def __init__(self,
vertexCoords,
faceVertexIDs,
cellFaceIDs,
communicator=serialComm,
_RepresentationClass=_MeshRepresentation,
_TopologyClass=_MeshTopology):
super(Mesh, self).__init__(communicator=communicator,
_RepresentationClass=_RepresentationClass,
_TopologyClass=_TopologyClass)
"""faceVertexIds and cellFacesIds must be padded with minus ones."""
self.vertexCoords = vertexCoords
self.faceVertexIDs = MA.masked_values(faceVertexIDs, -1)
self.cellFaceIDs = MA.masked_values(cellFaceIDs, -1)
self.dim = self.vertexCoords.shape[0]
if not hasattr(self, "numberOfFaces"):
self.numberOfFaces = self.faceVertexIDs.shape[-1]
if not hasattr(self, "numberOfCells"):
self.numberOfCells = self.cellFaceIDs.shape[-1]
if not hasattr(self, "globalNumberOfCells"):
self.globalNumberOfCells = self.numberOfCells
if not hasattr(self, "globalNumberOfFaces"):
self.globalNumberOfFaces = self.numberOfFaces
self.faceCellIDs = self._calcFaceCellIDs()
self._setTopology()
self._setGeometry(scaleLength=1.)
def __init__(self, vertexCoords, faceVertexIDs, cellFaceIDs, communicator=serialComm, _RepresentationClass=_MeshRepresentation, _TopologyClass=_MeshTopology):
super(Mesh, self).__init__(communicator=communicator,
_RepresentationClass=_RepresentationClass,
_TopologyClass=_TopologyClass)
"""faceVertexIds and cellFacesIds must be padded with minus ones."""
self.vertexCoords = vertexCoords
self.faceVertexIDs = MA.masked_values(faceVertexIDs, -1)
self.cellFaceIDs = MA.masked_values(cellFaceIDs, -1)
self.dim = self.vertexCoords.shape[0]
if not hasattr(self, "numberOfFaces"):
self.numberOfFaces = self.faceVertexIDs.shape[-1]
if not hasattr(self, "numberOfCells"):
self.numberOfCells = self.cellFaceIDs.shape[-1]
if not hasattr(self, "globalNumberOfCells"):
self.globalNumberOfCells = self.numberOfCells
if not hasattr(self, "globalNumberOfFaces"):
self.globalNumberOfFaces = self.numberOfFaces
self.faceCellIDs = self._calcFaceCellIDs()
self._setTopology()
self._setGeometry(scaleLength = 1.)
def __init__(self, vertexCoords, faceVertexIDs, cellFaceIDs):
"""faceVertexIds and cellFacesIds must be padded with minus ones."""
self.vertexCoords = vertexCoords
self.faceVertexIDs = MA.masked_values(faceVertexIDs, -1)
self.cellFaceIDs = MA.masked_values(cellFaceIDs, -1)
_CommonMesh.__init__(self)
def faceCellIDs(self):
Hids = numerix.zeros((2, self.nx, self.numberOfHorizontalRows),
'l')
indices = numerix.indices((self.nx, self.numberOfHorizontalRows))
Hids[1] = indices[0] + indices[1] * self.nx
Hids[0] = Hids[1] - self.nx
if self.numberOfHorizontalRows > 0:
Hids[0, ..., 0] = Hids[1, ..., 0]
Hids[1, ..., 0] = -1
Hids[1, ..., -1] = -1
Vids = numerix.zeros((2, self.numberOfVerticalColumns, self.ny),
'l')
indices = numerix.indices((self.numberOfVerticalColumns, self.ny))
Vids[1] = indices[0] + indices[1] * self.nx
Vids[0] = Vids[1] - 1
if self.numberOfVerticalColumns > 0:
Vids[0, 0] = Vids[1, 0]
Vids[1, 0] = -1
Vids[1, -1] = -1
return MA.masked_values(numerix.concatenate(
(Hids.reshape(
(2, self.numberOfHorizontalFaces), order="FORTRAN"),
Vids.reshape(
(2, self.numberOfFaces - self.numberOfHorizontalFaces),
order="FORTRAN")),
axis=1),
value=-1)
def faceCellIDs(self):
Hids = numerix.zeros((2, self.nx, self.numberOfHorizontalRows), 'l')
indices = numerix.indices((self.nx, self.numberOfHorizontalRows))
Hids[1] = indices[0] + indices[1] * self.nx
Hids[0] = Hids[1] - self.nx
if self.numberOfHorizontalRows > 0:
Hids[0, ..., 0] = Hids[1, ..., 0]
Hids[1, ..., 0] = -1
Hids[1, ..., -1] = -1
Vids = numerix.zeros((2, self.numberOfVerticalColumns, self.ny), 'l')
indices = numerix.indices((self.numberOfVerticalColumns, self.ny))
Vids[1] = indices[0] + indices[1] * self.nx
Vids[0] = Vids[1] - 1
if self.numberOfVerticalColumns > 0:
Vids[0, 0] = Vids[1, 0]
