TST: fixturize skipna in test_nanops (pandas-dev#32607)

Author: jbrockmendel

pandas/tests/test_nanops.py

@@ -19,6 +19,14 @@
 has_c16 = hasattr(np, "complex128")
 
 
+@pytest.fixture(params=[True, False])
+def skipna(request):
+    """
+    Fixture to pass skipna to nanops functions.
+    """
+    return request.param
+
+
 class TestnanopsDataFrame:
     def setup_method(self, method):
         np.random.seed(11235)
@@ -89,38 +97,22 @@ def teardown_method(self, method):
 
     def check_results(self, targ, res, axis, check_dtype=True):
         res = getattr(res, "asm8", res)
-        res = getattr(res, "values", res)
-
-        # timedeltas are a beast here
-        def _coerce_tds(targ, res):
-            if hasattr(targ, "dtype") and targ.dtype == "m8[ns]":
-                if len(targ) == 1:
-                    targ = targ[0].item()
-                    res = res.item()
-                else:
-                    targ = targ.view("i8")
-            return targ, res
 
-        try:
-            if (
-                axis != 0
-                and hasattr(targ, "shape")
-                and targ.ndim
-                and targ.shape != res.shape
-            ):
-                res = np.split(res, [targ.shape[0]], axis=0)[0]
-        except (ValueError, IndexError):
-            targ, res = _coerce_tds(targ, res)
+        if (
+            axis != 0
+            and hasattr(targ, "shape")
+            and targ.ndim
+            and targ.shape != res.shape
+        ):
+            res = np.split(res, [targ.shape[0]], axis=0)[0]
 
         try:
             tm.assert_almost_equal(targ, res, check_dtype=check_dtype)
         except AssertionError:
 
             # handle timedelta dtypes
             if hasattr(targ, "dtype") and targ.dtype == "m8[ns]":
-                targ, res = _coerce_tds(targ, res)
-                tm.assert_almost_equal(targ, res, check_dtype=check_dtype)
-                return
+                raise
 
             # There are sometimes rounding errors with
             # complex and object dtypes.
@@ -149,29 +141,29 @@ def check_fun_data(
         targfunc,
         testarval,
         targarval,
+        skipna,
         check_dtype=True,
         empty_targfunc=None,
         **kwargs,
     ):
         for axis in list(range(targarval.ndim)) + [None]:
-            for skipna in [False, True]:
-                targartempval = targarval if skipna else testarval
-                if skipna and empty_targfunc and isna(targartempval).all():
-                    targ = empty_targfunc(targartempval, axis=axis, **kwargs)
-                else:
-                    targ = targfunc(targartempval, axis=axis, **kwargs)
+            targartempval = targarval if skipna else testarval
+            if skipna and empty_targfunc and isna(targartempval).all():
+                targ = empty_targfunc(targartempval, axis=axis, **kwargs)
+            else:
+                targ = targfunc(targartempval, axis=axis, **kwargs)
 
-                res = testfunc(testarval, axis=axis, skipna=skipna, **kwargs)
+            res = testfunc(testarval, axis=axis, skipna=skipna, **kwargs)
+            self.check_results(targ, res, axis, check_dtype=check_dtype)
+            if skipna:
+                res = testfunc(testarval, axis=axis, **kwargs)
+                self.check_results(targ, res, axis, check_dtype=check_dtype)
+            if axis is None:
+                res = testfunc(testarval, skipna=skipna, **kwargs)
+                self.check_results(targ, res, axis, check_dtype=check_dtype)
+            if skipna and axis is None:
+                res = testfunc(testarval, **kwargs)
                 self.check_results(targ, res, axis, check_dtype=check_dtype)
-                if skipna:
-                    res = testfunc(testarval, axis=axis, **kwargs)
-                    self.check_results(targ, res, axis, check_dtype=check_dtype)
-                if axis is None:
-                    res = testfunc(testarval, skipna=skipna, **kwargs)
-                    self.check_results(targ, res, axis, check_dtype=check_dtype)
-                if skipna and axis is None:
-                    res = testfunc(testarval, **kwargs)
-                    self.check_results(targ, res, axis, check_dtype=check_dtype)
 
         if testarval.ndim <= 1:
             return
@@ -184,12 +176,15 @@ def check_fun_data(
             targfunc,
             testarval2,
             targarval2,
+            skipna=skipna,
             check_dtype=check_dtype,
             empty_targfunc=empty_targfunc,
             **kwargs,
         )
 
