{"action":"opened","issue":{"url":"https://api.github.com/repos/fidelram/deepTools/issues/450","repository_url":"https://api.github.com/repos/fidelram/deepTools","labels_url":"https://api.github.com/repos/fidelram/deepTools/issues/450/labels{/name}","comments_url":"https://api.github.com/repos/fidelram/deepTools/issues/450/comments","events_url":"https://api.github.com/repos/fidelram/deepTools/issues/450/events","html_url":"https://github.com/fidelram/deepTools/issues/450","id":192294607,"number":450,"title":"multiBigwigSummary: get sum value instead of average per bin","user":{"login":"AlicePsyche","id":13633282,"avatar_url":"https://avatars.githubusercontent.com/u/13633282?v=3","gravatar_id":"","url":"https://api.github.com/users/AlicePsyche","html_url":"https://github.com/AlicePsyche","followers_url":"https://api.github.com/users/AlicePsyche/followers","following_url":"https://api.github.com/users/AlicePsyche/following{/other_user}","gists_url":"https://api.github.com/users/AlicePsyche/gists{/gist_id}","starred_url":"https://api.github.com/users/AlicePsyche/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/AlicePsyche/subscriptions","organizations_url":"https://api.github.com/users/AlicePsyche/orgs","repos_url":"https://api.github.com/users/AlicePsyche/repos","events_url":"https://api.github.com/users/AlicePsyche/events{/privacy}","received_events_url":"https://api.github.com/users/AlicePsyche/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2016-11-29T14:23:10Z","updated_at":"2016-11-29T14:23:10Z","closed_at":null,"body":"Hi, \r\n\r\nI have multiple bigwig files(100bp bin) to compare but instead of average value, I prefer to get sum value on 2K bin. Is it possible to use multiBigwigSummary? I am new to python, I think in your getScorePerBigWigBin.py script, the following code do the average calculation:\r\n```\r\n103             for exon in reg:\r\n104                 weights.append(exon[1] - exon[0])\r\n105                 score = bwh.stats(chrom, exon[0], exon[1])\r\n106\r\n107                 if score is None or score == [None] or np.isnan(score[0]):\r\n108                     score = [np.nan]\r\n109                 scores.extend(score)\r\n110             avgReadsArray.append(np.average(scores, weights=weights))\r\n```\r\n\r\nCan I simply change `np.average` to `np.sum` ? \r\n\r\nThanks for your help.\r\n"}}
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