Final_project_Dijkstra.ipynb

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    {
      "cell_type": "code",
      "source": [
        "SIZE = 100\n"
      ],
      "metadata": {
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      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "markdown",
      "source": [
        "## CODE"
      ],
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      }
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      "metadata": {
        "id": "IHPOi9zWRrU5"
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      "outputs": [],
      "source": [
        "class Vertex:\n",
        "\n",
        "    def __init__(self, node):\n",
        "        self.id = node\n",
        "        self.adjacent = {}\n",
        "\n",
        "\n",
        "        if int(node)==id:\n",
        "          return id\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "    def __str__(self):\n",
        "        #return str(self.id) + ' adjacent: ' + str([x.id for x in self.adjacent])\n",
        "        return str([x.id for x in self.adjacent])\n",
        "\n",
        "\n",
        "\n",
        "    def add_neighbor(self, neighbor, weight=0):\n",
        "        self.adjacent[neighbor] = weight\n",
        "\n",
        "    def get_connections(self):\n",
        "        return self.adjacent.keys()\n",
        "\n",
        "    def get_id(self):\n",
        "        return self.id\n",
        "\n",
        "    def get_weight(self, neighbor):\n",
        "        return self.adjacent[neighbor]\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class Graph:\n",
        "    def __init__(self):\n",
        "        self.vert_dict = {} #key=vertex, values=\n",
        "        self.num_vertices = 0\n",
        "\n",
        "\n",
        "    def __iter__(self):\n",
        "        return iter(self.vert_dict.values())\n",
        "\n",
        "    def add_vertex(self, node):\n",
        "        self.num_vertices = self.num_vertices + 1\n",
        "\n",
        "        new_vertex = Vertex(node)\n",
        "        self.vert_dict[node] = new_vertex\n",
        "        return new_vertex\n",
        "\n",
        "    def get_vertex(self, n):\n",
        "        if n in self.vert_dict:\n",
        "            return self.vert_dict[n]\n",
        "        else:\n",
        "            return None\n",
        "\n",
        "    def add_edge(self, frm, to, cost):\n",
        "        if frm not in self.vert_dict:\n",
        "            self.add_vertex(frm)\n",
        "        if to not in self.vert_dict:\n",
        "            self.add_vertex(to)\n",
        "        #print(\"connected \", frm , \"with\" , to)\n",
        "        self.vert_dict[frm].add_neighbor(self.vert_dict[to], cost)\n",
        "        self.vert_dict[to].add_neighbor(self.vert_dict[frm], cost)\n",
        "\n",
        "    def get_vertices(self):\n",
        "        return self.vert_dict.keys()\n",
        "\n",
        "    def get_values(self):\n",
        "      return self.vert_dict.values()"
      ],
      "metadata": {
        "id": "j_29ouDSRv6y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from numpy import random\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "def createGaussian(size):\n",
        "  gaussianDist=random.normal(loc=50.0, scale=10.0, size=SIZE*SIZE)\n",
        "  sns.distplot(gaussianDist, hist=False)\n",
        "\n",
        "  plt.show()\n",
        "  return gaussianDist"
      ],
      "metadata": {
        "id": "SpxjsG7YYdxI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "\n",
        "def createGraph(SIZE, Gaussian):\n",
        "  G = Graph()\n",
        "  size=SIZE\n",
        "  gaussianDist=[]\n",
        "\n",
        "  if Gaussian==True:\n",
        "    gaussianDist=createGaussian(size)\n",
        "\n",
        "  matrix = np.ones((size,size))\n",
        "  c=0\n",
        "  for r in range(0, size):\n",
        "    for k in range(0,size):\n",
        "      matrix[r][k]=c\n",
        "      c+=1\n",
        "\n",
        "  print(matrix)\n",
        "  #matrix=np.ones(shape=(size,size))\n",
        "  count=0\n",
        "  for i in range(size):\n",
        "    for j in range(size):\n",
        "      #G.add_vertex(matrix[i][j])\n",
        "\n",
        "\n",
        "      if(j<size-1): #the last index will be one less\n",
        "        if Gaussian==True:\n",
        "          w=gaussianDist[count]\n",
        "        else:\n",
        "          w=np.random.randint(1,100)\n",
        "\n",
        "        G.add_edge(matrix[i][j],matrix[i][j+1],w )\n",
        "        #print(\"adding right weight of \", w, \"between\",i,j)\n",
        "      if(j>0): # and j<size-1): #if j is 1\n",
        "        #w=np.random.randint(1,100)\n",
        "        #w=w=gaussianDist[count]\n",
        "        if Gaussian==True:\n",
        "          w=gaussianDist[count]\n",
        "        else:\n",
        "          w=np.random.randint(1,100)\n",
        "\n",
        "        G.add_edge(matrix[i][j],matrix[i][j-1],w)\n",
        "        #print(\"adding left weight of\",w,\"between\", i,j)\n",
        "      if(i<size-1):\n",
        "        #w=np.random.randint(1,100)\n",
        "        #w=gaussianDist[count]\n",
        "        if Gaussian==True:\n",
        "          w=gaussianDist[count]\n",
        "        else:\n",
        "          w=np.random.randint(1,100)\n",
        "\n",
        "        G.add_edge(matrix[i][j], matrix[i+1][j],w)\n",
        "        #print(\"adding down weight of\",w,\" between\", i,j)\n",
        "      if(i>0):# and i<size-1):\n",
        "        #w=np.random.randint(1,100)\n",
        "        #w=gaussianDist[count]\n",
        "        if Gaussian==True:\n",
        "          w=gaussianDist[count]\n",
        "        else:\n",
        "          w=np.random.randint(1,100)\n",
        "\n",
        "        G.add_edge(matrix[i][j], matrix[i-1][j],np.random.randint(1,100))\n",
        "        #print(\"adding up weight of \",w, \" between\", i,j)\n",
        "      count=count+1\n",
        "\n",
        "  G.get_vertices()\n",
        "  return G\n",
        "\n",
        "\n",
        "\n"
      ],
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      "source": [
        "count"
      ],
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          "base_uri": "https://localhost:8080/"
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        "id": "W9_PoJ-IkKir",
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              "160000"
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    },
    {
      "cell_type": "code",
      "source": [
        "len(G.get_vertices())\n"
      ],
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          "base_uri": "https://localhost:8080/"
        },
        "id": "V1MppZS80u9O",
        "outputId": "2b92a96f-c725-4a32-9c40-ee673f5e15b9"
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              "160000"
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          "metadata": {},
          "execution_count": 8
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    },
    {
      "cell_type": "code",
      "source": [
        "#checking if everything has been added correctly\n",
        "for v in G:\n",
        "    for w in v.get_connections():\n",
        "            vid = v.get_id()\n",
        "            wid = w.get_id()\n",
        "            print ( '( %s , %s, %3d)'  % ( vid, wid, v.get_weight(w)))\n",
        "\n",
        "for v in G:\n",
        "\n",
        "  print ('g.vert_dict[%s]=%s' %(v.get_id(), G.vert_dict[v.get_id()]))"
      ],
      "metadata": {
        "id": "lc7qFQJER8w3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def findcost(u,dist,prev,q,site):\n",
        "  for n in u.get_connections():\n",
        "      cost = u.get_weight(n)\n",
        "      uid=u.get_id()\n",
        "      temp=dist[int(uid)]+ cost\n",
        "      nid=n.get_id()\n",
        "      if temp<dist[int(nid)]:\n",
        "        dist[int(nid)]=temp\n",
        "        prev[int(nid)]=u\n",
        "        site[int(nid)]=site[int(uid)]\n",
        "        q.put(nid,temp)"
      ],
      "metadata": {
        "id": "psBfwBRJWEnR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def findcostThreshold(u,dist,prev,q,site):\n",
        "  for n in u.get_connections():\n",
        "      cost = u.get_weight(n)\n",
        "      if cost<50:\n",
        "        cost=cost/2\n",
        "      else:\n",
        "        cost=cost*2\n",
        "      uid=u.get_id()\n",
        "      temp=dist[int(uid)]+ cost\n",
        "      nid=n.get_id()\n",
        "      if temp<dist[int(nid)]:\n",
        "        dist[int(nid)]=temp\n",
        "        prev[int(nid)]=u\n",
        "        site[int(nid)]=site[int(uid)]\n",
        "        q.put(nid,temp)\n"
      ],
      "metadata": {
        "id": "i3VUendfWvIc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def findcostmax(u, dist, prev, q, paths, site):\n",
        "\n",
        "    for n in u.get_connections():\n",
        "        cost = u.get_weight(n)\n",
        "        uid = u.get_id()\n",
        "\n",
        "        path = paths[int(uid)]\n",
        "        maxE = max(path)\n",
        "\n",
        "        if cost > maxE:\n",
        "            maxE = cost\n",
        "\n",
        "        path_distance = dist[int(uid)] + cost\n",
        "        path_cost = path_distance + maxE * 1000\n",
        "        nid = n.get_id()\n",
        "\n",
        "        if path_cost < dist[int(nid)] + max(paths[int(nid)]) * 1000:\n",
        "            dist[int(nid)] = path_distance  # original_dist #new_dist runs into infinite loop\n",
        "            prev[int(nid)] = u\n",
        "            site[int(nid)] = site[int(uid)]\n",
        "            paths[int(nid)] = paths[int(uid)].copy()\n",
        "            paths[int(nid)].append(cost)\n",
        "            q.put(nid, path_distance)"
      ],
      "metadata": {
        "id": "Yw603hOwarEF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def getSecondMax(path):\n",
        "    if len(path) == 0:\n",
        "        return 0\n",
        "    if len(path) == 1:\n",
        "        return path[-1]\n",
        "    else:\n",
        "        return path[-2]\n",
        "\n",
        "def findcostsecmax(u, dist, prev, q, paths, site):  # SECOND MAX EDGE\n",
        "\n",
        "    for n in u.get_connections():\n",
        "        cost = u.get_weight(n)\n",
        "        uid = u.get_id()\n",
        "\n",
        "        path = paths[int(uid)]\n",
        "        secondMax = getSecondMax(path)\n",
        "\n",
        "        if cost > secondMax:\n",
        "            if cost > path[-1]:\n",
        "                secondMax = path[-1]\n",
        "            else:\n",
        "                secondMax = cost\n",
        "\n",
        "\n",
        "        path_distance = dist[int(uid)] + cost\n",
        "        path_cost = path_distance + secondMax * 1000\n",
        "        nid = n.get_id()\n",
        "\n",
        "        if path_cost < dist[int(nid)] + getSecondMax(paths[int(nid)]) * 1000:\n",
        "            dist[int(nid)] = path_distance  # original_dist #new_dist runs into infinite loop\n",
        "            prev[int(nid)] = u\n",
        "            site[int(nid)] = site[int(uid)]\n",
        "            paths[int(nid)] = paths[int(uid)].copy()\n",
        "            paths[int(nid)].append(cost)\n",
