frostie.utils
=============

.. py:module:: frostie.utils


Functions
---------

.. autoapisummary::

   frostie.utils.load_water_op_cons
   frostie.utils.load_co2_op_cons
   frostie.utils.spectra_list_match
   frostie.utils.wav_bins
   frostie.utils.find_nearest
   frostie.utils.Z_to_sigma


Module Contents
---------------

.. py:function:: load_water_op_cons(wav_low=None, wav_high=None)

   Load water ice optical constants included in FROSTIE.

   :returns: * **wav** (*ndarray*) -- Wavelength array in microns.
             * **n** (*ndarray*) -- Real part of the refractive index.
             * **k** (*ndarray*) -- Imaginary part of the refractive index.


.. py:function:: load_co2_op_cons(wav_low=None, wav_high=None)

   Load carbon dioxide ice optical constants included in FROSTIE.

   :returns: * **wav** (*ndarray*) -- Wavelength array in microns.
             * **n** (*ndarray*) -- Real part of the refractive index.
             * **k** (*ndarray*) -- Imaginary part of the refractive index.


.. py:function:: spectra_list_match(data_list, wav_list)

   Resample all input spectra to a common wavelength axis.

   The common axis is chosen as the lowest-resolution wavelength array in the list.

   :param data_list: List of 1D arrays representing spectral data to be resampled.
   :type data_list: list of ndarray
   :param wav_list: Corresponding list of 1D wavelength arrays.
   :type wav_list: list of ndarray

   :returns: * **data_matched_list** (*list of ndarray*) -- Spectra resampled to the common wavelength grid.
             * **wav_common** (*ndarray*) -- Common wavelength axis used for resampling.


.. py:function:: wav_bins(wav)

   Compute the wavelength bin edges for a given wavelength array.

   :param wav: Wavelength array.
   :type wav: ndarray

   :returns: **bins** -- Bin widths between consecutive wavelengths.
   :rtype: ndarray


.. py:function:: find_nearest(array, value)

   Find the index of the array element closest to the supplied value.

   If multiple elements are equally close, the first match is returned.

   :param array: Array to search.
   :type array: ndarray
   :param value: Target value.
   :type value: float

   :returns: **index** -- Index of the closest array element.
   :rtype: int


.. py:function:: Z_to_sigma(ln_Z1, ln_Z2)

   Convert log-evidences of two models to a sigma confidence level.

   :param ln_Z1: Log-evidence of full model.
   :type ln_Z1: float
   :param ln_Z2: Log-evidence of reduced model.
   :type ln_Z2: float

   :returns: * **B** (*float*) -- Bayes factor.
             * **sigma** (*float*) -- Sigma confidence level.