sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2f4e8599dff68947843a24bfd88989f5e3ca66950a4801099093b98113b37728 | MATLAB | 1,202 | 22 | function sp_min2nat_apply(fn_mni_para,fn_mni_mask,fn_nat_img,fn_y_def,saving_dir)
% this is subject-specific process
[~,fn] = fileparts(fn_nat_img);
matlabbatch = {};
matlabbatch{1}.spm.util.defs.comp{1}.inv.comp{1}.def = fn_y_def;
matlabbatch{1}.spm.util.defs.comp{1}.inv.space = fn_nat_img;
matlabbatch{1}.spm.ut... |
4b3eb9acd72fff55e24e7042d851fe134af9442cf105a4f4d124e1824eea98c6 | MATLAB | 1,202 | 34 | %% normpdfcol2zero
% A method to nomalize the negative components of a column vector/ SDO such
% that the sum of the column is 0.
%
% Copyright (C) 2023 Trevor S. Smith
% Drexel University College of Medicine
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of t... |
69c89fabcfa8abd8df413478e49008469f6f2a11e56d18854610dd9c2bda82f0 | MATLAB | 1,202 | 31 | function [ pulseTime, pulseRecorded ] = utils_WaitForTRPulse( trLength, triggerKey, inputDevice, timeToWait )
% (c) Coraline Rinn Iordan 10/2017
if nargin < 3, inputDevice = -3; end
if nargin < 4, timeToWait = inf; end
pulseTime = -1; pulseRecorded = false;
loopDelay = 0.0005; % half a milisecond!
timeout = 0.050; % ... |
978869592376646331163fc0f241bb6868bbd3b464c6b812b90d78976e4433ab | MATLAB | 1,202 | 21 | %% Line (Trapezoid)
kx = linspace(-5,5, 256)';
ky = 0*kx;
kz = 0*ky;
C = [kx ky kz];
[C_rv, time_rv, g_rv, s_rv, k_rv] = minTimeGradient(C,0, 0, 0, 4, 15, 4e-3); % Rotationally variant solution
[C_riv, time_riv, g_riv, s_riv, k_riv] = minTimeGradient(C,1, 0, 0, 4, 15, 4e-3); % Rotationally invariant solut... |
c24b8c7c5a8360e04f5d48a5a3f0c79a739f4543e98633d108cae2e27cd4f2a9 | MATLAB | 1,202 | 31 | function [ pulseTime, pulseRecorded ] = utils_WaitForTRPulse( trLength, triggerKey, inputDevice, timeToWait )
% (c) Coraline Rinn Iordan 06/2018
if nargin < 3, inputDevice = -3; end
if nargin < 4, timeToWait = inf; end
pulseTime = -1; pulseRecorded = false;
loopDelay = 0.0005; % half a milisecond!
timeout = 0.050; % ... |
1c782750949a6aae063812bbda0cb963d5b029a5eecec1247886cb66bb9ff790 | MATLAB | 1,203 | 34 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
1d97e98d118cc49953822dc07607468df8ec26148d813c2bc58f5ff88fa41d5e | MATLAB | 1,203 | 46 | function relativePath = h_getRelativePath(path1, path2)
% this function try to get the relative path from path1 to path2.
length1 = length(path1);
length2 = length(path2);
minLength = min([length1, length2]);
ind = find(~(lower(path1(1:minLength))==lower(path2(1:minLength))),1);%1:ind-1 are the same for bo... |
2e1c8a8835e1a414bc437bb8bc7a8d606c3f2e4d7f62fc7d0986d657c86d2b4c | MATLAB | 1,203 | 43 | function local = islocal(varargin)
% Return true iff the method is locally defined in the class
% which means
%
% (1) the method is implemented in the class, (or at least abstractly defined so long as allowAbstract = true)
% (2) the method is not the class constructor
% (3) the method is public
% (4) the method is not ... |
36e51c75dfe56bf2ba93a9d6806f24f994d54da899b5f21fcdf67c39f6d6c5c9 | MATLAB | 1,203 | 45 | function [S,Vx,Vy,Vz] = getsaliency( I, s, mode )
% GETSALIENCY Get ridge saliency and its normal
% INPUT:
% E - Input tomogram (foreground bright), input data must be single and double
% s - smoothing scale
% mode: 1-> analytical (fastest), 2-> hybird (intermediate) ohterwise-> Jacobi
% (... |
5a84008752e471e0e35d560de5ec8c15afdbce71f4309fd70d6b5ae63caedbee | MATLAB | 1,203 | 30 | % subspace estimations are based on permutations - values won't be excactly
% the same as in the paper
nPCs = 5;
P1 = [eye(nPCs); zeros(nPCs,nPCs)];
P2 = [zeros(nPCs, nPCs); eye(nPCs)];
eigvals_1 = eigs(Xcov{1}, nPCs, 'la');
eigvals_2 = eigs(Xcov{2}, nPCs, 'la');
% variance explained for each condition in ... |
9741359d676962f9b4f8b4207e288e202ae0cd2b0d3361591a95789966fa0c05 | MATLAB | 1,203 | 37 | function [FD_abs, FD_rms ] = compute_FD(mp,flag)
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% [FD_abs, FD_rms, FD_rmsvd ] = compute_FD(mp,afniflag)
% mp: nT x 6 rigid body head movement estimates
% flag: 2 if motion parameters are estimated using FSL
% 1 if motion parameters are estimated usi... |
b756d404dcbbd80adaf7be70c4b247787d52e61266de3a4a640f98c635303644 | MATLAB | 1,203 | 30 | % subspace estimations are based on permutations - values won't be excactly
% the same as in the paper
nPCs = 5;
P1 = [eye(nPCs); zeros(nPCs,nPCs)];
P2 = [zeros(nPCs, nPCs); eye(nPCs)];
eigvals_1 = eigs(Xcov{1}, nPCs, 'la');
eigvals_2 = eigs(Xcov{2}, nPCs, 'la');
% variance explained for each condition in ... |
f56717c4e71526796eac65e2546eb2912bc50fab473d15475f1ef480ec91dddb | MATLAB | 1,203 | 42 | function [ft,tBreak]=essential_distMinAnglePair_ftFromQ(t,Q1,Q2,varargin)
kFlip=1;
term='both';
ivarargin=1;
while(ivarargin<=length(varargin))
switch(lower(varargin{ivarargin}))
case 'kflip'
ivarargin=ivarargin+1;
kFlip=varargin{ivarargin};
case 'term'
... |
0b5e02614e2ccd3aff95a81d818efc091168abfbc3c0cbcb3d49540b336d5526 | MATLAB | 1,204 | 50 | %% Make the lung cancer dgm
%
%%
% This file is from pmtk3.googlecode.com
function dgm = mkLungCancerDgm(toporder)
% S
% / \
% v v
% CB LC
% \/ \
% v v
% SOB X
if nargin < 1, toporder = true; end
if toporder
S = 1; CB = 2; LC = 3; SOB = 4; X = 5;
names = {'S','CB','LC','SOB','X'};
e... |
55020817feb66eed06549fcac5d60a46fd772a27c97d1337903ca0b4372358ec | MATLAB | 1,204 | 33 | function result = fillInCustomStage1(rawTCI2, stage1Spec)
% Used to fill in the type of stage 1 in a custom two-stage tracker.
