{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1e26a3f7",
   "metadata": {},
   "source": [
    "# Tutorial 3g: Model Glass and Continuous Nd/Vd Optimization\n",
    "\n",
    "Tutorial 3e optimized the glasses with `GlassExpert`, which is a *categorical* search over a fixed list of catalogue glasses. This tutorial takes the complementary route:\n",
    "\n",
    "1. **Model glass.** Every lens is converted to an `optiland.materials.ModelMaterial`: a Buchdahl polynomial fitted to the glass descriptors `Nd` (index at the d-line) and `Vd` (Abbe number). Both descriptors become ordinary continuous variables, so the optimizer is free to invent glasses that no catalogue contains.\n",
    "2. **Snap to reality.** Each fictitious glass is projected back onto a real catalogue glass with `optiland.materials.find_closest_glass`, and the geometry is re-optimized.\n",
    "\n",
    "The starting system is the same deliberately poor six-lens design used in Tutorial 3e."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7f3c1a2",
   "metadata": {},
   "source": [
    "## Dispersion routes: visible vs infrared\n",
    "\n",
    "`ModelMaterial` is a 6th-order Buchdahl polynomial built from three glass descriptors: `nd` (index at the d-line), `Vd` (Abbe number) and `dPgF` (deviation of the relative partial dispersion). The model has two variants, called *routes*, and the tutorial below uses the visible one.\n",
    "\n",
    "**Visible route (default).** For systems that work at visible wavelengths. The three descriptors are enough to build the polynomial, so no extra input is required.\n",
    "\n",
    "**Infrared route.** For systems that work beyond the visible band, where `(nd, Vd, dPgF)` no longer constrain the near-IR curve shape well. It adds one descriptor, `P_ref`, the relative partial dispersion evaluated at the reference wavelength `lambda_ref`:\n",
    "\n",
    "$$\n",
    "P_\\mathrm{ref} = \\frac{n(\\lambda_\\mathrm{ref}) - n_d}{(n_d - 1)/V_d}.\n",
    "$$\n",
    "\n",
    "**Why `lambda_ref` defaults to 1.55 um.** The IR regression matrix shipped with Optiland was built from commercial glasses with `P_ref` evaluated at 1.55 um, the reference wavelength used for free-space-optics work in this model. The matrix therefore expects the descriptor at that wavelength, not at the design wavelength: a `P_ref` measured elsewhere describes a different quantity than the one the matrix was calibrated on. The updater consequently uses `ModelMaterial.IR_REF_WTH = 1.55 um` whenever the IR route is selected, and evaluates `P_ref` from the current glass at the same wavelength. The anchor at 1.55 um is then reproduced exactly, independently of the system's primary wavelength.\n",
    "\n",
    "**How the route is chosen.** `OpticUpdater` (used by `set_index`, `set_abbe` and `GlassExpert`) inspects the optic's primary wavelength:\n",
    "\n",
    "- primary <= 0.78 um (`ModelMaterial.MAX_VISIBLE_WTH`): visible route, `P_ref` and `lambda_ref` stay unset;\n",
    "- primary > 0.78 um: IR route, `lambda_ref = 1.55 um` (`IR_REF_WTH`) and `P_ref` is computed from the current glass at 1.55 um.\n",
    "\n",
    "A `ModelMaterial` that already stores a `P_ref`/`lambda_ref` pair keeps them unchanged. When building a model glass from scratch, pass both to select the IR route (`ModelMaterial(nd, vd, dPgF, P_ref=..., lambda_ref=1.55)`); pass neither to keep the visible route. Supplying only one raises a `ValueError`.\n",
    "\n",
    "This tutorial traces the F, d and C lines (0.4861, 0.5876 and 0.6563 um), so the primary wavelength is 0.5876 um and the visible route is used throughout; the IR descriptors are not needed here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bd4a44bf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:25.575419Z",
     "iopub.status.busy": "2026-11-04T17:43:25.575287Z",
     "iopub.status.idle": "2026-11-04T17:43:28.239673Z",
     "shell.execute_reply": "2026-11-04T17:43:28.239132Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "import optiland.backend as be\n",
    "from optiland import optic, optimization\n",
    "from optiland.materials import (\n",
    "    Material,\n",
    "    MaterialCatalog,\n",
    "    find_closest_glass,\n",
    "    get_nd_vd,\n",
    "    glasses_selection,\n",
    ")\n",
    "from optiland.optimization import HistoryObserver, minimize"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e891bbc1",
   "metadata": {},
   "source": [
    "## The starting point\n",
    "\n",
    "The design is intentionally mediocre: six identical collimating lenses made of N-BK7, with radii of 1000 mm and no attempt at colour correction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f9830efd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:28.241463Z",
     "iopub.status.busy": "2026-11-04T17:43:28.241259Z",
     "iopub.status.idle": "2026-11-04T17:43:28.555904Z",
     "shell.execute_reply": "2026-11-04T17:43:28.555422Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 1000x400 with 1 Axes>,\n",
       " <Axes: title={'center': 'Starting lens'}, xlabel='Z [mm]', ylabel='Y [mm]'>)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D_LINE = 0.5875618  # [um]\n",
    "GLASS_SURFACES = (1, 3, 4, 7, 8, 10)\n",
    "TARGET_FOCAL_LENGTH = 100  # [mm]\n",
    "\n",
    "\n",
    "class SixLensesStartPoint(optic.Optic):\n",
    "    \"\"\"A 6 lens design with very poor quality meant to be optimized.\"\"\"\n",
    "\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "\n",
    "        self.surfaces.add(index=0, radius=be.inf, thickness=be.inf)\n",
    "        self.surfaces.add(index=1, radius=1000, thickness=25, material=\"N-BK7\")\n",
    "        self.surfaces.add(index=2, radius=1000, thickness=5.0)\n",
    "        self.surfaces.add(index=3, radius=1000, thickness=25, material=\"N-BK7\")\n",
    "        self.surfaces.add(index=4, radius=be.inf, thickness=25, material=\"N-BK7\")\n",
    "        self.surfaces.add(index=5, radius=1000, thickness=25)\n",
    "        self.surfaces.add(index=6, radius=be.inf, thickness=25.0, is_stop=True)\n",
    "        self.surfaces.add(index=7, radius=-1000, thickness=25, material=\"N-BK7\")\n",
    "        self.surfaces.add(index=8, radius=be.inf, thickness=25, material=\"N-BK7\")\n",
    "        self.surfaces.add(index=9, radius=-1000, thickness=5.0)\n",
    "        self.surfaces.add(index=10, radius=1000, thickness=25, material=\"N-BK7\")\n",
    "        self.surfaces.add(index=11, radius=-1000, thickness=200)\n",
    "        self.surfaces.add(index=12)\n",
    "\n",
    "        self.set_aperture(aperture_type=\"imageFNO\", value=5)\n",
    "        self.fields.set_type(field_type=\"angle\")\n",
    "\n",
    "        self.fields.add(y=-14)\n",
    "        self.fields.add(y=-10)\n",
    "        self.fields.add(y=0)\n",
    "        self.fields.add(y=10)\n",
    "        self.fields.add(y=14)\n",
    "\n",
    "        self.wavelengths.add(value=0.4861)\n",
    "        self.wavelengths.add(value=0.5876, is_primary=True)\n",
    "        self.wavelengths.add(value=0.6563)\n",
    "\n",
    "\n",
    "lens = SixLensesStartPoint()\n",
    "lens.draw(title=\"Starting lens\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5b7e52b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:28.557753Z",
     "iopub.status.busy": "2026-11-04T17:43:28.557611Z",
     "iopub.status.idle": "2026-11-04T17:43:28.582930Z",
     "shell.execute_reply": "2026-11-04T17:43:28.582280Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒════╤═══════════════╤═══════════╤══════════╤═════════════╤════════════╤═════════╤═════════════════╕\n",
      "│    │ Type          │ Comment   │   Radius │   Thickness │ Material   │   Conic │   Semi-aperture │\n",
      "╞════╪═══════════════╪═══════════╪══════════╪═════════════╪════════════╪═════════╪═════════════════╡\n",
      "│  0 │ Planar        │           │      inf │         inf │ Air        │       0 │        116.634  │\n",
      "│  1 │ Standard      │           │     1000 │          25 │ N-BK7      │       0 │        116.634  │\n",
      "│  2 │ Standard      │           │     1000 │           5 │ Air        │       0 │        111.531  │\n",
      "│  3 │ Standard      │           │     1000 │          25 │ N-BK7      │       0 │        110.271  │\n",
      "│  4 │ Planar        │           │      inf │          25 │ N-BK7      │       0 │        105.179  │\n",
      "│  5 │ Standard      │           │     1000 │          25 │ Air        │       0 │        100.087  │\n",
      "│  6 │ Stop - Planar │           │      inf │          25 │ Air        │       0 │         93.6559 │\n",
      "│  7 │ Standard      │           │    -1000 │          25 │ N-BK7      │       0 │        100.023  │\n",
      "│  8 │ Planar        │           │      inf │          25 │ N-BK7      │       0 │        105.073  │\n",
      "│  9 │ Standard      │           │    -1000 │           5 │ Air        │       0 │        110.123  │\n",
      "│ 10 │ Standard      │           │     1000 │          25 │ N-BK7      │       0 │        111.37   │\n",
