tidy3d.PermittivityData
tidy3d.PermittivityData#
- class tidy3d.PermittivityData#
Bases:
tidy3d.components.data.dataset.PermittivityDataset
,tidy3d.components.data.monitor_data.AbstractFieldData
Data for a
PermittivityMonitor
: diagonal components of the permittivity tensor.- Parameters
monitor (PermittivityMonitor) – symmetry : Tuple[Literal[0, -1, 1], Literal[0, -1, 1], Literal[0, -1, 1]] = (0, 0, 0) Symmetry eigenvalues of the original simulation in x, y, and z.
symmetry_center (Optional[Tuple[float, float, float]] = None) – Center of the symmetry planes of the original simulation in x, y, and z. Required only if any of the
symmetry
field are non-zero.grid_expanded (Optional[Grid] = None) –
Grid
on which the symmetry will be expanded. Required only if any of thesymmetry
field are non-zero.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
>>> from tidy3d import ScalarFieldDataArray >>> 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) >>> monitor = PermittivityMonitor(size=(2,4,6), freqs=[2e14, 3e14], name='eps') >>> data = PermittivityData(monitor=monitor, eps_xx=sclr_fld, eps_yy=sclr_fld, eps_zz=sclr_fld)
Show JSON schema
{ "title": "PermittivityData", "description": "Data for a :class:`.PermittivityMonitor`: diagonal components of the permittivity tensor.\n\nParameters\n----------\nmonitor : PermittivityMonitor\n symmetry : Tuple[Literal[0, -1, 1], Literal[0, -1, 1], Literal[0, -1, 1]] = (0, 0, 0)\n Symmetry eigenvalues of the original simulation in x, y, and z.\nsymmetry_center : Optional[Tuple[float, float, float]] = None\n Center of the symmetry planes of the original simulation in x, y, and z. Required only if any of the ``symmetry`` field are non-zero.\ngrid_expanded : Optional[Grid] = None\n :class:`.Grid` on which the symmetry will be expanded. Required only if any of the ``symmetry`` field are non-zero.\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>>> from tidy3d import ScalarFieldDataArray\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>>> monitor = PermittivityMonitor(size=(2,4,6), freqs=[2e14, 3e14], name='eps')\n>>> data = PermittivityData(monitor=monitor, eps_xx=sclr_fld, eps_yy=sclr_fld, eps_zz=sclr_fld)", "type": "object", "properties": { "type": { "title": "Type", "default": "PermittivityData", "enum": [ "PermittivityData" ], "type": "string" }, "monitor": { "$ref": "#/definitions/PermittivityMonitor" }, "symmetry": { "title": "Symmetry", "description": "Symmetry eigenvalues of the original simulation in x, y, and z.", "default": [ 0, 0, 0 ], "type": "array", "minItems": 3, "maxItems": 3, "items": [ { "enum": [ 0, -1, 1 ], "type": "integer" }, { "enum": [ 0, -1, 1 ], "type": "integer" }, { "enum": [ 0, -1, 1 ], "type": "integer" } ] }, "symmetry_center": { "title": "Symmetry Center", "description": "Center of the symmetry planes of the original simulation in x, y, and z. Required only if any of the ``symmetry`` field are non-zero.", "type": "array", "minItems": 3, "maxItems": 3, "items": [ { "type": "number" }, { "type": "number" }, { "type": "number" } ] }, "grid_expanded": { "title": "Expanded Grid", "description": ":class:`.Grid` on which the symmetry will be expanded. Required only if any of the ``symmetry`` field are non-zero.", "allOf": [ { "$ref": "#/definitions/Grid" } ] }, "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": [ "monitor", "eps_xx", "eps_yy", "eps_zz" ], "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 }, "PermittivityMonitor": { "title": "PermittivityMonitor", "description": ":class:`Monitor` that records the diagonal components of the complex-valued relative\npermittivity tensor in the frequency domain. The recorded data has the same shape as a\n:class:`.FieldMonitor` of the same geometry: the permittivity values are saved at the\nYee grid locations, and can be interpolated to any point inside the monitor.