sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9f9e2cd6e2f63c78a4073c84f4be2e7061c2fe8a98179147ed9363bf10fca503 | MATLAB | 2,815 | 84 | % master
% open dataset
% run openETS, extracts image stack into memory
% get two files, baseline and treatment
disp("reading ETS and VSI...")
% rbase and rtreat raw data files, nbase ntreat meaningful names
[ baseRaw, basetiming, baseName, baseETS ] = openETSui(); % puts image stack into 'stack'
[ treatRaw, treattimin... |
5c4cfc6c2db18a8ecee1cccd4fb42a43fe9d3d3afec6f0ea901de31010fa434f | MATLAB | 2,817 | 94 | function ET_stopRecording()
%ET_stopRecording Function to run at recording stop
%get globals
global sET;
global sEyeFig;
%close video writer
if isfield(sET,'objVidWriter'),close(sET.objVidWriter);end
if isfield(sET,'objVidWriterROI')
close(sET.objVidWriterROI);
try,fclose(sET.ptrFileLuminance);catch,end
... |
7d2da32afac0b9be68172aa47ca82a16ffdc87d0ea071f568c95aabb53856400 | MATLAB | 2,818 | 76 | function [objopt,kopt,kvec,maps,gev] = cluster_globalkoptimum(obj,varargin)
% Calculate optimum microstate maps at the group level.
options = microstate.functions.make_options(varargin) ;
% default options
defaults = {'clustermethod','kmeans'; % kmeans, aahc, pca, ica, hmm
'kmeans... |
48e5a990b3b9fd0b70d8feadb2ff0c3e084dcd6dfe47ba49a9b428aa65045760 | MATLAB | 2,826 | 56 | function plot_all_udf_one_ens_pr(app)
udf = app.StimulusEV.Value;
dataset = app.ViewEnsPerfButtonGroup.SelectedObject.Text;
newcolors = app.newcolors;
num_udf = app.params.num_udf;
all_udf = [1:app.params.num_udf];
all_udf = setdiff(all_udf, udf);
legend_string = cell(1+num_udf,1);
legend_string{1} = app.params.udf_... |
8146441ea66fa7c0aa1f158b7ba1f5d985700daa9238718e801bc7250ee68e86 | MATLAB | 2,834 | 90 | function [actstates,hmm,Gamma,Xi] = getactivestates(hmm,Gamma,Xi)
%ndim = size(X,2);
K = hmm.K;
orders = formorders(hmm.train.order,hmm.train.orderoffset,hmm.train.timelag,hmm.train.exptimelag);
if isfield(hmm.state(1),'Omega')
ndim = size(hmm.state(1).Omega.Gam_rate,2);
else
ndim = size(hmm.state(1).W.Mu_W,2)... |
a6a7122b7e71ca6bc618ea212f2d836f2d3e44083579d168e83537d2a7cfad35 | MATLAB | 2,849 | 88 | function [G1, G2, G3] = zef_tetra_gradient_field(nodes, tetrahedra, volume, tensor, eval_point_inds, K, N)
% Calculates a gradient field [G1,G2,G3] for a given set of nodes, tetrahedra,
% volume, volume current tensor, gradient field evaluation points and matrix
% size K and N.
G1 = spalloc(K,N,0);
G2 = spalloc(K,N,0... |
cd9b2a9cbffb393ddfb13d9585fadc059556dd9bb41ad6aaf7a8a1e924fb5d9a | MATLAB | 2,855 | 90 | function sUniqueCombos = getUniqueFieldCombos(sData,cellFields)
%getUniqueFieldCombos Retrieve unique value-combinations from data structure
% Syntax: sUniqueCombos = getUniqueFieldCombos(sData,cellFields)
%
% Outputs four fields in structOut:
% vecUniqueIdx vector containing unique indices corresponding to mat... |
2d8846c0895fa7e6207683d454eb58e193d63e36fd49a3e4579fab6a9d47b204 | MATLAB | 2,856 | 82 | function points = zef_strip_coordinate_transform(strip_struct,transform_type,points)
if nargin > 2
points = mat2cell(points,1);
strip_struct.points{1} = points{1};
else
points = strip_struct.points;
end
if isequal(transform_type,'reverse')
points{1} = points{1} - strip_struct.tip... |
b4b682e3261e3dede8702dc706a5d09f74a48eb8085e2fa51d7f0ee2150309ec | MATLAB | 2,860 | 117 | function matGabor = getGabor(matMeshX,matMeshY,dblCenterX,dblCenterY,sigma,length,theta,dblSF,psi)
%getGabor Creates scaleable gabor filter
% matGabor = getGabor(matMeshX,matMeshY,dblCenterX,dblCenterY,sigma,length,theta,dblSF,psi)
%
% inputs:
%matMeshX = mesh grid for x
%matMeshY = mesh grid for y
%dblCenterX... |
006deac78a693a365471a09c254e3a9042ed58dbe24b12a2caaad5ef153525ea | MATLAB | 2,862 | 73 | function [hmm,info] = hmmsinith(Xin,T,options,hmm)
% Initialisation before stochastic HMM variational inference, when an initial
% hmm structure is provided
%
% INPUTS
% Xin: cell with strings referring to the files containing each subject's data,
% or cell with with matrices (time points x channels) with each
%... |
567edb593cf7c68ffec830ab92079aab543244d354d43ee49a996fe9e0e919a4 | MATLAB | 2,863 | 70 | % OV_MATLAB toolkit
% OV_define.m
% -------------------------------
% Author : Laurent Bonnet (INRIA)
% Date : 28/07/2011
% This file is meant to be executed prior to any user defined script.
% It declare all stim IDs as variable for use by the user.
% MEANT TO BE CALLED BY OPENVIBE
%
% Stimulation codes
% Origi... |
ec637277bd8f2259bb93d8eb687d41f318f5c432e8231a7458a55d49ad95a8ae | MATLAB | 2,864 | 81 | function obj = simulate(obj,varargin) ;
% Wrapper for default simulation pipelines.
