nqrduck/nqrduck-broadband
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Added default value for LUT.

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jupfi 2023-12-12 19:22:00 +01:00
parent b1da9f48e7
commit 2bb6ab1524
1 changed files with 16 additions and 7 deletions
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23
src/nqrduck_broadband/model.py
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@ -24,6 +24,7 @@ class BroadbandModel(ModuleModel):
self.DEFAULT_FREQUENCY_STEP = self.DEFAULT_FREQUENCY_STEP
self.current_broadband_measurement = None
self.waiting_for_tune_and_match = False
self.LUT = None
@property
def start_frequency(self):
@ -146,10 +147,18 @@ class BroadbandModel(ModuleModel):
logger.debug("Assembling broadband spectrum from %d single frequency measurements." % len(single_frequency_measurements))
fdy_assembled = np.array([])
fdx_assembled = np.array([])
# We cut out step_size / 2 around 0 Hz of the spectrum and assemble the broadband spectrum
# We cut out step_size / 2 around the IF of the spectrum and assemble the broadband spectrum
for measurement in single_frequency_measurements:
# This finds the center of the spectrum
center = np.where(measurement.fdx == 0)[0][0]
# This finds the center of the spectrum if the IF is not 0 it will cut out step_size / 2 around the IF
logger.debug("IF frequency: %f" % measurement.IF_frequency)
logger.debug(measurement.fdx)
offset = measurement.IF_frequency * 1e-6
logger.debug("Offset: %f" % offset)
#center = np.where(measurement.fdx == offset)[0][0]
# Find closest to offset
center = self.find_nearest(measurement.fdx, offset)
logger.debug("Center: %d" % center)
# This finds the nearest index of the lower and upper frequency step
logger.debug("Frequency step: %f" % self.frequency_step)
@ -159,16 +168,16 @@ class BroadbandModel(ModuleModel):
# This interpolates the y values of the lower and upper frequency step
yf_interp_lower = np.interp(-self.frequency_step/2 * 1e-6, [measurement.fdx[idx_xf_lower], measurement.fdx[center]],
[measurement.fdy[idx_xf_lower][0], measurement.fdy[center][0]])
[abs(measurement.fdy)[idx_xf_lower][0], abs(measurement.fdy)[center][0]])
yf_interp_upper = np.interp(+self.frequency_step/2 * 1e-6, [measurement.fdx[center], measurement.fdx[idx_xf_upper]],
[measurement.fdy[center][0], measurement.fdy[idx_xf_lower][0]])
[abs(measurement.fdy)[center][0], abs(measurement.fdy)[idx_xf_lower][0]])
try:
# We take the last point of the previous spectrum and the first point of the current spectrum and average them
fdy_assembled[-1] = (fdy_assembled[-1] + yf_interp_lower) / 2
# Then we append the data from idx_xf_lower + 1 (because of the averaged datapoint) to idx_xf_upper
fdy_assembled = np.append(fdy_assembled, measurement.fdy[idx_xf_lower+1:idx_xf_upper-1])
fdy_assembled = np.append(fdy_assembled, abs(measurement.fdy)[idx_xf_lower+1:idx_xf_upper-1])
fdy_assembled = np.append(fdy_assembled, yf_interp_upper)
# We append the frequency values of the current spectrum and shift them by the target frequency
@ -178,7 +187,7 @@ class BroadbandModel(ModuleModel):
# On the first run we will get an Index Error
except IndexError:
fdy_assembled = np.array([yf_interp_lower])
fdy_assembled = np.append(fdy_assembled, measurement.fdy[idx_xf_lower+1:idx_xf_upper-1])
fdy_assembled = np.append(fdy_assembled, abs(measurement.fdy)[idx_xf_lower+1:idx_xf_upper-1])
fdy_assembled = np.append(fdy_assembled, yf_interp_upper)
first_time_values = (measurement.fdx[idx_xf_lower:idx_xf_upper] + measurement.target_frequency * 1e-6)