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@aulemahal
aulemahal committed Jun 11, 2024
2 parents 7ebb276 + 1680be7 commit 64bf562
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10 changes: 10 additions & 0 deletions CHANGES.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,16 @@ New features and enhancements
Breaking changes
^^^^^^^^^^^^^^^^
* `pint` has been pinned below v0.24 until `xclim` can be updated to support the latest version. (:issue:`1771`, :pull:`1772`).
* Calendar utilities that have an equivalent in `xarray` have been deprecated and will be removed in `xclim` v0.51.0. (:issue:`1010`, :pull:`1761`). This concerns the following members of ``xclim.core.calendar``:
- ``convert_calendar`` : Use ``Dataset.convert_calendar``, ``DataArray.convert_calendar`` or ``xr.coding.calendar_ops.convert_calendar`` instead.
+ If your code passes ``target`` as an array, first convert the source to the target's calendar and then reindex the result to ``target``.
+ If you were using the ``doy=True`` option, replace it with ``xc.core.calendar.convert_doy(source, target_cal).convert_calendar(target_cal)``.
+ ``"default"`` is no longer a valid calendar name for any xclim functions and will not be returned by ``get_calendar``. Xarray has a ``use_cftime`` argument, xclim exposes it when the distinction is needed.
- ``date_range`` : Use ``xarray.date_range`` instead.
- ``date_range_like``: Use ``xarray.date_range_like`` instead.
- ``interp_calendar`` : Use ``Dataset.interp_calendar`` or ``xarray.coding.calendar_ops.interp_calendar`` instead.
- ``days_in_year`` : Use ``xarray.coding.calendar_ops._days_in_year`` instead.
- ``datetime_to_decimal_year`` : Use ``xarray.coding.calendar_ops._datetime_to_decimal_year`` instead.

Internal changes
^^^^^^^^^^^^^^^^
Expand Down
270 changes: 24 additions & 246 deletions tests/test_calendar.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,16 +16,11 @@
common_calendar,
compare_offsets,
construct_offset,
convert_calendar,
convert_doy,
date_range,
datetime_to_decimal_year,
days_in_year,
days_since_to_doy,
doy_to_days_since,
ensure_cftime_array,
get_calendar,
interp_calendar,
max_doy,
parse_offset,
percentile_doy,
Expand Down Expand Up @@ -236,7 +231,7 @@ def test_adjust_doy_366_to_360():
"360_day",
360,
),
(("NRCANdaily", "nrcan_canada_daily_pr_1990.nc"), "default", 366),
(("NRCANdaily", "nrcan_canada_daily_pr_1990.nc"), "proleptic_gregorian", 366),
],
)
def test_get_calendar(file, cal, maxdoy, open_dataset):
Expand All @@ -249,8 +244,8 @@ def test_get_calendar(file, cal, maxdoy, open_dataset):
@pytest.mark.parametrize(
"obj,cal",
[
([pd.Timestamp.now()], "default"),
(pd.Timestamp.now(), "default"),
([pd.Timestamp.now()], "standard"),
(pd.Timestamp.now(), "standard"),
(cftime.DatetimeAllLeap(2000, 1, 1), "all_leap"),
(np.array([cftime.DatetimeNoLeap(2000, 1, 1)]), "noleap"),
(xr.cftime_range("2000-01-01", periods=4, freq="D"), "standard"),
Expand All @@ -266,158 +261,6 @@ def test_get_calendar_errors(obj):
get_calendar(obj)


@pytest.mark.parametrize(
"source,target,target_as_str,freq",
[
("standard", "noleap", True, "D"),
("noleap", "default", True, "D"),
("noleap", "all_leap", False, "D"),
("proleptic_gregorian", "noleap", False, "4h"),
("default", "noleap", True, "4h"),
],
)
def test_convert_calendar(source, target, target_as_str, freq):
src = xr.DataArray(
date_range("2004-01-01", "2004-12-31", freq=freq, calendar=source),
dims=("time",),
name="time",
)
da_src = xr.DataArray(
np.linspace(0, 1, src.size), dims=("time",), coords={"time": src}
)
tgt = xr.DataArray(
date_range("2004-01-01", "2004-12-31", freq=freq, calendar=target),
dims=("time",),
name="time",
)

conv = convert_calendar(da_src, target if target_as_str else tgt)

assert get_calendar(conv) == target

if target_as_str and max_doy[source] < max_doy[target]:
assert conv.size == src.size
elif not target_as_str:
assert conv.size == tgt.size

assert conv.isnull().sum() == max(max_doy[target] - max_doy[source], 0)


