221 lines
7.0 KiB
Python
221 lines
7.0 KiB
Python
#!/usr/bin/env python3
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# -*- coding: UTF-8 -*-
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#Nom : : ps.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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from pandas.core.reshape.merge import merge
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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 .params import con
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from .tools import _get_relation_tab,_set_geom
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schema = 'ps'
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milieu = 'Pelouses sèches'
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def get_param():
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from .tools import _get_param
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return _get_param(schema=schema,param_table='param',type_table='type_param',type_court=False)
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def get_sitesInfos(id_site=None, nom_site=None, columns=None, with_nameOrga=False, statut='actif'):
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from .sites.sites import get_sitesInfos
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df = get_sitesInfos(
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ids=id_site, nom=nom_site, columns=columns,
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with_nameOrga=with_nameOrga, milieu=milieu, statut=statut)
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df.drop(columns=['typo_sdage'], inplace=True)
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return df
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def get_listLegendePS():
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from .params import con
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return _get_table(con,schema,'param_legende')
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def get_sitesGeom(id_site=None, nom_site=None, columns=None, last_update=False, with_nameOrga=False,
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params_col={}, statut='actif'):
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from .sites.sites import get_sitesGeom
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df = get_sitesGeom(
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id_site=id_site, nom_site=nom_site, columns=columns,
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with_nameOrga=with_nameOrga,last_update=last_update,
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params_col=params_col, milieu=milieu, statut=statut)
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# df.drop(columns=['typo_sdage'], inplace=True)
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return df
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def ps_r_site_param(id_site=None, nom_site=None, columns=None, last_update=False,
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geom=False, raw=False, idparam=False, pivot=True):
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from pandas import pivot_table
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from .pers.pers import _merge_relation, _merge_author
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table = 'r_site_param'
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r_tab_auteur = 'r_siteparam_auteur'
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df = _get_relation_tab(schema=schema,tab=table,id_site=id_site,nom_site=nom_site,
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last_update=last_update,geom=geom,milieu=milieu)
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if 'auteur' in df.columns:
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df.rename(columns={'auteur': 'auteur_geom'}, inplace=True)
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df = _merge_relation(df=df,table=r_tab_auteur,schema=schema, left_id='id',right_id='id_siteparam')
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df = _merge_author(df=df, col_aut='id_auteur')
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df.rename(columns={'auteur': 'auteur_param'}, inplace=True)
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dic = get_param()
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if not df.empty:
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df.date_geom = df.date_geom.astype(str)
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nval = 'param'
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ntyp = 'type'
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df = merge(df,dic, how='left', left_on='id_param', right_on='id', suffixes=(None,'_y'))\
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.drop(columns=['id_y','id_param']) \
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.rename(columns={'description':'desc_param_ps', 'nom':nval})
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if raw:
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df.drop(columns='desc_param_ps', inplace=True)
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else:
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df.drop(columns=nval, inplace=True)
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df.rename(columns={'desc_param_ps':nval}, inplace=True)
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df.taux.fillna(-999, inplace=True)
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if geom:
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dfgeom = df[['id_site', 'date_geom', 'geom']]
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print(dfgeom)
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dfgeom = dfgeom.drop_duplicates()
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df.drop(columns=['geom'], inplace=True)
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indexs = df.columns[~df.columns.isin(['taux',nval,'id','type'])].tolist()
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if pivot:
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df2 = pivot_table(
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df.fillna(''),
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values=['taux',nval,'id'],
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index=indexs,
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columns=['type'],
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# dropna=False,
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aggfunc={lambda x: ', '.join(x.astype(str))})
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df2.columns = [ x[0].split('_')[0] + '_' + x[2][:6] for x in df2.columns ]
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date = [x for x in df2.index.names if x.startswith('date_par')]
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df2.reset_index(['auteur_param', *date], inplace=True)
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df = df2
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else :
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df.set_index(indexs, inplace=True)
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if geom:
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idx = df.index.names
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df.reset_index(inplace=True)
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df = df.merge(dfgeom, how='left', on=['id_site', 'date_geom'])
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df.set_index(idx, inplace=True)
