Comparison of matrices and arrays in NUMpy

Array can realize all functions of matrix, but it is easier to operate matrix in realizing some functions, for example, matrix multiplication directly uses A*B instead of functions, but array can deal with various data more flexibly, and can represent high-dimensional array with faster speed

numpy.matrix

Create a matrix

Matrix (string/list/tuple/array) mat (string/list/tuple/array)

a= np.matrix('1 2 3; 4, 5 6 ')
b = np.mat([
    [1.2.3],
    [4.5.6]])print(a)
print(type(a))
print(b)
print(type(b))
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c = np.array([
    [1.2.3],
    [4.5.6]
])
d = np.mat(c)
print(d)
print(type(c))
print(type(d))
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Properties of a matrix object

print(d)
print(d.ndim)
print(d.shape)
print(d.size)
print(d.dtype)
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Matrix operations

Matrix multiplication

m1 = np.mat([
    [0.1],
    [2.3]
])

m2 = np.mat([
    [1.1],
    [2.0]])print(m1*m2)
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Matrix transpose

Matrix transpose:.t

Inverse matrix

m = np.mat([
    [0.1],
    [2.3]])print(m.T)
print(m.I)
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