      "│ 11 │ Standard      │           │    -1000 │         200 │ Air        │       0 │        114.533  │\n",
      "│ 12 │ Planar        │           │      inf │         nan │ Air        │       0 │        141.078  │\n",
      "╘════╧═══════════════╧═══════════╧══════════╧═════════════╧════════════╧═════════╧═════════════════╛\n",
      "\n"
     ]
    }
   ],
   "source": [
    "lens.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "895aa1b6",
   "metadata": {},
   "source": [
    "## Step 1 - from catalogue glass to model glass\n",
    "\n",
    "A `ModelMaterial` is defined by four descriptors: `Nd`, `Vd`, `dPgF` (the partial-dispersion deviation from the normal line) and, for infrared work, a reference partial dispersion `P_ref` at `lambda_ref`. Optiland can build one from any existing material:\n",
    "\n",
    "```python\n",
    "lens.updater.set_index(value, surface_number)   # wavelength=None\n",
    "```\n",
    "\n",
    "With `wavelength=None`, `set_index` reads the `Nd`, `Vd` and `dPgF` of the current glass and rebuilds the surface material as a `ModelMaterial`. The Buchdahl fit is anchored on the d, F, C and g lines, so the model glass reproduces the original catalogue glass very closely.\n",
    "\n",
    "The model is only valid for `1.0 < Nd < 3.0` and `10 < Vd < 100`, which we will respect when setting the variable bounds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "39ee2ee0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:28.584495Z",
     "iopub.status.busy": "2026-11-04T17:43:28.584349Z",
     "iopub.status.idle": "2026-11-04T17:43:28.604906Z",
     "shell.execute_reply": "2026-11-04T17:43:28.604323Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " surface       material        Nd       Vd\n",
      "       1  ModelMaterial   1.51680   64.167\n",
      "       3  ModelMaterial   1.51680   64.167\n",
      "       4  ModelMaterial   1.51680   64.167\n",
      "       7  ModelMaterial   1.51680   64.167\n",
      "       8  ModelMaterial   1.51680   64.167\n",
      "      10  ModelMaterial   1.51680   64.167\n"
     ]
    }
   ],
   "source": [
    "def nd_vd(material):\n",
    "    \"\"\"Return Nd and Vd of a catalogue or model glass as plain floats.\"\"\"\n",
    "    nd = float(np.ravel(be.to_numpy(material.n(D_LINE)))[0])\n",
    "    vd = float(np.ravel(be.to_numpy(material.abbe()))[0])\n",
    "    return nd, vd\n",
    "\n",
    "\n",
    "before = {k: nd_vd(lens.surfaces[k].material_post) for k in GLASS_SURFACES}\n",
    "\n",
    "for surface_number in GLASS_SURFACES:\n",
    "    lens.updater.set_index(before[surface_number][0], surface_number)\n",
    "\n",
    "print(f\"{'surface':>8}{'material':>15}{'Nd':>10}{'Vd':>9}\")\n",
    "for k in GLASS_SURFACES:\n",
    "    material = lens.surfaces[k].material_post\n",
    "    nd, vd = nd_vd(material)\n",
    "    print(f\"{k:>8}{type(material).__name__:>15}{nd:>10.5f}{vd:>9.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ede8c467",
   "metadata": {},
   "source": [
    "## Merit function\n",
    "\n",
    "Tutorial 3e evaluated the spot size only at the primary wavelength, so the merit function had no information about colour. Here the focal length and the RMS spot size are evaluated at **all three wavelengths**: an optimizer can only move `Vd` if the merit function sees chromatic aberration.\n",
    "\n",
    "- `real_y_intercept_lcs` on the image plane keeps the focal length at 100 mm for five field points, at every wavelength (this is the axial colour constraint).\n",
    "- `rms_spot_size` with 16 uniform rays per field minimises the spot at every field and wavelength.\n",
    "\n",
    "Both sets of operands are wrapped in a `make_problem` helper so that the same merit can be rebuilt after the glasses are replaced."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4d74a7ca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:28.606388Z",
     "iopub.status.busy": "2026-11-04T17:43:28.606242Z",
     "iopub.status.idle": "2026-11-04T17:43:29.017232Z",
     "shell.execute_reply": "2026-11-04T17:43:29.016584Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "variables: 31   starting merit: 3.925e+06\n",
      "╒════╤════════════════════════╤═══════════════════╕\n",
      "│    │   Merit Function Value │   Improvement (%) │\n",
      "╞════╪════════════════════════╪═══════════════════╡\n",
      "│  0 │            3.92499e+06 │                 0 │\n",
      "╘════╧════════════════════════╧═══════════════════╛\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒════╤══════════════════════╤══════════╤══════════════╤══════════════╤══════════╤═══════════════╤═════════╤═════════╤════════════════╕\n",
      "│    │ Operand Type         │   Target │ Min. Bound   │ Max. Bound   │   Weight │   Eff. Weight │   Value │   Delta │   Contrib. [%] │\n",
      "╞════╪══════════════════════╪══════════╪══════════════╪══════════════╪══════════╪═══════════════╪═════════╪═════════╪════════════════╡\n",
      "│  0 │ real y intercept lcs │  -24.933 │              │              │        1 │             1 │ -66.044 │ -41.111 │           0.04 │\n",
      "│  1 │ real y intercept lcs │  -17.633 │              │              │        1 │             1 │ -46.902 │ -29.269 │           0.02 │\n",
      "│  2 │ real y intercept lcs │    0     │              │              │        1 │             1 │   0     │   0     │           0    │\n",
      "│  3 │ real y intercept lcs │   17.633 │              │              │        1 │             1 │  46.902 │  29.269 │           0.02 │\n",
      "│  4 │ real y intercept lcs │   24.933 │              │              │        1 │             1 │  66.044 │  41.111 │           0.04 │\n",
      "│  5 │ real y intercept lcs │  -24.933 │              │              │        1 │             1 │ -66.148 │ -41.215 │           0.04 │\n",
      "│  6 │ real y intercept lcs │  -17.633 │              │              │        1 │             1 │ -46.975 │ -29.342 │           0.02 │\n",
      "│  7 │ real y intercept lcs │    0     │              │              │        1 │             1 │   0     │   0     │           0    │\n",
      "│  8 │ real y intercept lcs │   17.633 │              │              │        1 │             1 │  46.975 │  29.342 │           0.02 │\n",
      "│  9 │ real y intercept lcs │   24.933 │              │              │        1 │             1 │  66.148 │  41.215 │           0.04 │\n",
      "│ 10 │ real y intercept lcs │  -24.933 │              │              │        1 │             1 │ -66.198 │ -41.265 │           0.04 │\n",
      "│ 11 │ real y intercept lcs │  -17.633 │              │              │        1 │             1 │ -47.01  │ -29.377 │           0.02 │\n",
      "│ 12 │ real y intercept lcs │    0     │              │              │        1 │             1 │   0     │   0     │           0    │\n",
      "│ 13 │ real y intercept lcs │   17.633 │              │              │        1 │             1 │  47.01  │  29.377 │           0.02 │\n",
      "│ 14 │ real y intercept lcs │   24.933 │              │              │        1 │             1 │  66.198 │  41.265 │           0.04 │\n",
      "│ 15 │ rms spot size        │    0     │              │              │       10 │            10 │  50.529 │  50.529 │           6.51 │\n",
      "│ 16 │ rms spot size        │    0     │              │              │       10 │            10 │  50.701 │  50.701 │           6.55 │\n",
      "│ 17 │ rms spot size        │    0     │              │              │       10 │            10 │  50.782 │  50.782 │           6.57 │\n",
      "│ 18 │ rms spot size        │    0     │              │              │       10 │            10 │  51.009 │  51.009 │           6.63 │\n",
      "│ 19 │ rms spot size        │    0     │              │              │       10 │            10 │  51.176 │  51.176 │           6.67 │\n",
      "│ 20 │ rms spot size        │    0     │              │              │       10 │            10 │  51.255 │  51.255 │           6.69 │\n",
      "│ 21 │ rms spot size        │    0     │              │              │       10 │            10 │  51.491 │  51.491 │           6.76 │\n",
      "│ 22 │ rms spot size        │    0     │              │              │       10 │            10 │  51.653 │  51.653 │           6.8  │\n",
      "│ 23 │ rms spot size        │    0     │              │              │       10 │            10 │  51.73  │  51.73  │           6.82 │\n",
      "│ 24 │ rms spot size        │    0     │              │              │       10 │            10 │  51.009 │  51.009 │           6.63 │\n",
      "│ 25 │ rms spot size        │    0     │              │              │       10 │            10 │  51.176 │  51.176 │           6.67 │\n",
      "│ 26 │ rms spot size        │    0     │              │              │       10 │            10 │  51.255 │  51.255 │           6.69 │\n",
