def __init__(self, dx = 1., dy = 1., nx = 1, ny = 1, _RepresentationClass=_Grid2DRepresentation, _TopologyClass=_Mesh2DTopology): """ Creates a 2D triangular mesh with horizontal faces numbered first then vertical faces, then diagonal faces. Vertices are numbered starting with the vertices at the corners of boxes and then the vertices at the centers of boxes. Cells on the right of boxes are numbered first, then cells on the top of boxes, then cells on the left of boxes, then cells on the bottom of boxes. Within each of the 'sub-categories' in the above, the vertices, cells and faces are numbered in the usual way. :Parameters: - `dx, dy`: The X and Y dimensions of each 'box'. If `dx` <> `dy`, the line segments connecting the cell centers will not be orthogonal to the faces. - `nx, ny`: The number of boxes in the X direction and the Y direction. The total number of boxes will be equal to `nx * ny`, and the total number of cells will be equal to `4 * nx * ny`. """ self.args = { 'dx': dx, 'dy': dy, 'nx': nx, 'ny': ny } self.nx = nx self.ny = ny self.numberOfHorizontalFaces = self.nx * (self.ny + 1) self.numberOfVerticalFaces = self.ny * (self.nx + 1) self.numberOfEachDiagonalFaces = self.nx * self.ny self.dx = PhysicalField(value = dx) scale = PhysicalField(value = 1, unit = self.dx.unit) self.dx /= scale self.dy = PhysicalField(value = dy) if self.dy.unit.isDimensionless(): self.dy = dy else: self.dy /= scale self.numberOfCornerVertices = (self.nx + 1) * (self. ny + 1) self.numberOfCenterVertices = self.nx * self.ny self.numberOfTotalVertices = self.numberOfCornerVertices + self.numberOfCenterVertices self.offset = (0, 0) vertices = self._createVertices() faces = self._createFaces() cells = self._createCells() cells = numerix.sort(cells, axis=0) Mesh2D.__init__(self, vertices, faces, cells, _RepresentationClass=_RepresentationClass, _TopologyClass=_TopologyClass) self.scale = scale
def _calcValue(self): l = len(self.distribution) bins = self.mesh.cellCenters[0] n = numerix.searchsorted(numerix.sort(self.distribution), bins) n = numerix.concatenate([n, [l]]) dx = bins[1:] - bins[:-1] return (n[1:] - n[:-1]) / numerix.concatenate([dx, [dx[-1]]]) / float(l)
def _calcBaseFaceVertexIDs(self): cellVertexIDs = self.cellVertexIDs ## compute the face vertex IDs. ### this assumes triangular grid #cellFaceVertexIDs = numerix.ones((self.dimensions, self.dimensions + 1, self.numCells)) cellFaceVertexIDs = numerix.ones((self.dimensions,len(cellVertexIDs), self.numCells)) cellFaceVertexIDs = -1 * cellFaceVertexIDs if (self.dimensions == 3): cellFaceVertexIDs[:, 0, :] = cellVertexIDs[:3] cellFaceVertexIDs[:, 1, :] = numerix.concatenate((cellVertexIDs[:2], cellVertexIDs[3:]), axis = 0) cellFaceVertexIDs[:, 2, :] = numerix.concatenate((cellVertexIDs[:1], cellVertexIDs[2:]), axis = 0) cellFaceVertexIDs[:, 3, :] = cellVertexIDs[1:] elif (self.dimensions == 2):#define face with vertex pairs ###This isn't very general. ###Would be nice to allow cells with different number of faces. if len(cellVertexIDs)==3: cellFaceVertexIDs[:, 0, :] = cellVertexIDs[:2] cellFaceVertexIDs[:, 1, :] = numerix.concatenate((cellVertexIDs[2:], cellVertexIDs[:1]), axis = 0) cellFaceVertexIDs[:, 2, :] = cellVertexIDs[1:] elif len(cellVertexIDs)==4: cellFaceVertexIDs[:, 0, :] = cellVertexIDs[0:2] cellFaceVertexIDs[:, 1, :] = cellVertexIDs[1:3] cellFaceVertexIDs[:, 2, :] = cellVertexIDs[2:4] cellFaceVertexIDs[:, 3, :] = numerix.concatenate((cellVertexIDs[3:], cellVertexIDs[:1]), axis = 0) cellFaceVertexIDs = cellFaceVertexIDs[::-1]#reverses order of vertex pair #self.unsortedBaseIDs = numerix.reshape(cellFaceVertexIDs.swapaxes(1,2), # (self.dimensions, # self.numCells * (self.dimensions + 1))) self.unsortedBaseIDs = numerix.reshape(cellFaceVertexIDs.swapaxes(1,2), (self.dimensions, self.numCells * (len(cellVertexIDs)))) cellFaceVertexIDs = numerix.sort(cellFaceVertexIDs, axis=0) baseFaceVertexIDs = numerix.reshape(cellFaceVertexIDs.swapaxes(1,2), (self.dimensions, self.numCells * (len(cellVertexIDs)))) self.baseFaceVertexIDs = baseFaceVertexIDs self.cellFaceVertexIDs = cellFaceVertexIDs