        "            paths[int(nid)].sort()\n",
        "            q.put(nid, path_distance)"
      ],
      "metadata": {
        "id": "j8Xnk6j9oP_k"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def getThirdMax(path):\n",
        "    if len(path) == 0:\n",
        "        return 0\n",
        "    if len(path) == 1:\n",
        "        return path[-1]\n",
        "    if len(path) == 2:\n",
        "        return path[-2]\n",
        "    else:\n",
        "      return path[-3]\n",
        "\n",
        "def findcostthirdmax(u, dist, prev, q, paths, site):  # THIRD MAX EDGE\n",
        "\n",
        "    for n in u.get_connections():\n",
        "        cost = u.get_weight(n)\n",
        "        uid = u.get_id()\n",
        "\n",
        "        path = paths[int(uid)]\n",
        "        thirdMax = getThirdMax(path)\n",
        "\n",
        "        if cost > thirdMax:\n",
        "            if cost > path[-1]:\n",
        "                thirdMax = path[-1]\n",
        "            if cost > path[-2]:\n",
        "                thirdMax = path[-2]\n",
        "            else:\n",
        "                thirdMax = cost\n",
        "\n",
        "\n",
        "        path_distance = dist[int(uid)] + cost\n",
        "        path_cost = path_distance + thirdMax * 1000\n",
        "        nid = n.get_id()\n",
        "\n",
        "        if path_cost < dist[int(nid)] + getThirdMax(paths[int(nid)]) * 1000:\n",
        "            dist[int(nid)] = path_distance\n",
        "            prev[int(nid)] = u\n",
        "            site[int(nid)] = site[int(uid)]\n",
        "            paths[int(nid)] = paths[int(uid)].copy()\n",
        "            paths[int(nid)].append(cost)\n",
        "            paths[int(nid)].sort()\n",
        "            q.put(nid, path_distance)"
      ],
      "metadata": {
        "id": "RL-N5BzjocLg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# def findcostMAXEDGE(u,dist,prev,q, maxEdge,site):\n",
        "#   for n in u.get_connections():\n",
        "#       cost = u.get_weight(n)\n",
        "#       uid=u.get_id()\n",
        "#       maxE=maxEdge[int(uid)]\n",
        "\n",
        "#       if(cost>maxE):\n",
        "#         maxE=cost\n",
        "#       sum_of_edges=dist[int(uid)]+ cost\n",
        "#       path_cost=sum_of_edges+maxE*1000\n",
        "#       nid=n.get_id()\n",
        "#       if(path_cost < dist[int(nid)]+ maxEdge[int(nid)]*1000):\n",
        "#           dist[int(nid)]=sum_of_edges #original_dist #new_dist runs into infinite loop\n",
        "#           prev[int(nid)]=u\n",
        "#           site[int(nid)]=site[int(uid)]\n",
        "#           maxEdge[int(nid)]= maxE\n",
        "\n",
        "#           q.put(nid,sum_of_edges ) #original_dist"
      ],
      "metadata": {
        "id": "cFUURUXhXIzC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def findcostRECIPROCAL(u,dist,prev,q,site): #RECIPROCAL\n",
        "  for n in u.get_connections():\n",
        "      cost = u.get_weight(n)\n",
        "      uid=u.get_id()\n",
        "      temp=dist[int(uid)]+(1/cost)\n",
        "      nid=n.get_id()\n",
        "      if temp<dist[int(nid)]:\n",
        "        dist[int(nid)]=temp\n",
        "        prev[int(nid)]=u\n",
        "        site[int(nid)]=site[int(uid)]\n",
        "        q.put(nid,temp)"
      ],
      "metadata": {
        "id": "YLcmHoJXBm7L"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import math\n",
        "\n",
        "\n",
        "def findcostEdgeDiff(u, dist, prev, q, paths, site):\n",
        "\n",
        "\n",
        "    for n in u.get_connections():\n",
        "        cost = u.get_weight(n)\n",
        "        uid = u.get_id()\n",
        "        path = paths[int(uid)]\n",
        "        prevcost=path[-1] #is this getting the last edge's cost?\n",
        "\n",
        "        temp=dist[int(uid)]+abs(cost-prevcost)\n",
        "        nid=n.get_id()\n",
        "        if temp<dist[int(nid)]:\n",
        "          dist[int(nid)]=temp\n",
        "          prev[int(nid)]=u\n",
        "          site[int(nid)]=site[int(uid)]\n",
        "          paths[int(nid)] = paths[int(uid)].copy()\n",
        "          paths[int(nid)].append(cost)\n",
        "          #paths[int(nid)].sort()\n",
        "          q.put(nid,temp)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "9Jb6pyqt7eXH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# def findcost4(u,dist,prev,q, maxEdge,secondmaxEdge,site): #SECOND MAX EDGE\n",
        "#   #list_of_costs=[]\n",
        "#   for n in u.get_connections():\n",
        "\n",
        "#       cost = u.get_weight(n)\n",
        "#       #list_of_costs.append(cost)\n",
        "#       uid=u.get_id()\n",
        "#       maxE=maxEdge[int(uid)]\n",
        "#       secondmaxE=secondmaxEdge[int(uid)]\n",
        "#       #secondmaxE=maxEdge[int(uid)]\n",
        "#       # if(len(list_of_costs)>1):\n",
        "#       #   list_of_costs.sort()\n",
        "#       #   secondMaxE= list_of_costs[-2]\n",
        "#       # else:\n",
        "#       #   secondMaxE=cost\n",
        "#       if(cost>maxE):\n",
        "#         maxE=cost\n",
        "#         if(cost>secondmaxE and secondmaxE<maxE):\n",
        "#           secondmaxE=cost\n",
        "\n",
        "#       sum_of_edges=dist[int(uid)]+ cost\n",
        "#       path_cost=sum_of_edges+secondmaxE*1000\n",
        "#       nid=n.get_id()\n",
        "#       if(path_cost < dist[int(nid)]+ secondmaxEdge[int(nid)]*1000):\n",
        "#           dist[int(nid)]=sum_of_edges #original_dist #new_dist runs into infinite loop\n",
        "#           prev[int(nid)]=u\n",
        "#           site[int(nid)]=site[int(uid)]\n",
        "#           secondmaxEdge[int(nid)]= secondmaxE\n",
        "\n",
        "#           q.put(nid,sum_of_edges ) #original_dist"
      ],
      "metadata": {
        "id": "RHKpNyI1ChHi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# def findcost5(u,dist,prev,q, maxEdge,site): #THIRD MAX EDGE NOT WORKINGGGG\n",
        "#   list_of_costs=[]\n",
        "#   for n in u.get_connections():\n",
        "\n",
        "#       cost = u.get_weight(n)\n",
        "#       list_of_costs.append(cost)\n",
        "#       uid=u.get_id()\n",
        "#       #maxE=maxEdge[int(uid)]\n",
        "#       #secondmaxE=maxEdge[int(uid)]\n",
        "#       if(len(list_of_costs)>2):\n",
        "#         list_of_costs.sort()\n",
        "#         thirdMaxE= list_of_costs[-3]\n",
        "#       else:\n",
        "#         thirdMaxE=min(list_of_costs)\n",
        "#       # if(cost>maxE):\n",
        "#       #   maxE=cost\n",
        "\n",
        "#       sum_of_edges=dist[int(uid)]+ cost\n",
        "#       path_cost=sum_of_edges+thirdMaxE*(1000)\n",
        "#       nid=n.get_id()\n",
        "#       if(path_cost < dist[int(nid)]+ maxEdge[int(nid)]*(1000)):\n",
        "#           dist[int(nid)]=sum_of_edges #original_dist #new_dist runs into infinite loop\n",
        "#           prev[int(nid)]=u\n",
        "#           site[int(nid)]=site[int(uid)]\n",
        "#           maxEdge[int(nid)]= thirdMaxE\n",
        "\n",
        "#           q.put(nid,sum_of_edges ) #original_dist"
      ],
      "metadata": {
        "id": "ywVINcvBKfGe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def recolor(matrix,site,size):\n",
        "  for i in range(size):\n",
        "    for j in range(size):\n",
        "      matrix[i][j]=site[i*size+j]\n",
        "  return matrix\n"
      ],
      "metadata": {
        "id": "_PXVBgDf3U9h"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "def normalize(matrix,size):\n",
        "  N=np.zeros(shape=(size,size))\n",
        "  mat_flattened = matrix.flatten()\n",
        "  min = np.min(mat_flattened)\n",
        "  max=np.max(mat_flattened)\n",
        "  for x in range(size):\n",
        "      for y in range(size):\n",
        "        N[x][y]=(matrix[x][y]-min ) * (255/(max-min))\n",
        "  return N\n"
      ],
      "metadata": {
        "id": "hYjWSZBqYwbV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import math\n",
        "import queue as Q\n",
        "import heapq as hq\n",
        "import ast\n",
        "\n",
        "\n",
        "def dijsktra(Graph, src, costMetric,size):\n",
        "    # costmetric 0=dijkstra, 1=threshold with 50, 2=multiplied maxEdge by 1000\n",
        "\n",
        "    c = 0\n",
        "    start = [None] * len(src)\n",
        "    for i in src:\n",
        "        start[c] = int(i)\n",
        "        c = c + 1\n",
        "\n",
        "    # print(start)\n",
        "    matrix = np.zeros(shape=(size, size))\n",
        "    dist = [None] * (size * size)\n",
        "    print(len(dist))\n",
        "    prev = [None] * (size * size)\n",
        "    maxEdge = [math.inf] * (size * size)\n",
        "    site = [None] * (size * size)\n",
        "    paths = [[]] * (size * size)\n",
        "\n",
        "    for j in start:\n",
        "        dist[j] = 0\n",
        "        maxEdge[j] = 0\n",
        "        site[j] = j\n",
        "        paths[j].append(0)\n",
        "\n",
        "    q = Q.PriorityQueue()\n",
        "\n",
        "    for v in Graph:\n",
        "        vID = v.get_id()  # float originally\n",
        "\n",
        "        if (not (int(vID) in start)):\n",
        "            dist[int(vID)] = math.inf  # index has to be int\n",
        "            prev[int(vID)] = None\n",
        "\n",
        "        q.put(vID, dist[int(vID)])\n",
        "\n",
        "    while not q.empty():\n",
        "\n",
        "        uu = q.get()\n",
        "\n",
        "        u = Graph.get_vertex(uu)  # turning uu into a vertex item\n",
        "\n",
        "        if (costMetric == 0):\n",
        "            findcost(u, dist, prev, q, site)\n",
        "\n",
        "        if (costMetric == 1):\n",
        "            findcostThreshold(u, dist, prev, q, site)\n",
        "\n",
        "        if (costMetric == 2):  # max edge\n",
        "            findcostmax(u, dist, prev, q, paths, site)\n",
        "\n",
        "        if (costMetric == 3):  # reciprocal of distance\n",
        "            findcostRECIPROCAL(u, dist, prev, q, site)\n",
        "\n",
        "        if (costMetric == 4):  # second max edge\n",
        "            findcostsecmax(u, dist, prev, q, paths, site)\n",
        "\n",
        "        if (costMetric == 5):  # third max edge\n",
        "            findcostthirdmax(u, dist, prev, q, paths, site)\n",
        "\n",
        "        if (costMetric == 6):  # Adding by the abs diff between new and prevs edges\n",
        "            findcostEdgeDiff(u, dist, prev, q, paths, site)\n",
        "\n",
        "    for x in range(size):\n",
        "        for y in range(size):\n",
        "            matrix[x][y] = dist[x * size + y]\n",
        "\n",
        "    return matrix, site"
      ],
      "metadata": {
        "id": "CUq7y4ZF-CkL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "n-FaZ8mOSLWQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## RESULTS"
      ],
      "metadata": {
        "id": "NG3gFpvTn9_V"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "G=createGraph(SIZE,False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iKaojiMJ15gZ",
        "outputId": "2e47913b-47b3-4d52-a7c2-8cb72ca4d581"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0.000e+00 1.000e+00 2.000e+00 ... 9.700e+01 9.800e+01 9.900e+01]\n",