Vids[1, 0] = -1
Vids[1, -1] = -1
return MA.masked_values(numerix.concatenate((Hids.reshape((2, self.numberOfHorizontalFaces), order="FORTRAN"),
Vids.reshape((2, self.numberOfFaces - self.numberOfHorizontalFaces), order="FORTRAN")), axis=1), value = -1)
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 _getAddedMeshValues(self, other, smallNumber):
"""
Returns a `dictionary` with 3 elements: the new mesh vertexCoords, faceVertexIDs, and cellFaceIDs.
"""
other = other._getConcatenableMesh()
selfNumFaces = self.faceVertexIDs.shape[-1]
selfNumVertices = self.vertexCoords.shape[-1]
otherNumFaces = other.faceVertexIDs.shape[-1]
otherNumVertices = other.vertexCoords.shape[-1]
## check dimensions
if(self.vertexCoords.shape[0] != other.vertexCoords.shape[0]):
raise MeshAdditionError, "Dimensions do not match"
## compute vertex correlates
vertexCorrelates = {}
for i in range(selfNumVertices):
for j in range(otherNumVertices):
diff = self.vertexCoords[...,i] - other.vertexCoords[...,j]
diff = numerix.array(diff)
if (sum(diff ** 2) < smallNumber):
vertexCorrelates[j] = i
if (self._getNumberOfVertices() > 0 and other._getNumberOfVertices() > 0 and vertexCorrelates == {}):
raise MeshAdditionError, "Vertices are not aligned"
## compute face correlates
faceCorrelates = {}
for i in range(otherNumFaces):
## Seems to be overwriting other.faceVertexIDs with new numpy
## currFace = other.faceVertexIDs[i]
## currFace = other.faceVertexIDs[...,i].copy()
## Changed this again as numpy 1.0.4 seems to have no copy method for
## masked arrays.
try:
currFace = other.faceVertexIDs[...,i].copy()
except:
currFace = MA.array(other.faceVertexIDs[...,i], mask=MA.getmask(other.faceVertexIDs[...,i]))
keepGoing = 1
currIndex = 0
for item in currFace:
if(vertexCorrelates.has_key(item)):
currFace[currIndex] = vertexCorrelates[item]
currIndex = currIndex + 1
else:
keepGoing = 0
if(keepGoing == 1):
for j in range(selfNumFaces):
if (self._equalExceptOrder(currFace, self.faceVertexIDs[...,j])):
faceCorrelates[i] = j
if (self._getNumberOfFaces() > 0 and other._getNumberOfFaces() > 0 and faceCorrelates == {}):
raise MeshAdditionError, "Faces are not aligned"
faceIndicesToAdd = ()
for i in range(otherNumFaces):
if(not faceCorrelates.has_key(i)):
faceIndicesToAdd = faceIndicesToAdd + (i,)
vertexIndicesToAdd = ()
for i in range(otherNumVertices):
if(not vertexCorrelates.has_key(i)):
vertexIndicesToAdd = vertexIndicesToAdd + (i,)
##compute the full face and vertex correlation list
a = selfNumFaces
for i in faceIndicesToAdd:
faceCorrelates[i] = a
a = a + 1
b = selfNumVertices
for i in vertexIndicesToAdd:
vertexCorrelates[i] = b
b = b + 1
## compute what the cells are that we need to add
cellsToAdd = numerix.ones((self.cellFaceIDs.shape[0], other.cellFaceIDs.shape[-1]))
cellsToAdd = -1 * cellsToAdd
for j in range(other.cellFaceIDs.shape[-1]):
for i in range(other.cellFaceIDs.shape[0]):
cellsToAdd[i, j] = faceCorrelates[other.cellFaceIDs[i, j]]
cellsToAdd = MA.masked_values(cellsToAdd, -1)
## compute what the faces are that we need to add
facesToAdd = numerix.take(other.faceVertexIDs, faceIndicesToAdd, axis=1)
for j in range(facesToAdd.shape[-1]):
for i in range(facesToAdd.shape[0]):
facesToAdd[i, j] = vertexCorrelates[facesToAdd[i, j]]
## compute what the vertices are that we need to add
verticesToAdd = numerix.take(other.vertexCoords, vertexIndicesToAdd, axis=1)
return {
'vertexCoords': numerix.concatenate((self.vertexCoords, verticesToAdd), axis=1),
'faceVertexIDs': numerix.concatenate((self.faceVertexIDs, facesToAdd), axis=1),
'cellFaceIDs': MA.concatenate((self.cellFaceIDs, cellsToAdd), axis=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)
}
def mp2mesh(self,
segs,
TairK=293
): #TODO: adapt to make more time efficient. do it in c++?
