wallaceEcoMod · danflop · Nov 20, 2024 · Nov 19, 2024 · Nov 19, 2024 · Nov 19, 2024
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: wallace
-Version: 2024.09.18
-Date: 2024-09-18
+Version: 2024.11.18
+Date: 2024-11-18
 Title: A Modular Platform for Reproducible Modeling of Species Niches 
     and Distributions
 Description: The 'shiny' application Wallace is a modular platform for 
@@ -44,6 +44,7 @@ Imports:
     knitcitations,
     leafem,
     leaflet.extras (>= 1.0.0),
+    lwgeom, 
     magrittr,
     maskRangeR,
     markdown,
@@ -58,6 +59,7 @@ Imports:
     shinyWidgets (>= 0.6.0),
     spocc (>= 1.2.0),
     spThin,
+    stars,
     terra (>= 1.6-7),
     zip
 Suggests: 
@@ -80,7 +82,6 @@ Suggests:
     rgbif (>= 3.3.0),
     sf,
     sp,
-    stars,
     testthat,
     tidyselect,
     tools

diff --git a/README.md b/README.md
@@ -1,35 +1,46 @@
 [![R-CMD-check](https://github.com/wallaceEcoMod/wallace/workflows/R-CMD-check/badge.svg)](https://github.com/wallaceEcoMod/wallace/actions) [![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0) [![CRAN version](http://www.r-pkg.org/badges/version/wallace)](https://CRAN.R-project.org/package=wallace) [![downloads](https://cranlogs.r-pkg.org:443/badges/grand-total/wallace?color=orange)](https://cranlogs.r-pkg.org:443/badges/grand-total/wallace?color=orange)
 
-# Wallace (v2024.09.18)
+# Wallace (v2024.11.18)
 *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.
+Developmental versions (such as this branch) can be downloaded from Github with the following R code.
 
 ```R
-install.packages("wallace")
+install.packages("devtools")
+devtools::install_github("wallaceEcoMod/wallace@biomodelos")
 library(wallace)
 run_wallace()
 ```
 
-Development versions can be downloaded from Github with the following R code.
+Alternatively, you can install the CRAN version of *Wallace* and run the application with the following R code.
 
 ```R
-install.packages("devtools")
-devtools::install_github("wallaceEcoMod/wallace")
+install.packages("wallace")
 library(wallace)
 run_wallace()
 ```
 
+
+
 ### Before using *Wallace*
 
 #### Update R and RStudio versions
 Please make sure you have installed the latest versions of both R (<a href= "https://cran.r-project.org/bin/macosx/" target="_blank">Mac OS</a>, <a href= "https://cran.r-project.org/bin/windows/base/" target="_blank">Windows</a>) and RStudio (<a href= "https://posit.co/download/rstudio-desktop/" target="_blank">Mac OS /  Windows</a>: choose the free version).
 
 #### How to run Maxent with maxent.jar
-*Wallace* v.2024.09.18 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 <a href="https://biodiversityinformatics.amnh.org/open_source/maxent/" target="_blank">here</a>, 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.
+*Wallace* v.2024.11.18 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 <a href="https://biodiversityinformatics.amnh.org/open_source/maxent/" target="_blank">here</a>, 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
 
+#### changeRangeR off CRAN
+As of 2024-07-26, `changerangeR` is temporarily off CRAN. You will have to install it prior to the installation of Wallace.
+```R
+install.packages("devtools")
+devtools::install_github("wallaceEcoMod/changeRangeR")
+library(wallace)
+run_wallace()
+```
+
 #### 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 <a href="https://java.com/en/download/manual.jsp" target="_blank">here</a>, 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 <a href="https://stackoverflow.com/questions/30738974/rjava-load-error-in-rstudio-r-after-upgrading-to-osx-yosemite" target="_blank">this StackOverflow post</a> 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 <a href="https://www.java.com/en/download/help/mac_install.html" target="_blank">Mac</a> and <a href="https://www.java.com/en/download/help/windows_offline_download.html" target="_blank">Windows</a>.
 

diff --git a/inst/shiny/Rmd/text_intro_tab.Rmd b/inst/shiny/Rmd/text_intro_tab.Rmd
@@ -5,7 +5,7 @@ output: html_document
 
 #### WORKFLOW
 
-*Wallace* (v2024.09.18) currently includes ten components, or steps of a possible workflow. Each component includes two or more modules, which are possible analyses for that step.  
+*Wallace* (v2024.11.18) currently includes ten components, or steps of a possible workflow. Each component includes two or more modules, which are possible analyses for that step.  
 
 **Components:**  
 

diff --git a/inst/shiny/Rmd/userReport_intro.Rmd b/inst/shiny/Rmd/userReport_intro.Rmd
@@ -10,7 +10,7 @@ knit_engines$set(asis = function(options) {
 knitr::opts_chunk$set(message = FALSE, warning = FALSE, eval = FALSE)
 ```
 
-Please find below the R code history from your *Wallace* v2024.09.18 session. 
+Please find below the R code history from your *Wallace* v2024.11.18 session. 
 
 You can reproduce your session results by running this R Markdown file in RStudio. 
 

diff --git a/inst/shiny/modules/mask_userSDM.R b/inst/shiny/modules/mask_userSDM.R
@@ -83,6 +83,9 @@ mask_userSDM_module_server <- function(input, output, session, common) {
       spp[[sppName]]$mask$userSDM <- userSDMs$sdm * 1
       spp[[sppName]]$mask$userPolyExt <- userSDMs$extSdm
       logger %>% writeLog(hlSpp(sppName), "User SDM prediction loaded")
+      # For biomodelos
+      spp[[sppName]]$biomodelos$mask$userSDM <- userSDMs$sdm * 1
+      spp[[sppName]]$biomodelos$mask$userPolyExt <- userSDMs$extSdm
 
       # REFERENCES ####
       knitcitations::citep(citation("raster"))