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clib.conversion._to_numpy: Add tests for numpy array with np.datetime64 dtypes #3687

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Jan 9, 2025
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clib.conversion._to_numpy: Add tests for numpy array with np.datetime64 dtypes #3687

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30 changes: 30 additions & 0 deletions pygmt/tests/test_clib_to_numpy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -152,6 +152,36 @@ def test_to_numpy_numpy_string(dtype):
npt.assert_array_equal(result, array)


@pytest.mark.parametrize(
"dtype",
[
np.datetime64, # The expected dtype is "datetime64[D]" for this test.
"datetime64[Y]",
"datetime64[M]",
"datetime64[W]",
"datetime64[D]",
"datetime64[h]",
"datetime64[m]",
"datetime64[s]",
"datetime64[ms]",
"datetime64[us]",
"datetime64[ns]",
],
)
def test_to_numpy_numpy_datetime(dtype):
"""
Test the _to_ndarray function with 1-D NumPy arrays of datetime.

Time units "fs", "as", "ps" are not tested here because they can only represent a
small range of times in 1969-1970.
"""
array = np.array(["2024-01-01", "2024-01-02", "2024-01-03"], dtype=dtype)
result = _to_numpy(array)
_check_result(result, np.datetime64)
assert result.dtype == (dtype if isinstance(dtype, str) else "datetime64[D]")
npt.assert_array_equal(result, array)


########################################################################################
# Test the _to_numpy function with pandas.Series.
#
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