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Fix Flake8 errors/warnings in consequences-v3.10.0.py
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@anthonyfok
anthonyfok committed May 5, 2022
1 parent 6c7fcac commit 8b35ed2
Showing 1 changed file with 77 additions and 64 deletions.
141 changes: 77 additions & 64 deletions scripts/consequences-v3.10.0.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,76 +17,89 @@
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.

import csv
import sys

import numpy as np
from openquake.baselib import datastore, sap
import pandas as pd
from openquake.baselib import datastore
from tqdm import tqdm
import sys

params_file = "scripts/Hazus_Consequence_Parameters.xlsx" #/mnt/storage/earthquake-scenarios/scripts/Hazus_Consequence_Parameters.xlsx"
params_file = "scripts/Hazus_Consequence_Parameters.xlsx" # /mnt/storage/earthquake-scenarios/scripts/Hazus_Consequence_Parameters.xlsx"


def read_square_footage(xlsx):
square_footage_df = pd.read_excel(xlsx, sheet_name="Square Footage", skiprows=1, index_col=0)
return square_footage_df


def read_repair_ratio_str(xlsx):
repair_ratio_str_df = pd.read_excel(xlsx, sheet_name="Structural Repair Ratios", skiprows=2, index_col=0)
repair_ratio_str_df.index.name = "Occupancy"
repair_ratio_str_df.rename_axis("Structural Damage State", axis="columns", inplace=True)
return repair_ratio_str_df/100


def read_repair_ratio_nsa(xlsx):
repair_ratio_nsa_df = pd.read_excel(xlsx, sheet_name="NonstrAccel Repair Ratios", skiprows=2, index_col=0)
repair_ratio_nsa_df.index.name = "Occupancy"
repair_ratio_nsa_df.rename_axis("Acceleration Sensitive Non-structural Damage State", axis="columns", inplace=True)
return repair_ratio_nsa_df/100


def read_repair_ratio_nsd(xlsx):
repair_ratio_nsd_df = pd.read_excel(xlsx, sheet_name="NonstrDrift Repair Ratios", skiprows=2, index_col=0)
repair_ratio_nsd_df.index.name = "Occupancy"
repair_ratio_nsd_df.rename_axis("Drift Sensitive Non-structural Damage State", axis="columns", inplace=True)
return repair_ratio_nsd_df/100


def read_repair_ratio_con(xlsx):
repair_ratio_con_df = pd.read_excel(xlsx, sheet_name="Contents Damage Ratios", skiprows=2, index_col=0)
repair_ratio_con_df.index.name = "Occupancy"
repair_ratio_con_df.rename_axis("Acceleration Sensitive Non-structural Damage State", axis="columns", inplace=True)
return repair_ratio_con_df/100


def read_collapse_rate(xlsx):
collapse_rate_df = pd.read_excel(xlsx, sheet_name="Collapse Rates", skiprows=1, index_col=0)
return collapse_rate_df/100


def read_casualty_rate_in(xlsx):
casualty_rate_in_df = pd.read_excel(xlsx, sheet_name="Indoor Casualty Rates", skiprows=1, index_col=0, header=[0,1])
casualty_rate_in_df = pd.read_excel(xlsx, sheet_name="Indoor Casualty Rates", skiprows=1, index_col=0, header=[0, 1])
casualty_rate_in_df.index.name = "Building Type"
casualty_rate_in_df.columns.names = ["Damage State", "Severity Level"]
return casualty_rate_in_df/100


def read_casualty_rate_out(xlsx):
casualty_rate_out_df = pd.read_excel(xlsx, sheet_name="Outdoor Casualty Rates", skiprows=1, index_col=0, header=[0,1])
casualty_rate_out_df = pd.read_excel(xlsx, sheet_name="Outdoor Casualty Rates", skiprows=1, index_col=0, header=[0, 1])
casualty_rate_out_df.index.name = "Building Type"
casualty_rate_out_df.columns.names = ["Damage State", "Severity Level"]
return casualty_rate_out_df/100


def read_debris_weight(xlsx):
debris_df = pd.read_excel(xlsx, sheet_name="Debris", index_col=0, header=[0,1,2])
debris_df = pd.read_excel(xlsx, sheet_name="Debris", index_col=0, header=[0, 1, 2])
debris_df.index.name = "Building Type"
debris_df.columns.names = ["Item", "Material", "Component"]
return debris_df


def read_repair_time(xlsx):
repair_time_df = pd.read_excel(xlsx, sheet_name="Building Repair Time", skiprows=2, index_col=0)
repair_time_df.index.name = "Occupancy"
repair_time_df.rename_axis("Structural Damage State", axis="columns", inplace=True)
return repair_time_df


