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doi: 10.5281/zenodo.13679420 , 10.5281/zenodo.14868324 , 10.5281/zenodo.5162003 , 10.5281/zenodo.6349217 , 10.5281/zenodo.6426493 , 10.5281/zenodo.4522136 , 10.5281/zenodo.15071586 , 10.5281/zenodo.6702566 , 10.5281/zenodo.7772533 , 10.5281/zenodo.3930577 , 10.5281/zenodo.11062720 , 10.5281/zenodo.15628725 , 10.5281/zenodo.4025418 , 10.5281/zenodo.17156962 , 10.5281/zenodo.8303186 , 10.5281/zenodo.14535921 , 10.5281/zenodo.5607255 , 10.5281/zenodo.14742338 , 10.5281/zenodo.3781524 , 10.5281/zenodo.4978645 , 10.5281/zenodo.3781525 , 10.5281/zenodo.4253459 , 10.5281/zenodo.10578540 , 10.5281/zenodo.3837197 , 10.5281/zenodo.19398871 , 10.5281/zenodo.18080259 , 10.5281/zenodo.7481934 , 10.5281/zenodo.3782862 , 10.5281/zenodo.4592991
PyGMT is a library for processing geospatial and geophysical data and making publication quality maps and figures. It provides a Pythonic interface for the Generic Mapping Tools (GMT), a command-line program widely used in the Earth Sciences.
The development of PyGMT has been supported by NSF grants OCE-1558403 and EAR-1948602.
geology, Generic Mapping Tools PyGMT, Ecology, geophysics, Information Systems not elsewhere classified, Pythonic interface, Computational Biology, seismology, Generic Mapping Tools, figure, Mental Health, processing geospatial, publication quality maps, Genetics, Earth Sciences, Python interface, geodesy, cartography, oceanography, geophysical data, geospatial, Neuroscience, command-line program
geology, Generic Mapping Tools PyGMT, Ecology, geophysics, Information Systems not elsewhere classified, Pythonic interface, Computational Biology, seismology, Generic Mapping Tools, figure, Mental Health, processing geospatial, publication quality maps, Genetics, Earth Sciences, Python interface, geodesy, cartography, oceanography, geophysical data, geospatial, Neuroscience, command-line program
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 174 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
| views | 8 |

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