examples/multi_objectives.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from gpytorch.priors import NormalPrior\n",
    "\n",
    "from mobius import Planner, SequenceGA\n",
    "from mobius import Map4Fingerprint\n",
    "from mobius import GPModel, ExpectedImprovement, TanimotoSimilarityKernel\n",
    "from mobius import LinearPeptideEmulator\n",
    "from mobius import homolog_scanning, alanine_scanning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the linear peptide emulators\n",
    "hla_a32 = LinearPeptideEmulator('../data/IEDB_MHC_I-2.9_matx_smm_smmpmbec/smmpmbec_matrix/HLA-A-32:15-9.txt')\n",
    "hla_a26 = LinearPeptideEmulator('../data/IEDB_MHC_I-2.9_matx_smm_smmpmbec/smmpmbec_matrix/HLA-A-26:02-9.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reach max. number of peptides allowed.\n"
     ]
    }
   ],
   "source": [
    "# Predicted to bind to both HLA-A*32:15 and HLA-A*26:02 with\n",
    "# pIC50 of 3.00 and 3.77, respectively.\n",
    "lead_peptide = 'PEPTIDE1{Q.F.V.R.T.N.D.I.I}$$$$V2.0'\n",
    "seed_library = [lead_peptide]\n",
    "\n",
    "for seq in alanine_scanning(lead_peptide):\n",
    "    seed_library.append(seq)\n",
    "\n",
    "for seq in homolog_scanning(lead_peptide):\n",
    "    seed_library.append(seq)\n",
    "\n",
    "    if len(seed_library) >= 96:\n",
    "        print('Reach max. number of peptides allowed.')\n",
    "        break\n",
    "\n",
    "# Virtually test the seed library using the MHC emulators\n",
    "hla_a32_scores = hla_a32.score(seed_library)\n",
    "hla_a26_scores = hla_a26.score(seed_library)\n",
    "pic50_seed_library = np.column_stack((hla_a32_scores, hla_a26_scores))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "map4 = Map4Fingerprint(input_type='helm', dimensions=4096, radius=1)\n",
    "\n",
    "# Create the Gaussian Process models\n",
    "gpmodel_a32 = GPModel(kernel=TanimotoSimilarityKernel(), transform=map4, noise_prior=NormalPrior(loc=0, scale=1))\n",
    "gpmodel_a26 = GPModel(kernel=TanimotoSimilarityKernel(), transform=map4, noise_prior=NormalPrior(loc=0, scale=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# .. pass them to the acquisition function\n",
    "# Here we want to both minimize the pIC50 values for HLA-A*32:15 and HLA-A*26:02\n",
    "# so we set the `maximize` argument to `False` for both models. But you can also\n",
    "# set it to `True` for one of the models, and `False` for the other one, depending\n",
    "# on your optimization problem.\n",
    "acq = ExpectedImprovement([gpmodel_a32, gpmodel_a26], maximize=[False, False])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Instead of using the classic GA, we are going to use the SMS-EMOA algorithm\n",
    "optimizer = SequenceGA(algorithm='SMSEMOA', period=15)\n",
    "ps = Planner(acq, optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================================\n",
      "n_gen  |  n_eval  | n_nds  |      eps      |   indicator  \n",
      "==========================================================\n",
      "     1 |        0 |      6 |             - |             -\n",
      "     2 |      500 |     11 |  7.912373E+03 |         ideal\n",
      "     3 |     1000 |     14 |  0.4940479971 |         ideal\n",
      "     4 |     1500 |     12 |  0.0235893586 |             f\n",
      "     5 |     2000 |     15 |  0.0146754632 |             f\n",
      "     6 |     2500 |     16 |  0.0123450098 |         ideal\n",
      "     7 |     3000 |     23 |  0.0149561200 |             f\n",
      "     8 |     3500 |     15 |  0.0039977944 |         ideal\n",
      "     9 |     4000 |     15 |  0.1028017238 |         ideal\n",
      "    10 |     4500 |     25 |  0.0151334390 |             f\n",
      "    11 |     5000 |     21 |  0.0190857160 |             f\n",
      "    12 |     5500 |     23 |  0.3937026610 |         ideal\n",
      "    13 |     6000 |     29 |  0.0116091193 |             f\n",
      "    14 |     6500 |     34 |  0.0060351801 |             f\n",
