Merge branch 'master' into carsten_optimization

R-package/NAMESPACE

@@ -9,8 +9,9 @@ export(multi_Class_Sampling)
 export(plot_configuration)
 export(plot_results)
 export(sample_nb)
+export(saveSamplePoints)
 export(save_class_tiff)
 export(save_kml)
 export(save_run)
-export(write_Out_Samples)
+export(writeOutSamples)
 exportClasses(Habitat)

R-package/R/WriteOutSamples.r

-#' Sample Collection for Habitat Types
-#'
-#'Writes out a set of samples (SpatialPointsDataFrame) into ESRI shapefiles or a GeoJSON file for a selected habitat type. Each point represents a valid sample location that identifies the selected habitat type.
-#'
-#' @param inPath file path (character) for results of habitat type sampling and probability mapping (same as outPath from function multi_Class_Sampling)
-#' @param step step number (numeric)
-#' @param className name (character) of habitat type for which samples should be selected
-#' @param output_format format (character) of output; whether shp (default) or geojson
-#'
-#' @return ESRI shapefiles/GeoJSON with name: RefHaSa_step_classname.shp/RefHaSa_step_classname.geojson
-#' 1) Point Shape represents pixel that belong to selected habitat type and can be used as reference for further model building
-#'
-#'
-#' @export
-
-###write out selected samples
-write_Out_Samples <- function (inPath, step, className, output_format = c("shp", "geojson")) {
-
-  paste(inPath, "step_", step, "_", className, ".tif", sep = "")
-  run1 <- get(load(paste(inPath, "Run", step, sep = "")))
-  load(paste(inPath, "threshold_step_", step, sep = ""))
-  dummy_sample <-
-    raster::raster(paste(inPath, "step_", step, "_", className, ".tif", sep =
-                           ""))
-
-  length_threshold <- length(threshold)
-  thres <- threshold[length_threshold]
-  dummy_sample[dummy_sample < thres] <- NA
-  dummy_sample[dummy_sample >= thres] <- 1
-
-  collect <- list()
-  j <- 0
-
-  ###extract only class samples
-  for (i in 1:length(run1@ref_samples)) {
-    if (length(dim(run1@ref_samples[[i]])) != 0)
-    {
-      if (is.na(run1@switch[i]) == F) {
-        j = j + 1
-        collect[[j]] <-
-          run1@ref_samples[[i]][which(run1@ref_samples[[i]]@data == 1), ]
-      } else
-      {
-        j = j + 1
-        collect[[j]] <-
-          run1@ref_samples[[i]][which(run1@ref_samples[[i]]@data == 2), ]
-      }
-    }
-  }
-  
-  result <- do.call(rbind, collect)
-
-  res <- raster::extract(dummy_sample, result)
-  if (length(which(is.na(res))) > 0) {
-    res <- result[-which(is.na(res)), ]
-  }
-  
-  output_format <- match.arg(output_format)
-  
-  if (output_format == "geojson") {
-    crs_dummy <- sp::proj4string(dummy_sample)
-    crs(res) <- crs_dummy
-    res <- sp::spTransform(res, CRS("+proj=longlat +datum=WGS84 +init=epsg:4326"))
-    
-    rgdal::writeOGR(
-      res,
-      layer = paste("RefHaSa_step_", step, "_", className, sep = ""),
-      dsn = paste(inPath, "RefHaSa_step_", step, "_", className, ".geojson", sep = ""),
-      driver = "GeoJSON",
-      check_exists = TRUE,
-      overwrite_layer = TRUE
-    ) 
-   } else {
-      crs_dummy <- sp::proj4string(dummy_sample)
-      crs(res) <- crs_dummy
-      res <- sp::spTransform(res, CRS("+proj=longlat +datum=WGS84 +init=epsg:4326"))
-
-      rgdal::writeOGR(
-        res,
-        layer = paste("RefHaSa_step_", step, "_", className, sep = ""),
-        dsn = paste(inPath, "RefHaSa_", className, "_", step, ".shp", sep = ""),
-        driver = "ESRI Shapefile",
-        check_exists = TRUE,
-        overwrite_layer = TRUE
-      )
-     }
-}

