Updated tests
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This commit is contained in:
Anne de Jong 2023-01-12 20:31:55 +01:00
parent 3da6595b0c
commit d1dea1483f
3 changed files with 48 additions and 50 deletions

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@ -2,15 +2,10 @@
import numpy as np
from lasp import SeriesBiquad, AvPowerSpectra
from lasp.filter import SPLFilterDesigner
import matplotlib.pyplot as plt
from scipy.signal import sosfreqz
# plt.close('all')
plt.close('all')
# def test_cppslm2():
# """
# Generate a sine wave, now A-weighted
# """
fs = 48000
omg = 2*np.pi*1000

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@ -8,8 +8,6 @@ Created on Mon Jan 15 19:45:33 2018
import numpy as np
from lasp import AvPowerSpectra, Window
import matplotlib.pyplot as plt
# plt.close('all')
def test_aps1():
nfft = 16384

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@ -2,7 +2,7 @@
import numpy as np
from lasp import cppSLM
from lasp.filter import SPLFilterDesigner
import matplotlib.pyplot as plt
def test_cppslm1():
"""
@ -11,7 +11,8 @@ def test_cppslm1():
fs = 48000
omg = 2 * np.pi * 1000
slm = cppSLM.fromBiquads(fs, 2e-5, 1, 0.125, [1.,0,0,1,0,0])
slm = cppSLM.fromBiquads(fs, 2e-5, 1, 0.125,
np.array([[1., 0, 0, 1, 0, 0]]).T)
t = np.linspace(0, 10, 10 * fs, endpoint=False)
@ -40,7 +41,10 @@ def test_cppslm2():
omg = 2 * np.pi * 1000
filt = SPLFilterDesigner(fs).A_Sos_design()
slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125, filt.flatten(), [1.,0,0,1,0,0])
slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125,
filt.flatten(), # Pre-filter coefs
np.array([[1., 0, 0, 1, 0, 0]]).T # Bandpass coefs
)
t = np.linspace(0, 10, 10 * fs, endpoint=False)
@ -60,12 +64,15 @@ def test_cppslm2():
# (Fast, Slow etc)
assert np.isclose(out[-1, 0], level, atol=1e-2)
def test_cppslm3():
fs = 48000
omg = 2 * np.pi * 1000
filt = SPLFilterDesigner(fs).A_Sos_design()
slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125, filt.flatten(), [1.,0,0,1,0,0])
slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125,
filt.flatten(),
np.array([[1., 0, 0, 1, 0, 0]]).T)
t = np.linspace(0, 10, 10 * fs, endpoint=False)
in_ = 10 * np.sin(omg * t) * np.sqrt(2) + np.random.randn()
@ -74,16 +81,14 @@ def test_cppslm3():
# Compute overall level
level = 20 * np.log10(rms / 2e-5)
# Output of SLM
out = slm.run(in_)
Lpeak = 20 * np.log10(np.max(np.abs(in_) / 2e-5))
Lpeak
slm.Lpeak()
assert np.isclose(out[-1,0], slm.Leq()[0][0], atol=1e-2)
assert np.isclose(Lpeak, slm.Lpeak()[0][0], atol=2e0)
assert np.isclose(out[-1, 0], slm.Leq()[0], atol=1e-2)
assert np.isclose(Lpeak, slm.Lpeak()[0], atol=2e0)
if __name__ == '__main__':