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import functools
import itertools
import logging
import math
from numbers import Integral, Number, Real
import re
import numpy as np
import matplotlib as mpl
import matplotlib.category # Register category unit converter as side effect.
import matplotlib.cbook as cbook
import matplotlib.collections as mcoll
import matplotlib.colorizer as mcolorizer
import matplotlib.colors as mcolors
import matplotlib.contour as mcontour
import matplotlib.dates # noqa: F401, Register date unit converter as side effect.
import matplotlib.image as mimage
import matplotlib.inset as minset
import matplotlib.legend as mlegend
import matplotlib.lines as mlines
import matplotlib.markers as mmarkers
import matplotlib.mlab as mlab
import matplotlib.patches as mpatches
import matplotlib.path as mpath
import matplotlib.quiver as mquiver
import matplotlib.stackplot as mstack
import matplotlib.streamplot as mstream
import matplotlib.table as mtable
import matplotlib.text as mtext
import matplotlib.ticker as mticker
import matplotlib.transforms as mtransforms
import matplotlib.tri as mtri
import matplotlib.units as munits
from matplotlib import _api, _docstring, _preprocess_data
from matplotlib.axes._base import (
_AxesBase, _TransformedBoundsLocator, _process_plot_format)
from matplotlib.axes._secondary_axes import SecondaryAxis
from matplotlib.container import BarContainer, ErrorbarContainer, StemContainer
from matplotlib.transforms import _ScaledRotation
_log = logging.getLogger(__name__)
# The axes module contains all the wrappers to plotting functions.
# All the other methods should go in the _AxesBase class.
def _make_axes_method(func):
"""
Patch the qualname for functions that are directly added to Axes.
Some Axes functionality is defined in functions in other submodules.
These are simply added as attributes to Axes. As a result, their
``__qualname__`` is e.g. only "table" and not "Axes.table". This
function fixes that.
Note that the function itself is patched, so that
``matplotlib.table.table.__qualname__` will also show "Axes.table".
However, since these functions are not intended to be standalone,
this is bearable.
"""
func.__qualname__ = f"Axes.{func.__name__}"
return func
class _GroupedBarReturn:
"""
A provisional result object for `.Axes.grouped_bar`.
This is a placeholder for a future better return type. We try to build in
backward compatibility / migration possibilities.
The only public interfaces are the ``bar_containers`` attribute and the
``remove()`` method.
"""
def __init__(self, bar_containers):
self.bar_containers = bar_containers
def remove(self):
[b.remove() for b in self.bar_containers]
@_docstring.interpd
class Axes(_AxesBase):
"""
An Axes object encapsulates all the elements of an individual (sub-)plot in
a figure.
It contains most of the (sub-)plot elements: `~.axis.Axis`,
`~.axis.Tick`, `~.lines.Line2D`, `~.text.Text`, `~.patches.Polygon`, etc.,
and sets the coordinate system.
Like all visible elements in a figure, Axes is an `.Artist` subclass.
The `Axes` instance supports callbacks through a callbacks attribute which
is a `~.cbook.CallbackRegistry` instance. The events you can connect to
are 'xlim_changed' and 'ylim_changed' and the callback will be called with
func(*ax*) where *ax* is the `Axes` instance.
.. note::
As a user, you do not instantiate Axes directly, but use Axes creation
methods instead; e.g. from `.pyplot` or `.Figure`:
`~.pyplot.subplots`, `~.pyplot.subplot_mosaic` or `.Figure.add_axes`.
"""
### Labelling, legend and texts
def get_title(self, loc="center"):
"""
Get an Axes title.
Get one of the three available Axes titles. The available titles
are positioned above the Axes in the center, flush with the left
edge, and flush with the right edge.
Parameters
----------
loc : {'center', 'left', 'right'}, str, default: 'center'
Which title to return.
Returns
-------
str
The title text string.
"""
titles = {'left': self._left_title,
'center': self.title,
'right': self._right_title}
title = _api.check_getitem(titles, loc=loc.lower())
return title.get_text()
def set_title(self, label, fontdict=None, loc=None, pad=None, *, y=None,
**kwargs):
"""
Set a title for the Axes.
Set one of the three available Axes titles. The available titles
are positioned above the Axes in the center, flush with the left
edge, and flush with the right edge.
