v1.0.3

README.md

@@ -50,7 +50,7 @@ The ```-p``` flag controls the port number on local host. For example, writing `
 ## Documentation
 Extensive documentation, including several tutorials, can be found in [CAJAL's readthedocs.io website](https://cajal.readthedocs.io/en/latest/index.html). This website is under development and will continue to be substantially updated during the coming months.
 
-## New in this release (v1.0.2, 8/22/2024)
+## New in this release (v1.0.3, 8/22/2024)
 - Released on PyPI
 - Included a fix in cell segmentation contributed by @YuchenXiangEMBL
 - Wheels are available on the Github Release page

pyproject.toml

@@ -12,7 +12,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "cajal"
-version = "1.0.2"
+version = "1.0.3"
 description="A library for multi-modal cell morphology analyses using Gromov-Wasserstein (GW) distance."
 readme="./README.md"
 requires-python=">=3.9"

src/cajal/sample_seg.py

@@ -11,6 +11,18 @@
 from pathos.pools import ProcessPool
 from .utilities import write_csv_block
 
+def _filter_to_cells(segmask: npt.NDArray[np.int_], background: int) -> list[int]:
+    """
+    Return a list of identifiers for cells in the interior of the image.
+    """
+    cell_ids = set(np.unique(segmask))
+    remove_cells = set()
+    remove_cells.add(background)
+    remove_cells.update(np.unique(segmask[0, :]))
+    remove_cells.update(np.unique(segmask[-1, :]))
+    remove_cells.update(np.unique(segmask[:, 0]))
+    remove_cells.update(np.unique(segmask[:, -1]))
+    return list(cell_ids.difference(remove_cells))
 
 def cell_boundaries(
     imarray: npt.NDArray[np.int_],
@@ -40,18 +52,9 @@ def cell_boundaries(
        containing points sampled from the contours.
     """
 
-    cell_ids = set(np.unique(imarray))
-    remove_cells = set()
-    remove_cells.update(np.unique(imarray[0, :]))
-    remove_cells.update(np.unique(imarray[-1, :]))
-    remove_cells.update(np.unique(imarray[:, 0]))
-    remove_cells.update(np.unique(imarray[:, -1]))
-    cell_id_list = list(cell_ids.difference(remove_cells))
-
-    outlist: List[npt.NDArray[np.float64]] = []
+    cell_id_list = _filter_to_cells(imarray, background)
+    outlist: List[Tuple[int, npt.NDArray[np.float64]]] = []
     for cell in cell_id_list:
-        if cell == background:  # Don't draw a boundary around background
-            continue
         cell_imarray = (imarray == cell) * 1
         boundary_pts_list = measure.find_contours(
             cell_imarray, 0.5, fully_connected="high"
@@ -73,8 +76,9 @@ def cell_boundaries(
                 + str(cell)
             )
         indices = np.linspace(0, boundary_pts.shape[0] - 1, n_sample)
-        outlist.append(boundary_pts[indices.astype("uint32")])
-    return list(enumerate(outlist))
+        outlist.append((cell, boundary_pts[indices.astype("uint32")]))
+    return list(outlist)
+
 
 
 def _compute_intracell_all(