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https://github.com/nqrduck/nqrduck-autotm.git
synced 2024-11-04 17:30:01 +00:00
Changed to S11Data structure.
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720e3ac9f1
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711a04f945
3 changed files with 117 additions and 39 deletions
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@ -54,31 +54,42 @@ class AutoTMController(ModuleController):
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text = text.rstrip('\r\n')
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# logger.debug("Received data: %s", text)
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# If the text starts with 'f' and the frequency sweep spinner is visible we know that the data is a data point
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# then we have the data for the return loss and the phase at a certain frequency
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if text.startswith("f") and self.module.view.frequency_sweep_spinner.isVisible():
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text = text[1:].split("r")
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frequency = float(text[0])
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return_loss, phase = map(float, text[1].split("p"))
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self.module.model.add_data_point(frequency, return_loss, phase)
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# If the text starts with 'r' and no calibration is active we know that the data is a measurement
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elif text.startswith("r") and self.module.model.active_calibration == None:
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logger.debug("Measurement finished")
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self.module.view.plot_data()
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self.module.model.measurement = self.module.model.data_points.copy()
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self.module.view.frequency_sweep_spinner.hide()
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# If the text starts with 'r' and a short calibration is active we know that the data is a short calibration
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elif text.startswith("r") and self.module.model.active_calibration == "short":
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logger.debug("Short calibration finished")
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self.module.model.short_calibration = self.module.model.data_points.copy()
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self.module.model.active_calibration = None
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self.module.view.frequency_sweep_spinner.hide()
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# If the text starts with 'r' and an open calibration is active we know that the data is an open calibration
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elif text.startswith("r") and self.module.model.active_calibration == "open":
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logger.debug("Open calibration finished")
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self.module.model.open_calibration = self.module.model.data_points.copy()
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self.module.model.active_calibration = None
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self.module.view.frequency_sweep_spinner.hide()
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# If the text starts with 'r' and a load calibration is active we know that the data is a load calibration
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elif text.startswith("r") and self.module.model.active_calibration == "load":
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logger.debug("Load calibration finished")
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self.module.model.load_calibration = self.module.model.data_points.copy()
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self.module.model.active_calibration = None
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self.module.view.frequency_sweep_spinner.hide()
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else:
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# If the text starts with 'i' we know that the data is an info message
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elif text.startswith("i"):
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text = "ATM Info: " + text[1:]
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self.module.view.add_info_text(text)
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# If the text starts with 'e' we know that the data is an error message
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elif text.startswith("e"):
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text = "ATM Error: " + text[1:]
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self.module.view.add_info_text(text)
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def on_short_calibration(self, start_frequency : float, stop_frequency : float) -> None:
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@ -133,9 +144,9 @@ class AutoTMController(ModuleController):
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ideal_gamma_open = 1
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ideal_gamma_load = 0
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short_calibration = [10 **(-returnloss_s[1] /6 / 24 / 20) for returnloss_s in self.module.model.short_calibration]
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open_calibration = [10 **(-returnloss_o[1] / 6 / 24 / 20) for returnloss_o in self.module.model.open_calibration]
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load_calibration = [10 **(-returnloss_l[1] / 6 / 24 / 20) for returnloss_l in self.module.model.load_calibration]
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short_calibration = [10 **(-returnloss_s[1]) for returnloss_s in self.module.model.short_calibration]
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open_calibration = [10 **(-returnloss_o[1]) for returnloss_o in self.module.model.open_calibration]
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load_calibration = [10 **(-returnloss_l[1]) for returnloss_l in self.module.model.load_calibration]
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e_00s = []
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e11s = []
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@ -1,4 +1,5 @@
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import serial
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import cmath
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import numpy as np
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import logging
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from PyQt6.QtCore import pyqtSignal
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from PyQt6.QtSerialPort import QSerialPort
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@ -6,14 +7,51 @@ from nqrduck.module.module_model import ModuleModel
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logger = logging.getLogger(__name__)
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class S11Data:
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# Conversion factors - the data is generally sent and received in mV
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# These values are used to convert the data to dB and degrees
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CENTER_POINT = 900 # mV
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MAGNITUDE_SLOPE = 30 # dB/mV
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PHASE_SLOPE = 10 # deg/mV
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def __init__(self, data_points : list) -> None:
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self.frequency = np.array([data_point[0] for data_point in data_points])
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self.return_loss_mv = np.array([data_point[1] for data_point in data_points])
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self.phase_mv = np.array([data_point[2] for data_point in data_points])
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@property
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def millivolts(self):
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return self.frequency, self.return_loss_mv, self.phase_mv