      "    15 |     7000 |     34 |  0.0073082073 |             f\n",
      "    16 |     7500 |     36 |  0.0186988833 |         ideal\n",
      "    17 |     8000 |     41 |  0.0020836990 |             f\n",
      "    18 |     8500 |     45 |  0.0054408416 |             f\n",
      "    19 |     9000 |     48 |  0.1007739484 |         ideal\n",
      "    20 |     9500 |     48 |  0.0008086288 |             f\n",
      "    21 |    10000 |     51 |  0.0030193404 |             f\n",
      "    22 |    10500 |     55 |  0.0007719970 |             f\n",
      "    23 |    11000 |     54 |  0.0013102995 |             f\n",
      "    24 |    11500 |     54 |  0.0013102995 |             f\n",
      "    25 |    12000 |     55 |  0.0015885977 |             f\n",
      "    26 |    12500 |     56 |  0.0017740811 |             f\n",
      "    27 |    13000 |     56 |  0.0134684968 |         ideal\n",
      "    28 |    13500 |     57 |  0.0002284038 |             f\n",
      "    29 |    14000 |     58 |  0.0005227921 |             f\n",
      "    30 |    14500 |     58 |  0.0005227921 |             f\n",
      "    31 |    15000 |     59 |  0.0006274692 |             f\n",
      "    32 |    15500 |     59 |  0.0006274692 |             f\n",
      "    33 |    16000 |     59 |  0.0006626750 |             f\n",
      "    34 |    16500 |     59 |  0.0006626750 |             f\n",
      "    35 |    17000 |     59 |  0.0006626750 |             f\n",
      "    36 |    17500 |     59 |  0.0006626750 |             f\n",
      "    37 |    18000 |     59 |  0.0006626750 |             f\n",
      "    38 |    18500 |     60 |  0.0007538637 |             f\n",
      "    39 |    19000 |     60 |  0.0007538637 |             f\n",
      "    40 |    19500 |     60 |  0.0007538637 |             f\n",
      "    41 |    20000 |     61 |  0.0007920389 |             f\n",
      "    42 |    20500 |     61 |  0.0007920389 |             f\n",
      "    43 |    21000 |     61 |  0.0007920389 |             f\n",
      "    44 |    21500 |     61 |  0.0009342185 |             f\n",
      "    45 |    22000 |     62 |  0.0012734358 |             f\n",
      "    46 |    22500 |     61 |  0.0013254436 |             f\n",
      "    47 |    23000 |     62 |  0.0014002449 |             f\n",
      "    48 |    23500 |     62 |  0.0014002449 |             f\n",
      "    49 |    24000 |     62 |  0.0014714246 |             f\n",
      "    50 |    24500 |     62 |  0.0014714246 |             f\n",
      "    51 |    25000 |     62 |  0.0014714246 |             f\n",
      "    52 |    25500 |     62 |  0.0014714246 |             f\n",
      "    53 |    26000 |     62 |  0.0014714246 |             f\n",
      "    54 |    26500 |     63 |  0.0015940572 |             f\n",
      "    55 |    27000 |     63 |  0.0015940572 |             f\n",
      "    56 |    27500 |     63 |  0.0015940572 |             f\n",
      "    57 |    28000 |     63 |  0.0015940572 |             f\n",
      "    58 |    28500 |     63 |  0.0015940572 |             f\n",
      "    59 |    29000 |     62 |  0.0016189042 |             f\n",
      "    60 |    29500 |     62 |  0.0016189042 |             f\n",
      "    61 |    30000 |     62 |  0.0016189042 |             f\n",
      "    62 |    30500 |     62 |  0.0016189042 |             f\n",
      "    63 |    31000 |     62 |  0.0016189042 |             f\n",
      "    64 |    31500 |     62 |  0.0016189042 |             f\n",
      "    65 |    32000 |     62 |  0.0016189042 |             f\n",
      "    66 |    32500 |     62 |  0.0016189042 |             f\n",
      "    67 |    33000 |     62 |  0.0016189042 |             f\n",
      "    68 |    33500 |     62 |  0.0016189042 |             f\n",
      "    69 |    34000 |     62 |  0.0016189042 |             f\n",
      "    70 |    34500 |     62 |  0.0016189042 |             f\n",
      "    71 |    35000 |     62 |  0.0016189042 |             f\n",
