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ebf5ac3de4
@ -67,10 +67,7 @@ void fillUlDaqDeviceInfo(DeviceInfoList &devinfolist) {
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DataTypeDescriptor::DataType::dtype_fl64);
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devinfo.prefDataTypeIndex = 0;
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devinfo.availableSampleRates = {8000, 10000, 11025, 16000, 20000,
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22050, 24000, 32000, 44056, 44100,
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47250, 48000, 50000, 50400, 51000};
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devinfo.availableSampleRates = ULDAQ_SAMPLERATES;
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devinfo.prefSampleRateIndex = 11;
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devinfo.availableFramesPerBlock = {512, 1024, 2048, 4096, 8192};
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@ -70,7 +70,7 @@ DT9837A::DT9837A(const DeviceInfo &devinfo, const DaqConfiguration &config)
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throw rte("Unsensible number of samples per block chosen");
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}
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if (samplerate() < 10000 || samplerate() > 51000) {
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if (samplerate() < ULDAQ_SAMPLERATES.at(0) || samplerate() > ULDAQ_SAMPLERATES.at(ULDAQ_SAMPLERATES.size()-1)) {
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throw rte("Invalid sample rate");
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}
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@ -14,6 +14,14 @@ using std::cerr;
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using std::endl;
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using rte = std::runtime_error;
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/**
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* @brief List of available sampling frequencies for DT9837A
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*/
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const std::vector<d> ULDAQ_SAMPLERATES = {8000, 10000, 11025, 16000, 20000,
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22050, 24000, 32000, 44056, 44100,
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47250, 48000, 50000, 50400, 51000};
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/**
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* @brief UlDaq-specific device information. Adds a copy of the underlying
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* DaqDeDaqDeviceDescriptor.
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@ -23,7 +23,8 @@ y[n] = 1/ba[3] * ( ba[0] * x[n] + ba[1] * x[n-1] + ba[2] * x[n-2] +
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"""
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__all__ = ['peaking', 'biquadTF', 'notch', 'lowpass', 'highpass',
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'highshelf', 'lowshelf', 'LPcompensator', 'HPcompensator']
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'highshelf', 'lowshelf', 'LP1compensator', 'LP2compensator',
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'HP1compensator', 'HP2compensator']
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from numpy import array, cos, pi, sin, sqrt
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from scipy.interpolate import interp1d
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@ -157,7 +158,32 @@ def lowshelf(fs, f0, Q, gain):
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a2 = (A+1) + (A-1)*cos(w0) - 2*sqrt(A)*alpha
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return array([b0/a0, b1/a0, b2/a0, a0/a0, a1/a0, a2/a0])
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def LPcompensator(fs, f0o, Qo, f0n, Qn):
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def LP1compensator(fs, f0o, f0n):
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"""
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Shelving type filter that, when multiplied with a first-order low-pass
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filter, alters the response of that filter to a different first-order
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low-pass filter.
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Args:
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fs: Sampling frequency [Hz]
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f0o: Cut-off frequency of the original filter [Hz]
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f0n: Desired cut-off frequency [Hz]
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"""
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omg0o = 2*pi*f0o
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omg0n = 2*pi*f0n
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z = -omg0o
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p = -omg0n
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k = p/z
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zd, pd, kd = bilinear_zpk(z, p, k, fs)
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sos = zpk2sos(zd,pd,kd)
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return sos[0]
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def LP2compensator(fs, f0o, Qo, f0n, Qn):
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"""
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Shelving type filter that, when multiplied with a second-order low-pass
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filter, alters the response of that filter to a different second-order
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@ -194,7 +220,32 @@ def LPcompensator(fs, f0o, Qo, f0n, Qn):
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return sos[0]
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def HPcompensator(fs, f0o, Qo, f0n, Qn):
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def HP1compensator(fs, f0o, f0n):
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"""
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Shelving type filter that, when multiplied with a first-order high-pass
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filter, alters the response of that filter to a different first-order
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high-pass filter.
