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

for more information, see https://pre-commit.ci

src/alfasim_sdk/result_reader/aggregator.py

@@ -4,7 +4,7 @@
 from collections import namedtuple
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Any, Type
+from typing import Any
 from typing import Callable
 from typing import DefaultDict
 from typing import Dict
@@ -13,6 +13,7 @@
 from typing import Literal
 from typing import Optional
 from typing import Tuple
+from typing import Type
 from typing import Union
 
 import attr
@@ -22,9 +23,7 @@
 from typing_extensions import Self
 
 from alfasim_sdk.result_reader.aggregator_constants import (
-    GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME, UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME,
-    UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS, UNCERTAINTY_PROPAGATION_GROUP_NAME,
-    UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT, UNCERTAINTY_PROPAGATION_DSET_STD_RESULT,
+    GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME,
 )
 from alfasim_sdk.result_reader.aggregator_constants import (
     HISTORY_MATCHING_DETERMINISTIC_DSET_NAME,
@@ -42,6 +41,21 @@
 from alfasim_sdk.result_reader.aggregator_constants import RESULT_FILE_PREFIX
 from alfasim_sdk.result_reader.aggregator_constants import TIME_SET_DSET_NAME
 from alfasim_sdk.result_reader.aggregator_constants import TRENDS_GROUP_NAME
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_DSET_STD_RESULT,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_GROUP_NAME,
+)
 
 OutputKeyType = str
 """\
@@ -106,6 +120,7 @@ class ResultsNeedFullReloadError(RuntimeError):
     "restart file" and the option "keep old results" is selected.
     """
 
+
 @attr.s(slots=True, hash=False)
 class BaseUQMetaData:
     """
@@ -126,6 +141,7 @@ class BaseUQMetaData:
     :ivar unit:
         The unit of a dimensionless property (-, %)
     """
+
     property_id: str = attr.ib(validator=attr.validators.instance_of(str))
     trend_id: str = attr.ib(validator=attr.validators.instance_of(str))
     category: str = attr.ib(validator=attr.validators.instance_of(str))
@@ -158,9 +174,12 @@ class UPItem(BaseUQMetaData):
         :ivar sample_indexes:
             The indexes to access each sample of an item.
         """
+
         samples: int = attr.ib(validator=attr.validators.instance_of(int))
         result_index: int = attr.ib(validator=attr.validators.instance_of(int))
-        sample_indexes: List[List[int]] = attr.ib(validator=attr.validators.instance_of(List))
+        sample_indexes: List[List[int]] = attr.ib(
+            validator=attr.validators.instance_of(List)
+        )
 
         @classmethod
         def from_dict(cls, data: Dict[str, Any]) -> Self:
@@ -173,8 +192,8 @@ def from_dict(cls, data: Dict[str, Any]) -> Self:
                 position_unit=data["position_unit"],
                 unit=data["unit"],
                 samples=data["samples"],
-                result_index=data['result_index'],
-                sample_indexes=data['sample_indexes']
+                result_index=data["result_index"],
+                sample_indexes=data["sample_indexes"],
             )
 
     items: Dict[str, UPItem] = attr.ib(validator=attr.validators.instance_of(Dict))
@@ -188,7 +207,6 @@ def empty(cls, result_directory: Path) -> Self:
 
     @classmethod
     def get_metadata_from_dir(cls, result_directory: Path) -> Self:
-
         def map_data(
             up_metadata: Dict,
         ) -> Dict[str, UncertaintyPropagationAnalysesMetaData.UPItem]:
@@ -197,7 +215,13 @@ def map_data(
                 for key, data in up_metadata.items()
             }
 
-        return read_results_file(result_directory=result_directory, metadata_class=cls, meta_data_attrs=UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME, map_data=map_data)
+        return read_results_file(
+            result_directory=result_directory,
+            metadata_class=cls,
+            meta_data_attrs=UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME,
+            map_data=map_data,
+        )
+
 
