sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0e0138294ddf4869689323b2e4d08b7f24c90db0c1a4b928ae8f32b70e2c72c3 | MATLAB | 1,372 | 36 | function [processed_data] = zef_ellip_low_pass_filter(f, filter_order, ripple, attenuation, edge_frequency, sampling_frequency)
%Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
%This function processes the N-by-M data array f for N channels and M tim... |
2ca21df7f196d67899bc62a00541ca2a2e1ec45cf531a1aa762a9e35b39b741d | MATLAB | 1,376 | 40 | function cleaned = replaceOutliersb( A, outliers )
% out is a logical array identifying outliers to limit search
tic
sx = size( A, 1 );
sy = size( A, 2 );
cleaned = A; %zeros( sx, sy, sz, 'uint16');
meanround = zeros(1,size(A,3));
for i = 1 : sx
for j = 1 : sy
if outlier... |
73e9f7b6b48d0220e60d3c31545b0a77d10997c855777654b16ff5f7017dc42d | MATLAB | 1,380 | 62 | function lights_vec = zef_update_lights(varargin)
if not(isempty(varargin))
h_figure = varargin{1};
else
h_figure = evalin('base','zef.h_zeffiro');
end
h_1 = evalin('base','findobj(get(gcf,''Children''),''Tag'',''axes1'');');
h_2 = evalin('base','findobj(get(gcf,''Children''),''Tag'',''lightsselection'');');... |
1e617ee9b6f21b9dffa59510b61bb2d566886cbe2704f38f15df43a15af32279 | MATLAB | 1,381 | 59 | function c = ismemberstr(a,b,doerrorflag)
%ISMEMBERSTR Check whether string is part of a set of strings (faster than Matlab ismember)
%---
% function c = ismemberstr(a,b[,'doerror'])
% ---
% Same as ismember(a,b), but faster!!, for cell arrays of strings only.
% For easier programming, the set of strings b can also be ... |
8d9327451dd42a38106008ba212538a37d0b3483c74847a884df8da517a2c863 | MATLAB | 1,382 | 36 | function [processed_data] = zef_ellip_high_pass_filter(f, filter_order, ripple, attenuation, edge_frequency, sampling_frequency)
%Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
%This function processes the N-by-M data array f for N channels and M ti... |
11b1939d76bf681bc5bc5464558f472c1cf0ec76c8954b6c0ab312836110176f | MATLAB | 1,383 | 48 | function zef_plot_3D_stem_reconstructed_source(varargin)
%A static plot showing the active synthetic sources
arrow_scale = 100;
arrow_type = 1;
arrow_color = 0.5*[1 1 1];
arrow_shape = 10;
arrow_length = 1;
arrow_head_size = 2;
arrow_n_polygons = 100;
if not(isempty(varargin))
arrow_scale = varargin{1};
if le... |
552b955011611264f0c4993503bb0b630ff56c7f846ffcfd1980482e69367930 | MATLAB | 1,383 | 48 | function zef_plot_3D_arrow_reconstructed_source(varargin)
%A static plot showing the active synthetic sources
arrow_scale = 1;
arrow_type = 2;
arrow_color = 0.5*[1 1 1];
arrow_shape = 10;
arrow_length = 1;
arrow_head_size = 2;
arrow_n_polygons = 100;
if not(isempty(varargin))
arrow_scale = varargin{1};
if len... |
991ae6ad52cb54bd6de65de98b5bc2f6812eaa83d2cd4db5462b7fe6d6893636 | MATLAB | 1,383 | 58 | clearvars -except thepath h;
tic
y=importdata('y.txt',",");
y=y.data;y=y';
u=importdata('u.txt',",");
u=u.data;u=u';temp=repelem(1,size(u,2)); u=[temp;u];
N=importdata('N.txt',",");
N=N.data;
label=importdata('label.txt',",");
label=label.data;
coord=importdata('coord.txt',",");
coord=coord.data;
D=pdist(co... |
e191ff0f169e8b212744041b757cde49d7ca1b9a61db789678dae82a2c2d22db | MATLAB | 1,383 | 47 |
function dti_tensor = zef_dti_tensor_condition(dti_tensor,scale_value)
nx = size(dti_tensor,1);
ny = size(dti_tensor,2);
nz = size(dti_tensor,3);
if nargin < 2
scale_value = 1;
end
for ix = 1:nx
for iy = 1:ny
for iz = 1:nz
D = [dti_tensor(ix, iy, iz, 1), dti_tensor(ix, iy, iz, 4), dti_te... |
c9d677f56852be935faf3591a0b4a6f3ff07b3337d736bf099bc667e1937430f | MATLAB | 1,384 | 38 | function zef = zef_ES_recursive_search(zef, num_lattice, recursive_instances, varargin)
zef = zef_ES_find_currents(zef);
adapted_y_ES{1} = zef.y_ES_interval;
% num_lattice = num_lattice;
% num_lattice = num_lattice; % K = Size of the adaptive window
% recursive_instances = recursive_instanc... |
6c0bfc4d658edb7061ebe281ab4dd807987023b638a82a398af4f6f9a238d3fb | MATLAB | 1,385 | 84 | function M = zef_surface_scalar_matrix_DD(nodes, tetra, g_i_ind, g_j_ind, scalar_field, weighting)
%
% zef_surface_scalar_matrix_DD
%
% TODO: Sampsa should document this.
%
% Inputs:
%
% - nodes
%
% TODO: explanation.
%
% - tetra
%
% TODO: explanation.
%
% - g_i_ind
%
% TODO: explanation.
%
% - g_j_ind
%
% TODO... |
7a5a0cfee805b12ea3e377fcea46e06d57ccd41fbef539c54ffa02b020b57d64 | MATLAB | 1,385 | 88 | function M = zef_surface_scalar_matrix_n(nodes, tetra, n_ind, scalar_field, weighting)
%
% zef_surface_scalar_matrix_n
%
% TODO: Sampsa should document this.
%
% Inputs:
%
% - nodes
%
% TODO: explanation.
%
% - tetra
%
% TODO: explanation.
%
% - n_ind
%
% TODO: explanation.
