{ "cells": [ { "cell_type": "markdown", "id": "4a965641979b8803", "metadata": {}, "source": [ "# Tutorial 04: Implementing an analytical module for an X-ray component to allow gradient descent" ] }, { "cell_type": "markdown", "id": "64e50431c607f433", "metadata": {}, "source": [ "### **What You Will Need**\n", "- **Parameters**: $a, b, c, \\dots$ to be estimated or optimized. \n", "- **An analtyical model**: $S(E; a, b, c, \\dots)$ that defines the spectrum or energy response. \n", "\n", "### **What You Will Expect**\n", "- How to build an **analtyical model**?\n", "- Implementing the model using **PyTorch** for differentiability.\n", "- A step-by-step guide to setting up and testing the interpolation module." ] }, { "cell_type": "markdown", "id": "240c91980e878e60", "metadata": {}, "source": [ "## A. Analytical Model of Filter\n", "### A1. Background\n", "\n", "In X-ray systems, filters are always used to protect the detector and enhance image quality by selectively absorbing low-energy X-rays that contribute to image noise without improving image contrast. According to Beer's law, the response of a single filter is\n", "\n", "$$\n", "f\\left(E; m, \\theta\\right) = \\mathrm{e}^{-\\mu(E, m) \\theta}\n", "$$\n", "\n", "where:\n", "\n", "- $m$ denotes the filter material, which is a discrete parameter with only a limited set of choices. \n", "- $\\mu(E, m)$ is the Linear Attenuation Coefficient (LAC) of material $m$ at energy $E$.\n", "- $\\theta$ denotes filter thickness, which is a continuous parameter within a continuous range." ] }, { "cell_type": "markdown", "id": "37302efc2b5027b9", "metadata": {}, "source": [ "### **A2. Step-by-Step Implementation**\n", "\n", "To build an analytical model that supports **gradient descent**, we need two key functions:\n", "\n", "1. **`__init__` (Initialize the Model)** \n", " - Defines **materials** and **thickness** as model parameters. \n", " - Assigns **separate memory for continuous parameters** corresponding to each discrete material selection. \n", " - Enables **search over all material combinations**, allowing the model to explore different discrete parameter configurations.\n", "\n", "2. **`forward` (Compute Filter Response)** \n", " - Retrieves the current **material** and **thickness** for the filter. \n", " - Calls `gen_fltr_res()` to compute the **X-ray attenuation response** using Beer's Law. \n", " - Ensures the response is computed for a given set of **X-ray energies**. \n", "\n", "This setup enables **efficient spectral modeling and optimization** using PyTorch.\n" ] }, { "cell_type": "markdown", "id": "32d067f8c9a46284", "metadata": {}, "source": [ "#### **Note 1: Material Class Overview** \n", "\n", "The `Material` class stores the **chemical formula** and **density** of a material, ensuring valid input types and allowing it to be used in X-ray modeling and optimization." ] }, { "cell_type": "markdown", "id": "a0a6d82c120c16d8", "metadata": {}, "source": [ "#### **Note 2: Get LAC value**\n", "The `get_lin_att_c_vs_E` function calculates the linear attenuation coefficient (LAC) value with density, thickness, and energy vector." ] }, { "cell_type": "markdown", "id": "885e8ae28cd90fd", "metadata": {}, "source": [ "#### **Note 3: `get_params()` Function Overview** \n", "\n", "The `get_params()` function, defined in `Base_Spec_Model`, retrieves the **estimated parameters** as a dictionary, applying **denormalization and clamping** to ensure they remain within valid bounds while maintaining gradient flow for optimization." ] }, { "cell_type": "code", "execution_count": 1, "id": "dc35ea51faa1b7d8", "metadata": { "ExecuteTime": { "end_time": "2025-05-25T04:51:48.107421Z", "start_time": "2025-05-25T04:51:46.399489Z" } }, "outputs": [], "source": [ "import numpy as np\n", "import torch\n", "from xcal.models import Base_Spec_Model\n", "from xcal.defs import Material\n", "from xcal.chem_consts._consts_from_table import get_lin_att_c_vs_E\n", "\n", "# Implement the analytical model for filter.