computing determinant of a matrix (nxn) recursively

Question

I\'m about to write some code that computes the determinant of a square matrix (nxn), using the Laplace algorithm (Meaning recursive algorithm) as written Wikipedia\'s Lapla

Answer 1

import numpy as np

def smaller_matrix(original_matrix,row, column):
    for ii in range(len(original_matrix)):
        new_matrix=np.delete(original_matrix,ii,0)
        new_matrix=np.delete(new_matrix,column,1)
        return new_matrix


def determinant(matrix):
    """Returns a determinant of a matrix by recursive method."""
    (r,c) = matrix.shape 
    if r != c:
        print("Error!Not a square matrix!")
        return None
    elif r==2:
        simple_determinant = matrix[0][0]*matrix[1][1]-matrix[0][1]*matrix[1][0]
        return simple_determinant
    else: 
        answer=0
        for j in range(r):
            cofactor = (-1)**(0+j) * matrix[0][j] * determinant(smaller_matrix(matrix, 0, j))
            answer+= cofactor
        return answer



#test the function
#Only works for numpy.array input
np.random.seed(1)
matrix=np.random.rand(5,5)

determinant(matrix)