Remove tests for pyarrow.array. Already in PR #3599

Author: seisman

pygmt/tests/test_clib_to_numpy.py

@@ -229,82 +229,3 @@ def test_to_numpy_pandas_series_pyarrow_dtypes_numeric_with_na(dtype, expected_d
     result = _to_numpy(series)
     _check_result(result, expected_dtype)
     npt.assert_array_equal(result, np.array([1.0, np.nan, 5.0], dtype=expected_dtype))
-
-
-########################################################################################
-# Test the _to_numpy function with PyArrow arrays.
-#
-# PyArrow provides the following dtypes:
-#
-# - Numeric dtypes:
-#   - int8, int16, int32, int64
-#   - uint8, uint16, uint32, uint64
-#   - float16, float32, float64
-#
-# In PyArrow, array types can be specified in two ways:
-#
-# - Using string aliases (e.g., "int8")
-# - Using pyarrow.DataType (e.g., ``pa.int8()``)
-#
-# Reference: https://arrow.apache.org/docs/python/api/datatypes.html
-########################################################################################
-@pytest.mark.skipif(not _HAS_PYARROW, reason="pyarrow is not installed")
-@pytest.mark.parametrize(
-    ("dtype", "expected_dtype"),
-    [
-        pytest.param("int8", np.int8, id="int8"),
-        pytest.param("int16", np.int16, id="int16"),
-        pytest.param("int32", np.int32, id="int32"),
-        pytest.param("int64", np.int64, id="int64"),
-        pytest.param("uint8", np.uint8, id="uint8"),
-        pytest.param("uint16", np.uint16, id="uint16"),
-        pytest.param("uint32", np.uint32, id="uint32"),
-        pytest.param("uint64", np.uint64, id="uint64"),
-        pytest.param("float16", np.float16, id="float16"),
-        pytest.param("float32", np.float32, id="float32"),
-        pytest.param("float64", np.float64, id="float64"),
-    ],
-)
-def test_to_numpy_pyarrow_array_pyarrow_dtypes_numeric(dtype, expected_dtype):
-    """
-    Test the _to_numpy function with PyArrow arrays of PyArrow numeric dtypes.
-    """
-    data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]
-    if dtype == "float16":  # float16 needs special handling
-        # Example from https://arrow.apache.org/docs/python/generated/pyarrow.float16.html
-        data = np.array(data, dtype=np.float16)
-    array = pa.array(data, type=dtype)[::2]
-    result = _to_numpy(array)
-    _check_result(result, expected_dtype)
-    npt.assert_array_equal(result, array)
-
-
-@pytest.mark.skipif(not _HAS_PYARROW, reason="pyarrow is not installed")
-@pytest.mark.parametrize(
-    ("dtype", "expected_dtype"),
-    [
-        pytest.param("int8", np.float64, id="int8"),
-        pytest.param("int16", np.float64, id="int16"),
-        pytest.param("int32", np.float64, id="int32"),
-        pytest.param("int64", np.float64, id="int64"),
-        pytest.param("uint8", np.float64, id="uint8"),
-        pytest.param("uint16", np.float64, id="uint16"),
-        pytest.param("uint32", np.float64, id="uint32"),
-        pytest.param("uint64", np.float64, id="uint64"),
-        pytest.param("float16", np.float16, id="float16"),
-        pytest.param("float32", np.float32, id="float32"),
-        pytest.param("float64", np.float64, id="float64"),
-    ],
-)
-def test_to_numpy_pyarrow_array_pyarrow_dtypes_numeric_with_na(dtype, expected_dtype):
-    """
-    Test the _to_numpy function with PyArrow arrays of PyArrow numeric dtypes and NA.
-    """
-    data = [1.0, 2.0, None, 4.0, 5.0, 6.0]
-    if dtype == "float16":  # float16 needs special handling
-        # Example from https://arrow.apache.org/docs/python/generated/pyarrow.float16.html
-        data = np.array(data, dtype=np.float16)
-    array = pa.array(data, type=dtype)[::2]
-    result = _to_numpy(array)
-    _check_result(result, expected_dtype)
-    npt.assert_array_equal(result, array)