feb2019_test.ipynb

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    "### NOTE FOR LUCA\n",
    "\n",
    "**Remember to set/remove metadata as:**\n",
    "{\n",
    "  \"nbsphinx\": \"hidden\"\n",
    "}\n",
    "\n",
    "to enable/disable solutions view"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scientific Programmming 13/02/2019\n",
    "\n",
    "## Before you start\n",
    "**Please write one single python script for the lab part and one text file with the answers to the theoretical questions.**\n",
    "\n",
    "**IMPORTANT: Add your name and ID (matricola) on top of the .py and text files!**\n",
    "\n",
    "\n",
    "## Theory\n",
    "\n",
    "**Please write the solution in a text file**.\n",
    "\n",
    "### Exercise 1:\n",
    "\n",
    "Let L a list of size n, and i and j two indeces. Return the \n",
    "computational complexity of function fun() with respect to n.\n",
    "\n",
    "```\n",
    "def fun(L, i, j):\n",
    "     # j-i+1 is the number of elements\n",
    "     # between index i and index j (both included)\n",
    "     if j-i+1 <= 3:\n",
    "         # Compute their minimum\n",
    "         return min(L[i:j+1])\n",
    "     else:\n",
    "        onethird = (j-i+1)//3\n",
    "        res1 = fun(L,i, i+onethird)\n",
    "        res2 = fun(L,i+onethird+1, i+2*onethird)\n",
    "        res3 = fun(L,i+2*onethird+1, j)\n",
    "        return min(res1,res2,res3)\n",
    "```\n",
    "\n",
    "\n",
    "## Practical part\n",
    "\n",
    "\n",
    "## Exercise 1:\n",
    "\n",
    "The file [test_genes.tsv](file_samples/test_genes.tsv) is a tab separated file containing the following information regarding genes:\n",
    "\n",
    "```\n",
    "ScaffoldID\tfeature\tStartPos\tEndPos\tGeneID\n",
    "s159888\tgene\t48555\t49286\tgene00001\n",
    "s159888\tmRNA\t48555\t49286\tgene00001\n",
    "s159888\tstart_codon\t48555\t48557\tgene00001\n",
    "s159888\tCDS\t48555\t48653\tgene00001\n",
    "...\n",
    "```\n",
    "\n",
    "As the header says, the first column is the scaffold where the gene os located, feature represents the information specified in the line (e.g. gene, mRNA, start_codon,...) , StartPos and EndPos are the starting and ending position of the feature and GeneID is the identifier of the gene . \n",
    "\n",
    "The file [test_seqs.fasta](file_samples/test_seqs.fasta) is a fasta file with the sequence of some of the scaffolds contained in the test_genes.tsv file.\n",
    "\n",
    "Read the file in input and store it in a suitable data structure ```data``` (hint: pandas?) then write the following methods:\n",
    "\n",
    "1. ```computestats(data)``` gets the data structure loaded and prints the total number of scaffolds, geneIDs and features. The method should also print the first ten genes. For each feature (i.e. second column) print the average length of the feature (with 3 decimal places of precision); \n",
    "\n",
    "\n",
    "2. ```scaffInfo(data, scaffold, start, end, kind='bar')``` given the input data, a scaffold, a start postion and an end position,  prints how many features are **entirely** contained in the closed interval [start,end] and plots the counts of the different number of features in the interval. An optional parameter ```kind``` can be specified to control the type of plot (possible values: bar, pie). The default of this optional parameter is ```bar```;\n",
    "\n",
    "\n",
    "3. ```getInfo(data, geneID, sequenceFile)``` given the input data, a geneID and a fasta file containing sequences, the function prints all the features belonging to geneID (if geneID exists and the corresponding scaffold is in the sequenceFile, an error message otherwise) and the sequence of the start_codon, all exons and end_codon (**note that positions in the test_genes.tsv file are 1-based, which means that the first base is considered in position 1**). **See example below to see how the output should look like.**\n",
    "\n",
    "\n",
    "After loading the data, calling \n",
    "\n",
    "```\n",
    "dataFile = \"test_genes.tsv\"\n",
    "seqFile = \"test_seqs.fasta\"\n",
    "\n",
    "data = pd.read_csv(dataFile,\n",
    "                     sep=\"\\t\",  header = 0)\n",
    "    \n",
    "\n",
    "computestats(data)\n",
    "print(\"\\n\")\n",
    "scaffInfo(data, \"s160692\",1,300000)\n",
    "scaffInfo(data, \"s160448\",1,125000, \"pie\")\n",
    "scaffInfo(data, \"s160551\",1,50000)\n",
    "scaffInfo(data, \"s163228\", 1,10000)\n",
    "print(\"\\n\")\n",
    "getInfo(data, \"gene00001\" ,seqFile)\n",
    "print(\"\\n\")\n",
    "getInfo(data, \"gene00607\" ,seqFile)\n",
    "print(\"\\n\")\n",
    "getInfo(data, \"gene72\" ,seqFile)\n",
    "```\n",
    "\n",
    "should return \n",
    "\n",
    "```\n",
    "The file contains 9982 features\n",
    "Belonging to 481 scaffolds and 622 genes.\n",
    "First 10 genes are:\n",
    "\tgene00044\n",
    "\tgene00556\n",
    "\tgene00512\n",
    "\tgene00323\n",
    "\tgene00124\n",
    "\tgene00541\n",
    "\tgene00553\n",
    "\tgene00430\n",
    "\tgene00588\n",
    "\tgene00382\n",
    "Overall average feature length: 1193.051 bps\n",
    "\n",
    "Feature CDS has avg. length 338.342 bps\n",
    "Feature exon has avg. length 338.342 bps\n",
    "Feature gene has avg. length 5644.326 bps\n",
    "Feature initial has avg. length 357.402 bps\n",
    "Feature internal has avg. length 222.450 bps\n",
    "Feature intron has avg. length 2007.303 bps\n",
    "Feature mRNA has avg. length 5644.326 bps\n",
    "Feature start_codon has avg. length 3.000 bps\n",
    "Feature stop_codon has avg. length 3.000 bps\n",
    "Feature terminal has avg. length 465.545 bps\n",
    "\n",
    "86 total features are in s160692 in [1,300000]\n",
    "```\n",
    "![](img/examFeb19/img1.png)\n",
    "\n",
    "```\n",
    "11 total features are in s160448 in [1,125000]\n",
    "```\n",
    "\n",
    "![](img/examFeb19/img2.png)\n",
    "\n",
    "\n",
    "```\n",
    "15 total features are in s160551 in [1,50000]\n",
    "```\n",
    "\n",
    "![](img/examFeb19/img3.png)\n",
    "\n",
    "```\n",
    "0 total features are in s163228 in [1,10000]\n",
    "Nothing to plot for s163228:[1,10000]\n",
    "\n",
    "\n",
    "Features of gene \"gene00001\"\n",
    "gene on s159888 in position [48555,49286]\n",
    "mRNA on s159888 in position [48555,49286]\n",
    "start_codon on s159888 in position [48555,48557]\n",
    "\tSequence: ATG\n",
    "CDS on s159888 in position [48555,48653]\n",
    "exon on s159888 in position [48555,48653]\n",
