QNN-IBMQ.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quantum Neural Network-based correlation for frictional pressure drop of non-azeotropic mixtures during cryogenic forced boiling\n",
    "\n",
    "This work proposes a Quantum neural network-based methodology to estimate frictional pressure drop during boiling in mini-channels of non-azeotropic mixtures including nitrogen, methane, ethane, and propane. The methodology can assist in thermal analysis or design of heat exchangers used in cryogenic applications. The proposed model architecture includes the local quality, roughness, mass flux, and Reynolds number as inputs and frictional pressure drop as outputs.\n",
    "It will compare with one paper where my colleagues and I use the same data to create an ANN-based correlation for pressure drop estimation in microchannels [1].\n",
    "\n",
    "[1] Barroso-Maldonado, J. M., Montañez-Barrera, J. A., Belman-Flores, J. M., and Aceves, S. M. (2019). ANN-based correlation for frictional pressure drop of non-azeotropic mixtures during cryogenic forced boiling. Applied Thermal Engineering, 149(August 2018), 492-501. https://doi.org/10.1016/j.applthermaleng.2018.12.082"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Experimental Data\n",
    "The data of this project was obtained from Barraza et. al [2]. The input variables were choose based on the input used for the correlations which are the local quality, roughness, mass flux, and Reynolds number. The following tables show the conditions for each experiment.\n",
    "<img src=\"./Images/T2.png\" width=\"600\">\n",
    "<img src=\"./Images/T3.png\" width=\"300\">\n",
    "<img src=\"./Images/T1.png\" width=\"600\">\n",
    "\n",
    "[2] R.Barraza,G.Nellis,S.Klein,D.Reindl,Measuredandpredictedfrictionalpressure drop for boiling zeotropic mixed refrigerants in horizontal tubes, Int. J. Heat Mass Transf. 98 (2016) 285–298, https://doi.org/10.1016/j.ijheatmasstransfer.2016.03.010."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import qiskit as qk\n",
    "from tqdm import tqdm\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "Data = np.load(\"./Data/training_data.npy\", allow_pickle=True).item()\n",
    "ll = 1000\n",
    "trainData = Data[\"train\"][:ll,[0,4,21,-1]]\n",
    "testData = Data[\"test\"][:ll,[0,4,21,-1]]\n",
    "\n",
    "data_set = np.concatenate((trainData, testData))\n",
    "minD = np.min(data_set, axis=0)\n",
    "maxD = np.max(data_set, axis=0)\n",
    "\n",
    "normalized_data = (trainData - minD)/ (maxD - minD)\n",
    "\n",
    "np.random.shuffle(normalized_data)\n",
    "\n",
    "train_input = normalized_data[:,:3]\n",
    "train_output = normalized_data[:,3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### QNN Architecture\n",
    "\n",
    "To create a QNN, we need three ingredients:\n",
    "* a Feature Map to encode the data\n",
    "* an Ansatz to train\n",
    "* an Observable to evaluate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Feature Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1110x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.circuit.library import ZZFeatureMap\n",
    "\n",
    "dim = trainData.shape[-1]\n",
    "feature_map = ZZFeatureMap(dim-1, reps=1)  # let's keep it simple!\n",
    "feature_map.draw('mpl', style='iqx')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Ansatz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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eaZtWvGsGf/v9ENp4u6lWl7NzmlCorKwkLy+v1kVLycnJFBUVcfXqVc6dO0dRURG9e/du0dqinpxJwrt/IurJmYRMG8mkPS8QMDQcnasL4z/4M7888W/bLbKu3p5M2JHC8H8sbtEaAZY+NICBff0cMlbMgI4smhnukLGaqn07D9v3Wg2Dunrkhm7jY5ia9RKgbo+AE4WCj48PZrOZRYsWqV2Kgm9YV9x8vMmYtAKP9m1x9fYkZ912SjOPYjWZ2TV7Fad2HLAtb7pSjfHh51Sp1c1Nz1t/icfvLo86l6nrLMNPdWzvyb9T4uQgXgPV1yM39JgwhMtnzgHq9gg4UShoVUBMP9uNK2eM2VgtFsX86rKLapRVp369fPnklQQ6+Xk26vWdO3qxa/04+nS/y8GVtV72eiTo3kGc2fMtVqvlVi9vcRIKTeTu68OgpdNI2JpE5JLJuPv6qF2SXYP6+ZO9dTKTRnW/rddNT+hJdupk+vdxzC7IncJej4RMG0n+1s9Vqq42OTzbRDXllRx69m1Of5RF8Oho2nTpoHZJDRLQwYutfxuFMauEtW/n8u6nJzHd4qPZ3Fz1TBndgwXT+zG8mU5rtnb19UjgsP788FUelmsmFStUklBootIvcgmZHs/pj7IIjDVQWXgWMKtdVoPodDpGDu7MyMGdqao2kZ13nqP55VRfNePl6YKhd3sG9GmPp4e0SVPU1yPt+3aj65i7CYofiG9oVwY9/gCH/rpZ1Xrlf7uJyo+fxmIykbA1ibNfHcd0pRqd681LcONefoyAe/rStmdncta+z+kPv1Sx2rp5eboSE9GJmIhOapfS6tTXI7kb0sjdcP1K3XHvJ6seCCCh4BBfp7xl+777hCEMWDSJioJiSjOPYpz3N8Wyrt6eDF+zmLJv5FqKO0l9PXJD+n1PAer3iISCg53aeYBTOw/UOd90pdr2ny/uTFrvEQkFO/wMPe/I9xYNp9b/U3O9r86q5Y+mEaKBblxwZe/j6YV9cp2CEEJBQkEIoSChIIRQkFAQQihIKAghFCQUhBAKEgpCCAUJBSGEgoSCEEJBQkEIoSChIIRQkFAQQihIKAghFOTWaTu+eOo1zh8pUOW9/Qw9iUlu/KPKRctQq0eaqz8kFOw4f6RA8ek4Qvxca+sR2X0QQihIKAghFGT3QTgls9nCp1+c4fOvSvjq6Dnb9PsWf0x0uD+jYroQO7ATOl0dz6oXdZJQEE7FbLbw0pZj/O/rORR8f6nW/O2fFbL9s0JWrv2aAX3as/w3A5k2tqeEw22QUHCQhK1JdIwOxWIyYTVbqCw8y+EXtnFqR6bapbUaBUWXmLXcyL5DpQ1a/tv/u8ADy3azOSOfV1f+B/7tG/f8TEdwpv6QUHCgw8+nkv38VnQuevrNGUfc2iW8m1PApZMlapfm9I4VlBOfmEZJWdVtv/a9Xac4VlDO7g3jCfT3bobqGsZZ+kMONDYDq9lC3hufoHdzxc/QQ+1ynN75i1f5xdyMRgXCDccKLjJh4UfUXFP/kX5a7w8JhWagd3Ml7KGxAFTkF6tcjfNb8tdMikov17uMNTvR7se7f517jqdf+caBlTWO1vtD06FgsVhYvXo1ffr0wdPTk8jISIxGI2FhYcydO1ft8mqJWDyZmcde58GCN4l6/AH2PbaWC7mnABixZgnBo6Nty9772jK6xEWqVarTOHD4LG/scNzj055Zf5iikvoDprk4S39oOhQSExNJTk5m3rx5pKenM23aNGbMmEF+fj7R0dH2B2hh2S9u462+D7HZMIeiXYcIHNbfNu/gitcYtOwBXL096TY+hpqKK5wxHlaxWuew9u1ch45nMlt5detxh47ZUM7SH5oNhU2bNrFx40a2b9/O0qVLiY+PZ/ny5QwdOhSTyURUVJTaJdap5uJl9v1uHcGjoug6djAA1ecqyF2/k5in5xD5yBQOrtyobpFOoOaamS0fO/6egrfS1X24r9b7Q7OhkJKSQkJCAnFxcYrpISEhuLm5ERERwYULF5g4cSKhoaFERkYyZswYTpw4oVLFSjXllRx5ZQdRT8yEH8+Rn3jnM9r17kzu+jRqyitVrlD7jpy4QPVVxx8YPFFYQXnFVYePezu03B+aDIWioiJycnKYOnVqrXmFhYUYDAY8PDzQ6XQ88sgj5OXlcfjwYSZOnMjs2dq5qzD31Z14d/IlZOrNYLtUUEKFxk5BadWR78qdcuyG0mp/aPI6haKiIgACAwMV06uqqjAajYwbNw4AX19fRo8ebZsfGxvLqlWrGvQeDb3C7XG/EfR172h3uYwpK2tNu1ZZxabwxoeU0Whk/J18JV77ERD834pJ9s4w1DX/xgNob/iPEfdCpWPubGxIj2ihPxr6LGlNbin4+/sDkJeXp5i+atUqiouL6zzI+Pzzz3P//fc3d3mipVivNd/YlprmG9vJafJR9BaLhUGDBlFcXMzq1asJCgoiNTWVtLQ0CgsLOXDgADExMYrXJCUlkZ6ezq5du/D2dtxVa+mTV6h2r3zA0HDGbfuTKu+tBVlHfmDwjO0NWvbGFsLPtwjqUvb5L+ng65jLntXqkebqD01uKej1erZs2YLBYGD+/PnMnj0bf39/Fi5ciIuLCxEREYrln376aXbs2EFGRoZDA0Goa0AfP9zdHN+iPYPaOiwQWiNNHlMACA0NZffu3Ypps2bNIjw8HC8vL9u0pKQk0tLS+Pjjj/H19W3hKkVz8nB34f57u/POh449LTk9oadDx2ttNLmlUJesrCzF8YQjR47wxz/+kXPnzjFy5EgGDhzIwIED1StQONyC6f0cOp5OB3On9HXomK2NZrcUfq6yspK8vDwWLFhgm2YwGBp8RFU4pxHRgUwe1YNtn550yHiPzepPz+C2DhmrtXKaUPDx8cFsVv8Ot1uJenImnQb35eyXx6g4cYYBiyaxf9nLXC4qY/jfF2G1Wrly5hx7Fv0dq8XCqH89gftd3qTf95TapWueTqdj7R9i2XuohLPnq+tergEHGPv18iX5t+pcHl9Xj5RmHmXm8dc5n3MSgF2Jz1JTXqlqjzjV7oMW+YZ1xc3Hm4xJK/Bo3xZXb09y1m2nNPMoNRWX+WTWM2RMWsGl02cJGjUIgE//+xmVq3YuAR28yFg3Fr+7PBo9Ro8uPmSsG4uXZ8v/HqyvRwAuHCskY8pKMqastF3JqGaPSCg0UUBMP9uNK2eM2VgtFtu8mouXuXbpCgDWa2asZsstxxD2Dernz56NExjY1++2X3vvPZ3Z96+JdOvs0wyV2VdfjwDcFRLMuPeSiX7yl2qUV4uEQhO5+/owaOk0ErYmEblkMu6+tRvPK6A9nUdEyF2RTRTeuz0H37yPlMV308nP/inFnkFteXnFMD55dRxdOrVpgQpvzV6PbBu2iPT7n8Ldtw1dx9ytUpU3Oc0xBa2qKa/k0LNvc/qjLIJHR9OmSwfFfL27K8Nf+C37f/+SbCk4gJubnid+HcnvHurP+7sL2fN1CV8dLePs+Wp0Ogjq1Ibofh0YFdOFMbFBuLio/3vPXo/c2GUozPgSv/49Of1Rlhpl2kgoNFHpF7mETI/n9EdZBMYaqCw8C9w8IBr77MMc25jBxbwi9YpshdzdXJg6pidTx2j/moP6esTVywPz1WtYLRY6DQ7jQm6husUiuw9NVn78NBaTiYStSVhMJkxXbh4h7xgdSvfxMYT/ZiIJW5PoNu4eFSsVaqmvR9r16szEjL+Q8O6faNPFn1M7DqhY6XWypeAAX6e8Zfu++4QhDFg0iYqCYkozj/Jmn1m1lh/1ryeoKi1vwQqF2urrkQ/GLKu1vJo9oskborREnjot7GltT52WUBBCKMgxBSGEgoSCEEJBQkEIoSChIIRQkFAQQihIKAghFCQUhBAKEgpCCAUJBSGEgoSCEEJBQkEIoSChIIRQkFAQQihIKAghFCQUhBAKEgpCCAUJBSGEgoSCEELh/wE7EtR5CBrAYAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 327.397x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.circuit.library import RealAmplitudes\n",
    "\n",
    "ansatz = RealAmplitudes(num_qubits=dim-1, entanglement='linear', reps=1)  # also simple here!\n",
    "ansatz.draw('mpl', style='iqx')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Putting all togehter "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1350.8x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit = feature_map.compose(ansatz)\n",
    "circuit.draw('mpl', style='iqx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.opflow import Z, I, X, Y\n",
    "hamiltonian = Z ^ Z ^ Z# global Z operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plugged together to $\\langle\\Psi(\\vec\\theta) | \\hat H | \\Psi(\\vec\\theta)\\rangle$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.opflow import StateFn\n",
    "\n",
    "expectation = StateFn(hamiltonian, is_measurement=True) @ StateFn(ansatz)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training\n",
    "For the training, I used mini-batches and my cost function is just the difference between the squared value of my output and the target output. The optimizer with better performance was the AdamOptimizer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import Aer\n",
    "from qiskit.utils import QuantumInstance\n",
    "\n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "q_instance = QuantumInstance(backend, shots = 1000, seed_simulator = 2718, seed_transpiler = 2718)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results\n",
    "Below, I show the results for the different experiments. Even though I work with many different architectures, neither of them was good enough to get close to the performance of the ANN. The minimum error I got was for experiment K with mre = 6.8% and a similar error for the other experiments in Table 1 (with exception of experiment F).\n",
    "The parameters used in this model were 3*3*4*3 = 108 parameters. With the ANN in paper [1], we used 11 neurons which means 88Weights + 12Bias  = 100 parameters. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.circuit.library import EfficientSU2\n",
    "from qiskit.opflow import PauliExpectation, CircuitSampler\n",
    "\n",
    "tfi_sampler = CircuitSampler(q_instance)\n",
    "exp = StateFn(hamiltonian, is_measurement=True).compose(StateFn(circuit))  \n",
    "\n",
    "def evaluate_tfi(params):\n",
    "    cost = 0\n",
    "    for i, inputs in enumerate(train_input):\n",
    "        parameters = np.concatenate((inputs, params))\n",
    "        value_dict = dict(zip(circuit.parameters, parameters))\n",
    "        result = tfi_sampler.convert(PauliExpectation().convert(exp), params=value_dict).eval()\n",
    "#         cost += ((1 + result.real)/2 - train_target[i]) ** 2\n",
    "        result = (1 + result.real)/2\n",
    "        cost += (1 - result/train_target[i])\n",
    "    return cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mre: 47.512337135887826\n",
      "mre: 41.837601778480014\n",
      "mre: 45.315732739312246\n",
      "mre: 43.72524047627117\n",
      "mre: 45.207331910119066\n",
      "mre: 41.54326405328483\n",
      "mre: 45.40463156875099\n",
      "mre: 42.34757174142169\n",
      "mre: 44.27253472399653\n",
      "mre: 44.86467122902584\n",
      "mre: 44.625784990268\n",
      "mre: 42.200907686590725\n",
      "mre: 42.53227877126178\n",
      "mre: 47.104209132409075\n",
      "mre: 43.45471251564628\n",
      "mre: 42.96012996881668\n",
      "mre: 45.1203970250026\n",
      "mre: 39.768167809781964\n",
      "mre: 42.26407937782576\n",
      "mre: 42.041888607850105\n",
      "mre: 46.504986497208975\n",
      "mre: 40.71197915689136\n",
      "mre: 45.207331910119066\n",
      "mre: 41.54326405328483\n",
      "mre: 42.041888607850105\n",
      "mre: 42.26407937782576\n",
      "mre: 43.45471251564628\n",
      "mre: 42.96012996881668\n",
      "mre: 44.44496671593243\n",
      "mre: 40.201143808009576\n",
