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ede452be85
Algorithms are now passed a QgsProcessingFeedback object instead of the loosely defined progress parameter.
137 lines
5.4 KiB
Python
137 lines
5.4 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 (Qgis, QgsFields, QgsField, QgsDistanceArea, QgsGeometry, QgsWkbTypes,
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QgsSpatialIndex, QgsPoint, QgsFeature)
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from processing.core.GeoAlgorithm import GeoAlgorithm
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from processing.core.ProcessingLog import ProcessingLog
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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 getIcon(self):
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return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'random_points.png'))
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def defineCharacteristics(self):
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self.name, self.i18n_name = self.trAlgorithm('Random points inside polygons (fixed)')
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self.group, self.i18n_group = self.trAlgorithm('Vector creation tools')
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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, feedback):
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layer = dataobjects.getObjectFromUri(
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self.getParameterValue(self.VECTOR))
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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(
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fields, QgsWkbTypes.Point, layer.crs())
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da = QgsDistanceArea()
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features = vector.features(layer)
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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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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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ProcessingLog.addToLog(ProcessingLog.LOG_INFO,
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self.tr('Can not generate requested number of random '
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'points. Maximum number of attempts exceeded.'))
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feedback.setProgress(0)
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del writer
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