@pytest.mark.parametrize(
"source,target,freq",
[
("standard", "360_day", "D"),
("360_day", "default", "D"),
("proleptic_gregorian", "360_day", "4h"),
],
)
@pytest.mark.parametrize("align_on", ["date", "year"])
def test_convert_calendar_360_days(source, target, freq, align_on):
src = xr.DataArray(
date_range("2004-01-01", "2004-12-30", freq=freq, calendar=source),
dims=("time",),
name="time",
)
da_src = xr.DataArray(
np.linspace(0, 1, src.size), dims=("time",), coords={"time": src}
)

conv = convert_calendar(da_src, target, align_on=align_on)

assert get_calendar(conv) == target

if align_on == "date":
np.testing.assert_array_equal(
conv.time.resample(time="ME").last().dt.day,
[30, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30],
)
elif target == "360_day":
np.testing.assert_array_equal(
conv.time.resample(time="ME").last().dt.day,
[30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 29],
)
else:
np.testing.assert_array_equal(
conv.time.resample(time="ME").last().dt.day,
[30, 29, 30, 30, 31, 30, 30, 31, 30, 31, 29, 31],
)
if source == "360_day" and align_on == "year":
assert conv.size == 360 if freq == "D" else 360 * 4
else:
assert conv.size == 359 if freq == "D" else 359 * 4


def test_convert_calendar_360_days_random():
da_std = xr.DataArray(
np.linspace(0, 1, 366 * 2),
dims=("time",),
coords={
"time": date_range(
"2004-01-01", "2004-12-31T23:59:59", freq="12h", calendar="default"
)
},
)
da_360 = xr.DataArray(
np.linspace(0, 1, 360 * 2),
dims=("time",),
coords={
"time": date_range(
"2004-01-01", "2004-12-30T23:59:59", freq="12h", calendar="360_day"
)
},
)

conv = convert_calendar(da_std, "360_day", align_on="random")
assert get_calendar(conv) == "360_day"
assert conv.size == 720
conv2 = convert_calendar(da_std, "360_day", align_on="random")
assert (conv != conv2).any()

conv = convert_calendar(da_360, "default", align_on="random")
assert get_calendar(conv) == "default"
assert conv.size == 720
assert np.datetime64("2004-02-29") not in conv.time
conv2 = convert_calendar(da_360, "default", align_on="random")
assert (conv2 != conv).any()

conv = convert_calendar(da_360, "noleap", align_on="random", missing=np.NaN)
conv = conv.where(conv.isnull(), drop=True)
nandoys = conv.time.dt.dayofyear[::2]
assert all(nandoys < np.array([74, 147, 220, 293, 366]))
assert all(nandoys > np.array([0, 73, 146, 219, 292]))


@pytest.mark.parametrize(
"source,target,freq",
[
("standard", "noleap", "D"),
("noleap", "default", "4h"),
("noleap", "all_leap", "ME"),
("360_day", "noleap", "D"),
("noleap", "360_day", "D"),
],
)
def test_convert_calendar_missing(source, target, freq):
src = xr.DataArray(
date_range(
"2004-01-01",
"2004-12-31" if source != "360_day" else "2004-12-30",
freq=freq,
calendar=source,
),
dims=("time",),
name="time",
)
da_src = xr.DataArray(
np.linspace(0, 1, src.size), dims=("time",), coords={"time": src}
)
out = convert_calendar(da_src, target, missing=0, align_on="date")
assert xr.infer_freq(out.time) == freq
if source == "360_day":
assert out.time[-1].dt.day == 31
assert out[-1] == 0


def test_convert_calendar_and_doy():
doy = xr.DataArray(
[31, 32, 336, 364.23, 365],
Expand All @@ -427,114 +270,49 @@ def test_convert_calendar_and_doy():
},
attrs={"is_dayofyear": 1, "calendar": "noleap"},
)
out = convert_calendar(doy, "360_day", align_on="date", doy=True)
out = convert_doy(doy, target_cal="360_day").convert_calendar(
"360_day", align_on="date"
)
# out = convert_calendar(doy, "360_day", align_on="date", doy=True)
np.testing.assert_allclose(
out, [30.575342, 31.561644, 331.39726, 359.240548, 360.0]
)
assert out.time.dt.calendar == "360_day"
out = convert_calendar(doy, "360_day", align_on="date", doy="date")
out = convert_doy(doy, target_cal="360_day", align_on="date").convert_calendar(
"360_day", align_on="date"
)
np.testing.assert_array_equal(out, [np.NaN, 31, 332, 360.23, np.NaN])
assert out.time.dt.calendar == "360_day"


