Aug-22-2019, 04:56 PM
Hello,
I would like to save my sensor data from the bme680 into a json or csv file. For the last section I wrote myself. I've been trying to learn python for a few months now. Perhaps you can help me. I do not really know what I have to use for 'numbers'.
BME680 Example https://github.com/pimoroni/bme680-python
Many thanks
I would like to save my sensor data from the bme680 into a json or csv file. For the last section I wrote myself. I've been trying to learn python for a few months now. Perhaps you can help me. I do not really know what I have to use for 'numbers'.
BME680 Example https://github.com/pimoroni/bme680-python
Many thanks
#!/usr/bin/env python
import bme680
import time
import json
print("""indoor-air-quality.py - Estimates indoor air quality.
Runs the sensor for a burn-in period, then uses a
combination of relative humidity and gas resistance
to estimate indoor air quality as a percentage.
Press Ctrl+C to exit!
""")
try:
sensor = bme680.BME680(bme680.I2C_ADDR_PRIMARY)
except IOError:
sensor = bme680.BME680(bme680.I2C_ADDR_SECONDARY)
# These oversampling settings can be tweaked to
# change the balance between accuracy and noise in
# the data.
sensor.set_humidity_oversample(bme680.OS_2X)
sensor.set_pressure_oversample(bme680.OS_4X)
sensor.set_temperature_oversample(bme680.OS_8X)
sensor.set_filter(bme680.FILTER_SIZE_3)
sensor.set_gas_status(bme680.ENABLE_GAS_MEAS)
sensor.set_gas_heater_temperature(320)
sensor.set_gas_heater_duration(150)
sensor.select_gas_heater_profile(0)
# start_time and curr_time ensure that the
# burn_in_time (in seconds) is kept track of.
start_time = time.time()
curr_time = time.time()
burn_in_time = 300
burn_in_data = []
try:
# Collect gas resistance burn-in values, then use the average
# of the last 50 values to set the upper limit for calculating
# gas_baseline.
print('Collecting gas resistance burn-in data for 5 mins\n')
while curr_time - start_time < burn_in_time:
curr_time = time.time()
if sensor.get_sensor_data() and sensor.data.heat_stable:
gas = sensor.data.gas_resistance
burn_in_data.append(gas)
print('Gas: {0} Ohms'.format(gas))
time.sleep(10)
gas_baseline = sum(burn_in_data[-50:]) / 50.0
# Set the humidity baseline to 40%, an optimal indoor humidity.
hum_baseline = 40.0
# This sets the balance between humidity and gas reading in the
# calculation of air_quality_score (25:75, humidity:gas)
hum_weighting = 0.25
print('Gas baseline: {0} Ohms, humidity baseline: {1:.2f} %RH\n'.format(
gas_baseline,
hum_baseline))
while True:
if sensor.get_sensor_data() and sensor.data.heat_stable:
gas = sensor.data.gas_resistance
gas_offset = gas_baseline - gas
hum = sensor.data.humidity
hum_offset = hum - hum_baseline
# Calculate hum_score as the distance from the hum_baseline.
if hum_offset > 0:
hum_score = (100 - hum_baseline - hum_offset)
hum_score /= (100 - hum_baseline)
hum_score *= (hum_weighting * 100)
else:
hum_score = (hum_baseline + hum_offset)
hum_score /= hum_baseline
hum_score *= (hum_weighting * 100)
# Calculate gas_score as the distance from the gas_baseline.
if gas_offset > 0:
gas_score = (gas / gas_baseline)
gas_score *= (100 - (hum_weighting * 100))
else:
gas_score = 100 - (hum_weighting * 100)
# Calculate air_quality_score.
air_quality_score = hum_score + gas_score
print('Gas: {0:.2f} Ohms,humidity: {1:.2f} %RH,air quality: {2:.2f}'.format(
gas,
hum,
air_quality_score))
time.sleep(10)
#import json
numbers = "Gas: {0:.2f} Ohms,humidity: {1:.2f} %RH,air quality: {2:.2f}" **think** **think** **think**
filename = 'home/pi/bme680/log.json'
try:
with open(filename, 'w', encoding='utf8') as f_obj:
json.dump(numbers, f_obj)
except:
msg= "Sorry, the file " + filename + " does not exist."
print(msg)
except KeyboardInterrupt:
pass