\n", "def _obtain_attenuation(energies, formula, density, thickness, torch_mode=False):\n", " # thickness is mm\n", "\tmu = get_lin_att_c_vs_E(density, formula, energies)\n", "\tif torch_mode:\n", "\t\tmu = torch.tensor(mu)\n", "\t\tatt = torch.exp(-mu * thickness)\n", "\telse:\n", "\t\tatt = np.exp(-mu * thickness)\n", "\treturn att\n", "\n", "def gen_fltr_res(energies, fltr_mat:Material, fltr_th:float, torch_mode=True):\n", "\n", " return _obtain_attenuation(energies, fltr_mat.formula, fltr_mat.density, fltr_th, torch_mode)\n", "\n", "# Gradient descent module.\n", "class Filter(Base_Spec_Model):\n", " def __init__(self, materials, thickness):\n", " \"\"\"\n", " A template filter model based on Beer's Law and NIST mass attenuation coefficients, including all necessary methods.\n", "\n", " Args:\n", " materials (list): A list of possible materials for the filter,\n", " where each material should be an instance containing formula and density.\n", " thickness (tuple or list): If a tuple, it should be (initial value, lower bound, upper bound) for the filter thickness.\n", " If a list, it should have the same length as the materials list, specifying thickness for each material.\n", " These values cannot be all None. It will not be optimized when lower == upper.\n", " \"\"\"\n", " if isinstance(thickness, tuple):\n", " if all(t is None for t in thickness):\n", " raise ValueError(\"Thickness tuple cannot have all None values.\")\n", " params_list = [{'material': mat, 'thickness': thickness} for mat in materials]\n", " elif isinstance(thickness, list):\n", " if len(thickness) != len(materials):\n", " raise ValueError(\"Length of thickness list must match length of materials list.\")\n", " params_list = [{'material': mat, 'thickness': th} for mat, th in zip(materials, thickness)]\n", " else:\n", " raise TypeError(\"Thickness must be either a tuple or a list.\")\n", "\n", " super().__init__(params_list)\n", "\n", " def forward(self, energies):\n", " \"\"\"\n", " Takes X-ray energies and returns the filter response.\n", "\n", " Args:\n", " energies (torch.Tensor): A tensor containing the X-ray energies of a poly-energetic source in units of keV.\n", "\n", " Returns:\n", " torch.Tensor: The filter response as a function of input energies, selected material, and its thickness.\n", " \"\"\"\n", "\t\t# Retrieves \n", " mat = self.get_params()[f\"{self.prefix}_material\"]\n", " th = self.get_params()[f\"{self.prefix}_thickness\"]\n", " energies = torch.tensor(energies, dtype=torch.float32) if not isinstance(energies, torch.Tensor) else energies\t\t\n", " return gen_fltr_res(energies, mat, th)\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "b48eb84db2687e2c", "metadata": { "ExecuteTime": { "end_time": "2025-05-25T04:51:48.181932Z", "start_time": "2025-05-25T04:51:48.117588Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'Filter_1_material': Material(formula='Al', density=2.702), 'Filter_1_thickness': tensor(2.5000, grad_fn=)}\n" ] }, { "data": { "text/plain": "[]" }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": "
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" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "gt_fltr_th = 2.5 # target thickness in um\n", "\n", "psb_fltr_mat = [Material(formula='Al', density=2.702), Material(formula='Cu', density=8.92)]\n", "filter_1 = Filter(psb_fltr_mat, thickness=(gt_fltr_th, 0, 10))\n", "\n", "ee = np.linspace(1,150,150)\n", "ff = filter_1(ee)\n", "est_param = filter_1.get_params()\n", "print(f'{est_param}')\n", "\n", "plt.plot(ee, ff.data)" ] }, { "cell_type": "markdown", "source": [ "# B. An Example of Estimating Filter Thickness" ], "metadata": { "collapsed": false }, "id": "5f4fc6a9c163288d" }, { "cell_type": "markdown", "source": [ "## B1. Data Simulation" ], "metadata": { "collapsed": false }, "id": "619e33fede676b4b" }, { "cell_type": "code", "execution_count": 3, "outputs": [], "source": [ "max_simkV = 50 # keV\n", "takeoff_angle = 13 # degree\n", "mas_list = 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", "\n", "ct_info = {\n", " \"SDD\": 15,\n", " \"psize\": [0.01, 0.01], # Width and height in mm\n", "}" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:48.183719Z", "start_time": "2025-05-25T04:51:48.182974Z" } }, "id": "1823c81de029becf" }, { "cell_type": "code", "execution_count": 