%
% - scalar_field
%
% TODO: explanat... |
94516f995e623466023d3d1cb9bfa1fb2e0ed8247983a17dcaad3a359d12382c | MATLAB | 1,386 | 47 | % myobj = SetAudioParams( myobj, group_string, params_struct )
%
% Set subgroup of parameters for audio-out operation. Parameters
% are a struct of name/value pairs. This call stops current output.
% Call SetAudioEnable( myobj, 1 ) to restart it.
%
function [s] = SetAudioParams( s, group, params )
if( ... |
f5f10932c0a2fb4e0edf3cfb02d1ab5537d4c403ef36753bd3651edbea8c0d0b | MATLAB | 1,386 | 46 | function [param] = optimize_svm_param(data, param, model)
opt_thr = 0;
opt_Nrefrac = 0;
opt_Npre = 1;
opt_Nwin = 4;
max_f1 = 0;
for svm_thr = 0:0.5:2
for Nrefrac = [0 1]
for Npre = [1 2 3]
for Nwin = [4 6 8 10]
param.threshold = svm_thr;
param.Nrefrac = Nrefrac... |
a2f1e13a5dd5a9a17062530c26a4310d66fa9c13babe35b85e9b14aa38d5a0f8 | MATLAB | 1,387 | 46 | function [triangles_out, points_out] = zef_get_sensor_boundary(zef)
points_ind = [];
triangles_ind = [];
compartments_ind = [];
if isfield(zef,[zef.current_sensors '_boundary_cell'])
boundary_cell = zef.([zef.current_sensors '_boundary_cell']);
points_ind = zeros(length(boundary_cell)+1,... |
c2d6a89ff3c36b5f2b78e0ea36e9a492161b1529b9b70c4a7f4283d4d005290d | MATLAB | 1,389 | 31 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
set(zef.h_filter_pipeline_list,'Value',cell(0),'Items',cell(0),'Multiselect','on');
zef.filter_pipeline_list = cell(0);
for zef_i = 1 : length(zef.filter_pipeline)
zef.filter_pipeline_list{zef_i} ... |
92205af4a5f0fa2d3851090ea52a597de9bda99d9e3545ebe06e1d2cf8068a05 | MATLAB | 1,390 | 48 | function h = hashmd5(inp)
% Computes the MD5 hash of input data.
%
% function h = hashmd5(inp)
%
% Returns a string containing the MD5 hash of the input variable. The input
% variable may be of any class that can be typecast to uint8 format, which
% is fairly non-restrictive.
% This file is part of Manopt: www.manopt... |
90d110b967f1d9e51edea4fe747dd6732a529221d4a5fe966a0583e3150a4f1f | MATLAB | 1,391 | 80 | function [x, function_val, flag_val] = zef_cvx_linprog(Q,z,A,b,Aeq,beq,lb,ub,varargin)
%Finds the minimum of z'*x with respect to x and with the constraint A x - b <= 0
%Outputs: x (size: [n x 1]), flag_val (1 if the solution was found -2
%otherwise)
%Arguments: z (size: [n x 1]), A (size: [m x n]), b
%(size: [m x 1])... |
d3f6f469d412241102081098c73b6a28175c4b3a1b66ff99ab7bb55555ae1444 | MATLAB | 1,391 | 56 | function implot(matData,vecScale,matColormap,dblLineWidth)
%implot Creates vectorized heat map plot using lines instead of bitmaps
%as with imagesc(). Syntax:
% implot(matData,vecScale,matColormap,dblLineWidth)
%
%
% Version history:
% 1.0 - July 22 2015
% Created by Jorrit Montijn
%
%Dependencies: makeBins... |
abf47f344477ef76b523b3bb0d8ee4c6b603cd81f4aed40cbc188f01641c9326 | MATLAB | 1,399 | 40 | function uilock(handles)
%uilock Shared Core GUI locker
% uilock(handles)
%Enable,'off'
%{
cellNames = fieldnames(handles);
for intPtr=1:numel(cellNames)
if (~isempty(strfind(cellNames{intPtr},'ptrButton')) || ...
~isempty(strfind(cellNames{intPtr},'ptrList')) || ...
~isempty(strfind(cellNames{intPtr}... |
d3278a8bcfcc7be11153e7020a85c17a0f6bd82c2baf0c5ae66d2843f8dbba17 | MATLAB | 1,402 | 51 | function rois = simulate_rois(num_neurons)
image_size = [512 512];
radius = 5;
illegal_area = radius*2;
true_image_area = [512-radius 512-radius];
rois = struct();
rois.xpix = cell(num_neurons,1);
rois.ypix = cell(num_neurons, 1);
rois.boundaryOutlines = cell(num_neurons, 1);
start_time = tic;
current_time = tic;
... |
c7315bbfff68ecce10a35a2dadf12b943189f88106a0efebbc16a016556e89a4 | MATLAB | 1,403 | 53 | function zef = zef_dataBank_addButtonPress(zef)
if nargin == 0
zef = evalin('base','zef');
end
dbtype=zef.dataBank.app.Entrytype.Value;
if isempty(zef.dataBank.app.Tree.SelectedNodes) %either no selected or no node in tree, either way start on first level
newNode= uitreenode(zef.dataBank.app.Tree);
dbPa... |
218691ffc5700b3da0d2e95801315947e26780e4357188be22a8b9aff0c7ed4e | MATLAB | 1,405 | 32 | function h = box3(vol, I2X, bbox)
% Cut out a box from volumetric data and display it using texture mapping.
