tidy3d.FieldTimeData
tidy3d.FieldTimeData#
- class tidy3d.FieldTimeData#
Bases:
tidy3d.components.data.dataset.FieldTimeDataset
,tidy3d.components.data.monitor_data.ElectromagneticFieldData
Data associated with a
FieldTimeMonitor
: scalar components of E and H fields.- Parameters
Ex (Optional[ScalarFieldTimeDataArray] = None) – Spatial distribution of the x-component of the electric field.
Ey (Optional[ScalarFieldTimeDataArray] = None) – Spatial distribution of the y-component of the electric field.
Ez (Optional[ScalarFieldTimeDataArray] = None) – Spatial distribution of the z-component of the electric field.
Hx (Optional[ScalarFieldTimeDataArray] = None) – Spatial distribution of the x-component of the magnetic field.
Hy (Optional[ScalarFieldTimeDataArray] = None) – Spatial distribution of the y-component of the magnetic field.
Hz (Optional[ScalarFieldTimeDataArray] = None) – Spatial distribution of the z-component of the magnetic field.
monitor (FieldTimeMonitor) – 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.grid_primal_correction (Union[float, FreqDataArray, TimeDataArray, FreqModeDataArray] = 1.0) – Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the primal grid locations along the normal direction.
grid_dual_correction (Union[float, FreqDataArray, TimeDataArray, FreqModeDataArray] = 1.0) – Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the dual grid locations along the normal direction.
Example
>>> from tidy3d import ScalarFieldTimeDataArray >>> x = [-1,1] >>> y = [-2,0,2] >>> z = [-3,-1,1,3] >>> t = [0, 1e-12, 2e-12] >>> coords = dict(x=x, y=y, z=z, t=t) >>> scalar_field = ScalarFieldTimeDataArray(np.random.random((2,3,4,3)), coords=coords) >>> monitor = FieldTimeMonitor(size=(2,4,6), interval=100, name='field', fields=['Ex', 'Hz']) >>> data = FieldTimeData(monitor=monitor, Ex=scalar_field, Hz=scalar_field)
Show JSON schema
{ "title": "FieldTimeData", "description": "Data associated with a :class:`.FieldTimeMonitor`: scalar components of E and H fields.\n\nParameters\n----------\nEx : Optional[ScalarFieldTimeDataArray] = None\n Spatial distribution of the x-component of the electric field.\nEy : Optional[ScalarFieldTimeDataArray] = None\n Spatial distribution of the y-component of the electric field.\nEz : Optional[ScalarFieldTimeDataArray] = None\n Spatial distribution of the z-component of the electric field.\nHx : Optional[ScalarFieldTimeDataArray] = None\n Spatial distribution of the x-component of the magnetic field.\nHy : Optional[ScalarFieldTimeDataArray] = None\n Spatial distribution of the y-component of the magnetic field.\nHz : Optional[ScalarFieldTimeDataArray] = None\n Spatial distribution of the z-component of the magnetic field.\nmonitor : FieldTimeMonitor\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.\ngrid_primal_correction : Union[float, FreqDataArray, TimeDataArray, FreqModeDataArray] = 1.0\n Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the primal grid locations along the normal direction.\ngrid_dual_correction : Union[float, FreqDataArray, TimeDataArray, FreqModeDataArray] = 1.0\n Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the dual grid locations along the normal direction.\n\nExample\n-------\n>>> from tidy3d import ScalarFieldTimeDataArray\n>>> x = [-1,1]\n>>> y = [-2,0,2]\n>>> z = [-3,-1,1,3]\n>>> t = [0, 1e-12, 2e-12]\n>>> coords = dict(x=x, y=y, z=z, t=t)\n>>> scalar_field = ScalarFieldTimeDataArray(np.random.random((2,3,4,3)), coords=coords)\n>>> monitor = FieldTimeMonitor(size=(2,4,6), interval=100, name='field', fields=['Ex', 'Hz'])\n>>> data = FieldTimeData(monitor=monitor, Ex=scalar_field, Hz=scalar_field)", "type": "object", "properties": { "type": { "title": "Type", "default": "FieldTimeData", "enum": [ "FieldTimeData" ], "type": "string" }, "Ex": { "title": "DataArray", "description": "Spatial distribution of the x-component of the electric field.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "Ey": { "title": "DataArray", "description": "Spatial distribution of the y-component of the electric field.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "Ez": { "title": "DataArray", "description": "Spatial distribution of the z-component of the electric field.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "Hx": { "title": "DataArray", "description": "Spatial distribution of the x-component of the magnetic field.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "Hy": { "title": "DataArray", "description": "Spatial distribution of the y-component of the magnetic field.