sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
6cc1ac36a2ec789e4aa05ca01c43c0fd19b1ee8be21ab8c9c48b296f14d48a9f | MATLAB | 282 | 10 | function zef_add_dof_space
%This function plots the degrees of freedom
h_axes = evalin('base','zef.h_axes1');
%axes(h_axes);
hold on
source_positions = evalin('base','zef.source_positions');
scatter3(source_positions(:,1),source_positions(:,2),source_positions(:,3),'filled')
end
|
2a4afb97f803bb8b6073976591d9fb6df50ecf18f5bf9c18d2b8bd26c3ca64e7 | MATLAB | 283 | 8 | function vecY = logfitfun(vecParams,vecX)
%logfitfun Logarithmic function with scaling factors for fitting
% Syntax: vecY = logfitfun(vecParams,vecX)
%params; x-offset, x-scaling, y-offset, y-scaling
vecY = vecParams(3)+vecParams(4)*log(vecX*vecParams(2)+vecParams(1));
end
|
7bfffa6d2d89cb7bec8c93f00d87c5215dcb43e27c6fdb211cebc5dd1e881ef9 | MATLAB | 284 | 10 | % THIS FUNCTION IS PRIVATE AND SHOULD NOT BE CALLED BY OUTSIDE CODE!
%
function [] = ReceiveOK( sm, cmd )
line = CalinsNetMex( 'readline', sm.handle );
if( ~contains( line, 'OK' ) )
error( 'After cmd [%s] got [%s] but expected ''OK''.\n', cmd, line );
end
end
|
1aa8c63a141d31731bf95f69f6beac5a7ccb77ae073a176b78e8440171604fef | MATLAB | 285 | 12 | function x_transform = transform_clusterstat(x,modality)
switch modality
case 'eeg'
x = x-mean(x,2) ; % re-reference to average
case 'meg'
% do nothing
case 'source'
x = abs(x) ; % .^2 ; % set to magnitude
case 'ampenv'
% do nothing
end |
9f81911967e6c492bdd742eda9b148a237eb61323ae3cd4fea592972d05d84ee | MATLAB | 285 | 12 | function x_stdft = stdft(x, N, K, N_fft)
frames = 1:K:(length(x)-N);
x_stdft = zeros(length(frames), N_fft);
w = hanning(N);
x = x(:);
for i = 1:length(frames)
ii = frames(i):(frames(i)+N-1);
x_stdft(i, :) = fft(x(ii).*w, N_fft);
end
|
f2b58b8f48d744f37b690ad7e1f06f5e5d6c5b8d54ea51555666ba163664ac7e | MATLAB | 286 | 14 | function zef = zef_strip_tool_open(zef)
if not(isfield(zef,'strip_tool'))
zef.strip_tool = struct;
zef.strip_tool.strip_current_id = 1;
end
zef.strip_tool.current_strip = 1;
zef = zef_strip_tool_window(zef);
zef = zef_strip_tool_init(zef);
zef = zef_strip_tool_update(zef);
end
|
081d0d0df0878dbea40e7d08ab98f01b8b68454b65798aa9f2c6d7bea1d77138 | MATLAB | 287 | 9 | function vecY = gnmgauss(vecX,vecParams)
%gnmgauss Wrapper with scale-parameter for normal distribution
% vecY = gnmgauss(vecX,vecParams)
%
%Function:
%vecY = vecParams(1)*normpdf(vecX,vecParams(2),vecParams(3));
vecY = vecParams(1)*normpdf(vecX,vecParams(2),vecParams(3));
end
|
4fbb47a550c353f878686b54a6d82f74d3a7e41f8c57fb8f6e73b5f6d3235d74 | MATLAB | 287 | 14 | function GammaInit = initGamma_seq(T,K)
GammaInit = zeros(sum(T),K);
for j = 1:length(T)
ind = (1:T(j)) + sum(T(1:j-1));
assig = ceil(K*(1:T(j))./T(j));
Gammaj = zeros(T(j), K);
for k = 1:K
Gammaj(assig==k,k) = 1;
end
GammaInit(ind,:) = Gammaj;
end
end
|
6f66cd0e8317097264058a6c06513ed6ddffafb2cc247a60601a6d88035b6d6a | MATLAB | 287 | 10 | %trim frames
function [ trimmed, tTarray ] = trimArray( array, tarray, startindex, endindex )
tic
trimmed = array;
tTarray = tarray;
trimmed(:,:, startindex : endindex )=[];
tTarray(:,startindex : endindex )=[];
str = append('trimming took ', num2str(toc), ' seconds' );
disp(str);
end |
0f04438c149d52b604214720bc71d2b86bd1a3bb5211cc97b679aa25e45d5dbf | MATLAB | 288 | 15 | function retrieve_gui_colors(app)
newcolors = [
0.47 0.25 0.80
0.25 0.80 0.54
1.0000 0.3098 0.2941
0.0745 0.6235 1.00
1.00 0.54 0.00
0.6510 0.6510 0.6510
1.00 0.0745 0.6510
0 0.2980 0.6000
];
app.newcolors = newcolors;
end |
c427eed0dc052be616b55ea93065970855f18e6e3d3c4b1defa6eea7f8e208a6 | MATLAB | 288 | 12 | function x_stdft = stdft(x, N, K, N_fft)
frames = 1:K:(length(x)-N);
x_stdft = zeros(length(frames), N_fft);
w = ml_hanning(N);
x = x(:);
for i = 1:length(frames)
ii = frames(i):(frames(i)+N-1);
x_stdft(i, :) = fft(x(ii).*w, N_fft);
end
|
e5f3bfc3bedd72b3d49f43ea4734c5a0ecf9ad1909f881132f3b108cbcc821d6 | MATLAB | 288 | 9 | % List of open inputs
nrun = X; % enter the number of runs here
jobfile = {'/home/mfromano/Research/mri-pet/image_processing/mask_mni_brain_job.m'};
jobs = repmat(jobfile, 1, nrun);
inputs = cell(0, nrun);
for crun = 1:nrun
end
spm('defaults', 'PET');
spm_jobman('run', jobs, inputs{:});
|
877afbdd9b06c4bc450c7194c2e8c38b78e34fbed4b939dc8af6f3c1a8b53974 | MATLAB | 289 | 11 | function []=zef_callbackstop(src,~)
if ~src.Value
evalin('base',[ num2str(src.Value),';'])
set(src,'foregroundcolor',[0 0 0]);
set(src,'string','Stop');
else
evalin('base','zef.stop_movie=1;') ;
set(src,'foregroundcolor',[1 0 0]);
set(src,'string','Stopped');
end
|
653f912633a2c6dcf77506bb7ba9612dcf00a7d623342a7a6c775b21fdca0762 | MATLAB | 290 | 11 | function th = threeshold_estimation(distance,method)
if nargin < 2
method = 'mean';
end
switch method
case 'mean'
th = mean(distance)+2.5*std(distance);
