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github | lcnhappe/happe-master | rejkurt.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/rejkurt.m | 4,127 | utf_8 | 871cc2da42fee9b970ec91508ece96fb | % rejkurt() - calculation of kutosis of a 1D, 2D or 3D array and
% rejection of outliers values of the input data array
% using the discrete kutosis of the values in that dimension.
%
% Usage:
% >> [kurtosis rej] = rejkurt( signal, threshold, kurtosis, normalize);
%
% Inputs:
% signal... |
github | lcnhappe/happe-master | readeetraklocs.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/readeetraklocs.m | 2,399 | utf_8 | 9e9ab75538baff3f8e51e2d15bcbbfc8 | % readeetraklocs() - read 3-D location files saved using the EETrak
% digitizing software.
% Usage:
% >> CHANLOCS = readeetraklocs( filename );
%
% Inputs:
% filename - [string] file name
%
% Outputs:
% CHANLOCS - EEGLAB channel location data structure.
% See hel... |
github | lcnhappe/happe-master | nan_mean.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/nan_mean.m | 1,341 | utf_8 | e87ae15c116d4211709116e3c5abf693 | % nan_mean() - Average, not considering NaN values
%
% Usage: same as mean()
% Author: Arnaud Delorme, CNL / Salk Institute, 16 Oct 2002
% Copyright (C) 2001 Arnaud Delorme, Salk Institute, arno@salk.edu
%
% This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General P... |
github | lcnhappe/happe-master | dipoledensity.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/dipoledensity.m | 22,135 | utf_8 | e26078ef7126108f2f7737b5c773de3d | % dipoledensity() - compute and optionally plot a measure of the 3-D spatial
% (in)homogeneity of a specified (large) set of 1- or 2-dipole
% component models, either as physical dipole density or as
% dipole-position entropy across subjects. In either case,
% ... |
github | lcnhappe/happe-master | icaproj.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/icaproj.m | 5,346 | utf_8 | 4a90dc72f4d7531154efd0ac71fb422c | % icaproj() - project ICA component activations through the
% associated weight matrices to reconstitute the
% observed data using only the selected ICA components.
% Usage:
% >> [icaprojdata] = icaproj(data,weights,compindex,[datameans],chansout);
%
% Inputs:
% data - data matrix (ch... |
github | lcnhappe/happe-master | epoch.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/epoch.m | 7,001 | utf_8 | 340a95a2503450e01dbd7c4c0dcc9951 | % epoch() - Extract epochs time locked to specified events from continuous EEG data.
%
% Usage:
% >> epocheddata = epoch( data, events, timelim);
% >> [epocheddata, newtime, indices, rerefevent, rereflatencies ] = ...
% epoch( data, events, timelim, 'key1', value1, ... );
%
% Inputs:
% data ... |
github | lcnhappe/happe-master | headplot.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/headplot.m | 34,780 | utf_8 | df090bdd0b2bc2329ab6ebb70a00813d | % headplot() - plot a spherically-splined EEG field map on a semi-realistic
% 3-D head model. Can 3-D rotate the head image using the left
% mouse button.
% Example:
% >> headplot example % show an example spherical 'eloc_angles' file
% >> headplot cartesian % show an example cartesian... |
github | lcnhappe/happe-master | eegfiltfft.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/eegfiltfft.m | 4,093 | utf_8 | 7a24c770da0253fdd7c37b4d445adada | % eegfiltfft() - (high|low|band)-pass filter data using inverse fft
% (without using the Matlab signal processing toolbox)
% Usage:
% >> [smoothdata] = eegfiltfft(data,srate,locutoff,hicutoff);
% >> [smoothdata] = eegfiltfft(data,srate,locutoff,hicutoff,epochframes,filtorder,revfilt);
%
% Inputs:
% ... |
github | lcnhappe/happe-master | rejstatepoch.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/rejstatepoch.m | 17,342 | utf_8 | 284e9677ee175d6c99cf0d443ddc1676 | % rejstatepoch() - reject bad eeg trials based a statistical measure. Can
% be applied either to the raw eeg data or the ICA
% component activity. This is an interactive function.
%
% Usage:
% >> [ Irej, Irejdetails, n, threshold, thresholdg] = ...
% rejstatep... |
github | lcnhappe/happe-master | binica.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/binica.m | 13,069 | utf_8 | e1bfb70b5edae53d01116b6f9cf42d51 | % binica() - Run stand-alone binary version of runica() from the
% Matlab command line. Saves time and memory relative
% to runica(). If stored in a float file, data are not
% read into Matlab, and so may be larger than Matlab
% can handle owing to memory limitations.
% Usa... |
github | lcnhappe/happe-master | mattocell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/mattocell.m | 1,311 | utf_8 | bb1357cab390093724fa7887f66ebef3 | % mattocell() - convert matrix to cell array
%
% Usage: >> C = mattocell( M );
%
% Author: Arnaud Delorme, CNL / Salk Institute, Jan 25 2002
%
% Note: this function overload the nnet toolbox function mattocell,
% but does not have all its capacities. You can delete the current
% function if you have the toolbox.
% ... |
github | lcnhappe/happe-master | readegihdr.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/readegihdr.m | 3,589 | utf_8 | 009a2ce2b93412350699c09bebfaeb4e | % readegihdr() - read header information from EGI (versions 2,3,4,5,6,7) data file.
%
% Usage:
% >> [head] = readegihdr(fid,forceversion)
%
% Input:
% fid - file identifier of EGI datafile
% forceversion - optional integer input to override automatic reading of version number.
%
% Output:
% head - structure con... |
github | lcnhappe/happe-master | timtopo.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/timtopo.m | 15,459 | utf_8 | a449d814e428e5d230cda9f0adfe661a | % timtopo() - plot all channels of a data epoch on the same axis
% and map its scalp map(s) at selected latencies.
