examples/matrix_sparse_only.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c87cba9b",
   "metadata": {},
   "source": [
    "# <center>Compressing Influence Matrix Using Sparse Only</center>\n",
    "\n",
    "The dose influence matrix is a fundamental component in the optimization process, but its handling can introduce computational challenges. The original matrix, being dense, requires substantial computational resources to manage. Hence, sparse influence matrix is being used in planning acorss various TPS to avoid computational issue. But it often leads to sub-optimal solutions, thus comprimising accuracy and plan quality. Hence we introduce novel technique of compressing original dense matrix using Randomized Minor-Value Rectification(RMR)\n",
    "\n",
    "1. Generating a plan utilizing the sparse matrix with naive threshold of 1% of max(A)\n",
    "2. Compressed planning using RMR method.\n",
    "3. Visualizing and evaluating plan\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c39ff13",
   "metadata": {},
   "source": [
    "### 1) Generating a plan utilizing the sparse matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3bb8c029",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install -r requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "09ee5011",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "#sys.path.append('../../PortPy')\n",
    "sys.path.append('../')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2fb76060",
   "metadata": {},
   "outputs": [],
   "source": [
    "import portpy.photon as pp\n",
    "from compress_rtp.utils.get_sparse_only import get_sparse_only\n",
    "import numpy as np\n",
    "from copy import deepcopy\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0cebcdfb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating optimization structures.. It may take some time due to dilation\n",
      "Optimization structures created!!\n",
      "Creating BEV..\n",
      "Loading full influence matrix..\n",
      "Done\n"
     ]
    }
   ],
   "source": [
    "# specify the patient data location.\n",
    "data_dir = r'../../PortPy/data'\n",
    "# Use PortPy DataExplorer class to explore PortPy data\n",
    "data = pp.DataExplorer(data_dir=data_dir)\n",
    "\n",
    "# pick a patient from the existing patient list to get detailed info (e.g., beam angles, structures).\n",
    "data.patient_id = 'Lung_Patient_2'\n",
    "\n",
    "ct = pp.CT(data)\n",
    "structs = pp.Structures(data)\n",
    "\n",
    "# If the list of beams are not provided, it uses the beams selected manually\n",
    "# by a human expert planner for the patient (manually selected beams are stored in portpy data).\n",
    "# Create beams for the planner beams by default\n",
    "# for the customized beams, you can pass the argument beam_ids\n",
    "# e.g. beams = pp.Beams(data, beam_ids=[0,10,20,30,40,50,60])\n",
    "beams = pp.Beams(data, load_inf_matrix_full=True)\n",
    "\n",
    "# In order to create an IMRT plan, we first need to specify a protocol which includes the disease site,\n",
    "# the prescribed dose for the PTV, the number of fractions, and the radiation dose thresholds for OARs.\n",
    "# These information are stored in .json files which can be found in a directory named \"config_files\".\n",
    "# An example of such a file is 'Lung_2Gy_30Fx.json'. Here's how you can load these files:\n",
    "protocol_name = 'Lung_2Gy_30Fx'\n",
    "# load clinical criteria from the config files for which plan to be optimized\n",
    "clinical_criteria = pp.ClinicalCriteria(data, protocol_name=protocol_name)\n",
    "\n",
    "# Optimization problem formulation\n",
    "protocol_name = 'Lung_2Gy_30Fx'\n",
    "# Loading hyper-parameter values for optimization problem\n",
    "opt_params = data.load_config_opt_params(protocol_name=protocol_name)\n",
    "# Creating optimization structures (i.e., Rinds)\n",
    "structs.create_opt_structures(opt_params=opt_params, clinical_criteria=clinical_criteria)\n",
    "# Loading influence matrix\n",
    "inf_matrix = pp.InfluenceMatrix(ct=ct, structs=structs, beams=beams, is_full=True)\n",
