{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f94e93e3",
   "metadata": {},
   "source": [
    "# Tutorial 01: Model-Based Spectral Calibration using LEAP\n",
    "This tutorial introduces a **model-based spectral calibration** approach using the [LEAP](https://github.com/LLNL/LEAP) projector. \n",
    "\n",
    "To run this notebook, you also need to download and install [spekpy](https://bitbucket.org/spekpy/spekpy_release/src/master/)\n",
    "\n",
    "In this tutorial, we will \n",
    "- simulate multi-energy dataset using LEAP projector\n",
    "  - simulate CT scans with specific source, filter, and detector configurations. \n",
    "  - scan multiple materials at different source voltages to generate multi-energy dataset. \n",
    "- model-based spectral calibration\n",
    "  - Step 0: Obtain sample masks and calculate forward matrix.\n",
    "  - Step 1: Configure Spectral Models including source, filters, and detector(scintillator).\n",
    "  - Step 2: Spectral Calibration."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e3f8bd2497841a6",
   "metadata": {},
   "source": [
    "## X-ray System Setup\n",
    "\n",
    "### Source\n",
    "- **Type**: Reflection\n",
    "- **Take-off Angle**: 13°\n",
    "- **Voltages Used for Scanning**:\n",
    "  - 50 kV\n",
    "  - 100 kV\n",
    "  - 150 kV\n",
    "\n",
    "### Filter\n",
    "- **Material**: Aluminum (Al)\n",
    "- **Thickness**: 3 mm\n",
    "\n",
    "### Detector\n",
    "- **Material**: Cesium Iodide (CsI)\n",
    "- **Thickness**: 0.33 mm\n",
    "\n",
    "### Samples\n",
    "- **Shapes**: Rods with 0.5 mm radius\n",
    "- **Materials**: \n",
    "  - Vanadium (V)\n",
    "  - Aluminum (Al)\n",
    "  - Titanium (Ti)\n",
    "  - Magnesium (Mg)\n",
    "- **Height**: 0.2 mm\n",
    "\n",
    "### CT Geometry\n",
    "- **Beam Type**: Cone Beam\n",
    "- **Source-to-Object Distance (SOD)**: 8 mm\n",
    "- **Source-to-Detector Distance (SDD)**: 15 mm\n",
    "- **Detector Specifications**:\n",
    "  - **Pixel Size**: 0.01 mm × 0.01 mm\n",
    "  - **Scan Shape**: 50 × 512 pixels\n",
    "- **Number of Views**: 64"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "59d7a864",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "max_simkV = 180 # keV\n",
    "takeoff_angle = 13 # degree\n",
    "voltage_list = [40, 80, 180] # keV\n",
    "mas_list = [0.01,0.01,0.01] # Milliampere-seconds\n",
    "\n",
    "fltr_mat = 'Al' # filter material\n",
    "fltr_th = 3 # filter thickness in mm\n",
    "\n",
    "det_mat = 'CsI' # scintillator material\n",
    "det_density = 4.51 # scintillator density g/cm^3\n",
    "det_th = 0.33 # scintillator thickness in mm\n",
    "\n",
    "sample_mats = ['V', 'Al', 'Ti', 'Mg']\n",
    "sample_radius = 0.5 # sample diameter in mm\n",
    "\n",
    "\n",
    "ct_info = {\n",
    "    \"Geometry\": \"Cone\",\n",
    "    \"SOD\": 8, # mm\n",
    "    \"SDD\": 15,# mm\n",
    "    \"psize\": [0.01875, 0.01875],  # Width and height in mm\n",
    "    \"rsize\": [0.01, 0.01],\n",
    "    \"shape\": [50, 512],     # Rows and columns\n",
    "    \"NViews\": 64\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36ee8975",
   "metadata": {},
   "source": [
    "## A. Simulate multi-energy dataset using LEAP projector"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa5bc309",
   "metadata": {},
   "source": [
    "### A01. Ground Truth Source Spectra\n",
    "In this tutorial,\n",
    "- use spekpy to generate X-ray source spectum.\n",
    "- the description of 2 used functions from spekpy is shown below by the help function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "64989bda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function __init__ in module spekpy.SpekPy:\n",
      "\n",
      "__init__(self, kvp=None, th=None, dk=None, mu_data_source=None, physics=None, x=None, y=None, z=None, mas=None, brem=None, char=None, obli=None, comment=None, targ=None, shift=None, init_default=True)\n",
      "    Constructor method for the Spek class \n",
      "    \n",
      "    SEE THE WIKI PAGES FOR MORE INFO:\n",
      "    https://bitbucket.org/spekpy/spekpy_release/wiki/Further_information\n",
      "    \n",
      "    :param float kvp: tube potential [kV] (default: depends on target)\n",
      "    :param float th: anode angle [degrees] (default: 12 degrees)\n",
      "    :param float dk: energy bin width [keV] (default: 0.5 keV)\n",
      "    :param string: mu_data_source (default: depends on physics model)\n",
      "        options: ('pene' or 'nist')\n",
      "    :param float physics: physics model (default: 'casim')\n",
      "        options: ('casim', 'kqp', 'spekpy-v1', 'spekcalc',\n",
      "                  'diff', 'uni', 'sim', 'classical')\n",
      "    :param float x: displacement from central axis in anode-cathode \n",
      "        direction [cm] (default: 0 cm)\n",
      "    :param float y: displacement from central axis in orthogonal \n",
      "        direction [cm] (default: 0 cm)\n",
      "    :param float z: focus-to-detector distance [cm] (default: 100 cm)\n",
      "    :param float mas: the tube current-time product [mAs] (default: 1 mAs)\n",
      "    :param logical brem: whether bremsstrahlung x rays requested \n",
      "        (default: true)\n",
      "    :param logical char: whether characteristic x rays requested\n",
      "        (default: true)\n",
      "    :param logical obli: whether increased oblique paths through filtration\n",
      "        are assumed for off axis positions (default: true)\n",
      "    :param string comment: any text annotation the user wishes to add\n",
      "    :param string targ: the anode target material (default: 'W')\n",
      "        options: ('W', 'Mo', or 'Rh')\n",
      "    :param float shift: optional fraction of an energy bin to shift the\n",
      "        energy bins (useful when matching to measurements) (default: 0.0)\n"
     ]
    }
   ],
   "source": [
    "import spekpy as sp\n",
    "help(sp.Spek.__init__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "75cfbcd3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function get_spectrum in module spekpy.SpekPy:\n",
      "\n",
      "get_spectrum(self, edges=False, flu=True, diff=True, sig=None, addend=False, **kwargs)\n",
      "    A method to get the energy and spectrum for the parameters in the \n",
      "    current spekpy state\n",
      "    \n",
      "    :param bool edges: Keyword argument to determine whether midbin or edge\n",
      "        of bins data are returned\n",
      "    :param bool addend: Keyword argument to determine whether a zero\n",
      "        end point is added to the spectrum\n",
      "    :param bool flu: Whether to return fluence or energy-fluence\n",
      "    :param bool diff: Whether to return spectrum differential in energy\n",
      "    :param kwargs: Keyword arguments to change parameters that are used for\n",
      "        the calculation\n",
      "    :return array k: Array with photon energies (mid-bin or edge values)\n",
      "        [keV]\n",
      "    :return array spk: Array with corresponding photon fluences \n",
      "        [Photons cm^-2 keV^-1], [Photons cm^-2] or [Photons cm^-2 keV^1]\n",
      "        depending of values of flu and diff inputs\n"
     ]
    }
   ],
   "source": [
    "help(sp.Spek.get_spectrum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "53d207ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x150b247daf50>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "max_simkV = max(voltage_list)\n",
    "takeoff_angle = 13\n",
    "\n",
    "# Define energy bins from 1.5 keV up to (max_simkV - 0.5) keV.\n",
    "energies = np.linspace(1.5, max_simkV - 0.5, max_simkV-1)\n",
    "\n",
    "# Initialize an empty list to store the generated source spectra.\n",
    "gt_src_spec_list = []\n",
    "\n",
    "for case_i, simkV in enumerate(voltage_list):\n",
    "    # Generate the X-ray spectrum model with Spekpy for each voltage.\n",
    "    # kvp is source voltage\n",
    "    # th is anode angle\n",
    "    # dk is energy bin size\n",
    "    # z is focus-to-detector distance [cm], use source-detector distance instead and convert mm to cm.\n",
    "    # mas is current-time product mA*s\n",
    "    # char=True requests characteristic x rays.\n",
    "    s = sp.Spek(kvp=simkV, th=takeoff_angle, dk=1, z=ct_info['SDD']/10, mas=mas_list[case_i], char=True)\n",
    "    \n",
    "    # Return data at the mid of a bin or the edges of a bin.\n",
    "    k, phi_k = s.get_spectrum(edges=False)  # Retrieve energy bins and fluence spectrum [Photons cm^-2 keV^-1]\n",
    "    \n",
    "    # Adjust the fluence for the detector pixel area.\n",
    "    phi_k = phi_k * ((ct_info['psize'][0] / 10) * (ct_info['psize'][1] / 10))  # Convert pixel size from cm² to mm²\n",
    "\n",
    "    # Initialize a zero-filled spectrum array with length max_simkV.\n",
    "    src_spec = np.zeros(max_simkV-1)\n",
    "    src_spec[:simkV-1] = phi_k  # Assign spectrum values starting from 1.5 keV\n",
    "\n",
    "    # Add the processed spectrum for this voltage to the list.\n",
    "    gt_src_spec_list.append(src_spec)\n",
    "\n",
    "# Convert the list of source spectra to a numpy array for easy handling.\n",
    "gt_src_spec_list = np.array(gt_src_spec_list)\n",
    "\n",
    "# Plot each generated source spectrum.\n",
    "for src_i, gt_src_spec in enumerate(gt_src_spec_list):\n",
    "    plt.plot(energies, gt_src_spec, label='%d kV' % voltage_list[src_i])\n",
    "\n",
    "plt.title('Ground Truth Source Spectra')\n",
    "plt.xlabel('Energy (keV)')\n",
    "plt.ylabel('Photons per pixel [$mm^{-2}$ $keV^{-1}$]')\n",
    "plt.grid()\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0068e00",
   "metadata": {},
   "source": [
    "#### A02. Ground Truth Filter Response\n",
    "Filter response is defined as\n",
    "$$\n",
    "f(E) = e^{-\\mu(m, E)\\cdot t} \n",
    "$$\n",
    "where $t$ is thickness; $\\mu$ is linear attenuation coefficient(LAC), which depends on photon energy and material $m$ formula and density."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "90edac07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from xcal import get_filter_response\n",
    "from xcal.chem_consts._periodictabledata import density\n",
    "\n",
    "# get_filter_response returns a ratio of passing through photons.\n",
    "# F(E) = e^(-\\mu_{mat}(E)*thickness) \n",
    "# \\mu_{mat}(E) = mac{mat}(E) * density\n",
    "# where \\mu denotes linear attenuation coefficient; mac means mass attenuation coefficient.\n",
    "gt_fltr = get_filter_response(energies, fltr_mat, density[fltr_mat], fltr_th)\n",
    "\n",
    "plt.plot(energies, gt_fltr, label='3mm Al')\n",
    "plt.title('Ground Truth Filter Response')\n",
    "plt.legend()\n",
    "plt.xlabel('Energy (keV)')\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "243da20d",
   "metadata": {},
   "source": [
    "### A03. Ground Truth Detector Response\n",
    "\n",
    "Converted energy from a X-ray photon with energy from 1 to 180 keV. \n",
    "\n",
    "Detector response is defined as\n",
    "$$\n",
    "D(E) =\\frac{\\mu_{en}(m, E)}{\\mu(m, E)} (1 - e^{-\\mu(m, E)\\cdot t} )\n",
    "$$\n",
