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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>matplotlib.transforms — Matplotlib 3.2.0 documentation</title>

title="Search within Matplotlib 3.2.0 documentation"

href="../../_static/opensearch.xml"/>

</head><body>

<div id="unreleased-message"> You are reading an old version of the documentation (v3.2.0). For the latest version see <a href="/stable/">https://matplotlib.org/stable/</a> </div>

<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 3.2.0</div>

<div id="forkongithub"><a href="https://github.com/matplotlib/matplotlib">Fork me on GitHub</a></div>

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<li class="nav-item nav-item-1"><a href="../index.html" >Module code</a> »</li>

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</div>

<h1>Source code for matplotlib.transforms</h1><div class="highlight"><pre>

"""

matplotlib includes a framework for arbitrary geometric

transformations that is used determine the final position of all

elements drawn on the canvas.

Transforms are composed into trees of `TransformNode` objects

whose actual value depends on their children. When the contents of

children change, their parents are automatically invalidated. The

next time an invalidated transform is accessed, it is recomputed to

reflect those changes. This invalidation/caching approach prevents

unnecessary recomputations of transforms, and contributes to better

interactive performance.

For example, here is a graph of the transform tree used to plot data

to the graph:

.. image:: ../_static/transforms.png

The framework can be used for both affine and non-affine

transformations. However, for speed, we want use the backend

renderers to perform affine transformations whenever possible.

Therefore, it is possible to perform just the affine or non-affine

part of a transformation on a set of data. The affine is always

assumed to occur after the non-affine. For any transform::

full transform == non-affine part + affine part

The backends are not expected to handle non-affine transformations

themselves.

"""

# Note: There are a number of places in the code where we use `np.min` or

# `np.minimum` instead of the builtin `min`, and likewise for `max`. This is

# done so that `nan`s are propagated, instead of being silently dropped.

import re

import weakref

import numpy as np

from numpy.linalg import inv

from matplotlib import cbook

from matplotlib._path import (

affine_transform, count_bboxes_overlapping_bbox, update_path_extents)

from .path import Path

DEBUG = False

def _indent_str(obj): # textwrap.indent(str(obj), 4) on Py3.

return re.sub("(^|\n)", r"\1 ", str(obj))

<div class="viewcode-block" id="TransformNode"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.TransformNode">[docs]</a>class TransformNode:

"""

:class:`TransformNode` is the base class for anything that

participates in the transform tree and needs to invalidate its

parents or be invalidated. This includes classes that are not

really transforms, such as bounding boxes, since some transforms

depend on bounding boxes to compute their values.

"""

_gid = 0

# Invalidation may affect only the affine part. If the

# invalidation was "affine-only", the _invalid member is set to

# INVALID_AFFINE_ONLY

INVALID_NON_AFFINE = 1

INVALID_AFFINE = 2

INVALID = INVALID_NON_AFFINE | INVALID_AFFINE

# Some metadata about the transform, used to determine whether an

# invalidation is affine-only

is_affine = False

is_bbox = False

pass_through = False

"""

If pass_through is True, all ancestors will always be

invalidated, even if 'self' is already invalid.

"""

def __init__(self, shorthand_name=None):

"""

Creates a new :class:`TransformNode`.

Parameters

----------

shorthand_name : str

A string representing the "name" of the transform. The name carries

no significance other than to improve the readability of

``str(transform)`` when DEBUG=True.

"""

self._parents = {}

# TransformNodes start out as invalid until their values are

# computed for the first time.

self._invalid = 1

self._shorthand_name = shorthand_name or ''

if DEBUG:

def __str__(self):

# either just return the name of this TransformNode, or its repr

return self._shorthand_name or repr(self)

def __getstate__(self):

# turn the dictionary with weak values into a normal dictionary

return {**self.__dict__,

'_parents': {k: v() for k, v in self._parents.items()}}

def __setstate__(self, data_dict):

self.__dict__ = data_dict

# turn the normal dictionary back into a dictionary with weak values

# The extra lambda is to provide a callback to remove dead

# weakrefs from the dictionary when garbage collection is done.

self._parents = {k: weakref.ref(v, lambda ref, sid=k,

target=self._parents:

target.pop(sid))

for k, v in self._parents.items() if v is not None}

def __copy__(self, *args):

raise NotImplementedError(

"TransformNode instances can not be copied. "

"Consider using frozen() instead.")

