#!/usr/bin/env python3
"""
The standard Cartesian axes used for most ProPlot figures.
"""
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
import numpy as np
from .. import constructor
from .. import scale as pscale
from .. import ticker as pticker
from ..config import _parse_format, rc
from ..internals import ic # noqa: F401
from ..internals import _not_none, docstring, rcsetup, text, warnings
from . import plot, shared
__all__ = ['CartesianAxes']
_alt_kwargs = ( # TODO: More systematic approach?
'lim', 'min', 'max', 'reverse', 'scale', 'label',
'tickdir', 'grid', 'gridminor',
'tickminor', 'ticklabeldir', 'tickrange', 'wraprange',
'rotation', 'formatter', 'ticklabels',
'ticks', 'locator', 'minorticks', 'minorlocator',
'bounds', 'margin', 'color', 'linewidth', 'ticklen', 'gridcolor',
'label_kw', 'scale_kw', 'locator_kw', 'formatter_kw', 'minorlocator_kw',
)
# Shared docstring
_shared_docstring = """
%(descrip)s
Parameters
----------
%(extra)s{xargs} : optional
Passed to `Axes.format`.
{args} : optional
Prepended with ``'{x}'`` and passed to `Axes.format`.
Returns
-------
CartesianAxes
The new axes.
Note
----
This enforces the following default settings:
* Places the old {x} axis on the {x1} and the new {x}
axis on the {x2}.
* Makes the old {x2} spine invisible and the new {x1}, {y1},
and {y2} spines invisible.
* Adjusts the {x} axis tick, tick label, and axis label positions
according to the visible spine positions.
* Syncs the old and new {y} axis limits and scales, and makes the
new {y} axis labels invisible.
"""
_shared_x_keys = dict(
x='x', x1='bottom', x2='top',
y='y', y1='left', y2='right',
args=', '.join(_alt_kwargs),
xargs=', '.join('x' + key for key in _alt_kwargs),
)
_shared_y_keys = dict(
x='y', x1='left', x2='right',
y='x', y1='bottom', y2='top',
args=', '.join(_alt_kwargs),
xargs=', '.join('y' + key for key in _alt_kwargs),
)
# Alt docstrings
# NOTE: Used by SubplotGrid.altx
_alt_descrip = """
Add an axes locked to the same location with a
distinct {x} axis.
This is an alias and possibly more intuitive name for
`~CartesianAxes.twin{y}`, which generates two {x} axes
with a shared ("twin") {y} axes.
"""
_alt_docstring = _shared_docstring % {'descrip': _alt_descrip, 'extra': ''}
docstring._snippet_manager['axes.altx'] = _alt_docstring.format(**_shared_x_keys)
docstring._snippet_manager['axes.alty'] = _alt_docstring.format(**_shared_y_keys)
# Twin docstrings
# NOTE: Used by SubplotGrid.twinx
_twin_descrip = """
Add an axes locked to the same location with a
distinct {x} axis.
This builds upon `matplotlib.axes.Axes.twin{y}`.
"""
_twin_docstring = _shared_docstring % {'descrip': _twin_descrip, 'extra': ''}
docstring._snippet_manager['axes.twinx'] = _twin_docstring.format(**_shared_y_keys)
docstring._snippet_manager['axes.twiny'] = _twin_docstring.format(**_shared_x_keys)
# Dual docstrings
# NOTE: Used by SubplotGrid.dualx
_dual_descrip = """
Add an axes locked to the same location whose {x} axis denotes
equivalent coordinates in alternate units.
This is an alternative to `matplotlib.axes.Axes.secondary_{x}axis` with
additional convenience features.
"""
_dual_extra = """
funcscale : callable, 2-tuple of callables, or scale-spec
The scale used to transform units from the parent axis to the secondary
axis. This can be a `~proplot.scale.FuncScale` itself or a function,
(function, function) tuple, or an axis scale specification
interpreted by the `~proplot.constructor.Scale` constructor function,
any of which will be used to build a `~proplot.scale.FuncScale` and
applied to the dual axis (see `~proplot.scale.FuncScale` for details).
