# -*- coding: utf-8 -*-
"""Figure classes for MNE-Python's 2D plots.

Class Hierarchy
---------------

MNEFigParams    Container object, attached to MNEFigure by default. Sets
                close_key='escape' plus whatever other key-value pairs are
                passed to its constructor.

matplotlib.figure.Figure
  └ MNEFigure
     ├ MNEBrowseFigure         Interactive figure for scrollable data.
     │                         Generated by:
     │                         - raw.plot()
     │                         - epochs.plot()
     │                         - ica.plot_sources(raw)
     │                         - ica.plot_sources(epochs)
     │
     ├ MNEAnnotationFigure     GUI for adding annotations to Raw
     │
     ├ MNESelectionFigure      GUI for spatial channel selection. raw.plot()
     │                         and epochs.plot() will generate one of these
     │                         alongside an MNEBrowseFigure when
     │                         group_by == 'selection' or 'position'
     │
     └ MNELineFigure           Interactive figure for non-scrollable data.
                               Generated by:
                               - raw.plot_psd()
                               - evoked.plot()        TODO Not yet implemented
                               - evoked.plot_white()  TODO Not yet implemented
                               - evoked.plot_joint()  TODO Not yet implemented
"""

# Authors: Daniel McCloy <dan@mccloy.info>
#
# License: Simplified BSD

import datetime
import platform
import warnings
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial

import matplotlib.pyplot as plt
import numpy as np
from matplotlib import get_backend
from matplotlib.figure import Figure

from .. import channel_indices_by_type, pick_types
from ..fixes import _close_event
from ..annotations import _sync_onset
from ..defaults import _handle_default
from ..io.pick import (_DATA_CH_TYPES_ORDER_DEFAULT, _DATA_CH_TYPES_SPLIT,
                       _FNIRS_CH_TYPES_SPLIT, _VALID_CHANNEL_TYPES,
                       _picks_to_idx)
from ..time_frequency import psd_multitaper, psd_welch
from ..utils import Bunch, _check_option, _check_sphere, _click_ch_name, logger
from . import plot_sensors
from ._figure import BrowserBase
from .utils import (DraggableLine, _events_off, _fake_click, _fake_keypress,
                    _merge_annotations, _plot_psd, _prop_kw, _set_window_title,
                    _validate_if_list_of_axes, plt_show, _fake_scroll)

name = 'matplotlib'
plt.ion()
BACKEND = get_backend()
#   This  ↑↑↑↑↑↑↑↑↑↑↑↑↑  does weird things:
#   https://github.com/matplotlib/matplotlib/issues/23298
#   but wrapping it in ion() context makes it go away (can't actually use
#   `with plt.ion()` as context manager, though, for compat reasons).
#   Moving this bit to a separate function in ../../fixes.py doesn't work.
plt.ioff()

# CONSTANTS (inches)
ANNOTATION_FIG_PAD = 0.1
ANNOTATION_FIG_MIN_H = 2.9  # fixed part, not including radio buttons/labels
ANNOTATION_FIG_W = 5.0
ANNOTATION_FIG_CHECKBOX_COLUMN_W = 0.5


class MNEFigure(Figure):
    """Base class for 2D figures & dialogs; wraps matplotlib.figure.Figure."""

    def __init__(self, **kwargs):
        from matplotlib import rcParams

        # figsize is the only kwarg we pass to matplotlib Figure()
        figsize = kwargs.pop('figsize', None)
        super().__init__(figsize=figsize)
        # things we'll almost always want
        defaults = dict(fgcolor=rcParams['axes.edgecolor'],
                        bgcolor=rcParams['axes.facecolor'])
        for key, value in defaults.items():
            if key not in kwargs:
                kwargs[key] = value

        # add param object if not already added (e.g. by BrowserBase)
        if not hasattr(self, 'mne'):
            from mne.viz._figure import BrowserParams
            self.mne = BrowserParams(**kwargs)
        else:
            for key in [k for k in kwargs if not hasattr(self.mne, k)]:
                setattr(self.mne, key, kwargs[key])

    def _close(self, event):
        """Handle close events."""
        logger.debug(f'Closing {self!r}')
        # remove references from parent fig to child fig
        is_child = getattr(self.mne, 'parent_fig', None) is not None
        is_named = getattr(self.mne, 'fig_name', None) is not None
        if is_child:
            self.mne.parent_fig.mne.child_figs.remove(self)
            if is_named:
                setattr(self.mne.parent_fig.mne, self.mne.fig_name, None)

    def _keypress(self, event):
        """Handle keypress events."""
        if event.key == self.mne.close_key:
            plt.close(self)
        elif event.key == 'f11':  # full screen
            self.canvas.manager.full_screen_toggle()

    def _buttonpress(self, event):
        """Handle buttonpress events."""
        pass

    def _pick(self, event):
        """Handle matplotlib pick events."""
        pass

    def _resize(self, event):
        """Handle window resize events."""
        pass

    def _add_default_callbacks(self, **kwargs):
        """Remove some matplotlib default callbacks and add MNE-Python ones."""
        # Remove matplotlib default keypress catchers
        default_callbacks = list(
            self.canvas.callbacks.callbacks.get('key_press_event', {}))
        for callback in default_callbacks:
            self.canvas.callbacks.disconnect(callback)
        # add our event callbacks
        callbacks = dict(resize_event=self._resize,
                         key_press_event=self._keypress,
                         button_press_event=self._buttonpress,
                         close_event=self._close,
                         pick_event=self._pick)
        callbacks.update(kwargs)
        callback_ids = dict()
        for event, callback in callbacks.items():
            callback_ids[event] = self.canvas.mpl_connect(event, callback)
        # store callback references so they aren't garbage-collected
        self.mne._callback_ids = callback_ids

    def _get_dpi_ratio(self):
        """Get DPI ratio (to handle hi-DPI screens)."""
        dpi_ratio = 1.
        for key in ('_dpi_ratio', '_device_scale'):
            dpi_ratio = getattr(self.canvas, key, dpi_ratio)
        return dpi_ratio

    def _get_size_px(self):
        """Get figure size in pixels."""
        dpi_ratio = self._get_dpi_ratio()
        return self.get_size_inches() * self.dpi / dpi_ratio

    def _inch_to_rel(self, dim_inches, horiz=True):
        """Convert inches to figure-relative distances."""
        fig_w, fig_h = self.get_size_inches()
        w_or_h = fig_w if horiz else fig_h
        return dim_inches / w_or_h


class MNEAnnotationFigure(MNEFigure):
    """Interactive dialog figure for annotations."""

    def _close(self, event):
        """Handle close events (via keypress or window [x])."""
        parent = self.mne.parent_fig
        # disable span selector
        parent.mne.ax_main.selector.active = False
        # clear hover line
        parent._remove_annotation_hover_line()
        # disconnect hover callback
        callback_id = parent.mne._callback_ids['motion_notify_event']
        parent.canvas.callbacks.disconnect(callback_id)
        # do all the other cleanup activities
        super()._close(event)

    def _keypress(self, event):
        """Handle keypress events."""
        text = self.label.get_text()
        key = event.key
        if key == self.mne.close_key:
            plt.close(self)
        elif key == 'backspace':
            text = text[:-1]
        elif key == 'enter':
            self.mne.parent_fig._add_annotation_label(event)
            return
        elif len(key) > 1 or key == ';':  # ignore modifier keys
            return
        else:
            text = text + key
        self.label.set_text(text)
        self.canvas.draw()

    def _radiopress(self, event):
        """Handle Radiobutton clicks for Annotation label selection."""
        # update which button looks active
        buttons = self.mne.radio_ax.buttons
        labels = [label.get_text() for label in buttons.labels]
        idx = labels.index(buttons.value_selected)
        self._set_active_button(idx)
        # update click-drag rectangle color
        color = buttons.circles[idx].get_edgecolor()
        selector = self.mne.parent_fig.mne.ax_main.selector
        # https://github.com/matplotlib/matplotlib/issues/20618
        # https://github.com/matplotlib/matplotlib/pull/20693
        try:  # > 3.4.2
            selector.set_props(color=color, facecolor=color)
        except AttributeError:
            with warnings.catch_warnings(record=True):
                warnings.simplefilter('ignore', DeprecationWarning)
                selector.rect.set_color(color)
                selector.rectprops.update(dict(facecolor=color))

    def _click_override(self, event):
        """Override MPL radiobutton click detector to use transData."""
        ax = self.mne.radio_ax
        buttons = ax.buttons
        if (buttons.ignore(event) or event.button != 1 or event.inaxes != ax):
            return
        pclicked = ax.transData.inverted().transform((event.x, event.y))
        distances = {}
        for i, (p, t) in enumerate(zip(buttons.circles, buttons.labels)):
            if (t.get_window_extent().contains(event.x, event.y)
                    or np.linalg.norm(pclicked - p.center) < p.radius):
                distances[i] = np.linalg.norm(pclicked - p.center)
        if len(distances) > 0:
            closest = min(distances, key=distances.get)
            buttons.set_active(closest)

    def _set_active_button(self, idx):
        """Set active button in annotation dialog figure."""
        buttons = self.mne.radio_ax.buttons
        with _events_off(buttons):
            buttons.set_active(idx)
        for circle in buttons.circles:
            circle.set_facecolor(self.mne.parent_fig.mne.bgcolor)
        # active circle gets filled in, partially transparent
        color = list(buttons.circles[idx].get_edgecolor())
        color[-1] = 0.5
        buttons.circles[idx].set_facecolor(color)
        self.canvas.draw()


class MNESelectionFigure(MNEFigure):
    """Interactive dialog figure for channel selections."""

    def _close(self, event):
        """Handle close events."""
        self.mne.parent_fig.mne.child_figs.remove(self)
        self.mne.fig_selection = None
        # selection fig & main fig tightly integrated; closing one closes both
        plt.close(self.mne.parent_fig)

    def _keypress(self, event):
        """Handle keypress events."""
        if event.key in ('up', 'down', 'b'):
            self.mne.parent_fig._keypress(event)
        else:  # check for close key
            super()._keypress(event)

    def _radiopress(self, event):
        """Handle RadioButton clicks for channel selection groups."""
        selections_dict = self.mne.parent_fig.mne.ch_selections
        buttons = self.mne.radio_ax.buttons
        labels = [label.get_text() for label in buttons.labels]
        this_label = buttons.value_selected
        parent = self.mne.parent_fig
        if this_label == 'Custom' and not len(selections_dict['Custom']):
            with _events_off(buttons):
                buttons.set_active(self.mne.old_selection)
            return
        # clicking a selection cancels butterfly mode
        if parent.mne.butterfly:
            parent._toggle_butterfly()
            with _events_off(buttons):
                buttons.set_active(labels.index(this_label))
        parent._update_selection()

    def _set_custom_selection(self):
        """Set custom selection by lasso selector."""
        chs = self.lasso.selection
        parent = self.mne.parent_fig
        buttons = self.mne.radio_ax.buttons
        if not len(chs):
            return
        labels = [label.get_text() for label in buttons.labels]
        inds = np.in1d(parent.mne.ch_names, chs)
        parent.mne.ch_selections['Custom'] = inds.nonzero()[0]
        buttons.set_active(labels.index('Custom'))

    def _style_radio_buttons_butterfly(self):
        """Handle RadioButton state for keyboard interactions."""
        # Show all radio buttons as selected when in butterfly mode
        parent = self.mne.parent_fig
        buttons = self.mne.radio_ax.buttons
        color = (buttons.activecolor if parent.mne.butterfly else
                 parent.mne.bgcolor)
        for circle in buttons.circles:
            circle.set_facecolor(color)
        # when leaving butterfly mode, make most-recently-used selection active
        if not parent.mne.butterfly:
            with _events_off(buttons):
                buttons.set_active(self.mne.old_selection)
        # update the sensors too
        parent._update_highlighted_sensors()


class MNEBrowseFigure(BrowserBase, MNEFigure):
    """Interactive figure with scrollbars, for data browsing."""

