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

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src/alfasim_sdk/result_reader/aggregator.py

@@ -23,9 +23,13 @@
 from alfasim_sdk.result_reader.aggregator_constants import (
     GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME,
 )
+from alfasim_sdk.result_reader.aggregator_constants import (
+    HISTORY_MATCHING_DETERMINISTIC_DSET_NAME,
+)
 from alfasim_sdk.result_reader.aggregator_constants import HISTORY_MATCHING_GROUP_NAME
-from alfasim_sdk.result_reader.aggregator_constants import HISTORY_MATCHING_PROBABILISTIC_DSET_NAME
-from alfasim_sdk.result_reader.aggregator_constants import HISTORY_MATCHING_DETERMINISTIC_DSET_NAME
+from alfasim_sdk.result_reader.aggregator_constants import (
+    HISTORY_MATCHING_PROBABILISTIC_DSET_NAME,
+)
 from alfasim_sdk.result_reader.aggregator_constants import META_GROUP_NAME
 from alfasim_sdk.result_reader.aggregator_constants import PROFILES_GROUP_NAME
 from alfasim_sdk.result_reader.aggregator_constants import (
@@ -200,7 +204,9 @@ def map_data(
                 for key, data in gsa_metadata.items()
             }
 
-        with open_result_file(result_directory, result_filename='uq_result') as result_file:
+        with open_result_file(
+            result_directory, result_filename="uq_result"
+        ) as result_file:
             if not result_file:
                 return cls.empty(result_directory=result_directory)
 
@@ -1658,7 +1664,7 @@ def read_global_sensitivity_analysis_time_set(
     """
     Get the time set for sensitivity analysis results.
     """
-    with open_result_file(result_directory, result_filename='uq_result') as result_file:
+    with open_result_file(result_directory, result_filename="uq_result") as result_file:
         if not result_file:
             return
         return result_file[GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME]["time_set"][:]
@@ -1675,7 +1681,9 @@ def read_global_sensitivity_coefficients(
     if not metadata.gsa_items:
         return None
     meta = metadata.gsa_items[coefficients_key]
-    with open_result_file(metadata.result_directory, result_filename='uq_result') as result_file:
+    with open_result_file(
+        metadata.result_directory, result_filename="uq_result"
+    ) as result_file:
         gsa_group = result_file[GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME]
         coefficients_dset = gsa_group["global_sensitivity_analysis"]
         return coefficients_dset[meta.qoi_index, meta.qoi_data_index]
@@ -1690,8 +1698,8 @@ def read_history_matching_metadata(result_directory: Path) -> HistoryMatchingMet
 
 
 def read_history_matching_result(
-    metadata: HistoryMatchingMetadata, 
-    hm_type: Literal['deterministic', 'probabilistic'],
+    metadata: HistoryMatchingMetadata,
+    hm_type: Literal["deterministic", "probabilistic"],
     hm_result_key: HistoryMatchingResultKeyType | None = None,
 ) -> Dict[HistoryMatchingResultKeyType, np.ndarray | float]:
     """
@@ -1707,21 +1715,21 @@ def read_history_matching_result(
         could be an array with N values (N being the sampling size) for the probabilistic or a single
         float for the deterministic.
     """
-    if hm_type not in ('deterministic', 'probabilistic'):
-        raise ValueError(f'history matching of type {hm_type} not supported')
+    if hm_type not in ("deterministic", "probabilistic"):
+        raise ValueError(f"history matching of type {hm_type} not supported")
 
-    if hm_type == 'deterministic':
+    if hm_type == "deterministic":
         dataset_key = HISTORY_MATCHING_DETERMINISTIC_DSET_NAME
     else:
-        assert hm_type == 'probabilistic'
+        assert hm_type == "probabilistic"
         dataset_key = HISTORY_MATCHING_PROBABILISTIC_DSET_NAME
 
     with open_result_file(metadata.result_directory) as result_file:
         if not result_file:
             return {}
 
         result = result_file[HISTORY_MATCHING_GROUP_NAME][dataset_key]
-        
+
         result_map = {}
         if hm_result_key is None:
             for key, meta in metadata.hm_items.items():
@@ -1736,7 +1744,7 @@ def read_history_matching_result(
 
