Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/matplotlib/tri/trifinder.py

@@ -0,0 +1,93 @@
+import numpy as np
+
+from matplotlib import cbook
+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):
+        cbook._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
+        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()