"""
Plot a fitted spectrum
======================
This is an example showing how to plot the result of fitting
a spectrum using the :class:`~mcalf.models.IBIS8542Model` class.
"""

#%%
# First we shall create a list of wavelengths, with a variable
# wavelength spacing.
# Next, we shall use the Voigt profile to generate spectral
# intensities at each of the wavelength points.
# Typically you would provide a spectrum obtained from observations.
#
# The data in this example are produced from randomly selected
# parameters, so numerical values in this example should be ignored.

import numpy as np
from mcalf.models import IBIS8542Model
from mcalf.profiles.voigt import double_voigt

# Create the wavelength grid and intensity values
wavelengths = np.linspace(8541, 8543, 20)
wavelengths = np.delete(wavelengths, np.s_[1:6:2])
wavelengths = np.delete(wavelengths, np.s_[-6::2])

spectrum = double_voigt(wavelengths, -526, 8542, 0.1, 0.1,
                        300, 8541.9, 0.2, 0.05, 1242)

#%%

from mcalf.visualisation import plot_spectrum

plot_spectrum(wavelengths, spectrum, normalised=False)

#%%
# A basic model is created,

model = IBIS8542Model(original_wavelengths=wavelengths)

#%%
# The spectrum is provided to the model's fit method.
# A classifier has not been loaded so the classification must be
# provided manually.
# The fitting algorithm assumes that the intensity at the ends of the
# spectrum is zero, so in this case we need to provide it with a
# background value to subtract from the spectrum before fitting.
fit = model.fit(spectrum=spectrum, classifications=4, background=1242)

print(fit)

#%%
# The spectrum can now be plotted,

# sphinx_gallery_thumbnail_number = 2
model.plot(fit, spectrum=spectrum, background=1242)

#%%
# If an array of spectra and associated background values
# had been loaded into the model with the
# :meth:`~mcalf.models.ModelBase.load_array` and
# :meth:`~mcalf.models.ModelBase.load_background`
# methods respectively, the ``spectrum`` and ``background``
# parameters would not have to be specified when plotting.
# This is because the ``fit`` object would contain
# indices that the ``model`` object would use to look
# up the original loaded values.
#
# Equivalent to above, the plot method can be called on
# the fit object directly. Remember to specify the ``model``
# which is needed for additional information such as the
# stationary line core value.

fit.plot(model, spectrum=spectrum, background=1242)

#%%
# If the fit has multiple spectral components, such as
# an active emission profile mixed with a quiescent
# absorption profile, the follow method can be used
# to plot the components separatly.
#
# If the fit only has a single component the ``plot``
# method as shown above is used.

model.plot_separate(fit, spectrum=spectrum, background=1242)

#%%
# If the fit has an emission component, it is subtracted
# from the raw spectral data. Otherwise, the default
# ``plot`` method is used.

model.plot_subtraction(fit, spectrum=spectrum, background=1242)

#%%
# The same line on multiple plots is only labelled the first time it
# plotted in the figure. This prevents duplicated entries in
# legends.

import matplotlib.pyplot as plt

fig, ax = plt.subplots(1, 2)

model.plot(fit, spectrum=spectrum, background=1242,
           show_legend=False, ax=ax[0])
model.plot_separate(fit, spectrum=spectrum, background=1242,
                    show_legend=False, ax=ax[1])

fig.subplots_adjust(top=0.75)  # Create space above for legend
fig.legend(ncol=2, loc='upper center', bbox_to_anchor=(0.5, 0.97))

plt.show()

#%%
# The underlying :func:`mcalf.visualisation.plot_ibis8542`
# function can be used directly. However, it is recommended
# to plot using the method detailed above as it will do
# additional processing to the wavelengths and spectrum
# and also pass additional parameters, such as sigma,
# to this fitting function.

from mcalf.visualisation import plot_ibis8542

plot_ibis8542(wavelengths, spectrum, fit.parameters, 1242)

#%%
# The y-axis and legend can be easily hidden,

model.plot(fit, spectrum=spectrum, background=1242,
           show_intensity=False, show_legend=False)