Relax tolerance of some tests for numpy 1.22

Most likely as a consequence of numpy now supporting the faster but
slightly less precise Intel Short Vector Math Library (SVML), some of
our tests are failing, in ways that are not really interesting.  So,
up the tolerance slightly.

See numpy/numpy#19478

astropy/coordinates/tests/test_matching.py

@@ -167,7 +167,7 @@ def test_search_around():
     idx1_0p05deg, idx2_0p05deg, d2d_0p05deg, d3d_0p05deg = search_around_sky(coo1, coo2, 0.05*u.deg)
 
     assert list(zip(idx1_1deg, idx2_1deg)) == [(0, 2), (0, 3), (1, 1), (1, 2)]
-    assert d2d_1deg[0] == 1.0*u.deg
+    assert_allclose(d2d_1deg[0], 1.0*u.deg, atol=1e-14*u.deg, rtol=0)
     assert_allclose(d2d_1deg, [1, 0, .1, .9]*u.deg)
 
     assert list(zip(idx1_0p05deg, idx2_0p05deg)) == [(0, 3)]

astropy/coordinates/tests/test_sky_coord.py

@@ -1886,10 +1886,10 @@ def test_match_to_catalog_3d_and_sky():
 
     idx, angle, quantity = cfk5_J1950.match_to_catalog_3d(cfk5_default)
     npt.assert_array_equal(idx, [0, 1, 2, 3])
-    assert_allclose(angle, 0*u.deg, atol=1e-15*u.deg, rtol=0)
+    assert_allclose(angle, 0*u.deg, atol=2e-15*u.deg, rtol=0)
     assert_allclose(quantity, 0*u.kpc, atol=1e-15*u.kpc, rtol=0)
 
     idx, angle, distance = cfk5_J1950.match_to_catalog_sky(cfk5_default)
     npt.assert_array_equal(idx, [0, 1, 2, 3])
-    assert_allclose(angle, 0 * u.deg, atol=1e-15*u.deg, rtol=0)
-    assert_allclose(distance, 0*u.kpc, atol=1e-15*u.kpc, rtol=0)
+    assert_allclose(angle, 0 * u.deg, atol=2e-15*u.deg, rtol=0)
+    assert_allclose(distance, 0*u.kpc, atol=2e-15*u.kpc, rtol=0)