# -*- coding: utf-8 -*-
"""Provide functionality to read optical constants in format provided by `refractiveindex.info <https://refractiveindex.info/>`_ website"""
# GPL license from Smuthi project

from scipy.interpolate import interp1d
import numpy as np
import yaml


def read_refractive_index_from_yaml(filename, vacuum_wavelength, units="mkm", kind=1):
    """Read optical constants in format provided by refractiveindex.info website.

    Args:
            filename (str): path and file name for yaml data
                            downloaded from refractiveindex.info
            vacuum_wavelength (float or np.array): wavelengths where refractive
                                                   index data is needed
            units (str): units for wavelength. currently, microns ('mkm' or 'um')
                         and nanometers ('nm') can be selected
            kind (int): order of interpolation

    Returns:
            A pair (or np.array of pairs) of wavelength and
            corresponding refractive index (complex)
    """
    if units == "nm":
        factor = 1000
    elif units in ("mkm", "um"):
        factor = 1
    else:
        raise NotImplementedError("Converting wavelength into '"+units
                                  + "' units for refractive index data"
                                  + " was not implemented.")

    with open(filename) as f:
        the_file = yaml.load(f, yaml.SafeLoader)['DATA'][0]
    data_type = the_file['type']
    if data_type != 'tabulated nk':
        raise NotImplementedError("Input data type '"+data_type
                                  + "' available in file "+filename
                                  + " was not implemented.")
    data = the_file['data'].splitlines()
    data_split = []
    for wl in data:
        data_split.append(wl.split())
    data_num = []
    for wl in data_split:
        record = []
        for val in wl:
            record.append(float(val))
        data_num.append(record)
    data_np = np.array(data_num)
    data_wl = data_np[:, 0]*factor
    index_re = data_np[:, 1]
    index_im = data_np[:, 2]
    f_re = interp1d(data_wl, index_re, kind=kind)
    f_im = interp1d(data_wl, index_im, kind=kind)
    data_out = np.transpose(np.vstack(
        (vacuum_wavelength, f_re(vacuum_wavelength)+f_im(vacuum_wavelength)*1j)))
    if len(data_out) == 1:
        return data_out[0]
    return data_out