MeasurementPlot.py

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import time

# Different exceptions can be thrown while plotting, depending on the backend.
# We catch them all locally and raise our own exception instead
class PlottingError(Exception):
    "Raised when plotting fails"
    pass

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, pdf_name=''):
        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])

        if not pdf_name == '':
            self.fig.savefig(pdf_name)

        plt.show()
        if plt.isinteractive():
            try:
                self.fig.canvas.draw()
                self.fig.canvas.flush_events()
            except Exception as e:
                raise PlottingError from e

    # add 5 % of the distance between min and max to the range
    @staticmethod
    def get_extended_min_max(array):
        distance = array.max() - array.min()
        if distance == 0.:
            distance = 0.5
        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, 'the.pdf')