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enviro.py
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enviro.py
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#!/usr/bin/env python3
# Northcliff Environment Monitor from https://github.com/roscoe81/enviro-monitor
# Retrieved 2024-12-27, v8.2 Gen (SHA 73a8e02923434d8c7555ff91899c8f04f73aaf47)
import paho.mqtt.client as mqtt
import colorsys
import math
import json
import requests
import ST7735
import os
import time
from datetime import datetime, timedelta
from fonts.ttf import RobotoMedium as UserFont
import pytz
from pytz import timezone
from astral.geocoder import database, lookup, add_locations
from astral.sun import sun
try:
from smbus2 import SMBus
except ImportError:
from smbus import SMBus
try:
# Transitional fix for breaking change in LTR559
from ltr559 import LTR559
ltr559 = LTR559()
except ImportError:
import ltr559
from enviroplus import gas
from bme280 import BME280
from pms5003 import PMS5003, ReadTimeoutError, ChecksumMismatchError
from subprocess import check_output
from PIL import Image, ImageDraw, ImageFont, ImageFilter
try:
from smbus2 import SMBus
except ImportError:
from smbus import SMBus
import logging
monitor_version = "7.2 - Gen"
logging.basicConfig(
format='%(asctime)s.%(msecs)03d %(levelname)-8s %(message)s',
level=logging.INFO,
datefmt='%Y-%m-%d %H:%M:%S')
logging.info("""Northcliff_Environment_Monitor.py - Pimoroni Enviro+ with noise measurement (and optional SGP30) sensor capture and display.
Supports external sensor capture and Luftdaten, mqtt and Adafruit IO Updates
Disclaimer: The noise measurement is not to be used for accurate sound level measurements.
#Note: you'll need to register with Luftdaten at:
#https://meine.luftdaten.info/ and enter your Raspberry Pi
#serial number that's displayed on the Enviro plus LCD along
#with the other details before the data appears on the
#Luftdaten map.
#""")
print(monitor_version)
bus = SMBus(1)
# Create a BME280 instance
bme280 = BME280(i2c_dev=bus)
# Create an LCD instance
disp = ST7735.ST7735(
port=0,
cs=1,
dc=9,
backlight=12,
rotation=270,
spi_speed_hz=10000000
)
# Initialize display
disp.begin()
def retrieve_config():
try:
with open('config.json', 'r') as f:
parsed_config_parameters = json.loads(f.read())
print('Retrieved Config', parsed_config_parameters)
except IOError:
print('Config Retrieval Failed')
temp_offset = parsed_config_parameters['temp_offset']
altitude = parsed_config_parameters['altitude']
enable_display = parsed_config_parameters['enable_display'] # Enables the display and flags that the
# weather protection cover is used with different temp/hum compensation
enable_adafruit_io = parsed_config_parameters['enable_adafruit_io']
aio_user_name = parsed_config_parameters['aio_user_name']
aio_key = parsed_config_parameters['aio_key']
aio_feed_window = parsed_config_parameters['aio_feed_window']
aio_feed_sequence = parsed_config_parameters['aio_feed_sequence']
aio_household_prefix = parsed_config_parameters['aio_household_prefix']
aio_location_prefix = parsed_config_parameters['aio_location_prefix']
aio_package = parsed_config_parameters['aio_package']
enable_send_data_to_homemanager = parsed_config_parameters['enable_send_data_to_homemanager']
enable_receive_data_from_homemanager = parsed_config_parameters['enable_receive_data_from_homemanager']
enable_indoor_outdoor_functionality = parsed_config_parameters['enable_indoor_outdoor_functionality']
mqtt_broker_name = parsed_config_parameters['mqtt_broker_name']
enable_luftdaten = parsed_config_parameters['enable_luftdaten']
enable_climate_and_gas_logging = parsed_config_parameters['enable_climate_and_gas_logging']
enable_particle_sensor = parsed_config_parameters['enable_particle_sensor']
if 'enable_eco2_tvoc' in parsed_config_parameters:
enable_eco2_tvoc = parsed_config_parameters['enable_eco2_tvoc']
else:
enable_eco2_tvoc = False
if 'gas_daily_r0_calibration_hour' in parsed_config_parameters:
gas_daily_r0_calibration_hour = parsed_config_parameters['gas_daily_r0_calibration_hour']
else:
gas_daily_r0_calibration_hour = 3
if 'reset_gas_sensor_calibration' in parsed_config_parameters:
reset_gas_sensor_calibration = parsed_config_parameters['reset_gas_sensor_calibration']
else:
reset_gas_sensor_calibration = False
if 'mqtt_username' in parsed_config_parameters:
mqtt_username = parsed_config_parameters['mqtt_username']
else:
mqtt_username = None
if 'mqtt_password' in parsed_config_parameters:
mqtt_password = parsed_config_parameters['mqtt_password']
else:
mqtt_password = None
if 'outdoor_source_type' in parsed_config_parameters:
outdoor_source_type = parsed_config_parameters['outdoor_source_type'] # Can be "Enviro", "Luftdaten"
# or "Adafruit IO"
else:
outdoor_source_type = 'Enviro'
if 'outdoor_source_id' in parsed_config_parameters:
outdoor_source_id = parsed_config_parameters['outdoor_source_id'] # Sets Luftdaten or Adafruit IO Sensor IDs
# if using those sensors for outdoor readings, with the format: {"Climate": id, "PM": id} for Luftdaten or
# {"User Name": "<aio_user_name>", "Key": "<aio_key>", "Household Name": "<aio_household_name>"} for Adafruit IO
else:
outdoor_source_id = {}
if 'enable_noise' in parsed_config_parameters: # Enables Noise level sensing
enable_noise = parsed_config_parameters['enable_noise']
else:
enable_noise = False
if 'enable_luftdaten_noise' in parsed_config_parameters: # Enables Noise level uploads to Luftdaten. enable_noise must also be set to true for this to work
enable_luftdaten_noise = parsed_config_parameters['enable_luftdaten_noise']
