R-CMD-check License: GPL v3 CRAN version downloads

Wallace (v2.1.3)

Wallace is a modular platform for reproducible modeling of species niches and distributions, written in R. The application guides users through a complete analysis, from the acquisition of data to visualizing model predictions on an interactive map, thus bundling complex workflows into a single, streamlined interface.

Install Wallace via CRAN and run the application with the following R code.


Development versions can be downloaded from Github with the following R code.


Before using Wallace

Update R and RStudio versions

Please make sure you have installed the latest versions of both R (Mac OS, Windows) and RStudio (Mac OS / Windows: choose the free version).

How to run Maxent with maxent.jar

Wallace v2.1.3 includes two options to run Maxent models: maxnet and maxent.jar. The former, which is an R implementation and fits the model with the package glmnet, is now the default and does not require the package rJava (see Phillips et al. 2017). The latter, which is the Java implementation, runs the maxent() function in the package dismo. This function requires the user to place the maxent.jar file in the /java directory of the dismo package root folder. You can download Maxent here, and locate maxent.jar, which is the Maxent program itself, in the downloaded folder. You can find the directory path to dismo/java by running system.file('java', package="dismo") at the R console. Simply copy maxent.jar and paste it into this folder. If you try to run Maxent in Wallace without the file in place, you will get a warning message in the log window and Maxent will not run.

Potential Issues

rJava and Java versions (just for maxent.jar option)

Wallace uses the rJava package only to run the program maxent.jar. The package rJava will not load properly if the version of Java on your computer (32-bit or 64-bit) does not match that of the R installation you are using. For example, if you are running 64-bit R, please make sure your Java is also 64-bit, or else rJava will be unable to load. Install the latest version of Java here, and 64-bit Windows users should make sure to select “Windows Offline (64-bit)”. There is currently only a 64-bit download for Mac OS. For Mac users running OSX Yosemite and above with problems, see this StackOverflow post for some tips on how to get rJava working again. If you need to install Java for the first time, you can follow these instructions for Mac and Windows.

Problems viewing tables

If for some reason you are unable to view the tables in Wallace, please install (force if necessary) the development version of htmlwidgets by running this code: devtools::install_github("ramnathv/htmlwidgets"). You should be able to view tables now.

Windows Users: PDF download of session code

If PDF downloading of session code is not working for you, please follow the following instructions, taken from here: - Step 1: Download and Install MiKTeX from http://miktex.org/2.9/setup - Step 2: Run Sys.getenv("PATH") in R studio. This command returns the path where Rstudio is trying to find pdflatex.exe. In Windows (64-bit), it should return “C:Files.exe”. If pdflatex.exe is not located in this location Rstudio gives this error code 41. - Step 3: To set this path variable run: Sys.setenv(PATH=paste(Sys.getenv("PATH"),"C:/Program Files/MiKTeX 2.9/miktex/bin/x64/",sep=";")).

Windows Users: Only for Github installation

If you are using Windows, please download and install RTools before installing the devtools package. After you install RTools, please make sure you add “C:” to your PATH variable (instructions here). Additionally, when using devtools on Windows machines, there is a known bug that sometimes results in the inability to download all package dependencies. If this happens to you, please install the packages and their dependencies directly from CRAN.

Any other problems with install_github()

Although the recommended way to install is through CRAN, if you are trying to install the Github version and are having problems, follow these steps. 1. Download the zip file from the repository page. 2. Unzip and open the wallace.Rproj file in RStudio. 3. In the right-hand pane, click Build, then Install & Restart. 4. Type run_wallace() in the console and press Enter.