    "where $t$ is scintillator thickness; $\\mu$ is linear attenuation coefficient(LAC), which depends on photon energy $E$ and material $m$ formula and density; $\\mu_en$ is linear energy-absorption coefficient(LAC)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d133bdd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from xcal import get_scintillator_response\n",
    "from xcal.chem_consts._periodictabledata import density\n",
    "\n",
    "# get_scintillator_response returns converted energy per photon at energy E.\n",
    "# D(E) = -\\mu_en/\\mu * (1-e^(-\\mu(E)*thickness))\n",
    "# \\mu(E) = mac(E) * density\n",
    "# \\mu_en(E) = mac_en(E) * density\n",
    "# where \\mu denotes linear attenuation coefficient; mac means mass attenuation coefficient.\n",
    "# where \\mu_en denotes linear energy-absorption coefficient; mac_en means mass energy-absorption coefficient.\n",
    "gt_det = get_scintillator_response(energies, det_mat, det_density, det_th)\n",
    "\n",
    "plt.plot(energies, gt_det, label='%.2fmm %s'%(det_th, det_mat))\n",
    "plt.title('Ground Truth Scintillator Response')\n",
    "plt.legend()\n",
    "plt.xlabel('Energy (keV)')\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0354506",
   "metadata": {},
   "source": [
    "### A04. Linear Attenuation Coefficients of homogenous samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f83936fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function get_lin_att_c_vs_E in module xcal.chem_consts._consts_from_table:\n",
      "\n",
      "get_lin_att_c_vs_E(density, formula, energy_vector)\n",
      "    Calculate the linear attenuation coefficient (mu) as a function of energy,\n",
      "    using mass attenuation coefficients from the NIST website:\n",
      "    https://physics.nist.gov/PhysRefData/XrayMassCoef/tab3.html.\n",
      "    \n",
      "    Author: Wenrui Li, Purdue University\n",
      "    Date: 04/12/2022\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    density : float\n",
      "        Density of the material in g/cm^3.\n",
      "    formula : str/dict\n",
      "        Chemical formula of the compound, either as a string or a dict.\n",
      "        For example, \"H2O\" and {\"H\": 2, \"O\": 1} are both acceptable.\n",
      "    energy_vector : list/numpy.ndarray\n",
      "        Energy (units: keV) list or 1D array for which beta values are calculated.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    numpy.ndarray\n",
      "        Linear attenuation coefficient values in mm^-1, with the same size as energy_vector.\n"
     ]
    }
   ],
   "source": [
    "from xcal.chem_consts import get_lin_att_c_vs_E\n",
    "help(get_lin_att_c_vs_E)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1cdc097c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x150a4f7e9030>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scanned Homogeneous Rods\n",
    "# Density for homogenous material is stored in the imported density dictionary\n",
    "mat_density = [density[formula] for formula in sample_mats]\n",
    "lac_vs_E_list = [get_lin_att_c_vs_E(den, formula, energies) for den, formula in zip(mat_density, sample_mats)]\n",
    "\n",
    "# Plot LAC\n",
    "for lac_vs_E,mat in zip(lac_vs_E_list, sample_mats):\n",
    "    plt.plot(energies, lac_vs_E, label=mat)\n",
    "plt.yscale('log')\n",
    "plt.title(r'Linear Attenuation Coefficient $\\mu$ ($mm^{-1}$)')\n",
    "plt.xlabel('Energy (keV)')\n",
    "plt.grid()\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48155589",
   "metadata": {},
   "source": [
    "### A05. GT X-ray System Spectral Responses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1ffded42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x150a4f366260>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gt_spec_list = [gt_source * gt_fltr  * gt_det for gt_source in gt_src_spec_list]\n",
    "for spec_i, gt_spec in enumerate(gt_spec_list):\n",
    "    plt.plot(energies, gt_spec/np.trapezoid(gt_spec,energies), label='%d kV'%voltage_list[spec_i])\n",
    "plt.legend()\n",
    "plt.title('Ground Truth: X-ray System Spectral Response')\n",
    "plt.xlabel('Energy (keV)')\n",
    "plt.grid()\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dba2a84",
   "metadata": {},
   "source": [
    "### A06. Masks for 4 homogenous samples\n",
    "\n",
    "Obtain a list of mask for each corresponding homogenous sample rod.\n",
    "These masks is then used to calculate the forward matrix for the transmission function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "24de231d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function __init__ in module xcal._utils:\n",
      "\n",
      "__init__(self, canvas_shape, pixel_size)\n",
      "    Initialize the Circle class.\n",
      "    \n",
      "    Parameters:\n",
      "    canvas_shape (tuple): The shape of the canvas, in pixels.\n",
      "    pixel_size (tuple): The size of a pixel, in the same units as the canvas.\n"
     ]
    }
   ],
   "source": [
    "from xcal._utils import Gen_Circle\n",
    "help(Gen_Circle.__init__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "49b3da10",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function generate_mask in module xcal._utils:\n",
      "\n",
      "generate_mask(self, radius, center=None)\n",
      "    Generate a binary mask for the circle.\n",
      "    \n",
      "    Parameters:\n",
      "    radius (int): The radius of the circle, in pixels.\n",
      "    center (tuple): The center of the circle.\n",
      "    \n",
      "    Returns:\n",
      "    ndarray: A 2D numpy array where points inside the circle are marked as True and points outside are marked as False.\n"
     ]
    }
   ],
   "source": [
    "help(Gen_Circle.generate_mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8eaa1f94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Phantom: 4 homogenous samples')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define parameters for 4 cylinders with 0.5mm radius, evenly distributed on a circle with a radius of 1.5mm.\n",
    "Radius = [sample_radius for _ in range(len(sample_mats))]  # Radius of each cylindrical cross-section in mm\n",
    "arrange_with_radius = 1.5  # Radius of the circle on which cylinder centers are distributed (in mm)\n",
    "\n",
    "# Calculate center positions for each cylinder, evenly spaced around the circular arrangement\n",
    "centers = [[np.sin(rad_angle) * arrange_with_radius, np.cos(rad_angle) * arrange_with_radius]\n",
    "           for rad_angle in np.linspace(-np.pi / 2, -np.pi / 2 + np.pi * 2, len(sample_mats), endpoint=False)]\n",
    "\n",
    "# Generate 3D masks for each cylinder\n",
    "# Obtain a list of mask for each corresponding homogenous sample rod. \n",
    "# These masks is then used to calculate the forward matrix for the transmission function.\n",
    "mask_list = []\n",
    "for mat_id, mat in enumerate(sample_mats):\n",
    "    # Initialize a circular mask generator for 2D slices\n",
    "    # Use the number of column pixels to define a canvas\n",
    "    circle = Gen_Circle((ct_info[\"shape\"][1], ct_info[\"shape\"][1]), \n",
    "                        (ct_info[\"rsize\"][0], ct_info[\"rsize\"][1])) # Image volume size\n",
    "    # Create a 3D mask array for the current cylinder by repeating the circular 2D mask across slices\n",
    "    mask_3d = np.array([circle.generate_mask(Radius[mat_id], centers[mat_id]) \n",
    "                        for i in range(ct_info[\"shape\"][0])])\n",
    "    mask_list.append(mask_3d)\n",
    "\n",
    "# Below just for display    \n",
    "# Initialize the phantom array to hold combined cylinder masks\n",
    "phantom = np.zeros(mask_list[0].shape)    \n",
    "\n",
    "# Combine all masks into the phantom, weighted by the linear attenuation coefficients for each material\n",
    "for mat_id, mat in enumerate(sample_mats):\n",
    "    phantom += mask_list[mat_id] * np.mean(lac_vs_E_list[mat_id])\n",
    "\n",
    "# Display a slice of the phantom (e.g., 26th slice) to show cross-sectional circles of cylinders\n",
    "plt.imshow(phantom[25], extent=[-2.56, 2.56, -2.56, 2.56], origin='lower')\n",
    "\n",
    "# Annotate each circle with its corresponding material name\n",
    "for mat_id, mat in enumerate(sample_mats):\n",
    "    plt.text(centers[mat_id][1], centers[mat_id][0], mat, fontsize=15, ha='right', color='red')\n",
    "plt.title('Phantom: 4 homogenous samples')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21371741",
   "metadata": {},
   "source": [
    "### A07. Setup forward projector with LEAP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "089fd7cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "from leapctype import *\n",
    "\n",
    "class fw_projector:\n",
    "    \"\"\"A class for forward projection using LEAP.\"\"\"\n",
    "\n",
    "    def __init__(self, numAngles, numRows, numCols, pixelHeight, pixelWidth, centerRow, centerCol, phis, sod, sdd):\n",
    "        \"\"\"\n",
    "        Initializes the forward projector with specified geometric parameters.\n",
    "        \"\"\"\n",
    "        # Initialize parameters as instance variables\n",
    "        self.numAngles = numAngles\n",
    "        self.numRows = numRows\n",
    "        self.numCols = numCols\n",
    "        self.pixelHeight = pixelHeight\n",
    "        self.pixelWidth = pixelWidth\n",
    "        self.centerRow = centerRow\n",
    "        self.centerCol = centerCol\n",
    "        self.phis = phis\n",
    "        self.sod = sod  # Source-to-object distance\n",
    "        self.sdd = sdd  # Source-to-detector distance\n",
    "        self.leapct = tomographicModels()\n",
    "        self.leapct.about()\n",
    "    def forward(self, mask):\n",
    "        \"\"\"\n",
    "        Computes the projection of a given mask.\n",
    "\n",
    "        Parameters:\n",
    "            mask (numpy.ndarray): 3D mask of the object to be projected. 1 for the region of object and 0 elsewhere.\n",
    "\n",
    "        Returns:\n",
    "            numpy.ndarray: The computed projection of the mask.\n",
    "        \"\"\"\n",
    "\n",
    "        self.leapct.set_conebeam(self.numAngles, \n",
    "                            self.numRows, \n",
    "                            self.numCols, \n",
    "                            self.pixelHeight, \n",
    "                            self.pixelWidth, \n",
    "                            self.centerRow, \n",
    "                            self.centerCol, \n",
    "                            self.phis, \n",
    "                            self.sod, \n",
    "                            self.sdd)\n",
    "        self.leapct.set_default_volume()\n",
    "        proj = self.leapct.allocate_projections() # shape is numAngles, numRows, numCols\n",
    "        volume = np.ascontiguousarray(mask.astype(np.float32), dtype=np.float32)\n",
    "        \n",
    "        # Obtain projection data\n",
    "        startTime = time.time()\n",
    "        self.leapct.project(proj,volume)\n",
    "        print('Forward Projection Elapsed Time: ' + str(time.time()-startTime))\n",
    "        return proj\n",
    "\n",
    "leapct2 = tomographicModels()\n",
    "projector =fw_projector(ct_info['NViews'], \n",
    "                        ct_info[\"shape\"][0], \n",
    "                        ct_info[\"shape\"][1], \n",
    "                        ct_info[\"psize\"][0], \n",
    "                        ct_info[\"psize\"][1], \n",
    "                        0.5*(ct_info[\"shape\"][0]-1), \n",
