def test_noise():
N = 500
rate = 1.0
w = noise.white(N)
b = noise.brown(N)
v = noise.violet(N)
p = noise.pink(N)
assert len(w) == N
assert len(b) == N
assert len(v) == N - 1 # why?
assert len(p) == N
def test_noise():
N = 500
rate = 1.0
w = noise.white(N)
b = noise.brown(N)
v = noise.violet(N)
p = noise.pink(N)
assert len(w) == N
assert len(b) == N
assert len(v) == N-1 # why?
assert len(p) == N
def add_pink_noise(filename):
print "Adding Pink Noise..."
fps, snd_array = wavfile.read('../audio/transformed/' + filename)
noise1 = noise.pink(len(snd_array))
noise1 = map(lambda x: int(x/.01), noise1)
noise2 = np.array([noise1,noise1]).T
noisy_array = noise2 + snd_array
filename, file_extension = os.path.splitext(filename)
filename = "../audio/transformed/"+filename+"pinknoise.wav"
scaled = np.int16(noisy_array/np.max(np.abs(noisy_array)) * 32767)
write(filename, 44100, scaled)
return
def test_noise():
N = 500
#rate = 1.0
w = noise.white(N)
b = noise.brown(N)
v = noise.violet(N)
p = noise.pink(N)
# check output length
assert len(w) == N
assert len(b) == N
assert len(v) == N
assert len(p) == N
# check output type
for x in [w, b, v, p]:
assert type(x) == numpy.ndarray, "%s is not numpy.ndarray" % (type(x))
plt.subplot(111, xscale="log", yscale="log")
N = 100000
# Colors: http://en.wikipedia.org/wiki/Colors_of_noise
# Brownian a.k.a random walk frequency => sqrt(tau) ADEV
print("Random Walk frequency noise - should have sqrt(tau) ADEV")
freq_rw = noise.brown(N)
phase_rw_rw = numpy.cumsum(noise.brown(N)) # integrate to get phase
plotallan(plt, freq_rw, 1, t, 'm.')
plotallan_phase(plt, phase_rw_rw, 1, t, 'mo',label='random walk frequency')
plotline(plt, +0.5, t, 'm',label="f^(+1/2)")
# pink frequency noise => constant ADEV
print("Pink frequency noise - should have constant ADEV")
freq_pink = noise.pink(N)
phase_p = numpy.cumsum(noise.pink(N)) # integrate to get phase, color??
plotallan_phase(plt, phase_p, 1, t, 'co',label="pink/flicker frequency noise")
plotallan(plt, freq_pink, 1, t, 'c.')
plotline(plt, 0, t, 'c',label="f^0")
# white frequency modulation => 1/sqrt(tau) ADEV
print("White frequency noise - should have 1/sqrt(tau) ADEV")
freq_white = noise.white(N)
phase_rw = noise.brown(N) # integrate to get Brownian, or random walk phase
plotallan(plt, freq_white, 1, t, 'b.')
plotallan_phase(plt, phase_rw, 1, t, 'bo',label='random walk phase a.k.a. white frequency noise')
plotline(plt, -0.5, t, 'b',label="f^(-1/2)")
# pink phase noise => 1/tau ADEV and MDEV
print("Pink phase noise - should tau^(-3/2) MDEV")
# Brownian a.k.a random walk frequency => sqrt(tau) ADEV
print("Random Walk frequency noise - should have sqrt(tau) ADEV")
freq_rw = noise.brown(N)
phase_rw_rw = numpy.cumsum(noise.brown(N)) # integrate to get phase
plotallan(plt, freq_rw, 1, t, 'm.')
plotallan_phase(plt,
phase_rw_rw,
1,
t,
'mo',
label='random walk frequency')
plotline(plt, +0.5, t, 'm', label="f^(+1/2)")
# pink frequency noise => constant ADEV
print("Pink frequency noise - should have constant ADEV")
freq_pink = noise.pink(N)
phase_p = numpy.cumsum(noise.pink(N)) # integrate to get phase, color??
plotallan_phase(plt,
phase_p,
1,
t,
'co',
label="pink/flicker frequency noise")
plotallan(plt, freq_pink, 1, t, 'c.')
plotline(plt, 0, t, 'c', label="f^0")
# white frequency modulation => 1/sqrt(tau) ADEV
print("White frequency noise - should have 1/sqrt(tau) ADEV")
freq_white = noise.white(N)
phase_rw = noise.brown(
N) # integrate to get Brownian, or random walk phase
