Dear list,
I need your help with a more advanced wps python script with Geoscript. Thank
you all in advance for your valuable time and comments.
I have successfully installed the 2.5.1 Geoserver with the geoscript and wps
extensions and implemented some simple examples as the one described here:
http://suite.opengeo.org/opengeo-docs/processing/scripting/processcreate.html
I have also successfully implemented my own wps that combines gs:BarnesSurface
and gs:Contour
For your help gs:Contour is defined here:
http://www.massapi.com/source/geoserver-2.1.1-src/geoserver-2.1.1/extension/wps/wps-core/src/main/java/org/geoserver/wps/gs/ContourProcess.java.html
As you can see it requires as input either levels that is type double[] either
interval that is type Double
The following code is working fine having "interval" in place of "levels" and
"Double" instead of "ArrayList<Double>()" but I can't find how I should define
levels1 in order to make it work with Double[].
I have made some efforts as the following code that is throwing an error
org.geotools.process.ProcessException: Could not convert -100 to target type [D
Do you have any ideas how to define levels1 in order to make it work?
Kind Regars,
Vassilis Dalakas
________________
from java.lang import String, Integer, Double
from geoscript.layer import Layer, Raster
from geoserver.wps import process
from geoscript.process import Process
from geoscript.geom import *
from org.geotools.data.simple import SimpleFeatureCollection
from org.geotools.geometry.jts import ReferencedEnvelope
from org.geotools.coverage.grid import GridCoverage2D
from java.util import ArrayList as ArrayList
barnes = Process.lookup('gs:BarnesSurface')
contour = Process.lookup('gs:Contour')
@process(
title = 'Barnes and Contour',
description = 'Uses Barnes Analysis to compute an interpolated surface over a
set of irregular data points and computes contour lines at specified intervals
or levels for the values in a raster.',
inputs = {
'data1': (SimpleFeatureCollection, 'Input features'),
'valueAttr1': (String, 'Name of attribute containing the data value to be
interpolated'),
'scale1': (Double, 'Length scale for the interpolation, in units of the
source data CRS'),
'maxObservationDistance1': (Double, 'Maximum distance to an observation for
it to support a grid cell, in units of the source CRS (default = 0, meaning all
observations used)'),
'pixelsPerCell1': (Integer, 'Resolution of the computed grid in pixels per
grid cell (default = 1)'),
'queryBuffer1': (Double, 'Distance to expand the query envelope by, in units
of the source CRS (larger values provide a more stable surface)'),
'outputBBOX1': (ReferencedEnvelope, 'Bounding box for output'),
'outputWidth1': (Integer, 'Width of the output raster in pixels'),
'outputHeight1': (Integer, 'Height of the output raster in pixels'),
'levels1': (ArrayList<Double>(), 'Values of levels at which to generate
contours')
},
outputs = {
'result': (SimpleFeatureCollection, 'Contour line features. Contour level is
in value attribute.')
}
)
def run(data1, valueAttr1, scale1, maxObservationDistance1, pixelsPerCell1,
queryBuffer1, outputBBOX1, outputWidth1, outputHeight1, levels1):
barnesed = barnes.run(data=data1, valueAttr=valueAttr1, scale=scale1,
maxObservationDistance=maxObservationDistance1, pixelsPerCell=pixelsPerCell1,
queryBuffer=queryBuffer1, outputBBOX=outputBBOX1, outputWidth=outputWidth1,
outputHeight=outputHeight1)['result']
return contour.run(data=barnesed, levels=levels1)['result']
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