Added cy_mesh.pyi and floodfill.pyi

pyproject.toml

@@ -87,7 +87,7 @@ module = [
 ignore_missing_imports = true
 
 [tool.ruff]
-include = ["pyproject.toml", "invesalius/**/*.py",'setup.py','app.py']
+include = ["pyproject.toml", "invesalius/**/*.py",'setup.py','app.py',"typings/**/*.pyi"]
 line-length = 100
 # extend-exclude = ["plugins"]
 

typings/invesalius_cy-stubs/cy_mesh.pyi

@@ -0,0 +1,28 @@
+from vtk import vtkPolyData
+
+class Mesh:
+    def __init__(self, pd: vtkPolyData | None = None, other: Mesh | None = None) -> None: ...
+    def copy_to(self, other: Mesh) -> None:
+        """
+        Copies self content to other.
+        """
+    def to_vtk(self) -> vtkPolyData:
+        """
+        Converts Mesh to vtkPolyData.
+        """
+
+def ca_smoothing(mesh: Mesh, T: float, tmax: float, bmin: float, n_iters: int) -> None:
+    """
+    This is a implementation of the paper "Context-aware mesh smoothing for
+    biomedical applications". It can be used to smooth meshes generated by
+    binary images to remove its staircase artifacts and keep the fine features.
+
+    Params:
+        mesh: Mesh
+        T: Min angle (between vertex faces and stack_orientation) to consider a
+           vertex a staircase artifact
+        tmax: max distance the vertex must be to its nearest artifact vertex
+              to considered to calculate the weight
+        bmin: The minimum weight
+        n_iters: Number of iterations.
+    """

typings/invesalius_cy-stubs/floodfill.pyi

@@ -0,0 +1,28 @@
+from typing import Iterable
+
+import numpy as np
+
+def floodfill(
+    data: np.ndarray,
+    i: int,
+    j: int,
+    k: int,
+    v: int,
+    fill: int,
+    out: np.ndarray | None,
+) -> np.ndarray | None: ...
+def floodfill_threshold(
+    data: np.ndarray,
+    seeds: list[Iterable[int]],
+    t0: int,
+    t1: int,
+    fill: int,
+    strct: np.ndarray,
+    out: np.ndarray | None,
+) -> np.ndarray | None: ...
+def floodfill_auto_threshold(
+    data: np.ndarray, seeds: list[Iterable[int]], p: float, fill: int, out: np.ndarray | None
+) -> np.ndarray | None: ...
+def fill_holes_automatically(
+    mask: np.ndarray, labels: np.ndarray, nlabels: int, max_size: int
+) -> bool: ...