{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import keras\n",
    "from keras.models import Sequential, Model, load_model\n",
    "\n",
    "from keras.layers import Dense, Dropout, Activation, Flatten, Input, Lambda\n",
    "from keras.layers import Conv2D, MaxPooling2D, Conv1D, MaxPooling1D, LSTM, ConvLSTM2D, GRU, BatchNormalization, LocallyConnected2D, Permute\n",
    "from keras.layers import Concatenate, Reshape, Softmax, Conv2DTranspose, Embedding, Multiply\n",
    "from keras.callbacks import ModelCheckpoint, EarlyStopping, Callback\n",
    "from keras import regularizers\n",
    "from keras import backend as K\n",
    "import keras.losses\n",
    "\n",
    "import tensorflow as tf\n",
    "from tensorflow.python.framework import ops\n",
    "\n",
    "import isolearn.keras as iso\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import tensorflow as tf\n",
    "import logging\n",
    "logging.getLogger('tensorflow').setLevel(logging.ERROR)\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "import os\n",
    "import pickle\n",
    "import numpy as np\n",
    "\n",
    "import scipy.sparse as sp\n",
    "import scipy.io as spio\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import isolearn.io as isoio\n",
    "import isolearn.keras as isol\n",
    "\n",
    "from genesis.visualization import *\n",
    "from genesis.generator import *\n",
    "from genesis.predictor import *\n",
    "from genesis.optimizer import *\n",
    "\n",
    "from definitions.generator.mpradragonn_deconv_conv_generator_concat import load_generator_network, get_shallow_copy_function\n",
    "from definitions.predictor.mpradragonn_deep_factorized_model import load_saved_predictor\n",
    "#from definitions.predictor.mpradragonn_conv_model import load_saved_predictor\n",
    "\n",
    "import sklearn\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "\n",
    "from scipy.stats import pearsonr\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "from matplotlib import colors\n",
    "\n",
    "class IdentityEncoder(iso.SequenceEncoder) :\n",
    "    \n",
    "    def __init__(self, seq_len, channel_map) :\n",
    "        super(IdentityEncoder, self).__init__('identity', (seq_len, len(channel_map)))\n",
    "        \n",
    "        self.seq_len = seq_len\n",
    "        self.n_channels = len(channel_map)\n",
    "        self.encode_map = channel_map\n",
    "        self.decode_map = {\n",
    "            nt: ix for ix, nt in self.encode_map.items()\n",
    "        }\n",
    "    \n",
    "    def encode(self, seq) :\n",
    "        encoding = np.zeros((self.seq_len, self.n_channels))\n",
    "        \n",
    "        for i in range(len(seq)) :\n",
    "            if seq[i] in self.encode_map :\n",
    "                channel_ix = self.encode_map[seq[i]]\n",
    "                encoding[i, channel_ix] = 1.\n",
    "\n",
    "        return encoding\n",
    "    \n",
    "    def encode_inplace(self, seq, encoding) :\n",
    "        for i in range(len(seq)) :\n",
    "            if seq[i] in self.encode_map :\n",
    "                channel_ix = self.encode_map[seq[i]]\n",
    "                encoding[i, channel_ix] = 1.\n",
    "    \n",
    "    def encode_inplace_sparse(self, seq, encoding_mat, row_index) :\n",
    "        raise NotImplementError()\n",
    "    \n",
    "    def decode(self, encoding) :\n",
    "        seq = ''\n",
    "    \n",
    "        for pos in range(0, encoding.shape[0]) :\n",
    "            argmax_nt = np.argmax(encoding[pos, :])\n",
    "            max_nt = np.max(encoding[pos, :])\n",
    "            seq += self.decode_map[argmax_nt]\n",
    "\n",
    "        return seq\n",
    "    \n",
    "    def decode_sparse(self, encoding_mat, row_index) :\n",
    "        raise NotImplementError()\n",
    "\n",
    "def load_data(data_name, valid_set_size=0.05, test_set_size=0.05) :\n",
    "    \n",
    "    #Load cached dataframe\n",
    "    cached_dict = pickle.load(open(data_name, 'rb'))\n",
    "    x_train = cached_dict['x_train']\n",
    "    y_train = cached_dict['y_train']\n",
    "    x_test = cached_dict['x_test']\n",
    "    y_test = cached_dict['y_test']\n",
    "\n",
    "    g_nt = np.zeros((1, 1, 1, 4))\n",
    "    g_nt[0, 0, 0, 2] = 1.\n",
    "\n",
    "    x_train = np.concatenate([x_train, np.tile(g_nt, (x_train.shape[0], 1, 15, 1))], axis=2)\n",
    "    x_test = np.concatenate([x_test, np.tile(g_nt, (x_test.shape[0], 1, 15, 1))], axis=2)\n",
    "    \n",
    "    return x_train, x_test\n",
    "\n",
    "def load_predictor_model(model_path) :\n",
    "\n",
    "    saved_model = Sequential()\n",
    "\n",
    "    # sublayer 1\n",
    "    saved_model.add(Conv1D(48, 3, padding='same', activation='relu', input_shape=(145, 4), name='dragonn_conv1d_1_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_1_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_1_copy'))\n",
    "\n",
    "    saved_model.add(Conv1D(64, 3, padding='same', activation='relu', name='dragonn_conv1d_2_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_2_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_2_copy'))\n",