      "    72 |    35500 |     62 |  0.0016189042 |             f\n",
      "    73 |    36000 |     62 |  0.0016189042 |             f\n",
      "    74 |    36500 |     62 |  0.0016189042 |             f\n",
      "==========================================================\n",
      "n_gen  |  n_eval  | n_nds  |      eps      |   indicator  \n",
      "==========================================================\n",
      "     1 |        0 |     11 |             - |             -\n",
      "     2 |      500 |     10 |  5.431827E+04 |         ideal\n",
      "     3 |     1000 |     13 |  0.0376002370 |             f\n",
      "     4 |     1500 |     15 |  0.0256669054 |             f\n",
      "     5 |     2000 |     16 |  0.6322069159 |         ideal\n",
      "     6 |     2500 |     22 |  0.2531063819 |         ideal\n",
      "     7 |     3000 |     25 |  0.0165404822 |         ideal\n",
      "     8 |     3500 |     26 |  0.0076199984 |             f\n",
      "     9 |     4000 |     30 |  0.0884601334 |         ideal\n",
      "    10 |     4500 |     36 |  0.0099355182 |         ideal\n",
      "    11 |     5000 |     36 |  0.0027208303 |             f\n",
      "    12 |     5500 |     37 |  0.0010009277 |             f\n",
      "    13 |     6000 |     43 |  0.0024419915 |             f\n",
      "    14 |     6500 |     42 |  0.0052084909 |             f\n",
      "    15 |     7000 |     41 |  0.0007626409 |             f\n",
      "    16 |     7500 |     41 |  0.0007626409 |             f\n",
      "    17 |     8000 |     42 |  0.0015150061 |             f\n",
      "    18 |     8500 |     42 |  0.0015150061 |             f\n",
      "    19 |     9000 |     44 |  0.0021913860 |             f\n",
      "    20 |     9500 |     44 |  0.0021913860 |             f\n",
      "    21 |    10000 |     44 |  0.0021913860 |             f\n",
      "    22 |    10500 |     44 |  0.0021913860 |             f\n",
      "    23 |    11000 |     44 |  0.0021913860 |             f\n",
      "    24 |    11500 |     44 |  0.0021913860 |             f\n",
      "    25 |    12000 |     44 |  0.0021913860 |             f\n",
      "    26 |    12500 |     44 |  0.0021913860 |             f\n",
      "    27 |    13000 |     44 |  0.0021913860 |             f\n",
      "    28 |    13500 |     44 |  0.0021913860 |             f\n",
      "    29 |    14000 |     44 |  0.0021913860 |             f\n",
      "    30 |    14500 |     44 |  0.0021913860 |             f\n",
      "    31 |    15000 |     44 |  0.0021913860 |             f\n",
      "    32 |    15500 |     44 |  0.0021913860 |             f\n",
      "    33 |    16000 |     44 |  0.0021913860 |             f\n",
      "    34 |    16500 |     44 |  0.0021913860 |             f\n",
      "==========================================================\n",
      "n_gen  |  n_eval  | n_nds  |      eps      |   indicator  \n",
      "==========================================================\n",
      "     1 |        0 |     15 |             - |             -\n",
      "     2 |      500 |     21 |  1.578331E+05 |         ideal\n",
      "     3 |     1000 |     28 |  0.0179913927 |         ideal\n",
      "     4 |     1500 |     32 |  0.0066730070 |             f\n",
      "     5 |     2000 |     21 |  0.1084502037 |         ideal\n",
      "     6 |     2500 |     20 |  0.0210276789 |             f\n",
      "     7 |     3000 |     23 |  0.0213072982 |             f\n",
      "     8 |     3500 |     28 |  0.0246435015 |             f\n",
      "     9 |     4000 |     29 |  0.0084441029 |             f\n",
      "    10 |     4500 |     33 |  0.3536738491 |         ideal\n",
      "    11 |     5000 |     37 |  0.0310491278 |         ideal\n",
      "    12 |     5500 |     37 |  0.0310656179 |         ideal\n",
      "    13 |     6000 |     39 |  0.2276091331 |         ideal\n",
      "    14 |     6500 |     42 |  0.0029032304 |             f\n",
