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function [cfg] = ft_singleplotER(cfg, varargin)
% FT_SINGLEPLOTER plots the event-related fields or potentials of a single
% channel or the average over multiple channels. Multiple datasets can be
% overlayed.
%
% Use as
% ft_singleplotER(cfg, data)
% or
% ft_singleplotER(cfg, data1, data2, ..., datan)
%
% The data can be an erp/erf produced by FT_TIMELOCKANALYSIS, a power
% spectrum produced by FT_FREQANALYSIS or connectivity spectrum produced by
% FT_CONNECTIVITYANALYSIS.
%
% The configuration can have the following parameters:
% cfg.parameter = field to be plotted on y-axis, for example 'avg', 'powspctrm' or 'cohspctrm' (default is automatic)
% cfg.maskparameter = field in the first dataset to be used for masking of data; this is not supported when
% computing the mean over multiple channels, or when giving multiple input datasets (default = [])
% cfg.maskstyle = style used for masking of data, 'box', 'thickness' or 'saturation' (default = 'box')
% cfg.maskfacealpha = mask transparency value between 0 and 1
% cfg.xlim = 'maxmin' or [xmin xmax] (default = 'maxmin')
% cfg.ylim = 'maxmin', 'maxabs', 'zeromax', 'minzero', or [ymin ymax] (default = 'maxmin')
% cfg.channel = Nx1 cell-array with selection of channels (default = 'all'), see FT_CHANNELSELECTION for details
% cfg.title = string, title of plot
% cfg.showlegend = 'yes' or 'no', show the legend with the colors (default = 'no')
% cfg.refchannel = name of reference channel for visualising connectivity, can be 'gui'
% cfg.baseline = 'yes', 'no' or [time1 time2] (default = 'no'), see ft_timelockbaseline
% cfg.baselinetype = 'absolute' or 'relative' (default = 'absolute')
% cfg.trials = 'all' or a selection given as a 1xn vector (default = 'all')
% cfg.fontsize = font size of title (default = 8)
% cfg.hotkeys = enables hotkeys (leftarrow/rightarrow/uparrow/downarrow/m) for dynamic zoom and translation (ctrl+) of the axes
% cfg.interactive = interactive plot 'yes' or 'no' (default = 'yes')
% in a interactive plot you can select areas and produce a new
% interactive plot when a selected area is clicked. multiple areas
% can be selected by holding down the shift key.
% cfg.renderer = 'painters', 'zbuffer', ' opengl' or 'none' (default = [])
% cfg.linestyle = linestyle/marker type, see options of the PLOT function (default = '-')
% can be a single style for all datasets, or a cell-array containing one style for each dataset
% cfg.linewidth = linewidth in points (default = 0.5)
% cfg.linecolor = color(s) used for plotting the dataset(s). The default is defined in LINEATTRIBUTES_COMMON, see
% the help of this function for more information
% cfg.directionality = '', 'inflow' or 'outflow' specifies for
% connectivity measures whether the inflow into a
% node, or the outflow from a node is plotted. The
% (default) behavior of this option depends on the dimor
% of the input data (see below).
% cfg.select = 'intersect' or 'union' (default = 'intersect')
% with multiple input arguments determines the
% pre-selection of the data that is considered for
% plotting.
% cfg.showlocations = 'no' (default), or 'yes'. plot a small spatial layout of all sensors, highlighting the specified subset
% cfg.layouttopo = filename, or struct (see FT_PREPARE_LAYOUT) used for showing the locations with cfg.showlocations = 'yes'
%
% The following options for the scaling of the EEG, EOG, ECG, EMG, MEG and NIRS channels
% is optional and can be used to bring the absolute numbers of the different
% channel types in the same range (e.g. fT and uV). The channel types are determined
% from the input data using FT_CHANNELSELECTION.