    "\tSequence: ATGGAGAAGGGCGATACTATATCTACATACCTGAACAAGCTCACCACCTGTATAGATGAGCTTAGTAGTGTGGGAATAACTACTGTTGATGATGATATG\n",
    "initial on s159888 in position [48555,48653]\n",
    "intron on s159888 in position [48654,48764]\n",
    "CDS on s159888 in position [48765,49286]\n",
    "exon on s159888 in position [48765,49286]\n",
    "\tSequence: GAGGATATCAGGAGGAGCACACGAGATGGTTCTTCATCCAAGAATGATGATGAAGAAAATCTGGCCTTAGCAAGTAAGGCAAGGAAAGGGAAAGGTAAGGCTTCCCATTCCAAATCGAATTCTTCTCATGGAGGGAAGAAGGTTGACAAGTCTAAAGTGAGATGCTTTAATTGTCACGACATGGGACATTATGCAACTAACTTCCCATTGAAGAAGTCCAAGAAGGGATCCTCGAAAGGATCACAAGGTGAGGCATTAGCCTCTCAGTTTGAAATGGACTTTTCCCTCATCGCATGCATGGTTTCATCGATGGTGGGTTGTGTTTGGTACCTTGACAGCGGAGCCTCATTCCACATGACCGGCAATAAAAGTTTATTCAGTACCTTGGAGGAGAAAGACCTTAAGATGCACATAGAAATGGGTGACAACAGAAAGTACAGTGTTTCAAGAGTGGGCACAGTTGCTTTTCAGAGGGAACACAGATCTCCTCATACCTTGATAGATGTGAAGTATGTGCCTTGA\n",
    "terminal on s159888 in position [48765,49286]\n",
    "stop_codon on s159888 in position [49284,49286]\n",
    "\tSequence: TGA\n",
    "\n",
    "\n",
    "Features of gene \"gene00607\"\n",
    "gene on s163228 in position [77187,90573]\n",
    "mRNA on s163228 in position [77187,90573]\n",
    "start_codon on s163228 in position [77187,77189]\n",
    " - Sequence information UNAVAILABLE\n",
    "CDS on s163228 in position [77187,77465]\n",
    "exon on s163228 in position [77187,77465]\n",
    " - Sequence information UNAVAILABLE\n",
    "initial on s163228 in position [77187,77465]\n",
    "intron on s163228 in position [77466,89710]\n",
    "CDS on s163228 in position [89711,89768]\n",
    "exon on s163228 in position [89711,89768]\n",
    " - Sequence information UNAVAILABLE\n",
    "internal on s163228 in position [89711,89768]\n",
    "intron on s163228 in position [89769,90073]\n",
    "CDS on s163228 in position [90074,90573]\n",
    "exon on s163228 in position [90074,90573]\n",
    " - Sequence information UNAVAILABLE\n",
    "terminal on s163228 in position [90074,90573]\n",
    "stop_codon on s163228 in position [90571,90573]\n",
    " - Sequence information UNAVAILABLE\n",
    "\n",
    "\n",
    "No information available for gene \"gene72\"\n",
    "```\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "## Exercise 2:\n",
    "\n",
    "Recall directed graphs as adjacency matrices (implemented in the included ```DiGraphAsAdjacencyMatrix```).\n",
    "\n",
    "1. Write a method ```getInConnected(self, mynode)``` that returns the list of nodes that outlink to the node ```mynode``` if ```mynode``` exists in the set of nodes, it should print an error message and return None otherwise.\n",
    "\n",
    "2. Write a method ```getTopConnected(self, connectionType)``` that returns the node with the highest number of connections of the specified type (and the corresponding connections count). Connection type can be ```incoming``` to get the node with the highest number of incoming edges, ```outgoing``` to get the node with the highest number of outgoing edges or ```both``` to get the node that has the highest number of connections (regardless if they are outgoing or incoming). \n",
    "\n",
    "3. Write a **recursive method** ```countPathsRec(self, startNode, endNode, K)``` that given a starting node ```startNode``` and a ending node ```endNode``` counts how many paths of length exactly equal to $K$ connect the two (following the right orientation of edges).\n",
    "\n",
    "To solve this problem consider that the base cases are:\n",
    "\n",
    "a. if startNode == endNode and K = 0 there is one path connecting the two;\n",
    "\n",
    "b. if startNode outlinks to endNode and K = 1, then there is one path;\n",
    "\n",
    "c. if K <0 there are no possible paths;\n",
    "\n",
    "The recursive method should move from start node to all its adjacent nodes and recursively count how many paths of length K-1 exist from that point on towards endNode.\n",
    "\n",
    "4. Modify the previous method to return also all the found paths. Hint: add a parameter ```path``` to the countPathsRec method.\n",
    "\n",
    "Test the code with the following graph:\n",
    "\n",
    "![](img/testgraph_feb.png)\n",
    "\n",
    "\n",
    "that can be implemented with:\n",
    "\n",
    "```\n",
    "G = DiGraphAsAdjacencyMatrix()\n",
    "    for i in range(11):\n",
    "        n = \"Node{}\".format(i+1)\n",
    "        G.insertNode(n)\n",
    "\n",
    "G.insertEdge(\"Node1\",\"Node2\", 1)\n",
    "G.insertEdge(\"Node2\", \"Node3\", 1)\n",
    "G.insertEdge(\"Node2\",\"Node4\", 1)\n",
    "G.insertEdge(\"Node2\" ,\"Node5\", 1)\n",
    "G.insertEdge(\"Node3\" ,\"Node5\", 1)\n",
    "G.insertEdge(\"Node9\" ,\"Node5\", 1)\n",
    "G.insertEdge(\"Node4\",\"Node6\", 1)\n",
    "G.insertEdge(\"Node6\",\"Node7\", 1)\n",
    "G.insertEdge(\"Node7\",\"Node5\", 1)\n",
    "G.insertEdge(\"Node7\" ,\"Node4\", 1)\n",
    "G.insertEdge(\"Node4\" ,\"Node7\", 1)\n",
    "G.insertEdge(\"Node8\" ,\"Node3\", 1)\n",
    "G.insertEdge(\"Node8\" ,\"Node2\", 1)\n",
    "G.insertEdge(\"Node1\" ,\"Node9\", 1)\n",
    "G.insertEdge(\"Node9\" ,\"Node1\", 1)\n",
    "G.insertEdge(\"Node9\" ,\"Node10\", 1)\n",
    "G.insertEdge(\"Node5\" ,\"Node10\", 1)\n",
    "G.insertEdge(\"Node5\" ,\"Node9\", 1)\n",
    "G.insertEdge(\"Node6\" ,\"Node9\", 1)\n",
    "G.insertEdge(\"Node7\" ,\"Node9\", 1)\n",
    "G.insertEdge(\"Node9\" ,\"Node8\", 1)\n",
    "G.insertEdge(\"Node9\" ,\"Node3\", 1)\n",
    "G.insertEdge(\"Node8\" ,\"Node1\", 1)\n",
    "G.insertEdge(\"Node10\" ,\"Node3\", 1)\n",
    "G.insertEdge(\"Node11\" ,\"Node10\", 1)\n",
    "\n",
    "```\n",
    "\n",
    "Calling\n",
    "\n",
    "```\n",
    "print(G)\n",
    "\n",
    "n=\"Node3\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node7\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node9\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node472\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node11\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "print(\"\\n\")\n",
    "TI = G.getTopConnected(\"incoming\")\n",
    "print(\"Top connected node(s) (incoming) is: {} ({} tot connections)\".format(TI[0],TI[1]))\n",
    "TO = G.getTopConnected(\"outgoing\")\n",
    "print(\"Top connected node(s) (outgoing) is: {} ({} tot connections)\".format(TO[0],TO[1]))\n",
    "TB = G.getTopConnected(\"both\")\n",
    "print(\"Top connected node(s) is: {} ({} tot connections)\".format(TB[0],TB[1]))\n",
    "\n",
    "print(\"\\n\")\n",
    "n1 = \"Node1\"\n",
    "n2 = \"Node4\"\n",
    "n = 4\n",
    "print(\"{} paths of length {} between node {} and {}\".format(G.countPathsRec(n1,n2,n),\n",
    "                                                           n, n1,n2))\n",