% This is a pure function.
if ~isempty(stage1Spec)
if iscell(stage1Spec) ,
stage1ConstructorArgs = stage1Spec ;
result = stage1ConstructorArgs ;
elseif isa(stage1S... |
e2a388daf3226e29ff4301c1d0d0e59943fe6bd7b9c042f107cbac123481d0d7 | MATLAB | 1,204 | 51 | function smart_3D_plot(mask,xyz,PET2D,hemi_scan,vox_size,angulation,figures_dir,vessel)
x=xyz(:,1);
y=xyz(:,2);
z=xyz(:,3);
indx=sub2ind(size(mask),x,y,z);
PET_voxs=PET2D(indx,:);
peaks=max(PET_voxs,[],2);
%%
figure()
subplot(121)
isosurface(mask)
% hold on
% p = patch(isosurface(vessels_PET,0.5));
... |
153ee92e40e63951ff531bb9f1b2fa82f1c06cab66b5623074f0b26302fe2e45 | MATLAB | 1,205 | 55 | %% PPCA Imputation Demo
% Reproduce fig 12. 11 from Bishop's book
%
% Data from http://www.ncrg.aston.ac.uk/GTM/3PhaseData.html
%%
% This file is from pmtk3.googlecode.com
loadData('oilFlow3Class');
ndx = 1:1000;
X = DataTrn(ndx,:); % 1000x12
y = DataTrnLbls(ndx,:); % 1000x3
setSeed(0);
[C, ss, mu, Z, Ximputed] = ... |
11fd873232334f30fe71e9d52c1d9b8c04370e374198b5044150ed34fb6908cb | MATLAB | 1,206 | 45 | function [S,Vx,Vy,Vz] = getsaliency( I, s, mode )
% GETSALIENCY Get ridge saliency and its normal
% INPUT:
% E - Input tomogram (foreground bright), input data must be single and double
% s - smoothing scale
% mode: 1-> analytical (fastest), 2-> hybird (intermediate) ohterwise-> Jacobi
% (... |
21e53dd0a1685273db5f1f100040e6e230a0a97be7589eacc3a22e15c30d9066 | MATLAB | 1,206 | 64 | function [boxedX,Bx,By]=boxpdf(X)
% Forces the pdf of data to have a boxed distribution using a data adaptive lookup table.
%
% [boxedX,Bx,By]=boxpdf(X)
%
% boxedX=N(X) where N is an data adaptive monotonically increasing function.
% boxedX vary between zero and one.
%
% Bx,By describes the lookup table
%
% (c) As... |
427fcfd9127390a05c3844b7bdd1026fc22aff1612227b244b70b74560ee9562 | MATLAB | 1,206 | 39 | %% Plot an MVN in 2D
%
%%
% This file is from pmtk3.googlecode.com
model = struct('mu', [0 0]', 'Sigma', [2 1.8; 1.8 2]);
figure; plotContour(@(x)gaussProb(x, model.mu, model.Sigma), [-5 5 -10 10]);
title('full');
printPmtkFigure gaussPlot2dDemoContourFull
figure; plotSurface(@(x)gaussProb(x, model.mu, model.Sigma)... |
4d380d7c59018cb637e33000cb1680fd7976f3397ae0d2862cbe01c0d76de5e4 | MATLAB | 1,206 | 33 | function [D,P] = dijkstra( G, varargin )
% Runs Dijkstra's shortest path algorithm on a distance matrix.
%
% Runs Dijkstra's on the given SPARSE nxn distance matrix G, where missing
% values mean no edge (infinite distance). Uses a Finonacci heap resulting
% in fast computation. Finds the shortest path distance from ev... |
89b7df306cff521452546a37b2c4e864fb512b274496c35407f243f25b8e2537 | MATLAB | 1,206 | 41 | function [uniquedays,sxperday,hax,hfig] = PlotLabeledReachPosXStdPerMouse(labeldata,Sperday,uniquedays,varargin)
[hax,hfig,mousename] = myparse(varargin,'hax',[],'hfig',[],'mousename','');
if isempty(hax),
if isempty(hfig),
hfig = figure;
else
figure(hfig);
end
hax = gca;
end
for i = 1:numel(labeldat... |
be11e5b46b138a4df1690636defeb27c12bbb0b5ee0d2cc48fe6d38cd8131cdb | MATLAB | 1,206 | 53 | function [C, grps, G] = grp2cell(X, G, dim)
%GRP2CELL Splits an array into a cell using a grouping variable.