    "\n",
    "    saved_model.add(Conv1D(100, 3, padding='same', activation='relu', name='dragonn_conv1d_3_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_3_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_3_copy'))\n",
    "\n",
    "    saved_model.add(Conv1D(150, 7, padding='same', activation='relu', name='dragonn_conv1d_4_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_4_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_4_copy'))\n",
    "\n",
    "    saved_model.add(Conv1D(300, 7, padding='same', activation='relu', name='dragonn_conv1d_5_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_5_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_5_copy'))\n",
    "\n",
    "    saved_model.add(MaxPooling1D(3))\n",
    "\n",
    "    # sublayer 2\n",
    "    saved_model.add(Conv1D(200, 7, padding='same', activation='relu', name='dragonn_conv1d_6_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_6_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_6_copy'))\n",
    "\n",
    "    saved_model.add(Conv1D(200, 3, padding='same', activation='relu', name='dragonn_conv1d_7_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_7_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_7_copy'))\n",
    "\n",
    "    saved_model.add(Conv1D(200, 3, padding='same', activation='relu', name='dragonn_conv1d_8_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_8_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_8_copy'))\n",
    "\n",
    "    saved_model.add(MaxPooling1D(4))\n",
    "\n",
    "    # sublayer 3\n",
    "    saved_model.add(Conv1D(200, 7, padding='same', activation='relu', name='dragonn_conv1d_9_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_9_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_9_copy'))\n",
    "\n",
    "    saved_model.add(MaxPooling1D(4))\n",
    "\n",
    "    saved_model.add(Flatten())\n",
    "    saved_model.add(Dense(100, activation='relu', name='dragonn_dense_1_copy'))\n",
    "    saved_model.add(BatchNormalization(name='dragonn_batchnorm_10_copy'))\n",
    "    saved_model.add(Dropout(0.1, name='dragonn_dropout_10_copy'))\n",
    "    saved_model.add(Dense(12, activation='linear', name='dragonn_dense_2_copy'))\n",
    "\n",
    "    saved_model.compile(\n",
    "        loss= \"mean_squared_error\",\n",
    "        optimizer=keras.optimizers.SGD(lr=0.1)\n",
    "    )\n",
    "\n",
    "    saved_model.load_weights(model_path)\n",
    "    \n",
    "    return saved_model\n",
    "\n",
    "from keras.backend.tensorflow_backend import set_session\n",
    "\n",
    "def contain_tf_gpu_mem_usage() :\n",
    "    config = tf.ConfigProto()\n",
    "    config.gpu_options.allow_growth = True\n",
    "    sess = tf.Session(config=config)\n",
    "    set_session(sess)\n",
    "\n",
    "contain_tf_gpu_mem_usage()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "class GenesisMonitor(Callback):\n",
    "    def __init__(self, generator_model, sequence_encoder, run_dir=\"\", run_prefix=\"\", n_sequences=32, batch_size=32, input_tensor_funcs=None) :\n",
    "        self.generator_model = generator_model\n",
    "        self.batch_size = batch_size\n",
    "        self.n_sequences = n_sequences\n",
    "        self.input_tensor_funcs = input_tensor_funcs\n",
    "        self.sequence_encoder = sequence_encoder\n",
    "        self.run_prefix = run_prefix\n",
    "        self.run_dir = run_dir\n",
    "        \n",
    "        if not os.path.exists(self.run_dir): os.makedirs(self.run_dir)\n",
    "\n",
    "        seqs = self._sample_sequences()\n",
    "        self._store_sequences(seqs, 0)\n",
    "    \n",
    "    def _sample_sequences(self) :\n",
    "        n_batches = self.n_sequences // self.batch_size\n",
    "        \n",
    "        self.input_tensors = [self.input_tensor_funcs[i](i) for i in range(len(self.input_tensor_funcs))]\n",
    "        gen_bundle = self.generator_model.predict(x=self.input_tensors, batch_size=self.batch_size)\n",
    "        _, _, _, _, _, sampled_pwm, _, _, _ = gen_bundle\n",
    "        \n",
    "        seqs = [\n",
    "            self.sequence_encoder.decode(sampled_pwm[i, 0, :, :, 0]) for i in range(sampled_pwm.shape[0])\n",
    "        ]\n",
    "        \n",
    "        return seqs\n",
    "    \n",
    "    def _store_sequences(self, seqs, epoch) :\n",
    "        #Save sequences to file\n",
    "        with open(self.run_dir + self.run_prefix + \"_epoch_\" + str(epoch) + \"_\" + str(self.n_sequences) + \"_sequences.txt\", \"wt\") as f:\n",
    "            for i in range(len(seqs)) :\n",
    "                f.write(seqs[i] + \"\\n\")\n",
    "    \n",
    "    def on_epoch_end(self, epoch, logs={}) :\n",
    "        \n",
    "        seqs = self._sample_sequences()\n",
    "        self._store_sequences(seqs, epoch)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#Define margin activity loss function\n",