case 'median'
th = median(distance)+2.5*1.4826*mad(distance,1);
end
|
b33c2b70b6b1cca55357132aed3ad4539536c90919cf1bf4d05bd8ff57753777 | MATLAB | 290 | 13 | function [Y] = vl_nnunpool(X, Ind, sizeY, varargin)
% forward mode
if(isempty(varargin))
Y = gpuArray.zeros(sizeY(1), sizeY(2), size(X, 3), size(X, 4), 'single');
Y(real(Ind+1)) = X;
% backward mode
else
DZDX = (varargin{1});
Y = reshape(DZDX(Ind+1), sizeY);
end
end
|
b3c99bd2ddab0f2023f7b21d8b873244804d07bc76b5b91bd2e575e19284be6e | MATLAB | 290 | 11 | function strDate = datemod(strFile)
%datemod Returns last modified date for file
% strDate = datemod(strFile)
try
sDate = System.IO.File.GetLastWriteTime(strFile);
strDate = sprintf('%04d-%02d-%02d',sDate.Year,sDate.Month,sDate.Day);
catch
strDate = 'Unable-to-read';
end
end
|
bc5759824601bf4d4f7e2b89d46c2935103fcd32f67a63afb017feed001e69cc | MATLAB | 290 | 16 | function [zef] = zef_turn_compartment_onoff(zef,compartment_onoff_vec)
c_t = zef.compartment_tags;
n_c_t = length(c_t);
% if isempty(compartment_onoff_vec)
compartment_onoff_vec = ones(1,n_c_t);
% end
for i = 1 : n_c_t
zef.([c_t{i} '_on']) = compartment_onoff_vec(i);
end
end
|
16f8ccedd251c10b3cb27f95159de0b2f8627b1713327a5cde380a11e6c7bb28 | MATLAB | 291 | 10 | function vecMahal=getMahalCell(cellXY,matThisCovInv)
%UNTITLED8 Summary of this function goes here
% Detailed explanation goes here
%get number of trials
vecMahal = cellfun(@calcMahal,cellXY);
function dblMahal=calcMahal(vecXY)
dblMahal = vecXY * matThisCovInv * vecXY';
end
end
|
f7fd761bc2d3e56166999dbc6bec36ced677f6b7a4b95e398a74d0854b960983 | MATLAB | 291 | 5 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.filter_pipeline = zef.filter_pipeline([zef.filter_pipeline_selected setdiff([1:length(zef.filter_pipeline)],zef.filter_pipeline_selected)]);
zef_update_filter_tool;
|
6149a8c7df494c45dfad47fc92ad63ff7f16c2c2bbdbb556dc161ac84075a7da | MATLAB | 292 | 14 | function [udf] = secondary_validation_udf(udf)
u = unique(udf);
for uu = 1:length(u)
assert(round(u(uu)) == u(uu), 'UDF must contain only integers');
end
% make sure it's binary, if it's a vector of states then one-hot encode
if length(u)~= 2
udf = quick_expand_udf(udf);
end
end
|
86fc9cccbd0da60e54cc8ed4bf93e2f2b92f3db025763918f12732f977819c92 | MATLAB | 292 | 10 | function y=minf(pab,papb)
% Used by the mutual information function (you can compile this to your
% machine using the Matlab coder if you want to speed up the algorithm even
% further).
I=find(papb(:)>1e-12 & pab(:)>1e-12); % function support
y=pab(I).*log2(pab(I)./papb(I));
end |
8d3ee88ec22a9691fe9ddf5c314a96de9fbd9f71d517982e89313789e91dc169 | MATLAB | 292 | 6 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.filter_pipeline = zef.filter_pipeline([setdiff([1:length(zef.filter_pipeline)],zef.filter_pipeline_selected) zef.filter_pipeline_selected]);
zef_update_filter_tool;
|
da9d419ecb8bf52b439338c4308cc7fef21b2d111208ebf5ab8f5e013d00d4e6 | MATLAB | 294 | 10 | % boolval = IsUserOrder( myobj, streamID )
%
% Returns 1 if graphs currently sorted in user order.
%
% This query is sent only to the main Graphs window.
%
function [ret] = IsUserOrder( s, streamID )
ret = sscanf( DoQueryCmd( s, sprintf( 'ISUSRORDER %d', streamID ) ), '%d' );
end
|
e440674d42c12aed7f8ece763e35ff298448d392410e7f2bea69364547b94b5f | MATLAB | 294 | 4 | writecell(zef.h_system_settings_table.Data,[zef.program_path '/profile/zeffiro_interface.ini'],'FileType','text');
for zef_i = 1 : size(zef.h_system_settings_table.Data,1)
evalin('base',['zef.' zef.h_system_settings_table.Data{zef_i,3} '= zef.h_system_settings_table.Data{zef_i,2};']);
end
|
fd80991820111616d6925a726a4d96e5405f9d948a1482ba27c69360f74b4f05 | MATLAB | 295 | 12 | function [app, status] = variable_loader(app, filename, key)
try v = load(filename, key);
app.(key) = v.(key);
msg = strcat(['Located ', key]);
update_log(app, msg);
status = 0;
catch
msg = strcat(['Unable to Retrieve ', key]);
update_log(app, msg);
status = 1;
end
|
31ceb3ee5897d86f3645f6f9a1f2b648d146aabc383bf9ea01a44d6d49a2161d | MATLAB | 297 | 13 | function norm = zef_L2_norm(arr, dim)
% Calculates the L2-norm of a given array arr along a given dimension dim.
% If the dimension is not given, calculates the norm assuming arr is a
% vector.
if nargin == 2
norm = sqrt(sum(arr.^2, dim));
else
norm = sqrt(sum(arr.^2, 'all'));
end
end
|
60e06bc3807ee4076113dbeb3c261c6759f2b01269085946ca912c4f0fd97896 | MATLAB | 297 | 15 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
function [y] = mat_vec(R,x,gpu_extended_memory)
R = gpuArray(R);
x = gpuArray(double(x));
y = R*x;
if (ismember(gpu_extended_memory,[0 2]))
y = gather(y);
end
end
|
d71245b3965474326b14aedb74679e9b2790d5aae566ad82e53e0d6dc71c3333 | MATLAB | 298 | 10 | function s = softmax(x, dim)
% Softmax function
% By default dim = 1 (columns).