% h = box3(vol, I2X, bbox)
%
% vol, is a volume that is either N x M x K if it consists of scalar values
% or N x M x K x 3 if it is in RGB. The behaviour of the color handling is
% is similar to image3 and sli... |
589e13f095c62c2291fef256c53b6b59abd2016ab49a9817f9c6642ec93703ae | MATLAB | 1,405 | 58 | figure(100);
clf
surface_triangles = zef_surface_mesh(tetra);
u_amp = sqrt(u_1_plot.^2 + u_2_plot.^2 + u_3_plot.^2);
hold on;
for time_point_ind = 1 : size(u_1_plot,2)
time_point_ind
u_amp_aux = u_amp(:,time_point_ind);
plot_field = db(mean(u_amp_aux(surface_triangles),2));
if time_point_ind > 1
... |
64fb74ef04cc9efd4682ae69134985f5f9552fae9722decadc872fe712731490 | MATLAB | 1,405 | 46 |
%--------------------------------------------------------------------------------
% regression_analysis.m
%
% Copyright (C) 2024 Takuya Isomura
% (RIKEN Center for Brain Science)
%
% 2024-10-28
%--------------------------------------------------------------------------------
function reg = regression_analysis(data,Tt... |
aa60f1fadfd11cf7b377240d234457bc19495b8b56429fa0bac939b65108a576 | MATLAB | 1,405 | 83 | function [x, function_val, flag_val] = zef_cvx_linprog(z, y, A,b,Aeq,beq,lb,ub,varargin)
%Finds the minimum of z'*x with respect to x and with the constraint A x - b <= 0
%Outputs: x (size: [n x 1]), flag_val (1 if the solution was found -2
%otherwise)
%Arguments: z (size: [n x 1]), A (size: [m x n]), b
%(size: [m x 1... |
717db9bcaca62b6f12b3810d73d420b79a1778a5a973573a4cb50a54a6504581 | MATLAB | 1,409 | 68 | full_address = 'exportImage';
file_name = 'carsten';
file_full = fullfile(full_address, file_name);
%%
%% Deep Component
set(zef.h_axes1,'clim',[0 1])
f1 = gcf;
f2 = figure();
%612 510
f2.Position(3) = 620;
f2.Position(4) = 600;
copyobj(findobj(f1.Children, 'tag','axes1'), f2);
f2.Children.Position(2) = 60;
grid o... |
8d73dfb59c05a0492ed1f95e3b1de1ea6936895a27bf4dd2a77f9147d500ed86 | MATLAB | 1,409 | 50 | function [P_s_store, m_s_store, G_store] = Block_RTS_smoother(P_store, z_inverse, A, Q, number_of_frames, dim,sL)
P_s_store = cell(0);
m_s_store = cell(0);
G_store = cell(0);
h = zef_waitbar(0,1,'Smoothing');
if sL>=dim
I1=eye(size(A,1),size(A,1)*dim);
else
I1=eye(size(A,1)*sL,size(A,1)*dim);
end
zero_m=zeros(... |
8093bbfdefe2d60cbb0469ec4ba2c7110707d913379ef2d9cd115d9ef3c0fdd8 | MATLAB | 1,411 | 39 | function ET_SwitchOnlineDetection(strSelected)
%% globals
global sET;
global sEyeFig;
%% update switch
if strcmpi(strSelected,'On')
set(sEyeFig.ptrButtonDetectPupilOn,'Value',1);
sET.boolDetectPupil = true;
%check if an output file has been defined
if isfield(sET,'objVidWriter') && isprop(sET.objVidWriter... |
707ef2ba07fa294dbd0faf7a5da8c4d171f929656eef503481ed56a64aec178b | MATLAB | 1,415 | 48 | function printf(strBase,varargin) %#ok<*INUSL>
%printf Writes output to log file instead of printing to screen
%define global pointer to file
global ptrOutputFile;
global strLogDir;
global boolClust;
if boolClust
%format input
strExec = 'sprintf(strBase';
for intArg=1:numel(varargin)
strExec = [strExec... |
76122d5fd8869e07e2b062325675cb9ae62dc303fbc9dc39193cacae40010502 | MATLAB | 1,415 | 46 | function [acc,acc_star] = tudacv_permutations(X,Y,T,options,nperms)
% This function computes a null distribution for decoding by randomly
% permuting the labels nperms times. This code is designed to be run
% immediately following a call to tudacv, such that the data and
% options are exactly unchanged.
%
% The only ad... |
858ec1bd099723dabecc401bf3be44a837668703e3bfb66b11e24f4e0461fcf1 | MATLAB | 1,415 | 39 | function [params] = learn_neighborhoods_par(params)
% Reviewed Darik A ONeil 04-15-2023
% Inputs:
% a structure params
%Outputs:
% a structure params
%grab necessary parameters & pre-allocate
%% Setup
warning('off','all');
x_train = params.x_train;
neighborhoods=params.neighborhoods;
options = params.glm_options;
nod... |
c23c95963c62bb0b700453e88021fbec795689cfb5a7de292a2f0104a7f6656b | MATLAB | 1,417 | 45 | % load minimum of data to allow ROI selection
function S = loadFlatProj(m)
varlist = who(m);
% m is the result of a call to matfile
S.timing = m.timing; % convert to sec
index = find(strcmp(varlist,'interval'), 1);
if isempty(index)
m.interval = mean(diff(S.timing));
disp(append("N... |
b89ff686cac92dbdee02ba0f0d2458e1361d385f12aa6ee000843d3c7c43a842 | MATLAB | 1,418 | 48 | function [tree] = zef_dataBank_importDataBank(tree, savePath, saveFile, parentHash, dataBank)
dataTree=load(strcat(savePath, saveFile));
dataTree=zef_dataBank_sortTree(dataTree);
dataTree=zef_dataBank_rebuildTree(dataTree);
data=dataTree.node_1.data;
[tree, firsthash]=zef_dataBank_add(tree, parentHash, data);
tree.(... |
42fb35ea3c772d73dbd833138cace491cd8fc62a9f26ac180e0a62b38a4c40ca | MATLAB | 1,419 | 52 | function recon_spike = calibrate_spike_time(t, y, str_index, dir, length0, dt0, Npre, Nwin, model)
Ntp_spike = length(str_index);
str_index = sort(str_index, dir);
% acquiring spike model
t0 = 0:dt0:t(end);
N0 = length(t0);
N = length(y);
transient = dbl_exp_func(t0, model);
... |
f12eb78377241b090c98c043ae8a28ec325fa967cd31e7796b0d3c55c3289495 | MATLAB | 1,420 | 57 | function data = leadingPhEigenvector(data,T)
% Computes the leading eigenvectors of the time series of phase coherence.