% By default, this method will:
% - Generate time axis. If one is a property of the microstate object, it
% will use this. Otherwise, 2 seconds of data at a sampling rate of 256
% will be simulated.
% - Get number of state... |
e9774338d934894807cf6fbd4b2d212b7e6635c599cfde16c159ed7205efc599 | MATLAB | 2,868 | 81 | function gamma = mymcs_gamma_yao2003 ( headmodel, order )
% Returns the Gamma series expansion for EEG leadfields.
%
% Use as:
% Gamma = mymcs_gamma ( headmodel, order );
%
% where:
% headmodel FieldTrip concentric spheres definition:
% headmodel.r Radius of the spheres.
% headmodel.cond Conduct... |
eb90480b4d2701ff6b5ffc83ac74ef1462954696f22e0f3d82bc2585cea2e148 | MATLAB | 2,868 | 139 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef = zef_import_parcellation_colortable(zef,varargin)
if nargin==0
zef = evalin('base','zef');
end
if isempty(zef)
zef = evalin('base','zef');
end
fileFolder = zef.file_path ;
... |
1a4ab14b91fefff540fa6bbd4802e6acbca21e90cc161e08dec07de71a669973 | MATLAB | 2,874 | 98 | function ET_setVidOut(strRecFile)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
%% globals
global sET;
global sEyeFig;
%% set video writer
%create videowriter object to save video using MPEG-4
cellVidFormats = {'Motion JPEG AVI','Motion JPEG 2000','MPEG-4','Archival'};
cel... |
65608c53039e5d1112e6d2cd9ebee62c7cab20874ab752a1e63760715fbfa4e3 | MATLAB | 2,875 | 75 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if not(isfield(zef,'ramus_multires_dec'));
zef.ramus_multires_dec = [];
end;
if not(isfield(zef,'ramus_multires_n_decompositions'));
zef.ramus_multires_n_decompositions = [20];
end;
if not(isfi... |
f128d1e2970b5af25dae06cf8de8b959a25d0494606f94904a8462ae795d263a | MATLAB | 2,876 | 110 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [shape_param, scale_param, snr_vec] = zef_find_g_hyperprior(snr_val, tail_length_db, varargin)
L = [];
source_space_size = 1;
normalize_data = 'maximum';
eps_val = 1e-10;
delta_val = 0.1;
ba... |
0b12b46c99011281e35f485f5b96fb7182c05182d4921c3f1e9e024823bf713b | MATLAB | 2,883 | 83 | function [dblRoundness,dblArea,vecCentroid,imBW] = getApproxPupil(gMatVid,dblPupilT,objSE,vecPrevLoc,boolLowest)
%getApproxPupil Thresholds an image to find a potential pupil area
% [dblRoundness,dblArea,vecCentroid,imBW] = getApproxPupil(gMatVid,dblPupilT,objSE,vecPrevLoc,boolLowest)
%% take trough in histogram ... |
2b63cd58f193d04ed77d8e42a1003df6a002894fa674d1fc23cc4e141da6380c | MATLAB | 2,890 | 107 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [shape_param, scale_param, snr_vec] = zef_find_ig_hyperprior(snr_val,tail_length_db,varargin)
L = [];
source_space_size = 1;
normalize_data = 'maximum';
eps_val = 2e-3;
delta_val = 0.1;
bala... |
2e7c90404042859ec01d35fe3ddd8883ded58be51c49389524237269da43f9fe | MATLAB | 2,896 | 80 | function [] = compute_voxel_based_temporal_functional_connectivity(subject,part,window)
% This script is meant to be the continuation of the
% extract_voxel_based_BOLD_signal.m and compute_voxel_based_functional_connectivity.m
% scripts and it will generate voxel-based temporal functional connectivity
% matrices for... |
73795095a971481b8b51b220b6011e906d7a82f5a775b4682efe9dbc1390470d | MATLAB | 2,896 | 102 | function out_info = spike_state_max_output(state, spike_state)
% --- estimated spike state for window
% out_info = spike_state_max_output(state,spike_state)
% --- Estimated spike info for extracted window
% out_info.spike_num(n) = spike peak number within n-th window : (1 x Nwin)
% out_info.spike_time{n} = e... |
f0ea2883b7f6ca650957be61ff36f638480721aba8d2c9adacee36e764f77ea5 | MATLAB | 2,897 | 62 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
function [boundary_vec_1, boundary_vec_2, s_orbit] = boundary_source(fade_out_param, source_points, orbit_triangles, orbit_nodes)
n_triangles = size(orbit_triangles(:,1), 1);
n_nodes = size(orb... |
9c615492cdb3cab18d747397f867e41bf6183f67146f140da583e7a8b8d90ae2 | MATLAB | 2,899 | 57 | function varargout = nancorr(vecA,vecB)
%NANCORR Linear or rank correlation.
% RHO = NANCORR(X) returns a P-by-P matrix containing the pairwise linear
% correlation coefficient between each pair of columns in the N-by-P
% matrix X.
%
% RHO = NANCORR(X,Y,...) returns a P1-by-P2 matrix containing the pairwise
% ... |
ad9a003d726bb1ea9c8b3e97ba0579dc84e0c048b37953d9c7d5eea405a96ed1 | MATLAB | 2,899 | 76 | function s = structappend(s0,s1) ;
f1 = fieldnames(s1) ;
s = s0 ;
for i = 1:length(f1)
% deal with matrices
if strcmp(class(s1.(f1{i})),'double') ;
dim = size(s1.(f1{i})) ;
if (length(dim) == 2) && (dim(2) == 1) % column vector
s1.(f1... |
a4f5cc2567e08166bb7d447ca98b8d0d697cfa6bd81a15610d945291c1390b9c | MATLAB | 2,900 | 84 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if not(isfield(zef,'exp_em_q'))
zef.exp_em_q = 1;
end
if not(isfield(zef,'exp_em_hyper_type'))
zef.exp_em_hyper_type = 2;
end
if not(isfield(zef,'exp_em_beta'));
zef.exp_em_beta = 1.5;
end... |
edaf9d42d26f7e5d0249b10efddd5f9eb88763b3d8af4df1d4c6c2eaf067af1d | MATLAB | 2,902 | 54 | function [path,version,versionmatfiles] = toolbox_path() ;
% Version 1.7 updates
% - Fixed bug with plotting Neuromag MEG sensors
% Previous version updates:
% Version 1.6
% - Update allowing option to keep polarity when clustering in sensor
% space, useful for ERPs/ERFs.