      "│ 27 │ rms spot size        │    0     │              │              │       10 │            10 │  50.529 │  50.529 │           6.51 │\n",
      "│ 28 │ rms spot size        │    0     │              │              │       10 │            10 │  50.701 │  50.701 │           6.55 │\n",
      "│ 29 │ rms spot size        │    0     │              │              │       10 │            10 │  50.782 │  50.782 │           6.57 │\n",
      "╘════╧══════════════════════╧══════════╧══════════════╧══════════════╧══════════╧═══════════════╧═════════╧═════════╧════════════════╛\n",
      "╒════╤═════════════════╤═══════════╤════════════╤══════════════╤══════════════╕\n",
      "│    │ Variable Type   │   Surface │      Value │   Min. Bound │   Max. Bound │\n",
      "╞════╪═════════════════╪═══════════╪════════════╪══════════════╪══════════════╡\n",
      "│  0 │ radius          │         1 │  1000      │       -500   │          500 │\n",
      "│  1 │ radius          │         2 │  1000      │       -500   │          500 │\n",
      "│  2 │ radius          │         3 │  1000      │       -500   │          500 │\n",
      "│  3 │ radius          │         5 │  1000      │       -500   │          500 │\n",
      "│  4 │ radius          │         7 │ -1000      │       -500   │          500 │\n",
      "│  5 │ radius          │         9 │ -1000      │       -500   │          500 │\n",
      "│  6 │ radius          │        10 │  1000      │       -500   │          500 │\n",
      "│  7 │ radius          │        11 │ -1000      │       -500   │          500 │\n",
      "│  8 │ thickness       │         1 │    25      │          8   │           20 │\n",
      "│  9 │ thickness       │         2 │     5      │          0.4 │            5 │\n",
      "│ 10 │ thickness       │         3 │    25      │          8   │           20 │\n",
      "│ 11 │ thickness       │         4 │    25      │          3   │           10 │\n",
      "│ 12 │ thickness       │         5 │    25      │         10   │           20 │\n",
      "│ 13 │ thickness       │         6 │    25      │         10   │           20 │\n",
      "│ 14 │ thickness       │         7 │    25      │          3   │           20 │\n",
      "│ 15 │ thickness       │         8 │    25      │          8   │           20 │\n",
      "│ 16 │ thickness       │         9 │     5      │          0.4 │            5 │\n",
      "│ 17 │ thickness       │        10 │    25      │          6   │           20 │\n",
      "│ 18 │ thickness       │        11 │   200      │         20   │           45 │\n",
      "│ 19 │ index           │         1 │     1.5168 │          1.4 │            2 │\n",
      "│ 20 │ abbe            │         1 │    64.1673 │         20   │           90 │\n",
      "│ 21 │ index           │         3 │     1.5168 │          1.4 │            2 │\n",
      "│ 22 │ abbe            │         3 │    64.1673 │         20   │           90 │\n",
      "│ 23 │ index           │         4 │     1.5168 │          1.4 │            2 │\n",
      "│ 24 │ abbe            │         4 │    64.1673 │         20   │           90 │\n",
      "│ 25 │ index           │         7 │     1.5168 │          1.4 │            2 │\n",
      "│ 26 │ abbe            │         7 │    64.1673 │         20   │           90 │\n",
      "│ 27 │ index           │         8 │     1.5168 │          1.4 │            2 │\n",
      "│ 28 │ abbe            │         8 │    64.1673 │         20   │           90 │\n",
      "│ 29 │ index           │        10 │     1.5168 │          1.4 │            2 │\n",
      "│ 30 │ abbe            │        10 │    64.1673 │         20   │           90 │\n",
      "╘════╧═════════════════╧═══════════╧════════════╧══════════════╧══════════════╛\n"
     ]
    }
   ],
   "source": [
    "def make_problem(lens, optimize_glass=True):\n",
    "    \"\"\"Build the merit function, the geometric variables and (optionally) glass variables.\"\"\"\n",
    "    problem = optimization.OptimizationProblem()\n",
    "\n",
    "    # Focal length at every field and every wavelength.\n",
    "    for wavelength in lens.wavelengths:\n",
    "        for k, hy in enumerate([-1, -0.714, 0, 0.714, 1]):\n",
    "            input_data = {\n",
    "                \"optic\": lens,\n",
    "                \"surface_number\": 12,\n",
    "                \"Hx\": 0,\n",
    "                \"Hy\": hy,\n",
    "                \"Px\": 0,\n",
    "                \"Py\": 0,\n",
    "                \"wavelength\": wavelength.value,\n",
    "            }\n",
    "            problem.add_operand(\n",
    "                operand_type=\"real_y_intercept_lcs\",\n",
    "                target=TARGET_FOCAL_LENGTH\n",
    "                * be.tan(be.deg2rad(lens.fields.y_fields[k])),\n",
    "                weight=1,\n",
    "                input_data=input_data,\n",
    "            )\n",
    "\n",
    "    # RMS spot size at every field and every wavelength.\n",
    "    for field in lens.fields.get_field_coords():\n",
    "        for wavelength in lens.wavelengths:\n",
    "            input_data = {\n",
    "                \"optic\": lens,\n",
    "                \"surface_number\": 12,\n",
    "                \"Hx\": field[0],\n",
    "                \"Hy\": field[1],\n",
    "                \"num_rays\": 16,\n",
    "                \"wavelength\": wavelength.value,\n",
    "                \"distribution\": \"uniform\",\n",
    "            }\n",
    "            problem.add_operand(\n",
    "                operand_type=\"rms_spot_size\",\n",
    "                target=0.0,\n",
    "                weight=10,\n",
    "                input_data=input_data,\n",
    "            )\n",
    "\n",
    "    # Curvatures.\n",
    "    for surface_number in (1, 2, 3, 5, 7, 9, 10, 11):\n",
    "        problem.add_variable(\n",
    "            lens, \"radius\", surface_number=surface_number, min_val=-500, max_val=500\n",
    "        )\n",
    "\n",
    "    # Thicknesses.\n",
    "    thickness_bounds = {\n",
    "        1: (8, 20),\n",
    "        2: (0.4, 5),\n",
    "        3: (8, 20),\n",
    "        4: (3, 10),\n",
    "        5: (10, 20),\n",
    "        6: (10, 20),\n",
    "        7: (3, 20),\n",
    "        8: (8, 20),\n",
    "        9: (0.4, 5),\n",
    "        10: (6, 20),\n",
    "        11: (20, 45),\n",
    "    }\n",
    "    for surface_number, (lo, hi) in thickness_bounds.items():\n",
    "        problem.add_variable(\n",
    "            lens, \"thickness\", surface_number=surface_number, min_val=lo, max_val=hi\n",
    "        )\n",
    "\n",
    "    # Glass: index at the d-line and Abbe number, both continuous.\n",
    "    if optimize_glass:\n",
    "        for surface_number in GLASS_SURFACES:\n",
    "            problem.add_variable(\n",
    "                lens,\n",
    "                \"index\",\n",
    "                surface_number=surface_number,\n",
    "                wavelength=None,\n",
    "                min_val=1.40,\n",
    "                max_val=2.00,\n",
    "            )\n",
    "            problem.add_variable(\n",
    "                lens,\n",
    "                \"abbe\",\n",
    "                surface_number=surface_number,\n",
    "                min_val=20,\n",
    "                max_val=90,\n",
    "            )\n",
    "\n",
    "    return problem\n",
    "\n",
    "\n",
    "problem = make_problem(lens, optimize_glass=True)\n",
    "merit_start = problem.sum_squared()\n",
    "print(f\"variables: {len(problem.variables)}   starting merit: {merit_start:.3e}\")\n",
    "problem.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "188a4984",
   "metadata": {},
   "source": [
    "## Optimizing Nd and Vd continuously\n",
    "\n",
    "The `index` variable moves `Nd` (it calls `updater.set_index`, which rebuilds the `ModelMaterial` with the new index while keeping `Vd` and `dPgF`). The `abbe` variable moves `Vd` through `updater.set_abbe`, which keeps `Nd` and `dPgF`.\n",
    "\n",
    "`dPgF` is deliberately left at its starting value: the six model glasses therefore share the dispersion curve shape of N-BK7 and differ only in `Nd` and `Vd`.\n",
    "\n",
    "The problem is fully continuous, so Optiland's native damped least squares (`\"dls\"`) can solve it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "96488419",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:29.018714Z",
     "iopub.status.busy": "2026-11-04T17:43:29.018547Z",
     "iopub.status.idle": "2026-11-04T17:43:43.655226Z",
     "shell.execute_reply": "2026-11-04T17:43:43.654685Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stop reason: `ftol` termination condition is satisfied.\n",
      "merit: 6.055   residual evaluations: 932\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "# Trial designs during optimisation can vignette an entire field; Optiland\n",
    "# scores them as very poor, but NumPy warns about the empty ray bundle first.\n",
    "warnings.filterwarnings(\"ignore\", message=\"Mean of empty slice\")\n",
    "\n",
    "history = HistoryObserver()\n",
