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Cleanup test_coding_times.py #9223

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Jul 10, 2024
Merged

Cleanup test_coding_times.py #9223

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e8e9cce
Cleanup test_coding_times
Illviljan Jul 9, 2024
1d6077e
Update test_coding_times.py
Illviljan Jul 9, 2024
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93 changes: 44 additions & 49 deletions xarray/tests/test_coding_times.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,20 +14,25 @@
Dataset,
Variable,
cftime_range,
coding,
conventions,
date_range,
decode_cf,
)
from xarray.coding.times import _STANDARD_CALENDARS as _STANDARD_CALENDARS_UNSORTED
from xarray.coding.times import (
CFDatetimeCoder,
_encode_datetime_with_cftime,
_netcdf_to_numpy_timeunit,
_numpy_to_netcdf_timeunit,
_should_cftime_be_used,
cftime_to_nptime,
decode_cf_datetime,
decode_cf_timedelta,
encode_cf_datetime,
encode_cf_timedelta,
format_cftime_datetime,
infer_datetime_units,
infer_timedelta_units,
to_timedelta_unboxed,
)
from xarray.coding.variables import SerializationWarning
Expand All @@ -53,11 +58,9 @@
"all_leap",
"366_day",
}
_ALL_CALENDARS = sorted(
_NON_STANDARD_CALENDARS_SET.union(coding.times._STANDARD_CALENDARS)
)
_STANDARD_CALENDARS = sorted(_STANDARD_CALENDARS_UNSORTED)
_ALL_CALENDARS = sorted(_NON_STANDARD_CALENDARS_SET.union(_STANDARD_CALENDARS))
_NON_STANDARD_CALENDARS = sorted(_NON_STANDARD_CALENDARS_SET)
_STANDARD_CALENDARS = sorted(coding.times._STANDARD_CALENDARS)
_CF_DATETIME_NUM_DATES_UNITS = [
(np.arange(10), "days since 2000-01-01"),
(np.arange(10).astype("float64"), "days since 2000-01-01"),
Expand Down Expand Up @@ -130,7 +133,7 @@ def test_cf_datetime(num_dates, units, calendar) -> None:

with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Unable to decode time axis")
actual = coding.times.decode_cf_datetime(num_dates, units, calendar)
actual = decode_cf_datetime(num_dates, units, calendar)

abs_diff = np.asarray(abs(actual - expected)).ravel()
abs_diff = pd.to_timedelta(abs_diff.tolist()).to_numpy()
Expand All @@ -139,17 +142,15 @@ def test_cf_datetime(num_dates, units, calendar) -> None:
# we could do this check with near microsecond accuracy:
# https://github.com/Unidata/netcdf4-python/issues/355
assert (abs_diff <= np.timedelta64(1, "s")).all()
encoded, _, _ = coding.times.encode_cf_datetime(actual, units, calendar)
encoded, _, _ = encode_cf_datetime(actual, units, calendar)

assert_array_equal(num_dates, np.around(encoded, 1))
assert_array_equal(num_dates, np.round(encoded, 1))
if hasattr(num_dates, "ndim") and num_dates.ndim == 1 and "1000" not in units:
# verify that wrapping with a pandas.Index works
# note that it *does not* currently work to put
# non-datetime64 compatible dates into a pandas.Index
encoded, _, _ = coding.times.encode_cf_datetime(
pd.Index(actual), units, calendar
)
assert_array_equal(num_dates, np.around(encoded, 1))
encoded, _, _ = encode_cf_datetime(pd.Index(actual), units, calendar)
assert_array_equal(num_dates, np.round(encoded, 1))


@requires_cftime
Expand All @@ -169,7 +170,7 @@ def test_decode_cf_datetime_overflow() -> None:
for i, day in enumerate(days):
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Unable to decode time axis")
result = coding.times.decode_cf_datetime(day, units)
result = decode_cf_datetime(day, units)
assert result == expected[i]