% Usage:
% >> timtopo(data, chan_locs);
% >> timtopo(data, chan_locs, 'key', 'val', ...);
% Inputs:
% data = (channels,frames) single-epoch data matrix
% chan_locs = channel loc... |
github | lcnhappe/happe-master | rmbase.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/rmbase.m | 3,813 | utf_8 | 7f8fcb4d54c16b3482b307e2c8133cbb | % rmbase() - subtract basevector channel means from multi-epoch data matrix
%
% Usage:
% >> [dataout] = rmbase(data); % remove whole-data channel means
% >> [dataout datamean] = rmbase(data,frames,basevector);
% % remove mean of basevector from each channel and epoch
% Inputs:
% data - da... |
github | lcnhappe/happe-master | realproba.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/realproba.m | 2,315 | utf_8 | f564644151c35bcc6b310d8e54773abd | % realproba() - compute the effective probability of the value
% in the sample.
%
% Usage:
% >> [probaMap, probaDist ] = realproba( data, discret);
%
% Inputs:
% data - the data onto which compute the probability
% discret - discretisation factor (default: (size of data)/5)
% ... |
github | lcnhappe/happe-master | eegfilt.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/eegfilt.m | 8,031 | utf_8 | 5d305e3ed98f5df8a36f43880470f905 | % eegfilt() - (high|low|band)-pass filter data using two-way least-squares
% FIR filtering. Optionally uses the window method instead of
% least-squares. Multiple data channels and epochs supported.
% Requires the MATLAB Signal Processing Toolbox.
% Usage:
% >> [smoothdata] = ... |
github | lcnhappe/happe-master | phasecoher.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/phasecoher.m | 13,038 | utf_8 | 2b8981e6f824cfb02a87b964d5e114e4 | % phasecoher() - Implements inter-trial amp/coherence using Gaussian wavelets.
% Returns same data length as input frames.
% Plots results when nargin>6. Outputs have flat ends
% at data indices [1:halfwin] and [frames-halfwin:frames].
% Usage:
% >> [amps,cohers ] = pha... |
github | lcnhappe/happe-master | plotchans3d.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/plotchans3d.m | 3,251 | utf_8 | 8664823c760a1d16ba00362311f2de52 | % plotchans3d() - Plots the 3-D configuration from a Polhemus ELP
% file. The axes of the Cartesian coordinate system are
% plotted. The nose is plotted as a bold red segment.
% Usage:
% >> plotchans3d( elpfile, zs);
% >> plotchans3d( [X,Y,Z], elecnames, zs);
%
% Inputs:... |
github | lcnhappe/happe-master | biosig2eeglab.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/biosig2eeglab.m | 7,146 | utf_8 | 382204f79712220b2bbab12edc97455f | % biosig2eeglab() - convert BIOSIG structue to EEGLAB structure
%
% Usage:
% >> OUTEEG = pop_biosig2eeglab(hdr, data, interval);
%
% Inputs:
% hdr - BIOSIG header
% data - BIOSIG data array
%
% Optional input:
% interval - BIOSIG does not remove event which are outside of
% the data range when i... |
github | lcnhappe/happe-master | changeunits.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/changeunits.m | 4,318 | utf_8 | 94064327606cc4ebb997d7e5e58d4bfe | % changeunits() - Takes one or more points in one axes and gives its position
% in another axes. Useful for drawing lines between
% sbplots (see sbplot()).
%
% Usage: >> newpoint(s) = changeunits(point(s),curaxhandle,newaxhandle)
%
% Inputs:
% point(s) - two-column vector of c... |
github | lcnhappe/happe-master | ploterp.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/ploterp.m | 3,923 | utf_8 | 86b19356589f4063b6895c62ff72609c | % ploterp() - plot a selected multichannel data epoch on a common timebase
%
% Usage: >> ploterp(data,frames,epoch,[limits],'title',[plotchans]);
%
% Inputs:
% data = EEG/ERP data epoch (chans,frames)
% frames = frames per epoch {default: data length}
% epoch = epoch to plot {default: 1}
% [limits] ... |
github | lcnhappe/happe-master | forcelocs.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/forcelocs.m | 7,010 | utf_8 | a97dcbb735eedf75d6f3a7e5590deaee | % forcelocs() - rotate location in 3-D so specified electrodes
% match specified locations.
% CAUTION: Only for use on electrodes in
% and remaining in the upper spherical hemisphere,
% otherwise it will work improperly. Written primarily for
% adju... |
github | lcnhappe/happe-master | rejtrend.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/rejtrend.m | 3,677 | utf_8 | 9196ccbe2b666079d926f2bbbdc7fa83 | % rejtrend() - detect linear trends in EEG activity and reject the
% epoched trials based on the accuracy of the linear
% fit.
% Usage:
% >> [rej rejE] = rejtrend( signal, winsize, maxslope, minR, step);
%
% Inputs:
% signal - 3 dimensional signal (channels x frames x trials)... |
github | lcnhappe/happe-master | slider.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/slider.m | 5,310 | utf_8 | da3f7a317a05c2c37254282f6d2b6bac | % slider() - add slider to a figure
%
% Usage:
% >> slider( handler, horiz, vert, horizmag, vertmag);
%
% Inputs:
% handler - figure handler (for the current figure, use gcf)
% horiz - [0|1] add a horizontal slider
% vert - [0|1] add a horizontal slider
% horizmag - magnify the width of the figure be... |
github | lcnhappe/happe-master | loadcnt.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/loadcnt.m | 29,097 | utf_8 | 5e1876613970ecc4b37123e6cf44f648 | % loadcnt() - Load a Neuroscan continuous signal file.
%
% Usage:
% >> cnt = loadcnt(file, varargin)
%
% Inputs:
% filename - name of the file with extension
%
% Optional inputs:
% 't1' - start at time t1, default 0. Warning, events latency
% might be innacurate (this is an open issue).