    "\n",
    "n1 = \"Node3\"\n",
    "n2 = \"Node9\"\n",
    "n = 7\n",
    "print(\"{} paths of length {} between node {} and {}\".format(G.countPathsRec(n1,n2,n),\n",
    "                                                           n, n1,n2))\n",
    "```\n",
    "\n",
    "should return:\n",
    "\n",
    "```\n",
    "Node3 has incoming links from: ['Node2', 'Node8', 'Node9', 'Node10']\n",
    "Node7 has incoming links from: ['Node4', 'Node6']\n",
    "Node9 has incoming links from: ['Node1', 'Node5', 'Node6', 'Node7']\n",
    "Error. Node \"Node472\" does not exist\n",
    "Node472 has incoming links from: None\n",
    "Node11 has incoming links from: []\n",
    "\n",
    "\n",
    "Top connected node(s) (incoming) is: Node3,Node5,Node9 (4 tot connections)\n",
    "Top connected node(s) (outgoing) is: Node9 (5 tot connections)\n",
    "Top connected node(s) is: Node9 (9 tot connections)\n",
    "\n",
    "\n",
    "3 paths of length 4 between node Node1 and Node4\n",
    "18 paths of length 7 between node Node3 and Node9\n",
    "12 paths of length 5 between node Node4 and Node10\n",
    "```\n",
    "\n",
    "with the paths:\n",
    "\n",
    "```\n",
    "PATH: Node1 --> Node2 --> Node4 --> Node7 --> Node4\n",
    "PATH: Node1 --> Node9 --> Node1 --> Node2 --> Node4\n",
    "PATH: Node1 --> Node9 --> Node8 --> Node2 --> Node4\n",
    "3 paths of length 4 between node Node1 and Node4\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node2 --> Node3 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node2 --> Node4 --> Node6 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node2 --> Node4 --> Node7 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node9 --> Node3 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node9 --> Node8 --> Node1 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node3 --> Node5 --> Node9 --> Node1 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node3 --> Node5 --> Node9 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node5 --> Node9 --> Node3 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node5 --> Node9 --> Node8 --> Node1 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node5 --> Node10 --> Node3 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node1 --> Node2 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node1 --> Node9 --> Node1 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node1 --> Node9 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node2 --> Node3 --> Node5 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node2 --> Node4 --> Node6 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node2 --> Node4 --> Node7 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node10 --> Node3 --> Node5 --> Node9 --> Node1 --> Node9\n",
    "PATH: Node3 --> Node5 --> Node10 --> Node3 --> Node5 --> Node9 --> Node5 --> Node9\n",
    "18 paths of length 7 between node Node3 and Node9\n",
    "PATH: Node4 --> Node6 --> Node7 --> Node5 --> Node9 --> Node10\n",
    "PATH: Node4 --> Node6 --> Node7 --> Node9 --> Node5 --> Node10\n",
    "PATH: Node4 --> Node6 --> Node9 --> Node1 --> Node9 --> Node10\n",
    "PATH: Node4 --> Node6 --> Node9 --> Node3 --> Node5 --> Node10\n",
    "PATH: Node4 --> Node6 --> Node9 --> Node5 --> Node9 --> Node10\n",
    "PATH: Node4 --> Node7 --> Node4 --> Node6 --> Node9 --> Node10\n",
    "PATH: Node4 --> Node7 --> Node4 --> Node7 --> Node5 --> Node10\n",
    "PATH: Node4 --> Node7 --> Node4 --> Node7 --> Node9 --> Node10\n",
    "PATH: Node4 --> Node7 --> Node5 --> Node9 --> Node5 --> Node10\n",
    "PATH: Node4 --> Node7 --> Node9 --> Node1 --> Node9 --> Node10\n",
    "PATH: Node4 --> Node7 --> Node9 --> Node3 --> Node5 --> Node10\n",
    "PATH: Node4 --> Node7 --> Node9 --> Node5 --> Node9 --> Node10\n",
    "12 paths of length 5 between node Node4 and Node10\n",
    "```\n"
   ]
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   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\tNode1\tNode2\tNode3\tNode4\tNode5\tNode6\tNode7\tNode8\tNode9\tNode10\tNode11\n",
      "Node1\t0\t1\t0\t0\t0\t0\t0\t0\t1\t0\t0\n",
      "Node2\t0\t0\t1\t1\t1\t0\t0\t0\t0\t0\t0\n",
      "Node3\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\n",
      "Node4\t0\t0\t0\t0\t0\t1\t1\t0\t0\t0\t0\n",
      "Node5\t0\t0\t0\t0\t0\t0\t0\t0\t1\t1\t0\n",
      "Node6\t0\t0\t0\t0\t0\t0\t1\t0\t1\t0\t0\n",
      "Node7\t0\t0\t0\t1\t1\t0\t0\t0\t1\t0\t0\n",
      "Node8\t1\t1\t1\t0\t0\t0\t0\t0\t0\t0\t0\n",
      "Node9\t1\t0\t1\t0\t1\t0\t0\t1\t0\t1\t0\n",
      "Node10\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\n",
      "Node11\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "NAME:\n",
    "SURNAME:\n",
    "Matricola: \n",
    "\n",
    "Exercise2.py\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "class DiGraphAsAdjacencyMatrix:\n",
    "    def __init__(self):\n",
    "        #would be better a set, but I need an index\n",
    "        self.__nodes = list()\n",
    "        self.__matrix = list()\n",
    "        \n",
    "    def __len__(self):\n",
    "        \"\"\"gets the number of nodes\"\"\"\n",
    "        return len(self.__nodes)\n",
    "        \n",
    "    def nodes(self):\n",
    "        return self.__nodes\n",
    "    \n",
    "    def matrix(self):\n",
    "        return self.__matrix\n",
    "    \n",
    "    def __str__(self):\n",
    "        header = \"\\t\".join([n for n in self.__nodes])\n",
    "        data = \"\"\n",
    "        for i in range(0,len(self.__matrix)):\n",
    "            data += str(self.__nodes[i]) +\"\\t\" + \"\\t\".join([str(x) for x in self.__matrix[i]]) + \"\\n\"\n",
    "\n",
    "        return \"\\t\"+ header +\"\\n\" + data\n",
    "    \n",
    "    def insertNode(self, node):\n",
    "        #add the node if not there.\n",
    "        if node not in self.__nodes:\n",
    "            self.__nodes.append(node)\n",
    "            #add a row and a column of zeros in the matrix\n",
    "            if len(self.__matrix) == 0:\n",
    "                #first node\n",
    "                self.__matrix = [[0]]\n",
    "            else:\n",
    "                N = len(self.__nodes)\n",
    "                for row in self.__matrix:\n",
    "                    row.append(0)\n",
    "                self.__matrix.append([0 for x in range(N)])\n",
    "    \n",
    "    def insertEdge(self, node1, node2, weight):\n",
    "        i = -1\n",
    "        j = -1\n",
    "        if node1 in self.__nodes:\n",
    "            i = self.__nodes.index(node1)\n",
    "        if node2 in self.__nodes:\n",
