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Merged
danflop merged 2 commits into from
Jan 22, 2026
Merged

Fix/categorical vars #461

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e277dd8
Fix: Enable running models with categorical variables when using ENMe…
danflop Dec 16, 2025
f5cf107
Add test case for categorical variables in MaxEnt
danflop Jan 22, 2026
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8 changes: 4 additions & 4 deletions R/model_bioclim.R
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Expand Up @@ -35,8 +35,8 @@
#' @param bg coordinates of background points to be used for modeling.
#' @param user.grp a list of two vectors containing group assignments for
#' occurrences (occs.grp) and background points (bg.grp).
#' @param bgMsk a RasterStack or a RasterBrick of environmental layers cropped
#' and masked to match the provided background extent.
#' @param bgMsk a SpatRaster of environmental layers cropped and masked to
#' match the provided background extent.
#' @param logger Stores all notification messages to be displayed in the Log
#' Window of Wallace GUI. Insert the logger reactive list here for running
#' in shiny, otherwise leave the default NULL.
Expand All @@ -55,7 +55,7 @@
#' bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv",
#' package = "wallace"))
#' partblock <- part_partitionOccs(occs, bg, method = 'block')
#' m <- model_bioclim(occs, bg, partblock, envs)
#' m <- model_bioclim(occs, bg, partblock, terra::rast(envs))
#' }
#'
#' @return Function returns an ENMevaluate object with all the evaluated models
Expand All @@ -80,7 +80,7 @@ model_bioclim <- function(occs, bg, user.grp, bgMsk, logger = NULL,
smartProgress(logger,
message = paste0("Building/Evaluating BIOCLIM model for ",
spName(spN), "..."), {
e <- ENMeval::ENMevaluate(occs = occs.xy, envs = terra::rast(bgMsk), bg = bg.xy,
e <- ENMeval::ENMevaluate(occs = occs.xy, envs = bgMsk, bg = bg.xy,
algorithm = "bioclim", partitions = "user",
user.grp = user.grp)
})
Expand Down
15 changes: 11 additions & 4 deletions R/model_maxent.R
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Expand Up @@ -36,8 +36,8 @@
#' @param bg coordinates of background points to be used for modeling.
#' @param user.grp a list of two vectors containing group assignments for
#' occurrences (occs.grp) and background points (bg.grp).
#' @param bgMsk a RasterStack or a RasterBrick of environmental layers cropped
#' and masked to match the provided background extent.
#' @param bgMsk a SpatRaster of environmental layers cropped and masked to
#' match the provided background extent.
#' @param rms vector of range of regularization multipliers to be used in the
#' ENMeval run.
#' @param rmsStep step to be used when defining regularization multipliers to
Expand Down Expand Up @@ -76,7 +76,7 @@
#' rmsStep <- 1
#' fcs <- c('L', 'LQ')
#' m <- model_maxent(occs = occs, bg = bg, user.grp = partblock,
#' bgMsk = envs, rms = rms, rmsStep, fcs,
#' bgMsk = terra::rast(envs), rms = rms, rmsStep, fcs,
#' clampSel = TRUE, algMaxent = "maxnet",
#' parallel = FALSE)
#' }
Expand All @@ -86,6 +86,7 @@
#' @author Jamie M. Kass <jamie.m.kass@@gmail.com>
#' @author Gonzalo E. Pinilla-Buitrago <gepinillab@@gmail.com>
#' @author Bethany A. Johnson <bjohnso005@@citymail.cuny.edu>
#' @author Daniel Lopez-Lozano <dlopezlozano@@amnh.org.co>
# @note

#' @seealso \code{\link[ENMeval]{ENMevaluate}}
Expand Down Expand Up @@ -192,12 +193,18 @@ model_maxent <- function(occs, bg, user.grp, bgMsk, rms, rmsStep, fcs,
# get just coordinates
occs.xy <- occs %>% dplyr::select("longitude", "latitude")
bg.xy <- bg %>% dplyr::select("longitude", "latitude")

# convert the categorical variables to factors
if (!is.null(catEnvs)) {
bgMsk[[catEnvs]] <- terra::as.factor(bgMsk[[catEnvs]])
}

# run ENMeval
e <- ENMeval::ENMevaluate(occs = as.data.frame(occs.xy),
bg = as.data.frame(bg.xy),
partitions = 'user',
user.grp = user.grp,
envs = terra::rast(bgMsk),
envs = bgMsk,
tune.args = tune.args,
doClamp = clampSel,
algorithm = algMaxent,
Expand Down
18 changes: 9 additions & 9 deletions R/penvs_bgMask.R
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Expand Up @@ -31,8 +31,8 @@
#' environmental layers to be used in the modeling are cropped and masked
#' to the provided background area. The background area is determined in
#' the function penvs_bgExtent from the same component. The function returns
#' the provided environmental layers cropped and masked in the provided
#' format (either a rasterBrick or a rasterStack).
