| 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 |
|
|
| def __call__(self, x, y): |
| raise NotImplementedError |
|
|
|
|
| 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() |
|
|
