import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import time
import sys
# 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='', env_cond_sensors ='', legend_loc = 'upper left',\
legend_bbox_to_anchor = (1.09, 1)):
# set python for opening an separate plot window when starting from anaconda, Michael
if 'ipykernel' in sys.modules:
from IPython import get_ipython
get_ipython().run_line_magic('matplotlib', 'qt')
self.env_cond_sensors = env_cond_sensors
# parameter for legend of subplots
self.legend_loc = legend_loc
self.legend_bbox_to_anchor = legend_bbox_to_anchor
# Third, Fourth and Fifth plot for additional external sensors, Michael
self.fig, self.ax1 = plt.subplots(5, figsize=(25, 20))
self.fig.subplots_adjust(bottom= 0.1, right=0.8, hspace = 0.4)
self.fig.suptitle("Measurement "+title, color="red")
# First plot: Phase and magnitude, Michael
self.path_collection_phase = self.ax1[0].scatter([], [], c='red', marker='<', label='DUT Phase')
self.path_collection_fit = self.ax1[0].scatter([], [], c='green', marker='.', label = ' ')
self.magnitude_axis = self.ax1[0].twinx()
# in entry of legend for phase and magnitude the word DUT is added in front, Michael
self.path_collection_mag = self.magnitude_axis.scatter([], [], c='#3120E0', marker='4', label='DUT Magnitude')
self.equi_axis0 = self.ax1[0].twinx()
self.equi_axis0.spines['right'].set_position(('outward', 75))
self.path_collection_equi0 = self.equi_axis0.scatter([], [], c='black', marker=".", label='Equilibrium_Indicator')
# units added to y-axes of subplot 1, Michael
self.ax1[0].set_xlabel("TIMESTAMP")
self.ax1[0].set_ylabel("PHASE [°]", color='red')
self.magnitude_axis.set_ylabel("MAGNITUDE [dB]", color='#3120E0')
# label of y-axis for equilibrium indicator is changed to Indiccator Value because it's shorter, Michael
self.equi_axis0.set_ylabel("INDICATOR VALUE", 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, self.path_collection_fit]
labels = [pc.get_label() for pc in all_path_collections]
self.phase_legend = self.ax1[0].legend(all_path_collections, labels, loc=self.legend_loc, bbox_to_anchor = \
self.legend_bbox_to_anchor)
ax = self.fig.axes
# plot delta values for phase and magnitude at left position outside the plot, Michael
self.annotation = ax[0].annotate('' ,xy=(0,1), \
xycoords='axes fraction', xytext=(-0.16,1), \
textcoords='axes fraction',fontsize = '16', \
horizontalalignment='left',verticalalignment='bottom')
# Second plot: Humidity and temperature of climate chamber requested from internal sensors of chamber
self.path_collection_temp = self.ax1[1].scatter([], [], c='blue', marker='p', label="Chamber Temperature")
self.humidity_axis = self.ax1[1].twinx()
self.path_collection_hum = self.humidity_axis.scatter([], [], c='green', marker="*", label="Chamber Humidity")
self.equi_axis1 = self.ax1[1].twinx()
self.equi_axis1.spines['right'].set_position(('outward', 75))
self.path_collection_equi1 = self.equi_axis1.scatter([], [], c='black', marker=".", label="Equilibrium_Indicator")
# units added to y-axes of subplot 2, Michael
self.ax1[1].set_xlabel("TIMESTAMP")
self.ax1[1].set_ylabel("TEMPERATURE [°C] ", color='blue')
self.humidity_axis.set_ylabel("HUMIDITY [%RH]", color='green')
# label of y-axis for equilibrium indicator is changed to Indiccator Value because it's shorter, Michael
self.equi_axis1.set_ylabel("INDICATOR VALUE", 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=self.legend_loc, bbox_to_anchor = \
self.legend_bbox_to_anchor)
# Third plot: parameter of external sensors
# DUT temperature, DUT humidity, Michael
# configuration of used sensor port in ext_sens_data.json, Michael
self.path_collection_temp_dut = self.ax1[2].scatter([],[], c='red', marker='p', \
label='DUT temperature')
self.ext_sens_hum_axis = self.ax1[2].twinx()
self.path_collection_hum_dut = self.ext_sens_hum_axis.scatter([],[], c='purple', \
marker='*', label='DUT humidity')
self.ax1[2].set_xlabel("TIMESTAMP")
self.ax1[2].set_ylabel("TEMPERATURE [°C]", color='red')
self.ext_sens_hum_axis.set_ylabel("HUMIDITY [%RH]", color = 'purple')
self.ax1[2].grid(True, linestyle=":")
