Analyser_Merge_street_lamp_FR_eclext.py

#!/usr/bin/env python
#-*- coding: utf-8 -*-

###########################################################################
##                                                                       ##
## Copyrights François Lacombe - 2023                                    ##
##                                                                       ##
## 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 3 of the License, or     ##
## (at your option) any later version.                                   ##
##                                                                       ##
## This program is distributed in the hope that it will be useful,       ##
## but WITHOUT ANY WARRANTY; without even the implied warranty of        ##
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the         ##
## GNU General Public License for more details.                          ##
##                                                                       ##
## You should have received a copy of the GNU General Public License     ##
## along with this program.  If not, see <http://www.gnu.org/licenses/>. ##
##                                                                       ##
###########################################################################

from modules.OsmoseTranslation import T_
from dateutil.parser import parse
from .Analyser_Merge import Analyser_Merge_Point, CSV, Load_XY, Conflate, Select, Mapping


class Analyser_Merge_street_lamp_FR_eclext (Analyser_Merge_Point):
    def __init__(self, config, source_url, dataset_name, source, srid, classs, logger = None):
        Analyser_Merge_Point.__init__(self, config, logger)
        self.def_class_missing_official(item = 8490, id = classs + 1, level = 3, tags = ['merge', 'street_lamp', 'fix:chair', 'fix:survey'],
            title = T_('Street light not integrated'))
        self.def_class_possible_merge(item = 8491, id = classs + 3, level = 3, tags = ['merge', 'street_lamp', 'fix:chair', 'fix:picture'],
            title = T_('Street light integration suggestion'))
        self.def_class_update_official(item = 8492, id = classs + 4, level = 3, tags = ['merge', 'street_lamp', 'fix:chair', 'fix:survey'],
            title = T_('Street light update'))

        self.init(
            source_url,
            dataset_name,
            CSV(source, srid = srid),
            Load_XY('X', 'Y'),
            Conflate(
                select = Select(
                    types = ['nodes'],
                    tags = {'highway': 'street_lamp'}),
                conflationDistance = 20,
                mapping = Mapping(
                    static1 = {'highway': 'street_lamp', 'operator': 'Syane'},
                    static2 = {'source': self.source},
                    mapping1 = {
                        'light:method': lambda res: self.extract_light_method.get(res['typeSource']),
                        'light:colour': lambda res: self.extract_temperature(res['TemperatureCouleur']),
                        'light:flux': lambda res: self.clean_float(res.get('fluxSource')) if res.get('fluxSource') else None,
                        'light:height': lambda res: self.clean_float(res.get('hauteurFeu')) if res.get('hauteurFeu') else None,
                        'light:power': lambda res: self.clean_float(res['puissance']),
                        'light:lit': lambda res: self.extract_adaptatif.get(res.get('eclairageAdaptatif')) if res.get('eclairageAdaptatif') else None,
                        'support': lambda res: self.extract_support.get(res['support']),
                        'manufacturer': lambda res: self.clean_string_tag(res.get('fabricant')) if res.get('fabricant') else None,
                        'model': lambda res: self.clean_string_tag(res.get('model')) if res.get('model') else None,
                        'power': lambda res: 'pole' if (res['typeSource'] == 'POT') else None,
                        'start_date': lambda res: parse(res.get('datePremieInstallation')).date() if res.get('datePremieInstallation') else None},
                text = lambda tags, fields: {} )))

    extract_light_method = {
        'FLUO': 'fluorescent',
        'HAL': 'halogen',
        'IM': 'metal-iodide',
        'INC': 'incandescent',
        'IND': 'induction',
        'LED': 'LED',
        'SBP': 'low_pressure_sodium',
        'SHP': 'high_pressure_sodium',
        'VM': 'mercury',
        'XEN': 'xenon'
    }

    extract_support = {
        'CAT': 'catenary',
        'MUR': 'wall',
        'SOL': 'ground'
    }

    def extract_temperature(self, v):
        if v is None:
            return None

        try:
            num_value = int(float(v))
            if num_value > 0:
                return str(num_value)+' K'
            else:
                return None
        except ValueError:
            return None

    extract_adaptatif = {
        'EN': 'dusk_dawn',
        'CO': 'motion',
        'AV': 'demand'
    }

    def clean_string_tag(self, v):
        if v and v != 'INCONNU':
            return v.lower()
        else:
            return None

    def clean_float(self, v):
        """
        If this can be parsed as a number, ensures it is printed as
        an integer, otherwise return the string unchanged.
        Returns None for 0.
        """
        if v is None:
            return None
        try:
            num_value = float(v)
            if num_value:
                return num_value
        except ValueError:
            return v