Expand All @@ -178,7 +179,7 @@ def test_decode_cf_datetime_non_standard_units() -> None:
# netCDFs from madis.noaa.gov use this format for their time units
# they cannot be parsed by cftime, but pd.Timestamp works
units = "hours since 1-1-1970"
actual = coding.times.decode_cf_datetime(np.arange(100), units)
actual = decode_cf_datetime(np.arange(100), units)
assert_array_equal(actual, expected)


Expand All @@ -193,7 +194,7 @@ def test_decode_cf_datetime_non_iso_strings() -> None:
(np.arange(100), "hours since 2000-01-01 0:00"),
]
for num_dates, units in cases:
actual = coding.times.decode_cf_datetime(num_dates, units)
actual = decode_cf_datetime(num_dates, units)
abs_diff = abs(actual - expected.values)
# once we no longer support versions of netCDF4 older than 1.1.5,
# we could do this check with near microsecond accuracy:
Expand All @@ -212,7 +213,7 @@ def test_decode_standard_calendar_inside_timestamp_range(calendar) -> None:
expected = times.values
expected_dtype = np.dtype("M8[ns]")

actual = coding.times.decode_cf_datetime(time, units, calendar=calendar)
actual = decode_cf_datetime(time, units, calendar=calendar)
assert actual.dtype == expected_dtype
abs_diff = abs(actual - expected)
# once we no longer support versions of netCDF4 older than 1.1.5,
Expand All @@ -235,9 +236,7 @@ def test_decode_non_standard_calendar_inside_timestamp_range(calendar) -> None:
)
expected_dtype = np.dtype("O")

actual = coding.times.decode_cf_datetime(
non_standard_time, units, calendar=calendar
)
actual = decode_cf_datetime(non_standard_time, units, calendar=calendar)
assert actual.dtype == expected_dtype
abs_diff = abs(actual - expected)
# once we no longer support versions of netCDF4 older than 1.1.5,
Expand All @@ -264,7 +263,7 @@ def test_decode_dates_outside_timestamp_range(calendar) -> None:

with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Unable to decode time axis")
actual = coding.times.decode_cf_datetime(time, units, calendar=calendar)
actual = decode_cf_datetime(time, units, calendar=calendar)
assert all(isinstance(value, expected_date_type) for value in actual)
abs_diff = abs(actual - expected)
# once we no longer support versions of netCDF4 older than 1.1.5,
Expand All @@ -282,7 +281,7 @@ def test_decode_standard_calendar_single_element_inside_timestamp_range(
for num_time in [735368, [735368], [[735368]]]:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Unable to decode time axis")
actual = coding.times.decode_cf_datetime(num_time, units, calendar=calendar)
actual = decode_cf_datetime(num_time, units, calendar=calendar)
assert actual.dtype == np.dtype("M8[ns]")


Expand All @@ -295,7 +294,7 @@ def test_decode_non_standard_calendar_single_element_inside_timestamp_range(
for num_time in [735368, [735368], [[735368]]]:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Unable to decode time axis")
actual = coding.times.decode_cf_datetime(num_time, units, calendar=calendar)
actual = decode_cf_datetime(num_time, units, calendar=calendar)
assert actual.dtype == np.dtype("O")


Expand All @@ -309,9 +308,7 @@ def test_decode_single_element_outside_timestamp_range(calendar) -> None:
for num_time in [days, [days], [[days]]]:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Unable to decode time axis")
actual = coding.times.decode_cf_datetime(
num_time, units, calendar=calendar
)
actual = decode_cf_datetime(num_time, units, calendar=calendar)

expected = cftime.num2date(
days, units, calendar, only_use_cftime_datetimes=True
Expand All @@ -338,7 +335,7 @@ def test_decode_standard_calendar_multidim_time_inside_timestamp_range(
expected1 = times1.values
expected2 = times2.values

actual = coding.times.decode_cf_datetime(mdim_time, units, calendar=calendar)
actual = decode_cf_datetime(mdim_time, units, calendar=calendar)
assert actual.dtype == np.dtype("M8[ns]")

abs_diff1 = abs(actual[:, 0] - expected1)
Expand Down Expand Up @@ -379,7 +376,7 @@ def test_decode_nonstandard_calendar_multidim_time_inside_timestamp_range(

