sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9b59ceb2aab050e098cb353c2d7d8965e8c7b2ddc7df8d22c60d9c205c4ac861 | MATLAB | 295 | 17 | % bem5a_figure_scales
A = 40;
Emax = A;
Emin = -A;
Eprimax = A;
Eprimin = -A;
n_ELevels = 40;
%% Define dimensionless radius of the integration sphere (for precise integration near boundaries)
R = 2;
%% Define observation points in the cross-section (MsxMs observation points)
Ms = 800;
|
c22885defe4dbd64f4621e81d7e94b7a630793786f2d1945dbc5ff7e5668f6e1 | MATLAB | 295 | 7 | function [meanFiringRate, peakFiringRate] = ml_placefield_firingrate(meanFiringRateMap, positionProbMap)
% Compute the mean firing rate across all of the locations
meanFiringRate = sum( meanFiringRateMap .* positionProbMap, 'all' );
peakFiringRate = max(meanFiringRateMap(:));
end
|
01bb2924f737462b9226f45b6dc75057bb2e2cca94dffe5e0e46b60924b202ee | MATLAB | 296 | 14 | function[la,LLopt] = get_lambda(Y,zDimList,numFolds,M)
dim = crossvalidate_fa(Y, 'zDimList', zDimList,'showPlots',false,'numFolds',numFolds);
sumLL=[dim.sumLL];
LLopt= find(sumLL== max(sumLL),1);
L=dim(M).estParams.L;
LL=L*L';
[V,D]=eig(LL);
la=diag(D);
la=sort(la,'descend');
la=la(1:M);
end
|
d563bbc1d98b57d0192bc7d420915855b3a34d88414798001885cde2da0b9cfb | MATLAB | 296 | 8 | function mask_f = had_get_mask(SC,HAD_S,i_it)
mask_f=HAD_S.had_mat(HAD_S.row_i(i_it),:)'*HAD_S.had_mat(HAD_S.col_j(i_it),:);
mask_f = (mask_f+1)/2;
mask_f=interp2(HAD_S.XM,HAD_S.YM,mask_f,SC.gfx,SC.gfy,'nearest',0);
mask_f(isnan(mask_f(:)))=0;
mask_f(isinf(mask_f(:)))=0;
mask_f=exp(mask_f*1i);
|
daa6c147eeb7332b6e3f492b3f4b86b67724921b0d640c83e3562240d6961760 | MATLAB | 296 | 8 | function type_list = nexterrortype_type()
type_list = {'Track Birth','birth',
'Track Death','death',
'Match Cost Ambiguity','swap',
'Large Jump','jump',
'Large Change in Orientation','orientchange',
'Velocity & Orient. Mismatch','orientvelmismatch',
'Large Major Axis','largemajor'};
|
1557010cfb5aca9ce4289e076829320ea72c19c9534ca14c98d792b3c0e2ed6e | MATLAB | 298 | 11 | % VL_GETPID Get MATLAB process ID
% VL_GETPID() returns MATLAB process ID.
%
% Algorithm::
% VL_GETPID() returns the result of the getpid() system call on
% UNIX-like operating systems and of GetCurrentProcessID() on
% Windows.
%
% See also: VL_HELP().
% Authors: Andrea Vedaldi
|
25b16e9a97768772a042df00118edb92fe82f640b80a5d73ff44a065234fbc18 | MATLAB | 299 | 11 | % Author: Zachary Chiang, Buenrostro Lab, Harvard University
% Writes a 3D .tif file with the given filename
function[] = write_3d_tif(filename, img)
imwrite(uint16(img(:,:,1)),filename);
for z=2:size(img,3)
imwrite(uint16(img(:,:,z)),filename,'WriteMode','append');
end
end
|
390c4f66541cdb8f2863b5925a78159992dd533a952aaba4e114bf452eac745b | MATLAB | 300 | 11 | function plotmyhist(Var,Nbins,VarRange,Mode,NN)
% not sure what was this function. calls myhist (without NN)
if nargin<4, Mode = 'lin'; end;
if nargin<3, VarRange = [0,1]; end;
if nargin<2, Nbins = 20; end;
if isempty(VarRange), VarRange = [0,1]; end
myhist(Var, VarRange, Nbins, Mode); |
ed4fe42858a610b24fc28b3538f6ed8e9f96551edd467d1ffc2f24b031b6a349 | MATLAB | 300 | 11 | function [similarity indSim] = SSSimBoxFillSize(a, b, blobStruct)
% Calculate similarity for a single edge.
% a is blob a.
% b is blob b.
% blobStruct is the list of blobStruct
indSim(:,1) = SSSimBoxFill(a, b, blobStruct);
indSim(:,2) = SSSimSize(a, b, blobStruct);
similarity = mean(indSim, 2); |
1a6d1bbfbfababb09fbd780a77c51c06ff9dbb38fcedbeb111ed15fcbae10782 | MATLAB | 301 | 14 | function [map] = assignTextons(fim,textons)
% function [map] = assignTextons(fim,textons)
d = numel(fim);
n = numel(fim{1});
data = zeros(d,n);
for i = 1:d,
data(i,:) = fim{i}(:)';
end
d2 = distSqr(data,textons);
[y,map] = min(d2,[],2);
[w,h] = size(fim{1});
map = reshape(map,w,h);
|
93b4692227dbd6f87b6b027deb51d8071685ed5f08d23b024754b8e4ca82c5a4 | MATLAB | 301 | 17 | function [tl] = tlcompact(nR,nC,titlestr,tftsz)
%tlcompact.m
%title string and title font size are optional
tl = tiledlayout(nR,nC,'Padding','compact','TileSpacing','compact');
n = nargin;
if n >= 3
tl.Title.String = titlestr;
if n > 3
tl.Title.FontSize = tftsz;
end
end
end
|
a68dda92c3ff8a71e0d11b043d3a567497b71bc363bb30505a970bca25b6e2a2 | MATLAB | 301 | 8 | function post_install (d)
fprintf ('The statistics-resampling package was installed into the directory:\n');
fprintf ('%s\n', d.dir);
fprintf ('License and copyright information can be found at:\n');
fprintf ('https://github.com/gnu-octave/statistics-resampling/blob/master/COPYING\n');
end
|
4ffdc1ac94a033cf54f3d74d5c7e790a52fdc57e8d108b18601bd278459a1af7 | MATLAB | 302 | 14 | function Ind = IndexOfMultiples(A)
T = true(size(A));
off = false;
A = A(:);
for iA = 1:numel(A)
if T(iA) % if not switched already
d = (A(iA) == A);
if sum(d) > 1 % More than 1 occurrence found
T(d) = off; % switch all occurrences
end
end
end
Ind = find(~T);
end |
8911f7f02ca4320b94032151dd8a80facf3f1cf2116a640f91ff90039506359d | MATLAB | 302 | 9 | function Params = permuteParams(Params)
Params.fov = Params.fov([2,1,3]);
Params.sizeVol = Params.sizeVol([2,1,3]);
Params.voxSize = Params.voxSize([2,1,3]);
if isfield(Params, 'sizeRecAll')
Params.sizeRecAll = Params.sizeRecAll([2,1,3:length(Params.sizeRecAll)]);
end
end
|
edce67e3453106294e3870352d44c9a81b2c261866bcd2f934fdd9ffdfb7cb22 | MATLAB | 302 | 6 | function [center_bins_deg] = ml_alg_chist_center_bins(n_bins)
% Computes the center bins for a circular histogram (equal bin widths).
