpike( Filename, AppendToFileFlag, ExportMode, ExportModeVector,
% FieldSelectionFlags, Timestamps, ScNumbers, CellNumbers,
% Features, Samples, Header);
%
% Version 6.0.0
%
% Requires MATLAB... |
e3625ee28496f3d237c2732825cd14075a5316d19c88dc04a06afbedf218ac2e | MATLAB | 9,235 | 232 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [sensors_attached_volume] = zef_attach_sensors_volume(zef,sensors,varargin)
if isempty(zef)
zef = evalin('base','zef');
end
attach_type = 'mesh';
bypass_functions = 0;
I_get_functions =... |
441aad7629ae679a2ae1f26ffb3cc3e2e4b33dfb0feff4968fddc2e2bdd43a4a | MATLAB | 9,236 | 145 | % MAT2NLXNRD Exports data from Matlab into a Neuralynx NRD file.
%
% Mat2NlxNRD(FileName, ChannelNumber, AppendToFileFlag, ExportMode,
% ExportModeVector, FieldSelectionFlags, Timestamps,
% Samples, Header);
%
% Version 6.0.0
%
% Requires MATLAB R2012b (8.0) or newer
%
%
% IMPORTAN... |
1a262763f4e0930838d02147ea5b5004199597fe8f14ac76b21cf4e1d3662444 | MATLAB | 9,255 | 193 | %% 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... |
b55bedf06171a8b2d0d951da361c52d9b9ccbf75e0eae2e0f539b4dd4e5d84bc | MATLAB | 9,265 | 320 | function [noise,dat]=sw_simple_noise_rejection(varargin)
% %sleepwalker help---------------------------------------------------------
% sw_simple_noise rejection accepts different input argument combinations
% sleepwalker simple noise rejection
% detect extreme values in signal based on squared - zscored signa... |
c8a685b7cd54935dd1a379b14022810c4c924cba086b329bf5fac4c38ef60098 | MATLAB | 9,282 | 245 | function [x, info, options] = stochasticgradient(problem, x, options)
% Stochastic gradient (SG) minimization algorithm for Manopt.
%
% function [x, info, options] = stochasticgradient(problem)
% function [x, info, options] = stochasticgradient(problem, x0)
% function [x, info, options] = stochasticgradient(problem, x0... |
81ec646142de14ec7c4c64e92c785a56d96775db541c12729bb253fca5344a4a | MATLAB | 9,317 | 283 | function [UI] = fn_UI_fmincon(P,nz,ny,nx,flag)
% flag: 0 if fmincon is blackbox, 1 if derivative is included and 2 if Hessian and derivative is included
if flag==0
% Blackbox fmincon
TSTART = tic;
[~,UI,~] = fn_UI_fmincon_main_BB(P,nz,ny,nx);
t = toc(TSTART)
else
% flag =... |
102745a96804ff08e1c4038a91be183eeb6a9fd15e3c85cce15db309839f7bc5 | MATLAB | 9,324 | 272 | %%Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [L_eeg, dipole_locations, dipole_directions] = lead_field_eeg_fem( ...
zef, ...
nodes, ...
elements, ...
sigma, ...
electrodes, ...
p_nearest_neighbour_inds, ...
o... |
4fee291704abb5f428965558207665125f82104ed87edb94fa8094c588fe12b6 | MATLAB | 9,333 | 331 | classdef UKFNMMInverter < inverse.CommonInverseParameters
%
% KalmanInverter, Copyright © 2025- Joonas Lahtinen
%
% A class which defines the properties needed by the Kalma filter / Standardized Kalman filter inversion method,
% and the method itself.
% The method is based on the article:
%... |
fe588128c80c9325d8e2adcfa62a975d65b8948ecc0319747442073d2b5b174a | MATLAB | 9,357 | 293 | function M = essentialfactory(k, strSigned)
% Manifold structure to optimize over the space of essential matrices.
%
% function M = essentialfactory(k)
% function M = essentialfactory(k, 'signed')
% function M = essentialfactory(k, 'unsigned')
%
%
% Quotient representation of the essential manifold: deals with ... |
db181a56f2cef6eb704e2d8b3383a9d1320d05c6b9775cd1c33ecf530da8ce5b | MATLAB | 9,358 | 308 | function [opt,delta,stats] = sw_run_delta_hEEG(varargin)
% [rip] = run_ripple_LFP(dat, opt)
% top level function to perform ripple detection
% inputs:
% 1) dat - data input which can be either
% a) a string: dat='data/human_eeg3.edf'
% or
% b) a data structure wit... |
dca1dae8e91732327bb6d86fdaea25238ec6dddc8eef8a225b8db92dc9479274 | MATLAB | 9,394 | 165 | zef_init_forward_and_inverse_options;
zef_data = zef_forward_and_inverse_processing_options;
zef.fieldnames = fieldnames(zef_data);
for zef_i = 1:length(zef.fieldnames)
zef.(zef.fieldnames{zef_i}) = zef_data.(zef.fieldnames{zef_i});
if find(ismember(properties(zef.(zef.fieldnames{zef_i})),'ValueChangedFcn'))
... |
f6a21dc14d4c622030d3e170a889117ccb945ec15cec96d18bbbe549966db57a | MATLAB | 9,399 | 148 | function project_struct = lead_field_example ( kwargs, mesh_kwargs, lead_field_kwargs )
%
% examples.lead_field_example ( kwargs )
%
% Demonstrates how one might construct a lead field matrix with Zeffirro
% Interface, from the Matlab command line. Look into the wiki page
% https://github.com/sampsapursiainen/zeffiro_i... |
0ada5f2bf48658c125a7b1df7a11c9921ac769c72e8ed92083b32838af525e02 | MATLAB | 9,407 | 202 | % Parameter values and their initial values for Zeffiro-Brainstorm plugin.
