"""
 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
import csv

# constant settings
SENSORS_MAX = 4  # maximum sensor ports

def read():
    """
    read the data from a board, if any. If "no device" selected generate random values for demo
    """
    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()
    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:
        # generate random value

        # open the file and add a line of header to it, then close
        f = open(file_name, "a", newline="", encoding="utf-8")
        writer = csv.writer(f)
        # headers based on number of ports used
        if len(sensor_ports) == 1: 
            header = ['Time', 'Resistance']
        if len(sensor_ports)== 2:
            header = ['Time', 'Resistance1', 'Resistance2']
        if len(sensor_ports) == 3:
            header = ['Time', 'Resistance1', 'Resistance2', 'Resistance3']
        if len(sensor_ports) == 4:
            header = ['Time', 'Resistance1', 'Resistance2', 'Resistance3', 'Resistance4']
        writer.writerow(header)
        f.close()
        while True:
            dat_list = np.random.randint(0, v_in * 1000, SENSORS_MAX)  # create a randomized voltage data
            # take only the nonzero indices, and truncated to two decimal places to "filter" out some hardware errors
            # According to the actual req, the data in the data list should be (3.3-data)
            for x in range(dat_list.size):
                np.put(dat_list, x, 3.3 - dat_list[x])
            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) # *2 <-- change with actual formula for ammonia concentration
            # created a new array to convert resistance values to sci notation
            r_arr2 = np.empty(len(r_arr), dtype=object)
            for i in range(len(r_arr)) :
                a = np.format_float_scientific(r_arr[i], precision = 2)
                r_arr2[i] = a
            # write + export values as .csv format
            # converted resistance values in array to scientific notation
            dat = f", ".join(np.insert(r_arr2.astype(str), 0, datetime.now().strftime('%H:%M:%S'))) #np.format_float_scientific()
            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: sometimes serial port is in use, make it promt user when it happens
        
    # open the file and add a line of header to it, then close
    f = open(file_name, "a", newline="", encoding="utf-8")
    writer = csv.writer(f)
    # headers based on number of ports used
    if len(sensor_ports) == 1: 
        header = ['Time', 'Resistance']
    if len(sensor_ports) == 2:
        header = ['Time', 'Resistance1', 'Resistance2']
    if len(sensor_ports) == 3:
        header = ['Time', 'Resistance1', 'Resistance2', 'Resistance3']
    if len(sensor_ports) == 4:
        header = ['Time', 'Resistance1', 'Resistance2', 'Resistance3', 'Resistance4']
    writer.writerow(header)
    f.close()
    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.float32)[:SENSORS_MAX]
            # According to the actual req, the data in the data list should be (3.3-data)
            for x in range(dat_list.size):
                np.put(dat_list, x, 3.3 - dat_list[x])
            dat_sel = np.take(dat_list, sensor_ports)
            # 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
            r_arr = np.take(refRes, sensor_ports) * (v_in / dat_sel - 1) # *2 <-- change with actual formula for ammonia concentration
            # created a new array to convert resistance values to sci notation
            r_arr2 = np.empty(len(r_arr), dtype=object)
            for i in range(len(r_arr)) :
                a = np.format_float_scientific(r_arr[i], precision = 2)
                r_arr2[i] = a
            # write + export values as .csv format
            # converted resistance values in array to scientific notation
            dat = f", ".join(np.insert(r_arr2.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')