% Written by Mo Chen (sth4nth@gmail.com).
if nargin == 1,
% Determine which dimension sum will use
dim = find(size(x)~=1,1);
if isempty(dim), dim = 1; end
end
s = exp(bsxfun(@minus,x,logsumexp(x,dim)));
|
866a79d331616b6e8455cf9784f693d639ebe08223ea0815b00c47fc9a5d294d | MATLAB | 300 | 10 | % boolval = IsConsoleHidden( myobj )
%
% Returns 1 if console window is hidden, false otherwise.
% The console window may be hidden/shown using ConsoleHide()
% and ConsoleUnhide().
%
function [ret] = IsConsoleHidden( s )
ret = sscanf( DoQueryCmd( s, 'ISCONSOLEHIDDEN' ), '%d' );
end
|
ea2b548d03ca1e6f5653949217cf8f3333a5a2a629dfea7ef2ed51fc89e03a61 | MATLAB | 301 | 15 | function [dfof] = quick_extract_dfof(traces)
num_samples = size(traces, 1);
num_neurons = size(traces, 2);
dfof = zeros(num_samples, num_neurons);
for neuron = 1:num_neurons
baseline = median(traces(:, neuron));
dfof(:, neuron) = (traces(:, neuron) - baseline)./baseline;
end
end
|
0cb34131870c9b39c449dae4804925fd494b2f44e432ae783261cad6f414a140 | MATLAB | 303 | 11 | warning('off');
zef.lead_field_type = 1;
zef.source_interpolation_on = 1;
set(zef.h_source_interpolation_on,'value',1);
zef_create_finite_element_mesh;
zef_postprocess_finite_element_mesh;
zef.n_sources_mod = 1;
zef.source_ind = [];
zef_update_fig_details;
zef_eeg_lead_field;
zef_source_interpolation;
|
4b53012439a0f9dd5c5fc31781bf51b7590035f88c3ad60551b261a03d0ec8fb | MATLAB | 303 | 16 | function zef_ES_optimization(zef)
if nargin == 0
zef = evalin('base','zef');
end
org_val = zef.font_size;
zef.font_size = 14;
zef = zef_tool_start(zef, 'zef_ES_optimization_window', 1/5, 1);
zef.font_size = org_val;
if nargout == 0
assignin('base','zef',zef);
end
end |
4e3344711dc58b9f6a90832380c9f34efa5987b76c2d5c05919b7a8696872634 | MATLAB | 303 | 11 | warning('off');
zef.lead_field_type = 5;
zef.source_interpolation_on = 1;
set(zef.h_source_interpolation_on,'value',1);
zef_create_finite_element_mesh;
zef_postprocess_finite_element_mesh;
zef.n_sources_mod = 1;
zef.source_ind = [];
zef_update_fig_details;
zef_tes_lead_field;
zef_source_interpolation;
|
5a6b07909a04db53cccf53be53f6e3b956bd7d6fdc9d6c99c186add153a55a19 | MATLAB | 303 | 11 | warning('off');
zef.lead_field_type = 4;
zef.source_interpolation_on = 1;
set(zef.h_source_interpolation_on,'value',1);
zef_create_finite_element_mesh;
zef_postprocess_finite_element_mesh;
zef.n_sources_mod = 1;
zef.source_ind = [];
zef_update_fig_details;
zef_eit_lead_field;
zef_source_interpolation;
|
c7580b95ed215b2ea791b0a26ccf1606b375d9f890a6e5dfdfea639ba8611ddc | MATLAB | 304 | 10 | function [ModProbMap] = ReMapSagProbMap(ProbMap)
ReMapInd = [1, 2, 3, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 4, 5, 6, 7, 8, 9, 10, 14, 15, 16 ];
sz = size(ProbMap);
ModProbMap = zeros(sz(1),sz(2),28,sz(4), 'single');
for i = 1:28
ModProbMap(:,:,i,:) = ProbMap(:,:,ReMapInd(i),:);
end
|
2b70418bb84fbae56ad1488086b2f27ce9111ee166130941879ca1823a3f0e24 | MATLAB | 305 | 8 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
zef.parcellation_colortable = cell(0);
zef.parcellation_points = cell(0);
zef.parcellation_merge = 1;
zef.use_parcellation = 0;
zef.parcellation_selected = [];
zef_update_parcellation;
|
775369e8276a54231b2a64f41c207ffe19eda4f701069ac2994454367fbb8cf9 | MATLAB | 305 | 14 | function fdn = zef_tetra_fdn
% The face defining neighbours on nodes in a tetrahedron. The sets of vectors
% fdn[:,2] - fdn[:,1] and fdn[:,3] - fdn[:,1] define a basis which spans the
% plane that defines the faces of a tetrahedron.