% That is,
% - Calculates the iFC (or instantaneous coherence matrix)
% - Calculates the instantaneous Leading Eigenvector
% - Calculates the instantaneous % of variance
% - Calculates de time x time ... |
8a0498282c7d15ea4e77e3e460207179036147811012b98d2cdd8463465d68e3 | MATLAB | 1,422 | 40 | function [preds_K,hard_class_pred] = multinomLogRegPred(preds_N)
% function to convert a mmultinomial logistic regression data back to class
% probabilities. input should be a [T x nTr x N] matrix of scores, where
% N=(K.^2-K)/2 possible permutations
[T,nTr,N] = size(preds_N);
K = 0.5*(1+sqrt(1+8*N)); %solving by quad... |
acefb48d86d089e9e29b37f755e63745b83328f19c605108716ee53856056f0b | MATLAB | 1,422 | 39 | function [t, A_fr] = FiringRate(spikes, method, binsize, stim_time,plotit)
%Neural Response Tuning Curve = Average firing rate
%Designed for output from NEL
%A_Fr = average firing rate
%t = times corresponding to average firing rate
%spikes = 2 columns, first column is trial, second is spike times
%method = 'bi... |
6b5f0603dbd7cb1c8648a522afcbf08daba926c6c3c70d5beecff8d7c1a3e643 | MATLAB | 1,424 | 41 | function vecYhat = gnmlinfunc(vecLinCoeffs,matX,cellFunctions,vecLinCoeffFunctions)
%gnmlinfunc Wrapper for lsqcurvefit()
% vecYhat = gnmlinfunc(vecLinCoeffs,matX,cellFunctions,vecLinCoeffFunctions);
%
%vecYhat is summed contribution of all predictors into [n x 1] vector,
%where n is the number of observations
... |
9bb8d25bbe9c3450b8d6f557d48247a2d7d709a40798bd8461602499de32fd38 | MATLAB | 1,424 | 47 | function [beta,beta_t] = tudabeta(tuda,Gamma_mean)
% Given a precomputed TUDA model, it returns the decoding coefficients
% (aka the "beta" parameters)
%
% INPUT
% tuda: Estimated TUDA model, using tudatrain
% Gamma_mean: (Optional) if time-resolved coefficients are desired,
% inputting the mean state timecourse he... |
b14f3de11b38099f06a5869c7f1138f84f57dff2c06149589bde36ab7ceda157 | MATLAB | 1,427 | 42 | function [P_s_store, m_s_store, G_store] = RTS_smoother_standardized(P_store, D_store, z_inverse, A, Q, number_of_frames)
P_s_store = cell(0);
m_s_store = cell(0);
G_store = cell(0);
h = zef_waitbar(0,'Smoothing');
for f_ind = number_of_frames:-1:1
zef_waitbar(1 - f_ind/number_of_frames,h, ['Smoothing (standardized... |
5d05fdf82f8d48f296066d1a0c27d67e0baeb1c42fcd88addce6084b1718aa24 | MATLAB | 1,431 | 22 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.ias_hyperprior = get(zef.h_ias_hyperprior ,'value');
zef.ias_snr = str2num(get(zef.h_ias_snr,'string'));
zef.ias_type = get(zef.h_ias_type,'value');
zef.ias_n_map_iterations = str2num(get(zef.h_ias... |
d6c6e11ff62ab78531217a8604a760c6eac30cf7eb91c19e93c94b2949dbe766 | MATLAB | 1,431 | 22 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.sl1_hyperprior = get(zef.h_sl1_hyperprior ,'value');
zef.sl1_snr = str2num(get(zef.h_sl1_snr,'string'));
zef.sl1_type = get(zef.h_sl1_type,'value');
zef.sl1_n_map_iterations = str2num(get(zef.h_sl1... |
9a5acb709016f1701aa02ef9d59ac30002256e8be980b05fe0fd432fe143692c | MATLAB | 1,432 | 76 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
function [x,conv_val,n_iter] = pcg_iteration_gpu(A,b,tol_val,max_it,M,x,gpu_extended_memory)
if nargin < 5
M = [];
end
if nargin < 6
x = zeros(size(b,1),1);
end
if nargin < 7
gpu_... |
85405f3a67d4bca666ec9333ca4e304ef0de2a1a17bcab112d81285a2d042dec | MATLAB | 1,434 | 39 | function [t, A_fr] = SpikeProb(spikes, method, binsize, stim_time,plotit)
%Neural Response Tuning Curve = Average firing rate
%Designed for output from NEL
%A_Fr = #of spks per bin
%t = times corresponding to average firing rate
%spikes = 2 columns, first column is trial, second is spike times
%method = 'bin', ... |
ad5d329484b5d3f00386f042ca41d740fff96f098231dfc3f9ce7d8503d4b051 | MATLAB | 1,434 | 22 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.inv_hyperprior = get(zef.h_mcmc_hyperprior ,'value');
zef.inv_snr = str2num(get(zef.h_mcmc_snr,'string'));
zef.inv_n_burn_in = str2num(get(zef.h_mcmc_n_burn_in,'string'));
zef.inv_sample_size = str... |
aff7505a80e4772ddde603c0b74f58feb926983c2d7a22664e3e184f5ec02377 | MATLAB | 1,435 | 45 | function zef_add_package(package_path, package_folder, file_folder, file_folder_dir)
if not(isempty(package_folder))
mkdir([package_path filesep '+' package_folder]);
package_path = [package_path filesep '+' package_folder];
end
if nargin == 3
file_folder_dir = dir(file_folder);
end
for k = 1 : length(fi... |
eb279b1daf9787d3ef758a408f7a4015b8bba84d1fc56f77b8501c3442c94b5c | MATLAB | 1,439 | 48 | function [dti_directions, dti_anisotropy] = zef_dti_directions(dti_tensor)
nx = size(dti_tensor,1);
ny = size(dti_tensor,2);
nz = size(dti_tensor,3);
dti_anisotropy = zeros(nx,ny,nz, 'single');
dti_directions = zeros(nx,ny,nz,3, 'single');
for ix = 1:nx
for iy = 1:ny
for iz = 1:nz
D = [ ...... |
7948c8ea194d061d0dde53068095ecfac92f6cf417a6365c9b7d3831c81412ca | MATLAB | 1,440 | 37 | function evaluate_neuronal_contributions_button_pushed(app)
update_log(app, 'Evaluating Neuronal Contributions...');
if ispc()
[user_mem, ~] = memory();
RAM = user_mem.MaxPossibleArrayBytes/(1024^3)*0.95;
else
RAM = 0.95*8192;
end
if app.params.par_proc
num_workers = gcp('nocreate').NumWo... |
eeeafe32bfba9d6f7691bf745a9f1764304f3a49b41900f863d440a1f1f0b7d7 | MATLAB | 1,441 | 39 | function [] = concatenate_voxel_based_hurst_exponent(subject)
% The goal of this script is to concatenate all hurst exponent parts files
% that were generated by the compute_voxel_based_hurst_exponent.m script
% Requirements:
% 1. The script compute_voxel_based_hurst_exponent.m has been run.
