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124 lines
6.1 KiB
Python
124 lines
6.1 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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SaveSelectedFeatures.py
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---------------------
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Date : August 2012
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Copyright : (C) 2012 by Victor Olaya
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Email : volayaf at gmail dot com
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***************************************************************************
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* *
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* This program is free software; you can redistribute it and/or modify *
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* it under the terms of the GNU General Public License as published by *
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* the Free Software Foundation; either version 2 of the License, or *
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* (at your option) any later version. *
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* *
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***************************************************************************
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"""
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__author__ = 'Victor Olaya'
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__date__ = 'August 2012'
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__copyright__ = '(C) 2012, Victor Olaya'
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# This will get replaced with a git SHA1 when you do a git archive
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__revision__ = '$Format:%H$'
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from processing.core.GeoAlgorithm import GeoAlgorithm
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from processing.outputs.OutputVector import OutputVector
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from processing.parameters.ParameterVector import ParameterVector
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from qgis.core import *
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from PyQt4.QtCore import *
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from PyQt4.QtGui import *
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from processing.tools import dataobjects, vector
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class SaveSelectedFeatures(GeoAlgorithm):
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'''This is an example algorithm that takes a vector layer and creates
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a new one just with just those features of the input layer that are
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selected.
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It is meant to be used as an example of how to create your own Processing
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algorithms and explain methods and variables used to do it.
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An algorithm like this will be available in all Processing elements, and
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there is not need for additional work.
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All geoprocessingalgorithms should extend the GeoAlgorithm class'''
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#constants used to refer to parameters and outputs.
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#They will be used when calling the algorithm from another algorithm,
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#or when calling from the QGIS console.
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OUTPUT_LAYER = "OUTPUT_LAYER"
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INPUT_LAYER = "INPUT_LAYER"
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def defineCharacteristics(self):
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'''Here we define the inputs and output of the algorithm, along
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with some other properties.
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This will give the algorithm its semantics, and allow to use it in the modeler.
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As a rule of thumb, do not produce anything not declared here.
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It will work fine in the toolbox, but it will not work in the modeler.
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If that's what you intend, then set self.showInModeler = False'''
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#the name that the user will see in the toolbox
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self.name = "Save selected features"
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#the branch of the toolbox under which the algorithm will appear
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self.group = "Vector general tools"
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#we add the input vector layer. It can have any kind of geometry
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#It is a mandatory (not optional) one, hence the False argument
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self.addParameter(ParameterVector(self.INPUT_LAYER, "Input layer", [ParameterVector.VECTOR_TYPE_ANY], False))
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# we add a vector layer as output
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self.addOutput(OutputVector(self.OUTPUT_LAYER, "Output layer with selected features"))
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def processAlgorithm(self, progress):
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'''Here is where the processing itself takes place'''
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#the first thing to do is retrieve the values of the parameters
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#entered by the user.
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#The getParameterValue will return the value with its corresponding type,
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#strings in the case of inputs and outputs
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inputFilename = self.getParameterValue(self.INPUT_LAYER)
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#The output. It will get the value of the destinatation file entered by the user.
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#If the user select "Save to temporary file", when we arrive here it will already have an asigned value,
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#which will be a temporary file using the first supported file format of the corresponding algorithm provider
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output = self.getOutputFromName(self.OUTPUT_LAYER)
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#input layers values are always a string with its location.
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#That string can be converted into a QGIS object (a QgsVectorLayer in this case))
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#using the processing.getObject() method
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vectorLayer = dataobjects.getObjectFromUri(inputFilename)
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#And now we can process
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#First we create the output layer.
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#To do so, we call the getVectorWriter method in the Output object.
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#That will give us a VectorWriter, that we can later use to add features.
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#The destination file has its format selected based on the file extension.
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#If the selected format is not supported, the first available format from
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#the provider is used, and the corresponding file extension appended
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provider = vectorLayer.dataProvider()
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writer = output.getVectorWriter( provider.fields(),
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provider.geometryType(),
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#this is the layer crs. By default all resulting layers are
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#assumed to be in the same crs are the inputs, and will be loaded
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#with this assumptions when executed from the toolbox.
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#The self.crs variable has to be canged in case this is not true,
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#or in case there are no input layer from which the output crs can be infered
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vectorLayer.crs() )
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#Now we take the selected features and add them to the output layer
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features = vector.features(vectorLayer)
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total = len(features)
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i = 0
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for i, feat in enumerate(features):
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writer.addFeature(feat)
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#we use the progress object to communicate with the user
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progress.setPercentage(100 * i / float(total))
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i += 1
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del writer
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#There is nothing more to do here. We do not have to open the layer that we have created.
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#The processing framework will take care of that, or will handle it if this algorithm is executed within
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#a complex model
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