% cfg.eegscale = number, scaling to apply to the EEG channels prior to display
% cfg.eogscale = number, scaling to apply to the EOG channels prior to display
% cfg.ecgscale = number, scaling to apply to the ECG channels prior to display
% cfg.emgscale = number, scaling to apply to the EMG channels prior to display
% cfg.megscale = number, scaling to apply to the MEG channels prior to display
% cfg.gradscale = number, scaling to apply to the MEG gradiometer channels prior to display (in addition to the cfg.megscale factor)
% cfg.magscale = number, scaling to apply to the MEG magnetometer channels prior to display (in addition to the cfg.megscale factor)
% cfg.nirsscale = number, scaling to apply to the NIRS channels prior to display
% cfg.mychanscale = number, scaling to apply to the channels specified in cfg.mychan
% cfg.mychan = Nx1 cell-array with selection of channels
% cfg.chanscale = Nx1 vector with scaling factors, one per channel specified in cfg.channel
%
% For the plotting of directional connectivity data the cfg.directionality
% option determines what is plotted. The default value and the supported
% functionality depend on the dimord of the input data. If the input data
% is of dimord 'chan_chan_XXX', the value of directionality determines
% whether, given the reference channel(s), the columns (inflow), or rows
% (outflow) are selected for plotting. In this situation the default is
% 'inflow'. Note that for undirected measures, inflow and outflow should
% give the same output. If the input data is of dimord 'chancmb_XXX', the
% value of directionality determines whether the rows in data.labelcmb are
% selected. With 'inflow' the rows are selected if the refchannel(s) occur in
% the right column, with 'outflow' the rows are selected if the
% refchannel(s) occur in the left column of the labelcmb-field. Default in
% this case is '', which means that all rows are selected in which the
% refchannel(s) occur. This is to robustly support linearly indexed
% undirected connectivity metrics. In the situation where undirected
% connectivity measures are linearly indexed, specifying 'inflow' or
% 'outflow' can result in unexpected behavior.
%
% to facilitate data-handling and distributed computing you can use
% cfg.inputfile = ...
% if you specify this option the input data will be read from a *.mat
% file on disk. this mat files should contain only a single variable named 'data',
% corresponding to the input structure.
%
% See also FT_SINGLEPLOTTFR, FT_MULTIPLOTER, FT_MULTIPLOTTFR, FT_TOPOPLOTER, FT_TOPOPLOTTFR
% Copyright (C) 2003-2006, Ole Jensen
% Copyright (C) 2006-2022, Donders Centre for Cognitive Neuroimaging
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% FieldTrip is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with FieldTrip. If not, see <http://www.gnu.org/licenses/>.
%
% $Id$
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% DEVELOPERS NOTE: This code is organized in a similar fashion for multiplot/singleplot/topoplot
% and for ER/TFR and should remain consistent over those 6 functions.
% Section 1: general cfg handling that is independent from the data
% Section 2: data handling, this also includes converting bivariate (chan_chan and chancmb) into univariate data
