Issue/blend negative values (#165)

* TDD: add test for negtaive values

* fix for negative values

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: peterdudfield

nowcasting_datamodel/read/blend.py

@@ -208,9 +208,14 @@ def get_blend_forecast_values_latest(
     forecast_values = []
     logger.debug(forecast_values_blended)
     for i, row in forecast_values_blended.iterrows():
+        # make sure we don't have negative values
+        expected_power_generation_megawatts = row.expected_power_generation_megawatts
+        if expected_power_generation_megawatts < 0:
+            expected_power_generation_megawatts = 0
+
         forecast_value = ForecastValue(
             target_time=row.target_time,
-            expected_power_generation_megawatts=row.expected_power_generation_megawatts,
+            expected_power_generation_megawatts=expected_power_generation_megawatts,
         )
         forecast_value._adjust_mw = row.adjust_mw
         forecast_values.append(forecast_value)

tests/read/test_blend.py

@@ -207,3 +207,47 @@ def test_get_blend_forecast_values_latest_two_model_read_two(db_session):
     assert forecast_values_read[0]._adjust_mw == 0
     assert forecast_values_read[2]._adjust_mw == 50
     assert forecast_values_read[3]._adjust_mw == 100
+
+
+@freeze_time("2023-01-01 00:00:01")
+def test_get_blend_forecast_values_latest_negative(db_session):
+    model_1 = get_model(session=db_session, name="test_1", version="0.0.1")
+    model_2 = get_model(session=db_session, name="test_2", version="0.0.1")
+
+    for model in [model_1, model_2]:
+        f1 = make_fake_forecasts(gsp_ids=[1, 2], session=db_session)
+        f1[0].historic = True
+
+        if model == model_1:
+            power = -1
+        else:
+            power = -2
+
+        forecast_horizon_minutes = [0, 30, 8 * 30, 15 * 30]
+        f1[0].forecast_values_latest = [
+            ForecastValueLatestSQL(
+                gsp_id=1,
+                expected_power_generation_megawatts=power,
+                target_time=datetime(2023, 1, 1, tzinfo=timezone.utc) + timedelta(minutes=t),
+                model_id=model.id,
+                adjust_mw=1,
+            )
+            for t in forecast_horizon_minutes
+        ]
+
+        db_session.add_all(f1)
+    assert len(db_session.query(ForecastValueLatestSQL).all()) == 8
+
+    forecast_values_read = get_blend_forecast_values_latest(
+        session=db_session,
+        gsp_id=f1[0].location.gsp_id,
+        start_datetime=datetime(2023, 1, 1, 0, 0, tzinfo=timezone.utc),
+        model_names=["test_1", "test_2"],
+    )
+
+    assert len(forecast_values_read) == 4
+    assert forecast_values_read[0].target_time == f1[0].forecast_values_latest[0].target_time
+    assert forecast_values_read[0].expected_power_generation_megawatts == 0
+    assert forecast_values_read[1].expected_power_generation_megawatts == 0
+    assert forecast_values_read[2].expected_power_generation_megawatts == 0
+    assert forecast_values_read[3].expected_power_generation_megawatts == 0