4, "outputs": [], "source": [ "from xcal import get_filter_response,get_scintillator_response\n", "from xcal.chem_consts._periodictabledata import density\n", "import spekpy as sp\n", "\n", "simkV = 50\n", "gt_takeoff_angle = 13\n", "s = sp.Spek(kvp=simkV, th=gt_takeoff_angle, dk=1, z=ct_info['SDD']/10, mas=mas_list, char=True)\n", "k, phi_k = s.get_spectrum(edges=False) \n", "phi_k = phi_k * ((ct_info['psize'][0] / 10) * (ct_info['psize'][1] / 10)) #\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", "ee = k\n", "gt_src = src_spec\n", "gt_fltr = get_filter_response(ee, fltr_mat, density[fltr_mat], fltr_th)\n", "gt_det = get_scintillator_response(ee, det_mat, det_density, det_th)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:48.716005Z", "start_time": "2025-05-25T04:51:48.185415Z" } }, "id": "c9ed8595fe350c9b" }, { "cell_type": "code", "execution_count": 5, "outputs": [ { "data": { "text/plain": "
", "image/png": 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}, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "# Plot setup\n", "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n", "\n", "# Subplot 1: Source spectra for different voltages\n", "axes[0].plot(ee, src_spec, label=f'{simkV} kVp')\n", "axes[0].set_title('Transmission Source Spectra')\n", "axes[0].set_xlabel('Energy (keV)')\n", "axes[0].set_ylabel('Intensity')\n", "axes[0].legend()\n", "axes[0].grid(True)\n", "\n", "# Subplot 2: Filter response\n", "axes[1].plot(ee, gt_fltr, label=f'{fltr_mat} {fltr_th} mm')\n", "axes[1].set_title('Filter Response')\n", "axes[1].set_xlabel('Energy (keV)')\n", "axes[1].set_ylabel('Transmission')\n", "axes[1].legend()\n", "axes[1].grid(True)\n", "\n", "# Subplot 3: Scintillator response\n", "axes[2].plot(ee, gt_det, label=f'{det_mat} {det_th} mm')\n", "axes[2].set_title('Scintillator Response')\n", "axes[2].set_xlabel('Energy (keV)')\n", "axes[2].set_ylabel('Absorption Efficiency')\n", "axes[2].legend()\n", "axes[2].grid(True)\n", "\n", "# Layout adjustment\n", "plt.tight_layout()\n", "plt.show()" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:48.880721Z", "start_time": "2025-05-25T04:51:48.736684Z" } }, "id": "b2dd9e83f95c0a6a" }, { "cell_type": "code", "execution_count": 6, "outputs": [ { "data": { "text/plain": "
", "image/png": 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" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "# Assuming ee, gt_srcs, gt_fltr, gt_det, and vol_list are already defined\n", "\n", "# Create a new figure with a specified size\n", "plt.figure(figsize=(10, 6))\n", "gt_spec_list = []\n", "# Plot the efficient spectra for each voltage\n", "\n", "# Calculate the efficient spectrum by multiplying with filter and detector responses. \n", "# Then do normalization.\n", "efficient_spectrum = gt_src * gt_fltr * gt_det\n", "gt_spec_list.append(efficient_spectrum)\n", "# efficient_spectrum/=np.trapezoid(efficient_spectrum)\n", "# Plot the efficient spectrum\n", "plt.plot(ee, efficient_spectrum/np.trapezoid(efficient_spectrum), label=f'{simkV} kVp')\n", "\n", "# Add labels and title\n", "plt.xlabel('Energy (keV)')\n", "plt.ylabel('Relative Intensity')\n", "plt.title('Efficient Spectra (Source × Filter × Detector)')\n", "plt.legend()\n", "plt.grid(True)\n", "plt.tight_layout()\n", "plt.show()" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:48.945739Z", "start_time": "2025-05-25T04:51:48.892073Z" } }, "id": "c3580aefcdb7fcb6" }, { "cell_type": "code", "execution_count": 7, "outputs": [], "source": [ "from xcal.chem_consts import get_lin_att_c_vs_E\n", "sample_mats = ['V', 'Al', 'Ti', 'Mg']\n", "mat_density = [density[formula] for formula in sample_mats]\n", "lac_vs_E_list = [get_lin_att_c_vs_E(den, formula, ee) for den, formula in zip(mat_density, sample_mats)]\n", "sample_thicknesses = np.linspace(0, 1, 100) # mm\n", "\n", "# Attenuation Matrix, multiply effective spectrum can obtain tranmission measurement.\n", "# (4*100)*145: 4 materials, 100 different thicknesses, at total 400 measurements and 145 energy bins.\n", "spec_F = np.concatenate([np.exp(-sample_thicknesses[:,np.newaxis]@lac_vs_E[np.newaxis]) for lac_vs_E in lac_vs_E_list],axis=0)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:48.950947Z", "start_time": "2025-05-25T04:51:48.947756Z" } }, "id": "30ede8260b00f321" }, { "cell_type": "code", "execution_count": 8, "outputs": [ { "data": { "text/plain": "
