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Issue No.01 - January/February (2008 vol.10)
pp: 80-87
Michele Vallisneri , NASA Jet Propulsion Laboratory
ABSTRACT
To set up a mock data challenge, the authors needed to string together a lot of existing and new code. Here, they describe how Python and XML came to the rescue.
INDEX TERMS
Python, XML, agile computing, scientific programming
CITATION
Michele Vallisneri, "Python and XML for Agile Scientific Computing", Computing in Science & Engineering, vol.10, no. 1, pp. 80-87, January/February 2008, doi:10.1109/MCSE.2008.20
REFERENCES
1. J. Baker et al., eds. "LISA: Probing the Universe with Gravitational Waves," LISA Mission Science Office whitepaper, 2007; www.lisa-science.org/resources/talks-articles/ sciencelisa_science_case.pdf.
2. K.A. Arnaud et al., "An Overview of the Second round of the Mock LISA Data Challenges," Classical and Quantum Gravity, vol. 24, no. 19, 2007, pp. S551–S564.
3. T.L. Cottom, "Using SWIG to Bind C++ to Python," Computing in Science &Eng., vol. 5, no. 2, 2003, pp. 88–96.
4. Computing in Science &Eng., special issue on Python, vol. 9, no. 3, 2007.
5. G.K. Thiruvathukal, "XML and Computational Science," Computing in Science &Eng., vol. 6, no. 1, 2004, pp. 74–80.
6. G.K. Thiruvathukal and K. Laufer, "Natural XML for Data Binding, Processing, and Persistence," Computing in Science &Eng., vol. 6, no. 2, 2004, pp. 86–92.
7. T.E. Oliphant, "Python for Scientific Computing," Computing in Science &Eng., vol. 9, no. 3, 2007, pp. 10–20.
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