ProbShakemap

ProbShakemap is a Python toolbox that propagates source uncertainty from an ensemble of earthquake scenarios to ground motion predictions at a grid of Points of Interest (POIs). It accounts for model uncertainty by accommodating multiple Ground Motion Models (GMMs) and their inherent variability. The output consists of a set of products aiding the user to explore and visualize the predictive distribution of ground motion at each target point. The package includes SeisEnsMan, a tool for generating event-compatible source scenario ensembles. Originally designed for Urgent Computing applications, ProbShakemap is versatile enough to be adapted for other uses, such as scenario-based seismic hazard assessments.

Dependencies

• OpenQuake

Command line usage

usage: ProbShakemap.py [-h] [--imt {PGA,PGV,SA0.3),SA(1.0),SA(3.0}] [--tool {StationRecords,Save_Output,QueryHDF5}]
                       [--prob_tool {GetStatistics,GetDistributions,EnsemblePlot} [{GetStatistics,GetDistributions,EnsemblePlot} ...]]
                       [--numGMPEsRealizations NUMGMPESREALIZATIONS] [--num_processes NUM_PROCESSES]
                       [--imt_min IMT_MIN] [--imt_max IMT_MAX] [--station_file STATION_FILE] [--scenario SCENARIO]
                       [--pois_file POIS_FILE] [--deg_round DEG_ROUND] [--pois_subset] [--n_pois N_POIS]
                       [--max_distance MAX_DISTANCE] [--pois_selection_method {random,azimuth_uniform}]
                       [--reuse_pois_subset] [--vector_npy] [--fileScenariosWeights FILESCENARIOSWEIGHTS]

ProbShakemap Toolbox

optional arguments:
  -h, --help            show this help message and exit

input params:
  --imt {PGA,PGV,SA(0.3),SA(1.0),SA(3.0)}
                        Intensity measure type (IMT)
  --tool {StationRecords,Save_Output,QueryHDF5}
                        Tool(s) to use
  --prob_tool {GetStatistics,GetDistributions,EnsemblePlot} [{GetStatistics,GetDistributions,EnsemblePlot} ...]
                        ProbShakemap Tool(s) to use
  --numGMPEsRealizations NUMGMPESREALIZATIONS
                        Total number of GMPEs random samples
  --num_processes NUM_PROCESSES
                        Number of CPU cores for code parallelization
  --imt_min IMT_MIN     Minimum value for the selected IMT (for plot only)
  --imt_max IMT_MAX     Maximum value for the selected IMT (for plot only)
  --station_file STATION_FILE
                        Station file (.json, Shakemap-formatted)
  --scenario SCENARIO   Scenario number
  --pois_file POIS_FILE
                        Filename with latitude and longitude of POIs
  --deg_round DEG_ROUND
                        Rounding precision for latitude and longitude
  --pois_subset         Extract a subset of POIs
  --n_pois N_POIS       Number of POIs in the subset
  --max_distance MAX_DISTANCE
                        Max distance from epicenter of POIs in the subset
  --pois_selection_method {random,azimuth_uniform}
                        Selection method for the POIs of the subset
  --reuse_pois_subset   Reuse the subset of POIs already extracted in POIs.txt
  --vector_npy          Store ground motion distributions at all POIs (vector.npy)
  --fileScenariosWeights FILESCENARIOSWEIGHTS
                        File with scenarios weights

INSTALLATION

To install ProbShakemap, clone the ProbShakemap repository to your local machine:

git clone https://github.com/INGV/ProbShakemap.git

Then, create and activate the probshakemap conda environment:

conda env create -f probshakemap_environment.yml -n probshakemap
conda activate probshakemap

The repository includes example input files (INPUT_FILES) and output (OUTPUT_REPO) from the Mw 6.5, 2016 October 30, Norcia Earthquake.

SeisEnsMan requires a separate virtual environment. To set it up, follow these steps:

python -m venv SeisEnsMan

On macOS and Linux:

source [path_to]SeisEnsMan/bin/activate

On Windows:

[path_to]SeisEnsMan\Scripts\activate

Navigate to the SeisEnsManV2 folder and use the provided requirements.txt to install the necessary libraries:

python3 -m pip install -r requirements.txt

GETTING STARTED

To get started with ProbShakemap, make sure to provide all required input files in the folder INPUT_FILES:

1. input_file.txt

This file (do not rename) contains the necessary inputs for OpenQuake, including:

• TectonicRegionType: as defined in OpenQuake tectonic regionalisation.
• Magnitude_Scaling_Relationship: as required from openquake.hazardlib.scalerel.
• Rupture_aratio: rupture aspect ratio as required from openquake.hazardlib.geo.surface.PlanarSurface.from_hypocenter
• ID_Event: Event ID, pointing to the corresponding event folder in the events directory.
• Vs30file: GMT .grd Vs30 file; if not provided, set it to None. Default Vs30 value (760 m/s) will be used instead.
• CorrelationModel: as required from openquake.hazardlib.correlation.
• CrosscorrModel: as required from openquake.hazardlib.cross_orrelation.
• vs30_clustering: True value means that Vs30 values are expected to show clustering (as required from openquake.hazardlib.correlation).
• truncation_level: number of standard deviations for truncation of the cross-correlation model distribution (as required from openquake.hazardlib.cross_correlation). Note that the truncation feature is lost if you use correlation (see OpenQuake documentation). This parameter is only accounted for when 'NoCrossCorrelation' is selected by the user.
• seed: Random seed to ensure reproducibility in sampling from the GMMs.

2. POIs file

A file with two space-separated columns: LAT and LON of the POIs.

3. ENSEMBLE

This folder must contain the ensemble of source scenarios for the current event. Scenarios can be loaded by the user or automatically generated by SeisEnsMan.

4. events

This folder should contain a subfolder named with the current event ID, which needs to include:

• event.xml: contains event magnitude and time, allowing SeisEnsMan to download the event's QUAKEML file and generate an ensemble of compatible earthquake source scenarios.
• gmpes.conf: configuration file for GMMs and their relative weights, which the user must input under gmpe_sets. GMMs available in OpenQuake are listed under gmpe_modules and can be updated by the user.

5. vs30 (Optional)

Place the Vs30 .grd file here. An example file, global_italy_vs30_clobber.grd (Michelini et al., 2020), is available at this link.

7. stationlist.json (Optional)

This file should contain ground shaking records from a set of stations and be placed in the event's subfolder. The file should be formatted like USGS Shakemap files (see the example in INPUT_FILES/events/8863681).

HOW TO RUN

Generate the scenarios ensemble with SeisEnsMan

First, create a subfolder under events named with the event ID. In this folder, populate the event.xml file with the event's magnitude and time. This information will be used by SeisEnsMan to download the event's QUAKEML file, which is required to generate the ensemble of event-compatible scenarios.

Next, activate the SeisEnsMan environment and navigate to the SeisEnsManV2 directory. Run the following command, adjusting the --nb_scen parameter to specify the number of scenarios in the ensemble. The --angles parameter is optional, and includes the strike, dip, and rake of the inverted fault model in the plot:

./line_call.sh

Once the scenarios are generated, SeisEnsMan will: 1) copy the ensemble of scenarios to the INPUT_FILES/ENSEMBLE folder, making them ready for ProbShakemap; 2) move any previous files to the BACKUP folder; 3) copy the event_stat.json and parameters_histo_map_99999999.pdf files to the event subfolder.

Before running ProbShakemap, make sure to deactivate the SeisEnsMan environment:

deactivate

Run ProbShakemap

Activate probshakemap conda environment:

conda activate probshakemap

Use any of the ProbShakemap utilities to explore and visualize the predictive distribution of ground motion at POIs. ProbShakemap comes with three utility tools - StationRecords, Save_Output, QueryHDF5 - and three 'prob tools' - GetStatistics, GetDistributions, EnsemblePlot.

TOOL: StationRecords

Plot data from station file stationlist.json, if provided.

python ProbShakemap.py --imt PGA --tool StationRecords --imt_min 0.01 --imt_max 1 --station_file stationlist.json

OUTPUT

Data_stationfile_{imt}.pdf: Plot data from .json station file for the selected IMT (PGA in the example).

TOOL: Save_Output

Run the probabilistic analysis and save the output to a .HDF5 file (can be large!) with the following hierarchical structure.

scenario --> POI --> GMPEs realizations

python ProbShakemap.py --imt PGA --tool Save_Output --num_processes 8 --pois_file grid.txt --numGMPEsRealizations 10

OUTPUT

SIZE_{num_scenarios}_ENSEMBLE_{IMT}.hdf5

TOOL: QueryHDF5

Navigate and query the .HDF5 file.

python ProbShakemap.py --tool QueryHDF5 --imt PGA --scenario 10 --pois_file grid.txt

OUTPUT

GMF_info.txt: Print the ground motion fields for the selected scenario at the POIs listed in grid.txt.

