A python library for teaching computation to seismology students
- Python is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who isPython is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who is interested in Python for data analysis and map making can use these materials.…
Author details: | John M. AikenORCiD, Chastity AikenORCiD, Fabrice Pierre CottonORCiDGND |
---|---|
DOI: | https://doi.org/10.1785/0220170246 |
ISSN: | 0895-0695 |
ISSN: | 1938-2057 |
Title of parent work (English): | Seismological research letters |
Publisher: | Seismological Society of America |
Place of publishing: | Albany |
Publication type: | Article |
Language: | English |
Date of first publication: | 2018/03/14 |
Publication year: | 2018 |
Release date: | 2021/12/03 |
Volume: | 89 |
Issue: | 3 |
Number of pages: | 7 |
First page: | 1165 |
Last Page: | 1171 |
Funding institution: | Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe (SERA) project - EU [730900] |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |