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

"""
***************************************************************************
    BasicStatistics.py
    ---------------------
    Date                 : November 2016
    Copyright            : (C) 2016 by Nyall Dawson
    Email                : nyall dot dawson 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__ = 'Nyall Dawson'
__date__ = 'November 2016'
__copyright__ = '(C) 2016, Nyall Dawson'

# This will get replaced with a git SHA1 when you do a git archive

__revision__ = '$Format:%H$'

import os
import codecs

from qgis.PyQt.QtCore import QVariant
from qgis.PyQt.QtGui import QIcon

from qgis.core import (QgsStatisticalSummary,
                       QgsStringStatisticalSummary,
                       QgsDateTimeStatisticalSummary,
                       QgsFeatureRequest,
                       QgsProcessingException,
                       QgsProcessingParameterFeatureSource,
                       QgsProcessingParameterField,
                       QgsProcessingParameterFileDestination,
                       QgsProcessingOutputNumber,
                       QgsProcessingFeatureSource)

from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm

pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]


class BasicStatisticsForField(QgisAlgorithm):

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

    MIN = 'MIN'
    MAX = 'MAX'
    COUNT = 'COUNT'
    UNIQUE = 'UNIQUE'
    EMPTY = 'EMPTY'
    FILLED = 'FILLED'
    MIN_LENGTH = 'MIN_LENGTH'
    MAX_LENGTH = 'MAX_LENGTH'
    MEAN_LENGTH = 'MEAN_LENGTH'
    CV = 'CV'
    SUM = 'SUM'
    MEAN = 'MEAN'
    STD_DEV = 'STD_DEV'
    RANGE = 'RANGE'
    MEDIAN = 'MEDIAN'
    MINORITY = 'MINORITY'
    MAJORITY = 'MAJORITY'
    FIRSTQUARTILE = 'FIRSTQUARTILE'
    THIRDQUARTILE = 'THIRDQUARTILE'
    IQR = 'IQR'

    def icon(self):
        return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'basic_statistics.png'))

    def tags(self):
        return self.tr('stats,statistics,date,time,datetime,string,number,text,table,layer,maximum,minimum,mean,average,standard,deviation,'
                       'count,distinct,unique,variance,median,quartile,range,majority,minority').split(',')

    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_LAYER,
                                                              self.tr('Input layer')))

        self.addParameter(QgsProcessingParameterField(self.FIELD_NAME,
                                                      self.tr('Field to calculate statistics on'),
                                                      None, self.INPUT_LAYER, QgsProcessingParameterField.Any))

        self.addParameter(QgsProcessingParameterFileDestination(self.OUTPUT_HTML_FILE, self.tr('Statistics'), self.tr('HTML files (*.html)'), None, True))

        self.addOutput(QgsProcessingOutputNumber(self.COUNT, self.tr('Count')))
        self.addOutput(QgsProcessingOutputNumber(self.UNIQUE, self.tr('Number of unique values')))
        self.addOutput(QgsProcessingOutputNumber(self.EMPTY, self.tr('Number of empty (null) values')))
        self.addOutput(QgsProcessingOutputNumber(self.FILLED, self.tr('Number of non-empty values')))
        self.addOutput(QgsProcessingOutputNumber(self.MIN, self.tr('Minimum value')))
        self.addOutput(QgsProcessingOutputNumber(self.MAX, self.tr('Maximum value')))
        self.addOutput(QgsProcessingOutputNumber(self.MIN_LENGTH, self.tr('Minimum length')))
        self.addOutput(QgsProcessingOutputNumber(self.MAX_LENGTH, self.tr('Maximum length')))
        self.addOutput(QgsProcessingOutputNumber(self.MEAN_LENGTH, self.tr('Mean length')))
        self.addOutput(QgsProcessingOutputNumber(self.CV, self.tr('Coefficient of Variation')))
        self.addOutput(QgsProcessingOutputNumber(self.SUM, self.tr('Sum')))
        self.addOutput(QgsProcessingOutputNumber(self.MEAN, self.tr('Mean value')))
        self.addOutput(QgsProcessingOutputNumber(self.STD_DEV, self.tr('Standard deviation')))
        self.addOutput(QgsProcessingOutputNumber(self.RANGE, self.tr('Range')))
        self.addOutput(QgsProcessingOutputNumber(self.MEDIAN, self.tr('Median')))
        self.addOutput(QgsProcessingOutputNumber(self.MINORITY, self.tr('Minority (rarest occurring value)')))
        self.addOutput(QgsProcessingOutputNumber(self.MAJORITY, self.tr('Majority (most frequently occurring value)')))
        self.addOutput(QgsProcessingOutputNumber(self.FIRSTQUARTILE, self.tr('First quartile')))
        self.addOutput(QgsProcessingOutputNumber(self.THIRDQUARTILE, self.tr('Third quartile')))
        self.addOutput(QgsProcessingOutputNumber(self.IQR, self.tr('Interquartile Range (IQR)')))