fdn = [
2 3 4 ;
3 4 1 ;
4 1 2 ;
1 2 3
];
end
|
3b5e787558682053be250aa5954aa57bda02887aefa0f9795467b32cc059b4d6 | MATLAB | 306 | 9 | function Gamma = vpath_to_stc(vpath,K)
% changes a viterbi path (T x 1) to a state time course (T x K) format
if size(vpath,2)>1, error('Viterbi paths have one single column'); end
if nargin<2, K = max(vpath); end
Gamma = zeros(numel(vpath),K,'double');
for k=1:K, Gamma(vpath==k,k) = 1; end
end
|
4070d86105f47b2e1f084ab8c93b88e48c6aa65b306562c4a9970ce3791f6a19 | MATLAB | 307 | 12 | function plot_roi_2D_dots
%grab and format
rois = app.rois;
numROIs = size(rois,1);
C = jet(numROIs);
S = ones(1,numROIs)*10;
%plots
scatter(app.roi_preview, rois(:,1),rois(:,2),S,C, 'MarkerFaceColor','flat','MarkerFaceAlpha',0.5,'MarkerEdgeAlpha', 0.75, 'Marker','o');
axis(app.roi_preview,'tight');
end
|
782cc82108661fbadfb64a4833a6d0ad3831ffab22576e9914f54ca5e9d5a442 | MATLAB | 308 | 11 | if ~isempty(strfind(fsub,'.mat'))
if exist(fsub,'file')
save(fsub,'X','-append')
else
save(fsub,'X')
end
elseif ~isempty(strfind(fsub,'.txt'))
dlmwrite(fsub,X);
else % no extension - assumed to be an SPM file
error('For now, we can only deal with .mat and .txt files')
end |
80546d7928324e3e6f6e003f9d19cb437b53d01bab6c7bc1f18d6b92683f4360 | MATLAB | 308 | 11 | function [m, P] = kf_predict(m,P,A,Q)
% kf_predict is the prediction step of kalman filter
% Skip multiplications if A is Indentity
if (isdiag(A) && all(diag(A) - 1) < eps)
P = P + Q;
else
% Basic kalman prediction steps
m = A * m;
P = A * P * A' + Q;
end
end
|
706853c7ebfa9bb6dccb2057660ef5977e759c96b27883e7346b0472bf000130 | MATLAB | 309 | 8 | function N=bsliang_nonemptycol(data)
% ͳ¼Æ¶þά¾ØÕóµÄµÚһά¶ÈÿһÐзǿյ¥Ôª¸ñÊýÁ¿£¨ÓÃÓÚ¼ÆËãstandard error£©
N=nan(size(data,1),1);
for row=1:size(data,1)
datacol=data(row,:);
datacol=datacol(~isnan(datacol));
N(row)=length(datacol);
end |
e5e763715492a2642c26e543fb94b73cdedc11807c8f319d0666e70cc7589bc7 | MATLAB | 309 | 11 | function [m, P, K] = kf_update(m,P,y,H,R)
% kf_update is the update step of kalman filter
v = y-H*m;
% downsample? H, P, R before S
S = H*P*H'+R;
K = (P*H')/S; % /S is same as *inv(S) but faster and more accurate
% upsample? K, P
m = m+K*v;
P = P-K*S*K';
% upsample P
end
|
ee06a8d3f823b9bca16b37b480c0438f97bb39c07f5816673b36347b79b49fea | MATLAB | 309 | 17 | function [info, columnNames] = zef_dataBank_WorkingSpaceInfo(tree, hash)
columnNames={'hash', 'node type', 'name'};
if ~iscell(hash)
hash={hash};
end
info=cell(length(hash), 3);
for i=1:length(hash)
info{i,1}=hash{i};
info{i,2}=tree.(hash{i}).type;
info{i,3}=tree.(hash{i}).name;
end
end
|
4cdc0c11e63e43501f65e898a43ec6bfdc193708ff68769cfcc0b6a6c3302d7a | MATLAB | 310 | 8 | function [colormap_vec] = zef_blue_brain_3_colormap(colortune_param, colormap_size)
colormap_vec = [[1:colormap_size] ; 0.5*[1:colormap_size] ; 0.5*[colormap_size:-1:1] ];
colormap_vec = colormap_vec + 1;
colormap_vec = colormap_vec'/max(colormap_vec(:));
colormap_vec = colormap_vec.^(colortune_param);
end
|
933b9470124fa8e939749d438039704ab8369c780b011c25cf372b94a100f844 | MATLAB | 310 | 11 | function sesNew = doSelectNeurons(ses,vecNeurons)
%UNTITLED4 Summary of this function goes here
% Detailed explanation goes here
sesNew = rmfield(ses, 'neuron');
intNewCounter=0;
for intNeuron=vecNeurons
intNewCounter=intNewCounter+1;
sesNew.neuron(intNewCounter) = ses.neuron(intNeuron);
end
end
|
dee6adb18cca689669154b2de9898527d2508c8a5e720a98393b759018186480 | MATLAB | 310 | 56 | clear all
close all
clc
time_today = datestr(now, 'mmddyyyy');
% traj_type = 'lorenz';
% uncertain_test_saferegion
% traj_type = 'circle';
% uncertain_test_saferegion
% traj_type = 'mg17';
% uncertain_test_saferegion
traj_type = 'infty';
uncertain_test_saferegion
|
3fe316e83ee67434de95c43d81a638e440de095b9fd6c75a0af62c25bf574543 | MATLAB | 311 | 14 | function compartment_tag = zef_compartment_tag(zef)
ismember_tag = 1;
compartment_counter = 0;
while ismember_tag
compartment_counter = compartment_counter + 1;
compartment_tag = ['c' num2str(compartment_counter)];
ismember_tag = ismember(compartment_tag,eval('zef.compartment_tags'));
end
end
|
8256a63c1c3174b3c5a599bb275a99051d6da464a3a8f89875ccaf5905376eac | MATLAB | 311 | 16 | ns = 2; ny = 2; nz = 2;
N = ns*ny*nz;
P = zeros(N);
P = sort([0, rand(1,N-1), 1]);
P = P(end:-1:2)-P(end-1:-1:1);
P = P/sum(P);
Pzys = reshape(P,nz,ny,ns);
Psy = squeeze(sum(Pzys,1))';
Psz = squeeze(sum(Pzys,2))';
[UI,~] = admUI(Psy, Psz)
%% test the generated MEX
%[UI,~]=admUI_mex(Psy, Psz, accu, g)
|
fd9041fdb155483d219200f506ec92b2fc962eef97c068a43f73ee90c86533f0 | MATLAB | 312 | 8 | function dblDateDiff = datediff(strDate1,strDate2)
%datediff Calculates difference in days between two dates. Syntax:
%dblDateDiff = datediff(strDate1,strDate2)
%
%dblDateDiff = etime(datevec(strDate1),datevec(strDate2))/(60*60*24);
dblDateDiff = etime(datevec(strDate1),datevec(strDate2))/(60*60*24);
end
|
371fd2ff7c5d5400860a63f0da451e62cc969b1081be30e575b0c367735c4c70 | MATLAB | 313 | 7 | function zef_init_profile_table_selection(hObject,eventdata,handles)
init_profile_selected = eventdata.Indices(:,1);
init_profile_selected = unique(init_profile_selected);
init_profile_selected = init_profile_selected(:)';
evalin('base',['zef.init_profile_selected =[' num2str(init_profile_selected) '];']);
end
|
3b01caf353bf113a6778e1671973516bcdde23e790fa6d47eeb372fcbdd8d863 | MATLAB | 313 | 16 | function weights = RidgeRRR(X,Y,lambda,rank)
% Y = X*weights subject to Ridge regularisation
Sig = (X'*X + lambda*eye(size(X,2)));
MAT = X'*Y*Y'*X/Sig;
[U, D] = eig(MAT);
[sortedD,permutation]=sort(diag(D));
U = U(:,permutation);
U = U(:,1:rank);
P = orth(U);
P = P';
W = P*X'*Y/(P*Sig*P');
weights = P'*W;
end |
4d4e3d5acb061d98a7b5b302a12e781d7ffe80a3efd635221857ddefc86fc1af | MATLAB | 313 | 12 | % [Vmin,Vmax] = GetImVoltageRange( myobj, streamID )
%
% Returns votlage range of selected IMEC probe.