#' the provided environmental layers cropped and masked in the SpatRaster
#' format.
#'
#' @param occs data frame of cleaned or processed occurrences obtained from
#' components occs: Obtain occurrence data or, poccs: Process occurrence data.
Expand All @@ -59,10 +59,11 @@
#' bgMask <- penvs_bgMask(occs, envs, bgExt)
#' }
#'
#' @return A RasterStack or a RasterBrick of environmental layers cropped and
#' @return A SpatRaster of environmental layers cropped and
#' masked to match the provided background extent.
#' @author Jamie Kass <jamie.m.kass@@gmail.com>
#' @author Gonzalo E. Pinilla-Buitrago <gepinillab@@gmail.com>
#' @author Daniel Lopez-Lozano <dlopezlozano@@amnh.org.co>
#' @seealso \code{\link{penvs_userBgExtent}},
#' \code{\link{penvs_drawBgExtent}}, \code{\link{penvs_bgExtent}},
#' \code{\link{penvs_bgSample}}
Expand All @@ -81,18 +82,17 @@ penvs_bgMask <- function(occs, envs, bgExt, logger = NULL, spN = NULL) {
message = paste0("Masking rasters for ",
spName(spN), "..."), {

bgCrop <- raster::crop(envs, bgExt)
bgMask <- raster::mask(bgCrop, bgExt)
envs <- terra::rast(envs)
bgCrop <- terra::crop(envs, bgExt)
bgMask <- terra::mask(bgCrop, terra::vect(bgExt))
# GEPB: Workaround when raster alignment is changed after crop, which makes appears
# new duplicated occs in the same grid cells.
occsEnvsVals <- as.data.frame(raster::extract(bgMask,
occsEnvsVals <- as.data.frame(terra::extract(bgMask,
occs[, c('longitude', 'latitude')],
cellnumbers = TRUE))
occs.dups <- duplicated(occsEnvsVals[, 1])
if (sum(occs.dups) > 0) {
bgMask <- terra::project(terra::rast(bgMask),
terra::rast(envs), method = 'near')
bgMask <- methods::as(bgMask, "Raster")
bgMask <- terra::project(bgMask, envs, method = 'near')
}
})

Expand Down
2 changes: 1 addition & 1 deletion R/penvs_bgSample.R
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Expand Up @@ -58,7 +58,7 @@
#' doBrick = TRUE)
#' bgExt <- penvs_bgExtent(occs, bgSel = 'bounding box', bgBuf = 0.5)
#' bgMask <- penvs_bgMask(occs, envs, bgExt)
#' bgsample <- penvs_bgSample(occs, bgMask, bgPtsNum = 1000)
#' bgsample <- penvs_bgSample(occs, raster::stack(bgMask), bgPtsNum = 1000)
#' }
#'
#' @return a dataframe containing point coordinates (longitude and latitude).
