Combine swmpr data types for a station by common time series
Usage
comb(...)
# S3 method for class 'swmpr'
comb(..., timestep = 15, differ = NULL, method = "union")
# Default S3 method
comb(..., date_col, timestep = 15, differ = NULL, method = "union")
Arguments
- ...
input time series data objects, from one to many
- timestep
numeric value of time step to use in minutes, passed to
setstep
- differ
numeric value defining buffer for merging time stamps to standardized time series, passed to
setstep
- method
chr string indicating method of combining data. Use
'union'
for all dates as continuous time series or'intersect'
for only areas of overlap. If input is aswmpr
object, a'station'
name can be used to combine by the date range of a given station, assuming there is overlap with the second station. A numeric value can be supplied for the default method that specifies which data object to use for the date range based on order of execution in the function call.- date_col
chr string indicating name of the date column
Details
The comb
function is used to combine multiple swmpr objects into a single object with a continuous time series at a given step. The timestep
function is used internally such that timestep
and differ
are accepted arguments for comb
.
The function requires one or more swmpr objects as input as separate, undefined arguments. The remaining arguments must be called explicitly since an arbitrary number of objects can be used as input. In general, the function combines data by creating a master time series that is used to iteratively merge all swmpr objects. The time series for merging depends on the value passed to the method
argument. Passing 'union'
to method
will create a time series that is continuous starting from the earliest date and the latest date for all input objects. Passing 'intersect'
to method
will create a time series that is continuous from the set of dates that are shared between all input objects. Finally, a seven or eight character station name passed to method
will merge all input objects based on a continuous time series for the given station. The specified station must be present in the input data. Currently, combining data types from different stations is not possible, excluding weather data which are typically at a single, dedicated station.