G1 = np.transpose(G)
>>> import numpy as np
>>> G = np.array([[1,0,0,1],[0,1,0,-1],[0,0,1,1]])
>>> G1=np.transpose(G)
>>> G1
array([[ 1, 0, 0],
[ 0, 1, 0],
[ 0, 0, 1],
[ 1, -1, 1]])
2. python求矩阵乘法
G2 = np.dot(G,G1)
>>> import numpy as np
>>> G = np.array([[1,0,0,1],[0,1,0,-1],[0,0,1,1]])
>>> G1=np.transpose(G)
>>> G1
array([[ 1, 0, 0],
[ 0, 1, 0],
[ 0, 0, 1],
[ 1, -1, 1]])
>>> G2 = np.dot(G,G1)
>>> G2
array([[ 2, -1, 1],
[-1, 2, -1],
[ 1, -1, 2]])
3. python求矩阵的逆
G3 = np.linalg.inv(G2)
>>> import numpy as np
>>> G = np.array([[1,0,0,1],[0,1,0,-1],[0,0,1,1]])
>>> G1=np.transpose(G)
>>> G1
array([[ 1, 0, 0],
[ 0, 1, 0],
[ 0, 0, 1],
[ 1, -1, 1]])
>>> G2 = np.dot(G,G1)
>>> G2
array([[ 2, -1, 1],
[-1, 2, -1],
[ 1, -1, 2]])
>>> G3 = np.linalg.inv(G2)
>>> G3
array([[ 0.75, 0.25, -0.25],
[ 0.25, 0.75, 0.25],
[-0.25, 0.25, 0.75]])
4. python求矩阵的伪逆
K = np.linalg.pinv(J)
>>> import numpy as np
>>> J = np.array([[1,0,0,1],[1,1,0,0],[0,1,1,0],[0,0,1,1]])
>>> K = np.linalg.pinv(J)
>>> K
array([[ 0.375, 0.375, -0.125, -0.125],
[-0.125, 0.375, 0.375, -0.125],
[-0.125, -0.125, 0.375, 0.375],
[ 0.375, -0.125, -0.125, 0.375]])
