ObsPy
ObsPy: A Python Toolbox for Seismology. The wide variety of computer platforms, file formats, and methods to access seismological data often requires considerable effort in preprocessing such data. Although preprocessing work-flows are mostly very similar, few software standards exist to accomplish this task. The objective of ObsPy is to provide a Python toolbox that simplifies the usage of Python programming for seismologists. It is conceptually similar to SEATREE (Milner and Thorsten 2009) or the exploration seismic software project MADAGASCAR (http://www.reproducibility.org). In ObsPy the following essential seismological processing routines are implemented and ready to use: reading and writing data only SEED/MiniSEED and Dataless SEED (http://www.iris.edu/manuals/SEEDManual_V2.4.pdf), XML-SEED (Tsuboi et al. 2004), GSE2 (http://www.seismo.ethz.ch/autodrm/downloads/provisional_GSE2.1.pdf) and SAC (http://www.iris.edu/manuals/sac/manual.html), as well as filtering, instrument simulation, triggering, and plotting. There is also support to retrieve data from ArcLink (a distributed data request protocol for accessing archived waveform data, see Hanka and Kind 1994) or a SeisHub database (Barsch 2009). Just recently, modules were added to read SEISAN data files (Havskov and Ottemöller 1999) and to retrieve data with the IRIS/FISSURES data handling interface (DHI) protocol (Malone 1997).
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
Sorted by year (- Andy Nowacki: SeisModels.jl: A Julia package for models of the Earth’s interior (2020) not zbMATH
- Tobias Stål, Anya M. Reading: A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing (2020) not zbMATH
- Pascal Audet; Colin J. Thomson; Michael G. Bostock; Tom Eulenfeld: Telewavesim: Python software for teleseismic body wavemodeling (2019) not zbMATH
- Peter A.Predein; Anna A.Dobrynina; Tsyren A.Tubanov; Eugeny I.German: CodaNorm: A software package for the body-wave attenuation calculation by the coda-normalization method (2017) not zbMATH