Running maximum of numpy array values

Question

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]) 

I'd want:

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

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 

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.

Answer 1

numpy.maximum.accumulate works for me.

>>> 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]) 

Answer 2

As suggested, there is scipy.maximum.accumulate:

In [9]: x Out[9]: [1, 3, 2, 5, 4]  In [10]: scipy.maximum.accumulate(x) Out[10]: array([1, 3, 3, 5, 5])