            " [1.000e+02 1.010e+02 1.020e+02 ... 1.970e+02 1.980e+02 1.990e+02]\n",
            " [2.000e+02 2.010e+02 2.020e+02 ... 2.970e+02 2.980e+02 2.990e+02]\n",
            " ...\n",
            " [9.700e+03 9.701e+03 9.702e+03 ... 9.797e+03 9.798e+03 9.799e+03]\n",
            " [9.800e+03 9.801e+03 9.802e+03 ... 9.897e+03 9.898e+03 9.899e+03]\n",
            " [9.900e+03 9.901e+03 9.902e+03 ... 9.997e+03 9.998e+03 9.999e+03]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "G.get_vertices()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IMUQmUS84BKk",
        "outputId": "a9d0fe65-9de8-4657-8650-dc665b5c668d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m,site=dijsktra(G, [90,210,999,1609,8686,130878,34546,10989,20543,69432,19000,148777,154389,89060,122130],0, SIZE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6tjdlD0ha33a",
        "outputId": "854c5b89-9f84-4456-9023-ad3ca96672fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "490000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m,site= dijsktra(G,[6,98,450,934,1206,1734,2198,4380,6302,7825,9954],0,SIZE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4LLBqT-R4azB",
        "outputId": "dff3cb4c-1196-4223-e2bc-86584c95c700"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m,site=dijsktra(G, [90,210,999,1609,8686,130878,34546,10989,20543,69432,19000,148777,154389,89060,122130],0, SIZE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r8-rQGUoB15g",
        "outputId": "08b705f7-5938-4178-f7f0-f15f1df0fbfb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib import pyplot as plt\n",
        "\n",
        "#m=normalize(m,SIZE)\n",
        "plt.gray()\n",
        "plt.imshow(m, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "sJk7PiK84y_N",
        "outputId": "5c2bc000-1161-43ef-8cfb-fb1064704df6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m_segmented=recolor(m,site,SIZE)\n",
        "plt.gray()\n",
        "plt.imshow(m_segmented, interpolation='nearest')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "zBEbrfq_486f",
        "outputId": "021e8983-53df-4815-f193-83364a5b6c4d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#m0,site=dijsktra(G,[10,100,34499,39867,932,3000,15222,6310,7438,19898],0 )\n",
        "#m0,site=dijsktra(G, [10,510,999,11300,20311,25080,50499,87321,100400,120999,150333,17777,195000,210476,240987],0)\n",
        "#m0,site=dijsktra(G, [90,210,999,16090,20999,23080,50401,87100,100800,120250,150333,195099,210700,240120],0)\n",
        "m0,site=dijsktra(G, [90,210,999,1609,5000,8686],0, SIZE)\n"
      ],
      "metadata": {
        "id": "yW9VfNdXYB1x",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "62953fb3-611b-4443-83a7-02f80a6bc447"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib import pyplot as plt\n",
        "\n",
        "m0=normalize(m0,SIZE)\n",
        "plt.gray()\n",
        "plt.imshow(m0, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "13GTnpOUY2L5",
        "outputId": "de14f42b-bfcf-478a-e8c5-d59a5690a65a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m1,site=dijsktra(G, [90,210,999,1609,5000,8686],1,SIZE)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tmPLhYM5P71A",
        "outputId": "076e5074-412c-42cd-d645-1f5d59e09bb2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "m2=normalize(m2,SIZE)\n",
        "plt.gray()\n",
        "plt.imshow(m2, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "ZFDZ-wKkP-Yv",
        "outputId": "a793c43b-1c25-4e4b-82bd-368d789aef5f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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ra8uc8T27jxP+9YzmJTtYbTPSmI/xiB88y2r7abSa6hRtgyWb1SYzfk/zmUJUstZ685KVMuDzcHIIMP+7Zuqje/6URda7s6I9Iy1GNER9b9iDz9dlVVtm4plHo9XnXrq6bKFQeGVg5d747e3tOW+t/u59jvrVbdnTa7UZxbYXPWaU3GKNe0qcehSLnxJnj8414hgA/hrlLE0tDU4koPwfrYPmUXaje+tJctmuvdZcEo01RisVm+1ujhhEFNaIHzJKQMr4NjyUZC8UNgT1shcKG4K1LOxoVZf1SBDyKepTFMbxSB1W2ynU1JE6nKGSRiqn1zZq45F2rOq4XjWViEzjjSki1WRUzkjdnQqLqMQUWnYAWs8emxCeOh+1lbGIeWAd4/0OlunCayJMCcN6KMleKGwIVi7Ze++mg8KrAxYtmOdJWpndrXpyXNFTnDMWDdGiw1rb9flZcmRCbZ7WYd0nTypHDkavzRSNxOvTuh6PsqqvZbTMM3BRujH9OZK8nCzjkbT0mKbcFy9ximnLGl44MHpGRlplxtnKKMleKGwIVirZe+/Y29sz62V74Qi2byxtQMBhkYz9PYWiGtFM+TyiMcinRcDxqvBMobNOoe561EsrqYJh3R9PyjFBSvcpv5HYtnzNVgKJdz3RPn5erGdu1IdVqSa7YlFUX9FLX9XfmaTDz7b1O4zqxpdkLxQ2BGvxxj///PMAbCni2SiWPcXHs70WSSyv5nxExPHGlFmHzoJX8XYKWApZ6bbZTz1uuV/R6ii8jT9FelsJJV6hiIhAFBWI8Mbkjd+K1HCBEStVWiQtt/Eo27pf7i9Kq/auPaLLlmQvFAoAVizZL1y4gLNnzx5IjbNnz14cCNmRHIeNkmckhiozKFMwNaQNx0OtGZ/H5K0Eo2dZj6YZxakZU9IZvf8zyHiB2da1bEW5ZrYvo7ro0o/HqwDmfTIsTa0xeeuYR7XamcvB57O0Je+5lHugnz2h2/JYrPvPK8JY67Fz/9bKRBZKshcKG4K1eONfeOEFAHZMW2Z+jqVGNrUX47Ti7FznO5KMnpc8KqogGgPPzFZ6pmePeb4Ba5wZhls2nm/1ExXo5N8m8mEwMvff0uY0pK1Ic8CX+tF9soqB6v61FOVx8u9taZPS1uMW6Pcgw4zUY+ZrLpu9UCjUy14obApWrsafP3/eXJbZU9nYeZIJUzCxBfDJIlwl1CKAeGZCRg3m7RG8Y60wSyb/31MJ2RyxyE2ZsbEZxSq5FVrykmcyNFY+Vn5fbSJlKK/ApfnsogZLZWOmPEeJMJ5TL3pOGZZTmJ1uHBLV74l+hiMHbUn2QmFDsHJSzfnz5w9mRSHXABdnSJmteaa3QhDeLMg0VGBeCnu1zfUxEgbhCqieo846D8+0UVJLxpkkGDkPM22sY7xrtJxvcl+YkhqFM726dVb/vE/6Ze1vStUWK8XVux9M1dbfPceidc2elmdds7fQKJ9PpDlwqVZakr1QKOQle2ttG8CDAB7vvb+ntXYzgPsAvAbAQwA+2Hv3i3Fjf6aUP2sfcHHGFUkvs5ZVz0y2vfjiiwDmk060PcUznthsUUEH1gI82z0ivTCi0FhGSrANF7X17PuIIuytVReta8e/ESNaxYe3a8nvkWr4t9S+GbazvbXSrLAvk4EizWqkhWWIUEwGAy4ScPhZjp7TjD8ImCbZPwTgEfX/RwF8rPd+C4AfA7hrQl+FQmHFSEn21tpNAP4lgP8E4N+1/ankHQA+MGvyKQC/DeDjU05uzfKcJBPZr2z/SX9Cw4086yIBMqu9SBEFOXe02uciCQze+m1M09X9ZhKFRppChkgU+QSYcmxJZ29M/Gmle/I9Y+3OStYZleCK/B+e199aMVXAbazKxl4arEWH9iivU35nD1nJ/gcAfhOAXPVrADzVexc9+TEAN1oHttbubq092Fp70MtPLhQKlx9Dyd5aew+AJ3vvD7XW3j71BL33MwDOAMDp06f7uXPnzGQETnxhT29ks7NEiWZXzytvzeJ8HvaELlLiKLK1MvafN/Nn48ujMY68wBp8vzn2bHm+Pc3BiqDwbzTy+lvHCLx11XW//AxE3AX+tDQTAfMNvNrzwEUtkv1E7GvQ2kzWZs+o8W8D8POttXcDOA7gGgD3AriutbYzk+43AXg8dcZCobAWDNX43vtHeu839d7fAOD9AP6y9/6LAL4I4L2zZncC+NxlG2WhUFgay5BqPgzgvtba7wD4CoBPjg64cOECnn322VDl4W281K7VVj7FuRepX+yEYZXfOobHwmplJgxiZVZFtFWNiKIa9ZEl6Uw5Rrcd1fq3+vcqz1oEFk+9ZhPDqgrDYTT5P6Jde8s7WzUU2OmWqRQ7MiWjtlnTK1LpJ73svfcvAfjS7Pu3ALxlyvGFQmF9WEs+u+V4khnXkw6WA+2ll14CEC99G43F6tci4rCzkPuIaul5ISb93QtzZRxELOGjGgGjsCB/t47Rixyyw2kkTa3xetLa2ifwqrRa1+pVlbVCoOwktKSop5nwcxQtw8z966QcTnjxlqnWdNls7cKiyxYKG4K1rAjz3HPPzQ/ECNNoyKz4zDPPHGxjEgrPxLovrozCtrpH49T7RmFBPZYRkUXDS6yxqsOMKLYW3XekMViS3VuJR0saTkzha9NagMCyzaPz6mMykpd/I04JjZKX+P9MaHJEctJgaW/9vtxGqvBIv5bPQWsDlQhTKBRWK9nPnz+Pp59+2qQJWp5POUbvjwoVRJ5IprqyhLdsxshTn0XUh+efYFj7M4kwHuU4k47J95Ilpt7mkWgsPwvb2WznW/XYmDbsSXoen9XG+g1HGkO0JqE3Jus3k2tmEpJVvZbJNF4kaHRtGiXZC4UNwVpWhLFmcZbgFuX1MDGSppm21iy+iJRepm1GO5iyLpxAJFdGYsk2qRrM6aVa2rJGFcW0eQyiBXAaq0RlAD8lmrUPnacx0pKsMQlGq9Lq79yfZd972pd47OVTa7ijgh0H1xnuLRQKrxisJc4us6suS8U2Cs+QVrwxI3VGbb14PuB73b0Yqz7GS/RYB0be5gzk/msp7cXXObvRuj/eubUH31s/jc+rJZqXIi1jkP3aA86SNoIkqsin53OwPOzyDHAUQ98va815faw8i7rghS50EWlvJdkLhQ1BveyFwoZg5Wr8uXPnDmrGaQcdO+ZEnYsWUfSSZKyQj6des6puhYk8Mk2UpLMIDsMhF+X7C6KQpZf8k0la8mCNyQuR6e2cL89qsECeJw12fkkfFoXXqz1nUV85dOiZdh7NVe/z7oUGmwBW1ZusWVaSvVDYEKw89HbhwoWDmUzPyF79NZ5lM5KXQzYZZJx7U9pmnIZZzWDK+Rbpxwr9eNV/Iokon9I2WsCTK65YEpfvjzwvItUsh6DskzqETF+2qsR4FY8s0g6nU3tJWPp/Dst5yTP6XPIpGm7k8M2GqUuyFwobgpVK9r29PfzoRz+ak96AT66IasMJFpHgy0hCwRSbfZHzrtIXwG1ZSkeSncNykQ3qaWMsTaM2IuGnpDbzPdBEHD4f3wPRUKxzenTWaB1DJvpYKcB8v7k4iZV2e+HChfC3LsleKGwIVirZt7a2cPz48TmvJ3/X/0+plprBYbaN0hkv53mntl3mXkb2pUcuYlqrlUKb0eB4W0bjEYnN5/E0Cr2Ni25Y3n9L2gPzPid9DGsBVmRJwNKevfoWhVf7qkqyFwqF1XvjdVG8KYUOM0UHvCINVtvR/9l9U9uuU8JPabsMBVkg0kcXK/HWMrPsbs9LzhJf98/Sk7UCS2LKmJh+G8Xkvdrvlu9Bvst5onTVUdFL7ktfc8XZC4UCgHrZC4WNwVry2SNMUUcX6der2mJVqhm1zZwvQra/KfdkSv6/1a+3DFek0nJozFO3Ad8xZ4X2BBx2jZxt4qDjKrZyrVa4zqO6Wpl+nkORnZFWDr9XI0C39ZydcqxcnxW2rtBboVAAsGLJvru7i9e97nUmzZHrcTHN0aq2wvsyVUH5/0WkdCTppzj+RudZtM3Utla7bP5/tC+q5MMSUein+vfl6rQRsWo0JtY2hE6rz8kOOktz8K6V8+gtYhETcOT6tJPPSxCSsXEfwEVpX5K9UCgAWLPNboVbWFozAUHP/NEyvB48OzlK9xyFBaM15byaYpn+MvXMDqNtJNkjjEJuFn3Wq+4bJUdxv5FNzTYuVxmyfAOcsBM9R3y819ai/conn0+3tVJY9XmX+c1KshcKG4KVSvbWGo4fP34wa2mb7PTp0wDmZ1deH8uSjEzQsGa4jFTW26NjvP3ZNsv072GZtlENNM8Trr97xI/IZmdbNKMFcB9RIpLYsSNNQn8XrYLrukfUV74e8QVE3n7WfPT4vX7597COefHFF0O/Rkn2QmFDsBa6rLWuG9vmMutJFU9uB/hrl1n9jyTfFM96ZCePxjaFIpzRCiJMkfYCL87LZZgyfURtxXvtlfwC5qXcFJov29SZElDe+CPNJBO14Iq2lkddwONjTcQqXsHcAg8l2QuFDcHKbfadnR0zicCLmbPE1/WyOS7KfWSk0CLSL9Ofh0U897pP1hi8FWCtfjw+QiZ+zau96OPY9ozKeHnxb0visq0+5XcVsAZhRYA8NlyGJ8CaRBTH599XrtmSyPzb8Hl1/5Z/wEJJ9kJhQ1Ave6GwIUip8a216wB8AsCbAHQA/xrAowD+CMAbAPwdgPf13n886Afb29sHqogsNA/YiwACPn1WH8/VQUQFOnHixEFbOWdUJUQfy9/1/1McaIs42zK0X89ciMbP2y2nFavk0cKLXp00QaQG8/9WbvfoGGtMniouYxRzRB8jpiGHHS3SjoyPw3XsTLQSYXi88jtYNe74mfaq8erjd3d3QwdkVrLfC+DPeu8/CeCnADwC4B4A9/febwVw/+z/QqFwRDGU7K21awH8MwD/CgB67y8DeLm1dgeAt8+afQrAlwB8ONFfiowiMxs7NayqHl4f+n9Z6pZnVT6PdfyyaaOH0XbUx5RQHCd6aMnpVXuNEmA4vTNDevFCVZZEFHg17izJPtJMLA3FG6Pe/8wzzwC4KGn5XrLk1234eqLquJy4I9V4WFPh45d10N0M4IcA/rC19pXW2idaaycBXN97f2LW5vsArrcObq3d3Vp7sLX2YLQkTqFQuLzI2Ow7AH4awK/03h9ord0LUtl77721Zk4pvfczAM4AwOnTp/upU6fmbCJgnhDDxJhIG2D7W2ww3ZZnYJaE7Buwzskz9BSJvwwul7aQqXvP4TVLIrL9yravpkXLb+PZ3ZbNzmmwTCG1VpEZVWnVktdbacZaPpkpxiJVo6WSGVG6LWuao/Rb4KLU393dXZou+xiAx3rvD8z+/wz2X/4ftNZumA3sBgBPJvoqFAprwlCy996/31r7bmvttt77owDeCeDh2d+dAH539vm5UV9ir1vSx6O8crXQyBZiSWtRa3nmm2LrTtnvjc3STEakl6jfyHPv9SvgeunAvCSMVjrxyCfRKj4iRT2tSKS3HoO3/p/ljfd8AZ69rzGKRPB33UaOFeqqlvRca56vy4oMSb9cBz9Kzum9h1palkH3KwA+3Vo7BuBbAH4J+1rBH7fW7gLw9wDel+yrUCisAamXvff+VQC3G7veOfWEW1tbZlKFZ1Oz9LOO8erFW+mw3jFRcYwRjTVDgeVxZNpY/S8Sk+f/FykxZYG91SOpCsyXV/IKXOrvbL/K/xHVdjQW6zyjNdkAfzXVaCyizXDNfEtzGGkgmaiIh2LQFQobgnrZC4UNwcqz3jRd1srmkk+uPiPbdX47q4JyjKhLlrOKs+fYOWKpwV5YZQpNNpPPfph15aJzc0jJcrpxtRYrDMXImABeRZeMSSEhJnZw6Wv2qK683ap/z+e14IUrWfXXtfR4vJxrb5lpXIGWQ5aRU9JDSfZCYUOwlko1gik14CMiy/HjxwHMJxHottKvtGXnD4f49DFeiMQa02iVl8tFkFmGTGM5q7zQm5YoXBfNWxkm6j+qhCPfuSa7tx2Yl4zsAIySZ5599lkA81JUw9NsIg2INVBvOWkN3iaakPSRpchqlGQvFDYEK5fsW1tbB7OSRUNkCmwUGpMZmMN20VK4ApHwLC209LbOqc8XJcqMbOtoX+xezNYAABJOSURBVCb0Nvq0kJHWHL7xUkb1d4+Smklx5WMiWzSTpONdf0T7HaXQWuMXScsrGUXJLVHtOQFTd61QoYey2QuFAoA1eOO3trYOZqCI9OJJdC1lpxBMBFF/ej9/1//L+K3zMLEnktKehhDRgEdtLG2GqZZRkohXx122ZwpRRJKREVFsPXILbxdKKeAnUHnns8bJkYIohTZzzd59sHwmXGTD82noMYk2sLOzU3XjC4XCGiS7ZcsAY6pfZL+yfWN5z7114dgbr8GSN5N26413mZj5Ina+hpfMEiWseJLKWnnX0xQyZaPYvxKl0LIkZM+7BYlTR3F29rCzxqC1JW/8iyTnyKcuS2UlJ+n+5XfXabG64vKyxSsKhcIrAEdOsmdWWxGwlJPSU7w+HH+P+tXj80pjTYlp8/mmpNQu29aL52ZKNI1qqUf9sHTSY/M86SKpLIkrvwnb7BazkaWxJ+ksycsxcjmv9gmMtACLEcj3Sa+nDtj3h7WXTEy+EmEKhQKAetkLhY3Bykk129vbBw6FyNmTSSQRWHW5vLbsvIvMBm/5IQ5lWcdMIbuM1PVFzAaNbLgI8KmuUR74iC4bOd28EF8Er2a7vhbPKWnVgvccjLoeO7cdmUgaOjQGXHSoCd1XvwdyPD9rbBp55nA56AqFwmol+/b2Nk6ePGlW4eCZkckvFsGEiTE8q2kHDkt0luxRlVCuWMNJNXqWjaQ+/z/SAiJtY4rzTpBNmAB8p5sVRhslm1jaANdSs2qrCUQysvYn913XrePf0ZPa+jxeco586v459dq75qhirK62q4/1rh+46NSLnoly0BUKBQBrstllBrLsDg6fecvd6u9eZdoogYT7sOrG8+ydSW7xzhfVxVumIIW3hLM3LmBanTk+JtOGkzYin0CmUATb2ezX0RApzBI80hw4NZrPZ41f7jePybLzR34nq7qvgO+BVYm2ilcUCoVLsNayVHomEvuXvZ1sU1vFJaZUfc2kp+rx6rFx/XLLzmfJ4SXG6H3edWSKY0S2e5ZscdgSPjpm5C3XWgGXzcr4ETz7O4oQTBmTwKPHMkkI8Nc+sDzr7B8SRNqMluyVCFMoFFZvswNxrFw+ZW11pkZaNjVLaZa8wHxaKktVq39PKmc0CKb/Rja1J6UziTaRPbhICuqUNFWv+CLvzxTHiOBJWivO7tn5kZQWCctxb0vyyv311o6zEm3kGO6PC2kCF58PfobZDxVppB5KshcKG4K1SHYLLNFlZoyK/wkyRSW8teOiYhae9Pc84fr7yZMnAcyn3WqMvPEZbkGkOXiriWSKSYwKLmSOmaI5RMUpM557gWfPe6Wl9T4vycXSTEYrwkR+BO5rimaVSRv2UJK9UNgQ1MteKGwIVqrGX3XVVbjlllsO1BlNG+RtHr3RyjdnNZ4JORY8cs2Uem+R40wgYTuuPqrbTqkU67Wxxh9VYQXGDjaNKW0yTrdFiD2Z0JsXRvNCZMA4GUc70NgM9Fa00f+L489bEUa39ZKWrH6noiR7obAhODIOOkaUQCLwqs9EVV89x1wk2UdrvVlOMY/mmyHILBNeWRYjiXu5CTiZ/rhfnagyWhY568wC5hNv9HeunuNRbfV3L2FF/++tgRA5PctBVygULsFa1nrLSESZuSICi9WPPjYKd3nbMzXvPEmsv3sJNnpG9ui33nmtc/MYDsv+5rZTQm7R+Ua2aJT2zNujkBxXlY38N6Mwl0XE8dKqo+vwKtJabUfHWte8t7dXxSsKhUJSsrfWfh3AvwHQAfwVgF8CcAOA+wC8BsBDAD7Ye3/Z7WS