dfs_bfs_bestfs_idds.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "**Ghazaleh Hamzeh**\n",
        "# Machine Learning - HW1\n",
        "\n",
        "*inja matrix ro dobare be sorate foshorde barnagrdoonam, hamoon 0,1 be kar bordam*"
      ],
      "metadata": {
        "id": "ITR920lqH5_2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Part 0 : Uploading the matrix "
      ],
      "metadata": {
        "id": "10zwEV9wFWKE"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6l8bqgRvA3kg",
        "outputId": "38bec58d-cb6f-4129-f33f-7166da721583"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] \n",
            " Number of nodes in the graph is 100\n"
          ]
        }
      ],
      "source": [
        "with open('NodeConnections.txt', 'r') as f:\n",
        "    l = [[int(num) for num in line.split(',')] for line in f]\n",
        "\n",
        "numOfNodes = len(l)\n",
        "print(l,'\\n',f'Number of nodes in the graph is {numOfNodes}')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####Part 0.2 : Transfering evrey node from binay to numeric format. "
      ],
      "metadata": {
        "id": "6WcnSh6ylpgp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "mat = []\n",
        "for i in range(0,100):\n",
        "  mat.append([])\n",
        "  for j in range(0,100):\n",
        "      if l[i][j] == 1:\n",
        "        mat[i].append(j)\n",
        "print(mat)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bo6ZM9hblUL5",
        "outputId": "7f7cdf1d-cda8-4a70-dc10-884a450846c4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[4, 21, 60, 68, 93], [24, 27, 60, 62, 74, 86, 94], [21, 52, 87, 88, 90], [4, 8, 39, 92, 96], [29, 41, 63, 73, 84, 90, 99], [32, 33, 43, 48, 68, 74, 86], [1, 9, 25, 29, 47, 56, 61, 64], [4, 16, 41, 97], [6, 9, 49, 50], [35, 48, 71, 81], [2, 14, 21, 45, 62, 73, 82, 84, 98], [3, 7, 16, 25], [0, 17, 23], [0, 24, 41, 64], [1, 3, 33], [5, 9, 10, 51, 56, 77, 79, 84], [6, 22, 50, 55, 66, 75, 85, 88], [73, 77], [4, 47, 87, 89], [3, 14, 23, 42, 82], [5, 6, 13, 27, 61, 94, 98], [32, 36, 46, 85, 93], [24, 29, 38, 63, 86, 98], [10, 39, 77], [13, 49, 70, 74, 92], [10, 18, 22, 24, 32, 44, 48, 56, 69], [9, 13, 35, 60], [1, 37, 50, 51, 57, 92, 96], [20, 23], [10, 53, 61, 64, 90, 94], [4, 16, 26, 45, 55, 63, 70, 78, 99], [22, 36, 47, 51, 77], [43, 48, 55, 68, 71, 80, 83, 97], [5, 10, 12, 50, 59, 68, 89], [10, 23, 86, 90, 93], [5, 6, 8, 14, 45, 49], [4, 19, 42], [61], [3, 16, 37, 52, 57, 75], [26, 62, 79], [9, 27, 28, 31, 54, 57, 71], [62, 97], [0, 20, 33, 68, 92, 94], [18, 46, 73, 86], [12, 34, 49, 82], [30, 57, 66, 77, 78, 92, 96], [33, 39, 62, 65, 73, 78], [35, 40, 53, 64, 83], [84, 85], [0, 7, 48, 55, 58, 68, 97], [93], [86], [14, 20, 48, 60, 72, 77], [8], [32, 42, 95, 99], [37, 84, 87], [59, 89], [28, 31, 37, 50], [2, 76, 98], [16, 34, 38, 58], [0, 10, 25, 35, 44, 51, 76, 95], [38, 47, 67], [19, 36, 61, 76], [15, 24, 53, 69, 81, 83, 97], [24, 26, 40, 67, 80], [56, 72, 77, 95], [7, 49, 57, 71, 74], [24, 38, 41, 57, 82, 90], [4, 11, 22, 31, 36, 37, 94], [74, 79, 84, 95], [7, 33, 96], [16, 22, 24, 66, 80], [7, 32, 58, 75, 79, 98], [25, 30], [], [7, 14, 16, 18, 20, 21, 29, 38, 46, 63, 70], [6, 22, 37, 69, 74], [44, 46, 60, 63, 67, 75, 83], [96], [36, 52, 55, 65], [15, 22, 65, 69], [23, 36, 96], [6, 7, 51, 99], [0, 24, 30, 46, 65, 71, 99], [24, 31, 62, 79], [47, 64, 70, 91], [5, 31, 43, 48, 75], [56, 62, 77], [10, 26, 29, 43, 70], [13, 20, 22, 32, 33, 40, 59, 93], [0, 16, 27, 40, 88, 91], [17, 23, 31, 44], [11, 30, 37, 51, 55, 58, 65, 67, 73, 75], [6, 44, 56, 63], [35, 41, 50, 75], [19, 29, 39, 89], [11, 19, 21, 29, 41, 62, 78], [63, 83], [40, 77, 81], [3, 12, 39, 69]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Search algorithms with visited list**\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "9XAeV4aeH5zs"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 1 : Breadth First Search Algorithm Function\n",
