sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
471ed40575f6236adf5218b50fbf0f20681a9faacb7e01986f0e0aa81488d213 | MATLAB | 3,698 | 116 | function obj = preprocess_orthogonalize(obj,display)
% Orthogonalize time courses
% Colclough et al (2015), NeuroImage 117:439-448
% Input:
% - obj.data: Original data. mobj.datan, where m is number of samples, n number of ROIs
% - display: Display progress. Can be:
% 'none', disp... |
042916f982729f2106424f7227262470a1bdf6d11c3b8d4249284e9fc293288f | MATLAB | 3,700 | 97 |
%--------------------------------------------------------------------------------
% fig2_simulated_response.m
%
% This analysis is included in
% Experimental validation of the free-energy principle with in vitro neural networks
% Takuya Isomura, Kiyoshi Kotani, Yasuhiko Jimbo, Karl Friston
%
% Copyright (C) 2022 Takuy... |
73551947c1737450023ca60bd8e9dc7fbf2caa554533e816d0d02e518b324dd0 | MATLAB | 3,700 | 117 | function d_EEGheader
% function to create a generic meta-data file for an EEG experiment
% contains electrode positions and trigger explanations
% can contain other useful study information
% DHB 30/9/18
load Waveguard.mat;
outputfile = 'headerfile.csv'; % generate a filename for the output based on the ... |
5ed77aa4d73627ed6ed83bc90ae9579179ae6b7075903cfb73977f0c6f83e566 | MATLAB | 3,705 | 136 | function relative_resolution_vec = zef_find_relative_resolution(zef)
[active_compartments, source_compartments] = zef_get_active_compartments(zef);
source_compartments = find(ismember(active_compartments,source_compartments));
relative_resolution_vec = ones(size(active_compartments));
if zef.refinement_on
if zef.r... |
60148affd9d8db1f299c619c1e1e6b04d01951de6ad2add42296c0610339ebf9 | MATLAB | 3,706 | 212 | function y = mls_mark(n,flag,RandSeed)
%y = mls(n,{flag});
%
%Generates a Maximum Length Sequence of n bits by utilizing a
%linear feedback shift register with an XOR gate on the tap bits
%
%Function can accept bit lengths of between 2 and 24
%
%y is a vector of 1's & -1's that is (2^n)-1 in length.
%
%o... |
19f0ede5dcc02f2f4bf37da6179ce6beed9e0a4b07b894610521150c7c11f45e | MATLAB | 3,707 | 99 | function [acc_chance,p_cluster] = group_accuracy_significance(acc_true,acc_perms,nPerms,pthresh)
% This function implements the cluster significance tests as outlined by
% Stelzer 2013; unlike int he original publication this is inferred over
% time rather than space. This allows for inference of temporal clusters in
%... |
a214571329a1ae9db6cb99818eeec3503a790cd1eb4bb05639bee9743306cd88 | MATLAB | 3,708 | 86 | function [cellEpochList,sEpochs] = ETC_GenEpochList(ptrEpochList,sEpochs,vecPupilTime,sPupil)
%vecPupilFixedCenterX(intBegin:intEnd) = sEpoch.CenterX;
%vecPupilFixedCenterY(intBegin:intEnd) = sEpoch.CenterY;
%vecPupilFixedRadius(intBegin:intEnd) = sEpoch.Radius;
%vecPupilFixedBlinks(intBegin:intEnd) = sEpoch.Blinks... |
fd8e48fd5ba9e3da17ddf6b303703cba938d468573201c6eac845706e50f3491 | MATLAB | 3,708 | 102 | function [psderr,coherr,pcoherr,pdcerr,sdphase] = spectrerr(psdc,pdcc,coh,pcoh,pdc,options,mar)
if nargin<7, mar = 0; end
coherr = []; pcoherr = []; pdcerr = []; sdphase = [];
Nf = options.Nf;
ndim = size(psdc,2);
jksamples = size(psdc,4);
psd = mean(psdc,4);
SA = zeros(Nf,ndim,ndim,jksamples);
if options.to_do(1)==1... |
b29966c848c24247e6c829c053f53c329f195f52ab2ba0313a32df60a0f093f8 | MATLAB | 3,717 | 99 | function r_estimated = chradiiphcode(varargin)
%CHRADIIPHCODE Estimate circle radius for Circular Hough Transform using the Phase-Coding method
% R_ESTIMATED = CHRADIIPHCODE(CENTERS, H, R) takes a two-column array CENTERS,
% which contains the x (first column) and y (second column) coordinates
% of the center loc... |
2c9d81e3596000d299056a5ae771598b90efc9aff18b2006671cb930035b0989 | MATLAB | 3,721 | 93 | function [random_ensemble_performance, ensemble_nodes] = compare_random_ensembles(params, node_performance, best_model)
data = params.data;
udf = params.udf;
num_controls=params.num_controls;
merge=1;
par_proc=params.par_proc;
[~, num_udf] = size(udf);
true_label = udf';
perf_curve_crit... |
0019aebd54ae00262d70e577a8de174d965c4fa32cfc40cac3c5a0500f231dc3 | MATLAB | 3,723 | 131 | zef.ES_opt_solver_list = {'Matlab','SDPT3','SeDuMi','MOSEK','Gurobi'};
zef.ES_opt_method_list = {'L1L1 optimization','L1L2 optimization','Least squares optimization','Backpropagation','L2L2 optimization'};
zef.ES_opt_algorithm_list = {'interior-point','interior-point-legacy','dual-simplex','primal-sim... |
b61023620d0bcb6a430ddfc0b829359817ae21f740ddf860a0d5bb4f244859b5 | MATLAB | 3,732 | 158 | function M = spherecomplexfactory(n, m)
% Returns a manifold struct to optimize over unit-norm complex matrices.
%
% function M = spherecomplexfactory(n)
% function M = spherecomplexfactory(n, m)
%
% Manifold of n-by-m complex matrices of unit Frobenius norm.
