fix typing

glass-dev · Nov 5, 2024 · 14c3f2c · 14c3f2c
1 parent 88f5ee4
commit 14c3f2c
Showing 1 changed file with 22 additions and 21 deletions.
diff --git a/tests/test_points.py b/tests/test_points.py
@@ -4,9 +4,7 @@
 
 import numpy as np
 import numpy.typing as npt
-
 import pytest
-import pytest_mock
 
 from glass.points import (
     effective_bias,
@@ -20,6 +18,8 @@
 if typing.TYPE_CHECKING:
     import collections.abc
 
+    import pytest_mock
+
 
 def catpos(
     pos: collections.abc.Generator[
@@ -53,17 +53,17 @@ def test_effective_bias(mocker: pytest_mock.MockerFixture) -> None:
     z = np.linspace(0, 1, 10)
     bz = np.zeros((10,))
 
-    np.testing.assert_allclose(effective_bias(z, bz, w), np.zeros((10,)))  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(effective_bias(z, bz, w), np.zeros((10,)))
 
     z = np.zeros((10,))
     bz = np.full_like(z, 0.5)
 
-    np.testing.assert_allclose(effective_bias(z, bz, w), np.zeros((10,)))  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(effective_bias(z, bz, w), np.zeros((10,)))
 
     z = np.linspace(0, 1, 10)
     bz = np.full_like(z, 0.5)
 
-    np.testing.assert_allclose(effective_bias(z, bz, w), 0.25)  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(effective_bias(z, bz, w), 0.25)
 
 
 def test_linear_bias(rng: np.random.Generator) -> None:
@@ -72,21 +72,21 @@ def test_linear_bias(rng: np.random.Generator) -> None:
     delta = np.zeros((2, 2))
     b = 2.0
 
-    np.testing.assert_allclose(linear_bias(delta, b), np.zeros((2, 2)))  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(linear_bias(delta, b), np.zeros((2, 2)))
 
     # test with 0 b
 
     delta = rng.normal(5, 1, size=(2, 2))
     b = 0.0
 
-    np.testing.assert_allclose(linear_bias(delta, b), np.zeros((2, 2)))  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(linear_bias(delta, b), np.zeros((2, 2)))
 
     # compare with original implementation
 
     delta = rng.normal(5, 1, size=(2, 2))
     b = 2.0
 
-    np.testing.assert_allclose(linear_bias(delta, b), b * delta)  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(linear_bias(delta, b), b * delta)
 
 
 def test_loglinear_bias(rng: np.random.Generator) -> None:
@@ -95,24 +95,24 @@ def test_loglinear_bias(rng: np.random.Generator) -> None:
     delta = np.zeros((2, 2))
     b = 2.0
 
-    np.testing.assert_allclose(loglinear_bias(delta, b), np.zeros((2, 2)))  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(loglinear_bias(delta, b), np.zeros((2, 2)))
 
     # test with 0 b
 
     delta = rng.normal(5, 1, size=(2, 2))
     b = 0.0
 
-    np.testing.assert_allclose(loglinear_bias(delta, b), np.zeros((2, 2)))  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(loglinear_bias(delta, b), np.zeros((2, 2)))
 
     # compare with numpy implementation
 
     delta = rng.normal(5, 1, size=(2, 2))
     b = 2.0
 
-    np.testing.assert_allclose(loglinear_bias(delta, b), np.expm1(b * np.log1p(delta)))  # type: ignore[no-untyped-call]
+    np.testing.assert_allclose(loglinear_bias(delta, b), np.expm1(b * np.log1p(delta)))
 
 
-def test_positions_from_delta(rng: np.random.Generator) -> None:
+def test_positions_from_delta(rng: np.random.Generator) -> None:  # noqa: PLR0915
     # create maps that saturate the batching in the function
     nside = 128
     npix = 12 * nside**2
@@ -131,31 +131,31 @@ def test_positions_from_delta(rng: np.random.Generator) -> None:
 
