Regional aftershock sequence¶

Pull a mainshock and its aftershock sequence (the 2019 Ridgecrest, California events) in a tight bounding box over the following month, and plot magnitude against time to show the Omori-law decay.

Setup¶

The imports up front: EarthLens is the unified entry point, matplotlib draws the magnitude-vs-time scatter, and Path prepares the output directory FDSN writes its QuakeML into.

In [ ]:

from pathlib import Path

import matplotlib.pyplot as plt

from earthlens import EarthLens

OUT_DIR = Path('fdsn_output')
OUT_DIR.mkdir(exist_ok=True)

from pathlib import Path import matplotlib.pyplot as plt from earthlens import EarthLens OUT_DIR = Path('fdsn_output') OUT_DIR.mkdir(exist_ok=True)

Query the sequence¶

Build the FDSN request first: a tight bounding box around the 2019 Ridgecrest, California sequence over the month that follows the mainshock, keeping only events at or above magnitude 2.5.

In [ ]:

# A mainshock + its aftershock sequence: a tight box around the 2019
# Ridgecrest, California sequence over the following month.
quake = EarthLens(
    variables=['USGS'],
    data_source='fdsn',
    start='2019-07-04',
    end='2019-08-04',
    aoi=[-117.9, 35.4, -117.2, 36.1],
    min_magnitude=2.5,
    path=str(OUT_DIR),
)

# A mainshock + its aftershock sequence: a tight box around the 2019 # Ridgecrest, California sequence over the following month. quake = EarthLens( variables=['USGS'], data_source='fdsn', start='2019-07-04', end='2019-08-04', aoi=[-117.9, 35.4, -117.2, 36.1], min_magnitude=2.5, path=str(OUT_DIR), )

Run the download as its own step. FDSN is a live network query, so it is wrapped in a try/except that prints a friendly message and leaves events as None when the notebook runs offline.

In [ ]:

events = None
try:
    events = quake.download()
    print(f'{len(events)} events in the sequence')
except Exception as exc:
    print(f'live FDSN query skipped (offline?): {type(exc).__name__}: {exc}')

events = None try: events = quake.download() print(f'{len(events)} events in the sequence') except Exception as exc: print(f'live FDSN query skipped (offline?): {type(exc).__name__}: {exc}')

Magnitude vs time¶

Sort the events chronologically and scatter magnitude against time. The tail of small aftershocks decaying after the mainshock is the visual signature of Omori-law decay. The plot is skipped when the query above returned no events.

In [ ]:

if events is not None and len(events):
    df = events.sort_values('time')
    fig, ax = plt.subplots(figsize=(11, 5))
    ax.scatter(df['time'], df['magnitude'], s=12, alpha=0.6, color='darkorange')
    ax.set_title('Ridgecrest 2019 — magnitude vs time (aftershock decay)')
    ax.set_xlabel('time')
    ax.set_ylabel('magnitude')
    fig.autofmt_xdate()

if events is not None and len(events): df = events.sort_values('time') fig, ax = plt.subplots(figsize=(11, 5)) ax.scatter(df['time'], df['magnitude'], s=12, alpha=0.6, color='darkorange') ax.set_title('Ridgecrest 2019 — magnitude vs time (aftershock decay)') ax.set_xlabel('time') ax.set_ylabel('magnitude') fig.autofmt_xdate()