def random(self, count=1, distribution='uniform', random_state=None, seed=None, reserve=0, **kwargs):
assert count >= 0
assert reserve >= 0
assert random_state is None or seed is None
random_state = get_random_state(random_state, seed)
va = self.zeros(count, reserve)
va._array[:count] = _create_random_values((count, self.dim), distribution, random_state, **kwargs)
return va
def random(self, count=1, distribution='uniform', random_state=None, seed=None, reserve=0, **kwargs):
assert count >= 0
assert reserve >= 0
assert random_state is None or seed is None
random_state = get_random_state(random_state, seed)
va = self.zeros(count, reserve)
va._array[:count] = _create_random_values((count, self.dim), distribution, random_state, **kwargs)
return va
def random_vector(self, distribution, random_state, **kwargs):
impl = df.Function(self.V).vector()
values = _create_random_values(impl.local_size(), distribution, random_state, **kwargs)
impl[:] = values
return FenicsVector(impl)
def random_vector(self, distribution, random_state, **kwargs):
values = _create_random_values(self.dim, distribution, random_state,
**kwargs)
return self.vector_from_numpy(values)
def random_vector(self, distribution, random_state, **kwargs):
values = _create_random_values(self.dim, distribution, random_state, **kwargs)
return self.vector_from_numpy(values)
def random_vector(self, distribution, random_state, **kwargs):
impl = df.Function(self.V).vector()
values = _create_random_values(impl.local_size(), distribution, random_state, **kwargs)
impl[:] = values
return FenicsVector(impl)
