pllim · May 29, 2024 · Oct 29, 2023 · May 28, 2024 · Jul 3, 2023 · Aug 10, 2023
@@ -62,8 +62,10 @@ jobs:
       envs: |
         # NOTE: this coverage test is needed for tests and code that
         #       run only with minimal dependencies.
+        # 2024-05-30: added predeps to ensure new PRs do not break numpy 2.0
+        # docs.  Fine to remove once numpy 2.0 is released (if problematic).
         - name: Python 3.12 with minimal dependencies and full coverage
-          linux: py312-test-cov
+          linux: py312-test-cov-predeps
           coverage: codecov
 
         - name: Python 3.11 in Parallel with all optional dependencies

diff --git a/astropy/conftest.py b/astropy/conftest.py
@@ -17,14 +17,9 @@
     PYTEST_HEADER_MODULES = {}
     TESTED_VERSIONS = {}
 
-import numpy as np
 import pytest
 
 from astropy import __version__
-from astropy.utils.compat.numpycompat import NUMPY_LT_2_0
-
-if not NUMPY_LT_2_0:
-    np.set_printoptions(legacy="1.25")
 
 # This is needed to silence a warning from matplotlib caused by
 # PyInstaller's matplotlib runtime hook.  This can be removed once the
@@ -67,17 +62,6 @@ def fast_thread_switching():
     sys.setswitchinterval(old)
 
 
-@pytest.fixture
-def without_legacy_printoptions():
-    # this can be removed when/after removing the call to np.set_printoptions
-    # at the top level
-    # reverting https://github.com/astropy/astropy/pull/15096
-    legacy_val = np.get_printoptions()["legacy"]
-    np.set_printoptions(legacy=False)
-    yield
-    np.set_printoptions(legacy=legacy_val)
-
-
 def pytest_configure(config):
     from astropy.utils.iers import conf as iers_conf
 

diff --git a/astropy/coordinates/baseframe.py b/astropy/coordinates/baseframe.py
@@ -1766,13 +1766,13 @@ def position_angle(self, other: BaseCoordinateFrame | SkyCoord) -> Angle:
         >>> from astropy.coordinates import ICRS, SkyCoord
         >>> c1 = SkyCoord(0*u.deg, 0*u.deg)
         >>> c2 = ICRS(1*u.deg, 0*u.deg)
-        >>> c1.position_angle(c2).degree
-        90.0
-        >>> c2.position_angle(c1).degree
-        270.0
+        >>> c1.position_angle(c2).to(u.deg)
+        <Angle 90. deg>
+        >>> c2.position_angle(c1).to(u.deg)
+        <Angle 270. deg>
         >>> c3 = SkyCoord(1*u.deg, 1*u.deg)
-        >>> c1.position_angle(c3).degree  # doctest: +FLOAT_CMP
-        44.995636455344844
+        >>> c1.position_angle(c3).to(u.deg)  # doctest: +FLOAT_CMP
+        <Angle 44.995636455344844 deg>
         """
         return position_angle(*self._prepare_unit_sphere_coords(other, "ignore"))
 

diff --git a/astropy/coordinates/tests/test_sky_coord.py b/astropy/coordinates/tests/test_sky_coord.py
@@ -766,7 +766,6 @@ def test_repr():
     assert repr(sc_default) == "<SkyCoord (ICRS): (ra, dec) in deg\n    (0., 1.)>"
 
 
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_repr_altaz():
     sc2 = SkyCoord(1 * u.deg, 1 * u.deg, frame="icrs", distance=1 * u.kpc)
 

@@ -677,7 +677,6 @@ def test_partially_identical_files1(self):
         assert "a: 2\n b: 3" in report
         assert "No differences found between common HDUs" in report
 
-    @pytest.mark.usefixtures("without_legacy_printoptions")
     def test_partially_identical_files2(self):
         """
         Test files that have some identical HDUs but one different HDU.

@@ -64,7 +64,6 @@ def test_onediff(self):
         numdiff = fitsdiff.main([tmp_a, tmp_b])
         assert numdiff == 1
 
-    @pytest.mark.usefixtures("without_legacy_printoptions")
     def test_manydiff(self, capsys):
         a = np.arange(100).reshape(10, 10)
         hdu_a = PrimaryHDU(data=a)
@@ -95,7 +94,6 @@ def test_manydiff(self, capsys):
             "     100 different pixels found (100.00% different).",
         ]
 
-    @pytest.mark.usefixtures("without_legacy_printoptions")
     def test_outputfile(self):
         a = np.arange(100).reshape(10, 10)
         hdu_a = PrimaryHDU(data=a)
@@ -148,7 +146,6 @@ def test_rtol(self):
         numdiff = fitsdiff.main(["-r", "1e-1", tmp_a, tmp_b])
         assert numdiff == 0
 
-    @pytest.mark.usefixtures("without_legacy_printoptions")
     def test_rtol_diff(self, capsys):
         a = np.arange(100, dtype=float).reshape(10, 10)
         hdu_a = PrimaryHDU(data=a)

@@ -46,7 +46,6 @@
         np.complex128(1.0 - 2**-52 + 1j * (1.0 - 2**-52)),
     ],
 )
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_numpy_types(c):
     cy = load(dump(c))
     assert c == cy

diff --git a/astropy/io/votable/tests/test_converter.py b/astropy/io/votable/tests/test_converter.py
@@ -134,7 +134,6 @@ def test_float_mask_permissive():
     assert c.parse("null", config=config) == (c.null, True)
 
