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rearranging of interpolation code.

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rowanc1
2014-03-06 19:05:58 -08:00
parent cfb0a7f447
commit 5bcdc5d46a
3 changed files with 186 additions and 181 deletions
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SimPEG/Mesh/TensorMesh.py
+81 -78
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@@ -170,6 +170,87 @@ class BaseTensorMesh(BaseRectangularMesh):
return [t for t in ten if t is not None]
# --------------- Methods ---------------------
def isInside(self, pts, locType='N'):
"""
Determines if a set of points are inside a mesh.
:param numpy.ndarray pts: Location of points to test
:rtype numpy.ndarray
:return inside, numpy array of booleans
"""
tensors = self.getTensor(locType)
if type(pts) == list:
pts = np.array(pts)
assert type(pts) == np.ndarray, "must be a numpy array"
if self.dim > 1:
assert pts.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
elif len(pts.shape) == 1:
pts = pts[:,np.newaxis]
else:
assert pts.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
inside = np.ones(pts.shape[0],dtype=bool)
for i, tensor in enumerate(tensors):
inside = inside & (pts[:,i] >= tensor.min()) & (pts[:,i] <= tensor.max())
return inside
def getInterpolationMat(self, loc, locType, zerosOutside=False):
""" Produces interpolation matrix
:param numpy.ndarray loc: Location of points to interpolate to
:param str locType: What to interpolate (see below)
:rtype: scipy.sparse.csr.csr_matrix
:return: M, the interpolation matrix
locType can be::
'Ex' -> x-component of field defined on edges
'Ey' -> y-component of field defined on edges
'Ez' -> z-component of field defined on edges
'Fx' -> x-component of field defined on faces
'Fy' -> y-component of field defined on faces
'Fz' -> z-component of field defined on faces
'N' -> scalar field defined on nodes
'CC' -> scalar field defined on cell centers
"""
if type(loc) == list:
loc = np.array(loc)
assert type(loc) == np.ndarray, "must be a numpy array"
if self.dim > 1:
assert loc.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
elif len(loc.shape) == 1:
loc = loc[:,np.newaxis]
else:
assert loc.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
if zerosOutside is False:
assert np.all(self.isInside(loc)), "Points outside of mesh"
else:
indZeros = np.logical_not(self.isInside(loc))
loc[indZeros, :] = np.array([v.mean() for v in self.getTensor('CC')])
if locType in ['Fx','Fy','Fz','Ex','Ey','Ez']:
ind = {'x':0, 'y':1, 'z':2}[locType[1]]
assert self.dim >= ind, 'mesh is not high enough dimension.'
nF_nE = self.vnF if 'F' in locType else self.vnE
components = [Utils.spzeros(loc.shape[0], n) for n in nF_nE]
components[ind] = Utils.interpmat(loc, *self.getTensor(locType))
Q = sp.hstack(components)
elif locType in ['CC', 'N']:
Q = Utils.interpmat(loc, *self.getTensor(locType))
else:
raise NotImplementedError('getInterpolationMat: locType=='+locType+' and mesh.dim=='+str(self.dim))
if zerosOutside:
Q[indZeros, :] = 0
return Q.tocsr()
class TensorMesh(BaseTensorMesh, TensorView, DiffOperators, InnerProducts):
"""
@@ -320,84 +401,6 @@ class TensorMesh(BaseTensorMesh, TensorView, DiffOperators, InnerProducts):
self._edge = np.r_[Utils.mkvc(l1), Utils.mkvc(l2), Utils.mkvc(l3)]
return self._edge
# --------------- Methods ---------------------
def isInside(self, pts, locType='N'):
"""
Determines if a set of points are inside a mesh.
:param numpy.ndarray pts: Location of points to test
:rtype numpy.ndarray
:return inside, numpy array of booleans
"""
tensors = self.getTensor(locType)
if type(pts) == list:
pts = np.array(pts)
assert type(pts) == np.ndarray, "must be a numpy array"
if self.dim > 1:
assert pts.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
elif len(pts.shape) == 1:
pts = pts[:,np.newaxis]
else:
assert pts.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
inside = np.ones(pts.shape[0],dtype=bool)
for i, tensor in enumerate(tensors):
inside = inside & (pts[:,i] >= tensor.min()) & (pts[:,i] <= tensor.max())
return inside
def getInterpolationMat(self, loc, locType, zerosOutside=False):
""" Produces interpolation matrix
:param numpy.ndarray loc: Location of points to interpolate to
:param str locType: What to interpolate (see below)
:rtype: scipy.sparse.csr.csr_matrix
:return: M, the interpolation matrix
locType can be::
'Ex' -> x-component of field defined on edges
'Ey' -> y-component of field defined on edges
'Ez' -> z-component of field defined on edges
'Fx' -> x-component of field defined on faces
'Fy' -> y-component of field defined on faces
'Fz' -> z-component of field defined on faces
'N' -> scalar field defined on nodes
'CC' -> scalar field defined on cell centers
"""
if type(loc) == list:
loc = np.array(loc)
assert type(loc) == np.ndarray, "must be a numpy array"
if self.dim > 1:
assert loc.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
elif len(loc.shape) == 1:
loc = loc[:,np.newaxis]
else:
assert loc.shape[1] == self.dim, "must be a column vector of shape (nPts, mesh.dim)"
if zerosOutside is False:
assert np.all(self.isInside(loc)), "Points outside of mesh"
else:
indZeros = np.logical_not(self.isInside(loc))
loc[indZeros, :] = np.array([v.mean() for v in self.getTensor('CC')])
ind = 0 if 'x' in locType else 1 if 'y' in locType else 2 if 'z' in locType else -1
if locType in ['Fx','Fy','Fz','Ex','Ey','Ez'] and self.dim >= ind:
nF_nE = self.vnF if 'F' in locType else self.vnE
components = [Utils.spzeros(loc.shape[0], n) for n in nF_nE]
components[ind] = Utils.interpmat(loc, *self.getTensor(locType))
Q = sp.hstack(components)
elif locType in ['CC', 'N']:
Q = Utils.interpmat(loc, *self.getTensor(locType))
else:
raise NotImplementedError('getInterpolationMat: locType=='+locType+' and mesh.dim=='+str(self.dim))
if zerosOutside:
Q[indZeros, :] = 0
return Q.tocsr()
@property
def faceBoundaryInd(self):
"""