 @attr.s(slots=True, hash=False)
 class GlobalSensitivityAnalysisMetadata:
@@ -219,6 +243,7 @@ class GSAItem(BaseUQMetaData):
         :ivar qoi_data_index:
             The data index of a quantity of interest.
         """
+
         parametric_var_id: str = attr.ib(validator=attr.validators.instance_of(str))
         parametric_var_name: str = attr.ib(validator=attr.validators.instance_of(str))
         qoi_index: Optional[int] = attr.ib(
@@ -269,25 +294,50 @@ def map_data(
                 key: GlobalSensitivityAnalysisMetadata.GSAItem.from_dict(data)
                 for key, data in gsa_metadata.items()
             }
-        return read_results_file(result_directory=result_directory,metadata_class=cls, map_data=map_data,meta_data_attrs=GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME)
 
-UQMetadataClass = Union[GlobalSensitivityAnalysisMetadata,UncertaintyPropagationAnalysesMetaData]
+        return read_results_file(
+            result_directory=result_directory,
+            metadata_class=cls,
+            map_data=map_data,
+            meta_data_attrs=GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME,
+        )
+
+
+UQMetadataClass = Union[
+    GlobalSensitivityAnalysisMetadata, UncertaintyPropagationAnalysesMetaData
+]
+
 
 @attr.s(frozen=True)
 class UPResult:
     """
     Holder for each uncertainty propagation result.
     """
-    realization_output: List[np.ndarray] = attr.ib(validator=attr.validators.optional(attr.validators.instance_of(List)))
-    mean_result: np.ndarray = attr.ib(validator=attr.validators.optional(attr.validators.instance_of(np.ndarray)))
-    std_result: np.ndarray = attr.ib(validator=attr.validators.optional(attr.validators.instance_of(np.ndarray)))
-    category: str = attr.ib(validator=attr.validators.optional(attr.validators.instance_of(str)))
-    unit: str = attr.ib(validator=attr.validators.optional(attr.validators.instance_of(str)))
 
-def read_results_file(result_directory: Path, metadata_class: Type[UQMetadataClass], map_data: Callable, meta_data_attrs: str) -> UQMetadataClass:
-    with open_result_file(
-        result_directory, result_filename="result"
-    ) as result_file:
+    realization_output: List[np.ndarray] = attr.ib(
+        validator=attr.validators.optional(attr.validators.instance_of(List))
+    )
+    mean_result: np.ndarray = attr.ib(
+        validator=attr.validators.optional(attr.validators.instance_of(np.ndarray))
+    )
+    std_result: np.ndarray = attr.ib(
+        validator=attr.validators.optional(attr.validators.instance_of(np.ndarray))
+    )
+    category: str = attr.ib(
+        validator=attr.validators.optional(attr.validators.instance_of(str))
+    )
+    unit: str = attr.ib(
+        validator=attr.validators.optional(attr.validators.instance_of(str))
+    )
+
+
+def read_results_file(
+    result_directory: Path,
+    metadata_class: Type[UQMetadataClass],
+    map_data: Callable,
+    meta_data_attrs: str,
+) -> UQMetadataClass:
+    with open_result_file(result_directory, result_filename="result") as result_file:
         if not result_file:
             return metadata_class.empty(result_directory=result_directory)
 
@@ -298,6 +348,7 @@ def read_results_file(result_directory: Path, metadata_class: Type[UQMetadataCla
             items=map_data(loaded_metadata), result_directory=result_directory
         )
 
+
 @attr.s(slots=True, hash=False)
 class HistoryMatchingMetadata:
     """
@@ -1770,9 +1821,10 @@ def read_global_sensitivity_analysis_meta_data(
         result_directory=result_directory
     )
 