% - Updated methods for choosing... |
233b0fb1a7bc603d0dc4b5884da5e82f1c46e29c895a07e4f44fffbc06e17ccf | MATLAB | 2,903 | 101 | function [Lsignx, Lsigny, Lsignz] = zef_lead_field_sign( ...
p_source_positions, ...
p_electrode_positions, ...
p_L ...
)
% Documentation
%
% Calculates the x-, y- and z-signs of the given lead field p_L based on
% cartesian source positions, their directions, the electrode positions
% and the lead fie... |
2b349fc465f83c0c40830edfff7b1fa99be1f0fba17621c725d06b79be089393 | MATLAB | 2,904 | 64 | function [identified_neurons, auc_threshold, node_threshold, node_scores] = identify_motifs(params, best_model, node_performance, random_ensemble_performance, ensemble_nodes, threshold_type)
% Consolidated Function for Motif Identification
% Darik O'Neil 12-14-2021, Rafael Yuste Laboratory
%
% Purpose: To identify mot... |
7a555446e5f4647d5a0d093b50d19f993ba4e07fc2013d4c92e5b4f6284474c0 | MATLAB | 2,920 | 90 | %% Nat Comms Ictogenesis Figure S9
clear
load('20230127_PooledData.mat');
%% Load pulsogram for recording
EXP = "EXP_OP141_D210415-1211";
recdat = load(rectable.MATFile(EXP));
pcacfg = rectable.pcacfg{EXP};
pcacfg.eeg_channel = 1;
[PCA, recdat.pulsogram] = pulso_pca(recdat.streams.(pcacfg.EEG), "pulsogram... |
6d62665033f13fae15e1e28e9dc887748dc66faba19c8894d842a6bbd6b447a3 | MATLAB | 2,922 | 64 | function p = if2_paths(version)
%if2_paths Canonical paths for the interface2 repo. Cross-platform.
%
% p = if2_paths(version) returns a struct with fields:
% .home — user home dir
% .data — IF2_DATA_ROOT, or ~/University of Michigan Dropbox/Richard DeFazio/data
% .sts — <data>/STS/STS... |
e3ac61e5495263d885eb800613d7beb2f445e0aca4ddf9c30b3ab70c7e094ae2 | MATLAB | 2,923 | 71 | function [optimization_results, params, model_collection] = smbo(params, model_collection, app_handles)
%% Description
% This is an implementation of a sequential model-based bayesian optimization
% Darik A ONeil, 04/10/2023
% At instantiation, we take the the valid_likelihoods we've already got
% We then form a sur... |
25d03e29d485e40447b28bc3f7839631641b99a2ade409159b83602911d425d1 | MATLAB | 2,926 | 88 | function [fracMissGauss,binsGauss,spikeCountsGauss,gaussCutoff] = getFractionMiss(amplitudes,nBins,makePlot)
% April 2024, RH based on bombcell's bc_percSpikesMissing()
% estimate fraction of missing spikes
amplitudes = double(amplitudes(:)');
%prep
if ~exist('nBins','var') || isempty(nBins)
nBins = 50;
end
if ~... |
d07e6b75b6640dd47c6f1ab7e55379d8407242bc526c9c0af5906d8711671e0d | MATLAB | 2,927 | 97 | function result=mahalanobis(x,locvct,varargin)
%MAHALANOBIS computes the distance of each observation in x
% from the location estimate (locvct) of the data,
% relative to the shape of the data.
%
% Required input arguments:
% x : data matrix (n observations in rows, p variables in columns)
% ... |
8bb29e4bd5b39916e75ad3f16c00e191fe293b3db183dc8b68b318309e763d2d | MATLAB | 2,929 | 52 | function TDATA=bsliang_Trandata(DATA)
% ¶ÁÈ¡ºÍת»»Êý¾Ýµ½´¦ÀíÊý¾ÝµÄ¸ñʽ
% ================================
% DATA structure:
% turn: L T S
% block:
% Id_Di BLOCK NAME NUMBER
% Id A T_CLEAR_ID 1
% Id B P_CLEAR_ID 2
% Id C ... |
0f7abd79d1d944bdbe5eeab85a448021ef48a4eabf1adf9e6953dd45961e7db0 | MATLAB | 2,930 | 94 | function avg = plot_pulsopower_summary(TB, tt, cfg)
cmap = struct();
cmap.lines = lines(7);
cmap.base = [0.8 0.8 0.8];
cmap.onset = 'k';
cmap.onset1 = [0.5 0.5 0.5];
cmap.powseg = cmap.lines([5 2 3],:);
% Calculations
pp = cat(3,TB{:});
avg.tt = tt;
avg.pulso = nanmean(pp,3)';
tmask = 100:200;
... |
1d8241403e22ff1ccee6b768b932668bbbf25a391312e265d8bf5f884f5e0e87 | MATLAB | 2,930 | 102 | function M = centeredmatrixfactory(m, n, rows_or_cols)
% Linear manifold struct. for optimization over matrices with centered cols
%
% function M = centeredmatrixfactory(m, n)
% function M = centeredmatrixfactory(m, n, 'cols')
% function M = centeredmatrixfactory(m, n, 'rows')
%
% Returns M, a structure for Manopt desc... |
95853a533f07aada131605a0b7161d0b3ad15dda835aaf956963763f8c0d5edc | MATLAB | 2,930 | 88 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.filter_name_list = cell(0);
zef.filter_file_list = cell(0);
zef.filter_parameter_list = cell(0);
if not(isfield(zef,'filter_zoom'));
zef.filter_zoom = 1;
end
if not(isfield(zef,'filter_epoch... |
7f3ce1d07484033ecf3142f4b156ee3bdbbf76dd2e4a93a44fb5ce250f8d2988 | MATLAB | 2,935 | 89 | function [newstatetimecourse,stats] = fitEquivUnsupervisedModel(X_train,Gamma,X_test,T_train,T_test)
% Given a precomputed TUDA model, this function estimates an equivalent