"""
_dual_docstring = _shared_docstring % {'descrip': _dual_descrip, 'extra': _dual_extra.lstrip()} # noqa: E501
docstring._snippet_manager['axes.dualx'] = _dual_docstring.format(**_shared_x_keys)
docstring._snippet_manager['axes.dualy'] = _dual_docstring.format(**_shared_y_keys)
[docs]class CartesianAxes(shared._SharedAxes, plot.PlotAxes):
"""
Axes subclass for plotting in ordinary Cartesian coordinates.
Adds the `~CartesianAxes.format` method and overrides several existing
methods.
"""
_name = 'cartesian'
_name_aliases = ('cart', 'rect', 'rectilinar') # include matplotlib name
def __init__(self, *args, **kwargs):
"""
See also
--------
proplot.ui.subplots
proplot.axes.Axes
proplot.axes.PlotAxes
"""
# Impose default formatter
self._xaxis_current_rotation = 'horizontal' # current rotation
self._yaxis_current_rotation = 'horizontal'
self._xaxis_isdefault_rotation = True # whether to auto rotate the axis
self._yaxis_isdefault_rotation = True
super().__init__(*args, **kwargs)
formatter = pticker.AutoFormatter()
self.xaxis.set_major_formatter(formatter)
self.yaxis.set_major_formatter(formatter)
self.xaxis.isDefault_majfmt = True
self.yaxis.isDefault_majfmt = True
self._dualx_funcscale = None # for scaling units on dual axes
self._dualx_prevstate = None # prevent excess _dualy_scale calls
self._dualy_funcscale = None
self._dualy_prevstate = None
def _apply_axis_sharing(self):
"""
Enforce the "shared" axis labels and axis tick labels. If this is not
called at drawtime, "shared" labels can be inadvertantly turned off.
"""
# X axis
# NOTE: Critical to apply labels to *shared* axes attributes rather
# than testing extents or we end up sharing labels with twin axes.
# NOTE: Similar to how _align_super_labels() calls _apply_title_above() this
# is called inside _align_axis_labels() so we align the correct text.
# NOTE: The "panel sharing group" refers to axes and panels *above* the
# bottommost or to the *right* of the leftmost panel. But the sharing level
# used for the leftmost and bottommost is the *figure* sharing level.
axis = self.xaxis
if self._sharex is not None:
level = 3 if self._panel_sharex_group else self.figure._sharex
if level > 0:
text._transfer_text(axis.label, self._sharex.xaxis.label)
axis.label.set_visible(False)
if level > 2:
# WARNING: Cannot set NullFormatter because shared axes share the
# same Ticker(). Instead use approach copied from mpl subplots().
axis.set_tick_params(which='both', labelbottom=False, labeltop=False)
# Y axis
axis = self.yaxis
if self._sharey is not None:
level = 3 if self._panel_sharey_group else self.figure._sharey
if level > 0:
text._transfer_text(axis.label, self._sharey.yaxis.label)
axis.label.set_visible(False)
if level > 2:
axis.set_tick_params(which='both', labelleft=False, labelright=False)
axis.set_minor_formatter(mticker.NullFormatter())
def _dualx_scale(self):
"""
Lock the child "dual" *x* axis limits to the parent.