%
% zef_bst.save_project = 1;
%
% This flag (logical 1 or 0) defines whether the
% Zeffiro's project file with mesh is saved on disk.
%
% zef_bst.import_settings = ""; ... |
f559e2569c9b979fbb7285b27ab998cf80eeb335757ee46232b9ad10646d7b09 | MATLAB | 9,414 | 234 |
function zef = zef_nse_iteration(zef)
[zef.nse_field.nodes, zef.nse_field.tetra] = zef_get_submesh(zef.nodes,zef.tetra,zef.active_compartment_ind);
signal_pulse.dir = zeros(size(zef.inv_synth_source,1),3);
flux_val = 7.5e-4/60;
flux_vec = [0.5 0.5 -1/3 -1/3 -1/3]*flux_val;
n_smoothing = 0;
atmosphere_pressure = 1.0... |
a7ae6a5a881560c90f810cc95ccdeaed13683e788c19d14b5240410c55d81e30 | MATLAB | 9,433 | 200 | function signal = clean_channels(signal,corr_threshold,noise_threshold,window_len,max_broken_time,num_samples,subset_size)
% Remove channels with abnormal data from a continuous data set.
% Signal = clean_channels(Signal,CorrelationThreshold,WindowLength,MaxBrokenTime,NumSamples,SubsetSize,UseGPU)
%
% This is an automa... |
1f917779da77f21eb9ea784d47c80e77375d5c61397efbfbc1db74f454e761b9 | MATLAB | 9,474 | 264 | %% Nat Comms Ictogenesis Figure 5
clear
load('20230127_PooledData.mat');
EXP5HZ = "B30_P5F5_";
EXP10HZ = "B30_P5F10_";
EXP20HZ = "B30_P5F20_";
sz = struct();
sz.stim5Hz = startsWith(sztable.ExpProtocol, EXP5HZ);
sz.stim10Hz = startsWith(sztable.ExpProtocol, EXP10HZ);
sz.stim20Hz = startsWith... |
2dc184685daeedf09955dc68357ae3b3daea6dcc1e1385e4a11313b3efc3bb6a | MATLAB | 9,503 | 278 | function [hmm,Gamma,Xi,fehist] = hmmtrain(data,T,hmm,Gamma,residuals,fehist)
%
% Train Hidden Markov Model using using Variational Framework
%
% INPUTS:
%
% data observations - a struct with X (time series) and C (classes)
% T Number of time points for each time series
% hmm hmm structure... |
3e67d6e79d3c753e5896ef146e3b402479ac9438119cb092b23428889702bb5e | MATLAB | 9,511 | 239 | function M = hyperbolicfactory(n, m, transposed)
% Factory for matrices whose columns live on the hyperbolic manifold
%
% function M = hyperbolicfactory(n)
% function M = hyperbolicfactory(n, m)
% function M = hyperbolicfactory(n, m, transposed)
%
% Returns a structure M which describes the hyperbolic manifold in Manop... |
142cf159cc9f485ea6fcf7b531707de341abe0f2aa22b18810586845ae3bad0f | MATLAB | 9,527 | 241 | function [x, cost, info, options] = steepestdescent(problem, x, options)
% Steepest descent (gradient descent) minimization algorithm for Manopt.
%
% function [x, cost, info, options] = steepestdescent(problem)
% function [x, cost, info, options] = steepestdescent(problem, x0)
% function [x, cost, info, options] = stee... |
cd42e0a7bbec3520e852f0745d6c32f6a79e427d74d3f80142626b40a581c5b0 | MATLAB | 9,556 | 231 | function zef = zef_ES_find_currents(varargin)
%% Loading data
switch nargin
case {0,1}
if nargin == 0
zef = evalin('base','zef');
else
zef = varargin{1};
end
[alpha, epsilon] = zef_ES_find_parameters(zef);
case {3}
[zef, alpha, epsilon] = deal(vara... |
43fc5481507ff8d069b1b24ed489614f9c94a586d5a9fcf2c992349c3bf5a73e | MATLAB | 9,618 | 244 | function L = obslike(X,hmm,residuals,XX,cache)
%
% Evaluate likelihood of data given observation model, for one continuous trial
%
% INPUT
% X N by ndim data matrix
% hmm hmm data structure
% residuals in case we train on residuals, the value of those.
% XX alternatively to X (which in this case... |
a9be78e05c06535f874842f30eec2556cd8d95f3ffa3516b850e75e3af54dd61 | MATLAB | 9,628 | 249 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [parcellation_interpolation_ind] = zef_parcellation_interpolation(zef)
domain_labels = eval('zef.domain_labels(zef.brain_ind)');
submesh_ind_vec = eval('zef.submesh_ind');
parcellation_compar... |
17374ae92022edb3a9a2754fb3cb9a8cd3e511cd71a7577fb5b7a15888064d09 | MATLAB | 9,695 | 157 | % MAT2NLXNDE Exports data from Matlab into a Neuralynx NDE file.
