tidy3d.FluxData#

class tidy3d.FluxData#

Bases: tidy3d.components.data.monitor_data.MonitorData

Data associated with a FluxMonitor: flux data in the frequency-domain.

Parameters: monitor (FluxMonitor) – flux : FluxDataArray

Example

>>> from tidy3d import FluxDataArray
>>> f = [2e14, 3e14]
>>> coords = dict(f=f)
>>> flux_data = FluxDataArray(np.random.random(2), coords=coords)
>>> monitor = FluxMonitor(size=(2,0,6), freqs=[2e14, 3e14], name='flux')
>>> data = FluxData(monitor=monitor, flux=flux_data)

Show JSON schema

{
   "title": "FluxData",
   "description": "Data associated with a :class:`.FluxMonitor`: flux data in the frequency-domain.\n\nParameters\n----------\nmonitor : FluxMonitor\n        flux : FluxDataArray\n    \nExample\n-------\n>>> from tidy3d import FluxDataArray\n>>> f = [2e14, 3e14]\n>>> coords = dict(f=f)\n>>> flux_data = FluxDataArray(np.random.random(2), coords=coords)\n>>> monitor = FluxMonitor(size=(2,0,6), freqs=[2e14, 3e14], name='flux')\n>>> data = FluxData(monitor=monitor, flux=flux_data)",
   "type": "object",
   "properties": {
      "type": {
         "title": "Type",
         "default": "FluxData",
         "enum": [
            "FluxData"
         ],
         "type": "string"
      },
      "monitor": {
         "$ref": "#/definitions/FluxMonitor"
      },
      "flux": {
         "title": "DataArray",
         "type": "xr.DataArray",
         "properties": {
            "_dims": {
               "title": "_dims",
               "type": "Tuple[str, ...]"
            }
         },
         "required": [
            "_dims"
         ]
      }
   },
   "required": [
      "monitor",
      "flux"
   ],
   "additionalProperties": false,
   "definitions": {
      "ApodizationSpec": {
         "title": "ApodizationSpec",
         "description": "Stores specifications for the apodizaton of frequency-domain monitors.\n\nParameters\n----------\nstart : Optional[NonNegativeFloat] = None\n    [units = sec].  Defines the time at which the start apodization ends.\nend : Optional[NonNegativeFloat] = None\n    [units = sec].  Defines the time at which the end apodization begins.\nwidth : Optional[PositiveFloat] = None\n    [units = sec].  Characteristic decay length of the apodization function.\n\nExample\n-------\n>>> apod_spec = ApodizationSpec(start=1, end=2, width=0.5)",
         "type": "object",
         "properties": {
            "start": {
               "title": "Start Interval",
               "description": "Defines the time at which the start apodization ends.",
               "units": "sec",
               "minimum": 0,
               "type": "number"
            },
            "end": {
               "title": "End Interval",
               "description": "Defines the time at which the end apodization begins.",
               "units": "sec",
               "minimum": 0,
               "type": "number"
            },
            "width": {
               "title": "Apodization Width",
               "description": "Characteristic decay length of the apodization function.",
               "units": "sec",
               "exclusiveMinimum": 0,
               "type": "number"
            },
            "type": {
               "title": "Type",
               "default": "ApodizationSpec",
               "enum": [
                  "ApodizationSpec"
               ],
               "type": "string"
            }
         },
         "additionalProperties": false
      },
      "FluxMonitor": {
         "title": "FluxMonitor",
         "description": ":class:`Monitor` that records power flux in the frequency domain.\nIf the monitor geometry is a 2D box, the total flux through this plane is returned, with a\npositive sign corresponding to power flow in the positive direction along the axis normal to\nthe plane. If the geometry is a 3D box, the total power coming out of the box is returned by\nintegrating the flux over all box surfaces (excpet the ones defined in ``exclude_surfaces``).\n\nParameters\n----------\ncenter : Tuple[float, float, float] = (0.0, 0.0, 0.0)\n    [units = um].  Center of object in x, y, and z.\nsize : Tuple[NonNegativeFloat, NonNegativeFloat, NonNegativeFloat]\n    [units = um].  Size in x, y, and z directions.\nname : ConstrainedStrValue\n    Unique name for monitor.\nfreqs : Union[Tuple[float, ...], Array]\n    [units = Hz].  Array or list of frequencies stored by the field monitor.\napodization : ApodizationSpec = ApodizationSpec(start=None, end=None, width=None, type='ApodizationSpec')\n    Sets parameters of (optional) apodization. Apodization applies a windowing function to the Fourier transform of the time-domain fields into frequency-domain ones, and can be used to truncate the beginning and/or end of the time signal, for example to eliminate the source pulse when studying the eigenmodes of a system. Note: apodization affects the normalization of the frequency-domain fields.\nnormal_dir : Optional[Literal['+', '-']] = None\n    Direction of the surface monitor's normal vector w.r.t. the positive x, y or z unit vectors. Must be one of ``'+'`` or ``'-'``. Applies to surface monitors only, and defaults to ``'+'`` if not provided.\nexclude_surfaces : Optional[Tuple[Literal['x-', 'x+', 'y-', 'y+', 'z-', 'z+'], ...]] = None\n    Surfaces to exclude in the integration, if a volume monitor.\n\nExample\n-------\n>>> monitor = FluxMonitor(\n...     center=(1,2,3),\n...     size=(2,2,0),\n...     freqs=[200e12, 210e12],\n...     name='flux_monitor')",
