sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e029538a4122fcf2aae07ad981186a91f5446996e6906684a434ee231499d974 | MATLAB | 1,256 | 57 | function [bMax splitVal splitDat] = MaxBimodal(waves, varargin)
showPlot = false;
datType = 'PCA';
for i = 1:2:length(varargin)
switch lower(varargin{i})
case 'showplot'
showPlot = varargin{i+1};
case 'type'
datType = varargin{i+1};
end
end
[wL nChan nSpk] = size(waves)... |
4e9020d490002f8a406bec5bb41f86c4f1b2f905e59fbb2fe3568b666cc8cd34 | MATLAB | 1,257 | 48 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% changes the ylims of a particular channel and fixes it there
function resetYLims(self,src,~)
i... |
c2543beb72464e45823a9d800c0d84d81c7f1416db16b429e38f35e9033ab2d6 | MATLAB | 1,257 | 41 | function V = hogDraw( H, w, fhog )
% Create visualization of hog descriptor.
%
% USAGE
% V = hogDraw( H, [w], [fhog] )
%
% INPUTS
% H - [m n oBin*4] computed hog features
% w - [15] width for each glyph
% fhog - [0] if true draw features returned by fhog
%
% OUTPUTS
% V - [m*w n*w]... |
df45a4be7fab7d7b46705dc8351f4405f18c0cbde84c66c15bca8da14569cd17 | MATLAB | 1,257 | 44 | function B = nonmaxsup( I, M, Vx, Vy, Vz )
% NONMAXSUP Ridge centreline detection by non-maximum suppresion criteria
% INPUT:
% I: Input tomogram, input data must be single or double
% M: Binary (logical format) mask for improve the speed
% Vi: The i coordinate of the major eigenvector
% OUTP... |
7c6a805632d5a34b611b3d19b0c2a8365c308eff7ec4cf16f1e4d121a98c3ea0 | MATLAB | 1,258 | 48 | function LAN = lan_from_ncs(merge)
% Currently assumes one channel and even sampling rate
% It also assumes all Timestamps are sorted in ascending order
% If merge = true, all it does is concatenating all "recording"
[File, Path, iii] = uigetfile({'*.ncs','NCS file'}, 'Open .ncs EEG files','*.ncs', 'MultiSelect', 'off... |
de56fd2f44f9746f04eae58047849d193e7eddec99fe237e4665567e09011773 | MATLAB | 1,258 | 74 | clear;close all;clc;FS=22;
%pkg load image
% Co-ordinates and dispersions for the kernel
y=-81:80;
x=-86:85;
[X,Y]=meshgrid(x,y);
D=2;
t=1:30;
sigma2=4*D*t;
for j=1:length(t);
P0{j}=exp(-(X.^2+Y.^2)/(4*D*t(j)))/(pi*4*D*t(j));
P{j}=exp(-(X.^2+Y.^2)/(4*D*t(j)))/(pi*4*D*t(j))+exp(-((X-10).^2+(Y-10).^2)... |
e785c22e051175d9c4f5dd138f8acaeda7eef179a65e90864babc9dc53e2a4c5 | MATLAB | 1,258 | 30 | function domex_nirfast()
% Routine to compile the NIRFAST CORE mex files in a batch.
% Should only be run on a machine that has mex set up properly.
% It should be called whenever NIRFAST CORE mex C/C++ files are updated.
% A normal user is unlikely to run this script!
% Written by Hamid Dehghani September, 2018
mypwd... |
b710ca6d919b9a34376baf2a3d5911c0233633825cf36ac279348abadc30a871 | MATLAB | 1,259 | 40 | function [Clean2,Clean3] = RemoveArtifacts(A2,A3,win,perMax)
% cedric Wannaz remove artifacts solutions
%
A_temp2 = movmean(A2,win);
d2 = [0; diff( A_temp2 )] ;
Rderv=max(d2)-perMax*max( d2);
isValid_2 = ~logical(cumsum( -sign( d2) .* (abs( d2 ) > Rderv) ));
% ... |
c33b2953a64fdd4f6b25cafe51dd92037f63d7753db603eb47204dfc784b175b | MATLAB | 1,259 | 34 | %{
Copyright (c) 2025 Axion BioSystems, Inc.
Contact: support@axion-biosystems.com
All Rights Reserved
%}
classdef VoltageWaveform < Waveform
methods
function this = VoltageWaveform(aChannel, aStart, aData, aSource, aSubsampleFactor)
this@Waveform(aChannel, aStart, aData, aSource, a... |
6738d87f89696390d0d566e09374aa36c9b878c5fb966aa92bf15224e0599bc3 | MATLAB | 1,260 | 33 | function [ x_cm,y_cm] = transformCoordinates(behavior)
%transformCoordinates converts xy coordinates using max and min input
%values by translating and then scaling (by maze diameter).
% input:
% - dia: maze diameter (assumes symetric environment) in cm
% - x_max: maze x_max in pixels
% - x_min: ... |
ef7b3020e954d815e952b6bda627aeb62c81ae044239a01c2d11b54a9365fed9 | MATLAB | 1,260 | 48 | function [pathname] = uigetdir2(start_path, dialog_title, selections)
% Pick multiple directories and/or files
import javax.swing.JFileChooser;
if nargin == 0 || isempty(start_path) || isnumeric(start_path) % Allow a null argument.
start_path = pwd;
end
jchooser = javaObjectEDT('javax.swing.JFileChooser', start_... |
fda7cab32822890c3f158e9bd69641daa136554193c91e2dd76bd132d20286bc | MATLAB | 1,260 | 43 | datRoot = '/Volumes/LaCie/Farries recordings/';
rat = 'IM1130';
sesList = dir([datRoot rat '/20*']);
sesList = arrayfun(@(x) x.name, sesList, 'UniformOutput', false)
taskList = {'RL', 'Pav'}; % tasks on which to perform burst analysis
for iSes = 2:13
sesDir = [datRoot rat filesep sesList{iSes}]
% create ... |
0e88f3cafc36a2d61af840fe6272b6f2df632e45d065afd6a4723177d0130c89 | MATLAB | 1,261 | 52 | function sagg = aggregateLabelsAddRoi(lObj,isObjDet,sPrmBBox,...
sPrmLossMask,varargin)
[incPartialRows,treatInfPosAsOcc] = myparse(varargin,...
