def test_PredictionEnsemble_plot(
hind_ds_initialized_1d,
hist_ds_uninitialized_1d,
reconstruction_ds_1d,
observations_ds_1d,
variable,
show_members,
x,
):
"""Test PredictionEnsemble.plot()."""
he = HindcastEnsemble(hind_ds_initialized_1d)
kws = {"show_members": show_members, "variable": variable, "x": x}
he.plot(**kws)
he = he.add_uninitialized(hist_ds_uninitialized_1d)
he.plot(**kws)
he = he.add_observations(reconstruction_ds_1d)
he.plot(**kws)
he = he.add_observations(observations_ds_1d)
he.plot(**kws)
if x == "time":
pm = PerfectModelEnsemble(hind_ds_initialized_1d)
pm.plot(**kws)
pm = pm.add_control(hist_ds_uninitialized_1d.isel(member=0, drop=True))
pm.plot(**kws)
def test_calendar_matching_observations(hind_ds_initialized_1d,
reconstruction_ds_1d):
"""Tests that error is thrown if calendars mismatch when adding observations."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
reconstruction_ds_1d["time"] = xr.cftime_range(
start="1950",
periods=reconstruction_ds_1d.time.size,
freq="MS",
calendar="all_leap",
)
with pytest.raises(ValueError, match="does not match"):
hindcast.add_observations(reconstruction_ds_1d)
def test_verify(hind_ds_initialized_1d, reconstruction_ds_1d,
observations_ds_1d):
"""Test to see if verify can be run from the HindcastEnsemble"""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(reconstruction_ds_1d,
'reconstruction')
hindcast = hindcast.add_observations(observations_ds_1d, 'observations')
# Don't need to check for NaNs, etc. since that's handled in the prediction
# module testing.
hindcast.verify() # compute over all observations
hindcast.verify('reconstruction') # compute over single observation
# test all keywords
hindcast.verify(metric='rmse', comparison='m2o')
def make_climpred_hindcast_object(hindcast, observations):
"""
This function takes a hindcasting dataset of streamflow as well as associated
observations and creates a hindcasting object that can be used by the
climpred toolbox for hindcast verification.
Parameters
----------
hindcast : xarray.Dataset
The hindcasting streamflow data for a given period
observations : xarray.Dataset
The streamflow observations that are used to verify the hindcasts
Returns
-------
hindcast_obj : climpred.HindcastEnsemble object
The hindcast ensemble formatted to be used in climpred.
"""
# Todo: Add verification that the variable names are the same
# Todo: Add verification of sizes, catch and return message.
# Make the hindcastEnsemble object for the hindcast data
hindcast_obj = HindcastEnsemble(hindcast)
# Add the observations to that hindcastEnsemble object for verification.
hindcast_obj = hindcast_obj.add_observations(observations)
return hindcast_obj
def test_verify_single(hind_ds_initialized_1d, reconstruction_ds_1d):
"""Test to see if verify automatically works with a single observational
product."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(reconstruction_ds_1d,
'reconstruction')
hindcast.verify()
def test_inplace(hind_ds_initialized_1d, reconstruction_ds_1d,
hist_ds_uninitialized_1d):
"""Tests that inplace operations do not work."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
# Adding observations.
hindcast.add_observations(reconstruction_ds_1d, 'FOSI')
with_obs = hindcast.add_observations(reconstruction_ds_1d, 'FOSI')
assert hindcast != with_obs
# Adding an uninitialized ensemble.
hindcast.add_uninitialized(hist_ds_uninitialized_1d)
with_uninit = hindcast.add_uninitialized(hist_ds_uninitialized_1d)
assert hindcast != with_uninit
# Applying arbitrary func.
hindcast.sum('init')
summed = hindcast.sum('init')
assert hindcast != summed
def test_isel_xarray_func(hind_ds_initialized_1d, reconstruction_ds_1d):
"""Test whether applying isel to the objects works."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(reconstruction_ds_1d, 'FOSI')
hindcast = hindcast.isel(lead=0, init=slice(0, 3)).isel(time=slice(5, 10))
assert hindcast.get_initialized().init.size == 3
assert hindcast.get_initialized().lead.size == 1
assert hindcast.get_observations('FOSI').time.size == 5
def test_hindcastEnsemble_operator_different_datasets(hind_ds_initialized_1d,
observations_ds_1d):
"""Test that HindcastEnsemble math operator (+-*/) on HindcastEnsemble."""
