Added comments and maybe some minor repairs.
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@ -1,12 +1,14 @@
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from .lasp_common import *
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# Comments are what is imported, state of 6-8-2021
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from .lasp_avstream import *
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from .wrappers import *
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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
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from .lasp_atomic import *
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from .lasp_avstream import * # StreamManager, ignoreSigInt, StreamStatus
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from .lasp_imptube import *
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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
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from .lasp_measurement import *
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from .lasp_atomic import * # Atomic
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from .lasp_octavefilter import *
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from .lasp_imptube import * # TwoMicImpedanceTube
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from .lasp_slm import *
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from .lasp_measurement import * # Measurement, scaleBlockSens
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from .lasp_record import *
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from .lasp_octavefilter import * # FirOctaveFilterBank, FirThirdOctaveFilterBank, OverallFilterBank, SosOctaveFilterBank, SosThirdOctaveFilterBank
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from .lasp_siggen import *
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from .lasp_slm import * # SLM, Dummy
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from .lasp_weighcal import *
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from .lasp_record import * # RecordStatus, Recording
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from .tools import *
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from .lasp_siggen import * # SignalType, NoiseType, SiggenMessage, SiggenData, Siggen
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from .lasp_weighcal import * # WeighCal
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from .tools import * # SmoothingType, smoothSpectralData, SmoothingWidth
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@ -117,7 +117,7 @@ void PowerSpectra_compute(const PowerSpectra* ps,
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TRACE(15,"fft done");
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TRACE(15,"fft done");
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/* Scale fft such that power is easily comxputed */
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/* Scale fft such that power is easily computed */
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const c scale_fac = d_sqrt(2/win_pow)/nfft;
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const c scale_fac = d_sqrt(2/win_pow)/nfft;
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cmat_scale(&fft_work,scale_fac);
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cmat_scale(&fft_work,scale_fac);
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TRACE(15,"scale done");
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TRACE(15,"scale done");
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@ -1,5 +1,8 @@
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from .soundpressureweighting import *
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# Comments what modules are imported are state of 6-8-2021.
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from .filterbank_design import *
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from .fir_design import *
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from .soundpressureweighting import * # SPLFilterDesigner
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from .colorednoise import *
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from .filterbank_design import * # OctaveBankDesigner, ThirdOctaveBankDesigner
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from .biquad import *
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from .fir_design import * # freqResponse, bandpass_fir_design, lowpass_fir_design, arbitrary_fir_design
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from .colorednoise import * # PinkNoise # not imported: BrownianNoise, BlueNoise
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from .biquad import * # peaking, biquadTF, notch, lowpass, highpass, highshelve, lowshelve
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# Nothing is imported from decimation_fir.py
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@ -81,7 +81,7 @@ class FilterBankDesigner:
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if self.nominal_txt(x) == nom_txt:
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if self.nominal_txt(x) == nom_txt:
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return x
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return x
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raise ValueError(
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raise ValueError(
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f'Could not find an x-value corresponding to {nom_txt}.')
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f'Could not find a nominal frequency corresponding to {nom_txt}. Hint: use \'5k\' instead of \'5000\'.')
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def sanitize_input(self, input_):
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def sanitize_input(self, input_):
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if isinstance(input_, int):
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if isinstance(input_, int):
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@ -601,4 +601,3 @@ class ThirdOctaveBankDesigner(FilterBankDesigner):
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else:
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else:
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raise ValueError('Unimplemented sampling frequency for SOS'
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raise ValueError('Unimplemented sampling frequency for SOS'
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'filter design')
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'filter design')
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@ -160,7 +160,7 @@ class Recording:
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return
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return
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# The 'Audio' dataset as specified in lasp_measurement, where data is
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# The 'Audio' dataset as specified in lasp_measurement, where data is
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# send to. We use gzip as compression, this gives moderate a moderate
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# sent to. We use gzip as compression, this gives moderate a moderate
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# compression to the data.
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# compression to the data.
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f = self.f
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f = self.f
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blocksize = md.blocksize
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blocksize = md.blocksize
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@ -101,9 +101,12 @@ def smoothSpectralData(freq, M, sw: SmoothingWidth,
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# elif st == SmoothingType.tf:
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# elif st == SmoothingType.tf:
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# P = P**2
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# P = P**2
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Psm = np.zeros_like(P) # smoothed power - to be calculated
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# P is power while smoothing. x are indices of P.
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x0 = 1 if freq[0]==0 else 0 # skip first data point if zero frequency
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Psm = np.zeros_like(P) # Smoothed power - to be calculated
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df = freq[1] - freq[0] # frequency step
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x0 = 1 if freq[0]==0 else 0 # Skip first data point if zero frequency
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Psm[0] = P[0] # Reuse old value in case first data..
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# ..point is skipped. Not plotted any way.
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df = freq[1] - freq[0] # Frequency step
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# Loop through data points
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# Loop through data points
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for x in range(x0, L):
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for x in range(x0, L):
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