Treffer: PyGMT – Accessing and Integrating GMT with Python and the Scientific Python Ecosystem (AGU24, U12B-05)

Title:
PyGMT – Accessing and Integrating GMT with Python and the Scientific Python Ecosystem (AGU24, U12B-05)
Authors:
Fröhlich, Yvonne, Tian, Dongdong, Leong, Wei Ji, Jones, Max, Grund, Michael
Publication Year:
2025
Collection:
KITopen (Karlsruhe Institute of Technologie)
Subject Terms:
Other earth sciences not elsewhere classified, Geophysics not elsewhere classified, Oceanography not elsewhere classified, Atmospheric sciences not elsewhere classified, ddc:530, Physics, info:eu-repo/classification/ddc/530
Document Type:
Fachzeitschrift article in journal/newspaper<br />conference object
File Description:
application/pdf
Language:
English
Relation:
https://publikationen.bibliothek.kit.edu/1000177747; https://publikationen.bibliothek.kit.edu/1000177747/156351621; https://doi.org/10.5445/IR/1000177747
DOI:
10.5445/IR/1000177747
Availability:
https://publikationen.bibliothek.kit.edu/1000177747
https://publikationen.bibliothek.kit.edu/1000177747/156351621
https://doi.org/10.5445/IR/1000177747
Rights:
https://creativecommons.org/licenses/by/4.0/deed.de ; info:eu-repo/semantics/openAccess
Accession Number:
edsbas.9D9D090F
Database:
BASE

Weitere Informationen

The Generic Mapping Tools (GMT) are widely used across the Earth, Ocean, and Planetary Sciences and beyond to process geospatial and geophysical data as well as produce high-quality (static) vector and raster plots and maps. However, GMT suffers from its cryptic syntax.PyGMT (https://www.pygmt.org/) wraps around the very fast GMT C code to make it accessible through the Python programming language. The introduction of meaningful aliases for the single-letter flags (e. g., "region" for "R" or "projection" for "J") and ongoing efforts regarding a more Pythonic syntax for GMT arguments significantly increase user-friendliness and readability of the code. Furthermore, PyGMT provides auto-compilation and supports rich display in Jupyter notebooks for improved user experience. The Python library is indexed on PyPI (https://pypi.org/project/pygmt/) and conda-forge (https://anaconda.org/conda-forge/pygmt) and is installable via the pip, mamba, and conda packages managers. PyGMT integrates smoothly within the Scientific Python ecosystem. In addition to standard file formats such as ASCII and NetCDF files, common Pythonic data structures for tabular and grid data such as numpy.ndarray, pandas.DataFrame, geopandas.GeoDataFrame, and xarray.DataArray are supported. PyGMT also provides easy access to the GMT remote datasets. Numerous gallery examples, tutorials, and intros help new users and users coming from GMT learn the main concepts of PyGMT. There is also a Q&A subsection on the GMT forum to help with common user issues.The project was started in 2017 by Leonardo Uieda and Paul Wessel as an open-source project hosted on GitHub (https://github.com/GenericMappingTools/pygmt). Now it is a community-driven effort, with all versions still available on GitHub and recorded on Zenodo (https://doi.org/10.5281/zenodo.3781524) and v0.12.0 being the latest release (2024/05/01). People are encouraged to pick any issue they like, where the label “good first issue” indicates a low knowledge barrier to get involved in PyGMT. --- ...