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analyser_merge_public_transport_FR_stan.py
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analyser_merge_public_transport_FR_stan.py
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#!/usr/bin/env python
#-*- coding: utf-8 -*-
###########################################################################
## ##
## Copyrights Frédéric Rodrigo 2017 ##
## ##
## 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 .Analyser_Merge import Analyser_Merge_Point, SourceDataGouv, GTFS, Load_XY, Conflate, Select, Mapping
class Analyser_Merge_Public_Transport_FR_stan(Analyser_Merge_Point):
def __init__(self, config, logger = None):
Analyser_Merge_Point.__init__(self, config, logger)
place = "STAN"
self.def_class_missing_official(item = 8040, id = 91, level = 3, tags = ['merge', 'public transport', 'fix:survey', 'fix:picture'],
title = T_('{0} stop not integrated', place))
self.def_class_possible_merge(item = 8041, id = 93, level = 3, tags = ['merge', 'public transport', 'fix:chair'],
title = T_('{0} stop, integration suggestion', place))
self.init(
"https://www.data.gouv.fr/fr/datasets/arrets-horaires-et-parcours-theoriques-du-reseau-stan-gtfs/",
"Arrêts, horaires et parcours théoriques du réseau STAN | GTFS",
GTFS(SourceDataGouv(attribution = "Métropole du Grand Nancy",
dataset = "5aa94714c751df666fefc80f", resource = "22ff00b8-aa07-4f01-af47-8f198964bb1a")),
Load_XY("stop_lon", "stop_lat"),
Conflate(
select = Select(
types = ["nodes", "ways"],
tags = [{"highway": "bus_stop"}, {"public_transport": "stop_position"}]),
conflationDistance = 2,
osmRef = "ref:FR:STAN",
mapping = Mapping(
static1 = {
"highway": "bus_stop",
"public_transport": "stop_position",
"bus": "yes"},
static2 = {"source": self.source},
mapping1 = {
"ref:FR:STAN": "stop_code",
"wheelchair": lambda fields: self.wheelchair_boarding[fields.get("wheelchair_boarding")]},
mapping2 = {"name": "stop_name"},
text = lambda tags, fields: T_("{0} stop of {1}", place, fields["stop_name"]) )))
wheelchair_boarding = {
None: None,
"0": None,
"1": "yes",
"2": "no"
}