    "def get_activity_loss(output_ix, fitness_target, fitness_weight=2., pwm_start=0, pwm_end=145, pwm_target_bits=1.8, vae_pwm_start=0, entropy_weight=0.0, entropy_loss_mode='margin', similarity_weight=0.0, similarity_margin=0.5) :\n",
    "    \n",
    "    masked_entropy_mse = get_target_entropy_sme_masked(pwm_start=pwm_start, pwm_end=pwm_end, target_bits=pwm_target_bits)\n",
    "    if entropy_loss_mode == 'margin' :\n",
    "        masked_entropy_mse = get_margin_entropy_ame_masked(pwm_start=pwm_start, pwm_end=pwm_end, min_bits=pwm_target_bits)\n",
    "    \n",
    "    pwm_sample_entropy_func = get_pwm_margin_sample_entropy_masked(pwm_start=pwm_start, pwm_end=pwm_end, margin=similarity_margin, shift_1_nt=True)\n",
    "    \n",
    "    def loss_func(loss_tensors) :\n",
    "        _, _, _, sequence_class, pwm_logits_1, pwm_logits_2, pwm_1, pwm_2, sampled_pwm_1, sampled_pwm_2, mask, sampled_mask, score_pred = loss_tensors\n",
    "        \n",
    "        #Specify costs\n",
    "        fitness_loss = fitness_weight * K.mean(K.maximum(-K.print_tensor(score_pred[..., output_ix], message=\"score_pred=\") + fitness_target, K.zeros_like(score_pred[..., output_ix])), axis=1)\n",
    "        \n",
    "        entropy_loss = entropy_weight * masked_entropy_mse(pwm_1, mask)\n",
    "        \n",
    "        similarity_loss = similarity_weight * K.mean(pwm_sample_entropy_func(sampled_pwm_1, sampled_pwm_2, sampled_mask), axis=1)\n",
    "        \n",
    "        #Compute total loss\n",
    "        total_loss = fitness_loss + entropy_loss + similarity_loss\n",
    "        \n",
    "        return total_loss\n",
    "    \n",
    "    return loss_func\n",
    "\n",
    "class EpochVariableCallback(Callback):\n",
    "    def __init__(self, my_variable, my_func):\n",
    "        self.my_variable = my_variable       \n",
    "        self.my_func = my_func\n",
    "    def on_epoch_end(self, epoch, logs={}):\n",
    "        K.set_value(self.my_variable, self.my_func(K.get_value(self.my_variable), epoch))\n",
    "\n",
    "#Function for running GENESIS\n",
    "def run_genesis(run_prefix, sequence_templates, loss_func, model_path, batch_size=32, n_samples=1, n_epochs=10, steps_per_epoch=100, n_intermediate_sequences=960) :\n",
    "    \n",
    "    #Build Generator Network\n",
    "    _, generator = build_generator(batch_size, len(sequence_templates[0]), load_generator_network, n_classes=len(sequence_templates), n_samples=n_samples, sequence_templates=sequence_templates, batch_normalize_pwm=False)\n",
    "\n",
    "    #Build Validation Generator Network\n",
    "    _, val_generator = get_generator_copier(generator)(batch_size, len(sequence_templates[0]), get_shallow_copy_function(generator), n_classes=len(sequence_templates), n_samples=n_samples, sequence_templates=sequence_templates, batch_normalize_pwm=False, validation_sample_mode='sample', supply_inputs=True)\n",
    "    \n",
    "    #Build Predictor Network and hook it on the generator PWM output tensor\n",
    "    _, predictor = build_predictor(generator, load_saved_predictor(model_path), batch_size, n_samples=n_samples, eval_mode='sample')\n",
    "\n",
    "    #Build Loss Model (In: Generator seed, Out: Loss function)\n",
    "    _, loss_model = build_loss_model(predictor, loss_func)\n",
    "    \n",
    "    #Specify Optimizer to use\n",
    "    opt = keras.optimizers.Adam(lr=0.001, beta_1=0.9, beta_2=0.999)\n",
    "    \n",
    "    #Compile Loss Model (Minimize self)\n",
    "    loss_model.compile(loss=lambda true, pred: pred, optimizer=opt)\n",
    "    \n",
    "    #Randomized validation tensors\n",
    "    val_random_tensor_funcs = [\n",
    "        lambda i: np.array(np.zeros(n_intermediate_sequences)).reshape(-1, 1),\n",
    "        lambda i: np.random.uniform(-1, 1, (n_intermediate_sequences, 100)),\n",
    "        lambda i: np.random.uniform(-1, 1, (n_intermediate_sequences, 100))\n",
    "    ]\n",
    "\n",
    "    #Standard sequence decoder\n",
    "    acgt_encoder = IdentityEncoder(145, {'A':0, 'C':1, 'G':2, 'T':3})\n",
    "    \n",
    "    #Build callback for printing intermediate sequences\n",
    "    random_genesis_monitor = GenesisMonitor(val_generator, acgt_encoder, run_dir=\"./samples/\" + run_prefix + \"/\", run_prefix=\"intermediate\", n_sequences=n_intermediate_sequences, batch_size=batch_size, input_tensor_funcs=val_random_tensor_funcs)\n",
    "\n",
    "    #Fit Loss Model\n",
    "    train_history = loss_model.fit(\n",
    "        [], np.ones((1, 1)),\n",
    "        epochs=n_epochs,\n",
    "        steps_per_epoch=steps_per_epoch,\n",
    "        callbacks=[random_genesis_monitor]\n",
    "    )\n",
    "    \n",
    "    train_history = None\n",
    "\n",
    "    return generator, predictor, train_history\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Specfiy file path to pre-trained predictor network\n",
    "saved_predictor_model_path = '../../../seqprop/examples/mpradragonn/pretrained_deep_factorized_model.hdf5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Maximize isoform proportions for all native minigene libraries\n",