-    def check_fun(self, testfunc, targfunc, testar, empty_targfunc=None, **kwargs):
+    def check_fun(
+        self, testfunc, targfunc, testar, skipna, empty_targfunc=None, **kwargs
+    ):
 
         targar = testar
         if testar.endswith("_nan") and hasattr(self, testar[:-4]):
@@ -202,6 +197,7 @@ def check_fun(self, testfunc, targfunc, testar, empty_targfunc=None, **kwargs):
             targfunc,
             testarval,
             targarval,
+            skipna=skipna,
             empty_targfunc=empty_targfunc,
             **kwargs,
         )
@@ -210,36 +206,37 @@ def check_funs(
         self,
         testfunc,
         targfunc,
+        skipna,
         allow_complex=True,
         allow_all_nan=True,
         allow_date=True,
         allow_tdelta=True,
         allow_obj=True,
         **kwargs,
     ):
-        self.check_fun(testfunc, targfunc, "arr_float", **kwargs)
-        self.check_fun(testfunc, targfunc, "arr_float_nan", **kwargs)
-        self.check_fun(testfunc, targfunc, "arr_int", **kwargs)
-        self.check_fun(testfunc, targfunc, "arr_bool", **kwargs)
+        self.check_fun(testfunc, targfunc, "arr_float", skipna, **kwargs)
+        self.check_fun(testfunc, targfunc, "arr_float_nan", skipna, **kwargs)
+        self.check_fun(testfunc, targfunc, "arr_int", skipna, **kwargs)
+        self.check_fun(testfunc, targfunc, "arr_bool", skipna, **kwargs)
         objs = [
             self.arr_float.astype("O"),
             self.arr_int.astype("O"),
             self.arr_bool.astype("O"),
         ]
 
         if allow_all_nan:
-            self.check_fun(testfunc, targfunc, "arr_nan", **kwargs)
+            self.check_fun(testfunc, targfunc, "arr_nan", skipna, **kwargs)
 
         if allow_complex:
-            self.check_fun(testfunc, targfunc, "arr_complex", **kwargs)
-            self.check_fun(testfunc, targfunc, "arr_complex_nan", **kwargs)
+            self.check_fun(testfunc, targfunc, "arr_complex", skipna, **kwargs)
+            self.check_fun(testfunc, targfunc, "arr_complex_nan", skipna, **kwargs)
             if allow_all_nan:
-                self.check_fun(testfunc, targfunc, "arr_nan_nanj", **kwargs)
+                self.check_fun(testfunc, targfunc, "arr_nan_nanj", skipna, **kwargs)
             objs += [self.arr_complex.astype("O")]
 
         if allow_date:
             targfunc(self.arr_date)
-            self.check_fun(testfunc, targfunc, "arr_date", **kwargs)
+            self.check_fun(testfunc, targfunc, "arr_date", skipna, **kwargs)
             objs += [self.arr_date.astype("O")]
 
         if allow_tdelta:
@@ -248,7 +245,7 @@ def check_funs(
             except TypeError:
                 pass
             else:
-                self.check_fun(testfunc, targfunc, "arr_tdelta", **kwargs)
+                self.check_fun(testfunc, targfunc, "arr_tdelta", skipna, **kwargs)
                 objs += [self.arr_tdelta.astype("O")]
 
         if allow_obj:
@@ -260,7 +257,7 @@ def check_funs(
                 targfunc = partial(
                     self._badobj_wrap, func=targfunc, allow_complex=allow_complex
                 )
-            self.check_fun(testfunc, targfunc, "arr_obj", **kwargs)
+            self.check_fun(testfunc, targfunc, "arr_obj", skipna, **kwargs)
 
     def _badobj_wrap(self, value, func, allow_complex=True, **kwargs):
         if value.dtype.kind == "O":
@@ -273,28 +270,22 @@ def _badobj_wrap(self, value, func, allow_complex=True, **kwargs):
     @pytest.mark.parametrize(
         "nan_op,np_op", [(nanops.nanany, np.any), (nanops.nanall, np.all)]
     )
-    def test_nan_funcs(self, nan_op, np_op):
-        # TODO: allow tdelta, doesn't break tests
-        self.check_funs(
-            nan_op, np_op, allow_all_nan=False, allow_date=False, allow_tdelta=False
-        )
+    def test_nan_funcs(self, nan_op, np_op, skipna):
+        self.check_funs(nan_op, np_op, skipna, allow_all_nan=False, allow_date=False)
 
-    def test_nansum(self):
+    def test_nansum(self, skipna):
         self.check_funs(
             nanops.nansum,
             np.sum,
+            skipna,
             allow_date=False,
             check_dtype=False,
             empty_targfunc=np.nansum,
         )
 
-    def test_nanmean(self):
+    def test_nanmean(self, skipna):
         self.check_funs(
-            nanops.nanmean,
-            np.mean,
-            allow_complex=False,  # TODO: allow this, doesn't break test
-            allow_obj=False,
-            allow_date=False,
+            nanops.nanmean, np.mean, skipna, allow_obj=False, allow_date=False,
         )
 
     def test_nanmean_overflow(self):
@@ -336,33 +327,36 @@ def test_returned_dtype(self, dtype):
             else:
                 assert result.dtype == dtype
 
