Numpy中常用的10个矩阵操作示例（一）

importnumpyasnp#Vectorsas1Dnumpyarraysa=np.array([1, 2, 3])
b=np.array([4, 5, 6])
print("a= ", a)
print("b= ", b)
print("\ninner:", np.inner(a, b))
print("dot:", np.dot(a, b))

importnumpyasnp#Matricesasndarrayobjectsa=np.array([[1, 2], [3, 4]])
b=np.array([[5, 6, 7], [8, 9, 10]])
print("a", type(a))
print(a)
print("\nb", type(b))
print(b)
#Matricesasmatrixobjectsc=np.matrix([[1, 2], [3, 4]])
d=np.matrix([[5, 6, 7], [8, 9, 10]])
print("\nc", type(c))
print(c)
print("\nd", type(d))
print(d)
print("\ndot product of two ndarray objects")
print(np.dot(a, b))
print("\ndot product of two matrix objects")
print(np.dot(c, d))

importnumpyasnp#Matricesasndarrayobjectsa=np.array([[1, 2], [3, 4]])
b=np.array([[5, 6], [8, 9]])
print("a", type(a))
print(a)
print("\nb", type(b))
print(b)
#Matricesasmatrixobjectsc=np.matrix([[1, 2], [3, 4]])
d=np.matrix([[5, 6], [8, 9]])
print("\nc", type(c))
print(c)
print("\nd", type(d))
print(d)
print("\n* operation on two ndarray objects (Elementwise)")
print(a*b)
print("\n* operation on two matrix objects (same as np.dot())")
print(c*d)

importnumpyasnpa=np.array([[1, 2], [3, 4], [5, 6]])
print("a = ")
print(a)
print("\nWith np.transpose(a) function")
print(np.transpose(a))
print("\nWith ndarray.transpose() method")
print(a.transpose())
print("\nWith ndarray.T short form")
print(a.T)

importnumpyasnpa=np.array([1, 2, 3])
print("a = ")
print(a)
print("\na.T = ")
print(a.T)