"""
# NOTE: We bypass autoscale_view because we set limits manually, and bypass
# child.stale = True because that is done in call to set_xlim() below.
# NOTE: We set the scale using private API to bypass application of
# set_default_locators_and_formatters: only_if_default=True is critical
# to prevent overriding user settings!
# NOTE: Dual axis only needs to be constrained if the parent axis scale
# and limits have changed, and limits are always applied before we reach
# the child.draw() because always called after parent.draw()
funcscale, parent, child = self._dualx_funcscale, self._altx_parent, self
if funcscale is None or parent is None:
return
olim = parent.get_xlim()
scale = parent.xaxis._scale
if (scale, *olim) == child._dualx_prevstate:
return
funcscale = pscale.FuncScale(funcscale, invert=True, parent_scale=scale)
child.xaxis._scale = funcscale
child._update_transScale()
funcscale.set_default_locators_and_formatters(child.xaxis, only_if_default=True)
nlim = list(map(funcscale.functions[1], np.array(olim)))
if np.sign(np.diff(olim)) != np.sign(np.diff(nlim)):
nlim = nlim[::-1] # if function flips limits, so will set_xlim!
child.set_xlim(nlim, emit=False)
child._dualx_prevstate = (scale, *olim)
def _dualy_scale(self):
"""
Lock the child "dual" *y* axis limits to the parent.
"""
# See _dualx_scale() comments
funcscale, parent, child = self._dualy_funcscale, self._alty_parent, self
if funcscale is None or parent is None:
return
olim = parent.get_ylim()
scale = parent.yaxis._scale
if (scale, *olim) == child._dualy_prevstate:
return
funcscale = pscale.FuncScale(funcscale, invert=True, parent_scale=scale)
child.yaxis._scale = funcscale
child._update_transScale()
funcscale.set_default_locators_and_formatters(child.yaxis, only_if_default=True)
nlim = list(map(funcscale.functions[1], np.array(olim)))
if np.sign(np.diff(olim)) != np.sign(np.diff(nlim)):
nlim = nlim[::-1]
child.set_ylim(nlim, emit=False)
child._dualy_prevstate = (scale, *olim)
def _is_panel_group_member(self, other):
"""
Return whether the axes belong in a panel sharing stack..
"""
return (
self._panel_parent is other # other is child panel
or other._panel_parent is self # other is main subplot
or other._panel_parent and self._panel_parent # ...
and other._panel_parent is self._panel_parent # other is sibling panel
)
@staticmethod
def _parse_alt(x, kwargs):
"""
Interpret keyword args passed to all "twin axis" methods so they
can be passed to Axes.format.
"""
kw_bad, kw_out = {}, {}
for key, value in kwargs.items():
if key in _alt_kwargs:
kw_out[x + key] = value
elif key[0] == x and key[1:] in _alt_kwargs:
# NOTE: We permit both e.g. 'locator' and 'xlocator' because
# while is more elegant and consistent with e.g. colorbar() syntax
# but latter is more consistent and easier to use when refactoring.
kw_out[key] = value
elif key in rcsetup._rc_nodots:
kw_out[key] = value
else:
kw_bad[key] = value
if kw_bad:
raise TypeError(f'Unexpected keyword argument(s): {kw_bad!r}')
return kw_out
def _sharex_limits(self, sharex):
"""
Safely share limits and tickers without resetting things.
"""
# Copy non-default limits and scales. Either this axes or the input
# axes could be a newly-created subplot while the other is a subplot
# with possibly-modified user settings we are careful to preserve.
for (ax1, ax2) in ((self, sharex), (sharex, self)):
if ax1.get_xscale() == 'linear' and ax2.get_xscale() != 'linear':
ax1.set_xscale(ax2.get_xscale()) # non-default scale
if ax1.get_autoscalex_on() and not ax2.get_autoscalex_on():
ax1.set_xlim(ax2.get_xlim()) # non-default limits
# Copy non-default locators and formatters
self._shared_x_axes.join(self, sharex) # share limit/scale changes
if sharex.xaxis.isDefault_majloc and not self.xaxis.isDefault_majloc:
sharex.xaxis.set_major_locator(self.xaxis.get_major_locator())
if sharex.xaxis.isDefault_minloc and not self.xaxis.isDefault_minloc:
sharex.xaxis.set_minor_locator(self.xaxis.get_minor_locator())
if sharex.xaxis.isDefault_majfmt and not self.xaxis.isDefault_majfmt:
sharex.xaxis.set_major_formatter(self.xaxis.get_major_formatter())
if sharex.xaxis.isDefault_minfmt and not self.xaxis.isDefault_minfmt:
sharex.xaxis.set_minor_formatter(self.xaxis.get_minor_formatter())
self.xaxis.major = sharex.xaxis.major
self.xaxis.minor = sharex.xaxis.minor
def _sharey_limits(self, sharey):
"""
Safely share limits and tickers without resetting things.
