sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
8cef0f004403edca1f65dff9525b237260394fdb6a17eea7fa9757fee3283cd8 | MATLAB | 3,899 | 114 | function [Kernel, feat, D] = hmm_kernel(X_all, hmm, options)
% [Kernel, feat, D] = hmm_kernel(X_all, hmm, options)
%
% Computes a kernel, feature matrix, and/or distance matrix from HMMs.
% Implemented for linear and Gaussian versions of Fisher kernel & "naive"
% kernels
%
% INPUT:
% X_all: timeseries of all subjec... |
a4ffd96ad0f78706a54605846fbde13c1b78c73188f772bf4f3e2e7d6c07ae81 | MATLAB | 3,899 | 132 | function Metrics = Gradient_Metrics_Calculation(GradientResult, Options, OutDir)
% =========================================
% Gradient Metrics Calculation (Subject-wise)
% Compatible with Result struct from Gradient_Calculation
% =========================================
% Input:
% GradientResult: struct with fields... |
b92235251e96a862189295f89783130c1407742a673748b650e1d8d5f8d4876d | MATLAB | 3,899 | 108 | % Second-kind integral equation on the unit square, Laplace single-layer.
%
% This is basically the same as IE_SQUARE1 but with the identity added to the
% system matrix in order to create an artificial second-kind volume integral
% operator. It skips the preconditioned GMRES comparison since the problem is
% well-cond... |
d9d4f445c36ad09e01ccb920c9f99b110db234525ba09f1904077bb692f0ee62 | MATLAB | 3,899 | 114 | function [goodTrials,badTrials,p]=inputBADtrials(p_strct,subj_location)
% prep work
numTrial = ceil(p_strct.epoching(subj_location,3) / p_strct.epoching(subj_location,2));
%%%%%% GUI
f=figure('Visible','off','Units','pixels','Name','Bad Trial Input',...
'Position',[50 200 250 400]);
% Enter Channels
textIN=uico... |
2a8816e7299324f35647bc538241eeb4c9f6f22e373bdc3461136d82c7c25f89 | MATLAB | 3,900 | 70 | %% Apply a new atlas to an image
% Here the atlas HCPex_SUIT_AGBT was applied to the PET scan,
% which means that the scan was masked.
% Each parcel of the new image is now the average voxel intensity
% of the corresponding parcel on the PET scan.
% 08.04.2022 - JVH
%% SPM is needed for Lead DBS, which we use to read ... |
5622dc9057f904f7379fd8a76da122b8a600a987dc08d117b9110f14fb932242 | MATLAB | 3,901 | 170 |
function xend = filter_hilbert(x,Fs,Fp1,Fp2,norbin)
% <°LAN)<]
% v.0.1.2
%
% Hilbert filter
% (1) Realizar filtros pasabanda de la senal x, Entre Fp1 yFp2,
% Fs como frecuencia de muestreo
% (2) Aplica transfomada de hilbert para generar senal analitica (Sa)
% de la senal (S), forma:... |
b6528ce3e2ade82b95c8cde20bfae0e4246ac8ed6c1af9c4e591942dbc33f95e | MATLAB | 3,902 | 62 | function X0 = getStartingState_ToRORdLand(varargin)
if (~isempty(varargin))
if (strcmp(varargin{1}, 'm_endo'))
X0 = [-88.6369922306458,11.8973412949238,11.8976610470850,...
141.234464714982,141.234423402713,7.26747296460659e-05,...
6.33786975780735e-05,1.53265306371... |
ee701548bdcf6ac7495cb73ee352577a422f423d68ddcc9e0638661cbb1fb393 | MATLAB | 3,904 | 91 | function id = ticStatus( msg, updateFreq, updateMinT, erasePrev )
% Used to display the progress of a long process.
%
% Essentially, use 'ticId = ticStatus' to start a new progress
% indicator, and then update the progress indicator with a call to
% 'tocStatus( ticId, fracDone )', where fracDone is the fraction of
% th... |
b61ccf50cac6ed8c1df7f3f28d3cf5c9234303c51fa4c47007565f28bc94a734 | MATLAB | 3,905 | 129 | %XMLDEMO1 Demonstrate how to create an XML tree and save it
%
% Description
% This script demonstrates the use of the xmltree class to
% create an XML tree from scratch and save it in a file.
% Copyright (C) 2003 Guillaume Flandin
% Please note that this script is only a demonstration of how
% to use xml... |
05210184e669d31468b52a64e1b25c41d5b15796ea9434f5a5c2befadf45fb07 | MATLAB | 3,906 | 96 | function filt = filter_with_correction(B,A,dat,dir,usefftfilt)
% FILTER_WITH_CORRECTION applies a to the data and corrects
% edge-artifacts for one-pass filtering.