else:
enable_luftdaten_noise = False
if 'disable_luftdaten_sensor_upload' in parsed_config_parameters: # Luftdaten currently only supports two sensors per node
# When enable_luftdaten_noise is true, this must be set to either 'Climate' to disable climate reading uploads or 'PM' to disable air particle reading uploads
# Set to 'None' when enable_luftdaten_noise is false
disable_luftdaten_sensor_upload = parsed_config_parameters['disable_luftdaten_sensor_upload']
else:
disable_luftdaten_sensor_upload = 'None'
# Correct any Luftdaten Noise misconfigurations
if not enable_noise:
disable_luftdaten_sensor_upload = 'None'
if enable_luftdaten_noise:
print('Noise sensor must be enabled in order to enable Luftdaten Noise. Disabling Luftdaten Noise')
enable_luftdaten_noise = False
else:
if enable_luftdaten_noise and disable_luftdaten_sensor_upload == 'None':
# Comment out next two lines once Luftdaten supports three sensors per node
print('Luftdaten currently only supports two sensors and three have been enabled. Disabling Luftdaten Climate uploads')
disable_luftdaten_sensor_upload = 'Climate'
pass
incoming_temp_hum_mqtt_topic = parsed_config_parameters['incoming_temp_hum_mqtt_topic']
incoming_temp_hum_mqtt_sensor_name = parsed_config_parameters['incoming_temp_hum_mqtt_sensor_name']
incoming_barometer_mqtt_topic = parsed_config_parameters['incoming_barometer_mqtt_topic']
incoming_barometer_sensor_id = parsed_config_parameters['incoming_barometer_sensor_id']
indoor_outdoor_function = parsed_config_parameters['indoor_outdoor_function']
mqtt_client_name = parsed_config_parameters['mqtt_client_name']
outdoor_mqtt_topic = parsed_config_parameters['outdoor_mqtt_topic']
indoor_mqtt_topic = parsed_config_parameters['indoor_mqtt_topic']
city_name = parsed_config_parameters['city_name']
time_zone = parsed_config_parameters['time_zone']
custom_locations = parsed_config_parameters['custom_locations']
return (temp_offset, altitude, enable_display, enable_adafruit_io, aio_user_name, aio_key, aio_feed_window,
aio_feed_sequence, aio_household_prefix, aio_location_prefix, aio_package, enable_send_data_to_homemanager,
enable_receive_data_from_homemanager, enable_indoor_outdoor_functionality,
mqtt_broker_name, mqtt_username, mqtt_password, outdoor_source_type, outdoor_source_id, enable_noise, enable_luftdaten,
enable_luftdaten_noise, disable_luftdaten_sensor_upload, enable_climate_and_gas_logging, enable_particle_sensor,
enable_eco2_tvoc, gas_daily_r0_calibration_hour, reset_gas_sensor_calibration, incoming_temp_hum_mqtt_topic,
incoming_temp_hum_mqtt_sensor_name, incoming_barometer_mqtt_topic, incoming_barometer_sensor_id,
indoor_outdoor_function, mqtt_client_name, outdoor_mqtt_topic, indoor_mqtt_topic, city_name, time_zone,
custom_locations)
# Config Setup
(temp_offset, altitude, enable_display, enable_adafruit_io, aio_user_name, aio_key, aio_feed_window, aio_feed_sequence,
aio_household_prefix, aio_location_prefix, aio_package, enable_send_data_to_homemanager,
enable_receive_data_from_homemanager, enable_indoor_outdoor_functionality, mqtt_broker_name,
mqtt_username, mqtt_password, outdoor_source_type, outdoor_source_id, enable_noise, enable_luftdaten,
enable_luftdaten_noise, disable_luftdaten_sensor_upload, enable_climate_and_gas_logging, enable_particle_sensor, enable_eco2_tvoc,
gas_daily_r0_calibration_hour, reset_gas_sensor_calibration, incoming_temp_hum_mqtt_topic, incoming_temp_hum_mqtt_sensor_name,
incoming_barometer_mqtt_topic, incoming_barometer_sensor_id, indoor_outdoor_function, mqtt_client_name,
outdoor_mqtt_topic, indoor_mqtt_topic, city_name, time_zone, custom_locations) = retrieve_config()
# Add to city database
db = database()
add_locations(custom_locations, db)
if enable_particle_sensor:
# Create a PMS5003 instance
pms5003 = PMS5003()
time.sleep(1)
if enable_noise:
import sounddevice as sd
import numpy as np
from numpy import pi, log10
from scipy.signal import zpk2tf, zpk2sos, freqs, sosfilt
from waveform_analysis.weighting_filters._filter_design import _zpkbilinear
def read_pm_values(luft_values, mqtt_values, own_data, own_disp_values):
if enable_particle_sensor:
try:
pm_values = pms5003.read()
#print('PM Values:', pm_values)
own_data["P2.5"][1] = pm_values.pm_ug_per_m3(2.5)
mqtt_values["P2.5"] = own_data["P2.5"][1]
own_disp_values["P2.5"] = own_disp_values["P2.5"][1:] + [[own_data["P2.5"][1], 1]]
luft_values["P2"] = str(mqtt_values["P2.5"])
own_data["P10"][1] = pm_values.pm_ug_per_m3(10)
mqtt_values["P10"] = own_data["P10"][1]
own_disp_values["P10"] = own_disp_values["P10"][1:] + [[own_data["P10"][1], 1]]
luft_values["P1"] = str(own_data["P10"][1])
own_data["P1"][1] = pm_values.pm_ug_per_m3(1.0)
mqtt_values["P1"] = own_data["P1"][1]
own_disp_values["P1"] = own_disp_values["P1"][1:] + [[own_data["P1"][1], 1]]
except (ReadTimeoutError, ChecksumMismatchError):
logging.info("Failed to read PMS5003")
display_error('Particle Sensor Error')
pms5003.reset()
pm_values = pms5003.read()
own_data["P2.5"][1] = pm_values.pm_ug_per_m3(2.5)
mqtt_values["P2.5"] = own_data["P2.5"][1]
own_disp_values["P2.5"] = own_disp_values["P2.5"][1:] + [[own_data["P2.5"][1], 1]]
luft_values["P2"] = str(mqtt_values["P2.5"])
own_data["P10"][1] = pm_values.pm_ug_per_m3(10)
mqtt_values["P10"] = own_data["P10"][1]
own_disp_values["P10"] = own_disp_values["P10"][1:] + [[own_data["P10"][1], 1]]
luft_values["P1"] = str(own_data["P10"][1])
own_data["P1"][1] = pm_values.pm_ug_per_m3(1.0)
mqtt_values["P1"] = own_data["P1"][1]
own_disp_values["P1"] = own_disp_values["P1"][1:] + [[own_data["P1"][1], 1]]
