Add maxcell for quantization

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: GLCMTextures
 Title: GLCM Textures of Raster Layers
-Version: 0.3.9
+Version: 0.3.10
 Authors@R: 
     person(given = "Alexander",
            family = "Ilich",

R/glcm_textures.R

@@ -9,6 +9,7 @@
 #' @param quantization quantization method (either "equal range", "equal prob", or "none"). "equal range" quantization will create bins that cover a range of equal size. "equal prob" performs equal probability quantization and will use quantiles to create bins with approximately equal number of samples. "none" means the layer has already been quantized.
 #' @param min_val minimum value for equal range quantization (if not supplied, the minimum value of the raster is used)
 #' @param max_val maximum value for equal range quantization (if not supplied, the maximum value of the raster is used)
+#' @param maxcell positive integer used to take a regular sample for quantization if "equal prob" is used (default is Inf)
 #' @param na.rm a logical value indicating whether NA values should be stripped before the computation proceeds (default=FALSE)
 #' @param include_scale Logical indicating whether to append window size to the layer names (default = FALSE).
 #' @param filename character Output filename. Can be a single filename, or as many filenames as there are layers to write a file for each layer
@@ -33,7 +34,7 @@
 #' Haralick, R.M., Shanmugam, K., Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics 610–621. https://doi.org/10.1109/TSMC.1973.4309314
 #' @export
 #'
-glcm_textures<- function(r, w = c(3,3), n_levels, shift=list(c(1,0), c(1,1), c(0,1), c(-1,1)), metrics= c("glcm_contrast", "glcm_dissimilarity", "glcm_homogeneity", "glcm_ASM", "glcm_entropy", "glcm_mean", "glcm_variance", "glcm_correlation"), quantization, min_val=NULL, max_val=NULL, na.rm=FALSE, include_scale=FALSE, filename=NULL, overwrite=FALSE, wopt=list()){
+glcm_textures<- function(r, w = c(3,3), n_levels, shift=list(c(1,0), c(1,1), c(0,1), c(-1,1)), metrics= c("glcm_contrast", "glcm_dissimilarity", "glcm_homogeneity", "glcm_ASM", "glcm_entropy", "glcm_mean", "glcm_variance", "glcm_correlation"), quantization, min_val=NULL, max_val=NULL, maxcell=Inf, na.rm=FALSE, include_scale=FALSE, filename=NULL, overwrite=FALSE, wopt=list()){
   og_class<- class(r)[1]
   if(og_class=="RasterLayer"){
     r<- terra::rast(r) #Convert to SpatRaster
@@ -84,7 +85,7 @@ glcm_textures<- function(r, w = c(3,3), n_levels, shift=list(c(1,0), c(1,1), c(0
 
   out_list<- vector(mode = "list", length=length(shift))
   if(quantization!="none"){
-    r<- quantize_raster(r = r, n_levels = n_levels, method = quantization, min_val = min_val, max_val = max_val, wopt=wopt)
+    r<- quantize_raster(r = r, n_levels = n_levels, method = quantization, min_val = min_val, max_val = max_val, maxcell=maxcell, wopt=wopt)
     } else if(!terra::is.int(r)){
     r<- terra::as.int(r, wopt=wopt) #Make it an integer raster
     }

R/quantize_raster.R

@@ -6,6 +6,7 @@
 #' @param method quantization method (either "equal range" or "equal prob"). "equal range" quantization will create bins that cover a range of equal size. "equal prob" performs equal probability quantization and will use quantiles to create bins with approximately equal number of samples.
 #' @param min_val minimum value for equal range quantization (if not supplied, the minimum value of the raster is used)
 #' @param max_val maximum value for equal range quantization (if not supplied, the maximum value of the raster is used)
+#' @param maxcell positive integer used to take a regular sample of x if "equal prob" is used (default is Inf)
 #' @param filename character Output filename.
 #' @param overwrite logical. If TRUE, filename is overwritten (default is FALSE).
 #' @return a single layer SpatRaster or RasterLayer with integer values ranging from 0 to n_levels-1
@@ -26,7 +27,7 @@
 #' Hyndman, R.J., Fan, Y., 1996. Sample Quantiles in Statistical Packages. The American Statistician 50, 361–365. https://doi.org/10.1080/00031305.1996.10473566
 #' @export
 
-quantize_raster<- function(r, n_levels, method, min_val=NULL, max_val=NULL, filename= NULL, overwrite = FALSE, wopt=list()){
+quantize_raster<- function(r, n_levels, method, min_val=NULL, max_val=NULL, maxcell=Inf, filename= NULL, overwrite = FALSE, wopt=list()){
   og_class<- class(r)[1]
   if(og_class =="RasterLayer"){
     r<- terra::rast(r) #Convert to SpatRaster
@@ -39,10 +40,12 @@ quantize_raster<- function(r, n_levels, method, min_val=NULL, max_val=NULL, file
     if(is.null(max_val)){max_val<- unlist(terra::global(r, fun = max, na.rm=TRUE))}
     qrules<- seq(min_val, max_val, length.out = (n_levels + 1))
   } else if (method == "equal prob") {
-    qrules<- unlist(terra::global(r, fun = quantile, probs= seq(0,1,length.out = n_levels+1), na.rm=TRUE, type=8))
+    qrules<- unlist(terra::global(r, fun = quantile, probs= seq(0,1,length.out = n_levels+1), na.rm=TRUE, type=8, maxcell=maxcell))
   } else {
     message("Error: method must be 'equal range' or 'equal prob'")
   }
+  qrules[1]<- -Inf
+  qrules[length(qrules)]<- Inf #Make edges infinite in case sample is used which doesn't contain min/max value
   rq <- terra::classify(r, rcl = qrules, include.lowest = TRUE, right = FALSE, wopt=wopt)
   rq<- terra::as.int(rq, wopt=wopt)