685 lines
29 KiB
Python
685 lines
29 KiB
Python
#!/usr/bin/env python3
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# -*- coding: UTF-8 -*-
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#Nom : : zh.py
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#Description :
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#Copyright : 2021, CEN38
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#Auteur : Colas Geier
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#Version : 1.0
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import pandas as pd
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# import pandas_access as mdb
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# import numpy as np
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# from sqlalchemy.sql.expression import column
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from sqlalchemy import create_engine
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from geoalchemy2 import Geometry
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from .pers.pers import _get_table
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from .sites.sites import _get_typ_milieux
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from .tools import _get_relation_autor
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#####################################
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### schema personnes ###
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#####################################
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# class pers:
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# def __init__(self):
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# from .params import con
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# self.schema = 'personnes'
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# self.con = con
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# # self._get_table = _get_table
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# def get_auteur(self, nom=None, prenom=None):
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# sql = 'SELECT * FROM %s.personne'%self.schema
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# if nom or prenom : sql = sql + ' WHERE '
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# if nom :
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# sql = sql + 'nom IN %(nom)s'
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# nom = to_upper(nom)
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# if nom and prenom : sql = sql + ' AND '
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# if prenom :
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# sql = sql + 'prenom IN %(prenom)s'
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# prenom = to_upperfirst(prenom)
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# df = pd.read_sql(
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# sql = sql,
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# con = self.con,
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# params = {'nom': to_tuple(nom), 'prenom': to_tuple(prenom) })
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# return df
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# def get_organisme(self, ids=None, nom=None):
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# table = 'organisme'
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# return _get_table(self.con, self.schema, table, ids=ids, nom=nom)
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#####################################
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### schema sites ###
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#####################################
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# class sites:
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# def __init__(self):
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# from .params import con
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# from .pers import pers
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# self.schema = 'sites'
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# self.con = con
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# self.typ_milieux = self._get_typ_milieux()
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# self.typo_sdage = self._get_typo_sdage()
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# self.typ_site = self._get_typ_site()
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# self.auteur = pers.get_auteur()
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# self.organisme = pers.get_organisme()
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# def _get_typ_milieux(self, ids=None, nom=None):
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# table = 'type_milieu'
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# df = _get_table(self.con, self.schema, table, ids=ids, nom=nom)
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# return df
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# def _get_typo_sdage(self, ids=None, nom=None):
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# table = 'typo_sdage'
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# df = _get_table(self.con, self.schema, table, ids=ids, nom=nom)
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# return df
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# def _get_typ_site(self, ids=None, nom=None):
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# table = 'type_site'
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# df = _get_table(self.con, self.schema, table, ids=ids, nom=nom)
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# return df
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# def _merge_orga(self, df, split_cols):
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# org = self.organisme
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# aut = self.auteur
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# df = df.copy()
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# for c in split_cols:
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# if not isinstance(df[c], int): df[c] = df[c].astype(float)
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# df[c].replace(aut.id.tolist(), aut.id_organisme.tolist(), inplace=True)
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# df[c].replace(org.id.tolist(), org.nom.tolist(), inplace=True)
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# df['organisme'] = None
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# for c in split_cols:
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# df.loc[df.organisme.isna(), 'organisme'] = df.loc[df['organisme'].isna(), c]
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# for c in split_cols:
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# comp = df.loc[~df[c].isna(),'organisme'].compare(df.loc[~df[c].isna(), c])
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# if not comp.empty:
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# comp['test'] = comp.apply(lambda x: x['other'] in x['self'], axis=1)
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# comp = comp[~comp.test]
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# if not comp.empty:
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# df.loc[comp.index,'organisme'] = comp.self + ' & ' + comp.other
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# df.drop(columns=split_cols, inplace=True)
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# return df
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# def _merge_author(self, df, col_aut, orga=False):
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# # récupération des auteurs
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# aut = self.auteur.fillna('')
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# aut['nom_prenom'] = (aut['nom'] + ' ' + aut['prenom']).str.strip()
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# aut['id'] = aut['id'].astype(str)
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# # merge des auteurs
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# r_id = df[['id', col_aut]].copy()
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# r_idSplit = r_id[col_aut].str.split(' & ', expand=True)
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# r_id = r_id.join(r_idSplit)
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# cSplit = r_idSplit.shape[1]
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# cSplit = list(range(cSplit))
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# if orga:
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# # récup des organismes
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# org = self._merge_orga(r_id, cSplit)
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# r_id[cSplit] = r_id[cSplit].replace(aut['id'].tolist(),aut['nom_prenom'].tolist())
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# r_id = _aggr_cols(r_id,cSplit,' & ') \
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# .rename(columns={'aggreg': 'auteur'}) \
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# .drop(columns=cSplit)
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# if orga:
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# # merge des organismes
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# r_id = pd.merge(r_id,org, on=['id', col_aut])
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# df = pd.merge(df,r_id, on=['id', col_aut]) \
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# .drop(columns=[col_aut])
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# return df
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# def _merge_relation(self, df, table, schema, id=None, left_id=None,right_id=None):
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# con = self.con
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# if id:
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# params = {id: df[id].tolist() }
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# elif left_id and right_id:
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# params = {right_id: df[left_id].tolist() }
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# mrg = _get_table(con, schema, table, params_col=params)
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# if table == 'r_sites_auteur' or table == 'r_geomsites_auteur':
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# mrg = mrg[[right_id,'id_auteur']].groupby(
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# [right_id])['id_auteur'].apply(lambda x: ' & '.join(x.astype(str)))
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# mrg = pd.DataFrame(data=mrg)
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# if id:
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# df = pd.merge(df,mrg, how='left', on=id)
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# elif left_id and right_id:
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# df = pd.merge(df,mrg, how='left', left_on=left_id, right_on=right_id)
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# return df
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# def get_sitesInfos(self, ids=None, nom=None, columns=None, with_nameOrga=False, details=False, params_col={}):
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# drop = []
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# table = 'sites'
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# df = _get_table(self.con, self.schema, table, ids=ids, nom=nom, cols=columns, params_col=params_col)
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# # récupération des auteurs
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# if 'id_auteur' in df.columns:
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# df.drop(columns='id_auteur', inplace=True)
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# df = _merge_relation(df=df,table='r_sites_auteur',schema=self.schema, left_id='id',right_id='id_site')
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# df = _merge_author(df=df, col_aut='id_auteur', orga=with_nameOrga)
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# # merge type_site
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# if 'id_type_site' in df.columns:
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# df = pd.merge(df, self.typ_site, how='left', left_on='id_type_site', right_on='id', suffixes=('','_y') ) \
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# .drop(columns=['id_type_site', 'id_y']) \
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# .rename(columns={'nom_y': 'type_site', 'description': 'desc_type_site'})
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# drop += ['desc_type_site']
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# # merge typo_sdage
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# if 'id_typo_sdage' in df.columns:
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# df = pd.merge(df, self.typo_sdage, how='left', left_on='id_typo_sdage', right_on='id', suffixes=('','_y') ) \
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# .drop(columns=['id_typo_sdage', 'id_y']) \
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# .rename(columns={'nom_y': 'typo_sdage', 'description': 'desc_typo_sdage'})
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# drop += ['desc_typo_sdage']
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# # merge type_milieu
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# if 'id_type_milieu' in df.columns:
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# df = pd.merge(df, self.typ_milieux, how='left', left_on='id_type_milieu', right_on='id', suffixes=('','_y') ) \
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# .drop(columns=['id_type_milieu', 'id_y']) \
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# .rename(columns={'nom_y': 'type_milieu', 'description': 'desc_type_milieu', 'nom_court': 'nom_court_milieu'})
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# drop += ['desc_type_milieu', 'nom_court_milieu']
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# if not details:
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# df.drop(columns=drop, inplace=True)
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# return df.sort_values('id')
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# def get_sitesGeom(self, id_site=None, nom_site=None, columns=None, last_update=False, with_nameOrga=False, params_col={}):
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# # from shapely.wkb import loads
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# # import geopandas as gpd # set_geometry
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# if columns:
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# if not isinstance(columns, list): columns = [columns]
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# if 'id' not in columns: columns.insert(0,'id')
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# if 'id_site' not in columns: columns.insert(1,'id_site')
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# if 'geom' not in columns: columns.insert(2,'geom')
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# table = 'sites'
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# df = _get_table(self.con, self.schema, table, ids=id_site, nom=nom_site, cols='id', params_col=params_col)
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# idSite = df.id.tolist()
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# table = 'r_sites_geom'
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# df = _get_table(self.con, self.schema, table, params_col={'id_site':idSite}, cols=columns)
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# if last_update:
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# df.drop_duplicates(subset=['id_site'], keep='last', inplace=True)
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# df.reset_index(inplace=True, drop=True)
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# # df = _set_geom(df)
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# # df['geom'] = [(loads(geom, hex=True)) for geom in df['geom']]
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# # df = df.set_geometry('geom', crs='EPSG:2154')
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# # merge auteur
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# if 'id_auteur' in df.columns:
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# df.drop(columns='id_auteur', inplace=True)
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# df = _merge_relation(df=df,table='r_geomsites_auteur',schema=self.schema, left_id='id',right_id='id_geom_site')
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# df = _merge_author(df=df, col_aut='id_auteur', orga=with_nameOrga)
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# return df
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#####################################
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### schema zh ###
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#####################################
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class zh():
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def __init__(self):
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from .params import con
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from .tools import _get_relation_tab
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self.schema = 'zones_humides'
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self.con = con
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self.typ_milieux = _get_typ_milieux(nom='Tourbières et marais')
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self.id_milieux = self.typ_milieux.id.values[0]
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self._get_relation_tab = _get_relation_tab
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self.lst_tab = con.dialect.get_table_names(con,schema=self.schema)
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self.columns_rSiteFcts = con.dialect.get_columns(con,schema=self.schema,table_name='r_site_fctecosociopatri')
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self.columns_r_SiteCon = con.dialect.get_columns(con,schema=self.schema,table_name='r_site_type_connect')
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self.columns_rSiteCritDelim = con.dialect.get_columns(con,schema=self.schema,table_name='r_site_critdelim')
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self.columns_r_SiteHabs = con.dialect.get_columns(con,schema=self.schema,table_name='r_site_habitat')
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self.columns_rSiteRegHyd = con.dialect.get_columns(con,schema=self.schema,table_name='r_site_reghydro')
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self.columns_r_SiteSub = con.dialect.get_columns(con,schema=self.schema,table_name='r_site_sub')
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self.columns_r_SiteUsgPrss = con.dialect.get_columns(con,schema=self.schema,table_name='r_site_usageprocess')
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def _get_param(self, param_table, type_table=None, type_court=True):
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if type_table:
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typ = _get_table(self.con, self.schema, table=type_table)
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par = _get_table(self.con, self.schema, table=param_table, params_col={'id_type':typ.id.tolist()})
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df = pd.merge(par, typ, left_on='id_type', right_on='id', how='left', suffixes=(None, '_typ')) \
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.drop(columns=['id_type','id_typ'])
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if 'description_typ' in df.columns: del df['description_typ']
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if type_court: df = df.drop(columns=['nom_typ']).rename(columns={'nom_court_typ':'type'})
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else : df = df.drop(columns=['nom_court_typ'],errors='ignore').rename(columns={'nom_typ':'type'})
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df = df.set_index(['id', 'type']).reset_index()
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else:
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df = _get_table(self.con, self.schema, table=param_table)
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return df
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# def _get_relation_tab(self, tab, id_site=None, nom_site=None, last_update=False, geom=False,params_col={}):
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# table = 'sites'
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# dfSG = get_sitesGeom(columns='date', id_site=id_site, nom_site=nom_site, last_update=last_update,params_col=params_col)
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# if not geom and not dfSG.empty:
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# dfSG.drop('geom',1,inplace=True)
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# ids = dfSG.id.tolist()
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# table = tab
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# if ids :
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# df = _get_table(self.con, self.schema, table, params_col={'id_geom_site':ids})
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# # if not df.empty:
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# df = pd.merge(dfSG,df, how='left', left_on='id', right_on='id_geom_site', suffixes=('_x', None)) \
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# .drop(['id_x','id_geom_site'],1) \
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# .set_index('id').reset_index()
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# return df
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# else:
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# print('PAS de géometries de sites sélectionnées ...')
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def get_delim(self, id_site=None, nom_site=None, last_update=True, geom=False,
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nom_type_court=True,statut='actif'):
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table = 'r_site_critdelim'
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df = self._get_relation_tab(
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schema=self.schema,tab=table,id_site=id_site,nom_site=nom_site,last_update=last_update,geom=geom,
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params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
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dic = self._get_param(type_table='type_param_delim_fct', param_table='param_delim_fct', type_court=nom_type_court)
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if not df.empty:
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df = _get_relation_autor(df, relation_tab='r_rsitedelim_auteur', schema=self.schema,
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id_df='id', id_relation='id_sitedelim', id_rela_auth='id_auteur' )
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df = pd.merge(df,dic, how='left', left_on='id_crit_delim', right_on='id', suffixes=(None,'_y')) \
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.drop(['id_y','id_crit_delim'],1) \
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.rename(columns={'description_y':'desc_param', 'nom_court':'nom_court_crit','nom':'nom_crit'}) \
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.sort_values('id_site')
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if df.nom_court_crit.isnull().sum() == df.shape[0] : del df['nom_court_crit']
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# typ = df.type.unique()
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# x = {}
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# for t in typ:
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# x[t] = df[df.type == t]
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# x[t] = x[t].rename(columns={'nom': t}) \
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# .reset_index(drop=True)
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return df
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def get_fct(self, id_site=None, nom_site=None, last_update=True, geom=False, nom_type_court=True,statut='actif'):
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table = 'r_site_fctecosociopatri'
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df = self._get_relation_tab(schema=self.schema,tab=table,id_site=id_site,nom_site=nom_site,last_update=last_update,geom=geom,
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params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
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dic = self._get_param(type_table='type_param_fct', param_table='param_fct_eco_socio_patri', type_court=nom_type_court)
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if not df.empty:
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df = _get_relation_autor(df, relation_tab='r_rsitefct_auteur', schema=self.schema,
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id_df='id', id_relation='id_sitefct', id_rela_auth='id_auteur' )
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df = pd.merge(df,dic, how='left', left_on='id_fct', right_on='id', suffixes=(None,'_y')) \
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.drop(['id_y','id_fct'],1) \
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.rename(columns={'description_y':'desc_param', 'nom_court':'nom_court_fct','nom':'nom_fct'}) \
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.sort_values('id_site')
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if df.nom_court_fct.isnull().sum() == df.shape[0] : del df['nom_court_fct']
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return df
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def get_connex(self, id_site=None, nom_site=None, last_update=True, geom=False,statut='actif'):
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table = 'r_site_type_connect'
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df = self._get_relation_tab(schema=self.schema,tab=table,id_site=id_site,nom_site=nom_site,last_update=last_update,geom=geom,
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params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
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dic = self._get_param(param_table='param_type_connect')
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if not df.empty:
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df = _get_relation_autor(df, relation_tab='r_rsiteconnect_auteur', schema=self.schema,
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id_df='id', id_relation='id_siteconnect', id_rela_auth='id_auteur' )
