关于numpy.concatenate()函数的使用及说明

>>> a=np.array([1,2,3])
>>> b=np.array([11,22,33])
>>> c=np.array([44,55,66])
>>> np.concatenate((a,b,c),axis=0)  # 默认情况下，axis=0可以不写
array([ 1,  2,  3, 11, 22, 33, 44, 55, 66]) #对于一维数组拼接，axis的值不影响最后的结果

>>> a=np.array([[1,2,3],[4,5,6]])
>>> b=np.array([[11,21,31],[7,8,9]])
>>> np.concatenate((a,b),axis=0)  # axis=0为按列拼接
array([[ 1,  2,  3],
       [ 4,  5,  6],
       [11, 21, 31],
       [ 7,  8,  9]])

>>> np.concatenate((a,b),axis=1)  #axis=1表示对应行的数组进行拼接
array([[ 1,  2,  3, 11, 21, 31],
       [ 4,  5,  6,  7,  8,  9]])

np.concatenate((a,b))
Out[22]: 
array([[ 1,  2,  3],
       [ 4,  5,  6],
       [11, 21, 31],
       [ 7,  8,  9]])

np.concatenate((a,b),axis=-1)
Out[21]: 
array([[ 1,  2,  3, 11, 21, 31],
       [ 4,  5,  6,  7,  8,  9]])

numpy.concatenate（（a1，a2，...），axis = 0，out = None，dtype = None，cast =“ same_kind” 

array01=np.arange(24).reshape(4,6)
array01
结果
array([[ 0,  1,  2,  3,  4,  5],
       [ 6,  7,  8,  9, 10, 11],
       [12, 13, 14, 15, 16, 17],
       [18, 19, 20, 21, 22, 23]])
array04 = np.ones((4,15),dtype='int32')
array04
结果
array([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])
np.concatenate((array01,array03),axis=1,out=array04)
结果
array([[ 0,  1,  2,  3,  4,  5,  0,  1,  2,  3,  4,  5,  6,  7,  8],
       [ 6,  7,  8,  9, 10, 11,  9, 10, 11, 12, 13, 14, 15, 16, 17],
       [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26],
       [18, 19, 20, 21, 22, 23, 27, 28, 29, 30, 31, 32, 33, 34, 35]])