Usage¶
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.
Use an included scenario¶
from pymagicc.scenarios import rcp26
rcp26.head()
Read a MAGICC scenario file¶
from pymagicc.scenarios import read_scen_file
scenario = read_scen_file("PATHWAY.SCEN")
Run MAGICC for a scenario¶
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))
)
Using a different MAGICC version¶
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 test
Or in a script:
#!/bin/bash
export MAGICC_EXECUTABLE_7=tmp/magicc/run/magicc.exe
make test