    "                        0.5*(ct_info[\"shape\"][1]-1), \n",
    "                        leapct2.setAngleArray(ct_info['NViews'], 360.0), \n",
    "                        ct_info[\"SOD\"], \n",
    "                        ct_info[\"SDD\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87231fe0",
   "metadata": {},
   "source": [
    "### A08. Calculate Attenuation Matrix \n",
    "We let $ \\mu_k(E) $ denote the LAC of the $k^\\text{th}$ homogeneous sample at energy $E$, and let $L_{k, i}$ denote the path length through the $k^{th}$ material at projection $i$ for samples $k=0, \\ldots, K-1$.\n",
    "The attenuation matrix is calculated as below,\n",
    "$$\n",
    "A_{i}(E) = \\exp \\left\\{-\\sum_{k=0}^{K-1} \\mu_k(E) L_{k, i}\\right\\}\n",
    "$$\n",
    "\n",
    "Notice that $L_{k, i}$ is calcuated by projecting $k^\\text{th}$ mask in mask_list with a projector defined in A07.\n",
    "One should create the “projector” object in a similar way defined in A07 if use CT projector other than LEAP."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ffc1d600",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forward Projection Elapsed Time: 0.1924912929534912\n",
      "Forward Projection Elapsed Time: 0.028488874435424805\n",
      "Forward Projection Elapsed Time: 0.027208566665649414\n",
      "Forward Projection Elapsed Time: 0.027233123779296875\n"
     ]
    }
   ],
   "source": [
    "from xcal import calc_forward_matrix\n",
    "spec_F = calc_forward_matrix(mask_list, lac_vs_E_list, projector)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfd7c60e",
   "metadata": {},
   "source": [
    "### A09. Simulate Transmission Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6ce8b4d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "trans_list = []\n",
    "for case_i, gt_spec in zip(np.arange(len(gt_spec_list)), gt_spec_list):\n",
    "    # Obtain the converted energy, which is proportional to the detected visible light photons by the camera.\n",
    "    # gt_spec is the converted energy without an object.\n",
    "    # Notice that, trapezoid does the energy integration.\n",
    "    trans = np.trapezoid(spec_F * gt_spec, energies, axis=-1) # Object scan\n",
    "    trans_0 = np.trapezoid(gt_spec, energies, axis=-1) # Air scan value\n",
    "    # Add poisson noise.\n",
    "    # The noise level can be adjusted by changing the mas, the current-time product in the beginning of this tutorial.\n",
    "    trans_noise = np.random.poisson(trans).astype(np.float32)\n",
    "    trans_noise /= trans_0\n",
    "\n",
    "    # Store noisy transmission data.\n",
    "    trans_list.append(trans_noise)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8181d136",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Simulated Transmission Data')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for case_i, gt_spec in enumerate(gt_spec_list):\n",
    "    plt.plot(trans_list[case_i][3, 25], label=f'{voltage_list[case_i]} keV')\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.title('Simulated Transmission Data')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d036739",
   "metadata": {},
   "source": [
    "## B. Spectral Calibration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b405b6bc",
   "metadata": {},
   "source": [
    "### B01. FBP Reconstruction using LEAP\n",
    "Reconstructing one CT scan using FBP/RWLS."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ba48ad8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RWLS iteration 1 of 20\n",
      "\tlambda = 0.541518\n",
      "RWLS iteration 2 of 20\n",
      "\tlambda = 0.3469472\n",
      "RWLS iteration 3 of 20\n",
      "\tlambda = 0.2867504\n",
      "RWLS iteration 4 of 20\n",
      "\tlambda = 0.2613304\n",
      "RWLS iteration 5 of 20\n",
      "\tlambda = 0.24231522\n",
      "RWLS iteration 6 of 20\n",
      "\tlambda = 0.2291172\n",
      "RWLS iteration 7 of 20\n",
      "\tlambda = 0.21515176\n",
      "RWLS iteration 8 of 20\n",
      "\tlambda = 0.20481074\n",
      "RWLS iteration 9 of 20\n",
      "\tlambda = 0.195452\n",
      "RWLS iteration 10 of 20\n",
      "\tlambda = 0.18794225\n",
      "RWLS iteration 11 of 20\n",
      "\tlambda = 0.18118744\n",
      "RWLS iteration 12 of 20\n",
      "\tlambda = 0.17525595\n",
      "RWLS iteration 13 of 20\n",
      "\tlambda = 0.16966107\n",
      "RWLS iteration 14 of 20\n",
      "\tlambda = 0.16442218\n",
      "RWLS iteration 15 of 20\n",
      "\tlambda = 0.15923582\n",
      "RWLS iteration 16 of 20\n",
      "\tlambda = 0.15322512\n",
      "RWLS iteration 17 of 20\n",
      "\tlambda = 0.14910358\n",
      "RWLS iteration 18 of 20\n",
      "\tlambda = 0.14532383\n",
      "RWLS iteration 19 of 20\n",
      "\tlambda = 0.14127181\n",
      "RWLS iteration 20 of 20\n",
      "\tlambda = 0.1381174\n",
      "Reconstruction Elapsed Time: 5.577737331390381\n"
     ]
    }
   ],
   "source": [
    "leapct = tomographicModels()\n",
    "leapct.about()\n",
    "\n",
    "leapct.set_conebeam(ct_info['NViews'], \n",
    "                    ct_info[\"shape\"][0], \n",
    "                    ct_info[\"shape\"][1], \n",
    "                    ct_info[\"psize\"][0], \n",
    "                    ct_info[\"psize\"][1], \n",
    "                    0.5*(ct_info[\"shape\"][0]-1), \n",
    "                    0.5*(ct_info[\"shape\"][1]-1), \n",
    "                    leapct.setAngleArray(ct_info['NViews'], 360.0), \n",
    "                    ct_info[\"SOD\"], \n",
    "                    ct_info[\"SDD\"])\n",
    "\n",
    "leapct.set_default_volume()\n",
    "# Reconstructing one CT scan using FBP/RWLS.\n",
    "sino = -np.log(trans_list[-1]).astype(np.float32)\n",
    "sino = np.ascontiguousarray(sino, dtype=np.float32) # shape is numAngles, numRows, numCols\n",
    "recon = leapct.allocate_volume() # shape is numZ, numY, numX\n",
    "recon[:] = 0.0\n",
    "\n",
    "startTime = time.time()\n",
    "#leapct.backproject(g,f)\n",
    "leapct.FBP(sino,recon)\n",
    "filters = filterSequence(1.0e0) # filter strength argument must be turned to your specific application\n",
    "filters.append(TV(leapct, delta=0.02/20.0)) # the delta argument must be turned to your specific application\n",
    "leapct.RWLS(sino,recon,20,filters,None,'SQS')\n",
    "print('Reconstruction Elapsed Time: ' + str(time.time()-startTime))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "404cf9f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50, 512, 512)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recon.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ee96af31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Reconstruction')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(recon[25])\n",
    "plt.colorbar()\n",
    "plt.title('Reconstruction')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3d5c0bb",
   "metadata": {},
   "source": [
    "### B02. Circle Detection (Optional)\n",
    "The circle detection provides a coarse bounding box for object segmentation.\n",
    "One can manually set the bounding box for the object segmentation, if the sample is not cylindrical.\n",
    "\n",
    "Below is an example to use detect_hough_circles to detect circles on the $25^{th}$ slice of the reconstruction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ec205d58",
   "metadata": {},
   "outputs": [],
   "source": [
    "from xcal.phantom import detect_hough_circles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fdc6e0a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function detect_hough_circles in module xcal.phantom:\n",
      "\n",
      "detect_hough_circles(phantom, radius_range=None, vmin=0, vmax=None, min_dist=100, HoughCircles_params1=300, HoughCircles_params2=1)\n",
      "    Detects circles in an image using the Hough Circle Transform.\n",
      "    \n",
      "    Args:\n",
      "        phantom (numpy.ndarray): The 2D image to detect circles in.\n",
      "        radius_range (list of int, optional): The minimum and maximum radius of\n",
      "            circles to detect. Defaults to a range based on the image size.\n",
      "        vmin (int, optional): Minimum value for clipping the image before\n",
      "            detection. Defaults to 0.\n",
      "        vmax (int, optional): Maximum value for clipping the image before\n",
      "            detection. If None, the 90th percentile of the image is used.\n",
      "            Defaults to None.\n",
      "        min_dist (int, optional): Minimum distance between the centers of the\n",
      "            detected circles. If too small, multiple neighbor circles may be\n",
      "            falsely detected in addition to a true one. If too large, some\n",
      "            circles may be missed. Defaults to 100.\n",
      "        HoughCircles_params1 (float, optional): Upper threshold for the internal edge detection.\n",
      "        HoughCircles_params2 (float, optional): Threshold for center detection, which influences the detection sensitivity. Large param2 leads to fewer detected circles. \n",
      "    \n",
      "    Returns:\n",
      "        numpy.ndarray: An array of detected circles, each represented by the\n",
      "            center coordinates (x, y) and radius. Returns an empty array if no\n",
      "            circles are detected.\n"
     ]
    }
   ],
   "source": [
    "help(detect_hough_circles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1e1a343b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import Circle\n",
    "import math\n",
    "\n",
    "plt.imshow(recon[25],origin='lower')\n",
    "plt.colorbar()\n",
    "# Get the current axes.\n",
    "ax = plt.gca()\n",
    "circles = detect_hough_circles(recon[25], \n",
    "                               radius_range=(45, 55), \n",
    "                               vmin=0.00, vmax=0.02, \n",
    "                               min_dist=200,\n",
    "                               HoughCircles_params2=10)\n",
    "\n",
    "# Below is for display and sort the detected circles.\n",
    "# x is horizontal axis, y is vertical axis. \n",
    "circles_values = np.array([np.mean(recon[25][int(y-r):int(y+r),int(x-r):int(x+r)]) for x,y,r in circles])\n",
    "# Sort `circles` based on the order in `circles_values`\n",
    "circles = [cir for _, cir in sorted(zip(circles_values, circles))]\n",
    "# Rearrange based on material ['V', 'Al', 'Ti', 'Mg'] \n",
    "circles = [circles[i] for i in [3,1,2,0]]\n",
    "\n",
    "# Create and add circles to the plot.\n",
    "for x, y, radius in circles:\n",
    "    circle = Circle((x, y), radius, color='red', fill=False)\n",
    "    ax.add_patch(circle)\n",
    "\n",
    "# Optionally set the aspect of the plot to be equal.\n",
    "# This makes sure that the circles are not skewed.\n",
    "ax.set_aspect('equal')\n",
    "plt.title('Circle Detection')\n",
    "# Show the plot with the circles.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26521115",
   "metadata": {},
   "source": [
    "### B03. Segment Object to get 3D Mask\n",
    "\n",
    "segment_object is a function to segment one sample from background."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0c31740e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from xcal.phantom import segment_object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "07799204",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function segment_object in module xcal.phantom:\n",