% unsupervised model - that is, the distribution oer only the data that
% best describes the state timecourse
%
% INPUT
% X_train: Data that the TU... |
00673ec0e0c1234a75798e894b0a737e3c786c5b9ca4be8ffb36e644f5e503e0 | MATLAB | 2,936 | 84 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if not(isfield(zef,'exp_ias_q'))
zef.exp_ias_q = 1;
end
if not(isfield(zef,'exp_ias_hyper_type'))
zef.exp_ias_hyper_type = 2;
end
if not(isfield(zef,'exp_ias_beta'));
zef.exp_ias_beta = 1.... |
a5c7ce984e4e2dda52c7f76914c52ddcfc090729851e32b620e7892992f900e6 | MATLAB | 2,937 | 86 | % zef.reconstructionTool.currentInfo=cell(1,5);
%
%
% if ~isfield(zef, 'reconstruction_information')
% zef.reconstruction_information=[];
% end
%
%
% if isfield(zef, 'reconstruction_information') && isfield(zef.reconstruction_information, 'tag')
% zef.reconstructionTool.currentInfo{1}=zef.reconstruction_informa... |
0670b017ccbaf795ed19e178b320c18c74926be6dd2751d09da4f4400eee6fa2 | MATLAB | 2,938 | 104 | function [stats]=sw_get_stats(dat,ev,opt)
%[stats]=sw_get_stats(dat,ev,opt)
if isfield (ev, 'auto')
ev=ev.auto;
end
histwin=10;% histogram window for averaging event properties in s
%% some descriptive stats---------------------------------------------------
% histogram, mean, std, var of propert... |
1d537e34efd1af84b0c6c3a138a811944c2617173afcf7a6b9a9d346740feb58 | MATLAB | 2,940 | 86 | function gamma = mymcs_gamma_yao2000 ( headmodel, order )
% Returns the Gamma series expansion for EEG leadfields.
%
% Use as:
% Gamma = mymcs_gamma ( headmodel, order );
%
% where:
% headmodel FieldTrip concentric spheres definition:
% headmodel.r Radius of the spheres.
% headmodel.cond Conduct... |
49a4491e4804f86e07042976725e433b9787a7df8808a7b9c3e41a0d41353cf5 | MATLAB | 2,942 | 148 | function zef = import_electrodes_callback(zef)
%
% import_electrodes_callback
%
% The callback called by Menu tool > Import > Import elecrodes. Adds the
% fields "sensors" and "s2_name_list" to the given zef struct, or overwrites
% them if they already exist. If the chosen input file could not be read, an
% error dialo... |
b0980e9e91cf528355117283981d19a12dcb6e81c9e678a5036e3e3b67ff6e32 | MATLAB | 2,945 | 96 | function hmm = obsupdate (T,Gamma,hmm,residuals,XX,XXGXX,Tfactor)
%
% Update observation model
%
% INPUT
% X observations
% T length of series
% Gamma p(state given X)
% hmm hmm data structure
% residuals in case we train on residuals, the value of those.
%
% OUTPUT
% hmm ... |
c6abefcfe7e3bb405e7817d6a85e87858dd8b18a5267e98e766b5018bf67734b | MATLAB | 2,955 | 66 | function [performance] = calculate_performance_given_threshold(log_likelihood_by_frame, node, true_labels, data_index,...
threshold)
% prune ll
log_likelihood = log_likelihood_by_frame(node, data_index);
% prune labels
true_labels = true_labels(data_index);
[fpr, tpr, threshold, AUC, operating_point] = perfcurve(... |
c0d2782c4d7958d3f8737430c91a0b154090bc5eb44a47405483c55b2bd0458f | MATLAB | 2,959 | 51 | zef_data = zef_wireframe_creator_app;
zef_assign_data;
if not(isfield(zef,'wireframe_edge_threshold'))
zef.wireframe_edge_threshold = 1.2;
end
if not(isfield(zef,'wireframe_printer_resolution'))
zef.wireframe_printer_resolution = 0.15;
end
if not(isfield(zef,'wireframe_relative_permittivity'))
zef.wirefr... |
abdd743945614c68ff1810e6095c5d8d3f6ed32381877955d8fe3e9d068c534e | MATLAB | 2,960 | 104 | function zef_play_cdata(varargin)
warning('off');
if evalin('base','exist(''zef'',''var'');')
zef = evalin('base','zef');
else
zef = [];
end
show_frame_number = 0;
loop_count = 1;
if not(isempty(varargin))
loop_count = varargin{1};
if length(varargin) > 1
show_frame_number = varargin{2};
... |
605f350814c48b61430184402ab29b1401c53049116095e2da1031cef8e600e7 | MATLAB | 2,964 | 66 | function [inmat_s_rm_sp_rlr,inmat_s_rm]=bsliang_tmssham_lr_out(TDATA,inmat,LT_ind,outTag,is_rmsd)
% is_rmsd: ÊÇ·ñÈ¥³ý3SD
% ±ê×¼»¯£¨¡÷TMS=(rTMS-Sham)/Sham£©£¬·Ö×óÓÒÄÔ£¬Êä³öSPSS¸ñʽ
% inmat£º block(4)*turn(5)*subj(197)
% LT_ind£ºlarynx tongue index
% outTag£ºÊä³öÓÃÓÚSPSS·ÖÎöµÄmatÎļþÃû
% Êä³ö£ºinmat_s_r... |
9b7a672df9f3ec3db89fdc1e9204cd19e3e7d8444adabf86f99fd035a534fe72 | MATLAB | 2,971 | 87 | %% 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 instance of KalmanInverter with the method-... |
a0b5321639dce50000428d41aa75a51250de50a500e595491e742cf3880498fc | MATLAB | 2,972 | 121 | function result = cvmultnet(object, lambda, x, y, weights, offset, foldid, ...
type, grouped, keep)
if nargin < 10 || isempty(keep)
keep = false;
end
typenames = struct('mse','Mean-Squared Error','mae','Mean Absolute Error',...
