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azs - apply black to the tools as well
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@zsarnoczay
zsarnoczay committed May 7, 2024
1 parent 1f1cdfa commit 630d09a
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Showing 3 changed files with 24 additions and 69 deletions.
86 changes: 24 additions & 62 deletions pelicun/tools/DL_calculation.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -380,7 +380,6 @@ def run_pelicun(
config_ap, CMP = auto_populate(config, auto_script_path)

if config_ap['DL'] is None:

log_msg(
"The prescribed auto-population script failed to identify "
"a valid damage and loss configuration for this asset. "
Expand Down Expand Up @@ -633,8 +632,7 @@ def run_pelicun(
# save results
if 'Demand' in config['DL']['Outputs']:
out_reqs = [
out if val else ""
for out, val in config['DL']['Outputs']['Demand'].items()
out if val else "" for out, val in config['DL']['Outputs']['Demand'].items()
]

if np.any(np.isin(['Sample', 'Statistics'], out_reqs)):
Expand Down Expand Up @@ -721,9 +719,7 @@ def run_pelicun(
cmp_marginals.loc['excessive.coll.DEM', 'Units'] = 'ea'

locs = demand_sample[coll_DEM].columns.unique(level=0)
cmp_marginals.loc['excessive.coll.DEM', 'Location'] = ','.join(
locs
)
cmp_marginals.loc['excessive.coll.DEM', 'Location'] = ','.join(locs)

dirs = demand_sample[coll_DEM].columns.unique(level=1)
cmp_marginals.loc['excessive.coll.DEM', 'Direction'] = ','.join(
Expand Down Expand Up @@ -802,8 +798,7 @@ def run_pelicun(
)

out_reqs = [
out if val else ""
for out, val in config['DL']['Outputs']['Asset'].items()
out if val else "" for out, val in config['DL']['Outputs']['Asset'].items()
]

if np.any(np.isin(['Sample', 'Statistics'], out_reqs)):
Expand Down Expand Up @@ -872,9 +867,7 @@ def run_pelicun(
):
component_db = [
'PelicunDefault/'
+ default_DBs['fragility'][
config['DL']['Asset']['ComponentDatabase']
],
+ default_DBs['fragility'][config['DL']['Asset']['ComponentDatabase']],
]
else:
component_db = []
Expand Down Expand Up @@ -932,9 +925,9 @@ def run_pelicun(
adf.loc[coll_CMP_name, ('Demand', 'Type')] = coll_DEM_name

else:
adf.loc[coll_CMP_name, ('Demand', 'Type')] = (
f'{coll_DEM_name}|{coll_DEM_spec}'
)
adf.loc[
coll_CMP_name, ('Demand', 'Type')
] = f'{coll_DEM_name}|{coll_DEM_spec}'

coll_DEM_unit = add_units(
pd.DataFrame(
Expand Down Expand Up @@ -990,9 +983,9 @@ def run_pelicun(
# input file
adf.loc['excessiveRID', ('Demand', 'Directional')] = 1
adf.loc['excessiveRID', ('Demand', 'Offset')] = 0
adf.loc['excessiveRID', ('Demand', 'Type')] = (
'Residual Interstory Drift Ratio'
)
adf.loc[
'excessiveRID', ('Demand', 'Type')
] = 'Residual Interstory Drift Ratio'

adf.loc['excessiveRID', ('Demand', 'Unit')] = 'unitless'
adf.loc['excessiveRID', ('LS1', 'Theta_0')] = irrep_config[
Expand All @@ -1019,7 +1012,6 @@ def run_pelicun(
# TODO: we can improve this by creating a water
# network-specific assessment class
if "Water" in config['DL']['Asset']['ComponentDatabase']:

# add a placeholder aggregate fragility that will never trigger
# damage, but allow damage processes to aggregate the
# various pipeline damages
Expand Down Expand Up @@ -1086,9 +1078,7 @@ def run_pelicun(

for target_val in target_vals:
for cmp_type, cmp_id in cmp_map.items():
if (cmp_type in target_val) and (
cmp_id != ''
):
if (cmp_type in target_val) and (cmp_id != ''):
target_val = target_val.replace(
cmp_type, cmp_id
)
Expand All @@ -1113,9 +1103,7 @@ def run_pelicun(
dmg_process = None

else:
log_msg(
f"Prescribed Damage Process not recognized: " f"{dp_approach}"
)
log_msg(f"Prescribed Damage Process not recognized: " f"{dp_approach}")

# calculate damages
PAL.damage.calculate(sample_size, dmg_process=dmg_process)
Expand All @@ -1131,13 +1119,9 @@ def run_pelicun(
)
is True
):
damage_units = damage_units.groupby(
level=[0, 1, 2, 4], axis=1
).first()
damage_units = damage_units.groupby(level=[0, 1, 2, 4], axis=1).first()

damage_groupby_uid = damage_sample.groupby(
level=[0, 1, 2, 4], axis=1
)
damage_groupby_uid = damage_sample.groupby(level=[0, 1, 2, 4], axis=1)

damage_sample = damage_groupby_uid.sum().mask(
damage_groupby_uid.count() == 0, np.nan
Expand All @@ -1161,9 +1145,7 @@ def run_pelicun(
damage_sample_s.to_csv(
output_path / "DMG_sample.zip",
index_label=damage_sample_s.columns.name,
compression=dict(
method='zip', archive_name='DMG_sample.csv'
),
compression=dict(method='zip', archive_name='DMG_sample.csv'),
)
output_files.append('DMG_sample.zip')