%
% Mat2NlxNDE(FileName, AppendToFileFlag, ExportMode, ExportModeVector,
% FieldSelectionFlags, StartTimestamps, EndTimestamps,
% SamplesLost, DataTypes, ObjectNames, Header);
%
% Version 6.0.0
%
% Requires MATLAB R2012b (... |
3076c48d170698b4cbb46298d6ffdfc04a9f9598cbcb83e167b40eed0f640b0d | MATLAB | 9,699 | 222 | function computeSyncResults(varargin)
%% function computeSyncResults(N, b, c, undirected, discretized, repeats, networkType, p, d, S, maxMotifLength, folder, MaxK, dt)
% function computeSyncResults(properties)
%
% Generate networks and compute the synchronizability for a number of networks assuming gaussian dynamics
% ... |
651ffdadc450061e134b2f174e7695c6ddb7249f5948456ea1e333decea2985c | MATLAB | 9,762 | 316 | %=============================================================================%
% generate_tube frames: Given a 3D curve (x,y,z) build a tube as a mesh of %
% polygons (mainly triangles of quadrilateral) %
% %
... |
f1e5c5e501f31d053d0a757661ebea4d0a4483b9360f5d64e7f49d0f9f2408e3 | MATLAB | 9,821 | 230 | function plotSyncResults(varargin)
%% function plotSyncResults(N, b, c, undirected, discretized, repeats, networkType, p, d, S, maxMotifLength, folder, MaxK, dt)
% function plotSyncResults(parameters)
%
% Plot the synchronisation versus p or c for a number of network samples
% (discrete time AR or continuous time Orns... |
1f453fe70f1b22cd5018b2c209507333e65a3072e412c774480a8e206b0ee3f5 | MATLAB | 9,831 | 237 |
%--------------------------------------------------------------------------------
% adder_evo.m
%
% This demo is included in
% Triple equivalence for the emergence of biological intelligence
% Takuya Isomura
%
% The MATLAB scripts are available at
% https://github.com/takuyaisomura/reverse_engineering
%
% Copyright (C... |
92effdb2e3eed24e243a8f8f5390dba052f616ea1407e854cb5da0b959ad0c8d | MATLAB | 9,881 | 270 | function [hdr, record] = edfreadUntilDone(fname, varargin)
% Read European Data Format file into MATLAB
%
% [hdr, record] = edfread(fname)
% Reads data from ALL RECORDS of file fname ('*.edf'). Header
% information is returned in structure hdr, and the signals
% (waveforms) are returned in struc... |
9e9751c00199c9d85a5692adc47b61c6bee7a2dd131846d34f23113b7f265f64 | MATLAB | 9,900 | 324 | function M = productmanifold(elements)
% Returns a structure describing a product manifold M = M1 x M2 x ... x Mn.
%
% function M = productmanifold(elements)
%
% Input: an elements structure such that each field contains a manifold
% structure.
%
% Output: a manifold structure M representing the manifold obtained by
%... |
0948366e2e06d151db076fad60d828edb5523e44336ce8d430397018fb7de0c2 | MATLAB | 9,906 | 262 | function [hdr, record] = edfread(fname, varargin)
% Read European Data Format file into MATLAB
%
% [hdr, record] = edfread(fname)
% Reads data from ALL RECORDS of file fname ('*.edf'). Header
% information is returned in structure hdr, and the signals
% (waveforms) are returned in structure reco... |
fe2da6727ef74390c878ab04933e4f3182c05144937ee7a12b76994017c99e1c | MATLAB | 9,919 | 306 |
h1 = figure(...
'PaperUnits',get(0,'defaultfigurePaperUnits'),...
'Units','normalized',...
'Position',[0.4325 0.754529914529915 0.184722222222222 0.271111111111111],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'IntegerHandle','off',...
'Colormap',[... |
073952a330369f5c6eb5a70e3b3acfe519549cf6a6c5f3ace8befb52f8f9abf1 | MATLAB | 9,932 | 317 | function [ sensitivities_with_statistics, L ] = main ( ...
project_path, ...
inverse_method, ...
n_of_runs, ...
noise_level_db, ...
diff_type, ...
dispersion_radius, ...
args ...
)
%
% examples.studies.santtus_peeling_article.main
%
% Computes normed distance, direction and magnitude differe... |
a0eb3a6fada9c0f9f2a8abd55cc1cce9db63b31de05998ebdc7d37b23559a118 | MATLAB | 9,933 | 307 | function [dat] = sw_load_LFP (opt)
% [dat] = detect_load_LFP (opt)
%--------------------------------------------------------------------------
% function to load LFP data
% add custom load routines as needed
%
% inputs: 1) structure opt with fields
% opt.pat : path to data file in string
% ... |
23a727c84a62abe39546721296445eae39d09cff581282a53dbbe33f94c30693 | MATLAB | 9,970 | 359 | function [G, interpolation_positions] = zef_hdiv_interpolation( ...
p_nodes, ...
p_tetrahedra, ...
p_brain_inds, ...
p_intended_source_inds, ...
p_nearest_neighbour_inds, ...
p_optimization_system_type ...
)
% Documentation
%
% Produces a lead field interpolation matrix G with position-base... |
1ce63636cd5b4f8746bed9f2913dc98c744442c28dbf5c627abe2cd6e6c0b3d5 | MATLAB | 9,975 | 290 | function [fh,fnprnt,cdata]= sw_plot_detection(dat,ev, stats,opt)
% funtion to plot a summary of detection results and save as pdf
%%
if isfield(ev,'auto')
ev=ev.auto;
end
% Get the length of noise epochs and discard it when computing the total duration
% and the frequency of spindles per seconds
noiseLe... |
0c3eb3a27287b1ae52f9277ae83c6163255d619e84e847501d92a90354bea353 | MATLAB | 9,978 | 285 | function [x, cost, info, options] = neldermead(problem, x, options)
% Nelder Mead optimization algorithm for derivative-free minimization.
