kopia lustrzana https://github.com/NanoVNA-Saver/nanovna-saver
150 wiersze
5.3 KiB
Python
150 wiersze
5.3 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) 2020,2021 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 PyQt5 import QtWidgets
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import scipy
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import numpy as np
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from NanoVNASaver.Analysis.Base import QHLine
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from NanoVNASaver.Analysis.SimplePeakSearchAnalysis import (
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SimplePeakSearchAnalysis)
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from NanoVNASaver.Formatting import format_vswr
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from NanoVNASaver.Formatting import format_gain
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from NanoVNASaver.Formatting import format_resistance
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from NanoVNASaver.Formatting import format_frequency_short
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logger = logging.getLogger(__name__)
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class PeakSearchAnalysis(SimplePeakSearchAnalysis):
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def __init__(self, app):
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super().__init__(app)
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self.peak_cnt = QtWidgets.QSpinBox()
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self.peak_cnt.setValue(1)
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self.peak_cnt.setMinimum(1)
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self.peak_cnt.setMaximum(10)
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self.layout.addRow("Max number of peaks", self.peak_cnt)
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self.layout.addRow(QHLine())
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self.layout.addRow(QtWidgets.QLabel("<b>Results</b>"))
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self.results_header = self.layout.rowCount()
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self.set_titel('Peak search')
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def runAnalysis(self):
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if not self.app.data.s11:
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return
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self.reset()
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s11 = self.app.data.s11
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s21 = self.app.data.s21
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if not s21:
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self.button['gain'].setEnabled(False)
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if self.button['gain'].isChecked():
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self.button['vswr'].setChecked(True)
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else:
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self.button['gain'].setEnabled(True)
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count = self.peak_cnt.value()
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if self.button['vswr'].isChecked():
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fn = format_vswr
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data = [d.vswr for d in s11]
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elif self.button['gain'].isChecked():
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fn = format_gain
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data = [d.gain for d in s21]
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elif self.button['resistance'].isChecked():
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fn = format_resistance
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data = [d.impedance().real for d in s11]
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elif self.button['reactance'].isChecked():
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fn = format_resistance
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data = [d.impedance().imag for d in s11]
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else:
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logger.warning("Searching for peaks on unknown data")
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return
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sign = 1
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if self.button['peak_h'].isChecked():
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peaks, _ = scipy.signal.find_peaks(
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data, width=3, distance=3, prominence=1)
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elif self.button['peak_l'].isChecked():
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sign = -1
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data = [x * sign for x in data]
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peaks, _ = scipy.signal.find_peaks(
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data, width=3, distance=3, prominence=1)
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else:
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# Both is not yet in
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logger.warning(
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"Searching for peaks,"
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" but neither looking at positive nor negative?")
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return
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# Having found the peaks, get the prominence data
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for i, p in np.ndenumerate(peaks):
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logger.debug("Peak %i at %d", i, p)
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prominences = scipy.signal.peak_prominences(data, peaks)[0]
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logger.debug("%d prominences", len(prominences))
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# Find the peaks with the most extreme values
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# Alternately, allow the user to select "most prominent"?
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indices = np.argpartition(prominences, -count)[-count:]
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logger.debug("%d indices", len(indices))
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for i in indices:
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logger.debug("Index %d", i)
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logger.debug("Prominence %f", prominences[i])
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logger.debug("Index in sweep %d", peaks[i])
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logger.debug("Frequency %d", s11[peaks[i]].freq)
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logger.debug("Value %f", sign * data[peaks[i]])
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self.layout.addRow(
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f"Freq"
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f" {format_frequency_short(s11[peaks[i]].freq)}",
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QtWidgets.QLabel(f" value {fn(sign * data[peaks[i]])}"
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))
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if self.button['move_marker'].isChecked():
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if count > len(self.app.markers):
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logger.warning("More peaks found than there are markers")
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for i in range(min(count, len(self.app.markers))):
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self.app.markers[i].setFrequency(
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str(s11[peaks[indices[i]]].freq))
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max_val = -10**10
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max_idx = -1
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for p in peaks:
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if data[p] > max_val:
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max_val = data[p]
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max_idx = p
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logger.debug("Max peak at %d, value %f", max_idx, max_val)
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def reset(self):
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logger.debug("Reset analysis")
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logger.debug("Results start at %d, out of %d",
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self.results_header, self.layout.rowCount())
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for _ in range(self.results_header, self.layout.rowCount()):
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logger.debug("deleting %s", self.layout.rowCount())
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self.layout.removeRow(self.layout.rowCount() - 1)
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