dtheta_deg = 360.0 / n_bins;
center_bins_deg = (0:n_bins)*dtheta_deg;
center_bins_deg(center_bins_deg==360) = []; % drop if 360 included
end % function
|
ef723b624dfe5a4bc156a44ad2f5d4c642187dda92d9dbad7209fed2f0655794 | MATLAB | 302 | 11 | function o = vertcat(varargin)
% Vertical concatenation of file_array objects.
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: vertcat.m 8776 2013-11-14 09:04:48Z roboos $
o = cat(1,varargin{:});
return;
|
769a1fe77fe3a8ba959fb0e1687a1dd6fbdca8756cbf4d68c866f6b8d04fb9b1 | MATLAB | 303 | 11 | function out = gaussianfilterdata(data,sigma)
%convolves a data set with a gaussian of width 'sigma'
L = length(data);
xx = (1:L) - round(L/2);
if iscolumn(data)
xx = xx';
end
g = exp(-.5.*xx.^2./sigma^2)/sqrt(2*pi*sigma^2);
out = fftshift(ifft(fft(data).*fft(g))); |
99f269f10b95dd0f2c10641b33e7ac3376eda49ca4a7c2ec579fd8b86f0054d3 | MATLAB | 303 | 10 | function varargout = permute(varargin)
% Can not be permuted.
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: permute.m 8776 2013-11-14 09:04:48Z roboos $
error('file_array objects can not be permuted.');
|
45061cad6f8b5c5c4bc850f5ed494e4482e07d0d6d4591c9811a43ebda63811d | MATLAB | 304 | 12 | function n=SONMaxChans(fh)
% SONMAXCHANS returns the number of channels supported by a SON file
%
% N=SONMAXCHANS(FH)
% where FH is the SON file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
n=calllib('son32','SONMaxChans',fh);
|
0b8fe277c6044cf32c9edab1ad118c3b030f2946bb5e584a7b025e944ac667d4 | MATLAB | 306 | 11 | function o = horzcat(varargin)
% Horizontal concatenation of file_array objects
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: horzcat.m 8776 2013-11-14 09:04:48Z roboos $
o = cat(2,varargin{:});
return;
|
19d1a3413353a583df3be23546c378544712d7930b02958d8d8b4b6ab06de634 | MATLAB | 306 | 7 | %% Chi2stat and pval sub-function
function [pval, chi2stat_out] = calc_chi2(metric_use, bins_use)
n = histcounts(metric_use, bins_use);
e_unif = sum(n)/length(n); % Expected count in each bin for uniform distribution
chi2stat_out = sum((n-e_unif).^2/e_unif);
pval = chi2pdf(chi2stat_out,length(n)-1);
end
|
4f712f96f6daf1dc1deac75a16a0bdbb0924207d2f98726b7f6e04e9de8d473b | MATLAB | 306 | 8 | %data是想要滤波的矩阵，Fs实际采样率，f滤波半径（截至频率），按列滤波
function [output]=zero_filter_lowpass(data,Fs,f)
Mix_Signal=data;
Wc=2*f/Fs; %生成Butterworth滤波函数
[b,a]=butter(2,Wc);
Signal_Filter=filtfilt(b,a,Mix_Signal);%滤波
output=Signal_Filter;
end |
f1bdce865122b687215bf48fe2ea02db3cd6c329b5dacf3fb77a67557672fae7 | MATLAB | 307 | 13 | % plot ephys
Files = dir(cd);
Files(~contains({Files.name}, {'.mat'})) = [];
for i = 1:length(Files)
figure()
load(fullfile(Files(i).folder, Files(i).name))
timeVec = 0:(1/50000):(length(ephysData)-1)/50000;
plot(timeVec, ephysData);
title(Files(i).name);
disp(Files(i).name);
end
|
02878225b75ecbe5c7465de2a043d67b77b7c5ed7c064721bbe1b5f18285ad48 | MATLAB | 308 | 10 | function NuOut = Phi(NuIn, Net)
% sigmoid = @(x)1./(1+exp(-4*x)); % Logistic function as a shifted hyperbolic tangent.
sigmoid = @(x)tanh(x); % As in (Sompolisky et al., PRL 1988).
if size(NuIn,1) == 1
NuIn = NuIn';
end
NuOut = sigmoid(Net.CParam.J*NuIn + Net.MParam.IExt)./Net.MParam.Tarp;
|
12335948f3e3104571c6ce33f36d2c1599ff3d89ce413cf94ecb8954d407a6f2 | MATLAB | 308 | 11 | function [similarity indSim] = SSSimBoxFillOrigSize(a, b, blobStruct)
% Calculate similarity for a single edge.
% a is blob a.
% b is blob b.
% blobStruct is the list of blobStruct
indSim(:,1) = SSSimBoxFillOrig(a, b, blobStruct);
indSim(:,2) = SSSimSize(a, b, blobStruct);
similarity = mean(indSim, 2); |
40151304d8131673a1216bc1c328f986cceb9e43ae49ec50ff27d1bb0fdaaafa | MATLAB | 308 | 11 |
% send triggers via USB to serial adapter (e.g. USB 2.0 Adapter [1x RS485-Stecker - 1x USB 2.0 Stecker A] Weiß Digitus)
USBTTL_2('Open' ,'USB0');
triggerDur = 0.01;
% send trigger after e.g. Screen(window, 'Flip') command
triggerOnset = sendTrigger( p.triggerDur);
USBTTL_2('Close' ,'USB0'); |
c3ba9c908b1ef23a5f49c6f8c76a91293ac6e01f4b0462e86f16acb4bff133c3 | MATLAB | 308 | 12 | function d = double(ipa)
% INPLACE/DOUBLE Return the data as a Matlab double type.
% d = double(ipa) returns a double array. Changing d will not change the
% ipa data.
%
% Example:
% ipa = inplace(cumsum(ones(5,1)));
% d = double(ipa);
% d(2) = 10: % Doesn't change ipa
% ipa
d = ipa.get_a(); |
e89ee913a40a5390916f653110445270863716099736879e2c8155d5a1dec7f0 | MATLAB | 308 | 20 | function maxV = findMaxLength(fpr_iter, fnr_iter)
%init
maxV = -1;
for i = 1 : numel(fpr_iter)
l = length(fpr_iter{i});
if l > maxV
maxV = l;
end %if l
end %for i
for i = 1 : numel(fnr_iter)
l = length(fnr_iter{i});
if l > maxV
maxV = l;
end %if l
end %for i
|
b4cb545fca06615633520b25ee9e5a68058c6f40f9f5449516a34814d2af650b | MATLAB | 309 | 11 | function bytes=SONFileSize(fh)
% SONFILESIZE Returns the expected size of a file
% BYTES=SONFILESIZE(FH) where FH is the file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
bytes=calllib('son32','SONFileSize',fh);
return; |
de827b8f7a2a3ce7fb46a73c96656783e02874e0718da9a7e03fa76695799194 | MATLAB | 309 | 20 | function minV = findMinLength(fpr_iter, fnr_iter)
%init
minV = 1e9;
for i = 1 : numel(fpr_iter)
l = length(fpr_iter{i});
if l < minV
minV = l;
end %if l
end %for i
for i = 1 : numel(fnr_iter)
l = length(fnr_iter{i});
if l < minV
minV = l;
end %if l
end %for i
|
f627dbdfb09bec6dffc64516e0e57d61cc962367088c8c3b045ca95ae9c158d1 | MATLAB | 309 | 14 | function display(obj)
% Display a NIFTI-1 object
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: display.m 8776 2013-11-14 09:04:48Z roboos $
disp(' ');
disp([inputname(1),' = '])
disp(' ');
disp(obj)
disp(' ')
|
0e7e1b3f455cfd13cc651876c3df6a1606be73953d20f909f43a0cd08453c9da | MATLAB | 310 | 23 | function [FD cat_FD FD_TR]=get_frame_removal(filename,ticks);
if nargin<2
ticks=51;
end
load(filename);
try
mot=FD_data;
end
try
mot=motion_data;
end
cat_FD=mot;
FD_TR=mot{1}.epi_TR;
[r c v]=size(mot);
if v==1
FD=zeros(1,ticks);
end
for j=1:ticks
FD(j)=mot{j}.remaining_frame_count;
end
|
440951b5ba564e4bc0be8bd9175b3ddb8d8e5cafc3d27595480f85d5aa354aea | MATLAB | 310 | 15 | function n=num_vertices(A)
% NUM_VERTICES The number of vertices in a graph.
%
% n = num_vertices(A) returns the number of vertices in graph A.
%
% Example:
% A = sparse(ones(5));
% n = num_vertices(A);
%
% See also NUM_EDGES
% David Gleich
% Copyright, Stanford University, 2006-2008
n = size(A,1);
|
71d5979b04b14637d04018284f37ef29774f1bf9bbb69f579017e1c0b9bd271c | MATLAB | 310 | 10 | function [similarity indSim] = SSSimColour(a, b, blobStruct)
% Calculate similarity for a single edge.
% a is blob a.
% b is blob b.
% blobStruct is the list of blobStruct
% Histogram intersection
similarity = sum(bsxfun(@min, blobStruct.colourHist(:,a), blobStruct.colourHist(:,b)));
indSim = similarity;
|
38a23d1e71f0c5bacf9932155f0c312df5c6a961ee2a5a4bdcac0b368ffad698 | MATLAB | 311 | 11 | function [spiketrain,ytrue] = SimulateSpike(splinematrix,theta,lastknot,nsteps)
spiketrain = zeros(nsteps,1);
for i=lastknot+1:nsteps
lambda(i) = exp(theta*[1; splinematrix'*spiketrain(i-1:-1:i-lastknot)]);
spiketrain(i) = min(poissrnd(lambda(i)),1);
end
ytrue = glmval(theta',splinematrix,'log');
end
|
dcd2b1b4be04378511fd42453dd406699b04aa893291d344b5b622c1a82458d0 | MATLAB | 311 | 13 | function [xs] = ml_alg_circ_movmean(x, M)
if mod(M,2) ~= 1
error('Windows size needs to be odd-valued');
end
MH = (M-1)/2;
y = [x(end-MH+1:end), x, x(1:MH)];
% Older versions of MATLAB do not have "movmean"
z = movmean(y, [MH, MH]);
xs = z(MH+1:end-(MH));
end
|
41e479d4764e926fe0f24a5250aaffd983a500479147b6787a70d57edb967172 | MATLAB | 312 | 19 |
% choice of tissue_dim: 4x4, 4x2, 4x1 (for Fig5)
% For supplementary:
% 1x1, 1x2, 1x4
% 2x1, 2x2, 2x4
% 4x1, 4x2, 4x4
% just set tissue_dim accordingly
%
tissue_dim = '4x4'; %<----
bem0_load_model;
bem1_setup_coil;
bem2_charge_engine;
bem4_define_planes;
bem5_figure_scales;
bem5_volume_XY;
bem5_volume_YZ;
|
8f7b56d93087c268fdc79c4091aa00b585e48a94bebdd77bd22c0220c65a8cf2 | MATLAB | 312 | 14 | function display(obj)
% Display a file_array object
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: display.m 8776 2013-11-14 09:04:48Z roboos $
disp(' ');
disp([inputname(1),' = '])
disp(' ');
disp(obj)
disp(' ')
|
db8ea2587a6813d3d0af2c246161e10a247554577f29b19a949eb275ce7f3903 | MATLAB | 312 | 10 | function [similarity indSim] = SSSimTexture(a, b, blobStruct)
% Calculate similarity for a single edge.
% a is blob a.
% b is blob b.
% blobStruct is the list of blobStruct
% Histogram intersection
similarity = sum(bsxfun(@min, blobStruct.textureHist(:,a), blobStruct.textureHist(:,b)));
indSim = similarity; |
084e243ac9a33000bee52c2eff064333d2bbb6b174c34309d1bc38f7aa72f1fa | MATLAB | 313 | 8 | function w = padded_conv(u, v)
%This function takes variables u and v, convolves them like
%conv(u,v,'same') but without the edge effect of the sharp jump
padded_u = [repmat(u(1),1,length(v)), u, repmat(u(end),1,length(v))];
w = conv(padded_u, v, 'same');
w = w(length(v)+1:length(v)+length(u));
end
|
41ea483583ceb1e6d107188b88727ad6511c8c7a5a4a8acce6374bb45c67f1fb | MATLAB | 313 | 12 | function out = double(fa)
% Convert to double precision
% FORMAT double(fa)
% fa - a file_array
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: double.m 8776 2013-11-14 09:04:48Z roboos $
out = double(numeric(fa));
|
a9a911101468c7931ce628055d0966dd4b10dfd5d7862e0de76e31eaba1eb856 | MATLAB | 313 | 7 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [hFig] = plot_average_rate_differences_within_across_bars(T)
R = compute_average_rate_differences_within_across_for_table(T);
hFig = plot_average_rate_differences_within_across_bars_table(R);
end % function
|
edbcd12829dec82a31e07c0efde11b9b783fc96cebb851a63c17ae4f59363c2b | MATLAB | 313 | 9 | function varargout = ctranspose(varargin)
% Transposing not allowed
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: ctranspose.m 8776 2013-11-14 09:04:48Z roboos $
error('file_array objects can not be transposed.');
|
091445f217916d6d746bce5db242b513ade581b001de52314104be5ecba8a233 | MATLAB | 314 | 10 | function [similarity indSim] = SSSimFlow(a, b, blobStruct)
% Calculate similarity for a single edge.
% a is blob a.
% b is blob b.
% blobStruct is the list of blobStruct
% Histogram intersection
similarity = sum(bsxfun(@min, blobStruct.flowHist(:,a), blobStruct.flowHist(:,b)));
indSim = similarity;
|
b0100a244e067baa9dd8ce531d501fea8457a408c59739312c08c6f618845a2d | MATLAB | 314 | 11 | function v=SONGetVersion(fh)
% SONGETVERSION returns the SON file system version number for a file
%
% VERSION=SONGETVERSION(FH)
% where fh is the SON File handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
v=calllib('son32', 'SONGetVersion', fh); |
0d470a2c0ea1414ec507d3add4217c1567780adb7210cd1cb6e748c8973ced25 | MATLAB | 315 | 18 | % Vertical Investigation for calibration issues
%% Open Files
file = 'G:\My Drive\Expmt Data\2019_09 - Kiah Calibration\Calibrations Modified';
fileInfo = dir([file '/*/*videoresults.mat']);
for i = 1:length(fileInfo)
cd(fileInfo(i).folder);
findmagscaleVel
end
%% Plot x and y values of video |
7cb0b45efaacb409a90d1c2fdd24061022e8b0f86e4e11e9eca06c94993949d6 | MATLAB | 315 | 15 | function [head,tail] = period(r,multiFreq)
%PERIOD Get last period
% Detailed explanation goes here
head = zeros(5,1); tail = zeros(5,1);
if multiFreq
idx = 2;
else
idx = 1;
end
for i = 1:5
[pks,locs] = findpeaks(r(5,:,i));
head(i) = locs(end-idx);
tail(i) = locs(end);
end
end
|
369e6120b45a1fcadf8da7af68726e0bf4b45630b710ed5a94ca7078d2774d11 | MATLAB | 316 | 11 | function result = get_scratch_folder_path()
if ispc() ,
result = tempdir() ;
elseif ~isempty(getenv('LSF_BINDIR')) ,
% We assume we're on a cluster node
user_name = get_user_name() ;
result = fullfile('/scratch', user_name) ;
else
result = tempdir() ;
end
end
|
36a646b572d9550ca96aec999fb46e8840b3266fc7a1f94855f083a5b3683b04 | MATLAB | 316 | 16 | function err=SONEmptyFile(fh)
% SONEMPTYFILE Deletes data written to file FH
%
% ERR=SONEMPTYFILE(FH)
% - see CED documentation for details
%
%
% Malcolm Lidierth 05/05
% Copyright © The Author & King's College London 2005-2006
if nargin<1
err=-1000;
return;
end;
err=calllib('son32','SONEmptyFile',fh); |
8ab1e894b8053f522660b0825f5f85876469cba555dc2e98fc617401c698a41d | MATLAB | 316 | 12 | function n=SONMaxChans(fh)
% SONMAXCHANS returns the number of channels supported by a SON file
%
% N=SONMAXCHANS(FH)
% where FH is the SON file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
n=calllib('son32','SONMaxChans',fh);
|
cdce1009eaed9a685c84faf98d6b96a923a4a7f6eeee1fe37e569ee32a7359c6 | MATLAB | 316 | 10 | function varargout = transpose(varargin)
% Transposing is not allowed.
