stock_price_hibryd_algorithm_with_noise.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QI4PhD_bi9dN"
   },
   "source": [
    "## **Importing Libraries**\n",
    "\n",
    "A library was built with the name tfqml.py to store all the dependencies, classes and methods that are used in this work, these classes are\n",
    "- ClassicalPreprocessing,\n",
    "- QuantumPreprocessing,\n",
    "- CircuitLayer,\n",
    "- QuantumModel-\n",
    "\n",
    "together with the methods \n",
    "- visualization and \n",
    "- save_data\n",
    "\n",
    "\n",
    "the dependencies are:\n",
    "- numpy \n",
    "- pandas \n",
    "- matplotlib\n",
    "- sklearn\n",
    "- cirq\n",
    "- tensorflow_quantum\n",
    "- tensorflow\n",
    "- sympy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-02-25 10:23:08.856436: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
      "2022-02-25 10:23:08.856455: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n",
      "2022-02-25 10:23:09.855759: E tensorflow/stream_executor/cuda/cuda_driver.cc:271] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected\n",
      "2022-02-25 10:23:09.855780: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (toto): /proc/driver/nvidia/version does not exist\n",
      "2022-02-25 10:23:09.856018: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "from tfqml import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3J64HGEcjKho"
   },
   "source": [
    "## **Choose the 8 stocks**\n",
    "\n",
    "we select 8 stocks from 8 conglomerates based on the dataset of Xu et al. [[2]](https://aclanthology.org/P18-1183/): \n",
    "\n",
    "- Basic Materials: TOTAL S.A. \"TOT\"\n",
    "\n",
    "- Consumer Goods: Appel Inc. \"AAPL\"\n",
    "\n",
    "- Healthcare: AbbVie Inc. \"ABBV\"\n",
    "\n",
    "- Services: Wall-Mart Stores Inc. \"WMT\"\n",
    "\n",
    "- Utilites: Duke energy corporation \"DUK\"\n",
    "\n",
    "- Financial: HSBS Holding pcl \"HSBC\"\n",
    "\n",
    "- Industrial Goods: ABB Ltd. \"ABB\"\n",
    "\n",
    "- Technology: China Mobile Limited \"CHL\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "name_stocks = ['AAPL','ABB','ABBV','TOT','WMT','DUK','CHL','HSBC']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classical Preprocessing\n",
    "\n",
    "The methods of our library are used to preprocess the csv files of the 8 stocks,\n",
    "We consider 30 days por each instance and we obtain the shape of the train and test dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of train data: (880, 1)\n",
      "Shape of test data: (378, 1)\n"
     ]
    }
   ],
   "source": [
    "cp = ClassicalPreprocessing(filename=name_stocks[0])\n",
    "days = 30\n",
    "x_train,y_train,x_test,y_test = cp.preprocessing(days=days,flag_pca=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point we can check the dataset for trai nand test and confirm is the same dimention of the days and using a normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.50210573, 0.5198373 , 0.5154993 , 0.52431991, 0.52865792,\n",
       "       0.50093085, 0.50407582, 0.52309078, 0.54584719, 0.56281965,\n",
       "       0.56377762, 0.56446444, 0.56247619, 0.56835058, 0.54024395,\n",
       "       0.54277451, 0.50749205, 0.49944871, 0.52558515, 0.51186616,\n",
       "       0.49496611, 0.50047898, 0.51202891, 0.5010935 , 0.46798009,\n",
       "       0.45310439, 0.45507448, 0.46729319, 0.43667413, 0.44171711])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quantum Pre processing\n",
    "\n",
    "Convert the classical information fo the train and test dataset into a quantumcircuit this is possible using cirq, for this proposal we consider two encoding method, amplitude and angle, we keep the last one, for its result it was very well with respect the amplitude. Using as reference this the paper [Quantum Long Short-Term Memory](https://arxiv.org/pdf/2009.01783.pdf)  for the encoding, is important apply the arctang of the data and add a proposal. It was proposed for this encoding to reduce the number of qubits with the consideration that there are 30 data, one for each of the 3 coordinates, therefore the number of days divided by 3 will have to be used, it should be noted that data of multiples of 3 are needed to use this encoding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "qp = QuantumPreprocessing(x_train,x_test)\n",