    "            j = self.__nodes.index(node2)\n",
    "        if i != -1 and j != -1:\n",
    "            self.__matrix[i][j] = weight\n",
    "    \n",
    "    def deleteEdge(self, node1,node2):\n",
    "        \"\"\"removing an edge means to set its\n",
    "        corresponding place in the matrix to 0\"\"\"\n",
    "        i = -1\n",
    "        j = -1\n",
    "        if node1 in self.__nodes:\n",
    "            i = self.__nodes.index(node1)\n",
    "        if node2 in self.__nodes:\n",
    "            j = self.__nodes.index(node2)\n",
    "        if i != -1 and j != -1:\n",
    "            self.__matrix[i][j] = 0\n",
    "    \n",
    "    def deleteNode(self, node):\n",
    "        \"\"\"removing a node means removing\n",
    "        its corresponding row and column in the matrix\"\"\"\n",
    "        i = -1\n",
    "\n",
    "        if node in self.__nodes:\n",
    "            i = self.__nodes.index(node)\n",
    "        #print(\"Removing {} at index {}\".format(node, i))\n",
    "        if node != -1:\n",
    "            self.__matrix.pop(i)\n",
    "            for row in self.__matrix:\n",
    "                row.pop(i)\n",
    "            self.__nodes.pop(i)\n",
    "    \n",
    "    \n",
    "     \n",
    "    def edges(self):\n",
    "        \"\"\"Returns all the edges in the graph as triplets\"\"\"\n",
    "        ret = []\n",
    "        for i in range(len(self.__nodes)):\n",
    "            start = self.__nodes[i]\n",
    "            for j in range(len(self.__nodes)):\n",
    "                end = self.__nodes[j]\n",
    "                w = self.__matrix[i][j]\n",
    "                if w != 0:\n",
    "                    ret.append((start, end, w))\n",
    "        return ret\n",
    "    \n",
    "    \n",
    "    def getInConnected(self, mynode):\n",
    "        \"\"\"returns the list of nodes that outlink to the node ```mynode```\n",
    "        if ```mynode``` exists in the set of nodes, it should print an error message and\n",
    "        return None otherwise\n",
    "        \"\"\"\n",
    "        \n",
    "    def getTopConnected(self, connectionType):\n",
    "        \"\"\"\n",
    "        Returns the node with the highest number of connections of the specified type.\n",
    "        (and the corresponding connections count).\n",
    "        Connection type can be: \n",
    "        ```incoming``` to get the node with the highest number of incoming edges, \n",
    "        ```outgoing``` to get the node with the highest number of outgoing edges or \n",
    "        ```both``` to get the node that has the highest number of connections \n",
    "        (regardless if they are outgoing or incoming).\"\"\"        \n",
    "            \n",
    "            \n",
    "    def countPathsRec(self, startNode, endNode, K):\n",
    "        \"\"\"given a starting node ```startNode``` and a ending node ```endNode``` counts \n",
    "        how many paths of length exactly equal to $K$ connect the two \n",
    "        (following the right orientation of edges).\n",
    "        \"\"\"\n",
    "        \n",
    "if __name__ == \"__main__\":\n",
    "    G = DiGraphAsAdjacencyMatrix()\n",
    "    for i in range(11):\n",
    "        n = \"Node{}\".format(i+1)\n",
    "        G.insertNode(n)\n",
    "\n",
    "    G.insertEdge(\"Node1\",\"Node2\", 1)\n",
    "    G.insertEdge(\"Node2\", \"Node3\", 1)\n",
    "    G.insertEdge(\"Node2\",\"Node4\", 1)\n",
    "    G.insertEdge(\"Node2\" ,\"Node5\", 1)\n",
    "    G.insertEdge(\"Node3\" ,\"Node5\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node5\", 1)\n",
    "    G.insertEdge(\"Node4\",\"Node6\", 1)\n",
    "    G.insertEdge(\"Node6\",\"Node7\", 1)\n",
    "    G.insertEdge(\"Node7\",\"Node5\", 1)\n",
    "    G.insertEdge(\"Node7\" ,\"Node4\", 1)\n",
    "    G.insertEdge(\"Node4\" ,\"Node7\", 1)\n",
    "    G.insertEdge(\"Node8\" ,\"Node3\", 1)\n",
    "    G.insertEdge(\"Node8\" ,\"Node2\", 1)\n",
    "    G.insertEdge(\"Node1\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node1\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node10\", 1)\n",
    "    G.insertEdge(\"Node5\" ,\"Node10\", 1)\n",
    "    G.insertEdge(\"Node5\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node6\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node7\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node8\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node3\", 1)\n",
    "    G.insertEdge(\"Node8\" ,\"Node1\", 1)\n",
    "    G.insertEdge(\"Node10\" ,\"Node3\", 1)\n",
    "    G.insertEdge(\"Node11\" ,\"Node10\", 1)\n",
    "        \n",
    "print(G)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A possible solution: \n",
    "\n",
    "## Theory\n",
    "\n",
    "Exercise 1. Solution:\n",
    "$\\Theta(n)$\n",
    "\n",
    "## Practical part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The file contains 9982 features\n",
      "Belonging to 481 scaffolds and 622 genes.\n",
      "First 10 genes are:\n",
      "\tgene00044\n",
      "\tgene00556\n",
      "\tgene00512\n",
      "\tgene00323\n",
      "\tgene00124\n",
      "\tgene00541\n",
      "\tgene00553\n",
      "\tgene00430\n",
      "\tgene00588\n",
      "\tgene00382\n",
      "Overall average feature length: 1193.051 bps\n",
      "\n",
      "Feature CDS has avg. length 338.342 bps\n",
      "Feature exon has avg. length 338.342 bps\n",
      "Feature gene has avg. length 5644.326 bps\n",
      "Feature initial has avg. length 357.402 bps\n",
      "Feature internal has avg. length 222.450 bps\n",
      "Feature intron has avg. length 2007.303 bps\n",
      "Feature mRNA has avg. length 5644.326 bps\n",
      "Feature start_codon has avg. length 3.000 bps\n",
      "Feature stop_codon has avg. length 3.000 bps\n",
      "Feature terminal has avg. length 465.545 bps\n",
      "\n",
      "\n",
      "86 total features are in s160692 in [1,300000]\n"
     ]
    },
    {
     "data": {
      "image/png": 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4Or4oatuAx1g/x/Zs27OHhoY6LS4iIpZgqgn9dklrAVS/F3QvpIiImIqpJvRTgL2qx3sB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\nqhdFl9AqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33d7149fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11 total features are in s160448 in [1,125000]\n"
     ]
    },
    {
     "data": {
      "image/png": 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UUQ6w2+k4QkXB2xTHjoN9OFRm3Y+RXpYrBbXJEjN37zpRZmpW985xjY/3rSU5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\nlKqJIpx26lMj6N6cNrU8Wqo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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33d70a3550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15 total features are in s160551 in [1,50000]\n"