% By default, m = 1, which corresponds to the unit sphere in... |
e386f2a26ce6c12c8338f48af45c1b12060eb5430716fdc245f19c5aab5d828b | MATLAB | 3,735 | 100 | function layout = layout_creator(varargin) ;
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
narginchk(0,2)
switch nargin
case 0
microstate.functions.layout_creator_gui ; % call the GUI
case 1
if ~strcmpi(varargin{1},'gui')
error("Une... |
b184f0c36a06206436bce49c1da1fd71e1775924751d47f95afdec2f2724019a | MATLAB | 3,755 | 118 | function [hPanelD,sHandles] = ETP_genDetectPanel(ptrMainGUI,vecLocation,strName,sET)
%ETP_genQuadSliders Generates quad sliders
% [hPanelD,hGain,hGamma,hTempAvg,hBlur,hMinRad,hReflLum,hPupLum] = ETP_genDetectPanel(ptrMainGUI,vecLocation,'Detection settings');
%% get parameters
%get defaults & overwrite with sup... |
0297d6a95d374b7bf22e24f25869b5adf8431c08dd3c1059b7df09d9aeec0a4a | MATLAB | 3,756 | 151 | function B = map(fun,A,varargin)
%MAP Apply a given function to the elements, columns or rows of an array (more versatile than Matlab arrayfun)
%---
% function B = map(fun,A[,'columns|rows'][,'array|cell|arraydirect'][,errorval])
% function B = map(A,fun,...)
%---
% map function 'fun' to elements [default] / columns / ... |
8645ae10ad699bba91a0ab14d85ce1ae01ad93b221061869018cc593d52f60de | MATLAB | 3,761 | 133 | function [p,confusionmat,nets] = networks_plv(obj,frq,keepstates,epochlength,orthogonalize,Nperms) ;
% Calculate microstate segmented functional connectivity
% check we have GFP, maps, and labels
if isempty(obj.data)
error('Data is required to calculate microstate networks')
end
if isem... |
f9eedc42c4420fb64e8308d791924f99aba18b3e0b74a36a126a82b8f20ae118 | MATLAB | 3,764 | 108 | function f_DA_pcn_struct(app)
UDF_NUM = app.Stimulus_PCN.Value;
cla(app.PC2);
app.PC2.XAxis.LineWidth=1.5;
app.PC2.YAxis.LineWidth=1.5;
app.PC2.XTick=[];
app.PC2.XTickLabel=[];
app.PC2.XLabel.String=[];
app.PC2.YLabel.String=[];
app.PC2.YTick=[];
app.PC2.YTickLabel=[];
app.P... |
4c772545595e76866ef18efd23d45a770aca30c934c9db486d677c1d349073be | MATLAB | 3,766 | 87 |
%--------------------------------------------------------------------------------
% fig2_empirical_response.m
%
% This analysis is included in
% Experimental validation of the free-energy principle with in vitro neural networks
% Takuya Isomura, Kiyoshi Kotani, Yasuhiko Jimbo, Karl Friston
%
% Copyright (C) 2022 Takuy... |
0f14451aeb8cbd2f2f704395c02f2172064e948b40364d49ae12ff19cd6192a6 | MATLAB | 3,778 | 102 | function M = euclideansparsefactory(A)
% Returns a manifold struct to optimize over real matrices with given sparsity pattern.
%
% function M = euclideansparsefactory(A)
%
% Returns M, a structure describing the Euclidean space of real matrices
% with a fixed sparsity pattern. This linear manifold is equipped with
% th... |
0fdb260a4444efc6627e8f17a25dfec008a1571be829352612621e2fc60600af | MATLAB | 3,779 | 76 | function hmm = updateAlpha(hmm)
K = length(hmm.state); ndim = hmm.train.ndim;
if isfield(hmm.train,'B'), Q = size(hmm.train.B,2);
else Q = ndim; end
setstateoptions;
for k=1:K
if ~hmm.train.active(k), continue; end
if isempty(orders) || ~isempty(train.prior), continue; end
hmm.state(k).alpha.Gam_shape = h... |
7eceef050520743a139e0b059bd1ddd232ed15a2f1793748d7e2aaeefc05b7a8 | MATLAB | 3,779 | 110 | function [n, xout] = histx(varargin)
% A wrapper for hist that picks the "ideal" number of bins to use if
% unspecified.
%
% N = HISTX(Y) bins the elements of Y into M equally spaced containers and
% returns the number of elements in each container. If Y is a matrix, HIST
% works down the columns. The value of ... |
2cb3943e87da2aa8220da2a4e3ac6c29b957d8eacdae7b8925ffeb95e90e33bf | MATLAB | 3,784 | 170 | function options = checkspelling (options)
potential_options = {
'K';...
'onpower';...
'leida';...
'order';...
'maxorder';...
'covtype';...
'zeromean';...
'embeddedlags';...
'pca';...
'pca_spatial';...
'lowrank';...
'varimax';...
'maxFOth'; ...
'pcamar';...
