Juergen E. Fischer e8b954537e indentation update
2013-08-25 10:48:41 +02:00

116 lines
4.8 KiB
Python

# -*- coding: utf-8 -*-
"""
***************************************************************************
__init__.py
---------------------
Date : July 2013
Copyright : (C) 2013 by Victor Olaya
Email : volayaf at gmail dot com
***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************
"""
__author__ = 'Victor Olaya'
__date__ = 'July 2013'
__copyright__ = '(C) 2013, Victor Olaya'
# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from qgis.core import *
from processing.core.Processing import Processing
from processing.core.GeoAlgorithm import GeoAlgorithm
from processing.core.QGisLayers import QGisLayers
from processing.parameters.ParameterVector import ParameterVector
from processing.outputs.OutputVector import OutputVector
class ExampleAlgorithm(GeoAlgorithm):
'''This is an example algorithm that takes a vector layer and creates
a new one just with just those features of the input layer that are
selected.
It is meant to be used as an example of how to create your own
algorithms and explain methods and variables used to do it. An algorithm
like this will be available in all elements, and there is not need
for additional work.
All processing algorithms should extend the GeoAlgorithm class.
'''
# constants used to refer to parameters and outputs.
# They will be used when calling the algorithm from another algorithm,
# or when calling from the QGIS console.
OUTPUT_LAYER = "OUTPUT_LAYER"
INPUT_LAYER = "INPUT_LAYER"
def defineCharacteristics(self):
'''Here we define the inputs and output of the algorithm, along
with some other properties
'''
# the name that the user will see in the toolbox
self.name = "Create copy of layer"
# the branch of the toolbox under which the algorithm will appear
self.group = "Algorithms for vector layers"
# we add the input vector layer. It can have any kind of geometry
# It is a mandatory (not optional) one, hence the False argument
self.addParameter(ParameterVector(self.INPUT_LAYER, "Input layer", [ParameterVector.VECTOR_TYPE_ANY], False))
# we add a vector layer as output
self.addOutput(OutputVector(self.OUTPUT_LAYER, "Output layer with selected features"))
def processAlgorithm(self, progress):
'''Here is where the processing itself takes place'''
# the first thing to do is retrieve the values of the parameters
# entered by the user
inputFilename = self.getParameterValue(self.INPUT_LAYER)
output = self.getOutputValue(self.OUTPUT_LAYER)
# input layers vales are always a string with its location.
# That string can be converted into a QGIS object (a QgsVectorLayer in
# this case) using the Processing.getObjectFromUri() method.
vectorLayer = QGisLayers.getObjectFromUri(inputFilename)
# And now we can process
# First we create the output layer. The output value entered by the user
# is a string containing a filename, so we can use it directly
settings = QSettings()
systemEncoding = settings.value( "/UI/encoding", "System" )
provider = vectorLayer.dataProvider()
writer = QgsVectorFileWriter(output,
systemEncoding,
provider.fields(),
provider.geometryType(),
provider.crs()
)
# Now we take the features from input layer and add them to the output.
# Method features() returns an iterator, considering the selection that
# might exist in layer and the configuration that indicates
# should algorithm use only selected features or all of them
features = QGisLayers.features(vectorLayer)
for f in features:
writer.addFeature(f)
# There is nothing more to do here. We do not have to open the layer
# that we have created. The framework will take care of that, or will handle
# it if this algorithm is executed within a complex model