{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial 2: ``ScipyOptimizer`` Tutorial\n",
    "\n",
    "This tutorial demonstrates how to use the `ScipyOptimizer` from BrainTools for gradient-based optimization. The ScipyOptimizer provides a convenient wrapper around SciPy's optimization methods with automatic differentiation via JAX, support for complex parameter structures, and seamless integration with BrainUnit quantities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction and Setup\n",
    "\n",
    "The `ScipyOptimizer` is designed for gradient-based optimization where derivatives can be computed automatically via JAX. It's particularly useful for:\n",
    "- Smooth, differentiable objective functions\n",
    "- Neural network parameter optimization\n",
    "- Physics-based models with analytical gradients\n",
    "- Problems where gradient information is reliable\n",
    "\n",
    "Key advantages over derivative-free methods:\n",
    "- **Faster convergence** for smooth problems\n",
    "- **Higher precision** solutions\n",
    "- **Automatic gradients** via JAX\n",
    "- **Mature algorithms** from SciPy\n",
    "\n",
    "Let's start by importing the necessary libraries:"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:17.233909Z",
     "start_time": "2025-09-23T16:19:14.060941Z"
    }
   },
   "source": [
    "# Core imports\n",
    "import jax\n",
    "import jax.numpy as jnp\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import OptimizeResult\n",
    "\n",
    "# BrainTools imports\n",
    "import braintools as bts\n",
    "import brainunit as u\n",
    "import brainstate as bst\n",
    "\n",
    "# Set up plotting\n",
    "plt.style.use('default')\n",
    "plt.rcParams['figure.figsize'] = (10, 6)\n",
    "\n",
    "print(\"BrainTools version:\", bts.__version__)\n",
    "print(\"JAX version:\", jax.__version__)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BrainTools version: 0.0.12\n",
      "JAX version: 0.7.1\n"
     ]
    }
   ],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let's check if SciPy is installed (it's required for the optimizer to work):"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:17.267697Z",
     "start_time": "2025-09-23T16:19:17.262722Z"
    }
   },
   "source": [
    "try:\n",
    "    import scipy\n",
    "    from scipy.optimize import minimize\n",
    "    print(f\"SciPy version: {scipy.__version__}\")\n",
    "    print(\"✓ SciPy is available\")\n",
    "except ImportError:\n",
    "    print(\"❌ SciPy is not installed. Please install it with:\")\n",
    "    print(\"   pip install scipy\")\n",
    "    raise"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SciPy version: 1.14.1\n",
      "✓ SciPy is available\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Usage: Scalar Parameters\n",
    "\n",
    "Let's start with a simple example: optimizing a quadratic function with two scalar parameters."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:17.382134Z",
     "start_time": "2025-09-23T16:19:17.300999Z"
    }
   },
   "source": [
    "# Define a simple quadratic loss function\n",
    "def quadratic_loss(x, y):\n",
    "    \"\"\"\n",
    "    Simple quadratic function with known minimum at (2, -1).\n",
    "    \n",
    "    Args:\n",
    "        x, y: Scalar parameters\n",
    "        \n",
    "    Returns:\n",
    "        Scalar loss value\n",
    "    \"\"\"\n",
    "    return (x - 2.0)**2 + (y + 1.0)**2\n",
    "\n",
    "# Define bounds for each parameter: (min, max)\n",
    "bounds = [\n",
    "    (-5.0, 5.0),  # bounds for x\n",
    "    (-3.0, 3.0),  # bounds for y\n",
    "]\n",
    "\n",
    "# Create the optimizer\n",
    "optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=quadratic_loss,\n",
    "    bounds=bounds,\n",
    "    method='L-BFGS-B'  # Limited-memory BFGS with bounds\n",
    ")\n",
    "\n",
    "print(\"Optimizer created successfully!\")\n",
    "print(f\"Method: {optimizer.method}\")\n",
    "print(f\"Bounds structure: {type(bounds).__name__}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizer created successfully!\n",
      "Method: L-BFGS-B\n",
      "Bounds structure: list\n"
     ]
    }
   ],
   "execution_count": 3
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:17.653165Z",
     "start_time": "2025-09-23T16:19:17.389667Z"
    }
   },
   "source": [
    "# Run the optimization\n",
    "result = optimizer.minimize(n_iter=3)  # Try 3 random starting points\n",
    "\n",
    "print(f\"\\nOptimization completed!\")\n",
    "print(f\"Success: {result.success}\")\n",
    "print(f\"Message: {result.message}\")\n",
    "print(f\"Optimal parameters: x={result.x[0]:.6f}, y={result.x[1]:.6f}\")\n",
    "print(f\"True optimum: x=2.0, y=-1.0\")\n",
    "print(f\"Final loss: {result.fun:.10f}\")\n",
    "print(f\"Function evaluations: {result.nfev}\")\n",
    "print(f\"Gradient evaluations: {result.njev}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Optimization completed!\n",
      "Success: True\n",
      "Message: CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL\n",
      "Optimal parameters: x=2.000000, y=-1.000000\n",
      "True optimum: x=2.0, y=-1.0\n",
      "Final loss: 0.0000000000\n",
      "Function evaluations: 4\n",
      "Gradient evaluations: 4\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:18.237752Z",
     "start_time": "2025-09-23T16:19:17.672731Z"
    }
   },
   "source": [
    "# Visualize the optimization landscape and result\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "# Plot the function landscape\n",
    "x_range = np.linspace(-5, 5, 100)\n",
    "y_range = np.linspace(-3, 3, 100)\n",
    "X, Y = np.meshgrid(x_range, y_range)\n",
    "Z = (X - 2.0)**2 + (Y + 1.0)**2\n",
    "\n",
    "contour = ax1.contourf(X, Y, Z, levels=30, cmap='viridis', alpha=0.7)\n",
    "ax1.contour(X, Y, Z, levels=20, colors='black', alpha=0.3, linewidths=0.5)\n",
    "plt.colorbar(contour, ax=ax1)\n",
    "\n",
    "# Mark the true optimum and found optimum\n",
    "ax1.plot(2.0, -1.0, 'r*', markersize=15, label='True optimum')\n",
    "ax1.plot(result.x[0], result.x[1], 'bo', markersize=10, label='Found optimum')\n",
    "\n",
    "ax1.set_xlabel('x')\n",
    "ax1.set_ylabel('y')\n",
    "ax1.set_title('Quadratic Function Landscape')\n",
    "ax1.legend()\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# Show convergence (we don't have iteration history, so show final result)\n",
    "ax2.bar(['Final Loss'], [result.fun], color='blue', alpha=0.7)\n",
    "ax2.set_ylabel('Loss Value')\n",
    "ax2.set_title('Optimization Result')\n",
    "ax2.set_yscale('log')\n",
    "ax2.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(f\"Distance from true optimum: {np.sqrt((result.x[0] - 2.0)**2 + (result.x[1] + 1.0)**2):.2e}\")"
   ],
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\adadu\\AppData\\Local\\Temp\\ipykernel_59268\\1560779676.py:28: UserWarning: Data has no positive values, and therefore cannot be log-scaled.\n",
      "  ax2.set_yscale('log')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x500 with 3 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance from true optimum: 0.00e+00\n"
     ]
    }
   ],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multi-dimensional Array Parameters\n",
    "\n",
    "The ScipyOptimizer can handle multi-dimensional arrays as parameters. Let's optimize a function that takes matrix parameters."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:18.300913Z",
     "start_time": "2025-09-23T16:19:18.250027Z"
    }
   },
   "source": [
    "# Define a loss function with matrix parameters\n",
    "def matrix_frobenius_loss(W, b):\n",
    "    \"\"\"\n",
    "    Find matrix W and vector b that minimize Frobenius norm from targets.\n",
    "    \n",
    "    Args:\n",
    "        W: Matrix parameter of shape (3, 2)\n",
    "        b: Vector parameter of shape (2,)\n",
    "        \n",
    "    Returns:\n",
    "        Scalar loss (Frobenius norm squared)\n",
    "    \"\"\"\n",
    "    W_target = jnp.array([[1.0, -0.5], [0.3, 1.2], [-0.8, 0.9]])\n",
    "    b_target = jnp.array([0.1, -0.3])\n",
    "    \n",
    "    W_diff = W - W_target\n",
    "    b_diff = b - b_target\n",
    "    \n",
    "    return jnp.sum(W_diff**2) + jnp.sum(b_diff**2)\n",
    "\n",
    "# Define bounds for array parameters\n",
    "bounds = [\n",
    "    (jnp.full((3, 2), -2.0), jnp.full((3, 2), 2.0)),  # bounds for W (3x2 matrix)\n",
    "    (jnp.full(2, -1.0), jnp.full(2, 1.0)),            # bounds for b (2D vector)\n",
    "]\n",
    "\n",
    "# Create optimizer\n",
    "matrix_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=matrix_frobenius_loss,\n",
    "    bounds=bounds,\n",
    "    method='L-BFGS-B'  # Good for smooth, bounded problems\n",
    ")\n",
    "\n",
    "print(\"Multi-dimensional optimizer created!\")\n",
    "print(f\"W parameter shape: {bounds[0][0].shape}\")\n",
    "print(f\"b parameter shape: {bounds[1][0].shape}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Multi-dimensional optimizer created!\n",
      "W parameter shape: (3, 2)\n",
      "b parameter shape: (2,)\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:18.707197Z",
     "start_time": "2025-09-23T16:19:18.306922Z"
    }
   },
   "source": [
