Issue #207: Support Gymnasium 1.0.0

Author: Mark2000

pyproject.toml

@@ -15,7 +15,7 @@ requires-python = ">=3.10.0"
 license = { text = "MIT" }
 dependencies = [
     "Deprecated",
-    "gymnasium<1.0.0",
+    "gymnasium",
     "numpy",
     "pandas",
     "pettingzoo",
@@ -29,7 +29,7 @@ dependencies = [
 
 [project.optional-dependencies]
 docs = ["ipykernel", "ipywidgets", "nbdime", "nbsphinx", "sphinx-rtd-theme"]
-rllib = ["dm_tree", "pyarrow", "ray[rllib]", "scikit-image", "torch", "typer"]
+rllib = ["dm_tree", "pyarrow", "ray[rllib]==2.35.0", "scikit-image", "torch", "typer"]
 
 [project.scripts]
 finish_install = "bsk_rl.finish_install:pck_install"

src/bsk_rl/obs/observations.py

@@ -37,18 +37,17 @@ def nested_obs_to_space(obs_dict):
         )
     elif isinstance(obs_dict, list):
         return spaces.Box(
-            low=-1e16, high=1e16, shape=(len(obs_dict),), dtype=np.float64
+            low=-1e16, high=1e16, shape=(len(obs_dict),), dtype=np.float32
         )
     elif isinstance(obs_dict, (float, int)):
-        return spaces.Box(low=-1e16, high=1e16, shape=(1,), dtype=np.float64)
+        return spaces.Box(low=-1e16, high=1e16, shape=(1,), dtype=np.float32)
     elif isinstance(obs_dict, np.ndarray):
-        return spaces.Box(low=-1e16, high=1e16, shape=obs_dict.shape, dtype=np.float64)
+        return spaces.Box(low=-1e16, high=1e16, shape=obs_dict.shape, dtype=np.float32)
     else:
         raise TypeError(f"Cannot convert {obs_dict} to gym space.")
 
 
 class ObservationBuilder:
-
     def __init__(self, satellite: "Satellite", obs_type: type = np.ndarray) -> None:
         """Satellite subclass for composing observations.
 
@@ -312,7 +311,6 @@ def _r_LB_H(sat, opp):
 
 
 class OpportunityProperties(Observation):
-
     _fn_map = {
         "priority": lambda sat, opp: opp["object"].priority,
         "r_LP_P": lambda sat, opp: opp["r_LP_P"],

tests/integration/test_int_gym_env.py

@@ -35,7 +35,9 @@ def test_action_space(self):
         assert self.env.action_space == spaces.Discrete(1)
 
     def test_observation_space(self):
-        assert self.env.observation_space == spaces.Box(-1e16, 1e16, (1,))
+        assert self.env.observation_space == spaces.Box(
+            -1e16, 1e16, (1,), dtype=np.float32
+        )
 
     def test_step(self):
         observation, reward, terminated, truncated, info = self.env.step(0)
@@ -124,7 +126,10 @@ def test_action_space(self):
 
     def test_observation_space(self):
         assert self.env.observation_space == spaces.Tuple(
-            (spaces.Box(-1e16, 1e16, (1,)), spaces.Box(-1e16, 1e16, (1,)))
+            (
+                spaces.Box(-1e16, 1e16, (1,), dtype=np.float32),
+                spaces.Box(-1e16, 1e16, (1,), dtype=np.float32),
+            )
         )
 
     def test_step(self):

tests/unittest/obs/test_observations.py

@@ -69,23 +69,23 @@ def test_obs_cache(self):
         [
             (
                 np.array([1]),
-                spaces.Box(low=-1e16, high=1e16, shape=(1,), dtype=np.float64),
+                spaces.Box(low=-1e16, high=1e16, shape=(1,), dtype=np.float32),
             ),
             (
                 np.array([1, 2]),
-                spaces.Box(low=-1e16, high=1e16, shape=(2,), dtype=np.float64),
+                spaces.Box(low=-1e16, high=1e16, shape=(2,), dtype=np.float32),
             ),
             (
                 {"a": 1, "b": {"c": 1}},
                 spaces.Dict(
                     {
                         "a": spaces.Box(
-                            low=-1e16, high=1e16, shape=(1,), dtype=np.float64
+                            low=-1e16, high=1e16, shape=(1,), dtype=np.float32
                         ),
                         "b": spaces.Dict(
                             {
                                 "c": spaces.Box(
-                                    low=-1e16, high=1e16, shape=(1,), dtype=np.float64
+                                    low=-1e16, high=1e16, shape=(1,), dtype=np.float32
                                 )
                             }
                         ),

tests/unittest/test_gym_env.py

@@ -1,5 +1,6 @@
 from unittest.mock import MagicMock, patch
 
+import numpy as np
 import pytest
 from gymnasium import spaces
 
@@ -132,7 +133,9 @@ def test_get_obs_retasking_only(self):
             satellites=[
                 MagicMock(
                     get_obs=MagicMock(return_value=[i + 1]),
-                    observation_space=spaces.Box(-1e9, 1e9, shape=(1,)),
+                    observation_space=spaces.Box(
+                        -1e9, 1e9, shape=(1,), dtype=np.float32
+                    ),
                     requires_retasking=(i == 1),
                 )
                 for i in range(3)