        "\n",
        "*   input: Matrix list, start, goal\n",
        "*   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "23k0cAwkEvzC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def breadthFirstSearch(graph,s,g):\n",
        "  queue = [[s]]\n",
        "  path = []\n",
        "  visited = [s]\n",
        "  flag = False\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while queue:\n",
        "    if space_complex_calc < len(queue):\n",
        "      space_complex_calc = len(queue)\n",
        "    sN = queue.pop(0)\n",
        "    if sN[0] == g:\n",
        "      path = sN\n",
        "      queue = []\n",
        "      flag = True\n",
        "    else:\n",
        "      sN1 = sN.copy()\n",
        "      for i in sN:\n",
        "          for j in graph[i]:\n",
        "            if j not in visited:\n",
        "              visited.append(j)\n",
        "              sN1.insert(0,j)\n",
        "              queue.append(sN1.copy())\n",
        "              tIME_calc += 1\n",
        "              sN1.pop(0)\n",
        "      sN1 = []\n",
        "\n",
        "  spc = max(len(visited),space_complex_calc)       \n",
        "  return tIME_calc, spc, path, flag"
      ],
      "metadata": {
        "id": "JW7jibnBH5eF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 2 : Depth First Search Algorithm Function\n",
        "\n",
        "*   input: Matrix list, start, goal\n",
        "*   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "p9G9G6SHD8Ej"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def depthFirstSearch(graph,s,g):\n",
        "  queue = [[s]]\n",
        "  path = []\n",
        "  visited = [s]\n",
        "  flag = False\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while queue:\n",
        "    if space_complex_calc < len(queue):\n",
        "      space_complex_calc = len(queue)\n",
        "    sN = queue.pop(0)\n",
        "    if sN[0] == g:\n",
        "      path = sN\n",
        "      queue = []\n",
        "      flag = True\n",
        "    else:\n",
        "      sN1 = sN.copy()\n",
        "      for j in graph[sN1[0]]:\n",
        "        if j not in visited:\n",
        "          visited.append(j)\n",
        "          sN1.insert(0,j)\n",
        "          queue.insert(0,sN1.copy())\n",
        "          if queue[0][0] == g:\n",
        "            path = sN1\n",
        "            queue = []\n",
        "            flag = True\n",
        "            break\n",
        "          tIME_calc += 1\n",
        "          sN1.pop(0)\n",
        "\n",
        "  spc = max(len(visited),space_complex_calc)\n",
        "  return tIME_calc, spc, path, flag\n"
      ],
      "metadata": {
        "id": "JkThCfXCEHqD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Best First Search Algorithm\n",
        "####Part 3.0 : Uploading the Heuristic.txt as a list of costs for every node\n",
        "\n",
        "Asigning every cost to the first of every node list"
      ],
      "metadata": {
        "id": "6yvhjPrqSuAw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "with open('Heuristic.txt', 'r') as f:\n",
        "    data = f.read()\n",
        "cost = data.replace('\\n','').split(',')\n",
        "\n",
        "print(f'Cost is {cost}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ORfVWRUfSn3_",
