import soundfile as sf 
import numpy as np
from scipy.fftpack import ifft, fft, rfft, fftshift, fftfreq
import scipy.signal as sig 
from scipy.signal import chirp
import matplotlib.pyplot as plt


def filter20_to_20k(x, fs):
    nyq = 0.5 * fs
    sos = sig.butter(5, [20.0 / nyq, 20000.0 / nyq], btype="band", output="sos")
    return sig.sosfilt(sos, x)


def normalize(data):
    assert isinstance(data, np.ndarray), "Assertion failed, input data is not an numpy array."
    return (data - data.min()) / (np.ptp(data))


def pad_input_to_output_length(x, y):
    """
    x: input array
    y: output array
    """
    # Output is always longer or the same length as input because of delay
    assert len(x) != len(y), "Arrays are already of the same length"
    x_pad = np.pad(x, (0, len(y)-len(x)), "constant", constant_values=(0, 0))
    return x_pad


def get_delay(in_data, out_data, fs, t):
    corr = np.correlate(in_data[:int(t*fs)], out_data[:int(t*fs)], mode="same")  # mode="same" makes it very slow => use small t
    return (int(len(corr)/2) - np.argmax(corr)) / fs  # seconds


def filename_generator(filename, N):
    filenames = []
    for i in range(N):
        name = filename + str(i) + ".wav"
        filenames.append(name)
    return filenames


def get_available_devices():
    raise NotImplementedError 


def decode(in_data, channels):
    in_data = np.fromstring(in_data, dtype=np.float32)
    # ...
    raise NotImplementedError


def encode(data):
    raise NotImplementedError


def generate_sweep(f1, f2, fs, T, volume):
    assert volume > 0 and volume <= 1, "The volume must be between 0 and 1"
    t = np.linspace(0, T, T*fs)
    w = (chirp(t, f1, T, f2, method='linear', phi=90)*volume).astype(np.float32)
    return w


def round_up_to_multiple(number, multiple):
    num = number + (multiple - 1)
    return num - (num % multiple)
3b4a065ef9cbf25f7a09caa90cb33d8acbc3141a
<mask token>


def normalize(data):
    assert isinstance(data, np.ndarray
        ), 'Assertion failed, input data is not an numpy array.'
    return (data - data.min()) / np.ptp(data)


def pad_input_to_output_length(x, y):
    """
    x: input array
    y: output array
    """
    assert len(x) != len(y), 'Arrays are already of the same length'
    x_pad = np.pad(x, (0, len(y) - len(x)), 'constant', constant_values=(0, 0))
    return x_pad


def get_delay(in_data, out_data, fs, t):
    corr = np.correlate(in_data[:int(t * fs)], out_data[:int(t * fs)], mode
        ='same')
    return (int(len(corr) / 2) - np.argmax(corr)) / fs


def filename_generator(filename, N):
    filenames = []
    for i in range(N):
        name = filename + str(i) + '.wav'
        filenames.append(name)
    return filenames


<mask token>


def decode(in_data, channels):
    in_data = np.fromstring(in_data, dtype=np.float32)
    raise NotImplementedError


def encode(data):
    raise NotImplementedError


def generate_sweep(f1, f2, fs, T, volume):
    assert volume > 0 and volume <= 1, 'The volume must be between 0 and 1'
    t = np.linspace(0, T, T * fs)
    w = (chirp(t, f1, T, f2, method='linear', phi=90) * volume).astype(np.
        float32)
    return w


<mask token>

<mask token>


def filter20_to_20k(x, fs):
    nyq = 0.5 * fs
    sos = sig.butter(5, [20.0 / nyq, 20000.0 / nyq], btype='band', output='sos'
        )
    return sig.sosfilt(sos, x)


def normalize(data):
    assert isinstance(data, np.ndarray
        ), 'Assertion failed, input data is not an numpy array.'
    return (data - data.min()) / np.ptp(data)


def pad_input_to_output_length(x, y):
    """
    x: input array
    y: output array
    """
    assert len(x) != len(y), 'Arrays are already of the same length'
    x_pad = np.pad(x, (0, len(y) - len(x)), 'constant', constant_values=(0, 0))
    return x_pad


def get_delay(in_data, out_data, fs, t):
    corr = np.correlate(in_data[:int(t * fs)], out_data[:int(t * fs)], mode
        ='same')
    return (int(len(corr) / 2) - np.argmax(corr)) / fs


def filename_generator(filename, N):
    filenames = []
    for i in range(N):
        name = filename + str(i) + '.wav'
        filenames.append(name)
    return filenames


<mask token>


def decode(in_data, channels):
    in_data = np.fromstring(in_data, dtype=np.float32)
    raise NotImplementedError


def encode(data):
    raise NotImplementedError


def generate_sweep(f1, f2, fs, T, volume):
    assert volume > 0 and volume <= 1, 'The volume must be between 0 and 1'
    t = np.linspace(0, T, T * fs)
    w = (chirp(t, f1, T, f2, method='linear', phi=90) * volume).astype(np.
        float32)
    return w