... |
a779a91ef96cda647d98b1d2fb772c80102ada957bbd943c27711e5d1b7292ea | MATLAB | 3,790 | 79 | function [omitted_voxel_IDs_list] = extract_omitted_voxel_IDs(subject,dataset)
% The purpose of this script is to come up with a list of voxel IDs that
% are being skipped over in the voxel-based structural connectivity
% matrices, and then use that list to remove those rows from the
% functional signal timeseries that... |
616a5fbdbe17a5f00537b4ace6ee28ef03e94ff40bb02202abe3dd7a6677b116 | MATLAB | 3,797 | 114 | function sOut = getClusterQuality(vecSpikeTimes,boolMakePlots)
%getClusterQuality Calculates ISI violation index and non-stationarity index
%syntax: sOut = getClusterQuality(vecSpikeTimes,boolMakePlots)
% input:
% - vecSpikes; spike times
% - boolMakePlots; set to 0 to suppress plotting
%
%Version history:
%1.0... |
2b4fb63998e5d936baacc8b8bc32a84d9158009f0852dc4f19f931a211723bf5 | MATLAB | 3,803 | 121 | % calculate dF over F0, checks minBarF for <= 0
function [dFoverF0,minBF] = deltaFoverFzeroEmbedded( stack, t1, t2, t4 ) %, minminBF )
% bar F "smoothing"
%disp('starting BarFofT');
BarF = BarFofTse;
function BarF = BarFofTse %( stack, t1 )%; % s version uses single precision
%t1 = 100;
%bFofT = ... |
30f88370d0b43d9a4a5535a28b3aff5e8d2f482eeaa4336208e06ea665dfcd4b | MATLAB | 3,843 | 78 | %This is the startup script for MUSIC app. One must add this as launch
%script to zeffiro_plugins file:
%MUSIC, inverse_tools, MUSIC_app_start
zef.MUSIC = MUSIC_app;
%_ Names of methods that are included in app _
zef_MUSIC_names = {'Source projection',
'Noise out-projection'
};
zef.MUSIC.MUSIC_type.Items = z... |
aa9863375fad5ded440afd094afb38f4e06856bd3fdc21b103449043eb290f34 | MATLAB | 3,850 | 108 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef_arrange_windows(varargin)
arrange_function = 'tile';
arrange_target = 'windows';
arrange_mode = 'on-screen';
if not(isempty(varargin))
arrange_function = varargin{1};
if length(... |
c69829fe37d6d0d26fd7003d30896766b0cf6e832e5afbdab9fce753c3412b49 | MATLAB | 3,851 | 88 | function [ET,labels] = segmentationLeaflet(MRK_stream, MOUSE_stream, MOUSE_position, ET_stream)
IDX = find(contains(MRK_stream.time_series,'EOE'));
MRK_stream.time_series=MRK_stream.time_series(1:IDX);
MRK_stream.time_stamps=MRK_stream.time_stamps(1:IDX);
Event_List = unique(MRK_stream.time_series);
my_segments{6,24}=... |
a12537ed1029298d28b1c593fc4e396a27f0a9122544f9b5106ed3abf3fdba7e | MATLAB | 3,857 | 106 | %Copyright © 2018, Sampsa Pursiainen
%[zef.rho,zef.brain_ind] = zef_rho([]);
tic;
if zef.source_direction_mode == 1
zef.lf_param.direction_mode = 'cartesian';
end
if zef.source_direction_mode == 2
zef.lf_param.direction_mode = 'normal';
end
if zef.source_direction_mode == 3
zef.lf_param.direction_mode = 'f... |
27b99481e9ae60bac116492e6d658bb0533abcc978e993f51747feae9d5b39f9 | MATLAB | 3,862 | 161 | function overlap = find_ovelap_window(...
data, Data, spike_state, print_mode)
% find overlap window for post processing
% overlap = find_ovelap_window(data, Data, spike_state)
%
% overlap.twin{n} = overlap time index
% in n-th overlap window
% overlap.nwin{n} = overlap window index
... |
f36b035295be6d95b7830d2c4fb195f2377ba66af7c4bc45cdd313f6cf7ae08a | MATLAB | 3,866 | 100 | classdef AbstractFW < handle
% AbstractFW
% Base class for Frank-Wolfe algorithms.
% Handles outer loop and convergence checks.
properties
algo_name
objective
duality_gap
opts
total_iter_time
end
methods (Abstract)
% ... |
68e9c2bfb1534ed38dbff9d47746ecdbad910d3c8f36dcd3d5174a68a2dfb24c | MATLAB | 3,872 | 121 | % Generates data for Table 1 in paper
function copytest
addpath(genpath('../'))
UIv = [];
Errorv = [];
Elapased_Timev = [];
c=0;
% ----------------------------------------
% High dimensional COPY: UI(S;Y\Z) = I(S;Y)
for ny=2:14
c = c+1
nz=ny;
ns=ny*nz;
... |
386c09e1a47d379ded45f042f73b0716327e47e44982ece0fcf1c481b036167c | MATLAB | 3,873 | 83 | function [ overcomplete_params ] = samples_to_overcomplete(samples, adjacency_matrix)
%CONVERT_SAMPLES_TO_OVERCOMPLETE This functions uses the graph structure
%and the samples in its simple format (one sample per row, one variable per
%column), and converts the samples to the overcomplete parametrization
%necessary to... |
7a070cb28e2ced9da5f09fad6253871f588af5fc311f24b932e5a7cab255f5f0 | MATLAB | 3,873 | 132 | /*
Magma code to randomly generate 200000 weights corresponding to terminal Fano
toric varieties of Picard rank two, in dimensions 2..10. The resulting weights
are written to the files "rank_2_dim_N.txt", where N is the dimension.
*/
// Reorder the weights wts so that the columns are cyclically ordered.
function cycli... |
7d84365955fd39c1fd69a4504b4391967fdebe4a796d3782e61bcf84cff3d9eb | MATLAB | 3,878 | 120 | function cost = getCost(problem, x, storedb, key)
% Computes the cost function at x.
%
% function cost = getCost(problem, x)
% function cost = getCost(problem, x, storedb)
% function cost = getCost(problem, x, storedb, key)
%
% Returns the value at x of the cost function described in the problem
% structure.
%
% stored... |
d9364df14aed0babec942c0635ae89afa54430d2c7773d32ffb48a51d1eb8305 | MATLAB | 3,885 | 177 | function [post_spike, ypred] = post_spike_search(...
data, ypred, Model, parm, plot_mode);
if nargin < 5, plot_mode = 0; end
tau = Model.tau;
a = Model.a; % spike waveform amplitude
b = Model.b; % bias
if isfield(Model,'b0')
b0 = Model.b0; % bias
else
b0 = b;
end
sx = Model.sx; % noise variance
p... |
0399ddee3cba862b8e72ad59e6d0e2d1b0c9ec4f4fa46bed692605b48c409041 | MATLAB | 3,895 | 102 | function ridges_ravines_2vtk_v2(fileridges,fileravines,vtkfile)
% License & disclaimer.