%
function [Vmin,Vmax] = GetImVoltageRange( s, streamID )
ret = DoQueryCmd( s, sprintf( 'GETIMVOLTAGERANGE %d', streamID ) );
C = textscan( ret, '%f %f' );
Vmin = C{1};
Vmax = C{2};
end
|
31d0f945bba335b9b13ad2d05cf041273d03b09fffe63da80dc95da98a9f9e5b | MATLAB | 314 | 19 | function [useBIG, chunks] = check_memory_requirements(elements, RAM)
if nargin<2
RAM=115;
end
memoryRequirementInBytes = (elements*8)/(1024^3);
if memoryRequirementInBytes>=RAM
useBIG = logical(1);
chunks = ceil(memoryRequirementInBytes/RAM);
else
useBIG = logical(0);
chunks = 1;
end
end |
8ccacab46464c32595fb59eaa39b6628d41f691027d53d770955e0f3a26ef31c | MATLAB | 314 | 9 | function [d] = zef_distance_to_resection(points, mesh_points, mesh_edges)
d=nan(size(points,1),1);
inside_index=zef_tetra_in_compartment(mesh_points, mesh_edges, points);
not_inside=setdiff(1:size(points, 1), inside_index);
d(inside_index)=0;
[~, d(not_inside)]=knnsearch(mesh_points, points(not_inside,:));
end
|
2b304fd8dbdda0090cd9c206881fa0dc4bcf490262a380dc4e7bda3e860806e7 | MATLAB | 315 | 11 | function [nearest_points] = find_closest_points_brute(Set1, Set2)
distances = pdist2(Set1, Set2);
minDistance = min(distances(:));
[rowOfA, rowOfB] = find(distances == minDistance);
nearest_points = [Set1(rowOfA, :), Set2(rowOfB, :)];
if size(nearest_points,1) > 1
nearest_points = nearest_points(1, :);
end
|
2939b9926ec2209e701a08a24db89345733680781aa507ae1ddab323a6aec24e | MATLAB | 316 | 11 | warning('off');
zef.lead_field_type = 3;
zef.source_interpolation_on = 1;
set(zef.h_source_interpolation_on,'value',1);
zef_create_finite_element_mesh;
zef_postprocess_finite_element_mesh;
zef.n_sources_mod = 1;
zef.source_ind = [];
zef_update_fig_details;
zef_meg_gradiometers_lead_field;
zef_source_interpolation;
|
c1d938868fc0028351e390b10b9ead7feebeb172cc87f7de4982479c5f2723cd | MATLAB | 316 | 8 | function ETO_SliderCallback(hObject,eventdata,ptrSubPanel)
vecSize = ptrSubPanel.Position;
val = get(hObject,'Value');
dblRealMax = vecSize(end) - 1;
dblStartY = val*dblRealMax;
vecSetPanelPos = [0 -dblStartY 1 vecSize(end)];
set(ptrSubPanel,'Position',vecSetPanelPos);%[from-left from-bottom width height]
end |
fc2c62799aa038a184e43aab09dc269dd8d57ff61459554f6a9f4400baf8c93c | MATLAB | 317 | 11 | function update_unlearned_models(app)
totalModelsPlanned = numel(app.params.s_lambda_sequence) * numel(app.params.p_lambda_sequence);
currentModelsLearned = length(app.model_collection.models);
val = totalModelsPlanned-currentModelsLearned;
if val <= 0
val = 0;
end
app.ModelsUnlearnedEditField.Value = val;
end |
fc7be4aaccbb4e3221fd435d22f785cf479f806be3222fc699bbb8b8fba3dfa0 | MATLAB | 317 | 11 | warning('off');
zef.lead_field_type = 2;
zef.source_interpolation_on = 1;
set(zef.h_source_interpolation_on,'value',1);
zef_create_finite_element_mesh;
zef_postprocess_finite_element_mesh;
zef.n_sources_mod = 1;
zef.source_ind = [];
zef_update_fig_details;
zef_meg_magnetometers_lead_field;
zef_source_interpolation;
|
160268a1f9a42d0fc0d6a57817d0b1b4819f9cfac80be8dc399d24d27353eb2d | MATLAB | 318 | 14 | function plot_pattern_completion_coordinates(app)
if app.roi_style == 0
plot_pcn_coordinates_style_0(app);
elseif app.roi_style == 1
plot_pcn_coordinates_style_1(app);
elseif app.roi_style == 2
plot_pcn_coordinates_style_2(app);
elseif app.roi_style == 3
plot_pcn_coordinates_style_3(app);
end
end |
64b25e6e03e3627f57d78c8874ff5b4bc5d2e3459f89cd4a94102d638aa65911 | MATLAB | 318 | 16 | function fdn = zef_prism_fdn
% The face defining neighbours on nodes in a prism. The sets of vectors
% fdn[:,2] - fdn[:,1] and fdn[:,3] - fdn[:,1] define a basis which spans the
% plane that defines the faces of a tetrahedron.
fdn = [
2 3 5;
3 1 6;
1 2 4;
5 6 2;
6 4 3;
4 5 1
];
end
|
f6bf36140ee1085e4869248e506c8d924f75d8eaa77ac39bd59cddc082adce56 | MATLAB | 318 | 14 | function load_params(app)
% Function to load params
try
params = load(app.file_params,'params');
params = params.params;
app.params = convert_paths_to_absolute(params);
update_log(app,'Retrieved Parameters');
update_params(app);
catch
update_log(app, 'Could Not Retrieve Parameters');
end
end |
396031a10582e3e0e111dd78addf8fe3507db6759213c0bb4160a841556a3986 | MATLAB | 319 | 10 | function update_s_lambda_text(app)
completeString = [];
for i = 1:length(app.params.s_lambda_sequence)
completeString = [completeString regexprep(char(vpa(app.params.s_lambda_sequence(i))),'([0-9]+\.[0-9]+)','${num2str(str2num($1),''%e'')}') newline];
end
app.SelectedLambdasTextArea.Value = completeString;
end
|
74a0b60c13a7d9fe116d1c40432577b3c77ab0a4a12ba8c121ffce03debb8d53 | MATLAB | 319 | 9 | function vecSD = xstd2(matInput)
%xstd2 Fast standard deviation calculation over second dimension of 2D
%matrix. Calculation time is approximately 75% of original std().