 @contextmanager
 def open_result_file(
-    result_directory: Path, result_filename: str = 'result'
+    result_directory: Path, result_filename: str = "result"
 ) -> Iterator[Optional[h5py.File]]:
     """
     :param result_directory:
@@ -1747,7 +1755,7 @@ def open_result_file(
         The result HDF file, or None if it doesn't exist or is still being created.
     """
     filepath = result_directory / result_filename
-    ignored_file = result_directory / f'{result_filename}.creating'
+    ignored_file = result_directory / f"{result_filename}.creating"
 
     if not filepath.is_file():
         yield None

tests/conftest.py

@@ -3,7 +3,9 @@
 import shutil
 import textwrap
 from pathlib import Path
-from typing import List, Sequence, Tuple
+from typing import List
+from typing import Sequence
+from typing import Tuple
 
 import h5py
 import numpy as np
@@ -13,8 +15,12 @@
 
 from alfasim_sdk.result_reader.aggregator_constants import (
     GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
     HISTORY_MATCHING_DETERMINISTIC_DSET_NAME,
-    HISTORY_MATCHING_GROUP_NAME,
+)
+from alfasim_sdk.result_reader.aggregator_constants import HISTORY_MATCHING_GROUP_NAME
+from alfasim_sdk.result_reader.aggregator_constants import (
     HISTORY_MATCHING_PROBABILISTIC_DSET_NAME,
 )
 from alfasim_sdk.result_reader.aggregator_constants import META_GROUP_NAME
@@ -269,11 +275,11 @@ def _create_and_populate_hm_result_file(
     result_dir: Path,
     result: np.ndarray,
     dataset_key: str,
-    limits: Sequence[Tuple[float, float]]
+    limits: Sequence[Tuple[float, float]],
 ) -> None:
     result_dir.mkdir(parents=True, exist_ok=True)
     result_filepath = result_dir / "result"
-    
+
     file = h5py.File(result_filepath, "x", libver="latest", locking=False)
     meta_group = file.create_group(META_GROUP_NAME, track_order=True)
     data_group = file.create_group(HISTORY_MATCHING_GROUP_NAME, track_order=True)
@@ -304,7 +310,7 @@ def _create_and_populate_hm_result_file(
 
     meta_group.attrs[HISTORY_MATCHING_GROUP_NAME] = json.dumps(fake_meta)
     dataset[:] = result
-    
+
     file.swmr_mode = True
     file.close()
 
@@ -318,16 +324,18 @@ def hm_probabilistic_results_dir(datadir: Path) -> Path:
     import numpy as np
 
     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]])
+    probabilistic_result = np.array(
+        [[0.1, 0.22, 1.0, 0.8, 0.55], [3.0, 6.0, 5.1, 4.7, 6.3]]
+    )
     limits = [(0.0, 1.0), (2.5, 7.5)]
-    
+
     _create_and_populate_hm_result_file(
         result_dir=result_dir,
         result=probabilistic_result,
         dataset_key=HISTORY_MATCHING_PROBABILISTIC_DSET_NAME,
-        limits=limits
+        limits=limits,
     )
-    
+
     return result_dir
 
 
@@ -342,12 +350,12 @@ def hm_deterministic_results_dir(datadir: Path) -> Path:
     result_dir = datadir / "main-HM-deterministic"
     deterministic_result = np.array([0.1, 3.2])
     limits = [(0.0, 1.0), (2.5, 7.5)]
-    
+
     _create_and_populate_hm_result_file(
         result_dir=result_dir,
         result=deterministic_result,
         dataset_key=HISTORY_MATCHING_DETERMINISTIC_DSET_NAME,
-        limits=limits
+        limits=limits,
     )
-    
-    return result_dir
+
+    return result_dir

tests/results/test_aggregator.py

@@ -1,15 +1,17 @@
 import itertools
 import re
 from pathlib import Path
-from typing import List, Literal
+from typing import List
+from typing import Literal
 
 import attr
 import numpy
 import pytest
 from pytest_mock import MockerFixture
 from pytest_regressions.num_regression import NumericRegressionFixture
 
-from alfasim_sdk.result_reader.aggregator import HistoryMatchingMetadata, concatenate_metadata, read_history_matching_metadata, read_history_matching_result
+from alfasim_sdk.result_reader.aggregator import concatenate_metadata
+from alfasim_sdk.result_reader.aggregator import HistoryMatchingMetadata
 from alfasim_sdk.result_reader.aggregator import open_result_files
 from alfasim_sdk.result_reader.aggregator import (
     read_global_sensitivity_analysis_meta_data,
@@ -18,6 +20,8 @@
     read_global_sensitivity_analysis_time_set,
 )
 from alfasim_sdk.result_reader.aggregator import read_global_sensitivity_coefficients
+from alfasim_sdk.result_reader.aggregator import read_history_matching_metadata
+from alfasim_sdk.result_reader.aggregator import read_history_matching_result
 from alfasim_sdk.result_reader.aggregator import read_metadata
 from alfasim_sdk.result_reader.aggregator import read_profiles_local_statistics
 from alfasim_sdk.result_reader.aggregator import read_time_sets
@@ -372,98 +376,102 @@ def test_read_incomplete_gsa_metadata(global_sa_results_dir: Path) -> None:
     assert coefficients is None
 