all_path_collections = [self.path_collection_temp_dut, self.path_collection_hum_dut]
labels = [pc.get_label() for pc in all_path_collections]
self.ax1[2].legend(all_path_collections, labels, loc=self.legend_loc, bbox_to_anchor = \
self.legend_bbox_to_anchor)
# Forth plot: parameter of external sensors
# room temperature, room humidity , air pressure room, Michael
# configuration of used sensor port in ext_sens_data.json, Michael
self.path_collection_temp_room = self.ax1[3].scatter([],[], c='green', marker='*', label='room temperature')
self.sec_ext_hum_sens_axis = self.ax1[3].twinx()
self.path_collection_hum_room = self.sec_ext_hum_sens_axis.scatter([],[], c='orange', marker='>', label='room humidity')
self.press_axis = self.ax1[3].twinx()
self.press_axis.spines['right'].set_position(('outward', 60))
self.path_collection_air_press_room = self.press_axis.scatter([],[], c='grey', marker='4', label='air pressure room')
self.ax1[3].set_xlabel("TIMESTAMP")
self.ax1[3].set_ylabel("TEMPERATURE [°C]", color='green')
self.sec_ext_hum_sens_axis.set_ylabel("HUMIDITY [%RH]", color = 'orange')
self.press_axis.set_ylabel("AIR PRESSURE [mb]", color ='grey')
self.ax1[3].grid(True, linestyle=":")
all_path_collections = [self.path_collection_temp_room, self.path_collection_hum_room, \
self.path_collection_air_press_room]
labels = [pc.get_label() for pc in all_path_collections]
self.ax1[3].legend(all_path_collections, labels, loc=self.legend_loc, bbox_to_anchor = \
self.legend_bbox_to_anchor)
# Fifth plot: parameter of external sensors
# meas instruments temperature, meas instruments humidity, Michael
# configuration of used sensor port in ext_sens_data.json, Michael
subplot_dict = self.config_fith_subplot()
self.path_collection_trace_1 = self.ax1[4].scatter([], [], c='black', \
marker='p', label = subplot_dict.get('label_trace_1'))
self.sec_plot_param_axis = self.ax1[4].twinx()
self.path_collection_trace_2 = self.sec_plot_param_axis.scatter([], [], c='brown', \
marker="*",label = subplot_dict.get('label_trace_2'))
# # units added to y-axes of subplot 5, Michael
self.ax1[4].set_xlabel("TIMESTAMP")
self.ax1[4].set_ylabel(subplot_dict.get('y_axis'), color='black')
self.sec_plot_param_axis.set_ylabel(subplot_dict.get('sec_y_axis'), color='brown')
self.ax1[4].grid(True, linestyle=":")
all_path_collections = [self.path_collection_trace_1, \
self.path_collection_trace_2]
labels = [pc.get_label() for pc in all_path_collections]
self.ax1[4].legend(all_path_collections, labels, loc=self.legend_loc, bbox_to_anchor = \
self.legend_bbox_to_anchor)
# sclae fontsize of all plot window elements to size 16, Michael
plt.rcParams.update({'font.size':16})
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)
# because subplots where increase x-axis limits has to be set equal to first and second plot, Michael
self.ax1[2].set_xlim(minimum, maximum)
self.ax1[3].set_xlim(minimum, maximum)
self.ax1[4].set_xlim(minimum, maximum)
# refresh data for phase in subplot for phase and magnitude
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])
self.path_collection_fit.set_offsets(np.c_[[], []])
# refresh data for magnitude in subplot for phase and magnitude
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])
# refresh data for chamber temperature in subplot for chamber temperature and humidity
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])
# refresh data for chamber humidity in subplot for chamber temperature and humidity
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])
# refresh temperatures for used external sensors in subplots, Michael
temp_dut = data_frame.TEMP_DUT
temp_room = data_frame.TEMP_ROOM
minimum, maximum = self.get_extended_min_max(temp_dut)
self.ax1[2].set_ylim(minimum, maximum)
self.path_collection_temp_dut.set_offsets(np.c_[timestamps, temp_dut])
minimum, maximum = self.get_extended_min_max(temp_room)
self.ax1[3].set_ylim(minimum, maximum)
self.path_collection_temp_room.set_offsets(np.c_[timestamps, temp_room])
# refresh humidities external sensors in subplots for DUT humidity and room humidity
# humidity, Michael
hum_dut = data_frame.HUM_DUT
hum_room = data_frame.HUM_ROOM