Parameters
----------
label : str
Text to use for the title
fontdict : dict
.. admonition:: Discouraged
The use of *fontdict* is discouraged. Parameters should be passed as
individual keyword arguments or using dictionary-unpacking
``set_title(..., **fontdict)``.
A dictionary controlling the appearance of the title text,
the default *fontdict* is::
{'fontsize': rcParams['axes.titlesize'],
'fontweight': rcParams['axes.titleweight'],
'color': rcParams['axes.titlecolor'],
'verticalalignment': 'baseline',
'horizontalalignment': loc}
loc : {'center', 'left', 'right'}, default: :rc:`axes.titlelocation`
Which title to set.
y : float, default: :rc:`axes.titley`
Vertical Axes location for the title (1.0 is the top). If
None (the default) and :rc:`axes.titley` is also None, y is
determined automatically to avoid decorators on the Axes.
pad : float, default: :rc:`axes.titlepad`
The offset of the title from the top of the Axes, in points.
Returns
-------
`.Text`
The matplotlib text instance representing the title
Other Parameters
----------------
**kwargs : `~matplotlib.text.Text` properties
Other keyword arguments are text properties, see `.Text` for a list
of valid text properties.
"""
loc = mpl._val_or_rc(loc, 'axes.titlelocation').lower()
y = mpl._val_or_rc(y, 'axes.titley')
if y is None:
y = 1.0
else:
self._autotitlepos = False
kwargs['y'] = y
titles = {'left': self._left_title,
'center': self.title,
'right': self._right_title}
title = _api.check_getitem(titles, loc=loc)
default = {
'fontsize': mpl.rcParams['axes.titlesize'],
'fontweight': mpl.rcParams['axes.titleweight'],
'verticalalignment': 'baseline',
'horizontalalignment': loc}
titlecolor = mpl.rcParams['axes.titlecolor']
if not cbook._str_lower_equal(titlecolor, 'auto'):
default["color"] = titlecolor
self._set_title_offset_trans(float(mpl._val_or_rc(pad, 'axes.titlepad')))
title.set_text(label)
title.update(default)
if fontdict is not None:
title.update(fontdict)
title._internal_update(kwargs)
return title
def get_legend_handles_labels(self, legend_handler_map=None):
"""
Return handles and labels for legend
``ax.legend()`` is equivalent to ::
h, l = ax.get_legend_handles_labels()
ax.legend(h, l)
"""
# pass through to legend.
handles, labels = mlegend._get_legend_handles_labels(
[self], legend_handler_map)
return handles, labels
@_docstring.interpd
def legend(self, *args, **kwargs):
"""
Place a legend on the Axes.
Call signatures::
legend()
legend(handles, labels)
legend(handles=handles)
legend(labels)
The call signatures correspond to the following different ways to use
this method:
**1. Automatic detection of elements to be shown in the legend**
The elements to be added to the legend are automatically determined,
when you do not pass in any extra arguments.
In this case, the labels are taken from the artist. You can specify
them either at artist creation or by calling the
:meth:`~.Artist.set_label` method on the artist::
ax.plot([1, 2, 3], label='Inline label')
ax.legend()
or::
line, = ax.plot([1, 2, 3])
line.set_label('Label via method')
ax.legend()
.. note::
Specific artists can be excluded from the automatic legend element
selection by using a label starting with an underscore, "_".
A string starting with an underscore is the default label for all
artists, so calling `.Axes.legend` without any arguments and
without setting the labels manually will result in a ``UserWarning``
and an empty legend being drawn.
**2. Explicitly listing the artists and labels in the legend**
For full control of which artists have a legend entry, it is possible
to pass an iterable of legend artists followed by an iterable of
legend labels respectively::
ax.legend([line1, line2, line3], ['label1', 'label2', 'label3'])
**3. Explicitly listing the artists in the legend**
This is similar to 2, but the labels are taken from the artists'
label properties. Example::
line1, = ax.plot([1, 2, 3], label='label1')
line2, = ax.plot([1, 2, 3], label='label2')
ax.legend(handles=[line1, line2])
**4. Labeling existing plot elements**
.. admonition:: Discouraged
This call signature is discouraged, because the relation between
plot elements and labels is only implicit by their order and can
easily be mixed up.
