本文整理汇总了Python中qgis.core.QgsStatisticalSummary.addVariant方法的典型用法代码示例。如果您正苦于以下问题：Python QgsStatisticalSummary.addVariant方法的具体用法？Python QgsStatisticalSummary.addVariant怎么用？Python QgsStatisticalSummary.addVariant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.QgsStatisticalSummary的用法示例。
在下文中一共展示了QgsStatisticalSummary.addVariant方法的3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: calcNumericStats
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import addVariant [as 别名]
def calcNumericStats(self, features, feedback, field, count):
total = 100.0 / count if count else 0
stat = QgsStatisticalSummary()
for current, ft in enumerate(features):
if feedback.isCanceled():
break
stat.addVariant(ft[field.name()])
feedback.setProgress(int(current * total))
stat.finalize()
cv = stat.stDev() / stat.mean() if stat.mean() != 0 else 0
results = {self.COUNT: stat.count(),
self.UNIQUE: stat.variety(),
self.EMPTY: stat.countMissing(),
self.FILLED: count - stat.countMissing(),
self.MIN: stat.min(),
self.MAX: stat.max(),
self.RANGE: stat.range(),
self.SUM: stat.sum(),
self.MEAN: stat.mean(),
self.MEDIAN: stat.median(),
self.STD_DEV: stat.stDev(),
self.CV: cv,
self.MINORITY: stat.minority(),
self.MAJORITY: stat.majority(),
self.FIRSTQUARTILE: stat.firstQuartile(),
self.THIRDQUARTILE: stat.thirdQuartile(),
self.IQR: stat.interQuartileRange()}
data = []
data.append(self.tr('Count: {}').format(stat.count()))
data.append(self.tr('Unique values: {}').format(stat.variety()))
data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing()))
data.append(self.tr('Minimum value: {}').format(stat.min()))
data.append(self.tr('Maximum value: {}').format(stat.max()))
data.append(self.tr('Range: {}').format(stat.range()))
data.append(self.tr('Sum: {}').format(stat.sum()))
data.append(self.tr('Mean value: {}').format(stat.mean()))
data.append(self.tr('Median value: {}').format(stat.median()))
data.append(self.tr('Standard deviation: {}').format(stat.stDev()))
data.append(self.tr('Coefficient of Variation: {}').format(cv))
data.append(self.tr('Minority (rarest occurring value): {}').format(stat.minority()))
data.append(self.tr('Majority (most frequently occurring value): {}').format(stat.majority()))
data.append(self.tr('First quartile: {}').format(stat.firstQuartile()))
data.append(self.tr('Third quartile: {}').format(stat.thirdQuartile()))
data.append(self.tr('Interquartile Range (IQR): {}').format(stat.interQuartileRange()))
return data, results示例2: calcNumericStats
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import addVariant [as 别名]
def calcNumericStats(self, features, progress, field):
count = len(features)
total = 100.0 / float(count)
stat = QgsStatisticalSummary()
for current, ft in enumerate(features):
stat.addVariant(ft[field.name()])
progress.setPercentage(int(current * total))
stat.finalize()
cv = stat.stDev() / stat.mean() if stat.mean() != 0 else 0
self.setOutputValue(self.COUNT, stat.count())
self.setOutputValue(self.UNIQUE, stat.variety())
self.setOutputValue(self.EMPTY, stat.countMissing())
self.setOutputValue(self.FILLED, count - stat.countMissing())
self.setOutputValue(self.MIN, stat.min())
self.setOutputValue(self.MAX, stat.max())
self.setOutputValue(self.RANGE, stat.range())
self.setOutputValue(self.SUM, stat.sum())
self.setOutputValue(self.MEAN, stat.mean())
self.setOutputValue(self.MEDIAN, stat.median())
self.setOutputValue(self.STD_DEV, stat.stDev())
self.setOutputValue(self.CV, cv)
self.setOutputValue(self.MINORITY, stat.minority())
self.setOutputValue(self.MAJORITY, stat.majority())
self.setOutputValue(self.FIRSTQUARTILE, stat.firstQuartile())
self.setOutputValue(self.THIRDQUARTILE, stat.thirdQuartile())
self.setOutputValue(self.IQR, stat.interQuartileRange())
data = []
data.append(self.tr('Count: {}').format(stat.count()))
data.append(self.tr('Unique values: {}').format(stat.variety()))
data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing()))
data.append(self.tr('Minimum value: {}').format(stat.min()))
data.append(self.tr('Maximum value: {}').format(stat.max()))
data.append(self.tr('Range: {}').format(stat.range()))
data.append(self.tr('Sum: {}').format(stat.sum()))
data.append(self.tr('Mean value: {}').format(stat.mean()))
data.append(self.tr('Median value: {}').format(stat.median()))
data.append(self.tr('Standard deviation: {}').format(stat.stDev()))
data.append(self.tr('Coefficient of Variation: {}').format(cv))
data.append(self.tr('Minority (rarest occurring value): {}').format(stat.minority()))
data.append(self.tr('Majority (most frequently occurring value): {}').format(stat.majority()))
data.append(self.tr('First quartile: {}').format(stat.firstQuartile()))
data.append(self.tr('Third quartile: {}').format(stat.thirdQuartile()))
data.append(self.tr('Interquartile Range (IQR): {}').format(stat.interQuartileRange()))
return data示例3: processAlgorithm
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import addVariant [as 别名]
#.........这里部分代码省略.........
