Merge pull request #21 from giswqs/develop

Update to use WBT backend v1.3.1

Author: giswqs

.github/workflows/R-CMD-check.yaml

@@ -14,7 +14,7 @@ jobs:
       matrix:
         config:
         - { os: windows-latest, r: '3.6', args: "--no-manual"}
-        - { os: macOS-latest, r: 'devel', args: "--no-manual"}
+        # - { os: macOS-latest, r: 'devel', args: "--no-manual"}
         # - { os: ubuntu-16.04, r: '3.2', cran: "https://demo.rstudiopm.com/all/__linux__/xenial/latest", args: "--no-manual" }
         # - { os: ubuntu-16.04, r: '3.3', cran: "https://demo.rstudiopm.com/all/__linux__/xenial/latest", args: "--no-manual" }
         # - { os: ubuntu-16.04, r: '3.4', cran: "https://demo.rstudiopm.com/all/__linux__/xenial/latest", args: "--no-manual" }

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: whitebox
 Type: Package
 Title: 'WhiteboxTools' R Frontend
-Version: 1.3.0
+Version: 1.3.1
 Description: An R frontend of the 'WhiteboxTools' library, which is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. 'WhiteboxTools' can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. 'WhiteboxTools' also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. Suggested citation: Lindsay (2016) <doi:10.1016/j.cageo.2016.07.003>.
 Authors@R: person("Qiusheng", "Wu", email = "giswqs@gmail.com", role = c("aut", "cre"))
 Maintainer: Qiusheng Wu <giswqs@gmail.com>

NAMESPACE

@@ -166,6 +166,7 @@ export(wbt_hole_proportion)
 export(wbt_horizon_angle)
 export(wbt_horton_stream_order)
 export(wbt_hypsometric_analysis)
+export(wbt_hypsometrically_tinted_hillshade)
 export(wbt_idw_interpolation)
 export(wbt_ihs_to_rgb)
 export(wbt_image_autocorrelation)
@@ -223,6 +224,7 @@ export(wbt_lidar_ransac_planes)
 export(wbt_lidar_rbf_interpolation)
 export(wbt_lidar_remove_duplicates)
 export(wbt_lidar_remove_outliers)
+export(wbt_lidar_rooftop_analysis)
 export(wbt_lidar_segmentation)
 export(wbt_lidar_segmentation_based_filter)
 export(wbt_lidar_thin)
@@ -281,6 +283,7 @@ export(wbt_modulo)
 export(wbt_mosaic)
 export(wbt_mosaic_with_feathering)
 export(wbt_multi_part_to_single_part)
+export(wbt_multidirectional_hillshade)
 export(wbt_multiply)
 export(wbt_multiscale_elevation_percentile)
 export(wbt_multiscale_roughness)

PY2R/scripts/lidar_analysis.R

@@ -1164,6 +1164,70 @@ wbt_lidar_remove_outliers <- function(input, output, radius=2.0, elev_diff=50.0,
 }
 
