def __init__(self, h_in, x0_in=None):
assert type(h_in) in [list, tuple], 'h_in must be a list'
assert len(h_in) in [1,2,3], 'h_in must be of dimension 1, 2, or 3'
h = range(len(h_in))
for i, h_i in enumerate(h_in):
if Utils.isScalar(h_i) and type(h_i) is not np.ndarray:
# This gives you something over the unit cube.
h_i = self._unitDimensions[i] * np.ones(int(h_i))/int(h_i)
elif type(h_i) is list:
h_i = Utils.meshTensor(h_i)
assert isinstance(h_i, np.ndarray), ("h[%i] is not a numpy array." % i)
assert len(h_i.shape) == 1, ("h[%i] must be a 1D numpy array." % i)
h[i] = h_i[:] # make a copy.
x0 = np.zeros(len(h))
if x0_in is not None:
assert len(h) == len(x0_in), "Dimension mismatch. x0 != len(h)"
for i in range(len(h)):
x_i, h_i = x0_in[i], h[i]
if Utils.isScalar(x_i):
x0[i] = x_i
elif x_i == '0':
x0[i] = 0.0
elif x_i == 'C':
x0[i] = -h_i.sum()*0.5
elif x_i == 'N':
x0[i] = -h_i.sum()
else:
raise Exception("x0[%i] must be a scalar or '0' to be zero, 'C' to center, or 'N' to be negative." % i)
BaseRectangularMesh.__init__(self, np.array([x.size for x in h]), x0)
# Ensure h contains 1D vectors
self._h = [Utils.mkvc(x.astype(float)) for x in h]
def __init__(self, nodes):
assert type(nodes) == list, "'nodes' variable must be a list of np.ndarray"
assert len(nodes) > 1, "len(node) must be greater than 1"
for i, nodes_i in enumerate(nodes):
assert isinstance(nodes_i, np.ndarray), ("nodes[%i] is not a numpy array." % i)
assert nodes_i.shape == nodes[0].shape, ("nodes[%i] is not the same shape as nodes[0]" % i)
assert len(nodes[0].shape) == len(nodes), "Dimension mismatch"
assert len(nodes[0].shape) > 1, "Not worth using Curv for a 1D mesh."
BaseRectangularMesh.__init__(self, np.array(nodes[0].shape)-1, None)
# Save nodes to private variable _gridN as vectors
self._gridN = np.ones((nodes[0].size, self.dim))
for i, node_i in enumerate(nodes):
self._gridN[:, i] = Utils.mkvc(node_i.astype(float))
def __init__(self, nodes):
assert type(nodes) == list, "'nodes' variable must be a list of np.ndarray"
assert len(nodes) > 1, "len(node) must be greater than 1"
for i, nodes_i in enumerate(nodes):
assert isinstance(nodes_i, np.ndarray), ("nodes[%i] is not a numpy array." % i)
assert nodes_i.shape == nodes[0].shape, ("nodes[%i] is not the same shape as nodes[0]" % i)
assert len(nodes[0].shape) == len(nodes), "Dimension mismatch"
assert len(nodes[0].shape) > 1, "Not worth using Curv for a 1D mesh."
BaseRectangularMesh.__init__(self, np.array(nodes[0].shape)-1, None)
# Save nodes to private variable _gridN as vectors
self._gridN = np.ones((nodes[0].size, self.dim))
for i, node_i in enumerate(nodes):
self._gridN[:, i] = Utils.mkvc(node_i.astype(float))
def __init__(self, h_in, x0_in=None):
assert type(h_in) in [list, tuple], 'h_in must be a list'
assert len(h_in) in [1, 2, 3], 'h_in must be of dimension 1, 2, or 3'
h = range(len(h_in))
for i, h_i in enumerate(h_in):
if Utils.isScalar(h_i) and type(h_i) is not np.ndarray:
# This gives you something over the unit cube.
h_i = self._unitDimensions[i] * np.ones(int(h_i)) / int(h_i)
elif type(h_i) is list:
h_i = Utils.meshTensor(h_i)
assert isinstance(h_i,
np.ndarray), ("h[%i] is not a numpy array." % i)
assert len(h_i.shape) == 1, ("h[%i] must be a 1D numpy array." % i)
h[i] = h_i[:] # make a copy.
x0 = np.zeros(len(h))
if x0_in is not None:
assert len(h) == len(x0_in), "Dimension mismatch. x0 != len(h)"
for i in range(len(h)):
x_i, h_i = x0_in[i], h[i]
if Utils.isScalar(x_i):
x0[i] = x_i
elif x_i == '0':
x0[i] = 0.0
elif x_i == 'C':
x0[i] = -h_i.sum() * 0.5
elif x_i == 'N':
x0[i] = -h_i.sum()
else:
raise Exception(
"x0[%i] must be a scalar or '0' to be zero, 'C' to center, or 'N' to be negative."
% i)
if isinstance(self, BaseRectangularMesh):
BaseRectangularMesh.__init__(self, np.array([x.size for x in h]),
x0)
else:
BaseMesh.__init__(self, np.array([x.size for x in h]), x0)
# Ensure h contains 1D vectors
self._h = [Utils.mkvc(x.astype(float)) for x in h]
