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b1cadb1822
have specific icons, instead of generic qgis icon We consider these 'top level' algorithms, and using the standard algorithm icon should help reflect this and differentiate them from 3rd party algorithms.
102 lines
4.4 KiB
Python
102 lines
4.4 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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StatisticsByCategories.py
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---------------------
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Date : September 2012
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Copyright : (C) 2012 by Victor Olaya
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Email : volayaf at gmail dot com
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***************************************************************************
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* *
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* This program is free software; you can redistribute it and/or modify *
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* it under the terms of the GNU General Public License as published by *
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* the Free Software Foundation; either version 2 of the License, or *
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* (at your option) any later version. *
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* *
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***************************************************************************
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"""
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from builtins import str
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__author__ = 'Victor Olaya'
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__date__ = 'September 2012'
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__copyright__ = '(C) 2012, Victor Olaya'
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# This will get replaced with a git SHA1 when you do a git archive
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__revision__ = '$Format:%H$'
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from qgis.core import (QgsApplication,
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QgsFeatureSink,
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QgsStatisticalSummary,
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QgsProcessingUtils)
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from processing.core.outputs import OutputTable
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from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
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from processing.core.parameters import ParameterVector
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from processing.core.parameters import ParameterTableField
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class StatisticsByCategories(QgisAlgorithm):
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INPUT_LAYER = 'INPUT_LAYER'
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VALUES_FIELD_NAME = 'VALUES_FIELD_NAME'
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CATEGORIES_FIELD_NAME = 'CATEGORIES_FIELD_NAME'
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OUTPUT = 'OUTPUT'
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def group(self):
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return self.tr('Vector table tools')
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def __init__(self):
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super().__init__()
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self.addParameter(ParameterVector(self.INPUT_LAYER,
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self.tr('Input vector layer')))
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self.addParameter(ParameterTableField(self.VALUES_FIELD_NAME,
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self.tr('Field to calculate statistics on'),
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self.INPUT_LAYER, ParameterTableField.DATA_TYPE_NUMBER))
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self.addParameter(ParameterTableField(self.CATEGORIES_FIELD_NAME,
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self.tr('Field with categories'),
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self.INPUT_LAYER, ParameterTableField.DATA_TYPE_ANY))
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self.addOutput(OutputTable(self.OUTPUT, self.tr('Statistics by category')))
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def name(self):
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return 'statisticsbycategories'
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def displayName(self):
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return self.tr('Statistics by categories')
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def processAlgorithm(self, parameters, context, feedback):
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layer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.INPUT_LAYER), context)
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valuesFieldName = self.getParameterValue(self.VALUES_FIELD_NAME)
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categoriesFieldName = self.getParameterValue(self.CATEGORIES_FIELD_NAME)
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output = self.getOutputFromName(self.OUTPUT)
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valuesField = layer.fields().lookupField(valuesFieldName)
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categoriesField = layer.fields().lookupField(categoriesFieldName)
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features = QgsProcessingUtils.getFeatures(layer, context)
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total = 100.0 / layer.featureCount() if layer.featureCount() else 0
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values = {}
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for current, feat in enumerate(features):
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feedback.setProgress(int(current * total))
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attrs = feat.attributes()
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try:
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value = float(attrs[valuesField])
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cat = str(attrs[categoriesField])
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if cat not in values:
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values[cat] = []
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values[cat].append(value)
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except:
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pass
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fields = ['category', 'min', 'max', 'mean', 'stddev', 'sum', 'count']
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writer = output.getTableWriter(fields)
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stat = QgsStatisticalSummary(QgsStatisticalSummary.Min | QgsStatisticalSummary.Max |
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QgsStatisticalSummary.Mean | QgsStatisticalSummary.StDevSample |
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QgsStatisticalSummary.Sum | QgsStatisticalSummary.Count)
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for (cat, v) in list(values.items()):
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stat.calculate(v)
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record = [cat, stat.min(), stat.max(), stat.mean(), stat.sampleStDev(), stat.sum(), stat.count()]
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writer.addRecord(record)
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