Changement seuils proximax

app.py

@@ -12,6 +12,9 @@ from vicinity import Vicinity, Backend, Metric
 from sklearn.decomposition import TruncatedSVD
 
 
+proximax_emploi=0.65
+proximax_formation=0.68
+
 gcantons=gpd.read_file("cantons-normandie.geojson").rename(columns={"nom": "canton"})
 si=gcantons.sindex
 def assigne_canton(row):
@@ -67,7 +70,7 @@ vicf = Vicinity.from_vectors_and_items(
 )
 
 query=pn.widgets.TextInput(name="Rechercher une compétence")
-proximax=0.68
+
 
 
 score=pn.indicators.Number(name="Score d'adéquation", value=2, visible=False,
@@ -89,7 +92,7 @@ def carte(col):
         score.visible=False
     else:
         test_emb=model.encode(req)
-        selcol = [nom for (nom, dist) in vice.query(test_emb, k=200)[0] if dist<proximax]
+        selcol = [nom for (nom, dist) in vice.query(test_emb, k=200)[0] if dist<proximax_emploi]
         dfselcol=dfcomp[dfcomp["Compétence"].isin(selcol)]
         dfg=dfselcol.groupby("canton")
         dfa=dfg.agg(total= ("Compétence", lambda x: len(x)), 
@@ -98,7 +101,7 @@ def carte(col):
         m=gdet.explore(column="total", tooltip=["canton", "compétence", "total"],
                      cmap="viridis", vmax=10, tiles="CartoDB positron")
 
-        res_form =  [nom for (nom, dist) in vicf.query(test_emb, k=50)[0] if dist<proximax]
+        res_form =  [nom for (nom, dist) in vicf.query(test_emb, k=50)[0] if dist<proximax_formation]
         dft=pd.DataFrame(res_form, columns=[certcol]).merge(dfform).drop_duplicates(subset=["latitude", "longitude"])
         
         for irow, row in dft.iterrows():