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# -*- coding: utf-8 -*-
"""
***************************************************************************
StatisticsByCategories.py
---------------------
Date : September 2012
Copyright : (C) 2012 by Victor Olaya
Email : volayaf at gmail dot com
***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************
"""
__author__ = 'Victor Olaya'
__date__ = 'September 2012'
__copyright__ = '(C) 2012, Victor Olaya'
from qgis.core import (QgsProcessingParameterFeatureSource,
QgsStatisticalSummary,
QgsDateTimeStatisticalSummary,
QgsStringStatisticalSummary,
QgsFeatureRequest,
QgsApplication,
QgsProcessingException,
QgsProcessingParameterField,
QgsProcessingParameterFeatureSink,
QgsFields,
QgsField,
QgsWkbTypes,
QgsCoordinateReferenceSystem,
QgsFeature,
QgsFeatureSink,
QgsProcessing,
QgsProcessingFeatureSource,
NULL)
from qgis.PyQt.QtCore import QVariant
from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
from collections import defaultdict
class StatisticsByCategories(QgisAlgorithm):
INPUT = 'INPUT'
VALUES_FIELD_NAME = 'VALUES_FIELD_NAME'
CATEGORIES_FIELD_NAME = 'CATEGORIES_FIELD_NAME'
OUTPUT = 'OUTPUT'
def group(self):
return self.tr('Vector analysis')
def groupId(self):
return 'vectoranalysis'
def tags(self):
return self.tr('groups,stats,statistics,table,layer,sum,maximum,minimum,mean,average,standard,deviation,'
'count,distinct,unique,variance,median,quartile,range,majority,minority,histogram,distinct,summary').split(',')
def icon(self):
return QgsApplication.getThemeIcon("/algorithms/mAlgorithmBasicStatistics.svg")
def svgIconPath(self):
return QgsApplication.iconPath("/algorithms/mAlgorithmBasicStatistics.svg")
def __init__(self):
super().__init__()
def initAlgorithm(self, config=None):
self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT,
self.tr('Input vector layer'),
types=[QgsProcessing.TypeVector]))
self.addParameter(QgsProcessingParameterField(self.VALUES_FIELD_NAME,
self.tr(
'Field to calculate statistics on (if empty, only count is calculated)'),
parentLayerParameterName=self.INPUT, optional=True))
self.addParameter(QgsProcessingParameterField(self.CATEGORIES_FIELD_NAME,
self.tr('Field(s) with categories'),
parentLayerParameterName=self.INPUT,
type=QgsProcessingParameterField.Any, allowMultiple=True))
self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT, self.tr('Statistics by category')))
def name(self):
return 'statisticsbycategories'
def displayName(self):
return self.tr('Statistics by categories')
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
value_field_name = self.parameterAsString(parameters, self.VALUES_FIELD_NAME, context)
category_field_names = self.parameterAsFields(parameters, self.CATEGORIES_FIELD_NAME, context)
value_field_index = source.fields().lookupField(value_field_name)
if value_field_index >= 0:
value_field = source.fields().at(value_field_index)
else:
value_field = None
category_field_indexes = [source.fields().lookupField(n) for n in category_field_names]
# generate output fields
fields = QgsFields()
for c in category_field_indexes:
fields.append(source.fields().at(c))
def addField(name):
"""
Adds a field to the output, keeping the same data type as the value_field
"""
field = QgsField(value_field)
field.setName(name)
fields.append(field)
if value_field is None:
field_type = 'none'
fields.append(QgsField('count', QVariant.Int))
elif value_field.isNumeric():
field_type = 'numeric'
fields.append(QgsField('count', QVariant.Int))
fields.append(QgsField('unique', QVariant.Int))
fields.append(QgsField('min', QVariant.Double))
fields.append(QgsField('max', QVariant.Double))
fields.append(QgsField('range', QVariant.Double))
fields.append(QgsField('sum', QVariant.Double))
fields.append(QgsField('mean', QVariant.Double))
