diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
index 5e716eeb2248a6bd9073a8de4ac68908a511279a..805ff3c23aaef33389f22753cf7f7a999aa4a915 100644
--- a/R-package/DESCRIPTION
+++ b/R-package/DESCRIPTION
@@ -1,6 +1,6 @@
Package: HaSa
Title: Autonomous Image Sampling and Probability Mapping
-Version: 1.2.0
+Version: 1.3.0
Authors@R:
person(given = "Carsten",
family = "Neumann",
@@ -15,6 +15,7 @@ Imports:
sp (<= 1.4-1),
rgdal (<= 1.4-8),
raster,
+ geojsonio,
maptools,
rgeos,
spatialEco,
@@ -24,6 +25,7 @@ Imports:
velox,
leaflet,
leafem,
+ IRdisplay,
htmlwidgets
Remotes:url::https://cran.r-project.org/src/contrib/Archive/velox/velox_0.2.0.tar.gz
Encoding: UTF-8
diff --git a/R-package/R/inner_procedure.r b/R-package/R/inner_procedure.r
index c0e16163959adde9781f2df815a17bd1f565c433..8baadfc4b42b597d8a5053434f519c4d472a7aaf 100644
--- a/R-package/R/inner_procedure.r
+++ b/R-package/R/inner_procedure.r
@@ -15,19 +15,21 @@
#' @param last only true for one class classifier c("FALSE", TRUE")
#' @param seed set seed for reproducable results
#' @param init.seed "sample" for new or use run1@seeds to reproduce previous steps
-#' @param parallel_mode run loops using all available cores
+#' @param save_runs if the user wants to save the runs, if TRUE the complete Habitat Class object is returned
+#' @param parallel_mode run loops in parallel
+#' @param max_num_cores maximum number of cores for parallelism
#'
#' @return a list with 3 elements:
#' 1) An index
#' 2) Accuracy vector
#' 3) A vector with a Habitat objects, each consisting of 7 slots: \cr
-#' run1@models - list of selected classifiers \cr
-#' run1@ref_samples - list of SpatialPointsDataFrames with same length as run1@models holding reference labels [1,2] for each selected model \cr
-#' run1@switch - vector of length run1@models indicating if target class equals 2, if not NA the labels need to be switched \cr
+#' run1@models - list of selected classifiers (only if save_runs is TRUE) \cr
+#' run1@ref_samples - list of SpatialPointsDataFrames with same length as run1@models holding reference labels [1,2] for each selected model (only if save_runs is TRUE) \cr
+#' run1@switch - vector of length run1@models indicating if target class equals 2, if not NA the labels need to be switched (only if save_runs is TRUE) \cr
#' run1@layer - raster map of habitat type probability \cr
-#' run1@mod_all - list of all classifiers (equals nb_models) \cr
-#' run1@class_ind - vector of predictive distance measure for all habitats \cr
-#' run1@seeds - vector of seeds for random sampling \cr
+#' run1@mod_all - list of all classifiers (equals nb_models) (only if save_runs is TRUE) \cr
+#' run1@class_ind - vector of predictive distance measure for all habitats (only if save_runs is TRUE) \cr
+#' run1@seeds - vector of seeds for random sampling (only if save_runs is TRUE) \cr
#' all files are saved with step number, the *.tif file is additionally saved with class names
#' @keywords internal
@@ -46,7 +48,9 @@ sample_nb <- function(raster,
last,
seed,
init.seed,
- parallel_mode) {
+ save_runs,
+ parallel_mode,
+ max_num_cores) {
###
n_channel <- length(names(raster))
###velox
@@ -74,8 +78,8 @@ sample_nb <- function(raster,
seed2 <- init.seed
}
oobe <- matrix(NA, nrow = n, ncol = nb_mean)
- models <- list()
- points <- list()
+ models_list <- list()
+ points_list <- list()
dif <- matrix(NA, nrow = nb_mean, ncol = nrow(reference))
channel <- matrix(NA, nrow = nb_mean, ncol = nrow(reference))
switch <- matrix(NA, nrow = nb_mean, ncol = nrow(reference))
@@ -85,6 +89,12 @@ sample_nb <- function(raster,
if (parallel_mode == TRUE) {
cores = parallel::detectCores( logical = TRUE)
+ if (cores > max_num_cores) {
+ cores <- max_num_cores
+ } else {
+ cores <- cores - 1
+ }
+
res <- parallel::mclapply(
1:nb_mean,
model_opt_r,
@@ -103,11 +113,13 @@ sample_nb <- function(raster,
pbtn2 = pbtn2,
ras_vx = ras.vx,
max_samples_per_class = max_samples_per_class,
- mc.cores = cores
+ mc.cores = cores,
+ mc.preschedule = TRUE,
+ mc.cleanup = TRUE
)
for (k in 1:nb_mean) {
- points[[k]] <- res[["k" = k]][["points"]]
- models[[k]] <- res[["k" = k]][["models"]]
+ points_list[[k]] <- res[["k" = k]][["points"]]
+ models_list[[k]] <- res[["k" = k]][["models"]]
oobe[, k] <- res[["k" = k]][["oobe"]][, 1]
}
} else {
@@ -130,22 +142,29 @@ sample_nb <- function(raster,