     ]
    },
    {
     "data": {
      "image/png": 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Jtv/UQizP743DdqN9/mvf+sWUitcfKf3MX+IG5oGStLvtZXXg0gPY/u/pjqEv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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33d7213898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 total features are in s163228 in [1,10000]\n",
      "Nothing to plot for s163228:[1,10000]\n",
      "\n",
      "\n",
      "Features of gene \"gene00001\"\n",
      "gene on s159888 in position [48555,49286]\n",
      "mRNA on s159888 in position [48555,49286]\n",
      "start_codon on s159888 in position [48555,48557]\n",
      "\tSequence: ATG\n",
      "CDS on s159888 in position [48555,48653]\n",
      "exon on s159888 in position [48555,48653]\n",
      "\tSequence: ATGGAGAAGGGCGATACTATATCTACATACCTGAACAAGCTCACCACCTGTATAGATGAGCTTAGTAGTGTGGGAATAACTACTGTTGATGATGATATG\n",
      "initial on s159888 in position [48555,48653]\n",
      "intron on s159888 in position [48654,48764]\n",
      "CDS on s159888 in position [48765,49286]\n",
      "exon on s159888 in position [48765,49286]\n",
      "\tSequence: GAGGATATCAGGAGGAGCACACGAGATGGTTCTTCATCCAAGAATGATGATGAAGAAAATCTGGCCTTAGCAAGTAAGGCAAGGAAAGGGAAAGGTAAGGCTTCCCATTCCAAATCGAATTCTTCTCATGGAGGGAAGAAGGTTGACAAGTCTAAAGTGAGATGCTTTAATTGTCACGACATGGGACATTATGCAACTAACTTCCCATTGAAGAAGTCCAAGAAGGGATCCTCGAAAGGATCACAAGGTGAGGCATTAGCCTCTCAGTTTGAAATGGACTTTTCCCTCATCGCATGCATGGTTTCATCGATGGTGGGTTGTGTTTGGTACCTTGACAGCGGAGCCTCATTCCACATGACCGGCAATAAAAGTTTATTCAGTACCTTGGAGGAGAAAGACCTTAAGATGCACATAGAAATGGGTGACAACAGAAAGTACAGTGTTTCAAGAGTGGGCACAGTTGCTTTTCAGAGGGAACACAGATCTCCTCATACCTTGATAGATGTGAAGTATGTGCCTTGA\n",
      "terminal on s159888 in position [48765,49286]\n",
      "stop_codon on s159888 in position [49284,49286]\n",
      "\tSequence: TGA\n",
      "\n",
      "\n",
      "Features of gene \"gene00607\"\n",
      "gene on s163228 in position [77187,90573]\n",
      "mRNA on s163228 in position [77187,90573]\n",
      "start_codon on s163228 in position [77187,77189]\n",
      " - Sequence information UNAVAILABLE\n",
      "CDS on s163228 in position [77187,77465]\n",
      "exon on s163228 in position [77187,77465]\n",
      " - Sequence information UNAVAILABLE\n",
      "initial on s163228 in position [77187,77465]\n",
      "intron on s163228 in position [77466,89710]\n",
      "CDS on s163228 in position [89711,89768]\n",
      "exon on s163228 in position [89711,89768]\n",
      " - Sequence information UNAVAILABLE\n",
      "internal on s163228 in position [89711,89768]\n",
      "intron on s163228 in position [89769,90073]\n",
      "CDS on s163228 in position [90074,90573]\n",
      "exon on s163228 in position [90074,90573]\n",
      " - Sequence information UNAVAILABLE\n",
      "terminal on s163228 in position [90074,90573]\n",
      "stop_codon on s163228 in position [90571,90573]\n",
      " - Sequence information UNAVAILABLE\n",
      "\n",
      "\n",
      "No information available for gene \"gene72\"\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "NAME:\n",
    "SURNAME:\n",
    "Matricola: \n",
    "\n",
    "partA.py\n",
    "\"\"\"\n",
    "% reset -f \n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "from Bio import SeqIO\n",
    "\n",
    "def computestats(data):\n",
    "    \"\"\"\n",
    "    gets the data structure loaded and prints the total number of scaffolds, geneIDs and features.\n",
    "    The method should also print the first ten genes.\n",
    "    For each feature (i.e. second column) print the average length of the feature (with 3 decimal \n",
    "    places of precision)\n",
    "    \"\"\"\n",
    "    print(\"The file contains {} features\".format(data.shape[0]))\n",
    "    \n",
    "    countsByS = data['ScaffoldID'].value_counts()\n",
    "    countsByG = data['GeneID'].value_counts()\n",
    "    print(\"Belonging to {} scaffolds and {} genes.\".format(len(countsByS), len(countsByG)))\n",
    "    print(\"First 10 genes are:\")\n",
    "    for gene in countsByG.head(10).index:\n",
    "        print(\"\\t{}\".format(gene))\n",
    "    \n",
    "    data['featureLen'] = data['EndPos']-data['StartPos'] + 1\n",
    "    \n",
    "    lensByType = data.groupby('feature')['featureLen'].mean()\n",
    "    print(\"Overall average feature length: {:.3f} bps\\n\".format(data[\"featureLen\"].mean()))\n",
    "    \n",
    "    for el in lensByType.index:\n",
    "        print(\"Feature {} has avg. length {:.3f} bps\".format(el, lensByType[el]))\n",
    "        \n",
    "\n",
    "    \n",
    "    \n",
    "def scaffInfo(data,scaff, start, end, kind='bar'):\n",
    "    \"\"\"\n",
    "    given the input data, a scaffold, a start postion and an end position,  \n",
    "    prints how many features are **entirely** contained in the closed interval [start,end] \n",
    "    and plots the counts of the different number of features in the interval.\n",
    "    An optional parameter ```kind``` can be specified to control the type of plot (possible values: bar, pie)\n",
    "    \"\"\"\n",
    "    sFilt = data[data['ScaffoldID'] == scaff]\n",
    "    tmp = sFilt[sFilt['StartPos'] >= start]\n",
    "    filtFeatures = tmp[tmp['EndPos'] <= end]\n",
    "    countsByType = filtFeatures['feature'].value_counts()\n",
    "    print(\"{} total features are in {} in [{},{}]\".format(len(filtFeatures), scaff, start,end))\n",
    "    if len(countsByType):\n",
    "        countsByType.plot(kind = kind)\n",
    "        plt.title('# features of {} in [{},{}]'.format(scaff, start,end))\n",
    "        plt.show()\n",
    "    else:\n",
    "        print(\"Nothing to plot for {}:[{},{}]\".format(scaff, start,end))\n",
    "    \n",
    "\n",
    "\n",
    "def getInfo(data, geneID, sequenceFile):\n",
    "    \"\"\"\n",
    "    given the input data, a geneID and a fasta file containing sequences, \n",
    "    the function prints all the features belonging to geneID \n",
    "    (if geneID exists and the corresponding scaffold is in the sequenceFile, an error message otherwise) \n",
    "    and the sequence of the start_codon, all exons and end_codon\n",
    "    \"\"\"\n",
    "    filtData = data[data['GeneID'] == geneID]\n",
    "    seqDict = SeqIO.to_dict(SeqIO.parse(sequenceFile, \"fasta\"))\n",
    "    \n",
    "    if len(filtData) > 0:\n",
    "        print(\"Features of gene \\\"{}\\\"\".format(geneID))\n",
