EGU2020-9177
https://doi.org/10.5194/egusphere-egu2020-9177
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Open and reproducible science: from theory to equations, algorithms and plots

Stan Schymanski1,3 and Jiří Kunčar2,3
Stan Schymanski and Jiří Kunčar
  • 1Catchment and Eco-Hydrology, ERIN, Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg (stanislaus.schymanski@list.lu)
  • 2Datadog Inc.
  • 3Swiss Data Science Center, ETH Zurich, Zurich, Switzerland

Scientific theory is commonly formulated in the form of mathematical equations and new theory is often derived from a set of pre-existing equations. Most of us have experienced difficulty in following mathematical derivations in scientific publications and even more so their transfer into numerical algorithms that eventually result in quantitative tests and data plots. The Python package Environmental Science using Symbolic Math (ESSM, https://github.com/environmentalscience/essm) offers an open and transparent way to (a) verify derivations in the literature, (b) ensure dimensional consistency of the equations, (c) perform symbolic derivations, and (d) transfer mathematical equations into numerical code, perform computations and (e) generate plots.

Here we present an example workflow using jupyter notebooks illustrating the capabilities of the package from (a) to (e), including recently added advanced features.

How to cite: Schymanski, S. and Kunčar, J.: Open and reproducible science: from theory to equations, algorithms and plots, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9177, https://doi.org/10.5194/egusphere-egu2020-9177, 2020

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