minimum, maximum = self.get_extended_min_max(hum_dut)
self.ext_sens_hum_axis.set_ylim(minimum, maximum)
minimum, maximum = self.get_extended_min_max(hum_room)
self.sec_ext_hum_sens_axis.set_ylim(minimum, maximum)
self.path_collection_hum_dut.set_offsets(np.c_[timestamps, hum_dut])
self.path_collection_hum_room.set_offsets(np.c_[timestamps, hum_room])
# refresh air pressure of external sensor in subplot for air pressure room, Michael
air_press_room = data_frame.AIR_PRESS_ROOM
minimum, maximum = self.get_extended_min_max(air_press_room)
self.press_axis.set_ylim(minimum, maximum)
self.path_collection_air_press_room.set_offsets(np.c_[timestamps, air_press_room])
# refresh temperature and humidity of external sensor in subplot for measurement
# for instrument temperature and measurement instrument humidity, Michael
val_trace_1, val_trace_2 = self.refresh_param_fith_subplot(data_frame)
minimum, maximum = self.get_extended_min_max(val_trace_1)
self.ax1[4].set_ylim(minimum, maximum)
minimum, maximum = self.get_extended_min_max(val_trace_2)
self.sec_plot_param_axis.set_ylim(minimum, maximum)
self.path_collection_trace_1.set_offsets(np.c_[timestamps, val_trace_1])
self.path_collection_trace_2.set_offsets(np.c_[timestamps, val_trace_2])
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
def config_fith_subplot(self):
# key names for config parameter fith subplot
keys = ["label_trace_1", "label_trace_2", "y_axis", "sec_y_axis"]
if self.env_cond_sensors == 'ext':
# values for plotting evironmental conditions in measurement instrument chamber
values = ["temp sensor\nmeas instruments", "hum sensor\nmeas instruments", \
"TEMPERATURE [°C]", "HUMIDITY [%RH]"]
elif self.env_cond_sensors == 'int':
# values for plotting evironmental conditions in measurement instrument chamber
values = ["chamber temperature\nmeas instruments", "chamber humidity\nmeas instruments", \
"TEMPERATURE [°C]", "HUMIDITY [%RH]"]
else:
# values for plotting heater activity in fith subplot
values = ["Temp Heater", "Temp Heater", \
"ACTIVITY [%]","ACTIVITY [%]"]
# generate dictionary from selection
config_subplot_dict = dict(zip(keys, values))
return config_subplot_dict
def refresh_param_fith_subplot(self, data_frame):
if self.env_cond_sensors == 'ext':
# chose sensor values for refreshing fith subplot
val_trace_1 = data_frame.TEMP_MEAS_INSTR
val_trace_2 = data_frame.HUM_MEAS_INSTR
elif self.env_cond_sensors == 'int':
val_trace_1 = data_frame.READBACK_TEMP_MEAS_INSTR
val_trace_2 = data_frame.READBACK_HUM_MEAS_INSTR
else:
# chose heater values for refreshing fift plot
val_trace_1 = data_frame.TEMP_HEATER
val_trace_2 = data_frame.HUM_HEATER
return val_trace_1, val_trace_2
# 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 = 1
return array.min()-0.05*distance, array.max()+0.05*distance
# test procedure for measurement plot procedure
if __name__ == '__main__':
m = MeasurementPlot(env_cond_sensors = "int")
plt.ion()
measurements = []
# generation of datapoints for plot
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,
#acivity temp heater and hum heater, Michael
'TEMP_HEATER': 10,
# activity humidity heater, Michael, Michael
'HUM_HEATER': 3,
# DUT Temperature of external temp sensor added, Michael
'TEMP_DUT': i,
# room temperature of external temp sensor added, Michael
'TEMP_ROOM': 25-i,
# DUT Humidity of external hum sensor added, Michael
'HUM_DUT': 40,
# room humidity of external hum sensor added, Michael
'HUM_ROOM': 45,
# Air pressure of external sensor added, Michael
'AIR_PRESS_ROOM': 1000+10*i,
# measurement instrument temperature of external temp sensor added, Michael
'TEMP_MEAS_INSTR': 40-1.5*i,
# measurement instrument humidity of external hum sensor added, Michael
'HUM_MEAS_INSTR': 55,
'READBACK_TEMP_MEAS_INSTR': 50-2*i,
# measurement instrument humidity of external hum sensor added, Michael
'READBACK_HUM_MEAS_INSTR': 39
}
measurements.append(measurement)
data_frame = pd.DataFrame(measurements)
# plot of data frame with test data for actual step
m.draw(data_frame)
# plot of step number
print(str(i))
time.sleep(0.3)
print('I am done. ')
plt.ioff()
m.draw(data_frame, 'the.pdf')