tidy3d.plugins.DispersionFitter
tidy3d.plugins.DispersionFitter#
- class tidy3d.plugins.DispersionFitter#
Tool for fitting refractive index data to get a dispersive medium described by
PoleResidue
model.- Parameters
wvl_um (Union[Tuple[float, ...], Array]) – [units = um]. Wavelength data in micrometers.
n_data (Union[Tuple[float, ...], Array]) – Real part of the complex index of refraction.
k_data (Union[Tuple[float, ...], Array] = None) – Imaginary part of the complex index of refraction.
wvl_range (Tuple[float, float] = (None, None)) – [units = um]. Truncate the wavelength-nk data to wavelength range [wvl_min,wvl_max] for fitting
Show JSON schema
{ "title": "DispersionFitter", "description": "Tool for fitting refractive index data to get a\ndispersive medium described by :class:`.PoleResidue` model.\n\nParameters\n----------\nwvl_um : Union[Tuple[float, ...], Array]\n [units = um]. Wavelength data in micrometers.\nn_data : Union[Tuple[float, ...], Array]\n Real part of the complex index of refraction.\nk_data : Union[Tuple[float, ...], Array] = None\n Imaginary part of the complex index of refraction.\nwvl_range : Tuple[float, float] = (None, None)\n [units = um]. Truncate the wavelength-nk data to wavelength range [wvl_min,wvl_max] for fitting", "type": "object", "properties": { "wvl_um": { "title": "Wavelength data", "description": "Wavelength data in micrometers.", "units": "um", "anyOf": [ { "type": "array", "items": { "type": "number" } }, { "title": "Array Like", "description": "Accepts sequence (tuple, list, numpy array) and converts to tuple.", "type": "tuple", "properties": {}, "required": [] } ] }, "n_data": { "title": "Index of refraction data", "description": "Real part of the complex index of refraction.", "anyOf": [ { "type": "array", "items": { "type": "number" } }, { "title": "Array Like", "description": "Accepts sequence (tuple, list, numpy array) and converts to tuple.", "type": "tuple", "properties": {}, "required": [] } ] }, "k_data": { "title": "Extinction coefficient data", "description": "Imaginary part of the complex index of refraction.", "anyOf": [ { "type": "array", "items": { "type": "number" } }, { "title": "Array Like", "description": "Accepts sequence (tuple, list, numpy array) and converts to tuple.", "type": "tuple", "properties": {}, "required": [] } ] }, "wvl_range": { "title": "Wavelength range [wvl_min,wvl_max] for fitting", "description": "Truncate the wavelength-nk data to wavelength range [wvl_min,wvl_max] for fitting", "default": [ null, null ], "units": "um", "type": "array", "minItems": 2, "maxItems": 2, "items": [ { "type": "number" }, { "type": "number" } ] }, "type": { "title": "Type", "default": "DispersionFitter", "enum": [ "DispersionFitter" ], "type": "string" } }, "required": [ "wvl_um", "n_data" ], "additionalProperties": false }
- attribute k_data: Union[Tuple[float, ...], tidy3d.components.types.Array] = None#
Imaginary part of the complex index of refraction.
- Validated by
_kdata_setup_and_length_match
- attribute n_data: Union[Tuple[float, ...], tidy3d.components.types.Array] [Required]#
Real part of the complex index of refraction.
- Validated by
_ndata_length_match_wvl
- attribute wvl_range: Tuple[Optional[float], Optional[float]] = (None, None)#
Truncate the wavelength-nk data to wavelength range [wvl_min,wvl_max] for fitting
- attribute wvl_um: Union[Tuple[float, ...], tidy3d.components.types.Array] [Required]#
Wavelength data in micrometers.
- Validated by
_setup_wvl
- fit(num_poles: int = 1, num_tries: int = 50, tolerance_rms: float = 0.01) Tuple[tidy3d.components.medium.PoleResidue, float] #
Fits data a number of times and returns best results.
- Parameters
num_poles (int, optional) – Number of poles in the model.
num_tries (int, optional) – Number of optimizations to run with random initial guess.
tolerance_rms (float, optional) – RMS error below which the fit is successful and the result is returned.
- Returns
Best results of multiple fits: (dispersive medium, RMS error).
- Return type
Tuple[
PoleResidue
, float]
- classmethod from_file(fname: str, **loadtxt_kwargs)#
Loads
DispersionFitter
from file containing wavelength, n, k data.- Parameters
fname (str) – Path to file containing wavelength (um), n, k (optional) data in columns.
**loadtxt_kwargs – Kwargs passed to
np.loadtxt
, such asskiprows
,delimiter
.
Hint
The data file should be in this format (
delimiter
andskiprows
can be customized in**loadtxt_kwargs
):For lossless media:
wl n [float] [float] . . . . . .
For lossy media:
wl n k [float] [float] [float] . . . . . . . . .
- Returns
A
DispersionFitter
instance.- Return type
- classmethod from_url(url_file: str, delimiter: str = ',', ignore_k: bool = False, **kwargs)#
loads
DispersionFitter
from url linked to a csv/txt file that contains wavelength (micron), n, and optionally k data. Preferred from refractiveindex.info.Hint
The data file from url should be in this format (delimiter not displayed here, and note that the strings such as “wl”, “n” need to be included in the file):
For lossless media:
wl n [float] [float] . . . . . .
For lossy media:
wl n [float] [float] . . . . . . wl k [float] [float] . . . . . .
- Parameters
url_file (str) – Url link to the data file. e.g. “https://refractiveindex.info/data_csv.php?datafile=data/main/Ag/Johnson.yml”
delimiter (str = ",") – E.g. in refractiveindex.info, it’ll be “,” for csv file, and “\t” for txt file.
ignore_k (bool = False) – Ignore the k data if they are present, so the fitted material is lossless.
- Returns
A
DispersionFitter
instance.- Return type
- plot(medium: tidy3d.components.medium.PoleResidue = None, wvl_um: Tuple[float, ...] = None, ax: matplotlib.axes._axes.Axes = None) matplotlib.axes._axes.Axes #
Make plot of model vs data, at a set of wavelengths (if supplied).
- Parameters
medium (
PoleResidue
= None) – medium containing model to plot against datawvl_um (Tuple[float, ...] = None) – Wavelengths to evaluate model at for plot in micrometers.
ax (matplotlib.axes._subplots.Axes = None) – Axes to plot the data on, if None, a new one is created.
- Returns
Matplotlib axis corresponding to plot.
- Return type
matplotlib.axis.Axes
- property eps_data: complex#
Convert filtered input n(k) data into complex permittivity.
- Returns
Complex-valued relative permittivty.
- Return type
complex
- property freqs: Tuple[float, ...]#
Convert filtered input wavelength data to frequency.
- Returns
Frequency array converted from filtered input wavelength data
- Return type
Tuple[float, …]
- property frequency_range: Tuple[float, float]#
Frequency range of filtered input data
- Returns
The minimal frequency and the maximal frequency
- Return type
Tuple[float, float]
- property lossy: bool#
Find out if the medium is lossy or lossless based on the filtered input data.
- Returns
True for lossy medium; False for lossless medium
- Return type
bool