      "    15 |     7000 |     44 |  0.2673411123 |         ideal\n",
      "    16 |     7500 |     44 |  6.132028E-06 |             f\n",
      "    17 |     8000 |     44 |  0.0008332846 |             f\n",
      "    18 |     8500 |     48 |  0.0023738271 |             f\n",
      "    19 |     9000 |     50 |  0.0047285985 |             f\n",
      "    20 |     9500 |     47 |  0.0008362264 |             f\n",
      "    21 |    10000 |     46 |  0.0027590310 |             f\n",
      "    22 |    10500 |     46 |  0.000000E+00 |             f\n",
      "    23 |    11000 |     46 |  0.000000E+00 |             f\n",
      "    24 |    11500 |     48 |  0.0002043401 |             f\n",
      "    25 |    12000 |     48 |  0.0002261800 |             f\n",
      "    26 |    12500 |     48 |  0.0002261800 |             f\n",
      "    27 |    13000 |     48 |  0.0002261800 |             f\n",
      "    28 |    13500 |     48 |  0.0025596092 |             f\n",
      "    29 |    14000 |     48 |  0.000000E+00 |             f\n",
      "    30 |    14500 |     48 |  0.000000E+00 |             f\n",
      "    31 |    15000 |     48 |  0.000000E+00 |             f\n",
      "    32 |    15500 |     49 |  0.0000140814 |             f\n",
      "    33 |    16000 |     50 |  0.0491149635 |         ideal\n",
      "    34 |    16500 |     50 |  0.000000E+00 |             f\n",
      "    35 |    17000 |     50 |  0.000000E+00 |             f\n",
      "    36 |    17500 |     50 |  0.0001578561 |             f\n",
      "    37 |    18000 |     50 |  0.0001578561 |             f\n",
      "    38 |    18500 |     50 |  0.0001578561 |             f\n",
      "    39 |    19000 |     50 |  0.0001578561 |             f\n",
      "    40 |    19500 |     50 |  0.0001578561 |             f\n",
      "    41 |    20000 |     50 |  0.0001578561 |             f\n",
      "    42 |    20500 |     50 |  0.0001578561 |             f\n",
      "    43 |    21000 |     50 |  0.0001578561 |             f\n",
      "    44 |    21500 |     50 |  0.0001578561 |             f\n",
      "    45 |    22000 |     49 |  0.1706930492 |         ideal\n",
      "    46 |    22500 |     49 |  0.000000E+00 |             f\n",
      "    47 |    23000 |     49 |  0.000000E+00 |             f\n",
      "    48 |    23500 |     50 |  0.0005633464 |             f\n",
      "    49 |    24000 |     50 |  0.0005633464 |             f\n",
      "    50 |    24500 |     50 |  0.0005633464 |             f\n",
      "    51 |    25000 |     50 |  0.0005633464 |             f\n",
      "    52 |    25500 |     50 |  0.0005633464 |             f\n",
      "    53 |    26000 |     50 |  0.0005633464 |             f\n",
      "    54 |    26500 |     50 |  0.0005633464 |             f\n",
      "    55 |    27000 |     50 |  0.0005633464 |             f\n",
      "    56 |    27500 |     50 |  0.0005633464 |             f\n",
      "    57 |    28000 |     50 |  0.0005633464 |             f\n",
      "    58 |    28500 |     50 |  0.0005633464 |             f\n",
      "    59 |    29000 |     50 |  0.0005633464 |             f\n",
      "    60 |    29500 |     50 |  0.0005633464 |             f\n",
      "    61 |    30000 |     50 |  0.0005633464 |             f\n",
      "    62 |    30500 |     50 |  0.0005633464 |             f\n",
      "    63 |    31000 |     50 |  0.0005633464 |             f\n",
      "==========================================================\n",
      "n_gen  |  n_eval  | n_nds  |      eps      |   indicator  \n",
      "==========================================================\n",
      "     1 |        0 |     21 |             - |             -\n",
      "     2 |      500 |     16 |  2.230470E+05 |         ideal\n",
      "     3 |     1000 |     22 |  0.6706664402 |         ideal\n",
      "     4 |     1500 |     25 |  0.0074310331 |             f\n",
      "     5 |     2000 |     20 |  0.0118036147 |             f\n",