%
% function [x, cost, info, options] = neldermead(problem)
% function [x, cost, info, options] = neldermead(problem, x0)
% function [x, cost, info, options] = neldermead(problem, x... |
ebf45dcc32d42cfbf888d1d26055ac5c5b0fed114f0b15a6a36243a78e621df3 | MATLAB | 9,984 | 307 | function [net,stats] = cnn_train_dag_seg(net, imdb, getBatch, varargin)
%CNN_TRAIN_DAG Demonstrates training a CNN using the DagNN wrapper
% CNN_TRAIN_DAG() is similar to CNN_TRAIN(), but works with
% the DagNN wrapper instead of the SimpleNN wrapper.
% Copyright (C) 2014-15 Andrea Vedaldi.
% All rights reserved... |
57b8b434be1d78585e15bd5775f17f9818db2e49bce4a513dc3332b1013ad7dc | MATLAB | 10,011 | 237 | function obj = simulate_seq_randomwalk(obj,varargin)
% Simulate a random-walk decision-tree microstate sequence
% check inputs
options = microstate.functions.make_options(varargin) ;
% default options
defaults = {'Nsample',[] ;
'fsample',[] ;
'Nstates',4... |
3dd3d26c8c3d6bb1d42b2c9629686ac9447c29416b1f996cec15e264c528596d | MATLAB | 10,051 | 337 |
h1 = figure(...
'PaperUnits',get(0,'defaultfigurePaperUnits'),...
'Units','normalized',...
'Position',[0.4325 0.754529914529915 0.184722222222222 0.271111111111111],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'IntegerHandle','off',...
'Colormap',[... |
57288595b7deb1ada95e3dbc4cb5dde29c8bd1949c323d6842f6a82f618f14c4 | MATLAB | 10,058 | 244 | function checkhessian(problem, x, d)
% Checks the consistency of the cost function and the Hessian.
%
% function checkhessian(problem)
% function checkhessian(problem, x)
% function checkhessian(problem, x, d)
%
% checkhessian performs a numerical test to check that the directional
% derivatives and Hessian defined in ... |
420b2f6d916e88bd098b3d08a9fd110a46010a8f6f200b546bc4284206d97f60 | MATLAB | 10,087 | 164 | %% Demo code ver. 02/17/2020
%=============================================================================================================
% A brain-inspired architecture for cost-efficient object recognition in shallow neural networks
% Prerequirement
% 1) MATLAB 2018b or later version is recommended.
% 2) In... |
af6c926b194029085428583ef0bddbbd5b3ffe514a7097641d6a09f0fdf3e80f | MATLAB | 10,127 | 257 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [z,reconstruction_information] = exp_iteration(zef)
parameters = fields(zef.EXP.parameters);
for n = 1:length(parameters)
eval([erase(parameters{n},'exp_'),'=',num2str(zef.EXP.parameters.... |
9d53d874aa1bf0359cce345625e9d5318f372ffc1da1fe041db25177ef2bc6ac | MATLAB | 10,136 | 273 | function hiso=plot3t(varargin)
% PLOT3T Plots a (cylindrical) 3D line with a certain thickness.
%
% h = plot3t(x,y,z,r,'color',n);
%
% PLOT3T(x,y,z), where x, y and z are three vectors of the same length,
% plots a line in 3-space through the points whose coordinates are the
% elements of x, y and z. With a rad... |
e11b309cec16ff747862f37540e7571e947e99eb0d6052eb710b38505046f267 | MATLAB | 10,137 | 264 | function [acc_t,predictions_hard,predictions_soft,genplot] = standard_classifier_test(model,X,Y,T,options,binsize)
% Fit an already trained classifier given by the structure model to the
% test data given in X with labels Y.
%
% INPUT
% model: a classification model outputted from the function
% standard_cla... |
0d4bcfd0b446d108fee639502c9454fc76e49c32027b51884336131e74fbc87b | MATLAB | 10,159 | 334 | function [dat]=sw_noise_rejection(dat,opt)
% %sleepwalker help---------------------------------------------------------
% sw_simple_noise rejection
% sleepwalker simple noise rejection
% detect extreme values in signal based on squared - zscored signal
% case 1 switch off
% inputs: dat = sw data structure
%
% ... |
95d847b3499da1f855b8ad310681adf8218e87935f4e66350b399ec8b3a05451 | MATLAB | 10,167 | 337 | function [opt,spindle,stats] = sw_run_spindle_hEEG(varargin)
% [rip] = run_ripple_LFP(dat, opt)
% top level function to perform ripple detection
% inputs:
% 1) dat - data input which can be either
% a) a string: dat='data/human_eeg3.edf'
% or
% b) a data structure... |
b0d88d68062e917d465ed0ff00e3641421715d0de43342b4a7c798f09da6aada | MATLAB | 10,180 | 304 | function [tuda,Gamma,GammaInit,vpath,stats] = encodertrain(X,Y,T,options)
% Performs the Temporal Unconstrained Decoding Approach (TUDA),
% an alternative approach for decoding where we dispense with the assumption
% that the same decoding is active at the same time point at all trials.
