I have used your code to try and count the number of days per year that a fire weather index is above or below a set threshold. For the most part, the code worked well, but I have noticed that there are some errors in the total counts. For example, (total days meeting or exceeding threshold) + (total days below threshold) does not equal the total number of days in a year. And similarly, when looking at the graphed data, I count x number of distinct periods (above or below threshold), but the results of the code indicate there are (x-1) distinct periods.

I have essentially used your exact code, so I’m wondering if you may have any insight into this problem or have encountered similar problems in your own program.

Thanks!

The short python snippet below counts transitions from one result to
the next. The second sequence is far more extreme than the first in
this regard, as a head is always followed by a tail and a tail is most
often followed by a head.

import numpy as np

r1 = “HTTTTHHTHHHHTTHHHHTT”
r2 = “HTHTHTHTHTHTTHTHTTTH”

def transition_freqs(rr):
rr = np.where(np.array(list(rr)) == “H”, 1, 0)
freqs = np.zeros((2, 2), dtype=float)
for last, cur in zip(rr[:-1], rr[1:]):
freqs[last, cur] += 1
return freqs / freqs.sum(0)[None, :]

print(transition_freqs(r1).round(2))
print(transition_freqs(r2).round(2))

[[0.56 0.3 ]
[0.44 0.7 ]]
[[0.27 1. ]
[0.73 0. ]]

So my bet is on the second sequence to be the one made up.

thanks

How does your data look like – could you be more specific?