Bisezione vs Netwon Plot

from matplotlib import pyplot as plt
import struct
import numpy as np
import math
from scipy import stats


# read the data from the program Bisection
def read_data(filename, datasize):
    with open(filename, "rb") as f:
      lines = f.read()

    print(f"File {filename} Read ", len(lines), "bytes")

    data = struct.unpack('d'*datasize*2 + "i"*datasize, lines);

    # first bite packet are the tolear
    tolerance_values = data[:datasize]
    result_values = data[datasize: datasize*2]
    iteration_values = data[datasize*2:]
    return tolerance_values, result_values, iteration_values

# calculate the error in log form
def calc_error(teo_y, y):
    erry = []
    for v in y:
        print("value:", v, end=" ")
        err = (teo_y - v) / teo_y

        if err != 0:
            err = np.log10(abs(err))
            erry.append(err)
            print("log10(error)", err)
        else:
            print("Max precision reached")
            erry.append(min(erry))

    return erry

#plot and evaluate the data points
def plot_eval(filename, datasize, teo_y):
    # read the data
    _, y, i = read_data(filename, datasize)
    # calculate the errro
    erry = calc_error(teo_y, y)
    plt.plot(i, erry)

    slope, intercept, r_value, p_value, std_err = stats.linregress(i,erry)
    print("y = " + str(slope) + "x + ", intercept)
    print("angular coeff.:", math.tan(slope))


# fixed parameters
datasize = 10
teo_y = math.sqrt(2)

# newton
filename = "./Bisezione/newton_data.dat"
plot_eval(filename, datasize, teo_y)


filename = "./Bisezione/bisezione_data.dat"
plot_eval(filename, datasize, teo_y)

plt.title('Error in function of iterations')
plt.xlabel('Number of iterations')
plt.ylabel('log(error)')

plt.show()