update code
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@ -8,9 +8,9 @@
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# import re
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from contextlib import AsyncExitStack
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from os import register_at_fork
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from os import register_at_fork,path
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import types
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from numpy.lib.shape_base import expand_dims
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# from numpy.lib.shape_base import expand_dims
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import pandas as pd
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import geopandas as gpd
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from pandas.io.pytables import incompatibility_doc
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@ -340,6 +340,7 @@ def normalize_colname(df):
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'remarque' :'remarques',
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'remarq_' :'remarques',
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'rmq_intere' :'remarques',
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# 'rmq_site' :'remarques',
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'legendes' :'legende',
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'legend' :'legende',
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'sources' :'source',
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@ -398,6 +399,7 @@ def existing_ps(df):
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return df
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def define_siteOrg(df):
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gdf = pycen.get_districtNat()[['abrev','geom']]
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tmp = df[['geom']].copy().set_geometry('geom')
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@ -415,6 +417,7 @@ def define_siteOrg(df):
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return df
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# tmp[tmp.id_site==334]
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# 'touches', None, 'contains', 'overlaps', 'contains_properly', 'within', 'intersects', 'crosses', 'covers', 'covered_by'
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def ident_newsite(df,rcvmt=10):
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'''
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@ -467,7 +470,7 @@ def ident_newsite(df,rcvmt=10):
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tmpp[['site_code','id_origine']], on=['id_origine'])
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maj2['id_site'] = maj2['site_code']
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del maj2['site_code']
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if maj : df_maj = pd.concat([maj,maj2])
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if not maj.empty : df_maj = pd.concat([maj,maj2])
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else : df_maj = maj2
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# Isolement des nouveaux sites
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orig_maj_all = df_maj.id_origine
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@ -483,7 +486,6 @@ def ident_newsite(df,rcvmt=10):
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return df_new, df_cor, df_maj
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def define_siteName(df,rcvmt=10):
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'''
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Return df_new, df_replace, df_maj
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@ -536,7 +538,6 @@ def define_siteName(df,rcvmt=10):
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return df_new, df_replace, df_maj
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def normalize_formatIdsite(id_site):
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import re
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df = pd.DataFrame({'id_site':id_site})
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@ -753,12 +754,12 @@ def insert_site(df):
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df['type_site'] = 'N.D.'
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if 'type_milieu' not in df.columns:
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df['type_milieu'] = 'Pelouses sèches'
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# if 'remarques' not in df.columns:
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# df['remarques'] = None
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if 'remarques' not in df.columns:
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df['remarques'] = None
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df = df[['id_site','nom','date','auteur','type_site','type_milieu',
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'structure'
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# 'remarques'
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,'remarques'
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]]
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drop_col = ['auteur','structure']
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typs = pycen.sites._get_typ_site()
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@ -836,7 +837,7 @@ def insert_geom(df):
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colindict = [ *df.columns[df.columns.isin(dic.keys())] ]
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if colindict:
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df.rename(
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columns={'remarques':'rmq_interet_patri','legende':'rmq_usage_process'},
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columns=dic,
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inplace=True,
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)
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if 'table_org' in df.columns:
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@ -1166,6 +1167,7 @@ def filter_saisierror(df):
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continue
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print('\t'+cod + ' : '+ perc.astype(str))
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lst_error1 = [*lst_error1,*tmp[(tmp.hab_ == hab)&(tmp.code_hab==cod)].sort_values('id_site').id_site.unique()]
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try:
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df[df.id_site.isin(lst_error1)].to_postgis(
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name='incoherence_habVScodehab',
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con=con,
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@ -1175,6 +1177,10 @@ def filter_saisierror(df):
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# geom_col='geom',
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index_label='id_site',
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)
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except Exception as e:
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print(e)
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df[df.id_site.isin(lst_error1)].to_file(path.join(path0,'incoherence_habVScodehab.geojson'),driver='GeoJSON')
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if lst_error1:
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print('%i'%len(lst_error1))
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@ -1196,6 +1202,7 @@ def filter_saisierror(df):
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if lst_error2:
