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Port random selection algorithms to new API
And heavily optimise random selection within subsets alg
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Nyall Dawson
parent
a64d199e6f
commit
7ab82444f1
@ -99,6 +99,8 @@ from .RandomPointsAlongLines import RandomPointsAlongLines
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from .RandomPointsExtent import RandomPointsExtent
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from .RandomPointsLayer import RandomPointsLayer
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from .RandomPointsPolygons import RandomPointsPolygons
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from .RandomSelection import RandomSelection
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from .RandomSelectionWithinSubsets import RandomSelectionWithinSubsets
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from .RasterLayerStatistics import RasterLayerStatistics
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from .RegularPoints import RegularPoints
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from .ReverseLineDirection import ReverseLineDirection
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@ -135,8 +137,6 @@ from .VoronoiPolygons import VoronoiPolygons
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from .ZonalStatistics import ZonalStatistics
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# from .ExtractByLocation import ExtractByLocation
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# from .RandomSelection import RandomSelection
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# from .RandomSelectionWithinSubsets import RandomSelectionWithinSubsets
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# from .SelectByLocation import SelectByLocation
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# from .SpatialJoin import SpatialJoin
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# from .GridLine import GridLine
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@ -185,7 +185,6 @@ class QGISAlgorithmProvider(QgsProcessingProvider):
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def getAlgs(self):
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# algs = [
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# RandomSelection(), RandomSelectionWithinSubsets(),
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# SelectByLocation(),
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# ExtractByLocation(),
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# SpatialJoin(),
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@ -270,6 +269,8 @@ class QGISAlgorithmProvider(QgsProcessingProvider):
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RandomPointsExtent(),
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RandomPointsLayer(),
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RandomPointsPolygons(),
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RandomSelection(),
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RandomSelectionWithinSubsets(),
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RasterLayerStatistics(),
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RegularPoints(),
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ReverseLineDirection(),
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@ -30,13 +30,16 @@ import os
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import random
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from qgis.PyQt.QtGui import QIcon
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from qgis.core import QgsFeatureSink, QgsProcessingUtils
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from qgis.core import (QgsFeatureSink,
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QgsProcessingException,
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QgsProcessingUtils,
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QgsProcessingParameterVectorLayer,
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QgsProcessingParameterEnum,
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QgsProcessingParameterNumber,
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QgsProcessingParameterFeatureSink,
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QgsProcessingOutputVectorLayer)
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from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
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from processing.core.GeoAlgorithmExecutionException import GeoAlgorithmExecutionException
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from processing.core.parameters import ParameterSelection
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from processing.core.parameters import ParameterVector
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from processing.core.parameters import ParameterNumber
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from processing.core.outputs import OutputVector
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pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]
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@ -61,13 +64,14 @@ class RandomSelection(QgisAlgorithm):
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self.methods = [self.tr('Number of selected features'),
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self.tr('Percentage of selected features')]
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self.addParameter(ParameterVector(self.INPUT,
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self.tr('Input layer')))
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self.addParameter(ParameterSelection(self.METHOD,
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self.tr('Method'), self.methods, 0))
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self.addParameter(ParameterNumber(self.NUMBER,
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self.tr('Number/percentage of selected features'), 0, None, 10))
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self.addOutput(OutputVector(self.OUTPUT, self.tr('Selection'), True))
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self.addParameter(QgsProcessingParameterVectorLayer(self.INPUT,
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self.tr('Input layer')))
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self.addParameter(QgsProcessingParameterEnum(self.METHOD,
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self.tr('Method'), self.methods, False, 0))
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self.addParameter(QgsProcessingParameterNumber(self.NUMBER,
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self.tr('Number/percentage of selected features'), QgsProcessingParameterNumber.Integer,
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10, False, 0.0, 999999999999.0))
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self.addOutput(QgsProcessingOutputVectorLayer(self.OUTPUT, self.tr('Selected (random)')))
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def name(self):
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return 'randomselection'
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@ -76,23 +80,20 @@ class RandomSelection(QgisAlgorithm):
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return self.tr('Random selection')
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def processAlgorithm(self, parameters, context, feedback):
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filename = self.getParameterValue(self.INPUT)
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layer = QgsProcessingUtils.mapLayerFromString(filename, context)
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method = self.getParameterValue(self.METHOD)
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layer = self.parameterAsVectorLayer(parameters, self.INPUT, context)
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method = self.parameterAsEnum(parameters, self.METHOD, context)
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featureCount = layer.featureCount()
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value = int(self.getParameterValue(self.NUMBER))
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layer.removeSelection()
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value = self.parameterAsInt(parameters, self.NUMBER, context)
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if method == 0:
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if value > featureCount:
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raise GeoAlgorithmExecutionException(
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raise QgsProcessingException(
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self.tr('Selected number is greater than feature count. '
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'Choose a lower value and try again.'))
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else:
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if value > 100:
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raise GeoAlgorithmExecutionException(
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raise QgsProcessingException(
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self.tr("Percentage can't be greater than 100. Set a "
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"different value and try again."))
