{
    "cells": [
        {
            "cell_type": "markdown",
            "id": "7fb27b941602401d91542211134fc71a",
            "metadata": {},
            "source": [
                "# Glass Expert Optimization Example\n",
                "\n",
                "This notebook demonstrates how to use the `GlassExpert` optimizer in Optiland to optimize an optical system with both continuous (radii, thicknesses) and categorical (glasses) variables.\n",
                "\n",
                "A description of `GlassExpert`'s architecture can be found in the documentation (Developer's Guide: [Categorical Optimization with Glass Expert](https://optiland.readthedocs.io/en/latest/developers_guide/optimization_framework.html#categorical-optimization-with-glass-expert))"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "id": "acae54e37e7d407bbb7b55eff062a284",
            "metadata": {},
            "outputs": [],
            "source": [
                "import optiland.backend as be\n",
                "from optiland import optic, optimization\n",
                "from optiland.materials import glasses_selection"
            ]
        },
        {
            "cell_type": "markdown",
            "id": "9a63283cbaf04dbcab1f6479b197f3a8",
            "metadata": {},
            "source": [
                "## 1. Define the Optical System\n",
                "\n",
                "We'll use a simple Cooke Triplet as the starting point for our optimization."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 2,
            "id": "8dd0d8092fe74a7c96281538738b07e2",
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤═════════════════╤═══════════╤══════════╤═════════════╤════════════╤═════════╤═════════════════╕\n",
                        "│    │ Type            │ Comment   │   Radius │   Thickness │ Material   │   Conic │   Semi-aperture │\n",
                        "╞════╪═════════════════╪═══════════╪══════════╪═════════════╪════════════╪═════════╪═════════════════╡\n",
                        "│  0 │ Planar          │           │      inf │       inf   │ Air        │       0 │         7.04289 │\n",
                        "│  1 │ Standard        │           │       25 │         2.5 │ N-BK7      │       0 │         7.04289 │\n",
                        "│  2 │ Standard        │           │     -150 │         7.5 │ Air        │       0 │         6.5123  │\n",
                        "│  3 │ Stop - Standard │           │      -25 │         1.5 │ N-F2       │       0 │         3.92965 │\n",
                        "│  4 │ Standard        │           │       25 │         5   │ Air        │       0 │         4.11651 │\n",
                        "│  5 │ Standard        │           │      150 │         2.5 │ N-BK7      │       0 │         5.63609 │\n",
                        "│  6 │ Standard        │           │      -25 │        40   │ Air        │       0 │         6.105   │\n",
                        "│  7 │ Planar          │           │      inf │       nan   │ Air        │       0 │        12.4368  │\n",
                        "╘════╧═════════════════╧═══════════╧══════════╧═════════════╧════════════╧═════════╧═════════════════╛\n"
                    ]
                },
                {
                    "data": {
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",
                        "text/plain": [
                            "<Figure size 1000x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "class CookeTripletStartPoint(optic.Optic):\n",
                "    def __init__(self):\n",
                "        super().__init__()\n",
                "        self.surfaces.add(index=0, radius=be.inf, thickness=be.inf)  # Object surface\n",
                "        self.surfaces.add(index=1, radius=25.0, thickness=2.5, material=\"N-BK7\")\n",
                "        self.surfaces.add(index=2, radius=-150.0, thickness=7.5)\n",
                "        self.surfaces.add(\n",
                "            index=3, radius=-25.0, thickness=1.5, material=\"N-F2\", is_stop=True\n",
                "        )  # Stop surface\n",
                "        self.surfaces.add(index=4, radius=25.0, thickness=5.0)\n",
                "        self.surfaces.add(index=5, radius=150.0, thickness=2.5, material=\"N-BK7\")\n",
                "        self.surfaces.add(index=6, radius=-25.0, thickness=40.0)\n",
                "        self.surfaces.add(index=7)  # Image surface\n",
                "\n",
                "        self.set_aperture(aperture_type=\"EPD\", value=10)\n",
                "        self.fields.set_type(field_type=\"angle\")\n",
