# template file for Lab #6, Task #5
import numpy
import matplotlib.pyplot as p
import lab6
from lab6_1 import freq_res_usr
from lab6_2 import zfreqs_to_usr

# return unit-sample response for a single-frequency notch
# filter at the specified frequency
def notch_one_freq(freq):
    pass  # your code here

# Using notch_one_freq, create a notch filter at the frequency
# of the hum (you'll have to convert 400Hz to the appropriate
# omega), and then apply the filter to a numpy array of audio
# samples.
def eliminate_hum(audio_samples):
    pass  # your code here

if __name__ == '__main__':
    # plot freq response of notch_one_freq @ pi/2
    omega_notch, mag_hejw_notch = \
      freq_res_usr(notch_one_freq(numpy.pi/2))
    lab6.plot_freq_response(omega_notch,mag_hejw_notch,
      'notch filter @ $\Omega=\pi/2$')
    print "Please close plot window to start audio playback."
    p.show()

    # Read in the good sound and play
    without_hum = lab6.read_sound('without_hum.wav')
    lab6.play_sound(without_hum)
    
    # Read in the corrupted sound and play
    with_hum = lab6.read_sound('with_hum.wav')
    lab6.play_sound(with_hum)

    # Filter the sound and play
    hum_removed = eliminate_hum(with_hum)
    lab6.play_sound(hum_removed)