      "\n",
      "segment_object(phantom, vmin, vmax, canny_sigma, roi_radius=None, bbox=None)\n",
      "    Segments an object within a given region of interest (ROI) or bounding box in an image.\n",
      "    \n",
      "    This function creates a segmentation mask for an object in an image. The image values\n",
      "    are clipped and normalized based on provided minimum and maximum values. Canny edge\n",
      "    detection is then applied to the normalized image. The edges are filled to create a\n",
      "    binary mask that segments the object.\n",
      "    \n",
      "    Args:\n",
      "        phantom (np.array): The input image to segment.\n",
      "        vmin (float): The minimum value for clipping the image.\n",
      "        vmax (float): The maximum value for clipping the image.\n",
      "        canny_sigma (float): The standard deviation for the Gaussian filter used in\n",
      "                             Canny edge detection.\n",
      "        roi_radius (int, optional): The radius of the circular region of interest. If not\n",
      "                                    provided, it defaults to half the image size.\n",
      "        bbox (tuple of int, optional): The bounding box within which to perform segmentation,\n",
      "                                       specified as (r_min, c_min, r_max, c_max). If not\n",
      "                                       provided, the entire image is used.\n",
      "    \n",
      "    Returns:\n",
      "        np.array: A binary segmentation mask of the object.\n"
     ]
    }
   ],
   "source": [
    "help(segment_object)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ab237b24",
   "metadata": {},
   "outputs": [],
   "source": [
    "est_mask_list = []\n",
    "bbox_half_size = int(np.mean([cir[2] for cir in circles])*1.1)\n",
    "# Manually set the threshold based on above plot.\n",
    "vmin_list = [0.02,0.01,0.2,0.01]\n",
    "vmax_list = [0.7,0.02,0.4,0.02]\n",
    "# Loop through each slice to get 3D mask.\n",
    "for vi,cir in enumerate(circles):\n",
    "    xcenter, ycenter, r = cir\n",
    "    # Segment object with 3D mask\n",
    "    # Set different vmin and vmax for different samples.\n",
    "    # Set bbox to restrict a box region for object segmentation.\n",
    "    est_mask = [segment_object(\n",
    "        recon[i], \n",
    "        vmin_list[vi], \n",
    "        vmax_list[vi], \n",
    "        10, # Canny sigma in canny edge detection. Larger value is more possible to connect to a line.\n",
    "        roi_radius=None,\n",
    "        bbox=(\n",
    "            int(ycenter - bbox_half_size),\n",
    "            int(xcenter - bbox_half_size),\n",
    "            int(ycenter + bbox_half_size),\n",
    "            int(xcenter + bbox_half_size)\n",
    "        )) for i in range(len(recon))]\n",
    "    est_mask_list.append(np.array(est_mask))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "337e89ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 2, figsize=(8, 8))\n",
    "\n",
    "for j in range(len(est_mask_list)):\n",
    "    ax = axs.flat[j]\n",
    "    est_mask = est_mask_list[j]\n",
    "    gtmask = mask_list[j]\n",
    "    # Display the image or the difference image.\n",
    "#     ax.imshow(est_mask[25],origin='lower')\n",
    "    ax.imshow(est_mask[25].astype('float32')-gtmask[25].astype('float32'),vmin=-1,vmax=1,origin='lower')\n",
    "# Adjust the layout\n",
    "plt.tight_layout()\n",
    "plt.title('Difference between estimated masks and GT mask.')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "85d74d93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define colors for each mask\n",
    "colors = ['b', 'g', 'r', 'm']  # Blue, Green, Red, Magenta for each est_mask\n",
    "\n",
    "# Plot the 3D masks using a scatter plot with different colors\n",
    "fig = plt.figure(figsize=(8, 8))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "for i, est_mask in enumerate(est_mask_list):\n",
    "    # Get the coordinates of the points where the mask is 1\n",
    "    z, y, x = np.where(est_mask == 1)\n",
    "    ax.scatter(x, y, z, color=colors[i], marker='o', s=1, alpha=0.7, label=sample_mats[i])\n",
    "\n",
    "# Set labels and title\n",
    "ax.set_xlabel(\"X-axis\")\n",
    "ax.set_ylabel(\"Y-axis\")\n",
    "ax.set_zlabel(\"Z-axis\")\n",
    "ax.set_title(\"Estimated 3D Binary Mask Visualization with Different Colors\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b54317b",
   "metadata": {},
   "source": [
    "### B04. Calculate Forward Matrix with Estimated 3D Masks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "990d8753",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Only use 8 different views for spectral calibration\n",
    "NViews_For_MBSC = 8\n",
    "calib_angles = leapct.setAngleArray(ct_info['NViews'], 360.0)[::ct_info[\"NViews\"]//NViews_For_MBSC]\n",
    "calib_angles = np.ascontiguousarray(calib_angles.astype(np.float32), dtype=np.float32)\n",
    "projector2 =fw_projector(NViews_For_MBSC, \n",
    "                        ct_info[\"shape\"][0], \n",
    "                        ct_info[\"shape\"][1], \n",
    "                        ct_info[\"psize\"][0], \n",
    "                        ct_info[\"psize\"][1], \n",
    "                        0.5*(ct_info[\"shape\"][0]-1), \n",
    "                        0.5*(ct_info[\"shape\"][1]-1), \n",
    "                        calib_angles, \n",
    "                        ct_info[\"SOD\"], \n",
    "                        ct_info[\"SDD\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "76c388b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forward Projection Elapsed Time: 0.012677669525146484\n",
      "Forward Projection Elapsed Time: 0.011296510696411133\n",
      "Forward Projection Elapsed Time: 0.011538028717041016\n",
      "Forward Projection Elapsed Time: 0.011275291442871094\n"
     ]
    }
   ],
   "source": [
    "est_spec_F = calc_forward_matrix(est_mask_list, lac_vs_E_list, projector2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bf6938d",
   "metadata": {},
   "source": [
    "### B05. X-ray System Model Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9b600c60",
   "metadata": {},
   "outputs": [],
   "source": [
    "from xcal.models import Reflection_Source, Filter, Scintillator\n",
    "from xcal.defs import Material"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "309458e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use Spekpy to generate a source spectra dictionary.\n",
    "takeoff_angles = np.linspace(5,45,11)\n",
    "src_spec_list = []\n",
    "for case_i,simkV in enumerate(voltage_list):\n",
    "    for ta in takeoff_angles:\n",
    "        # Generate the X-ray spectrum model with Spekpy for each voltage.\n",
    "        s = sp.Spek(kvp=simkV, th=ta, dk=1, z=ct_info['SDD'], mas=mas_list[case_i], char=True)\n",
    "        k, phi_k = s.get_spectrum(edges=False)  # Retrieve energy bins and fluence spectrum [Photons cm^-2 keV^-1]\n",
    "\n",
    "        # Adjust the fluence for the detector pixel area.\n",
    "        phi_k = phi_k * ((ct_info['psize'][0] / 10) * (ct_info['psize'][1] / 10))  # Convert pixel size from mm² to cm²\n",
    "\n",
    "        # Initialize a zero-filled spectrum array with length max_simkV.\n",
    "        src_spec = np.zeros(max_simkV-1)\n",
    "        src_spec[:simkV-1] = phi_k  # Assign spectrum values starting from 1.5 keV\n",
    "\n",
    "        # Add the processed spectrum for this voltage to the list.\n",
    "        src_spec_list.append(src_spec)\n",
    "\n",
    "src_spec_list = np.array(src_spec_list)\n",
    "src_spec_list = src_spec_list.reshape((len(voltage_list),len(takeoff_angles),-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "061db0d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure the Reflection Source Model\n",
    "# Reflection_Source is a PyTorch module that supports gradient descent.\n",
    "# Reflection_Source initializes with specified source voltage and takeoff angle.\n",
    "# The set_src_spec_list method assigns a dictionary for each source configuration.\n",
    "# Reflection_Source.forward() provides interpolated dictionary components for each source.\n",
    "\n",
    "# Source voltage is set to be fixed by setting minbound and maxbound to None.\n",
    "# Takeoff angle is estimated in range [5,45] with inital value 25 degree.\n",
    "sources = [Reflection_Source(voltage=(voltage, None, None), takeoff_angle=(25, 5, 45), single_takeoff_angle=True)\n",
    "           for voltage in voltage_list]\n",
    "# Assigning the dictionaries for each source.\n",
    "for src_i, source in enumerate(sources):\n",
    "    source.set_src_spec_list(energies, src_spec_list, voltage_list, takeoff_angles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "855e2472",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Both the filter and scintillator contain discrete and continuous parameters.\n",
    "# All continuous parameters are defined using a tuple format with an initial value, minimum bound, and maximum bound.\n",
    "# Any other format is recognized as a discrete parameter.\n",
    "# Concatenating all component instances (sources, filters, scintillator) into a list, called spectral configuration like [source, filter_1, scintillator_1], \n",
    "# allows the Estimator defined in B07 to recognize all parameters, whether discrete or continuous for a scan.\n",
    "# The spec_models collects all spectral configuration. Each spectral configuration corresponding to a scan.\n",
    "# The Estimator will then automatically determine all possible combinations for the discrete parameters and optimize the continous parameters.\n",
    "\n",
    "\n",
    "# Configure Filter Model\n",
    "# Knowns: Use one filter for both scans.\n",
    "# Possible filter materials: Al and Cu.\n",
    "psb_fltr_mat = [Material(formula='Al', density=2.702), \n",
    "                Material(formula='Cu', density=8.92)]\n",
    "filter_1 = Filter(psb_fltr_mat, thickness=(5, 0, 10))\n",
    "\n",
    "# Configure Scintillator Model\n",
    "# Knowns: Use one scintillator for both scans.\n",
    "# Possible scintillator materials\n",
    "scint_params_list = [\n",
    "    {'formula': 'CsI', 'density': 4.51},\n",
    "    {'formula': 'Gd3Al2Ga3O12', 'density': 6.63},\n",
    "    {'formula': 'Lu3Al5O12', 'density': 6.73},\n",
    "    {'formula': 'CdWO4', 'density': 7.9},\n",
    "    {'formula': 'Y3Al5O12', 'density': 4.56},\n",
    "    {'formula': 'Bi4Ge3O12', 'density': 7.13},\n",
    "    {'formula': 'Gd2O2S', 'density': 7.32}\n",
    "]\n",
    "psb_scint_mat = [Material(formula=scint_p['formula'], density=scint_p['density']) for scint_p in scint_params_list]\n",
    "scintillator_1 = Scintillator(materials=psb_scint_mat, thickness=(0.25, 0.01, 0.5))\n",
    "\n",
    "# For each scan using a different source voltage, we define a different total spectral model.\n",
    "# Each spectral model is a list containing source, filters, and scintillator models. \n",
    "# Allow filter_1, ..., filter_n.\n",
    "spec_models = [[source, filter_1, scintillator_1] for source in sources]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22284e85",
   "metadata": {},
   "source": [
    "### B06. Spectral Calibration with Simulated Multi-Energy Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5f989693",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Measurement Shape: \n",