% Usage:
% C = grp2cell(X, G)
% C = grp2cell(X, G, dim)
% [C, grps] = grp2cell(_)
%
% Args:
% X: array with at least one dimension of the same size as G
% G: grouping variable vector
% dim: dimensio... |
3907621ee32570d5c2ab5ab06c59fc16bf8fb321cb9c7db7c2fe4e97b2425e86 | MATLAB | 1,207 | 57 | %% Cluster yeast data using Kmeans
% This file is from pmtk3.googlecode.com
setSeed(0);
loadData('yeastData310') % 'X', 'genes', 'times');
figure;imagesc(X);
%colormap(redgreencmap) % bioinfoToolbox
colormap(redgreenColormap)
xlabel('time')
set(gca,'xticklabel',times)
ylabel('genes')
title('yeast microarray data')
... |
722daf873ecdfd7dbd2f93027c8b3602bccaf6c14d15e5a6f80129334c99f602 | MATLAB | 1,207 | 43 | %% Visualize projection onto the principal components
%
%%
% This file is from pmtk3.googlecode.com
setSeed(0);
n = 5;
X=[randn(n,2)+2.*ones(n,2);2.*randn(n,2)-2.*ones(n,2)];
[n d] = size(X);
%%%
[W, Z, evals, Xrecon2, mu] = pcaPmtk(X, 2);
Xrecon1 = Z(:,1)*W(:,1)' + repmat(mu, n, 1);
figure;
plot(X(:,1), X(:,2), '... |
551ac731c571f4a265cc395e14981afd0593abf9aacb75a55a217fe95fafc90b | MATLAB | 1,208 | 55 | %% var_decay
%
% Decay VAR coefficients
%
% <matlab:open('var_decay.m') code>
%
%% Syntax
%
% A = var_decay(A,dfac)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% A VAR coefficients matrix
% dfac decay factor
%
% _output_
%
% A ... |
65e3d0042b0e2f9d11b4a600ae25b8cdc803b4c619040298b1c8060cca2c02d9 | MATLAB | 1,208 | 40 | % CheckIfCorruptFast.m
% Sarah West
% 9/2/21
% Checks if a file/stack is corrupt WITHOUT HAVING TO LOAD IT :D
% Basis code is from https://stackoverflow.com/questions/38325121/check-if-mat-file-is-corrupt-without-load
% matfile doesn't need to load in the whole file, and it issues a warning
% if the file is corrupt.
... |
95f0062e1f10917b3778a63ef1d179cc2d218afc3ecd2cdb915b956718b6efe3 | MATLAB | 1,208 | 47 | function [fx] = f_HH(Xt, Theta, ut, inF)
% Hodgkin-Hoxley membrane potential evolution function
% function [fx] = f_HH(Xt,Theta,ut,inF)
% IN:
% - Xt: system's states, ie:
% Xt(1): membrane depolarization (mV)
% Xt(2:4): type I-II-III ion channel opening probabilities, in
% inverse-sigmoid space (Gau... |
fde15ed3dc720ec58b82c95ab3955c21394414095b6a0b47f90256eee21ad94b | MATLAB | 1,208 | 52 | %% Plot Linear Gaussian CPD p(y|x) = N(Y|a + bx, sigma)
% Here a is the offset and b is the slope.
%%
% This file is from pmtk3.googlecode.com
[xtrain, ytrain, xtest, ytestNoisefree, ytest] = polyDataMake('sampling','thibaux');
n = size(xtrain,1);
Xtrain = [ones(n,1) xtrain];
w = Xtrain\ytrain;
ntest = size(xtest,... |
93aca8f0a5831b7327c07a9dd3bef7d7c0e503e66cc40e1e6ce488213eae73d7 | MATLAB | 1,209 | 30 | %% Download Datasets
%% download and save the walking chamber dataset
websave('WalkingChamber.zip','https://www.dropbox.com/scl/fi/6d94o2k25hb2qup10e9ih/WalkingChamber.zip?rlkey=898sc0dxy1xevj5nv5x0inyf1&st=5k81ukyr&dl=1');
movefile WalkingChamber.zip Data.zip
if ~exist('WalkingChamberCodeBase/Data', 'dir')
mkdir(y... |
9b54326f3c0df12913aad04369d0275c2a3777da8a28253e0cdd5b2d877e19e3 | MATLAB | 1,209 | 47 | function [h_plot] = plotLogTuning2D(xvals, yvals, tuningcurve)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
yy = zeros(numel(yvals)+1, 1);
alldiffsy = diff(yvals);
yy(2:end-1, 1) = yvals(1:end-1) + alldiffsy/2;
yy(1) = yvals(1) - alldiffsy(1)/2;
yy(end) = yvals(end) + alldif... |
b60ec0af4a542def24a061483615cc728f5341856b4d247643fcf35b170c8028 | MATLAB | 1,209 | 45 | function softev = localEvToSoftEv(model, localev)
% Convert local evidence to soft evidence
% localev(:,t) is vector of observations for node t
% softev(k,t) is p(st=k| ev(:,t)) using model.localCPDs{t}
%
% Model can be any model with these fields:
% localCPDs, localCPDpointers
% If model.obsType = 'localev',
% we ju... |
bbf0cffa135f9c05efe4f20ab30c706d7b36f74c8e0b8aa37bdc0a02347c97dc | MATLAB | 1,209 | 37 | function X = matrandnorm(varargin)
%MATRANDNORM Normalizes columns of X so that each is unit 2-norm.
%
% X = MATRANDNORM(M,N) creates a random M x N matrix with randomly using
% normally distributed enries and then rescales the columsn so that each
% has a unit 2-norm.
%
% X = MATRANDNORM(X) rescales the column... |
d3011404fd7dab576a4ca456fc550800f36e07a373aadef9b89f87c24e3b450e | MATLAB | 1,209 | 53 | %% Probit Regression Demo
%
%%
% This file is from pmtk3.googlecode.com
setSeed(0);
N = 100; D = 2;
X = randn(N,D);
w = randn(D,1);
p = 0;
y01 = flipBits(double((X*w>0)), p); % add some label noise
ypm1 = sign(y01-0.5);
if statsToolboxInstalled
wGlm = glmfit(X,y01,'binomial','link','probit','constant','on');
N ... |
e0b6b4cbf52740a46bad692862fd05a6822f5215b6164b099009ca904e9c6c17 | MATLAB | 1,209 | 52 | function h = PhasePlot(x,y,phase,sz,varargin)
% Plots arrows indicating the phase on current axis.
%
% [h,yy,zz] = PhasePlot(x,y,phase,sz[,ArrowParameters])
%
%
% Requires the Arrow function by Erik A. Johnson.
%
% Note: Arrows will get skewed if you resize the axis.
%
% Aslak Grinsted 2003
% ----------------------... |
22447801a925641f674727c2a6b676a040be781b4df02b4773658622f9fece86 | MATLAB | 1,210 | 43 | function [Y_out, Y0] = j_detrend2b(Y_in, L, dim, norm_opt, med_opt)
% [Y_out, Y0] = j_detrend2b(Y_in, L, dim, norm_opt, med_opt)
% Input
% L: Number of frames over which to compute moving baseline Y0
% dim: Dimension across which to compute Y0
% norm_opt: Option to compute output as (Y-Y0)/Y0 (... |
eeff0eec1fa554c7abf613824abe11578ed41609c9f3031abc8a960f0c357bc3 | MATLAB | 1,210 | 43 | function headerinfo = ReadIndexedMJPGHeader(filename,indexfilename)
headerinfo = struct('filename',filename,'indexfilename',indexfilename,...
