def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
pointCount = self.parameterAsDouble(parameters, self.POINTS_NUMBER, context)
minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE, context)
bbox = source.sourceExtent()
sourceIndex = QgsSpatialIndex(source, feedback)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
fields, QgsWkbTypes.Point, source.sourceCrs())
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount if pointCount else 1
index = QgsSpatialIndex()
points = dict()
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)
ids = sourceIndex.intersects(geom.buffer(5, 5).boundingBox())
if len(ids) > 0 and \
vector.checkMinDistance(p, index, minDistance, points):
request = QgsFeatureRequest().setFilterFids(ids).setSubsetOfAttributes([])
for f in source.getFeatures(request):
if feedback.isCanceled():
break
tmpGeom = f.geometry()
if geom.within(tmpGeom):
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.'))
return {self.OUTPUT: dest_id}
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.VECTOR))
pointCount = int(self.getParameterValue(self.POINT_NUMBER))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
bbox = layer.extent()
extent = QgsGeometry().fromRect(bbox)
idxLayer = vector.spatialindex(layer)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QGis.WKBPoint, layer.dataProvider().crs())
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount
index = QgsSpatialIndex()
points = dict()
request = QgsFeatureRequest()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = bbox.xMinimum() + bbox.width() * random.random()
ry = bbox.yMinimum() + bbox.height() * random.random()
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
ids = idxLayer.intersects(geom.buffer(5, 5).boundingBox())
if len(ids) > 0 and \
vector.checkMinDistance(pnt, index, minDistance, points):
for i in ids:
f = layer.getFeatures(request.setFilterFid(i)).next()
tmpGeom = QgsGeometry(f.geometry())
if geom.within(tmpGeom):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
progress.setPercentage(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
ProcessingLog.addToLog(
ProcessingLog.LOG_INFO,
'Can not generate requested number of random points. Maximum '
'number of attempts exceeded.')
del writer
def processAlgorithm(self, feedback):
pointCount = int(self.getParameterValue(self.POINT_NUMBER))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
extent = str(self.getParameterValue(self.EXTENT)).split(',')
crsId = self.getParameterValue(self.CRS)
crs = QgsCoordinateReferenceSystem()
crs.createFromUserInput(crsId)
xMin = float(extent[0])
xMax = float(extent[1])
yMin = float(extent[2])
yMax = float(extent[3])
extent = QgsGeometry().fromRect(
QgsRectangle(xMin, yMin, xMax, yMax))
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QgsWkbTypes.Point, crs)
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount
index = QgsSpatialIndex()
points = dict()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = xMin + (xMax - xMin) * random.random()
ry = yMin + (yMax - yMin) * random.random()
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if geom.within(extent) and \
vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
feedback.setProgress(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
ProcessingLog.addToLog(ProcessingLog.LOG_INFO,
self.tr('Can not generate requested number of random points. '
'Maximum number of attempts exceeded.'))
del writer
def processAlgorithm(self, progress):
pointCount = int(self.getParameterValue(self.POINT_NUMBER))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
extent = str(self.getParameterValue(self.EXTENT)).split(',')
xMin = float(extent[0])
xMax = float(extent[1])
yMin = float(extent[2])
yMax = float(extent[3])
extent = QgsGeometry().fromRect(
QgsRectangle(xMin, yMin, xMax, yMax))
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
mapCRS = iface.mapCanvas().mapSettings().destinationCrs()
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QGis.WKBPoint, mapCRS)
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount
index = QgsSpatialIndex()
points = dict()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = xMin + (xMax - xMin) * random.random()
ry = yMin + (yMax - yMin) * random.random()
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if geom.within(extent) and \
vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
progress.setPercentage(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
ProcessingLog.addToLog(
ProcessingLog.LOG_INFO,
'Can not generate requested number of random points. Maximum '
'number of attempts exceeded.')
del writer
def processAlgorithm(self, parameters, context, feedback):
pointCount = self.parameterAsDouble(parameters, self.POINTS_NUMBER, context)
minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE, context)
crs = self.parameterAsCrs(parameters, self.TARGET_CRS, context)
bbox = self.parameterAsExtent(parameters, self.EXTENT, context, crs)
extent = QgsGeometry().fromRect(bbox)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
fields, QgsWkbTypes.Point, crs)
if sink is None:
raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT))
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount if pointCount else 1
index = QgsSpatialIndex()
points = dict()
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 geom.within(extent) 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.addFeature(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.'))