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Args:
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fs: Sampling frequency [Hz]
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f0o: Cut-on frequency of the original filter [Hz]
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f0n: Desired cut-on frequency [Hz]
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"""
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omg0o = 2*pi*f0o
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omg0n = 2*pi*f0n
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z = -omg0o
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p = -omg0n
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k = 1
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zd, pd, kd = bilinear_zpk(z, p, k, fs)
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sos = zpk2sos(zd,pd,kd)
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return sos[0]
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def HP2compensator(fs, f0o, Qo, f0n, Qn):
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"""
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Shelving type filter that, when multiplied with a second-order high-pass
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filter, alters the response of that filter to a different second-order
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@ -52,6 +52,7 @@ import os, time, wave, logging
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from .lasp_common import SIQtys, Qty, getFreq
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from .lasp_cpp import Window, DaqChannel, LASP_VERSION_MAJOR, AvPowerSpectra
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from typing import List
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from functools import lru_cache
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def getSampWidth(dtype):
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@ -248,6 +249,9 @@ class Measurement:
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except KeyError:
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self._sens = np.ones(self.nchannels)
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# The time is cached AND ALWAYS ASSUMED TO BE AN IMMUTABLE OBJECT.
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# It is also cached. Changing the measurement timestamp should not
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# be done.
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self._time = f.attrs['time']
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# Quantity stored as channel.
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@ -260,7 +264,7 @@ class Measurement:
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try:
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qtys_json = f.attrs['qtys']
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# Load quantity data
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self._qtys = [Qty.from_json(qty_json) for qty_json in qtys_json]
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self._qtys = [Qty.from_json(qty_json) for qty_json in qtys_json]
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except KeyError:
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# If quantity data is not available, this is an 'old'
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# measurement file.
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@ -270,7 +274,6 @@ class Measurement:
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self._qtys = [SIQtys.default() for i in range(self.nchannels)]
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logging.debug(f'Physical quantity data not available in measurement file. Assuming {SIQtys.default}')
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def setAttribute(self, atrname, value):
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"""
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Set an attribute in the measurement file, and keep a local copy in
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@ -375,6 +378,7 @@ class Measurement:
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self._comment = cmt
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@property
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@lru_cache()
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def recTime(self):
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"""Returns the total recording time of the measurement, in float
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seconds."""
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@ -385,6 +389,19 @@ class Measurement:
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"""Returns the measurement time in seconds since the epoch."""
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return self._time
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@property
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@lru_cache()
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def timestr(self):
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"""
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Return a properly formatted string of the measurement time, in order of
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year-month-day hour etc.
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"""
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time_struct = time.localtime(self.time)
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time_string = time.strftime('%Y-%m-%d %H:%M:%S', time_struct)
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return time_string
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def rms(self, channels=None, substract_average=False):
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"""Returns the root mean square values for each channel
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@ -408,7 +425,7 @@ class Measurement:
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meansquare += np.sum(block**2, axis=0) / self.N
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avg = sum_/N
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# In fact, this is not the complete RMS, as in includes the DC
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# In fact, this is not the complete RMS, as in includes the DC
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# If p = p_dc + p_osc, then rms(p_osc) = sqrt(ms(p)-ms(p_dc))
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if substract_average:
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meansquare -= avg**2
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@ -419,7 +436,7 @@ class Measurement:
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return self.rms(substract_average=True)
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def rawData(self, channels=None, **kwargs):
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"""Returns the raw data as stored in the measurement file,
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"""Returns the raw data as stored in the measurement file,
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without any transformations applied
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args:
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@ -472,10 +489,10 @@ class Measurement:
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window: Window type
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overlap: Overlap percentage (value between 0.0 and up to and
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including 100.0)
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weighting:
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weighting:
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Returns:
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Cross-power-spectra. C[freq, ch_i, ch_j] = C_ij
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Cross-power-spectra. C[freq, ch_i, ch_j] = C_ij
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"""
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nfft = kwargs.pop('nfft', 2048)
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@ -517,14 +534,14 @@ class Measurement:
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# Estimate noise power in block
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blocks = [signal[i*N:(i+1)*N] for i in range(Nblocks)]
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if noiseCorrection:
