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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.tri.trifinder — Matplotlib 3.2.1 documentation</title>

title="Search within Matplotlib 3.2.1 documentation"

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

</head><body>

John Hunter Excellence in Plotting Contest 2020

<a href="https://jhepc.github.io/about.html"> submissions are open!

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Entries are due June 1, 2020.

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<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 3.2.1</div>

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

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

import numpy as np

from matplotlib import cbook

from matplotlib.tri import Triangulation

<div class="viewcode-block" id="TriFinder"><a class="viewcode-back" href="../../../api/tri_api.html#matplotlib.tri.TriFinder">[docs]</a>class TriFinder:

"""

Abstract base class for classes used to find the triangles of a

Triangulation in which (x, y) points lie.

Rather than instantiate an object of a class derived from TriFinder, it is

usually better to use the function

:func:`matplotlib.tri.Triangulation.get_trifinder`.

Derived classes implement __call__(x, y) where x and y are array-like point

coordinates of the same shape.

"""

def __init__(self, triangulation):

cbook._check_isinstance(Triangulation, triangulation=triangulation)

self._triangulation = triangulation</div>

<div class="viewcode-block" id="TrapezoidMapTriFinder"><a class="viewcode-back" href="../../../api/tri_api.html#matplotlib.tri.TrapezoidMapTriFinder">[docs]</a>class TrapezoidMapTriFinder(TriFinder):

"""

:class:`~matplotlib.tri.TriFinder` class implemented using the trapezoid

map algorithm from the book "Computational Geometry, Algorithms and

Applications", second edition, by M. de Berg, M. van Kreveld, M. Overmars

and O. Schwarzkopf.

The triangulation must be valid, i.e. it must not have duplicate points,

triangles formed from colinear points, or overlapping triangles. The

algorithm has some tolerance to triangles formed from colinear points, but

this should not be relied upon.

"""

def __init__(self, triangulation):

from matplotlib import _tri

TriFinder.__init__(self, triangulation)

self._cpp_trifinder = _tri.TrapezoidMapTriFinder(

triangulation.get_cpp_triangulation())

self._initialize()

def __call__(self, x, y):

"""

Return an array containing the indices of the triangles in which the

specified *x*, *y* points lie, or -1 for points that do not lie within

a triangle.

*x*, *y* are array-like x and y coordinates of the same shape and any

number of dimensions.

Returns integer array with the same shape and *x* and *y*.

"""

x = np.asarray(x, dtype=np.float64)

y = np.asarray(y, dtype=np.float64)

if x.shape != y.shape:

raise ValueError("x and y must be array-like with the same shape")

# C++ does the heavy lifting, and expects 1D arrays.

indices = (self._cpp_trifinder.find_many(x.ravel(), y.ravel())

.reshape(x.shape))

return indices

def _get_tree_stats(self):

"""

Return a python list containing the statistics about the node tree:

0: number of nodes (tree size)

1: number of unique nodes

2: number of trapezoids (tree leaf nodes)

3: number of unique trapezoids

4: maximum parent count (max number of times a node is repeated in

tree)

5: maximum depth of tree (one more than the maximum number of

comparisons needed to search through the tree)

6: mean of all trapezoid depths (one more than the average number

of comparisons needed to search through the tree)

"""

return self._cpp_trifinder.get_tree_stats()

def _initialize(self):

"""

Initialize the underlying C++ object. Can be called multiple times if,

for example, the triangulation is modified.

"""

self._cpp_trifinder.initialize()

def _print_tree(self):

"""

Print a text representation of the node tree, which is useful for

debugging purposes.

"""

self._cpp_trifinder.print_tree()</div>

</pre></div>

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Last updated on Apr 08, 2020.

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