R-package/R/inner_procedure.r

@@ -267,7 +267,6 @@ sample_nb <- function(raster,
   flush(stdout())
   switch <- switch[ch, index]
   points <- points_list[ch]
-  remove(points_list)
   dif <- dif[2,]
   ##############################################################################
   ###Vohersage
@@ -315,8 +314,8 @@ sample_nb <- function(raster,
     obj <- new(
       "Habitat",
       models = list(),
-      ref_samples = list(),
-      switch = vector(),
+      ref_samples = points,
+      switch = switch,
       layer = layer,
       mod_all = list(),
       class_ind = 0,

R-package/R/outer_procedure.r

@@ -28,7 +28,7 @@
 #' @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
+#' 1) Habitat type probability map as geocoded *.kmz file (with a *.kml layer and *.png image output), and *.tif raster file 
 #' 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
@@ -491,9 +491,7 @@ multi_Class_Sampling <- function(in.raster,
 
     if ( save_runs == TRUE) {
       run1 <- maFo_rf
-      save_run(outPath,
-               ni,
-               run1)
+      save_run(outPath = outPath, step = ni, run1 = run1)
       remove(run1)
     }
  

R-package/R/plot_results.r

@@ -12,6 +12,23 @@
 #'
 #' @export
 plot_results <- function(inPath, color = NULL) {
+    num_files <- length(list.files(
+        inPath,
+        pattern = ".kmz$",
+        all.files = FALSE,
+        include.dirs = TRUE,
+        no.. = TRUE
+    ))
+    
+    if (num_files == 0) {
+        num_files <- length(list.files(
+            inPath,
+            pattern = ".kml$",
+            all.files = FALSE,
+            include.dirs = TRUE,
+            no.. = TRUE
+        ))  
+    }
 
     # Compares the number of .png to that of step_*.tif. If step_*.tif files are missing the
     # user's attention is drawn.
@@ -21,14 +38,8 @@ plot_results <- function(inPath, color = NULL) {
         all.files = FALSE,
         include.dirs = TRUE,
         no.. = TRUE
-    )) != length(list.files(
-        inPath,
-        pattern = ".png$",
-        all.files = FALSE,
-        include.dirs = TRUE,
-        no.. = TRUE
-    ))) {
-        message("Make sure the number of the step_*.tif files fits to the number of the .png files and that
+    )) != num_files) {
+        message("Make sure the number of the step_*.tif files fits to the number of the step_*.km(l|z) files and that
                 there are no other files from previous runs.
                 If you have resumed a run, then the data of the aborted and the continued run needs 
                 to be in the Results directory. You need them for plotting the classification map.")

R-package/R/save_files.r

@@ -4,11 +4,11 @@
 #'
 #' @param outPath output path
 #' @param step step number
-#' @param run the object to be saved
+#' @param run1 the object to be saved
 #'
 #' @export
-save_run <- function(outPath, step, run) {
-  save(run, file = paste(outPath, paste("Run", step, sep = ""), sep = ""))
+save_run <- function(outPath, step, run1) {
+  save(run1, file = paste(outPath, paste("Run", step, sep = ""), sep = ""))
 }
 
 #' Save Tif
@@ -52,5 +52,175 @@ save_kml <- function(outPath, step, raster, overwrite) {
                                crs = "+proj=longlat +datum=WGS84",
                                method = 'ngb')
   
