This package provides an interface for solving a Computable General Equilibrium (CGE) model in Python, using the package pyomo as the back end.
The aim of this package is to separate model analysis from model
definition. For a given a model definition, pycge provides a
common interface for analysis, including: generating model instances
with different data sets; modifying model instances to simulate "shocks";
solving model instances; and post-processing solutions (e.g., conducting
comparative statics).
python-3.x and pyomo 5.2
See ./docs/index.rst
A quick summary of a standard workflow::
# create model definition object
testdef = ModelDef()
# create pycge object
testcge = PyCGE(testdef)
# add data
testcge.load_data(path/to/data)
# create base instance
testcge.model_instance()
# calibrate base instance
testcge.model_calibrate(solver, mgr='')
# create sim instance to modify
testcge.model_sim()
# modify sim instance
testcge.model_modify_instance(...) # modify some value
testcge.model_modify_instnace(...) # modify another value
# solve sim instance
testcge.model_solve(solver, mgr='')
# compare base and sim equilibria
testcge.model_compare()
The package is maintained by Juan Fung <juan.fung@nist.gov>