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erpimage_ql.m
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% erpimage() - Plot a colored image of a collection of single-trial data epochs, optionally
% sorted on and/or aligned to an input sorting variable and smoothed across
% trials with a Gaussian weighted moving-average. (To return event-aligned data
% without plotting, use eegalign()). Optionally sort trials on value, amplitude
% or phase within a specified latency window. Optionally plot the ERP mean
% and std. dev.and moving-window spectral amplitude and inter-trial coherence
% at aselected or peak frequency. Optionally 'time warp' the single trial
% time-domain (potential) or power data to align the plotted data to a series
% of events with varying latencies that occur in each trial. Click on
% individual figures parts to examine them separately and zoom (using axcopy()).
% Usage:
% >> figure; erpimage(data,[],times); % image trials as colored lines in input order
%
% >> figure; [outdata,outvar,outtrials,limits,axhndls, ...
% erp,amps,cohers,cohsig,ampsig,outamps,...
% phsangls,phsamp,sortidx,erpsig] ...
% = erpimage(data,sortvar,times,'title',avewidth,decimate,...
% 'key', 'val', ...); % use options
% Required input:
% data = [vector or matrix] Single-channel input data to image.
% Formats (1,frames*trials) or (frames,trials)
%
% Optional ordered inputs {with defaults}:
%
% sortvar = [vector | []] Variable to sort epochs on (length(sortvar) = nepochs)
% Example: sortvar may by subject response time in each epoch (in ms)
% {default|[]: plot in input order}
% times = [vector | []] vector of latencies (in ms) for each epoch time point.
% Else [startms ntimes srate] = [start latency (ms), time points
% (=frames) per epoch, sampling rate (Hz)]. Else [] -> 0:nframes-1
% {default: []}
% 'title' = ['string'] Plot title {default: none}
% avewidth = [positive scalar (may be non-integer)]. If avg_type is set to 'boxcar'
% (the default), this is the number of trials used to smooth
% (vertically) with a moving-average. If avg_type is set to
% 'Gaussian,' this is the standard deviation (in units of
% trials) of the Gaussian window used to smooth (vertically)
% with a moving-average. Gaussian window extends three
% standard deviations below and three standard deviations above window
% center (trials beyond window are not incorporated into average). {default: no
% smoothing}
% decimate = Factor to decimate|interpolate ntrials by (may be non-integer)
% Else, if this is large (> sqrt(ntrials)), output this many epochs.
% {default|0->1}
%
% Optional unordered 'keyword',argument pairs:
%
% Re-align data epochs:
% 'align' = [latency] Time-lock data to sortvar. Plot sortvar at given latency
% (in ms). Else Inf -> plot sortvar at median sortvar latency
% {default: do not align}
% 'timewarp' = {[events], [warpms], {colors}} Time warp ERP, amplitude and phase
% time-courses before smoothing. 'events' is a matrix whose columns
% specify the latencies (in ms) at which a series of successive events occur
% in each trial. 'warpms' is an optional vector of latencies (in ms) to which
% the series of events should be time locked. (Note: Epoch start and end
% should not be declared as events or warpms}. If 'warpms' is absent or [],
% the median of each 'events' column will be used. {colors} contains a
% list of Matlab linestyles to use for vertical lines marking the occurrence
% of the time warped events. If '', no line will be drawn for this event
% column. If fewer colors than event columns, cycles through the given color
% labels. Note: Not compatible with 'vert' (below).
% 'renorm' = ['yes'|'no'| formula] Normalize sorting variable to epoch
% latency range and plot. 'yes'= autoscale. formula must be a linear
% transformation in the format 'a*x+b'
% Example of formula: '3*x+2'. {default: 'no'}
% If sorting by string values like event type, suggested formulas for:
% letter string: '1000*x', number string: '30000*x-1500'
% 'noplot' = ['on'|'off'] Do not plot sortvar {default: Plot sortvar if in times range}
% 'NoShow' = ['on'|'off'] Do not plot erpimage, simply return outputs {default: 'off'}
%
% Sort data epochs:
% 'nosort' = ['on'|'off'] Do not sort data epochs. {default: Sort data epochs by
% sortvar (see sortvar input above)}
% 'replace_ties' = ['yes'|'no'] Replace trials with the same value of
% sortvar with the mean of those trials. Only works if sorting trials
% by sortvar. {default: 'no'}
% 'valsort' = [startms endms direction] Sort data on (mean) value
% between startms and (optional) endms. Direction is 1 or -1.
% If -1, plot max-value epoch at bottom {default: sort on sortvar}
% 'phasesort' = [ms_center prct freq maxfreq topphase] Sort epochs by phase in
% a 3-cycle window centered at latency ms_center (ms).
% Percentile (prct) in range [0,100] gives percent of trials
% to reject for (too) low amplitude. Else, if in range [-100,0],
% percent of trials to reject for (too) high amplitude;
% freq (Hz) is the phase-sorting frequency. With optional
% maxfreq, sort by phase at freq of max power in the data in
% the range [freq,maxfreq] (Note: 'phasesort' arg freq overrides
% the frequency specified in 'coher'). With optional topphase,
% sort by phase, putting topphase (degrees, in range [-180,180])
% at the top of the image. Note: 'phasesort' now uses circular
% smoothing. Use 'cycles' (below) for wavelet length.
% {default: [0 25 8 13 180]}
% 'ampsort' = [center_ms prcnt freq maxfreq] Sort epochs by amplitude.