Expand Down
2 changes: 1 addition & 1 deletion R/vis_bioclimPlot.R
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Expand Up @@ -56,7 +56,7 @@
#' bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv",
#' package = "wallace"))
#' partblock <- part_partitionOccs(occs, bg, method = 'block')
#' m <- model_bioclim(occs, bg, partblock, envs)
#' m <- model_bioclim(occs, bg, partblock, terra::rast(envs))
#' bioclimPlot <- vis_bioclimPlot(x = m@@models$bioclim,
#' a = 1, b = 2, p = 1)
#' }
Expand Down
2 changes: 1 addition & 1 deletion R/xfer_area.R
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Expand Up @@ -77,7 +77,7 @@
#' partblock <- part_partitionOccs(occs, bg, method = 'block')
#' m <- model_maxent(occs, bg,
#' user.grp = partblock,
#' bgMsk = envs, rms = c(1:2),
#' bgMsk = terra::rast(envs), rms = c(1:2),
#' rmsStep = 1, fcs = c('L', 'LQ'),
#' clampSel = TRUE,
#' algMaxent = "maxnet",
Expand Down
2 changes: 1 addition & 1 deletion R/xfer_time.R
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Expand Up @@ -78,7 +78,7 @@
#' occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv",package = "wallace"))
#' bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace"))
#' partblock <- part_partitionOccs(occs, bg, method = 'block')
#' m <- model_maxent(occs, bg, user.grp = partblock, bgMsk = envs, rms = c(1:2),
#' m <- model_maxent(occs, bg, user.grp = partblock, bgMsk = terra::rast(envs), rms = c(1:2),
#' rmsStep = 1, fcs = c('L', 'LQ'),
#' clampSel = TRUE, algMaxent = "maxnet", parallel = FALSE)
#' occsEnvs <- m@@occs
Expand Down
2 changes: 1 addition & 1 deletion R/xfer_userEnvs.R
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Expand Up @@ -72,7 +72,7 @@
#' rasName = list.files(system.file("extdata/wc",package = "wallace"),
#' pattern = ".tif$", full.names = FALSE))
#' partblock <- part_partitionOccs(occs, bg, method = 'block')
#' m <- model_maxent(occs, bg, user.grp = partblock, bgMsk = envs, rms = c(1:2),
#' m <- model_maxent(occs, bg, user.grp = partblock, bgMsk = terra::rast(envs), rms = c(1:2),
#' rmsStep = 1, fcs = c('L', 'LQ'), clampSel = TRUE, algMaxent = "maxnet", parallel = FALSE)
#' envsFut <- list.files(path = system.file('extdata/wc/future',
#' package = "wallace"),
Expand Down
2 changes: 1 addition & 1 deletion inst/shiny/modules/part_spat.Rmd
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Expand Up @@ -22,6 +22,6 @@ groups_{{spAbr}} <- part_partitionOccs(
occs = occs_{{spAbr}} ,
bg = bgSample_{{spAbr}},
method = "{{method_code_rmd}}",
bgMask = bgMask_{{spAbr}},
bgMask = raster::stack(bgMask_{{spAbr}}),
aggFact = {{aggFact_rmd}})
```
9 changes: 5 additions & 4 deletions inst/shiny/modules/penvs_bgExtent.R
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Expand Up @@ -128,7 +128,8 @@ penvs_bgExtent_module_server <- function(input, output, session, common) {
bgMask <- penvs_bgMask(spp[[sp]]$occs, envs.global[[spp[[sp]]$envs]],
spp[[sp]]$procEnvs$bgExt, logger, spN = sp)
req(bgMask)
bgNonNA <- raster::ncell(bgMask) - raster::freq(bgMask, value = NA)[[1]]
bgMaskR <- raster::stack(bgMask)
bgNonNA <- raster::ncell(bgMaskR) - raster::freq(bgMaskR, value = NA)[[1]]
if ((bgNonNA + 1) < input$bgPtsNum) {
logger %>%
writeLog(
Expand All @@ -138,15 +139,15 @@ penvs_bgExtent_module_server <- function(input, output, session, common) {
"(n = ", bgNonNA, "). Please reduce the number of requested points.")
return()
}
bgPts <- penvs_bgSample(spp[[sp]]$occs, bgMask, input$bgPtsNum, logger,
bgPts <- penvs_bgSample(spp[[sp]]$occs, bgMaskR, input$bgPtsNum, logger,
spN = sp)
req(bgPts)
withProgress(
message = paste0("Extracting background values for ", spName(sp), "..."), {
bgEnvsVals <- as.data.frame(raster::extract(bgMask, bgPts))
bgEnvsVals <- as.data.frame(terra::extract(bgMask, bgPts))
})