<mask token>

<mask token>


def filter20_to_20k(x, fs):
    nyq = 0.5 * fs
    sos = sig.butter(5, [20.0 / nyq, 20000.0 / nyq], btype='band', output='sos'
        )
    return sig.sosfilt(sos, x)


def normalize(data):
    assert isinstance(data, np.ndarray
        ), 'Assertion failed, input data is not an numpy array.'
    return (data - data.min()) / np.ptp(data)


def pad_input_to_output_length(x, y):
    """
    x: input array
    y: output array
    """
    assert len(x) != len(y), 'Arrays are already of the same length'
    x_pad = np.pad(x, (0, len(y) - len(x)), 'constant', constant_values=(0, 0))
    return x_pad


def get_delay(in_data, out_data, fs, t):
    corr = np.correlate(in_data[:int(t * fs)], out_data[:int(t * fs)], mode
        ='same')
    return (int(len(corr) / 2) - np.argmax(corr)) / fs


def filename_generator(filename, N):
    filenames = []
    for i in range(N):
        name = filename + str(i) + '.wav'
        filenames.append(name)
    return filenames


<mask token>


def decode(in_data, channels):
    in_data = np.fromstring(in_data, dtype=np.float32)
    raise NotImplementedError


def encode(data):
    raise NotImplementedError


def generate_sweep(f1, f2, fs, T, volume):
    assert volume > 0 and volume <= 1, 'The volume must be between 0 and 1'
    t = np.linspace(0, T, T * fs)
    w = (chirp(t, f1, T, f2, method='linear', phi=90) * volume).astype(np.
        float32)
    return w


def round_up_to_multiple(number, multiple):
    num = number + (multiple - 1)
    return num - num % multiple

<mask token>


def filter20_to_20k(x, fs):
    nyq = 0.5 * fs
    sos = sig.butter(5, [20.0 / nyq, 20000.0 / nyq], btype='band', output='sos'
        )
    return sig.sosfilt(sos, x)


def normalize(data):
    assert isinstance(data, np.ndarray
        ), 'Assertion failed, input data is not an numpy array.'
    return (data - data.min()) / np.ptp(data)


def pad_input_to_output_length(x, y):
    """
    x: input array
    y: output array
    """
    assert len(x) != len(y), 'Arrays are already of the same length'
    x_pad = np.pad(x, (0, len(y) - len(x)), 'constant', constant_values=(0, 0))
    return x_pad


def get_delay(in_data, out_data, fs, t):
    corr = np.correlate(in_data[:int(t * fs)], out_data[:int(t * fs)], mode
        ='same')
    return (int(len(corr) / 2) - np.argmax(corr)) / fs


def filename_generator(filename, N):
    filenames = []
    for i in range(N):
        name = filename + str(i) + '.wav'
        filenames.append(name)
    return filenames


def get_available_devices():
    raise NotImplementedError


def decode(in_data, channels):
    in_data = np.fromstring(in_data, dtype=np.float32)
    raise NotImplementedError


def encode(data):
    raise NotImplementedError


def generate_sweep(f1, f2, fs, T, volume):
    assert volume > 0 and volume <= 1, 'The volume must be between 0 and 1'
    t = np.linspace(0, T, T * fs)
    w = (chirp(t, f1, T, f2, method='linear', phi=90) * volume).astype(np.
        float32)
    return w


def round_up_to_multiple(number, multiple):
    num = number + (multiple - 1)
    return num - num % multiple

import soundfile as sf 
import numpy as np
from scipy.fftpack import ifft, fft, rfft, fftshift, fftfreq
import scipy.signal as sig 
from scipy.signal import chirp
import matplotlib.pyplot as plt


def filter20_to_20k(x, fs):
    nyq = 0.5 * fs
    sos = sig.butter(5, [20.0 / nyq, 20000.0 / nyq], btype="band", output="sos")
    return sig.sosfilt(sos, x)


def normalize(data):
    assert isinstance(data, np.ndarray), "Assertion failed, input data is not an numpy array."
    return (data - data.min()) / (np.ptp(data))


def pad_input_to_output_length(x, y):
    """
    x: input array
    y: output array
    """
    # Output is always longer or the same length as input because of delay
    assert len(x) != len(y), "Arrays are already of the same length"
    x_pad = np.pad(x, (0, len(y)-len(x)), "constant", constant_values=(0, 0))
    return x_pad


def get_delay(in_data, out_data, fs, t):
    corr = np.correlate(in_data[:int(t*fs)], out_data[:int(t*fs)], mode="same")  # mode="same" makes it very slow => use small t
    return (int(len(corr)/2) - np.argmax(corr)) / fs  # seconds


def filename_generator(filename, N):
    filenames = []
    for i in range(N):
        name = filename + str(i) + ".wav"
        filenames.append(name)
    return filenames


def get_available_devices():
    raise NotImplementedError 


def decode(in_data, channels):
    in_data = np.fromstring(in_data, dtype=np.float32)
    # ...
    raise NotImplementedError


def encode(data):
    raise NotImplementedError


def generate_sweep(f1, f2, fs, T, volume):
    assert volume > 0 and volume <= 1, "The volume must be between 0 and 1"
    t = np.linspace(0, T, T*fs)
    w = (chirp(t, f1, T, f2, method='linear', phi=90)*volume).astype(np.float32)
    return w


def round_up_to_multiple(number, multiple):
    num = number + (multiple - 1)
    return num - (num % multiple)