    "        for ind,row in filtData.iterrows():\n",
    "            \n",
    "            print(\"{} on {} in position [{},{}]\".format(row[1], \n",
    "                                                        row[0], \n",
    "                                                        row[2],\n",
    "                                                       row[3]))\n",
    "            if row[1] == 'start_codon' or row[1] == 'stop_codon' or row[1] == 'exon':\n",
    "                if row[0] in seqDict:\n",
    "                    seq = seqDict[row[0]][row[2]-1:row[3]]\n",
    "                    print(\"\\tSequence: {}\".format(seq.seq))\n",
    "                else:\n",
    "                    print(\" - Sequence information UNAVAILABLE\")\n",
    "                \n",
    "            \n",
    "    else:\n",
    "        print(\"No information available for gene \\\"{}\\\"\".format(geneID))\n",
    "\n",
    "dataFile = \"file_samples/test_genes.tsv\"\n",
    "seqFile = \"file_samples/test_seqs.fasta\"\n",
    "\n",
    "data = pd.read_csv(dataFile,\n",
    "                     sep=\"\\t\",  header = 0)\n",
    "    \n",
    "\n",
    "computestats(data)\n",
    "print(\"\\n\")\n",
    "scaffInfo(data, \"s160692\",1,300000)\n",
    "scaffInfo(data, \"s160448\",1,125000, \"pie\")\n",
    "scaffInfo(data, \"s160551\",1,50000)\n",
    "scaffInfo(data, \"s163228\", 1,10000)\n",
    "print(\"\\n\")\n",
    "getInfo(data, \"gene00001\" ,seqFile)\n",
    "print(\"\\n\")\n",
    "getInfo(data, \"gene00607\" ,seqFile)\n",
    "print(\"\\n\")\n",
    "getInfo(data, \"gene72\" ,seqFile)\n",
    "\n",
    "    \n",
    "    \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\tNode1\tNode2\tNode3\tNode4\tNode5\tNode6\tNode7\tNode8\tNode9\tNode10\tNode11\n",
      "Node1\t0\t1\t0\t0\t0\t0\t0\t0\t1\t0\t0\n",
      "Node2\t0\t0\t1\t1\t1\t0\t0\t0\t0\t0\t0\n",
      "Node3\t0\t0\t0\t0\t1\t0\t0\t0\t0\t0\t0\n",
      "Node4\t0\t0\t0\t0\t0\t1\t1\t0\t0\t0\t0\n",
      "Node5\t0\t0\t0\t0\t0\t0\t0\t0\t1\t1\t0\n",
      "Node6\t0\t0\t0\t0\t0\t0\t1\t0\t1\t0\t0\n",
      "Node7\t0\t0\t0\t1\t1\t0\t0\t0\t1\t0\t0\n",
      "Node8\t1\t1\t1\t0\t0\t0\t0\t0\t0\t0\t0\n",
      "Node9\t1\t0\t1\t0\t1\t0\t0\t1\t0\t1\t0\n",
      "Node10\t0\t0\t1\t0\t0\t0\t0\t0\t0\t0\t0\n",
      "Node11\t0\t0\t0\t0\t0\t0\t0\t0\t0\t1\t0\n",
      "\n",
      "Node3 has incoming links from: ['Node2', 'Node8', 'Node9', 'Node10']\n",
      "Node7 has incoming links from: ['Node4', 'Node6']\n",
      "Node9 has incoming links from: ['Node1', 'Node5', 'Node6', 'Node7']\n",
      "Error. Node \"Node472\" does not exist\n",
      "Node472 has incoming links from: None\n",
      "Node11 has incoming links from: []\n",
      "\n",
      "\n",
      "Top connected node(s) (incoming) is: Node3,Node5,Node9 (4 tot connections)\n",
      "Top connected node(s) (outgoing) is: Node9 (5 tot connections)\n",
      "Top connected node(s) is: Node9 (9 tot connections)\n",
      "\n",
      "\n",
      "PATH: Node1 --> Node2 --> Node4 --> Node7 --> Node4\n",
      "PATH: Node1 --> Node9 --> Node1 --> Node2 --> Node4\n",
      "PATH: Node1 --> Node9 --> Node8 --> Node2 --> Node4\n",
      "3 paths of length 4 between node Node1 and Node4\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node2 --> Node3 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node2 --> Node4 --> Node6 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node2 --> Node4 --> Node7 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node9 --> Node3 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node1 --> Node9 --> Node8 --> Node1 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node3 --> Node5 --> Node9 --> Node1 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node3 --> Node5 --> Node9 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node5 --> Node9 --> Node3 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node5 --> Node9 --> Node8 --> Node1 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node5 --> Node10 --> Node3 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node1 --> Node2 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node1 --> Node9 --> Node1 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node1 --> Node9 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node2 --> Node3 --> Node5 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node2 --> Node4 --> Node6 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node9 --> Node8 --> Node2 --> Node4 --> Node7 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node10 --> Node3 --> Node5 --> Node9 --> Node1 --> Node9\n",
      "PATH: Node3 --> Node5 --> Node10 --> Node3 --> Node5 --> Node9 --> Node5 --> Node9\n",
      "18 paths of length 7 between node Node3 and Node9\n",
      "PATH: Node4 --> Node6 --> Node7 --> Node5 --> Node9 --> Node10\n",
      "PATH: Node4 --> Node6 --> Node7 --> Node9 --> Node5 --> Node10\n",
      "PATH: Node4 --> Node6 --> Node9 --> Node1 --> Node9 --> Node10\n",
      "PATH: Node4 --> Node6 --> Node9 --> Node3 --> Node5 --> Node10\n",
      "PATH: Node4 --> Node6 --> Node9 --> Node5 --> Node9 --> Node10\n",
      "PATH: Node4 --> Node7 --> Node4 --> Node6 --> Node9 --> Node10\n",
      "PATH: Node4 --> Node7 --> Node4 --> Node7 --> Node5 --> Node10\n",
      "PATH: Node4 --> Node7 --> Node4 --> Node7 --> Node9 --> Node10\n",
      "PATH: Node4 --> Node7 --> Node5 --> Node9 --> Node5 --> Node10\n",
      "PATH: Node4 --> Node7 --> Node9 --> Node1 --> Node9 --> Node10\n",
      "PATH: Node4 --> Node7 --> Node9 --> Node3 --> Node5 --> Node10\n",
      "PATH: Node4 --> Node7 --> Node9 --> Node5 --> Node9 --> Node10\n",
      "12 paths of length 5 between node Node4 and Node10\n"
     ]
    }
   ],
   "source": [
    "class DiGraphAsAdjacencyMatrix:\n",
    "    def __init__(self):\n",
    "        #would be better a set, but I need an index\n",
    "        self.__nodes = list()\n",
    "        self.__matrix = list()\n",
    "        \n",
    "    def __len__(self):\n",
    "        \"\"\"gets the number of nodes\"\"\"\n",
    "        return len(self.__nodes)\n",
    "        \n",
    "    def nodes(self):\n",
    "        return self.__nodes\n",
    "    \n",
    "    def matrix(self):\n",
    "        return self.__matrix\n",
    "    \n",
    "    def __str__(self):\n",
    "        header = \"\\t\".join([n for n in self.__nodes])\n",
    "        data = \"\"\n",
    "        for i in range(0,len(self.__matrix)):\n",
    "            data += str(self.__nodes[i]) +\"\\t\" + \"\\t\".join([str(x) for x in self.__matrix[i]]) + \"\\n\"\n",
    "\n",
    "        return \"\\t\"+ header +\"\\n\" + data\n",