NApoints <- sum(rowSums(is.na(raster::extract(bgMask, spp[[sp]]$occs[ , c("longitude", "latitude")]))))
NApoints <- sum(rowSums(is.na(terra::extract(bgMask, spp[[sp]]$occs[ , c("longitude", "latitude")]))))
if (NApoints > 0) {
logger %>%
writeLog(type = "error", hlSpp(sp),
Expand Down
4 changes: 2 additions & 2 deletions inst/shiny/modules/penvs_bgExtent.Rmd
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Expand Up @@ -17,10 +17,10 @@ bgMask_{{spAbr}} <- penvs_bgMask(
# Sample background points from the provided area
bgSample_{{spAbr}} <- penvs_bgSample(
occs = occs_{{spAbr}},
bgMask = bgMask_{{spAbr}},
bgMask = raster::stack(bgMask_{{spAbr}}),
bgPtsNum = {{bgPtsNum_rmd}})
# Extract values of environmental layers for each background point
bgEnvsVals_{{spAbr}} <- as.data.frame(raster::extract(bgMask_{{spAbr}}, bgSample_{{spAbr}}))
bgEnvsVals_{{spAbr}} <- as.data.frame(terra::extract(bgMask_{{spAbr}}, bgSample_{{spAbr}}))
##Add extracted values to background points table
bgEnvsVals_{{spAbr}} <- cbind(scientific_name = paste0("bg_", "{{spName}}"), bgSample_{{spAbr}},
occID = NA, year = NA, institution_code = NA, country = NA,
Expand Down
9 changes: 5 additions & 4 deletions inst/shiny/modules/penvs_drawBgExtent.R
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Expand Up @@ -127,7 +127,8 @@ penvs_drawBgExtent_module_server <- function(input, output, session, common) {
logger,
spN = sp)
req(bgMask)
bgNonNA <- raster::ncell(bgMask) - raster::freq(bgMask, value = NA)[[1]]
bgMaskR <- raster::stack(bgMask)
bgNonNA <- raster::ncell(bgMaskR) - raster::freq(bgMaskR, value = NA)[[1]]
if ((bgNonNA + 1) < input$bgPtsNum) {
logger %>%
writeLog(
Expand All @@ -138,17 +139,17 @@ penvs_drawBgExtent_module_server <- function(input, output, session, common) {
return()
}
bgPts <- penvs_bgSample(spp[[sp]]$occs,
bgMask,
bgMaskR,
input$bgPtsNum,
logger,
spN = sp)
req(bgPts)
withProgress(message = paste0("Extracting background values for ",
spName(sp), "..."), {
bgEnvsVals <- as.data.frame(raster::extract(bgMask, bgPts))
bgEnvsVals <- as.data.frame(terra::extract(bgMask, bgPts))
})

if (sum(rowSums(is.na(raster::extract(bgMask, spp[[sp]]$occs[ , c("longitude", "latitude")])))) > 0) {
if (sum(rowSums(is.na(terra::extract(bgMask, spp[[sp]]$occs[ , c("longitude", "latitude")])))) > 0) {
logger %>%
writeLog(type = "error", hlSpp(sp),
"One or more occurrence points have NULL raster values.",
Expand Down
4 changes: 2 additions & 2 deletions inst/shiny/modules/penvs_drawBgExtent.Rmd
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Expand Up @@ -18,10 +18,10 @@ bgMask_{{spAbr}} <- penvs_bgMask(
# Sample background points from the provided area
bgSample_{{spAbr}} <- penvs_bgSample(
occs = occs_{{spAbr}},
bgMask = bgMask_{{spAbr}},
bgMask = raster::stack(bgMask_{{spAbr}}),
bgPtsNum = {{bgPtsNum_rmd}})
# Extract values of environmental layers for each background point
bgEnvsVals_{{spAbr}} <- as.data.frame(raster::extract(bgMask_{{spAbr}}, bgSample_{{spAbr}}))
bgEnvsVals_{{spAbr}} <- as.data.frame(terra::extract(bgMask_{{spAbr}}, bgSample_{{spAbr}}))
##Add extracted values to background points table
bgEnvsVals_{{spAbr}} <- cbind(scientific_name = paste0("bg_", "{{spName}}"), bgSample_{{spAbr}},
occID = NA, year = NA, institution_code = NA, country = NA,
Expand Down
9 changes: 5 additions & 4 deletions inst/shiny/modules/penvs_userBgExtent.R
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Expand Up @@ -148,7 +148,8 @@ penvs_userBgExtent_module_server <- function(input, output, session, common) {
logger,
spN = sp)
req(bgMask)
bgNonNA <- raster::ncell(bgMask) - raster::freq(bgMask, value = NA)[[1]]
bgMaskR <- raster::stack(bgMask)
bgNonNA <- raster::ncell(bgMaskR) - raster::freq(bgMaskR, value = NA)[[1]]
if ((bgNonNA + 1) < input$bgPtsNum) {
logger %>%
writeLog(
