H A D | functional_models.py | 1589 amplitude_L = Parameter(default=1, # noqa: N815 variable in Voigt1D 1603 def __init__(self, x_0=x_0.default, amplitude_L=amplitude_L.default, # noqa: N803 argument 1615 super().__init__(x_0=x_0, amplitude_L=amplitude_L, fwhm_L=fwhm_L, fwhm_G=fwhm_G, **kwargs) 1629 def evaluate(self, x, x_0, amplitude_L, fwhm_L, fwhm_G): # noqa: N803 argument 1635 return self._wrap_wofz(z).real * self.sqrt_ln2pi / fwhm_G * fwhm_L * amplitude_L 1637 def fit_deriv(self, x, x_0, amplitude_L, fwhm_L, fwhm_G): # noqa: N803 argument 1643 w = self._wrap_wofz(z) * s * fwhm_L * amplitude_L * self.sqrt_pi 1646 dwdz = -2 * z * w + 2j * s * fwhm_L * amplitude_L 1649 w.real / amplitude_L,
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