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@property
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def return_loss_db(self):
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return (self.return_loss_mv - self.CENTER_POINT) / self.MAGNITUDE_SLOPE
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@property
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def phase_deg(self):
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return (self.phase_mv - self.CENTER_POINT) / self.PHASE_SLOPE
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@property
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def phase_rad(self):
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return self.phase_deg * cmath.pi / 180
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@property
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def gamma(self):
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"""Complex reflection coefficient"""
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return cmath.rect(10 ** (-self.return_loss_db / 20), self.phase_rad)
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class AutoTMModel(ModuleModel):
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available_devices_changed = pyqtSignal(list)
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serial_changed = pyqtSignal(QSerialPort)
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data_points_changed = pyqtSignal(list)
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short_calibration_finished = pyqtSignal(list)
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open_calibration_finished = pyqtSignal(list)
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load_calibration_finished = pyqtSignal(list)
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short_calibration_finished = pyqtSignal(S11Data)
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open_calibration_finished = pyqtSignal(S11Data)
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load_calibration_finished = pyqtSignal(S11Data)
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measurement_finished = pyqtSignal(S11Data)
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def __init__(self, module) -> None:
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super().__init__(module)
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@ -31,6 +69,8 @@ class AutoTMModel(ModuleModel):
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@property
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def serial(self):
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"""The serial property is used to store the current serial connection.
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"""
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return self._serial
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@serial.setter
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@ -39,7 +79,9 @@ class AutoTMModel(ModuleModel):
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self.serial_changed.emit(value)
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def add_data_point(self, frequency: float, return_loss: float, phase : float) -> None:
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"""Add a data point to the model."""
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"""Add a data point to the model. These data points are our intermediate data points read in via the serial connection.
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They will be saved in the according properties later on.
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"""
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self.data_points.append((frequency, return_loss, phase))
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self.data_points_changed.emit(self.data_points)
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@ -48,6 +90,20 @@ class AutoTMModel(ModuleModel):
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self.data_points.clear()
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self.data_points_changed.emit(self.data_points)
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@property
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def measurement(self):
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"""The measurement property is used to store the current measurement.
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This is the measurement that is shown in the main S11 plot"""
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return self._measurement
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@measurement.setter
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def measurement(self, value):
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"""The measurement value is a tuple of three lists: frequency, return loss and phase."""
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self._measurement = S11Data(value)
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self.measurement_finished.emit(self._measurement)
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# Calibration properties
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@property
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def active_calibration(self):
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return self._active_calibration
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@ -63,8 +119,8 @@ class AutoTMModel(ModuleModel):
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@short_calibration.setter
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def short_calibration(self, value):
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logger.debug("Setting short calibration")
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self._short_calibration = value
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self.short_calibration_finished.emit(value)
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self._short_calibration = S11Data(value)
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self.short_calibration_finished.emit(self._short_calibration)
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def init_short_calibration(self):
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"""This method is called when a frequency sweep has been started for a short calibration in this way the module knows that the next data points are for a short calibration."""
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@ -78,8 +134,8 @@ class AutoTMModel(ModuleModel):
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@open_calibration.setter
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def open_calibration(self, value):
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logger.debug("Setting open calibration")
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self._open_calibration = value
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self.open_calibration_finished.emit(value)
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self._open_calibration = S11Data(value)
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self.open_calibration_finished.emit(self._open_calibration)
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def init_open_calibration(self):
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"""This method is called when a frequency sweep has been started for an open calibration in this way the module knows that the next data points are for an open calibration."""
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@ -93,8 +149,8 @@ class AutoTMModel(ModuleModel):
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@load_calibration.setter
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def load_calibration(self, value):
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logger.debug("Setting load calibration")
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self._load_calibration = value
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self.load_calibration_finished.emit(value)
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self._load_calibration = S11Data(value)
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self.load_calibration_finished.emit(self._load_calibration)
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def init_load_calibration(self):
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"""This method is called when a frequency sweep has been started for a load calibration in this way the module knows that the next data points are for a load calibration."""