ras_vx = ras.vx,
max_samples_per_class = max_samples_per_class
)
- points[[k]] <- res$points
- models[[k]] <- res$models
+ points_list[[k]] <- res$points
+ models_list[[k]] <- res$models
oobe[, k] <- res$oobe[, 1]
setTxtProgressBar(pb, k)
}
}
#which_models_null <- which(models == "NULL")
- which_models_null <- vapply(models, is.not.null <- function(x){!is.null(x)}, FALSE)
- if (length(models) == 0 |
- length(which_models_null[which_models_null == FALSE]) == length(models)) {
+ which_models_null <- vapply(models_list, is.not.null <- function(x){!is.null(x)}, FALSE)
+ if (length(models_list) == 0 |
+ length(which_models_null[which_models_null == FALSE]) == length(models_list)) {
+ remove(points_list)
+ remove(models_list)
+ remove(ooe)
stop("No Models - would you be so kind to increase init.samples, please")
}
if (length(which_models_null[which_models_null == FALSE]) > 0) {
- models <- models[which_models_null]
+ models <- models_list[which_models_null]
+ } else {
+ models <- models_list
}
+ remove(models_list)
+
for (jj in 1:nrow(reference)) {
ref <- jj
rr = 3
@@ -204,11 +223,16 @@ sample_nb <- function(raster,
}
close(pb)
- mod_all <- models
+ if (save_runs == TRUE) {
+ mod_all <- models
+ } else {
+ mod_all = list()
+ }
models <- models[ch]
print(paste("n_models =", length(models)))
switch <- switch[ch, index]
- points <- points[ch]
+ points <- points_list[ch]
+ remove(points_list)
dif <- dif[2,]
##############################################################################
###Vohersage
@@ -241,16 +265,38 @@ sample_nb <- function(raster,
dummy <- raster::calc(dummy, fun = sum)
layer[[1]] <- dummy
- obj <- new(
- "Habitat",
- models = models,
- ref_samples = points,
- switch = switch,
- layer = layer,
- mod_all = mod_all,
- class_ind = dif,
- seeds = seed2
- )
+ if (save_runs == TRUE) {
+ obj <- new(
+ "Habitat",
+ models = models,
+ ref_samples = points,
+ switch = switch,
+ layer = layer,
+ mod_all = mod_all,
+ class_ind = dif,
+ seeds = seed2
+ )
+ } else {
+ obj <- new(
+ "Habitat",
+ models = list(),
+ ref_samples = list(),
+ switch = vector(),
+ layer = layer,
+ mod_all = list(),
+ class_ind = 0,
+ seeds = 0
+ )
+ }
+ remove(models)
+ remove(points)
+ remove(switch)
+ remove(layer)
+ remove(mod_all)
+ remove(dif)
+ remove(seed2)
+ gc(full = TRUE)
+
out <- list(index = index, acc = acc, obj = obj)
return(out)
}
diff --git a/R-package/R/model_opt.r b/R-package/R/model_opt.r
index 394663f255be3ba9fcf5e97c88b88b6301f81568..c9c674dc0f2f8c1a8833de9205563f92909ade5e 100644
--- a/R-package/R/model_opt.r
+++ b/R-package/R/model_opt.r
@@ -120,10 +120,7 @@ model_opt_r <- function(k,
break
}
}
- model_pre <- model1
- pbtn1_pre <- pbtn1
- pbtn2_pre <- pbtn2
- oobe <- oobe
+
########################################################################
if (model == "rf") {
correct <-
@@ -138,8 +135,6 @@ model_opt_r <- function(k,
if (length(which_classes_correct) == 0) {
if (j == 1) {
break
- } else{
- pbtn1 <- pbtn1
}
} else {
d1 <- correct[which_classes_correct]
@@ -149,7 +144,8 @@ model_opt_r <- function(k,
pbtn1 <-
as.data.frame(cbind(classes[d1], matrix(p1, ncol = 2)))
sp::coordinates(pbtn1) <- c("V2", "V3")
- sp::proj4string(pbtn1) <- sp::proj4string(pbt)
+ #sp::proj4string(pbtn1) <- sp::proj4string(pbt)
+ crs(pbtn1) <- crs(pbt)
poly <- rgeos::gBuffer(spgeom = pbtn1,
width = buffer,
@@ -201,8 +197,6 @@ model_opt_r <- function(k,
if (length(which_classes_correct_2) == 0) {
if (j == 1) {
break
- } else{
- pbtn2 <- pbtn2
}
} else {
d2 <- correct[which_classes_correct_2]
@@ -212,7 +206,8 @@ model_opt_r <- function(k,
pbtn2 <-
as.data.frame(cbind(classes[d2], matrix(p2, ncol = 2)))
sp::coordinates(pbtn2) <- c("V2", "V3")
- sp::proj4string(pbtn2) <- sp::proj4string(pbt)
+ #sp::proj4string(pbtn2) <- sp::proj4string(pbt)
+ crs(pbtn2) <- crs(pbt)
poly <- rgeos::gBuffer(spgeom = pbtn2,
width = buffer,
@@ -298,6 +293,8 @@ model_opt_r <- function(k,
classes <- data$classes
pbt <- rbind(pbtn1, pbtn2)
}
+ remove(pbt)
+
return(list(
"k" = k,
"models" = models,
diff --git a/R-package/R/outer_procedure.r b/R-package/R/outer_procedure.r
index eb81359d618e8111f9172ca7e11f96da7275841f..781f9cb873440a57cd31ff3d452018c0989bb27a 100644
--- a/R-package/R/outer_procedure.r
+++ b/R-package/R/outer_procedure.r
@@ -20,13 +20,15 @@
#' @param n_classes total number of classes (habitat types) to be separated
