def _getStencil(self, id1, id2):
id1 = self._globalOverlappingRowIDs[id1]
id2 = self._globalOverlappingColIDs[id2]
mask = numerix.in1d(id1, self._globalNonOverlappingRowIDs)
id1 = self._ao.app2petsc(id1[mask].astype('int32'))
id2 = self._ao.app2petsc(id2[mask].astype('int32'))
return id1, id2, mask
def _getStencil(self, id1, id2):
globalOverlappingCellIDs = self.mesh._getGlobalOverlappingCellIDs()
globalNonOverlappingCellIDs = self.mesh._getGlobalNonOverlappingCellIDs()
id1 = globalOverlappingCellIDs[id1]
id2 = globalOverlappingCellIDs[id2]
mask = numerix.in1d(id1, globalNonOverlappingCellIDs)
id1 = id1[mask]
id2 = id2[mask]
return id1, id2, mask
def _getStencil(self, id1, id2):
globalOverlappingCellIDs = self.mesh._getGlobalOverlappingCellIDs()
globalNonOverlappingCellIDs = self.mesh._getGlobalNonOverlappingCellIDs()
id1 = globalOverlappingCellIDs[id1]
id2 = globalOverlappingCellIDs[id2]
mask = numerix.in1d(id1, globalNonOverlappingCellIDs)
id1 = id1[mask]
id2 = id2[mask]
return id1, id2, mask
def _getStencil_(self,
id1,
id2,
globalOverlappihgIDs,
globalNonOverlappihgIDs,
overlapping=False):
id1 = globalOverlappihgIDs[id1]
if overlapping:
mask = numerix.ones(id1.shape, dtype=bool)
else:
mask = numerix.in1d(id1, globalNonOverlappihgIDs)
id1 = self.matrix()._mesh2matrix(id1[mask])
id2 = numerix.asarray(id2)[mask]
return id1, id2, mask
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 bodies(self):
if self._bodies is None:
self._bodies = numerix.in1d(self.mesh._globalOverlappingCellIDs,
self.mesh._globalNonOverlappingCellIDs)
return self._bodies
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)
}
def _bodies(self):
if not hasattr(self, "_bodies_"):
self._bodies_ = numerix.in1d(
self.mesh._globalOverlappingCellIDs,
self.mesh._globalNonOverlappingCellIDs)
return self._bodies_