%
% Use as
% [filt] = filter_with_correction(B,A,dat,dir);
% where
% B,A filter coefficients
% dat data matrix (Nchans X Ntime)
% dir... |
357b950c4a214a61fa1dffc0d874b1ddb5fb8b53a809721a01d068dceebf594a | MATLAB | 3,906 | 230 | function [] = plot_neur_new(rat_name,type)
%%% plot pulse responses
rat=rat_name(2:end);
rat=str2double(rat);
res=2;
dur=66;
load data/combined_kernels.mat
%%% (generated by combine_neural_kernels.m)
data=data_all_trials;
data.centers=-1:res/100:2;
vecx=0.01:0.02:dur/100;
data.vecx=vecx;
load data/rat_for_e... |
6fea27e1a1cd3b46ab5b2ab687b9ced96c955cdc248ea77b3e4e4720435aa71f | MATLAB | 3,907 | 84 | function [bvc_loglik,fr_loglik, fd_loglik, uniform_loglik, bvc_prob, fr_prob, fd_prob, bvc_logprob, fr_logprob, fd_logprob] = fit_bvc_and_other_models(v, dataset)
% Generate bvc tunings
v = calculate_bvc_tunings(v);
% Create environment based on resolution and aspect ratio
v = env_distances(v);
bvc_pop = generate_bvc_... |
6480c001b49ed9842d527f51136fe35a099a1d3bb66af1271ad4e9a13d2bfe84 | MATLAB | 3,908 | 120 | function meg_Fig4b_TE_allTrials_mdlFit_slope_bar
% meg_Fig4b_allTrials_mdlFit_slope_bar
% Plot linear model slope (All trials)
%% Load data
filename = 'figData/ModelFit_SeparatePrecueT1T2_2Hz_session.mat';
load(filename)
%% Figure settings
titleVis = 0; % if title vis off, then will plot for appropriate manuscrip... |
8d1c4636a1e03bf69c15615a8a7cd640c8208a92c77bdfb5401fcc1779d237c4 | MATLAB | 3,908 | 138 | clear;
clc;
close all;
srate = 400;
atimes = linspace(-1500,1500,srate*3);
mtimes = linspace(-1500,1500,srate*3);
frequency_range = [1:40];
%%
warning('off');
band_labels = {'\delta (<3Hz)','\theta (3-6Hz)','\alpha (7-14Hz)','\beta (15-30Hz)','low \gamma (31-40Hz)'};
band_limits = [3 6 14 30 40];
... |
e1e09bd84520fd9dd1ab853f03bdced25678624c6e02707854891a0c3c803270 | MATLAB | 3,908 | 108 | function [dat] = read_ricoh_data(filename, hdr, begsample, endsample, chanindx)
%function [dat] = read_ricoh_data(filename, hdr, begsample, endsample, chanindx)
%
%% READ_RICOH_DATA reads continuous or averaged MEG data
%% generated by the RICOH MEG system and software,
%% and allows the data to be used in FieldTrip.
... |
267db5b3da621a5f02c87e6b91ca35ab78d39d0246269c6210120f83984102c3 | MATLAB | 3,910 | 107 | function [group_copes, thresh] = run_group_glm( data, ...
first_level_design_matrix,first_level_contrasts,...
group_level_design_matrix,group_level_contrasts,...
nperms, use_tstat,use_flame)
%%function [group_copes, thresh] = run_group_... |
8bd0d31e9300fde5b674ec051d47a23120a1b0f9dd897cd8482263426ef60206 | MATLAB | 3,910 | 108 | classdef ActionResults < handle
%
%
%
%<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 ... |
dda10d292aea891d91948f2e6b45099388cfa1a9f3528d2b4bdb73aaf65fe336 | MATLAB | 3,911 | 191 | %%% This code is an additional code that helps doing projector calibration in 3D scanning setup.
%%% This is not a useful code for anyone else but me.
%%% I included it in the toolbox for illustration only.
fprintf(1,'3D scanner calibration code\n');
fprintf(1,'(c) Jean-Yves Bouguet - August 2000\n');
fprintf(1,'Inte... |
f7e9dbbe2197bc06cbfdcabdd57e63f3ab1ab34440ff042201ecdafa5d71aa9d | MATLAB | 3,912 | 264 | clear
clc
close all
%%% uncomment rat name to produce the corresponding plot
% ratto='P049';
ratto='P055';
% ratto='P059';
% ratto='P095';
% ratto='P100';
% ratto='P101';
% ratto='P102';
directory_sessions='data/Sessions_trials/';
load([directory_sessions ratto '_sessions.mat']);
minperf=.65;
minbeta=.65;... |
5a36fb7260ff7ff999203f88f4977616daaba219df3876c94407a53b61afc0a0 | MATLAB | 3,914 | 100 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This script computes the global efficiency and participation coefficient%
% according to the Seitzman et al. (2020) atlases. %
% Make sure to compute the information for the group atlas first!!! %
% ... |
5dadc14c79cb61b6c994548811587f73bfb015aa156a619deebf66878921bdd6 | MATLAB | 3,914 | 98 | function [event] = read_nmc_archive_k_event(eventfile)
% READ_NMC_ARCHIVE_K_EVENT extracts event-data from nmc_archive_k datasets
%
% Use as
% event = read_nmc_archive_k_event(eventfile)
%
%
% This function specifically only reads data from one of the archived
% datasets of the Neurophysiological Mechanisms of Cogni... |
6ae082bc787df84648e6aa66ddac46e62b1ff78b6ec1a92e7f65b7ef4f56d889 | MATLAB | 3,917 | 150 | function y = dyadup_gpu(x,varargin)
%DYADUP Dyadic upsampling.
% DYADUP implements a simple zero-padding scheme very
% useful in the wavelet reconstruction algorithm.
%
% Y = DYADUP(X,EVENODD), where X is a vector, returns
% an extended copy of vector X obtained by inserting zeros.
% Whether the zeros are ins... |
4435a14b1dc3724daa812f4d55e657e5ecd11e02b5bc3562b04c2c04372cd197 | MATLAB | 3,918 | 72 | function [PC, integralpd] = meshneighborints_Pn(P, t, normals, Area, Center, RnumberP, ineighborP, Indicator, numThreads)
% Accurate integration for electric potential on neighbor facets
% Done for a selected interface only ("Indicator" variable is used)
% Copyright SNM 2018-2022
ppool = gcp('nocre... |
b50a1a0f1b0d736aebbdcd797141b0f2341c583574ab49244238f2ec78a9f759 | MATLAB | 3,918 | 124 | function doitColor(debugging,scale,aspect,imFile,append,origin,seedFile)
randn('state',sum(100*clock));
stimPath = '/e/2.2/p1/freeman/Documents/EeroLab/textures/stimuli/';
oim = double(((imread(fullfile(stimPath,imFile)))));
% for 256, scale of 2, aspect of 0.25, overlap of 0.01, and rad deg of 0.5
% gives me a good... |
58234d11d8e13004a2e1233cf983293ca802766c3524e4bb19a932b907563978 | MATLAB | 3,920 | 141 | % Re-select te corners after calibration
if ~exist('n_ima')|~exist('fc'),
fprintf(1,'No calibration data available.\n');
return;
end;
check_active_images;
flag = 0;
for kk = ind_active,
if ~exist(['y_' num2str(kk)]),
flag = 1;
else
eval(['ykk = y_' num2str(kk) ';']);
if isnan(ykk(1,1)),... |
4398298436278ac271c1e849908c97f7f567650060e4c77d519f24b90a9437cc | MATLAB | 3,921 | 122 | function [data] = femdata_TR_moments(mesh, varargin)
% FEMDATA_TR_MOMENTS Calculates spatial distributions and boundary values
% of statistical moments or Mellin transforms of time-resolved data for a
% FEM mesh in the NIRFAST format. This function is a wrapper to call
% mesh-type-specific femdata functions. This... |
ab036f62487cb095b9d24242cf02b5362ca0a5eeb93ed2c2b523878b717e3239 | MATLAB | 3,921 | 94 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
% Description:
% This script computes a sensitivity analysis of the mean maximum muscle-tendon (MT) moment to changes in
% muscle para... |
768109015b7716d58bf539171426214c3b2b2779707237a6cbc6f9bbca999902 | MATLAB | 3,923 | 95 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
% Description:
% This script computes a sensitivity analysis of the mean maximum muscle-tendon (MT) moment to changes in
% muscle para... |
2f05a6cde3419c0895a54abb164f789e4d420204ca5287ddbfbac2c24ed24525 | MATLAB | 3,924 | 100 | %{
Copyright (c) 2025 Axion BioSystems, Inc.
