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add influx calibration script, readme note.

Thomas Buck 2 years ago
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f685f39044
2 changed files with 77 additions and 0 deletions
  1. 13
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      README.md
  2. 64
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      influx/influx-calibration.py

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README.md View File

@@ -56,6 +56,19 @@ When an ESP is used, a webinterface and OTA updater will be included as well.
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 For the ESP32, you can upload a new firmware using a webbrowser.
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 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.
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+Writing events to InfluxDB is also supported.
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+Configure the server and database in 'include/config.h'.
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+It will store the valve-open duration (in seconds) with the following measurement types:
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+
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+    fertilizer
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+    plant
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+    calibrated_filling
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+    calibrated_watering
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+
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+Fertilizer shows each time a fertilizer pump has been running.
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+Plant shows when multiple plants have been watered at the same time.
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+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.
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+
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 ## License
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     Copyright (c) 2021 Thomas Buck <thomas@xythobuz.de>

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influx/influx-calibration.py View File

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

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