Format after updating ruff

.pre-commit-config.yaml

@@ -126,7 +126,7 @@ repos:
     hooks:
       - id: "markdownlint-cli2-fix"
   - repo: "https://github.com/charliermarsh/ruff-pre-commit"
-    rev: "v0.1.7"
+    rev: "v0.1.9"
     hooks:
       - id: "ruff"
         types_or: ["python", "pyi", "jupyter"]

.tools/requirements/requirements_both.txt

@@ -10,7 +10,7 @@ cachier@git+https://github.com/blakeNaccarato/cachier@0892f53dc8fd9fb8a7f959305a
 # Type checking
 pyright==1.1.336
 # Pre-commit common requirements
-ruff==0.1.6
+ruff==0.1.9
 # Testing
 pytest==7.4.3
 # Testing plugins

.tools/scripts/pythonstartup.py

@@ -57,7 +57,7 @@ def filter_certain_warnings():
 
 
 def get_default_warnings_for_src(
-    category: type[Warning]
+    category: type[Warning],
 ) -> tuple[WarningFilter, WarningFilter]:
     """Get filter which sets default warning behavior only for the package in `src`."""
     package = next(path for path in Path("src").iterdir() if path.is_dir()).name

src/boilercv/data/sets.py

@@ -116,13 +116,11 @@ def get_dataset(
             xr.Dataset({VIDEO: ds[VIDEO], HEADER: ds[HEADER]}).to_netcdf(
                 path=unc_source, encoding={VIDEO: {"zlib": False}}
             )
-        return xr.Dataset(
-            {
-                VIDEO: unpack(ds[VIDEO].sel(frame=frame)),
-                ROI: roi_ds[ROI],
-                HEADER: ds[HEADER],
-            }
-        )
+        return xr.Dataset({
+            VIDEO: unpack(ds[VIDEO].sel(frame=frame)),
+            ROI: roi_ds[ROI],
+            HEADER: ds[HEADER],
+        })
 
 
 def get_stage(name: str, stage: Stage = STAGE_DEFAULT) -> tuple[Path, Path]:

src/boilercv/docs.py

@@ -136,19 +136,17 @@ def truncate(df: DfOrS, head: bool = False) -> tuple[pd.DataFrame, bool]:
     df.columns = [str(col) for col in df.columns]
     # Resolves ValueError: Length of names must match number of levels in MultiIndex.
     ellipsis_index = ("...",) * df.index.nlevels
-    df = pd.concat(
-        [
-            df.head(pd.options.display.min_rows // 2),
-            df.iloc[[0]]  # Resolves ValueError: cannot handle a non-unique multi-index!
-            .reindex(
-                pd.MultiIndex.from_tuples([ellipsis_index], names=df.index.names)
-                if isinstance(df.index, pd.MultiIndex)
-                else pd.Index(ellipsis_index, name=df.index.name)
-            )
-            .assign(**{col: "..." for col in df.columns}),
-            df.tail(pd.options.display.min_rows // 2),
-        ]
-    )
+    df = pd.concat([
+        df.head(pd.options.display.min_rows // 2),
+        df.iloc[[0]]  # Resolves ValueError: cannot handle a non-unique multi-index!
+        .reindex(
+            pd.MultiIndex.from_tuples([ellipsis_index], names=df.index.names)
+            if isinstance(df.index, pd.MultiIndex)
+            else pd.Index(ellipsis_index, name=df.index.name)
+        )
+        .assign(**{col: "..." for col in df.columns}),
+        df.tail(pd.options.display.min_rows // 2),
+    ])
     return df, True
 
 

src/boilercv/examples/detect_surface.py

@@ -104,9 +104,12 @@ def find_boiling_surface(img: Img) -> tuple[Img, ArrInt]:
     xpx_left = points.xpx.min()
     xpx_right = points.xpx.max()
     ypx_horizontal = np.round(points.ypx.mean()).astype(int)
-    boiling_surface_coords = np.array(
-        [ypx_horizontal, xpx_left, ypx_horizontal, xpx_right]
-    ).astype(int)
+    boiling_surface_coords = np.array([
+        ypx_horizontal,
+        xpx_left,
+        ypx_horizontal,
+        xpx_right,
+    ]).astype(int)
 
     if PREVIEW:
         view_images(

src/boilercv/old/_contours.py

@@ -67,16 +67,14 @@ def _get_contours(
 
 
 def interact_with_images(_input_image, _masked, thresholded, contoured):
-    _plt, ax = subplot_mosaic(
+    _plt, ax = subplot_mosaic([
         [
-            [
-                # "input",
-                # "masked",
-                "thresholded",
-                "contoured",
-            ]
+            # "input",
+            # "masked",
+            "thresholded",
+            "contoured",
         ]
-    )
+    ])
     for ax_ in ax.values():
         ax_.axis("off")
     # ax["input"].imshow(input_image, cmap="gray")

src/boilercv/stages/experiments/e230920_subcool/__init__.py

@@ -129,13 +129,11 @@ def crop_image(img, ylim, xlim):
 
 
 def get_hists(df: pd.DataFrame, groupby: str, cols: list[str]) -> pd.DataFrame:
-    df = df.groupby(groupby, **GBC).agg(
-        **{
-            # type: ignore  # pyright 1.1.333
-            col: pd.NamedAgg(column=col, aggfunc=sparkhist)
-            for col in cols
-        }
-    )
+    df = df.groupby(groupby, **GBC).agg(**{
+        # type: ignore  # pyright 1.1.333
+        col: pd.NamedAgg(column=col, aggfunc=sparkhist)
+        for col in cols
+    })
     # Can't one-shot this because of the comprehension {...: ... for col in hist_cols}
     return df.assign(**{col: df[col].str.center(WIDTH, "▁") for col in cols})
 
