Replace use of deprecated np.bool with dtype alias np.bool_

bluesky · Oct 18, 2024 · d0be011 · d0be011
1 parent 6291ec7
commit d0be011
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Showing 2 changed files with 6 additions and 8 deletions.
diff --git a/src/scanspec/core.py b/src/scanspec/core.py
@@ -41,7 +41,7 @@
 C = TypeVar("C")
 T = TypeVar("T")
 
-GapArray = npt.NDArray[np.bool]
+GapArray = npt.NDArray[np.bool_]
 
 
 def discriminated_union_of_subclasses(
@@ -586,9 +586,7 @@ def consume(self, num: int | None = None) -> Frames[Axis]:
             end_index = min(self.index + num, self.end_index)
         indices = np.arange(self.index, end_index)
         self.index = end_index
-        stack: Frames[Axis] = Frames(
-            {}, {}, {}, np.zeros(indices.shape, dtype=np.bool_)
-        )
+        stack: Frames[Axis] = Frames({}, {}, {}, np.zeros(indices.shape, dtype=bool_))
         # Example numbers below from a 2x3x4 ZxYxX scan
         for i, frames in enumerate(self.stack):
             # Number of times each frame will repeat: Z:12, Y:4, X:1

diff --git a/src/scanspec/regions.py b/src/scanspec/regions.py
@@ -40,7 +40,7 @@
     "find_regions",
 ]
 
-NpMask = npt.NDArray[np.bool]
+NpMask = npt.NDArray[np.bool_]
 
 
 @discriminated_union_of_subclasses
@@ -96,7 +96,7 @@ def get_mask(region: Region[Axis], points: AxesPoints[Axis]) -> NpMask:
     if needs_mask:
         return region.mask(points)
     else:
-        return np.ones(len(list(points.values())[0]), dtype=np.bool)
+        return np.ones(len(list(points.values())[0]), dtype=np.bool_)
 
 
 def _merge_axis_sets(axis_sets: list[set[Axis]]) -> Iterator[set[Axis]]:
@@ -287,11 +287,11 @@ def mask(self, points: AxesPoints[Axis]) -> NpMask:  # noqa: D102
         x = points[self.x_axis]
         y = points[self.y_axis]
         v1x, v1y = self.x_verts[-1], self.y_verts[-1]
-        mask = np.full(len(x), False, dtype=np.bool)
+        mask = np.full(len(x), False, dtype=np.bool_)
         for v2x, v2y in zip(self.x_verts, self.y_verts, strict=False):
             # skip horizontal edges
             if v2y != v1y:
-                vmask = np.full(len(x), False, dtype=np.bool)
+                vmask = np.full(len(x), False, dtype=np.bool_)
                 vmask |= (y < v2y) & (y >= v1y)
                 vmask |= (y < v1y) & (y >= v2y)
                 t = (y - v1y) / (v2y - v1y)