 
+#' Lidar rooftop analysis
+#'
+#' Identifies roof segments in a LiDAR point cloud.
+#'
+#' @param input Input LiDAR file.
+#' @param buildings Input vector build footprint polygons file.
+#' @param output Output vector polygon file.
+#' @param radius Search Radius.
+#' @param num_iter Number of iterations.
+#' @param num_samples Number of sample points on which to build the model.
+#' @param threshold Threshold used to determine inlier points.
+#' @param model_size Acceptable model size.
+#' @param max_slope Maximum planar slope.
+#' @param norm_diff Maximum difference in normal vectors, in degrees.
+#' @param azimuth Illumination source azimuth in degrees.
+#' @param altitude Illumination source altitude in degrees.
+#' @param wd Changes the working directory.
+#' @param verbose_mode Sets verbose mode. If verbose mode is False, tools will not print output messages.
+#'
+#' @return Returns the tool text outputs.
+#' @export
+wbt_lidar_rooftop_analysis <- function(buildings, output, i=NULL, radius=2.0, num_iter=50, num_samples=10, threshold=0.15, model_size=15, max_slope=65.0, norm_diff=10.0, azimuth=180.0, altitude=30.0, wd=NULL, verbose_mode=FALSE) {
+  wbt_init()
+  args <- ""
+  args <- paste(args, paste0("--buildings=", buildings))
+  args <- paste(args, paste0("--output=", output))
+  if (!is.null(i)) {
+    args <- paste(args, paste0("--i=", i))
+  }
+  if (!is.null(radius)) {
+    args <- paste(args, paste0("--radius=", radius))
+  }
+  if (!is.null(num_iter)) {
+    args <- paste(args, paste0("--num_iter=", num_iter))
+  }
+  if (!is.null(num_samples)) {
+    args <- paste(args, paste0("--num_samples=", num_samples))
+  }
+  if (!is.null(threshold)) {
+    args <- paste(args, paste0("--threshold=", threshold))
+  }
+  if (!is.null(model_size)) {
+    args <- paste(args, paste0("--model_size=", model_size))
+  }
+  if (!is.null(max_slope)) {
+    args <- paste(args, paste0("--max_slope=", max_slope))
+  }
+  if (!is.null(norm_diff)) {
+    args <- paste(args, paste0("--norm_diff=", norm_diff))
+  }
+  if (!is.null(azimuth)) {
+    args <- paste(args, paste0("--azimuth=", azimuth))
+  }
+  if (!is.null(altitude)) {
+    args <- paste(args, paste0("--altitude=", altitude))
+  }
+  if (!is.null(wd)) {
+    args <- paste(args, paste0("--wd=", wd))
+  }
+  tool_name <- as.character(match.call()[[1]])
+  wbt_run_tool(tool_name, args, verbose_mode)
+}
+
+
 #' Lidar segmentation
 #'
 #' Segments a LiDAR point cloud based on differences in the orientation of fitted planar surfaces and point proximity.

PY2R/scripts/terrain_analysis.R

@@ -680,6 +680,62 @@ wbt_hypsometric_analysis <- function(inputs, output, watershed=NULL, wd=NULL, ve
 }
 
 
+#' Hypsometrically tinted hillshade
+#'
+#' Creates an colour shaded relief image from an input DEM.
+#'
+#' @param dem Input raster DEM file.
+#' @param output Output raster file.
+#' @param altitude Illumination source altitude in degrees.
+#' @param hs_weight Weight given to hillshade relative to relief (0.0-1.0).
+#' @param brightness Brightness factor (0.0-1.0).
+#' @param atmospheric Atmospheric effects weight (0.0-1.0).
+#' @param palette Options include 'atlas', 'high_relief', 'arid', 'soft', 'muted', 'purple', 'viridi', 'gn_yl', 'pi_y_g', 'bl_yl_rd', and 'deep.
+#' @param reverse Optional flag indicating whether to use reverse the palette.
+#' @param zfactor Optional multiplier for when the vertical and horizontal units are not the same.
+#' @param full_mode Optional flag indicating whether to use full 360-degrees of illumination sources.
+#' @param wd Changes the working directory.
+#' @param verbose_mode Sets verbose mode. If verbose mode is False, tools will not print output messages.
+#'
+#' @return Returns the tool text outputs.
+#' @export
+wbt_hypsometrically_tinted_hillshade <- function(dem, output, altitude=45.0, hs_weight=0.5, brightness=0.5, atmospheric=0.0, palette="atlas", reverse=FALSE, zfactor=1.0, full_mode=FALSE, wd=NULL, verbose_mode=FALSE) {
+  wbt_init()
+  args <- ""
+  args <- paste(args, paste0("--dem=", dem))
+  args <- paste(args, paste0("--output=", output))
+  if (!is.null(altitude)) {
+    args <- paste(args, paste0("--altitude=", altitude))
+  }
+  if (!is.null(hs_weight)) {
+    args <- paste(args, paste0("--hs_weight=", hs_weight))
+  }
+  if (!is.null(brightness)) {
+    args <- paste(args, paste0("--brightness=", brightness))
+  }
+  if (!is.null(atmospheric)) {
+    args <- paste(args, paste0("--atmospheric=", atmospheric))
+  }
+  if (!is.null(palette)) {
+    args <- paste(args, paste0("--palette=", palette))
+  }
+  if (reverse) {
+    args <- paste(args, "--reverse")
+  }
+  if (!is.null(zfactor)) {
+    args <- paste(args, paste0("--zfactor=", zfactor))
+  }
+  if (full_mode) {
+    args <- paste(args, "--full_mode")
+  }
+  if (!is.null(wd)) {
+    args <- paste(args, paste0("--wd=", wd))
+  }
+  tool_name <- as.character(match.call()[[1]])
+  wbt_run_tool(tool_name, args, verbose_mode)
+}
+
+
 #' Max anisotropy dev
 #'
 #' Calculates the maximum anisotropy (directionality) in elevation deviation over a range of spatial scales.
@@ -930,6 +986,42 @@ wbt_min_downslope_elev_change <- function(dem, output, wd=NULL, verbose_mode=FAL
 }
 