'nr',0,'nc',0,'nframes',0,'frame2file',[],'timestamp',[],'type','mjpg');
fid = fopen(indexfilename,'r');
if fid < 0,
error('Could not open file %s for reading',indexfilenam... |
2ffd8afffa8b1ca515011b0fe552a78f53be4895a3edc8a7be778acfc9064bc5 | MATLAB | 1,211 | 47 | function vcout=mk_vcharm(vc,center,coeffs);
% returns something
[nbasis,ndum]=size(coeffs);
order=sqrt(nbasis)-1;
vc=vc(:,1:3);
[nsurf,ndum]=size(vc);
vc=vc-repmat(center,nsurf,1);
block=1000;
nblock=ceil(nsurf/block);
vcoutall=[];
k=1;
for i=1:nblock
kb=min(k+block-1,nsurf);
blockloc=kb-k+1;
vcloc=vc(... |
994151c4bc1e559d506aefeee073db10c343d60f9addd65ab7b237bae6b2987c | MATLAB | 1,211 | 44 | function [Aout, avg_C, img] = h_improfile2(n)
%[Aout, avg_C] = h_improfile2(n)
%h_improfile2 mimic improfile but with an averaging function across a few lines
%n = parallel lines to average 1, 3, 5, 7... default 5
if ~exist('n','var')||isempty(n)
n = 5;
end
Aout = [];
avg_C = [];
handle = findobj(gca... |
b540b0960bf086c0c94e60bd1571dfadac5f53938645cf210de0b71105c4b78c | MATLAB | 1,211 | 43 | function filtsign = lan_butter(LAN, min_freq, max_freq, chan, poles)
% lan_butter realiza de forma intuitiva un filtro Butterworth sobre todos
% los canales especificados 'chan' en un entorno LAN, para uno o multiples
% trials, con un rollover constante de 0.5
%
% Los parametros min_xfreq y max_freq pueden ser [] o un ... |
d3ac5a814c93c06467c4fa67a7abac6c7835c3e492a0e9f4905696d16d8092ff | MATLAB | 1,211 | 47 | function vcout=mk_vcharm(vc,center,coeffs);
% returns something
[nbasis,ndum]=size(coeffs);
order=sqrt(nbasis)-1;
vc=vc(:,1:3);
[nsurf,ndum]=size(vc);
vc=vc-repmat(center,nsurf,1);
block=5000;
nblock=ceil(nsurf/block);
vcoutall=[];
k=1;
for i=1:nblock
kb=min(k+block-1,nsurf);
blockloc=kb-k+1;
vcloc=vc(... |
de0d209807c12c6358418a8e466f788e9e242e42809e46ae6def00bac8b22146 | MATLAB | 1,211 | 48 | function [err] = CNN(fz,data_x, target_y)
% Input paramters (arguments) are:
% data_x: 4-D double containing the input data in the following form
% [128 1 1 numberOfReadings]
% target_y: 1-D Categorial containing the signal labels
% [numberOfReadings 1]
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
7dd49beb1f3f7289823f8a11a0f0e702b5fee229b1fb1efc2fa65e5ac582f5a3 | MATLAB | 1,212 | 41 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function mrmr_esg_isopotentialplot(subjects, chanvalues, colorbar_axes, chan_labels)
%% isopotential maps
%% get grid parameters
[labels, elec_pos, grid_size, grid_pos] = get_gridparameters(subjects);
%% sort channels + reduce to actual channel size
allchan_idx = find(... |
e7b6666f8aeca05ff91269e8dd0bcac01ed5e379d49661b4c9bda735958cb6ae | MATLAB | 1,212 | 34 | function t = fractile(x, f)
%FRACTILE finds fractiles of a distribution
% T = FRACTILE(X, F) finds a value T for which a fraction F of the
% elements of X are less than T. A fractile is like a centile, except
% that the argument is a fraction rather then a percentage.
%
% Linear interpolation is used bet... |
51d1736a11c39c8738dbfca112f25cfc2340542587ff3b3aa9a3f964c6c9dc66 | MATLAB | 1,213 | 35 | function [Gx,Gy] = gradient2( I )
% Compute numerical gradients along x and y directions.
%
% For 2D arrays identical to Matlab's gradient() with a spacing value of
% h=1 but ~10-20x faster (due to mexed implementation). Like gradient(),
% computes centered derivatives in interior of image and uncentered
% derivatives ... |
5726feb61965c68699d648caa612885be2d885ad55795dfc0223159bf7949e69 | MATLAB | 1,213 | 39 | function V = mttkrp(X,U,n)
%MTTKRP Matricized tensor times Khatri-Rao product for ktensor.