%
% Input:
% 1. subject -... |
c345c2b00b8186e3b34b5eff9f5e6dcab167e661ec764662c2eef297046a6c28 | MATLAB | 1,443 | 55 | %% Copyright © 2025- Joonas Lahtinen
function self = initialize(self,L,f_data)
%
% initialization function
%
% Initialize recursively updated variables before the computation of
% the first time step.
%
% Inputs:
%
% - self
%
% An... |
fa1540c63b4b47c560badd51cc6597a4e71095bd4e1a2864b0a8b073a73046f5 | MATLAB | 1,446 | 60 | function obj = preprocess_spatialfilter(obj,pos,kneigh)
% CARTOOL style spatial filter, see
% https://doi.org/10.3389/fneur.2019.00325 for reference
if nargin < 3
kneigh = 6 ;
end
if strcmp(obj.modality,'source') || strcmp(obj.modality,'ampenv')
error('Spatial filtering should only be applied to sensor signa... |
00c66c8ddc8bb359cea97d214f44b7098b577ad393557bff20c25fcf2220139e | MATLAB | 1,447 | 58 | function [nodes] = zef_inflate_surface(zef,nodes,surface_triangles,varargin)
N = size(nodes,1);
if not(isempty(varargin))
smoothing_steps_surf = varargin{1};
else
smoothing_steps_surf = eval('zef.inflate_n_iterations');
end
smoothing_param = eval('zef.inflate_strength');
A = sparse(N, N, 0);
diag_ind_aux = unique(sur... |
07f5ca3550a33c73a52f4a3cf56b736049fd3ee4a657509322e1f71ce1558e7c | MATLAB | 1,451 | 39 | function hmm = updateBeta(hmm)
K = length(hmm.state); ndim = hmm.train.ndim;
M = hmm.train.pcapred;
for k = 1:K
if ~hmm.train.active(k), continue; end
setstateoptions;
if isempty(orders) || train.uniqueAR || ~isempty(train.prior), continue; end
% shape
hmm.state(k).beta.Gam_shape = hmm.state(... |
42337d7d3e78c5fbe241bce205528c79262445f44e6c785e2983cf52a47ffdf8 | MATLAB | 1,452 | 48 | function [D,HMMs_dualregr] = computeDistMatrix (data,T,hmm)
%
% It performs dual regression on each element of T in order to compute a
% subject-specific HMM per subject;
% Then, it uses an approximation of the KL-divergence to compute a
% subject-by-subject distance matrix.
%
% INPUT
% data observations; in ... |
7d73fac3599310b7f8c0d9ccda87f7e626255e7a0b6a3f9a74cfafe6468c4f54 | MATLAB | 1,452 | 51 | function [upperEnv,lowerEnv] = getEnvelope(x, n)
%getEnvelope Envelope detector.
% [YUPPER,YLOWER] = getEnvelope(X) returns the upper and lower envelopes of
% the input sequence, X, using the magnitude of its analytic signal.
%
% The function initially removes the mean of X and restores it after
% computi... |
ed8fb05c2ec1f214f698de7346daefa5991fc87a4d7ce7bf9abbaa733152157a | MATLAB | 1,452 | 39 | function mocoConfirm( fig, stack, smoco_stack, name )
nframes = size(stack,3);
step_size = floor(nframes/3);
im1 = MeanMaxSTD( stack(:,:,1:step_size), 'mean' );
im2 = MeanMaxSTD( stack(:,:,step_size:2*step_size), 'mean' );
im3 = MeanMaxSTD( stack(:,:,2*step_size:3*step_size), 'mean' );
% ... |
297dcc372f17fe53762427e505406c35555411a832b6a7b8b468979d210cd1d8 | MATLAB | 1,453 | 36 | zef_bst.subject_struct = struct;
zef_bst.subject_folder = "";
zef_bst.save_project = 1;
zef_bst.import_settings = "";
zef_bst.verbose_mode = 1;
zef_bst.use_waitbar = 1;
zef_bst.surface_names = cell(0);
zef_bst.mesh_resolution = 3;
zef_bst.refine_surface = {'Scalp','OuterSkull','InnerSkull','Cortex','Other','subcortical... |
db5447c36148b48f0501838f8fbdf9ca26679bd939c886c54937ab9639f890c9 | MATLAB | 1,453 | 26 | % Adapted from ncomp_tools -- see below. Free license given on this software:
function result = negligible(X,Y,tol)
% Return true if X is "negligible" with respect to Y with tolerance 'tol'
% We must be careful with zero elements of Y...
%************************************************************************%
% ... |
4f3e4ffb1ae0b96b410b548b0e1d4df15c7219ad1315722cfc060335481279ac | MATLAB | 1,454 | 51 | function [f,t] = zef_getTimeStepClassObj(f_data, f_ind, zef, ClassObj)
%zef_getTimeStep gets the time windows and segments of f_data that are
%specified in the zef.inv_time* parameters. f_ind gives the number of the given window (first, second, third ...)
% if there is only one time step, f_data is returned.