% (See 'phasesort' above). If ms_center is 'Inf', then sorting
% is by mean power across the time window specified by 'sortwin'
% below. If third arg, freq, is < 0, sort by mean power in the range
% [ abs(freq) maxfreq ].
% 'sortwin' = [start_ms end_ms] If center_ms == Inf in 'ampsort' arg (above), sorts
% by mean amplitude across window centers shifted from start_ms
% to end_ms by 10 ms.
% 'showwin' = ['on'|'off'] Show sorting window behind ERP trace. {default: 'off'}
%
% Plot time-varying spectral amplitude instead of potential:
% 'plotamps' = ['on'|'off'] Image amplitudes at each trial and latency instead of
% potential values. Note: Currently requires 'coher' (below) with alpha signif.
% Use 'cycles' (see below) > (its default) 3 for better frequency specificity,
% {default: plot potential, not amplitudes, with no minimum}. The average power
% (in log space) before time 0 is automatically removed. Note that the
% 'baseline' parameter has no effect on 'plotamps'. Instead use
% change "baselinedb" or "basedB" in the 'limits' parameter. By default
% the baseline is removed before time 0.
%
% Specify plot parameters:
% 'limits' = [lotime hitime minerp maxerp lodB hidB locoher hicoher basedB]
% Plot axes limits. Can use NaN (or nan, but not Nan) for missing items
% and omit late items. Use last input, basedB, to set the
% baseline dB amplitude in 'plotamps' plots {default: from data}
% 'sortvar_limits' = [min max] minimum and maximum sorting variable
% values to image. This only affects visualization of
% ERPimage and ERPs (not smoothing). Cannot be used
% if sorting by any factor besides sortvar (e.g.,
% phase).
% 'signif' = [lo_dB, hi_dB, coher_signif_level] Use precomputed significance
% thresholds (as from outputs ampsig, cohsig) to save time. {default: none}
% 'caxis' = [lo hi] Set color axis limits. Else [fraction] Set caxis limits at
% (+/-)fraction*max(abs(data)) {default: symmetrical in dB, based on data limits}
%
% Add epoch-mean ERP to plot:
% 'erp' = ['on'|'off'|1|2|3|4] Plot ERP time average of the trials below the
% image. If 'on' or 1, a single ERP (the mean of all trials) is shown. If 2,
% two ERPs (super and sub median trials) are shown. If 3, the trials are split into
% tertiles and their three ERPs are shown. If 4, the trials are split into quartiles
% and four ERPs are shown. Note, if you want negative voltage plotted up, change YDIR
% to -1 in icadefs.m. If 'erpalpha' option is used, any values of 'erp' greater than
% 1 will be reset to 1. {default no ERP plotted}
% 'erpalpha' = [alpha] Visualizes two-sided significance threshold (i.e., a two-tailed test) for the
% null hypothesis of a zero mean, symmetric distribution (range: [.001 0.1]). Thresholds
% are determined via a permutation test. Requires 'erp' to be a value other than 'off'.
% If 'erp' is set to a value greater than 1, it is reset to 1 to increase plot readability.
% {default: no alpha significance thresholds plotted}
% 'erpstd' = ['on'|'off'] Plot ERP +/- stdev. Requires 'erp' {default: no std. dev. plotted}
% 'erp_grid' = If 'erp_grid' is added as an option voltage axis dashed grid lines will be
% added to the ERP plot to facilitate judging ERP amplitude
% 'rmerp' = ['on'|'off'] Subtract the average ERP from each trial before processing {default: no}
%
% Add time/frequency information:
% 'coher' = [freq] Plot ERP average plus mean amplitude & coherence at freq (Hz)
% Else [minfrq maxfrq] = same, but select frequency with max power in
% given range. (Note: the 'phasesort' freq (above) overwrites these
% parameters). Else [minfrq maxfrq alpha] = plot coher. signif. level line
% at probability alpha (range: [0,0.1]) {default: no coher, no alpha level}
% 'srate' = [freq] Specify the data sampling rate in Hz for amp/coher (if not
% implicit in third arg, times) {default: as defined in icadefs.m}
% 'cycles' = [float] Number of cycles in the wavelet time/frequency decomposition {default: 3}
%
% Add plot features:
% 'cbar' = ['on'|'off'] Plot color bar to right of ERP-image {default no}
% 'cbar_title' = [string] The title for the color bar (e.g., '\muV' for
% microvolts).
% 'topo' = {map,chan_locs,eloc_info} Plot a 2-D scalp map at upper left of image.
% map may be a single integer, representing the plotted data channel,
% or a vector of scalp map channel values. chan_locs may be a channel locations
% file or a chanlocs structure (EEG.chanlocs). See '>> topoplot example'
% eloc_info (EEG.chaninfo), if empty ([]) or absent, implies the 'X' direction
% points towards the nose and all channels are plotted {default: no scalp map}
% 'spec' = [loHz,hiHz] Plot the mean data spectrum at upper right of image.
% 'specaxis' = ['log'|'lin] Use 'lin' for linear spectrum frequency scaling,
% else 'log' for log scaling {default: 'log'}
% 'horz' = [epochs_vector] Plot horizontal lines at specified epoch numbers.
% 'vert' = [times_vector] Plot vertical dashed lines at specified latencies
% 'auxvar' = [size(nvars,ntrials) matrix] Plot auxiliary variable(s) for each trial
% as separate traces. Else, 'auxvar',{[matrix],{colorstrings}}
% to specify N trace colors. Ex: colorstrings = {'r','bo-','','k:'}
% (see also: 'vert' and 'timewarp' above). {default: none}
% 'sortvarpercent' = [float vector] Plot percentiles for the sorting variable
% for instance, [0.1 0.5 0.9] plots the 10th percentile, the median
% and the 90th percentile.
