本文整理汇总了Python中qgis.core.QgsStatisticalSummary.count方法的典型用法代码示例。如果您正苦于以下问题:Python QgsStatisticalSummary.count方法的具体用法?Python QgsStatisticalSummary.count怎么用?Python QgsStatisticalSummary.count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.count方法的8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 count [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 count [as 别名]
def calcNumericStats(self, values, sink, feedback):
stat = QgsStatisticalSummary()
total = 50.0 / len(values) if values else 0
current = 0
for cat, v in values.items():
if feedback.isCanceled():
break
feedback.setProgress(int(current * total) + 50)
stat.calculate(v)
f = QgsFeature()
f.setAttributes(list(cat) + [stat.count(),
stat.variety(),
stat.min(),
stat.max(),
stat.range(),
stat.sum(),
stat.mean(),
stat.median(),
stat.stDev(),
stat.minority(),
stat.majority(),
stat.firstQuartile(),
stat.thirdQuartile(),
stat.interQuartileRange()])
sink.addFeature(f, QgsFeatureSink.FastInsert)
current += 1
示例3: calcNumericStats
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import count [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4: processAlgorithm
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import count [as 别名]
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
join_source = self.parameterAsSource(parameters, self.JOIN, context)
join_fields = self.parameterAsFields(parameters, self.JOIN_FIELDS, context)
discard_nomatch = self.parameterAsBool(parameters, self.DISCARD_NONMATCHING, context)
summaries = [self.statistics[i][0] for i in
sorted(self.parameterAsEnums(parameters, self.SUMMARIES, context))]
if not summaries:
# none selected, so use all
summaries = [s[0] for s in self.statistics]
source_fields = source.fields()
fields_to_join = QgsFields()
join_field_indexes = []
if not join_fields:
# no fields selected, use all
join_fields = [join_source.fields().at(i).name() for i in range(len(join_source.fields()))]
def addFieldKeepType(original, stat):
"""
Adds a field to the output, keeping the same data type as the original
"""
field = QgsField(original)
field.setName(field.name() + '_' + stat)
fields_to_join.append(field)
def addField(original, stat, type):
"""
Adds a field to the output, with a specified type
"""
field = QgsField(original)
field.setName(field.name() + '_' + stat)
field.setType(type)
if type == QVariant.Double:
field.setLength(20)
field.setPrecision(6)
fields_to_join.append(field)
numeric_fields = (
('count', QVariant.Int, 'count'),
('unique', QVariant.Int, 'variety'),
('min', QVariant.Double, 'min'),
('max', QVariant.Double, 'max'),
('range', QVariant.Double, 'range'),
('sum', QVariant.Double, 'sum'),
('mean', QVariant.Double, 'mean'),
('median', QVariant.Double, 'median'),
('stddev', QVariant.Double, 'stDev'),
('minority', QVariant.Double, 'minority'),
('majority', QVariant.Double, 'majority'),
('q1', QVariant.Double, 'firstQuartile'),
('q3', QVariant.Double, 'thirdQuartile'),
('iqr', QVariant.Double, 'interQuartileRange')
)
datetime_fields = (
('count', QVariant.Int, 'count'),
('unique', QVariant.Int, 'countDistinct'),
('empty', QVariant.Int, 'countMissing'),
('filled', QVariant.Int),
('min', None),
('max', None)
)
string_fields = (
('count', QVariant.Int, 'count'),
('unique', QVariant.Int, 'countDistinct'),
('empty', QVariant.Int, 'countMissing'),
('filled', QVariant.Int),
('min', None, 'min'),
('max', None, 'max'),
('min_length', QVariant.Int, 'minLength'),
('max_length', QVariant.Int, 'maxLength'),
('mean_length', QVariant.Double, 'meanLength')
)
field_types = []
for f in join_fields:
idx = join_source.fields().lookupField(f)
if idx >= 0:
join_field_indexes.append(idx)
join_field = join_source.fields().at(idx)
if join_field.isNumeric():
field_types.append('numeric')
field_list = numeric_fields
elif join_field.type() in (QVariant.Date, QVariant.Time, QVariant.DateTime):
field_types.append('datetime')
field_list = datetime_fields
else:
field_types.append('string')
field_list = string_fields
for f in field_list:
if f[0] in summaries:
if f[1] is not None:
addField(join_field, f[0], f[1])
else:
addFieldKeepType(join_field, f[0])
#.........这里部分代码省略.........
示例5: processAlgorithm
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import count [as 别名]
def processAlgorithm(self, parameters, context, feedback):
layer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.INPUT_LAYER), context)
valuesFieldName = self.getParameterValue(self.VALUES_FIELD_NAME)
categoriesFieldName = self.getParameterValue(self.CATEGORIES_FIELD_NAME)
output = self.getOutputFromName(self.OUTPUT)
valuesField = layer.fields().lookupField(valuesFieldName)
categoriesField = layer.fields().lookupField(categoriesFieldName)
features = QgsProcessingUtils.getFeatures(layer, context)
total = 100.0 / QgsProcessingUtils.featureCount(layer, context)
values = {}
for current, feat in enumerate(features):
feedback.setProgress(int(current * total))
attrs = feat.attributes()
try:
value = float(attrs[valuesField])
cat = str(attrs[categoriesField])
if cat not in values:
values[cat] = []
values[cat].append(value)
except:
pass
fields = ['category', 'min', 'max', 'mean', 'stddev', 'sum', 'count']
writer = output.getTableWriter(fields)
stat = QgsStatisticalSummary(QgsStatisticalSummary.Min | QgsStatisticalSummary.Max |
QgsStatisticalSummary.Mean | QgsStatisticalSummary.StDevSample |
QgsStatisticalSummary.Sum | QgsStatisticalSummary.Count)
for (cat, v) in list(values.items()):
stat.calculate(v)
record = [cat, stat.min(), stat.max(), stat.mean(), stat.sampleStDev(), stat.sum(), stat.count()]
writer.addRecord(record)
示例6: processAlgorithm
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import count [as 别名]
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.INPUT_LAYER))
fieldName = self.getParameterValue(self.FIELD_NAME)
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
index = layer.fieldNameIndex(fieldName)
cvValue = 0
minValue = 0
maxValue = 0
sumValue = 0
meanValue = 0
medianValue = 0
stdDevValue = 0
minority = 0
majority = 0
firstQuartile = 0
thirdQuartile = 0
iqr = 0
isFirst = True
values = []
features = vector.features(layer)
count = len(features)
total = 100.0 / float(count)
current = 0
for ft in features:
if ft.attributes()[index]:
values.append(float(ft.attributes()[index]))
current += 1
progress.setPercentage(int(current * total))
stat = QgsStatisticalSummary()
stat.calculate(values)
count = stat.count()
uniqueValue = stat.variety()
minValue = stat.min()
maxValue = stat.max()
rValue = stat.range()
sumValue = stat.sum()
meanValue = stat.mean()
medianValue = stat.median()
stdDevValue = stat.stDev()
if meanValue != 0.00:
cvValue = stdDevValue / meanValue
minority = stat.minority()
majority = stat.majority()
firstQuartile = stat.firstQuartile()
thirdQuartile = stat.thirdQuartile()
iqr = stat.interQuartileRange()
data = []
data.append('Count: ' + unicode(count))
data.append('Unique values: ' + unicode(uniqueValue))
data.append('Minimum value: ' + unicode(minValue))
data.append('Maximum value: ' + unicode(maxValue))
data.append('Range: ' + unicode(rValue))
data.append('Sum: ' + unicode(sumValue))
data.append('Mean value: ' + unicode(meanValue))
data.append('Median value: ' + unicode(medianValue))
data.append('Standard deviation: ' + unicode(stdDevValue))
data.append('Coefficient of Variation: ' + unicode(cvValue))
data.append('Minority (rarest occurring value): ' + unicode(minority))
data.append('Majority (most frequently occurring value): ' + unicode(majority))
data.append('First quartile: ' + unicode(firstQuartile))
data.append('Third quartile: ' + unicode(thirdQuartile))
data.append('Interquartile Range (IQR): ' + unicode(iqr))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, count)
self.setOutputValue(self.UNIQUE, uniqueValue)
self.setOutputValue(self.MIN, minValue)
self.setOutputValue(self.MAX, maxValue)