Preview of an example output file:

GMF realizations at Site_LAT:43.2846_LON:12.7778 for Scenario_10: [0.17520797, 0.21844997, 0.093965515, 0.27266037, 0.079073295, 0.09725358, 0.08347481, 0.06693749, 0.005907976, 0.060873847]
GMF realizations at Site_LAT:43.1846_LON:12.8778 for Scenario_10: [0.100996606, 0.35003924, 0.24363522, 0.19941418, 0.15757227, 0.1009447, 0.19146584, 0.06460667, 0.03146108, 0.097111605]
GMF realizations at Site_LAT:43.0846_LON:13.4778 for Scenario_10: [0.18333985, 0.11954803, 0.2914887, 0.050770156, 0.07628956, 0.17871241, 0.10297835, 0.15162756, 0.020328628, 0.04087482]

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PROB_TOOLS

TOOL: GetStatistics

Calculate, save and plot the statistics of the ground motion predictive distributions at all POIs.

python ProbShakemap.py --imt PGA --prob_tool GetStatistics --num_processes 8 --pois_file grid.txt --numGMPEsRealizations 10 --imt_min 0.001 --imt_max 1

OUTPUT

• npy files with the statistics (saved in the npyFiles folder)
• map view of the statistics in vector_stat.npy (saved in the STATISTICS folder)

Output saved in the npyFiles folder:

• vector_stat.npy: dictionary of statistics computed for the ground motion distributions at all POIs: 'Mean', 'Median','Percentile 10','Percentile 20','Percentile 80','Percentile 90','Percentile 5','Percentile 95','Percentile 2.5','Percentile 97.5';
• (OPTIONAL, with command --vector_npy) vector.npy: a 2D array that stores the ground-motion distributions at all POIs. The array has dimensions (num_pois, num_GMPEsRealizations * num_scenarios), where num_GMPEsRealizations represents the number of realizations per scenario, and num_scenarios is the total number of scenarios in the ensemble.

TOOL: GetDistributions

Plot the cumulative distribution of the predicted ground-motion values and main statistics at a specific POI together with the ground-motion value recorded at the closest station (or at a POI coincident with the station, if available).

Note: requires stationlist.json file.

python ProbShakemap.py --imt PGA --prob_tool GetDistributions --num_processes 8 --pois_file grid.txt --numGMPEsRealizations 10 --imt_min 0.001 --imt_max 10 --station_file stationlist.json

OUTPUT

• POIs_Map.pdf: Spatial map of the POIs
• Distr_POI-{POI_idx}.pdf: Plot of Datum-Ensemble comparison at a given POI

TOOL: EnsemblePlot

Plot and summarize the key statistical features of the distribution of predicted ground-motion values at the POIs.

python ProbShakemap.py --imt PGA --prob_tool EnsemblePlot --num_processes 8 --pois_file grid.txt --numGMPEsRealizations 10

OUTPUT

• POIs_Map.pdf: Spatial map of the POIs
• Ensemble_Spread_Plot_{imt}.pdf: Boxplot

POIs SUBSET OPTION

When using the tools QueryHDF5, GetStatistics, GetDistributions and EnsemblePlot, you can require to extract a subset of POIs within a maximum distance from the event epicenter following one of the following spatial distributions: random and azimuthally uniform. This changes the command line to:

python ProbShakemap.py [...] --pois_subset --n_pois 12 --max_distance 50 --pois_selection_method azimuth_uniform

If azimuthally uniform is selected, POIs are chosen within a ring in the range max_distance +- max_distance/10.

MULTIPLE TOOLS AT THE SAME TIME

ProbShakemap can handle multiple tools at the same time. Be aware that, in this case, the same settings will apply (ie,--imt_min, --imt_max, --pois_subset etc.).

python ProbShakemap.py --imt PGA --prob_tool GetDistributions EnsemblePlot --num_processes 8 --pois_file grid.txt --numGMPEsRealizations 10 --imt_min 0.001 --imt_max 10 --station_file stationlist.json --pois_subset --n_pois 12 --max_distance 50 --pois_selection_method azimuth_uniform

HPC

ProbShakemap can be executed on a HPC cluster. IMPORTANT: the number set at --ntasks-per-node must coincide with num_processes.

Contact

If you need support write to [email protected].

Contributions & Acknowledgements

Jacopo Selva coded the GetStatistics tool; Louise Cordrie authored the SeisEnsMan tool and tested ProbShakemap on the INGV-Bologna ADA cluster. I thank Valentino Lauciani for testing and developing the INGV Shakemap Docker and Licia Faenza for testing ProbShakemap. I also thank Michele Proietto (@https://github.com/miproietto) for assisting us in building the Docker image on the HPC cluster using Singularity.

Citation

If you use ProbShakemap in your research, please cite using the following citation:

@article{stallone2025probshakemap,
  title={ProbShakemap: A Python toolbox propagating source uncertainty to ground motion prediction for urgent computing applications},
  author={Stallone, Angela and Selva, Jacopo and Cordrie, Louise and Faenza, Licia and Michelini, Alberto and Lauciani, Valentino},
  journal={Computers \& Geosciences},
  volume={195},
  pages={105748},
  year={2025},
  publisher={Elsevier}
}