cis/trans different using cooler vs. cooltools

[biofilos]

Hi. I am using the sample cool file you provide in the notebook tutorial to learn how the cool* environment works.
I was trying to calculate cis/trans contacts by traversing the matrix, like this:

filepath = 'data/Rao2014-GM12878-MboI-allreps-filtered.5kb.cool'
c = cooler.Cooler(filepath)
def allvsall(lst):
    for ix1, i1 in enumerate(lst):
        for ix2, i2 in enumerate(lst[ix1:]):
            yield i1, i2
cis, trans = 0, 0
for c1, c2 in allvsall(c.chromsizes.index):
    print(c1, c2)
    mat = c.matrix(sparse=False, balance=False).fetch(c1, c2)
    counts = np.nansum(np.triu(mat))
    if c1 == c2:
        cis += counts
    else:
        trans += counts

When comparing the cis and trans values from this approach with the ones in the metadata on the cool file, I find that the cis values are the same, but the trans values are different.
When doing the same calculation using cooltools:

from concurrent import futures
with futures.ProcessPoolExecutor(4) as pool:
    cis, total = coverage.get_coverage(c, ignore_diags=0, map=pool.map)
cis_total = cis.sum()
trans_total = total.sum() - cis_total

cis_total and trans_total correspond to what I see in the metadata of the cool file.

I coded the first method as a way of learning how to use the library, which is incredibly slow. However, I expected the results to be consistent with the metadata of the file.
My question is, why do those two methods differ in their values?

[nvictus]

From a quick glance, it looks like you are applying np.triu(mat) even when mat comes from trans. Could that be the issue?

[biofilos]

oh yes, that makes sense. Thanks!
By the way, do you guys have a google group or forum, or something like that?
I realize that github issues is not the best place to post these kinds of questions

thanks again

[nvictus]

Yes, we're on Slack! Join here: https://bit.ly/2UaOpAe