import numpy as np
import pandas as pd
import scipy.io
import os
[docs]
def select_events_with_options(
catalog_file,
output_file,
min_mag=6.0,
start_year=1988,
end_year=2025,
max_depth=40.0,
MC=2.5,
exclude_921_aftershocks=True
):
"""
Select earthquakes from the catalog based on specified criteria, with optional exclusion of 921 earthquake aftershocks.
Args:
catalog_file (str): Input .mat file name.
output_file (str): Output file name.
min_mag (float): Minimum magnitude to filter.
start_year (int): Starting year to filter (inclusive).
end_year (int): Ending year to filter (exclusive).
max_depth (float): Maximum depth to filter (exclusive), in kilometers.
MC (float): A custom parameter, default is 2.5.
exclude_921_aftershocks (bool): Whether to exclude 921 aftershocks, default is True.
"""
if not os.path.exists(catalog_file):
print(f"Error: File '{catalog_file}' not found. Please confirm the file has been uploaded.")
return
try:
mat_data = scipy.io.loadmat(catalog_file)
var_name = [k for k in mat_data if not k.startswith('__')][0]
cat = mat_data[var_name]
print(f"Successfully loaded variable '{var_name}' from '{catalog_file}'.")
except Exception as e:
print(f"Failed to read file '{catalog_file}': {e}")
return
columns = ['Year', 'Month', 'Day', 'Hour', 'Minute', 'Second', 'Latitude', 'Longitude', 'Depth', 'Magnitude']
df = pd.DataFrame(cat, columns=columns)
df['datetime'] = pd.to_datetime(df[['Year', 'Month', 'Day', 'Hour', 'Minute', 'Second']].astype(int), errors='coerce')
df.dropna(subset=['datetime'], inplace=True)
# --- Define filter conditions ---
# 1. Basic conditions: magnitude, year and depth
final_mask = (
(df['Magnitude'] >= min_mag) &
(df['Year'] >= start_year) &
(df['Year'] < end_year) &
(df['Depth'] < max_depth)
)
# 2. Decide whether to add exclusion condition based on option
if exclude_921_aftershocks:
print("921 aftershock exclusion enabled.")
aftershock_exclusion_condition = ~(
(df['datetime'] >= '1999-09-21') &
(df['datetime'] <= '1999-12-31')
)
final_mask = final_mask & aftershock_exclusion_condition
else:
print("921 aftershock exclusion disabled.")
# 3. Apply final filter conditions
selected_df = df[final_mask].copy()
n = len(selected_df)
if n == 0:
print(f"No earthquakes found matching criteria (M>={min_mag}, year between {start_year} and {end_year}, depth < {max_depth}km).")
return
# --- Post-processing and write to file ---
names = [f"K7EQ{i}" for i in range(1, n + 1)]
selected_df['name'] = names
selected_df['startyr'] = selected_df['Year'] - 30
selected_df['endyr'] = selected_df['Year'] + 1
cati = "K7"
with open(output_file, 'w') as f:
for _, row in selected_df.iterrows():
lineout = [
row['name'], cati,
int(row['startyr']), 1, 1,
int(row['Year']), int(row['Month']), int(row['Day']),
int(row['endyr']), 1, 1,
row['Latitude'], row['Longitude'], MC,
int(row['Hour']), 0, 0, row['Magnitude']
]
line_str = ' '.join(map(str, lineout))
f.write(line_str + '\n')
exclusion_status = "921 aftershocks excluded" if exclude_921_aftershocks else "921 aftershocks not excluded"
print(f"Selected {n} M{min_mag}+ earthquakes (year >= {start_year} and < {end_year}, depth < {max_depth}km, {exclusion_status}) and wrote to '{output_file}'")