/H2xtbZne7CxlNPJQ82xrFa+Qtkw/tAgy3qoxUaVaIdOwtLaKWXjXFKWtevRey77PSvDDtq2n4DB8AJbmMEqHzRCLIhuYJaxHz9XfveQr3ZZTZ3mtAqvwi17ZdSnJ3lq7EcCvAri99/4mANsA3g/gowA+1nu/BcCPAdw16qtQKKwPWZt9B8DVrbVzAE4AeALAOwB8YLb/UwB+G8DHRx1liytOKbsknyJFRbpqcOqsFye17GPvfOxxj3D11Vdfcj7AX/XDo+la29hHoKWEZ+9FEmskaS+XN/6w24688FbBSYvqyufzVlNljofmkOgVW0bXwZRvvh5r5RzhAezu7oarvQ4le+/9cQC/B+A72H/Jn8a+2v5U711iEo8BuNE6vrV2d2vtwdbag5qcUCgUVouMGv8qAHcAuBnATwA4CeBd2RP03s/03m/vvd9+6tSphQdaKBSWQ0aN/1kA3+69/xAAWmufBfA2ANe11nZm0v0mAI9nT5oJo41og1G/1v8jkotFe/SIONKWTQJrn1cfT5+LnYdRjvqIWmuRLTxMoZtafWV/m6PgABTijai5FlXbWxZZj5/NQWsJJ4ZHlxX13goR8zY5hmvQ635GNfczobfvAHhra+1E27+idwJ4GMAXAbx31uZOAJ9L9FUoFNaEoWTvvT/QWvsMgP8LYA/AVwCcAfA/AdzXWvud2bZPjvpqrWFnZ8eUCDzreWQaa0bjWdCaZaVqrUhepjBaDq4RIgfdlFpx3F+muqxHplkk33xKW31/Rk6wiNrpSc+IgJOhjo7CZiNSivVpaQEsYa1lwnlMUnmWw2lWGE3A1Wot4pV+liMtKuWN773/FoDfos3fAvCWzPGFQmH9WDlddmtrywwfMNEgqtbigUMcVu0wJtUwohRaj86qQ2MeTVa2i4YBzEuQTEKMt28Zu3hZm3pEa81I3oyWMTp/ZgyRtuGlV1ttuQ4eVyTSYVWuK5fxCbDmkNFmRvep6LKFwoZgLZJdYHnLWXryCjHa48jS0/JIC1hKSz8RgcXTLniMGW/5FM96VPHWq5nnrREG+LZvpm2GVrqITb3I+bxjlm070jIiPwXTZa0VYVj7Yltd809GWqTlO/GSchgl2QuFDcFai1doG1tmRqGVymzIEl1LMLGxvFi2tdKGgFd5sTz7ViVSDes83uyaWYstKnfFx3htIikatR3hsNuO7HzAj/VHmkr2mqfUq59S9orj+sD8s8ee9ci3xFEii6OSuRagJHuhsDFY+VpvrTUznZS9mZwQYEk0TxJOKdgYFceQMUhiDc+u3KdGpkil+CNYi4n6XQRHWcILstIpe86MFsDHeG31MV4qqxej1xjZ4ZcbJdkLhQ1BveyFwoZgLaE3q7qKOMxGy/NqB5eoP5nqLV5oL6KmsgOOQ3sW0UccfZwQY4X2pH9xSkr/4niMlgpeJN9/1G7RvjyTKGNGeY6o7LmzbTNEJS8EapG/vP6m9B/Rob17maFmeyjJXihsCFbuoNve3jYlI89onsPGqkjrSU8txb19nBijZ0de/UMwxZE2RSqxc1IWudTn8xIuMueJCD6LjDvrQJziaLzcbadoB9E+JrLw86pp0fL7edTviGjloZZsLhQKLlYu2Xd2duYosLIPmLeTovCU2PmCiDI6kmZyHk308bQLkbgi+XU7T4OwtA3WLjL0XI/2K4jsZG/7lOIYmX4WsdkzodWRvT9l3NZ5vDbWugBMwpJnwKJ1yzauMBwt+e1RpzPHeCjJXihsCFYq2be3t3HttdfO2TDA/CqtMktxW105Vuwl9rBbq4CM0ket2ZEptddcc80l/fO6X7ptVMzAG5P3qTUY1iYiO3y0gk0k2b0xTqm+m5Hw3v/R8RlvtmBKEREvzVrD+305sUqDyToRXZaf/5Gk1222t7fj63P3FAqFVxTWutZbJmYrM6dl5/MsKP+fPn36kj6A+USakbSwxpI5xrOxeIz62jhtla/PiipMKcA5xX4d2X1TPMeLeMAzkjfTnxe3txKSGLz6SiZ5SRCVpeI2U655Sqkyt69wb6FQeMWgXvZCYUOwcjV+e3s7rPDJ+eUctrDAanCmDrdgCjFDwCpiFPoRWI4VzyzgcN2y4/VwFMgumaq+Xn+WSj7KXGMilrWNTSVNkGFnMNcPtJ5TdrRmrpUp35HjV9O6y0FXKBRWT6rxcnolGURmU49iGJFSomqwXrgjOiaqkgPMk2usfkRKWPnNHs2XNZVIqxEsQmSJ+hk5JTP9ZogyVr+j/lnyZpxV8j9rjLofDmfy+axzc/+WtsEhXNZerUo1/MxFDjr9jpRkLxQK66lUI8QYPTuybe6RXjIVTTJkC96eCet4tcSstd64RrjlT/CWXebtmlTDocNMaugIh+kHmIqoUpAnnRdZMSejofD9t9Zxk+9RmrN1Po2slAZ8zTOqW+eeN9xbKBReMVgrqSYihnizlNj2wDjF1fJ8ewkF1uwoEnWkdVg2nbcabTSLW+NmHCaBJdNPRCfOto2kKN8Xq+CI52G3rsPTFPieZmrZy7OmtTFvFZ8o5dUrqhL5KQTyDLJEj1ZT8lCSvVDYEByZuvE8E4sUZZqs9qKOSgJZUpThSSVgfsZn77s1y7LXnTUIqyyV9ynH6FVEvfFH8LzaU+iny8AqOMLFQiwvN0tw1paiUmV8bayl6d9sin3v2fOZ6ALDeiZkm1C+5Rnj58qK/e/u7oZSviR7obAhWEvByciWE+nJcUbLFmIPtCe5AD8xxTtWtxVw7JwTGvQ5ZdzsRY08917tfKtQQaYgYVT+yNs+JWbO+zzJa0lRq5ij3m7t4+2ZVWK5j+jZYB+QJSU9PwtrGdZabJHmmW0bJUdVimuhUABQL3uhsDFYqRq/s7OD1772taazjdVrz+mm1WBR2Sx12kPkkOM+vKSciAgychpGyS1cU89bbiq6rilhtSltBZb6KxDTK7pmz7FlkaY8lT9a0slbcDEK140cmFbojY/lWnT6mJFJZD0/3FaIaNKv5aguUk2hUACwYsm+tbWFkydPmoklLO09Z0nkTPISSazjPekTETU854kFL0wXaTOLhMCmhHii1MpRf5ZDLbsIZ/SbsePJkljsqOTzWuE6Dpt6FYo0POKV9Rwx5Jk+derUJdejx8uJVVa6qpxLtEnvfllErp2dnXLQFQoFoK1quVgAaK39EMBZAD9a2UmXw2tx5YwVuLLGeyWNFbhyxvsPe+//wNqx0pcdAFprD/beb1/pSRfElTRW4Moa75U0VuDKG6+FUuMLhQ1BveyFwoZgHS/7mTWcc1FcSWMFrqzxXkljBa688c5h5TZ7oVBYD0qNLxQ2BPWyFwobgpW97K21d7XWHm2tfaO1ds+qzptFa+31rbUvttYebq19rbX2odn2V7fW/qK19vXZ56vWPVZBa227tfaV1toXZv/f3Fp7YHaP/6i1dmzUx6rQWruutfaZ1trftNYeaa39zFG9t621X589A3/dWvtvrbXjR/neZrGSl721tg3gPwP4FwDeCOAXWmtvXMW5J2APwG/03t8I4K0Afnk2xnsA3N97vxXA/bP/jwo+BOAR9f9HAXys934LgB8DuGsto7JxL4A/673/JICfwv64j9y9ba3dCOBXAdzee38TgG0A78fRvrc59N4v+x+AnwHw5+r/jwD4yCrOvcSYPwfg5wA8CuCG2bYbADy67rHNxnIT9l+QdwD4AoCGfYbXjnXP1zzWawF8GzOHsNp+5O4tgBsBfBfAq7GfO/IFAP/8qN7bKX+rUuPlBgoem207kmitvQHAmwE8AOD63vsTs13fB3D9mobF+AMAvwlAMlNeA+Cp3rvkYB6le3wzgB8C+MOZ2fGJ1tpJHMF723t/HMDvAfgOgCcAPA3gIRzde5tGOegIrbVTAP4EwK/13p/R+/r+tL72WGVr7T0Anuy9P7TusSSxA+CnAXy89/5m7OdHXKKyH6F7+yoAd2B/gvoJACcBvGutgzokrOplfxzA69X/N822HSm01nax/6J/uvf+2dnmH7TWbpjtvwHAk+san8LbAPx8a+3vANyHfVX+XgDXtdYkX/Io3ePHADzWe39g9v9nsP/yH8V7+7MAvt17/2Hv/RyAz2L/fh/Ve5vGql72LwO4debRPIZ9h8fnV3TuFNp+IvAnATzSe/99tevzAO6cfb8T+7b8WtF7/0jv/abe+xuwfy//svf+iwC+COC9s2ZHYqwA0Hv/PoDvttZum216J4CHcQTvLfbV97e21k7MngkZ65G8t5OwQsfHuwH8LYBvAvgP63ZWGOP7p9hXI/8fgK/O/t6NfVv4fgBfB/C/ALx63WOlcb8dwBdm3/8RgP8D4BsA/juAq9Y9PjXOfwzgwdn9/R8AXnVU7y2A/wjgbwD8NYD/CuCqo3xvs39Fly0UNgTloCsUNgT1shcKG4J62QuFDUG97IXChqBe9kJhQ1Ave6GwIaiXvVDYEPx/DRGg/qO/aWgAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m4,site=dijsktra(G, [90,210,999,1609,5000,8686],4,SIZE)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DuDaq4u7RYR2",
        "outputId": "ccc785fe-3dae-47b9-b277-09c110f8be29"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m4\n",
        "m4=normalize(m4,SIZE)\n",
        "plt.gray()\n",
        "plt.imshow(m4, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "PNQIgkxFRgat",
        "outputId": "6e64d5cc-62ca-44f8-d0ba-1c7a6736205d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(m4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZFoxfzJ1iGSm",
        "outputId": "aff18e9e-80cf-4870-a066-3388db7424bc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib import pyplot as plt\n",
        "\n",
        "m_segmented=recolor(m4,site,SIZE)\n",
        "\n",
        "plt.gray()\n",
        "plt.imshow(m_segmented, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "GALqtGj57PTP",
        "outputId": "180d4c84-d547-4db6-cc0a-ed7a43bd7d6c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m1=dijsktra(G,[10,100,499,867,932,3000,5222,6310,7438,9898],1 ,SIZE)\n",
        "#m1= dijsktra(G,[999,11300,20311,50499,87321,100400,120999,150333,147777,155074,134560,30291],1)\n",
        "#m1= dijsktra(G,[999,11300,200311,400499,87321,100400,120999,150333,17777,195000,210476,240987],1)\n",
        "#m1,site=dijsktra(G, [90,210,999,16090,20999,23080,50401,87100,100800,120250,150333,195099,210700,240120],1)\n",
        "\n"
      ],
      "metadata": {
        "id": "S1xwS56OY6Qg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a19f94cb-2288-44c3-e6b6-14e3019f6bfa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m4=dijsktra(G,[10,100,499,867,932,3000,5222,6310,7438,9898],4 ,SIZE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CEUX5zzLln8n",
        "outputId": "b017abf4-bcfc-4f97-fad9-64362aad0824"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m,site= dijsktra(G,[999,11300,20311,50499,87321,100400,120999,150333,147777,155074,134560,30291],5,SIZE)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mLWje5dTiBJv",
        "outputId": "e724d482-3586-42d4-9f50-cd1d1c8b44a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m,site= dijsktra(G,[40,973,3443,8609,13426,16780,20982,67606,140902,11763],5,SIZE)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vokhEJ3UzpNI",
        "outputId": "aeed26d5-a593-4744-8c85-06a2b310709c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(m)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uv7I8a_8jj4e",
        "outputId": "f707fb14-d381-4af7-cea5-31c0987814d3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m=normalize(m,SIZE)\n",
        "plt.gray()\n",
        "plt.imshow(m, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "kLeY8s56Y_eN",
        "outputId": "a0a4d64c-b3cf-4818-96ae-9f113703862b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "m_segmented=recolor(m,site,SIZE)\n",
        "\n",
        "plt.gray()\n",
        "plt.imshow(m_segmented, interpolation='nearest')\n",
        "\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "Ej1LKd8js-6z",
        "outputId": "00a89d8b-88e4-40c1-d4bb-d0cbc6146b71"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#m2=dijsktra(G,[10,100,499,867,932,3000,5222,6310,7438,9898],2)\n",
        "#m2= dijsktra(G,[999,11300,200311,400499,87321,100400,120999,150333,17777,195000,210476,240987],2)\n",
        "#m2= dijsktra(G,[999,50499,87321,100400,17777,195000,240987],2)\n",
        "#m2=dijsktra(G,[10,100,34499,39867,932,3000,15222,6310,7438,19898],2 )\n",
        "#m2=dijsktra(G,[10,100,299,167,332,60],2)\n",
        "#m2,site=dijsktra(G, [10,510,999,11300,20311,25080,50499,87321,100400,120999,150333,17777,195000,210476,240987],2)\n",
        "#m2,site=dijsktra(G, [90,210,999,16090,20999,23080,50401,87100,100800,120250,150333,195099,210700,240120],2)\n",
        "m2,site=dijsktra(G, [90,210,999,1609,5000,8686],2)\n"
      ],
      "metadata": {
        "id": "EGIKdUOEZDYW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "outputId": "3545194e-4f94-418c-95bd-47c168ce12d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160000\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-e043616e1408>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;31m#m2,site=dijsktra(G, [10,510,999,11300,20311,25080,50499,87321,100400,120999,150333,17777,195000,210476,240987],2)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;31m#m2,site=dijsktra(G, [90,210,999,16090,20999,23080,50401,87100,100800,120250,150333,195099,210700,240120],2)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mm2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0msite\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdijsktra\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m90\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m210\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m999\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1609\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5000\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8686\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-12-27e34bf3f988>\u001b[0m in \u001b[0;36mdijsktra\u001b[0;34m(Graph, src, costMetric)\u001b[0m\n\u001b[1;32m     53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     54\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mcostMetric\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m# max edge\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 55\u001b[0;31m             \u001b[0mfindcostmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mu\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprev\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpaths\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msite\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     56\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     57\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mcostMetric\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m# reciprocal of distance\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNameError\u001b[0m: name 'findcostmax' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib import pyplot as plt\n",
        "m2=normalize(m2)\n",
        "\n",
        "plt.imshow(m2, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "HpuUiUMuZIla",
        "outputId": "d1a91cb2-a13f-4bb1-c0a5-816c6175d651"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.imshow(m2, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "fnkRUTHoBU1L",
