import csv
import argparse


# Using the method described in "Ziegler–Nichols Tuning Method∗" by Vishakha Vijay Patel
# (https://www.ias.ac.in/article/fulltext/reso/025/10/1385-1397)


def line(a, b, x):
    return a * x + b


def invline(a, b, y):
    return (y - b) / a


def plot(xdata, ydata,
         tangent_min, tangent_max, tangent_slope, tangent_offset,
         lower_crossing_x, upper_crossing_x):
    from matplotlib import pyplot

    minx = min(xdata)
    maxx = max(xdata)
    miny = min(ydata)
    maxy = max(ydata)

    pyplot.scatter(xdata, ydata)

    pyplot.plot([minx, maxx], [miny, miny], '--', color='purple')
    pyplot.plot([minx, maxx], [maxy, maxy], '--', color='purple')

    pyplot.plot(tangent_min[0], tangent_min[1], 'v', color='red')
    pyplot.plot(tangent_max[0], tangent_max[1], 'v', color='red')
    pyplot.plot([minx, maxx], [line(tangent_slope, tangent_offset, minx), line(tangent_slope, tangent_offset, maxx)], '--', color='red')

    pyplot.plot([lower_crossing_x, lower_crossing_x], [miny, maxy], '--', color='black')
    pyplot.plot([upper_crossing_x, upper_crossing_x], [miny, maxy], '--', color='black')

    pyplot.show()


def calculate(filename, tangentdivisor, showplot):
    # parse the csv file
    xdata = []
    ydata = []
    filemintime = None
    with open(filename) as f:
        for row in csv.DictReader(f):
            try:
                time = float(row['pid_time'])
                temp = float(row['pid_ispoint'])
                if filemintime is None:
                    filemintime = time

                xdata.append(time - filemintime)
                ydata.append(temp)
            except ValueError:
                continue  # just ignore bad values!

    # gather points for tangent line
    miny = min(ydata)
    maxy = max(ydata)
    midy = (maxy + miny) / 2
    yoffset = int((maxy - miny) / tangentdivisor)
    tangent_min = tangent_max = None
    for i in range(0, len(xdata)):
        rowx = xdata[i]
        rowy = ydata[i]

        if rowy >= (midy - yoffset) and tangent_min is None:
            tangent_min = (rowx, rowy)
        elif rowy >= (midy + yoffset) and tangent_max is None:
            tangent_max = (rowx, rowy)

    # calculate tangent line to the main temperature curve
    tangent_slope = (tangent_max[1] - tangent_min[1]) / (tangent_max[0] - tangent_min[0])
    tangent_offset = tangent_min[1] - line(tangent_slope, 0, tangent_min[0])

    # determine the point at which the tangent line crosses the min/max temperaturess
    lower_crossing_x = invline(tangent_slope, tangent_offset, miny)
    upper_crossing_x = invline(tangent_slope, tangent_offset, maxy)

    # compute parameters
    L = lower_crossing_x - min(xdata)
    T = upper_crossing_x - lower_crossing_x

    # Magic Ziegler-Nicols constants ahead!
    Kp = 1.2 * (T / L)
    Ti = 2 * L
    Td = 0.5 * L
    Ki = Kp / Ti
    Kd = Kp * Td

    # outut to the user
    print(f"Kp: {Kp} 1/Ki: {1/ Ki}, Kd: {Kd}")

    if showplot:
        plot(xdata, ydata,
             tangent_min, tangent_max, tangent_slope, tangent_offset,
             lower_crossing_x, upper_crossing_x)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Perform Ziegler-Nichols PID tuning')
    parser.add_argument('csvfile', type=str, help="The CSV file to read from. Must contain two columns called pid_time (time in seconds) and pid_ispoint (observed temperature)")
    parser.add_argument('--showplot', action='store_true', help="If set, also plot results (requires pyplot to be pip installed)")
    parser.add_argument('--tangentdivisor', type=float, default=4, help="Adjust the tangent calculation to fit better. Must be >= 2.")
    args = parser.parse_args()

    if args.tangentdivisor < 2:
        raise ValueError("tangentdivisor must be >= 2")

    calculate(args.csvfile, args.tangentdivisor, args.showplot)