To make a legend for all artists on an Axes, call this function with
an iterable of strings, one for each legend item. For example::
ax.plot([1, 2, 3])
ax.plot([5, 6, 7])
ax.legend(['First line', 'Second line'])
Parameters
----------
handles : list of (`.Artist` or tuple of `.Artist`), optional
A list of Artists (lines, patches) to be added to the legend.
Use this together with *labels*, if you need full control on what
is shown in the legend and the automatic mechanism described above
is not sufficient.
The length of handles and labels should be the same in this
case. If they are not, they are truncated to the smaller length.
If an entry contains a tuple, then the legend handler for all Artists in the
tuple will be placed alongside a single label.
labels : list of str, optional
A list of labels to show next to the artists.
Use this together with *handles*, if you need full control on what
is shown in the legend and the automatic mechanism described above
is not sufficient.
Returns
-------
`~matplotlib.legend.Legend`
Other Parameters
----------------
%(_legend_kw_axes)s
See Also
--------
.Figure.legend
Notes
-----
Some artists are not supported by this function. See
:ref:`legend_guide` for details.
Examples
--------
.. plot:: gallery/text_labels_and_annotations/legend.py
"""
handles, labels, kwargs = mlegend._parse_legend_args([self], *args, **kwargs)
self.legend_ = mlegend.Legend(self, handles, labels, **kwargs)
self.legend_._remove_method = self._remove_legend
return self.legend_
def _remove_legend(self, legend):
self.legend_ = None
def inset_axes(self, bounds, *, transform=None, zorder=5, **kwargs):
"""
Add a child inset Axes to this existing Axes.
Parameters
----------
bounds : [x0, y0, width, height]
Lower-left corner of inset Axes, and its width and height.
transform : `.Transform`
Defaults to `!ax.transAxes`, i.e. the units of *rect* are in
Axes-relative coordinates.
projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', \
'polar', 'rectilinear', str}, optional
The projection type of the inset `~.axes.Axes`. *str* is the name
of a custom projection, see `~matplotlib.projections`. The default
None results in a 'rectilinear' projection.
polar : bool, default: False
If True, equivalent to projection='polar'.
axes_class : subclass type of `~.axes.Axes`, optional
The `.axes.Axes` subclass that is instantiated. This parameter
is incompatible with *projection* and *polar*. See
:ref:`axisartist_users-guide-index` for examples.
zorder : number
Defaults to 5 (same as `.Axes.legend`). Adjust higher or lower
to change whether it is above or below data plotted on the
parent Axes.
**kwargs
Other keyword arguments are passed on to the inset Axes class.
Returns
-------
ax
The created `~.axes.Axes` instance.
Examples
--------
This example makes two inset Axes, the first is in Axes-relative
coordinates, and the second in data-coordinates::
fig, ax = plt.subplots()
ax.plot(range(10))
axin1 = ax.inset_axes([0.8, 0.1, 0.15, 0.15])
axin2 = ax.inset_axes(
[5, 7, 2.3, 2.3], transform=ax.transData)
"""
if transform is None:
transform = self.transAxes
kwargs.setdefault('label', 'inset_axes')
# This puts the rectangle into figure-relative coordinates.
inset_locator = _TransformedBoundsLocator(bounds, transform)
bounds = inset_locator(self, None).bounds
fig = self.get_figure(root=False)
projection_class, pkw = fig._process_projection_requirements(**kwargs)
inset_ax = projection_class(fig, bounds, zorder=zorder, **pkw)
# this locator lets the axes move if in data coordinates.
# it gets called in `ax.apply_aspect() (of all places)
inset_ax.set_axes_locator(inset_locator)
self.add_child_axes(inset_ax)
return inset_ax
@_docstring.interpd
def indicate_inset(self, bounds=None, inset_ax=None, *, transform=None,
facecolor='none', edgecolor='0.5', alpha=0.5,
zorder=None, **kwargs):
"""
Add an inset indicator to the Axes. This is a rectangle on the plot
at the position indicated by *bounds* that optionally has lines that
connect the rectangle to an inset Axes (`.Axes.inset_axes`).
Warnings
--------
This method is experimental as of 3.0, and the API may change.