        "outputId": "5e9190de-8d70-41b2-bc1c-7e711edb8953"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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OtYgz9KwtfDZ6tl4pgCcK1GE/1nVXLUn6n7oNL+FIr7PxKmWvqBgSDNxddnR01M3dTejuSldVhqZaRLKQl2pKZcUoHNMLYIiSGlC+3W233Tr3li1b1qobyc0W0Wklnvz3d3/3dwCAP/zDP2yV0ba8PvmdlIDup5Yi66m25Da41vYsschNNvoPtG3Ctt0bb7wRAHDIIYd0yuo1WmQOO+wwd15AfCKMch02yYPOg7I7dQVeogh9X7hOHpXVgCDOmZaaEudDsC7r2PlwvCMjIzUQpqKiYsCUfYMNNsAOO+zgUsyHH354YkCTO/92220HoAkEUBne1o8CF7zQ0ygpJT2iPPtltFuW0mtFZ8v1I79GIZEA8LGPfazVDm3lGlJbGqdyHTYQg4kueBqsck32XHjKj9Qg9+NVppSdeN/73tdVlmm1opRSP/zhDwG0k3JEYbZK6UucVkmPEIUHa/v2PSPlJXXWE1mtjobyu66lnpDrhSWXqDrQB2VPKW2XUroxpfRASun+lNKZk9dnp5S+l1J6ePL/5r3aqqiomDr0w8avAfDpnPPuAPYD8ImU0u4AzgawKOe8M4BFk98rKiqmKXqy8TnnlQBWTn5+KaW0FMA8AEcBOHiy2CUAbgLwv3u1NzIy4h7IR7adiNw0PfNC5ICwLqyOV0fNK9qGd9jejjvu2CrDNugwU8p7r2Pj8UYWyhpHrqpAbJLhPDyl5Hve855WP7feeisA4NBDDwXQjq++/fbbATRsNMUNFYmskw1ZWI6JrDrHasWEKAsP/3uiRunZWBx//PGdz5dddplbhii9c54zk45J15luzJ5Tlvceet+9vBBjY2Ovn4IupbQAwJ4AbgOw9eRGAACrAGwd1DktpXRHSumO0qmbFRUVv1r0raBLKW0K4CoAf5xzflF2lpxScjUeOecLAVwIALNmzco5584uZd1QvRM0gOYA+5KDBqlCaXc142nVVXimqygfuofIlZPtMtTVGwPX49lnn23dLwVi0DHGowi8Rmqsa+jllf/Od74DoDkSmv89Csl7SuU0Jz+VfkB3Prx+lKq9FJn2uXgBUx48boDhwxdddFGrXc8FWd8FlmFos52XDeW28JR5JRfsqE4vxVynbj+FUkpjmPihX5Zzvnry8rMppbmT9+cCeK6vHisqKqYEPSl7mtg2LgawNOf8l+bWtQBOAvClyf/XrGvndvcjNWBoK6EuqnZH9oJXgO5QVFtPc4epKcjbJdk3xxgFZtj2lcLb3HNR+yxLmU7Db+01zWlO85ldH81H1o98SRMYRa4ob5q9F8mX5FBIzW1fUVCIzdEemVYjim/rRAE8Xk575tIrBb4QUR561ed4uQwJri31E/Z5sB0NUiq5jfdjTgT6Y+MPAHAigHtTSswGeC4mfuTfTimdCuAJAMf20VZFRcUUoR9t/C0Aoq3usOC6i5QSRkZGivJ3tJN5Mp5SRN3V7QkfLKMBL5FLqR0ToXIx/9u88uyHIbrarpewQykKc7R78j/rMHVVKe86g1nILUXUzuNM9KRalrFuywyD1XDPiLra8anMS2pnNfcs+2//9m8AGrdZbYPJSgBgyZIlAJrMtDoWcmd2bHQbJleh75UdK/sm5dUAJy+Trq6hBt6U3jn2o8/DglaQXvqK6i5bUTEkmJJAGE8mYmJJpbQqO5Z22ZI8qH1Gbo8leY0WA5VVSS3s+EhtVDtLORZoghqUY7j22mtb/R511FHhOPmf9mu7fkzMSK0714nUpxQWS52AzrUURllKikgwSeW+++7rzsOClFUTW3AM3nnqe+yxR2sMSj35DL15qPuq55sRBV0RXh2l/soJeXOPgqG8hCP8vNFGGxWfT6XsFRVDgoEmnJw9e3Y+/PDDOzvdypUrO/d094somEfZdcdUjTvQfUJndOqKl/wvoj78Tgrt1eF3+gt4Oy/LaopqTUcNNKmf2M6jjz4KoPFi89I269iUk7CnwOy6664AutNe6VjteL17tn2evW7LqK6B3IbVxkfUWfuxYbdRSqkojBgAvve97wHo79y2Y4+d0ENffvnlrbKsq2fLAQ3HoPMpBVKxrCZKLQWEARNhwatXr3bZ00rZKyqGBPXHXlExJBiogu7VV1/F448/3lduMmWdPfaIiEQRzyVSWamSQk7NUJFJxo5NWU1197WsL9l0FVFYlqYUK7rwxBOa58i+e/PRwx5V6cPrb3vb27rmTPa9lFWol5smFY02JsI62Nh2NV7b9h09s3VxXy65obI9mjMpytCMRwWnHQPFQjWneaKGmiTVPOc9M9aZPXt2qwwV2R5qDrqKigoAU5A3/rXXXnNzd3tlgW5Tg1cnCtn0KH6U1cbLHBtlk1UnCevUQUrOnZiOJ3RntUpD1qdSKnL79fq+9NJLAQBnnHGGOz+goSC8pqfSeIE2nCtNVBwvTXF2TFFmVVJ0j8rpmrIMzZc2a45SMVW+edxA9HyjjC9AE76rz5XmQS8QhmuppuFSaK0GVKkpFGjeH7pXK3e5YMECAO3zFHjc9cyZM7sU0RaVsldUDAkGTtk910/7OQoN9ah0rwB/K7OTMimV1qyd/eQtV4pl834r1D3XllWKqxTeo7w6tpK7r96jiYpjYfZWO2c9YaaXvOmV/aM/+qPWdUtFf/SjH7XKcv1p6rPPh1Rql112afWtugLLLdHMRScjNfVpOW8s+o7cfPPNnc+93lPCOlrxuVJHQ07QeyfYrj5f5XC33XbbTh2rSyqZ0itlr6gYEgz8RJjx8fFiUgbd2VQG8Vw7S6epKqJz2j0Zi9ReM31qUIKlGnouXC+HENsOKTxPpS05XfTzneP8j//4DwDAXnvt1eqP/w888MBOnSg7q6dn0ZzsTMyhZe2YmEpq8eLFblnb/sKFCwF062t0TTVjMBCno2IdZsYF2noCW5fv1cEHH9y5x7PpOCfVwnucqHJ3qmG3iCwMpfPi9L2MUCl7RcWQYOCU3cLTcuruzQQMnhZezyVT+6u1f3P3jmy2tGlz17UgxWVdTV7hUdNeSRSAJlxU0xZFiR2Abo0uKQ2/62kpALDPPvsA6KYOpLIWUYILT/6mzK9JKkuJIngyLaFU2Tt9Jcpd6FGy1atXu2UjLT3QWB7Udn7XXXd11VGKrtTaC0vWBJylVFyEJmYpvRPReQOKStkrKoYE9cdeUTEkGLjpbXx83FU8qRkiUmjZ73QmiDK6erm7o1himkVKR/2UssJoHWUx1QnDa09FAG+dtK5GUHnizmOPPQagMb0pm23r8JDKfg7LPPzww1tlmFGG4sGiRYu62tIMPrz3+c9/HoDv1HTBBRcAaMxZqgSjmc0bpz4rdTQCup2DoihKe49gHjlVaHp55ZR917q2L31GfG8omnqOSr1QKXtFxZBg4Ao6bxezn5VCqVOEVeg89dRTrbKk9J4ZR/PSq9uml5FWqUSUO8xSON675557ADRBJh4XoMc7E/3kctMTc1jnn/7pnzpl9LDHyFGm1Pf9998PAHjnO9/ZNZYodp9gzrjvfve74RhKnNuf//mft+6p45PnMBMF/5QUdMrhRGY7oOE89TjnKA+fN15CMxwD3U5LGojkKT2JGghTUVEBYAoou901PTOLV87Cc9fU0zi8QBjNu6a7reeYQZmKZTV7J3dXazrj7kqKXnIwUROhl4VEodRBORZrbiRVphzO+dChxKOMPALaOtpYlEygNPGVwocjxw/NfQcAp59+OgDgb//2b1v9qMxu35USVbbwZGqlzgx5ffDBB7vq6dwoU3tcZXRMOB2wSjoBlfc9812/eeMrZa+oGBJMiVNNyeUvcszwdi/VtC5duhQAsPPOO3e1Hznt0CGH161TBil5VNeDUpYojxrQaJdJFbjTRxpl+1nb81yGSZk4Jg2E0THaz/zPxA2eLEquInpGN9xwAwBfw679lXKob7/99m4ZWji8s9K0jZK7aeQk5Vldojx+0fyAbmcdjtEL7OlFpfmO2PeM7c2aNatml62oqJgiyu5RLM8+CfhaeCI6N3358uUA2medsU8NR91664mTprnL2vusY7OX2v5KyTGUguhZ77ZMRME8OyzXh+e9K7WwgTi6lmyvJOczzRWhdumSNl7bYyZcW+eaa65x73l+ApGtXLkbj1prgIquv+eCq+2UdA+R3O1p/aPMyXw+9plFYdqq9beg23WV2SsqKgBMAWUfHR3t7KpW8xrt1tz1vJ1fZdBS0j9+ZjvUNqssZ3d33f11Z/bk2IiyaxAN0L0j667unaSq81BKUgpz9LgL7VfH0I/MG50W463p7/zO74RzA7pDhAHg/e9/P4Dm7PgoPz0Qzz/ykrPQtfSoaHTqr76nntWJddRq5CVMUa6Vcr/Hbdg51eQVFRUV9cdeUTEsGPjBjiMjI27+NGVPVRnjsVaREqyffOK33norgCaDaMlVMnKtZf/2yCIepcRsM4TGNNv6bJ+HPpay2nAMepwUHWWsMpHOIHTwoeKsFDBE3H333QCaHOr9uNaWTFYK7ZNtWDFHRRObXQZoAmCsuZSmVB76qM+K62ah66FKPE9MYx2aT5X99pxemFNB8xd4ULGjFBQVKUq7yvXstaKi4k2BgVL2tWvX4uWXX3YpSaQAouOEUn5bVqmOd3pMZC67/fbbAXQfCwzECj9eZ3CIBYNPIkcTz4ymFKREGUmxaKajaUxPl7FzJgUk1SO8ABbmhouCWzwFUETRPW6GaxcF/3ic1VVXXdWqw7KcM02KQHfmGM5dzacW6iij/VhOkWWYy5DnAqiC2Quoit5x75kph6v59qzbeOm0pNY8+ypVUVHxhkfflD2lNAPAHQCezjl/IKW0EMC3AMwBsBjAiTlnP1mYwfj4uCuTqkmEux93ZnU59KC7ojUxaQirypul5A/qnknqXZKj2B/ls5Kph2A+ccp2HoVnmKfu9B5FVG6CcyMlIJdgHYnoIsz2mJmWCSn6Cd0kIpOcNyYvuQfLfPjDHwbQUHg1WXnvEcG11AAqz4Sr3J8GWHmwx3UDjV7Bvhv6jpUy6ipnoJTdy6hrsyyX5PZ1oexnAlhqvp8H4K9yzjsBWA3g1HVoq6KiYsDoi7KnlOYDOBLAFwF8Kk1sH4cCOGGyyCUAPgfgy73ayjm78qvuWKpZVxkG6B2s77l2RnW8IJcoAKa0M5My9ZOdlZphapPtKSIW3vlq7JPcACmMPXdu8803b42b2n7VPdjxaxiscmGk9LYes8sqd1ayiujacYw8pRZoTqplu8cff7w7pltuuaVTh30yMyzbVQcmz5FFg4o8pxdyIL1g5ejIwcrTU0Sn0kRtAb4FwEO/lP2vAZwFgD3NAfDTnDN5lRUA5nkVU0qnpZTuSCnd0W+scUVFxeuPnpQ9pfQBAM/lnBenlA5e1w5yzhcCuBAAZs6cmVNKnV3PJoPgrqQaXMq8VuNK9NIUl0IH+wlN1PZYhqG0Xj/ckSkHMsz08ccfB4DOKSdAvOOXQmgZxGKDfICGEm+33XZhe1GqL2u/Vp8Cgjni7VwpB//Lv/wLAOCII44A0KSh8rTZdH0ldCwnnXRS595ll10GADjuuOMAlPUqBP0ctIzawa1ugNyQzt2zX/P9VAqvpwZ5MntE7LwgL3W7jc4DBLpDoyP0w8YfAOCDKaX3A9gQwGYAzgcwK6U0Oknd5wN4uo+2Kioqpgg92fic8zk55/k55wUAjgPwg5zzRwHcCOCYyWInAbjmVzbKioqK9UbqJdS3Ck+w8Z+ZNL3tiAnT22wASwD8z5xz0Q9www03zJbNtOyLHmNLcHxbbrklAN/cVYoiIpSV5dHEpbxvkSKOddimPXxSY+vVkcI6tkQx0PrfzrmUGdb2DzQiBKGKKI99pIhFMUGdYLx+yWar2EA23K7tMccc0yqjrPIPf/jDTtlnnnmm1c8JJ5zgjsF+5/jPPPNMAMCOO+7YKus9b+Y/oJlO3yO7phSj2CdFmegMgNJcS27RegAp22D/9shm61J78cUXY+XKlS4/v04edDnnmwDcNPn5MQD7rkv9ioqKqcOUZqqx2GGHHQAAjz76aOt6yY1S24vcHS3WJW+5Kgm9Mvpdqb2avyx6cVVe7LVntrRlvOCidQlY+clPfgKg+5hhUjBrUoryBfK7l6mG0KAcb/yqJGhmrY8AACAASURBVGSZH/3oRwCarDqeUw0p+COPPNIaAym9bZt9UqmqmXws+Fz1aHFtyxu3jrH0zPisnnzySQANJdcDSi1GRkZeN6eaioqKNzAGHuK64YYburI1d6q3vvWtALpPS3n++ecBNLK7BeV9UqNSVlCCjhjMWOPtlJpNJcr0Yl0x9XhnDcv0Mq1GThYlPQKhDjKW8lIWVblVOSC7TpQVeY2BHv3mJrfQk3S8MZTMp8wPyDI333xzqz3K5baN6AQVtktKWTpvUMficW4l/ZDWibILeRxu5Mj19NNPt+7zdwL4zlEeKmWvqBgSTInMrhlegTiLrO6cK1eu7HwmxSJlLeUXU3mVO/+SJUtadS3l5UkqiihoB2icf3SH9qioUrdIO+9RDy9Xmx2b9gU0QUV0HSXVtu1z/b1Tbe1YbV9RyKZyHd7cSiHAmledXFMp7z0RUVwvPz2vkZOLxgh0W2KIKHcf0K17KOmfWI+WCH3XPKcnu4ZVZq+oqBi8zD46OurKQrozqszlURGVPVmGtnzbpuUIvDreOB566CEAbfkIaHZ8amZtqiOV5UqJBdiOhl9ybJ5bcaRh93Z8juG5555r1aHLJTW7Vq9Aqk8uQEODPT3Lt7/9bQDAscce25rH5ZdfDqAJYPHmqJyWFxwVcT6e3NxLt0CNu/dcdCx8Ll6gU1TXK0duQPv0wpP1LELlODkWa7Vi6rCalqqiogLAFMnsPLvcS8qnKIWmPvbYY6173P1I2a3GlZpd7pQlWyrBM+M8Tzbbr8ehaCLCfmzN2n7Ju0+pWmmdOFfNPa7BNHYu+t/TXqtsS485lS+th6FSS47l2muvBdDmTJQish+eKuNRsihYRmVfT7ehnJbHgWqSjSiBiaebUeuOl3wjejbRfADggQce6IxXTxputRHeqaioeFOh/tgrKoYEA2XjX3nlFdx9990uq6lBB8qaaxYRoGFlqCBT04mFsltkx+gK6ymgqKDbZZdd3PmQ1aJSC2hMVhw3y2jOedu3KiM5VprxSq62mlXFy3FOKBvpsal0UIpYcW8sOg+2e+qpp3bNmWW++c1vdrWj49drkXNKKVuxjqm0TmriI0vs5XnXtVWHqNKRVCUnrSivn7L+kbtsCZWyV1QMCQauoMs5h66SQLfpgWW8Y2kjxwm2YZUVvRwxqIyj0s/i4YcfBgAsWLAAQOPwsNVWWwFoXDCBJhechobyvz09plemGprESg4amg3GOyxTlXdqYvLysXG9S1lztF3WJbfBfi699NKuOfeTKYjPT09xOfTQQwEAixYtCsdUUowC7edAJ69obT30SrHmBQxFlNcLhNH2NUtxye06QqXsFRVDgnVKXrHenaUUdhad6kL5iZTGOqCorKXmFTqN2HvqIKPXLSWwFNuOke0zKMdS3ne84x2tdtQUZLO/RmuvgTCeiYkydMmRgpyH5rAvQR161C3X9hc5DOm8bL62yBmoFJasp7xcccUVYX8qz6sOqLQWXs48OzZbXxOAqD7E1uGz0oCVknMZzaXqnls67Wh8fByLFi3CCy+84L4UlbJXVAwJBi6zp5RcGUYpVOQKa6HtqJxs6+hOrFwAs7/Om9dkxJ47dy6AJmCEMuQ222wDoOEyrDb1vvvua7WrrozWjVKpG3ftKNWR/RxZLyxnEjkBRW6oQHfueqU+ngOItq9lS6G6KoPaZ3b99de3xqRz9trVtdM6JecgnZc3Jq0TJTbxqHXksGR1S70y6HrvttWDlDj1StkrKoYEU0LZPY1itCPp7lfiBhTeqRpMikHtO+Up7qhMkgE0MiK1tfyv7pRejnCCOeZ5XnvpdJd+0moRmhaJ1M/qNNSeq+vF9m3IccQNeCeV2OSQAHDIIYcAaPLGM4+8F6ii8+C4mZ/ejk+5F5bls/NyqFvdiO2HsLJvr+AW274GqCiVLp0SRN2Fjr/kJ6D2e/VpsJgxY0YNca2oqKg/9oqKocHA2fiRkRGXJVRWU48mtvUj6AF33iGNkVMH2WB7BG/ERkeukhZqwqL4YFlmxlZr9Jiau0qiC7+zLXs/UmAqK2jZWI91td89BR2vKVv/z//8z1BEpjDCKgh5jwdfak5+zkfzAVhELrUl1lmVYF4MvyrxNMOS957qO06nKS9HQxSz7+Xz4zs7Pj5e2fiKioopyFRjTW9eTDHjzgnukFTQeWYoVXSoy61+BppsnYx997LBksqoCUYpuaXEajpRExMpsG0/ymLrmcZUeUelj0cpo/xukVLJluE1HtHsPTOlXjoPBvJ4pqVojKWgH3XhLbnyRhxhKbMxoRS9xE1GHKOt88ILLwBoFL5at4QoA479nUQx9YpK2SsqhgRTIrOXsqoQkbupRS/TktUJkNprXvcSZYkcfbTN0vgjqgo0LpGqw9Cx2DqU+bVdhtLaMfIUkX6dXyx46opH0RXRqShe7jUbgGL7Zh3LBWhAjcrqbMt7Zpwjx1ByxInqeHPX56jvp2cS01yAyr16Y6FeJQrVtWPyMiN7qJS9omJIMCWUveRS6OUPt2W9cEClTKWdjjJPFIhh26L8Tplcx+TJStGY1F0X6HbQKGmmtX1NkqCadqAJzWUdhuiW4IW9evOwY4jyxnvf9fkqpfTWJwK5HJuvTbXkfN6qb/Gy2EaJITxuQNdfnYOor/DmsWrVKgDd7t32cy/3cev8xYQpr776anWXraiomEZ54wnuyKp913BND9xlqfG2oZW6u9I2STmKwS3emJQbUBnPyqTaj+oTSoEwui6lhA5K0UnlLGVn31wzTbNV4pYiO7iHyDrBulYOjzTfNhyZUL8JllELDU/KBRrNN6EutdYaQqjtX/UKNjsu66tOiWPld75XtqzCe9d6nTenvga2Tk1eUVFRAWAKKPvY2Jh70gZ3KgYwlDTdhGomuQN7si53RD0vjNdJjUq2eZVn+d1SdnIMnA/PO9cx23YiTke19baM5qenfsGOhZRP86EzOMdLlaWyqK5xKZGDjtvzuotQSjQZycWeVYcJRfQEIK61p3/R56BJPL12tI7qbzzdhtr6NUDGllVoyq8oaWuV2SsqKuqPvaJiWNAXG59SmgXgIgBvB5ABfAzAMgCXA1gA4HEAx+acV/dqK+cex8oKe0IWlooXy96r0wWVU3r0km2X11RM0Bh1W0YVWcriWqUYrzG7DRVnqvSx7eoxUKW8bJbl0zkCbXZSzXTKkntOO6ooo1jlOaUo66pj6WU6s+15Jj+6MkeHb5Zyp0fZcjQm3kLdfPVZ2nGqU00UwGKhDjj8bo8i4/ONFKWeua4UCGTRL2U/H8ANOefdAOwBYCmAswEsyjnvDGDR5PeKioppip6UPaX0FgDvAXAyAOScXwXwakrpKAAHTxa7BMBNAP53j7Za2TQ8xwalchpgYM0g6gpJ5wJe9w4UJHrlbAcais17zF9OM13J2YIUXefqKQA1QELHZudB6GGHVDxZk486Falyie16xwsTqnD0gloiDsKDZknlc+ER0TZHPK/ZEE4P3pHWUYiup9TTPHL9BCJFrrv9oBTIoyZC5XzIZdjgK2uGXV8F3UIAzwP4WkppSUrpopTSJgC2zjlT5bkKgOvwm1I6LaV0R0rpjn7YuoqKil8N+pHZRwH8BoDTc863pZTOh7DsOeecgpzwOecLAVwIAGNjY5mONUB7d1VZKtqh7S4cyfeeLEo5TGUtwnNMUFmRlIZZZ7WubV+pnGcqiYIzlFqXTEDar6XmGnIaoRSiq+3bNeGaRufllSi9BrGwDctl8OSdKCx2//337xrT8uXLATTPSMeijka2PaXanusqx61cEzkVXvcofa9TiYDG9Tc6vYewnCq5yNfjrLcVAFbknG+b/H4lJn78z6aU5k4OaC6A54L6FRUV0wA9KXvOeVVK6amU0q4552UADgPwwOTfSQC+NPn/mn46tDuUpSjqnKAykSfzqlaWDizz589vtWU/qza7lNap1xlp3omdShkZzkgqZcuSGii1UDnfUgCV1clteJyQJo+IXC5tHeWOVGfi6Vki5xlN7OAh4uiAOOsrcfPNNwMA9txzz64xLV68uNW3rqWdMzP/KqfFtbVUOpqT9lMKN42sIvYeoc/Do94c32abbVbk4vr1oDsdwGUppQ0APAbgFExwBd9OKZ0K4AkAx/bZVkVFxRSgrx97zvkuAHs7tw5bl87SZFoqpdb2s6aUimzP9h6pdWSPBbp37chF1duRWWafffZpXad9tJQKKsovbstE3z234l4hm57OQSm5auO9XPORzG7dcTXJg6JkrSBKlCsKxlEZnlQcALbYYovWeNcFylF5PhmRi3MpYEh1SPzP99YG56i1IrLmeIEwvVA96CoqhgT1x15RMSSYkqg3D5EpSZ1sbN51ZfnVldCLHY+O3O0n6krdY73891Q6anvMjGrB9sjGRQ5FlmVTFlYPqiw5VahjjHfssx6AqNFjFlFO80jJZMepc2QdTymnrH5JXNN4dp0P61rlsEYBRjHkQOMApWx1KXttpCTkXD02nKJVpFD28Morr5SVoeGdioqKNxUGStlHR0ex1VZbdXbBZ599tnOPVE0DC1TJ5Lmz8h5jmT3qELnfaqaRUnZQNauROtj+IrdfjTu3YPCJp5DT78qRsG8vg0kUR63ZVEonnniuzToubdcbt7avY/TqKOekQVFeLHnE2Wg/1pzW6zQX686sVF/Xqx9lWT/ONaqo66fdtWvX1nj2ioqKAVP2nDPWrFnT2aWsHMvdlI4xkQOIZybSjJteDm/NXsMxaJCFZw4klAJ4529pVhiFt/P2OibZq8//lLvJ5VgKoMETOg8vRFfNQqq3sGYinaNSRI7FW4vIhOU5NWmdklMTQY4n4iSs7idykFG3aNtelCvfG3vkQu05iqlTjv4OSpS75qCrqKgAMAV54y0811d1k1Vtc692bBulrK+U7/W6pUIqx0duoXZsSo2jvGlA9w5P91bVOXiBNv04CZUcbmy7nrac91Qb7HEOveRJ5Sx0nICfczAK7FBuw3OL5ti47uoA5GWZJVj3qaeean23n9n3nDlzAHQ7T5VyGaplIMonBwA//vGPW2XoNOTl0LNnMniolL2iYkgwcJn9tddec09s4e4fuZt6J7OqNpg6gF6yC9BodFnHoxK6495+++2tce+7775d/WkdpVgeF0ANfaTJ96i1UgtyBXZNNVyyH42xUi61QFg9S5SyqhTWq8+Gc6PuwUurpeAYeLKKnXOvABVv/dRFuBTMwmdDXwX6IdAywwQqdu58DrqWXnKMyI07moe9NzIyUrXxFRUVUyCz251H0wFZqOyuFMeDJnm0UNs4d0P1XvOo9AknnNBqS0NG7Zh47nskS3vjp53dO5VUoUkSCI8K8RRX/l+2bBmAbv1HSc5TKu35CWg7Shk9fYtaHDh3OxY+K6WIqt0unbIaBax4z9k7B0ChfiBKnanjKNn+lcMqWV30vSklMqlnvVVUVACoP/aKiqHBwNn4kkkCiF0wvaAQKnX0aB8vj5qn4LOgiabEUl177bUAgN/+7d9uteWxqZ6TiCLKBqOusCVFl47Xi3PmNR7oeN9994V1ermb2vs6R51HydWWc+N/72BHopcI5z3TKFMM3xmbkZZzi/LF24y3KnpG4oHnthwpJ2m+s2VVMV0S8fo5fBOolL2iYmgwJU41nmlGQxH1AMaSYmJdssKwfe7iCi+TKPs58sgjW9+5y9s6PD7YUg47V72u9W37paw5kQKqRKU1BNhToKlCSKm0VV6xvnIgHP+TTz7Z+u6BY6R5yo6flJV5+tn+E0884fZnP2tmXaXoNsSVz5mu2rr+NmxW3xt1dX700Ue75hhlCeZ1KnWBxtmLUGeskovtBhtsUJ1qKioqpoCyj46OFvNo6c7EHY0UxcpMKptHbqFAt2mHJiRNNmEp1ymnnNJqgzL7QQcd5I7R9q2ynGdmVGrMdmg69Jxq+FlPq/FMe9r+ihUrusronMlRMb+ezqMkH+t4PRlby5RCXPn58ccfb/VDlHQ+npMU4CfJiGReL6OuFzBlv3uUNQpp9cyNkbu1chRePzV5RUVFBQAg9eNa+nphyy23zEcffXRnV2Leb6DZRamVpXxJeYk7mw1U0VM+2C7b8DKtElHCAoa82msnnngigMYBR6l0Ke83y3pBD1FSDMJLSMEylEFV/2EDPLgOjzzySKs/lY/tWrAdaqBVZ2LPkovcYx9++OHWd+8suYgyWlma8jXXTudMd13PQkBoQIxHESPq73Em5LqiICOPq4lCoz3dDOtzHRYuXAig0V94jkQW9957L15++WVXcK+UvaJiSDAldvYoVBTolqlI0T3KqPKfutaWgloid0c7po985COtsfRyxbRjUurgldV10O+lhA5R2ijrKhxRH9UJeJSRHILKwF44LOuQopfyyat8r9plmy4qskvrKTieTE1oWqeSXkf9BVjX0yOQ69AgIE/OL3EVel3XR0N2I10E+6zushUVFYMPcbVJ8Uqni0ReR6VEDgQ1yTbxglJPtq8niFhZSGXqiNJ4YbcEZS+V3W1ZDZ7QgAzPDh55q3lQuTUaq20n4jJsHaV8e+21FwBgyZIlrTGWvCYjrgxoniPRj81ZoaepepRd00vr2tqykZUiSkDp3SNK669l9fQY+9sppaRu9Ve8W1FR8aZB/bFXVAwJpsRdlgfxlTK89AqysJ8jU4ZVYmi+NI1f91igq6++GkDDqtFtc//99w/HpO14hwMSVJRFyqNSjjJ1X/XGr2xp5PxyyCGHdOqwb5pFI7dZO6f777/fHQPvW/Fh++2372oHAJYvX+5et+1G2WY8Baa6R2udUnYYfqfjlSe66NhK2WcIz9Rpxwg05kUvv4Jt31M+Vza+oqICwBRRdubpolMEECuGSu6UHmUFmt3Q7qCqzNOz1zyThe6UBx98cKsN7vyeO2svpwuv/Si01Y6NZXbYYYdWG8yEaqGcATkSgu16ufgPPPBAAN1HB3/5y1/ulI2cgBQetda5eaY9Kk+Za65XqKj9rM4pbJ/OKd7zpvJLFciljMBRYJKnoCOikGagodjz5s1rzVmVq577daXsFRUVAKYoBx13L5uwoFfmU0/mVepvXS3ZF6EcA3d4tquJMLx+omQVnlMKr9EpSMNiPajcR3imq2idPPmeSSs4tlJSDEXJDFXSKVhQ12Hra11PJxCZ6fS7F/wTjdHjDiJHFHXDBpp3TLlHlvGcXfTd0mQr3lgY/MN258+f36rr1RkfH69ONRUVFX1S9pTSJwF8HEAGcC+AUwDMBfAtAHMALAZwYs65+/hUQc4ZO++8M4AJp32Cu58tZ+GdmFoKpbT3gUbzrTtvFLLotROdyeZpdj2LgI41os6UVb2gB3JDvGZPwrVjtX1xTHQz1cQgVk5W2Vm/e5lcI20wE3l4jkSUh1Uu9qwt0XcvGETHqdyeNw8dtwYglfQ55NQ0SMciCn/1HHyoB+K6kDNUHQTfEaA5NWa9ZfaU0jwAZwDYO+f8dgAzABwH4DwAf5Vz3gnAagCn9mqroqJi6tCvzD4KYKOU0msANgawEsChAJhQ/RIAnwPwZbe2gDuQpeZKJXhPU0NZKkRqHeVSdycyKWOtXr261Z8nn0VBLNdddx0A4AMf+EBXnUjz6qV1ooa1ZDfWeWmgEK0KXCcvKETXuyQzRlplL+xT5XmlRqxz9tlnd+pccMEFALoTiXphyVwfaqY1CYen5dfThrQMkzvyxF9btlf4qB0ToclEPPs4n5W+p57OQ+/RQsAgo9122w1A2xXcJsFYL5k95/w0gL8A8CQmfuQ/wwTb/tOcM3nUFQDmefVTSqellO5IKd2hfsoVFRWDQz9s/OYAjgKwEMC2ADYBcES/HeScL8w5751z3ltPBK2oqBgc+mHj3wtgec75eQBIKV0N4AAAs1JKo5PUfT6ApwttAJhgbcbHxzssHF0ngYZ9eeyxxwA0bAydRwjL8lA5tckmmwBo2CUvSk0dSNSUp4ovoJvdJRt21FFHte6XYqPZj8cG854q8ahI47wsImWSp6RUsYDro26stq5mzVHW89xzz+2UjRxMVEnpge1rbLrnBqqur8rWe2wwM9tG2HrrrTuf1XFIM8R6ORT0np5L4JkQ9X3xMhxH+eq0P1vOOyjVQz+mtycB7JdS2jhNzOAwAA8AuBHAMZNlTgJwTR9tVVRUTBF6Uvac820ppSsB3AlgDYAlAC4E8B0A30opfWHy2sX9dOjtSPYzd211gvCcOuh2GymTLLjrebnegUbJYRVoGvSgLrceBYtcSElF+8mIWqISSllKwT9RRp2SEkehXBIpMdAoSCPTm+cIpesze/ZsAI3CzMtLb/Pq2bEwttxTMLIuc+mVglu0P3Wi8tyJtY6a+Cw0WEmz8tjx9xJ1lfO1Y+h1Mkxf2vic82cBfFb7BbBvP/UrKiqmHgN1l33ttdewatUqbLXVVgD8fGbc5Xg6B6k3YZ1I9J7KxR7noNlhNPih5KihnINn+ullerP3lTOIwm09bkipaUknEJnTSjJvlAevZNojoowvXp8q99t3gnnedI78Tp2G5TZ0bnoCjJoFbZ2HHnqo65733bbPe8zYS1OoFzzTK4zbG7+ul+eOq9l3I1R32YqKIcGUhLgSXlIAymGUtbhr0SXQ4wYIUjJPO6k7JndI1ZZbaLBDr8yuQLfsFp36qZ/teEv55JUL0LY8iqJlSN0ixxPbjlJTT3OvcnIpQOa0004D0Gj1I32FbUfnoUFMXj90mlJHGY+D4/hJGdke5XuLSC/Uj0OXZqT1nhk/U09A7qXEwek8IlTKXlExJBgoZR8bG8O2227rUoleGmLVvNvP/P+JT3wCgC9L6lllF154IYBmlz355JMBANdff32nTpQUI5JngW5qHGnE7Zwoc/IET5664oV9RqGh3poqh9Mrdz7Q2J95Eo+eD+6FuFJO9QI7gLZtXqmZjskmNCklefD6AbpPYlWuw5uHjo0gVbVZbnWOHButCqV2o7PwPM4t4hS8OhrYFKFS9oqKIcFAz3qbM2dOPvLII11ZVwNeol3Ko+y7775767snu/AM7A9+8INuu/Qus7LcokWLWu29+93vbo2NMp4GRwDd8is99LyxcdwamELZ1CKSyzwZrlforyez6/ngHvdCkIoqZSfOOeecrusaMqsWA9sPuQtN2qnvhp3nypUrW32qzkH1IfaahpGyLmVtoB1i7c3Z+z1x3LpO3pzVazJKxsGAHsWyZcvwi1/8wn1JKmWvqBgS1B97RcWQYKAKupQSRkZGXNOGsjZRkIi2BwAPPvggAGCnnXZqXbcs0O/+7u8C6HZOuPLKKwEAH/rQhwC02fhDDz0UAHDjjTe6/RLWxVHZPFWeePHgOl5V5HhQRY5n7iI7GuVuI7zsM2p21PtAo5TiPM477zwAjdnLM3NpHLuidFQUv3ONPddSFV1UxIocl+w11vGOzVIRVMUQz1yoQVaRc41+tmVLTjXWHFt6Zyplr6gYEgz8YMc1a9b0dZIKETmyAMCCBQtaZSNzC/sGuk1wRx99dOu+pwA86KCD3DKeg0XkDtrLLAI0FEvb8OrqfDwHDQ2S0TFRwWipRWRa8pSqvPe5z32u1R8pGRWMJWqj/XkuzpErM9v3KK+aQDUzsOfCq4dvltad6OXe6pXRZ2bfUyqqWYZ5/PTQT+u8Zee2XplqKioq3hwYKGWfMWMGNttss85360ChlISyEHOOexRS5fzo3C37OaKwJRfbyO00ciLxxlLiNrQMZVHNw2fHGbXvITJJqn4BaPQoHAP77ifRgsrHXtinypz9cD4RR0V4OocokYbnHq3BUNqWRSRTK0XvxxHK41h0bnS4Yp3tttsOQPudiE5GUlTKXlExJBi4zL527douxwogDtnUMEdLLSLnBJbdZ599OmWjdD9RRleLSPuuMhjQULcoLZXXrs5DM5V6oYvW0aMXNK0ToZpkoHHqUA6CLqNe8BKzx372s59t1Sk5SEXPzHP3XRduLLJk8DvnR4cgr4xyA7Z/DZ+OXF+tpSBKS+UlZFE3WbbP9GyeA5eOLbxfvFtRUfGmwZSc9eY5+XNXIuVWCkN4CQmVSrD9W2+9tVOW9/bee2+3bCmljyZfjHZqW5b/586d2yrj2VRZlu6hJSjHQJRScWldrWPP3It0Ap4sGp12wzJcL48L0bJeklBPs+2NrUQZ1aeDSSa8fqKx2bPquD7kdEjBlXvyuJFtt922VZZh2xb0FYk4UY9zsdxutbNXVFTUH3tFxbBgSth4mjq8eHbLUgLlrCee0s7CsjQRO1qKYtI+1SxIxZmNTiMbtmrVKgANW8l+rIJFxQCNQvNYW1Uocgz95IiLnF1svLYeUFjKVEP82Z/9Was9FZG+8Y1vdI2JMe7MllqCii46Z8u6e8cvAcDSpUtbdfpx6CI80x4z60ZKRKtU1XVmXR7OSMcZ246uf8mN3LpkVza+oqJiakxvhOfAolSnpGRShRnhUR/ukIsXL25d32OPPVr92B2TO7BSSDXJ2NNFlAJSCUOq6pmu2B4VWRwrlZReLjTNt+ft6JEST5WfHrdBaKZYD5zTV77yFfe6F9zCsdBJxFMAMttrFGTimT4JpeBve9vbAAAPPPAAgPbaaJ5A5Qo8LiAyn3lKQ17j+6Scm0V0yKTm27NjItf4epwIU1FR8SbAwENcR0dHXWeLXpS8lAHV6wfoz42V/++8804AwDvf+c5O2chNVimJpbykhJG875l8Isce77pSdHVQIvUAGk5BnWdICUoBSazD9ihv2udDDuFv/uZv3PGy3bPOOqtT50//9E8BdJuo+N265erpQHrENUNpLZVWpxO2/8wzzwDww2LVEUr7szoNZojRNYxMZbbdKFuuravBUOuSmSjnXANhKioqphFl1xzkCi+DppYt5RFXcAdcsmRJ1xgJpeCso6d+ehpwBvxwTN4Zc+QCeiU1sNRaQzW1LU+23Tvq0wAABi9JREFU1vaVgnkyL8df0sJH586pA8gXvvCFsI4mZfDy7uk5eSXqpeG8UWirlZfVmqPUtRSoopYU71lqn8pVWp1BFFATJRPRMVVtfEVFxdTY2UuhobRPKvXnbuvJl/3kaPdkZm0vap9QN1CPImr7SiUsIhddnY+nzdaQTcLTyCoHUTqfndll1f/A0wKzPeoGSME///nPt8bvJQTRU3W1H9s+oZSWpwbZ9VEuIAqwKulzIt2Jfrbt67ysnT3SE5FbtfNU/UrkKmyfez8p3IBK2SsqhgYDp+wpJZfKahhnv5TYQm3OdoeOdt699tqrVddLjsEdWNMWcUe1p8kqRxKFTWpfdkwsy/48za62W5IV1QasoaEe5VV4lF3txaTovc4Jt32XEimqhaYf6qxcka6LV7dXKjFLRZlMgnXU49M7fYf17dnzEaKELMrBeZxD9aCrqKgAUH/sFRVDg4Gz8TNmzOg6Eglocmopm64usaVAFQ0W8I7lJSJW07JLUZwzx7L99tsDaHKYAXFWU89pSB1L+skXT6i5iOtknUoi5VGJTY3G4LH8uv69ssEC3UdCsW/vaKco442auUriGgNtVKlqWWqKS9Gz8sScyAlMy9l2oyPGLbRPL1uOflcxLUKl7BUVQ4IpMb15n1VBp0oTLw8bKSOdTpSiWNdIvced8fbbbwfQncHG9q27uAbNeBljI7OgbT9yEillYonqeAo63fGV2+B3m/E3chohJfQyBbGMmkc9qkdqxntUeFnHoWiuOmdPGcb3hOvBAJj77rsPgM818T1he3R/9kxx+hwjLswzp+nYiJK7cmTq6xWW66FS9oqKIcFAj2xOKT0P4OcAupNvTU9sgTfOWIE31njfSGMF3jjj3SHnvKV3Y6A/dgBIKd2Rc957oJ3+kngjjRV4Y433jTRW4I03Xg+Vja+oGBLUH3tFxZBgKn7sF05Bn78s3khjBd5Y430jjRV44423CwOX2SsqKqYGlY2vqBgS1B97RcWQYGA/9pTSESmlZSmlR1JKZw+q336RUtoupXRjSumBlNL9KaUzJ6/PTil9L6X08OT/zXu1NSiklGaklJaklK6b/L4wpXTb5BpfnlLyT8+YAqSUZqWUrkwpPZhSWppS2n+6rm1K6ZOT78B9KaVvppQ2nM5r2y8G8mNPKc0AcAGA/wFgdwDHp5R2H0Tf64A1AD6dc94dwH4APjE5xrMBLMo57wxg0eT36YIzASw1388D8Fc5550ArAZw6pSMysf5AG7IOe8GYA9MjHvarW1KaR6AMwDsnXN+O4AZAI7D9F7b/sA0Ub/KPwD7A/iu+X4OgHMG0fd6jPkaAO8DsAzA3MlrcwEsm+qxTY5lPiZ+IIcCuA5AwoSH16i35lM81rcAWI5JhbC5Pu3WFsA8AE8BmI2J2JHrABw+Xdd2Xf4GxcZzAYkVk9emJVJKCwDsCeA2AFvnnFdO3loFYOug2qDx1wDOAsCIiDkAfppzZqTKdFrjhQCeB/C1SbHjopTSJpiGa5tzfhrAXwB4EsBKAD8DsBjTd237RlXQCVJKmwK4CsAf55xftPfyxLY+5bbKlNIHADyXc17cs/D0wCiA3wDw5ZzznpiIj2ix7NNobTcHcBQmNqhtAWwC4IgpHdTrhEH92J8GsJ35Pn/y2rRCSmkMEz/0y3LOV09efjalNHfy/lwAz03V+AwOAPDBlNLjAL6FCVb+fACzUkoMW55Oa7wCwIqc822T36/ExI9/Oq7tewEszzk/n3N+DcDVmFjv6bq2fWNQP/b/BLDzpEZzA0woPK4dUN99IU0EJl8MYGnO+S/NrWsBnDT5+SRMyPJTipzzOTnn+TnnBZhYyx/knD8K4EYAx0wWmxZjBYCc8yoAT6WUdp28dBiABzAN1xYT7Pt+KaWNJ98JjnVaru06YYCKj/cDeAjAowD+z1QrK5zxHYgJNvIeAHdN/r0fE7LwIgAPA/g+gNlTPVYZ98EArpv8vCOA2wE8AuAKADOnenxmnO8CcMfk+v4/AJtP17UF8H8BPAjgPgBfBzBzOq9tv3/VXbaiYkhQFXQVFUOC+mOvqBgS1B97RcWQoP7YKyqGBPXHXlExJKg/9oqKIUH9sVdUDAn+P+D3UZgxh4TaAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib import pyplot as plt\n",
        "\n",
        "m_segmented=recolor(m2,site)\n",
        "\n",
        "plt.gray()\n",
        "plt.imshow(m_segmented, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "S_n0jU_0ZjnO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "outputId": "0ced998f-def7-41d3-d1b6-391d12ae3729"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m4,site=dijsktra(G,[999.0,11300.0,200311.0,6000.0,40999.0,106550.0,78320.0,160093.0],4)"
      ],
      "metadata": {
        "id": "8Eht3x4uBHTl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "56c2f1a7-9a76-4526-8077-56769c696ca2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "250000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(dist)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 164
        },
        "id": "o08Z0VhP0dqI",
        "outputId": "5bdfd202-11ef-4120-a950-ae43c89996ff"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-21-a07ecd6c8733>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m: name 'dist' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m4"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RzG6wkXAIb27",
        "outputId": "589da00f-656d-4c80-fb90-c02a67a73485"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1.3690e+03, 1.3050e+03, 1.3780e+03, ..., 9.2000e+01, 1.0400e+02,\n",
              "        1.3000e+02],\n",
              "       [1.2840e+03, 1.2830e+03, 1.3480e+03, ..., 1.1700e+02, 1.7000e+02,\n",
              "        0.0000e+00],\n",
              "       [1.2760e+03, 1.2790e+03, 1.2590e+03, ..., 1.6000e+02, 6.1000e+01,\n",
              "        5.0000e+00],\n",
              "       ...,\n",
              "       [1.4790e+04, 1.4744e+04, 1.4702e+04, ..., 2.5041e+04, 2.5075e+04,\n",
              "        2.5133e+04],\n",
              "       [1.4848e+04, 1.4780e+04, 1.4840e+04, ..., 2.5069e+04, 2.5062e+04,\n",
              "        2.5097e+04],\n",
              "       [1.4886e+04, 1.4839e+04, 1.4854e+04, ..., 2.5043e+04, 2.5087e+04,\n",
              "        2.5161e+04]])"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib import pyplot as plt\n",
        "plt.gray()\n",
        "plt.imshow(m4, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "82HIMwdwCAvz",
        "outputId": "3d787995-a2b1-4d0e-b169-83ec60f3f913"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m_segmented=recolor(m4,site)\n",
        "\n",
        "plt.gray()\n",
        "plt.imshow(m_segmented, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "z_PJmhUXJEhG",
        "outputId": "7518d612-9d26-4fd5-ad73-19006ad6b897"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m2,site=dijsktra(G, [90,210,999,1609,5000,8686],2)"
      ],
      "metadata": {
        "id": "w13r7dSdCPz4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.gray()\n",
        "plt.imshow(m2, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "yZBibdprI0a4",
        "outputId": "b2dba5a0-8e57-4c16-e70a-ca541dd11c5b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m2_segmented=recolor(m2,site)\n",
        "\n",
        "plt.gray()\n",
        "plt.imshow(m2_segmented, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "p8nWeEzmI7bp",
        "outputId": "14e8e1a1-66b1-4dee-ad0b-1d3b4c606221"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m5,site=dijsktra(G, [90,210,999,1609,5000,8686],5)"
      ],
      "metadata": {
        "id": "xchU6F6dJNit"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.gray()\n",
        "plt.imshow(m5, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "c_QdAuKYKxrI",