    "\n",
    "# create a plan using ct, structures, beams and influence matrix. Clinical criteria is optional\n",
    "my_plan = pp.Plan(ct=ct, structs=structs, beams=beams, inf_matrix=inf_matrix, clinical_criteria=clinical_criteria)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2919d690d27dcee7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# run optimization with naive thresold of 1% of max(A)\n",
    "# create cvxpy problem using the clinical criteria and optimization parameters\n",
    "A = deepcopy(inf_matrix.A)\n",
    "S_sparse = get_sparse_only(A=A, threshold_perc=1)\n",
    "inf_matrix.A = S_sparse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bbcb5f28",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Objective Start\n",
      "Objective done\n",
      "Constraints Start\n",
      "Constraints done\n",
      "Running Optimization..\n",
      "Optimal value: 71.00920964647031\n",
      "Elapsed time: 269.4082179069519 seconds\n"
     ]
    }
   ],
   "source": [
    "# Run IMRT fluence map optimization\n",
    "opt = pp.Optimization(my_plan, inf_matrix=inf_matrix, opt_params=opt_params)\n",
    "opt.create_cvxpy_problem()\n",
    "sol_sparse_naive = opt.solve(solver='MOSEK', verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2b1516c",
   "metadata": {},
   "source": [
    "### 2) Generating plan utilizing compression of Influence Matrix using RMR"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "005283cc",
   "metadata": {},
   "source": [
    "Now instead of optimizing the plan using sparse influence matrix $ S $ we optimize it using sparse matrix obtained using RMR method discussed in (RMR)[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fbe96589e6efeebd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating sparse matrix using RMR...\n",
      "Objective Start\n",
      "Objective done\n",
      "Constraints Start\n",
      "Constraints done\n",
      "Running Optimization..\n",
      "Optimal value: 78.43856937934272\n",
      "Elapsed time: 383.08576369285583 seconds\n"
     ]
    }
   ],
   "source": [
    "# run optimization with thresold of 1% and sparsifying matrix using RMR method\n",
    "# create cvxpy problem using the clinical criteria and optimization parameters\n",
    "S_rmr = get_sparse_only(A=A, threshold_perc=10, compression='rmr')\n",
    "inf_matrix.A = S_rmr\n",
    "opt = pp.Optimization(my_plan, inf_matrix=inf_matrix, opt_params=opt_params)\n",
    "opt.create_cvxpy_problem()\n",
    "sol_sparse_rmr = opt.solve(solver='MOSEK', verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3717099f9e0b5c25",
   "metadata": {},
   "source": [
    "### 3) Visualizing and evaluate plan with and without compression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "81073568",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(20, 7))\n",
    "struct_names = ['PTV', 'ESOPHAGUS', 'HEART', 'CORD', 'LUNGS_NOT_GTV']\n",
    "dose_1d_naive = (S_sparse @ sol_sparse_naive['optimal_intensity']) * my_plan.get_num_of_fractions()\n",
    "dose_1d_full_naive = (A @ sol_sparse_naive['optimal_intensity']) * my_plan.get_num_of_fractions()\n",
    "ax0 = pp.Visualization.plot_dvh(my_plan, dose_1d=dose_1d_naive, struct_names=struct_names, style='dotted', ax=ax[0], norm_flag=True)\n",
    "ax0 = pp.Visualization.plot_dvh(my_plan, dose_1d=dose_1d_full_naive, struct_names=struct_names, style='solid', ax=ax0, norm_flag=True)\n",
    "ax0.set_title(\"sparse_naive(dot)_vs_full(solid)\")\n",
    "\n",
    "dose_1d_rmr = (S_rmr @ sol_sparse_rmr['optimal_intensity']) * my_plan.get_num_of_fractions()\n",
    "dose_1d_full_rmr = (A @ sol_sparse_rmr['optimal_intensity']) * my_plan.get_num_of_fractions()\n",
    "ax1 = pp.Visualization.plot_dvh(my_plan, dose_1d=dose_1d_rmr, struct_names=struct_names, style='dotted', ax=ax[1], norm_flag=True)\n",
    "ax1 = pp.Visualization.plot_dvh(my_plan, dose_1d=dose_1d_full_rmr, struct_names=struct_names, style='solid', ax=ax1, norm_flag=True)\n",
    "ax1.set_title(\"sparse_rmr(dot)_vs_full(solid)\")\n",
