sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b72b436b115a28ca0ef859a73bdabb75f72c3acf4483f8068cec908cb6099d38 | MATLAB | 2,319 | 60 | function [K,dK] = covMask(mask, cov, hyp, x, z)
% Apply a covariance function to a subset of the dimensions only. The subset can
% either be specified by a 0/1 mask by a boolean mask or by an index set.
%
% This function doesn't actually compute very much on its own, it merely does
% some bookkeeping, and calls anothe... |
247d41a537e24c9466a065c4c007302cda5ddb4b59c79fc524d4abf5e246dc3e | MATLAB | 2,320 | 60 | function [] = plotBetas(beta, colors)
% This code reproduces the analyses in the paper
% Urai AE, Braun A, Donner THD (2016) Pupil-linked arousal is driven
% by decision uncertainty and alters serial choice bias.
%
% Permission is hereby granted, free of charge, to any person obtaining a
% copy of this software and ass... |
4b734f4c48efca527cd9d67122f75728d43c1ade3212af323a74d8586996bfa2 | MATLAB | 2,320 | 81 | % clear all
% load rez
% load TT2_1.mat
<<<<<<< HEAD
% [d, timestamps, info] = load_open_ephys_data(sprintf('100_CH1.continuous'));
clear title
k = 1;
Toler = 1;
for icell_1 = [10] % 4 8 19 16 15]
for icell_2 = [22] % 26 22 13 30 21]
=======
clear title
for icell_1 = [7 8 9 23] % 4 8 19 16 15]... |
5c2dcb73932778e0642ec74bf5cbb6bda696909fa78840f8d76c095c70836ef5 | MATLAB | 2,320 | 71 | %% h = sepia_handle_panel_bkgRemoval_SHARP(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global structure contains all new and oth... |
89bed2b3045b04bda6e6ae0bb6daf8156fbb9aac095fba3e0a898b630ebce968 | MATLAB | 2,320 | 57 | function out = DN_Burstiness(y)
% DN_Burstiness Burstiness statistic of a time series
%
% Returns the 'burstiness' statistic from
%
% Goh and Barabasi, 'Burstiness and memory in complex systems' Europhys. Lett.
% 81, 48002 (2008).
%
% ---INPUT:
% y, the input time series
%
% ---OUTPUT:
% The burstiness statistic, B... |
ebb3a7fdf9c7ef396f5665ff52e055051e8af15d72e1657fc2dd3c637dbbf29f | MATLAB | 2,320 | 70 | function [BetasPro, BetasDi] = DARegressRewardHistory_estrous(ratlist,...
Pstruct, Bstruct, auc1, auc2, nback, Stages)
%%% Dopamine AUC as a function of late alpha model-predicted RPE
% Just mixed blocks
% Note: robustfit produces longer taus than regress
%Get DA AUC x reward history betas, split by stage for mixe... |
1f3d3405dcc11225ace88684273b2b587ac2f73fe52f5c28e4f4a3a482090568 | MATLAB | 2,321 | 48 | set_up_paths_and_data_directories;
emo_types = {'2dtrajMDS'};%{'category','binary_valence_arousal', 'valence_arousal'};
emotions_category = {'Anger', 'Anxiety', 'Fear', 'Surprise', 'Guilt', 'Disgust', 'Sad', 'Regard', 'Satisfaction', 'WarmHeartedness', 'Happiness', 'Pride', 'Love'};
emotions_valence_arousal = {'Good',... |
d9f7f81625182f09ffd4b030a97094bbaa8093e20d97def8388ae29d894402b6 | MATLAB | 2,321 | 68 | function [t] = neuralynx_timestamp(filename, num)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for reading a single timestamp of a single channel Neuralynx file
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright (C) 2007, Robe... |
67bea45c6c81143b8190900bdec47041904563c4fa9520edadc15d0dc9090f76 | MATLAB | 2,322 | 79 | function eventout = biosig2fieldtripevent(eventin)
% BIOSIG2FIELDTRIPEVENT converts event information from a biosig hdr into
% fieldtrip events
ft_hastoolbox('BIOSIG', 1);
f = which('sopen.m');
[p,f,e] = fileparts(f);
if contains(p, 'external')
% assume the biosig to be shipped with the fieldtrip distro, in which
... |
8757b872d4a3bc8470921dbbd7425ecc346f98d7e121d386bc3ef1621378dcb1 | MATLAB | 2,323 | 68 | function A = affineBuild(trans, rot, scale, skew)
%
% A = affineBuild(trans, rot, scale, skew)
%
% Builds an affine (orthogonal linear) transformation matrix from the four
% componets: translations, rotations scales and skews.
%
% trans, rot, scale, skew should all be 1x3 vectors specifying x,y,z.
% Rotations are in ra... |
4208ab1d977b2e7cd026220c8580d52794957ca47e8a0978b72bba49953667e5 | MATLAB | 2,324 | 65 | % Main script for separating supragranular and infragranular SANDI fraction-weighted surface intensity maps
% derived from partial-volume laminar sampling
%
% Reference:
% Lee H, ..., Huang S, Communications Biology, 2026
%
% Requirements:
% - FreeSurfer installed and configured
% - FreeSurfer recon-all completed for e... |
e86ed0744730369eea114a3998c451a6a63d65274f914436f696a64225051201 | MATLAB | 2,324 | 84 | function Test_fixedrank_2factors()
% function Test_LR()
% Test for fixedrankLRquotientfactory geometry (low rank matrix completion)
%
% Paper link: http://www.icml-2011.org/papers/350_icmlpaper.pdf
%
% This file is part of Manopt: www.manopt.org.
% Original author: Bamdev Mishra, July 11, 2013.
% Contributors:
% Chang... |
7ad5c2fb1e2cbb79bcf41d4bf488fe8995e504a43a4099072fd624cd5071cdb0 | MATLAB | 2,325 | 81 | function plot_fig1d(datadir)
% Plot time to opt-out by block type for an example rat and all
% rats included in fiber photometry experiment (N = 16).
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to download can
% be found in README.