    def name(self):
        return 'basicstatisticsforfields'

    def displayName(self):
        return self.tr('Basic statistics for fields')

    def processAlgorithm(self, parameters, context, feedback):
        source = self.parameterAsSource(parameters, self.INPUT_LAYER, context)
        if source is None:
            raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))

        field_name = self.parameterAsString(parameters, self.FIELD_NAME, context)
        field = source.fields().at(source.fields().lookupField(field_name))

        output_file = self.parameterAsFileOutput(parameters, self.OUTPUT_HTML_FILE, context)

        request = QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([field_name], source.fields())
        features = source.getFeatures(request, QgsProcessingFeatureSource.FlagSkipGeometryValidityChecks)
        count = source.featureCount()

        data = []
        data.append(self.tr('Analyzed field: {}').format(field_name))
        results = {}

        if field.isNumeric():
            d, results = self.calcNumericStats(features, feedback, field, count)
            data.extend(d)
        elif field.type() in (QVariant.Date, QVariant.Time, QVariant.DateTime):
            d, results = self.calcDateTimeStats(features, feedback, field, count)
            data.extend(d)
        else:
            d, results = self.calcStringStats(features, feedback, field, count)
            data.extend(d)

        if output_file:
            self.createHTML(output_file, data)
            results[self.OUTPUT_HTML_FILE] = output_file

        return results

    def calcNumericStats(self, features, feedback, field, count):
        total = 100.0 / count if count else 0
        stat = QgsStatisticalSummary()
        for current, ft in enumerate(features):
            if feedback.isCanceled():
                break
            stat.addVariant(ft[field.name()])
            feedback.setProgress(int(current * total))
        stat.finalize()

        cv = stat.stDev() / stat.mean() if stat.mean() != 0 else 0

        results = {self.COUNT: stat.count(),
                   self.UNIQUE: stat.variety(),
                   self.EMPTY: stat.countMissing(),
                   self.FILLED: count - stat.countMissing(),
                   self.MIN: stat.min(),
                   self.MAX: stat.max(),
                   self.RANGE: stat.range(),
                   self.SUM: stat.sum(),
                   self.MEAN: stat.mean(),
                   self.MEDIAN: stat.median(),
                   self.STD_DEV: stat.stDev(),
                   self.CV: cv,
                   self.MINORITY: stat.minority(),
                   self.MAJORITY: stat.majority(),
                   self.FIRSTQUARTILE: stat.firstQuartile(),
                   self.THIRDQUARTILE: stat.thirdQuartile(),
                   self.IQR: stat.interQuartileRange()}