% Section 3: select the data to be plotted and determine min/max range
% Section 4: do the actual plotting
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Section 1: general cfg handling that is independent from the data
% these are used by the ft_preamble/ft_postamble function and scripts
ft_revision = '$Id$';
ft_nargin = nargin;
ft_nargout = nargout;
% do the general setup of the function
ft_defaults
ft_preamble init
ft_preamble debug
ft_preamble loadvar varargin
ft_preamble provenance varargin
% the ft_abort variable is set to true or false in ft_preamble_init
if ft_abort
return
end
Ndata = numel(varargin);
for i=1:Ndata
% check if the input data is valid for this function
varargin{i} = ft_checkdata(varargin{i}, 'datatype', {'timelock', 'freq'});
end
% check if the input cfg is valid for this function
cfg = ft_checkconfig(cfg, 'forbidden', {'channels', 'trial'}); % prevent accidental typos, see issue 1729
cfg = ft_checkconfig(cfg, 'unused', {'cohtargetchannel'});
cfg = ft_checkconfig(cfg, 'renamedval', {'zlim', 'absmax', 'maxabs'});
cfg = ft_checkconfig(cfg, 'renamedval', {'directionality', 'feedforward', 'outflow'});
cfg = ft_checkconfig(cfg, 'renamedval', {'directionality', 'feedback', 'inflow'});
cfg = ft_checkconfig(cfg, 'renamed', {'matrixside', 'directionality'});
cfg = ft_checkconfig(cfg, 'renamed', {'channelindex', 'channel'});
cfg = ft_checkconfig(cfg, 'renamed', {'channelname', 'channel'});
cfg = ft_checkconfig(cfg, 'renamed', {'cohrefchannel', 'refchannel'});
cfg = ft_checkconfig(cfg, 'renamed', {'zparam', 'parameter'});
cfg = ft_checkconfig(cfg, 'renamed', {'graphcolor', 'linecolor'});
cfg = ft_checkconfig(cfg, 'deprecated', {'xparam'});
cfg = ft_checkconfig(cfg, 'renamed', {'newfigure', 'figure'});
% set the defaults
cfg.baseline = ft_getopt(cfg, 'baseline', 'no');
cfg.trials = ft_getopt(cfg, 'trials', 'all', 1);
cfg.xlim = ft_getopt(cfg, 'xlim', 'maxmin');
cfg.ylim = ft_getopt(cfg, 'ylim', 'maxmin');
cfg.zlim = ft_getopt(cfg, 'zlim', 'maxmin');
cfg.comment = ft_getopt(cfg, 'comment', strcat([date '\n']));
cfg.axes = ft_getopt(cfg, ' axes', 'yes');
cfg.fontsize = ft_getopt(cfg, 'fontsize', 8);
cfg.interpreter = ft_getopt(cfg, 'interpreter', 'none'); % none, tex or latex
cfg.hotkeys = ft_getopt(cfg, 'hotkeys', 'yes');
cfg.interactive = ft_getopt(cfg, 'interactive', 'yes');
cfg.maskparameter = ft_getopt(cfg, 'maskparameter', []);
cfg.colorgroups = ft_getopt(cfg, 'colorgroups', 'condition'); % this is the only supported option
cfg.linecolor = ft_getopt(cfg, 'linecolor', []);
cfg.linestyle = ft_getopt(cfg, 'linestyle', '-');
cfg.linewidth = ft_getopt(cfg, 'linewidth', 0.5);
cfg.maskstyle = ft_getopt(cfg, 'maskstyle', 'box');
cfg.maskfacealpha = ft_getopt(cfg, 'maskfacealpha', 1);
cfg.channel = ft_getopt(cfg, 'channel', 'all');
cfg.title = ft_getopt(cfg, 'title', []);
cfg.directionality = ft_getopt(cfg, 'directionality', []);
cfg.figurename = ft_getopt(cfg, 'figurename', []);
cfg.preproc = ft_getopt(cfg, 'preproc', []);
cfg.frequency = ft_getopt(cfg, 'frequency', 'all'); % needed for frequency selection with TFR data
cfg.latency = ft_getopt(cfg, 'latency', 'all'); % needed for latency selection with TFR data, FIXME, probably not used
cfg.showlegend = ft_getopt(cfg, 'showlegend', 'no');