% load list of photometry rats and example rat
load(fullfile(d... |
bfb5c5dd82d5f7b5c32beadcbdfbec0c66aedb11418014ee1c406e85b0de02e1 | MATLAB | 2,327 | 97 | function [ p, s, levp , c, mtbl, sumtxt ] = nmri_groupcompare( x , l , bf, use_nonparam)
%[ p, s, levp , mtbl] = nmri_groupcompare( x , l , bf)
% Does (somewhat smart) group comparisons using ANOVA and/or Kruskal
% Wallis test (n case Levene is not passed)7*2*2*3
%
%
% p = p value
% s = multiple comparisions tabe
%... |
cec3632f606e28ddab9a6ff074251b4d410191b2370e5c7912298ffb6561056a | MATLAB | 2,327 | 54 | % Example 02 - dual-coded map (contrast estimates and t-statistics) overlaid on an anatomical image
% Define directories
example_dir = fileparts(mfilename('fullpath'));
data_dir = fullfile(example_dir,'data');
sd_dir = fileparts(example_dir);
% Make sure directory containing slice display functions is on path... |
8336941d613c19337dc78c160918249ff06ee544576548a21fa7dc4848b9b08a | MATLAB | 2,328 | 67 | function outputs = targetXTClassifier(data, config)
% Fit models on 100 ms periods nonoverlapping
config.tBins = config.preT:100:config.postT;
nFolds = 1;
nPartitions = 5;
outputs = [];
[outputs.tPtsTrain] = deal(NaN);
[outputs.models] = deal(NaN);
for train = 1:length(config.tBins)-1
% Select a subset of time bi... |
07fcc50be93f758e8ebee3e934e6654928617666f477b49f65129db1ebae7caf | MATLAB | 2,329 | 83 | function [M,dsym,VoxelSize]=track_clust(TrackFile,Lthresh,J)
% This script computes the distance between each pair of streamlines
% Input
% TrackFile: Streamlines file computed in Diffusion Toolkit
% Lthresh: length threshold of streamlines
% J:Number of points resampled for each streamline
% Output
% M: x y z coordin... |
2ec034ddf40b588c211cfd83bacd70aab721c31d6682cf3f4bd31f7c28d922e4 | MATLAB | 2,329 | 75 | function idxs=surfing_afni_node2voxelidxs(Info,vertw,vertp,n,orientation)
% projects nodes on a surface to indices on the surface
%
% IDXS=SURFING_NODE2VOXELIDXS(INFO,WSURF,PSURF,N,ORIENT) takes an afni
% volume with info INFO and inner and outer surfaces WSURF and PSURF in
% orientation ORIENT, and returns N linear in... |
6b0c53266251c2cd30857e7855ac21b7231b300ee737508312140c086ebbd27c | MATLAB | 2,329 | 68 | function shrunk = Shrink(matrix,rowBinSize,columnBinSize)
%Shrink - reduce matrix resolution by shrinking it (akin to pixelating)
% This returns a matrix 'shrunk' which is produced by taking the
% mean of [columnBinSize rowBinSize]-sized blocks within the input matrix.
% From this follows that columnBinSize needs to b... |
7e4a764cc4efa7b385616b8d75e9fb9785c474102fd6d25f66428e6a7942feac | MATLAB | 2,329 | 59 | function filterTags = get_filterTags(varName)
% return filter processing pipeline given the variable name
% typically designed for extraction of trajectory derivatives
% (c) Jiri, Apr17
%% notes
% - 'zeroMean' used until 19.07.2017 (large car game tuning analysis v5)
%% code
varName = lower(varName);
switch varName
... |
c80043d958c728637ab1fc3bb18ee416a09ca2be7143bb2bff100a39071818ff | MATLAB | 2,329 | 55 | function plotTrajectories(kinematics, plotParams)
% Params
xshift = 20; % offset between L and R trials
spoutCol = [0.5, 0.5, 0.5];
% Make figure
fig;
hA = gca;
axis off
hold on;
hA.View = [-22,4];
axis equal
% R spout
line(hA, [plotParams.spoutPose(1,1) plotParams.spoutPose(1,1) plotParams.spoutPose(2,1) plotParams... |
e47e8923bc8a9268d67eaea01e247b44ffde262631b8863c3a8ec2ae43211230 | MATLAB | 2,329 | 93 | function [traj, infStates] = tapas_ph_binary(r, p, varargin)
% Calculates the trajectories of v under the Pearce-Hall learning model
%
% This function can be called in two ways:
%
% (1) tapas_ph_binary(r, p)
%
% where r is the structure generated by tapas_fitModel and p is the parameter vector in native space;
... |
39bd2e9a33bf4bb0bd53787bd969295c40c1db986a6686049af0ce5ebfa86899 | MATLAB | 2,330 | 53 | % bids_geteventfiledsfromfolder() - Scan bids folders recursively to get the list of event fields
% from the first events.tsv file
%
% Usage:
% >> fields = bids_geteventfieldsfromfolder(bidsfolder);
%
% Inputs:
% bidsfolder - a loaded epoched EEG dataset structure.
%
% Outputs:
% ... |
6ef72b5c1133986083d834e2acf49ff6886d49e59fd8e6ecad22f52028a69f0c | MATLAB | 2,331 | 80 | function [data_brain, brain_mask] = bet(varargin)
% This function does a brain segmentation for diffusion data.
% It uses a median filter smoothing of the b0 volumes and an automatic histogram Otsu thresholding.
% Input
% ----------
% data: diffusion data, (X, Y, Z, T).
% bvals: b-values, (X, Y, Z, T).
% median_radiu... |
7e1cb2b53d11c2093b73879df6bb29ea0e12d56d1177d43c7764da57aa554e8b | MATLAB | 2,331 | 74 | function [periods,quiescence] = QuietPeriods(v,velocity,duration,brief)
%QuietPeriods - Find periods of immobility.
%
% Find periods of immobility, i.e. periods of sufficient duration
% where instantaneous linear velocity remains low. Brief movements
% can be ignored.
%
% USAGE
%
% [periods,quiescence... |
a937a29f598ab2b9cc3eaac804ce191005633ef39b7c56842f5a7284542cc6e0 | MATLAB | 2,331 | 82 | function [msize,summary]=h5moviesize(filepath,varargin)
% HELP
% Find a dataset '/mov' in h5 file and reads the matrix size.
% SYNTAX
%[msize,summary]= h5moviesize(filepath) - use 2, etc.
