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author | Muriithi Frederick Muriuki | 2021-07-20 15:12:38 +0300 |
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committer | Muriithi Frederick Muriuki | 2021-07-20 15:12:38 +0300 |
commit | 8dc60fd93b9eab9fd655a1f0c23ed038d4ac3eed (patch) | |
tree | 94305f9b648bffd99116ae28f93fadc52ed09392 /gn3/computations | |
parent | 5a8f4f3c85be4645c9a918bc25397170f4370341 (diff) | |
download | genenetwork3-8dc60fd93b9eab9fd655a1f0c23ed038d4ac3eed.tar.gz |
Implement the correlation function
Issue:
https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/clustering.gmi
* Implement the correlation computation function, such that it passes the
tests created previously.
Diffstat (limited to 'gn3/computations')
-rw-r--r-- | gn3/computations/correlations2.py | 33 |
1 files changed, 32 insertions, 1 deletions
diff --git a/gn3/computations/correlations2.py b/gn3/computations/correlations2.py index 193f646..6c456db 100644 --- a/gn3/computations/correlations2.py +++ b/gn3/computations/correlations2.py @@ -1,4 +1,35 @@ +from math import sqrt +from functools import reduce ## From GN1: mostly for clustering and heatmap generation +def items_with_values(dbdata, userdata): + """Retains only corresponding items in the data items that are not `None` values. +This should probably be renamed to something sensible""" + def both_not_none(item1, item2): + if (item1 is not None) and (item2 is not None): + return (item1, item2) + return None + def split_lists(accumulator, item): + return [accumulator[0] + [item[0]], accumulator[1] + [item[1]]] + return reduce( + split_lists, + filter(lambda x: x is not None, map(both_not_none, dbdata, userdata)), + [[], []]) + def compute_correlation(dbdata, userdata): - return tuple() + x, y = items_with_values(dbdata, userdata) + if len(x) < 6: + return (0.0, len(x)) + meanx = sum(x)/len(x) + meany = sum(y)/len(y) + def cal_corr_vals(acc, item): + xitem, yitem = item + return [ + acc[0] + ((xitem - meanx) * (yitem - meany)), + acc[1] + ((xitem - meanx) * (xitem - meanx)), + acc[2] + ((yitem - meany) * (yitem - meany))] + xyd, sxd, syd = reduce(cal_corr_vals, zip(x, y), [0.0, 0.0, 0.0]) + try: + return ((xyd/(sqrt(sxd)*sqrt(syd))), len(x)) + except ZeroDivisionError as zde: + return(0, len(x)) |