Merge remote-tracking branch 'origin/main' into feat/add-basic-arrays

Author: Thijss

.github/workflows/check-code-quality.yml

@@ -30,7 +30,7 @@ jobs:
         uses: actions/checkout@v5
 
       - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         if: ${{ always() }}
         with:
           activate-environment: true

.github/workflows/ci.yml

@@ -38,7 +38,7 @@ jobs:
         uses: actions/checkout@v5
 
       - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         if: ${{ always() }}
         with:
           activate-environment: true
@@ -62,7 +62,7 @@ jobs:
           uv build
 
       - name: Store built wheel file
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
         with:
           name: power-grid-model-ds
           path: dist/
@@ -81,7 +81,7 @@ jobs:
         uses: actions/checkout@v5
 
       - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         if: ${{ always() }}
         with:
           activate-environment: true
@@ -91,7 +91,7 @@ jobs:
         run: uv tool install poethepoet
 
       - name: Load built wheel file
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v6
         with:
           name: power-grid-model-ds
           path: dist/
@@ -117,7 +117,7 @@ jobs:
         uses: actions/checkout@v5
 
       - name: Load built wheel file
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v6
         with:
           name: power-grid-model-ds
           path: dist/

.github/workflows/citations.yml

@@ -30,6 +30,7 @@ jobs:
     runs-on: ubuntu-24.04
     steps:
     - name: checkout
-      uses: actions/checkout@v4
+      uses: actions/checkout@v5
+
     - name: Validate CITATION.cff
       uses: dieghernan/cff-validator@v4

.github/workflows/reuse-compliance.yml

@@ -20,4 +20,4 @@ jobs:
     - name: checkout
       uses: actions/checkout@v5
     - name: REUSE Compliance Check
-      uses: fsfe/reuse-action@v5
+      uses: fsfe/reuse-action@v6

.github/workflows/sonar.yml

@@ -26,7 +26,7 @@ jobs:
         uses: actions/checkout@v5
 
       - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         if: ${{ always() }}
         with:
           activate-environment: true
@@ -46,7 +46,7 @@ jobs:
 
       - name: SonarCloud Scan
         if: ${{ (github.event_name == 'push') || (github.event.pull_request.head.repo.owner.login == 'PowerGridModel') }}
-        uses: SonarSource/sonarqube-scan-action@v5
+        uses: SonarSource/sonarqube-scan-action@v6
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
           SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}

docs/model_interface.ipynb

@@ -265,7 +265,8 @@
    "outputs": [],
    "source": [
     "all_paths = grid.graphs.active_graph.get_all_paths(56, 41)\n",
-    "components = grid.graphs.active_graph.get_components(substation_nodes=np.array([1, 2, 3]))\n",
+    "with grid.graphs.active_graph.tmp_remove_nodes([1, 2, 3]):\n",
+    "    components = grid.graphs.active_graph.get_components()\n",
     "connected = grid.graphs.active_graph.get_connected(node_id=56)"
    ]
   }

src/power_grid_model_ds/_core/model/arrays/base/array.py

@@ -6,7 +6,7 @@
 from collections import namedtuple
 from copy import copy
 from functools import lru_cache
-from typing import Any, Iterable, Literal, Type, TypeVar
+from typing import Any, Iterable, Literal, Type, TypeVar, overload
 
 import numpy as np
 from numpy.typing import ArrayLike, NDArray
@@ -59,14 +59,14 @@ class FancyArray(ABC):
     _defaults: dict[str, Any] = {}
     _str_lengths: dict[str, int] = {}
 
-    def __init__(self: Self, *args, data: NDArray | None = None, **kwargs):
+    def __init__(self, *args, data: NDArray | None = None, **kwargs):
         if data is None:
             self._data = build_array(*args, dtype=self.get_dtype(), defaults=self.get_defaults(), **kwargs)
         else:
             self._data = data
 
     @property
-    def data(self: Self) -> NDArray:
+    def data(self) -> NDArray:
         return self._data
 
     @classmethod
@@ -110,7 +110,7 @@ def get_dtype(cls):
                 dtype_list.append((name, dtype))
         return np.dtype(dtype_list)
 
-    def __repr__(self: Self) -> str:
+    def __repr__(self) -> str:
         try:
             data = getattr(self, "data")
             if data.size > 3:
@@ -125,7 +125,7 @@ def __str__(self) -> str:
     def __len__(self) -> int:
         return len(self._data)
 
-    def __iter__(self: Self):
+    def __iter__(self):
         for record in self._data:
             yield self.__class__(data=np.array([record]))
 
