[DEPR] remove pd.index.is_all_dates

enlopy/generate.py

@@ -388,7 +388,7 @@ def gen_demand_response(Load, percent_peak_hrs_month=0.03, percent_shifted=0.05,
     Return:
         pd.Series: New load profile with reduced peaks. The peak can be shifted to low load hours or shaved
     """
-    if not Load.index.is_all_dates:
+    if not isinstance(Load.index, pd.DatetimeIndex):
         print ('Need date Time indexed series. Trying to force one.')
         Load = clean_convert(Load, force_timed_index=True)
     demand = Load

enlopy/utils.py

@@ -123,7 +123,7 @@ def clean_convert(x, force_timed_index=True, always_df=False, **kwargs):
     elif isinstance(x, pd.Series):
         if always_df:
             x = pd.DataFrame(x)
-        if x.index.is_all_dates:
+        if isinstance(x.index, pd.DatetimeIndex):
             return x
         else:  # if not datetime index
             if force_timed_index:
@@ -137,7 +137,7 @@ def clean_convert(x, force_timed_index=True, always_df=False, **kwargs):
         if x.shape[1] == 1 and not always_df:
             return clean_convert(x.squeeze(), force_timed_index, always_df, **kwargs)
         else:
-            if force_timed_index and not x.index.is_all_dates:
+            if force_timed_index and not isinstance(x.index, pd.DatetimeIndex):
                 return make_timeseries(x, **kwargs)
             else:  # does not require datetimeindex
                 return x

tests/test_utils.py

@@ -66,22 +66,22 @@ class Test_clean_convert():
     def test_ndarray_to_series_indexed(self):
         a = np.random.rand(8760)
         b = clean_convert(a, force_timed_index=True, always_df=False)
-        assert isinstance(b, pd.Series) and b.index.is_all_dates
+        assert isinstance(b, pd.Series) and isinstance(b.index, pd.DatetimeIndex)
 
     def test_ndarray_to_df_indexed(self):
         a = np.random.rand(8760)
         b = clean_convert(a, force_timed_index=True, always_df=True)
-        assert isinstance(b, pd.DataFrame) and b.index.is_all_dates
+        assert isinstance(b, pd.DataFrame) and isinstance(b.index, pd.DatetimeIndex)
 
     def test_1d_series_to_frame(self):
         a = pd.Series(np.random.rand(8760))
         b = clean_convert(a, force_timed_index=True, always_df=True)
-        assert isinstance(b, pd.DataFrame) and b.index.is_all_dates
+        assert isinstance(b, pd.DataFrame) and isinstance(b.index, pd.DatetimeIndex)
 
     def test_2d_ndarray_to_df_indexed(self):
         a = np.random.rand(8760, 2)
         b = clean_convert(a, force_timed_index=True, always_df=True)
-        assert isinstance(b, pd.DataFrame) and b.index.is_all_dates
+        assert isinstance(b, pd.DataFrame) and isinstance(b.index, pd.DatetimeIndex)
 
     def test_list_to_series(self):
         a = list(np.random.rand(8760))