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df = _set_geom(df, hex=False)
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cols = df.columns[df.columns.str.startswith('param')].sort_values()
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rcol = dic.type.unique()
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rcol.sort()
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dicc = dict(zip(cols,rcol))
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df.rename(columns=dicc, inplace=True)
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if not idparam:
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rmcol = df.columns[df.columns.str.startswith('id')]
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df.drop(columns=rmcol, inplace=True)
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df.replace(['-999',-999],[None, None],inplace=True, regex=True)
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df.dropna(how='all', axis=1, inplace=True)
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return df
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def ps_r_site_habitat(id_site=None, nom_site=None, columns=None, last_update=False,
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geom=False, raw=False, idhabitat=False, pivot=True):
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from pandas import pivot_table
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from .pers.pers import _merge_relation, _merge_author
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table = 'r_site_habitat'
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r_tab_auteur = 'r_sitehab_auteur'
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r_hab_cb = 'r_hab_cb'
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df = _get_relation_tab(schema=schema,tab=table,id_site=id_site,
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nom_site=nom_site,last_update=last_update,geom=geom,milieu=milieu)
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if 'auteur' in df.columns:
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df.rename(columns={'auteur': 'auteur_geom'}, inplace=True)
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df = _merge_relation(df=df,table=r_tab_auteur,schema=schema,
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left_id='id',right_id='id_sitehab')
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df = _merge_author(df=df, col_aut='id_auteur')
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df.rename(columns={'auteur': 'auteur_hab'}, inplace=True)
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indexs = df.columns[~df.columns.isin(['id','n_hab','geom','index'])].tolist()
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df = _merge_relation(df=df,table=r_hab_cb,schema=schema,
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left_id='id',right_id='id_sitehab') \
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.drop(columns=['id_sitehab'])
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if not raw:
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from .zh import ref_hab
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cb = ref_hab().get_CB(cols=['id','lb_hab_fr','descriptif_cb_fr'])
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df = merge(df,cb, how='left', left_on='code_hab',right_on='id',suffixes=[None,'_y']) \
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.drop(columns=['code_hab','id_y']) \
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.rename(columns={'lb_hab_fr':'hab','descriptif_cb_fr':'desc_hab'})
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if not df.empty:
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df.date_geom = df.date_geom.astype(str)
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if geom:
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dfgeom = df[['id_site', 'date_geom', 'geom']]
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print(dfgeom)
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dfgeom = dfgeom.drop_duplicates()
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df.drop(columns=['geom'], inplace=True)
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vals = df.columns[~df.columns.isin(['id',*indexs])].tolist()
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if pivot:
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df2 = pivot_table(
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df.fillna(''),
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values=vals,
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index=indexs,
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columns=['index'],
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# dropna=False,
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aggfunc={lambda x: ', '.join(x.astype(str)),})
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df2.columns = [ x[0] + str(x[2]) for x in df2.columns ]
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date = [x for x in df2.index.names if x.startswith('date_hab')]
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df2.reset_index(['auteur_hab', *date], inplace=True)
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df = df2
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else :
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df.set_index(indexs, inplace=True)
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if geom:
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idx = df.index.names
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df.reset_index(inplace=True)
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df = df.merge(dfgeom, how='left', on=['id_site', 'date_geom'])
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df.set_index(idx, inplace=True)
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df = _set_geom(df, hex=False)
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if not idhabitat:
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idx = df.columns[df.columns.str.startswith('id')]
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df.drop(columns=idx, inplace=True)
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return df
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def get_ps(id_site=None, nom_site=None, columns=None, last_update=False,
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geom=False, raw=[False,True], idparam=False, idhabitat=False):
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if isinstance(raw, bool):
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rawp = rawh = raw
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elif isinstance(raw, list):
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rawp = raw[0]
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rawh = raw[1]
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df = ps_r_site_param(id_site=id_site, nom_site=nom_site, columns=columns,
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last_update=last_update, geom=False, raw=rawp, idparam=idparam, pivot=True)
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df2 = ps_r_site_habitat(id_site=id_site, nom_site=nom_site, columns=columns,
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last_update=last_update, geom=geom, raw=rawh, idhabitat=idhabitat, pivot=True)
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df = merge(df, df2, on=df.index.names)
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return df
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