Documentation: http://software.ene.iiasa.ac.at/pyam Questions? Start a discussion on our listserv
The pyam package provides a range of diagnostic tools and functions
for analyzing and working with IAMC-format timeseries data.
Features:
- Summary of models, scenarios, variables, and regions included in a snapshot.
- Display of timeseries data as pandas.DataFrame with IAMC-specific filtering options.
- Simple visualization and plotting functions.
- Diagnostic checks for non-reported variables or timeseries data to identify outliers and potential reporting issues.
- Categorization of scenarios according to timeseries data or meta-identifiers for further analysis.
The package can be used with timeseries data that follows the data template convention of the Integrated Assessment Modeling Consortium (IAMC). An illustrative example is shown below; see data.ene.iiasa.ac.at/database for more information.
| model | scenario | region | variable | unit | 2005 | 2010 | 2015 |
|---|---|---|---|---|---|---|---|
| MESSAGE V.4 | AMPERE3-Base | World | Primary Energy | EJ/y | 454.5 | 479.6 | ... |
| ... | ... | ... | ... | ... | ... | ... | ... |
A comprehensive tutorial for the basic functions is included in the first tutorial using a partial snapshot of the IPCC AR5 scenario database.
The documentation pages can be built locally. See the instruction in doc/README.
This package was developed and is currently maintained by Matthew Gidden (@gidden) and Daniel Huppmann (@danielhuppmann).
Copyright 2017-2018 IIASA Energy Program
The pyam package is licensed
under the Apache License, Version 2.0 (the "License");
see LICENSE and NOTICE for details.
For basic instructions see our website.
To install from source after cloning this repository, simply run
pip install -e .
To setup a development environment, the simplest route is to make yourself
a conda environment and then follow the Makefile.
# pyam can be replaced with any other name
# you don't have to specify your python version if you don't want
conda create --name pyam pip python=X.Y.Z
conda activate pyam # may be simply `source activate pyam` or just `activate pyam`
# use the make file to create your development environment
# (you only require the -B flag the first time, thereafter you can
# just run `make virtual-environment` and it will only update if
# environment definition files have been updaed)
make -B virtual-environmentTo check everything has installed correctly,
pytest tests
All the tests should pass.