def command_instrumental(*args):
if len(args) != 2:
usage()
return
w = wav.Wav(args[0])
out = music.extract_instrumentals(w.time_series)
wav.write(args[1], out, w.sample_rate)
def command_transpose(*args):
if len(args) != 3:
usage()
return
w = wav.Wav(args[0])
out = music.transpose_key(float(args[2]), w)
wav.write(args[1], out, w.sample_rate)
def main():
if not os.path.exists("../img"):
os.mkdir("../img", 0755)
fs = 44100 # in Hz
length = 0.01 # in seconds
t = np.linspace(0, length, num=length * fs)
h_function = lambda t: b * np.exp(-t / tau)
h = h_function(t)
plt.plot(h, t, fs, 3, "h(t)", "Signal h(t)")
plt.savefig("../img/4.1-transfer_function.png")
x_function = lambda t: a1 * np.cos(2 * np.pi * f1 * t) + a2 * np.sin(
2 * np.pi * f2 * t) + a3 * np.cos(2 * np.pi * f3 * t)
x = x_function(t)
plt.plot(x, t, fs, 10, "x(t)", "Signal x(t)")
yx = np.convolve(h, x)
plt.plot(np.array([x, yx[0:len(t)]]), t, fs, 10, "yx(t)", "Signal yx(t)")
plt.savefig("../img/4.2-sines.png")
z_function = lambda t: A * (abs((t - T / 2) / T) < 1.0)
z = z_function(t)
yz = np.convolve(h, z)
plt.plot(np.array([z, yz[0:len(t)]]), t, fs, 10, "yz(t)", "Signal yz(t)")
plt.savefig("../img/4.3-rect.png")
w, tw, rate, size, max = wav.readWav("../3-audio/af2.wav")
h = h_function(tw) # new sample rate and time vector
yw = np.convolve(h, w)
plt.plot(np.array([w, yw[0:len(tw)]]), tw, rate, 10, "yw(t)",
"Signal yw(t)")
rel_max = np.amax(yw) if np.amax(yw) > abs(np.amin(yw)) else abs(
np.amin(yw))
yw = yw * (max / rel_max)
wav.write("convoluted.wav", rate, yw.astype(np.dtype('i2')))
plt.savefig("../img/4.4-audio.png")
def command_mash(*args):
wavs = [wav.Wav(w) for w in args[:-1]]
out = mashup.generate(wavs)
wav.write(args[-1], out, 44100)