@@ -152,20 +152,33 @@ def __setattr__(self: Self, attr: str, value: object) -> None:
         except (AttributeError, ValueError) as error:
             raise AttributeError(f"Cannot set attribute {attr} on {self.__class__.__name__}") from error
 
-    def __getitem__(self: Self, item):
-        """Used by for-loops, slicing [0:3], column-access ['id'], row-access [0], multi-column access.
-        Note: If a single item is requested, return a named tuple instead of a np.void object.
-        """
-
-        result = self._data.__getitem__(item)
-
-        if isinstance(item, (list, tuple)) and (len(item) == 0 or np.array(item).dtype.type is np.bool_):
-            return self.__class__(data=result)
-        if isinstance(item, (str, list, tuple)):
-            return result
-        if isinstance(result, np.void):
-            return self.__class__(data=np.array([result]))
-        return self.__class__(data=result)
+    @overload
+    def __getitem__(
+        self: Self, item: slice | int | NDArray[np.bool_] | list[bool] | NDArray[np.int_] | list[int]
+    ) -> Self: ...
+
+    @overload
+    def __getitem__(self, item: str | NDArray[np.str_] | list[str]) -> NDArray[Any]: ...
+
+    def __getitem__(self, item):
+        if isinstance(item, slice | int):
+            new_data = self._data[item]
+            if new_data.shape == ():
+                new_data = np.array([new_data])
+            return self.__class__(data=new_data)
+        if isinstance(item, str):
+            return self._data[item]
+        if (isinstance(item, np.ndarray) and item.size == 0) or (isinstance(item, list | tuple) and len(item) == 0):
+            return self.__class__(data=self._data[[]])
+        if isinstance(item, list | np.ndarray):
+            item_array = np.array(item)
+            if item_array.dtype == np.bool_ or np.issubdtype(item_array.dtype, np.int_):
+                return self.__class__(data=self._data[item_array])
+            if np.issubdtype(item_array.dtype, np.str_):
+                return self._data[item_array.tolist()]
+        raise NotImplementedError(
+            f"FancyArray[{type(item).__name__}] is not supported. Try FancyArray.data[{type(item).__name__}] instead."
+        )
 
     def __setitem__(self: Self, key, value):
         if isinstance(value, FancyArray):
@@ -177,16 +190,18 @@ def __contains__(self: Self, item: Self) -> bool:
             return item.data in self._data
         return False
 
-    def __hash__(self: Self):
+    def __hash__(self):
         return hash(f"{self.__class__} {self}")
 
-    def __eq__(self: Self, other):
-        return self._data.__eq__(other.data)
+    def __eq__(self, other):
+        if not isinstance(other, self.__class__):
+            return False
+        return self.data.__eq__(other.data)
 
-    def __copy__(self: Self):
+    def __copy__(self):
         return self.__class__(data=copy(self._data))
 
-    def copy(self: Self):
+    def copy(self):
         """Return a copy of this array including its data"""
         return copy(self)
 
@@ -281,15 +296,15 @@ def get(
         return self.__class__(data=apply_get(*args, array=self._data, mode_=mode_, **kwargs))
 
     def filter_mask(
-        self: Self,
+        self,
         *args: int | Iterable[int] | np.ndarray,
         mode_: Literal["AND", "OR"] = "AND",
         **kwargs: Any | list[Any] | np.ndarray,
     ) -> np.ndarray:
         return get_filter_mask(*args, array=self._data, mode_=mode_, **kwargs)
 
     def exclude_mask(
-        self: Self,
+        self,
         *args: int | Iterable[int] | np.ndarray,
         mode_: Literal["AND", "OR"] = "AND",
         **kwargs: Any | list[Any] | np.ndarray,
@@ -299,7 +314,7 @@ def exclude_mask(
     def re_order(self: Self, new_order: ArrayLike, column: str = "id") -> Self:
         return self.__class__(data=re_order(self._data, new_order, column=column))
 
-    def update_by_id(self: Self, ids: ArrayLike, allow_missing: bool = False, **kwargs) -> None:
+    def update_by_id(self, ids: ArrayLike, allow_missing: bool = False, **kwargs) -> None:
         try:
             _ = update_by_id(self._data, ids, allow_missing, **kwargs)
         except ValueError as error:
@@ -312,13 +327,13 @@ def get_updated_by_id(self: Self, ids: ArrayLike, allow_missing: bool = False, *
         except ValueError as error:
             raise ValueError(f"Cannot update {self.__class__.__name__}. {error}") from error
 