        "outputId": "475c3288-6aa6-4415-d97d-8a9df1f85f6c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cost is ['3', '2', '3', '2', '3', '3', '3', '3', '4', '3', '2', '3', '4', '3', '3', '3', '4', '4', '3', '0', '3', '2', '4', '3', '3', '3', '3', '2', '4', '3', '3', '2', '3', '3', '3', '3', '1', '5', '3', '2', '3', '2', '3', '3', '4', '2', '2', '4', '3', '3', '5', '4', '3', '5', '2', '3', '5', '3', '4', '4', '2', '4', '1', '3', '4', '2', '4', '3', '2', '2', '2', '4', '3', '4', '100', '3', '3', '3', '2', '2', '3', '2', '4', '3', '2', '3', '3', '2', '3', '4', '3', '3', '3', '4', '3', '1', '1', '4', '3', '3']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 3 : Best First Search Algorithm Function\n",
        "\n",
        "*   input: Matrix list, cost, start, goal\n",
        "*   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "6CVg2xbpQVKa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def bestFirstSearch(graph, cost, s, g):\n",
        "\n",
        "  pqueue = [[int(cost[s]),s]] # Priority Queue\n",
        "  path = []\n",
        "  visited = [s]\n",
        "  flag = False\n",
        "  tmp = -1\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while pqueue:\n",
        "    if space_complex_calc < len(pqueue):\n",
        "      space_complex_calc = len(pqueue)\n",
        "    sN = pqueue.pop(0)\n",
        "    if sN[1] == g:\n",
        "      path = sN[1:]\n",
        "      pqueue = []\n",
        "      flag = True\n",
        "    else:\n",
        "      sN.pop(0) #cost ro bardashtam\n",
        "      sN1 = sN.copy()\n",
        "      for j in sN:\n",
        "          for i in graph[j]:\n",
        "            if i not in visited:\n",
        "              visited.append(i)\n",
        "              sN1.insert(0,i)\n",
        "              cost_i_value = int(cost[i])\n",
        "              sN1.insert(0, cost_i_value)\n",
        "              f = True\n",
        "              for k in range(len(pqueue)):\n",
        "                if cost_i_value <= int(pqueue[k][0]):\n",
        "                  pqueue.insert(k, sN1.copy())\n",
        "                  tIME_calc += 1\n",
        "                  f = False\n",
        "                  break\n",
        "              if f:\n",
        "                pqueue.append(sN1.copy())\n",
        "                tIME_calc += 1\n",
        "              sN1.pop(0)\n",
        "              sN1.pop(0)\n",
        "  \n",
        "  spc = max(len(visited),space_complex_calc)\n",
        "  return tIME_calc, spc, path, flag"
      ],
      "metadata": {
        "id": "bdPcA-tXSSSU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 4 : Progressive Deepening (Iterative Deepening) Search Algorithm Function\n",
        "\n",
        "\n",
        "1.   depthFirstSearch_ddfs function:\n",
        "  *   input: Matrix list, start, goal, depth\n",
        "  *   output: time complexity, space complexity, path, flag\n",
        "\n",
        "2.   iterativeDDFS function:\n",
        "  *   input: Matrix list, start, goal, max depth\n",
        "  *   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "k3yhL8rLq-FB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def depthFirstSearch_ddfs(graph,s,g,depth):\n",
        "  queue = [[s]]\n",
        "  path = []\n",
        "  visited = [s]\n",
        "  flag = False\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while queue:\n",
        "    if space_complex_calc < len(queue):\n",
        "      space_complex_calc = len(queue)\n",
        "    \n",
        "    sN = queue.pop(0)\n",
        "    if sN[0] == g:\n",
        "      path = sN\n",
        "      queue = []\n",
        "      flag = True\n",
        "\n",
        "    if depth <= 0:\n",
        "      flag = False\n",
        "      spc = max(len(visited),space_complex_calc)\n",
        "      return tIME_calc, spc, path, flag\n",
        "\n",
        "    else:\n",
        "      depth -= 1\n",
        "      sN1 = sN.copy()\n",
        "      if sN1[0] < len(graph):\n",
        "        for j in graph[sN1[0]]:\n",
        "          if j not in visited:\n",
