computation.py

import json
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit

a = []
b = []
h = "h"
for bike in ["10", "8", "6", "4", "3", "2", "1"]:
    with open(f"./calibration_files/resisting_current_load_h{h}_b{bike}.json", "r") as f:
        data = json.load(f)
        a.append(data["a"])
        b.append(data["b"])


def find(pig, prop, cst):
    return prop / pig + cst


pig = np.asarray([11, 15, 19, 25, 28, 32, 36])

popt = curve_fit(find, pig, a)


plt.plot(pig, a)
plt.plot(pig, find(pig, *popt[0]))
print(popt[0])
plt.show()

a = []
b = []
bike = "10"
for h in ["h", "5", "4", "3", "2", "1", "l"]:
    with open(f"./calibration_files/resisting_current_load_h{h}_b{bike}.json", "r") as f:
        data = json.load(f)
        a.append(data["a"])
        b.append(data["b"])


def find(ht, prop, cst):
    return prop * ht + cst


ht = np.asarray([6, 5, 4, 3, 2, 1, 0])

popt = curve_fit(find, ht, a)
print(popt[0])

plt.plot(ht, a)
plt.plot(ht, find(ht, *popt[0]))
plt.show()