""" Converts a mappedPlant into a network of 1D grids
outputs:
creates mesh and stores it in self.mesh
fills self.phi => allows for visualization of the mesh with vtk"""
self.TairK = TairK
nodes = self.get_nodes()
#cells = [[bottom 1], [top 1], [bottom 2], [top 2]]
#bottom 1 = x_node: link to segment bellow or parent seg bellow
#top 1: y_node: link to segment above
#bottom 2: x_node: link to child bellow or parent cell above
#top 2: y_node: link to child above
#only bottom 1 and top 1 are used to define cellCenter
for segnum, seg in enumerate(segs): #go through each organ
seg = np.array(
list(map(lambda x: np.array(x), seg))
) # converts the list of Vector3d to a numpy array. shape: (num_nodes, 3)
if segnum == 0: #basal root
bot1 = np.array(
[s for s in range(len(seg) - 1)],
dtype=np.int64) #nodes put back in oder after growth?
top1 = np.array([s for s in range(1, len(seg))
]) #nodes put back in oder after growth?
bot2 = np.full(len(seg) - 1, -1)
top2ID = np.array([])
elif np.where(np.all(nodes == seg[0],
axis=1))[0][0] == 0: #main stem
start = max(top1) + 1
#max val of nde instead of len seg
bot1 = np.concatenate(
(bot1, np.array([0]),
np.array([s + start for s in range(0,
len(seg) - 2)],
dtype=np.int64)
)) #nodes put back in oder after growth?
top1 = np.concatenate(
(top1,
np.array([s + start for s in range(0,
len(seg) - 1)
]))) #nodes put back in oder after growth?
bot2 = np.concatenate((bot2, np.full(len(seg) - 1, -1)))
else: #lateral
start = max(top1) + 1
bot1 = np.concatenate(
(bot1, np.array([start]),
np.array([s + start for s in range(2, len(seg))],
dtype=np.int64)
)) #nodes put back in oder after growth?
top1 = np.concatenate(
(top1,
np.array([s + start for s in range(2,
len(seg) + 1)
]))) #nodes put back in oder after growth?
top2ID = np.concatenate((top2ID, [start]))
bot2 = np.concatenate(
(bot2, [start + 1], np.full(len(seg) - 2, -1)))
oldbot1 = np.concatenate([
np.array(
list(
map(
lambda x: np.where(np.all(nodes == np.array(x), axis=1)
)[0][0], segs[i])))[:-1]
for i in range(len(segs))
])
oldtop1 = np.concatenate([
np.array(
list(
map(
lambda x: np.where(np.all(nodes == np.array(x), axis=1)
)[0][0], segs[i])))[1:]
for i in range(len(segs))
])
oldbot2 = oldbot1[np.where(bot2 >= 0)[0]]
newIDS = np.concatenate((bot1, top1, bot2[np.where(bot2 >= 0)[0]]))
oldIDS = np.concatenate((oldbot1, oldtop1, oldbot2))
self.new2oldNodeID = dict(zip(newIDS, oldIDS))
oldIDSu = np.array(list(set(oldIDS)))
newIDS = [
np.array(list(set(newIDS[np.where(oldIDS == ui)[0]])))
for ui in oldIDSu
]
self.old2newNodeID = dict(zip(oldIDSu, newIDS))
self.orgID = np.concatenate([
np.full(len(seg) - 1, segnum) for segnum, seg in enumerate(segs)
]) # organ id for each cell
faces = np.array((np.arange(0,
max(top1) + 1), ),
dtype=np.int64) #index of verticies on each face
nodes_x_coord = [nodes[self.new2oldNodeID[ni]][0] for ni in faces[0]]
nodes_y_coord = [nodes[self.new2oldNodeID[ni]][1] for ni in faces[0]]
nodes_z_coord = [nodes[self.new2oldNodeID[ni]][2] for ni in faces[0]]
vertices = np.vstack((nodes_x_coord, nodes_y_coord,
nodes_z_coord)) #change how coords are stored
top2 = np.full(len(bot1), -1)
top2Idx = np.where([
sum(oldbot1 == t1) > 1 for t1 in oldtop1
])[0] #np.where(oldtop1== b1)#np.concatenate((top2Idx,np.where()))
top2[top2Idx] = top2ID
bot2[top2Idx + 1] = top2ID + 1
cells = np.vstack((bot1, top1, bot2, top2))
if (not isinstance(
self.Px, float)): #get mean rx of the segment (used by GrSink)
self.rxCells = np.mean(
[[self.Px[self.new2oldNodeID[xi]] for xi in cells[0]],
[self.Px[self.new2oldNodeID[xi]] for xi in cells[1]]],
axis=0)
#rxCell >= rxThrMax -> rxFactor = 1
else:
self.rxCells = np.minimum(self.rxThrMax, self.Px)
length = np.array([
norm(nodes[self.new2oldNodeID[cells[0][i]]] -
nodes[self.new2oldNodeID[cells[1][i]]])
for i in range(len(cells[0]))
])
cells = MA.masked_values(cells, -1)
radiiVertices = np.array(
[
self.rs.radii[max((self.new2oldNodeID[xi] - 1, 0))]
for xi in faces[0]
]
) #radius for each node, seed node take radius of 1st segment of root
radiiCells = np.array(
[self.rs.radii[self.new2oldNodeID[xi] - 1] for xi in cells[1]])
self.mesh = Mesh1Dmod(
radiiVertices=radiiVertices * 1e-2,
radiiCells=radiiCells * 1e-2,
length=length,
vertexCoords=vertices,
faceVertexIDs=faces,
cellFaceIDs=cells
) #1e-2 to go from radius of segment to radius of phloem
#take out radiiCells and length: compute durectly in Mesh1Dmod
#store max growth rate and max organ length for computaiton of the CW-limited growth
self.orgLength = np.array([
sum(length[np.where(self.orgID == oid)[0]]) for oid in self.orgID
])
organTypes = self.get_organ_types()
subTypes = self.get_subtypes()
self.orgLengthThr = np.array([
self.rs.organParam[organTypes[self.new2oldNodeID[xi] - 1]]
[subTypes[self.new2oldNodeID[xi] - 1] + 2 *
(organTypes[self.new2oldNodeID[xi] - 1] == 4)].getParameter(
'lmax') for xi in cells[1]
])
self.maxGrowth = np.array([
self.rs.organParam[organTypes[self.new2oldNodeID[xi] - 1]]
[subTypes[self.new2oldNodeID[xi] - 1] + 2 *
(organTypes[self.new2oldNodeID[xi] - 1] == 4)].getParameter('r') /
(24 * 60 * 60) for xi in cells[1]
]) #maxgrwth rate from cm/d to cm/s
self.phi = CellVariablemod(name="solution variable",
mesh=self.mesh,
value=0.,
hasOld=True)
self.Rm = CellVariablemod(name="solution variable",
mesh=self.mesh,
value=0.,
hasOld=True)
def mp2mesh(self, segs, TairK=293): #create an old2newNodeID map?
