mvpa2.misc.plot.erp.plot_erps(erps, data=None, ax=None, pre=0.2, post=None, pre_onset=None, xlabel='time (s)', ylabel='$\\mu V$', ylim=None, ymult=1.0, legend=None, xlformat='%4g', ylformat='%4g', loffset=10, alinewidth=2, **kwargs)

Plot multiple ERPs on a new figure.


erps : list of tuples

List of definitions of ERPs. Each tuple should consist of (label, color, onsets) or a dictionary which defines, label, color, onsets, data. Data provided in dictionary overrides ‘common’ data provided in the next argument data


Data for ERPs to be derived from 1D (samples)


Where to draw (e.g. subplot instance). If None, new figure is created

pre : float, optional

Duration (seconds) to be plotted prior to onset

pre_onset : None or float

If data is already in epochs (2D) then pre_onset provides information on how many seconds pre-stimulus were used to generate them. If None, then pre_onset = pre

post : None or float

Duration (seconds) to be plotted after the onset. If any data is provided with onsets, it can’t be None. If None – plots all time points after onsets

ymult : float, optional

Multiplier for the values. E.g. if negative-up ERP plot is needed: provide ymult=-1.0

xlformat : str, optional

Format of the x ticks

ylformat : str, optional

Format of the y ticks

legend : None or string

If not None, legend will be plotted with position argument provided in this argument

loffset : int, optional

Offset in voxels for axes and tick labels. Different matplotlib frontends might have different opinions, thus offset value might need to be tuned specifically per frontend

alinewidth : int, optional

Axis and ticks line width


Additional arguments provided to plot_erp()



current fig handler


kwargs  = {'SR' : eeg.SR, 'pre_mean' : 0.2}
fig = plot_erps((('60db', 'b', eeg.erp_onsets['60db']),
                 ('80db', 'r', eeg.erp_onsets['80db'])),
                data[:, eeg.sensor_mapping['Cz']],
                ax=fig.add_subplot(1,1,1,frame_on=False), pre=0.2,
                post=0.6, **kwargs)


fig = plot_erps((('60db', 'b', eeg.erp_onsets['60db']),
                  {'color': 'r',
                   'onsets': eeg.erp_onsets['80db'],
                   'data' : data[:, eeg.sensor_mapping['Cz']]}
                data[:, eeg.sensor_mapping['Cz']],
                ax=fig.add_subplot(1,1,1,frame_on=False), pre=0.2,
                post=0.6, **kwargs)