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@ -109,3 +165,4 @@ class AutoTMModel(ModuleModel):
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def calibration(self, value):
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logger.debug("Setting calibration")
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self._calibration = value
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@ -45,10 +45,14 @@ class AutoTMView(ModuleView):
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# On clicking of the calibration button call the on_calibration_button_clicked method
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self._ui_form.calibrationButton.clicked.connect(self.on_calibration_button_clicked)
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# Connect the measurement finished signal to the plot_measurement slot
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self.module.model.measurement_finished.connect(self.plot_measurement)
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# Add a vertical layout to the info box
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self._ui_form.scrollAreaWidgetContents.setLayout(QVBoxLayout())
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self._ui_form.scrollAreaWidgetContents.layout().setAlignment(Qt.AlignmentFlag.AlignTop)
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self.init_plot()
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self.init_labels()
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@ -115,15 +119,15 @@ class AutoTMView(ModuleView):
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self._ui_form.connectionLabel.setText("Disconnected")
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logger.debug("Updated serial connection label")
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def plot_data(self) -> None:
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def plot_measurement(self, data : "S11Data") -> None:
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"""Update the S11 plot with the current data points.
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Args:
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data_points (list): List of data points to plot.
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"""
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x = [data_point[0] for data_point in self.module.model.data_points]
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y = [(data_point[1] - 900) / 30 for data_point in self.module.model.data_points]
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phase = [(data_point[2] - 900) / 10 for data_point in self.module.model.data_points]
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frequency = data.frequency
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return_loss_db = data.return_loss_db
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phase = data.phase_deg
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# Calibration test:
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#calibration = self.module.model.calibration
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@ -143,7 +147,7 @@ class AutoTMView(ModuleView):
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phase_ax = self._ui_form.S11Plot.canvas.ax.twinx()
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phase_ax.set_ylabel("Phase (deg)")
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phase_ax.plot(x, phase, color="orange", linestyle="--")
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phase_ax.plot(frequency, phase, color="orange", linestyle="--")
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phase_ax.set_ylim(-180, 180)
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phase_ax.invert_yaxis()
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@ -153,7 +157,7 @@ class AutoTMView(ModuleView):
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magnitude_ax.set_ylabel("S11 (dB)")
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magnitude_ax.set_title("S11")
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magnitude_ax.grid(True)
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magnitude_ax.plot(x, y)
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magnitude_ax.plot(frequency, return_loss_db, color="blue")
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# make the y axis go down instead of up
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magnitude_ax.invert_yaxis()
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@ -294,33 +298,39 @@ class AutoTMView(ModuleView):
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self.module.model.open_calibration_finished.connect(self.on_open_calibration_finished)
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self.module.model.load_calibration_finished.connect(self.on_load_calibration_finished)
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def on_short_calibration_finished(self, short_calibration : list) -> None:
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def on_short_calibration_finished(self, short_calibration : "S11Data") -> None:
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self.on_calibration_finished("short", self.short_plot, short_calibration)
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def on_open_calibration_finished(self, open_calibration : list) -> None:
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def on_open_calibration_finished(self, open_calibration : "S11Data") -> None:
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self.on_calibration_finished("open", self.open_plot, open_calibration)
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def on_load_calibration_finished(self, load_calibration : list) -> None:
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def on_load_calibration_finished(self, load_calibration : "S11Data") -> None:
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self.on_calibration_finished("load", self.load_plot, load_calibration)
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def on_calibration_finished(self, type : str, widget: MplWidget, data :list) -> None:
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def on_calibration_finished(self, type : str, widget: MplWidget, data :"S11Data") -> None:
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"""This method is called when a calibration has finished.
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It plots the calibration data on the given widget.
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"""
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x = [data_point[0] for data_point in data]
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magnitude = [data_point[1] for data_point in data]
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phase = [data_point[2] for data_point in data]
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ax = widget.canvas.ax
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ax.clear()
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ax.set_xlabel("Frequency (MHz)")
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ax.set_ylabel("S11 (dB)")
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ax.set_title("S11")
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ax.grid(True)
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ax.plot(x, magnitude, label="Magnitude")
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ax.plot(x, phase, label="Phase")
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ax.legend()
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frequency = data.frequency
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return_loss_db = data.return_loss_db
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phase = data.phase_deg
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phase_ax = widget.canvas.ax.twinx()
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phase_ax.set_ylabel("Phase (deg)")
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phase_ax.plot(frequency, phase, color="orange", linestyle="--")
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phase_ax.set_ylim(-180, 180)
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phase_ax.invert_yaxis()
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magnitude_ax = widget.canvas.ax
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magnitude_ax.clear()
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magnitude_ax.set_xlabel("Frequency (MHz)")
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magnitude_ax.set_ylabel("S11 (dB)")
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magnitude_ax.set_title("S11")
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magnitude_ax.grid(True)
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magnitude_ax.plot(frequency, return_loss_db, color="blue")
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# make the y axis go down instead of up
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ax.invert_yaxis()
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magnitude_ax.invert_yaxis()
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widget.canvas.draw()
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widget.canvas.flush_events()
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