Fix issue #370 (energy_from_power returns incorrect index for shifted hourly data)

docs/sphinx/source/changelog.rst

@@ -1,5 +1,6 @@
 RdTools Change Log
 ==================
+.. include:: changelog/pending.rst
 .. include:: changelog/v3.0.0-beta.0.rst
 .. include:: changelog/v2.2.0-beta.2.rst
 .. include:: changelog/v2.2.0-beta.1.rst

docs/sphinx/source/changelog/pending.rst

@@ -0,0 +1,15 @@
+**************************
+v3.0.0 (December XX, 2024)
+**************************
+
+Enhancements
+------------
+* Add `CITATION.cff` file for citation information (:pull:`434`)
+* Added checks to TrendAnalysis for `filter_params` and `filter_params_aggregated`. Raises an error if unkown filter is supplied. (:pull:`436`)
+
+
+Bug fixes
+---------
+* Set marker linewidth to zero in `rdtools.plotting.degradation_summary_plots` (:pull:`433`)
+* Fix :py:func:`~rdtools.normalization.energy_from_power` returns incorrect index for shifted hourly data (:issue:`370`, :pull:`437`)
+

docs/sphinx/source/changelog/v3.0.0-beta.0.rst

@@ -22,7 +22,7 @@ Enhancements
 * Added codecov.yml configuration file (:pull:`420`)
 * Availability module no longer considered experimental (:pull:`429`)
 * Add capability to seed the CircularBlockBootstrap (:pull:`429`)
-* Allow sub-daily aggregation in :py:func:`~rdtools.degradation.degradation_year_on_year` (:pull:`390`) 
+* Allow sub-daily aggregation in :py:func:`~rdtools.degradation.degradation_year_on_year` (:pull:`390`)
 
 Bug fixes
 ---------

rdtools/normalization.py

@@ -478,9 +478,9 @@ def _aggregate(time_series, target_frequency, max_timedelta, series_type):
     '''
 
     # series that has same index as desired output
-    output_dummy = time_series.resample(target_frequency,
-                                        closed='right',
-                                        label='right').sum()
+    output_dummy = time_series.resample(
+        target_frequency, closed="right", label="right", origin="start"
+    ).sum()
 
     union_index = time_series.index.union(output_dummy.index)
     time_series = time_series.dropna()
@@ -521,13 +521,13 @@ def _aggregate(time_series, target_frequency, max_timedelta, series_type):
         raise ValueError("series_type must be either 'instantaneous' or 'right_labeled', "
                          "not '{}'".format(series_type))
 
-    series_sum = pd.Series(data=series_sum, index=time_series.index[1:])
+    series_sum = pd.Series(data=np.insert(series_sum, 0, np.nan), index=time_series.index)
 
-    aggregated = series_sum.resample(target_frequency,
-                                     closed='right',
-                                     label='right').sum(min_count=1)
+    aggregated = series_sum.resample(
+        target_frequency, closed="right", label="right", origin="start"
+    ).sum(min_count=1)
 
-    return aggregated
+    return aggregated[1:]
 
 
 def _interpolate_series(time_series, target_index, max_timedelta=None,

rdtools/test/analysis_chains_test.py

@@ -740,3 +740,21 @@ def test_plot_degradation_timeseries(sensor_analysis, clearsky_analysis):
     assert_isinstance(
         clearsky_analysis.plot_degradation_timeseries("clearsky"), plt.Figure
     )
+
+
+def test_energy_from_power_hourly_data():
+
+    times = pd.date_range("2019-01-01 00:00:00", periods=3, freq="H")
+    pv = pd.Series([1.2, 2.8, 2.0], index=times)
+
+    energy = normalization.energy_from_power(pv)
+    pd.testing.assert_series_equal(energy, pv[1:], check_names=False)
+
+
+def test_energy_from_power_shifted_hourly_data():
+
+    times = pd.date_range("2019-01-01 00:30:00", periods=3, freq="H")
+    pv = pd.Series([1.2, 2.8, 2.0], index=times)
+
+    energy = normalization.energy_from_power(pv)
+    pd.testing.assert_series_equal(energy, pv[1:], check_names=False)