Read-Sensor-Resistances/read_arduino.py

"""
 Read raw data from Arduino and then converted into actual resistance using parameters provided from top level
"""
from datetime import datetime
import serial, time, json
import serial.tools.list_ports
import numpy as np

# constant settings
SENSORS_MAX = 4  # maximum sensor ports

def read():
    baud = 19200
    settings = json.load(open('settings.json', 'r'))
    resolution = settings["resolution"]  # this is not in use, but just in case if we decide to switch back to analogRead() instead of ESP32's analogReadMiliVolts() on the firmware
    v_in = settings["v_in"]
    refRes = np.array(settings["refRes"])
    sensor_ports = np.array(settings["sensor_ports"])  # ports that sensor(s) are connected to
    file_name = settings["file_name"]
    port = settings["port"]
    delay = settings["delay"]

    if np.any(sensor_ports >= SENSORS_MAX):
        raise ValueError("Port range is 0-3!")
    if "- No Device -" in port:
        while True:
            dat_list = np.random.randint(0, 3300, len(sensor_ports))  # create a randomized voltage data
            # take only the nonzero indices, and truncated to two decimal places to "filter" out some hardware errors
            dat_sel = np.trunc((np.take(dat_list, sensor_ports) / 1000) * 10**2) / 10**2
            r_arr = np.take(refRes, sensor_ports) * (v_in / dat_sel - 1)
            # write + export values as .csv format
            dat = f", ".join(np.insert(r_arr.astype(str), 0, datetime.now().strftime('%H:%M:%S')))
            print(dat)
            f = open(file_name, "a", newline="", encoding="utf-8")
            f.write(dat + '\n')
            f.close()
            time.sleep(delay / 1000)
        exit(0)
    else:
        controller = serial.Serial(port, baudrate=baud)

    # TODO: separate data in each run but still keep them in one csv file
    while controller.isOpen():
        try:
            read_data = controller.readline().decode("utf-8")
            # use numpy so it can make list calculations easier (and possibly faster)
            dat_list = np.asarray(json.loads(read_data), dtype=np.uint32)[:SENSORS_MAX]

            # if we decided to switch back to analogRead(), replace this line of comment to the algorithm to something like the commented line below
            # dat_sel = np.take(dat_list, sensor_ports) * v_in / resolution

            # take only the nonzero indices, and truncated to two decimal places to "filter" out some hardware errors
            dat_sel = np.trunc((np.take(dat_list, sensor_ports) / 1000) * 10**2) / 10**2
            r_arr = np.take(refRes, sensor_ports) * (v_in / dat_sel - 1)
            # write + export values as .csv format
            dat = f", ".join(np.insert(r_arr.astype(str), 0, datetime.now().strftime('%H:%M:%S')))
            print(dat)
            f = open(file_name, "a", newline="", encoding="utf-8")
            f.write(dat + '\n')
            f.close()
        # except KeyboardInterrupt as e:
        #     print(e.__class__.__name__)
        #     break
        except (json.decoder.JSONDecodeError, UnicodeDecodeError):
            print('decoder error')