    def __init__(self, inst, figsize, ica=None,
                 xlabel='Time (s)', **kwargs):
        from matplotlib.colors import to_rgba_array
        from matplotlib.patches import Rectangle
        from matplotlib.ticker import (FixedFormatter, FixedLocator,
                                       FuncFormatter, NullFormatter)
        from matplotlib.transforms import blended_transform_factory
        from matplotlib.widgets import Button
        from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
        from mpl_toolkits.axes_grid1.axes_size import Fixed

        self.backend_name = 'matplotlib'

        kwargs.update({'inst': inst,
                       'figsize': figsize,
                       'ica': ica,
                       'xlabel': xlabel})

        BrowserBase.__init__(self, **kwargs)
        MNEFigure.__init__(self, **kwargs)

        # MAIN AXES: default sizes (inches)
        # XXX simpler with constrained_layout? (when it's no longer "beta")
        l_margin = 1.
        r_margin = 0.1
        b_margin = 0.45
        t_margin = 0.25
        scroll_width = 0.25
        hscroll_dist = 0.25
        vscroll_dist = 0.1
        help_width = scroll_width * 2
        # MAIN AXES: default margins (figure-relative coordinates)
        left = self._inch_to_rel(l_margin - vscroll_dist - help_width)
        right = 1 - self._inch_to_rel(r_margin)
        bottom = self._inch_to_rel(b_margin, horiz=False)
        top = 1 - self._inch_to_rel(t_margin, horiz=False)
        width = right - left
        height = top - bottom
        position = [left, bottom, width, height]
        # Main axes must be a subplot for subplots_adjust to work (so user can
        # adjust margins). That's why we don't use the Divider class directly.
        ax_main = self.add_subplot(1, 1, 1, position=position)
        self.subplotpars.update(left=left, bottom=bottom, top=top, right=right)
        div = make_axes_locatable(ax_main)
        # this only gets shown in zen mode
        self.mne.zen_xlabel = ax_main.set_xlabel(xlabel)
        self.mne.zen_xlabel.set_visible(not self.mne.scrollbars_visible)
        # make sure background color of the axis is set
        if 'bgcolor' in kwargs:
            ax_main.set_facecolor(kwargs['bgcolor'])

        # SCROLLBARS
        ax_hscroll = div.append_axes(position='bottom',
                                     size=Fixed(scroll_width),
                                     pad=Fixed(hscroll_dist))
        ax_vscroll = div.append_axes(position='right',
                                     size=Fixed(scroll_width),
                                     pad=Fixed(vscroll_dist))
        ax_hscroll.get_yaxis().set_visible(False)
        ax_hscroll.set_xlabel(xlabel)
        ax_vscroll.set_axis_off()
        # HORIZONTAL SCROLLBAR PATCHES (FOR MARKING BAD EPOCHS)
        if self.mne.is_epochs:
            epoch_nums = self.mne.inst.selection
            for ix, _ in enumerate(epoch_nums):
                start = self.mne.boundary_times[ix]
                width = np.diff(self.mne.boundary_times[:2])[0]
                ax_hscroll.add_patch(
                    Rectangle((start, 0), width, 1, color='none',
                              zorder=self.mne.zorder['patch']))
            # both axes, major ticks: gridlines
            for _ax in (ax_main, ax_hscroll):
                _ax.xaxis.set_major_locator(
                    FixedLocator(self.mne.boundary_times[1:-1]))
                _ax.xaxis.set_major_formatter(NullFormatter())
            grid_kwargs = dict(color=self.mne.fgcolor, axis='x',
                               zorder=self.mne.zorder['grid'])
            ax_main.grid(linewidth=2, linestyle='dashed', **grid_kwargs)
            ax_hscroll.grid(alpha=0.5, linewidth=0.5, linestyle='solid',
                            **grid_kwargs)
            # main axes, minor ticks: ticklabel (epoch number) for every epoch
            ax_main.xaxis.set_minor_locator(FixedLocator(self.mne.midpoints))
            ax_main.xaxis.set_minor_formatter(FixedFormatter(epoch_nums))
            # hscroll axes, minor ticks: up to 20 ticklabels (epoch numbers)
            ax_hscroll.xaxis.set_minor_locator(
                FixedLocator(self.mne.midpoints, nbins=20))
            ax_hscroll.xaxis.set_minor_formatter(
                FuncFormatter(lambda x, pos: self._get_epoch_num_from_time(x)))
            # hide some ticks
            ax_main.tick_params(axis='x', which='major', bottom=False)
            ax_hscroll.tick_params(axis='x', which='both', bottom=False)
        else:
            # RAW / ICA X-AXIS TICK & LABEL FORMATTING
            ax_main.xaxis.set_major_formatter(
                FuncFormatter(partial(self._xtick_formatter,
                                      ax_type='main')))
            ax_hscroll.xaxis.set_major_formatter(
                FuncFormatter(partial(self._xtick_formatter,
                                      ax_type='hscroll')))
            if self.mne.time_format != 'float':
                for _ax in (ax_main, ax_hscroll):
                    _ax.set_xlabel('Time (HH:MM:SS)')

        # VERTICAL SCROLLBAR PATCHES (COLORED BY CHANNEL TYPE)
        ch_order = self.mne.ch_order
        for ix, pick in enumerate(ch_order):
            this_color = (self.mne.ch_color_bad
                          if self.mne.ch_names[pick] in self.mne.info['bads']
                          else self.mne.ch_color_dict)
            if isinstance(this_color, dict):
                this_color = this_color[self.mne.ch_types[pick]]
            ax_vscroll.add_patch(
                Rectangle((0, ix), 1, 1, color=this_color,
                          zorder=self.mne.zorder['patch']))
        ax_vscroll.set_ylim(len(ch_order), 0)
        ax_vscroll.set_visible(not self.mne.butterfly)
        # SCROLLBAR VISIBLE SELECTION PATCHES
        sel_kwargs = dict(alpha=0.3, linewidth=4, clip_on=False,
                          edgecolor=self.mne.fgcolor)
        vsel_patch = Rectangle((0, 0), 1, self.mne.n_channels,
                               facecolor=self.mne.bgcolor, **sel_kwargs)
        ax_vscroll.add_patch(vsel_patch)
        hsel_facecolor = np.average(
            np.vstack((to_rgba_array(self.mne.fgcolor),
                       to_rgba_array(self.mne.bgcolor))),
            axis=0, weights=(3, 1))  # 75% foreground, 25% background
        hsel_patch = Rectangle((self.mne.t_start, 0), self.mne.duration, 1,
                               facecolor=hsel_facecolor, **sel_kwargs)
        ax_hscroll.add_patch(hsel_patch)
        ax_hscroll.set_xlim(self.mne.first_time, self.mne.first_time +
                            self.mne.n_times / self.mne.info['sfreq'])
        # VLINE
        vline_color = (0., 0.75, 0.)
        vline_kwargs = dict(visible=False, zorder=self.mne.zorder['vline'])
        if self.mne.is_epochs:
            x = np.arange(self.mne.n_epochs)
            vline = ax_main.vlines(
                x, 0, 1, colors=vline_color, **vline_kwargs)
            vline.set_transform(blended_transform_factory(ax_main.transData,
                                                          ax_main.transAxes))
            vline_hscroll = None
        else:
            vline = ax_main.axvline(0, color=vline_color, **vline_kwargs)
            vline_hscroll = ax_hscroll.axvline(0, color=vline_color,
                                               **vline_kwargs)
        vline_text = ax_main.annotate(
            '', xy=(0, 0), xycoords='axes fraction', xytext=(-2, 0),
            textcoords='offset points', fontsize=10, ha='right', va='center',
            color=vline_color, **vline_kwargs)

        # HELP BUTTON: initialize in the wrong spot...
        ax_help = div.append_axes(position='left',
                                  size=Fixed(help_width),
                                  pad=Fixed(vscroll_dist))
        # HELP BUTTON: ...move it down by changing its locator
        loc = div.new_locator(nx=0, ny=0)
        ax_help.set_axes_locator(loc)
        # HELP BUTTON: make it a proper button
        with _patched_canvas(ax_help.figure):
            self.mne.button_help = Button(ax_help, 'Help')
        # PROJ BUTTON
        ax_proj = None
        if len(self.mne.projs) and not self.mne.inst.proj:
            proj_button_pos = [
                1 - self._inch_to_rel(r_margin + scroll_width),  # left
                self._inch_to_rel(b_margin, horiz=False),        # bottom
                self._inch_to_rel(scroll_width),                 # width
                self._inch_to_rel(scroll_width, horiz=False)     # height
            ]
            loc = div.new_locator(nx=4, ny=0)
            ax_proj = self.add_axes(proj_button_pos)
            ax_proj.set_axes_locator(loc)
            with _patched_canvas(ax_help.figure):
                self.mne.button_proj = Button(ax_proj, 'Prj')

        # INIT TRACES
        self.mne.trace_kwargs = dict(antialiased=True, linewidth=0.5)
        self.mne.traces = ax_main.plot(
            np.full((1, self.mne.n_channels), np.nan), **self.mne.trace_kwargs)

        # SAVE UI ELEMENT HANDLES
        vars(self.mne).update(
            ax_main=ax_main, ax_help=ax_help, ax_proj=ax_proj,
            ax_hscroll=ax_hscroll, ax_vscroll=ax_vscroll,
            vsel_patch=vsel_patch, hsel_patch=hsel_patch, vline=vline,
            vline_hscroll=vline_hscroll, vline_text=vline_text)

    def _get_size(self):
        return self.get_size_inches()

    def _resize(self, event):
        """Handle resize event for mne_browse-style plots (Raw/Epochs/ICA)."""
        old_width, old_height = self.mne.fig_size_px
        new_width, new_height = self._get_size_px()
        new_margins = _calc_new_margins(
            self, old_width, old_height, new_width, new_height)
        self.subplots_adjust(**new_margins)
        # zen mode bookkeeping
        self.mne.zen_w *= old_width / new_width
        self.mne.zen_h *= old_height / new_height
        self.mne.fig_size_px = (new_width, new_height)
        self.canvas.draw_idle()

    def _hover(self, event):
        """Handle motion event when annotating."""
        if (event.button is not None or event.xdata is None or
                event.inaxes != self.mne.ax_main):
            return
        if not self.mne.draggable_annotations:
            self._remove_annotation_hover_line()
            return
        from matplotlib.patheffects import Normal, Stroke
        for coll in self.mne.annotations:
            if coll.contains(event)[0]:
                path = coll.get_paths()
                assert len(path) == 1
                path = path[0]
                color = coll.get_edgecolors()[0]
                ylim = self.mne.ax_main.get_ylim()
                # are we on the left or right edge?
                _l = path.vertices[:, 0].min()
                _r = path.vertices[:, 0].max()
                x = _l if abs(event.xdata - _l) < abs(event.xdata - _r) else _r
                mask = path.vertices[:, 0] == x

                def drag_callback(x0):
                    path.vertices[mask, 0] = x0

                # create or update the DraggableLine
                hover_line = self.mne.annotation_hover_line
                if hover_line is None:
                    line = self.mne.ax_main.plot([x, x], ylim, color=color,
                                                 linewidth=2, pickradius=5.)[0]
                    hover_line = DraggableLine(
                        line, self._modify_annotation, drag_callback)
                else:
                    hover_line.set_x(x)
                    hover_line.drag_callback = drag_callback
                # style the line
                line = hover_line.line
                patheff = [Stroke(linewidth=4, foreground=color, alpha=0.5),
                           Normal()]
                line.set_path_effects(patheff if line.contains(event)[0] else
                                      patheff[1:])
                self.mne.ax_main.selector.active = False
                self.mne.annotation_hover_line = hover_line
                self.canvas.draw_idle()
                return
        self._remove_annotation_hover_line()

