sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fb37011a0166de6464d19f1e433e0fdb7b7850b708028d3b60bb552457dfe158 | MATLAB | 1,882 | 66 | function [idx] = gen_cvpartition(y,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% gen_cvpartition generates k-fold cross-validation partitions. It returns
% a structure which consists of test and train indices for each
% iteration. Stratified folds can be generated for c... |
180e7a3bccc784e4e58c33610e01382942ddc49bff55023c6d7996ed659afc80 | MATLAB | 1,883 | 75 | function tapas_rdcm_plot_fft(y, region_id)
% tapas_rdcm_plot_fft(y, region_id)
%
% Plots signals in both frequency and time domains.
%
% Input:
% y - data
% region_id - region index
%
% Output:
%
% ----------------------------------------------------------------------
%
% Authors: ... |
b391cf5b072c02934295ddf5794ea8e4ad1aee5bf898f4078ec8947a2cfda31c | MATLAB | 1,883 | 64 | function [CL] = visutil_getCommonRange(erp,ivals,varargin)
%VISUTIL_GETMAXRANGE - get maximum CLim range for several scalp plots of
%data in erp defined by ivals
%
%Synopsis:
% CLIM= visutil_getMaxRange(erp, ivals)
%
%Input:
% erp: eeg data
% ERP: struct of epoched EEG data.
% IVAL: time intervals for which scalp topog... |
376770aa9b3adbefd18f52c4e7e9af1fdb1bd23e3f23c8279ce94f88dc83f5e5 | MATLAB | 1,884 | 58 | function varargout = subsref(this,subs)
% Subscript referencing for GIfTI objects
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
% Guillaume Flandin
% $Id: subsref.m 4136 2010-12-09 22:22:28Z guillaume $
if length(this) > 1 && ~s... |
d2f4bd53272d18d1291038e85ff381366bed7735b8b3758399c61db2ee0174aa | MATLAB | 1,884 | 69 | function [novSC, repSC] = count_spikes(procData, window)
%{
PURPOSE: Counts the number of spikes in a given window using the spikeTimes
in a procData file.
ARGUMENTS:
- procData: (struct)
- window: (array) 1x2 with start and end time for spike count window
(in ms)
OUTPUTS:
- novSC: (struct) fields... |
4633bcf72940d331210f8b7ed110febf5ac4e9340562a6c3c592441dbdb74684 | MATLAB | 1,885 | 82 | % op_lorentzianPeak.m
% Helge Zollner, Johns Hopkins University 2020.
%
% USAGE:
% out=op_lorentzianPeak(n,sw,Bo,centerFreq,lw,ppm0,amp);
%
% DESCRIPTION:
% Generate a noiseless spectrum containing a single lorentzian peak with
% desired parameters (frequency, amplitude, linewidth, etc.).
%
% INPUTS:
% n ... |
64e54ff57d3e871920d5b657f9679045f8d79aa2bda5cf23b837ba5165e43ebb | MATLAB | 1,885 | 63 | function [normval, rbar] = divisiveNorm_fun_2(A, params, rewType)
% Divisive normalization model. Based on model in Khaw et al. 2017 https://doi.org/10.1073/pnas.1715293114
%INPUTS:
% A = .mat file of rat behavior data
% params = 3 parameter values (K, alpha, N)
% rewType = string indicating whether to use log2 ... |
092e92f77fbbcc633960178844ace2532b233085cb7417f8ff28b1b1741646e1 | MATLAB | 1,886 | 57 | %% [RDF] = Wrapper_BFR_LBV(totalField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% totalField : total field map (background + tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial resolution of each dimension ... |
1865b61034c826a088d1856a8519fa6ea1cd206fc4c1dbb9ad29d2e3d821a1e4 | MATLAB | 1,886 | 67 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Unit tests for mutual information functions. Can be run from the repository's
% root folder with runtests('tests/').
%
% Note: these tests are stochastic, so if any of them fails try running them
% again :]
%
% Pedro Mediano and Fernando Rosas, Aug 2020
%
%%%%%%%%%%%%%%%%... |
3ac45ad2b727a0314065754dbd73ffaefcf8c134d823eb4afa13f7aefb3e3a6d | MATLAB | 1,887 | 57 | function output = decodePartialPrxDst(kinematics, neurons, tBins, ROIs, kinematicField, neuralField)
% Fit instantaneous regression of joint angles with proximal and distal
% variances partial'ed
prox = 1:7;
dist = 8:24;
% Format kinematics
outcomes = kinematics([kinematics.locked]);
% Subselect to desired time perio... |
0fb6ec784d3d91178eab59a56dc675eaa407e0d9b8ba498aab6974e5b4192749 | MATLAB | 1,888 | 50 | function out = DN_Quantile(y, p)
% DN_Quantile Quantile of the data vector
%
% Calculates the quantile value at a specified proportion, p, using the
% Statistics Toolbox function, quantile.
%
% ---INPUTS:
% y, the input data vector
% p, the quantile proportion
% ------------------------------------------------------... |
537ea1fca083438e218ce7d658f49fb05375fc51404bc461b4e284b14bb9a3bf | MATLAB | 1,888 | 65 | % clear all
% clc
% close all
% Parameters used in the simulation
gT1=1000:100:3000; % unit: ms; T1 of global brain tissue
fun=@(beta,x)(beta(1).*(1-exp(-x./beta(2)))); % fitting equation
noise=linspace(0,0.05,50); % normalized noise level
niter=1000; % iteration number
% % Using equidis... |
e18f5837c9610c67cc67a25977396cdbd1279f4cc65c81b74139f97420da96c0 | MATLAB | 1,888 | 59 | %test
% Parameters
fs = 1000; % Sampling frequency (Hz)
t = 0:1/fs:10-1/fs; % Time vector (2 seconds duration)
f_low = 10; % Frequency of low-frequency signal (Hz)
f_high = 60; % Frequency of high-frequency signal (Hz)
% Low-frequency signal (10 Hz)
low_freq_signal = 3*sin(2*pi*f_low*t);
% Creat... |
266dfe99b99c2b9d433c97614fd6d5422041a8c2ece4d36527e6054b75c6f933 | MATLAB | 1,889 | 88 | function [example_dir] = tapas_download_example_data(version)
%% Download example data and install it in tapas/examples/.
