def test_rms():
t = np.linspace(0, 1, 1000)
for rms_desired in [0, 0.5, 1, 100]:
f = whitenoise(1, 100, rms=rms_desired)
rms = np.sqrt(np.mean([f(tt) ** 2 for tt in t]))
assert np.allclose(rms, rms_desired, atol=.1, rtol=.01)
def test_array():
rms_desired = 0.5
f = whitenoise(1, 5, rms=rms_desired, dimensions=5)
t = np.linspace(0, 1, 1000)
data = np.array([f(tt) for tt in t])
rms = np.sqrt(np.mean(data**2, axis=0))
assert np.allclose(rms, rms_desired, atol=.1, rtol=.01)