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
% $Id: transpose.m 8776 2013-11-14 09:04:48Z roboos $
error('file_array objects can not be transposed.');
|
1c0075132d2a0153fda6c589141414049b7da09f2d03e2f327e071bfa0042444 | MATLAB | 317 | 6 | clear
load('P:\MSEv1.0\000000000200894\Genuine\000000000200894_Genuine_000000000200894_1_7268_11.5251.mat');
epoc_length=subject.EpochLength;
chanlocs = '.\insightCED.ced';
eegData=subject.EEG;
[d,eegICAprunned]=preProcessingPipeLine2(eegData,epoc_length,chanlocs);%% 'eegICAprunned' IS YOUR PREPROCESSED SIGNAL. |
e7df1d3e0d5f7fcf2ee9152108864e31147faff531e3de8673b51e4dab9ae74d | MATLAB | 317 | 15 | function [map,textons] = computeTextons(fim,k)
% function [map,textons] = computeTextons(fim,k)
d = numel(fim);
n = numel(fim{1});
data = zeros(d,n);
for i = 1:d,
data(i,:) = fim{i}(:)';
end
[map,textons] = kmeansML(k,data,'maxiter',30,'verbose',0);
[w,h] = size(fim{1});
map = reshape(map,w,h);
|
08cb1200360bfd2ef8d1a68347e8946a286212220d5b0b7b16b06debd6d56112 | MATLAB | 318 | 11 | function bytes=SONFileBytes(fh)
% SONFILEBYTES Returns the number of bytes in the file
% BYTES=SONFILEBYTES(FH) where FH is the file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
bytes=calllib('son32','SONFileBytes',fh);
return; |
a09639f7cab31b6993a505ea8b7c6dabf116b49329e2cfa9c529143551943fa6 | MATLAB | 318 | 11 | % SONFACTIVE tests filter mask layers to see if they are active
%
% Implemented through SONFActive.dll
%
% ANS=SONFActive(FilterMask)
%
% Bits 0 to 3 are set in ANS if filter mask layers 0 to 3 are active.
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006 |
dea52071a67b0c17b4eddb92be8adcc5b724d3ddbff6ee1fced18533706b7234 | MATLAB | 318 | 10 | function bytes=SONGetExtraDataSize(fh)
% SONGETEXTRADATASIZE returns the size of the extra data area of file FH in bytes
%
% BYTES=SONGETEXTRADATASIZE(FH)
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
bytes=calllib('son32', 'SONGetExtraDataSize', fh); |
e1ac87f29e519aa908a53cc7dd0257e40b35c588b007fc8ff52ed630a752543e | MATLAB | 318 | 14 | function gen_or_imp = checkGenOrImp(fileName_1, fileName_2)
%IITD
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ind1 = getIndName_IITD(fileName_1);
ind2 = getIndName_IITD(fileName_2);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if strcmp(ind1, ind2) == 1
gen_or_imp = 'gen';
else % if strcmp
gen_or_imp = 'imp';
end %if strcmp
|
fd8c5c1f293a1e4c6a6ed5ddf8b853e1f6dbcc80051f3fc856cebfd4aca89b7c | MATLAB | 318 | 9 | function [similarity indSim] = SSSimTextureFlowSizeFill(a, b, blobStruct)
% Texture + Flow + Size + Fill
indSim(:,1) = SSSimTexture(a, b, blobStruct);
indSIm(:,2) = SSSimFlow(a, b, blobStruct);
indSim(:,3) = SSSimSize(a, b, blobStruct);
indSim(:,4) = SSSimBoxFillOrig(a, b, blobStruct);
similarity = mean(indSim, 2); |
4ea936535d20950af39abc7ac680b08411633a209dd0636a79af4a3b009ead23 | MATLAB | 319 | 15 | function [bases,phi] = RaisedCos(t,a,b,nbases,cntrspace)
input_cos = a*log(t + b);
phi_srt = min(input_cos);
phi_end = max(input_cos);
phi = phi_srt:cntrspace:phi_end;
bases = zeros(length(t),nbases);
for i = 1:nbases
bases(:,i) = ( cos( ...
max(-pi, min(pi,(input_cos - phi(i)) )) ) ...
+ 1) / 2;
end
end
|
e75db6526b261bf2d90a7f566914dfdc92a1d9d3dd4af919ae196038bbbce837 | MATLAB | 319 | 11 | function bytes=SONFileSize(fh)
% SONFILESIZE Returns the expected size of a file
% BYTES=SONFILESIZE(FH) where FH is the file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
bytes=calllib('son32','SONFileSize',fh);
return; |
0a513a8a572e1ffb76eceef9243f2cf3b444afc73865973cbd38f499ab0fa83f | MATLAB | 320 | 13 | function [dr,ds] = getDistancesForEachSegment(data)
data = sortrows(data,'hg38_pos');
dx = abs(data.x_um(1:end-1)-data.x_um(2:end));
dy = abs(data.y_um(1:end-1)-data.y_um(2:end));
dz = abs(data.z_um(1:end-1)-data.z_um(2:end));
ds = abs(data.hg38_pos(1:end-1)-data.hg38_pos(2:end));
dr = sqrt(dx.^2+dy.^2+dz.^2);
end |
84c6a52801c673607b1c1e8e851e46cff78a2654989c9154ce1f93a385848de7 | MATLAB | 320 | 9 | function [similarity indSim] = SSSimColourTextureSizeFill(a, b, blobStruct)
% Colour + Texture + Size + Fill
indSim(:,1) = SSSimColour(a, b, blobStruct);
indSim(:,2) = SSSimTexture(a, b, blobStruct);
indSim(:,3) = SSSimSize(a, b, blobStruct);
indSim(:,4) = SSSimBoxFill(a, b, blobStruct);
similarity = mean(indSim, 2); |
d0504617f6ca52b510664af8f7ddac7c05b226e08d0d7cde71d40d46fdbf3b49 | MATLAB | 321 | 16 | %
% Compute a link prediction measure.
%
% PARAMETERS
% measure Name of measure
% p (e*1) Predictions
% T (e*3) To be predicted
%
% RESULT
% value Link prediction measure ; higher is better
%
function [value] = measure_compute(measure, p, T)
fh = str2func(sprintf('measure_compute_%s', measure));
value = fh(p, T);... |
485f975d212fd49792d3f58c29d9c2508de361a6dffbfc0d27c07ceb08c7f890 | MATLAB | 324 | 11 | function v=SONGetVersion(fh)
% SONGETVERSION returns the SON file system version number for a file
%
% VERSION=SONGETVERSION(FH)
% where fh is the SON File handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
v=calllib('son32', 'SONGetVersion', f... |
86ff2b7434ad27d6e2d898114f71d759407cfddd5a3e061aad80d88bf20d351e | MATLAB | 324 | 11 | function chan=SONGetFreeChan(fh)
% SONGETFREECHAN returns the number of the first free channel in a file
%
% CHAN=SONGETFREECHAN(FH)
% where FH is the SON file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
chan=calllib('son32', 'SONGetFreeChan', fh... |
198b0e647a1d6ae7cdd36737b900e5826a2dcf6c8c55d8010d5f82ac399b5db8 | MATLAB | 325 | 6 | function behavcam_roi_create( obj, session, trial )
% Ask the user to define the ROI
[pROI] = ml_cai_behavcam_roi_create( trial.getAnalysisDirectory(), 'verbose', obj.isVerbose(), 'includeOtherROI', obj.Config.includeOtherRoi==1 );
save(fullfile(trial.getAnalysisDirectory(), 'pROI.mat'), 'pROI');
end % fun... |
6943d8c7f2d85b6e3241824057259a7c9ed9ae18283aebf801f4c6457e7fc08a | MATLAB | 325 | 11 | SessionName = '20150906Thalamus36';
base_folder = SessionName;
Files = getFiles(base_folder);
filename = sprintf('%s\\%s',base_folder,Files{mm});
[spikes, LFP, theta, nose,Fs] = getSpikes(filename);
Nframes = length(nose.x);
[Nelecs, Nunits]=size(spikes);
save ('tessdata1','Fs','spikes','theta','nose','LFP')... |
6c70a1c0152785dfafa50bb495b5ae037bbec2a3a5bdcd2e79e3f948c2c95b45 | MATLAB | 325 | 11 | function chan=SONGetFreeChan(fh)
% SONGETFREECHAN returns the number of the first free channel in a file
%
% CHAN=SONGETFREECHAN(FH)
% where FH is the SON file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
chan=calllib('son32', 'SONGetFreeChan', f... |
2baab1f1742123de05b1fcaba86d9f1464c887b62f81c1221f667ce44f9c4c70 | MATLAB | 326 | 17 | function [ynn_t,nn_stat] = TrainNLS(Imat_t,dsr_t,nh,no)
u = Imat_t;
net_s = newff(Imat_t,dsr_t,nh,{'logsig','logsig'},'trainlm');
net_s.trainParam.max_fail = 1000;
net_s = init(net_s);
net_s.trainParam.epochs = 5000;
[net_s,tr_s] = train(net_s,u,dsr_t);
nn_stat = net_s;
ynn_t = (sim(nn_stat,u))';
... |
d0677c5dde4a0285d3453d99e7b9d58f17cf91dd630fa48a4890d14d26991b1c | MATLAB | 326 | 12 | function [cycleMat, cycleMean] = VOR_breakTrace(cycleLength, startpt, vector)
[cycleMat, ~] = vec2mat(vector(startpt:end), cycleLength, NaN);
% Remove first 5 cycles (to account for drift)
%cycleMat(1:5,:) = [];
% Remove final (partial) cycle
cycleMat(end,:) = [];
% Calculate Cycles Mean
cycleMean = nanmean(cycleMa... |
18f9c131f3473bfb386466f72937e1a7ad06fd8d439df1a9cd86f370bd173791 | MATLAB | 327 | 12 | function [edgesX] = ml_it_edges_x_uniform_density(x)
nBinsX = 100;
x = reshape(x, 1, numel(x));
nSamples = length(x);
minX = min(x, [], 'all');
maxX = max(x, [], 'all');
nSamplesPerBinX = ceil(nSamples ./ nBinsX);
sx = sort(x);
edgesX = unique([minX, sx(1:nSamplesPerBinX:end), maxX... |
2fa99da262f0bd67ad66d01e22d25936ea3e6e42ea71f3c3c75275d568078eaf | MATLAB | 327 | 9 | OCVRoot = 'D:\OpenCV2p49\opencv\build';
IPath = ['-I',fullfile(OCVRoot,'include')];
LPath = fullfile(OCVRoot, 'x64','vc12','lib');
% lib1 = fullfile(LPath,'cv210d.lib');
lib2 = fullfile(LPath,'opencv_core249d.lib');
lib3 = fullfile(LPath,'opencv_highgui249d.lib');
mex('edgesDetectMex.cpp', IPath, lib2, lib3, ... |
4468c8ce40b296fdf4f788a6c3bdadba665266a845546ec56eb15053cf371c04 | MATLAB | 327 | 10 | function bytes=SONGetExtraDataSize(fh)
% SONGETEXTRADATASIZE returns the size of the extra data area of file FH in bytes
%
% BYTES=SONGETEXTRADATASIZE(FH)
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
bytes=calllib('son32', 'SONGetExtraDataSize'... |
f615240a663be3f8f4d7fa750b02058f19f02e4a4099af44d946a6a5ee84045b | MATLAB | 327 | 12 | '20160601Thalamus45_opF'
'20160602Thalamus48_opF'
'20160602Thalamus49_opF'
'20160603Thalamus39_opF'
'20160603Thalamus44_opF'
'20160730Thalamus43_opF'
'20160730Thalamus44_opF_Nw'
'20160730Thalamus45_opF_Nw'
'20160730Thalamus48_opF_Nw'
'20160801Thalamus43_opF_Nw'
'20160904Thalamus40_opF'
'20160905Thalamus40_op... |
2f3b0822ee3ec54075a4ccb8e465846831aa67fab8b7eaa08d8f122b70698495 | MATLAB | 328 | 22 | function ynn_v = ValNLD(Imat_v,dsr_init,nn_dyn,Xi,Ai,tv,no)
u_v = Imat_v;
X = tonndata(u_v,true,false);
yv = nn_dyn(X,Xi,Ai);
yn = zeros(no,tv-1);
for i = 1:tv-1
yn(1:no,i) = yv{i};
end
ynn_v = zeros(tv,no);
ynn_v(1,1:no) = dsr_init;
for i = 1:no
ynn_v(2:tv,i) = (yn(i,:))';
en... |
4d8494f702d46db4a04e95e5b02a2568f48e5bfee301e1b4cc0ad9c5ed321cf2 | MATLAB | 328 | 11 | % SONFACTIVE tests filter mask layers to see if they are active
%
% Implemented through SONFActive.dll
%
% ANS=SONFActive(FilterMask)
%
% Bits 0 to 3 are set in ANS if filter mask layers 0 to 3 are active.