#' @param multiTest number of test runs to compare different probability outputs
#' @param RGB rgb channel numbers for image plot
-#' @param overwrite overwrite the results file
-#' @param parallel_mode run loops using all available cores
-
+#' @param overwrite overwrite the KML and raster files from previous runs (default TRUE)
+#' @param save_runs an Habitat object and extra info (to restart a run) is saved (default TRUE)
+#' @param parallel_mode run loops using all available cores (default FALSE)
+#' @param max_num_cores maximum number of cores for parallelism (default 5)
+#' @param plot_on_browser plot on the browser or inline in a notebook (default TRUE)
#'
#' @return 4 files per step:
#' 1) Habitat type probability map as geocoded *.kml layer and *.tif raster files and *.png image output
-#' 2) A Habitat object consisting of 7 slots: \cr
+#' 2) A Habitat object (only if save_runs is set to TRUE) consisting of 7 slots: \cr
#' run1@models - list of selcted classifiers \cr
#' run1@ref_samples - list of SpatialPointsDataFrames with same length as run1@models holding reference labels [1,2] for each selected model \cr
#' run1@switch - vector of lenght run1@models indicating if target class equals 2, if not NA the labels need to be switched \cr
@@ -83,7 +85,10 @@ multi_Class_Sampling <- function(in.raster,
multiTest = 1,
RGB = c(19, 20, 21),
overwrite = TRUE,
- parallel_mode = FALSE) {
+ save_runs = TRUE,
+ parallel_mode = FALSE,
+ max_num_cores = 5,
+ plot_on_browser = TRUE) {
###first steps: data preparation
if (class(reference) == "SpatialPointsDataFrame") {
reference <- as.data.frame(raster::extract(in.raster, reference))
@@ -92,7 +97,8 @@ multi_Class_Sampling <- function(in.raster,
input_raster <- in.raster
area <- as(raster::extent(in.raster), 'SpatialPolygons')
area <- sp::SpatialPolygonsDataFrame(area, data.frame(ID = 1:length(area)))
- sp::proj4string(area) <- sp::proj4string(in.raster)
+ #sp::proj4string(area) <- sp::proj4string(in.raster)
+ crs(area) <- crs(in.raster)
col <- colorRampPalette(c("lightgrey",
"orange",
@@ -151,7 +157,9 @@ multi_Class_Sampling <- function(in.raster,
last = last,
seed = seed,
init.seed = init.seed,
- parallel_mode = parallel_mode
+ save_runs = save_runs,
+ parallel_mode = parallel_mode,
+ max_num_cores = max_num_cores
)
index <- maFo_rf$index
@@ -182,6 +190,9 @@ multi_Class_Sampling <- function(in.raster,
maFo_rf <- maFo[[as.numeric(decision)]]
index <- new.names[[as.numeric(decision)]]
acc <- new.acc[[as.numeric(decision)]]
+ remove(maFo)
+ remove(new.names)
+ remove(new.acc)
##########################################################################
} else{
########################
@@ -199,7 +210,9 @@ multi_Class_Sampling <- function(in.raster,
last = last,
seed = seed,
init.seed = init.seed,
- parallel_mode = parallel_mode
+ save_runs = save_runs,
+ parallel_mode = parallel_mode,
+ max_num_cores = max_num_cores
)
index <- maFo_rf$index
@@ -217,7 +230,8 @@ multi_Class_Sampling <- function(in.raster,
g = RGB[2],
b = RGB[3],
acc = acc,
- outPath = outPath
+ outPath = outPath,
+ plot_on_browser = plot_on_browser
)
decision <-
@@ -226,6 +240,7 @@ multi_Class_Sampling <- function(in.raster,
sample2 <- init.samples
models2 <- nb_models
while (decision == "0") {
+ remove(maFo_rf)
decision2 <-
readline("Adjust init.samples/nb.models or auto [../.. or 0]: ")
if (decision2 != "0") {
@@ -253,7 +268,9 @@ multi_Class_Sampling <- function(in.raster,
last = last,
seed = seed,
init.seed = init.seed,
- parallel_mode = parallel_mode
+ save_runs = save_runs,
+ parallel_mode = parallel_mode,
+ max_num_cores = max_num_cores
)
index <- maFo_rf$index
@@ -270,20 +287,25 @@ multi_Class_Sampling <- function(in.raster,
g = RGB[2],
b = RGB[3],
acc = acc,
- outPath = outPath
+ outPath = outPath,
+ plot_on_browser = plot_on_browser
)
decision <-
readline("Threshold for Habitat Extraction or Sample Again [../0]: ")
}
- run1 <- maFo_rf
if (i < 10) {
ni <- paste("0", i, sep = "")
} else{
ni <- i
}
- save(run1, file = paste(outPath, paste("Run", ni, sep = ""), sep = ""))
+
+ if ( save_runs == TRUE) {
+ run1 <- maFo_rf
+ save(run1, file = paste(outPath, paste("Run", ni, sep = ""), sep = ""))
+ remove(run1)
+ }
###rgdal version issue
not_good_workaround <- comment(dummy@crs)
comment(dummy@crs) <- ""
@@ -312,12 +334,16 @@ multi_Class_Sampling <- function(in.raster,
