题解 | 使用行阶梯形求矩阵的像(image)

import numpy as np

def matrix_image(A):
    mat = np.array(A, dtype=np.float64).copy()
    row, col = mat.shape  
    pivot_cols = []       
    cur_row = 0           
    for c in range(col):
        pivot_row = -1
        for r in range(cur_row, row):
            if abs(mat[r, c]) > 1e-8:  
                pivot_row = r
                break
        if pivot_row == -1:
            continue  
        mat[[cur_row, pivot_row], :] = mat[[pivot_row, cur_row], :]
        for r in range(cur_row + 1, row):
            factor = mat[r, c] / mat[cur_row, c]
            mat[r, :] = mat[r, :] - factor * mat[cur_row, :]
        pivot_cols.append(c)
        cur_row += 1
        
        if cur_row >= row:
            break  
    res = np.array(A)[:, pivot_cols]
    return res

if __name__ == "__main__":
    A = np.array(eval(input()))
    print(matrix_image(A))