`~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
| 25 | |
| 26 | |
| 27 | class TrapezoidMapTriFinder(TriFinder): |
| 28 | """ |
| 29 | `~matplotlib.tri.TriFinder` class implemented using the trapezoid |
| 30 | map algorithm from the book "Computational Geometry, Algorithms and |
| 31 | Applications", second edition, by M. de Berg, M. van Kreveld, M. Overmars |
| 32 | and O. Schwarzkopf. |
| 33 | |
| 34 | The triangulation must be valid, i.e. it must not have duplicate points, |
| 35 | triangles formed from colinear points, or overlapping triangles. The |
| 36 | algorithm has some tolerance to triangles formed from colinear points, but |
| 37 | this should not be relied upon. |
| 38 | """ |
| 39 | |
| 40 | def __init__(self, triangulation): |
| 41 | from matplotlib import _tri |
| 42 | super().__init__(triangulation) |
| 43 | self._cpp_trifinder = _tri.TrapezoidMapTriFinder( |
| 44 | triangulation.get_cpp_triangulation()) |
| 45 | self._initialize() |
| 46 | |
| 47 | def __call__(self, x, y): |
| 48 | """ |
| 49 | Return an array containing the indices of the triangles in which the |
| 50 | specified *x*, *y* points lie, or -1 for points that do not lie within |
| 51 | a triangle. |
| 52 | |
| 53 | *x*, *y* are array-like x and y coordinates of the same shape and any |
| 54 | number of dimensions. |
| 55 | |
| 56 | Returns integer array with the same shape and *x* and *y*. |
| 57 | """ |
| 58 | x = np.asarray(x, dtype=np.float64) |
| 59 | y = np.asarray(y, dtype=np.float64) |
| 60 | if x.shape != y.shape: |
| 61 | raise ValueError("x and y must be array-like with the same shape") |
| 62 | |
| 63 | # C++ does the heavy lifting, and expects 1D arrays. |
| 64 | indices = (self._cpp_trifinder.find_many(x.ravel(), y.ravel()) |
| 65 | .reshape(x.shape)) |
| 66 | return indices |
| 67 | |
| 68 | def _get_tree_stats(self): |
| 69 | """ |
| 70 | Return a python list containing the statistics about the node tree: |
| 71 | 0: number of nodes (tree size) |
| 72 | 1: number of unique nodes |
| 73 | 2: number of trapezoids (tree leaf nodes) |
| 74 | 3: number of unique trapezoids |
| 75 | 4: maximum parent count (max number of times a node is repeated in |
| 76 | tree) |
| 77 | 5: maximum depth of tree (one more than the maximum number of |
| 78 | comparisons needed to search through the tree) |
| 79 | 6: mean of all trapezoid depths (one more than the average number |
| 80 | of comparisons needed to search through the tree) |
| 81 | """ |
| 82 | return self._cpp_trifinder.get_tree_stats() |
| 83 | |
| 84 | def _initialize(self): |
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