return {self.OUTPUT: dest_id}
def processAlgorithm(self, parameters, context, feedback):
layer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.VECTOR), context)
pointCount = int(self.getParameterValue(self.POINT_NUMBER))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
bbox = layer.extent()
idxLayer = QgsProcessingUtils.createSpatialIndex(layer, context)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(fields, QgsWkbTypes.Point, layer.crs(), context)
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount
index = QgsSpatialIndex()
points = dict()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = bbox.xMinimum() + bbox.width() * random.random()
ry = bbox.yMinimum() + bbox.height() * random.random()
pnt = QgsPointXY(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
ids = idxLayer.intersects(geom.buffer(5, 5).boundingBox())
if len(ids) > 0 and \
vector.checkMinDistance(pnt, index, minDistance, points):
request = QgsFeatureRequest().setFilterFids(ids).setSubsetOfAttributes([])
for f in layer.getFeatures(request):
tmpGeom = f.geometry()
if geom.within(tmpGeom):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
feedback.setProgress(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
QgsMessageLog.logMessage(self.tr('Can not generate requested number of random points. '
'Maximum number of attempts exceeded.'), self.tr('Processing'), QgsMessageLog.INFO)
del writer
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
expressionContext = self.createExpressionContext(
parameters, context, source)
dynamic_value = QgsProcessingParameters.isDynamic(parameters, "VALUE")
value_property = None
if self.EXPRESSION in parameters and parameters[
self.EXPRESSION] is not None:
expression = QgsExpression(
self.parameterAsString(parameters, self.EXPRESSION, context))
value = None
if expression.hasParserError():
raise QgsProcessingException(expression.parserErrorString())
expression.prepare(expressionContext)
else:
expression = None
if dynamic_value:
value_property = parameters["VALUE"]
value = self.parameterAsDouble(parameters, self.VALUE, context)
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.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)
this_value = value
if value_property is not None or expression is not None:
expressionContext.setFeature(f)
if value_property:
this_value, _ = value_property.valueAsDouble(
expressionContext, value)
else:
this_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(this_value)
else:
pointCount = int(round(this_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}
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.VECTOR))
pointCount = float(self.getParameterValue(self.POINT_NUMBER))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QgsWkbTypes.Point, layer.crs())
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
featureCount = layer.featureCount()
total = 100.0 / pointCount
index = QgsSpatialIndex()
points = dict()
da = QgsDistanceArea()
request = QgsFeatureRequest()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
# pick random feature
fid = random.randint(0, featureCount - 1)
f = next(layer.getFeatures(request.setFilterFid(fid).setSubsetOfAttributes([])))
fGeom = f.geometry()
if fGeom.isMultipart():
lines = fGeom.asMultiPolyline()
# pick random line
lineId = random.randint(0, len(lines) - 1)
vertices = lines[lineId]
else:
vertices = fGeom.asPolyline()
# pick random segment
if len(vertices) == 2:
vid = 0
else:
vid = random.randint(0, len(vertices) - 2)
startPoint = vertices[vid]
endPoint = vertices[vid + 1]
length = da.measureLine(startPoint, endPoint)
dist = length * random.random()
if dist > minDistance:
d = dist / (length - dist)
rx = (startPoint.x() + d * endPoint.x()) / (1 + d)
ry = (startPoint.y() + d * endPoint.y()) / (1 + d)
# generate random point
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
progress.setPercentage(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
ProcessingLog.addToLog(ProcessingLog.LOG_INFO,
self.tr('Can not generate requested number of random points. '
'Maximum number of attempts exceeded.'))
del writer
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
pointCount = self.parameterAsDouble(parameters, self.POINTS_NUMBER, context)
minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE, context)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
fields, QgsWkbTypes.Point, source.sourceCrs())
if sink is None:
raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT))
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
featureCount = source.featureCount()
total = 100.0 / pointCount if pointCount else 1
index = QgsSpatialIndex()
points = dict()
da = QgsDistanceArea()
da.setSourceCrs(source.sourceCrs(), context.transformContext())
da.setEllipsoid(context.project().ellipsoid())
request = QgsFeatureRequest()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
if feedback.isCanceled():
break
# pick random feature
fid = random.randint(0, featureCount - 1)
f = next(source.getFeatures(request.setFilterFid(fid).setSubsetOfAttributes([])))
fGeom = f.geometry()
if fGeom.isMultipart():
lines = fGeom.asMultiPolyline()
# pick random line
lineId = random.randint(0, len(lines) - 1)
vertices = lines[lineId]
else:
vertices = fGeom.asPolyline()
# pick random segment
if len(vertices) == 2:
vid = 0
else:
vid = random.randint(0, len(vertices) - 2)
startPoint = vertices[vid]
endPoint = vertices[vid + 1]
length = da.measureLine(startPoint, endPoint)
dist = length * random.random()
if dist > minDistance:
d = dist / (length - dist)
rx = (startPoint.x() + d * endPoint.x()) / (1 + d)
ry = (startPoint.y() + d * endPoint.y()) / (1 + d)
# generate random point
p = QgsPointXY(rx, ry)
geom = QgsGeometry.fromPointXY(p)
if 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.addFeature(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.'))