      "mre: 46.36623371849685\n",
      "mre: 42.790013867819155\n",
      "mre: 44.47846707055884\n",
      "mre: 40.07164219147431\n",
      "mre: 46.36623371849685\n",
      "mre: 42.790013867819155\n",
      "mre: 44.01777507226769\n",
      "mre: 46.024362415574366\n",
      "mre: 45.1203970250026\n",
      "mre: 39.768167809781964\n",
      "mre: 44.850379346863996\n",
      "mre: 42.73220798629418\n",
      "mre: 40.317550999993244\n",
      "mre: 46.90847781876431\n",
      "mre: 43.426505038531666\n",
      "mre: 43.630453749045955\n",
      "mre: 47.104209132409075\n",
      "mre: 42.53227877126178\n",
      "mre: 40.201143808009576\n",
      "mre: 44.44496671593243\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mre: 12.383316266672496\n",
      "mre: 12.371497547702454\n",
      "mre: 11.357472146074949\n",
      "mre: 11.357472146074949\n"
     ]
    }
   ],
   "source": [
    "from qiskit.algorithms.optimizers import SPSA\n",
    "np.random.seed(0)\n",
    "\n",
    "tfi_init = np.random.rand(ansatz.num_parameters)\n",
    "\n",
    "autospsa_loss = []\n",
    "def autospsa_callback(nfev, x, fx, stepsize, accepted):\n",
    "    autospsa_loss.append(fx)\n",
    "    \n",
    "autospsa_new = SPSA(maxiter=100, learning_rate=None, perturbation=None, callback=autospsa_callback)\n",
    "\n",
    "result = autospsa_new.optimize(tfi_init.size, evaluate_tfi, initial_point=tfi_init)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wVaCh6XQvYG2Msa7p9GJgYIYztKoRvUbw0bKPkp3KzMqW3KxcfvDhH/DoGY/ytXFfoyiniJtm3cRblW9lZH+SJElKL2NrmkMIJwHLY4wzQwhHvo/LXwhcCDB48ODWDdcO9OvSj0/t9yk+td+nWL5pOT3ye1BbX8t1z1/HAb0P4OS9Tk46oiRJUqeRyRcCjgcmhhBOBPKBbsBPge4hhOym2eZSYIfvEBJjnAxMBqioqOjUh5ToU9gHgLqGOt5Y+wb3v3E/w3oMY3jP4QknkyRJ6hwytjwjxviNGGNpjLEMOBt4PMZ4LvAEcEbT2c4H7s9Uho4mO5XN9R++nqLcIi578jLW1axLOpIkSVKnkMRxmr8GXBZCeIPGNc63JpCh3SopKOFHR/6Idza8wzef/iYNsSH9hSRJkvSBtElpjjE+GWM8qenr+THGg2OMe8cYz4wxVrdFho7kwD4HcsW4K5i+dDrz185POo4kSVKHl/E3N1FmfHLfT3L0oKPp37V/0lEkSZI6PN9Gu50KIdC/a39ijNz7+r0s27gs6UiSJEkdljPN7dyqqlVc9/x19MrvxT499gEgELh07KUM7jaY2oZaquuq6ZrbNeGkkiRJ7Zczze1cSUEJPzzih3TJ6cKi9YtYuG4hC9YtoKa+hhgjl0y9hMunXU59Q33SUSVJktotZ5o7gMNLD+fw0sN3OHbckOP43nPf48ZZN/Klg77UxskkSZI6BmeaO7jTh53O6fuczq9e/hVTF05NOo4kSVK7ZGnuBCYdMolRvUbxzWe+yfxKD1EnSZK0uyzNnUBuVi43HHUDQ4uHUltfm3QcSZKkdsc1zZ1Evy79uOPEOwghABBjbP5akiRJu+ZMcycSQqCuoY7//sd/89s5v006jiRJUrvhTHMnkxWyWFu9lj+99icCgU/t9ylyUjlJx5IkSdqjOdPcyYQQ+P6Hvs/hAw/nxzN/zCce/AQzls1IOpYkSdIezdLcCRXmFPLzo3/Oz476GZtqN3HFtCuoqqtKOpYkSdIey+UZnVQIgaMGH8WhAw5lQeUC8rPzqWuo46H5D3HS0JPITnnXkCRJ2sKZ5k6uILuAEb1GAPD4osf59jPf5rN//SwrNq1IOJkkSdKew9KsZscNOY6rJ1zN3FVzOfPBM13rLEmS1MTSrGYhBCbuNZE7P3YnRblFfO5vn+Oe1+5JOpYkSVLiLM3azj499uGuj93FR8s+yr499006jiRJUuJ8tZd2qGtuV6474rrm07e+fCt9CvvQr0s/+hT2oU9hHwqyCxJMKEmS1HYszUqrsrqSO+fdyfLNy7fZfv5+53PFuCuoa6jj6ulXM7DrQAZ0GcCAro0fJQUlpIJ/zJAkSe2fpVlpFecV8/DpD7Nk/RLe3fQuKzavYPmm5ezXaz8A1lSt4fFFj7O6avU2l7tg1AVcOvbSJCJLkiS1KkuzWiQvK4+h3YcytPvQ7cZ6F/Zm2lnT2FS7iaUbl/LOhndYsmEJR5QeAcDzy57nT6/9iXNHnMsBvQ9o6+iSJEkfmKVZraYwp5C9uu/FXt332mb7kg1LeGrxU/zfW//H6JLRfHb0Zzlm8DEJpZQkSdp9LjhVxp2696lMPXMqkw6ZxLqadXzlia+woHJB0rEkSZJazNKsNlGYU8g5+57DzcfeTElBCe9seCfpSJIkSS3m8gy1qdKiUh4/83FCCElHkSRJajFnmtXmQgjEGGmIDUlHkSRJahFLs9rc62te57i7j+O5d55LOookSVKLWJrV5kqLSllTtYanlzyddBRJkqQWsTSrzRVkFzCu3zieeeeZpKNIkiS1iKVZiRg/cDxvVb7Fkg1Lko4iSZKUlqVZiRg/cDwAzyxxtlmSJO35LM1KRHm3cj4z8jMM6zEs6SiSJElpeZxmJSKEwGUVlyUdQ5IkqUWcaVZiGmID81bNY/H6xUlHkSRJ2iVLsxKzuW4zn/zLJ/nTa39KOookSdIuWZqVmC45XTiw74G+GFCSJO3xLM1K1PgB43l1zass37Q86SiSJEk7ZWlWoiYMnADAs+88m3ASSZKknbM0K1HDegyjpKCEZ5dYmiVJ0p7LQ84pUSEEbj72ZgYVDUo6iiRJ0k5ZmpW44T2HJx1BkiRpl1yeocTFGJn80mTuff3epKNIkiTtkDPNSlwIgWmLp0GE0/Y5Lek4kiRJ23GmWXuECQMm8PLKl3l04aOs2rwq6TiSJEnbsDRrj/DR8o/SNacrlz15GUf+8UgWrlsIwPzK+by+5nVijAknlCRJnZnLM7RHGFo8lMc/8TjzVs/jpRUvNR9N47bZt3HvG/dy1KCj+N6HvkfP/J4JJ5UkSZ1RaA8zeBUVFXHGjBlJx1AClmxYwv+99X/cNOsmuuV246rxV3F46eFJx5IkSR1QCGFmjLFiR2Muz9AebWDXgXxu9Oe462N30SO/BxdPvZhHFjySdCxJktTJuDxD7cLwnsP5/Um/53dzfseHSz8MQG1DLTmpnISTSZKkzsDSrHYjLyuP/9z/PwHYVLuJcx8+l6yQRSTSEBuIMfLxfT7OeSPPSzipJEnqaCzNapfqYz0H9zuYpRuXEgikQooQAr0KelFTX8OCdQsY1mNY0jElSVIHYWlWu1SUW8Q3DvnGDsdumnUTt7x0C8+d8xyFOYVtnEySJHVEvhBQHc7IXiNpiA28uubVpKNIkqQOImOlOYSQH0L4ZwjhxRDCnBDCfzVtLw8hTA8hvBFC+EMIITdTGdQ57ddrPwBmr5ydcBJJktRRZHKmuRo4OsZ4ADAGOD6EcChwHXBDjHFvYA3w2QxmUCfUu7A3fQr7MGfVnKSjSJKkDiJjpTk22tB0MqfpIwJHA3c3bZ8CnJqpDOq8RvYayZyVlmZJktQ6MvpCwBBCFjAT2Bu4EXgTWBtjrGs6y2Jg4E4ueyFwIcDgwYMzGVMd0AWjLqCmvibpGJIkqYPIaGmOMdYDY0II3YF7gX1347KTgcnQ+DbaGQmoDmtMnzFJR5AkSR1Imxw9I8a4FngCOAzoHkLYUtZLgSVtkUGdS4yRvy/+O/9a/q+ko0iSpA4gk0fP6N00w0wIoQA4DphHY3k+o+ls5wP3ZyqDOq8QAtdMv4Y75t2RdBRJktQBZHJ5Rn9gStO65hTwxxjjQyGEucDvQwj/DfwLuDWDGdSJ+WJASZLUWjJWmmOMLwEH7mD7fODgTO1X2mJkyUj+tvBvrK1aS/f87knHkSRJ7ZjvCKgOa2SvkQDMXTU34SSSJKm9szSrwxrRawQAc1dbmiVJ0geT0UPOSUnqltuNB099kEFFg5KOIkmS2jlLszq0suKypCNIkqQOwOUZ6tBeX/M6Vz13Fas2r0o6iiRJascszerQ1tWs44+v/ZE5qzz0nCRJev8szerQRvQcQSqkPF6zJEn6QCzN6tAKcwoZWjyU2atmJx1FkiS1Y5ZmdXj79dqPOSvnEGNMOookSWqnLM3q8Eb2Gkl+dj7ratYlHUWSJLVToT3MvlVUVMQZM2YkHUPtVIyREELSMSRJ0h4uhDAzxlixozFnmtXhWZglSdIHZWlWp/DjGT/mm09/M+kYkiSpnbI0q1NYV7OOaYun+WJASZL0vlia1SmMLBlJZXUlSzYsSTqKJElqhyzN6hRG9hoJ4PGaJUnS+2JpVqewT/d9yEnlMHfl3KSjSJKkdig76QBSW8jJyuGkoSfRt0tfAL737PdYU7WGrFQWqZCiX2E/Lhh9AT3zeyacVJIk7Ykszeo0vj/++81fv7vpXd7d9C4NDQ000MDUhVNZXbWaaw6/JsGEkiRpT2VpVqf0y2N/uc3p+WvnU5hTCMCidYtYV7OOUSWjkogmSZL2QK5ploCh3YfSr0s/AH4x6xd88i+f5PvPfZ/K6sqEk0mSpD2BpVl6j+8c+h3OHXEuf379z0y8byKvrn416UiSJClhlmbpPbrmduVrB3+NP5z0B7JT2XzhsS+weP3ipGNJkqQEWZqlnRjecziTj5vM/iX7U5xXnHQcSZKUIF8IKO3CXt334qdH/xSAqroqahpq6JbbLeFUkiSprTnTLLVAjJFLHr+EL079IpvrNicdR5IktTFLs9QCIQTOGHYGs5bP4vInL6e2oTbpSJIkqQ21qDSHEL4cQugWGt0aQnghhPCRTIeT9iQfLfso3z7s2zy15Cm+9fS3aIgNSUeSJEltpKUzzRfEGNcBHwF6AJ8Grs1YKmkPdeawM/nimC/y8FsP8493/pF0HEmS1EZa+kLA0PT5ROD2GOOcEELY1QWkjursfc9m+abldM/vnnQUSZLURlpammeGEP4GlAPfCCEUAf5tWp1ScV4x3z7s20nHkCRJbailpfmzwBhgfoxxUwihJ/CZjKWS9nB1DXWsrlpNn8I+SUeRJEltoKVrmg8DXo0xrg0hfAr4FlCZuVjSnu17z36Pcx46J+kYkiSpjbS0NP8S2BRCOAC4HHgT+F3GUkl7uCHdhrB883I21W5KOookSWoDLS3NdTHGCJwC/CLGeCNQlLlY0p6trLgMgIXrFiYbRJIktYmWlub1IYRv0Hioub+EEFJATuZiSXu2Id2GAJZmSZI6i5aW5rOAahqP17wMKAV+mLFU0h5ucNFgAoG31r2VdBRJktQGWlSam4ryHUBxCOEkoCrG6JpmdVr52fl87eCvMWHAhKSjSJKkNtDSt9H+BPBP4EzgE8D0EMIZmQwm7enOHXEuo3uPTjqGJElqAy09TvM3gXExxuUAIYTewGPA3ZkKJu3pKqsreW3Na1T0rcA3yJQkqWNr6Zrm1JbC3GTVblxW6pAemv8QF/z1AlZVrUo6iiRJyrCWzjQ/EkL4K3BX0+mzgIczE0lqH8q6lQGwoHIBJQUlyYaRJEkZ1dIXAl4JTAb2b/qYHGP8WiaDSXs6j9UsSVLn0dKZZmKM9wD3ZDCL1K70K+xHbirX0ixJUiewy9IcQlgPxB0NATHG2C0jqaR2ICuVxeBugz1WsyRJncAuS3OM0bfKlnZh0iGT6Jbrc0dJkjq6Fi/PkLS9cf3GJR1BkiS1AQ8bJ30Aqzav4sE3H2R11eqko0iSpAyyNEsfwKL1i5j09CRmr5yddBRJkpRBlmbpA9hyrGaPoCFJUsdmaZY+gO553emW240FlQuSjiJJkjLI0ix9ACEEyorLnGmWJKmDszRLH1BZtzIWrFuQdAxJkpRBGSvNIYRBIYQnQghzQwhzQghfbtreM4TwaAjh9abPPTKVQWoLXxzzRe448Y6kY0iSpAzK5ExzHXB5jHE/4FDg/4UQ9gO+DkyNMe4DTG06LbVb/bv2p2+XvknHkCRJGZSx0hxjXBpjfKHp6/XAPGAgcAowpelsU4BTM5VBagsbazfy65d/zcsrXk46iiRJypA2WdMcQigDDgSmA31jjEubhpYBTtGpXcsKWfz0hZ/yzDvPJB1FkiRlSMZLcwihK3AP8JUY47qtx2KMEYg7udyFIYQZIYQZK1asyHRM6X3Lz86nf5f+HkFDkqQOLKOlOYSQQ2NhviPG+Oemze+GEPo3jfcHlu/osjHGyTHGihhjRe/evTMZU/rAhnQb4rGaJUnqwDJ59IwA3ArMizH+eKuhB4Dzm74+H7g/UxmktjKk2xAWrltI4x9PJElSR5PJmebxwKeBo0MIs5o+TgSuBY4LIbwOHNt0WmrXyovL2Vy3mcrqyqSjSJKkDAjtYWasoqIizpgxI+kY0k5V1VWRlcoiJ5WTdBRJkvQ+hRBmxhgrdjSW3dZhpI4oPzs/6QiSJCmDfBttqZX84PkfcM9r9yQdQ5IkZYClWWolzy55lmmLpyUdQ5IkZYClWWolW46gIUmSOh5Ls9RKyorLWLR+EfUN9UlHkSRJrczSLLWSsm5l1DXU8c6Gd5KOIkmSWpmlWWol5cXl9O/Sn7XVa5OOIkmSWpmHnJNayZg+Y/jbGX8D4IlFTwAwfuB4crNyk4wlSZJagaVZyoApc6cw892ZFOUUcdTgozi+7Hg+NOBDZKWyko4mSZLeB5dnSBnwq4/8il8e+0uOHnw0Tyx6gounXsxPXvhJ0rEkSdL75EyzlAE5qRwmDJzAhIETqKmv4X/n/S+H9Dsk6ViSJOl9sjRLGZablcsFoy5IOoYkSfoAXJ4htZE5q+Zw+9zbk44hSZLeB0uz1EaefPtJfvj8D1m2cVnSUSRJ0m6yNEtt5JS9TiESeeDNB5KOIkmSdpOlWWojpUWljOs3jvvfuJ8YY9JxJEnSbrA0S23o1L1PZdH6Rbyw/IWko0iSpN1gaZba0LGDj6V/l/4s3bg06SiSJGk3eMg5qQ0V5hTyyOmPkAo+X5UkqT3xf26pjaVCihgja6rWJB1FkiS1kDPNUgIunnoxm+s2c9vxtyUdRZIktYAzzVICxvYdy8x3Z/L2ureTjiJJklrA0iwl4OShJ5MKKe57876ko0iSpBawNEsJ6NulL4cNOIwH3nyA+ob6pONIkqQ0LM1SQk7d+1SWbVzG9GXTk44iSZLS8IWAUkKOGnQUNxx5A+P6jmPOqjnc/OLN9MzvSc/8nvTI60GP/B4cNuAwSgpK2FS7iU11myjOLSY7lc3mus2sr1lPz4Ke5KRyWLhuIa+ufpVued3okdeDnvk96Z7XnZysnKS/TUmSOgRLs5SQvKw8jh1yLACbajfxzoZ3mLNyDmuq1lAX6wCYcvwUSgpKmLpoKpOengRAVsiiPjYu6bjvlPvYq/tePLX4Ka57/rrt9vHX0//KgK4DmL92PiEEyovL2+i7kySpY7E0S3uAcf3Gcc/EewCIMbKuZh1rq9fSp7APAKNKRjHpkEmsq15HdX01XXO70jWnKz3zewLwsaEfY1y/cayrWceaqjWsqVrD6urVzeO/mPULHl34KAf1OYjT9jmNjwz5CIU5hcl8s5IktUMhxph0hrQqKirijBkzko4htVsrN6/kgTcf4N7X72XBugV0yenCp0Z8ii8e+MWko0mStMcIIcyMMVbsaMyZZqkTKCko4YJRF/CZkZ/hheUv8OfX/0x+dj7w75nt4rzihFNKkrTnsjRLnUgIgbF9xzK279jmbY8seISr/nEVX9j/C5yz7zm+eFCSpB3wkHNSJzesxzD2770/P5zxQ065/xQeW/gY7WHZliRJbcnSLHVye3Xfi5uPvZlfHvtL8rLyuPTJS/nG099oHn/2nWdZtnGZRVqS1Km5PEMSABMGTuDQ/ofyl/l/aT6yxoaaDXz+0c8D0DO/JyN7jeTAPgdy1KCj2LvH3knGlSSpTVmaJTXLTmVzyt6nNJ/Oy87j9hNuZ97qecxdNZeXV7zMU0ueoii3iL177M2yjcuYMmcKxw05joP6HpRgckmSMsvSLGmnclI5jOkzhjF9xjRvW1u1lqxUFgDz187nT6/9ibteuYvbjr9tm/NJktSRuKZZ0m7pnt+dotwiAD408EM8/onH6d+lP1dMu4K1VWuTDSdJUoZYmiV9IN1yu3H9kdezumo1k56eRENsSDqSJEmtztIs6QMb2WskV467ktqGWjbXbU46jiRJrc41zZJaxdnDz+YTwz7RvN5ZkqSOxJlmSa0ihEBWKosVm1bw1b9/lTVVa5KOJElSq7E0S2pVKzevZOrCqa5vliR1KJZmSa1qRK8RfO3gr/H0kqe5adZNLKhcQG1DbdKxJEn6QFzTLKnVnTnsTJ5f9jy3vHQLt7x0C3857S8M7jaYKXOmcMuLt1CYU0hBdgF5WXnkZ+dz4zE3UpxXzGMLH6NLThcOG3BY0t+CJEnbsDRLanUhBK6ZcA0n73UyldWVlBSUADCsxzAm7j2RjbUbqa6rpqq+iqq6KnJSOQC8tPIlfjv7txw16CiurLiSQd0GJfltSJLULMQYk86QVkVFRZwxY0bSMSRlWHV9NbfPvZ3JL02mrqGO8/Y7j//c/z/pktMl6WiSpE4ghDAzxlixozHXNEvaY+Rl5fG50Z/jodMe4oTyE7h19q3c/drdAGyu28zG2o3UNtTSHp7sS5I6FmeaJe2xZq+czT499iEvK48bZt7Ab2b/BoBAIC8rj9ysXB478zEKsgu49/V7mbViFr3ye9Ezvyddc7uSl5XHCeUnADBn1RxWbV5FKqQIBKCxpFf0a5xQmLdqHis2r6CuoY76WE9dQx0F2QUcOehIAP6++O+s2ryqcf+h8fK98ntxeOnhAMxaPouq+salJjFGahtq6ZbbjZElIwF4YtET1DTUUJBdQH5WPnnZefTM78mgosYlKJXVleSkcsjLytvhsa6r6qqorq+mpr6GmoYaYox0zelK9/zuxBhZvH4xBOia05Wi3CKyU3vO6rv6hnoaYgOpkGr8+Tf9/GKMhBCoqqtiddVqquqrqKmvob6hHoDy4nIKcwpZtXkV72x4h6xUFvlZ+eRm5ZKfnU/3vO6t8n3WNdQ17jfWN98/UiFFfnb+NjkldXy7mmnec36rStJ7jCoZ1fz1EaVH0COvBzUNNVTXV1NbX0ttQy0F2QUAvL3+bZ5e/DSrq1ZTF+sAKMopai7Nv3n5N/xt4d+2uf6+hX157MzHAPjZv37G00ue3ma8vLi8uTTf+vKtvLD8hW3G9y/Zv7k0//c//ptX17y6zfgh/Q7h1x/9NQA/eP4HLN6weJvxowcdzU+P/ikAE++byOqq1QBkh2xys3KZuNdEvnnoNwE47M7Dmr+vLc7Z9xwmHTKJ2oZaTrz3xG3GuuR04YJRF3Dh/hdSWV3JldOu5L0+PuzjHF92PEs3LOWKaVdQ21Db/BFj5OIxF/OxoR9jfuV8Ln/yckIINP8LgUsOvIQjSo9g7qq5fOeZ71BVX8Xmus1U1TWuVb/hqBs4ovQInl7yNF98/IvN+91y+V9/5NeM6zeOxxY9xjee+sZ2+X5/0u8Z2WskUxdN5ap/XLXd+AOnPkB5cTlT5kzhJy/8hNxULjlZOY2fUznc8bE7KCkoYcqcKfxuzu+oj43lvS7WUddQx7SzplGQXcCPZvyI/533v9tcdyDw0vkvAfC9577HfW/cR04qp/mjOK+YB097EICr/3E10xZPIxJpiA3EGOld2Js/nPQHAH72ws94ZfUrFGQXkJ3Kpq6hjj6FffjawV8D4H+m/w+vrXkNgEjjRNbQ4qF857DvAPD1p77OgsoFzU/mGmIDI3uN5JrDrwHgymlXsrpqdfP3HgiM7j2az43+XPP4+pr1pEKqMX9WDhV9Kzh737Ob89c01FDXUEdtQy11DXWMHzCe04edTm1DLZc8fglEGr+3pn8nlp/Ix/f5OJtqN/GtZ75FdsgmK5XV/DM4vux4jh58NKs2r+Ka6Y05t9x/AE7Z+xQmDJzA0g1LuX7G9c2Xq4/1xBg5d8S5HDbgMN5Y8wb/88//ad6+5TCWXzroS4zrN46XVrzEdc9fR4yR+lhPfUM99bGe7x72Xcb0GcMzS55p3v+WDAA/OOIH7NdrP55Y9AQ3zrqRVEiRFbJIpRr/AH/thGsZ1G0Qjyx4hN/O/i0xxuaMDbGBW467hT6Fffjjq3/krlfuIi8rr/mFzXlZeVw94WqKcov464K/8vfFf9/mfhWJXDX+KlIhxR3z7mDqoqnNv9NSIUVeVh5TTpgCwK9e+hXPLX2OFI1PNlMhRVFuEdd/+HoAbpp1EzPfnbnNbdezoCc3H3szAN955ju8uOLF5vtWjJGybmX8/JifA3DRYxcxd9VcoPH3TnYqm1Elo/jRkT8C4IppV7Bk/RJSqcafTyBwQO8DuKziMgC+/cy3qayuJDuVTXbIJpVKMbpkNOeOOBeAzz/6edZVr6O6obr5yeexg4/l4jEXA3D2Q2c33+e3OLH8RM4fef52j/c9gaVZUrswtu9YxvYdu9PxLx30Jb500JdoiA2sr1nPhtoN2xwn+itjv8J/jPwP6mN987YtL0AEuHzs5Vx0wEWNv/ybPgqyCprHf3Tkj6ipr2n+Bd8QG7a5/NUTrmZ9zXpqGxr/48tOZVOcW9w8Pvkjk5tf/LilWHbP6948/v/G/D821G5onEmub3xiMLzn8G3yb/kPNSeVQyqkKC8uByArZHHNhGtoiA1sqN3Auup1rKtZx/Ae/778prpN2