-    def check_ids(self: Self, return_duplicates: bool = False) -> NDArray | None:
+    def check_ids(self, return_duplicates: bool = False) -> NDArray | None:
         return check_ids(self._data, return_duplicates=return_duplicates)
 
-    def as_table(self: Self, column_width: int | str = "auto", rows: int = 10) -> str:
+    def as_table(self, column_width: int | str = "auto", rows: int = 10) -> str:
         return convert_array_to_string(self, column_width=column_width, rows=rows)
 
-    def as_df(self: Self):
+    def as_df(self):
         """Convert to pandas DataFrame"""
         if pandas is None:
             raise ImportError("pandas is not installed")

src/power_grid_model_ds/_core/model/graphs/models/base.py

@@ -29,12 +29,12 @@ def __init__(self, active_only=False) -> None:
 
     @property
     @abstractmethod
-    def nr_nodes(self):
+    def nr_nodes(self) -> int:
         """Returns the number of nodes in the graph"""
 
     @property
     @abstractmethod
-    def nr_branches(self):
+    def nr_branches(self) -> int:
         """Returns the number of branches in the graph"""
 
     @property
@@ -251,7 +251,7 @@ def get_all_paths(self, ext_start_node_id: int, ext_end_node_id: int) -> list[li
         return [self._internals_to_externals(path) for path in internal_paths]
 
     def get_components(self) -> list[list[int]]:
-        """Returns all separate components when the substation_nodes are removed of the graph as lists
+        """Returns all separate components of the graph as lists
 
         If you want to get the components of the graph without certain nodes,
         use the `tmp_remove_nodes` context manager.

src/power_grid_model_ds/_core/model/graphs/models/rustworkx.py

@@ -26,11 +26,11 @@ def __init__(self, active_only=False) -> None:
         self._external_to_internal: dict[int, int] = {}
 
     @property
-    def nr_nodes(self):
+    def nr_nodes(self) -> int:
         return self._graph.num_nodes()
 
     @property
-    def nr_branches(self):
+    def nr_branches(self) -> int:
         return self._graph.num_edges()
 
     @property

tests/unit/model/arrays/test_array.py

@@ -74,6 +74,17 @@ def test_getitem_unique_multiple_columns(fancy_test_array: FancyTestArray):
     assert np.array_equal(np.unique(fancy_test_array[columns]), fancy_test_array[columns])
 
 
+def test_getitem_array_index(fancy_test_array: FancyTestArray):
+    assert fancy_test_array[0].data.tolist() == fancy_test_array.data[0:1].tolist()
+
+
+def test_getitem_array_nested_index(fancy_test_array: FancyTestArray):
+    nested_array = fancy_test_array[0][0][0][0][0][0]
+    assert isinstance(nested_array, FancyArray)
+    assert nested_array.data.shape == (1,)
+    assert nested_array.data.tolist() == fancy_test_array.data[0:1].tolist()
+
+
 def test_getitem_array_slice(fancy_test_array: FancyTestArray):
     assert fancy_test_array.data[0:2].tolist() == fancy_test_array[0:2].tolist()
 
@@ -84,18 +95,20 @@ def test_getitem_with_array_mask(fancy_test_array: FancyTestArray):
     assert np.array_equal(fancy_test_array.data[mask], fancy_test_array[mask].data)
 
 
-def test_getitem_with_tuple_mask(fancy_test_array: FancyTestArray):
-    mask = (True, False, True)
-    assert isinstance(fancy_test_array[mask], FancyArray)
-    assert np.array_equal(fancy_test_array.data[mask], fancy_test_array[mask].data)
-
-
 def test_getitem_with_list_mask(fancy_test_array: FancyTestArray):
     mask = [True, False, True]
     assert isinstance(fancy_test_array[mask], FancyArray)
     assert np.array_equal(fancy_test_array.data[mask], fancy_test_array[mask].data)
 
 
+def test_getitem_with_tuple_mask(fancy_test_array: FancyTestArray):
+    # Numpy gives unexpected results with tuple masks. Therefore, we raise NotImplementedError here.
+    # e.g: np.array([1,2,3])[(True, False, True)] returns an empty array (array([], shape=(0, 3), dtype=int64)
+    mask = (True, False, True)
+    with pytest.raises(NotImplementedError):
+        fancy_test_array[mask]  # type: ignore[call-overload]  # noqa
+
+
 def test_getitem_with_empty_list_mask():
     array = FancyTestArray()
     mask = []