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
"""
pts = utils.asArray_N_x_Dim(pts, self.dim)
tensors = self.getTensor(locType)
if locType == 'N' and self._meshType == 'CYL':
# NOTE: for a CYL mesh we add a node to check if we are inside in
# the radial direction!
tensors[0] = np.r_[0., tensors[0]]
tensors[1] = np.r_[tensors[1], 2.0*np.pi]
inside = np.ones(pts.shape[0], dtype=bool)
for i, tensor in enumerate(tensors):
TOL = np.diff(tensor).min() * 1.0e-10
inside = (
inside &
(pts[:, i] >= tensor.min()-TOL) &
(pts[:, i] <= tensor.max()+TOL)
)
return inside
def point2index(self, locs):
locs = utils.asArray_N_x_Dim(locs, self.dim)
inds = np.empty(locs.shape[0], dtype=np.int64)
for ind, loc in enumerate(locs):
inds[ind] = self._get_containing_cell_index(loc)
return inds
def test_asArray_N_x_Dim(self):
true = np.array([[1, 2, 3]])
listArray = asArray_N_x_Dim([1, 2, 3], 3)
self.assertTrue(np.all(true == listArray))
self.assertTrue(true.shape == listArray.shape)
listArray = asArray_N_x_Dim(np.r_[1, 2, 3], 3)
self.assertTrue(np.all(true == listArray))
self.assertTrue(true.shape == listArray.shape)
listArray = asArray_N_x_Dim(np.array([[1, 2, 3.0]]), 3)
self.assertTrue(np.all(true == listArray))
self.assertTrue(true.shape == listArray.shape)
true = np.array([[1, 2], [4, 5]])
listArray = asArray_N_x_Dim([[1, 2], [4, 5]], 2)
self.assertTrue(np.all(true == listArray))
self.assertTrue(true.shape == listArray.shape)
def _getInterpolationMat(self, loc, locType='CC', 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_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
'CCVx' -> x-component of vector field defined on cell centers
'CCVy' -> y-component of vector field defined on cell centers
'CCVz' -> z-component of vector field defined on cell centers
"""
loc = utils.asArray_N_x_Dim(loc, self.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))
# remove any zero blocks (hstack complains)
components = [comp for comp in components if comp.shape[1] > 0]
Q = sp.hstack(components)
elif locType in ['CC', 'N']:
Q = utils.interpmat(loc, *self.getTensor(locType))
elif locType in ['CCVx', 'CCVy', 'CCVz']:
Q = utils.interpmat(loc, *self.getTensor('CC'))
Z = utils.spzeros(loc.shape[0], self.nC)
if locType == 'CCVx':
Q = sp.hstack([Q, Z, Z])
elif locType == 'CCVy':
Q = sp.hstack([Z, Q, Z])
elif locType == 'CCVz':
Q = sp.hstack([Z, Z, Q])
else:
raise NotImplementedError(
'getInterpolationMat: locType==' + locType +
' and mesh.dim==' + str(self.dim)
)
if zerosOutside:
Q[indZeros, :] = 0
return Q.tocsr()