%
% INPUT
% X: Brain data, (... |
7ad964b3dbea39c27095a5aaf8ea1293592028b75d4702ccc6dda6798a7f9096 | MATLAB | 10,192 | 304 | function [reconstruction, reconstruction_info] = zef_nse_reconstruction(nse_field,type)
reconstruction = cell(0);
reconstruction_info = cell(0);
if isequal(type,1)
for i = 1 : size(nse_field.bp_vessels,2)
aux_vec = zef_nse_threshold_distribution(nse_field.bp_vessels{i}(:),nse_field.min_reconstruction_qu... |
00606490217d31ce445bc46a16da9fa950184e5b7ce1b10a072a7bb226097db2 | MATLAB | 10,197 | 239 | classdef TrainingOptionsSGDM_conv3 < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM Train... |
65ff72b9a9a4cfb9cc022def33d83f81372773a06aa8735f72d5108bb690f43a | MATLAB | 10,197 | 239 | classdef TrainingOptionsSGDM_conv5 < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM Train... |
7eadb95d801b1c8218888dd2a6f9ea18b28a7a7184f25adf6bb31a4d111894b1 | MATLAB | 10,197 | 239 | classdef TrainingOptionsSGDM_conv3 < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM Train... |
eb3a0b89f165d73b9caa3bed030884c5e8d130893c45dd96b7b412d3312aa476 | MATLAB | 10,197 | 239 | classdef TrainingOptionsSGDM_conv5 < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM Train... |
04c56daf2fa0ecae1a4ef90c969a1961f24c8b229b21b934895950c02a7fb0c2 | MATLAB | 10,198 | 239 | classdef TrainingOptionsSGDM_conv4 < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM Trai... |
57fbd2eef4c839c9e0df31fd324d99453e49ded533ab78cf76c92fe5c05908be | MATLAB | 10,198 | 239 | classdef TrainingOptionsSGDM_conv4 < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM Trai... |
d1bafdc2f5b8fa4a03160419fd8f2d3a97e2cc0342fe2d7263b72786a42249b3 | MATLAB | 10,209 | 239 | classdef TrainingOptionsSGDM_conv3_LRC < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM T... |
d38dc500cc2bef1fbf41012210a3d9e49fb2e4e7d39aa98ffeabf7ec03cd2ed1 | MATLAB | 10,209 | 239 | classdef TrainingOptionsSGDM_conv3_LRC < nnet.cnn.TrainingOptions
% ================================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn\+nnet\+cnn
% ================================================================
% TrainingOptionsSGDM T... |
d709ac5c4364111988572e277789f5bb1eb0dfa7d0834625fdf844aa03e0f4de | MATLAB | 10,248 | 245 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [z,reconstruction_information] = exp_em_iteration_multires(void)
h = zef_waitbar(0,1,['EM MAP iteration for EP.']);
n_multires = evalin('base','zef.exp_multires_n_levels');
sparsity_factor = ... |
f6007bb5b38d4c6ad7275983ed6023716940af98fec2cc3b0e877e27e45d756b | MATLAB | 10,260 | 290 | function [varargout]=gscatter3(x,y,z,g,clr,mrksle,mrksze,mrkfclr,leg,legloc)
%------------------------------HELP START----------------------------------
% gscatter3 - 3D scatter plot by group
%
% Ussage:
% gscatter3(x,y,z,g);
% gscatter3(x,y,z,g,opt_param);
% opt_param - optional parameters such a... |
489497fe50db8064d53d8a4e4f3b7bce198744a8041c9eed9da1412b2179be55 | MATLAB | 10,328 | 262 | function sFiles = RP_CompileDataLibrary(sRP,ptrText)
%%
%strOutputPath: 'D:\Data\Processed\Neuropixels'
% strTempPath: 'E:\_TempData'
% strEphysPath: 'D:\Data\Raw\Neuropixels'
% strStimLogPath: 'D:\Data\Raw\Neuropixels'
%strEyeTrackingPath: 'D:\Data\Raw\Neuropixels'
% strProbeLocPath: 'D:\Data\... |
fb9af6c9ea7af0369953d24f27e4f420ca20b7ddabd7c66ff75f2f7924ffe08c | MATLAB | 10,351 | 316 | function [zef, Y, info] = zef_simulate_measurements_from_outPub(zef, sourceTree, outPub, varargin)
%ZEF_SIMULATE_MEASUREMENTS_FROM_OUTPUB
% Plot-driven measurement simulator (outPub -> sensor data):
% - iterates over outPub.nodes exactly like zef_plot_outPub
% - takes y = upAbsByPass(:,pass) and ignores NaNs like p... |
10d242ee6fdcc37ccb72be33fb9c5d1f426c1eb6de6f98afcf747459e5024afc | MATLAB | 10,373 | 295 | %% Nat Comms Ictogenesis Figure S3
clear
load('20230127_PooledData.mat');
EXP5HZ = "B30_P5F5_";
EXP10HZ = "B30_P5F10_";
EXP20HZ = "B30_P5F20_";
sz = struct();
sz.stim5Hz = startsWith(sztable.ExpProtocol, EXP5HZ);
sz.stim10Hz = startsWith(sztable.ExpProtocol, EXP10HZ);
sz.stim20Hz = startsWit... |
ad69fa83e0076612f41dca9ce1ead60a5dff768ed15f59fa6999f8719e18acca | MATLAB | 10,415 | 286 | function [params] = parameterize(varargin)
% Reviewed Darik A ONeil 04-15-2023
%
%Primary validation is done in-line.
%
%Secondary validation functions are constructed below and performed last.