    "# Run optimization\n",
    "matrix_result = matrix_optimizer.minimize(n_iter=5)\n",
    "\n",
    "W_best, b_best = matrix_result.x\n",
    "print(f\"\\nOptimization completed!\")\n",
    "print(f\"Success: {matrix_result.success}\")\n",
    "print(f\"Function evaluations: {matrix_result.nfev}\")\n",
    "\n",
    "print(f\"\\nOptimal W matrix:\")\n",
    "print(W_best)\n",
    "print(f\"\\nOptimal b vector:\")\n",
    "print(b_best)\n",
    "\n",
    "# Compare with targets\n",
    "W_target = jnp.array([[1.0, -0.5], [0.3, 1.2], [-0.8, 0.9]])\n",
    "b_target = jnp.array([0.1, -0.3])\n",
    "print(f\"\\nTarget W matrix:\")\n",
    "print(W_target)\n",
    "print(f\"\\nTarget b vector:\")\n",
    "print(b_target)\n",
    "\n",
    "print(f\"\\nFinal loss: {matrix_result.fun:.10f}\")\n",
    "print(f\"W error (Frobenius): {jnp.linalg.norm(W_best - W_target):.2e}\")\n",
    "print(f\"b error (L2): {jnp.linalg.norm(b_best - b_target):.2e}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Optimization completed!\n",
      "Success: True\n",
      "Function evaluations: 3\n",
      "\n",
      "Optimal W matrix:\n",
      "[[ 1.  -0.5]\n",
      " [ 0.3  1.2]\n",
      " [-0.8  0.9]]\n",
      "\n",
      "Optimal b vector:\n",
      "[ 0.10000002 -0.3       ]\n",
      "\n",
      "Target W matrix:\n",
      "[[ 1.  -0.5]\n",
      " [ 0.3  1.2]\n",
      " [-0.8  0.9]]\n",
      "\n",
      "Target b vector:\n",
      "[ 0.1 -0.3]\n",
      "\n",
      "Final loss: 0.0000000000\n",
      "W error (Frobenius): 0.00e+00\n",
      "b error (L2): 2.24e-08\n"
     ]
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:19.321069Z",
     "start_time": "2025-09-23T16:19:18.717515Z"
    }
   },
   "source": [
    "# Visualize the matrix optimization results\n",
    "fig, axes = plt.subplots(2, 3, figsize=(15, 8))\n",
    "\n",
    "# Plot W matrix: target, found, and difference\n",
    "im1 = axes[0, 0].imshow(W_target, cmap='RdBu_r', aspect='auto')\n",
    "axes[0, 0].set_title('Target W Matrix')\n",
    "axes[0, 0].set_xlabel('Column')\n",
    "axes[0, 0].set_ylabel('Row')\n",
    "plt.colorbar(im1, ax=axes[0, 0])\n",
    "\n",
    "im2 = axes[0, 1].imshow(W_best, cmap='RdBu_r', aspect='auto')\n",
    "axes[0, 1].set_title('Found W Matrix')\n",
    "axes[0, 1].set_xlabel('Column')\n",
    "axes[0, 1].set_ylabel('Row')\n",
    "plt.colorbar(im2, ax=axes[0, 1])\n",
    "\n",
    "W_diff = W_best - W_target\n",
    "im3 = axes[0, 2].imshow(W_diff, cmap='RdBu_r', aspect='auto')\n",
    "axes[0, 2].set_title('Difference (Found - Target)')\n",
    "axes[0, 2].set_xlabel('Column')\n",
    "axes[0, 2].set_ylabel('Row')\n",
    "plt.colorbar(im3, ax=axes[0, 2])\n",
    "\n",
    "# Plot b vector: target, found, and difference\n",
    "x_pos = np.arange(len(b_target))\n",
    "width = 0.35\n",
    "\n",
    "axes[1, 0].bar(x_pos - width/2, b_target, width, label='Target', alpha=0.7)\n",
    "axes[1, 0].bar(x_pos + width/2, b_best, width, label='Found', alpha=0.7)\n",
    "axes[1, 0].set_xlabel('Element')\n",
    "axes[1, 0].set_ylabel('Value')\n",
    "axes[1, 0].set_title('b Vector Comparison')\n",
    "axes[1, 0].legend()\n",
    "axes[1, 0].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot the difference in b\n",
    "b_diff = b_best - b_target\n",
    "axes[1, 1].bar(x_pos, b_diff, alpha=0.7, color='red')\n",
    "axes[1, 1].set_xlabel('Element')\n",
    "axes[1, 1].set_ylabel('Difference')\n",
    "axes[1, 1].set_title('b Vector Difference')\n",
    "axes[1, 1].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot optimization info\n",
    "info_text = f\"\"\"Optimization Results:\n",
    "Success: {matrix_result.success}\n",
    "Final Loss: {matrix_result.fun:.2e}\n",
    "Function Evals: {matrix_result.nfev}\n",
    "Gradient Evals: {matrix_result.njev}\n",
    "W Error: {jnp.linalg.norm(W_diff):.2e}\n",
    "b Error: {jnp.linalg.norm(b_diff):.2e}\"\"\"\n",
    "\n",
    "axes[1, 2].text(0.1, 0.9, info_text, transform=axes[1, 2].transAxes, \n",
    "                verticalalignment='top', fontsize=10, fontfamily='monospace')\n",
    "axes[1, 2].set_xlim(0, 1)\n",
    "axes[1, 2].set_ylim(0, 1)\n",
    "axes[1, 2].axis('off')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x800 with 9 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 8
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Named Parameters with Dictionary Bounds\n",
    "\n",
    "For better organization, especially with many parameters, you can use dictionary bounds to give meaningful names to your parameters."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:19.334973Z",
     "start_time": "2025-09-23T16:19:19.328591Z"
    }
   },
   "source": [
    "# Define a loss function that accepts named parameters\n",
    "def rosenbrock_loss(**params):\n",
    "    \"\"\"\n",
    "    The famous Rosenbrock function with named parameters.\n",
    "    Global minimum at x=1, y=1 with value 0.\n",
    "    \n",
    "    Args:\n",
    "        **params: Dictionary with keys 'x' and 'y'\n",
    "        \n",
    "    Returns:\n",
    "        Scalar loss value\n",
    "    \"\"\"\n",
    "    x, y = params['x'], params['y']\n",
    "    a, b = 1.0, 100.0\n",
    "    return (a - x)**2 + b * (y - x**2)**2\n",
    "\n",
    "# Define named bounds\n",
    "named_bounds = {\n",
    "    'x': (-2.0, 2.0),\n",
    "    'y': (-1.0, 3.0)\n",
    "}\n",
    "\n",
    "# Create optimizer with named parameters\n",
    "named_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=rosenbrock_loss,\n",
    "    bounds=named_bounds,\n",
    "    method='L-BFGS-B'\n",
    ")\n",
    "\n",
    "print(\"Named parameter optimizer created!\")\n",
    "print(f\"Parameters: {list(named_bounds.keys())}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Named parameter optimizer created!\n",
      "Parameters: ['x', 'y']\n"
     ]
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:19.656265Z",
     "start_time": "2025-09-23T16:19:19.351863Z"
    }
   },
   "source": [
    "# Run optimization\n",
    "named_result = named_optimizer.minimize(n_iter=5)\n",
    "\n",
    "print(f\"\\nOptimization completed!\")\n",
    "print(f\"Success: {named_result.success}\")\n",
    "print(f\"Function evaluations: {named_result.nfev}\")\n",
    "print(f\"Gradient evaluations: {named_result.njev}\")\n",
    "\n",
    "print(f\"\\nOptimal parameters:\")\n",
    "for param_name, value in named_result.x.items():\n",
    "    print(f\"  {param_name}: {value:.6f}\")\n",
    "\n",
    "print(f\"\\nTrue optimal values:\")\n",
    "print(f\"  x: 1.000000\")\n",
    "print(f\"  y: 1.000000\")\n",
    "\n",
    "print(f\"\\nFinal loss: {named_result.fun:.10f}\")\n",
    "print(f\"Distance from optimum: {np.sqrt((named_result.x['x'] - 1.0)**2 + (named_result.x['y'] - 1.0)**2):.2e}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Optimization completed!\n",
      "Success: True\n",
      "Function evaluations: 30\n",
      "Gradient evaluations: 30\n",
      "\n",
      "Optimal parameters:\n",
      "  x: 1.000000\n",
      "  y: 1.000000\n",
      "\n",
      "True optimal values:\n",
      "  x: 1.000000\n",
      "  y: 1.000000\n",
      "\n",
      "Final loss: 0.0000000000\n",
      "Distance from optimum: 2.67e-07\n"
     ]
    }
   ],
   "execution_count": 10
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:19.909263Z",
     "start_time": "2025-09-23T16:19:19.668371Z"
    }
   },
   "source": [
    "# Visualize the Rosenbrock function and optimization result\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "# Plot the Rosenbrock function landscape\n",
    "x_range = np.linspace(-2, 2, 100)\n",
    "y_range = np.linspace(-1, 3, 100)\n",
    "X, Y = np.meshgrid(x_range, y_range)\n",
    "Z = (1 - X)**2 + 100 * (Y - X**2)**2\n",
    "\n",
    "# Use log scale for better visualization\n",
    "Z_log = np.log10(Z + 1e-10)\n",
    "contour = ax1.contourf(X, Y, Z_log, levels=30, cmap='viridis')\n",
    "ax1.contour(X, Y, Z_log, levels=20, colors='black', alpha=0.3, linewidths=0.5)\n",
    "plt.colorbar(contour, ax=ax1, label='log10(Loss)')\n",
    "\n",
    "# Mark the true optimum and found optimum\n",
    "ax1.plot(1.0, 1.0, 'r*', markersize=15, label='True optimum')\n",
    "ax1.plot(named_result.x['x'], named_result.x['y'], 'bo', markersize=10, label='Found optimum')\n",
    "\n",
    "ax1.set_xlabel('x')\n",
    "ax1.set_ylabel('y')\n",
    "ax1.set_title('Rosenbrock Function (log scale)')\n",
    "ax1.legend()\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# Plot parameter values\n",
    "param_names = list(named_result.x.keys())\n",
    "param_values = [named_result.x[name] for name in param_names]\n",
    "target_values = [1.0, 1.0]\n",
    "\n",
    "x_pos = np.arange(len(param_names))\n",
    "width = 0.35\n",
    "\n",
    "ax2.bar(x_pos - width/2, target_values, width, label='Target', alpha=0.7, color='red')\n",
    "ax2.bar(x_pos + width/2, param_values, width, label='Found', alpha=0.7, color='blue')\n",
    "\n",
    "ax2.set_xlabel('Parameter')\n",
    "ax2.set_ylabel('Value')\n",
    "ax2.set_title('Parameter Comparison')\n",
    "ax2.set_xticks(x_pos)\n",
    "ax2.set_xticklabels(param_names)\n",
    "ax2.legend()\n",