%[msize,summary]= h5moviesize(filepath,'optionName',optionValue,...) - passing options using a 'Name', 'Value' paradigm frequently ... |
77a348822d9e4a5fceac76741957251169a5ccdf1c1d15a36c727c0d52154d2e | MATLAB | 2,332 | 61 | function corrstats=surf_sig_roi_corr(Mean_rapid_slope,indnodes,cifti_scalar,Xlabels,Ylablels,namef,Pathnew)
lhgii=[Pathnew,'\Forgithub\Data\Atlas\Par_500_fslr-lh.gii'];
rhgii=[Pathnew,'\Forgithub\Data\Atlas\Par_500_fslr-rh.gii'];
%cifti_scalar=['D:\Documents\OneDrive - bnu.edu.cn\My_publications\0-8years\atlases_Oct... |
4031dd4f7e4b80baa01b5a65b4efd57b5d2961a324bf9d77aa8ac9375349ccef | MATLAB | 2,333 | 83 | % (C) Copyright 2018 Mohamed Rezk
% (C) Copyright 2020 CPP visual motion localizer developpers
function [onset, duration, dots] = doDotMo(cfg, thisEvent, thisFixation, dots)
% Draws the stimulation of static/moving in 4 directions dots or static
%
% DIRECTIONS
% 0=Right; 90=Up; 180=Left; 270=down
... |
f808de1f4b4edf519f61265692ba2a29206f594c8f10d7682807bc2c809bfd62 | MATLAB | 2,334 | 80 | function [Data,Mask,Data_masked,ROIs,T1map, Params] = load_data(path_Data,path_Mask,Params,varargin)
%load_Data(path_Data 'string', path_Mask 'string', Params 'struct', varargin)
% load different niftis for further processing
% if the ROI path cell is not supplied the function will fill it with the
% mask
%
% path_Da... |
d6ea74addae5e3459e1becb6fb851a8a0514f92889ede5721f9463e49380995e | MATLAB | 2,335 | 78 | function plotGraphMetricsByLag(compiledData, eMeti, eMetl, Params)
%PLOTGRAPHMETRICSBYLAG Summary of this function goes here
% Detailed explanation goes here
AgeDiv = Params.DivNm;
nDIV = length(Params.DivNm);
divColorMap = flipud(viridis(nDIV));
xt = 1:length(Params.FuncConLagval);
if isempty(Params.customGrpOr... |
67353ede228b186849b10999a1259d79529deb3a14f93e430bb3f4deb2cd2afb | MATLAB | 2,336 | 88 | function [out] = smf_rx_detector(hsi_img,tgt_sig,mask,guard_win,bg_win)
%
%function [out] = smf_rx_detector(hsi_img,tgt_sig,mask)
%
% Spectral Matched Filter with RX style local background estimation
%
% inputs:
% hsi_image - n_row x n_col x n_band hyperspectral image
% tgt_sig - target signature (n_band x 1 - column... |
8acc35051e94b5d5d9acea2b63dba029fa5a80db8066cc3e52b520839ad18a09 | MATLAB | 2,336 | 55 | function [homerPruneMat, sciAvgs, pspAvgs, motionWindows, channelsRetained, snrMat, saveFlags] = initialiseMetricsStorage(statsOutLoc, cohort, task, timepoint, sub, params)
% Initialises data structures for storing quality metrics, pruning results,
% and SNR values across subjects. Creates empty matrices sized
% ... |
e122c2a142f262c29e313e68296d950302aafda2ed650e4b4b0c03f817540bce | MATLAB | 2,337 | 58 | function [PWD, F, TW]=CWT_v1(signal, time, labels, setting)
% Function computes power of continuous wavelet transfor (P-CWT) in dB from trials data for
% each channel. Single precision used to save memory and computational time
% INPUTS:
% trials_data... EEG (time X channel X trials)
% trials_time... time vector in sec... |
d07a165608bf694797bd5093e00bc3f7dd58d7b96b5efe5ccca96f795042605d | MATLAB | 2,338 | 48 | function plotFullDepthRaster(expInfoAll, exSubject, exProbes, paramBC, bankSelList, day2pltList, depthWinList, fullProbeScan, colAni)
for pp = 1:numel(exProbes)
fullProbeScanSpec = cellfun(@(x) [exSubject '__' exProbes{pp} '__' x{1}], fullProbeScan, 'uni', 0);
meas = cell(1,numel(fullProbeScan... |
ef68b6abf9f79edfab2ed0ae95f9723f6c633af3191046041b6be66d9457cad8 | MATLAB | 2,338 | 64 | %% [chi] = Wrapper_QSM_myQSM(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... |
58edecdb700173382c5c4994f34779c9ca96901a2261d3f4f5617e6adf41bc04 | MATLAB | 2,339 | 64 | % Recipe_fMRI
% this 'recipe' performs region of interest analysis on fMRI data.
% Cai Wingfield 5-2010, 6-2010, 7-2010, 8-2010
%__________________________________________________________________________
% Copyright (C) 2010 Medical Research Council
%%%%%%%%%%%%%%%%%%%%
%% Initialisation %%
%%%%%%%%%%%%%%%%%%%%
toolb... |
766976f696876dd98ee3f36e21e0e55cf5e7eac70320a0733d5ab7cc4f8e0a1a | MATLAB | 2,340 | 64 |
% cpd2oct - Convert cycles per degree (cpd) to octaves
% Finds the lowest and highest SF in cycles/degree (cpd) that produced half the maximum response.
% Converts cpd to octaves.
%
% Syntax
% [bandwidth_oct, sf_halfmax] = cpd2oct(pSFT, sf)
%
% Input Arguments
% pSFT – pSFT curve
% sf – spati... |
b0b547ac67aa23623403a3bfc532b5a9251aae6c17f8a2ea48b7b8866d8b906a | MATLAB | 2,340 | 61 | function corrstats=surf_sig_roi_corr_cov(Mean_rapid_slope,indnodes,cifti_scalar,Xlabels,Ylablels,namef,Pathnew,Cov)
lhgii=[Pathnew,'\Forgithub\Data\Atlas\Par_500_fslr-lh.gii'];
rhgii=[Pathnew,'\Forgithub\Data\Atlas\Par_500_fslr-rh.gii'];
%cifti_scalar=['D:\Documents\OneDrive - bnu.edu.cn\My_publications\0-8years\atl... |
fc4829847cfe786023fda79cad992e8c4cf1b816ea14fdb0749562dc13da25a3 | MATLAB | 2,340 | 60 | %FHBC_fade
EEG = pop_marks_event_gap(EEG,{'-f'},3000,'in_task_fhbc_fade',[.7 .7 1], ...
