tidy3d.GaussianPulse
tidy3d.GaussianPulse#
- class tidy3d.GaussianPulse#
Bases:
tidy3d.components.source.Pulse
Source time dependence that describes a Gaussian pulse.
- Parameters
amplitude (NonNegativeFloat = 1.0) – Real-valued maximum amplitude of the time dependence.
phase (float = 0.0) – [units = rad]. Phase shift of the time dependence.
freq0 (PositiveFloat) – [units = Hz]. Central frequency of the pulse.
fwidth (PositiveFloat) – [units = Hz]. Standard deviation of the frequency content of the pulse.
offset (ConstrainedFloatValue = 5.0) – Time delay of the maximum value of the pulse in units of 1 / (
2pi * fwidth
).
Example
>>> pulse = GaussianPulse(freq0=200e12, fwidth=20e12)
Show JSON schema
{ "title": "GaussianPulse", "description": "Source time dependence that describes a Gaussian pulse.\n\nParameters\n----------\namplitude : NonNegativeFloat = 1.0\n Real-valued maximum amplitude of the time dependence.\nphase : float = 0.0\n [units = rad]. Phase shift of the time dependence.\nfreq0 : PositiveFloat\n [units = Hz]. Central frequency of the pulse.\nfwidth : PositiveFloat\n [units = Hz]. Standard deviation of the frequency content of the pulse.\noffset : ConstrainedFloatValue = 5.0\n Time delay of the maximum value of the pulse in units of 1 / (``2pi * fwidth``).\n\nExample\n-------\n>>> pulse = GaussianPulse(freq0=200e12, fwidth=20e12)", "type": "object", "properties": { "amplitude": { "title": "Amplitude", "description": "Real-valued maximum amplitude of the time dependence.", "default": 1.0, "minimum": 0, "type": "number" }, "phase": { "title": "Phase", "description": "Phase shift of the time dependence.", "default": 0.0, "units": "rad", "type": "number" }, "type": { "title": "Type", "default": "GaussianPulse", "enum": [ "GaussianPulse" ], "type": "string" }, "freq0": { "title": "Central Frequency", "description": "Central frequency of the pulse.", "units": "Hz", "exclusiveMinimum": 0, "type": "number" }, "fwidth": { "title": "Fwidth", "description": "Standard deviation of the frequency content of the pulse.", "units": "Hz", "exclusiveMinimum": 0, "type": "number" }, "offset": { "title": "Offset", "description": "Time delay of the maximum value of the pulse in units of 1 / (``2pi * fwidth``).", "default": 5.0, "minimum": 2.5, "type": "number" } }, "required": [ "freq0", "fwidth" ], "additionalProperties": false }
- attribute amplitude: pydantic.types.NonNegativeFloat = 1.0#
Real-valued maximum amplitude of the time dependence.
- Constraints
minimum = 0
- attribute freq0: pydantic.types.PositiveFloat [Required]#
Central frequency of the pulse.
- Constraints
exclusiveMinimum = 0
- attribute fwidth: pydantic.types.PositiveFloat [Required]#
Standard deviation of the frequency content of the pulse.
- Constraints
exclusiveMinimum = 0
- attribute offset: float = 5.0#
Time delay of the maximum value of the pulse in units of 1 / (
2pi * fwidth
).- Constraints
minimum = 2.5
- attribute phase: float = 0.0#
Phase shift of the time dependence.
- classmethod add_type_field() None #
Automatically place “type” field with model name in the model field dictionary.
- amp_time(time: float) complex #
Complex-valued source amplitude as a function of time.
- 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')
- frequency_range(num_fwidth: float = 4.0) Tuple[float, float] #
Frequency range within 5 standard deviations of the central frequency.
- Parameters
num_fwidth (float = 4.) – Frequency range defined as plus/minus
num_fwidth * self.fwdith
.- Returns
Minimum and maximum frequencies of the
GaussianPulse
orContinuousWave
power.- Return type
Tuple[float, float]
- 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 #
- plot(times: tidy3d.components.types.ArrayLike_dtype=<class 'float'>_ndim=1, val: typing.Literal['real', 'imag', 'abs'] = 'real', ax: matplotlib.axes._axes.Axes = None) matplotlib.axes._axes.Axes #
Plot the complex-valued amplitude of the source time-dependence.
- Parameters
times (np.ndarray) – Array of times (seconds) to plot source at. To see source time amplitude for a specific
Simulation
, passsimulation.tmesh
.val (Literal['real', 'imag', 'abs'] = 'real') – Which part of the spectrum to plot.
ax (matplotlib.axes._subplots.Axes = None) – Matplotlib axes to plot on, if not specified, one is created.
- Returns
The supplied or created matplotlib axes.
- Return type
matplotlib.axes._subplots.Axes
- plot_spectrum(times: tidy3d.components.types.ArrayLike_dtype=<class 'float'>_ndim=1, num_freqs: int = 101, val: typing.Literal['real', 'imag', 'abs'] = 'real', ax: matplotlib.axes._axes.Axes = None, complex_fields: bool = False) matplotlib.axes._axes.Axes #
Plot the complex-valued amplitude of the source time-dependence.
- Parameters
times (np.ndarray) – Array of evenly-spaced times (seconds) to evaluate source time-dependence at. The spectrum is computed from this value and the source time frequency content. To see source spectrum for a specific
Simulation
, passsimulation.tmesh
.num_freqs (int = 101) – Number of frequencies to plot within the SourceTime.frequency_range.
ax (matplotlib.axes._subplots.Axes = None) – Matplotlib axes to plot on, if not specified, one is created.
complex_fields (bool) – Whether time domain fields are complex, e.g., for Bloch boundaries
- Returns
The supplied or created matplotlib axes.
- Return type
matplotlib.axes._subplots.Axes
- 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 #
- spectrum(times: tidy3d.components.types.ArrayLike_dtype=<class 'float'>_ndim=1, freqs: tidy3d.components.types.ArrayLike_dtype=<class 'float'>_ndim=1, dt: float, complex_fields: bool = False) complex #
Complex-valued source spectrum as a function of frequency
- Parameters
times (np.ndarray) – Times to use to evaluate spectrum Fourier transform. (Typically the simulation time mesh).
freqs (np.ndarray) – Frequencies in Hz to evaluate spectrum at.
dt (float or np.ndarray) – Time step to weight FT integral with. If array, use to weigh each of the time intervals in
times
.complex_fields (bool) – Whether time domain fields are complex, e.g., for Bloch boundaries
- Returns
Complex-valued array (of len(freqs)) containing spectrum at those frequencies.
- Return type
np.ndarray
- 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 #