    "ax2.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x500 with 3 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 11
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Working with BrainUnit Quantities\n",
    "\n",
    "The ScipyOptimizer seamlessly integrates with BrainUnit quantities, allowing you to optimize parameters with physical units."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:19.924912Z",
     "start_time": "2025-09-23T16:19:19.916582Z"
    }
   },
   "source": [
    "# Define a loss function for neuron model parameters with units\n",
    "def neuron_model_loss(tau_m, V_th, V_reset, I_ext):\n",
    "    \"\"\"\n",
    "    Loss function for fitting a neuron model to target parameters.\n",
    "    \n",
    "    Args:\n",
    "        tau_m: Membrane time constant (scalar)\n",
    "        V_th: Threshold voltage (scalar)\n",
    "        V_reset: Reset voltage (scalar)\n",
    "        I_ext: External current (scalar)\n",
    "        \n",
    "    Returns:\n",
    "        Scalar loss representing deviation from target behavior\n",
    "    \"\"\"\n",
    "    # Target values (without units - optimizer handles unit conversion)\n",
    "    tau_target = 20.0    # ms\n",
    "    V_th_target = -50.0  # mV\n",
    "    V_reset_target = -70.0  # mV\n",
    "    I_target = 100.0     # pA\n",
    "    \n",
    "    # Compute normalized squared differences\n",
    "    tau_loss = ((tau_m - tau_target) / 10.0)**2\n",
    "    V_th_loss = ((V_th - V_th_target) / 10.0)**2\n",
    "    V_reset_loss = ((V_reset - V_reset_target) / 10.0)**2\n",
    "    I_loss = ((I_ext - I_target) / 50.0)**2\n",
    "    \n",
    "    return tau_loss + V_th_loss + V_reset_loss + I_loss\n",
    "\n",
    "# Define bounds with units\n",
    "unit_bounds = {\n",
    "    'tau_m': (5.0 * u.ms, 50.0 * u.ms),\n",
    "    'V_th': (-80.0 * u.mV, -30.0 * u.mV),\n",
    "    'V_reset': (-90.0 * u.mV, -60.0 * u.mV),\n",
    "    'I_ext': (10.0 * u.pA, 200.0 * u.pA)\n",
    "}\n",
    "\n",
    "# Create optimizer\n",
    "unit_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=neuron_model_loss,\n",
    "    bounds=unit_bounds,\n",
    "    method='L-BFGS-B'\n",
    ")\n",
    "\n",
    "print(\"Neuron parameter optimizer with units created!\")\n",
    "for name, (low, high) in unit_bounds.items():\n",
    "    print(f\"  {name}: {low} to {high}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Neuron parameter optimizer with units created!\n",
      "  tau_m: 5.0 * msecond to 50.0 * msecond\n",
      "  V_th: -80.0 * mvolt to -30.0 * mvolt\n",
      "  V_reset: -90.0 * mvolt to -60.0 * mvolt\n",
      "  I_ext: 10.0 * pamp to 200.0 * pamp\n"
     ]
    }
   ],
   "execution_count": 12
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:20.137214Z",
     "start_time": "2025-09-23T16:19:19.938426Z"
    }
   },
   "source": [
    "# Run optimization with units\n",
    "unit_result = unit_optimizer.minimize(n_iter=3)\n",
    "\n",
    "print(f\"\\nOptimization completed!\")\n",
    "print(f\"Success: {unit_result.success}\")\n",
    "print(f\"Function evaluations: {unit_result.nfev}\")\n",
    "\n",
    "print(f\"\\nOptimal neuron parameters:\")\n",
    "for param_name, value in unit_result.x.items():\n",
    "    print(f\"  {param_name}: {value:.6f}\")\n",
    "\n",
    "print(f\"\\nTarget parameters:\")\n",
    "print(f\"  tau_m: 20.0\")\n",
    "print(f\"  V_th: -50.0\")\n",
    "print(f\"  V_reset: -70.0\")\n",
    "print(f\"  I_ext: 100.0\")\n",
    "\n",
    "print(f\"\\nFinal loss: {unit_result.fun:.10f}\")\n",
    "\n",
    "# Note: The optimizer works with dimensionless values internally\n",
    "# but maintains the parameter structure"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Optimization completed!\n",
      "Success: True\n",
      "Function evaluations: 9\n",
      "\n",
      "Optimal neuron parameters:\n",
      "  I_ext: 100.000000\n",
      "  V_reset: -70.000000\n",
      "  V_th: -50.000000\n",
      "  tau_m: 20.000000\n",
      "\n",
      "Target parameters:\n",
      "  tau_m: 20.0\n",
      "  V_th: -50.0\n",
      "  V_reset: -70.0\n",
      "  I_ext: 100.0\n",
      "\n",
      "Final loss: 0.0000000000\n"
     ]
    }
   ],
   "execution_count": 13
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:19:20.467110Z",
     "start_time": "2025-09-23T16:19:20.151754Z"
    }
   },
   "source": [
    "# Visualize neuron parameter optimization results\n",
    "fig, axes = plt.subplots(2, 2, figsize=(12, 8))\n",
    "axes = axes.flatten()\n",
    "\n",
    "# Define target values and units for visualization\n",
    "targets = {\n",
    "    'tau_m': (20.0, 'ms'),\n",
    "    'V_th': (-50.0, 'mV'),\n",
    "    'V_reset': (-70.0, 'mV'),\n",
    "    'I_ext': (100.0, 'pA')\n",
    "}\n",
    "\n",
    "for i, (param_name, (target_val, unit)) in enumerate(targets.items()):\n",
    "    found_val = unit_result.x[param_name]\n",
    "    \n",
    "    # Plot comparison\n",
    "    axes[i].bar(['Target', 'Found'], [target_val, found_val], \n",
    "               color=['red', 'blue'], alpha=0.7)\n",
    "    axes[i].set_ylabel(f'{param_name} ({unit})')\n",
    "    axes[i].set_title(f'{param_name} Optimization')\n",
    "    axes[i].grid(True, alpha=0.3)\n",
    "    \n",
    "    # Add value labels on bars\n",
    "    axes[i].text(0, target_val, f'{target_val:.1f}', ha='center', va='bottom')\n",
    "    axes[i].text(1, found_val, f'{found_val:.1f}', ha='center', va='bottom')\n",
    "    \n",
    "    # Add error information\n",
    "    error = abs(found_val - target_val)\n",
    "    rel_error = error / abs(target_val) * 100\n",
    "    axes[i].text(0.5, max(target_val, found_val) * 1.1, \n",
    "                f'Error: {error:.2f} ({rel_error:.2f}%)', \n",
    "                ha='center', va='bottom', fontsize=10)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\nParameter Errors:\")\n",
    "for param_name, (target_val, unit) in targets.items():\n",
    "    found_val = unit_result.x[param_name]\n",
    "    error = abs(found_val - target_val)\n",
    "    rel_error = error / abs(target_val) * 100\n",
    "    print(f\"  {param_name}: {error:.3f} {unit} ({rel_error:.2f}%)\")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x800 with 4 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Parameter Errors:\n",
      "  tau_m: 0.000 ms (0.00%)\n",
      "  V_th: 0.000 mV (0.00%)\n",
      "  V_reset: 0.000 mV (0.00%)\n",
      "  I_ext: 0.000 pA (0.00%)\n"
     ]
    }
   ],
   "execution_count": 14
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Different SciPy Methods\n",
    "\n",
    "SciPy provides many optimization algorithms. Let's compare several of them on the same problem."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:13.403907Z",
     "start_time": "2025-09-23T16:22:12.564280Z"
    }
   },
   "source": [
    "# Define a more challenging test function\n",
    "def beale_function(x, y):\n",
    "    \"\"\"\n",
    "    Beale function - a challenging optimization benchmark.\n",
    "    Global minimum at (3, 0.5) with value 0.\n",
    "    \"\"\"\n",
    "    return ((1.5 - x + x*y)**2 + \n",
    "            (2.25 - x + x*y**2)**2 + \n",
    "            (2.625 - x + x*y**3)**2)\n",
    "\n",
    "bounds = [(-4.5, 4.5), (-4.5, 4.5)]\n",
    "\n",
    "# Test different SciPy methods\n",
    "methods = [\n",
    "    'L-BFGS-B',    # Limited memory BFGS with bounds\n",
    "    # 'TNC',         # Truncated Newton with bounds\n",
    "    'SLSQP',       # Sequential Least Squares Programming\n",
    "    'Powell',      # Powell's method (derivative-free but included for comparison)\n",
    "]\n",
    "\n",
    "results = {}\n",
    "\n",
    "print(\"Testing different SciPy optimization methods...\\n\")\n",
    "\n",
    "for method in methods:\n",
    "    print(f\"Testing {method}...\")\n",
    "    \n",
    "    optimizer = bts.optim.ScipyOptimizer(\n",
    "        loss_fun=beale_function,\n",
    "        bounds=bounds,\n",
    "        method=method\n",
    "    )\n",
    "    \n",
    "    result = optimizer.minimize(n_iter=3)\n",
    "    \n",
    "    results[method] = {\n",
    "        'result': result,\n",
    "        'success': result.success,\n",
    "        'final_loss': result.fun,\n",
    "        'nfev': result.nfev,\n",
    "        'njev': getattr(result, 'njev', 0),\n",
    "        'params': result.x\n",
    "    }\n",
    "    \n",
    "    print(f\"  Success: {result.success}\")\n",
    "    print(f\"  Final loss: {result.fun:.8f}\")\n",
    "    print(f\"  Parameters: ({result.x[0]:.4f}, {result.x[1]:.4f})\")\n",
    "    print(f\"  Function evaluations: {result.nfev}\")\n",
    "    if hasattr(result, 'njev'):\n",
    "        print(f\"  Gradient evaluations: {result.njev}\")\n",
    "    print()\n",
    "\n",
    "print(\"Method comparison completed!\")\n",
    "print(f\"\\nTrue optimum: (3.0, 0.5) with loss = 0.0\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing different SciPy optimization methods...\n",
      "\n",
      "Testing L-BFGS-B...\n",
      "  Success: True\n",
      "  Final loss: 0.00000000\n",
      "  Parameters: (3.0000, 0.5000)\n",
      "  Function evaluations: 21\n",
      "  Gradient evaluations: 21\n",
      "\n",
      "Testing SLSQP...\n",
      "  Success: True\n",