        data = []
        data.append(self.tr('Count: {}').format(stat.count()))
        data.append(self.tr('Unique values: {}').format(stat.variety()))
        data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing()))
        data.append(self.tr('Minimum value: {}').format(stat.min()))
        data.append(self.tr('Maximum value: {}').format(stat.max()))
        data.append(self.tr('Range: {}').format(stat.range()))
        data.append(self.tr('Sum: {}').format(stat.sum()))
        data.append(self.tr('Mean value: {}').format(stat.mean()))
        data.append(self.tr('Median value: {}').format(stat.median()))
        data.append(self.tr('Standard deviation: {}').format(stat.stDev()))
        data.append(self.tr('Coefficient of Variation: {}').format(cv))
        data.append(self.tr('Minority (rarest occurring value): {}').format(stat.minority()))
        data.append(self.tr('Majority (most frequently occurring value): {}').format(stat.majority()))
        data.append(self.tr('First quartile: {}').format(stat.firstQuartile()))
        data.append(self.tr('Third quartile: {}').format(stat.thirdQuartile()))
        data.append(self.tr('Interquartile Range (IQR): {}').format(stat.interQuartileRange()))
        return data, results

    def calcStringStats(self, features, feedback, field, count):
        total = 100.0 / count if count else 1
        stat = QgsStringStatisticalSummary()
        for current, ft in enumerate(features):
            if feedback.isCanceled():
                break
            stat.addValue(ft[field.name()])
            feedback.setProgress(int(current * total))
        stat.finalize()

        results = {self.COUNT: stat.count(),
                   self.UNIQUE: stat.countDistinct(),
                   self.EMPTY: stat.countMissing(),
                   self.FILLED: stat.count() - stat.countMissing(),
                   self.MIN: stat.min(),
                   self.MAX: stat.max(),
                   self.MIN_LENGTH: stat.minLength(),
                   self.MAX_LENGTH: stat.maxLength(),
                   self.MEAN_LENGTH: stat.meanLength()}

        data = []
        data.append(self.tr('Count: {}').format(count))
        data.append(self.tr('Unique values: {}').format(stat.countDistinct()))
        data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing()))
        data.append(self.tr('Minimum value: {}').format(stat.min()))
        data.append(self.tr('Maximum value: {}').format(stat.max()))
        data.append(self.tr('Minimum length: {}').format(stat.minLength()))
        data.append(self.tr('Maximum length: {}').format(stat.maxLength()))
        data.append(self.tr('Mean length: {}').format(stat.meanLength()))

        return data, results

    def calcDateTimeStats(self, features, feedback, field, count):
        total = 100.0 / count if count else 1
        stat = QgsDateTimeStatisticalSummary()
        for current, ft in enumerate(features):
            if feedback.isCanceled():
                break
            stat.addValue(ft[field.name()])
            feedback.setProgress(int(current * total))
        stat.finalize()

        results = {self.COUNT: stat.count(),
                   self.UNIQUE: stat.countDistinct(),
                   self.EMPTY: stat.countMissing(),
                   self.FILLED: stat.count() - stat.countMissing(),
                   self.MIN: stat.statistic(QgsDateTimeStatisticalSummary.Min),
                   self.MAX: stat.statistic(QgsDateTimeStatisticalSummary.Max)}

        data = []
        data.append(self.tr('Count: {}').format(count))
        data.append(self.tr('Unique values: {}').format(stat.countDistinct()))
        data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing()))
        data.append(self.tr('Minimum value: {}').format(field.displayString(stat.statistic(QgsDateTimeStatisticalSummary.Min))))
        data.append(self.tr('Maximum value: {}').format(field.displayString(stat.statistic(QgsDateTimeStatisticalSummary.Max))))

        return data, results

    def createHTML(self, outputFile, algData):
        with codecs.open(outputFile, 'w', encoding='utf-8') as f:
            f.write('<html><head>\n')
            f.write('<meta http-equiv="Content-Type" content="text/html; \
                    charset=utf-8" /></head><body>\n')
            for s in algData:
                f.write('<p>' + str(s) + '</p>\n')
            f.write('</body></html>\n')