      " (8, 3, 512) (8, 3, 512) (8, 3, 512)\n",
      "Training Forward Matrix Shape: \n",
      " (8, 3, 512, 179) (8, 3, 512, 179) (8, 3, 512, 179)\n"
     ]
    }
   ],
   "source": [
    "# Build Training Set\n",
    "# Use first 8 views and center 2 slices.\n",
    "train_rads = [trans[::ct_info[\"NViews\"]//NViews_For_MBSC,10:-10:10] for trans in trans_list]\n",
    "\n",
    "# Assume a same forward matrix for different scans at different voltages.\n",
    "forward_matrices = [est_spec_F[:,10:-10:10] for i in range(len(voltage_list))]\n",
    "\n",
    "print(\"Training Measurement Shape: \\n\", train_rads[0].shape,train_rads[1].shape,train_rads[2].shape)\n",
    "print(\"Training Forward Matrix Shape: \\n\",forward_matrices[0].shape,forward_matrices[1].shape,forward_matrices[2].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8554f462",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of cases for different discrete parameters: 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-07 01:28:03,034  - Start Estimation.\n",
      "2025-05-07 01:28:03,295  - Initial cost: 1.587707e-03\n",
      "2025-05-07 01:28:05,063  - Iteration: 5\n",
      "2025-05-07 01:28:05,335  - Cost: 0.0006723980768583715\n",
      "2025-05-07 01:28:05,336  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:05,336  - Filter_2_thickness: 4.213513374328613\n",
      "2025-05-07 01:28:05,336  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:05,336  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:05,336  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:05,336  - Reflection_Source_takeoff_angle: 25.23719596862793\n",
      "2025-05-07 01:28:05,336  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:05,336  - Scintillator_2_thickness: 0.25396865606307983\n",
      "2025-05-07 01:28:05,336  - \n",
      "2025-05-07 01:28:06,458  - Iteration: 10\n",
      "2025-05-07 01:28:06,739  - Cost: 0.0005372301675379276\n",
      "2025-05-07 01:28:06,739  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:06,739  - Filter_2_thickness: 3.917762279510498\n",
      "2025-05-07 01:28:06,739  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:06,739  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:06,739  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:06,739  - Reflection_Source_takeoff_angle: 24.901470184326172\n",
      "2025-05-07 01:28:06,739  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:06,740  - Scintillator_2_thickness: 0.26431193947792053\n",
      "2025-05-07 01:28:06,740  - \n",
      "2025-05-07 01:28:07,843  - Iteration: 15\n",
      "2025-05-07 01:28:08,107  - Cost: 0.0004892278229817748\n",
      "2025-05-07 01:28:08,107  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:08,107  - Filter_2_thickness: 3.723284959793091\n",
      "2025-05-07 01:28:08,107  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:08,107  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:08,107  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:08,107  - Reflection_Source_takeoff_angle: 24.221975326538086\n",
      "2025-05-07 01:28:08,108  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:08,108  - Scintillator_2_thickness: 0.2807618975639343\n",
      "2025-05-07 01:28:08,108  - \n",
      "2025-05-07 01:28:09,133  - Iteration: 20\n",
      "2025-05-07 01:28:09,441  - Cost: 0.0004244772717356682\n",
      "2025-05-07 01:28:09,441  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:09,441  - Filter_2_thickness: 3.4932219982147217\n",
      "2025-05-07 01:28:09,441  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:09,441  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:09,441  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:09,442  - Reflection_Source_takeoff_angle: 22.232118606567383\n",
      "2025-05-07 01:28:09,442  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:09,442  - Scintillator_2_thickness: 0.3217521011829376\n",
      "2025-05-07 01:28:09,442  - \n",
      "2025-05-07 01:28:10,528  - Iteration: 25\n",
      "2025-05-07 01:28:10,788  - Cost: 0.00037808914203196764\n",
      "2025-05-07 01:28:10,788  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:10,788  - Filter_2_thickness: 3.3206706047058105\n",
      "2025-05-07 01:28:10,789  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:10,789  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:10,789  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:10,789  - Reflection_Source_takeoff_angle: 19.43391227722168\n",
      "2025-05-07 01:28:10,789  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:10,789  - Scintillator_2_thickness: 0.3617841303348541\n",
      "2025-05-07 01:28:10,789  - \n",
      "2025-05-07 01:28:11,846  - Iteration: 30\n",
      "2025-05-07 01:28:11,934  - Cost: 0.00037053183768875897\n",
      "2025-05-07 01:28:11,934  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:11,934  - Filter_2_thickness: 3.2547454833984375\n",
      "2025-05-07 01:28:11,934  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:11,934  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:11,935  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:11,935  - Reflection_Source_takeoff_angle: 18.24373435974121\n",
      "2025-05-07 01:28:11,935  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:11,935  - Scintillator_2_thickness: 0.37452903389930725\n",
      "2025-05-07 01:28:11,935  - \n",
      "2025-05-07 01:28:13,000  - Iteration: 35\n",
      "2025-05-07 01:28:13,259  - Cost: 0.0003688415454234928\n",
      "2025-05-07 01:28:13,260  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:13,260  - Filter_2_thickness: 3.212918281555176\n",
      "2025-05-07 01:28:13,260  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:13,260  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:13,260  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:13,260  - Reflection_Source_takeoff_angle: 17.559783935546875\n",
      "2025-05-07 01:28:13,260  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:13,260  - Scintillator_2_thickness: 0.38003554940223694\n",
      "2025-05-07 01:28:13,260  - \n",
      "2025-05-07 01:28:14,334  - Iteration: 40\n",
      "2025-05-07 01:28:14,596  - Cost: 0.00036846011062152684\n",
      "2025-05-07 01:28:14,597  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:14,597  - Filter_2_thickness: 3.189002513885498\n",
      "2025-05-07 01:28:14,597  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:14,597  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:14,597  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:14,597  - Reflection_Source_takeoff_angle: 17.103303909301758\n",
      "2025-05-07 01:28:14,597  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:14,597  - Scintillator_2_thickness: 0.3803960978984833\n",
      "2025-05-07 01:28:14,597  - \n",
      "2025-05-07 01:28:15,543  - Iteration: 45\n",
      "2025-05-07 01:28:15,967  - Cost: 0.00036830356111750007\n",
      "2025-05-07 01:28:15,967  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:15,967  - Filter_2_thickness: 3.1706764698028564\n",
      "2025-05-07 01:28:15,967  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:15,967  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:15,967  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:15,968  - Reflection_Source_takeoff_angle: 16.706764221191406\n",
      "2025-05-07 01:28:15,968  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:15,968  - Scintillator_2_thickness: 0.3783363997936249\n",
      "2025-05-07 01:28:15,968  - \n",
      "2025-05-07 01:28:16,964  - Iteration: 50\n",
      "2025-05-07 01:28:17,220  - Cost: 0.000368042616173625\n",
      "2025-05-07 01:28:17,221  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:17,221  - Filter_2_thickness: 3.1412482261657715\n",
      "2025-05-07 01:28:17,221  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:17,221  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:17,221  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:17,221  - Reflection_Source_takeoff_angle: 15.944174766540527\n",
      "2025-05-07 01:28:17,221  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:17,221  - Scintillator_2_thickness: 0.36924588680267334\n",
      "2025-05-07 01:28:17,221  - \n",
      "2025-05-07 01:28:18,165  - Iteration: 55\n",
      "2025-05-07 01:28:18,422  - Cost: 0.00036780975642614067\n",
      "2025-05-07 01:28:18,423  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:18,423  - Filter_2_thickness: 3.1230220794677734\n",
      "2025-05-07 01:28:18,423  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:18,423  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:18,423  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:18,423  - Reflection_Source_takeoff_angle: 15.295877456665039\n",
      "2025-05-07 01:28:18,423  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:18,424  - Scintillator_2_thickness: 0.3571985065937042\n",
      "2025-05-07 01:28:18,424  - \n",
      "2025-05-07 01:28:19,409  - Iteration: 60\n",
      "2025-05-07 01:28:19,775  - Cost: 0.00036774860927835107\n",
      "2025-05-07 01:28:19,775  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:19,776  - Filter_2_thickness: 3.1128337383270264\n",
      "2025-05-07 01:28:19,776  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:19,776  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:19,776  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:19,776  - Reflection_Source_takeoff_angle: 14.917986869812012\n",
      "2025-05-07 01:28:19,776  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:19,776  - Scintillator_2_thickness: 0.35052624344825745\n",
      "2025-05-07 01:28:19,776  - \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-07 01:28:20,831  - Iteration: 65\n",
      "2025-05-07 01:28:21,097  - Cost: 0.0003677362692542374\n",
      "2025-05-07 01:28:21,097  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:21,097  - Filter_2_thickness: 3.1076555252075195\n",
      "2025-05-07 01:28:21,097  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:21,097  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:21,097  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:21,097  - Reflection_Source_takeoff_angle: 14.74304485321045\n",
      "2025-05-07 01:28:21,097  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:21,097  - Scintillator_2_thickness: 0.3474627435207367\n",
      "2025-05-07 01:28:21,097  - \n",
      "2025-05-07 01:28:26,326  - Stopping at epoch 69 because updates are too small.\n",
      "2025-05-07 01:28:26,327  - Cost: 0.00036773463943973184\n",
      "2025-05-07 01:28:26,327  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:26,327  - Filter_2_thickness: 3.106395959854126\n",
      "2025-05-07 01:28:26,327  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:26,327  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:26,327  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:26,327  - Reflection_Source_takeoff_angle: 14.694992065429688\n",
      "2025-05-07 01:28:26,327  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:28:26,327  - Scintillator_2_thickness: 0.3465994596481323\n",
      "2025-05-07 01:28:26,327  - \n",
      "2025-05-07 01:28:26,344  - Start Estimation.\n",
      "2025-05-07 01:28:26,455  - Initial cost: 2.492245e-03\n",
      "2025-05-07 01:28:27,683  - Iteration: 5\n",