cfg.renderer = ft_getopt(cfg, 'renderer', []); % let MATLAB decide on the default
cfg.select = ft_getopt(cfg, 'select', 'intersect'); % for ft_selectdata
cfg.showlocations = ft_getopt(cfg, 'showlocations', 'no');
cfg.layouttopo = ft_getopt(cfg, 'layouttopo');
% this is needed for the figure title and correct labeling of linecolor later on
if isfield(cfg, 'dataname') && ~isempty(cfg.dataname)
dataname = cfg.dataname;
elseif isfield(cfg, 'inputfile') && ~isempty(cfg.inputfile)
dataname = cfg.inputfile;
elseif nargin>1
dataname = arrayfun(@inputname, 2:nargin, 'UniformOutput', false);
else
dataname = {};
end
%% Section 2: data handling, this also includes converting bivariate (chan_chan and chancmb) into univariate data
for i=1:Ndata
dtype{i} = ft_datatype(varargin{i});
hastime(i) = isfield(varargin{i}, 'time');
hasfreq(i) = isfield(varargin{i}, 'freq');
end
% check if the input has consistent datatypes
if ~all(strcmp(dtype, dtype{1})) || ~all(hastime==hastime(1)) || ~all(hasfreq==hasfreq(1))
ft_error('different datatypes are not allowed as input');
else
dtype = dtype{1};
hastime = hastime(1);
hasfreq = hasfreq(1);
end
% Set x/y/parameter according to datatype and dimord
switch dtype
case 'timelock'
xparam = 'time';
if isfield(varargin{1}, 'trial')
cfg.parameter = ft_getopt(cfg, 'parameter', 'trial');
elseif isfield(varargin{1}, 'individual')
cfg.parameter = ft_getopt(cfg, 'parameter', 'individual');
elseif isfield(varargin{1}, 'avg')
cfg.parameter = ft_getopt(cfg, 'parameter', 'avg');
end
case 'freq'
if hastime && hasfreq
xparam = 'time'; % average over selected frequencies
else
xparam = 'freq';
end
cfg.parameter = ft_getopt(cfg, 'parameter', 'powspctrm');
case 'comp'
% not supported
otherwise
% not supported
end
% check whether rpt/subj is present and remove if necessary
dimord = getdimord(varargin{1}, cfg.parameter);
dimtok = tokenize(dimord, '_');
hasrpt = any(ismember(dimtok, {'rpt' 'subj'}));
if ~hasrpt
assert(isequal(cfg.trials, 'all') || isequal(cfg.trials, 1), 'incorrect specification of cfg.trials for data without repetitions');
else
assert(~isempty(cfg.trials), 'empty specification of cfg.trials for data with repetitions');
end
% parse cfg.channel
if isfield(cfg, 'channel') && isfield(varargin{1}, 'label')
cfg.channel = ft_channelselection(cfg.channel, varargin{1}.label);
elseif isfield(cfg, 'channel') && isfield(varargin{1}, 'labelcmb')
cfg.channel = ft_channelselection(cfg.channel, unique(varargin{1}.labelcmb(:)));
end
% apply baseline correction
if ~strcmp(cfg.baseline, 'no')
tmpcfg = keepfields(cfg, {'baseline', 'baselinetype', 'baselinewindow', 'demean', 'parameter', 'channel'});
for i=1:Ndata
% keep mask-parameter if it is set
if ~isempty(cfg.maskparameter)
tempmask = varargin{i}.(cfg.maskparameter);
end
if strcmp(dtype, 'timelock') && strcmp(xparam, 'time')
varargin{i} = ft_timelockbaseline(tmpcfg, varargin{i});
elseif strcmp(dtype, 'freq') && strcmp(xparam, 'time')
varargin{i} = ft_freqbaseline(tmpcfg, varargin{i});
elseif strcmp(dtype, 'freq') && strcmp(xparam, 'freq')
ft_error('baseline correction is not supported for spectra without a time dimension');
else
ft_warning('baseline correction not applied, please set xparam');
end
% put mask-parameter back if it is set
if ~isempty(cfg.maskparameter)
