Hi,
I'd like to create a generic UFL operator by inheriting from ufl.MathFunction. It's an approach I've used before and it works.
The problem here is in the format function that I use to generate c++ code for that operator. I'd like to be able to call the "map_function" which is a python object into the code generate by ffc.
How to generate the right call_to_map_function string below? Is it even possible?
def nonlinear_function_evaluate(map_function,n, x):
return map_function(x,n)
class NonlinearFunction(MathFunction):
def __new__(cls, map_function, n, argument):
if isinstance(argument, (ScalarValue, Zero)):
return FloatValue(nonlinear_function_evaluate(map_function,
n,
float(argument)
)
)
return MathFunction.__new__(cls)
def evaluate(self, x, mapping, component, index_values, derivatives=()):
#print x, mapping, component, index_values
a = self._argument.evaluate(x, mapping, component, index_values)
map_function = self._map_function
n = self._n
return nonlinear_function_evaluate(map_function, n, a)
def __init__(self, map_function, n, argument):
self._map_function = map_function;
self._n = n
MathFunction.__init__(self, map_function.name()+'eval_derivatives_'+str(n),
argument)
self._argument = argument
def _ufl_expr_reconstruct_(self, argument):
"Return a new object of the same type with new operands."
return self.__class__(self._map_function, self._n , argument)
def derivative(self, ):
"""Used in ufl.algorithms.forward_ad"""
return self.__class__(self._map_function, self._n+1, self._argument)
def format(self,v):
map_function = self._map_function.name()
return "call_to_map_function("+v+")"