      "  Final loss: 0.00000011\n",
      "  Parameters: (2.9992, 0.4998)\n",
      "  Function evaluations: 42\n",
      "  Gradient evaluations: 33\n",
      "\n",
      "Testing Powell...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\codes\\projects\\braintools\\braintools\\optim\\_scipy_optimizer.py:286: RuntimeWarning: Method Powell does not use gradient information (jac).\n",
      "  results = minimize(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Success: True\n",
      "  Final loss: 0.00000000\n",
      "  Parameters: (3.0000, 0.5000)\n",
      "  Function evaluations: 483\n",
      "\n",
      "Method comparison completed!\n",
      "\n",
      "True optimum: (3.0, 0.5) with loss = 0.0\n"
     ]
    }
   ],
   "execution_count": 16
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:18.560999Z",
     "start_time": "2025-09-23T16:22:17.939696Z"
    }
   },
   "source": [
    "# Visualize method comparison\n",
    "fig, axes = plt.subplots(2, 2, figsize=(14, 10))\n",
    "\n",
    "# Plot the Beale function landscape\n",
    "x_range = np.linspace(-4.5, 4.5, 100)\n",
    "y_range = np.linspace(-4.5, 4.5, 100)\n",
    "X, Y = np.meshgrid(x_range, y_range)\n",
    "Z = ((1.5 - X + X*Y)**2 + \n",
    "     (2.25 - X + X*Y**2)**2 + \n",
    "     (2.625 - X + X*Y**3)**2)\n",
    "\n",
    "# Use log scale for better visualization\n",
    "Z_log = np.log10(Z + 1e-10)\n",
    "contour = axes[0, 0].contourf(X, Y, Z_log, levels=30, cmap='viridis')\n",
    "axes[0, 0].contour(X, Y, Z_log, levels=20, colors='black', alpha=0.3, linewidths=0.5)\n",
    "plt.colorbar(contour, ax=axes[0, 0], label='log10(Loss)')\n",
    "\n",
    "# Plot results from different methods\n",
    "colors = ['red', 'blue', 'green', 'orange']\n",
    "for i, (method, result_data) in enumerate(results.items()):\n",
    "    x_opt, y_opt = result_data['params']\n",
    "    axes[0, 0].plot(x_opt, y_opt, 'o', color=colors[i], markersize=8, \n",
    "                   label=f'{method}', markeredgecolor='black')\n",
    "\n",
    "# Mark true optimum\n",
    "axes[0, 0].plot(3.0, 0.5, '*', color='black', markersize=15, label='True optimum')\n",
    "\n",
    "axes[0, 0].set_xlabel('x')\n",
    "axes[0, 0].set_ylabel('y')\n",
    "axes[0, 0].set_title('Beale Function: Method Comparison')\n",
    "axes[0, 0].legend()\n",
    "axes[0, 0].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot final losses\n",
    "method_names = list(results.keys())\n",
    "final_losses = [results[m]['final_loss'] for m in method_names]\n",
    "bars = axes[0, 1].bar(method_names, final_losses, color=colors[:len(method_names)], alpha=0.7)\n",
    "axes[0, 1].set_yscale('log')\n",
    "axes[0, 1].set_ylabel('Final Loss')\n",
    "axes[0, 1].set_title('Final Performance')\n",
    "axes[0, 1].tick_params(axis='x', rotation=45)\n",
    "axes[0, 1].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot function evaluations\n",
    "nfevs = [results[m]['nfev'] for m in method_names]\n",
    "axes[1, 0].bar(method_names, nfevs, color=colors[:len(method_names)], alpha=0.7)\n",
    "axes[1, 0].set_ylabel('Function Evaluations')\n",
    "axes[1, 0].set_title('Computational Cost')\n",
    "axes[1, 0].tick_params(axis='x', rotation=45)\n",
    "axes[1, 0].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot success/distance from optimum\n",
    "distances = []\n",
    "for method in method_names:\n",
    "    x_opt, y_opt = results[method]['params']\n",
    "    dist = np.sqrt((x_opt - 3.0)**2 + (y_opt - 0.5)**2)\n",
    "    distances.append(dist)\n",
    "\n",
    "bars = axes[1, 1].bar(method_names, distances, color=colors[:len(method_names)], alpha=0.7)\n",
    "axes[1, 1].set_yscale('log')\n",
    "axes[1, 1].set_ylabel('Distance from True Optimum')\n",
    "axes[1, 1].set_title('Accuracy')\n",
    "axes[1, 1].tick_params(axis='x', rotation=45)\n",
    "axes[1, 1].grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Print summary\n",
    "print(\"\\nMethod Performance Summary:\")\n",
    "print(\"Method\\t\\tSuccess\\tFinal Loss\\tFunc Evals\\tDistance\")\n",
    "print(\"-\" * 65)\n",
    "for i, method in enumerate(method_names):\n",
    "    data = results[method]\n",
    "    print(f\"{method:12s}\\t{data['success']}\\t{data['final_loss']:.2e}\\t{data['nfev']:4d}\\t\\t{distances[i]:.2e}\")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x1000 with 5 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Method Performance Summary:\n",
      "Method\t\tSuccess\tFinal Loss\tFunc Evals\tDistance\n",
      "-----------------------------------------------------------------\n",
      "L-BFGS-B    \tTrue\t1.78e-14\t  21\t\t2.55e-07\n",
      "SLSQP       \tTrue\t1.15e-07\t  42\t\t8.72e-04\n",
      "Powell      \tTrue\t1.60e-13\t 483\t\t5.09e-07\n"
     ]
    }
   ],
   "execution_count": 17
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Neural Network Parameter Optimization\n",
    "\n",
    "Let's demonstrate a practical application: optimizing parameters of a simple neural network."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:26.071174Z",
     "start_time": "2025-09-23T16:22:26.023443Z"
    }
   },
   "source": [
    "# Generate synthetic regression data\n",
    "np.random.seed(42)\n",
    "n_samples = 200\n",
    "n_features = 3\n",
    "\n",
    "# Create synthetic data with known pattern\n",
    "X = np.random.randn(n_samples, n_features)\n",
    "# True relationship: y = 2*x1 - 1.5*x2 + 0.8*x3 + noise\n",
    "true_weights = np.array([2.0, -1.5, 0.8])\n",
    "y = X @ true_weights + 0.1 * np.random.randn(n_samples)\n",
    "\n",
    "# Split into train/test\n",
    "split = int(0.8 * n_samples)\n",
    "X_train, X_test = jnp.array(X[:split]), jnp.array(X[split:])\n",
    "y_train, y_test = jnp.array(y[:split]), jnp.array(y[split:])\n",
    "\n",
    "print(f\"Training set: {X_train.shape[0]} samples\")\n",
    "print(f\"Test set: {X_test.shape[0]} samples\")\n",
    "print(f\"True weights: {true_weights}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training set: 160 samples\n",
      "Test set: 40 samples\n",
      "True weights: [ 2.  -1.5  0.8]\n"
     ]
    }
   ],
   "execution_count": 18
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:27.194582Z",
     "start_time": "2025-09-23T16:22:27.128485Z"
    }
   },
   "source": [
    "# Define a simple neural network loss function\n",
    "def neural_network_loss(W1, b1, W2, b2):\n",
    "    \"\"\"\n",
    "    Loss function for a simple 2-layer neural network.\n",
    "    \n",
    "    Args:\n",
    "        W1: First layer weights, shape (n_features, hidden_size)\n",
    "        b1: First layer bias, shape (hidden_size,)\n",
    "        W2: Second layer weights, shape (hidden_size, 1)\n",
    "        b2: Second layer bias, shape (1,)\n",
    "        \n",
    "    Returns:\n",
    "        Mean squared error on training set\n",
    "    \"\"\"\n",
    "    # Forward pass\n",
    "    h = jax.nn.relu(X_train @ W1 + b1)  # Hidden layer with ReLU\n",
    "    y_pred = h @ W2 + b2  # Output layer\n",
    "    \n",
    "    # Mean squared error\n",
    "    mse = jnp.mean((y_pred.flatten() - y_train)**2)\n",
    "    \n",
    "    # Add small L2 regularization\n",
    "    l2_reg = 0.01 * (jnp.sum(W1**2) + jnp.sum(W2**2))\n",
    "    \n",
    "    return mse + l2_reg\n",
    "\n",
    "# Define bounds for network parameters\n",
    "hidden_size = 5\n",
    "network_bounds = {\n",
    "    'W1': (jnp.full((n_features, hidden_size), -2.0), jnp.full((n_features, hidden_size), 2.0)),\n",
    "    'b1': (jnp.full(hidden_size, -1.0), jnp.full(hidden_size, 1.0)),\n",
    "    'W2': (jnp.full((hidden_size, 1), -2.0), jnp.full((hidden_size, 1), 2.0)),\n",
    "    'b2': (jnp.full(1, -1.0), jnp.full(1, 1.0))\n",
    "}\n",
    "\n",
    "print(f\"Neural network architecture: {n_features} -> {hidden_size} -> 1\")\n",
    "print(f\"Total parameters: {n_features * hidden_size + hidden_size + hidden_size * 1 + 1}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Neural network architecture: 3 -> 5 -> 1\n",
      "Total parameters: 26\n"
     ]
    }
   ],
   "execution_count": 19
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:29.087820Z",
     "start_time": "2025-09-23T16:22:27.897501Z"
    }
   },
   "source": [
    "# Create and run neural network optimizer\n",
    "nn_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=neural_network_loss,\n",
    "    bounds=network_bounds,\n",
    "    method='L-BFGS-B',\n",
    "    options={'maxiter': 1000}  # Allow more iterations for neural network\n",
    ")\n",
    "\n",
    "print(\"Optimizing neural network parameters...\")\n",
    "print(\"(This may take a moment)\\n\")\n",
    "\n",
    "nn_result = nn_optimizer.minimize(n_iter=3)\n",
    "\n",
    "print(f\"Optimization completed!\")\n",
    "print(f\"Success: {nn_result.success}\")\n",
    "print(f\"Function evaluations: {nn_result.nfev}\")\n",
    "print(f\"Gradient evaluations: {nn_result.njev}\")\n",
    "print(f\"Final training loss: {nn_result.fun:.6f}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizing neural network parameters...\n",
      "(This may take a moment)\n",
      "\n",
      "Optimization completed!\n",
      "Success: True\n",
      "Function evaluations: 196\n",
      "Gradient evaluations: 196\n",