/3MausbDwWYncqmKLeouVBlh2xCCPTM79n8cyovLm8uhFv+bXnCkpPKoX/X/hRkFZCfnd/8MaDLAADKisu45MBLmgvHlo9+hf0AOKD3AXz/Q99vLh5Zqcb/nLfMwh8+8HBuPObG5hnh6vpqquurm19gOqpkFOfvdz41DTXNT6ZqG2rJy8oDoLSolAmlE5qLUVbIav4ZAnx40IfpXdibrJDVfNtu/R/5kaVHUlJQ0ni9Tde/5bwAe3Xfi011m/49k06gKLeoebyqvopVVavYXLeZ+oZ6slPZ1DTUNI/Xx3oicZsnJFuyQeNfD3rm9yQrldVYTEKKod2HNo+nQoq6hjo21W6iuqGaQGBg0cDm8crqSjbUbmgu3bUNtc23DcC0xdOoj/XkpHLICllkp7Kb7zuBQGVVZWOeAKmmVZ1b7ju1DbXMXzu/+YnIlu+/om9F8/f2xto3mgvbFkdUHQFATUMNb6x9o/kvECkaf4ZVdVVAY9Hbcr3ZqWwINP8lACArlUXXnK4EGt9cKRVSZIfs5r8SdMvt1vzke+vbtDC7EICCnAL6d+3fWNibCveW2wAgPyufXvm9mm+TLfvesv9eBb0o61ZGVX3jX4I21GxgZf3K5vElG5Yw892ZzY+bLT/TuoY6crNym/8K0zWnK9l52cQYt/tLU31DPfU0nq+BbY99X1Pf+GQnJ5XT/KSsb2Hf5vEBXQewsXbjNveVAV3/fduP7TuW/l36A41/calrqGt+3G35+W3I30BDQ+O+33vs/RWbV7Bi04rmn11dQ902v/dys3Lpnt+98clcCMQY6ZHfo3m8pKBku9JcmFPInsrlGZIkSRK+EFCSJEn6QCzNkiRJUhqWZkmSJCmNjJXmEMJvQgjLQwizt9rWM4TwaAjh9abPPXZ1HZIkSdKeIJMzzbcBx79n29eBqTHGfYCpTaclSZKkPVrGSnOM8e/A6vdsPgWY0vT1FODUTO1fkiRJai1tvaa5b4xxadPXy4C+OztjCOHCEMKMEMKMFStWtE06SZIkaQcSeyFgbDxA9E4PEh1jnBxjrIgxVvTu3bsNk0mSJEnbauvS/G4IoT9A0+flbbx/SZIkabe1dWl+ANjyhuLnA/e38f4lSZKk3ZbJQ87dBTwHDA8hLA4hfBa4FjguhPA6cGzTaUmSJGmPlp2pK44xnrOToWMytU9JkiQpE3xHQEmSJCkNS7MkSZKUhqVZkiRJSsPSLEmSJKVhaZYkSZLSsDRLkiRJaViaJUmSpDQszZIkSVIalmZJkiQpDUuzJEmSlIalWZIkSUrD0ixJkiSlYWmWJEmS0rA0S5IkSWlYmiVJkqQ0LM2SJElSGpZmSZIkKQ1LsyRJkpSGpVmSJElKw9IsSZIkpWFpliRJktKwNEuSJElpWJolSZKkNCzNkiRJUhqWZkmSJCkNS7MkSZKUhqVZkiRJSsPSLEmSJKVhaZYkSZLSsDRLkiRJaViaJUmSpDQszZIkSVIalmZJkiQpDUuzJEmSlIalWZIkSUrD0ixJkiSlYWmWJEmS0rA0S5IkSWlYmiVJkqQ0LM2SJElSGpZmSZIkKQ1LsyRJkpSGpVmSJElKw9IsSZIkpWFpliRJktKwNEuSJElpWJolSZKkNCzNkiRJUhqWZkmSJCkNS7MkSZKUhqVZkiRJSsPSLEmSJKVhaZYkSZLSsDRLkiRJaSRSmkMIx4cQXg0hvBFC+HoSGSRJkqSWavPSHELIAm4ETgD2A84JIezX1jkkSZKklspOYJ8HA2/EGOcDhBB+D5wCzN3ZBWreeouFnz5vm21FJxxPz09+kobNm3n7ws9vd5ni006j+8dPo27NGpZ86cvbjfc452y6nXgitUuX8s5Xv7bdeM/PfIaio4+iev5bLPvud7cbL7noC3T50IeomjePd6/5n+3Ge196KYUHHcimF/7Fihtu2G6876RvkD9iBBuffZaVv7x5u/F+//Vf5A0tZ/3jT7D6t7/dbnzAD64jp39/1j38MGvu+v124wN/9lOye/Rg7Z/vpfLee7cbHzT5FlIFBay+807W/98j240Puf13AKy69TdsePLJbcZCfj6DfzUZgBU33cSm5/6xzXhW9+6U/vxnACz/0Y/ZPGvWNuPZ/fox8Ic/AGDZNddQPe+VbcZzy8rof9X3AVj67e9Qs2DBNuN5I/al36RJACy58qvULVu2zXjBmDH0ufwyABZf8iXq167dZrzwsEPpffHFACz6zwuJVVXbjHc98kh6ffYCgO3ud+B9z/ue9z3ve9733sv7nvc96Jj3va0lsTxjIPD2VqcXN23bRgjhwhDCjBDCjNra2jYLJ0mSJL1XiDG27Q5DOAM4Psb4uabTnwYOiTF+cWeXqaioiDNmzGiriJIkSeqEQggzY4wVOxpLYqZ5CTBoq9OlTdskSZKkPVISpfl5YJ8QQnkIIRc4G3gggRySJElSi7T5CwFjjHUhhC8CfwWygN/EGOe0dQ5JkiSppZI4egYxxoeBh5PYtyRJkrS7fEdASZIkKQ1LsyRJkpSGpVmSJElKw9IsSZIkpWFpliRJktKwNEuSJElpWJolSZKkNCzNkiRJUhqWZkmSJCmNEGNMOkNaIYQVwMIEdl0CrExgv2p73tadh7d15+Ft3Xl4W3cemb6th8QYe+9ooF2U5qSEEGbEGCuSzqHM87buPLytOw9v687D27rzSPK2dnmGJEmSlIalWZIkSUrD0rxrk5MOoDbjbd15eFt3Ht7WnYe3deeR2G3tmmZJkiQpDWeaJUmSpDQszTsRQjg+hPBqCOGNEMLXk86j1hNCGBRCeCKEMDeEMCeE8OWm7T1DCI+GEF5v+twj6az64EIIWSGEf4UQHmo6XR5CmN702P5DCCE36YxqHSGE7iGEu0MIr4QQ5oUQDvNx3TGFEC5t+v09O4RwVwgh38d2xxBC+E0IYXkIYfZW23b4OA6NftZ0m78UQjgok9kszTsQQsgCbgROAPYDzgkh7JdsKrWiOuDyGON+wKHA/2u6fb8OTI0x7gNMbTqt9u/LwLytTl8H3BBj3BtYA3w2kVTKhJ8Cj8QY9wUOoPF293HdwYQQBgJfAipijKOALOBsfGx3FLcBx79n284exycA+zR9XAj8MpPBLM07djDwRoxxfoyxBvg9cErCmdRKYoxLY4wvNH29nsb/WAfSeBtPaTrbFODURAKq1YQQSoGPAb9uOh2Ao4G7m87i7dxBhBCKgSOAWwFijDUxxrX4uO6osoGCEEI2UAgsxcd2hxBj/Duw+j2bd/Y4PgX4XWz0D6B7CKF/prJZmndsIPD2VqcXN21TBxNCKAMOBKYDfWOMS5uGlgF9k8qlVvMT4KtAQ9PpXsDaGGNd02kf2x1HObAC+G3TcpxfhxC64OO6w4kxLgGuBxbRWJYrgZn42O7IdvY4btO+ZmlWpxVC6ArcA3wlxrhu67HYeFgZDy3TjoUQTgKWxxhnJp1FbSIbOAj4ZYzxQGAj71mK4eO6Y2haz3oKjU+UBgBd2P7P+eqgknwcW5p3bAkwaKvTpU3b1EGEEHJoLMx3xBj/3LT53S1/1mn6vDypfGoV44GJIYQFNC6xOprGNa/dm/6kCz62O5LFwOIY4/Sm03fTWKJ9XHc8xwJvxRhXxBhrgT/T+Hj3sd1x7exx3KZ9zdK8Y88D+zS9EjeXxhcYPJBwJrWSpnWttwLzYow/3mroAeD8pq/PB+5v62xqPTHGb8QYS2OMZTQ+hh+PMZ4LPAGc0XQ2b+cOIsa4DHg7hDC8adMxwFx8XHdEi4BDQwiFTb/Pt9zWPrY7rp09jh8Azms6isahQOVWyzhanW9ushMhhBNpXA+ZBfwmxnh1sonUWkIIE4CngJf591rXSTSua/4jMBhYCHwixvjeFyOoHQohHAlcEWM8KYQwlMaZ557Av4BPxRirE4ynVhJCGEPjiz5zgfnAZ2icHPJx3cGEEP4LOIvGoyH9C/gcjWtZfWy3cyGEu4AjgRLgXeC7wH3s4HHc9KTpFzQuz9kEfCbGOCNj2SzNkiRJ0q65PEOSJElKw9IsSZIkpWFpliRJktKwNEuSJElpWJolSZKkNCzNkpSgEMKzTZ/LQgifbOXrnrSjfUmSdp+HnJOkPcDWx5LejctkxxjrdjG+IcbYtRXiSVKn50yzJCUohLCh6ctrgcNDCLNCCJeGELJCCD8MITwfQngphPD5pvMfGUJ4KoTwAI3vgkYI4b4QwswQwpwQwoVN264FCpqu746t99X07lk/DCHMDiG8HEI4a6vrfjKEcHcI4ZUQwh1Nbx5ACOHaEMLcpizXt+XPSJL2BNnpzyJJagNfZ6uZ5qbyWxljHBdCyAOeCSH8rem8BwGjYoxvNZ2+oOndsQqA50MI98QYvx5C+GKMccwO9vVxYAxwAI3vuvV8COHvTWMHAiOBd4BngPEhhHnAacC+McYYQujeut+6JO35nGmWpD3TR4DzQgizaHyL917APk1j/9yqMAN8KYTwIvAPYNBW59uZCcBdMcb6GOO7wDRg3FbXvTjG2ADMAsqASqAKuDWE8HEa365WkjoVS7Mk7ZkCcEmMcUzTR3mMcctM88bmMzWuhT4WOCzGeADwLyD/A+y3equv64Et66YPBu4GTgIe+QDXL0ntkqVZkvYM64GirU7/FbgohJADEEIYFkLosoPLFQNrYoybQgj7AoduNVa75fLv8RRwVtO66d7AEcA/dxYshNAVKI4xPgxcSuOyDknqVFzTLEl7hpeA+qZlFrcBP6VxacQLTS/GWwGcuoPLPQJ8oWnd8as0LtHYYjLwUgjhhRjjuVttvxc4DHgRiMBXY4zLmkr3jhQB94cQ8mmcAb/sfX2HktSOecg5SZIkKQ2XZ0iSJElpWJolSZKkNCzNkiRJUhqWZkmSJCkNS7MkSZKUhqVZkiRJSsPSLEmSJKVhaZYkSZLS+P9rG9T9t8XZRwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_loss():\n",
    "    plt.figure(figsize=(12, 6))\n",
    "#     plt.plot(gd_loss, 'tab:blue', label='vanilla gradient descent')\n",
    "#     plt.plot(qng_loss, 'tab:green', label='quantum natural gradient')\n",
    "#     plt.plot(spsa_loss, 'tab:blue', ls='--', label='SPSA')\n",
    "    plt.plot(autospsa_loss, 'tab:green', ls='--', label='SPSA')\n",
    "    plt.axhline(0, c='tab:red', ls='--', label='target')\n",
    "    plt.ylabel('loss')\n",
    "    plt.xlabel('iterations')\n",
    "    plt.legend()\n",
    "    \n",
    "plot_loss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.circuit.library import EfficientSU2\n",
    "from qiskit.opflow import PauliExpectation, CircuitSampler\n",
    "\n",
    "H_tfi = Z ^ Z ^ Z # TODO \n",
