AIAlgorithmsFinal.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "632dcd6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import networkx as nx\n",
    "import matplotlib.animation as animation\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "26717ff9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def oracle_search(d,start,goal,max_no_goalcutoff):\n",
    "    '''\n",
    "    params d=the adjacency dict,goal=goal node <str>,max_no_goalcutoff=set this as MAX_LIMIT to get all paths to goals or you can restrict the paths accessed\n",
    "    returns oracle cost This will be the boilerplate code for all algos and further tweak done to specific algos  ....\n",
    "    '''\n",
    "    queue=[[0,start]]\n",
    "    res=[]\n",
    "    g=goal\n",
    "    f=0\n",
    "    n_g=max_no_goalcutoff\n",
    "    while (len(queue)!=0):\n",
    "        tmp=[]\n",
    "        curr=queue.pop(0)         # This is the list of paths with index 0 storing cumulative cost\n",
    "        currnode=curr[-1]           # This is the last node in the traversed path\n",
    "        for i in d[currnode].keys():\n",
    "            if i in curr:continue   # prevent accessing ancesstors to child\n",
    "            tmp1=curr+list(i)\n",
    "            tmp1[0]=curr[0]+d[currnode][i]\n",
    "            tmp.append(tmp1)\n",
    "            queue.append(tmp1)\n",
    "            queue.sort(key=lambda k1:k1[0])   # Should have used a priority queue but sort works !\n",
    "            if g==i:f+=1\n",
    "        for i in tmp:res.append(i)\n",
    "        if(f==n_g):break\n",
    "    print(res)\n",
    "    goal_node=[]\n",
    "    for i in res:\n",
    "        if 'G' in i:goal_node.append(i)\n",
    "    print('Oracle Paths:',goal_node)\n",
    "    return goal_node[0][0] # return oracle cost for B&b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a3f6a92",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f95ac95d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['S', 'A'], ['S', 'B'], ['S', 'A', 'B'], ['S', 'A', 'D'], ['S', 'B', 'A'], ['S', 'B', 'C'], ['S', 'B', 'A', 'D'], ['S', 'A', 'B', 'C'], ['S', 'B', 'C', 'E'], ['S', 'A', 'B', 'C', 'E'], ['S', 'A', 'D', 'G'], ['S', 'B', 'A', 'D', 'G']]\n",
      "BMS Paths: [['S', 'A', 'D', 'G'], ['S', 'B', 'A', 'D', 'G']]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[['S', 'A'],\n",
       " ['S', 'B'],\n",
       " ['S', 'A', 'B'],\n",
       " ['S', 'A', 'D'],\n",
       " ['S', 'B', 'A'],\n",
       " ['S', 'B', 'C'],\n",
       " ['S', 'B', 'A', 'D'],\n",
       " ['S', 'A', 'B', 'C'],\n",
       " ['S', 'B', 'C', 'E'],\n",
       " ['S', 'A', 'B', 'C', 'E'],\n",
       " ['S', 'A', 'D', 'G'],\n",
       " ['S', 'B', 'A', 'D', 'G']]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def BMS(d,start,goal,max_no_goalcutoff):\n",
    "    queue=[[start]]\n",
    "    #print(queue[-1][-1])\n",
    "    res=[]\n",
    "    g=goal\n",
    "    f=0\n",
    "    n_g=max_no_goalcutoff\n",
    "    while (len(queue)!=0):\n",
    "        tmp=[]\n",
    "        curr=queue.pop(0)\n",
    "        currnode=curr[-1][-1]\n",
    "        for i in d[currnode].keys():\n",
    "            if i in curr:continue\n",
    "            tmp1=curr+list(i)\n",
    "            #tmp1[0]=curr[0]+d[currnode][i]\n",
    "            tmp.append(tmp1)\n",