%
% V = MTTKRP(X,U,n) efficiently calculates the matrix product of the
% n-mode matricization of X with the Khatri-Rao product of all
% entries in U, a cell array of matrices, except the nth. How to
% most efficiently do... |
71ca59c7e2ee805ae7870e093178fc40424f584cc36dbc07fada324361040202 | MATLAB | 1,213 | 41 | clear
clc
%{
delete(gcp('nocreate'))
myCluster.NumWorkers = 8;
parpool('local',8)
%}
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
MaxFunctionEvaluations_Data = 10^300;
MaxIterations_Data = 60;
OptimalityToler... |
bd301858dd83e13f63302f121b27a270fc397db9217c0f5689f54bd107a71a4f | MATLAB | 1,213 | 36 | function [impreds, stadog] = predictDogModel(mdlparams, imEnsemble, nrx, nry)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
[ypix, xpix, Nims] = size(imEnsemble);
swt = mdlparams.surrwt / mdlparams.surrsc^2;
rfparams = [mdlparams.gaussparams 1 mdlparams.surrsc swt];
% rfparams(1:... |
09f378d1a006088c3f5d6b760c31d2475fe9bed1618229fe6990e40e8384eade | MATLAB | 1,214 | 54 | function xc = CrossCorr2(refSpk, testSpk, varargin)
nSamp = 10000;
binSpec = [];
binEdges = -100.5:100.5;
for i = 1:2:length(varargin)
switch varargin{i}
case 'nSamp'
nSampTarget = varargin{i+1};
case 'binEdges'
binEdges = varargin{i+1};
case 'binSpec'
b... |
3c085d8af6c7cd4728126dc495eb6335617a536093bc78582efc07c5b2acc868 | MATLAB | 1,214 | 39 | clear
clc
%{
delete(gcp('nocreate'))
myCluster.NumWorkers = 8;
parpool('local',8)
%}
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
MaxFunctionEvaluations_Data = 10^300;
MaxIterations_Data = 60;
OptimalityToler... |
72d3ae9afbaeabdca9a46333e63efdd93186e6876cb17811b42c3f5e80182bef | MATLAB | 1,214 | 66 | function [H,Hnorm,inv_Hnorm] = compute_collineation (a00, a10, a11, a01);
% new formalism using homographies
a00 = a00 / a00(3);
a10 = a10 / a10(3);
a11 = a11 / a11(3);
a01 = a01 / a01(3);
% Prenormalization of point coordinates (very important):
% (Affine normalization)
ax = [a00(1);a10(1);a11(1);a01(1)];
ay = [a... |
c0d5dcdecdd3d067acd49e2e33e27127f33011cd4fd92dd9d76f37cb76b1c426 | MATLAB | 1,214 | 29 | function [segments, Fs] = CARL_get_voice_segments(filename, chunk_s, distance_s)
% filename: filename of the .wav file (incl. extension)
% chunk_s: duration of chunk in seconds
% distance_s: min. distance between chunks in seconds
segments = [];
tmp.info = audioinfo([filename]);
... |
ddf8e8b78adcb2e5887d43526aecb3227cb5d5f4cf9a4d08de8a219636ac3270 | MATLAB | 1,214 | 26 | function result = trimTrackersAfterLoad(trackers, isFilePreTrackerHistory, currTrackerThatWas)
% Trim the trackers, deleting all untrained models, except for the
% current tracker. We do this after loading b/c there are legacy projects
% which include a bunch of untrained trackers. For newer project files, ther... |
ffc1cafdb9c85dbb276f52a2e172430cf3f0c2ac98e2307e264267dbf8ff1c41 | MATLAB | 1,214 | 28 | classdef (Sealed) AdjMatrixGridGraph < adjmatrix.AdjMatrixFromNetX
methods
function this = AdjMatrixGridGraph(params, loadOnInit, delAfterLoad)
% creates a complete graph (mean-field network)
%
% params {AdjMatrixParams}: params of the adjacency matrix
% loadO... |
3e918fb6585f4ce394c08f3b9eeb7b4959c85acfba6aa46a33ac24cd4ab2fcae | MATLAB | 1,215 | 34 | function [kdr,nap,km,cal,kca] = calc_steady_states(v,ca)
global gKCa %% ...
global nV12 nk ntau ntauV12 ntauk %% Potassium rectifier (Kdr)
global nMV12 nMk nMtau nMtauV12 nMtauk %% Potassium M (M)
global mpV12 mpk hpV12 hpk hptau h... |
5c5e70a67d268be82ee4643ac10591fbbc2a1bc26309b2d674ebc87ab0735c0e | MATLAB | 1,215 | 26 | % Plot Figure 4b
load(fullfile(saveLoc, 'decoderPerf_crossTP'))
load(fullfile(par_sess{1}.datPath, 'Plotting', 'darkRedBlue')); darkRedBlueUpper = darkRedBlue(size(darkRedBlue,1)/2+1:end, :);
% useTPTs = find(winStart >= 0.1 & winStart <= 0.5); useTPTs = useTPTs(1) : 2 : useTPTs(end);
xyLims = [0.1 0.501]; useTP... |
926ed61d2173c5dcd659a5cb18fdac4b9f6dfcd3ab76d7cbd3e60731f3ceecfd | MATLAB | 1,215 | 36 | function downloadAllSupport(destnRoot, quiet)
%% Download pmtkSupport packages from pmtkSupport.googlecode.com
% This file is from pmtk3.googlecode.com
SetDefaultValue(1, 'destnRoot', fullfile(pmtk3Root(), 'pmtksupportCopy'));
SetDefaultValue(2, 'quiet', false);
fprintf('downloading packages to pmtk3/pmtksupportCop... |
edac482116374e01130d7adb6750d653617a546972d34f9bb85388aafac0e1b7 | MATLAB | 1,215 | 43 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Optimization loop of the MU filter to minimize the coefficient of
% varation of the inter spike intervals
% Input:
% w = initial weigths
% X = whitened signal
% CoV = coefficient of varation of the inter spike intervals
% fsamp = sa... |
214da844edc231a584cb405be24c84a9c8bab83ff0e525364e3b97c562445e1c | MATLAB | 1,216 | 33 | %% Figure 4.1
% Generate the simplest adjacency matrix
figure;
g = graph(res.adjacencyMat);
plot(g, 'Layout', 'force', 'Usegravity', true, 'WeightEffect', 'inverse');
%% Figure 2
% We can do better by coloring the nodes based on the average value of the node members
% averaging over nodeMembers cell array
avgNode = c... |
9c604901bd233c8db93bb624b6bbe886b2714a5f976ef1411c6472e77b8ae2d4 | MATLAB | 1,216 | 51 | function A=mkfilt_eloreta(L);
[nchan ng ndum]=size(L);
LL=zeros(nchan,ndum,ng);
for i=1:ndum;
LL(:,i,:)=L(:,:,i);
end
LL=reshape(LL,nchan,ndum*ng);
u0=eye(nchan);
W=reshape(repmat(eye(ndum),1,ng),ndum,ndum,ng);
Winv=zeros(ndum,ndum,ng);
winvkt=zeros(ng*ndum,nchan);
kont=0;
kk=0;
while kont==0;
kk=kk+1;
fo... |
aabb09030bf8ffc23238b6373680750a259cc74fde83aabaecee7027bea692ce | MATLAB | 1,216 | 41 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% callback when cluster is called
% this calls other plugins that handle
% the actual clustering
... |
029c8871d39da2666d6201e3f615a2faa1ca4a2fae8a6b3a4dc4bbb482426e14 | MATLAB | 1,217 | 41 |
function dF = CBIG_MFMem_rfMRI_rfMRI_BW_ode1(y,F,Nnodes)
%-----------------------------------------------------------------------------
% dF = CBIG_MFMem_rfMRI_rfMRI_BW_ode1(y,F,Nnodes)
%
% Function for hemodynamic model diffiential equation 1st order
%
% Input:
% - y: current neural activiy
% - F: ... |
59b2128d54e19e56d679c2892bee2d04fc9bf41deaf96be13af9ffaca4abaa22 | MATLAB | 1,217 | 51 | % Plot stimulus-locked mean traces during viewing task for all coherences
% - considering nans in each trial
% meanTracesSLview_bigSbigT
filter = ones(size(sigSLv.sig_coh))==1;
conditions = sigSLv.sig_coh;
allCond = nanunique(sigSL.sig_coh);
colores = NS_colorsBY(length(allCond));
clear Son
dt = sigSL.t(2)... |
82c3358083d27f3b5c14bdc8444cd810d15d35306ad0115e13fecb1ec4e650ae | MATLAB | 1,217 | 46 | function Xtensor = tucker2multiarray(X)
% Converts a 3d Tucker form tensor to a multiarray.