% Plot options:
% 'noxlabel' = ['on'|'off'] Do not plot "Time (ms)" on the bottom x-axis
% 'yerplabel' = ['string'] ERP ordinate axis label (default is ERP). Print uV with '\muV'
% 'avg_type' = ['boxcar'|'Gaussian'] The type of moving average used to smooth
% the data. 'Boxcar' smoothes the data by simply taking the mean of
% a certain number of trials above and below each trial.
% 'Gaussian' does the same but first weights the trials
% according to a Gaussian distribution (e.g., nearby trials
% receive greater weight). The Gaussian is better than the
% boxcar in that it rather evenly filters out high frequency
% vertical components in the ERPimage. See 'avewidth' argument
% description for more information. {default: boxcar}
% 'img_trialax_label' = ['string'] The label of the axis corresponding to trials in the ERPimage
% (e.g., 'Reaction Time'). Note, if img_trialax_label is set to something
% besides 'Trials' or [], the tick marks on this axis will be set in units
% of the sorting variable. This is a useful alternative to plotting the
% sorting variable when the sorting variable is not in milliseconds. This
% option is not effective if sorting by amplitude, phase, or EEG value. {default: 'Trials'}
% 'img_trialax_ticks' = Vector of sorting variable values at which tick marks (e.g., [300 350 400 450]
% for reaction time in msec) will appear on the trial axis of the erpimage. Tick mark
% values should be given in units img_trialax_label (e.g., 'Trials' or msec).
% This option is not effective if sorting by amplitude, phase, or EEG value.
% {default: automatic}
% 'baseline' = [low_boundary high_boundary] a time window (in msec) whose mean amplitude in
% each trial will be removed from each trial (e.g., [-100 0]) after filtering.
% Useful in conjunction with 'filt' option to re-basline trials after they have been
% filtered. Not necessary if data have already been baselined and erpimage
% processing does not affect baseline amplitude {default: no further baselining
% of data}.
% 'baselinedb' = [low_boundary high_boundary] a time window (in msec) whose mean amplitude in
% each trial will be removed from each trial (e.g., [-100 0]). Use basedB in limits
% to remove a fixed value. Default is time before 0. If you do not want to use a
% baseline for amplitude plotting, enter a NaN value.
% 'filt' = [low_boundary high_boundary] a two element vector indicating the frequency
% cut-offs for a 3rd order Butterworth filter that will be applied to each
% trial of data. If low_boundary=0, the filter is a low pass filter. If
% high_boundary=srate/2, then the filter is a high pass filter. If both
% boundaries are between 0 and srate/2, then the filter is a bandpass filter.
% If both boundaries are between 0 and -srate/2, then the filter is a bandstop
% filter (with boundaries equal to the absolute values of low_boundary and
% high_boundary). Note, using this option requires the 'srate' option to be
% specified and the signal processing toolbox function butter.m. You should
% probably use the 'baseline' option as well since the mean prestimulus baseline
% may no longer be 0 after the filter is applied {default: no filtering}
%
% Optional outputs:
% outdata = (times,epochsout) data matrix (after smoothing)
% outvar = (1,epochsout) actual values trials are sorted on (after smoothing).
% if 'sortvarpercent' is used, this variable contains a cell array with
% { sorted_values { sorted_percent1 ... sorted_percentN } }
% outtrials = (1,epochsout) smoothed trial numbers
% limits = (1,10) array, 1-9 as in 'limits' above, then analysis frequency (Hz)
% axhndls = vector of 1-7 plot axes handles (img,cbar,erp,amp,coh,topo,spec)
% erp = plotted ERP average
% amps = mean amplitude time course
% coher = mean inter-trial phase coherence time course
% cohsig = coherence significance level
% ampsig = amplitude significance levels [lo high]
% outamps = matrix of imaged amplitudes (from option 'plotamps')
% phsangls = vector of sorted trial phases at the phase-sorting frequency
% phsamp = vector of sorted trial amplitudes at the phase-sorting frequency
% sortidx = indices of input data epochs in the sorting order
% erpsig = trial average significance levels [2,frames]
%
% Example: >> figure;
% erpimage(data,RTs,[-400 256 256],'Test',1,1,...
% 'erp','cbar','vert',-350);
% Plots an ERP-image of 1-s data epochs sampled at 256 Hz, sorted by RTs, with
% title ('Test'), and sorted epochs not smoothed or decimated (1,1). Overplots
% the (unsmoothed) RT latencies on the colored ERP-image. Also plots the
% epoch-mean (ERP), a color bar, and a dashed vertical line at -350 ms.
%
% Authors: Scott Makeig, Tzyy-Ping Jung & Arnaud Delorme,
% CNL/Salk Institute, La Jolla, 3-2-1998 -
%
% See also: phasecoher, rmbase, cbar, movav
% Copyright (C) Scott Makeig & Tzyy-Ping Jung, CNL / Salk Institute, La Jolla 3-2-98
%
% 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 permitted provided that the following conditions are met:
%
% 1. Redistributions of source code must retain the above copyright notice,
% this list of conditions and the following disclaimer.
%
% 2. Redistributions in binary form must reproduce the above copyright notice,
% this list of conditions and the following disclaimer in the documentation
% and/or other materials provided with the distribution.
