A simple Numpy translation of your Matlab code is this:
import numpy as np
v = np.array([1., 1., 1., np.nan, 1., 1., 1., 1., np.nan, 1.])
n = np.isnan(v)
a = ~n
c = np.cumsum(a)
d = np.diff(np.concatenate(([0.], c[n])))
v[n] = -d
np.cumsum(v)
Executing this code returns the result array([ 1., 2., 3., 0., 1., 2., 3., 4., 0., 1.])
. This solution will only be as valid as the original one, but maybe it will help you come up with something better if it isn't sufficient for your purposes.