    def _keypress(self, event):
        """Handle keypress events."""
        key = event.key
        n_channels = self.mne.n_channels
        if self.mne.is_epochs:
            last_time = self.mne.n_times / self.mne.info['sfreq']
        else:
            last_time = self.mne.inst.times[-1]
        # scroll up/down
        if key in ('down', 'up', 'shift+down', 'shift+up'):
            key = key.split('+')[-1]
            direction = -1 if key == 'up' else 1
            # butterfly case
            if self.mne.butterfly:
                return
            # group_by case
            elif self.mne.fig_selection is not None:
                buttons = self.mne.fig_selection.mne.radio_ax.buttons
                labels = [label.get_text() for label in buttons.labels]
                current_label = buttons.value_selected
                current_idx = labels.index(current_label)
                selections_dict = self.mne.ch_selections
                penult = current_idx < (len(labels) - 1)
                pre_penult = current_idx < (len(labels) - 2)
                has_custom = selections_dict.get('Custom', None) is not None
                def_custom = len(selections_dict.get('Custom', list()))
                up_ok = key == 'up' and current_idx > 0
                down_ok = key == 'down' and (
                    pre_penult or
                    (penult and not has_custom) or
                    (penult and has_custom and def_custom))
                if up_ok or down_ok:
                    buttons.set_active(current_idx + direction)
            # normal case
            else:
                ceiling = len(self.mne.ch_order) - n_channels
                ch_start = self.mne.ch_start + direction * n_channels
                self.mne.ch_start = np.clip(ch_start, 0, ceiling)
                self._update_picks()
                self._update_vscroll()
                self._redraw()
        # scroll left/right
        elif key in ('right', 'left', 'shift+right', 'shift+left'):
            old_t_start = self.mne.t_start
            direction = 1 if key.endswith('right') else -1
            if self.mne.is_epochs:
                denom = 1 if key.startswith('shift') else self.mne.n_epochs
            else:
                denom = 1 if key.startswith('shift') else 4
            t_max = last_time - self.mne.duration
            t_start = self.mne.t_start + direction * self.mne.duration / denom
            self.mne.t_start = np.clip(t_start, self.mne.first_time, t_max)
            if self.mne.t_start != old_t_start:
                self._update_hscroll()
                self._redraw(annotations=True)
        # scale traces
        elif key in ('=', '+', '-'):
            scaler = 1 / 1.1 if key == '-' else 1.1
            self.mne.scale_factor *= scaler
            self._redraw(update_data=False)
        # change number of visible channels
        elif (key in ('pageup', 'pagedown') and
              self.mne.fig_selection is None and
              not self.mne.butterfly):
            new_n_ch = n_channels + (1 if key == 'pageup' else -1)
            self.mne.n_channels = np.clip(new_n_ch, 1, len(self.mne.ch_order))
            # add new chs from above if we're at the bottom of the scrollbar
            ch_end = self.mne.ch_start + self.mne.n_channels
            if ch_end > len(self.mne.ch_order) and self.mne.ch_start > 0:
                self.mne.ch_start -= 1
                self._update_vscroll()
            # redraw only if changed
            if self.mne.n_channels != n_channels:
                self._update_picks()
                self._update_trace_offsets()
                self._redraw(annotations=True)
        # change duration
        elif key in ('home', 'end'):
            old_dur = self.mne.duration
            dur_delta = 1 if key == 'end' else -1
            if self.mne.is_epochs:
                # prevent from showing zero epochs, or more epochs than we have
                self.mne.n_epochs = np.clip(self.mne.n_epochs + dur_delta,
                                            1, len(self.mne.inst))
                # use the length of one epoch as duration change
                min_dur = len(self.mne.inst.times) / self.mne.info['sfreq']
                new_dur = self.mne.duration + dur_delta * min_dur
            else:
                # never show fewer than 3 samples
                min_dur = 3 * np.diff(self.mne.inst.times[:2])[0]
                # use multiplicative dur_delta
                dur_delta = 5 / 4 if dur_delta > 0 else 4 / 5
                new_dur = self.mne.duration * dur_delta
            self.mne.duration = np.clip(new_dur, min_dur, last_time)
            if self.mne.duration != old_dur:
                if self.mne.t_start + self.mne.duration > last_time:
                    self.mne.t_start = last_time - self.mne.duration
                self._update_hscroll()
                self._redraw(annotations=True)
        elif key == '?':  # help window
            self._toggle_help_fig(event)
        elif key == 'a':  # annotation mode
            self._toggle_annotation_fig()
        elif key == 'b' and self.mne.instance_type != 'ica':  # butterfly mode
            self._toggle_butterfly()
        elif key == 'd':  # DC shift
            self.mne.remove_dc = not self.mne.remove_dc
            self._redraw()
        elif key == 'h':  # histogram
            self._toggle_epoch_histogram()
        elif key == 'j' and len(self.mne.projs):  # SSP window
            self._toggle_proj_fig()
        elif key == 'J' and len(self.mne.projs):
            self._toggle_proj_checkbox(event, toggle_all=True)
        elif key == 'p':  # toggle draggable annotations
            self._toggle_draggable_annotations(event)
            if self.mne.fig_annotation is not None:
                checkbox = self.mne.fig_annotation.mne.drag_checkbox
                with _events_off(checkbox):
                    checkbox.set_active(0)
        elif key == 's':  # scalebars
            self._toggle_scalebars(event)
        elif key == 'w':  # toggle noise cov whitening
            self._toggle_whitening()
        elif key == 'z':  # zen mode: hide scrollbars and buttons
            self._toggle_scrollbars()
            self._redraw(update_data=False)
        elif key == 't':
            self._toggle_time_format()
        else:  # check for close key / fullscreen toggle
            super()._keypress(event)

    def _buttonpress(self, event):
        """Handle mouse clicks."""
        butterfly = self.mne.butterfly
        annotating = self.mne.fig_annotation is not None
        ax_main = self.mne.ax_main
        inst = self.mne.inst
        # ignore middle clicks, scroll wheel events, and clicks outside axes
        if event.button not in (1, 3) or event.inaxes is None:
            return
        elif event.button == 1:  # left-click (primary)
            # click in main axes
            if (event.inaxes == ax_main and not annotating):
                if self.mne.instance_type == 'epochs' or not butterfly:
                    for line in self.mne.traces + self.mne.epoch_traces:
                        if line.contains(event)[0]:
                            if self.mne.instance_type == 'epochs':
                                self._toggle_bad_epoch(event)
                            else:
                                idx = self.mne.traces.index(line)
                                self._toggle_bad_channel(idx)
                            return
                self._show_vline(event.xdata)  # butterfly / not on data trace
                self._redraw(update_data=False, annotations=False)
                return
            # click in vertical scrollbar
            elif event.inaxes == self.mne.ax_vscroll:
                if self.mne.fig_selection is not None:
                    self._change_selection_vscroll(event)
                elif self._check_update_vscroll_clicked(event):
                    self._redraw()
            # click in horizontal scrollbar
            elif event.inaxes == self.mne.ax_hscroll:
                if self._check_update_hscroll_clicked(event):
                    self._redraw(annotations=True)
            # click on proj button
            elif event.inaxes == self.mne.ax_proj:
                self._toggle_proj_fig(event)
            # click on help button
            elif event.inaxes == self.mne.ax_help:
                self._toggle_help_fig(event)
        else:  # right-click (secondary)
            if annotating:
                if any(c.contains(event)[0] for c in ax_main.collections):
                    xdata = event.xdata - self.mne.first_time
                    start = _sync_onset(inst, inst.annotations.onset)
                    end = start + inst.annotations.duration
                    ann_idx = np.where((xdata > start) & (xdata < end))[0]
                    for idx in sorted(ann_idx)[::-1]:
                        # only remove visible annotation spans
                        descr = inst.annotations[idx]['description']
                        if self.mne.visible_annotations[descr]:
                            inst.annotations.delete(idx)
                self._remove_annotation_hover_line()
                self._draw_annotations()
                self.canvas.draw_idle()
            elif event.inaxes == ax_main:
                self._toggle_vline(False)

    def _pick(self, event):
        """Handle matplotlib pick events."""
        from matplotlib.text import Text
        if self.mne.butterfly:
            return
        # clicked on channel name
        if isinstance(event.artist, Text):
            ch_name = event.artist.get_text()
            ind = self.mne.ch_names[self.mne.picks].tolist().index(ch_name)
            if event.mouseevent.button == 1:  # left click
                self._toggle_bad_channel(ind)
            elif event.mouseevent.button == 3:  # right click
                self._create_ch_context_fig(ind)

    def _create_ch_context_fig(self, idx):
        fig = super()._create_ch_context_fig(idx)
        plt_show(fig=fig)

    def _new_child_figure(self, fig_name, **kwargs):
        """Instantiate a new MNE dialog figure (with event listeners)."""
        fig = _figure(toolbar=False, parent_fig=self, fig_name=fig_name,
                      **kwargs)
        fig._add_default_callbacks()
        self.mne.child_figs.append(fig)
        if isinstance(fig_name, str):
            setattr(self.mne, fig_name, fig)
        return fig

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # HELP DIALOG
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _create_help_fig(self):
        """Create help dialog window."""
        text = {key: val for key, val in self._get_help_text().items()
                if val is not None}
        keys = ''
        vals = ''
        for key, val in text.items():
            newsection = '\n' if key.startswith('_') else ''
            key = key[1:] if key.startswith('_') else key
            newlines = '\n' * len(val.split('\n'))  # handle multiline values
            keys += f'{newsection}{key}      {newlines}'
            vals += f'{newsection}{val}\n'
        # calc figure size
        n_lines = len(keys.split('\n'))
        longest_key = max(len(k) for k in text.keys())
        longest_val = max(max(len(w) for w in v.split('\n')) if '\n' in v else
                          len(v) for v in text.values())
        width = (longest_key + longest_val) / 12
        height = (n_lines) / 5
        # create figure and axes
        fig = self._new_child_figure(figsize=(width, height),
                                     fig_name='fig_help',
                                     window_title='Help')
        ax = fig.add_axes((0.01, 0.01, 0.98, 0.98))
        ax.set_axis_off()
        kwargs = dict(va='top', linespacing=1.5, usetex=False)
        ax.text(0.42, 1, keys, ma='right', ha='right', **kwargs)
        ax.text(0.42, 1, vals, ma='left', ha='left', **kwargs)

    def _toggle_help_fig(self, event):
        """Show/hide the help dialog window."""
        if self.mne.fig_help is None:
            self._create_help_fig()
            plt_show(fig=self.mne.fig_help)
        else:
            plt.close(self.mne.fig_help)

    def _get_help_text(self):
        """Generate help dialog text; `None`-valued entries removed later."""
        inst = self.mne.instance_type
        is_raw = inst == 'raw'
        is_epo = inst == 'epochs'
        is_ica = inst == 'ica'
        has_proj = bool(len(self.mne.projs))
        # adapt keys to different platforms
        is_mac = platform.system() == 'Darwin'
        dur_keys = ('fn + ←', 'fn + →') if is_mac else ('Home', 'End')
        ch_keys = ('fn + ↑', 'fn + ↓') if is_mac else ('Page up', 'Page down')
        # adapt descriptions to different instance types
        ch_cmp = 'component' if is_ica else 'channel'
        ch_epo = 'epoch' if is_epo else 'channel'
        ica_bad = 'Mark/unmark component for exclusion'
        dur_vals = ([f'Show {n} epochs' for n in ('fewer', 'more')]
                    if self.mne.is_epochs else
                    [f'Show {d} time window' for d in ('shorter', 'longer')])
        ch_vals = [f'{inc_dec} number of visible {ch_cmp}s' for inc_dec in
                   ('Increase', 'Decrease')]
        lclick_data = ica_bad if is_ica else f'Mark/unmark bad {ch_epo}'
        lclick_name = (ica_bad if is_ica else 'Mark/unmark bad channel')
        rclick_name = dict(ica='Show diagnostics for component',
                           epochs='Show imageplot for channel',
                           raw='Show channel location')[inst]
        # TODO not yet implemented
        # ldrag = ('Show spectrum plot for selected time span;\nor (in '
        #          'annotation mode) add annotation') if inst== 'raw' else None
        ldrag = 'add annotation (in annotation mode)' if is_raw else None
        noise_cov = (None if self.mne.noise_cov is None else
                     'Toggle signal whitening')
        scrl = '1 epoch' if self.mne.is_epochs else '¼ window'
        # below, value " " is a hack to make "\n".split(value) have length 1
        help_text = OrderedDict([
            ('_NAVIGATION', ' '),
            ('→', f'Scroll {scrl} right (scroll full window with Shift + →)'),
            ('←', f'Scroll {scrl} left (scroll full window with Shift + ←)'),
            (dur_keys[0], dur_vals[0]),
            (dur_keys[1], dur_vals[1]),
            ('↑', f'Scroll up ({ch_cmp}s)'),
            ('↓', f'Scroll down ({ch_cmp}s)'),
            (ch_keys[0], ch_vals[0]),
            (ch_keys[1], ch_vals[1]),
            ('_SIGNAL TRANSFORMATIONS', ' '),
            ('+ or =', 'Increase signal scaling'),
            ('-', 'Decrease signal scaling'),
            ('b', 'Toggle butterfly mode' if not is_ica else None),
            ('d', 'Toggle DC removal' if is_raw else None),
            ('w', noise_cov),
            ('_USER INTERFACE', ' '),
            ('a', 'Toggle annotation mode' if is_raw else None),
            ('h', 'Toggle peak-to-peak histogram' if is_epo else None),
            ('j', 'Toggle SSP projector window' if has_proj else None),
            ('shift+j', 'Toggle all SSPs'),
            ('p', 'Toggle draggable annotations' if is_raw else None),
            ('s', 'Toggle scalebars' if not is_ica else None),
            ('z', 'Toggle scrollbars'),
            ('t', 'Toggle time format' if not is_epo else None),
            ('F11', 'Toggle fullscreen' if not is_mac else None),
            ('?', 'Open this help window'),
            ('esc', 'Close focused figure or dialog window'),
            ('_MOUSE INTERACTION', ' '),
            (f'Left-click {ch_cmp} name', lclick_name),
            (f'Left-click {ch_cmp} data', lclick_data),
            ('Left-click-and-drag on plot', ldrag),
            ('Left-click on plot background', 'Place vertical guide'),
            ('Right-click on plot background', 'Clear vertical guide'),
            ('Right-click on channel name', rclick_name)
        ])
        return help_text