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df = pd.merge(df,dic, how='left', left_on='id_param_connect', right_on='id', suffixes=(None,'_y')) \
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.drop(['id_y','id_param_connect'],1) \
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.rename(columns={'description_y':'desc_param', 'nom':'connexion'}) \
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.sort_values('id_site')
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return df
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def get_sub(self, id_site=None, nom_site=None, last_update=True, geom=False,statut='actif'):
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table = 'r_site_sub'
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df = self._get_relation_tab(schema=self.schema,tab=table,id_site=id_site,nom_site=nom_site,last_update=last_update,geom=geom,
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params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
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dic = self._get_param(type_table='type_param_sub', param_table='param_sub', type_court=False)
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d1 = dic[dic.type == 'Submersion étendue']
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d2 = dic[dic.type == 'Submersion fréquente']
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if not df.empty:
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df = _get_relation_autor(df, relation_tab='r_rsitesub_auteur', schema=self.schema,
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id_df='id', id_relation='id_sitesub', id_rela_auth='id_auteur' )
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df = pd.merge(df,d1, how='left', left_on='id_etendsub', right_on='id', suffixes=(None,'_y')) \
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.drop(['id_y','id_etendsub', 'type'],1) \
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.rename(columns={'description':'desc_param_etend', 'nom':'Submersion étendue'})
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df = pd.merge(df,d2, how='left', left_on='id_freqsub', right_on='id', suffixes=(None,'_y')) \
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.drop(['id_y','id_freqsub', 'type'],1) \
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.rename(columns={'description':'desc_param_freq', 'nom':'Submersion fréquente'}) \
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.sort_values('id_site')
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df.rename(columns={'id_origsub': 'origine_sub'}, inplace=True)
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if df['desc_param_etend'].isnull().sum() == df.shape[0] : del df['desc_param_etend']
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if df['desc_param_freq'].isnull().sum() == df.shape[0] : del df['desc_param_freq']
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return df
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||
|
||
def get_usageprocess(self, id_site=None, nom_site=None, last_update=True, geom=False,statut='actif'):
|
||
|
||
table = 'r_site_usageprocess'
|
||
df = self._get_relation_tab(schema=self.schema,tab=table,id_site=id_site,nom_site=nom_site,last_update=last_update,geom=geom,
|
||
params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
|
||
dic1 = self._get_param(param_table='param_activ_hum')
|
||
dic2 = self._get_param(param_table='param_position')
|
||
dic3 = self._get_param(param_table='param_impact')
|
||
|
||
if not df.empty:
|
||
df = _get_relation_autor(df, relation_tab='r_rsiteusage_auteur', schema=self.schema,
|
||
id_df='id', id_relation='id_siteusage', id_rela_auth='id_auteur' )
|
||
|
||
df = pd.merge(df,dic1, how='left', left_on='id_activ_hum', right_on='id', suffixes=(None,'_y')) \
|
||
.drop(['id_y','id_activ_hum'],1) \
|
||
.rename(columns={'description':'desc_param_usag', 'nom':'activite_hum'})
|
||
df = pd.merge(df,dic2, how='left', left_on='id_position', right_on='id', suffixes=(None,'_y')) \
|
||
.drop(['id_y','id_position'],1) \
|
||
.rename(columns={'description':'desc_param_pos', 'nom':'position'}) \
|
||
.sort_values('id_site')
|
||
df = pd.merge(df,dic3, how='left', left_on='id_impact', right_on='id', suffixes=(None,'_y')) \
|
||
.drop(['id_y','id_impact'],1) \
|
||
.rename(columns={'description':'desc_param_imp', 'nom':'impact'}) \
|
||
.sort_values('id_site')
|
||
|
||
return df
|
||
|
||
|
||
def _get_r_toponymie(self, ids=None):
|
||
table = 'r_toponymie'
|
||
df = _get_table(self.con, self.schema, table=table, ids=ids)
|
||
dic1 = self._get_param(param_table='liste_table_topohydro')
|
||
if not df.empty:
|
||
df = pd.merge(df,dic1, how='left', left_on='id_orig', right_on='id', suffixes=(None,'_y')) \
|
||
.drop(['id_y','id_orig'],1)
|
||
n_tab = df.nom_table.unique()
|
||
for tab in n_tab:
|
||
iids = df.loc[df.nom_table == tab, 'id_topo'].to_list()
