tidy3d.plugins.adjoint.JaxPermittivityDataset
tidy3d.plugins.adjoint.JaxPermittivityDataset#
- class tidy3d.plugins.adjoint.JaxPermittivityDataset#
- Bases: - tidy3d.components.data.dataset.PermittivityDataset,- tidy3d.plugins.adjoint.components.base.JaxObject- A - PermittivityDatasetregistered with jax.- Parameters
- eps_xx (JaxDataArray) – Spatial distribution of the xx-component of the relative permittivity. 
- eps_yy (JaxDataArray) – Spatial distribution of the yy-component of the relative permittivity. 
- eps_zz (JaxDataArray) – Spatial distribution of the zz-component of the relative permittivity. 
 
 - Show JSON schema- { "title": "JaxPermittivityDataset", "description": "A :class:`.PermittivityDataset` registered with jax.\n\nParameters\n----------\neps_xx : JaxDataArray\n Spatial distribution of the xx-component of the relative permittivity.\neps_yy : JaxDataArray\n Spatial distribution of the yy-component of the relative permittivity.\neps_zz : JaxDataArray\n Spatial distribution of the zz-component of the relative permittivity.", "type": "object", "properties": { "type": { "title": "Type", "default": "JaxPermittivityDataset", "enum": [ "JaxPermittivityDataset" ], "type": "string" }, "eps_xx": { "title": "Epsilon xx", "description": "Spatial distribution of the xx-component of the relative permittivity.", "jax_field": true, "allOf": [ { "$ref": "#/definitions/JaxDataArray" } ] }, "eps_yy": { "title": "Epsilon yy", "description": "Spatial distribution of the yy-component of the relative permittivity.", "jax_field": true, "allOf": [ { "$ref": "#/definitions/JaxDataArray" } ] }, "eps_zz": { "title": "Epsilon zz", "description": "Spatial distribution of the zz-component of the relative permittivity.", "jax_field": true, "allOf": [ { "$ref": "#/definitions/JaxDataArray" } ] } }, "required": [ "eps_xx", "eps_yy", "eps_zz" ], "additionalProperties": false, "definitions": { "JaxDataArray": { "title": "JaxDataArray", "description": "A :class:`.DataArray`-like class that only wraps xarray for jax compability.\n\nParameters\n----------\nvalues : Optional[Any]\n Nested list containing the raw values, which can be tracked by jax.\ncoords : Mapping[str, list]\n Dictionary storing the coordinates, namely ``(direction, f, mode_index)``.", "type": "object", "properties": { "values": { "title": "Values", "description": "Nested list containing the raw values, which can be tracked by jax.", "jax_field": true }, "coords": { "title": "Coords", "description": "Dictionary storing the coordinates, namely ``(direction, f, mode_index)``.", "type": "object", "additionalProperties": { "type": "array", "items": {} } }, "type": { "title": "Type", "default": "JaxDataArray", "enum": [ "JaxDataArray" ], "type": "string" } }, "required": [ "values", "coords" ], "additionalProperties": false } } } - attribute eps_xx: tidy3d.plugins.adjoint.components.data.data_array.JaxDataArray [Required]#
- Spatial distribution of the xx-component of the relative permittivity. 
 - attribute eps_yy: tidy3d.plugins.adjoint.components.data.data_array.JaxDataArray [Required]#
- Spatial distribution of the yy-component of the relative permittivity. 
 - attribute eps_zz: tidy3d.plugins.adjoint.components.data.data_array.JaxDataArray [Required]#
- Spatial distribution of the zz-component of the relative permittivity. 
 - classmethod add_type_field() None#
- Automatically place “type” field with model name in the model field dictionary. 
 - colocate(x=None, y=None, z=None) xarray.core.dataset.Dataset#
- colocate all of the data at a set of x, y, z coordinates. - Parameters
- x (Optional[array-like] = None) – x coordinates of locations. If not supplied, does not try to colocate on this dimension. 
- y (Optional[array-like] = None) – y coordinates of locations. If not supplied, does not try to colocate on this dimension. 
- z (Optional[array-like] = None) – z coordinates of locations. If not supplied, does not try to colocate on this dimension. 
 