__deepcopy__ = __copy__

<div class="viewcode-block" id="TransformNode.invalidate"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.TransformNode.invalidate">[docs]</a> def invalidate(self):

"""

Invalidate this `TransformNode` and triggers an invalidation of its

ancestors. Should be called any time the transform changes.

"""

value = self.INVALID

if self.is_affine:

value = self.INVALID_AFFINE

return self._invalidate_internal(value, invalidating_node=self)</div>

def _invalidate_internal(self, value, invalidating_node):

"""

Called by :meth:`invalidate` and subsequently ascends the transform

stack calling each TransformNode's _invalidate_internal method.

"""

# determine if this call will be an extension to the invalidation

# status. If not, then a shortcut means that we needn't invoke an

# invalidation up the transform stack as it will already have been

# invalidated.

# N.B This makes the invalidation sticky, once a transform has been

# invalidated as NON_AFFINE, then it will always be invalidated as

# NON_AFFINE even when triggered with a AFFINE_ONLY invalidation.

# In most cases this is not a problem (i.e. for interactive panning and

# zooming) and the only side effect will be on performance.

status_changed = self._invalid < value

if self.pass_through or status_changed:

self._invalid = value

for parent in list(self._parents.values()):

# Dereference the weak reference

parent = parent()

if parent is not None:

parent._invalidate_internal(

value=value, invalidating_node=self)

def set_children(self, *children):

"""

Set the children of the transform, to let the invalidation

system know which transforms can invalidate this transform.

Should be called from the constructor of any transforms that

depend on other transforms.

"""

# Parents are stored as weak references, so that if the

# parents are destroyed, references from the children won't

# keep them alive.

for child in children:

# Use weak references so this dictionary won't keep obsolete nodes

# alive; the callback deletes the dictionary entry. This is a

# performance improvement over using WeakValueDictionary.

ref = weakref.ref(self, lambda ref, sid=id(self),

target=child._parents: target.pop(sid))

child._parents[id(self)] = ref

if DEBUG:

_set_children = set_children

<div class="viewcode-block" id="TransformNode.set_children"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.TransformNode.set_children">[docs]</a> def set_children(self, *children):

self._set_children(*children)

self._children = children</div>

set_children.__doc__ = _set_children.__doc__

<div class="viewcode-block" id="TransformNode.frozen"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.TransformNode.frozen">[docs]</a> def frozen(self):

"""

Returns a frozen copy of this transform node. The frozen copy

will not update when its children change. Useful for storing

a previously known state of a transform where

``copy.deepcopy()`` might normally be used.

"""

return self</div>

if DEBUG:

def write_graphviz(self, fobj, highlight=[]):

"""

For debugging purposes.

Writes the transform tree rooted at 'self' to a graphviz "dot"

format file. This file can be run through the "dot" utility

to produce a graph of the transform tree.

Affine transforms are marked in blue. Bounding boxes are

marked in yellow.

*fobj*: A Python file-like object

Once the "dot" file has been created, it can be turned into a

png easily with::

$> dot -Tpng -o $OUTPUT_FILE $DOT_FILE

"""

seen = set()

def recurse(root):

if root in seen:

return

seen.add(root)

props = {}

label = root.__class__.__name__

if root._invalid:

label = '[%s]' % label

if root in highlight:

props['style'] = 'bold'

props['shape'] = 'box'

props['label'] = '"%s"' % label

props = ' '.join(map('{0[0]}={0[1]}'.format, props.items()))

fobj.write('%s [%s];\n' % (hash(root), props))

if hasattr(root, '_children'):

for child in root._children:

name = next((key for key, val in root.__dict__.items()

if val is child), '?')

fobj.write('"%s" -> "%s" [label="%s", fontsize=10];\n'

% (hash(root),

hash(child),

name))

recurse(child)

fobj.write("digraph G {\n")

recurse(self)

fobj.write("}\n")</div>

<div class="viewcode-block" id="BboxBase"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase">[docs]</a>class BboxBase(TransformNode):

"""

This is the base class of all bounding boxes, and provides read-only access

to its data. A mutable bounding box is provided by the `Bbox` class.

The canonical representation is as two points, with no

restrictions on their ordering. Convenience properties are

provided to get the left, bottom, right and top edges and width

and height, but these are not stored explicitly.