     # test with rng
 
-    lon, lat, cnt = catpos(positions_from_delta(ngal, delta, bias, vis, rng=rng))  # type: ignore[no-untyped-call]
+    lon, lat, cnt = catpos(positions_from_delta(ngal, delta, bias, vis, rng=rng))
 
     assert isinstance(cnt, int)
     assert lon.shape == lat.shape == (cnt,)
 
     # case: Nons bias and callable bias model
 
     lon, lat, cnt = catpos(
-        positions_from_delta(ngal, delta, None, vis, bias_model=lambda x: x)  # type: ignore[no-untyped-call]
+        positions_from_delta(ngal, delta, None, vis, bias_model=lambda x: x)
     )
 
     assert isinstance(cnt, int)
     assert lon.shape == lat.shape == (cnt,)
 
     # case: None vis
 
-    lon, lat, cnt = catpos(positions_from_delta(ngal, delta, bias, None))  # type: ignore[no-untyped-call]
+    lon, lat, cnt = catpos(positions_from_delta(ngal, delta, bias, None))
 
     assert isinstance(cnt, int)
     assert lon.shape == lat.shape == (cnt,)
 
     # case: remove monopole
 
     lon, lat, cnt = catpos(
-        positions_from_delta(ngal, delta, bias, vis, remove_monopole=True)  # type: ignore[no-untyped-call]
+        positions_from_delta(ngal, delta, bias, vis, remove_monopole=True)
     )
 
     assert isinstance(cnt, int)
@@ -164,7 +164,7 @@ def test_positions_from_delta(rng: np.random.Generator) -> None:
     # case: negative delta
 
     lon, lat, cnt = catpos(
-        positions_from_delta(ngal, np.linspace(-1, -1, 196608), None, vis)  # type: ignore[no-untyped-call]
+        positions_from_delta(ngal, np.linspace(-1, -1, 196608), None, vis)
     )
 
     assert isinstance(cnt, int)
@@ -173,7 +173,7 @@ def test_positions_from_delta(rng: np.random.Generator) -> None:
     # case: large delta
 
     lon, lat, cnt = catpos(
-        positions_from_delta(ngal, rng.normal(100, 1, size=(196608,)), bias, vis)  # type: ignore[no-untyped-call]
+        positions_from_delta(ngal, rng.normal(100, 1, size=(196608,)), bias, vis)
     )
 
     assert isinstance(cnt, int)
@@ -225,16 +225,17 @@ def test_positions_from_delta(rng: np.random.Generator) -> None:
 
     vis[: vis.size // 2] = 0.0
 
-    lon, lat, cnt = catpos(positions_from_delta(ngal, delta, bias, vis))  # type: ignore[no-untyped-call]
+    lon, lat, cnt = catpos(positions_from_delta(ngal, delta, bias, vis))
 
+    assert isinstance(cnt, np.ndarray)
     assert cnt.shape == (3, 2)
     assert lon.shape == (cnt.sum(),)
     assert lat.shape == (cnt.sum(),)
 
     # test TypeError
 
     with pytest.raises(TypeError, match="bias_model must be string or callable"):
-        next(positions_from_delta(ngal, delta, bias, vis, bias_model=0))  # type: ignore[no-untyped-call]
+        next(positions_from_delta(ngal, delta, bias, vis, bias_model=0))  # type: ignore[arg-type]
 
 
 def test_uniform_positions(rng: np.random.Generator) -> None:
@@ -246,7 +247,7 @@ def test_uniform_positions(rng: np.random.Generator) -> None:
 
     # test with rng
 
-    lon, lat, cnt = catpos(uniform_positions(ngal, rng=rng))  # type: ignore[no-untyped-call]
+    lon, lat, cnt = catpos(uniform_positions(ngal, rng=rng))
 
     assert isinstance(cnt, int)
     assert lon.shape == lat.shape == (cnt,)