\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, ...], ArrayLike_dtype=<class 'float'>_ndim=1]\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.\n\nNote\n----\nIf 2D materials are present, then the permittivity values correspond to the\nvolumetric equivalent of the 2D materials.\n\nExample\n-------\n>>> monitor = PermittivityMonitor(\n... center=(1,2,3),\n... size=(2,2,2),\n... freqs=[250e12, 300e12],\n... name='eps_monitor')", "type": "object", "properties": { "type": { "title": "Type", "default": "PermittivityMonitor", "enum": [ "PermittivityMonitor" ], "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": "ArrayLike", "type": "ArrayLike" } ] }, "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": [ { "$ref": "#/definitions/ApodizationSpec" } ] } }, "required": [ "size", "name", "freqs" ], "additionalProperties": false }, "Coords": { "title": "Coords", "description": "Holds data about a set of x,y,z positions on a grid.\n\nParameters\n----------\nx : ArrayLike_dtype=<class 'float'>_ndim=1\n 1-dimensional array of x coordinates.\ny : ArrayLike_dtype=<class 'float'>_ndim=1\n 1-dimensional array of y coordinates.\nz : ArrayLike_dtype=<class 'float'>_ndim=1\n 1-dimensional array of z coordinates.\n\nExample\n-------\n>>> x = np.linspace(-1, 1, 10)\n>>> y = np.linspace(-1, 1, 11)\n>>> z = np.linspace(-1, 1, 12)\n>>> coords = Coords(x=x, y=y, z=z)", "type": "object", "properties": { "x": { "title": "ArrayLike", "description": "1-dimensional array of x coordinates.", "type": "ArrayLike" }, "y": { "title": "ArrayLike", "description": "1-dimensional array of y coordinates.", "type": "ArrayLike" }, "z": { "title": "ArrayLike", "description": "1-dimensional array of z coordinates.", "type": "ArrayLike" }, "type": { "title": "Type", "default": "Coords", "enum": [ "Coords" ], "type": "string" } }, "required": [ "x", "y", "z" ], "additionalProperties": false }, "Grid": { "title": "Grid", "description": "Contains all information about the spatial positions of the FDTD grid.\n\nParameters\n----------\nboundaries : Coords\n x,y,z coordinates of the boundaries between cells, defining the FDTD grid.\n\nExample\n-------\n>>> x = np.linspace(-1, 1, 10)\n>>> y = np.linspace(-1, 1, 11)\n>>> z = np.linspace(-1, 1, 12)\n>>> coords = Coords(x=x, y=y, z=z)\n>>> grid = Grid(boundaries=coords)\n>>> centers = grid.centers\n>>> sizes = grid.sizes\n>>> yee_grid = grid.yee", "type": "object", "properties": { "boundaries": { "title": "Boundary Coordinates", "description": "x,y,z coordinates of the boundaries between cells, defining the FDTD grid.", "allOf": [ { "$ref": "#/definitions/Coords" } ] }, "type": { "title": "Type", "default": "Grid", "enum": [ "Grid" ], "type": "string" } }, "required": [ "boundaries" ], "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’]
- attribute grid_expanded: tidy3d.components.grid.grid.Grid = None#
Grid
on which the symmetry will be expanded. Required only if any of thesymmetry
field are non-zero.- Validated by
_make_required
- attribute monitor: tidy3d.components.monitor.PermittivityMonitor [Required]#
- attribute symmetry: Tuple[Literal[0, -1, 1], Literal[0, -1, 1], Literal[0, -1, 1]] = (0, 0, 0)#
Symmetry eigenvalues of the original simulation in x, y, and z.
- attribute symmetry_center: Tuple[float, float, float] = None#
Center of the symmetry planes of the original simulation in x, y, and z. Required only if any of the
symmetry
field are non-zero.- Validated by
_make_required
- 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().
- normalize(source_spectrum_fn: Callable[[float], complex]) tidy3d.components.data.dataset.Dataset #
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 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.
- property symmetry_expanded_copy: tidy3d.components.data.monitor_data.AbstractFieldData#
Create a copy of the
AbstractFieldData
with fields expanded based on symmetry.- Returns
A data object with the symmetry expanded fields.
- Return type
AbstractFieldData