    "            queue.append(tmp1)\n",
    "            queue.sort(key=lambda k1:ord(k1[-1]))\n",
    "            if g==i:f+=1\n",
    "        for i in tmp:res.append(i)\n",
    "        if(f==n_g):break\n",
    "    print(res)\n",
    "    goal_node=[]\n",
    "    for i in res:\n",
    "        if 'G' in i:goal_node.append(i)\n",
    "    print('BMS Paths:',goal_node)\n",
    "    return res\n",
    "BMS(d,'S','G',2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "9ae38589",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0, 'S']]\n",
      "[[3, 'S', 'A'], [5, 'S', 'B']]\n",
      "[[6, 'S', 'A', 'D'], [7, 'S', 'A', 'B'], [9, 'S', 'B', 'A'], [9, 'S', 'B', 'C']]\n",
      "[[[3, 'S', 'A'], [5, 'S', 'B']], [[6, 'S', 'A', 'D'], [7, 'S', 'A', 'B'], [9, 'S', 'B', 'A'], [9, 'S', 'B', 'C']], [[11, 'S', 'A', 'D', 'G'], [11, 'S', 'A', 'B', 'C'], [12, 'S', 'B', 'A', 'D'], [15, 'S', 'B', 'C', 'E']]]\n",
      "[11, 'S', 'A', 'D', 'G']\n"
     ]
    }
   ],
   "source": [
    "def beamsearch(d,start,end,bw):\n",
    "    queue=[[0,start]]\n",
    "    fr=[]\n",
    "    goal=end\n",
    "    Beam=bw\n",
    "    gn=[]\n",
    "    f=0\n",
    "    #print(queue)\n",
    "    n_g=0\n",
    "    f=n_g\n",
    "    while(len(queue)!=0):\n",
    "        print(queue)\n",
    "        tmp=queue.copy()\n",
    "        sl=[]\n",
    "        for j in range(len(tmp)):\n",
    "            cp=queue.pop(0)\n",
    "            n=cp[-1]\n",
    "            for i in d[n].keys():    # SAme loops as oracle search \n",
    "                #print(i)\n",
    "                if i in cp:\n",
    "                    continue\n",
    "                el=cp+[i]\n",
    "                el[0]+=d[n][i]\n",
    "                sl.append(el)\n",
    "                #queue.append(el)\n",
    "                sl.sort(key=lambda x: x[0])\n",
    "                if goal==i:\n",
    "                    f=1\n",
    "                    gn=el\n",
    "        queue=sl\n",
    "        if f==1:\n",
    "            fr.append(queue.copy())\n",
    "            break\n",
    "        queue=queue[:Beam+2]\n",
    "        fr.append(queue.copy())\n",
    "    print(fr)\n",
    "    print(gn)\n",
    "\n",
    "beamsearch(d,'S','G',2)   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "488ff050",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0, 'S']]\n",
      "[[3, 'S', 'A'], [5, 'S', 'B']]\n",
      "[[6, 'S', 'A', 'D'], [7, 'S', 'A', 'B'], [9, 'S', 'B', 'A'], [9, 'S', 'B', 'C']]\n",
      "[[[3, 'S', 'A'], [5, 'S', 'B']], [[6, 'S', 'A', 'D'], [7, 'S', 'A', 'B'], [9, 'S', 'B', 'A'], [9, 'S', 'B', 'C']], [[11, 'S', 'A', 'B', 'C'], [11, 'S', 'A', 'D', 'G'], [12, 'S', 'B', 'A', 'D'], [15, 'S', 'B', 'C', 'E']]]\n",
      "[11, 'S', 'A', 'D', 'G']\n"
     ]
    }
   ],
   "source": [
    "def bfs(d,start,end):\n",
    "    queue=[[0,start]]\n",
    "    fr=[]\n",
    "    goal=end\n",
    "    gn=[]\n",
    "    f=0\n",
    "    #print(queue)\n",
    "    n_g=0\n",
    "    f=n_g\n",
    "    while(len(queue)!=0):\n",
    "        print(queue)\n",
    "        tmp=queue.copy()\n",
    "        sl=[]\n",
    "        for j in range(len(tmp)):\n",
    "            cp=queue.pop(0)\n",
    "            n=cp[-1]\n",
    "            for i in d[n].keys():    # SAme loops as oracle search \n",
    "                #print(i)\n",