'interval','off', ...
'critdir','max', ...
'exact','off', ...
'offsets',[3000 -3000], ...
'ref_point','both', ...
'invert_flags','on');
EEG = pop_marks_event_gap(EEG,{'-f'},3000,'in_leadup_fhbc_fade',[.4 .4 1... |
1161a7d8f22e29edbdcda27623618951b4fb6351ec547f18b8599549554d84a6 | MATLAB | 2,341 | 84 | function [OUT] = indic2classify2(indic,n,nms)
%
% indic is matrix of indicators, studies/contrasts are rows, 1/0 codes yes/no for
% task and regional activation. integers in indic above 1 are treated as
% 1.
%
% first n indicator vars are task codes, rest are regional activation
% nms is cell array of strings, first t... |
46e82ebaa0e3946e342ea801c718c01975e66e10426fb9e7bdfe69669d430826 | MATLAB | 2,342 | 76 | function s = db_select(tablename, fields, sel)
% DB_SELECT selects data from a database table and converts it into a
% Matlab structure.Each of the fields in the database table will be
% represented as field in the strucure.
%
% Use as
% s = db_select(tablename, fields)
% s = db_select(tablename, fields, num)
%
% ... |
667b334ab7b45669ffca81e96fc6a40e4bba21929c117b461addfd6acf7858bd | MATLAB | 2,342 | 82 | classdef nnbnorm < nntest
properties (TestParameter)
rows = {2 8 13}
cols = {2 8 17}
numDims = {1 3 4}
batchSize = {2 7}
end
methods (Test)
function regression(test, rows,cols, numDims, batchSize)
r = rows ;
c = cols ;
nd = numDims ;
bs = batchSize ;
x = test.rand... |
22b8615d1766b710473275b39bbce5f85bf90feff2814e33a6d863090a1ed847 | MATLAB | 2,343 | 91 | function phiBC = cellBoundary2D(phi, BC)
% function phiBC = cellBoundary2D(MeshStructure, BC, phi)
% It creates the matrix of coefficient based on the BC structure provided
% by the user. It also generates the right hand side vector of the linear
% system of equations
%
% SYNOPSIS:
% phiBC = cellBoundary2D(MeshStruct... |
55c9f3d86d0eaefd1c45ff3eed7f394b899ab7077abab9afe31f995e5ae80ad2 | MATLAB | 2,343 | 57 | function using_gpu()
% Manopt example on how to use GPU with manifold factories that allow it.
%
% We are still working on this feature, and so far only few factories have
% been adapted to work on GPU. But the adaptations are rather easy. If
% there is a manifold you'd like to use on GPU, let us know via the forum
% o... |
8d5f3e1acc11e5893bb5a15145b6680d900e82c5a3810112f24f7013754735cb | MATLAB | 2,343 | 70 | function [cfg] = loadAudioFiles(cfg)
%% This function loads the pre-recorded audiofiles.
%R=Right, L=Left, U=Up, D=Down
%T=Target
%% Load the sounds
% static Stimuli
fileName = fullfile('input', 'Static', 'one25.wav');
[soundData.S1, freq1] = audioread(fileName);
soundData.S1 = soundData.S1';
... |
ad91901548a482abb64b13f582ec69a3f8f210301ae094304c4118f20b288b74 | MATLAB | 2,343 | 58 | % For compilation under Windows/Octave you need to install the package
% octavex.x-headers.
% Under Linux/Octave, compilation works out of the box.
%
% There is a big variety of platforms running Matlab/Octave around and the
% script is tested for:
%
% Linux 32bit / Matlab R2008b, 7.7
% Linux 64bit / Matlab R... |
bfc3bc858cd7c6bb6e2966d3f3f00d721efa8540313292b6872d1ca30f64a814 | MATLAB | 2,343 | 83 | function autoqc_nsd_grand(subjix,glmdirname)
% setup
nsdsetup;
% get all scan directories
alldirs0 = [nsdscreeningfun2(subjix) nsdallsessfun2(subjix)];
%%%%% get mean and valid from every session
% init
meanvols = single([]);
validvols = single([]);
% loop over directories
for p=1:length(alldirs0)
% calc
ppd... |
ea68275904dafb2f6759c8d1862160cc2c3a73f530426aa359707bdc038d57f8 | MATLAB | 2,343 | 56 | function [Data_Filtered] = TMSIdealFilter(Data, SamplePeriod, Band)
% FORMAT [Data_Filtered] = y_IdealFilter(Data, SamplePeriod, Band)
% Input:
% Data - 2D data matrix (nDimTimePoints * nTimeSeries)
% SamplePeriod - Sample period, i.e., 1/sample frequency. E.g., TR
% Band - The frequency... |
38ae2de147f7587b6f5c0bec3af4b0ed35d6ec75eaa5d63f8da4ff1eb7e4f3f1 | MATLAB | 2,345 | 96 | function imdb = attach_proposals(imdb,boxes,fgThresh,bgThreshHi,bgThreshLo)
%
% Copyright (C) 2016 Hakan Bilen.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
% gtboxes = imdb.images.gtboxes;
% imdb.images = rmfield(... |
51385ebaafdebc84994cc1e19ab783947bfb4d85269271ed82d17f403fc093ca | MATLAB | 2,345 | 66 | %{
# produces synchronization information between two-photon scanning and visual stimulus
-> preprocess.Prepare
---
-> vis.Session
first_trial : int # first trial index from psy.Trial overlapping recording
last_trial : int # last trial... |
5ea811b8548837d102c2ac2b41564a46816b0498ac823e19d0bcd77e92405fda | MATLAB | 2,345 | 96 | function Test_MN_completion()
% Test for fixedrankMNquotientfactory geometry (low rank matrix completion)
%
% Paper link: http://arxiv.org/abs/1209.0068
%
% This file is part of Manopt: www.manopt.org.