      "Final training loss: 0.095723\n"
     ]
    }
   ],
   "execution_count": 20
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:32.460457Z",
     "start_time": "2025-09-23T16:22:32.159180Z"
    }
   },
   "source": [
    "# Evaluate the optimized network\n",
    "def evaluate_network(W1, b1, W2, b2, X, y):\n",
    "    \"\"\"Evaluate network performance on given data.\"\"\"\n",
    "    h = jax.nn.relu(X @ W1 + b1)\n",
    "    y_pred = h @ W2 + b2\n",
    "    mse = jnp.mean((y_pred.flatten() - y)**2)\n",
    "    return y_pred.flatten(), mse\n",
    "\n",
    "# Get optimized parameters\n",
    "W1_opt = nn_result.x['W1']\n",
    "b1_opt = nn_result.x['b1']\n",
    "W2_opt = nn_result.x['W2']\n",
    "b2_opt = nn_result.x['b2']\n",
    "\n",
    "# Evaluate on train and test sets\n",
    "y_train_pred, train_mse = evaluate_network(W1_opt, b1_opt, W2_opt, b2_opt, X_train, y_train)\n",
    "y_test_pred, test_mse = evaluate_network(W1_opt, b1_opt, W2_opt, b2_opt, X_test, y_test)\n",
    "\n",
    "print(f\"\\nNetwork Performance:\")\n",
    "print(f\"Training MSE: {train_mse:.6f}\")\n",
    "print(f\"Test MSE: {test_mse:.6f}\")\n",
    "\n",
    "# Compare with linear regression baseline\n",
    "linear_weights = jnp.linalg.lstsq(X_train, y_train, rcond=None)[0]\n",
    "y_test_linear = X_test @ linear_weights\n",
    "linear_mse = jnp.mean((y_test_linear - y_test)**2)\n",
    "\n",
    "print(f\"Linear regression MSE: {linear_mse:.6f}\")\n",
    "print(f\"\\nTrue weights: {true_weights}\")\n",
    "print(f\"Linear regression weights: {linear_weights}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Network Performance:\n",
      "Training MSE: 0.014361\n",
      "Test MSE: 0.021628\n",
      "Linear regression MSE: 0.008314\n",
      "\n",
      "True weights: [ 2.  -1.5  0.8]\n",
      "Linear regression weights: [ 1.9943104  -1.4900746   0.81011224]\n"
     ]
    }
   ],
   "execution_count": 21
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:35.517736Z",
     "start_time": "2025-09-23T16:22:34.670334Z"
    }
   },
   "source": [
    "# Visualize neural network results\n",
    "fig, axes = plt.subplots(2, 2, figsize=(14, 10))\n",
    "\n",
    "# Plot predictions vs true values for training set\n",
    "axes[0, 0].scatter(y_train, y_train_pred, alpha=0.6, color='blue')\n",
    "min_val, max_val = min(jnp.min(y_train), jnp.min(y_train_pred)), max(jnp.max(y_train), jnp.max(y_train_pred))\n",
    "axes[0, 0].plot([min_val, max_val], [min_val, max_val], 'r--', alpha=0.8)\n",
    "axes[0, 0].set_xlabel('True Values')\n",
    "axes[0, 0].set_ylabel('Predicted Values')\n",
    "axes[0, 0].set_title(f'Training Set (MSE: {train_mse:.4f})')\n",
    "axes[0, 0].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot predictions vs true values for test set\n",
    "axes[0, 1].scatter(y_test, y_test_pred, alpha=0.6, color='green')\n",
    "min_val, max_val = min(jnp.min(y_test), jnp.min(y_test_pred)), max(jnp.max(y_test), jnp.max(y_test_pred))\n",
    "axes[0, 1].plot([min_val, max_val], [min_val, max_val], 'r--', alpha=0.8)\n",
    "axes[0, 1].set_xlabel('True Values')\n",
    "axes[0, 1].set_ylabel('Predicted Values')\n",
    "axes[0, 1].set_title(f'Test Set (MSE: {test_mse:.4f})')\n",
    "axes[0, 1].grid(True, alpha=0.3)\n",
    "\n",
    "# Compare MSE values\n",
    "mse_values = [train_mse, test_mse, linear_mse]\n",
    "mse_labels = ['NN Train', 'NN Test', 'Linear Test']\n",
    "colors = ['blue', 'green', 'orange']\n",
    "\n",
    "bars = axes[1, 0].bar(mse_labels, mse_values, color=colors, alpha=0.7)\n",
    "axes[1, 0].set_ylabel('Mean Squared Error')\n",
    "axes[1, 0].set_title('Model Comparison')\n",
    "axes[1, 0].grid(True, alpha=0.3)\n",
    "\n",
    "# Add value labels on bars\n",
    "for bar, value in zip(bars, mse_values):\n",
    "    axes[1, 0].text(bar.get_x() + bar.get_width()/2, bar.get_height(), \n",
    "                   f'{value:.4f}', ha='center', va='bottom')\n",
    "\n",
    "# Plot weight comparison (first layer weights)\n",
    "im = axes[1, 1].imshow(W1_opt.T, cmap='RdBu_r', aspect='auto')\n",
    "axes[1, 1].set_xlabel('Input Feature')\n",
    "axes[1, 1].set_ylabel('Hidden Unit')\n",
    "axes[1, 1].set_title('First Layer Weights')\n",
    "plt.colorbar(im, ax=axes[1, 1])\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(f\"\\nNetwork architecture summary:\")\n",
    "print(f\"W1 shape: {W1_opt.shape}, range: [{jnp.min(W1_opt):.3f}, {jnp.max(W1_opt):.3f}]\")\n",
    "print(f\"b1 shape: {b1_opt.shape}, range: [{jnp.min(b1_opt):.3f}, {jnp.max(b1_opt):.3f}]\")\n",
    "print(f\"W2 shape: {W2_opt.shape}, range: [{jnp.min(W2_opt):.3f}, {jnp.max(W2_opt):.3f}]\")\n",
    "print(f\"b2 shape: {b2_opt.shape}, value: {b2_opt[0]:.3f}\")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x1000 with 5 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Network architecture summary:\n",
      "W1 shape: (3, 5), range: [-0.813, 0.779]\n",
      "b1 shape: (5,), range: [-0.456, 1.000]\n",
      "W2 shape: (5, 1), range: [-1.126, 1.165]\n",
      "b2 shape: (1,), value: 0.171\n"
     ]
    }
   ],
   "execution_count": 22
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Advanced Features: Constraints and Options\n",
    "\n",
    "The ScipyOptimizer supports advanced features like constraints and custom options."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:39.921603Z",
     "start_time": "2025-09-23T16:22:39.657989Z"
    }
   },
   "source": [
    "# Example with constraints: optimize a portfolio with constraints\n",
    "def portfolio_loss(weights):\n",
    "    \"\"\"\n",
    "    Portfolio optimization: minimize risk while maintaining expected return.\n",
    "    \n",
    "    Args:\n",
    "        weights: Portfolio weights, shape (n_assets,)\n",
    "        \n",
    "    Returns:\n",
    "        Portfolio variance (risk measure)\n",
    "    \"\"\"\n",
    "    # Synthetic covariance matrix (risk model)\n",
    "    cov_matrix = jnp.array([\n",
    "        [0.04, 0.01, 0.005],\n",
    "        [0.01, 0.09, 0.02],\n",
    "        [0.005, 0.02, 0.16]\n",
    "    ])\n",
    "    \n",
    "    # Portfolio variance\n",
    "    portfolio_var = weights.T @ cov_matrix @ weights\n",
    "    return portfolio_var\n",
    "\n",
    "# Define constraints\n",
    "def constraint_sum_to_one(weights):\n",
    "    \"\"\"Constraint: weights must sum to 1.\"\"\"\n",
    "    return jnp.sum(weights) - 1.0\n",
    "\n",
    "def constraint_min_return(weights):\n",
    "    \"\"\"Constraint: minimum expected return.\"\"\"\n",
    "    expected_returns = jnp.array([0.08, 0.12, 0.15])  # 8%, 12%, 15%\n",
    "    portfolio_return = weights.T @ expected_returns\n",
    "    return portfolio_return - 0.10  # At least 10% return\n",
    "\n",
    "# Convert constraints to scipy format\n",
    "constraints = [\n",
    "    {'type': 'eq', 'fun': lambda w: float(constraint_sum_to_one(jnp.array(w)))},\n",
    "    {'type': 'ineq', 'fun': lambda w: float(constraint_min_return(jnp.array(w)))}\n",
    "]\n",
    "\n",
    "# Bounds: each weight between 0 and 1\n",
    "n_assets = 3\n",
    "portfolio_bounds = [(jnp.zeros(n_assets), jnp.ones(n_assets))]\n",
    "\n",
    "# Create constrained optimizer\n",
    "portfolio_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=portfolio_loss,\n",
    "    bounds=portfolio_bounds,\n",
    "    method='SLSQP',  # Good for constrained optimization\n",
    "    constraints=constraints,\n",
    "    options={'ftol': 1e-9, 'disp': True}\n",
    ")\n",
    "\n",
    "print(\"Portfolio optimization with constraints:\")\n",
    "print(\"- Weights must sum to 1 (budget constraint)\")\n",
    "print(\"- Expected return >= 10%\")\n",
    "print(\"- Each weight between 0 and 1 (long-only)\")\n",
    "print()\n",
    "\n",
    "portfolio_result = portfolio_optimizer.minimize(n_iter=3)\n",
    "\n",
    "print(f\"\\nOptimization completed!\")\n",
    "print(f\"Success: {portfolio_result.success}\")\n",
    "print(f\"Message: {portfolio_result.message}\")\n",
    "\n",
    "optimal_weights = portfolio_result.x[0]\n",
    "print(f\"\\nOptimal portfolio weights:\")\n",
    "asset_names = ['Asset A', 'Asset B', 'Asset C']\n",
    "for i, (name, weight) in enumerate(zip(asset_names, optimal_weights)):\n",
    "    print(f\"  {name}: {weight:.4f} ({weight*100:.1f}%)\")\n",
    "\n",
    "# Verify constraints\n",
    "weight_sum = jnp.sum(optimal_weights)\n",
    "expected_returns = jnp.array([0.08, 0.12, 0.15])\n",
    "portfolio_return = optimal_weights.T @ expected_returns\n",
    "portfolio_risk = jnp.sqrt(portfolio_result.fun)\n",
    "\n",
    "print(f\"\\nPortfolio metrics:\")\n",
    "print(f\"  Weight sum: {weight_sum:.6f} (should be 1.0)\")\n",
    "print(f\"  Expected return: {portfolio_return:.4f} ({portfolio_return*100:.1f}%)\")\n",
    "print(f\"  Risk (volatility): {portfolio_risk:.4f} ({portfolio_risk*100:.1f}%)\")\n",
    "print(f\"  Variance: {portfolio_result.fun:.6f}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Portfolio optimization with constraints:\n",
      "- Weights must sum to 1 (budget constraint)\n",
      "- Expected return >= 10%\n",
      "- Each weight between 0 and 1 (long-only)\n",
      "\n",
      "Singular matrix C in LSQ subproblem    (Exit mode 6)\n",