Contact: support@axion-biosystems.com
All Rights Reserved
%}
classdef BlockVectorHeader < Entry
%BlockVectorHeader Primary data regarding a BlockVectorSet of Data
% This class contains the basic information about an entry of
% Block Vector Data th... |
aba8dd1152f748355f144d6ec6f1963c10d9110a93ac20c9f877a5e5eac068fd | MATLAB | 3,924 | 152 | function hh = herrorbar(cax, x, y, l, u, symbol)
%HERRORBAR Horizontal Error bar plot.
% HERRORBAR(X,Y,L,R) plots the graph of vector X vs. vector Y with
% horizontal error bars specified by the vectors L and R. L and R contain the
% left and right error ranges for each point in X. Each error bar
% is L(i)... |
bc684a600d67c6a314559c28f7e83fc4243aebe1e8320107bb9b92b840ecdf83 | MATLAB | 3,924 | 96 | %#########################################################################
% Parse the ontology.xml of the AllenBrainMouse_CCFv3_201710
%
xDoc = xmlread('1.2_ontology_-_used for manuscript.xml');
allListitems = xDoc.getElementsByTagName('structure');
parsedOntologyXML={'structureId', 'structureLR', 'structure... |
d5669516fe85212a1f4473bfd508081d5d10bcb803fad4037f8da710cdd114a1 | MATLAB | 3,924 | 121 | function StoreEdfInMat(IDs, behDataFolder, exeFile, skipPractice)
% StoreEdfInMat
% convert edf to asc, readAllEdf, store that in result.s
addpath ../../Experiments/MyFuncs/
if exist('IDs') && ~isempty(IDs)
if ~iscell(IDs)
IDs = {IDs};
end
else
IDs = {'Tri';}; % find all by default
end
if ~exist('... |
85233d10fdc46640b6e4075a42d0839a9510fd48c6c85da84af64cd3bb9a0630 | MATLAB | 3,925 | 89 |
function y_Normalize_WriteToMNI_DARTEL(SubjectID,SourceDir,OutpurDir,T1ImgNewSegmentDir,DARTELTemplateFile,IsSubDirectory,BoundingBox,VoxSize)
% FORMAT y_Normalize_WriteToMNI_DARTEL(SubjectID,SourceDir,OutpurDir,T1ImgNewSegmentDir,DARTELTemplateFile,IsSubDirectory,BoundingBox,VoxSize)
% SubjectID - The ID (or nam... |
bc2818650f5c5f4de255af8db7ca5a95ccaaeb4cc647f43daddb1688957745bf | MATLAB | 3,925 | 119 | function draw_figureS5(p,decRes,rsaRes)
%
% This code is for drawing figure S5
% In the paper, we used Pycortex (Gat et al., 2015) for drawing map.
% Here, similar visualization is mimicked without pycortex
%
%% settings
% prepare surface map
load([p.rootPath,'code/util/hcp360colMap.mat'],'hcp360colMap');
% ROI info.... |
7204df40332d441a0e5507550e47347463b4cca92d4b21edf481080ba9135117 | MATLAB | 3,927 | 110 | function grad = getGradient(problem, x, storedb, key)
% Computes the gradient of the cost function at x.
%
% function grad = getGradient(problem, x)
% function grad = getGradient(problem, x, storedb)
% function grad = getGradient(problem, x, storedb, key)
%
% Returns the gradient at x of the cost function descri... |
b34368038819018d3cb8d48e39a4ccbb508e1c43452e8b5158883338c19f7a3b | MATLAB | 3,928 | 103 | % Five-point stencil on the unit square, Poisson equation.
%
% This example solves the Poisson equation on the unit square with Dirichlet
% boundary conditions. The system is discretized using the standard five-point
% stencil; the resulting matrix is square, real, and positive definite.
%
% This demo does the followin... |
3981eaec953978db24e1faed04f363763790d540243b72667529d256609650ef | MATLAB | 3,930 | 93 | % calc_pop_signals
% load(fullfile(saveLoc, 'par_sess'))
for sess = 1 : 8
clear par dd beh behMap behView spk spkMap spkView
clear spkZ spkMapZ spkViewZ spkZnan spkMapZnan spkViewZnan
load(fullfile(saveLoc, ['spk_S' num2str(sess)]))
load(fullfile(saveLoc, ['spkZ_S' num2str(sess)]... |
509f4f07142a1dffe225ce152f392352ae11c4303fbf00efaf2bf7a5939d9929 | MATLAB | 3,930 | 105 | %PURPOSE: Calculate language lateralization in HCP subjects using
%Fedorenko lab methods
%INPUTS: t-statistic maps from story-math contrast (preprocessed and
%fsaverage6 resolution), LanA atlas in fsaverage6 resolution
%OUTPUTS: .csv file contatining lateralization values per participant
%DEPENDENCIES: gifti
%package(h... |
cdbc54f832de616fa896c6c7e665ced13a2190bf94fafed2672697353d159b9e | MATLAB | 3,930 | 98 | classdef DataspaceLook < dspace.app.DataspaceLook_whiteTheme
% Change the constants defined in this class to adjust the dataspace
% GUI appearence.