%
% Input
% version -- String with the desired release. If empty it defaults
% to the current version.
% Output
% example_dir - folder containing example data
% ... |
8ffb50e527690e40c5abfe9e3c566b02d4f4bf645781d86a7c61cc0406ec97cf | MATLAB | 1,889 | 53 | function varargout = update_NBSPredictFigure(weightAdj,labels,wThresh)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% update_NBSPredictFigure returns thresholded adjacency matrix, graph of
% the biggest subgraph, applying weight threshold provided. It also provides
% labes for nodes found... |
fcb585044ca6bf0dad49a3473e7a8a7f7328a3c2b537306ca1cb25f1fdca8e26 | MATLAB | 1,890 | 56 | function [I,windowsize,noverlap,nfft,rate,box,s,fr,ti,audio,p] = CreateFocusSpectrogram(call,handles, make_spectrogram, options, audioReader)
%% Extract call features for CalculateStats and display
if nargin < 3
make_spectrogram = true;
end
if nargin < 4 || isempty(options)
yRange = mean(call.Box(1,4));
x... |
c4a6e3dbf15183da16716aeb8d5962a2d0a8c8343d05a65b8f14e9ea0a0b5d63 | MATLAB | 1,891 | 65 | function tapas_BLT_runStimAnswer(params)
% tapas_BLT_runStimAnswer is showing the stimulus question / answer screen
% Show stimulus question
Screen('DrawTexture', params.screen.window, params.text.imgstimanswer, [], params.screen.fit, 0);
% Flip and log
Screen('Flip', params.screen.window);
tapas_BLT_logEvent('stim_a... |
e0b95afb8ed39e6233f078049a4214f1cf300a3d33566912c07e875c11aa2438 | MATLAB | 1,891 | 76 | function [S, xtr] = RemoveExtension (S, xt)
%
% [Sx, xtr] = RemoveExtension (S, [xt])
%
%Purpose:
% removes the extension xt from the end of S
%
%
%Input Parameters:
% S : string
% xt: string of characters to be removed from the end of S
% xt can be | delimited strings. Trainling blanks will be removed
% ... |
0f5e15fdf8699ccc9a398128d030e905d76ea22f19d4276c63d6f5fdd75ab7c0 | MATLAB | 1,892 | 59 | function [p0,pa_h0] = p0_monte_carlo(DB)
% [p0,pa_h0] = p0_monte_carlo(DB)
%
% needs fields:
% DB.XYZmm % mm coords for each study
% DB.maskV % mask mapped volume
% DB.radius % in voxels
% ----------------------------------------------------
% * get list of all coordinates; select n at random
% vol: row, co... |
a93ac64930a2fdcbd8b5ed781e58ebcbe675a08f5b14d4cdff0ec95083aa8e53 | MATLAB | 1,892 | 55 | function [logp, yhat, res] = tapas_rs_surprise(r, infStates, ptrans)
% Calculates the log-probability of response speed y (in units of ms^-1) according to the surprise
% model introduced in:
%
% Vossel, S.*, Mathys, C.*, Daunizeau, J., Bauer, M., Driver, J., Friston, K. J., and Stephan, K. E.
% (2013). Spatial Attentio... |
3d01c1e59f4ac12b3336842ebf2316b7fc52d9a3d5e569f5251aabe517f4aeba | MATLAB | 1,893 | 48 | function outi = cellstrfind(targ,str)
% Searches cell arrays for a given string occurence. Returns indices of
% cells in which target string found.
%
% Input:
% targ : Cell array to search for string
% str : target string
%
% Output:
% outi : indices of string
%
% 2021 Mark C Nelson, McConnell Brain Ima... |
4f93e3ba3e562ab277e90fbfa99ebb9318ce84f3f05830a416a70cded0338d73 | MATLAB | 1,894 | 70 | function figHandle = plotStimTimes(rawData, stimInfo, Params, figHandle)
if ~exist('figHandle', 'var')
figHandle = figure();
elseif ~isgraphics(figHandle)
figHandle = figure();
end
p = [100 100 600 1500];
set(figHandle, 'Position', p);
stimResamplingHz = 1000;
numTimeSamples = size(rawData, 1);
stimDataD... |
ea262a94aece1330abdd2e27f3a0d1299b81103f19d2ca029e7727744e1e11bf | MATLAB | 1,894 | 59 | %% get_set_bfr_lbv(h,mode,input)
%
% Input
% --------------
% h : structure contains all handles of SEPIA
% mode : 'set' - extract information from GUI to config file
% 'get' - extract information from config file to GUI
% input : if mode is 'set' then input should be fid
% ... |
f8601fba6c504fcb8883e1fdb17937bedd1953fc79d4b2fdd47f411d87f99837 | MATLAB | 1,894 | 74 | function Test_positivedefinite()
% function Test_positivedefinite()
% Test for sympositivedefinite geometry (matrix completion)
%
% This file is part of Manopt: www.manopt.org.
% Original author: Bamdev Mishra, August 29, 2013.
% Contributors:
% Change log:
% Problem
n = 100;
B = randn(n, n);
C = B*B'... |
330e05cb8b8922814bd0e870383841f714ed43f8fb4e74ad8bd4f55cbe546b81 | MATLAB | 1,895 | 59 | % evaluatePSFT - Evaluate goodness of fit of pSFT parameters
% Evaluates the sum of squares error (SSE) between the measured and estimated BOLD.
% 1. Neural response, R, is generated from logGauss()
% 2. R is convolved with the HRF to generate BOLD time series
% 3. Generated BOLD is converted to percent signal ... |
51c497db86214c95a4a5b5043ae0f068f463cb28d1449017bc7c916db52cb650 | MATLAB | 1,895 | 59 | function otherImage = split_complex(this, partitionPair)
% Splits complex data in magnitude/phase or real/imag part as extra dim
% 'complex_mp' or 'complex_ri'
%
% Y = MrImage()
% Y.split_complex(partitionPair)
%
% This is a method of class MrImage.
%
% IN
% partitionPair 'mp' for magnitude/phase (default)
%... |
d8152183843fdc6e21aa7f8b4ed57217587639627546bd29207972003fb16af9 | MATLAB | 1,895 | 83 | % op_gaussianPeak.m
% Jamie Near, McGill University 2014.
%
% USAGE:
% out=op_gaussianPeak(n,sw,Bo,centerFreq,lw,ppm0,amp);
%
% DESCRIPTION:
% Generate a noiseless spectrum containing a single gaussian peak with
% desired parameters (frequency, amplitude, linewidth, etc.).
%
% INPUTS:
% n = Number of poi... |
2f57e15a218ad82107b46a9b60e0e1fd81389cd89160d8b0a03e39b3e48e185b | MATLAB | 1,896 | 64 | function [folderName, folderPath] = ...
tapas_uniqc_find_processing_folder(MrSeriesFolder, processingStep)
% Finds the folder given a processing step in an MrSeries_folder
%
% [folder_name, folder_path] = ...
% tapas_uniqc_find_processing_folder(MrSeries_folder, processing_step)
%
% IN
% MrSeriesFolder p... |
d38a2f68b3212da3b6cc85f9d4790b8c5e0e3cbd36732f8813651266e8611a94 | MATLAB | 1,896 | 73 | function varargout = preprocColorSpace(S, params)
% Usage: [Spreproc, params] = preprocColorSpace(S, params)
%
% A script for switching between color spaces for color stimuli; relies on
% color functions in Matlab's ImageProcessing toolbox.
%
% Created by SN 2009
% Modified/commented by ML 2013.03.21
% Default parame... |
e3348a806c1a7c59223fd120ca9ed8bf65506b65daa5f30b4083f81de0ec2cb5 | MATLAB | 1,896 | 46 | function V=varianceLDC(d,C,Sig,nPart,nVox);
% function V=varianceLDC(d,C,Sig,nPart,nVox);
% returns predicted variance-covariance of a set of LDC distances, which are
% assumed to caluclated using rsa.distanceLDC.
% INPUT:
% d/G: d: (nDist x 1) or (1 x nDist) vector of expected distances,
% the... |
257cc45f852ad7ac57475e57f2da61e0de42069f7194c019a78086122f8fb893 | MATLAB | 1,897 | 48 | function store = incrementcounter(store, countername, increment)
% Increment a manopt counter in a store or storedb.
%
% function store = incrementcounter(store, countername)
% function store = incrementcounter(store, countername, increment)
%
% function incrementcounter(storedb, countername)
% function incrementcount... |
364cd05bc48b2dec331b230535ad1d8e1026de4da5c2b6f7c5f6cf1142ac516e | MATLAB | 1,897 | 73 | function x = gaussFilt1(x, sd, varargin)
% out = gaussFilt1(x, sd)
% out = gaussFilt1(x, sd, dim)
%
% Filter 1 dimension of matrix or n-dimensional array "x" with a Gaussian
% of standard deviation sd. Default dimension to filter is dimension 1. To
% filter a different dimension, supply the dimension as argument "dim"... |
4b38a1ab3fd9397274c46b39cc7b6e02e58dad2ab7149971f55a1a8bdf89d415 | MATLAB | 1,897 | 56 | function pred = nnrpred(Xtest,X,y,K,dist_type,pret_type)
% prediction of new samples with knn regression model
%
% pred = nnrpred(Xtest,X,y,K,dist_type,pret_type)
%
% ------------ INPUT ---------------------------------------------------
% Xtest: dataset to be predicted [n_test x p] n objects, p variables
% X: ... |
510d87f7ecfbe4568c9ae998a59e2b7f2d35faf923f8565b48050abc82a62344 | MATLAB | 1,897 | 51 | function [GMD] = compute_gmd(dataset1)
% computediss: computes dissimilarity for a dataset
%
% inputs: data as 2-D numeric arrays where dimension 1 contains the
% timeframes, dimension 2 contains the channels
%
% outputs: diss and sc as 1-D numeric arrays that contain the
% dissimilarity
%
% Cartool: https://urldefense... |
30ad61d8b7ae64e6b0a05a7d0011b919d37d5008f1ff56f62aa0eed52cfa62cb | MATLAB | 1,898 | 79 | function MEAbatchConvert(ext, dataFolder)
%This function converts MEA bin (binary, RAW) files into mat files in a batch. It will
%attempt to convert all "raw" files in the directory, so make sure they are
%all MEA files or enter an extension to select a few.
%
%To create the RAW file,
%1. open MC_DataTool
%2. F... |
884718384751019b117390dd4bc935c046940549e906a6de0ffced4e5ca3eeca | MATLAB | 1,898 | 86 | function [x,k,res,negCurv] = conjGrad(A,b,optTol,maxIter,verbose,precFunc,precArgs,matrixVectFunc,matrixVectArgs)
% [x,k,res,negCurv] =
% conjGrad(A,b,optTol,maxIter,verbose,precFunc,precArgs,matrixVectFunc,matrixVect
% Args)
% Linear Conjugate Gradient, where optionally we use
% - preconditioner on vector v with ... |
e51b4d13e25e78b96868d4458c608a7434a2234b33f0a0ae0ddcc9d480ec3d9f | MATLAB | 1,898 | 45 | function [pVals, observedEdgeValues, permEdgeValues] = compute_permEdgePvals(observedEdgeValues, permEdgeValues)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% compute_permEdgePvals computes edge-wise permutation p-values.