      "            Current function value: 0.1654115915298462\n",
      "            Iterations: 1\n",
      "            Function evaluations: 1\n",
      "            Gradient evaluations: 1\n",
      "Singular matrix C in LSQ subproblem    (Exit mode 6)\n",
      "            Current function value: 0.07909038662910461\n",
      "            Iterations: 1\n",
      "            Function evaluations: 1\n",
      "            Gradient evaluations: 1\n",
      "Singular matrix C in LSQ subproblem    (Exit mode 6)\n",
      "            Current function value: 0.10067348182201385\n",
      "            Iterations: 1\n",
      "            Function evaluations: 1\n",
      "            Gradient evaluations: 1\n",
      "\n",
      "Optimization completed!\n",
      "Success: False\n",
      "Message: Singular matrix C in LSQ subproblem\n",
      "\n",
      "Optimal portfolio weights:\n",
      "  Asset A: 0.1539 (15.4%)\n",
      "  Asset B: 0.8158 (81.6%)\n",
      "  Asset C: 0.2244 (22.4%)\n",
      "\n",
      "Portfolio metrics:\n",
      "  Weight sum: 1.194170 (should be 1.0)\n",
      "  Expected return: 0.1439 (14.4%)\n",
      "  Risk (volatility): 0.2812 (28.1%)\n",
      "  Variance: 0.079090\n"
     ]
    }
   ],
   "execution_count": 23
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:41.140919Z",
     "start_time": "2025-09-23T16:22:40.524845Z"
    }
   },
   "source": [
    "# Visualize portfolio optimization results\n",
    "fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n",
    "\n",
    "# Plot portfolio weights\n",
    "axes[0].pie(optimal_weights, labels=asset_names, autopct='%1.1f%%', startangle=90)\n",
    "axes[0].set_title('Optimal Portfolio Allocation')\n",
    "\n",
    "# Plot risk-return characteristics\n",
    "asset_returns = jnp.array([0.08, 0.12, 0.15])\n",
    "asset_risks = jnp.sqrt(jnp.diag(jnp.array([\n",
    "    [0.04, 0.01, 0.005],\n",
    "    [0.01, 0.09, 0.02],\n",
    "    [0.005, 0.02, 0.16]\n",
    "])))\n",
    "\n",
    "# Plot individual assets\n",
    "axes[1].scatter(asset_risks, asset_returns, c=['red', 'blue', 'green'], \n",
    "               s=100, alpha=0.7, label='Individual Assets')\n",
    "for i, name in enumerate(asset_names):\n",
    "    axes[1].annotate(name, (asset_risks[i], asset_returns[i]), \n",
    "                    xytext=(5, 5), textcoords='offset points')\n",
    "\n",
    "# Plot optimal portfolio\n",
    "axes[1].scatter(portfolio_risk, portfolio_return, c='black', \n",
    "               s=150, marker='*', label='Optimal Portfolio')\n",
    "axes[1].annotate('Optimal', (portfolio_risk, portfolio_return), \n",
    "                xytext=(5, 5), textcoords='offset points')\n",
    "\n",
    "axes[1].set_xlabel('Risk (Volatility)')\n",
    "axes[1].set_ylabel('Expected Return')\n",
    "axes[1].set_title('Risk-Return Space')\n",
    "axes[1].legend()\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot constraint satisfaction\n",
    "constraint_names = ['Weight Sum', 'Min Return']\n",
    "constraint_values = [weight_sum, portfolio_return]\n",
    "constraint_targets = [1.0, 0.10]\n",
    "constraint_errors = [abs(cv - ct) for cv, ct in zip(constraint_values, constraint_targets)]\n",
    "\n",
    "x_pos = np.arange(len(constraint_names))\n",
    "axes[2].bar(x_pos, constraint_errors, alpha=0.7, color=['orange', 'purple'])\n",
    "axes[2].set_xlabel('Constraint')\n",
    "axes[2].set_ylabel('Absolute Error')\n",
    "axes[2].set_title('Constraint Violations')\n",
    "axes[2].set_xticks(x_pos)\n",
    "axes[2].set_xticklabels(constraint_names)\n",
    "axes[2].set_yscale('log')\n",
    "axes[2].grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 24
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison with Derivative-Free Methods\n",
    "\n",
    "Let's compare the ScipyOptimizer with the derivative-free NevergradOptimizer on the same problem."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:43.177936Z",
     "start_time": "2025-09-23T16:22:42.965852Z"
    }
   },
   "source": [
    "# Define a test function for comparison\n",
    "def comparison_function(x, y):\n",
    "    \"\"\"A smooth function suitable for gradient-based optimization.\"\"\"\n",
    "    return (x - 1.5)**2 + 2*(y + 0.5)**2 + 0.1*jnp.sin(10*x)*jnp.cos(10*y)\n",
    "\n",
    "bounds = [(-3.0, 3.0), (-2.0, 2.0)]\n",
    "\n",
    "# Test ScipyOptimizer\n",
    "print(\"Testing ScipyOptimizer (gradient-based)...\")\n",
    "scipy_opt = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=comparison_function,\n",
    "    bounds=bounds,\n",
    "    method='L-BFGS-B'\n",
    ")\n",
    "\n",
    "import time\n",
    "start_time = time.time()\n",
    "scipy_result = scipy_opt.minimize(n_iter=3)\n",
    "scipy_time = time.time() - start_time\n",
    "\n",
    "print(f\"  Success: {scipy_result.success}\")\n",
    "print(f\"  Final loss: {scipy_result.fun:.8f}\")\n",
    "print(f\"  Parameters: ({scipy_result.x[0]:.6f}, {scipy_result.x[1]:.6f})\")\n",
    "print(f\"  Function evaluations: {scipy_result.nfev}\")\n",
    "print(f\"  Time: {scipy_time:.4f} seconds\\n\")\n",
    "\n",
    "# Test NevergradOptimizer (if available)\n",
    "try:\n",
    "    print(\"Testing NevergradOptimizer (derivative-free)...\")\n",
    "    \n",
    "    # Define batched version for Nevergrad\n",
    "    def batched_comparison_function(x, y):\n",
    "        return (x - 1.5)**2 + 2*(y + 0.5)**2 + 0.1*jnp.sin(10*x)*jnp.cos(10*y)\n",
    "    \n",
    "    nevergrad_opt = bts.optim.NevergradOptimizer(\n",
    "        batched_loss_fun=batched_comparison_function,\n",
    "        bounds=bounds,\n",
    "        n_sample=10,\n",
    "        method='L-BFGS-B'  # Actually uses scipy internally for this method\n",
    "    )\n",
    "    \n",
    "    start_time = time.time()\n",
    "    nevergrad_result = nevergrad_opt.minimize(n_iter=20, verbose=False)\n",
    "    nevergrad_time = time.time() - start_time\n",
    "    \n",
    "    print(f\"  Final loss: {comparison_function(nevergrad_result[0], nevergrad_result[1]):.8f}\")\n",
    "    print(f\"  Parameters: ({nevergrad_result[0]:.6f}, {nevergrad_result[1]:.6f})\")\n",
    "    print(f\"  Function evaluations: {len(nevergrad_opt.errors)}\")\n",
    "    print(f\"  Time: {nevergrad_time:.4f} seconds\\n\")\n",
    "    \n",
    "    nevergrad_available = True\n",
    "    \n",
    "except Exception as e:\n",
    "    print(f\"  NevergradOptimizer not available: {e}\\n\")\n",
    "    nevergrad_available = False\n",
    "\n",
    "print(f\"True optimum: (1.5, -0.5) with loss ≈ 0.0\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing ScipyOptimizer (gradient-based)...\n",
      "  Success: True\n",
      "  Final loss: -0.04498873\n",
      "  Parameters: (1.430242, -0.369797)\n",
      "  Function evaluations: 26\n",
      "  Time: 0.2017 seconds\n",
      "\n",
      "Testing NevergradOptimizer (derivative-free)...\n",
      "  NevergradOptimizer not available: 'L-BFGS-B'\n",
      "\n",
      "True optimum: (1.5, -0.5) with loss ≈ 0.0\n"
     ]
    }
   ],
   "execution_count": 25
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:44.297156Z",
     "start_time": "2025-09-23T16:22:43.962528Z"
    }
   },
   "source": [
    "# Visualize the comparison\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "# Plot the function landscape\n",
    "x_range = np.linspace(-3, 3, 200)\n",
    "y_range = np.linspace(-2, 2, 200)\n",
    "X, Y = np.meshgrid(x_range, y_range)\n",
    "Z = (X - 1.5)**2 + 2*(Y + 0.5)**2 + 0.1*np.sin(10*X)*np.cos(10*Y)\n",
    "\n",
    "contour = axes[0].contourf(X, Y, Z, levels=30, cmap='viridis')\n",
    "axes[0].contour(X, Y, Z, levels=20, colors='black', alpha=0.3, linewidths=0.5)\n",
    "plt.colorbar(contour, ax=axes[0])\n",
    "\n",
    "# Mark results\n",
    "axes[0].plot(1.5, -0.5, 'r*', markersize=15, label='True optimum')\n",
    "axes[0].plot(scipy_result.x[0], scipy_result.x[1], 'bo', markersize=10, label='ScipyOptimizer')\n",
    "\n",
    "if nevergrad_available:\n",
    "    axes[0].plot(nevergrad_result[0], nevergrad_result[1], 'gs', markersize=10, label='NevergradOptimizer')\n",
    "\n",
    "axes[0].set_xlabel('x')\n",
    "axes[0].set_ylabel('y')\n",
    "axes[0].set_title('Optimization Comparison')\n",
    "axes[0].legend()\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# Compare performance metrics\n",
    "if nevergrad_available:\n",
    "    methods = ['ScipyOptimizer', 'NevergradOptimizer']\n",
    "    final_losses = [scipy_result.fun, comparison_function(nevergrad_result[0], nevergrad_result[1])]\n",
    "    func_evals = [scipy_result.nfev, len(nevergrad_opt.errors)]\n",
    "    times = [scipy_time, nevergrad_time]\n",
    "else:\n",
    "    methods = ['ScipyOptimizer']\n",
    "    final_losses = [scipy_result.fun]\n",
    "    func_evals = [scipy_result.nfev]\n",
    "    times = [scipy_time]\n",
    "\n",
    "x_pos = np.arange(len(methods))\n",
    "width = 0.25\n",
    "\n",
    "# Subplot for metrics\n",
    "ax2 = axes[1]\n",
    "ax2_twin = ax2.twinx()\n",
    "\n",
    "bars1 = ax2.bar(x_pos - width, final_losses, width, label='Final Loss', alpha=0.7, color='blue')\n",
    "bars2 = ax2.bar(x_pos, func_evals, width, label='Function Evals', alpha=0.7, color='green')\n",
