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Implement basic elements_aggregation processing algorithm
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| # -*- coding: utf-8 -*- | ||
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| """ | ||
| *************************************************************************** | ||
| * * | ||
| * 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. * | ||
| * * | ||
| *************************************************************************** | ||
| """ | ||
|
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| from qgis.PyQt.QtCore import QCoreApplication | ||
| from qgis.core import ( | ||
| QgsProcessingParameterNumber, | ||
| QgsProcessingAlgorithm, | ||
| QgsProcessingParameterEnum, | ||
| QgsProcessingParameterVectorLayer, | ||
| QgsProcessingParameterString, | ||
| QgsProcessingParameterBoolean, | ||
| QgsProcessingParameterDateTime, | ||
| QgsWkbTypes, | ||
| ) | ||
|
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| from ohsomeTools.common import AGGREGATION_SPECS | ||
| from .procDialog import run_processing_alg | ||
| from qgis.utils import iface | ||
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| class ElementsAggregation(QgsProcessingAlgorithm): | ||
| """ | ||
| This is an example algorithm that takes a vector layer and | ||
| creates a new identical one. | ||
| 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 QgsProcessingAlgorithm | ||
| 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. | ||
|
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| LAYER = "LAYER" | ||
| PARAMETER = "PARAMETER" | ||
| INPUT = "INPUT" | ||
| FILTER = "FILTER" | ||
| check_activate_temporal = "check_activate_temporal" | ||
| check_show_metadata = "check_show_metadata" | ||
| timeout_input = "timeout_input" | ||
| check_clip_geometry = "check_clip_geometry" | ||
| property_groups_check_tags = "property_groups_check_tags" | ||
| property_groups_check_metadata = "property_groups_check_metadata" | ||
| data_aggregation_format = "data_aggregation_format" | ||
| date_start = "date_start" | ||
| date_end = "date_end" | ||
| YEARS = "YEARS" | ||
| MONTHS = "MONTHS" | ||
| DAYS = "DAYS" | ||
| RADIUS = "RADIUS" | ||
| check_keep_geometryless = "check_keep_geometryless" | ||
| check_merge_geometries = "check_merge_geometries" | ||
| group_by_values_line_edit = "group_by_values_line_edit" | ||
| group_by_key_line_edit = "group_by_key_line_edit" | ||
| formats = ["json", "geojson"] | ||
| parameters = [i.split('/')[1] for i in AGGREGATION_SPECS.keys() if 'elements' in i] | ||
| group_by = [] | ||
| DENSITY = 'DENSITY' | ||
|
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||
| def tr(self, string): | ||
| """ | ||
| Returns a translatable string with the self.tr() function. | ||
| """ | ||
| return QCoreApplication.translate("Processing", string) | ||
|
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||
| def createInstance(self): | ||
| return ElementsAggregation() | ||
|
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| def name(self): | ||
| """ | ||
| Returns the algorithm name, used for identifying the algorithm. This | ||
| string should be fixed for the algorithm, and must not be localised. | ||
| The name should be unique within each provider. Names should contain | ||
| lowercase alphanumeric characters only and no spaces or other | ||
| formatting characters. | ||
| """ | ||
| return "elementsaggregation" | ||
|
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| def displayName(self): | ||
| """ | ||
| Returns the translated algorithm name, which should be used for any | ||
| user-visible display of the algorithm name. | ||
| """ | ||
| return self.tr("Elements Aggregation") | ||
|
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| def group(self): | ||
| """ | ||
| Returns the name of the group this algorithm belongs to. This string | ||
| should be localised. | ||
| """ | ||
| return self.tr("Data Aggregation") | ||
|
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| def groupId(self): | ||
| """ | ||
| Returns the unique ID of the group this algorithm belongs to. This | ||
| string should be fixed for the algorithm, and must not be localised. | ||
| The group id should be unique within each provider. Group id should | ||
| contain lowercase alphanumeric characters only and no spaces or other | ||
| formatting characters. | ||
| """ | ||
| return "dataaggregation" | ||
|
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| def shortHelpString(self): | ||
| """ | ||
| Returns a localised short helper string for the algorithm. This string | ||
| should provide a basic description about what the algorithm does and the | ||
| parameters and outputs associated with it. | ||
| """ | ||
| return self.tr("Example algorithm short description") | ||
|
