Fix CI and CD: twine metadata, mypy/numpy/python version clash

.github/workflows/cd.yml

@@ -29,7 +29,7 @@ jobs:
         with:
           fetch-depth: 0
 
-      - uses: hynek/build-and-inspect-python-package@v2
+      - uses: hynek/build-and-inspect-python-package@v3.0.1
 
   publish:
     needs: [dist]

.github/workflows/ci.yml

@@ -27,7 +27,9 @@ jobs:
           fetch-depth: 0
       - uses: actions/setup-python@v6
         with:
-          python-version: "3.x"
+          python-version: |
+            3.11
+            3.x
 
       - uses: astral-sh/setup-uv@v7
 
@@ -42,7 +44,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.12", "3.13", "3.14"]
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
         runs-on: [ubuntu-latest]
 
     steps:

.pre-commit-config.yaml

@@ -55,6 +55,7 @@ repos:
       - id: mypy
         files: eye_patch|tests
         args: ["--ignore-missing-imports"]
+        language_version: python3.11
         additional_dependencies:
           - numpy
           - capn-crunch

eye_patch/masking.py

@@ -301,7 +301,9 @@ def beam_shape_erode(
             scales (list[int] | tuple[int, ...] | None, optional): Defines the scales that are being used during multi-scale clean. Perform the beam erosion at each of these scales. Defaults to None.
 
         Returns:
-    MaskLike: The eroded beam shape. If a no/single scale provide it is a bool return, otherwise int32.
+    MaskLike: The eroded beam shape. For no/single scale the dtype of ``mask`` is
+        preserved; for multiple scales a float64 bitmask is returned, where the
+        n'th scale is stored as the n'th bit.
     """
 
     if not all(key in fits_header for key in ["BMAJ", "BMIN", "BPA"]):
@@ -899,14 +901,14 @@ def create_snr_mask_from_fits(
         mask_data = reverse_negative_flood_fill(
             base_image=np.squeeze(signal_data),
             masking_options=masking_options,
-        )
+        ).astype(np.float32)
         mask_data = mask_data.reshape(signal_data.shape)
     else:
         logger.info(f"Clipping using a {masking_options.base_snr_clip=}")
         mask_data = (signal_data > masking_options.base_snr_clip).astype(float)
 
     if masking_options.beam_shape_erode:
-        mask_data = beam_shape_erode(  # type: ignore[assignment]
+        mask_data = beam_shape_erode(
             mask=mask_data,
             fits_header=fits_header,
             minimum_response=masking_options.beam_shape_erode_minimum_response,

pyproject.toml

@@ -22,7 +22,6 @@ classifiers = [
   "Programming Language :: Python",
   "Programming Language :: Python :: 3",
   "Programming Language :: Python :: 3 :: Only",
-  "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
   "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
@@ -98,7 +97,7 @@ report.exclude_also = ['\.\.\.', 'if typing.TYPE_CHECKING:']
 
 [tool.mypy]
 files = ["eye_patch", "tests"]
-python_version = "3.10"
+python_version = "3.11"
 warn_unused_configs = true
 strict = true
 enable_error_code = ["ignore-without-code", "redundant-expr", "truthy-bool"]

tests/test_masking.py

@@ -491,6 +491,58 @@ def test_fits_masking(fits_dir):
     assert valid == np.prod(SHAPE)
 
 
+@pytest.fixture
+def beam_fits_dir(tmp_path: Path, beam_fits_header: fits.Header) -> Path:
+    """As ``fits_dir``, but the image carries the beam keywords that
+    ``beam_shape_erode`` needs to build its kernel."""
+    beam_fits_dir = tmp_path / "beam_fits"
+    beam_fits_dir.mkdir()
+
+    fits.writeto(beam_fits_dir / "image.fits", np.ones(SHAPE), header=beam_fits_header)
+    fits.writeto(beam_fits_dir / "rms.fits", np.ones(SHAPE) * 0.1)
+    fits.writeto(beam_fits_dir / "bkg.fits", np.ones(SHAPE) * 0.5)
+
+    return beam_fits_dir
+
+
+def test_fits_masking_flood_fill_with_beam_erode(beam_fits_dir: Path) -> None:
+    """The flood filled mask reaches ``beam_shape_erode``, which types its input
+    as floats. This is the path the bool mask was travelling down."""
+    masking_options = MaskingOptions(flood_fill=True, beam_shape_erode=True)
+    names = create_snr_mask_from_fits(
+        fits_image_path=beam_fits_dir / "image.fits",
+        fits_rms_path=beam_fits_dir / "rms.fits",
+        fits_bkg_path=beam_fits_dir / "bkg.fits",
+        masking_options=masking_options,
+    )
+
+    assert isinstance(names, FITSMaskNames)
+    assert names.mask_fits.exists()
+
+    mask_data = fits.getdata(names.mask_fits)
+    assert mask_data.dtype.kind == "f", "A bool mask cannot be written to FITS"
+
+
+def test_fits_masking_flood_fill_writes_float_mask(fits_dir: Path) -> None:
+    """The flood fill path builds its mask as a bool array, which ``fits.writeto``
+    rejects. Reported by Beth via #14, and not caught earlier because every other
+    mask test runs with ``flood_fill=False``."""
+    masking_options = MaskingOptions(flood_fill=True)
+    names = create_snr_mask_from_fits(
+        fits_image_path=fits_dir / "image.fits",
+        fits_rms_path=fits_dir / "rms.fits",
+        fits_bkg_path=fits_dir / "bkg.fits",
+        masking_options=masking_options,
+    )
+
+    assert isinstance(names, FITSMaskNames)
+    assert names.mask_fits.exists()
+
+    mask_data = fits.getdata(names.mask_fits)
+    assert mask_data.dtype.kind == "f", "A bool mask cannot be written to FITS"
+    assert np.sum(mask_data) == np.prod(SHAPE)
+
+
 def test_fits_masking_with_signal(fits_dir):
     masking_options = MaskingOptions(flood_fill=False)
     names = create_snr_mask_from_fits(