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# The difference between the measured signal in the previous block and
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# The difference between the measured signal in the previous block and
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# the current block
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en = [None] + [blocks[i] - blocks[i-1] for i in range(1,Nblocks)]
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noise_est = [None] + [-np.average(en[i]*en[i+1]) for i in range(1,len(en)-1)]
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# Create weighting coefficients
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sum_inverse_noise = sum([1/n for n in noise_est[1:]])
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c_n = [1/(ni*sum_inverse_noise) for ni in noise_est[1:]]
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@ -533,7 +550,7 @@ class Measurement:
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assert np.isclose(sum(c_n), 1.0)
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assert Nblocks-2 == len(c_n)
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# Average signal over blocks
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avg = np.zeros((blocks[0].shape), dtype=float)
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for n in range(0, Nblocks-2):
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@ -558,7 +575,7 @@ class Measurement:
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CS = ps.compute(avg)
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freq = getFreq(self.samplerate, N)
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return freq, CS
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return freq, CS
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@property
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@ -614,8 +631,8 @@ class Measurement:
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return False
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def exportAsWave(self, fn=None, force=False, newsampwidth=None,
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normalize=True, **kwargs):
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def exportAsWave(self, fn=None, force=False, dtype=None,
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normalize=False, **kwargs):
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"""Export measurement file as wave. In case the measurement data is
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stored as floats, the values are scaled to the proper integer (PCM)
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data format.
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@ -627,9 +644,8 @@ class Measurement:
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force: If True, overwrites any existing files with the given name
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, otherwise a RuntimeError is raised.
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newsampwidth: sample width in bytes with which to export the data.
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This should only be given in case the measurement data is stored as
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floating point values, otherwise an error is thrown
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dtype: if not None, convert data to this data type.
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Options are 'int16', 'int32', 'float32'.
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normalize: If set: normalize the level to something sensible.
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"""
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@ -643,39 +659,49 @@ class Measurement:
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if os.path.exists(fn) and not force:
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raise RuntimeError(f'File already exists: {fn}')
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if not np.isclose(self.samplerate%1,0):
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raise RuntimeError(f'Sample rates should be approximately integer for exporting to Wave to work')
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# TODO: With VERY large measurment files, this is not possible! Is this
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# a theoretical case?
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# TODO: add sensitivity? Then use self.data() instead of self.rawData()
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data = self.rawData(**kwargs)
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if np.issubdtype(data.dtype, np.floating) and newsampwidth is None:
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raise ValueError('Newsampwidth parameter should be given for floating point raw data')
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if normalize:
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# Scale back to maximum of absolute value
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maxabs = np.max(np.abs(data))
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data = data / maxabs # "data /= maxabs" fails if dtpyes differ
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if newsampwidth is not None:
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# Convert to floats, then to new sample width
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sensone = np.ones_like(self.sensitivity)
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data = scaleBlockSens(data, sensone)
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if dtype==None:
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dtype = data.dtype # keep existing
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logging.debug(f"dtype not passed as arg; using dtype = {dtype}")
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if newsampwidth == 2:
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newtype = np.int16
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elif newsampwidth == 4:
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newtype = np.int32
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else:
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raise ValueError('Invalid sample width, should be 2 or 4')
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# dtype conversion
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if dtype=='int16':
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newtype = np.int16
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newsampwidth = 2
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elif dtype=='int32':
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newtype = np.int32
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newsampwidth = 4
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elif dtype=='float32':
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newtype = np.float32
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elif dtype=='float64':
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newtype = np.float64
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else:
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logging.debug(f"cannot handle this dtype {dtype}")
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pass
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# Convert range to [-1, 1]
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# TODO: this is wrong for float data where full scale > 1
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sensone = np.ones_like(self.sensitivity)
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data = scaleBlockSens(data, sensone)
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if dtype=='int16' or dtype=='int32':
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# Scale data to integer range and convert to integers
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scalefac = 2**(8*newsampwidth-1)-1
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# Scale data to integer range, and then convert to integers
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data = (data*scalefac).astype(newtype)
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wavfile.write(fn, int(self.samplerate), data)
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wavfile.write(fn, int(self.samplerate), data.astype(newtype))
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@staticmethod
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def fromtxt(fn,
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