问题描述
在准备用于NumPy计算的数据时.我对构造方法感到好奇:
During preparing data for NumPy calculate. I am curious about way to construct:
myarray.shape => (2,18,18)
来自:
d1.shape => (18,18)
d2.shape => (18,18)
我尝试使用NumPy命令:
I try to use NumPy command:
hstack([[d1],[d2]])
但它似乎不起作用！
推荐答案
hstack和vstack不会更改数组的维数:它们只是将它们并排"放置.因此，组合二维数组会创建一个新的二维数组(不是3D数组！).
hstack and vstack do no change the number of dimensions of the arrays: they merely put them "side by side". Thus, combining 2-dimensional arrays creates a new 2-dimensional array (not a 3D one!).
您可以执行丹尼尔(Daniel)建议的操作(直接使用numpy.array([d1, d2])).
You can do what Daniel suggested (directly use numpy.array([d1, d2])).
通过在每个数组上添加新尺寸，您还可以在将数组堆叠之前将其转换为3D数组:
You can alternatively convert your arrays to 3D arrays before stacking them, by adding a new dimension to each array:
d3 = numpy.vstack([ d1[newaxis,...], d2[newaxis,...] ]) # shape = (2, 18, 18)
实际上是d1[newaxis,...].shape == (1, 18, 18)，您可以直接堆叠两个3D阵列并获得所需的新3D阵列(d3).
In fact, d1[newaxis,...].shape == (1, 18, 18), and you can stack both 3D arrays directly and get the new 3D array (d3) that you wanted.
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