    "\n",
    "sequence_templates = [\n",
    "    'N' * 145\n",
    "]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training GENESIS\n",
      "Epoch 1/250\n",
      "100/100 [==============================] - 7s 74ms/step - loss: 1.1326\n",
      "Epoch 2/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.4450\n",
      "Epoch 3/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2794\n",
      "Epoch 4/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2440\n",
      "Epoch 5/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2286\n",
      "Epoch 6/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2150\n",
      "Epoch 7/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2123\n",
      "Epoch 8/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2029\n",
      "Epoch 9/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2007\n",
      "Epoch 10/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.2037\n",
      "Epoch 11/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1911\n",
      "Epoch 12/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1889\n",
      "Epoch 13/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1880\n",
      "Epoch 14/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1893\n",
      "Epoch 15/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1876\n",
      "Epoch 16/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1863\n",
      "Epoch 17/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1921\n",
      "Epoch 18/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1903\n",
      "Epoch 19/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1876\n",
      "Epoch 20/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1857\n",
      "Epoch 21/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1855\n",
      "Epoch 22/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1905\n",
      "Epoch 23/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1921\n",
      "Epoch 24/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1903\n",
      "Epoch 25/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1904\n",
      "Epoch 26/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1916\n",
      "Epoch 27/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1862\n",
      "Epoch 28/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1881\n",
      "Epoch 29/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1825\n",
      "Epoch 30/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1911\n",
      "Epoch 31/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1852\n",
      "Epoch 32/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1833\n",
      "Epoch 33/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1851\n",
      "Epoch 34/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1843\n",
      "Epoch 35/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1800\n",
      "Epoch 36/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1822\n",
      "Epoch 37/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1773\n",
      "Epoch 38/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1742\n",
      "Epoch 39/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1740\n",
      "Epoch 40/250\n",
      "100/100 [==============================] - 4s 44ms/step - loss: 0.1711\n",
      "Epoch 41/250\n",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "100/100 [==============================] - 5s 47ms/step - loss: 0.1257\n",
      "Epoch 249/250\n",
      "100/100 [==============================] - 7s 71ms/step - loss: 0.1241\n",
      "Epoch 250/250\n",
      "100/100 [==============================] - 8s 79ms/step - loss: 0.1212\n",
      "Saved trained model at saved_models/genesis_mpradragonn_max_activity_sv40_25000_updates_similarity_margin_03_earthmover_weight_01_target_35_generator.h5 \n",
      "Saved trained model at saved_models/genesis_mpradragonn_max_activity_sv40_25000_updates_similarity_margin_03_earthmover_weight_01_target_35_predictor.h5 \n"
     ]
    }
   ],
   "source": [
    "#Train MPRA-DragoNN GENESIS Network\n",
    "\n",
    "print(\"Training GENESIS\")\n",
    "\n",
    "model_prefix = \"genesis_mpradragonn_max_activity_sv40_25000_updates_similarity_margin_03_earthmover_weight_01_target_35\"\n",
    "\n",
    "#Number of PWMs to generate per objective\n",
    "batch_size = 64\n",
    "#Number of One-hot sequences to sample from the PWM at each grad step\n",
    "n_samples = 10\n",
    "#Number of epochs per objective to optimize\n",
    "n_epochs = 250\n",
    "#Number of steps (grad updates) per epoch\n",
    "steps_per_epoch = 100\n",
    "\n",
    "#Number of sequences to sample and store for each epoch\n",
    "n_intermediate_sequences = 960\n",
    "\n",
    "K.clear_session()\n",
    "\n",
    "loss = get_activity_loss(\n",
    "    5,\n",
    "    3.5,\n",
    "    fitness_weight=0.1,\n",
    "    pwm_start=0,\n",
    "    pwm_end=145,\n",