", "image/png": 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}, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "# Create a new figure with a specified size\n", "plt.figure(figsize=(10, 6))\n", "\n", "# Plot the data for each sample material\n", "for smid, sample_mat in enumerate(sample_mats):\n", " plt.plot(sample_thicknesses, spec_F[100*smid:100*(smid+1), 30], label=sample_mat)\n", "\n", "# Set the y-axis to a logarithmic scale\n", "plt.yscale('log')\n", "\n", "# Add labels and title\n", "plt.xlabel('Sample Thickness (mm)')\n", "plt.ylabel('Intensity at 30 keV')\n", "plt.title('Attenuation vs. Sample Thickness at 30 keV')\n", "plt.legend()\n", "plt.grid(True, which='both', linestyle='--', linewidth=0.5)\n", "plt.tight_layout()\n", "plt.show()" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:49.120812Z", "start_time": "2025-05-25T04:51:48.963709Z" } }, "id": "cc4192ee9b438a52" }, { "cell_type": "code", "execution_count": 9, "outputs": [], "source": [ "trans_list = []\n", "\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 * efficient_spectrum, ee, axis=-1) # Object scan\n", "trans_0 = np.trapezoid(efficient_spectrum, ee, 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)" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:49.123741Z", "start_time": "2025-05-25T04:51:49.121266Z" } }, "id": "be5083799171d444" }, { "cell_type": "code", "execution_count": 10, "outputs": [ { "data": { "text/plain": "
", "image/png": 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" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "# Determine the number of cases\n", "num_cases = len(gt_spec_list)\n", "\n", "# Ensure axes is iterable\n", "if num_cases == 1:\n", " axes = [axes]\n", "\n", "# Plot data for each case\n", "\n", "for smid, sample_mat in enumerate(sample_mats):\n", " # Extract the transmission data for the current sample and case\n", " transmission_data = trans_list[0][100 * smid : 100 * (smid + 1)]\n", " plt.plot(sample_thicknesses, transmission_data, label=sample_mat)\n", "\n", "\n", "# Set the x-axis label for the bottom subplot\n", "plt.xlabel('Sample Thickness (mm)')\n", "\n", "# Adjust layout to prevent overlap\n", "plt.tight_layout()\n", "plt.show()\n" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:49.170947Z", "start_time": "2025-05-25T04:51:49.135687Z" } }, "id": "79b27c8f3fc060b0" }, { "cell_type": "markdown", "source": [ "## B2. Estimation" ], "metadata": { "collapsed": false }, "id": "47239fa06699394f" }, { "cell_type": "code", "execution_count": 11, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of cases for different discrete parameters: 2\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2025-05-25 12:51:53,737 - Start Estimation.\n", "2025-05-25 12:51:53,759 - Initial cost: 2.388144e-03\n", "2025-05-25 12:51:53,842 - Iteration: 50\n", "2025-05-25 12:51:53,844 - Cost: 0.0015051235677674413\n", "2025-05-25 12:51:53,844 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:53,844 - Filter_1_thickness: 4.509207248687744\n", "2025-05-25 12:51:53,845 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:53,845 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:53,845 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:53,845 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:53,845 - \n", "2025-05-25 12:51:53,936 - Iteration: 100\n", "2025-05-25 12:51:53,938 - Cost: 0.0008214872796088457\n", "2025-05-25 12:51:53,938 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:53,938 - Filter_1_thickness: 4.061138153076172\n", "2025-05-25 12:51:53,938 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:53,938 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:53,938 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:53,938 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:53,938 - \n", "2025-05-25 12:51:54,028 - Iteration: 150\n", "2025-05-25 12:51:54,029 - Cost: 0.00037792042712680995\n", "2025-05-25 12:51:54,030 