return {self.OUTPUT: dest_id}
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)
minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE, context)
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
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 = 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 \
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.addFeature(f)
points[nPoints] = p
nPoints += 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}
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.VECTOR))
fieldName = self.getParameterValue(self.FIELD)
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
strategy = self.getParameterValue(self.STRATEGY)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QGis.WKBPoint, layer.crs())
da = QgsDistanceArea()
features = vector.features(layer)
for current, f in enumerate(features):
fGeom = QgsGeometry(f.geometry())
bbox = fGeom.boundingBox()
if strategy == 0:
pointCount = int(f[fieldName]) if f[fieldName] else 0
else:
if f[fieldName]:
pointCount = int(round(f[fieldName] * da.measure(fGeom)))
else:
pointCount = 0
if strategy == 0 and pointCount == 0:
continue
index = QgsSpatialIndex()
points = dict()
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount if pointCount > 0 else 1
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = bbox.xMinimum() + bbox.width() * random.random()
ry = bbox.yMinimum() + bbox.height() * random.random()
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if geom.within(fGeom) and \
vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
progress.setPercentage(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
ProcessingLog.addToLog(ProcessingLog.LOG_INFO,
self.tr('Can not generate requested number of random '
'points. Maximum number of attempts exceeded.'))
progress.setPercentage(0)
del writer
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.VECTOR))
value = float(self.getParameterValue(self.VALUE))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
strategy = self.getParameterValue(self.STRATEGY)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QGis.WKBPoint,
layer.dataProvider().crs())
da = QgsDistanceArea()
features = vector.features(layer)
for current, f in enumerate(features):
fGeom = QgsGeometry(f.geometry())
bbox = fGeom.boundingBox()
if strategy == 0:
pointCount = int(value)
else:
pointCount = int(round(value * da.measure(fGeom)))
index = QgsSpatialIndex()
points = dict()
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = bbox.xMinimum() + bbox.width() * random.random()
ry = bbox.yMinimum() + bbox.height() * random.random()
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if geom.within(fGeom) and \
vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
progress.setPercentage(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
ProcessingLog.addToLog(
ProcessingLog.LOG_INFO,
self.tr('Can not generate requested number of random '
'points. Maximum number of attempts exceeded.'))
progress.setPercentage(0)
del writer
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)
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))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT,
context, fields,
QgsWkbTypes.Point,
source.sourceCrs())
da = QgsDistanceArea()
da.setSourceCrs(source.sourceCrs())
da.setEllipsoid(context.project().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()
p = QgsPointXY(rx, ry)
geom = QgsGeometry.fromPointXY(p)
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}
def processAlgorithm(self, parameters, context, feedback):
layer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.VECTOR), context)
value = float(self.getParameterValue(self.VALUE))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
strategy = self.getParameterValue(self.STRATEGY)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(fields, QgsWkbTypes.Point, layer.crs(), context)
da = QgsDistanceArea()
features = QgsProcessingUtils.getFeatures(layer, context)
for current, f in enumerate(features):
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
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = bbox.xMinimum() + bbox.width() * random.random()
ry = bbox.yMinimum() + bbox.height() * random.random()
pnt = QgsPointXY(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if geom.within(fGeom) and \
vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
feedback.setProgress(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
QgsMessageLog.logMessage(self.tr('Can not generate requested number of random '
'points. Maximum number of attempts exceeded.'), self.tr('Processing'), QgsMessageLog.INFO)
feedback.setProgress(0)
del writer
def processAlgorithm(self, context, feedback):
layer = QgsProcessingUtils.mapLayerFromString(
self.getParameterValue(self.VECTOR), context)
fieldName = self.getParameterValue(self.FIELD)
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
strategy = self.getParameterValue(self.STRATEGY)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QgsWkbTypes.Point, layer.crs(), context)
da = QgsDistanceArea()
features = QgsProcessingUtils.getFeatures(layer, context)
for current, f in enumerate(features):
fGeom = f.geometry()
bbox = fGeom.boundingBox()
if strategy == 0:
pointCount = int(f[fieldName])
else:
pointCount = int(round(f[fieldName] * 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
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
rx = bbox.xMinimum() + bbox.width() * random.random()
ry = bbox.yMinimum() + bbox.height() * random.random()
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if geom.within(fGeom) and \
vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
feedback.setProgress(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
QgsMessageLog.logMessage(
self.tr('Can not generate requested number of random '
'points. Maximum number of attempts exceeded.'),
self.tr('Processing'), QgsMessageLog.INFO)
feedback.setProgress(0)
del writer
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
pointCount = self.parameterAsDouble(parameters, self.POINTS_NUMBER, context)
minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE, context)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
fields, QgsWkbTypes.Point, source.sourceCrs())
if sink is None:
raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT))
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
featureCount = source.featureCount()
total = 100.0 / pointCount if pointCount else 1
index = QgsSpatialIndex()
points = dict()
da = QgsDistanceArea()
da.setSourceCrs(source.sourceCrs(), context.transformContext())
da.setEllipsoid(context.project().ellipsoid())
request = QgsFeatureRequest()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
if feedback.isCanceled():
break
# pick random feature
fid = random.randint(0, featureCount - 1)
f = next(source.getFeatures(request.setFilterFid(fid).setSubsetOfAttributes([])))
fGeom = f.geometry()
if fGeom.isMultipart():
lines = fGeom.asMultiPolyline()
# pick random line
lineId = random.randint(0, len(lines) - 1)
vertices = lines[lineId]
else:
vertices = fGeom.asPolyline()
# pick random segment
if len(vertices) == 2:
vid = 0
else:
vid = random.randint(0, len(vertices) - 2)
startPoint = vertices[vid]
endPoint = vertices[vid + 1]
length = da.measureLine(startPoint, endPoint)
dist = length * random.random()
if dist > minDistance:
d = dist / (length - dist)
rx = (startPoint.x() + d * endPoint.x()) / (1 + d)
ry = (startPoint.y() + d * endPoint.y()) / (1 + d)
# generate random point
p = QgsPointXY(rx, ry)
geom = QgsGeometry.fromPointXY(p)
if 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.'))