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 20... |
5ef13266c5798318deea2b41b3bed7924cbff9f26545623f6cb913cb85df2b97 | MATLAB | 328 | 9 | function [similarity indSim] = SSSimColourTextureSizeFillOrig(a, b, blobStruct)
% Colour + Texture + Size + Fill
indSim(:,1) = SSSimColour(a, b, blobStruct);
indSim(:,2) = SSSimTexture(a, b, blobStruct);
indSim(:,3) = SSSimSize(a, b, blobStruct);
indSim(:,4) = SSSimBoxFillOrig(a, b, blobStruct);
similarity = mean(ind... |
c2e9f3f4a93379109cd2549f0718cedb9a556b1db5afb0932187ba4585083ed6 | MATLAB | 328 | 16 |
function output_valid=check_valid_net_output(output_info)
% output_valid=true;
if isempty(output_info)
output_valid=false;
else
output_valid=output_info.forward_finished;
% if isfield(output_info, 'valid_data')
% if ~output_info.valid_data
% output_valid=false;
% end
% end
... |
c39a3443fda0040bb89d6d58657599e9e3a4cdb13c8d05e23c840c7339e62590 | MATLAB | 328 | 12 | function [theta_max,A,theta_A,B] = had_fit_sin(OPT_S,ints)
X=OPT_S.H_hat*ints;
phases = OPT_S.phases;
% ints = A*cos(phases + theta) + B
A = sqrt(X(1)^2+X(2)^2);
theta_A = atan2(X(2),X(1));
B = X(3);
theta_max = -theta_A;
x_est = A*cos(phases+theta_A)+B;
figure(1251234);plot(phases,ints);hold on;
plot(phases,x_est);hol... |
ed8723904039309dadc4d2c0c7d1dceda0da1061278cdfd92e0b956532bbf32a | MATLAB | 328 | 11 | function bytes=SONFileBytes(fh)
% SONFILEBYTES Returns the number of bytes in the file
% BYTES=SONFILEBYTES(FH) where FH is the file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
bytes=calllib('son32','SONFileBytes',fh);
... |
fd36f456f9352e4581c9797559a7a442cca7e9b408de18771494d9db2f882429 | MATLAB | 328 | 12 | function DPF = age2DPF(age, wl)
% This function calculates the DPF based on age and wavelength(wl) as given by the formula of
% Scholkmann & Wolf, 2013 (https://doi.org/10.1117/1.JBO.18.10.105004)
a = 223.3;
b = 0.05624;
g = 0.8493;
d = -5.723 * 10^(-7);
e = 0.001245;
z = -0.9025;
DPF = a + b*age^g + d*wl^3 + e*wl^2 ... |
13d696d6c3e6e7937bffb43683f1efcf20fc0b96130d824bd25140802f3e07c3 | MATLAB | 329 | 15 | function labelidx = FlyTrackerBouts2LabelIdx(bouts,nframes)
nflies = numel(bouts);
labelidx = zeros(nflies,nframes);
for fly = 1:nflies,
if isempty(bouts{fly}),
continue;
end
labelidx(fly,:) = 2;
for i = 1:size(bouts{fly},1),
t0 = bouts{fly}(i,1);
t1 = bouts{fly}(i,2);
labelidx(fly,t0:t1) = 1;
... |
111a5f4d8f1bf6a37cc09f28a8e4d2e99dd7548ac2c57316c95d2d36524a955c | MATLAB | 330 | 6 | %capture ground truth from validation camera
SC = set_PG_BP(SC);
SC = laser_set(SC.laser_settings.laser_big_FOV,SC); %set laser to big area
I = capture_PG_area_ramps(SC,FOV.TS_scan(end)/4,FOV.TS_scan(3)-FOV.TS_scan(1),'Ground Truth');
FOV.big_FOV_PG_finish = I;
figure;imagesc(I);title('Big a... |
2f8908366de949faca820c93446ed8dd17c0f3ea9d2b28a9a90a66745e026962 | MATLAB | 331 | 16 | function err=SONEmptyFile(fh)
% SONEMPTYFILE Deletes data written to file FH
%
% ERR=SONEMPTYFILE(FH)
% - see CED documentation for details
%
%
% Malcolm Lidierth 05/05
% Copyright © The Author & King's College London 2005-2006
if nargin<1
err=-1000;
return;
end;
err=calllib('son32','SONEmpty... |
7ad7c1abf4e33ad9f8e82395db4def2e21e4b069974abb6aa24787243555d9aa | MATLAB | 331 | 18 | function [cell_stat,redcell_vect,Fall]= convert_to_isCell(Fall,redcell_vect)
% convert stat and redcell_vect to be in isCell==1 coordinates
stat=Fall.stat;
iscell=Fall.iscell;
cell_stat=stat(iscell(:,1)==1); % reduce stat to only iscells
redcell_vect=redcell_vect(iscell(:,1)==1);
Fall.redcell_vect=redcell_ve... |
c31f57e032394f13cf9238bcd6ecb787c1dca00cfaa5fc7e5c39a028cf84a098 | MATLAB | 332 | 8 | function stabilityI = stability(xmat)
[R C] = size(xmat);
half1 = nanmean(xmat(1:floor(R/2),:),1);
half1 = smooth(half1,3); % Nachum (and all other head dir people) use 3
half2 = nanmean(xmat(floor(R/2+1):end,:),1);
half2 = smooth(half2,3); % Nachum (and all other head dir people) use 3
stabilityI = corr(half1,ha... |
ca12d3c3bf7191a4e8ced951fd5b1c8493ba952595c9c645ba83b6b53e30d936 | MATLAB | 332 | 4 | function s = zasoFxysum(zaso, fct, varargin)
% This may look stupid, but it is to reduce a very likely and hard to debug problem where one calls z1.fxsum(z2, fct) which is nonsensical. This function makes the interface more Python-like and requires only one reference to the object.
s = zaso.fxysum(zaso, fct, vararg... |
6aa3462aa1c8ee6be67d5ec105405969342d1cf4217672d5b412bd679e9ac125 | MATLAB | 333 | 15 |
% Close an open video.
%
% video_close(vinfo)
%
% closes any open files associated with the video specified by vinfo.