dummy <- maFo_rf@layer[[1]]
dummy[dummy < thres] <- 1
dummy[dummy >= thres] <- NA
+ in.raster <- in.raster * dummy
reference <- reference[-index,]
- out.reference <<- reference
classNames <- classNames[-index]
- out.names <<- classNames
- in.raster <- in.raster * dummy
- out.raster <<- in.raster
+ if (save_runs) {
+ out.reference <<- reference
+ out.names <<- classNames
+ out.raster <<- in.raster
+ }
+ remove(dummy)
+ remove(maFo_rf)
print(paste(paste("Habitat", i), "Done"))
@@ -335,6 +361,8 @@ multi_Class_Sampling <- function(in.raster,
paste("threshold_step_", ni, sep = ""),
sep = ""))
}
+ # Release memory
+ gc(full = TRUE)
if (i == r) {
print("Congratulation - you finally made it towards the last habitat")
diff --git a/R-package/R/plot_interactive.r b/R-package/R/plot_interactive.r
index 17c63efbb161a04b13327e80ae68c5f36b68deaf..7edb98876ce9c302bb72a1110ce5f8a268ef93f2 100644
--- a/R-package/R/plot_interactive.r
+++ b/R-package/R/plot_interactive.r
@@ -10,9 +10,10 @@
#' @param b blue channel (integer)
#' @param acc predictive accuracy (integer)
#' @param outPath file path for '.html export (character)
+#' @param plot_on_browser plot on the browser or inline in a notebook (default TRUE)
#'
#' @export
-iplot <- function(x, y, HaTy, r, g, b, acc, outPath) {
+iplot <- function(x, y, HaTy, r, g, b, acc, outPath, plot_on_browser = TRUE) {
#x=layerInfo, y=RGB Image
##############################################################################
if (exists("color") == F) {
@@ -165,18 +166,35 @@ iplot <- function(x, y, HaTy, r, g, b, acc, outPath) {
file = paste(outPath, 'leaflet.html', sep = ""),
append = TRUE
)
- utils::browseURL(paste(outPath, 'leaflet.html', sep =
- ""), browser = "firefox")
+ rm(mv)
+ if (plot_on_browser == TRUE) {
+ utils::browseURL(paste(outPath, 'leaflet.html', sep = ""),
+ browser = "firefox")
+ } else {
+ html_code = sprintf(
+ '',
+ paste(outPath, 'leaflet.html', sep = "")
+ )
+ IRdisplay::display_html(html_code)
+ }
} else {
htmlwidgets::saveWidget(mv,
selfcontained = FALSE,
paste(outPath, 'leaflet.html', sep = ""))
+ rm(mv)
cat(
"",
file = paste(outPath, 'leaflet.html', sep = ""),
append = TRUE
)
- utils::browseURL(paste(outPath, 'leaflet.html', sep = ""))
+ if (plot_on_browser == TRUE) {
+ utils::browseURL(paste(outPath, 'leaflet.html', sep = ""))
+ } else {
+ html_code = sprintf(
+ '',
+ paste(outPath, 'leaflet.html', sep = ""))
+ IRdisplay::display_html(html_code)
+ }
}
#cat("",
# file = "leaflet.html",
diff --git a/R-package/man/iplot.Rd b/R-package/man/iplot.Rd
index 48a16ae341f9039530014eeeef775da6b59af324..8ff53f5a10f70f491cc75e00ed43de33a0921154 100644
--- a/R-package/man/iplot.Rd
+++ b/R-package/man/iplot.Rd
@@ -4,7 +4,7 @@
\alias{iplot}
\title{Plot Habitat Types}
\usage{
-iplot(x, y, HaTy, r, g, b, acc, outPath)
+iplot(x, y, HaTy, r, g, b, acc, outPath, plot_on_browser = TRUE)
}
\arguments{
\item{x}{probability image (*rasterObject)}
@@ -22,6 +22,8 @@ iplot(x, y, HaTy, r, g, b, acc, outPath)
\item{acc}{predictive accuracy (integer)}
\item{outPath}{file path for '.html export (character)}
+
+\item{plot_on_browser}{plot on the browser or inline in a notebook (default TRUE)}
}
\description{
A quick wrapper to produce an interactive raster map of habitat type probability in a web browser using leaflet
diff --git a/R-package/man/multi_Class_Sampling.Rd b/R-package/man/multi_Class_Sampling.Rd
index 55a288b8f1558261f8e7a16df97d4c3b94a3188c..e9ee9a47a204a8dbf5e53ff579ed233be2557b3f 100644
--- a/R-package/man/multi_Class_Sampling.Rd
+++ b/R-package/man/multi_Class_Sampling.Rd
@@ -24,7 +24,10 @@ multi_Class_Sampling(
multiTest = 1,
RGB = c(19, 20, 21),
overwrite = TRUE,
- parallel_mode = FALSE
+ save_runs = TRUE,
+ parallel_mode = FALSE,
+ max_num_cores = 5,
+ plot_on_browser = TRUE
)
}
\arguments{
@@ -64,15 +67,21 @@ multi_Class_Sampling(
\item{RGB}{rgb channel numbers for image plot}
-\item{overwrite}{overwrite the results file}
+\item{overwrite}{overwrite the KML and raster files from previous runs (default TRUE)}
-\item{parallel_mode}{run loops using all available cores}
+\item{save_runs}{an Habitat object and extra info (to restart a run) is saved (default TRUE)}
+
+\item{parallel_mode}{run loops using all available cores (default FALSE)}
+
+\item{max_num_cores}{maximum number of cores for parallelism (default 5)}