"""
# NOTE: See _sharex_limits for notes
for (ax1, ax2) in ((self, sharey), (sharey, self)):
if ax1.get_yscale() == 'linear' and ax2.get_yscale() != 'linear':
ax1.set_yscale(ax2.get_yscale())
if ax1.get_autoscaley_on() and not ax2.get_autoscaley_on():
ax1.set_ylim(ax2.get_ylim())
self._shared_y_axes.join(self, sharey) # share limit/scale changes
if sharey.yaxis.isDefault_majloc and not self.yaxis.isDefault_majloc:
sharey.yaxis.set_major_locator(self.yaxis.get_major_locator())
if sharey.yaxis.isDefault_minloc and not self.yaxis.isDefault_minloc:
sharey.yaxis.set_minor_locator(self.yaxis.get_minor_locator())
if sharey.yaxis.isDefault_majfmt and not self.yaxis.isDefault_majfmt:
sharey.yaxis.set_major_formatter(self.yaxis.get_major_formatter())
if sharey.yaxis.isDefault_minfmt and not self.yaxis.isDefault_minfmt:
sharey.yaxis.set_minor_formatter(self.yaxis.get_minor_formatter())
self.yaxis.major = sharey.yaxis.major
self.yaxis.minor = sharey.yaxis.minor
def _sharex_setup(self, sharex, *, labels=True, limits=True):
"""
Configure shared axes accounting. Input is the 'parent' axes from which this
one will draw its properties. Use keyword args to override settings.
"""
# Share panels across *different* subplots
super()._sharex_setup(sharex)
# Get the axis sharing level
level = (
3 if self._panel_sharex_group and self._is_panel_group_member(sharex)
else self.figure._sharex
)
if level not in range(5): # must be internal error
raise ValueError(f'Invalid sharing level sharex={level!r}.')
if sharex in (None, self) or not isinstance(sharex, CartesianAxes):
return
# Share future axis label changes. Implemented in _apply_axis_sharing().
# Matplotlib only uses these attributes in __init__() and cla() to share
# tickers -- all other builtin sharing features derives from _shared_x_axes
if level > 0 and labels:
self._sharex = sharex
# Share future axis tickers, limits, and scales
# NOTE: Only difference between levels 2 and 3 is level 3 hides tick
# labels. But this is done after the fact -- tickers are still shared.
if level > 1 and limits:
self._sharex_limits(sharex)
def _sharey_setup(self, sharey, *, labels=True, limits=True):
"""
Configure shared axes accounting for panels. The input is the
'parent' axes, from which this one will draw its properties.
"""
# NOTE: See _sharex_setup for notes
super()._sharey_setup(sharey)
level = (
3 if self._panel_sharey_group and self._is_panel_group_member(sharey)
else self.figure._sharey
)
if level not in range(5): # must be internal error
raise ValueError(f'Invalid sharing level sharey={level!r}.')
if sharey in (None, self) or not isinstance(sharey, CartesianAxes):
return
if level > 0 and labels:
self._sharey = sharey
if level > 1 and limits:
self._sharey_limits(sharey)
def _update_bounds(self, x, fixticks=False):
"""
Ensure there are no out-of-bounds labels. Mostly a brute-force version of
`~matplotlib.axis.Axis.set_smart_bounds` (which I couldn't get to work).