Expand All @@ -159,17 +160,17 @@ penvs_userBgExtent_module_server <- function(input, output, session, common) {
return()
}
bgPts <- penvs_bgSample(spp[[sp]]$occs,
bgMask,
bgMaskR,
input$bgPtsNum,
logger,
spN = sp)
req(bgPts)
withProgress(message = paste0("Extracting background values for ",
spName(sp), "..."), {
bgEnvsVals <- as.data.frame(raster::extract(bgMask, bgPts))
bgEnvsVals <- as.data.frame(terra::extract(bgMask, bgPts))
})

if (sum(rowSums(is.na(raster::extract(bgMask, spp[[sp]]$occs[ , c("longitude", "latitude")])))) > 0) {
if (sum(rowSums(is.na(terra::extract(bgMask, spp[[sp]]$occs[ , c("longitude", "latitude")])))) > 0) {
logger %>%
writeLog(type = "error", hlSpp(sp),
"One or more occurrence points have NULL raster values.",
Expand Down
4 changes: 2 additions & 2 deletions inst/shiny/modules/penvs_userBgExtent.Rmd
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Expand Up @@ -21,10 +21,10 @@ bgMask_{{spAbr}} <- penvs_bgMask(
# Sample background points from the provided area
bgSample_{{spAbr}} <- penvs_bgSample(
occs = occs_{{spAbr}},
bgMask = bgMask_{{spAbr}},
bgMask = raster::stack(bgMask_{{spAbr}}),
bgPtsNum = {{bgPtsNum_rmd}})
# Extract values of environmental layers for each background point
bgEnvsVals_{{spAbr}} <- as.data.frame(raster::extract(bgMask_{{spAbr}}, bgSample_{{spAbr}}))
bgEnvsVals_{{spAbr}} <- as.data.frame(terra::extract(bgMask_{{spAbr}}, bgSample_{{spAbr}}))
##Add extracted values to background points table
bgEnvsVals_{{spAbr}} <- cbind(scientific_name = paste0("bg_", "{{spName}}"), bgSample_{{spAbr}},
occID = NA, year = NA, institution_code = NA, country = NA,
Expand Down
12 changes: 6 additions & 6 deletions inst/shiny/modules/vis_mapPreds.R
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Expand Up @@ -87,7 +87,7 @@ vis_mapPreds_module_server <- function(input, output, session, common) {
# pick the prediction that matches the model selected
predSel <- evalOut()@predictions[[curModel()]]
predSel <- raster::raster(predSel)
raster::crs(predSel) <- raster::crs(bgMask())
raster::crs(predSel) <- raster::crs(raster::stack(bgMask()))
if(is.na(raster::crs(predSel))) {
logger %>% writeLog(
type = "error",
Expand All @@ -103,10 +103,10 @@ vis_mapPreds_module_server <- function(input, output, session, common) {
if (spp[[curSp()]]$rmm$model$algorithms == "BIOCLIM") {
predType <- "BIOCLIM"
m <- evalOut()@models[[curModel()]]
predSel <- dismo::predict(m, terra::rast(bgMask()))
predSel <- dismo::predict(m, bgMask())
predSel <- raster::raster(predSel)
# define crs
raster::crs(predSel) <- raster::crs(bgMask())
raster::crs(predSel) <- raster::crs(raster::raster(bgMask()))
# define predSel name
names(predSel) <- curModel()
} else if (spp[[curSp()]]$rmm$model$algorithms %in% c("maxent.jar", "maxnet")) {
Expand All @@ -125,7 +125,7 @@ vis_mapPreds_module_server <- function(input, output, session, common) {
clamping <- spp[[curSp()]]$rmm$model$algorithm$maxent$clamping
if (spp[[curSp()]]$rmm$model$algorithms == "maxnet") {
if (predType == "raw") predType <- "exponential"
predSel <- predictMaxnet(m, bgMask(),
predSel <- predictMaxnet(m, raster::stack(bgMask()),
type = predType,
clamp = FALSE)
} else if (spp[[curSp()]]$rmm$model$algorithms == "maxent.jar") {
Expand All @@ -135,15 +135,15 @@ vis_mapPreds_module_server <- function(input, output, session, common) {
} else {
doClamp <- "doclamp=false"
}
predSel <- dismo::predict(m, terra::rast(bgMask()),
predSel <- dismo::predict(m, bgMask(),
args = c(outputFormat, doClamp),
#na.rm = TRUE
)
predSel <- raster::raster(predSel)
}
})
# define crs
raster::crs(predSel) <- raster::crs(bgMask())
raster::crs(predSel) <- raster::crs(raster::stack(bgMask()))
# define predSel name
names(predSel) <- curModel()

Expand Down
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