%
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
% CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
% SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
% INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
% THE POSSIBILITY OF SUCH DAMAGE.
% Uses external toolbox functions: phasecoher(), rmbase(), cbar(), movav()
% Uses included functions: plot1trace(), phasedet()
% UNIMPLEMENTED - 'allcohers',[data2] -> image the coherences at each latency & epoch.
% Requires arg 'coher' with alpha significance.
% Shows projection on grand mean coherence vector at each latency
% and trial. {default: no}
%% LOG COMMENTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [data,outsort,outtrials,limits,axhndls,erp,amps,cohers,cohsig,ampsig,allamps,phaseangles,phsamp,sortidx,erpsig] = erpimage(data,sortvar,times,titl,avewidth,decfactor,arg1,arg2,arg3,arg4,arg5,arg6,arg7,arg8,arg9,arg10,arg11,arg12,arg13,arg14,arg15,arg16,arg17,arg18,arg19,arg20,arg21,arg22,arg23,arg24,arg25,arg26,arg27,arg28,arg29,arg30,arg31,arg32,arg33,arg34,arg35,arg36,arg37,arg38,arg39,arg40,arg41,arg42,arg43,arg44,arg45,arg46,arg47,arg48,arg49,arg50,arg51,arg52,arg53,arg54,arg55,arg56,arg57,arg58,arg59,arg60,arg61,arg62,arg63,arg64,arg65,arg66)
%
%% %%%%%%%%%%%%%%%%% Define defaults %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Initialize optional output variables:
warning off;
erp = []; amps = []; cohers = []; cohsig = []; ampsig = [];
allamps = []; phaseangles = []; phsamp = []; sortidx = [];
auxvar = []; erpsig = []; winloc = [];winlocs = [];
timeStretchColors = {};
YES = 1; % logical variables
NO = 0;
DEFAULT_BASELINE_END = 0; % ms
TIMEX = 1; % 1 -> plot time on x-axis;
% 0 -> plot trials on x-axis
BACKCOLOR = [0.8 0.8 0.8]; % grey background
try, icadefs; catch, end
% read BACKCOLOR for plot from defs file (edit this)
% read DEFAULT_SRATE for coher,phase,allamps, etc.
% read YDIR for plotting ERP
% Fix plotting text and line style parameters
SORTWIDTH = 2.5; % Linewidth of plotted sortvar
ZEROWIDTH = 3.0; % Linewidth of vertical 0 line
VERTWIDTH = 2.5; % Linewidth of optional vertical lines
HORZWIDTH = 2.1; % Linewidth of optional vertical lines
SIGNIFWIDTH = 1.9; % Linewidth of red significance lines for amp, coher
DOTSTYLE = 'k--'; % line style to use for vetical dotted/dashed lines
LINESTYLE = '-'; % solid line
LABELFONT = 10; % font sizes for axis labels, tick labels
TICKFONT = 10;
PLOT_HEIGHT = 0.2; % fraction of y dim taken up by each time series axes
YGAP = 0.03; % fraction gap between time axes
YEXPAND = 1.3; % expansion factor for y-axis about erp, amp data limits
DEFAULT_SDEV = 1/7; % smooth trials with this window size by default if Gaussian window
DEFAULT_AVEWIDTH = 1; % smooth trials with this window size by default
DEFAULT_DECFACTOR = 1; % decimate by this factor by default
DEFAULT_CYCLES = 3; % use this many cycles in amp,coher computation window
cycles = DEFAULT_CYCLES;
DEFAULT_CBAR = NO;% do not plot color bar by default
DEFAULT_PHARGS = [0 25 8 13]; % Default arguments for phase sorting
DEFAULT_ALPHA = 0.01;
alpha = 0; % default alpha level for coherence significance
MIN_ERPALPHA = 0.001; % significance bounds for ERP
MAX_ERPALPHA = 0.1;
NoShowVar = NO; % show sortvar by default
Nosort = NO; % sort on sortvar by default
Caxflag = NO; % use default caxis by default
timestretchflag = NO; % Added -JH
mvavg_type='boxcar'; % use the original rectangular moving average -DG
erp_grid = NO; % add y-tick grids to ERP plot -DG
cbar_title = []; % title to add above ERPimage color bar (e.g., '\muV') -DG
img_ylab = 'Trials'; % make the ERPimage y-axis in units of the sorting variable -DG
img_ytick_lab = []; % the values at which tick marks will appear on the trial axis of the ERPimage (the y-axis by default).
