add influx calibration script, readme note.

README.md

@@ -56,6 +56,19 @@ When an ESP is used, a webinterface and OTA updater will be included as well.
 For the ESP32, you can upload a new firmware using a webbrowser.
 Simply use the link on the main page of the web ui, then upload the '.pio/build/esp32_main/firmware.bin' file from the project directory after building.
 
+Writing events to InfluxDB is also supported.
+Configure the server and database in 'include/config.h'.
+It will store the valve-open duration (in seconds) with the following measurement types:
+
+    fertilizer
+    plant
+    calibrated_filling
+    calibrated_watering
+
+Fertilizer shows each time a fertilizer pump has been running.
+Plant shows when multiple plants have been watered at the same time.
+Additionally, calibrated_filling can be used to determine the inlet flowrate and calibrated_watering can be used to determine each outlet flowrate, as long as the tank size is known.
+
 ## License
 
     Copyright (c) 2021 Thomas Buck <thomas@xythobuz.de>

influx/influx-calibration.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env python
+
+from influxdb import InfluxDBClient
+import matplotlib.pyplot as plt
+import matplotlib
+from datetime import datetime
+
+# config
+host = '10.23.42.14'
+port = 8086
+user = 'root'
+password = 'root'
+dbname = 'giessomat'
+
+# data
+client = InfluxDBClient(host, port, user, password, dbname)
+print("Querying DB " + dbname + " on " + host)
+result = client.query('SELECT "duration" FROM "calibrated_filling";')
+#print("Result: {0}".format(result))
+
+data = list(result.get_points())
+print("Got " + str(len(data)) + " datapoints")
+#print(data)
+
+times = ([datetime.strptime(d['time'], '%Y-%m-%dT%H:%M:%S.%fZ') for d in data])
+durations = ([d['duration'] for d in data])
+
+max_t = max(durations)
+min_t = min(durations)
+
+simple_average = min_t + ((max_t - min_t) / 2)
+average = 0
+for d in durations:
+    average += d
+average /= len(durations)
+
+sorted_durations = sorted(durations)
+median = sorted_durations[int(len(sorted_durations) / 2)]
+
+print("Min. Filling Time: " + str(min_t))
+print("Max. Filling Time: " + str(max_t))
+print("Average Filling Time:")
+print("  Simple = " + str(simple_average))
+print("  Average = " + str(average))
+print("  Median = " + str(median))
+
+# plot results
+plt.ioff()
+
+# ---------------------------
+
+fig, ax = plt.subplots()
+
+dates = matplotlib.dates.date2num(times)
+ax.plot_date(dates, durations, '-', label='filling')
+
+ax.set_xlabel('Time')
+ax.set_ylabel('Duration')
+ax.set_title('Filling Durations')
+ax.legend()
+
+# ---------------------------
+
+plt.show()