    "result = minimize(problem, \"dls\", observers=[history])\n",
    "\n",
    "merit_continuous = problem.sum_squared()\n",
    "print(f\"stop reason: {result.stop_reason}\")\n",
    "print(f\"merit: {merit_continuous:.3f}   residual evaluations: {result.n_evals}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b37f14a4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:43.656793Z",
     "iopub.status.busy": "2026-11-04T17:43:43.656630Z",
     "iopub.status.idle": "2026-11-04T17:43:43.877159Z",
     "shell.execute_reply": "2026-11-04T17:43:43.876820Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAk0AAAE2CAYAAAB896bHAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjExLjIsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvgI3uAAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAT01JREFUeJzt3Qd4U1UbB/C3ew+66KBQNpRVtoogMhTZU0QZKvqpiAtUhqKAAgoOFBkKIm4BQYYLmbL3pkAZBUpLd+nevd/znpKYNClNmqQZ9/97nkuSm+Tm5OSmeTnnPefYSZIkEQAAAADclf3d7wYAAAAABE0AAAAAOkJLEwAAAIAOEDQBAAAA6ABBEwAAAIAOEDQBAAAA6ABBEwAAAIAOEDQBAAAA6ABBEwAAAIAOEDQBWKAOHTpQnz59zF0MqzZ48GBq1qyZzb+mOc8nc56n+I6AOSBoAlnbsGEDDRgwgIKDg8nZ2Znq1KlD3bp1oy+++IIyMzNN+totW7ak/v37m/Q1rE2vXr3Izs6O7rnnHq33Ozo60ujRow1+nV27donX+ffff8XnPmzYsLs+vmnTplS/fn2y5FWnbPF8ssX3BNbN0dwFADCHkpIS8eP722+/0bRp0+iTTz6hevXqUWpqKq1fv55mzpxJ165do48++sgs5Tt69CjJ2aFDh2jNmjX06KOPmuT4mzZtooYNG9IDDzwggubNmzdTcnIyBQUFaTx29+7dFBMTQ++9954ItKyRqc4nc56ncv+OgHmgpQlk6d1336XVq1fTL7/8IgKkxo0bixaH0NBQmjhxIp06dUq0LkDNCwkJoaioKJo+fToVFxeb5DU2btxIgwYNEtefeeYZ8Trff/+91seuWLGCHBwc6KmnnjJJWQDAikgAMnP79m3J3d1devDBB3V+TllZmbRo0SKpZcuWkouLi1SrVi1p4MCB0unTp9Ue17BhQ2nYsGFSdHS0OL6bm5sUFhYmzZkzR+1xHh4e3M+jtvFzFdq3by89/PDD1To24zK+8sorGvv79esntWjRolrvTZ9jbtu2Terevbvk5+cneXt7S/fee6/0yy+/iNe6m549e4r39M8//4g6Wbhwodr9Dg4O0hNPPKG2r6SkRJo5c6ZUp04dUSddu3aVTp48KQ0aNEhq2rSpxmucOXNGHPvff/8Vt0tLS6W6detKzZs313qu8DH79+9v0Gsaej4dP35c6tKli+Tq6irK+v7774tyG+N8OnHihHT//feL98GfI3927NixY+J98f6IiAjx+VVU8bjz5s3TKIdi69y5s9o5o9hvb28vBQYGSsOHD5diYmIMek/G/p4CVISgCWRn8+bN4g/w/PnzdX7Oa6+9Jjk6OkqfffaZlJaWJp0/f178wPMfdtU/yPzH+IEHHpCGDBkinTp1Svzofvjhh+L11q5dq3ZM/oHiHw9tKvuR0/XY+gQ4ur43XY958eJF8dhJkyZJiYmJUk5OjnTo0CHpsccek65fv65T0MQeeughyd/fX7zPuwVNEyZMEK/39ddfSxkZGSJ44edykKEtgOGAg4/LgY8CB0Bcj/v27VN77JIlS8T+jRs3GvSahpxPHLg88sgj4jNPT0+XvvzyS8nZ2VnUr6HnU7du3cT5xMEDl2P8+PHiPxT79++X+vbtK509e1a85nPPPSfq/sqVK1Uet6JVq1aJOuRja1NQUCACNw5euEzZ2dnVfk+m+J4CqELQBLLzxRdfiD+O2v7nrE1sbKz43zD/UKriP7Q+Pj5qf9T5jzG3BiQkJKg9llsxevfubfCPnK7H1jXA0ee96XpMxY9kVQFSVUET/5hx2aZOnVpp0KQo/5QpU9SOc/nyZfFYbQFMx44dpXHjxqntu3HjhjjO008/rba/Xbt2UmhoqFqAVZ3XNOR8cnJyEuVT9eqrr4rXiouLM/h8unXrlnIfBxocdHBQGR8fr1Y2LseMGTOqPK6q7du3i+dxS2N+fv5daqW8/vi82bBhQ7Xek6m+pwCqkNMEoMNIq7KyMho6dKjafh8fHzHaa8eOHWqjqtq2bSvyciqOArp69arBdW3sY+v73nTRqlUrkTA9fvx42rJlC+Xl5VWrbK1bt6YxY8bQwoULKS4uTutjdu7cKco/cOBAtf2c5M3lqCghIUEkECvymRTCw8Pp4YcfFnlu2dnZYt/Jkyfp+PHj9OSTT4qcpuq+pqF1zvldXL6KUxuUlpaK0X+Gnk88clTBz89PJMM3aNBA5Peplo3PO33Os+joaDEqsW7duiLx3tXVVXkfH2fs2LFitKqTk5M4Xxo1aiTuu3z5stV/T8F2IWgC2eFRcuzGjRs6PT4tLU1cqv64KPC+/Px8tcCg4h9i5u3tTbdv3zag1MY5dsUASN/3pssx27VrR2vXrhVleuSRR8jX11dM4/Dzzz+Tvt5//31xOWPGDK33K8pfu3Ztjfu07eMfbxcXFxEgVfTss89Sbm6uCJwUCeCK4M+Q16yszLrW+d1eh0d7Gvt88vLyqnS/rudZUlIS9evXj+zt7enPP/+kgIAA5X1ZWVl0//330/nz52ndunWUkZEhzqHExERxf3WT/y3pewq2C0ETyE7Xrl3J3d2d/vrrL50ez//7VvwQVMT73NzcxPEUTDksXddj8/+uFS0mquLj46v93nQ9JuMWhiNHjogfMp7CgX+MHn/8cTFaUR/cEvHKK6+IkW08orEif3//u5ZfW9DUu3dvtc9Lgace4GDk66+/poKCAvrxxx+pZ8+eotXFkNc09Hy62+soymLs88mQc5gDE67LW7duiXnQmjRponb/tm3bxH0ff/wxde7cmTw9PcX+2NhYMoQlfU/BdiFoAtnhH/9XX31VdLPwj6g2HAgsX75cXH/wwQfF/5h5TidV/D9m/gHo0aNHtf4Ae3h4UGFhIZkCdxWdPXtWbR//KHGXiSp93puux1RVq1YtMTkhB078Ojznkb54Hi3+QXzzzTc17uvevbsoH8+zVLFcZ86cUduXk5Mjumgqds2pTpzJXXEHDx6kWbNmiRYHno7AkNfURt/zibsJb968qTFlAncZ8jxTNXE+6Yq7x5544gnRBfrNN9+I/6BUhlv8VH333Xcaj9HnPZnqewqgCkETyBL/KI4cOVJMnjh79myRR1FUVCRyXhYvXkxt2rShixcvisdGRESIuZu+/PJLcV96erq4b/jw4eI5c+bMqVYZOH+CW08M/R+2NtzVdPjwYVq6dKloHeLcnNdee406deqk9jh93puux/z8889p8uTJdOzYMRGocPcL7+MfVP5hq06Q+/bbb9M///wj8nhU8Szdzz33nMh7WrVqlZjF/fTp0zRhwgSNWcX//vtv0fXDrSCV4SCJf1g//PBD0aU0ZMgQjcfo85ra6Hs+8TH59Tgg40COuw2XLFkijqGa62TK80lX/F3i1iXuVh01apTWx3AgxV22/JlyF3lKSgotWLBA1ENF+rwnU31PAdSopYUDyMz69evFqJqgoCAxyodHSvEQb57rRXWoO8//wsOYeTQPD/fm0Tg8dw8PNdc2/0tFPNyaRySp4hFRPFrM09NTr3l1dDk2l5dHOgUHB4tRQj169BBz4FQ2T5Mu703XY2ZlZYn5lXiUGr83nquJ5wFas2aNpM/oOVVFRUXi/XM9aZun6Z133hHP43Ldd999Yl6jinMmjR49WtxXFR76zq/Dw9cro+trVkbf8+no0aNiBBq/Fs8NNXv2bLV5mox5PnH5+X1UpG0kW8Xj8vF0maeJpzTgOuOpAPh8ev3116WkpCTxOJ7rqbrvyRTfUwBVdvyPehgFAGB7y+ZwvtKUKVO0dvNZKh5RxqPnfv31V3MXBQDQPQcAcrBnzx7RXVNZPhMAgC6wYC8A2DzOpUKjOgAYCongAAAAADpAThMAAACADtDSBAAAAKADBE0AAAAAOkAi+B088R5PbMjrK2HWWAAAANsnSZKYrJcXqOYZ5auCoOkODpgqriQOAAAAti8uLk6sdVkVBE13cAuTouJ4cVFjt2LxUgGBgYE6RbKA+sP5Zznw/UX94fyz3e9vVlaWaDBRxABVQdB0h6JLjgMmUwRNvGo6HxdBE+qvpuH8Q/2ZE84/1J81nH+6puXIvtmDF3aMjIykjh07GvFjAgAAAFsj+6DpxRdfpOjoaDpy5Ii5PwsAAACwYLIPmgAAAAB0gaAJAAAAQAcImgAAAADkNnquqKiIvv/+ezp79qy4/emnn5IluJWZTyfjsinKxYvCanmYuzgAAAAg56CptLSUHnjgAXJxcaGBAweSu7s7WYLv9l+jdzedI0kMaYyhWQNa0Nj7IsxdLAAAAJBr0LR27VrKyMgQrUyOjo4W08L07ubygIlJEtE7m87Rkl1XqHmIFzWp/d/WKMiT3JwdKj1ObGou1Q/woBAftxp9DwAAAFDO0VLWftmyZQstW7aMLly4QN999x116tRJ43Fff/21uI/XienSpQvNnDmT/P39xX0nT56kAQMG0KJFiyg9PZ2GDBlC7dq1I3PiQIcDpYoSswrEtvNiinIfz6sVXsudmtT2VAZSjWt70okbt+mdjWepTCKytyOaN7QVjexYt2bfCAAAAFhG0DRlyhQ6deoUDR48mDZu3Eh5eXkaj1m4cCG9/fbbtGTJEqpXrx5Nnz6dHn74YTp06BA5OJS30GzevJlGjhwpZv3k+3bs2EGtWrUic+GWIQ50OOBR4NtfjGpLaXnFdCkpmy4mZtOl5BxKzy2iG+l5Ytt2Plnr8fg409efpW5NAtHiBAAAIMeg6b333hO5SDdv3qQJEyZo3F9cXCwe89Zbb9HYsWPFvp9//pkiIiJo06ZNolWpZcuWdOvWLZo1a5a4/9q1a2LCSnMGTdyVxi1D09efoVKJyMGOaO7QVtS3dajGY1NzCikmKZtiErMpJjlHBFTRCVmUW1Sq9rhSSaJrqXkImgAAAOQYNHHAdDenT58WXW59+vRR7qtbt64IlHbu3CmCphEjRojRco899pjo7tuzZw+9//77lR6zsLBQbKqL9inWqeHNWEa0r0P3NfCj01cTqHWDUAqr5a71+H7uTnRPfT+xKSTczqduC3ZptFTV9XM1ahktHb9X/kzl9J6NCfWH+sP5Z73w/TVt/en7u2IRQVNV4uLixGVISIja/uDgYNE6pQi8du/eTX///bcIhrgbT5HvpM28efOUrVKqeDVkXtzPmBzKyqiBZyk5FGZRcnKOXh/O1J716IPt15WB0yPN/cihMJuSk7NJLvikzszMFCc+FjxG/eH8sy74/qL+LPn84xxpmwuaeDoB5uzsrLafA6WSkhLlbQ8PDxo2bJhOx5w2bRpNmjSJli9fLjZ+jcuXL1NgYKBYDdnYHxqvoMzH1vdH/5keQdSvfX1asvMK/Xg4jg5ezyFXr1rk7eZEcmFI/QHqD+efeeH7i/qz5PPP1dXV9oImRYtRamoq+fn9133Ft5s1a1atY3LAxdvkyZPFxt1zPj4+olJN8cPMH1p1j80TYr47sCUdjE2nKym59NmOy/TugBYkJ4bUH6D+cP6ZF76/qD9LPf/0/U2xil+gqKgoMffSwYMHlft4hB3nOnXo0MGgYy9evJgiIyOpY8eOZMmcHe1p5sDyQOm7A9fFqDsAAACoOVYRNPn6+oqpBObPn09paWmib3L27Nnk5OQkEr8N8eKLL1J0dLQYaWfpujYOpIdb1KbSMolm8izj2iaBAgAAANsNmn777TfRzda9e3dxm6cV4NtffPGFWosQTzEQGhoquut++ukn2rBhw12TvW3R2/0iycXRng5cTaM/zySauzgAAACyYRE5TT169BABUEUBAQHK65xv9Pvvv4uWppycHAoPDzdKfgsHY7wpks0tXbifOz3/QEP6bPslmvNHND3YLJDcnS3iYwQAALBpFvFrywERb7rgliVjti5x9xxvikRwa/BC94b067GbFH87n5buukKTH2pq7iIBAADYPIvonjMna0kEV+Xq5EAz+jcX17/cfZVupGkuOwMAAADGJfugyZoSwVU93CKY7m8UQEUlZTT792hzFwcAAMDmyT5osuZ5J2YOjCRHezvadj6Jdl3UvsgvAAAAGIfsgyZr7J5TaBTkRU/eFyGuz94cLVqdAAAAwDRkHzRZa/ecwiu9GlOApwtdTc2llftizV0cAAAAmyX7oMnaebk60dRHypeSWbT9EiVlGXexYQAAACiHoMkGDG0bRm3r+lJuUSnN+/O8uYsDAABgk2QfNFlzTpOCvb0dzR7YkuzsiDacTKAj19LNXSQAAACbI/ugydpzmhRa1fGhxzqGi+vvbjwn1qcDAAAA45F90GRLXn+oKXm7OlL0rSz66fANcxcHAADApiBosiH+ni7KJVU+/uciZeQWmbtIAAAANgNBk415onNdahbsRbfziumjfy6auzgAAAA2Q/ZBky0kgqtydLCnmQNbiOvcRXc2PtPcRQIAALAJsg+abCURXNU9DfxpQJtQkiSimZvOkcRXAAAAwCCyD5ps1fS+zcjNyYGOXs+gVftjaf+VVLqVmW/uYgEAAFgtR3MXAEwjxMeNJvZoRAu2XKRZm8snvLS3I5o3tBWN7FgX1Q4AAKAntDTZsP6tQ9Ru89RN09efRYsTAABANSBosmHxtzW740olia6l5pmlPAAAANYMQZMNqx/gIbrkVDnY2VFEgLu5igQAAGC1ZB802dqUAxXzmjiHidekU3hvcAuxHwAAAPQj+6DJFqccUMVJ3/++3p183JzEbQ8X5P4DAABUh+yDJjmo6+9B4++vL66v3HfN3MUBAACwSgiaZOLxznXJ2cGeTsXdpuM3MsxdHAAAAKtjM301mZmZdODAAeXtkJAQatOmjVnLZEkCPF1oUFQorT12k1bujaV2j9cyd5EAAACsis0ETefPn6dx48ZR27Ztxe3u3bsjaKrgqS71RdD019lEMVcTEsIBAABkGDSxVq1a0bRp06hBgwYUHh5u7uJYnMhQb7qngR8dvJpO3x+4Tm/2aWbuIgEAAFgNi8lpys3NpRUrVtDrr79OV65c0fqY2NhYWrBgAb3zzju0ZcsWtft8fX3J0dGRZs2aRa1bt6a5c+fWUMmtr7WJ/XT4BuUXlZq7OAAAAFbDIoKmlStXUuPGjenvv/+mjz/+mOLi4jQes2fPHmrRooWYGiA/P5+eeOIJmjhxovL+Zs2aiefv2LGDzp49S/Pnz6fbt2/X8DuxfL2a16ZwPze6nVdMG07Gm7s4AAAAVsMigqaoqCiRk7Rw4cJKH/PCCy/QyJEjac2aNaK1afXq1WJiymPHjmk8NiwsjPz8/CgjA6PEKnKwt6Nx90aI69/siyVJkoz8aQIAANgmi8hpateunbjMzs7Wev/ly5fp3LlztGjRIuW+nj17irylDRs2UPv27SkmJoauXr1KRUVFtHHjRvLy8qKIiPLgQJvCwkKxKWRlZYnLsrIysRkTH4+DE2Mft7qGtw+jT7fGUExSDu25lEL3NwogS2Zp9WdtUH+oP5x/1gvfX9PWn76/KxYRNFXl4sWL4rJhw4Zq+znhm4Mltm/fPtH65OLiIrrxtm7dSnaq64dUMG/ePJH/VFFKSgoVFBQYtfz8ofCUCPzB2dtbROMe9Y30o7UnU+jLnTHUxNuygxFLrD9rgvpD/eH8s174/pq2/iprrLHqoCkvL09cent7q+338fERCeTsqaeeEpuueJTdpEmT1FqauOUqMDBQ43WM8aFxAMfHtpQf/ed7eNCvp1JoX2wm5dp7iMV9LZUl1p81Qf2h/nD+WS98f01bf66urrYXNHl6eopLTuzmUXIKfDs0NLRax+QWKd44L4q30tLykWRcqab4YeYPzVTHro6GQV7Uo2kQbb+QTN8fvEEzB7YgS2Zp9WdtUH+oP5x/1gvfX9PVn76/KVbxCxQZGanWTce4qY275po3b27QsW19wV5dph9YezSOsgqKzV0cAAAAi2YVQVO9evWoY8eO9NVXXyn3cQJ4UlISDRs2zKBjcysTB2V8fLnp0sifmtT2pNyiUlpzRHOaBwAAALCwoOno0aNiUsv3339f3F66dKm4/c8//ygfwwHTrl276IEHHqAxY8bQ2LFjaebMmSLp2xBybmniJktFa9Oq/deotAzTDwAAAFh0TpObmxsFBweL6zwHU8VcJsVcTtwd98cff4hsd07iVqwzZ4iKOU1yM6RtGM3/+wLdzMinbeeT6OEW5Z8DAAAAWGDQxK1FurQY+fv7ixYmY+KWJt549ByPxpMbVycHGtWpLi3ZdYVW7o1F0AQAAGDJ3XNgXmPurUeO9nZ0KDadziVk4uMAAADQQvZBk5wTwRVCfNzokVYh4vqqfdfMXRwAAACLJPugSc6J4Kqe6lK+5MzGkwmUmvPf8jIAAABgpKApPz+fYmNj6fr162pruYF1aVe