    "plt.show(block=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ed8f98ae5d7f17c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: dose_1d value 60.0 is greater than max dose_1d for ESOPHAGUS\n",
      "Warning: dose_1d value 60.0 is greater than max dose_1d for ESOPHAGUS\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_8bbaf_row0_col0, #T_8bbaf_row0_col1, #T_8bbaf_row0_col2, #T_8bbaf_row0_col3, #T_8bbaf_row1_col0, #T_8bbaf_row1_col1, #T_8bbaf_row1_col2, #T_8bbaf_row1_col3, #T_8bbaf_row2_col0, #T_8bbaf_row2_col1, #T_8bbaf_row2_col2, #T_8bbaf_row2_col3, #T_8bbaf_row3_col0, #T_8bbaf_row3_col1, #T_8bbaf_row3_col2, #T_8bbaf_row3_col3, #T_8bbaf_row4_col0, #T_8bbaf_row4_col1, #T_8bbaf_row4_col2, #T_8bbaf_row4_col3, #T_8bbaf_row5_col0, #T_8bbaf_row5_col1, #T_8bbaf_row5_col2, #T_8bbaf_row5_col3, #T_8bbaf_row6_col0, #T_8bbaf_row6_col1, #T_8bbaf_row6_col2, #T_8bbaf_row6_col3, #T_8bbaf_row7_col0, #T_8bbaf_row7_col1, #T_8bbaf_row7_col2, #T_8bbaf_row7_col3, #T_8bbaf_row8_col0, #T_8bbaf_row8_col1, #T_8bbaf_row8_col2, #T_8bbaf_row8_col3, #T_8bbaf_row9_col0, #T_8bbaf_row9_col1, #T_8bbaf_row9_col2, #T_8bbaf_row9_col3, #T_8bbaf_row10_col0, #T_8bbaf_row10_col1, #T_8bbaf_row10_col2, #T_8bbaf_row10_col3, #T_8bbaf_row11_col0, #T_8bbaf_row11_col1, #T_8bbaf_row11_col2, #T_8bbaf_row11_col3, #T_8bbaf_row12_col0, #T_8bbaf_row12_col1, #T_8bbaf_row12_col2, #T_8bbaf_row12_col3, #T_8bbaf_row13_col0, #T_8bbaf_row13_col1, #T_8bbaf_row13_col2, #T_8bbaf_row13_col3, #T_8bbaf_row14_col0, #T_8bbaf_row14_col1, #T_8bbaf_row14_col2, #T_8bbaf_row14_col3, #T_8bbaf_row15_col0, #T_8bbaf_row15_col1, #T_8bbaf_row15_col2, #T_8bbaf_row15_col3 {\n",
       "  text-align: center;\n",
       "}\n",
       "#T_8bbaf_row0_col4, #T_8bbaf_row1_col4 {\n",
       "  background-color: #ffb38a;\n",
       "  text-align: center;\n",
       "}\n",
       "#T_8bbaf_row0_col5, #T_8bbaf_row1_col5, #T_8bbaf_row2_col4, #T_8bbaf_row2_col5, #T_8bbaf_row3_col4, #T_8bbaf_row3_col5, #T_8bbaf_row4_col4, #T_8bbaf_row4_col5, #T_8bbaf_row5_col5, #T_8bbaf_row6_col4, #T_8bbaf_row6_col5, #T_8bbaf_row7_col4, #T_8bbaf_row7_col5, #T_8bbaf_row8_col4, #T_8bbaf_row8_col5, #T_8bbaf_row9_col4, #T_8bbaf_row9_col5, #T_8bbaf_row10_col5, #T_8bbaf_row11_col4, #T_8bbaf_row11_col5, #T_8bbaf_row12_col4, #T_8bbaf_row12_col5, #T_8bbaf_row13_col5, #T_8bbaf_row14_col4, #T_8bbaf_row14_col5, #T_8bbaf_row15_col4, #T_8bbaf_row15_col5 {\n",
       "  background-color: #90ee90;\n",
       "  text-align: center;\n",
       "}\n",
       "#T_8bbaf_row5_col4, #T_8bbaf_row10_col4, #T_8bbaf_row13_col4 {\n",
       "  background-color: red;\n",
       "  text-align: center;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_8bbaf\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_8bbaf_level0_col0\" class=\"col_heading level0 col0\" >constraint</th>\n",
       "      <th id=\"T_8bbaf_level0_col1\" class=\"col_heading level0 col1\" >structure_name</th>\n",
       "      <th id=\"T_8bbaf_level0_col2\" class=\"col_heading level0 col2\" >Limit</th>\n",
       "      <th id=\"T_8bbaf_level0_col3\" class=\"col_heading level0 col3\" >Goal</th>\n",
       "      <th id=\"T_8bbaf_level0_col4\" class=\"col_heading level0 col4\" >Naive Sparsification</th>\n",
       "      <th id=\"T_8bbaf_level0_col5\" class=\"col_heading level0 col5\" >RMR Sparsification</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_8bbaf_row0_col0\" class=\"data row0 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row0_col1\" class=\"data row0 col1\" >GTV</td>\n",
       "      <td id=\"T_8bbaf_row0_col2\" class=\"data row0 col2\" >69.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row0_col3\" class=\"data row0 col3\" >66.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row0_col4\" class=\"data row0 col4\" >83.57</td>\n",
       "      <td id=\"T_8bbaf_row0_col5\" class=\"data row0 col5\" >61.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_8bbaf_row1_col0\" class=\"data row1 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row1_col1\" class=\"data row1 col1\" >PTV</td>\n",
       "      <td id=\"T_8bbaf_row1_col2\" class=\"data row1 col2\" >69.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row1_col3\" class=\"data row1 col3\" >66.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row1_col4\" class=\"data row1 col4\" >85.98</td>\n",
