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README.Rmd
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---
bibliography: /home/persican/Documents/library.bib
output:
github_document:
html_preview: true
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
fig.path = "inst/images/README-"
)
```
```{r setup, echo = FALSE}
library(ggplot2)
theme_set(theme_bw(base_size = 12, base_family = "Open Sans"))
```
## cdom [](https://travis-ci.org/PMassicotte/cdom) [](https://ci.appveyor.com/project/PMassicotte/cdom) [](http://www.gnu.org/licenses/gpl-2.0.html) [](http://cran.rstudio.com/package=cdom) [](http://www.r-pkg.org/pkg/cdom)
The **cdom** package implements various functions used to model and calculate metrics from absorption spectra of chromophotic dissolved organic matter (CDOM).
This package provides:
1. Simple wrappers to calculate common metrics found in the literature.
+ The **spectral curve** [@Loiselle2009].
+ The **slope ratio (Sr)** [@Helms2008].
+ The **spectral slope (S)** [@Jerlov1968; @Lundgren1976; @Bricaud1981].
2. The function to use the **Gaussian decomposition approach** proposed in Massicotte and Markager, (2015).
The package can be installed using the following command.
```{r install, eval = FALSE}
devtools::install_github("PMassicotte/cdom")
```
Please note that this is a developing version of the package for testing only. Please fill an issue when you find bugs.
All functions from the package start with the `cdom_` prefix.
```{r}
library(cdom)
ls("package:cdom")
```
# Examples
## The spectral slope (S)
The `cdom_fit_exponential()` function fits an exponential curve to CDOM data using the simple model proposed by @Jerlov1968, @Lundgren1976, @Bricaud1981.
```tex
a(\lambda) = a(\lambda0)e^{-S(\lambda - \lambda0)} + K
```
```{r exponential}
library(ggplot2)
library(cdom)
data("spectra")
fit <- cdom_exponential(wl = spectra$wavelength,
absorbance = spectra$spc3,
wl0 = 350,
startwl = 190,
endwl = 900)
coef(fit)
p <- plot(fit)
p
```
## The slope ratio (SR)
The `cdom_slope_ratio()` function calculates the slope ratio (S<sub>R</sub>) which is defined as: S<sub>275-295</sub>/S<sub>350-400</sub>. See @Helms2008 for detailed information.
```{r sr}
library(cdom)
data("spectra")
cdom_slope_ratio(spectra$wavelength, spectra$spc1)
```
## The spectral curve
The `cdom_spectral_curve()` function generates the spectral curve using the slope of the linear regression between the natural log absorption spectrum and wavelengths over a sliding window of 21 nm interval (default) at 1 nm resolution. See @Loiselle2009 for detailed information.
```{r spectral_curve}
library(cdom)
data("spectra")
res <- cdom_spectral_curve(wl = spectra$wavelength,
absorbance = spectra$spc10,
interval = 21,
r2threshold = 0.98) # Maybe to restrictive...
ggplot(res, aes(x = wl, y = s)) +
geom_point() +
geom_line() +
xlab("Wavelength (nm)") +
ylab(expression(paste("Spectral slope (", nm ^ {-1}, ")")))
```
## Using the pipe operator
```{r}
library(dplyr)
library(tidyr)
data(spectra)
spectra <- spectra %>%
gather(sample, absorption, starts_with("spc")) %>%
group_by(sample) %>%
nest() %>%
mutate(model = purrr::map(data, ~cdom_exponential(.$wavelength, .$absorption, wl0 = 350, startwl = 190, endwl = 900)))
#spectra %>% unnest(model %>% purrr::map(~.$data$.fitted))
```
# Data
A total 25 absorption spectra are provided in the package.
```{r data}
library(ggplot2)
library(tidyr)
data("spectra")
spectra <- gather(spectra, sample, absorption, -wavelength)
ggplot(spectra, aes(x = wavelength, y = absorption, group = sample)) +
geom_line(size = 0.1) +
xlab("Wavelength (nm)") +
ylab(expression(paste("Absorption (", m ^ {-1}, ")")))
```
# How to cite the package
```{r}
citation("cdom")
```
# References