Screen Link:
My Code:
matrix_a = np.asarray([
[1.5, 3],
[1, 4]
])
def matrix_inverse_two(matrix):
det = matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0]
matrix = np.asarray([
[matrix[1][1], -matrix[0][1]],
[-matrix[1][0], matrix[0][0]]
],dtype=np.float32)
if det == 0:
raise ValueError("The matrix isn't invertible")
else:
return np.dot(1/det,matrix)
inverse_a = matrix_inverse_two(matrix_a)
i_2 = np.dot(inverse_a, matrix_a)
print(i_2)
What I expected to happen:
What actually happened:
np.dot(1/det,matrix) doesn’t make sense to me because I don’t calculate a dot product using this.
1/det is a scalar, not matrix or vector.
But without using this, I didn’t make it.