Simplified machine-learning driven earthquake detection, location, and analysis in one easy-to-implement python package.
On most systems you should be able to simply:
pip install easyQuake
To stay on the bleeding edge of updates:
pip install easyQuake --upgrade
Or if you need to tweak something, like the number of GPUs in gpd_predict, you could:
git clone https://github.com/jakewalter/easyQuake.git
cd easyQuake
pip install .
If you find this useful, please cite:
Walter, J. I., P. Ogwari, A. Thiel, F. Ferrer, and I. Woelfel (in press), easyQuake: Putting machine
learning to work for your regional seismic network or local earthquake study, Seismological Research
Letters
This code leverages machine-learning for earthquake detection. You should have suitable hardware to run CUDA/Tensorflow, which usually means some sort of GPU. This has been tested on servers with nvidia compute cards and modest multi-core desktop with consumer gaming nvidia card (e.g. Geforce 1050 Ti). The event-mode can be run efficiently enough on a laptop.
- Requires nvidia-cuda-toolkit, obspy, keras==2.3.1, tensorflow-gpu==2.1 (if using multiple GPUs only tensorflow 1.15 is tested), basemap
- I've found that the the easiest way to install cuda, tensorflow, and keras is through installing Anaconda python and running
conda install tensorflow-gpu==2.1 - Because tensorflow-gpu 2.1 requires python 3.7 (not the latest version), you might find an easier road creating a new environment:
conda create -n easyquake python=3.7 anaconda
conda activate easyquake
conda install tensorflow-gpu==2.1
conda install keras
conda install obspy -c conda-forge
pip install easyQuake
The example runs easyQuake for a recent M6.5 earthquake in Idaho for the 2 days around the earthquake (foreshocks and aftershocks). The catalog from running the example is in the examples folder: https://github.com/jakewalter/easyQuake/blob/master/examples/catalog_idaho_2days.xml
from easyQuake import download_mseed
from easyQuake import daterange
from datetime import date
from easyQuake import combine_associated
from easyQuake import detection_continuous
from easyQuake import association_continuous
from easyQuake import magnitude_quakeml
from easyQuake import simple_cat_df
import matplotlib.pyplot as plt
maxkm = 300
maxdist=300
lat_a = 42
lat_b = 47.5
lon_a = -118
lon_b = -111
start_date = date(2020, 3, 31)
end_date = date(2020, 4, 2)
project_code = 'idaho'
project_folder = '/data/id'
for single_date in daterange(start_date, end_date):
print(single_date.strftime("%Y-%m-%d"))
dirname = single_date.strftime("%Y%m%d")
download_mseed(dirname=dirname, project_folder=project_folder, single_date=single_date, minlat=lat_a, maxlat=lat_b, minlon=lon_a, maxlon=lon_b)
detection_continuous(dirname=dirname, project_folder=project_folder, project_code=project_code, single_date=single_date, machine=True,local=True)
association_continuous(dirname=dirname, project_folder=project_folder, project_code=project_code, maxdist=maxdist, maxkm=maxkm, single_date=single_date, local=True)
cat, dfs = combine_associated(project_folder=project_folder, project_code=project_code)
cat = magnitude_quakeml(cat=cat, project_folder=project_folder,plot_event=True)
cat.write('catalog_idaho.xml',format='QUAKEML')
catdf = simple_cat_df(cat)
plt.figure()
plt.plot(catdf.index,catdf.magnitude,'.')
Within your systems, consider running driver scripts as nohup background processes nohup python ~/work_dir/okla_daily.py &. In this way, one could cat nohup.out | grep Traceback to understand python errors or grep nohup.out | Killed to understand when the system runs out of memory.
If you have access to shared computing resources that utilize SLURM, you can drive easyQuake by making a bash script to run the example code or any code (thanks to Xiaowei Chen at OU). Save the following to a drive_easyQuake.sh and then run it
#!/bin/bash
#
#SBATCH --partition=gpu_cluster
#SBATCH --ntasks=1
#SBATCH --mem=1024
#SBATCH --output=easyquake_%J_stdout.txt
#SBATCH --error=easyquake_%J_stderr.txt
#SBATCH --time=24:00:00
#SBATCH --job-name=easyquake
#SBATCH [email protected]
#SBATCH --mail-type=ALL
#SBATCH --chdir=/drive/group/user/folder
conda init bash
bash
conda activate easyquake
python idaho_example.py
This project is licensed under the MIT License - see the LICENSE.md file for details
- code was reused from obspy (https://github.com/obspy/obspy/wiki), gpd (https://github.com/interseismic/generalized-phase-detection), PhasePApy (https://github.com/austinholland/PhasePApy), and others
- would not be possible without the robust documentation in the obspy project
- this work was developed at the Oklahoma Geological Survey
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