    "    \n",
    "    def insertNode(self, node):\n",
    "        #add the node if not there.\n",
    "        if node not in self.__nodes:\n",
    "            self.__nodes.append(node)\n",
    "            #add a row and a column of zeros in the matrix\n",
    "            if len(self.__matrix) == 0:\n",
    "                #first node\n",
    "                self.__matrix = [[0]]\n",
    "            else:\n",
    "                N = len(self.__nodes)\n",
    "                for row in self.__matrix:\n",
    "                    row.append(0)\n",
    "                self.__matrix.append([0 for x in range(N)])\n",
    "    \n",
    "    def insertEdge(self, node1, node2, weight):\n",
    "        i = -1\n",
    "        j = -1\n",
    "        if node1 in self.__nodes:\n",
    "            i = self.__nodes.index(node1)\n",
    "        if node2 in self.__nodes:\n",
    "            j = self.__nodes.index(node2)\n",
    "        if i != -1 and j != -1:\n",
    "            self.__matrix[i][j] = weight\n",
    "    \n",
    "    def deleteEdge(self, node1,node2):\n",
    "        \"\"\"removing an edge means to set its\n",
    "        corresponding place in the matrix to 0\"\"\"\n",
    "        i = -1\n",
    "        j = -1\n",
    "        if node1 in self.__nodes:\n",
    "            i = self.__nodes.index(node1)\n",
    "        if node2 in self.__nodes:\n",
    "            j = self.__nodes.index(node2)\n",
    "        if i != -1 and j != -1:\n",
    "            self.__matrix[i][j] = 0\n",
    "    \n",
    "    def deleteNode(self, node):\n",
    "        \"\"\"removing a node means removing\n",
    "        its corresponding row and column in the matrix\"\"\"\n",
    "        i = -1\n",
    "\n",
    "        if node in self.__nodes:\n",
    "            i = self.__nodes.index(node)\n",
    "        #print(\"Removing {} at index {}\".format(node, i))\n",
    "        if node != -1:\n",
    "            self.__matrix.pop(i)\n",
    "            for row in self.__matrix:\n",
    "                row.pop(i)\n",
    "            self.__nodes.pop(i)\n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "    def edges(self):\n",
    "        \"\"\"Returns all the edges in the graph as triplets\"\"\"\n",
    "        ret = []\n",
    "        for i in range(len(self.__nodes)):\n",
    "            start = self.__nodes[i]\n",
    "            for j in range(len(self.__nodes)):\n",
    "                end = self.__nodes[j]\n",
    "                w = self.__matrix[i][j]\n",
    "                if w != 0:\n",
    "                    ret.append((start, end, w))\n",
    "        return ret\n",
    "    \n",
    "    def getInConnected(self, mynode):\n",
    "        \"\"\"returns the list of nodes that outlink to the node ```mynode```\n",
    "        if ```mynode``` exists in the set of nodes, it should print an error message and return None otherwise\n",
    "        \"\"\"\n",
    "        M = self.matrix()\n",
    "        \n",
    "        res = \"\"\n",
    "        \n",
    "        ind = -1 \n",
    "        if mynode in self.__nodes:\n",
    "            ind = self.__nodes.index(mynode)\n",
    "        else:\n",
    "            print(\"Error. Node \\\"{}\\\" does not exist\".format(mynode))\n",
    "            return None\n",
    "        \n",
    "        resInd = [self.nodes()[M.index(x)] for x in M if x[ind] != 0]\n",
    "        return resInd\n",
    "        \n",
    "    def getTopConnected(self, connectionType):\n",
    "        \"\"\"\n",
    "        Returns the node with the highest number of connections of the specified type \n",
    "        (and the corresponding connections count). \n",
    "        Connection type can be: \n",
    "        ```incoming``` to get the node with the highest number of incoming edges, \n",
    "        ```outgoing``` to get the node with the highest number of outgoing edges or \n",
    "        ```both``` to get the node that has the highest number of connections \n",
    "        (regardless if they are outgoing or incoming).\"\"\" \n",
    "        top_out = \"\"\n",
    "        count_out = 0\n",
    "        top_in = \"\"\n",
    "        count_in = 0\n",
    "        top_both = \"\"\n",
    "        count_both = 0\n",
    "        M = self.matrix()\n",
    "        for node in self.nodes():\n",
    "            i = self.nodes().index(node)\n",
    "            #get the number of outgoing edges\n",
    "            tout = len([x for x in M[i] if x != 0 ])\n",
    "            #get the number of incoming edges\n",
    "            tin = len([x[i] for x in M if x[i] != 0])\n",
    "            #print(\"{} incoming: {}\".format(node,tin))\n",
    "            if tout > count_out:\n",
    "                count_out = tout\n",
    "                top_out = node\n",
    "            elif tout == count_out:\n",
    "                top_out += \",\" + node\n",
    "            \n",
    "            if tin > count_in:\n",
    "                count_in = tin\n",
    "                top_in = node\n",
    "            elif tin == count_in:\n",
    "                top_in += \",\" + node\n",
    "                \n",
    "            \n",
    "            if tin + tout > count_both:\n",
    "                count_both = tin + tout\n",
    "                top_both = node\n",
    "            elif tin + tout == count_both:\n",
    "                top_both += \",\" + node   \n",
    "            \n",
    "        if connectionType == \"incoming\":\n",
    "            return (top_in, count_in)\n",
    "        elif connectionType == \"outgoing\":\n",
    "            return (top_out, count_out)\n",
    "        elif connectionType == \"both\":\n",
    "            return (top_both, count_both)\n",
    "        else:\n",
    "            return (-1,-1)\n",
    "        \n",
    "    def countPathsRec(self, startNode, endNode, K, path=\"\"):\n",
    "        \"\"\"given a starting node ```startNode``` and a ending node ```endNode``` counts \n",
    "        how many paths of length exactly equal to $K$ connect the two \n",
    "        (following the right orientation of edges).\n",
    "        \"\"\"\n",
    "        sInd = None\n",
    "        eInd = None\n",
    "        if startNode in self.nodes():\n",
    "            sInd = self.__nodes.index(startNode)\n",
    "        if endNode in self.nodes():\n",
    "            eInd = self.__nodes.index(endNode)\n",
    "            \n",
    "        if startNode == endNode and K == 0:\n",
    "            print(\"PATH: {}\".format(path + \" --> \" + endNode))\n",
    "            return 1\n",
