QGIS/python/plugins/processing/algs/qgis/RandomPointsPolygons.py
Nyall Dawson a49edf1f25 [processing] Make minimum distance between points in "Random Points in polygon"
algorithm optional

And don't do any unnecessary index work when it's not set. Shaves roughly 1/3rd
off the time of algorithm execution.
2019-09-30 16:58:15 +10:00

212 lines
8.5 KiB
Python

# -*- coding: utf-8 -*-
"""
***************************************************************************
RandomPointsPolygons.py
---------------------
Date : April 2014
Copyright : (C) 2014 by Alexander Bruy
Email : alexander dot bruy at gmail dot com
***************************************************************************
* *
* 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. *
* *
***************************************************************************
"""
__author__ = 'Alexander Bruy'
__date__ = 'April 2014'
__copyright__ = '(C) 2014, Alexander Bruy'
import os
import random
from qgis.PyQt.QtCore import QVariant
from qgis.core import (QgsApplication,
QgsField,
QgsFeatureSink,
QgsFeature,
QgsFields,
QgsGeometry,
QgsPointXY,
QgsWkbTypes,
QgsSpatialIndex,
QgsExpression,
QgsDistanceArea,
QgsProcessing,
QgsProcessingException,
QgsProcessingParameterDistance,
QgsProcessingParameterFeatureSource,
QgsProcessingParameterFeatureSink,
QgsProcessingParameterExpression,
QgsProcessingParameterEnum)
from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
from processing.tools import vector
pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]
class RandomPointsPolygons(QgisAlgorithm):
INPUT = 'INPUT'
EXPRESSION = 'EXPRESSION'
MIN_DISTANCE = 'MIN_DISTANCE'
STRATEGY = 'STRATEGY'
OUTPUT = 'OUTPUT'
def icon(self):
return QgsApplication.getThemeIcon("/algorithms/mAlgorithmRandomPointsWithinPolygon.svg")
def svgIconPath(self):
return QgsApplication.iconPath("/algorithms/mAlgorithmRandomPointsWithinPolygon.svg")
def group(self):
return self.tr('Vector creation')
def groupId(self):
return 'vectorcreation'
def __init__(self):
super().__init__()
def initAlgorithm(self, config=None):
self.strategies = [self.tr('Points count'),
self.tr('Points density')]
self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT,
self.tr('Input layer'),
[QgsProcessing.TypeVectorPolygon]))
self.addParameter(QgsProcessingParameterEnum(self.STRATEGY,
self.tr('Sampling strategy'),
self.strategies,
False,
0))
self.addParameter(QgsProcessingParameterExpression(self.EXPRESSION,
self.tr('Expression'),
parentLayerParameterName=self.INPUT))
self.addParameter(QgsProcessingParameterDistance(self.MIN_DISTANCE,
self.tr('Minimum distance between points'),
None, self.INPUT, True, 0, 1000000000))
self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT,
self.tr('Random points'),
type=QgsProcessing.TypeVectorPoint))
def name(self):
return 'randompointsinsidepolygons'
def displayName(self):
return self.tr('Random points inside polygons')
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
strategy = self.parameterAsEnum(parameters, self.STRATEGY, context)
if self.MIN_DISTANCE in parameters and parameters[self.MIN_DISTANCE] is not None:
minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE, context)
else:
minDistance = None
expression = QgsExpression(self.parameterAsString(parameters, self.EXPRESSION, context))
if expression.hasParserError():
raise QgsProcessingException(expression.parserErrorString())
expressionContext = self.createExpressionContext(parameters, context, source)
expression.prepare(expressionContext)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
fields, QgsWkbTypes.Point, source.sourceCrs(), QgsFeatureSink.RegeneratePrimaryKey)
if sink is None:
raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT))
da = QgsDistanceArea()
da.setSourceCrs(source.sourceCrs(), context.transformContext())
da.setEllipsoid(context.project().ellipsoid())
total = 100.0 / source.featureCount() if source.featureCount() else 0
current_progress = 0
pointId = 0
for current, f in enumerate(source.getFeatures()):
if feedback.isCanceled():
break
if not f.hasGeometry():
continue
current_progress = total * current
feedback.setProgress(current_progress)
expressionContext.setFeature(f)
value = expression.evaluate(expressionContext)
if expression.hasEvalError():
feedback.pushInfo(
self.tr('Evaluation error for feature ID {}: {}').format(f.id(), expression.evalErrorString()))
continue
fGeom = f.geometry()
engine = QgsGeometry.createGeometryEngine(fGeom.constGet())
engine.prepareGeometry()
bbox = fGeom.boundingBox()
if strategy == 0:
pointCount = int(value)
else:
pointCount = int(round(value * da.measureArea(fGeom)))
if pointCount == 0:
feedback.pushInfo("Skip feature {} as number of points for it is 0.".format(f.id()))
continue
index = None
if minDistance:
index = QgsSpatialIndex()
points = dict()
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
feature_total = total / pointCount if pointCount else 1
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
if feedback.isCanceled():
break
rx = bbox.xMinimum() + bbox.width() * random.random()
ry = bbox.yMinimum() + bbox.height() * random.random()
p = QgsPointXY(rx, ry)
geom = QgsGeometry.fromPointXY(p)
if engine.contains(geom.constGet()) and \
(not minDistance or vector.checkMinDistance(p, index, minDistance, points)):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', pointId)
f.setGeometry(geom)
sink.addFeature(f, QgsFeatureSink.FastInsert)
if minDistance:
index.addFeature(f)
points[nPoints] = p
nPoints += 1
pointId += 1
feedback.setProgress(current_progress + int(nPoints * feature_total))
nIterations += 1
if nPoints < pointCount:
feedback.pushInfo(self.tr('Could not generate requested number of random '
'points. Maximum number of attempts exceeded.'))
feedback.setProgress(100)
return {self.OUTPUT: dest_id}