|
||
if tab == 'orig_hydro': dic = _get_table(self.con, self.schema, table='orig_hydro', ids=iids)
|
||
if tab == 'troncon_hydro': dic = ref_hydro.get_troncon(cols=['id','nom'], ids=iids)
|
||
df.loc[df.nom_table == tab, 'id_topo'] = df.loc[df.nom_table == tab, 'id_topo'].replace(dic.id.to_list(),dic.nom.to_list())
|
||
if tab == 'troncon_hydro': df = pd.merge(df, dic, how='left', left_on='id_topo', right_on='nom', suffixes=(None,'_y')) \
|
||
.drop(columns=['id_y', 'nom'])
|
||
df.rename(columns={'id_topo':'toponymie'})
|
||
|
||
return df
|
||
|
||
|
||
def get_regHydro(self, id_site=None, nom_site=None, last_update=True, geom=False,statut='actif'):
|
||
|
||
table = 'r_site_reghydro'
|
||
df = self._get_relation_tab(schema=self.schema,tab=table,id_site=id_site,nom_site=nom_site,last_update=last_update,geom=geom,
|
||
params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
|
||
dic1 = self._get_param(param_table='param_reg_hydro')
|
||
dic2 = self._get_param(param_table='param_permanence')
|
||
|
||
if not df.empty:
|
||
df = _get_relation_autor(df, relation_tab='r_rsitehydro_auteur', schema=self.schema,
|
||
id_df='id', id_relation='id_sitehydro', id_rela_auth='id_auteur' )
|
||
|
||
# dic3 = self._get_r_toponymie(ids=df.rmq_toponymie.unique().tolist())
|
||
df.in_out = df.in_out.replace([True,False],['entree','sortie'])
|
||
df = pd.merge(df,dic1, how='left', left_on='id_reg_hydro', right_on='id', suffixes=(None,'_y')) \
|
||
.drop(['id_y','id_reg_hydro'],1) \
|
||
.rename(columns={'description':'desc_param_regHydri', 'nom':'regime_hydri'})
|
||
|
||
if df.id_permanence.isna().all() :
|
||
df.rename(columns={'id_permanence':'permanence'}, inplace=True)
|
||
df['desc_param_perm'] = None
|
||
else:
|
||
df = pd.merge(df,dic2, how='left', left_on='id_permanence', right_on='id', suffixes=(None,'_y')) \
|
||
.drop(['id_y','id_permanence'],1) \
|
||
.rename(columns={'description':'desc_param_perm', 'nom':'permanence'})
|
||
|
||
# df = pd.merge(df,dic3, left_on='rmq_toponymie', right_on='id', suffixes=(None,'_y')) \
|
||
# .drop(['id_y','rmq_toponymie'],1) \
|
||
# .rename(columns={'description':'desc_topo'}) \
|
||
# .sort_values('id_site')
|
||
|
||
return df
|
||
|
||
|
||
def get_habitat(self, id_site=None, nom_site=None, last_update=True, geom=False,statut='actif'):
|
||
|
||
table = 'r_site_habitat'
|
||
df = self._get_relation_tab(schema=self.schema,tab=table,id_site=id_site,nom_site=nom_site,last_update=last_update,geom=geom,
|
||
params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
|
||
|
||
if not df.empty:
|
||
df = _get_relation_autor(df, relation_tab='r_rsitehab_auteur', schema=self.schema,
|
||
id_df='id', id_relation='id_sitehab', id_rela_auth='id_auteur' )
|
||
|
||
ids = df[~df.id_cb.isna()].id_cb.unique().tolist()
|
||
dic = ref_hab().get_CB(ids=ids,cols=['id','lb_hab_fr'])
|
||
df = pd.merge(df,dic, how='left', left_on='id_cb', right_on='id', suffixes=(None,'_y')) \
|
||
.drop(['id_y'], 1) \
|
||
.rename(columns={'id_cb':'code_cb'}) \
|
||
.sort_values('id_site')
|
||
|
||
return df
|
||
|
||
|
||
def get_sitesInfos(self, id_site=None, nom_site=None, columns=None, with_nameOrga=False, statut='actif'):
|
||
from .sites.sites import get_sitesInfos
|
||
|
||
df = get_sitesInfos(ids=id_site, nom=nom_site, columns=columns, with_nameOrga=with_nameOrga,
|
||
params_col={'id_type_milieu':self.id_milieux.astype(str)}, statut=statut)
|
||
|
||
return df
|
||
|
||
|
||
def get_sitesGeom(self, id_site=None, nom_site=None, columns=None, last_update=True, with_nameOrga=False,
|
||
params_col={}, statut='actif'):
|
||
from .sites.sites import get_sitesGeom
|
||
|
||
if params_col:
|
||
params_col = {**params_col, 'id_type_milieu':self.id_milieux.astype(str) }
|
||
|
||
df = get_sitesGeom(id_site=id_site, nom_site=nom_site, columns=columns,
|
||
with_nameOrga=with_nameOrga,last_update=last_update,
|
||
params_col=params_col , statut=statut)
|
||
|
||
drop_cols = ['link_pdf', 'rmq_fct_majeur',
|
||
'rmq_interet_patri', 'rmq_bilan_menace', 'rmq_orient_act',
|
||
'rmq_usage_process']
|
||
cols = df.columns
|
||
c = cols[cols.isin(drop_cols)]
|
||
if not c.empty:
|
||
df.drop(columns=c, inplace=True)
|
||
|
||
return df
|
||
|
||
|
||
def get_evaluation(self, id_site=None, nom_site=None, columns=None, last_update=True, with_nameOrga=False,
|
||
params_col={}, statut='actif'):
|
||
from .sites.sites import get_sitesGeom
|
||
|
||
if params_col:
|
||
params_col = {**params_col, 'id_type_milieu':self.id_milieux.astype(str) }
|
||
|
||
df = get_sitesGeom(id_site=id_site, nom_site=nom_site, columns=columns,
|
||
with_nameOrga=with_nameOrga,last_update=last_update,
|
||
params_col=params_col, statut=statut)
|
||
|
||
df.drop(columns=['geom'], inplace=True)
|
||
|
||
return df
|
||
|
||
|
||
def get_bilan(self, code_site=None, nom_site=None, statut='actif',last_update=True):
|
||
'''
|
||
:code_site: list,str. Code du site de la zh.
|
||
:nom_site: list,str. Nom du site de la zh.
|
||
'''
|
||
info = self.get_sitesInfos(id_site=code_site, nom_site=nom_site,statut=statut)
|
||
CB = self.get_habitat(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
delim = self.get_delim(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
desc = self.get_usageprocess(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
rghyd = self.get_regHydro(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
subm = self.get_sub(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
conn = self.get_connex(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
fct = self.get_fct(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
evall = self.get_evaluation(id_site=code_site, nom_site=nom_site,last_update=last_update,statut=statut)
|
||
|
||
print('subm : {}'.format(subm))
|
||
print('conn : {}'.format(conn))
|
||
if subm.empty:
|
||
sub_con = conn.rename(columns={
|
||
'description': 'desc_connex',
|
||
'valid': 'valid_cnx',
|
||
})
|
||
elif conn.empty:
|
||
sub_con = subm.rename(columns={'valid': 'valid_sub',})
|
||
else:
|
||
sub_con = pd.merge(subm, conn, how='outer', on=['id', 'id_site', 'date_geom','auteur_geom']) \
|
||
.rename(columns={
|
||
'description': 'desc_connex',
|
||
'valid_x': 'valid_sub',
|
||
'valid_y': 'valid_cnx',
|
||
})
|
||
fctmt = {
|
||
'entree_eau': rghyd[rghyd.in_out == 'entree'].drop(columns=['in_out']),
|
||
'sortie_eau': rghyd[rghyd.in_out == 'sortie'].drop(columns=['in_out']),
|
||
'sub_connex': sub_con,
|
||
}
|
||
lst_df = {
|
||
'infos':info,
|
||
'corine_biotope': CB,
|
||
'delimitation': delim,
|
||
'description': desc,
|
||
'fonctionnement': fctmt,
|
||
'fonction': fct,
|
||
'evaluation': evall}
|
||
for key in lst_df:
|
||
if isinstance(lst_df[key], pd.DataFrame): lst_df[key].name = key
|
||
if isinstance(lst_df[key], dict):
|
||
for d in lst_df[key]:
|
||
lst_df[key][d].name = d
|
||
lst_df[key]['title'] = key
|
||
return lst_df
|
||
|
||
#####################################
|
||
### schema ref_habitats ###
|
||
#####################################
|
||
class ref_hab:
|
||
def __init__(self):
|
||
from .params import con
|
||
self.schema = 'ref_habitats'
|
||
self.con = con
|
||
|
||
def get_CB(self, ids=None, cols=None, params_col={}):
|
||
table = 'corine_biotope'
|
||
df = _get_table(self.con, self.schema, table=table, ids=ids, cols=cols, params_col=params_col)
|
||
return df
|
||
|
||
|
||
#####################################
|
||
### schema ref_hydro ###
|
||
#####################################
|
||
class ref_hydro:
|
||
def __init__(self):
|
||
from .params import con
|
||
self.schema = 'ref_hydro'
|
||
self.con = con
|
||
|
||
def get_troncon(self, ids=None, cols=None, params_col={}):
|
||
|
||
table = 'troncon_hydro'
|
||
df = _get_table(self.con, self.schema, table=table, ids=ids, cols=cols, params_col=params_col)
|
||
# df = _set_geom(df)
|
||
|
||
return df
|
||
|
||
def get_coursEau(self, ids=None, cols=None, params_col={}):
|
||
|
||
table = 'cours_eau'
|
||
df = _get_table(self.con, self.schema, table=table, ids=ids, cols=cols, params_col=params_col)
|
||
# df = _set_geom(df)
|
||
|
||
return df
|
||
|
||
def get_masseEau(self, ids=None, cols=None, params_col={}):
|
||
|
||
table = 'masse_eau'
|
||
df = _get_table(self.con, self.schema, table=table, ids=ids, cols=cols, params_col=params_col)
|
||
# df = _set_geom(df)
|
||
|
||
return df
|
||
|
||
def get_planEau(self, ids=None, cols=None, params_col={}):
|
||
|
||
table = 'plan_eau'
|
||
df = _get_table(self.con, self.schema, table=table, ids=ids, cols=cols, params_col=params_col)
|
||
# df = _set_geom(df)
|
||
|
||
return df
|
||
|
||
def get_ssbv(self, ids=None, cols=None, params_col={}):
|
||
|
||
table = 'ssbv'
|
||
df = _get_table(self.con, self.schema, table=table, ids=ids, cols=cols, params_col=params_col)
|
||
# df = _set_geom(df)
|
||
|
||
return df
|
||
|
||
|
||
|
||
|
||
|
||
#####################################
|
||
### Update ###
|
||
#####################################
|
||
def update_to_sql(df, con, table_name, schema_name, key_name):
|
||
a = []
|
||
b = []
|
||
table = table_name
|
||
schema = schema_name
|
||
primary_key = key_name
|
||
if isinstance(primary_key, str): primary_key = [primary_key]
|
||
for col in df.columns:
|
||
if col in primary_key:
|
||
b.append("t.{col}=f.{col}".format(col=col))
|
||
else:
|
||
a.append("{col}=t.{col}".format(col=col))
|
||
df.to_sql(
|
||
name = 'temp_table',
|
||
con = con,
|
||
schema = schema,
|
||
if_exists = 'replace',
|
||
index = False,
|
||
method = 'multi'
|
||
)
|
||
update_stmt_1 = "UPDATE {sch}.{final_table} f".format(sch=schema,final_table=table)
|
||
update_stmt_2 = " FROM {sch}.temp_table t".format(sch=schema)
|
||
update_stmt_6 = " WHERE %s"%' AND '.join(b)
|
||
update_stmt_3 = " SET "
|
||
update_stmt_4 = ", ".join(a)
|
||
update_stmt_5 = update_stmt_1 + update_stmt_3 + update_stmt_4 + update_stmt_2 + update_stmt_6 + ";"
|
||
drop_stmt = "DROP TABLE {sch}.temp_table ;".format(sch=schema)
|
||
with con.begin() as cnx:
|
||
cnx.execute(update_stmt_5)
|
||
cnx.execute(drop_stmt)
|
||
return print('END update')
|
||
|
||
|
||
# [SQL: INSERT INTO zones_humides.r_site_reghydro (id, id_geom_site, id_reg_hydro, id_permanence, rmq_toponymie, in_out)
|
||
# VALUES (%(id)s, %(id_geom_site)s, %(id_reg_hydro)s, %(id_permanence)s, %(rmq_toponymie)s, %(in_out)s)]
|
||
# [parameters: ({'id': 0, 'id_geom_site': 5, 'id_reg_hydro': '0', 'id_permanence': '1', 'rmq_toponymie': '', 'in_out': True},
|
||
# {'id': 1, 'id_geom_site': 5, 'id_reg_hydro': '1', 'id_permanence': '1', 'rmq_toponymie': '', 'in_out': False},
|
||
# {'id': 2, 'id_geom_site': 6, 'id_reg_hydro': '0', 'id_permanence': '1', 'rmq_toponymie': '', 'in_out': True},
|
||
# {'id': 3, 'id_geom_site': 6, 'id_reg_hydro': '1', 'id_permanence': '1', 'rmq_toponymie': '', 'in_out': False},
|
||
# {'id': 4, 'id_geom_site': 7, 'id_reg_hydro': '2', 'id_permanence': '2', 'rmq_toponymie': 'plusieurs petites sources dans versant', 'in_out': True},
|
||
# {'id': 5, 'id_geom_site': 7, 'id_reg_hydro': '1', 'id_permanence': '2', 'rmq_toponymie': 'longe la route D209a', 'in_out': False},
|
||
# {'id': 6, 'id_geom_site': 8, 'id_reg_hydro': '0', 'id_permanence': '2', 'rmq_toponymie': '', 'in_out': True},
|
||
# {'id': 7, 'id_geom_site': 8, 'id_reg_hydro': '3', 'id_permanence': None, 'rmq_toponymie': '', 'in_out': False}
|
||
# ... displaying 10 of 5779 total bound parameter sets ...
|
||
# {'id': 5777, 'id_geom_site': 1951, 'id_reg_hydro': '0', 'id_permanence': None, 'rmq_toponymie': '', 'in_out': True},
|
||
# {'id': 5778, 'id_geom_site': 1951, 'id_reg_hydro': '3', 'id_permanence': None, 'rmq_toponymie': '', 'in_out': False})]
|