sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
84961570847f8fa97b3c7b0e6b2fffab3de6c35bb343b04f07b55fb69478d20d | MATLAB | 1,374 | 34 | function process_mat_data(ALLEEG,main_folder_path,PreprocessedDataPath)
%% ²»Óù˼Éparams£¬×ªepoch ºÍlabel mat¸ñʽ
% clear all; close all;
% ´´½¨Ò»¸ö¿ÕµÄ ALLEEG ½á¹¹
% ALLEEG = [];
% % µÝ¹é¼ÓÔØÎļþ¼ÐÄÚËùÓÐ .set Îļþ
% ALLEEG = load_all_sets(main_folder_path, ALLEEG);
% ÏÖÔÚ ALLEEG ½á¹¹Öаüº¬ÁËËùÓмÓÔØµÄ .set ÎļþµÄ E... |
9524a9d973a1ec36c961bc997938ea7086c0de0988261a92769d0e8da05eed9a | MATLAB | 1,374 | 78 | function [modelfit_path,temp_path,maps_path,IDIF_path, IDIFTemp_path, IDIFVessels_path, IDIFQC_path, MOCO_path, SEG_path, COREG_path]=out_path_preparation(destination_dir)
%% ModelFit
modelfit_path=fullfile(destination_dir,'ModelFit');
if(not(isfolder(modelfit_path)))
mkdir(modelfit_path);
end
% subdirectories
... |
fcddc213a93669a2662b797edce335126118414f7a638bb196f9dcf19a6f3b73 | MATLAB | 1,374 | 53 | function [IDX,C] = meanShiftPost( X, IDX, C, minCl, forceOutl )
% Some post processing routines for meanShift not currently being used.
%
% USAGE
% [IDX,C] = meanShiftPost( X, IDX, C, minCl, forceOutl )
%
% INPUTS
% see meanShift
%
% OUTPUTS
% see meanShift
%
% EXAMPLE
%
% See also MEANSHIFT, KMEANS2
%
% Piotr's Com... |
db8fe6fd99444989329ec5be5e4bfefcbba57e44a181f946ebe9cdb7202cbe1f | MATLAB | 1,375 | 48 | function nstr = int2str2( n, nDigits )
% Convert integer to string of given length; improved version of int2str.
%
% Pads string with zeros on the left. For integers similar to
% sprintf( '%03i', n ); %for nDigits=3
% If input n is an array, output is a cell array of strings of the same
% dimension as n. Works also ... |
b62804fa1336565dfd85ea649657844e5f60273790b58e7d6566038ef6e4fade | MATLAB | 1,376 | 62 | function [s,param,value] = read_ann_line(fid)
s = fgetl(fid);
param = [];
value = [];
if s == -1
return;
end
if strcmp(s,'end header'),
return;
end
% if isspecial,
% sz = str2num(value);
% value = fread(fid,sz,'uint8');
% else
% tmp = str2num(value);
% if ~isempty(tmp),
% value = tmp;
% end;
% end;... |
10e5ebca45c5059486a8000c6c526f63acc81a4490c5c2974aa017e8cfdc9d1d | MATLAB | 1,377 | 34 | % FT_PREAMBLE_TRACKCONFIG is a helper script that calls ft_checkconfig to switch the
% (optional) configuration tracking on. This should be used together with
% FT_POSTAMBLE_TRACKCONFIG.
%
% Use as
% ft_preamble trackconfig
% ... regular code goes here ...
% ft_postamble trackconfig
%
% See also FT_PREAMBLE, FT_P... |
71a3f89c335c66793c0d9540b4163348befe83b7547e5d21d13e968e4ea219e5 | MATLAB | 1,377 | 40 | function [fpred, insignal] = predictSubGridSubSurrModel(mdlparams, stiminfo, stimorder)
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
kt = mdlparams.ktbasis * mdlparams.ktwts;
ktsurr = mdlparams.ktbasis * mdlparams.subsurrwt;
Nt = numel(kt);
Nstim = size(stimorder, 2);
%Nsub... |
bf7e7c13d0cc8dabeec4009fec458d2714081e6b11cb3249ab010e799c8f501e | MATLAB | 1,378 | 45 | function B = betheFreeEnergy(G, nodePots, edgePots, nodeBel, edgeBel)
% Approximate the log likelihood for a pairwise MRF
% If the model is a tree, this is exact
% F = -theta^T tau - sum_{st} H(s,t) + sum_s (d(s)-1) H(s)
% where exp(-theta)=[nodePot edgePot]
% tau = [nodeBel edgeBel]
% H(s,t) = entropy edgeBel(:,:,e)
%... |
2271ab7080ee369071a98c15a87a516993bb2094f45adcc05a8619d8e786a349 | MATLAB | 1,379 | 34 | clear all
%%
%Define Parameters
[opt] = ParameterOptions();
%%
%Define threshold array
PrecisionArray=10.^[-18:-3];
%%
%Full distributionan
for k=1:length(PrecisionArray)
opt.Precision=PrecisionArray(k);
%Generate Pathway Amplitude & Gradient Waveform basis set
%First Dictionary
[PathwaySignalFirstOrder... |
343965a1a83ede000f06098dba04ecdc5a8b25e3b0d0dab9c8cdb361e012e8d3 | MATLAB | 1,379 | 46 | function vec = tangent2vec(M, x, basis, u)
% Expands a tangent vector into an orthogonal basis in the Manopt framework
%
% vec = tangent2vec(M, x, basis, u)
%
% The inverse operation is lincomb (see below).
%
% M is a Manopt manifold structure obtained from a factory.
% x is a point on the manifold M.