    "efficient_su2 = EfficientSU2(3, entanglement=\"linear\", reps=2)\n",
    "# efficient_su2 = ansatz\n",
    "circuit = feature_map.compose(efficient_su2)\n",
    "tfi_sampler = CircuitSampler(q_instance)\n",
    "exp = StateFn(H_tfi, is_measurement=True).compose(StateFn(circuit))  \n",
    "\n",
    "def evaluate_tfiB(params):\n",
    "    cost = 0\n",
    "    for i, inputs in enumerate(train_input):\n",
    "        parameters = np.concatenate((inputs, params))\n",
    "        value_dict = dict(zip(circuit.parameters, parameters))\n",
    "        result = tfi_sampler.convert(PauliExpectation().convert(exp), params=value_dict).eval()\n",
    "#         cost += ((1 + result.real)/2 - train_target[i]) ** 2\n",
    "        result = (1 + result.real)/2\n",
    "        cost += (1 - result/train_target[i])\n",
    "    print(f\"The Cost: {100*cost/len(train_input)}\")\n",
    "    return cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
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     "text": [
      "The Cost: 57.11716240434645\n",
      "The Cost: 61.17181305444053\n",
      "The Cost: 58.203660856471515\n",
      "The Cost: 55.7465523823077\n",
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      "The Cost: 63.1289050331896\n",
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      "The Cost: 59.88903816438532\n",
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      "The Cost: 25.935001400714146\n",
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      "The Cost: 15.610293767495488\n",
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      "The Cost: 16.94144599007431\n",
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      "The Cost: 10.289240280582503\n",
      "The Cost: 12.133105332201879\n"
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      "The Cost: 8.557118782950779\n",
      "The Cost: 10.97131538419099\n",
      "The Cost: 12.210016935497663\n",
      "The Cost: 8.541472778590293\n",
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      "The Cost: 9.837470761381276\n",
      "The Cost: 9.016582382784417\n",
      "The Cost: 5.609102788392059\n",
      "The Cost: 10.181589198379461\n",
      "The Cost: 11.76697551203107\n",
      "The Cost: 5.513653460916722\n",
      "The Cost: 7.9569819121480325\n",
      "The Cost: 7.1342510764361995\n",
      "The Cost: 5.500941806887107\n",
      "The Cost: 8.341340241361273\n",
      "The Cost: 8.27539510298525\n",
      "The Cost: 5.488605754691618\n",
      "The Cost: 8.295078744436008\n",
      "The Cost: 8.629850321459239\n",
      "The Cost: 5.489588035155883\n",
      "The Cost: 6.37552140997281\n",
      "The Cost: 8.223974995832465\n",
      "The Cost: 5.398536732354898\n",
      "The Cost: 8.595429792420052\n",
      "The Cost: 6.4626463631290765\n",
      "The Cost: 5.184985295762532\n",
      "The Cost: 9.817796607747853\n",
      "The Cost: 11.488663969625055\n",
      "The Cost: 5.2218774604735305\n",
      "The Cost: 8.18099701751458\n",
      "The Cost: 7.990349289623307\n",
      "The Cost: 5.222591783528077\n",
      "The Cost: 8.449221713737705\n",
      "The Cost: 8.612174569881562\n",
      "The Cost: 5.215158193831795\n",
      "The Cost: 9.431652848275643\n",
      "The Cost: 10.712599578139177\n",
      "The Cost: 5.168366125387339\n",
      "The Cost: 8.468071680139767\n",
      "The Cost: 9.052497827582524\n",
      "The Cost: 5.136014879984447\n",
      "The Cost: 9.355453949712745\n",
      "The Cost: 7.486739186864707\n",
      "The Cost: 5.10679443061598\n",
      "The Cost: 8.867623955852604\n",
      "The Cost: 8.101774502871136\n",
      "The Cost: 5.145144793037221\n",
      "The Cost: 8.143372651538748\n",
      "The Cost: 9.02605072471635\n",
      "The Cost: 5.119201554213221\n",
      "The Cost: 7.263267922949891\n",
      "The Cost: 9.191520332594688\n",
      "The Cost: 5.086053451883835\n",
      "The Cost: 8.450836566981454\n",
      "The Cost: 9.436822367983314\n",
      "The Cost: 5.064609687388948\n",
      "The Cost: 7.7805260471004685\n",
      "The Cost: 5.52671218553944\n",
      "The Cost: 4.882501479069244\n",
      "The Cost: 7.61091080969282\n",
      "The Cost: 7.915063697537006\n",
      "The Cost: 4.885503182992697\n",
      "The Cost: 8.54757125987556\n",
      "The Cost: 8.791175125069488\n",
      "The Cost: 4.874868757311304\n",
      "The Cost: 9.260318085404338\n",
      "The Cost: 7.517517674995644\n",
      "The Cost: 4.854846498615556\n",
      "The Cost: 7.581328293627864\n",
      "The Cost: 9.664903688885294\n",
      "The Cost: 4.764428978641468\n",
      "The Cost: 7.6594875028476395\n",
      "The Cost: 8.336574046401875\n",
      "The Cost: 4.736141920115947\n",
      "The Cost: 7.624384900632464\n",
      "The Cost: 8.173309763692899\n",
      "The Cost: 4.741014878281537\n",
      "The Cost: 7.848021490727538\n",
      "The Cost: 7.1351253062765\n",
      "The Cost: 4.7414247600599735\n",
      "The Cost: 7.743881628812354\n",
      "The Cost: 8.570835084791982\n",
      "The Cost: 4.674763638067777\n",
      "The Cost: 9.430307071672672\n",
      "The Cost: 8.772576502218119\n",
      "The Cost: 4.672155420086755\n",
      "The Cost: 7.936403628314659\n",
      "The Cost: 7.631025831811113\n",
      "The Cost: 4.67642807397378\n",
      "The Cost: 7.920833208696687\n",
      "The Cost: 7.8702621014944585\n",
      "The Cost: 4.676531023346383\n",
      "The Cost: 6.725866113042801\n",
      "The Cost: 6.5898925195747\n",
      "The Cost: 4.684880028217977\n",
      "The Cost: 7.183885888342174\n",
      "The Cost: 7.6304208008726775\n",
      "The Cost: 4.6997397117157185\n",
      "The Cost: 7.5709023965374005\n",
      "The Cost: 8.618442795994408\n",
      "The Cost: 4.669966712213629\n",