%
% Arguments:
% observedEdgeValues = Observed edge values as nE... |
f3770804b282ec67b796de437995d6d975db2c5242d27c8642498de1ff57d627 | MATLAB | 1,898 | 57 | function param_complete = bc_checkParameterFields(param)
% JF, Check input structure has all necessary fields + add them with
% default values if not. This is to ensure backcompatibility when any new
% paramaters are introduced. By default, any parameters not already present
% will be set so that the quality metrics ar... |
79c2ffb17754b9220123d3a4e591d9408f10b9d9e0b0243ed9592f71624fa3dc | MATLAB | 1,899 | 66 | function [header] = read_ahdf5_hdr(datafile)
%read header
if nargin ~= 1
ft_error('Wrong number of input arguments');
end
if ~isempty(datafile),
id = h5readatt(datafile, '/', 'id');
if ~strcmp(id, 'AnyWave')
ft_error('This is not the ahf5 format.');
end
ch = h5read(datafile, '/channels');
typ... |
d32cd47ec4980496e35339d9fa58123f82c3b10e9736be2051193be9c92197f0 | MATLAB | 1,899 | 52 | %{
experiment.DisplayGeometry (manual) # geometry
-> experiment.Session
---
monitor_distance : decimal(4,1) # (cm) eye-to-monitor distance
monitor_size : decimal(5,2) # (inches) size diagonal dimension
monitor_aspect : decimal(4,3) ... |
ff82459fbdd08dc934961c3900c78efe548c813fbb9c0d5cfd2247eba340da57 | MATLAB | 1,899 | 69 | function physio = tapas_physio_new_philips(physio)
% Initializes physio-properties for Philips 3T Achieva system with good
% ECG-data
%
% physio = tapas_physio_new_philips(physio)
%
% IN
%
% OUT
%
% EXAMPLE
% tapas_physio_new_philips
%
% See also
% Author: Lars Kasper
% Created: 2014-10-09
% Copyright (C) 2014 T... |
077cd7c92539fd6698884cf1ca0e685b470862d6f6a773821359c67838d56eda | MATLAB | 1,900 | 49 | function [trl] = support_func_trl_determine_overlap(trl,pks)
%% ########################################################################
% - [trl] = support_func_trl_determine_overlap(trl,pks)
% #########################################################################
% [Notes:] Determine overlap of trials with specifi... |
503f770cd91aef349730b212c9867d8059dd1dea883bcd6daa68fd4ad92b30ce | MATLAB | 1,900 | 76 | % op_addphase.m
% Jamie Near, McGill University 2014.
%
% USAGE:
% out=op_addphase(in,ph0,ph1,ppm0,suppressPlot);
%
% DESCRIPTION:
% add zero and first order phase to a spectrum.
%
% INPUTS:
% in = input spectrum in matlab structure format
% ph0 = zero order phase to add (degrees)
% ph1 ... |
6194476fd4102c923d2cc561f6e5e9e8ab460c35240acf9e6b15f055aec378e8 | MATLAB | 1,900 | 39 | function [tapers, eigs]= checkTapers(tapers, N, Fs)
% Helper function to calculate tapers and, if precalculated tapers are supplied,
% to check that they (the precalculated tapers) the same length in time as
% the time series being studied. The length of the time series is specified
% as the second input argument N. T... |
201e1806a9968766f95ed2c263681cb86828310426fd7cad0cdcab0c1ed6e22e | MATLAB | 1,901 | 85 | function bn = get_basename_or_root(fullfilename)
% returns basename from filename (if standard convention P/C.name.seq)
% if not possible try to determine root filename an return this
% written by Niels Focke 05/2009 for new UMG basename code
bn=get_basename(char(fullfilename));
if (strcmp(bn,''))
% if no basename c... |
6cdde2d824832fb330345af63c4e70b6d3a5bd0c31271f579e44bb1d423c17da | MATLAB | 1,901 | 57 | function dimInfo = get_dims(this, iDim)
% Returns reduced dimInfo object just with specified dimensions
%
% This can be used e.g. for simple query of all dimInfo of one (or more)
% dimensions
%
% dimInfo = MrDimInfo()
% dimInfo.get_dims(iDim)
%
% This is a method of class MrDimInfo.
%
% IN
% iDim (vector o... |
8ed9b6f8eeb89e934a42408bd6e359a08c93b3e2c5e6547f619003186ea56724 | MATLAB | 1,901 | 43 | % NEURAL_NET - computes clusters using Matlab Neural Net toolbox.
% Alternative clustering algorithm to KMEANS.
% This is a helper function called from POP_CLUST.
% Copyright (C) 2006 UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution... |
bf8c240905f3582e45dae16715c61a5bb1f88042f68190673d9e104fb24c9e35 | MATLAB | 1,901 | 61 | function [C thetaout] = iem_trialwise(data,angs,angspace,foldvar,exclusion,recenter)
% [C thetaout] = iem_trialwise(data,angs,angspace,foldvar,exclusion,recenter)
nChan = length(angspace);
ntrl = size(data,1);
nsens = size(data,2);
ntime = size(data,3);
if nargin < 5
exclusion = zeros(ntrl,1)... |
ca679b67e0b6e5b0287f40dade8bc50543c33376e8ad4d299b311fb05438805a | MATLAB | 1,901 | 55 | % defineHRF - Define the canonical hemodynamic impulse response function (HRF)
% Boynton & Heeger, 1996 Journal of Neuroscience
%
% Syntax
% HRF = defineHRF()
%
% Output Arguments
% HRF – hemodynamic impulse response function
function HRF = defineHRF()
%% HRF parameters
delta = 2.05; % delay betwee... |
f7c47f8a0ce6a63ee9c1691177d7e6801e1950ef1ce093efe4f0c2282f24f7cc | MATLAB | 1,901 | 64 | function this = load(this, fileName)
% Loads Geometry info from affine image header (.nii/.hdr/.img) or Philips
% (par/rec) or recon6-ImageData (.mat, Geometry-object)
%
% NOTE: .mat-header files (for 4D niftis) are ignored, since the same voxel
% position is assumed in each volume for MrImage
%
% geom = MrAffi... |
0b06f80e7d04ab1f6b1e3bd659c8af78d2333a2409e2e405926540a7977f1a5a | MATLAB | 1,903 | 64 | function [MRSCont] = RunOspreyJob(jobFilePath)
%% [MRSCont] = RunOspreyJob(jobFilePath)
% This function creates performs a full Osprey analysis on the supplied
% job file. This is the foundation for the compiled version of Osprey.
