tidy3d.plugins.dispersion.DispersionFitter#

class DispersionFitter[source]#

Bases: Tidy3dBaseModel

Tool for fitting refractive index data to get a dispersive medium described by PoleResidue model.

Parameters:

attrs (dict = {}) – Dictionary storing arbitrary metadata for a Tidy3D object. This dictionary can be freely used by the user for storing data without affecting the operation of Tidy3D as it is not used internally. Note that, unlike regular Tidy3D fields, attrs are mutable. For example, the following is allowed for setting an attr obj.attrs['foo'] = bar. Also note that Tidy3D` will raise a TypeError if attrs contain objects that can not be serialized. One can check if attrs are serializable by calling obj.json().
wvl_um (ArrayLike[dtype=float, ndim=1]) – [units = um]. Wavelength data in micrometers.
n_data (ArrayLike[dtype=float, ndim=1]) – Real part of the complex index of refraction.
k_data (Optional[ArrayLike[dtype=float, ndim=1]] = None) – Imaginary part of the complex index of refraction.
wvl_range (Tuple[float, float] = (None, None)) – [units = um]. Truncate the wavelength, n and k data to the wavelength range ‘[wvl_min, wvl_max]’ for fitting.

Attributes

`data_in_range`	Filter the wavelength-nk data to wavelength range for fitting.
`eps_data`	Convert filtered input n(k) data into complex permittivity.
`freqs`	Convert filtered input wavelength data to frequency.
`frequency_range`	Frequency range of filtered input data
`lossy`	Find out if the medium is lossy or lossless based on the filtered input data.
`attrs`

Methods

`fit`([num_poles, num_tries, tolerance_rms, guess])	Fit data a number of times and returns best results.
`from_complex_permittivity`(wvl_um, eps_real)	Loads `DispersionFitter` from wavelength and complex relative permittivity data
`from_file`(fname, **loadtxt_kwargs)	Loads `DispersionFitter` from file containing wavelength, n, k data.
`from_loss_tangent`(wvl_um, eps_real, loss_tangent)	Loads `DispersionFitter` from wavelength and loss tangent data.
`from_url`(url_file[, delimiter, ignore_k])	loads `DispersionFitter` from url linked to a csv/txt file that contains wavelength (micron), n, and optionally k data.
`plot`([medium, wvl_um, ax])	Make plot of model vs data, at a set of wavelengths (if supplied).

Inherited Common Usage

wvl_um#

n_data#

k_data#

wvl_range#

property data_in_range#

Filter the wavelength-nk data to wavelength range for fitting.

Returns:: Filtered wvl_um, n_data, k_data
Return type:: Tuple[ArrayFloat1D, ArrayFloat1D, ArrayFloat1D]

property lossy#

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

property eps_data#

Convert filtered input n(k) data into complex permittivity.

Returns:: Complex-valued relative permittivty.
Return type:: complex

property freqs#

Convert filtered input wavelength data to frequency.

Returns:: Frequency array converted from filtered input wavelength data
Return type:: Tuple[float, …]

property frequency_range#

Frequency range of filtered input data

Returns:: The minimal frequency and the maximal frequency
Return type:: Tuple[float, float]

fit(num_poles=1, num_tries=50, tolerance_rms=0.01, guess=None)[source]#

Fit 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 different initial guesses.
tolerance_rms (float, optional) – RMS error below which the fit is successful and the result is returned.
guess (PoleResidue = None) – A PoleResidue medium to use as the initial guess in the first optimization run.

Returns:

Best results of multiple fits: (dispersive medium, RMS error).

Return type:

Tuple[PoleResidue, float]

plot(medium=None, wvl_um=None, ax=None)[source]#

Make plot of model vs data, at a set of wavelengths (if supplied).

Parameters:

medium (PoleResidue = None) – medium containing model to plot against data
wvl_um (ArrayFloat1D = 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

classmethod from_url(url_file, delimiter=',', ignore_k=False, **kwargs)[source]#

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:

DispersionFitter

classmethod from_file(fname, **loadtxt_kwargs)[source]#

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 as skiprows, delimiter.

Hint

The data file should be in this format (delimiter and skiprows 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:: DispersionFitter

classmethod from_complex_permittivity(wvl_um, eps_real, eps_imag=None, wvl_range=(None, None))[source]#

Loads DispersionFitter from wavelength and complex relative permittivity data

Parameters:

wvl_um (ArrayFloat1D) – Wavelength data in micrometers.
eps_real (ArrayFloat1D) – Real parts of relative permittivity data
eps_imag (Optional[ArrayFloat1D]) – Imaginary parts of relative permittivity data; None for lossless medium.
wvg_range (Tuple[Optional[float], Optional[float]]) – Wavelength range [wvl_min,wvl_max] for fitting.

Returns:

A DispersionFitter instance.

Return type:

DispersionFitter

classmethod from_loss_tangent(wvl_um, eps_real, loss_tangent, wvl_range=(None, None))[source]#

Loads DispersionFitter from wavelength and loss tangent data.

Parameters:

wvl_um (ArrayFloat1D) – Wavelength data in micrometers.
eps_real (ArrayFloat1D) – Real parts of relative permittivity data
loss_tangent (Optional[ArrayFloat1D]) – Loss tangent data, defined as the ratio of imaginary and real parts of permittivity.
wvl_range (Tuple[Optional[float], Optional[float]]) – Wavelength range [wvl_min,wvl_max] for fitting.

Returns:

A DispersionFitter instance.

Return type:

DispersionFitter

__hash__()#: Hash method.

tidy3d.plugins.dispersion.DispersionFitter

Contents

tidy3d.plugins.dispersion.DispersionFitter#