kopia lustrzana https://github.com/NanoVNA-Saver/nanovna-saver
398 wiersze
16 KiB
Python
398 wiersze
16 KiB
Python
# NanoVNASaver - a python program to view and export Touchstone data from a NanoVNA
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# Copyright (C) 2019. Rune B. Broberg
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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import collections
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from time import sleep
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from typing import List
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import numpy as np
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from PyQt5 import QtCore
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from PyQt5.QtCore import pyqtSlot, pyqtSignal
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import NanoVNASaver
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import logging
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from NanoVNASaver.Hardware import VNA, InvalidVNA
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from NanoVNASaver.RFTools import RFTools, Datapoint
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logger = logging.getLogger(__name__)
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class WorkerSignals(QtCore.QObject):
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updated = pyqtSignal()
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finished = pyqtSignal()
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sweepError = pyqtSignal()
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fatalSweepError = pyqtSignal()
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class SweepWorker(QtCore.QRunnable):
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def __init__(self, app: NanoVNASaver):
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super().__init__()
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logger.info("Initializing SweepWorker")
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self.signals = WorkerSignals()
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self.app = app
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self.vna: VNA = InvalidVNA()
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self.noSweeps = 1
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self.setAutoDelete(False)
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self.percentage = 0
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self.data11: List[Datapoint] = []
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self.data21: List[Datapoint] = []
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self.rawData11: List[Datapoint] = []
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self.rawData21: List[Datapoint] = []
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self.stopped = False
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self.continuousSweep = False
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self.averaging = False
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self.averages = 3
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self.truncates = 0
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self.error_message = ""
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@pyqtSlot()
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def run(self):
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logger.info("Initializing SweepWorker")
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self.percentage = 0
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if not self.app.serial.is_open:
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logger.debug("Attempted to run without being connected to the NanoVNA")
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return
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if int(self.app.sweepCountInput.text()) > 0:
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self.noSweeps = int(self.app.sweepCountInput.text())
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logger.info("%d sweeps", self.noSweeps)
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if self.averaging:
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logger.info("%d averages", self.averages)
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if self.app.sweepStartInput.text() == "" or self.app.sweepEndInput.text() == "":
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logger.debug("First sweep - standard range")
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# We should handle the first startup by reading frequencies?
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sweep_from = 1000000
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sweep_to = 800000000
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else:
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sweep_from = RFTools.parseFrequency(self.app.sweepStartInput.text())
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sweep_to = RFTools.parseFrequency(self.app.sweepEndInput.text())
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logger.debug("Parsed sweep range as %d to %d", sweep_from, sweep_to)
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if sweep_from < 0 or sweep_to < 0 or sweep_from == sweep_to:
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logger.warning("Can't sweep from %s to %s",
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self.app.sweepStartInput.text(),
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self.app.sweepEndInput.text())
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self.error_message = "Unable to parse frequency inputs - check start and stop fields."
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self.stopped = True
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self.signals.sweepError.emit()
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return
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span = sweep_to - sweep_from
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stepsize = int(span / (100 + (self.noSweeps-1)*101))
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# Setup complete
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values = []
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values21 = []
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frequencies = []
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if self.averaging:
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for i in range(self.noSweeps):
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logger.debug("Sweep segment no %d averaged over %d readings", i, self.averages)
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if self.stopped:
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logger.debug("Stopping sweeping as signalled")
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break
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start = sweep_from + i * 101 * stepsize
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freq, val11, val21 = self.readAveragedSegment(start, start + 100 * stepsize, self.averages)
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frequencies += freq
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values += val11
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values21 += val21
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self.percentage = (i + 1) * 100 / self.noSweeps
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logger.debug("Saving acquired data")
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self.saveData(frequencies, values, values21)
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else:
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for i in range(self.noSweeps):
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logger.debug("Sweep segment no %d", i)
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if self.stopped:
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logger.debug("Stopping sweeping as signalled")
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break
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start = sweep_from + i*101*stepsize
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try:
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freq, val11, val21 = self.readSegment(start, start+100*stepsize)
