def hstack(tup):
"""
Stack arrays in sequence horizontally (column wise).
水平（按列）顺序堆叠数组。
This is equivalent to concatenation along the second axis, except for 1-D
arrays where it concatenates along the first axis. Rebuilds arrays divided
by `hsplit`.
这等效于沿第二个轴的串联，除了一维数组沿第一个轴的串联。 重建除以“ hsplit”的数组。
This function makes most sense for arrays with up to 3 dimensions. For
instance, for pixel-data with a height (first axis), width (second axis),
and r/g/b channels (third axis). The functions `concatenate`, `stack` and
`block` provide more general stacking and concatenation operations.
此功能对最多3维的阵列最有意义。
例如，对于具有高度（第一轴），宽度（第二轴）和r / g / b通道（第三轴）的像素数据。
函数concatenate，stack和block提供了更常规的堆叠和串联操作。
Parameters
----------
tup : sequence of ndarrays
The arrays must have the same shape along all but the second axis,
except 1-D arrays which can be any length.
ndarray的序列
除第二个轴外，所有阵列的形状都必须相同，除了一维阵列可以是任意长度。
Returns
-------
stacked : ndarray
The array formed by stacking the given arrays.
堆叠：ndarray
通过堆叠给定数组形成的数组。
See Also
--------
stack : Join a sequence of arrays along a new axis.
沿新轴连接一系列数组。
vstack : Stack arrays in sequence vertically (row wise).
垂直（行）按顺序堆叠数组。
dstack : Stack arrays in sequence depth wise (along third axis).
沿深度方向（沿第三轴）按顺序堆叠数组。
concatenate : Join a sequence of arrays along an existing axis.
沿现有轴连接一系列数组。
hsplit : Split array along second axis.
沿第二个轴拆分数组。
block : Assemble arrays from blocks.
从块组装数组。
Examples
--------
>>> a = np.array((1,2,3))
>>> b = np.array((2,3,4))
>>> np.hstack((a,b))
array([1, 2, 3, 2, 3, 4])
>>> a = np.array([[1],[2],[3]])
>>> b = np.array([[2],[3],[4]])
>>> np.hstack((a,b))
array([[1, 2],
[2, 3],
[3, 4]])
"""
arrs = [atleast_1d(_m) for _m in tup]
if arrs and arrs[0].ndim == 1:
return _nx.concatenate(arrs, 0)
else:
return _nx.concatenate(arrs, 1)