      "     6 |     2500 |     23 |  0.1847816181 |         ideal\n",
      "     7 |     3000 |     22 |  0.2332695415 |         ideal\n",
      "     8 |     3500 |     25 |  0.3711998389 |         ideal\n",
      "     9 |     4000 |     32 |  0.0072295023 |             f\n",
      "    10 |     4500 |     26 |  0.0097361067 |             f\n",
      "    11 |     5000 |     33 |  0.0546673776 |         ideal\n",
      "    12 |     5500 |     38 |  0.0024670277 |             f\n",
      "    13 |     6000 |     39 |  0.0028639141 |             f\n",
      "    14 |     6500 |     44 |  0.0001853254 |             f\n",
      "    15 |     7000 |     45 |  0.0001853810 |             f\n",
      "    16 |     7500 |     47 |  0.0003905427 |             f\n",
      "    17 |     8000 |     49 |  0.3354436769 |         ideal\n",
      "    18 |     8500 |     50 |  0.0000529866 |             f\n",
      "    19 |     9000 |     50 |  0.0000529866 |             f\n",
      "    20 |     9500 |     51 |  0.0018609113 |             f\n",
      "    21 |    10000 |     51 |  0.0018609113 |             f\n",
      "    22 |    10500 |     51 |  0.0018609113 |             f\n",
      "    23 |    11000 |     53 |  0.0020003619 |             f\n",
      "    24 |    11500 |     53 |  0.0020003619 |             f\n",
      "    25 |    12000 |     54 |  0.0043674161 |             f\n",
      "    26 |    12500 |     55 |  0.0001806605 |             f\n",
      "    27 |    13000 |     55 |  0.0001806605 |             f\n",
      "    28 |    13500 |     55 |  0.0001806605 |             f\n",
      "    29 |    14000 |     55 |  0.0007728834 |             f\n",
      "    30 |    14500 |     55 |  0.0007728834 |             f\n",
      "    31 |    15000 |     56 |  0.0007625701 |             f\n",
      "    32 |    15500 |     56 |  0.0007625701 |             f\n",
      "    33 |    16000 |     57 |  0.0007548895 |             f\n",
      "    34 |    16500 |     57 |  0.0007548895 |             f\n",
      "    35 |    17000 |     57 |  0.0007548895 |             f\n",
      "    36 |    17500 |     57 |  0.0007548895 |             f\n",
      "    37 |    18000 |     58 |  0.0787549345 |         ideal\n",
      "    38 |    18500 |     58 |  0.000000E+00 |             f\n",
      "    39 |    19000 |     58 |  0.000000E+00 |             f\n",
      "    40 |    19500 |     58 |  0.000000E+00 |             f\n",
      "    41 |    20000 |     58 |  0.000000E+00 |             f\n",
      "    42 |    20500 |     58 |  0.000000E+00 |             f\n",
      "    43 |    21000 |     58 |  0.000000E+00 |             f\n",
      "    44 |    21500 |     59 |  0.0002093966 |             f\n",
      "    45 |    22000 |     59 |  0.0002093966 |             f\n",
      "    46 |    22500 |     59 |  0.0002093966 |             f\n",
      "    47 |    23000 |     59 |  0.0002093966 |             f\n",
      "    48 |    23500 |     59 |  0.0002093966 |             f\n",
      "    49 |    24000 |     59 |  0.0002093966 |             f\n",
      "    50 |    24500 |     59 |  0.0002093966 |             f\n",
      "    51 |    25000 |     59 |  0.0002093966 |             f\n",
      "    52 |    25500 |     59 |  0.0002093966 |             f\n",
      "    53 |    26000 |     59 |  0.0002093966 |             f\n",
      "    54 |    26500 |     59 |  0.0002093966 |             f\n",
      "    55 |    27000 |     59 |  0.0002093966 |             f\n",
      "    56 |    27500 |     59 |  0.0002093966 |             f\n",
      "    57 |    28000 |     59 |  0.0002093966 |             f\n",
      "    58 |    28500 |     59 |  0.0002093966 |             f\n",
      "    59 |    29000 |     59 |  0.0002093966 |             f\n",
      "==========================================================\n",
      "n_gen  |  n_eval  | n_nds  |      eps      |   indicator  \n",
      "==========================================================\n",