%
% There are two blocks of constants:
% (1) Looks
% (2) Other Constants
%
% Best practice is to copy a block, comment out the origi... |
c2ae655100689a6ef73cd12a393cd5084384e208661cd541f008dd56fe29088b | MATLAB | 3,931 | 157 | classdef HeatmapReader < handle
properties (Constant)
% sprintf-style pattern; tgt,frm,part, all 1-based
filepat = 'hmap_trx_%d_t_%d_part_%d.jpg';
filepatre = 'hmap_trx_(?<iTgt>[0-9]+)_t_(?<t>[0-9]+)_part_(?<ipt>[0-9]+).jpg';
end
properties
dir % fullpath heatmap dir
imnr
imn... |
f3c5d5ddcadd81247c65c223368ed0565947ad14312262eca241b5dcb917aa91 | MATLAB | 3,932 | 95 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
% Description:
% This script computes a sensitivity analysis of the mean maximum muscle-tendon (MT) moment to changes in
% muscle para... |
351ba950ce442d4cde281a9b22b63fb45715735cab693f2e96def4694f00a0ca | MATLAB | 3,934 | 92 | function [ titleStr, settings, results ] = runMatlabFunction( dataview, settings )
% Run matlab commands on the current datasource. The matlab commands have
% to be specified as a one or several matlab expressions that may use the variables:
%
% >> dsource
%
% >> dview
%
% >> p... |
dfcad275c0e136c7afafcc5d346e553ca4217621d2d3079df88342e7b5d02f0b | MATLAB | 3,934 | 101 | function [dat, dimord] = read_shm_data(hdr, chanindx, begtrial, endtrial)
% READ_SHM_DATA reads the data in real-time from shared memory
% this is a helper function for READ_DATA
% Copyright (C) 2007-2009, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentatio... |
fed6ed32f1e9ab5440b7387cb41a55bf1b596ad51051177d291cb3585e8ef4d6 | MATLAB | 3,934 | 127 | %% autocov_to_var
%
% Calculate VAR parameters from autocovariance sequence
%
% <matlab:open('autocov_to_var.m') code>
%
%% Syntax
%
% [A,SIG] = autocov_to_var(G)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% G autocovariance sequence
%
% _outp... |
c5896e43a44bc8e22700e80e44d7579f91baeaf9c156da932145e8892e815b7a | MATLAB | 3,935 | 116 | function [ferns,hsPr] = fernsClfReplaceFeature( data, hs, ferns, features_remove, varargin )
% Train random fern classifier.
%
% See "Fast Keypoint Recognition in Ten Lines of Code" by Mustafa Ozuysal,
% Pascal Fua and Vincent Lepetit, CVPR07.
%
% Dimensions:
% M - number ferns
% S - fern depth
% F - number... |
f1506c242f69778e6a0d6443b28e1184099e84ee871100c62b9ea741b6578a95 | MATLAB | 3,935 | 100 | function NewColorMap = y_AdjustColorMap(OriginalColorMap,NullColor,NMax,NMin,PMin,PMax, PN_Flag)
% Adjust the colormap to leave blank to values under threshold, the orginal color map with be set into [NMax NMin] and [PMin PMax].
% Input: OriginalColorMap - the original color map
% NullColor - The values between ... |
4a0f3bd473b162accb76f63782d383b39da81b52012f92336569ca8fcafdeb5f | MATLAB | 3,937 | 80 | %%
%NOTE - x axis in Figure 8d of the manuscript should be labelled radius, not diameter - this has been updated in this script
%%
clear all
%%
%Define Parameters
[opt] = ParameterOptions();
%%
%Define Parameters for Oscillating gradients
opt.nOscillations=3; % Number of oscillations per TR
opt.Waveform='Sine'; %... |
c84763538199c1bf2e0ded0df9bf18c284706fdac235438bf0dbb623c4dd0149 | MATLAB | 3,938 | 101 | function [posterior, out]=demo_Qlearning(choices, feedbacks)
% // VBA toolbox //////////////////////////////////////////////////////////
%
% [posterior, out] = demo_Qlearning([choices, feedbacks])
% Demo of Q-learning simulation and inference
%
% This is a simple example of reinforcement learning algorithm.
%
% Backgro... |
c9b3ef750421d3995cfd768edac19be659d853c655798723f586ea0c39ea1ef3 | MATLAB | 3,938 | 102 | function [w,output] = boundOptL1Stepwise(X,Y,lambda)
% Fit the weights for L1 penalized multinomial logistic regression by
% updating each component of each weight sequentially in O(ndc)time where n
% is the number of training examples, d is the number of dimensions and c
% is the number of classes.
%
% Inputs:
%
% ... |
23885cec85e53035ae0ca9954477c4b55597bd3a918d0e811b8f20611ba23388 | MATLAB | 3,939 | 96 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
% Description:
% This script computes a sensitivity analysis of the mean maximum muscle-tendon (MT) moment to changes in
% muscle para... |
5df1763db1c6b2405b24bd3a802505caae3507bda584069c954bd891198b6c72 | MATLAB | 3,939 | 152 | function [tot_newbdye,tot_newbdyp]=create_nodes_perimeter(bdye,bdyp,dl)
% gets a 2d bdy and creates new nodes along that bdy which are located 'dl'
% apart each other along that bdy
idx=1;
tot_newbdyp=[];
tot_newbdye=[];
allnodes=unique([bdye(:,1);bdye(:,2)]);
twod = false;
if size(bdyp,2) == 2
bdyp(:,3) = zeros(s... |
cb3e9cb45553f57fafe228fa6939f365f9c1644ead4d158b013e9a1f53ef0ce4 | MATLAB | 3,941 | 112 | function ret = w_spm_ov_rgb(varargin)
% RGB overlays
% A shorthand to overlaying the absolute value of three different images
% onto a displayed image in colours red, green and blue. The overlay images
% are optionally masked and multiplied with a scaling image. The displayed
% overlay images are the absolute value of ... |
76637d1904a5c93431af549db3f4b4a564b3feeaefe1ca511faf412097b66485 | MATLAB | 3,942 | 118 | function [] = randnetDecode(replaytrajectory, varargin)
% plots.randnetDecode.m
%
% Plots decode results from run_net_decode.m
%
% Inputs:
% - replaytrajectory: Bayesian decoding results cell array
% - replaytrajectory{p.day}{p.ep}.<fieldname>
%
% Outputs:
% - No output. Generates plots.