%Should th... |
c896129e5538c7c9b61fc89e10eee67faf3dd4447e869302145648aeba3e5f7e | MATLAB | 1,455 | 76 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
function [p] = B_prod(u,entry_ind,n,t,gpu_extended_memory)
u = gpuArray(single(u));
n = gpuArray(n);
t = gpuArray(t);
v_ind = gpuArray([1 2 3 4; 2 3 1 4; 3 4 1 2; 4 1 3 2]);
size_n = [size(n,1... |
9bfaf3523a6af1dd399ebdec83678d6837744a6f58aa78a2e9c3ddc57232c5c3 | MATLAB | 1,456 | 40 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if not(isfield(zef,'mne_prior'));
zef.mne_prior = 2;
end;
if not(isfield(zef,'mne_type'));
zef.mne_type = 1;
end;
if not(isfield(zef,'mne_pcg_tol'));
zef.mne_pcg_tol = 1e-8;
end;
zef.mne_s... |
170d6f522c1117de434550d9275c19ffccd4cb84fcf26895bf42aaaa9cfbff69 | MATLAB | 1,459 | 53 | function pval = permtest_aux(X,D,Nperm,confounds)
% permutation testing routine (through regression)
% X: data
% D: design matrix
% Nperm: no. of permutations
% confounds
% grouping: the first grouping(1) rows belong to one group,
% the next grouping(2) rows belong to the second group,
% and so on and so on - D... |
709947356efec8994ecc4273f69f746c7ca8ab4af66a744172e2e160f933517e | MATLAB | 1,464 | 32 | function update_udf_press(app, value)
switch app.TabGroup.SelectedTab.Title
case 'Evaluate Model'
current_value = app.StimulusEM.Value;
if current_value + value <= app.StimulusEM.Limits(2) && current_value + value >= app.StimulusEM.Limits(1)
app.StimulusEM.Value = app.StimulusEM.Va... |
6da99ec20251907161c66cf00d82b6af3528b8f398756c5b6092e2adb8fee7c4 | MATLAB | 1,465 | 24 | %% Result 1 : Long-Range Connections Enhance Object Recognition in Shallow Networks (Figure 2)
% ============================================================================================================
%% Add LRC vs Add Layers (Figure 2g)
disp('================================================================='... |
ad2684cc2a51acb6d3411a02a22fcff011e2fc7772278a1f25aa8bef98c2b007 | MATLAB | 1,466 | 36 | function [Y, Ind, s, s2] = vl_nnpoolInd(X, POOL, Ind, pad, Kernel, dzdx, varargin)
% forward mode
if(isempty(dzdx))
% initial padding
if(sum(pad) > 0)
X1 = [gpuArray.zeros(pad(1), size(X, 2), size(X, 3), size(X, 4), 'single'); X; gpuArray.zeros(pad(2), size(X, 2), size(X, 3), size(X, 4), 'single... |
771da0f9d441b5270d7011bfab01039762a70ab6fe8be2db0f7e4905a7e0e671 | MATLAB | 1,468 | 48 | function new_model(app)
% file handles
app.file_data=[];
app.file_udf=[];
app.file_rois=[];
app.file_model=[];
app.file_params=[];
% imported handles
app.data=[]; %data
app.udf=[]; %user defined features in binary
app.udf_labels=[]; % labels for udf
app.rois=[]; %roi coordinates, can be many forms (see functions for ... |
8012c7dab1e1397d2f40a81f940df2b2658e7e737ec36381e726dae1c6c3361b | MATLAB | 1,469 | 69 | % script to test loading edf
% edf is a little different since one data file has many channels:
% always set > optx.load=1; this will always load up the data from the
% original data file.
% loading edf you have to set a channel index:
% eg > opt.edf_ch=1;
clearvars
close all hidden
fprintf (' sw > test edf \n\n'... |
823749b796827382e58351ed2c46a588f48d363bb7a33c545229853c519e2153 | MATLAB | 1,469 | 48 | %% make gmm for every reconstruction
for gmm_opt=1:3
zef.GMM.parameters{23,2}={num2str(gmm_opt)};
switch gmm_opt
case 1
meth='_kmeans';
case 2
meth='_maxProb_';
case 3
meth='_maxComp_';
end
for ii=[0.25, 0.5, 0.75]
%open gmm tool ... |
f122865caf8401f25fd133cf02185a0646ac0257fc50a0417c3c57a74c9d8de4 | MATLAB | 1,469 | 22 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.top_regularization_parameter = str2num(get(zef.h_top_regularization_parameter,'string'));
zef.top_sampling_frequency = str2num(get(zef.h_top_sampling_frequency,'string'));
zef.top_low_cut_frequency... |
2a5ab92ca6e052febff73b98818d58d3368e5fd2d9342fd00919d3d1ba95725f | MATLAB | 1,470 | 50 |
%--------------------------------------------------------------------------------
% utm_init.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)... |
010f4f2d4bc9d4c2b2d3ac420aca5628abe9ce0c0e6d16bb62f570d02966b188 | MATLAB | 1,472 | 38 | function [cellFoldsX,cellFoldsY,cellFoldsShuffledX,cellFoldsShuffledY] = getFolds(intFoldK,matX,matY)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
%% general metadata
intRepetitions = size(matX,1);
intNeuronsX = size(matX,2);
intNeuronsY = size(matY,2);
intTrialsPerFold = flo... |
69d56f2810c7486f576292b13d85ea11f9096a806b4196cd8e0398246438d553 | MATLAB | 1,472 | 46 | function parm = set_default_param(parm)
if nargin<1, parm = struct; end
%% parameters for estimating the spike model
% number of time constant, 2 or 3
if ~isfield(parm,'Ntau'), parm.Twin = 2; end
% decay rate [s]
if ~isfield(parm,'decay'), parm.decay = 1; end
% sampling window in second
if ~isfield(parm,'Twin'), par... |
23cf62af32567f173d7de08bdba7442c86608e890ca21a6664a3d10f79a75cde | MATLAB | 1,473 | 78 | function [x,fval,exitflag] = zef_gurobi_linprog(f,A,b,Aeq,beq,lb,ub,options)
if nargin < 4
Aeq = [];
end
if nargin < 5
beq = [];
end
model.obj = f;
model.A = [sparse(A); Aeq];
model.sense = [repmat('<',size(A,1),1); repmat('=',size(Aeq,1),1)];
model.rhs = [b; beq];
if nargin > 5
if not(isempty(l... |
1bd9e1a218946d3a59862b8aafce6f7c8898fcc1990c1d3b3aa153680a2a2ab8 | MATLAB | 1,474 | 58 | function [fnc_call, fnc_str, fnc_name] = zef_read_function_call(file_name)
[~,fnc_name,~] = fileparts(file_name);
fnc_str = '';
%fnc_name = '';
fnc_call = '';
s0=strtrim(fileread(file_name));
s = s0;
if not(isempty(s))
c_aux = s(1);
nline = regexp(s,'\n');
n_line_counter = 0;
while isequal(c_aux,'%')
... |
c327fb04d3d8db2c5b3136258a9cdcf7e368348dba9998e61bf1e4fb2edebbbd | MATLAB | 1,474 | 44 | function Scorings = Fun_ReadScoringFiles(Path, FileNames,...