3FkWF+1JRaRn9dOiGuYsDAABgG0FTRkYGffzxx9SpUyexMC6vAceL4/L1bt260Zdffqlc3sTSoXtOs7Xp+4PXqajEstejAwAAsOigiWfh/uSTT0SAxIvj9u3blzZu3EiHDx+mgwcP0tq1a6lr1660aNEiEUitXLmSLB265/7Tt1UI1fZ2oZTsQvrjTIIZPxUAAAArn3KAF87ds2eP2Fq3bq31MYMGDaI5c+aIIOrDDz+kp59+2lhlBRNzcrCnsfdG0IItF+mbfddocFSYmAATAAAA9Gxp8vDwoN9++63SgEnVPffcIx5r6dA9p47nbHJxtKfTNzPp2PUMM30qAAAAlgej5zB6To2fh7OYJZxxaxMAAADoGTTxyDhe623ixIl05coV5X5eI+7ixYu6HgasgGI9ur/PJVL87XxzFwcAAMC6gqa5c+fS1q1bqVWrVvTEE0/Q6dOnxf69e/eK0XRgO5oGe1GXRv5iAd/vDqC1CQAAQK+gad++faKl6bnnnqPNmzeLFideQBds01P3lbc2/XzoBuUVlZi7OAAAANYTNDVu3FjZLRcYGEirVq2i0aNHU0pKClkzJIJr16NZENXzd6esghJafzy+hj8VAAAAKw6aZsyYQevWraOCggJxm+dhWrp0qbjt5ORE1gqJ4NrZ29vRk/eVT3a5fPcV2ncplW5lIr8JAADkS+egKTQ0VOQ0ubq6itulpaVi3qb4+Hhq3769KcsIZjKiQ7iYfuB6ej498fUh6vLBDlp9BEusAACAPFV7yoHi4mLq06ePcUsDFiW7oFhtOZUyiWj6+rNocQIAAFmqdtDELU681hy3NIFtik3NJanCvlJJomupeWYqEQAAgJVObsl5Tjz9wNGjRyk7O1vkNyk2ntcJrFv9AA+yr7CKioOdHUUEuJurSAAAANax9pyqnJwcMe0A69ixo9YlV/gxYL1CfNxo3tBWNGXdGXGbl6GbO7Sl2A8AACA31Q6a3N3dxcK9lXFwcCBrwFMO8MaJ7aBpZMe6dDLuNv18OI6GtQ0TtwEAAOSo2kGTvb093X///WTteMoB3rKyssjHx8fcxbFIner7iaDpWhpymQAAQL70ymkqKSmhS5cu6fz4c+fOVadMYGFahJYHk+dvZVEZD6EDAACQIb2Dpm7dutH48ePp0KFDWh/D3Vzbtm2jESNG0JAhQ4xVTjCjBgEeYr6m3KJSup6O1iYAAJAnR32nGeDWo9mzZ1OvXr3E7bZt21JQUBCVlZXRrVu36NixY2KG8AkTJoilVsD6OTrYU7NgLzp1M5OiE7LEqDoAAAC50XvKAT8/P1q4cCHdvHmTPvvsM2ratKmYGbyoqIiioqJEoMT3vffee2IEXU3jeaPatWtHy5cvr/HXtmWRd7roziVkmrsoAAAA1pUIzknTjz/+uNgsBbd2TZo0SbR+paWlmbs4NiUy1FtcnkvIMndRAAAArG9yS2PjCTG5lepuE2Pm5+dTenq61vvmzp1L//vf/ygkJMSEpZSnFneCpuhbCJoAAECeDAqaLl68KNaf8/X1JTs7O7XN09NT5+PExsbS66+/TnXr1qXw8HA6cOCAxmNyc3Np1KhRooWrTp061Lx5c7Vk9N27d4vX7dmzpyFvCSrRPNhbzA6ekl1IydkFqCcAAJCdanfPsccee0wEOStXriRvb2/1AzvqfujffvuNateuTVu2bBFda9q8/PLLIsmcAyxOPJ88eTL169ePLl++LIK2KVOmiC6577//nlJTU8U8Uhy4KWYtB8O4OTuIBPArKbkiGTyoqSuqFAAAZKXaQRNPP3D27Fnav38/ubkZtqwG5yEx7prThiee/OGHH2jp0qUUFhYm9s2ZM0cke69evZqee+45+vnnn8Wad4wT1HnGcg7qwLjzNXHQxHlN3ZsGoWoBAEBWqh00cUtSYGCgWKjX0KCpKidPnhSj87p06aLc5+XlRW3atKHDhw+LoCkiIkJ5n7+/v2hlCggIqPSYnDelmjvFgZkimZw3Y+LjSZJk9OPWtOYhXrTpFNG5+MwafS+2Un/mgvpD/eH8s174/pq2/vT9XTGoe+6dd96hsWPH0oIFC0TQwjlFCnzdWFMOpKSkiMuKQRDfVtyn6tVXXxXdc3czb948mjVrltbXUrRYGQt/KJmZmeKDq6pclizUrfzkOnMzg5KTk2vsdW2l/swF9Yf6w/lnvfD9NW39ccNPjQVNTZo0ob1791Lr1q017uOAKScnh4xB8Ua5S1BVcXGx6Iar6G4tTArTpk0T3YLcxccbz2TO+VHcelYxP8sYHxoHkXxsa/7Rv8/dh+i3SxR3u5DcffzI08Wg00d29WcuqD/UH84/64Xvr2nrjyfp1odBv3pPPfUU9e/fn55++mmNQMPBwYGMhUfLscTERJEwrpCUlFTtRYNdXFzExgnlvCkW7OVKNcUPM39opjp2TQn0dqNgb1dKzCqgmKQc6hDhV2OvbQv1Z06oP9Qfzj/rhe+v6epP398UgxLBExIS6NtvvxXBhylx7hIHNFu3bhXXGb/2mTNnaPr06QYde/HixWLjlibQbb4mDpo4GbwmgyYAAABzszckEZxbgIwx8zYvw8Ij57glSZFXxLcVydnOzs5iSgFemoWnJ+CpB8aMGUORkZEGLwr84osvUnR0NB05csTg9yGvmcGxnAoAAMiLQd1z48ePF8uozJ8/n+rXr6+RCM6j2HTxxx9/0GuvvSau85QCiuucc6SYjmDq1KlilB4HTpy4xSPpfvzxR7E4MNQczAwOAAByVe2giZO8Z8yYIa537tzZoETwESNGiO1uOAjjUXG8GRO65/Sfq4nFJOZQcWkZOTkgxwgAAOSh2kETj1o7ceJEpfcbMxHclLh7jjdFIjjcXZ1abuTl6kjZBSV0OTmHmocYd6QhAACAzQVNnHEeFRVF1g4tTfrhFr/IEG86FJsuksERNAEAgFwYNHrul19+qfR+zjUaOXIkWTq0NFUvGbw8aMqk4e3Lp4MAAACwddUOmnhZk9dff11jEileLJdn3mzQoIFVBE1Q/bwmXrgXAABALgzKaVJMEaCKg6bRo0eLUXXWAN1z+uPuORZ9K0sEyKqjJgEAAGyV0Yc+8RImn376KS1atIisAeZp0l/j2p7k7GAvksFvZuSb4FMBAACwPCYZL86tUHFxcaY4NFgAnmagSbCnuI5JLgEAQC6q3T3H+UvHjx/X2M8zhC9YsIDat29vaNnAwrvozsZniRF0fVqGmLs4AAAAlhs08dInHTt21DpqrmvXriJXyBogp8mQZPCbSAYHAADZqHbQ5OnpSRkZGWr7OCGY91vLxJYMUw4YugYdRtABAIA8GLT2nK+vr8Y+DqR4Zm2e/BJsF09qyYPmErMKKC2nkPw9XcxdJAAAAJMyKLI5evQovfPOO8rbTz75JPn5+VF4eDhFR0cbo3xgoTxdHCnC30M59QAAAICtMyhoeuWVV6hfv37i+rFjx2jjxo20bds2GjJkCL311lvGKiNY+HxN6KIDAAA5qHb3XGlpqViwt0OHDuL2li1bxAzgPXv2pGbNmlHnzp3JGiAR3LC8pj/O3EIyOAAAyEK1W5o42ZvzllJSUsTtP//8k3r06CGuFxQUkKurK1kDTG5pjGTwTKN9HgAAADaZCN6/f3965JFHqHnz5iKHqU+fPmI/d9H17t3bWGUEC9XiTtB0NTWX8opKyN3ZoNMJAADAdnOaVqxYIQInNzc3+uuvv8jb21uZIP72228bq4xgoYK8XCnQy4UkiehCYra5iwMAAGBSBjUN8JxM7733nsb+5cuXG3JYsLJk8H+zU0QyeLu6tcxdHAAAAJPBZEpglC66aExyCQAANk72QROPnouMjNS6JAzongwejWRwAACwcbIPmjB6zhhr0JXnNJWUlhnlpAQAALBEsg+awDD1/NzJw9mBCkvKxCg6AAAAW4WgCQw7geztxDp0DPM1AQCALUPQBAZDMjgAAMiBTQVNvLTL8ePH6erVq+YuikxnBsfCvQAAYLtsZgrnGzduiIWCeXmXuLg4GjBgAH311VfmLpasksGjb2WRJElkZ2dn7iIBAABYTktTSUkJffvtt3rfZyrp6en0888/0+HDh+nSpUviem4uEpNrQuPanuRob0e384opIbOgRl4TAADAaoImXpSXh+tXdt/EiRP1Ol5+fj6tWrWKpk6dWmn3GrcmffrppzR79mzavn272n1RUVHk7+9PW7dupSVLllDbtm3Jw8NDrzJA9bg4OlCjIE9x/Vw8Fu8FAADbZJKcpvj4eKpVS/clNbhVqmHDhrRhwwb68MMPRXBU0b59+8TCwHv27KGMjAwaMWIEvfrqq2qPiY2NpXnz5tGXX35JPXr0MMp7Af276AAAAGyR3jlN3CLUtWtXKisrE9c7dOigkYzNLUWPPvqozsds0aIFnTt3TnSnbdy4UetjXnjhBRo+fLiy269v37700EMP0dixY6ldu3aUl5cnyrJjxw5RBm55GjhwoLgPaiYZfN1xJIMDAIDt0jtocnR0FMFLUVGRCHT4uipnZ2dq0KAB9e/fX+djKgKvynKQLl++TGfOnKGFCxcq9/Xu3Zvq1KlDv/32mwiMvvjiC8rMzKR7771XPD4pKYnCwsIqfc3CwkKxKWRllbeQcDDImzHx8ThB2tjHtSSRwZ7KNehQf5ZFDuefKaH+UH84/2z3+1um599FvYMmJycnkXfEyd716tWjcePGkanFxMSIy0aNGqnt5y49xX2TJ0+mRYsW0fLlyykkJIS2bNlCtWvXrvSY3I03a9Ysjf0pKSkiJ8uY+EPhgI4/OHt7m5rlQSnQqVRcxt/Op0s3EsjH1XgDM+VQf6aE+kP94fyzXvj+mrb+srOz9TpetX/ZuMWpJgIm1RYob+/y+YAUfHx8lPfxVAOc41Qxz6ky06ZNo0mTJqm1NIWHh1NgYKDG6xjjQ+Nh+HxsW/3RDyKi8FoXKS4jn1KLXahxXX+jHVsO9WdKqD/UH84/64Xvr2nrz9XV1XRBEwco3Hrj6elJV65cuWtLDj8mMTFRr8Lc7ViMo0VfX1/l/tu3b4tWpepwcXER2+LFi8XGeVCMK9UUP8z8oZnq2JaUDM5B0/nEbOrSONCox5ZD/ZkS6g/1h/PPeuH7a7r60/c3Ra+giSOyH374QbQyKa5XemBH43XP8Kg5dvHiRdElyLipjedjMnSUHE+bwBu3NHHLFRiWDP73uUTMDA4AADZJr8iGu8AGDx4srnNOU1paGo0fP55MLSIiQiSLr1ixQoyYY5s2bRItWcOGDTPo2BVbmqD6sAYdAADYMkdD+glfeuklowRNx44do7Vr1yoTsnj5k7///pt69eolNrZs2TJxvWfPnlS3bl369ddf6e2336aWLVsa9NpoaTL+GnSXU3KooLiUXJ0cjHh0AAAAKw2aeGqB0NBQio6OpsjISIMKwcfiXCXeeFSbtgSt9u3bi5FymzdvFsEVBzsV54iqDrQ0GU+wtyv5eThTem4RxSRlU+s6/+WfAQAAyLql6dlnn6WhQ4eKFp+mTZuK6QhUu/JatWql07H4cbo8lrPfn376aTImtDQZN9mOu+j2XEoVeU0ImgAAwJZUO2jiGbh5viY2ZswYjft53becnBzDSgdWJzJEETRhDToAALAtjoZMA8ATQd6t1cEaoHvONHlNPDM4AACALTFoXoCAgACyduieM80IuvO3sqm0TCIHe+sIngEAAKpi0EyBPO3AnDlzRD6Tv7+/WiDCa7+B/NQP8CQ3JwfKLy6la2na1xIEAACQXdDEa7fxBJe8HInq4rc8DcDcuXPJWrrnePRfx44dzV0Um8AtS81CvMR1TgYHAACwFQYFTbw47oYNG2j06NFq+3mW7o0bN5I14FYxnjbhyJEj5i6KTSWDMySDAwCALal20FRcXEypqanUpEkTjaRvnl8JI+fki9egY0gGBwAAW1LtoInnZOLJLY8fP64RNK1Zs4ZatGhB1gDdc6YdQcdrBAIAAJDcu+def/11evTRR+nnn38Wk13+9ddfNHHiRJo+fbq4zxqge874mgV7idymtNwiSs7+L9cNAABAtlMOvPzyy6KVacaMGZSfn099+/YV68J98803NGDAAOOVEqwKrznXMNCDYpJyRF5Tbe//lsMBAACQZUsT40V74+PjxRQDvF2/fl0jMRxknAwejxF0AABgGwwOmhjnrXh7e4utoKBAbKpTEICMk8FvIWgCAADbYFDQdO7cOerevTu5u7uTm5ub2qY62aUlQyK4aZPBMVcTAADYCoNymkaNGiWmHFi3bp1oZVLl4OBA1gDLqJh2OZUb6XmUVVBM3q5OJnolAAAACw+aeAmV8+fP0+HDh8W8TACqfN2dKczXjeJv59P5hCzq3MA6Wh4BAACM3j3n6OhItWvXpoyMjOoeAmxcc+XM4MhrAgAAmec0zZ49W4yU4yVIUlJSxAzhii0tLc14pQSr7qJDMjgAAJDcc5p4RvBDhw5Rp06dNO7z8PDAUioyh2RwAACwJQYFTc8++ywNHTqUnnnmGatNBAfTtzRdTs6mopIycnY0ygwXAAAA1pcInpiYSCtWrCBnZ2eyVjzlAG+lpaXmLorN4URwHzcnyswvppikbGoZVj53EwAAgOwSwcPDwyk5OZmsGdaeMx1eYkcxMzgv3gsAACDLoIlnAX/yySdp5MiRtHv3boqLi6ObN28qt4SEBOOWFKy6i277hSS6lZlv7uIAAADUfPdcbm4uvfvuu+L6Aw88oHE/EsGB8cSWbMu5JNoanUTzhraikR3ronIAAEA+QRMHRTy5ZWXs7ZH0K3fcsvTrsZvK22US0fT1Z6lbk0AK8XEza9kAAABqLGjifJVmzZqRpSguLqYFCxbQ77//LqZCmDFjBrVp08bcxZK12NRcESipKpUkupaah6AJAACsjs00B3388ceUn58vLjlYGjhwoLmLJHv1AzzI3k69Gvh2RIC77OsGAABkNk+TsRUVFVF6ejr5+flVOo0BP6agoEBjXqjJkyeTk1P5orAtW7akzz//vEbKDJXjLjjOYeIuOW5hUgRSwd5YqxAAAKyPRbQ0Xb9+naZOnUp169alkJAQ2r9/v8Zj8vLyaMyYMeTl5UVBQUHUqlUrsXyLgiJg4lF9r732Gs2dO7dG3wNox0nfe6c+SJ+PiiInBzu6kpJL289b9zQVAAAgTxYRNK1Zs4Z8fHzozz//rPQxr776Kh04cIBiYmIoMzOTunbtSv369RPXVfOaxo0bR1FRUWK2crCcFqeBbcLoma4NxO25f56n4tIycxcLAADA+rrn3njjDXHJ8ztpk52dTd9++y0tWbKE6tWrJ/Z98MEHtHLlSlq9ejX973//E8HTo48+KlqjeBHhqhQWFopNISurfPLFsrIysRkTH49bwIx9XGvzfLf6tOZIHF1NzaUfDlyjcfdF6PQ81J9hUH+oP3PC+Yf6s+TzT9/fZYsImqpy8uRJkct0//33K/dxThMnfB8+fFgETe+//77o1ouPjxcBFeOWKe7O02bevHk0a9Ysjf0pKSkiZ8qY+EPhoI4/OLlPxfBM52D6cMcNWrgthrrUcSZv16pPQdSfYVB/qD9zwvmH+rPk848bZWwuaOJAhgUEBKjtDwwMVC7jwong3DVXcS6pykybNo0mTZqk1tLEy8LwMSsmmRvjQ+MpGvjYcg+axj8YQL+dTaeY5BxaczaLpvetetoK1J9hUH+oP3PC+Yf6s+Tzz9XV1faCJn7DikWCVfFtN7fySRKDg4PFpisXFxexVVywlyvVFIENvwdTHduaONvb0/R+zenJb47Qtweu0Zh761E9/8qDWwXUn2FQf6g/c8L5h/qz1PNP399kq/gFDwsLE5dJSUlq+/k2T2RpCCzYW/O6Nw0Ss4IXl0r0wV8XzFACAAAA/VlF0MS5S9xltnXrVuW+xMREOn36NHXr1s2gY3MrU2RkJHXs2NEIJQVdvdW3uZjo8q+ziXTkWjoqDgAALJ5FBE08kzcHQYrcJZ7gkm/n5OSI29yNxiPsONl78+bNdOrUKTFKjpdxGTp0qEGvjZYm82ga7EWPdSpfuPf936OprOJ6KwAAABbGIoKmTZs2ibmVHnnkEapduzZNmDBB3F62bJnyMW+99ZZyGzx4sHgctzwpJrWsLrQ0mc9rvZqQh7MDnbqZSZtOJZixJAAAAFWzk3gcHojRczzBJg9NNMXoOR7lxzOZyz0RvKLFOy/Tgi0XKdTHlXa83p1cnRw0HoP6MwzqD/VnTjj/UH+WfP7p+9uPX3Awq/H316cwXzdKyCygr/fG4tMAAACLJfugCd1z5sUtS2/2aSquL9l5mZKzjTuxKAAAgLHIPmhCIrj5DWwTSlHhvpRbVEqfbo0xd3EAAAC0kn3QBJYx8diM/s3F9dVH4uhCYvk6gAAAAJZE9kETuucsQ/t6ftSvVQjxzANz/jgv1gkCAACwJLIPmtA9Zzmm9GlGzg72tOdSKu2KKZ+zCwAAwFLIPmgCy1HX352e6hIhrnNrU0lpmbmLBAAAoISgCSzKhAcbUS13J7qcnEM/H4kzd3EAAACUZB80IafJsvi4OdFrvZuI6zySLqug2NxFAgAAEGQfNCGnyfKM6lSXGgZ6UHpuES3ZecXcxQEAABBkHzSB5XFysKe3+pVPQbBybyzFpeeZu0gAAAAImsAyPdg0iLo08qei0jKa/ft5OhaXTbcy881dLAAAkDG0NIHFTnj5Vt9IcX37hWR6cV0MdZ2/i1YfuWHuogEAgEzJPmhCIrjlquXhpHabJ76ctv4MWpwAAMAsZB80IRHccsWm5mrs48DpzbWn6eDVNMwaDgAANcqxZl8OQHf1AzzI3q48UFK153Kq2CL83WlEh3Aa3r4O1fZ2RdUCAIBJyb6lCSxXiI8bzRvaihzsym9zAPVi94Y0qlM4eTg70LW0PFqw5SLd98EOGr/qCG05l0jFmEUcAABMBC1NYNFGdqxL9zfyp5OXEyiqUSiF1fIQ+2f0j6Q/Tt+i1Ufi6Oj1DJEszluApwsNaxdGj3YMp4aBnuKxPOqOu/q45YoDMQAAgOpA0AQWjwMdh3AvClIJeNydHUXXHG+85Mrao3G07vhNSs0ppC93XxVbx4haFOHvIfZzFx+3VHHLFQdiAAAA+pJ90MSj53grLS3Vu/LAMjQK8qRpfZvT6w83pR0XkmnNkTjaeTGZjlzLEJsCB05T152h+Ix8igjwIH9PF/L3cCZ/T2fy83AmF0cHrcdHSxUAADDZB008eo63rKws8vHxwVlh5TOJP9wiWGxJWQX0yT8xtPqo+qK/nFP++Y7LWp/v5eKoDKAUARUfZ9fFFPE8tFQBAMib7IMmsE08mu7V3o1p7bE4tdF3nFPeO7I25RWVUlpuEaXlFIo17krKJMouLBEbJ5hrw8eZsu4MpWQX0qCoMAr3c6+5NwQAAGaHoAlsfvTd9PVnqVSSyMHOjuYObamR0yRJEmXll1BqbnkAxYEUB1QnbtymX4/d1DjuR//EiI27BR9sGiiWfOkQ4UfOjhiMCgBgyxA0gU3jAKlbk0C6lppHEQHuWkfP8ZItPu5OYmsY+N/+Hs2CaP2dJHLlY4moTR1fOpOQKRLQeVu+J1ZMgXB/4wARQHVvGkTBPv/NG4WcKAAA22AzQVN8fDwtWrRIXO/evTv16dPH3EUCC8GBUnWmGrhbS1VmfjHtvZQqEs4554lH7W05lyQ21jzEW7RClUkSfbX7qkGj9xB0AQBYBpsJmhwcHMjX15f27dsnbiNoAlO2VPm4OVG/1iFiKyuT6FxClgigeDsZd5vO38oSmyrF6L3j129TiK8rebs6kZerI3m73bl0dRLH5eterk7kYG8nFijm9fYwZQIAgPnZTNAUHBxMU6dOpYULF1JiYqK5iwMyaqmyt7ejVnV8xPZyz8YiL2p3TAqtORpH+6+kqT2We/oqjuirjJuTPeUXl2kEXRcSs8X8U4qRfjyhJ1/WcncWgZa2lqqTcdkU5eKlnBxUH2jpAgCwsKDp4MGDtGzZMrpw4QItWbKE2rVrp/GYdevW0XfffUfZ2dnUpUsXevPNN8nLy8ss5QWoDAcwg9uGUecGftTlgx0aOVGP31OXJIkoK7+YsgtKKKvgzuWd2/nF5XOGqQZMCnyob/Zd0/q6dnYkAicxZcKd+ac4gDt0NV08z45iaFTnumL0oIezI7k7O5CniyO5uzgob3N+lyq0dAEAWFjQ9NZbb9G2bdto6NCh9O2334o5kypavnw5vfTSSzR//nyqV68ezZw5k/7991+xVfxDD2BNo/cqKiopo+yCYrqSkkMjvzooAiwFPtMHR4VSQUkZpeUUUVpu+Ui/23nF4nEcJPGmbSYqPsxPh26ITRv+Grk7OZCHi6PYnBzsKCYpR6OlKzGzgOr5e5Cvu5MI0njz9XAS81xp+y4a2lKFli4AsBQWETRxi9GcOXPo5s2booutIp6t++233xb3vfzyy2JfixYtqHHjxvTnn39Sv379zFBqAOOM3quIpy4Qk2t6utAHOgZdJaVllJFXLIKo9JwiSs0tomPX0unbA9c1HsvlsCM7yi0sEfNV5RaViICLt1xxu5Qou1Br2Tjw+nTbJa33OdrbiUDKVwRS5ZcZXI7rGXdauohGdKhDPZvXFgGWp6ujaOniSy8XJ3J1sjdJSxeCLgCwqaCpqpm4z5w5Q8nJyTRgwADlvkaNGlFkZKRooeKgqaCgQLQ+HT16lHJzc0WA9cYbb5C/v7/WYxYWFopNQdG6VVZWJjZj4uPxXEDGPq5cWHv91fZyERvT9z2MaF9HLFh8PS2P6vmXB13ajsEBhb+Hk9goqHxf+7o+9P3B62rdgw52RD+O76QWvHEie0FJKeUWllJeUYm45EDqZkY+vb72tAh4FDik6d40kAqKy+h2fnkLV0ZekbjNE4SmcsCWU6T1vfBx1hy9KTZtOB+LgygPl/JuQxcHezqTkKXR0hWXnkdhvm7KgItbxfi6IhDj6R8cHcrnzOL8sbd+O6sMuuYMaUkjO4Tr9RnEZ+TRqRtZ1MbJk8JqYUJTuX1/zQ31Z9r60/e8tIigqSrXr5f/bzk0NFRtP99W3Mf/Q+XRc7169VIbUVeZefPm0axZszT2p6SkiADMmPhDyczMFB+cvT0mQET96YfP4gaeHOlnU3Jytl7Pm9qzHn2w/boyaJjSsx453OU4HEq5ORIFOBLVc3eiab3Un8/HG9gyQON53F2YVVBCmfmco1VKmQUldDohh345kazx2IharsRfA9GqVVgmLjmgKi2TxFQOvFWGH/fFzitVvncXRztyc7Sn2wX/rSnJ72Ha+rO07cxN8vNwIjdHB3JztheP41Yu7prkS07Ad3NyEJf7Ym/T0v0JohXO3u5Spe//bpKziyjudiGF+7pQkJczyQ3+/qH+LPn84xxpfdhJfCQLwd1z4eHhtHPnTjHXksKvv/5KI0aMoLS0NPLz81PuHzhwoKiIzZs36/1a2lqa+LUzMjLI29ubjP2hcTAWGBiIoAn1V+O4peT01QRq3SC0Wi0l3L2l2tKlz/O6zt+l0dK1+83uGi1dnPyeU1hCOQUl4pKXs+EWpbc3nNNo6erVPEh0V3KLWMXncD6YqYX4uIpuSNG6pehiVHQz8jQSKrePXsugr/fF3gm6qtfSxfWoT/eupcHfP9SfJZ9//Ntfq1YtEVjp8ttvFS1NikApPT1dLWjiIIrzmqrDxcVFbIsXLxYb500xrlRTtAZxS5ipji0HqL/q40DJKdybgmq5V+v842kKqjNVAT9HWyJ8xWNxkbwcHcjLTbMVhrvZ9Emk56CJc7U4iIpNyaVxqw6rJ9LbET3XrYHoCuR8rvw7OVz5RYr8rvLrHJApRjVWdCuzQGz6UrR0fbb9MgV7u1KAZ/l0Ebz5q1xX7Oc5u3jtRFuYpwvfX9SfpZ5/+v5NtIqgqU2bNqKr7ciRIyKXiXEX2unTp+nRRx816Ngvvvii2DjarCq3CgBMnwhvyPM5id7Z0ZlqeTiLBZV1TaSvrIWn4pQRHLgsG92eXJwc7rRwlQdWvFVs9Uq4nUeXk3M1jsujD3mrCrfKlaq8tiKni/PImoV4ixYvXq6nslGLxhq9CABWFjRxMvegQYPoo48+El1yHh4e9PHHH4uuuZEjRxp07IotTQBgGcvYGOP5hgRt/00ZcUYELxzEzB3aih5qEWxw0MW7eOkdnjZCcZmSU6i8znldqgGTAu+a99cFtX2c+M7BE5e3/NJVeXkqLpMW7biE0YcARmIROU1//PEHvffee1RUVEQnTpyg5s2bi77FZ555RmyM+ySHDBkiWpc4iOKWIZ7TqX///kYpg6KlSdd+TX37VHn0X1BQELrnUH81DuefYeIzcunk5QSKahSqdzclT5lQnZYu7mY8fyuTBi/ZrzFPF0+ayq1N3EV4t6T5ynRp6C9a4ZRdgV6KbkEXCvRyIW/X/1qujDHlgyH1ZwnzfJn7+ai/fIPqr6q/f/r+9ltE0MQB0ZUrmiNi6tSpIzZVV69eFdnuzZo1EzlJhlJtaYqJiUHQZIHwo4/6s+bzz5BE7qqCLp4iQtHdx0FUYhZf5ovbl5Nz6Fpant7ldXawF8EUr4nIS/ao4lDq2a71qZaHi5j8lOfm4rwzxWX5PntydLAT1/ddTqOVdxLhFflkPZrV1vq62noYt59Poi93X1U+/8XujahPy2Cyt7MTeWk8swQHeA53bvOSRnydPya+3HQqgd77PVoZ9M0e1JKGt68jns+37VQuK6t/Q4JGPP+GWevPZoMmS4CWJsuFoAn1J+fzr7pBV2Xdg2883IyKS8tEVyBvKdl8WUSp2YUiF0uuOG7i0IkDKkUMVaylj5S7QzlA40BL8RxxXRn4le/nUaE8W39FPAhAsUakeP6d1+Ij/He9fMLam7c1c9/q+bmJAFU10FNcUz0Wf8ZXUzVz6hoGepBTheerHkOhpKxMbUUAhabBnuSsMp2P6mHsKraWVgi6WWSIt8g9rAo/P7rCouccCO+d+qBe3wNjB01WkdNkSshpAgBLVt2cruos41NQXHonmCqii4nZNHWd5uSmA9qEkJODA5WWlVFxmSR+3EtKpQrXy0QXIneraJTL25XcnNXn0NP2P3ce2cgtZxXxbPMcNHBQwu+L5/dSXOd5Cst4nySpdWvqQsyKLxLu7/5EMWO+AbS9J31cT8836PlXUjQ/E31cTNQMpPRRMRDSB3+u/B8Icw5okH3QhNFzAGCr9E2Ed3VyoDq13MUWFe4rwhljjj7kY6x/8T6dfvQqe/6fr3TV6fk8evH+D3dqtLRtebUb1fZxJelOgKUIlMqXEvrvdlJmAQ1dul/j+T8/e4/IAyuPre48Txl0lQdufMkteE+tOqIWvPHzvxrbQeSPKTp5FHcrjqe4npZTSM//eFzj+V+Makt+nuWpKYr7ykv938H4gpdUeuWXkxrP/3RklFjUW1tsqLqL17CctEbz+QtGtBHPV32w4vVVH8sDGqasP63x/HlDW5c/vwr8+lMrPJ8/fz6PzUn2QRMAgC2zrNGHLXU+RmUtZbo+P9TXXevzG9f2Muj1OzfQvjSXNtqmvOjVvLaez1cfvdm3tfrKGHfDrXUVX39QVJjOzy8q0Xz+sHbqecZ3I2kNuvWZ3FXz+eaeNkP2OU1IBLd85s4psXaoP9SfORlj9JchM6Jb+/NRf/kG1R8SwU0EieCWCz/6qD+cf9YL31/UnzkZO2jCf9sBAAAAdICgCQAAAEAHsg+aOKcpMjKSOnbsqEt9AQAAgEzJPmjiKQeio6PFYsAAAAAAlcGUA3co5szgpDBTJKLx0i+urq4Y/YX6q3E4/1B/5oTzD/Vnyeef4jdf18VREDTdwZXKwsP1mUMCAAAAbCEG4FF0VZH9PE2q0WhCQgJ5eXlVunhjdXEky8FYXFycTkMaAfWH889y4PuL+sP5Z7vfX0mSRMAUGhqqU08QWpru4MqqU0f3mU6rgz8wBE2oP3PB+Yf6Myecf6g/Sz3/dGlhUpB9IjgAAACALhA0AQAAAOgAQVMNcHFxoXfffVdcAuqvpuH8Q/2ZE84/1J8tnX9IBAcAAADQAVqaAAAAAHSAoAkAAABABwiaAAAAAHSAeZpMLD8/X6xtx/NANGrUyNQvZzNKS0vpwIEDGvubNm1KgYGBZimTNUhPTxfnW5MmTSgoKEjrY5KSkujGjRtUv359CggIqPEyWjKe5O706dMUERFBYWFhGvV26dIljed06dLF6BPiWqv4+HhKS0ujBg0akKenp9bHZGZminoMDg42+dx41iYxMVFsXH8V5xTic/PUqVMaz4mKiqq0ruUmJyeHYmJixG9EZat7FBQUiL+RPJF148aN9X8RCUxm/fr1ko+Pj9SoUSNxed9990kpKSmocR1kZGTwQkBSmzZtpC5duii3LVu2oP60iImJkZ588kkpJCRE1Ns333yj8ZiysjJpwoQJkouLixQZGSkup0yZgvqUJOnGjRvS888/LwUHB0tOTk7SggULNOpl+fLlos5Uz0feCgsLZV+Hv//+u9S6dWspLCxMatWqleTu7i699dZbGvXy6aefSq6urlLz5s0lNzc3afjw4VJBQYHs62/Xrl1S586dpdq1a4u/eVw3L730klRaWqqsmwMHDojv9r333qt2/l24cEH29ZeSkiL+/vn7+0vt2rWTatWqJbVv3166dOmSWt1s3LhR3Me/yb6+vtI999wjJSUl6VV/CJpMJC4uTpz4n3zyibidnZ0tvgwjRoww1UvaZNB05MgRcxfFKvAfg6+//lrKy8uTHBwctAZNy5Ytk7y8vKSzZ8+K24cOHZKcnZ2l1atXS3K3fft2afHixVJWVpb44aosaKpXr55ZymfpFi1aJJ05c0Z5e+/eveLc+vHHH9X22dnZSX/88YfybyQHqTNmzJDkbsWKFdLhw4eVt0+fPi15enpKn332mUbQxL8loO7UqVPS2rVrlUFmfn6+1K1bN6lnz57KxyQkJIhgfv78+eJ2bm6uCLCGDBki6QNBk4nwB8MRbXFxsXLfqlWrJEdHRxEQgG5BE7fWHT16FHWmh8qCpk6dOon/janq37+/9PDDD+N0VHG3oCk8PFwEB+fOnUMLUxU6dOggvfDCC8rbTz/9tNinaurUqaJ1CjT16dNH7T/ZiqDp+PHj0okTJ6ScnBxU2128+eabUrNmzZS3uQHD29tb7Xv7ww8/iL+Xqampkq6QCG4iJ06coNatW5Oj439pY506daKSkhI6c+aMqV7W5jz33HP05JNPivycxx9/XORDgP74P0icD9G+fXu1/XxO8rkKurl58yYNHz6c+vXrR/7+/vT555+j6u6St6Sax8nnmbbzj/OgUlJSUI8qCgsLxe+EtjzYQYMG0WOPPUZ+fn40adIkkf8J5U6ePEm7du2ixYsX06pVq2jmzJlq51+rVq3I2dlZ7fzj+uM8Rl0hEdyECbn8R1WV4jbfB3fn5OREP/74owiU2OXLl6lnz5708ssv07fffovq01Nubq74Q6ztnMT5qBsehHDu3Dlq3ry5uP3TTz/R6NGjRUL9gAEDcE6qeP7550Vy8lNPPaXz30QM8PjP5MmTxSCiF198UbmPg6QdO3bQgw8+KG4fPHiQevXqJept2rRpOP+I6LPPPhPfUU4Gf+CBB8Sm6/mnK7Q0mfBHn7P0VfGXgKlGuqCdh4eHMmBi/D+uN954g9auXUtlZWWotmqcj0zbOYnzUTddu3ZVBkyMz89u3brRL7/8gvNRxWuvvUZ///03bd68mWrVqqV2DuJvYtXmzJlD33zzDa1fv15tBCePiFUETOyee+4RrfA4//7D9Xb48GHResm9On379jX6+YegyUTq1asnPjhVitt169Y11cvatNq1a4uTHC0j+uN1l7j+tJ2TOB8NOycr1qmc8X9suFtk69at1LZtW53+Jjo4OFBoaGgNl9QyffDBByJo4oBTtZWkMjj/Kv9P94QJE0SXHE/hYMzfZARNJtK7d2/RT3r9+nXlvo0bN4r/Oaj+bxUq706q6J9//hFzu1RsYgXdz0n+Y6zAffm///672A/6n5N5eXm0f/9+atmyJaqPiN58801avny5+J526NBB6/nHwZTq//b5byK31mExc6L58+fT7NmzxXe0R48eVZ5/jOsT5x9prRtO6eAWJJ6PSXH+cdfdlStX1M4//k3hXCddIafJRDjH4b777qMhQ4bQ22+/TVevXqVPPvmEvv76a7K3R6xalS+//JKOHDki6tHX11f8uPP/YFeuXImJBCtJvFUdYMBJuHv37hX/E1VM4MbnYceOHemZZ54RyaSck8Otdtw6IHccAB0/flxcLy4upmvXron64zySyMhIsX/YsGGi/jp37iz+SC9cuFB0AXCwIHf8Y//RRx/Rxx9/LHLnuO4Y/wdH8Z9EznNatmyZ+Jv4wgsv0J49e+ivv/6inTt3ktwtWbKEpkyZQrNmzRIBpKL+eFJkxQ86n2c8iSoHVPwb8v3339PRo0dF4CR38+bNEy1KDz30kKgz7qL78MMPxd82bnVi3FXHrXf8PZ4xY4Zo0FiwYIE4J/X5TbbjIXQmfC+yxjO48ofCM1vz7K7jxo2jgQMHmrtYVoP/F/Drr79SamoqNWzYkP73v/+JEYmgiZuhX3rpJY39/Idi+vTpytv8Py3+YeM/GFyn/IcYM9UTxcbG0pgxY7TO9s1/fBkHSkuXLqXdu3eLUbHc/cQDE/iPtNzxKFc+tyriVqS5c+cqb9+6dUt0QZ09e1b8D3/ixIl07733ktxxwLRv3z6N/fz3jgMqRcswD4LhfDFOU+BglL/zlc18LSeSJNGaNWto06ZNYkZ67m4bNWqUWg6Y4jvMv8lc19wCNXbsWBo8eLBer4WgCQAAAEAH6CcCAAAA0AGCJgAAAAAdIGgCAAAA0AGCJgAAAAAdIGgCAAAA0AGCJgAAAAAdIGgCAAAA0AGCJgCAajh58qSY1RoA5APLqACAbPDSPLz0iTFmof7hhx/owoUL1LVrV7OWAwBqDoImAJDVmoY5OTlmD1YspRwAoB8ETQBgEF5HjDfGiyvzAqNhYWGVPpZXGW/SpIlyIVd97j99+rRY/JrX2+K131QX2jx48KBY0JQX2OW1+Dgo4QU6FQt2Kp5bUFBAv/zyi9jHi58GBQVVeWzGz+N155ycnMT9uuCFf/k9BQYGUrt27cRzDSlHVe8RAEwLQRMAGIS7qDZs2CCu82KZ+/fvF6veT548WfmYzMxMevTRR0W3VOfOnenGjRuilWXFihU63Z+VlUXDhw8XrxUVFSUua9WqRZs3b1YGG1988QVFR0dTRkYGNW7cWByDg4rt27dT06ZNxYKyvFAxd4spyssLorq6ulZ57Js3b1L37t3FwqB8bH4dDgz9/f0rrZeZM2fSJ598IrrvuPxclvXr1xtUjqreIwCYmAQAYERHjhyRnJ2dpWvXrin3jRkzRoqMjJSSk5OV+zZs2KDz/U8//bQ0YMAAqaioSNwuKSmRBg0aJI0bN075mCeeeELiP2m7d+9WPqZfv37SQw89pHzM+PHjpZEjR6qVV5djjxo1SurWrZtUUFAgbp84cUJydHQUx9eGH8f379ixQ7nvwoUL0rlz5wwqhy7vEQBMBy1NAGAwbini0WTJyclUWlpKnp6edPz4capXr57ohlq9ejV99dVXoptKYdCgQeKyqvuLiorop59+oldeeYU2btwoWnt4q1OnjmiFUXXPPfcoE7MdHBxEaxd3fXH5fHx8NMqty7HLyspo3bp14nEuLi5iH7cEPfTQQ5XWB3epOTs705kzZ0T3Gd++W0uQKd8jABgPgiYAMMiaNWvo2WefFd1FnIfDgQUHARxAsaSkJHGb85S0qer+xMREEVhxDg/nCKnigERVRESE2u369euLS+4O4y6w6hybH8Pl03bsis9R4NwlHl3HAc37778vjjVq1CgaOnRojb9HADAeBE0AYJCJEyfSBx98QC+88IJyHyeEc0sJU7R+cL6TNlXd7+XlJS6fe+65SoMOBc710XY7ICCg2sf28/MTydeVHbsyQ4YMEVtMTAz9+eef9NRTT4ncqJdffrlG3yMAGA8mtwSAaisuLqb09HS1rqdt27aJriLVAKpTp0703XffqT03JSVFp/s5GZqTw3mYviIQU4iPj1e7vXfvXrXgixOvuSUmJCRE3OZuQ27RUdDl2Jyg3b59e2XSNsvNzaUtW7ZUWi95eXl0+/ZtcZ1b0F599VXq37+/GP1W3XLo+h4BwHTQ0gQA1cbdUH379qWXXnpJ5ONwV9uiRYvIzc1N7XGLFy+mnj17ijylfv36iVFfO3fupH379ul0/7Jly6hXr15i4xFm+fn5tHXrVmrWrBl9+umnytfhAIfze55//nkxbH/hwoUiV4hbiliHDh1EcLZ06VIRqPBjdTn2vHnz6JFHHhHXW7ZsSd98881d64WDRs474vfDj+f3w0HX999/b1A5dHmPAGA6dpwNbsLjA4CN41YVDnoU8xGNHj2aVq1aJVpWOABQiIuLo5UrV1JsbKwIBLg7TzVxuar7OSDj454/f168Tu/evdWSsfl1HR0d6fHHH6e//vpLtAaNHDlSBGMKnNTNAQ+3+GRnZ9M777wj5jyq6tiMp1LgQIcTvPmYPNSfW4HefPNNrfXC3Wb8WjzFAHfxDRs2TCRxG1IOXd4jAJgOgiYAsAmKgIKDDlslh/cIYMmQ0wQAAACgA+Q0AYBN4BnEKy59Ymvk8B4BLBm65wAAAAB0gP+yAAAAAOgAQRMAAACADhA0AQAAAOgAQRMAAACADhA0AQAAAOgAQRMAAACADhA0AQAAAOgAQRMAAACADhA0AQAAAFDV/g8kIVnRIgFiiwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 600x320 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 3.2))\n",