expected_dtype = np.dtype("O")

actual = coding.times.decode_cf_datetime(mdim_time, units, calendar=calendar)
actual = decode_cf_datetime(mdim_time, units, calendar=calendar)

assert actual.dtype == expected_dtype
abs_diff1 = abs(actual[:, 0] - expected1)
Expand Down Expand Up @@ -412,7 +409,7 @@ def test_decode_multidim_time_outside_timestamp_range(calendar) -> None:

with warnings.catch_warnings():
warnings.filterwarnings("ignore", "Unable to decode time axis")
actual = coding.times.decode_cf_datetime(mdim_time, units, calendar=calendar)
actual = decode_cf_datetime(mdim_time, units, calendar=calendar)

assert actual.dtype == np.dtype("O")

Expand All @@ -435,7 +432,7 @@ def test_decode_non_standard_calendar_single_element(calendar, num_time) -> None

units = "days since 0001-01-01"

actual = coding.times.decode_cf_datetime(num_time, units, calendar=calendar)
actual = decode_cf_datetime(num_time, units, calendar=calendar)

expected = np.asarray(
cftime.num2date(num_time, units, calendar, only_use_cftime_datetimes=True)
Expand All @@ -460,9 +457,7 @@ def test_decode_360_day_calendar() -> None:

with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
actual = coding.times.decode_cf_datetime(
num_times, units, calendar=calendar
)
actual = decode_cf_datetime(num_times, units, calendar=calendar)
assert len(w) == 0

assert actual.dtype == np.dtype("O")
Expand All @@ -476,8 +471,8 @@ def test_decode_abbreviation() -> None:

val = np.array([1586628000000.0])
units = "msecs since 1970-01-01T00:00:00Z"
actual = coding.times.decode_cf_datetime(val, units)
expected = coding.times.cftime_to_nptime(cftime.num2date(val, units))
actual = decode_cf_datetime(val, units)
expected = cftime_to_nptime(cftime.num2date(val, units))
assert_array_equal(actual, expected)


Expand All @@ -498,7 +493,7 @@ def test_decode_abbreviation() -> None:
def test_cf_datetime_nan(num_dates, units, expected_list) -> None:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "All-NaN")
actual = coding.times.decode_cf_datetime(num_dates, units)
actual = decode_cf_datetime(num_dates, units)
# use pandas because numpy will deprecate timezone-aware conversions
expected = pd.to_datetime(expected_list).to_numpy(dtype="datetime64[ns]")
assert_array_equal(expected, actual)
Expand All @@ -510,7 +505,7 @@ def test_decoded_cf_datetime_array_2d() -> None:
variable = Variable(
("x", "y"), np.array([[0, 1], [2, 3]]), {"units": "days since 2000-01-01"}
)
result = coding.times.CFDatetimeCoder().decode(variable)
result = CFDatetimeCoder().decode(variable)
assert result.dtype == "datetime64[ns]"
expected = pd.date_range("2000-01-01", periods=4).values.reshape(2, 2)
assert_array_equal(np.asarray(result), expected)
Expand All @@ -531,7 +526,7 @@ def test_decoded_cf_datetime_array_2d() -> None:
def test_infer_datetime_units(freq, units) -> None:
dates = pd.date_range("2000", periods=2, freq=freq)
expected = f"{units} since 2000-01-01 00:00:00"
assert expected == coding.times.infer_datetime_units(dates)
assert expected == infer_datetime_units(dates)


@pytest.mark.parametrize(
Expand All @@ -549,7 +544,7 @@ def test_infer_datetime_units(freq, units) -> None:
],
)
def test_infer_datetime_units_with_NaT(dates, expected) -> None:
assert expected == coding.times.infer_datetime_units(dates)
assert expected == infer_datetime_units(dates)


_CFTIME_DATETIME_UNITS_TESTS = [
Expand All @@ -573,7 +568,7 @@ def test_infer_datetime_units_with_NaT(dates, expected) -> None:
def test_infer_cftime_datetime_units(calendar, date_args, expected) -> None:
date_type = _all_cftime_date_types()[calendar]
dates = [date_type(*args) for args in date_args]
assert expected == coding.times.infer_datetime_units(dates)
assert expected == infer_datetime_units(dates)