bbox_transform = QgsCoordinateTransform(source.sourceCrs(), join_source.sourceCrs(), context.project())
for current, f in enumerate(features):
if feedback.isCanceled():
break
if not f.hasGeometry():
if not discard_nomatch:
# ensure consistent count of attributes - otherwise non matching
# features will have incorrect attribute length
# and provider may reject them
attrs = f.attributes()
if len(attrs) < len(out_fields):
attrs += [NULL] * (len(out_fields) - len(attrs))
f.setAttributes(attrs)
sink.addFeature(f, QgsFeatureSink.FastInsert)
continue
bbox = bbox_transform.transformBoundingBox(f.geometry().boundingBox())
engine = None
values = []
request = QgsFeatureRequest().setFilterRect(bbox).setSubsetOfAttributes(join_field_indexes).setDestinationCrs(source.sourceCrs(), context.transformContext())
for test_feat in join_source.getFeatures(request):
if feedback.isCanceled():
break
join_attributes = []
for a in join_field_indexes:
join_attributes.append(test_feat.attributes()[a])
if engine is None:
engine = QgsGeometry.createGeometryEngine(f.geometry().constGet())
engine.prepareGeometry()
for predicate in predicates:
if getattr(engine, predicate)(test_feat.geometry().constGet()):
values.append(join_attributes)
break
feedback.setProgress(int(current * total))
if len(values) == 0:
if discard_nomatch:
continue
else:
# ensure consistent count of attributes - otherwise non matching
# features will have incorrect attribute length
# and provider may reject them
attrs = f.attributes()
if len(attrs) < len(out_fields):
attrs += [NULL] * (len(out_fields) - len(attrs))
f.setAttributes(attrs)
sink.addFeature(f, QgsFeatureSink.FastInsert)
else:
attrs = f.attributes()
for i in range(len(join_field_indexes)):
attribute_values = [v[i] for v in values]
field_type = field_types[i]
if field_type == 'numeric':
stat = QgsStatisticalSummary()
for v in attribute_values:
stat.addVariant(v)
stat.finalize()
for s in numeric_fields:
if s[0] in summaries:
attrs.append(getattr(stat, s[2])())
elif field_type == 'datetime':
stat = QgsDateTimeStatisticalSummary()
stat.calculate(attribute_values)
for s in datetime_fields:
if s[0] in summaries:
if s[0] == 'filled':
attrs.append(stat.count() - stat.countMissing())
elif s[0] == 'min':
attrs.append(stat.statistic(QgsDateTimeStatisticalSummary.Min))
elif s[0] == 'max':
attrs.append(stat.statistic(QgsDateTimeStatisticalSummary.Max))
else:
attrs.append(getattr(stat, s[2])())
else:
stat = QgsStringStatisticalSummary()
for v in attribute_values:
if v == NULL:
stat.addString('')
else:
stat.addString(str(v))
stat.finalize()
for s in string_fields:
if s[0] in summaries:
if s[0] == 'filled':
attrs.append(stat.count() - stat.countMissing())
else:
attrs.append(getattr(stat, s[2])())
f.setAttributes(attrs)
sink.addFeature(f, QgsFeatureSink.FastInsert)
return {self.OUTPUT: dest_id}