'incPartialRows',true,...
'treatInfPosAsOcc',true ...
);
isgt = lObj.gtIsGTMode;
lbls = lObj.labelsGTaware;
mfafs = lObj.movieFilesAllFullGTaware;
... |
357d418a728a6d5d16f30d1a3d6debe43ad3eaf39601c6b052ee9a63c0f1c107 | MATLAB | 1,261 | 39 | function data = read_data(path)
%% Read data from path based on the extension
% For CSV-like files, the lines of the files will become rows on the matrix.
% Note: Mapper will reduce the matrix over rows, but you could also transpose
% using preprocessing step
%
% **Supported formats:**
... |
357db25ba778219ea86e8262d7cfbc41276fbde16779852e192140ffe64bf3ea | MATLAB | 1,261 | 63 | function c2 = makec2f
% makecolormap.m
% ----> c3(64,3)
% red
% yellow
% black
% cyan
% blue
c2 = zeros(64,3);
% for ii=1:10 % black to grey
% c2(ii,1) = 0.1 + 0.4*ii/10; % red
% c2(ii,2) = 0.1 + 0.4*ii/10; % green
% c2(ii,3) = 0.1 + 0.4*ii/10; % blue
% end
for ii=1:10 % black to grey
c2(ii,1)... |
41b27e4cf38e5bc87e10b4e40fed808a51be697c81bcb5b19b6162478067d531 | MATLAB | 1,261 | 31 | areatxt{1} = 'lip'; areatxt{2} = 'fef';
timevector = -0.05:0.001:0.2;
rgb = [0.1 0.4 0.5; 0.7, 0.4, 0.7];
labels = [{'Singleton distr in RF'}; {'Matched stimuli in RF'}];
for iArea = 1: 2
figtitle = upper(areatxt{iArea});
xlimToPlot = [-0.05 .2];
figure('Name', figtitle , 'NumberTitle', 'off', ... |
98777ef8dcbd46799bfdc195b237fef073e21d10ed3ba1df9cc54d6fd3b33b8d | MATLAB | 1,261 | 49 | function [x,msg] = roundn(x,n)
%ROUNDN Rounds input data at specified power of 10
%
% y = ROUNDN(x) rounds the input data x to the nearest hundredth.
%
% y = ROUNDN(x,n) rounds the input data x at the specified power
% of tens position. For example, n = -2 rounds the input data to
% the 10E-2 (hundredths) positi... |
00a9e22aa2a4eac06168effcef1136c3067e84ff246fe540330e7c3d8d0cf6a9 | MATLAB | 1,262 | 30 | areatxt{1} = 'lip'; areatxt{2} = 'fef';
rgb = [0.1 0.4 0.5; 0.7, 0.4, 0.7];
timevector = -0.05:0.001:0.2;
labels = [{'Singleton distr in RF'}; {'Non-singleton distr in RF'}];
for iArea =1:2
xlimToPlot = [-0.05 .2];
figtitle = upper(areatxt{iArea});
figure('Name', figtitle , 'NumberTitle', 'off',... |
29f75dbdfb75823adb17182a9678992f469a9d58c4556f46c63da8380bc6d19c | MATLAB | 1,262 | 51 | function [logP,bestPhi] = gridL_binomial(y,u,f_fname,g_fname,dim,options)
% nuemrically evaluates the posterior of (binomial) likelihood parameters
[options,u,dim] = VBA_check(y,u,f_fname,g_fname,dim,options);
iQ = VBA_inv(options.priors.SigmaPhi);
gridPhi1 = -3:0.2e-1:3;
gridPhi2 = -0.5:1e-2:0.5;
n1 = length(gridPh... |
eaa9cf8dca29a2400daec4877aae3cb92ecb94d964d071c55e0ae58f827222e0 | MATLAB | 1,262 | 63 | function mergeAll()
allfiles = dir([pwd filesep '*.crab']);
assert(length(allfiles)>0,'No data found. Make sure you have .crab files in this folder')
[~,thisdir]=fileparts(allfiles(1).folder);
savename = [thisdir '_merged.crab'];
if exist(savename) == 2
disp('Already merged, aborting...')
return
end
% first es... |
ee4eba96496636b9280f4446108cd346f8d047467fea12ba4173db29ff564cde | MATLAB | 1,262 | 29 | function bvc_pop = generate_bvc_firing(v)
bvc_pop = cell(v.bvc.N, 1);
FiringSquare = zeros(size(v.env.SquareSpaceY,1),size(v.env.SquareSpaceX,2));
FiringRect = zeros(size(v.env.RectSpaceY,1),size(v.env.RectSpaceX,2));
c = 1;
for d = 1:length(v.bvc.dist_tunings) % for all preferred distances
for a = 1:length(v.bvc... |
fc32e2eb7338178d451be318ce0a04b09492136ed1374536de817b5bc571dd19 | MATLAB | 1,262 | 41 | function [g,dgdx,dgdp] = g_conv0(x,P,u,in)
% this function evaluates a linear convolution of the inputs
% function [gx,dgdx,dgdp] = g_conv0(x,P,u,in)
% This function evaluates the following multiple convolution model:
% y(t) = cst + sum_k sum_tau w(k,tau)*u(k,t-tau)
% where u can be of any dimension (k=1,...,K).