%
% USAGE:
% MRSCont = RunOspreyJob(jobFilePath)
%
% INPUTS:
% jobFi... |
f33c5e403549472998003bd395472963c03d46714cc679bb11da4a6ccba1d00f | MATLAB | 1,903 | 57 | function STAImage = createUnitSTAImage(str)
% STA Image generator for SpikeSorterUnit Object
%
% function STAImages = createUnitSTAImage(str)
%
% Takes a SpikeSorterUnit Object and computes the single Unit STA image
% struct
%
% INPUT:
%
% str - SpikeSorterUnit Object
%
%
% OUTPUT:
%
... |
43ae692a7671e3e17bef246f12271f3c0044b8417339c649d557d9315190c421 | MATLAB | 1,906 | 47 | function [corr_ph, ph_corr_coeff] = ph_k_space(to_phase, all_spec_wat, all_spec_lip, all_spec)
%sob, sob :(
move_spec = find(to_phase);
static_spec = find(to_phase == 0);
% Try all phases from 5 to 355 (avoiding 0 degrees)
%ph = 5:5:355;
ph = 0:180;
move_spec_w_ph_wat = all_spec_wat(find(to_phase),:);
%move_spec_w_ph_... |
aacdf9c9064819a5993d517678e17fe5ae516318b5b7881297cf013fbc5510eb | MATLAB | 1,906 | 48 | function yp = resampleSINC(y,m)
% TIME-DOMAIN SINC INTERPOLATION (RESAMPLING)
%
% Syntax:
% yp = resampleSINC(y, m)
%
% Input:
% y = input signal to be resampled to higher sampling rate (y must be a row vector)
%
% m = resampling factor (e.g., if y is 100 sps and yp will be
% ... |
c7e5a0759abe548174e3b7c985c59b2207cf112cb1e4a5db0ad89a28d8fb0c43 | MATLAB | 1,907 | 61 | function shepardPlot(dissimilarities,disparities,distances,figI,titleString)
% displays a Shepard plot for the result of multidimensional scaling (MDS)
%
% dissimilarities
% the dissimilarities to be depicted
% [disparities]
% the corresponding monotonically transformed distances MDS
% str... |
0c7108aa36f4c0a659d2a1444fa319fffedb5f15ec9fcdf3404ae052319baabb | MATLAB | 1,908 | 50 | % RESHAPE - reshape of memory mapped underlying array
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, Nov. 2008
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with o... |
1823b4de24def387681b4246d3b5290139aa288bc21f0af362f9561f3073b641 | MATLAB | 1,908 | 62 | function ft_flush_header(filename, varargin)
% FT_FLUSH_HEADER removes the header information from the data queue
% this also removes all data associated with the specific header.
%
% Use as
% ft_flush_header(filename, ...)
%
% See also FT_FLUSH_DATA, FT_FLUSH_EVENT
% Copyright (C) 2007-2010 Robert Oostenveld
%
% T... |
2e46b6ec5aca05c1e445d0bc29484b3ff3a416b759e4d85216556d3272042feb | MATLAB | 1,908 | 51 | function data = transientrates2_VRon(data,moving)
% Define the rate of Calcium signals for all cells in all categories of a
% dataset. Store the average rate for each category. Also stores the
% the acquisition rate with each trace in the metadata.
% TODO=Swap this step to the dataset conversion routine.
if n... |
cf00196319f4a750865853f16748e192bc4a1dcd5a7fbd7e78e78f3d32d85b3b | MATLAB | 1,908 | 92 | function save_avw_hdr(img,fname,vtype,vsize)
% SAVE_AVW_HDR(img,fname,vtype,vsize)
%
% Create and save an analyse header file
% for either a 2D or 3D or 4D array (automatically determined).
%
% vtype is 1 character: 'b' unsigned byte, 's' short, 'i' int,
% 'f' float, 'd' double
% vsize is ... |
e8a7e18ea8f5787261e3780b8ae22a9e1ab0a46a526e891c2a308cf4a6bf053b | MATLAB | 1,908 | 53 | function [dimLabels, dimValues, pfx, sfx] = tapas_uniqc_get_dim_labels_from_string(filename)
% parses file name (string) for patterns _<dimLabel><index>...
%
% [dimLabels, dimValues, pfx, sfx] = tapas_uniqc_get_dim_labels_from_string(filename)
%
% IN
% filename string (e.g. file name) of the form
% ... |
ede9d83df9e7dc7ed532fa4f4fe460af69d1675b5e12212fcdbfc15505ce5315 | MATLAB | 1,908 | 67 | function h = cateye(Y, x, col, wid, rawhist)
%
%cateye(Y, x, [c=hsv(size(Y,2)), wid=2, rawhist])
%
% Plots cat eye graph showing how data X are distributed (using kernel density function).
% Each column of Y is a variable to plot a cat eye for.
% The input x defines the x position of each cat eye.
% This can... |
ad6d16990b9ac0eed0092c7d46fa9ab22653e6e5b3c1930c2bcfae8f4c21306e | MATLAB | 1,909 | 63 | function [logp, yhat, res] = tapas_softmax_2beta(r, infStates, ptrans)
% Calculates the log-probability of responses under the softmax model with different betas for
% rewards and punishments
%
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2013-2016... |
ec6588c14ba3ac10999ebdf8c350d84db7f871c083aededa1636662bab3a076a | MATLAB | 1,909 | 36 | %This function plot values in a dot plot style, in which values that are close to each other (according
% to the selected density_distance)are plotted as a single marker.