%
% function Xtensor = tucker2multiarray(X)
%
% X has fields U1, U2, U3, and G.
%
% The matrices U1 (n1-by-r1), U2 (n2-by-r2) and U3 (n3-by-r3) are
% orthogonal matrices.
% G (r1-by-r2-by-r3) is a multidimensional array... |
88b2b323302ec0128e5239b3208ecfb29ba2c4730cceae70d0db2cebecf26195 | MATLAB | 1,217 | 48 | % MF_SPDIAG_SV_N Dispatch for MF_SPDIAG with DINV = 1 and F.SYMM = 'N'.
function D = mf_spdiag_sv_n(F,spinfo)
% initialize
N = F.N;
n = length(spinfo.i);
P = zeros(N,1); % for indexing
D = zeros(N,1); % for output
% loop over all leaf blocks from top to bottom
for i = n:-1:1
% find active indic... |
bf1da7dfcc21f3eb88f16ab2b8bc017564f8b72745a92c0c79ee483c2e12f617 | MATLAB | 1,217 | 48 | % MF_SPDIAG_MV_N Dispatch for MF_SPDIAG with DINV = 0 and F.SYMM = 'N'.
function D = mf_spdiag_mv_n(F,spinfo)
% initialize
N = F.N;
n = length(spinfo.i);
P = zeros(N,1); % for indexing
D = zeros(N,1); % for output
% loop over all leaf blocks from top to bottom
for i = n:-1:1
% find active indic... |
045db696d4945499c1e0e789ecc96d830209838b15fd213fe6f859c2e183c9a6 | MATLAB | 1,218 | 26 | function [centroid] = find_centroid(aal_node,sourcemodel)
% aal_node: array comprised of indices of sources in region
% example: aal_node=find(source_aal.tissue==1);
% sourcemodel: is the source model structure
if length(aal_node)==1 % only one source
centroid=aal_node;
else % find centroid by computing min... |
61c66c4b9b8f2b02d321eebf6381449644bd5083f68241bdd7944cf76b15ec37 | MATLAB | 1,218 | 40 | function vv = crf_smooth_3D(vin,outx,ksz,sigsc)
% smooth volume based on crf
% inputs: vin - volume (scalar)
% outx - volume x 9 (reference frame) usually cortical
% ksz - 1/2 size of kernel width (in voxels)
% sigsc - standard deviations
% output: vout - smoothed vin
%
% Ale... |
91dd844e237e5dcebd7d8055675f2f8ccc42c7db9677c1b97c24d3a284afa590 | MATLAB | 1,218 | 42 | function [S,bEff,Tmix] = DWSTE(G,tau,b,TE,TR,D,T1,T2)
%
% calculates DW-STE Signal
%
% input:
% G = strength of diffusion gradient (mT/m)
% tau = duration of diffusion gradient (ms)
% b = b-value (ms/um2)
% TE = Echo time (ms)
% TR = repetition time (ms)
% D = diffusion coefficient (um2/ms)
% T1 = longitudin... |
ea563454dea73e9944f36ff6674de4284c026f5609b0d2f5c347cac20b1d09b7 | MATLAB | 1,218 | 40 | function memberMat = construct_cover_from_graph(g, resolution, gain)
%% Create a cover.
% The number of landmarks is divided proportional to
% the size of each connected component.
n = size(g.Nodes, 1);
[cc,ccs] = conncomp(g);
binAlloc = ceil((ccs/n)*resolution); %grab extra landmarks if needed
memberMat = zeros(s... |
2eac1f0f6288e0765ed0cae5dd9d11cc4281db11aeea3431c99f0baf54d5f47e | MATLAB | 1,219 | 40 | % Returns the inverse coordinate transformation (Rigid is in head
% coordinates and transformed to non-head coordinates of Locations).
function NewLocations = CorrectRigid(Locations, Rigid)
switch ndims(Locations)
case 2 % Single trial dataset.
NeedReshape = true;
nS = size(Locations, 1);
nT = 1... |
9297d9b93c9229286ddbca89a3fbf28594bb8f20062a0c0ff9cd8d0fa39fcc0a | MATLAB | 1,219 | 50 | function write_vtk(fn, pnt, tri)
% WRITE_VTK writes a triangulation to a VTK (Visualisation ToolKit) format file.
% Supported are triangles, tetraheders and hexaheders.
%
% Use as
% write_vtk(filename, pnt, tri)
%
% See also READ_VTK, WRITE_PLY
% Copyright (C) 2002, Robert Oostenveld
%
% $Id$
fid = fopen_or_error(... |
47251fecfdeb3244a425894c60d4d7aae511ec855cf0df2fb9aa3d698e19e40c | MATLAB | 1,220 | 61 | A = load('/nrs/branson/mayank/janOut/151106_03_016_02_C001H001S.mat');
B = load('~/temp/delete_10.mat');
l1 = permute(A.locs(:,:,1,:),[1 4 2 3]);
l2 = permute(B.pTrk,[2 3 1]);
%
rfn = get_readframe_fcn(A.expname);
% %%
% figure; imshow(rfn(30));
% hold on;
% id = 4;
% scatter(l1(30,1,id),l1(30,2,id),'.');
%
gg = sqr... |
4950991ba7c814975bf7b889aeec9355a3262d03b1060726199de8a4232f3d51 | MATLAB | 1,220 | 45 | function [] = transformQuiver(processedImagePair)
%% Figure out axis convention
% x = [10:10:50];
% y = [10:10:30];
% [x,y] = meshgrid(x,y);
% figure;
% quiver(x,y,2*ones(size(x)),ones(size(x)),0)
% set(gca,'YDir','reverse');
%% real stuff
%decimate transform field
spacing = 10;
mytform = processedImagePair.ImgMovin... |
ef417dad98ec7d66bb4066faa28cda878082d46323e695ae7060308eb581cd9b | MATLAB | 1,220 | 49 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef SuhAbstractClass< handle
methods(Static)
function AssertIsA(this, className)
assert(isa(this, className),...