    "    pwm_target_bits=1.8,\n",
    "    entropy_weight=0.5,\n",
    "    entropy_loss_mode='margin',\n",
    "    similarity_weight=5.0,\n",
    "    similarity_margin=0.3,\n",
    ")\n",
    "\n",
    "generator_model, predictor_model, train_history = run_genesis(model_prefix, [sequence_templates[0]], loss, saved_predictor_model_path, batch_size, n_samples, n_epochs, steps_per_epoch, n_intermediate_sequences)\n",
    "\n",
    "generator_model.get_layer('lambda_rand_sequence_class').function = lambda inp: inp\n",
    "generator_model.get_layer('lambda_rand_input_1').function = lambda inp: inp\n",
    "generator_model.get_layer('lambda_rand_input_2').function = lambda inp: inp\n",
    "\n",
    "predictor_model.get_layer('lambda_rand_sequence_class').function = lambda inp: inp\n",
    "predictor_model.get_layer('lambda_rand_input_1').function = lambda inp: inp\n",
    "predictor_model.get_layer('lambda_rand_input_2').function = lambda inp: inp\n",
    "\n",
    "# Save model and weights\n",
    "save_dir = 'saved_models'\n",
    "\n",
    "if not os.path.isdir(save_dir):\n",
    "    os.makedirs(save_dir)\n",
    "\n",
    "model_name = model_prefix + '_generator.h5'\n",
    "model_path = os.path.join(save_dir, model_name)\n",
    "generator_model.save(model_path)\n",
    "print('Saved trained model at %s ' % model_path)\n",
    "\n",
    "model_name = model_prefix + '_predictor.h5'\n",
    "model_path = os.path.join(save_dir, model_name)\n",
    "predictor_model.save(model_path)\n",
    "print('Saved trained model at %s ' % model_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#Specfiy file path to pre-trained predictor network\n",
    "\n",
    "saved_predictor_model_path = '../../../seqprop/examples/mpradragonn/pretrained_deep_factorized_model.hdf5'\n",
    "\n",
    "saved_predictor = load_predictor_model(saved_predictor_model_path)\n",
    "\n",
    "acgt_encoder = IdentityEncoder(145, {'A':0, 'C':1, 'G':2, 'T':3})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/anaconda3/envs/tensorflow_p36/lib/python3.6/site-packages/keras/engine/saving.py:292: UserWarning: No training configuration found in save file: the model was *not* compiled. Compile it manually.\n",
      "  warnings.warn('No training configuration found in save file: '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.4849217\n"
     ]
    },
    {
     "data": {
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L6Iutzs0ENlLVZSISL8hgYEao1w7AU8CbwOFAa2Cr8P8FwErgNqAtMAq4VFVvymn3rsA/Klya3VR1bIXrlhbKBqvq9Ap5OY7jOI7jOI7zX0CzrJSp6koROQH4HbBl+JwJfCAiB6jqC0GIOhnYE9gAeB0TynbPyfJY4J+Y8NYW+LGqXi0iwzAhaUtgSir+vap6WBAO3wNqgC8AD2byHY0JZAuBl0PYW8BI4HjgYmxlbw5wDzBRVaeKSMuCdo/FVvP+dyhLZ2ADSvpmJqwXJZ1SmK44v05AX0o6eV1UT4T1gAGqvLEu8qMs6wFDgImUgkbDwjYEXq8Ly69LmxBvsioxbTvsuX6tkbStgU2AiXVp/xOUpSWwEfAWJa0NYa2ATYE3KOmqoqQitACGYe2NaVtiq9+TKenKCmklxJuiSmG8JrQj1uVtSrqsqclFGApMV2VZyE+w+zGDki5NhQ0DplPSJWtd56ZQlqHA+5T0kzVIuwnwASVdsC6qIsIgYL4q89dFflVTlkHAYkr64brIToQ+wGpVPlgX+RWUsQHQSpX3K0YsS2+gNSV9t8mFlKUX0I6SvrNGlcwgQhegiyrT10V+lKUr0J1SQyuRdYUI7YG+qqTHqU5AH0pacWwQYX2gnypNH8+qr19bYLAq62Tca0K5rbHxZ9J/dFzJr0tLYGioy2oAytI6hlUaa8KYNIxGxpUw/gwFplSMtzbYOLApMJWSrliDtEOAdxtLK8KmwDuZMWkY8A4lW9yokHYT4D1V1s04VZY2wMpKc5i1JYwrH6uSjFPWdyyhpMv/XeX+p2m2PWWq+hegN/BF4CeYYNMLuABARI7EBKGfA98GDg5Je+ZkN0lVVwHxQYyd7MLw3T4bP9RhJbbKBtAvJ99B4bsj8K3wGRnCNlLVRcApmKB1P/C2iLwL7JTXZhHZSESurPDZKC/dp4aytAgCSPzdHXgRmEJZLgph3YDngTcoy0/q4oqcgQnZ9vMk0fQnpO0EPANMoixXpNI+hshjlaqWl58IrYB7gckifCeV3wOI/KtiXSzeTYg8kWpvW8yE9jVgDGWR0Bn9Fdsb+acw+QeRMYhMTrJCgBsxc9lLQn6xfq8A91CWlgXtEOC6UO5VqfqNQCRPSVGRwvZmsU7+emAy8ChlaRvCfhfq8kTd8yDyY0Q+RKRzKocLQ7zbRZCQ9jehvf+kLB2zdUnV59yQ9t4g3IHI2aGM/nntqNgW+FHIbxxl6dGk6yWcgPUZY4NgDdYnTQZepSxxH+xZmPLodcpSExKXEPkAkW1SGe6DyDOIbJkK+xIiMxDZPhV2aGjvLhUrWJZYvylBwAKRfUPaL0KFa1WWEtZfvkVZNgtpdw9pD84pjUr5ibADpgB7TYTeIb/tQn5HV2xHFVRox66h3OmUZbdQ7sah3EKT8Qrt2IRwTUUYHvLrG/I7t2JdRHqEeD+o2BZhANZvvCXCNoURTeCeHNpWeA0Lrospi2AaZTkxFNwCkVmI/DZTzvphklOYnwhdsf79LRH2TTXmbcwSJd3A1xH5YyZsfL2wsmyAjfNvUpbzUvH+gcjvK7at8ELI84g8kPykHfAodi9PCOV2Bp4DJlOWyyu0tzXwEPCGSGrrgcgjiDxZ8VpVG2bCyB3AJBGSa1AFFcau7yNyc8X62bhyA/Z8/KIubVlqKMuxYSyvULhcjcj7iI151d6jCvEuxfrom0I9BPg9Nl4kY00Wi3dtiPcMZWkf6vfD8B6m23FlKOOflKVj6lp9iMi68mfwI6zveLnoGlYYu76DKf7HU5aeoX7HhzFki7r0wrFYn/BUEOih/vjTr0Lf9mWsz/9nUDiAyGHhGuzcSP0aUpY9gE+AF4MCaJ0jws6YpdorIkEGKMvumNzwdugjm5LhqNDe49aoQmXZjbKMXqO0jdAsQpmItBaRHVV1mar+TVXPJ05UTQAC+Er4vg5b/Yq/81aaahv5nWVYrAemlQBbMcsyPXzPAtqpqqiqAOuT7A27SVVrMFPIb2HC3QUF5fYjEe7yPnmC4acDG8ReABZQrpvk/BhbRQE4O3xfhK0gpMMAvoe1sRIXAJuFv88MWi1C2Ig1qPUx2EorwImp8OHAZog0tmq5DfC5VLxvkgjcR2IrrKdgexMBvgz0D38PAzbF9kkC7BfSAJwUvo8H9gp/H4hpLPPYPcRNpwW7/o8i0qZhknXCPqlydwW2x/ZWxrDtsZVksHveA7smcWUpvgeHAN2w6/SNEDYq5NmAoBGLAv0+2LsFdn16kFzj6ijLFti+TzAt6f6p/1V8BsIk9Dfh53bAZmGie2kI2xA4NKzSXBbCBgGHpf6/ATAwle0W2LXbJBW2MdauwamwIVh7B1VoW3fg6vCrFxAn7YOrSNsJE7oJcY9N1b9Hpi6Nkprktcaegy+Gfw0M+Q2BJgvTjWP9xE2h3PWxdxJgQCh3TZRdv8H2MnfCTNbB7k8Pit/TSL8q412OPRvrEU3ty9KOstxAWe6gLPGZuS7UpQVwRtOawW+xvdCCTdoIZfbGtPmEcgdgQu0HdcJbPj/A2tUSOA4AkfbYvU0mRiLtsH52RCqsDWa1Uje5xJSug8Lf3wnxWgA7Yu9b07C+erNQduSbwOfC3yeE7wtScc6q0A+cRNK/p