interp2length: Interpolate regularly sampled data to increase its sampling...
In tagtools: Work with Data from High-Resolution Biologging Tags

interp2length

R Documentation

Interpolate regularly sampled data to increase its sampling rate and match its length to another variable.

Description

This function is used to reduce the time span of data by cropping out any data that falls before and after two time cues.

Usage

interp2length(X, Z, fs_in = NULL, fs_out = NULL, n_out = NULL)

Arguments

`X`	A sensor list, vector, or matrix. If x is or contains matrix, each column is treated as an independent signal.
`Z`	is a sensor structure, vector or matrix whose sampling rate and length is to be matched.
`fs_in`	is the sampling rate in Hz of the data in X. This is only needed if X is not a sensor structure.
`fs_out`	is the required new sampling rate in Hz. This is only needed if Z is not given.
`n_out`	is an optional length for the output data. If n_out is not given, the output data length will be the input data length * fs_out/fs_in.

Value

Y is a sensor structure, vector or matrix of interpolated data with the same number of columns as X.

Examples

         plott_base(X = list(harbor_seal$P), fsx = 5)
         P_dec <- decdc(harbor_seal$P, 5)
         P_interp <- interp2length(X = P_dec, Z = harbor_seal$A)
         plott_base(X = list(P_interp$data), fsx = 1)

tagtools documentation built on June 28, 2024, 5:07 p.m.