-    def test_nanmedian(self):
+    def test_nanmedian(self, skipna):
         with warnings.catch_warnings(record=True):
             warnings.simplefilter("ignore", RuntimeWarning)
             self.check_funs(
                 nanops.nanmedian,
                 np.median,
+                skipna,
                 allow_complex=False,
                 allow_date=False,
                 allow_obj="convert",
             )
 
     @pytest.mark.parametrize("ddof", range(3))
-    def test_nanvar(self, ddof):
+    def test_nanvar(self, ddof, skipna):
         self.check_funs(
             nanops.nanvar,
             np.var,
+            skipna,
             allow_complex=False,
             allow_date=False,
             allow_obj="convert",
             ddof=ddof,
         )
 
     @pytest.mark.parametrize("ddof", range(3))
-    def test_nanstd(self, ddof):
+    def test_nanstd(self, ddof, skipna):
         self.check_funs(
             nanops.nanstd,
             np.std,
+            skipna,
             allow_complex=False,
             allow_date=False,
             allow_obj="convert",
@@ -371,13 +365,14 @@ def test_nanstd(self, ddof):
 
     @td.skip_if_no_scipy
     @pytest.mark.parametrize("ddof", range(3))
-    def test_nansem(self, ddof):
+    def test_nansem(self, ddof, skipna):
         from scipy.stats import sem
 
         with np.errstate(invalid="ignore"):
             self.check_funs(
                 nanops.nansem,
                 sem,
+                skipna,
                 allow_complex=False,
                 allow_date=False,
                 allow_tdelta=False,
@@ -388,10 +383,10 @@ def test_nansem(self, ddof):
     @pytest.mark.parametrize(
         "nan_op,np_op", [(nanops.nanmin, np.min), (nanops.nanmax, np.max)]
     )
-    def test_nanops_with_warnings(self, nan_op, np_op):
+    def test_nanops_with_warnings(self, nan_op, np_op, skipna):
         with warnings.catch_warnings(record=True):
             warnings.simplefilter("ignore", RuntimeWarning)
-            self.check_funs(nan_op, np_op, allow_obj=False)
+            self.check_funs(nan_op, np_op, skipna, allow_obj=False)
 
     def _argminmax_wrap(self, value, axis=None, func=None):
         res = func(value, axis)
@@ -408,17 +403,17 @@ def _argminmax_wrap(self, value, axis=None, func=None):
             res = -1
         return res
 
-    def test_nanargmax(self):
+    def test_nanargmax(self, skipna):
         with warnings.catch_warnings(record=True):
             warnings.simplefilter("ignore", RuntimeWarning)
             func = partial(self._argminmax_wrap, func=np.argmax)
-            self.check_funs(nanops.nanargmax, func, allow_obj=False)
+            self.check_funs(nanops.nanargmax, func, skipna, allow_obj=False)
 
-    def test_nanargmin(self):
+    def test_nanargmin(self, skipna):
         with warnings.catch_warnings(record=True):
             warnings.simplefilter("ignore", RuntimeWarning)
             func = partial(self._argminmax_wrap, func=np.argmin)
-            self.check_funs(nanops.nanargmin, func, allow_obj=False)
+            self.check_funs(nanops.nanargmin, func, skipna, allow_obj=False)
 
     def _skew_kurt_wrap(self, values, axis=None, func=None):
         if not isinstance(values.dtype.type, np.floating):
@@ -433,21 +428,22 @@ def _skew_kurt_wrap(self, values, axis=None, func=None):
         return result
 
     @td.skip_if_no_scipy
-    def test_nanskew(self):
+    def test_nanskew(self, skipna):
         from scipy.stats import skew
 
         func = partial(self._skew_kurt_wrap, func=skew)
         with np.errstate(invalid="ignore"):
             self.check_funs(
                 nanops.nanskew,
                 func,
+                skipna,
                 allow_complex=False,
                 allow_date=False,
                 allow_tdelta=False,
             )
 
     @td.skip_if_no_scipy
-    def test_nankurt(self):
+    def test_nankurt(self, skipna):
         from scipy.stats import kurtosis
 
         func1 = partial(kurtosis, fisher=True)
@@ -456,15 +452,17 @@ def test_nankurt(self):
             self.check_funs(
                 nanops.nankurt,
                 func,
+                skipna,
                 allow_complex=False,
                 allow_date=False,
                 allow_tdelta=False,
             )
 
-    def test_nanprod(self):
+    def test_nanprod(self, skipna):
         self.check_funs(
             nanops.nanprod,
             np.prod,
+            skipna,
             allow_date=False,
             allow_tdelta=False,
             empty_targfunc=np.nanprod,