Check sizes of forecast data vs. Hazard and Impact (#1180)

* Add data shape check for HazardForecast, ImpactForecast

Author: peanutfun

climada/engine/impact_forecast.py

@@ -24,6 +24,7 @@
 import numpy as np
 
 from ..util import log_level
+from ..util.checker import size
 from ..util.forecast import Forecast
 from .impact import Impact
 
@@ -51,8 +52,8 @@ def __init__(
         impact_kwargs
             Keyword-arguments passed to ~:py:class`climada.engine.impact.Impact`.
         """
-        # TODO: Maybe assert array lengths?
         super().__init__(lead_time=lead_time, member=member, **impact_kwargs)
+        self._check_sizes()
 
     @classmethod
     def from_impact(
@@ -88,3 +89,16 @@ def from_impact(
                 imp_mat=impact.imp_mat,
                 haz_type=impact.haz_type,
             )
+
+    def _check_sizes(self):
+        """Check sizes of forecast data vs. impact data.
+
+        Raises
+        ------
+        ValueError
+            If the sizes of the forecast data do not match the
+            :py:attr:`~climada.engine.impact.Impact.event_id`
+        """
+        num_entries = len(self.event_id)
+        size(exp_len=num_entries, var=self.member, var_name="Forecast.member")
+        size(exp_len=num_entries, var=self.lead_time, var_name="Forecast.lead_time")

climada/engine/test/test_impact_forecast.py

@@ -41,13 +41,15 @@ def impact(impact_kwargs):
 
 
 @pytest.fixture
-def lead_time():
-    return pd.timedelta_range(start="1 day", periods=6).to_numpy()
+def lead_time(impact_kwargs):
+    return pd.timedelta_range(
+        start="1 day", periods=len(impact_kwargs["event_id"])
+    ).to_numpy()
 
 
 @pytest.fixture
-def member():
-    return np.arange(6)
+def member(impact_kwargs):
+    return np.arange(len(impact_kwargs["event_id"]))
 
 
 @pytest.fixture
@@ -76,6 +78,12 @@ def test_impact_forecast_init(self, impact_kwargs, lead_time, member):
         npt.assert_array_equal(forecast1.member, member)
         self.assert_impact_kwargs(forecast1, **impact_kwargs)
 
+    def test_impact_forecast_init_error(self, impact, impact_kwargs, lead_time, member):
+        with pytest.raises(ValueError, match="Forecast.lead_time"):
+            ImpactForecast(lead_time=lead_time[:-2], member=member, **impact_kwargs)
+        with pytest.raises(ValueError, match="Forecast.member"):
+            ImpactForecast.from_impact(impact, lead_time=lead_time, member=member[1:])
+
     def test_impact_forecast_from_impact(
         self, impact_forecast, impact_kwargs, lead_time, member
     ):

climada/hazard/forecast.py

@@ -23,8 +23,9 @@
 
 import numpy as np
 
-from climada.hazard.base import Hazard
-from climada.util.forecast import Forecast
+from ..util.checker import size
+from ..util.forecast import Forecast
+from .base import Hazard
 
 LOGGER = logging.getLogger(__name__)
 
@@ -52,6 +53,7 @@ def __init__(
             py:meth`~climada.hazard.base.Hazard.__init__` for details.
         """
         super().__init__(lead_time=lead_time, member=member, **hazard_kwargs)
+        self._check_sizes()
 
     @classmethod
     def from_hazard(cls, hazard: Hazard, lead_time: np.ndarray, member: np.ndarray):
@@ -89,3 +91,16 @@ def from_hazard(cls, hazard: Hazard, lead_time: np.ndarray, member: np.ndarray):
             intensity=hazard.intensity,
             fraction=hazard.fraction,
         )
+
+    def _check_sizes(self):
+        """Check sizes of forecast data vs. hazard data.
+
+        Raises
+        ------
+        ValueError
+            If the sizes of the forecast data do not match the
+            :py:attr:`~climada.hazard.base.Hazard.event_id`
+        """
+        num_entries = len(self.event_id)
+        size(exp_len=num_entries, var=self.member, var_name="Forecast.member")
+        size(exp_len=num_entries, var=self.lead_time, var_name="Forecast.lead_time")

climada/hazard/test/test_forecast.py

@@ -41,13 +41,13 @@ def hazard(haz_kwargs):
 
 
 @pytest.fixture
-def lead_time():
-    return pd.timedelta_range("1h", periods=6).to_numpy()
+def lead_time(haz_kwargs):
+    return pd.timedelta_range("1h", periods=len(haz_kwargs["event_id"])).to_numpy()
 
 
 @pytest.fixture
-def member():
-    return np.arange(6)
+def member(haz_kwargs):
+    return np.arange(len(haz_kwargs["event_id"]))
 
 
 @pytest.fixture
@@ -78,6 +78,13 @@ def test_init_hazard_forecast(haz_fc, member, lead_time, haz_kwargs):
     assert_hazard_kwargs(haz_fc, **haz_kwargs)
 
 
+def test_init_hazard_forecast_error(hazard, member, lead_time, haz_kwargs):
+    with pytest.raises(ValueError, match="Forecast.lead_time"):
+        HazardForecast(lead_time=lead_time[:-2], member=member, **haz_kwargs)
+    with pytest.raises(ValueError, match="Forecast.member"):
+        HazardForecast.from_hazard(hazard, lead_time=lead_time, member=member[1:])
+
+
 def test_from_hazard(lead_time, member, hazard, haz_kwargs):
     haz_fc_from_haz = HazardForecast.from_hazard(
         hazard, lead_time=lead_time, member=member