"""

is_bbox = True

is_affine = True

if DEBUG:

@staticmethod

def _check(points):

if isinstance(points, np.ma.MaskedArray):

cbook._warn_external("Bbox bounds are a masked array.")

points = np.asarray(points)

if (points[1, 0] - points[0, 0] == 0 or

points[1, 1] - points[0, 1] == 0):

cbook._warn_external("Singular Bbox.")

<div class="viewcode-block" id="BboxBase.frozen"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.frozen">[docs]</a> def frozen(self):

return Bbox(self.get_points().copy())</div>

frozen.__doc__ = TransformNode.__doc__

def __array__(self, *args, **kwargs):

return self.get_points()

<div class="viewcode-block" id="BboxBase.is_unit"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.is_unit">[docs]</a> @cbook.deprecated("3.2")

def is_unit(self):

"""Return whether this is the unit box (from (0, 0) to (1, 1))."""

return self.get_points().tolist() == [[0., 0.], [1., 1.]]</div>

@property

def x0(self):

"""

The first of the pair of *x* coordinates that define the bounding box.

This is not guaranteed to be less than :attr:`x1` (for that, use

:attr:`xmin`).

"""

return self.get_points()[0, 0]

@property

def y0(self):

"""

The first of the pair of *y* coordinates that define the bounding box.

This is not guaranteed to be less than :attr:`y1` (for that, use

:attr:`ymin`).

"""

@property

def x1(self):

"""

The second of the pair of *x* coordinates that define the bounding box.

This is not guaranteed to be greater than :attr:`x0` (for that, use

:attr:`xmax`).

"""

return self.get_points()[1, 0]

@property

def y1(self):

"""

The second of the pair of *y* coordinates that define the bounding box.

This is not guaranteed to be greater than :attr:`y0` (for that, use

:attr:`ymax`).

"""

return self.get_points()[1, 1]

@property

def p0(self):

"""

The first pair of (*x*, *y*) coordinates that define the bounding box.

This is not guaranteed to be the bottom-left corner (for that, use

:attr:`min`).

"""

return self.get_points()[0]

@property

def p1(self):

"""

The second pair of (*x*, *y*) coordinates that define the bounding box.

This is not guaranteed to be the top-right corner (for that, use

:attr:`max`).

"""

return self.get_points()[1]

@property

def xmin(self):

"""The left edge of the bounding box."""

return np.min(self.get_points()[:, 0])

@property

def ymin(self):

"""The bottom edge of the bounding box."""

@property

def xmax(self):

"""The right edge of the bounding box."""

return np.max(self.get_points()[:, 0])

@property

def ymax(self):

"""The top edge of the bounding box."""

@property

def min(self):

"""The bottom-left corner of the bounding box."""

return np.min(self.get_points(), axis=0)

@property

def max(self):

"""The top-right corner of the bounding box."""

return np.max(self.get_points(), axis=0)

@property

def intervalx(self):

"""

The pair of *x* coordinates that define the bounding box.

This is not guaranteed to be sorted from left to right.

"""

return self.get_points()[:, 0]

@property

def intervaly(self):

"""

The pair of *y* coordinates that define the bounding box.

This is not guaranteed to be sorted from bottom to top.

"""

return self.get_points()[:, 1]

@property

def width(self):

"""The (signed) width of the bounding box."""

points = self.get_points()

return points[1, 0] - points[0, 0]

@property

def height(self):

"""The (signed) height of the bounding box."""

points = self.get_points()

return points[1, 1] - points[0, 1]

@property

def size(self):

"""The (signed) width and height of the bounding box."""

points = self.get_points()

return points[1] - points[0]

@property

def bounds(self):

"""Return (:attr:`x0`, :attr:`y0`, :attr:`width`, :attr:`height`)."""

(x0, y0), (x1, y1) = self.get_points()

return (x0, y0, x1 - x0, y1 - y0)

@property

def extents(self):

"""Return (:attr:`x0`, :attr:`y0`, :attr:`x1`, :attr:`y1`)."""

<div class="viewcode-block" id="BboxBase.get_points"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.get_points">[docs]</a> def get_points(self):

raise NotImplementedError</div>

<div class="viewcode-block" id="BboxBase.containsx"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.containsx">[docs]</a> def containsx(self, x):

"""

Return whether *x* is in the closed (:attr:`x0`, :attr:`x1`) interval.

