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Maxent pipeline: some docs, bug fix, defaults and simplified create background function #110

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merged 12 commits into from
Nov 14, 2023
Merged

Maxent pipeline: some docs, bug fix, defaults and simplified create background function #110

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77ffa30
be explicit about the possible methods and exact since there is some …
Sep 8, 2023
6814b92
check argument value to make sure it goes to a specific place
Sep 8, 2023
73c134f
slightly better documentation for create_background
Sep 13, 2023
c49b39a
as.data.frame does not check names which avoids the conversion of - i…
Sep 29, 2023
494e57e
some transition to terra (started because raster also converts - to .…
Oct 2, 2023
a829f19
changed some defaults for faster pipeline runs and more predictors
Oct 3, 2023
fc87e2b
default back to block
Oct 3, 2023
d282d20
replaced with a simplified version and added some options that were u…
Oct 4, 2023
165ceef
added background thickening as an option
Oct 4, 2023
2a5953b
update description with what was on remote
Oct 4, 2023
d076032
added some metada to pipeline
frousseu Oct 4, 2023
2bb0409
Merge branch 'main' into sdm
jmlord Oct 5, 2023
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27 changes: 21 additions & 6 deletions pipelines/SDM/SDM_maxEnt.json
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Original file line number Diff line number Diff line change
Expand Up @@ -366,7 +366,6 @@
"data": {
"type": "text[]",
"value": [
"L",
"LQ",
"LQHP"
]
Expand All @@ -384,8 +383,7 @@
"type": "float[]",
"value": [
0.5,
1,
2
1
]
}
},
Expand Down Expand Up @@ -763,7 +761,8 @@
"random",
"inclusion_buffer",
"weighted_raster",
"unweighted_raster"
"unweighted_raster",
"thickening"
],
"example": "random"
},
Expand Down Expand Up @@ -866,14 +865,18 @@
"type": "text[]",
"example": [
"chelsa-clim|bio1",
"chelsa-clim|bio2"
"chelsa-clim|bio7",
"chelsa-clim|bio12",
"earthenv_topography|elevation_median",
"earthenv_landcover|class_3",
"earthenv_landcover|class_12"
]
},
"data>loadFromStac.yml@119|spatial_res": {
"description": "Integer, spatial resolution of the rasters",
"label": "spatial resolution",
"type": "int",
"example": 1000
"example": 5000
},
"data>loadFromStac.yml@119|mask": {
"description": "Shapefile, used to mask the output rasters",
Expand All @@ -896,5 +899,17 @@
1
]
}
},
"metadata": {
"name": "Maxent SDM pipeline",
"description": "A pipeline to produce species distribution models using Maxent",
"author": [
{
"name": "Sarah Valentin",
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"identifier": "https://orcid.org/0000-0002-9028-681X"
}
],
"license": null,
"external_link": null
}
}
12 changes: 6 additions & 6 deletions scripts/SDM/runMaxent.R
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ print("Inputs : ")
print(input)


presence_background <- read.table(file = input$presence_background, sep = '\t', header = TRUE)
presence_background <- read.table(file = input$presence_background, sep = '\t', header = TRUE, check.names = FALSE)
predictors <- terra::rast(unlist(input$predictors))
mod_tuning <- run_maxent(presence_background,
with_raster = F, # can be set to F to speed up
Expand All @@ -52,7 +52,7 @@ mod_tuning <- run_maxent(presence_background,
res_tuning <- mod_tuning@results
tuned_param <- select_param(res_tuning, method = input$method_select_params, list = T)

predictors <- raster::stack(predictors)
#predictors <- raster::stack(predictors)

sdms <- predict_maxent(presence_background,
algorithm = "maxent.jar",
Expand All @@ -73,17 +73,17 @@ names(sdm_pred) <- "prediction"
sdm_runs <- sdms[["pred_runs"]]

pred.output <- file.path(outputFolder, "sdm_pred.tif")
runs.output <- paste0(outputFolder,"/sdm_runs_", 1:nlayers(sdm_runs), ".tif")
runs.output <- paste0(outputFolder,"/sdm_runs_", 1:nlyr(sdm_runs), ".tif")
#runs.output <- file.path(outputFolder, "sdm_runs.tif")

sdm_pred<-project(rast(sdm_pred),crs(input$proj)) ##Temporary fix while maxent transitions to terra
sdm_pred<-project(sdm_pred,crs(input$proj)) ##Temporary fix while maxent transitions to terra
terra::writeRaster(x = sdm_pred,
filename = pred.output,
filetype = "COG",
wopt= list(gdal=c("COMPRESS=DEFLATE")),
overwrite = TRUE)
for (i in 1:nlayers(sdm_runs)){
thisrun<-project(rast(sdm_runs[[i]]),crs(input$proj)) ##Temporary fix while maxent transitions to terra
for (i in 1:nlyr(sdm_runs)){
thisrun<-project(sdm_runs[[i]],crs(input$proj)) ##Temporary fix while maxent transitions to terra
terra::writeRaster(x = thisrun,
filename = file.path(outputFolder, paste0("/sdm_runs_", i, ".tif")),
filetype = "COG",
Expand Down
30 changes: 18 additions & 12 deletions scripts/SDM/runMaxentFunc.R
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Original file line number Diff line number Diff line change
Expand Up @@ -22,8 +22,8 @@ run_maxent <- function(presence.bg, with_raster = F,
parallelType = "doParallel"
) {

presence <- presence.bg |> dplyr::filter(pa == 1) |> data.frame()
background <- presence.bg |> dplyr::filter(pa == 0) |> data.frame()
presence <- presence.bg |> dplyr::filter(pa == 1) |> as.data.frame()
background <- presence.bg |> dplyr::filter(pa == 0) |> as.data.frame()

if (with_raster) {
ENMmodel <- ENMeval::ENMevaluate(occs = presence[, c("lon", "lat")],
Expand Down Expand Up @@ -259,8 +259,8 @@ predict_maxent <- function(presence_background,

# We calculate the prediction with the whole dataset

presence <- presence_background |> dplyr::filter(pa == 1) |> data.frame()
background <- presence_background |> dplyr::filter(pa == 0) |> data.frame()
presence <- presence_background |> dplyr::filter(pa == 1) |> as.data.frame()
background <- presence_background |> dplyr::filter(pa == 0) |> as.data.frame()


mod_tuning <- ENMeval::ENMevaluate(occs = presence[, c("lon", "lat", layers)],
Expand Down Expand Up @@ -304,8 +304,8 @@ runs <- c("run_1")
backg_test <- backgr[bg.grp == g, ]
presence_bg_train <- group.all[which(group.all[,1] == g),]

presence <- presence_bg_train |> dplyr::filter(pa == 1) |> data.frame()
background <- presence_bg_train |> dplyr::filter(pa == 0) |> data.frame()
presence <- presence_bg_train |> dplyr::filter(pa == 1) |> as.data.frame()
background <- presence_bg_train |> dplyr::filter(pa == 0) |> as.data.frame()


mod_tuning <- ENMeval::ENMevaluate(occs = presence[, c("lon", "lat", layers)],
Expand All @@ -322,12 +322,18 @@ runs <- c("run_1")
pred_pres <- dismo::predict(mod_tuning@models[[tuned_param]], predictors,
args = sprintf("outputformat=%s", type))

if (inherits(pred_runs, "RasterLayer") || inherits(pred_runs, "RasterStack")) {
pred_runs <- raster::stack(pred_runs, pred_pres)

} else {
pred_runs <- pred_pres
}
#if (inherits(pred_runs, "RasterLayer") || inherits(pred_runs, "RasterStack")) {
# pred_runs <- raster::stack(pred_runs, pred_pres)
#} else {
# pred_runs <- pred_pres
#}
if (is.null(pred_runs)) {
pred_runs <- pred_pres
} else {
pred_runs <- c(pred_runs, pred_pres)
}



}

Expand Down
1 change: 1 addition & 0 deletions scripts/SDM/selectBackground.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@ inputs:
- inclusion_buffer
- weighted_raster
- unweighted_raster
- thickening
example: random
n_background:
label: number of background points
Expand Down
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