'deviance','Multinomial Deviance','class','Misclassification Error');
if strc... |
6ee419fcbfe33cc1a16af500d208ac80d17615cf1f345483fa886f7c75a2fa1a | MATLAB | 2,984 | 70 | %This is the startup script for CSM app. One must add this as launch
%script to zeffiro_plugins file:
%Beamformer, inverse_tools, zef_CSM_start
zef.CSM = CSM_app;
%_ Names of methods that are included in app _
zef_csm_names = {'dSPM',
'sLORETA',
'3D sLORETA',
'Sparse Bayesian Learning'
};
zef.CSM.csm... |
94219cabcd336efe5776221e5f73616a2def64b6b39efb5d90390387c4141472 | MATLAB | 2,987 | 136 | clear all
close all
clc
addpath('./tools/')
%% test for network size, training length,
% reset time and noise level
% please record the rmse and running time
% network_set = round(linspace(20, 500, 10));
% training_length_set = round(linspace(20000, 200000, 10));
network_set = round(exp(linspace(log(20), log(250),... |
33eeb9eb5b339248b46d75d27889c36b98f68969816794fd96bc9479a994da7e | MATLAB | 2,991 | 88 | %% 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 instance of KalmanInverter with the method-... |
33f5887e710938c4f137f2b60e50e7078de434e8dc160d86c06a2f2136d6317b | MATLAB | 2,997 | 53 | %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.RAPMUSIC = RAPMUSIC_app;
%_ Initial values _
zef.RAPMUSIC.RAPMUSIC_leadfield_lambda.Value = '1e-3';
zef.RAPMUSIC.inv_snr.Value = '30';
zef.RAPMUSIC.RAPMUSIC_n_dipoles.Valu... |
d63024a616cd89d5bd9e20b49026c8cb1e685f45e59595e77379fa1caace566e | MATLAB | 3,000 | 83 | function zef = zef_disable_box_ROIsource(zef)
shapeValue = zef.h_synth_source_ROI_style.Value;
Ori_style = zef.h_synth_source_ROI_dipOri_style;
Ori_options ={ 'Custom','Max SVD direction','Min SVD direction','Normal to cortex','Normal to patch surface'};
switch shapeValue
case 1 %flat
set(zef... |
59fea850e8931c4c28bc066b5c7dd1d7b4a5e39fdde58f7dad22377cc645f6ff | MATLAB | 3,003 | 83 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef_arrange_windows(varargin)
arrange_mode = 'on-screen';
arrange_target = 'windows';
arrange_function = 'tile';
if not(isempty(varargin))
arrange_function = varargin{1};
if length(... |
d61116f896de034581def1a525103d62c831cda2f8c4735d68d6ce8b54415989 | MATLAB | 3,004 | 85 | function [newtree, listOld, listNew] = zef_dataBank_reorderTree(tree)
%reorders the tree nodes so that the numberings starts at 1 and continues
%without jumping
%this is needed to rebuild the tree when things were deleted
%derive new hashList on this level
array=[];
arrayToGive=1;
N=length(fieldnames(tree));
listOl... |
e827a4e55a41724b6ef575027b2e9b122957e034ffde3754f11446e77e0cfeb2 | MATLAB | 3,004 | 126 | function [] = func_plot_figures(control_infor, output_infor, val_length, plot_movie)
data_pred=output_infor.data_pred;
q_pred=output_infor.q_pred;
qdt_pred=output_infor.qdt_pred;
q2dt_pred=output_infor.q2dt_pred;
tau_pred=output_infor.tau_pred;
q_control=control_infor.q_control;
qdt_control=control_infor.qdt_control;... |
036e3c5d5f98350e05443a7bafdd1d40d7f8bc76fda89f326ade778397dd2873 | MATLAB | 3,009 | 103 | function Model = update_spike_model(state)
% update noise variance & spike amplitude/bias for spike model
% ---
% Model = update_spike_model(state)
% --- Model parameters (update parameter)
% Model.a
% Model.b
% Model.sx
% --- amplitude & bias estimation
% E = sum((y(t) - a*g(t) - b)^2)
%
% y0 = mea... |
5a79f06fd747682b01313b53f37d5cb173ade77c46d92578767bae4a1f21326f | MATLAB | 3,023 | 74 | function [log_lh,mahalaD]=WeightedCondDensity(positions, mu, weight, Sigma, p, sharedCov, CovType)
%WDENSITY Weighted conditional density and mahalanobis distance.
% LOG_LH = WDENSITY(...) returns log of component conditional density
% (weighted by the component probability) of X. LOG_LH is a N-by-K matrix
% LO... |
ac78adb8848c8dd03cfc22f2183a6befaa65f01c62f84831980e21ba6e1c6f4c | MATLAB | 3,024 | 71 | function [] = threshold_voxel_based_structural_connectivity_matrices(subject,dataset,h5_file_ID)
% The purpose of this script is to take the structural connectivity matrices generated by MITTENS
% (and converted into .mat format) and apply a density-threshold on them (currently 70%).
%
% Requirements:
% 1. The Python ... |
2e724fd72e44f69c1cf2ceffb303ac6797f6a73ef5349f2a26e9fe6a2d812eca | MATLAB | 3,029 | 97 | function [psd_tf,coh_tf,pdc_tf] = hmmtimefreq(spectra,Gamma,center)
% obtains a time-frequency representation of the power spectra density,
% coherence and PDC - the estimations of which (contained in 'spectra') had to be
% estimated with hmmspectramar or hmmspectramt. If coherence or PDC are
% missing from the estimat... |
4e663e5cdacbe733baa6f42b6f8848b5ae4a025e5d219ff26e9e2993f23a3aae | MATLAB | 3,030 | 88 | function install()
% Function to install the latest version of the toolbox.
