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119 lines
4.4 KiB
Python
119 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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__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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import math
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from processing.core.outputs import OutputTable
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from processing.core.GeoAlgorithm import GeoAlgorithm
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from processing.tools import dataobjects, vector
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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(GeoAlgorithm):
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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 defineCharacteristics(self):
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self.name, self.i18n_name = self.trAlgorithm('Statistics by categories')
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self.group, self.i18n_group = self.trAlgorithm('Vector table tools')
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self.addParameter(ParameterVector(self.INPUT_LAYER,
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self.tr('Input vector layer'), [ParameterVector.VECTOR_TYPE_ANY], False))
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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 processAlgorithm(self, progress):
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layer = dataobjects.getObjectFromUri(self.getParameterValue(self.INPUT_LAYER))
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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.fieldNameIndex(valuesFieldName)
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categoriesField = layer.fieldNameIndex(categoriesFieldName)
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features = vector.features(layer)
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nFeats = len(features)
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values = {}
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nFeat = 0
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for feat in features:
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nFeat += 1
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progress.setPercentage(int(100 * nFeats / nFeat))
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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 = unicode(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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for (cat, v) in values.items():
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(min, max, mean, stddev, sum) = calculateStats(v)
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record = [cat, min, max, mean, stddev, sum, len(v)]
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writer.addRecord(record)
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def calculateStats(values):
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n = 0
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sum = 0
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mean = 0
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M2 = 0
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minvalue = None
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maxvalue = None
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for v in values:
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sum += v
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n = n + 1
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delta = v - mean
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mean = mean + delta / n
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M2 = M2 + delta * (v - mean)
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if minvalue is None:
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minvalue = v
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maxvalue = v
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else:
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minvalue = min(v, minvalue)
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maxvalue = max(v, maxvalue)
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if n > 1:
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variance = M2 / (n - 1)
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else:
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variance = 0
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stddev = math.sqrt(variance)
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return (minvalue, maxvalue, mean, stddev, sum)
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