% vecSD = xstd2(matInput)
intP = size(matInput,2);
vecSD = sqrt(sum(bsxfun(@minus,matInput,sum(matInput,2)./intP).^2,2)*(1/(intP-1)));
end
|
0f20918c96cd4523ae2eb4be6c24d90d44582aabb1d5e306cc292efc825a2ec6 | MATLAB | 320 | 15 | function score = matching_score(data, Model)
N = numel(data.y);
tmodel = 0:0.001:data.t(end);
ymodel = dbl_exp_func(tmodel, Model);
t = 0:data.dt:tmodel(end);
[~,idx] = findClosest(t, tmodel);
temperate = ymodel(idx);
dy = diff( [data.y data.y(end)] );
dt = diff( temperate );
coin = conv(dy, dt);
score = coin(1:N); |
7ce473df142af39f0591048be2611f5c415b417c203221a455a5dbe49d2761e2 | MATLAB | 320 | 10 | function [x] = loadPic(picNum) % Load picture
picSearchString = sprintf('p%04d*.m', picNum);
picMFile = dir(picSearchString);
if (~isempty(picMFile))
eval( strcat('x = ',picMFile.name(1:length(picMFile.name)-2),';') );
else
error = sprintf('Picture file p%04d*.m not found.', picNum)
x = [];
return;
end
|
ab07481f4b469960f78f99857a65b402c7156e312de3dae7618515f446db024d | MATLAB | 320 | 11 | function zef_plot_graph
zef = evalin('base','zef');
g_list = eval('zef.mesh_visualization_graph_list');
g_ind = eval('zef.mesh_visualization_graph_selected');
p_ind = eval('zef.mesh_visualization_parameter_selected');
[~,v_name] = zef_get_profile_parameters(zef,p_ind);
eval([g_list{2}{g_ind} '(' v_name ');']);
end
|
53e8ec857a1f3f3e731f0d513d35e86e97193685c8196ffbe419a89adab4bcae | MATLAB | 321 | 10 | function update_p_lambda_text(app)
completeString = [];
for i = 1:length(app.params.p_lambda_sequence)
completeString = [completeString regexprep(char(vpa(app.params.p_lambda_sequence(i))),'([0-9]+\.[0-9]+)','${num2str(str2num($1),''%e'')}') newline];
end
app.SelectedLambdasTextArea_PE.Value = completeString;
en... |
34beed7d35132e0e7e68f9b12b174b761dbcbdbd47c5f691854e33a77b5362c6 | MATLAB | 322 | 17 | function [params] = convert_paths_to_relative(params)
root_dir = params.source_directory;
params.experiment_directory = erase(params.experiment_directory, root_dir);
[filepath, name, ~] = fileparts(params.filename);
params.data_directory = erase(filepath, root_dir);
params.filename = name;
end
... |
8799961842868047983b6812631b0f809a63292a695c9fffce927a567a232e25 | MATLAB | 323 | 9 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if zef.use_display
zef = zeffiro_interface('zeffiro_restart', true);
else
zef = zeffiro_interface('zeffiro_restart', true, 'start_mode','nodisplay');
end
zef = zef_delete_all_compartments(zef)... |
7cf5f1abe960b71cd4fa531ed6a454026c32b40c96298ae32822f61c7014762e | MATLAB | 324 | 14 | % how to normalize each frame
function [nst, Smax] = normStack( st )
% assumes 3rd
%Smean = squeeze(mean(st, [1 2]));
sz = size( st );
for i=1:sz(3)
Smax(i) = single(1.1*max( st(:,:,i),[], "all")); % 1.1 to avoid saturation
nst(:,:,i) = single(st(:,:,i) / Smax(i));
end
%mn2 = mean(nst, [1 2]);
... |
1d85952314357a64a26206a6298db6504b6451145664a35a643d481fb329dae6 | MATLAB | 325 | 10 | function zef_set_linear_colorbar_ticks(zef,n_ticks,n_digits,max_val)
h_c = findobj(zef.h_zeffiro.Children,'Tag','rightColorbar');
h_c.Ticks = linspace(h_c.Limits(1),h_c.Limits(2),n_ticks);
TicksLabels = round(max_val.*10.^((h_c.Ticks - h_c.Limits(2))./20),n_digits);
h_c.TickLabels = cellstr(num2str(TicksLabels(:)));
... |
699ef37bc7521215e84517934e5957fd5f76151488d238488e9b3db892af119f | MATLAB | 326 | 7 | function [tuda,Gamma,GammaInit,vpath,stats] = tucatrain(X,Y,T,options)
% Wrapper function to perform temporally unconstrained classification
% Analysis (TUCA). This function is now merely a wrapper function with core
% functionality maintained in tudatrain.
[tuda,Gamma,GammaInit,vpath,stats] = tudatrain(X,Y,T,options)... |
3c95a0b5bf31f0dc40b1a376943b44e9d394840fa88a1e9017bb092f502212be | MATLAB | 327 | 16 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
for zef_i = 1:length(zef.lf_bank_storage)
if ismember(zef_i,zef.lf_item_selected)
zef.lf_bank_storage{zef_i}.noise_data = zef.noise_data;
end
end
clear zef_i;
zef_update_lf_bank_... |
b2905a2255d86be8e8a18f73ce7325769ef462358c1bd9ba1123adfd94d36906 | MATLAB | 327 | 10 | % filtfilt filter ROIs
function fdata = filterData( data, Fsampling, Niir, Fstop )
% data = nsamples x ncells
% Fs = 10; % sampling rate
% Niir = 7; % order
% Fst = 1; % stop frequency
iir = designfilt('lowpassiir','FilterOrder',Niir,...
