Added comments and maybe some minor repairs.

lasp/__init__.py

@@ -1,12 +1,14 @@
-from .lasp_common import *
+# Comments are what is imported, state of 6-8-2021
-from .lasp_avstream import *
+
-from .wrappers import *
+from .lasp_common import *  # P_REF, FreqWeighting, TimeWeighting, getTime, getFreq, Qty, SIQtys, Window, lasp_shelve, this_lasp_shelve, W_REF, U_REF, I_REF, dBFS_REF, AvType
-from .lasp_atomic import *
+from .lasp_avstream import *  # StreamManager, ignoreSigInt, StreamStatus
-from .lasp_imptube import *
+from .wrappers import *  # AvPowerSpectra, SosFilterBank, FilterBank, Siggen, sweep_flag_forward, sweep_flag_backward, sweep_flag_linear, sweep_flag_exponential, load_fft_wisdom, store_fft_wisdom
-from .lasp_measurement import *
+from .lasp_atomic import *  # Atomic
-from .lasp_octavefilter import *
+from .lasp_imptube import *  # TwoMicImpedanceTube
-from .lasp_slm import *
+from .lasp_measurement import *  # Measurement, scaleBlockSens
-from .lasp_record import *
+from .lasp_octavefilter import *  # FirOctaveFilterBank, FirThirdOctaveFilterBank, OverallFilterBank, SosOctaveFilterBank, SosThirdOctaveFilterBank
-from .lasp_siggen import *
+from .lasp_slm import *  # SLM, Dummy
-from .lasp_weighcal import *
+from .lasp_record import *  # RecordStatus, Recording
-from .tools import *
+from .lasp_siggen import *  # SignalType, NoiseType, SiggenMessage, SiggenData, Siggen
+from .lasp_weighcal import *  # WeighCal
+from .tools import *  # SmoothingType, smoothSpectralData, SmoothingWidth

lasp/c/lasp_ps.c

@@ -117,7 +117,7 @@ void PowerSpectra_compute(const PowerSpectra* ps,
     
     TRACE(15,"fft done");
     
-    /* Scale fft such that power is easily comxputed */
+    /* Scale fft such that power is easily computed */
     const c scale_fac = d_sqrt(2/win_pow)/nfft;
     cmat_scale(&fft_work,scale_fac);
     TRACE(15,"scale done");

lasp/filter/__init__.py

@@ -1,5 +1,8 @@
-from .soundpressureweighting import *
+# Comments what modules are imported are state of 6-8-2021.
-from .filterbank_design import *
+
-from .fir_design import *
+from .soundpressureweighting import *  # SPLFilterDesigner
-from .colorednoise import *
+from .filterbank_design import *  # OctaveBankDesigner, ThirdOctaveBankDesigner
-from .biquad import *
+from .fir_design import *  # freqResponse, bandpass_fir_design, lowpass_fir_design, arbitrary_fir_design
+from .colorednoise import *  # PinkNoise # not imported: BrownianNoise, BlueNoise
+from .biquad import *  # peaking, biquadTF, notch, lowpass, highpass, highshelve, lowshelve
+# Nothing is imported from decimation_fir.py

lasp/filter/filterbank_design.py

@@ -81,7 +81,7 @@ class FilterBankDesigner:
             if self.nominal_txt(x) == nom_txt:
                 return x
         raise ValueError(
-            f'Could not find an x-value corresponding to {nom_txt}.')
+            f'Could not find a nominal frequency corresponding to {nom_txt}. Hint: use \'5k\' instead of \'5000\'.')
 
     def sanitize_input(self, input_):
         if isinstance(input_, int):
@@ -492,7 +492,7 @@ class ThirdOctaveBankDesigner(FilterBankDesigner):
             index_start = x[0] - self.xs[0]
             index_stop = x[-1] - self.xs[0]
             return self._nominal_txt[index_start:index_stop+1]
-            
+
 
     def band_limits(self, x, filter_class=0):
         """Returns the third octave band filter limits for filter designator x.
@@ -601,4 +601,3 @@ class ThirdOctaveBankDesigner(FilterBankDesigner):
         else:
             raise ValueError('Unimplemented sampling frequency for SOS'
                              'filter design')
-

lasp/lasp_record.py

@@ -160,7 +160,7 @@ class Recording:
             return
 
         # The 'Audio' dataset as specified in lasp_measurement, where data is
-        # send to. We use gzip as compression, this gives moderate a moderate
+        # sent to. We use gzip as compression, this gives moderate a moderate
         # compression to the data.
         f = self.f
         blocksize = md.blocksize

lasp/tools/tools.py

@@ -101,9 +101,12 @@ def smoothSpectralData(freq, M, sw: SmoothingWidth,
     # elif st == SmoothingType.tf:
     #     P = P**2
 
-    Psm = np.zeros_like(P)           # smoothed power - to be calculated
+    # P is power while smoothing. x are indices of P.
-    x0 = 1 if freq[0]==0 else 0      # skip first data point if zero frequency
+    Psm = np.zeros_like(P)           # Smoothed power - to be calculated
-    df = freq[1] - freq[0]           # frequency step
+    x0 = 1 if freq[0]==0 else 0      # Skip first data point if zero frequency
+    Psm[0] = P[0]                    # Reuse old value in case first data..
+                                     # ..point is skipped. Not plotted any way.
+    df = freq[1] - freq[0]           # Frequency step
 
     # Loop through data points
     for x in range(x0, L):