return(luft_values, mqtt_values, own_data, own_disp_values)
def read_eco2_tvoc_values(mqtt_values, own_data, own_disp_values):
eco2, tvoc = sgp30.command('measure_air_quality')
#print(eco2, tvoc)
own_data["CO2"][1] = eco2
mqtt_values["CO2"] = eco2
own_disp_values["CO2"] = own_disp_values["CO2"][1:] + [[own_data["CO2"][1], 1]]
own_data["VOC"][1] = tvoc
mqtt_values["VOC"] = tvoc
own_disp_values["VOC"] = own_disp_values["VOC"][1:] + [[own_data["VOC"][1], 1]]
return mqtt_values, own_data, own_disp_values
# Read gas and climate values from Home Manager and /or BME280
def read_climate_gas_values(luft_values, mqtt_values, own_data, maxi_temp, mini_temp, own_disp_values, gas_sensors_warm,
gas_calib_temp, gas_calib_hum, gas_calib_bar, altitude, enable_eco2_tvoc):
raw_temp, comp_temp = adjusted_temperature()
raw_hum, comp_hum = adjusted_humidity()
current_time = time.time()
use_external_temp_hum = False
use_external_barometer = False
if enable_receive_data_from_homemanager:
use_external_temp_hum, use_external_barometer = es.check_valid_readings(current_time)
if use_external_temp_hum == False:
print("Internal Temp/Hum Sensor")
luft_values["temperature"] = "{:.2f}".format(comp_temp)
own_data["Temp"][1] = round(comp_temp, 1)
luft_values["humidity"] = "{:.2f}".format(comp_hum)
own_data["Hum"][1] = round(comp_hum, 1)
else: # Use external temp/hum sensor but still capture raw temp and raw hum for gas compensation and logging
print("External Temp/Hum Sensor")
luft_values["temperature"] = es.temperature
own_data["Temp"][1] = float(luft_values["temperature"])
luft_values["humidity"] = es.humidity
own_data["Hum"][1] = float(luft_values["humidity"])
own_data["Dew"][1] = round(calculate_dewpoint(own_data["Temp"][1], own_data["Hum"][1]),1)
own_disp_values["Dew"] = own_disp_values["Dew"][1:] + [[own_data["Dew"][1], 1]]
mqtt_values["Dew"] = own_data["Dew"][1]
own_disp_values["Temp"] = own_disp_values["Temp"][1:] + [[own_data["Temp"][1], 1]]
mqtt_values["Temp"] = own_data["Temp"][1]
own_disp_values["Hum"] = own_disp_values["Hum"][1:] + [[own_data["Hum"][1], 1]]
mqtt_values["Hum"][0] = own_data["Hum"][1]
mqtt_values["Hum"][1] = domoticz_hum_map[describe_humidity(own_data["Hum"][1])]
if enable_eco2_tvoc: # Calculate and send the absolute humidity reading to the SGP30 for humidity compensation
absolute_hum = int(1000 * 216.7 * (raw_hum/100 * 6.112 * math.exp(17.62 * raw_temp / (243.12 + raw_temp)))
/(273.15 + raw_temp))
sgp30.command('set_humidity', [absolute_hum])
else:
absolute_hum = None
# Determine max and min temps
if first_climate_reading_done :
if maxi_temp is None:
maxi_temp = own_data["Temp"][1]
elif own_data["Temp"][1] > maxi_temp:
maxi_temp = own_data["Temp"][1]
else:
pass
if mini_temp is None:
mini_temp = own_data["Temp"][1]
elif own_data["Temp"][1] < mini_temp:
mini_temp = own_data["Temp"][1]
else:
pass
mqtt_values["Min Temp"] = mini_temp
mqtt_values["Max Temp"] = maxi_temp
raw_barometer = bme280.get_pressure()
if use_external_barometer == False:
print("Internal Barometer")
own_data["Bar"][1] = round(raw_barometer * barometer_altitude_comp_factor(altitude, own_data["Temp"][1]), 2)
own_disp_values["Bar"] = own_disp_values["Bar"][1:] + [[own_data["Bar"][1], 1]]
mqtt_values["Bar"][0] = own_data["Bar"][1]
luft_values["pressure"] = "{:.2f}".format(raw_barometer * 100) # Send raw air pressure to Lufdaten,
# since it does its own altitude air pressure compensation
print("Raw Bar:", round(raw_barometer, 2), "Comp Bar:", own_data["Bar"][1])
else:
print("External Barometer")
own_data["Bar"][1] = round(float(es.barometer), 2)
own_disp_values["Bar"] = own_disp_values["Bar"][1:] + [[own_data["Bar"][1], 1]]
mqtt_values["Bar"][0] = own_data["Bar"][1]
# Remove altitude compensation from external barometer because Lufdaten does its own altitude air pressure
# compensation
luft_values["pressure"] = "{:.2f}".format(float(es.barometer) / barometer_altitude_comp_factor (
altitude, own_data["Temp"][1]) * 100)
print("Luft Bar:", luft_values["pressure"], "Comp Bar:", own_data["Bar"][1])
red_in_ppm, oxi_in_ppm, nh3_in_ppm, comp_red_rs, comp_oxi_rs, comp_nh3_rs, raw_red_rs, raw_oxi_rs, raw_nh3_rs =\
read_gas_in_ppm(gas_calib_temp, gas_calib_hum, gas_calib_bar, raw_temp, raw_hum, raw_barometer, gas_sensors_warm)
own_data["Red"][1] = round(red_in_ppm, 2)
own_disp_values["Red"] = own_disp_values["Red"][1:] + [[own_data["Red"][1], 1]]
mqtt_values["Red"] = own_data["Red"][1]
own_data["Oxi"][1] = round(oxi_in_ppm, 2)
own_disp_values["Oxi"] = own_disp_values["Oxi"][1:] + [[own_data["Oxi"][1], 1]]
mqtt_values["Oxi"] = own_data["Oxi"][1]
own_data["NH3"][1] = round(nh3_in_ppm, 2)
own_disp_values["NH3"] = own_disp_values["NH3"][1:] + [[own_data["NH3"][1], 1]]
mqtt_values["NH3"] = own_data["NH3"][1]
mqtt_values["Gas Calibrated"] = gas_sensors_warm
proximity = ltr559.get_proximity()
if proximity < 500:
own_data["Lux"][1] = round(ltr559.get_lux(), 1)
else:
own_data["Lux"][1] = 1
own_disp_values["Lux"] = own_disp_values["Lux"][1:] + [[own_data["Lux"][1], 1]]
mqtt_values["Lux"] = own_data["Lux"][1]
return luft_values, mqtt_values, own_data, maxi_temp, mini_temp, own_disp_values, raw_red_rs, raw_oxi_rs,\
raw_nh3_rs, raw_temp, comp_temp, comp_hum, raw_hum, use_external_temp_hum, use_external_barometer,\
raw_barometer, absolute_hum
def barometer_altitude_comp_factor(alt, temp):
comp_factor = math.pow(1 - (0.0065 * altitude/(temp + 0.0065 * alt + 273.15)), -5.257)
return comp_factor
def read_raw_gas():
gas_data = gas.read_all()
raw_red_rs = round(gas_data.reducing, 0)
raw_oxi_rs = round(gas_data.oxidising, 0)