"""
# NOTE: Previously triggered this every time FixedFormatter was found
# on axis but 1) that seems heavy-handed + strange and 2) internal
# application of FixedFormatter by boxplot resulted in subsequent format()
# successfully calling this and messing up the ticks for some reason.
# So avoid using this when possible, and try to make behavior consistent
# by cacheing the locators before we use them for ticks.
axis = getattr(self, x + 'axis')
sides = ('bottom', 'top') if x == 'x' else ('left', 'right')
bounds = tuple(self.spines[side].get_bounds() is not None for side in sides)
if fixticks or any(bounds) or axis.get_scale() == 'cutoff':
# Major locator
lim = bounds[0] or bounds[1] or getattr(self, 'get_' + x + 'lim')()
locator = getattr(axis, '_major_locator_cached', None)
if locator is None:
locator = axis._major_locator_cached = axis.get_major_locator()
locator = constructor.Locator([x for x in locator() if lim[0] <= x <= lim[1]]) # noqa: E501
axis.set_major_locator(locator)
# Minor locator
locator = getattr(axis, '_minor_locator_cached', None)
if locator is None:
locator = axis._minor_locator_cached = axis.get_minor_locator()
locator = constructor.Locator([x for x in locator() if lim[0] <= x <= lim[1]]) # noqa: E501
axis.set_minor_locator(locator)
def _update_formatter(
self, x, formatter=None, *, formatter_kw=None,
tickrange=None, wraprange=None,
):
"""
Update the axis formatter. Passes `formatter` through `Formatter` with kwargs.
"""
# Test if this is date axes
# See: https://matplotlib.org/api/units_api.html
# And: https://matplotlib.org/api/dates_api.html
axis = getattr(self, x + 'axis')
date = isinstance(axis.converter, mdates.DateConverter)
# Major formatter
# NOTE: The default axis formatter accepts lots of keywords. So unlike
# everywhere else that uses constructor functions we also allow only
# formatter_kw input without formatter and use 'auto' as the default.
formatter_kw = formatter_kw or {}
formatter_kw = formatter_kw.copy()
if formatter is not None or tickrange is not None or wraprange is not None or formatter_kw: # noqa: E501
# Tick range
formatter = _not_none(formatter, 'auto')
if tickrange is not None or wraprange is not None:
if formatter != 'auto':
warnings._warn_proplot(
'The tickrange and autorange features require '
'proplot.AutoFormatter formatter. Overriding the input.'
)
if tickrange is not None:
formatter_kw.setdefault('tickrange', tickrange)
if wraprange is not None:
formatter_kw.setdefault('wraprange', wraprange)
# Set the formatter
# Note some formatters require 'locator' as keyword arg
if formatter in ('date', 'concise'):
locator = axis.get_major_locator()
formatter_kw.setdefault('locator', locator)
formatter = constructor.Formatter(formatter, date=date, **formatter_kw)
axis.set_major_formatter(formatter)
def _update_labels(self, x, *args, **kwargs):
"""
Apply axis labels to the relevant shared axis. If spanning labels are toggled
this keeps the labels synced for all subplots in the same row or column. Label
positions will be adjusted at draw-time with figure._align_axislabels.
"""
# NOTE: Critical to test whether arguments are None or else this
# will set isDefault_label to False every time format() is called.
# NOTE: This always updates the *current* labels and sharing is handled
# later so that labels set with set_xlabel() and set_ylabel() are shared too.
# See notes in _align_axis_labels() and _apply_axis_sharing().
kwargs = self._get_label_props(**kwargs)
if all(a is None for a in args) and all(v is None for v in kwargs.values()):
return # also returns if args and kwargs are empty
getattr(self, 'set_' + x + 'label')(*args, **kwargs)
def _update_locators(
self, x, locator=None, minorlocator=None, *,
tickminor=None, locator_kw=None, minorlocator_kw=None,
):
"""
Update the locators. Requires `Locator` instances.
