DTSg (version 0.6.0)

aggregate.DTSg: Aggregate Values

Description

Applies a temporal aggregation level function to the .dateTime column of a DTSg object and aggregates its values column-wise to the function's temporal aggregation level utilising one or more provided summary functions. Additionally, it sets the object's aggregated field to TRUE. See DTSg for further information.

Usage

# S3 method for DTSg
aggregate(
  x,
  funby,
  fun,
  ...,
  cols = self$cols(class = "numeric"),
  n = FALSE,
  ignoreDST = FALSE,
  clone = getOption("DTSgClone")
)

Arguments

x

A DTSg object (S3 method only).

funby

One of the temporal aggregation level functions described in TALFs or a user defined temporal aggregation level function. See details for further information.

fun

A summary function, list of summary functions or character vector specifying summary functions applied column-wise to all the values of the same temporal aggregation level, for instance, mean, list(min = min, max = max) or c(sd = "sd", var = "var"). A list or character vector must have names in case more than one summary function is provided. The method can benefit from data.table's GForce optimisation in case a character vector is used. The return value(s) must be of length one.

…

Further arguments passed on to fun.

cols

A character vector specifying the columns to aggregate.

n

A logical specifying if a column named .n giving the number of values per temporal aggregation level is added. See details for further information.

ignoreDST

A logical specifying if day saving time is ignored during aggregation. See details for further information.

clone

A logical specifying if the object is modified in place or if a clone (copy) is made beforehand.

Value

Returns an aggregated DTSg object.

Details

User defined temporal aggregation level functions have to return a POSIXct vector of the same length as the time series and accept two arguments: a POSIXct vector as its first and a list with helper data as its second. This list in turn contains the following named elements:

• timezone: Same as timezone field. See DTSg for further information.

• ignoreDST: Same as ignoreDST argument.

• periodicity: Same as periodicity field. See DTSg for further information.

• na.status: Same as na.status field. See DTSg for further information.

Depending on the number of columns to aggregate, the .n column contains different counts:

• One column: The counts are calculated from the value column without any missing values. This means that missing values are always stripped regardless of the value of a possible na.rm argument.

• More than one column: The counts are calculated from the .dateTime column including all missing values.

ignoreDST tells a temporal aggregation level function if it is supposed to ignore day saving time while forming new timestamps. This can be a desired feature for time series strictly following the position of the sun (such as hydrological time series). Doing so ensures that diurnal variations are preserved and all intervals are of “correct” length, however, a possible limitation might be that the day saving time shift is invariably assumed to be exactly one hour long. This feature requires that the periodicity of the time series is recognised and is supported by the following temporal aggregation level functions of the package:

• byY_____

• byYQ____

• byYm____

• byYmd___

• by_Q____

• by_m____

• by___H__

See Also

DTSg, TALFs, list, GForce, cols, POSIXct

Examples

# NOT RUN {
# new DTSg object
x <- DTSg$new(values = flow)

# mean yearly river flows
## R6 method
x$aggregate(funby = byY_____, fun = "mean", na.rm = TRUE)

## S3 method
aggregate(x = x, funby = byY_____, fun = "mean", na.rm = TRUE)

# standard deviation and variance of river flows per quarter
## R6 method
x$aggregate(funby = byYQ____, fun = c(sd = "sd", var = "var"), na.rm = TRUE)

## S3 method
aggregate(x = x, funby = byYQ____, fun = c(sd = "sd", var = "var"), na.rm = TRUE)

# }