6/LCNZsTMrjKyR9UqVr3xQOAI5CpJI11N4k/YWNK9afPI4pEF8I434RQzHHbE1ScuUhwiiS5/PoIGjsi43hYP3l5wuS70FyX7chGaPjmGTzqrLsTDJvG0VidbVxvXhrg401cdwbQbyvZWlDWfYMSoiitBtj7wPY/OFL4e+NsHd2AIAInYFrwv+2BrbMjD8DSfqsegQhLPb5m0OdMiiONQPz0lWoc3vgLyRbd06pnKDpBKXsHzHLvgHAXkEZflsIqwFOa2K29cakJlGWk7B35EXKayjUVaC5VsraAk+JyEQRGSMi15NMmh4J39FkZF/sAbyKdceBInIH8AT2sL+PXeQsL2HatD7ACyJyrYjcE+LHCccHIewCkhch12xHVcdGwa7gM7aowmE/3NWpoF+IyI0iTdP6rwWXYi9da+CSMIgdmhPvSw1CTDDZgMY7vUppe62B8NFQ02+Ddl9s8lZpwAF72duQDDoN65cfFtNC4k30kCakzVK0YtEfm2z1hSZqk6ujuvtr1GS+8+pcbXsPJF/5ki2jWvLLLcs3gWWU5ZEKWuEvAu0yYQfl1O/gnDBInvn0s5/XjmrDbPCOWl7rH/Pei2qu1V4QNKVNT5vHMOoLmmubX7WMIkxY1kW5InTCJnprml+j8cIKzP45/7oaU3ocCvwhrOru3Eh5+dgzslfOf/Lqd1343RpbpS4irx/Ly69vTlifemE2huTltwHJZKupdMGE3L4pZdq67XtN0OkFdEMKVm+aRl791pZ+2Pyud4U4eX30qSTv8BDy36tIVe+DCC1FGByUNkWszT2qdkzKG8/y4uUjciwiYxGpdE0b1sWURn8C/o5ZEBUJ84dQ3RiyJ/aMp8kbk/LYDVM0ZVnTPnofoGvqd+7WnbVkcxoKT7tg/USkqduC1qy91qdekQrZpzCuSGdETkNkZGGcHJpLKFuGeUdcjk0qvooJMj8m0UD/CHOK0RPb2/XTdVj+1ZhguBVmOnGAatgXkkJVV2MP+7XYg3wcZr74ILaHDUyIHIVpakaE/317HdY1cizJSgtYB3Ms5izl34uZ5H05/JoXvvtiL8Wt2CrI2GDG1QcoYy/q46m4AJ0Q6QSg12vdS6TXqwSzmSHYUQmdgYfDv9MmBYXmBQ3yM0ZhpjbdMEctYFrjuHpVU5hWpCNJ59UvdKxbAU+H8FuxjmAk8GwIuymkbUPSYcSXfhSmie4B3B8mJKMxwb8zNilCr1eJdci0Yzr2Lvwl1ey8CX+jFJSRx+hQbl+SlewY1gt7RyPZTm4U5pRmIPCrVNhM7D6ek1eX8PcoYBGmIYyawwZlFKTNI9ZlQ+DrAJRla2w1pA02AT8EQIR+IlwpwoGptCux+xxNYEeH+o3A+i4N8RaHsCNDWN51gbUR1MpyKfYcvUtZdkzVbzusL12Zl7bCdV6NaZa/gPXHRXWpR4X8CO3fJ+RdVX7V0ki5R2ArMR+tZTu2xN7tc0Pecd9Ftc9fNe0dhgn7l2ArDvMpSxeSlQEwq5E4oJ+HTZAL911VaMfFoS4Tc+tnK6Z7A6swq5Dc/ETojr3PN2PP7oxMfn1I9lPHZ7t3arUmhkUF2xCs7/s91i8/m4nXFZH103XJ/p1DrEtboHswDdwKM1/sgZmFdcVWge/EhLi/5ZURhIhRWJ/fDYgm771J5k59i+pXbVgoY3woo85MX4R2ImxcSZgpGLtakhGAK5T7drgud4WwvcP3nVgfl48JvNUqH/6MbRO5XwSpMMbNwa7n71Nh07Bx76LCuli8GdiYdH4qPG9Mej/8PqcoXoWV/B0xYaDSCvhobI60EbZCC6ZkjEJnF2Dbgr5jNLblZjPg5FSeee1Yha2SnZkKi+PPV4DVFfpKxSxcvl5URhPG1q1Dfl/GrGDqlMEiDA2WJmtrHRH798Owa6nYtSKUewDJ2FUtazom7YDNuadi5rKVGIHNfY5sJF49mkUoU9VVqnqWqo5U1a6q2k5VN1LVH4S9Yajq+6q6u6qup6pbqeqvw2pSl/D/6akVpvkhrEt6xUlVdw2/b8xU4SNVPUBV11fV0ar6cqpuMc/p4feHqnqKqg4K9RyoqkermiMKVT1cVQeoaltV7aaq+/87vCJWWF1b52UBIHJk3I+CdUJdsMG9F+YVM74ol1DSjzGziziB+DklnU9iUtAfiM4VigSIrVJpPwG+hr18/TAHLssqpM2pPj2xF+63qnwMdbb6/UK+HzeSX3xZPw5/b4ztTbycki7Elum7YxOnK0LYNzFvnFEI/QjoF/YhjQCuV+Uj4LshTk/gytDeM4AGDgrC0v2WwA2qzCWahNqkphfWORea861xR2j750YA11DSWdhK8FRMa3UdJZ2DDZSvB3OjmtjekMNI4HZVZgDn77DJ08uxe/wHSjobM7V4qaD0kcA9qryNCX7ReUUso6kd6UigTEmnUtLfYYqUaA79T8KqfFgheRYzs71XhI1D2sdVGY/tR5iBPft3UtKJlPRWzMnPKODuEPYnbI9IUZ1rsOckK6jNo6GglqQty/YkJsGdMUFqFPAoJX2ekv4V+EMqv4+o/IyPAp6kpE9T0sdJVuKrSZvHSGxS/2dVHiZRrNRrRxMG/GqJk7e/UNJXMOUerF07VgG/UWUcUdlS/fOXlFtsIh37yiuDE6JrgG0xTfPFmFnRO1jblmN9zLskJl7VEIXuSynp+9jRMel2dAxKstGY8PZ1TOi6pyC/2EdfqcpMEgVqbG9LrE9Kl5FerakhUer1of4YMo/ENLuGxMtwU9/1GkzBG8eOjbB++1eh772Q+uPUAmysyaMf1sf/OowhF6TCV2JCy1qZvAVTtCHANaGM74fwXljfNAVTADaFXti9WFhUv7DfenPg93VjkjnVGAlcTUkPw0zuV+elx5SQ7anwXod4R5OsUO1Xoc4jgTGqzALOueX/jm6JCSfXUtK5hH1aIogI54jwnghX3P6tw1tj5rDXhzHpp8Ar4b1L3kNTLG8F3BDehcuw/fBQ/Xs9KPOdxyhgDCV9m5JejSmm42rKrzABv1Lav1DS1ynp9dhexrz6jQSeVOWlkOe0kPbeMP78Bbi9oIyRwD9VeRYzY5wUwte0rxwNjKWkt1PS64BbAETq9tVNDVsZ1oaRwLvAXarcjylYRgPjQrkPUMmSTqQ9Ip9HJO2PYk3buw2wAltx3JpE2Z/H4Mx3VTTn4dHOpxXTbN5EskoR7Y5/GzwgnYUN3suITlVKOhPT5K4gamQtDBKtaqWXYAA2ALwS0s6ipKuxjuh9Eg1XtUSzi1cAVJkTftdgws+MRvKLE+e3w98xv5dD/RZhA3Y6bHEQRmuwidTE8Ld5TrPjH2JdBmbSLqOkUcOfphs2+OW1QzBHAf2hSStg1dAHMyGK9avFJjqtU2Grg8DWI4S/RHJNB6TqvPDpH+60XmhHTKthcMxjAMm1WqrKJ2GPSo9QRvUdqa1w9iPxnhqfyx0wAWxHrNN/HxPU+mMbiudjJiLpdtQGwXggdtjN0yB9AAAgAElEQVR9Or+BmTJi22LZ6TrnhdVQ//rFeOn2HoC9I9/GJh9aody8/LKsTdo8BgCvRC9uqWc12451jbUjev5q2I4+0RlBlQwA3lI1x1E57ahbwSkglpuYSIu0QeQYRKIgMgCYHfMO35/DtN0/pqQvYvskBmKeXpdl2lZtO94MCqO8ZzLWdWus3741eKQ7n3xiHz0xVeeYxyvYXu74zPTDHCqsJLnvcbVuefh7INbHTsvUrwZ7BxfR9GcwjjVzqN9vZ/veWqzvtHLzvcZVGkNmYav+a7v6GxVq6fqBCYDREVCu47AK9MOUCq9S/M71xFZq023bJISZUF7SJ4mT9rK0pCw9U3vvYr7ZfizLAZhweAK2FaQBYTWtT6ou847eYUw0Yc2ONQcCP8Ou+5kiOjjUOTuudA3hsR/riq1wpOPNRKQD9o7W9U8VlEaDsecmf5Jtjrv6Un9seA/bD3cHJf0WZnr4WsG1yvbH0dNqdrxIj4+rVfkwhOX15VnSaTXzTK9Jnz+ERLiFkr4ZHCNFJ0ddSO9dXTMGABMy48og0krdUsXFid2wsT6tfFnT9m4FPE9JZ4S+8uoKcV0oc9YZG2KT7E2DKUQvYHZY4SC4++6Auf5OO1XpiLljzbqu7UciWBV14B0wl95ZM9I4AM4iWTHoQFkuoCy3UJajCjZpxz03UzPhUchL8sunX6rcfqF+qzCNTbrOimm08+ocBclYl2mpONHsNFu/atvRD5vcvEaFQXEtBLW8covqHK/jOKAmrAy2qTJtPYKpTseceHH1sfGOVORoRB5GZBCJ59UkP3te4spWbRjsH8bMGN/CVgi3wybIHTNpW2LC2tupsBahnPp1tv2QPbBBqyaEtcKE9ERIqR8W47XAJirp9u4K3E9Jr6Ck52GrYtGUIl1u1BI3dq0apjWSASuu9Jin0eF1XiXzybtv6fx6pBzfVIdIW8zLaNcKsRprRyvq7z9ojMbaEf8uoob6Qg+YU4mbSMym8sroD4yvc4Vd0g8obls1VLoub2Er0DXYBP31VLlFR0Z0xNxoZ02FajBHWR9Q3yxoJjA7FRbHgXSfOjVHIIp9b6XxoojseNERm0inHXl1AGZWcTTG2o4h1dBgbAh94IHAWKz9NzdMVpF+2HWfSfH1y2tb3Ff7al1ISVcHz3YTMEF3InY8Q1Zp2YDQjl0wa5UbKN47lzc2FI0XJUxhdhjw516dPmjYvxuxTrEPrHQv0/HysXlQFHyKJtmxztmxYRhxK4cpX19okNIsU1o3qJ+tZHcgPYY0HJOE6vuJjtSfh6TNXddESOkIqWMmjP2xudIOmDXHsqZYR4TV0C1ECtqbhFV7hMaIzDckfXmX4KioWrqTfT8AyrITZXmMsjxEWaISZQi2aNEkZyLNck5Zc6GqxxE9RjmVGIaZmXTDNBKdoME5Oh2JNufmgroDpo1Kh3XE9gXGwXg5lQeJmHZnTMPyZCqtpNLehWmcFmHmEXdhJo7Z/CA5JiESB/zZFeoCDQfet7AzkJSybIsJqjUhbHUI643tYcsKobGzTtvox8nC8uBa1