def get_dev_projects_table(scenario, parcels):
# requires the user has MTC's urban_data_internal
# repository alongside bayarea_urbansim
urban_data_repo = ("../urban_data_internal/development_projects/")
file = "2021_0309_1939_development_projects.csv"
print('Version of development_projects: {}'.format(file))
current_dev_proj = (file)
orca.add_injectable("dev_proj_file", current_dev_proj)
df = pd.read_csv(os.path.join(urban_data_repo, current_dev_proj))
df = reprocess_dev_projects(df)
orca.add_injectable("devproj_len", len(df))
# this filters project by scenario
scen = 'scen' + str(scenario)
if scen in df:
# df[scenario] is 1s and 0s indicating whether to include it
df = df[df[scen].astype('bool')]
orca.add_injectable("devproj_len_scen", len(df))
df = df.dropna(subset=['geom_id'])
cnts = df.geom_id.isin(parcels.geom_id).value_counts()
if False in cnts.index:
print("%d MISSING GEOMIDS!" % cnts.loc[False])
df = df[df.geom_id.isin(parcels.geom_id)]
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
orca.add_injectable("devproj_len_geomid", len(df))
return df
def parcels_geography(parcels, scenario, settings, policy):
file = os.path.join(misc.data_dir(), "2021_02_25_parcels_geography.csv")
print('Version of parcels_geography: {}'.format(file))
df = pd.read_csv(file, index_col="geom_id")
df = geom_id_to_parcel_id(df, parcels)
# this will be used to map juris id to name
juris_name = pd.read_csv(os.path.join(misc.data_dir(),
"census_id_to_name.csv"),
index_col="census_id").name10
df["juris_name"] = df.jurisdiction_id.map(juris_name)
df.loc[2054504, "juris_name"] = "Marin County"
df.loc[2054505, "juris_name"] = "Santa Clara County"
df.loc[2054506, "juris_name"] = "Marin County"
df.loc[572927, "juris_name"] = "Contra Costa County"
# assert no empty juris values
assert True not in df.juris_name.isnull().value_counts()
df['juris_trich'] = df.juris + '-' + df.trich_id
df["pda_id_pba40"] = df.pda_id_pba40.str.lower()
# danville wasn't supposed to be a pda
df["pda_id_pba40"] = df.pda_id_pba40.replace("dan1", np.nan)
# Add Draft Blueprint geographies: PDA, TRA, PPA, sesit
if scenario in policy['geographies_db_enable']:
df["pda_id_pba50"] = df.pda_id_pba50.str.lower()
df["gg_id"] = df.gg_id.str.lower()
df["tra_id"] = df.tra_id.str.lower()
df['juris_tra'] = df.juris + '-' + df.tra_id
df["ppa_id"] = df.ppa_id.str.lower()
df['juris_ppa'] = df.juris + '-' + df.ppa_id
df["sesit_id"] = df.sesit_id.str.lower()
df['juris_sesit'] = df.juris + '-' + df.sesit_id
# Use Final Blueprint geographies: PDA, TRA, PPA, sesit
elif scenario in policy['geographies_fb_enable']:
df["pda_id_pba50"] = df.pda_id_pba50_fb.str.lower()
df["gg_id"] = df.fbp_gg_id.str.lower()
df["tra_id"] = df.fbp_tra_id.str.lower()
df['juris_tra'] = df.juris + '-' + df.tra_id
df["ppa_id"] = df.fbp_ppa_id.str.lower()
df['juris_ppa'] = df.juris + '-' + df.ppa_id
df["sesit_id"] = df.fbp_sesit_id.str.lower()
df['juris_sesit'] = df.juris + '-' + df.sesit_id
# Use EIR geographies: TRA, PPA, sesit, CoC
elif scenario in policy['geographies_eir_enable']:
df["pda_id_pba50"] = df.pda_id_pba50_fb.str.lower()
df["gg_id"] = df.eir_gg_id.str.lower()
df["tra_id"] = df.eir_tra_id.str.lower()
df['juris_tra'] = df.juris + '-' + df.tra_id
df["ppa_id"] = df.eir_ppa_id.str.lower()
df['juris_ppa'] = df.juris + '-' + df.ppa_id
df["sesit_id"] = df.eir_sesit_id.str.lower()
df['juris_sesit'] = df.juris + '-' + df.sesit_id
df['coc_id'] = df.eir_coc_id.str.lower()
df['juris_coc'] = df.juris + '-' + df.coc_id
return df
def zoning_baseline(parcels, zoning_lookup, settings):
file = os.path.join(misc.data_dir(),
"2020_11_05_zoning_parcels_hybrid_pba50.csv")
print('Version of zoning_parcels: {}'.format(file))
df = pd.read_csv(file, index_col="geom_id")
df = pd.merge(df,
zoning_lookup.to_frame(),
left_on="zoning_id",
right_index=True)
df = geom_id_to_parcel_id(df, parcels)
return df
def static_parcels(settings, parcels):
# list of geom_ids to not relocate
static_parcels = settings["static_parcels"]
# geom_ids -> parcel_ids
return geom_id_to_parcel_id(pd.DataFrame(index=static_parcels),
parcels).index.values