"""

x0, x1 = self.intervalx

return x0 <= x <= x1 or x0 >= x >= x1</div>

<div class="viewcode-block" id="BboxBase.containsy"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.containsy">[docs]</a> def containsy(self, y):

"""

Return whether *y* is in the closed (:attr:`y0`, :attr:`y1`) interval.

"""

y0, y1 = self.intervaly

return y0 <= y <= y1 or y0 >= y >= y1</div>

<div class="viewcode-block" id="BboxBase.contains"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.contains">[docs]</a> def contains(self, x, y):

"""

Return whether ``(x, y)`` is in the bounding box or on its edge.

"""

return self.containsx(x) and self.containsy(y)</div>

<div class="viewcode-block" id="BboxBase.overlaps"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.overlaps">[docs]</a> def overlaps(self, other):

"""

Return whether this bounding box overlaps with the other bounding box.

Parameters

----------

other : `.BboxBase`

"""

ax1, ay1, ax2, ay2 = self.extents

bx1, by1, bx2, by2 = other.extents

if ax2 < ax1:

ax2, ax1 = ax1, ax2

if ay2 < ay1:

ay2, ay1 = ay1, ay2

if bx2 < bx1:

bx2, bx1 = bx1, bx2

if by2 < by1:

by2, by1 = by1, by2

return ax1 <= bx2 and bx1 <= ax2 and ay1 <= by2 and by1 <= ay2</div>

<div class="viewcode-block" id="BboxBase.fully_containsx"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.fully_containsx">[docs]</a> def fully_containsx(self, x):

"""

Return whether *x* is in the open (:attr:`x0`, :attr:`x1`) interval.

"""

x0, x1 = self.intervalx

return x0 < x < x1 or x0 > x > x1</div>

<div class="viewcode-block" id="BboxBase.fully_containsy"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.fully_containsy">[docs]</a> def fully_containsy(self, y):

"""

Return whether *y* is in the open (:attr:`y0`, :attr:`y1`) interval.

"""

y0, y1 = self.intervaly

return y0 < y < y1 or y0 > y > y1</div>

<div class="viewcode-block" id="BboxBase.fully_contains"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.fully_contains">[docs]</a> def fully_contains(self, x, y):

"""

Return whether ``x, y`` is in the bounding box, but not on its edge.

"""

return self.fully_containsx(x) and self.fully_containsy(y)</div>

<div class="viewcode-block" id="BboxBase.fully_overlaps"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.fully_overlaps">[docs]</a> def fully_overlaps(self, other):

"""

Return whether this bounding box overlaps with the other bounding box,

not including the edges.

Parameters

----------

other : `.BboxBase`

"""

if ax2 < ax1:

ax2, ax1 = ax1, ax2

if ay2 < ay1:

ay2, ay1 = ay1, ay2

if bx2 < bx1:

bx2, bx1 = bx1, bx2

if by2 < by1:

by2, by1 = by1, by2

return ax1 < bx2 and bx1 < ax2 and ay1 < by2 and by1 < ay2</div>

<div class="viewcode-block" id="BboxBase.transformed"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.transformed">[docs]</a> def transformed(self, transform):

"""

Construct a `Bbox` by statically transforming this one by *transform*.

"""

pts = self.get_points()

ll, ul, lr = transform.transform(np.array([pts[0],

[pts[0, 0], pts[1, 1]], [pts[1, 0], pts[0, 1]]]))

return Bbox([ll, [lr[0], ul[1]]])</div>

<div class="viewcode-block" id="BboxBase.inverse_transformed"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.inverse_transformed">[docs]</a> def inverse_transformed(self, transform):

"""

Construct a `Bbox` by statically transforming this one by the inverse

of *transform*.

"""

return self.transformed(transform.inverted())</div>

coefs = {'C': (0.5, 0.5),

'SW': (0, 0),

'S': (0.5, 0),

'SE': (1.0, 0),

'E': (1.0, 0.5),

'NE': (1.0, 1.0),

'N': (0.5, 1.0),

'NW': (0, 1.0),

'W': (0, 0.5)}

<div class="viewcode-block" id="BboxBase.anchored"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.anchored">[docs]</a> def anchored(self, c, container=None):

"""

Return a copy of the `Bbox` shifted to position *c* within *container*.