       "      <td id=\"T_8bbaf_row1_col5\" class=\"data row1 col5\" >62.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_8bbaf_row2_col0\" class=\"data row2 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row2_col1\" class=\"data row2 col1\" >ESOPHAGUS</td>\n",
       "      <td id=\"T_8bbaf_row2_col2\" class=\"data row2 col2\" >66.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row2_col4\" class=\"data row2 col4\" >47.09</td>\n",
       "      <td id=\"T_8bbaf_row2_col5\" class=\"data row2 col5\" >43.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_8bbaf_row3_col0\" class=\"data row3 col0\" >mean_dose</td>\n",
       "      <td id=\"T_8bbaf_row3_col1\" class=\"data row3 col1\" >ESOPHAGUS</td>\n",
       "      <td id=\"T_8bbaf_row3_col2\" class=\"data row3 col2\" >34.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row3_col3\" class=\"data row3 col3\" >21.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row3_col4\" class=\"data row3 col4\" >7.64</td>\n",
       "      <td id=\"T_8bbaf_row3_col5\" class=\"data row3 col5\" >9.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "      <td id=\"T_8bbaf_row4_col0\" class=\"data row4 col0\" >V(60.0Gy)</td>\n",
       "      <td id=\"T_8bbaf_row4_col1\" class=\"data row4 col1\" >ESOPHAGUS</td>\n",
       "      <td id=\"T_8bbaf_row4_col2\" class=\"data row4 col2\" >17.0%</td>\n",
       "      <td id=\"T_8bbaf_row4_col3\" class=\"data row4 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row4_col4\" class=\"data row4 col4\" >0.00</td>\n",
       "      <td id=\"T_8bbaf_row4_col5\" class=\"data row4 col5\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "      <td id=\"T_8bbaf_row5_col0\" class=\"data row5 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row5_col1\" class=\"data row5 col1\" >HEART</td>\n",
       "      <td id=\"T_8bbaf_row5_col2\" class=\"data row5 col2\" >66.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row5_col3\" class=\"data row5 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row5_col4\" class=\"data row5 col4\" >82.40</td>\n",
       "      <td id=\"T_8bbaf_row5_col5\" class=\"data row5 col5\" >62.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "      <td id=\"T_8bbaf_row6_col0\" class=\"data row6 col0\" >mean_dose</td>\n",
       "      <td id=\"T_8bbaf_row6_col1\" class=\"data row6 col1\" >HEART</td>\n",
       "      <td id=\"T_8bbaf_row6_col2\" class=\"data row6 col2\" >27.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row6_col3\" class=\"data row6 col3\" >20.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row6_col4\" class=\"data row6 col4\" >14.29</td>\n",
       "      <td id=\"T_8bbaf_row6_col5\" class=\"data row6 col5\" >13.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "      <td id=\"T_8bbaf_row7_col0\" class=\"data row7 col0\" >V(30.0Gy)</td>\n",
       "      <td id=\"T_8bbaf_row7_col1\" class=\"data row7 col1\" >HEART</td>\n",
       "      <td id=\"T_8bbaf_row7_col2\" class=\"data row7 col2\" >50.0%</td>\n",
       "      <td id=\"T_8bbaf_row7_col3\" class=\"data row7 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row7_col4\" class=\"data row7 col4\" >13.23</td>\n",
       "      <td id=\"T_8bbaf_row7_col5\" class=\"data row7 col5\" >10.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "      <td id=\"T_8bbaf_row8_col0\" class=\"data row8 col0\" >V(30.0Gy)</td>\n",
       "      <td id=\"T_8bbaf_row8_col1\" class=\"data row8 col1\" >HEART</td>\n",
       "      <td id=\"T_8bbaf_row8_col2\" class=\"data row8 col2\" ></td>\n",
       "      <td id=\"T_8bbaf_row8_col3\" class=\"data row8 col3\" >48.0%</td>\n",
       "      <td id=\"T_8bbaf_row8_col4\" class=\"data row8 col4\" >13.23</td>\n",
       "      <td id=\"T_8bbaf_row8_col5\" class=\"data row8 col5\" >10.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "      <td id=\"T_8bbaf_row9_col0\" class=\"data row9 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row9_col1\" class=\"data row9 col1\" >LUNG_L</td>\n",