raw_nh3_rs = round(gas_data.nh3, 0)
return raw_red_rs, raw_oxi_rs, raw_nh3_rs
def read_gas_in_ppm(gas_calib_temp, gas_calib_hum, gas_calib_bar, raw_temp, raw_hum, raw_barometer, gas_sensors_warm):
if gas_sensors_warm:
comp_red_rs, comp_oxi_rs, comp_nh3_rs, raw_red_rs, raw_oxi_rs, raw_nh3_rs = comp_gas(gas_calib_temp,
gas_calib_hum,
gas_calib_bar,
raw_temp,
raw_hum, raw_barometer)
print("Reading Compensated Gas sensors after warmup completed")
else:
raw_red_rs, raw_oxi_rs, raw_nh3_rs = read_raw_gas()
comp_red_rs = raw_red_rs
comp_oxi_rs = raw_oxi_rs
comp_nh3_rs = raw_nh3_rs
print("Reading Raw Gas sensors before warmup completed")
print("Red Rs:", round(comp_red_rs, 0), "Oxi Rs:", round(comp_oxi_rs, 0), "NH3 Rs:", round(comp_nh3_rs, 0))
if comp_red_rs/red_r0 > 0:
red_ratio = comp_red_rs/red_r0
else:
red_ratio = 0.0001
if comp_oxi_rs/oxi_r0 > 0:
oxi_ratio = comp_oxi_rs/oxi_r0
else:
oxi_ratio = 0.0001
if comp_nh3_rs/nh3_r0 > 0:
nh3_ratio = comp_nh3_rs/nh3_r0
else:
nh3_ratio = 0.0001
red_in_ppm = math.pow(10, -1.25 * math.log10(red_ratio) + 0.64)
oxi_in_ppm = math.pow(10, math.log10(oxi_ratio) - 0.8129)
nh3_in_ppm = math.pow(10, -1.8 * math.log10(nh3_ratio) - 0.163)
return red_in_ppm, oxi_in_ppm, nh3_in_ppm, comp_red_rs, comp_oxi_rs, comp_nh3_rs, raw_red_rs, raw_oxi_rs, raw_nh3_rs
def comp_gas(gas_calib_temp, gas_calib_hum, gas_calib_bar, raw_temp, raw_hum, raw_barometer):
gas_data = gas.read_all()
gas_temp_diff = raw_temp - gas_calib_temp
gas_hum_diff = raw_hum - gas_calib_hum
gas_bar_diff = raw_barometer - gas_calib_bar
raw_red_rs = round(gas_data.reducing, 0)
comp_red_rs = round(raw_red_rs - (red_temp_comp_factor * raw_red_rs * gas_temp_diff +
red_hum_comp_factor * raw_red_rs * gas_hum_diff +
red_bar_comp_factor * raw_red_rs * gas_bar_diff), 0)
raw_oxi_rs = round(gas_data.oxidising, 0)
comp_oxi_rs = round(raw_oxi_rs - (oxi_temp_comp_factor * raw_oxi_rs * gas_temp_diff +
oxi_hum_comp_factor * raw_oxi_rs * gas_hum_diff +
oxi_bar_comp_factor * raw_oxi_rs * gas_bar_diff), 0)
raw_nh3_rs = round(gas_data.nh3, 0)
comp_nh3_rs = round(raw_nh3_rs - (nh3_temp_comp_factor * raw_nh3_rs * gas_temp_diff +
nh3_hum_comp_factor * raw_nh3_rs * gas_hum_diff +
nh3_bar_comp_factor * raw_nh3_rs * gas_bar_diff), 0)
print("Gas Compensation. Raw Red Rs:", raw_red_rs, "Comp Red Rs:", comp_red_rs, "Raw Oxi Rs:",
raw_oxi_rs, "Comp Oxi Rs:", comp_oxi_rs,
"Raw NH3 Rs:", raw_nh3_rs, "Comp NH3 Rs:", comp_nh3_rs)
return comp_red_rs, comp_oxi_rs, comp_nh3_rs, raw_red_rs, raw_oxi_rs, raw_nh3_rs
def adjusted_temperature():
raw_temp = bme280.get_temperature()
#comp_temp = comp_temp_slope * raw_temp + comp_temp_intercept
comp_temp = (comp_temp_cub_a * math.pow(raw_temp, 3) + comp_temp_cub_b * math.pow(raw_temp, 2) +
comp_temp_cub_c * raw_temp + comp_temp_cub_d)
return raw_temp, comp_temp
def adjusted_humidity():
raw_hum = bme280.get_humidity()
#comp_hum = comp_hum_slope * raw_hum + comp_hum_intercept
comp_hum = comp_hum_quad_a * math.pow(raw_hum, 2) + comp_hum_quad_b * raw_hum + comp_hum_quad_c
return raw_hum, min(100, comp_hum)
def calculate_dewpoint(dew_temp, dew_hum):
dewpoint = (237.7 * (math.log(dew_hum/100)+17.271*dew_temp/(237.7+dew_temp))/(17.271 - math.log(dew_hum/100) - 17.271*dew_temp/(237.7 + dew_temp)))
return dewpoint
def log_climate_and_gas(run_time, own_data, raw_red_rs, raw_oxi_rs, raw_nh3_rs, raw_temp, comp_temp, comp_hum,
raw_hum, use_external_temp_hum, use_external_barometer, raw_barometer):
# Used to log climate and gas data to create compensation algorithms
raw_temp = round(raw_temp, 2)
raw_hum = round(raw_hum, 2)
comp_temp = round(comp_temp, 2)
comp_hum = round(comp_hum, 2)
raw_barometer = round(raw_barometer, 1)
raw_red_rs = round(raw_red_rs, 0)
raw_oxi_rs = round(raw_oxi_rs, 0)
raw_nh3_rs = round(raw_nh3_rs, 0)
today = datetime.now()
time_stamp = today.strftime('%A %d %B %Y @ %H:%M:%S')
if use_external_temp_hum and use_external_barometer:
environment_log_data = {'Time': time_stamp, 'Run Time': run_time, 'Raw Temperature': raw_temp,
'Output Temp': comp_temp, 'Real Temperature': own_data["Temp"][1],
'Raw Humidity': raw_hum, 'Output Humidity': comp_hum,
'Real Humidity': own_data["Hum"][1], 'Real Bar': own_data["Bar"][1],
'Raw Bar': raw_barometer, 'Oxi': own_data["Oxi"][1], 'Red': own_data["Red"][1],
'NH3': own_data["NH3"][1], 'Raw OxiRS': raw_oxi_rs, 'Raw RedRS': raw_red_rs,
'Raw NH3RS': raw_nh3_rs}
elif use_external_temp_hum and not(use_external_barometer):
environment_log_data = {'Time': time_stamp, 'Run Time': run_time, 'Raw Temperature': raw_temp,
'Output Temp': comp_temp, 'Real Temperature': own_data["Temp"][1],
'Raw Humidity': raw_hum, 'Output Humidity': comp_hum,
'Real Humidity': own_data["Hum"][1], 'Output Bar': own_data["Bar"][1],
'Raw Bar': raw_barometer, 'Oxi': own_data["Oxi"][1], 'Red': own_data["Red"][1],
'NH3': own_data["NH3"][1], 'Raw OxiRS': raw_oxi_rs, 'Raw RedRS': raw_red_rs,
'Raw NH3RS': raw_nh3_rs}
elif not(use_external_temp_hum) and use_external_barometer:
environment_log_data = {'Time': time_stamp, 'Run Time': run_time, 'Raw Temperature': raw_temp,
'Output Temp': comp_temp, 'Raw Humidity': raw_hum, 'Output Humidity': comp_hum,
'Real Bar': own_data["Bar"][1], 'Raw Bar': raw_barometer, 'Oxi': own_data["Oxi"][1],
'Red': own_data["Red"][1], 'NH3': own_data["NH3"][1], 'Raw OxiRS': raw_oxi_rs,
'Raw RedRS': raw_red_rs, 'Raw NH3RS': raw_nh3_rs}
else:
environment_log_data = {'Time': time_stamp, 'Run Time': run_time, 'Raw Temperature': raw_temp,
'Output Temp': comp_temp, 'Raw Humidity': raw_hum, 'Output Humidity': comp_hum,
