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

# -*- coding: utf-8 -*-

"""
***************************************************************************
    BasicStatisticsNumbers.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__ = '$Format:%H$'

import math

from processing.core.GeoAlgorithm import GeoAlgorithm
from processing.core.parameters import ParameterVector
from processing.core.parameters import ParameterTableField
from processing.core.outputs import OutputHTML
from processing.core.outputs import OutputNumber
from processing.tools import dataobjects, vector


class BasicStatisticsNumbers(GeoAlgorithm):

    INPUT_LAYER = 'INPUT_LAYER'
    FIELD_NAME = 'FIELD_NAME'
    OUTPUT_HTML_FILE = 'OUTPUT_HTML_FILE'

    CV = 'CV'
    MIN = 'MIN'
    MAX = 'MAX'
    SUM = 'SUM'
    MEAN = 'MEAN'
    COUNT = 'COUNT'
    STD_DEV = 'STD_DEV'
    RANGE = 'RANGE'
    MEDIAN = 'MEDIAN'
    UNIQUE = 'UNIQUE'

    def defineCharacteristics(self):
        self.name, self.i18n_name = self.trAlgorithm('Basic statistics for numeric fields')
        self.group, self.i18n_group = self.trAlgorithm('Vector table tools')

        self.addParameter(ParameterVector(self.INPUT_LAYER,
            self.tr('Input vector layer'), ParameterVector.VECTOR_TYPE_ANY, False))
        self.addParameter(ParameterTableField(self.FIELD_NAME,
            self.tr('Field to calculate statistics on'),
            self.INPUT_LAYER, ParameterTableField.DATA_TYPE_NUMBER))

        self.addOutput(OutputHTML(self.OUTPUT_HTML_FILE,
            self.tr('Statistics')))

        self.addOutput(OutputNumber(self.CV, self.tr('Coefficient of Variation')))
        self.addOutput(OutputNumber(self.MIN, self.tr('Minimum value')))
        self.addOutput(OutputNumber(self.MAX, self.tr('Maximum value')))
        self.addOutput(OutputNumber(self.SUM, self.tr('Sum')))
        self.addOutput(OutputNumber(self.MEAN, self.tr('Mean value')))
        self.addOutput(OutputNumber(self.COUNT, self.tr('Count')))
        self.addOutput(OutputNumber(self.RANGE, self.tr('Range')))
        self.addOutput(OutputNumber(self.MEDIAN, self.tr('Median')))
        self.addOutput(OutputNumber(self.UNIQUE, self.tr('Number of unique values')))
        self.addOutput(OutputNumber(self.STD_DEV, self.tr('Standard deviation')))

    def processAlgorithm(self, progress):
        layer = dataobjects.getObjectFromUri(
            self.getParameterValue(self.INPUT_LAYER))
        fieldName = self.getParameterValue(self.FIELD_NAME)

        outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)

        index = layer.fieldNameIndex(fieldName)

        cvValue = 0
        minValue = 0
        maxValue = 0
        sumValue = 0
        meanValue = 0
        medianValue = 0
        stdDevValue = 0

        isFirst = True
        values = []

        features = vector.features(layer)
        count = len(features)
        total = 100.0 / float(count)
        current = 0
        for ft in features:
            if ft.attributes()[index]:
                value = float(ft.attributes()[index])
                if isFirst:
                    minValue = value
                    maxValue = value
                    isFirst = False
                else:
                    if value < minValue:
                        minValue = value
                    if value > maxValue:
                        maxValue = value

                values.append(value)
                sumValue += value

            current += 1
            progress.setPercentage(int(current * total))

        # Calculate additional values
        rValue = maxValue - minValue
        uniqueValue = vector.getUniqueValuesCount(layer, index)

        if count > 0:
            meanValue = sumValue / count
            if meanValue != 0.00:
                for v in values:
                    stdDevValue += (v - meanValue) * (v - meanValue)
                stdDevValue = math.sqrt(stdDevValue / count)
                cvValue = stdDevValue / meanValue

        if count > 1:
            tmp = values
            tmp.sort()

            # Calculate median
            if count % 2 == 0:
                medianValue = 0.5 * (tmp[(count - 1) / 2] + tmp[count / 2])
            else:
                medianValue = tmp[(count + 1) / 2 - 1]

        data = []
        data.append('Count: ' + unicode(count))
        data.append('Unique values: ' + unicode(uniqueValue))
        data.append('Minimum value: ' + unicode(minValue))
        data.append('Maximum value: ' + unicode(maxValue))
        data.append('Range: ' + unicode(rValue))
        data.append('Sum: ' + unicode(sumValue))
        data.append('Mean value: ' + unicode(meanValue))
        data.append('Median value: ' + unicode(medianValue))
        data.append('Standard deviation: ' + unicode(stdDevValue))
        data.append('Coefficient of Variation: ' + unicode(cvValue))

        self.createHTML(outputFile, data)

        self.setOutputValue(self.COUNT, count)
        self.setOutputValue(self.UNIQUE, uniqueValue)
        self.setOutputValue(self.MIN, minValue)
        self.setOutputValue(self.MAX, maxValue)
        self.setOutputValue(self.RANGE, rValue)
        self.setOutputValue(self.SUM, sumValue)
        self.setOutputValue(self.MEAN, meanValue)
        self.setOutputValue(self.MEDIAN, medianValue)
        self.setOutputValue(self.STD_DEV, stdDevValue)
        self.setOutputValue(self.CV, cvValue)

    def createHTML(self, outputFile, algData):
        f = open(outputFile, 'w')
        for s in algData:
            f.write('<p>' + unicode(s) + '</p>')
        f.close()