Parameters
----------
bounds : [x0, y0, width, height], optional
Lower-left corner of rectangle to be marked, and its width
and height. If not set, the bounds will be calculated from the
data limits of *inset_ax*, which must be supplied.
inset_ax : `.Axes`, optional
An optional inset Axes to draw connecting lines to. Two lines are
drawn connecting the indicator box to the inset Axes on corners
chosen so as to not overlap with the indicator box.
transform : `.Transform`
Transform for the rectangle coordinates. Defaults to
``ax.transData``, i.e. the units of *rect* are in the Axes' data
coordinates.
facecolor : :mpltype:`color`, default: 'none'
Facecolor of the rectangle.
edgecolor : :mpltype:`color`, default: '0.5'
Color of the rectangle and color of the connecting lines.
alpha : float or None, default: 0.5
Transparency of the rectangle and connector lines. If not
``None``, this overrides any alpha value included in the
*facecolor* and *edgecolor* parameters.
zorder : float, default: 4.99
Drawing order of the rectangle and connector lines. The default,
4.99, is just below the default level of inset Axes.
**kwargs
Other keyword arguments are passed on to the `.Rectangle` patch:
%(Rectangle:kwdoc)s
Returns
-------
inset_indicator : `.inset.InsetIndicator`
An artist which contains
inset_indicator.rectangle : `.Rectangle`
The indicator frame.
inset_indicator.connectors : 4-tuple of `.patches.ConnectionPatch`
The four connector lines connecting to (lower_left, upper_left,
lower_right upper_right) corners of *inset_ax*. Two lines are
set with visibility to *False*, but the user can set the
visibility to True if the automatic choice is not deemed correct.
.. versionchanged:: 3.10
Previously the rectangle and connectors tuple were returned.
"""
# to make the Axes connectors work, we need to apply the aspect to
# the parent Axes.
self.apply_aspect()
if transform is None:
transform = self.transData
kwargs.setdefault('label', '_indicate_inset')
indicator_patch = minset.InsetIndicator(
bounds, inset_ax=inset_ax,
facecolor=facecolor, edgecolor=edgecolor, alpha=alpha,
zorder=zorder, transform=transform, **kwargs)
self.add_artist(indicator_patch)
return indicator_patch
def indicate_inset_zoom(self, inset_ax, **kwargs):
"""
Add an inset indicator rectangle to the Axes based on the axis
limits for an *inset_ax* and draw connectors between *inset_ax*
and the rectangle.
Warnings
--------
This method is experimental as of 3.0, and the API may change.
Parameters
----------
inset_ax : `.Axes`
Inset Axes to draw connecting lines to. Two lines are
drawn connecting the indicator box to the inset Axes on corners
chosen so as to not overlap with the indicator box.
**kwargs
Other keyword arguments are passed on to `.Axes.indicate_inset`
Returns
-------
inset_indicator : `.inset.InsetIndicator`
An artist which contains
inset_indicator.rectangle : `.Rectangle`
The indicator frame.
inset_indicator.connectors : 4-tuple of `.patches.ConnectionPatch`
The four connector lines connecting to (lower_left, upper_left,
lower_right upper_right) corners of *inset_ax*. Two lines are
set with visibility to *False*, but the user can set the
visibility to True if the automatic choice is not deemed correct.
.. versionchanged:: 3.10
Previously the rectangle and connectors tuple were returned.
"""
return self.indicate_inset(None, inset_ax, **kwargs)
@_docstring.interpd
def secondary_xaxis(self, location, functions=None, *, transform=None, **kwargs):
"""
Add a second x-axis to this `~.axes.Axes`.
For example if we want to have a second scale for the data plotted on
the xaxis.
%(_secax_docstring)s
Examples
--------
The main axis shows frequency, and the secondary axis shows period.
.. plot::
fig, ax = plt.subplots()
ax.loglog(range(1, 360, 5), range(1, 360, 5))
ax.set_xlabel('frequency [Hz]')
def invert(x):
# 1/x with special treatment of x == 0
x = np.array(x).astype(float)
near_zero = np.isclose(x, 0)
x[near_zero] = np.inf
x[~near_zero] = 1 / x[~near_zero]
return x
# the inverse of 1/x is itself
secax = ax.secondary_xaxis('top', functions=(invert, invert))
secax.set_xlabel('Period [s]')
plt.show()
To add a secondary axis relative to your data, you can pass a transform
to the new axis.
