{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# **!!!_2 Geometric interpretation of NNF**"
      ],
      "metadata": {
        "id": "SQY9F6DYog7B"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import math\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 1. Original data (from the table)\n",
        "# ------------------------------------------------------------\n",
        "data = [\n",
        "    (1, 1, 36), (2, 5, 4), (3, 6, 1), (4, 7, 0), (5, 8, 1),\n",
        "    (6, 9, 4), (7, 10, 9), (8, 11, 16), (9, 12, 25), (10, 13, 75),\n",
        "    (11, 14, 49), (12, 15, 64), (13, 16, 81), (14, 17, 100),\n",
        "    (15, 18, 121), (16, 19, 144), (17, 20, 169), (18, 21, 196),\n",
        "    (19, 22, 225), (20, 27, 400)\n",
        "]\n",
        "\n",
        "X = np.array([row[1] for row in data], dtype=np.float32).reshape(-1, 1)\n",
        "y = np.array([row[2] for row in data], dtype=np.float32).reshape(-1, 1)\n",
        "\n",
        "Q = X.shape[0]          # number of samples = 20\n",
        "N_x = X.shape[1]        # 1 input feature\n",
        "N_y = y.shape[1]        # 1 output variable\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 2. Calculation of the hidden layer neuron count bounds\n",
        "# ------------------------------------------------------------\n",
        "log2q = math.log2(Q)\n",
        "N_min = (N_y * Q) / ((1 + log2q) * (N_x + N_y))\n",
        "N_max = (N_y / (N_x + N_y)) * ((Q / N_x + 1) * (N_x + N_y + 1) + 1)\n",
        "\n",
        "print(\"\\n\" + \"=\"*50)\n",
        "print(f\"Q = {Q}, N_x = {N_x}, N_y = {N_y}\")\n",
        "print(f\"N_min = {N_min:.4f}, N_max = {N_max:.4f}\")\n",
        "print(\"=\"*50)\n",
        "\n",
        "# Index of the outlier (sample #10)\n",
        "outlier_idx = 9\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 3. Scaling to [-1, 1]\n",
        "# ------------------------------------------------------------\n",
        "def scale_to_minus1_1(data):\n",
        "    min_val = data.min(axis=0)\n",
        "    max_val = data.max(axis=0)\n",
        "    range_val = max_val - min_val\n",
        "    range_val[range_val == 0] = 1.0\n",
        "    scaled = 2.0 * (data - min_val) / range_val - 1.0\n",
        "    return scaled, min_val, max_val\n",
        "\n",
        "X_scaled, x_min, x_max = scale_to_minus1_1(X)\n",
        "y_scaled, y_min, y_max = scale_to_minus1_1(y)\n",
        "\n",
        "X_tensor = torch.tensor(X_scaled, dtype=torch.float32)\n",
        "y_tensor = torch.tensor(y_scaled, dtype=torch.float32)\n",
        "\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 4. Training networks for N = 2, 8, 13 and collecting results\n",
        "# ------------------------------------------------------------\n",
        "N_list = [2, 8, 13]\n",
        "predictions_scaled = {}   # predictions in scaled coordinates\n",
        "errors = {}               # squared errors (in scaled coordinates)\n",
        "\n",
        "for N in N_list:\n",
        "    torch.manual_seed(42)  # fix for reproducibility\n",
        "    model = nn.Sequential(\n",
        "        nn.Linear(N_x, N),\n",
        "        nn.Tanh(),\n",
        "        nn.Linear(N, N_y),\n",
        "    )\n",
        "    criterion = nn.MSELoss()\n",
        "    optimizer = optim.Rprop(model.parameters())\n",
        "\n",
        "    # Training\n",
        "    model.train()\n",
        "    for epoch in range(1000):\n",
        "        optimizer.zero_grad()\n",
        "        outputs = model(X_tensor)\n",
        "        loss = criterion(outputs, y_tensor)\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "\n",
        "    # Predictions and errors\n",
        "    model.eval()\n",
        "    with torch.no_grad():\n",
        "        pred = model(X_tensor).numpy().flatten()\n",
        "        err = (pred - y_scaled.flatten()) ** 2\n",
        "    predictions_scaled[N] = pred\n",
        "    errors[N] = err\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 5. Building the composite figure (2 rows, 3 columns)\n",
        "# ------------------------------------------------------------\n",
        "fig = plt.figure(figsize=(16, 10))\n",
        "\n",
        "# General settings\n",
        "x_orig = X.flatten()\n",
        "y_orig = y.flatten()\n",
        "x_smooth = np.linspace(X.min(), X.max(), 200)  # for smooth curve (not used, but kept)\n",
        "\n",
        "for i, N in enumerate(N_list):\n",
        "    # Top row: approximation\n",
        "    ax_top = plt.subplot(2, 3, i+1)\n",
        "    # Original points\n",
        "    colors = ['red' if j == outlier_idx else 'blue' for j in range(Q)]\n",
        "    ax_top.scatter(x_orig, y_orig, c=colors, s=40, edgecolors='black', linewidth=0.5)\n",
        "\n",
        "    # Add sample numbers (1 to 20) next to the points\n",
        "    for j in range(Q):\n",
        "        text_color = 'red' if j == outlier_idx else 'blue'\n",
        "        ax_top.text(x_orig[j], y_orig[j] + 5, str(j+1), fontsize=12,\n",
        "                    ha='center', va='bottom', color=text_color, fontweight='bold')\n",
        "\n",
        "    # Approximating curve (piecewise linear through points) with transparency 0.6\n",
        "    pred_orig = (predictions_scaled[N] + 1) / 2 * (y_max - y_min) + y_min\n",
        "    sort_idx = np.argsort(x_orig)\n",
        "    ax_top.plot(x_orig[sort_idx], pred_orig[sort_idx], 'g-', linewidth=2, alpha=0.6, label=f'N={N}')\n",
        "\n",
        "    ax_top.set_xlim(0, 28)\n",
        "    ax_top.set_ylim(0, 420)\n",
        "    ax_top.set_xlabel('X')\n",
        "    ax_top.set_ylabel('y')\n",
        "    ax_top.set_title(f'Approximation, N={N}')\n",
        "    ax_top.grid(True, linestyle=':', alpha=0.05)\n",
        "\n",
        "    # Bottom row: errors\n",
        "    ax_bottom = plt.subplot(2, 3, i+4)  # indices 4,5,6 for the three plots\n",
        "    examples = np.arange(1, Q+1)\n",
        "    bars = ax_bottom.bar(examples, errors[N], color='skyblue', edgecolor='black')\n",
        "    # highlight the outlier in red\n",
        "    bars[outlier_idx].set_color('red')\n",
        "    ax_bottom.set_xlabel('Sample number')\n",
        "    ax_bottom.set_ylabel('Error (MSE)')\n",
        "    ax_bottom.set_title(f'Errors, N={N}')\n",
        "    ax_bottom.set_xticks(examples[::2])\n",
        "    ax_bottom.grid(axis='y', linestyle=':', alpha=0.7)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "vGiOvsNqpq78",
        "outputId": "8a8bfb9f-8575-4926-86e2-b5c0256b7d34"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "==================================================\n",
            "Q = 20, N_x = 1, N_y = 1\n",
            "N_min = 1.8790, N_max = 32.0000\n",
            "==================================================\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x1000 with 6 Axes>"
            ],
            "image/png": 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  ]
}