change obs and action to dict

.gitignore

@@ -11,3 +11,6 @@
 # Python egg metadata, regenerated from source files by setuptools.
 /*.egg-info
 /*.egg
+
+/.claude/
+/.venv/

pyproject.toml

@@ -0,0 +1,36 @@
+[project]
+name = "simglucose"
+version = "0.2.11"
+description = "A Type-1 Diabetes Simulator as a Reinforcement Learning Environment in OpenAI gym or rllab"
+readme = "README.md"
+license = {text = "MIT"}
+authors = [{name = "Jinyu Xie", email = "xjygr08@gmail.com"}]
+requires-python = ">=3.9"
+dependencies = [
+    "gym==0.9.4",
+    "gymnasium~=0.29.1",
+    "pathos>=0.3.1",
+    "scipy>=1.11.0",
+    "matplotlib>=3.7.2",
+    "numpy>=1.25.0",
+    "pandas>=2.0.3",
+]
+
+[project.optional-dependencies]
+gpu = ["torch>=2.0"]
+
+[project.urls]
+Homepage = "https://github.com/jxx123/simglucose"
+
+[build-system]
+requires = ["setuptools>=64"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools.packages.find]
+include = ["simglucose*"]
+
+[tool.setuptools.package-data]
+simglucose = ["params/*.csv"]
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]

setup.py

@@ -1,25 +1,3 @@
 from setuptools import setup
 
-setup(
-    name="simglucose",
-    version="0.2.11",
-    description="A Type-1 Diabetes Simulator as a Reinforcement Learning Environment in OpenAI gym or rllab (python implementation of UVa/Padova Simulator)",
-    url="https://github.com/jxx123/simglucose",
-    author="Jinyu Xie",
-    author_email="xjygr08@gmail.com",
-    license="MIT",
-    packages=["simglucose"],
-    install_requires=[
-        "gym==0.9.4",
-        "gymnasium~=0.29.1",
-        "pathos>=0.3.1",
-        "scipy>=1.11.0",
-        "matplotlib>=3.7.2",
-        "numpy>=1.25.0",
-        "pandas>=2.0.3",
-    ],
-    include_package_data=True,
-    zip_safe=False,
-    long_description=open("README.md").read(),
-    long_description_content_type="text/markdown",
-)
+setup()

simglucose/__init__.py

@@ -1,6 +1,6 @@
-from gym.envs.registration import register
+from gymnasium.envs.registration import register
 
 register(
     id='simglucose-v0',
-    entry_point='simglucose.envs:T1DSimEnv',
+    entry_point='simglucose.envs:T1DSimGymnaisumEnv',
 )

simglucose/_paths.py

@@ -0,0 +1,17 @@
+"""Centralized path resolution for simglucose data files.
+
+Uses __file__-relative paths so editable installs work correctly.
+"""
+
+import os
+
+_PACKAGE_DIR = os.path.dirname(os.path.abspath(__file__))
+
+
+def resource_path(*parts: str) -> str:
+    """Resolve a path relative to the simglucose package root.
+
+    Usage:
+        resource_path("params", "vpatient_params.csv")
+    """
+    return os.path.join(_PACKAGE_DIR, *parts)

simglucose/actuator/pump.py

@@ -1,10 +1,9 @@
 import pandas as pd
-import pkg_resources
 import logging
 import numpy as np
+from simglucose.utils import _get_resource_path
 
-INSULIN_PUMP_PARA_FILE = pkg_resources.resource_filename(
-    'simglucose', 'params/pump_params.csv')
+INSULIN_PUMP_PARA_FILE = _get_resource_path("simglucose", "params/pump_params.csv")
 logger = logging.getLogger(__name__)
 
 

simglucose/analysis/risk.py

@@ -1,5 +1,6 @@
 import numpy as np
 
+
 def risk_index(BG, horizon):
     # BG is in mg/dL
     BG_to_compute = BG[-horizon:]
@@ -38,3 +39,57 @@ def risk(BG):
     if U >= 0:
         rh = ri
     return (rl, rh, ri)
+
+
+# ---------------------------------------------------------------------------
+# Vectorised batch variants (PyTorch) — used by the GPU batch environment
+# ---------------------------------------------------------------------------
+
+def risk_batch(BG):
+    """
+    Vectorised risk score for a (N,) BG tensor.
+
+    Mirrors the scalar ``risk()`` function but operates on a full batch.
+
+    Returns
+    -------
+    ri : Tensor, shape (N,)  — total risk index per patient
+    rl : Tensor, shape (N,)  — low-BG component
+    rh : Tensor, shape (N,)  — high-BG component
+    """
+    import torch
+    MIN_BG = 20.0
+    MAX_BG = 600.0
+
+    BG_safe = BG.clamp(min=MIN_BG + 1e-8, max=MAX_BG - 1e-8)
+    U = 1.509 * (torch.log(BG_safe) ** 1.084 - 5.381)
+    ri = 10.0 * U ** 2
+
+    # Boundary overrides
+    ri = torch.where(BG <= MIN_BG, torch.full_like(ri, 100.0), ri)
+    ri = torch.where(BG >= MAX_BG, torch.full_like(ri, 100.0), ri)
+
+    rl = torch.where((U <= 0) & (BG > MIN_BG) & (BG < MAX_BG), ri, torch.zeros_like(ri))
+    rl = torch.where(BG <= MIN_BG, torch.full_like(rl, 100.0), rl)
+
+    rh = torch.where((U >= 0) & (BG > MIN_BG) & (BG < MAX_BG), ri, torch.zeros_like(ri))
+    rh = torch.where(BG >= MAX_BG, torch.full_like(rh, 100.0), rh)
+
+    return ri, rl, rh
+
+
+def risk_diff_batch(cgm_hist):
+    """
+    Batch reward = risk[t-1] - risk[t]  (risk reduction is positive).
+
+    Parameters
+    ----------
+    cgm_hist : Tensor shape (N, W), W >= 2 — rolling CGM window, newest last.
+
+    Returns
+    -------
+    reward : Tensor shape (N,)
+    """
+    ri_prev, _, _ = risk_batch(cgm_hist[:, -2])
+    ri_curr, _, _ = risk_batch(cgm_hist[:, -1])
+    return ri_prev - ri_curr

simglucose/controller/basal_bolus_ctrller.py

@@ -2,14 +2,12 @@
 from .base import Action
 import numpy as np
 import pandas as pd
-import pkg_resources
 import logging
+from simglucose.utils import _get_resource_path
 
 logger = logging.getLogger(__name__)
-CONTROL_QUEST = pkg_resources.resource_filename('simglucose',
-                                                'params/Quest.csv')
-PATIENT_PARA_FILE = pkg_resources.resource_filename(
-    'simglucose', 'params/vpatient_params.csv')
+CONTROL_QUEST = _get_resource_path("simglucose", "params/Quest.csv")
+PATIENT_PARA_FILE = _get_resource_path("simglucose", "params/vpatient_params.csv")
 
 
 class BBController(Controller):

simglucose/envs/__init__.py

@@ -1,2 +1,6 @@
 from simglucose.envs.simglucose_gym_env import T1DSimEnv
 from simglucose.envs.simglucose_gym_env import T1DSimGymnaisumEnv
+try:
+    from simglucose.envs.batch_env import T1DSimVectorEnv
+except Exception:
+    pass