% ------------------------------------------------------------------------------
% Copyright 2019 Dumoncel Jean
% ------------------------------------------------------------------------------
%
% IMPORTANT
% If you use t... |
23e82e1a904d415464b24c6ecf8415bf3dd7365c1c25a14f1425ad753e2047a4 | MATLAB | 3,905 | 90 | % The purpose of this script is to estimate the intracortical myelin content for each
% voxel of the Penn subjects, using the T1w/T2w method
% Requirements:
% 1. The scripts HCP_orig_to_b0.sh and register_T1w_T2w_files_to_b0_HCP.sh have been run.
%
% Output:
% The voxel-based intracortical myelin estimates (within 1 ... |
2c915778f260f30057a890c6080172d94b6aac2d3fcfe6acd2bdf7d7ecfab4b2 | MATLAB | 3,907 | 137 | %% Copyright © 2025- Joonas Lahtinen
function [reconstruction, self] = smoother(self, z_inverse, L)
%
% smoother
%
% Computes the desired smoother for Kalman filter solution
%
% Inputs:
%
% - self
%
% An instance of KalmanInverter with the method-specific parameters.
%
... |
f3575101e79adbd9d209e8bd2fffda911da1aad49e6ffc5b00fc628b14d770bc | MATLAB | 3,916 | 108 | %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;
%_ Initial values _
if isfield(zef,'inv_snr')
zef.KF.inv_snr.Value = num2str(zef.inv_snr);
else
zef.KF.inv_snr.Value = '30... |
c9415ca1786acea965b9e0528a143ce619dad7d2854da119e72e098f8944219c | MATLAB | 3,917 | 133 | function params = initialize_params(params)
params.G_K = 25;
params.G_Na = 30;
G_L = 0.05;
params.C = 1.0;
params.g_l_k = G_L;
params.g_l_na = 0.35*G_L; % 0.0175
params.g_l_cl = G_L;
params.dslp =0.33; % K diffusion rate
params.gmag=8; % this is G_glia in the eqs--- glia uptake strength of potassium
params.ga... |
0b0b2061473a8d48798c9d4d1473ca76fe23e32ae810e6103331c08da93225cf | MATLAB | 3,918 | 103 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if not(isfield(zef,'exp_multires_dec'));
zef.exp_multires_dec = [];
end;
if not(isfield(zef,'exp_multires_n_decompositions'));
zef.exp_multires_n_decompositions = [20];
end;
if not(isfield(zef,... |
41ca6c27753056aca43360b8452a872f806970cfe7373fc0187c856605514f49 | MATLAB | 3,926 | 71 | %This is script for opening advanced GMM plot options.
zef.GMM_PlotOpt = GMMclustering_PlotOpt_app;
%Set position besides GMM app
zef.GMM_PlotOpt.UIFigure.Position(2) = zef.GMMclustering.UIFigure.Position(2);
zef_temp_screen_size = get(0, 'ScreenSize');
if zef.GMMclustering.UIFigure.Position(3)+zef.GMM_PlotOpt.UIFigu... |
d9dba562a06cd315fbcf7f0a46cfb6728747eb2029ce351c2422d78bacd230a3 | MATLAB | 3,927 | 84 | % The purpose of this script is to compute the Hurst exponent of all of the
% 100 unrelated HCP subjects' BOLD timeseries—-as a proxy of their
% excitation-inhibition ratio--using the nonfractal toolbox:
% https://github.com/wonsang/nonfractal
% described in the paper:
% https://www.ncbi.nlm.nih.gov/pmc/articles/PM... |
e28fab23230c8fd5433f545c6ab4568bd06749414ab2b7bef443063b37c5606d | MATLAB | 3,939 | 104 | function checkmanifold(M)
% Run a collection of tests on a manifold obtained from a manopt factory
%
% function checkmanifold(M)
%
% M should be a manifold structure obtained from a Manopt factory. This
% tool runs a collection of tests on M to verify (to some extent) that M is
% indeed a valid description of a Rieman... |
00d512cd2adf0fc9db8ecfb41c950494fccd6942eac8339d0f8f406f27f6ea8e | MATLAB | 3,941 | 94 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef = zef_update_fig_details(zef)
if nargin == 0
zef = evalin('base','zef');
end
zef.aux_field = cell(0);
zef_j = 0;
if isfield(zef,[zef.current_sensors '_points'])
if size(eval(['ze... |
457b42ee7ce7e5f1cbd19b6e4eb1d9b200c5acbd3933dd22c1f668a4897eb732 | MATLAB | 3,953 | 140 | function A = zef_stiffness_matrix(nodes, tetrahedra, volume, tensor)
% The stiffness matrix 𝐴 of a discretized scalar function 𝑢ₕ = ∑ᵢ𝑧ᵢψᵢ, with
% each 𝑧ᵢ being a coordinate and ψᵢ a linear basis function, is defined by
%
% 𝐴[i,j] = ∫[Ω] ∇ψⱼ ⋅ (𝑇∇ψᵢ) d𝑉 ,
%
% where Ω is the entire domain and d𝑉 is a finite v... |
ec304423a0af0bb1756ba840753a2497d0683addeafbdf5c453da02ab26209e3 | MATLAB | 3,953 | 130 | % Code used in Vidaurre et al. (2016) NeuroImage
%
% 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 THE MATLAB PATHS AND FILE NAMES
mydir = '/home/diego... |
b595460ff1e7c0d8f04d9a20d7e5aa1d3aaa3aa9b22087d97d0f8d47988542b2 | MATLAB | 3,955 | 103 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if not(isfield(zef,'exp_multires_dec'));
zef.exp_multires_dec = [];
end;
if not(isfield(zef,'exp_multires_n_decompositions'));
zef.exp_multires_n_decompositions = [20];
end;
if not(isfield(zef,... |
96ce1fe9307377c461bfbdc1f6db367bf091f7cb3c78a49f51a4d31f3c6e6f90 | MATLAB | 3,960 | 92 | function cellPaths = getSubDirs(strMasterPath,intMaxDepth,cellExcludePathName)
%getSubDirs Returns cell array of target directory and all its subfolders
% Syntax: cellPaths = getSubDirs(strMasterPath,intMaxDepth,strExcludePathName)
%
%Default search depth (intMaxDepth) is set at [2] subfolders
%Default folder ex... |
48e251aa2ccf50bc1baad46321adb90c0e1331c40bd097c30a6d8c746bf35828 | MATLAB | 3,964 | 136 | function [dblStartT,intFlagOut,vecTotErr] = SyncEvents(vecRefT,vecSignalT,boolUsePath,boolVerbose)
%SyncEvents Syncs events
%[dblStartT,intFlagOut,vecTotErr] = SyncEvents(vecRefT,vecSignalT,boolVerbose)
%
%inputs:
%vecRefT: [1 x n] timestamp vector
%vecSignalT: [1 x p] timestamp vector where p>n
%
%outputs:
%v... |
685f30449da5723cf855a2c61beeb72c7c1a1e67707ffccd0534d18494598303 | MATLAB | 3,966 | 89 | function [P,Pi] = getMaskedTransProbMats (data,T,hmm,Masks,Gamma,Xi)
% Obtain local Markov transitive probability matrices (LMTPM) for each of the
% masks specified by the variable masks (see description of parameters).