%Steps
%(1, Construct the Parser)
%(2, Global Parameters)
%(3, Structural Learning Parameters)
%(4, Parameter Estimation Pa... |
6a8c3bced41260653fb47ba8a92a86be2fc203bb68a7a4046033ebd225e043d1 | MATLAB | 10,441 | 310 | classdef HALpRInverter < inverse.CommonInverseParameters & dynamicprops
%
% HALpRInverter, Copyright © 2025- Joonas Lahtinen
%
% A class which defines the properties needed by the Hierarchical Adaptive Lp-Regression (HALpR) inversion method,
% and the method itself.
% The method is based on the... |
66184a6c26c2449010fd8742a9adfbf565d16c679c59960d2666af8c1e652fd3 | MATLAB | 10,452 | 303 | function M = grassmannfactory(n, p, k, gpuflag)
% Returns a manifold struct to optimize over the space of vector subspaces.
%
% function M = grassmannfactory(n, p)
% function M = grassmannfactory(n, p, k)
% function M = grassmannfactory(n, p, k, gpuflag)
%
% Grassmann manifold: each point on this manifold is a collecti... |
b6eb30b156704b539b5c87bbc51698d5539836af1f022ccd7b0658527439d3a3 | MATLAB | 10,521 | 273 | function [hdr, record] = sw_edfread(fname, varargin)
% Read European Data Format file into MATLAB
%
% [hdr, record] = edfread(fname)
% Reads data from ALL RECORDS of file fname ('*.edf'). Header
% information is returned in structure hdr, and the signals
% (waveforms) are returned in structure r... |
40fb25b948bd8de5a5c97082a2ca69969970b9f0e9fe00584d5be13c14daadd3 | MATLAB | 10,529 | 211 | %% 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... |
d7f6d7f39678716ae248b3368ad2a40899b151713809d6b3067ed35a390f95fb | MATLAB | 10,592 | 291 | function progressbar(fractiondone, img, position)
% Description:
% progressbar(fractiondone,position) provides an indication of the progress of
% some task using graphics and text. Calling progressbar repeatedly will update
% the figure and automatically estimate the amount of time remaining.
% This implementa... |
3d48c95ed87396a41eb604493ef5a732b55070326ea01d9ca5d35fde8ec091b6 | MATLAB | 10,594 | 329 | % %%Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [L_tes, S_tes, dof_positions, dof_directions, dof_ind, dof_count] = lead_field_tes_fem( ...
zef, ...
nodes, ...
elements, ...
sigma, ...
electrodes, ...
p_nearest_ne... |
fc00c4408faffbf4e01b21e20d966825df2e3aea9fabb473ef46ed99945d9cac | MATLAB | 10,630 | 288 | function [eta, Heta, inner_it, stop_tCG] ...
= tCG(problem, x, grad, eta, Delta, options, storedb, key)
% tCG - Truncated (Steihaug-Toint) Conjugate-Gradient method
% minimize <eta,grad> + .5*<eta,Hess(eta)>
% subject to <eta,eta>_[inverse precon] <= Delta^2
%
% See also: trustregions
% This file is p... |
1fee97615d5b1432528a9deca23a8dbc478899af5c272b03ed2457eea913e783 | MATLAB | 10,643 | 302 | function [accumMatrix, gradientImg] = chaccum(varargin)
%CHACCUM Compute 2D accumulator array using Circular Hough Transform
% H = CHACCUM(A, RADIUS) computes the 2D accumulator array H using
% Circular Hough Transform for 2D grayscale input image A with the
% specified radius. The size of H is the same as the in... |
5a8c81774cf5f19c5aea8ee7b9d1a7d9ed16a8b6893af997e85ef02ad2c7c78d | MATLAB | 10,649 | 247 | function SleepFragTC = Fun_ComputeSleepFragTC(NumberOfFilesPerSubject,...
ScoringTC, EpochLength, NumOfTimePoints, WepochsSkip, SepochsSkip,...
NepochsSkip, RepochsSkip)
%% Written and updated by M. Nollet (Aug 2023)
%
% Function to be used to compute sleep fragmentation and consolidation
% data per tim... |
d7b57dd937c87d4d8a9def6cb52788acbddb90d956a7b4dbf7a221001ca544c9 | MATLAB | 10,653 | 349 | function outPub = zef_publish_jr_tree_delays(outTree, sourceTree, gd, varargin)
%ZEF_PUBLISH_JR_TREE_DELAYS Publish per-pass signals into absolute-time arrays using delays.
%
% Key idea:
% - Do NOT sum overlapping segments.
% - Do NOT replace missing samples by zeros.
% - Keep NaN padding; plotting will ignore Na... |
c8214c19dfbd31d6459da4cb49d328c0b609318884018fee01477ec76e5e1652 | MATLAB | 10,661 | 221 | function [outdata,outstate, Y] = asr_process(data,srate,state,windowlen,lookahead,stepsize,maxdims,maxmem,usegpu)
% Processing function for the Artifact Subspace Reconstruction (ASR) method.
% [Data,State] = asr_process(Data,SamplingRate,State,WindowLength,LookAhead,StepSize,MaxDimensions,MaxMemory,UseGPU)
%
% This fun... |
22701890d06db7d9df709cc4c905b7ae38fa087fe836a31e7e949a81bf02898d | MATLAB | 10,684 | 229 | %This is the startup script for GMModel app. One must add this as launch
%script to zeffiro_plugins file:
%GMMing, inverse_tools, GMModel_start
%don't allow to open multiple app window because it cause ether App
%Designer or app's functionalities to crash or both of them
%9.7.2024 updation - Joonas Lahtinen
if isfi... |
ff081c0b9a0d79c5de1a936355d1c564e4bd0110f33510dd15799bfeeffcede9 | MATLAB | 10,697 | 312 | function [ripples,sd,bad] = detect_ripples_Zugaro(filtered,varargin)
%FindRipples - Find hippocampal ripples (100~200Hz oscillations).