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| def initAlgorithm(self, config=None): | ||
| """ | ||
| Here we define the inputs and output of the algorithm, along | ||
| with some other properties. | ||
| """ | ||
|
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||
| # We add the input vector features source. It can have any kind of | ||
| # geometry. | ||
| self.addParameter( | ||
| QgsProcessingParameterVectorLayer( | ||
| self.LAYER, self.tr("Query Layer") | ||
| ) | ||
| ) | ||
|
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||
| self.addParameter( | ||
| QgsProcessingParameterEnum( | ||
| self.PARAMETER, | ||
| self.tr("Aggregation Type"), | ||
| options=self.parameters, | ||
| defaultValue=0, | ||
| ) | ||
| ) | ||
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| self.addParameter( | ||
| QgsProcessingParameterBoolean( | ||
| self.DENSITY, | ||
| self.tr("Density"), | ||
| defaultValue=False, | ||
| ) | ||
| ) | ||
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| self.addParameter( | ||
| QgsProcessingParameterDateTime( | ||
| self.date_start, "Start Date", defaultValue="2007-10-08" | ||
| ) | ||
| ) | ||
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| self.addParameter( | ||
| QgsProcessingParameterDateTime( | ||
| self.date_end, "End Date", defaultValue="2023-07-28" | ||
| ) | ||
| ) | ||
|
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| self.addParameter( | ||
| QgsProcessingParameterString( | ||
| self.FILTER, | ||
| self.tr("Filter"), | ||
| defaultValue="building=* or (type:way and highway=residential)", | ||
| ) | ||
| ) | ||
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| self.addParameter( | ||
| QgsProcessingParameterNumber( | ||
| self.RADIUS, | ||
| "Radius [m]", | ||
| type=QgsProcessingParameterNumber.Integer, | ||
| defaultValue=100, | ||
| ) | ||
| ) | ||
|
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| '''self.addParameter( | ||
| QgsProcessingParameterEnum( | ||
| self.PARAMETER, | ||
| self.tr("Group By"), | ||
| options=self.group_by, | ||
| defaultValue=0, | ||
| optional=True | ||
| ) | ||
| )''' | ||
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| def processAlgorithm(self, parameters, context, feedback): | ||
| """ | ||
| Here is where the processing itself takes place. | ||
| """ | ||
| layer = self.parameterAsLayer(parameters, self.LAYER, context) | ||
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||
| if layer.geometryType() == QgsWkbTypes.PointGeometry: | ||
| geom = 1 | ||
| elif layer.geometryType() == QgsWkbTypes.PolygonGeometry: | ||
| geom = 2 | ||
| else: | ||
| # implement user information | ||
| pass | ||
|
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| if self.parameterAsBool(parameters, self.DENSITY, context): | ||
| density = '/density' | ||
| else: | ||
| density = '' | ||
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| processingParams = { | ||
| "geom": geom, | ||
| "selection": "data-Aggregation", | ||
| "preference": f"elements/{self.parameters[self.parameterAsInt(parameters, self.PARAMETER, context)]}{density}", | ||
| "filter": self.parameterAsString(parameters, self.FILTER, context), | ||
| "LAYER": self.parameterAsLayer(parameters, self.LAYER, context), | ||
| "RADIUS": self.parameterAsInt(parameters, self.RADIUS, context), | ||
| "date_start": self.parameterAsDateTime( | ||
| parameters, self.date_start, context | ||
| ), | ||
| "date_end": self.parameterAsDateTime( | ||
| parameters, self.date_end, context | ||
| ), | ||
| 'preference_specification': '', | ||
| 'YEARS': 0, | ||
| 'MONTHS': 0, | ||
| 'DAYS': 1, | ||
| 'data_aggregation_format': 'json', | ||
| 'check_show_metadata': '', | ||
| 'timeout_input': 0, | ||
|
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| } | ||
|
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| run_processing_alg(processingParams, feedback) | ||
|
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| # To run another Processing algorithm as part of this algorithm, you can use | ||
| # processing.run(...). Make sure you pass the current context and feedback | ||
| # to processing.run to ensure that all temporary layer outputs are available | ||
| # to the executed algorithm, and that the executed algorithm can send feedback | ||
| # reports to the user (and correctly handle cancellation and progress reports!) | ||
|
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| # Return the results of the algorithm. In this case our only result is | ||
| # the feature sink which contains the processed features, but some | ||
| # algorithms may return multiple feature sinks, calculated numeric | ||
| # statistics, etc. These should all be included in the returned | ||
| # dictionary, with keys matching the feature corresponding parameter | ||
| # or output names. | ||
| return {} |
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