def _getAddedMeshValues(self, other, resolution=1e-2): """Calculate the parameters to define a concatenation of `other` with `self` Parameters ---------- other : ~fipy.meshes.mesh.Mesh The `Mesh` to concatenate with `self` resolution : float How close vertices have to be (relative to the smallest cell-to-cell distance in either mesh) to be considered the same Returns ------- dict (`vertexCoords`, `faceVertexIDs`, `cellFaceIDs`) for the new mesh. """ selfc = self._concatenableMesh otherc = other._concatenableMesh selfNumFaces = selfc.faceVertexIDs.shape[-1] selfNumVertices = selfc.vertexCoords.shape[-1] otherNumFaces = otherc.faceVertexIDs.shape[-1] otherNumVertices = otherc.vertexCoords.shape[-1] ## check dimensions if(selfc.vertexCoords.shape[0] != otherc.vertexCoords.shape[0]): raise MeshAdditionError("Dimensions do not match") ## compute vertex correlates # from fipy.tools.debug import PRINT # PRINT("selfNumFaces", selfNumFaces) # PRINT("otherNumFaces", otherNumVertices) # PRINT("selfNumVertices", selfNumVertices) # PRINT("otherNumVertices", otherNumVertices) # # from fipy.tools.debug import PRINT # from fipy.tools.debug import PRINT # PRINT("otherExt", otherc.exteriorFaces.value) # raw_input() # PRINT("selfExt", selfc.exteriorFaces.value) # # PRINT("self filled", selfc.faceVertexIDs.filled()) # PRINT("othe filled", otherc.faceVertexIDs.filled()) # raw_input() # # PRINT("selfc.faceVertexIDs.filled()\n",selfc.faceVertexIDs.filled()) # PRINT("flat\n",selfc.faceVertexIDs.filled()[..., # selfc.exteriorFaces.value].flatten()) # PRINT("selfc.exteriorFaces.value\n",selfc.exteriorFaces.value) # PRINT("extfaces type", type(selfc.exteriorFaces)) # PRINT("extfaces mesh", selfc.exteriorFaces.mesh) ## only try to match along the operation manifold if hasattr(self, "opManifold"): self_faces = self.opManifold(selfc) else: self_faces = selfc.exteriorFaces.value if hasattr(other, "opManifold"): other_faces = other.opManifold(otherc) else: other_faces = otherc.exteriorFaces.value ## only try to match exterior (X) vertices self_Xvertices = numerix.unique(selfc.faceVertexIDs.filled()[..., self_faces].flatten()) other_Xvertices = numerix.unique(otherc.faceVertexIDs.filled()[..., other_faces].flatten()) self_XvertexCoords = selfc.vertexCoords[..., self_Xvertices] other_XvertexCoords = otherc.vertexCoords[..., other_Xvertices] closest = numerix.nearest(self_XvertexCoords, other_XvertexCoords) # just because they're closest, doesn't mean they're close tmp = self_XvertexCoords[..., closest] - other_XvertexCoords distance = numerix.sqrtDot(tmp, tmp) # only want vertex pairs that are 100x closer than the smallest # cell-to-cell distance close = distance < resolution * min(selfc._cellToCellDistances.min(), otherc._cellToCellDistances.min()) vertexCorrelates = numerix.array((self_Xvertices[closest[close]], other_Xvertices[close])) # warn if meshes don't touch, but allow it if (selfc._numberOfVertices > 0 and otherc._numberOfVertices > 0 and vertexCorrelates.shape[-1] == 0): import warnings warnings.warn("Vertices are not aligned", UserWarning, stacklevel=4) ## compute face correlates # ensure that both sets of faceVertexIDs have the same maximum number of (masked) elements self_faceVertexIDs = selfc.faceVertexIDs other_faceVertexIDs = otherc.faceVertexIDs diff = self_faceVertexIDs.shape[0] - other_faceVertexIDs.shape[0] if diff > 0: other_faceVertexIDs = numerix.append(other_faceVertexIDs, -1 * numerix.ones((diff,) + other_faceVertexIDs.shape[1:], 'l'), axis=0) other_faceVertexIDs = MA.masked_values(other_faceVertexIDs, -1) elif diff < 0: self_faceVertexIDs = numerix.append(self_faceVertexIDs, -1 * numerix.ones((-diff,) + self_faceVertexIDs.shape[1:], 'l'), axis=0) self_faceVertexIDs = MA.masked_values(self_faceVertexIDs, -1) # want self's Faces for which all faceVertexIDs are in vertexCorrelates self_matchingFaces = numerix.in1d(self_faceVertexIDs, vertexCorrelates[0]).reshape(self_faceVertexIDs.shape).all(axis=0).nonzero()[0] # want other's Faces for which all faceVertexIDs are in vertexCorrelates other_matchingFaces = numerix.in1d(other_faceVertexIDs, vertexCorrelates[1]).reshape(other_faceVertexIDs.shape).all(axis=0).nonzero()[0] # map other's Vertex IDs to new Vertex IDs, # accounting for overlaps with self's Vertex IDs vertex_map = numerix.empty(otherNumVertices, dtype=numerix.INT_DTYPE) verticesToAdd = numerix.delete(numerix.arange(otherNumVertices), vertexCorrelates[1]) vertex_map[verticesToAdd] = numerix.arange(otherNumVertices - len(vertexCorrelates[1])) + selfNumVertices vertex_map[vertexCorrelates[1]] = vertexCorrelates[0] # calculate hashes of faceVertexIDs for comparing Faces if self_matchingFaces.shape[-1] == 0: self_faceHash = numerix.empty(self_matchingFaces.shape[:-1] + (0,), dtype="str") else: # sort each of self's Face's vertexIDs for canonical comparison self_faceHash = numerix.sort(self_faceVertexIDs[..., self_matchingFaces], axis=0) # then hash the Faces for comparison (NumPy set operations are only for 1D arrays) self_faceHash = numerix.apply_along_axis(str, axis=0, arr=self_faceHash) face_sort = numerix.argsort(self_faceHash) self_faceHash = self_faceHash[face_sort] self_matchingFaces = self_matchingFaces[face_sort] if other_matchingFaces.shape[-1] == 0: other_faceHash = numerix.empty(other_matchingFaces.shape[:-1] + (0,), dtype="str") else: # convert each of other's Face's vertexIDs to new IDs other_faceHash = vertex_map[other_faceVertexIDs[..., other_matchingFaces]] # sort each of other's Face's vertexIDs for canonical comparison other_faceHash = numerix.sort(other_faceHash, axis=0) # then hash the Faces for comparison (NumPy set operations are only for 1D arrays) other_faceHash = numerix.apply_along_axis(str, axis=0, arr=other_faceHash) face_sort = numerix.argsort(other_faceHash) other_faceHash = other_faceHash[face_sort] other_matchingFaces = other_matchingFaces[face_sort] self_matchingFaces = self_matchingFaces[numerix.in1d(self_faceHash, other_faceHash)] other_matchingFaces = other_matchingFaces[numerix.in1d(other_faceHash, self_faceHash)] faceCorrelates = numerix.array((self_matchingFaces, other_matchingFaces)) # warn if meshes don't touch, but allow it if (selfc.numberOfFaces > 0 and otherc.numberOfFaces > 0 and faceCorrelates.shape[-1] == 0): import warnings warnings.warn("Faces are not aligned", UserWarning, stacklevel=4) # map other's Face IDs to new Face IDs, # accounting for overlaps with self's Face IDs face_map = numerix.empty(otherNumFaces, dtype=numerix.INT_DTYPE) facesToAdd = numerix.delete(numerix.arange(otherNumFaces), faceCorrelates[1]) face_map[facesToAdd] = numerix.arange(otherNumFaces - len(faceCorrelates[1])) + selfNumFaces face_map[faceCorrelates[1]] = faceCorrelates[0] other_faceVertexIDs = vertex_map[otherc.faceVertexIDs[..., facesToAdd]] # ensure that both sets of cellFaceIDs have the same maximum number of (masked) elements self_cellFaceIDs = selfc.cellFaceIDs other_cellFaceIDs = face_map[otherc.cellFaceIDs] diff = self_cellFaceIDs.shape[0] - other_cellFaceIDs.shape[0] if diff > 0: other_cellFaceIDs = numerix.append(other_cellFaceIDs, -1 * numerix.ones((diff,) + other_cellFaceIDs.shape[1:], 'l'), axis=0) other_cellFaceIDs = MA.masked_values(other_cellFaceIDs, -1) elif diff < 0: self_cellFaceIDs = numerix.append(self_cellFaceIDs, -1 * numerix.ones((-diff,) + self_cellFaceIDs.shape[1:], 'l'), axis=0) self_cellFaceIDs = MA.masked_values(self_cellFaceIDs, -1) # concatenate everything and return return { 'vertexCoords': numerix.concatenate((selfc.vertexCoords, otherc.vertexCoords[..., verticesToAdd]), axis=1), 'faceVertexIDs': numerix.concatenate((self_faceVertexIDs, other_faceVertexIDs), axis=1), 'cellFaceIDs': MA.concatenate((self_cellFaceIDs, other_cellFaceIDs), axis=1) }
