Merge 085ae9a into 8e3a220

hpat/datatypes/hpat_pandas_series_functions.py

@@ -657,6 +657,45 @@ def hpat_pandas_series_isna_impl(self):
         return hpat_pandas_series_isna_impl
 
 
+@overload_method(SeriesType, 'notna')
+def hpat_pandas_series_notna(self):
+    """
+    Pandas Series method :meth:`pandas.Series.notna` implementation.
+
+    .. only:: developer
+
+        Test: python -m -k hpat.runtests hpat.tests.test_series.TestSeries.test_series_notna*
+
+    Parameters
+    -----------
+    self : :obj:`pandas.Series` object
+        input series
+
+    Returns
+    -------
+    :obj:`pandas.Series`
+         returns :obj:`pandas.Series` object
+    """
+
+    _func_name = 'Method notna().'
+
+    if not isinstance(self, SeriesType):
+        raise TypingError('{} The object must be a pandas.series. Given: {}'.format(_func_name, self))
+
+    if isinstance(self.data.dtype, types.Number):
+        def hpat_pandas_series_notna_impl(self):
+            return pandas.Series(numpy.invert(numpy.isnan(self._data)))
+
+        return hpat_pandas_series_notna_impl
+
+    if isinstance(self.data.dtype, types.UnicodeType):
+        def hpat_pandas_series_notna_impl(self):
+            result = self.isna()
+            return pandas.Series(numpy.invert(result._data))
+
+        return hpat_pandas_series_notna_impl
+
+
 @overload_method(SeriesType, 'ne')
 def hpat_pandas_series_ne(self, other, level=None, fill_value=None, axis=0):
     """

hpat/hiframes/hiframes_typed.py

@@ -1006,10 +1006,10 @@ def run_call_series_quantile_default(A):
                 func = series_replace_funcs['append_tuple']
             return self._replace_func(func, [data, other], pre_nodes=nodes)
 
-        if func_name == 'notna':
-            # TODO: make sure this is fused and optimized properly
-            return self._replace_func(
-                lambda S: S.isna() == False, [series_var])
+        # if func_name == 'notna':
+        #     # TODO: make sure this is fused and optimized properly
+        #     return self._replace_func(
+        #         lambda S: S.isna() == False, [series_var])
 
         if func_name == 'value_counts':
             nodes = []

hpat/hiframes/pd_series_ext.py

@@ -666,11 +666,11 @@ def resolve_isnull(self, ary, args, kws):
         assert not args
         return signature(SeriesType(types.boolean))
 
-    @bound_function("series.notna")
-    def resolve_notna(self, ary, args, kws):
-        assert not kws
-        assert not args
-        return signature(SeriesType(types.boolean))
+    # @bound_function("series.notna")
+    # def resolve_notna(self, ary, args, kws):
+    #     assert not kws
+    #     assert not args
+    #     return signature(SeriesType(types.boolean))
 
     @bound_function("series.nlargest")
     def resolve_nlargest(self, ary, args, kws):

hpat/tests/test_series.py

@@ -1756,6 +1756,60 @@ def test_impl(S):
         S = pd.Series([np.nan, 2., 3.])
         pd.testing.assert_series_equal(hpat_func(S), test_impl(S))
 
+    def test_series_notna_noidx_float(self):
+        def test_impl(S):
+            return S.notna()
+
+        hpat_func = hpat.jit(test_impl)
+        for input_data in test_global_input_data_float64:
+            S = pd.Series(input_data)
+            result_ref = test_impl(S)
+            result_jit = hpat_func(S)
+            pd.testing.assert_series_equal(result_jit, result_ref)
+
+    @unittest.skip("Need fix test_global_input_data_integer64")
+    def test_series_notna_noidx_int(self):
+        def test_impl(S):
+            return S.notna()
+
+        hpat_func = hpat.jit(test_impl)
+        for input_data in test_global_input_data_integer64:
+            S = pd.Series(input_data)
+            result_ref = test_impl(S)
+            result_jit = hpat_func(S)
+            pd.testing.assert_series_equal(result_jit, result_ref)
+
+    @unittest.skip("Need fix test_global_input_data_integer64")
+    def test_series_notna_noidx_num(self):
+        def test_impl(S):
+            return S.notna()
+
+        hpat_func = hpat.jit(test_impl)
+        for input_data in test_global_input_data_numeric:
+            S = pd.Series(input_data)
+            result_ref = test_impl(S)
+            result_jit = hpat_func(S)
+            pd.testing.assert_series_equal(result_jit, result_ref)
+
+    def test_series_notna_noidx_str(self):
+        def test_impl(S):
+            return S.notna()
+
+        hpat_func = hpat.jit(test_impl)
+        input_data = test_global_input_data_unicode_kind4
+        S = pd.Series(input_data)
+        result_ref = test_impl(S)
+        result_jit = hpat_func(S)
+        pd.testing.assert_series_equal(result_jit, result_ref)
+
+    def test_series_str_notna(self):
+        def test_impl(S):
+            return S.notna()
+        hpat_func = hpat.jit(test_impl)
+
+        S = pd.Series(['aa', None, 'c', 'cccd'])
+        pd.testing.assert_series_equal(hpat_func(S), test_impl(S))
+
     def test_series_str_isna1(self):
         def test_impl(S):
             return S.isna()