 
-def test_read_history_matching_result_metadata(hm_probabilistic_results_dir: Path) -> None:
+def test_read_history_matching_result_metadata(
+    hm_probabilistic_results_dir: Path,
+) -> None:
     """
     Check reading the HM metadata from a probabilistic result file, which should be enough to
     evaluate the deterministic metadata too as they are handled exactly the same.
     """
     hm_results_dir = hm_probabilistic_results_dir
-    
+
     # Existent and completed result file, metadata should be filled.
     metadata = read_history_matching_metadata(hm_results_dir)
-    
+
     assert metadata.result_directory == hm_results_dir
     items_meta = metadata.hm_items
 
     expected_meta1 = HistoryMatchingMetadata.HMItem(
-        parametric_var_id='parametric_var_1',
-        parametric_var_name='mg',
+        parametric_var_id="parametric_var_1",
+        parametric_var_name="mg",
         min_value=0.0,
         max_value=1.0,
         data_index=0,
     )
-    
+
     expected_meta2 = HistoryMatchingMetadata.HMItem(
-        parametric_var_id='parametric_var_2',
-        parametric_var_name='mo',
+        parametric_var_id="parametric_var_2",
+        parametric_var_name="mo",
         min_value=2.5,
         max_value=7.5,
         data_index=1,
     )
-    
-    assert items_meta['parametric_var_1'] == expected_meta1
-    assert items_meta['parametric_var_2'] == expected_meta2
-    
+
+    assert items_meta["parametric_var_1"] == expected_meta1
+    assert items_meta["parametric_var_2"] == expected_meta2
+
     # Result file still being created, metadata should be empty.
     creating_file = hm_results_dir / "result.creating"
     creating_file.touch()
-    
+
     metadata = read_history_matching_metadata(hm_results_dir)
     assert metadata.result_directory == hm_results_dir
     assert metadata.hm_items == {}
-    
+
     creating_file.unlink()
-    
+
     # Non-existent result directory, metadata should be empty.
-    unexistent_result_dir = Path('foo/bar')
+    unexistent_result_dir = Path("foo/bar")
     metadata = read_history_matching_metadata(unexistent_result_dir)
     assert metadata.result_directory == unexistent_result_dir
     assert metadata.hm_items == {}
 
 
-@pytest.mark.parametrize('hm_type', ('probabilistic', 'deterministic'))
+@pytest.mark.parametrize("hm_type", ("probabilistic", "deterministic"))
 def test_read_history_matching_result_data(
     hm_probabilistic_results_dir: Path,
     hm_deterministic_results_dir: Path,
-    hm_type: Literal['probabilistic', 'deterministic'],
+    hm_type: Literal["probabilistic", "deterministic"],
 ) -> None:
     """
     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.
     """
     # Setup.
-    if hm_type == 'probabilistic':
+    if hm_type == "probabilistic":
         expected_results = ([0.1, 0.22, 1.0, 0.8, 0.55], [3.0, 6.0, 5.1, 4.7, 6.3])
         results_dir = hm_probabilistic_results_dir
     else:
-        assert hm_type == 'deterministic'
+        assert hm_type == "deterministic"
         expected_results = (0.1, 3.2)
         results_dir = hm_deterministic_results_dir
 
     metadata = read_history_matching_metadata(results_dir)
-    
+
     # Read the result of a single parametric var entry.
     result = read_history_matching_result(
-        metadata, hm_type=hm_type, hm_result_key='parametric_var_1'
+        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[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[0])
+    assert result["parametric_var_2"] == pytest.approx(expected_results[1])
 
     # Unexistent result key, result should be empty.
-    result = read_history_matching_result(metadata, hm_type=hm_type, hm_result_key='foo')
+    result = read_history_matching_result(
+        metadata, hm_type=hm_type, hm_result_key="foo"
+    )
     assert result == {}
-    
+
     # Result still being created, result should be empty.
     creating_file = results_dir / "result.creating"
     creating_file.touch()
-    
+
     result = read_history_matching_result(metadata, hm_type=hm_type)
     assert result == {}
-    
+
     creating_file.unlink()