updated numpy to 2.0.0+

requirements.txt

@@ -1,3 +1,3 @@
-numpy>=1.18.0
-gymnasium>=0.26
+numpy>=2.0.0
+gymnasium>=1.0.0
 pygame>=2.2.0

tests/test_wfc/test_wfc_solver.py

@@ -18,7 +18,7 @@ def test_entropyLocationHeuristic() -> None:
     wave = np.ones((5, 3, 4), dtype=bool)  # everything is possible
     wave[1:, 0, 0] = False  # first cell is fully observed
     wave[4, :, 2] = False
-    preferences: NDArray[np.float_] = np.ones((3, 4), dtype=np.float_) * 0.5
+    preferences: NDArray[np.float64] = np.ones((3, 4), dtype=np.float64) * 0.5
     preferences[1, 2] = 0.3
     preferences[1, 1] = 0.1
     heu = wfc_solver.makeEntropyLocationHeuristic(preferences)

tests/test_wrappers.py

@@ -305,11 +305,11 @@ def test_symbolic_obs_wrapper(env_id):
     goal_pos = env.unwrapped.goal_pos
 
     assert obs["image"].shape == (env.unwrapped.width, env.unwrapped.height, 3)
-    assert np.alltrue(
+    assert np.all(
         obs["image"][agent_pos[0], agent_pos[1], :]
         == np.array([agent_pos[0], agent_pos[1], OBJECT_TO_IDX["agent"]])
     )
-    assert np.alltrue(
+    assert np.all(
         obs["image"][goal_pos[0], goal_pos[1], :]
         == np.array([goal_pos[0], goal_pos[1], OBJECT_TO_IDX["goal"]])
     )
@@ -319,11 +319,11 @@ def test_symbolic_obs_wrapper(env_id):
     goal_pos = env.unwrapped.goal_pos
 
     assert obs["image"].shape == (env.unwrapped.width, env.unwrapped.height, 3)
-    assert np.alltrue(
+    assert np.all(
         obs["image"][agent_pos[0], agent_pos[1], :]
         == np.array([agent_pos[0], agent_pos[1], OBJECT_TO_IDX["agent"]])
     )
-    assert np.alltrue(
+    assert np.all(
         obs["image"][goal_pos[0], goal_pos[1], :]
         == np.array([goal_pos[0], goal_pos[1], OBJECT_TO_IDX["goal"]])
     )