-  raster::KML(kml, paste(outPath, paste("step_", step, sep = ""), sep = ""), overwrite = overwrite, zip = FALSE)
+  raster::KML(kml, paste(outPath, paste("step_", step, sep = ""), sep = ""), overwrite = overwrite, zip = '')
 }
+
+
+#' Save Sample Points
+#'
+#' Saves the reference sample points
+#'
+#' @param in_path file path (character) for results of habitat type sampling and probability mapping (same as outPath from function multi_Class_Sampling)
+#' @param step step number (numeric)
+#' @param class_name name (character) of habitat type for which samples should be selected
+#' @param output_format format (character) of output; whether shp (default) or geojson
+#' @param ref_samples list of reference sample points
+#' @param ref_switch vector with switch values
+#' @param num_models number of models used for the classification of a habitat
+#' @param dummy_raster raster with probabilities for each pixel
+#'
+#' @return ESRI shapefiles/GeoJSON with name: SamplePoints_step_classname.shp/SamplePoints_step_classname.geojson
+#' 1) Point Shape/GeoJSON represents the pixels which were used to train the models for that habitat.
+#'    ESRI shapefiles have the same CRS as the input raster. GeoJSON files are in the standard CRS of GeoJSON (EPSG:4326).
+#'
+#'
+#' @export
+saveSamplePoints <-
+  function(in_path,
+           step,
+           class_name,
+           output_format = c("shp", "geojson"),
+           ref_samples,
+           ref_switch,
+           num_models,
+           dummy_raster) {
+    collect <- list()
+    j <- 0
+    dummy_raster[dummy_raster == num_models] <- NA
+    dummy_raster[dummy_raster > num_models] <- 1
+
+    ###extract only class samples
+    for (i in 1:length(ref_samples)) {
+      if (length(dim(ref_samples[[i]])) != 0)
+      {
+        if (is.na(ref_switch[i]) == F) {
+          j = j + 1
+          collect[[j]] <-
+            ref_samples[[i]][which(ref_samples[[i]]@data == 1), ]
+        } else
+        {
+          j = j + 1
+          collect[[j]] <-
+            ref_samples[[i]][which(ref_samples[[i]]@data == 2), ]
+        }
+      }
+    }
+    
+    result <- do.call(rbind, collect)
+    
+    res <- raster::extract(dummy_raster, result)
+    if (length(which(is.na(res))) > 0) {
+      result <- result[-which(is.na(res)), ]
+    }
+    raster::crs(result) <- raster::crs(dummy_raster)
+
+    output_format <- match.arg(output_format)
+    if (output_format == "geojson") {
+      # Only transform is there points to be saved.
+      if (nrow(result) > 0) {
+        result <- sp::spTransform(result, sp::CRS("+init=epsg:4326"))
+      }
+      rgdal::writeOGR(
+        obj = result,
+        layer = paste("SamplePoints_step_", step, "_", class_name, sep = ""),
+        dsn = paste(in_path, "SamplePoints_step_", step, "_", class_name, ".geojson", sep = ""),
+        driver = "GeoJSON",
+        check_exists = TRUE,
+        overwrite_layer = TRUE
+      ) 
+    } else {
+      rgdal::writeOGR(
+        obj = result,
+        layer = paste("SamplePoints_step_", step, "_", class_name, sep = ""),
+        dsn = paste(in_path, "SamplePoints_step_", step, "_", class_name, ".shp", sep = ""),
+        driver = "ESRI Shapefile",
+        check_exists = TRUE,
+        overwrite_layer = TRUE
+      )
+    }
+  }
+
+
+#' Selected Sample Collection for Habitat Types
