NeuralFCA_Big_hw.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install fcapy[all]\n",
        "!pip install frozendict\n",
        "!pip install ipynb\n",
        "!pip install sparselinear\n",
        "!pip install bitsets\n",
        "!pip install bitarray\n",
        "import torch\n",
        "!pip install torch-scatter -f https://data.pyg.org/whl/torch-2.0.0+cuda118.html\n",
        "!pip install torch-sparse -f https://data.pyg.org/whl/torch-2.0.0+cuda118.html\n",
        "!pip install torch-cluster -f https://data.pyg.org/whl/torch-2.0.0+cuda118.html\n",
        "!pip install git+https://github.com/pyg-team/pytorch_geometric.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cuicenOBvdEQ",
        "outputId": "ad1943da-99e0-493b-dd85-8b98956acbfc"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Collecting torch-cluster\n",
            "  Using cached torch_cluster-1.6.3.tar.gz (54 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "Building wheels for collected packages: torch-cluster\n",
            "  Building wheel for torch-cluster (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for torch-cluster: filename=torch_cluster-1.6.3-cp310-cp310-linux_x86_64.whl size=690648 sha256=20fb6b0d0e0a09ebd2663f4743f3f353d6ea12401514c50bf6265dc112425a34\n",
            "  Stored in directory: /root/.cache/pip/wheels/51/78/c3/536637b3cdcc3313aa5e8851a6c72b97f6a01877e68c7595e3\n",
            "Successfully built torch-cluster\n",
            "Installing collected packages: torch-cluster\n",
            "Successfully installed torch-cluster-1.6.3\n",
            "Collecting git+https://github.com/pyg-team/pytorch_geometric.git\n",
            "  Cloning https://github.com/pyg-team/pytorch_geometric.git to /tmp/pip-req-build-u8yh0d0s\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/pyg-team/pytorch_geometric.git /tmp/pip-req-build-u8yh0d0s\n",
            "  Resolved https://github.com/pyg-team/pytorch_geometric.git to commit 9f7e82442efb41687e60469f1e63b0efaa793165\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (4.66.1)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (1.23.5)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (1.11.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (3.1.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (2.31.0)\n",
            "Requirement already satisfied: pyparsing in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (3.1.1)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (1.2.2)\n",
            "Requirement already satisfied: psutil>=5.8.0 in /usr/local/lib/python3.10/dist-packages (from torch_geometric==2.4.0) (5.9.5)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch_geometric==2.4.0) (2.1.3)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric==2.4.0) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric==2.4.0) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric==2.4.0) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric==2.4.0) (2023.7.22)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->torch_geometric==2.4.0) (1.3.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->torch_geometric==2.4.0) (3.2.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3v12S4V2u8J0"
      },
      "source": [
        "# Import libs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "dUEvmHBsu8J0"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "TLvzJls4u8J2"
      },
      "outputs": [],
      "source": [
        "from fcapy.context import FormalContext\n",
        "from fcapy.lattice import ConceptLattice"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "dh6ROPg2u8J3"
      },
      "outputs": [],
      "source": [
        "from fcapy.visualizer import LineVizNx\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.rcParams['figure.facecolor'] = (1,1,1,1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "6CreHYwWu8J3"
      },
      "outputs": [],
      "source": [
        "import neural_lib as nl"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "sB1UqaW_u8J3",
        "outputId": "863a82d3-f3e9-49f6-b569-079be9ee7b86"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             firm  smooth  fruit  yellow  green   blue  white  round   oval  \\\n",
              "title                                                                         \n",
              "apple       False    True   True    True  False  False  False   True  False   \n",
              "grapefruit  False   False   True    True  False  False  False   True  False   \n",
              "kiwi        False   False   True   False   True  False  False  False   True   \n",
              "plum        False    True   True   False  False   True  False  False   True   \n",
              "toy cube     True    True  False   False   True  False  False  False  False   \n",
              "\n",
              "            cubic  \n",
              "title              \n",