% ... |
github | lcnhappe/happe-master | icaact.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/icaact.m | 2,583 | utf_8 | e90b9a3cfaabf4e09cf26a0a692344e4 | % icaact() - compute ICA activation waveforms = weights*sphere*(data-meandata)
%
% Usage: >> [activations] = icaact(data,weights,datamean);
%
% Inputs:
% data = input data (chans,frames)
% weights = unmixing matrix (runica() weights*sphere)
% datamean = 0 or mean(data') (default 0);
%
% Note: If da... |
github | lcnhappe/happe-master | gettempfolder.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/gettempfolder.m | 1,470 | utf_8 | 71281778d892c5545193292a61509dd9 | % gettempfolder() - return the temporary folder
%
% Usage: >> folder = gettempfolder;
%
% Output: a string containing the folder if a temporary folder can be found.
% Empty if the folder cannot be found.
%
% Author: Arnaud Delorme, SCCN, UCSD, 2012
%
% Copyright (C) Arnaud Delorme
% This program is free softw... |
github | lcnhappe/happe-master | loadtxt.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/loadtxt.m | 6,712 | utf_8 | 6bb912af759266869498c019520fc4c9 | % loadtxt() - load ascii text file into numeric or cell arrays
%
% Usage:
% >> array = loadtxt( filename, 'key', 'val' ...);
%
% Inputs:
% filename - name of the input file
%
% Optional inputs
% 'skipline' - number of lines to skip {default:0}. If this number is
% negative the program will only sk... |
github | lcnhappe/happe-master | plotmesh.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/plotmesh.m | 3,048 | utf_8 | 8345a3f062504b918e1d6e64dda75110 | % plotmesh() - plot mesh defined by faces and vertex
%
% Usage:
% plotmesh(faces, vertex);
%
% Input:
% faces - array of N x 3. Each row defines a triangle. The 3 points
% in each row are row indices in the matrix below.
% vertex - array of M x 3 points, (x = first colum; y=second colum
% ... |
github | lcnhappe/happe-master | mri3dplot.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/mri3dplot.m | 18,772 | utf_8 | 710c890eda7ee5b1b19e7efefa357f7c | % mri3dplot() - plot 3-D density image translucently on top of the mean MR
% brain image used in dipplot(). Plot brain slices in directions
% 'top' (axial), or 'side' (sagittal), or 'rear' (coronal).
% Creates a new figure(). Smoothing uses Matlab smooth3()
% Usage:
% >> ... |
github | lcnhappe/happe-master | spherror.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/spherror.m | 1,249 | utf_8 | c912e32a9b9351420468261b94d5b5e8 | % 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 program is free software; you can redistribute it and/or modify
% it under the... |
github | lcnhappe/happe-master | envtopo.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/envtopo.m | 47,733 | utf_8 | 31745f07983ae21a1a8d735d9a6e5a5e | %
% envtopo() - Plot the envelope of a multichannel data epoch, plus envelopes and
% scalp maps of specified or largest-contributing components. If a 3-D
% input matrix, operates on the mean of the data epochs. Click on
% individual axes to examine them in detail. The black lines ... |
github | lcnhappe/happe-master | runica.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/runica.m | 64,868 | utf_8 | fa36c213fe0a11f1d407d1847d81bac0 | % runica() - Perform Independent Component Analysis (ICA) decomposition
% of input data using the logistic infomax ICA algorithm of
% Bell & Sejnowski (1995) with the natural gradient feature
% of Amari, Cichocki & Yang, or optionally the extended-ICA
% algorithm of Lee, G... |
github | lcnhappe/happe-master | jader.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/jader.m | 11,455 | utf_8 | 8b74fa9e0345ee0857e1e564b74dd872 | % jader() - blind separation of real signals using JADE (v1.5, Dec. 1997).
%
% Usage:
% >> B = jader(X);
% >> B = jader(X,m);
%
% Notes:
% 1) If X is an nxT data matrix (n sensors, T samples) then
% B=jader(X) is a nxn separating matrix such that S=B*X is an nxT
% matrix of estimated source signals.
% 2)... |
github | lcnhappe/happe-master | spectopo.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/spectopo.m | 41,106 | utf_8 | 1d8873878f4c3dc70942cc4aea480585 | % spectopo() - Plot the power spectral density (PSD) of winsize length segments of data
% epochs at all channels as a bundle of traces. At specified frequencies,
% plot the relative topographic distribution of PSD. If available, uses
% pwelch() from the Matlab signal processing t... |
github | lcnhappe/happe-master | loadavg.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/loadavg.m | 10,977 | utf_8 | eab4ed6a06ccdcb41d04203ec4f0b489 | % loadavg() - loading eeg average data file from Neuroscan into
% matlab.
% Usage:
% >> [signal, variance, chan_names, ...
% pnts, rate, xmin, xmax] = loadavg( filename, version );
% Input:
% filename - input Neuroscan .avg file
% version - [1 or 2] function version. Default... |
github | lcnhappe/happe-master | biosig2eeglabevent.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/biosig2eeglabevent.m | 4,111 | utf_8 | 9ecfe50ab1307bb14c583e5262750407 | % biosig2eeglabevent() - convert biosig events to EEGLAB event structure
%
% Usage:
% >> eeglabevent = biosig2eeglabevent( biosigevent, interval, mode)
%
% Inputs:
% biosigevent - BioSig event structure
% interval - Period to extract events for, in frames.
% Default [] is all.
% mode... |
github | lcnhappe/happe-master | acsobiro.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/acsobiro.m | 5,108 | utf_8 | a67b95f026833f1e4dfeaf44fcd94335 | % acsobiro() - A. Chickocki's robust Second-Order Blind Identification (SOBI)
% by joint diagonalization of the time-delayed covariance matrices.
% NOTE: THIS CODE ASSUMES TEMPORALLY CORRELATED SIGNALS.
% Thus, the estimated time-delayed covariance matrices
% for a... |
github | lcnhappe/happe-master | metaplottopo.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/metaplottopo.m | 13,145 | utf_8 | 2f89761aa47cc2b3914162e988f6f1cc | % metaplottopo() - plot concatenated multichannel data epochs in a topographic or
% rectangular array. Uses a channel location file with the same
% format as topoplot(), or else plots data on a rectangular grid.
