Python 索引错误：布尔索引与维度 0 的索引数组不匹配
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IndexError: boolean index did not match indexed array along dimension 0
提问by Ibe
My code was working fine until I updated Numpy to 1.13.1. Now I get the following error
我的代码运行良好，直到我将 Numpy 更新到 1.13.1。现在我收到以下错误
IndexError: boolean index did not match indexed array along dimension 0; dimension is 5 but corresponding boolean dimension is 4
... which is thrown at this line:
...这是在这一行抛出的：
m = arr[np.diff(np.cumsum(arr) >= sum(arr) * i)]
I can't seem to wrap my head around it. Any suggestions?
我似乎无法绕过它。有什么建议？
Here is my sample code:
这是我的示例代码：
a = [1,2,3,4,5]
l = [0.85,0.90]
s = sorted(a, reverse = False)
arr = np.array(s)
for i in l:
m = arr[np.diff(np.cumsum(arr) >= sum(arr) * i)]
采纳答案by Joe
np.diffis one element smaller than data_array.
np.diff比 data_array 小一个元素。
The shape of the output is the same as a except along axis where the dimension is smaller by n.
输出的形状与 a 相同，除了沿轴的维度小 n。
I am using Numpy 1.11, instead of an IndexErrorI get a VisibleDeprecationWarning. So I guess using an incorrect size is no longer tolerated.
我正在使用 Numpy 1.11，而不是IndexError我得到一个VisibleDeprecationWarning. 所以我想不再容忍使用不正确的大小。
You need to define which behaviour you want, e.g. start at the second element, or remove the last:
您需要定义您想要的行为，例如从第二个元素开始，或删除最后一个：
arr = np.array([1,2,3,4,5])
arr2 = arr[:-1]
m = arr2[np.diff(np.cumsum(arr) >= sum(arr))]
arr3 = arr[1:]
m = arr3[np.diff(np.cumsum(arr) >= sum(arr))]