% No... |
1e64976c24a12fc1c51657a21987e456cde78901fd40a0cb5f859b5302500fc9 | MATLAB | 1,263 | 44 | %% Test for CME data on run_main.m
% Setup base path
clear;
basefolder = fileparts(fileparts(mfilename('fullpath')));
codefolder = [basefolder,'/code'];
toolsfolder = [basefolder,'/tests/tools'];
addpath(genpath(codefolder));
addpath(genpath(toolsfolder));
% Load Data
data_root = [basefolder, '/tests/fixtures/cme']... |
49b37e43535a351c725d67b097f5adfc9d8d23f37657f871c8342b89fa5c8e76 | MATLAB | 1,263 | 46 | % Setup base path
% clear;
basefolder = fileparts(fileparts(mfilename('fullpath')));
codefolder = [basefolder,'/code'];
toolsfolder = [basefolder,'/tests/tools'];
addpath(genpath(codefolder));
addpath(genpath(toolsfolder));
% Load Data
data_path = [basefolder, '/tests/fixtures/sub-1_rest1_schaefer400x7_ts.1D'];
dat... |
5d8a277dc14df1831e8faecfa831f6c20fc30504865b80c47caf3c94649b3ad7 | MATLAB | 1,263 | 46 | function [model, loglikHist] = probitRegFit(X, y, varargin)
%% Find MAP estimate (under L2 prior) for binary probit regression using EM
%
%% Inputs
% X(i, :) is i'th case
% y(i) is in {-1, +1}
%
%% Optional named inputs
%
% 'lambda' - value of the L2 regularizer
% 'preproc' - a preprocessor struct
% 'method' - one of... |
793c242482f82a2a96179bf37017c0f144bc33696b9026cba6a7cadf814be7fd | MATLAB | 1,263 | 44 | %% From Schmee and Hahn, "A simple method for regression analysis
% with censored data", technometrics 1979 table 1
% PMTKauthor Hannes Bretschneider
%% Load
% This file is from pmtk3.googlecode.com
setSeed(0);
loadData('schmeeHahn');
y = log10(time);
x = 1000./(temp+273.2);
n = length(y);
uncensored = ~censored;
%%... |
ff6888139961fad61f2096568f9b93495c4e2ba6f2e3899b09154cb4c61a518b | MATLAB | 1,263 | 46 |
function [parameters] = FindBetaChanges(parameters)
MessageToUser('Beta change of ', parameters);
% Inputs
dataset = parameters.dataset; % Output from DatasetPrep
if ~parameters.onPermutations
if strcmp(parameters.comparison_type, 'categorical')
betas = parameters.betas(2, :); %... |
71c9e48c0c6b7e63f2700ff1e7fb2a8b8922a0072f0145cf45d82a5f7666dbcd | MATLAB | 1,264 | 53 | function f = displayTrigger(trigSeq, nBlocks)
%
% function displayTrigger(trigSeq, nBlocks)
%
% Given a trigger sequence, displays the triggers as they should appear in
% the MEG channels
%
% trigSeq is the trigger sequence
% nBlocks (optional) is the number of blocks for plotting = number of subplots
%
% Rachel Denis... |
889aa7bf76c9288413dd6ff6731634bdf8c6754a08f619bf64a08a1bc900ebd5 | MATLAB | 1,264 | 38 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% PCA before withening the EMG signal
% Input:
% signal: row-wise signal
% Output:
% E = full matrix E whose columns are the corresponding eigenvectors
% D = diagonal matrix D of eigenvalues EIG(A) produces a diagonal matrix D of eigenva... |
ba64c4d30ad53ca1f1497a004f157a965852e4fbc3f04ae3f071c84884dc7ad8 | MATLAB | 1,265 | 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 = 100;
OptimalityTole... |
c7c6434055ba60e7b75d25c81d0860804fbdae48801dc3009cff242ae18f1c2e | MATLAB | 1,265 | 39 | % Based on Tyson/MLfw/+tests/FindCenterOutFiles.m
N1=hst.Subject('n1')
today = datestr(now, 'yyyymmdd');
o=N1.getSessions('RANGE',{'20190401',today});
AllOpenLoop=table()
for sesID=1:length(o)
cSes=N1.getSessionObject(o{sesID});
cSes.TaskInfo=cSes.TaskInfo(cSes.TaskInfo.NumTrials>=48 & strcmp(cSes.TaskInf... |
f49f4575eb97973c216a5521d05e4661744f624854617bbeada7dafaa8f679a6 | MATLAB | 1,265 | 42 | % run_paper_tests
% clear the workspace
clear;
% define save directory
save_dir = fullfile('data', 'nov26_paper_test_run_true');
[~, ~, ~] = mkdir(save_dir);
% calculate map6 values
tau_map6_ratio = [10];
default_params = genParams();
map6_vals = default_params.tau_on .* (1./tau_map6_ratio);
% iterate over values o... |
5e8eaf9a03691155cd2e3c57dfbae84713115becf032633d63961d78e064b6b4 | MATLAB | 1,266 | 46 | function [model, output] = mlpGenericFitNetlab(X, y, H, lambda, options, type)
% Train a multi-layer perceptron; needs netlab and minFunc
% X is an N*D matrix of inputs
% y should be a N*K matrix contain reals or 0,1
% type is 'linear', 'logistic' or 'softmax'
% H is the number of hidden nodes (single layer)
% lambda i... |
6e96efe4d8420ac9bf6423c96c79bbd503c4e0960b80e240ac418b25a162a697 | MATLAB | 1,266 | 45 | function C = or(A,B)
%OR Logical OR (|) for sptensors.
%
% See also SPTENSOR.
%
%MATLAB Tensor Toolbox.
%Copyright 2015, Sandia Corporation.
% This is the MATLAB Tensor Toolbox by T. Kolda, B. Bader, and others.
% http://www.sandia.gov/~tgkolda/TensorToolbox.
% Copyright (2015) Sandia Corporation. Under the terms of... |
70db30ea120882673809918dc7ef95007b6f4a07ee1cf25f68bf7669ca036a92 | MATLAB | 1,266 | 29 | function [Params, lh_labels, rh_labels] = CBIG_MSHBM_example_wrapper(out_dir)
% [Params, lh_labels, rh_labels] = CBIG_MSHBM_example_wrapper(out_dir)
%
% This function will run examples sequentially
%
% Written by Ru(by) Kong and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
CBI... |
99fba9e6c55180fde3b59982a61d717c7ca617638e38bd2bc2d2b08b69b9727b | MATLAB | 1,266 | 40 | %%
addpath('../engines/bem_fmm_engine/');
[f1,f2] = uigetfile(fullfile(patient_path,"mesh_data","*.stl"));
FileName = strcat(f2,f1)
TR = stlread(FileName);
P = TR.Points;
t = TR.ConnectivityList;
normals = meshnormals(P, t);
% % If you also want to display normal vectors, uncomment... |
a13fb542547278c4281d923da83c48b91a9508f33502bf7a2dcc5933e1b5644c | MATLAB | 1,266 | 47 | % [3D] Used to convert a stack of T images into a movie.
%
% To display same data statically use montage.
%
% USAGE
% M = makemovies( IS )
%
% INPUTS
% IS - MxNxT or MxNx1xT or MxNx3xT array of movies.