Expand All @@ -1185,18 +1167,14 @@ def run_pelicun(
)
is True
):
damage_groupby = damage_sample.groupby(
level=[0, 1, 3], axis=1
)
damage_groupby = damage_sample.groupby(level=[0, 1, 3], axis=1)

damage_units = damage_units.groupby(
level=[0, 1, 3], axis=1
).first()

else:
damage_groupby = damage_sample.groupby(
level=[0, 1, 4], axis=1
)
damage_groupby = damage_sample.groupby(level=[0, 1, 4], axis=1)

damage_units = damage_units.groupby(
level=[0, 1, 4], axis=1
Expand Down Expand Up @@ -1256,9 +1234,7 @@ def run_pelicun(
grp_damage_s.to_csv(
output_path / "DMG_grp.zip",
index_label=grp_damage_s.columns.name,
compression=dict(
method='zip', archive_name='DMG_grp.csv'
),
compression=dict(method='zip', archive_name='DMG_grp.csv'),
)
output_files.append('DMG_grp.zip')

Expand Down Expand Up @@ -1469,9 +1445,7 @@ def run_pelicun(
adf.loc[rcarb, ('DS1', 'Theta_0')] = rCarbon_config["Median"]

if pd.isna(rCarbon_config.get('Distribution', np.nan)) is False:
adf.loc[rcarb, ('DS1', 'Family')] = rCarbon_config[
"Distribution"
]
adf.loc[rcarb, ('DS1', 'Family')] = rCarbon_config["Distribution"]
adf.loc[rcarb, ('DS1', 'Theta_1')] = rCarbon_config["Theta_1"]
else:
# add a default replacement carbon value as a placeholder
Expand Down Expand Up @@ -1563,12 +1537,9 @@ def run_pelicun(
drivers.append(f'DMG-{dmg_cmp}')
loss_models.append(loss_cmp)

loss_map = pd.DataFrame(
loss_models, columns=['Repair'], index=drivers
)
loss_map = pd.DataFrame(loss_models, columns=['Repair'], index=drivers)

elif repair_config['MapApproach'] == "User Defined":

if repair_config.get('MapFilePath', False) is not False:
loss_map_path = repair_config['MapFilePath']

Expand Down Expand Up @@ -1634,8 +1605,7 @@ def run_pelicun(
)

out_reqs = [
out if val else ""
for out, val in out_config_loss['Repair'].items()
out if val else "" for out, val in out_config_loss['Repair'].items()
]

if np.any(
Expand Down Expand Up @@ -1682,9 +1652,7 @@ def run_pelicun(
if np.any(
np.isin(['GroupedSample', 'GroupedStatistics'], out_reqs)
):
repair_groupby = repair_sample.groupby(
level=[0, 1, 2], axis=1
)
repair_groupby = repair_sample.groupby(level=[0, 1, 2], axis=1)

repair_units = repair_units.groupby(
level=[0, 1, 2], axis=1
Expand All @@ -1697,9 +1665,7 @@ def run_pelicun(
if 'GroupedSample' in out_reqs:
grp_repair_s = pd.concat([grp_repair, repair_units])

grp_repair_s = convert_to_SimpleIndex(
grp_repair_s, axis=1
)
grp_repair_s = convert_to_SimpleIndex(grp_repair_s, axis=1)
grp_repair_s.to_csv(
output_path / "DV_repair_grp.zip",
index_label=grp_repair_s.columns.name,
Expand Down Expand Up @@ -1765,14 +1731,12 @@ def run_pelicun(
damage_sample_s['irreparable'] = np.zeros(damage_sample_s.shape[0])

if 'Losses' in config['DL']:

if 'agg_repair' not in locals():
agg_repair = PAL.repair.aggregate_losses()

agg_repair_s = convert_to_SimpleIndex(agg_repair, axis=1)

else:

agg_repair_s = pd.DataFrame()

summary = pd.concat(
Expand Down Expand Up @@ -1816,8 +1780,7 @@ def run_pelicun(
out_dict.update(
{
"Units": {
col: df_units.loc["Units", col]
for col in df_units.columns
col: df_units.loc["Units", col] for col in df_units.columns
}
}
)
Expand All @@ -1841,7 +1804,6 @@ def run_pelicun(


def main():

args = sys.argv[1:]

parser = argparse.ArgumentParser()
Expand Down
3 changes: 0 additions & 3 deletions pelicun/tools/HDF_to_CSV.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,6 @@


def convert_HDF(HDF_path):

HDF_ext = HDF_path.split('.')[-1]
CSV_base = HDF_path[: -len(HDF_ext) - 1]

Expand All @@ -53,14 +52,12 @@ def convert_HDF(HDF_path):
store = pd.HDFStore(HDF_path)

for key in store.keys():

store[key].to_csv(f'{CSV_base}_{key[1:].replace("/","_")}.csv')

store.close()


if __name__ == '__main__':

args = sys.argv[1:]

parser = argparse.ArgumentParser()
Expand Down
4 changes: 0 additions & 4 deletions pelicun/tools/export_DB.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -59,7 +59,6 @@ def export_DB(data_path, target_dir):
DB_df = pd.read_hdf(data_path, 'data')

for row_id, row in DB_df.iterrows():

row_dict = convert_Series_to_dict(row)

with open(target_dir_data / f'{row_id}.json', 'w', encoding='utf-8') as f:
Expand All @@ -68,13 +67,11 @@ def export_DB(data_path, target_dir):
# add population if it exists

try:

DB_df = pd.read_hdf(data_path, 'pop')

pop_dict = {}

for row_id, row in DB_df.iterrows():

pop_dict.update({row_id: convert_Series_to_dict(row)})

with open(target_dir / 'population.json', 'w', encoding='utf-8') as f:
Expand All @@ -85,7 +82,6 @@ def export_DB(data_path, target_dir):


if __name__ == '__main__':

args = sys.argv[1:]

parser = argparse.ArgumentParser()
Expand Down

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