Add equality checks to the UQ result readers.

src/alfasim_sdk/result_reader/aggregator.py

@@ -114,7 +114,7 @@ class TimeSetInfoItem(NamedTuple):
     uuid: str
 
 
-TimeSetInfo = Dict[int, TimeSetInfoItem]
+TimeSetInfo = Dict[TimeStepIndex, TimeSetInfoItem]
 
 
 _PROFILE_ID_ATTR = "profile_id"
@@ -1957,7 +1957,7 @@ def read_uncertainty_propagation_analyses_meta_data(
     )
 
 
-@attr.s(frozen=True)
+@attr.s(frozen=True, eq=False)
 class UPResult:
     """
     Holder for each uncertainty propagation result.
@@ -1967,6 +1967,16 @@ class UPResult:
     std_result: np.ndarray = attr.ib(default=attr.Factory(lambda: np.array([])))
     mean_result: np.ndarray = attr.ib(default=attr.Factory(lambda: np.array([])))
 
+    def __eq__(self, other: Any) -> bool:
+        if not isinstance(other, UPResult):
+            return False
+
+        return (
+            np.array_equal(self.realization_output, other.realization_output)
+            and np.array_equal(self.std_result, other.std_result)
+            and np.array_equal(self.mean_result, other.mean_result)
+        )
+
 
 def read_uncertainty_propagation_results(
     metadata: UncertaintyPropagationAnalysesMetaData,

src/alfasim_sdk/result_reader/reader.py

@@ -355,7 +355,7 @@ def validator(inst: Any, attribute: attr.Attribute, value: Any) -> None:
     return validator
 
 
-@define(frozen=True)
+@define(frozen=True, eq=False)
 class GlobalSensitivityAnalysisResults:
     timeset: np.ndarray = attr.field(validator=attr.validators.min_len(1))
     coefficients: dict[GSAOutputKey, np.ndarray] = attr.field(
@@ -393,6 +393,22 @@ def get_sensitivity_curve(
         domain = Array(self.timeset, "s")
         return Curve(image=image, domain=domain)
 
+    def __eq__(self, other: Any) -> bool:
+        if not isinstance(other, GlobalSensitivityAnalysisResults):
+            return False
+
+        return (
+            np.array_equal(self.timeset, other.timeset)
+            and _all_dict_close(self.coefficients, other.coefficients)
+            and self.metadata == other.metadata
+        )
+
+
+def _all_dict_close(a: dict[Any, np.ndarray], b: dict[Any, np.ndarray]) -> bool:
+    if a.keys() != b.keys():
+        return False
+    return all(np.array_equal(a[key], b[key]) for key in a)
+
 
 @define(frozen=True)
 class _BaseHistoryMatchingResults:
@@ -423,7 +439,7 @@ def from_directory(cls, result_dir: Path) -> Self | None:
         )
 
 
-@define(frozen=True)
+@define(frozen=True, eq=False)
 class HistoryMatchingProbabilisticResults(_BaseHistoryMatchingResults):
     probabilistic_distributions: dict[HMOutputKey, np.ndarray] = attr.field(
         validator=_non_empty_dict_validator(values_type=np.ndarray)
@@ -443,6 +459,18 @@ def from_directory(cls, result_dir: Path) -> Self | None:
             metadata=metadata,
         )
 
+    def __eq__(self, other: Any) -> bool:
+        if not isinstance(other, HistoryMatchingProbabilisticResults):
+            return False
+
+        return (
+            _all_dict_close(
+                self.probabilistic_distributions, other.probabilistic_distributions
+            )
+            and self.historic_data_curves == other.historic_data_curves
+            and self.metadata == other.metadata
+        )
+
 
 def _read_curves_data(
     metadata: HistoryMatchingMetadata,
@@ -460,7 +488,7 @@ def _read_curves_data(
     return result
 
 
-@define(frozen=True)
+@define(frozen=True, eq=False)
 class UncertaintyPropagationResults:
     timeset: np.ndarray = attr.field(validator=attr.validators.min_len(1))
     results: dict[UPOutputKey, UPResult] = attr.field(
@@ -481,3 +509,13 @@ def from_directory(cls, result_dir: Path) -> Self | None:
             results=read_uncertainty_propagation_results(metadata),
             metadata=metadata,
         )
+
+    def __eq__(self, other: Any) -> bool:
+        if not isinstance(other, UncertaintyPropagationResults):
+            return False
+
+        return (
+            np.array_equal(self.timeset, other.timeset)
+            and self.results == other.results
+            and self.metadata == other.metadata
+        )

tests/results/test_result_reader.py

@@ -3,6 +3,7 @@
 import json
 from pathlib import Path
 
+import attr
 import numpy
 import numpy as np
 import pytest
@@ -188,6 +189,11 @@ def test_global_sensitivity_analysis_results_reader(
         qoi_data_index=0,
     )
 
+    # Test equality check.
+    assert results == attr.evolve(results)
+    assert results != object()
+    assert results != attr.evolve(results, timeset=np.array([0.1, 0.2]))
+
     # Ensure the reader can handle a nonexistent result file.
     results = GlobalSensitivityAnalysisResults.from_directory(Path("foo"))
     assert results is None
@@ -204,6 +210,13 @@ def test_deterministic_reader(self, hm_deterministic_results_dir: Path) -> None:
         }
         self._validate_meta_and_historic_curves(results)
 
+        # Test equality check.
+        assert results == attr.evolve(results)
+        assert results != object()
+        assert results != attr.evolve(
+            results, deterministic_values={HMOutputKey("parametric_var_1"): 0.1}
+        )
+
     def test_probabilistic_reader(self, hm_probabilistic_results_dir: Path) -> None:
         results = HistoryMatchingProbabilisticResults.from_directory(
             hm_probabilistic_results_dir
@@ -217,6 +230,16 @@ def test_probabilistic_reader(self, hm_probabilistic_results_dir: Path) -> None:
         )
         self._validate_meta_and_historic_curves(results)
 
+        # Test equality check.
+        assert results == attr.evolve(results)
+        assert results != object()
+        assert results != attr.evolve(
+            results,
+            probabilistic_distributions={
+                HMOutputKey("parametric_var_1"): np.array([0.1, 0.3])
+            },
+        )
+
     def test_wrong_result_file(
         self, hm_probabilistic_results_dir: Path, hm_deterministic_results_dir: Path
     ) -> None:
@@ -331,6 +354,11 @@ def test_uncertainty_propagation_results_reader(up_results_dir: Path) -> None:
         sample_indexes=[[0, 0], [0, 1], [0, 2], [0, 3], [0, 4]],
     )
 
+    # Test equality check.
+    assert reader == attr.evolve(reader)
+    assert reader != object()
+    assert reader != attr.evolve(reader, timeset=np.array([0.1, 0.2]))
+
     # Ensure the reader can handle a nonexistent result file.
     reader = UncertaintyPropagationResults.from_directory(Path("foo"))
     assert reader is None