@@ -163,12 +161,10 @@ def __post_init__(self):
 
 
 def transform_cols(df: pd.DataFrame, cols: list[Col]) -> pd.DataFrame:
-    return df.assign(
-        **{
-            col.new: df[col.old] if col.scale == 1 else df[col.old] * col.scale
-            for col in cols
-        }
-    )[[col.new for col in cols]]
+    return df.assign(**{
+        col.new: df[col.old] if col.scale == 1 else df[col.old] * col.scale
+        for col in cols
+    })[[col.new for col in cols]]
 
 
 class Conversion(TypedDict):

src/boilercv/stages/experiments/e230920_subcool/find_collapse.ipynb

@@ -514,18 +514,14 @@
     "    time=time,\n",
     ")\n",
     "\n",
-    "nondimensionalized_departing_long_lived_objects = departing_long_lived_objects.assign(\n",
-    "    **{\n",
-    "        \"Bubble Fourier number\": lambda df: fourier(\n",
-    "            initial_bubble_diameter=df[\"diameterinit\"],\n",
-    "            liquid_thermal_diffusivity=liquid_thermal_diffusivity,\n",
-    "            time=df[\"time\"],\n",
-    "        ),\n",
-    "        \"Dimensionless bubble diameter\": (\n",
-    "            lambda df: df[\"diameter\"] / df[\"diameterinit\"]\n",
-    "        ),\n",
-    "    }\n",
-    ")"
+    "nondimensionalized_departing_long_lived_objects = departing_long_lived_objects.assign(**{\n",
+    "    \"Bubble Fourier number\": lambda df: fourier(\n",
+    "        initial_bubble_diameter=df[\"diameterinit\"],\n",
+    "        liquid_thermal_diffusivity=liquid_thermal_diffusivity,\n",
+    "        time=df[\"time\"],\n",
+    "    ),\n",
+    "    \"Dimensionless bubble diameter\": (lambda df: df[\"diameter\"] / df[\"diameterinit\"]),\n",
+    "})"
    ]
   },
   {

src/boilercv/stages/experiments/e230920_subcool/get_thermal_data.ipynb

@@ -103,12 +103,10 @@
    "outputs": [],
    "source": [
     "scatterplot(\n",
-    "    data=data.reset_index().assign(\n",
-    "        **{\n",
-    "            \"Time (s)\": lambda df: (df.time - df.time[0]).dt.total_seconds(),\n",
-    "            \"Flux (W/cm^2)\": lambda df: df[\"Q34 (W)\"] / 0.712557392,\n",
-    "        }\n",
-    "    ),\n",
+    "    data=data.reset_index().assign(**{\n",
+    "        \"Time (s)\": lambda df: (df.time - df.time[0]).dt.total_seconds(),\n",
+    "        \"Flux (W/cm^2)\": lambda df: df[\"Q34 (W)\"] / 0.712557392,\n",
+    "    }),\n",
     "    x=\"superheat\",\n",
     "    y=\"Flux (W/cm^2)\",\n",
     "    hue=\"Time (s)\",\n",

tests/boilercv_tests/conftest.py

@@ -36,18 +36,16 @@ def _project_session_path(tmp_path_factory):
 @pytest.fixture(autouse=True)
 def _filter_certain_warnings():
     """Filter certain warnings."""
-    filter_certain_warnings(
-        [
-            WarningFilter(
-                message=r"numpy\.ndarray size changed, may indicate binary incompatibility\. Expected \d+ from C header, got \d+ from PyObject",
-                category=RuntimeWarning,
-            ),
-            WarningFilter(
-                message=r"A grouping was used that is not in the columns of the DataFrame and so was excluded from the result\. This grouping will be included in a future version of pandas\. Add the grouping as a column of the DataFrame to silence this warning\.",
-                category=FutureWarning,
-            ),
-        ]
-    )
+    filter_certain_warnings([
+        WarningFilter(
+            message=r"numpy\.ndarray size changed, may indicate binary incompatibility\. Expected \d+ from C header, got \d+ from PyObject",
+            category=RuntimeWarning,
+        ),
+        WarningFilter(
+            message=r"A grouping was used that is not in the columns of the DataFrame and so was excluded from the result\. This grouping will be included in a future version of pandas\. Add the grouping as a column of the DataFrame to silence this warning\.",
+            category=FutureWarning,
+        ),
+    ])
 
 
 # * -------------------------------------------------------------------------------- * #
@@ -109,22 +107,15 @@ def update_fixture_stores(
 
 @pytest.fixture(scope="session")
 def fixtures(nested_fixture_store) -> SimpleNamespace:
-    return SimpleNamespace(
-        **{
-            key: SimpleNamespace(
-                **{
-                    key: SimpleNamespace(
-                        **{
-                            key: SimpleNamespace(**value)
-                            for key, value in value.items()
-                        }
-                    )
-                    for key, value in value.items()
-                }
-            )
-            for key, value in nested_fixture_store.items()
-        }
-    )
+    return SimpleNamespace(**{
+        key: SimpleNamespace(**{
+            key: SimpleNamespace(**{
+                key: SimpleNamespace(**value) for key, value in value.items()
+            })
+            for key, value in value.items()
+        })
+        for key, value in nested_fixture_store.items()
+    })
 
 
 @pytest.fixture(scope="session")