The open-source Python package pyam provides a suite of tools and functions for analyzing and visualizing input data (i.e., assumptions/parametrization) and results (model output) of integrated-assessment models, macro-energy scenarios, energy systems analysis, and sectoral studies.
The comprehensive documentation is hosted on Read the Docs!
- Simple analysis of scenario timeseries data with an interface similar in feel & style to the widely used pandas.DataFrame
- Advanced visualization and plotting functions (see the gallery)
- Scripted validation and processing of scenario data and results
The pyam package was initially developed to work with the IAMC template, a timeseries format for yearly data developed and used by the Integrated Assessment Modeling Consortium (IAMC).
| model | scenario | region | variable | unit | 2005 | 2010 | 2015 |
|---|---|---|---|---|---|---|---|
| MESSAGE | CD-LINKS 400 | World | Primary Energy | EJ/y | 462.5 | 500.7 | ... |
| ... | ... | ... | ... | ... | ... | ... | ... |
An illustration of the IAMC template using a scenario
from the CD-LINKS project
via the The IAMC 1.5°C Scenario Explorer
The package also supports timeseries data with a sub-annual time resolution:
- Continuous-time data using the Python datetime format
- "Representative timeslices" (e.g., "winter-night", "summer-day") using the pyam extra-columns feature
Read the docs for more information about the pyam data model or look at the data-table tutorial to see how to cast from a variety of timeseries formats to a pyam.IamDataFrame.
An introduction to the basic functions is shown in the "first-steps" notebook.
All tutorials are available in rendered format (i.e., with output) as part of the online documentation. The source code of the tutorials notebooks is available in the folder doc/source/tutorials of this repository.
The comprehensive documentation is hosted on Read the Docs.
The documentation pages can be built locally, refer to the instruction in doc/README.
This package was initiated and is currently maintained by Matthew Gidden (@gidden) and Daniel Huppmann (@danielhuppmann).
See the complete list of contributors.
Copyright 2017-2021 IIASA and the pyam developer team
The pyam package is licensed
under the Apache License, Version 2.0 (the "License");
see LICENSE and NOTICE for details.
For basic instructions, please read the docs!
To install from source (including all dependencies) after cloning this repository, simply run
pip install --editable .[tests,optional-io-formats,tutorials]
To check that the package was installed correctly, run
pytest tests