Updated tests

examples/example_biquadbank.py

@@ -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
 

test/test_aps.py

@@ -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

test/test_cppslm.py

@@ -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__':