%
%% Parse inputs
i... |
d9d5fb04eec83baaf24a583ce940acdabd6b6b88c539ba016263ea7155e76ce6 | MATLAB | 3,942 | 91 | %% This file runs and saves the results used in Figure 2.
% for each set of Delta (2500 sets), 1000 simulations of randomly chosen
% D,beta pairs are used to test the R^2 values of simulations.
%% Machine and simulation parameters
N = 1000; % Number of simulations
NDirs = 64;
SNR = [5,10,20]; % Signal-to-Noise ... |
9a5ce6289c1837eb06c725eae7eec090819b9a79423473913060fb936f6523d9 | MATLAB | 3,943 | 152 | %--------------------------------------------------------------------------
% OUTLIERS: outlier detection
%
% [ Xmd,OL ] = OUTLIERS( Xol ) takes as input a dataset Xol, which may
% contain outliers, and returns as output a modified dataset Xmd, where
% the outliers have been removed (i.e. every outlier is re... |
3a8afc9e9ab57a17a785b61b5a608f076097a36d17a497fc2be9d1d8ce6e3701 | MATLAB | 3,945 | 116 |
function [negloglik, grad] = neglogLikBTDR_IncompObs_uneqvar_lambonly(pars,S,Ai,Ri,zzi,r,ni,g)
% Negative marginal log-likelihood for basis of population regression
% model
%
%[negloglik, grad] = neglogLikBTDR_IncompObs_uneqvar_S_fast(pars,Ai,Ri,zzi,r,ni,g)
%
%Computes negative log-likelihood under linear Gaussian reg... |
08fd3f2bae17378ee2732d089bf0d9972959a341fb3509bc77b2a95ab9f414bd | MATLAB | 3,946 | 145 | function RGB = colormaplan(type,n,lim,cbar,nmax,ne)
% <*LAN)<]
% v.0.0.3
%
% RGB = colormaplan(type,n,lim,cbar,nmax,ne)
% Created Colormap and colorbar
% type = 'pval' % using the rval result of nonparamteric.m
% 'logP' % plot the -log10(p value)
% n = n % resolution, default... |
4585c215c2eb2808970e78954f8c8fbd1da8d39e37fb3282ca026f27fb030517 | MATLAB | 3,949 | 1 | function GLAN = timefreq_stata_boot(GLAN,cfg)
% REALIZA BOOTSTRAPPING A TIEMPO-FRECUENCIA
%
%
%
% cfg.
% subject = [{}{}{}]
% comp =[n1], 'all'; % INDEX OF THE CONDITION,
% alpha =0.05;
% bl =[ 0 0.4]; % BASELINE
% boot = 1
% nrandom = 2000
% tail = 'both', 'lower', 'upper'
%
%
%
% Pab... |
1a26f184b44aab46a600cdd4910295864f63a27be3fb11f298902fd948b3bd5e | MATLAB | 3,951 | 92 | function [ titleStr, settings, results ] = labelDatapoints( dataview, settings )
% Allows to manually label datapoints. A labeling variable is created that contains
% labels per datapoint. Three labelling modes are available.
%
% This function can be particularly useful for continual labeling if it... |
ac5557dc58b0bf9f5f240754523d1a9659ca8b798e15d79eb673e2bfac334f19 | MATLAB | 3,952 | 118 | function mesh = move_detector(mesh)
% MOVE_DETECTOR Moves MESH detectors onto the surface of the MESH
%
% [MESH] = MOVE_DETECTOR(MESH) Where MESH is a FEM mesh in the NIRFAST
% format.
%
% See also MYTSEARCHN, MYTSEARCHN_FAST, LOAD_MESH, MOVE_SOURCE.
%
% Part of NIRFAST package.
% H. Dehghani and S. Wojtki... |
075b56d8998d21778e7ec05398efae6e4f1418b91aac70601f2f4279e2928fb4 | MATLAB | 3,953 | 92 |
function [] = visualise_replay_probability_matrix(log_odd,folders,folder_number)
index_pval = intersect(find(log_odd.experiment==folder_number),...
find(log_odd.pvalue >= log10(0.001) & log_odd.pvalue <= log10(0.005)));
index_log_odd = intersect(index_pval,find(...
log_odd.normal_zscored.original>= -1 & ...
... |
7807b9da2a985d0fdff59fb5cf9274352dfecab7e48ad8ad067b839bde8b806f | MATLAB | 3,954 | 127 | if exist('myPool')&&myPool.Connected~=0
disp('Parpool active...')
