ind_nan = np.isnan(z_xyz)
if any(ind_nan):
tree = cKDTree(xyz)
_, ind = tree.query(locations[ind_nan, :])
z_xyz[ind_nan] = xyz[ind, dim]
# Create an active bool of all True
active = np.all((locations[:, dim] < z_xyz).reshape((mesh.nC, -1),
order="F"),
axis=1)
return active.ravel()
meshTensor = deprecate_function(unpack_widths,
"meshTensor",
removal_version="1.0.0",
future_warn=False)
closestPoints = deprecate_function(closest_points_index,
"closestPoints",
removal_version="1.0.0",
future_warn=False)
ExtractCoreMesh = deprecate_function(extract_core_mesh,
"ExtractCoreMesh",
removal_version="1.0.0",
future_warn=False)
closest_points = deprecate_function(closest_points_index,
"closest_points",
removal_version="1.0.0",
future_warn=False)
# Area calculation
#
# Approximate by 4 different triangles, and divide by 2.
# Each triangle is one half of the length of the cross product
#
# So also could be viewed as the average parallelogram.
#
# TODO: This does not compute correctly for concave quadrilaterals
area = (length(nA) + length(nB) + length(nC) + length(nD)) / 4
return N, area
exampleLrmGrid = deprecate_function(example_curvilinear_grid,
"exampleLrmGrid",
removal_version="1.0.0",
future_warn=True)
volTetra = deprecate_function(volume_tetrahedron,
"volTetra",
removal_version="1.0.0",
future_warn=True)
indexCube = deprecate_function(index_cube,
"indexCube",
removal_version="1.0.0",
future_warn=True)
faceInfo = deprecate_function(face_info,
"faceInfo",
removal_version="1.0.0",
future_warn=True)
raise ValueError(
"Input array does not have the same length as the number of cells in input mesh"
)
if output is not None and len(output) != mesh_out.nC:
raise ValueError(
"Output array does not have the same length as the number of cells in output mesh"
)
if values is not None:
values = np.asarray(values, dtype=np.float64)
if output is not None:
output = np.asarray(output, dtype=np.float64)
if in_type == "TENSOR":
if out_type == "TENSOR":
return _vol_interp(mesh_in, mesh_out, values, output)
elif out_type == "TREE":
return mesh_out._vol_avg_from_tens(mesh_in, values, output)
elif in_type == "TREE":
if out_type == "TENSOR":
return mesh_in._vol_avg_to_tens(mesh_out, values, output)
elif out_type == "TREE":
return mesh_out._vol_avg_from_tree(mesh_in, values, output)
else:
raise TypeError("Unsupported mesh types")
interpmat = deprecate_function(
interpolation_matrix, "interpmat", removal_version="1.0.0", future_warn=False
)
The origin of rotation.
Returns
-------
(n, 3) numpy.ndarray
The rotated xyz locations.
"""
# Compute rotation matrix between v0 and v1
R = rotation_matrix_from_normals(v0, v1)
if xyz.shape[1] != 3:
raise ValueError("Grid of xyz points should be n x 3")
if len(x0) != 3:
raise ValueError("x0 should have length 3")
# Define origin
X0 = np.ones([xyz.shape[0], 1]) * mkvc(x0)
return (xyz - X0).dot(R.T) + X0 # equivalent to (R*(xyz - X0)).T + X0
rotationMatrixFromNormals = deprecate_function(rotation_matrix_from_normals,
"rotationMatrixFromNormals",
removal_version="1.0.0",
future_warn=True)
rotatePointsFromNormals = deprecate_function(rotate_points_from_normals,
"rotatePointsFromNormals",
removal_version="1.0.0",
future_warn=True)
# average the normals at each vertex.
N = (nA + nB + nC + nD) / 4 # this is intrinsically weighted by area
# normalize
N = normalize(N)
else:
if normalize_normals:
N = [normalize(nA), normalize(nB), normalize(nC), normalize(nD)]
else:
N = [nA, nB, nC, nD]