    "        if K < 0:\n",
    "            return 0\n",
    "        \n",
    "        M = self.matrix()\n",
    "        if M[sInd][eInd] != 0 and K == 1:\n",
    "            print(\"PATH: {}\".format(path +  \" --> \" + endNode))\n",
    "            return 1\n",
    "        outGoing = M[sInd]\n",
    "        #print(outGoing)\n",
    "        count = 0\n",
    "        for i in range(len(outGoing)):\n",
    "            if outGoing[i] != 0:\n",
    "                nextN = self.nodes()[i]\n",
    "                #print(\"{}-->{}\".format(startNode, nextN))\n",
    "                #print(path)\n",
    "                if len(path) == 0:\n",
    "                    path = startNode\n",
    "\n",
    "                count += self.countPathsRec(nextN, endNode, K-1, path + \" --> \" + nextN)\n",
    "        \n",
    "        return count\n",
    "                \n",
    "\n",
    "        \n",
    "            \n",
    "if __name__ == \"__main__\":\n",
    "    G = DiGraphAsAdjacencyMatrix()\n",
    "    for i in range(11):\n",
    "        n = \"Node{}\".format(i+1)\n",
    "        G.insertNode(n)\n",
    "\n",
    "    G.insertEdge(\"Node1\",\"Node2\", 1)\n",
    "    G.insertEdge(\"Node2\", \"Node3\", 1)\n",
    "    G.insertEdge(\"Node2\",\"Node4\", 1)\n",
    "    G.insertEdge(\"Node2\" ,\"Node5\", 1)\n",
    "    G.insertEdge(\"Node3\" ,\"Node5\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node5\", 1)\n",
    "    G.insertEdge(\"Node4\",\"Node6\", 1)\n",
    "    G.insertEdge(\"Node6\",\"Node7\", 1)\n",
    "    G.insertEdge(\"Node7\",\"Node5\", 1)\n",
    "    G.insertEdge(\"Node7\" ,\"Node4\", 1)\n",
    "    G.insertEdge(\"Node4\" ,\"Node7\", 1)\n",
    "    G.insertEdge(\"Node8\" ,\"Node3\", 1)\n",
    "    G.insertEdge(\"Node8\" ,\"Node2\", 1)\n",
    "    G.insertEdge(\"Node1\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node1\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node10\", 1)\n",
    "    G.insertEdge(\"Node5\" ,\"Node10\", 1)\n",
    "    G.insertEdge(\"Node5\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node6\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node7\" ,\"Node9\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node8\", 1)\n",
    "    G.insertEdge(\"Node9\" ,\"Node3\", 1)\n",
    "    G.insertEdge(\"Node8\" ,\"Node1\", 1)\n",
    "    G.insertEdge(\"Node10\" ,\"Node3\", 1)\n",
    "    G.insertEdge(\"Node11\" ,\"Node10\", 1)\n",
    "        \n",
    "print(G)\n",
    "\n",
    "n=\"Node3\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node7\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node9\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node472\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "n=\"Node11\"\n",
    "print(\"{} has incoming links from: {}\".format(n, G.getInConnected(n)))\n",
    "print(\"\\n\")\n",
    "TI = G.getTopConnected(\"incoming\")\n",
    "print(\"Top connected node(s) (incoming) is: {} ({} tot connections)\".format(TI[0],TI[1]))\n",
    "TO = G.getTopConnected(\"outgoing\")\n",
    "print(\"Top connected node(s) (outgoing) is: {} ({} tot connections)\".format(TO[0],TO[1]))\n",
    "TB = G.getTopConnected(\"both\")\n",
    "print(\"Top connected node(s) is: {} ({} tot connections)\".format(TB[0],TB[1]))\n",
    "\n",
    "print(\"\\n\")\n",
    "n1 = \"Node1\"\n",
    "n2 = \"Node4\"\n",
    "n = 4\n",
    "print(\"{} paths of length {} between node {} and {}\".format(G.countPathsRec(n1,n2,n),\n",
    "                                                           n, n1,n2))\n",
    "\n",
    "n1 = \"Node3\"\n",
    "n2 = \"Node9\"\n",
    "n = 7\n",
    "print(\"{} paths of length {} between node {} and {}\".format(G.countPathsRec(n1,n2,n),\n",
    "                                                           n, n1,n2))\n",
    "\n",
    "n1 = \"Node4\"\n",
    "n2 = \"Node10\"\n",
    "n = 5\n",
    "print(\"{} paths of length {} between node {} and {}\".format(G.countPathsRec(n1,n2,n),\n",
    "                                                           n, n1,n2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "nbsphinx": "hidden"
   },
   "outputs": [],
   "source": [
    "\"CODE NOT SHOWN\"\n",
    "\n",
    "#Drawing a graph in pygraphviz\n",
    "import pygraphviz as pgv\n",
    "\n",
    "G=pgv.AGraph(directed=True)\n",
    "\n",
    "#Attributes can be added when adding nodes or edge\n",
    "G.add_node(\"Node1\", color='black')\n",
    "G.add_node(\"Node2\", color='black')\n",
    "G.add_node(\"Node3\", color='black')\n",
    "G.add_node(\"Node4\", color='black')\n",
    "G.add_node(\"Node5\", color='black')\n",
    "G.add_node(\"Node6\", color='black')\n",
    "G.add_node(\"Node7\", color='black')\n",
    "G.add_node(\"Node8\", color='black')\n",
    "G.add_node(\"Node9\", color='black')\n",
    "G.add_node(\"Node10\", color='black')\n",
    "G.add_node(\"Node11\", color='black')\n",
    "\n",
    "\n",
    "G.add_edge(\"Node1\" ,\"Node2\", color='blue')\n",
    "G.add_edge(\"Node2\", \"Node3\", color='blue')\n",
    "G.add_edge(\"Node2\" ,\"Node4\", color='blue')\n",
    "G.add_edge(\"Node2\" ,\"Node5\", color='blue')\n",
    "G.add_edge(\"Node3\" ,\"Node5\", color='blue')\n",
    "G.add_edge(\"Node9\" ,\"Node5\", color='blue')\n",
    "G.add_edge(\"Node4\" ,\"Node6\", color='blue')\n",
    "G.add_edge(\"Node6\" ,\"Node7\", color='blue')\n",
    "G.add_edge(\"Node7\" ,\"Node5\", color='blue')\n",
    "G.add_edge(\"Node7\" ,\"Node4\", color='blue')\n",
    "G.add_edge(\"Node4\" ,\"Node7\", color='blue')\n",
    "G.add_edge(\"Node8\" ,\"Node3\", color='blue')\n",
    "G.add_edge(\"Node8\" ,\"Node2\", color='blue')\n",
    "G.add_edge(\"Node1\" ,\"Node9\", color='blue')\n",
    "G.add_edge(\"Node9\" ,\"Node1\", color='blue')\n",
    "G.add_edge(\"Node9\" ,\"Node10\", color='blue')\n",
    "G.add_edge(\"Node5\" ,\"Node10\", color='blue')\n",
    "G.add_edge(\"Node5\" ,\"Node9\", color='blue')\n",
    "G.add_edge(\"Node6\" ,\"Node9\", color='blue')\n",
    "G.add_edge(\"Node7\" ,\"Node9\", color='blue')\n",
    "G.add_edge(\"Node9\" ,\"Node8\", color='blue')\n",
    "G.add_edge(\"Node9\" ,\"Node3\", color='blue')\n",
    "G.add_edge(\"Node8\" ,\"Node1\", color='blue')\n",
    "G.add_edge(\"Node10\" ,\"Node3\", color='blue')\n",
    "G.add_edge(\"Node11\" ,\"Node10\", color='blue')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# write to a dot file\n",
    "#G.write('test.dot')\n",
    "\n",
    "#create a png file\n",
    "G.layout(prog='dot') # use dot\n",
    "G.draw('img/testgraph_feb.png')"
   ]
  }
 ],
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