Convert an irregular to regular precipitation time series
I have an xts series with a year of precipitation data:
str(data_prec) An ‘xts’ object from 2011-01-01 to 2011-12-31 23:55:00 containing: Data: num [1:105125, 1] 0 0 0 0 0 0 0 0 0 0 ... Indexed by objects of class: [POSIXct,POSIXt] TZ: xts Attributes: List of 2 $ tclass: chr [1:2] "POSIXct" "POSIXt" $ tzone : chr ""
Part of data looks like:
2011-12-15 05:15:00, 0 2011-12-15 05:20:00, 0 2011-12-15 05:25:00, 0.1 2011-12-15 05:30:00, 1.2 2011-12-15 05:31:00, 0.2 2011-12-15 05:32:00, 0.6 2011-12-15 05:33:00, 0.1 2011-12-15 05:35:00, 0.1 2011-12-15 05:36:00, 0 2011-12-15 05:37:00, 0.6 2011-12-15 05:40:00, 0 2011-12-15 05:45:00, 0 2011-12-15 05:50:00, 0.1
I need to have my data at each five minutes, by summing the previous data. I've tried to use aggregate, to.minutes5 and merge without success. I don't know what I'm doing wrong. This is the closest way I've reached:
align.time(period.sum(data_prec,endpoints(data_prec,"minutes",k=5)),300)
That gave me:
2011-12-15 05:15:00, 0 2011-12-15 05:20:00, 0 2011-12-15 05:25:00, 0 2011-12-15 05:30:00, 0.1 2011-12-15 05:35:00, 2.1 2011-12-15 05:40:00, 0.7 2011-12-15 05:45:00, 0 2011-12-15 05:50:00, 0 2011-12-15 05:55:00, 0.1 2011-12-15 06:00:00, 0
This is what I'm looking for:
2011-12-15 05:15:00, 0 2011-12-15 05:20:00, 0 2011-12-15 05:25:00, 0.1 2011-12-15 05:30:00, 1.2 2011-12-15 05:35:00, 1.0 2011-12-15 05:40:00, 0.6 2011-12-15 05:45:00, 0 2011-12-15 05:50:00, 0.1 2011-12-15 05:55:00, 0 2011-12-15 06:00:00, 0
Thanks for any suggestion.
