# Path: pambox/inner.py
# CENTER_F = np.asarray([63, 80, 100, 125, 160, 200, 250, 315, 400, 500,
#                        630, 800, 1000, 1250, 1600, 2000, 2500, 3150, 4000,
#                        5000, 6300, 8000])
# FS = np.asarray([22050.])
#         X = rfft(x)
#     N = next_pow_2(N_orig)
# def erb_bandwidth(fc):
# def lowpass_env_filtering(x, cutoff=150., n=1, fs=22050):
#     def __init__(self, fs, cf, b=1.019, order=1, q=9.26449, min_bw=24.7):
#     def _calculate_coefficients(self):
#     def filter(self, x):
#     def __init__(self, fs, center_f, width=3, output_time=False):
#     def filter(self, x):
# def hilbert_envelope(signal):
# class GammatoneFilterbank(object):
# class RectangularFilterbank(object):


import csv
import os.path
import numpy as np
import scipy.io as sio
import pytest
from numpy.testing import assert_allclose
from pambox import inner
    from itertools import product
                           'test_third_octave_filtering_of_noise.csv')) as \
            csv_file:
        pass
        data_file = csv.reader(csv_file)
        temp = next(data_file)
        n_samples = int(temp[0])
        x = np.empty(n_samples)

        for i, s in enumerate(data_file):
            x[i] = np.asarray(s, dtype=np.float)

    target = np.array([ 151.66437785,  688.6881118 ])
    center_f = [63, 125]
    fs = 22050
    filterbank = inner.RectangularFilterbank(fs, center_f, width=3)
    rms_out = filterbank.filter(x)
    assert_allclose(rms_out, target, rtol=1e-4)


@pytest.mark.parametrize("x, target", [
    ([0, 1, 2, 1, 0],
     [0.70710678, 1.56751612, 2., 1.56751612, 0.70710678]),
    ([0, 1, 2, 1, 0],
     [0.70710678, 1.56751612, 2., 1.56751612, 0.70710678]),
    ([[0, 1], [0, 1]],
     [[0., 1.], [0., 1.]]),
    ([[0, 1, 0], [2, 3, 0]],
     [[0.5, 1., 0.5], [2.5, 3.16227766, 1.5]]),
    ])
def test_hilbert_env_on_2d_array_with_last_dimension(x, target):

# Path: pambox/inner.py
# CENTER_F = np.asarray([63, 80, 100, 125, 160, 200, 250, 315, 400, 500,
#                        630, 800, 1000, 1250, 1600, 2000, 2500, 3150, 4000,
#                        5000, 6300, 8000])
# FS = np.asarray([22050.])
#         X = rfft(x)
#     N = next_pow_2(N_orig)
# def erb_bandwidth(fc):
# def lowpass_env_filtering(x, cutoff=150., n=1, fs=22050):
#     def __init__(self, fs, cf, b=1.019, order=1, q=9.26449, min_bw=24.7):
#     def _calculate_coefficients(self):
#     def filter(self, x):
#     def __init__(self, fs, center_f, width=3, output_time=False):
#     def filter(self, x):
# def hilbert_envelope(signal):
# class GammatoneFilterbank(object):
# class RectangularFilterbank(object):


# Path: pambox/tests/test_inner.py
import csv
import os.path
import numpy as np
import scipy.io as sio
import pytest
from numpy.testing import assert_allclose
from pambox import inner
    from itertools import product

                           'test_third_octave_filtering_of_noise.csv')) as \
            csv_file:
        pass
        data_file = csv.reader(csv_file)
        temp = next(data_file)
        n_samples = int(temp[0])
        x = np.empty(n_samples)

        for i, s in enumerate(data_file):
            x[i] = np.asarray(s, dtype=np.float)

    target = np.array([ 151.66437785,  688.6881118 ])
    center_f = [63, 125]
    fs = 22050
    filterbank = inner.RectangularFilterbank(fs, center_f, width=3)
    rms_out = filterbank.filter(x)
    assert_allclose(rms_out, target, rtol=1e-4)


@pytest.mark.parametrize("x, target", [
    ([0, 1, 2, 1, 0],
     [0.70710678, 1.56751612, 2., 1.56751612, 0.70710678]),
    ([0, 1, 2, 1, 0],
     [0.70710678, 1.56751612, 2., 1.56751612, 0.70710678]),
    ([[0, 1], [0, 1]],
     [[0., 1.], [0., 1.]]),
    ([[0, 1, 0], [2, 3, 0]],
     [[0.5, 1., 0.5], [2.5, 3.16227766, 1.5]]),
    ])
def test_hilbert_env_on_2d_array_with_last_dimension(x, target):

    env = inner.hilbert_envelope(x)