import os
from io import BytesIO

import numpy as np

from amodem import send
from amodem import recv
from amodem import common
from amodem import sigproc

import logging
logging.basicConfig(level=logging.DEBUG,
                    format='%(asctime)s %(levelname)-12s %(message)s')


class Args(object):
    def __init__(self, **kwargs):
        self.__dict__.update(kwargs)


def run(size, chan):
    tx_data = os.urandom(size)
    tx_audio = BytesIO()
    send.main(Args(silence_start=1, silence_stop=1,
              input=BytesIO(tx_data), output=tx_audio))

    data = tx_audio.getvalue()
    data = common.loads(data)
    data = chan(data)
    data = common.dumps(data)
    rx_audio = BytesIO(data)

    rx_data = BytesIO()
    recv.main(Args(skip=100, input=rx_audio, output=rx_data))
    rx_data = rx_data.getvalue()

    assert rx_data == tx_data

def apply_filter(b, a, x):
    f = sigproc.Filter(b=b, a=a)
    y = list(f(list(x)))
    return np.array(y)


def test_lowpass():
    run(1024, lambda x: apply_filter(b=[0.9], a=[1.0, -0.1], x=x))


def test_highpass():
    run(1024, lambda x: apply_filter(b=[0.9], a=[1.0, 0.1], x=x))


def test_small():
    run(1024, lambda x: x)


def test_large():
    run(54321, lambda x: x)


def test_attenuation():
    run(5120, lambda x: x * 0.1)


def test_low_noise():
    r = np.random.RandomState(seed=0)
    run(5120, lambda x: x + r.normal(size=len(x), scale=0.0001))


def test_medium_noise():
    r = np.random.RandomState(seed=0)
    run(5120, lambda x: x + r.normal(size=len(x), scale=0.001))