本文整理汇总了Python中qgis.core.QgsProcessingUtils.generateIteratingDestination方法的典型用法代码示例。如果您正苦于以下问题：Python QgsProcessingUtils.generateIteratingDestination方法的具体用法？Python QgsProcessingUtils.generateIteratingDestination怎么用？Python QgsProcessingUtils.generateIteratingDestination使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类qgis.core.QgsProcessingUtils的用法示例。
在下文中一共展示了QgsProcessingUtils.generateIteratingDestination方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: executeIterating
# 需要导入模块: from qgis.core import QgsProcessingUtils [as 别名]
# 或者: from qgis.core.QgsProcessingUtils import generateIteratingDestination [as 别名]
def executeIterating(alg, parameters, paramToIter, context, feedback):
# Generate all single-feature layers
parameter_definition = alg.parameterDefinition(paramToIter)
if not parameter_definition:
return False
iter_source = QgsProcessingParameters.parameterAsSource(parameter_definition, parameters, context)
sink_list = []
if iter_source.featureCount() == 0:
return False
total = 100.0 / iter_source.featureCount()
for current, feat in enumerate(iter_source.getFeatures()):
if feedback.isCanceled():
return False
sink, sink_id = QgsProcessingUtils.createFeatureSink('memory:', context, iter_source.fields(), iter_source.wkbType(), iter_source.sourceCrs())
sink_list.append(sink_id)
sink.addFeature(feat, QgsFeatureSink.FastInsert)
del sink
feedback.setProgress(int(current * total))
# store output values to use them later as basenames for all outputs
outputs = {}
for out in alg.destinationParameterDefinitions():
if out.name() in parameters:
outputs[out.name()] = parameters[out.name()]
# now run all the algorithms
for i, f in enumerate(sink_list):
if feedback.isCanceled():
return False
parameters[paramToIter] = f
for out in alg.destinationParameterDefinitions():
if out.name() not in outputs:
continue
o = outputs[out.name()]
parameters[out.name()] = QgsProcessingUtils.generateIteratingDestination(o, i, context)
feedback.setProgressText(QCoreApplication.translate('AlgorithmExecutor', 'Executing iteration {0}/{1}…').format(i + 1, len(sink_list)))
feedback.setProgress(i * 100 / len(sink_list))
ret, results = execute(alg, parameters, context, feedback)
if not ret:
return False
handleAlgorithmResults(alg, context, feedback, False)
return True