%
% Usage:
% >> axes = metaplottopo(data, 'key1', 'val1', 'key2', 'val2')
%
%... |
github | lcnhappe/happe-master | blockave.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/blockave.m | 2,707 | utf_8 | 74345d9d3d97007ec7f3ef4dd137abd4 | % blockave() - make block average of concatenated data sets of same size
% Each data set is assumed to be of size (chans,frames).
% Usage:
% >> aveout = blockave(data,frames)
% >> aveout = blockave(data,frames,epochs,weights)
% Inputs:
% data = data matrix of size (chans,fra... |
github | lcnhappe/happe-master | posact.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/posact.m | 2,789 | utf_8 | 485896d0a8c23f3b21a5d76bdb1209fe | % posact() - Make runica() activations all RMS-positive.
% Adjust weights and inverse weight matrix accordingly.
%
% Usage: >> [actout,winvout,weightsout] = posact(data,weights,sphere)
%
% Inputs:
% data = runica() input data
% weights = runica() weights
% sphere = runica() sphere {... |
github | lcnhappe/happe-master | eegplot.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/eegplot.m | 91,576 | utf_8 | f16189ff1fb950bdd445c8f97db68826 | % eegplot() - Scroll (horizontally and/or vertically) through multichannel data.
% Allows vertical scrolling through channels and manual marking
% and unmarking of data stretches or epochs for rejection.
% Usage:
% >> eegplot(data, 'key1', value1 ...); % use interface buttons, etc.
%... |
github | lcnhappe/happe-master | uigetfile2.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/uigetfile2.m | 2,667 | utf_8 | a344bcefaca772c110df38301343a003 | % uigetfile2() - same as uigetfile but remember folder location.
%
% Usage: >> uigetfile2(...)
%
% Inputs: Same as uigetfile
%
% Author: Arnaud Delorme & Hilit Serby, Scott Makeig, SCCN, UCSD, 2004
% Thanks to input from Bas Kortmann
%
% Copyright (C) Arnaud Delorme & Hilit Serby, Scott Makeig, SCCN, UCSD, 2004... |
github | lcnhappe/happe-master | readelp.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/readelp.m | 3,428 | utf_8 | 2869dca997f92d27420c23c7cf912e6f | % readelp() - read electrode locations from an .elp (electrode positions)
% file as generated, for example, by a Polhemus tracking device
% Usage:
% >> [eloc, elocnames, X, Y, Z] = readelp(filename);
%
% Inputs:
% filename - name of the .elp file containing cartesian (XYZ) electrode
% loca... |
github | lcnhappe/happe-master | plottopo.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/plottopo.m | 30,821 | utf_8 | eba3d347d7a02858e68b8395d284199f | % plottopo() - plot concatenated multichannel data epochs in a topographic
% or
% rectangular array. Uses a channel location file with the same
% format as topoplot(), or else plots data on a rectangular grid.
% If data are all positive, they are assumed to be spectra.
% Usage:
... |
github | lcnhappe/happe-master | plotcurve.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/plotcurve.m | 13,176 | utf_8 | b247086675025ad96d7229832935ff76 | % plotcurve() - plot curve(s) with optional significance highlighting.
%
% Usage: >> plotcurve(times, data, 'key1', 'val1', 'key2', val2' ...);
%
% Required inputs:
% times - [float] vector of time indices
% data - [float] data array, size of [n x times]. If n>1 several
% curves are plotted (unless 'plot... |
github | lcnhappe/happe-master | readneurolocs.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/readneurolocs.m | 4,352 | utf_8 | a351981666e50fa3ac943a11a7799b84 | % readneurolocs() - read neuroscan polar location file (.asc)
%
% Usage:
% >> CHANLOCS = readneurolocs( filename );
% >> CHANLOCS = readneurolocs( filename, 'key1', val1, ...);
%
% Inputs:
% filename - file name or matlab cell array { names x_coord y_coord }
%
% Optional inputs:
% same as caliblocs()
% ... |
github | lcnhappe/happe-master | condstat.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/condstat.m | 11,329 | utf_8 | 42bfdcd65fdf5e5de0ed089486888d0c | % condstat() - accumulate surrogate data for comparing two data conditions
%
% Usage:
% >> [diffres, accres, res1, res2] = condstat(formula, naccu, alpha, ...
% bootside, condboot, arg1, arg2 ...);
%
% Inputs:
% formula - [string or cell array of strings] formula(s)... |
github | lcnhappe/happe-master | movav.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/movav.m | 7,664 | utf_8 | a7743cb15a5f70fdc8db72736287f7ec | % movav() - Perform a moving average of data indexed by xvals.
% Supports use of a moving non-rectangular window.
% Can be used to resample a data matrix to any size
% (see xadv NOTE below) and to regularize sampling of
% irregularly sampled data.
% Usage:
% >> [outdata,outx] ... |
github | lcnhappe/happe-master | readtxtfile.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/readtxtfile.m | 1,473 | utf_8 | 884a7c06601ae6728761a5e03fd42521 | % readtxtfile() - Read text file into a Matlab variable
%
% Usage: >> str = readtxtfile( filename );
%
% Input:
% filename - [string] name of the file.
%
% Output:
% str - [string] content of the file.
%
% Author: Arnaud Delorme, SCCN / INC / UCSD, August 2009
% Copyright (C) Arnaud Delorme, August 2009
%
% This p... |
github | lcnhappe/happe-master | openbdf.m | .m | happe-master/Packages/eeglab14_0_0b/functions/sigprocfunc/openbdf.m | 6,712 | utf_8 | 1496f13e75bb80dd10e647e3497b1a52 | % openbdf() - Opens an BDF File (European Data Format for Biosignals) in MATLAB (R)
%
% Usage:
% >> EDF=openedf(FILENAME)
%
% Note: About EDF -> www.biosemi.com/faq/file_format.htm
%
% Author: Alois Schloegl, 5.Nov.1998
%
% See also: readedf()
% Copyright (C) 1997-1998 by Alois Schloegl
% a.schloegl@ieee.org
% Ver ... |
github | lcnhappe/happe-master | anova2rm_cell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/anova2rm_cell.m | 6,774 | utf_8 | 37ad08d0dfb97a5ae59971a6becc90b7 | % anova2rm_cell() - compute F-values in cell array using repeated measure
% ANOVA.
