A grid for multidimensional and multivariate spatial representation and data processing
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[1] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[2] Ben Evans,et al. The Australian Geoscience Data Cube - foundations and lessons learned , 2017 .
[3] Adam Lewis,et al. Rapid, high-resolution detection of environmental change over continental scales from satellite data – the Earth Observation Data Cube , 2016, Int. J. Digit. Earth.
[4] Kuang‐An Chang,et al. Experimental study on plunging breaking waves in deep water , 2015 .
[5] Prasanth H. Nair,et al. Astropy: A community Python package for astronomy , 2013, 1307.6212.
[6] Lion Krischer,et al. ObsPy: A Python Toolbox for Seismology , 2010 .
[7] Bo Sun,et al. Bedmap2: improved ice bed, surface and thickness datasets for Antarctica , 2012 .
[8] Lion Krischer,et al. ObsPy – What can it do for data centers and observatories? , 2011 .
[9] Konrad Hinsen,et al. A data and code model for reproducible research and executable papers , 2011, ICCS.
[10] Russ Rew,et al. NetCDF: an interface for scientific data access , 1990, IEEE Computer Graphics and Applications.
[11] Gaël Varoquaux,et al. Mayavi: 3D Visualization of Scientific Data , 2010, Computing in Science & Engineering.
[12] John D. Hunter,et al. Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.
[13] Gaël Varoquaux,et al. The NumPy Array: A Structure for Efficient Numerical Computation , 2011, Computing in Science & Engineering.
[14] Leonardo Uieda. Verde: Processing and gridding spatial data using Green's functions , 2018, J. Open Source Softw..