@pytest.mark.filterwarnings("ignore:Timedeltas can't be serialized faithfully")
Expand All @@ -600,18 +595,18 @@ def test_cf_timedelta(timedeltas, units, numbers) -> None:
numbers = np.array(numbers)

expected = numbers
actual, _ = coding.times.encode_cf_timedelta(timedeltas, units)
actual, _ = encode_cf_timedelta(timedeltas, units)
assert_array_equal(expected, actual)
assert expected.dtype == actual.dtype

if units is not None:
expected = timedeltas
actual = coding.times.decode_cf_timedelta(numbers, units)
actual = decode_cf_timedelta(numbers, units)
assert_array_equal(expected, actual)
assert expected.dtype == actual.dtype

expected = np.timedelta64("NaT", "ns")
actual = coding.times.decode_cf_timedelta(np.array(np.nan), "days")
actual = decode_cf_timedelta(np.array(np.nan), "days")
assert_array_equal(expected, actual)


Expand All @@ -622,7 +617,7 @@ def test_cf_timedelta_2d() -> None:
timedeltas = np.atleast_2d(to_timedelta_unboxed(["1D", "2D", "3D"]))
expected = timedeltas

actual = coding.times.decode_cf_timedelta(numbers, units)
actual = decode_cf_timedelta(numbers, units)
assert_array_equal(expected, actual)
assert expected.dtype == actual.dtype

Expand All @@ -637,7 +632,7 @@ def test_cf_timedelta_2d() -> None:
],
)
def test_infer_timedelta_units(deltas, expected) -> None:
assert expected == coding.times.infer_timedelta_units(deltas)
assert expected == infer_timedelta_units(deltas)


@requires_cftime
Expand All @@ -653,7 +648,7 @@ def test_infer_timedelta_units(deltas, expected) -> None:
def test_format_cftime_datetime(date_args, expected) -> None:
date_types = _all_cftime_date_types()
for date_type in date_types.values():
result = coding.times.format_cftime_datetime(date_type(*date_args))
result = format_cftime_datetime(date_type(*date_args))
assert result == expected


Expand Down Expand Up @@ -1008,7 +1003,7 @@ def test_decode_ambiguous_time_warns(calendar) -> None:

# we don't decode non-standard calendards with
# pandas so expect no warning will be emitted
is_standard_calendar = calendar in coding.times._STANDARD_CALENDARS
is_standard_calendar = calendar in _STANDARD_CALENDARS

dates = [1, 2, 3]
units = "days since 1-1-1"
Expand Down Expand Up @@ -1043,9 +1038,9 @@ def test_encode_cf_datetime_defaults_to_correct_dtype(
pytest.skip("Nanosecond frequency is not valid for cftime dates.")
times = date_range("2000", periods=3, freq=freq)
units = f"{encoding_units} since 2000-01-01"
encoded, _units, _ = coding.times.encode_cf_datetime(times, units)
encoded, _units, _ = encode_cf_datetime(times, units)

numpy_timeunit = coding.times._netcdf_to_numpy_timeunit(encoding_units)
numpy_timeunit = _netcdf_to_numpy_timeunit(encoding_units)
encoding_units_as_timedelta = np.timedelta64(1, numpy_timeunit)
if pd.to_timedelta(1, freq) >= encoding_units_as_timedelta:
assert encoded.dtype == np.int64
Expand Down Expand Up @@ -1202,7 +1197,7 @@ def test_decode_float_datetime():
def test_scalar_unit() -> None:
# test that a scalar units (often NaN when using to_netcdf) does not raise an error
variable = Variable(("x", "y"), np.array([[0, 1], [2, 3]]), {"units": np.nan})
result = coding.times.CFDatetimeCoder().decode(variable)
result = CFDatetimeCoder().decode(variable)
assert np.isnan(result.attrs["units"])


Expand Down
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