def generate_subs(deriv_order, function, index):
dim = retrieve_dimensions(index)[0]
if dim.is_Time:
fd_order = function.time_order
elif dim.is_Space:
fd_order = function.space_order
else:
# Shouldn't arrive here
raise TypeError("Dimension type not recognised")
subs = {}
mapper = {dim: index}
indices, x0 = generate_indices(function, dim,
fd_order, side=None, x0=mapper)
coeffs = sympy.finite_diff_weights(deriv_order, indices, x0)[-1][-1]
for j in range(len(coeffs)):
subs.update({function._coeff_symbol
(indices[j], deriv_order, function, index): coeffs[j]})
return subs
def generate_subs(deriv_order, function, dim):
if dim.is_Time:
fd_order = function.time_order
elif dim.is_Space:
fd_order = function.space_order
else:
# Shouldn't arrive here
raise TypeError("Dimension type not recognised")
side = form_side((dim, ), function)
stagger = side.get(dim)
subs = {}
indices, x0 = generate_indices(function,
dim,
dim.spacing,
fd_order,
side=None,
stagger=stagger)
coeffs = sympy.finite_diff_weights(deriv_order, indices, x0)[-1][-1]
for j in range(len(coeffs)):
subs.update({
function._coeff_symbol(indices[j], deriv_order, function, dim):
coeffs[j]
})
return subs
def generate_subs(i):
deriv_order = i.deriv_order
function = i.function
dim = i.dimension
weights = i.weights
if isinstance(weights, np.ndarray):
fd_order = len(weights)-1
else:
fd_order = weights.shape[-1]-1
subs = {}
indices, x0 = generate_indices(function, dim, fd_order, side=None)
# NOTE: This implementation currently assumes that indices are ordered
# according to their position in the FD stencil. This may not be the
# case in all schemes and should be changed such that the weights are
# passed as a dictionary of the form {pos: w} (or something similar).
if isinstance(weights, np.ndarray):
for j in range(len(weights)):
subs.update({function._coeff_symbol
(indices[j], deriv_order, function, dim): weights[j]})
else:
shape = weights.shape
x = weights.dimensions
for j in range(shape[-1]):
idx = list(x)
idx[-1] = j
subs.update({function._coeff_symbol
(indices[j], deriv_order, function, dim):
weights[as_tuple(idx)]})
return subs
def generate_subs(i):
deriv_order = i.deriv_order
function = i.function
dim = i.dimension
weights = i.weights
fd_order = len(weights) - 1
side = form_side((dim, ), function)
stagger = side.get(dim)
subs = {}
indices, x0 = generate_indices(function,
dim,
dim.spacing,
fd_order,
side=None,
stagger=stagger)
for j in range(len(weights)):
subs.update({
function._coeff_symbol(indices[j], deriv_order, function, dim):
weights[j]
})
return subs