implement updatable MeasurementPlot class

Python_script/MeasurementPlot.py

+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+import time
+
+class MeasurementPlot:
+    def __init__(self, title=''):
+        self.fig, self.ax1 = plt.subplots(2, figsize=(12, 10))
+        self.fig.suptitle("Measurement "+title, color="red")
+
+        # First plot: Phase and magnitude
+        self.path_collection_phase = self.ax1[0].scatter([], [], c='red', marker='<', label='Phase')
+        self.magnitude_axis = self.ax1[0].twinx()
+        self.path_collection_mag = self.magnitude_axis.scatter([], [], c='#3120E0', marker='4', label='Magnitude')
+        self.equi_axis0 = self.ax1[0].twinx()
+        self.equi_axis0.spines['right'].set_position(('outward', 40))
+        self.path_collection_equi0 = self.equi_axis0.scatter([], [], c='black', marker=".", label='Equilibrium_Indicator')
+
+        self.ax1[0].set_xlabel("TIMESTAMP")
+        self.ax1[0].set_ylabel("PHASE", color='red')
+        self.magnitude_axis.set_ylabel("MAGNITUDE", color='#3120E0')
+        self.equi_axis0.set_ylabel("EQUILIBRIUM_INDICATOR", color='black')
+        # fix range to 0..31 with some extra margin for plotting
+        self.equi_axis0.set_ylim(-1, 32)
+
+        self.ax1[0].grid(True, linestyle=":")
+        all_path_collections = [self.path_collection_phase, self.path_collection_mag, self.path_collection_equi0]
+        labels = [pc.get_label() for pc in all_path_collections]
+        self.ax1[0].legend(all_path_collections, labels, loc='lower right')
+
+        # Second plot: Humidity and temperature
+        self.path_collection_temp = self.ax1[1].scatter([], [], c='blue', marker='p', label="Temperature")
+        self.humidity_axis = self.ax1[1].twinx()
+        self.path_collection_hum = self.humidity_axis.scatter([], [], c='green', marker="*", label="Humidity")
+        self.equi_axis1 = self.ax1[1].twinx()
+        self.equi_axis1.spines['right'].set_position(('outward', 40))
+        self.path_collection_equi1 = self.equi_axis1.scatter([], [], c='black', marker=".", label="Equilibrium_Indicator")
+
+        self.ax1[1].set_xlabel("TIMESTAMP")
+        self.ax1[1].set_ylabel("TEMPERATURE ", color='blue')
+        self.humidity_axis.set_ylabel("HUMIDITY", color='green')
+        self.equi_axis1.set_ylabel("EQUILIBRIUM_INDICATOR", color='black')
+        self.equi_axis1.set_ylim(-1, 32)
+
+        self.ax1[1].grid(True, linestyle=":")
+        all_path_collections = [self.path_collection_temp, self.path_collection_hum, self.path_collection_equi1]
+        labels = [pc.get_label() for pc in all_path_collections]
+        self.ax1[1].legend(all_path_collections, labels, loc='lower right')
+
+    def draw(self, data_frame, save_pdf=True):
+        timestamps = data_frame.TIMESTAMP
+        minimum, maximum = self.get_extended_min_max(timestamps)
+        self.ax1[0].set_xlim(minimum, maximum)
+        self.ax1[1].set_xlim(minimum, maximum)
+
+        phases = data_frame.S21_PHASE
+        minimum, maximum = self.get_extended_min_max(phases)
+        self.ax1[0].set_ylim(minimum, maximum)
+        self.path_collection_phase.set_offsets(np.c_[timestamps, phases])
+
+        magnitudes = data_frame.S21_MAGNITUDE
+        minimum, maximum = self.get_extended_min_max(magnitudes)
+        self.magnitude_axis.set_ylim(minimum, maximum)
+        self.path_collection_mag.set_offsets(np.c_[timestamps, magnitudes])
+
+        temperatures = data_frame.READBACK_TEMPERATURE
+        minimum, maximum = self.get_extended_min_max(temperatures)
+        self.ax1[1].set_ylim(minimum, maximum)
+        self.path_collection_temp.set_offsets(np.c_[timestamps, temperatures])
+
+        humidities = data_frame.READBACK_HUMIDITY
+        minimum, maximum = self.get_extended_min_max(humidities)
+        self.humidity_axis.set_ylim(minimum, maximum)
+        self.path_collection_hum.set_offsets(np.c_[timestamps, humidities])
+
+        self.path_collection_equi0.set_offsets(np.c_[timestamps, data_frame.EQUILIBRIUM_INDICATOR])
+        self.path_collection_equi1.set_offsets(np.c_[timestamps, data_frame.EQUILIBRIUM_INDICATOR])
+
+        plt.show()
+        if plt.isinteractive():
+            self.fig.canvas.draw()
+            self.fig.canvas.flush_events()
+
+    # add 5 % of the distance between min and max to the range
+    def get_extended_min_max(self, array):
+        distance = array.max() - array.min()
+        return array.min()-0.05*distance, array.max()+0.05*distance
+
+if __name__ == '__main__':
+    m = MeasurementPlot()
+    plt.ion()
+    measurements = []
+
+    for i in range(20):
+        measurement = {
+            'TIMESTAMP': i,
+            'READBACK_TEMPERATURE': 25 - i,
+            'READBACK_HUMIDITY': 10 + 0.1*i,
+            'EQUILIBRIUM_INDICATOR': i % 4,
+            'S21_PHASE': 20 - 2*i,
+            'S21_MAGNITUDE': 0.3*i
+        }
+        measurements.append(measurement)
+        data_frame = pd.DataFrame(measurements)
+        m.draw(data_frame)
+        print(str(i))
+        time.sleep(0.3)
+
+    print('I am done. ')
+    plt.ioff()
+    m.draw(data_frame)

