"""
***************************************************************************
    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'

import warnings

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

from qgis.PyQt.QtCore import QCoreApplication


class BoxPlot(QgisAlgorithm):
    INPUT = 'INPUT'
    OUTPUT = 'OUTPUT'
    NAME_FIELD = 'NAME_FIELD'
    VALUE_FIELD = 'VALUE_FIELD'
    MSD = 'MSD'
    TITLE = 'TITLE'
    XAXIS_TITLE = "XAXIS_TITLE"
    YAXIS_TITLE = "YAXIS_TITLE"

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

    def groupId(self):
        return 'plots'

    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.DataType.Any))
        self.addParameter(QgsProcessingParameterField(self.VALUE_FIELD,
                                                      self.tr('Value field'),
                                                      parentLayerParameterName=self.INPUT,
                                                      type=QgsProcessingParameterField.DataType.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(QgsProcessingParameterString(
            self.TITLE,
            self.tr('Title'),
            optional=True))

        self.addParameter(QgsProcessingParameterString(
            self.XAXIS_TITLE,
            self.tr('Xaxis Title'),
            optional=True))

        self.addParameter(QgsProcessingParameterString(
            self.YAXIS_TITLE,
            self.tr('Yaxis Title'),
            optional=True))

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

    def name(self):
        return 'boxplot'

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

    def processAlgorithm(self, parameters, context, feedback):
        try:
            # importing plotly throws Python warnings from within the library - filter these out
            with warnings.catch_warnings():
                warnings.filterwarnings("ignore", category=ResourceWarning)
                warnings.filterwarnings("ignore", category=ImportWarning)
                import plotly as plt
                import plotly.graph_objs as go
        except ImportError:
            raise QgsProcessingException(QCoreApplication.translate('BoxPlot', 'This algorithm requires the Python “plotly” library. Please install this library and try again.'))

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

        namefieldname = self.parameterAsString(parameters, self.NAME_FIELD, context)
        valuefieldname = self.parameterAsString(parameters, self.VALUE_FIELD, context)

        title = self.parameterAsString(parameters, self.TITLE, context)
        xaxis_title = self.parameterAsString(parameters, self.XAXIS_TITLE, context)
        yaxis_title = self.parameterAsString(parameters, self.YAXIS_TITLE, context)

        if title.strip() == "": title = None
        if xaxis_title.strip() == "": xaxis_title = None
        if yaxis_title.strip() == "": xaxis_title = None

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

        values = vector.values(source, valuefieldname)

        x_index = source.fields().lookupField(namefieldname)
        x_var = vector.convert_nulls([i[namefieldname] for i in source.getFeatures(QgsFeatureRequest().setFlags(QgsFeatureRequest.Flag.NoGeometry).setSubsetOfAttributes([x_index]))], '<NULL>')

        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)]

        fig = go.Figure(
            data=data,
            layout_title_text=title,
            layout_xaxis_title=xaxis_title,
            layout_yaxis_title=yaxis_title)

        fig.write_html(output)

        return {self.OUTPUT: output}