# Path: friture/filter.py
# def octave_frequencies(total_bands_count, bands_per_octave):
#     f0 = 1000.  # audio reference frequency is 1 kHz
# 
#     b = 1. / bands_per_octave
# 
#     imax = total_bands_count // 2
#     if total_bands_count % 2 == 0:
#         i = arange(-imax, imax)
#     else:
#         i = arange(-imax, imax + 1)
# 
#     fi = f0 * 2 ** (i * b)
#     f_low = fi * sqrt(2 ** (-b))
#     f_high = fi * sqrt(2 ** b)
# 
#     return fi, f_low, f_high
# 
# def octave_filter_bank(forward, feedback, x, zis=None):
#     # This function filters the waveform x with the array of filters
#     # specified by the forward and feedback parameters. Each row
#     # of the forward and feedback parameters are the parameters
#     # to the Matlab builtin function "filter".
#     filter_count = len(forward)
#     y = zeros((filter_count, len(x)))
# 
#     zfs = []
#     y = []
# 
#     if zis is None:
#         zis = []
#         for i in range(0, filter_count):
#             zis += [zeros(max(len(forward[i]), len(feedback[i])) - 1)]
# 
#     for i in range(0, filter_count):
#         filt, zf = pyx_lfilter_float64_1D(forward[i], feedback[i], x, zis[i])
#         # zf can be reused to restart the filter
#         zfs += [zf]
#         y += [filt]
# 
#     return y, zfs
# 
# def octave_filter_bank_decimation(blow, alow, forward, feedback, x, zis):
#     # This function filters the waveform x with the array of filters
#     # specified by the forward and feedback parameters. Each row
#     # of the forward and feedback parameters are the parameters
#     # to the Matlab builtin function "filter".
#     bands_per_octave = len(forward)
#     filter_count = NOCTAVE * bands_per_octave
# 
#     y = [0.] * filter_count
#     dec = [0.] * filter_count
# 
#     x_dec = x
# 
#     zfs = []
# 
#     m = 0
#     k = filter_count - 1
# 
#     for j in range(0, NOCTAVE):
#         for i in range(0, bands_per_octave)[::-1]:
#             filt, zf = pyx_lfilter_float64_1D(forward[i], feedback[i], x_dec, zis[m])
#             m += 1
#             # zf can be reused to restart the filter
#             zfs += [zf]
#             y[k] = filt
#             dec[k] = 2 ** j
#             k -= 1
#         x_dec, zf = decimate(blow, alow, x_dec, zis[m])
#         m += 1
#         # zf can be reused to restart the filter
#         zfs += [zf]
# 
#     return y, dec, zfs
# 
# NOCTAVE = 9
# 
# Path: friture/audiobackend.py
# SAMPLING_RATE = 48000


from numpy import pi, exp, arange, cos, sin, sqrt, zeros, ones, log, arange, set_printoptions
from scipy.special import factorial
from scipy.signal.signaltools import lfilter
from scipy.signal.filter_design import ellip, butter, cheby1, iirdesign, freqz
from scipy.signal.fir_filter_design import firwin
from friture.filter import (octave_frequencies, octave_filter_bank,
                            octave_filter_bank_decimation, NOCTAVE)
from friture.audiobackend import SAMPLING_RATE
    from matplotlib.pyplot import semilogx, plot, show, xlim, ylim, figure, legend, subplot, bar
    from numpy.fft import fft, fftfreq, fftshift, ifft
    from numpy import log10, linspace, interp, angle, array, concatenate
import scipy
import sys
    import os
    import json
        [b, a] = ellip(order, pbrip, sbrip, freq, btype='bandpass')

        B += [b.tolist()]
        A += [a.tolist()]

    return [B, A, fi, f_low, f_high]


def generate_filters_params():

    params = {}

    # generate the low-pass filter for decimation
    Ndec = 3
    fc = 0.5
    # other possibilities
    # (bdec, adec) = ellip(Ndec, 0.05, 30, fc)
    # print(bdec)
    # (bdec, adec) = cheby1(Ndec, 0.05, fc)
    # (bdec, adec) = butter(Ndec, fc)
    (bdec, adec) = iirdesign(0.48, 0.50, 0.05, 70, analog=0, ftype='ellip', output='ba')
    # bdec = firwin(30, fc)
    # adec = [1.]