varargin{i}.(cfg.maskparameter) = tempmask;
end
end
end
% channels should NOT be selected and averaged here, since a topoplot might follow in interactive mode
tmpcfg = keepfields(cfg, {'trials', 'select', 'showcallinfo', 'trackcallinfo', 'trackusage', 'trackdatainfo', 'trackmeminfo', 'tracktimeinfo'});
if hasrpt
tmpcfg.avgoverrpt = 'yes';
else
tmpcfg.avgoverrpt = 'no';
end
if hastime && hasfreq
tmpcfg.avgoverfreq = 'yes'; % average over selected frequencies
tmpcfg.frequency = cfg.frequency; % not to be confused with cfg.xlim or cfg.ylim
tmpcfg.keepfreqdim = 'no';
else
tmpcfg.avgoverfreq = 'no';
end
tmpvar = varargin{1};
[varargin{:}] = ft_selectdata(tmpcfg, varargin{:});
% restore the provenance information and put back cfg.channel
tmpchannel = cfg.channel;
[cfg, varargin{:}] = rollback_provenance(cfg, varargin{:});
cfg.channel = tmpchannel;
if isfield(tmpvar, cfg.maskparameter) && ~isfield(varargin{1}, cfg.maskparameter)
% the mask parameter is not present after ft_selectdata, because it is
% not included in all input arguments. Make the same selection and copy
% it over
tmpvar = ft_selectdata(tmpcfg, tmpvar);
varargin{1}.(cfg.maskparameter) = tmpvar.(cfg.maskparameter);
end
clear tmpvar tmpcfg dimord dimtok hastime hasfreq hasrpt
% ensure that the preproc specific options are located in the cfg.preproc
% substructure, but also ensure that the field 'refchannel' remains at the
% highest level in the structure. This is a little hack by JM because the field
% refchannel can relate to connectivity or to an EEg reference.
if isfield(cfg, 'refchannel'), refchannelincfg = cfg.refchannel; cfg = rmfield(cfg, 'refchannel'); end
cfg = ft_checkconfig(cfg, 'createsubcfg', {'preproc'});
if exist('refchannelincfg', 'var'), cfg.refchannel = refchannelincfg; end
if ~isempty(cfg.preproc)
% preprocess the data, i.e. apply filtering, baselinecorrection, etc.
fprintf('applying preprocessing options\n');
if ~isfield(cfg.preproc, 'feedback')
cfg.preproc.feedback = cfg.interactive;
end
for i=1:Ndata
varargin{i} = ft_preprocessing(cfg.preproc, varargin{i});
end
end
% Handle the bivariate case
dimord = getdimord(varargin{1}, cfg.parameter);
if startsWith(dimord, 'chan_chan_') || startsWith(dimord, 'chancmb_')
% convert the bivariate data to univariate and call this plotting function again
cfg.originalfunction = 'ft_singleplotER';
cfg.trials = 'all'; % trial selection has been taken care off
bivariate_common(cfg, varargin{:});
return
end
% Apply channel-type specific scaling
fn = fieldnames(cfg);
fn = setdiff(fn, {'skipscale', 'showscale', 'gridscale'}); % these are for the layout and plotting, not for CHANSCALE_COMMON
fn = fn(endsWith(fn, 'scale') | startsWith(fn, 'mychan') | strcmp(fn, 'channel') | strcmp(fn, 'parameter'));
tmpcfg = keepfields(cfg, fn);
if ~isempty(tmpcfg)
for i=1:Ndata
varargin{i} = chanscale_common(tmpcfg, varargin{i});
end
% remove the scaling fields from the configuration, to prevent them from being called again in interactive mode
% but keep the parameter and channel field
cfg = removefields(cfg, setdiff(fn, {'parameter', 'channel'}));
else
% do nothing
end
%% Section 3: select the data to be plotted and determine min/max range
if istrue(cfg.showlocations)
% Read or create the layout that will be used for plotting, if specified
tmpcfg = keepfields(cfg, {'rows', 'columns', 'commentpos', 'scalepos', 'projection', 'viewpoint', 'rotate', 'width', 'height', 'elec', 'grad', 'opto', 'layouttopo', 'showcallinfo', 'trackcallinfo', 'trackusage', 'trackdatainfo', 'trackmeminfo', 'tracktimeinfo'});
tmpcfg.skipcomnt = 'yes';
tmpcfg.skipscale = 'yes';
tmpcfg.pointcolor = cfg.linecolor; % switch of name for ft_prepare_layout
if ~isempty(cfg.layouttopo)
tmpcfg.layout = cfg.layouttopo;
elseif isfield(cfg, 'layout') && ~isempty(cfg.layout)
tmpcfg.layout = cfg.layout;
else
ft_warning('no explicit layout specified, attempting to create one from the data');
end
cfg.layouttopo = ft_prepare_layout(tmpcfg, varargin{1});
end
% Take the desided subselection of channels, this is the same in all datasets
[selchan] = match_str(varargin{1}.label, cfg.channel);
% Get physical min/max range of x, i.e. time or frequency
if strcmp(cfg.xlim, 'maxmin')
% Find maxmin throughout all varargins:
xmin = [];
xmax = [];
for i=1:Ndata
xmin = min([xmin varargin{i}.(xparam)]);
xmax = max([xmax varargin{i}.(xparam)]);
end
else
xmin = cfg.xlim(1);
xmax = cfg.xlim(2);
end
% Get the index of the nearest bin, this is the same in all datasets
xminindx = nearest(varargin{1}.(xparam), xmin);
xmaxindx = nearest(varargin{1}.(xparam), xmax);
xmin = varargin{1}.(xparam)(xminindx);
xmax = varargin{1}.(xparam)(xmaxindx);
selx = xminindx:xmaxindx;
xval = varargin{1}.(xparam)(selx);
% get physical y-axis range, i.e. parameter to be plotted
if ~isnumeric(cfg.ylim)
% find maxmin throughout all varargins
ymin = +inf;
ymax = -inf;
for i=1:Ndata
% select the channels in the data that match with the layout and that are selected for plotting
dat = nanmean(varargin{i}.(cfg.parameter)(selchan, selx), 1); % mean over channels
ymin = min(ymin, min(dat(:)));
ymax = max(ymax, max(dat(:)));
end
switch cfg.ylim
case 'maxmin'
% keep them as they are
case 'maxabs'
ymax = max(abs(ymax), abs(ymin));
ymin = -ymax;
case 'zeromax'
ymin = 0;
case 'minzero'
ymax = 0;
otherwise
ft_error('invalid specification of cfg.ylim');
end
else
ymin = cfg.ylim(1);
ymax = cfg.ylim(2);
end
% gather the data from all input data structures
datamatrix = zeros(Ndata, length(selx));
for i=1:Ndata
datamatrix(i,:) = mean(varargin{i}.(cfg.parameter)(selchan, selx), 1); % mean over channels
end
% gather the mask from the first input data structure
if ~isempty(cfg.maskparameter)
maskmatrix = mean(varargin{1}.(cfg.maskparameter)(selchan, selx), 1); % mean over channels
else
% create an Nx0 matrix
maskmatrix = zeros(length(selchan), 0);
end
%% Section 4: do the actual plotting
% determine the coloring of channels/conditions
[linecolor, linestyle, linewidth] = lineattributes_common(cfg, varargin{:});
linecolor = mean(linecolor(selchan, :, :), 1);
linestyle = linestyle(selchan(1), :);
linewidth = mean(linewidth(selchan, :), 1);
% open a new figure, or add it to the existing one
open_figure(keepfields(cfg, {'figure', 'position', 'visible', 'renderer', 'figurename', 'title'}));
yval = datamatrix;
mask = maskmatrix;
if strcmp(cfg.maskstyle, 'difference')
% combine the conditions in a single plot, highlight the difference