        "            visited.append(j)\n",
        "            sN1.insert(0,j)\n",
        "            queue.insert(0,sN1.copy())\n",
        "            if queue[0][0] == g:\n",
        "              path = sN1\n",
        "              queue = []\n",
        "              flag = True\n",
        "              break\n",
        "            tIME_calc += 1\n",
        "            sN1.pop(0)\n",
        "        sN1 = []\n",
        "\n",
        "  spc = max(len(visited),space_complex_calc)\n",
        "  return tIME_calc, spc, path, flag"
      ],
      "metadata": {
        "id": "lyzP3o7soaW6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def iterativeDDFS(graph, source, goal, maxDepth):\n",
        "  if maxDepth > len(graph)-1:\n",
        "    print(\"Choose another depth\")\n",
        "    return '', False\n",
        "  for i in range(maxDepth):\n",
        "    tIME_calc = 0\n",
        "    spc = 0\n",
        "    tIME_calc1, spc1, path, flag = depthFirstSearch_ddfs(graph[:i+1], source, goal,i+1)\n",
        "    tIME_calc += tIME_calc1\n",
        "    spc += spc1\n",
        "    if flag:\n",
        "      return tIME_calc, spc, path, True\n",
        "  return tIME_calc, spc, path, False"
      ],
      "metadata": {
        "id": "R4MOwdmgmGG7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Search algorithms without visited list**\n"
      ],
      "metadata": {
        "id": "luX1fN3TrV9h"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 5.1 : Breadth First Search Algorithm Function\n",
        "**without visited list**\n",
        "\n",
        "*   input: Matrix list, start, goal\n",
        "*   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "hB98PX8CE9fY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def wo_breadthFirstSearch(graph,s,g):\n",
        "  queue = [[s]]\n",
        "  path = []\n",
        "  flag = False\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while queue:\n",
        "    if space_complex_calc < len(queue):\n",
        "      space_complex_calc = len(queue)\n",
        "    sN = queue.pop(0)\n",
        "    if sN[0] == g:\n",
        "      path = sN\n",
        "      queue = []\n",
        "      flag = True\n",
        "    else:\n",
        "      sN1 = sN.copy()\n",
        "      for i in sN:\n",
        "          for j in graph[i]:\n",
        "            sN1.insert(0,j)\n",
        "            if sN1 not in queue:\n",
        "              queue.append(sN1.copy())\n",
        "              tIME_calc += 1\n",
        "              sN1.pop(0)\n",
        "      sN1 = []\n",
        "  \n",
        "  return tIME_calc, space_complex_calc, path, flag"
      ],
      "metadata": {
        "id": "pPVAQX96sKf2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 5.2 : Depth First Search Algorithm Function\n",
        "**without visited list**\n",
        "*   input: Matrix list, start, goal\n",
        "*   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "bFqaqI96sND_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def wo_depthFirstSearch(graph,s,g):\n",
        "  queue = [[s]]\n",
        "  path = []\n",
        "  flag = False\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while queue:\n",
        "    if space_complex_calc < len(queue):\n",
        "      space_complex_calc = len(queue)\n",
        "    sN = queue.pop(0)\n",
        "    if sN[0] == g:\n",
        "      path = sN\n",
        "      queue = []\n",
        "      flag = True\n",
        "    else:\n",
        "      sN1 = sN.copy()\n",
        "      for j in graph[sN1[0]]:\n",
        "        sN1.insert(0,j)\n",
        "        queue.insert(0,sN1.copy())\n",
        "        if queue[0][0] == g:\n",
        "          path = sN1\n",
        "          queue = []\n",