        "outputId": "0a77458d-d761-4431-e3b7-58b56e861eda"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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1R87feOONk9d4LrbIxcruLYEOlmL6OEnnxz/+ceO3HgeL3l2CYLxALstAp9W9tWvX4uGHH95+11spZTmAowFcBWCfWuuG3qmNAPZxrjmzlLK6lLJa9jJLJBKDR2cDXSllHoD/APCPtdYHKFyvllJMllVrXQlgJQAcdNBBVae4ashK6VXitDbxiwIlejSbfxN9APoNOFY/vHGkFbDBSSzs9oo4pCfdWNyOa6hLm6OPPrqv/2OOOabxW8Jj5T7Pe97zJs9F7kuPbi+BJ3Kn8W/LPdjF1QYAhx9+uEujQGrYWwlWLKHJfST0tgsH5r60C5T7bUvz1dd4xmDL0NuGTq1KKbMx8aFfXGv9eu/wXT3xHb3//YDuRCIxdLRy9jKxxFwAYE2t9TPq1LcBnAHgX3r/f6vrTa2Vsuv2wlZQipdQoH+La4Q5SFQvzbMfCG1WmClXQGX9zJI25BpxWXG4b1TkI+pfwGONarcxp5KED9Hro0ILbEOJAnE8nVTDe/ZRWizbXqStBPhYe/FJkRKhhSUfTz/WNJ544omNfjWNv/jFLxrHWO+25on3nRNY25FrKTh0+blnprACwBsAXFdK+U3v2P/GxEf+76WUNwO4HcBrOvSVSCSGhNaPvdb6UwDecnHydG84NjY2LeusZVkXtKVFaqswSwpSpkiMhhGHYbBl1NrLjPf16tK/t4NLlM7oWaije3reC31OxrR69WoAdgkuadO2k6lFvxdAZCUKeddadde9wCqh3yo6Icee/exnAwCuv/76xnEJ6gGA6667rkFbl8QtkY4k7FZsJBYXFinAe08sHb6rRy3DZROJEcFQildYlmlPj+GVWK+gfE76E9137ty5k21FZ+fCgwsXLmzQqFfU++67DwCwePHiRpt777238TsKy432D2vj9pE/tkvpKub6LN1YKaLip/csxrqtWJxlvrn/SPIS3Vqeh/ShdVSuy8+6e+Qz98JmrWuf9axnNdocddRRjd96zJ7kGe2yI+ckhiFKzZU2v/zlLxttIskhkn41krMnEiOCoSbC6JWfLbhd9hhjv6VcI9xCr3Say2sIx7c4pKS9MnfgpJYonZFXb+s+VkKH10eb5yGylnNbwW9+85u+Np60YXFr1ueZFm07kTZs8baiBnnfei9RRV/jpR9zKXI9195YLQ7Mz897ZpqmKIYDaOrh0v9zn/vcvn70eYnY02jT3ZOzJxIjgvzYE4kRwcDF+LGxMTPwwDNGsavBEo+84JouddfFyCRtJUQSmFIH9DEZg75vdI7VE8t14oVrCqwxe8ETOtCHDWYC6V/cSNY88RyKCKoNaDIvLJLzs7TUNQHXZ7NEahHnBfLMOHBJ35Np8baI1n97KpKm+ZnPfCYA4IYbbmiMLQqFZYMlvxvWNtte/T3Op+fxR0jOnkiMCAbueps1a5a52whzEi/AxDrGHMwKB/VcVfx7jz326LtGOIu0lWqk8lvvfCL3lkAMCdCwdo/hnUGYpocffrhvHFInXiDGL2t+2HDJcyxBJJqma6+9ttHGSkASSAqo0CAcVzi+Fegjc8n13S1jGFeI9fb205yYx8yhzVaSjpxjCcWStHgOJQmH561LApFAP1+WDJnTn3TSSQCaBroXvvCFk22lXqKF5OyJxIhgoHXjDz744PrpT3/aJoRWTC+s0lplOWnASpjwqn9GLj7mHNKW631rmjwbw29/+9sGjdbY2JZhBYB4ySdcA02PSeiVa++4447Ged2/uLk4yceipa1SbGQzYdsD20V0P0ILS3Bc+w7oL0rCtAqsFFF+vhb9rEN7/UcFNdgmYLn2OOyXpQ7r3qUUXHTRRdiwYcP2F69IJBI7LoZijZ9OYQTWRaPKrh7X1v15XMe6H+t9XJJI9M8o4Ef6kBDMNWvW9LVlvdizylvj4Oqm1jXiVZB+DzjgAJduqeDqeUescF9GVGLMK8zBujwwFQglYxauzQEy1jNjDsw2G2t/OznGQTBRXXamQeZPX8OVeYUGkSAsqcxLAbZoekKLVyQSiR0fA7fGe6GlbaV7oqR8TjkVbIs9wipoySWCIm7Heiz3IRwemLLUe2mrkc7L+qpYxqM5FWiPA1/Dks/2lJriPjU83Vf71Dk8mcOhZSdbDU9Kmg5NXfa3E5pkh9ouz45tAVbsBccDSH/imWHPkO4n+kaA5OyJxMggP/ZEYkQwlI0dRdzm+uJyHmjPR7aOsfGiq+ECmDLORBVxvK13LXcdG4Cs7Y0k8EaMdl6oZ+RCjGroebUAWNS0qtcyvVa9PY8mrvFvqTksrlpiL4vaoqrIcclKtPqXWgT8zKzn4NW6s8R5fiZeHnsXFdJyEfO34bmILXfd1q1bw/smZ08kRgRDdb1Z4awCz+hjbS/s5TBHHNercmMZOaJQSyBObpEVmWvN634OO+wwAMDNN9/cuIbHo6/xAliiKq1MvyTC6PF4UkyUO84SVnQNz7snyfHfuk3EXYUm2bhRDFssSVg16Dx3l56fu+++22wTST6e4SySPHk/AI9WoFsdeiA5eyIxMhiKzm7pad7uIpE7gVdXWQ2t1Equ584c13KrebXbPClBt2FY3J912yOOOKJxXkIuNQfgVTzaF44htIkEYUkqMiZ2Q1nppOzqZE5lcRxvLzy+r6aX3Yye7US3kf/FzShuOoubttV5i0KoOX3VkgZYKo1q0PH8tFVQ1m3bOHxy9kRiRDCUoBornJVXV8+CbIUJesUZdHVSr843J89Y1WstCyjQr8tHiIoaCJ0cfstVTvU5oVcs+ZJqqedHgnYEEsrpBczoY55+bHE5nruIG/Gz4iSdKNHGs/Jbteb5WUkVYYuzS7VgnheL8+63334A+iWpP/7xj+44WKpjrq3nhIuEdNHHM6gmkUg0MBSdXRCl63mprZZOx2meUYIKW3B5ddVcyVtVrUIUTD/DSidliYATIjiBRYMt+Zb+zdxe6qN/4xvfMGkE+uMNOFxT988c0PNWWCG8ci2ntlqVVttCdqN0VU/60Nhrr70AAJs2bQIALFmyxKV/48aNDVo4tsPb610fY04fWeXZXmTZFyIPRuM+7plEIrFTYeCcfXx83EyC4OJ7nh5uXcNtrd1FuB/2r1t+Xo+TeIU29DEv0cPaBcdL1rDG4VmMLY7C3O2b3/xm4xqLo3C8gXBeSTd96KGHJtuyJ4C5dsSxmBNaaIv4i6Lu2G4QFQQRPOUpT2n8tqLt5J4iDUhRkmOOOQbAVA1+yx7VVj9e9+8VNrH8+d77w0jOnkiMCPJjTyRGBEPZ2NELrACmRB02VkVGKhbZLNePJy5GrqW2PqLcbhbHLLGVc695WymuwQbY7hrArnbChspTTz0VwJQ4b4nDbCCVarbyW5JRNNh4aiU4MdpUGIs+Fn+t6rxeeCn3Hxn1ZDycjAL0i/pHH31047cl+h977LEApjZrlC2b5X66Umxbgo11XofQpoEukUgM3kDXtvqwIUU4AFcYBfpDOr3AGbkv4KeyWq495sZegI/uy0uIiDg7r9rs2rPcXR6iBI8rrrgCALBgwQIAwIMPPthop/tn416by0cjMrqxEY/76FLvjWnRUg3PqecmjeoTRsk5bCjm8UjIs65ALOeOO+64Bk1y/MQTT+wbs/T/85//vEE31+Zn+iIkZ08kRgSdOXspZRzAagDra60vL6UcCOBSAIsBXA3gDbXWR6M+gIkVi7k1MLViSfCGp9drfdBK/geaYbL6vkB/XXEJXLHgpZF6HAfo57ycAqm5Hksk3o4kun/m9pzaqudL5or3BxMaZexWuiQnbURBR23SRhdJzpJieI+3Nm6t6WW3K9tOLNeYJ3VY+rH87+1AY4HfBe/91TSsWLECAHDllVc2aH3Ri1402VboW7VqlXtvYHqc/Z0AdB3kcwB8ttZ6MIB7Abx5Gn0lEokBo9OOMKWUZQAuAvBxAO8G8AoAmwDsW2vdUko5AcCHa60vjfo59NBD6/nnnz/5m3dWAaZWLh28AfQnrvToAtC/uka6ljE2AFNcLtofjvvtUvYqCh5hbuntuqrhcY4uettPfvITAP0cOQqBjQo5MGcS3Zlp0XYQz/sReQa8OvRdEm94/qOEG28O9ZijJBzdh2U7EXg7/Oq23rvFZcOA5vt/5pln4qabbjIH0pWznwvgPQCEqsUA7qu1ihy+DsBS68JSypmllNWllNVSFyyRSAwerTp7KeXlAO6utV5dSnnBdG9Qa10JYCUwwdl7xwDYvmHWi6PEAr7G27U0up6LWFjWdNbredWNdHaBJW1wUQbPJ+z5VK3+r7rqqsljou/xtTwOy8bRdg3/DUz55OW58m4v+l68GwqnGuu/Pamsi2Tl7YYaeRX4OVgpwF4KtlVMxJtDK37AsmdpWLEXXa3xXQx0KwD8bSnlZQB2BTAfwOcALCylzOpx92UA1ne6YyKRGApal8Za61m11mW11uUATgPww1rr6QAuB/CqXrMzAHzrSaMykUhsN7YnqOafAVxaSvkYgGsAXND5poFBRcTpNqNJ1F9kdBSRUsRJr5aY7sfLupK+LKMVZ49Z4+CMOw4HFVHXchMJhN5f/OIXff2Ly41ViyiH36sYG7VleIY1PSY5JnNoqXQyH1zfLYIXVMPG3Cjf3FK5uH/uhwN8tOriqQXW9k/eWL0sSo22uvHT+thrrVcAuKL3960AjpvO9YlEYngYSiKMQK9ezNG9JIgoh9kLSgF8g0oU+upVWpXjUd68F7pr5ct7XMfiEl49sy61yvg+YlCzjEkSSitYvHgxgKmdVoCppJA///nPjbY8Lm0A9Fx5QosVLsvJUV6os4ZX7dUKfvE4uSWVee8N96GfhxjTZIxMv1WDjiH0yndiScdjY2OZCJNIJIaQCOPBq/rKLg0rtNMLetEcl91LXqJHlz3HmNYuNdCsfjkd0uNCWp9tS+yI7AesL1sBHHJMKrFwaKdUadVgbsY0ai7qJdZYqbssxQhnlLncvHlzH/3MGYV+3lPAmicvZTpKZfbm0kq04V2BrAApz+bDc2klL7XZt5KzJxIjgqHuCGPp1Ay2SkZBHREXFb1XrmGuYIW1egkRwmkt/Y+5RKQrCnjswgHkWqlJDgBPf/rTGzQJJE1Sp0Qy3R7n0uAUYG6r54eDgjzvheaMFrfX1+gwaebGvCuN1MUTjg80bQr6PpGFnWniQByLs7NFnSVRfY0VQgv070YU3TvyREQ7EGskZ08kRgRD2cVVyvL89Kc/7TvP1s6XvOQl5nkA+P73vw/ALy4RhSwKV2Adz9LlPN+zwLKmsl5mWc1ZtxUaNadimm666abGMW+3VYte5lxWKLJXudWyaXjptlGyiPeM5H/Zm80aE1vYLW4nhTkkVZphSTc8h8IprZBVtnt49iINfieYfj0OT//mZ2VJG8nZE4kEgI4prk8UxsbG6i677GL6EiUCzPNLv/jFL+67Rs5dfvnlAOIa7d7OGlEKp2Vt131ZcydJMx63iBI9ppM6KzuxekUq9d9yjq3lVgQXjzUqjiH+dY/TRjYCj9tptNWf5/Exffo3W7etqESOl4iiOL0dbKN4Ci8pJ9LvPW+R9ZwB4E1vehPWrFmzXSmuiURiB0d+7InEiGAo1WUFWtSR3Ov58+cD8MVtjR/96EeN3yxKWRU++d4sXmvDTluih3We1QKuDW+JX55rxhIJ5e9DDz20cR/BDTfc0Hd9ZIQE7KAdAdfss7ZC4mQQ7ssyenoba2qVguvPsytOaLMMjPzeeKGwfE8Nyx3LqomnHliG0raQbf239+5Fqk0G1SQSCQAD5uy1VmzZssV0YcnqKUEVnD7KYYT6mKx24iqRa63VsY3j6qo0QkuXWmc8Do/rWVyCf0dBKXwfwfXXX9/X1uNqUdKMzKE3VitgifvjObDgBdVYbXgeOHkm2sDT43YRbRJw1aUmoBfYZUkzfO8oDLeLkbZLfw1aO/eYSCR2aAxcZ9+6desk19Dcg90TsuMFu7I0OOBGOIzsnaVXdS/ZgVNrdSAFr+wsQVhcQ6QBGY8E71h6vlegQGiz6qV57sAIXhgx30/3y8U9Ik7p6d3R1sre7jqWruvtUmPNaRdXlb5WXy8SQlSJtuvuMZZk1CX01UvxZsnWqi6bnD2RSAAYQvGKWbNm9RWDAPpXf/6n0GIAAB6QSURBVE7W9/oD+rmc3jtLIEE7zJnEwsscXtMkUkYUDMF0y32kX7YkW+CEhmilFlrWrFnT+K0lEy+ZgqUbKyzU00U12sp2CSIbARcn0fo3X9fFmu0l2vBc6r5Zely0aBGAqaQa6znwsSiM1dPDreqy3NabU6vISikli1ckEokhWOO3bt1qhld6OiHrXnpFE/8wcyprdXvuc5/b+C1tJCXU0muZS7SVDNJj4pXYklDY4+Bxn7Vr1/bR5F1j7SXn7VpilVBizsLWeSvct60klh477xnPtgHd1tu/XhDZEVjPjwpUtNWC13PM9hrPXtFFEhJExT34OCfiAE3PT3L2RCKRH3siMSoYag06y/3h1UkTWAEUnuhj1VZjteCkk05qXHPFFVdM/t1W5y2iRRAFZvBGiGzAufXWW/uOs0uGq7dYBqITTjgBwNS2vwJpq8OKmSYv+0r/3eaO0vn5bdmGVv/ec7AMtJ4qF4U489ZfkbHNo5dVI+uZeYFKUdCUR0uXWol9tIdnE4nEToOhcPbIiMCchQ06emVu2/TRMhwJF2PDinD0yJ0mHIBpsfLBrWqpTCtzCTFWCSeUenMaXk0+ay4s146GdY0EAUlCEHMq3ReP1Qtrtehl46GV4NH2XCODrJewYo3Zc1HOmzevr18JpfXcvlHAjJcQY3HpLmG4fK4NydkTiRHBUKvLWvW+WR/jeu9av+TVzquJBvS7Uzg18YUvfCEA4Ic//OHkNd4qzdwoCrqIAnA8vZV3gonCNSPOyBzdCzO1uKlIF+wyjBI8PN3aqiTDLiorAYfrrQuYM0bclAOGorp7ntSkU4BF8pFAK34H5X21qvCyfYVpAvp3H/IkRCtVPFNcE4kEgCGEy46NjfWtgkA/R/f0G73KeztscN0xDS/BRnR2K/TS6z/i7F12FYkSLoApThDtSxbtBnLttdc22nD/VtGGaO74Gi85Q+iOUoz5fl2SZXjsVl08rqTLEhzvcKOvZ88JS5u6bZvko58H35PpjkKcGVx0ZTpIzp5IjAgGrrOPj4+bVmLW72TlYmuqxXF4BY58kBwGKivl85//fJdmXm25f/2bOewPfvADsy8N5lQsFeiVn5NleN6kiIU+5kkOUVktps3Sdb358Diw1Q9LSZaE4nEx6xouM+ZJKNY4WPcV7q1LlfFc8o6+AmvMXWrMe94bfs5WCLLX5yRN7plEIrFTYeA6++zZs0P/InN95h5WoopX79ta1VlP6qL7tCVgRKvpKaec0qDpu9/9buv92KIb9S+03XLLLX1tvbmMIg253yjCTcDcRzwmlk3DG4v2sggi3R+wd0PlZy7PVzihtS8ac1zh6Nb7w++WF0mnwfEI7BGyoga939bxyAffoD08m0gkdhrkx55IjAg6ifGllIUAzgdwBIAK4E0AbgbwFQDLAdwG4DW11nvb+moTNVg05q1wNdrE6yiMle9jieTRlkHeWNiNw67Dl770pX3XiBGPE1Pk/nfddddkW6GBt3W2jHALFy5sHLvnnnsAAE95ylMATG0FvWzZsslrNmzYAKBftLXq7nk53V0CQNgIGdW2YzcjVxeycrv53pHozEY9Dou2aON3jF2Wluohhj5vuywLotIJjVbyUld05eyfA/BftdZDARwFYA2A9wJYVWs9BMCq3u9EIjFD0crZSykLAJwE4H8CQK31UQCPllJOBfCCXrOLAFwB4J9b+sL4+Hgfx+Q2gM/RLS7BhizLQMfGHPktoZByP2tLZUHXyixAv4vE4mjf+973+sYETIXuXnzxxY37avBKbxkw2bi2zz77NGgRjm4Fpey7774AgDvvvNOlwQoK0WO0DKhsnGXXm+WyEnCILT9L3Z88I+GAEkxlcUbP3SiQEFlgijsz/eyCsyRErqrMY9fH2I3MgUv6HbTeXQtdOPuBADYB+EIp5ZpSyvmllLkA9qm1bui12QhgH+viUsqZpZTVpZTV0yl/nEgknlh00dlnATgGwN/XWq8qpXwOJLLXWmspxVTGa60rAawEgPHx8bp161aTo3O4LHMLa8tjr0CBxYVYh5YVlOvAWUkJAtb7LXeUJ4nI/zoYwnOZcDpmm51D02a53jggIypIIdxf5mv58uXuPdevX9/4zYkrXcJx+ZlF20cLWIKz0lVZz5fnHOnUXaoH8zHh+rLv3OLFiwFMVaa1+pPqtbLldfTOcdVdy36kA3qid6ULZ18HYF2t9are769h4uO/q5SypEfAEgB3d+grkUgMCa2cvda6sZRyZynlGbXWmwGcDODG3r8zAPxL7/9vdb2ppb966ZiRFVW4gLdzi0abChFZg71+o6SFth1gAeDkk09utI3CcAVeeKklzXjhmZ6Eov/mJKOIJp4nDkqx5sKTjrREx6HSbEOJ9mtjqUb6tazYbFeJAmT22GOPRr8C4fByjXBvq98ugUpMg9DP49J/t+nsXSPo/h7AxaWUXQDcCuDvMCEV/Hsp5c0Abgfwmo59JRKJIaB00QefKMyaNavOmzfPXDk9/ZJ1Oqvet7fCR+V+PC5hJUjIys8cKuIsHi2Wn7oNehUXKebSSy9t0HT66af30SRj/MpXvtLoj+9rPYcuksm6desa11g6NNDkXNE+edzW83Pzs7P0/C472vA5j8Pr+zFNnvSnaWor1yXxD9Y5gUgk3l7ycu/Xvva1uOGGG8zBZgRdIjEiyI89kRgRDKUGXRSg4WWUWa4rrmrKgQdW7W4OQPBqeQP9mXHSnwRo6DEx2ABlVUL1Ql1ZhNZBKTLW0047zby3ZWyLxHaG3PuNb3wjgKnAnte//vV915577rmNa7xnZgXKiLsoUiP5eu7fyu3mYCOPJiv4yNuOS7u2vK3ApD95zpZqwaHUAkuNYkOstfkmj3lsbCzz2ROJxJDy2S2O463E0YZ8HHbr1YgD/BrqEYdnNw27liTUVnMJq7qJvo+uRc4VStkYaUlALL0wLGPe6173OgBThjovV53/BqYMf3L8vPPOmzy3ZMkSAMDGjRtNWqzQVJZe+H/9TkTbFHtoqylvBcy0GfMsdx1Lj7zlt1XZWOoeclUbCU0GmklPFr2WtKTrH2xvUE0ikdgJMFDX2+zZs+uee+7p1kTT8FIVu1SqEUT6uJfkEgUrcOKNBS85J4K0ZWnA0g+9MVk0eXqqjOuSSy5pnNfXiM4eBX589atfbfzetGmTSX8XCPeTHVeA/oo3XjVfK1yWdXfW+/V8ebX3rbZtNeYtycEL67bClb13TEKTo0pBtVacdtpp6XpLJEYdA7fGWzW49XEOseTVLypUwMcta7zHGaPdUTjtNtrfq60ggdVWxsQ6XZdUWoHVlqUL5pCvfvWrW2mKkk74es/6b3FRljY+85nPAJiaAz0m7tfj1voc777CVnKLQ7bV8feOWbRY9iK2V1g0eAVSeBxRZWYPydkTiRHBwDl7rdVMhPF8qLIqiv5mJUp4iR169fPK+ET+14iDtMFbbS3JhqUNsdiL/qr7aEs2sSQXTgbhebOqs3oFQSx4BTQsTu/tucd9aXgcPdoRhktYcbKUhlez3koGYjsKjznyKrA+bkkQnJIr5w455BAAwG233dZHk36P0s+eSCSGo7NH3EKOCeeazv7Xgqg4BmM6+llbGayIhkivEo4rYxaahMNH9e8FluWbuY1wdOaIOgLNS0Sy7ssSGksMViKL5y9+97vf3ehD9/PJT37SvMZ6znyM4xK6vBvRc/VKqrGfXY+DJc5IMmE6+T5STEQfv/322wGkzp5IJHrIjz2RGBEMPFzWC4f0DAueEU4f8wIcNNgVYxkJAVtk5gCNqDKOV78sSv4RWiR8ll18kbjKNdStemYeTVyXT9PguSit7aM9WKKop1pE7qizzjqr8Vvm5yMf+Uhf/ywicwJJF7XNqwak/4423wSaqpGnpln1GNh1aG1xBUyJ7tNBcvZEYkQwcAMdEFeFEfAG9han8UJeLY7fFgxhSQ5eyC7TFoVesqvGooMNK9y/ZRTjaql6216BHJOEHea0VoAJ99slEMQK+/TGKuDEJMsVx+8JSzwf/OAH++7z0Y9+tNFGxsibZVoGTea0EWdnTs6BM1GqMf+2xtyWohuF43pIzp5IjAgGztk1F7Q4O+tc0p51GH2si87uuZ84+CIKUWXaIjeOl5prBciwLSByq3HAkNUvt2WXIYdcRmGbUTqs17ZLlVaBVeFWwFyNn7f1HD70oQ81xnr22Wc32nBKqqZbwBJFxEWj8Fu+xkvgsa5lqVXq/Vl06Pcng2oSicRgU1znzJlTlyxZYq5ozMGZY0UpnALm6FYYKK+YrAdGHMZLpbV0Oq+tLlwQBVfovqKUWvYUWNdHFXoZnp5tcQwu3qG5pUYXD4p1H8smoo9zqTGg3wMhbT72sY+Z97NokbkU63l0b4aVLMX2gShQSaATgnQbKRSir9H2lVe+8pW47rrrMsU1kRhlDDURxrKIeitnVAzCswLr47xXlqyGIklEHId1RuaMUWgkSya6refPZYurJaF4BRAszujp9dMpDxZJY1wwguc0Sl6KSkK1he4KtJ3FKkmmaY12EI7sEh5Y6rAkUZYquZCpZY1neu++e2J3NSlhJb91v/rbspCcPZEYEQy1eIWGF9kkK6W1IrMuGiUCcJE/8Sd3KWrIupuXbKHPCU1t+hrg67pRIYTpcB+vZJKV8OF5RaxoOK/QSJd0T8++EnloBEy3VTbKkqSsOdDwyndpdNkJF7CLS3i7Als++YceeqhxH+Hoco3sFqvbcFkwRnL2RGJEkB97IjEiGEq4bJfQVxbbLXGJRW5uEwXITEcMZnEyCnphlcJzG+k2bbuMWOPgebHEU1YhPNeeFp3ZkMnj0H1wjXw2CEqgku6fE23YSKVplus4V5zPa3iqShTKy4FVbFiMwmW952sFj/H7armDmW5PxdOQa/bee++wom9y9kRiRDDwFFe9a4UVBupxH4G1R5fXh2Vgsapz6rZ69eU0STYuceADMGUI5HTGyCXC3JTdg5brjbmPZVRiQ1Zbyqvuj3c8ieqlyZzKfEibv/zlL339C/eczpbZTEsU5stBTXLNxz/+8Ua797///ZN/e2O06hJ63DlKS+Z+plPLsC3ZS9OQO8IkEgkAAw6X3W233ery5ctN95bHpdmNYwVoeIj0Jk/ntcAFC4RWy33HqY/C4dmVZfXPRTGitqLLMZewnqfQyWO2EklYj7S4m8AL2pH+JJzWCsTh5+GFxuq2zHmtnU3Z5cbX8vsEAB/4wAcAAJ/4xCcATKXORkk/bcFfljuTpb0ohZnp7SodrFixAr/+9a8zXDaRGGV04uyllHcBeAuACuA6AH8HYAmASwEsBnA1gDfUWh91OwGw66671v3333/yt2WF5HNROCgnz0QFIrxqndyXBbbSCrwdYjSYE8ydO3fynGcx9u6n2/KKL5xeJ4XwWNvsFfpvL7jGghcibOnWViCPHo91jINPOPEmsv14yUAa7A2R8Yheb9H/qU99CgDwnve8p9GXJS3xu6ffAT0+DQ6t5XfC2s14bGwMJ5xwAq6++upt4+yllKUA/gHAsbXWIwCMAzgNwDkAPltrPRjAvQDe3NZXIpEYHrpa42cB2K2U8hiA3QFsAPAiAK/vnb8IwIcB/FvUSSkFs2bNCjkWI5I8PD3GSlEU/66giz/W849aeh/Ds3hLGKQ+Jys9j8OaE67RLnqxVZYqKn+kERVfjDi616+XTGOdYwnO0nXZNtPFmu21sewhIiGwDUbSYnVfwmFZ8vEShzT9vCuR5eFgW0AXPb/LswI6cPZa63oAnwZwByY+8vsxIbbfV2sVC8k6AEut60spZ5ZSVpdSVlsGlUQiMRh0EeP3BHAqgAMB7AdgLoBTut6g1rqy1npsrfXYNut5IpF48tDl63sxgD/UWjcBQCnl6wBWAFhYSpnV4+7LAKzvckNLTOv12zjvGZc0WES2RFkBb4fMYhEbRCya23KkLUR1xgQSfCL9zZ8/37wP0O+eY7HSEl89+qxMs7Y888j4yWHKkWvJqy1oVXjhuYtEWlbtpA/eN0DDC4P