              "apple       False  \n",
              "grapefruit  False  \n",
              "kiwi        False  \n",
              "plum        False  \n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "df = pd.read_csv('https://raw.githubusercontent.com/EgorDudyrev/FCApy/main/data/mango_bin.csv', index_col=0)\n",
        "df.columns = [f.split('_')[-1] for f in df.columns]\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "de8PEof6u8J5"
      },
      "source": [
        "# Pipeline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Joqy7QCNu8J5"
      },
      "source": [
        "# Step 0. Binarize the data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "QHv87ygJu8J5"
      },
      "outputs": [],
      "source": [
        "df_bin = df  # Skip this part as the data is already binary"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OgvmQkGnu8J6"
      },
      "source": [
        "Split the data to train and test"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "kkxmcv3iu8J6"
      },
      "outputs": [],
      "source": [
        "y_feat = 'fruit'\n",
        "df_test = df_bin.loc[['mango']]\n",
        "df_train = df_bin.drop(df_test.index, axis=0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "zWq_LuVQu8J6"
      },
      "outputs": [],
      "source": [
        "X_train, y_train = df_train.drop(y_feat, axis=1), df_train[y_feat]\n",
        "X_test, y_test = df_test.drop(y_feat, axis=1), df_test[y_feat]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "obxf3WTzu8J6"
      },
      "source": [
        "## Step 1. Build Monotone Concept Lattice"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OFZ9pxGXu8J7"
      },
      "source": [
        "Put binarized data in FormalContext and compute monotone ConceptLattice"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2s3nNfPCu8J7",
        "outputId": "d436cd4b-9c51-4599-d58e-30b8a2128247"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "FormalContext (7 objects, 9 attributes, 20 connections)\n",
              "           |firm|smooth|yellow|green|blue|white|round|oval|cubic|\n",
              "apple      |    |     X|     X|     |    |     |    X|    |     |\n",
              "grapefruit |    |      |     X|     |    |     |    X|    |     |\n",
              "kiwi       |    |      |      |    X|    |     |     |   X|     |\n",
              "plum       |    |     X|      |     |   X|     |     |   X|     |\n",
              "toy cube   |   X|     X|      |    X|    |     |     |    |    X|\n",
              "egg        |   X|     X|      |     |    |    X|     |   X|     |\n",
              "tennis ball|    |      |      |     |    |    X|    X|    |     |"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "K_train = FormalContext.from_pandas(X_train)\n",
        "K_train"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6pXFHy-Hu8J7",
        "outputId": "b4dcdb98-2be2-45fb-91e8-2974ea5c8626"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "46"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "L = ConceptLattice.from_context(K_train, is_monotone=True)\n",
        "len(L)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DawYnkrju8J8"
      },
      "source": [
        "Compute F1 score for each formal concept  (assuming that an object is predicted True if it is in the extent of the concept)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "1Jr6a97Uu8J8"
      },
      "outputs": [],
      "source": [
        "from sklearn.metrics import f1_score\n",
        "\n",
        "for c in L:\n",
        "    y_preds = np.zeros(K_train.n_objects)\n",
        "    y_preds[list(c.extent_i)] = 1\n",
        "    c.measures['f1_score'] = f1_score(y_train, y_preds)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gWFF79g1u8J8"
      },
      "source": [
        "Select indices of the best concepts from the lattice"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "V_TSgE1tu8J8"
      },
      "outputs": [],
      "source": [
        "best_concepts = list(L.measures['f1_score'].argsort()[::-1][:7])\n",
        "\n",
        "assert len({g_i for c in L[best_concepts] for g_i in c.extent_i})==K_train.n_objects, \"Selected concepts do not cover all train objects\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FEbdcXTuu8J9"
      },
      "source": [
        "Construct neural network based on concept lattice"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "m24Z9BF1u8J9"
      },
      "outputs": [],
      "source": [
        "cn = nl.ConceptNetwork.from_lattice(L, best_concepts, sorted(set(y_train)))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ECcFd7WNu8J9"
      },
      "source": [
        "Setup visuzalier for the architecture"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "hZCxWnGlu8J-"
      },
      "outputs": [],
      "source": [