%
% USAGE
%
% [ripples,stdev,noise] = FindRipples(filtered,<options>)
%
% Ripples are detected using the normalized squared signal (NSS) by
% thresholding the baseline, mergi... |
756808dcf938039ed1e62f6273db163d5dd8122095e11b9d73e013b3a063dc2d | MATLAB | 10,818 | 298 | function [tuda,Gamma,GammaInit,vpath,stats] = tudatrain(X,Y,T,options,noGamma)
% Performs the Temporal Unconstrained Decoding Approach (TUDA),
% or Temporal Unconstrained Classification Approach (TUCA) if the stimulus
% is discrete. For the latter, options.classifier must be specified.
% This is an alternative approac... |
7742f96632511603b7d8e73db7f919f89ddeef5b6b1dcf937ed7ba50d9fd8a9b | MATLAB | 10,827 | 237 | function zef_PlotGMMcluster
m_size = evalin('base','zef.GMMcluster_markersize');
m_width = evalin('base','zef.GMMcluster_markerwidth');
m_sym = evalin('base','zef.GMMcluster_markercolor');
s_length = evalin('base','zef.GMMcluster_veclength')^2;
plot_ellipsoids = evalin('base','zef.GMMcluster_plotellip');
ellip_trans =... |
7f4d8d844064cd48504ad2f1ab32e573a69deaeae49074e75d56f61f3c8b2b4a | MATLAB | 10,847 | 368 | %% statistical analysis of the lognormal parameters you gathered in the "logfit" script
% first step is to read the data into the script
% repeat / copy this section
% change the folder to where you saved all the parameters and values
% cd('C:\Users\Nina R��ler\Google Drive\PhD\Paper\12_2021_new figures\gof_sig... |
1aac991d6f46fb7c13e29ea5331f452bcd4b3459ad3d4f28597149494cd71725 | MATLAB | 10,860 | 309 |
clear all
files={''};
alldata=[]; alldataSTD=[]; cells=0; framerate=28;
stdz=1;
baseper=round(framerate*1.2):((framerate*2)-3); %for baseline correcting df
actper2=1:(framerate*2);%for calculating standard deviatiion of df (for scaling/selecting)
ends=[91 91 76 84 85 86 86]; for stim=1:7; actper{stim}=ends(stim):((f... |
02600060ac8eb58c4f738e195c95e98d7b741573adbeacbb01e76ce86969e0ba | MATLAB | 10,886 | 254 | function ETC_redraw(varargin)
%get globals
global sETC;
global sFigETC;
%% redraw image
%get data
vecT = sFigETC.ptrAxesX.Children(contains(arrayfun(@(x) x.Type,sFigETC.ptrAxesX.Children,'UniformOutput',false),'line')).XData;
vecX = sFigETC.ptrAxesX.Children(contains(arrayfun(@(x) x.Type,sFigETC.ptrAxesX.Chi... |
7801ab098c1e85f9d77f1db4d2835433e3f79dcedf5f103ee4c1db7d57fbfb74 | MATLAB | 10,911 | 337 | % TD custard
% quick version
function custardOutput = TDcustard(n,signal,sigthresh,minAmp,minWidth,tXrise,noFig,detailFlag)
% n, number of points to test for a change
% signal, 1xnpnts
% sigthresh, significance to call an up
% minAmp, to be a peak the relative amplitude needs to exceed this
nBase = n;
if detailFlag==... |
d98a7175e89ef29bfec93b041d1dc7b036fb6ad6c01639948ce7619831f25ae5 | MATLAB | 10,962 | 176 | % pop_clean_rawdata(): Launches GUI to collect user inputs for clean_artifacts().
% ASR stands for artifact subspace reconstruction.
% To disable method(s), enter -1.
% Usage:
% >> EEG = pop_clean_rawdata(EEG);
%
% see also: clean_artifacts
% Author: Makoto Miyakoshi and Ch... |
c5f9e7deccd333d849901c0b28cf252d980e633dde73cc4c86fdc2cf2969ff70 | MATLAB | 10,976 | 267 | %% Nat Comms Ictogenesis Figure 4
clear
load('20230127_PooledData.mat');
EXP5HZ = "B30_P5F5_";
EXP10HZ = "B30_P5F10_";
EXP20HZ = "B30_P5F20_";
sz = struct();
sz.stim5Hz = startsWith(sztable.ExpProtocol, EXP5HZ);
sz.stim10Hz = startsWith(sztable.ExpProtocol, EXP10HZ);
sz.stim20Hz = startsWith... |
defdd3cca198f2999cf42fa8abbb5e31a99bf5099fa0249df0c7a3b3f6fed4bf | MATLAB | 10,984 | 254 | function obj = FitAdvGMM(positions, weight, k, varargin)
%FITGMDIST Fit a Gaussian mixture distribution to data.
% GM = FITGMDIST(X,K) fits a Gaussian mixture distribution with K
% components to the data in X. X is an N-by-D matrix. Rows of X
% correspond to observations; columns correspond to variables. FITGMD... |
daeff74af45a3999189466a24e2f5824ce0daa159c13b88026f1f34b6a74f775 | MATLAB | 11,010 | 420 | function zef = zef_DBS_strip_struct_window(zef)
h1 = figure(...