      "The Cost: 10.186738879744844\n",
      "The Cost: 8.453402469520448\n",
      "The Cost: 4.563221034914337\n",
      "The Cost: 8.091528406157035\n",
      "The Cost: 7.128191682682587\n",
      "The Cost: 4.565632814580736\n",
      "The Cost: 7.674330477462316\n",
      "The Cost: 7.9021779029271055\n",
      "The Cost: 4.57487829956271\n",
      "The Cost: 6.7561235530665975\n",
      "The Cost: 6.9951603703184375\n",
      "The Cost: 4.580725708667622\n",
      "The Cost: 8.997301435866326\n",
      "The Cost: 8.18341490303631\n",
      "The Cost: 4.534396947091074\n",
      "The Cost: 7.414372681295904\n",
      "The Cost: 6.869353116797416\n",
      "The Cost: 4.532962646771427\n",
      "The Cost: 8.389543902394001\n",
      "The Cost: 7.649063917867189\n",
      "The Cost: 4.471959401564119\n",
      "The Cost: 7.7413500000915345\n",
      "The Cost: 7.975412356816281\n",
      "The Cost: 4.485863781969053\n",
      "The Cost: 6.879494057333987\n",
      "The Cost: 7.671096136155156\n",
      "The Cost: 4.473718490049112\n",
      "The Cost: 9.106831650896892\n",
      "The Cost: 9.183148374897861\n",
      "The Cost: 4.461393982676979\n",
      "The Cost: 8.417644369249606\n",
      "The Cost: 9.517898260757292\n",
      "The Cost: 4.45440946911892\n",
      "The Cost: 9.356150633819619\n",
      "The Cost: 7.902731412246732\n",
      "The Cost: 4.468227482476106\n",
      "The Cost: 8.139700522837662\n",
      "The Cost: 7.528968188801331\n",
      "The Cost: 4.42648912440303\n",
      "The Cost: 9.19116470214583\n",
      "The Cost: 9.43419439312417\n",
      "The Cost: 4.440304080937434\n",
      "The Cost: 9.41877303323512\n",
      "The Cost: 8.238965257275495\n",
      "The Cost: 4.38787046947615\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Cost: 9.70795789222869\n",
      "The Cost: 9.581374979786617\n",
      "The Cost: 4.375766437795576\n",
      "The Cost: 10.073305462141574\n",
      "The Cost: 10.282575803413271\n",
      "The Cost: 4.379421229189868\n",
      "The Cost: 9.51013986290502\n",
      "The Cost: 9.518199775345483\n",
      "The Cost: 4.382421229189867\n",
      "The Cost: 9.276616827064789\n",
      "The Cost: 9.1725696171391\n",
      "The Cost: 4.38650494570937\n",
      "The Cost: 9.019314574350318\n",
      "The Cost: 8.476941711711081\n",
      "The Cost: 4.375761555303487\n",
      "The Cost: 7.589503176022688\n",
      "The Cost: 7.428959383859852\n",
      "The Cost: 4.362381204446527\n",
      "The Cost: 7.871184941764054\n",
      "The Cost: 7.8392227768667775\n",
      "The Cost: 4.3601543743624305\n",
      "The Cost: 7.773381709720906\n",
      "The Cost: 8.028060530004977\n",
      "The Cost: 4.385365260782918\n",
      "The Cost: 8.029721966918718\n",
      "The Cost: 8.313708721425165\n",
      "The Cost: 4.376790720170796\n",
      "The Cost: 8.862956303885417\n",
      "The Cost: 9.114913331733772\n",
      "The Cost: 4.384024326165794\n",
      "The Cost: 7.566081816432154\n",
      "The Cost: 6.721961876364073\n",
      "The Cost: 4.3270322394706495\n",
      "The Cost: 8.57365408921608\n",
      "The Cost: 8.446238327626114\n",
      "The Cost: 4.327831056569807\n",
      "The Cost: 6.933975428279033\n",
      "The Cost: 6.850878889427868\n",
      "The Cost: 4.342118054587776\n",
      "The Cost: 6.267325065128047\n",
      "The Cost: 6.188516482869276\n",
      "The Cost: 4.342860978519151\n",
      "The Cost: 7.101370753122438\n",
      "The Cost: 6.999870532017765\n",
      "The Cost: 4.347962977981103\n",
      "The Cost: 7.223497992725073\n",
      "The Cost: 6.325737103873341\n",
      "The Cost: 4.355640672120793\n",
      "The Cost: 6.004209925530401\n",
      "The Cost: 6.255877294581726\n",
      "The Cost: 4.337453891048809\n",
      "The Cost: 8.135177609323812\n",
      "The Cost: 6.882196492611984\n",
      "The Cost: 4.292285444682792\n",
      "The Cost: 7.253989122491371\n",
      "The Cost: 7.383234247757633\n",
      "The Cost: 4.281274220565859\n",
      "The Cost: 6.673459790666665\n",
      "The Cost: 6.6767067628702765\n",
      "The Cost: 4.279131102413506\n",
      "The Cost: 7.4131378072495275\n",
      "The Cost: 7.301744992959538\n",
      "The Cost: 4.28442232700049\n",
      "The Cost: 7.019952290095817\n",
      "The Cost: 8.117895654901748\n",
      "The Cost: 4.314328975185452\n",
      "The Cost: 9.259600764836513\n",
      "The Cost: 9.292700392651694\n",
      "The Cost: 4.313600407777159\n",
      "The Cost: 4.313600407777159\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "\n",
    "tfi_init = np.random.rand(efficient_su2.num_parameters)\n",
    "\n",
    "autospsa_loss2 = []\n",
    "def autospsa_callback(nfev, x, fx, stepsize, accepted):\n",
    "    autospsa_loss2.append(fx)\n",
    "    \n",
    "autospsa_new = SPSA(maxiter=200, learning_rate=None, perturbation=None, callback=autospsa_callback)\n",
    "\n",
    "result = autospsa_new.optimize(tfi_init.size, evaluate_tfiB, initial_point=tfi_init)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Cost: 33.732758728115805\n",
      "The Cost: 33.89367603866398\n",
      "The Cost: 33.934950890515495\n",
      "The Cost: 28.734815331215717\n",
      "The Cost: 31.807691800400296\n",
      "The Cost: 30.532420126354694\n",
      "The Cost: 33.927423546742986\n",
      "The Cost: 30.808210494011313\n",
      "The Cost: 34.984583139222934\n",
      "The Cost: 31.167653114251323\n",
      "The Cost: 33.25590570375264\n",
      "The Cost: 31.242700746142802\n",
      "The Cost: 35.99419599333742\n",
      "The Cost: 33.943855940134625\n",
      "The Cost: 32.37717068145807\n",
      "The Cost: 38.04677114706423\n",
      "The Cost: 39.00792050956546\n",
      "The Cost: 34.17604348063635\n",