# Area calculation
#
# Approximate by 4 different triangles, and divide by 2.
# Each triangle is one half of the length of the cross product
#
# So also could be viewed as the average parallelogram.
#
# TODO: This does not compute correctly for concave quadrilaterals
area = (length(nA) + length(nB) + length(nC) + length(nD)) / 4
return N, area
volTetra = deprecate_function(volume_tetrahedron,
"volTetra",
removal_version="1.0.0")
indexCube = deprecate_function(index_cube,
"indexCube",
removal_version="1.0.0")
faceInfo = deprecate_function(face_info, "faceInfo", removal_version="1.0.0")
\mathbf{Q( x ) = 0.5 x A x + b x} + c
"""
def Quadratic(x, return_g=True, return_H=True):
f = 0.5 * x.dot(A.dot(x)) + b.dot(x) + c
out = (f, )
if return_g:
g = A.dot(x) + b
out += (g, )
if return_H:
H = A
out += (H, )
return out if len(out) > 1 else out[0]
return Quadratic
# DEPRECATIONS
setupMesh = deprecate_function(setup_mesh,
"setupMesh",
removal_version="1.0.0")
Rosenbrock = deprecate_function(rosenbrock,
"Rosenbrock",
removal_version="1.0.0")
checkDerivative = deprecate_function(check_derivative,
"checkDerivative",
removal_version="1.0.0")
getQuadratic = deprecate_function(get_quadratic,
"getQuadratic",
removal_version="1.0.0")
def __init__(self, val=None):
self._val = val
def __getitem__(self, key):
if isinstance(key, slice):
return _inftup(self._val)
return self._val
def __len__(self):
return 0
def __repr__(self):
return f"({self._val}, {self._val}, ...)"
sdInv = deprecate_function(sdinv, "sdInv", removal_version="1.0.0")
getSubArray = deprecate_function(get_subarray,
"getSubArray",
removal_version="1.0.0")
inv3X3BlockDiagonal = deprecate_function(inverse_3x3_block_diagonal,
"inv3X3BlockDiagonal",
removal_version="1.0.0")
inv2X2BlockDiagonal = deprecate_function(inverse_2x2_block_diagonal,
"inv2X2BlockDiagonal",
removal_version="1.0.0")
makePropertyTensor = deprecate_function(make_property_tensor,
"makePropertyTensor",
removal_version="1.0.0")
invPropertyTensor = deprecate_function(inverse_property_tensor,
"invPropertyTensor",
removal_version="1.0.0")
# Interpolate z values on CC or N
z_xyz = z_interpolate(locations[:, :-1]).squeeze()
# Apply nearest neighbour if in extrapolation
ind_nan = np.isnan(z_xyz)
if any(ind_nan):
tree = cKDTree(xyz)
_, ind = tree.query(locations[ind_nan, :])
z_xyz[ind_nan] = xyz[ind, dim]
# Create an active bool of all True
active = np.all((locations[:, dim] < z_xyz).reshape((mesh.nC, -1),
order="F"),
axis=1)
return active.ravel()
exampleLrmGrid = deprecate_function(example_curvilinear_grid,
"exampleLrmGrid",
removal_version="1.0.0")
meshTensor = deprecate_function(unpack_widths,
"meshTensor",
removal_version="1.0.0")
closestPoints = deprecate_function(closest_points_index,
"closestPoints",
removal_version="1.0.0")
ExtractCoreMesh = deprecate_function(extract_core_mesh,
"ExtractCoreMesh",
removal_version="1.0.0")
raise ValueError(
"Input array does not have the same length as the number of cells in input mesh"
)
if output is not None and len(output) != mesh_out.nC:
raise ValueError(
"Output array does not have the same length as the number of cells in output mesh"
)
if values is not None:
values = np.asarray(values, dtype=np.float64)
if output is not None:
output = np.asarray(output, dtype=np.float64)
if in_type == "TENSOR":
if out_type == "TENSOR":
return _vol_interp(mesh_in, mesh_out, values, output)
elif out_type == "TREE":
return mesh_out._vol_avg_from_tens(mesh_in, values, output)
elif in_type == "TREE":
if out_type == "TENSOR":
return mesh_in._vol_avg_to_tens(mesh_out, values, output)
elif out_type == "TREE":
return mesh_out._vol_avg_from_tree(mesh_in, values, output)
else:
raise TypeError("Unsupported mesh types")
interpmat = deprecate_function(
interpolation_matrix, "interpmat", removal_version="1.0.0"
)