clean up and correction output

data/hts/entd/cleaned.py

@@ -247,6 +247,8 @@ def execute(context):
 
     # Socioprofessional class
     df_persons["socioprofessional_class"] = df_persons["CS24"].fillna(80).astype(int) // 10
+
+    hts.fix_activity_types(df_trips)
 
     return df_households, df_persons, df_trips
 

data/hts/entd/filtered.py

@@ -10,10 +10,10 @@ def configure(context):
     context.stage("data.hts.entd.cleaned")
     context.stage("data.spatial.codes")
 
-    context.config("filter_entd", False)
+    context.config("filter_hts", True)
 
 def execute(context):
-    filter_entd = context.config("filter_entd")
+    filter_entd = context.config("filter_hts")
     df_codes = context.stage("data.spatial.codes")
     df_households, df_persons, df_trips = context.stage("data.hts.entd.cleaned")
 
@@ -31,13 +31,10 @@ def execute(context):
         ]["person_id"].unique())
 
         df_persons = df_persons[~df_persons["person_id"].isin(remove_ids)]
-
-    else:
-        df_persons = df_persons[~df_persons["person_id"].isin([34581])] # remove persons leading to activity types error
 
-    # Only keep trips and households that still have a person
-    df_trips = df_trips[df_trips["person_id"].isin(df_persons["person_id"].unique())]
-    df_households = df_households[df_households["household_id"].isin(df_persons["household_id"])]
+        # Only keep trips and households that still have a person
+        df_trips = df_trips[df_trips["person_id"].isin(df_persons["person_id"].unique())]
+        df_households = df_households[df_households["household_id"].isin(df_persons["household_id"])]
 
     # Finish up
     df_households = df_households[hts.HOUSEHOLD_COLUMNS + ["urban_type", "income_class"]]

data/od/weighted.py

@@ -12,7 +12,7 @@
 def configure(context):
     context.stage("data.od.cleaned")
     context.stage("data.spatial.codes")
-    context.config("output_path")
+
     context.config("education_location_source","bpe")
 
 def fix_origins(df, commune_ids, purpose,category): 

documentation/flow_output.py

@@ -39,6 +39,7 @@ def execute(context):
         "Yrs:75+":{"min_age": 76, "max_age": 110,},}
 
     if not context.config("analysis_from_file"):
+        print("Récupération simu données ...")
         # from simulation cache
         df_trips = context.stage("synthesis.population.trips")
         df_persons = context.stage("synthesis.population.enriched")[["person_id", "household_id","age"]]
@@ -84,7 +85,6 @@ def execute(context):
     for prefix, figure in figures.items():
         df_select_age = df_stats[df_stats["age"].between(figure["min_age"],figure["max_age"])]
         df_select_age = df_select_age.dissolve(by=["id_carr_1km","following_purpose"],aggfunc="count").reset_index()
-        print(prefix)
         df_select_age = df_select_age[~(df_select_age["geometry"].isna())]
         df_select_age["following_purpose"] = df_select_age["following_purpose"].astype('str')
 
@@ -101,8 +101,9 @@ def execute(context):
                 df_tiles_select = gpd.sjoin(df_tiles_select,df_tile,how='right',predicate="contains").fillna(0)
                 df_select = gpd.sjoin(df_select.drop(columns=['index_right']),df_tiles_select.drop(columns=[ 'index_left']),how='right',predicate="contains").rename(columns={"count_left":"volume_studied_simu","count_right":"volume_compared_simu"}).fillna(0)
                 df_select["volume_difference"] = df_select["volume_studied_simu"] - df_select["volume_compared_simu"]
-                #df_select  = df_select[df_select["volume_difference"] != 0]
-                px.choropleth_mapbox(df_select,geojson=df_select.geometry,locations=df_select.index,color="volume_difference", opacity= 0.7,color_continuous_scale="picnic", color_continuous_midpoint= 0,hover_name="id_carr_1km_right", hover_data=["volume_studied_simu", "volume_compared_simu"],
+                df_select  = df_select[(df_select["volume_studied_simu"] != 0 )| (df_select["volume_compared_simu"] != 0)]
+                df_select["pourcentage_vol"] = df_select["volume_difference"] / df_select["volume_compared_simu"]
+                px.choropleth_mapbox(df_select,geojson=df_select.geometry,locations=df_select.index,color="volume_difference", opacity= 0.7,color_continuous_scale="picnic", color_continuous_midpoint= 0,hover_name="id_carr_1km_right", hover_data=["volume_studied_simu", "volume_compared_simu","pourcentage_vol"],
                                         mapbox_style = 'open-street-map',center=dict(lat= point.y,lon=point.x),title=f"Comparison flow distribution with previous simulation for {prefix} group with {purpose} purpose").write_html(f'{context.config("output_path")}/{context.config("output_prefix")}{prefix}_{purpose}.html')
 
 

synthesis/population/spatial/primary/candidates.py

@@ -10,7 +10,7 @@ def configure(context):
     context.stage("synthesis.population.spatial.home.zones")
     context.stage("synthesis.population.enriched")
     context.stage("synthesis.population.trips")
-    context.config("output_path")
+
     context.config("random_seed")
     context.config("education_location_source", "bpe")