% The size of the marker increases according to the number of the values that it represents
function [new_vec,size]=compute_density(col,density_di... |
1a8961be7947ff7c8585d7a598e78e96c691e9e9ad09d9fa2f8aa34343325919 | MATLAB | 1,911 | 60 | %% [chi] = Wrapper_QSM_TKD(localField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% localField : local field map (tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial resolution of each dimension of the data, ... |
64c1238c83b9563c65a7a97b53d24117b6f0b3526bc5ead660ecb8db2d73b66f | MATLAB | 1,911 | 63 | function obj = loadobj(s)
% LOADOBJ Initialize a DagNN object from a structure.
% OBJ = LOADOBJ(S) initializes a DagNN objet from the structure
% S. It is the opposite of S = OBJ.SAVEOBJ().
% If S is a string, initializes the DagNN object with data
% from a mat-file S. Otherwise, if S is an instance of `dagnn.... |
83d34fc593ed37dfa14d3fd884a947cb541c081383bd6f951494f8225856f412 | MATLAB | 1,911 | 61 | function [logp, yhat, res] = tapas_logrt_linear_binary_minimal(r, infStates, ptrans)
% Calculates the log-probability of log-reaction times
%
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2016 Christoph Mathys, UZH & ETHZ
%
% This file is part of th... |
88b31cef0d8803b555be49dd0f71f40bdad4debce060da85713a7443e0c0d365 | MATLAB | 1,911 | 45 | function reducedPath = tapas_uniqc_genpath_exclude_subdirs(completePath, pathsExcluded)
% works as genpath, but allows to specify excluded subfolders, which are...
% removed incl. their subfolders from the returned path
%
% reducedPath = tapas_uniqc_genpath_exclude_subdirs(completePath, pathsExcluded)
%
% IN
% com... |
dec013dc1f1b7454eaabe11600079282575042831842b1512a839a3385a86d45 | MATLAB | 1,911 | 69 | function [logp, yhat, res] = tapas_softmax_mu3(r, infStates, ptrans)
% Calculates the log-probability of responses under the softmax model
%
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2017-2019 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is p... |
163e326edf16d8f986925dbddcb5baf4b6ce02dbecf0cf0b19e75ece2083e2c0 | MATLAB | 1,913 | 79 | function [state] = tapas_sem_mixed_init_state(data, model, inference)
%% Generate the structure of the states of the sampler.
%
% Input
%
% Output
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
ptheta = model.graph{1}.htheta.model;
nc = size(model.graph{1}.htheta.T, 2);
ns = size(data, 1);
mu = mod... |
42ba590705cc88e184fb929e8af48dd8929c8e72a5aa73e3587be6c1085f8d6e | MATLAB | 1,913 | 70 | function obj = init_elbo_parts(obj)
N = numel(obj.data);
D = prod(obj.lat);
% ----------
% ELBO parts
% ----------
mu = brca.format.read(obj.mu);
mu0 = brca.format.read(obj.mu0);
dot = obj.dot;
U = obj.U;
M = obj.M;
D = pr... |
7cadbe7611f3199b8c7a34c08f0b8f048081e3c8a643f7ce097a2947f59203a1 | MATLAB | 1,914 | 51 | function data = transientrates2_VRoff(data,moving)
% Define the rate of Calcium signals for all cells in all categories of a
% dataset. Store the average rate for each category. Also stores the
% the acquisition rate with each trace in the metadata.
% TODO=Swap this step to the dataset conversion routine.
if ... |
9c4422e614880f4d723f911cbb58772ed073b95c8f4fd67fefab8a6c64733994 | MATLAB | 1,914 | 40 | function [m,dm] = meanMask(mask, mean, hyp, x)
% MEANMASK Apply a mean function to a subset of the dimensions only.
% [m, dm] = MEANMASK (mask, mean, hyp, x)
%
% The subset of dimensions is specified by the input argument mask, and can
% either be a 0/1 mask, by a boolean mask, or by an index set. The second inpu... |
4aec2e9ad0be40e385102902793d2630ea313e5bed007ebf99e3fe96eee2df6d | MATLAB | 1,915 | 63 | function [data_high,pks_frame,pks] = findActiveFrames(data,pks)
% find high activity frame using a threshold determined from shuffled data
% INPUT:
% data: N-by-T spike matrix
% pks: significant level of frame activity; if left empty ([]), this
% function will determine its value using shuffled data
% O... |
d4516ca51f5a858afbb55b6488f86b84e7abec6c7f80aab7a5357cfd0bee79fc | MATLAB | 1,915 | 42 | function [TS_DataMat,TimeSeries] = FilterLabeledTimeSeries(TS_DataMat,TimeSeries)
%
% ------------------------------------------------------------------------------
% Copyright (C) 2013-2026, Ben D. Fulcher <ben.d.fulcher@gmail.com>,
% <http://www.benfulcher.com>
%
% If you use this code for your research, please cite ... |
e3ef1e2ebe5991a8de494ec92e559526e4557fcd14539038a5131a36a3e87d51 | MATLAB | 1,915 | 90 | function [range_ttlE,range_ttlO]=alignSyncTTL(ttlE,ttlO,fps,varargin)
% align two time trace based off a common syncTTL. Assume that both are at
% the same sampling rate
% [ttlE_cal,ttlO_cal]=alignRecording(ttlE,ttlO,fps)
%% OPTIONS
options.savePath=[];
options.plotFigure=true;
%% UPDATE OPTIONS
if nargin>=4
opti... |
e27022183d3da21be3a95bad22c579ff6e177c3a7c6605be25362bb1a0294395 | MATLAB | 1,916 | 41 | % SPHERROR - CHANCENTER sub function to compute minimum distance
% of Cartesian coordinates to a sphere
%
% Author: Scott Makeig, CNL / Salk Institute, 2000
% Copyright (C) Scott Makeig, CNL / Salk Institute, 2000
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and deta... |
55c4f2e7ff5454c363669c64925ad0efa00a22ea19c31b644054443300aca513 | MATLAB | 1,917 | 59 | function recastMrImageSpm4D = recast_as_MrImageSpm4D(this)
% recasts a 4D MrImage as MrImageSpm4D, enabling usage of SPM interfaces
%
% Y = MrImage()
% Yas4D = Y.recast_as_MrImageSpm4D(inputs)
%
% This is a method of class MrImage.
