def make_dantzig(mp: Platform,
solve: bool = False,
quiet: bool = False) -> Scenario:
"""Return :class:`ixmp.Scenario` of Dantzig's canning/transport problem.
Parameters
----------
mp : .Platform
Platform on which to create the scenario.
solve : bool, optional
If :obj:`True`. then solve the scenario before returning. Default :obj:`False`.
quiet : bool, optional
If :obj:`True`, suppress console output when solving.
Returns
-------
.Scenario
See also
--------
.DantzigModel
"""
# add custom units and region for timeseries data
try:
mp.add_unit("USD/km")
except Exception:
# Unit already exists. Pending bugfix from zikolach
pass
mp.add_region("DantzigLand", "country")
# Initialize a new Scenario, and use the DantzigModel class' initialize()
# method to populate it
annot = "Dantzig's transportation problem for illustration and testing"
scen = Scenario(
mp,
**models["dantzig"], # type: ignore [arg-type]
version="new",
annotation=annot,
scheme="dantzig",
with_data=True,
)
# commit the scenario
scen.commit("Import Dantzig's transport problem for testing.")
# set this new scenario as the default version for the model/scenario name
scen.set_as_default()
if solve:
# Solve the model using the GAMS code provided in the `tests` folder
scen.solve(model="dantzig", case="transport_standard", quiet=quiet)
# add timeseries data for testing `clone(keep_solution=False)`
# and `remove_solution()`
scen.check_out(timeseries_only=True)
scen.add_timeseries(HIST_DF, meta=True)
scen.add_timeseries(INP_DF)
scen.commit("Import Dantzig's transport problem for testing.")
return scen
def test_timeseries_remove_single_entry(mp):
args_single = ('Douglas Adams', 'test_remove_single')
scen = Scenario(mp, *args_single, version='new', annotation='fo')
scen.add_timeseries(DATA['timeseries'].pivot_table(values='value',
index=IDX_COLS))
scen.commit('importing a testing timeseries')
scen = Scenario(mp, *args_single)
assert_timeseries(scen, DATA['timeseries'])
scen.check_out()
scen.remove_timeseries(DATA['timeseries'][DATA['timeseries'].year == 2010])
scen.commit('testing for removing a single timeseries data point')
exp = DATA['timeseries'][DATA['timeseries'].year == 2020]
assert_timeseries(scen, exp)
def test_timeseries_remove_single_entry(mp):
args_single = ("Douglas Adams", "test_remove_single")
scen = Scenario(mp, *args_single, version="new", annotation="fo")
scen.add_timeseries(DATA["timeseries"].pivot_table(values="value",
index=IDX_COLS))
scen.commit("importing a testing timeseries")
scen = Scenario(mp, *args_single)
assert_timeseries(scen, DATA["timeseries"])
scen.check_out()
scen.remove_timeseries(DATA["timeseries"][DATA["timeseries"].year == 2010])
scen.commit("testing for removing a single timeseries data point")
exp = DATA["timeseries"][DATA["timeseries"].year == 2020]
assert_timeseries(scen, exp)
def test_timeseries_remove_all_data(mp):
args_all = ('Douglas Adams', 'test_remove_all')
scen = Scenario(mp, *args_all, version='new', annotation='fo')
scen.add_timeseries(DATA['timeseries'].pivot_table(values='value',
index=IDX_COLS))
scen.commit('importing a testing timeseries')
scen = Scenario(mp, *args_all)
assert_timeseries(scen, DATA['timeseries'])
exp = DATA['timeseries'].copy()
exp['variable'] = 'Testing2'
scen.check_out()
scen.add_timeseries(exp)
scen.remove_timeseries(DATA['timeseries'])
scen.commit('testing for removing a full timeseries row')
assert scen.timeseries(region='World', variable='Testing').empty
assert_timeseries(scen, exp)
def test_timeseries_remove_all_data(mp):
args_all = ("Douglas Adams", "test_remove_all")
scen = Scenario(mp, *args_all, version="new", annotation="fo")
scen.add_timeseries(DATA["timeseries"].pivot_table(values="value",
index=IDX_COLS))
scen.commit("importing a testing timeseries")
scen = Scenario(mp, *args_all)
assert_timeseries(scen, DATA["timeseries"])
exp = DATA["timeseries"].copy()
exp["variable"] = "Testing2"
scen.check_out()
scen.add_timeseries(exp)
scen.remove_timeseries(DATA["timeseries"])
scen.commit("testing for removing a full timeseries row")
assert scen.timeseries(region="World", variable="Testing").empty
assert_timeseries(scen, exp)
def test_store_ts(request, caplog, test_mp):
# Computer and target scenario
c = Computer()
# Target scenario
model_name = __name__
scenario_name = "test scenario"
scen = Scenario(test_mp, model_name, scenario_name, version="new")
scen.commit("Empty scenario")
c.add("target", scen)
# Add test data to the Computer: a pd.DataFrame
input_1 = test_data[0].assign(variable="Foo")
c.add("input 1", input_1)
# A pyam.IamDataFrame
input_2 = test_data[2050].assign(variable="Bar")
c.add("input 2", pyam.IamDataFrame(input_2))
# Expected results: same as input, but with the `model` and `scenario` columns
# filled automatically.
expected_1 = input_1.assign(model=model_name, scenario=scenario_name)
expected_2 = input_2.assign(model=model_name, scenario=scenario_name)
# Task to update the scenario with the data
c.add("test 1", store_ts, "target", "input 1", "input 2")
# Scenario starts empty of time series data
assert 0 == len(scen.timeseries())
# The computation runs successfully
c.get("test 1")
# All rows from both inputs are present
assert len(input_1) + len(input_2) == len(scen.timeseries())
# Input is stored exactly
assert_frame_equal(expected_1, scen.timeseries(variable="Foo"))
assert_frame_equal(expected_2, scen.timeseries(variable="Bar"))
def test_error_message(self, test_data_path, test_mp):
"""GAMSModel.solve() displays a user-friendly message on error."""
# Empty Scenario
s = Scenario(test_mp, model="foo", scenario="bar", version="new")
s.commit("Initial commit")
# Expected paths for error message
paths = map(
lambda name: re.escape(str(test_data_path.joinpath(name))),
["_abort.lst", "default_in.gdx"],
)
with pytest.raises(
ModelError,
match="""GAMS errored with return code 2:
There was a compilation error
For details, see the terminal output above, plus:
Listing : {}
Input data: {}""".format(*paths),
):
s.solve(model_file=test_data_path / "_abort.gms",
use_temp_dir=False)
