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Pymagicc is a Python wrapper around the reduced complexity climate model MAGICC6. It wraps the CC-BY-NC-SA licensed MAGICC6 binary. Pymagicc itself is BSD-3 licensed.
MAGICC (Model for the Assessment of Greenhouse Gas Induced Climate Change) is widely used in the assessment of future emissions pathways in climate policy analyses, e.g. in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change or to model the physical aspects of climate change in Integrated Assessment Models (IAMs).
Pymagicc makes the MAGICC model easily installable and usable from Python and allows for the easy modification of all MAGICC model parameters and emissions scenarios directly from Python. In climate research it can, for example, be used in the analysis of mitigation scenarios, in Integrated Assessment Models, complex climate model emulation, and uncertainty analyses, as well as in climate science education and communication.
See www.magicc.org and Meinshausen et al. 2011 for further information.
import matplotlib.pyplot as plt
import pymagicc
import scmdata
from pymagicc import rcps
results = []
for scen in rcps.groupby("scenario"):
results_scen = pymagicc.run(scen)
results.append(results_scen)
results = scmdata.run_append(results)
temperature_rel_to_1850_1900 = (
results
.filter(variable="Surface Temperature", region="World")
.relative_to_ref_period_mean(year=range(1850, 1900 + 1))
)
temperature_rel_to_1850_1900.lineplot()
plt.title("Global Mean Temperature Projection")
plt.ylabel("°C over pre-industrial (1850-1900 mean)");
# Run `plt.show()` to display the plot when running this example
# interactively or add `%matplotlib inline` on top when in a Jupyter Notebook.
For more example usage see this Jupyter Notebook. Thanks to the Binder project the Notebook can be run and modified without installing anything locally.
pip install pymagicc
On Linux and OS X the original compiled Windows binary available on http://www.magicc.org/ and included in Pymagicc can run using Wine.
On modern 64-bit systems one needs to use the 32-bit version of Wine
sudo dpkg --add-architecture i386 sudo apt-get install wine32
On 32-bit systems Debian/Ubuntu-based systems wine can be installed with
sudo apt-get install wine
On OS X wine is available in the Homebrew package manager:
brew install wine
It should also be available in other package managers, as well as directly from the Wine project.
Note that after the first install the first run of Pymagicc might be slow due to setting up of the wine configuration and be accompanied by pop-ups or debug output.
To run an example session using Jupyter Notebook and Python 3 you can run the
following commands to create a virtual environment venv and install an
editable version for local development:
git clone https://github.com/openscm/pymagicc.git
cd pymagicc
make venv
./venv/bin/pip install --editable .
./venv/bin/jupyter-notebook notebooks/Example.ipynbFor local development, install dependencies and an editable version of Pymagicc from a clone or download of the Pymagicc repository with
make venv ./venv/bin/pip install --editable .
To run the tests run
./venv/bin/pytest tests --verbose
To skip tests which run MAGICC and take longer use
./venv/bin/pytest tests --skip-slow
To get a test coverage report, run
./venv/bin/pytest --cov
To unify coding style, allowing us to focus more on writing useful code and less time worrying about formatting, black is used.
To format the files in pymagicc and tests as well as setup.py run
make black
In our miscellaneous csv's, for example the definitional csv's, we follow the following conventions to make our lives easier:
- column names are all lower case, with underscores as separators (i.e. no spaces)
A user of pymagicc should be able to pip install and run all of our notebooks. This means that all of the libraries for running notebooks should be explicit dependencies, rather than being included in an extras requirement. Whilst this means that we have more dependencies, it makes it easier for end users and avoids extremely cryptic import errors.
The docs use Sphinx and can be rebuilt locally in docs/builds/html/ with
make docs
from pymagicc.scenarios import rcp26
rcp26.head()from pymagicc.scenarios import read_scen_file
scenario = read_scen_file("PATHWAY.SCEN")import pymagicc
from pymagicc.scenarios import read_scen_file
scenario = read_scen_file("PATHWAY.SCEN")
results = pymagicc.run(scenario)
temperature_rel_to_1850_1900 = (
results
.filter(variable="Surface Temperature")
.relative_to_ref_period_mean(year=range(1850, 1900 + 1))
)A custom version of MAGICC may be used with pymagicc using the
MAGICC_EXECUTABLE_6 and MAGICC_EXECUTABLE_7 environment variables for MAGICC6
and MAGICC7 respectively. These environment variables should be set to the
location of the magicc executable (either magicc for linux/mac or
magicc.exe for Windows).
For example, a custom MAGICC7 folder located at /tmp/magicc can be used on
under Linux by setting MAGICC_EXECUTABLE_7 to /tmp/magicc/run/magicc.
Example usage in Bash:
MAGICC_EXECUTABLE_7=/tmp/magicc/run/magicc.exe make testOr in a script:
#!/bin/bash
export MAGICC_EXECUTABLE_7=tmp/magicc/run/magicc.exe
make testPlease report issues or discuss feature requests on Pymagicc's issue tracker.
You can also contact the pymagicc authors via email: mailto:[email protected],[email protected]
The compiled MAGICC binary by Tom Wigley, Sarah Raper, and Malte Meinshausen included in this package is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
See also the MAGICC website and Wiki for further information.
The pymagicc wrapper itself is released under a BSD-3 license. For details, see LICENSE.
If you make any use of MAGICC, its license requires citing of:
M. Meinshausen, S. C. B. Raper and T. M. L. Wigley (2011). "Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6: Part I "Model Description and Calibration." Atmospheric Chemistry and Physics 11: 1417-1456. https://doi.org/10.5194/acp-11-1417-2011
If you use Pymagicc in your research, please additionally cite
R. Gieseke, S. N. Willner and M. Mengel, (2018). Pymagicc: A Python wrapper for the simple climate model MAGICC. Journal of Open Source Software, 3(22), 516, https://doi.org/10.21105/joss.00516
For proper reproducibility please reference the version of Pymagicc used. In Python it can be printed with
import pymagicc
print(pymagicc.__version__)Pymagicc releases are archived at Zenodo and the version used should also be cited. See https://doi.org/10.5281/zenodo.1111815.