    "x_trainq,x_testq = qp.data2qubits()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print a quantum circuit of our encoding, apart of the angle we add a Hadamard prevous the X and Z rotation and  do an entenglament for each pair of qubits. You can see in the next cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "<cirq.contrib.svg.svg.SVGCircuit at 0x7f9c2e4fe3a0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qp.print_circuit(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "following with the idea that they must be multiples of 3, the ansatz is used and this is designed with a layer of RY followed by CX with the qubit target of each CX applying an RY and then an H and the same is done with the RX gate, the number of parameters for each layer is indicated. these are 15 per layer. We use reference the tutorial from [tensorflow Quantum](https://www.tensorflow.org/quantum/tutorials/mnist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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      ],
      "text/plain": [
       "<cirq.contrib.svg.svg.SVGCircuit at 0x7f9c2803f9a0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qubits_required = days//3\n",
    "qm = QuantumModel(qubits_required)\n",
    "model_circuit, model_readout =qm.quantum_circuit([cirq.Y,cirq.X])\n",
    "SVGCircuit(model_circuit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eyHweGaykp-o"
   },
   "source": [
    "Creating our LSTM hibryd model.The first layer is our proposal which input is 30 parameters per instance and output is 10, followed by LSTM and Dropout layers, at the end a Dense layer to have an output value.\n",
    "\n",
    "\n",
    "We use a noise Parameter Quantum circuit , this is posible use the NoisyPQC method, and is important add repetitions  for the time is 10 and consider a the fag dample_based= True, this las one parameter is improtant to run our noise simulation. More information you can find [here](https://www.tensorflow.org/quantum/api_docs/python/tfq/layers/NoisyPQC)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build the Keras model.\n",
    "model = tf.keras.Sequential([\n",
    "    # The input is the data-circuit, encoded as a tf.string\n",
    "    tf.keras.layers.Input(shape=(), dtype=tf.string),\n",
    "    # The NoisyPQC layer returns the expected value of the readout gate.\n",
    "    tfq.layers.NoisyPQC(model_circuit, model_readout,repetitions=10,sample_based=True),\n",
    "    tf.keras.layers.Reshape((1,10)),\n",
    "    tf.keras.layers.LSTM(units=100, return_sequences=True),\n",
    "    tf.keras.layers.Dropout(0.2),\n",
    "    tf.keras.layers.LSTM(units=100, return_sequences=True),\n",
    "    tf.keras.layers.Dropout(0.2),\n",
    "    tf.keras.layers.LSTM(units=5),\n",
    "    tf.keras.layers.Dense(units=1),\n",
    "])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apply the as loss the MSE and optimizer ADAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " noisy_pqc (NoisyPQC)        (None, 10)                30        \n",
      "                                                                 \n",
      " reshape (Reshape)           (None, 1, 10)             0         \n",
      "                                                                 \n",
      " lstm (LSTM)                 (None, 1, 100)            44400     \n",
      "                                                                 \n",
      " dropout (Dropout)           (None, 1, 100)            0         \n",
      "                                                                 \n",
      " lstm_1 (LSTM)               (None, 1, 100)            80400     \n",
      "                                                                 \n",
      " dropout_1 (Dropout)         (None, 1, 100)            0         \n",
      "                                                                 \n",
      " lstm_2 (LSTM)               (None, 5)                 2120      \n",
      "                                                                 \n",
      " dense (Dense)               (None, 1)                 6         \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 126,956\n",
      "Trainable params: 126,956\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "model.compile(\n",
    "    loss='mean_squared_error',\n",
    "    optimizer=tf.keras.optimizers.Adam(),\n",
    "    metrics=[tf.keras.metrics.RootMeanSquaredError()])\n",
    "\n",
    "print(model.summary())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Consider only 60 epoch with a batch size of 32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/60\n",
      "27/27 [==============================] - 33s 1s/step - loss: 0.2493 - root_mean_squared_error: 0.4993\n",
      "Epoch 2/60\n",
      "27/27 [==============================] - 27s 1s/step - loss: 0.0637 - root_mean_squared_error: 0.2523\n",
