create_custom_interpolation: Reduces the data to a specified temporal resolution

In KiranLDA/PAMLr: Suite Of Functions For Manipulating Pressure, Activity, Magnetism, Temperature And Light Data In R

Reduces the data to a specified temporal resolution

Description

This function takesthe typical PAM_data input, which is a nested list of different sensor data, all formatted at different time resolutions. By specifying a particular sensor, all data are formatted at the same temporal resolution as this data. By default, the median of data with smaller temporal resolution are kept, and data are interpolated.

Usage

create_custom_interpolation(dta, varint, interp = TRUE, summary = "median")

Arguments

dta	raw pam data see ⁠data(bee_eater⁠ for example
varint	the variable of interest.Sipprots c("pressure","light","acceleration","temperature","magnetic"). For instance if all other variables should be summarised at the same temporal resolution as this specified variable.
interp	Default TRUE. Whether or not to replace NAs with interpolated values
summary	Can be "sum", "median" or "none". What type of summary variable to give when condensing data -

Value

reduced/summarised and interpolated dataset

Examples

## Not run: 
data(bee_eater)
PAM_data = bee_eater

start = as.POSIXct("2015-08-01","%Y-%m-%d", tz="UTC")
end = as.POSIXct("2016-06-21","%Y-%m-%d", tz="UTC")
PAM_data = create_crop(PAM_data, start, end)

reduced_dta = create_custom_interpolation(PAM_data , "pressure", interp = FALSE)
head(reduced_dta)

reduced_dta = create_custom_interpolation(PAM_data , "act", interp = FALSE)
head(reduced_dta)

## End(Not run)

KiranLDA/PAMLr documentation built on April 5, 2025, 6:12 a.m.