      "     1 |        0 |     15 |             - |             -\n",
      "     2 |      500 |     18 |  2.834115E+05 |         ideal\n",
      "     3 |     1000 |     21 |  0.0206184509 |             f\n",
      "     4 |     1500 |     22 |  0.1550308985 |         ideal\n",
      "     5 |     2000 |     31 |  0.1242112181 |         ideal\n",
      "     6 |     2500 |     28 |  0.6454286421 |         ideal\n",
      "     7 |     3000 |     28 |  0.0131026446 |             f\n",
      "     8 |     3500 |     29 |  0.0031026217 |             f\n",
      "     9 |     4000 |     40 |  0.0067756949 |             f\n",
      "    10 |     4500 |     44 |  0.0078738806 |             f\n",
      "    11 |     5000 |     50 |  0.0053405672 |             f\n",
      "    12 |     5500 |     49 |  0.0438220999 |         ideal\n",
      "    13 |     6000 |     54 |  0.0975861455 |         ideal\n",
      "    14 |     6500 |     53 |  0.0010332375 |             f\n",
      "    15 |     7000 |     53 |  0.0015931888 |             f\n",
      "    16 |     7500 |     56 |  0.0021623521 |             f\n",
      "    17 |     8000 |     56 |  0.0027140533 |             f\n",
      "    18 |     8500 |     60 |  0.0004357037 |             f\n",
      "    19 |     9000 |     59 |  0.0007969273 |             f\n",
      "    20 |     9500 |     60 |  0.0007845267 |             f\n",
      "    21 |    10000 |     60 |  0.0007845267 |             f\n",
      "    22 |    10500 |     63 |  0.0277476001 |         ideal\n",
      "    23 |    11000 |     66 |  0.0003044376 |             f\n",
      "    24 |    11500 |     67 |  0.0061413268 |         ideal\n",
      "    25 |    12000 |     67 |  0.000000E+00 |             f\n",
      "    26 |    12500 |     65 |  0.0002684959 |             f\n",
      "    27 |    13000 |     65 |  0.0002691609 |             f\n",
      "    28 |    13500 |     65 |  0.0570198808 |         ideal\n",
      "    29 |    14000 |     66 |  0.0002288914 |             f\n",
      "    30 |    14500 |     66 |  0.0002288914 |             f\n",
      "    31 |    15000 |     67 |  0.0002259468 |             f\n",
      "    32 |    15500 |     65 |  0.0002422824 |             f\n",
      "    33 |    16000 |     65 |  0.0002422824 |             f\n",
      "    34 |    16500 |     64 |  0.0002461645 |             f\n",
      "    35 |    17000 |     64 |  0.0002461645 |             f\n",
      "    36 |    17500 |     64 |  0.0002461645 |             f\n",
      "    37 |    18000 |     65 |  0.0002926442 |             f\n",
      "    38 |    18500 |     65 |  0.0002926442 |             f\n",
      "    39 |    19000 |     63 |  0.0004441941 |             f\n",
      "    40 |    19500 |     63 |  0.0004441941 |             f\n",
      "    41 |    20000 |     63 |  0.0004446006 |             f\n",
      "    42 |    20500 |     63 |  0.0004446006 |             f\n",
      "    43 |    21000 |     64 |  0.0004380077 |             f\n",
      "    44 |    21500 |     64 |  0.0004380077 |             f\n",
      "    45 |    22000 |     64 |  0.0004380077 |             f\n",
      "    46 |    22500 |     65 |  0.0004979248 |             f\n",
      "    47 |    23000 |     65 |  0.0004979248 |             f\n",
      "    48 |    23500 |     65 |  0.0004979248 |             f\n",
      "    49 |    24000 |     65 |  0.0004979248 |             f\n",
      "    50 |    24500 |     66 |  0.0005193020 |             f\n",
      "    51 |    25000 |     66 |  0.0005193020 |             f\n",
      "    52 |    25500 |     66 |  0.0005193020 |             f\n",
      "    53 |    26000 |     66 |  0.0005193020 |             f\n",
      "    54 |    26500 |     66 |  0.0005193020 |             f\n",
      "    55 |    27000 |     66 |  0.0005193020 |             f\n",
      "    56 |    27500 |     66 |  0.0005193020 |             f\n",
      "    57 |    28000 |     66 |  0.0005193020 |             f\n",
      "    58 |    28500 |     66 |  0.0005193020 |             f\n",
