add old pvnet main model back in.

Add test to check it runs

pvnet_app/model_configs/all_models.yaml

@@ -47,7 +47,19 @@ models:
         version: 4fe6b1441b6dd549292c201ed85eee156ecc220c
     ecmwf_only: True
     uses_satellite_data: False
-# This is the old model for pvnet_ecmwf
+# This is the old model for pvnet and pvnet_ecmwf
+  - name: pvnet_v2
+    pvnet:
+      repo: openclimatefix/pvnet_uk_region
+      version: 62e5e20ab793cee7cf94eadac870d2199501a730
+    summation:
+      repo: openclimatefix/pvnet_v2_summation
+      version: ffac655f9650b81865d96023baa15839f3ce26ec
+    use_adjuster: True
+    save_gsp_sum: False
+    verbose: True
+    save_gsp_to_recent: True
+    uses_ocf_data_sampler: False
   - name: pvnet_ecmwf # this name is important as it used for blending
     pvnet:
         repo: openclimatefix/pvnet_uk_region

tests/model_configs/test_pydantic_models.py

@@ -35,7 +35,7 @@ def test_get_all_models_ocf_data_sampler():
     assert len(models) == 5
 
     models = get_all_models(use_ocf_data_sampler=False, run_extra_models=True)
-    assert len(models) == 1
+    assert len(models) == 2
 
     models = get_all_models(use_ocf_data_sampler=False, run_extra_models=True, get_day_ahead_only=True)
     assert len(models) == 1

tests/test_app.py

@@ -111,14 +111,15 @@ def test_app_day_ahead_model(
 
         os.environ["DAY_AHEAD_MODEL"] = "True"
         os.environ["RUN_EXTRA_MODELS"] = "False"
+        os.environ["USE_OCF_DATA_SAMPLER"] = "False"
 
         # Run prediction
         # Thes import needs to come after the environ vars have been set
         from pvnet_app.app import app
 
         app(gsp_ids=list(range(1, 318)), num_workers=2)
 
-    all_models = get_all_models(get_day_ahead_only=True)
+    all_models = get_all_models(get_day_ahead_only=True, use_ocf_data_sampler=False)
 
     # Check correct number of forecasts have been made
     # (317 GSPs + 1 National + maybe GSP-sum) = 318 or 319 forecasts
@@ -213,4 +214,72 @@ def test_app_no_sat(
         expected_forecast_results += 317 * model_config.save_gsp_to_recent
         expected_forecast_results += model_config.save_gsp_sum  # optional Sum of GSPs
 
-    assert len(db_session.query(ForecastValueSevenDaysSQL).all()) == expected_forecast_results * 16
+    assert len(db_session.query(ForecastValueSevenDaysSQL).all()) == expected_forecast_results * 16
+
+
+# test legacy models
+# Its nice to have this here, so we can run the latest version in production, but still use the old models
+# Once we have re trained PVnet summation models we can remove this
+def test_app_ocf_datapipes(
+        db_session, nwp_ukv_data, nwp_ecmwf_data, sat_5_data, gsp_yields_and_systems, me_latest
+):
+    """Test the app running the day ahead model"""
+
+    with tempfile.TemporaryDirectory() as tmpdirname:
+        os.chdir(tmpdirname)
+
+        temp_nwp_path = "temp_nwp_ukv.zarr"
+        os.environ["NWP_UKV_ZARR_PATH"] = temp_nwp_path
+        nwp_ukv_data.to_zarr(temp_nwp_path)
+
+        temp_nwp_path = "temp_nwp_ecmwf.zarr"
+        os.environ["NWP_ECMWF_ZARR_PATH"] = temp_nwp_path
+        nwp_ecmwf_data.to_zarr(temp_nwp_path)
+
+        temp_sat_path = "temp_sat.zarr.zip"
+        os.environ["SATELLITE_ZARR_PATH"] = temp_sat_path
+        with zarr.storage.ZipStore(temp_sat_path, mode="x") as store:
+            sat_5_data.to_zarr(store)
+
+        os.environ["DAY_AHEAD_MODEL"] = "False"
+        os.environ["RUN_EXTRA_MODELS"] = "False"
+        os.environ["USE_OCF_DATA_SAMPLER"] = "False"
+
+        # Run prediction
+        # Thes import needs to come after the environ vars have been set
+        from pvnet_app.app import app
+
+        app(gsp_ids=list(range(1, 318)), num_workers=2)
+
+    all_models = get_all_models(use_ocf_data_sampler=False)
+
+    # Check correct number of forecasts have been made
+    # (317 GSPs + 1 National + maybe GSP-sum) = 318 or 319 forecasts
+    # Forecast made with multiple models
+    expected_forecast_results = 0
+    for model_config in all_models:
+        expected_forecast_results += 318 + model_config.save_gsp_sum
+
+    forecasts = db_session.query(ForecastSQL).all()
+    # Doubled for historic and forecast
+    assert len(forecasts) == expected_forecast_results * 2
+
+    # Check probabilistic added
+    assert "90" in forecasts[0].forecast_values[0].properties
+    assert "10" in forecasts[0].forecast_values[0].properties
+
+    # 72 time steps in forecast
+    expected_forecast_timesteps = 72
+
+    assert (
+            len(db_session.query(ForecastValueSQL).all())
+            == expected_forecast_results * expected_forecast_timesteps
+    )
+    assert (
+            len(db_session.query(ForecastValueLatestSQL).all())
+            == expected_forecast_results * expected_forecast_timesteps
+    )
+    assert (
+            len(db_session.query(ForecastValueSevenDaysSQL).all())
+            == expected_forecast_results * expected_forecast_timesteps
+    )