else
delete(gcp('nocreate'))
myPool=parpool;%
end
GPU_Accelerate=0;
QuaSOR_PixelSize_nm=21
AZBoxSize=50;
CenterCoord=[26,26];
AZBox_XData_px=[0:1:AZBoxSize];
AZBox_XData_px=AZBox_XData_px-AZBoxSize/2;
ProfileCoords=[1:1:AZBoxS... |
0d125aae0381d6ee629348add917d1049baa9c867f71ee427c00eb5d0a49659e | MATLAB | 3,957 | 160 | function [p] = violinPlotsStats2(data,opts)
% significant box of violins
% setup commonly used values
nCond = size(data,2);
nObs = size(data,1);
nPt = 200;
if ~isfield(opts,'yl') || isempty(opts.yl)
yl = [min(data(:)) max(data(:))];
opts.yl = yl+diff(yl).*[-0.1 0.1];
end
if ~isfield(opts,'sigLevel') || isempt... |
fe792bf1c4ed36e0649bcfbab442a5cd40ac783003e2f55529a948a1fa32de08 | MATLAB | 3,958 | 64 | function [ ] = bemf1_graphics_dipole_zoom(strdipolePplus, strdipolePminus, strdipoleCurrent, type)
% Dipole(s) plot with several options
% type = 1 for a planar plot in the coronal plane (XZ)
% type = 2 for a planar plot in the sagittal plane(YZ)
% type = 3 for a planar plot in the transverse plane(XY)
% ... |
096578bf32d18c1c51c46fb5be196eaa785fbf0724bd97a1bf02d534a9bf1bcb | MATLAB | 3,959 | 170 | classdef ParameterVisualization < handle
% Parameters that want a visualization when they are being set should
% subclass this abstract base class
properties
hTile
hAx
lObj
prm
propFullName
is_ma = false;
is2stage = false;
is_ma_net = false;
stage = 1;
end
methods (Abst... |
f31f8f4c9f9ceaac51a891f9924ad05274c7d1e3448350d66b6ed6fa3dab5fbe | MATLAB | 3,959 | 139 | % calc_sig_struct_view
global dNames
% dNames = {'TinC', 'TinI', 'Ramp', 'PC1', 'WhatD', 'WhenD', 'MinC', 'MinI'};
disp(['Finished generating signals until ' dNames{d}])
par = par_sess{1};
fw = ones(1, 50)/50;
tsl = find(par.tsl >= 0 & par.tsl <=0.6);
sig_coh = [];
session = [];
sigSL = [];
sigRL... |
288053bf4cfde4fad46fe527fb5cc60d535fe36802a2da36ed98e61e4fd8abc5 | MATLAB | 3,960 | 116 | function sp_combat_est(input_fn,avg_fn,pkg_dir)
threshold = 10; % threshold based on intensity histgram (specify other values if necessary in your case)
seed = 60000; % initial number of seeds used in superpixel parcellation (specify other values if necessary in your case)
% by defauly, the mask is 121*145*121... |
297f1ed950aa0facf747be206f555fa0ecf5a7a7ec125b31a0535446f7177ec4 | MATLAB | 3,960 | 94 | function [varargout] = rfbevent(varargin)
% RFBEVENT sends a keyboard or mouse event to a VNC server
%
% RFB ("remote frame buffer") is a simple protocol for remote access to
% graphical user interfaces. Because it works at the framebuffer level it
% is applicable to all windowing systems and applications, including X... |
7d43e03e3be808dc454584eeeb707bf0054cfada400ccd30d018ffc6bf10b469 | MATLAB | 3,960 | 107 | function varargout = jbm_skeletonGUI3(varargin)
% JBM_SKELETONGUI3 MATLAB code for jbm_skeletonGUI3.fig
% JBM_SKELETONGUI3, by itself, creates a new JBM_SKELETONGUI3 or raises the existing
% singleton*.
%
% H = JBM_SKELETONGUI3 returns the handle to a new JBM_SKELETONGUI3 or the handle to
% the exis... |
ef611260a16b90953f3c27a26945fed3fee6aec1bdfebc56340a011a5ed4e595 | MATLAB | 3,960 | 109 | % testRandnetCalculator.m
%
% Adapted from simulateNetwork.m. Tests that all randnet_calculators produce
% identical spike results.
%
%% Set up
addpath("../src")
Config = utils.setConfig();
[s,simParam.sim_git_hash_string] = system('git rev-parse HEAD');
myPlotSettings
%% Simulation options
simParam.saveFlag = ... |
5c894c530109d814b4a0ebb761d48b6fa2bba4ba935a7f56a51ff6e010a4d3f4 | MATLAB | 3,962 | 65 | function [ ] = bemf1_graphics_dipole(strdipolePplus, strdipolePminus, strdipoleCurrent, type)
% Dipole(s) plot with several options
% type = 1 for a planar plot in the coronal plane (XZ)
% type = 2 for a planar plot in the sagittal plane(YZ)
% type = 3 for a planar plot in the transverse plane(XY)
% type ... |
b7c3a057da9243740240e200c1697137caefc5a101beafdcdf63d2831baecce9 | MATLAB | 3,962 | 115 | function [basis,gradbasis]=legs(x,dir,n,scale)
% usage: [basis,gradbasis]=legs(x,dir,n,scale)
%
% returns the values and directional derivatives of (n+1)^2-1 basis functions
% constructed from spherical harmonics at locations given in x and, for the
% gradients, for (in general non-normalized) directions given in di... |
5ef8866e0c8a9a2572722edb41ebee2e5b8f4ec4ce0b3a87ef5ad0aecead3d8c | MATLAB | 3,963 | 70 | %% Simulation
% Figure 1B/1C
cd('/data/wheelock/data1/people/Cindy/DIAN'); % where the centrality results were saved
savedir = './postcovbat_individual_signed_complete_Z_/';
load(fullfile(savedir,'Centrality.mat'));
load('Mutation_CDR_bins_NCmatched.mat')
refgroup = bins==4; % NC match 1
meanS = sort(mean(S(refgroup... |
ad6ac2b34e8c7e398005ba5e7be80f85e5701aef787977366276db37bdc2e0a9 | MATLAB | 3,965 | 96 | function [vertices, fs_coords] = CBIG_RF_MNICoord2fsaverageVertex(mni_coords, surf_mesh)
% [vertices, fs_coords] = CBIG_RF_MNICoord2fsaverageVertex(mni_coords, surf_mesh)
%
% This function takes in RAS coordinates in MNI152 space, to convert to the corresponding
% vertex number and coordinates in fsavearge surface spa... |
53868e28a8bfaf09a0596d9c527d2b5c8b821abc1821331476fde6028b7ba443 | MATLAB | 3,970 | 122 | clear glob_avg1 glob_avg2 glob_avg3 glob_avg4 glob_avg5 glob_avg6
[traces_int_on] = extract_variables ('traces',[],resultsPath, 'all', [],conditionType,conditionValue);
[pyr_id,int_id] = extract_variables ('nCells',[],resultsPath, 'pyr', 'int',conditionType,conditionValue);
[si_img] = extract_variables ('si_img',[],re... |
3060f91a3dd6e59e70a44693ecd9517a979596442791f42dc02c1f484e1d5304 | MATLAB | 3,971 | 135 | %% plot clusterperm fig5
% load up combined files with permutations
% cluster to get p-vals
% plot
clear;
%% combine
if ~exist('spatial_neighbors','file'); eeglab nogui; end
timelock = 'readyBS';
file1 = sprintf('RegressPermuteStuff2_%s.mat',timelock);
if ~exist('xTimes','var'); load(file1, 'xTimes','timesToPlot');... |
62ab313e8788c8eed3bc915cff72d7de67a35534956a24a8500c60dcb6333d75 | MATLAB | 3,972 | 75 | function lan_master_gui_spec_comp(LAN_var)
LAN = LAN_var;
comp_ax = figure();
cfg_control(1) = uicontrol('style', 'text', 'units', 'norm', 'position', [.3 .92 .44 .05],...