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,030 - Filter_1_thickness: 3.6804146766662598\n", "2025-05-25 12:51:54,030 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,030 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,030 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,030 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,030 - \n", "2025-05-25 12:51:54,109 - Iteration: 200\n", "2025-05-25 12:51:54,111 - Cost: 0.00014460438978858292\n", "2025-05-25 12:51:54,111 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,111 - Filter_1_thickness: 3.387305974960327\n", "2025-05-25 12:51:54,111 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,111 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,111 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,111 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,111 - \n", "2025-05-25 12:51:54,212 - Iteration: 250\n", "2025-05-25 12:51:54,214 - Cost: 5.164837057236582e-05\n", "2025-05-25 12:51:54,214 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,214 - Filter_1_thickness: 3.190600633621216\n", "2025-05-25 12:51:54,214 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,214 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,214 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,214 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,214 - \n", "2025-05-25 12:51:54,315 - Iteration: 300\n", "2025-05-25 12:51:54,316 - Cost: 2.4953735191957094e-05\n", "2025-05-25 12:51:54,316 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,316 - Filter_1_thickness: 3.0789196491241455\n", "2025-05-25 12:51:54,316 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,316 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,316 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,316 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,316 - \n", "2025-05-25 12:51:54,397 - Iteration: 350\n", "2025-05-25 12:51:54,400 - Cost: 1.9495602828101255e-05\n", "2025-05-25 12:51:54,400 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,400 - Filter_1_thickness: 3.025747776031494\n", "2025-05-25 12:51:54,400 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,400 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,400 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,400 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,400 - \n", "2025-05-25 12:51:54,470 - Iteration: 400\n", "2025-05-25 12:51:54,472 - Cost: 1.868593790277373e-05\n", "2025-05-25 12:51:54,472 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,472 - Filter_1_thickness: 3.004319429397583\n", "2025-05-25 12:51:54,472 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,472 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,472 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,472 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,472 - \n", "2025-05-25 12:51:54,545 - Iteration: 450\n", "2025-05-25 12:51:54,547 - Cost: 1.8596598238218576e-05\n", "2025-05-25 12:51:54,547 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,547 - Filter_1_thickness: 2.9969093799591064\n", "2025-05-25 12:51:54,547 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,547 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,547 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,547 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,547 - \n", "2025-05-25 12:51:54,614 - Iteration: 500\n", "2025-05-25 12:51:54,616 - Cost: 1.8589174942462705e-05\n", "2025-05-25 12:51:54,616 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,616 - Filter_1_thickness: 2.9946932792663574\n", "2025-05-25 12:51:54,616 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,616 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,616 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,616 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,616 - \n", "2025-05-25 12:51:54,657 - Stopping at epoch 528 because updates are too small.