+
 def read_uncertainty_propagation_analyses_meta_data(
     result_directory: Path,
-)-> Optional[UncertaintyPropagationAnalysesMetaData]:
+) -> Optional[UncertaintyPropagationAnalysesMetaData]:
     """
     Read the uncertainty propagation analyses metadata persisted in a result file.
     """
@@ -1782,7 +1834,9 @@ def read_uncertainty_propagation_analyses_meta_data(
     )
 
 
-def read_uncertainty_propagation_results(metadata: UncertaintyPropagationAnalysesMetaData, results_key: str) -> Optional[UPResult]:
+def read_uncertainty_propagation_results(
+    metadata: UncertaintyPropagationAnalysesMetaData, results_key: str
+) -> Optional[UPResult]:
     """
     Get the uncertainty propagation results.
 
@@ -1798,22 +1852,31 @@ def read_uncertainty_propagation_results(metadata: UncertaintyPropagationAnalyse
 
     with open_result_file(metadata.result_directory) as file:
         up_group = file[UNCERTAINTY_PROPAGATION_GROUP_NAME]
-        realization_output_samples = up_group[UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS]
-
-        realization_outputs = [realization_output_samples[sample_index][qoi_index] for qoi_index, sample_index in meta.sample_indexes]
-        mean_result = up_group[UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT][meta.result_index]
-        std_result = up_group[UNCERTAINTY_PROPAGATION_DSET_STD_RESULT][meta.result_index]
+        realization_output_samples = up_group[
+            UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS
+        ]
+
+        realization_outputs = [
+            realization_output_samples[sample_index][qoi_index]
+            for qoi_index, sample_index in meta.sample_indexes
+        ]
+        mean_result = up_group[UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT][
+            meta.result_index
+        ]
+        std_result = up_group[UNCERTAINTY_PROPAGATION_DSET_STD_RESULT][
+            meta.result_index
+        ]
         return UPResult(
             realization_output=realization_outputs,
             mean_result=mean_result,
             std_result=std_result,
             category=meta.category,
-            unit=meta.unit
+            unit=meta.unit,
         )
 
+
 def read_based_uq_time_set(
-    result_directory: Path,
-    group_name: str
+    result_directory: Path, group_name: str
 ) -> Optional[numpy.array]:
     """
     Get the time set for based uq analysis results.

src/alfasim_sdk/result_reader/aggregator_constants.py

@@ -13,7 +13,7 @@
 )
 UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT = "uncertainty_propagation_mean_results"
 UNCERTAINTY_PROPAGATION_DSET_STD_RESULT = "uncertainty_propagation_std_results"
-UNCERTAINTY_PROPAGATION_GROUP_NAME = 'uncertainty_propagation'
+UNCERTAINTY_PROPAGATION_GROUP_NAME = "uncertainty_propagation"
 
 TIME_SET_DSET_NAME = "time_set"
 

tests/conftest.py

@@ -12,9 +12,7 @@
 from _pytest.monkeypatch import MonkeyPatch
 
 from alfasim_sdk.result_reader.aggregator_constants import (
-    GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME, UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME, UNCERTAINTY_PROPAGATION_GROUP_NAME,
-    UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS, UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT,
-    UNCERTAINTY_PROPAGATION_DSET_STD_RESULT,
+    GLOBAL_SENSITIVITY_ANALYSIS_GROUP_NAME,
 )
 from alfasim_sdk.result_reader.aggregator_constants import (
     HISTORY_MATCHING_DETERMINISTIC_DSET_NAME,
@@ -25,6 +23,21 @@
 )
 from alfasim_sdk.result_reader.aggregator_constants import META_GROUP_NAME
 from alfasim_sdk.result_reader.aggregator_constants import TIME_SET_DSET_NAME
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_DSET_STD_RESULT,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME,
+)
+from alfasim_sdk.result_reader.aggregator_constants import (
+    UNCERTAINTY_PROPAGATION_GROUP_NAME,
+)
 from alfasim_sdk.result_reader.reader import Results
 
 
@@ -270,6 +283,7 @@ def global_sa_results_dir(datadir: Path) -> Path:
     file.close()
     return result_dir
 
