plot.py

#!/usr/bin/env python3

# 1. Setup a device with a INA219 module connected and uplinking telemetry to a broker.
# 2. Acquire telemetry data
#    mosquitto_sub -h mqtt.server.net -t "msh/2/json/#" >mqtt-json.log
# 3. Plot a graph
#    plot.py mqtt-json.log graph.png "title"

import sys
import json
import pandas as pd
import matplotlib.pyplot as pyplot
import matplotlib.dates as mdates
import matplotlib.ticker as ticker

input_filename = sys.argv[1]
output_filename = sys.argv[2]
title = sys.argv[3]

def load_telemetry_data(filename):
    ina219_data = []
    espadc_data = []
    with open(filename) as file:
        for line in file:
            j = json.loads(line)
            t = j.get("timestamp")
            p = j.get("payload")
            if t is None or p is None:
                continue
            voltage = p.get("voltage")
            voltage_ch3 = p.get("voltage_ch3")
            current_ch3 = p.get("current_ch3")
            if not voltage is None and voltage > 2.0:
                espadc_data.append([t, voltage])
            elif not (voltage_ch3 is None or current_ch3 is None):
                ina219_data.append([t, voltage_ch3, current_ch3])
    ina219_df = pd.DataFrame(ina219_data, columns=["timestamp", "voltage", "current"])
    espadc_df = pd.DataFrame(espadc_data, columns=["timestamp", "voltage"])
    return ina219_df, espadc_df

ina219_df, espadc_df = load_telemetry_data(input_filename)

ina219_df.set_index(pd.to_datetime(ina219_df["timestamp"], unit="s"), inplace=True)
ina219_current_df = ina219_df[["current"]].resample("1min").ffill()
ina219_df = ina219_df[["voltage"]].resample("1min").ffill()

espadc_df.set_index(pd.to_datetime(espadc_df["timestamp"], unit="s"), inplace=True)
espadc_df = espadc_df[["voltage"]].resample("1min").ffill()

deviation_df = (espadc_df - ina219_df).abs() * 1000

pyplot.rcParams['lines.linewidth'] = 1
fig, ax1 = pyplot.subplots()
fig.set_figwidth(15)
fig.set_figheight(7)

ax1.grid(True, linestyle="dashed")
ax1.set_title(title)
ax1.set_xlabel("Time")
ax1.set_ylabel("Battery Voltage, V")
espadc = ax1.plot(espadc_df, color="blue",  label="espadc, V")
ina219 = ax1.plot(ina219_df, color="green", label="ina219, V")
ax1.xaxis.set_major_locator(mdates.MinuteLocator(byminute=[0]))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
ax1.yaxis.set_major_locator(ticker.MultipleLocator(base=0.05))

ax2 = ax1.twinx()
ax2.set_ylabel("Voltage Deviation =|espadc—ina219|, mV")
ax2.set_ylim((0, 250))
deviation_label = "deviation, mV\nmax {0}mV\navg {1}mV\nmin {2}mV".format(
    round(deviation_df.max().iloc[0]),
    round(deviation_df.mean().iloc[0]),
    round(deviation_df.min().iloc[0]))
deviation = ax2.plot(deviation_df, color="black", label=deviation_label)

ax3 = ax1.twinx()
ax3.set_ylim((0, 500))
ax3.yaxis.set_major_locator(pyplot.NullLocator())
current_label = "current, mA\n%dmA avg" % round(ina219_current_df.mean().iloc[0])
current = ax3.plot(ina219_current_df, color="red", label=current_label)

lines = espadc + ina219 + deviation + current
labels = [l.get_label() for l in lines]
ax2.legend(lines, labels, loc="upper right")

pyplot.savefig(output_filename)