def __init__(self, products=None, estimator=None, visualizer=None,
name=None, **kwargs):
products = FrozenDict(products or {})
if products:
for k, v in products.items():
setattr(self, f'{k}_product', v)
setattr(self, f'{k}_norm', induced_norm(v))
self.__auto_init(locals())
class DiscretizationBase(DiscretizationInterface):
"""Base class for |Discretizations| providing some common functionality."""
sid_ignore = DiscretizationInterface.sid_ignore | {'visualizer'}
add_with_arguments = DiscretizationInterface.add_with_arguments | {'operators'}
special_operators = frozenset()
def __init__(self, operators=None, products=None, estimator=None, visualizer=None,
cache_region=None, name=None, **kwargs):
operators = {} if operators is None else dict(operators)
# handle special operators
for on in self.special_operators:
# special operators must be provided as keyword argument to __init__
assert on in kwargs
# special operators may not already exist as attributes
assert not hasattr(self, on)
# special operators may not be contained in operators dict
assert on not in operators
op = kwargs[on]
# operators either have to be None or an Operator
assert op is None \
or isinstance(op, OperatorInterface) \
or all(isinstance(o, OperatorInterface) for o in op)
# set special operator as an attribute
setattr(self, on, op)
# add special operator to the operators dict
operators[on] = op
self.operators = FrozenDict(operators)
self.linear = all(op is None or op.linear for op in operators.values())
self.products = FrozenDict(products or {})
self.estimator = estimator
self.visualizer = visualizer
self.enable_caching(cache_region)
self.name = name
if products:
for k, v in products.items():
setattr(self, '{}_product'.format(k), v)
setattr(self, '{}_norm'.format(k), induced_norm(v))
self.build_parameter_type(*operators.values())
def with_(self, **kwargs):
assert set(kwargs.keys()) <= self.with_arguments
if 'operators' in kwargs:
# extract special operators from provided operators dict
operators = kwargs['operators'].copy()
for on in self.special_operators:
if on in operators:
assert on not in kwargs or kwargs[on] == operators[on]
kwargs[on] = operators.pop(on)
kwargs['operators'] = operators
else:
# when an operators dict is not specified make sure that we use the old operators dict
# but without the special operators
kwargs['operators'] = {on: op for on, op in self.operators.items()
if on not in self.special_operators}
# delete empty 'operators' dicts for cases where __init__ does not take
# an 'operator' argument
if 'operators' not in self._init_arguments:
operators = kwargs.pop('operators')
# in that case, there should not be any operators left in 'operators'
assert not operators
return super(DiscretizationBase, self).with_(**kwargs)
def visualize(self, U, **kwargs):
"""Visualize a solution |VectorArray| U.
Parameters
----------
U
The |VectorArray| from
:attr:`~pymor.discretizations.interfaces.DiscretizationInterface.solution_space`
that shall be visualized.
kwargs
See docstring of `self.visualizer.visualize`.
"""
if self.visualizer is not None:
self.visualizer.visualize(U, self, **kwargs)
else:
raise NotImplementedError('Discretization has no visualizer.')
def estimate(self, U, mu=None):
if self.estimator is not None:
return self.estimator.estimate(U, mu=mu, d=self)
else:
raise NotImplementedError('Discretization has no estimator.')
class DiscretizationBase(DiscretizationInterface):
"""Base class for |Discretizations| providing some common functionality."""
sid_ignore = DiscretizationInterface.sid_ignore | {'visualizer'}
add_with_arguments = DiscretizationInterface.add_with_arguments | {'operators'}
special_operators = frozenset()
def __init__(self, operators=None, products=None, estimator=None, visualizer=None,
cache_region=None, name=None, **kwargs):
operators = {} if operators is None else dict(operators)
# handle special operators
for on in self.special_operators:
# special operators must be provided as keyword argument to __init__
assert on in kwargs
# special operators may not already exist as attributes
assert not hasattr(self, on)
# special operators may not be contained in operators dict
assert on not in operators
op = kwargs[on]
# operators either have to be None or an Operator
assert op is None \
or isinstance(op, OperatorInterface) \
or all(isinstance(o, OperatorInterface) for o in op)
# set special operator as an attribute
setattr(self, on, op)
# add special operator to the operators dict
operators[on] = op
self.operators = FrozenDict(operators)
self.linear = all(op is None or op.linear for op in operators.values())
self.products = FrozenDict(products or {})
self.estimator = estimator
self.visualizer = visualizer
self.enable_caching(cache_region)
self.name = name
if products:
for k, v in products.items():
setattr(self, '{}_product'.format(k), v)
setattr(self, '{}_norm'.format(k), induced_norm(v))
self.build_parameter_type(*operators.values())
def with_(self, **kwargs):
assert set(kwargs.keys()) <= self.with_arguments
if 'operators' in kwargs:
# extract special operators from provided operators dict
operators = kwargs['operators'].copy()
for on in self.special_operators:
if on in operators:
assert on not in kwargs or kwargs[on] == operators[on]
kwargs[on] = operators.pop(on)
kwargs['operators'] = operators
else:
# when an operators dict is not specified make sure that we use the old operators dict
# but without the special operators
kwargs['operators'] = {on: op for on, op in self.operators.items()
if on not in self.special_operators}
# delete empty 'operators' dicts for cases where __init__ does not take
# an 'operator' argument
if 'operators' not in self._init_arguments:
operators = kwargs.pop('operators')
# in that case, there should not be any operators left in 'operators'
assert not operators
return super(DiscretizationBase, self).with_(**kwargs)
def visualize(self, U, **kwargs):
"""Visualize a solution |VectorArray| U.
Parameters
----------
U
The |VectorArray| from
:attr:`~pymor.discretizations.interfaces.DiscretizationInterface.solution_space`
that shall be visualized.
kwargs
See docstring of `self.visualizer.visualize`.
"""
if self.visualizer is not None:
self.visualizer.visualize(U, self, **kwargs)
else:
raise NotImplementedError('Discretization has no visualizer.')
def estimate(self, U, mu=None):
if self.estimator is not None:
return self.estimator.estimate(U, mu=mu, discretization=self)
else:
raise NotImplementedError('Discretization has no estimator.')