+
+\item{plot_on_browser}{plot on the browser or inline in a notebook (default TRUE)}
}
\value{
4 files per step:
\enumerate{
\item Habitat type probability map as geocoded *.kml layer and *.tif raster files and *.png image output
-\item A Habitat object consisting of 7 slots: \cr
+\item A Habitat object (only if save_runs is set to TRUE) consisting of 7 slots: \cr
run1@models - list of selcted classifiers \cr
run1@ref_samples - list of SpatialPointsDataFrames with same length as run1@models holding reference labels \link{1,2} for each selected model \cr
run1@switch - vector of lenght run1@models indicating if target class equals 2, if not NA the labels need to be switched \cr
diff --git a/R-package/man/sample_nb.Rd b/R-package/man/sample_nb.Rd
index da32d5d1e6f0efab1e89f94185fb4c75058e9e51..43c7a8061da411830401b098584d1cb6b217faed 100644
--- a/R-package/man/sample_nb.Rd
+++ b/R-package/man/sample_nb.Rd
@@ -18,7 +18,9 @@ sample_nb(
last,
seed,
init.seed,
- parallel_mode
+ save_runs,
+ parallel_mode,
+ max_num_cores
)
}
\arguments{
@@ -46,7 +48,11 @@ sample_nb(
\item{init.seed}{"sample" for new or use run1@seeds to reproduce previous steps}
-\item{parallel_mode}{run loops using all available cores}
+\item{save_runs}{if the user wants to save the runs, if TRUE the complete Habitat Class object is returned}
+
+\item{parallel_mode}{run loops in parallel}
+
+\item{max_num_cores}{maximum number of cores for parallelism}
\item{nb_models}{number of models (independent classifiers) to collect}
}
@@ -56,13 +62,13 @@ a list with 3 elements:
\item An index
\item Accuracy vector
\item A vector with a Habitat objects, each consisting of 7 slots: \cr
-run1@models - list of selected classifiers \cr
-run1@ref_samples - list of SpatialPointsDataFrames with same length as run1@models holding reference labels \link{1,2} for each selected model \cr
-run1@switch - vector of length run1@models indicating if target class equals 2, if not NA the labels need to be switched \cr
+run1@models - list of selected classifiers (only if save_runs is TRUE) \cr
+run1@ref_samples - list of SpatialPointsDataFrames with same length as run1@models holding reference labels \link{1,2} for each selected model (only if save_runs is TRUE) \cr
+run1@switch - vector of length run1@models indicating if target class equals 2, if not NA the labels need to be switched (only if save_runs is TRUE) \cr
run1@layer - raster map of habitat type probability \cr
-run1@mod_all - list of all classifiers (equals nb_models) \cr
-run1@class_ind - vector of predictive distance measure for all habitats \cr
-run1@seeds - vector of seeds for random sampling \cr
+run1@mod_all - list of all classifiers (equals nb_models) (only if save_runs is TRUE) \cr
+run1@class_ind - vector of predictive distance measure for all habitats (only if save_runs is TRUE) \cr
+run1@seeds - vector of seeds for random sampling (only if save_runs is TRUE) \cr
all files are saved with step number, the *.tif file is additionally saved with class names
}
}
diff --git a/demo/HabitatSampler.ipynb b/demo/HabitatSampler.ipynb
index 67852415ae29aae2d89f56416892677c87986360..df023cfeca04ff5c5ed84281df2e8623af5a721f 100644
--- a/demo/HabitatSampler.ipynb
+++ b/demo/HabitatSampler.ipynb
@@ -27,31 +27,23 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Installing package into ‘/home/romulo/R/x86_64-pc-linux-gnu-library/3.6’\n",
- "(as ‘lib’ is unspecified)\n",
- "\n",
- "Installing package into ‘/home/romulo/R/x86_64-pc-linux-gnu-library/3.6’\n",
- "(as ‘lib’ is unspecified)\n",
- "\n",
- "Installing package into ‘/home/romulo/R/x86_64-pc-linux-gnu-library/3.6’\n",
- "(as ‘lib’ is unspecified)\n",
- "\n",
- "Installing package into ‘/home/romulo/R/x86_64-pc-linux-gnu-library/3.6’\n",
- "(as ‘lib’ is unspecified)\n",
- "\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
- "install.packages(\"https://cran.r-project.org/src/contrib/Archive/BH/BH_1.69.0-1.tar.gz\", repos=NULL, type=\"source\")\n",
- "install.packages(\"https://cran.r-project.org/src/contrib/Archive/sf/sf_0.8-1.tar.gz\", repos=NULL, type=\"source\")\n",
- "install.packages(\"https://cran.r-project.org/src/contrib/Archive/sp/sp_1.4-1.tar.gz\", repos=NULL, type=\"source\")\n",
- "install.packages(\"https://cran.r-project.org/src/contrib/Archive/rgdal/rgdal_1.4-8.tar.gz\", repos=NULL, type=\"source\") "
+ "install_dependencies <- FALSE"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "if (install_dependencies == TRUE) {\n",
+ " install.packages(\"https://cran.r-project.org/src/contrib/Archive/BH/BH_1.69.0-1.tar.gz\", repos=NULL, type=\"source\")\n",
+ " install.packages(\"https://cran.r-project.org/src/contrib/Archive/sf/sf_0.8-1.tar.gz\", repos=NULL, type=\"source\")\n",
+ " install.packages(\"https://cran.r-project.org/src/contrib/Archive/sp/sp_1.4-1.tar.gz\", repos=NULL, type=\"source\")\n",
+ " install.packages(\"https://cran.r-project.org/src/contrib/Archive/rgdal/rgdal_1.4-8.tar.gz\", repos=NULL, type=\"source\") \n",
+ "}"
]
},
{
@@ -65,89 +57,18 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
- "from_sources <- FALSE"
+ "from_sources <- TRUE"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Downloading git repo https://git.gfz-potsdam.de/habitat-sampler/HabitatSampler.git\n",
- "\n",
- "'/usr/bin/git' clone --depth 1 --no-hardlinks https://git.gfz-potsdam.de/habitat-sampler/HabitatSampler.git /tmp/RtmpLaI3S7/filede3c1ec5d7e\n",
- "\n",
- "'/usr/bin/git' fetch origin performance\n",
- "\n",
- "'/usr/bin/git' checkout FETCH_HEAD\n",
- "\n",
- "Downloading package from url: https://cran.r-project.org/src/contrib/Archive/velox/velox_0.2.0.tar.gz\n",
- "\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\u001b[32m✔\u001b[39m \u001b[38;5;247mchecking for file ‘/tmp/RtmpLaI3S7/remotesde3c5959756f/velox/DESCRIPTION’\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mpreparing ‘velox’:\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[32m✔\u001b[39m \u001b[38;5;247mchecking DESCRIPTION meta-information\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mcleaning src\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mchecking for LF line-endings in source and make files and shell scripts\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mchecking for empty or unneeded directories\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mbuilding ‘velox_0.2.0.tar.gz’\u001b[39m\u001b[36m\u001b[39m\n",
- " \n",
- "\r"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Installing package into ‘/home/romulo/R/x86_64-pc-linux-gnu-library/3.6’\n",
- "(as ‘lib’ is unspecified)\n",
- "\n",
- "Downloading package from url: https://cran.r-project.org/src/contrib/Archive/velox/velox_0.2.0.tar.gz\n",
- "\n",
- "Skipping velox, it is already being installed\n",
- "\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\u001b[32m✔\u001b[39m \u001b[38;5;247mchecking for file ‘/tmp/RtmpLaI3S7/filede3c1ec5d7e/R-package/DESCRIPTION’\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mpreparing ‘HaSa’:\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[32m✔\u001b[39m \u001b[38;5;247mchecking DESCRIPTION meta-information\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247minstalling the package to build vignettes\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[32m✔\u001b[39m \u001b[38;5;247mcreating vignettes\u001b[39m\u001b[36m\u001b[36m (1.5s)\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mchecking for LF line-endings in source and make files and shell scripts\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mchecking for empty or unneeded directories\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mlooking to see if a ‘data/datalist’ file should be added\u001b[39m\u001b[36m\u001b[39m\n",
- "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m \u001b[39m\u001b[38;5;247mbuilding ‘HaSa_1.1.0.tar.gz’\u001b[39m\u001b[36m\u001b[39m\n",
- " \n",
- "\r"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Installing package into ‘/home/romulo/R/x86_64-pc-linux-gnu-library/3.6’\n",
- "(as ‘lib’ is unspecified)\n",
- "\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"if (from_sources == TRUE) {\n",
" wd<-\"./\"\n",
@@ -247,15 +168,6 @@
" Linking to sp version: 1.4-5 \n",
" Polygon checking: TRUE \n",
"\n",
- "\n",
- "\n",
- "Attaching package: ‘HaSa’\n",
- "\n",
- "\n",
- "The following object is masked from ‘package:graphics’:\n",
- "\n",
- " clip\n",
- "\n",
"\n"
]
},
@@ -345,7 +257,7 @@
".list-inline>li {display: inline-block}\n",
".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
"\n",
- "- 'HaSa'
- 'htmlwidgets'
- 'leaflet'
- 'rgeos'
- 'velox'
- 'devtools'
- 'usethis'
- 'e1071'
- 'randomForest'
- 'spatialEco'
- 'maptools'
- 'raster'
- 'rgdal'
- 'sp'
- 'stats'
- 'graphics'
- 'grDevices'
- 'utils'
- 'datasets'
- 'methods'
- 'base'
\n",
+ "- 'IRdisplay'
- 'htmlwidgets'
- 'leaflet'
- 'rgeos'
- 'velox'
- 'devtools'
- 'usethis'
- 'e1071'
- 'randomForest'
- 'spatialEco'
- 'maptools'
- 'raster'
- 'rgdal'
- 'sp'
- 'stats'
- 'graphics'
- 'grDevices'
- 'utils'
- 'datasets'
- 'methods'
- 'base'
\n",
"\n",
"\n"
],
@@ -544,7 +456,7 @@
"\\end{enumerate*}\n",
"\n",
"\\item \\begin{enumerate*}\n",
- "\\item 'HaSa'\n",
+ "\\item 'IRdisplay'\n",
"\\item 'htmlwidgets'\n",
"\\item 'leaflet'\n",
"\\item 'rgeos'\n",
@@ -762,7 +674,7 @@
"\n",
"\n",
"\n",
- "12. 1. 'HaSa'\n",
+ "12. 1. 'IRdisplay'\n",
"2. 'htmlwidgets'\n",
"3. 'leaflet'\n",
"4. 'rgeos'\n",
@@ -848,7 +760,7 @@
"[16] \"grDevices\" \"utils\" \"datasets\" \"methods\" \"base\" \n",
"\n",
"[[12]]\n",
- " [1] \"HaSa\" \"htmlwidgets\" \"leaflet\" \"rgeos\" \"velox\" \n",
+ " [1] \"IRdisplay\" \"htmlwidgets\" \"leaflet\" \"rgeos\" \"velox\" \n",
" [6] \"devtools\" \"usethis\" \"e1071\" \"randomForest\" \"spatialEco\" \n",
"[11] \"maptools\" \"raster\" \"rgdal\" \"sp\" \"stats\" \n",
"[16] \"graphics\" \"grDevices\" \"utils\" \"datasets\" \"methods\" \n",
@@ -860,10 +772,11 @@
}
],
"source": [
+ "options(\"rgdal_show_exportToProj4_warnings\"=\"none\")\n",
"if (from_sources == TRUE) {\n",
- " libraries <- c(\"rgdal\",\"raster\",\"maptools\",\"spatialEco\",\"randomForest\",\"e1071\",\"devtools\",\"velox\",\"rgeos\",\"leaflet\",\"htmlwidgets\")\n",
+ " libraries <- c(\"rgdal\",\"raster\",\"maptools\",\"spatialEco\",\"randomForest\",\"e1071\",\"devtools\",\"velox\",\"rgeos\",\"leaflet\",\"htmlwidgets\", \"IRdisplay\")\n",
"} else {\n",
- " libraries <- c(\"rgdal\",\"raster\",\"maptools\",\"spatialEco\",\"randomForest\",\"e1071\",\"devtools\",\"velox\",\"rgeos\",\"leaflet\",\"htmlwidgets\", \"HaSa\")\n",
+ " libraries <- c(\"rgdal\",\"raster\",\"maptools\",\"spatialEco\",\"randomForest\",\"e1071\",\"devtools\",\"velox\",\"rgeos\",\"leaflet\",\"htmlwidgets\", \"IRdisplay\", \"HaSa\")\n",
"}\n",
"lapply(libraries, library, character.only = TRUE)"
]
@@ -1071,6 +984,15 @@
"classNames<-c(\"deciduous\",\"coniferous\",\"heather_young\",\"heather_old\",\"heather_shrub\",\"bare_ground\",\"xeric_grass\")"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "library(profvis)"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -1080,30 +1002,39 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"init.samples = 50 models = 200\"\n",
- "[1] \"class=4 difference=0.84\"\n",
+ "[1] \"init.samples = 75 models = 220\"\n",
+ "[1] \"class=5 difference=0.8\"\n",
"\n"
]
},
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"name": "stdin",
"output_type": "stream",
"text": [
- "Threshold for Habitat Extraction or Sample Again [../0]: 16\n"
+ "Threshold for Habitat Extraction or Sample Again [../0]: 15\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"n_models = 9\"\n",
+ "[1] \"n_models = 8\"\n",
"[1] 1\n",
"[1] 2\n",
"[1] 3\n",
@@ -1111,8 +1042,7 @@
"[1] 5\n",
"[1] 6\n",
"[1] 7\n",
- "[1] 8\n",
- "[1] 9\n"
+ "[1] 8\n"
]
},
{
@@ -1127,23 +1057,32 @@
"output_type": "stream",
"text": [
"[1] \"Habitat 1 Done\"\n",
- "[1] \"init.samples = 100 models = 215\"\n",
- "[1] \"class=4 difference=0.8\"\n",
+ "[1] \"init.samples = 125 models = 235\"\n",
+ "[1] \"class=4 difference=0.88\"\n",
"\n"
]
},
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"name": "stdin",
"output_type": "stream",
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- "Threshold for Habitat Extraction or Sample Again [../0]: 32\n"
+ "Threshold for Habitat Extraction or Sample Again [../0]: 24\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"n_models = 17\"\n",
+ "[1] \"n_models = 13\"\n",
"[1] 1\n",
"[1] 2\n",
"[1] 3\n",
@@ -1156,11 +1095,7 @@
"[1] 10\n",
"[1] 11\n",
"[1] 12\n",
- "[1] 13\n",
- "[1] 14\n",
- "[1] 15\n",
- "[1] 16\n",
- "[1] 17\n"
+ "[1] 13\n"
]
},
{
@@ -1175,23 +1110,32 @@
"output_type": "stream",
"text": [
"[1] \"Habitat 2 Done\"\n",
- "[1] \"init.samples = 150 models = 230\"\n",
- "[1] \"class=2 difference=0.92\"\n",
+ "[1] \"init.samples = 175 models = 250\"\n",
+ "[1] \"class=3 difference=0.84\"\n",
"\n"
]
},
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"name": "stdin",
"output_type": "stream",
"text": [
- "Threshold for Habitat Extraction or Sample Again [../0]: 44\n"
