Update inversedistanceweighted.rst

Author: lucalanteri

python/plugins/processing/algs/saga/help/inversedistanceweighted.rst

@@ -3,21 +3,54 @@ INVERSE DISTANCE WEIGHTED
 
 Description
 -----------
+It uses a point shapes data layer to provide values for “control points”. 
+The points are irregularly distributed. A numeric attribute is chosen from the attribute table 
+linked to the shapes data layer. The attribute data are the data values for the control points.
 
 Parameters
 ----------
 
-- ``Points[Vector]``:
-- ``Attribute[TableField]``:
+- ``Points[Vector]``: 
+	Points shapes data layer for input.
+	
+- ``Attribute[TableField]``: 
+	Identifying the attribute of the point shapes data layer that will provide the numeric 
+	data for the point objects
+	
 - ``Target Grid[Selection]``:
+	Grid data layer that will contain the interpolated data values as grid cell data. 
+	With “user defined” option (default) user must enter the target dimensions for the output 
+	grid data layer. Other options are:
+	- ‘Grid Size’: the length of one side of the grid cells defining the grid data layer.
+	- ‘Fit Extent’: if the box is checked, the west-east and north-south boundaries of the generated grid 
+	  data layer will be defined by the minimum and maximum x and y coordinates for the data points. 
+	  When the box is un-checked, the coordinate values entered for the ‘X-Extent’ and ‘Y-Extent’ parameters 
+	  will be used to define the boundaries for the generated grid data layer.
+	- “grid project”:allows the user to choose an existing grid system. 
+	- “grid”: it allows to choose a specific grid data layer to provide the target dimensions for the output 
+	  grid data layer. The numeric data type used in the chosen grid data layer will be the same type used 
+	  in the output grid data layer.
+	
 - ``Distance Weighting[Selection]``:
 - ``Inverse Distance Power[Number]``:
+	The degree of the equation used in the interpolation
+	
 - ``Exponential and Gaussian Weighting Bandwidth[Number]``:
 - ``Search Range[Selection]``:
+	The distance out from each known data point the algorithm will search to locate additional known data 
+	points for use in the interpolation equation. The default is 100.
+	
 - ``Search Radius[Number]``:
 - ``Search Mode[Selection]``:
+	There are two search modes to choose. The default is “all directions”. The second choice is “quadrants”. 
+	In this case, the search will be on a quadrant basis. When it finds the ‘Maximum Points’ in the quadrant, 
+	it will move to the next point object.
+
 - ``Number of Points[Selection]``:
 - ``Maximum Number of Points[Number]``:
+	Identifies how many points will be sought for use in the interpolation formula. 
+	The default maximum number of points is 10.
+	
 - ``Output extent[Extent]``:
 - ``Cellsize[Number]``: