find_affines.py

import numpy as np
from sklearn.linear_model import LinearRegression


v00 = [
0.30268568571622034,0.0,0.0,-0.5210486131988373,0.0,0.30268568571622034,0.0,-0.49323289091937955,0.0,0.0,0.30268568571622034,-0.046215261237895364
]

v01 = [
0.30268568571622034,0.0,0.0,-1.5243930948041884,0.0,0.30268568571622034,0.0,-0.5066108173407842,0.0,0.0,0.30268568571622034,-0.046215261237895364
]

v02 = [
0.30268568571622034,0.0,0.0,-2.5227208540015127,0.0,0.30268568571622034,0.0,-0.5283499477755668,0.0,0.0,0.30268568571622034,-0.046215261237895364
]

v03 = [
0.30268568571622034,0.0,0.0,-3.5544934292523487,0.0,0.30268568571622034,0.0,-0.49323289091937955,0.0,0.0,0.30268568571622034,-0.046215261237895364
]


v10 = [
0.30268568571622034,0.0,0.0,-0.4942927603560279,0.0,0.30268568571622034,0.0,-1.5066108173407844,0.0,0.0,0.30268568571622034,-0.046215261237895364
]

v20 = [
0.30268568571622034,0.0,0.0,-0.465864666710543,0.0,0.30268568571622034,0.0,-2.5517613190130253,0.0,0.0,0.30268568571622034,-0.046215261237895364
]

v30 = [
0.30268568571622034,0.0,0.0,-0.4842593155399744,0.0,0.30268568571622034,0.0,-3.5383833925916206,0.0,0.0,0.30268568571622034,-0.046215261237895364
]


def fit_line(v_index):
    x = np.arange(4)
    if v_index == 0:
        views = [v00, v01, v02, v03]
        view_index = 3
    else:
        views = [v00, v10, v20, v30]
        view_index = 7
    y = np.array([view[view_index] for view in views])

    # print(x)
    # print(y)

    reg = LinearRegression().fit(x.reshape(-1, 1), y)
    print("a, b =", reg.coef_[0], reg.intercept_)


if __name__ == '__main__':
    print("X-coefficeints:")
    fit_line(0)

    print()
    print("Y-coefficeints:")
    fit_line(1)