%Note, this is in units of the sorting variable if img_ylab~='Trials', otherwise it is in units of trials -DG
baseline = []; %time window of each trial whose mean amp will be used to baseline the trial -DG
baselinedb = []; %time window of each trial whose mean power will be used to baseline the trial
flt=[]; %frequency domain filter parameters -DG
sortvar_limits=[]; %plotting limits for sorting variable/trials; limits only affect visualization, not smoothing -DG
replace_ties = NO; %if YES, trials with the exact same value of a sorting variable will be replaced by their average -DG
erp_vltg_ticks=[]; %if non-empty, these are the voltage axis ticks for the ERP plot
Caxis = [];
caxfraction = [];
Coherflag = NO; % don't compute or show amp,coher by default
Cohsigflag= NO; % default: do not compute coherence significance
Allampsflag=NO; % don't image the amplitudes by default
Allcohersflag=NO; % don't image the coherence amplitudes by default
Topoflag = NO; % don't plot a topoplot in upper left
Specflag = NO; % don't plot a spectrum in upper right
SpecAxisflag = NO; % don't change the default spectrum axis type from default
SpecAxis = 'log'; % default log frequency spectrum axis (if Specflag)
Erpflag = NO; % don't show erp average by default
Erpstdflag= NO;
Erpalphaflag= NO;
Alignflag = NO; % don't align data to sortvar by default
Colorbar = NO; % if YES, plot a colorbar to right of erp image
Limitflag = NO; % plot whole times range by default
Phaseflag = NO; % don't sort by phase
Ampflag = NO; % don't sort by amplitude
Sortwinflag = NO; % sort by amplitude over a window
Valflag = NO; % don't sort by value
Srateflag = NO; % srate not given
Vertflag = NO;
Horzflag = NO;
titleflag = NO;
NoShowflag = NO;
Renormflag = NO;
Showwin = NO;
yerplabel = '';
yerplabelflag = NO;
verttimes = [];
horzepochs = [];
NoTimeflag= NO; % by default DO print "Time (ms)" below bottom axis
Signifflag= NO; % compute significance instead of receiving it
Auxvarflag= NO;
plotmodeflag= NO;
plotmode = 'normal';
Cycleflag = NO;
signifs = NaN;
coherfreq = nan; % amp/coher-calculating frequency
freq = 0; % phase-sorting frequency
srate = DEFAULT_SRATE; % from icadefs.m
aligntime = nan;
timelimits= nan;
topomap = []; % topo map vector
lospecHz = []; % spec lo frequency
topphase = 180; % default top phase for 'phase' option
renorm = 'no';
NoShow = 'no';
Rmerp = 'no';
percentiles = [];
percentileflag = NO;
erp_ptiles = 1;
minerp = NaN; % default limits
maxerp = NaN;
minamp = NaN;
maxamp = NaN;
mincoh = NaN;
maxcoh = NaN;
baseamp =NaN;
allamps = []; % default return
ax1 = NaN; % default axes handles
axcb = NaN;
ax2 = NaN;
ax3 = NaN;
ax4 = NaN;
timeStretchRef = [];
timeStretchMarks = [];
tsurdata = []; % time-stretched data before smoothing (for timestretched-erp computation)
% If time-stretching is off, this variable remains empty
%
%% %%%%%%%%%%%%%%%%% Test, fill in commandline args %%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
if nargin < 1
help erpimage
return
end
data = squeeze(data);
if nargin < 3 || isempty(times)
if size(data,1)==1 || size(data,2)==1
fprintf('\nerpimage(): either input a times vector or make data size = (frames,trials).\n')
return
end
times = 1:size(data,1);
NoTimesPassed= 1;
end
if nargin < 2 || isempty(sortvar)
sortvar = 1:size(data,2);
NoShowVar = 1; % don't plot the dummy sortvar
end
framestot = size(data,1)*size(data,2);
ntrials = length(sortvar);
if ntrials < 2
help erpimage
fprintf('\nerpimage(): too few trials.\n');
return
end
frames = floor(framestot/ntrials);
if frames*ntrials ~= framestot
help erpimage
fprintf(...
'\nerpimage(); length of sortvar doesn''t divide number of data elements??\n')
return
end
if nargin < 6
decfactor = 0;
end
if nargin < 5
avewidth = DEFAULT_AVEWIDTH;
end
if nargin<4
titl = ''; % default no title
end
if nargin<3
times = NO;
end
if (length(times) == 1) || (length(times) == 1 && times(1) == NO) % make default times
times = 0:frames-1;
srate = 1000*(length(times)-1)/(times(length(times))-times(1));
fprintf('Using sampling rate %g Hz.\n',srate);
elseif length(times) == 3
mintime = times(1);
frames = times(2);
srate = times(3);
times = mintime:1000/srate:mintime+(frames-1)*1000/srate;
fprintf('Using sampling rate %g Hz.\n',srate);
else
% Note: might use default srate read from icadefs here...
srate = 1000*(length(times)-1)/(times(end)-times(1));
end
if length(times) ~= frames
fprintf(...
'\nerpimage(): length(data)(%d) ~= length(sortvar)(%d) * length(times)(%d).\n\n',...
framestot, length(sortvar), length(times));
return
end
if decfactor == 0,
decfactor = DEFAULT_DECFACTOR;
elseif decfactor > ntrials
fprintf('Setting variable decfactor to max %d.\n',ntrials)
decfactor = ntrials;
end
%
%% %%%%%%%%%%%%%%% Collect optional args %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
if nargin > 6
flagargs = [];
a = 6;
while a < nargin % for each remaining Arg
a = a + 1;
Arg = eval(['arg' int2str(a-6)]);
if Caxflag == YES
if size(Arg,1) ~= 1 || size(Arg,2) > 2
help erpimage
fprintf('\nerpimage(): caxis arg must be a scalar or (1,2) vector.\n');
return
end
if size(Arg,2) == 2
Caxis = Arg;
else
caxfraction = Arg;
end
Caxflag = NO;
elseif timestretchflag == YES % Added -JH
timeStretchMarks = Arg{1};
timeStretchMarks = round(1+(timeStretchMarks-times(1))*srate/1000); % convert from ms to frames -sm
[smc smr] = find(diff(timeStretchMarks') < 0);
if ~isempty(smr)
fprintf('\nerpimage(): Timewarp event latencies not in ascending order in trial %d.\n',smr)
return
end
timeStretchMarks = [ ...
