R/predict_maxent.r

In enmSdmX: Species Distribution Modeling and Ecological Niche Modeling

# # Author: Robert J. Hijmans, r.hijmans@gmail.com
# # Date: 2009-2021
# # Version 0.1
# # Licence GPL v3

# # NB These functions copied directly from predicts package because cannot import/depends/etc. on predicts::predict() function. Would love another solution so I can just Imports on predict().

# methods::setGeneric(name = "predictME", def = function(object, ...) standardGeneric("predictME"))

# .maxent_predict <- function(object, mxe, args, x) {
# 	lambdas <- paste(object@lambdas, collapse='\n')
# 	variables <- colnames(object@presence)
# 	x <- x[,variables,drop=FALSE]
# 	if (inherits(x, "data.frame")) {
# 		for (i in 1:ncol(x)) {
# 			if (inherits(x[,i], "factor")) {
# 				x[,i] <- as.numeric(as.character(x[,i]))
# 			} else if (inherits(x[,i], "character")) {
# 				x[,i] <- as.numeric(x[,i])
# 			}
# 		}
# 	} else {
# 		x[] <- as.numeric(x)
# 	}
	
# 	out <- rep(NA, times=nrow(x))
# 	ok <- rowSums(is.na(x)) == 0
# 	if (sum(ok) > 0) {
# 		x <- as.matrix(x[ok, ,drop=FALSE])
# 		p <- rJava::.jcall(mxe, "[D", "predict", lambdas, rJava::.jarray(colnames(x)), rJava::.jarray(x, dispatch=TRUE), args) 
# 		p[p == -9999] <- NA
# 		out[ok] <- p
# 	}
# 	out
# }


# setMethod("predictME", signature(object="MaxEnt_model"), 
# 	function(object, x, ext=NULL, args="", filename="", ...) {

# 		stopifnot(predicts::MaxEnt(silent=TRUE))

# 		args <- c(args, "")
# 		lambdas <- paste(object@lambdas, collapse="\n")
# 		variables <- colnames(object@presence)
			
# 		mxe <- rJava::.jnew("mebridge") 		
# 		args <- c("-z", args)
# 		tst <- rJava::.jcall(mxe, "S", "testPredictArgs", lambdas, args) 
# 		if (!is.null(tst)) {
# 			stop("args not understood:\n", tst)
# 		}

# 		if (!inherits(x, "SpatRaster")) {
# 			if (! all(variables %in% colnames(x))) {
# 				stop("missing predictor variables in x")
# 			}
# 			me <- .maxent_predict(object, mxe, args, x)
# 			return(me)
# 		}

# 		filename <- trimws(filename)
			
# 		if (! all(variables  %in%  names(x) )) {
# 			stop("missing layers (or wrong names)")
# 		}
# 		if (terra::nlyr(x) > length(variables)) {
# 			x <- x[[variables]]
# 		}
# 		if (!is.null(ext)) {
# 			x <- terra::crop(x, ext)
# 		}
# 		out <- terra::rast(x, nlyr=1)
# 		names(out)  <- "maxent"
# 		ncols <- terra::ncol(out)
# 		terra::readStart(x)
# 		on.exit(terra::readStop(x))
# 		b <- terra::writeStart(out, filename, ...)
# 		for (i in 1:b$n) {
# 			rowvals <- terra::readValues(x, b$row[i], b$nrows[i], 1, ncol(x), TRUE, FALSE)
# 			p <- .maxent_predict(object, mxe, args, rowvals)
# 			terra::writeValues(out, p, b$row[i], b$nrows[i])
# 		}
# 		terra::writeStop(out)
# 		return(out)
# 	}
# )