% The matrices include state persistency probabilities
% (see getTransProbs.m to obtain just the t... |
ef79dd67b743fd930b7343a09f24a728252943a5bb6c7f3957409f094663916a | MATLAB | 3,967 | 96 |
%--------------------------------------------------------------------------------
% 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
%---------------... |
8977e332b215b062d24a8c307ea68eba5b740dcc487f2a31246ff1a0869020e6 | MATLAB | 3,974 | 103 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
parameters;
if system_setting_index == 1
loop_constant = 2;
else
loop_constant = 1;
end
for k = 1 : loop_constant*n_r
if exist(['./data_' int2str(folder_ind) '/point_' int2str(k) '... |
db8aed854fb8d12770b878bedc2ff7ecdb724874f8156068e2ebe3275c71ba1a | MATLAB | 3,974 | 128 | function [FO,ntrials] = getFractionalOccupancy (Gamma,T,options,dim,alignment)
%
% Computes the fractional occupancy
% - across trials if dim==1 (i.e. FO is time by no.states)
% This is indicating how the fractional occupancy evolves as a function
% of time across trials.
% - across time if dim==2 (i.e. FO is no... |
b4641f4c2bd99a5d174981f5b3d6df45b4c78698f0d57b71e67f3b314949820e | MATLAB | 3,980 | 130 | function [hmm,Gamma,vpath] = hmmdual(data,T,hmm,Gamma,Xi,residuals)
%
% Dual estimation of the HMM, first Gamma and then the HMM structure
%
% INPUTS:
%
% data observations - a struct with X (time series) and C (classes; optional)
% T Number of time points for each time series
% hmm hmm s... |
ad8f1ed4de156cd6e7bff9f7fd080f010e33576a1733c15bf2ae14bd89f41fe3 | MATLAB | 3,990 | 87 | %% 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... |
212638ca0d814c5c44d6116b9e092af23a438d621a05bf41bf35a571c9379f44 | MATLAB | 3,999 | 94 | function plot_pcn_scatter(app)
udf = app.Stimulus_PCN.Value;
cla(app.pattern_completion_scatter);
app.pattern_completion_scatter.NextPlot='replacechildren';
% need
num_original_neurons = size(app.params.data,2);
pcn_neurons = app.pattern_completion_nodes{udf};
node_scores = app.node_scores(1:num_original_neurons, :)... |
f4f9479060917085e75c01dab762162441359432f388233aaabff8b9b3334f6e | MATLAB | 3,999 | 65 |
zef.LeadFieldProcessingTool.combineNew=true;
zef.LeadFieldProcessingTool.combinePoints=zef.LeadFieldProcessingTool.app.NoisestartSpinner.Value:zef.LeadFieldProcessingTool.app.NoiseendSpinner.Value;
zef.LeadFieldProcessingTool.combineData=[];
for zef_LeadFieldProcessingTool_index_combine=1:zef.LeadFieldProcessingTool.b... |
5f35a1e5c19602a8f153a9a3545d6015e47eaafbfaaab09e84fb4752046d829a | MATLAB | 4,004 | 155 | function out = check_mar_spectra( data, T, order, sample_rate, to_plot )
%%function check_mar_spectra( data, T, order, sample_rate )
%
% Function to explore the static fit for a MAR model as a sanity check
% before fitting a HMM-MAR.
%
%
% INPUT
%
% data observations; a matrix of dimension (nsamples x nchannel... |
5947d713541458d3096b268c0b5528aca8b0628a3b9b9307db5a6cf2e7aafa4f | MATLAB | 4,007 | 141 | function lifetimes = getStateLifeTimes (Gamma,T,options,threshold,threshold_Gamma,do_concat)
% Computes the state life times for the state time courses, in number of time points
%
% Gamma can be the probabilistic state time courses (time by states),
% which can contain the probability of all states or a subset of th... |
0086ee8a4cd6c8fc4ce1c2547c527b5952f3dfb181e49cf459190fe9ae4110f4 | MATLAB | 4,019 | 123 | function spike_info = spike_overlap_info(...
data, overlap, print_mode)
% spike_information for overlap window
% spike_info = spike_overlap_info(data, overlap)
%
% --- spike info for overlap window
% spike_info.spike_num(n) = spike number of n-th overlap window
% spike_info.spike_time{n} = spike onset ti... |
6d3d355a5f9017ba6c6a0cdf5ef30e083cf42891db44876e461532cedc2b5679 | MATLAB | 4,019 | 79 | function plot_ensemble_graph_structure_style_2(app)
cla(app.ensemble_graph);
app.ensemble_graph.NextPlot = 'replacechildren';
% 1
udf_id = app.StimulusEV.Value;
% 1
rois = app.rois;
num_rois = size(rois.xpix, 1);
best_model = app.best_model;
edge_mat = best_model.structure(1:length(rois.xpix), 1:length(rois.xpix));
... |
3df6ad626e9aa41f4773255b44702093a440cecbd5be536d37524d52fa0ffc74 | MATLAB | 4,024 | 76 | %This is the startup script for dipole_app app. One must add this as launch
%script to zeffiro_plugins file:
%dipoleScan, inverse_tools, zef_dipole_start
function zef = zef_dipole_window(zef)
zef.dipole_app = dipole_app;
appName='dipole_app';
zef.dipole_app.ZEFFIROInterfaceDipoleScanUIFigure.Name = 'ZEFFIRO Interface... |
96e6e45c3b31f7308dbbe23fefe0e37e6ac371d8fe10498a708ccb4cd32df328 | MATLAB | 4,031 | 149 | 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 instance of CSMInverter with the metho... |
6a8035bfdf6b23ff0ff1e99436b7c48db38e4bc0547514881b4e6ceac806c334 | MATLAB | 4,033 | 124 | function [e_group,e_subj] = explainedvar_PCA(data,T,options)
% Performs preprocessing on the data, performs PCA,
% and returns the explained variance for each PCA component.