%
% IN
%
% OUT
%
% EXAMPLE
% recast_as_MrImageSpm4D
%
% See also MrImage
% Auth... |
b4768c8694a1e9c12bbeffd0cdb507896372f19cf7aa2854bcbc83456bed1b85 | MATLAB | 1,917 | 58 | function density_choose_radius(XYZ,radii,niterations)
% function density_choose_radius(XYZ,radii,niterations)
%
% XYZ is 3-column vector of coordinates
% radii is a vector of radius values in mm for density analysis
% niterations is number of iterations per Monte Carlo simulation
%
% This function takes an XYZ list of ... |
257525a68861795e5b1db446fe6e5427af98736dcd256792bf73b8c98629d69c | MATLAB | 1,918 | 73 | function [cl,ptname,pname,pt] = dens_fdr_thresh(fname,histo,varargin)
% [cl,ptname,pname,pt] = dens_fdr_thresh(fname,histo,[doplot],[pthresh],[count data])
%
% fname is name of image to threshold
% histo is vector of Ho (null hypothesis) hvalues of image
% distribution of histo is used to convert image intensity val... |
3b4d20e086bf0905a4f8dea9d07834c2d519254f87877b83ab55b04d2472c72d | MATLAB | 1,918 | 64 | function t_SA = getSignificantActivationTimes(hVals, pVals, xVals, yVals, SA_params)
% t_SA = cell(1,2) of significant activation times
% t_SA{1} = class 1 > class 2
% t_SA{2} = class 1 < class 2
%
% hVals = 1D: lag x 1
% pVals = 1D: lag x 1
% yVals = 2D: lag x clz, where nClz = 2 !!! works only for two classes !!!
%... |
4f089d7b31c4ea9fe324242d1d8edafc5c81cdcad0593ca3277fd1f5641a4e0c | MATLAB | 1,918 | 61 | function test_suite = test_setFixationTargets %#ok<*STOUT>
% (C) Copyright 2021 CPP visual motion localizer developers
try % assignment of 'localfunctions' is necessary in Matlab >= 2016
test_functions = localfunctions(); %#ok<*NASGU>
catch % no problem; early Matlab versions can use initTestSuite f... |
7f62ac4a56e032df760ef79a2ce5950d7859254957260b30357aa41e66ec9913 | MATLAB | 1,918 | 93 | function res = mergePeriod(p1,p2,tBeg,tEnd)
% res = mergePeriod(p1,p2,tBeg,tEnd)
%
% res{1,1} p1 off, p2 off;
% res{1,2} p1 off p2 on;
% res{2,1} p1 on p2 off;
% res{2,2} p1 on p2 on;
if ~exist('tBeg','var') || isempty(tBeg)
tBeg=min([p1(:);p2(:)]);
end
if ~exist('tEnd','var') || isempty(tEnd)
tEnd=max([p1(:)... |
fce2b9c52902b4d7c7dad1625d7ca7b33b33bd57d90f27b73aef0d7c67f5ba4b | MATLAB | 1,918 | 60 | function [trial_idx,idx_flat] = parse_pseudotrials(ops,trial_id)
%make pseudotrials of continuous-time trial sets
%based on trial_idx binary mask, will look at start and
%stop indices in ops and
%
%trial_id: trial numbers to be used/extracted from data
%
%output
%trial_idx: [ns,2] array of ns "pseudotrials" of contino... |
147bb9c6c7fb9ca242cca4d73fd3d9fce346df850f1a3f87cfb4d43012536448 | MATLAB | 1,919 | 44 | % remove all path with a given parent path
% varargin contains a list of path to exclude
% Copyright (C) 2006 Arnaud Delorme
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitt... |
c0c3760f305fe01496d2fd9bd1cad09cf4613a8a61f81a0723e2b9e3de2da464 | MATLAB | 1,919 | 62 | function plot_Cz_ERSP_all_clean(PATH, cfg, fieldNames)
% Plot ERSP and GPM at Cz of the raw data and clean A-E
% with single subject gait ERSPS at data PATHIN named file_in
%
% INPUT
% - sii: vector of subject IDs to be processed
% - PATH: structure with all paths leading to diff processing steps
% generated i... |
411c63c9dce67ac1f99ddef3836bd59645d10268c7c0735ef78f89334966f7d3 | MATLAB | 1,920 | 79 | function [LatOpt, LatMdl, RPE, Kappa] =...
GenerateLatencyData_VanillaAlpha(params, ratTrial,...
gen_arg, noise_arg, noise_params)
%GenerateLatencyData_VanillaAlpha
% params - model parameters
% params(1) = learning rate, in [0, 1]
% params(2) = scale parameter, [0, 1]
% ratTrial - trial data. U... |
e06cd40f56b6b60ec8fb45aad92fbddee38c475326d3e5b15c858ad487fbe38d | MATLAB | 1,920 | 90 | function [summaries, fits] = tapas_sem_display_posterior(posterior, time)
%% Displays a summary of the posterior estimates.
%
% Input
% posterior -- Estimate from the model.
% Output
%
% aponteeduardo@gmail.com
% copyright (C) 2019
%
n = 1;
n = n + 1;
if nargin < n
time = [];
end
% Plot the ... |
cdc58484b02e36d074a725cc967a39f957b01d85fcca4821b0fe338accb7dd80 | MATLAB | 1,921 | 61 | %% get_set_bfr_lbv(h,mode,input)
%
% Input
% --------------
% h : structure contains all handles of SEPIA
% mode : 'set' - extract information from GUI to config file
% 'get' - extract information from config file to GUI
% input : if mode is 'set' then input should be fid
% ... |
38b26c33416ce41ea9615b521adc7273e42e911b1a61064e0398948b6fab039f | MATLAB | 1,924 | 80 | function [LatOpt, LatMdl, RPE, Kappa] =...