... |
39325c78523a857b6befef5af3a5ac0c250b021ac4fb535fe1a7bbd5d8f5b408 | MATLAB | 1,221 | 40 | function [ u, dim, options ] = setInput(options,dim,varargin )
% allow to specify labels to inputs (u)
% IN
% options: a structure
% varargin: should be organized as: my_n1_times_nTrial_maxtrix1, name1, my_nk_times_nTrial_maxtrixk, namek...
% OUT
% u : a concatenate (n1+...+nk) * nTrial matrix
% options... |
3e583827d4b4d7db1a9ff7ee9fe18abf9a5bea13958f141a45ff860afa31c6dd | MATLAB | 1,221 | 45 | function f = meg_checkTriggers(fileName, trigChans, verbose)
% function rd_checkTriggers(fileName, [trigChans], [verbose])
% INPUTS:
% fileName is the path to the sqd file
% trigChans (optional) is the trigger channels to plot. Default is 160:167.
% verbose (optional) [1 or 0] specify whether to print the trigger coun... |
6d12f0a19fa67a94371c0ec8f2b9a28c216a7aa87e857ab85b30c3c86a7a2cf7 | MATLAB | 1,221 | 50 | function [EVec, Eload, EVal, pca_info] = mypca_calc(vecs)
%
% PCA_CALC Principal Component Analysis
%
% [EVEC, ELOAD, EVAL] = PCA_CALC(X) takes a column-wise de-meaned
% data matrix X of size n-by-m and calculates the n
% Eigenvectors (EVEC of size n-by-n) of the data covariance
% matrix, the fac... |
701f45d59b453e328260f6d92038989b2102d7ec05c142095ffc5c3a34910190 | MATLAB | 1,221 | 55 | %% PCA digit visualization demo
% Based on code by Nando de Freitas.
%%
% This file is from pmtk3.googlecode.com
loadData('uspsAll'); % data(1:256, 1:1100, 1:10)
figure;
i = 1;
for c=1:10
for j=1:2
subplot(4,5,i)
imagesc(reshape(data(:,j,c),[16 16]));
axis off
colormap(gray)
i=i+1;
end
end
... |
a279ae40dabe2551d955ad20bcbf53774314fde20000674f73ac193f8ad40b97 | MATLAB | 1,221 | 28 | psthPara.binsize = 10; psthPara.binstep = 10; % ms
if contains(protStr, "Passive noise")
devStr = "durSeq";
end
tIndex = [trialAll.(devStr)] == devType(dIndex);
trials = trialAll(tIndex);
trialsSPK = trialsSpike(tIndex);
% spike
spkNoise(dIndex).devType = devType(dIndex);
spkNoise(dIndex).trials = find... |
0b24efcb8b2f4e7968ad064a51ca7e12fb23eadff53f6548807a878f0ebeb5a2 | MATLAB | 1,222 | 47 | % This demonstrates the smoothing properties of the Kalman lagged filter.
% Hidden states follow a triangular wave, whose observation is perturbed
% with white noise. Critically, we render the inversion scheme blind during
% half a period of the oscillation. We then invert the model (under AR
% priors on hidden states)... |
2c0b0449a253e992c87ff99682bf86220c89f726b4c57a2aeb41114e06f3fd1a | MATLAB | 1,222 | 52 | function [pnt, tri] = mesh_cube()
% MESH_CUBE creates a triangulated cube
%
% Use as
% [pos, tri] = mesh_cube()
%
% See also MESH_TETRAHEDRON, MESH_OCTAHEDRON, MESH_ICOSAHEDRON, MESH_SPHERE, MESH_CONE
% Copyright (C) 2019, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% f... |
9bfa8ad7e2ae3abe9ecd12ab5cbe567dc6f6ff96071445460743a73ac38162c5 | MATLAB | 1,222 | 45 | function [slocgrp] = genLocsGroupedI(s,imov,varargin)
% s: scalar element of 'sagg', ie labels data structure for one movie.
% imov: movie index, only used for metadata
imgpat = myparse(varargin,...
'imgpat','im/%s.png' ...
);
% s = Labels.addsplitsifnec(s);
slocgrp = [];
frmsun = unique([s.f... |
b41bf29fa451c1bf4759e948d863e207a5557f6941e125db3fe4b34cb54cc780 | MATLAB | 1,222 | 39 | function riptimes = getRipTimes(animalprefix, loadDir, day, epoch, modelParam)
% riptimes = decode.getRipTimes(animalprefix, loadDir, day, epoch, modelParam);
%
%
%% Set up
minEventDur = modelParam.minEventDur;
sToMsConversion = 1000;
%% get ripple time
% load(sprintf('%s%srippletime0%d.mat',dir,animalprefix,day))... |
d4677aaec6f2f1e843614a5f40e0195b7c86c73bc89645ce2bfd104b6e9bf0cc | MATLAB | 1,223 | 34 | function signal = noise (frames, epochs, srate, outvar)
% function signal = noise (frames, epochs, srate, outvar)
%
% Function generates noise with the power spectrum of human EEG
% Inputs:
% frames - number of signal frames per each trial
% epochs - number of simulated trials
% srate - sampling rate of simulated s... |
fede6ab5e3baba7f9022ca4a4173d855f4d620550e6dc29a598173013efbaeba | MATLAB | 1,223 | 31 | function [rt] = isGraph(in)
%
%
%
%<PRE>
% This file is part of dspace-core.
%
% Copyright (C) 2020 University Zurich, Sepp Kollmorgen
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Affero General Public License as publ... |
6b39aefead75a12685628984dfae609f5c7ca1cef50750a87e667db9ee0f69e9 | MATLAB | 1,224 | 34 | function plot_TWO_place_fields(place_fields1,place_fields2,track_id)
place_fields{1}=place_fields1.track(track_id);
place_fields{2}=place_fields2.track(track_id);
%%% PLOT WITH IMAGESC
c=1;
figure
y_vector=[];
for i=1:2
for j=1:2
matrix=[];
normalized_matrix=[];
subplot(2,2,c)
for k=... |
2303c6db0ccdceca50baa61dc0a42d63ea1e1519f0b34179e6b993f66b1f600e | MATLAB | 1,225 | 50 | function [dupcats,idupcats] = finddups(x,varargin)
% Look for duplicates in rows of x
%
% x: [Nxncol] numerical or cellstr
%
% dupcats: [Ndupsetsx1] cell. dupcats{i} contains identified/matching
% rows of x for duplicate category i
% idupcats: [Nx1] indices into dupcats. idupcats(i) is:
% * nan if x(i,:) is not a ... |
42a58b298af0e7a8411402b17ac8e70bd53a7a3d2fa6c635fbc677965cbcd4e2 | MATLAB | 1,225 | 23 | % FILTERS
% See also
%
% Filters:
% filterBinomial1d - 1D binomial filter (approximation to Gaussian filter)
% filterDog2d - Difference of Gaussian (Dog) Filter.