return {self.OUTPUT: dest_id}
def processAlgorithm(self, feedback):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.VECTOR))
pointCount = float(self.getParameterValue(self.POINT_NUMBER))
minDistance = float(self.getParameterValue(self.MIN_DISTANCE))
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, QgsWkbTypes.Point, layer.crs())
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
featureCount = layer.featureCount()
total = 100.0 / pointCount
index = QgsSpatialIndex()
points = dict()
da = QgsDistanceArea()
request = QgsFeatureRequest()
random.seed()
while nIterations < maxIterations and nPoints < pointCount:
# pick random feature
fid = random.randint(0, featureCount - 1)
f = next(layer.getFeatures(request.setFilterFid(fid).setSubsetOfAttributes([])))
fGeom = f.geometry()
if fGeom.isMultipart():
lines = fGeom.asMultiPolyline()
# pick random line
lineId = random.randint(0, len(lines) - 1)
vertices = lines[lineId]
else:
vertices = fGeom.asPolyline()
# pick random segment
if len(vertices) == 2:
vid = 0
else:
vid = random.randint(0, len(vertices) - 2)
startPoint = vertices[vid]
endPoint = vertices[vid + 1]
length = da.measureLine(startPoint, endPoint)
dist = length * random.random()
if dist > minDistance:
d = dist / (length - dist)
rx = (startPoint.x() + d * endPoint.x()) / (1 + d)
ry = (startPoint.y() + d * endPoint.y()) / (1 + d)
# generate random point
pnt = QgsPoint(rx, ry)
geom = QgsGeometry.fromPoint(pnt)
if vector.checkMinDistance(pnt, index, minDistance, points):
f = QgsFeature(nPoints)
f.initAttributes(1)
f.setFields(fields)
f.setAttribute('id', nPoints)
f.setGeometry(geom)
writer.addFeature(f)
index.insertFeature(f)
points[nPoints] = pnt
nPoints += 1
feedback.setProgress(int(nPoints * total))
nIterations += 1
if nPoints < pointCount:
ProcessingLog.addToLog(ProcessingLog.LOG_INFO,
self.tr('Can not generate requested number of random points. '
'Maximum number of attempts exceeded.'))
del writer
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(
self.invalidSourceError(parameters, self.INPUT))
pointCount = self.parameterAsDouble(parameters, self.POINTS_NUMBER,
context)
minDistance = self.parameterAsDouble(parameters, self.MIN_DISTANCE,
context)
bbox = source.sourceExtent()
sourceIndex = QgsSpatialIndex(source, feedback)
fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 10, 0))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT,
context, fields,
QgsWkbTypes.Point,
source.sourceCrs())
if sink is None:
raise QgsProcessingException(
self.invalidSinkError(parameters, self.OUTPUT))
nPoints = 0
nIterations = 0
maxIterations = pointCount * 200
total = 100.0 / pointCount if pointCount else 1
index = QgsSpatialIndex()
points = dict()
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)
ids = sourceIndex.intersects(geom.buffer(5, 5).boundingBox())
if len(ids) > 0 and \
vector.checkMinDistance(p, index, minDistance, points):
request = QgsFeatureRequest().setFilterFids(
ids).setSubsetOfAttributes([])
for f in source.getFeatures(request):
if feedback.isCanceled():
break
tmpGeom = f.geometry()
if geom.within(tmpGeom):
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.'))
return {self.OUTPUT: dest_id}