      "2025-05-07 01:28:27,987  - Cost: 0.0022279920522123575\n",
      "2025-05-07 01:28:27,987  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:27,988  - Filter_2_thickness: 4.5608134269714355\n",
      "2025-05-07 01:28:27,988  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:27,988  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:27,988  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:27,988  - Reflection_Source_takeoff_angle: 24.26715660095215\n",
      "2025-05-07 01:28:27,988  - Scintillator_2_material: Material(formula='Gd3Al2Ga3O12', density=6.63)\n",
      "2025-05-07 01:28:27,988  - Scintillator_2_thickness: 0.24550770223140717\n",
      "2025-05-07 01:28:27,988  - \n",
      "2025-05-07 01:28:29,093  - Iteration: 10\n",
      "2025-05-07 01:28:29,369  - Cost: 0.0020399701315909624\n",
      "2025-05-07 01:28:29,369  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:29,369  - Filter_2_thickness: 4.043423652648926\n",
      "2025-05-07 01:28:29,369  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:29,369  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:29,370  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:29,370  - Reflection_Source_takeoff_angle: 20.537090301513672\n",
      "2025-05-07 01:28:29,370  - Scintillator_2_material: Material(formula='Gd3Al2Ga3O12', density=6.63)\n",
      "2025-05-07 01:28:29,370  - Scintillator_2_thickness: 0.24091015756130219\n",
      "2025-05-07 01:28:29,370  - \n",
      "2025-05-07 01:28:36,547  - Stopping at epoch 12 because updates are too small.\n",
      "2025-05-07 01:28:36,547  - Cost: 0.0018955550622195005\n",
      "2025-05-07 01:28:36,547  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:36,547  - Filter_2_thickness: 3.614506959915161\n",
      "2025-05-07 01:28:36,547  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:36,547  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:36,547  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:36,547  - Reflection_Source_takeoff_angle: 16.471574783325195\n",
      "2025-05-07 01:28:36,548  - Scintillator_2_material: Material(formula='Gd3Al2Ga3O12', density=6.63)\n",
      "2025-05-07 01:28:36,548  - Scintillator_2_thickness: 0.23732063174247742\n",
      "2025-05-07 01:28:36,548  - \n",
      "2025-05-07 01:28:36,556  - Start Estimation.\n",
      "2025-05-07 01:28:36,626  - Initial cost: 3.077974e-03\n",
      "2025-05-07 01:28:37,763  - Iteration: 5\n",
      "2025-05-07 01:28:38,021  - Cost: 0.0028075443115085363\n",
      "2025-05-07 01:28:38,021  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:38,021  - Filter_2_thickness: 4.450414180755615\n",
      "2025-05-07 01:28:38,021  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:38,021  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:38,022  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:38,022  - Reflection_Source_takeoff_angle: 23.74559783935547\n",
      "2025-05-07 01:28:38,022  - Scintillator_2_material: Material(formula='Lu3Al5O12', density=6.73)\n",
      "2025-05-07 01:28:38,022  - Scintillator_2_thickness: 0.2595919072628021\n",
      "2025-05-07 01:28:38,022  - \n",
      "2025-05-07 01:28:39,071  - Iteration: 10\n",
      "2025-05-07 01:28:39,313  - Cost: 0.002328362548723817\n",
      "2025-05-07 01:28:39,313  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:39,313  - Filter_2_thickness: 3.1984691619873047\n",
      "2025-05-07 01:28:39,313  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:39,313  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:39,313  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:39,313  - Reflection_Source_takeoff_angle: 16.630538940429688\n",
      "2025-05-07 01:28:39,313  - Scintillator_2_material: Material(formula='Lu3Al5O12', density=6.73)\n",
      "2025-05-07 01:28:39,314  - Scintillator_2_thickness: 0.31992319226264954\n",
      "2025-05-07 01:28:39,314  - \n",
      "2025-05-07 01:28:44,460  - Stopping at epoch 13 because updates are too small.\n",
      "2025-05-07 01:28:44,460  - Cost: 0.0020117536187171936\n",
      "2025-05-07 01:28:44,460  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:44,460  - Filter_2_thickness: 2.4119725227355957\n",
      "2025-05-07 01:28:44,460  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:44,460  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:44,461  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:44,461  - Reflection_Source_takeoff_angle: 10.766779899597168\n",
      "2025-05-07 01:28:44,461  - Scintillator_2_material: Material(formula='Lu3Al5O12', density=6.73)\n",
      "2025-05-07 01:28:44,461  - Scintillator_2_thickness: 0.36598074436187744\n",
      "2025-05-07 01:28:44,461  - \n",
      "2025-05-07 01:28:44,468  - Start Estimation.\n",
      "2025-05-07 01:28:44,584  - Initial cost: 3.022571e-03\n",
      "2025-05-07 01:28:45,723  - Iteration: 5\n",
      "2025-05-07 01:28:45,972  - Cost: 0.0013409802922978997\n",
      "2025-05-07 01:28:45,973  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:45,973  - Filter_2_thickness: 3.805534601211548\n",
      "2025-05-07 01:28:45,973  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:45,973  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:45,973  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:45,973  - Reflection_Source_takeoff_angle: 24.96942710876465\n",
      "2025-05-07 01:28:45,973  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:45,973  - Scintillator_2_thickness: 0.2639610469341278\n",
      "2025-05-07 01:28:45,973  - \n",
      "2025-05-07 01:28:47,032  - Iteration: 10\n",
      "2025-05-07 01:28:47,275  - Cost: 0.0009760453831404448\n",
      "2025-05-07 01:28:47,276  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:47,276  - Filter_2_thickness: 3.228907823562622\n",
      "2025-05-07 01:28:47,276  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:47,276  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:47,276  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:47,276  - Reflection_Source_takeoff_angle: 23.93007469177246\n",
      "2025-05-07 01:28:47,276  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:47,276  - Scintillator_2_thickness: 0.29830750823020935\n",
      "2025-05-07 01:28:47,276  - \n",
      "2025-05-07 01:28:48,355  - Iteration: 15\n",
      "2025-05-07 01:28:48,624  - Cost: 0.0007440934423357248\n",
      "2025-05-07 01:28:48,624  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:48,624  - Filter_2_thickness: 2.812162399291992\n",
      "2025-05-07 01:28:48,624  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:48,624  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:48,625  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:48,625  - Reflection_Source_takeoff_angle: 21.70795249938965\n",
      "2025-05-07 01:28:48,625  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:48,625  - Scintillator_2_thickness: 0.35040944814682007\n",
      "2025-05-07 01:28:48,625  - \n",
      "2025-05-07 01:28:49,706  - Iteration: 20\n",
      "2025-05-07 01:28:49,955  - Cost: 0.0004922390799038112\n",
      "2025-05-07 01:28:49,956  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:49,956  - Filter_2_thickness: 2.4898428916931152\n",
      "2025-05-07 01:28:49,956  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:49,956  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:49,956  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:49,956  - Reflection_Source_takeoff_angle: 16.514972686767578\n",
      "2025-05-07 01:28:49,956  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:49,956  - Scintillator_2_thickness: 0.4168078303337097\n",
      "2025-05-07 01:28:49,956  - \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-07 01:28:50,954  - Iteration: 25\n",
      "2025-05-07 01:28:51,034  - Cost: 0.0004464127996470779\n",
      "2025-05-07 01:28:51,035  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:51,035  - Filter_2_thickness: 2.3622331619262695\n",
      "2025-05-07 01:28:51,035  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:51,035  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:51,035  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:51,035  - Reflection_Source_takeoff_angle: 14.109383583068848\n",
      "2025-05-07 01:28:51,035  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:51,035  - Scintillator_2_thickness: 0.4380587935447693\n",
      "2025-05-07 01:28:51,035  - \n",
      "2025-05-07 01:28:52,155  - Iteration: 30\n",
      "2025-05-07 01:28:52,435  - Cost: 0.00043726476724259555\n",
      "2025-05-07 01:28:52,436  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:52,436  - Filter_2_thickness: 2.3069417476654053\n",
      "2025-05-07 01:28:52,436  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:52,436  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:52,436  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:52,436  - Reflection_Source_takeoff_angle: 13.096059799194336\n",
      "2025-05-07 01:28:52,436  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:52,436  - Scintillator_2_thickness: 0.448375403881073\n",
      "2025-05-07 01:28:52,436  - \n",
      "2025-05-07 01:28:53,529  - Iteration: 35\n",
      "2025-05-07 01:28:53,780  - Cost: 0.00043515473953448236\n",
      "2025-05-07 01:28:53,781  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:53,781  - Filter_2_thickness: 2.2871174812316895\n",
      "2025-05-07 01:28:53,781  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:53,781  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:53,781  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:53,781  - Reflection_Source_takeoff_angle: 12.802369117736816\n",
      "2025-05-07 01:28:53,781  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:53,781  - Scintillator_2_thickness: 0.4561339318752289\n",
      "2025-05-07 01:28:53,781  - \n",
      "2025-05-07 01:28:54,669  - Iteration: 40\n",
      "2025-05-07 01:28:54,943  - Cost: 0.00043402143637649715\n",
      "2025-05-07 01:28:54,943  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:54,944  - Filter_2_thickness: 2.2812235355377197\n",
      "2025-05-07 01:28:54,944  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:54,944  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:54,944  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:54,944  - Reflection_Source_takeoff_angle: 12.808342933654785\n",
      "2025-05-07 01:28:54,944  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:54,944  - Scintillator_2_thickness: 0.46502411365509033\n",
      "2025-05-07 01:28:54,944  - \n",
      "2025-05-07 01:28:56,019  - Iteration: 45\n",
      "2025-05-07 01:28:56,261  - Cost: 0.00043026055209338665\n",
      "2025-05-07 01:28:56,261  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:28:56,261  - Filter_2_thickness: 2.299126625061035\n",
      "2025-05-07 01:28:56,261  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:28:56,261  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:28:56,261  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:28:56,261  - Reflection_Source_takeoff_angle: 13.916543960571289\n",
      "2025-05-07 01:28:56,261  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:28:56,262  - Scintillator_2_thickness: 0.49995315074920654\n",
      "2025-05-07 01:28:56,262  - \n",
      "2025-05-07 01:29:01,141  - Stopping at epoch 46 because updates are too small.\n",
      "2025-05-07 01:29:01,141  - Cost: 0.00043026095954701304\n",
