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 = 'Basic statistics for numeric fields'
        self.group = '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 for numeric field')))

        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>' + str(s) + '</p>')
        f.close()