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # ANNOTATIONS
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _create_annotation_fig(self):
        """Create the annotation dialog window."""
        from matplotlib.widgets import Button, CheckButtons, SpanSelector
        from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
        from mpl_toolkits.axes_grid1.axes_size import Fixed

        # make figure
        labels = np.array(sorted(set(self.mne.inst.annotations.description)))
        radio_button_h = self._compute_annotation_figsize(len(labels))
        figsize = (ANNOTATION_FIG_W, ANNOTATION_FIG_MIN_H + radio_button_h)
        fig = self._new_child_figure(figsize=figsize,
                                     FigureClass=MNEAnnotationFigure,
                                     fig_name='fig_annotation',
                                     window_title='Annotations')
        # make main axes
        left = fig._inch_to_rel(ANNOTATION_FIG_PAD)
        bottom = fig._inch_to_rel(ANNOTATION_FIG_PAD, horiz=False)
        width = 1 - 2 * left
        height = 1 - 2 * bottom
        fig.mne.radio_ax = fig.add_axes((left, bottom, width, height),
                                        frame_on=False, aspect='equal')
        div = make_axes_locatable(fig.mne.radio_ax)
        # append show/hide checkboxes at right
        fig.mne.show_hide_ax = div.append_axes(
            position='right', size=Fixed(ANNOTATION_FIG_CHECKBOX_COLUMN_W),
            pad=Fixed(ANNOTATION_FIG_PAD), aspect='equal',
            sharey=fig.mne.radio_ax)
        # populate w/ radio buttons & labels
        self._update_annotation_fig()
        # append instructions at top
        instructions_ax = div.append_axes(position='top', size=Fixed(1),
                                          pad=Fixed(5 * ANNOTATION_FIG_PAD))
        # XXX when we support a newer matplotlib (something >3.0) the
        # instructions can have inline bold formatting:
        # instructions = '\n'.join(
        #     [r'$\mathbf{Left‐click~&~drag~on~plot:}$ create/modify annotation',  # noqa E501
        #      r'$\mathbf{Right‐click~on~plot~annotation:}$ delete annotation',
        #      r'$\mathbf{Type~in~annotation~window:}$ modify new label name',
        #      r'$\mathbf{Enter~(or~click~button):}$ add new label to list',
        #      r'$\mathbf{Esc:}$ exit annotation mode & close this window'])
        instructions = '\n'.join(
            ['Left click & drag on plot: create/modify annotation',
             'Right click on annotation highlight: delete annotation',
             'Type in this window: modify new label name',
             'Enter (or click button): add new label to list',
             'Esc: exit annotation mode & close this dialog window'])
        instructions_ax.text(0, 1, instructions, va='top', ha='left',
                             linespacing=1.7,
                             usetex=False)  # force use of MPL mathtext parser
        instructions_ax.set_axis_off()
        # append text entry axes at bottom
        text_entry_ax = div.append_axes(position='bottom',
                                        size=Fixed(3 * ANNOTATION_FIG_PAD),
                                        pad=Fixed(ANNOTATION_FIG_PAD))
        text_entry_ax.text(0.4, 0.5, 'New label:', va='center', ha='right',
                           weight='bold')
        fig.label = text_entry_ax.text(0.5, 0.5, 'BAD_', va='center',
                                       ha='left')
        text_entry_ax.set_axis_off()
        # append button at bottom
        button_ax = div.append_axes(position='bottom',
                                    size=Fixed(3 * ANNOTATION_FIG_PAD),
                                    pad=Fixed(ANNOTATION_FIG_PAD))
        fig.button = Button(button_ax, 'Add new label')
        fig.button.on_clicked(self._add_annotation_label)
        plt_show(fig=fig)
        # add "draggable" checkbox
        drag_ax_height = 3 * ANNOTATION_FIG_PAD
        drag_ax = div.append_axes('bottom', size=Fixed(drag_ax_height),
                                  pad=Fixed(ANNOTATION_FIG_PAD),
                                  aspect='equal')
        checkbox = CheckButtons(drag_ax, labels=('Draggable edges?',),
                                actives=(self.mne.draggable_annotations,))
        checkbox.on_clicked(self._toggle_draggable_annotations)
        fig.mne.drag_checkbox = checkbox
        # reposition & resize axes
        width_in, height_in = fig.get_size_inches()
        width_ax = fig._inch_to_rel(width_in
                                    - ANNOTATION_FIG_CHECKBOX_COLUMN_W
                                    - 3 * ANNOTATION_FIG_PAD)
        aspect = width_ax / fig._inch_to_rel(drag_ax_height)
        drag_ax.set_xlim(0, aspect)
        drag_ax.set_axis_off()
        # reposition & resize checkbox & label
        rect = checkbox.rectangles[0]
        _pad, _size = (0.2, 0.6)
        rect.set_bounds(_pad, _pad, _size, _size)
        lines = checkbox.lines[0]
        for line, direction in zip(lines, (1, -1)):
            line.set_xdata((_pad, _pad + _size)[::direction])
            line.set_ydata((_pad, _pad + _size))
        text = checkbox.labels[0]
        text.set(position=(3 * _pad + _size, 0.45), va='center')
        for artist in lines + (rect, text):
            artist.set_transform(drag_ax.transData)
        # setup interactivity in plot window
        col = ('#ff0000' if len(fig.mne.radio_ax.buttons.circles) < 1 else
               fig.mne.radio_ax.buttons.circles[0].get_edgecolor())
        # TODO: we would like useblit=True here, but it behaves oddly when the
        # first span is dragged (subsequent spans seem to work OK)
        rect_kw = _prop_kw('rect', dict(alpha=0.5, facecolor=col))
        selector = SpanSelector(self.mne.ax_main, self._select_annotation_span,
                                'horizontal', minspan=0.1, useblit=False,
                                **rect_kw)
        self.mne.ax_main.selector = selector
        self.mne._callback_ids['motion_notify_event'] = \
            self.canvas.mpl_connect('motion_notify_event', self._hover)

    def _toggle_visible_annotations(self, event):
        """Enable/disable display of annotations on a per-label basis."""
        checkboxes = self.mne.show_hide_annotation_checkboxes
        labels = [t.get_text() for t in checkboxes.labels]
        actives = checkboxes.get_status()
        self.mne.visible_annotations = dict(zip(labels, actives))
        self._redraw(update_data=False, annotations=True)

    def _toggle_draggable_annotations(self, event):
        """Enable/disable draggable annotation edges."""
        self.mne.draggable_annotations = not self.mne.draggable_annotations

    def _update_annotation_fig(self):
        """Draw or redraw the radio buttons and annotation labels."""
        from matplotlib.widgets import CheckButtons, RadioButtons

        # define shorthand variables
        fig = self.mne.fig_annotation
        ax = fig.mne.radio_ax
        labels = self._get_annotation_labels()
        # compute new figsize
        radio_button_h = self._compute_annotation_figsize(len(labels))
        fig.set_size_inches(ANNOTATION_FIG_W,
                            ANNOTATION_FIG_MIN_H + radio_button_h,
                            forward=True)
        # populate center axes with labels & radio buttons
        ax.clear()
        title = 'Existing labels:' if len(labels) else 'No existing labels'
        ax.set_title(title, size=None, loc='left')
        ax.buttons = RadioButtons(ax, labels)
        # adjust xlim to keep equal aspect & full width (keep circles round)
        aspect = (ANNOTATION_FIG_W - ANNOTATION_FIG_CHECKBOX_COLUMN_W
                  - 3 * ANNOTATION_FIG_PAD) / radio_button_h
        ax.set_xlim((0, aspect))
        # style the buttons & adjust spacing
        radius = 0.15
        circles = ax.buttons.circles
        for circle, label in zip(circles, ax.buttons.labels):
            circle.set_transform(ax.transData)
            center = ax.transData.inverted().transform(
                ax.transAxes.transform((0.1, 0)))
            circle.set_center((center[0], circle.center[1]))
            circle.set_edgecolor(
                self.mne.annotation_segment_colors[label.get_text()])
            circle.set_linewidth(4)
            circle.set_radius(radius / len(labels))
        # style the selected button
        if len(labels):
            fig._set_active_button(0)
        # add event listeners
        ax.buttons.disconnect_events()  # clear MPL default listeners
        ax.buttons.on_clicked(fig._radiopress)
        ax.buttons.connect_event('button_press_event', fig._click_override)

        # now do the show/hide checkboxes
        show_hide_ax = fig.mne.show_hide_ax
        show_hide_ax.clear()
        show_hide_ax.set_axis_off()
        aspect = ANNOTATION_FIG_CHECKBOX_COLUMN_W / radio_button_h
        show_hide_ax.set(xlim=(0, aspect), ylim=(0, 1))
        # ensure new labels have checkbox values
        check_values = {label: False for label in labels}
        check_values.update(self.mne.visible_annotations)  # existing checks
        actives = [check_values[label] for label in labels]
        # regenerate checkboxes
        checkboxes = CheckButtons(ax=fig.mne.show_hide_ax,
                                  labels=labels,
                                  actives=actives)
        checkboxes.on_clicked(self._toggle_visible_annotations)
        # add title, hide labels
        show_hide_ax.set_title('show/\nhide ', size=None, loc='right')
        for label in checkboxes.labels:
            label.set_visible(False)
        # fix aspect and right-align
        if len(labels) == 1:
            bounds = (0.05, 0.375, 0.25, 0.25)  # undo MPL special case
            checkboxes.rectangles[0].set_bounds(bounds)
            for line, step in zip(checkboxes.lines[0], (1, -1)):
                line.set_xdata((bounds[0], bounds[0] + bounds[2]))
                line.set_ydata((bounds[1], bounds[1] + bounds[3])[::step])
        for rect in checkboxes.rectangles:
            rect.set_transform(show_hide_ax.transData)
            bbox = rect.get_bbox()
            bounds = (aspect, bbox.ymin, -bbox.width, bbox.height)
            rect.set_bounds(bounds)
            rect.set_clip_on(False)
        for line in np.array(checkboxes.lines).ravel():
            line.set_transform(show_hide_ax.transData)
            line.set_xdata(aspect + 0.05 - np.array(line.get_xdata()))
        # store state
        self.mne.visible_annotations = check_values
        self.mne.show_hide_annotation_checkboxes = checkboxes

    def _toggle_annotation_fig(self):
        """Show/hide the annotation dialog window."""
        if self.mne.fig_annotation is None and not self.mne.is_epochs:
            self._create_annotation_fig()
        else:
            plt.close(self.mne.fig_annotation)

    def _compute_annotation_figsize(self, n_labels):
        """Adapt size of Annotation UI to accommodate the number of buttons.

