How to add conditional counter to numpy array?

Question

I want to replace a numpy array values with a counter, if they meet a condition.

'Arr' is a NxM numpy array. I would like 'ArrCount' (NxM) to have values from i=1 to i=n, if the value in 'Arr' doesn't equal 65535. for large arrays, iterating over each cell takes a long time.

import numpy as np
ArrCount= np.empty_like(Arr)
    i = 1
    for index, x in np.ndenumerate(Arr):
        if x!= 65535:
            ArrCount[index] = i
            i += 1

I've also tries working with mask and Boolean arrays, but this doesn't improve the iterating time. Is there a better way of doing this?

Sorry it isn't clear to me exactly what you want to do. Can you supply an example input and expected output? — tomjn
– tomjn, Commented Sep 3, 2019 at 12:03

Joe · Accepted Answer · 2019-09-03 12:59:25Z

2

Try to avoid for-loops at all when you use Numpy. Here is a vectorized approach to do something like that:

import numpy as np

a = np.random.rand(10)

# boolean array, other operators also work (>=, ==, <=)
is_larger = a > 0.5

# how many elements fit the criteria?
count = np.count_nonzero(is_larger)

# create an ascending array that long
asc = np.arange(count)

# boolean indexing to assign the values to the correct places
a[is_larger] = asc

print(a)

answered Sep 3, 2019 at 12:59

Joe

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1 Comment

Yalf Over a year ago

Thanks This works great in a much more efficient way. i knew i needed to avoid looping just didn't know how.

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