update
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182
loop/3_NPM/get_data_closest_pair.py
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182
loop/3_NPM/get_data_closest_pair.py
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import serial
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import json
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import time
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import math
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# Record the start time of the script
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start_time = time.time()
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#get config
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def load_config(config_file):
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try:
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with open(config_file, 'r') as file:
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config_data = json.load(file)
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return config_data
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except Exception as e:
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print(f"Error loading config file: {e}")
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return {}
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# Define the config file path
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config_file = '/var/www/nebuleair_pro_4g/config.json'
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# Load the configuration data
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config = load_config(config_file)
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# Access the shared variables
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need_to_log = config.get('loop_log', False)
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# Initialize serial ports for the three sensors
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ser3 = serial.Serial(
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port='/dev/ttyAMA3',
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baudrate=115200,
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parity=serial.PARITY_EVEN,
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stopbits=serial.STOPBITS_ONE,
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bytesize=serial.EIGHTBITS,
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timeout=1
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)
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ser4 = serial.Serial(
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port='/dev/ttyAMA4',
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baudrate=115200,
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parity=serial.PARITY_EVEN,
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stopbits=serial.STOPBITS_ONE,
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bytesize=serial.EIGHTBITS,
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timeout=1
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)
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ser5 = serial.Serial(
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port='/dev/ttyAMA5',
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baudrate=115200,
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parity=serial.PARITY_EVEN,
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stopbits=serial.STOPBITS_ONE,
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bytesize=serial.EIGHTBITS,
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timeout=1
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)
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# Function to read and parse sensor data
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def read_sensor_data(ser, sonde_id):
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try:
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# Send the command to request data (e.g., data for 60 seconds)
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ser.write(b'\x81\x12\x6D')
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# Read the response
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byte_data = ser.readline()
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# Extract the state byte and PM data from the response
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PM1 = int.from_bytes(byte_data[9:11], byteorder='big') / 10
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PM25 = int.from_bytes(byte_data[11:13], byteorder='big') / 10
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PM10 = int.from_bytes(byte_data[13:15], byteorder='big') / 10
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# Create a dictionary with the parsed data
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data = {
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'sondeID': sonde_id,
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'PM1': PM1,
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'PM25': PM25,
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'PM10': PM10
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}
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return data
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except Exception as e:
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print(f"Error reading from sensor {sonde_id}: {e}")
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return None
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# Function to calculate the Euclidean distance between two sensor readings
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def calculate_distance(sensor1, sensor2):
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PM1_diff = sensor1['PM1'] - sensor2['PM1']
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PM25_diff = sensor1['PM25'] - sensor2['PM25']
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PM10_diff = sensor1['PM10'] - sensor2['PM10']
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return math.sqrt(PM1_diff**2 + PM25_diff**2 + PM10_diff**2)
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# Function to select the closest pair of sensors and average their data
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def average_closest_pair(data):
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# List of sensor names and their data
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sensors = list(data.items())
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# Variable to keep track of the smallest distance and corresponding pair
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min_distance = float('inf')
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closest_pair = None
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# Compare each pair of sensors to find the closest one
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for i in range(len(sensors)):
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for j in range(i + 1, len(sensors)):
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sensor1 = sensors[i][1]
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sensor2 = sensors[j][1]
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# Calculate the distance between the two sensors
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distance = calculate_distance(sensor1, sensor2)
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# Update the closest pair if a smaller distance is found
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if distance < min_distance:
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min_distance = distance
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closest_pair = (sensor1, sensor2)
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# If a closest pair is found, average their values
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if closest_pair:
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sensor1, sensor2 = closest_pair
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averaged_data = {
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'sondeID': f"Average_{sensor1['sondeID']}_{sensor2['sondeID']}",
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'PM1': round((sensor1['PM1'] + sensor2['PM1']) / 2, 2),
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'PM25': round((sensor1['PM25'] + sensor2['PM25']) / 2, 2),
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'PM10': round((sensor1['PM10'] + sensor2['PM10']) / 2, 2)
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}
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return averaged_data
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else:
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return None
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# Function to create a JSON object with all sensor data
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def collect_all_sensor_data():
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all_data = {}
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# Read data from each sensor and add to the all_data dictionary
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sensor_data_3 = read_sensor_data(ser3, 'USB2')
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sensor_data_4 = read_sensor_data(ser4, 'USB3')
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sensor_data_5 = read_sensor_data(ser5, 'USB4')
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# Store the data for each sensor in the dictionary
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if sensor_data_3:
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all_data['sensor_3'] = sensor_data_3
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if sensor_data_4:
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all_data['sensor_4'] = sensor_data_4
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if sensor_data_5:
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all_data['sensor_5'] = sensor_data_5
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return all_data
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# Main script to run once and average data for the closest sensors
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if __name__ == "__main__":
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try:
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# Collect data from all sensors
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data = collect_all_sensor_data()
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if need_to_log:
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print("Getting Data from all sensors:")
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print(data)
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# Average the closest pair of sensors
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averaged_data = average_closest_pair(data)
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if need_to_log:
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print("Average the closest pair of sensors:")
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print(averaged_data)
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if averaged_data:
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# Convert the averaged data to JSON
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json_data = json.dumps(averaged_data, indent=4)
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# Define the output file path
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output_file = "/var/www/nebuleair_pro_4g/loop/data.json" # Change this to your desired file path
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# Write the JSON data to the file
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with open(output_file, 'w') as file:
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file.write(json_data)
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if need_to_log:
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print(f"Data successfully written to {output_file}")
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else:
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print("No closest pair found to average.")
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# Calculate and print the elapsed time
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elapsed_time = time.time() - start_time
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if need_to_log:
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print(f"Elapsed time: {elapsed_time:.2f} seconds")
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print("-----------------")
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except Exception as e:
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print(f"Error: {e}")
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