Maz scale microdata devprojects

baus.py

@@ -138,7 +138,7 @@ def get_simulation_models(SCENARIO):
         "balance_rental_and_ownership_hedonics",
 
         "price_vars",
-        #"scheduled_development_events",
+        "scheduled_development_events",
 
         # run the subsidized acct system
         "lump_sum_accounts",

baus/datasources.py

@@ -256,39 +256,38 @@ def reprocess_dev_projects(df):
     # record, we change the later ones to add records - we don't want to
     # constantly be redeveloping projects, but it's a common error for users
     # to make in their development project configuration
-    df = df.sort_values(["geom_id", "year_built"])
-    prev_geom_id = None
+    df = df.sort_values(["parcel_id", "year_built"])
+    prev_pcl_id = None
     for index, rec in df.iterrows():
-        if rec.geom_id == prev_geom_id:
+        if rec.parcel_id == prev_pcl_id:
             df.loc[index, "action"] = "add"
-        prev_geom_id = rec.geom_id
+        prev_pcl_id = rec.parcel_id
 
     return df
 
 
 # shared between demolish and build tables below
 def get_dev_projects_table(scenario, parcels):
-    return pd.DataFrame()
-    df = pd.read_csv(os.path.join(misc.data_dir(), "development_projects.csv"))
+    df = pd.read_csv(os.path.join(misc.data_dir(),
+                     "development_projects.csv"))
+    # find nearest parcel centroid to dev project x, y and assign parcel_id
+    df = pd.merge(df, parcels.apn.reset_index(), how='left', left_on='apn',
+                  right_on='apn')
+
     df = reprocess_dev_projects(df)
 
     # this filters project by scenario
     if scenario in df:
         # df[scenario] is 1s and 0s indicating whether to include it
         df = df[df[scenario].astype('bool')]
 
-    df = df.dropna(subset=['geom_id'])
+    df = df.dropna(subset=['parcel_id'])
 
-    cnts = df.geom_id.isin(parcels.geom_id).value_counts()
+    cnts = df.parcel_id.isin(parcels.index).value_counts()
     if False in cnts.index:
-        print "%d MISSING GEOMIDS!" % cnts.loc[False]
-
-    df = df[df.geom_id.isin(parcels.geom_id)]
+        print "%d MISSING PARCELIDS!" % cnts.loc[False]
 
-    geom_id = df.geom_id  # save for later
-    df = df.set_index("geom_id")
-    df = geom_id_to_parcel_id(df, parcels).reset_index()  # use parcel id
-    df["geom_id"] = geom_id.values  # add it back again cause it goes away
+    df = df[df.parcel_id.isin(parcels.index)]
 
     return df
 
@@ -328,6 +327,10 @@ def development_projects(parcels, settings, scenario):
     # we don't predict prices for schools and hotels right now
     df = df[~df.building_type.isin(["SC", "HO"])]
 
+    df['sqft_job'] = df.building_type.map(settings['building_sqft_per_job'])
+    df['job_spaces'] = np.divide(df.building_sqft, df.sqft_job)
+    del df['sqft_job']
+
     # need a year built to get built
     df = df.dropna(subset=["year_built"])
     df = df[df.action.isin(["add", "build"])]
@@ -378,10 +381,9 @@ def buildings():
     df["non_residential_rent"] = 0.0
     for col in ["residential_units", "non_residential_sqft", "building_sqft"]:
         df[col] = df[col].fillna(0).astype("int")
-    del df["juris_name"]
-    del df["small_building"]
-    del df["sqft_per_job"]
-    del df["calc_area"]
+    df = df.drop(['juris_name', 'small_building', 'sqft_per_job', 'calc_area',
+                  'apn', 'base_residential_units', 'maz_building_id',
+                  'maz_id', 'name', 'osm_building_type'], axis=1)
     return df
 
 

baus/models.py

@@ -345,7 +345,6 @@ def scheduled_development_events(buildings, development_projects,
         new_buildings.building_type.fillna("OF").map(building_sqft_per_job)
     new_buildings["job_spaces"] = new_buildings.job_spaces.\
         fillna(0).astype('int')
-    new_buildings["geom_id"] = parcel_id_to_geom_id(new_buildings.parcel_id)
     new_buildings["SDEM"] = True
     new_buildings["subsidized"] = False