 
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_double_array():
     config = {"verify": "exception", "version_1_3_or_later": True}
     field = tree.Field(None, name="c", datatype="double", arraysize="3", config=config)
@@ -278,7 +277,6 @@ def test_integer_overflow():
         c.parse("-2208988800", config=config)
 
 
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_float_default_precision():
     config = {"verify": "exception"}
 

diff --git a/astropy/io/votable/tests/test_vo.py b/astropy/io/votable/tests/test_vo.py
@@ -178,23 +178,20 @@ def _test_regression(tmp_path, _python_based=False, binary_mode=1):
 
 
 @pytest.mark.xfail("legacy_float_repr")
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_regression(tmp_path):
     # W39: Bit values can not be masked
     with pytest.warns(W39), np.errstate(over="ignore"):
         _test_regression(tmp_path, False)
 
 
 @pytest.mark.xfail("legacy_float_repr")
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_regression_python_based_parser(tmp_path):
     # W39: Bit values can not be masked
     with pytest.warns(W39), np.errstate(over="ignore"):
         _test_regression(tmp_path, True)
 
 
 @pytest.mark.xfail("legacy_float_repr")
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_regression_binary2(tmp_path):
     # W39: Bit values can not be masked
     with pytest.warns(W39), np.errstate(over="ignore"):
@@ -267,7 +264,6 @@ def test_iter_coosys(self):
         pytest.param(["c1", "string_test", "c2"], ["c1", "c2"], id="list-only-missing"),
     ],
 )
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_select_missing_columns_error_message(columns, expected_missing):
     # see https://github.com/astropy/astropy/pull/15956
     filename = get_pkg_data_filename("data/regression.xml")
@@ -461,7 +457,6 @@ def test_long(self):
         )
         assert_array_equal(self.mask["long"], [False, True, False, False, True])
 
-    @pytest.mark.usefixtures("without_legacy_printoptions")
     def test_double(self):
         assert issubclass(self.array["double"].dtype.type, np.float64)
         assert_array_equal(
@@ -642,7 +637,6 @@ def test_nulls_array(self):
             ],
         )
 
-    @pytest.mark.usefixtures("without_legacy_printoptions")
     def test_double_array(self):
         assert issubclass(self.array["doublearray"].dtype.type, np.object_)
         assert len(self.array["doublearray"][0]) == 0
@@ -698,7 +692,6 @@ def test_get_info_by_id(self):
             info = self.votable.get_info_by_id("ErrorInfo")
             assert info.value == "One might expect to find some INFO here, too..."
 
-    @pytest.mark.usefixtures("without_legacy_printoptions")
     def test_repr(self):
         assert "3 tables" in repr(self.votable)
         assert (
@@ -877,7 +870,6 @@ def test_too_many_columns():
         parse(get_pkg_data_filename("data/too_many_columns.xml.gz"))
 
 
-@pytest.mark.usefixtures("without_legacy_printoptions")
 def test_build_from_scratch(tmp_path):
     # Create a new VOTable file...
     votable = tree.VOTableFile()

@@ -95,7 +95,7 @@ def bayesian_info_criterion(log_likelihood, n_params, n_samples):
     >>> bic_g = bayesian_info_criterion(lnL_g, n_params_g, n_samples)
     >>> bic_t = bayesian_info_criterion(lnL_t, n_params_t, n_samples)
     >>> bic_g - bic_t # doctest: +FLOAT_CMP
-    2.1948298140119391
+    np.float64(2.1948298140119391)
 
     Therefore, there exist a moderate evidence that the increasing in
     likelihood for t-Student model is due to the larger number of parameters.
@@ -385,11 +385,11 @@ def akaike_info_criterion_lsq(ssr, n_params, n_samples):
     >>> ssr_g2 = np.sum((g2_fit(x) - y)**2.0)
     >>> ssr_g1 = np.sum((g1_fit(x) - y)**2.0)
     >>> akaike_info_criterion_lsq(ssr_g3, 9, x.shape[0]) # doctest: +FLOAT_CMP
-    -634.5257517810961
+    np.float64(-634.5257517810961)
     >>> akaike_info_criterion_lsq(ssr_g2, 6, x.shape[0]) # doctest: +FLOAT_CMP
-    -662.83834510232043
+    np.float64(-662.83834510232043)
     >>> akaike_info_criterion_lsq(ssr_g1, 3, x.shape[0]) # doctest: +FLOAT_CMP
-    -647.47312032659499
+    np.float64(-647.47312032659499)
 
     Hence, from the AIC values, we would prefer to choose the model g2_fit.
     However, we can considerably support the model g3_fit, since the

@@ -116,11 +116,11 @@ def jackknife_stats(data, statistic, confidence_level=0.95):
     >>> estimate, bias, stderr, conf_interval = jackknife_stats(
     ...     data, test_statistic, 0.95)
     >>> estimate
-    4.5
+    np.float64(4.5)
     >>> bias
-    0.0
+    np.float64(0.0)
     >>> stderr  # doctest: +FLOAT_CMP
-    0.95742710775633832
+    np.float64(0.95742710775633832)
     >>> conf_interval
     array([2.62347735,  6.37652265])