        self._create_annotation_fig() implements the following:

        Fixed part of height:
        0.1  top margin
        1.0  instructions
        0.5  padding below instructions
        ---  (variable-height axis for label list, returned by this method)
        0.1  padding above text entry
        0.3  text entry
        0.1  padding above button
        0.3  button
        0.1  padding above checkbox
        0.3  checkbox
        0.1  bottom margin
        ------------------------------------------
        2.9  total fixed height
        """
        return max(ANNOTATION_FIG_PAD, 0.7 * n_labels)

    def _add_annotation_label(self, event):
        """Add new annotation description."""
        text = self.mne.fig_annotation.label.get_text()
        self.mne.new_annotation_labels.append(text)
        self._setup_annotation_colors()
        self._update_annotation_fig()
        # automatically activate new label's radio button
        idx = [label.get_text() for label in
               self.mne.fig_annotation.mne.radio_ax.buttons.labels].index(text)
        self.mne.fig_annotation._set_active_button(idx)
        # simulate a click on the radiobutton → update the span selector color
        self.mne.fig_annotation._radiopress(event=None)
        # reset the text entry box's text
        self.mne.fig_annotation.label.set_text('BAD_')

    def _select_annotation_span(self, vmin, vmax):
        """Handle annotation span selector."""
        onset = _sync_onset(self.mne.inst, vmin, True) - self.mne.first_time
        duration = vmax - vmin
        buttons = self.mne.fig_annotation.mne.radio_ax.buttons
        labels = [label.get_text() for label in buttons.labels]
        if buttons.value_selected is not None:
            active_idx = labels.index(buttons.value_selected)
            _merge_annotations(onset, onset + duration, labels[active_idx],
                               self.mne.inst.annotations)
            # if adding a span with an annotation label that is hidden, show it
            if not self.mne.visible_annotations[buttons.value_selected]:
                self.mne.show_hide_annotation_checkboxes.set_active(active_idx)
            self._redraw(update_data=False, annotations=True)
        else:
            logger.warning('No annotation-label exists! '
                           'Add one by typing the name and clicking '
                           'on "Add new label" in the annotation-dialog.')

    def _remove_annotation_hover_line(self):
        """Remove annotation line from the plot and reactivate selector."""
        if self.mne.annotation_hover_line is not None:
            self.mne.annotation_hover_line.remove()
            self.mne.annotation_hover_line = None
            self.mne.ax_main.selector.active = True
            self.canvas.draw()

    def _modify_annotation(self, old_x, new_x):
        """Modify annotation."""
        segment = np.array(np.where(self.mne.annotation_segments == old_x))
        if segment.shape[1] == 0:
            return
        raw = self.mne.inst
        annotations = raw.annotations
        first_time = self.mne.first_time
        idx = [segment[0][0], segment[1][0]]
        onset = _sync_onset(raw, self.mne.annotation_segments[idx[0]][0], True)
        ann_idx = np.where(annotations.onset == onset - first_time)[0]
        if idx[1] == 0:  # start of annotation
            onset = _sync_onset(raw, new_x, True) - first_time
            duration = annotations.duration[ann_idx] + old_x - new_x
        else:  # end of annotation
            onset = annotations.onset[ann_idx]
            duration = _sync_onset(raw, new_x, True) - onset - first_time
        if duration < 0:
            onset += duration
            duration *= -1.
        _merge_annotations(onset, onset + duration,
                           annotations.description[ann_idx],
                           annotations, ann_idx)
        self._draw_annotations()
        self._remove_annotation_hover_line()
        self.canvas.draw_idle()

    def _clear_annotations(self):
        """Clear all annotations from the figure."""
        for annot in list(self.mne.annotations):
            annot.remove()
            self.mne.annotations.remove(annot)
        for annot in list(self.mne.hscroll_annotations):
            annot.remove()
            self.mne.hscroll_annotations.remove(annot)
        for text in list(self.mne.annotation_texts):
            text.remove()
            self.mne.annotation_texts.remove(text)

    def _draw_annotations(self):
        """Draw (or redraw) the annotation spans."""
        self._clear_annotations()
        self._update_annotation_segments()
        segments = self.mne.annotation_segments
        times = self.mne.times
        ax = self.mne.ax_main
        ylim = ax.get_ylim()
        for idx, (start, end) in enumerate(segments):
            descr = self.mne.inst.annotations.description[idx]
            segment_color = self.mne.annotation_segment_colors[descr]
            kwargs = dict(color=segment_color, alpha=0.3,
                          zorder=self.mne.zorder['ann'])
            if self.mne.visible_annotations[descr]:
                # draw all segments on ax_hscroll
                annot = self.mne.ax_hscroll.fill_betweenx((0, 1), start, end,
                                                          **kwargs)
                self.mne.hscroll_annotations.append(annot)
                # draw only visible segments on ax_main
                visible_segment = np.clip([start, end], times[0], times[-1])
                if np.diff(visible_segment) > 0:
                    annot = ax.fill_betweenx(ylim, *visible_segment, **kwargs)
                    self.mne.annotations.append(annot)
                    xy = (visible_segment.mean(), ylim[1])
                    text = ax.annotate(descr, xy, xytext=(0, 9),
                                       textcoords='offset points', ha='center',
                                       va='baseline', color=segment_color)
                    self.mne.annotation_texts.append(text)

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # CHANNEL SELECTION GUI
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _create_selection_fig(self):
        """Create channel selection dialog window."""
        from matplotlib.colors import to_rgb
        from matplotlib.gridspec import GridSpec
        from matplotlib.widgets import RadioButtons

        # make figure
        fig = self._new_child_figure(figsize=(3, 7),
                                     FigureClass=MNESelectionFigure,
                                     fig_name='fig_selection',
                                     window_title='Channel selection')
        # XXX when matplotlib 3.3 is min version, replace this with
        # XXX gs = fig.add_gridspec(15, 1)
        gs = GridSpec(nrows=15, ncols=1)
        # add sensor plot at top
        fig.mne.sensor_ax = fig.add_subplot(gs[:5])
        plot_sensors(self.mne.info, kind='select', ch_type='all', title='',
                     axes=fig.mne.sensor_ax, ch_groups=self.mne.group_by,
                     show=False)
        fig.subplots_adjust(bottom=0.01, top=0.99, left=0.01, right=0.99)
        # style the sensors so the selection is easier to distinguish
        fig.lasso.linewidth_selected = 2
        self._update_highlighted_sensors()
        # add radio button axes
        radio_ax = fig.add_subplot(gs[5:-3], frame_on=False, aspect='equal')
        fig.mne.radio_ax = radio_ax
        selections_dict = self.mne.ch_selections
        selections_dict.update(Custom=np.array([], dtype=int))  # for lasso
        labels = list(selections_dict)
        # make & style the radio buttons
        activecolor = to_rgb(self.mne.fgcolor) + (0.5,)
        radio_ax.buttons = RadioButtons(radio_ax, labels,
                                        activecolor=activecolor)
        fig.mne.old_selection = 0
        for circle in radio_ax.buttons.circles:
            circle.set_radius(0.25 / len(labels))
            circle.set_linewidth(2)
            circle.set_edgecolor(self.mne.fgcolor)
        fig._style_radio_buttons_butterfly()
        # add instructions at bottom
        instructions = (
            'To use a custom selection, first click-drag on the sensor plot '
            'to "lasso" the sensors you want to select, or hold Ctrl while '
            'clicking individual sensors. Holding Ctrl while click-dragging '
            'allows a lasso selection adding to (rather than replacing) the '
            'existing selection.')
        instructions_ax = fig.add_subplot(gs[-3:], frame_on=False)
        instructions_ax.text(0.04, 0.08, instructions, va='bottom', ha='left',
                             ma='left', wrap=True)
        instructions_ax.set_axis_off()
        # add event listeners
        radio_ax.buttons.on_clicked(fig._radiopress)
        fig.lasso.callbacks.append(fig._set_custom_selection)

    def _change_selection_vscroll(self, event):
        """Handle clicks on vertical scrollbar when using selections."""
        buttons = self.mne.fig_selection.mne.radio_ax.buttons
        labels = [label.get_text() for label in buttons.labels]
        offset = 0
        selections_dict = self.mne.ch_selections
        for idx, label in enumerate(labels):
            offset += len(selections_dict[label])
            if event.ydata < offset:
                with _events_off(buttons):
                    buttons.set_active(idx)
                self.mne.fig_selection._radiopress(event)
                return

    def _update_selection(self):
        """Update visible channels based on selection dialog interaction."""
        selections_dict = self.mne.ch_selections
        fig = self.mne.fig_selection
        buttons = fig.mne.radio_ax.buttons
        label = buttons.value_selected
        labels = [_label.get_text() for _label in buttons.labels]
        self.mne.fig_selection.mne.old_selection = labels.index(label)
        self.mne.picks = selections_dict[label]
        self.mne.n_channels = len(self.mne.picks)
        self._update_highlighted_sensors()
        # if "Vertex" is defined, some channels appear twice, so if
        # "Vertex" is selected, ch_start should be the *first* match;
        # otherwise it should be the *last* match (since "Vertex" is
        # always the first selection group, if it exists).
        index = 0 if label == 'Vertex' else -1
        ch_order = np.concatenate(list(selections_dict.values()))
        ch_start = np.where(ch_order == self.mne.picks[0])[0][index]
        self.mne.ch_start = ch_start
        self._update_trace_offsets()
        self._update_vscroll()
        self._redraw(annotations=True)

    def _update_highlighted_sensors(self):
        """Update the sensor plot to show what is selected."""
        inds = np.in1d(self.mne.fig_selection.lasso.ch_names,
                       self.mne.ch_names[self.mne.picks]).nonzero()[0]
        self.mne.fig_selection.lasso.select_many(inds)

    def _update_bad_sensors(self, pick, mark_bad):
        """Update the sensor plot to reflect (un)marked bad channels."""
        # replicate plotting order from plot_sensors(), to get index right
        sensor_picks = list()
        ch_indices = channel_indices_by_type(self.mne.info)
        for this_type in _DATA_CH_TYPES_SPLIT:
            if this_type in self.mne.ch_types:
                sensor_picks.extend(ch_indices[this_type])
        sensor_idx = np.in1d(sensor_picks, pick).nonzero()[0]
        # change the sensor color
        fig = self.mne.fig_selection
        fig.lasso.ec[sensor_idx, 0] = float(mark_bad)  # change R of RGBA array
        fig.lasso.collection.set_edgecolors(fig.lasso.ec)
        fig.canvas.draw_idle()