%
% Usage:
% >> [FC FR FI dfc dfr dfi] = anova2rm_cell( data );
%
% Inputs:
% data = data consisting of PAIRED arrays to be compared. The last
% dimension of the data array is used to comput... |
github | lcnhappe/happe-master | statcond.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/statcond.m | 24,879 | utf_8 | 8adfae55efd5defaad53dc2a93a6dc25 | % statcond() - compare two or more data conditions statistically using
% standard parametric or nonparametric permutation-based ANOVA
% (1-way or 2-way) or t-test methods. Parametric testing uses
% fcdf() from the Matlab Statistical Toolbox.
% Usage:
% >> [stats, d... |
github | lcnhappe/happe-master | surrogdistrib.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/surrogdistrib.m | 5,888 | utf_8 | 18526734957324ab037d603d38a328cf | % surrogdistrib - Build surrogate distribution
%
% surrog = surrogdistrib(data, varargin);
%
% Inputs:
% data - [cell] data arrays for which to compute a surrogate
% distribution.
%
% Optional inputs:
% 'method' - ['bootstrap'|'perm'] use either 'bootstrap' or 'permutation'
% method. Bootstr... |
github | lcnhappe/happe-master | stat_surrogate_pvals.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/stat_surrogate_pvals.m | 2,648 | utf_8 | 74534793d4027376c995150218faf240 | function pvals = stat_surrogate_pvals(distribution,observed,tail)
% compute empirical p-vals under the null hypothesis that observed samples
% come from a given surrogate distribution. P-values for Type I error in
% rejecting the null hypothesis are obtained by finding the proportion of
% samples in the distribution th... |
github | lcnhappe/happe-master | anova1rm_cell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/anova1rm_cell.m | 3,731 | utf_8 | 40890df8c96f1a41aca5846c8c9c4883 | % anova1rm_cell() - compute F-values in cell array using repeated measure
% ANOVA.
%
% Usage:
% >> [FC dfc] = anova2rm_cell( data );
%
% Inputs:
% data = data consisting of PAIRED arrays to be compared. The last
% dimension of the data array is used to compute ANOVA.
% Out... |
github | lcnhappe/happe-master | teststat.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/teststat.m | 20,505 | utf_8 | 8521a1c623a39fbdaded6534e27d6c3c | % teststat - EEGLAB statistical testing function
%
% Statistics are critical for inference testing in Science. It is thus
% primordial to make sure than all the statistics implemented are
% robust and at least bug free. Statistical function using complex
% formulas are inherently prone to bugs. EEGLAB functions are a... |
github | lcnhappe/happe-master | ttest2_cell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/ttest2_cell.m | 4,634 | utf_8 | cb20a27eff3e4cd6eb3c9ae82e863eed | % ttest2_cell() - compute unpaired t-test. Allow fast computation of
% multiple t-test using matrix manipulation.
%
% Usage:
% >> [F df] = ttest2_cell( { a b } );
% >> [F df] = ttest2_cell(a, b);
% >> [F df] = ttest2_cell(a, b, 'inhomogenous');
%
% Inputs:
% a,b = data consisting of UN... |
github | lcnhappe/happe-master | concatdata.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/concatdata.m | 4,076 | utf_8 | f9b1c761e3ea4846ea5891a0ac56a923 | % concatdata - concatenate data stored into a cell array into a single
% array. only concatenate along the last dimension
% Usage:
% [dataarray len dims] = concatata(cellarraydata);
%
% Input:
% cellarraydata - cell array containing data
%
% Output:
% dataarray - single array containing all data
%... |
github | lcnhappe/happe-master | ttest_cell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/ttest_cell.m | 3,107 | utf_8 | a669e2ffb5b0d990717a40eda3db4a2f | % ttest_cell() - compute paired t-test. Allow fast computation of
% multiple t-test using matrix manipulation.
%
% Usage:
% >> [F df] = ttest_cell( { a b } );
% >> [F df] = ttest_cell(a, b);
%
% Inputs:
% a,b = data consisting of PAIRED arrays to be compared. The last
% dime... |
github | lcnhappe/happe-master | statcondfieldtrip.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/statcondfieldtrip.m | 15,781 | utf_8 | 796460d89be7fccc4c28be4a80fc7dac | % statcondfiledtrip() - same as statcond except that it uses the fieldtrip
% statistical functions. This is useful to perform
% a wider variety of corrections for multiple
% comparisons for instance.
% Usage:
% >> [stats, df, pvals, surrog]... |
github | lcnhappe/happe-master | corrcoef_cell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/corrcoef_cell.m | 3,242 | utf_8 | 0c78b817804b92c20e7a7a7b084134ab | % corrcoef_cell() - compute pairwise correlations using arrays and
% cell array inputs.
%
% Usage:
% >> c = corrcoef_cell( data );
% >> c = corrcoef_cell( data );
%
% Inputs:
% data - [cell array] data consisting of PAIRED arrays to be compared.
% The last dimension of e... |
github | lcnhappe/happe-master | stat_surrogate_ci.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/stat_surrogate_ci.m | 3,125 | utf_8 | cd001b0625997e12a9b2e0bd2accbfe5 | % compute empirical p-vals under the null hypothesis that observed samples
% come from a given surrogate distribution. P-values for Type I error in
% rejecting the null hypothesis are obtained by finding the proportion of
% samples in the distribution that
% (a) are larger than the observed sample (one-sided test)
% (b... |
github | lcnhappe/happe-master | anova1_cell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/anova1_cell.m | 4,428 | utf_8 | 60e8465ee6822f93b4e4d4bcad190d42 | % anova1_cell() - compute F-values in cell array using ANOVA.
