Remove SpeX fitting

[mdecleir]

This function to fit SpeX extinction data should be removed from this repository.
A more extended fitting is done in the spex_nir_extinction repo.

I expect that in the future, most stars will not have SpeX data available, so this should not be the default way to calculate A(V).

measure_extinction/measure_extinction/extdata.py

Lines 1344 to 1406 in d13198c

	def fit_spex_ext(
	self, amp_bounds=(-1.5, 1.5), index_bounds=(0.0, 5.0), AV_bounds=(0.0, 6.0)
	):
	"""
	Fit the observed NIR extinction curve with a powerlaw model, based on the SpeX spectra
	Parameters
	----------
	amp_bounds : tuple [default=(-1.5,1.5)]
	Model amplitude bounds to be used in the fitting
	index_bounds : tuple [default=(0.0,5.0)]
	Powerlaw index bounds to be used in the fitting
	AV_bounds : tuple [default=(0.0,6.0)]
	A(V) bounds to be used in the fitting
	Returns
	-------
	Updates self.model["waves", "exts", "residuals", "params"] and self.columns["AV"] with the fitting results:
	- waves: np.ndarray with the wavelengths used in the fitting
	- exts: np.ndarray with the fitted powerlaw model to the extinction curve
	- residuals: np.ndarray with the fractional residuals, i.e. (data-fit)/fit
	- params: tuple with the parameters (amplitude, alpha) if data in A(lambda)/A(V) or (amplitude, alpha, A(V)) if data in E(lambda-V)
	"""
	# retrieve the SpeX data, and sort the curve from short to long wavelengths
	(waves, exts, exts_unc) = self.get_fitdata(["SpeX_SXD", "SpeX_LXD"])
	indx = np.argsort(waves)
	waves = waves[indx].value
	exts = exts[indx]
	exts_unc = exts_unc[indx]
	# fit a powerlaw to the spectrum
	if self.type == "alav":
	func = PowerLaw1D(
	fixed={"x_0": True},
	bounds={"amplitude": amp_bounds, "alpha": index_bounds},
	)
	else:
	func = (
	PowerLaw1D(
	fixed={"x_0": True},
	bounds={"amplitude": amp_bounds, "alpha": index_bounds},
	)
	| AxAvToExv(bounds={"Av": AV_bounds})
	)
	fit = LevMarLSQFitter()
	fit_result = fit(func, waves, exts, weights=1 / exts_unc)
	# save the fitting results
	self.model["waves"] = waves
	self.model["exts"] = fit_result(waves)
	self.model["residuals"] = exts - self.model["exts"]
	if self.type == "alav":
	self.model["params"] = (fit_result.amplitude.value, fit_result.alpha.value)
	else: # in this case, fitted amplitude has to be multiplied by A(V) to get the "combined" amplitude
	self.model["params"] = (
	fit_result.amplitude_0.value * fit_result.Av_1.value,
	fit_result.alpha_0.value,
	fit_result.Av_1.value,
	)
	self.columns["AV"] = fit_result.Av_1.value