% Make options for webpage - timeout after 2 minutes
webopts = weboptions('Timeout',120);
% Get path to toolbox and current version
[path,currentversion] = microstate.functions.toolbox_path ;
% Get latest version
tmpfile = sprintf(... |
b1c3efc178053859021fea04a7c89f043012f5a00e5def9cec0fa9d749298f3e | MATLAB | 3,034 | 155 | function [y_1, y_2, y_3, b_coord, volume] = zef_volume_scalar_matrix_uFG(nodes, tetra, h, x_1, x_2, x_3, u_field, scalar_field, i_node_ind, b_coord, volume)
%
% zef_volume_scalar_matrix_uFG
%
% TODO: Sampsa should document this.
%
% Inputs:
%
% - nodes
%
% TODO: explanation.
%
% - tetra
%
% TODO: explanation.
%
% -... |
2fc99c7d80396e879d3779f4ad27c48082dd85867a27e9537816174fdb20a654 | MATLAB | 3,036 | 101 | function [tracedtensor] = diagsum(tensor1, d1, d2)
% C = DIAGSUM(A, d1, d2) Performs the trace
% C(i[1],...,i[d1-1],i[d1+1],...,i[d2-1],i[d2+1],...i[n]) =
% A(i[1],...,i[d1-1],k,i[d1+1],...,i[d2-1],k,i[d2+1],...,i[n])
% (Sum on k).
%
% C = DIAGSUM(A, d1, d2) traces A along the diagonal formed by dimensions... |
fc6f3e7a42dbdae220990fc3f2aad8e526b5b04f2b7482ce88a9cdde1474d272 | MATLAB | 3,047 | 82 | function [Lsamps,Rsamps,ITDt,dur_real] = GetMovingNoiseBand(params)
global ChanConfigInfo %This global variable is set by the user at startup, and determines which channel is considered "contra-lateral".... taking into account the recording side, and the connections between channels and ears (i.e., this should be ro... |
03220351bcffc233aa446eecfe05b005b27b8cc2a23674db2fcda8a1599ec19a | MATLAB | 3,059 | 86 | %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) '... |
e2111f7363f01c2e6c8434bd608a8a392d382b344339771815d6be82f9b79516 | MATLAB | 3,060 | 86 | function [y,ty,x,tx] = vl_ode_wrapper(P,M,U,integrator)
% Wrapper to enable SPM or Matlab integrators to be used with
% variational_laplace.m.
%
% P - model parameters [Np x 1]
% M.x - starting values for hidden states [Nx x 1]
% M.ns - number of samp... |
f64f97d67fa7e36790b3dee9bf0fa3ea56a90a31dc21d2b24c7f206440c4fc64 | MATLAB | 3,062 | 80 | %Copyright © 2018- Joonas Lahtinen, Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [z] = SESAME_inversion(void)
h = waitbar(0,['SESAME iteration.']);
[s_ind_1] = unique(evalin('base','zef.source_interpolation_ind{1}'));
sampling_freq = evalin('base','zef.in... |
63d60e0f3f07524022c350ca5c6d6e831397ccec0a91e1f372fe1232713558ca | MATLAB | 3,077 | 78 | % script to test sleepwalker ripple detection
close all;
clearvars;
%% run ripple detection test
%% test loading data: add your data location here:
pathfile= 'data/csc_CA1_rest.ncs';
%load data
[dat] = sw_load_LFP (pathfile);
figure(1); clf
plot(dat.ts, dat.csc,'k');
pause(2)
close all
%% settings for ripple detect... |
f70fcf1db30297ead76777b5df23c0506caa192b7a22c098da4cd7ad8b11ea03 | MATLAB | 3,083 | 28 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef_data = zeffiro_interface_lf_bank_tool;
zef.fieldnames = fieldnames(zef_data);
for zef_i = 1:length(zef.fieldnames)
zef.(zef.fieldnames{zef_i}) = zef_data.(zef.fieldnames{zef_i});
end
clear zef_... |
8ea61ddf185806a2fbe22aa611b16a7967fb21605e7c4f3caa98194ff232dc64 | MATLAB | 3,084 | 71 |
function Read_fMRI(varargin)
% Converts the HCP subject data as provided by the MIPlab and stored in
% functional_HCP_folder (external drive) in a matrix N x T per session
% where N is the number of voxels and T is the time points.
% Results are still saved on the external drive
% to avoid undesired c... |
2f9cb9b1c43173deb61057746dcbcf06a6439b4e42418bec11c57df7567157b5 | MATLAB | 3,091 | 102 | function M = skewsymmetricfactory(n, k)
% Returns a manifold struct to optimize over k skew-symmetric matrices of size n
%
% function M = skewsymmetricfactory(n)
% function M = skewsymmetricfactory(n, k)
%
% Returns M, a structure describing the Euclidean space of n-by-n
% skew-symmetric matrices equipped with the stan... |
a10881aed5ee057ef136d460bb00847db79fb4078061bd9f7c11838437d5e662 | MATLAB | 3,094 | 84 | function checkretraction(M, x, v)
% Check the order of agreement of a retraction with an exponential.