%
% Usage:
% >> [F df] = anova1_cell( data );
%
% Inputs:
% data = data consisting of PAIRED arrays to be compared. The last
% dimension of the data array is used to compute ANOVA.
% Outputs:
% F - F-value
% df - degree of f... |
github | lcnhappe/happe-master | fdr.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/fdr.m | 2,273 | utf_8 | 0339630d5b76067fde504d464d26a9bf | % fdr() - compute false detection rate mask
%
% Usage:
% >> [p_fdr, p_masked] = fdr( pvals, alpha);
%
% Inputs:
% pvals - vector or array of p-values
% alpha - threshold value (non-corrected). If no alpha is given
% each p-value is used as its own alpha and FDR corrected
% array is ret... |
github | lcnhappe/happe-master | anova2_cell.m | .m | happe-master/Packages/eeglab14_0_0b/functions/statistics/anova2_cell.m | 8,530 | utf_8 | 3f58b154b60557add57c3652a63d8b62 | % anova2_cell() - compute F-values in cell array using ANOVA.
%
% Usage:
% >> [FC FR FI dfc dfr dfi] = anova2_cell( data );
%
% Inputs:
% data = data consisting of PAIRED arrays to be compared. The last
% dimension of the data array is used to compute ANOVA.
% Outputs:
% FC - F-value for... |
github | lcnhappe/happe-master | pop_expica.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_expica.m | 2,190 | utf_8 | de6256134d052dc2d501f1da80a85a5a | % pop_expica() - export ICA weights or inverse matrix
%
% Usage:
% >> pop_expica( EEG, whichica); % a window pops up
% >> pop_expica( EEG, whichica, filename );
%
% Inputs:
% EEG - EEGLAB dataset
% whichica - ['weights'|'inv'] export ica 'weights' or ica inverse
% matrix (... |
github | lcnhappe/happe-master | pop_loadbci.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_loadbci.m | 13,381 | utf_8 | 471e8acb985f699ddd0e2e3b3a723d45 | % pop_loadbci() - import a BCI2000 ascii file into EEGLAB
%
% Usage:
% >> OUTEEG = pop_loadbci( filename, srate );
%
% Inputs:
% filename - file name
% srate - sampling rate
%
% Outputs:
% OUTEEG - EEGLAB data structure
%
% Author: Arnaud Delorme, CNL / Salk Institute, 9 July 2002
%
% See... |
github | lcnhappe/happe-master | pop_fileio.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_fileio.m | 7,131 | utf_8 | 9330dd4ef5ede2f403e6e848748bfd57 | % pop_fileio() - import data files into EEGLAB using FileIO
%
% Usage:
% >> OUTEEG = pop_fileio; % pop up window
% >> OUTEEG = pop_fileio( filename );
%
% Inputs:
% filename - [string] file name
%
% Optional inputs:
% 'channels' - [integer array] list of channel indices
% 'samples' - [min max] sample po... |
github | lcnhappe/happe-master | pop_compareerps.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_compareerps.m | 2,848 | utf_8 | d0e259f378ec39efae7121f2225f9cbf | % pop_compareerps() - Compare the (ERP) averages of two datasets.
%
% Usage:
% >> pop_compareerps( ALLEEG, datasetlist, chansubset, title);
% Inputs:
% ALLEEG - array of datasets
% datasetlist - list of datasets
% chansubset - vector of channel subset
% title - plot title
%
% Author: Arnaud De... |
github | lcnhappe/happe-master | importevent.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/importevent.m | 16,193 | utf_8 | 3c5abc8a8b32a3fe9ba00144fbaed59d | % importevent() - Import experimental events from data file or Matlab
% array into a structure.
%
% Usage: >> eventstruct = importevent( event, oldevent, srate);
% >> eventstruct = importevent( event, oldevent, srate, 'key1', 'value1', ...);
%
% Input:
% event - [ 'filename'|array ] Filenam... |
github | lcnhappe/happe-master | pop_saveset.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_saveset.m | 12,652 | utf_8 | f327353b0e7ee940640ebfd448f68f9d | % pop_saveset() - save one or more EEG dataset structures
%
% Usage:
% >> pop_saveset( EEG ); % use an interactive pop-up window
% >> EEG = pop_saveset( EEG, 'key', 'val', ...); % no pop-up
%
% Inputs:
% EEG - EEG dataset structure. May only contain one datase... |
github | lcnhappe/happe-master | eeg_pv.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_pv.m | 8,193 | utf_8 | 23a0d260095460fdd46f49f5060dcf52 | % eeg_pv() - Compute EEG.data 'percent variance ' (pv) of the whole EEG data versus the projections
% of specified components.
% Can omit specified components and channels from the computation. Can draw a plot
% of the scalp distribution of pv, or progressively compute the pv ... |
github | lcnhappe/happe-master | eeg_epoch2continuous.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_epoch2continuous.m | 1,716 | utf_8 | 79ffa71e29359c2ca1a0f21c2caf95cf | % eeg_epoch2continuous() - convert epoched dataset to continuous dataset
% with data epochs separated by boundary events.
% Usage:
% >> EEGOUT = eeg_epoch2continuous(EEGIN);
%
% Inputs:
% EEGIN - a loaded epoched EEG dataset structure.
%
% Inputs:
% EEGOUT - a continuous EEG data... |
github | lcnhappe/happe-master | eeg_interp.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_interp.m | 14,002 | utf_8 | 05337b7e8a6e06975f7173af18eec59a | % eeg_interp() - interpolate data channels
%
% Usage: EEGOUT = eeg_interp(EEG, badchans, method);
%
% Inputs:
% EEG - EEGLAB dataset
% badchans - [integer array] indices of channels to interpolate.
% For instance, these channels might be bad.
% [chanlocs structure] channe... |
github | lcnhappe/happe-master | pop_editeventvals.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_editeventvals.m | 25,793 | utf_8 | de89caf08acbbceb7572ea96a994e688 | % pop_editeventvals() - Edit events contained in an EEG dataset structure.