% basis ... |
6d1a4d14dbd99fb7ce2882f94fc20db6ced4e2c47e5d590fdeb42f27348e0518 | MATLAB | 1,379 | 58 | %% infocrit
%
% Calculate Akaike and Bayesian information criteria
%
% <matlab:open('infocrit.m') code>
%
%% Syntax
%
% [aic,bic] = infocrit(L,k,m)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% L maximum log-likelihood
% k number o... |
a48b3da212dcaa452a0f4ca9b9d3b77597501c1ce2cbb565f44e7224782321d7 | MATLAB | 1,379 | 45 | function spkPerBin = getBinnedEventSpikes(celldata, riptimes, eventindex, event, modelParam)
% spkPerBin = decode.getBinnedEventSpikes();
%
%
%% Set up
sToMsConversion = 1000;
tBinSz = modelParam.tBinSz;
hpnum = numel(unique((celldata(:,3))));
%%
cellsiAll = celldata(find(celldata(:,2)==eventindex(event)),3);
[cells... |
aee72e9bdfc2ef7663f89631b82c12d17274d1cb741b787a7e7d95dc5a910fec | MATLAB | 1,379 | 55 | %% Illustration of the likelihood surface created by a GMM
% The GMM has 10 isotropic components in 2d. The centers are marked with a
% '+' symbol. The three modes are marked with blue triangles. The green
% line is the convex hull of the centers.
%
%%
% This file is from pmtk3.googlecode.com
setSeed(39)
mu = [0.0... |
c4989908821ad38fcd8a400046bcf44ee482248e12c6e18908dacee4c9ee7a01 | MATLAB | 1,379 | 54 | % crabsort plugin
% plugin_type = 'load-file';
% data_extension = 'mat';
%
% _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
%
function S = MAT(se... |
d4697cd539148b72b6eef503be64f1978b322ee847268745a6ff28a2583d3435 | MATLAB | 1,379 | 56 | function [mu ul ll] = circ_mean(alpha, w, dim)
%
% mu = circ_mean(alpha, w)
% Computes the mean direction for circular data.
%
% Input:
% alpha sample of angles in radians
% [w weightings in case of binned angle data]
% [dim compute along this dimension, default is 1]
%
% If dim argument is specif... |
f1a33a85eaa770307034bd79189b4390531dea370adb6bba5e5ce51217d7230c | MATLAB | 1,379 | 52 | clear
close all
%% Input folder paths to data and MRI atlas
folder_path = ...
'/Users/jstrohl/Data/20240216 Sepsis Fear PET data/20240216 preprocessed nifti files/'
addpath('./atlas_functions')
addpath('./MRI_template')
addpath(folder_path)
%% Import
% Import MRI atlas
MRI_template = niftiread('2011-10-30_MRI... |
9d09fae2a05a5f2937a2ee84af7d841b6954b215c7d74d0cfd997ea755e243b1 | MATLAB | 1,380 | 47 | % - simulate a network of rate-based units
dt = 1; % Time step
tau = 10; % Time constant
T_end = 150; % Total simulation time
T = 0:dt:T_end; % Time vector
t_trans = 50; % Time for transient responses
dp = 1; % Perturbation magnitude
W = w; % Connectivity matrix
% - baseline vs per... |
893090a32be454de731ba904f1b8cba673ea70b891a823420f8ae17e6605bf59 | MATLAB | 1,381 | 60 | function out = getcfg(cfg,field,default,posible)
% <*LAN)<]
% v.0.0.4
% get cfg field and set default parameter
% Pablo Billeke
% 30.03.2012 fix bug in logical default
% 20.03.2012 fix bug
% 01.02.2012 add posible = {'op1','op2','op3',...}
% 25.11.2011
% 21.11.2011
if nargin <4
posible = [];
end
% get t... |
8ea9cd0329b9eefb68153bac222207e9c2049cffb3a7e50b47985d5283d3e396 | MATLAB | 1,381 | 67 | % deletes data (in .crab format) and associated .crabsort files
% if certain conditions are met
%
% exampple usage
%
% to purge all data where the LP channel is blank (has a single value)
%
% use this:
% crabsort.purgeData('LP',@(x) length(unique(x),1)
function purgeData(ChannelName, FcnHandle, Value)
allfiles = ... |
8f78e67b633b9d04e23dd97f82b9d4005ffd8a2de188ee574ff5dbe9bcb9d4ad | MATLAB | 1,381 | 57 | function [timePlot, freqPlot, dB_powPlot]= plot_dAM_spectrogram(sig, fs, tWindow, fracOVlap, nfft, cbar_range, useDefaultPlot, tStart)
if ~exist('tStart', 'var')
tStart= 0;
end
if ~exist('useDefaultPlot', 'var')
useDefaultPlot= 1;
end
if ~exist('cbar_range', 'var')
cbar_range= 40;
end
if ~exist('tWindow'... |
98c30ba1c925e254850aa45c989057baa747477a88764c4714c7d599d9268ef2 | MATLAB | 1,381 | 33 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This script generates the information excel file for each parcellation %
% set based on Seitzman (2020). %
% %
% Author: ana.tr... |
a61beda19967fa7ae72f6a6215e15f79b149b24152319506aa5259335faee4ee | MATLAB | 1,381 | 53 | %% Compare inference in a QMR like network (dgm)
% This file is from pmtk3.googlecode.com
setSeed(0);
nfindings = 100; % turn down if you run out of memory
ndiseases = 15;
nnodes = nfindings + ndiseases;
% first and last findings are hidden
% first half are positive, second half negative
posNdx = ndiseases+2:ndi... |
137a79e488d12c8c3ec10a74c8edb59d268ed904b78a444fd2cbfd51654c9ce0 | MATLAB | 1,382 | 42 | function [DT,bonds] = Triangle(params)
a = params.a;
n = params.n;
a1 = [a,0];
a2 = [a*cos(pi/3),a*sin(pi/3)];
p = [];
for i = 0:n-1
for j = 0:n-i
p = [p;-j*a1 - i*a2];
end
end
DT = delaunayTriangulation(p(:,1),p(:,2));
ind = [];
for i = 1:size(DT.Conn... |
0e32752557a80cd6a0a4611901fb8295cbb4201c53943cc6318ae244c456e382 | MATLAB | 1,383 | 56 | function j = CBIG_MFMem_rfMRI_diff_PC1(func,para,num)
%-----------------------------------------------------------------------------
% Function for Complex-step first order derivative approximation
%
% Im[f(x0+ih)]
% diff(f(x0) = --------------
% h
%
% Input:
% ... |
7a3ea18d81833a702b336efdeab81f9055356c747e4689f65540815a637b4b58 | MATLAB | 1,383 | 64 |
if ~glmnetInstalled
fprintf('cannot run %s without glmnet; skipping\n', mfilename());
return;
end
if 0
x=randn(100,20);
y=randn(100,1);
g2=randsample(2,100,true);
g4=randsample(4,100,true);
fit1=glmnet(x,y);
glmnetPrint(fit1);
glmnetCoef(fit1,0.01) % extract coefficients at a single value of lambda
glmnetPre... |
97505edb9a53bff941b8223edb728684662092eba68c79c88fbc6d5c51026863 | MATLAB | 1,383 | 73 | n=250;
eg1=exgausrnd(200,20,100,1,n);
nr=normrnd(300,20,1,n);
er=exprnd(300,1,n);
al=[eg1; nr ;er]';
mean(al)
fh=figure(1)
set(fh,'Units','inches','PaperUnits','inches');
orient landscape
set(fh,'position',[0.25 0.25 8 3]);
set(fh,'paperposition',[0.25 0.25 8 3]);
clf
subplot(1,3,1)
br=hist(eg1);
hist(eg1)
% fb=bar(br... |
02ea0deb42e4cfed01a94de2898d9399410cb64f7ac92617b7a8fcc0a4b4af28 | MATLAB | 1,384 | 51 | clear all;
close all;
%Load the network:
load('results_training.mat');
imDir1 = '/mnt/DATOS2/jvargas/ScipionUserData/projects/RNP_Vargas/Solo_Puntas/IMAGES_FILTERED/';
imds = imageDatastore(imDir1,"FileExtensions", [".mrc",".jpg",".tif",".png"],"ReadFcn",@(x)normy(x))
downsampling = 1;
%%
for idx = 1:length(imds.Fil... |
9e1967e818b75e851e13a5b6c08a456709bbba33ee3cb5d32a0cfa59dff57061 | MATLAB | 1,384 | 46 | function varargout = xml2mat(xmlfile, matfile)
%XML2MAT Convert an XML-file into a MAT-file
% XML2MAT(XMLFILE, MATFILE) converts an XML file or an XML string
% (as saved by MAT2XML) into a MAT-file MATFILE.
