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| /venv/ | ||
| /env/ | ||
| .idea | ||
| .vscode | ||
| /build/ | ||
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| Original file line number | Diff line number | Diff line change |
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| # NanoVNASaver | ||
| # | ||
| # A python program to view and export Touchstone data from a NanoVNA | ||
| # Copyright (C) 2020 NanoVNA-Saver Authors | ||
| # | ||
| # 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/>. | ||
| ''' | ||
| Created on 30 giu 2020 | ||
| Created on May 30th 2020 | ||
| @author: mauro | ||
| ''' | ||
|
|
||
| from PyQt5 import QtWidgets, QtTest | ||
| import logging | ||
| import math | ||
|
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| from NanoVNASaver.Analysis import Analysis | ||
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| from NanoVNASaver.Hardware import VNA | ||
| from PyQt5 import QtWidgets | ||
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| import numpy as np | ||
| from NanoVNASaver.Marker import Marker | ||
| from NanoVNASaver import RFTools | ||
| from NanoVNASaver.Analysis.VSWRAnalysis import VSWRAnalysis | ||
| from NanoVNASaver.Formatting import format_frequency_sweep | ||
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| logger = logging.getLogger(__name__) | ||
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| class Antenna(object): | ||
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| @staticmethod | ||
| def group_consecutives(vals, step=1): | ||
| """ | ||
| https://stackoverflow.com/questions/7352684/how-to-find-the-groups-of-consecutive-elements-from-an-array-in-numpy | ||
| Return list of consecutive lists of numbers from vals (number list). | ||
| :param vals: | ||
| :param step: | ||
| """ | ||
| run = [] | ||
| result = [run] | ||
| expect = None | ||
| for v in vals: | ||
| if (v == expect) or (expect is None): | ||
| run.append(v) | ||
| else: | ||
| run = [v] | ||
| result.append(run) | ||
| expect = v + step | ||
| return result | ||
|
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| @classmethod | ||
| def analyze(cls, frequencies, values, FIELD_NAME, step=5000, vuoto=False): | ||
| ''' | ||
| dati dati, prova a trovare minimi e bands passanti | ||
| :param cls: | ||
| ''' | ||
|
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| if FIELD_NAME == "rl": | ||
| BAND_THRESHOLD = -7.0 | ||
| MIN_CALCOLO_Q = -27 | ||
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| elif FIELD_NAME == "vswr": | ||
| BAND_THRESHOLD = 2.62 | ||
| MIN_CALCOLO_Q = 1.1 | ||
| else: | ||
| raise ValueError("unknown threshold for {}".format(FIELD_NAME)) | ||
|
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| bands_raw = np.where(values < BAND_THRESHOLD)[0] | ||
|
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| # raggruppo posizioni in cui il valore è sotto la soglia | ||
| bands = cls.group_consecutives(bands_raw) | ||
| # print("raggruppate in ", bands) | ||
| out = [] | ||
| # print "bands", bands | ||
| banda_dict = None | ||
| for band in bands: | ||
| if band: | ||
|
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| print("band ", band) | ||
| fmin = frequencies[band[0]] | ||
|
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| fmax = frequencies[band[-1]] | ||
| estensione = fmax - fmin | ||
| x = np.argmin(values[band[0]:band[-1] + 1]) | ||
| prog = x + band[0] | ||
| min_val = values[prog] | ||
|
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| if banda_dict: | ||
| salto = fmin - banda_dict["fmax"] | ||
| if salto < (10 * step): | ||
| logger.warning("unisco band e proseguo") | ||
| if min_val < banda_dict["min"]: | ||
| logger.debug("aggiusto nuovo minimo, da %s a %s", | ||
| banda_dict["min"], min_val) | ||
| banda_dict["min"] = min_val | ||
| # invalido eventuale Q e band passante ?!? | ||
| banda_dict["q"] = None | ||
| banda_dict["banda_passante"] = None | ||
| banda_dict["fmax"] = fmax | ||
| # non servono ulteriori elaborazioni | ||
| continue | ||
|
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||
| else: | ||
| logger.warning("finalizzo band precedente") | ||
| out.append(banda_dict) | ||
| banda_dict = None | ||
| # se sono qui è nuova | ||
|
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| if estensione == 0 and vuoto: | ||
| logger.warning("ritorno minima estensione") | ||
| banda_dict = {"fmin": fmin - 30 * step, | ||
| "fmax": fmin + 30 * step, | ||
| "banda_passante": None, | ||
| "q": None, | ||
| "min": min_val, | ||
| "freq": fmin, | ||
| "prog": prog, | ||
| } | ||
| else: | ||
| logger.warning("Nuova band") | ||
| if min_val <= MIN_CALCOLO_Q: | ||
|
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| # FIXME: verificare che ci siano valori > | ||
| # BAND_THRESHOLD?!? | ||
| q = np.sqrt(fmax * fmin) / (fmax - fmin) | ||
| logger.info("Q=%s", q) | ||
| else: | ||
| logger.info( | ||
| "non calcolo Q perchè minimo %s non è abbastanza", min_val) | ||
| q = None | ||
| banda_dict = {"fmin": fmin, | ||
| "fmax": fmax, | ||
| "banda_passante": fmax - fmin, | ||
| "q": q, | ||
| "min": min_val, | ||
| "freq": frequencies[prog], | ||
| "prog": prog, | ||
| } | ||
|
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| if banda_dict: | ||
| out.append(banda_dict) | ||
| return out | ||
|
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| class ChartFactory(object): | ||
|
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| @classmethod | ||
| def NewChart(cls, chart_class, name, app): | ||
| from NanoVNASaver.NanoVNASaver import BandsModel | ||
| new_chart = chart_class(name) | ||
| new_chart.isPopout = True | ||
| new_chart.data = app.data | ||
| new_chart.bands = BandsModel() | ||