% If the dataset is the only input, a window pops up
% allowing the user to insert the relevant parameter values.
%
% Usage: >> EEGOUT = pop_editeventvals( EEG, 'key1', value1, ...
% ... |
github | lcnhappe/happe-master | pop_icathresh.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_icathresh.m | 14,758 | utf_8 | 365bfcb08f0dd1c0da09de203c810155 | % pop_icathresh() - main menu for choosing threshold for component
% rejection in EEGLAB.
%
% Usage:
% >> [OUTEEG rej] = pop_icathresh(INEEG, threshval, rejmethod,
% rejvalue, interact);
%
% Inputs:
% INEEG - input dataset
% threshval - values of t... |
github | lcnhappe/happe-master | pop_eegthresh.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_eegthresh.m | 10,919 | utf_8 | 9d094caa6dcd548bca0d55978b85170a | % pop_eegthresh() - reject artifacts by detecting outlier values. This has
% long been a standard method for selecting data to reject.
% Applied either for electrode data or component activations.
% Usage:
% >> pop_eegthresh( INEEG, typerej); % pop-up interactive window
% >> [E... |
github | lcnhappe/happe-master | pop_timef.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_timef.m | 8,964 | utf_8 | 479d128417dbb0d8ab96a1795c580e3b | % pop_timef() - Returns estimates and plots of event-related (log) spectral
% perturbation (ERSP) and inter-trial coherence (ITC) changes
% timelocked to a set of input events in one data channel.
%
% Usage:
% >> pop_timef(EEG, typeplot); % pop_up window
% >> pop_timef(EEG, typeplot, lastcom);... |
github | lcnhappe/happe-master | eeg_chantype.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_chantype.m | 2,353 | utf_8 | cc106eb578fad38a9d0ce04e66c68cc5 | % eeg_chantype() - Returns the channel indices of the desired channel type(s).
%
% Usage:
% >> indices = eeg_chantype(struct, types )
%
% Inputs:
% struct - EEG.chanlocs data structure returned by readlocs() containing
% channel location, type and gain information.
%
% Optional input
% types ... |
github | lcnhappe/happe-master | eeg_eegrej.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_eegrej.m | 7,999 | utf_8 | 3b125781cbf3005ebe8633b783f823ce | % eeg_eegrej() - reject porition of continuous data in an EEGLAB
% dataset
%
% Usage:
% >> EEGOUT = eeg_eegrej( EEGIN, regions );
%
% Inputs:
% INEEG - input dataset
% regions - array of regions to suppress. number x [beg end] of
% regions. 'beg' and 'end' are expressed in... |
github | lcnhappe/happe-master | eeg_point2lat.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_point2lat.m | 3,118 | utf_8 | e0dbc1311eceee071f6dcfb1dfcfb9bb | % eeg_point2lat() - convert latency in data points to latency in ms relative
% to the time locking. Used in eeglab().
% Usage:
% >> [newlat ] = eeg_point2lat( lat_array, [], srate);
% >> [newlat ] = eeg_point2lat( lat_array, epoch_array,...
% srate, timelimi... |
github | lcnhappe/happe-master | pop_averef.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_averef.m | 2,591 | utf_8 | 13d6362c4bcdd4d0c831e5b62379549f | % pop_averef() - Convert an EEG dataset to average reference.
% This function is obsolete. See pop_reref() instead.
%
% Usage:
% >> EEGOUT = pop_averef( EEG );
%
% Author: Arnaud Delorme, CNL / Salk Institute, 22 March 2002
%
% See also: eeglab(), reref(), averef()
% Copyright (C) 22 March 2002 Ar... |
github | lcnhappe/happe-master | eeg_matchchans.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_matchchans.m | 5,088 | utf_8 | 070c5b272529f4f74dc88932ce5baa77 | % eeg_matchchans() - find closest channels in a larger EEGLAB chanlocs structure
% to channels in a smaller chanlocs structure
% Usage:
% >> [selchans,distances,selocs] = eeg_matchchans(BIGlocs,smalllocs,'noplot');
% Inputs:
% BIGlocs - larger (or equal-sized) EEG.chanlocs structur... |
github | lcnhappe/happe-master | eeg_insertbound.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_insertbound.m | 5,043 | utf_8 | a3e502740369f695218d0309e13a6578 | % eeg_insertbound() - insert boundary event in an EEG event structure.
%
% Usage:
% >> [eventout indnew] = eeg_insertbound( eventin, pnts, ...
% abslatency, duration);
% Required Inputs:
% eventin - EEGLAB event structure (EEG.event)
% pnts - data points... |
github | lcnhappe/happe-master | pop_reref.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_reref.m | 12,991 | utf_8 | 14d26bdeeaca5ad12a0890e8f01c25df | % pop_reref() - Convert an EEG dataset to average reference or to a
% new common reference channel (or channels). Calls reref().
% Usage:
% >> EEGOUT = pop_reref( EEG ); % pop up interactive window
% >> EEGOUT = pop_reref( EEG, ref, 'key', 'val' ...);
%
% Graphic interface:
% "Compute averag... |
github | lcnhappe/happe-master | eeg_dipselect.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_dipselect.m | 2,895 | utf_8 | b9770dbf991cd2bc42e30f80792ce7a4 | % eeg_dipselect() - select componet dipoles from an EEG dataset with
% reisdual variance (rv) less than a selected threshold
% and equivalent dipole location inside the brain volume.
% Usage:
% >> selctedComponents = eeg_dipselect(EEG, rvThreshold, selectionType, depthThreshold)
... |
github | lcnhappe/happe-master | pop_loadcnt.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_loadcnt.m | 9,914 | utf_8 | 196225b3e7d78dc84817620c2a7cffab | % pop_loadcnt() - load a neuroscan CNT file (pop out window if no arguments).
