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I have an unsorted array of integers, and I want to fill all decreasing numbers with the previous larger value.

Example:

>>> np.array([10, -1, 2, 5, 19, 5, 5, 4, 10, 2]) [10 10 10 10 19 19 19 19 19 19] >>> np.array([0, 3, 5, 4, 3, 7, 2] [0 3 5 5 5 7 7]

I've come up with this solution, but it has to be a more elegant way of doing it.

def func(a): a = a.copy() for i in range(1, a.shape[0]): if a[i] < a[i-1]: a[i] = a[i-1] return a

Any suggestions?

I have looked at two similar questions, but I am unable to modify the examples to make them work the way I intend.

  1. If value is greater than the previous replace with previous in Pandas

  2. Most efficient way to forward-fill NaN values in numpy array

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You can use numpy.maximum.accumulate:

np.maximum.accumulate([10, -1, 2, 5, 19, 5, 5, 4, 10, 2]) # array([10, 10, 10, 10, 19, 19, 19, 19, 19, 19]) np.maximum.accumulate([0, 3, 5, 4, 3, 7, 2]) # array([0, 3, 5, 5, 5, 7, 7])
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Of course it had to be this simple... thanks, man!

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