{"action":"opened","issue":{"url":"https://api.github.com/repos/giseislab/gismotools/issues/36","labels_url":"https://api.github.com/repos/giseislab/gismotools/issues/36/labels{/name}","comments_url":"https://api.github.com/repos/giseislab/gismotools/issues/36/comments","events_url":"https://api.github.com/repos/giseislab/gismotools/issues/36/events","html_url":"https://github.com/giseislab/gismotools/issues/36","id":98565389,"number":36,"title":"Update Waveform to take advantage of timeseries objects","user":{"login":"CelsoReyes","id":2513248,"avatar_url":"https://avatars.githubusercontent.com/u/2513248?v=3","gravatar_id":"","url":"https://api.github.com/users/CelsoReyes","html_url":"https://github.com/CelsoReyes","followers_url":"https://api.github.com/users/CelsoReyes/followers","following_url":"https://api.github.com/users/CelsoReyes/following{/other_user}","gists_url":"https://api.github.com/users/CelsoReyes/gists{/gist_id}","starred_url":"https://api.github.com/users/CelsoReyes/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/CelsoReyes/subscriptions","organizations_url":"https://api.github.com/users/CelsoReyes/orgs","repos_url":"https://api.github.com/users/CelsoReyes/repos","events_url":"https://api.github.com/users/CelsoReyes/events{/privacy}","received_events_url":"https://api.github.com/users/CelsoReyes/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":{"login":"CelsoReyes","id":2513248,"avatar_url":"https://avatars.githubusercontent.com/u/2513248?v=3","gravatar_id":"","url":"https://api.github.com/users/CelsoReyes","html_url":"https://github.com/CelsoReyes","followers_url":"https://api.github.com/users/CelsoReyes/followers","following_url":"https://api.github.com/users/CelsoReyes/following{/other_user}","gists_url":"https://api.github.com/users/CelsoReyes/gists{/gist_id}","starred_url":"https://api.github.com/users/CelsoReyes/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/CelsoReyes/subscriptions","organizations_url":"https://api.github.com/users/CelsoReyes/orgs","repos_url":"https://api.github.com/users/CelsoReyes/repos","events_url":"https://api.github.com/users/CelsoReyes/events{/privacy}","received_events_url":"https://api.github.com/users/CelsoReyes/received_events","type":"User","site_admin":false},"milestone":null,"comments":0,"created_at":"2015-08-01T22:31:59Z","updated_at":"2015-08-01T22:31:59Z","closed_at":null,"body":"I looked into this, and realize that (on r2012b, on Macbook air) timeseries takes significantly longer than the current implementation.\r\n\r\nI tested with 1 day of data at 100 samples / second\r\n```matlab\r\nnsamp = 100*60*60*24;\r\n\r\nw = waveform('XXXX', 'SHZ', 100, '5/20/2003', 1:nsamp);\r\n\r\nts = timeseries(1:nsamp);\r\nts.setuniformtime('Interval',0.01,'StartTime',datenum('5/20/2003'))\r\nts.Name = '.XXXX..SHZ';\r\n```\r\ntests: \r\n```\r\n>> whos\r\n  Name       Size               Bytes  Class         Attributes\r\n  ts         1x1             69120903  timeseries              \r\n  w          1x1             69124076  waveform                \r\n```\r\nso the size is about the same. good!\r\n```\r\n>> tic;w2 = w .* 2; toc; clear w2\r\nElapsed time is 0.029052 seconds.\r\n>> tic;ts2 = ts .* 2; toc; clear ts2\r\nElapsed time is 0.182587 seconds.\r\n>> tic;w2 = (w .* 2 + 4)/3; toc; clear w2\r\nElapsed time is 0.081250 seconds.\r\n>> tic;ts2 = (ts .* 2 + 4)/3; toc; clear ts2\r\nElapsed time is 0.354160 seconds.\r\n>> \r\n```\r\napparently the built-in timeseries is 5-10 times slower for these basic operations. "}}