repmat(1, [size(timeStretchMarks,1), 1]), ...% Epoch begins
timeStretchMarks, ...
repmat(length(times), [size(timeStretchMarks,1), 1])]; % Epoch ends
if length(Arg) < 2 || isempty(Arg{2})
timeStretchRef = median(timeStretchMarks);
else
timeStretchRef = Arg{2};
timeStretchRef = round(1+(timeStretchRef-times(1))*srate/1000); % convert from ms to frames -sm
timeStretchRef = [1 timeStretchRef length(times)]; % add epoch beginning, end
end
if length(Arg) < 3 || isempty(Arg{3})
timeStretchColors = {};
else
timeStretchColors = Arg{3};
end
fprintf('The %d events specified in each trial will be time warped to latencies:',length(timeStretchRef)-2);
fprintf(' %.0f', times(1)+1000*(timeStretchRef(2:end-1)-1)/srate); % converted from frames to ms -sm
fprintf(' ms\n');
timestretchflag = NO;
elseif Coherflag == YES
if length(Arg) > 3 || length(Arg) < 1
help erpimage
fprintf('\nerpimage(): coher arg must be size <= 3.\n');
return
end
coherfreq = Arg(1);
if size(Arg,2) == 1
coherfreq = Arg(1);
else
coherfreq = Arg(1:2);
end
if size(Arg,2) == 3
Cohsigflag = YES;
alpha = Arg(3);
if alpha < 0 || alpha > 0.1
fprintf('\nerpimage(): alpha value %g out of bounds.\n',alpha);
return
end
end
Coherflag = NO;
Erpflag = YES; % plot amp, coher below erp time series
elseif Topoflag == YES;
if length(Arg) < 2
help erpimage
fprintf('\nerpimage(): topo arg must be a list of length 2 or 3.\n');
return
end
topomap = Arg{1};
eloc_file = Arg{2};
if length(Arg) > 2, eloc_info = Arg{3};
else eloc_info = [];
end
Topoflag = NO;
elseif Specflag == YES;
if length(Arg) ~= 2
error('\nerpimage(): ''spec'' flag argument must be a numeric array of length 2.\n');
return
end
lospecHz = Arg(1);
hispecHz = Arg(2);
Specflag = NO;
elseif SpecAxisflag == YES;
SpecAxis = Arg;
if ~strcmpi(SpecAxis,'lin') && ~strcmpi(SpecAxis,'log')
error('\nerpimage(): spectrum axis type must be ''lin'' or ''log''.\n');
return
end
if strcmpi(SpecAxis,'lin')
SpecAxis = 'linear'; % convert to MATLAB Xscale keyword
end
SpecAxisflag = NO;
elseif Renormflag == YES
renorm = Arg;
Renormflag = NO;
elseif NoShowflag == YES
NoShow = Arg;
if strcmpi(NoShow, 'off'), NoShow = 'no'; end
NoShowflag = NO;
elseif Alignflag == YES
aligntime = Arg;
Alignflag = NO;
elseif percentileflag == YES
percentiles = Arg;
percentileflag = NO;
elseif Limitflag == YES
% [lotime hitime loerp hierp loamp hiamp locoher hicoher]
if size(Arg,1) ~= 1 || size(Arg,2) < 2 || size(Arg,2) > 9
help erpimage
fprintf('\nerpimage(): limits arg must be a vector sized (1,2<->9).\n');
return
end
if ~isnan(Arg(1)) && (Arg(2) <= Arg(1))
help erpimage
fprintf('\nerpimage(): time limits out of order or out of range.\n');
return
end
if Arg(1) < min(times)
Arg(1) = min(times);
fprintf('Adjusting mintime limit to first data value %g\n',min(times));
end
if Arg(2) > max(times)
Arg(2) = max(times);
fprintf('Adjusting maxtime limit to last data value %g\n',max(times));
end
timelimits = Arg(1:2);
if length(Arg)> 2
minerp = Arg(3);
end
if length(Arg)> 3
maxerp = Arg(4);
end
if ~isnan(maxerp) && maxerp <= minerp
help erpimage
fprintf('\nerpimage(): erp limits args out of order.\n');
return
end
if length(Arg)> 4
minamp = Arg(5);
end
if length(Arg)> 5
maxamp = Arg(6);
end
if maxamp <= minamp
help erpimage
fprintf('\nerpimage(): amp limits args out of order.\n');
return
end
if length(Arg)> 6
mincoh = Arg(7);
end
if length(Arg)> 7
maxcoh = Arg(8);
end
if maxcoh <= mincoh
help erpimage
fprintf('\nerpimage(): coh limits args out of order.\n');
return
end
if length(Arg)>8
baseamp = Arg(9); % for 'allamps'
end
Limitflag = NO;
elseif Srateflag == YES
srate = Arg(1);
Srateflag = NO;
elseif Cycleflag == YES
cycles = Arg;
Cycleflag = NO;
elseif Auxvarflag == YES;
if isa(Arg,'cell')==YES && length(Arg)==2
auxvar = Arg{1};
auxcolors = Arg{2};
elseif isa(Arg,'cell')==YES
fprintf('\nerpimage(): auxvars argument must be a matrix or length-2 cell array.\n');
return
else
auxvar = Arg; % no auxcolors specified
end
[xr,xc] = size(auxvar);
lns = length(sortvar);
if xr ~= lns && xc ~= lns
