def jacobian(self, params, unknowns, resids):
"""
Uses complex step method to calculate a Jacobian dict.
Returns
-------
dict
A jacobian dict
"""
# our complex step
step = self.complex_stepsize * 1j
J = {}
for param, pmeta in params.items():
pwrap = TmpDict(params)
pval = params[param]
if isinstance(pval, ndarray):
# replace the param array with a complex copy
pwrap[param] = numpy.asarray(params[param], complex)
idx_iter = array_idx_iter(pwrap[param].shape)
psize = pval.size
else:
pwrap[param] = complex(params[param])
idx_iter = (None,)
psize = 1
for i,idx in enumerate(idx_iter):
# set a complex param value
if idx is None:
pwrap[param] += step
else:
pwrap[param][idx] += step
uwrap = TmpDict(unknowns, complex=True)
# solve with complex param value
self.solve_nonlinear(pwrap, uwrap, resids)
for u in unknowns:
jval = imag(uwrap[u] / self.complex_stepsize)
if (u,param) not in J: # create the dict entry
J[(u,param)] = numpy.zeros((jval.size, psize))
# set the column in the Jacobian entry
J[(u,param)][:,i] = jval.flat
# restore old param value
if idx is None:
pwrap[param] -= step
else:
pwrap[param][idx] -= step
return J
def jacobian(self, params, unknowns, resids):
"""
Uses complex step method to calculate a Jacobian dict.
Args
----
params : `VecWrapper`
`VecWrapper` containing parameters. (p)
unknowns : `VecWrapper`
`VecWrapper` containing outputs and states. (u)
resids : `VecWrapper`
`VecWrapper` containing residuals. (r)
Returns
-------
dict
Dictionary whose keys are tuples of the form ('unknown', 'param')
and whose values are ndarrays.
"""
# our complex step
step = self.complex_stepsize * 1j
J = {}
for param in params:
pwrap = TmpDict(params)
pval = params[param]
if isinstance(pval, ndarray):
# replace the param array with a complex copy
pwrap[param] = numpy.asarray(params[param], complex)
idx_iter = array_idx_iter(pwrap[param].shape)
psize = pval.size
else:
pwrap[param] = complex(params[param])
idx_iter = (None,)
psize = 1
for i, idx in enumerate(idx_iter):
# set a complex param value
if idx is None:
pwrap[param] += step
else:
pwrap[param][idx] += step
uwrap = TmpDict(unknowns, complex=True)
# solve with complex param value
self.solve_nonlinear(pwrap, uwrap, resids)
for u in unknowns:
jval = imag(uwrap[u] / self.complex_stepsize)
if (u, param) not in J: # create the dict entry
J[(u, param)] = numpy.zeros((jval.size, psize))
# set the column in the Jacobian entry
J[(u, param)][:, i] = jval.flat
# restore old param value
if idx is None:
pwrap[param] -= step
else:
pwrap[param][idx] -= step
return J