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value = int(round(value / 100.0, 4) * featureCount)
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@ -100,4 +101,4 @@ class RandomSelection(QgisAlgorithm):
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selran = random.sample(list(range(featureCount)), value)
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layer.selectByIds(selran)
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self.setOutputValue(self.OUTPUT, filename)
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return {self.OUTPUT: parameters[self.INPUT]}
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@ -31,15 +31,17 @@ import random
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from qgis.PyQt.QtGui import QIcon
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from qgis.core import QgsFeature, QgsFeatureSink, QgsProcessingUtils
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from qgis.core import (QgsFeatureRequest,
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QgsProcessingException,
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QgsProcessingUtils,
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QgsProcessingParameterVectorLayer,
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QgsProcessingParameterEnum,
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QgsProcessingParameterField,
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QgsProcessingParameterNumber,
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QgsProcessingParameterFeatureSink,
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QgsProcessingOutputVectorLayer)
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from collections import defaultdict
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from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
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from processing.core.GeoAlgorithmExecutionException import GeoAlgorithmExecutionException
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from processing.core.parameters import ParameterSelection
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from processing.core.parameters import ParameterVector
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from processing.core.parameters import ParameterNumber
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from processing.core.parameters import ParameterTableField
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from processing.core.outputs import OutputVector
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pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]
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@ -65,16 +67,17 @@ class RandomSelectionWithinSubsets(QgisAlgorithm):
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self.methods = [self.tr('Number of selected features'),
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self.tr('Percentage of selected features')]
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self.addParameter(ParameterVector(self.INPUT,
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self.tr('Input layer')))
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self.addParameter(ParameterTableField(self.FIELD,
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self.tr('ID Field'), self.INPUT))
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self.addParameter(ParameterSelection(self.METHOD,
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self.tr('Method'), self.methods, 0))
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self.addParameter(ParameterNumber(self.NUMBER,
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self.tr('Number/percentage of selected features'), 1, None, 10))
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self.addOutput(OutputVector(self.OUTPUT, self.tr('Selection stratified'), True))
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self.addParameter(QgsProcessingParameterVectorLayer(self.INPUT,
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self.tr('Input layer')))
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self.addParameter(QgsProcessingParameterField(self.FIELD,
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self.tr('ID field'), None, self.INPUT))
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self.addParameter(QgsProcessingParameterEnum(self.METHOD,
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self.tr('Method'), self.methods, False, 0))
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self.addParameter(QgsProcessingParameterNumber(self.NUMBER,
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self.tr('Number/percentage of selected features'),
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QgsProcessingParameterNumber.Integer,
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10, False, 0.0, 999999999999.0))
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self.addOutput(QgsProcessingOutputVectorLayer(self.OUTPUT, self.tr('Selected (stratified random)')))
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def name(self):
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return 'randomselectionwithinsubsets'
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@ -83,61 +86,52 @@ class RandomSelectionWithinSubsets(QgisAlgorithm):
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return self.tr('Random selection within subsets')
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def processAlgorithm(self, parameters, context, feedback):
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filename = self.getParameterValue(self.INPUT)
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layer = self.parameterAsVectorLayer(parameters, self.INPUT, context)
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method = self.parameterAsEnum(parameters, self.METHOD, context)
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field = self.parameterAsString(parameters, self.FIELD, context)
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layer = QgsProcessingUtils.mapLayerFromString(filename, context)
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field = self.getParameterValue(self.FIELD)
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method = self.getParameterValue(self.METHOD)
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layer.removeSelection()
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index = layer.fields().lookupField(field)
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unique = QgsProcessingUtils.uniqueValues(layer, index, context)
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unique = layer.uniqueValues(index)
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featureCount = layer.featureCount()
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value = int(self.getParameterValue(self.NUMBER))
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value = self.parameterAsInt(parameters, self.NUMBER, context)
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if method == 0:
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if value > featureCount:
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raise GeoAlgorithmExecutionException(
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raise QgsProcessingException(
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self.tr('Selected number is greater that feature count. '
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'Choose lesser value and try again.'))
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else:
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if value > 100:
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raise GeoAlgorithmExecutionException(
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raise QgsProcessingException(
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self.tr("Percentage can't be greater than 100. Set a "
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"different value and try again."))
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value = value / 100.0
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selran = []
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inFeat = QgsFeature()
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current = 0
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total = 100.0 / (featureCount * len(unique)) if featureCount else 1
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if not len(unique) == featureCount:
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for i in unique:
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features = QgsProcessingUtils.getFeatures(layer, context)
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FIDs = []
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for inFeat in features:
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attrs = inFeat.attributes()
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if attrs[index] == i:
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FIDs.append(inFeat.id())
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current += 1
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feedback.setProgress(int(current * total))
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classes = defaultdict(list)
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if method == 1:
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selValue = int(round(value * len(FIDs), 0))
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else:
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selValue = value
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features = layer.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([index]))
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if selValue >= len(FIDs):
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selFeat = FIDs
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else:
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selFeat = random.sample(FIDs, selValue)
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for i, feature in enumerate(features):
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if feedback.isCanceled():
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break
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classes[feature.attributes()[index]].append(feature.id())
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feedback.setProgress(int(i * total))
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selran = []
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for subset in classes.values():
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if feedback.isCanceled():
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break
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selValue = value if method != 1 else int(round(value * len(subset), 0))
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selran.extend(random.sample(subset, selValue))
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selran.extend(selFeat)
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layer.selectByIds(selran)
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else:
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layer.selectByIds(list(range(featureCount))) # FIXME: implies continuous feature ids
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self.setOutputValue(self.OUTPUT, filename)
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return {self.OUTPUT: parameters[self.INPUT]}
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