\n", "2025-05-25 12:51:54,657 - Cost: 1.858877294580452e-05\n", "2025-05-25 12:51:54,657 - Filter_1_material: Material(formula='Al', density=2.702)\n", "2025-05-25 12:51:54,657 - Filter_1_thickness: 2.9942777156829834\n", "2025-05-25 12:51:54,657 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,657 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,657 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,657 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,657 - \n", "2025-05-25 12:51:54,659 - Start Estimation.\n", "2025-05-25 12:51:54,662 - Initial cost: 9.644821e-02\n", "2025-05-25 12:51:54,731 - Iteration: 50\n", "2025-05-25 12:51:54,733 - Cost: 0.09464140981435776\n", "2025-05-25 12:51:54,733 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:54,733 - Filter_1_thickness: 4.4902663230896\n", "2025-05-25 12:51:54,733 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,733 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,733 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,733 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,733 - \n", "2025-05-25 12:51:54,802 - Iteration: 100\n", "2025-05-25 12:51:54,804 - Cost: 0.09225913137197495\n", "2025-05-25 12:51:54,804 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:54,804 - Filter_1_thickness: 3.9403140544891357\n", "2025-05-25 12:51:54,804 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,804 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,804 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,804 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,804 - \n", "2025-05-25 12:51:54,877 - Iteration: 150\n", "2025-05-25 12:51:54,879 - Cost: 0.08896404504776001\n", "2025-05-25 12:51:54,879 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:54,879 - Filter_1_thickness: 3.3324739933013916\n", "2025-05-25 12:51:54,879 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,879 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,879 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,879 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,879 - \n", "2025-05-25 12:51:54,954 - Iteration: 200\n", "2025-05-25 12:51:54,956 - Cost: 0.08397167176008224\n", "2025-05-25 12:51:54,956 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:54,956 - Filter_1_thickness: 2.643720865249634\n", "2025-05-25 12:51:54,956 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:54,956 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:54,956 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:54,956 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:54,956 - \n", "2025-05-25 12:51:55,028 - Iteration: 250\n", "2025-05-25 12:51:55,030 - Cost: 0.07504528015851974\n", "2025-05-25 12:51:55,030 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:55,030 - Filter_1_thickness: 1.82919442653656\n", "2025-05-25 12:51:55,030 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:55,030 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:55,030 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:55,030 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:55,030 - \n", "2025-05-25 12:51:55,098 - Iteration: 300\n", "2025-05-25 12:51:55,100 - Cost: 0.04900381714105606\n", "2025-05-25 12:51:55,100 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:55,100 - Filter_1_thickness: 0.7538713216781616\n", "2025-05-25 12:51:55,100 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:55,100 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:55,100 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:55,100 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:55,100 - \n", "2025-05-25 12:51:55,171 - Iteration: 350\n", "2025-05-25 12:51:55,173 - Cost: 0.0006778572569601238\n", "2025-05-25 12:51:55,173 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:55,173 - Filter_1_thickness: 0.08765144646167755\n", "2025-05-25 12:51:55,173 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:55,173 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:55,173 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:55,173 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:55,173 - \n", "2025-05-25 12:51:55,260 - Iteration: 400\n", "2025-05-25 12:51:55,262 - Cost: 0.00014357846521306783\n", "2025-05-25 12:51:55,262 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:55,262 - Filter_1_thickness: 0.10207980126142502\n", "2025-05-25 12:51:55,262 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:55,262 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:55,262 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:55,262 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:55,262 - \n", "2025-05-25 12:51:55,287 - Stopping at epoch 417 because updates are too small.