      "2025-05-07 01:29:01,141  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:01,141  - Filter_2_thickness: 2.299126625061035\n",
      "2025-05-07 01:29:01,141  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:01,141  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:01,141  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:01,142  - Reflection_Source_takeoff_angle: 13.91654109954834\n",
      "2025-05-07 01:29:01,142  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:29:01,142  - Scintillator_2_thickness: 0.49995318055152893\n",
      "2025-05-07 01:29:01,142  - \n",
      "2025-05-07 01:29:01,150  - Start Estimation.\n",
      "2025-05-07 01:29:01,219  - Initial cost: 5.902383e-03\n",
      "2025-05-07 01:29:02,280  - Iteration: 5\n",
      "2025-05-07 01:29:02,515  - Cost: 0.0054838890209794044\n",
      "2025-05-07 01:29:02,515  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:02,515  - Filter_2_thickness: 5.216713905334473\n",
      "2025-05-07 01:29:02,515  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:02,515  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:02,515  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:02,515  - Reflection_Source_takeoff_angle: 22.25094223022461\n",
      "2025-05-07 01:29:02,516  - Scintillator_2_material: Material(formula='Y3Al5O12', density=4.56)\n",
      "2025-05-07 01:29:02,516  - Scintillator_2_thickness: 0.27568092942237854\n",
      "2025-05-07 01:29:02,516  - \n",
      "2025-05-07 01:29:03,510  - Iteration: 10\n",
      "2025-05-07 01:29:03,782  - Cost: 0.004397060256451368\n",
      "2025-05-07 01:29:03,782  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:03,783  - Filter_2_thickness: 4.727838516235352\n",
      "2025-05-07 01:29:03,783  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:03,783  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:03,783  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:03,783  - Reflection_Source_takeoff_angle: 8.110776901245117\n",
      "2025-05-07 01:29:03,783  - Scintillator_2_material: Material(formula='Y3Al5O12', density=4.56)\n",
      "2025-05-07 01:29:03,783  - Scintillator_2_thickness: 0.3944402039051056\n",
      "2025-05-07 01:29:03,783  - \n",
      "2025-05-07 01:29:09,231  - Stopping at epoch 13 because updates are too small.\n",
      "2025-05-07 01:29:09,231  - Cost: 0.00410512974485755\n",
      "2025-05-07 01:29:09,231  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:09,231  - Filter_2_thickness: 4.393474578857422\n",
      "2025-05-07 01:29:09,231  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:09,231  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:09,231  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:09,231  - Reflection_Source_takeoff_angle: 5.157588481903076\n",
      "2025-05-07 01:29:09,231  - Scintillator_2_material: Material(formula='Y3Al5O12', density=4.56)\n",
      "2025-05-07 01:29:09,231  - Scintillator_2_thickness: 0.428583025932312\n",
      "2025-05-07 01:29:09,231  - \n",
      "2025-05-07 01:29:09,239  - Start Estimation.\n",
      "2025-05-07 01:29:09,532  - Initial cost: 3.977945e-03\n",
      "2025-05-07 01:29:10,743  - Iteration: 5\n",
      "2025-05-07 01:29:11,013  - Cost: 0.0022856811992824078\n",
      "2025-05-07 01:29:11,014  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:11,014  - Filter_2_thickness: 3.5601279735565186\n",
      "2025-05-07 01:29:11,014  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:11,014  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:11,014  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:11,014  - Reflection_Source_takeoff_angle: 24.381519317626953\n",
      "2025-05-07 01:29:11,014  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:29:11,014  - Scintillator_2_thickness: 0.28235334157943726\n",
      "2025-05-07 01:29:11,014  - \n",
      "2025-05-07 01:29:12,129  - Iteration: 10\n",
      "2025-05-07 01:29:12,398  - Cost: 0.0016559113282710314\n",
      "2025-05-07 01:29:12,399  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:12,399  - Filter_2_thickness: 2.7152271270751953\n",
      "2025-05-07 01:29:12,399  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:12,399  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:12,399  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:12,399  - Reflection_Source_takeoff_angle: 22.01042366027832\n",
      "2025-05-07 01:29:12,399  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:29:12,399  - Scintillator_2_thickness: 0.3455880284309387\n",
      "2025-05-07 01:29:12,399  - \n",
      "2025-05-07 01:29:13,514  - Iteration: 15\n",
      "2025-05-07 01:29:13,789  - Cost: 0.0008422461105510592\n",
      "2025-05-07 01:29:13,789  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:13,790  - Filter_2_thickness: 1.9757590293884277\n",
      "2025-05-07 01:29:13,790  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:13,790  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:13,790  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:13,790  - Reflection_Source_takeoff_angle: 13.930182456970215\n",
      "2025-05-07 01:29:13,790  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:29:13,790  - Scintillator_2_thickness: 0.45166105031967163\n",
      "2025-05-07 01:29:13,790  - \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-07 01:29:14,872  - Iteration: 20\n",
      "2025-05-07 01:29:15,054  - Cost: 0.00047232609358616173\n",
      "2025-05-07 01:29:15,055  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:15,055  - Filter_2_thickness: 1.5964481830596924\n",
      "2025-05-07 01:29:15,055  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:15,055  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:15,055  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:15,055  - Reflection_Source_takeoff_angle: 6.7790141105651855\n",
      "2025-05-07 01:29:15,055  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:29:15,055  - Scintillator_2_thickness: 0.49253514409065247\n",
      "2025-05-07 01:29:15,055  - \n",
      "2025-05-07 01:29:16,283  - Iteration: 25\n",
      "2025-05-07 01:29:16,557  - Cost: 0.00046448659850284457\n",
      "2025-05-07 01:29:16,557  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:16,557  - Filter_2_thickness: 1.5243067741394043\n",
      "2025-05-07 01:29:16,557  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:16,557  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:16,557  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:16,557  - Reflection_Source_takeoff_angle: 6.323040008544922\n",
      "2025-05-07 01:29:16,557  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:29:16,558  - Scintillator_2_thickness: 0.49814164638519287\n",
      "2025-05-07 01:29:16,558  - \n",
      "2025-05-07 01:29:17,754  - Iteration: 30\n",
      "2025-05-07 01:29:18,157  - Cost: 0.0004632597847376019\n",
      "2025-05-07 01:29:18,157  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:18,157  - Filter_2_thickness: 1.486148715019226\n",
      "2025-05-07 01:29:18,157  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:18,158  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:18,158  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:18,158  - Reflection_Source_takeoff_angle: 6.07885217666626\n",
      "2025-05-07 01:29:18,158  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:29:18,158  - Scintillator_2_thickness: 0.5\n",
      "2025-05-07 01:29:18,158  - \n",
      "2025-05-07 01:29:22,845  - Stopping at epoch 31 because updates are too small.\n",
      "2025-05-07 01:29:22,846  - Cost: 0.0004632597556337714\n",
      "2025-05-07 01:29:22,846  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:22,846  - Filter_2_thickness: 1.4861483573913574\n",
      "2025-05-07 01:29:22,846  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:22,846  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:22,846  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:22,846  - Reflection_Source_takeoff_angle: 6.07885217666626\n",
      "2025-05-07 01:29:22,846  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:29:22,846  - Scintillator_2_thickness: 0.5\n",
      "2025-05-07 01:29:22,846  - \n",
      "2025-05-07 01:29:22,854  - Start Estimation.\n",
      "2025-05-07 01:29:23,129  - Initial cost: 2.657442e-03\n",
      "2025-05-07 01:29:24,244  - Iteration: 5\n",
      "2025-05-07 01:29:24,488  - Cost: 0.0019817014690488577\n",
      "2025-05-07 01:29:24,488  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:24,489  - Filter_2_thickness: 4.3209123611450195\n",
      "2025-05-07 01:29:24,489  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:24,489  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:24,489  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:24,489  - Reflection_Source_takeoff_angle: 24.611125946044922\n",
      "2025-05-07 01:29:24,489  - Scintillator_2_material: Material(formula='Gd2O2S', density=7.32)\n",
      "2025-05-07 01:29:24,489  - Scintillator_2_thickness: 0.2407224327325821\n",
      "2025-05-07 01:29:24,489  - \n",
      "2025-05-07 01:29:26,926  - Iteration: 10\n",
      "2025-05-07 01:29:27,164  - Cost: 0.0018169821705669165\n",
      "2025-05-07 01:29:27,165  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:27,165  - Filter_2_thickness: 3.9611289501190186\n",
      "2025-05-07 01:29:27,165  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:27,165  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:27,165  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:27,165  - Reflection_Source_takeoff_angle: 22.84878921508789\n",
      "2025-05-07 01:29:27,165  - Scintillator_2_material: Material(formula='Gd2O2S', density=7.32)\n",
      "2025-05-07 01:29:27,165  - Scintillator_2_thickness: 0.23107032477855682\n",
      "2025-05-07 01:29:27,165  - \n",
      "2025-05-07 01:29:28,128  - Iteration: 15\n",
      "2025-05-07 01:29:29,048  - Cost: 0.0015188619727268815\n",
      "2025-05-07 01:29:29,049  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:29,049  - Filter_2_thickness: 3.1533756256103516\n",
      "2025-05-07 01:29:29,049  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:29,049  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:29,049  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:29,049  - Reflection_Source_takeoff_angle: 13.88071060180664\n",
      "2025-05-07 01:29:29,049  - Scintillator_2_material: Material(formula='Gd2O2S', density=7.32)\n",
      "2025-05-07 01:29:29,049  - Scintillator_2_thickness: 0.1945681869983673\n",
      "2025-05-07 01:29:29,049  - \n",
      "2025-05-07 01:29:34,729  - Stopping at epoch 16 because updates are too small.\n",
      "2025-05-07 01:29:34,730  - Cost: 0.001518862321972847\n",
      "2025-05-07 01:29:34,730  - Filter_2_material: Material(formula='Al', density=2.702)\n",
      "2025-05-07 01:29:34,730  - Filter_2_thickness: 3.153376340866089\n",
      "2025-05-07 01:29:34,730  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:34,730  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:34,730  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:34,731  - Reflection_Source_takeoff_angle: 13.88071060180664\n",
      "2025-05-07 01:29:34,731  - Scintillator_2_material: Material(formula='Gd2O2S', density=7.32)\n",
      "2025-05-07 01:29:34,731  - Scintillator_2_thickness: 0.1945682168006897\n",
      "2025-05-07 01:29:34,731  - \n",
      "2025-05-07 01:29:34,738  - Start Estimation.\n",