Parameters

----------

c : (float, float) or str

May be either:

* A sequence (*cx*, *cy*) where *cx* and *cy* range from 0

to 1, where 0 is left or bottom and 1 is right or top

* a string:

- 'C' for centered

- 'S' for bottom-center

- 'SE' for bottom-left

- 'E' for left

- etc.

container : Bbox, optional

The box within which the :class:`Bbox` is positioned; it defaults

to the initial :class:`Bbox`.

"""

if container is None:

container = self

l, b, w, h = container.bounds

if isinstance(c, str):

cx, cy = self.coefs[c]

else:

cx, cy = c

L, B, W, H = self.bounds

return Bbox(self._points +

[(l + cx * (w - W)) - L,

(b + cy * (h - H)) - B])</div>

<div class="viewcode-block" id="BboxBase.shrunk"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.shrunk">[docs]</a> def shrunk(self, mx, my):

"""

Return a copy of the :class:`Bbox`, shrunk by the factor *mx*

in the *x* direction and the factor *my* in the *y* direction.

The lower left corner of the box remains unchanged. Normally

*mx* and *my* will be less than 1, but this is not enforced.

"""

w, h = self.size

return Bbox([self._points[0],

self._points[0] + [mx * w, my * h]])</div>

<div class="viewcode-block" id="BboxBase.shrunk_to_aspect"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.shrunk_to_aspect">[docs]</a> def shrunk_to_aspect(self, box_aspect, container=None, fig_aspect=1.0):

"""

Return a copy of the :class:`Bbox`, shrunk so that it is as

large as it can be while having the desired aspect ratio,

*box_aspect*. If the box coordinates are relative---that

is, fractions of a larger box such as a figure---then the

physical aspect ratio of that figure is specified with

*fig_aspect*, so that *box_aspect* can also be given as a

ratio of the absolute dimensions, not the relative dimensions.

"""

if box_aspect <= 0 or fig_aspect <= 0:

raise ValueError("'box_aspect' and 'fig_aspect' must be positive")

if container is None:

container = self

w, h = container.size

H = w * box_aspect / fig_aspect

if H <= h:

W = w

else:

W = h * fig_aspect / box_aspect

H = h

self._points[0] + (W, H)])</div>

<div class="viewcode-block" id="BboxBase.splitx"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.splitx">[docs]</a> def splitx(self, *args):

"""

Return a list of new `Bbox` objects formed by splitting the original

one with vertical lines at fractional positions given by *args*.

"""

xf = [0, *args, 1]

x0, y0, x1, y1 = self.extents

w = x1 - x0

return [Bbox([[x0 + xf0 * w, y0], [x0 + xf1 * w, y1]])

for xf0, xf1 in zip(xf[:-1], xf[1:])]</div>

<div class="viewcode-block" id="BboxBase.splity"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.splity">[docs]</a> def splity(self, *args):

"""

Return a list of new `Bbox` objects formed by splitting the original

one with horizontal lines at fractional positions given by *args*.

"""

yf = [0, *args, 1]

h = y1 - y0

return [Bbox([[x0, y0 + yf0 * h], [x1, y0 + yf1 * h]])

for yf0, yf1 in zip(yf[:-1], yf[1:])]</div>

<div class="viewcode-block" id="BboxBase.count_contains"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.count_contains">[docs]</a> def count_contains(self, vertices):

"""

Count the number of vertices contained in the :class:`Bbox`.

Any vertices with a non-finite x or y value are ignored.

Parameters

----------

vertices : Nx2 Numpy array.

"""

if len(vertices) == 0:

return 0

vertices = np.asarray(vertices)

with np.errstate(invalid='ignore'):

return (((self.min < vertices) &

(vertices < self.max)).all(axis=1).sum())</div>

<div class="viewcode-block" id="BboxBase.count_overlaps"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.count_overlaps">[docs]</a> def count_overlaps(self, bboxes):

"""

Count the number of bounding boxes that overlap this one.

Parameters

----------

bboxes : sequence of `.BboxBase`

"""

return count_bboxes_overlapping_bbox(

self, np.atleast_3d([np.array(x) for x in bboxes]))</div>

<div class="viewcode-block" id="BboxBase.expanded"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.expanded">[docs]</a> def expanded(self, sw, sh):

"""

Construct a `Bbox` by expanding this one around its center by the

factors *sw* and *sh*.

