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# -*- 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'
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# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
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from qgis.core import QgsVectorFileWriter, QgsSettings, QgsProcessingUtils
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from processing.core.GeoAlgorithm import GeoAlgorithm
from processing.core.parameters import ParameterVector
from processing.core.outputs import OutputVector
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from processing.tools import dataobjects
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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.
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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.
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All Processing algorithms should extend the GeoAlgorithm class.
"""
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# 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'
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def name(self):
# Unique (non-user visible) name of algorithm
return 'create_copy_of_layer'
def displayName(self):
# The name that the user will see in the toolbox
return self.tr('Create copy of layer')
def group(self):
return self.tr('Algorithms for vector layers')
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def defineCharacteristics(self):
"""Here we define the inputs and output of the algorithm, along
with some other properties.
"""
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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
self.addParameter(ParameterVector(self.INPUT_LAYER,
self.tr('Input layer'), [dataobjects.TYPE_VECTOR_ANY], False))
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# We add a vector layer as output
self.addOutput(OutputVector(self.OUTPUT_LAYER,
self.tr('Output layer with selected features')))
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def processAlgorithm(self, context, feedback):
"""Here is where the processing itself takes place.
:param context:
"""
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# The first thing to do is retrieve the values of the parameters
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# 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 layer (a
# QgsVectorLayer in this case) using the
# QgsProcessingUtils.mapLayerFromString() method.
vectorLayer = QgsProcessingUtils.mapLayerFromString(inputFilename, context)
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# 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 = QgsSettings()
systemEncoding = settings.value('/UI/encoding', 'System')
writer = QgsVectorFileWriter(output,
systemEncoding,
vectorLayer.fields(),
vectorLayer.wkbType(),
vectorLayer.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 = QgsProcessingUtils.getFeatures(vectorLayer, context)
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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