fix for windnet ad

india_forecast_app/models/pvnet/model.py

@@ -263,9 +263,13 @@ def _prepare_data_sources(self):
 
             # Save generation data as netcdf file
             generation_da = self.generation_data["data"].to_xarray()
+
+            # get the minimum timestamp in generation data
+            min_timestamp = generation_da.index.min().values
             # Add the forecast timesteps to the generation, with 0 values
+            # 192 is 48 hours of 15 min intervals
             forecast_timesteps = pd.date_range(
-                start=self.t0 - pd.Timedelta("1H"), periods=197, freq="15min"
+                start=min_timestamp, periods=len(generation_da.index) + 192, freq="15min"
             )
 
             generation_da = generation_da.reindex(index=forecast_timesteps, fill_value=0.00001)

tests/test_app.py

@@ -210,11 +210,13 @@ def test_app_client_ad(
 
     app_run(timestamp=None, write_to_db=True)
 
-    n_forecasts = 2 * 2
-    # one model is 8 hours, one model is 4 hours
+    # 2 pv models, 1 wind model
+    # x2 for adjuster
+    n_forecasts = 3 * 2
+    # one models is 8 hours, two model is 4 hours
     # x 4 for each 15 minutes
     # x 2 for adjuster
-    n_forecast_values = (8 + 4) * 4 * 2
+    n_forecast_values = (8 + 4 + 4) * 4 * 2
 
     assert db_session.query(ForecastSQL).count() == init_n_forecasts + n_forecasts
     assert db_session.query(ForecastValueSQL).count() == init_n_forecast_values + n_forecast_values