The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Mayavi: 3D Visualization of Scientific Data
Open accessAbstract
Mayavi is a general purpose, open source 3D scientific visualization package that is tightly integrated with the rich ecosystem of Python scientific packages. Mayavi provides a continuum of tools for developing scientific applications, ranging from interactive and script-based data visualization in Python to full-blown custom end-user applications.
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Cites
Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249
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IPython: A System for Interactive Scientific Computing
Perez, F., & Granger, B. E. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.53 · Cited by 4,009
SCHROEDER, W. J., & MARTIN, K. M. (2005) · Visualization Handbook · doi:10.1016/b978-012387582-2/50032-0 · Cited by 1,355
Test Driven Development: By Example
Beck (2002) · Addison-Wesley Longman Publishing Co., Inc. eBooks · Cited by 1,282
Guest Editor's Introduction: Python: Batteries Included
Dubois, P. F. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.51 · Cited by 41
(2002)
Cited by
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2019) · Apollo - University of Cambridge Repository · doi:10.17863/cam.64134 · Cited by 10,460
SchNet – A deep learning architecture for molecules and materials
Schütt, K. T., Sauceda, H. E., Kindermans, P.-J., Tkatchenko, A., & Müller, K.-R. (2018) · The Journal of Chemical Physics · doi:10.1063/1.5019779 · Cited by 2,217
Quantum-chemical insights from deep tensor neural networks
Schütt, K. T., Arbabzadah, F., Chmiela, S., Müller, K. R., & Tkatchenko, A. (2017) · Nature Communications · doi:10.1038/ncomms13890 · Cited by 1,445
pyGIMLi: An open-source library for modelling and inversion in geophysics
Rücker, C., Günther, T., & Wagner, F. M. (2017) · Computers & Geosciences · doi:10.1016/j.cageo.2017.07.011 · Cited by 512
Metadata
- Authors
- Ramachandran, P., & Varoquaux, G.
- Venue
- Computing in Science & Engineering
- Published
- 2011-03
- Volume
- 13
- Issue
- 2
- Pages
- 40-51
- ISSN
- 1521-9615 (ISSN-L)
- OpenAlex
- W2044105167
- Cited by
- 648
- References
- 7
- FWCI
- 25.13
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