% S = XML2MAT(XMLFILE) returns the content of XMLFILE in variable S.
% S is a struct containing fields matchi... |
3cd867c3822df55ee92ad2accde024fdad33b7d12841508611613b2f2a412aeb | MATLAB | 1,385 | 45 | function tf = isfield2( S, fs, isinit )
% Similar to isfield but also test whether fields are initialized.
%
% A more comprehensive test of what fields are present [and optionally
% initialized] in a stuct S. fs is either a single field name or a cell
% array of field names. The presence of all fields in fs are teste... |
8d6334c92544ee3144d5fb48027ad9ccaf7ea3e1d93707102f9e9ab3a07b806a | MATLAB | 1,385 | 48 | function V = LinearVelocity(X,smooth)
%LinearVelocity - Compute instantaneous linear velocity.
%
% Compute linear velocity for a time-varying vector X.
%
% USAGE
%
% V = LinearVelocity(X,smooth)
%
% X the time-varying vector given as a list of triplets [t x y]
% smooth optional standard ... |
0f120e126e6ed1c423dc0258cc831547f834cafe19d63cd72d6f9f514ae46cd2 | MATLAB | 1,386 | 62 | function [P] = Conv_Lstm(fz,data_x, target_y,data_test)
% 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]
%%%%%%%%%%%%%%%%%%%%%%%%%%... |
241724dbf6f5ba3507d7b02c10f3e1b5ee0381516f6938138d174abff8af8071 | MATLAB | 1,386 | 47 | function y = CBIG_MFMem_rfMRI_simBOLD_downsampling(x,bin)
%--------------------------------------------------------------------------
% y = CBIG_MFMem_rfMRI_simBOLD_downsampling(x,bin)
%
% Function for reducing data samples of x {n x samples} columns , i.e. bin=8,
% put 8 points together, only count the first number ... |
6114958c546e312333dab64a5038e3a8d475ceb1c6863e620156da1e08397aa1 | MATLAB | 1,386 | 41 | % Calculate the forward matrix based on the cortical segmentation.
% Assume the headmodel was exported from Brainstorm as bs_headmodel
assert(size(bs_headmodel.Gain, 2) == length(rm)*3)
lfd_free = bs_headmodel.Gain;
lfd = lfd_free2fix(lfd_free,bs_headmodel.GridOrient);
fwd = fwd_to_rmfwd(lfd, rm);
save('../anatomy/... |
7ee482aaf78fcbf22535410641127451ee7a42eb6eb281727b738f2d3c663134 | MATLAB | 1,386 | 40 | function ret = make_links_in_normalization_dir()
ret = true;
loadParameters;
src_dir = relpath(params.normalizedImagesDir,params.colorCorrectionImagesDir);
old_dir = pwd;
cd(params.normalizedImagesDir);
for do_downsample = [true,false]
if do_downsample && ~params.DO_DOWNSAMPLE
... |
b78046b311333bd138b4895ce82ee7a1a72204f62662d35faf28e5ee29dc5f50 | MATLAB | 1,386 | 57 | %% Run NaiveBayes on the mnist data
%
%%
% This file is from pmtk3.googlecode.com
loadData('mnistAll')
% train_images: [28x28x60000 uint8]
% test_images: [28x28x10000 uint8]
% train_labels: [60000x1 uint8]
% test_labels: [10000x1 uint8]
seed = 0; rand('state', seed); randn('state', seed);
digit = 7;
ndx = find(mnist... |
30a30f6a3e5fae311179b25eec43378ab9c015326a783f71d34b5a1b52f27492 | MATLAB | 1,387 | 32 | function spread = generate_spread_values(inp)
switch inp
case 'wurth_led'
dang = [0 10 20 30 40 50 60 70 80 90]*pi/180; % angle for directional radiation - angles in radians
drad = [1.0 0.99 0.97 0.90 0.82 0.67 0.50 0.34 0.16 0]; % for the wurth LEDs
sz = [0.15 0.15];
case 'visha... |
31db6612d7c60ff370fc9d1317634db152e49043bd03199df226a8aee38fc7fb | MATLAB | 1,387 | 43 | function a = subsref(t,s)
%SUBSREF Subscripted reference for a ttensor.
