Scientific references¶
Matthew Gidden and Daniel Huppmann. pyam: a Python package for the analysis and visualization of models of the interaction of climate, human, and environmental systems. Journal of Open Source Software (JOSS), 4(33):1095, 2019. doi:10.21105/joss.01095.
John D. Hunter. Matplotlib: a 2d graphics environment. Computing in Science & Engineering, 9(3):90–95, 2007. doi:10.1109/MCSE.2007.55.
Daniel Huppmann, Matthew Gidden, Zebedee Nicholls, Jonas Hörsch, Robin Lamboll, Paul Natsuo Kishimoto, Thorsten Burandt, Oliver Fricko, Edward Byers, Jarmo Kikstra, Maarten Brinkerink, Maik Budzinski, Florian Maczek, Sebastian Zwickl-Bernhard, Lara Welder, Erik Francisco Álvarez Quispe, and Christopher J. Smith. pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios. Open Research Europe, 2021. doi:10.12688/openreseurope.13633.1.
Daniel Huppmann, Elmar Kriegler, Volker Krey, Keywan Riahi, Joeri Rogelj, Katherine Calvin, Florian Humpenoeder, Alexander Popp, Steven K. Rose, John Weyant, and et al. IAMC 1.5 °C Scenario Explorer and Data hosted by IIASA (release 2.0). Integrated Assessment Modeling Consortium & International Institute for Applied Systems Analysis, 2019. URL: https://data.ece.iiasa.ac.at/iamc-1.5c-explorer, doi:10.5281/zenodo.3363345.
Wes McKinney. Data structures for statistical computing in python. In Stefan van der Walt and Jarrod Millman, editors, Proceedings of the 9th Python in Science Conference, 51–56. 2012.
Travis Oliphant. NumPy: a guide to NumPy. USA: Trelgol Publishing, 2006. URL: http://www.numpy.org/.
