diff options
Diffstat (limited to 'numpy/lib/tests')
| -rw-r--r-- | numpy/lib/tests/test_nanfunctions.py | 50 | ||||
| -rw-r--r-- | numpy/lib/tests/test_polynomial.py | 31 |
2 files changed, 60 insertions, 21 deletions
diff --git a/numpy/lib/tests/test_nanfunctions.py b/numpy/lib/tests/test_nanfunctions.py index e0f723a3c..1f1f5601b 100644 --- a/numpy/lib/tests/test_nanfunctions.py +++ b/numpy/lib/tests/test_nanfunctions.py @@ -588,6 +588,15 @@ class TestNanFunctions_MeanVarStd(SharedNanFunctionsTestsMixin): assert_(len(w) == 0) +_TIME_UNITS = ( + "Y", "M", "W", "D", "h", "m", "s", "ms", "us", "ns", "ps", "fs", "as" +) + +# All `inexact` + `timdelta64` type codes +_TYPE_CODES = list(np.typecodes["AllFloat"]) +_TYPE_CODES += [f"m8[{unit}]" for unit in _TIME_UNITS] + + class TestNanFunctions_Median: def test_mutation(self): @@ -662,23 +671,32 @@ class TestNanFunctions_Median: res = np.nanmedian(_ndat, axis=1) assert_almost_equal(res, tgt) - def test_allnans(self): - mat = np.array([np.nan]*9).reshape(3, 3) - for axis in [None, 0, 1]: - with suppress_warnings() as sup: - sup.record(RuntimeWarning) + @pytest.mark.parametrize("axis", [None, 0, 1]) + @pytest.mark.parametrize("dtype", _TYPE_CODES) + def test_allnans(self, dtype, axis): + mat = np.full((3, 3), np.nan).astype(dtype) + with suppress_warnings() as sup: + sup.record(RuntimeWarning) - assert_(np.isnan(np.nanmedian(mat, axis=axis)).all()) - if axis is None: - assert_(len(sup.log) == 1) - else: - assert_(len(sup.log) == 3) - # Check scalar - assert_(np.isnan(np.nanmedian(np.nan))) - if axis is None: - assert_(len(sup.log) == 2) - else: - assert_(len(sup.log) == 4) + output = np.nanmedian(mat, axis=axis) + assert output.dtype == mat.dtype + assert np.isnan(output).all() + + if axis is None: + assert_(len(sup.log) == 1) + else: + assert_(len(sup.log) == 3) + + # Check scalar + scalar = np.array(np.nan).astype(dtype)[()] + output_scalar = np.nanmedian(scalar) + assert output_scalar.dtype == scalar.dtype + assert np.isnan(output_scalar) + + if axis is None: + assert_(len(sup.log) == 2) + else: + assert_(len(sup.log) == 4) def test_empty(self): mat = np.zeros((0, 3)) diff --git a/numpy/lib/tests/test_polynomial.py b/numpy/lib/tests/test_polynomial.py index 6c3e4fa02..3734344d2 100644 --- a/numpy/lib/tests/test_polynomial.py +++ b/numpy/lib/tests/test_polynomial.py @@ -4,6 +4,12 @@ from numpy.testing import ( assert_array_almost_equal, assert_raises, assert_allclose ) +import pytest + +# `poly1d` has some support for `bool_` and `timedelta64`, +# but it is limited and they are therefore excluded here +TYPE_CODES = np.typecodes["AllInteger"] + np.typecodes["AllFloat"] + "O" + class TestPolynomial: def test_poly1d_str_and_repr(self): @@ -57,11 +63,26 @@ class TestPolynomial: assert_equal(np.polydiv(np.poly1d([1, 0, -1]), np.poly1d([1, 1])), (np.poly1d([1., -1.]), np.poly1d([0.]))) - def test_poly1d_misc(self): - p = np.poly1d([1., 2, 3]) - assert_equal(np.asarray(p), np.array([1., 2., 3.])) + @pytest.mark.parametrize("type_code", TYPE_CODES) + def test_poly1d_misc(self, type_code: str) -> None: + dtype = np.dtype(type_code) + ar = np.array([1, 2, 3], dtype=dtype) + p = np.poly1d(ar) + + # `__eq__` + assert_equal(np.asarray(p), ar) + assert_equal(np.asarray(p).dtype, dtype) assert_equal(len(p), 2) - assert_equal((p[0], p[1], p[2], p[3]), (3.0, 2.0, 1.0, 0)) + + # `__getitem__` + comparison_dct = {-1: 0, 0: 3, 1: 2, 2: 1, 3: 0} + for index, ref in comparison_dct.items(): + scalar = p[index] + assert_equal(scalar, ref) + if dtype == np.object_: + assert isinstance(scalar, int) + else: + assert_equal(scalar.dtype, dtype) def test_poly1d_variable_arg(self): q = np.poly1d([1., 2, 3], variable='y') @@ -257,7 +278,7 @@ class TestPolynomial: assert_equal(q.coeffs.dtype, np.complex128) assert_equal(r.coeffs.dtype, np.complex128) assert_equal(q*a + r, b) - + c = [1, 2, 3] d = np.poly1d([1, 2, 3]) s, t = np.polydiv(c, d) |