%
% Examples
% core = tensor(rand(2,2,2));
% X = TTENSOR(core, rand{4,2), rand(5,2),rand(3,2));
% X.core %<-- returns core array
% X.U %<-- returns a cell array of three matrices
% X.U{1} %<-- returns the matrix corresponding to the fir... |
5337459c02c9e9b3efe65f5f7066519274d8d3db4b8fad177d26a32b453eebc7 | MATLAB | 1,387 | 50 | %% Visualize word-document binary matrix
%
%%
% This file is from pmtk3.googlecode.com
loadData('20news_w100');
% documents, wordlist, newsgroups, groupnames
X = documents'; % 16,642 documents by 100 words (sparse logical matrix)
y = uint8(newsgroups); % class label, 1..4
classlabels = groupnames;
%% Visualize ra... |
5b1087a51ba2615ba018ec68de84c1b8a06084b61313fe19df93ee75c40b949c | MATLAB | 1,387 | 50 | function y = centroid(M, x)
% Attempts the computation of a centroid of a set of points on a manifold.
%
% function y = centroid(M, x)
%
% M is a structure representing a manifold.
% x is a cell of points on that manifold.
% This file is part of Manopt: www.manopt.org.
% Original author: Nicolas Boumal, Dec.... |
80831e00a6554c8dce86293b6a38806d59036b433951047286534d5d204fa11e | MATLAB | 1,387 | 33 | areatxt{1} = 'lip'; areatxt{2} = 'fef';
timevector = -0.15:0.001:0.05;
rgb = [0.1 0.4 0.5; 0.7, 0.4, 0.7];
labels = [{'Singleton distr in RF'}; {'Non-singleton distr in RF'}];
clear h
for iArea = 1: 2
figtitle = upper(areatxt{iArea});
xlimToPlot = [-0.15 .05];
figure('Name', figtitle , 'NumberTi... |
a239ac3aa79f207d1390649d780e9782904c48f191dfaf588a2e4dccf287b478 | MATLAB | 1,387 | 52 | function [ENLwFC] = calc_ENLwFC(data)
% This function can be used to calculate an explicitly nonlinear functional
% connectivity matrix for fMRI time series data. data: time*feature
% Cf. Kinsey et al. Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to diffe... |
b3280c036d47a9abd09562464a6f90fff7cd738b095ac49215da36ebc49b25c5 | MATLAB | 1,387 | 46 | % this method adds a data frame to the NNdata
function self = addDataFrame(self,raw_data,file_idx,spiketimes,label_idx)
% tic
assert(iscategorical(label_idx),'label_idx must be a categorical')
assert(isscalar(spiketimes),'spiketimes must be a scalar')
assert(isscalar(file_idx),'file_idx must be a scalar')
assert(is... |
321ea11f694edd5943b9b60be15c32f181b1e09b54cfbec879d6af69d17585a4 | MATLAB | 1,388 | 44 | function insertCopyright(noticeText, file, verbose)
%% Insert a copyright notice into the specified file
% noticeText is a single string, or cell array of strings, one cell per
% line and is written as a comment to the specified file - the %
% prefixes are automatically added. It is inserted immediately after the
% fir... |
a0c5d579db85d777563101f6635936a532f0f2309e3bfc8b08aa60f84c39fa38 | MATLAB | 1,388 | 43 | function [SNReff,bEff] = DWSSFP_SNREfficiency(x,optSample,optScanner,b)
%%
% calculates DW-SSFP SNR Efficiency
%
% input:
% x = array with diffusion gradient (mT/m), duration of diffusion gradient (ms), difference between TR & gradient duration (incorporating deadtime) and the flip angle
% optSample = T1 (ms), T2 ... |
ae89e18e07d5817fadf716265b6da8aae189b0602664601d5fb8761ea76caf4f | MATLAB | 1,388 | 53 | Q = load('/groups/branson/bransonlab/mayank/PoseTF/janLegTracking/160819_Dhyey_2_al_retrain20160911_v7_cleaned20161101.lbl','-mat');
%%
nmovies = numel(Q.labeledpos);
newm = cell(nmovies,1);
numLabels = [];
flyId = {};
missing = false(1,nmovies);
for ndx = 1:numel(Q.movieFilesAll)
curmov = Q.movieFilesAll{ndx};
... |
fce81222c9840c6ef0674bfb4eeb12a258287bfe0eaf77b84edd5dfeffafe4f1 | MATLAB | 1,388 | 37 | % ReorderSources.m
% Sarah West
% 4/4/22
function [parameters] = ReorderSources(parameters)
% Tell user what you're doing.
MessageToUser('Reordering', parameters);
% Make a holding matrix
parameters.sources_reordered = NaN(parameters.yDim, parameters.xDim, parameters.num_new_sources);
% For each... |
f413bf2510067e8671d9a6002b859f79d8d6b6e2b4ac508e28dfbf6b6da91e58 | MATLAB | 1,389 | 39 | function [HC,EC] = RFT_expectedTopo(u,L,fwhm,c,type,dof)
% derives E[EC] and E[HC] for a Gaussian RF defined on a regular lattice
% [out] = RFT_expectedTopo(u,L,fwhm,c,verbose)
% IN:
% - u: set-inducing threshold
% - L: length of the lattice
% - fwhm: smoothness of the random field
% - c: number of unbroken fie... |
396e6674802a9d8d6fafb548f5586d0e903ad05e6a8b945ea85710ac0cfec91f | MATLAB | 1,390 | 43 | function y=anastep(N,ti);
%ANASTEP Analytic projection of unit step signal.
% Y=ANASTEP(N,TI) generates the analytic projection of a
% unit step signal.
%
% N : number of points.
% TI : starting position of the unit step.
%
% Examples :
% signal=anastep(256,128);plot(real(signal));
% signal=-2.5*anastep(512,301);p... |
8396e9717d18fac7d2497866171dbfa2fb945c93024cda4a735adfebd75726f6 | MATLAB | 1,390 | 57 | pos = NP2*(ip1-1)+ip2;
fs = 8;
Xtxt = t1; Ytxt = -80;
Xtxt1 = t1; Ytxt1 = -85;
figure(1),subplot(NP1,NP2,pos),plot(time,x(:,1),'k','LineWidth',1.);
hold on;
set(gca,'TickDir','out');
set(gca,'TickLength',[0.02 1]);
set(gca,'YTick',[-60 -40 -20 0 ],'FontSize',fs);
if ip2 == 1
set(gca,'YTickLabel',[-60 -40 -20 0 ]... |
188677c4e7f33cd1c72a5a701411adb7f800f6d2d9f1d8b91336146dda1d92b4 | MATLAB | 1,391 | 57 | function ns = count_squares(I,x1,y1,x2,y2,win);
[ny,nx] = size(I);
if ((x1-win <= 0) || (x1+win >= nx) || (y1-win <= 0) || (y1+win >= ny) || ...