      "Epoch 3/60\n",
      "27/27 [==============================] - 27s 1s/step - loss: 0.0213 - root_mean_squared_error: 0.1461\n",
      "Epoch 4/60\n",
      "27/27 [==============================] - 28s 1s/step - loss: 0.0166 - root_mean_squared_error: 0.1289\n",
      "Epoch 5/60\n",
      "27/27 [==============================] - 28s 1s/step - loss: 0.0139 - root_mean_squared_error: 0.1181\n",
      "Epoch 6/60\n",
      "27/27 [==============================] - 27s 992ms/step - loss: 0.0137 - root_mean_squared_error: 0.1170\n",
      "Epoch 7/60\n",
      "27/27 [==============================] - 27s 1s/step - loss: 0.0117 - root_mean_squared_error: 0.1082\n",
      "Epoch 8/60\n",
      "27/27 [==============================] - 27s 994ms/step - loss: 0.0113 - root_mean_squared_error: 0.1063\n",
      "Epoch 9/60\n",
      "27/27 [==============================] - 28s 1s/step - loss: 0.0107 - root_mean_squared_error: 0.1036\n",
      "Epoch 10/60\n",
      "27/27 [==============================] - 29s 1s/step - loss: 0.0093 - root_mean_squared_error: 0.0967\n",
      "Epoch 11/60\n",
      "27/27 [==============================] - 30s 1s/step - loss: 0.0093 - root_mean_squared_error: 0.0965\n",
      "Epoch 12/60\n",
      "27/27 [==============================] - 27s 1s/step - loss: 0.0088 - root_mean_squared_error: 0.0937\n",
      "Epoch 13/60\n",
      "27/27 [==============================] - 28s 1s/step - loss: 0.0081 - root_mean_squared_error: 0.0900\n",
      "Epoch 14/60\n",
      "27/27 [==============================] - 27s 995ms/step - loss: 0.0080 - root_mean_squared_error: 0.0894\n",
      "Epoch 15/60\n",
      "27/27 [==============================] - 28s 1s/step - loss: 0.0081 - root_mean_squared_error: 0.0897\n",
      "Epoch 16/60\n",
      "27/27 [==============================] - 26s 980ms/step - loss: 0.0077 - root_mean_squared_error: 0.0880\n",
      "Epoch 17/60\n",
      "27/27 [==============================] - 36s 1s/step - loss: 0.0078 - root_mean_squared_error: 0.0881\n",
      "Epoch 18/60\n",
      "27/27 [==============================] - 36s 1s/step - loss: 0.0075 - root_mean_squared_error: 0.0866\n",
      "Epoch 19/60\n",
      "27/27 [==============================] - 36s 1s/step - loss: 0.0069 - root_mean_squared_error: 0.0831\n",
      "Epoch 20/60\n",
      "27/27 [==============================] - 28s 1s/step - loss: 0.0071 - root_mean_squared_error: 0.0844\n",
      "Epoch 21/60\n",
      "27/27 [==============================] - 26s 960ms/step - loss: 0.0070 - root_mean_squared_error: 0.0835\n",
      "Epoch 22/60\n",
      "27/27 [==============================] - 26s 966ms/step - loss: 0.0064 - root_mean_squared_error: 0.0801\n",
      "Epoch 23/60\n",
      "27/27 [==============================] - 26s 956ms/step - loss: 0.0065 - root_mean_squared_error: 0.0808\n",
      "Epoch 24/60\n",
      "27/27 [==============================] - 26s 958ms/step - loss: 0.0069 - root_mean_squared_error: 0.0831\n",
      "Epoch 25/60\n",
      "27/27 [==============================] - 26s 954ms/step - loss: 0.0068 - root_mean_squared_error: 0.0824\n",
      "Epoch 26/60\n",
      "27/27 [==============================] - 26s 960ms/step - loss: 0.0063 - root_mean_squared_error: 0.0793\n",
      "Epoch 27/60\n",
      "27/27 [==============================] - 26s 956ms/step - loss: 0.0066 - root_mean_squared_error: 0.0812\n",
      "Epoch 28/60\n",
      "27/27 [==============================] - 26s 957ms/step - loss: 0.0062 - root_mean_squared_error: 0.0786\n",
      "Epoch 29/60\n",
      "27/27 [==============================] - 26s 961ms/step - loss: 0.0059 - root_mean_squared_error: 0.0770\n",
      "Epoch 30/60\n",
      "27/27 [==============================] - 26s 969ms/step - loss: 0.0062 - root_mean_squared_error: 0.0786\n",
      "Epoch 31/60\n",
      "27/27 [==============================] - 26s 962ms/step - loss: 0.0064 - root_mean_squared_error: 0.0801\n",
      "Epoch 32/60\n",
      "27/27 [==============================] - 26s 966ms/step - loss: 0.0064 - root_mean_squared_error: 0.0799\n",
      "Epoch 33/60\n",
      "27/27 [==============================] - 26s 965ms/step - loss: 0.0060 - root_mean_squared_error: 0.0777\n",
      "Epoch 34/60\n",
      "27/27 [==============================] - 26s 960ms/step - loss: 0.0062 - root_mean_squared_error: 0.0789\n",
      "Epoch 35/60\n",
      "27/27 [==============================] - 26s 965ms/step - loss: 0.0058 - root_mean_squared_error: 0.0760\n",
      "Epoch 36/60\n",