NumOfEpochsExpected)
%% Written and updated by M. Nollet (Aug 2023)
% Adapted from a script written by R. Winsky-Sommerer (DE_RWS Jan 2013)
%
% Read information (scoring of vigilance states) contained in the files
%
% INPUTS: txt files (with "_s... |
56d109d7502b8cf76f1fc21559e6f90dafb64353b1a5ecf53f53fa85d3388b76 | MATLAB | 1,475 | 59 | function [] = Write_vtk_polyline_multi_scalar(Pts, Tri,Scalars,Scalars2,Scalars3,filename,name)
% Usage :
% Write_vtk_polyline(contour.',{tri},'MNHN-ZO-MO-1973-115_URM3_slice_contour.vtk');
% Pts : 3xN
% Copyright modified by Jean Dumoncel
fid = fopen([filename(1:end-4) '.vtk'] ,'wt');
fprintf(fid,'# vtk DataF... |
f1fa3f916500155a96367526c3d9102ac3022aad47c894acacae653536b0f3d2 | MATLAB | 1,475 | 61 | function [info,columnNames, hashList] = zef_databank_showAll(tree, type)
%get all hashes of type nodes
% this will add a tiny bit of runtime, but makes the funtion more readable
info=cell(0,0);
columnNames=cell(0,0);
dbFieldNames=fieldnames(tree);
hashList=cell(0,0);
for i=1:length(dbFieldNames)
if strcmp(tree.... |
a89e231b57b54247af0f05eb644a87b3b31e276df73d907b2dab3c91cb4b0097 | MATLAB | 1,476 | 44 | function p=powerspectrum( data, Fs )
%
% powerspectrum
%
% Take the FFT of the data series and spit back power
% spectrum formated data.
%
% Inputs:
%
% data - signal of dimmensions 1 x N (N = no. samples).
% Fs - sampling rate (Hz)
%
% Output:
%
... |
1f3085ad3274a6cdf386946d2764b4753d37261e69b8d81670c0158699461780 | MATLAB | 1,477 | 55 | %% Copyright © 2025- Joonas Lahtinen and Alexandra Koulouri
function self = initialize(self,L,f_data)
%
% initialization function
%
% Initialize recursively updated variables before the computation of
% the first time step.
%
% Inputs:
%
% - self
... |
8ac57279437640b8a4d6d6bc633d679b0c2afe9c34bbb67287d7836ce617eafc | MATLAB | 1,477 | 46 | function [outdata,errind]=bsliang_rmoutlier3sd(indata)
% indata is a list
c_extrm=10;
c=2.5;
%% ÅųýÌر𼫶˵ÄÖµ
errind=[];
while 1
finished_minextreme=0;
finished_maxextreme=0;
indata_rm_min=indata(indata>min(indata));
m_rm_min=mean(indata_rm_mi... |
dc5a943cb1608b7a954c866b40ef79270eae2b81432df46cc60523f124ef270e | MATLAB | 1,478 | 70 | function figure_without_colorbar_fn(figtool, filename, filetypes, resolution)
%
% figure_without_colorbar_fn
%
% Saves a given Zeffiro Interface figure tool image without the colobar
% included.
%
% Inputs:
%
%
% - figtool (1,1) matlab.ui.Figure
%
% An instace of a Zeffiro Interface Figure tool.
%
% - filename (1,1) ... |
11f960198d07b2858337eee7d7198e83822b1f461c37b4859d8e1c123ad117c3 | MATLAB | 1,479 | 45 | function [tree] = zef_dataBank_rebuildTreeSaveFile(tree)
%tree is sorted and rebuild, but the names and hashes of the nodes might
%longer match the names of the save files.
%rename the old files to tmp-files, then rename them to the new names
%(avoids overwriting) and renew the node matfiles
% IF the hash and filename... |
5774ed3089077d7462ba5306515deadaa3a960b49dab7a0a296de7ca2ffbf0e1 | MATLAB | 1,480 | 66 | function [pval,d,side] = permtestdiff_aux(Xin,Yin,Nperm,confounds,side,func)
% tests if @func (mean by default) of Xin is higher than the mean of Yin
% Diego Vidaurre, University of Oxford (2015)
% pval : pvalue
% d: the permutation values
% side: 1 if mean(Xin)>mean(Yin), -1 otherwise
% Diego Vidaurre
Xin = Xin(~isn... |
e63f7aa46db341af388e3e73ae38883389e10ecc6df7ece5d18d678f4f70e3bb | MATLAB | 1,482 | 43 | function stats = applyStatsfun(problem, x, storedb, key, options, stats)
% Apply the statsfun function to a stats structure (for solvers).
%
% function stats = applyStatsfun(problem, x, storedb, key, options, stats)
%
% Applies the options.statsfun user supplied function (if it was provided)
% to the stats structure, a... |
ee7866f3f8bfd1517b77363c4ecf41bd95b144d1647f36198e012544ca2cba74 | MATLAB | 1,482 | 37 | function [q] = find_evolution_prior(L, f_data, likelihood_std, evolution_prior_db,evolution_mode)
% q to evolution prior
switch evolution_mode
case 1
%Since R = likelihood_std^2*eye, we have
% A_noise = (1/(p*A_signal))*A_signal => SNR = p^2*A_signal^2 =
% (q||L||^2)^2/E[||noise||^2]
% => E[dy^2] ... |
3ff5a7a25de64a1cb06040209577ad8ea750777cde3d87305b767392fa7009e4 | MATLAB | 1,484 | 38 | % Get location of the toolbox and specify data directory
toolbox_path = microstate.functions.toolbox_path ; % location where the toolbox is installed
datadir = fullfile(fileparts(toolbox_path),'tutorials','tutorial5_Chi2_Stimulus_Response') ; % path to folder containing the data
addpath(datadir) % add this to the path
... |
a77e4e3dc91e1e0a37417b7fc71458b478751db3ed9f290bc4b7fe596e6cc1c6 | MATLAB | 1,484 | 42 | function Tau = set_tau_grid_cs(Ntau)
% set_tau_grid_cs
% parm.tau = [0.01; 0.5; 1.0]; % [onset time; decay time] [sec]
% ??on was constrained to 2 - 30 ms to avoid steep or shallow onsets.