% filterDoog - n-dim difference of offset Gaussian DooG filter (Gaussian derivative).
% filterGabor1d - Creates an even/odd pair of 1D G... |
2b28a614a2d2ee29f56692bf48d58bb49e1213421a2a789a5be0c46e08598d54 | MATLAB | 1,226 | 51 | % data is from
% http://archive.ics.uci.edu/ml/datasets/Congressional+Voting+Records
fid = fopen('house-votes-84.csv', 'r');
D = 17;
linenum = 1;
while 1
tline = fgetl(fid);
if ~ischar(tline), break, end
disp(tline)
s=regexp(tline, ',', 'split');
switch s{1}
case 'republican',
data.X(linenum, 1) = 1... |
666eca18cad910f92f7aa420adaef58f1027b8de70b6e8b867cbcc1502dbd195 | MATLAB | 1,227 | 56 | %% Demo of the pagerank algorithm, based on code by Cleve Moler
% See also pagerankDemoMoler, pagerankDemoGui, surfer, pagerankpow
%%
%% 6 node web example
% This file is from pmtk3.googlecode.com
i = [ 2 6 3 4 4 5 6 1 1];
j = [ 1 1 2 2 3 3 3 4 6];
n = 6;
G = sparse(i,j,1,n,n); % sparse n x n matrix with 1's in spec... |
66d58a4caefce87bbd6eaa1b99610596ecbc500fe1abf08a2d7f0d475cb080d7 | MATLAB | 1,227 | 49 | function image_rgb(M)
% Show a matrix of integers as a color image.
% This is like imagesc, except we know what the mapping is from integer to color.
% If entries of M contain integers in {1,2,3,4,5}, we map
% this to red/green/blue/aquamarine/black.
% So if we call image_rgb on 2 different matrices,
% we always know b... |
af934d78da167ce3efbb379ad60e575d0ebed49ee501e329f22241247c522356 | MATLAB | 1,227 | 39 | function ok = tt_subscheck(subs)
%TT_SUBSCHECK Checks for valid subscripts.
%
% TT_SUBSCHECK(S) throws an error if S is not a valid subscript
% array, which means that S is a matrix of real-valued, finite,
% positive, integer subscripts.
%
% X = TT_SUBSCHECK(S) returns true if S is a valid and false
% otherwise.
%... |
0f40e86621fb666d6a8ba12ec2ab6c4c7e95064891c58b17d8f725e32a242d24 | MATLAB | 1,228 | 35 | function stage_base_calling()
loadParameters;
%Save the loadParameters into the output director in case we need to do
%later debugging
copyfile('loadParameters.m',fullfile(params.basecallingResultsDir,...
sprintf('loadParameters.m.log-%s',date)))
[ret,messages] = check_files_in_base_calling... |
7137ef6a13eeeff0c31fa900aaa095204941d616b2d236f94a29a49e58f0269b | MATLAB | 1,228 | 45 | function [dat,nvox] = iimg_cluster_extent(dat,volInfo,k)
% Apply a cluster size threshold to a series of index image data vectors
% (each img is one column)
% given volInfo (must be created with iimg_read_img, with extended output)
%
% :Usage:
% ::
%
% [dat,nvox] = iimg_cluster_extent(dat,volInfo,k)
%
% :Inputs:
%
... |
6b880d1db8420e3a21f8cdf4e812a60162b4c439ed032d5b030ae6f3ceb29730 | MATLAB | 1,229 | 30 | function qh = quivercolor(ax,x,y,u,v,colorVar,colorMap,varargin)
if isempty(ax)
ax = gca;
end
if (nargin < 5) || isempty(colorVar)
colorVar = hypot(u(:),v(:)); % magnitude of vectors is the default color
end
varargin = func.get_args_set_default(varargin,'LineWidth',1.... |
a47a36f7577f4a27a3288160fa7d59607ab24db0ca4cf36b3aea95af9f2bc27a | MATLAB | 1,229 | 40 | function [Xc] = mixGaussImpute(model, X, varargin)
% Fill in NaN entries of X using posterior mode on each row
% Xc(i,j) = E[X(i,j) | D]
%PMTKauthor Hannes Bretschneider
% This file is from pmtk3.googlecode.com
if ~isfield(model, 'cpd') || isempty(model.cpd.mu)
if ~isfield(model, 'K') || isempty(model.K)
... |
25a5d8c2d1c8bbc244ea31f24418a7c0caeebe0bd080ce69912923f7a033fc92 | MATLAB | 1,230 | 50 | %% fnc_FAST_getFreqs: Selection of a frequency set. Done recursively as described in:
%% ‘A computational implementation of FAST’ [McRae et al.]
%
% Usage:
% W = fnc_FAST_getFreqs(k)
%
% Inputs:
% k scalar number of inputs
%
% Output:
% W frequencies of parameters
%
% -------------... |
770e65cbbec899bf49d167ca9d66b821296ce84d24b67f9211fccbef944bd5ba | MATLAB | 1,230 | 46 | function tests = mex_meanfilesTest
tests = functiontests(localfunctions);
end
function setup(testCase)
testCase.TestData.tempDir = '/mp/nvme0/tmp/testworks';
if ~exist(testCase.TestData.tempDir)
mkdir(testCase.TestData.tempDir)
end
n = 4000;
data = {};
for i = 1:4
data{i}=[... |
a3e742a3b86939314d74b8a13354e346c4a303ba921d957718bf87baaadfa4fb | MATLAB | 1,230 | 52 | classdef CalRigDummy < CalRig
% Generic "No calibration" Calrig
properties
nviews
viewNames % [nviews]. cellstr viewnames
viewSizes % [nviews x 2]. viewSizes(iView,:) gives [nc nr] or [width height]
end
methods
function obj = CalRigDummy(numVw,vwNames,vwSizes)
if isstruct(numVw), % handl... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.