在做图像和nlp数组数据处理的时候,经常要实现两个数组堆叠或者连接的功能,这经常用numpy库的一些函数实现,常用于堆叠数组的numy函数如下: stack : Join a sequence of arrays along a new axis. hstack: Stack arrays in sequence horizontally (column wise). vstack
Stack arrays in sequence horizontally (column wise). All arrays must have the same shape along all but the second axis. Notes --- Equivalent to ``np.concatenate(tup, axis=1)`` if `tup` contains arrays that are at least 2-dimensional. 如果矩阵至少有两个轴,则这个函数会沿着第二个轴扩充...
Take a sequence of arrays and stack them horizontally to make a single array. Rebuild arrays divided byhsplit. This function continues to be supported for backward compatibility, but you should prefernp.concatenateornp.stack. Thenp.stackfunction was added in NumPy 1.10. 用法: >>> a = np.arr...
stackoverflow上也有类似的讨论,在这里numpy vstack vs. column_stack。 给一个相关函数的列表: stack() Join a sequence of arrays along a new axis. hstack() Stack arrays in sequence horizontally (column wise). dstack() Stack arrays in sequence depth wise (along third dimension). concatenate() Jo...
Here, we have concatenated two numpy arrays horizontally. Hence, all the elements of the input arrays are converted to elements of the output array. You cannot concatenate 1-D numpy arrays using the concatenate() function vertically using the axis=1 parameter. Doing so will lead to numpy.AxisE...
This is a very simple tool that we use to manipulate NumPy arrays. Specifically, we use np.hstack to combine NumPy arrays horizontally. The function “stacks” arrays in the horizontal direction. Again, this is a fairly simple function, but to use it properly, you need to know a few thi...
numpy.hstack(tup) numpy.hstack(tup)Stack arrays in sequence horizontally (column wise).Take a sequence of arrays and stack them horizontally to make a single array. Rebuild arrays divided by hsplit.Parameters : tup : sequence of ndarrays All arrays must have the same shape along all but ...
import numpy as geek # input array in_arr1 = geek.array([ 1, 2, 3] ) print ("1st Input array : \n", in_arr1) in_arr2 = geek.array([ 4, 5, 6] ) print ("2nd Input array : \n", in_arr2) # Stacking the two arrays horizontally ...
numpy.hstack(tup)[source] Stack arrays in sequence horizontally (column wise). This is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis. Rebuilds arrays divided byhsplit. ...
numpy.hstack(tup) Parameter: Return value: stacked : ndarray The array formed by stacking the given arrays. Example 1: Horizontally Stacking 1-D Arrays import numpy as np x = np.array([3, 5, 7]) y = np.array([5, 7, 9])