    "                if i in cp:\n",
    "                    continue\n",
    "                el=cp+[i]\n",
    "                el[0]+=d[n][i]\n",
    "                sl.append(el)\n",
    "                sl=sorted(sl)\n",
    "                #sl.sort(key=lambda x: ord(x[-1]))\n",
    "                if goal==i:\n",
    "                    f=1\n",
    "                    gn=el\n",
    "        queue=sl\n",
    "        if f==1:\n",
    "            fr.append(queue.copy())\n",
    "            break\n",
    "        queue=queue[:]\n",
    "        fr.append(queue.copy())\n",
    "    print(fr)\n",
    "    print(gn)\n",
    "bfs(d,'S','G')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "09766006",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0, 'S', 'A'], [0, 'S', 'A', 'B'], [0, 'S', 'A', 'B', 'C'], [0, 'S', 'A', 'B', 'C', 'E'], [0, 'S', 'A', 'D'], [0, 'S', 'A', 'D', 'G']]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[0, 'S', 'A'],\n",
       " [0, 'S', 'A', 'B'],\n",
       " [0, 'S', 'A', 'B', 'C'],\n",
       " [0, 'S', 'A', 'B', 'C', 'E'],\n",
       " [0, 'S', 'A', 'D'],\n",
       " [0, 'S', 'A', 'D', 'G']]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def dfs(d,start,end):\n",
    "    queue=[[0,start]]\n",
    "    path=[]\n",
    "    while(len(queue)!=0):\n",
    "        cp=queue.pop(0)\n",
    "        cn=cp[-1]\n",
    "        if cn==end:\n",
    "            break\n",
    "        else:\n",
    "            for i in d[cn].keys():\n",
    "                if i not in cp:\n",
    "                    queue.append(cp+list(i))\n",
    "            queue=sorted(queue)\n",
    "            \n",
    "            path.append(queue[0])\n",
    "            \n",
    "    print(path)\n",
    "    return path\n",
    "dfs(d,'S','G')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "47f2ad99",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5, 'S', 'B']\n",
      "[3, 'S', 'A']\n",
      "[4, 'S', 'A', 'B']\n",
      "[3, 'S', 'A', 'D']\n",
      "[5, 'S', 'A', 'D', 'G']\n",
      "[[3, 'S', 'A'], [3, 'S', 'A', 'D'], [5, 'S', 'A', 'D', 'G']]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def hill_climb(d_heur,start,end):\n",
    "    queue=[[0,start]]\n",
    "    path=[]\n",
    "    while(len(queue)!=0):\n",
    "        cp=queue.pop(0)\n",
    "        sl=[]\n",
    "        #print(cp)\n",
    "        cn=cp[-1]\n",
    "        if cn==end:\n",
    "            break\n",
    "        else:\n",
    "            for i in d[cn].keys():\n",
    "                if i in cp :\n",
    "                    continue\n",
    "                el=cp+list(i)\n",
    "                el[0]=d[cn][i]\n",
    "                sl.append(el)\n",
    "            \n",
    "        \n",
    "        sl.sort(key=lambda x:x[0],reverse=True) #Perform Similar to stack by LIFO by reversing the sorted queue\n",
    "        #print(sl)#same thing as DFS but with heuristics\n",
    "        \n",
    "        for k in sl:\n",
    "            print(k)\n",
    "            queue.insert(0,k)\n",
    "        \n",
    "        path.append(queue[0])\n",
    "    print(path)\n",
    "hill_climb(d,'S','G')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d0c4327f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[3, 'S', 'A'], [5, 'S', 'B'], [6, 'S', 'A', 'D'], [7, 'S', 'A', 'B'], [9, 'S', 'B', 'A'], [9, 'S', 'B', 'C'], [11, 'S', 'A', 'B', 'C'], [11, 'S', 'A', 'D', 'G']]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[3, 'S', 'A'],\n",
