autoGoldy: Automated processing of LICOR / IRGA Data

In jtlovell/goldy: Process Time-Series Gas Exchange Data

Description

autoGoldy Define the most stable set of observations in time-series infrared gas exchange data. Currently optimized for LICOR 6400 .rtf data output.

Usage

autoGoldy(filename = NULL, dirname = NULL, trait1 = "Photo",
  trait2 = "Cond", window = 6, verbose = TRUE, weights = c(1, 1, 1, 1),
  output.dir = NULL)

Arguments

filename	The path and name of a file to parse and optimize
trait1	Character string that matches the name of a column in the input dataset. This data will be used for optimization computation
trait2	A (optional) second trait to assist with optimization
window	The size of the window in the sliding window optimization protocol
verbose	Logical, should updates be printed
weights	A numeric vector of length 4. These values indicate the weighting of the slope [1] and coeficient of variation (cv) [2] of trait1 and trait2 [3,4]
...	additional arguments, not currently in use.

Details

This function runs the following pipeline:

• 1. Import and parse rtf LICOR datasets

• 2. Standardize (0-1) and plot the raw data

• 3. Run sliding window analysis to calculate the slope and CV of standardized data

• 4. Find the most stable window

• 5. Plot diagnostics

• 6. Output the optimal data

Value

a single row dataframe that gives the most stable data from the time series data input originally. A single page figure with some information is also printed.

Examples

## Not Run out<-autoGoldy(filename="./data/RO_052714_rr11_h57s", window=4, weights=c(1,1,.5,.5))

jtlovell/goldy documentation built on May 20, 2019, 3:14 a.m.