pyam-iamc 0.11.0

Analysis & visualization of integrated-assessment scenarios

pyam: analysis & visualization
of integrated-assessment scenarios

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Overview and scope

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 scenarios.

Key features:

• Simple analysis of timeseries data in the IAMC format (more about it here) with an interface similar in feel and style to the widely used pandas.DataFrame
• Advanced visualization and plotting functions (see the gallery)
• Diagnostic checks for scripted validation of scenario data and results

The complete documentation is hosted on Read the Docs!

Data model

An illustrative example of the timeseries format developed by the Integrated Assessment Modeling Consortium (IAMC) is shown below. The row is taken from the IAMC 1.5°C scenario explorer, showing a scenario from the CD-LINKS project. Read the docs for more information on the IAMC format and the pyam data model.

model	scenario	region	variable	unit	2005	2010	2015
MESSAGE	CD-LINKS 400	World	Primary Energy	EJ/y	462.5	500.7	...
...	...	...	...	...	...	...	...

Tutorials

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.

Documentation

The complete documentation is hosted on Read the Docs.

The documentation pages can be built locally, refer to the instruction in doc/README.

Authors & Contributors

This package was initiated and is currently maintained by Matthew Gidden (@gidden) and Daniel Huppmann (@danielhuppmann).

See the complete list of contributors.

License

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.

Install

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