       " [5, 'S', 'B'],\n",
       " [6, 'S', 'A', 'D'],\n",
       " [7, 'S', 'A', 'B'],\n",
       " [9, 'S', 'B', 'A'],\n",
       " [9, 'S', 'B', 'C'],\n",
       " [11, 'S', 'A', 'B', 'C'],\n",
       " [11, 'S', 'A', 'D', 'G']]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def branch_and_bound(d,start,end,oracle):\n",
    "    queue=[[0,start]]\n",
    "    path=[]\n",
    "    isgoal=0\n",
    "    gn=[]\n",
    "    while(len(queue)!=0):\n",
    "        sl=[]\n",
    "        cp=queue.pop(0)\n",
    "        cn=cp[-1]\n",
    "        if cn==end:\n",
    "                gn=el\n",
    "                break\n",
    "        for i in d[cn].keys():\n",
    "            #print(queue)\n",
    "            if i in cp:\n",
    "                continue\n",
    "            \n",
    "            elif cp[0]+d[cn][i]<=oracle:\n",
    "                el=cp+list(i)\n",
    "                el[0]+=d[cn][i]\n",
    "                sl.append(el)\n",
    "                sl.sort(key=lambda x:x[0])\n",
    "                queue.append(el)\n",
    "                \n",
    "        \n",
    "        sl.sort(key=lambda x:x[0])\n",
    "        for i in sl:path.append(i)\n",
    "        #print(sl)\n",
    "        #if(isgoal==1):break\n",
    "    print(path)\n",
    "    return path\n",
    "branch_and_bound(d,'S','G',11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3df17df3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['A', 'B', 'D', 'C', 'G']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[3, 'S', 'A'],\n",
       " [5, 'S', 'B'],\n",
       " [6, 'S', 'A', 'D'],\n",
       " [9, 'S', 'B', 'C'],\n",
       " [11, 'S', 'A', 'D', 'G']]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def branch_and_bound_EL(d,start,end,oracle):\n",
    "    queue=[[0,start]]\n",
    "    path=[]\n",
    "    isgoal=0\n",
    "    gn=[]\n",
    "    vis=[]\n",
    "    while(len(queue)!=0):\n",
    "        sl=[]\n",
    "        cp=queue.pop(0)\n",
    "        cn=cp[-1]\n",
    "        if cn==end:\n",
    "                    \n",
    "                gn=el\n",
    "                break\n",
    "        for i in d[cn].keys():\n",
    "            #print(queue)\n",
    "            if i in cp:\n",
    "                continue\n",
    "            elif cp[0]+d[cn][i]<=oracle and i not in vis: \n",
    "                vis.append(i)\n",
    "                el=cp+list(i)\n",
    "                el[0]+=d[cn][i]\n",
    "                sl.append(el)\n",
    "                sl.sort(key=lambda x:x[0])\n",
    "                queue.append(el)\n",
    "                \n",
    "        \n",
    "        sl.sort(key=lambda x:x[0])\n",
    "        for i in sl:path.append(i)\n",
    "        #print(sl)\n",
    "        \n",
    "    print(vis)\n",
    "    return path\n",
    "branch_and_bound_EL(d,'S','G',11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c680bb3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[10.379999999999999, 'S', 'A'], [11, 'S', 'B'], [20.38, 'S', 'A', 'B'], [18.38, 'S', 'A', 'D'], [22.38, 'S', 'B', 'A'], [22.58, 'S', 'B', 'C'], [23.38, 'S', 'A', 'D', 'G'], [31.96, 'S', 'A', 'B', 'C'], [30.38, 'S', 'B', 'A', 'D'], [inf, 'S', 'B', 'C', 'E'], [35.379999999999995, 'S', 'B', 'A', 'D', 'G']]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "23.38"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "def oracle_cost_heur(d,start,end,d_heuristic,max_no_goalcutoff):\n",