% Original author: Bamdev Mishra, July 11, 2013.
% Contributors:
% Change log:
clear all; close all; clc;
% ... |
961a1b9ec1a495ea1ba1e99ed37de1b304b6ba3a24e27566bceb6ef5c75402fd | MATLAB | 2,346 | 80 | function [high, low, err_high, err_low, deltas, T, tstartbl, tendbl, tzero]...
= hiloRew_stages(bstruct, pstruct, window, thirdrew_arg,...
Stages)
%%plot response aligned to offer cue in high versus low blocks, separated by
%%input:
%ratlist = which rats to run through on at a time
%pstruct = align... |
a4f742c86ceebc65917a79db9674b977ce0c46b7d1447b6e2faa2bd4880d1d4c | MATLAB | 2,346 | 84 | function [err,contrfile] = ContrastTest (N_runs, polort, N_basis, Task, N_tasks, N_contr, El, N_base)
%
% [err,] = ContrastTest ()
%
%Purpose:
% Construct the contrast test matrix used in -glt option of 3dDeconvolve.
%
%
%Input Parameters:
%
%
%
%Output Parameters:
% err : 0 No Problem
% : 1 Problems
%
%
%... |
ae2e3c3b67a26ddae2f4aa27c5b7b93417a31e4831907e93b655e69d8cd2622c | MATLAB | 2,346 | 55 | function mouseHandlerHeatMap(src, evt)
% function mouseHandlerHeatMap(src, evt)
%
% Is triggered when the mouse is clicked in the HeatMap figure. Reads
% the current mouse position, translates it to a sensor ID and visualizes
% (if matches unit in sta data) its neighborhood and its activity
%SET PARAMETERS
uni... |
5744514198764731b7272cf953d4461ca3531b308e07ca6007ff966ad096b493 | MATLAB | 2,347 | 69 | function outargs = hlp_resolve(x,default,context)
% Look up a symbol from the current hlp_scope scope.
% Data = hlp_resolve(Symbol,Default,Context)
%
% More precisely, perform a lookup for a symbol in the current (dynamic) scope formed by (possibly
% nested) hlp_scope(s). Returns a cell array of all the values associat... |
9fa9093689fdd3ad62eeebe4b663f77d8fb3527f2c352c45ba8ea410e5953362 | MATLAB | 2,347 | 69 | function [distance_cos,distance_difference,pred_cond,distances] = ...
mahal_func_theta_kfold(data,conditions,theta,n_folds)
%%
train_partitions = cvpartition(conditions,'KFold',n_folds); % split data n times using Kfold
distances=nan(length(unique(conditions)),size(data,1),size(data,3)); % prepare for ou... |
2801c9fb658385ef0dda4d6da52ed033943b900c75dd05f6d5f9322f4a4c6e03 | MATLAB | 2,348 | 62 | function [chi2,actual,expected,colnames] = simplechi2(studycount,totalstudycount)
% function [chi2,colnames] = computechi2(studycount,totalstudycount)
%
% 07.22.01 by Tor Wager
%
% computes an a vs b chi2, where #nos is total - #yesses
% can generalize to other things, L/R for example, but must give L or R and total
%
... |
9b390e48d048371f1dbe91d4cf2cfc08089cce38d71c9ab89b34e641ea7be341 | MATLAB | 2,348 | 59 | clear all %#ok<CLALL> % Clear all variables from the workspace
close all % Close all open figure windows
%% INSERT YOUR RECEIVER IPv4 ADDRESS HERE
IPv4 = '127.0.0.1';
%% RUN THE REST
% Define Image Dimensions and Preallocate Storage
xpixels = 512; % Image height (number of rows)
ypixels = 796; ... |
c10432834aa224c9155e37b3d6184a85187bea7123874bdd2e98442ef0fd1b52 | MATLAB | 2,349 | 59 | function X = filtfilt_fast(varargin)
% Like filtfilt(), but faster when filter and signal are long (and A=1).
% Y = filtfilt_fast(B,A,X)
%
% Uses FFT convolution (needs fftfilt). The function is faster than filter when approx.
% length(B)>256 and size(X,Dim)>1024, otherwise slower (due size-testing overhead).
%
% Note:... |
40f5e73c43586eedf7c27ee730c44b31821e93eefe29a8159d7e81bca9b63e21 | MATLAB | 2,350 | 79 | clear
clc
close all
tic;
load input
load output
data=[input,output];
Particles_no=20; % Number of particles
Max_iteration=100; % Maximum number of iterations
% number of hidden layer, number of neuron layer1, number of neuron layer1, trasfer function 1, trasfer function 2, trasfer function 3, learning ra... |
cb74628f91e413fcc745aa6848152a74a9ac522296273fac2909e83df9a930ae | MATLAB | 2,351 | 90 | function result = FuzSam(proj,result,param)
%rand('seed',120)
%Adapt the data
P = proj.P; %P projected data or dimension
d = result.data.d; %d distances
f = result.data.f; %f partition matrix
m = param.m; %m fuzzy exponent
maxstep = param.max;
alpha = param.alpha;
% compute data dimens... |
ff636e6ca08d04f8a6f1fc22224656da2c0ffbe79be7bfd9bda9c52f54c11d28 | MATLAB | 2,351 | 72 | function [ rsq,hd,p_fit,s,y_fit,delta_fit,p,r ] = plot_fit_linear( x,y,zz,color,varargin )
n = 1;
linestyle = '-'; linewidth = 1;
if numel(x)>2
ci_type = 'function';
showError = 0;
coor_type = 'Pearson';
for v = 1:numel(varargin)
if strcmpi(varargin{v},'degree')
n = varargin{v+1};
elseif strcmpi... |
558a1935a0589a0093435edf3b12f2c90d919d7edc794e41705279b5cd77320f | MATLAB | 2,352 | 90 | function [traj, infStates] = tapas_kf(r, p, varargin)
% The scalar Kalman filter
%
% This function can be called in two ways:
%
% (1) tapas_kf(r, p)
%
% where r is the structure generated by tapas_fitModel and p is the parameter vector in native space;
%
% (2) tapas_kf(r, ptrans, 'trans')
%
% where r is th... |
ef2e8aad172c3495112b0f8dcb99da4c2adfb7912aecc6e8704b13ae1fad5a1c | MATLAB | 2,352 | 71 | function map = tab10(N)
% Qualitative colormap from MatPlotLib, for plots using the line ColorOrder.
