SWMPr (version 2.1.0)

aggreswmp: Aggregate swmpr data

Description

Aggregate swmpr data by specified time period and method

Usage

aggreswmp(swmpr_in, ...)

## S3 method for class 'swmpr':
aggreswmp(swmpr_in, by, FUN = function(x) mean(x, na.rm =
  TRUE), params = NULL, aggs_out = FALSE, na.action = na.pass, ...)

Arguments

swmpr_in

input swmpr object

...

additional arguments passed to other methods

by

chr string of time period for aggregation one of 'years', 'quarters', 'months', 'weeks', 'days', or 'hours'

FUN

aggregation function, default mean with na.rm = TRUE

params

names of parameters to aggregate, default all

aggs_out

logical indicating if data.frame is returned of raw data with datetimestamp formatted as aggregation period, default FALSE

na.action

function for treating missing data, default na.pass. See the documentation for aggregate for options.

Value

• Returns an aggregated swmpr object. QAQC columns are removed if included with input object.

concept

analyze analyze

Details

The function aggregates parameter data for a swmpr object by set periods of observation and a user-supplied function. It is most useful for aggregating noisy data to evaluate trends on longer time scales, or to simply reduce the size of a dataset. Data can be aggregated by 'years', 'quarters', 'months', 'weeks', 'days', or 'hours' for the supplied function, which defaults to the mean. A swmpr object is returned for the aggregated data, although the datetimestamp vector will be converted to a date object if the aggregation period is a day or longer. Days are assigned to the date vector if the aggregation period is a week or longer based on the round method for IDate objects. This approach was used to facilitate plotting using predefined methods for Date and POSIX objects. The method of treating NA values for the user-supplied function should be noted since this may greatly affect the quantity of data that are returned (see the examples). Finally, the default argument for na.action is set to na.pass for swmpr objects to preserve the time series of the input data.

See Also

aggregate

Examples

## get data, prep
data(apacpwq)
dat <- apacpwq
swmpr_in <- subset(qaqc(dat), rem_cols = TRUE)

## get mean DO by quarters
aggreswmp(swmpr_in, 'quarters', params = c('do_mgl'))

## get variance of DO by years, remove NA when calculating variance
## omit NA data in output
fun_in <- function(x)  var(x, na.rm = TRUE)
aggreswmp(swmpr_in, FUN = fun_in, 'years')