    "    queue=[[0,start]]\n",
    "    res=[]\n",
    "    g='G'\n",
    "    f=0\n",
    "    n_g=max_no_goalcutoff\n",
    "    while (len(queue)!=0):\n",
    "        tmp=[]\n",
    "        curr=queue.pop(0)         # This is the list of paths with index 0 storing cumulative cost\n",
    "        currnode=curr[-1]           # This is the last node in the traversed path\n",
    "        for i in d[currnode].keys():\n",
    "            if i in curr:continue   # prevent accessing ancesstors to child\n",
    "            tmp1=curr+list(i)\n",
    "            tmp1[0]=curr[0]+d[currnode][i]+d_heuristic[currnode][i]\n",
    "            tmp.append(tmp1)\n",
    "            queue.append(tmp1)\n",
    "            queue.sort(key=lambda k1:k1[0])   # Should have used a priority queue but sort works !\n",
    "            if g==i:f+=1\n",
    "        for i in tmp:res.append(i)\n",
    "        if(f==n_g):break\n",
    "    print(res)\n",
    "    goal_node=[]\n",
    "    for i in res:\n",
    "        if end in i:goal_node.append(i)\n",
    "    return goal_node[0][0]\n",
    "    print('Oracle Paths:',goal_node)\n",
    "oracle_cost_heur(d,'S','G',d_h,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "12dd940e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[10.379999999999999, 'S', 'A'], [11, 'S', 'B'], [20.38, 'S', 'A', 'B'], [18.38, 'S', 'A', 'D'], [22.38, 'S', 'B', 'A'], [22.58, 'S', 'B', 'C'], [23.38, 'S', 'A', 'D', 'G'], [31.96, 'S', 'A', 'B', 'C'], [30.38, 'S', 'B', 'A', 'D'], [inf, 'S', 'B', 'C', 'E'], [35.379999999999995, 'S', 'B', 'A', 'D', 'G']]\n",
      "['A', 'B', 'D', 'C', 'G']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[10.379999999999999, 'S', 'A'],\n",
       " [11, 'S', 'B'],\n",
       " [18.38, 'S', 'A', 'D'],\n",
       " [22.58, 'S', 'B', 'C'],\n",
       " [23.38, 'S', 'A', 'D', 'G']]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def A_star_search(d,start,end,d_heur,oracle_cost_heur):\n",
    "    queue=[[0,start]]\n",
    "    path=[]\n",
    "    isgoal=0\n",
    "    gn=[]\n",
    "    vis=[]\n",
    "    while(len(queue)!=0):\n",
    "        sl=[]\n",
    "        cp=queue.pop(0)\n",
    "        cn=cp[-1]\n",
    "        for i in d[cn].keys():\n",
    "            #print(queue)\n",
    "            if i in cp:\n",
    "                continue\n",
    "            elif cp[0]+d[cn][i]<=oracle_cost_heur and i not in vis : \n",
    "                vis.append(i)\n",
    "                el=cp+list(i)\n",
    "                el[0]+=d[cn][i]+d_heur[cn][i]\n",
    "                sl.append(el)\n",
    "                sl.sort(key=lambda x:x[0])\n",
    "                queue.append(el)\n",
    "                if cn==end:\n",
    "                    isgoal=1\n",
    "                    gn=el\n",
    "                    break\n",
    "        \n",
    "        sl.sort(key=lambda x:x[0])\n",
    "        for i in sl:path.append(i)\n",
    "        #print(sl)\n",
    "        if(isgoal==1):break\n",
    "    print(vis)\n",
    "    return path\n",