%
% OUTPUTS
% M - resulting movie
%
% EXAMPLE
% load( 'images.mat' );
% M = makemovie(... |
b63d32caa4838de8603926624550491b09c099cd4b7d0acd0832e33ccbe9466e | MATLAB | 1,266 | 52 | function unzipData(dataSource, dest, threshold)
%% Unzip all of the data to another directory, without the zip or svn files
% If threshold is specified, data is split into two by threshold size in
% MB, creating "big" and "small" directories.
%
% dataSource is the location of the pmtkData local copy of the svn
% repos... |
dfac88de8afbe66dc839a39afe25b984230a1a1d26d880bf487d75441c34a88e | MATLAB | 1,266 | 38 | function [tf, tf_lambda, tf_U] = isequal(A,B)
%ISEQUAL True if each datum of two ktensor's are numerically equal.
%
% TF = ISEQUAL(A,B) returns true if each factor matrix and the lambda
% values are equal for A and B. Does not do any scaling or normalization
% first.
%
% [TF, TF_LAMBDA, TF_FACTORS] = ISEQUAL(A,... |
28365d188367e21f0d74e0dfe65768d66656e26cc2f46736d13bda5d95e40d18 | MATLAB | 1,267 | 52 | function mask = voxel2mask(voxels,maskdims)
% :Usage:
% ::
%
% function mask = voxel2mask(voxels, x y z mask dimensions)
%
% :Voxels:
% - 3 column vectors
% - [i j k] = row, column, slice
% - [x y z] in brain if brain is in analyze format
%
% (x is rows, y is columns, z is slices)
%
% ..
% % Tor Wager,... |
54d86e195c6e48acfb7740bfabc7d3ceeb760db1c02e12318098effe9b04335b | MATLAB | 1,267 | 36 | % Copyright Christopher Fricke, University Leipzig Medical Center,
% Neurology 2024
close all;
clear;
datafolder = 'Resting State Connectivity Analysis\results\HCP\datscan_learning\firstlevel';
overwrite = 0;
d1 = dir(fullfile(datafolder,'cond_Rest_RL'));
for j = 3:length(d1)
fprintf('%s',d1(j).name... |
5e9b15c7d7eca5b3b0ab9f54fcbe499abe0980f06484a6b8aaaa77b87d663e80 | MATLAB | 1,267 | 75 | function S = jpattern(Nplus)
global N
global NaP CaL M KCa kCain
global mInst mpInst pInact qInst
global N_mNaF N_hNaF N_mNaP N_hNaP N_Kdr N_M N_qCaL N_zCaL N_KCa N_Cain
S = zeros(Nplus,Nplus);
%% NaF
if mInst == 0
S(N_mNaF,N_mNaF) = 1;
S(1,N_mNaF) = 1;
S(N_mNaF,1) = 1;
end
S(N_hNaF,N_hNaF) = 1;
S(... |
547cfc9b6098de29404c2021b164a772391f54f213f1c380d7c089a8b57deb09 | MATLAB | 1,268 | 51 | %% Image denoising using an mrf and approximate inference
%
%%
%PMTKneedsImageToolbox
% This file is from pmtk3.googlecode.com
if ~libdaiInstalled
fprintf('cannot run %s without libdai; skipping\n', mfilename());
return;
end
requireImageToolbox
setSeed(0);
infEngine = 'libdaibp';
sz = 32;
sigma = 1.5;
data... |
7a007bab26cbd8ce88c1798ec9a95248dae993c3ec028ad17328526a45a9cb0d | MATLAB | 1,268 | 46 | % this function opens the BG figures for a specific cell we are analysing and subtracts the smoothed BG from the
%BG trace, and then takes the images we took the signal and baseline values
%during for getdeltaF, and getsdeltaF for the BG too
function [deltaF_BG, change] = get_deltaF_backgroundiv (path, rec_num, fn, i... |
b2a74ec06f588c7f9010c9d824179fde5ff43c1ad91ff786cfa0030cc0503de0 | MATLAB | 1,268 | 44 | % FixImageSize.m
% Sarah West
% 12/3/21
% Removes the extra pixel in each dimension sometimes captured in
% microManager on 472 rig (no clue how that can happen).
% Input:
% data = the matrix of images you want to adjust. First 2 dimensions must
% be pixels by pixels.
% pixels = the y and x dimensions that you want... |
450ef38597c3d9216d14c1ab95c696875ef306e0d89f77d699a6cda562cbb511 | MATLAB | 1,269 | 20 | function test_AR_GRONe_SA_tracking()
% Test training and tracking on a project using some of AR's flybubble videos.
% That project is a multianimal project.
linux_project_file_path = '/groups/branson/bransonlab/apt/unittest/multitarget_bubble_training_20210523_allGT_AR_MAAPT_grone2_UT_resaved_3_lightly_trained... |
bbc88a9f55437b271722a494afa805ed3edc35f100f6d5c5c0c2484dc0bd3658 | MATLAB | 1,269 | 41 | function [labeler, labelerController] = StartAPT(varargin)
% Launch APT, the Advanced Part Tracker.
% Note that varargin may be coming from the command line in a deployed
% setting.
% Set up the APT path
APT.setpathsmart();
% If only one argument, assume it's a project file to be opened
if isscalar(varargin) ,
ar... |
dfaf2f3ecd98810594b00005c971e3b96c02f2635cf22c253b5c49a474be1ed5 | MATLAB | 1,269 | 35 | function arsEnvelope
x = randn([1,1000000]);
[n, xout] = hist(x, -1.5:0.1:1.5);
n(1) = []; xout(1) = [];
n(end) = []; xout(end) = [];
n = n / max(n);
n = log(n);
figure(1); clf; hold on;
plot(xout, n, '-b', 'LineWidth', 3);
x1 = -0.7;
ind1 = find(xout == x1)... |
146ef199230ef0be0e17f1ab706db1d23f2c4b8b5d2a353f7d86550ab9b5bc50 | MATLAB | 1,270 | 54 | %% Illustrate the robustness of the t-distribution compared to the Gaussian
%
%%
% This file is from pmtk3.googlecode.com
function gaussVsStudentOutlierDemo()
n = 30;
setSeed(8);
data = randn(n,1);
outliers = [8 ; 8.75 ; 9.5];
nn = length(outliers);
nbins = 7;
%%
figure;
plotHist(data,nbins,n);
plotPDFs(data);
printP... |
85b1828ba3af49b425b42c54ad54f52a6d6c9ad3917f6c762a4f5aa9404bf413 | MATLAB | 1,270 | 35 | function cg = cliqueGraphCreate(Tfac, nstates, G)
%% Construct a clique (a.k.a. cluster) graph
% This is used as as the input to many inference algorithms such
% as variable elimination, junction tree, and belief propagation.