"""
# Apply input major locator
axis = getattr(self, x + 'axis')
locator_kw = locator_kw or {}
if locator is not None:
locator = constructor.Locator(locator, **locator_kw)
axis.set_major_locator(locator)
if isinstance(locator, mticker.IndexLocator):
tickminor = _not_none(tickminor, False) # disable 'index' minor ticks
# Apply input or default minor locator
# NOTE: Parts of API (dualxy) rely on minor tick toggling preserving the
# isDefault_minloc setting. In future should override mpl minorticks_on()
# NOTE: Unlike matplotlib when "turning on" minor ticks we *always* use the
# scale default, thanks to scale classes refactoring with _ScaleBase.
isdefault = minorlocator is None
minorlocator_kw = minorlocator_kw or {}
if not isdefault:
minorlocator = constructor.Locator(minorlocator, **minorlocator_kw)
elif tickminor:
minorlocator = getattr(axis._scale, '_default_minor_locator', None)
if not minorlocator:
minorlocator = constructor.Locator('minor')
if minorlocator is not None:
axis.set_minor_locator(minorlocator)
axis.isDefault_minloc = isdefault
# Disable minor ticks
# NOTE: Generally if you *enable* minor ticks on a dual axis, want to
# allow FuncScale updates to change the minor tick locators. If you
# *disable* minor ticks, do not want FuncScale applications to turn them
# on. So we allow below to set isDefault_minloc to False.
if tickminor is not None and not tickminor:
axis.set_minor_locator(constructor.Locator('null'))
def _update_limits(self, x, *, min_=None, max_=None, lim=None, reverse=None):
"""
Update the axis limits.
"""
# Set limits for just one side or both at once
axis = getattr(self, x + 'axis')
if min_ is not None or max_ is not None:
if lim is not None:
warnings._warn_proplot(
f'Overriding {x}lim={lim!r} '
f'with {x}min={min_!r} and {x}max={max_!r}.'
)
lim = (min_, max_)
if lim is not None:
getattr(self, 'set_' + x + 'lim')(lim)
# Reverse direction
# NOTE: 3.1+ has axis.set_inverted(), below is from source code
if reverse is not None:
lo, hi = axis.get_view_interval()
if reverse:
lim = (max(lo, hi), min(lo, hi))
else:
lim = (min(lo, hi), max(lo, hi))
axis.set_view_interval(*lim, ignore=True)
def _update_rotation(self, x, *, rotation=None):
"""
Rotate the tick labels. Rotate 90 degrees by default for datetime *x* axes.
"""
# Apply rotation for datetime axes.
# NOTE: Rotation is done *before* horizontal/vertical alignment. Cannot
# change alignment with set_tick_params so we must apply to text objects.
# Note fig.autofmt_date calls subplots_adjust, so we cannot use it.
x = _not_none(x, 'x')
current = '_' + x + 'axis_current_rotation'
default = '_' + x + 'axis_isdefault_rotation'
axis = getattr(self, x + 'axis')
if rotation is not None:
setattr(self, default, False)
elif not getattr(self, default):
return # do not rotate
elif x == 'x' and isinstance(axis.converter, mdates.DateConverter):
rotation = rc['formatter.timerotation']
else:
rotation = 'horizontal'
# Apply tick label rotation if necessary
if rotation != getattr(self, current):
rotation = {'horizontal': 0, 'vertical': 90}.get(rotation, rotation)
kw = {'rotation': rotation}
if rotation not in (0, 90, -90):
kw['ha'] = 'right' if rotation > 0 else 'left'
for label in axis.get_ticklabels():
label.update(kw)
setattr(self, current, rotation)
def _update_spines(self, x, *, loc=None, bounds=None):
"""
Update the spine settings.
