def test_interval(self):
emin = 1.0
emax = 4.0
f = np.logspace(emin, emax, 50)
o = Octave(interval=f)
self.assertEqual(o.fmin, 10.0**emin)
self.assertEqual(o.fmax, 10.0**emax)
self.assertEqual(len(o.n), len(o.center))
o.unique = True
self.assertEqual(len(o.n), len(f))
def test_interval(self):
emin = 1.0
emax = 4.0
f = np.logspace(emin, emax, 50)
o = Octave(interval=f)
assert (o.fmin == 10.0**emin)
assert (o.fmax == 10.0**emax)
assert (len(o.n) == len(o.center))
o.unique = True
assert (len(o.n) == len(f))
def test_minmax(self):
fmin = 250.0
fmax = 1000.0
o = Octave(fmin=fmin, fmax=fmax)
self.assertEqual(len(o.center), 3) # 250, 500, and 1000 Hz
self.assertEqual(len(o.n), 3)
def test_minmax(self):
fmin = 250.0
fmax = 1000.0
o = Octave(fmin=fmin, fmax=fmax)
assert (len(o.center) == 3) # 250, 500, and 1000 Hz
assert (len(o.n) == 3)
def main():
"""We happen to have the following frequency vector."""
f = np.logspace(2, 4, 100)
"""And we want to get some 1/3-octave results, so we set octave to 3."""
o = Octave(interval=f, fraction=3)
"""We can now print the center frequencies of the 1/3 octave bands belonging
to this frequency vector."""
print(o.center)
"""
Since by default ``unique=True`` in :class:`Auraliser.Octave.Octave` we get
a value for every value in ``interval``. If we only want to obtain unique
values, it is fastest to set ``unique=True`. This could be done during
initialization but also now.
"""
o.unique = True
"""Now we should only get the unique center frequencies."""
print(o.center)
"""We can also calculate the bandwidth of each band."""
print(o.bandwidth)
"""As well as the lower limits of the frequency limits..."""
print(o.lower)
"""...and the upper frequency limits."""
print(o.upper)
"""
So far we used a frequency interval. Sometimes you have a lower frequency
and an upper frequency.
Instead of requiring to generate a frequency vector you can just give these
boundary values as well.
"""
o = Octave(fmin=100.0, fmax=20000, fraction=6)
print(o.center)
def octsmooth(amps, freq_vals, noct=24, st_freq=20, en_freq=20000):
"""Smooth magnitude spectrum values using octave bands for easier subtractions and viz.
Args
----------
amps : array
Magnitude spectrum values for smoothing
freq_vals : array
Magnitude spectrum frequency values
Parameters
----------
noct : int, optional
Number of octaves to smooth over (default is 24)
st_freq : int, optional
Start frequency for octave bands (default is 20)
en_freq : int, optional
End frequency for octave bands (default is 20000)
Returns
-------
array
Octave smoothed magnitude spectrum array
array
Octave smoothed magnitude spectrum array frequency bins
"""
o = Octave(fmin=st_freq, fmax=en_freq, fraction=noct)
octbins = np.zeros(len(o.center))
for i in range(0, len(o.center)):
st = (np.abs(freq_vals - o.lower[i])).argmin()
en = (np.abs(freq_vals - o.upper[i])).argmin()
if en - st > 0:
octbinvec = amps[st:en]
else:
octbinvec = amps[st:en + 1]
octbins[i] = np.max(octbinvec)
return octbins, o.center
import sys, json from acoustics.octave import Octave import numpy as np f = sys.argv[1] f = json.loads(f) o = Octave(interval=f, fraction=3) print(json.dumps(o.center.tolist()))