def test_testing_make_scenario(test_mp):
"""Check the model creation functions in message_ix.testing."""
# MESSAGE-scheme Dantzig problem can be created
scen = make_dantzig(test_mp, True)
assert isinstance(scen, Scenario)
# Multi-year variant can be created
scen = make_dantzig(test_mp, solve=True, multi_year=True)
assert isinstance(scen, Scenario)
# Westeros model can be created
scen = make_westeros(test_mp, solve=True)
assert isinstance(scen, Scenario)
def test_cli_export_test_data(monkeypatch, session_context, mix_models_cli,
tmp_path):
"""The :command:`export-test-data` command can be invoked."""
# Create an empty scenario in the temporary local file database
platform = "local"
mp = ixmp.Platform(platform)
scen = make_dantzig(mp)
# URL
url = f"ixmp://{platform}/{scen.model}/{scen.scenario}#{scen.version}"
# Monkeypatch MESSAGE_DATA_PATH in case tests are being performed on a system
# without message_data installed
monkeypatch.setattr(util.common, "MESSAGE_DATA_PATH", tmp_path)
tmp_path.joinpath("data", "tests").mkdir(exist_ok=True, parents=True)
# File that will be created
technology = ["coal_ppl"]
dest_file = util.private_data_path(
"tests", f"{scen.model}_{scen.scenario}_{'_'.join(technology)}.xlsx")
# Release the database lock
mp.close_db()
try:
# Export works
result = mix_models_cli.assert_exit_0(
[f"--url={url}", "export-test-data"])
# The file is created in the expected location
assert str(dest_file) in result.output
assert dest_file.exists()
finally:
# Remove this temporary file
dest_file.unlink()
def test_run_clone(tmpdir):
# this test is designed to cover the full functionality of the GAMS API
# - initialize a new ixmp platform instance
# - create a new scenario based on Dantzigs tutorial transport model
# - solve the model and read back the solution from the output
# - perform tests on the objective value and the timeseries data
mp = Platform(driver='hsqldb', path=tmpdir / 'db')
scen = make_dantzig(mp, solve=True)
assert np.isclose(scen.var('OBJ')['lvl'], 153.675)
assert scen.firstmodelyear == 1963
pdt.assert_frame_equal(scen.timeseries(iamc=True), TS_DF)
# cloning with `keep_solution=True` keeps all timeseries and the solution
# (same behaviour as `ixmp.Scenario`)
scen2 = scen.clone(keep_solution=True)
assert np.isclose(scen2.var('OBJ')['lvl'], 153.675)
assert scen2.firstmodelyear == 1963
pdt.assert_frame_equal(scen2.timeseries(iamc=True), TS_DF)
# cloning with `keep_solution=False` drops the solution and only keeps
# timeseries set as `meta=True` or prior to the first model year
# (DIFFERENT behaviour from `ixmp.Scenario`)
scen3 = scen.clone(keep_solution=False)
assert np.isnan(scen3.var('OBJ')['lvl'])
assert scen3.firstmodelyear == 1963
pdt.assert_frame_equal(scen3.timeseries(iamc=True), TS_DF_CLEARED)
def test_reporter_from_dantzig(test_mp):
scen = make_dantzig(test_mp, solve=True)
# Reporter.from_scenario can handle Dantzig example model
rep = Reporter.from_scenario(scen)
# Default target can be calculated
rep.get("all")
def test_year_int(test_mp):
scen = make_dantzig(test_mp, solve=True, multi_year=True)
# Dimensions indexed by 'year' are returned as integers for all item types
assert scen.set("cat_year").dtypes["year"] == "int"
assert scen.par("demand").dtypes["year"] == "int"
assert scen.par("bound_activity_up").dtypes["year_act"] == "int"
assert scen.var("ACT").dtypes["year_vtg"] == "int"
assert scen.equ("COMMODITY_BALANCE_GT").dtypes["year"] == "int"
def test_year_int(test_mp):
scen = make_dantzig(test_mp, solve=True, multi_year=True)
# Dimensions indexed by 'year' are returned as integers for all item types
assert scen.set('cat_year').dtypes['year'] == 'int'
assert scen.par('demand').dtypes['year'] == 'int'
assert scen.par('bound_activity_up').dtypes['year_act'] == 'int'
assert scen.var('ACT').dtypes['year_vtg'] == 'int'
assert scen.equ('COMMODITY_BALANCE_GT').dtypes['year'] == 'int'
def test_shift_first_model_year(test_mp):
scen = make_dantzig(test_mp, solve=True, multi_year=True)
# assert that `historical_activity` is empty in the source scenario
assert scen.par('historical_activity').empty
# clone and shift first model year
clone = scen.clone(shift_first_model_year=1964)
# check that solution and timeseries in new model horizon have been removed
assert np.isnan(clone.var('OBJ')['lvl'])
pdt.assert_frame_equal(clone.timeseries(iamc=True), TS_DF_SHIFT)
assert clone.firstmodelyear == 1964
# check that the variable `ACT` is now the parameter `historical_activity`
assert not clone.par('historical_activity').empty
def test_run_remove_solution(test_mp):
# create a new instance of the transport problem and solve it
scen = make_dantzig(test_mp, solve=True)
assert np.isclose(scen.var('OBJ')['lvl'], 153.675)
# check that re-solving the model will raise an error if a solution exists
pytest.raises(ValueError, scen.solve)