        "          flag = True\n",
        "          break\n",
        "        tIME_calc += 1\n",
        "        sN1.pop(0)\n",
        "\n",
        "  return tIME_calc, space_complex_calc, path, flag"
      ],
      "metadata": {
        "id": "mMj3iSc-onOn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 5.3 : Best First Search Algorithm Function\n",
        "**without visited list**\n",
        "*   input: Matrix list, cost, start, goal\n",
        "*   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "ak8CjYrWsUj_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def wo_bestFirstSearch(graph,cost,s,g):\n",
        "\n",
        "  pqueue = [[int(cost[s]),s]] # Priority Queue\n",
        "  path = []\n",
        "  flag = False\n",
        "  tmp = -1\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while pqueue:\n",
        "    if space_complex_calc < len(pqueue):\n",
        "      space_complex_calc = len(pqueue)\n",
        "    sN = pqueue.pop(0)\n",
        "    if sN[1] == g:\n",
        "      path = sN[1:]\n",
        "      pqueue = []\n",
        "      flag = True\n",
        "    else:\n",
        "      sN.pop(0) #cost ro bardashtam\n",
        "      sN1 = sN.copy()\n",
        "      for j in sN:\n",
        "        for i in graph[j]:\n",
        "          sN1.insert(0,i)\n",
        "          cost_i_value = int(cost[i])\n",
        "          sN1.insert(0, cost_i_value)\n",
        "          f = True\n",
        "          for k in range(len(pqueue)):\n",
        "            if cost_i_value <= int(pqueue[k][0]):\n",
        "              pqueue.insert(k, sN1.copy())\n",
        "              tIME_calc += 1\n",
        "              f = False\n",
        "              break\n",
        "          if f:\n",
        "            pqueue.append(sN1.copy())\n",
        "            tIME_calc += 1\n",
        "          sN1.pop(0)\n",
        "          sN1.pop(0)\n",
        "\n",
        "  return tIME_calc, space_complex_calc, path, flag"
      ],
      "metadata": {
        "id": "r4kH-H2-sjEA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Part 5.4 : Progressive Deepening (Iterative Deepening) Search Algorithm Function\n",
        "\n",
        "**without visited list**\n",
        "\n",
        "1.   wo_depthFirstSearch_ddfs function:\n",
        "  *   input: Matrix list, start, goal, depth\n",
        "  *   output: time complexity, space complexity, path, flag\n",
        "\n",
        "2.   wo_iterativeDDFS function:\n",
        "  *   input: Matrix list, start, goal, max depth\n",
        "  *   output: time complexity, space complexity, path, flag"
      ],
      "metadata": {
        "id": "fjSG460n6KLD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def wo_depthFirstSearch_ddfs(graph,s,g,depth):\n",
        "  queue = [[s]]\n",
        "  path = []\n",
        "  flag = False\n",
        "  tIME_calc = 0\n",
        "  space_complex_calc = 0\n",
        "\n",
        "  while queue:\n",
        "    if space_complex_calc < len(queue):\n",
        "      space_complex_calc = len(queue)\n",
        "    \n",
        "    sN = queue.pop(0)\n",
        "    if sN[0] == g:\n",
        "      path = sN\n",
        "      queue = []\n",
        "      flag = True\n",
        "\n",
        "    if depth <= 0:\n",
        "      flag = False\n",
        "      return tIME_calc, space_complex_calc, path, flag\n",
        "\n",
        "    else:\n",
        "      depth -= 1\n",
        "      sN1 = sN.copy()\n",
        "      if sN1[0] < len(graph):\n",
        "        for j in graph[sN1[0]]:\n",
        "            sN1.insert(0,j)\n",
        "            queue.insert(0,sN1.copy())\n",
        "            if queue[0][0] == g:\n",
        "              path = sN1\n",
        "              queue = []\n",