    "A_star_search(d,'S','G',d_h,oracle_cost_heur(d,'S','G',d_h,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d84994f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def bestfirst(d,s,e):\n",
    "    queue=[[0,s]]\n",
    "    res=[]\n",
    "    f=0\n",
    "    while(len(queue)!=0):\n",
    "        u=queue.pop(0)\n",
    "        if(u==e):\n",
    "            break\n",
    "        else:\n",
    "            cn=u[-1]\n",
    "            for i in d[cn].keys():\n",
    "                \n",
    "                if i in u:\n",
    "                    continue\n",
    "                if i=='G':\n",
    "                    f=1\n",
    "                else:\n",
    "                    t1=u+[i]\n",
    "                    t1[0]+=d[cn][i]\n",
    "                    queue.append(t1)\n",
    "            \n",
    "            queue.sort(key=lambda k:k[0]) # priority q must be used but nevertheless the same time complexity though\n",
    "            \n",
    "        res+=[u]\n",
    "        if(f==1):\n",
    "                break\n",
    "    return res\n",
    "bestfirst(d,'S','G')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f8868016",
   "metadata": {},
   "outputs": [],
   "source": [
    "def form_graph(d,FR): #FR is a function pertaining to defined search algos.\n",
    "    global l\n",
    "    g=nx.Graph()\n",
    "    g.add_nodes_from(d)\n",
    "    for i in d.keys():\n",
    "        for j in d[i].keys():\n",
    "            g.add_edge(i,j)\n",
    "\n",
    "    l=[]\n",
    "    #FR=BMS(d,'S','G',2)\n",
    "    #FR=dfs(d)\n",
    "    #FR=branch_and_bound(d,11)\n",
    "    #FR=A_star_search(d,'S','G',d_h,oracle_cost_heur(d,'S','G',d_h,2))\n",
    "    for i in FR:\n",
    "        #print(i)\n",
    "        st=i[1:]\n",
    "        tmp=[]\n",
    "        for c in range(len(i[1:])):\n",
    "\n",
    "            tmp.append(st[c:c+2])\n",
    "        tmp.pop(-1)\n",
    "        l+=[tmp]\n",
    "    l\n",
    "    \n",
    "\n",
    "    print((l))\n",
    "    return g\n",
    "\n",
    "def ret_edge(edge):\n",
    "    \n",
    "    c=0\n",
    "    \n",
    "    #print(edge)\n",
    "    for i in g.edges:\n",
    "        #print(i)\n",
    "        if(edge==list(i) or edge[::-1]==list(i)):\n",
    "            break\n",
    "        c+=1\n",
    "    #edge_col[c]=\"red\"\n",
    "    return c\n",
    "\n",
    "def animate(i):\n",
    "    edge_col=[]\n",
    "    for j in range(len(g.edges)):\n",
    "        edge_col+=[\"green\"]\n",
    "    tmp=edge_col.copy()\n",
    "    #for i in range(len(l)):\n",
    "    for j in (l[i]):\n",
    "            tmp[ret_edge(j)]=\"blue\"\n",
    "    print(tmp)\n",
    "        #node=nx.draw_shell(g, list(g.nodes),edge_color=tmp, with_labels=True, font_weight='bold')\n",
    "    nx.draw_networkx_labels(g,pos)\n",
    "    node=nx.draw_networkx_nodes(g, pos,nodelist=list(g.nodes), node_size=250,node_color='lightblue')\n",
    "    edges=nx.draw_networkx_edges(g,pos,edgelist=list(g.edges),edge_color=tmp)\n",
    "    return node,edges\n",
    "def Viz(g):\n",
    "    global pos\n",
    "    pos = nx.shell_layout(g)\n",
    "    g=nx.Graph()\n",
    "    g.add_nodes_from(d) \n",
    "    for i in d.keys():\n",
    "        for j in d[i].keys():\n",
    "            g.add_edge(i,j)\n",
    "    print(g.edges)\n",
    "\n",