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frequencies += freq
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values += val11
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values21 += val21
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self.percentage = (i+1)*100/self.noSweeps
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logger.debug("Saving acquired data")
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self.saveData(frequencies, values, values21)
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except NanoVNAValueException as e:
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self.error_message = str(e)
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self.stopped = True
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self.signals.fatalSweepError.emit()
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while self.continuousSweep and not self.stopped:
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logger.debug("Continuous sweeping")
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for i in range(self.noSweeps):
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logger.debug("Sweep segment no %d", i)
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if self.stopped:
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logger.debug("Stopping sweeping as signalled")
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break
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start = sweep_from + i * 101 * stepsize
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try:
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_, values, values21 = self.readSegment(start, start + 100 * stepsize)
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logger.debug("Updating acquired data")
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self.updateData(values, values21, i)
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except NanoVNAValueException as e:
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self.error_message = str(e)
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self.stopped = True
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self.signals.fatalSweepError.emit()
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# Reset the device to show the full range
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logger.debug("Resetting NanoVNA sweep to full range: %d to %d",
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RFTools.parseFrequency(self.app.sweepStartInput.text()),
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RFTools.parseFrequency(self.app.sweepEndInput.text()))
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self.vna.resetSweep(RFTools.parseFrequency(self.app.sweepStartInput.text()),
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RFTools.parseFrequency(self.app.sweepEndInput.text()))
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self.percentage = 100
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logger.debug("Sending \"finished\" signal")
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self.signals.finished.emit()
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return
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def updateData(self, values11, values21, offset):
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# Update the data from (i*101) to (i+1)*101
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# TODO: Get rid of the 101 point assumptions
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logger.debug("Calculating data and inserting in existing data at offset %d", offset)
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for i in range(len(values11)):
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re, im = values11[i]
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re21, im21 = values21[i]
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freq = self.data11[offset*101 + i].freq
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rawData11 = Datapoint(freq, re, im)
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rawData21 = Datapoint(freq, re21, im21)
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# TODO: Use applyCalibration instead
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if self.app.calibration.isCalculated:
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re, im = self.app.calibration.correct11(re, im, freq)
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if self.app.calibration.isValid2Port():
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re21, im21 = self.app.calibration.correct21(re21, im21, freq)
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self.data11[offset*101 + i] = Datapoint(freq, re, im)
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self.data21[offset * 101 + i] = Datapoint(freq, re21, im21)
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self.rawData11[offset * 101 + i] = rawData11
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self.rawData21[offset * 101 + i] = rawData21
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logger.debug("Saving data to application (%d and %d points)", len(self.data11), len(self.data21))
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self.app.saveData(self.data11, self.data21)
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logger.debug("Sending \"updated\" signal")
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self.signals.updated.emit()
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def saveData(self, frequencies, values11, values21):
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rawData11 = []
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rawData21 = []
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logger.debug("Calculating data including corrections")
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for i in range(len(values11)):
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re, im = values11[i]
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re21, im21 = values21[i]
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freq = frequencies[i]
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rawData11 += [Datapoint(freq, re, im)]
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rawData21 += [Datapoint(freq, re21, im21)]
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self.data11, self.data21 = self.applyCalibration(rawData11, rawData21)
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self.rawData11 = rawData11
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self.rawData21 = rawData21
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logger.debug("Saving data to application (%d and %d points)", len(self.data11), len(self.data21))
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self.app.saveData(self.data11, self.data21)
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logger.debug("Sending \"updated\" signal")
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self.signals.updated.emit()
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def applyCalibration(self, raw_data11: List[Datapoint], raw_data21: List[Datapoint]) ->\
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(List[Datapoint], List[Datapoint]):
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if not self.app.calibration.isCalculated:
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return raw_data11, raw_data21
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data11: List[Datapoint] = []
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data21: List[Datapoint] = []
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if self.app.calibration.isValid1Port():
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logger.debug("Applying S11 calibration.")
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for d in raw_data11:
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re, im = self.app.calibration.correct11(d.re, d.im, d.freq)
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data11.append(Datapoint(d.freq, re, im))
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else:
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data11 = raw_data11
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if self.app.calibration.isValid2Port():
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logger.debug("Applying S21 calibration.")
