resample#

resample(x: Union[jax.Array, numpy.ndarray, numpy.bool_, numpy.number, bool, int, float, complex], xp: Union[jax.Array, numpy.ndarray, numpy.bool_, numpy.number, bool, int, float, complex], sdict: Dict[Tuple[str, str], jaxtyping.Complex[Array, '...']]) → Dict[Tuple[str, str], jaxtyping.Complex[Array, '...']][source]#

Resample an s-dictionary to a new frequency grid.

Parameters

  • x (ArrayLike) – The x-coordinates at which to evaluate the interpolated values (desired frequency or wavelength grid).

  • xp (ArrayLike) – The x-coordinates of the data points, must be increasing (existing frequency or wavelength grid).

  • sdict (sax.SDict) – Dictionary of scattering parameters sampled at xp.

Returns

Dictionary of scattering parameters resampled at x.

Return type

sax.SDict

Examples

S-param files define frequencies, while most simulations are done in wavelength. You can resample the s-parameters to a new frequency grid using this function:

p = Path("dc_gap=200nm_Lc=0um.sparam")
_, df = load_sparams(p)
f, sdict = df_to_sdict(df)

wl = np.linspace(1.5, 1.6, 1000)
s_new = resample(wlum2freq(wl), f, sdict)
plt.plot(wl, np.abs(s_new["o1", "o3"]) ** 2)