def test_yearsplit(self, tmp_path):
_setup(tmp_path)
dataset, _, _ = _make_dataset(size=(2, 2))
engineer = Engineer(tmp_path)
train = engineer._train_test_split(
dataset,
years=[2001],
target_variable="VHI",
pred_months=11,
expected_length=11,
)
assert (train.time.values < np.datetime64("2001-01-01")).all(
), "Got years greater than the test year in the training set!"
# wrong shapes!
datasets = engineer._get_preprocessed_files()
ds_list = [xr.open_dataset(ds) for ds in datasets]
dims_list = [[dim for dim in ds.dims] for ds in ds_list]
variable_list = [[var for var in ds.variables if var not in dims_list[i]][0]
for i, ds in enumerate(ds_list)]
da_list = [ds[variable_list[i]] for i, ds in enumerate(ds_list)]
#
ds = engineer._make_dataset()
years = [1990]
train_ds, test_dict
train_ds = engineer._train_test_split(ds,
years,
target_variable="VHI",
pred_months=3,
expected_length=3)
xy_test, min_test_date = engineer.stratify_xy(
ds,
years[0],
target_variable="VHI",
target_month=7,
pred_months=3,
expected_length=3,
)
train_dict = engineer._stratify_training_data(train_ds, target_variable,
pred_months, expected_length)
#
years = [1990]