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print('ERROR code_hab : %i'%len(lst_error2))
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try:
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df[df.id_site.isin(lst_error2)].to_postgis(
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name='PB_codehab_nonPresent_dans_corineBiotope',
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con=con,
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@ -1205,17 +1212,25 @@ def filter_saisierror(df):
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# geom_col='geom',
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index_label='id_site',
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)
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except Exception as e:
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print(e)
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df[df.id_site.isin(lst_error2)].to_file(path.join(path0,'PB_codehab_nonPresent_dans_corineBiotope.geojson'),driver='GeoJSON')
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lst_iderror = [*lst_error1,*lst_error2]
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lst_iderrorindex = df[df.id_site.isin(lst_iderror)].index
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df.drop(lst_iderrorindex,inplace=True)
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return df.sort_values('id_site')
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def _insert_site_(df,ps_statut='actif'):
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def _insert_geomsite(df):
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df_ins, ins = insert_geom(df)
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if ins:
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insert_authordata(df_ins,id_data='id_site',tab_data='r_sites_geom',colname_rsite='id_geom_site', tab_auteur='r_geomsites_auteur')
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def _insert_site_(df,ps_statut='actif'):
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_insert_geomsite(df)
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df_ins, ins = insert_attrsPS(df,ps_statut)
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if ins:
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insert_authordata(df_ins,id_data='id_geom_site',tab_data='r_site_param',colname_rsite='id_siteparam', tab_auteur='r_siteparam_auteur')
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@ -1305,7 +1320,7 @@ if __name__ == "__main__":
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from_table = None
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from_file = 'PS prioritaire.geojson'
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from_tab = 'Tableau_saisie_PS_2026.xlsx'
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path0 = '/home/colas/Documents/9_PROJETS/2_PS/TO IMPORT/2026/'
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path0 = '/home/cgeier/Documents/9_PROJETS/2_PS/TO IMPORT/2026'
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# org = from_file.split('/')[1]
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tutu = pd.DataFrame()
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@ -1354,11 +1369,13 @@ if __name__ == "__main__":
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if from_file is not None:
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table = from_file.split('/')[-1]#.split('.')[0]
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df = gpd.read_file(path0+from_file)
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df = gpd.read_file(path.join(path0,from_file))
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df.dropna(axis=1, how='all', inplace=True)
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df = normalize_colname(df)
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df = format_date(df)
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df['table_org'] = table
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df['structure'] = 'CEN Isère'
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df['structure'] = df.organisme.copy()
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# df['type_pat'].replace(['Indéterminé','/'],None,inplace=True)
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# df.loc[df.type_pat.notna(),'pratiques'] = \
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# df[df.type_pat.notna()].pratiques + ' ' + df[df.type_pat.notna()].type_pat.str.lower()
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@ -1391,7 +1408,7 @@ if __name__ == "__main__":
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# }, inplace=True)
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df = pycen.tools.Polygons_to_MultiPolygon(df)
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df_new, df_replace, df_maj = define_siteName(df,rcvmt=10)
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df_new, df_replace, df_maj = define_siteName(df, rcvmt=5)
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df_new_tmp = df_new.copy()
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df_new = df_new_tmp[df_new_tmp.id_site.notna()].copy()
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@ -7,9 +7,8 @@ import geopandas as gpd
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def update_psInf1200(df):
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from rasterstats import zonal_stats
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path0 = '/home/colas/Documents/9_PROJETS/2_PS/'
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path0 = '/home/cgeier/Documents/9_PROJETS/2_PS/'
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path2_mnt = path0+'MNT/'
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file_mnt5 = 'MNT_5m.tif'
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@ -18,16 +17,16 @@ def update_psInf1200(df):
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zonal.columns = ['max_alti']
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tmp = gpd.pd.concat([df.reset_index(drop=True),zonal], axis=1)
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tmp = tmp.set_geometry('geom', crs=2154)
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tmp.infeq_1200 = tmp.max_alti <= 1200
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tmp['infeq_1200'] = tmp.max_alti <= 1200
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PS = tmp[['site_code','infeq_1200']]\
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.rename(columns={'site_code':'id_site'})
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PS = (tmp[['site_code','infeq_1200']]
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.rename(columns={'site_code':'id_site'},errors='ignore')
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)
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PS.to_sql('r_infeq_1200m',con,'ps',if_exists='append',index=False)
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# update_to_sql(PS,con,'r_infeq_1200m','ps','id_site')
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ps_all = gpd.read_postgis('''
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SELECT vp.*,s7.infeq_1200
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FROM ps."v_pelouseseches_all" vp
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@ -35,6 +34,8 @@ ps_all = gpd.read_postgis('''
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ORDER BY vp.site_code DESC NULLS LAST;
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''', con)
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isnot_1200 = ps_all.infeq_1200.isna()
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ps_all[~ps_all.infeq_1200]
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update_psInf1200(ps_all[isnot_1200])
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