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "Hz": { "title": "DataArray", "description": "Spatial distribution of the z-component of the magnetic field.", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, "monitor": { "$ref": "#/definitions/FieldTimeMonitor" }, "symmetry": { "title": "Symmetry", "description": "Symmetry eigenvalues of the original simulation in x, y, and z.", "default": [ 0, 0, 0 ], "type": "array", "minItems": 3, "maxItems": 3, "items": [ { "enum": [ 0, -1, 1 ], "type": "integer" }, { "enum": [ 0, -1, 1 ], "type": "integer" }, { "enum": [ 0, -1, 1 ], "type": "integer" } ] }, "symmetry_center": { "title": "Symmetry Center", "description": "Center of the symmetry planes of the original simulation in x, y, and z. Required only if any of the ``symmetry`` field are non-zero.", "type": "array", "minItems": 3, "maxItems": 3, "items": [ { "type": "number" }, { "type": "number" }, { "type": "number" } ] }, "grid_expanded": { "title": "Expanded Grid", "description": ":class:`.Grid` on which the symmetry will be expanded. Required only if any of the ``symmetry`` field are non-zero.", "allOf": [ { "$ref": "#/definitions/Grid" } ] }, "grid_primal_correction": { "title": "Field correction factor", "description": "Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the primal grid locations along the normal direction.", "default": 1.0, "anyOf": [ { "type": "number" }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } ] }, "grid_dual_correction": { "title": "Field correction factor", "description": "Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the dual grid locations along the normal direction.", "default": 1.0, "anyOf": [ { "type": "number" }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] }, { "title": "DataArray", "type": "xr.DataArray", "properties": { "_dims": { "title": "_dims", "type": "Tuple[str, ...]" } }, "required": [ "_dims" ] } ] } }, "required": [ "monitor" ], "additionalProperties": false, "definitions": { "FieldTimeMonitor": { "title": "FieldTimeMonitor", "description": ":class:`Monitor` that records electromagnetic fields in the time domain.\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.\nstart : NonNegativeFloat = 0.0\n [units = sec]. Time at which to start monitor recording.\nstop : Optional[NonNegativeFloat] = None\n [units = sec]. Time at which to stop monitor recording. If not specified, record until end of simulation.\ninterval : PositiveInt = 1\n Number of time step intervals between monitor recordings.\nfields : Tuple[Literal['Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz'], ...] = ['Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz']\n Collection of field components to store in the monitor.\ninterval_space : Tuple[PositiveInt, PositiveInt, PositiveInt] = (1, 1, 1)\n Number of grid step intervals between monitor recordings. If equal to 1, there will be no downsampling. If greater than 1, fields will be downsampled and automatically colocated.\ncolocate : Optional[bool] = None\n Toggle whether fields should be colocated to grid cell centers. Default: ``False`` if ``interval_space`` is 1 in each direction, ``True`` if ``interval_space`` is greater than one in any direction.\n\nExample\n-------\n>>> monitor = FieldTimeMonitor(\n... center=(1,2,3),\n... size=(2,2,2),\n... fields=['Hx'],\n... start=1e-13,\n... stop=5e-13,\n... interval=2,\n... name='movie_monitor')", "type": "object", "properties": { "type": { "title": "Type", "default": "FieldTimeMonitor", "enum": [ "FieldTimeMonitor" ], "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" }, "start": { "title": "Start time", "description": "Time at which to start monitor recording.", "default": 0.0, "units": "sec", "minimum": 0, "type": "number" }, "stop": { "title": "Stop time", "description": "Time at which to stop monitor recording. If not specified, record until end of simulation.", "units": "sec", "minimum": 0, "type": "number" }, "interval": { "title": "Time interval", "description": "Number of time step intervals between monitor recordings.", "default": 1, "exclusiveMinimum": 0, "type": "integer" }, "fields": { "title": "Field Components", "description": "Collection of field components to store in the monitor.", "default": [ "Ex", "Ey", "Ez", "Hx", "Hy", "Hz" ], "type": "array", "items": { "enum": [ "Ex", "Ey", "Ez", "Hx", "Hy", "Hz" ], "type": "string" } }, "interval_space": { "title": "Spatial interval", "description": "Number of grid step intervals between monitor recordings. If equal to 1, there will be no downsampling. If greater than 1, fields will be downsampled and automatically colocated.", "default": [ 1, 1, 1 ], "type": "array", "minItems": 3, "maxItems": 3, "items": [ { "type": "integer", "exclusiveMinimum": 0 }, { "type": "integer", "exclusiveMinimum": 0 }, { "type": "integer", "exclusiveMinimum": 0 } ] }, "colocate": { "title": "Colocate fields", "description": "Toggle whether fields should be colocated to grid cell centers. Default: ``False`` if ``interval_space`` is 1 in each direction, ``True`` if ``interval_space`` is greater than one in any direction.", "type": "boolean" } }, "required": [ "size", "name" ], "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 Ex: tidy3d.components.data.data_array.ScalarFieldTimeDataArray = None#
Spatial distribution of the x-component of the electric field.