                "        self.fields.add(y=0)\n",
                "        self.fields.add(y=5)\n",
                "        self.fields.add(y=10)\n",
                "\n",
                "        self.wavelengths.add(value=0.4861)  # F\n",
                "        self.wavelengths.add(value=0.5876, is_primary=True)  # d\n",
                "        self.wavelengths.add(value=0.6563)  # C\n",
                "\n",
                "\n",
                "lens_system = CookeTripletStartPoint()\n",
                "\n",
                "# Display initial lens\n",
                "lens_system.draw(title=\"Initial Cooke Triplet\")\n",
                "lens_system.info()"
            ]
        },
        {
            "cell_type": "markdown",
            "id": "72eea5119410473aa328ad9291626812",
            "metadata": {},
            "source": [
                "## 2. Define the Optimization Problem\n",
                "\n",
                "We'll set up operands to minimize RMS spot size and maintain a target focal length. Variables will include radii, thicknesses, and the materials of the lenses."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "id": "8edb47106e1a46a883d545849b8ab81b",
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "╒════╤════════════════════════╤═══════════════════╕\n",
                        "│    │   Merit Function Value │   Improvement (%) │\n",
                        "╞════╪════════════════════════╪═══════════════════╡\n",
                        "│  0 │                14065.2 │                 0 │\n",
                        "╘════╧════════════════════════╧═══════════════════╛\n",
                        "╒════╤════════════════╤══════════╤══════════════╤══════════════╤══════════╤═════════╤═════════╤════════════════╕\n",
                        "│    │ Operand Type   │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Value │   Delta │   Contrib. [%] │\n",
                        "╞════╪════════════════╪══════════╪══════════════╪══════════════╪══════════╪═════════╪═════════╪════════════════╡\n",
                        "│  0 │ f2             │       50 │              │              │        1 │ 161.994 │ 111.994 │          89.18 │\n",
                        "│  1 │ rms spot size  │        0 │              │              │       10 │   2.249 │   2.249 │           3.59 │\n",
                        "│  2 │ rms spot size  │        0 │              │              │       10 │   2.251 │   2.251 │           3.6  │\n",
                        "│  3 │ rms spot size  │        0 │              │              │       10 │   2.259 │   2.259 │           3.63 │\n",
                        "╘════╧════════════════╧══════════╧══════════════╧══════════════╧══════════╧═════════╧═════════╧════════════════╛\n",
                        "╒════╤═════════════════╤═══════════╤════════════════════╤══════════════╤══════════════╕\n",
                        "│    │ Variable Type   │   Surface │ Value              │   Min. Bound │   Max. Bound │\n",
                        "╞════╪═════════════════╪═══════════╪════════════════════╪══════════════╪══════════════╡\n",
                        "│  0 │ radius          │         1 │ 25.0               │           10 │          100 │\n",
                        "│  1 │ radius          │         2 │ -150.0             │         -200 │          -20 │\n",
                        "│  2 │ radius          │         3 │ -25.0              │         -100 │          -10 │\n",
                        "│  3 │ radius          │         4 │ 25.0               │           10 │          100 │\n",
                        "│  4 │ radius          │         5 │ 150.0              │           20 │          200 │\n",
                        "│  5 │ radius          │         6 │ -25.0              │         -100 │          -10 │\n",
                        "│  6 │ thickness       │         1 │ 2.5                │            1 │            5 │\n",
                        "│  7 │ thickness       │         2 │ 7.5                │            1 │           15 │\n",
                        "│  8 │ thickness       │         3 │ 1.5000000000000002 │            1 │            5 │\n",
                        "│  9 │ thickness       │         4 │ 5.0                │            1 │           15 │\n",
                        "│ 10 │ thickness       │         5 │ 2.5                │            1 │            5 │\n",
                        "│ 11 │ thickness       │         6 │ 40.0               │           30 │           60 │\n",
                        "│ 12 │ material        │         1 │ N-BK7              │          nan │          nan │\n",
