def generate(self, n_noise_samples=1):
"""Generate noise samples.
The type of the noise that will be generated, and the size of the noise array are defined by the argument given
to the constructor.
:param n_noise_samples: The number of noise samples to be generated.
:return: an np.array with the specified noise
"""
n = n_noise_samples * self.noise_size[0] * self.noise_size[1]
s = concat([n_noise_samples], list(self.noise_size))
if self.noise_type == 'simplistic':
return np.random.uniform(0, 1, size=concat([n_noise_samples], list(self.noise_size)))
elif self.noise_type.lower() in {'gaussian', 'white', 'normal'}:
return np.reshape(white(n), s)
elif self.noise_type.lower() == 'pink':
return np.reshape(pink(n), s)
elif self.noise_type.lower() == 'blue':
return np.reshape(blue(n), s)
elif self.noise_type.lower() == 'brown':
return np.reshape(brown(n), s)
elif self.noise_type.lower() == 'violet':
return np.reshape(violet(n), s)
else:
print("WARNING: noise type " + self.noise_type + " not defined. Returning 0")
return np.reshape(np.zeros(n), s)
def noise_make(sound, numbers_of_samples, factor):
noise = generator.brown(numbers_of_samples)
noise = noise * factor
low = 0.23
high = 0.8
b, a = signal.butter(4, (low, high),
btype="bandpass") ## filtr pasmowo przepustowy
output_signal = signal.filtfilt(b, a, noise)
#output_signal += sound
return output_signal
def test_power(self):
fs = 44100
samples = 44100 * 10
_, L = octaves(brown(samples), fs)
change = np.diff(L).mean().round(0)
assert (change == -3.)
def test_length(self):
N = 1000
assert (len(brown(N)) == N)
def test_power_density(self):
fs = 44100
samples = 44100 * 10
_, L = octaves(brown(samples), fs, density=True)
change = np.diff(L).mean().round(0)
assert (change == -6.)
def test_length(self):
N = 1000
assert(len(brown(N))==N)
def test_power_density(self):
fs = 44100
samples = 44100 * 10
_, L = octaves(brown(samples), fs, density=True);
change = np.diff(L).mean().round(0)
assert(change==-6.)
def test_power(self):
fs = 44100
samples = 44100 * 10
_, L = octaves(brown(samples), fs);
change = np.diff(L).mean().round(0)
assert(change==-3.)