- Constraints
title = DataArray
type = xr.DataArray
properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}
required = [‘_dims’]
- Validated by
_contains_fields
- attribute Ey: tidy3d.components.data.data_array.ScalarFieldTimeDataArray = None#
Spatial distribution of the y-component of the electric field.
- Constraints
title = DataArray
type = xr.DataArray
properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}
required = [‘_dims’]
- Validated by
_contains_fields
- attribute Ez: tidy3d.components.data.data_array.ScalarFieldTimeDataArray = None#
Spatial distribution of the z-component of the electric field.
- Constraints
title = DataArray
type = xr.DataArray
properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}
required = [‘_dims’]
- Validated by
_contains_fields
- attribute Hx: tidy3d.components.data.data_array.ScalarFieldTimeDataArray = None#
Spatial distribution of the x-component of the magnetic field.
- Constraints
title = DataArray
type = xr.DataArray
properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}
required = [‘_dims’]
- Validated by
_contains_fields
- attribute Hy: tidy3d.components.data.data_array.ScalarFieldTimeDataArray = None#
Spatial distribution of the y-component of the magnetic field.
- Constraints
title = DataArray
type = xr.DataArray
properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}
required = [‘_dims’]
- Validated by
_contains_fields
- attribute Hz: tidy3d.components.data.data_array.ScalarFieldTimeDataArray = None#
Spatial distribution of the z-component of the magnetic field.
- Constraints
title = DataArray
type = xr.DataArray
properties = {‘_dims’: {‘title’: ‘_dims’, ‘type’: ‘Tuple[str, …]’}}
required = [‘_dims’]
- Validated by
_contains_fields
- attribute grid_dual_correction: Union[float, tidy3d.components.data.data_array.FreqDataArray, tidy3d.components.data.data_array.TimeDataArray, tidy3d.components.data.data_array.FreqModeDataArray] = 1.0#
Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the dual grid locations along the normal direction.
- Validated by
_contains_fields
- 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
_contains_fields
_make_required
- attribute grid_primal_correction: Union[float, tidy3d.components.data.data_array.FreqDataArray, tidy3d.components.data.data_array.TimeDataArray, tidy3d.components.data.data_array.FreqModeDataArray] = 1.0#
Correction factor that needs to be applied for data corresponding to a 2D monitor to take into account the finite grid in the normal direction in the simulation in which the data was computed. The factor is applied to fields defined on the primal grid locations along the normal direction.
- Validated by
_contains_fields
- attribute monitor: tidy3d.components.monitor.FieldTimeMonitor [Required]#
- Validated by
_contains_fields
- 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.
- Validated by
_contains_fields
- 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
_contains_fields
_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')
- dot(field_data: tidy3d.components.data.monitor_data.ElectromagneticFieldData, conjugate: bool = True) xarray.core.dataarray.DataArray #
Inner product is not defined for time-domain data.
- 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.DataArray]#
Maps the field components to thier associated data.
- property flux: tidy3d.components.data.data_array.FluxTimeDataArray#
Flux for data corresponding to a 2D monitor.
- property grid_locations: Dict[str, str]#
Maps field components to the string key of their grid locations on the yee lattice.
- property poynting: tidy3d.components.data.data_array.ScalarFieldTimeDataArray#
Instantaneous Poynting vector for time-domain data associated to a 2D monitor, projected to the direction normal to the monitor plane.
- 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
- property time_reversed_copy: tidy3d.components.data.monitor_data.FieldTimeData#
Make a copy of the data with time-reversed fields. The sign of the magnetic fields is flipped, and the data is reversed along the
t
dimension, such that for a given field,field[t_beg + t] -> field[t_end - t]
, wheret_beg
andt_end
are the first and last coordinates along thet
dimension.