tidy3d.PermittivityDataset#

class tidy3d.PermittivityDataset#

Bases: tidy3d.components.data.dataset.AbstractFieldDataset

Dataset storing the diagonal components of the permittivity tensor.

Parameters

  • eps_xx (ScalarFieldDataArray) – Spatial distribution of the xx-component of the relative permittivity.

  • eps_yy (ScalarFieldDataArray) – Spatial distribution of the yy-component of the relative permittivity.

  • eps_zz (ScalarFieldDataArray) – Spatial distribution of the zz-component of the relative permittivity.

Example

>>> x = [-1,1]
>>> y = [-2,0,2]
>>> z = [-3,-1,1,3]
>>> f = [2e14, 3e14]
>>> coords = dict(x=x, y=y, z=z, f=f)
>>> sclr_fld = ScalarFieldDataArray((1+1j) * np.random.random((2,3,4,2)), coords=coords)
>>> data = PermittivityDataset(eps_xx=sclr_fld, eps_yy=sclr_fld, eps_zz=sclr_fld)

Show JSON schema
{
   "title": "PermittivityDataset",
   "description": "Dataset storing the diagonal components of the permittivity tensor.\n\nParameters\n----------\neps_xx : ScalarFieldDataArray\n    Spatial distribution of the xx-component of the relative permittivity.\neps_yy : ScalarFieldDataArray\n    Spatial distribution of the yy-component of the relative permittivity.\neps_zz : ScalarFieldDataArray\n    Spatial distribution of the zz-component of the relative permittivity.\n\nExample\n-------\n>>> x = [-1,1]\n>>> y = [-2,0,2]\n>>> z = [-3,-1,1,3]\n>>> f = [2e14, 3e14]\n>>> coords = dict(x=x, y=y, z=z, f=f)\n>>> sclr_fld = ScalarFieldDataArray((1+1j) * np.random.random((2,3,4,2)), coords=coords)\n>>> data = PermittivityDataset(eps_xx=sclr_fld, eps_yy=sclr_fld, eps_zz=sclr_fld)",
   "type": "object",
   "properties": {
      "type": {
         "title": "Type",
         "default": "PermittivityDataset",
         "enum": [
            "PermittivityDataset"
         ],
         "type": "string"
      },
      "eps_xx": {
         "title": "DataArray",
         "description": "Spatial distribution of the xx-component of the relative permittivity.",
         "type": "xr.DataArray",
         "properties": {
            "_dims": {
               "title": "_dims",
               "type": "Tuple[str, ...]"
            }
         },
         "required": [
            "_dims"
         ]
      },
      "eps_yy": {
         "title": "DataArray",
         "description": "Spatial distribution of the yy-component of the relative permittivity.",
         "type": "xr.DataArray",
         "properties": {
            "_dims": {
               "title": "_dims",
               "type": "Tuple[str, ...]"
            }
         },
         "required": [
            "_dims"
         ]
      },
      "eps_zz": {
         "title": "DataArray",
         "description": "Spatial distribution of the zz-component of the relative permittivity.",
         "type": "xr.DataArray",
         "properties": {
            "_dims": {
               "title": "_dims",
               "type": "Tuple[str, ...]"
            }
         },
         "required": [
            "_dims"
         ]
      }
   },
   "required": [
      "eps_xx",
      "eps_yy",
      "eps_zz"
   ],
   "additionalProperties": false
}

attribute eps_xx: tidy3d.components.data.data_array.ScalarFieldDataArray [Required]#

Spatial distribution of the xx-component of the relative permittivity.

Constraints

  • title = DataArray

  • type = xr.DataArray

  • properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}

  • required = [‘_dims’]

attribute eps_yy: tidy3d.components.data.data_array.ScalarFieldDataArray [Required]#

Spatial distribution of the yy-component of the relative permittivity.

Constraints

  • title = DataArray

  • type = xr.DataArray

  • properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}

  • required = [‘_dims’]

attribute eps_zz: tidy3d.components.data.data_array.ScalarFieldDataArray [Required]#

Spatial distribution of the zz-component of the relative permittivity.

Constraints

  • title = DataArray

  • type = xr.DataArray

  • properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}

  • required = [‘_dims’]

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=True as 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 Tidy3dBaseModel from.

  • 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 Tidy3dBaseModel from.

  • 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 Tidy3dBaseModel from.

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 Tidy3dBaseModel from.

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 Tidy3dBaseModel from .yaml, .json, or .hdf5 file.

Parameters

  • fname (str) – Full path to the .yaml or .json file to load the Tidy3dBaseModel from.

  • group_path (str, optional) – Path to a group inside the file to use as the base level. Only for .hdf5 files. Starting / is optional.

  • **parse_obj_kwargs – Keyword arguments passed to either pydantic’s parse_obj function 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 Tidy3dBaseModel instance to .hdf5 file.

Parameters

  • fname (str) – Full path to the .hdf5 file to load the Tidy3dBaseModel from.

  • 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_obj method.

Example

>>> simulation.to_hdf5(fname='folder/sim.hdf5')
classmethod from_json(fname: str, **parse_obj_kwargs) → tidy3d.components.base.Tidy3dBaseModel#

Load a Tidy3dBaseModel from .json file.

Parameters

fname (str) – Full path to the .json file to load the Tidy3dBaseModel from.

Returns

  • Tidy3dBaseModel – An instance of the component class calling load.

  • **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

Example

>>> simulation = Simulation.from_json(fname='folder/sim.json')
classmethod from_orm(obj: Any) → Model#
classmethod from_yaml(fname: str, **parse_obj_kwargs) → tidy3d.components.base.Tidy3dBaseModel#

Loads Tidy3dBaseModel from .yaml file.

Parameters

  • fname (str) – Full path to the .yaml file to load the Tidy3dBaseModel from.

  • **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

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_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 Tidy3dBaseModel instance to .yaml, .json, or .hdf5 file

Parameters

fname (str) – Full path to the .yaml or .json file to save the Tidy3dBaseModel to.

Example

>>> simulation.to_file(fname='folder/sim.json')
to_hdf5(fname: str) → None#

Exports Tidy3dBaseModel instance to .hdf5 file.

Parameters

fname (str) – Full path to the .hdf5 file to save the Tidy3dBaseModel to.

Example

>>> simulation.to_hdf5(fname='folder/sim.hdf5')
to_json(fname: str) → None#

Exports Tidy3dBaseModel instance to .json file

Parameters

fname (str) – Full path to the .json file to save the Tidy3dBaseModel to.

Example

>>> simulation.to_json(fname='folder/sim.json')
to_yaml(fname: str) → None#

Exports Tidy3dBaseModel instance to .yaml file.

Parameters

fname (str) – Full path to the .yaml file to save the Tidy3dBaseModel to.

Example

>>> simulation.to_yaml(fname='folder/sim.yaml')
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 **kwargs indicating 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.