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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$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
[](https://travis-ci.org/bgctw/RespChamberProc)
<!--
[](http://cran.r-project.org/package=REddyProc)
# From CRAN
install.packages("logitnorm")
# Or the the development version from GitHub:
-->
## Overview
`RespChamberProc` package supports deriving gas fluxes from a time series of gas
concentrations in a chamber.
## Installation
```{r, eval = FALSE}
install.packages( # dependencies from CRAN
c("rlang", "changepoint", "nlme", "segmented", "tibble", "dplyr", "purrr"))
# install.packages("devtools")
devtools::install_github("bgctw/RespChamberProc")
```
<!--
-->
## Usage
See the [package vignettes](../../tree/master/vignettes) for an introduction.
A simple example estimates photosynthesis (negative CO2 flux into the
light chamber) in units micromol/second from CO2 concentration data in ppm.
```{r example}
library(RespChamberProc)
#?RespChamberProc
ds <- chamberLoggerEx1s # example data with the package
ds$Pa <- chamberLoggerEx1s$Pa * 1000 # convert kPa to Pa
ds$CO2_dry <- corrConcDilution(ds) # correct for water vapour
resFit <- calcClosedChamberFlux(
ds
, colConc = "CO2_dry", colTime = "TIMESTAMP"
, colTemp = "TA_Avg", colPressure = "Pa" # Temperature in K, Pressure in Pa
, volume = 1, area = 1 # chamber dimensions m3 and m2
)
dplyr::select(resFit ,c("flux","sdFlux"))
plotResp(ds, resFit, label = "Example Series")
```