from .RandomPointsPolygons import RandomPointsPolygons

RandomPointsPolygons(),

__author__ = 'Alexander Bruy'

__date__ = 'April 2014'

__copyright__ = '(C) 2014, Alexander Bruy'

__revision__ = '$Format:%H$'

import os

import random

from qgis.PyQt.QtGui import QIcon

from qgis.PyQt.QtCore import QVariant

from qgis.core import (QgsField,

QgsFeatureSink,

QgsFeature,

QgsFields,

QgsGeometry,

QgsPoint,

QgsPointXY,

QgsWkbTypes,

QgsSpatialIndex,

QgsFeatureRequest,

QgsExpression,

QgsDistanceArea,

QgsProject,

QgsProcessing,

QgsProcessingException,

QgsProcessingParameterNumber,

QgsProcessingParameterBoolean,

QgsProcessingParameterFeatureSource,

QgsProcessingParameterFeatureSink,

QgsProcessingParameterExpression,

QgsProcessingParameterEnum,

QgsProcessingParameterDefinition)

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'

ADD_Z = 'ADD_Z'

ADD_M = 'ADD_M'

OUTPUT = 'OUTPUT'

def icon(self):

return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'random_points.png'))

def group(self):

return self.tr('Vector creation tools')

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(QgsProcessingParameterNumber(self.MIN_DISTANCE,

self.tr('Minimum distance between points'),

QgsProcessingParameterNumber.Double,

0, False, 0, 1000000000))

params = []

params.append(QgsProcessingParameterBoolean(self.ADD_Z,

self.tr('Add Z coordinate'),

False))

params.append(QgsProcessingParameterBoolean(self.ADD_M,

self.tr('Add M coordinate'),

False))

for p in params:

p.setFlags(p.flags() | QgsProcessingParameterDefinition.FlagAdvanced)

self.addParameter(p)

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)

strategy = self.parameterAsEnum(parameters, self.STRATEGY, context)

minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE, context)

addZ = self.parameterAsBool(parameters, self.ADD_Z, context)

addM = self.parameterAsBool(parameters, self.ADD_M, context)

expression = QgsExpression(self.parameterAsString(parameters, self.EXPRESSION, context))

if expression.hasParserError():

raise ProcessingException(expression.parserErrorString())

expressionContext = self.createExpressionContext(parameters, context)

if not expression.prepare(expressionContext):

raise ProcessingException(

self.tr('Evaluation error: {0}').format(expression.evalErrorString()))

fields = QgsFields()

fields.append(QgsField('id', QVariant.Int, '', 10, 0))

wkbType = QgsWkbTypes.Point

if addZ:

wkbType = QgsWkbTypes.addZ(wkbType)

if addM:

wkbType = QgsWkbTypes.addM(wkbType)

(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,

fields, wkbType, source.sourceCrs())

da = QgsDistanceArea()

da.setSourceCrs(source.sourceCrs())

da.setEllipsoid(QgsProject.instance().ellipsoid())

total = 100.0 / source.featureCount() if source.featureCount() else 0

for current, f in enumerate(source.getFeatures()):

if feedback.isCanceled():

break

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()

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.")

continue

index = QgsSpatialIndex()

points = dict()

nPoints = 0

nIterations = 0

maxIterations = pointCount * 200

total = 100.0 / 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()

pnt = QgsPoint(rx, ry)

p = QgsPointXY(rx, ry)

if addZ:

pnt.addZValue(0.0)

if addM:

pnt.addMValue(0.0)

geom = QgsGeometry(pnt)

if geom.within(fGeom) and \

vector.checkMinDistance(p, index, minDistance, points):

f = QgsFeature(nPoints)

f.initAttributes(1)

f.setFields(fields)

f.setAttribute('id', nPoints)

f.setGeometry(geom)

sink.addFeature(f, QgsFeatureSink.FastInsert)

index.insertFeature(f)

points[nPoints] = p

nPoints += 1

feedback.setProgress(int(nPoints * 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(0)

return {self.OUTPUT: dest_id}