error('\nerpimage(): auxvar columns different from the number of epochs in data');
elseif xr == lns && xc ~= lns
auxvar = auxvar'; % exchange rows/cols
end
Auxvarflag = NO;
elseif Vertflag == YES
verttimes = Arg;
Vertflag = NO;
elseif Horzflag == YES
horzepochs = Arg;
Horzflag = NO;
elseif yerplabelflag == YES
yerplabel = Arg;
yerplabelflag = NO;
elseif Signifflag == YES
signifs = Arg; % [low_amp hi_amp coher]
if length(signifs) ~= 3
fprintf('\nerpimage(): signif arg [%g] must have 3 values\n',Arg);
return
end
Signifflag = NO;
elseif Allcohersflag == YES
data2=Arg;
if size(data2) ~= size(data)
fprintf('\nerpimage(): allcohers data matrix must be the same size as data.\n');
return
end
Allcohersflag = NO;
elseif Phaseflag == YES
n = length(Arg);
if n > 5
error('\nerpimage(): Too many arguments for keyword ''phasesort''');
end
phargs = Arg;
if phargs(3) < 0
error('\nerpimage(): Invalid negative frequency argument for keyword ''phasesort''');
end
if n>=4
if phargs(4) < 0
error('\nerpimage(): Invalid negative argument for keyword ''phasesort''');
end
end
if min(phargs(1)) < times(1) || max(phargs(1)) > times(end)
error('\nerpimage(): time for phase sorting filter out of bound.');
end
if phargs(2) >= 100 || phargs(2) < -100
error('\nerpimage(): %-argument for keyword ''phasesort'' must be (-100;100)');
end
if length(phargs) >= 4 && phargs(3) > phargs(4)
error('\nerpimage(): Phase sorting frequency range must be increasing.');
end
if length(phargs) == 5
topphase = phargs(5);
end
Phaseflag = NO;
elseif Sortwinflag == YES % 'ampsort' mean amplitude over a time window
n = length(Arg);
sortwinarg = Arg;
if n > 2
error('\nerpimage(): Too many arguments for keyword ''sortwin''');
end
if min(sortwinarg(1)) < times(1) || max(sortwinarg(1)) > times(end)
error('\nerpimage(): start time for value sorting out of bounds.');
end
if n > 1
if min(sortwinarg(2)) < times(1) || max(sortwinarg(2)) > times(end)
error('\nerpimage(): end time for value sorting out of bounds.');
end
end
if n > 1 && sortwinarg(1) > sortwinarg(2)
error('\nerpimage(): Value sorting time range must be increasing.');
end
Sortwinflag = NO;
elseif Ampflag == YES % 'ampsort',[center_time,prcnt_reject,minfreq,maxfreq]
n = length(Arg);
if n > 4
error('\nerpimage(): Too many arguments for keyword ''ampsort''');
end
ampargs = Arg;
% if ampargs(3) < 0
% error('\nerpimage(): Invalid negative argument for keyword ''ampsort''');
% end
if n>=4
if ampargs(4) < 0
error('\nerpimage(): Invalid negative argument for keyword ''ampsort''');
end
end
if ~isinf(ampargs(1))
if min(ampargs(1)) < times(1) || max(ampargs(1)) > times(end)
error('\nerpimage(): time for amplitude sorting filter out of bounds.');
end
end
if ampargs(2) >= 100 || ampargs(2) < -100
error('\nerpimage(): percentile argument for keyword ''ampsort'' must be (-100;100)');
end
if length(ampargs) == 4 && abs(ampargs(3)) > abs(ampargs(4))
error('\nerpimage(): Amplitude sorting frequency range must be increasing.');
end
Ampflag = NO;
elseif Valflag == YES % sort by potential value in a given window
% Usage: 'valsort',[mintime,maxtime,direction]
n = length(Arg);
if n > 3
error('\nerpimage(): Too many arguments for keyword ''valsort''');
end
valargs = Arg;
if min(valargs(1)) < times(1) || max(valargs(1)) > times(end)
error('\nerpimage(): start time for value sorting out of bounds.');
end
if n > 1
if min(valargs(2)) < times(1) || max(valargs(2)) > times(end)
error('\nerpimage(): end time for value sorting out of bounds.');
end
end
if n > 1 && valargs(1) > valargs(2)
error('\nerpimage(): Value sorting time range must be increasing.');
end
if n==3 && (~isnumeric(valargs(3)) || valargs(3)==0)
error('\nerpimage(): Value sorting direction must be +1 or -1.');
end
Valflag = NO;
elseif plotmodeflag == YES
plotmode = Arg; plotmodeflag = NO;
elseif titleflag == YES
titl = Arg; titleflag = NO;
elseif Erpalphaflag == YES
erpalpha = Arg(1);
if erpalpha < MIN_ERPALPHA || erpalpha > MAX_ERPALPHA
fprintf('\nerpimage(): erpalpha value is out of bounds [%g, %g]\n',...