'Output Bar': own_data["Bar"][1], 'Raw Bar': raw_barometer, 'Oxi': own_data["Oxi"][1],
'Red': own_data["Red"][1], 'NH3': own_data["NH3"][1], 'Raw OxiRS': raw_oxi_rs,
'Raw RedRS': raw_red_rs, 'Raw NH3RS': raw_nh3_rs}
print('Logging Environment Data.', environment_log_data)
with open('<Your Environment Log File Location Here>', 'a') as f:
f.write(',\n' + json.dumps(environment_log_data))
# Calculate Air Quality Level
def max_aqi_level_factor(gas_sensors_warm, air_quality_data, air_quality_data_no_gas, data):
max_aqi_level = 0
max_aqi_factor = 'All'
max_aqi = [max_aqi_factor, max_aqi_level]
if gas_sensors_warm:
aqi_data = air_quality_data
else:
aqi_data = air_quality_data_no_gas
for aqi_factor in aqi_data:
aqi_factor_level = 0
thresholds = data[aqi_factor][2]
for level in range(len(thresholds)):
if data[aqi_factor][1] != None:
if data[aqi_factor][1] > thresholds[level]:
aqi_factor_level = level + 1
if aqi_factor_level > max_aqi[1]:
max_aqi = [aqi_factor, aqi_factor_level]
return max_aqi
# Get Raspberry Pi serial number to use as ID
def get_serial_number():
with open('/proc/cpuinfo', 'r') as f:
for line in f:
if line[0:6] == 'Serial':
return line.split(":")[1].strip()
# Check for Wi-Fi connection
def check_wifi():
if check_output(['hostname', '-I']):
return True
else:
return False
# Display Startup Message on LCD when using the SGP30 sensor
def display_startup(message):
text_colour = (255, 255, 255)
back_colour = (85, 15, 15)
error_message = "{}".format(message)
img = Image.new('RGB', (WIDTH, HEIGHT), color=(0, 0, 0))
draw = ImageDraw.Draw(img)
size_x, size_y = draw.textsize(message, mediumfont)
x = (WIDTH - size_x) / 2
y = (HEIGHT / 2) - (size_y / 2)
draw.rectangle((0, 0, 160, 80), back_colour)
draw.text((x, y), error_message, font=mediumfont, fill=text_colour)
disp.display(img)
# Display Error Message on LCD
def display_error(message):
text_colour = (255, 255, 255)
back_colour = (85, 15, 15)
error_message = "System Error\n{}".format(message)
img = Image.new('RGB', (WIDTH, HEIGHT), color=(0, 0, 0))
draw = ImageDraw.Draw(img)
size_x, size_y = draw.textsize(message, mediumfont)
x = (WIDTH - size_x) / 2
y = (HEIGHT / 2) - (size_y / 2)
draw.rectangle((0, 0, 160, 80), back_colour)
draw.text((x, y), error_message, font=mediumfont, fill=text_colour)
disp.display(img)
# Display the Raspberry Pi serial number and Adafruit IO Dashboard URL (if enabled) on a background colour
# based on the air quality level
def disabled_display(gas_sensors_warm, air_quality_data, air_quality_data_no_gas, data, palette, enable_adafruit_io,
aio_user_name, aio_household_prefix):
max_aqi = max_aqi_level_factor(gas_sensors_warm, air_quality_data, air_quality_data_no_gas, data)
back_colour = palette[max_aqi[1]]
text_colour = (0, 0, 0)
id = get_serial_number()
if enable_adafruit_io:
message = "{}\nhttp://io.adafruit.com\n/{}/dashboards\n/{}".format(id, aio_user_name, aio_household_prefix)
else:
message = "{}".format(id)
img = Image.new('RGB', (WIDTH, HEIGHT), color=(0, 0, 0))
draw = ImageDraw.Draw(img)
size_x, size_y = draw.textsize(message, font_smm)
x = (WIDTH - size_x) / 2
y = (HEIGHT / 2) - (size_y / 2)
draw.rectangle((0, 0, 160, 80), back_colour)
draw.text((x, y), message, font=font_smm, fill=text_colour)
disp.display(img)
# Display Raspberry Pi serial and Adafruit IO Dashboard URL (if enabled)
def display_status(enable_adafruit_io, aio_user_name, aio_household_prefix):
wifi_status = "connected" if check_wifi() else "disconnected"
text_colour = (255, 255, 255)
back_colour = (0, 170, 170) if check_wifi() else (85, 15, 15)
id = get_serial_number()
if enable_adafruit_io:
message = "{}\nhttp://io.adafruit.com\n/{}/dashboards\n/{}".format(id, aio_user_name, aio_household_prefix)
else:
message = "Northcliff\nEnviro Monitor\n{}\nwifi: {}".format(id, wifi_status)
img = Image.new('RGB', (WIDTH, HEIGHT), color=(0, 0, 0))
draw = ImageDraw.Draw(img)
size_x, size_y = draw.textsize(message, font_smm)
x = (WIDTH - size_x) / 2
y = (HEIGHT / 2) - (size_y / 2)
draw.rectangle((0, 0, 160, 80), back_colour)
draw.text((x, y), message, font=font_smm, fill=text_colour)
disp.display(img)
def send_data_to_aio(feed_key, data):
aio_json = {"value": data}
resp_error = False
reason = ''
response = ''
try:
response = requests.post(aio_url + '/feeds/' + feed_key + '/data',
headers={'X-AIO-Key': aio_key,
'Content-Type': 'application/json'},
data=json.dumps(aio_json), timeout=5)
status_code = response.status_code
except requests.exceptions.ConnectionError as e:
resp_error = True
reason = 'aio Connection Error'
print('aio Connection Error', e)
except requests.exceptions.Timeout as e:
resp_error = True
reason = 'aio Timeout Error'
print('aio Timeout Error', e)
except requests.exceptions.HTTPError as e:
resp_error = True
reason = 'aio HTTP Error'
print('aio HTTP Error', e)
except requests.exceptions.RequestException as e:
resp_error = True
reason = 'aio Request Error'
print('aio Request Error', e)
else:
if status_code == 429:
resp_error = True
reason = 'Throttling Error'
print('aio Throttling Error')
elif status_code >= 400:
resp_error = True
reason = 'Response Error: ' + str(response.status_code)
print('aio ', reason)
return not resp_error
def send_to_luftdaten(luft_values, id, enable_particle_sensor, enable_noise, luft_noise_values, disable_luftdaten_sensor_upload):
print("Sending Data to Luftdaten")
pm_send_attempt = False
climate_send_attempt = False
noise_send_attempt = False
all_responses_ok = True
resp_1_exception = False
resp_2_exception = False
resp_3_exception = False
if enable_particle_sensor and disable_luftdaten_sensor_upload != 'PM':