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # PROJECTORS & BAD CHANNELS
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _create_proj_fig(self):
        """Create the projectors dialog window."""
        from matplotlib.widgets import Button, CheckButtons

        projs = self.mne.projs
        labels = [p['desc'] for p in projs]
        for ix, active in enumerate(self.mne.projs_active):
            if active:
                labels[ix] += ' (already applied)'
        # make figure
        width = max([4.5, max([len(label) for label in labels]) / 8 + 0.5])
        height = (len(projs) + 1) / 6 + 1.5
        fig = self._new_child_figure(figsize=(width, height),
                                     fig_name='fig_proj',
                                     window_title='SSP projection vectors')
        # pass through some proj fig keypresses to the parent
        fig.canvas.mpl_connect(
            'key_press_event',
            lambda ev: self._keypress(ev) if ev.key in 'jJ' else None)
        # make axes
        offset = (1 / 6 / height)
        position = (0, offset, 1, 0.8 - offset)
        ax = fig.add_axes(position, frame_on=False, aspect='equal')
        # make title
        first_line = ('Projectors already applied to the data are dimmed.\n'
                      if any(self.mne.projs_active) else '')
        second_line = 'Projectors marked with "X" are active on the plot.'
        ax.set_title(f'{first_line}{second_line}')
        # draw checkboxes
        checkboxes = CheckButtons(ax, labels=labels, actives=self.mne.projs_on)
        # gray-out already applied projectors
        for label, rect, lines in zip(checkboxes.labels,
                                      checkboxes.rectangles,
                                      checkboxes.lines):
            if label.get_text().endswith('(already applied)'):
                label.set_color('0.5')
                rect.set_edgecolor('0.7')
                [x.set_color('0.7') for x in lines]
            rect.set_linewidth(1)
        # add "toggle all" button
        ax_all = fig.add_axes((0.25, 0.01, 0.5, offset), frame_on=True)
        fig.mne.proj_all = Button(ax_all, 'Toggle all')
        # add event listeners
        checkboxes.on_clicked(self._toggle_proj_checkbox)
        fig.mne.proj_all.on_clicked(partial(self._toggle_proj_checkbox,
                                            toggle_all=True))
        # save params
        fig.mne.proj_checkboxes = checkboxes
        # show figure
        self.mne.fig_proj.canvas.draw()
        plt_show(fig=self.mne.fig_proj, warn=False)

    def _toggle_proj_fig(self, event=None):
        """Show/hide the projectors dialog window."""
        if self.mne.fig_proj is None:
            self._create_proj_fig()
        else:
            plt.close(self.mne.fig_proj)

    def _toggle_proj_checkbox(self, event, toggle_all=False):
        """Perform operations when proj boxes clicked."""
        on = self.mne.projs_on
        applied = self.mne.projs_active
        fig = self.mne.fig_proj
        new_state = (np.full_like(on, not all(on)) if toggle_all else
                     np.array(fig.mne.proj_checkboxes.get_status()))
        # update Xs when toggling all
        if fig is not None:
            if toggle_all:
                with _events_off(fig.mne.proj_checkboxes):
                    for ix in np.where(on != new_state)[0]:
                        fig.mne.proj_checkboxes.set_active(ix)
            # don't allow disabling already-applied projs
            with _events_off(fig.mne.proj_checkboxes):
                for ix in np.where(applied)[0]:
                    if not new_state[ix]:
                        fig.mne.proj_checkboxes.set_active(ix)
        new_state[applied] = True
        # update the data if necessary
        if not np.array_equal(on, new_state):
            self.mne.projs_on = new_state
            self._update_projector()
            self._redraw()

    def _toggle_epoch_histogram(self):
        """Show or hide peak-to-peak histogram of channel amplitudes."""
        if self.mne.instance_type == 'epochs':
            if self.mne.fig_histogram is None:
                self._create_epoch_histogram()
            else:
                plt.close(self.mne.fig_histogram)

    def _toggle_bad_channel(self, idx):
        """Mark/unmark bad channels; `idx` is index of *visible* channels."""
        color, pick, marked_bad = super()._toggle_bad_channel(idx)

        # update sensor color (if in selection mode)
        if self.mne.fig_selection is not None:
            self._update_bad_sensors(pick, marked_bad)
        # update vscroll color
        vscroll_idx = (self.mne.ch_order == pick).nonzero()[0]
        for _idx in vscroll_idx:
            self.mne.ax_vscroll.patches[_idx].set_color(color)
        # redraw
        self._redraw()

    def _toggle_bad_epoch(self, event):
        """Mark/unmark bad epochs."""
        epoch_ix, color = super()._toggle_bad_epoch(event.xdata)
        self.mne.ax_hscroll.patches[epoch_ix].set_color(color)
        self._redraw(update_data=False)

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # SCROLLBARS
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _update_zen_mode_offsets(self):
        """Compute difference between main axes edges and scrollbar edges."""
        self.mne.fig_size_px = self._get_size_px()
        self.mne.zen_w = (self.mne.ax_vscroll.get_position().xmax -
                          self.mne.ax_main.get_position().xmax)
        self.mne.zen_h = (self.mne.ax_main.get_position().ymin -
                          self.mne.ax_hscroll.get_position().ymin)

    def _toggle_scrollbars(self):
        """Show or hide scrollbars (A.K.A. zen mode)."""
        self._update_zen_mode_offsets()
        # grow/shrink main axes to take up space from (or make room for)
        # scrollbars. We can't use ax.set_position() because axes are
        # locatable, so we use subplots_adjust
        should_show = not self.mne.scrollbars_visible
        margins = {side: getattr(self.subplotpars, side)
                   for side in ('left', 'bottom', 'right', 'top')}
        # if should_show, bottom margin moves up; right margin moves left
        margins['bottom'] += (1 if should_show else -1) * self.mne.zen_h
        margins['right'] += (-1 if should_show else 1) * self.mne.zen_w
        self.subplots_adjust(**margins)
        # handle x-axis label
        self.mne.zen_xlabel.set_visible(not should_show)
        # show/hide other UI elements
        for elem in ('ax_hscroll', 'ax_vscroll', 'ax_proj', 'ax_help'):
            if elem == 'ax_vscroll' and self.mne.butterfly:
                continue
            # sometimes we don't have a proj button (ax_proj)
            if getattr(self.mne, elem, None) is not None:
                getattr(self.mne, elem).set_visible(should_show)
        self.mne.scrollbars_visible = should_show

    def _update_vscroll(self):
        """Update the vertical scrollbar (channel) selection indicator."""
        self.mne.vsel_patch.set_xy((0, self.mne.ch_start))
        self.mne.vsel_patch.set_height(self.mne.n_channels)
        self._update_yaxis_labels()

    def _update_hscroll(self):
        """Update the horizontal scrollbar (time) selection indicator."""
        self.mne.hsel_patch.set_xy((self.mne.t_start, 0))
        self.mne.hsel_patch.set_width(self.mne.duration)

    def _check_update_hscroll_clicked(self, event):
        """Handle clicks on horizontal scrollbar."""
        time = event.xdata - self.mne.duration / 2
        max_time = (self.mne.n_times / self.mne.info['sfreq'] +
                    self.mne.first_time - self.mne.duration)
        time = np.clip(time, self.mne.first_time, max_time)
        if self.mne.is_epochs:
            ix = np.searchsorted(self.mne.boundary_times[1:], time)
            time = self.mne.boundary_times[ix]
        if self.mne.t_start != time:
            self.mne.t_start = time
            self._update_hscroll()
            return True
        return False

    def _check_update_vscroll_clicked(self, event):
        """Update vscroll patch on click, return True if location changed."""
        new_ch_start = np.clip(
            int(round(event.ydata - self.mne.n_channels / 2)),
            0, len(self.mne.ch_order) - self.mne.n_channels)
        if self.mne.ch_start != new_ch_start:
            self.mne.ch_start = new_ch_start
            self._update_picks()
            self._update_vscroll()
            return True
        return False

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # SCALEBARS & AXIS LABELS
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _show_scalebars(self):
        """Add channel scale bars."""
        for offset, pick in zip(self.mne.trace_offsets, self.mne.picks):
            this_name = self.mne.ch_names[pick]
            this_type = self.mne.ch_types[pick]
            if (this_type not in self.mne.scalebars and
                    this_type != 'stim' and
                    this_type in self.mne.scalings and
                    this_type in getattr(self.mne, 'units', {}) and
                    this_type in getattr(self.mne, 'unit_scalings', {}) and
                    this_name not in self.mne.info['bads'] and
                    this_name not in self.mne.whitened_ch_names):
                x = (self.mne.times[0] + self.mne.first_time,) * 2
                denom = 4 if self.mne.butterfly else 2
                y = tuple(np.array([-1, 1]) / denom + offset)
                self._draw_one_scalebar(x, y, this_type)
                if self.mne.is_epochs:
                    x = (self.mne.times[0], self.mne.times[0] +
                         self.mne.boundary_times[1] / 2)
                    y_value = self.mne.n_channels - 0.5
                    y = (y_value, y_value)
                    self._draw_one_scalebar(x, y, 'time')

    def _hide_scalebars(self):
        """Remove channel scale bars."""
        for bar in self.mne.scalebars.values():
            bar.remove()
        for text in self.mne.scalebar_texts.values():
            text.remove()
        self.mne.scalebars = dict()
        self.mne.scalebar_texts = dict()

    def _toggle_scalebars(self, event):
        """Show/hide the scalebars."""
        if self.mne.scalebars_visible:
            self._hide_scalebars()
        else:
            self._update_picks()
            self._show_scalebars()
        # toggle
        self.mne.scalebars_visible = not self.mne.scalebars_visible
        self._redraw(update_data=False)

    def _draw_one_scalebar(self, x, y, ch_type):
        """Draw a scalebar."""
        from .utils import _simplify_float
        color = '#AA3377'  # purple
        kwargs = dict(color=color, zorder=self.mne.zorder['scalebar'])
        if ch_type == 'time':
            label = f'{self.mne.boundary_times[1]/2:.2f} sec'
            text = self.mne.ax_main.text(x[0] + .015, y[1] - .05, label,
                                         va='bottom', ha='left',
                                         size='xx-small', **kwargs)
        else:
            scaler = 1 if self.mne.butterfly else 2
            inv_norm = (scaler *
                        self.mne.scalings[ch_type] *
                        self.mne.unit_scalings[ch_type] /
                        self.mne.scale_factor)
            label = f'{_simplify_float(inv_norm)} {self.mne.units[ch_type]} '
            text = self.mne.ax_main.text(x[1], y[1], label, va='baseline',
                                         ha='right', size='xx-small', **kwargs)
        bar = self.mne.ax_main.plot(x, y, lw=4, **kwargs)[0]
        self.mne.scalebars[ch_type] = bar
        self.mne.scalebar_texts[ch_type] = text

    def _update_yaxis_labels(self):
        """Change the y-axis labels."""
        if self.mne.butterfly and self.mne.fig_selection is not None:
            exclude = ('Vertex', 'Custom')
            ticklabels = list(self.mne.ch_selections)
            keep_mask = np.in1d(ticklabels, exclude, invert=True)
            ticklabels = [t.replace('Left-', 'L-').replace('Right-', 'R-')
                          for t in ticklabels]  # avoid having to rotate labels
            ticklabels = np.array(ticklabels)[keep_mask]
        elif self.mne.butterfly:
            _, ixs, _ = np.intersect1d(_DATA_CH_TYPES_ORDER_DEFAULT,
                                       self.mne.ch_types, return_indices=True)
            ixs.sort()
            ticklabels = np.array(_DATA_CH_TYPES_ORDER_DEFAULT)[ixs]
        else:
            ticklabels = self.mne.ch_names[self.mne.picks]
        texts = self.mne.ax_main.set_yticklabels(ticklabels, picker=True)
        for text in texts:
            sty = ('italic' if text.get_text() in self.mne.whitened_ch_names
                   else 'normal')
            text.set_style(sty)

    def _xtick_formatter(self, x, pos=None, ax_type='main'):
        """Change the x-axis labels."""
        tickdiff = np.diff(self.mne.ax_main.get_xticks())[0]
        digits = np.ceil(-np.log10(tickdiff) + 1).astype(int)
        # always show millisecond precision for vline text
        if ax_type == 'vline':
            digits = 3
        if self.mne.time_format == 'float':
            # round to integers when possible ('9.0' → '9')
            if int(x) == x:
                digits = None
            if ax_type == 'vline':
                return f'{round(x, digits)} s'
            return str(round(x, digits))
        # format as timestamp
        meas_date = self.mne.inst.info['meas_date']
        first_time = datetime.timedelta(seconds=self.mne.inst.first_time)
        xtime = datetime.timedelta(seconds=x)
        xdatetime = meas_date + first_time + xtime
        xdtstr = xdatetime.strftime('%H:%M:%S')
        if digits and ax_type != 'hscroll' and int(xdatetime.microsecond):
            xdtstr += f'{round(xdatetime.microsecond * 1e-6, digits)}'[1:]
        return xdtstr

    def _toggle_time_format(self):
        if self.mne.time_format == 'float':
            self.mne.time_format = 'clock'
            x_axis_label = 'Time (HH:MM:SS)'
        else:
            self.mne.time_format = 'float'
            x_axis_label = 'Time (s)'

        # Change x-axis label
        for _ax in (self.mne.ax_main, self.mne.ax_hscroll):
            _ax.set_xlabel(x_axis_label)

        self._redraw(update_data=False, annotations=False)

        # Update vline-text if displayed
        if self.mne.vline is not None and self.mne.vline.get_visible():
            self._show_vline(self.mne.vline.get_xdata())

