Source code for pymor.grids.unstructured

# This file is part of the pyMOR project (
# Copyright 2013-2019 pyMOR developers and contributors. All rights reserved.
# License: BSD 2-Clause License (

import numpy as np

from pymor.grids.interfaces import AffineGridInterface
from pymor.grids.referenceelements import triangle
from pymor.grids._unstructured import compute_edges

[docs]class UnstructuredTriangleGrid(AffineGridInterface): """A generic unstructured, triangular grid. Use :meth:`~UnstructuredTriangleGrid.from_vertices` to instantiate the grid from vertex coordinates and connectivity data. """ dim = 2 reference_element = triangle def __init__(self, sizes, subentity_data, embedding_data): self.__auto_init(locals()) vertices = self.centers(2) self.domain = np.array([[np.min(vertices[:, 0]), np.min(vertices[:, 1])], [np.max(vertices[:, 0]), np.max(vertices[:, 1])]])
[docs] @classmethod def from_vertices(cls, vertices, faces): """Instantiate grid from vertex coordinates and connectivity data. Parameters ---------- vertices A (num_vertices, 2)-shaped |array| containing the coordinates of all vertices in the grid. The row numbers in the array will be the global indices of the given vertices (codim 2 entities). faces A (num_faces, 3)-shaped |array| containing the global indices of the vertices which define a given triangle in the grid. The row numbers in the array will be the global indices of the given triangles (codim 0 entities). """ assert faces.shape[1] == 3 assert np.min(faces) == 0 assert np.max(faces) == len(vertices) - 1 vertices = vertices.astype(np.float64, copy=False) faces = faces.astype(np.int32, copy=False) edges, num_edges = compute_edges(faces, len(vertices)) COORDS = vertices[faces] SHIFTS = COORDS[:, 0, :] TRANS = COORDS[:, 1:, :] - SHIFTS[:, np.newaxis, :] TRANS = TRANS.swapaxes(1, 2) sizes = (len(faces), num_edges, len(vertices)) subentity_data = (np.arange(len(faces), dtype=np.int32).reshape(-1, 1), edges, faces) embedding_data = (TRANS, SHIFTS) return cls(sizes, subentity_data, embedding_data)
[docs] def size(self, codim=0): assert 0 <= codim <= 2, 'Invalid codimension' return self.sizes[codim]
[docs] def subentities(self, codim=0, subentity_codim=None): assert 0 <= codim <= 2, 'Invalid codimension' if subentity_codim is None: subentity_codim = codim + 1 assert codim <= subentity_codim <= self.dim, 'Invalid subentity codimensoin' if codim == 0: return self.subentity_data[subentity_codim] else: return super().subentities(codim, subentity_codim)
[docs] def embeddings(self, codim=0): if codim == 0: return self.embedding_data else: return super().embeddings(codim)
[docs] def visualize(self, U, codim=2, **kwargs): """Visualize scalar data associated to the grid as a patch plot. Parameters ---------- U |NumPy array| of the data to visualize. If `U.dim == 2 and len(U) > 1`, the data is visualized as a time series of plots. Alternatively, a tuple of |Numpy arrays| can be provided, in which case a subplot is created for each entry of the tuple. The lengths of all arrays have to agree. codim The codimension of the entities the data in `U` is attached to (either 0 or 2). kwargs See :func:`~pymor.gui.qt.visualize_patch` """ from pymor.gui.qt import visualize_patch from pymor.vectorarrays.interfaces import VectorArrayInterface from pymor.vectorarrays.numpy import NumpyVectorSpace, NumpyVectorArray if isinstance(U, (np.ndarray, VectorArrayInterface)): U = (U,) assert all(isinstance(u, (np.ndarray, VectorArrayInterface)) for u in U) U = tuple(NumpyVectorSpace.make_array(u) if isinstance(u, np.ndarray) else u if isinstance(u, NumpyVectorArray) else NumpyVectorSpace.make_array(u.to_numpy()) for u in U) bounding_box = kwargs.pop('bounding_box', self.domain) visualize_patch(self, U, codim=codim, bounding_box=bounding_box, **kwargs)
[docs] def __str__(self): return 'UnstructuredTriangleGrid with {} triangles, {} edges, {} vertices'.format(*self.sizes)