pm_values = dict(i for i in luft_values.items() if i[0].startswith("P"))
pm_send_attempt = True
try:
resp_1 = requests.post("https://api.luftdaten.info/v1/push-sensor-data/",
json={
"software_version": "northclff_enviro_monitor " + monitor_version,
"sensordatavalues": [{"value_type": key, "value": val} for
key, val in pm_values.items()]
},
headers={
"X-PIN": "1",
"X-Sensor": id,
"Content-Type": "application/json",
"cache-control": "no-cache"
},
timeout=5
)
except requests.exceptions.ConnectionError as e:
resp_1_exception = True
print('Luftdaten PM Connection Error', e)
except requests.exceptions.Timeout as e:
resp_1_exception = True
print('Luftdaten PM Timeout Error', e)
except requests.exceptions.RequestException as e:
resp_1_exception = True
print('Luftdaten PM Request Error', e)
if disable_luftdaten_sensor_upload != 'Climate':
temp_values = dict(i for i in luft_values.items() if not i[0].startswith("P"))
climate_send_attempt = True
try:
resp_2 = requests.post("https://api.luftdaten.info/v1/push-sensor-data/",
json={
"software_version": "northclff_enviro_monitor " + monitor_version,
"sensordatavalues": [{"value_type": key, "value": val} for
key, val in temp_values.items()]
},
headers={
"X-PIN": "11",
"X-Sensor": id,
"Content-Type": "application/json",
"cache-control": "no-cache"
},
timeout=5
)
except requests.exceptions.ConnectionError as e:
resp_2_exception = True
print('Luftdaten Climate Connection Error', e)
except requests.exceptions.Timeout as e:
resp_2_exception = True
print('Luftdaten Climate Timeout Error', e)
except requests.exceptions.RequestException as e:
resp_2_exception = True
print('Luftdaten Climate Request Error', e)
if enable_noise and enable_luftdaten_noise and luft_noise_values != []:
noise_values = [{"value_type": "noise_LAeq", "value": "{:.2f}".format(sum(luft_noise_values)/len(luft_noise_values))},
{"value_type": "noise_LA_min", "value": "{:.2f}".format(min(luft_noise_values))},
{"value_type": "noise_LA_max", "value": "{:.2f}".format(max(luft_noise_values))}]
print("Sending Luftdaten Noise Data", noise_values)
noise_send_attempt = True
try:
resp_3 = requests.post("https://api.luftdaten.info/v1/push-sensor-data/",
json={
"software_version": "northclff_enviro_monitor " + monitor_version,
"sensordatavalues": noise_values
},
headers={
"X-PIN": "15",
"X-Sensor": id,
"Content-Type": "application/json",
"cache-control": "no-cache"
},
timeout=5
)
except requests.exceptions.ConnectionError as e:
resp_3_exception = True
print('Luftdaten Noise Connection Error', e)
except requests.exceptions.Timeout as e:
resp_3_exception = True
print('Luftdaten Noise Timeout Error', e)
except requests.exceptions.RequestException as e:
resp_3_exception = True
print('Luftdaten Noise Request Error', e)
#print(resp_3)
if not (resp_1_exception or resp_2_exception or resp_3_exception):
if pm_send_attempt:
if not resp_1.ok:
all_responses_ok = False
if climate_send_attempt:
if not resp_2.ok:
all_responses_ok = False
if noise_send_attempt:
if not resp_3.ok:
all_responses_ok = False
else:
all_responses_ok = False
return all_responses_ok
def on_connect(client, userdata, flags, rc):
es.print_update('Northcliff Environment Monitor Connected with result code ' + str(rc))
if enable_receive_data_from_homemanager:
client.subscribe(incoming_temp_hum_mqtt_topic) # Subscribe to the topic for the external temp/hum data
client.subscribe(incoming_barometer_mqtt_topic) # Subscribe to the topic for the external barometer data
if enable_indoor_outdoor_functionality and indoor_outdoor_function == 'Indoor' and outdoor_source_type == "Enviro":
client.subscribe(outdoor_mqtt_topic)
def on_message(client, userdata, msg):
decoded_payload = str(msg.payload.decode("utf-8"))
parsed_json = json.loads(decoded_payload)
# Identify external temp/hum sensor
if msg.topic == incoming_temp_hum_mqtt_topic and parsed_json['name'] == incoming_temp_hum_mqtt_sensor_name:
es.capture_temp_humidity(parsed_json)
# Identify external barometer
if msg.topic == incoming_barometer_mqtt_topic and parsed_json['idx'] == incoming_barometer_sensor_id:
es.capture_barometer(parsed_json['svalue'])
if enable_indoor_outdoor_functionality and indoor_outdoor_function == 'Indoor' and msg.topic == outdoor_mqtt_topic:
capture_outdoor_data(parsed_json)
def capture_outdoor_data(parsed_json):
global captured_outdoor_data
captured_outdoor_data = parsed_json
# Displays graphed data and text on the 0.96" LCD
def display_graphed_data(location, disp_values, variable, data, WIDTH):
# Scale the received disp_values for the variable between 0 and 1
#print ("Display Values", disp_values)
received_disp_values = [disp_values[variable][v][0]*disp_values[variable][v][1]
for v in range(len(disp_values[variable]))]
graph_range = [(v - min(received_disp_values)) / (max(received_disp_values) - min(received_disp_values))
if ((max(received_disp_values) - min(received_disp_values)) != 0)
else 0 for v in received_disp_values]
# Format the variable name and value
if variable == "Oxi":
message = "{} {}: {:.2f} {}".format(location, variable[:4], data[1], data[0])
elif variable == "Bar":
message = "{}: {:.1f} {}".format(variable[:4], data[1], data[0])
elif (variable[:1] == "P" or variable == "Red" or variable == "NH3" or variable == "CO2" or variable == "VOC" or
variable == "Hum" or variable == "Lux"):
message = "{} {}: {:.0f} {}".format(location, variable[:4], round(data[1], 0), data[0])
else:
message = "{} {}: {:.1f} {}".format(location, variable[:4], data[1], data[0])
#logging.info(message)
draw.rectangle((0, 0, WIDTH, HEIGHT), (255, 255, 255))
