# -*- coding: utf-8 -*-

# Third party imports
import numpy as np

# Local application imports
from mosqito.sound_level_meter.noct_spectrum.noct_synthesis import noct_synthesis
from mosqito.sq_metrics.loudness.loudness_zwst._main_loudness import _main_loudness
from mosqito.sq_metrics.loudness.loudness_zwst._calc_slopes import _calc_slopes
from mosqito.utils.conversion import amp2db


def loudness_zwst_freq(spectrum, freqs, field_type="free"):
    """Zwicker-loudness calculation for stationary signals

    Calculates the acoustic loudness according to Zwicker method for
    stationary signals.
    Normatice reference:
        ISO 532:1975 (method B)
        DIN 45631:1991
        ISO 532-1:2017 (method 1)
    The code is based on BASIC program published in "Program for
    calculating loudness according to DIN 45631 (ISO 532B)", E.Zwicker
    and H.Fastl, J.A.S.J (E) 12, 1 (1991).
    Note that due to normative continuity, as defined in the
    preceeding standards, the method is in accordance with
    ISO 226:1987 equal loudness contours (instead of ISO 226:2003)

    Parameters
    ----------
    spectrum : numpy.array
        A RMS frequency spectrum, size (Nfreq, Ntime)
    freqs : list
        List of the corresponding frequencies, size (Nfreq,) or (Nfreq, Ntime)
    field_type : str
        Type of soundfield corresponding to spec_third ("free" by
        default or "diffuse")

    Outputs
    -------
    N : float or numpy.array
        Calculated loudness [sones], size (Ntime,).
    N_specific : numpy.ndarray
        Specific loudness [sones/bark], size (Nbark, Ntime).
    bark_axis : numpy.array
        Frequency axis in bark, size (Nbark,).
    """
    if len(spectrum) != len(freqs):
        raise ValueError('Input spectrum and frequency axis must have the same shape')

    # Compute third octave band spectrum
    spec_third, _ = noct_synthesis(spectrum, freqs, fmin=24, fmax=12600)

    # Compute dB values
    spec_third = amp2db(spec_third, ref=2e-5)

    # Compute main loudness
    Nm = _main_loudness(spec_third, field_type)
    #
    # Computation of specific loudness pattern and integration of overall
    # loudness by attaching slopes towards higher frequencies
    N, N_specific = _calc_slopes(Nm)

    # Define Bark axis
    bark_axis = np.linspace(0.1, 24, int(24 / 0.1))

    return N, N_specific, bark_axis

# -*- coding: utf-8 -*-

# Third party imports
import numpy as np

# Local application imports
from mosqito.sound_level_meter.noct_spectrum.noct_synthesis import noct_synthesis
from mosqito.sq_metrics.loudness.loudness_zwst._main_loudness import _main_loudness
from mosqito.sq_metrics.loudness.loudness_zwst._calc_slopes import _calc_slopes
from mosqito.utils.conversion import amp2db


def loudness_zwst_freq(spectrum, freqs, field_type="free"):
    """Zwicker-loudness calculation for stationary signals

    Calculates the acoustic loudness according to Zwicker method for
    stationary signals.
    Normatice reference:
        ISO 532:1975 (method B)
        DIN 45631:1991
        ISO 532-1:2017 (method 1)
    The code is based on BASIC program published in "Program for
    calculating loudness according to DIN 45631 (ISO 532B)", E.Zwicker
    and H.Fastl, J.A.S.J (E) 12, 1 (1991).
    Note that due to normative continuity, as defined in the
    preceeding standards, the method is in accordance with
    ISO 226:1987 equal loudness contours (instead of ISO 226:2003)

    Parameters
    ----------
    spectrum : numpy.array
        A RMS frequency spectrum, size (Nfreq, Ntime)
    freqs : list
        List of the corresponding frequencies, size (Nfreq,) or (Nfreq, Ntime)
    field_type : str
        Type of soundfield corresponding to spec_third ("free" by
        default or "diffuse")

    Outputs
    -------
    N : float or numpy.array
        Calculated loudness [sones], size (Ntime,).
    N_specific : numpy.ndarray
        Specific loudness [sones/bark], size (Nbark, Ntime).
    bark_axis : numpy.array
        Frequency axis in bark, size (Nbark,).
    """
    if len(spectrum) != len(freqs):
        raise ValueError('Input spectrum and frequency axis must have the same shape')

    # Compute third octave band spectrum
    spec_third, _ = noct_synthesis(spectrum, freqs, fmin=24, fmax=12600)

    # Compute dB values
    spec_third = amp2db(spec_third, ref=2e-5)

    # Compute main loudness
    Nm = _main_loudness(spec_third, field_type)
    #
    # Computation of specific loudness pattern and integration of overall
    # loudness by attaching slopes towards higher frequencies
    N, N_specific = _calc_slopes(Nm)

    # Define Bark axis
    bark_axis = np.linspace(0.1, 24, int(24 / 0.1))

    return N, N_specific, bark_axis

# -*- coding: utf-8 -*- # Third party imports # Local application imports Zwicker-loudness calculation for stationary signals      Calculates the acoustic loudness according to Zwicker method for     stationary signals.     Normatice reference:         ISO 532:1975 (method B)         DIN 45631:1991         ISO 532-1:2017 (method 1)     The code is based on BASIC program published in "Program for     calculating loudness according to DIN 45631 (ISO 532B)", E.Zwicker     and H.Fastl, J.A.S.J (E) 12, 1 (1991).     Note that due to normative continuity, as defined in the     preceeding standards, the method is in accordance with     ISO 226:1987 equal loudness contours (instead of ISO 226:2003)      Parameters     ----------     spectrum : numpy.array         A RMS frequency spectrum, size (Nfreq, Ntime)     freqs : list         List of the corresponding frequencies, size (Nfreq,) or (Nfreq, Ntime)     field_type : str         Type of soundfield corresponding to spec_third ("free" by         default or "diffuse")      Outputs     -------     N : float or numpy.array         Calculated loudness [sones], size (Ntime,).     N_specific : numpy.ndarray         Specific loudness [sones/bark], size (Nbark, Ntime).     bark_axis : numpy.array         Frequency axis in bark, size (Nbark,). # Compute third octave band spectrum # Compute dB values # Compute main loudness # # Computation of specific loudness pattern and integration of overall # loudness by attaching slopes towards higher frequencies # Define Bark axis