Python_script/prototype.py

@@ -70,6 +70,8 @@ class Measurements:
             # csv.dict writer add adda row wise
             writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
             writer.writeheader()
+            self.data_collection = []
+            self.subplot_tuple = plt.subplots(2, figsize=(12, 10))
 
             with open(self.sweep_file) as file:
                 try:
@@ -134,7 +136,8 @@ class Measurements:
                                 print('Setpoint: ' + str(next_temp) + ' ' + str(next_hum) + ' | Temp: ' + data.temp +
                                       ' °C' + ' | Humid: ' + data.hum + '%'
                                       + ' | soaking read nr' + str(len(magnitudes_queue)))
-                                self.write_data(writer, next_temp, next_hum, data, self.cook_up_equi_indicator())
+                                self.write_data(writer, next_temp, next_hum, data, self.cook_up_equi_indicator())#,
+                                                #data_frame, subplot_tuple)
 
                                 if self.temperature_stable and self.humidity_stable and self.magnitude_stable and\
                                         self.phase_stable:
@@ -198,8 +201,8 @@ class Measurements:
 
         return MeasurementData(int(self.clock.time()), temp, hum, power, frequency, s11, s21, s12, s22)
 
-    def write_data(self, writer, target_temp, target_hum, data, equi_indicator):
-        writer.writerow({
+    def write_data(self, writer, target_temp, target_hum, data, equi_indicator):#, data_frame, subplot_tuple):
+        measurement = {
             'TIMESTAMP': data.timestamp,
             'TARGET_TEMPERATURE': target_temp,
             'READBACK_TEMPERATURE': data.temp,
@@ -216,7 +219,11 @@ class Measurements:
             'S12_MAGNITUDE': self.calculate_mean_magnitude(data.s12),
             'S22_PHASE': self.calculate_mean_phase(data.s22),
             'S22_MAGNITUDE': self.calculate_mean_magnitude(data.s22)
-        })
+        }
+        writer.writerow(measurement)
+        self.data_collection.append(measurement)
+        data_frame = pd.DataFrame(self.data_collection)
+        plot_measurement(data_frame, False, False, self.subplot_tuple)
 
     def current_milli_time(self):
         return int(round(self.clock.time() * 1000))
@@ -280,7 +287,6 @@ def plot_measurement(data_frame, show_blocking_plot, save_pdf=True, subplot_tupl
     fig, ax1 = subplot_tuple
     if fig is None or ax1 is None:
         fig, ax1 = plt.subplots(2, figsize=(12, 10))
-    fig.suptitle("Graphical representation of chamber output", color="red")
 
     path_collection01 = ax1[0].scatter(data_frame.TIMESTAMP, data_frame.S21_PHASE, c='red', marker='<', label='Phase')
     twin2_0 = ax1[0].twinx()
@@ -326,6 +332,8 @@ def plot_measurement(data_frame, show_blocking_plot, save_pdf=True, subplot_tupl
         plt.ioff()
     else:
         plt.ion()
+        fig.canvas.draw()
+        fig.canvas.flush_events()
     plt.show()
 
 def plot_output(output_basename, show_blocking_plot, save_pdf=True):