%
% Here we assume one potential function per clique as opposed a factor
% graph representat... |
df21132e19f5ce9b8dcfbe0a6c879f7e2a2369cb4d326769d3805b36700d140e | MATLAB | 1,270 | 35 | function [dip] = ft_datatype_dip(dip, varargin)
% FT_DATATYPE_DIP descripts the FieldTrip MATLAB structure for dip data
%
% The dip structure reprents a dipole model that has been fitted to
% ERP or ERF data using a non-linear optimization approach. It is
% usually generated by the FT_DIPOLEFITTING function.
%
% FIXME... |
524ad095883878a348330ca9e2f7cba3eb498837c839e1d36d60b76721e2e5a3 | MATLAB | 1,271 | 45 | function model= deepBelNetFit(X, numhid, y, opts)
% Fit a deep belief network greedily, with no fine tuning
% INPUTS
% X ... X(n,d) is in [0,1]
% numhid ... [h1 h2 .. hn] is num hidden units per layer for n layers
% y ... y(i) in {1..C} for top level labels, or [] if none
% opts ... |
2f5c2a42689e39119320e0c9cc1ec3d442940975e7d2f9b5e3daa935090c2e65 | MATLAB | 1,272 | 41 | function antsResample_series(file_string, fName_contains, new_size, smoothing_sigma, convert2u16, fName_doesnotcontain)
%% User Input
% subIDs = {
% 'P14_JN0013';
% 'P14_JN0014';
% 'P14_JN0016';
% 'P14_JN0017';
% 'P14_JN0125';
% 'P14_XL1402';
% };
% file_string = '/hpc/home/cuk47... |
47b1c2b6fb9df3446541e1cd1061b95a88f8b06c53fe2710232ec9102b1a7d74 | MATLAB | 1,272 | 39 | function improfileOpts = h_getImprofileOpts(handles)
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
if isfield(currentStruct.state, 'lineWidthOpt')
switch currentStruct.state.lineWidthOpt.value
case {1, 5}
improfileOpts.lineWidth = 5;
case ... |
4bc23ee48a96cbfb820a3029144ecdb367ee3230cec7a75e20f608b4f350e585 | MATLAB | 1,272 | 31 | areatxt{1} = 'lip'; areatxt{2} = 'fef';
timevector = -0.05:0.001:0.2;
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 = [-0.05 .2];
figure('Name', figtitle , 'NumberTitl... |
2a38e805287e5ce31b8a7178e7cfa2987f259d178437f8a21da7e5313addc7af | MATLAB | 1,273 | 40 | clear
clc
%{
delete(gcp('nocreate'))
myCluster.NumWorkers = 8;
parpool('local',8)
%}
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
MaxFunctionEvaluations_Data = 10^300;
MaxIterations_Data = 100;
OptimalityTole... |
4decd608ef8b7eb6b610f6ec184055cbbb4ab0564e5567c0c10be823f89fb76f | MATLAB | 1,273 | 37 | function y = applyEnvelope(y, fs, rampDur_ms)
%
% function y = applyEnvelope(y, fs, [rampDur_ms])
%
% ramps a vector y on and off
% fs is the audio sampling frequency
% rampDur_ms is the duration of each ramp in ms (optional: defaults to 10)
%
% Rachel Denison
% March 2014
%
% Cosine ramp section from Elise Piazza
%% ... |
64fd041704f473bcd09a65cc359939e82b6b9929fd417c8ec2e83661f4f079e7 | MATLAB | 1,273 | 26 | % Count number of responses (individual spots) in input array
% (ImageArray_DeltaGFPnMax_Reg2)
% count only responses that are in the chosen region (AllBoutonsRegion)
function [RFNum_AllNMJ, RF_CorrAmp_AllNMJ] = CountResponses2_withAmp(ImageArray_DeltaGFPnMax_Reg2, ImageArray_CorrAmp_norm, AllBoutonsRegion)
Las... |
cc3f758a52b31934c045710e41626fb7dd78556810ff15909cd19762bbc7b97a | MATLAB | 1,273 | 57 | function ignoreEntireFiles(self, src, ~)
if self.verbosity > 9
disp(mfilename)
end
% get all files in this dataset
thisfile = self.file_name;
[~,~,ext]=fileparts(self.file_name);
allfiles = dir([self.path_name filesep '*' ext]);
if any(strfind(src.Text,'BEFORE'))
for i = 1:length(allfiles)
if strcmp(allfiles(... |
eb19f44076583ae75a737d1f9f1333373591b449d9edf8f041a358a3250f29ed | MATLAB | 1,273 | 42 | function [A2, C2] = component_split(A, C, shape, minSize, maxSize)
% [A2, C2] = component_split(A, C, shape, minSize, maxSize)
% Splits ROIs into connected components
if(nargin<5)
maxSize = Inf;
end
if(nargin<4)
minSize = 1;
end
nComponents = size(A,2);... |
fd67d90bb2b6f609ba7217e51ddb621bd505b42e6de582f1b26d7cb1d4f35820 | MATLAB | 1,273 | 42 | function [ f, J, H] = rlogistic4( params, x )
%LOGISTICFUN evaluates modified logistic with params at x
% Detailed explanation goes here
%==========================================================================
%define inputs
x = x(:);
epsilon = params(1);
gamma = params(2);
beta = params(3);
alpha ... |
55275d3531caf09f35fac3d56a72e1aa5c4c70de8532ea04e16561e351abe17a | MATLAB | 1,274 | 39 | % data_verification_controlscript.m
% Sarah West
% 5/28/22
clear all;
% Create the experiment name. This is used to name the output folder.
parameters.experiment_name='Random Motorized Treadmill';
% Output directory name bases
parameters.dir_base='Y:\Sarah\Data\';
parameters.dir_exper=[parameters.dir_base paramete... |
68cb8eb429ff2ecd42312a9f9c6f4ab5cf585691eec0391da254572eff0f95d5 | MATLAB | 1,274 | 44 | function rdelete(f,varargin)
%RDELETE Delete a series of files.
