numpy 合并

Join a sequence of arrays along an existing axis.
[https://numpy.org/doc/stable/reference/generated/numpy.concatenate.html#numpy.concatenate]
numpy.concatenate((a1, a2, ...), axis=0, out=None, dtype=None, casting="same_kind")

import numpy as np

a = np.array([[1, 2], [3, 4]])
b = np.array([[5, 6]])
np.concatenate((a, b), axis=0)

array([[1, 2],
       [3, 4],
       [5, 6]])

np.concatenate((a, b.T), axis=1)

array([[1, 2, 5],
       [3, 4, 6]])

np.concatenate((a, b), axis=None)

array([1, 2, 3, 4, 5, 6])

a = np.array((1,2,3))
b = np.array((4,5,6))
np.hstack((a,b))

array([1, 2, 3, 4, 5, 6])

a = np.array([[1],[2],[3]])
b = np.array([[4],[5],[6]])
np.hstack((a,b))

array([[1, 4],
       [2, 5],
       [3, 6]])

Stack arrays in sequence vertically (row wise)

a = np.array((1,2,3))
b = np.array((4,5,6))
np.vstack((a,b))

array([[1, 2, 3],
       [4, 5, 6]])

a = np.array([[1],[2],[3]])
b = np.array([[4],[5],[6]])
np.vstack((a,b))

array([[1],
       [2],
       [3],
       [4],
       [5],
       [6]])

Stack arrays in sequence depth wise (along third axis).

a = np.array((1,2,3))
b = np.array((2,3,4))
np.dstack((a,b))

array([[[1, 2],
        [2, 3],
        [3, 4]]])

a = np.array([[1],[2],[3]])
b = np.array([[2],[3],[4]])
np.dstack((a,b))

array([[[1, 2]],

       [[2, 3]],

       [[3, 4]]])

Join a sequence of arrays along a new axis.

arrays = [np.random.randn(3, 4) for _ in range(10)]
np.stack(arrays, axis=0).shape

(10, 3, 4)

np.stack(arrays, axis=1).shape

(3, 10, 4)

np.stack(arrays, axis=2).shape

(3, 4, 10)

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
np.stack((a, b))

array([[1, 2, 3],
       [4, 5, 6]])

np.stack((a, b), axis=-1)

array([[1, 4],
       [2, 5],
       [3, 6]])

Assemble an nd-array from nested lists of blocks.

A = np.eye(2) * 2
B = np.eye(3) * 3
np.block([
    [A,np.zeros((2, 3))],
    [np.ones((3, 2)), B]
])

array([[2., 0., 0., 0., 0.],
       [0., 2., 0., 0., 0.],
       [1., 1., 3., 0., 0.],
       [1., 1., 0., 3., 0.],
       [1., 1., 0., 0., 3.]])

np.block([1, 2, 3])              # hstack([1, 2, 3])

array([1, 2, 3])

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
np.block([a, b, 10])             # hstack([a, b, 10])

array([ 1,  2,  3,  4,  5,  6, 10])

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
np.block([[a], [b]])             # vstack([a, b])

array([[1, 2, 3],
       [4, 5, 6]])

A = np.ones((2, 2), int)
B = 2 * A
np.block([[A], [B]])             # vstack([A, B])

array([[1, 1],
       [1, 1],
       [2, 2],
       [2, 2]])

a = np.array(0)
b = np.array([1])
np.block([a])                    # atleast_1d(a)

array([0])

np.block([b])                    # atleast_1d(b)

array([1])

np.block([[a]])                  # atleast_2d(a)

array([[0]])

np.block([[b]])                  # atleast_2d(b)

array([[1]])

Stack 1-D arrays as columns into a 2-D array.

a = np.array((1,2,3))
b = np.array((2,3,4))
np.column_stack((a,b))

array([[1, 2],
       [2, 3],
       [3, 4]])

Append values to the end of an array

np.append([1, 2, 3], [[4, 5, 6], [7, 8, 9]])

array([1, 2, 3, 4, 5, 6, 7, 8, 9])

# 指定轴时，值必须具有正确的形状。
np.append([[1, 2, 3], [4, 5, 6]], [[7, 8, 9]], axis=0)

array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])

np.append([[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]], axis=1)

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