Python 用 2 个一维数组创建二维数组
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Create 2 dimensional array with 2 one dimensional array
提问by Am1rr3zA
I used numpy and scipy and there some function really care about the dimension of the array I have a function name CovexHull(point) which accept the point as 2 dimensional array.
我使用了 numpy 和 scipy 并且有一些函数真正关心数组的维度我有一个函数名称 CovexHull(point) 接受点作为二维数组。
hull = ConvexHull(points)
船体 = ConvexHull（点）
In [1]: points.ndim
Out[1]: 2
In [2]: points.shape
Out[2]: (10, 2)
In [3]: points
Out[3]:
array([[ 0. , 0. ],
[ 1. , 0.8],
[ 0.9, 0.8],
[ 0.9, 0.7],
[ 0.9, 0.6],
[ 0.8, 0.5],
[ 0.8, 0.5],
[ 0.7, 0.5],
[ 0.1, 0. ],
[ 0. , 0. ]])
As you can see above the points is a numpy with ndim 2.
正如您在上面看到的，这些点是一个带有 ndim 2 的 numpy。
Now I have 2 different numpy array (tp and fp) like this (for example fp)
现在我有 2 个不同的 numpy 数组（tp 和 fp）像这样（例如 fp）
In [4]: fp.ndim
Out[4]: 1
In [5]: fp.shape
Out[5]: (10,)
In [6]: fp
Out[6]:
array([ 0. , 0.1, 0.2, 0.3, 0.4, 0.4,
0.5, 0.6, 0.9, 1. ])
My question is how can I create a 2 dimensional numpy array effectively like points with tp and fp
我的问题是如何像 tp 和 fp 点一样有效地创建一个二维 numpy 数组
采纳答案by ijmarshall
If you wish to combine two 10 element 1-d arrays into a 2-d array np.vstack((tp, fp)).Twill do it. np.vstack((tp, fp))will return an array of shape (2, 10), and the Tattribute returns the transposed array with shape (10, 2) (i.e. with the two 1-d arrays forming columns rather than rows).
如果你想将两个 10 元素的一维数组组合成一个二维数组np.vstack((tp, fp)).T就可以了。np.vstack((tp, fp))将返回一个形状为 (2, 10) 的数组，并且该T属性返回形状为 (10, 2) 的转置数组（即两个一维数组形成列而不是行）。
>>> tp = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> tp.ndim
1
>>> tp.shape
(10,)
>>> fp = np.array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19])
>>> fp.ndim
1
>>> fp.shape
(10,)
>>> combined = np.vstack((tp, fp)).T
>>> combined
array([[ 0, 10],
[ 1, 11],
[ 2, 12],
[ 3, 13],
[ 4, 14],
[ 5, 15],
[ 6, 16],
[ 7, 17],
[ 8, 18],
[ 9, 19]])
>>> combined.ndim
2
>>> combined.shape
(10, 2)
