Lint tests

Author: rjanvier

pyproject.toml

@@ -52,12 +52,34 @@ sdist.exclude = [
   "third_party/taskflow/examples",
   "third_party/taskflow/sandbox",
   "third_party/taskflow/unittests",
-  "third_party/nanobind/doc",
-  "third_party/nanobind/examples",
-  "third_party/nanobind/scripts",
-  "third_party/nanobind/tests",
 ]
 
+[tool.ruff]
+target-version = "py310"
+line-length = 120
+
+[tool.ruff.lint]
+# TODO Add D, PTH, RET, disabled for now as they collides with intial choices
+select = ["E", "W", "YTT", "NPY", "PYI", "Q", "F", "B", "I", "SIM", "RUF"]
+# TODO: for now we ignore "Line too long error (E501)" 
+# because our comments are too longs
+# code formatting will take care of the line length in code anyway
+ignore = [
+  "E501",
+  # Ignore docstring in public package and module
+  "D100",
+  "D104",
+  # Blank line before class
+  "D203",
+  # multiline summary second line
+  "D213",
+  # yoda conditions
+  "SIM300",
+]
+
+[tool.ruff.lint.isort]
+known-first-party = ["pgeof"]
+
 [tool.tox]
 legacy_tox_ini = """
 [tox]

tests/bench_jakteristics.py

@@ -11,7 +11,8 @@
 
 @pytest.fixture
 def random_point_cloud():
-    return np.random.rand(1000000, 3) * 100
+    rng = np.random.default_rng()
+    return rng.random(0, 100, size=((1000000, 3)))
 
 
 @pytest.mark.benchmark(group="feature-computation-jak", disable_gc=True, warmup=True)

tests/bench_knn.py

@@ -7,7 +7,8 @@
 
 @pytest.fixture
 def random_point_cloud():
-    return np.random.rand(100000, 3).astype("float32")
+    rng = np.random.default_rng()
+    return rng.random(0, 100, size=((1000000, 3))).astype("float32")
 
 
 @pytest.mark.benchmark(group="knn", disable_gc=True, warmup=True)

tests/helpers.py

@@ -4,7 +4,8 @@
 
 def random_nn(num_points, k):
     # Generate a random synthetic point cloud
-    xyz = np.random.rand(num_points, 3)
+    rng = np.random.default_rng()
+    xyz = rng.random(size=(num_points, 3))
 
     # Converting k-nearest neighbors to CSR format
     kneigh = KDTree(xyz).query(xyz, k=k, workers=-1)
@@ -20,4 +21,4 @@ def random_nn(num_points, k):
     xyz = np.ascontiguousarray(xyz)
     nn_ptr = np.ascontiguousarray(nn_ptr)
     nn = np.ascontiguousarray(nn)
-    return xyz, nn, nn_ptr
+    return xyz, nn, nn_ptr

tests/test_pgeof.py

@@ -7,7 +7,8 @@
 
 def test_knn():
     knn = 10
-    xyz = np.random.rand(1000, 3)
+    rng = np.random.default_rng()
+    xyz = rng.random(size=(1000, 3))
     xyz = xyz.astype("float32")
     tree = KDTree(xyz)
     _, k_legacy = tree.query(xyz, k=knn, workers=-1)
@@ -18,7 +19,8 @@ def test_knn():
 def test_radius_search():
     knn = 10
     radius = 0.2
-    xyz = np.random.rand(1000, 3)
+    rng = np.random.default_rng()
+    xyz = rng.random(size=(1000, 3))
     xyz = xyz.astype("float32")
     tree = KDTree(xyz)
     _, k_legacy = tree.query(xyz, k=knn, distance_upper_bound=radius, workers=-1)
@@ -43,4 +45,4 @@ def test_pgeof_multiscale():
     simple = pgeof.compute_features(xyz, nn, nn_ptr, 50, False)
     multi_simple = pgeof.compute_features_multiscale(xyz, nn, nn_ptr, [20], False)
     np.testing.assert_allclose(multi[:, 0], multi_simple[:, 0], 1e-1, 1e-5)
-    np.testing.assert_allclose(multi[:, 1], simple, 1e-1, 1e-5)
+    np.testing.assert_allclose(multi[:, 1], simple, 1e-1, 1e-5)