he = HindcastEnsemble(hind_ds_initialized_1d)
he = he.add_observations(observations_ds_1d)
he2 = HindcastEnsemble(hind_ds_initialized_1d)
assert not (he2 - he).equals(he2)
assert not (he - he2).equals(he)
def hindcast_recon_3d(hind_ds_initialized_3d, reconstruction_ds_3d):
"""HindcastEnsemble initialized with `initialized`, `reconstruction`(`recon`)."""
hindcast = HindcastEnsemble(hind_ds_initialized_3d)
hindcast = hindcast.add_observations(reconstruction_ds_3d)
hindcast = hindcast - hindcast.sel(
time=slice("1964", "2014")).mean("time").sel(
init=slice("1964", "2014")).mean("init")
return hindcast
def test_verify(hind_ds_initialized_1d, reconstruction_ds_1d):
"""Test to see if verify automatically works."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(reconstruction_ds_1d)
hindcast.verify(metric="acc",
comparison="e2o",
dim="init",
alignment="same_verif")
def test_get_observations(hind_ds_initialized_1d, reconstruction_ds_1d):
"""Tests whether get_observations method works."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(reconstruction_ds_1d, 'FOSI')
# Without name keyword.
obs = hindcast.get_observations()
assert obs == hindcast._datasets['observations']['FOSI']
# With name keyword.
obs = hindcast.get_observations('FOSI')
assert obs == hindcast._datasets['observations']['FOSI']
def test_HindcastEnsemble_plot(
hind_ds_initialized_1d,
hist_ds_uninitialized_1d,
reconstruction_ds_1d,
observations_ds_1d,
variable,
show_members,
cmap,
):
"""Test PredictionEnsemble.plot()."""
he = HindcastEnsemble(hind_ds_initialized_1d)
kws = {"cmap": cmap, "show_members": show_members, "variable": variable}
he.plot(**kws)
he = he.add_uninitialized(hist_ds_uninitialized_1d)
he.plot(**kws)
he = he.add_observations(reconstruction_ds_1d)
he.plot(**kws)
he = he.add_observations(observations_ds_1d)
he.plot(**kws)
def hindcast_recon_1d_mm(hindcast_recon_1d_ym, reconstruction_ds_1d_mm):
"""HindcastEnsemble with initialized and reconstruction (observations) as a monthly
observational and initialized time series (no grid)."""
hind = hindcast_recon_1d_ym.get_initialized().sel(
init=slice("1964", "1970"))
del hind.coords["valid_time"]
hind["lead"].attrs["units"] = "months"
hindcast = HindcastEnsemble(hind)
hindcast = hindcast.add_observations(reconstruction_ds_1d_mm)
return hindcast
def hindcast_hist_obs_1d(hind_ds_initialized_1d, hist_ds_uninitialized_1d,
observations_ds_1d):
"""HindcastEnsemble initialized with `initialized`, `uninitialzed` and `obs`."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_uninitialized(hist_ds_uninitialized_1d)
hindcast = hindcast.add_observations(observations_ds_1d)
hindcast = hindcast - hindcast.sel(
time=slice("1964", "2014")).mean("time").sel(
init=slice("1964", "2014")).mean("init")
return hindcast
def hindcast_recon_3d(hind_ds_initialized_3d, reconstruction_ds_3d):
"""HindcastEnsemble initialized with `initialized`, `reconstruction`(`recon`)."""