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # DATA TRACES
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _toggle_butterfly(self):
        """Enter or leave butterfly mode."""
        self.mne.ax_vscroll.set_visible(self.mne.butterfly)
        self.mne.butterfly = not self.mne.butterfly
        self.mne.scale_factor *= 0.5 if self.mne.butterfly else 2.
        self._update_picks()
        self._update_trace_offsets()
        self._redraw(annotations=True)
        if self.mne.fig_selection is not None:
            self.mne.fig_selection._style_radio_buttons_butterfly()

    def _update_trace_offsets(self):
        """Compute viewport height and adjust offsets."""
        # simultaneous selection and butterfly modes
        if self.mne.butterfly and self.mne.ch_selections is not None:
            self._update_picks()
            selections_dict = self._make_butterfly_selections_dict()
            n_offsets = len(selections_dict)
            sel_order = list(selections_dict)
            offsets = np.array([])
            for pick in self.mne.picks:
                for sel in sel_order:
                    if pick in selections_dict[sel]:
                        offsets = np.append(offsets, sel_order.index(sel))
        # butterfly only
        elif self.mne.butterfly:
            unique_ch_types = set(self.mne.ch_types)
            n_offsets = len(unique_ch_types)
            ch_type_order = [_type for _type in _DATA_CH_TYPES_ORDER_DEFAULT
                             if _type in unique_ch_types]
            offsets = np.array([ch_type_order.index(ch_type)
                                for ch_type in self.mne.ch_types])
        # normal mode
        else:
            n_offsets = self.mne.n_channels
            offsets = np.arange(n_offsets, dtype=float)
        # update ylim, ticks, vertline, and scrollbar patch
        ylim = (n_offsets - 0.5, -0.5)  # inverted y axis → new chs at bottom
        self.mne.ax_main.set_ylim(ylim)
        self.mne.ax_main.set_yticks(np.unique(offsets))
        self.mne.vsel_patch.set_height(self.mne.n_channels)
        # store new offsets, update axis labels
        self.mne.trace_offsets = offsets
        self._update_yaxis_labels()

    def _draw_traces(self):
        """Draw (or redraw) the channel data."""
        from matplotlib.colors import to_rgba_array
        from matplotlib.patches import Rectangle

        # clear scalebars
        if self.mne.scalebars_visible:
            self._hide_scalebars()
        # get info about currently visible channels
        picks = self.mne.picks
        ch_names = self.mne.ch_names[picks]
        ch_types = self.mne.ch_types[picks]
        offset_ixs = (picks
                      if self.mne.butterfly and self.mne.ch_selections is None
                      else slice(None))
        offsets = self.mne.trace_offsets[offset_ixs]
        bad_bool = np.in1d(ch_names, self.mne.info['bads'])
        # colors
        good_ch_colors = [self.mne.ch_color_dict[_type] for _type in ch_types]
        ch_colors = to_rgba_array(
            [self.mne.ch_color_bad if _bad else _color
             for _bad, _color in zip(bad_bool, good_ch_colors)])
        self.mne.ch_colors = np.array(good_ch_colors)  # use for unmarking bads
        labels = self.mne.ax_main.yaxis.get_ticklabels()
        if self.mne.butterfly:
            for label in labels:
                label.set_color(self.mne.fgcolor)
        else:
            for label, color in zip(labels, ch_colors):
                label.set_color(color)
        # decim
        decim = np.ones_like(picks)
        data_picks_mask = np.in1d(picks, self.mne.picks_data)
        decim[data_picks_mask] = self.mne.decim
        # decim can vary by channel type, so compute different `times` vectors
        decim_times = {decim_value:
                       self.mne.times[::decim_value] + self.mne.first_time
                       for decim_value in set(decim)}
        # add more traces if needed
        n_picks = len(picks)
        if n_picks > len(self.mne.traces):
            n_new_chs = n_picks - len(self.mne.traces)
            new_traces = self.mne.ax_main.plot(np.full((1, n_new_chs), np.nan),
                                               **self.mne.trace_kwargs)
            self.mne.traces.extend(new_traces)
        # remove extra traces if needed
        extra_traces = self.mne.traces[n_picks:]
        for trace in extra_traces:
            trace.remove()
        self.mne.traces = self.mne.traces[:n_picks]

        # check for bad epochs
        time_range = (self.mne.times + self.mne.first_time)[[0, -1]]
        if self.mne.instance_type == 'epochs':
            epoch_ix = np.searchsorted(self.mne.boundary_times, time_range)
            epoch_ix = np.arange(epoch_ix[0], epoch_ix[1])
            epoch_nums = self.mne.inst.selection[epoch_ix[0]:epoch_ix[-1] + 1]
            visible_bad_epoch_ix, = np.in1d(
                epoch_nums, self.mne.bad_epochs).nonzero()
            while len(self.mne.epoch_traces):
                self.mne.epoch_traces.pop(-1).remove()
            # handle custom epoch colors (for autoreject integration)
            if self.mne.epoch_colors is None:
                # shape: n_traces × RGBA → n_traces × n_epochs × RGBA
                custom_colors = np.tile(ch_colors[:, None, :],
                                        (1, self.mne.n_epochs, 1))
            else:
                custom_colors = np.empty((len(self.mne.picks),
                                          self.mne.n_epochs, 4))
                for ii, _epoch_ix in enumerate(epoch_ix):
                    this_colors = self.mne.epoch_colors[_epoch_ix]
                    custom_colors[:, ii] = to_rgba_array([this_colors[_ch]
                                                          for _ch in picks])
            # override custom color on bad epochs
            for _ix in visible_bad_epoch_ix:
                _cols = np.array([self.mne.epoch_color_bad,
                                  self.mne.ch_color_bad],
                                 dtype=object)[bad_bool.astype(int)]
                custom_colors[:, _ix] = to_rgba_array(_cols)

        # update traces
        ylim = self.mne.ax_main.get_ylim()
        for ii, line in enumerate(self.mne.traces):
            this_name = ch_names[ii]
            this_type = ch_types[ii]
            this_offset = offsets[ii]
            this_times = decim_times[decim[ii]]
            this_data = this_offset - self.mne.data[ii] * self.mne.scale_factor
            this_data = this_data[..., ::decim[ii]]
            # clip
            if self.mne.clipping == 'clamp':
                this_data = np.clip(this_data, -0.5, 0.5)
            elif self.mne.clipping is not None:
                clip = self.mne.clipping * (0.2 if self.mne.butterfly else 1)
                bottom = max(this_offset - clip, ylim[1])
                height = min(2 * clip, ylim[0] - bottom)
                rect = Rectangle(xy=np.array([time_range[0], bottom]),
                                 width=time_range[1] - time_range[0],
                                 height=height,
                                 transform=self.mne.ax_main.transData)
                line.set_clip_path(rect)
            # prep z order
            is_bad_ch = this_name in self.mne.info['bads']
            this_z = self.mne.zorder['bads' if is_bad_ch else 'data']
            if self.mne.butterfly and not is_bad_ch:
                this_z = self.mne.zorder.get(this_type, this_z)
            # plot each trace multiple times to get the desired epoch coloring.
            # use masked arrays to plot discontinuous epochs that have the same
            # color in a single plot() call.
            if self.mne.instance_type == 'epochs':
                this_colors = custom_colors[ii]
                for cix, color in enumerate(np.unique(this_colors, axis=0)):
                    bool_ixs = (this_colors == color).all(axis=1)
                    mask = np.zeros_like(this_times, dtype=bool)
                    _starts = self.mne.boundary_times[epoch_ix][bool_ixs]
                    _stops = self.mne.boundary_times[epoch_ix + 1][bool_ixs]
                    for _start, _stop in zip(_starts, _stops):
                        _mask = np.logical_and(_start < this_times,
                                               this_times <= _stop)
                        mask = mask | _mask
                    _times = np.ma.masked_array(this_times, mask=~mask)
                    # always use the existing traces first
                    if cix == 0:
                        line.set_xdata(_times)
                        line.set_ydata(this_data)
                        line.set_color(color)
                        line.set_zorder(this_z)
                    else:  # make new traces as needed
                        _trace = self.mne.ax_main.plot(
                            _times, this_data, color=color, zorder=this_z,
                            **self.mne.trace_kwargs)
                        self.mne.epoch_traces.extend(_trace)
            else:
                line.set_xdata(this_times)
                line.set_ydata(this_data)
                line.set_color(ch_colors[ii])
                line.set_zorder(this_z)
        # update xlim
        self.mne.ax_main.set_xlim(*time_range)
        # draw scalebars maybe
        if self.mne.scalebars_visible:
            self._show_scalebars()
        # redraw event lines
        if self.mne.event_times is not None:
            self._draw_event_lines()

    def _redraw(self, update_data=True, annotations=False):
        """Redraw (convenience method for frequently grouped actions)."""
        super()._redraw(update_data, annotations)
        if self.mne.vline_visible and self.mne.is_epochs:
            # prevent flickering
            _ = self._recompute_epochs_vlines(None)
        self.canvas.draw_idle()

    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
    # EVENT LINES AND MARKER LINES
    # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

    def _draw_event_lines(self):
        """Draw the event lines and their labels."""
        from matplotlib.collections import LineCollection
        from matplotlib.colors import to_rgba_array
        if self.mne.event_nums is not None:
            mask = np.logical_and(self.mne.event_times >= self.mne.times[0],
                                  self.mne.event_times <= self.mne.times[-1])
            this_event_times = self.mne.event_times[mask]
            this_event_nums = self.mne.event_nums[mask]
            n_visible_events = len(this_event_times)
            colors = to_rgba_array([self.mne.event_color_dict[n]
                                    for n in this_event_nums])
            # create event lines
            ylim = self.mne.ax_main.get_ylim()
            xs = np.repeat(this_event_times, 2)
            ys = np.tile(ylim, n_visible_events)
            segs = np.vstack([xs, ys]).T.reshape(n_visible_events, 2, 2)
            event_lines = LineCollection(segs, linewidths=0.5, colors=colors,
                                         zorder=self.mne.zorder['events'])
            self.mne.ax_main.add_collection(event_lines)
            self.mne.event_lines = event_lines
            # create event labels
            while len(self.mne.event_texts):
                self.mne.event_texts.pop().remove()
            for _t, _n, _c in zip(this_event_times, this_event_nums, colors):
                label = self.mne.event_id_rev.get(_n, _n)
                this_text = self.mne.ax_main.annotate(
                    label, (_t, ylim[1]), ha='center', va='baseline',
                    color=self.mne.fgcolor, xytext=(0, 2),
                    textcoords='offset points', fontsize=8)
                self.mne.event_texts.append(this_text)

    def _recompute_epochs_vlines(self, xdata):
        """Recompute vline x-coords for epochs plots (after scrolling, etc)."""
        # special case: changed view duration w/ "home" or "end" key
        # (no click event, hence no xdata)
        if xdata is None:
            xdata = np.array(self.mne.vline.get_segments())[0, 0, 0]
        # compute the (continuous) times for the lines on each epoch
        epoch_dur = np.diff(self.mne.boundary_times[:2])[0]
        rel_time = xdata % epoch_dur
        abs_time = self.mne.times[0]
        xs = np.arange(self.mne.n_epochs) * epoch_dur + abs_time + rel_time
        segs = np.array(self.mne.vline.get_segments())
        # recreate segs from scratch in case view duration changed
        # (i.e., handle case when n_segments != n_epochs)
        segs = np.tile([[0.], [1.]], (len(xs), 1, 2))  # y values
        segs[..., 0] = np.tile(xs[:, None], 2)         # x values
        self.mne.vline.set_segments(segs)
        return rel_time

    def _show_vline(self, xdata):
        """Show the vertical line(s)."""
        if self.mne.is_epochs:
            # convert xdata to be epoch-relative (for the text)
            rel_time = self._recompute_epochs_vlines(xdata)
            xdata = rel_time + self.mne.inst.times[0]
        else:
            self.mne.vline.set_xdata(xdata)
            self.mne.vline_hscroll.set_xdata(xdata)
        text = self._xtick_formatter(xdata, ax_type='vline')[:12]
        self.mne.vline_text.set_text(text)
        self._toggle_vline(True)

    def _toggle_vline(self, visible):
        """Show or hide the vertical line(s)."""
        for artist in (self.mne.vline, self.mne.vline_hscroll,
                       self.mne.vline_text):
            if artist is not None:
                artist.set_visible(visible)
                self.draw_artist(artist)
        self.mne.vline_visible = visible
        self.canvas.draw_idle()