\n", "2025-05-25 12:51:55,287 - Cost: 0.00014372407167684287\n", "2025-05-25 12:51:55,287 - Filter_1_material: Material(formula='Cu', density=8.92)\n", "2025-05-25 12:51:55,287 - Filter_1_thickness: 0.10162963718175888\n", "2025-05-25 12:51:55,287 - Reflection_Source_1_voltage: 50.0\n", "2025-05-25 12:51:55,287 - Reflection_Source_takeoff_angle: 13.0\n", "2025-05-25 12:51:55,287 - Scintillator_2_material: Material(formula='CsI', density=4.51)\n", "2025-05-25 12:51:55,287 - Scintillator_2_thickness: 0.33000001311302185\n", "2025-05-25 12:51:55,287 - \n" ] } ], "source": [ "from xcal.models import Reflection_Source, Scintillator\n", "from xcal.defs import Material\n", "from xcal.estimate import Estimate\n", "from T04 import Filter\n", "\n", "learning_rate = 0.001 # 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 = 'Adam' # Can also use Adam.\n", "\n", "# Use Spekpy to generate a source spectra dictionary.\n", "takeoff_angles = np.linspace(5,45,11)\n", "src_spec_list = []\n", "\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, 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((1,len(takeoff_angles),-1))\n", "source = Reflection_Source(voltage=(50, None, None), takeoff_angle=(gt_takeoff_angle, None, None), single_takeoff_angle=True)\n", "source.set_src_spec_list(ee, src_spec_list, [50], takeoff_angles)\n", "\n", "\n", "# Not estimate filter and scintillator\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", "psb_scint_mat = [Material(formula='CsI', density=4.51)]\n", "scintillator_1 = Scintillator(materials=psb_scint_mat, thickness=(0.33, None, None))\n", "\n", "spec_models = [[source, filter_1, scintillator_1]]\n", "\n", "Estimator = Estimate(ee)\n", "# For each scan, add data and calculated forward matrix to Estimator.\n", "Estimator.add_data(trans_list[0], spec_F, spec_models[0], 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." ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:55.301854Z", "start_time": "2025-05-25T04:51:49.172623Z" } }, "id": "b95fe7425d463558" }, { "cell_type": "code", "execution_count": 12, "outputs": [ { "data": { "text/plain": "{'Reflection_Source_1_voltage': tensor(50.),\n 'Reflection_Source_takeoff_angle': tensor(13.),\n 'Filter_1_material': Material(formula='Al', density=2.702),\n 'Filter_1_thickness': tensor(2.9943, grad_fn=),\n 'Scintillator_2_material': Material(formula='CsI', density=4.51),\n 'Scintillator_2_thickness': tensor(0.3300)}" }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Estimator.get_params()" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:55.308675Z", "start_time": "2025-05-25T04:51:55.303536Z" } }, "id": "cd2b68519fb8a376" }, { "cell_type": "code", "execution_count": 13, "outputs": [ { "data": { "text/plain": "
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" }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Ground Truth: 2.50, Estimated: 2.99\n" ] } ], "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", "with torch.no_grad():\n", " plt.plot(ee, (gt_spec_list[0]/np.trapezoid(gt_spec_list[0],ee)),\n", " label='Ground Truth')\n", " es = est_sp[0].numpy()\n", " es /= np.trapezoid(es,ee)\n", " plt.plot(ee, es, '--', label='Estimate')\n", "\n", "plt.legend()\n", "plt.title(f'{simkV} kV Spectral Response')\n", "\n", "fig.suptitle('Comparison of Ground Truth and Estimate')\n", "plt.show()\n", "print(f\"Ground Truth: {gt_fltr_th:.2f}, Estimated: {Estimator.get_params()['Filter_1_thickness'].item():.2f}\")" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:55.370154Z", "start_time": "2025-05-25T04:51:55.310509Z" } }, "id": "34fe9ac8fd3da4a9" }, { "cell_type": "code", "execution_count": 13, "outputs": [], "source": [], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2025-05-25T04:51:55.372018Z", "start_time": "2025-05-25T04:51:55.370529Z" } }, "id": "52fd0080df11f8de" } ], "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 }