264 lines
8.3 KiB
Python
Executable File

#!/usr/bin/env python3
# -*- coding: UTF-8 -*-
import geopandas as gpd
from geoalchemy2 import Geometry
def _calc_recouvrmt(df1,df2,how='inner'):
'''
Calcule le recouvrement de df2 sur df1
pour chaque géométrie de df1:
Parameters
----------
df1 : GeoDataFrame.
df2 : GeoDataFrame.
'''
iddf1 = df1.columns[0]
iddf2 = df2.columns[0]
# Jointure spaciale
tmp = gpd.sjoin(
df1,
df2[['geom']],
predicate = 'intersects',
how = how)
tmp.dropna(subset=['index_right'],inplace=True)
tmp.index_right = tmp.index_right.astype(int)
tmp.reset_index(inplace=True)
tmp = tmp.join(
df2[['geom',iddf2]].rename(columns={'geom': 'right_geom'}),
on=['index_right'], how='left')
tmp2 = tmp[['index_right','right_geom',iddf2]].copy() \
.rename(columns={'right_geom': 'geom'}) \
.set_geometry('geom')
tmp1 = tmp[[iddf1,'geom']].copy() \
.set_geometry('geom')
if not tmp1.geom.values.is_valid.all():
tmp1.loc[~tmp1.geom.values.is_valid,'geom'] = tmp1.loc[~tmp1.geom.values.is_valid,'geom'].buffer(0)
if not tmp2.geom.values.is_valid.all():
tmp2.loc[~tmp2.geom.values.is_valid,'geom'] = tmp2.loc[~tmp2.geom.values.is_valid,'geom'].buffer(0)
tmp['perc_rcvmt'] = (tmp1.intersection(tmp2).area/tmp1.area)*100
return tmp[[iddf1,iddf2,'perc_rcvmt']]
def _cor_zh_area(con,tzh_code,typ,cover=False):
"""
@tzh : pd.Serie. Série de valeurs
correspondants à la colonne pr_zh.t_zh."code".
@typ : str. COM, DEP, ref_geo
"""
from math import ceil
table = 'cor_zh_area'
sqltzh = """
SELECT zh.id_zh, zh.geom FROM pr_zh.t_zh zh WHERE zh."code" in {tzh_code}
""".format(tzh_code=tuple(tzh_code))
tzh = gpd.read_postgis(sqltzh,con,crs=4326)
if tzh.crs.srs=='epsg:4326':
tzh.to_crs(2154,inplace=True)
if typ == 'COM':
cd2 = ' AND l."enable";'
else: cd2 = ';'
# sql = '''
# SELECT l.id_area,l.geom,zh.id_zh
# FROM ref_geo.l_areas l
# JOIN ref_geo.bib_areas_types bib USING (id_type),
# pr_zh.t_zh zh
# WHERE zh."code" in {tzh_code}
# AND bib.type_code='{typ}'
# AND ST_INTERSECTS( ST_SetSRID(l.geom,2154), ST_MakeValid(ST_Transform(ST_SetSRID(zh.geom,4326),2154)) )
# AND (l.id_area,zh.id_zh) NOT IN (SELECT id_area,id_zh FROM pr_zh.cor_zh_area)
# {cd2}
# '''.format(tzh_code=tuple(tzh_code),typ=typ,cd2=cd2)
# # larea = gpd.pd.read_sql_query(sql,con)
# larea = gpd.read_postgis(sql,con)
sqllarea = """
SELECT l.id_area, l.geom FROM ref_geo.l_areas l
JOIN ref_geo.bib_areas_types bib USING (id_type)
WHERE bib.type_code='{typ}' and l."enable"
""".format(typ=typ)
larea = gpd.read_postgis(sqllarea,con,crs=2154)
df = _calc_recouvrmt(larea,tzh).rename(columns={'perc_rcvmt':'cover'})
if cover:
df['cover'] = [ceil(x) for x in df.cover]
else :
df.drop(columns=['cover'],inplace=True)
if not df.empty:
df.to_sql(
name=table, con=con, schema='pr_zh',
if_exists='append', index=False
)
print('INSERT %i correspondances'%df.shape[0])
else:
sql = '''
SELECT l.id_area
FROM ref_geo.l_areas l
JOIN ref_geo.bib_areas_types bib USING (id_type)
WHERE bib.type_code='{typ}'
'''.format(typ=typ)
res = gpd.pd.read_sql_query(sql,con)
if not res.empty:
print('AUCUNE nouvelles correspondances identifiées')
else :
print('AUCUNE geometrie dans la table `ref_geo.l_areas` pour le `type_code` %s'%typ)
def _cor_zh_(con,tzh_code,typ):
"""
@tzh : pd.Serie. Série de valeurs
correspondants à la colonne pr_zh.t_zh."code".