      "    59 |    29000 |     67 |  0.0008137707 |             f\n",
      "    60 |    29500 |     67 |  0.0008137707 |             f\n",
      "    61 |    30000 |     67 |  0.0008137707 |             f\n",
      "    62 |    30500 |     67 |  0.0008137707 |             f\n",
      "    63 |    31000 |     67 |  0.0008137707 |             f\n",
      "    64 |    31500 |     67 |  0.0008137707 |             f\n",
      "    65 |    32000 |     67 |  0.0008137707 |             f\n",
      "    66 |    32500 |     68 |  0.0008038857 |             f\n",
      "    67 |    33000 |     68 |  0.0008038857 |             f\n",
      "    68 |    33500 |     68 |  0.0008038857 |             f\n",
      "    69 |    34000 |     68 |  0.0008038857 |             f\n",
      "    70 |    34500 |     68 |  0.0008038857 |             f\n",
      "    71 |    35000 |     69 |  0.0009725250 |             f\n",
      "    72 |    35500 |     69 |  0.0009725250 |             f\n",
      "    73 |    36000 |     69 |  0.0009725250 |             f\n",
      "    74 |    36500 |     69 |  0.0009725250 |             f\n",
      "    75 |    37000 |     69 |  0.0009725250 |             f\n",
      "    76 |    37500 |     69 |  0.0009725250 |             f\n",
      "    77 |    38000 |     69 |  0.0009725250 |             f\n",
      "    78 |    38500 |     69 |  0.0009725250 |             f\n",
      "    79 |    39000 |     69 |  0.0009725250 |             f\n",
      "    80 |    39500 |     69 |  0.0009725250 |             f\n",
      "    81 |    40000 |     69 |  0.0009725250 |             f\n",
      "    82 |    40500 |     69 |  0.0009725250 |             f\n",
      "    83 |    41000 |     69 |  0.0009725250 |             f\n",
      "    84 |    41500 |     69 |  0.0009725250 |             f\n",
      "    85 |    42000 |     69 |  0.0009725250 |             f\n",
      "    86 |    42500 |     69 |  0.0009725250 |             f\n"
     ]
    }
   ],
   "source": [
    "peptides = seed_library.copy()\n",
    "pic50_scores = pic50_seed_library.copy()\n",
    "\n",
    "data = [(0, p, s[0], s[1]) for p, s in zip(peptides, pic50_scores)]\n",
    "\n",
    "for i in range(5):\n",
    "    suggested_peptides, _ = ps.recommend(peptides, pic50_scores, batch_size=96)\n",
    "\n",
    "    # Virtually test the suggested peptides using the MHC emulators\n",
    "    # This is for benchmarking or demonstration purposes only and\n",
    "    # should be replaced with actual lab experiments.\n",
    "    exp_values = []\n",
    "    for emulator in [hla_a32, hla_a26]:\n",
    "        values = np.asarray(emulator.score(suggested_peptides))\n",
    "        exp_values.append(values)\n",
    "    exp_values = np.stack(exp_values, axis=1)\n",
    "\n",
    "    # Add the suggested peptides to the library, and start over\n",
    "    peptides = np.concatenate([peptides, suggested_peptides])\n",
    "    pic50_scores = np.vstack([pic50_scores, exp_values])\n",
    "    data.extend([(i + 1, p, s[0], s[1]) for p, s in zip(suggested_peptides, exp_values)])\n",
    "\n",
    "df = pd.DataFrame(data=data, columns=('iter', 'polymer', 'exp_value_a32', 'exp_value_a26'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 10))\n",
    "\n",
    "# pandas dataframe (df) columns: iter, peptide, exp_value, methods/protocols\n",
    "df['iter'] = df['iter'].replace({0: 'Init.', 1: '1', 2: '2', 3: '3', 4: '4', 5: '5'})\n",
    "\n",
    "sns.scatterplot(x='exp_value_a32', y='exp_value_a26', hue='iter', data=df, ax=ax)\n",
    "\n",
    "ax.set_xlim([-0.9, 5.5])\n",
    "ax.set_ylim([-1.1, 5.5])\n",
    "ax.set_ylabel('pIC50 (HLA-A-32:15-9)', fontsize=30)\n",
    "ax.set_xlabel('pIC50 (HLA-A-26:02-9)', fontsize=30)\n",
    "ax.xaxis.set_tick_params(labelsize=30)\n",
    "ax.yaxis.set_tick_params(labelsize=30)\n",
    "\n",
    "sns.despine()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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