         "type": "object",
         "properties": {
            "type": {
               "title": "Type",
               "default": "FluxMonitor",
               "enum": [
                  "FluxMonitor"
               ],
               "type": "string"
            },
            "center": {
               "title": "Center",
               "description": "Center of object in x, y, and z.",
               "default": [
                  0.0,
                  0.0,
                  0.0
               ],
               "units": "um",
               "type": "array",
               "minItems": 3,
               "maxItems": 3,
               "items": [
                  {
                     "type": "number"
                  },
                  {
                     "type": "number"
                  },
                  {
                     "type": "number"
                  }
               ]
            },
            "size": {
               "title": "Size",
               "description": "Size in x, y, and z directions.",
               "units": "um",
               "type": "array",
               "minItems": 3,
               "maxItems": 3,
               "items": [
                  {
                     "type": "number",
                     "minimum": 0
                  },
                  {
                     "type": "number",
                     "minimum": 0
                  },
                  {
                     "type": "number",
                     "minimum": 0
                  }
               ]
            },
            "name": {
               "title": "Name",
               "description": "Unique name for monitor.",
               "minLength": 1,
               "type": "string"
            },
            "freqs": {
               "title": "Frequencies",
               "description": "Array or list of frequencies stored by the field monitor.",
               "units": "Hz",
               "anyOf": [
                  {
                     "type": "array",
                     "items": {
                        "type": "number"
                     }
                  },
                  {
                     "title": "Array Like",
                     "description": "Accepts sequence (tuple, list, numpy array) and converts to tuple.",
                     "type": "tuple",
                     "properties": {},
                     "required": []
                  }
               ]
            },
            "apodization": {
               "title": "Apodization Specification",
               "description": "Sets parameters of (optional) apodization. Apodization applies a windowing function to the Fourier transform of the time-domain fields into frequency-domain ones, and can be used to truncate the beginning and/or end of the time signal, for example to eliminate the source pulse when studying the eigenmodes of a system. Note: apodization affects the normalization of the frequency-domain fields.",
               "default": {
                  "start": null,
                  "end": null,
                  "width": null,
                  "type": "ApodizationSpec"
               },
               "allOf": [
                  {
                     "$ref": "#/definitions/ApodizationSpec"
                  }
               ]
            },
            "normal_dir": {
               "title": "Normal vector orientation",
               "description": "Direction of the surface monitor's normal vector w.r.t. the positive x, y or z unit vectors. Must be one of ``'+'`` or ``'-'``. Applies to surface monitors only, and defaults to ``'+'`` if not provided.",
               "enum": [
                  "+",
                  "-"
               ],
               "type": "string"
            },
            "exclude_surfaces": {
               "title": "Excluded surfaces",
               "description": "Surfaces to exclude in the integration, if a volume monitor.",
               "type": "array",
               "items": {
                  "enum": [
                     "x-",
                     "x+",
                     "y-",
                     "y+",
                     "z-",
                     "z+"
                  ],
                  "type": "string"
               }
            }
         },
         "required": [
            "size",
            "name",
            "freqs"
         ],
         "additionalProperties": false
      }
   }
}

attribute flux: tidy3d.components.data.data_array.FluxDataArray [Required]#

Constraints

title = DataArray
type = xr.DataArray
properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}
required = [‘_dims’]

attribute monitor: tidy3d.components.monitor.FluxMonitor [Required]#

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().

normalize(source_spectrum_fn) → tidy3d.components.data.monitor_data.FluxData#: Return copy of self after normalization is applied using source spectrum function.

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 symmetry_expanded_copy: tidy3d.components.data.monitor_data.MonitorData#: Return copy of self with symmetry applied.