def read_recovery_time(xlsx):
recovery_time_df = pd.read_excel(xlsx, sheet_name="Building Recovery Time", skiprows=2, index_col=0)
recovery_time_df.index.name = "Occupancy"
recovery_time_df.rename_axis("Structural Damage State", axis="columns", inplace=True)
return recovery_time_df


def read_interruption_time(xlsx):
interruption_time_df = pd.read_excel(xlsx, sheet_name="Interruption Time Multipliers", skiprows=2, index_col=0)
interruption_time_df.index.name = "Occupancy"
Expand All @@ -110,11 +123,12 @@ def read_interruption_time(xlsx):
"Interruption Time Multipliers": read_interruption_time,
}


def calculate_consequences(job_id='-1'):
calc_id = datastore.get_last_calc_id() if job_id=='-1' else int(job_id)
calc_id = datastore.get_last_calc_id() if job_id == '-1' else int(job_id)
dstore = datastore.read(calc_id)
lt = 0 # structural damage
stat = 0 # damage state mean values
lt = 0 # structural damage
stat = 0 # damage state mean values
num_rlzs = len(dstore["weights"])
assetcol = dstore['assetcol']
taxonomies = assetcol.tagcol.taxonomy
Expand All @@ -126,9 +140,9 @@ def calculate_consequences(job_id='-1'):
elif calculation_mode == 'classical_damage':
damages = dstore['damages-stats']
else:
print("Consequence calculations not supported for ", calculation_mode)
print("Consequence calculations not supported for", calculation_mode)
return

# Read the various consequences tables from the spreadsheet
square_footage_df = read_params["Square Footage"](xlsx)
repair_ratio_str_df = read_params["Structural Repair Ratios"](xlsx)
Expand Down Expand Up @@ -159,20 +173,20 @@ def calculate_consequences(job_id='-1'):
writer = csv.writer(f)
# Write the header row to the csv file
writer.writerow(
["asset_ref", "number_of_buildings",
"value_structural", "value_nonstructural", "value_contents",
"occupants_day", "occupants_night", "occupants_transit",
"collapse_ratio", "mean_repair_time",
"mean_recovery_time","mean_interruption_time",
"casualties_day_severity_1", "casualties_day_severity_2",
"casualties_day_severity_3", "casualties_day_severity_4",
"casualties_night_severity_1", "casualties_night_severity_2",
"casualties_night_severity_3", "casualties_night_severity_4",
"casualties_transit_severity_1", "casualties_transit_severity_2",
"casualties_transit_severity_3", "casualties_transit_severity_4",
"sc_Displ3","sc_Displ30", "sc_Displ90", "sc_Displ180", "sc_Displ360",
"sc_BusDispl30", "sc_BusDispl90", "sc_BusDispl180", "sc_BusDispl360",
"debris_brick_wood_tons", "debris_concrete_steel_tons"])
["asset_ref", "number_of_buildings",
"value_structural", "value_nonstructural", "value_contents",
"occupants_day", "occupants_night", "occupants_transit",
"collapse_ratio", "mean_repair_time",
"mean_recovery_time", "mean_interruption_time",
"casualties_day_severity_1", "casualties_day_severity_2",
"casualties_day_severity_3", "casualties_day_severity_4",
"casualties_night_severity_1", "casualties_night_severity_2",
"casualties_night_severity_3", "casualties_night_severity_4",
"casualties_transit_severity_1", "casualties_transit_severity_2",
"casualties_transit_severity_3", "casualties_transit_severity_4",
"sc_Displ3", "sc_Displ30", "sc_Displ90", "sc_Displ180", "sc_Displ360",
"sc_BusDispl30", "sc_BusDispl90", "sc_BusDispl180", "sc_BusDispl360",
"debris_brick_wood_tons", "debris_concrete_steel_tons"])

for asset in tqdm(assetcol):
asset_ref = asset['id'].decode()
Expand Down Expand Up @@ -200,11 +214,11 @@ def calculate_consequences(job_id='-1'):
# Hazus tables 12.1, 12.2, 12.3
unit_weight = unit_weight_df.loc[asset_typ]
weight_brick_wood = (
unit_weight["Brick, Wood and Other"]
unit_weight["Brick, Wood and Other"]
* square_footage_df.loc[asset_occ].values[0] / 1000
* asset['number'])
weight_concrete_steel = (
unit_weight["Reinforced Concrete and Steel"]
unit_weight["Reinforced Concrete and Steel"]
* square_footage_df.loc[asset_occ].values[0] / 1000
* asset['number'])
debris_brick_wood_pct = debris_brick_wood_pct_df.loc[asset_typ]
Expand Down Expand Up @@ -261,43 +275,42 @@ def calculate_consequences(job_id='-1'):