""" Converts a mappedPlant into a network of 1D grids
outputs:
creates mesh and stores it in self.mesh
fills self.phi => allows for visualization of the mesh with vtk"""
self.new2oldNodeID = {
} #map to get MappedPlant node-ID from grid node-ID
self.old2newNodeID = {
} #map to get grid node-ID from MappedPlant node-ID
self.newCell2organID = {} #for grwth rate evaluation
self.organ2oldNodeID = {} #for growth rate evaluation
self.organ2newCellID = {} #for growth rate evaluation
self.oldNode2organID = {} #for growth rate evaluation
self.orgID = np.array([])
self.TairK = TairK
vertices = np.array([]) #containes x,y,z coords of each vertex
cells = np.array(
[[], [], [], []], dtype=np.int64
) #contains ID of the faces on each cell. here 1D => 1face == 1 vertex
#cells = [[bottom 1], [top 1], [bottom 2], [top 2]]
#bottom 1 = x_node: link to segment bellow or parent seg bellow
#top 1: y_node: link to segment above
#bottom 2: x_node: link to child bellow or parent cell above
#top 2: y_node: link to child above
#only bottom 1 and top 1 are used to define cellCenter
nodes = self.get_nodes()
newNodeID = 0
organTypes = self.get_organ_types()
subTypes = self.get_subtypes()
radiiCells = np.array([])
radiiVertices = np.array([])
length = np.array([])
tempOrgLength = np.array([])
newNodeID_prev = -1
nodes_x_coord = np.array(
[], dtype=np.float64
) #np.array([xi[0] for xi in seg], dtype=np.float64)
nodes_y_coord = np.array(
[], dtype=np.float64
) # np.array([xi[1] for xi in seg], dtype=np.float64)
nodes_z_coord = np.array(
[], dtype=np.float64
) # np.array([xi[2] for xi in seg], dtype=np.float64)
self.orgLengthThr = np.array([], dtype=np.float64)
self.maxGrowth = np.array([], dtype=np.float64)
self.rxCells = np.array([], dtype=np.float64)
for segnum, seg in enumerate(segs): #go through each organ
length_org = np.array([])
seg = np.array(
list(map(lambda x: np.array(x), seg))
) # converts the list of Vector3d to a numpy array. shape: (num_nodes, 3)
for j, n in enumerate(seg): #go through the nodes of the organ
oldNodeID = np.where(np.all(nodes == n, axis=1))[0][0]
if (oldNodeID == 0 and segnum != 0
): #do not do it for first node of stem (newnodeId = )
newNodeID_prev = 0
nOld = n
continue
self.new2oldNodeID[
newNodeID] = oldNodeID #map linking nodes ID between fipy and plant
temp = self.old2newNodeID.get(
oldNodeID, np.array([], dtype=np.int64)
) #one old node ID might refer ti several new nodes
self.old2newNodeID[oldNodeID] = np.append(
temp, np.array([newNodeID], dtype=np.int64))
if j > 0: #not first node of organ
ot = int(organTypes[oldNodeID - 1])
st = int(subTypes[oldNodeID - 1])
radiiCells = np.concatenate(
(radiiCells, [self.rs.radii[oldNodeID - 1]]))
self.newCell2organID[
newNodeID] = segnum #map from new ID of y node of segment to organ ID
temp = self.organ2newCellID.get(
segnum, np.array([], dtype=np.int64))
self.organ2newCellID[segnum] = np.append(
temp, np.array([newNodeID], dtype=np.int64))
#store max growth rate and max organ length for computaiton of the CW-limited growth
self.orgLengthThr = np.concatenate((self.orgLengthThr, [
self.rs.organParam[ot][st + 2 *
(ot == 4)].getParameter('lmax')
]))
self.maxGrowth = np.concatenate((self.maxGrowth, [
self.rs.organParam[ot][st + 2 *
(ot == 4)].getParameter('r') /
(24 * 60 * 60)
])) #maxgrwth rate from cm/d to cm/s
if (not isinstance(self.Px, float)
): #get mean rx of the segment (used by GrSink)
self.rxCells = np.concatenate(
(self.rxCells[self.rxCells < 1], [
np.minimum(
self.rxThrMax,