'HalfPowerFrequency',Fstop,'SampleRate',Fsampling);
fdata = filtfilt(iir, dat... |
60f61f2e0c1a7f3264f82e6f0a7bceb0d00dcd37d8df12994e4a988ab4cb6ccc | MATLAB | 328 | 11 | function zef_set_timepointline(h_axes)
h_line = findobj(h_axes.Children,'Tag','timepointline');
delete(h_line);
h_line = line(h_axes.CurrentPoint([1 1]),[h_axes.YLim]);
h_line.Color = 0.5*[1 1 1];
h_line.Tag = 'timepointline';
h_axes.Title.String = ['Time value = ' num2str(h_axes.CurrentPoint(1))];
h_line.LineWidth = ... |
a63e784a05c6fd131a546e8d6584eacf0d459484f44c24867703e287acae73d9 | MATLAB | 329 | 14 | function plot_ensemble_coordinates(app)
if app.roi_style == 0
plot_ensemble_coordinates_style_0(app);
elseif app.roi_style == 1
plot_ensemble_coordinates_style_1(app);
elseif app.roi_style == 2
plot_ensemble_coordinates_style_2(app);
elseif app.roi_style == 3
plot_ensemble_coordinates_style_3(app);
e... |
6cca04227a0ddb33810fe915c902de4ff9dc5d126f525a48fdd88b9a8fe82ad3 | MATLAB | 330 | 15 | function [nodes, triangles] = zef_triangulate_surface(X, Y, Z, varargin)
max_faces = 0;
if not(isempty(varargin))
max_faces = varargin{1};
end
patch_data = surf2patch(X,Y,Z,'triangles');
if max_faces > 0
patch_data = reducepatch(patch_data,max_faces);
end
nodes = patch_data.vertices;
triangles = patch_data.fa... |
ebdca5cf8a1bb8186c5cffaffa05b7663738d5c3afbfd61e23990b4bed4afb81 | MATLAB | 330 | 10 | function vecMean = xmean(matInput,intDim)
%xstd Fast mean calculation. Speed-up is approximately 95% of original
%time. Syntax:
% vecMean = xmean(matInput,intDim)
%
% By Dr. Jorrit S. Montijn, 29-11-16 (dd-mm-yy; Universite de Geneve)
vecMean = sum(matInput,intDim,'default','includenan')./size(matInput,intD... |
4798071270268e0157ab682792c97e11139226e7087a60aba299b3ace958ea03 | MATLAB | 332 | 13 | % [SN,type] = GetImProbeSN( myobj, streamID )
%
% Returns serial number string (SN) and integer type
% of selected IMEC probe.
%
function [SN,type] = GetImProbeSN( s, streamID )
ret = DoQueryCmd( s, sprintf( 'GETIMPROBESN %d', streamID ) );
C = textscan( ret, '%[^ ] %d' );
SN = C{1};
type ... |
7035abf6a2b20ea98c7a78378cf0778ca6a7ce1ce34e2121f878691094c3c3d6 | MATLAB | 333 | 11 | set(zef.h_zeffiro_window_main,'DeleteFcn','');
close(zef.h_zeffiro_window_main);
zef_segmentation_tool;
zef_update;
set(findobj(zef.h_zeffiro_window_main.Children,'-property','FontUnits'),'FontUnits','pixels')
set(findobj(zef.h_zeffiro_window_main.Children,'-property','FontSize'),'FontSize',zef.font_size);
zef.clear_... |
f51c7c3a705ee8b96cae9cd65fb8e1e1c797e63ba32ba62c2d824f4d9220e797 | MATLAB | 333 | 11 | function dPrime = getdprime2(vecIn1,vecIn2,intDim)
if ~exist('intDim','var') || isempty(intDim)
intDim=1;
end
if isvector(vecIn1) && isvector(vecIn2)
vecIn1 = vecIn1(:);
vecIn2 = vecIn2(:);
intDim = 1;
end
dPrime = (mean(vecIn1,intDim) - mean(vecIn2,intDim))./sqrt(0.5*(var(vecIn1,[],intDim)+var(vecIn2,[],i... |
64f6102010c618391ba8cde144d0226a731c81d443e8e790a83258fae23aae2a | MATLAB | 334 | 18 | function sc = sw_load_scoring_h (sc_fn, opt)
% funtion to import scorign for human EEG/PSG directly into sleepwalker
opt = opt;
%%formats:
% luna txt files:
% read table
sc0 = readtable (sc_fn);
sc=struct;
sc.id = sc0.ID{1};
sc.clocktime = sc0.CLOCK_TIME;
sc.mins = sc0.MINS;
sc.stage= sc0.STAGE;
sc.stage_no= ... |
1f617af628e24356e1bbd6b00cef53693079d4246c8c3fefd424de3ff26a3d31 | MATLAB | 336 | 12 | function cellOut = strparse(strInput,strDelimiter)
%strparse Splits input string by delimiter
% cellOut = strparse(strInput,strDelimiter)
intParts = sum(ismember(strInput, '_'));
cellOut = cell(1,intParts);
for intPart=1:(intParts+1)
[strTok, strInput] = strtok(strInput,strDelimiter);
cellOut{intPart} = st... |
689a933e7f01e0d3482ace1654cc05bad3e165c7e2e2afe62360caca9bd1bec3 | MATLAB | 336 | 19 |
%Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef = zef_minimum_norm_estimation(zef)
if nargin == 0
zef = evalin('base','zef');
end
zef = zef_tool_start(zef,'zef_mne_tool_start',1/4,0);
if nargout == 0
assignin('base','zef',... |
ab942954c66a36512a2def1fbef5d7579c391e31384b0918939378ba945ddf66 | MATLAB | 336 | 13 |
zef.aux_data_1 = cell(0);
zef.aux_data_2 = eval(['zef.' zef.current_tag '_transform_name']);
for zef_i = 1 : length(zef.aux_data_2)
zef.aux_data_1{zef_i,1} = zef_i;
zef.aux_data_1{zef_i,2} = zef.aux_data_2{zef_i};
end
zef.h_transform_table.Data = zef.aux_data_1;
zef = rmfield(zef,{'aux_data_1','aux_data_2'}... |
9532fbb470fb8fd4ddb9d7d8d874a14a9972d2ea45d1a1c859e8d71e73fd1653 | MATLAB | 337 | 4 | set(gcf,'AutoResizeChildren','off');
zef.zeffiro_current_size{zef_fig_num} = get(gcf,'Position');
set(gcf,'Tag',num2str(zef_fig_num));
set(gcf,'SizeChangedFcn','zef.zeffiro_current_size{str2num(get(gcf,''Tag''))} = zef_change_size_function(gcf,zef.zeffiro_current_size{str2num(get(gcf,''Tag''))},[],{''Colorbar'',''image... |