% RDELETE file_name deletes the named files. Wildcards may be used in
% the filename, as with DELETE, but also in the pathnames, which allows
% for deleting a series a files belonging to different directories.
% Brackets ([]) may also be used (se... |
7add91dce10f5ac1923498ae43ddd04a7fb28f8ec5af9b8d0ec308b4541ad10f | MATLAB | 1,274 | 40 | function f = whoDependsOnToolbox(TB, recache)
% Return a list of all user files on the path that recursively depend on a toolbox
%% Input
% TB - the name of a toolbox, e.g. 'stats', 'images', 'optim'
%
% recache - [false] if true, the whoCallsMe cache is updated
%% Output
% f - a list of user mfiles that depe... |
eed83f969a2a1caf5f3ee7745768e80d865779e24d4644e3e15321e4cb31d4f3 | MATLAB | 1,274 | 72 | function [output,e] = VLALE_imp(imp,fs,delay,mu,niter,w)
%%% Adaptive Variable Leaky ALE
%% Inputs:
% imp : ref sig
% delay : delay in samples , also corresponds to the filter order
% (default 4 sec)
% mu : convergance factor, default 0.1
% niter : number of iteration, default 2
%% Outputs :
% output : output signal
%... |
f3aa26892d4011687610611ac25c428c7ea01d9abf79f41cd7a9f91ab8c1650d | MATLAB | 1,274 | 39 | function restrict_and_transform(basepath,varargin)
% restrict_and_transform takes xy coordinates from animal behavior file and
% transforms them to cm.
%
% Assumes general behavior file and *maze_coords.csv is in basepath.
p = inputParser;
p.addParameter('overwrite',false,@islogical)
p.parse(varargin{:});
overwrite ... |
21ff6f1aeca85c71165733a48752b4b4cf5c3ba7d8acd24187f3907f3795c2ce | MATLAB | 1,275 | 56 | %% Settings
resultsPath = 'D:\GAD67 results\Recordings\';
conditionType = 'belt';
conditionValue = 'uncued';
%% DF/F
dff_uncued
clearvars -except resultsPath conditionType conditionValue
%% Corr
corr_uncued
clearvars -except resultsPath conditionType conditionValue
%% Corr vs distance
corrVsDistPooled_uncued
clearv... |
3fb1e3558d7c7de06b2b72b6cab168dd1c73699aa52483575c0a6b85d35851bc | MATLAB | 1,275 | 47 | %% Plot a Dirichlet distribution
% Here we plot the dirichlet distribution as a function of a three
% dimensional alpha vector, which we can do as the distribtion lives on a
% lower dimensional simplex due to the sum to one constraint.
% This file is from pmtk3.googlecode.com
alphas = [10 0.1];
for alpha=alphas(:)... |
8e4b7d8de93685330ab2316dda3ef374217fc33f71497f716bed6715537202ea | MATLAB | 1,275 | 48 | %% Kernel pca demo
% Based on code by Laurens van der Maaten
%{
setSeed(0);
n = 1000;
[X, labels, t] = generate_data('swiss', n, 1);
figure;
plot3(X(:,1), X(:,2), X(:,3), '.')
grid on
%}
% Data from kpcaScholopf
rbf_var = 0.1;
xnum = 4;
ynum = 2;
max_ev = xnum*ynum;
% (extract features from the first <max_ev> Eigenv... |
b964d517686eab6211a7c28664ae940b23261c23a1b6b80e393079d9ac8d601c | MATLAB | 1,275 | 40 | function [saturatedChannelEpochs, saturatedChannels, saturatedTrials] = meg_findSaturatedChannelEpochs(trigData)
cutoff = .10;
nChannels = size(trigData,2);
nTrials = size(trigData,3);
for iTrial = 1:nTrials
saturatedChannelEpochs(:,iTrial) = findClips(squeeze(trigData(:,:,iTrial)));
end
nSaturatedTrialsEachCha... |
140173ca4f244666ef62f758fcf78162886e1b143e7e27bfee998ddd84671bcc | MATLAB | 1,276 | 28 | function y = nanstd(varargin)
%NANSTD Standard deviation, ignoring NaNs.
% Y = NANSTD(X) returns the sample standard deviation of the values in X,
% treating NaNs as missing values. For a vector input, Y is the standard
% deviation of the non-NaN elements of X. For a matrix input, Y is a row
% vector containi... |
ed3b05aad1d193bced38476674a5caa23db8dd6c79760260818970c2f0597db0 | MATLAB | 1,276 | 41 | function S = randskew(n, N)
% Generates random skew symmetric matrices with normal entries.
%
% function S = randskew(n, N)
%
% S is an n-by-n-by-N matrix where each slice S(:, :, i) for i = 1..N is a
% random skew-symmetric matrix with upper triangular entries distributed
% independently following a normal dis... |
2f9d6872dad1eff55d45537388c535832582160486b3782483bf59f0e4dfb1f7 | MATLAB | 1,277 | 55 | % h = PlotInterpColorLine(x,y,colors,alphas,...)
function h = PlotInterpColorLine(x,y,colors,alphas,varargin)
if nargin < 4,
alphas = [];
end
if ischar(alphas),
varargin = [alphas,varargin];
alphas = [];
end
[usepatch,parent,leftovers] = myparse_nocheck(varargin,'usepatch',true,'Parent',[]);
x = x(:);
y = y(:)... |
85eeed4e68b3b1d01c4f4208bd25ca7a1a117961c99c63fa910fae1243fed762 | MATLAB | 1,277 | 51 | %% Simulation example from "a tale of three cousins: lasso, l2boosting, and dantzig"
% Meinshausen, Rocha and Yu
% [y w s X]=three_cousin(options) creates measurements y with weights w and
% selected variables s, and matrix X options has the following fields: n -
% number of measurements d - number of variables rho - c... |
59a7458666eb8d7e9f383df184da6b822100726c0f970692859a624c0d77072e | MATLAB | 1,278 | 43 | function H = calculateSecondPartials(rho,thc,psi, J0, J1, C0, th, N)
[f,kact] = calculateFunctions0([psi thc], th,N);
f0 = f(1);
frho = f(2);
fpsi = f(3);
Nact = length(kact);
W = 1/N*(J1*cos(th(kact) - th(kact)') + J0);
s1 = sum((cos(th(kact) - psi) - cos(thc)).^2);
s2 = (cos(th(kact) - psi) - cos(thc))'*W*(cos(th... |
5c2286ace9c21ca2ef430c5370fbca7a2b79d60b4c8f9beaf1f0ab28f9582ac3 | MATLAB | 1,278 | 54 | function shadowFunction(fname, output, quiet)
% Shadow a function so that when it is called it silently does nothing
% rather than its default behaviour. You can optionally specify a value
% for the shadow to output.