GenerateLatencyData_VanillaAlpha(params, ratTrial,...
gen_arg, noise_arg, noise_params)
%GenerateLatencyData_VanillaAlpha
% params - model parameters
% params(1) = learning rate, in [0, 1]
% params(2) = scale parameter, [0, 1]
% ratTrial - trial data. U... |
77efdee17a0e11c3ed2d3145bac291998ef88e538994091366fdeea7af23b581 | MATLAB | 1,924 | 59 | function plot_spectrum_two_groups(fig_num,group_1_2d_data,group_2_2d_data,frequencies,logical_log)
%Plot power spectra with mean and SEM. Group one is plotted in red, group
%two in black.
%find group means and standard errors
mean_group_1 = mean(group_1_2d_data,1);
SE_group_1 = zeros(1,length(mean_group_1));
fo... |
e68fbdc6bb0d4edc91c13cf2192d9349406cf2b7055ceaa584a480301c44f364 | MATLAB | 1,924 | 46 | function varargout = covPP(mode, par, v, hyp, x, varargin)
% Piecewise Polynomial covariance function with compact support, v = 0,1,2,3.
% The covariance functions are 2v times contin. diff'ble and the corresponding
% processes are hence v times mean-square diffble. The covariance function is:
%
% k(x,z) = max(1-r,0)... |
4ea40973c7373c86835b6ac3a4af5577f65fe7734be92981d16facbcdf0db21e | MATLAB | 1,925 | 94 | function [p_ste_avg,iterations] = meta_simulate_nonparamchi2(respfreq,numconds,N)
% [p_ste_avg,iterations] = meta_simulate_nonparamchi2(respfreq,numconds,N)
%
% Perform tests on made-up data to determine what the variability in
% nonparametric chi2 p-value estimates is as a function of the number
% of iterations in the... |
1f7a924d984c2b9cc463e98a0e40699bbbe50c3f4bbf15ba36e608853ee42b13 | MATLAB | 1,926 | 61 | function fear_memerCell_list(basename,varargin)
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
load([basicMetaData.AnalysesName '-icaReacInfo.mat'])
load([basicMetaData.AnalysesName '-okUnit.cellinfo.mat'])
load([basicMetaData.AnalysesNa... |
18162f2b5daa6c1ea3c0e6f70f3186e45d1e7b7da01eac9aefbccc2d00d9dd42 | MATLAB | 1,927 | 50 | function weights = InverseProbWeight(Labels)
% Returns inverse probability weights (used for unbalanced classification problems)
%
%---INPUT:
% Labels: integer class label assigned to each observation
%
%---OUTPUT:
% weights: inverse probability weight assigned to each observation
% -----------------------------------... |
534c72f2ea6aba605742580b4e4047c99906a1f34a3063fa56fdeefc3425bfe6 | MATLAB | 1,927 | 62 | function [hi, lo, mix] = blocks(A, varargin)
%script to calculate wait times in each block type.
%inputs: A struct or S struct (which will then be converted to A struct).
% varargin, if it exists, specifies trial indices to analyze
%output: hi, lo, and mix structs with fields 'wt' and 'er', corresponding to mea... |
5f97382b9906654bac7f5e1d565be6980cdf6dc1cab918061135074fe029ba01 | MATLAB | 1,927 | 86 | function xps = sero_pulseq_SERO_seq2xps(seq)
% function xps = sero_pulseq_SERO_seq2xps(seq)
%
% This function creates an experimental parameter structure from the
% sequence object or sequence file path. Note that the funciton is mainly
% adapted fro the SERO project and may therefore lack general function.
if isstrin... |
b198d1824671693e5f1b5a7353dd674a57d1a1610fdf0e0c6c611faa51933f39 | MATLAB | 1,927 | 68 | function [node,face,elem]=meshacylinder(c0,c1,r,tsize,maxvol,ndiv)
%
% [node,face]=meshacylinder(c0,c1,r,tsize,maxvol,ndiv)
% or
% [node,face,elem]=meshacylinder(c0,c1,r,tsize,maxvol,ndiv)
%
% create the surface and (optionally) tetrahedral mesh of a 3D cylinder
%
% author: Qianqian Fang, <q.fang at neu.edu>
%
% inp... |
dc4dc39bca9fae95e2debf47b1094ac70e38eca068fb136b56065580e4b900bd | MATLAB | 1,927 | 36 |
i = 1;
db = struct();
animal = 'ZZ39'; date = '20220610'; FOV = 1; % will concatenate recordings from the same FOV
session_name = []; % either provide a .isxd file name, or leave blank to read from excel file
crop_x_offset = 100; % in pixels, from the left of the raw image
crop_y_offset = 100; % in pixels, fr... |
efa736601c846a1bd2d06534e589c555c9123c0cf5d31912d39dbd6de95cd2c7 | MATLAB | 1,927 | 59 | function [paths] = addPaths()
% Defines filepaths and adds relevant paths to the MATLAB search path.
% Returns
% -------
% paths (struct) with fields
% main (str): filepath to main.m
% data (str): filepath to data directory
% external (str): filepath to external directories
% outputs (str): filepath to output d... |
7c81571d2471613c7b3629370579dfa6168ec5ca9abba64f429ad880aa57357e | MATLAB | 1,928 | 65 | function [varargout] = read_ctf_shm(varargin)
% READ_CTF_SHM reads metainformation or selected blocks of data from
% shared memory. This function can be used for real-time processing of
% data while it is being acquired.
%
% Use as
% [msgType msgId sampleNumber numSamples numChannels] = read_ctf_shm;
% or
% [data]... |
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