QGIS/python/plugins/processing/algs/qgis/StatisticsByCategories.py

312 lines
13 KiB
Python
Raw Normal View History

2013-02-16 00:23:56 +01:00
# -*- 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
2017-06-06 13:41:42 +10:00
from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
2013-02-16 00:23:56 +01:00
from collections import defaultdict
2013-02-16 00:23:56 +01:00
class StatisticsByCategories(QgisAlgorithm):
INPUT = 'INPUT'
VALUES_FIELD_NAME = 'VALUES_FIELD_NAME'
CATEGORIES_FIELD_NAME = 'CATEGORIES_FIELD_NAME'
OUTPUT = 'OUTPUT'
2013-02-28 22:08:32 +01:00
def group(self):
2017-08-22 23:36:42 +10:00
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,'
2018-06-20 15:06:36 +10:00
'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))
2013-02-16 00:23:56 +01:00
self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT, self.tr('Statistics by category')))
2013-02-28 22:08:32 +01:00
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)
2013-02-16 00:23:56 +01:00
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]
2013-02-28 22:08:32 +01:00
# 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))
2013-02-16 00:23:56 +01:00
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)
2013-02-28 22:08:32 +01:00
(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