"""
# Iterate over spines associated with this axis
sides = ('bottom', 'top') if x == 'x' else ('left', 'right')
for side in sides:
# Change default spine location from 'both' to the first relevant
# side if the user passes 'bounds'.
spine = self.spines[side]
if loc is None and bounds is not None:
loc = _not_none(loc, sides[0])
# Eliminate sides
if loc == 'neither':
spine.set_visible(False)
elif loc == 'both':
spine.set_visible(True)
elif loc in sides: # make relevant spine visible
spine.set_visible(side == loc)
# Special spine location, usually 'zero', 'center', or tuple with
# (units, location) where 'units' can be 'axes', 'data', or 'outward'.
# Matplotlib internally represents these with 'bottom' and 'left'.
elif loc is not None:
if side == sides[1]:
spine.set_visible(False)
else:
spine.set_visible(True)
try:
spine.set_position(loc)
except ValueError:
raise ValueError(
f'Invalid {x} spine location {loc!r}. Options are: '
+ ', '.join(map(repr, (*sides, 'both', 'neither'))) + '.'
)
# Apply spine bounds
if bounds is not None:
spine.set_bounds(*bounds)
def _update_locs(self, x, *, tickloc=None, ticklabelloc=None, labelloc=None):
"""
Update the tick, tick label, and axis label locations.
"""
# The tick and tick label sides for Cartesian axes
kw = {}
sides = ('bottom', 'top') if x == 'x' else ('left', 'right')
sides_active = tuple(side for side in sides if self.spines[side].get_visible())
sides_dict = {None: None, 'both': sides, 'none': (), 'neither': ()}
# The tick side(s)
ticklocs = sides_dict.get(tickloc, (tickloc,))
if ticklocs is not None:
kw.update({side: side in ticklocs for side in sides})
kw.update({side: False for side in sides if side not in sides_active})
# The tick label side(s). Make sure these only appear where ticks are
ticklabellocs = sides_dict.get(ticklabelloc, (ticklabelloc,))
if ticklabellocs is not None:
kw.update({'label' + side: (side in ticklabellocs) for side in sides})
kw.update(
{
'label' + side: False for side in sides
if side not in sides_active
or ticklocs is not None and side not in ticklocs
}
)
# The axis label side(s)
if labelloc is None:
if ticklocs is not None:
options = tuple(_ for _ in sides if _ in ticklocs and _ in sides_active)
if len(options) == 1:
labelloc = options[0]
if labelloc is not None and labelloc not in sides:
raise ValueError(
f'Invalid label location {labelloc!r}. Options are '
+ ', '.join(map(repr, sides)) + '.'
)
# Apply the tick, tick label, and label locations
self.tick_params(axis=x, which='both', **kw)
if labelloc is not None:
getattr(self, x + 'axis').set_label_position(labelloc)
[docs] @docstring._snippet_manager
def altx(self, **kwargs):
"""
%(axes.altx)s
"""