    # workaround: plt.close() doesn't spawn close_event on Agg backend
    # (check MPL github issue #18609; scheduled to be fixed by MPL 3.6)
    def _close_event(self, fig=None):
        """Force calling of the MPL figure close event."""
        fig = fig or self
        _close_event(fig)

    def _fake_keypress(self, key, fig=None):
        fig = fig or self
        _fake_keypress(fig, key)

    def _fake_click(self, point, add_points=None, fig=None, ax=None,
                    xform='ax', button=1, kind='press'):
        """Fake a click at a relative point within axes."""
        fig = fig or self
        ax = ax or self.mne.ax_main
        if kind == 'drag' and add_points is not None:
            _fake_click(fig=fig, ax=ax, point=point, xform=xform,
                        button=button, kind='press')
            for apoint in add_points:
                _fake_click(fig=fig, ax=ax, point=apoint, xform=xform,
                            button=button, kind='motion')
            _fake_click(fig=fig, ax=ax, point=add_points[-1], xform=xform,
                        button=button, kind='release')
        else:
            _fake_click(fig=fig, ax=ax, point=point, xform=xform,
                        button=button, kind=kind)

    def _fake_scroll(self, x, y, step, fig=None):
        fig = fig or self
        _fake_scroll(fig, x, y, step)

    def _click_ch_name(self, ch_index, button):
        _click_ch_name(self, ch_index, button)

    def _resize_by_factor(self, factor=None):
        size = self.canvas.manager.canvas.get_width_height()
        if isinstance(factor, tuple):
            size = int(size[0] * factor[0],
                       size[1] * factor[1])
        else:
            size = [int(x * factor) for x in size]
        self.canvas.manager.resize(*size)

    def _get_ticklabels(self, orientation):
        if orientation == 'x':
            labels = self.mne.ax_main.get_xticklabels(minor=self.mne.is_epochs)
        elif orientation == 'y':
            labels = self.mne.ax_main.get_yticklabels()
        label_texts = [lb.get_text() for lb in labels]

        return label_texts

    def _get_scale_bar_texts(self):
        texts = tuple(t.get_text().strip() for t in self.mne.ax_main.texts)
        # First text is empty because of vline
        texts = texts[1:]

        return texts


class MNELineFigure(MNEFigure):
    """Interactive figure for non-scrolling line plots."""

    def __init__(self, inst, n_axes, figsize, **kwargs):
        super().__init__(figsize=figsize, inst=inst, **kwargs)

        # AXES: default margins (inches)
        l_margin = 0.8
        r_margin = 0.2
        b_margin = 0.65
        t_margin = 0.35
        # AXES: default margins (figure-relative coordinates)
        left = self._inch_to_rel(l_margin)
        right = 1 - self._inch_to_rel(r_margin)
        bottom = self._inch_to_rel(b_margin, horiz=False)
        top = 1 - self._inch_to_rel(t_margin, horiz=False)
        # AXES: make subplots
        axes = [self.add_subplot(n_axes, 1, 1)]
        for ix in range(1, n_axes):
            axes.append(self.add_subplot(n_axes, 1, ix + 1, sharex=axes[0]))
        self.subplotpars.update(left=left, bottom=bottom, top=top, right=right,
                                hspace=0.4)
        # save useful things
        self.mne.ax_list = axes

    def _resize(self, event):
        """Handle resize event."""
        old_width, old_height = self.mne.fig_size_px
        new_width, new_height = self._get_size_px()
        new_margins = _calc_new_margins(
            self, old_width, old_height, new_width, new_height)
        self.subplots_adjust(**new_margins)
        self.mne.fig_size_px = (new_width, new_height)


def _close_all():
    """Close all figures (only used in our tests)."""
    plt.close('all')


def _get_n_figs():
    return len(plt.get_fignums())


def _figure(toolbar=True, FigureClass=MNEFigure, **kwargs):
    """Instantiate a new figure."""
    from matplotlib import rc_context
    title = kwargs.pop('window_title', None)  # extract title before init
    rc = dict() if toolbar else dict(toolbar='none')
    with rc_context(rc=rc):
        fig = plt.figure(FigureClass=FigureClass, **kwargs)
    # BACKEND defined globally at the top of this file
    fig.mne.backend = BACKEND
    if title is not None:
        _set_window_title(fig, title)
    # add event callbacks
    fig._add_default_callbacks()
    return fig


def _line_figure(inst, axes=None, picks=None, **kwargs):
    """Instantiate a new line figure."""
    from matplotlib.axes import Axes

    # if picks is None, only show data channels
    allowed_ch_types = (_DATA_CH_TYPES_SPLIT if picks is None else
                        _VALID_CHANNEL_TYPES)
    # figure out expected number of axes
    ch_types = np.array(inst.get_channel_types())
    if picks is not None:
        ch_types = ch_types[picks]
    n_axes = len(np.intersect1d(ch_types, allowed_ch_types))
    # handle user-provided axes
    if axes is not None:
        if isinstance(axes, Axes):
            axes = [axes]
        _validate_if_list_of_axes(axes, n_axes)
        fig = axes[0].get_figure()
    else:
        figsize = kwargs.pop('figsize', (10, 2.5 * n_axes + 1))
        fig = _figure(inst=inst, toolbar=True, FigureClass=MNELineFigure,
                      figsize=figsize, n_axes=n_axes, **kwargs)
        fig.mne.fig_size_px = fig._get_size_px()  # can't do in __init__
        axes = fig.mne.ax_list
    return fig, axes


def _psd_figure(inst, proj, picks, axes, area_mode, tmin, tmax, fmin, fmax,
                n_jobs, color, area_alpha, dB, estimate, average,
                spatial_colors, xscale, line_alpha, sphere, window, exclude,
                **kwargs):
    """Instantiate a new power spectral density figure."""
    from .. import BaseEpochs
    from ..io import BaseRaw

    # triage kwargs for different PSD methods (raw→welch, epochs→multitaper)
    welch_kwargs = ('n_fft', 'n_overlap', 'reject_by_annotation')
    multitaper_kwargs = ('bandwidth', 'adaptive', 'low_bias', 'normalization')
    psd_kwargs = dict()
    for kw in welch_kwargs + multitaper_kwargs:
        if kw in kwargs:
            psd_kwargs[kw] = kwargs.pop(kw)
    if isinstance(inst, BaseRaw):
        psd_func = partial(psd_welch, window=window)
    elif isinstance(inst, BaseEpochs):
        psd_func = psd_multitaper
    else:
        raise TypeError('Expected an instance of Raw or Epochs, got '
                        f'{type(inst)}.')
    # arg checking
    if np.isfinite(fmax) and (fmax > inst.info['sfreq'] / 2):
        raise ValueError(
            f'Requested fmax ({fmax} Hz) must not exceed ½ the sampling '
            f'frequency of the data ({0.5 * inst.info["sfreq"]}).')
    _check_option('area_mode', area_mode, [None, 'std', 'range'])
    _check_option('xscale', xscale, ('log', 'linear'))
    sphere = _check_sphere(sphere, inst.info)
    picks = _picks_to_idx(inst.info, picks, exclude=exclude)
    titles = _handle_default('titles', None)
    units = _handle_default('units', None)
    scalings = _handle_default('scalings', None)
    # containers
    picks_list = list()
    units_list = list()
    titles_list = list()
    scalings_list = list()
    psd_list = list()
    # initialize figure
    fig, axes = _line_figure(inst, axes, picks, **kwargs)
    # split picks, units, etc, for each subplot
    (picks_list, units_list, scalings_list, titles_list
     ) = _split_picks_by_type(inst, picks, units, scalings, titles)
    del picks
    # don't add ylabels & titles if figure has unexpected number of axes
    make_label = len(axes) == len(fig.axes)
    # Plot Frequency [Hz] xlabel only on the last axis
    xlabels_list = [False] * (len(axes) - 1) + [True]
    # compute PSDs
    for picks in picks_list:
        psd, freqs = psd_func(inst, tmin=tmin, tmax=tmax, picks=picks,
                              fmin=fmin, fmax=fmax, proj=proj, n_jobs=n_jobs,
                              **psd_kwargs)
        if isinstance(inst, BaseEpochs):
            psd = np.mean(psd, axis=0)
        psd_list.append(psd)
    # plot
    _plot_psd(inst, fig, freqs, psd_list, picks_list, titles_list, units_list,
              scalings_list, axes, make_label, color, area_mode, area_alpha,
              dB, estimate, average, spatial_colors, xscale, line_alpha,
              sphere, xlabels_list)
    fig.subplots_adjust(hspace=0.3)
    return fig


def _split_picks_by_type(inst, picks, units, scalings, titles):
    """Separate picks, units, etc, for plotting on separate subplots."""
    picks_list = list()
    units_list = list()
    scalings_list = list()
    titles_list = list()
    # if picks is None, only show data channels
    allowed_ch_types = (_DATA_CH_TYPES_SPLIT if picks is None else
                        _VALID_CHANNEL_TYPES)
    for ch_type in allowed_ch_types:
        pick_kwargs = dict(meg=False, ref_meg=False, exclude=[])
        if ch_type in ('mag', 'grad'):
            pick_kwargs['meg'] = ch_type
        elif ch_type in _FNIRS_CH_TYPES_SPLIT:
            pick_kwargs['fnirs'] = ch_type
        else:
            pick_kwargs[ch_type] = True
        these_picks = pick_types(inst.info, **pick_kwargs)
        these_picks = np.intersect1d(these_picks, picks)
        if len(these_picks) > 0:
            picks_list.append(these_picks)
            units_list.append(units[ch_type])
            scalings_list.append(scalings[ch_type])
            titles_list.append(titles[ch_type])
    if len(picks_list) == 0:
        raise RuntimeError('No data channels found')
    return picks_list, units_list, scalings_list, titles_list


def _calc_new_margins(fig, old_width, old_height, new_width, new_height):
    """Compute new figure-relative values to maintain fixed-size margins."""
    new_margins = dict()
    for side in ('left', 'right', 'bottom', 'top'):
        ratio = ((old_width / new_width) if side in ('left', 'right') else
                 (old_height / new_height))
        rel_dim = getattr(fig.subplotpars, side)
        if side in ('right', 'top'):
            new_margins[side] = 1 - ratio * (1 - rel_dim)
        else:
            new_margins[side] = ratio * rel_dim
    # gh-8304: don't allow resizing too small
    if (new_margins['bottom'] < new_margins['top'] and
            new_margins['left'] < new_margins['right']):
        return new_margins


@contextmanager
def _patched_canvas(fig):
    old_canvas = fig.canvas
    if fig.canvas is None:  # XXX old MPL (at least 3.0.3) does this for Agg
        fig.canvas = Bunch(mpl_connect=lambda event, callback: None)
    try:
        yield
    finally:
        fig.canvas = old_canvas


def _init_browser(**kwargs):
    """Instantiate a new MNE browse-style figure."""
    from mne.io import BaseRaw
    fig = _figure(toolbar=False, FigureClass=MNEBrowseFigure, **kwargs)

    # splash is ignored (maybe we could do it for mpl if we get_backend() and
    # check if it's Qt... but seems overkill)

    # initialize zen mode
    # (can't do in __init__ due to get_position() calls)
    fig.canvas.draw()
    fig._update_zen_mode_offsets()
    fig._resize(None)  # needed for MPL >=3.4

    # if scrollbars are supposed to start hidden,
    # set to True and then toggle
    if not fig.mne.scrollbars_visible:
        fig.mne.scrollbars_visible = True
        fig._toggle_scrollbars()

    # Initialize parts of the plot
    is_ica = fig.mne.instance_type == 'ica'

    if not is_ica:
        # make channel selection dialog,
        # if requested (doesn't work well in init)
        if fig.mne.group_by in ('selection', 'position'):
            fig._create_selection_fig()

    # start with projectors dialog open, if requested
    if getattr(fig.mne, 'show_options', False):
        fig._toggle_proj_fig()

    # update data, and plot
    fig._update_trace_offsets()
    fig._redraw(update_data=True, annotations=False)

    if isinstance(fig.mne.inst, BaseRaw):
        fig._setup_annotation_colors()
        fig._draw_annotations()

    return fig