                        "│ 13 │ material        │         3 │ N-F2               │          nan │          nan │\n",
                        "│ 14 │ material        │         5 │ N-BK7              │          nan │          nan │\n",
                        "╘════╧═════════════════╧═══════════╧════════════════════╧══════════════╧══════════════╛\n"
                    ]
                }
            ],
            "source": [
                "problem = optimization.OptimizationProblem()\n",
                "target_focal_length = 50.0\n",
                "\n",
                "# Operand: Effective Focal Length (EFL)\n",
                "problem.add_operand(\n",
                "    input_data={\"optic\": lens_system},\n",
                "    operand_type=\"f2\",\n",
                "    target=target_focal_length,\n",
                "    weight=1.0,\n",
                ")\n",
                "\n",
                "# Operands: RMS Spot Size for each field\n",
                "for Hx, Hy in lens_system.fields.get_field_coords():\n",
                "    problem.add_operand(\n",
                "        operand_type=\"rms_spot_size\",\n",
                "        target=0.0,\n",
                "        weight=10.0,\n",
                "        input_data={\n",
                "            \"optic\": lens_system,\n",
                "            \"surface_number\": -1,  # Image surface\n",
                "            \"Hx\": Hx,\n",
                "            \"Hy\": Hy,\n",
                "            \"num_rays\": 16,  # Rays on one axis for 'uniform' distribution\n",
                "            \"wavelength\": lens_system.primary_wavelength,\n",
                "            \"distribution\": \"uniform\",\n",
                "        },\n",
                "    )\n",
                "\n",
                "# Variables: Radii\n",
                "problem.add_variable(lens_system, \"radius\", surface_number=1, min_val=10, max_val=100)\n",
                "problem.add_variable(lens_system, \"radius\", surface_number=2, min_val=-200, max_val=-20)\n",
                "problem.add_variable(lens_system, \"radius\", surface_number=3, min_val=-100, max_val=-10)\n",
                "problem.add_variable(lens_system, \"radius\", surface_number=4, min_val=10, max_val=100)\n",
                "problem.add_variable(lens_system, \"radius\", surface_number=5, min_val=20, max_val=200)\n",
                "problem.add_variable(lens_system, \"radius\", surface_number=6, min_val=-100, max_val=-10)\n",
                "\n",
                "# Variables: Thicknesses (air and glass)\n",
                "problem.add_variable(\n",
                "    lens_system, \"thickness\", surface_number=1, min_val=1, max_val=5\n",
                ")  # Lens 1 thickness\n",
                "problem.add_variable(\n",
                "    lens_system, \"thickness\", surface_number=2, min_val=1, max_val=15\n",
                ")  # Air space 1\n",
                "problem.add_variable(\n",
                "    lens_system, \"thickness\", surface_number=3, min_val=1, max_val=5\n",
                ")  # Lens 2 thickness\n",
                "problem.add_variable(\n",
                "    lens_system, \"thickness\", surface_number=4, min_val=1, max_val=15\n",
                ")  # Air space 2\n",
                "problem.add_variable(\n",
                "    lens_system, \"thickness\", surface_number=5, min_val=1, max_val=5\n",
                ")  # Lens 3 thickness\n",
                "problem.add_variable(\n",
                "    lens_system, \"thickness\", surface_number=6, min_val=30, max_val=60\n",
                ")  # Back focal length (approx)\n",
                "\n",
                "# Variables: Materials (using Glass Expert)\n",
                "available_glasses = glasses_selection(\n",
                "    lambda_min=0.4, lambda_max=0.7, catalogs=[\"schott\", \"ohara_common\"]\n",
                ")\n",
                "problem.add_variable(\n",
                "    lens_system, \"material\", surface_number=1, glass_selection=available_glasses\n",
                ")\n",
                "problem.add_variable(\n",
                "    lens_system, \"material\", surface_number=3, glass_selection=available_glasses\n",
                ")\n",
                "problem.add_variable(\n",
                "    lens_system, \"material\", surface_number=5, glass_selection=available_glasses\n",
                ")\n",
                "\n",
                "problem.info()"
            ]
        },
        {
            "cell_type": "markdown",
