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

"""
***************************************************************************
    BarPlot.py
    ---------------------
    Date                 : March 2015
    Copyright            : (C) 2017 by Matteo Ghetta
    Email                : matteo dot ghetta 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__ = 'Matteo Ghetta'
__date__ = 'March 2017'
__copyright__ = '(C) 2017, Matteo Ghetta'

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

__revision__ = '$Format:%H$'

import plotly as plt
import plotly.graph_objs as go

from qgis.core import (QgsProcessingParameterFeatureSource,
                       QgsProcessingParameterField,
                       QgsProcessingParameterEnum,
                       QgsProcessingParameterFileDestination,
                       QgsProcessingOutputHtml,
                       QgsFeatureRequest)
from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
from processing.tools import vector


class BoxPlot(QgisAlgorithm):

    INPUT = 'INPUT'
    OUTPUT = 'OUTPUT'
    NAME_FIELD = 'NAME_FIELD'
    VALUE_FIELD = 'VALUE_FIELD'
    MSD = 'MSD'

    def group(self):
        return self.tr('Graphics')

    def __init__(self):
        super().__init__()

    def initAlgorithm(self, config=None):
        self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT,
                                                              self.tr('Input layer')))
        self.addParameter(QgsProcessingParameterField(self.NAME_FIELD,
                                                      self.tr('Category name field'),
                                                      parentLayerParameterName=self.INPUT,
                                                      type=QgsProcessingParameterField.Any))
        self.addParameter(QgsProcessingParameterField(self.VALUE_FIELD,
                                                      self.tr('Value field'),
                                                      parentLayerParameterName=self.INPUT,
                                                      type=QgsProcessingParameterField.Numeric))
        msd = [self.tr('Show Mean'),
               self.tr('Show Standard Deviation'),
               self.tr('Don\'t show Mean and Standard Deviation')
               ]
        self.addParameter(QgsProcessingParameterEnum(
            self.MSD,
            self.tr('Additional Statistic Lines'),
            options=msd, defaultValue=0))

        self.addParameter(QgsProcessingParameterFileDestination(self.OUTPUT, self.tr('Box plot'), self.tr('HTML files (*.html)')))
        self.addOutput(QgsProcessingOutputHtml(self.OUTPUT, self.tr('Box plot')))

    def name(self):
        return 'boxplot'

    def displayName(self):
        return self.tr('Box plot')

    def processAlgorithm(self, parameters, context, feedback):
        source = self.parameterAsSource(parameters, self.INPUT, context)
        namefieldname = self.parameterAsString(parameters, self.NAME_FIELD, context)
        valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD, context)

        output = self.parameterAsFileOutput(parameters, self.OUTPUT, context)

        values = vector.values(source, valuefieldname)

        x_index = source.fields().lookupField(namefieldname)
        x_var = [i[namefieldname] for i in source.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([x_index]))]

        msdIndex = self.parameterAsEnum(parameters, self.MSD, context)
        msd = True

        if msdIndex == 1:
            msd = 'sd'
        elif msdIndex == 2:
            msd = False

        data = [go.Box(
                x=x_var,
                y=values[valuefieldname],
                boxmean=msd)]

        plt.offline.plot(data, filename=output, auto_open=False)

        return {self.OUTPUT: output}