具有不同形状复制值的级联数组

Question

我有一个具有形状的数组：(15,2)。我还有另一个带有值的数组：[0, 3, 5]。

我想在第一个数组中创建另一个列，其值来自第二个数组，其中前5行的值为0，行6-10的值为3，最后5行的值为5。

就像这样：

[0,
 0,
 0,
 0,
 0,
 3,
 3,
 3,
 3,
 3,
 5,
 5,
 5,
 5,
 5]

有什么方法可以做到这一点吗？

谢谢!

Answer 1

您可以使用numpy的内置repeat和stacking：

a = np.zeros((15,2))
b = np.array([0,3,5])
np.hstack((a, np.repeat(b,5)[:,None]))

产出：

[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 3.]
 [0. 0. 3.]
 [0. 0. 3.]
 [0. 0. 3.]
 [0. 0. 3.]
 [0. 0. 5.]
 [0. 0. 5.]
 [0. 0. 5.]
 [0. 0. 5.]
 [0. 0. 5.]]

Answer 2

使用np.concatenate。

• 将第二个数组int转换为2d“向量”数组，其中每一行都有1列

a = [0, 0, 0, 0, 0, 3, 3, 3, 3, 3, 5, 5, 5, 5, 5] # your list of [0, 3, 5]
a = np.array([a]).T # [ [0], [0], [0], ..., [5] ] the "vector" array

然后简单地

b = np.array([[i, i +1] for i in range(15)]) # some example 15x2 array
print(np.concatenate((b, a), axis=1)) 

输出是

array([[ 0,  1,  0],
       [ 1,  2,  0],
       [ 2,  3,  0],
       [ 3,  4,  0],
       [ 4,  5,  0],
       [ 5,  6,  3],
       [ 6,  7,  3],
       [ 7,  8,  3],
       [ 8,  9,  3],
       [ 9, 10,  3],
       [10, 11,  5],
       [11, 12,  5],
       [12, 13,  5],
       [13, 14,  5],
       [14, 15,  5]])

Answer 3

rand = np.random.random((15,2)) # shape is (15,2)
vals = np.array([0,3,5]) # shape is (3,)
res = np.concatenate(([np.full((rand.shape[0]//vals.shape[0],), val) for val in vals]), axis=0)
res

产出：

array([0, 0, 0, 0, 0, 3, 3, 3, 3, 3, 5, 5, 5, 5, 5])

最后，

final = np.hstack((rand, res.reshape(15,1)))
final

产出：

array([[0.29759807, 0.60548479, 0.        ],
       [0.61242249, 0.46456274, 0.        ],
       [0.86172011, 0.2963868 , 0.        ],
       [0.91728575, 0.36366023, 0.        ],
       [0.56488556, 0.82130321, 0.        ],
       [0.59482141, 0.46148353, 3.        ],
       [0.7762271 , 0.25415058, 3.        ],
       [0.09176551, 0.9687253 , 3.        ],
       [0.06473259, 0.34686598, 3.        ],
       [0.69542414, 0.15540001, 3.        ],
       [0.02880707, 0.23169327, 5.        ],
       [0.90004256, 0.22145591, 5.        ],
       [0.61596969, 0.46807342, 5.        ],
       [0.02263769, 0.68522023, 5.        ],
       [0.81777274, 0.58145853, 5.        ]])