            "id": "10185d26023b46108eb7d9f57d49d2b3",
            "metadata": {},
            "source": [
                "## 3. Run the Glass Expert Optimization"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "id": "8763a12b2bbd4a93a75aff182afb95dc",
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "Initial error function value: 14065.2\n",
                        "Initial glasses combination: ['N-BK7', 'N-F2', 'N-BK7']\n",
                        "\n",
                        "----------------------------------------------------------------------\n",
                        "Global exploration\n",
                        "\n",
                        "Selecting Material, Surface 1:\n",
                        "\tTrying N-SF11   as Material, Surface 1. Error function value: 3.69e-03\n",
                        "\tTrying BOROFLOAT33 as Material, Surface 1. Error function value: 0.21\n",
                        "\tTrying N-SK4    as Material, Surface 1. Error function value: 5.03e-03\n",
                        "\tTrying N-KZFS4  as Material, Surface 1. Error function value: 7.40e-03\n",
                        "\tTrying N-PK52A  as Material, Surface 1. Error function value: 0.19\n",
                        "\tTrying N-SF2    as Material, Surface 1. Error function value: 4.47e-03\n",
                        "\t-> Selected N-SF11 as Material, Surface 1.\n",
                        "\tNew combination: ['N-SF11', 'N-F2', 'N-BK7']\n",
                        "\tBest error function value: 3.69e-03 (-100%).\n",
                        "\n",
                        "Selecting Material, Surface 3:\n",
                        "\tTrying N-SF11   as Material, Surface 3. Error function value: 4.53e-03\n",
                        "\tTrying BOROFLOAT33 as Material, Surface 3. Error function value: 4.20e-03\n",
                        "\tTrying N-SK4    as Material, Surface 3. Error function value: 3.96e-03\n",
                        "\tTrying N-KZFS4  as Material, Surface 3. Error function value: 3.91e-03\n",
                        "\tTrying N-PK52A  as Material, Surface 3. Error function value: 4.42e-03\n",
                        "\tTrying N-SF2    as Material, Surface 3. Error function value: 3.67e-03\n",
                        "\t-> Selected N-SF2 as Material, Surface 3.\n",
                        "\tNew combination: ['N-SF11', 'N-SF2', 'N-BK7']\n",
                        "\tBest error function value: 3.67e-03 (-1%).\n",
                        "\n",
                        "Selecting Material, Surface 5:\n",
                        "\tTrying N-SF11   as Material, Surface 5. Error function value: 3.35e-03\n",
                        "\tTrying BOROFLOAT33 as Material, Surface 5. Error function value: 4.25e-03\n",
                        "\tTrying N-SK4    as Material, Surface 5. Error function value: 2.78e-03\n",
                        "\tTrying N-KZFS4  as Material, Surface 5. Error function value: 2.55e-03\n",
                        "\tTrying N-PK52A  as Material, Surface 5. Error function value: 3.92e-03\n",
                        "\tTrying N-SF2    as Material, Surface 5. Error function value: 3.06e-03\n",
                        "\t-> Selected N-KZFS4 as Material, Surface 5.\n",
                        "\tNew combination: ['N-SF11', 'N-SF2', 'N-KZFS4']\n",
                        "\tBest error function value: 2.55e-03 (-31%).\n",
                        "\n",
                        "\n",
                        "----------------------------------------------------------------------\n",
                        "Local exploration\n",
                        "\n",
                        "Selecting Material, Surface 1:\n",
                        "\tTrying SF11     as Material, Surface 1. Error function value: 2.54e-03\n",
                        "\tTrying SFL6     as Material, Surface 1. Error function value: 3.99e-03\n",
                        "\tTrying N-SF6    as Material, Surface 1. Error function value: 3.99e-03\n",
                        "\tTrying N-SF6HT  as Material, Surface 1. Error function value: 3.99e-03\n",
                        "\tTrying N-SF6HTultra as Material, Surface 1. Error function value: 3.99e-03\n",
                        "\tTrying SF56A    as Material, Surface 1. Error function value: 2.54e-03\n",
                        "\t-> Selected SF56A as Material, Surface 1.\n",
                        "\tNew combination: ['SF56A', 'N-SF2', 'N-KZFS4']\n",
                        "\tBest error function value: 2.54e-03 (-0%).\n",
                        "\n",
                        "Selecting Material, Surface 3:\n",