'PaperUnits',get(0,'defaultfigurePaperUnits'),...
'Units','normalized',...
'Position',[0.43 0.52 0.20 0.45],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'IntegerHandle','off',...
'Colormap',[0 0 0.5625;0 0 0.625;... |
615cefb0211c8fe0378dff34f37bd825d548914d48c416f0fde2fd893b6d594a | MATLAB | 11,089 | 251 | function zef_nse_plot_graph(zef, nse_field)
if nargin == 0
zef = evalin('base','zef');
nse_field = evalin('base','zef.nse_field');
end
if zef.nse_field.graph_type == 1
roi_ind = zef_nse_roi_ind(zef, nse_field);
plot_vec = zeros(length(nse_field.bp_vessels),1);
for i = 1 : length(nse_field.bp_vesse... |
aac6a40bcaeef87daa12576587ab7c00089a7f4e9b6ea7b804b55e347b518db9 | MATLAB | 11,101 | 232 | function [outdata,outstate] = asr_process(data,srate,state,windowlen,lookahead,stepsize,maxdims,maxmem,usegpu)
% Processing function for the Artifact Subspace Reconstruction (ASR) method.
% [Data,State] = asr_process(Data,SamplingRate,State,WindowLength,LookAhead,StepSize,MaxDimensions,MaxMemory,UseGPU)
%
% This fu... |
beb7cc3ca1f903f52e22f279117bad51ec3a4d8404e459c99b27c6c69153ecdb | MATLAB | 11,143 | 346 | classdef MNEInverter < inverse.CommonInverseParameters & handle
%
% MNEInverter
%
% A class which defines the properties needed by the Minumum Norm Estimate (MNE)
% inversion method, and the method itself.
%
properties
%
% Parameter for prior variance selection
%
... |
7ec1d76f474f7d2f1631cb910cbf11ef6b68feb3cfb1050e12849b31165be429 | MATLAB | 11,165 | 225 | %% 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... |
96de1a1361e028902172d7d7c261cb9835517c68d84998c8834b3895e1a77ea5 | MATLAB | 11,187 | 230 | function hmm = updateOmega(hmm,Gamma,Gammasum,residuals,T,XX,XXGXX,XW,Tfactor)
is_gaussian = hmm.train.order == 0; % true if Gaussian observation model is being used
K = length(hmm.state); ndim = hmm.train.ndim;
S = hmm.train.S==1; regressed = sum(S,1)>0;
if nargin<9, Tfactor = 1; end
Tres = sum(T) - length(T)*hmm.tr... |
bad237e9183ada71888ddc6f971e112a7ae0bb2926f36d446e9b5f4ca5e81a78 | MATLAB | 11,196 | 261 | function bsliang_TMS_main(ambtag,is_getshamrepvals)
% clear all
% close all
% ambtag='ambiguous';
if isequal(ambtag,'unambiguous')
AMB=[1 5];
elseif isequal(ambtag,'halfambiguous')
AMB=[2 4];
elseif isequal(ambtag,'ambiguous')
AMB=3;
end
%... |
f87287222a3f93940f4bbfdd22ec31b16c74e9ede4e36ee20da55514a6ade102 | MATLAB | 11,232 | 270 | function zef_PlotGMModel
%This function plots the point clouds created by the GMM tool.
t = evalin('caller','f_ind');
parameters = evalin('base','zef.GMM.parameters.Values');
num_of_vars2 = evalin('base','zef.GMM.meta{2}');
m_size = str2num(parameters{8});
m_width = str2num(parameters{9});
m_sym = parameters{7};
s_le... |
6985bcbab7da3c3dc2d1b4d57a8a83f8b740dbef9d6a06df5924efd02600c85c | MATLAB | 11,264 | 326 | % TD custard
% quick version
function custardOutput = TDcustard2 (n, signal, sigthresh, minAmp, minWidth, tXrise, noFig, detailFlag, silent )
% n, number of points to test for a change
% signal, 1xnpnts
% sigthresh, significance to call an up
% minAmp, to be a peak the relative amplitude needs to exceed this
%detailFla... |
38cf39ea53756763f6caab77e7507c2f9d79582d6e9b9093a2d9498789c66da9 | MATLAB | 11,265 | 300 | function [sp_fit_group,sp_profiles,sp_fit] = spectdecompose(sp_fit,options,chan)
%
% From a multitaper or MAR estimation of the states spectra (per subject),
% it factorises the spectral information (which is given by frequency bin)
% into a set of spectral components (which are much fewer than the
% frequency bins),... |
db08764ef7992de360c4761a4214a793a8059e4d01e15b20f4fb2e1eafe7764d | MATLAB | 11,280 | 273 | function zef_PlotGMModel
%This function plots the point clouds created by the GMM tool.
h = evalin('caller','h_axes_image');
%axes(h);
t = evalin('caller','f_ind');
parameters = evalin('base','zef.GMM.parameters.Values');
num_of_vars2 = evalin('base','zef.GMM.meta{2}');
m_size = str2num(parameters{8});
m_width = str... |
96a95db8304e30d77a55b7086c9a1836dd0c77ea48f50b5d77df73afd973ac8a | MATLAB | 11,342 | 305 | % SYNOPSIS
% --------
%
% The @SpikeGL class is a MATLAB object with methods to access the
% SpikeGLX program via TCP/IP. SpikeGLX and MATLAB can run on the
% same machine (via loopback socket address 127.0.0.1 and port 4142)
% or across a network.
%
% This class provides extensive control over a running SpikeGLX proce... |
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