% decay constant ??2 was set to a fixed value of 70 ms
if nargin == 0, Ntau = 3; end;
Tau.Ntau = Ntau;
Tau.tau_... |
802e989f094d1eb01666210758679a6b40b151ecca5605b8c9a0be5c26e891a4 | MATLAB | 1,485 | 20 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef = zef_update_fss_legacy(zef)
zef.inv_synth_source = str2num(get(zef.h_inv_synth_source_1 ,'string'));
zef.inv_synth_source = zef.inv_synth_source(:);
zef.inv_synth_source = [ zef.inv_synt... |
6764506781b61f0adab12863965d522a4f949ec6129645ef8125eb647db9fc12 | MATLAB | 1,486 | 91 | function M = zef_surface_scalar_matrix_D(nodes, tetra, g_i_ind, scalar_field, weighting)
%
% zef_surface_scalar_matrix_D
%
% TODO: Sampsa should document this.
%
% Inputs:
%
% - nodes
%
% TODO: explanation.
%
% - tetra
%
% TODO: explanation.
%
% - g_i_ind
%
% TODO: explanation.
%
% - scalar_field
%
% TODO: expl... |
18ab1ff59e7721d7dc0297fb6682c5b51eb17320d198ddba8223ff54aa728be8 | MATLAB | 1,491 | 63 | % script to test loading edf
% edf is a little different since one data file has many channels:
% always set > optx.load=1; this will always load up the data from the
% original data file.
% loading edf you have to set a channel index:
% eg > opt.edf_ch=1;
clearvars
fprintf (' sw > test edf \n\n' )
fname='data/hu... |
f1c27021327d6276eb65dc881cc1ad2dbd9bf2242eaf3941f32d336d1b715cb3 | MATLAB | 1,491 | 69 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
function [div_u] = B_T_prod(p_1, p_2, p_3, div_vec, n, t, gpu_extended_memory)
n = gpuArray(n);
t = gpuArray(t);
div_u = gpuArray(zeros(size(n,1),3));
div_vec = gpuArray(div_vec);
v_ind = [ 1... |
94b6d51ee7439eb955f81b0ccecdda95b641cfbdd6c49e2d01767552614869a4 | MATLAB | 1,494 | 35 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if not(isfield(zef,'top_regularization_parameter'));
zef.top_regularization_parameter = 5;
end;
zef.top_sampling_frequency = zef.inv_sampling_frequency;
zef.top_low_cut_frequency = zef.inv_low_cu... |
560d0aa183f73679d64e19718ba1482f6efed591ee152042e380481bedd4c732 | MATLAB | 1,499 | 52 | function [index_vec,MahalanobisD,GMModel] = zef_find_clusters(n_clusters, rec_points,reg_val,cred_val,max_iter,tol_val)
index_vec = ones(size(rec_points,1),1);
if isequal(length(cred_val),1)
cred_val = cred_val*ones(size(index_vec));
end
options = statset('TolFun',tol_val,'MaxIter',max_iter);
r_squared = chi2inv... |
ecf775f20dad72540982bc5551afb975f91609dadc67c40857bc3471f87258b1 | MATLAB | 1,499 | 22 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.inv_multires_n_levels = str2num(get(zef.h_inv_multires_n_levels,'string'));
zef.inv_multires_sparsity = str2num(get(zef.h_inv_multires_sparsity,'string'));
zef.inv_multires_n_decompositions = str2n... |
99440e6c171daeff265c7b96e05e3e10316f67e7a1a0498dbb2eb1125f218a60 | MATLAB | 1,501 | 47 | function [z] = zef_postProcessInverse(z_inverse, procFile)
%zef_postProcessInverse reorders the inverse output z_inverse to fit the
%visibility options. The procFile is given by zef_processLeadfield
source_direction_mode=procFile.source_direction_mode;
source_directions=procFile.source_directions;
s_ind_1=procFile.s_in... |
c4cbdbf339b7a8ed361fe5d2aebe12f0173fa485ecf346536a0cf7e95ced7fb8 | MATLAB | 1,502 | 53 | function [Model, Info, Y] = ...
train_post_weight(post_info, spike_info,Model)
% Sparse classification by probit Model (Covariance method)
%
% [Model, Info] = ...
% probit_sparse_cov(X,Yid,Model_probi,parm)
%
% --- Input
% X : Input data ( M x T )
% Yid : Class id = {1, ..., N} ( 1 x T )
% N ... |
fc48cdd00803042800ccdb700edd73de01106bfbe179f4ccf640561c5826651a | MATLAB | 1,506 | 31 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef_i = length(zef.filter_pipeline_list)+1;
zef.filter_pipeline{zef_i}.name = zef.filter_name_list{zef.filter_list_selected};
zef.filter_pipeline{zef_i}.file = zef.filter_file_list{zef.filter_list_sel... |
d1533bd6046f47816e88e3eb455b26b2e9fbef96e0ade47c551aa8d1e05ca761 | MATLAB | 1,507 | 46 | folder = '/media/datadisk/paavo/zeffiro_interface/figures';
sg_data = [];
lm_data = [];
for i = 1:50
zef_import_figure([],['rec_',num2str(i),'.fig'], folder)
h = gcf;
h_axes = findobj(h.Children, 'type', 'axes');
sg = findobj(h_axes.Children, 'displayname', 'SG 005');
lm = findobj(h_axes.Children... |
28b42240efc762d54b9875009442363dbb35b51e06a1ee7a2e6e4059d5f7f053 | MATLAB | 1,508 | 53 | % V = joint_diag(C,method_diag,arg_diag)
%
% -----------------------------Definition---------------------------------%
%
% description : performs a joint diagonalization of a set of covariance
% matrices.
%
% usage : joint_diag(C,'uwedge',{})
%
% -----------------------------Input------------------------------... |
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