kopia lustrzana https://github.com/NanoVNA-Saver/nanovna-saver
373 wiersze
14 KiB
Python
373 wiersze
14 KiB
Python
# NanoVNASaver
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#
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# A python program to view and export Touchstone data from a NanoVNA
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# Copyright (C) 2019, 2020 Rune B. Broberg
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# Copyright (C) 2020 NanoVNA-Saver Authors
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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 logging
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from time import sleep
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from typing import List, Tuple
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import numpy as np
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from PyQt5 import QtCore, QtWidgets
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from PyQt5.QtCore import pyqtSlot, pyqtSignal
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from NanoVNASaver.Calibration import correct_delay
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from NanoVNASaver.Formatting import parse_frequency
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from NanoVNASaver.RFTools import Datapoint
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logger = logging.getLogger(__name__)
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def truncate(values: List[List[Tuple]], count: int) -> List[List[Tuple]]:
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"""truncate drops extrema from data list if averaging is active"""
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keep = len(values) - count
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logger.debug("Truncating from %d values to %d", len(values), keep)
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if count < 1 or keep < 1:
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logger.info("Not doing illegal truncate")
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return values
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truncated = []
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for valueset in np.swapaxes(values, 0, 1).tolist():
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avg = complex(*np.average(valueset, 0))
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truncated.append(
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sorted(valueset,
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key=lambda v, a=avg:
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abs(a - complex(*v)))[:keep])
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return np.swapaxes(truncated, 0, 1).tolist()
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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: QtWidgets.QWidget):
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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: app.vna
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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.running = 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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self.offsetDelay = 0
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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.running = True
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self.percentage = 0
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if not self.app.vna.connected():
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logger.debug(
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"Attempted to run without being connected to the NanoVNA")
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self.running = False
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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
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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 = parse_frequency(self.app.sweepStartInput.text())
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sweep_to = parse_frequency(self.app.sweepEndInput.text())
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logger.debug("Parsed sweep range as %d to %d",
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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 = (
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"Unable to parse frequency inputs"
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" - check start and stop fields.")
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self.stopped = True
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self.running = False
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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 / (self.noSweeps * self.vna.datapoints - 1))
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# Setup complete
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values11 = []
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values21 = []
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frequencies = []
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first_sweep = True
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finished = False
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while not finished:
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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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finished = True
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break
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start = sweep_from + i * self.vna.datapoints * stepsize
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try:
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if self.continuousSweep and not first_sweep:
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_, values11, values21 = self.readSegment(
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start, start + (self.vna.datapoints-1) * stepsize)
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self.percentage = (i + 1) * 100 / self.noSweeps
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self.updateData(values11, values21, i,
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self.vna.datapoints)
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continue
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if self.averaging:
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freq, val11, val21 = self.readAveragedSegment(
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start,
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start + (self.vna.datapoints - 1) * stepsize,
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self.averages)
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else:
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freq, val11, val21 = self.readSegment(
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start, start + (self.vna.datapoints - 1) * stepsize)
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frequencies.extend(freq)
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values11.extend(val11)
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values21.extend(val21)
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self.percentage = (i + 1) * 100 / self.noSweeps
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self.saveData(frequencies, values11, values21)
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except ValueError as e:
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self.error_message = str(e)
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self.stopped = True
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self.running = False
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self.signals.sweepError.emit()
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if not self.continuousSweep:
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finished = True
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first_sweep = False
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if self.noSweeps > 1:
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logger.debug("Resetting NanoVNA sweep to full range: %d to %d",
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parse_frequency(
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self.app.sweepStartInput.text()),
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parse_frequency(self.app.sweepEndInput.text()))
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self.vna.resetSweep(
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parse_frequency(self.app.sweepStartInput.text()),
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parse_frequency(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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self.running = False
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return
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def updateData(self, values11, values21, offset, segment_size=101):
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# Update the data from (i*101) to (i+1)*101
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logger.debug(
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"Calculating data and inserting in existing data at offset %d",
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offset)
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for i, val11 in enumerate(values11):
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re, im = val11
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re21, im21 = values21[i]
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freq = self.data11[offset * segment_size + i].freq
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raw_data11 = Datapoint(freq, re, im)
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raw_data21 = Datapoint(freq, re21, im21)
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data11, data21 = self.applyCalibration([raw_data11], [raw_data21])
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self.data11[offset * segment_size + i] = data11[0]
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self.data21[offset * segment_size + i] = data21[0]
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self.rawData11[offset * segment_size + i] = raw_data11
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self.rawData21[offset * segment_size + i] = raw_data21
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logger.debug("Saving data to application (%d and %d points)",
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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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logger.debug("Freqs: %d, values11: %d, values21: %d",
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len(frequencies), len(values11), len(values21))
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v11 = values11[:]
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v21 = values21[:]
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raw_data11 = []
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raw_data21 = []
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logger.debug("Calculating data including corrections")
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for freq in frequencies:
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real11, imag11 = v11.pop(0)
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real21, imag21 = v21.pop(0)
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raw_data11.append(Datapoint(freq, real11, imag11))
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raw_data21.append(Datapoint(freq, real21, imag21))
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self.rawData11 = raw_data11
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self.rawData21 = raw_data21
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self.data11, self.data21 = self.applyCalibration(
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raw_data11, raw_data21)
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logger.debug("Saving data to application (%d and %d points)",
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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,
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raw_data11: List[Datapoint],
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raw_data21: List[Datapoint]
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) -> Tuple[List[Datapoint], List[Datapoint]]:
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if self.offsetDelay != 0:
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tmp = []
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for dp in raw_data11:
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tmp.append(correct_delay(dp, self.offsetDelay, reflect=True))
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raw_data11 = tmp
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tmp = []
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for dp in raw_data21:
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tmp.append(correct_delay(dp, self.offsetDelay))
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raw_data21 = tmp
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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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for dp in raw_data11:
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data11.append(self.app.calibration.correct11(dp))
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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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for dp in raw_data21:
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data21.append(self.app.calibration.correct21(dp))
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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 = truncate(val11, self.truncates)
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val21 = 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 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.vna.readFrequencies()
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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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if (len(frequencies) != len(values11) or
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len(frequencies) != len(values21)):
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logger.info("No valid data during this run")
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# TODO: display gui warning
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return [], [], []
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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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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 self.vna.validateInput and (
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abs(float(a)) > 9.5 or
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abs(float(b)) > 9.5):
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logger.warning(
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"Got a non plausible data value: (%s)", d)
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done = False
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break
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returndata.append((float(a), float(b)))
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except ValueError as exc:
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logger.exception("An exception occurred reading %s: %s",
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data, exc)
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done = False
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if not done:
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logger.debug("Re-reading %s", data)
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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.",
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data, count)
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if count >= 20:
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logger.critical(
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"Tried and failed to read %s %d times. Giving up.",
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data, count)
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raise IOError(
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f"Failed reading {data} {count} times.\n"
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f"Data outside expected valid ranges,"
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f" or in an unexpected format.\n\n"
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f"You can disable data validation on the"
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f"device settings screen.")
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return returndata
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def setContinuousSweep(self, continuous_sweep: bool):
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self.continuousSweep = continuous_sweep
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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 ValueError:
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return
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def setVNA(self, vna):
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self.vna = vna
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