        "              flag = True\n",
        "              break\n",
        "            tIME_calc += 1\n",
        "            sN1.pop(0)\n",
        "        sN1 = []\n",
        "\n",
        "  return tIME_calc, space_complex_calc, path, flag"
      ],
      "metadata": {
        "id": "lkyRaIAq6nC0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def wo_iterativeDDFS(graph, source, goal, maxDepth):\n",
        "  if maxDepth > len(graph)-1:\n",
        "    print(\"Choose another depth\")\n",
        "    return '', False\n",
        "  for i in range(maxDepth):\n",
        "    tIME_calc = 0\n",
        "    spc = 0\n",
        "    tIME_calc1, spc1, path, flag = wo_depthFirstSearch_ddfs(graph[:i+1], source, goal,i+1)\n",
        "    tIME_calc += tIME_calc1\n",
        "    spc += spc1\n",
        "    if flag:\n",
        "      return tIME_calc, spc, path, True\n",
        "  return tIME_calc, spc, path, False"
      ],
      "metadata": {
        "id": "KEO89QNr6846"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##HOW TO RUN THIS CODE\n",
        "\n",
        "**Start from node 0 Goal is node 19**\n",
        "Print path format is [goal , <-- , source]\n",
        "\n",
        "*   BFS path for source = 0 and goal = 19 is\n",
        "[19, 36, 21, 0]\n",
        "\n",
        "*   DFS path for source = 0 and goal = 19 is\n",
        "[19, 95, 69, 99, 83, 97, 63, 93, 0]\n",
        "\n",
        "*   Best_FS path for source = 0 and goal = 19 is\n",
        "[19, 36, 68, 0]\n",
        "\n",
        "\n",
        "> *for best first search we assume between the nodes with same cost value, the one that is newer goes before the other node.(similar to bfs)*\n",
        "\n",
        "\n",
        "\n",
        "*   DDFS path for source = 0 and goal = 19 is\n",
        "[19, 36, 21, 0]"
      ],
      "metadata": {
        "id": "e1GdSQWlQ7B_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def print_func(name, tIME_calc, space_complex_calc, path, flag):\n",
        "  print(name,'search\\n')\n",
        "  if flag:\n",
        "    print(path,'\\n')\n",
        "  else:\n",
        "    print(name,': There is no path\\n')\n",
        "  print('Time complexity: ', tIME_calc)\n",
        "  print('space_complex_calc: ', space_complex_calc)\n",
        "  print('___________________________________________________________________\\n')\n",
        "  return"
      ],
      "metadata": {
        "id": "CaVW_oHYjSHo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "source = 0\n",
        "goal = 19\n",
        "maxDepth = 40\n",
        "##### WITH visited list #####\n",
        "print('**************RESULTS WITH VISITED LIST**************\\n')\n",
        "\n",
        "bfs_tIME_calc, bfs_space_complex_calc, bfs_path, bfs_flag = breadthFirstSearch(mat, source, goal)\n",
        "print_func('Breadth First', bfs_tIME_calc, bfs_space_complex_calc, bfs_path, bfs_flag)\n",
        "\n",
        "dfs_tIME_calc, dfs_space_complex_calc, dfs_path, dfs_flag = depthFirstSearch(mat, source, goal)\n",
        "print_func('Depth First', dfs_tIME_calc, dfs_space_complex_calc, dfs_path, dfs_flag)\n",
        "\n",
        "best_tIME_calc, best_space_complex_calc, best_path, best_flag = bestFirstSearch(mat, cost, source, goal)\n",
        "print_func('Best First', best_tIME_calc, best_space_complex_calc, best_path, best_flag) \n",
        "\n",
        "ddfs_tIME_calc, ddfs_space_complex_calc, ddfs_path, ddfs_flag = iterativeDDFS(mat, source, goal, maxDepth)\n",
        "print_func('DDFS', ddfs_tIME_calc, ddfs_space_complex_calc, ddfs_path, ddfs_flag) \n",
        "\n",
        "##### WITHOUT visited list ########\n",
        "print('**************RESULTS WITHOUT VISITED LIST**************\\n')\n",
        "\n",
