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initAlgorithm() method This allows 2 benefits: - algorithms can be subclassed and have subclasses add additional parameters/outputs to the algorithm. With the previous approach of declaring parameters/outputs in the constructor, it's not possible to call virtual methods to add additional parameters/ outputs (since you can't call virtual methods from a constructor). - initAlgorithm takes a variant map argument, allowing the algorithm to dynamically adjust its declared parameters and outputs according to this configuration map. This potentially allows model algorithms which can be configured to have variable numbers of parameters and outputs at run time. E.g. a "router" algorithm which directs features to one of any number of output sinks depending on some user configured criteria.
69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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PreconfiguredAlgorithm.py
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---------------------
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Date : April 2016
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Copyright : (C) 2016 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__ = 'April 2016'
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__copyright__ = '(C) 2016, 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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import os
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from qgis.core import (QgsProcessingAlgorithm,
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QgsApplication)
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from processing.core.GeoAlgorithm import GeoAlgorithm
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from copy import deepcopy
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import json
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class PreconfiguredAlgorithm(GeoAlgorithm):
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def __init__(self, descriptionFile):
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self.descriptionFile = descriptionFile
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with open(self.descriptionFile) as f:
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self.description = json.load(f)
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GeoAlgorithm.__init__(self)
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self._name = self.description["name"]
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self._group = self.description["group"]
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def group(self):
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return self._group
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def displayName(self):
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return self._name
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def name(self):
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return os.path.splitext(os.path.basename(self.descriptionFile))[0].lower()
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def flags(self):
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return QgsProcessingAlgorithm.FlagHideFromModeler
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def execute(self, parameters, context=None, feedback=None, model=None):
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new_parameters = deepcopy(parameters)
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self.alg = QgsApplication.processingRegistry().createAlgorithmById(self.description["algname"])
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for name, value in list(self.description["parameters"].items()):
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new_parameters[name] = value
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for name, value in list(self.description["outputs"].items()):
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self.alg.setOutputValue(name, value)
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self.alg.execute(new_parameters, feedback)
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self.outputs = self.alg.outputs
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