% This is useful to inspect the rank of the data and decide the number of
% PC components to use in an informed way
%
% Author: Diego Vidaurre, ... |
f7ac4cea2437f5c012863594714070dae270e3672aad6e33a7e52488171acb40 | MATLAB | 4,036 | 64 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
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_3,'Value'));
zef.smoothing_ste... |
c0f2b85db89dedc710370e5a09e5af71a011c65b6a6bad5ac58e1d6701292017 | MATLAB | 4,039 | 96 | function [sortedLambdasCU, UcovarianceU, err] = covarianceUGaussianNet(C, discreteTime, maximumIterations, forcePowerSeriesForSymmetric, verbose, skipPowerSeriesConvergenceCheck)
%
% Computes the eigenvalues of C, and the projected covariance matrix (U^T \Omega U) for the given network.
%
% Inputs
% - C - connectivity ... |
2e5c2be6dcbc530874c2b28c4311f1a518b60a31bcb3261f4fcd648c209d0b84 | MATLAB | 4,045 | 105 | function [IMAGE,LABEL]=fun_load_smnist_prep_backNoise_pos(train_num,valid_num,test_num,redim,max_Amp,pos_noise)
%% parameter setting
x_dim = 28;
y_dim = 28;
img_total_num = 60000;
train_set_num = train_num;
valid_set_num = valid_num;
test_set_num = test_num;
%% load image
... |
346aaef42ee1340998f2f8c3310eae696b2767ccc4c1d4a52f1886751ab3541c | MATLAB | 4,060 | 138 | function intervals = getStateIntervalTimes (Gamma,T,options,threshold,threshold_Gamma,do_concat)
% Computes the interval times for the state time courses
%
% Gamma can be the probabilistic state time courses (time by states),
% which can contain the probability of all states or a subset of them,
% or the Viterbi... |
85a740dbc2243c718e0123af646d05f8ced2238816bd65c8551635d55328dc9e | MATLAB | 4,060 | 118 | function gradfun = approxgradientFD(problem, options)
% Gradient approx. fnctn handle based on finite differences of the cost.
%
% function gradfun = approxgradientFD(problem)
% function gradfun = approxgradientFD(problem, options)
%
% Input:
%
% A Manopt problem structure (already containing the manifold and enough
% ... |
2226115739f16ac23acb392824bf751fc8603e7cf5574ec36860e2bdf4b43c68 | MATLAB | 4,067 | 124 | function zef_ES_plot_barplot(varargin)
switch nargin
case {0,1}
if nargin == 0
zef = evalin('base','zef');
warning('ZI: No zef were called as an input argument.')
else
zef = varargin{1};
end
try
[sr, sc] = zef_ES_objective_function(zef)... |
70df20004bd9f9e0bb25e599ddd066e4a6378ec354b99007244c2c6d0faffffd | MATLAB | 4,076 | 140 | function varargout = ghostscript(cmd)
%GHOSTSCRIPT Calls a local GhostScript executable with the input command
%
% Example:
% [status result] = ghostscript(cmd)
%
% Attempts to locate a ghostscript executable, finally asking the user to
% specify the directory ghostcript was installed into. The resulting path
% is s... |
b061fd58fbc92ce290dd73fa5fefd0467a179128d330d79a74b1fe61cc21b091 | MATLAB | 4,088 | 84 | function [inmat_s_rm_sp_rlr,inmat_s_rm,inmat_s_rm_sp_rlr_subj,GEN_subj]=bsliang_norm_lr_out(TDATA,inmat,LR_ind,GEN_ind,outTag,is_rmsd,is_norm)
% is_rmsd: ÊÇ·ñÈ¥³ý3SD
% ±ê×¼»¯£¨¡÷TMS=(rTMS-Sham)/Sham£©£¬·Ö×óÓÒÄÔ£¬Êä³öSPSS¸ñʽ
% inmat£º block(4)*turn(3)*subj(197)
% LR_ind£º×óÓÒÄÔindex
% outTag£ºÊä³öÓÃÓÚSPSS·Ö... |
005b1bcb1f5968ec40c922a7a58ed2ed456c417e7dfbe1826c995b027793660b | MATLAB | 4,091 | 145 | function [pdc, dtf] = subrutpdc(S,numIterations,tol)
% obtains approximated pdc and dc from cross-spectral information
Nf = size(S,1); N = size(S,2);
% Wilson factorization
H = wilsonfact(permute(S,[2 3 1]),numIterations,tol);
% Computing the PDC
G = zeros(size(H));
pdc = zeros(size(H));
dtf = zeros(size(H));
for f=1:... |
a09d929bd46c3889b164896c2e583d6313910b4f5f3343e2e65c9c8e57923d66 | MATLAB | 4,098 | 120 | function varargout = spk_autosigma(varargin)
% function psig = spk_autosigma('par'[,presetflag])
% function sigmaest = spk_autosigma(calcium,dt[,psig|presetflag])
%---
% Estimation of the level of noise in the calcium signal.
%
% Input:
% - calcium numerical vector or cell array thereof - calcium signal(s)
% - dt ... |
753f7f7dc26a44986a214e7289373477d47fd56f4fdef5f11f89322d4a75c42b | MATLAB | 4,105 | 101 | function creating_permutations(varargin)
% performs permutation test to find voxels whose correlation to a good
% outcome is statistically significant
p = inputParser;
pathExists = @(x) exist(x,'dir');
positiveInteger = @(x) (mod(x,1)==0 & x >0 );
addRequired(p,'assessmentFolder', path... |
48379132d3042bde7661fed7936739d303002e0e18fdfc3eeddc68cbd7f51d82 | MATLAB | 4,127 | 76 | zef = zef_update_transform(zef);
for zef_i = 1 : length(zef.compartment_tags)
if eval(['zef.' zef.compartment_tags{zef_i} '_on'])
if eval(['isfield(zef,''' zef.compartment_tags{zef_i} '_points_original_surface_mesh'')'])
eval(['zef.' zef.compartment_tags{zef_i} '_points' '= zef.' zef.compartme... |
1c93cef2a7ded24678a2594a7b3641c17c68edd75e6a40c1feccf243436e904e | MATLAB | 4,130 | 93 | function atlas_surfaces = zef_bst_get_atlas_surfaces(zef,atlas_struct,n_inflation_steps,transform_cell,compartment_type, volume_extension_vec)
if nargin < 4
transform_cell = cell(0);
end
if nargin < 5
compartment_type = '';
end
if nargin < 6
volume_extension_vec = zeros(size(atlas_struct.Labels,1),1);
end
atlas_surface... |
0e4e55d1036691f50f7533c08be0c9e95bcfc414e62fb85e80449f59a8008f30 | MATLAB | 4,140 | 139 | function dblError = ETP_FitWrapper(vecX,boolRescale)
%% get labels
global ETP_sLabels;
global sETP;
global ETP_matAllIm;
global ETP_matAllImOrig;
global ETP_Fit;
global sFigETP;
if nargin < 2 || isempty(boolRescale)
boolRescale = true;
end
%% get inputs
if ~boolRescale
vecX = vecX./ETP_Fit.vecOrigX;
... |
2821f9883c60586fd961b1bdf52e61d7592fc36df126e57326a837bc0c3b5334 | MATLAB | 4,150 | 111 | %% script to find rcp and calculate intensity over rcps
% this version of the script relies on knowing the thresholds that you want
% to set. this can easily be figured out with using the original version of
% the script and testing it on some channel images. there is also work
%being done on trying to best optimiz... |
b06294b249ae6c09530168c491dc8e33c36909e8e16abd11fe6566504ae40aee | MATLAB | 4,152 | 125 | function ETP_DetectEdit(hObject,eventdata,strParam)
%get globals
global sETP;
global sFigETP;
%% ensure input conforms to format
sHandles = sFigETP.sHandles;
if exist('strParam','var')
dblNewVal = str2double(sFigETP.sHandles.(strParam).String);
if isempty(dblNewVal) || ~isnumeric(dblNewVal)
dblNewVal =... |
3d7faec3ab07b987b73f040ea3894259be328ff058550b138146d96d631d8ac1 | MATLAB | 4,153 | 108 |
n_intervals = 15;
x_scale = 1.2;
ecc_min = 0;
n_s_p_1 = sqrt(sum(s_p_1.^2,2));
n_s_p_1 = repmat(n_s_p_1',3,1);
n_s_p_1 = n_s_p_1(:);
n_s_p_1 = n_s_p_1/max(n_s_p_1(:));
n_s_p_2 = sqrt(sum(s_p_2.^2,2));
n_s_p_2 = repmat(n_s_p_2',3,1);
n_s_p_2 = n_s_p_2(:);
n_s_p_2 = n_s_p_2/max(n_s_p_2(:));
n_s_p_3 = sqrt(sum(s_p_3.^... |
eb328011432076b63b206dbede0707c13a0cdcac509519cc3531791ccf3f8d01 | MATLAB | 4,168 | 129 | function [UI,Q] = admUIg(Psy, Psz, conf)
% admUIg computes the Unique Information for the marginals P_SY and P_SZ
% Inputs: Psy is a table of size S x Y and Psz is a table of size S x Z
% Outputs: UI is the unique information (natural logarithm) and Q is the
% minimizing distribution, which is a table of size S x Y x Z... |
208eb3ab056f6270ef44d009a75ad3e7fddbc680446be8b63ea18e66b38ac7f9 | MATLAB | 4,169 | 118 | function [samples,ts0,Fs,info] = load_csc(filename,mode,par)
% load_csc imports Neuralynx *.ncs files into Matlab
%% examples:
% [csc,ts,Fs] = load_csc('csc4.Ncs','all');
% [csc,ts,Fs,info] = load_csc('E:\LA04-03\CSC4.Ncs','ts',[4500e6 6500e6]);
%
%% outputs:
% samples: row vector of samples (uVolts)
%... |
2e6ea754eccb9f946c3adbff3f1912a9d58a4213c1a09bb796795ba7d6156ca4 | MATLAB | 4,174 | 107 | n_intervals = 5;
x_scale = 1.5;
ecc_min = 0.95;
n_s_p_1 = sqrt(sum(s_p_1.^2,2));
n_s_p_1 = repmat(n_s_p_1',3,1);
n_s_p_1 = n_s_p_1(:);
n_s_p_1 = n_s_p_1/max(n_s_p_1(:));
n_s_p_2 = sqrt(sum(s_p_2.^2,2));
n_s_p_2 = repmat(n_s_p_2',3,1);
n_s_p_2 = n_s_p_2(:);
n_s_p_2 = n_s_p_2/max(n_s_p_2(:));
n_s_p_3 = sqrt(sum(s_p_3.... |
652207a7b259428efef58db6f513e80de53abdf75dd608d933b0095b12cd262c | MATLAB | 4,175 | 137 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef_switch_color('s_on','pushbutton16','s_points');
if zef.imaging_method==2
zef_switch_color('s_on','pushbutton17','s_directions');
end
zef_switch_color('w_on','pushbutton1','w_points');
zef_col... |
163b8cab69a7e58068ac3782f7ad317acab7e6f0154da3e5310f5440a4bae59d | MATLAB | 4,179 | 188 |
%%
%%
%get the voxel to ras matrix with freeSurfer from orig.mri
%% voxel-to-ras
T=[-0.9995 -0.0280 -0.0112 133.3754
-0.0301 0.9302 0.3657 -142.3206
-0.0002 -0.3659 0.9306 -40.3920
0.0000 0.0000 0.0000 1.0000];
%% voxel-to-ras modified
Trot=[-0.9995 -0.0280 -0.0112 0
-0.03... |
643b35ffacff6a59ea99a386bcbf33ce201d4e714d9565a6bc3ba8f375f4ced6 | MATLAB | 4,184 | 109 | function analytes = analyzeROIs2( ROIdata, roll, minwidth, ...
Pfactor, prcthresh )
%fdataIIR = filter(iir,data);
%fdataIIRff = filtfilt(iir,data);
% P factor factor of 10th percentile rolling SD for prominence threshold
% prcthresh=10;
nFiles = size( ROIdata, 2 );
for iFile = 1 : nFiles
name = ROIdata(iFile)... |
9742f857cd1c377a268256f3097feaf30321bfc839a4c0c46f4edc032aaa9fde | MATLAB | 4,198 | 69 |
zef.LeadFieldProcessingTool.combineNew=true;
zef.LeadFieldProcessingTool.combinePoints=zef.LeadFieldProcessingTool.app.NoisestartSpinner.Value:zef.LeadFieldProcessingTool.app.NoiseendSpinner.Value;
zef.LeadFieldProcessingTool.combineData=[];
for zef_LeadFieldProcessingTool_index_combine=1:zef.LeadFieldProcessingTool.b... |
bd41dc5ee6686264a8ec855cbb3df3511bc99f6d46fad0ae7f76294c97f4d94a | MATLAB | 4,227 | 121 | function sFiles = ETO_CompileVideoLibrary(strMasterPath,cellExt,ptrText)
%% compile library
sFiles = [];
for intExt=1:numel(cellExt)
filelist = dir(fullfile(strMasterPath, '**',['*.' cellExt{intExt}]));
sFiles = [sFiles,filelist];
end
%remove mini vids
if ~all(contains({sFiles.name},'MiniVid'))
sFiles(con... |
c387bd8acf2991e0c9cc6646611aa401b1743a7ba2d565117a7d6537238fe497 | MATLAB | 4,234 | 149 | function [W Ms] = bgwedge(M,numiter,numiter2)
%
% Weighted Exhaustive Diagonalization using Gauss itEration (WEDGE)
% with weights selected in order to minimize the Pham's log-likelihood
% criterion
%
% Coded by Petr Tichavsky, March 2008. Updated July 2008. Revised June 2009.
%
% Please cite
%
% P. Tichavsky, A. Yere... |
38b3d848362aa908e723cc2c6decd5587e837a43af354b24a359d1406065168e | MATLAB | 4,241 | 105 | % Compute <sigma^2>, it's low order approximations, and leading eigenvalues
% for continuous-time Ornstein-Uhelnback process through a small-world
% transition.
%
% This recreates the plots in Figure 4 of our paper.
%
%% Linear Sync Toolkit (linsync)
% Copyright (C) 2023 Joseph T. Lizier
% Distributed under GNU General... |
515a7791ba3725ada7c733a7fe15899e08bf751edcd26e299f2cb7cda33ea263 | MATLAB | 4,250 | 116 | function [Gamma,fehist] = hmmmar_init(data,T,options,Sind)
%
% Initialise the hidden Markov chain using HMM-MAR
%
% INPUT
% data observations, a struct with X (time series) and C (classes, optional)
% T length of observation sequence
% options, structure with the training options
% Sind
%
% OUTPUT
% Gam... |
a4277cf6247db60a2bfdd8efc39844b64d25078ad7f12042ca9ee77e6040d3cf | MATLAB | 4,262 | 202 | load('postprandial_somnolence_fEI_ratio_alpha.mat')
load('EEG')
new2old_index=[1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
21
22
23
24
25
26
27
28
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
29
20];
%EEG = pop... |
860cafd34ac59aa599f6b9f176969be6f84c2063c684bc31c0ae598003bca16b | MATLAB | 4,270 | 91 | if isfield(zef,'h_zeffiro_window_main')
if isvalid(zef.h_zeffiro_window_main)
delete(zef.h_zeffiro_window_main)
end
end
set(groot,'defaultFigureVisible','off')
zef_data = zef_segmentation_tool_app_exported;
%zef_data.h_zeffiro_window_main.Visible = zef.use_display;
set(groot,'defaultFigureVisible','on... |
0dc594a0ed8b636d60b5b32d19407a5829bafa738a6bb7ae89085ca04ef23984 | MATLAB | 4,272 | 70 | for zef_i = 1 : length(zef.compartment_tags)
if evalin('base',['zef.' zef.compartment_tags{zef_i} '_on'])
if evalin('base',['isfield(zef,''' zef.compartment_tags{zef_i} '_points_original_surface_mesh'')'])
evalin('base',['zef.' zef.compartment_tags{zef_i} '_points' '= zef.' zef.compartment_tags{... |
b0cc3f06586184dd5d8c54d29ba069fd5499a65af7ac04a03940644ea4e5c752 | MATLAB | 4,273 | 114 | function [responseY,responseR,Gamma,explained_var] = ...
hmmpred(X,T,hmm,Gamma,residuals,actstates,grouping)
%
% Predictive distribution of the response and error on potentially unseen data
% useful for cross-validation routines; that is, this function returns the
% mean predicted signal according to the HMM observ... |
369cf1c4c507e7997e30d97d44b1369318f1fb9abbaf502a21fc67418312c051 | MATLAB | 4,275 | 122 | 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... |
108e82f426440abcd91e55ff58cd1c74b02e2841d749235aa9ecc2802ca2c379 | MATLAB | 4,286 | 120 | function zef_3D_plot_specs(h)
%Coordinate system's visualization parameters
head2axes_ratio = 1.0255; %percentual empty space between surface and coordinate limits
tick_number_limit = 8; %maximum number of ticks on visualization
%compartment_tags = evalin('base','zef.compartment_tags');
compartment_tags = {'d1'... |
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