# instance **Repository Path**: ucaslilong/instance ## Basic Information - **Project Name**: instance - **Description**: No description available - **Primary Language**: Unknown - **License**: CC-BY-4.0 - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2022-02-11 - **Last Updated**: 2022-02-11 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ![event](docs/logo.png) [![DOI](https://img.shields.io/badge/doi-10.13127%2Finstance-lightgray?style=flat-square)](https://doi.org/10.13127/instance) ## Description **INSTANCE** is a dataset of seismic waveforms data and associated metadata **suited for analysis based on machine learning**. It includes: * 54,008 earthquakes for a total of 1,159,249 3-channel waveforms; * 132,330 3-channel noise waveforms; * 115 precomputed observable quantities providing information on *station, trace, source, path* and *quality*; * 19 networks; * 620 seismic stations. ![maps](docs/Ita_epicenter_moment_tensor_compressed.png) *Earthquakes a) and stations b) in INSTANCE. Symbols size are proportional to earthquake magnitude and number of arrival phases recorded by stations, respectively* **Events with Magnitude in the range [2-4]** ![wf_c](docs/Wave_count_2_M_4.png) **Events selected from HN channel** ![wf_gm](docs/Wave_gm_HN.png) **Noise selected form HH channel** ![wf_n](docs/Wave_noise_HH.png) ## Open review Michelini, A., Cianetti, S., Gaviano, S., Giunchi, C., Jozinovic, D., and Lauciani, V.: INSTANCE – the Italian seismic dataset for machine learning, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-164, in review, 2021. **Review status: a revised version of this preprint was accepted for the journal ESSD** ## Reference **INSTANCE** The Italian Seismic Dataset For Machine Learning, Alberto Michelini, Spina Cianetti, Sonja Gaviano, Carlo Giunchi, Dario Jozinović & Valentino Lauciani, Seismic Waveforms And Associated Metadata published 2021 in Istituto Nazionale di Geofisica e Vulcanologia (INGV) https://doi.org/10.13127/instance ## Downloads To get the **full INSTANCE dataset** you have to download: * **Events metadata** ([**csv**](http://repo.pi.ingv.it/instance/metadata_Instance_events.csv.bz2), 238 MB bz2 file, 1.1 GB after decompression) - doi:10.13127/instance/eventsmetadata.1 * **Events data in counts** as [**single hdf5 file**](http://repo.pi.ingv.it/instance/Instance_events_counts.hdf5.bz2) (39 GB bz2 file, 156 GB after decompression) or 10 GB parts ([**part-a**](http://repo.pi.ingv.it/instance/events/Instance_events_counts.hdf5.bz2.part-a), [**part-b**](http://repo.pi.ingv.it/instance/events/Instance_events_counts.hdf5.bz2.part-b), [**part-c**](http://repo.pi.ingv.it/instance/events/Instance_events_counts.hdf5.bz2.part-c), [**part-d**](http://repo.pi.ingv.it/instance/events/Instance_events_counts.hdf5.bz2.part-d)) - doi:10.13127/instance/events.1 * **Events data in ground motion units** as [**single hdf5 file**](http://repo.pi.ingv.it/instance/Instance_events_gm.hdf5.bz2) (151 GB bz2 file, 156 GB after decompression) or 20 GB parts ([**part-a**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-a), [**part-b**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-b), [**part-c**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-c), [**part-d**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-d), [**part-e**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-e), [**part-f**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-f), [**part-g**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-g), [**part-h**](http://repo.pi.ingv.it/instance/gm/Instance_events_gm.hdf5.bz2.part-h)). Ground motion units are m/s for HH and EH channels and m/s2 for HN channel. doi:10.13127/instance/groundmotion.1 * **Noise metadata** ([**csv**](http://repo.pi.ingv.it/instance/metadata_Instance_noise.csv.bz2), 6.7 MB bz2 file, 53 MB after decompression) - doi:10.13127/instance/noisemetadata.1 * **Noise data** in counts ([**hdf5**](http://repo.pi.ingv.it/instance/Instance_noise.hdf5.bz2), 3.9 GB bz2 file, 18 GB after decompression) - doi:10.13127/instance/noise.1 * **Stations inventory** ([**StationXML**](http://repo.pi.ingv.it/instance/responses.tgz), 15 MB) All the above downloads provide `bzip2` compressed files. The multipart files can be reassembled and then unzipped (e.g., for the event data file) ``` cat Instance_events_counts.hdf5.bz2.part-* > Instance_events_counts.hdf5.bz2 bzip2 -d Instance_events_counts.hdf5.bz2 ``` A **sample dataset** of about 1.7 GB is provided to run the notebooks. This contains 10,000 events and 1000 noise waveforms together with the associated metadata. Potentially interested users can evaluate **INSTANCE** data and metadata without downloading the whole dataset. * [**Sample dataset**](http://repo.pi.ingv.it/instance/Instance_sample_dataset.tar.bz2) (1.7 GB bz2 file, 2.74 GB after decompression) ## Notebooks The following notebooks provide examples about reading waveforms and metadata of **INSTANCE**. They refers to the **sample dataset**; to use them with the full dataset filenames must be changed accordingly. `Plots.ipynb` to explore significant parameters distribution in **INSTANCE** using metadata `Waveforms.ipynb` to select and plot 3 channel waveforms `Station_Hypocenter_MomentTensor.ipynb` maps about earthquakes included in INSTANCE ## Requirements To run the notebooks please make sure the following packages are properly installed in your environment: * obspy * jupyter * basemap * pandas * seaborn * h5py * hdf5 or just create a dedicated environment for INSTANCE ``` conda create -n instance python=3.7 obspy jupyter basemap pandas seaborn h5py hdf5 conda activate instance git clone https://github.com/cjunkk/instance cd instance curl http://repo.pi.ingv.it/instance/Instance_sample_dataset.tar.bz2 | tar xj ``` ## Licence Creative commons license [Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/legalcode)