update for next release

readme.txt

@@ -56,14 +56,14 @@ for more details.
 * Release Notes: *
 ******************
 
-Version 1.3.0 (XX-XX-2020)
+Version 1.3.0 (07-06-2020)
 - Tools will now output DEFLATE compressed GeoTIFFs when the --compress_rasters parameter is used.
 - Added support for a newly developed compressed LiDAR data format, the ZLidar file. All tools
   that accepted LAS file inputs and produced LAS outputs can now use '*.zlidar' files as well. I 
   have also added the LasToZlidar and ZlidarToLas tools to perform conversions. While the ZLidar
-  format does not yield compression rates as good as the popular LAZ file format, you can expect 
-  ZLidar files to be between 20-30% of the size of the equivalent LAS file. A file specification 
-  will be published in the near future to describe the open ZLidar data format.
+  format does not yield compression rates quite as good as the popular LAZ file format, you can  
+  expect ZLidar files to be between 20-30% of the size of the equivalent LAS file. A file  
+  specification will be published in the near future to describe the open ZLidar data format.
 - Added the AsciiToLas tool.
 - Added the ContoursFromRaster tool for creating a vector contour coverage from a raster surface model (DEM).
 - Added the ContoursFromPoints tool for creating a vector contour coverage from vector points.

whitebox_tools.py

@@ -419,6 +419,7 @@ def list_tools(self, keywords=[]):
 
 
 
+
 
 
     ##############
@@ -3353,7 +3354,7 @@ def wetness_index(self, sca, slope, output, callback=None):
         Keyword arguments:
 
         sca -- Input raster specific contributing area (SCA) file. 
-        slope -- Input raster slope file. 
+        slope -- Input raster slope file (in degrees). 
         output -- Output raster file. 
         callback -- Custom function for handling tool text outputs.
         """
@@ -4469,7 +4470,7 @@ def modified_k_means_clustering(self, inputs, output, out_html=None, start_clust
         args.append("--class_change={}".format(class_change))
         return self.run_tool('modified_k_means_clustering', args, callback) # returns 1 if error
 
-    def mosaic(self, output, inputs=None, method="cc", callback=None):
+    def mosaic(self, output, inputs=None, method="nn", callback=None):
         """Mosaics two or more images together.
 
         Keyword arguments: