smoother: Smooth swmpr data

In fawda123/SWMPr: Retrieving, Organizing, and Analyzing Estuary Monitoring Data

Smooth swmpr data

Description

Smooth swmpr data with a moving window average

Usage

smoother(x, ...)

## Default S3 method:
smoother(x, window = 5, sides = 2, ...)

## S3 method for class 'swmpr'
smoother(x, params = NULL, ...)

Arguments

x	input object
...	arguments passed to or from other methods
window	numeric vector defining size of the smoothing window, passed to filter
sides	numeric vector defining method of averaging, passed to filter
params	is chr string of swmpr parameters to smooth, default all

Details

The smoother function can be used to smooth parameters in a swmpr object using a specified window size. This method is a simple wrapper to filter. The window argument specifies the number of observations included in the moving average. The sides argument specifies how the average is calculated for each observation (see the documentation for filter). A value of 1 will filter observations within the window that are previous to the current observation, whereas a value of 2 will filter all observations within the window centered at zero lag from the current observation. The params argument specifies which parameters to smooth.

Value

Returns a filtered swmpr object. QAQC columns are removed if included with input object.

See Also

filter

Examples

## import data
data(apadbwq)
swmp1 <- apadbwq

## qaqc and subset imported data
dat <- qaqc(swmp1)
dat <- subset(dat, subset = c('2012-07-09 00:00', '2012-07-24 00:00'))

## filter
test <- smoother(dat, window = 50, params = 'do_mgl')

## plot to see the difference
plot(do_mgl ~ datetimestamp, data = dat, type = 'l')
lines(test, select = 'do_mgl', col = 'red', lwd = 2)

fawda123/SWMPr documentation built on Aug. 20, 2023, 3:13 p.m.