      "2025-05-07 01:29:34,804  - Initial cost: 1.611838e-01\n",
      "2025-05-07 01:29:39,962  - Stopping at epoch 2 because updates are too small.\n",
      "2025-05-07 01:29:39,963  - Cost: 0.15039707720279694\n",
      "2025-05-07 01:29:39,963  - Filter_2_material: Material(formula='Cu', density=8.92)\n",
      "2025-05-07 01:29:39,963  - Filter_2_thickness: 0.0\n",
      "2025-05-07 01:29:39,963  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:39,963  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:39,963  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:39,963  - Reflection_Source_takeoff_angle: 26.320728302001953\n",
      "2025-05-07 01:29:39,963  - Scintillator_2_material: Material(formula='CsI', density=4.51)\n",
      "2025-05-07 01:29:39,963  - Scintillator_2_thickness: 0.23800449073314667\n",
      "2025-05-07 01:29:39,963  - \n",
      "2025-05-07 01:29:39,970  - Start Estimation.\n",
      "2025-05-07 01:29:40,048  - Initial cost: 1.618140e-01\n",
      "2025-05-07 01:29:45,393  - Stopping at epoch 2 because updates are too small.\n",
      "2025-05-07 01:29:45,394  - Cost: 0.1465068757534027\n",
      "2025-05-07 01:29:45,394  - Filter_2_material: Material(formula='Cu', density=8.92)\n",
      "2025-05-07 01:29:45,394  - Filter_2_thickness: 0.0\n",
      "2025-05-07 01:29:45,394  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:45,394  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:45,394  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:45,394  - Reflection_Source_takeoff_angle: 26.307336807250977\n",
      "2025-05-07 01:29:45,394  - Scintillator_2_material: Material(formula='Gd3Al2Ga3O12', density=6.63)\n",
      "2025-05-07 01:29:45,394  - Scintillator_2_thickness: 0.2367054522037506\n",
      "2025-05-07 01:29:45,395  - \n",
      "2025-05-07 01:29:45,402  - Start Estimation.\n",
      "2025-05-07 01:29:45,482  - Initial cost: 1.630148e-01\n",
      "2025-05-07 01:29:50,839  - Stopping at epoch 2 because updates are too small.\n",
      "2025-05-07 01:29:50,839  - Cost: 0.14229673147201538\n",
      "2025-05-07 01:29:50,839  - Filter_2_material: Material(formula='Cu', density=8.92)\n",
      "2025-05-07 01:29:50,839  - Filter_2_thickness: 0.0\n",
      "2025-05-07 01:29:50,839  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:50,839  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:50,840  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:50,840  - Reflection_Source_takeoff_angle: 26.294252395629883\n",
      "2025-05-07 01:29:50,840  - Scintillator_2_material: Material(formula='Lu3Al5O12', density=6.73)\n",
      "2025-05-07 01:29:50,840  - Scintillator_2_thickness: 0.24664917588233948\n",
      "2025-05-07 01:29:50,840  - \n",
      "2025-05-07 01:29:50,847  - Start Estimation.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-07 01:29:51,227  - Initial cost: 1.618287e-01\n",
      "2025-05-07 01:29:57,306  - Stopping at epoch 2 because updates are too small.\n",
      "2025-05-07 01:29:57,306  - Cost: 0.12914115190505981\n",
      "2025-05-07 01:29:57,306  - Filter_2_material: Material(formula='Cu', density=8.92)\n",
      "2025-05-07 01:29:57,306  - Filter_2_thickness: 0.0\n",
      "2025-05-07 01:29:57,306  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:29:57,306  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:29:57,307  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:29:57,307  - Reflection_Source_takeoff_angle: 26.30115509033203\n",
      "2025-05-07 01:29:57,307  - Scintillator_2_material: Material(formula='CdWO4', density=7.9)\n",
      "2025-05-07 01:29:57,307  - Scintillator_2_thickness: 0.250438928604126\n",
      "2025-05-07 01:29:57,307  - \n",
      "2025-05-07 01:29:57,314  - Start Estimation.\n",
      "2025-05-07 01:29:57,386  - Initial cost: 1.590084e-01\n",
      "2025-05-07 01:30:01,688  - Stopping at epoch 1 because updates are too small.\n",
      "2025-05-07 01:30:01,688  - Cost: 0.1590084731578827\n",
      "2025-05-07 01:30:01,688  - Filter_2_material: Material(formula='Cu', density=8.92)\n",
      "2025-05-07 01:30:01,689  - Filter_2_thickness: 5.000000476837158\n",
      "2025-05-07 01:30:01,689  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:30:01,689  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:30:01,689  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:30:01,689  - Reflection_Source_takeoff_angle: 24.9999942779541\n",
      "2025-05-07 01:30:01,689  - Scintillator_2_material: Material(formula='Y3Al5O12', density=4.56)\n",
      "2025-05-07 01:30:01,689  - Scintillator_2_thickness: 0.2500000298023224\n",
      "2025-05-07 01:30:01,689  - \n",
      "2025-05-07 01:30:01,697  - Start Estimation.\n",
      "2025-05-07 01:30:01,778  - Initial cost: 1.617665e-01\n",
      "2025-05-07 01:30:07,176  - Stopping at epoch 2 because updates are too small.\n",
      "2025-05-07 01:30:07,176  - Cost: 0.1254129856824875\n",
      "2025-05-07 01:30:07,176  - Filter_2_material: Material(formula='Cu', density=8.92)\n",
      "2025-05-07 01:30:07,176  - Filter_2_thickness: 0.0\n",
      "2025-05-07 01:30:07,176  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:30:07,176  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:30:07,177  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:30:07,177  - Reflection_Source_takeoff_angle: 26.3093204498291\n",
      "2025-05-07 01:30:07,177  - Scintillator_2_material: Material(formula='Bi4Ge3O12', density=7.13)\n",
      "2025-05-07 01:30:07,177  - Scintillator_2_thickness: 0.24034231901168823\n",
      "2025-05-07 01:30:07,177  - \n",
      "2025-05-07 01:30:07,184  - Start Estimation.\n",
      "2025-05-07 01:30:07,258  - Initial cost: 1.627629e-01\n",
      "2025-05-07 01:30:12,858  - Stopping at epoch 2 because updates are too small.\n",
      "2025-05-07 01:30:12,858  - Cost: 0.13278138637542725\n",
      "2025-05-07 01:30:12,858  - Filter_2_material: Material(formula='Cu', density=8.92)\n",
      "2025-05-07 01:30:12,858  - Filter_2_thickness: 0.0\n",
      "2025-05-07 01:30:12,858  - Reflection_Source_1_voltage: 40.0\n",
      "2025-05-07 01:30:12,858  - Reflection_Source_2_voltage: 80.0\n",
      "2025-05-07 01:30:12,858  - Reflection_Source_3_voltage: 180.0\n",
      "2025-05-07 01:30:12,858  - Reflection_Source_takeoff_angle: 26.278579711914062\n",
      "2025-05-07 01:30:12,858  - Scintillator_2_material: Material(formula='Gd2O2S', density=7.32)\n",
      "2025-05-07 01:30:12,859  - Scintillator_2_thickness: 0.23284363746643066\n",
      "2025-05-07 01:30:12,859  - \n"
     ]
    }
   ],
   "source": [
    "from xcal.estimate import Estimate\n",
    "\n",
    "learning_rate = 0.01 # 0.01 for NNAT_LBFGS and 0.001 for Adam\n",
    "max_iterations = 5000 # 5000 ~ 10000 would be enough\n",
    "stop_threshold = 1e-6 \n",
    "optimizer_type = 'NNAT_LBFGS' # Can also use Adam.\n",
    "\n",
    "Estimator = Estimate(energies)\n",
    "# For each scan, add data and calculated forward matrix to Estimator.\n",
    "for nrad, forward_matrix, concatenate_models in zip(train_rads, forward_matrices, spec_models):\n",
    "    Estimator.add_data(nrad, forward_matrix, concatenate_models, weight=None)\n",
    "\n",
    "# Fit data\n",
    "Estimator.fit(learning_rate=learning_rate,\n",
    "              max_iterations=max_iterations,\n",
    "              stop_threshold=stop_threshold,\n",
    "              optimizer_type=optimizer_type,\n",
    "              loss_type='transmission',\n",
    "              logpath=None,\n",
    "              num_processes=1) # Parallel computing for multiple cpus."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bbd09c7",
   "metadata": {},
   "source": [
    "### B07. Result Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "df709228",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import torch\n",
    "# Get the estimated effective response for each source voltage.\n",
    "# Make sure to convert to numpy array from tensor before plotting.\n",
    "est_sp = Estimator.get_spectra()\n",
    "\n",
    "fig, axs = plt.subplots(1, 3, figsize=(15, 5))\n",
    "\n",
    "for i in range(3):\n",
    "    ax = axs[i]\n",
    "    with torch.no_grad():\n",
    "        ax.plot(energies[:voltage_list[i]-1], (gt_spec_list[i]/np.trapezoid(gt_spec_list[i],energies))[:voltage_list[i]-1],\n",
    "                label='Ground Truth')\n",
    "        es = est_sp[i].numpy()\n",
    "        es /= np.trapezoid(es,energies)\n",
    "        ax.plot(energies[:voltage_list[i]-1], es[:voltage_list[i]-1], '--', label='Estimate')\n",
    "\n",
    "    ax.legend()\n",
    "    ax.set_title(f'{voltage_list[i]} kV Spectral Response')\n",
    "\n",
    "fig.suptitle('Comparison of Ground Truth and Estimate')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "5386b152",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ground Truth</th>\n",
       "      <th>Estimated</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>takeoff_angle (degree)</th>\n",
       "      <td>13</td>\n",
       "      <td>14.694992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fltr_mat</th>\n",
       "      <td>Al</td>\n",
       "      <td>Al</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fltr_th (mm)</th>\n",
       "      <td>3</td>\n",
       "      <td>3.106396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>det_mat</th>\n",
       "      <td>CsI</td>\n",
       "      <td>CsI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>det_th (mm)</th>\n",
       "      <td>0.33</td>\n",
       "      <td>0.346599</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Ground Truth  Estimated\n",
       "takeoff_angle (degree)           13  14.694992\n",
       "fltr_mat                         Al         Al\n",
       "fltr_th (mm)                      3   3.106396\n",
       "det_mat                         CsI        CsI\n",
       "det_th (mm)                    0.33   0.346599"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import torch\n",
    "\n",
    "# Return a dictionary containing the estimated parameters.\n",
    "res_params = Estimator.get_params()\n",
    "\n",
    "# Ground Truth values\n",
    "ground_truth = {\n",
    "    \"takeoff_angle (degree)\": takeoff_angle,\n",
    "    \"fltr_mat\": fltr_mat,\n",
    "    \"fltr_th (mm)\": fltr_th,\n",
    "    \"det_mat\": det_mat,\n",
    "    \"det_th (mm)\": det_th,\n",
    "}\n",
    "\n",
    "# Estimated values from res_params\n",
    "# .item() to return value for an estiamted continous parameter.\n",
    "# material with .formula is because the class Material contains both formula and density.\n",
    "estimated = {\n",
    "    \"takeoff_angle (degree)\": res_params['Reflection_Source_takeoff_angle'].item(),\n",
    "    \"fltr_mat\": res_params['Filter_2_material'].formula,\n",
    "    \"fltr_th (mm)\": res_params['Filter_2_thickness'].item(),\n",
    "    \"det_mat\": res_params['Scintillator_2_material'].formula,\n",
    "    \"det_th (mm)\": res_params['Scintillator_2_thickness'].item(),\n",
    "}\n",
    "\n",
    "# Combine into a DataFrame for comparison\n",
    "df = pd.DataFrame({'Ground Truth': ground_truth, 'Estimated': estimated})\n",
    "\n",
    "# Display the DataFrame\n",
    "df\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "xcal",
   "language": "python",
   "name": "xcal"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.17"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}