        "vis = LineVizNx(node_label_font_size=14, node_label_func=lambda el_i, P: nl.neuron_label_func(el_i, P, set(cn.attributes))+'\\n\\n')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5qjyAmIHu8J-"
      },
      "source": [
        "Move the nodes in visualization to make it look pretty"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "ea6AL79Nu8J-"
      },
      "outputs": [],
      "source": [
        "vis.init_mover_per_poset(cn.poset)\n",
        "mvr = vis.mover\n",
        "for a, b in [(11, 15), (2, 3), (2,8), (2, 4), (4,5), (24, 26), (22, 26), (23, 25), (22, 24), (6, 7), ]:\n",
        "    mvr.swap_nodes(a, b)\n",
        "\n",
        "for nodes, vert in [\n",
        "    ([19, 18], 0), ([23, 22], 5), ([14, 21,20], 1), ([13, 24, 25], 6), ([26], 7), ([9, 15], 8)\n",
        "]:\n",
        "    for a in nodes:\n",
        "        mvr.place_node(a, mvr.posx[vert])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "id": "zjwsGnWgu8J_"
      },
      "outputs": [],
      "source": [
        "descr = {'smooth', 'green', 'oval'}\n",
        "\n",
        "traced = cn.trace_description(descr, include_targets=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        },
        "id": "izLszKkXu8J_",
        "outputId": "f5ad4218-dcf1-4dca-ea7c-da724c260443"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(15,5))\n",
        "\n",
        "vis.draw_poset(\n",
        "    cn.poset, ax=ax,\n",
        "    flg_node_indices=False,\n",
        "    node_label_func=lambda el_i, P: nl.neuron_label_func(el_i, P, set(cn.attributes), only_new_attrs=True)+'\\n\\n',\n",
        "    node_color=['darkblue' if el_i in traced else 'lightgray' for el_i in range(len(cn.poset))]\n",
        ")\n",
        "plt.title(f'NN based on 7 best concepts from monotone concept lattice', loc='left', x=0.05, size=24)\n",
        "\n",
        "plt.text(max(vis.mover.posx), min(vis.mover.posy)-0.3, f'*Blue neurons are the ones activated by description {descr}', fontsize=14, ha='right', color='dimgray')\n",
        "\n",
        "plt.subplots_adjust()\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JPrsmFfRu8KA"
      },
      "source": [
        "Now fit the network"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "P7g8i3ecu8KA"
      },
      "outputs": [],
      "source": [
        "cn.fit(X_train, y_train)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i7h8bK8Zu8KA"
      },
      "source": [
        "To obtain the prediction"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v20CoH4cu8KG",
        "outputId": "a15bf3e9-0bc2-4173-f954-262f2ce7cf44"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Class prediction [0]\n",
            "Class prediction with probabilities [[0.8191675  0.18083249]]\n",
            "True class [ True]\n"
          ]
        }
      ],
      "source": [
        "print('Class prediction', cn.predict(X_test).numpy())\n",
        "print('Class prediction with probabilities', cn.predict_proba(X_test).detach().numpy())\n",
        "print('True class', y_test.values)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZMye6Bv5u8KG"
      },
      "source": [
        "Let us look at the fitted weights of edges"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vUOWnnwdu8KH",
        "outputId": "5a0f64d7-da28-4488-f49b-d62ea7017b49"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sparselinear/sparselinear.py:301: UserWarning: torch.sparse.SparseTensor(indices, values, shape, *, device=) is deprecated.  Please use torch.sparse_coo_tensor(indices, values, shape, dtype=, device=). (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:605.)\n",
            "  weight = torch.sparse.FloatTensor(self.indices, self.weights, (self.out_features, self.in_features))\n"
          ]
        }
      ],
      "source": [
        "edge_weights = cn.edge_weights_from_network()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "id": "EQSb6l_nu8KH",
        "outputId": "7d9a7561-0a43-4896-a4e3-c21649a8a307"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import networkx as nx\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(15,5))\n",
        "\n",
        "vis.draw_poset(\n",
        "    cn.poset, ax=ax,\n",
        "    flg_node_indices=False,\n",
        "    node_label_func=lambda el_i, P: nl.neuron_label_func(el_i, P, set(cn.attributes), only_new_attrs=True)+'\\n\\n',\n",
        "    edge_color=[edge_weights[edge] for edge in cn.poset.to_networkx().edges],\n",
        "    edge_cmap=plt.cm.RdBu,\n",
        ")\n",
        "nx.draw_networkx_edge_labels(cn.poset.to_networkx(), vis.mover.pos, {k: f\"{v:.1f}\" for k,v in edge_weights.items()}, label_pos=0.7)\n",
        "\n",
        "plt.title('Neural network with fitted edge weights', size=24, x=0.05, loc='left')\n",
        "plt.tight_layout()\n",
        "plt.subplots_adjust()\n",
        "plt.savefig('fitted_network.png')\n",
        "plt.show()"
      ]
    }
  ],
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