      "27/27 [==============================] - 26s 955ms/step - loss: 0.0055 - root_mean_squared_error: 0.0738\n",
      "Epoch 37/60\n",
      "27/27 [==============================] - 27s 1s/step - loss: 0.0059 - root_mean_squared_error: 0.0765\n",
      "Epoch 38/60\n",
      "27/27 [==============================] - 26s 958ms/step - loss: 0.0053 - root_mean_squared_error: 0.0726\n",
      "Epoch 39/60\n",
      "27/27 [==============================] - 26s 956ms/step - loss: 0.0062 - root_mean_squared_error: 0.0788\n",
      "Epoch 40/60\n",
      "27/27 [==============================] - 26s 956ms/step - loss: 0.0057 - root_mean_squared_error: 0.0755\n",
      "Epoch 41/60\n",
      "27/27 [==============================] - 26s 967ms/step - loss: 0.0058 - root_mean_squared_error: 0.0759\n",
      "Epoch 42/60\n",
      "27/27 [==============================] - 26s 956ms/step - loss: 0.0056 - root_mean_squared_error: 0.0746\n",
      "Epoch 43/60\n",
      "27/27 [==============================] - 26s 958ms/step - loss: 0.0056 - root_mean_squared_error: 0.0748\n",
      "Epoch 44/60\n",
      "27/27 [==============================] - 26s 966ms/step - loss: 0.0054 - root_mean_squared_error: 0.0736\n",
      "Epoch 45/60\n",
      "27/27 [==============================] - 26s 962ms/step - loss: 0.0056 - root_mean_squared_error: 0.0748\n",
      "Epoch 46/60\n",
      "27/27 [==============================] - 26s 965ms/step - loss: 0.0055 - root_mean_squared_error: 0.0739\n",
      "Epoch 47/60\n",
      "27/27 [==============================] - 26s 967ms/step - loss: 0.0059 - root_mean_squared_error: 0.0770\n",
      "Epoch 48/60\n",
      "27/27 [==============================] - 26s 961ms/step - loss: 0.0058 - root_mean_squared_error: 0.0760\n",
      "Epoch 49/60\n",
      "27/27 [==============================] - 26s 961ms/step - loss: 0.0054 - root_mean_squared_error: 0.0732\n",
      "Epoch 50/60\n",
      "27/27 [==============================] - 26s 955ms/step - loss: 0.0055 - root_mean_squared_error: 0.0742\n",
      "Epoch 51/60\n",
      "27/27 [==============================] - 26s 969ms/step - loss: 0.0057 - root_mean_squared_error: 0.0756\n",
      "Epoch 52/60\n",
      "27/27 [==============================] - 26s 964ms/step - loss: 0.0057 - root_mean_squared_error: 0.0757\n",
      "Epoch 53/60\n",
      "27/27 [==============================] - 26s 960ms/step - loss: 0.0052 - root_mean_squared_error: 0.0718\n",
      "Epoch 54/60\n",
      "27/27 [==============================] - 26s 964ms/step - loss: 0.0054 - root_mean_squared_error: 0.0736\n",
      "Epoch 55/60\n",
      "27/27 [==============================] - 26s 966ms/step - loss: 0.0054 - root_mean_squared_error: 0.0736\n",
      "Epoch 56/60\n",
      "27/27 [==============================] - 26s 956ms/step - loss: 0.0053 - root_mean_squared_error: 0.0726\n",
      "Epoch 57/60\n",
      "27/27 [==============================] - 26s 973ms/step - loss: 0.0058 - root_mean_squared_error: 0.0759\n",
      "Epoch 58/60\n",
      "27/27 [==============================] - 26s 955ms/step - loss: 0.0056 - root_mean_squared_error: 0.0747\n",
      "Epoch 59/60\n",
      "27/27 [==============================] - 26s 961ms/step - loss: 0.0055 - root_mean_squared_error: 0.0741\n",
      "Epoch 60/60\n",
      "27/27 [==============================] - 26s 964ms/step - loss: 0.0053 - root_mean_squared_error: 0.0730\n",
      "11/11 [==============================] - 1s 63ms/step - loss: 0.0342 - root_mean_squared_error: 0.1848\n"
     ]
    }
   ],
   "source": [
    "qnn_history = model.fit(\n",
    "      x_trainq, y_train,\n",
    "      batch_size=32,\n",
    "      epochs=60)\n",
    "\n",
    "qnn_results = model.evaluate(x_testq, y_test)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the result between the  real and predict with both data set, train and test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualization(model,x_trainq,y_train)\n",
    "visualization(model,x_testq,y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we save the model and outputs, the proposal save this model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE 5.64%\n",
      "MAE 14.22%\n"
     ]
    }
   ],
   "source": [
    "save_data(model,x_trainq,y_train,name_stocks[1]+\"_train\")\n",
    "save_data(model,x_testq,y_test,name_stocks[1]+\"_test\")"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "authorship_tag": "ABX9TyPVe0xJHFIRM8xqWAthKDQp",
   "include_colab_link": true,
   "name": "stock price predection.ipynb",
   "provenance": []
  },
  "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}