def _nodesPerFace(self): return numerix.sort(self._unsortedNodesPerFace, axis=0)[::-1]
def _getAddedMeshValues(self, other, resolution=1e-2): """Calculate the parameters to define a concatenation of `other` with `self` :Parameters: - `other`: The :class:`~fipy.meshes.numMesh.Mesh` to concatenate with `self` - `resolution`: How close vertices have to be (relative to the smallest cell-to-cell distance in either mesh) to be considered the same :Returns: A `dict` with 3 elements: the new mesh vertexCoords, faceVertexIDs, and cellFaceIDs. """ selfc = self._getConcatenableMesh() other = other._getConcatenableMesh() selfNumFaces = selfc.faceVertexIDs.shape[-1] selfNumVertices = selfc.vertexCoords.shape[-1] otherNumFaces = other.faceVertexIDs.shape[-1] otherNumVertices = other.vertexCoords.shape[-1] ## check dimensions if(selfc.vertexCoords.shape[0] != other.vertexCoords.shape[0]): raise MeshAdditionError, "Dimensions do not match" ## compute vertex correlates ## only try to match exterior (X) vertices self_Xvertices = numerix.unique(selfc._getFaceVertexIDs().filled()[..., selfc.getExteriorFaces().getValue()].flatten()) other_Xvertices = numerix.unique(other._getFaceVertexIDs().filled()[..., other.getExteriorFaces().getValue()].flatten()) self_XvertexCoords = selfc.vertexCoords[..., self_Xvertices] other_XvertexCoords = other.vertexCoords[..., other_Xvertices] # lifted from Mesh._getNearestCellID() other_vertexCoordMap = numerix.resize(other_XvertexCoords, (self_XvertexCoords.shape[-1], other_XvertexCoords.shape[0], other_XvertexCoords.shape[-1])).swapaxes(0,1) tmp = self_XvertexCoords[..., numerix.newaxis] - other_vertexCoordMap closest = numerix.argmin(numerix.dot(tmp, tmp), axis=0) # just because they're closest, doesn't mean they're close tmp = self_XvertexCoords[..., closest] - other_XvertexCoords distance = numerix.sqrtDot(tmp, tmp) # only want vertex pairs that are 100x closer than the smallest # cell-to-cell distance close = distance < resolution * min(selfc._getCellToCellDistances().min(), other._getCellToCellDistances().min()) vertexCorrelates = numerix.array((self_Xvertices[closest[close]], other_Xvertices[close])) # warn if meshes don't touch, but allow it if (selfc._getNumberOfVertices() > 0 and other._getNumberOfVertices() > 0 and vertexCorrelates.shape[-1] == 0): import warnings warnings.warn("Vertices are not aligned", UserWarning, stacklevel=4) ## compute face correlates # ensure that both sets of faceVertexIDs have the same maximum number of (masked) elements self_faceVertexIDs = selfc.faceVertexIDs other_faceVertexIDs = other.faceVertexIDs diff = self_faceVertexIDs.shape[0] - other_faceVertexIDs.shape[0] if diff > 0: other_faceVertexIDs = numerix.append(other_faceVertexIDs, -1 * numerix.ones((diff,) + other_faceVertexIDs.shape[1:]), axis=0) other_faceVertexIDs = MA.masked_values(other_faceVertexIDs, -1) elif diff < 0: self_faceVertexIDs = numerix.append(self_faceVertexIDs, -1 * numerix.ones((-diff,) + self_faceVertexIDs.shape[1:]), axis=0) self_faceVertexIDs = MA.masked_values(self_faceVertexIDs, -1) # want self's Faces for which all faceVertexIDs are in vertexCorrelates self_matchingFaces = numerix.in1d(self_faceVertexIDs, vertexCorrelates[0]).reshape(self_faceVertexIDs.shape).all(axis=0).nonzero()[0] # want