python 从现有的 2d 数组构造 numpy 中的 3d 数组
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Contruct 3d array in numpy from existing 2d array
提问by vernomcrp
During preparing data for NumPy calculate. I am curious about way to construct:
在为 NumPy 计算准备数据期间。我对构建方式感到好奇：
myarray.shape => (2,18,18)
from:
从：
d1.shape => (18,18)
d2.shape => (18,18)
I try to use NumPy command:
我尝试使用 NumPy 命令：
hstack([[d1],[d2]])
but it looks not work!
但它看起来不起作用！
采纳答案by Eric O Lebigot
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!).
hstack 和 vstack 不会改变数组的维数：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！）。
You can do what Daniel suggested (directly use numpy.array([d1, d2])).
您可以按照 Daniel 的建议进行操作（直接使用numpy.array([d1, d2])）。
You can alternatively convert your arrays to 3D arrays before stacking them, by adding a new dimension to each array:
您也可以在堆叠之前将数组转换为 3D 数组，方法是向每个数组添加一个新维度：
d3 = numpy.vstack([ d1[newaxis,...], d2[newaxis,...] ]) # shape = (2, 18, 18)
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.
事实上，d1[newaxis,...].shape == (1, 18, 18), 并且您可以直接堆叠两个 3D 数组并获得d3您想要的新 3D 数组 ( )。
回答by Daniel G
Just doing d3 = array([d1,d2])seems to work for me:
只是做d3 = array([d1,d2])似乎对我有用：
>>> from numpy import array
>>> # ... create d1 and d2 ...
>>> d1.shape
(18,18)
>>> d2.shape
(18,18)
>>> d3 = array([d1, d2])
>>> d3.shape
(2, 18, 18)
回答by Shu Zhang
arr3=np.dstack([arr1, arr2])
arr1, arr2 are 2d array shape (256,256), arr3: shape(256,256,2)
arr1, arr2 是二维数组shape (256,256), arr3:shape(256,256,2)
