knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The goal of mxsrquick is to is to make MixSIAR project run quicker
You can install the development version of stepurr from GitHub with:
# install.packages("devtools") # devtools::install_github("mncube/mxsrquick")
This is a basic example which shows you how to solve a common problem:
library(mxsrquick) #Create a dataframe which mimics isospace source data iso_data <- data.frame(iso_a = c(2.2, 4.4, 3.3, 5.1, 3.4), iso_b = c(1.6, 3.9, 5.2, 4.2, 3.7), prot = c("bug", "bug", "bug", "plant", "plant")) #Create an isospace plot using source groups' means and standard deviations #Use tdf1 and tdf2 to correct for trophic discrimination factors source_biplot(data = iso_data, group = prot, var1 = iso_a, var2 = iso_b, tdf1 = c(2, 1), tdf2 = c(1, 1), x_lab = "A", y_lab = "B")
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