def test_inplace(PM_ds_initialized_1d, PM_ds_control_1d):
"""Tests that inplace operations do not work."""
pm = PerfectModelEnsemble(PM_ds_initialized_1d)
# Adding a control.
pm.add_control(PM_ds_control_1d)
with_ctrl = pm.add_control(PM_ds_control_1d)
assert pm != with_ctrl
# Adding an uninitialized ensemble.
pm = pm.add_control(PM_ds_control_1d)
pm.generate_uninitialized()
with_uninit = pm.generate_uninitialized()
assert pm != with_uninit
# Applying arbitrary func.
pm.sum("init")
summed = pm.sum("init")
assert pm != summed
def test_HindcastEnsemble_as_PerfectModelEnsemble(hindcast_recon_1d_mm):
"""Test that initialized dataset for HindcastEnsemble can also be used for
PerfectModelEnsemble."""
v = "SST"
alignment = "maximize"
hindcast = hindcast_recon_1d_mm
assert (not hindcast.verify(
metric="acc", comparison="e2o", dim="init",
alignment=alignment)[v].isnull().any())
# try PerfectModelEnsemble predictability
init = hindcast.get_initialized()
pm = PerfectModelEnsemble(init)
assert (not pm.verify(metric="acc",
comparison="m2e",
dim=["member", "init"])[v].isnull().any())
pm = pm.add_control(
init.isel(member=0, lead=0, drop=True).rename({
"init": "time"
}).resample(time="1MS").interpolate("linear"))
pm = pm.generate_uninitialized()
assert (not pm.verify(
metric="acc",
comparison="m2e",
dim=["member", "init"],
reference=["uninitialized"],
)[v].isnull().any())
pm.bootstrap(iterations=2,
metric="acc",
comparison="m2e",
dim=["member", "init"])
def test_PerfectModelEnsemble_plot(PM_ds_initialized_1d, PM_ds_control_1d,
variable, show_members, cmap):
"""Test PredictionEnsemble.plot()."""
pm = PerfectModelEnsemble(PM_ds_initialized_1d)
kws = {"cmap": cmap, "show_members": show_members, "variable": variable}
pm.plot(**kws)
pm = pm.add_control(PM_ds_control_1d)
pm.plot(**kws)
pm = pm.generate_uninitialized()
pm.plot(**kws)
class GeneratePerfectModelEnsemble(GenerateHindcastEnsemble):
"""Generate `PerfectModelEnsemble` out of `HindcastEnsemble`."""
def setup(self, *args, **kwargs):
self.get_data()
self.PredictionEnsemble = PerfectModelEnsemble(
self.initialized).add_control(self.observations)
self.PredictionEnsemble = self.PredictionEnsemble.generate_uninitialized(
)
self.reference = None
self.resample_dim = "member"
self.iterations = ITERATIONS
class GeneratePerfectModelEnsembleSmall(GeneratePerfectModelEnsemble):
"""Generate single grid point `PerfectModelEnsemble`."""
def setup(self, *args, **kwargs):
self.get_data(spatial_res=360)
self.PredictionEnsemble = PerfectModelEnsemble(
self.initialized).add_control(self.observations)
self.PredictionEnsemble = self.PredictionEnsemble.generate_uninitialized(
)
self.alignment = None
self.reference = None
self.resample_dim = "member"
self.iterations = ITERATIONS
def test_compute_uninitialized(pm_ds_ds1d, pm_ds_control1d):
"""Test that compute uninitialized can be run for perfect model ensemble"""
pm = PerfectModelEnsemble(pm_ds_ds1d)
pm.add_control(pm_ds_control1d)
pm.generate_uninitialized()
pm.compute_uninitialized()
def test_generate_uninit(pm_ds_ds1d, pm_ds_control1d):
"""Test to see if uninitialized ensemble can be bootstrapped"""
pm = PerfectModelEnsemble(pm_ds_ds1d)
pm.add_control(pm_ds_control1d)
pm.generate_uninitialized()
def perfectModelEnsemble_initialized_control(PM_ds_initialized_1d,
PM_ds_control_1d):
"""PerfectModelEnsemble initialized with `initialized` and `control` xr.Dataset."""
pm = PerfectModelEnsemble(PM_ds_initialized_1d).add_control(
PM_ds_control_1d)
return pm.generate_uninitialized()