       "      <td id=\"T_8bbaf_row9_col2\" class=\"data row9 col2\" >66.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row9_col3\" class=\"data row9 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row9_col4\" class=\"data row9 col4\" >18.39</td>\n",
       "      <td id=\"T_8bbaf_row9_col5\" class=\"data row9 col5\" >16.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "      <td id=\"T_8bbaf_row10_col0\" class=\"data row10 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row10_col1\" class=\"data row10 col1\" >LUNG_R</td>\n",
       "      <td id=\"T_8bbaf_row10_col2\" class=\"data row10 col2\" >66.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row10_col3\" class=\"data row10 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row10_col4\" class=\"data row10 col4\" >85.98</td>\n",
       "      <td id=\"T_8bbaf_row10_col5\" class=\"data row10 col5\" >62.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "      <td id=\"T_8bbaf_row11_col0\" class=\"data row11 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row11_col1\" class=\"data row11 col1\" >CORD</td>\n",
       "      <td id=\"T_8bbaf_row11_col2\" class=\"data row11 col2\" >50.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row11_col3\" class=\"data row11 col3\" >48.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row11_col4\" class=\"data row11 col4\" >32.51</td>\n",
       "      <td id=\"T_8bbaf_row11_col5\" class=\"data row11 col5\" >22.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "      <td id=\"T_8bbaf_row12_col0\" class=\"data row12 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row12_col1\" class=\"data row12 col1\" >SKIN</td>\n",
       "      <td id=\"T_8bbaf_row12_col2\" class=\"data row12 col2\" >60.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row12_col3\" class=\"data row12 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row12_col4\" class=\"data row12 col4\" >56.58</td>\n",
       "      <td id=\"T_8bbaf_row12_col5\" class=\"data row12 col5\" >47.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "      <td id=\"T_8bbaf_row13_col0\" class=\"data row13 col0\" >max_dose</td>\n",
       "      <td id=\"T_8bbaf_row13_col1\" class=\"data row13 col1\" >LUNGS_NOT_GTV</td>\n",
       "      <td id=\"T_8bbaf_row13_col2\" class=\"data row13 col2\" >66.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row13_col3\" class=\"data row13 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row13_col4\" class=\"data row13 col4\" >85.98</td>\n",
       "      <td id=\"T_8bbaf_row13_col5\" class=\"data row13 col5\" >62.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "      <td id=\"T_8bbaf_row14_col0\" class=\"data row14 col0\" >mean_dose</td>\n",
       "      <td id=\"T_8bbaf_row14_col1\" class=\"data row14 col1\" >LUNGS_NOT_GTV</td>\n",
       "      <td id=\"T_8bbaf_row14_col2\" class=\"data row14 col2\" >21.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row14_col3\" class=\"data row14 col3\" >20.0Gy</td>\n",
       "      <td id=\"T_8bbaf_row14_col4\" class=\"data row14 col4\" >14.10</td>\n",
       "      <td id=\"T_8bbaf_row14_col5\" class=\"data row14 col5\" >11.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_8bbaf_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "      <td id=\"T_8bbaf_row15_col0\" class=\"data row15 col0\" >V(20.0Gy)</td>\n",
       "      <td id=\"T_8bbaf_row15_col1\" class=\"data row15 col1\" >LUNGS_NOT_GTV</td>\n",
       "      <td id=\"T_8bbaf_row15_col2\" class=\"data row15 col2\" >37.0%</td>\n",
       "      <td id=\"T_8bbaf_row15_col3\" class=\"data row15 col3\" ></td>\n",
       "      <td id=\"T_8bbaf_row15_col4\" class=\"data row15 col4\" >21.24</td>\n",
       "      <td id=\"T_8bbaf_row15_col5\" class=\"data row15 col5\" >20.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1d9db384eb0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize plan metrics based upon clinical criteria\n",
    "pp.Evaluation.display_clinical_criteria(my_plan, dose_1d=[dose_1d_full_naive, dose_1d_full_rmr], sol_names=['Naive Sparsification', 'RMR Sparsification'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4f216015",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}