def initialize_for_solve(self):
if hasattr(self, 'f'):
# If f is input in form of f(u,t), wrap f to f_f77 for Fortran code.
f = self.f
self.f_f77 = lambda t,u: np.asarray(f(u,t))
elif hasattr(self, 'f_f77'):
# If f is input in form of f(t,u) (usually in Fortran),
# wrap f_f77 to the general form f(u,t) for switch_to()
f_f77 = self.f_f77
self.f = lambda u,t: np.asarray(f_f77(t,u))
Solver.initialize_for_solve(self)
def initialize_for_solve(self):
# INFO(4) is an integer array to specify how the problem
# is to be solved
self.info = np.zeros(4, int)
self.info[0] = 1 # Compute solution at each time point
if hasattr(self, 'spcrad_f77') or hasattr(self, 'spcrad'):
self.info[1] = 1 # SPCRAD routine is supplied
else:
self.spcrad = lambda x,y: 0.0 # dummy function
# Is the Jacobian constant?
self.info[2] = self.jac_constant
if (np.iterable(self.atol) and (len(self.atol) == self.neq)):
self.info[3] = 1 # ATOL is a sequence of length NEQ
if hasattr(self, 'f'):
# If f is input in form of a Python function f(u,t),
# let self.f_f77 wrap f and have arguments t, u.
f = self.f
self.f_f77 = lambda t,u: np.asarray(f(u,t))
elif hasattr(self, 'f_f77'):
# The right-hand side "f" is input as a Fortran function
# taking the arguments t,u.
# Set self.f to be f_f77 wrapped to the general form f(u,t)
# for switch_to().
f_f77 = self.f_f77
self.f = lambda u,t: np.asarray(f_f77(t,u))
# If spcrad is input in form of spcrad(u,t),
# wrap spcrad to spcrad_f77 for Fortran code.
if hasattr(self, 'spcrad'):
# If spcrad is in form of spcrad(u,t), wrap for Fortran code.
spcrad = self.spcrad
self.spcrad_f77 = lambda t,u: np.asarray(spcrad(u,t))
# We call Solver and not Adaptive below because Adaptive
# just computes first_step, min_step and max_step, all of
# which are non-used parameters for rkc.f
Solver.initialize_for_solve(self) # Common settings
