Matrice inverse Python
import numpy as np
# X is the matrix to invert
X_inverted = numpy.linalg.inv(X)
Four Horned Antelope
import numpy as np
# X is the matrix to invert
X_inverted = numpy.linalg.inv(X)#You can either use the included inv fucntion
M_inverse = numpy.linalg.inv(M)
#Or use the exponent notation, which is also understood by numpy
M_inverse = M**(-1)>>> import numpy as np
>>> A = np.array(([1,3,3],[1,4,3],[1,3,4]))
>>> A
array([[1, 3, 3],
[1, 4, 3],
[1, 3, 4]])
>>> A_inv = np.linalg.inv(A)
>>> A_inv
array([[ 7., -3., -3.],
[-1., 1., 0.],
[-1., 0., 1.]])
>>> import numpy as np
>>> A = np.array(([1,3,3],[1,4,3],[1,3,4]))
>>> A
array([[1, 3, 3],
[1, 4, 3],
[1, 3, 4]])
>>> A_inv = np.linalg.inv(A)
>>> A_inv
array([[ 7., -3., -3.],
[-1., 1., 0.],
[-1., 0., 1.]])from numpy.linalg import inv
a = np.array([[1., 2.], [3., 4.]])
ainv = inv(a)
np.allclose(np.dot(a, ainv), np.eye(2))
True
np.allclose(np.dot(ainv, a), np.eye(2))
True