np.mean((self.Px[oldNodeID], self.Px[
self.new2oldNodeID[newNodeID_prev]])))
]))
#rxCell >= rxThrMax -> rxFactor = 1
else:
self.rxCells = np.minimum(self.rxThrMax, self.Px)
length = np.concatenate(
(length, [norm(nOld - n)
])) #length of each cell of plant
length_org = np.concatenate(
(length_org, [norm(nOld - n)
])) #length of cell of the organ
if (
segnum == 0
or cells[1][len(cells[1]) - 1] != newNodeID
): #not first cell of lateral stem, lat root or leaf => those cells were already added in previous loop
#create cell from curret and previous node
cells = np.hstack(
(cells,
np.array((np.array([newNodeID_prev]),
np.array([newNodeID]), np.array([-1]),
np.array([-1]))).reshape(4, 1)))
elif segnum > 0: #base of organ other tham main root
ot = int(organTypes[oldNodeID])
seg_parent = np.where(
[self.new2oldNodeID[xi] for xi in cells[1]
] == self.new2oldNodeID[newNodeID])[0][0]
#if seg_parent >= 0: #not for base of stem
cells[3,
seg_parent] = newNodeID #top2 of segment bellow link
nodes_x_coord = np.append(
nodes_x_coord, n[0]
) #np.array([xi[0] for xi in seg], dtype=np.float64)
nodes_y_coord = np.append(
nodes_y_coord, n[1]
) # np.array([xi[1] for xi in seg], dtype=np.float64)
nodes_z_coord = np.append(
nodes_z_coord, n[2]
) # np.array([xi[2] for xi in seg], dtype=np.float64)
newNodeID_prev = newNodeID
newNodeID += 1
self.new2oldNodeID[newNodeID] = oldNodeID
temp = self.old2newNodeID.get(oldNodeID,
np.array([], dtype=np.int64))
self.old2newNodeID[oldNodeID] = np.append(
temp, np.array([newNodeID], dtype=np.int64))
self.new2oldNodeID[newNodeID] = oldNodeID
temp = self.old2newNodeID.get(oldNodeID,
np.array([], dtype=np.int64))
self.old2newNodeID[oldNodeID] = np.append(
temp, np.array([newNodeID], dtype=np.int64))
seg_parent = np.where(
[self.new2oldNodeID[xi] for xi in cells[0]
] == self.new2oldNodeID[newNodeID])[0][0]
cells[
2,
seg_parent] = newNodeID #add node to parent seg to link with child branch: bot2
cells = np.hstack(
(cells,
np.array(
(np.array([newNodeID_prev]),
np.array([newNodeID + 1]), np.array([newNodeID]),
np.array([-1]))).reshape(4, 1)))
nodes_x_coord = np.append(
nodes_x_coord,
n[0]) #np.array([xi[0] for xi in seg], dtype=np.float64)
nodes_y_coord = np.append(
nodes_y_coord,
n[1]) # np.array([xi[1] for xi in seg], dtype=np.float64)
nodes_z_coord = np.append(
nodes_z_coord,
n[2]) # np.array([xi[2] for xi in seg], dtype=np.float64)
newNodeID_prev = newNodeID
newNodeID += 1
nOld = n
self.orgID = np.concatenate(
(self.orgID, np.full(len(length_org),
segnum))) # organ id for each cell
tempOrgLength = np.append(tempOrgLength,
sum(length_org)) #length of each organ
vertices = np.vstack((nodes_x_coord, nodes_y_coord,
nodes_z_coord)) #change how coords are stored
self.orgGr = np.full(segnum + 1, 0.)
self.orgLength = np.array(
[tempOrgLength[self.newCell2organID[xi]] for xi in cells[1]])
self.faces = np.array((np.arange(0,
max(cells[1]) + 1), ),
dtype=np.int64) #index of verticies on each face
cells = MA.masked_values(cells, -1)
radiiVertices = np.array(
[
self.rs.radii[max((self.new2oldNodeID[xi] - 1, 0))]
for xi in self.faces[0]
]
) #radius for each node, seed node take radius of 1st segment of root
self.mesh = Mesh1Dmod(
radiiVertices=radiiVertices * 1e-2,
radiiCells=radiiCells * 1e-2,
length=length,
vertexCoords=vertices,
faceVertexIDs=self.faces,
cellFaceIDs=cells
) #1e-2 to go from radius of segment to radius of phloem
self.phi = CellVariablemod(name="solution variable",
mesh=self.mesh,
value=0.,
hasOld=True)
