def default(self, o: Any) -> dict[str, Any]:
"""Handles JSON encoding of objects not supported by default."""
if hasattr(o, "_to_dict"):
return cast(dict, o._to_dict())
elif type(o) == type:
return obj_to_dict(o, _build=False, _name=o.__name__)
elif isinstance(o, np.ndarray):
return obj_to_dict(o, o.tolist(), _name="array")
elif isinstance(o, set):
return obj_to_dict(o, list(o))
else:
return cast(dict, JSONEncoder.default(self, o))
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(
self,
self.amplitude,
self.detuning,
self.phase,
post_phase_shift=self.post_phase_shift,
)
def _to_dict(self) -> dict[str, Any]:
# Allows for serialization of subclasses without a special _to_dict()
return obj_to_dict(
self,
self.trap_coordinates,
_module=__name__,
_name="RegisterLayout",
)
def _to_dict(self) -> dict[str, Any]:
def class_to_dict(cls: Callable) -> dict[str, Any]:
module = "numpy" if isinstance(cls, np.ufunc) else cls.__module__
return obj_to_dict(
self, _build=False, _name=cls.__name__, _module=module
)
args = list(self.args)
if isinstance(self.cls, Parametrized):
raise ValueError(
"Serialization of calls to parametrized objects is not "
"supported."
)
elif hasattr(args[0], self.cls.__name__) and inspect.isfunction(
self.cls
):
# Check for parametrized methods
if inspect.isclass(self.args[0]):
# classmethod
cls_dict = obj_to_dict(
self,
_build=False,
_name=self.cls.__name__,
_module=self.args[0].__module__,
_submodule=self.args[0].__name__,
)
args[0] = class_to_dict(self.args[0])
else:
raise NotImplementedError(
"Instance or static method "
"serialization is not supported."
)
else:
cls_dict = class_to_dict(self.cls)
return obj_to_dict(self, cls_dict, *args, **self.kwargs)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, self._layout, *self._qubit_ids)
def _to_dict(self) -> dict[str, Any]:
d = obj_to_dict(self, _build=False)
d.update(dataclasses.asdict(self))
return d
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, self._rows, self._columns, self._spacing)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, *self._waveforms)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, self._duration, self._area, self._beta)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, self.number_of_traps, self._spacing)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, self._duration, self._values, **self._kwargs)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, self._duration, self._start, self._stop)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self, self._samples)
def class_to_dict(cls: Callable) -> dict[str, Any]:
module = "numpy" if isinstance(cls, np.ufunc) else cls.__module__
return obj_to_dict(
self, _build=False, _name=cls.__name__, _module=module
)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self,
self.var,
self.key,
_module="operator",
_name="getitem")
def _to_dict(self) -> dict[str, Any]:
qs = dict(zip(self._ids, map(np.ndarray.tolist, self._coords)))
if self._layout_info is not None:
return obj_to_dict(self, qs, **(self._layout_info._asdict()))
return obj_to_dict(self, qs)
def _to_dict(self) -> dict[str, Any]:
return obj_to_dict(self,
_build=False,
_module="pulser.devices",
_name=self.name)
