In some previous posts we’ve seen how to create an easy script on gvSIG 2.0.
Now we show a video about how to implement a script to create a polygon shapefile that is obtained after applying a buffer to the geometries of a point layer. The buffer distance is obtained from a field of the point layer.
The steps to follow the script are:
-
We get the input layer.
- We create the data definition (Schema) of the new layer.
- We get the creation data of the new layer.
- We create the new layer.
- We scan the features of the input layer (points).
- We create the new geometries.
- We add the new feature to the new layer.
- We finish the editing of the new layer.
- We release the group of features of the input layer
The source code with comments is:
from gvsig import * def main(): #We get the active layer layer = currentLayer() #We create the data definition schema = createSchema(layer.getSchema()) schema.modify() #We get the projection crs = currentProject().getProjectionCode() #We define the path where the new layer ruta = "/home/victor/carto/influencia.shp" #We create the layer newLayer = createShape( schema, ruta, CRS = crs, geometryType = SURFACE ) #We get the features of the input layer features = layer.features() #We scan all the features for feature in features: # We get the value of the buffer influencia = feature.get("Influencia") # We create the geometry coming of the buffer on the feature geometry geom = feature.geometry().buffer(influencia) # We get the values of the input feature attributes values = feature.getValues() # We add the new geometry in the new layer values["GEOMETRY"] = geom newLayer.append(values) # We finish the editing of the new layer saving changes newLayer.commit() # We release the group of features of the input layer features.dispose()
You have to take into account that it’s necessary to use gvSIG 2.0 Final version and the Scripting Framework extension to work without problems. Although the view must have an active layer and this layer has to have a double type field called Influencia. And better, you can modify the script to adapt it to your data.
We hope you enjoyed it.