+#'
+#' Writes out a set of samples (SpatialPointsDataFrame) into ESRI shapefiles or a GeoJSON file for a selected habitat type.
+#' Each point represents a valid sample location that identifies the selected habitat type. Only those points are selected
+#' which lay in the habitat type selected by the user's input threshold.
+#'
+#' @param in_path file path (character) for results of habitat type sampling and probability mapping (same as outPath from function multi_Class_Sampling)
+#' @param step step number (numeric)
+#' @param class_name name (character) of habitat type for which samples should be selected
+#' @param output_format format (character) of output; whether shp (default) or geojson
+#'
+#' @return ESRI shapefiles/GeoJSON with name: SamplePoints_step_classname.shp/SamplePoints_step_classname.geojson
+#' 1) Point Shape/GeoJSON represents the pixels which belong to selected habitat type and can be used as reference for further model building.
+#'    ESRI shapefiles have the same CRS as the input raster. GeoJSON files are in the standard CRS of GeoJSON (EPSG:4326).
+#'
+#'
+#' @export
+
+###write out selected samples
+writeOutSamples <- function(in_path, step, class_name, output_format = c("shp", "geojson")) {
+  run1 <- get(load(paste(in_path, "Run", step, sep = "")))
+  load(paste(in_path, "threshold_step_", step, sep = ""))
+  dummy_sample <-
+    raster::raster(paste(in_path, "step_", step, "_", class_name, ".tif", sep =
+                           ""))
+  
+  length_threshold <- length(threshold)
+  thres <- threshold[length_threshold]
+  dummy_sample[dummy_sample < thres] <- NA
+  dummy_sample[dummy_sample >= thres] <- 1
+  
+  collect <- list()
+  j <- 0
+  
+  ###extract only class samples
+  for (i in 1:length(run1@ref_samples)) {
+    if (length(dim(run1@ref_samples[[i]])) != 0)
+    {
+      if (is.na(run1@switch[i]) == F) {
+        j = j + 1
+        collect[[j]] <-
+          run1@ref_samples[[i]][which(run1@ref_samples[[i]]@data == 1), ]
+      } else
+      {
+        j = j + 1
+        collect[[j]] <-
+          run1@ref_samples[[i]][which(run1@ref_samples[[i]]@data == 2), ]
+      }
+    }
+  }
+  
+  result <- do.call(rbind, collect)
+  
+  res <- raster::extract(dummy_sample, result)
+  if (length(which(is.na(res))) > 0) {
+    result <- result[-which(is.na(res)), ]
+  }
+  raster::crs(result) <- raster::crs(dummy_sample)
+  output_format <- match.arg(output_format)
+  if (output_format == "geojson") {
+    # Only transform is there points to be saved.
+    if (nrow(result) > 0) {
+      result <- sp::spTransform(result, sp::CRS("+init=epsg:4326"))
+    }
+    rgdal::writeOGR(
+      obj = result,
+      layer = paste("sel_SamplePoints_step_", step, "_", class_name, sep = ""),
+      dsn = paste(in_path, "sel_SamplePoints_step_", step, "_", class_name, ".geojson", sep = ""),
+      driver = "GeoJSON",
+      check_exists = TRUE,
+      overwrite_layer = TRUE
+    ) 
+  } else {
+    rgdal::writeOGR(
+      obj = result,
+      layer = paste("sel_SamplePoints_step_", step, "_", class_name, sep = ""),
+      dsn = paste(in_path, "sel_SamplePoints_step_", step, "_", class_name, ".shp", sep = ""),
+      driver = "ESRI Shapefile",
+      check_exists = TRUE,
+      overwrite_layer = TRUE
+    )
+  }
+}
\ No newline at end of file