other's Faces for which all faceVertexIDs are in vertexCorrelates other_matchingFaces = numerix.in1d(other_faceVertexIDs, vertexCorrelates[1]).reshape(other_faceVertexIDs.shape).all(axis=0).nonzero()[0] # map other's Vertex IDs to new Vertex IDs, # accounting for overlaps with self's Vertex IDs vertex_map = numerix.empty(otherNumVertices, dtype=int) verticesToAdd = numerix.delete(numerix.arange(otherNumVertices), vertexCorrelates[1]) vertex_map[verticesToAdd] = numerix.arange(otherNumVertices - len(vertexCorrelates[1])) + selfNumVertices vertex_map[vertexCorrelates[1]] = vertexCorrelates[0] # calculate hashes of faceVertexIDs for comparing Faces if self_matchingFaces.shape[-1] == 0: self_faceHash = numerix.empty(self_matchingFaces.shape[:-1] + (0,), dtype="str") else: # sort each of self's Face's vertexIDs for canonical comparison self_faceHash = numerix.sort(self_faceVertexIDs[..., self_matchingFaces], axis=0) # then hash the Faces for comparison (NumPy set operations are only for 1D arrays) self_faceHash = numerix.apply_along_axis(str, axis=0, arr=self_faceHash) face_sort = numerix.argsort(self_faceHash) self_faceHash = self_faceHash[face_sort] self_matchingFaces = self_matchingFaces[face_sort] if other_matchingFaces.shape[-1] == 0: other_faceHash = numerix.empty(other_matchingFaces.shape[:-1] + (0,), dtype="str") else: # convert each of other's Face's vertexIDs to new IDs other_faceHash = vertex_map[other_faceVertexIDs[..., other_matchingFaces]] # sort each of other's Face's vertexIDs for canonical comparison other_faceHash = numerix.sort(other_faceHash, axis=0) # then hash the Faces for comparison (NumPy set operations are only for 1D arrays) other_faceHash = numerix.apply_along_axis(str, axis=0, arr=other_faceHash) face_sort = numerix.argsort(other_faceHash) other_faceHash = other_faceHash[face_sort] other_matchingFaces = other_matchingFaces[face_sort] self_matchingFaces = self_matchingFaces[numerix.in1d(self_faceHash, other_faceHash)] other_matchingFaces = other_matchingFaces[numerix.in1d(other_faceHash, self_faceHash)] faceCorrelates = numerix.array((self_matchingFaces, other_matchingFaces)) # warn if meshes don't touch, but allow it if (selfc._getNumberOfFaces() > 0 and other._getNumberOfFaces() > 0 and faceCorrelates.shape[-1] == 0): import warnings warnings.warn("Faces are not aligned", UserWarning, stacklevel=4) # map other's Face IDs to new Face IDs, # accounting for overlaps with self's Face IDs face_map = numerix.empty(otherNumFaces, dtype=int) facesToAdd = numerix.delete(numerix.arange(otherNumFaces), faceCorrelates[1]) face_map[facesToAdd] = numerix.arange(otherNumFaces - len(faceCorrelates[1])) + selfNumFaces face_map[faceCorrelates[1]] = faceCorrelates[0] other_faceVertexIDs = vertex_map[other.faceVertexIDs[..., facesToAdd]] # ensure that both sets of cellFaceIDs have the same maximum number of (masked) elements self_cellFaceIDs = selfc.cellFaceIDs other_cellFaceIDs = face_map[other.cellFaceIDs] diff = self_cellFaceIDs.shape[0] - other_cellFaceIDs.shape[0] if diff > 0: other_cellFaceIDs = numerix.append(other_cellFaceIDs, -1 * numerix.ones((diff,) + other_cellFaceIDs.shape[1:]), axis=0) other_cellFaceIDs = MA.masked_values(other_cellFaceIDs, -1) elif diff < 0: self_cellFaceIDs = numerix.append(self_cellFaceIDs, -1 * numerix.ones((-diff,) + self_cellFaceIDs.shape[1:]), axis=0) self_cellFaceIDs = MA.masked_values(self_cellFaceIDs, -1) # concatenate everything and return return { 'vertexCoords': numerix.concatenate((selfc.vertexCoords, other.vertexCoords[..., verticesToAdd]), axis=1), 'faceVertexIDs': numerix.concatenate((self_faceVertexIDs, other_faceVertexIDs), axis=1), 'cellFaceIDs': MA.concatenate((self_cellFaceIDs, other_cellFaceIDs), axis=1) }