%
% function checkretraction(M)
% function checkretraction(M, x)
% function checkretraction(M, x, v)
%
% checkretraction performs a numerical test to check the order of agreement
% between the retraction and the expon... |
020e6b9bb3677b7b2272f5f3fb4808bc57450a5112be938f3653ae9548d8200e | MATLAB | 3,095 | 75 | function [Predictions, SegTime] = SegmentVol(DataVol,NumFrames)
% The segmentation is done 2D slice-wise. Speed is dependent on number of frames you can push 'NumFrames'. This is dependent on GPU size. Please
% try different values to optimize this for your GPU. In Titan Xp 12GB, 70 slices were pushed giving segmenta... |
b23cd64a65ee3aa269eac35dcf6ed4b12a7e3caf0c66e8248edceb3199ad67de | MATLAB | 3,098 | 79 | function bsliang_saveDDMform(TDATA,group_indx,save_path)
% ¶ÁÈ¡ºÍת»»Êý¾Ýµ½´¦ÀíÊý¾ÝµÄ¸ñʽ
% ================================
% DATA structure:
% turn: L T S
% block:
% Id_Di BLOCK NAME NUMBER
% Id A T_CLEAR_ID 1
% Id B P_CLEAR_ID 2
... |
7752d87b74b1ffe9e8d07d9cbe13a93b1f510473d5f3c7d2c76f06c629a1c4d7 | MATLAB | 3,099 | 125 | %% Copyright © 2025- Joonas Lahtinen
function [z_vec, self] = invert(self, f, L, procFile, source_direction_mode, source_positions, opts)
%
% invert
%
% Builds a reconstruction of source dipoles from a given lead field with
% the Kalman filtering method.
%
% Inputs:
%
% - self
%... |
b4a384793c258995744b5d9b1207d35f4bcdc18691490fa4d445ad309c2bcf20 | MATLAB | 3,099 | 101 | function [xfigure, yfigure]=axescoord2figurecoord(varargin)
% AXESCOORD2FIGURECOORD Transform axes coordinates in current
% figure units coordinate to the figure for annotation location
% [xfigure, yfigure]=axescoord2figurecoord(xaxes,yaxes)
% [xfigure, yfigure]=axescoord2figurecoord(xaxes,yaxes,handle_axes)
%
% Ex.
%... |
538a99123863bced0b7b9737374b82dba345adbaa7c07ff44db79ee5a8aa8453 | MATLAB | 3,100 | 111 | %% 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.
%
... |
4655d95ee15355a5a7e64d401e665c2ceb0eccbfdd5a4f9f1a21713c10867287 | MATLAB | 3,116 | 74 | function [frame_log_likelihood] = calculate_log_likelihood_blockwise(node_potentials, edge_potentials, logZ, ...
samples, blocks)
%Function to compute frame-wise log_likelihood
%blocks=2;
%Initialize
[sample_count,nodeCount] = size(samples);
L = floor(sample_count/blocks);
finalPartition = sample_count-(L*(blocks... |
6c3bddf0f89e89e2d3e022b249355d1f0b3e91806b03914081695d2afdda066d | MATLAB | 3,125 | 73 | function zef = zef_strip_tool_update(zef)
struct_aux = zef.([zef.current_sensors '_strip_cell']){zef.strip_tool.current_strip};
struct_aux.tip_point = [str2num(zef.strip_tool.h_tip_point_1.String) ; ...
str2num(zef.strip_tool.h_tip_point_2.String) ; ...
str2num(zef.strip_tool.h_tip_point_3.String) ];
struct_... |
193b2ff7d95700afc2bcec5d8846ab1ae8b4d5a002fbd0cdc2b4ac7e7743199a | MATLAB | 3,133 | 116 | function [ ...
out_deep_nodes, ...
out_deep_node_inds, ...
out_deep_tetra, ...
out_deep_tetra_inds ...
] = zef_deep_nodes_and_tetra( ...
in_nodes, ...
in_tetra, ...
in_volume_inds, ...
in_acceptable_depth_mm ...
)
% Documentation
%
% Produces the nodes and tetra which are deep e... |
214a2618f7cf71661b4c35c4297585ef646a23b79fad4bebfb2e532c0eb5f814 | MATLAB | 3,134 | 105 |
%{
This script contains example commands for demonstrating the log-Gaussian
inference routines implemented in this folder. This implementation is
slightly slower and less complete than the Python implementation.
Key files:
- NORMALIZEPOSITION(XY,MARGIN): This converts XY path data into normalized
[0,1)² coordin... |
eb5b049bcab460aa4ca61f7f8da4cd8e3b9a0c577523dbd9e5e6d05a2625bdb2 | MATLAB | 3,134 | 100 | function obj = stats_markov(obj)
% Calculate Markov matrix and Markov statistics
% Check inputs
if isempty(obj.label)
error('To calculation Markov property, property label is required')
end
% Number of states and number of samples
% Number of states
label = obj.label ;
... |
e2dec612f59290512dd32eae6dac5cb75be531d117d4fcd3a3d98f6c413bc054 | MATLAB | 3,136 | 91 |
% deprecated! XXX RUN COMBINE ROIS FIRST!!!!!!!!!!!!!!!
first_file=0; %45; % 34; % 0;
% 20240722 hard coded to use S.hROI.DFoF0!