.. plot::
fig, ax = plt.subplots()
ax.plot(range(0, 5), range(-1, 4))
# Pass 'ax.transData' as a transform to place the axis
# relative to your data at y=0
secax = ax.secondary_xaxis(0, transform=ax.transData)
"""
if not (location in ['top', 'bottom'] or isinstance(location, Real)):
raise ValueError('secondary_xaxis location must be either '
'a float or "top"/"bottom"')
secondary_ax = SecondaryAxis(self, 'x', location, functions,
transform, **kwargs)
self.add_child_axes(secondary_ax)
return secondary_ax
@_docstring.interpd
def secondary_yaxis(self, location, functions=None, *, transform=None, **kwargs):
"""
Add a second y-axis to this `~.axes.Axes`.
For example if we want to have a second scale for the data plotted on
the yaxis.
%(_secax_docstring)s
Examples
--------
Add a secondary Axes that converts from radians to degrees
.. plot::
fig, ax = plt.subplots()
ax.plot(range(1, 360, 5), range(1, 360, 5))
ax.set_ylabel('degrees')
secax = ax.secondary_yaxis('right', functions=(np.deg2rad,
np.rad2deg))
secax.set_ylabel('radians')
To add a secondary axis relative to your data, you can pass a transform
to the new axis.
.. plot::
fig, ax = plt.subplots()
ax.plot(range(0, 5), range(-1, 4))
# Pass 'ax.transData' as a transform to place the axis
# relative to your data at x=3
secax = ax.secondary_yaxis(3, transform=ax.transData)
"""
if not (location in ['left', 'right'] or isinstance(location, Real)):
raise ValueError('secondary_yaxis location must be either '
'a float or "left"/"right"')
secondary_ax = SecondaryAxis(self, 'y', location, functions,
transform, **kwargs)
self.add_child_axes(secondary_ax)
return secondary_ax
@_docstring.interpd
def text(self, x, y, s, fontdict=None, **kwargs):
"""
Add text to the Axes.
Add the text *s* to the Axes at location *x*, *y* in data coordinates,
with a default ``horizontalalignment`` on the ``left`` and
``verticalalignment`` at the ``baseline``. See
:doc:`/gallery/text_labels_and_annotations/text_alignment`.
Parameters
----------
x, y : float
The position to place the text. By default, this is in data
coordinates. The coordinate system can be changed using the
*transform* parameter.
s : str
The text.
fontdict : dict, default: None
.. admonition:: Discouraged
The use of *fontdict* is discouraged. Parameters should be passed as
individual keyword arguments or using dictionary-unpacking
``text(..., **fontdict)``.
A dictionary to override the default text properties. If fontdict
is None, the defaults are determined by `.rcParams`.
Returns
-------
`.Text`
The created `.Text` instance.
Other Parameters
----------------
**kwargs : `~matplotlib.text.Text` properties.
Other miscellaneous text parameters.
%(Text:kwdoc)s
Examples
--------
Individual keyword arguments can be used to override any given
parameter::
>>> text(x, y, s, fontsize=12)
The default transform specifies that text is in data coords,
alternatively, you can specify text in axis coords ((0, 0) is
lower-left and (1, 1) is upper-right). The example below places
text in the center of the Axes::
>>> text(0.5, 0.5, 'matplotlib', horizontalalignment='center',
... verticalalignment='center', transform=ax.transAxes)
You can put a rectangular box around the text instance (e.g., to
set a background color) by using the keyword *bbox*. *bbox* is
a dictionary of `~matplotlib.patches.Rectangle`
properties. For example::
>>> text(x, y, s, bbox=dict(facecolor='red', alpha=0.5))
"""
effective_kwargs = {
'verticalalignment': 'baseline',
'horizontalalignment': 'left',
'transform': self.transData,
'clip_on': False,
**(fontdict if fontdict is not None else {}),
**kwargs,
}
t = mtext.Text(x, y, text=s, **effective_kwargs)
if t.get_clip_path() is None:
t.set_clip_path(self.patch)
self._add_text(t)
return t
@_docstring.interpd
def annotate(self, text, xy, xytext=None, xycoords='data', textcoords=None,
arrowprops=None, annotation_clip=None, **kwargs):
# Signature must match Annotation. This is verified in
# test_annotate_signature().
a = mtext.Annotation(text, xy, xytext=xytext, xycoords=xycoords,
textcoords=textcoords, arrowprops=arrowprops,
annotation_clip=annotation_clip, **kwargs)
a.set_transform(mtransforms.IdentityTransform())
if kwargs.get('clip_on', False) and a.get_clip_path() is None:
a.set_clip_path(self.patch)
self._add_text(a)
return a
annotate.__doc__ = mtext.Annotation.__init__.__doc__
#### Lines and spans
@_docstring.interpd
def axhline(self, y=0, xmin=0, xmax=1, **kwargs):
"""
Add a horizontal line spanning the whole or fraction of the Axes.