      "The Cost: 35.3333467720593\n",
      "The Cost: 28.013734892890202\n",
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      "The Cost: 34.10665105596564\n",
      "The Cost: 28.162318139177945\n",
      "The Cost: 34.47607877195907\n",
      "The Cost: 35.889803102743244\n",
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      "The Cost: 23.555709318824473\n",
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      "The Cost: 23.17707651954836\n",
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      "The Cost: 22.829280315940004\n",
      "The Cost: 24.37457408909789\n",
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      "The Cost: 23.72229780426736\n",
      "The Cost: 20.88466791228126\n",
      "The Cost: 23.727686261617325\n",
      "The Cost: 25.185744728513683\n",
      "The Cost: 20.919000949275137\n",
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      "The Cost: 20.837263084702876\n"
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     "text": [
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    {
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     "output_type": "stream",
     "text": [
      "The Cost: 17.645222064774277\n",
      "The Cost: 17.185762585034336\n",
      "The Cost: 15.808011265537502\n",
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      "The Cost: 15.62181346596321\n",
      "The Cost: 15.62181346596321\n"
     ]
    }
   ],
   "source": [
    "init = result[0]\n",
    "autospsa_loss2 = []\n",
    "def autospsa_callback(nfev, x, fx, stepsize, accepted):\n",
    "    autospsa_loss2.append(fx)\n",
    "    \n",
    "autospsa_new = SPSA(maxiter=200, learning_rate=None, perturbation=None, callback=autospsa_callback)\n",
    "\n",
    "result2 = autospsa_new.optimize(tfi_init.size, evaluate_tfiB, initial_point=init)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_loss():\n",
    "    plt.figure(figsize=(12, 6))\n",
    "#     plt.plot(gd_loss, 'tab:blue', label='vanilla gradient descent')\n",
    "#     plt.plot(qng_loss, 'tab:green', label='quantum natural gradient')\n",
    "    plt.plot(np.array(autospsa_loss2)/10, 'tab:blue', ls='--', label='SPSA_B')\n",
    "    plt.plot(autospsa_loss, 'tab:green', ls='--', label='SPSA')\n",
    "    plt.axhline(0, c='tab:red', ls='--', label='target')\n",
    "    plt.ylabel('loss')\n",
    "    plt.xlabel('iterations')\n",
    "    plt.legend()\n",
    "    \n",
    "plot_loss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0.09255182,  2.96125091, -2.58314926,  1.3049876 , -2.36936663,\n",
       "         1.86960552, -2.61523763,  3.8262537 ,  3.86222721,  0.12046533,\n",
       "         0.29460505, -2.00511351,  1.74141472,  2.35644596,  0.12971376,\n",
       "        -0.97097519, -3.29980805,  0.00978226]),\n",
       " 4.313600407777159,\n",
       " 600)"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 18 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "folder = './Data/data_paper/'\n",
    "fig, ax = plt.subplots(3,6, figsize = (20,15))\n",
    "eN = [\"A\",\"B\",\"J\",\"K\",\"C\",\"D\",\"E\",\"L\",\"M\",\"F\",\"G\",\"N\",\"O\",\"P\",\"Q\",\"R\",\"T\",\"U\"]\n",
    "mre = []\n",
    "for n, i in enumerate(range(1,19)):\n",
    "    mre.append(100*(np.sum(abs(Data[i][:,-1] - prediction[i][1])/Data[i][:,-1])/len(Data[i][:,-1])))\n",
    "    if not i == 3:\n",
    "        X = np.load(folder + 'Run' + str(i) + 'X.npy')\n",
    "        ax[n//6, n%6].plot(Data[i][:,0],Data[i][:,-1],'^',label='Experiment',markersize = 3)\n",
    "        ax[n//6, n%6].plot(prediction[i][0],prediction[i][1],label = 'QNN',color='black')\n",
    "        ax[n//6, n%6].legend()\n",
    "        if not n%6:\n",
    "            ax[n//6, n%6].set_ylabel(r'$\\frac{dp}{dz} \\ [\\frac{kPa}{m}]$',fontsize=12)\n",
    "        ax[n//6, n%6].set_xlabel('Quality [-]',fontsize=8)\n",
    "        ax[n//6, n%6].set_title(eN[n])\n",
    "fig.savefig(\"./Images/Experiments.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(eN))  # the label locations\n",
    "width = 0.45  # the width of the bars\n",
    "\n",
    "fig, ax = plt.subplots(figsize = (10,5))\n",
    "rects1 = ax.bar(x, mre, width)\n",
    "ax.set_xticks(x)\n",
    "ax.set_xticklabels(eN)\n",
    "ax.set_ylabel(\"mre [%]\")\n",
    "ax.set_xlabel(\"Experiment\")\n",
    "fig.savefig(\"./Images/mre.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mre of the whole set of experiments is: 37.466885653516265\n"
     ]
    }
   ],
   "source": [
    "print(f\"The mre of the whole set of experiments is: {np.mean(mre)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions\n",
    "The proposed model uses a set of experimental parameters as input variables: local quality (0–1), surface roughness (0.4–2.6 mm), mass flux (139–242 kgm−2 s−1), and Reynolds number (197–50,740). Based on mre for different architectures we chosse the QNN model. This model uses 3 StronglyEntanglingLayers and in between these layers RX rotation to encode the inputs. Using the mean relative error, it is demonstrated that the proposed QNN-based model does not give the expected result with a mean relative error mre = 37.5%. If compared with the best available correlations produce mean relative errors mre = 23.9% (Sun and Mishima), mre = 24.1% (Awad and Muzychka), mre = 25.3%, (Cicchitti et al.), and the ANN in [1] has mre = 8.3%.\n",
    "\n",
    "I have two times more parameters in my QNN than those we used in the ANN [1]. Then, I do not think the problem is in the number of parameters used. Therefore, I have to change the architecture of the QNN and the way I encode the input data to get a better fit for the experimental results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}