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README.Rmd
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---
output:
github_document
---
<!--
README.md is generated from README.Rmd. Please edit that file
#knitr::knit("README.Rmd")
rmarkdown::render("README.Rmd")
maybe clear cache before
-->
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE
, comment = "#>"
, fig.path = "README-"
)
```
[](http://cran.r-project.org/package=REddyProc)
[](https://travis-ci.org/bgctw/REddyProc)
## Overview
`REddyProc` package supports processing (half)hourly data from Eddy-Covariance sensors.
There is an online-formular to use the functionality of the package including
description at
<https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWeb>.
## Installation
```{r, eval = FALSE}
# Release stable version from CRAN
install.packages("REddyProc")
# The development version from GitHub using devtools:
# install.packages("devtools")
devtools::install_github("bgctw/REddyProc")
```
The REddyProc~package requires a quite recent
versions of the tidyverse packages. On encountering problems on installations
with older versions should run the following code before installing REddyProc.
```{r, eval = FALSE}
install.packages("tidyverse")
update.packages(oldPkgs="dplyr")
```
## Usage
A simple example performs Lookuptable-based gapFilling of
Net-Ecosystem-Exchange (NEE) and plotting a fingerprint plot of the filled
values.
```{r example, results='hide', message=FALSE}
library(REddyProc)
#+++ Input data from csv (example needs to be downloaded)
examplePath <- getExamplePath('Example_DETha98.txt', isTryDownload = TRUE)
if (length(examplePath)) {
EddyData <- fLoadTXTIntoDataframe(examplePath)
} else {
warning(
"Could not find example text data file."
," In order to execute this example code,"
," please, allow downloading it from github. "
," Type '?getExamplePath' for more information.")
# using RData version distributed with the package instead
EddyData <- Example_DETha98
}
#+++ If not provided, calculate VPD from Tair and rH
EddyData$VPD <- fCalcVPDfromRHandTair(EddyData$rH, EddyData$Tair)
#+++ Add time stamp in POSIX time format
EddyDataWithPosix <- EddyData %>%
filterLongRuns("NEE") %>%
fConvertTimeToPosix('YDH', Year = 'Year', Day = 'DoY', Hour = 'Hour')
#+++ Initalize R5 reference class sEddyProc for processing of eddy data
#+++ with all variables needed for processing later
EProc <- sEddyProc$new(
'DE-Tha', EddyDataWithPosix, c('NEE','Rg','Tair','VPD', 'Ustar'))
#Location of DE-Tharandt
EProc$sSetLocationInfo(LatDeg = 51.0, LongDeg = 13.6, TimeZoneHour = 1)
#
#++ Fill NEE gaps with MDS gap filling algorithm (without prior ustar filtering)
EProc$sMDSGapFill('NEE', FillAll = FALSE)
#
#++ Export gap filled and partitioned data to standard data frame
FilledEddyData <- EProc$sExportResults()
#
#++ Example plots of filled data to screen or to directory \plots
EProc$sPlotFingerprintY('NEE_f', Year = 1998)
```
Further examples are in
[vignette(useCase)](https://github.com/bgctw/REddyProc/blob/master/vignettes/useCase.md)
and
[vignette(DEGebExample)](https://github.com/bgctw/REddyProc/blob/master/vignettes/DEGebExample.md)
and further md-files of the
[vignettes directory](https://github.com/bgctw/REddyProc/blob/master/vignettes).
## Docker images
Docker images are provided that comprise rstudio, rocker/tidyverse, and REddyProc.
There are different version for the latest push to github, for the version on CRAN and for specific tags starting
from 1.1.4.
- bgctw/reddyproc:latest
- bgctw/reddyproc_cran
- bgctw/reddyproc:`tag`
They are usually run with installed docker by typing at a shell:
```
docker run --rm -p 8787:8787 <imagename>
```
Then the loading url `localhost:8787` in a browser window should bring up RStudio
(default username and password are both rstudio), where
you can type the above usage example.
## Reference
The methodology and benchmark of `REddyProc` 1.1.3 is described
in the following paper:
Wutzler, T., Lucas-Moffat, A., Migliavacca, M., Knauer, J., Sickel, K., Šigut, L., Menzer, O., and Reichstein, M. (2018): Basic and extensible post-processing of eddy covariance flux data with REddyProc, Biogeosciences, 15, 5015-5030, [https://doi.org/10.5194/bg-15-5015-2018](https://doi.org/10.5194/bg-15-5015-2018).