def __mul__(self, arg):
if descriptors.is_lazy(arg):
return lazy_expressions.make_lazy(self) * arg
else:
res = self.copy()
res *= arg
return res
def __idiv__(self, arg):
""" If arg is a scalar, simple scalar multiplication
"""
if descriptors.is_lazy(arg): return lazy_expressions.make_lazy(self) / arg
if descriptors.is_scalar(arg):
self.data /= arg
self.tail /= arg
else:
raise RuntimeError, " argument type not recognized in imul for %s"%arg
return self
def __imul__(self, arg):
if descriptor_base.is_lazy(arg):
return lazy_expressions.make_lazy(self) * arg
# If arg is a Gf
if isinstance(arg, Gf):
assert type(self.mesh) == type(
arg.mesh
), "Can not multiply two Gf with meshes of different type"
assert self.mesh == arg.mesh, "Can not use in-place multiplication for two Gf with different mesh"
self.__imul__impl(arg)
elif isinstance(arg, numbers.Number):
self._data[:] *= arg
else:
assert False, "Invalid operand type for Gf in-place multiplication"
return self
def __iadd__(self, arg):
if descriptor_base.is_lazy(arg):
return lazy_expressions.make_lazy(self) + arg
if isinstance(arg, Gf):
assert type(self.mesh) == type(
arg.mesh), "Can not add two Gf with meshes of different type"
assert self.mesh == arg.mesh, "Can not add two Gf with different mesh"
self._data += arg._data
else:
if self._target_rank != 2 and not isinstance(arg, np.ndarray):
self._data[:] += arg
elif self._target_rank == 2:
wrapped_aux._iadd_g_matrix_scalar(self, arg)
else:
raise NotImplemented
return self
def __imul__(self, arg):
if descriptor_base.is_lazy(arg):
return lazy_expressions.make_lazy(self) * arg
# If arg is a Gf
if isinstance(arg, Gf):
assert type(self.mesh) == type(
arg.mesh
), "Can not multiply two Gf with meshes of different type"
assert self.mesh == arg.mesh, "Can not use in-place multiplication for two Gf with different mesh"
self.__imul__impl(arg)
elif isinstance(arg, numbers.Number):
self._data[:] *= arg
elif isinstance(arg, np.ndarray):
assert len(
arg.shape) == 2, "Multiplication only supported for matrices"
assert len(
self.target_shape
) == 2, "Multiplication only supported for matrix_valued Gfs"
self.data[:] = np.dot(self.data, arg)
else:
assert False, "Invalid operand type for Gf in-place multiplication"
return self
def __idiv__(self, arg):
if descriptor_base.is_lazy(arg):
return lazy_expressions.make_lazy(self) / arg
self._data[:] /= arg
return self
def div_precall(self, y):
if descriptor_base.is_lazy(y): return lazy_expressions.make_lazy(self) / y
def __rmul__(self, arg):
if descriptors.is_lazy(arg):
return arg * lazy_expressions.make_lazy(self)
elif descriptors.is_scalar(arg):
return self.__mul__(arg)
def __sub__(self, y):
if descriptors.is_lazy(y): return lazy_expressions.make_lazy(self) - y
c = self.copy()
return self.__sub_isub_impl(c,y,True)