Fix HM results reader

Since the shape of data is different than expected, the reader had
to be updated to consider the correct shape of data.

src/alfasim_sdk/result_reader/aggregator.py

@@ -1965,11 +1965,14 @@ def read_history_matching_result(
     if hm_type not in ("HM-deterministic", "HM-probabilistic"):
         raise ValueError(f"history matching of type `{hm_type}` not supported")
 
+    slicer: Callable[[int], Any]
     if hm_type == "HM-deterministic":
         dataset_key = HISTORY_MATCHING_DETERMINISTIC_DSET_NAME
+        slicer = lambda index: index
     else:
         assert hm_type == "HM-probabilistic"
         dataset_key = HISTORY_MATCHING_PROBABILISTIC_DSET_NAME
+        slicer = lambda index: (slice(None), index)
 
     with open_result_file(metadata.result_directory) as result_file:
         if not result_file:
@@ -1980,11 +1983,11 @@ def read_history_matching_result(
         result_map = {}
         if hm_result_key is None:
             for key, meta in metadata.hm_items.items():
-                result_map[key] = result[meta.data_index]
+                result_map[key] = result[slicer(meta.data_index)]
         else:
             meta = metadata.hm_items.get(hm_result_key)
             if meta is not None:
-                result_map[hm_result_key] = result[meta.data_index]
+                result_map[hm_result_key] = result[slicer(meta.data_index)]
 
         return result_map
 

tests/conftest.py

@@ -463,7 +463,7 @@ def hm_probabilistic_results_dir(datadir: Path) -> Path:
 
     result_dir = datadir / "main-HM-probabilistic"
     probabilistic_result = np.array(
-        [[0.1, 0.22, 1.0, 0.8, 0.55], [3.0, 6.0, 5.1, 4.7, 6.3]]
+        [[0.1, 3.0], [0.22, 6.0], [1.0, 5.1], [0.8, 4.7], [0.55, 6.3]]
     )
     historic_data_curves = {
         "observed_curve_1": np.array([[0.1, 0.5, 0.9], [1.1, 2.2, 3.3]]),

tests/results/test_aggregator.py

@@ -3,7 +3,7 @@
 import re
 import shutil
 from pathlib import Path
-from typing import List
+from typing import List, Callable, Any
 from typing import Literal
 
 import attr
@@ -511,14 +511,18 @@ def test_read_history_matching_result_data(
     Check reading the result of both HM type analysis. Both results are available simultaneously by
     the means of the fixtures, but only one is used at a time.
     """
+    import numpy as np
     # Setup.
+    slicer: Callable[[int], Any]
     if hm_type == "HM-probabilistic":
-        expected_results = ([0.1, 0.22, 1.0, 0.8, 0.55], [3.0, 6.0, 5.1, 4.7, 6.3])
+        expected_results = np.array([[0.1, 3.0], [0.22, 6.0], [1.0, 5.1], [0.8, 4.7], [0.55, 6.3]])
         results_dir = hm_probabilistic_results_dir
+        slicer = lambda index: (slice(None), index)
     else:
         assert hm_type == "HM-deterministic"
         expected_results = (0.1, 3.2)
         results_dir = hm_deterministic_results_dir
+        slicer = lambda index: index
 
     metadata = read_history_matching_metadata(results_dir)
 
@@ -527,13 +531,13 @@ def test_read_history_matching_result_data(
         metadata, hm_type=hm_type, hm_result_key="parametric_var_1"
     )
     assert len(result) == 1
-    assert result["parametric_var_1"] == pytest.approx(expected_results[0])
+    assert result["parametric_var_1"] == pytest.approx(expected_results[slicer(0)])
 
     # Read the result of all entries.
     result = read_history_matching_result(metadata, hm_type=hm_type)
     assert len(result) == 2
-    assert result["parametric_var_1"] == pytest.approx(expected_results[0])
-    assert result["parametric_var_2"] == pytest.approx(expected_results[1])
+    assert result["parametric_var_1"] == pytest.approx(expected_results[slicer(0)])
+    assert result["parametric_var_2"] == pytest.approx(expected_results[slicer(1)])
 
     # Unexistent result key, result should be empty.
     result = read_history_matching_result(