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for d in raw_data21:
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re, im = self.app.calibration.correct21(d.re, d.im, d.freq)
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data21.append(Datapoint(d.freq, re, im))
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else:
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data21 = raw_data21
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return data11, data21
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def readAveragedSegment(self, start, stop, averages):
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val11 = []
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val21 = []
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freq = []
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logger.info("Reading %d averages from %d to %d", averages, start, stop)
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for i in range(averages):
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if self.stopped:
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logger.debug("Stopping averaging as signalled")
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break
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logger.debug("Reading average no %d / %d", i+1, averages)
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freq, tmp11, tmp21 = self.readSegment(start, stop)
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val11.append(tmp11)
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val21.append(tmp21)
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self.percentage += 100/(self.noSweeps*averages)
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self.signals.updated.emit()
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logger.debug("Post-processing averages")
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logger.debug("Truncating %d values by %d", len(val11), self.truncates)
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val11 = self.truncate(val11, self.truncates)
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val21 = self.truncate(val21, self.truncates)
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logger.debug("Averaging %d values", len(val11))
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return11 = np.average(val11, 0).tolist()
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return21 = np.average(val21, 0).tolist()
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return freq, return11, return21
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def truncate(self, values: List[List[tuple]], count):
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logger.debug("Truncating from %d values to %d", len(values), len(values) - count)
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if count < 1:
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return values
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values = np.swapaxes(values, 0, 1)
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return_values = []
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for valueset in values:
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avg = np.average(valueset, 0) # avg becomes a 2-value array of the location of the average
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new_valueset = valueset
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for n in range(count):
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max_deviance = 0
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max_idx = -1
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for i in range(len(new_valueset)):
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deviance = abs(new_valueset[i][0] - avg[0])**2 + abs(new_valueset[i][1] - avg[1])**2
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if deviance > max_deviance:
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max_deviance = deviance
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max_idx = i
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next_valueset = []
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for i in range(len(new_valueset)):
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if i != max_idx:
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next_valueset.append((new_valueset[i][0], new_valueset[i][1]))
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new_valueset = next_valueset
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return_values.append(new_valueset)
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return_values = np.swapaxes(return_values, 0, 1)
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return return_values.tolist()
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def readSegment(self, start, stop):
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logger.debug("Setting sweep range to %d to %d", start, stop)
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self.vna.setSweep(start, stop)
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# Let's check the frequencies first:
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frequencies = self.readFreq()
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# TODO: Set up checks for getting the right frequencies. Challenge: We don't set frequency to single-Hz
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# accuracy, but rather "quite close". Ex: 106213728 vs 106213726
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# if start != int(frequencies[i*101]):
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# # We got the wrong frequencies? Let's just log it for now.
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# logger.warning("Wrong frequency received - %d is not %d", int(frequencies[i*101]), start)
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# S11
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values11 = self.readData("data 0")
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# S21
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values21 = self.readData("data 1")
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return frequencies, values11, values21
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def readData(self, data):
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logger.debug("Reading %s", data)
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done = False
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returndata = []
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count = 0
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while not done:
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done = True
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returndata = []
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tmpdata = self.vna.readValues(data)
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if not tmpdata:
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logger.warning("Read no values")
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raise NanoVNAValueException("Failed reading data: Returned no values.")
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logger.debug("Read %d values", len(tmpdata))
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for d in tmpdata:
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a, b = d.split(" ")
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try:
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if float(a) < -9.5 or float(a) > 9.5:
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logger.warning("Got a non-float data value: %s (%s)", d, a)
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logger.debug("Re-reading %s", data)
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done = False
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elif float(b) < -9.5 or float(b) > 9.5:
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logger.warning("Got a non-float data value: %s (%s)", d, b)
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logger.debug("Re-reading %s", data)
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done = False
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else:
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returndata.append((float(a), float(b)))
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except Exception as e:
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logger.exception("An exception occurred reading %s: %s", data, e)
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logger.debug("Re-reading %s", data)
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done = False
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if not done:
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sleep(0.2)
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count += 1
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if count == 10:
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logger.error("Tried and failed to read %s %d times.", data, count)
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if count >= 20:
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logger.critical("Tried and failed to read %s %d times. Giving up.", data, count)
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raise NanoVNAValueException("Failed reading " + str(data) + " " + str(count) + " times.\n" +
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"Data outside expected valid ranges, or in an unexpected format.")
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return returndata
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def readFreq(self):
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# TODO: Figure out why frequencies sometimes arrive as non-integers
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logger.debug("Reading frequencies")
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returnfreq = []
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done = False
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count = 0
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while not done:
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done = True
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returnfreq = []
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tmpfreq = self.vna.readFrequencies()
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if not tmpfreq:
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logger.warning("Read no frequencies")
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raise NanoVNAValueException("Failed reading frequencies: Returned no values.")
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for f in tmpfreq:
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if not f.isdigit():
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logger.warning("Got a non-digit frequency: %s", f)
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logger.debug("Re-reading frequencies")
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done = False
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count += 1
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if count == 10:
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logger.error("Tried and failed %d times to read frequencies.", count)
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if count >= 20:
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logger.critical("Tried and failed to read frequencies from the NanoVNA %d times.", count)
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raise NanoVNAValueException("Failed reading frequencies " + str(count) + " times.")
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else:
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returnfreq.append(int(f))
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return returnfreq
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def setContinuousSweep(self, continuousSweep: bool):
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self.continuousSweep = continuousSweep
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def setAveraging(self, averaging: bool, averages: str, truncates: str):
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self.averaging = averaging
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try:
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self.averages = int(averages)
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self.truncates = int(truncates)
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except:
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return
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def setVNA(self, vna):
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self.vna = vna
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class NanoVNAValueException(Exception):
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pass
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