# Determine the backgound colour for received data, based on level thresholds. Black for data not received.
for i in range(len(disp_values[variable])):
if disp_values[variable][i][1] == 1:
lim = data[2]
rgb = palette[0]
for j in range(len(lim)):
if disp_values[variable][i][0] > lim[j]:
rgb = palette[j+1]
else:
rgb = (0,0,0)
# Draw a 2-pixel wide rectangle of colour based on reading levels relative to level thresholds
draw.rectangle((i*2, top_pos, i*2+2, HEIGHT), rgb)
# Draw a 2 pixel by 2 pixel line graph in black based on the reading levels
line_y = (HEIGHT-2) - ((top_pos + 1) + (graph_range[i] * ((HEIGHT-2) - (top_pos + 1)))) + (top_pos + 1)
draw.rectangle((i*2, line_y, i*2+2, line_y+2), (0, 0, 0))
# Write the text at the top in black
draw.text((0, 0), message, font=font_ml, fill=(0, 0, 0))
disp.display(img)
# Displays the weather forecast on the 0.96" LCD
def display_forecast(valid_barometer_history, forecast, barometer_available_time, barometer, barometer_change):
text_colour = (255, 255, 255)
back_colour = (0, 0, 0)
if valid_barometer_history:
message = "Barometer {:.0f} hPa\n3Hr Change {:.0f} hPa\n{}".format(round(barometer, 0),
round(barometer_change, 0), forecast)
else:
minutes_to_forecast = (barometer_available_time - time.time()) / 60
if minutes_to_forecast >= 2:
message = "WEATHER FORECAST\nReady in {:.0f} minutes".format(minutes_to_forecast)
elif minutes_to_forecast > 0 and minutes_to_forecast < 2:
message = "WEATHER FORECAST\nReady in a minute"
else:
message = "WEATHER FORECAST\nPreparing Summary\nPlease Wait..."
img = Image.new('RGB', (WIDTH, HEIGHT), color=(0, 0, 0))
draw = ImageDraw.Draw(img)
size_x, size_y = draw.textsize(message, mediumfont)
x = (WIDTH - size_x) / 2
y = (HEIGHT / 2) - (size_y / 2)
draw.rectangle((0, 0, 160, 80), back_colour)
draw.text((x, y), message, font=mediumfont, fill=text_colour)
disp.display(img)
# Displays all the air quality text on the 0.96" LCD
def display_all_aq(location, data, data_in_display_all_aq, enable_eco2_tvoc):
draw.rectangle((0, 0, WIDTH, HEIGHT), (0, 0, 0))
column_count = 2
if enable_eco2_tvoc:
font=font_smm
else:
font=font_ml
draw.text((2, 2), location + ' AIR QUALITY', font=font, fill=(255, 255, 255))
row_count = round((len(data_in_display_all_aq) / column_count), 0)
for i in data_in_display_all_aq:
data_value = data[i][1]
unit = data[i][0]
column = int(data[i][3] / row_count)
row = data[i][3] % row_count
x = x_offset + ((WIDTH/column_count) * column)
y = y_offset + ((HEIGHT/(row_count + 1) * (row +1)))
if (i == "CO2" or i == "VOC") and location == "OUT" or data_value == None:
message = "{}: N/A".format(i) # No CO2 or TVOC data comes from an outdoor unit
# and no gas or P1 readings when Luftdaten is the source of outdoor readings
# (used on display of indoor unit when displaying outdoor readings)
elif i == "Oxi" and data_value != None:
message = "{}: {:.2f}".format(i, data_value)
else:
message = "{}: {:.0f}".format(i, round(data_value, 0))
lim = data[i][2]
rgb = palette[0]
if data_value != None:
for j in range(len(lim)):
if data_value > lim[j]:
rgb = palette[j+1]
draw.text((x, y), message, font=font, fill=rgb)
disp.display(img)
def display_noise(location, selected_display_mode, noise_level, noise_max, noise_max_datetime, display_changed, last_page, noise_values, freq_values):
draw.rectangle((0, 0, WIDTH, HEIGHT), noise_back_colour)
if noise_level<=noise_thresholds[0]:
message_colour = (0, 255, 0)
elif noise_thresholds[0]<noise_level<=noise_thresholds[1]:
message_colour=(255, 255, 0)
else:
message_colour = (255, 0, 0)
if selected_display_mode == "Noise Reading":
draw.text((5,0), location + " Noise Level", font=noise_smallfont, fill=message_colour)
draw.text((5, 32), f"{noise_level:.1f} dB(A)", font=noise_largefont, fill=message_colour)
disp.display(img)
elif selected_display_mode == "Noise Level":
if noise_max<=noise_thresholds[0]:
max_graph_colour = (0, 255, 0)
elif noise_thresholds[0]<noise_max<=noise_thresholds[1]:
max_graph_colour = (255, 255, 0)
else:
max_graph_colour = (255, 0, 0)
for i in range(len(noise_values)):
if noise_values[i][1] == 1:
if noise_values[i][0]<=noise_thresholds[0]:
graph_colour = (0, 255, 0)
elif noise_thresholds[0]<noise_max<=noise_thresholds[1]:
graph_colour=(255, 255, 0)
else:
graph_colour = (255, 0, 0)
draw.line((5+i*6, HEIGHT, 5+i*6, HEIGHT - (noise_values[i][0]-35)), fill=graph_colour, width=5)
draw.text((5,0), location + " Noise Level", font=noise_smallfont, fill=message_colour)
if noise_max != 0 and (time.time() - last_page) > 2:
draw.line((0, HEIGHT - (noise_max-35), WIDTH, HEIGHT - (noise_max-35)), fill=max_graph_colour, width=1) #Display Max Line
if noise_max > 85:
text_height = HEIGHT - (noise_max-37)
else:
text_height = HEIGHT - (noise_max-20)
draw.text((0, text_height), f"Max {noise_max:.1f} dB {noise_max_datetime['Time']} {noise_max_datetime['Date']}", font=noise_vsmallfont, fill=max_graph_colour)
disp.display(img)
else:
for i in range(len(freq_values)):
if freq_values[i][3] == 1:
draw.line((15+i*20, HEIGHT, 15+i*20, HEIGHT - (freq_values[i][2]*0.747-45)), fill=(0, 0, 255), width=5)
draw.line((10+i*20, HEIGHT, 10+i*20, HEIGHT - (freq_values[i][1]*0.844-59)), fill=(0, 255, 0), width=5)
draw.line((5+i*20, HEIGHT, 5+i*20, HEIGHT - (freq_values[i][0]*1.14-103)), fill=(255, 0, 0), width=5)
draw.text((0,0), location + " Noise Bands", font=noise_smallfont, fill=message_colour)
disp.display(img)
def display_results(start_current_display, current_display_is_own, display_modes,
indoor_outdoor_display_duration, own_data, data_in_display_all_aq, outdoor_data,
outdoor_reading_captured, own_disp_values, outdoor_disp_values, delay, last_page, mode,