%
% Also accepts a cell array of function names.
%
% **** Call removeShadows() when done ****
%
%% E... |
935aacf32020f29d7830119627eb17eb54f69dd6b33b56b784dbe5a28be2eacf | MATLAB | 1,278 | 30 | % Please first add chronux to Matlab path. http://chronux.org/
datafieled = load('path to EEG mat file');
eeg = datafieled.values;
movingwin=[5 5]; % set the moving window dimensions
params.Fs=Fs; % sampling frequency
params.fpass=[0 40]; % frequencies of interest
params.tapers=[4 9];... |
d477cf3acfcfa8fdcca23d56bf80af01d02709c473cc8363993a23f3e76e389a | MATLAB | 1,278 | 45 | % 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 [a... |
3ae21c03d026fc1030a29af321d9f20877ebf8349225206470fc595c1e058017 | MATLAB | 1,279 | 39 | function X = sptendiag(v,sz)
%SPTENDIAG Creates a sparse tensor with v on the diagonal.
%
% SPTENDIAG(V) creates a sparse tensor with N dimensions, each of
% size N, where N is the number of elements of V. The elements of V
% are placed on the superdiagonal.
%
% SPTENDIAG(V,SZ) is the same as above but creates ... |
5cb156af6c1c346248f8383c167f50c96073dba4d1711967a12ddebde6fb4b09 | MATLAB | 1,279 | 48 | function [yn,en] = RLS(ref,sig,M,lamda)
%% ================== Recursive Least Squares Filter ================ %%
%% === Inputs ===== %%
% ref: Reference signal channel (vector)
% sig: Input signal channel (vector)
% M : Order of the filter
% lambda : learning parameter
%% ==== Outputs ====== %%
% yn : output signal
% ... |
85e7dedb0e90052ca751da33268722d971796606409db067277b86baafe3513f | MATLAB | 1,279 | 50 | function LAN = lan_rt_segmentation(LAN, RT, chan, window)
% Assumes unsegmented signal
%
% chan : for common events, use empty array : [];
% window : window of interest in miliseconds
% example: [-500 1000] (default). Our window of interest begins 500 ms
% before the event and ends 1000 ms after the event.
if LAN.... |
b3a1a80c70d93065b901ebbd7d412e87437f1e43226dbccbc07ef3a08b07529c | MATLAB | 1,279 | 49 | %% NVR Low-Pass filtering 45Hz
% 2017 (edited 2018) by Felix Klotzsche
% 2024 update by Antonin Fourcade
function NVR_09_lpf(cropstyle, mov_cond, path_data, hicutoff)
%% 1.Set Variables
%clc
%clear all
%1.1 Set different paths:
% input paths:
path_data_eeg = [path_data 'EEG/'];
path_in_eeg = [path_data_eeg '08_rejcom... |
51a8db4dde6c8783eab1318a642fc354755e82df07cc7bf7c0345aca83f19968 | MATLAB | 1,280 | 44 | function tests = test_VBA_r2
% Unit Tests for VBA_test_r2
tests = functiontests (localfunctions);
% inputs
function test_inputs (testCase)
shouldFail = @() VBA_r2 (rand);
testCase.verifyError(shouldFail, 'MATLAB:narginchk:notEnoughInputs');
shouldFail = @() VBA_r2 (rand, rand, rand, rand);
testCase.ve... |
66186a19db6131cdabc2049b49dca51d11fb8c43d05b3b490460150cf668d7ef | MATLAB | 1,280 | 45 | % calculate_ICs.m
% Sarah West
% 9/1/21
% Calculates ICs from SVD compressed data. Assumes one compressed dataset
% per mouse.
function []= calculate_ICs_forMSI(mouse_number)
% Parameters.
mouse = num2str(mouse_number);
num_sources = 100;
spatial_component = 'V';
folder=pwd;
%addpa... |
8f6e60fc148d6d97270ebe4036528ff400cc7edc24618ac4b0c09cdf59c80988 | MATLAB | 1,280 | 39 | function fs_write_fstats(fstats,mri,fname,data_type)
% fs_write_fstats(fstats,mri,fname,data_type)
%
% Writes F-statistic or p-value or Freesurfer significance maps to Freesurfer's
% .mgh or .mgz data file. This can be useful for visualization and post-processing
% in Freesurfer.
%
% Input
% fstats: Structure obtai... |
b907e74b07f573e38c5ab1355805a1d10479cd9385f08e2c6f9d5eda642ea934 | MATLAB | 1,280 | 42 | function Y = squeeze(X)
%SQUEEZE Remove singleton dimensions from a tensor.
%
% Y = SQUEEZE(X) returns a tensor Y with the same elements as
% X but with all the singleton dimensions removed. A singleton
% is a dimension such that size(X,dim)==1.
%
% If X has *only* singleton dimensions, then Y is a scalar.
%... |
577a498023f01888359de50417d8a115882d0a73d3f2848f3d9b3f46e34efdab | MATLAB | 1,281 | 51 | function RecreateTspFile(fbasename)
tspdata=load([fbasename '.tsp']);
tspdata = tspdata(:,1);
if size(tspdata,2)>1
warning('tsp has data in it! Are You sure you want to continue?')