    "ax.semilogy(\n",
    "    [r[\"iteration\"] for r in history.records],\n",
    "    [r[\"value\"] for r in history.records],\n",
    "    marker=\"o\",\n",
    "    ms=3,\n",
    ")\n",
    "ax.set_xlabel(\"accepted step\")\n",
    "ax.set_ylabel(\"merit  sum(r$^2$)\")\n",
    "ax.set_title(\"Continuous Nd/Vd optimization\")\n",
    "ax.grid(alpha=0.3)\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ede0330e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:43.879103Z",
     "iopub.status.busy": "2026-11-04T17:43:43.878877Z",
     "iopub.status.idle": "2026-11-04T17:43:43.979781Z",
     "shell.execute_reply": "2026-11-04T17:43:43.979358Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " surface        Nd       Vd      dPgF\n",
      "       1   1.67717   66.964  -0.00094\n",
      "       3   1.55396   79.658  -0.00094\n",
      "       4   1.40000   53.568  -0.00094\n",
      "       7   1.40000   55.805  -0.00094\n",
      "       8   1.96385   77.774  -0.00094\n",
      "      10   1.40000   84.315  -0.00094\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 1000x400 with 1 Axes>,\n",
       " <Axes: title={'center': 'Continuous Nd/Vd optimum'}, xlabel='Z [mm]', ylabel='Y [mm]'>)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f\"{'surface':>8}{'Nd':>10}{'Vd':>9}{'dPgF':>10}\")\n",
    "for k in GLASS_SURFACES:\n",
    "    material = lens.surfaces[k].material_post\n",
    "    print(f\"{k:>8}{material.nd:>10.5f}{material.vd:>9.3f}{material.dPgf:>10.5f}\")\n",
    "\n",
    "lens.draw(title=\"Continuous Nd/Vd optimum\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "496393ec",
   "metadata": {},
   "source": [
    "## Step 2 - snapping back to real glass\n",
    "\n",
    "The optimum above is made of fictitious glasses. `find_closest_glass((Nd, Vd), catalog)` returns the name of the catalogue glass whose `(Nd, Vd)` is closest to the target, using the squared Euclidean distance in that plane.\n",
    "\n",
    "Two practical points:\n",
    "\n",
    "- The distance is **not normalised**: `Nd` spans roughly 0.3 index units while `Vd` spans roughly 70, so the metric is dominated by `Vd`. A model glass can therefore be matched to a real glass with a very different index - watch the `dist` column below.\n",
    "- `find_closest_glass` takes plain names, so we keep a name -> catalogue map and instantiate every replacement with `Material(name, catalog=...)` to avoid ambiguous matches between catalogues.\n",
    "\n",
    "The candidate list is restricted to Schott and Ohara glasses that transmit the full 0.4-0.7 um band."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f44b7a45",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:43.981103Z",
     "iopub.status.busy": "2026-11-04T17:43:43.980979Z",
     "iopub.status.idle": "2026-11-04T17:43:43.994188Z",
     "shell.execute_reply": "2026-11-04T17:43:43.993603Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "564 candidate glasses from ('schott', 'ohara')\n"
     ]
    }
   ],
   "source": [
    "catalogs = (\"schott\", \"ohara\")\n",
    "\n",
    "catalog_of = {}\n",
    "for catalog in catalogs:\n",
    "    for name in MaterialCatalog(catalog).list():\n",
    "        catalog_of.setdefault(name, catalog)\n",
    "\n",
    "candidates = glasses_selection(0.4, 0.7, catalogs=list(catalogs))\n",
    "print(f\"{len(candidates)} candidate glasses from {catalogs}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5e51a78b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:43.995371Z",
     "iopub.status.busy": "2026-11-04T17:43:43.995253Z",
     "iopub.status.idle": "2026-11-04T17:43:49.829797Z",
     "shell.execute_reply": "2026-11-04T17:43:49.829194Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "from optiland.materials import OptilandMaterialWarning\n",
    "\n",
    "# find_closest_glass and get_nd_vd resolve names without a catalogue, so\n",
    "# glasses present in several catalogues warn once each. The replacement\n",
    "# material itself uses the catalogue recorded in `catalog_of`.\n",
    "warnings.filterwarnings(\"ignore\", category=OptilandMaterialWarning)\n",
    "\n",
    "glass_map = {name: get_nd_vd(name) for name in candidates}\n",
    "# Glass entries without Nd/Vd in their data file come back as (0, 0); drop them.\n",
    "points = np.array([pair for pair in glass_map.values() if pair[0] > 0.0])\n",
    "model_points = np.array([nd_vd(lens.surfaces[k].material_post) for k in GLASS_SURFACES])\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(7, 4.5))\n",
    "ax.scatter(points[:, 1], points[:, 0], s=6, c=\"0.7\", label=\"catalogue glasses\")\n",
    "ax.scatter(\n",
    "    model_points[:, 1],\n",
    "    model_points[:, 0],\n",
    "    marker=\"x\",\n",
    "    s=70,\n",
    "    c=\"tab:orange\",\n",
    "    label=\"model glasses (optimum)\",\n",
    ")\n",
    "ax.invert_xaxis()\n",
    "ax.set_xlabel(\"$V_d$\")\n",
    "ax.set_ylabel(\"$n_d$\")\n",
    "ax.set_title(\"Where the optimizer wants to go\")\n",
    "ax.grid(alpha=0.3)\n",
    "ax.legend(loc=\"lower right\")\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2ef5fc4d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:43:49.831104Z",
     "iopub.status.busy": "2026-11-04T17:43:49.830964Z",
     "iopub.status.idle": "2026-11-04T17:44:22.412833Z",
     "shell.execute_reply": "2026-11-04T17:44:22.412350Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " surface  model Nd  model Vd         glass       Nd       Vd    dist\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       1   1.67717    66.964        N-BK10  1.49782   66.954   0.180\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       3   1.55396    79.658      S-FPL51Y  1.49700   81.138   1.482\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       4   1.40000    53.568          BAL5  1.54739   53.551   0.148\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       7   1.40000    55.805        N-BAK4  1.56883   55.976   0.240\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       8   1.96385    77.774        N-PK51  1.52855   76.976   0.910\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      10   1.40000    84.315        N-FK51  1.48656   84.468   0.176\n",
      "\n",
      "merit after snapping: 279.3\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    f\"{'surface':>8}{'model Nd':>10}{'model Vd':>10}\"\n",
    "    f\"{'glass':>14}{'Nd':>9}{'Vd':>9}{'dist':>8}\"\n",
    ")\n",
    "\n",
    "for surface_number in GLASS_SURFACES:\n",
    "    material = lens.surfaces[surface_number].material_post\n",
    "    nd, vd = material.nd, material.vd\n",
    "    glass = find_closest_glass((nd, vd), candidates)\n",
    "    replacement = Material(glass, catalog=catalog_of[glass])\n",
    "    new_nd, new_vd = nd_vd(replacement)\n",
    "    distance = ((nd - new_nd) ** 2 + (vd - new_vd) ** 2) ** 0.5\n",
    "    lens.updater.set_material(replacement, surface_number)\n",
    "    print(\n",
    "        f\"{surface_number:>8}{nd:>10.5f}{vd:>10.3f}\"\n",
    "        f\"{glass:>14}{new_nd:>9.5f}{new_vd:>9.3f}{distance:>8.3f}\"\n",
    "    )\n",
    "\n",
    "problem_real = make_problem(lens, optimize_glass=False)\n",
    "merit_snapped = problem_real.sum_squared()\n",
    "print(f\"\\nmerit after snapping: {merit_snapped:.1f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2420bf12",
   "metadata": {},
   "source": [
    "## Re-optimizing the geometry\n",
    "\n",
    "Substituting real glasses changes the optical power and the chromatic correction, so the merit function jumps. Only the radii and thicknesses are left as variables here; the glasses are now fixed catalogue materials."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9f7d511b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:44:22.415152Z",
     "iopub.status.busy": "2026-11-04T17:44:22.414893Z",
     "iopub.status.idle": "2026-11-04T17:44:27.203239Z",
     "shell.execute_reply": "2026-11-04T17:44:27.202799Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stop reason: `ftol` termination condition is satisfied.\n",
      "merit: 5.772\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 1000x400 with 1 Axes>,\n",