# check that removing solution with a first-model-year arg raises an error
# (DIFFERENT behaviour from `ixmp.Scenario`)
pytest.raises(TypeError, scen.remove_solution, first_model_year=1964)
# check that removing solution does not delete timeseries data
# before first model year (DIFFERENT behaviour from `ixmp.Scenario`)
scen.remove_solution()
assert scen.firstmodelyear == 1963
pdt.assert_frame_equal(scen.timeseries(iamc=True), TS_DF_CLEARED)
def test_shift_first_model_year(test_mp):
scen = make_dantzig(test_mp, solve=True, multi_year=True)
# assert that `historical_activity` is empty in the source scenario
assert scen.par("historical_activity").empty
# clone and shift first model year
clone = scen.clone(shift_first_model_year=1964)
exp = TS_DF.copy()
exp.loc[0, 1964] = np.nan
exp["scenario"] = "multi-year"
# check that solution and timeseries in new model horizon have been removed
assert np.isnan(clone.var("OBJ")["lvl"])
assert_frame_equal(exp, clone.timeseries(iamc=True))
assert clone.firstmodelyear == 1964
# check that the variable `ACT` is now the parameter `historical_activity`
assert not clone.par("historical_activity").empty
def test_multi_db_run(tmpdir):
# create a new instance of the transport problem and solve it
mp1 = Platform(driver="hsqldb", path=tmpdir / "mp1")
scen1 = make_dantzig(mp1, solve=True)
mp2 = Platform(driver="hsqldb", path=tmpdir / "mp2")
# add other unit to make sure that the mapping is correct during clone
mp2.add_unit("wrong_unit")
mp2.add_region("wrong_region", "country")
# check that cloning across platforms must copy the full solution
dest = dict(platform=mp2)
pytest.raises(NotImplementedError,
scen1.clone,
keep_solution=False,
**dest)
pytest.raises(NotImplementedError,
scen1.clone,
shift_first_model_year=1964,
**dest)
# clone solved model across platforms (with default settings)
scen1.clone(platform=mp2, keep_solution=True)
# close the db to ensure that data and solution of the clone are saved
mp2.close_db()
del mp2
# reopen the connection to the second platform and reload scenario
_mp2 = Platform(driver="hsqldb", path=tmpdir / "mp2")
scen2 = Scenario(_mp2, **SCENARIO["dantzig"])
assert_multi_db(mp1, _mp2)
# check that sets, variables and parameter were copied correctly
npt.assert_array_equal(scen1.set("node"), scen2.set("node"))
scen2.firstmodelyear == 1963
assert_frame_equal(scen1.par("var_cost"), scen2.par("var_cost"))
assert np.isclose(scen2.var("OBJ")["lvl"], 153.675)
assert_frame_equal(scen1.var("ACT"), scen2.var("ACT"))
# check that custom unit, region and timeseries are migrated correctly
assert_frame_equal(scen2.timeseries(iamc=True), TS_DF)
def test_from_scenario(self, test_context):
"""ScenarioInfo initialized from an existing Scenario."""
mp = test_context.get_platform()
scenario = make_dantzig(mp, multi_year=True)
# ScenarioInfo can be initialized from the scenario
info = ScenarioInfo(scenario)
# Shorthand properties
assert_frame_equal(
pd.DataFrame(
[
[1962, 1963],
[1962, 1964],
[1962, 1965],
[1963, 1963],
[1963, 1964],
[1963, 1965],
[1964, 1964],
[1964, 1965],
[1965, 1965],
],
columns=["year_vtg", "year_act"],
),
info.yv_ya,
)
assert [
"World",
"seattle",
"san-diego",
"new-york",
"chicago",
"topeka",
] == info.N
assert 1963 == info.y0
assert [1963, 1964, 1965] == info.Y
def test_multi_db_run(tmpdir):
# create a new instance of the transport problem and solve it
mp1 = Platform(tmpdir / 'mp1', dbtype='HSQLDB')
scen1 = make_dantzig(mp1, solve=True)
mp2 = Platform(tmpdir / 'mp2', dbtype='HSQLDB')
# add other unit to make sure that the mapping is correct during clone
mp2.add_unit('wrong_unit')
mp2.add_region('wrong_region', 'country')
# check that cloning across platforms must copy the full solution
dest = dict(platform=mp2)
pytest.raises(ValueError, scen1.clone, keep_solution=False, **dest)
pytest.raises(ValueError, scen1.clone, shift_first_model_year=1964, **dest)
# clone solved model across platforms (with default settings)
scen1.clone(platform=mp2, keep_solution=True)
# close the db to ensure that data and solution of the clone are saved
mp2.close_db()
del mp2
# reopen the connection to the second platform and reload scenario
_mp2 = Platform(tmpdir / 'mp2', dbtype='HSQLDB')
scen2 = Scenario(_mp2, **models['dantzig'])
assert_multi_db(mp1, _mp2)
# check that sets, variables and parameter were copied correctly
npt.assert_array_equal(scen1.set('node'), scen2.set('node'))
scen2.firstmodelyear == 1963
pdt.assert_frame_equal(scen1.par('var_cost'), scen2.par('var_cost'))
assert np.isclose(scen2.var('OBJ')['lvl'], 153.675)
pdt.assert_frame_equal(scen1.var('ACT'), scen2.var('ACT'))
# check that custom unit, region and timeseries are migrated correctly
pdt.assert_frame_equal(scen2.timeseries(iamc=True), TS_DF)
def message_test_mp(test_mp):
make_dantzig(test_mp)
make_dantzig(test_mp, multi_year=True)
yield test_mp
def scenario(test_context):
mp = test_context.get_platform()
yield make_dantzig(mp)