(x2-win <= 0) || (x2+win >= nx) || (y2-win <= 0) || (y2+win >= ny))
ns = -1;
return;
end;
if ((x1 - x2)^2+(y1-y2)^2) < win,
ns = -1;
return;
end;
... |
707e5eac87d55826508b576406b0f8eae9c83c6fb29e9e9438e8284489b6b8fb | MATLAB | 1,391 | 49 | shiftX1 = 0.19; shiftX2 = 0.02;
shiftY=0.195;
posX0 = 0.02;
switch iexp
case {1,2}
model_name = ' intact';
par_min = 0.1; par_max = 1;
Npar1 = 5; Npar2 = 10;
st_min = 0; st_max = time_max;
title_name = 'Intact';
posX = posX0;
Xmin = 0.5; Xmax = 1;
... |
7d1dbd22c9b3343d045eef9a8dabce7ecc13e216b209e73533e37da93433271d | MATLAB | 1,391 | 43 | function badlyClippingChannels = meg_findClips(data)
clippingChannelsThreshold = 4;
fractionClippingThreshold = 0.1;
numberExtraZeros = 0;
[timeOfData,numChannels] = size(data);
diffOfChannels = diff(data);
clips = diffOfChannels==0;
newClips = zeros(size(clips,1)+2,size(clips,2));
newClips( 2:end-1, :) = clips;
di... |
8fd7d7fc28ca0e8cdeb60bec09e9deab06a5381cb2857230b451cc302eedb263 | MATLAB | 1,391 | 63 | load clab_example;
sa=prepare_sourceanalysis(clab_example);
% plot potential
field=randn(118,1);
figure;showfield_general(field,sa.locs_2D);
% plot coherence
coh=randn(118,118);
figure; plot_coherence(coh,sa.locs_2D);
% plot cortex
figure;show_vc_tri(sa.cortex);
figure;show_vc_tri(sa.vc{3});
% plot 4 random ... |
a93b969d0e61ea9a2c45e18b34d175a3aff8a6c72d144f4115456db9b11f5cee | MATLAB | 1,391 | 60 | function [W, Z, evals, Xrecon, mu, iter] = pcaFitEm(X, k, varargin)
%% Principal component analysis using EM
%
%% Inputs
% X - n*d - rows are examples, columns are features
%
% If k is not specified, we use the maximum possible value (rank(X))
%
% * See emAlgo for additional EM related inputs
%% Outputs
% W -... |
1bc1b0d1744959dd694dc736475046a4326d19d6041d5d346e193275d1107bb6 | MATLAB | 1,392 | 55 | function s = fromarray(lpos,varargin)
% s = fromarray(lpos,'lposTS',lposTS,'lpostag',lpostag)
%
% lpos: [npt x 2 x nfrm x ntrx]
%
% if lposTS not provided, ts will be 'nan' (default upon Labels.new),
% and similarly for lpostag
[lposTS,lpostag,frms,tgts] = myparse(varargin,...
'lposTS',[],...
... |
35661d31f77a3cbf265ac90aede0f9d62679e8122462308ab3cdab213ee10cd5 | MATLAB | 1,392 | 41 | function [shape] = read_ctf_shape(filename)
% READ_CTF_SHAPE reads headshape points and header information
% from a CTF *.shape teh accompanying *.shape_info file.
%
% Use as
% [shape] = read_ctf_shape(filename)
% where filename should have the .shape extension
% Copyright (C) 2003, Robert Oostenveld
%
% This file... |
4234547273560861fefe6c477cab1a2c6c45e8444b960aaaf4d9dd8fdd83ca71 | MATLAB | 1,392 | 43 | function disprog(i,N,steps);
%DISPROG Display progression of a loop.
% DISPROG(i,N,steps) displays the progression of a loop.
%
% I : loop variable
% N : final value of i
% STEPS : number of displayed steps.
%
% Example:
% N=16; for i=1:N, disprog(i,N,5); end;
% F. Auger, August, December 1995.
% from a... |
36f7752b97dfd9945299e2980ae88d75d1373262b1d3398cc4683fa580a5a55a | MATLAB | 1,393 | 31 | function [mu,sigma] = FitMatrixWeights(A, nBins, showFit)
% generates new weights based on the weight distribution of adjacency matrix A
% considering that A has Gaussian distributed weights
%
% 1) fits a Gaussian function to the distribution of weights P(A_ij) to estimate mean and std
% 2) generates numel(A~=0) Gaussi... |
b9ce1eb868753e55e864ae7bcbfea519f8d18730a54c4bedf167729fa09ac760 | MATLAB | 1,393 | 52 | % HIFDE_SPDIAG_SV_N Dispatch for HIFDE_SPDIAG with DINV = 1 and F.SYMM = 'N'.
function D = hifde_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 act... |
c61a4e5608347f941988bf0fc0862fd9d6e083ba7831b73e97ac4f576db9a0e0 | MATLAB | 1,393 | 52 | % HIFDE_SPDIAG_MV_N Dispatch for HIFDE_SPDIAG with DINV = 0 and F.SYMM = 'N'.
function D = hifde_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 act... |
77d7901d4550926d134159c8994e2487a7e2191620e63260f37e000f8d83e7d3 | MATLAB | 1,394 | 52 | % HIFDE_SPDIAG_SV_S Dispatch for HIFDE_SPDIAG with DINV = 1 and F.SYMM = 'S'.
function D = hifde_spdiag_sv_s(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 act... |
8774752c02ba29d1665b6e70f5269d79d0de75b5c2e8bf496340dca8d5ac5b80 | MATLAB | 1,394 | 52 | % HIFDE_SPDIAG_MV_S Dispatch for HIFDE_SPDIAG with DINV = 0 and F.SYMM = 'S'.