'string', 'Test : ', 'horizontalalignment', 'right');
cfg_control(2) = uicontrol('style', 'text', 'units', 'norm', 'position', [.75 .92 .2 .05... |
199c4aec24ff0f93e308e958337351abddbbb1e0440732b8935f6504d6b7b2f1 | MATLAB | 3,974 | 103 | function tfrsave(name,tfr,method,sig,t,f,p1,p2,p3,p4,p5);
%TFRSAVE Save the parameters of a time-frequency representation.
% TFRSAVE(NAME,TFR,METHOD,SIG,T,F,P1,P2,P3,P4,P5) saves the
% parameters of a time-frequency representation in the file
% NAME.mat. Two additional parameters are saved : TfrQView and
% TfrView. If... |
5f719690c46995f7c050268c1d9a837d9a4a413b8abb027e581293e919b23671 | MATLAB | 3,975 | 83 | classdef CBIG_preproc_100subjects_clustering_unit_test < matlab.unittest.TestCase
%
% Target project:
% CBIG_fMRI_Preproc2016
%
% Case design:
% CBIG_fMRI_Preproc2016 already have unit tests, here we
% call its "100subjects_clustering" unit test and automatically
% ... |
a816cdcf661a18d70944493ade0f043eaa6574fc1adb7976819c2b21cee79305 | MATLAB | 3,975 | 65 | function [ ] = bemf1_graphics_dipole_thicc(strdipolePplus, strdipolePminus, strdipoleCurrent, type)
% Dipole(s) plot with several options
% type = 1 for a planar plot in the coronal plane (XZ)
% type = 2 for a planar plot in the sagittal plane(YZ)
% type = 3 for a planar plot in the transverse plane(XY)
% ... |
0d1570857d260e91bcb7cea694c306676403404f388f2ecef5efbf30cbb2247d | MATLAB | 3,976 | 159 | function [DJS,b,muy,Vy] = VBA_JensenShannon(mus,Qs,sources,w,base)
% evaluates the Jensen-Shannon divergence (DJS)
% function [DJS,b] = VBA_JensenShannon(mus,Qs,sources,w,base)
% This function evaluates the DJS:
% - either from a set of N-D Gaussian densities, in which case those are
% defined through their first- and ... |
861dff0ea8d626e7a4f901c4e6a416591ca091f4f6138d20388c9da488967b44 | MATLAB | 3,978 | 112 | function [allVec,allTs,allTs_marker,allTs_trigger] = Closed_Loop_ETP(fullCycle)
% Closed-loop algorithm using ETP method to detect peak based on the
% adjusted period
% allVec: Raw EEG (channel*sample)
% allTs: Timestamp of each sample
% allTs_marker: Timestamp of event markers
% allTs_trigger: Timestamp of the s... |
e8590cfe77df45cc9c519a36def4786ace889ae6ec9c06bb28227ac30b063bf6 | MATLAB | 3,981 | 104 | function [version] = hasyokogawa(desired)
% HASYOKOGAWA tests whether the data input toolbox for MEG systems by
% Yokogawa (www.yokogawa.com, designed by KIT/EagleTechnology) is
% installed. Only the newest version of the toolbox is accepted.
%
% Use as
% string = hasyokogawa;
% which returns a string describing th... |
40e79d82c22ba0fc51f6eda8467ef98c7af28ed5be5cbf482723dadd2e1ecf58 | MATLAB | 3,982 | 118 | function [X,Y,mX,sX,mY,sY,It,diff,Xrec,Yrec,T,P,C,W,Wstar]=plsmbtsr2(X,Y,A)
% TSR 2 for PLS-MB (adapted from PLS-ME)
%
% INPUTS:
% X: predictor data matrix with NaN for the missing data
% Y: response data matrix with NaN for the missing data
% A: number of PLS components
%
% OUTPUTS:
% X: original predictor data matri... |
c6be4b0cac6044ca4ee1fea895f29bf4dc5723bdd38df7ba978dbb766f582f6f | MATLAB | 3,984 | 95 | function [hdr] = read_shm_header(filename)
% READ_SHM_HEADER reads the header in real-time from shared memory
% this is a helper function for FT_READ_HEADER
% Copyright (C) 2007-2010, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% ... |
80c0c8ffadd632ad5086190b3a081df85a172b26c37b71340f7163002801ef11 | MATLAB | 3,986 | 169 | function newmatrix = wlAux_mergeTrialsChannels(oldmatrix, comparefunc)
% function newmatrix = wlAux_mergeTrialsChannels(oldmatrix, comparefunc)
%
% This function merges an event matrix's events across trials and channels
% (so that each band has a single trial with a single channel). Duplicate
% events (as detected by... |
dc8ff8584286c94fcddbf0a40bb7b7580b2d85de33478dab95094ec4d9a2fcb6 | MATLAB | 3,986 | 100 |
parfor total_wab_queue = 1:(shifting_key_n.*length(stitching_queue))
[kk, mm] = ind2sub([length(stitching_queue), shifting_key_n], total_wab_queue);
image_1_max = zeros(z_truncate,stitching_queue(kk).res_i);
image_2_max = zeros(z_truncate,stitching_queue(kk).res_i);
img_te... |
29991c1d8dc3a040b5f819b86196d7ad7befaf2d8847d999f55f2f31ec3a8027 | MATLAB | 3,987 | 93 | function varargout = jbm_fiducialFinderGUI3(varargin)
% JBM_FIDUCIALFINDERGUI3 M-file for jbm_fiducialFinderGUI3.fig
% JBM_FIDUCIALFINDERGUI3, by itself, creates a new JBM_FIDUCIALFINDERGUI3 or raises the existing
% singleton*.
%
% H = JBM_FIDUCIALFINDERGUI3 returns the handle to a new JBM_FIDUCIALF... |
c751eb120b6be240c1bdcbe4dfa360120fd0cc9ecdc10f5a89f5bd53218e95da | MATLAB | 3,990 | 136 | function ft_documentationreference(outdir)
% FT_DOCUMENTATIONREFERENCE is a function to maintain the online documentation.
%
% Normal users will not be calling this function, but will rather look at
% http://www.fieldtriptoolbox.org/reference where the output of this function can
% be found.
%
% See also FT_DOCUMENTAT... |
bca4cf2a71fa9e6076b6e162551335a2f8270ff2b662af345659daaec749f94b | MATLAB | 3,991 | 145 | function LAN = fourierp_lan(LAN,cfg)
% v.0.2
% <*LAN)<| version
% cfg.
% chn = numero del canal
% method = 'mt' (multitaper, otherway fourier)
% tapers = [TW K] where TW is the
% time-bandwidth product and K is the number of
% ... |
6dcdbd4889de23503b6e8034d954312a6031c5a05be040558b06aba89d282962 | MATLAB | 3,994 | 126 | function [EI,Pth,Qthth] = lme_mass_RgEI(X,Zcols,W,CBhat,L,phi,ni,GD,invG)
% [EI,Pth,Qthth] = lme_mass_RgEI(X,Zcols,W,CBhat,L,phi,ni,GD,invG)
%
% Expected information matrix of the restricted log-likelihood of a whole
% region.
%
% Input
% X: Ordered design Matrix (according to time for each subject).
% Zcols: Vector w... |
9c47ffd1baf42be90bc8a746e537be0e7856c12c75e4ee01dc9a675b304e64ad | MATLAB | 3,995 | 110 | function I = bfGetPlane(r, iPlane, varargin)
% BFGETPLANE Retrieve the plane data from a reader using Bio-Formats
%
% I = bfGetPlane(r, iPlane) returns a specified plane from the input
% format reader. The index specifying the plane to retrieve should be
% contained between 1 and the number of planes for the ser... |
9b7368ac6b268e94e8ba1999eeee32777c2c1ecd2ba5e3dccefd9249bb788b5c | MATLAB | 3,996 | 134 | function Y = ttm(X,V,varargin)
%TTM Sparse tensor times matrix.
%
% Y = TTM(X,A,N) computes the n-mode product of the sptensor X with
% a dense matrix A; i.e., X x_N A. The integer N specifies the
% dimension (or mode) of X along which A should be multiplied. If
% size(A) = [J,I], then X must have size(X,N) =... |
76ef1afc1f374d25d77890740e57ae46e9a6687ebd3a0baec8365e794c5853ed | MATLAB | 4,000 | 117 | %% Calculating Kappa Coefficient of Agreement
% This example illustrates hows JAGS handles a more complex hierarchical Bayesian model and compares the
% output from JAGS with the output from WinBUGS
%
% The model was taken from the WinBUGS course developed by Michael Lee and Eric-Jan
% Wagenmakers at <http://www.ejwag... |
d09d71f158e3a1fc15c7d3560313136989932eccab08dd9972a827d8ec4d5427 | MATLAB | 4,002 | 126 | close all;
clear all;
clc;
Rii=150; %Ohm*cm logituinal resistance
Rmm=1000; %Ohm*cm2 membrane resistance
a=0.0002; %cm neuron radius
ri=Rii/(pi*a^2); %Ohm/cm
rm=Rmm/(2*pi*a); %Ohm cm
lambda=1*((rm/ri)^0.5) %cm
V0=0.03; %0-1mV 100 intervals potential change per particle
d=[0.25*a 0.5*a 0.75*a a 2*a]; %part... |
3490a6024ef2e6d84ee7bdb8e75063988df12708b1d9a785b9e2143ef76cf64c | MATLAB | 4,003 | 129 | %% Plot Figure 2
function figureOut = PlotFigure2(xhatArr, xArr, params, Rs, figNr)
% Plot Ahat, Bhat and R in upper subplots, pain (xhat) and tissue
% damage (x) in lower subplots, all for different values of R
% ==== Input ===
% perceived pain: xhatArr = [nSim by n by nR-array] of xhat
% ... |
1ebcaaa28c54af15b29e989f44c6d095e4f73a7b351aa18e39213783f747c594 | MATLAB | 4,006 | 131 | function proc_separateDigits(epo, fname, fpath, trigger_name)
%% set max events
max_events = 6000; % all 3 conditions
%% select trials and reset signal to baseline
% D1
[epo1_short, epo1_long] = get_separatedEpoStruct(epo, max_events, trigger_name{1});
% D2
[epo2_short, epo2_long] = get_separatedEpoStruct(epo, max_e... |
6f2452460436c42681cea2cb59b51fef6e5ed03e52dad034420f8ee79c91f899 | MATLAB | 4,006 | 109 | function HumanOdorRep_plot_decoding_results(data_path,...
decoding_results_file, plot_title, plot_name, y_limits, save_path,...
figsize, Err_type)
% function HumanOdorRep_plot_decoding_results(data_path,...
% decoding_results_file, plot_title, plot_name, y_limits, save_path,...
% figsize, Err_type)
%
%... |
cd0a943c7755c8cd970ae880f931b3db9423cc97e44052ccd7fe614831c671ac | MATLAB | 4,006 | 103 | % AUTHORSHIP
% Primary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Secondary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
%
classdef DataSource
m... |
47cfc04a4b7e9c73c83f7a31f6cf8eea71969440a9cc09826d36b064bb4e3e6b | MATLAB | 4,008 | 108 | %-----------------------------------------------------------------------------------------
% Plot firing rate of odor-modulated neurons to liked vs. disliked odors
%
% Kehl et al. 2024 (DOI:XX)
% Single-Neuron Representations of Odors in the Human Brain
% Figure 4d
% Author: Marcel Kehl
% License: MIT License
%-----... |
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