Merge pull request #14 from datvodinh10/main

fix bug

Base/Imploding_Kitten/_env.py

@@ -232,7 +232,7 @@ def getAgentState(env, draw_pile, discard_pile):
                     card = np.zeros(19)
                     card[int(getCardType(env[91 + i]))] = 1
                     state[
-                        37 + 19 * i : 56 + 19 * i
+                        38 + 19 * i : 57 + 19 * i
                     ] = card  #  three card if use see the future
         state[100] = np.maximum(env[90], 0)  #  number of card player have to draw
 
@@ -779,9 +779,7 @@ def stepEnv(env, draw_pile, discard_pile, action):
         index_future = np.where(draw_pile != -1)[0]
         if index_future.shape[0] >= 3:
             if act>0:
-                draw_pile_2 = draw_pile.copy()
-                for i in range(3):
-                    draw_pile[index_future[i]] = draw_pile_2[index_future[0:3]][list_change[act][i]]
+                draw_pile[index_future[0:3]] = env[91:94]
         elif index_future.shape[0] == 2:
             if act == 2:
                 draw_pile[index_future] = draw_pile[index_future][np.array([1, 0])]

main.ipynb

@@ -0,0 +1,97 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from setup import make\n",
+    "env = make(\"Imploding_Kitten\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e44feb732034491eba43d57c2e098ff9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(Output(), HBox(children=(Dropdown(layout=Layout(width='20%'), options=('Take an action', 2, 3, …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "env.render(Agent=\"human\", per_data=[0], level=0, max_temp_frame=100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "a = np.array([1,1,1,0,0,1,1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.where(a==1)[0][3]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pytorchenv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}