- Returns
- Dataset containing all fields at the same spatial locations. For more details refer to xarray’s Documentaton. 
- Return type
- xr.Dataset 
 - Note - For many operations (such as flux calculations and plotting), it is important that the fields are colocated at the same spatial locations. Be sure to apply this method to your field data in those cases. 
 - classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model#
- Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values 
 - copy(**kwargs) tidy3d.components.base.Tidy3dBaseModel#
- Copy a Tidy3dBaseModel. With - deep=Trueas default.
 - dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny#
- Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. 
 - classmethod dict_from_file(fname: str, group_path: Optional[str] = None) dict#
- Loads a dictionary containing the model from a .yaml, .json, or .hdf5 file. - Parameters
- fname (str) – Full path to the .yaml or .json file to load the - Tidy3dBaseModelfrom.
- group_path (str, optional) – Path to a group inside the file to use as the base level. 
 
- Returns
- A dictionary containing the model. 
- Return type
- dict 
 - Example - >>> simulation = Simulation.from_file(fname='folder/sim.json') 
 - classmethod dict_from_hdf5(fname: str, group_path: str = '') dict#
- Loads a dictionary containing the model contents from a .hdf5 file. - Parameters
- fname (str) – Full path to the .hdf5 file to load the - Tidy3dBaseModelfrom.
- group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only. 
 
- Returns
- Dictionary containing the model. 
- Return type
- dict 
 - Example - >>> sim_dict = Simulation.dict_from_hdf5(fname='folder/sim.hdf5') 
 - classmethod dict_from_json(fname: str) dict#
- Load dictionary of the model from a .json file. - Parameters
- fname (str) – Full path to the .json file to load the - Tidy3dBaseModelfrom.
- Returns
- A dictionary containing the model. 
- Return type
- dict 
 - Example - >>> sim_dict = Simulation.dict_from_json(fname='folder/sim.json') 
 - classmethod dict_from_yaml(fname: str) dict#
- Load dictionary of the model from a .yaml file. - Parameters
- fname (str) – Full path to the .yaml file to load the - Tidy3dBaseModelfrom.
- Returns
- A dictionary containing the model. 
- Return type
- dict 
 - Example - >>> sim_dict = Simulation.dict_from_yaml(fname='folder/sim.yaml') 
 - classmethod from_file(fname: str, group_path: Optional[str] = None, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
- Loads a - Tidy3dBaseModelfrom .yaml, .json, or .hdf5 file.- Parameters
- fname (str) – Full path to the .yaml or .json file to load the - Tidy3dBaseModelfrom.
- group_path (str, optional) – Path to a group inside the file to use as the base level. Only for - .hdf5files. Starting / is optional.
- **parse_obj_kwargs – Keyword arguments passed to either pydantic’s - parse_objfunction when loading model.
 
- Returns
- An instance of the component class calling load. 
- Return type
- Tidy3dBaseModel
 - Example - >>> simulation = Simulation.from_file(fname='folder/sim.json') 
 - classmethod from_hdf5(fname: str, group_path: str = '', **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
- Loads - Tidy3dBaseModelinstance to .hdf5 file.- Parameters
- fname (str) – Full path to the .hdf5 file to load the - Tidy3dBaseModelfrom.
- group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only. Starting / is optional. 
- **parse_obj_kwargs – Keyword arguments passed to pydantic’s - parse_objmethod.
 
 - Example - >>> simulation.to_hdf5(fname='folder/sim.hdf5') 
 - classmethod from_json(fname: str, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
- Load a - Tidy3dBaseModelfrom .json file.- Parameters
- fname (str) – Full path to the .json file to load the - Tidy3dBaseModelfrom.
- Returns
- Tidy3dBaseModel– An instance of the component class calling load.
- **parse_obj_kwargs – Keyword arguments passed to pydantic’s - parse_objmethod.
 