%
% Usage:
% >> EEG = pop_loadcnt; % pop-up window mode
% >> EEG = pop_loadcnt( filename, 'key', 'val', ...);
%
% Graphic interface:
% "Data fomat" - [checkbox] 16-bits or 32-bits. We couldn't find in the
% data file w... |
github | lcnhappe/happe-master | eeg_amplitudearea.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_amplitudearea.m | 7,019 | utf_8 | 712e8efc8565d2b601dd9ec225a4d36c | % eeg_amplitudearea() - Resamples an ERP average using spline interpolation
% at a new sample rate (resrate) in Hz to get the exact limits
% of the window of integration. Finely samples the window
% and adds together very narrow rectangles capped by
... |
github | lcnhappe/happe-master | pop_eegplot.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_eegplot.m | 9,395 | utf_8 | 694d3469c8e08a65956f474715744049 | % pop_eegplot() - Visually inspect EEG data using a scrolling display.
% Perform rejection or marking for rejection of visually
% (and/or previously) selected data portions (i.e., stretches
% of continuous data or whole data epochs).
% Usage:
% >> pop_eegplot( EEG ) %... |
github | lcnhappe/happe-master | pop_editset.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_editset.m | 29,573 | utf_8 | d0871f09de508485acd7c591ec9228ae | % pop_editset() - Edit EEG dataset structure fields.
%
% Usage:
% >> EEGOUT = pop_editset( EEG ); % pops-up a data entry window
% >> EEGOUT = pop_editset( EEG, 'key', val,...); % no pop-up window
%
% Graphic interface:
% "Dataset name" - [Edit box] Name for the new dataset.
% In the right column... |
github | lcnhappe/happe-master | pop_snapread.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_snapread.m | 3,759 | utf_8 | 28b076d60861433397b0c0dd49338875 | % pop_snapread() - load an EEG SnapMaster file (pop out window if no arguments).
%
% Usage:
% >> [dat] = pop_snapread( filename, gain);
%
% Graphic interface:
% "Relative gain" - [edit box] to compute the relative gain, fisrt look at
% the text header of the snapmater file with a text editor.
% ... |
github | lcnhappe/happe-master | eeg_decodechan.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_decodechan.m | 3,799 | utf_8 | 600c82eb2fe26e4e9b5b1d1af79b383d | % eeg_decodechan() - given an input EEG dataset structure, output a new EEG data structure
% retaining and/or excluding specified time/latency, data point, channel,
% and/or epoch range(s).
% Usage:
% >> [chaninds chanlist] = eeg_decodechan(chanlocs, chanlist);
%
% Inputs:
% chanlocs... |
github | lcnhappe/happe-master | eeg_getica.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_getica.m | 1,704 | utf_8 | 00350d1cd6a4ab711db93297dd29454d | % eeg_getica() - get ICA component activation. Recompute if necessary.
%
% >> mergelocs = eeg_getica(EEG, comp);
%
% Inputs:
% EEG - EEGLAB dataset structure
% comp - component index
%
% Output:
% icaact - ICA component activity
%
% Author: Arnaud Delorme, 2006
% Copyright (C) Arnaud Delorme, CER... |
github | lcnhappe/happe-master | pop_mergeset.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_mergeset.m | 13,668 | utf_8 | 307f42bbcf51af31a20f499cdc766249 | % pop_mergeset() - Merge two or more datasets. If only one argument is given,
% a window pops up to ask for more arguments.
% Usage:
% >> OUTEEG = pop_mergeset( ALLEEG ); % use a pop-up window
% >> OUTEEG = pop_mergeset( ALLEEG, indices, keepall);
% >> OUTEEG = pop_mergeset( INEEG1, INEEG2, keepa... |
github | lcnhappe/happe-master | pop_importevent.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_importevent.m | 12,593 | utf_8 | 6b64e9391f0dca41020312951341bd55 | % pop_importevent() - Import events into an EEG dataset. If the EEG dataset
% is the only input, a window pops up to ask for the relevant
% parameter values.
%
% Usage: >> EEG = pop_importevent( EEG ); % pop-up window mode
% >> EEG = pop_importevent( EEG, 'key1', 'value1', ...);
%
% Gr... |
github | lcnhappe/happe-master | eeg_eventtypes.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/eeg_eventtypes.m | 5,504 | utf_8 | d106acb9a7c18278b36620b4a206edb5 | % eeg_eventtypes() - return a list of event or urevent types in a dataset and
% the respective number of events of each type. Ouput event
% types are sorted in reverse order of their number. If no
% outputs, print this list on the commandline instead.
%
% ... |
github | lcnhappe/happe-master | pop_signalstat.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_signalstat.m | 5,079 | utf_8 | 5066bdd6d63e075bfeaf649483b7b2bb | % pop_signalstat() - Computes and plots statistical characteristics of a signal,
% including the data histogram, a fitted normal distribution,
% a normal ditribution fitted on trimmed data, a boxplot, and
% the QQ-plot. The estimates value are printed in a panel ... |
github | lcnhappe/happe-master | pop_rejchanspec.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_rejchanspec.m | 10,691 | utf_8 | 8549b5c2d8a05e2ca0aa177b4a248efc | % pop_rejchanspec() - reject artifacts channels in an EEG dataset using
% channel spectrum. The average spectrum for all selected
% is computed and a threshold is applied.
%
% Usage:
% >> pop_rejchanspec( INEEG ) % pop-up interative window mode
% >> [OUTEEG, indelec] = pop_rejchan... |
github | lcnhappe/happe-master | pop_rejtrend.m | .m | happe-master/Packages/eeglab14_0_0b/functions/popfunc/pop_rejtrend.m | 9,362 | utf_8 | 8dba06eafda1461d9b44d39f9dfa3e5f | % pop_rejtrend() - Measure linear trends in EEG data; reject data epochs
% containing strong trends.
% Usage:
% >> pop_rejtrend( INEEG, typerej); % pop up an interactive window
% >> OUTEEG = pop_rejtrend( INEEG, typerej, elec_comp, ...
% winsize, maxslope, minR, superpose, reject,ca... |
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