ObsPy: a bridge for seismology into the scientific Python ecosystem
By Lion Krischer, T. Megies, Robert Barsch, M. Beyreuther, T. Lecocq, C. Caudron, Joachim Wassermann. 2015
745 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Geophysics
View Paper: https://www.semanticscholar.org/paper/98532b12b20952e60091a1a82b3dca7e76d6b2b9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Gregory C. Beroza
- S. M. Mousavi
- Weiqiang Zhu
- Y. Sheng
- P. Johnson
- Ebru Bozdag
- Maarten V. de Hoop
- Karianne J. Bergen
In Geophysics
- S. M. Mousavi
- Gregory C. Beroza
- Weiqiang Zhu
- Jeroen Tromp
- Ebru Bozdag
- Dimitri Komatitsch
- Y. Sheng
- Daniel Peter
Citations in the corpus
- Machine learning for data-driven discovery in solid Earth geoscience (2019, methodology): “Open source codes, often shared through online platforms (123, 124), have already been adopted for general data processing in seismology with the ObsPy (125, 126) and Pyrocko (127) toolboxes.”
- Global adjoint tomography: first-generation model (2016, methodology): “We are in the process of migrating the entire pre-processing phase to a Python-based workflow which seamlessly integrates ASDF with ObsPy (Krischer et al. 2015b), a Python framework for processing seismological data.”
- STanford EArthquake Dataset (STEAD): A Global Data Set of Seismic Signals for AI (2019, methodology): “We used the database of metadata to request the associated waveforms from continuous time-series archived at the IRIS data management center [22], [23].”