[Tests] Fix failing tests in 3.12

 Use np.isclose() and isinstance()

enlopy/generate.py

@@ -84,13 +84,13 @@ def gen_load_from_daily_monthly(ML, DWL, DNWL, weight=0.5, year=2015):
     if not(np.isclose(DWL.sum(), 1) and np.isclose(DNWL.sum(), 1)):
         raise ValueError('Daily profiles should be normalized')
         #TODO: Normalize here?
-    out = make_timeseries(year=year, length=8760, freq='H')  # Create empty pandas with datetime index
+    out = make_timeseries(year=year, length=8760, freq='h')  # Create empty pandas with datetime index
     import calendar
     febdays = 29 if calendar.isleap(year) else 28
     Days = np.array([31, febdays, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31])
     # Assumptions for non working days per month. Only weekends
     # TODO: Custom Calendars with holidays BDays
-    DaysNW = countweekend_days_per_month(out.resample('d').mean())
+    DaysNW = countweekend_days_per_month(out.resample('D').mean())
     DaysW = Days - DaysNW
     for month in range(12):
         # Estimate total load for working and non working day

tests/test_utils.py

@@ -10,45 +10,45 @@ def test_ndarray_h(self):
         a = np.random.rand(8760)
         b = make_timeseries(a)
         assert isinstance(b, pd.Series)
-        assert sum(a) == sum(b)
+        assert np.isclose(sum(a), sum(b))
 
     def test_ndarray_15m(self):
         a = np.random.rand(35040)
         b = make_timeseries(a)
         assert isinstance(b, pd.Series)
-        assert sum(a) == sum(b)
+        assert np.isclose(sum(a), sum(b))
 
     def test_ndarray_x(self):
         a = np.random.rand(8730)
         b = make_timeseries(a, freq='h')
         assert isinstance(b, pd.Series)
-        assert sum(a) == sum(b)
+        assert np.isclose(sum(a), sum(b))
 
     def test_pdseries(self):
         a = pd.Series(np.random.rand(8760))
         b = make_timeseries(a)
         assert isinstance(b, pd.Series)
-        assert sum(a) == sum(b)
+        assert np.isclose(sum(a), sum(b))
 
     def test_pddataframe(self):
         a = pd.DataFrame(np.random.rand(8760))
         b = make_timeseries(a)
-        assert type(b) == pd.DataFrame
+        assert isinstance(b, pd.DataFrame)
 
     def test_pddataframe_2d(self):
         a = pd.DataFrame(np.random.rand(35040,3))
         b = make_timeseries(a)
-        assert type(b) == pd.DataFrame
+        assert isinstance(b, pd.DataFrame)
 
     def test_2d_ndarray(self):
         a = np.random.rand(8760,5)
         b = make_timeseries(a)
-        assert type(b) == pd.DataFrame
+        assert isinstance(b, pd.DataFrame)
 
     def test_empty_frame(self):
         a = np.array([])
         b = make_timeseries(a, freq='h')
-        assert type(b) == pd.Series and len(b)==0
+        assert isinstance(b, pd.Series) and len(b)==0
 
     def test_empty_frame_to_indexed_empty(self):
         b = make_timeseries(freq='h', length=8760)
@@ -58,7 +58,7 @@ def test_multiannual_timeseries(self):
         a = np.random.rand(8760*2)
         b = make_timeseries(a, freq='h')
         assert isinstance(b, pd.Series)
-        assert sum(a) == sum(b)
+        assert np.isclose(sum(a), sum(b))
 
 
 class Test_clean_convert():