tidy3d.PML#

class tidy3d.PML#

Bases: tidy3d.components.boundary.AbsorberSpec

Specifies a standard PML along a single dimension.

Parameters

  • name (Optional[str] = None) – Optional unique name for boundary.

  • num_layers (NonNegativeInt = 12) – Number of layers of standard PML.

  • parameters (PMLParams = PMLParams(sigma_order=3, sigma_min=0.0, sigma_max=1.5, type='PMLParams', kappa_order=3, kappa_min=1.0, kappa_max=3.0, alpha_order=1, alpha_min=0.0, alpha_max=0.0)) – Parameters of the complex frequency-shifted absorption poles.

Example

>>> pml = PML(num_layers=10)

Show JSON schema
{
   "title": "PML",
   "description": "Specifies a standard PML along a single dimension.\n\nParameters\n----------\nname : Optional[str] = None\n    Optional unique name for boundary.\nnum_layers : NonNegativeInt = 12\n    Number of layers of standard PML.\nparameters : PMLParams = PMLParams(sigma_order=3, sigma_min=0.0, sigma_max=1.5, type='PMLParams', kappa_order=3, kappa_min=1.0, kappa_max=3.0, alpha_order=1, alpha_min=0.0, alpha_max=0.0)\n    Parameters of the complex frequency-shifted absorption poles.\n\nExample\n-------\n>>> pml = PML(num_layers=10)",
   "type": "object",
   "properties": {
      "name": {
         "title": "Name",
         "description": "Optional unique name for boundary.",
         "type": "string"
      },
      "type": {
         "title": "Type",
         "default": "PML",
         "enum": [
            "PML"
         ],
         "type": "string"
      },
      "num_layers": {
         "title": "Number of Layers",
         "description": "Number of layers of standard PML.",
         "default": 12,
         "minimum": 0,
         "type": "integer"
      },
      "parameters": {
         "title": "PML Parameters",
         "description": "Parameters of the complex frequency-shifted absorption poles.",
         "default": {
            "sigma_order": 3,
            "sigma_min": 0.0,
            "sigma_max": 1.5,
            "type": "PMLParams",
            "kappa_order": 3,
            "kappa_min": 1.0,
            "kappa_max": 3.0,
            "alpha_order": 1,
            "alpha_min": 0.0,
            "alpha_max": 0.0
         },
         "allOf": [
            {
               "$ref": "#/definitions/PMLParams"
            }
         ]
      }
   },
   "additionalProperties": false,
   "definitions": {
      "PMLParams": {
         "title": "PMLParams",
         "description": "Specifies full set of parameters needed for complex, frequency-shifted PML.\n\nParameters\n----------\nsigma_order : NonNegativeInt = 3\n    Order of the polynomial describing the absorber profile (~dist^sigma_order).\nsigma_min : NonNegativeFloat = 0.0\n    [units = 2*EPSILON_0/dt].  Minimum value of the absorber conductivity.\nsigma_max : NonNegativeFloat = 1.5\n    [units = 2*EPSILON_0/dt].  Maximum value of the absorber conductivity.\nkappa_order : NonNegativeInt = 3\n    Order of the polynomial describing the PML kappa profile (kappa~dist^kappa_order).\nkappa_min : NonNegativeFloat = 0.0\n    \nkappa_max : NonNegativeFloat = 1.5\n    \nalpha_order : NonNegativeInt = 3\n    Order of the polynomial describing the PML alpha profile (alpha~dist^alpha_order).\nalpha_min : NonNegativeFloat = 0.0\n    [units = 2*EPSILON_0/dt].  Minimum value of the PML alpha.\nalpha_max : NonNegativeFloat = 1.5\n    [units = 2*EPSILON_0/dt].  Maximum value of the PML alpha.\n\nExample\n-------\n>>> params = PMLParams(sigma_order=3, sigma_min=0.0, sigma_max=1.5, kappa_min=0.0)",
         "type": "object",
         "properties": {
            "sigma_order": {
               "title": "Sigma Order",
               "description": "Order of the polynomial describing the absorber profile (~dist^sigma_order).",
               "default": 3,
               "minimum": 0,
               "type": "integer"
            },
            "sigma_min": {
               "title": "Sigma Minimum",
               "description": "Minimum value of the absorber conductivity.",
               "default": 0.0,
               "units": "2*EPSILON_0/dt",
               "minimum": 0,
               "type": "number"
            },
            "sigma_max": {
               "title": "Sigma Maximum",
               "description": "Maximum value of the absorber conductivity.",
               "default": 1.5,
               "units": "2*EPSILON_0/dt",
               "minimum": 0,
               "type": "number"
            },
            "type": {
               "title": "Type",
               "default": "PMLParams",
               "enum": [
                  "PMLParams"
               ],
               "type": "string"
            },
            "kappa_order": {
               "title": "Kappa Order",
               "description": "Order of the polynomial describing the PML kappa profile (kappa~dist^kappa_order).",
               "default": 3,
               "minimum": 0,
               "type": "integer"
            },
            "kappa_min": {
               "title": "Kappa Minimum",
               "default": 0.0,
               "minimum": 0,
               "type": "number"
            },
            "kappa_max": {
               "title": "Kappa Maximum",
               "default": 1.5,
               "minimum": 0,
               "type": "number"
            },
            "alpha_order": {
               "title": "Alpha Order",
               "description": "Order of the polynomial describing the PML alpha profile (alpha~dist^alpha_order).",
               "default": 3,
               "minimum": 0,
               "type": "integer"
            },
            "alpha_min": {
               "title": "Alpha Minimum",
               "description": "Minimum value of the PML alpha.",
               "default": 0.0,
               "units": "2*EPSILON_0/dt",
               "minimum": 0,
               "type": "number"
            },
            "alpha_max": {
               "title": "Alpha Maximum",
               "description": "Maximum value of the PML alpha.",
               "default": 1.5,
               "units": "2*EPSILON_0/dt",
               "minimum": 0,
               "type": "number"
            }
         },
         "additionalProperties": false
      }
   }
}

attribute name: str = None#

Optional unique name for boundary.

attribute num_layers: pydantic.types.NonNegativeInt = 12#

Number of layers of standard PML.

Constraints

  • minimum = 0

attribute parameters: tidy3d.components.boundary.PMLParams = PMLParams(sigma_order=3, sigma_min=0.0, sigma_max=1.5, type='PMLParams', kappa_order=3, kappa_min=1.0, kappa_max=3.0, alpha_order=1, alpha_min=0.0, alpha_max=0.0)#

Parameters of the complex frequency-shifted absorption poles.

classmethod add_type_field() → None#

Automatically place “type” field with model name in the model field dictionary.

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#