运行numpy数组值的最大值 [英] Running maximum of numpy array values

问题描述

我需要一种快速的方法来保持numpy数组的运行最大值.例如，如果我的数组是:

I need a fast way to keep a running maximum of a numpy array. For example, if my array was:

x = numpy.array([11,12,13,20,19,18,17,18,23,21])

我想要:

numpy.array([11,12,13,20,20,20,20,20,23,23])

很明显，我可以做一个小循环:

Obviously I could do this with a little loop:

def running_max(x):
    result = [x[0]]
    for val in x:
        if val > result[-1]:
            result.append(val)
        else:
            result.append(result[-1])
    return result

但是我的数组有成千上万的条目，我需要多次调用它.似乎必须要有一个小技巧才能删除循环，但我似乎找不到任何有效的方法.替代方法是将此代码编写为C扩展名，但似乎我会重新发明轮子.

But my arrays have hundreds of thousands of entries and I need to call this many times. It seems like there's got to be a numpy trick to remove the loop, but I can't seem to find anything that will work. The alternative will be to write this as a C extension, but it seems like I'd be reinventing the wheel.

推荐答案

numpy.maximum.accumulate为我工作.

>>> import numpy
>>> numpy.maximum.accumulate(numpy.array([11,12,13,20,19,18,17,18,23,21]))
array([11, 12, 13, 20, 20, 20, 20, 20, 23, 23])

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