MIN_ERPALPHA,MAX_ERPALPHA);
return
end
Erpalphaflag = NO;
% -----------------------------------------------------------------------
% -----------------------------------------------------------------------
% -----------------------------------------------------------------------
elseif strcmpi(Arg,'avg_type')
if a < nargin,
a=a+1;
Arg = eval(['arg' int2str(a-6)]);
if strcmpi(Arg, 'Gaussian'), mvavg_type='gaussian';
elseif strcmpi(Arg, 'Boxcar'), mvavg_type='boxcar';
else error('\nerpimage(): Invalid value for optional argument ''avg_type''.');
end
else
error('\nerpimage(): Optional argument ''avg_type'' needs to be assigned a value.');
end
elseif strcmp(Arg,'nosort')
Nosort = YES;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), Nosort = YES; a = a+1;
elseif strcmpi(Arg, 'off') Nosort = NO; a = a+1;
end
end
elseif strcmp(Arg,'showwin')
Showwin = YES;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), Showwin = YES; a = a+1;
elseif strcmpi(Arg, 'off') Showwin = NO; a = a+1;
end
end
elseif strcmp(Arg,'noplot') % elseif strcmp(Arg,'NoShow') % by Luca && Ramon
NoShow = YES;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), NoShow = YES; a = a+1;
elseif strcmpi(Arg, 'off'), NoShow = NO; a = a+1;
end
end
elseif strcmpi(Arg,'replace_ties')
if a < nargin,
a = a+1;
temp = eval(['arg' int2str(a-6)]);
if strcmpi(temp,'on'),
replace_ties = YES;
elseif strcmpi(temp,'off') replace_ties = NO;
else
error('\nerpimage(): Argument ''replace_ties'' needs to be followed by the string ''on'' or ''off''.');
end
else
error('\nerpimage(): Argument ''replace_ties'' needs to be followed by the string ''on'' or ''off''.');
end
elseif strcmpi(Arg,'sortvar_limits')
if a < nargin,
a = a+1;
sortvar_limits = eval(['arg' int2str(a-6)]);
if ischar(sortvar_limits) || length(sortvar_limits)~=2
error('\nerpimage(): Argument ''sortvar_limits'' needs to be followed by a two element vector.');
end
else
error('\nerpimage(): Argument ''sortvar_limits'' needs to be followed by a two element vector.');
end
elseif strcmpi(Arg,'erp')
Erpflag = YES;
erp_ptiles=1;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), Erpflag = YES; erp_ptiles=1; a = a+1;
elseif strcmpi(Arg, 'off') Erpflag = NO; a = a+1;
elseif strcmpi(Arg,'1') || (Arg(1)==1) Erplag = YES; erp_ptiles=1; a=a+1;
elseif strcmpi(Arg,'2') || (Arg(1)==2) Erplag = YES; erp_ptiles=2; a=a+1;
elseif strcmpi(Arg,'3') || (Arg(1)==3) Erplag = YES; erp_ptiles=3; a=a+1;
elseif strcmpi(Arg,'4') || (Arg(1)==4) Erplag = YES; erp_ptiles=4; a=a+1;
end
end
elseif strcmpi(Arg,'rmerp')
Rmerp = 'yes';
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), Rmerp = 'yes'; a = a+1;
elseif strcmpi(Arg, 'off') Rmerp = 'no'; a = a+1;
end
end
elseif strcmp(Arg,'cbar') || strcmp(Arg,'colorbar')
Colorbar = YES;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), Colorbar = YES; a = a+1;
elseif strcmpi(Arg, 'off') Colorbar = NO; a = a+1;
end
end
elseif (strcmp(Arg,'allamps') || strcmp(Arg,'plotamps'))
Allampsflag = YES;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), Allampsflag = YES; a = a+1;
elseif strcmpi(Arg, 'off') Allampsflag = NO; a = a+1;
end
end
elseif strcmpi(Arg,'erpstd')
Erpstdflag = YES;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), Erpstdflag = YES; a = a+1;
elseif strcmpi(Arg, 'off') Erpstdflag = NO; a = a+1;
end
end
elseif strcmp(Arg,'noxlabel') || strcmp(Arg,'noxlabels') || strcmp(Arg,'nox')
NoTimeflag = YES;
if a < nargin,
Arg = eval(['arg' int2str(a+1-6)]);
if strcmpi(Arg, 'on'), NoTimeflag = YES; a = a+1;
elseif strcmpi(Arg, 'off') NoTimeflag = NO; a = a+1;
end
end
elseif strcmp(Arg,'plotmode')
plotmodeflag = YES;
elseif strcmp(Arg,'sortvarpercent')
percentileflag = YES;
elseif strcmp(Arg,'renorm')
Renormflag = YES;
elseif strcmp(Arg,'NoShow')
NoShowflag = YES;
elseif strcmp(Arg,'caxis')
Caxflag = YES;
elseif strcmp(Arg,'title')
titleflag = YES;
elseif strcmp(Arg,'coher')
Coherflag = YES;
elseif strcmp(Arg,'timestretch') || strcmp(Arg,'timewarp') % Added -JH
timestretchflag = YES;
elseif strcmp(Arg,'allcohers')
Allcohersflag = YES;
elseif strcmp(Arg,'topo') || strcmp(Arg,'topoplot')
Topoflag = YES;
elseif strcmp(Arg,'spec') || strcmp(Arg,'spectrum')
Specflag = YES;
elseif strcmp(Arg,'Specaxis') || strcmp(Arg,'specaxis') || strcmp(Arg,'SpecAxis')
SpecAxisflag = YES;
elseif strcmpi(Arg,'erpalpha')
Erpalphaflag = YES;
elseif strcmp(Arg,'align')
Alignflag = YES;
elseif strcmp(Arg,'limits')
Limitflag = YES;
elseif (strcmp(Arg,'phase') || strcmp(Arg,'phasesort'))
Phaseflag = YES;
elseif strcmp(Arg,'ampsort')
Ampflag = YES;
elseif strcmp(Arg,'sortwin')
Sortwinflag = YES;
elseif strcmp(Arg,'valsort')