def test_datetime_to_numeric_potential_overflow():
import cftime
times = pd.date_range("2000", periods=5,
freq="7D").values.astype("datetime64[us]")
cftimes = cftime_range("2000",
periods=5,
freq="7D",
calendar="proleptic_gregorian").values
offset = np.datetime64("0001-01-01")
cfoffset = cftime.DatetimeProlepticGregorian(1, 1, 1)
result = duck_array_ops.datetime_to_numeric(times,
offset=offset,
datetime_unit="D",
dtype=int)
cfresult = duck_array_ops.datetime_to_numeric(cftimes,
offset=cfoffset,
datetime_unit="D",
dtype=int)
expected = 730119 + np.arange(0, 35, 7)
np.testing.assert_array_equal(result, expected)
np.testing.assert_array_equal(cfresult, expected)
def test_datetime_to_numeric_cftime(dask):
if dask and not has_dask:
pytest.skip("requires dask")
times = cftime_range("2000", periods=5, freq="7D",
calendar="standard").values
if dask:
import dask.array
times = dask.array.from_array(times, chunks=-1)
with raise_if_dask_computes():
result = duck_array_ops.datetime_to_numeric(times,
datetime_unit="h",
dtype=int)
expected = 24 * np.arange(0, 35, 7)
np.testing.assert_array_equal(result, expected)
offset = times[1]
with raise_if_dask_computes():
result = duck_array_ops.datetime_to_numeric(times,
offset=offset,
datetime_unit="h",
dtype=int)
expected = 24 * np.arange(-7, 28, 7)
np.testing.assert_array_equal(result, expected)
dtype = np.float32
with raise_if_dask_computes():
result = duck_array_ops.datetime_to_numeric(times,
datetime_unit="h",
dtype=dtype)
expected = 24 * np.arange(0, 35, 7).astype(dtype)
np.testing.assert_array_equal(result, expected)
def test_datetime_to_numeric_datetime64():
times = pd.date_range("2000", periods=5, freq="7D").values
result = duck_array_ops.datetime_to_numeric(times, datetime_unit="h")
expected = 24 * np.arange(0, 35, 7)
np.testing.assert_array_equal(result, expected)
offset = times[1]
result = duck_array_ops.datetime_to_numeric(times, offset=offset, datetime_unit="h")
expected = 24 * np.arange(-7, 28, 7)
np.testing.assert_array_equal(result, expected)
dtype = np.float32
result = duck_array_ops.datetime_to_numeric(times, datetime_unit="h", dtype=dtype)
expected = 24 * np.arange(0, 35, 7).astype(dtype)
np.testing.assert_array_equal(result, expected)
def test_datetime_to_numeric_cftime():
times = cftime_range('2000', periods=5, freq='7D').values
result = duck_array_ops.datetime_to_numeric(times, datetime_unit='h')
expected = 24 * np.arange(0, 35, 7)
np.testing.assert_array_equal(result, expected)
offset = times[1]
result = duck_array_ops.datetime_to_numeric(
times, offset=offset, datetime_unit='h')
expected = 24 * np.arange(-7, 28, 7)
np.testing.assert_array_equal(result, expected)
dtype = np.float32
result = duck_array_ops.datetime_to_numeric(
times, datetime_unit='h', dtype=dtype)
expected = 24 * np.arange(0, 35, 7).astype(dtype)
np.testing.assert_array_equal(result, expected)
def test_datetime_to_numeric_cftime():
times = cftime_range('2000', periods=5, freq='7D').values
result = duck_array_ops.datetime_to_numeric(times, datetime_unit='h')
expected = 24 * np.arange(0, 35, 7)
np.testing.assert_array_equal(result, expected)
offset = times[1]
result = duck_array_ops.datetime_to_numeric(
times, offset=offset, datetime_unit='h')
expected = 24 * np.arange(-7, 28, 7)
np.testing.assert_array_equal(result, expected)
dtype = np.float32
result = duck_array_ops.datetime_to_numeric(
times, datetime_unit='h', dtype=dtype)
expected = 24 * np.arange(0, 35, 7).astype(dtype)
np.testing.assert_array_equal(result, expected)
