随机数np.random

    • 设置随机数种子 
    1. array([[0.77132064, 0.02075195, 0.63364823],
    2.        [0.74880388, 0.49850701, 0.22479665],
    3.        [0.19806286, 0.76053071, 0.16911084]])
    • 均匀分布 
    2. a = np.random.rand(3, 3)
    3. a
    1. array([[0.08833981, 0.68535982, 0.95339335],
    2.        [0.00394827, 0.51219226, 0.81262096],
    3.        [0.61252607, 0.72175532, 0.29187607]])
    1. # 生成均匀分布随机数，指定随机数取值范围和数组形状
    2. a = np.random.uniform(low = -1.0, high = 1.0, size=(2,2))
    3. a
    • 正态分布 
    1. # 生成标准正态分布随机数
    2. a = np.random.randn(3, 3)
    1. array([[ 1.484537  , -1.07980489, -1.97772828],
    2.        [ 1.12369125,  1.67262221,  0.09914922]])
    1. # 生成正态分布随机数，指定均值loc和方差scale
    2. a = np.random.normal(loc = 1.0, scale = 1.0, size = (3,3))
    3. a
    1. array([[2.39799638, 0.72875201, 1.61320418],
    2.        [0.73268281, 0.45069099, 1.1327083 ],
    3.        [0.52385799, 2.30847308, 1.19501328]])

    • 随机打乱1维ndarray数组顺序，发现所有元素位置都被打乱了，代码如下所示。 
    1. ('before random shuffle: ', array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
    2.        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]))
    3. ('after random shuffle: ', array([10, 21, 26,  7,  0, 23,  2, 17, 18, 20, 12,  6,  9,  3, 25,  5, 13,
    4.        14, 24, 29,  1, 28, 11, 15, 27, 16, 19,  4, 22,  8]))
    1. # 生成一维数组
    2. a = np.arange(0, 30)
    3. # 将一维数组转化成2维数组
    4. a = a.reshape(10, 3)
    6. print('before random shuffle: \n{}'.format(a))
    7. np.random.shuffle(a)
    8. print('after random shuffle: \n{}'.format(a))
    1. before random shuffle: 
    2. [[ 0  1  2]
    3.  [ 6  7  8]
    4.  [ 9 10 11]
    5.  [12 13 14]
    6.  [15 16 17]
    7.  [18 19 20]
    8.  [21 22 23]
    9.  [24 25 26]
    10.  [27 28 29]]
    11. after random shuffle: 
    12. [[15 16 17]
    13.  [12 13 14]
    14.  [27 28 29]
    15.  [ 3  4  5]
    16.  [ 9 10 11]
    17.  [21 22 23]
    18.  [18 19 20]
    19.  [ 0  1  2]
    20.  [ 6  7  8]
    21.  [24 25 26]]

    1. # 随机选取部分元素
    2. a = np.arange(30)
    3. b = np.random.choice(a, size=5)