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Algorithms and other processing code should use this method (instead of dataobjects.getLayerFromString) to retrieve layers from a string, as it considers the processing context and allows resolving strings to temporarily stored layers. This permits processing models to function correctly when intermediate results are stored as memory layers. Subsequent model algorithms can then access these temporary layers as inputs. All temporary layers will be removed when the context object is destroyed after the model algorithm is run.
145 lines
5.7 KiB
Python
145 lines
5.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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RandomPointsPolygonsFixed.py
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---------------------
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Date : April 2014
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Copyright : (C) 2014 by Alexander Bruy
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Email : alexander dot bruy 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__ = 'Alexander Bruy'
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__date__ = 'April 2014'
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__copyright__ = '(C) 2014, Alexander Bruy'
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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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import random
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from qgis.PyQt.QtGui import QIcon
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from qgis.PyQt.QtCore import QVariant
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from qgis.core import (QgsFields, QgsField, QgsDistanceArea, QgsGeometry, QgsWkbTypes,
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QgsSpatialIndex, QgsPoint, QgsFeature,
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QgsMessageLog,
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QgsProcessingUtils)
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from processing.core.GeoAlgorithm import GeoAlgorithm
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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 ParameterSelection
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from processing.core.outputs import OutputVector
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from processing.tools import dataobjects, vector
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pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]
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class RandomPointsPolygonsFixed(GeoAlgorithm):
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VECTOR = 'VECTOR'
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VALUE = 'VALUE'
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MIN_DISTANCE = 'MIN_DISTANCE'
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STRATEGY = 'STRATEGY'
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OUTPUT = 'OUTPUT'
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def icon(self):
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return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'random_points.png'))
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def group(self):
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return self.tr('Vector creation tools')
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def name(self):
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return 'randompointsinsidepolygonsfixed'
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def displayName(self):
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return self.tr('Random points inside polygons (fixed)')
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def defineCharacteristics(self):
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self.strategies = [self.tr('Points count'),
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self.tr('Points density')]
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self.addParameter(ParameterVector(self.VECTOR,
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self.tr('Input layer'), [dataobjects.TYPE_VECTOR_POLYGON]))
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self.addParameter(ParameterSelection(self.STRATEGY,
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self.tr('Sampling strategy'), self.strategies, 0))
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self.addParameter(ParameterNumber(self.VALUE,
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self.tr('Number or density of points'), 0.0001, None, 1.0))
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self.addParameter(ParameterNumber(self.MIN_DISTANCE,
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self.tr('Minimum distance'), 0.0, None, 0.0))
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self.addOutput(OutputVector(self.OUTPUT, self.tr('Random points'), datatype=[dataobjects.TYPE_VECTOR_POINT]))
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def processAlgorithm(self, context, feedback):
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layer = dataobjects.QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.VECTOR), context)
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value = float(self.getParameterValue(self.VALUE))
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minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
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strategy = self.getParameterValue(self.STRATEGY)
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fields = QgsFields()
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fields.append(QgsField('id', QVariant.Int, '', 10, 0))
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writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(fields, QgsWkbTypes.Point, layer.crs(), context)
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da = QgsDistanceArea()
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features = QgsProcessingUtils.getFeatures(layer, context)
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for current, f in enumerate(features):
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fGeom = f.geometry()
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bbox = fGeom.boundingBox()
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if strategy == 0:
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pointCount = int(value)
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else:
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pointCount = int(round(value * da.measureArea(fGeom)))
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if pointCount == 0:
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feedback.pushInfo("Skip feature {} as number of points for it is 0.")
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continue
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index = QgsSpatialIndex()
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points = dict()
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nPoints = 0
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nIterations = 0
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maxIterations = pointCount * 200
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total = 100.0 / pointCount
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random.seed()
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while nIterations < maxIterations and nPoints < pointCount:
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rx = bbox.xMinimum() + bbox.width() * random.random()
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ry = bbox.yMinimum() + bbox.height() * random.random()
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pnt = QgsPoint(rx, ry)
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geom = QgsGeometry.fromPoint(pnt)
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if geom.within(fGeom) and \
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vector.checkMinDistance(pnt, index, minDistance, points):
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f = QgsFeature(nPoints)
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f.initAttributes(1)
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f.setFields(fields)
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f.setAttribute('id', nPoints)
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f.setGeometry(geom)
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writer.addFeature(f)
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index.insertFeature(f)
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points[nPoints] = pnt
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nPoints += 1
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feedback.setProgress(int(nPoints * total))
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nIterations += 1
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if nPoints < pointCount:
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QgsMessageLog.logMessage(self.tr('Can not generate requested number of random '
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'points. Maximum number of attempts exceeded.'), self.tr('Processing'), QgsMessageLog.INFO)
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feedback.setProgress(0)
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del writer
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