 - Example - >>> simulation = Simulation.from_json(fname='folder/sim.json') 
 - classmethod from_orm(obj: Any) Model#
 - classmethod from_tidy3d(tidy3d_obj: tidy3d.components.base.Tidy3dBaseModel) tidy3d.plugins.adjoint.components.base.JaxObject#
- Convert - Tidy3dBaseModelinstance to- JaxObject.
 - classmethod from_yaml(fname: str, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#
- Loads - Tidy3dBaseModelfrom .yaml file.- Parameters
- fname (str) – Full path to the .yaml file to load the - Tidy3dBaseModelfrom.
- **parse_obj_kwargs – Keyword arguments passed to pydantic’s - parse_objmethod.
 
- Returns
- An instance of the component class calling from_yaml. 
- Return type
- Tidy3dBaseModel
 - Example - >>> simulation = Simulation.from_yaml(fname='folder/sim.yaml') 
 - classmethod generate_docstring() str#
- Generates a docstring for a Tidy3D mode and saves it to the __doc__ of the class. 
 - classmethod get_jax_field_names() List[str]#
- Returns list of field names that have a - jax_field_type.
 - classmethod get_sub_model(group_path: str, model_dict: dict | list) dict#
- Get the sub model for a given group path. 
 - static get_tuple_group_name(index: int) str#
- Get the group name of a tuple element. 
 - static get_tuple_index(key_name: str) int#
- Get the index into the tuple based on its group name. 
 - help(methods: bool = False) None#
- Prints message describing the fields and methods of a - Tidy3dBaseModel.- Parameters
- methods (bool = False) – Whether to also print out information about object’s methods. 
 - Example - >>> simulation.help(methods=True) 
 - json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode#
- Generate a JSON representation of the model, include and exclude arguments as per dict(). - encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). 
 - classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) Model#
 - classmethod parse_obj(obj: Any) Model#
 - classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) Model#
 - classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny#
 - classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode#
 - to_file(fname: str) None#
- Exports - Tidy3dBaseModelinstance to .yaml, .json, or .hdf5 file- Parameters
- fname (str) – Full path to the .yaml or .json file to save the - Tidy3dBaseModelto.
 - Example - >>> simulation.to_file(fname='folder/sim.json') 
 - to_hdf5(fname: str) None#
- Exports - Tidy3dBaseModelinstance to .hdf5 file.- Parameters
- fname (str) – Full path to the .hdf5 file to save the - Tidy3dBaseModelto.
 - Example - >>> simulation.to_hdf5(fname='folder/sim.hdf5') 
 - to_json(fname: str) None#
- Exports - Tidy3dBaseModelinstance to .json file- Parameters
- fname (str) – Full path to the .json file to save the - Tidy3dBaseModelto.
 - Example - >>> simulation.to_json(fname='folder/sim.json') 
 - to_yaml(fname: str) None#
- Exports - Tidy3dBaseModelinstance to .yaml file.- Parameters
- fname (str) – Full path to the .yaml file to save the - Tidy3dBaseModelto.
 - Example - >>> simulation.to_yaml(fname='folder/sim.yaml') 
 - tree_flatten() Tuple[list, dict]#
- How to flatten a - JaxObjectinstance into a pytree.
 - classmethod tree_unflatten(aux_data: dict, children: list) tidy3d.plugins.adjoint.components.base.JaxObject#
- How to unflatten a pytree into a - JaxObjectinstance.
 - classmethod tuple_to_dict(tuple_values: tuple) dict#
- How we generate a dictionary mapping new keys to tuple values for hdf5. 
 - classmethod update_forward_refs(**localns: Any) None#
- Try to update ForwardRefs on fields based on this Model, globalns and localns. 
 - updated_copy(**kwargs) tidy3d.components.base.Tidy3dBaseModel#
- Make copy of a component instance with - **kwargsindicating updated field values.
 - classmethod validate(value: Any) Model#
 - property field_components: Dict[str, tidy3d.components.data.data_array.ScalarFieldDataArray]#
- Maps the field components to thier associated data. 
 - property grid_locations: Dict[str, str]#
- Maps field components to the string key of their grid locations on the yee lattice. 
 - property symmetry_eigenvalues: Dict[str, Callable[[Literal[0, 1, 2]], float]]#
- Maps field components to their (positive) symmetry eigenvalues.