e80f46f751f4bda1ed2f56d030e39ac42babae632c24a1ae55284ebd3f31ea0c | MATLAB | 337 | 9 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
function save_jacobian_data_complex(aux_mat_cos, aux_mat_sin, ind_vec, torre_dir)
save([torre_dir '/system_data/aux_mat_' int2str(ind_vec(1)) '_' int2str(ind_vec(2)) '.mat'],'aux_mat_cos', 'aux... |
2646ddfb66f545d44fa26f1e25b67e0d6b5a622ddf17e0afdddd1ac0e0dd97f4 | MATLAB | 338 | 8 | function zef_system_settings_table_selection(hObject,eventdata,handles)
system_settings_selected = eventdata.Indices(:,1);
system_settings_selected = unique(system_settings_selected);
system_settings_selected = system_settings_selected(:)';
evalin('base',['zef.system_settings_selected =[' num2str(system_settings_selec... |
6fdd8aff3050ef8e0ca56ad852250149632e737e7c0895390fd4716c04b993ce | MATLAB | 338 | 6 | [zef.file zef.file_path] = uigetfile({'*.mat'},'Import interpolation',zef.save_file_path);
if not(isequal(zef.file,0));
[zef.eit_sensitivity_tool_data] = load([zef.file_path zef.file]);
zef.eit_sensitivity_tool_file = [zef.file_path zef.file];
set(zef.h_eit_sensitivity_tool_file, 'Value', zef.eit_sensitivit... |
8990c08fc064488e809f0d1e41f38903a89b9d7191bbb2d415cf47caae00cc90 | MATLAB | 338 | 8 | function zef_plugin_settings_table_selection(hObject,eventdata,handles)
plugin_settings_selected = eventdata.Indices(:,1);
plugin_settings_selected = unique(plugin_settings_selected);
plugin_settings_selected = plugin_settings_selected(:)';
evalin('base',['zef.plugin_settings_selected =[' num2str(plugin_settings_selec... |
dc986c7f05653507d12d3adc6818d9567ef6adceeb1c544afbb4444d89234da0 | MATLAB | 338 | 19 | function zef_wireframe_plot(w_t,w_n)
h_a = evalin('base','zef.h_axes1');
axes(h_a);
h_t = trimesh(w_t,w_n(:,1),w_n(:,2),w_n(:,3));
h_t.EdgeColor = 'none';
h_t.FaceColor = 0.5*[1 1 1];
h_l = light;
h_l.Position = [1 0 0];
h_l = light;
h_l.Position = [-1 0 0];
lighting phong;
axis equal;
h_t.Tag = 'surface';
h_a.Visi... |
7ce67f62ff5d006e36ac34da5d38be5ed486a88eb8510d4390363beaf0c37957 | MATLAB | 339 | 14 | function [nodes, tetra] = zef_optimize_mesh(nodes,tetra)
nodes_old = nodes;
tetra_old = tetra;
[tetra, optimizer_flag] = zef_tetra_turn(zef, nodes, tetra, evalin('base','zef.mesh_optimization_parameter'));
if optimizer_flag == -1
nodes = nodes_old;
tetra = tetra_old;
errordlg('Mesh optimization failed.')... |
481472ba4132814342ab1b4589f2340d0745ec867bb7710de6a42b7395172743 | MATLAB | 340 | 10 | %Copyright © 2021- Sampsa Pursiainen & GPU-ToRRe-3D Development Team
%See: https://github.com/sampsapursiainen/GPU-Torre-3D
function [min_ind] = array_min(i, xq, yq, zq, nodes_aux)
aux_pos = [xq(i),yq(i),zq(i)];
[min_val,min_ind] = min(sqrt(sum((nodes_aux - aux_pos(ones(size(nodes_aux,1),1),:)).^2,2)));
min_ind = gath... |
a6968fcd1b2ffd2dfe1b26f9285ece3dde5be548622a62e9f332bc41f5783e91 | MATLAB | 342 | 11 | function zef = zef_parcellation_roi_pick_color(zef)
color_vec = uisetcolor;
if not(isequal(color_vec,0))
color_str = num2str(color_vec);
zef.h_parcellation_roi_color.String = color_str;
zef.h_parcellation_roi_color.BackgroundColor = color_vec;
zef.parcellation_roi_color(zef.parcellation_roi_selected,:)... |
e6c262a7e88c47c7b412f3d8cdac1397ca1dd8584121f56e6c4851b01ec7ca4b | MATLAB | 342 | 15 | function sEpochs = ETC_GenEmptyEpochs
sEpochs = struct;
sEpochs.BeginFrame = nan;
sEpochs.BeginLabels = [];
sEpochs.EndFrame = nan;
sEpochs.EndLabels = [];
sEpochs.CenterX = [];
sEpochs.CenterY = [];
sEpochs.Radius = [];
sEpochs.Radius2 = [];
sEpochs.Angle = [];
sEpochs.Blinks = [];
sEpochs.IsDetected = [];... |
e7a8eb00d5722c85dc39ca53a360dba4cc4955b50bca7c2ffb3eaa9c60026a51 | MATLAB | 342 | 9 | function im8bit = dbl2uint8( stack )
tic
im8bit = uint8(255 * mat2gray(stack));
[premin, premax] = minmax(stack);
[postmin, postmax] = minmax(im8bit);
disp(append('pre min max: ', num2str(premin), ' , ', num2str(premax)))
disp(append('post min max: ', num2str(postmin), ' , ',num2str(postmax)))
disp(append('dbl2uint8: '... |
c81ea97f9ac1fc1b8df6391ee4e6a045ad0c8ae6fb9f081c957610a265b4908c | MATLAB | 343 | 15 | function post_info = estimate_spike_num_weight(post_info,Model)
% ---
% post_info = estimate_spike_num_weight(post_info,Model)
% ---
% post_info.Pspike(ns,n) = P(ns | yk) of n-th overlap window
X = post_info.Pspike;
X = [X; ones(1,size(X,2))];
Y = Model.W * X;
[ytmp, Yid] = max(Y,[],1);
post_info.s... |
6ca130eac8641ce33c5fe8b5bc9bcd8957c1d7668d634825c0c7355e209ad460 | MATLAB | 344 | 18 | function plot_rois_preview(app)
% Pull Out
rois = app.rois;
%now parse whether 3D Single-Point Coordinates OR 2D Polygons
if size(rois,2)==3
app.roi_style = 0;
plot_roi_dots(app);
elseif size(rois,2)==2
app.roi_style = 1;
plot_roi_2D_dots(app);
elseif isstruct(rois)
app.roi_style = 2;
plot_roi... |
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