# Write all consequence estimates for this asset to the csv file
writer.writerow(
[asset_ref,
"{0:,.1f}".format(asset['number']),
"{0:,.1f}".format(asset["value-structural"]),
"{0:,.1f}".format(asset["value-nonstructural"]),
"{0:,.1f}".format(asset["value-contents"]),
"{0:,.1f}".format(asset["occupants_day"]),
"{0:,.1f}".format(asset["occupants_night"]),
"{0:,.1f}".format(asset["occupants_transit"]),
collapse_ratio_str,
"{0:,.1f}".format(repair_time),
"{0:,.1f}".format(recovery_time),
"{0:,.1f}".format(interruption_time),
"{0:,.2f}".format(casualties_day["Severity 1"]),
"{0:,.2f}".format(casualties_day["Severity 2"]),
"{0:,.2f}".format(casualties_day["Severity 3"]),
"{0:,.2f}".format(casualties_day["Severity 4"]),
"{0:,.2f}".format(casualties_night["Severity 1"]),
"{0:,.2f}".format(casualties_night["Severity 2"]),
"{0:,.2f}".format(casualties_night["Severity 3"]),
"{0:,.2f}".format(casualties_night["Severity 4"]),
"{0:,.2f}".format(casualties_transit["Severity 1"]),
"{0:,.2f}".format(casualties_transit["Severity 2"]),
"{0:,.2f}".format(casualties_transit["Severity 3"]),
"{0:,.2f}".format(casualties_transit["Severity 4"]),
"{0:,.1f}".format(sc_Displ3),
"{0:,.1f}".format(sc_Displ30),
"{0:,.1f}".format(sc_Displ90),
"{0:,.1f}".format(sc_Displ180),
"{0:,.1f}".format(sc_Displ360),
"{0:,.1f}".format(sc_BusDispl30),
"{0:,.1f}".format(sc_BusDispl90),
"{0:,.1f}".format(sc_BusDispl180),
"{0:,.1f}".format(sc_BusDispl360),
"{0:,.1f}".format(debris_brick_wood),
"{0:,.1f}".format(debris_concrete_steel),
])

[asset_ref,
"{0:,.1f}".format(asset['number']),
"{0:,.1f}".format(asset["value-structural"]),
"{0:,.1f}".format(asset["value-nonstructural"]),
"{0:,.1f}".format(asset["value-contents"]),
"{0:,.1f}".format(asset["occupants_day"]),
"{0:,.1f}".format(asset["occupants_night"]),
"{0:,.1f}".format(asset["occupants_transit"]),
collapse_ratio_str,
"{0:,.1f}".format(repair_time),
"{0:,.1f}".format(recovery_time),
"{0:,.1f}".format(interruption_time),
"{0:,.2f}".format(casualties_day["Severity 1"]),
"{0:,.2f}".format(casualties_day["Severity 2"]),
"{0:,.2f}".format(casualties_day["Severity 3"]),
"{0:,.2f}".format(casualties_day["Severity 4"]),
"{0:,.2f}".format(casualties_night["Severity 1"]),
"{0:,.2f}".format(casualties_night["Severity 2"]),
"{0:,.2f}".format(casualties_night["Severity 3"]),
"{0:,.2f}".format(casualties_night["Severity 4"]),
"{0:,.2f}".format(casualties_transit["Severity 1"]),
"{0:,.2f}".format(casualties_transit["Severity 2"]),
"{0:,.2f}".format(casualties_transit["Severity 3"]),
"{0:,.2f}".format(casualties_transit["Severity 4"]),
"{0:,.1f}".format(sc_Displ3),
"{0:,.1f}".format(sc_Displ30),
"{0:,.1f}".format(sc_Displ90),
"{0:,.1f}".format(sc_Displ180),
"{0:,.1f}".format(sc_Displ360),
"{0:,.1f}".format(sc_BusDispl30),
"{0:,.1f}".format(sc_BusDispl90),
"{0:,.1f}".format(sc_BusDispl180),
"{0:,.1f}".format(sc_BusDispl360),
"{0:,.1f}".format(debris_brick_wood),
"{0:,.1f}".format(debris_concrete_steel),
])


if __name__ == "__main__":
Expand Down

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