def test_irregular_initialization_dates():
"""Tests that irregularly spaced initializations convert properly."""
inits = np.arange(1990, 2010)
inits = np.delete(inits, [3, 5, 8, 12, 15])
da = xr.DataArray(np.random.rand(len(inits)), dims="init", coords=[inits])
new_inits = convert_time_index(da, "init", "")
assert (new_inits["init"].to_index().year == inits).all()
def PM_ds_control_1d_ym_cftime(PM_ds_control_1d):
"""To MPI Perfect-model-framework corresponding control timeseries xr.Dataset with
time as cftime."""
PM_ds_control_1d = convert_time_index(
PM_ds_control_1d, "time", "PM_ds_control_1d.time", calendar=PM_CALENDAR_STR
)
return PM_ds_control_1d
def test_convert_time_index_does_not_overwrite():
"""Tests that `convert_time_index` does not overwrite the original index."""
inits = np.arange(1990, 2000)
da = xr.DataArray(np.random.rand(len(inits)), dims="init", coords=[inits])
new_inits = convert_time_index(da, "init", "")
assert isinstance(da.init.to_index(), pd.Int64Index)
assert isinstance(new_inits.init.to_index(), xr.CFTimeIndex)
def reconstruction_ds_1d_cftime(reconstruction_ds_1d):
"""CESM-FOSI historical reconstruction timeseries with cftime time axis."""
ds = reconstruction_ds_1d
ds = convert_time_index(ds,
'time',
'ds.init',
calendar=HINDCAST_CALENDAR_STR)
return ds
def hind_ds_initialized_1d_cftime(hind_ds_initialized_1d):
"""CESM-DPLE initialzed hindcast timeseries with cftime initializations."""
ds = hind_ds_initialized_1d
ds = convert_time_index(ds,
'init',
'ds.init',
calendar=HINDCAST_CALENDAR_STR)
ds.lead.attrs['units'] = 'years'
return ds
def test_numeric_index_auto_appends_lead_attrs():
"""Tests that for numeric inits, lead units are automatically set to 'years'"""
lead = np.arange(3)
int_inits = np.arange(1990, 2000)
float_inits = int_inits * 1.0
int_da = xr.DataArray(
np.random.rand(len(int_inits), len(lead)),
dims=["init", "lead"],
coords=[int_inits, lead],
)
float_da = xr.DataArray(
np.random.rand(len(float_inits), len(lead)),
dims=["init", "lead"],
coords=[float_inits, lead],
)
new_int_da = convert_time_index(int_da, "init", "")
new_float_da = convert_time_index(float_da, "init", "")
assert new_int_da.lead.attrs["units"] == "years"
assert new_float_da.lead.attrs["units"] == "years"
def PM_ds_initialized_1d_ym_cftime(PM_ds_initialized_1d):
"""MPI Perfect-model-framework initialized timeseries xr.Dataset with init as
cftime."""
PM_ds_initialized_1d = convert_time_index(
PM_ds_initialized_1d,
'init',
'PM_ds_initialized_1d.init',
calendar=PM_CALENDAR_STR,
)
PM_ds_initialized_1d['lead'].attrs['units'] = 'years'
return PM_ds_initialized_1d
def PM_ds_initialized_1d_ym_cftime(PM_ds_initialized_1d):
"""MPI Perfect-model-framework initialized timeseries xr.Dataset with init as
cftime."""
PM_ds_initialized_1d = convert_time_index(
PM_ds_initialized_1d,
"init",
"PM_ds_initialized_1d.init",
calendar=PM_CALENDAR_STR,
)
PM_ds_initialized_1d["lead"].attrs["units"] = "years"
return PM_ds_initialized_1d
def test_float64_converted_to_cftime():
"""Tests the xr.Float64Index is converted to xr.CFTimeIndex."""
inits = np.arange(1990, 2000) * 1.0
da = xr.DataArray(np.random.rand(len(inits)), dims="init", coords=[inits])
new_inits = convert_time_index(da, "init", "")
assert isinstance(new_inits["init"].to_index(), xr.CFTimeIndex)
def test_pandas_datetime_converted_to_cftime():
"""Tests that a pd.DatetimeIndex is converted to xr.CFTimeIndex."""
inits = pd.date_range("1990", "2000", freq="YS")
da = xr.DataArray(np.random.rand(len(inits)), dims="init", coords=[inits])
new_inits = convert_time_index(da, "init", "")
assert isinstance(new_inits["init"].to_index(), xr.CFTimeIndex)
def test_cftime_index_unchanged():
"""Tests that a CFTime index going through convert time is unchanged."""
inits = xr.cftime_range("1990", "2000", freq="Y", calendar="noleap")
da = xr.DataArray(np.random.rand(len(inits)), dims="init", coords=[inits])
new_inits = convert_time_index(da, "init", "")
assert_allclose(new_inits.init, da.init)
def test_int64_converted_to_cftime():
"""Tests the xr.Int64Index is converted to xr.CFTimeIndex."""
inits = np.arange(1990, 2000)
da = xr.DataArray(np.random.rand(len(inits)), dims='init', coords=[inits])
new_inits = convert_time_index(da, 'init', '')
assert isinstance(new_inits['init'].to_index(), xr.CFTimeIndex)
def test_pandas_datetime_converted_to_cftime():
"""Tests that a pd.DatetimeIndex is converted to xr.CFTimeIndex."""
inits = pd.date_range('1990', '2000', freq='YS')
da = xr.DataArray(np.random.rand(len(inits)), dims='init', coords=[inits])
new_inits = convert_time_index(da, 'init', '')
assert isinstance(new_inits['init'].to_index(), xr.CFTimeIndex)
def test_cftime_index_unchanged():
"""Tests that a CFTime index going through convert time is unchanged."""
inits = xr.cftime_range('1990', '2000', freq='Y', calendar='noleap')
da = xr.DataArray(np.random.rand(len(inits)), dims='init', coords=[inits])
new_inits = convert_time_index(da, 'init', '')
assert_allclose(new_inits.init, da.init)
