가우스 소거법(Gaussian elimination) Python

Gaussian_elimination.py

import numpy as np


def get_pivot(arr, reverse=False):
    if reverse:
        arr = np.flip(arr, 0)[1:]

    for item in arr:
        if item != 0:
            return item


def div_arr(mat, arr, idx, reverse=False):
    temp = get_pivot(arr, reverse)
    mat[idx] = arr / temp


if __name__ == '__main__':
    matrix = np.array([[3, -1, 2, 12],
                       [1, 2, 3, 11],
                       [2, -2, -1, 2]], dtype=np.float32)

    for i in range(len(matrix)):
        my_arr = matrix[i]
        div_arr(matrix, my_arr, i)
        n = get_pivot(my_arr)

        for idx, target in enumerate(matrix[i + 1:]):
            m = get_pivot(target)
            temp_my = my_arr * m / n
            new_target = target - temp_my
            matrix[i + idx + 1] = new_target

    for i in range(len(matrix)):
        my_idx = len(matrix) - i - 1
        my_arr = matrix[my_idx]
        div_arr(matrix, my_arr, my_idx)
        n = get_pivot(my_arr)

        for idx in range(len(matrix) - i - 2, -1, -1):
            target = matrix[idx]
            m = get_pivot(target, True)
            temp_my = my_arr * m / n
            new_target = target - temp_my
            matrix[idx] = new_target

    print(matrix)