# fix to align coords
for c in ["TLAT", "TLONG", "TAREA"]:
reconstruction_ds_3d[c] = hind_ds_initialized_3d[c]
hindcast = HindcastEnsemble(hind_ds_initialized_3d)
hindcast = hindcast.add_observations(reconstruction_ds_3d)
hindcast = hindcast - hindcast.sel(time=slice("1964", "2014")).mean("time").sel(
init=slice("1964", "2014")
).mean("init")
return hindcast
def test_smooth_coarsen(reconstruction_ds_3d, hind_ds_initialized_3d):
"""Test whether coarsening reduces dim.size."""
hindcast = HindcastEnsemble(hind_ds_initialized_3d)
hindcast = hindcast.add_observations(reconstruction_ds_3d,
'reconstruction')
hindcast = hindcast.add_uninitialized(reconstruction_ds_3d)
initialized_before = hindcast._datasets['initialized']
dim = 'nlon'
hindcast = hindcast.smooth(smooth_kws={dim: 2})
actual_initialized = hindcast._datasets['initialized']
assert initialized_before[dim].size // 2 == actual_initialized[dim].size
def test_smooth_goddard(reconstruction_ds_3d, hind_ds_initialized_3d):
"""Test whether goddard smoothing function reduces ntime."""
hindcast = HindcastEnsemble(
hind_ds_initialized_3d.isel(nlat=slice(1, None)))
hindcast = hindcast.add_observations(
reconstruction_ds_3d.isel(nlat=slice(1, None)), 'reconstruction')
hindcast = hindcast.add_uninitialized(
reconstruction_ds_3d.isel(nlat=slice(1, None)))
initialized_before = hindcast._datasets['initialized']
hindcast = hindcast.smooth(smooth_kws='goddard2013')
actual_initialized = hindcast._datasets['initialized']
dim = 'lead'
assert actual_initialized[dim].size < initialized_before[dim].size
for dim in ['nlon', 'nlat']:
assert actual_initialized[dim[1:]].size < initialized_before[dim].size
def test_hindcastEnsemble_plus_hindcastEnsemble(hind_ds_initialized_1d,
hist_ds_uninitialized_1d,
observations_ds_1d, operator):
"""Test that HindcastEnsemble math operator (+-*/) HindcastEnsemble works
correctly."""
he = HindcastEnsemble(hind_ds_initialized_1d)
he = he.add_uninitialized(hist_ds_uninitialized_1d)
he = he.add_observations(observations_ds_1d)
other = he.mean("init")
operator = eval(operator)
he2 = operator(he, other)
for dataset in he._datasets:
if he._datasets[dataset]:
print("check", dataset)
assert_equal(
he2._datasets[dataset],
operator(he._datasets[dataset], other._datasets[dataset]),
)
# check same dims and data_vars as before
check_dataset_dims_and_data_vars(he, he2, dataset)
def hindcast_obs_1d_for_alignment(hind_ds_initialized_1d_cftime,
reconstruction_ds_1d_cftime):
"""HindcastEnsemble initialized with `initialized`, `uninitialzed` and `obs`."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d_cftime)
hindcast = hindcast.add_observations(reconstruction_ds_1d_cftime)
return hindcast
def test_get_observations(hind_ds_initialized_1d, reconstruction_ds_1d):
"""Tests whether get_observations method works."""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(reconstruction_ds_1d)
obs = hindcast.get_observations()
assert obs == hindcast._datasets["observations"]
def test_add_observations_da_1d(hind_ds_initialized_1d, observations_da_1d):
"""Test to see if observations can be added to the HindcastEnsemble as a da"""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(observations_da_1d, 'observations')
assert hindcast.get_observations()
def test_add_observations(hind_ds_initialized_1d, reconstruction_ds_1d):
"""Test to see if observations can be added to the HindcastEnsemble"""
hindcast = HindcastEnsemble(hind_ds_initialized_1d)
hindcast = hindcast.add_observations(reconstruction_ds_1d,
'reconstruction')
assert hindcast.get_observations()