+4he/6F7z1re+FQBwzjnnAADe97739bURePNvGUwluy0yogLAfffdN/m3Vh22N5/9DgDHl1J2LxM9nQzgRgCXA3hVr80ZAL7Voa9EIjEkdHW9nQ3gtQC2ALgGE264pZhwvS3qHfsftda/Rv1IUI0gMgx5nCpykQmsBAz52zPURUY3ryprF8NIl+qsbJhbsGBB4xprtebacxbdHneI5tgLkGFDmtWGxyHGQ422jTqtcOhou2UGuy/5eHSN0P2lL33Jbcu7AMm1GzZsaL0PQ8anvwmBlwjz4IMPuv2VUnDcccdh9erVJnvvpETXWj8E4EN0+FYAx3W5PpFIDB9DCZe1Qv68fc2iqiGeG0dgBe1If1y5JoLn2rPuG6W0evSzDio6u8VNpS0H9FgBRdLW28HGSj5i3TxyjUVJMhqaO3mSiMW92wJvvAowml7uP3IHeoE4en4uvPDCBp08Hvmtq8a0JXfpcS5ZsqRxzqv643H4iLNnuGwiMSIYSg06Swf19EjWTTUX5eICUS06L0AmgtyLOSFzSIuzRMUSBF6BiwceeACA7V1gvZuTczSEo3rht5GFnec9Sif1klq4HTDlFREPxLx58wBMFcCIQqgFXSrFclsv9FajSzXbt7zlLQCAlStXmve2pBzPdhLRzZ4Ngcyb5YHY7qCaRCKxc2DgOvvBBx9spk3yKucF/kfpgKxDR6sfc1OxHOsQW+aM0oY5QFT/nscV6YoC3k1GnxdLvSehWMUreH68NF/9t7f7rLW7C/vDu3hMvProVsELAdsP5H8dG+FJdxxmbIGlR8tDw7vQ8Fyee+65bv9Mt7WbD9PP3hH5rd85bYfavHkztmzZkjp7IjHKGGrByah0D0eyWVzU09ms3V09riD/W/t6sYVYfgunFy7UxeIegbkcw+Kmgqj4hkcXc3iLRi/JyJIooig4BktB8gwl/sHy0HC/LDVZu694nocunqBoHJ5taToSsqePW+AUV4G1C22tNctSJRKJ/NgTiZHBwKvLegEobECzKnLodroti1JWgE5bW0vk5WQKpoErjuhruH8rEcMTkdlIpq8RF5XcO1IhIlek1Q7or+POxk5L9RJE22sLuAa8jFFccLpPnftv3Sd6Zt575NV7t/qP6grwe3Teeec1+o2Mw11Cdz01JEx0cdzak+fdM4lEYqfCULZstjgWr9JekkmXKiVizIhCbL3+LGNPW7hsl4AZ6cty7Xm0WJxZOHoXWpgDym9vU0vdll1v1vbCHoeNwnHZ+MW18/Qc7LHHHgCmODwbSqUvkQoA4P7772/ck0NqrSSpNlxwwQWTf7PE5iU6RZtNRoZRdh979fe2BcnZE4kRwcB19tmzZ4euHg448FxNFjh01Eqq8K63uBAnT3DQheV28fQzdp3o/pmbMpfWqaKcNipc2tIVtyWoRsBuIWu/NS+8lOfSCmRh3TqyPQiHZ85ouXAl6EjOiXtUEp+s/dsEHMz0hS98oa+Nx2mjXWrY5iO0yZxaIcIc0BXV4dPznDp7IpGYeUE1vJdZF3hcwQpGaSsxFUkD/L+VgOAFfkQlmpijM5fWVn/RXz2Obs0p34e5k+W1YD0zkow4uMkLhdXw7CCRnUW4shcgZY1REm94vz4LHIxl6daeRV04sHBkfR/vHRD7TfTM2pKw2sakkZw9kRgRDDQRZt68efXII48M/aSC6VSitSQFILasC5gGzYU4+YMtpF183F2svsx5uQyWhqd/R6WbPG4R0c2c3ZvjtnNMk0gkokNH+reHaA/yNmu1XKuLSwg8iUHr7jy/ngSki6O0SZNRQphXTER/t5qGP/3pT3jssccyESaRGGXkx55IjAiGIsZHrjEO5mBY+dpetlIk0nkiuVUJRxDVMRPwfHoZW1Zbrkxj1bjz3GkWTd58dMm2YhHTMkxxgEqX7YvbssS6GJv4XYnA70CUHSi12KPQVDl2/vnnN357z0Uf49/Wu+5l3PHzsPofGxvDPffck2J8IjHqGLjrbXx83OQsXSqvcDs2gkUBOF6tME520bTxiiycnkM7o0CWyJhnhYjq39HWzcyhIpeYV8fPmjc2ZHqVVy141+j+2djJLiUdQtwm3VmSCkt5Hse1DFweB7Zck29729sabaOKRJ///OdN2gSW5CYGPn5GkWRSyvbvCJNIJHYCDFxnP+qoo8z0VdaPRX+V41byDK/sXjilPscre6RTc2glu8h4q1+vHw0dNuvpZdE1XiKPFZrKoajebiwWZ/S4kA4pbXMTWck5PO+RXUWq17B9RWBd66UHd0kvlTaSTGPNW1vlm0gCkv5E349sVzyeKJFHp0+nzp5IJIZjjbdWdU9nZ4urXvm83TIsXY5XYI9bREEpgih4x6u0aiV8RFZ9jUhyYMuupV8yOD1Tw/IA6N96Ljy9Oyo4wrRFwUAe/V7qsQaf82wpwFRyEUtyVlppW3jvdFJnBTpoh+fK2yfAsrMAE8FCjz76aHL2RGKUMfAU1zlz5pjJLsyNPR9qxAEsHZT79/RvC7Lit/k+NdoqrXYJgbXSVQWen9oqt+TVdfcs1rqNl7pp7XTCqaGcUGL5/plGyyfPVnJ+zlYVYb7Wq7uu6ZDn7HFly+bgSSRdvBYC2f9do822ZD0HS1oxx9FKUSKR2CkwcD/7448/Hia5cEGHLpFJnu5uWdaZO0QRXWz5ZN+noEskHVtV9Vi5uKMgsjYzImszp6Ayd7Dm1NNJLWmMz0VJLZ6NiFOcNbxnFNHveSksC7jsmit77Mk52VFVJ814e+tZRU4ZX/7yl/vuzX15dEe2NS2thMlZ7plEIrFTIT/2RGJEMJQadJM3N4JqWEzy6prptl0SPbittOHAmKg+nrSRa6TSSLQZoRivLDHbC4FktcRyIbI4avXFIqBnoLPCWb3gIMsw5NWr47BfixZGpFJYFW49mlic5vfLuudee+0FIE6o4uco/YmKJ2O98MILzfFxf7ov655tVZK4nzBoyD2TSCR2Kgw0qGb+/Pn12GOPDdu0pSRaK7+3Y4u14nsGHGv7XC8hJTLCyI4tHhfSXM4zVEZj9lyGlrtO+u+S0urR4NVP023a5qVLoI8lBXihqV56rz7nGSG9oCENuVZccl3qyUWGZHGxRYY5AVfxnY40BgB33nknHnnkkQyqSSRGGQPl7KWUTQAeAnDPwG66fdgLOw6twI5F745EK7Dj0HtArXVv68RAP3YAKKWsrrXGsvwMwY5EK7Bj0bsj0QrsePRaSDE+kRgR5MeeSIwIhvGxrxzCPbcVOxKtwI5F745EK7Dj0duHgevsiURiOEgxPpEYEeTHnkiMCAb2sZdSTiml3FxKWVtKee+g7tsVpZT9SymXl1JuLKXcUEp5Z+/4olLK90spv+v9v+ewaRWUUsZLKdeUUi7r/T6wlHJVb46/UkrZpa2PQaGUsrCU8rVSyk2llDWllBNm6tyWUt7VeweuL6VcUkrZdSbPbVcM5GMvpYwD+D8A/juAwwG8rpRy+CDuPQ1sAfBPtdbDARwP4B09Gt8LYFWt9RAAq3q/ZwreCWCN+n0OgM/WWg8GcC+ANw+FKhufA/BftdZDARyFCbpn3NyWUpYC+AcAx9ZajwAwDuA0zOy57QbJlHky/wE4AcB31e+zAJw1iHtvB83fAvA3AG4GsKR3bAmAm4dNW4+WZZj4QF4E4DIABRMRXrOsOR8yrQsA/AE9g7A6PuPmFsBSAHcCWISJrNDLALx0ps7tdP4NSoyXCRSs6x2bkSilLAdwNICrAOxTa93QO7URwD5DIotxLoD3AJCMiMUA7qu1SgH+mTTHBwLYBOALPbXj/FLKXMzAua21rgfwaQB3ANgA4H4AV2Pmzm1npIGOUEqZB+A/APxjrfUBfa5OLOtD91WWUl4O4O5a69XDpqUjZgE4BsC/1VqPxkR+RENkn0FzuyeAUzGxQO0HYC6AU4ZK1BOEQX3s6wHsr34v6x2bUSilzMbEh35xrfXrvcN3lVKW9M4vAXD3sOhTWAHgb0sptwG4FBOi/OcALCylSL7jTJrjdQDW1Vqv6v3+GiY+/pk4ty8G8Ida66Za62MAvo6J+Z6pc9sZg/rYfwXgkJ5FcxdMGDy+PaB7d0KZSBi+AMCaWutn1KlvAzij9/cZmNDlh4pa61m11mW11uWYmMsf1lpPB3A5gFf1ms0IWgGg1roRwJ2llGf0Dp0M4EbMwLnFhPh+fCll9947IbTOyLmdFgZo+HgZgFsA/B7A+4ZtrDDoex4mxMhrAfym9+9lmNCFVwH4HYAfAFg0bFqJ7hcAuKz390EAfglgLYCvApgzbPoUnc8GsLo3v98EsOdMnVsAZwO4CcD1AP4fgDkzeW67/stw2URiRJAGukRiRJAfeyIxIsiPPZEYEeTHnkiMCPJjTyRGBPmxJxIjgvzYE4kRwf8HF0xvhi4O+3cAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m3,site=dijsktra(G, [90,210,999,1609,8686,130878,34546,10989,20543,69432,19000,148777,154389,89060,122130],3)"
      ],
      "metadata": {
        "id": "kR05XMtGK0qE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7aa6c486-0187-48c5-ea49-e6f9849c2c18"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.gray()\n",
        "plt.imshow(m3, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "8H7Y6bykMNUv",
        "outputId": "036305cc-8bbf-41a4-cf7b-2bc94c29d2e4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "segmented=recolor(m3,site)\n",
        "\n",
        "plt.gray()\n",
        "plt.imshow(segmented, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "hskncV5HMPt8",
        "outputId": "997c72aa-2c1c-461f-8f57-567fb2ac00bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m3b,site=dijsktra(G, [90,210,999,1609,5000,8686],3) #dist+ (1/cost)"
      ],
      "metadata": {
        "id": "rcdma0wuMW3g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.gray()\n",
        "plt.imshow(m3b, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "O75QIVM3M7ll",
        "outputId": "5650440c-3d81-4b6a-afe1-103476b348ad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m3b_segmented=recolor(m3b,site)\n",
        "\n",
        "plt.gray()\n",
        "plt.imshow(m3b_segmented, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "3YIo9KidMjyX",
        "outputId": "2032aa9e-f74a-4379-8532-0086368b7496"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "DgEN-AG2fx3K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## New dijkstra for 2nd max and 3rd max edges"
      ],
      "metadata": {
        "id": "Flay07gy1BBE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "\n",
        "import math\n",
        "import queue as Q\n",
        "import heapq as hq\n",
        "import ast\n",
        "\n",
        "\n",
        "def DIJKSTRA(Graph, src, costMetric):\n",
        "    # costmetric 0=dijkstra, 1=threshold with 50, 2=multiplied maxEdge by 1000\n",
        "\n",
        "    c = 0\n",
        "    start = [None] * len(src)\n",
        "    for i in src:\n",
        "        start[c] = int(i)\n",
        "        c = c + 1\n",
        "\n",
        "    # print(start)\n",
        "    matrix = np.zeros(shape=(size, size))\n",
        "    dist = [None] * (size * size)\n",
        "    print(len(dist))\n",
        "    prev = [None] * (size * size)\n",
        "    maxEdge = [math.inf] * (size * size)\n",
        "    site = [None] * (size * size)\n",
        "    paths = [[]] * (size * size)\n",
        "\n",
        "    for j in start:\n",
        "        dist[j] = 0\n",
        "        maxEdge[j] = 0\n",
        "        site[j] = j\n",
        "        paths[j].append(0)\n",
        "\n",
        "    q = Q.PriorityQueue()\n",
        "\n",
        "    for v in Graph:\n",
        "        vID = v.get_id()  # float originally\n",
        "\n",
        "        if (not (int(vID) in start)):\n",
        "            dist[int(vID)] = math.inf  # index has to be int\n",
        "            prev[int(vID)] = None\n",
        "\n",
        "        q.put(vID, dist[int(vID)])\n",
        "\n",
        "    while not q.empty():\n",
        "\n",
        "        uu = q.get()\n",
        "\n",
        "        u = Graph.get_vertex(uu)  # turning uu into a vertex item\n",
        "\n",
        "        if (costMetric == 0):\n",
        "            findcost0(u, dist, prev, q, site)\n",
        "\n",
        "        if (costMetric == 1):\n",
        "            findcost1(u, dist, prev, q, site)\n",
        "\n",
        "        if (costMetric == 2):  # max edge\n",
        "            findcostmax(u, dist, prev, q, paths, site)\n",
        "\n",
        "        if (costMetric == 3):  # reciprocal of distance\n",
        "            findcost3(u, dist, prev, q, site)\n",
        "\n",
        "        if (costMetric == 4):  # second max edge\n",
        "            findcostsecmax(u, dist, prev, q, paths, site)\n",
        "\n",
        "        if (costMetric == 5):  # third max edge\n",
        "            findcostthirdmax(u, dist, prev, q, paths, site)\n",
        "\n",
        "    for x in range(size):\n",
        "        for y in range(size):\n",
        "            matrix[x][y] = dist[x * size + y]\n",
        "\n",
        "    return matrix, site"
      ],
      "metadata": {
        "id": "1allKb7MM0Sg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def findcostwrong(u, dist, prev, q, paths, site):  # SECOND MAX EDGE\n",
        "\n",
        "    for n in u.get_connections():\n",
        "        cost = u.get_weight(n)\n",
        "        uid = u.get_id()\n",
        "\n",
        "        path = paths[int(uid)]\n",
        "        pathsorted=sorted(paths,key=float)\n",
        "        secmaxE = pathsorted[-2]\n",
        "\n",
        "        if cost > secmaxE:\n",
        "            secmaxE = cost\n",
        "\n",
        "        path_distance = dist[int(uid)] + cost\n",
        "        path_cost = path_distance + secmaxE * 1000\n",
        "        nid = n.get_id()\n",
        "\n",
        "        if path_cost < dist[int(nid)] + sorted( paths,key=float)[-2] * 1000:\n",
        "            dist[int(nid)] = path_distance  # original_dist #new_dist runs into infinite loop\n",
        "            prev[int(nid)] = u\n",
        "            site[int(nid)] = site[int(uid)]\n",
        "            paths[int(nid)] = paths[int(uid)].copy()\n",
        "            paths[int(nid)].append(cost)\n",
        "            q.put(nid, path_distance)"
      ],
      "metadata": {
        "id": "a9nvdd-McoMX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "LMmSOVq5zPvG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "m,site=dijsktranew(G, [90,210,999,1609,8686,130878,34546,10989,20543,69432,19000,148777,154389,89060,122130],5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3EmvNL4YayUj",
        "outputId": "80e84899-8301-40aa-d6b6-30197a833f6d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m,site=dijsktranew(G, [90,210,999,1609,8686,9878,4546,1098],5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2ANHuzVbl_DP",
        "outputId": "fa858136-5c57-4e8e-82ee-6d6e960eb48e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.gray()\n",
        "plt.imshow(m, interpolation='nearest')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "UA0H28DCa3Vy",
        "outputId": "48542990-d730-44f0-9e9c-4ca13fefcbf2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "segmented=recolor(m,site)\n",
        "plt.gray()\n",
        "plt.imshow(segmented, interpolation='nearest')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "LA_AHtUOeHE9",
        "outputId": "715ffa42-2ba1-4168-cfd5-dc674fa9b153"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "m4,site=dijsktra(G, [90,210,999,1609,5000,8686],4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3nk4n7uydTE6",
        "outputId": "42d93a6f-aa82-4df6-f62c-006171202507"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "sH3Sbm0GytGS"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}