% keyboard
end
nFramesTsp = size(tspdata,1);
tspnew = [tspdata -1*ones(size(tspdata,1),6)];
%readerobj = VideoReader([fbasename '... |
846fdf2d590dc400573a3b6a49a10f71f63cb5d0f4fd55f6486f78dec260d201 | MATLAB | 1,281 | 41 | % ApplyPawNormalization.m
% Sarah West
% 8/30/23
% A place to edit paw velocity normalizations with more control (was
% previously doing everything with EvaluateOnData.m)
function [parameters] =ApplyPawNormalization(parameters)
MessageToUser('Applying normalization on ', parameters);
% Inputs
data = par... |
0c12e12e97c7d08188814d64041ab908dc76f0f48a76f4e1321e91adc79b3bcb | MATLAB | 1,282 | 38 | function [WS, DS] = CBIG_AuthorTopicEM_ConvertActToGibbsFormat(act)
% [WS, DS] = CBIG_AuthorTopicEM_ConvertActToGibbsFormat(act)
%
% Convert activation data to appropriate format for the Gibbs sampler
%
% Input:
% - act = array containing activation data across all experiments
% Output:
% - WS and DS = arrays conta... |
5e9f7e0b23f119a8160c95df8b1fe1a1d5a64dd2af9ca2c6ca1bffaa457de622 | MATLAB | 1,282 | 50 | function E = energyLandscape(J1,J0,C0,N,psiSamples,thcSamples)
%% PREFERRED FEATURE SPACE
th = linspace(0,2*pi,N+1); th(end) = [];
%% CONNECTIVITY
W = 1/N*(J0 + J1*cos(th - th'));
%% CALCULATE ENERGY
Erec = NaN(length(thcSamples),length(psiSamples));
Eext = Erec;
Eleak = Erec;
frho = zeros(length(thcSamples), lengt... |
7382c0daf7eb17090dd806591c8ae6ee6fbfe9bd2a3ae1985eb7498f8b97febd | MATLAB | 1,282 | 40 | clc
clear all
close all
% alpha ratio code to produce the PSD figure in the alpha power ratio paper.
% will also need the following:
% raw data files
% redbluegraphs function
%% Figure (red blue graphs)
% create a folder to store data in
if ~isfolder(['alpha_ratio)'])
mkdir(['alpha_ratio']);
end
% Results figur... |
9410c390b5a85b6ee74fb0f09e4bcfe2021245d81b2d99845f1a03438f82671b | MATLAB | 1,282 | 58 | classdef String
% String utils
% comma-separated list of items
methods (Static)
function c = commaSepList2CellStr(s)
c = regexp(s,',','split');
c = strtrim(c);
end
function s = cellstr2CommaSepList(c)
if isempty(c)
s = '';
else
s = [sprintf('%s,',c{... |
25906e6509d966a117598267f0f9f111e59397097b031e0e656108ee6b8a978c | MATLAB | 1,283 | 67 | % [success,errmsg] = csvwrite(filename,struct,[prefix])
% [success,errmsg] = csvwrite(fid,struct,[prefix])
function [success,errmsg] = csvwrite(f,s,prefix)
errmsg = '';
success = false;
isfilename = ischar(f);
if nargin < 2,
errmsg = 'Usage: csvwrite(filename,struct,[prefix]) or csvwrite(fid,struct,[prefix])';
re... |
4033f41fe7107d0b08f1fff5df10a8026841f6531c05bfc9c5ca8b10c013e2b7 | MATLAB | 1,283 | 38 | function [Zica, W, T, mu] = kICA(Z,r)
%
% Syntax: Zica = kICA(Z,r);
% [Zica, W, T, mu] = kICA(Z,r);
%
% Inputs: Z is an d x n matrix containing n samples of d-dimensional
% data
%
% r is the number of independent components to compute
%... |
4ddace4841fd43ca7eb52e3a7bb2bc372e0d7a326c03d584d97a6f8e8f485b3c | MATLAB | 1,283 | 23 | function [Epri, Ppri] = bemf3_inc_field_electric_plain(strdipolePplus, strdipolePminus, strdipolesig, strdipoleCurrent, Points)
% Computes potential and electric field from the dipole distribution via the FMM
% at observation points (Points)
%
% Copyright SNM 2018-2020
% Define source (pole) positions and ... |
650e90010067e95f2dee2c8d80a46213b4a4ffa6fd40401287e4d9135b5a6843 | MATLAB | 1,283 | 39 | %% Gaussian Kernel
%// grab a generic gaussian kernel for 1D filtering of discrete-sampled
% points
%
% INPUTS
% WID (Integer) - Number of states/positions adjacent to mean to estimate
% the kernel over
% STD (Integer) - The standard deviation of the gaussian
% OUTPUT
% kn - Kernel for filtering, ... |
8140d776c53f3098ce1083fc67e19ccf593b79b3aa59b755e8c78ef8a74acb9b | MATLAB | 1,284 | 40 |
% Load data
load(fullfile(saveLoc, 'cosine_sim'), 'cosine_sim')
load(fullfile(saveLoc, 'resCorr_wiTrial'), 'filtW50b', 'resCorr', 'r_conv50b', 'rz_sess');
% load(fullfile(saveLoc, 'cosine_sim_randperm'), 'cosine_sim_randperm') % cosine_sim_randperm(sess, d1, d2, :)
% Plot d
load('E:\Matalb analyses\darkRed... |
97981774c7229f9adc9c014130846b480318d0e17c1662e7dba88256205ba406 | MATLAB | 1,284 | 28 | % Geometric Distortions Correction - Extract volumes to compute topup
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);
... |
cc9bd966fe3ebc623a85b6cac822e5f1933f02ab5fc4be0fc9a6ff2206a87de5 | MATLAB | 1,284 | 42 | function [True] = inside_triangle(P,P1,P2,P3)
% INSIDE_TRIANGLE checks if a 2D point belongs to a 2D triangle usign the
% 'area' criterion.
%
% TRUE = INSIDE_TRIANGLE(P,P1,P2,P3) Tests if point P belongs to the
% triangle spanned on P1, P2 and P3. All points are cartesian
% coordinates.
% P - the point to tes... |
0ead87899a47c0605087f9ae57a05b1ecc8da8cf05f53bedad6718f6d38df6f6 | MATLAB | 1,285 | 54 | function mesh = read_obj_mod(filename)
% read_obj - load a .obj file.
%
% mesh = read_obj(filename);
%
% mesh.v : vertices
% mesh.f : faces
% mesh.vn: vertex normals
%
% Copyright (c) 2008 Gabriel Peyre
%
% modified by Idse Heemskerk 2015, to accomodate obj format as output by
% meshlab, return mesh ... |
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