%
function video_close(vinfo)
% check video type
if (strcmp(vinfo.type,'seq'))
vinfo.seq.sr.close();
elseif strcmpi(vinfo.type,'ufmf'),
try fclose(vinfo.ufmf.fid); end %#ok<TRYNC... |
5ac7f19a280ba154ee3954d84cd429720d8ad51bfe491e66df56e2651ef7f706 | MATLAB | 334 | 26 | for i=1:50
ExampleCreateFile
clear
end
disp('Create done')
for i=1:50
ExampleCopy
clear
end
disp('Copy done')
for i=1:50
ExampleMask
clear
end
disp('Mask done')
for i=1:50
ExampleFilter
clear
end
disp('Filter done')
for i=1:50
ExampleDownSample
clear
end
clear functions
disp('Dow... |
a939722580471e0011deed9a72bdd81c6e951a86cedc047b2288af59fef1c37c | MATLAB | 334 | 24 |
function my_check_valid_numeric(feat_data)
try
tmp_check=any(isnan(feat_data)) | any(isinf(feat_data));
while numel(tmp_check)>1
tmp_check=any(tmp_check);
end
assert(~gather(tmp_check));
catch err_info
disp('my_check_valid_numeric failed');
dbstack;
keyboa... |
b97cf3123467a03fd08b64b5455a0939614bce32ff97dfd5430b337bc17363bd | MATLAB | 334 | 18 | % pDataPath.m
%
% Function that returns pDataPath as string. pDataPath is hard-coded into
% this function.
%
% INPUT:
% none
%
% OUTPUT:
% pdPath - full pData path, as string
%
% CREATED: 8/28/19 - HHY
% UPDATED: 8/28/19 - HHY
%
function pdPath = pDataPath()
pdPath = '/Users/hyang/Dropbox (HMS)/2PAnalysis-Hel... |
11e6c0206e20dc91800b1e9288775028c3e17359f129ac7530be77dbe850ed11 | MATLAB | 335 | 10 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [J] = ml_alg_entropy_prep_image(I, NUM_BINS)
% J will be discrete valued
minI = min(I, [], 'all', 'omitnan');
maxI = max(I, [], 'all', 'omitnan');
J = (I - minI) ./ (maxI - minI) * NUM_BINS;
J =... |
7084901b867408a619e5c09564060d02c628c66ac918ff0d3f58b19c1158b20f | MATLAB | 335 | 8 | function [ triggerOnset] = sendTrigger( triggerDuration )
%send a trigger via USB-serial adapter using USBTTL function
% triggerDuration: in seconds (minimum 4ms trigger is needed for vision recorder to recognize trigger)
triggerOnset = GetSecs;
USBTTL_2('Set', 1);%default 1
WaitSecs(triggerDuration);%
USBTTL_2('Set', ... |
80d43c3fadb2e8aba2c3577eb940bf1210da60bcabe1ce292a27ee0efb023f26 | MATLAB | 335 | 11 | function chan=SONGetFreeChan(fh)
% SONGETFREECHAN returns the number of the first free channel in a file
%
% CHAN=SONGETFREECHAN(FH)
% where FH is the SON file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
chan=calllib('son32', 'SONGetFre... |
22e49a1585322c9aed489790e2976b86a8eba9fffb16f922d2c5705c726f0dcc | MATLAB | 336 | 18 | % patternsDir.m
%
% Function that returns path where visual patterns live
%
% INPUTS:
% none
%
% OUTPUTS:
% patternDir - full path to visual patterns
%
% CREATED: 1/18/24 - HHY
%
% UPDATED:
% 1/18/24 - HHY
%
function patternDir = patternsDir()
patternDir = '/Users/hyang/Documents/EphysCode-Helen/Visual Stimul... |
5323aecbd72bf4a0b2b729994b62c9155873385eb23f0e3cf1c10e30ebec07f4 | MATLAB | 336 | 22 | function ynn_v = ValNLD4ParECNN(Imat_v,dsr_init,nn_dyn,Xi,Ai,tv,no)
u_v = Imat_v;
X = tonndata(u_v,true,false);
yv = nn_dyn(X,Xi,Ai);
yn = zeros(no,tv-1);
for i = 1:tv-1
yn(1:no,i) = yv{i};
end
ynn_v = zeros(tv,no);
ynn_v(1,1:no) = dsr_init;
for i = 1:no
ynn_v(2:tv,i) = (yn(i,:)... |
6f5c67efab055564dfb98c71f7666c1660c80eecf0e2fcba9599f8a9cdea8846 | MATLAB | 336 | 11 | function chan=SONGetFreeChan(fh)
% SONGETFREECHAN returns the number of the first free channel in a file
%
% CHAN=SONGETFREECHAN(FH)
% where FH is the SON file handle
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
chan=calllib('son32', 'SONGetFr... |
494abaf199545964ac6556e1cc9c979221d64dcf6151e1dbfab1dcda4031dff7 | MATLAB | 337 | 12 | function SONCommitFile(fh, bDelete)
% SONCOMMITFILE flushes data to disc
% FH is the SON file handle
% BDELETE ,if non-zero, causes the data buffers to be deleted
%
%
% Author:Malcolm Lidierth
% Matlab SON library:
% Copyright © The Author & King's College London 2005-2006
calllib('son32','SONCommitFile', fh, bD... |
555957c9680f8796962047ea73d27ade32a4179f50b169a05b7c22c22105272e | MATLAB | 337 | 10 | % mglShader.m
%
% $Id: mglShader.m,v 1.4 2007/01/17 15:49:49 justin Exp $
% usage: mglShader('command', [args])
% by: Christopher Broussard
% date: 11/13/07
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: Performs various shader functions.
% usage:... |
8ef844eafdfdf0f32fbd43cbb8eaee05371630c6a57c4ca91d9070fd10dd8ef5 | MATLAB | 337 | 9 | function [h] = ml_imagesci(I)
% This plots the data like imagesc, but uses pcolor so interpolation
% can be used. We have to flip the coordinates to match imagesc.
M = nan(size(I,1)+1, size(I,2)+1);
M(1:size(I,1), 1:size(I,2)) = I;
h = pcolor( M );
shading interp;
set(gca, 'ydir', 'reverse')... |
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