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"""Functions to plot EEG sensor montages or digitizer montages."""
from copy import deepcopy
import numpy as np
from ..utils import logger, _check_option, _validate_type, verbose
from . import plot_sensors
from ..io._digitization import _get_fid_coords
@verbose
def plot_montage(montage, scale_factor=20, show_names=True, kind='topomap',
show=True, sphere=None, verbose=None):
"""Plot a montage.
Parameters
----------
montage : instance of DigMontage
The montage to visualize.
scale_factor : float
Determines the size of the points.
show_names : bool | list
Whether to display all channel names. If a list, only the channel
names in the list are shown. Defaults to True.
kind : str
Whether to plot the montage as '3d' or 'topomap' (default).
show : bool
Show figure if True.
%(sphere_topomap_auto)s
%(verbose)s
Returns
-------
fig : instance of matplotlib.figure.Figure
The figure object.
"""
from scipy.spatial.distance import cdist
from ..channels import DigMontage, make_dig_montage
from .. import create_info
_check_option('kind', kind, ['topomap', '3d'])
_validate_type(montage, DigMontage, item_name='montage')
ch_names = montage.ch_names
title = None
if len(ch_names) == 0:
raise RuntimeError('No valid channel positions found.')
pos = np.array(list(montage._get_ch_pos().values()))
dists = cdist(pos, pos)
# only consider upper triangular part by setting the rest to np.nan
dists[np.tril_indices(dists.shape[0])] = np.nan
dupes = np.argwhere(np.isclose(dists, 0))
if dupes.any():
montage = deepcopy(montage)
n_chans = pos.shape[0]
n_dupes = dupes.shape[0]
idx = np.setdiff1d(np.arange(len(pos)), dupes[:, 1]).tolist()
logger.info("{} duplicate electrode labels found:".format(n_dupes))
logger.info(", ".join([ch_names[d[0]] + "/" + ch_names[d[1]]
for d in dupes]))
logger.info("Plotting {} unique labels.".format(n_chans - n_dupes))
ch_names = [ch_names[i] for i in idx]
ch_pos = dict(zip(ch_names, pos[idx, :]))
# XXX: this might cause trouble if montage was originally in head
fid, _ = _get_fid_coords(montage.dig)
montage = make_dig_montage(ch_pos=ch_pos, **fid)
info = create_info(ch_names, sfreq=256, ch_types="eeg")
info.set_montage(montage, on_missing='ignore')
fig = plot_sensors(info, kind=kind, show_names=show_names, show=show,
title=title, sphere=sphere)
collection = fig.axes[0].collections[0]
collection.set_sizes([scale_factor])
return fig
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