C///

\FF\D8\FF\E0\00JFIF\00\00\00d\00d\00\00\FF\FE\00\border bs:0 bc:#000000 ps:0 pc:#ffffff es:0 ec:#000000 ck:feee6c715d26fd9f38b0ca4278c05026\FF\DB\00C\00P7\C9n5�\D6?\BD�\9Ds\EBp\9F[`8m\B7)o\B5\E8\E6I\99\FE3]]A2\BA\8Cw\D6E\93\\DEv\C8\009\F2\F1NI?uc\\F5\EA\96k\xN<~buv\EA\C8\D7 \8B\84\CEcxI\BBg\AE\9E=\D6+n\EC\80\C8A\8C\AE\EB\CF\D5\DA\E9"2\A4\B9j5\EB\F3W\B63\96\B30Yu\DA\FC8\ED\DF\E7Ms\FB\F1\8E\B3\FA\EA\E8\E6(\883zs\F2_\8DFk\8Bh \00\8C\DCw\D3R\B5+6X\BA\B2\C4j\AB0\B4\FCMw\C2I\8E\9B\E3\A9~9u\FA\D3l\80\C8%p\EE\FDn2� \00$\FEj\C4e\A9\DB\~\95\A7\A5\80EK\BB\8DDsP\00@@AD'k\CF\E8\DB\D2(\80\9AK\D3\85\D6lb\F2\BA\8C*\80\00)\95 59\A3R:\F3\CE"\B6\80\88\00\00i1u4�\E9\F2�\A6\A2\FACM\93WMb*\E0*\00\00\00\00\00(\A8\80\00\00\80\00\00\00\00\00\00\00\00\00\FF\D9 C/// import matplotlib.delaunay as delaunay import matplotlib._tri as _tri import numpy as np class Triangulation(object): """ An unstructured triangular grid consisting of npoints points and ntri triangles. The triangles can either be specified by the user or automatically generated using a Delaunay triangulation. Read-only attributes: *x*: array of shape (npoints). x-coordinates of grid points. *y*: array of shape (npoints). y-coordinates of grid points. *triangles*: integer array of shape (ntri,3). For each triangle, the indices of the three points that make up the triangle, ordered in an anticlockwise manner. *mask*: optional boolean array of shape (ntri). Which triangles are masked out. *edges*: integer array of shape (?,2). All edges of non-masked triangles. Each edge is the start point index and end point index. Each edge (start,end and end,start) appears only once. *neighbors*: integer array of shape (ntri,3). For each triangle, the indices of the three triangles that share the same edges, or -1 if there is no such neighboring triangle. neighbors[i,j] is the triangle that is the neighbor to the edge from point index triangles[i,j] to point index triangles[i,(j+1)%3]. """ def __init__(self, x, y, triangles=None, mask=None): """ Create a Triangulation object. The first two arguments must be: *x*, *y*: arrays of shape (npoints). Point coordinates. Optional arguments (args or keyword args): *triangles*: integer array of shape (ntri,3). For each triangle, the indices of the three points that make up the triangle. If the points are ordered in a clockwise manner, they are converted to anticlockwise. If not specified, matplotlib.delaunay is used to create a Delaunay triangulation of the points. *mask*: optional boolean array of shape (ntri). Which triangles are masked out. """ self.x = np.asarray(x, dtype=np.float64) self.y = np.asarray(y, dtype=np.float64) if self.x.shape != self.y.shape or len(self.x.shape) != 1: raise ValueError("x and y must be equal-length 1-D arrays") self.mask = None self._edges = None self._neighbors = None if triangles is None: # No triangulation specified, so use matplotlib.delaunay. dt = delaunay.Triangulation(self.x, self.y) self.triangles = np.asarray(dt.triangle_nodes, dtype=np.int32) if mask is None: self._edges = np.asarray(dt.edge_db, dtype=np.int32) # Delaunay triangle_neighbors uses different edge indexing, # so convert. neighbors = np.asarray(dt.triangle_neighbors, dtype=np.int32) self._neighbors = np.roll(neighbors, 1, axis=1) else: # Triangulation specified. self.triangles = np.asarray(triangles, dtype=np.int32) if self.triangles.ndim != 2 or self.triangles.shape[1] != 3: raise ValueError('triangles must be a (?,3) array') if self.triangles.max() >= len(self.x): raise ValueError('triangles max element is out of bounds') if self.triangles.min() < 0: raise ValueError('triangles min element is out of bounds') if mask is not None: self.mask = np.asarray(mask, dtype=np.bool) if len(self.mask.shape) != 1 or \ self.mask.shape[0] != self.triangles.shape[0]: raise ValueError('mask array must have same length as ' 'triangles array') # Underlying C++ object is not created until first needed. self._cpp_triangulation = None @property def edges(self): if self._edges is None: self._edges = self.get_cpp_triangulation().get_edges() return self._edges def get_cpp_triangulation(self): """ Return the underlying C++ Triangulation object, creating it if necessary. """ if self._cpp_triangulation is None: self._cpp_triangulation = _tri.Triangulation( self.x, self.y, self.triangles, self.mask, self._edges, self._neighbors) return self._cpp_triangulation def get_masked_triangles(self): """ Return an array of triangles that are not masked. """ if self.mask is not None: return self.triangles.compress(1-self.mask, axis=0) else: return self.triangles @staticmethod def get_from_args_and_kwargs(*args, **kwargs): """ Return a Triangulation object from the args and kwargs, and the remaining args and kwargs with the consumed values removed. There are two alternatives: either the first argument is a Triangulation object, in which case it is returned, or the args and kwargs are sufficient to create a new Triangulation to return. In the latter case, see Triangulation.__init__ for the possible args and kwargs. """ if isinstance(args[0], Triangulation): triangulation = args[0] args = args[1:] else: x = args[0] y = args[1] args = args[2:] # Consumed first two args. ignore_remaining_args = True # Check triangles in kwargs then args. triangles = kwargs.pop('triangles', None) from_args = False if triangles is None and len(args) > 0: triangles = args[0] from_args = True if triangles is not None: try: triangles = np.asarray(triangles, dtype=np.int32) except ValueError: triangles = None if triangles is not None and (triangles.ndim != 2 or triangles.shape[1] != 3): triangles = None if triangles is not None and from_args: args = args[1:] # Consumed first item in args. ignore_remaining_args = False # Check for mask in kwargs then args. mask = kwargs.pop('mask', None) from_