R-package/man/multi_Class_Sampling.Rd

@@ -83,7 +83,7 @@ multi_Class_Sampling(
 \value{
 4 files per step:
 \enumerate{
-\item Habitat type probability map as geocoded *.kml layer and *.tif raster files and  *.png image output
+\item Habitat type probability map as geocoded *.kmz file (with a *.kml layer and *.png image output), and *.tif raster file
 \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

R-package/man/saveSamplePoints.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/save_files.r
+\name{saveSamplePoints}
+\alias{saveSamplePoints}
+\title{Save Sample Points}
+\usage{
+saveSamplePoints(
+  in_path,
+  step,
+  class_name,
+  output_format = c("shp", "geojson"),
+  ref_samples,
+  ref_switch,
+  num_models,
+  dummy_raster
+)
+}
+\arguments{
+\item{in_path}{file path (character) for results of habitat type sampling and probability mapping (same as outPath from function multi_Class_Sampling)}
+
+\item{step}{step number (numeric)}
+
+\item{class_name}{name (character) of habitat type for which samples should be selected}
+
+\item{output_format}{format (character) of output; whether shp (default) or geojson}
+
+\item{ref_samples}{list of reference sample points}
+
+\item{ref_switch}{vector with switch values}
+
+\item{num_models}{number of models used for the classification of a habitat}
+
+\item{dummy_raster}{raster with probabilities for each pixel}
+}
+\value{
+ESRI shapefiles/GeoJSON with name: SamplePoints_step_classname.shp/SamplePoints_step_classname.geojson
+\enumerate{
+\item Point Shape/GeoJSON represents the pixels which were used to train the models for that habitat.
+ESRI shapefiles have the same CRS as the input raster. GeoJSON files are in the standard CRS of GeoJSON (EPSG:4326).
+}
+}
+\description{
+Saves the reference sample points
+}

R-package/man/save_run.Rd

@@ -4,14 +4,14 @@
 \alias{save_run}
 \title{Save a run}
 \usage{
-save_run(outPath, step, run)
+save_run(outPath, step, run1)
 }
 \arguments{
 \item{outPath}{output path}
 
 \item{step}{step number}
 
-\item{run}{the object to be saved}
+\item{run1}{the object to be saved}
 }
 \description{
 Saves the run object for a step

R-package/man/writeOutSamples.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/save_files.r
+\name{writeOutSamples}
+\alias{writeOutSamples}
+\title{Selected Sample Collection for Habitat Types}
+\usage{
+writeOutSamples(in_path, step, class_name, output_format = c("shp", "geojson"))
+}
+\arguments{
+\item{in_path}{file path (character) for results of habitat type sampling and probability mapping (same as outPath from function multi_Class_Sampling)}
+
+\item{step}{step number (numeric)}
+
+\item{class_name}{name (character) of habitat type for which samples should be selected}
+
+\item{output_format}{format (character) of output; whether shp (default) or geojson}
+}
+\value{
+ESRI shapefiles/GeoJSON with name: SamplePoints_step_classname.shp/SamplePoints_step_classname.geojson
+\enumerate{
+\item Point Shape/GeoJSON represents the pixels which belong to selected habitat type and can be used as reference for further model building.
+ESRI shapefiles have the same CRS as the input raster. GeoJSON files are in the standard CRS of GeoJSON (EPSG:4326).
+}
+}
+\description{
+Writes out a set of samples (SpatialPointsDataFrame) into ESRI shapefiles or a GeoJSON file for a selected habitat type.
+Each point represents a valid sample location that identifies the selected habitat type. Only those points are selected
+which lay in the habitat type selected by the user's input threshold.
+}

R-package/man/write_Out_Samples.Rd

-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/WriteOutSamples.r
-\name{write_Out_Samples}
-\alias{write_Out_Samples}
-\title{Sample Collection for Habitat Types}
-\usage{
-write_Out_Samples(inPath, step, className, output_format = c("shp", "geojson"))
-}
-\arguments{
-\item{inPath}{file path (character) for results of habitat type sampling and probability mapping (same as outPath from function multi_Class_Sampling)}
-
-\item{step}{step number (numeric)}
-
-\item{className}{name (character) of habitat type for which samples should be selected}
-
-\item{output_format}{format (character) of output; whether shp (default) or geojson}
-}
-\value{
-ESRI shapefiles/GeoJSON with name: RefHaSa_step_classname.shp/RefHaSa_step_classname.geojson
-\enumerate{
-\item Point Shape represents pixel that belong to selected habitat type and can be used as reference for further model building
-}
-}
-\description{
-Writes out a set of samples (SpatialPointsDataFrame) into ESRI shapefiles or a GeoJSON file for a selected habitat type. Each point represents a valid sample location that identifies the selected habitat type.
-}