fields.append(QgsField('median', QVariant.Double))
fields.append(QgsField('stddev', QVariant.Double))
fields.append(QgsField('minority', QVariant.Double))
fields.append(QgsField('majority', QVariant.Double))
fields.append(QgsField('q1', QVariant.Double))
fields.append(QgsField('q3', QVariant.Double))
fields.append(QgsField('iqr', QVariant.Double))
elif value_field.type() in (QVariant.Date, QVariant.Time, QVariant.DateTime):
field_type = 'datetime'
fields.append(QgsField('count', QVariant.Int))
fields.append(QgsField('unique', QVariant.Int))
fields.append(QgsField('empty', QVariant.Int))
fields.append(QgsField('filled', QVariant.Int))
# keep same data type for these fields
addField('min')
addField('max')
else:
field_type = 'string'
fields.append(QgsField('count', QVariant.Int))
fields.append(QgsField('unique', QVariant.Int))
fields.append(QgsField('empty', QVariant.Int))
fields.append(QgsField('filled', QVariant.Int))
# keep same data type for these fields
addField('min')
addField('max')
fields.append(QgsField('min_length', QVariant.Int))
fields.append(QgsField('max_length', QVariant.Int))
fields.append(QgsField('mean_length', QVariant.Double))
request = QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry)
if value_field is not None:
attrs = [value_field_index]
else:
attrs = []
attrs.extend(category_field_indexes)
request.setSubsetOfAttributes(attrs)
features = source.getFeatures(request, QgsProcessingFeatureSource.FlagSkipGeometryValidityChecks)
total = 50.0 / source.featureCount() if source.featureCount() else 0
if field_type == 'none':
values = defaultdict(lambda: 0)
else:
values = defaultdict(list)
for current, feat in enumerate(features):
if feedback.isCanceled():
break
feedback.setProgress(int(current * total))
attrs = feat.attributes()
cat = tuple([attrs[c] for c in category_field_indexes])
if field_type == 'none':
values[cat] += 1
continue
if field_type == 'numeric':
if attrs[value_field_index] == NULL:
continue
else:
value = float(attrs[value_field_index])
elif field_type == 'string':
if attrs[value_field_index] == NULL:
value = ''
else:
value = str(attrs[value_field_index])
elif attrs[value_field_index] == NULL:
value = NULL
else:
value = attrs[value_field_index]
values[cat].append(value)
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
fields, QgsWkbTypes.NoGeometry, QgsCoordinateReferenceSystem())
if sink is None:
raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT))
if field_type == 'none':
self.saveCounts(values, sink, feedback)
elif field_type == 'numeric':
self.calcNumericStats(values, sink, feedback)
elif field_type == 'datetime':
self.calcDateTimeStats(values, sink, feedback)
else:
self.calcStringStats(values, sink, feedback)
return {self.OUTPUT: dest_id}
def saveCounts(self, values, sink, feedback):
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)
f = QgsFeature()
f.setAttributes(list(cat) + [v])
sink.addFeature(f, QgsFeatureSink.FastInsert)
current += 1
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
def calcDateTimeStats(self, values, sink, feedback):
stat = QgsDateTimeStatisticalSummary()
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.countDistinct(),
stat.countMissing(),
stat.count() - stat.countMissing(),
stat.statistic(QgsDateTimeStatisticalSummary.Min),
stat.statistic(QgsDateTimeStatisticalSummary.Max)
])
sink.addFeature(f, QgsFeatureSink.FastInsert)
current += 1
def calcStringStats(self, values, sink, feedback):
stat = QgsStringStatisticalSummary()
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.countDistinct(),
stat.countMissing(),
stat.count() - stat.countMissing(),
stat.min(),
stat.max(),
stat.minLength(),
stat.maxLength(),
stat.meanLength()
])
sink.addFeature(f, QgsFeatureSink.FastInsert)
current += 1
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