ft_plot_vector(xval, yval, 'color', permute(linecolor, [3 2 1]), 'style', linestyle(1,:), 'linewidth', linewidth(1,:), 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'facealpha', cfg.maskfacealpha);
else
% loop over the conditions, plot them on top of each other
for i=1:Ndata
ft_plot_vector(xval, yval(i,:), 'color', linecolor(1,:,i), 'style', linestyle{1,i}, 'linewidth', linewidth(1,i), 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'facealpha', cfg.maskfacealpha);
end
end
if ischar(linecolor)
set(gca, 'ColorOrder', char2rgb(linecolor))
elseif isnumeric(linecolor)
set(gca, 'ColorOrder', shiftdim(linecolor(1,:,:),1)');
end
% show the legend with the colors of the conditions
if istrue(cfg.showlegend) && Ndata>1
if strcmp(cfg.maskstyle, 'difference')
colorLabels = {'difference'};
else
colorLabels = {};
end
for i=1:Ndata
if ischar(linecolor)
colorLabels{end+1} = [dataname{i} '=' linecolor(i) ];
elseif isnumeric(linecolor)
colorLabels{end+1} = [dataname{i} '=' num2str(linecolor(1, :, i)) ];
end
end
legend(colorLabels)
end
% set xlim and ylim
if xmin~=xmax
xlim([xmin xmax]);
end
if ymin~=ymax
ylim([ymin ymax]);
end
% adjust mask box extents to ymin/ymax
if ~isempty(cfg.maskparameter)
ptchs = findobj(gcf, 'type', 'patch');
for i = 1:length(ptchs)
YData = get(ptchs(i), 'YData');
YData(YData == min(YData)) = ymin;
YData(YData == max(YData)) = ymax;
set(ptchs(i), 'YData',YData);
end
end
% Set callback to adjust axes
if strcmp('yes', cfg.hotkeys)
% attach data and cfg to figure and attach a key listener to the figure
set(gcf, 'KeyPressFcn', {@key_sub, xmin, xmax, ymin, ymax})
end
% Create axis title containing channel name(s) and channel number(s):
if ~isempty(cfg.title)
t = cfg.title;
else
if length(cfg.channel) == 1
t = [char(cfg.channel) ' / ' num2str(selchan) ];
else
t = sprintf('mean(%0s)', join_str(', ', cfg.channel));
end
end
title(t, 'fontsize', cfg.fontsize, 'interpreter', cfg.interpreter);
% set the figure window title, add channel labels if number is small
if isempty(get(gcf, 'Name'))
if length(selchan) < 5
chans = join_str(', ', cfg.channel);
else
chans = '<multiple channels>';
end
if ~isempty(cfg.figurename)
set(gcf, 'name', cfg.figurename);
set(gcf, 'NumberTitle', 'off');
elseif ~isempty(dataname)
set(gcf, 'Name', sprintf('%d: %s: %s (%s)', double(gcf), mfilename, join_str(', ', dataname), chans));
set(gcf, 'NumberTitle', 'off');
else
set(gcf, 'Name', sprintf('%d: %s (%s)', double(gcf), mfilename, chans));
set(gcf, 'NumberTitle', 'off');
end
end
if istrue(cfg.showlocations)
hpos = xmin+(xmax-xmin)*0.1;
vpos = ymin+(ymax-ymin)*0.9;
h = 0.2*(ymax-ymin);
w = 0.2*(xmax-xmin);
pointcolor = zeros(numel(cfg.layouttopo.label),3);
pointsize = ones(numel(cfg.layouttopo.label),2);
pointsize(selchan) = 4;
pointsymbol = 'o';
ft_plot_layout(cfg.layouttopo, 'box', 'no', 'label', 'off', 'pointsize', pointsize, 'pointcolor', pointcolor, 'pointsymbol', pointsymbol, 'hpos', hpos, 'vpos', vpos, 'width', w, 'height', h);
end
% make the figure interactive
if strcmp(cfg.interactive, 'yes')
% add the cfg/data/channel information to the figure under identifier linked to this axis
ident = ['axh' num2str(round(sum(clock.*1e6)))]; % unique identifier for this axis
set(gca, 'tag', ident);
info = guidata(gcf);
info.(ident).cfg = cfg;
info.(ident).varargin = varargin;
info.(ident).dataname = dataname;
if exist('linecolor', 'var')
