| | import numpy as np |
| |
|
| | from matplotlib import _api |
| | from matplotlib.tri import Triangulation |
| |
|
| |
|
| | 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 `.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): |
| | _api.check_isinstance(Triangulation, triangulation=triangulation) |
| | self._triangulation = triangulation |
| |
|
| |
|
| | class TrapezoidMapTriFinder(TriFinder): |
| | """ |
| | `~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 |
| | super().__init__(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") |
| |
|
| | |
| | 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() |
| |
|
