Merge pull request #7 from boettiger-lab/Niki

Niki

hyperpars/ppo-caribou.yml

@@ -35,13 +35,18 @@ algo_config:
 
 # env
 env_id: "CaribouScipy"
-config: {}
+config: {"r_b":.25 } #this is what is passed into the creation of the environment, could pass diff param values here to change the defaults (instead of messing with the params defined in caribou_ode.py)
 n_envs: 12
 
-# io
-repo: "cboettig/rl-ecology"
-save_path: "../saved_agents"
-
+tensorboard: "/home/rstudio/logs"
+#total_timesteps: 50000
+total_timesteps: 5000000
+use_sde: True
+repo: "boettiger-lab/rl4eco"
+save_path: "./saved_agents"
+id: "3"
+#rppo - ppo that has memory (should be better than PPO but hard to train lol) 
+#td3 - giving some weird errors
+#tqc is actually better if we can give it enough time to run
 # misc
-# id: ""
-additional_imports: ["torch"]
+additional_imports: ["torch"]

notebooks/compare-solutions.ipynb

@@ -2,10 +2,22 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "id": "cff325f3-71d3-469c-aec5-e340219ce0e4",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'rl4eco'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 8\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mplotnine\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m geom_point, ggplot, aes, geom_density, geom_bar\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrl4eco\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m load_hf_agent\n\u001b[1;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrl4caribou\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Caribou\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'rl4eco'"
+     ]
+    }
+   ],
    "source": [
     "import ibis\n",
     "from ibis import _\n",

src/rl4caribou/envs/caribou_ode.py

@@ -49,35 +49,35 @@ def ode_func(y, t, effort, p):
 ##
 ## Param vals taken from https://doi.org/10.1016/j.ecolmodel.2019.108891
 ##
-am = {"current": 15.32, "full_rest": 11.00}
-ab = {"current": 51.45, "full_rest": 26.39}
+#am = {"current": 15.32, "full_rest": 11.00}
+#ab = {"current": 51.45, "full_rest": 26.39}
 
-parameters = {
-    "r_m": np.float32(0.39),
-    "r_b": np.float32(0.30),
+#parameters = {
+#    "r_m": np.float32(0.39),
+#    "r_b": np.float32(0.30),
     #
-    "alpha_mm": np.float32(1),
-    "alpha_bb": np.float32(1),
-    "alpha_bm": np.float32(1),
-    "alpha_mb": np.float32(1),
+#    "alpha_mm": np.float32(1),
+#    "alpha_bb": np.float32(1),
+#    "alpha_bm": np.float32(1),
+#    "alpha_mb": np.float32(1),
     #
-    "a_M": am["current"],
-    "a_B": ab["current"],
+ #   "a_M": am["current"],
+#    "a_B": ab["current"],
     #
-    "K_m": np.float32(1.1),
-    "K_b": np.float32(0.40),
+#    "K_m": np.float32(1.1),
+#    "K_b": np.float32(0.40),
     #
-    "h_M": np.float32(0.112),
-    "h_B": np.float32(0.112),
+#    "h_M": np.float32(0.112),
+#    "h_B": np.float32(0.112),
     #
-    "x": np.float32(2),
-    "u": np.float32(1),
-    "d": np.float32(1),
+#    "x": np.float32(2),
+#    "u": np.float32(1),
+#    "d": np.float32(1),
     #
-    "sigma_M": np.float32(0.05),
-    "sigma_B": np.float32(0.05),
-    "sigma_W": np.float32(0.05),
-}
+#    "sigma_M": np.float32(0.05),
+#    "sigma_B": np.float32(0.05),
+#    "sigma_W": np.float32(0.05),
+#}
 #
 # computed using scipy's fsolve (coordinates where d Pops / dt = 0)
 singularities = [