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			202 lines
		
	
	
		
			7.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			202 lines
		
	
	
		
			7.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # -*- coding: utf-8 -*-
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| 
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| """
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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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| 
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| from qgis.PyQt.QtCore import QCoreApplication
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| from qgis.core import (QgsProcessing,
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|                        QgsFeatureSink,
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|                        QgsProcessingException,
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|                        QgsProcessingAlgorithm,
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|                        QgsProcessingParameterFeatureSource,
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|                        QgsProcessingParameterFeatureSink)
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| from qgis import processing
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| 
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| 
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| class ExampleProcessingAlgorithm(QgsProcessingAlgorithm):
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|     """
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|     This is an example algorithm that takes a vector layer and
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|     creates a new identical one.
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| 
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|     It is meant to be used as an example of how to create your own
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|     algorithms and explain methods and variables used to do it. An
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|     algorithm like this will be available in all elements, and there
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|     is not need for additional work.
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| 
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|     All Processing algorithms should extend the QgsProcessingAlgorithm
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|     class.
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|     """
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| 
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|     # Constants used to refer to parameters and outputs. They will be
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|     # used when calling the algorithm from another algorithm, or when
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|     # calling from the QGIS console.
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| 
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|     INPUT = 'INPUT'
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|     OUTPUT = 'OUTPUT'
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| 
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|     def tr(self, string):
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|         """
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|         Returns a translatable string with the self.tr() function.
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|         """
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|         return QCoreApplication.translate('Processing', string)
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| 
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|     def createInstance(self):
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|         return ExampleProcessingAlgorithm()
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| 
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|     def name(self):
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|         """
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|         Returns the algorithm name, used for identifying the algorithm. This
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|         string should be fixed for the algorithm, and must not be localised.
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|         The name should be unique within each provider. Names should contain
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|         lowercase alphanumeric characters only and no spaces or other
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|         formatting characters.
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|         """
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|         return 'myscript'
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| 
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|     def displayName(self):
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|         """
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|         Returns the translated algorithm name, which should be used for any
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|         user-visible display of the algorithm name.
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|         """
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|         return self.tr('My Script')
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| 
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|     def group(self):
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|         """
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|         Returns the name of the group this algorithm belongs to. This string
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|         should be localised.
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|         """
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|         return self.tr('Example scripts')
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| 
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|     def groupId(self):
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|         """
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|         Returns the unique ID of the group this algorithm belongs to. This
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|         string should be fixed for the algorithm, and must not be localised.
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|         The group id should be unique within each provider. Group id should
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|         contain lowercase alphanumeric characters only and no spaces or other
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|         formatting characters.
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|         """
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|         return 'examplescripts'
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| 
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|     def shortHelpString(self):
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|         """
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|         Returns a localised short helper string for the algorithm. This string
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|         should provide a basic description about what the algorithm does and the
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|         parameters and outputs associated with it..
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|         """
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|         return self.tr("Example algorithm short description")
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| 
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|     def initAlgorithm(self, config=None):
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|         """
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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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|         """
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| 
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|         # We add the input vector features source. It can have any kind of
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|         # geometry.
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|         self.addParameter(
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|             QgsProcessingParameterFeatureSource(
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|                 self.INPUT,
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|                 self.tr('Input layer'),
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|                 [QgsProcessing.TypeVectorAnyGeometry]
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|             )
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|         )
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| 
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|         # We add a feature sink in which to store our processed features (this
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|         # usually takes the form of a newly created vector layer when the
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|         # algorithm is run in QGIS).
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|         self.addParameter(
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|             QgsProcessingParameterFeatureSink(
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|                 self.OUTPUT,
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|                 self.tr('Output layer')
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|             )
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|         )
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| 
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|     def processAlgorithm(self, parameters, context, feedback):
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|         """
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|         Here is where the processing itself takes place.
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|         """
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| 
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|         # Retrieve the feature source and sink. The 'dest_id' variable is used
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|         # to uniquely identify the feature sink, and must be included in the
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|         # dictionary returned by the processAlgorithm function.
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|         source = self.parameterAsSource(
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|             parameters,
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|             self.INPUT,
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|             context
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|         )
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| 
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|         # If source was not found, throw an exception to indicate that the algorithm
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|         # encountered a fatal error. The exception text can be any string, but in this
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|         # case we use the pre-built invalidSourceError method to return a standard
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|         # helper text for when a source cannot be evaluated
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|         if source is None:
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|             raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
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| 
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|         (sink, dest_id) = self.parameterAsSink(
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|             parameters,
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|             self.OUTPUT,
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|             context,
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|             source.fields(),
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|             source.wkbType(),
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|             source.sourceCrs()
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|         )
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| 
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|         # Send some information to the user
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|         feedback.pushInfo('CRS is {}'.format(source.sourceCrs().authid()))
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| 
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|         # If sink was not created, throw an exception to indicate that the algorithm
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|         # encountered a fatal error. The exception text can be any string, but in this
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|         # case we use the pre-built invalidSinkError method to return a standard
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|         # helper text for when a sink cannot be evaluated
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|         if sink is None:
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|             raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT))
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| 
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|         # Compute the number of steps to display within the progress bar and
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|         # get features from source
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|         total = 100.0 / source.featureCount() if source.featureCount() else 0
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|         features = source.getFeatures()
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| 
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|         for current, feature in enumerate(features):
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|             # Stop the algorithm if cancel button has been clicked
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|             if feedback.isCanceled():
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|                 break
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| 
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|             # Add a feature in the sink
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|             sink.addFeature(feature, QgsFeatureSink.FastInsert)
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| 
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|             # Update the progress bar
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|             feedback.setProgress(int(current * total))
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| 
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|         # To run another Processing algorithm as part of this algorithm, you can use
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|         # processing.run(...). Make sure you pass the current context and feedback
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|         # to processing.run to ensure that all temporary layer outputs are available
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|         # to the executed algorithm, and that the executed algorithm can send feedback
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|         # reports to the user (and correctly handle cancellation and progress reports!)
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|         if False:
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|             buffered_layer = processing.run("native:buffer", {
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|                 'INPUT': dest_id,
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|                 'DISTANCE': 1.5,
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|                 'SEGMENTS': 5,
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|                 'END_CAP_STYLE': 0,
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|                 'JOIN_STYLE': 0,
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|                 'MITER_LIMIT': 2,
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|                 'DISSOLVE': False,
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|                 'OUTPUT': 'memory:'
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|             }, context=context, feedback=feedback)['OUTPUT']
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| 
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|         # Return the results of the algorithm. In this case our only result is
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|         # the feature sink which contains the processed features, but some
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|         # algorithms may return multiple feature sinks, calculated numeric
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|         # statistics, etc. These should all be included in the returned
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|         # dictionary, with keys matching the feature corresponding parameter
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|         # or output names.
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|         return {self.OUTPUT: dest_id}
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