+ "Threshold for Habitat Extraction or Sample Again [../0]: 40\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"n_models = 25\"\n",
+ "[1] \"n_models = 22\"\n",
"[1] 1\n",
"[1] 2\n",
"[1] 3\n",
@@ -1213,10 +1157,7 @@
"[1] 19\n",
"[1] 20\n",
"[1] 21\n",
- "[1] 22\n",
- "[1] 23\n",
- "[1] 24\n",
- "[1] 25\n"
+ "[1] 22\n"
]
},
{
@@ -1231,23 +1172,32 @@
"output_type": "stream",
"text": [
"[1] \"Habitat 3 Done\"\n",
- "[1] \"init.samples = 200 models = 245\"\n",
- "[1] \"class=1 difference=0.96\"\n",
+ "[1] \"init.samples = 225 models = 265\"\n",
+ "[1] \"class=3 difference=0.92\"\n",
"\n"
]
},
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"name": "stdin",
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- "Threshold for Habitat Extraction or Sample Again [../0]: 110\n"
+ "Threshold for Habitat Extraction or Sample Again [../0]: 55\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"n_models = 61\"\n",
+ "[1] \"n_models = 30\"\n",
"[1] 1\n",
"[1] 2\n",
"[1] 3\n",
@@ -1277,38 +1227,7 @@
"[1] 27\n",
"[1] 28\n",
"[1] 29\n",
- "[1] 30\n",
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- "[1] 58\n",
- "[1] 59\n",
- "[1] 60\n",
- "[1] 61\n"
+ "[1] 30\n"
]
},
{
@@ -1323,23 +1242,32 @@
"output_type": "stream",
"text": [
"[1] \"Habitat 4 Done\"\n",
- "[1] \"init.samples = 250 models = 260\"\n",
- "[1] \"class=1 difference=0.96\"\n",
+ "[1] \"init.samples = 275 models = 280\"\n",
+ "[1] \"class=2 difference=0.96\"\n",
"\n"
]
},
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"name": "stdin",
"output_type": "stream",
"text": [
- "Threshold for Habitat Extraction or Sample Again [../0]: 120\n"
+ "Threshold for Habitat Extraction or Sample Again [../0]: 85\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"n_models = 67\"\n",
+ "[1] \"n_models = 47\"\n",
"[1] 1\n",
"[1] 2\n",
"[1] 3\n",
@@ -1386,27 +1314,7 @@
"[1] 44\n",
"[1] 45\n",
"[1] 46\n",
- "[1] 47\n",
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- "[1] 67\n"
+ "[1] 47\n"
]
},
{
@@ -1421,23 +1329,32 @@
"output_type": "stream",
"text": [
"[1] \"Habitat 5 Done\"\n",
- "[1] \"init.samples = 300 models = 275\"\n",
- "[1] \"class=1 difference=0.96\"\n",
+ "[1] \"init.samples = 325 models = 295\"\n",
+ "[1] \"class=1 difference=1\"\n",
"\n"
]
},
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"name": "stdin",
"output_type": "stream",
"text": [
- "Threshold for Habitat Extraction or Sample Again [../0]: 150\n"
+ "Threshold for Habitat Extraction or Sample Again [../0]: 270\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"n_models = 81\"\n",
+ "[1] \"n_models = 144\"\n",
"[1] 1\n",
"[1] 2\n",
"[1] 3\n",
@@ -1518,7 +1435,70 @@
"[1] 78\n",
"[1] 79\n",
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+ "[1] 143\n",
+ "[1] 144\n"
]
},
{
@@ -1533,23 +1513,32 @@
"output_type": "stream",
"text": [
"[1] \"Habitat 6 Done\"\n",
- "[1] \"init.samples = 350 models = 290\"\n",
+ "[1] \"init.samples = 375 models = 310\"\n",
"[1] \"class=1 difference=0.92\"\n",
"\n"
]
},
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"name": "stdin",
"output_type": "stream",
"text": [
- "Threshold for Habitat Extraction or Sample Again [../0]: 65\n"
+ "Threshold for Habitat Extraction or Sample Again [../0]: 72\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[1] \"n_models = 37\"\n",
+ "[1] \"n_models = 39\"\n",
"[1] 1\n",
"[1] 2\n",
"[1] 3\n",
@@ -1587,17 +1576,19 @@
"[1] 35\n",
"[1] 36\n",
"[1] 37\n",
+ "[1] 38\n",
+ "[1] 39\n",
"[1] \"Habitat 7 Done\"\n",
"[1] \"Congratulation - you finally made it towards the last habitat\"\n"
]
}
],
"source": [
- "multi_Class_Sampling(\n",
+ "pros <- profvis(multi_Class_Sampling(\n",
" in.raster = a1,\n",
- " init.samples = 50,\n",
+ " init.samples = 75,\n",
" sample_type = \"regular\",\n",
- " nb_models = 200,\n",
+ " nb_models = 220,\n",
" nb_it = 10,\n",
" buffer = 15,\n",
" reference = ref,\n",
@@ -1612,8 +1603,108 @@
" n_classes = 7,\n",
" multiTest = 1,\n",
" RGB = c(19,20,21),\n",
- " overwrite=TRUE,\n",
- " parallel_mode=TRUE)"
+ " overwrite = TRUE,\n",
+ " save_runs = FALSE,\n",
+ " parallel_mode = TRUE,\n",
+ " max_num_cores = 7,\n",
+ " plot_on_browser = FALSE))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "\t\n",
+ "\t\t\n",
+ "\t\t\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\t\n",
+ "\t\n",
+ "\t\t\n",
+ "