function D = hifde_spdiag_mv_s(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 act... |
a57434dfb966bcd514615f8a0fb792c61e28c87fcb871313ae569568f5ca270e | MATLAB | 1,394 | 57 | %% Plot the pareto distribution
%
%%
% This file is from pmtk3.googlecode.com
figure; hold on;
%ks = [3 2 1 1];
%ms = [1 1 1 0.001];
ks = [1 2 3 3];
ms = [0.001 0.001 0.001 0.1];
[styles, colors] = plotColors();
xs = 0.01:0.01:2;
nk = length(ks);
legendStr = cell(1, nk);
for i=1:nk
model.K = ks(i);
model.m = m... |
fddb02acc4a8322ebc72450d0a2147e0d1b83dace07d446b818fd7f3b6919d39 | MATLAB | 1,394 | 22 | function result = totalFrameCountFromIntervals(startframes, endframes)
% Count the total number of frames covered by the intervals in startframes and
% endframes. startframes and endframes should be vectors of the same size,
% startframes(i) giving the first frame index of interval i, and endframes(i) giving the... |
1907dbaa9213f423302260f42feb0dd69bbe34c94fba889cbaaa255c7d16a67a | MATLAB | 1,395 | 43 | function hist = read_ctf_hist(filename)
% READ_CTF_HIST
% Copyright (C) 2010, Arjen Stolk
[p, f, x] = fileparts(filename);
if strcmp(x, '.ds')
% the filename should point to the hist file, not the ds
filename = fullfile(p, [f x], [f '.hist']);
end
fileline = 0;
fid = fopen(filename,'r');
% the hist file ... |
bc44cc0a6823540e248534d730bfd7ab0a7673f9de2a0b3db9bb96081510d697 | MATLAB | 1,395 | 49 | function model = mrf2Train(model, y, varargin)
% Fit pairwise MRF using ML/MAP estimation with L2 prior
% model = mrf2Train(model, y, ...)
% y is Ncases*Nnodes (y(i,n) in 1..nStates(n))
%
% Optional parameters
%
% lambdaNode, lambdaEdge : strength of L2 regularizers
% This file is from pmtk3.googlecode.com
[lambdaNo... |
4e41a75761e392c977faf18d81a093edaf0abe2a632d0a18086443696cd90d93 | MATLAB | 1,396 | 52 | function r2 = VBA_r2 (pred, data, isYout)
% // VBA toolbox //////////////////////////////////////////////////////////
%
% r2 = VBA_r2 (pred, data, isYout)
% coefficient of determination
%
% IN:
% - pred: predictions of the classifier
% - data: predicted data.
% - isYout: array of flags to exclude datapoints (def... |
aaa580875eb27b961bd43efe34b86810f39fb3a61e30b08f35b459994d3e6a1e | MATLAB | 1,396 | 29 | classdef CBIG_Yeo2011_unit_test < matlab.unittest.TestCase
% Written by XUE Aihuiping and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
methods (Test)
function test_example(testCase)
% Create output folder
script_dir = fileparts(mfilename('fullp... |
b3843eda0280fef12c62635d9bdb955ec884c84aed0d5f7289b65f6e1908482a | MATLAB | 1,396 | 51 | function [C,dt] = VBA_getNtuples(k,n,verbose)
% gets all n-draws (with replacement) from a k-urn.
% [C] = VBA_getNtuples(k,n,verbose)
% This function construct all the n-tuples that can be obtained (with
% replacement) from an urn containing k marbles.
% A couple of examples is worth a long description:
%
% VBA_getNtup... |
12a54eed158b456cacdcfadec9951328a1b7a2649d7c3d5d705aa5f84a43e3d0 | MATLAB | 1,397 | 50 | function final = NLMS_ecg(ACC,ECG,order,gr)
%% =========== ECG Artifact Removal with NLMS and ACC signals ======= %%
% ---------------------- Remove offsets -------------------------- %
ECG = ECG - mean(ECG);
for i = 1: 3
ACC(:,i) = ACC(:,i) - mean(ACC(:,i));
end
% --------------------- Initialize -------------... |
60b22ac9553241528149b2ee9647876a06182de80c4b83d69cf9788e0fc17ac1 | MATLAB | 1,397 | 43 | function [Ri,Ai,zzi,ni,Xi,Xzetai,zi] = MkSuffStatsBTDR_IncompObs_uneqvar_S_fast(X,Z,hk)
% Calculate the sufficient statistics for Bayesian TDR under the model of
% incomplete observations on each trial.
%
% [Ri,Ai,zzi,ni] = MkSuffStatsBTDR_IncompObs_uneqvar_S(X,Z,hk)
% N = # trials
% P = # input varaibles
% n = # neu... |
b55c5846a10727f4ff33ef21443446525c7fb7d75e0cd9bc387e76d5cecd32d6 | MATLAB | 1,397 | 42 | function y=anapulse(N,ti);
%ANAPULSE Analytic projection of unit amplitude impulse signal.
% y=ANAPULSE(N,TI) returns an analytic N-dimensional signal
% whose real part is a Dirac impulse at t=TI.
%
% N : number of points.
% TI : time position of the impulse (default : round(N/2)).
%
% Example :
% signal=2.5*anap... |
086de6e478319d9a15ceed7895d1954d4ba20bcc7083c7d7908cf236614940f2 | MATLAB | 1,398 | 46 | % Returns a random permutation of integers.
%
% randperm2(n) is a random permutation of the integers from 1 to n. For
% example, randperm2(6) might be [2 4 5 6 1 3]. randperm2(n,k) is only
% returns the first k elements of the permuation, so for example
% randperm2(6) might be [2 4]. This is a faster version of randp... |
54acc1b4c4ab9a27aa596ad24ea6437fcc18119d16cec788aa2837a434dffea4 | MATLAB | 1,398 | 72 | function [XYZ,XYZmm,val,V] = img2voxel(P,varargin)
% Given a mask or filtered image file name,
% returns XYZ coordinates in voxels and mm
% of nonzero, non-NaN voxels
%
% and img values at these coordinates in val
%
% ..
% Tor Wager 02/04/02
% Modified 2/15/06 to take raw data as well as image name
%
% ..
