NumPy:连接时出错 - 零维数组无法连接

Question

我试图通过np.concat()方法连接两个有效的数组.

我的代码:

print X_train.shape, train_names.shape
X_train = np.concatenate([train_names,X_train], axis=0)

输出:

(3545, 93355) (3545, 692)


ValueError                                Traceback (most recent call last)
<ipython-input-58-59dc66874663> in <module>()
  1 print X_train.shape, train_names.shape
----> 2 X_train = np.concatenate([train_names,X_train], axis=0)


ValueError: zero-dimensional arrays cannot be concatenated

正如你所看到的,数组的形状对齐,我仍然得到这个奇怪的错误.为什么？

编辑:我也尝试过axis=1.相同的结果编辑2:使用的Eqauted数据类型.astype(np.float64).结果相同.

Answer 1

应用np.concatenate到scipy sparse矩阵产生这个错误:

In [162]: from scipy import sparse
In [163]: x=sparse.eye(3)
In [164]: x
Out[164]: 
<3x3 sparse matrix of type '<class 'numpy.float64'>'
    with 3 stored elements (1 diagonals) in DIAgonal format>
In [165]: np.concatenate((x,x))
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-165-0b67d0029ca6> in <module>()
----> 1 np.concatenate((x,x))

ValueError: zero-dimensional arrays cannot be concatenated

有这样的sparse功能:

In [168]: sparse.hstack((x,x)).A
Out[168]: 
array([[ 1.,  0.,  0.,  1.,  0.,  0.],
       [ 0.,  1.,  0.,  0.,  1.,  0.],
       [ 0.,  0.,  1.,  0.,  0.,  1.]])
In [169]: sparse.vstack((x,x)).A
Out[169]: 
array([[ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  0.,  1.],
       [ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  0.,  1.]])