Note: If you want to set x-limits in data coordinates, use
`~.Axes.hlines` instead.
Parameters
----------
y : float, default: 0
y position in :ref:`data coordinates <coordinate-systems>`.
xmin : float, default: 0
The start x-position in :ref:`axes coordinates <coordinate-systems>`.
Should be between 0 and 1, 0 being the far left of the plot,
1 the far right of the plot.
xmax : float, default: 1
The end x-position in :ref:`axes coordinates <coordinate-systems>`.
Should be between 0 and 1, 0 being the far left of the plot,
1 the far right of the plot.
Returns
-------
`~matplotlib.lines.Line2D`
A `.Line2D` specified via two points ``(xmin, y)``, ``(xmax, y)``.
Its transform is set such that *x* is in
:ref:`axes coordinates <coordinate-systems>` and *y* is in
:ref:`data coordinates <coordinate-systems>`.
This is still a generic line and the horizontal character is only
realized through using identical *y* values for both points. Thus,
if you want to change the *y* value later, you have to provide two
values ``line.set_ydata([3, 3])``.
Other Parameters
----------------
**kwargs
Valid keyword arguments are `.Line2D` properties, except for
'transform':
%(Line2D:kwdoc)s
See Also
--------
hlines : Add horizontal lines in data coordinates.
axhspan : Add a horizontal span (rectangle) across the axis.
axline : Add a line with an arbitrary slope.
Examples
--------
* draw a thick red hline at 'y' = 0 that spans the xrange::
>>> axhline(linewidth=4, color='r')
* draw a default hline at 'y' = 1 that spans the xrange::
>>> axhline(y=1)
* draw a default hline at 'y' = .5 that spans the middle half of
the xrange::
>>> axhline(y=.5, xmin=0.25, xmax=0.75)
"""
self._check_no_units([xmin, xmax], ['xmin', 'xmax'])
if "transform" in kwargs:
raise ValueError("'transform' is not allowed as a keyword "
"argument; axhline generates its own transform.")
ymin, ymax = self.get_ybound()
# Strip away the units for comparison with non-unitized bounds.
yy, = self._process_unit_info([("y", y)], kwargs)
scaley = (yy < ymin) or (yy > ymax)
trans = self.get_yaxis_transform(which='grid')
l = mlines.Line2D([xmin, xmax], [y, y], transform=trans, **kwargs)
self.add_line(l)
l.get_path()._interpolation_steps = mpl.axis.GRIDLINE_INTERPOLATION_STEPS
if scaley:
self._request_autoscale_view("y")
return l
@_docstring.interpd
def axvline(self, x=0, ymin=0, ymax=1, **kwargs):
"""
Add a vertical line spanning the whole or fraction of the Axes.
Note: If you want to set y-limits in data coordinates, use
`~.Axes.vlines` instead.
Parameters
----------
x : float, default: 0
x position in :ref:`data coordinates <coordinate-systems>`.
ymin : float, default: 0
The start y-position in :ref:`axes coordinates <coordinate-systems>`.
Should be between 0 and 1, 0 being the bottom of the plot, 1 the
top of the plot.
ymax : float, default: 1
The end y-position in :ref:`axes coordinates <coordinate-systems>`.
Should be between 0 and 1, 0 being the bottom of the plot, 1 the
top of the plot.
Returns
-------
`~matplotlib.lines.Line2D`
A `.Line2D` specified via two points ``(x, ymin)``, ``(x, ymax)``.
Its transform is set such that *x* is in
:ref:`data coordinates <coordinate-systems>` and *y* is in
:ref:`axes coordinates <coordinate-systems>`.
This is still a generic line and the vertical character is only
realized through using identical *x* values for both points. Thus,
if you want to change the *x* value later, you have to provide two
values ``line.set_xdata([3, 3])``.