    # set_printoptions(precision=24)

    params['dec'] = [bdec.tolist(), adec.tolist()]

    # generate the octave filters
    for bands_per_octave in [1, 3, 6, 12, 24]:

# Path: friture/filter.py
# def octave_frequencies(total_bands_count, bands_per_octave):
#     f0 = 1000.  # audio reference frequency is 1 kHz
# 
#     b = 1. / bands_per_octave
# 
#     imax = total_bands_count // 2
#     if total_bands_count % 2 == 0:
#         i = arange(-imax, imax)
#     else:
#         i = arange(-imax, imax + 1)
# 
#     fi = f0 * 2 ** (i * b)
#     f_low = fi * sqrt(2 ** (-b))
#     f_high = fi * sqrt(2 ** b)
# 
#     return fi, f_low, f_high
# 
# def octave_filter_bank(forward, feedback, x, zis=None):
#     # This function filters the waveform x with the array of filters
#     # specified by the forward and feedback parameters. Each row
#     # of the forward and feedback parameters are the parameters
#     # to the Matlab builtin function "filter".
#     filter_count = len(forward)
#     y = zeros((filter_count, len(x)))
# 
#     zfs = []
#     y = []
# 
#     if zis is None:
#         zis = []
#         for i in range(0, filter_count):
#             zis += [zeros(max(len(forward[i]), len(feedback[i])) - 1)]
# 
#     for i in range(0, filter_count):
#         filt, zf = pyx_lfilter_float64_1D(forward[i], feedback[i], x, zis[i])
#         # zf can be reused to restart the filter
#         zfs += [zf]
#         y += [filt]
# 
#     return y, zfs
# 
# def octave_filter_bank_decimation(blow, alow, forward, feedback, x, zis):
#     # This function filters the waveform x with the array of filters
#     # specified by the forward and feedback parameters. Each row
#     # of the forward and feedback parameters are the parameters
#     # to the Matlab builtin function "filter".
#     bands_per_octave = len(forward)
#     filter_count = NOCTAVE * bands_per_octave
# 
#     y = [0.] * filter_count
#     dec = [0.] * filter_count
# 
#     x_dec = x
# 
#     zfs = []
# 
#     m = 0
#     k = filter_count - 1
# 
#     for j in range(0, NOCTAVE):
#         for i in range(0, bands_per_octave)[::-1]:
#             filt, zf = pyx_lfilter_float64_1D(forward[i], feedback[i], x_dec, zis[m])
#             m += 1
#             # zf can be reused to restart the filter
#             zfs += [zf]
#             y[k] = filt
#             dec[k] = 2 ** j
#             k -= 1
#         x_dec, zf = decimate(blow, alow, x_dec, zis[m])
#         m += 1
#         # zf can be reused to restart the filter
#         zfs += [zf]
# 
#     return y, dec, zfs
# 
# NOCTAVE = 9
# 
# Path: friture/audiobackend.py
# SAMPLING_RATE = 48000


# Path: friture/filter_design.py
from numpy import pi, exp, arange, cos, sin, sqrt, zeros, ones, log, arange, set_printoptions
from scipy.special import factorial
from scipy.signal.signaltools import lfilter
from scipy.signal.filter_design import ellip, butter, cheby1, iirdesign, freqz
from scipy.signal.fir_filter_design import firwin
from friture.filter import (octave_frequencies, octave_filter_bank,
                            octave_filter_bank_decimation, NOCTAVE)
from friture.audiobackend import SAMPLING_RATE
    from matplotlib.pyplot import semilogx, plot, show, xlim, ylim, figure, legend, subplot, bar
    from numpy.fft import fft, fftfreq, fftshift, ifft
    from numpy import log10, linspace, interp, angle, array, concatenate
import scipy
import sys
    import os
    import json

        [b, a] = ellip(order, pbrip, sbrip, freq, btype='bandpass')

        B += [b.tolist()]
        A += [a.tolist()]

    return [B, A, fi, f_low, f_high]


def generate_filters_params():

    params = {}

    # generate the low-pass filter for decimation
    Ndec = 3
    fc = 0.5
    # other possibilities
    # (bdec, adec) = ellip(Ndec, 0.05, 30, fc)
    # print(bdec)
    # (bdec, adec) = cheby1(Ndec, 0.05, fc)
    # (bdec, adec) = butter(Ndec, fc)
    (bdec, adec) = iirdesign(0.48, 0.50, 0.05, 70, analog=0, ftype='ellip', output='ba')
    # bdec = firwin(30, fc)
    # adec = [1.]

    # set_printoptions(precision=24)

    params['dec'] = [bdec.tolist(), adec.tolist()]

    # generate the octave filters
    for bands_per_octave in [1, 3, 6, 12, 24]:

        total_band_count = NOCTAVE * bands_per_octave