projection_type = 'DFoF0';
stack_type = 'Smoco';
% get dir
path = uigetdir('C:\Users\defazio\Documents\data\complete');
% get list of files in dir
codekey = 'complete*.mat';
if ismac
... |
df9502bffaba73dfdc2c1c682e94058fa76934cbc77b887bb4620a09fad6eb08 | MATLAB | 3,142 | 160 | function [Model] = estimate_spike_init(tau, Data)
% ----- Initial Estimation of model parameters
% using peak of windows
% [Model] = estimate_spike_init(tau, Data)
% Model.opt_threshold = opt_th;
plot_mode = -1;
if plot_mode >= 0
fprintf('--- Estimate_spike initial step\n')
end
Ntau = length(tau... |
f1edf6be92626d07fb4c34b8533fc9d59ba90155bbb4e420b24aa6e213f5b4de | MATLAB | 3,142 | 102 | function B = doubly_stochastic(A, maxiter, mode, checkperiod)
% Project a matrix to the doubly stochastic matrices (Sinkhorn's algorithm)
%
% function B = doubly_stochastic(A)
% function B = doubly_stochastic(A, maxiter)
% function B = doubly_stochastic(A, [], mode)
% function B = doubly_stochastic(A, maxiter, mode)
% ... |
ddfba1f43262c3c05550fa3d862058ebebc5a522602cf8b99fd82f6ad09f3cdc | MATLAB | 3,149 | 78 | %% 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... |
f256b4e33ab5a646e37cdf442951bb51fa9a529c63905bbcc84f63c7096b6bee | MATLAB | 3,158 | 123 | function [Points, Tri, Normals, Scalars, LUT] = VTKPolyDataReader(filename)
% Usage:
% [Points, Tri, Normals. Scalars, LUT] = VTKPolyDataReader(filename)
% Copyright modified by Jean Dumoncel
% Output:
Points = []; % set of vertices
Tri = []; % set of triangles
Normals = []; % set of normals
Scalars = []; % set ... |
86c8cc6639ef1cde412d7c64ace2e9e34fbce61ffbebde01e50c244062be3e84 | MATLAB | 3,159 | 104 | function hmmproj = project_hmm(hmm,A,B,V)
% Projects an hmm estimation from PCA space to original space
% A : standard PCA
% B : PCA on MAR (per order)
% V : PCA on regressors (all orders)
% using the matrix A/B/V
% it projects the HMM-MAR parameters to the space spanned by A/B/V
% it ignores the covariance of W, just... |
471cf726a4c06a7a83a873e2c1969e57be3cd5adc6068506797a581bd957ea29 | MATLAB | 3,162 | 64 | if size(zef.resection_points,1) > 1
A=alphaShape(zef.resection_points(:,1), zef.resection_points(:,2), zef.resection_points(:,3),3.4);
[AF, AP]=alphaTriangulation(A);
dist_resection = zef_distance_to_resection(z_ref_points,AP,AF);
dist_final_resection_max = zef_distance_to_resection(z_final_max_point,AP... |
3faba3457785e54782023cdfaa3974fdf6414b46f735ed9660af421e048e37ca | MATLAB | 3,172 | 113 | function hmm = hsupdate(Xi,Gamma,T,hmm)
%
% updates hidden state parameters of an HMM
%
% INPUT:
%
% Xi probability of past and future state cond. on data
% Gamma probability of current state cond. on data
% T length of observation sequences
% hmm single hmm data structure
%
% OUTPUT
% hmm single hmm da... |
0171d677a0ca1010c6dd7603e71524732d5da89e5166e1ad231be68fbf1b16b3 | MATLAB | 3,173 | 111 | function obj = stats_syntax(obj)
% Calculate syntax matrix
% Check inputs
if isempty(obj.label)
error('To calculation microstate syntax properties, property label is required')
end
% Get microstate transitioning sequence
transition = diff(obj.label) ~= 0 ;
label = [obj.lab... |
3b6f8c55f7bde3ea395869f512dde803fb1d86da88ea26da37554da3b5114137 | MATLAB | 3,177 | 90 | function [ICs mixMat wavePacks] = applyOnlineICAmethodWaveNowsobi( EEGdata )
%
% applyOnlineICAmethodWave
%
% Apply an online (has to be fast) ICA method.
%
% Inputs:
%
% EEGdata - N x M matrix of N channel by M sample EEG.
%
% Outputs:
%
% ICs ... |
1eaccdb144c861df3aaebacb96eb6c6d657df28aa36455e2359c13167873c13b | MATLAB | 3,178 | 132 | function zef_source_tree_selection_changed(~, ~, ~)
zef = evalin('base','zef');
sel = zef.h_source_tree.SourceTree.SelectedNodes;
if isempty(sel)
zef.h_source_tree.SourceParameters.Data = {};
return;
end
nd = sel(1).NodeData;
if isempty(nd) || (isstruct(nd) && isempty(fieldnames(... |
8aa4deefa205b87d0639e029615ee5ec0f98ab560eb079d47395606342f0b0c3 | MATLAB | 3,181 | 75 | function [avg_log_likelihood] = compute_avg_log_likelihood_blockwise(node_potentials, edge_potentials, logZ, ...
samples, blocks)
%Function to compute frame-wise log_likelihood
%blocks=2;
%Initialize
[sample_count,nodeCount] = size(samples);
L = floor(sample_count/blocks);
finalPartition = sample_count-(L*(blocks... |
778f44a67bb8f34ab1ee2a822d3181e1f7963cfeb06ad76f544eca4c6fc70a4a | MATLAB | 3,182 | 98 | function sLabels = ETP_SetLabels(hObject,eventdata)
%get globals
global sETP;
global sFigETP;
global ETP_sLabels;
global ETP_matAllIm;
global ETP_matAllImOrig;
%% check bounds
intTempAvg = str2double(sFigETP.sHandles.TempAvg.String);
if ~isnumeric(intTempAvg) || intTempAvg < 1
sFigETP.sHandles.TempAvg.St... |
21285a63714a1682f93ad8d9c76de641dfe1e3300962df494c6d9849130a11c8 | MATLAB | 3,185 | 81 | function plot_model_graph_structure_style_2(app)
cla(app.model_structure);
app.model_structure.NextPlot = 'replacechildren';
% 1
neuron_id = app.HighlightedNode.Value;
rois = app.rois;
num_rois = length(rois.xpix);
best_model = app.best_model;
edge_mat = best_model.structure(1:length(rois.xpix), 1:length(rois.xpix))... |
92bf2c9555e95f67ba163ba2772ae47e81705dca6bd4a95ce5f4cc6031b2c320 | MATLAB | 3,199 | 68 | classdef SolverFactory2
% ==================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn\+nnet\+internal\+cnn\+solver
% ==================================================
% SolverFactory Class for creating solvers.
% Copyright 2017 The Math... |
74b42ae46f8415e6fe115e84e36f5f501e3dfc4f35a25ca8c3267046774d991a | MATLAB | 3,204 | 69 | classdef SolverFactory2
% ==================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn\+nnet\+internal\+cnn\+solver
% ==================================================
% SolverFactory Class for creating solvers.
% Copyright 2017 The... |
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