npy autofix

Czaki · Mar 1, 2023 · 003fbc2 · 003fbc2
1 parent 82d419d
commit 003fbc2
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Showing 3 changed files with 8 additions and 8 deletions.
diff --git a/napari/_vispy/experimental/_tests/test_vispy_tiled_image.py b/napari/_vispy/experimental/_tests/test_vispy_tiled_image.py
@@ -57,7 +57,7 @@ def test_tiled_screenshot(qtbot, monkeypatch, make_napari_viewer, dtype):
 
     # Take the screenshot
     screenshot = viewer.screenshot(canvas_only=True, flash=False)
-    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(np.int)
+    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(int)
     target_center = np.array([0, 0, 128, 255], dtype='uint8')
     target_edge = np.array([0, 0, 0, 255], dtype='uint8')
     screen_offset = 3  # Offset is needed as our screenshots have black borders
@@ -98,7 +98,7 @@ def test_tiled_rgb(qtbot, monkeypatch, make_napari_viewer):
 
     # Take the screenshot
     screenshot = viewer.screenshot(canvas_only=True, flash=False)
-    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(np.int)
+    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(int)
     target_center = np.array([128, 128, 128, 255], dtype='uint8')
     target_edge = np.array([0, 0, 0, 255], dtype='uint8')
     screen_offset = 3  # Offset is needed as our screenshots have black borders
@@ -144,7 +144,7 @@ def test_tiled_changing_contrast_limits(
 
     # Take the screenshot
     screenshot = viewer.screenshot(canvas_only=True, flash=False)
-    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(np.int)
+    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(int)
     target_center = np.array([0, 0, 255, 255], dtype='uint8')
     target_edge = np.array([0, 0, 0, 255], dtype='uint8')
     screen_offset = 3  # Offset is needed as our screenshots have black borders
@@ -198,7 +198,7 @@ def test_tiled_single_scale(qtbot, monkeypatch, make_napari_viewer):
 
     # Take the screenshot
     screenshot = viewer.screenshot(canvas_only=True, flash=False)
-    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(np.int)
+    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(int)
     target_center = np.array([128, 128, 128, 255], dtype='uint8')
     screen_offset = 3  # Offset is needed as our screenshots have black borders
 
@@ -239,7 +239,7 @@ def test_tiled_labels(qtbot, monkeypatch, make_napari_viewer):
 
     # Take the screenshot
     screenshot = viewer.screenshot(canvas_only=True, flash=False)
-    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(np.int)
+    center_coord = np.round(np.array(screenshot.shape[:2]) / 2).astype(int)
     col = layer.get_color(1)
     target_center = np.array([c * 255 for c in col], dtype='uint8')
     target_edge = np.array([0, 0, 0, 255], dtype='uint8')

diff --git a/napari/layers/image/experimental/octree_level.py b/napari/layers/image/experimental/octree_level.py
@@ -181,7 +181,7 @@ def _create_chunk(self, row: int, col: int) -> OctreeChunk:
         # Create OctreeChunkGeom used by the visual for rendering this
         # chunk. Size it based on the base image pixels, not based on the
         # data in this level, so it's exact.
-        base = np.array(meta.base_shape[::-1], dtype=np.float)
+        base = np.array(meta.base_shape[::-1], dtype=float)
         remain = base - pos
         size = np.minimum(remain, [scaled_size, scaled_size])
         geom = OctreeChunkGeom(pos, size)

diff --git a/napari/layers/shapes/_shape_list.py b/napari/layers/shapes/_shape_list.py
@@ -1181,7 +1181,7 @@ def to_labels(self, labels_shape=None, zoom_factor=1, offset=(0, 0)):
             integer up to N for points inside the corresponding shape.
         """
         if labels_shape is None:
-            labels_shape = self.displayed_vertices.max(axis=0).astype(np.int)
+            labels_shape = self.displayed_vertices.max(axis=0).astype(int)
 
         labels = np.zeros(labels_shape, dtype=int)
 
@@ -1226,7 +1226,7 @@ def to_colors(
             value of the shape for points inside the corresponding shape.
         """
         if colors_shape is None:
-            colors_shape = self.displayed_vertices.max(axis=0).astype(np.int)
+            colors_shape = self.displayed_vertices.max(axis=0).astype(int)
 
         colors = np.zeros((*tuple(colors_shape), 4), dtype=float)
         colors[..., 3] = 1