+
 @pytest.fixture()
 def up_results_dir(datadir: Path) -> Path:
     """
@@ -285,8 +299,13 @@ def up_results_dir(datadir: Path) -> Path:
     realization_outputs = np.array(
         [
             [
-                [i + (qoi_index*10) + tl for tl in (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7)]
-                for qoi_index, trend_property in enumerate([('trend_id_1','temperature'), ('trend_id_1','absolute_pressure')])
+                [
+                    i + (qoi_index * 10) + tl
+                    for tl in (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7)
+                ]
+                for qoi_index, trend_property in enumerate(
+                    [("trend_id_1", "temperature"), ("trend_id_1", "absolute_pressure")]
+                )
             ]
             for i in range(5)
         ]
@@ -307,7 +326,7 @@ def up_results_dir(datadir: Path) -> Path:
                 "position_unit": "m",
                 "unit": "K",
                 "samples": 5,
-                "sample_indexes": [[0,0], [0,1], [0,2],[0,3],[0,4]],
+                "sample_indexes": [[0, 0], [0, 1], [0, 2], [0, 3], [0, 4]],
                 "result_index": 0,
             },
             "absolute_pressure@trend_id_1": {
@@ -319,28 +338,45 @@ def up_results_dir(datadir: Path) -> Path:
                 "position_unit": "m",
                 "unit": "bar",
                 "samples": 5,
-                "sample_indexes": [[1, 0],[1, 1], [1, 2], [1, 3],[1,4]],
+                "sample_indexes": [[1, 0], [1, 1], [1, 2], [1, 3], [1, 4]],
                 "result_index": 1,
             },
         }
-        meta_group.attrs[UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME] = json.dumps(fake_meta)
-        time_set_dset = uncertainty_propagation_group.create_dataset(name=TIME_SET_DSET_NAME, shape=time_set.shape)
+        meta_group.attrs[UNCERTAINTY_PROPAGATION_GROUP_META_ATTR_NAME] = json.dumps(
+            fake_meta
+        )
+        time_set_dset = uncertainty_propagation_group.create_dataset(
+            name=TIME_SET_DSET_NAME, shape=time_set.shape
+        )
         time_set_dset[:] = time_set
 
-        realization_outputs_dset = uncertainty_propagation_group.create_dataset(name=UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS, shape=realization_outputs.shape, maxshape=(None, None, None))
+        realization_outputs_dset = uncertainty_propagation_group.create_dataset(
+            name=UNCERTAINTY_PROPAGATION_DSET_REALIZATION_OUTPUS,
+            shape=realization_outputs.shape,
+            maxshape=(None, None, None),
+        )
         realization_outputs = realization_outputs
         realization_outputs_dset[:] = realization_outputs
 
         mean_results_array = np.mean(realization_outputs, axis=0)
-        mean_results = uncertainty_propagation_group.create_dataset(name=UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT, shape=mean_results_array.shape, maxshape=(None, None))
+        mean_results = uncertainty_propagation_group.create_dataset(
+            name=UNCERTAINTY_PROPAGATION_DSET_MEAN_RESULT,
+            shape=mean_results_array.shape,
+            maxshape=(None, None),
+        )
         mean_results[:] = mean_results_array
 
         std_results_array = np.std(realization_outputs, axis=0)
-        std_results = uncertainty_propagation_group.create_dataset(name=UNCERTAINTY_PROPAGATION_DSET_STD_RESULT, shape=std_results_array.shape, maxshape=(None, None))
+        std_results = uncertainty_propagation_group.create_dataset(
+            name=UNCERTAINTY_PROPAGATION_DSET_STD_RESULT,
+            shape=std_results_array.shape,
+            maxshape=(None, None),
+        )
         std_results[:] = std_results_array
         file.swmr_mode = True
     return result_dir
 
+
 def _create_and_populate_hm_result_file(
     result_dir: Path,
     result: np.ndarray,