% In MatPlotLib 2 it is named VEGA10, for MatPlotLib 3 was renamed TAB10.
%
% Copyright (c) 2017-2020 Stephen Cobeldick
%
%%% Syntax:
% map = tab10
% map = tab10(N)
%
% For MatPlotLib 2.0 improved colormaps were creat... |
df7de8dfc147e28521f15ce9935ad7676e2e916b6ddddae8c9597bb89fa0b16a | MATLAB | 2,353 | 81 | function [val, remaining] = keyval(key, varargin)
% KEYVAL returns the value that corresponds to the requested key in a
% key-value pair list of variable input arguments
%
% Use as
% [val] = keyval(key, varargin)
%
% See also VARARGIN
% Undocumented option
% [val] = keyval(key, varargin, default)
% Copyright (C)... |
c08120c12a0c38515cdb2f08b982e64cf27c9855c28f4cff8745089f4f7e15a7 | MATLAB | 2,354 | 83 | function MS = createMesh1D(varargin)
% MeshStructure = createMesh1D(Nx, Width)
% MeshStructure = createMesh1D(facelocationX)
% builds a uniform 1D mesh:
% Nx is the number of cells in x (horizontal) direction
% Width is the domain length in x direction
%
% SYNOPSIS:
% MeshStructure = createMesh1D(Nx, Width)
%
% PARAM... |
04fed92a0144a31aff77a2c54bd083d7504a1431e2a80871bd8fad7cb0eba990 | MATLAB | 2,355 | 79 | function adjM_out = limitEdgesForPlotting(adjM, Params)
%LIMITEDGESFORPLOTTING Keep only top weighted edges for visualization
% Support either parameter name
if isfield(Params, 'maxedgestoplot') && ~isempty(Params.maxedgestoplot)
maxEdges = Params.maxedgestoplot;
elseif isfield(Params, 'maxNumEdge... |
41f2fbdae67c15c66ac9b739a46997f98ad0d3d8f28c1c381a72bb676c07f410 | MATLAB | 2,355 | 54 | function [numEvents, eventRaster, freqBinEdgeTime, freq, spikeCount] = ...
YS_lzlab_eventhistogram(timeWidth, timeBinSize, eventTimes, spikeTimestampArray)
numEvents = size( find( eventTimes > 0),2);
% Loop over events.
iLastIndex = 0;
% Get bin edges.
freqBinEdgeTime=[timeWidth(1... |
12bd5329efc57fdf07e6f29718ae8fcd08cd560814d5d0bfdae446bbf1251ad4 | MATLAB | 2,357 | 76 | function tapas_sem_prosa_llh_check_input(t, a, u, theta)
%% Checks the input to the likelihood function
%
% aponteeduardo@gmail.com
% copyright (C) 2015
%
DIM_THETA = tapas_sem_prosa_ndims();
ns = size(t, 1);
np = size(theta, 2);
check_matrix(t, [ns, 1], 't');
check_matrix(a, [ns, 1], 'a');
check_matrix(u, [ns, 1]... |
7277771feab8d99db996009532bebed959fbfb71b4453f5ad8a0805e25829425 | MATLAB | 2,358 | 65 | clc
clear all
close all
for user_num = 13:13
for session = 1:1
for pattern = 1:1
processedpath = input('Enter processed_data location(such as /home/processed_data): ', 's');
load([processedpath,'\Frame_event_pupil_track_result\update_factor_1\left\update_20_point_user',num2str(user_num),'_session_',num2str(session)... |
734474e2a50daee3e7c3643bb99e9596c60c98eab3165fc2758f5075dd4e8376 | MATLAB | 2,359 | 80 | function [results,rt] = UnitTest(sequence,segmentation,GUItest)
%% quickUnitTest.m
% This function performs a quick unit test of the command line calls of
% Osprey. It is based on two Philips datasets of the Big GABA paper, which
% include a complete quantification of PRESS, MEGA-PRESS and HERMES
% spectra. The... |
9f1f3ae9dcce5d8b2e34af1749553859a4df3555e46926329c992e94f919097a | MATLAB | 2,359 | 62 | % Script demo_affine_geometry
% Exemplifies loading of affineTransformation from different data types
%
% demo_affine_geometry
%
%
% See also
% Author: Saskia Bollmann & Lars Kasper
% Created: 2017-10-27
% Copyright (C) 2017 Institute for Biomedical Engineering
% University of Zurich and ETH Z... |
250063af7fb4bda21a919eb6b422285ea4c18d348181538d089a3832654426a8 | MATLAB | 2,361 | 71 | function [mean_burst_amp,num_bursts,mean_burst_length] = BURST_ANALYSIS(bandpass_analysis,threshold_val)
% Identify burst count and duration, as well as mean burst amplitude
% Input is the hilbert transformed amplitude values, and the amplitude
% threshold value for determining a burst
% Output is the average a... |
46266c6f229fd57c9f668299eff18f327d01d846db50f55adf2bc8c0f8d8514c | MATLAB | 2,361 | 81 | function final_dist=surfing_dijkstradist(coords,faces,center_idx,max_distance,nbrs)
% Computes dijkstra distance on a surface mesh
%
% final_dist=surfing_dijkstradist(coords,faces,center_idx,max_distance,nbrs)
%
% INPUTS:
% coords: 3xP coordinates for P vertices
% faces: 3xQ vertex indices for Q f... |
9e6d46c40195c04318efabe80f5a73c95c1c671ae87a1b1c86b3888ed4ada54f | MATLAB | 2,361 | 89 | function facenb=faceneighbors(t,opt)
%
% facenb=faceneighbors(t,opt)
%
% to find 4 face-neighboring elements of a tetrahedron
%
% author: Qianqian Fang, <q.fang at neu.edu>
%
% input:
% t: tetrahedron element list, 4 columns of integers
% opt: if opt='surface', return boundary triangle list
% (should ... |
1badd21b5f84e2a815740abd69de69cd0ecd91f6a04a4e6a40efe289662fa0a7 | MATLAB | 2,363 | 58 | function [ sig_dF_F_activity , sig_dF_F_coactivity_threshold , sig_dF_F_coactivity_peaks ] = findSignificantDF_FCoactivity(dF_F, pars)
%FINDSIGNIFICANTDF_FCOACTIVITY( dF_F )
%
% PARAMETERS:
% \_ dF_F [TxN matrix]: dF/F-signal for N units in T time steps
%
%
% === Jan Moelter, The University of Queensland, 2018 ======... |
369df18bcb624f48a486010012c284453cdf718ef5e90b2e1ecd6b7441088afd | MATLAB | 2,363 | 60 | function [d,r] = cohens_d(data1,data2,pairedSamplesFlag)
% function [d,r] = cohens_d(data1[,data2,pairedSamplesFlag])
%
% Calculates a standardized measure of effect size for t-tests:
% Cohen's d and r for 1-sample and 2-sample t-tests.
% INPUTS:
% data1: mandatory, vector for 1st data sample.
% data2: if scalar,... |
86c96ee108f40048627140c2397668c1a996abd1e981198599016ea1fcb51c4e | MATLAB | 2,363 | 74 | function [hdr] = read_bucn_nirshdr(filename)
% READ_BUCN_NIRSHDR reads the header information of ASCII-formatted NIRS
% data acquired with the UCL-BIRKBECK machine and postprocessed by the
% Paris group. The first line contains the channel labels and the rest of
% the file contains per line a time sample. The first co... |
5723f9527a4a2f27d4880af27d336c0ea6d0a578b887271e337021c955587e0b | MATLAB | 2,364 | 93 | function [mc,stats] = maxcor_npm(X,perms,varargin);
% [mc,stats] = maxcor_npm(X,perms,[c],[MCD robust outlier removal])
%
% X data matrix, columns are variables, rows observations
% c contrast matrix for rotation of X prior to correlation
% contrasts should be rows
% -----------------------------------... |
bf0dad8fc2f6d1c880ff4c6106a2255211d4e2a5e5dccf408c5f46db822dc021 | MATLAB | 2,364 | 59 | %% =============================
% PALM Analysis: ACQ CS×TUS×EXP
% =============================
% --- Locate repo root (relative to this script)
thisfile = mfilename('fullpath');
[scriptdir, ~, ~] = fileparts(thisfile);
cd(scriptdir); % ensure consistent working dir
% Navigate up to FEARTUS root: stats/permutation... |
0c2eed667721630d988dcd2a9ed93de9b50915509c536003026d5817c325381e | MATLAB | 2,366 | 70 | % 3D scalar example
% Author: Aina Frau-Pascual
%%
% Input image
im = zeros(3,3,3);
im(:,:,1) = 1;
im(:,1,:) = 1;
im(3,3,3) = 1;
%%
% Construct mesh structure
Lx = size(im, 1); % domain length
Nx = size(im, 1); % number of cells
Ly = size(im, 2); % domain length
Ny = size(im, 2); % number of cells
Lz = size(im, 3); %... |
2146711e7c9bc1d45dffac9ab7a79c136f850dfe4feee56f9715db3ae03db866 | MATLAB | 2,366 | 71 | function update_fig(hObject, eventdata, handles, force_render_page)
if nargin < 4
force_render_page = false;
end
% Okay, so this is pretty annoying, but the GUI is a bit slower to update
% when a button is selected rather than the figure. I don't know the best
% way to fix this, but disabling and enabling the butto... |
3d3bcbdc8b371d140cefec4c6843cfe06558683d40a10644ba6c76b3c7e84712 | MATLAB | 2,366 | 70 | function [M, Mx, My] = diffusionTermCylindrical2D(D)
% This function uses the central difference scheme to discretize a 2D
% diffusion term in the form \grad . (D \grad \phi) where u is a face vactor
% It also returns the x and y parts of the matrix of coefficient.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% E... |
987072d6bdf64188c08ae3b85a2815fb357bd6bec034f7b044d33c4c8c169688 | MATLAB | 2,366 | 59 | % KURT - return kurtosis of input data distribution
%
% Usage:
% >> k=kurt(data)
%
% Algorithm:
% Calculates kurtosis or normalized 4th moment of an input data vector
% Given a matrix, returns a row vector giving the kurtosis' of the columns
% (Ref: "Numerical Recipes," p. 612)
%
% Author: Martin Mckeown, CNL /... |
726c2470d4781edc90ab7bd3230dd17e1b52b13af538cca3cc2ad85786c891af | MATLAB | 2,367 | 102 | %% %%% SETUP
% load
rdata = {};
for p=1:8
file0 = sprintf('~/nsd/nsddata/ppdata/subj%02d/behav/responses.tsv',p);
rdata{p} = importdata(file0);
end
% define
prffloc = [
DATECENSORED
DATECENSORED
DATECENSORED
DATECENSORED
DATECENSORED
DATECENSORED
DATECENSORED
DATECENSORED
];
nsdsyn = [
DATECENSORED
DATECENSORED
... |
840d96054f081aec003272a3cd7d410d73c75d0be2b426585859ddb2814db866 | MATLAB | 2,367 | 64 | function [ahr, binvals, subj] = get_allsubs_adj_hr(binType,cellFlag)
% [ahr, binvals, subj] = get_allsubs_adj_hr(binType,cellFlag)
%
% Produces adjusted hit rate values for all NSD subjects as a function of
% different inter-item lag bins specified by binType. if cellFlag is true
% (disabled by default), output is... |
a9e7eaf0d036c01b086f84edc5d1d6f36bc3fa27e32f730914bb3dcbf87ca78f | MATLAB | 2,367 | 74 | function model2dot(modelPath, outPath, varargin)
%MODEL2DOT Convert a model to Graphviz dot
% MODEL2DOT(MODEL_PATH, OUT_PATH) Generate a graphviz dot file OUT_PATH
% of MatConvNet model MODEL_PATH.