        "wo_bfs_tIME_calc, wo_bfs_space_complex_calc, wo_bfs_path, wo_bfs_flag = wo_breadthFirstSearch(mat, source, goal)\n",
        "print_func('WO Breadth First', wo_bfs_tIME_calc, wo_bfs_space_complex_calc, wo_bfs_path, wo_bfs_flag)\n",
        "\n",
        "wo_dfs_tIME_calc, wo_dfs_space_complex_calc, wo_dfs_path, wo_dfs_flag = wo_depthFirstSearch(mat, source, goal)\n",
        "print_func('WO Depth First', wo_dfs_tIME_calc, wo_dfs_space_complex_calc, wo_dfs_path, wo_dfs_flag)\n",
        "\n",
        "wo_best_tIME_calc, wo_best_space_complex_calc, wo_best_path, wo_best_flag = wo_bestFirstSearch(mat, cost, source, goal)\n",
        "print_func('WO Best First', wo_best_tIME_calc, wo_best_space_complex_calc, wo_best_path, wo_best_flag) \n",
        "\n",
        "wo_ddfs_tIME_calc, wo_ddfs_space_complex_calc, wo_ddfs_path, wo_ddfs_flag = wo_iterativeDDFS(mat, source, goal, maxDepth)\n",
        "print_func('WO DDFS', wo_ddfs_tIME_calc, wo_ddfs_space_complex_calc, wo_ddfs_path, wo_ddfs_flag) "
      ],
      "metadata": {
        "id": "AHsFmjk12TRP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1f8920d4-2cf7-4b84-b0ba-6796a60c6794"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "**************RESULTS WITH VISITED LIST**************\n",
            "\n",
            "Breadth First search\n",
            "\n",
            "[19, 36, 21, 0] \n",
            "\n",
            "Time complexity:  96\n",
            "space_complex_calc:  97\n",
            "___________________________________________________________________\n",
            "\n",
            "Depth First search\n",
            "\n",
            "[19, 96, 70, 75, 77, 87, 55, 79, 39, 99, 83, 63, 93, 0] \n",
            "\n",
            "Time complexity:  47\n",
            "space_complex_calc:  49\n",
            "___________________________________________________________________\n",
            "\n",
            "Best First search\n",
            "\n",
            "[19, 36, 68, 0] \n",
            "\n",
            "Time complexity:  13\n",
            "space_complex_calc:  14\n",
            "___________________________________________________________________\n",
            "\n",
            "DDFS search\n",
            "\n",
            "[19, 36, 21, 0] \n",
            "\n",
            "Time complexity:  9\n",
            "space_complex_calc:  11\n",
            "___________________________________________________________________\n",
            "\n",
            "**************RESULTS WITHOUT VISITED LIST**************\n",
            "\n",
            "WO Breadth First search\n",
            "\n",
            "[19, 36, 21, 0] \n",
            "\n",
            "Time complexity:  5865\n",
            "space_complex_calc:  5587\n",
            "___________________________________________________________________\n",
            "\n",
            "WO Depth First search\n",
            "\n",
            "[19, 95, 69, 99, 83, 97, 63, 93, 0] \n",
            "\n",
            "Time complexity:  33\n",
            "space_complex_calc:  27\n",
            "___________________________________________________________________\n",
            "\n",
            "WO Best First search\n",
            "\n",
            "[19, 36, 68, 0] \n",
            "\n",
            "Time complexity:  32\n",
            "space_complex_calc:  30\n",
            "___________________________________________________________________\n",
            "\n",
            "WO DDFS search\n",
            "\n",
            "[19, 36, 21, 0] \n",
            "\n",
            "Time complexity:  11\n",
            "space_complex_calc:  6\n",
            "___________________________________________________________________\n",
            "\n"
          ]
        }
      ]
    }
  ],
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