@pytest.mark.parametrize(
"source,target",
[
("standard", "noleap"),
("noleap", "default"),
("standard", "360_day"),
("360_day", "standard"),
("noleap", "all_leap"),
("360_day", "noleap"),
],
)
def test_interp_calendar(source, target):
src = xr.DataArray(
date_range("2004-01-01", "2004-07-30", freq="D", calendar=source),
dims=("time",),
name="time",
)
tgt = xr.DataArray(
date_range("2004-01-01", "2004-07-30", freq="D", calendar=target),
dims=("time",),
name="time",
)
da_src = xr.DataArray(
np.linspace(0, 1, src.size), dims=("time",), coords={"time": src}
)
conv = interp_calendar(da_src, tgt)

assert conv.size == tgt.size
assert get_calendar(conv) == target

np.testing.assert_almost_equal(conv.max(), 1, 2)
assert conv.min() == 0


@pytest.mark.parametrize(
"inp,calout",
[
(
xr.DataArray(
date_range("2004-01-01", "2004-01-10", freq="D"),
xr.date_range("2004-01-01", "2004-01-10", freq="D"),
dims=("time",),
name="time",
),
"standard",
),
(date_range("2004-01-01", "2004-01-10", freq="D"), "standard"),
(xr.date_range("2004-01-01", "2004-01-10", freq="D"), "standard"),
(
xr.DataArray(date_range("2004-01-01", "2004-01-10", freq="D")).values,
xr.DataArray(xr.date_range("2004-01-01", "2004-01-10", freq="D")).values,
"standard",
),
(date_range("2004-01-01", "2004-01-10", freq="D").values, "standard"),
(date_range("2004-01-01", "2004-01-10", freq="D", calendar="julian"), "julian"),
(xr.date_range("2004-01-01", "2004-01-10", freq="D").values, "standard"),
(
xr.date_range("2004-01-01", "2004-01-10", freq="D", calendar="julian"),
"julian",
),
],
)
def test_ensure_cftime_array(inp, calout):
out = ensure_cftime_array(inp)
assert get_calendar(out) == calout


@pytest.mark.parametrize(
"year,calendar,exp",
[
(2004, "standard", 366),
(2004, "noleap", 365),
(2004, "all_leap", 366),
(1500, "default", 365),
(1500, "standard", 366),
(1500, "proleptic_gregorian", 365),
(2030, "360_day", 360),
],
)
def test_days_in_year(year, calendar, exp):
assert days_in_year(year, calendar) == exp


@pytest.mark.parametrize(
"source_cal, exp180",
[
("standard", 0.49180328),
("default", 0.49180328),
("noleap", 0.49315068),
("all_leap", 0.49180328),
("360_day", 0.5),
(None, 0.49180328),
],
)
def test_datetime_to_decimal_year(source_cal, exp180):
times = xr.DataArray(
date_range(
"2004-01-01", "2004-12-30", freq="D", calendar=source_cal or "default"
),
dims=("time",),
name="time",
)
decy = datetime_to_decimal_year(times, calendar=source_cal)
np.testing.assert_almost_equal(decy[180] - 2004, exp180)


def test_clim_mean_doy(tas_series):
arr = tas_series(np.ones(365 * 10))
mean, stddev = climatological_mean_doy(arr, window=1)
Expand All @@ -552,12 +330,12 @@ def test_clim_mean_doy(tas_series):

def test_doy_to_days_since():
# simple test
time = date_range("2020-07-01", "2022-07-01", freq="YS-JUL")
time = xr.date_range("2020-07-01", "2022-07-01", freq="YS-JUL")
da = xr.DataArray(
[190, 360, 3],
dims=("time",),
coords={"time": time},
attrs={"is_dayofyear": 1, "calendar": "default"},
attrs={"is_dayofyear": 1, "calendar": "standard"},
)

out = doy_to_days_since(da)
Expand All @@ -583,13 +361,13 @@ def test_doy_to_days_since():
xr.testing.assert_identical(da, da2)

# with start
time = date_range("2020-12-31", "2022-12-31", freq="YE")
time = xr.date_range("2020-12-31", "2022-12-31", freq="YE")
da = xr.DataArray(
[190, 360, 3],
dims=("time",),
coords={"time": time},
name="da",
attrs={"is_dayofyear": 1, "calendar": "default"},
attrs={"is_dayofyear": 1, "calendar": "proleptic_gregorian"},
)

out = doy_to_days_since(da, start="01-02")
Expand All @@ -600,13 +378,13 @@ def test_doy_to_days_since():
xr.testing.assert_identical(da, da2)

# finer freq
time = date_range("2020-01-01", "2020-03-01", freq="MS")
time = xr.date_range("2020-01-01", "2020-03-01", freq="MS")
da = xr.DataArray(
[15, 33, 66],
dims=("time",),
coords={"time": time},
name="da",
attrs={"is_dayofyear": 1, "calendar": "default"},
attrs={"is_dayofyear": 1, "calendar": "proleptic_gregorian"},
)

out = doy_to_days_since(da)
Expand Down
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