def test_run_scenarios_multiple(self):
ts1_erf = np.linspace(0, 4, 101)
ts2_erf = np.sin(np.linspace(0, 4, 101))
inp = ScmRun(
data=np.vstack([ts1_erf, ts2_erf]).T,
index=np.linspace(1750, 1850, 101).astype(int),
columns={
"scenario": ["test_scenario_1", "test_scenario_2"],
"model": "unspecified",
"climate_model": "junk input",
"variable": "Effective Radiative Forcing",
"unit": "W/m^2",
"region": "World",
},
)
model = self.tmodel()
res = model.run_scenarios(inp)
for scenario_ts in inp.groupby("scenario"):
scenario = scenario_ts.get_unique_meta("scenario",
no_duplicates=True)
model.set_drivers(
scenario_ts.values.squeeze() *
ur(inp.get_unique_meta("unit", no_duplicates=True)))
model.reset()
model.run()
res_scen = res.filter(scenario=scenario)
npt.assert_allclose(
res_scen.filter(
variable="Surface Temperature|Upper").values.squeeze(),
model._temp_upper_mag,
)
assert (res.filter(
variable="Surface Temperature|Upper").get_unique_meta(
"unit", no_duplicates=True) == "delta_degC")
npt.assert_allclose(
res_scen.filter(
variable="Surface Temperature|Lower").values.squeeze(),
model._temp_lower_mag,
)
assert (res.filter(
variable="Surface Temperature|Lower").get_unique_meta(
"unit", no_duplicates=True) == "delta_degC")
npt.assert_allclose(
res_scen.filter(variable="Heat Uptake").values.squeeze(),
model._rndt_mag,
)
assert (res.filter(variable="Heat Uptake").get_unique_meta(
"unit", no_duplicates=True) == "W/m^2")
def _check_heat_content_heat_uptake_consistency(res):
hc_deltas = ScmRun(
res.filter(variable="Heat Content", region="World")
.timeseries(time_axis="year")
.diff(axis="columns")
)
hc_deltas["unit"] = "{} / yr".format(hc_deltas.get_unique_meta("unit", True))
ratio = hc_deltas.divide(
res.filter(variable="Heat Uptake", region="World"),
op_cols={"variable": "Heat Content / Heat Uptake"},
)
earth_surface_area = 5.100536e14
npt.assert_allclose(
earth_surface_area,
ratio.convert_unit("m^2").timeseries(drop_all_nan_times=True),
)