"""

width = self.width

height = self.height

deltaw = (sw * width - width) / 2.0

deltah = (sh * height - height) / 2.0

a = np.array([[-deltaw, -deltah], [deltaw, deltah]])

return Bbox(self._points + a)</div>

<div class="viewcode-block" id="BboxBase.padded"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.padded">[docs]</a> def padded(self, p):

"""Construct a `Bbox` by padding this one on all four sides by *p*."""

points = self.get_points()

return Bbox(points + [[-p, -p], [p, p]])</div>

<div class="viewcode-block" id="BboxBase.translated"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.translated">[docs]</a> def translated(self, tx, ty):

"""Construct a `Bbox` by translating this one by *tx* and *ty*."""

<div class="viewcode-block" id="BboxBase.corners"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.corners">[docs]</a> def corners(self):

"""

Return the corners of this rectangle as an array of points.

Specifically, this returns the array

``[[x0, y0], [x0, y1], [x1, y0], [x1, y1]]``.

"""

return np.array([[x0, y0], [x0, y1], [x1, y0], [x1, y1]])</div>

<div class="viewcode-block" id="BboxBase.rotated"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.rotated">[docs]</a> def rotated(self, radians):

"""

Return a new bounding box that bounds a rotated version of

this bounding box by the given radians. The new bounding box

is still aligned with the axes, of course.

"""

corners = self.corners()

corners_rotated = Affine2D().rotate(radians).transform(corners)

bbox = Bbox.unit()

bbox.update_from_data_xy(corners_rotated, ignore=True)

return bbox</div>

<div class="viewcode-block" id="BboxBase.union"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.union">[docs]</a> @staticmethod

def union(bboxes):

"""Return a `Bbox` that contains all of the given *bboxes*."""

if not len(bboxes):

raise ValueError("'bboxes' cannot be empty")

# needed for 1.14.4 < numpy_version < 1.15

# can remove once we are at numpy >= 1.15

x0 = np.min([bbox.xmin for bbox in bboxes])

x1 = np.max([bbox.xmax for bbox in bboxes])

y0 = np.min([bbox.ymin for bbox in bboxes])

y1 = np.max([bbox.ymax for bbox in bboxes])

<div class="viewcode-block" id="BboxBase.intersection"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.BboxBase.intersection">[docs]</a> @staticmethod

def intersection(bbox1, bbox2):

"""

Return the intersection of *bbox1* and *bbox2* if they intersect, or

None if they don't.

"""

x0 = np.maximum(bbox1.xmin, bbox2.xmin)

x1 = np.minimum(bbox1.xmax, bbox2.xmax)

y0 = np.maximum(bbox1.ymin, bbox2.ymin)

y1 = np.minimum(bbox1.ymax, bbox2.ymax)

return Bbox([[x0, y0], [x1, y1]]) if x0 <= x1 and y0 <= y1 else None</div></div>

<div class="viewcode-block" id="Bbox"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox">[docs]</a>class Bbox(BboxBase):

"""

A mutable bounding box.

"""

def __init__(self, points, **kwargs):

"""

Parameters

----------

points : ndarray

A 2x2 numpy array of the form ``[[x0, y0], [x1, y1]]``.

Notes

-----

If you need to create a :class:`Bbox` object from another form

of data, consider the static methods :meth:`unit`,

:meth:`from_bounds` and :meth:`from_extents`.

"""

BboxBase.__init__(self, **kwargs)

if points.shape != (2, 2):

raise ValueError('Bbox points must be of the form '

'"[[x0, y0], [x1, y1]]".')

self._points = points

self._minpos = np.array([np.inf, np.inf])

self._ignore = True

# it is helpful in some contexts to know if the bbox is a

# default or has been mutated; we store the orig points to

# support the mutated methods

self._points_orig = self._points.copy()

if DEBUG:

___init__ = __init__

self._check(points)

self.___init__(points, **kwargs)

def invalidate(self):

self._check(self._points)

TransformNode.invalidate(self)

<div class="viewcode-block" id="Bbox.unit"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox.unit">[docs]</a> @staticmethod

def unit():

"""Create a new unit `Bbox` from (0, 0) to (1, 1)."""

