mirror of
https://github.com/qgis/QGIS.git
synced 2025-02-28 00:17:30 -05:00
298 lines
12 KiB
Python
298 lines
12 KiB
Python
# -*- 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'
|
|
|
|
# This will get replaced with a git SHA1 when you do a git archive
|
|
|
|
__revision__ = '$Format:%H$'
|
|
|
|
from qgis.core import (QgsProcessingParameterFeatureSource,
|
|
QgsStatisticalSummary,
|
|
QgsDateTimeStatisticalSummary,
|
|
QgsStringStatisticalSummary,
|
|
QgsFeatureRequest,
|
|
QgsProcessingParameterField,
|
|
QgsProcessingParameterFeatureSink,
|
|
QgsFields,
|
|
QgsField,
|
|
QgsWkbTypes,
|
|
QgsCoordinateReferenceSystem,
|
|
QgsFeature,
|
|
QgsFeatureSink,
|
|
QgsProcessing,
|
|
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 __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)
|
|
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)
|
|
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 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
|