remove use of deprecated NumPy APIs

experimental/off_to_vtk.py

@@ -32,7 +32,7 @@ def off_mesh_file_to_vtk(input_filename, output_filename, data_format="binary",
         assert match
         num_vertices = int(match.group(1))
         num_triangles = int(match.group(2))
-        vertices = np.empty((num_vertices, 3), dtype=np.float)
+        vertices = np.empty((num_vertices, 3), dtype=float)
         for i in range(num_vertices):
             components = f.readline().split()
             assert len(components) >= 3

pyproject.toml

@@ -17,7 +17,7 @@ extend-select = [
     "W",
     "I",
     "N",
-    "NPY201",
+    "NPY",
 ]
 ignore = [
     "N802",  # Gives false positives when a name contains an uppercase acronym

setup.cfg

@@ -31,7 +31,7 @@ packages = find:
 python_requires = ~=3.6
 install_requires =
     nibabel >= 2
-    numpy >= 1.11.0
+    numpy >= 1.17
     pillow >= 1.1.6
     requests >= 2
     scikit-image  # TODO use pillow instead

unit_tests/test_data_types.py

@@ -135,9 +135,8 @@ def test_dtype_conversion_integer_downcasting(dtype):
 
 
 def test_unsupported_tupled_dtype():
-
-    random_val = np.random.rand(81).reshape((3, 3, 3, 3)) * 255
-    random_val = random_val.astype(np.uint8)
+    rng = np.random.default_rng()
+    random_val = rng.integers(256, size=(3, 3, 3, 3), dtype=np.uint8)
     wrong_type = np.dtype([('A', 'u1'), ('B', 'u1'), ('C', 'u1')])
     new_data = random_val.copy().view(dtype=wrong_type).reshape((3, 3, 3))
 
@@ -146,8 +145,8 @@ def test_unsupported_tupled_dtype():
 
 
 def test_supported_tupled_dtype():
-    random_val = np.random.rand(81).reshape((3, 3, 3, 3)) * 255
-    random_val = random_val.astype(np.uint8)
+    rng = np.random.default_rng()
+    random_val = rng.integers(256, size=(3, 3, 3, 3), dtype=np.uint8)
     right_type = np.dtype([('R', 'u1'), ('G', 'u1'), ('B', 'u1')])
     new_data = random_val.copy().view(dtype=right_type).reshape((3, 3, 3))
     dtype, isrgb = get_dtype(new_data.dtype)

unit_tests/test_volume_reader.py

@@ -11,15 +11,13 @@
 
 
 def prepare_nifti_images():
-
-    random_rgb_val = np.random.rand(81).reshape((3, 3, 3, 3)) * 255
-    random_rgb_val = random_rgb_val.astype(np.uint8)
+    rng = np.random.default_rng()
+    random_rgb_val = rng.integers(256, size=(3, 3, 3, 3), dtype=np.uint8)
     right_type = np.dtype([("R", "u1"), ("G", "u1"), ("B", "u1")])
     new_data = random_rgb_val.copy().view(dtype=right_type).reshape((3, 3, 3))
     rgb_img = nib.Nifti1Image(new_data, np.eye(4))
 
-    random_uint8_val = np.random.rand(27).reshape((3, 3, 3)) * 255
-    random_uint8_val = random_uint8_val.astype(np.uint8)
+    random_uint8_val = rng.integers(256, size=(3, 3, 3), dtype=np.uint8)
     uint8_img = nib.Nifti1Image(random_uint8_val, np.eye(4))
 
     return [(rgb_img, 3), (uint8_img, 1)]