Radius search filter: add documentation

doc/stages/filters.radiussearch.rst

@@ -0,0 +1,60 @@
+.. _filters.radiussearch:
+
+filters.radiussearch
+==========================
+
+The **radius search filter** allows you update the value of a dimension (using
+an assignment expression) for specific points depending on their neighbors
+in a given radius:
+For each point in the domain src_domain_, if it has any neighbor with a
+distance lower than radius_ that belongs to the domain reference_domain_,
+it is updated using the expression update_expression_.
+
+
+.. embed::
+
+Example 1
+---------
+
+This pipeline updates the Keypoint dimension of all points with classification
+1 to 2 (unclassified and ground) that are closer than 1 meter from a point with
+classification 6 (building)
+
+
+.. code-block:: json
+
+  [
+      "las/4_6.las",
+      {
+          "type" : "filters.radiussearch",
+          "src_domain" : "Classification[1:2]",
+          "reference_domain" : "Classification[6:6]"
+          "radius" : 1
+          "update_expression": "Keypoint = 1"
+      },
+      "output.las"
+  ]
+
+
+Options
+-------
+
+_`src_domain`
+  A :ref:`range <ranges>` which selects points to be processed by the filter.
+  Can be specified multiple times.  Points satisfying any range will be
+  processed
+
+_`reference_domain`
+  A :ref:`range <ranges>` which selects points that can are considered as
+  potential neighbors. Can be specified multiple times.
+
+_`radius`
+  An positive float which specifies the radius for the neighbors search.
+
+_`update_expression`
+  A list of :ref:`assignment expressions <Assignment Expressions>` to be applied to
+  the points that satisfy the radius search.   The list of values is evaluated in order.
+
+
+.. include:: filter_opts.rst
+

doc/stages/filters.rst

@@ -189,6 +189,7 @@ Pointwise Features
    filters.optimalneighborhood
    filters.planefit
    filters.radialdensity
+   filters.radiussearch
    filters.reciprocity
    filters.zsmooth
 
@@ -231,6 +232,9 @@ Pointwise Features
 :ref:`filters.radialdensity`
     Compute pointwise density of points within a given radius.
 
+:ref:`filters.radiussearch`
+    Assign values to a dimension       classification using k-nearest neighbor consensus voting.
+
 :ref:`filters.reciprocity`
     Compute the percentage of points that are considered uni-directional
     neighbors of a point.