@typ : str. [hydro,rb]
"""
typ = typ.lower()
table = 'cor_zh_%s'%typ
tab_typ = 't_hydro_area' if typ == 'hydro' else 't_river_basin'
id_typ = 'id_hydro' if typ == 'hydro' else 'id_rb'
sql = '''
SELECT h.{id_typ},zh.id_zh
FROM pr_zh.{tab_typ} h, pr_zh.t_zh zh
WHERE zh."code" in {tzh_code}
AND ST_INTERSECTS( ST_SetSRID(h.geom,4326),ST_MakeValid(ST_SetSRID(zh.geom,4326)))
AND (h.{id_typ},zh.id_zh) NOT IN (SELECT {id_typ},id_zh FROM pr_zh.{tab_to})
;'''.format(
tzh_code = tuple(tzh_code),
id_typ = id_typ,
tab_typ = tab_typ,
tab_to = table)
df = gpd.pd.read_sql_query(sql,con)
if not df.empty:
df.to_sql(
name=table, con=con, schema='pr_zh',
if_exists='append', index=False
)
print('INSERT %i correspondances'%df.shape[0])
else:
print('AUCUNE nouvelles correspondances identifiées')
def get_id_t_zh(con,code=None):
"""@code : str, list, Serie, Index. Code à 12 characters maximum de la zone humide.
"""
sql = "SELECT id_zh,code FROM pr_zh.t_zh" # "SELECT id_zh,zh_uuid,code FROM pr_zh.t_zh"
if isinstance(code,str):
sql += " WHERE code='%s'"%code
elif isinstance(code,list) or isinstance(code,gpd.pd.Series) or isinstance(code,gpd.pd.Index):
sql += " WHERE code IN {lst_code}".format(lst_code=str(tuple(code)))
return gpd.pd.read_sql_query(sql,con)
def to_tzh(df,con):
table = 't_zh'
if isinstance(df,gpd.GeoDataFrame):
epsg = df.crs.srs.split(':')[1]
df = df.to_wkt()
df.to_sql(
name=table, con=con, schema='pr_zh',
if_exists='append', index=False,
dtype={
'geom': Geometry(srid=epsg)
# 'id_lim_list':uuid.SafeUUID
}
)
if isinstance(df,gpd.pd.DataFrame):
df.geom = gpd.GeoSeries.from_wkt(df.geom)
df = df.set_geometry('geom',crs=epsg)
_cor_zh_area(con,tzh_code=df.code,typ='ZNIEFF1')
print('INSERT cor_zh_area ZNIEFF1 OK !')
_cor_zh_area(con,tzh_code=df.code,typ='ZNIEFF2')
print('INSERT cor_zh_area ZNIEFF2 OK !')
_cor_zh_area(con,tzh_code=df.code,typ='DEP')
print('INSERT cor_zh_area DEP OK !')
_cor_zh_area(con,tzh_code=df.code,typ='COM',cover=True)
print('INSERT cor_zh_area COM OK !')
_cor_zh_area(con,tzh_code=df.code,typ='ZPS')
print('INSERT cor_zh_area ZPS OK !')
_cor_zh_area(con,tzh_code=df.code,typ='SIC')
print('INSERT cor_zh_area SIC OK !')
_cor_zh_area(con,tzh_code=df.code,typ='SRAM')
print('INSERT cor_zh_area SRAM OK !')
_cor_zh_area(con,tzh_code=df.code,typ='ZICO')
print('INSERT cor_zh_area ZICO OK !')
_cor_zh_(con,tzh_code=df.code,typ='hydro')
print('INSERT cor_zh_hydro OK !')
_cor_zh_(con,tzh_code=df.code,typ='rb')
print('INSERT cor_zh_rb OK !')
def to_cor_(con,df,table):
df.to_sql(
name=table,con=con,schema='pr_zh',if_exists='append',index=False
)
def to_t_(con,df,table):
res = gpd.pd.merge(df,get_id_t_zh(con,df.SITE_COD),left_on='SITE_COD',right_on='code')\
.drop(columns=['SITE_COD','code'])
res.to_sql(
name=table,con=con,schema='pr_zh',if_exists='append',index=False
)
def add_bib_cb(df,con,humidity=None,is_ch=None):
"""
@df : pd.Dataframe. Tableau à 3 colonnes |lb_code|humidity|is_ch|.
@con : engine. Connexion PostgreSQL à la base de données cible.
@humidity : str. Caractère d'humidité a attribuer par défault
à chaque lb_code du tableau où la colonne est Null.
Défaut : None (désactivé)
Liste : P (Potentiellement), H (Humide).
@is_ch : bool. Caractère de présence/absence de carto d'habitat
à attribuer par défault à chaque lb_code du tableau où la colonne est Null.
Défaut : None (désactivé)
Liste : True (existe), False (n'existe pas).
"""
table = 'bib_cb'
if humidity is not None:
df.loc[df.humidity.isna(),'humidity'] = humidity.upper()
if is_ch is not None:
df.loc[df.is_ch.isna(),'is_ch'] = is_ch
bib_cb = gpd.pd.read_sql_table(table,con,'pr_zh')
df = df[~df.lb_code.isin(bib_cb.lb_code)]
if df.empty:
print('NO news data to insert !')
else:
df.to_sql(
name=table,con=con,schema='pr_zh',if_exists='append',index=False
)
print('INSERT %s news rows !'%df.shape[0])
if __name__ == '__main__':
from ..MEDWET2Geonat import get_t_zh
zh,_cor_lim_list = get_t_zh()