Other Parameters
----------------
**kwargs
Valid keyword arguments are `.Line2D` properties, except for
'transform':
%(Line2D:kwdoc)s
See Also
--------
vlines : Add vertical lines in data coordinates.
axvspan : Add a vertical span (rectangle) across the axis.
axline : Add a line with an arbitrary slope.
Examples
--------
* draw a thick red vline at *x* = 0 that spans the yrange::
>>> axvline(linewidth=4, color='r')
* draw a default vline at *x* = 1 that spans the yrange::
>>> axvline(x=1)
* draw a default vline at *x* = .5 that spans the middle half of
the yrange::
>>> axvline(x=.5, ymin=0.25, ymax=0.75)
"""
self._check_no_units([ymin, ymax], ['ymin', 'ymax'])
if "transform" in kwargs:
raise ValueError("'transform' is not allowed as a keyword "
"argument; axvline generates its own transform.")
xmin, xmax = self.get_xbound()
# Strip away the units for comparison with non-unitized bounds.
xx, = self._process_unit_info([("x", x)], kwargs)
scalex = (xx < xmin) or (xx > xmax)
trans = self.get_xaxis_transform(which='grid')
l = mlines.Line2D([x, x], [ymin, ymax], transform=trans, **kwargs)
self.add_line(l)
l.get_path()._interpolation_steps = mpl.axis.GRIDLINE_INTERPOLATION_STEPS
if scalex:
self._request_autoscale_view("x")
return l
@staticmethod
def _check_no_units(vals, names):
# Helper method to check that vals are not unitized
for val, name in zip(vals, names):
if not munits._is_natively_supported(val):
raise ValueError(f"{name} must be a single scalar value, "
f"but got {val}")
@_docstring.interpd
def axline(self, xy1, xy2=None, *, slope=None, **kwargs):
"""
Add an infinitely long straight line.
The line can be defined either by two points *xy1* and *xy2*, or
by one point *xy1* and a *slope*.
This draws a straight line "on the screen", regardless of the x and y
scales, and is thus also suitable for drawing exponential decays in
semilog plots, power laws in loglog plots, etc. However, *slope*
should only be used with linear scales; It has no clear meaning for
all other scales, and thus the behavior is undefined. Please specify
the line using the points *xy1*, *xy2* for non-linear scales.
The *transform* keyword argument only applies to the points *xy1*,
*xy2*. The *slope* (if given) is always in data coordinates. This can
be used e.g. with ``ax.transAxes`` for drawing grid lines with a fixed
slope.
Parameters
----------
xy1, xy2 : (float, float)
Points for the line to pass through.
Either *xy2* or *slope* has to be given.
slope : float, optional
The slope of the line. Either *xy2* or *slope* has to be given.
Returns
-------
`.AxLine`
Other Parameters
----------------
**kwargs
Valid kwargs are `.Line2D` properties
%(Line2D:kwdoc)s
See Also
--------
axhline : for horizontal lines
axvline : for vertical lines
Examples
--------
Draw a thick red line passing through (0, 0) and (1, 1)::
>>> axline((0, 0), (1, 1), linewidth=4, color='r')
"""
if slope is not None and (self.get_xscale() != 'linear' or
self.get_yscale() != 'linear'):
raise TypeError("'slope' cannot be used with non-linear scales")
datalim = [xy1] if xy2 is None else [xy1, xy2]
if "transform" in kwargs:
# if a transform is passed (i.e. line points not in data space),
# data limits should not be adjusted.
datalim = []
line = mlines.AxLine(xy1, xy2, slope, **kwargs)
# Like add_line, but correctly handling data limits.
self._set_artist_props(line)
if line.get_clip_path() is None:
line.set_clip_path(self.patch)
if not line.get_label():
line.set_label(f"_child{len(self._children)}")
self._children.append(line)
line._remove_method = self._children.remove
self.update_datalim(datalim)
self._request_autoscale_view()
return line
@_docstring.interpd
def axhspan(self, ymin, ymax, xmin=0, xmax=1, **kwargs):
"""
Add a horizontal span (rectangle) across the Axes.
The rectangle spans from *ymin* to *ymax* vertically, and, by default,
the whole x-axis horizontally. The x-span can be set using *xmin*
(default: 0) and *xmax* (default: 1) which are in axis units; e.g.
``xmin = 0.5`` always refers to the middle of the x-axis regardless of