<div class="viewcode-block" id="Bbox.null"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox.null">[docs]</a> @staticmethod

def null():

"""Create a new null `Bbox` from (inf, inf) to (-inf, -inf)."""

return Bbox(np.array([[np.inf, np.inf], [-np.inf, -np.inf]], float))</div>

<div class="viewcode-block" id="Bbox.from_bounds"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox.from_bounds">[docs]</a> @staticmethod

def from_bounds(x0, y0, width, height):

"""

Create a new `Bbox` from *x0*, *y0*, *width* and *height*.

*width* and *height* may be negative.

"""

return Bbox.from_extents(x0, y0, x0 + width, y0 + height)</div>

<div class="viewcode-block" id="Bbox.from_extents"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox.from_extents">[docs]</a> @staticmethod

def from_extents(*args):

"""

Create a new Bbox from *left*, *bottom*, *right* and *top*.

The *y*-axis increases upwards.

"""

points = np.array(args, dtype=float).reshape(2, 2)

return Bbox(points)</div>

def __format__(self, fmt):

return (

'Bbox(x0={0.x0:{1}}, y0={0.y0:{1}}, x1={0.x1:{1}}, y1={0.y1:{1}})'.

format(self, fmt))

def __str__(self):

return format(self, '')

def __repr__(self):

return 'Bbox([[{0.x0}, {0.y0}], [{0.x1}, {0.y1}]])'.format(self)

<div class="viewcode-block" id="Bbox.ignore"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox.ignore">[docs]</a> def ignore(self, value):

"""

Set whether the existing bounds of the box should be ignored

by subsequent calls to :meth:`update_from_data_xy`.

value : bool

- When ``True``, subsequent calls to :meth:`update_from_data_xy`

will ignore the existing bounds of the :class:`Bbox`.

- When ``False``, subsequent calls to :meth:`update_from_data_xy`

will include the existing bounds of the :class:`Bbox`.

"""

self._ignore = value</div>

<div class="viewcode-block" id="Bbox.update_from_path"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox.update_from_path">[docs]</a> def update_from_path(self, path, ignore=None, updatex=True, updatey=True):

"""

Update the bounds of the :class:`Bbox` based on the passed in

data. After updating, the bounds will have positive *width*

and *height*; *x0* and *y0* will be the minimal values.

Parameters

----------

path : :class:`~matplotlib.path.Path`

ignore : bool, optional

- when ``True``, ignore the existing bounds of the :class:`Bbox`.

- when ``False``, include the existing bounds of the :class:`Bbox`.

- when ``None``, use the last value passed to :meth:`ignore`.

updatex, updatey : bool, optional

When ``True``, update the x/y values.

"""

if ignore is None:

ignore = self._ignore

if path.vertices.size == 0:

return

points, minpos, changed = update_path_extents(

path, None, self._points, self._minpos, ignore)

if changed:

self.invalidate()

if updatex:

self._points[:, 0] = points[:, 0]

self._minpos[0] = minpos[0]

if updatey:

self._points[:, 1] = points[:, 1]

self._minpos[1] = minpos[1]</div>

<div class="viewcode-block" id="Bbox.update_from_data_xy"><a class="viewcode-back" href="../../api/transformations.html#matplotlib.transforms.Bbox.update_from_data_xy">[docs]</a> def update_from_data_xy(self, xy, ignore=None, updatex=True, updatey=True):

"""

Update the bounds of the :class:`Bbox` based on the passed in

data. After updating, the bounds will have positive *width*

and *height*; *x0* and *y0* will be the minimal values.

Parameters

----------

xy : ndarray

A numpy array of 2D points.

ignore : bool, optional

- When ``True``, ignore the existing bounds of the :class:`Bbox`.

- When ``False``, include the existing bounds of the :class:`Bbox`.

- When ``None``, use the last value passed to :meth:`ignore`.

updatex, updatey : bool, optional

When ``True``, update the x/y values.

"""

if len(xy) == 0:

return

path = Path(xy)

self.update_from_path(path, ignore=ignore,

updatex=updatex, updatey=updatey)</div>

@BboxBase.x0.setter

def x0(self, val):

self._points[0, 0] = val

self.invalidate()

@BboxBase.y0.setter

def y0(self, val):

self._points[0, 1] = val

self.invalidate()

@BboxBase.x1.setter

def x1(self, val):

self._points[1, 0] = val

self.invalidate()

@BboxBase.y1.setter

def y1(self, val):

self._points[1, 1] = val

self.invalidate()

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