    "bars3 = ax2_twin.bar(x_pos + width, times, width, label='Time (s)', alpha=0.7, color='red')\n",
    "\n",
    "ax2.set_xlabel('Method')\n",
    "ax2.set_ylabel('Loss / Function Evaluations')\n",
    "ax2_twin.set_ylabel('Time (seconds)')\n",
    "ax2.set_title('Performance Comparison')\n",
    "ax2.set_xticks(x_pos)\n",
    "ax2.set_xticklabels(methods)\n",
    "ax2.set_yscale('log')\n",
    "\n",
    "# Combine legends\n",
    "lines1, labels1 = ax2.get_legend_handles_labels()\n",
    "lines2, labels2 = ax2_twin.get_legend_handles_labels()\n",
    "ax2.legend(lines1 + lines2, labels1 + labels2, loc='upper right')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\nComparison Summary:\")\n",
    "print(\"==================\")\n",
    "print(\"ScipyOptimizer advantages:\")\n",
    "print(\"- Faster convergence for smooth functions\")\n",
    "print(\"- Higher precision solutions\")\n",
    "print(\"- Fewer function evaluations\")\n",
    "print(\"- Automatic gradient computation\")\n",
    "print(\"\\nNevergradOptimizer advantages:\")\n",
    "print(\"- Works with non-differentiable functions\")\n",
    "print(\"- Better for noisy objectives\")\n",
    "print(\"- More robust to local minima\")\n",
    "print(\"- Batched evaluation support\")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x500 with 4 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Comparison Summary:\n",
      "==================\n",
      "ScipyOptimizer advantages:\n",
      "- Faster convergence for smooth functions\n",
      "- Higher precision solutions\n",
      "- Fewer function evaluations\n",
      "- Automatic gradient computation\n",
      "\n",
      "NevergradOptimizer advantages:\n",
      "- Works with non-differentiable functions\n",
      "- Better for noisy objectives\n",
      "- More robust to local minima\n",
      "- Batched evaluation support\n"
     ]
    }
   ],
   "execution_count": 26
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Best Practices and Tips\n",
    "\n",
    "Here are some best practices for using the ScipyOptimizer effectively:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Choosing the Right Method\n",
    "\n",
    "**For bounded problems:**\n",
    "- `L-BFGS-B`: Excellent for smooth, unconstrained or box-constrained problems\n",
    "- `TNC`: Truncated Newton with bounds, good alternative to L-BFGS-B\n",
    "\n",
    "**For constrained problems:**\n",
    "- `SLSQP`: Sequential Least Squares Programming, handles equality and inequality constraints\n",
    "- `trust-constr`: Modern trust-region method, very robust for constrained optimization\n",
    "\n",
    "**For unconstrained problems:**\n",
    "- `BFGS`: Standard quasi-Newton method\n",
    "- `Newton-CG`: Uses Hessian information (computed by JAX)\n",
    "- `CG`: Conjugate gradient method\n",
    "\n",
    "**Derivative-free (when gradients unreliable):**\n",
    "- `Powell`: Direction set method\n",
    "- `Nelder-Mead`: Simplex method"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:46.980415Z",
     "start_time": "2025-09-23T16:22:46.974559Z"
    }
   },
   "source": [
    "# Best Practice 1: Method selection guidelines\n",
    "print(\"Method Selection Guidelines:\")\n",
    "print(\"==========================\\n\")\n",
    "\n",
    "guidelines = {\n",
    "    'L-BFGS-B': {\n",
    "        'description': 'Limited-memory BFGS with bounds',\n",
    "        'best_for': 'Smooth functions with box constraints',\n",
    "        'pros': 'Fast, memory-efficient, handles bounds well',\n",
    "        'cons': 'Only handles box constraints'\n",
    "    },\n",
    "    'SLSQP': {\n",
    "        'description': 'Sequential Least Squares Programming',\n",
    "        'best_for': 'Problems with equality/inequality constraints',\n",
    "        'pros': 'Handles general constraints, robust',\n",
    "        'cons': 'Can be slower than L-BFGS-B for simple problems'\n",
    "    },\n",
    "    'TNC': {\n",
    "        'description': 'Truncated Newton with bounds',\n",
    "        'best_for': 'Alternative to L-BFGS-B for bounded problems',\n",
    "        'pros': 'Good convergence properties, handles bounds',\n",
    "        'cons': 'May be slower than L-BFGS-B'\n",
    "    },\n",
    "    'Powell': {\n",
    "        'description': 'Direction set method (derivative-free)',\n",
    "        'best_for': 'When gradients are unreliable or discontinuous',\n",
    "        'pros': 'No gradient computation, robust',\n",
    "        'cons': 'Slower convergence, more function evaluations'\n",
    "    }\n",
    "}\n",
    "\n",
    "for method, info in guidelines.items():\n",
    "    print(f\"{method}:\")\n",
    "    print(f\"  Description: {info['description']}\")\n",
    "    print(f\"  Best for: {info['best_for']}\")\n",
    "    print(f\"  Pros: {info['pros']}\")\n",
    "    print(f\"  Cons: {info['cons']}\\n\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Method Selection Guidelines:\n",
      "==========================\n",
      "\n",
      "L-BFGS-B:\n",
      "  Description: Limited-memory BFGS with bounds\n",
      "  Best for: Smooth functions with box constraints\n",
      "  Pros: Fast, memory-efficient, handles bounds well\n",
      "  Cons: Only handles box constraints\n",
      "\n",
      "SLSQP:\n",
      "  Description: Sequential Least Squares Programming\n",
      "  Best for: Problems with equality/inequality constraints\n",
      "  Pros: Handles general constraints, robust\n",
      "  Cons: Can be slower than L-BFGS-B for simple problems\n",
      "\n",
      "TNC:\n",
      "  Description: Truncated Newton with bounds\n",
      "  Best for: Alternative to L-BFGS-B for bounded problems\n",
      "  Pros: Good convergence properties, handles bounds\n",
      "  Cons: May be slower than L-BFGS-B\n",
      "\n",
      "Powell:\n",
      "  Description: Direction set method (derivative-free)\n",
      "  Best for: When gradients are unreliable or discontinuous\n",
      "  Pros: No gradient computation, robust\n",
      "  Cons: Slower convergence, more function evaluations\n",
      "\n"
     ]
    }
   ],
   "execution_count": 27
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:47.822302Z",
     "start_time": "2025-09-23T16:22:47.736691Z"
    }
   },
   "source": [
    "# Best Practice 2: Proper scaling and conditioning\n",
    "print(\"Best Practice 2: Function scaling and conditioning\")\n",
    "print(\"===============================================\\n\")\n",
    "\n",
    "# Example of badly scaled vs well-scaled problems\n",
    "def badly_scaled_function(x, y):\n",
    "    \"\"\"Function with very different scales in x and y directions.\"\"\"\n",
    "    return 1e6 * (x - 1.0)**2 + 1e-3 * (y - 2.0)**2\n",
    "\n",
    "def well_scaled_function(x, y):\n",
    "    \"\"\"Same function but with similar scales.\"\"\"\n",
    "    return (x - 1.0)**2 + (y - 2.0)**2\n",
    "\n",
    "bounds = [(-5.0, 5.0), (-5.0, 5.0)]\n",
    "\n",
    "print(\"Testing badly scaled function...\")\n",
    "bad_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=badly_scaled_function, bounds=bounds, method='L-BFGS-B'\n",
    ")\n",
    "bad_result = bad_optimizer.minimize(n_iter=1)\n",
    "print(f\"  Success: {bad_result.success}\")\n",
    "print(f\"  Function evaluations: {bad_result.nfev}\")\n",
    "print(f\"  Final loss: {bad_result.fun:.2e}\")\n",
    "\n",
    "print(\"\\nTesting well scaled function...\")\n",
    "good_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=well_scaled_function, bounds=bounds, method='L-BFGS-B'\n",
    ")\n",
    "good_result = good_optimizer.minimize(n_iter=1)\n",
    "print(f\"  Success: {good_result.success}\")\n",
    "print(f\"  Function evaluations: {good_result.nfev}\")\n",
    "print(f\"  Final loss: {good_result.fun:.2e}\")\n",
    "\n",
    "print(\"\\nScaling Tips:\")\n",
    "print(\"- Normalize parameters to similar ranges (e.g., [-1, 1] or [0, 1])\")\n",
    "print(\"- Scale the objective function to have reasonable magnitude (≈1)\")\n",
    "print(\"- Use proper units with BrainUnit to maintain physical meaning\")\n",
    "print(\"- Consider the condition number of the Hessian matrix\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Practice 2: Function scaling and conditioning\n",
      "===============================================\n",
      "\n",
      "Testing badly scaled function...\n",
      "  Success: True\n",
      "  Function evaluations: 15\n",
      "  Final loss: 2.00e-04\n",
      "\n",
      "Testing well scaled function...\n",
      "  Success: True\n",
      "  Function evaluations: 3\n",
      "  Final loss: 3.55e-15\n",
      "\n",
      "Scaling Tips:\n",
      "- Normalize parameters to similar ranges (e.g., [-1, 1] or [0, 1])\n",
      "- Scale the objective function to have reasonable magnitude (≈1)\n",
      "- Use proper units with BrainUnit to maintain physical meaning\n",
      "- Consider the condition number of the Hessian matrix\n"
     ]
    }
   ],
   "execution_count": 28
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:48.938352Z",
     "start_time": "2025-09-23T16:22:48.444205Z"
    }
   },
   "source": [
    "# Best Practice 3: Handling multiple local minima\n",