                        "\tTrying SF2      as Material, Surface 3. Error function value: 2.54e-03\n",
                        "\tTrying N-SF19   as Material, Surface 3. Error function value: 2.59e-03\n",
                        "\tTrying N-KZFS8  as Material, Surface 3. Error function value: 4.07e-03\n",
                        "\tTrying N-LAF7   as Material, Surface 3. Error function value: 4.45e-03\n",
                        "\tTrying LAFN7    as Material, Surface 3. Error function value: 4.45e-03\n",
                        "\tTrying N-LASF45 as Material, Surface 3. Error function value: 3.18e-03\n",
                        "\tNo better glass found, keeping N-SF2.\n",
                        "\tCombination: ['SF56A', 'N-SF2', 'N-KZFS4']\n",
                        "\tBest error function value: 2.54e-03 (0%).\n",
                        "\n",
                        "Selecting Material, Surface 5:\n",
                        "\tTrying N-KZFS4HT as Material, Surface 5. Error function value: 2.54e-03\n",
                        "\tTrying KZFSN4   as Material, Surface 5. Error function value: 2.54e-03\n",
                        "\tTrying N-LAF2   as Material, Surface 5. Error function value: 1.85e-03\n",
                        "\tTrying N-BAF51  as Material, Surface 5. Error function value: 2.12e-03\n",
                        "\tTrying N-LAF33  as Material, Surface 5. Error function value: 1.91e-03\n",
                        "\tTrying N-BAF4   as Material, Surface 5. Error function value: 3.49e-03\n",
                        "\t-> Selected N-LAF2 as Material, Surface 5.\n",
                        "\tNew combination: ['SF56A', 'N-SF2', 'N-LAF2']\n",
                        "\tBest error function value: 1.85e-03 (-27%).\n",
                        "\n",
                        "╒════╤═════════════════╤═══════════╤═══════════╤═════════════╤════════════╤═════════╤═════════════════╕\n",
                        "│    │ Type            │ Comment   │    Radius │   Thickness │ Material   │   Conic │   Semi-aperture │\n",
                        "╞════╪═════════════════╪═══════════╪═══════════╪═════════════╪════════════╪═════════╪═════════════════╡\n",
                        "│  0 │ Planar          │           │  inf      │   inf       │ Air        │       0 │         7.30434 │\n",
                        "│  1 │ Standard        │           │   33.3728 │     3.85319 │ SF56A      │       0 │         7.30434 │\n",
                        "│  2 │ Standard        │           │ -158.569  │     7.54508 │ Air        │       0 │         6.55284 │\n",
                        "│  3 │ Stop - Standard │           │  -21.4607 │     4.11158 │ N-SF2      │       0 │         3.68193 │\n",
                        "│  4 │ Standard        │           │   24.3137 │     5.5196  │ Air        │       0 │         4.20475 │\n",
                        "│  5 │ Standard        │           │  155.658  │     3.1396  │ N-LAF2     │       0 │         5.97945 │\n",
                        "│  6 │ Standard        │           │  -20.5099 │    40.5119  │ Air        │       0 │         6.50684 │\n",
                        "│  7 │ Planar          │           │  inf      │   nan       │ Air        │       0 │         8.81285 │\n",
                        "╘════╧═════════════════╧═══════════╧═══════════╧═════════════╧════════════╧═════════╧═════════════════╛\n"
                    ]
                },
                {
                    "data": {
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",
                        "text/plain": [
                            "<Figure size 1000x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 1000x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": [
                "optimizer = optimization.GlassExpert(problem)\n",
                "\n",
                "# Draw the starting lens\n",
                "lens_system.draw(title=\"Starting lens\")\n",
                "print(f\"Initial error function value: {problem.initial_value:.1f}\")\n",
                "\n",
                "# Run optimization\n",
                "res = optimizer.run(\n",
                "    num_neighbours=6,\n",
                "    maxiter=100,\n",
                "    tol=1e-6,\n",
                "    verbose=True,\n",
                "    plot_glass_map=False,\n",
                ")\n",
                "\n",
                "# Display the optimized lens\n",
                "lens_system.draw(title=\"Optimized lens\")\n",
                "lens_system.info()"
            ]
        }
    ],
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