       " <Axes: title={'center': 'Real-glass design'}, xlabel='Z [mm]', ylabel='Y [mm]'>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_real = minimize(problem_real, \"dls\")\n",
    "\n",
    "merit_final = problem_real.sum_squared()\n",
    "print(f\"stop reason: {result_real.stop_reason}\")\n",
    "print(f\"merit: {merit_final:.3f}\")\n",
    "\n",
    "lens.draw(title=\"Real-glass design\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4e8a1f0",
   "metadata": {},
   "source": [
    "## Round-trip check: real glass back to model glass\n",
    "\n",
    "The snapped design uses catalogue glasses. Converting each glass surface back to a `ModelMaterial` with the same `Nd`, `Vd` and `dPgF` leaves the geometry untouched, so any RMS spot change measures the polynomial fit error rather than a design change. Two routes are compared on that same geometry: the visible route, selected automatically for the 0.5876 um primary, and the IR route, forced with `lambda_ref = 1.55 um` and `P_ref` evaluated at that wavelength. Both routes reproduce the d, F, C and g anchors, so both stay close to the catalogue design; the comparison quantifies the route choice rather than asserting which one must win. Deltas are percentages of the real-glass RMS, and fields are labelled by their normalized `Hy` coordinate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d1a7b3c9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:44:27.204522Z",
     "iopub.status.busy": "2026-11-04T17:44:27.204400Z",
     "iopub.status.idle": "2026-11-04T17:44:27.481624Z",
     "shell.execute_reply": "2026-11-04T17:44:27.480897Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Hy (norm)  wl [um]     real  visible       IR  dVis [%]   dIR [%]\n",
      "      -1.0   0.4861  93.5358  93.1786  93.4869     -0.38     -0.05\n",
      "      -1.0   0.5876  57.5568  57.5568  57.5568     -0.00     -0.00\n",
      "      -1.0   0.6563  48.4872  48.3715  48.4715     -0.24     -0.03\n",
      "      -0.7   0.4861  43.4028  43.1275  43.3653     -0.63     -0.09\n",
      "      -0.7   0.5876  36.9083  36.9084  36.9083     +0.00     +0.00\n",
      "      -0.7   0.6563  50.0156  50.3277  50.0583     +0.62     +0.09\n",
      "       0.0   0.4861  35.6091  35.9089  35.6497     +0.84     +0.11\n",
      "       0.0   0.5876  76.4849  76.4850  76.4850     +0.00     +0.00\n",
      "       0.0   0.6563  95.7910  96.1890  95.8451     +0.42     +0.06\n",
      "       0.7   0.4861  43.4028  43.1275  43.3653     -0.63     -0.09\n",
      "       0.7   0.5876  36.9083  36.9084  36.9083     +0.00     +0.00\n",
      "       0.7   0.6563  50.0156  50.3277  50.0583     +0.62     +0.09\n",
      "       1.0   0.4861  93.5358  93.1786  93.4869     -0.38     -0.05\n",
      "       1.0   0.5876  57.5568  57.5568  57.5568     -0.00     -0.00\n",
      "       1.0   0.6563  48.4872  48.3715  48.4715     -0.24     -0.03\n",
      "\n",
      "mean |delta|: visible 0.33 %, IR 0.05 %\n"
     ]
    }
   ],
   "source": [
    "from optiland.materials import ModelMaterial\n",
    "from optiland.optimization.operand.ray import RayOperand\n",
    "\n",
    "\n",
    "def rms_spots(lens):\n",
    "    \"\"\"RMS spot radius [um] per field, then per wavelength.\"\"\"\n",
    "    image_surface = lens.surfaces.num_surfaces - 1\n",
    "    values = []\n",
    "    for field in lens.fields.get_field_coords():\n",
    "        rows = []\n",
    "        for wavelength in lens.wavelengths:\n",
    "            rms = RayOperand.rms_spot_size(\n",
    "                lens,\n",
    "                image_surface,\n",
    "                field[0],\n",
    "                field[1],\n",
    "                16,\n",
    "                wavelength.value,\n",
    "                distribution=\"uniform\",\n",
    "            )\n",
    "            rows.append(float(np.ravel(be.to_numpy(rms))[0]) * 1e3)\n",
    "        values.append(rows)\n",
    "    return values\n",
    "\n",
    "\n",
    "# Keep the catalogue materials so both model routes start from the same glass.\n",
    "real_materials = {k: lens.surfaces[k].material_post for k in GLASS_SURFACES}\n",
    "rms_real = rms_spots(lens)\n",
    "\n",
    "# Visible route: selected automatically for the 0.5876 um primary wavelength.\n",
    "for surface_number in GLASS_SURFACES:\n",
    "    nd, _ = nd_vd(lens.surfaces[surface_number].material_post)\n",
    "    lens.updater.set_index(nd, surface_number)\n",
    "\n",
    "rms_visible = rms_spots(lens)\n",
    "\n",
    "# IR route: force lambda_ref = 1.55 um and evaluate P_ref at that wavelength.\n",
    "for surface_number in GLASS_SURFACES:\n",
    "    real = real_materials[surface_number]\n",
    "    nd = float(np.ravel(be.to_numpy(real.n(D_LINE)))[0])\n",
    "    vd = float(np.ravel(be.to_numpy(real.abbe()))[0])\n",
    "    dpgf = float(np.ravel(be.to_numpy(real.dPgF()))[0])\n",
    "    p_ref = float(np.ravel(be.to_numpy(real.P_ref(wavelength=1.55)))[0])\n",
    "    lens.updater.set_material(\n",
    "        ModelMaterial(\n",
    "            nd=nd, vd=vd, dPgF=dpgf, P_ref=p_ref, lambda_ref=1.55\n",
    "        ),\n",
    "        surface_number,\n",
    "    )\n",
    "\n",
    "rms_ir = rms_spots(lens)\n",
    "\n",
    "print(\n",
    "    f\"{'Hy (norm)':>10}{'wl [um]':>9}{'real':>9}{'visible':>9}{'IR':>9}\"\n",
    "    f\"{'dVis [%]':>10}{'dIR [%]':>10}\"\n",
    ")\n",
    "for i, field in enumerate(lens.fields.get_field_coords()):\n",
    "    for j, wavelength in enumerate(lens.wavelengths):\n",
    "        real = rms_real[i][j]\n",
    "        visible = rms_visible[i][j]\n",
    "        ir = rms_ir[i][j]\n",
    "        d_visible = 100.0 * (visible - real) / real\n",
    "        d_ir = 100.0 * (ir - real) / real\n",
    "        print(\n",
    "            f\"{field[1]:>10.1f}{wavelength.value:>9.4f}{real:>9.4f}\"\n",
    "            f\"{visible:>9.4f}{ir:>9.4f}{d_visible:>+10.2f}{d_ir:>+10.2f}\"\n",
    "        )\n",
    "\n",
    "rms_real = np.array(rms_real)\n",
    "rms_visible = np.array(rms_visible)\n",
    "rms_ir = np.array(rms_ir)\n",
    "mean_visible = float(np.mean(np.abs(100.0 * (rms_visible - rms_real) / rms_real)))\n",
    "mean_ir = float(np.mean(np.abs(100.0 * (rms_ir - rms_real) / rms_real)))\n",
    "print()\n",
    "print(f\"mean |delta|: visible {mean_visible:.2f} %, IR {mean_ir:.2f} %\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81142ad2",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "The two-stage workflow is a fast alternative to a categorical glass search: the continuous `Nd`/`Vd` optimum is found with a handful of damped-least-squares steps, and only the final snapping step touches the catalogue.\n",
    "\n",
    "Keep the following limitations in mind:\n",
    "\n",
    "- **The model glasses are fictitious.** Only `Nd` and `Vd` are free here; `dPgF` was frozen at the starting value, and the family of glasses the optimizer can reach is therefore narrower than the real glass map. Making `dPgF` a variable as well would require a partial-dispersion operand.\n",
    "- **`find_closest_glass` is an unweighted nearest neighbour.** Because `Vd` is numerically much larger than `Nd`, the match is essentially \"same Abbe number, any index\". If index accuracy matters more, restrict the candidate list, or build a custom weighted criterion (`get_neighbour_glasses` reserves `w_nd`/`w_vd` weights for this).\n",
    "- **Re-optimisation is mandatory.** Snapping alone can degrade the merit function by orders of magnitude; the final local optimisation recovers most of the performance.\n",
    "- **Tutorial 3e is the complementary tool.** `GlassExpert` searches the catalogue directly and can also explore glasses far from the continuous optimum, at the cost of many more merit-function evaluations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c9a693cb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-04T17:44:27.483132Z",
     "iopub.status.busy": "2026-11-04T17:44:27.482994Z",
     "iopub.status.idle": "2026-11-04T17:44:27.486553Z",
     "shell.execute_reply": "2026-11-04T17:44:27.485941Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stage                                    merit\n",
      "starting design                      3.925e+06\n",
      "continuous Nd/Vd optimum                 6.055\n",
      "after snapping to real glass             279.3\n",
      "after re-optimizing geometry             5.772\n"
     ]
    }
   ],
   "source": [
    "print(f\"{'stage':<32}{'merit':>14}\")\n",
    "print(f\"{'starting design':<32}{merit_start:>14.3e}\")\n",
    "print(f\"{'continuous Nd/Vd optimum':<32}{merit_continuous:>14.3f}\")\n",
    "print(f\"{'after snapping to real glass':<32}{merit_snapped:>14.1f}\")\n",
    "print(f\"{'after re-optimizing geometry':<32}{merit_final:>14.3f}\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_optiland",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.14.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