XYZ =... |
a99864b27f4095fa6b8449bf80c8208093bead5bcdfc637ee06a5e60e5efbdc8 | MATLAB | 1,398 | 72 | function v = lanversion(r,newr)
%
% LAN version function
%
% v.0.1.2 --> 10.01.2012
% v.0.1.1 --> 20.06.2011
% v.0.1.0 --> 11.01.2011
%
% Documentation in \tex\lan.pdf
% only in spanish
%
% 04.11.2011
% Pablo Billeke
%path
path = mfilename('fullpath');
path((end-10):end) = [];
% lan vers... |
deff0833ab99ad976092f75a8dcaf6925f746cbdde7ae67bca78c160b77f4b2e | MATLAB | 1,398 | 58 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
function [yes,... |
e70f1afbcad9b7ea19f873bcfa38aadac01d92c1783da3ef6918a721d7c141cb | MATLAB | 1,398 | 55 | function [exp_var1,exp_var2] = kernel_variance(DCM)
if ~isfield(DCM,'plot')
DCM.plot = 0;
end
M = DCM.M; % Model
Ep = DCM.Ep; % Parameters
%% Convert the model to a bilinear form
% This helps because there is a closed-form expression for
% the Volterra kernels of a bilinear system
[M0,M1,L1,L2] = ... |
f70246681748241fc503bceaf0cba767de131c75682c67b33b514a80911abefd | MATLAB | 1,398 | 36 |
ind = 1;
data = dir('/DATAPOOL/ERRORMONITORING/SEM_mri_data/P*');
%%
for i = 1:size(data,1)
data_func = dir([data(i).folder, '/', data(i).name, '/mri/SEM_', data(i).name, '/nifti/func/run*']);
fprintf(data(i).name);
for j = 1:size(data_func,1)
images = [data_func(j).folder, '/', data_func(j).n... |
356ddf31285c8424b938cdbf3fab8b67e1db0432d8aa4da0f3ea3c21eed72bb8 | MATLAB | 1,399 | 48 | %% xvect2px
% Generic method for turning a state signal (1 x M) into a (M x N) array
%of 0/1, which corresponds the 'probability' of state, represented as
%sequential column vectors. If DIM 1 is > 1, then average over p(x) over t
%over the same values.
% Copyright (C) 2023 Trevor S. Smith
% Drexel University C... |
6e27d00b94ecbb034ecff8d8fa21a54e1c0946cca3eca02459d945cf7ed60b2d | MATLAB | 1,399 | 56 | function [inspk] = wave_features(spikes, cfg)
% NOTA: este script es un PLAGIO
% NO DISTRIBUIR BAJO NINGUNA CIRCUMSTANCIA
%
% ************************cfg************************
% - scales
% - feature
% - inputs
%
% ********************DEPENDENCIAS********************
% - wavedec (Wavelet Toolbox)
%
scales = cfg.scale... |
8d9eecef92e0c9fd3f29bc60622ba74d4290493b1b571639d3fcde1ff81f1f64 | MATLAB | 1,399 | 37 | function [argout] = mxDeserialize(argin)
% MXDESERIALIZE reconstructs a MATLAB object from a uint8 array suitable
% for passing down a comms channel to be reconstructed at the other end.
%
% See also MXSERIALIZE
% Copyright (C) 2005, Brad Phelan http://xtargets.com
% Copyright (C) 2007, Robert Oostenveld ht... |
33463354c0e27ac5c6ca2731a2742ffe5aad3365ebc6e3a1abe13a4056dd7502 | MATLAB | 1,400 | 44 | % Basic demo for fitting mixture of Gaussians
% This demo first simulates a noisy MoG density profile, whose mode
% position and width are then estimated using VBA.
close all
clear all
clc
%---- simulate noisy data
% Choose basic settings for simulations
sigma = 1e-1; % precision
phi = [5;-1;1;3]; ... |
6f08b85f1bdb7e8f3a1158d2fc5e6d196e4ffea3aed16fcd44e0992f711fa523 | MATLAB | 1,400 | 25 | function [Epri, Ppri] = bemf3_inc_field_electric_plain_dipoles(strdipolePplus, strdipolePminus, strdipolesig, strdipoleCurrent, Points)
% Computes potential and electric field from the dipole distribution via the FMM
% at observation points (Points)
%
% Define source (pole) positions and FMM pseudo charges ... |
773a2ae991332d847086d28edddb5c0be87defdcd641eedd5521766c92809666 | MATLAB | 1,400 | 46 | function [sx, dsdx] = VBA_sign (x, smoothness)
% // VBA toolbox //////////////////////////////////////////////////////////
%
% [sx, dsdx] = VBA_sign (x)
% smooth (ie. derivable) approximation of the sign() function
%
% IN:
% - x: real value
% - smoothness: optional parameter that specify the speed of transition
% ... |
b65158d85dd086ccb7659ef64f6e0f9bde754528ddea82a9400c469e21e045ed | MATLAB | 1,400 | 45 | function posterior_predictive(stimulus, response, rt, spstart)
% plot posterior predictive as done in Python
% see de Gee et al. eLife 2017, figure 4
if ~exist('spstart', 'var'), spstart = 1; end
colors = linspecer(2);
% recode RTs to be negative
resps = unique(response);
rt(response == resps(1)) = -rt(response == re... |
f21e8a5b97b8e78cd79c01cff84ce23662199615985e5b03c035f6eae5e89880 | MATLAB | 1,400 | 51 | function makeGif( M, fileName, prm )
% Writes a matlab movie to an animated GIF.