 
+#' Multidirectional hillshade
+#'
+#' Calculates a multi-direction hillshade raster from an input DEM.
+#'
+#' @param dem Input raster DEM file.
+#' @param output Output raster file.
+#' @param altitude Illumination source altitude in degrees.
+#' @param zfactor Optional multiplier for when the vertical and horizontal units are not the same.
+#' @param full_mode Optional flag indicating whether to use full 360-degrees of illumination sources.
+#' @param wd Changes the working directory.
+#' @param verbose_mode Sets verbose mode. If verbose mode is False, tools will not print output messages.
+#'
+#' @return Returns the tool text outputs.
+#' @export
+wbt_multidirectional_hillshade <- function(dem, output, altitude=45.0, zfactor=1.0, full_mode=FALSE, wd=NULL, verbose_mode=FALSE) {
+  wbt_init()
+  args <- ""
+  args <- paste(args, paste0("--dem=", dem))
+  args <- paste(args, paste0("--output=", output))
+  if (!is.null(altitude)) {
+    args <- paste(args, paste0("--altitude=", altitude))
+  }
+  if (!is.null(zfactor)) {
+    args <- paste(args, paste0("--zfactor=", zfactor))
+  }
+  if (full_mode) {
+    args <- paste(args, "--full_mode")
+  }
+  if (!is.null(wd)) {
+    args <- paste(args, paste0("--wd=", wd))
+  }
+  tool_name <- as.character(match.call()[[1]])
+  wbt_run_tool(tool_name, args, verbose_mode)
+}
+
+
 #' Multiscale elevation percentile
 #'
 #' Calculates surface roughness over a range of spatial scales.

PY2R/whitebox_tools.py

@@ -420,6 +420,7 @@ def list_tools(self, keywords=[]):
 
 
 
+    
 
 
     ##############
@@ -2680,6 +2681,36 @@ def hypsometric_analysis(self, inputs, output, watershed=None, callback=None):
         args.append("--output='{}'".format(output))
         return self.run_tool('hypsometric_analysis', args, callback) # returns 1 if error
 
+    def hypsometrically_tinted_hillshade(self, dem, output, altitude=45.0, hs_weight=0.5, brightness=0.5, atmospheric=0.0, palette="atlas", reverse=False, zfactor=1.0, full_mode=False, callback=None):
+        """Creates an colour shaded relief image from an input DEM.
+
+        Keyword arguments:
+
+        dem -- Input raster DEM file. 
+        output -- Output raster file. 
+        altitude -- Illumination source altitude in degrees. 
+        hs_weight -- Weight given to hillshade relative to relief (0.0-1.0). 
+        brightness -- Brightness factor (0.0-1.0). 
+        atmospheric -- Atmospheric effects weight (0.0-1.0). 
+        palette -- Options include 'atlas', 'high_relief', 'arid', 'soft', 'muted', 'purple', 'viridi', 'gn_yl', 'pi_y_g', 'bl_yl_rd', and 'deep. 
+        reverse -- Optional flag indicating whether to use reverse the palette. 
+        zfactor -- Optional multiplier for when the vertical and horizontal units are not the same. 
+        full_mode -- Optional flag indicating whether to use full 360-degrees of illumination sources. 
+        callback -- Custom function for handling tool text outputs.
+        """
+        args = []
+        args.append("--dem='{}'".format(dem))
+        args.append("--output='{}'".format(output))
+        args.append("--altitude={}".format(altitude))
+        args.append("--hs_weight={}".format(hs_weight))
+        args.append("--brightness={}".format(brightness))
+        args.append("--atmospheric={}".format(atmospheric))
+        args.append("--palette={}".format(palette))
+        if reverse: args.append("--reverse")
+        args.append("--zfactor={}".format(zfactor))
+        if full_mode: args.append("--full_mode")
+        return self.run_tool('hypsometrically_tinted_hillshade', args, callback) # returns 1 if error
+
     def max_anisotropy_dev(self, dem, out_mag, out_scale, max_scale, min_scale=3, step=2, callback=None):
         """Calculates the maximum anisotropy (directionality) in elevation deviation over a range of spatial scales.
 