# WARNING: This repairs a matplotlib bug where twins fail to inherit the minor
# locator due to application of `AutoMinorLocator` when `ytick.minor.visible`
# is ``True`` in `Axes.cla` and due to the fact that passing ``sharey=self``
# to the alternate axes means that they share the same major and minor Tickers.
# >>> import matplotlib.pyplot as plt
# ... fig, ax = plt.subplots()
# ... ax.set_yscale('log')
# ... ax.twiny()
# WARNING: We add axes as children for tight layout algorithm convenience and
# to support eventual paradigm of arbitrarily many duplicates with spines
# arranged in an edge stack. However this means all artists drawn there take
# on zorder of their axes when drawn inside the "parent" (see Axes.draw()).
# To restore matplotlib behavior, which draws "child" artists on top simply
# because the axes was created after the "parent" one, use the inset_axes
# zorder of 4 and make the background transparent.
minorlocator = self.yaxis.get_minor_locator()
ax = self._make_twin_axes(
sharey=self, number=False, autoshare=False, projection='cartesian'
)
# Child defaults
ax._altx_parent = self
ax.yaxis.set_minor_locator(minorlocator)
ax.yaxis.isDefault_minloc = True
for side, spine in ax.spines.items():
spine.set_visible(side == 'top')
ax.xaxis.tick_top()
ax.xaxis.set_label_position('top')
ax.yaxis.set_visible(False)
ax.patch.set_visible(False)
ax.grid(False)
ax.set_zorder(4)
ax.set_autoscaley_on(self.get_autoscaley_on())
# Parent defaults
self.spines['top'].set_visible(False)
self.spines['bottom'].set_visible(True)
self.xaxis.tick_bottom()
self.xaxis.set_label_position('bottom')
# Add axes
self.add_child_axes(ax) # to facilitate tight layout
self.figure._axstack.remove(ax) # or gets drawn twice!
ax.format(**self._parse_alt('x', kwargs))
return ax
[docs] @docstring._snippet_manager
def alty(self, **kwargs):
"""
%(axes.alty)s
"""
# See altx() comments
minorlocator = self.xaxis.get_minor_locator()
ax = self._make_twin_axes(
sharex=self, number=False, autoshare=False, projection='cartesian'
)
# Child defaults
ax._alty_parent = self
ax.xaxis.set_minor_locator(minorlocator)
ax.xaxis.isDefault_minloc = True
for side, spine in ax.spines.items():
spine.set_visible(side == 'right')
ax.yaxis.tick_right()
ax.yaxis.set_label_position('right')
ax.xaxis.set_visible(False)
ax.patch.set_visible(False)
ax.grid(False)
ax.set_zorder(4)
ax.set_autoscalex_on(self.get_autoscalex_on())
# Parent defaults
self.spines['right'].set_visible(False)
self.spines['left'].set_visible(True)
self.yaxis.tick_left()
self.yaxis.set_label_position('left')
# Add axes
self.add_child_axes(ax) # to facilitate tight layout
self.figure._axstack.remove(ax) # or gets drawn twice!
ax.format(**self._parse_alt('y', kwargs))
return ax
[docs] @docstring._snippet_manager
def dualx(self, funcscale, **kwargs):
"""
%(axes.dualx)s
"""
# NOTE: Matplotlib 3.1 has a 'secondary axis' feature. For the time
# being, our version is more robust (see FuncScale) and simpler, since
# we do not create an entirely separate _SecondaryAxis class.
ax = self.altx(**kwargs)
ax._dualx_funcscale = funcscale
ax._dualx_scale()
return ax
[docs] @docstring._snippet_manager
def dualy(self, funcscale, **kwargs):
"""
%(axes.dualy)s
"""
# See dualx comments
ax = self.alty(**kwargs)
ax._dualy_funcscale = funcscale
ax._dualy_scale()
return ax
[docs] @docstring._snippet_manager
def twinx(self):
"""
%(axes.twinx)s
"""
return self.alty()
[docs] @docstring._snippet_manager
def twiny(self):
"""
%(axes.twiny)s
"""
return self.altx()
[docs] def draw(self, renderer=None, *args, **kwargs):
# Perform extra post-processing steps
# NOTE: In *principle* axis sharing application step goes here. But should
# already be complete because auto_layout() (called by figure pre-processor)
# has to run it before aligning labels. So this is harmless no-op.
self._dualx_scale()
self._dualy_scale()
self._apply_axis_sharing()
self._update_rotation('x')
if self._inset_parent is not None and self._inset_zoom:
self.indicate_inset_zoom()
super().draw(renderer, *args, **kwargs)
[docs] def get_tightbbox(self, renderer, *args, **kwargs):
# Perform extra post-processing steps
self._dualx_scale()
self._dualy_scale()
self._apply_axis_sharing()
self._update_rotation('x')
if self._inset_parent is not None and self._inset_zoom:
self.indicate_inset_zoom()
return super().get_tightbbox(renderer, *args, **kwargs)