WIDTH, valid_barometer_history, forecast, barometer_available_time, barometer_change,
barometer_trend, icon_forecast, maxi_temp, mini_temp, air_quality_data,
air_quality_data_no_gas, gas_sensors_warm, outdoor_gas_sensors_warm, enable_display,
palette, enable_adafruit_io, aio_user_name, aio_household_prefix, enable_eco2_tvoc,
outdoor_source_type, own_noise_level, own_noise_max, own_noise_max_datetime,
own_noise_values, own_noise_freq_values, outdoor_noise_level, outdoor_noise_max,
outdoor_noise_max_datetime, outdoor_noise_values, outdoor_noise_freq_values):
# Allow for display selection if display is enabled,
# else only display the serial number on a background colour based on max_aqi
if enable_display:
proximity = ltr559.get_proximity()
# If the proximity crosses the threshold, toggle the mode
if proximity > 1500 and time.time() - last_page > delay:
mode += 1
mode %= len(display_modes)
print('Mode', mode)
last_page = time.time()
display_changed = True
else:
display_changed = False
selected_display_mode = display_modes[mode]
if enable_indoor_outdoor_functionality and indoor_outdoor_function == 'Indoor':
if outdoor_reading_captured:
if ((time.time() - start_current_display) > indoor_outdoor_display_duration):
current_display_is_own = not current_display_is_own
start_current_display = time.time()
else:
current_display_is_own = True
if selected_display_mode in own_data:
if current_display_is_own and indoor_outdoor_function == 'Indoor' or selected_display_mode == "Bar":
display_graphed_data('IN', own_disp_values, selected_display_mode, own_data[selected_display_mode],
WIDTH)
elif current_display_is_own and indoor_outdoor_function == 'Outdoor':
display_graphed_data('OUT', own_disp_values, selected_display_mode, own_data[selected_display_mode],
WIDTH)
elif not current_display_is_own and (indoor_outdoor_function == 'Indoor'
and (selected_display_mode == "CO2"
or selected_display_mode == "VOC"
or outdoor_source_type == "Luftdaten"
and (selected_display_mode == "Oxi"
or selected_display_mode == "Red"
or selected_display_mode == "NH3"
or selected_display_mode == "P1"
or selected_display_mode == "Lux")
or outdoor_source_type == "Adafruit IO"
and selected_display_mode == "Lux")):
# No outdoor gas, P1, Lux graphs when outdoor source is Luftdaten.
# No outdoor Lux graphs when the outdoor source is Adafruit IO
# and no outdoor CO2 or TVOC graphs,
# so always display indoor graph
display_graphed_data('IN', own_disp_values, selected_display_mode, own_data[selected_display_mode],
WIDTH)
else:
display_graphed_data('OUT', outdoor_disp_values, selected_display_mode,
outdoor_data[selected_display_mode], WIDTH)
elif selected_display_mode == "Forecast":
display_forecast(valid_barometer_history, forecast, barometer_available_time, own_data["Bar"][1],
barometer_change)
elif selected_display_mode == "Status":
display_status(enable_adafruit_io, aio_user_name, aio_household_prefix)
elif selected_display_mode == "All Air":
# Display everything on one screen
if current_display_is_own and indoor_outdoor_function == 'Indoor':
display_all_aq('IN', own_data, data_in_display_all_aq, enable_eco2_tvoc)
elif current_display_is_own and indoor_outdoor_function == 'Outdoor':
display_all_aq('OUT', own_data, data_in_display_all_aq, enable_eco2_tvoc)
else:
display_all_aq('OUT', outdoor_data, data_in_display_all_aq, enable_eco2_tvoc)
elif selected_display_mode == "Icon Weather":
# Display icon weather/aqi
if current_display_is_own and indoor_outdoor_function == 'Indoor':
display_icon_weather_aqi('IN', own_data, barometer_trend, icon_forecast, maxi_temp, mini_temp,
air_quality_data,
air_quality_data_no_gas, icon_air_quality_levels, gas_sensors_warm, own_noise_level, own_noise_max)
elif current_display_is_own and indoor_outdoor_function == 'Outdoor':
display_icon_weather_aqi('OUT', own_data, barometer_trend, icon_forecast, maxi_temp, mini_temp,
air_quality_data,
air_quality_data_no_gas, icon_air_quality_levels, gas_sensors_warm, own_noise_level, own_noise_max)
else:
display_icon_weather_aqi('OUT', outdoor_data, barometer_trend, icon_forecast, outdoor_maxi_temp,
outdoor_mini_temp,
air_quality_data, air_quality_data_no_gas, icon_air_quality_levels,
outdoor_gas_sensors_warm, outdoor_noise_level, outdoor_noise_max)
elif "Noise" in selected_display_mode:
if selected_display_mode == "Noise Level" and display_changed:
own_noise_max = 0 # Reset Max Noise Reading when first entering "Noise Level Mode"
if current_display_is_own:
display_noise(indoor_outdoor_function, selected_display_mode, own_noise_level, own_noise_max, own_noise_max_datetime, display_changed, last_page, own_noise_values, own_noise_freq_values)
elif not current_display_is_own and indoor_outdoor_function == 'Indoor' and outdoor_noise_level == 0: # Don't display outdoor noise levels on indoor unit when there are no outdoor noise readings
display_noise("Indoor", selected_display_mode, own_noise_level, own_noise_max, own_noise_max_datetime, display_changed, last_page, own_noise_values, own_noise_freq_values)
else:
display_noise("Outdoor", selected_display_mode, outdoor_noise_level, outdoor_noise_max, outdoor_noise_max_datetime, display_changed, last_page, outdoor_noise_values, outdoor_noise_freq_values)
else:
pass
else:
disabled_display(gas_sensors_warm, air_quality_data, air_quality_data_no_gas, own_data, palette,
enable_adafruit_io, aio_user_name, aio_household_prefix)
return last_page, mode, start_current_display, current_display_is_own, own_noise_max
class ExternalSensors(object): # Handles the external temp/hum/bar sensors
def __init__(self):
self.barometer_update_time = 0
self.temp_humidity_update_time = 0
#self.print_update('Instantiated External Sensors')