@@ -2834,6 +2865,26 @@ def min_downslope_elev_change(self, dem, output, callback=None):
         args.append("--output='{}'".format(output))
         return self.run_tool('min_downslope_elev_change', args, callback) # returns 1 if error
 
+    def multidirectional_hillshade(self, dem, output, altitude=45.0, zfactor=1.0, full_mode=False, callback=None):
+        """Calculates a multi-direction hillshade raster from an input DEM.
+
+        Keyword arguments:
+
+        dem -- Input raster DEM file. 
+        output -- Output raster file. 
+        altitude -- Illumination source altitude in degrees. 
+        zfactor -- Optional multiplier for when the vertical and horizontal units are not the same. 
+        full_mode -- Optional flag indicating whether to use full 360-degrees of illumination sources. 
+        callback -- Custom function for handling tool text outputs.
+        """
+        args = []
+        args.append("--dem='{}'".format(dem))
+        args.append("--output='{}'".format(output))
+        args.append("--altitude={}".format(altitude))
+        args.append("--zfactor={}".format(zfactor))
+        if full_mode: args.append("--full_mode")
+        return self.run_tool('multidirectional_hillshade', args, callback) # returns 1 if error
+
     def multiscale_elevation_percentile(self, dem, out_mag, out_scale, sig_digits=3, min_scale=4, step=1, num_steps=10, step_nonlinearity=1.0, callback=None):
         """Calculates surface roughness over a range of spatial scales.
 
@@ -6164,6 +6215,40 @@ def lidar_remove_outliers(self, i, output, radius=2.0, elev_diff=50.0, use_media
         if classify: args.append("--classify")
         return self.run_tool('lidar_remove_outliers', args, callback) # returns 1 if error
 
+    def lidar_rooftop_analysis(self, buildings, output, i=None, radius=2.0, num_iter=50, num_samples=10, threshold=0.15, model_size=15, max_slope=65.0, norm_diff=10.0, azimuth=180.0, altitude=30.0, callback=None):
+        """Identifies roof segments in a LiDAR point cloud.
+
+        Keyword arguments:
+
+        i -- Input LiDAR file. 
+        buildings -- Input vector build footprint polygons file. 
+        output -- Output vector polygon file. 
+        radius -- Search Radius. 
+        num_iter -- Number of iterations. 
+        num_samples -- Number of sample points on which to build the model. 
+        threshold -- Threshold used to determine inlier points. 
+        model_size -- Acceptable model size. 
+        max_slope -- Maximum planar slope. 
+        norm_diff -- Maximum difference in normal vectors, in degrees. 
+        azimuth -- Illumination source azimuth in degrees. 
+        altitude -- Illumination source altitude in degrees. 
+        callback -- Custom function for handling tool text outputs.
+        """
+        args = []
+        if i is not None: args.append("--input='{}'".format(i))
+        args.append("--buildings='{}'".format(buildings))
+        args.append("--output='{}'".format(output))
+        args.append("--radius={}".format(radius))
+        args.append("--num_iter={}".format(num_iter))
+        args.append("--num_samples={}".format(num_samples))
+        args.append("--threshold={}".format(threshold))
+        args.append("--model_size={}".format(model_size))
+        args.append("--max_slope={}".format(max_slope))
+        args.append("--norm_diff={}".format(norm_diff))
+        args.append("--azimuth={}".format(azimuth))
+        args.append("--altitude={}".format(altitude))
+        return self.run_tool('lidar_rooftop_analysis', args, callback) # returns 1 if error
+
     def lidar_segmentation(self, i, output, radius=2.0, num_iter=50, num_samples=10, threshold=0.15, model_size=15, max_slope=80.0, norm_diff=10.0, maxzdiff=1.0, classes=False, ground=False, callback=None):
         """Segments a LiDAR point cloud based on differences in the orientation of fitted planar surfaces and point proximity.