info.(ident).linecolor = linecolor;
end
guidata(gcf, info);
set(gcf, 'windowbuttonupfcn', {@ft_select_range, 'multiple', false, 'yrange', false, 'callback', {@select_topoplotER}, 'event', 'windowbuttonupfcn'});
set(gcf, 'windowbuttondownfcn', {@ft_select_range, 'multiple', false, 'yrange', false, 'callback', {@select_topoplotER}, 'event', 'windowbuttondownfcn'});
set(gcf, 'windowbuttonmotionfcn', {@ft_select_range, 'multiple', false, 'yrange', false, 'callback', {@select_topoplotER}, 'event', 'windowbuttonmotionfcn'});
end
% do the general cleanup and bookkeeping at the end of the function
ft_postamble debug
ft_postamble previous varargin
ft_postamble provenance
ft_postamble savefig
% add a menu to the figure, but only if the current figure does not have subplots
menu_fieldtrip(gcf, cfg, false);
if ~ft_nargout
% don't return anything
clear cfg
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION which is called after selecting a time range
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function select_topoplotER(range, varargin)
% fetch cfg/data based on axis indentifier given as tag
ident = get(gca, 'tag');
info = guidata(gcf);
cfg = info.(ident).cfg;
varargin = info.(ident).varargin;
if ~isempty(range)
cfg = removefields(cfg, 'inputfile'); % the reading has already been done and varargin contains the data
cfg = removefields(cfg, 'showlabels'); % this is not allowed in topoplotER
cfg.baseline = 'no'; % make sure the next function does not apply a baseline correction again
cfg.dataname = info.(ident).dataname; % put data name in here, this cannot be resolved by other means
cfg.channel = 'all'; % make sure the topo displays all channels, not just the ones in this singleplot
cfg.comment = 'auto';
cfg.trials = 'all'; % trial selection has already been taken care of
cfg.xlim = range(1:2);
% if user specified a ylim, copy it over to the zlim of topoplot
if isfield(cfg, 'ylim')
cfg.zlim = cfg.ylim;
cfg = rmfield(cfg, 'ylim');
end
fprintf('selected cfg.xlim = [%f %f]\n', cfg.xlim(1), cfg.xlim(2));
% ensure that the new figure appears at the same position
cfg.figure = 'yes';
cfg.position = get(gcf, 'Position');
ft_topoplotER(cfg, varargin{:});
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION which handles hot keys in the current plot
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function key_sub(handle, eventdata, varargin)
xlimits = xlim;
ylimits = ylim;
incr_x = abs(xlimits(2) - xlimits(1)) /10;
incr_y = abs(ylimits(2) - ylimits(1)) /10;
if length(eventdata.Modifier) == 1 && strcmp(eventdata.Modifier{:}, 'control')
% TRANSLATE by 10%
switch eventdata.Key
case 'leftarrow'
xlim([xlimits(1)+incr_x xlimits(2)+incr_x])
case 'rightarrow'
xlim([xlimits(1)-incr_x xlimits(2)-incr_x])
case 'uparrow'
ylim([ylimits(1)-incr_y ylimits(2)-incr_y])
case 'downarrow'
ylim([ylimits(1)+incr_y ylimits(2)+incr_y])
end % switch
else
% ZOOM by 10%
switch eventdata.Key
case 'leftarrow'
xlim([xlimits(1)-incr_x xlimits(2)+incr_x])
case 'rightarrow'
xlim([xlimits(1)+incr_x xlimits(2)-incr_x])
case 'uparrow'
ylim([ylimits(1)-incr_y ylimits(2)+incr_y])
case 'downarrow'
ylim([ylimits(1)+incr_y ylimits(2)-incr_y])
case 'm'
xlim([varargin{1} varargin{2}])
ylim([varargin{3} varargin{4}])
end % switch
end % if