nanovna-saver/src/NanoVNASaver/Analysis/PeakSearchAnalysis.py

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Python
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# NanoVNASaver
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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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#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import logging
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from PyQt6 import QtWidgets
import numpy as np
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# pylint: disable=import-error, no-name-in-module
from scipy.signal import find_peaks, peak_prominences
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from NanoVNASaver.Analysis.Base import QHLine
from NanoVNASaver.Analysis.SimplePeakSearchAnalysis import (
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SimplePeakSearchAnalysis,
)
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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):
def __init__(self, app):
super().__init__(app)
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self.peak_cnt = QtWidgets.QSpinBox()
self.peak_cnt.setValue(1)
self.peak_cnt.setMinimum(1)
self.peak_cnt.setMaximum(10)
self.layout.addRow("Max number of peaks", self.peak_cnt)
self.layout.addRow(QHLine())
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self.layout.addRow(QtWidgets.QLabel("<b>Results</b>"))
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:
return
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self.reset()
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s11 = self.app.data.s11
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data, fmt_fnc = self.data_and_format()
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inverted = False
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if self.button["peak_l"].isChecked():
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inverted = True
peaks, _ = find_peaks(
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-np.array(data), width=3, distance=3, prominence=1
)
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else:
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self.button["peak_h"].setChecked(True)
peaks, _ = find_peaks(data, width=3, distance=3, prominence=1)
# Having found the peaks, get the prominence data
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for i, p in np.ndenumerate(peaks):
logger.debug("Peak %s at %s", i, p)
prominences = peak_prominences(data, peaks)[0]
logger.debug("%d prominences", len(prominences))
# Find the peaks with the most extreme values
# Alternately, allow the user to select "most prominent"?
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count = self.peak_cnt.value()
if count > len(prominences):
count = len(prominences)
self.peak_cnt.setValue(count)
indices = np.argpartition(prominences, -count)[-count:]
logger.debug("%d indices", len(indices))
for i in indices:
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pos = peaks[i]
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self.layout.addRow(
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f"Freq: {format_frequency_short(s11[pos].freq)}",
QtWidgets.QLabel(
f" Value: {fmt_fnc(-data[pos] if inverted else data[pos])}"
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),
)
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if self.button["move_marker"].isChecked():
if count > len(self.app.markers):
logger.warning("More peaks found than there are markers")
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)
)
def reset(self):
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super().reset()
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logger.debug(
"Results start at %d, out of %d",
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())
self.layout.removeRow(self.layout.rowCount() - 1)