self.setOutputValue(self.RANGE, rValue)
self.setOutputValue(self.SUM, sumValue)
self.setOutputValue(self.MEAN, meanValue)
self.setOutputValue(self.MEDIAN, medianValue)
self.setOutputValue(self.STD_DEV, stdDevValue)
self.setOutputValue(self.MINORITY, minority)
self.setOutputValue(self.MAJORITY, majority)
self.setOutputValue(self.FIRSTQUARTILE, firstQuartile)
self.setOutputValue(self.THIRDQUARTILE, thirdQuartile)
self.setOutputValue(self.IQR, iqr)
示例7: processAlgorithm
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import count [as 别名]
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(self.getParameterValue(self.INPUT_LAYER))
valuesFieldName = self.getParameterValue(self.VALUES_FIELD_NAME)
categoriesFieldName = self.getParameterValue(self.CATEGORIES_FIELD_NAME)
output = self.getOutputFromName(self.OUTPUT)
valuesField = layer.fieldNameIndex(valuesFieldName)
categoriesField = layer.fieldNameIndex(categoriesFieldName)
features = vector.features(layer)
total = 100.0 / len(features) if len(features) > 0 else 1
values = {}
for current, feat in enumerate(features):
progress.setPercentage(int(current * total))
attrs = feat.attributes()
try:
value = float(attrs[valuesField])
cat = unicode(attrs[categoriesField])
if cat not in values:
values[cat] = []
values[cat].append(value)
except:
pass
fields = ['category', 'min', 'max', 'mean', 'stddev', 'sum', 'count']
writer = output.getTableWriter(fields)
stat = QgsStatisticalSummary(QgsStatisticalSummary.Min | QgsStatisticalSummary.Max |
QgsStatisticalSummary.Mean | QgsStatisticalSummary.StDevSample |
QgsStatisticalSummary.Sum | QgsStatisticalSummary.Count)
for (cat, v) in values.items():
stat.calculate(v)
record = [cat, stat.min(), stat.max(), stat.mean(), stat.sampleStDev(), stat.sum(), stat.count()]
writer.addRecord(record)
示例8: processAlgorithm
# 需要导入模块: from qgis.core import QgsStatisticalSummary [as 别名]
# 或者: from qgis.core.QgsStatisticalSummary import count [as 别名]
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
value_field_name = self.parameterAsString(parameters, self.VALUES_FIELD_NAME, context)
category_field_name = self.parameterAsString(parameters, self.CATEGORIES_FIELD_NAME, context)
value_field_index = source.fields().lookupField(value_field_name)
category_field_index = source.fields().lookupField(category_field_name)
features = source.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry))
total = 100.0 / source.featureCount() if source.featureCount() else 0
values = {}
for current, feat in enumerate(features):
if feedback.isCanceled():
break
feedback.setProgress(int(current * total))
attrs = feat.attributes()
try:
value = float(attrs[value_field_index])
cat = attrs[category_field_index]
if cat not in values:
values[cat] = []
values[cat].append(value)
except:
pass
fields = QgsFields()
fields.append(source.fields().at(category_field_index))
fields.append(QgsField('min', QVariant.Double))
fields.append(QgsField('max', QVariant.Double))
fields.append(QgsField('mean', QVariant.Double))
fields.append(QgsField('stddev', QVariant.Double))
fields.append(QgsField('sum', QVariant.Double))
fields.append(QgsField('count', QVariant.Int))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
fields, QgsWkbTypes.NoGeometry, QgsCoordinateReferenceSystem())
stat = QgsStatisticalSummary(QgsStatisticalSummary.Min | QgsStatisticalSummary.Max |
QgsStatisticalSummary.Mean | QgsStatisticalSummary.StDevSample |
QgsStatisticalSummary.Sum | QgsStatisticalSummary.Count)
for (cat, v) in list(values.items()):
stat.calculate(v)
f = QgsFeature()
f.setAttributes([cat, stat.min(), stat.max(), stat.mean(), stat.sampleStDev(), stat.sum(), stat.count()])
sink.addFeature(f, QgsFeatureSink.FastInsert)
return {self.OUTPUT: dest_id}