    "print(\"\\nBest Practice 3: Multiple starting points for global optimization\")\n",
    "print(\"=============================================================\\n\")\n",
    "\n",
    "def multimodal_function(x, y):\n",
    "    \"\"\"Function with multiple local minima.\"\"\"\n",
    "    return (x**2 + y**2) * (1 + 0.3 * jnp.cos(5*x) * jnp.cos(5*y))\n",
    "\n",
    "bounds = [(-3.0, 3.0), (-3.0, 3.0)]\n",
    "\n",
    "# Single optimization run\n",
    "single_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=multimodal_function, bounds=bounds, method='L-BFGS-B'\n",
    ")\n",
    "single_result = single_optimizer.minimize(n_iter=1)\n",
    "\n",
    "# Multiple optimization runs\n",
    "multi_optimizer = bts.optim.ScipyOptimizer(\n",
    "    loss_fun=multimodal_function, bounds=bounds, method='L-BFGS-B'\n",
    ")\n",
    "multi_result = multi_optimizer.minimize(n_iter=10)  # Try 10 different starting points\n",
    "\n",
    "print(f\"Single run result:\")\n",
    "print(f\"  Final loss: {single_result.fun:.6f}\")\n",
    "print(f\"  Parameters: ({single_result.x[0]:.4f}, {single_result.x[1]:.4f})\")\n",
    "\n",
    "print(f\"\\nMultiple runs result:\")\n",
    "print(f\"  Final loss: {multi_result.fun:.6f}\")\n",
    "print(f\"  Parameters: ({multi_result.x[0]:.4f}, {multi_result.x[1]:.4f})\")\n",
    "\n",
    "print(f\"\\nImprovement: {(single_result.fun - multi_result.fun) / single_result.fun * 100:.1f}%\")\n",
    "\n",
    "print(\"\\nMultiple Starting Point Tips:\")\n",
    "print(\"- Always use n_iter > 1 for problems with multiple local minima\")\n",
    "print(\"- ScipyOptimizer automatically samples different starting points\")\n",
    "print(\"- For gradient-based methods, combine with derivative-free global search\")\n",
    "print(\"- Consider using NevergradOptimizer for highly multimodal problems\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Best Practice 3: Multiple starting points for global optimization\n",
      "=============================================================\n",
      "\n",
      "Single run result:\n",
      "  Final loss: 0.000000\n",
      "  Parameters: (-0.0000, 0.0000)\n",
      "\n",
      "Multiple runs result:\n",
      "  Final loss: 0.000000\n",
      "  Parameters: (-0.0000, -0.0000)\n",
      "\n",
      "Improvement: 99.9%\n",
      "\n",
      "Multiple Starting Point Tips:\n",
      "- Always use n_iter > 1 for problems with multiple local minima\n",
      "- ScipyOptimizer automatically samples different starting points\n",
      "- For gradient-based methods, combine with derivative-free global search\n",
      "- Consider using NevergradOptimizer for highly multimodal problems\n"
     ]
    }
   ],
   "execution_count": 29
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-23T16:22:49.811034Z",
     "start_time": "2025-09-23T16:22:49.556990Z"
    }
   },
   "source": [
    "# Best Practice 4: Convergence monitoring and debugging\n",
    "print(\"\\nBest Practice 4: Monitoring and debugging optimization\")\n",
    "print(\"===================================================\\n\")\n",
    "\n",
    "def monitored_optimization_example():\n",
    "    \"\"\"Example showing how to monitor optimization progress.\"\"\"\n",
    "    \n",
    "    # Function to optimize\n",
    "    def objective(x, y):\n",
    "        return (x - 2.0)**2 + (y + 1.0)**2\n",
    "    \n",
    "    # Storage for monitoring\n",
    "    iteration_data = []\n",
    "    \n",
    "    def callback(x_current):\n",
    "        \"\"\"Callback function to monitor progress.\"\"\"\n",
    "        loss_val = objective(x_current[0], x_current[1])\n",
    "        iteration_data.append({\n",
    "            'x': x_current[0],\n",
    "            'y': x_current[1], \n",
    "            'loss': loss_val\n",
    "        })\n",
    "        # Print every few iterations\n",
    "        if len(iteration_data) % 5 == 0:\n",
    "            print(f\"  Iteration {len(iteration_data)}: loss = {loss_val:.6f}, x = ({x_current[0]:.4f}, {x_current[1]:.4f})\")\n",
    "    \n",
    "    # Create optimizer with callback\n",
    "    optimizer = bts.optim.ScipyOptimizer(\n",
    "        loss_fun=objective,\n",
    "        bounds=[(-5.0, 5.0), (-3.0, 3.0)],\n",
    "        method='L-BFGS-B',\n",
    "        callback=callback,\n",
    "        options={'disp': True}  # Enable SciPy's own display\n",
    "    )\n",
    "    \n",
    "    print(\"Running monitored optimization...\")\n",
    "    result = optimizer.minimize(n_iter=1)\n",
    "    \n",
    "    print(f\"\\nOptimization completed!\")\n",
    "    print(f\"Total callback calls: {len(iteration_data)}\")\n",
    "    print(f\"Final result: success = {result.success}, loss = {result.fun:.8f}\")\n",
    "    \n",
    "    # Plot convergence if we have data\n",
    "    if iteration_data:\n",
    "        losses = [data['loss'] for data in iteration_data]\n",
    "        plt.figure(figsize=(10, 4))\n",
    "        \n",
    "        plt.subplot(1, 2, 1)\n",
    "        plt.plot(losses, 'b-', linewidth=2)\n",
    "        plt.xlabel('Iteration')\n",
    "        plt.ylabel('Loss')\n",
    "        plt.title('Convergence Curve')\n",
    "        plt.yscale('log')\n",
    "        plt.grid(True, alpha=0.3)\n",
    "        \n",
    "        plt.subplot(1, 2, 2)\n",
    "        x_vals = [data['x'] for data in iteration_data]\n",
    "        y_vals = [data['y'] for data in iteration_data]\n",
    "        plt.plot(x_vals, y_vals, 'ro-', alpha=0.7, markersize=4)\n",
    "        plt.plot(2.0, -1.0, 'g*', markersize=15, label='True optimum')\n",
    "        plt.xlabel('x')\n",
    "        plt.ylabel('y')\n",
    "        plt.title('Optimization Path')\n",
    "        plt.legend()\n",
    "        plt.grid(True, alpha=0.3)\n",
    "        \n",
    "        plt.tight_layout()\n",
    "        plt.show()\n",
    "\n",
    "monitored_optimization_example()\n",
    "\n",
    "print(\"\\nMonitoring Tips:\")\n",
    "print(\"- Use callback functions to track optimization progress\")\n",
    "print(\"- Set options={'disp': True} to see SciPy's internal messages\")\n",
    "print(\"- Check result.success and result.message for convergence info\")\n",
    "print(\"- Monitor both function values and parameter changes\")\n",
    "print(\"- Use visualization to understand optimization behavior\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Best Practice 4: Monitoring and debugging optimization\n",
      "===================================================\n",
      "\n",
      "Running monitored optimization...\n",
      "\n",
      "Optimization completed!\n",
      "Total callback calls: 2\n",
      "Final result: success = True, loss = 0.00000000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Monitoring Tips:\n",
      "- Use callback functions to track optimization progress\n",
      "- Set options={'disp': True} to see SciPy's internal messages\n",
      "- Check result.success and result.message for convergence info\n",
      "- Monitor both function values and parameter changes\n",
      "- Use visualization to understand optimization behavior\n"
     ]
    }
   ],
   "execution_count": 30
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "In this tutorial, we've covered the key aspects of using BrainTools' `ScipyOptimizer`:\n",
    "\n",
    "1. Key Features:\n",
    "- **Automatic differentiation**: JAX computes gradients automatically\n",
    "- **Flexible parameter structures**: Support for scalars, arrays, and named parameters\n",
    "- **Unit integration**: Seamless work with BrainUnit quantities\n",
    "- **Multiple algorithms**: Access to SciPy's extensive optimization methods\n",
    "- **Constraints**: Support for equality and inequality constraints\n",
    "- **Advanced options**: Custom tolerances, callbacks, and solver-specific options\n",
    "\n",
    "2.  Best Practices:\n",
    "- **Choose the right method** - Match the algorithm to your problem characteristics\n",
    "- **Scale properly** - Normalize parameters and objective function\n",
    "- **Use multiple starting points** - Set `n_iter > 1` for global optimization\n",
    "- **Monitor convergence** - Use callbacks and check optimization results\n",
    "\n",
    "3. When to Use ScipyOptimizer:\n",
    "- **Smooth, differentiable objectives** where gradients are reliable\n",
    "- **High-precision optimization** where exact solutions are important\n",
    "- **Constrained optimization** problems with equality/inequality constraints\n",
    "- **Neural network parameter optimization** and model fitting\n",
    "- **Physics-based models** with analytical structure\n",
    "\n",
    "4. When to Consider Alternatives:\n",
    "- **Noisy objectives** → Use NevergradOptimizer\n",
    "- **Discontinuous functions** → Use derivative-free methods\n",
    "- **Very high-dimensional problems** → Consider specialized methods\n",
    "- **Multiple local minima** → Combine with global optimization\n",
    "\n",
    "The ScipyOptimizer provides a powerful and mature interface for gradient-based optimization in the BrainTools ecosystem, making it ideal for scientific computing and machine learning applications where precision and efficiency are paramount."
   ]
  }
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