TqJZHUx246sfX9/bNCdCWttHgBA6AS3Bl7RMXXlLqQsw7CBKDqUWERZhmPC+0SsjR9iwuleFLc3pt0U055NpuFZdm0x05tse2swrfvrJKaHRXwJ2xuxPebMJ5Y7GDOJmRXKSXeuylGMxkwkVhLONRShQ6YuHVL59ce02XOx53MRZelHYm4Rz1N5CTgrCDhxP8pLwOlB+IrmRi8BZ4dBsifWP78EnItIa8YwiMQs0lbobOPxouCKeDvsuX4DExJtv6JIB+z4jiwxbU/Ms9mHHMXLoeyXiE5uylKLHflh7vrL8l1KellOftlrlXasE4WZvmQnBZXZM5T9M8yDax6xHe2xScBiSvoY9lyOIzFlm11lmQ3bYdRgbqiXkqzm5NEPMx9aEP5+ncRkLn7nldGJxONvpCPxOSqL7aco6f3VNaNen7o/9tw9EOr+BInSqBPVXZui69IPe+bSQlQN1h+kBZes1UO6fntgK4uPpOJ1oemTxJi2NtRlGbC47twrI13uLthKyRM55/R1BFaqkj0vKo4hTTKpLyCvrxyI9e//p8pMkbpVh3geVF9MqFxZkGc11iWV+uisxcZvsInlHVg/EYWyWMaOBWV0xOYQzwBUOO+vsfFiBPEcUHQPTMi7U4T7Nx/w6lapeMMIZ65h92U+1tfsT/1+exPiOZvWjiXh70qORfpiQtNTJPuZ8tobyxiMCQEfYO9dY+fPpdP2x8apGSTmoy8B/xf+zr6H64UyYlobf0o6jobkvcPp8eccRFqhFc6Ea1jvhWGf5jDgY9CdgEeDiWTcglEV4fiKe7F5xGoR9i6oc+zzO2NzlgXBuiCPzaxexCNf0kpLsGeg2jMIO5HdZlKWIZhJZRtMGF2CPSeDsTnsSYh0Rqs7B9RXypw8hmEaodnh745E4aYsd1GWl7AXOW6A/y1wH6aNjmG/wl6uGqpbKWtPIlj9IqQdQlbzaR30ntgetk5Yh5tn994eWFF3aHFCU1fKYp3bp9p2XmjvsFTYuaHO2zSoc7JakxYcrb2mJT4rpM0b3PLSQn2hrGku4nMQoYRNCK8HJs9f0jl6plyKmZ48SHK8wFLMycx9mAevatsbw47E2vtlGlLU3vqrj5WPM9gW0+pum8lv/1DnuIl6flj9OTHs1+pGYmMfNb3p5zJbvz0wgeHUVNhuoYzTScyIXiM4HiDZ0ziOxLNneqUxrkzHsJcxga83pvR4DzsvrkcYCNuEcrfGrul5qbSNrerEtm0e0v6IZEUyvdJzZohzHObYpGhTdXuSvaOR6Fjn1XAtmjrJ3jGkK5r4xXKXYtfoXuBq7LiTXtjEZi62gttShItFmBH2pBR5NW3YjsSxQTV9R8PVfTN7+RewUXAilH2uwPqzxcFU7D7Kcmcm3r1Ehwwi3RF5HJEfVqhHus+6PaSP+z/T9etEIqS8QFkmUc41z8yrc1F78/r8rPVBOr/fhfr1oH7fW3idC/bL5vVF2Tqnwy4P5eatflRq77paKcvr7+Kq7stgJmoAlOUUbHVzGnZ0Qd6ZrVD9eJsttxOwgpKupCzXUZZFlOUbmOv40ynp4diK77vk3/MscXU777ihxuqSDjsOuHfuwu6HYn30swCqrOiy/oJ2qXhHYffySzS8RzG/JZhDoPsw5V56XKm0B3QwZuL7Auk9ZWXZjLJ8nbLsQ+LNeSm20nk/yT7JTyjLdpTlIsqSnO/XsL1LMI+/D2F71Pthc68pRAVb8Zi0BFuZvJdk/2heOXljK9j405jHzgSzGmkXyv08Jnz/HHt+6wTCjEKkMY7GFGunh09b8seV2LcNxQSiKys4ExmB3YthQeHZGVMApU2pq8XmwmUZQlnmUpbnsLnQUkzQ70Gyn28wyR7Cqk0YXShz8hiGdQJTwt8tSQSfESTef7KuuFfkhEF1g8RyTBOVJdv5b4dpjm8MduEPFpzmvhxoneO5KmtaWES2U19Ow7atzAnLq3OsXzpuUXuz5KUFu44zWTMTn3oED2WXYxrIDYARbVqtiB13uo6rcsKgfns3GMVL8VnJtjcvbZZK7Y33LQo4eY2pCfW5ERPK8sqNFgLLMJPA61evliOwzjo6FSHYsGfve15+tTlhhHpEM6L4uwYTGN/NhH2YCeuHrVa/CyhdGBTavQhbBfwQM19cXVDuUmylotKgk/cM1oQ8Z2Ca5hpM8L6Okt5ESW+lpL8in7z84rP5Po2vTuexA+ZxdJsKpo955fbGhNn0u/5VTMD8Oiagz21Cfl2wgTwtVDTETGG60HDCOhLzLLsCc0yQ15+0xt4xwfbi7FdQFzBTsFHAGRWOCskrAxoKRy1IvKZtgk108ianRfnlTdCLwhrrU7PxKppm5/ydbltRGU3peyu1t6n7nIvKIFNONCOcVxdi2vhfY45+2mFeoYtWyqodb7Plria573EyXBPC7gagpJ+Evc/ZZyiP6L242ItjcV0a9LNT5wyJioIPK8ULpO9Rt7qdU8XjyiysvXnu4sEm1TMwxWV/RFpTltMxZdNJmDIzHqORrkv0RroCU9heQP4xFdW0I/4uGpOK+oFsOdl4NVhf+F7qdzWsJn/86Ub62W0aB2FOvn6tym8x4TTvfV2RDcs1kTQhbBi2T7Iddh9j+xpTKlSiBTYH6YJZkNxDSadQ0gWU9M9BKdgfm0PPpgkmjI0KZSIyXURURA5OhV0Zwm5sYkM+9YjI70VkkogsEpGPROQhEdms8ZQgIkeG66IicmUqvFs4U+x9EVkuIjNE5CrJTDLEeDiVx1ap/31eRP4hIgtEZJ6I3Cz1T6pflwzHlvOnhL8/IdHGxCXYxamw6MZ3SU4YVNeBL6qQdmnIux+m/Z5FSWspy/WU5XnKsnlOfguxwSR7xlS/kFdjpic1IY/F4e90/Z7GOoWlqbBnSDrHqN1aDtS0Y2k0oUxrnxcBbYO26Z8kGu28dmTTgr3w72MT/l5N3qtTn77YJPYWAFXeWr/N0iictMf2E8wjaV90PBIntf2w56IW4ArOiqYY2fbGtK9DoSlLvA7Z9taQeFWLv/PYBhN6HgBGMq1Ow9YeMzd7l2Qykz3rpZaG56wsqtCO6ZjWemUq7B0S+/d+mClQe+x56Bc+czDBcGEqbC4mFEavoHGg7AHMYwG9sAEwe5/jczmL+p60PsTelQ9p/J2bQ7L5PNalZ/iO9ZtEWTahLDdTlu9XyC/vvsU9qE3znGnP9DbYKgoUmw3FdizGzIdjOyLxmu4NPKDKX1UZr1roCa2oHWD34GOK25GONx/TvkfPb+Mx7ezIgjLS/Wx8btP9TvoszcMxb6AryD9TLZvW+tQL6UAwyyPZU5Yut4EH2Ex+9euc7IdcQXyekz0qy0JYTbgGfeuF2Xf9+pmhYOw/Y/2aQk0oI44Xede5aKzJshBol2N+FcekdWG+GPuTdB1jH5cWjD+H9b+/xd6JPuSfMRjr9xHWZxdZFeSVuxBoHUwkZ2HPSDSzn0dZfkpZplCWQ0ju30psBSdvX05U7DU2NuXVJd3PTgA+WrmqdWzH6oJ4r5E8v3FMsrj/qrvf7bF3MI4/cVzJHt+RZRAmlM0AWtCTwZiX1O9R0q0xk9O/psp4ExNyoulrJcdA2XZMI9mnHpVzUWGT90wvTqV9h/SetvxysnWJfX4UpoqfaZGTEHkDkaOClc/CkN8ckj1eStPPDUvXpc4RSlCM5tU59h0fk96G0JDoCOYZrI0jQhkrsPG/qR4YY7krSZ61XsDblKUbZbmYspyJ7T9sgd2Pd/CVsrXiBOwlvQ0bFPYBHhbz/laIiPTDPLHk2eJegS1x1mIa/A7Y0mx2cvNNbOk2m/cQ7ODBXTDNwUuY1ndMlW2qHhs8h2KTxhWYlmEhyQHK0U3+EpKzUM4P34uBPmHjqYV9RBy0b8Ns04tegIVAr7Ax1tIurzsY+arw6YuykMQ+fDY2QOUNCLGT65sJr8E81/2eyo4H+mEu328FOjOPlUA7ytIl7KdZgA06rSlLd0p6OfXdOJ+DafhbH8qdUaOTPmdtYV1YSX9NsZBS1I7+mHe2f6TKXFPigJTuD9L1uwWziV+eChtDIgTUYKaILwBsz7PdQ57pOqfzu53gASpLMHVYRP5925vo7bOyUPYe9ky044o6D2p9KOnDmEAd29Edex/vbNFCwQak7Arcwnp1sVXZlSG/f2CmE4pN0PoEj2V/T9VxS+w5jVrnGswUcAE24Ylhw7CBrWsqbBNsctQdrZs8xDP34ub/haHcl0nOGqrBBoWoBCm6VjHta9jhpjHtBiHtRiRCVTusT9iGfE1vw2uV5BdXmLasUJc8RmNa3RWYoLtDI+2Yja0mxHLBBsRdm1huUTvAJnT7V8gvho/HVrNqMC1px5DnQkwoyyvjE6BncJQUr7G1zTCX7CLdsXFiPvYO5pkBZ9Nanzqrrn5/x84VikJZNIU7kGIWAn0yQkrcI3k35hU0Pj+tsOfxu9gz2AO7l7djewPj5LJ+/V4gmnbehrmvr37ClHhovR7r46Pg0FaEtAJzIdC73jiVT+x7k347MWO9HBvP0mezrQlJv5gQVxnSfZFg/Yxi5oS3khwpkKUGe1YeJDGRLio3/QxGRVxPSvo9TDhYhimq2pJM2GO/9Q3CGW/kvw/zc9qRR15d0uPFrcDkDXu9HRV22XsZ4/2JZEJfg5kxmhndpLoVsD6U9A4S87oa7H1+vUI7wCbVw4lnqA1jG+w6PBj2Jf48/D+W8RAmCEShrAd23m36nNE0S7B725uSPkr9cX1brP+MB6pnx6Ra4nyspE+R3JM80n1CpAab883Crm3+NbDn/BxM+PpueBcWhTq/SDKG5I2jDSlLL8pyIWW5lbLcSFn2xubP2fcpr69cGMqdAtxQoZTNsPF6/1DXzUL72mBK7bifv1piH/0ODc8j7oxtHziFRAj7PtYf/meFMhHpKiK3i8hcEVkmItNE5Lrwv9Yi8oiIzBaRFSIyX0TuE5H+qfQ7isirIrJYRG4RkT/lrDYdKCLPi8gnIvKOiFwuFdwSi8gPwope3qdUoTlbq+rnVfUkbH8I2E0bXpRA7OG8CbvJd+ZE2TB8/1