# data[].attributes.attachment_link.readable_text
Bladel, J. (1958). On Helmholtz's Theorem in Finite Regions. Midwestern Universities Research Association
Chandrasekhar, S. (1961). Hydrodynamic and hydromagnetic stability. International Series of Monographs on Physics. Oxford: Clarendon.
See discussion on page 622.
Gubbins, D., Roberts, P. H., (1987), "Magnetohydrodynamics of the Earth's core". In: A, J. (Ed.), Geomagnetism, v. 2, Academic Press, pp. 1-183, London.
Hector, B., & Hinderer, J. (2016). pyGrav, a Python-based program for handling and processing relative gravity data. Computers & geosciences, 91, 90-97.
Hole, M. J., & Appel, L. C. (2007). Fourier decomposition of magnetic perturbations in toroidal plasmas using singular value decomposition.
Plasma Physics and Controlled Fusion, 49(12), 1971.
Krieger, L., & Peacock, J. R. (2014). MTpy: A Python toolbox for magnetotellurics. Computers & geosciences, 72, 167-175.
Lehmann, L. T., Jardine, M. M., Vidotto, A. A., Mackay, D. H., See, V., Donati, J. F., ... & Petit, P. (2016). The energy budget of stellar magnetic fields: comparing nonpotential simulations and observations. Monthly Notices of the Royal Astronomical Society: Letters, 466(1), L24-L28.
Lin, J. W. (2012). "Why Python Is the Next Wave in Earth Sciences Computing." Bulletin of the American Meteorological Society, 93(12), pp. 1823-1824.
Morley, S. K., Welling, D. T., Koller, J., Larsen, B. A., & Henderson, M. G. (2010).
Spacepy-A Python-based library of tools for the space sciences (No. LA-UR-1004308; LA-UR-10-4308). Los Alamos National Lab. (LANL), Los Alamos,
NM (United States). K.W. Morton y D.F. Mayers, Numerical Solution of Partial Differential Equations, An Introduction. Cambridge University Press, 2005.
Oliphant, T. E. (2007). "Python for Scientific Computing," in Computing in Science & Engineering, vol. 9, no. 3, pp. 10-20, doi: 10.1109/MCSE.2007.58
Peng, R. D. (2011). Reproducible Research in Computational Science. Science 334, Issue 6060, pp. 1226-1227 DOI: 10.1126/science.1213847
Peña, D., Amit, H., & Pinheiro, K. J. (2016). Magnetic field stretching at the top of the shell of numerical dynamos. Earth, Planets and Space, 68(1), 78.
Peña, D. A. (2017). Magnetic field stretching at the top of the Earth's core. (Tesis de Doctorado). Observatório Nacional ON/MCTIC, Rio de Janeiro, Brasil
Peña, D., Amit, H., & Pinheiro, K. J. (2018). Deep magnetic field stretching in numerical dynamos. Progress in Earth and Planetary Science, 5(1), 8.
Perez, F., B. E. Granger, and J. D. Hunter. (2011). "Python: An Ecosystem for Scientific Computing." Computing in Science & Engineering, vol. 13, no. 2, pp. 13-21.
Rücker, C., Günther, T., & Wagner, F. M. (2017). pyGIMLi: An open-source library for modelling and inversion in geophysics.
Computers & Geosciences, 109, 106-123.
Sáenz, J., Zubillaga, J., & Fernández, J. (2002). Geophysical data analysis using Python. Computers & geosciences, 28(4), 457-465.
Shikuo, L., & Shida, L. (1997). Toroidal-Poloidal Decomposition and Beltrami Flows in Atmosphere Motions [J]. SCIENTIA ATMOSPHERICA SINICA, 2.
Uieda, L., V. C. Oliveira Jr., A. Ferreira, H. B. Santos, and J. F. Caparica Jr., 2014, Fatiando a Terra: A Python package for modeling and inversion in geophysics:
figshare, http://dx.doi. org/10.6084/m9.figshare.1115194.
Uieda, L. (2018). Verde: Processing and gridding spatial data using Green's functions. Journal of Open Source Software, 3(29), 957. doi:10.21105/joss.00957
Wassermann, J. M., Krischer, L., Megies, T., Barsch, R., & Beyreuther, M. (2013, December). Obspy: A python toolbox for seismology. In AGU Fall Meeting Abstracts.
Weiss, C. J. (2017) Scientific Computing for Chemists: An Undergraduate Course in Simulations, Data Processing, and Visualization. Journal of Chemical Education. 94 (5), 592-597. DOI: 10.1021/acs.jchemed.7b00078
Werthmüller, D. (2017). An open-source full 3D electromagnetic modeler for 1D VTI media in Python: empymod. Geophysics, 82(6), WB9-WB19.

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Diego Andrés Peña Arcos Docente de la Facultad de Ingenierías de la Universidad ECOTEC

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Python en el desarrollo de la computación científica – caso de aplicación: cálculo del componente toroidal del flujo de un fluido incompresible en coordenadas esféricas | REVISTA CIENTÍFICA ECOCIENCIA

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La computación científica se ha convertido en una de las principales herramientas para el desarrollo de la ciencia actual, convirtiéndose en una necesidad su aprendizaje y utilización. A pesar de esto, no todos los científicos son expertos programadores y sus investigaciones puede verse afectadas po…

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La microbit es una computadora de bolsillo que te presenta cómo el software y el hardware funcionan juntos. Tiene una pantalla de luz LED, botones, sensores y muchas características de entrada/salida que, al programarse, le permiten interactuar contigo y con tu mundo.

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el Microbit solo va a hacer lo que uno ordene y para esto hay que escribir un programa