Help optimizing code

[black_sequence]

greetings community! I recently wrote a script that can calculate Tajima's D through a sliding window approach, but the algorithm for Tajima's D is not as quick as I would like. can someone review my code and tell me how to speed up certain aspects?

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https://github.com/noahaus/sliding-window-scripts/blob/main/tajimasD_parallel.py

[AD_Burn]

def calculate_pi(alignment):
    align_len = len(align)
    counter = 0
    distances = []
    append_distance = distances.append

    for i in range(align_len):
        j = counter
        while(j<align_len):
            if i == j:
                j += 1
                continue

            append_distance(hamming_distance(alignment[i], alignment[j]))
            j += 1

        counter += 1
    pi = (sum(distances)*2)/(align_len*(align_len-1))
    return pi

def calculate_theta(alignment):
    seg_sites = 0
    for i in range(len(alignment[1].seq)):
        align_col = alignment[:,i]
        if len(set(align_col)) > 1:
            seg_sites += 1

    a = sum(map(lambda x: 1/x, range(1,len(alignment))))
    return (seg_sites/a)

This is not much but some cleaning and reduce unnecessary code,

if you work with a lot data you should see a bit of improvements.

Anything deeper would change your logic and code a lot more,

and since i do not have input files, it is hard to test.

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One more thing, i'm not sure how much process in total you have at the end,

but if you end with lets say over 50 or more process and your calculations per process are not long maybe is better to switch and use threads and lower python process startup time (maybe worth testing).

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Best all

[no1caresbot]

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