%
% By default, the scripts attempts to guess the input sizes based on the
% network normalization options and the pa... |
44e04a7b4f05e1932cdc550ee450d039e0906b0481d0bae17ba7b46e5f4894cc | MATLAB | 2,368 | 79 | function [varargout] = simulateClusteredfMRIData(simulationOptions)
% simulateClusteredfMRIData
%
% [B_true, B_noisy[, B_noisy2[, ...]]] = simulateClusteredfMRIData(simulationOptions)
%
% Simulate both a 'true' beta matrix with clustered data (according to
% simulationOptions) and a 'noisy' one contaminated with simula... |
12edc1442429a4fca9158d031ca3ed9a2ecc547a4372cb3307f5aa14a93f179f | MATLAB | 2,371 | 71 | %% h = sepia_handle_panel_bkgRemoval_RESHARP(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global structure contains all new and o... |
5c7a82457c1442f586c28164196f2cd856915f39a8dbb02a52080d79752d98b4 | MATLAB | 2,371 | 80 | function [spikeRaster, spikest, fit, drift, parest]=inferSpikeTrain(trace,fs,varargin)
% TO DO > estimate more accuratly the par.a parameters... some neurons have
% slightly different 1-spike dff
%% OPTIONS
options.duration=[]; %in sec
options.MLspikeParam=[];
options.plotFigure=true;
options.savePath=[];
%% UPDATE ... |
dcb88c625088f6fe4018cc13f321df091ae098c51be25e682114d32145108010 | MATLAB | 2,371 | 71 | function samplingPointLabels = index2label(this, arrayIndices, iDims)
% Returns array of index labels for specified voxel indices
%
% Y = MrDimInfo()
% indexLabelArray = index2label(this, arrayIndices)
%
% For 3D data, this usually returns the voxel coordinates of the specified
% voxel indices, for 4D fMRI, it addi... |
de4332f00a1eb417603dbd05d650ffdf510b28b2bf5f107d274e109e3f3e15ab | MATLAB | 2,371 | 71 | function pred = knntest(Xtest,class_t,X,class,K,dist_type,pret_type)
% prediction of new samples with calculated model
%
% pred = knnpred(Xtest,X,class,K,dist_type,pret_type)
%
% ------------ INPUT ---------------------------------------------------
% Xtest: dataset to be predicted [n_test x p] n objects, p var... |
ef424065e3f60feb555b6b206e5dfadc57b9386295547a4d7addf24eb7f7412a | MATLAB | 2,371 | 78 | % orthMID42.png taken from subj01
% generate distribution visualization
n = 100000;
vals = vmrand((360/40/2)/180*pi,3^6,[1 6*n]); % center in middle of first session
vals2 = rand(1,4*n)*2*pi-pi;
figureprep([100 100 400*.6 250*.6],1); hold on;
h = histogram([vals vals2]/pi*180,5000,'Normalization','pdf');
set(h,'FaceC... |
e0f91dd273f2399915801246939cd8cf25c3063992348834cb20a3a1d868dab4 | MATLAB | 2,372 | 144 | % 1 x 1 % 1 x 1% plot_info
% plot Free energy and other infomation
a_min = 1e-5;
NX = 2;
NY = 2;
alpha_plot = 0;
FE = Info.FE;
tend = length(FE);
% Start and End of iteration number for plot
tmode = 2;
t0 = 10;
t3 = 600;
switch tmode
case 1
t1 = t0;
t2 = tend;
case 2
t1 = t3;
t2 = te... |
0725a9b5f22c6e9c6269c197c2868041f460310e206220c41448cb96cbd4cb61 | MATLAB | 2,374 | 41 | function B1Tx_GroupAverage(IndCorrMyelinAvgFile, IndCorrMyelinAsymmOutFile, IndCorrAllMyelinFile, GoodVoltagesFile, SB1TxFile, B1TxStatsFile, CSFStatsFile, RegressedMyelinOutFile, CovariatesOutFile)
AvgICorrMyelinMap = cifti_read(IndCorrMyelinAvgFile);
surfasymmnorm(AvgICorrMyelinMap, IndCorrMyelinAsymmOutFile,... |
769a6202cddf7c2a61d01e306f38171ea492dfe1837c5d5dcb3a9aa1891d313b | MATLAB | 2,374 | 71 | function preprocessing(mri_lst)
%
% Input: mri_lst <list of strings> list of fullpaths to MRI images to be
% preprocessed
%
% This function converts the MRI scan to nifti-fileformat, orients the input
% MRIs to the ACPC corrdinate system and creates an average MRI image (u... |
9b079bd48e04134185e1d6e0a57a99f88bc8b118055c93ae8c374abb971b8747 | MATLAB | 2,374 | 77 | function plotStimDetectionChecks(filteredData, stimInfo, expSubFolder, Params)
%PLOTSTIMDETECTIONCHECKS Summary of this function goes here
% Detailed explanation goes here
%% 1 | Overall stimulation trace
figName = '1_StimsDetected';
figHandle = figure;
figHandle = plotStimTimes(filteredData, stimInfo, Params, fig... |
f01dec3adf6fa82f734d92ea9a2491c53c92872d4fa39135ce5e284e86acb99c | MATLAB | 2,375 | 68 | function [coef, t, n] = nancorr_amd(A, B)
%NANCORR - Pearson correlation coefficient
%
% coef = NANCORR(A, B) is equivalent to
% coef = corr(A, B, 'rows','pairwise'),
% but NANCORR works much faster.
%
% [coef, t, n] = NANCORR(A, B)
% INPUT:
% A, B - input matrices, single or double, with e... |
8a9b34369960f4b4515a836c383811132793b48d1f00879cd05ef9c921017a44 | MATLAB | 2,376 | 95 | function obj = update_subspace(obj)
N = numel(obj.data);
D = prod(obj.lat);
% ---------
% precision
% ---------
% > Au = lam * E[Z*Z'] + I
obj.Au = eye(obj.M) + obj.lam * (obj.ZZ + N * obj.iAz);
obj.iAu = brca.utils.invPD(obj.Au);
% ----------------
% variational mean
%... |
8d70ab83035fcdef1c6da8dcfc00c5f7e26e03ce5fc0c9b8177db1e3b7df61ff | MATLAB | 2,376 | 82 | classdef numeric < brca.format.base
properties
type = 'single';
end
methods
function obj = numeric(type)
if nargin > 0
obj.type = type;
end
end
function data = read(~,array,index,dimension)
if nargin < 4
d... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.