Derivative writer refactor

doc/stages/writers.derivative.rst

@@ -13,8 +13,10 @@ The **Derivative Writer** supports writing of primary topographic attributes.
 .. _`GDAL`: http://gdal.org
 .. _`GeoTiff`: http://www.gdal.org/frmt_gtiff.html
 
-Example
--------
+Example #1
+----------
+
+Create a single GeoTIFF with slope values calculated using the D8 method.
 
 .. code-block:: json
 
@@ -28,6 +30,25 @@ Example
         }
       ]
     }
+    
+Example #2
+----------
+
+Create multiple GeoTIFFs containing slope, hillshade, and contour curvature
+values.
+
+.. code-block:: json
+
+    {
+      "pipeline":[
+        "inputfile.las",
+        {
+          "type":"writers.derivative",
+          "filename":"outputfile_#.tiff",
+          "primitive_type":"slope_d8,hillshade,contour_curvature"
+        }
+      ]
+    }
 
 
 Options
@@ -48,8 +69,13 @@ primitive_type
   * tangential_curvature
   * total_curvature
   * hillshade
-  * catchment_area
 
-grid_dist_x, grid_dist_y
+edge_length
   Size of grid cell in X and Y dimensions using native units of the input point
   cloud.  [Default: 15.0]
+
+altitude
+  Illumination altitude in degrees (hillshade only). [Default: 45.0]
+
+azimuth
+  Illumination azimuth in degrees (hillshade only). [Default: 315.0]

filters/pmf/PMFFilter.cpp

@@ -240,8 +240,8 @@ std::vector<PointId> PMFFilter::processGroundApprox(PointViewPtr view)
     for (PointId i = 0; i < view->size(); ++i)
         groundIdx.push_back(i);
 
-    MatrixXd ZImin = eigen::createDSM(*view.get(), rows, cols, m_cellSize,
-                                      bounds);
+    MatrixXd ZImin = eigen::createMinMatrix(*view.get(), rows, cols, m_cellSize,
+                                            bounds);
 
     // Progressively filter ground returns using morphological open
     for (size_t j = 0; j < wsvec.size(); ++j)

filters/smrf/SMRFilter.cpp

@@ -260,10 +260,11 @@ std::vector<PointId> SMRFilter::processGround(PointViewPtr view)
     // these latter techniques were nearly the same with regards to total error,
     // with the spring technique performing slightly better than the k-nearest
     // neighbor (KNN) approach.
-    MatrixXd ZImin = eigen::createDSM(*view.get(), m_numRows, m_numCols,
-                                      m_cellSize, m_bounds);
-    eigen::writeMatrix(ZImin, "zimin.tif", m_cellSize, m_bounds, srs);
 
+    MatrixXd ZImin = eigen::createMinMatrix(*view.get(), m_numRows, m_numCols,
+                                            m_cellSize, m_bounds);
+    eigen::writeMatrix(ZImin, "zimin.tif", m_cellSize, m_bounds, srs);
+
     // MatrixXd ZImin_painted = inpaintKnn(cx, cy, ZImin);
     // MatrixXd ZImin_painted = TPS(cx, cy, ZImin);
     MatrixXd ZImin_painted = expandingTPS(cx, cy, ZImin);