    "    fig=plt.gcf()\n",
    "    #nx.draw_shell(g, list(g.nodes), with_labels=True, font_weight='bold')\n",
    "\n",
    "    ani = animation.FuncAnimation(fig, animate, frames=len(l), interval=1000, repeat=True,blit=False)\n",
    "    #ani.save(\"D://anim.mp4\")\n",
    "    return HTML(ani.to_html5_video(30))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "afda1ef9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[10.379999999999999, 'S', 'A'], [11, 'S', 'B'], [20.38, 'S', 'A', 'B'], [18.38, 'S', 'A', 'D'], [22.38, 'S', 'B', 'A'], [22.58, 'S', 'B', 'C'], [23.38, 'S', 'A', 'D', 'G'], [31.96, 'S', 'A', 'B', 'C'], [30.38, 'S', 'B', 'A', 'D'], [inf, 'S', 'B', 'C', 'E'], [35.379999999999995, 'S', 'B', 'A', 'D', 'G']]\n",
      "['A', 'B', 'D', 'C', 'G']\n",
      "[[['S', 'A']], [['S', 'B']], [['S', 'A'], ['A', 'D']], [['S', 'B'], ['B', 'C']], [['S', 'A'], ['A', 'D'], ['D', 'G']]]\n",
      "[('S', 'A'), ('S', 'B'), ('A', 'B'), ('A', 'D'), ('B', 'C'), ('C', 'E'), ('D', 'G')]\n",
      "['blue', 'green', 'green', 'green', 'green', 'green', 'green']\n",
      "['blue', 'green', 'green', 'green', 'green', 'green', 'green']\n",
      "['green', 'blue', 'green', 'green', 'green', 'green', 'green']\n",
      "['blue', 'green', 'green', 'blue', 'green', 'green', 'green']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_33672\\3970117180.py:54: DeprecationWarning: `alltrue` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `all` instead.\n",
      "  edges=nx.draw_networkx_edges(g,pos,edgelist=list(g.edges),edge_color=tmp)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['green', 'blue', 'green', 'green', 'blue', 'green', 'green']\n",
      "['blue', 'green', 'green', 'blue', 'green', 'green', 'blue']\n"
     ]
    },
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       "  Your browser does not support the video tag.\n",
       "</video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# User Input Space \n",
    "# I am not taking user input from console ... feels more interactive to edit the dictionary d and d_h by the user at once \n",
    "'''\n",
    "Template For User\n",
    "\n",
    "d -> Adjacency Graph with normal weights\n",
    "d_h -> Adjacency Graph with Heuristics\n",
    "FR -> Function To Visualise \n",
    "Call form_graph()  -> Init Setup\n",
    "Call Viz(form_graph())  -> or use alias ret val //\n",
    "\n",
    "\n",
    "'''\n",
    "d={\n",
    "    'S':{'A':3,'B':5},\n",
    "    'A':{'S':3,'B':4,'D':3},\n",
    "    'B':{'S':5,'A':4,'C':4},\n",
    "    'C':{'B':4,'E':6},\n",
    "    'E':{'C':6},\n",
    "    'D':{'A':3,'G':5},\n",
    "    'G':{'D':5}\n",
    "}\n",
    "d_h={\n",
    "    'S':{'A':7.38,'B':6},\n",
    "    'A':{'S':np.inf,'B':6,'D':5},\n",
    "    'B':{'S':np.inf,'A':7.38,'C':7.58},\n",
    "    'C':{'B':6,'E':np.inf},\n",
    "    'E':{'C':7.58},\n",
    "    'D':{'A':7.38,'G':0},\n",
    "    'G':{'D':5}\n",
    "}\n",
    "\n",
    "FR=A_star_search(d,'S','G',d_h,oracle_cost_heur(d,'S','G',d_h,2))\n",
    "g=form_graph(d,FR)\n",
    "Viz(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f9251433",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea50b421",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb4748ef",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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