2023_05_24_graph_viz_with_networkx.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPS07pd4e4NrzrVJnc5dQix",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/chupvl/gcolab/blob/main/2023_05_24_graph_viz_with_networkx.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Graph representation of the chemical compound: rdkit + networkx\n"
      ],
      "metadata": {
        "id": "E4XsbvrDI36O"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "2023-05-25\n",
        "\n",
        "Vladimir Chupakhin\n",
        "\n",
        "A reminder for myself on how to work with NetworkX and graph representation of the chemical compounds."
      ],
      "metadata": {
        "id": "E9mXkPFddTkz"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Libs"
      ],
      "metadata": {
        "id": "5qJouCv2JD5u"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install rdkit -q"
      ],
      "metadata": {
        "id": "QPWODm-oJIbl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5f260bbd-358f-4403-c2eb-536c26c26498"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m29.7/29.7 MB\u001b[0m \u001b[31m25.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import networkx as nx\n",
        "from rdkit import Chem\n",
        "from rdkit.Chem import Draw"
      ],
      "metadata": {
        "id": "paz9HtzfI_3Z"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Visualization"
      ],
      "metadata": {
        "id": "A0YfR3_9JGbt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a RDKit molecule object for aspirin\n",
        "aspirin_smiles = 'CC(=O)OC1=CC=CC=C1C(=O)O'\n",
        "aspirin_mol = Chem.MolFromSmiles(aspirin_smiles)\n",
        "aspirin_mol"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 167
        },
        "id": "bTfkycMlJhD6",
        "outputId": "72f703af-0b60-4a54-d113-0ff193de8ee1"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<rdkit.Chem.rdchem.Mol at 0x7f8bbd268900>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "un-SDIG9IATd"
      },
      "outputs": [],
      "source": [
        "# Generate an RDKit graph from the molecule\n",
        "aspirin_graph = nx.Graph()\n",
        "\n",
        "atom_labels = {}\n",
        "atom_colors = {}\n",
        "\n",
        "for atom in aspirin_mol.GetAtoms():\n",
        "    atom_idx = atom.GetIdx()\n",
        "    atom_symbol = atom.GetSymbol()\n",
        "    atom_type = atom.GetAtomicNum()\n",
        "    aspirin_graph.add_node(atom_idx, symbol=atom_symbol)\n",
        "    atom_labels[atom_idx] = atom_symbol\n",
        "    atom_colors[atom_idx] = atom_type\n",
        "\n",
        "for bond in aspirin_mol.GetBonds():\n",
        "    atom1_idx = bond.GetBeginAtomIdx()\n",
        "    atom2_idx = bond.GetEndAtomIdx()\n",
        "    bond_type = bond.GetBondTypeAsDouble()\n",
        "    aspirin_graph.add_edge(atom1_idx, atom2_idx, bond_type=bond_type)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Print the graph representation - nodes\n",
        "for i in aspirin_graph.nodes(data=True):\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V6zafyezJpML",
        "outputId": "cad05877-d846-42fe-8c5c-37939c53d1b5"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(0, {'symbol': 'C'})\n",
            "(1, {'symbol': 'C'})\n",
            "(2, {'symbol': 'O'})\n",
            "(3, {'symbol': 'O'})\n",
            "(4, {'symbol': 'C'})\n",
            "(5, {'symbol': 'C'})\n",
            "(6, {'symbol': 'C'})\n",
            "(7, {'symbol': 'C'})\n",
            "(8, {'symbol': 'C'})\n",
            "(9, {'symbol': 'C'})\n",
            "(10, {'symbol': 'C'})\n",
            "(11, {'symbol': 'O'})\n",
            "(12, {'symbol': 'O'})\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Print the graph representation - edges\n",
        "for i in aspirin_graph.edges(data=True):\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8nm9B0-AJqFK",
        "outputId": "873edb3e-68a3-43f6-bd1f-4c92cf31342e"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(0, 1, {'bond_type': 1.0})\n",
            "(1, 2, {'bond_type': 2.0})\n",
            "(1, 3, {'bond_type': 1.0})\n",
            "(3, 4, {'bond_type': 1.0})\n",
            "(4, 5, {'bond_type': 1.5})\n",
            "(4, 9, {'bond_type': 1.5})\n",
            "(5, 6, {'bond_type': 1.5})\n",
            "(6, 7, {'bond_type': 1.5})\n",
            "(7, 8, {'bond_type': 1.5})\n",
            "(8, 9, {'bond_type': 1.5})\n",
            "(9, 10, {'bond_type': 1.0})\n",
            "(10, 11, {'bond_type': 2.0})\n",
            "(10, 12, {'bond_type': 1.0})\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualize the graph with labels\n",
        "labels = nx.get_node_attributes(aspirin_graph, 'symbol')\n",
        "edge_labels = nx.get_edge_attributes(aspirin_graph, 'bond_type')\n",
        "pos = nx.spring_layout(aspirin_graph)\n",
        "nx.draw(aspirin_graph, pos, with_labels=True, labels=labels)\n",
        "nx.draw_networkx_edge_labels(aspirin_graph, pos, edge_labels=edge_labels)\n",
        "\n",
        "# Show it\n",
        "import matplotlib.pyplot as plt\n",
        "plt.show()\n",
        "# yuk, ugly..."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
        },
        "id": "FkUvb7cuIBbP",
        "outputId": "2e7688f2-a346-4852-f72c-45222352e155"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Let's paint it..."
      ],
      "metadata": {
        "id": "5KTZhX0OMZ7v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Set up node colors based on user-specified list\n",
        "user_atom_colors = {6: 'gray', 8: 'red'}  # User-specified colors for carbon (6) and oxygen (8)\n",
        "node_colors = [user_atom_colors.get(atom_colors[node]) for node in aspirin_graph.nodes()]\n",
        "\n",
        "# Draw the graph with labels and colors\n",
        "plt.figure(figsize=(6, 6))\n",
        "pos = nx.spring_layout(aspirin_graph) # seed=42 - to keep graph stable\n",
        "nx.draw(aspirin_graph, pos, node_color=node_colors, with_labels=True, labels=atom_labels, font_size=10)\n",
        "edge_labels = nx.get_edge_attributes(aspirin_graph, 'bond_type')\n",
        "nx.draw_networkx_edge_labels(aspirin_graph, pos, edge_labels=edge_labels, font_size=8)\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "id": "4y_vS3waXe3H",
        "outputId": "dd875bad-32a1-4b85-f8a6-dd8e22b4b334"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}