%
% USAGE
% makeGif( M, fileName, prm )
%
% INPUTS
% M - Matlab movie
% fileName - file name of the output gif file
% prm
% .fps - number of frames per second
% .nColor - number of indexes colors
% .scale ... |
373b4c316df7b9a98e6a679c773872b93b2fa02204586dc1f1dde84d0fbe79ce | MATLAB | 1,401 | 58 | function [T, S] = FitzHughNagumo_OriginalTIStimOptimizedParameters(twidth, freq, amp, Fs)
init = [-1, -0.6];
tspan = 0:1/Fs:twidth; % ms
options = odeset('MaxStep', 0.05);
[T, S] = ode45(@(t, s)FNModel(t, s, freq, amp), tspan, init, options);
function ds = FNModel(t, s, freq, amp)
ix = sum(diag(amp)*cos(2*pi*freq... |
942d6a8da7e06c3ae02e53d52518b4f36d86eb20a263a01108b1ad378944bc26 | MATLAB | 1,401 | 48 | %% Compute empirical distribution of coefficients drawn from a Gaussian ensemble
% Exactly k0 elements are non-zero. The resulting marginal is a good prior
% for the weights in a sparse linear regression model
%
% Based on code by Baback Moghaddam
%%
% This file is from pmtk3.googlecode.com
if ~exist('n','var'), n=12... |
fda92a466f0b00139b0d26e3a86f9eec2877829a1cf0a5f062d167ea7c91f93d | MATLAB | 1,402 | 55 | %% Compare various optimizers on a binary logistic regression problem
% This file is from pmtk3.googlecode.com
%PMTKslow
setSeed(0);
% Use classes 2,3 for simplicity
Ntrain = [];
[Xtrain, ytrain, Xtest, ytest] = mnistLoad([2 3], Ntrain);
ytrain = setSupport(ytrain, [-1 +1]);
ytest = setSupport(ytest, [-1 +1]);
[N... |
0c8f51d2d6a0bff6927d10a39006c7928541d6691acb3d0eabfddb443f989c27 | MATLAB | 1,403 | 38 | function [ xcorr_scores,shifts ] = crossCorr3D(data1,data2,offsets )
%CROSSCORR3D Summary of this function goes here
% Detailed explanation goes here
border_mask = zeros(size(data1));
border_mask(1:offsets(1)+1,:,:)=1; border_mask(end-offsets(1):end,:,:)=1;
border_mask(:,1:offsets(2)+1,:)=1; border_mask(:,end-offset... |
8286d0230ac2e036446c8e5147287ad2e03cca79aaa710b1b819791efbd0305e | MATLAB | 1,403 | 48 | function [stacky,stdy,gridg,stdg] = VBA_Bin2Cont(gx,y,maxn)
% transform binary data into continuous intervals (for display purposes)
% function [stacky,stdy,gridg] = VBA_Bin2Cont(gx,y,maxn)
% This function first partitions the data according to percentiles of the
% empirical disitrbution of conditional likelihoods. The... |
b4a7fac94bd5827a1f743ef95d151f1b82065bb5277d2c05613667d54a9b3dbe | MATLAB | 1,403 | 35 | function h_roiQuality3(handles)
% [currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
roiobj = [findobj(handles.h_imstack3,'Tag','ROI3');findobj(handles.h_imstack3,'Tag','BGROI3');...
findobj(handles.h_imstack3,'Tag','annotationROI3')];
for i = 1:length(roiobj)
parent... |
b8b51ebeb370aef6bff5a8092b1aa3cd2e40576c53c2c5d33abb9ad10523de3c | MATLAB | 1,403 | 50 | %% Plot posterior on difference in rates given paired contingency table
% MC approx to figure 1a of Shi and Bai 2008
% PMTKneedsStatsToolbox ksdensity
%%
% This file is from pmtk3.googlecode.com
requireStatsToolbox
setSeed(1);
ns = [20 20 10 50 30];
n10s = [0 1 2 20 28];
n01s = [20 19 4 5 0];
figure; hold on;
[styles... |
e2f71e2a07e0f0580de92d9f38ffcb5c77eea7d1248367b4af0a2081c45a831d | MATLAB | 1,403 | 36 | function out = xpathNode(node, path)
% XPATHNODE Shorthand for loading node from xml file
%
% xpathNode(node, path)
%---------------------------------------------------------------------
% license
%---------------------------------------------------------------------
% Copyright 2015 I... |
2543b4868f7c337ef869d017551ed8fe25125bedd3ce4171b633669398092ff1 | MATLAB | 1,404 | 46 | function TSexporteventcodes(filename)
% TSEXPORTEVENTCODES Exports event codes to a textfile.
% TSexporteventcodes(filename) exports codes to an ascii textfile. This
% file can be imported later by TSimporteventcodes, or set to the default
% codeset using TSsetdefaulteventcodes.
%
% You can use this to send yo... |
48c8fa8f39c7971dcd3d8fe4d3bbd8e168fa8bc409eaa8669ea5a6e7c1671013 | MATLAB | 1,404 | 45 | % AverageData.m
% Sarah West
% 4/11/22
function [parameters] = AverageData(parameters)
% Display progress message to user.
MessageToUser('Averaging ', parameters);
% Pull out data.
data = parameters.data;
% If user says to remove outliers
if isfield(parameters, 'removeOutliers') && paramete... |
2d1e4764fff9162544fb311b5e317da79ffb2d5115eb4ba8edcf80bc8f7fc916 | MATLAB | 1,405 | 38 | % Written by Einat Peled
% einatspeled@gmail.com
%
% Get a vector of response amplitudes
% ImageArray_CorrAmp_norm_InMax: contains images with highest-value pixels at all response locations
function Vector_RF_CorrAmpNormValues_AllNMJ = GetRFAmpValues_Array(ImageArray_CorrAmp_norm_InMax, ImageArray_Max, AllBout... |
30ec8ceed75572244f6841db7f9d582d934f6357e66bee9be0e475bdebcce065 | MATLAB | 1,405 | 42 | function [fx] = f_wslsinGame(x,P,u,in)
% "win/stay - lose/switch" strategy in a dyadic game
% function [fx,dfdx,dfdP] = f_wslsinGame(x,P,u,in)
% The "win/stay - lose/switch" strategy is encoded in terms of the
% evolution of pseudo q-values, which swap sign depending upon the
% feedback.
% In a dyadic game, the feedb... |
8637161dc0dade91938363393e8b6af5816f7f557dde68ff40732ff413c2750b | MATLAB | 1,405 | 33 | function Wbig = interpolateLarsWeights(Wfull,lambdas,X,y)
% Wbig(i,j) = w(j) using lambdas(i) for the L1 penalty in lasso
% Input:
% Wfull is the output of lars; each row is a solution (gets denser)
% lambdas - desired range
% X: input data, each row is a case
% y: input data
%
% based on code by Skoglund
%%
% We have ... |
58a8f01d9fd7b03732c7bef3e0c3430d8c1bf277b57bea3efa6bb7176acc14d7 | MATLAB | 1,406 | 41 | function exportsvn(source, dest, exclusions, createEmpty)
% Export and zip up a local svn repository ignoring .svn files
% SOURCE: path to the root directory of the svn source
% DEST: path to destination including zip file name
% EXCLUSIONS: a cell array of directories to exclude from the
% zip ... |
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