| i=0 | ||
| default_color = app.default_marker_colors[i] | ||
| color = app.settings.value("Marker" + str(i+1) + "Color", default_color) | ||
| marker = Marker("Marker " + str(i+1), color) | ||
| marker.isMouseControlledRadioButton.setChecked(True) | ||
| new_chart.setMarkers([marker]) | ||
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| return new_chart | ||
|
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| class MinVswrAnalysis(Antenna, Analysis): | ||
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| def __init__(self, app): | ||
| super().__init__(app) | ||
| self._widget = QtWidgets.QWidget() | ||
|
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| def runAnalysis(self): | ||
| self.reset() | ||
|
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| if len(self.app.data) == 0: | ||
| logger.debug("No data to analyse") | ||
| self.result_label.setText("No data to analyse.") | ||
| return | ||
|
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| frequencies = [] | ||
| values = [] | ||
| for p in self.app.data: | ||
| frequencies.append(p.freq) | ||
| vswr = p.vswr | ||
| values.append(vswr) | ||
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| res = self.analyze(np.array(frequencies), | ||
| np.array(values), | ||
| "vswr") | ||
| marker = 0 | ||
| for banda in res: | ||
| if marker < 3: | ||
| self.app.markers[marker].setFrequency( | ||
| str(round(banda["freq"]))) | ||
| marker += 1 | ||
| print("min {min} a {freq}".format(**banda)) | ||
|
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| # Charts | ||
| progr = 0 | ||
| for c in self.app.subscribing_charts: | ||
| if c.name == "S11 VSWR": | ||
| new_chart = c.copy() | ||
| new_chart.isPopout = True | ||
| new_chart.show() | ||
| new_chart.setWindowTitle("%s %s" % (new_chart.name, progr)) | ||
|
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| vna = self.app.vna | ||
| if isinstance(vna, InvalidVNA): | ||
| logger.warning("end analysis, non valid vna") | ||
| else: | ||
| logger.warning("band zoom") | ||
| for banda in res: | ||
| progr += 1 | ||
| # scan | ||
| self.app.sweepStartInput.setText(str(banda["fmin"])) | ||
| self.app.sweepEndInput.setText(str(banda["fmax"])) | ||
| self.app.sweep() | ||
| while not self.app.btnSweep.isEnabled(): | ||
| QtTest.QTest.qWait(500) | ||
| for c in self.app.subscribing_charts: | ||
| if c.name == "S11 VSWR": | ||
| new_chart = c.copy() | ||
| new_chart.isPopout = True | ||
| new_chart.show() | ||
| new_chart.setWindowTitle("%s %s" % (new_chart.name, progr)) | ||
|
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| class ZeroCrossAnalysis(Antenna, Analysis): | ||
|
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| def __init__(self, app): | ||
| super().__init__(app) | ||
| self._widget = QtWidgets.QWidget() | ||
|
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| def runAnalysis(self): | ||
| self.reset() | ||
|
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| if len(self.app.data) == 0: | ||
| logger.debug("No data to analyse") | ||
| self.result_label.setText("No data to analyse.") | ||
| return | ||
|
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| frequencies = [] | ||
| values = [] | ||
| for p in self.app.data: | ||
|
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| frequencies.append(p.freq) | ||
|
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| values.append(p.z.imag) | ||
|
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| zero_crossings = np.where(np.diff(np.sign(np.array(values))))[0] | ||
|
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| marker = 0 | ||
| for pos in zero_crossings: | ||
| freq = round(frequencies[pos]) | ||
| if marker < 3: | ||
| self.app.markers[marker].setFrequency( | ||
| str(freq)) | ||
| marker += 1 | ||
| print("cross at {}".format(freq)) | ||
|
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| class MagLoopAnalysis(VSWRAnalysis): | ||
| ''' | ||
| Find min vswr and change sweep to zoom. | ||
| Useful for tuning magloop. | ||
| ''' | ||
| max_dips_shown = 1 | ||
| vswr_limit_value = 2.56 | ||
| bandwith = 250000 | ||
|
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| def runAnalysis(self): | ||
|
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| super().runAnalysis() | ||
|
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| for m in self.minimums: | ||
| start, lowest, end = m | ||
| if start != end: | ||
| Q = self.app.data[lowest].freq/(self.app.data[end].freq-self.app.data[start].freq) | ||
| self.layout.addRow("Q",QtWidgets.QLabel("{}".format(int(Q)))) | ||
| self.app.sweepStartInput.setText(self.app.data[start].freq) | ||
| self.app.sweepEndInput.setText(self.app.data[end].freq) | ||
| # self.app.sweepEndInput.textEdited.emit(self.app.sweepEndInput.text()) | ||
|
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| if len(self.minimums) > 1: | ||
| self.layout.addRow("", QtWidgets.QLabel( | ||
| "Not magloop or try to lower VSWR limit")) | ||
|
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| for m in self.minimums[:1]: | ||
| # only one time | ||
| start, lowest, end = m | ||
| if start != end: | ||
| Q = self.app.data11[lowest].freq / \ | ||
| (self.app.data11[end].freq - self.app.data11[start].freq) | ||
| self.layout.addRow( | ||
| "Q", QtWidgets.QLabel("{}".format(int(Q)))) | ||
| self.app.sweep_control.set_start(self.app.data11[start].freq) | ||
| self.app.sweep_control.set_end(self.app.data11[end].freq) | ||
| else: | ||
| self.app.sweep_control.set_start( | ||
| self.app.data11[start].freq - self.bandwith) | ||
| self.app.sweep_control.set_end( | ||
| self.app.data11[end].freq + self.bandwith) |
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