xVv07yEA1K5TEUO/flxzRkH0wQeUJVj8Qmpx8DXxSRIu3xmhJt/S/HNpYOYzVzgUHhkNHIR5gTgLRXs4+xSWWvupDn6El9rUnXAq3aXGzyNrAuZAJdqL9E3Yb3gua/LJtS0gsoPkclajGGQ3C7m5gWpcm+7NnDn42Jde9K+jn4pEHYyjpBso5vcG3bdLzgAnhug7T5zMPamE4Ldp9ak6z2rI3GdhYmyJwgQgsRtnhlxuZRwEzXb1FOGGQ6tdasiuZ4sc4t7nj+0E/S7WiEuam0EtqcbV9Re7fFJiumtZzHKKwDT5dbG9qyZfAkGjW6H5BajQln+XyYThvqUi8s8CH1vTtBw84+miVm21FtvDnAKOxcwGjOUnetGik3j7x25KWdhB1MPYnkHLQ86tWlSfetLEMpy68oyyWU5UeU5cvYPjLB9pAMo3hfWbXteATYT4Q9RdhMJDguyW/HsCh8NPH5yys3WjzcAOwcfn8IbBg2tqf7hOyqvz1X9T3MHoI9vwdifeZBBSaMc4FhQdFlrGhQv6glH1EvXj4fhvIGpOqc195qwvqyuq4vT8aVCQ0mjOnDpxsj25d32Yg3Y581LFXnudgYN4DKNBxDElfrkZY0zbNnlnrjQCgjOl3ZOhX2T6yvPwk7cPwT8kicGKTJe1bnYUJA3pi0eSYewDaU9BckjmiqKWM+NiEeGcpoWXAQ9nLseY51aTVzXt/obKTuve7Z6cMVId42IV6LF97eOo5Tlfvet+mE9fvZfqLa93oQpoCwM8ferbvnnUO++2P7qhZnylgVwrYIypY8pX304vcR0RlFUTsSC4psP5s3DuSRl7ba8WJf7Br8DBPidiF/3IvK8nQZeTwU8jsFm/fOxhQBdf1y8ORc1N5suXmMwOZJf8Du4QiK2isyHJHzEdmTYj6iYR/9AaZ4m0HijCWaK56KCWTrznyxSr6NuSh9E/gjNnjHCxtdO/8N02BNxezlrwcQkS7YJrzNMNOTDTDTjDpEZG+Szbh3YxPIs7Cl/CK+hh0Cm/cp0vSiqi+lfsaBrhabuBZxBjZhOIqGGxLBVnlWAucEYfVr2M39TWhfa0zzNQH4SU76mOdAEdkAe0CjYLNlTvy1YRjWWX+APfidGF9na3wYiYAVvQkdmhOWxJueEtAS8l76uHKSpJ2Sk/YSpmIv70OU5WqKn+Fp2GQ8uuE9qaDcvE64D2QGjztZggkVh4UQwbTwtfXCrPOvN0HakWe6YoPZl8KgdCJmGrosk18DgvvpycAhIe1JYXUvOxFYY2cfYXXqW8Ax2GD//Jbfe2UBZup3WJgQCjZ4Ts+EQf7ANgE4IHSghx9+1R3tQjuyafOYgE2e22J9RdrxRaThvbRV3m0ws66vYZ6Ptg35HRzOkYnlvgCUgkODqJl7EjhChC1FOAl7zyYAe4jQSYTPYx3yBODA4MY45jcBOICytGvkuqyNoPYcdv36kwjjE4C9w8S2Url5TAD2CA5DKqW9Ftvf9CTJgfBF+Q0XYZgIfchfUSoa8P+CrR5egWmXe2ArY3dg/fWFwA4FplgTgK2Dx7NK7biphdT+umWLVTe3kNrH27RanhUA0vl1wO57e8wNd7XtyCt3JPa+/xDTtG/WiQWvYX3XAWHicSxmAdE/eJ9NP1c9MGEuhvUHLkJ1d2xi9CJB6Chox151aVc3qPcGLOMVbDzZn8bfS0j6ohNy2tseW+FN046GZxW14Y06E61kDPmwgZOB6h0P5NyTWzk6mrBFz3onkjfW5DMF6/PSY0jeu7Q2CrGZmOBTVz9V3sXmSeeKsDnwC0r6NrYf8jfY+xH3S2aJjnUq1i+cwfcW6XElehhO5l8S6vc28CvK8hWgG4toRbKyGmlw7VVZhc3pThChI/b8NyCYqE0ADgr7m4/pd9rMJdgkt268aNliNdgK0jdF2Bq4bNsfvCDYvLPymLSI3tj4c2hQPsR41b7Xg0mEx1qm0x1bbfsRds2ikmwCcEhmrHkROCKMDZXm3OOxcaV1YTuSsXV3EbqIsA2m5JkA7J8Zf/KYAOwsQo/wbG1XUEYe3wrpjw11/Vb43jt4AY7ljgV2E+EgEY6geL7dFXu+ugHXYA7eyqFtN4hwPbafeQKwhQgbBw/R+8Z2BGc3Vq45wPqq7sbllOVSyrIjJoRNxixLniMxX6zfXpND7sXmPzcjsgUAIj0R2RWRjULcccB2lGVAqr3PhXoOJFFcZ1fG/uPmi1ES/hcmlH2ZoB1U1dipTcAe3mj/uUtYYdofW72YCuyuqnvT0EY0epIZh63GxE712KLVMlUdpKpS8DmusQaJebn5Y/h5harmCmVhv9klwA9UdXxBds9j2t5+mOe3rljnEvee/BAbtI5WrXfuV+R2rOMZjAlLr5JM/KsdsKplGDAJ1ej2tpZrARMgfoOd5wTWUS/DXqQHQtg0bBn9UuJKxUf0xjRmvTBhZzX5L/072L29mGjnP4eeoYze4bMs7K05YtXqli1VOXllbasHyXFNHQSNCcDxIozFnqHY4daE+hTtcYlhg0K5s5hDD8x07gzK8ig2UVqJKSBOD2G9mFa3bD80lDE15DcOm9iOBS4KWjPbJGxpB+XUIzIOM1l5AjOTiNdvdKjHeNbSA6Mid09n4L13cch7N3LsF4Nb+HHY+/k4QWsbwvbBnt/t+Jg22ObofUN7H021dzhmLvjHVNpdQzt2bqS9G4a05a7Mi6uPXwll3E3+fdsQey+uQvWPmPnU5iG/kZjZ3/4h7tNYBz2VxMX+Q9ikcjzJPqZx2DV+CjMHimGbhrDDUmEbhbBoTlaDTaR6YQqkKIB9B3uufk0igJ0T4v2SZGXh+yHsF+H3Y9hkaBo2IMZye4dyT0yVe1FIe3HBtYppozlk1PDVAJeFtOcDNRfe+cM7n35jh4tmz+/VY+qcwfPHTd/qsgr5gV3H5zAtcg024PbClFdFdbkceya+ha107gN8zBY8xBhacCZv0pbxNJwMxnJbYtcnTvxqMBO4XtgkokbHyAG1t7Y6dNUtrW+rvbXVdctvajcwJ690O24h8bZWgykPe2FCRO8Cs7UarI/sha1k9cDe07+iehF2TdvczwHRrOm6UMYIbPwklBPNU2Nd/kI8qFT1h6heISeJoroU1T1RzTMHjmlvJa5wrq57N+MRCkK5Tul2K4nnsDymY335T7CVm91De6eE/KKWfzg2PvQiERZHhPS9iALa9SzElFq/IjqSWEhvbKLWm0S73PCZKUsrynKK7sY1uhuXUZZLQrx5oYy+gG7H892xSdkZIjyJmf1PwxQAP8H6q1xCH/gq8A0RnsDG7hqs3+8dylmTA67TZURPrEeGcers8K97sPvzClEoPIrf8zXe4NvM5DS2pVRPgRyJY8PwUMepFE+yx2FWN08APwlmcC8DX6MsT2P9GZjgsQVmntaTCXVK4u2wazCO4mvwGNYHzyea3xbXZTTWF12TCtsPG2viyssd2L19AVPMx3h7YGPr9kFo7Eai0PsbyZi0S4i3CyuIx5EcGr7vy22HKc37Afuh2hG4BWUwcFzt6hYdgJdrV7cYjM3xxmH915PYmAjWF25BFB4rX4MR2NgUFQE1WN/cC1PoxHZ0C2U8jAkHcfx5GvMuWamMjtg9fwzrN2sw79G9MKVY3jVodfzOfKFPie3lRE7ofwTbHrMLB7O6bvx5mmT8eQBT7N+D9cFFK90HsYJRzOd6VlCLmVTf25oVl4EeDbo/1o+MC218GLuWHVLteBIbY8HmGSdi/fZN2Hs6AvgDqsdiY+JQ7F7+LrT3VBJz32dDPjcBP0fkQMy6Yhfgz4iczSpexOSdJ7H3AqyvjvsIoxXc4FCf9bB7uU6Fsmjak9b+R01MtPG9Envw/w8bWOYDN4tICxHZCZu4Xo51OMeENO2wyVx8AN5QrTtEss4tdWBQ+N4TG7RPCb+FgmXBtTBfRER6Yh3B9tiK3jkVoh+KXZtdROQBkj1hB4rIJeHv27Eb+z3M/ONq7OWMnc9R2CBxVcgj8isR+YKqfoIJuSdjAuAxWMcClTdmrwkbAxNFaCGoKrzBYjbEXoj1SCbny7EXe32SvR6rQ73WqwszDdV7qM5BdTYmVDYcJGzT6OPYtbQJ+wI2AN5H9QNUPwBm/ZUvbilH6dVtj1l+ffuvLf5ym2NW3hS8QeURN3HvEr5rgDmovo/qHGzwLxLK5qP6Tig3xnsMe+bS+/5iGRY2m+6YJnNKpowYb2eS965+2mJivJ2wDi5ev4mofoRpFCttzm0bvitp0A4byIxtDuGem4/l5h+HuLHcXUkUL+lr2pp36twAvx7a+w7127styapOuh2VNn/HeIjU/pEAAAXfSURBVFsD7b/Odd2xdk8KZUwj776pvonq+qhODxPWq1DdNpXf50j2I96C3ade2P14H+vD4qR0DrYiG50rbEHi4jnmtw2JOWy6zl2DP8a+wBuhzvGQ1ZoQ9gGmme6XCsvGm5IJuxObJEZh4OlUuVuQrJ7WAG+GtG/mXisjtm0EyT6DdNopQM2P7rrw9ztd9PT2fb45+/ANz5x6wqjzxhUpn17C+rFBJGbINcBbqfz6hhXN+phnx11a/oPzgMMo6QGMQTiHrwBL2Bq4gd+FfLI8hylvBpOYitcAU0P8yUAHajkfE9QvwoSlopWymaGuG5AIFTXAtFR+8eiCLDXA9BDPxrGdeIRL6EhZTmIMe3EQ5+zMU29gyrqu2L0De67HY+PiQGx8fRt7vzdIxauW2I7uxPPRlL7AjFA/20fzGO2x/S8dQ3ujV7V6BAHicex93jbV3ndT16UWuwfvpu75ykzYm8ByPqAn9gx3wN5NWFY3XnyAarR2yHt+z8QsdL6NTaam0Z4NgZlhrJmFjY2xL2qB9TvpsaZtXVgxsc+PSqQaYFao3xzWjQfGdJ8qAH26vP+T1i1X/AugfdtFj4RVoLNZzkxmcxvz+HlBXv2w6z059DHvUjw2pPvj2KdEZxU7hLrUchT3cAkPcTcvcBuHc3XdCudr4RpEF/l5XIet6LWg8lwl1uXzJHPN+mONMYZk3nQ39o6kx9Y2zKjbPzYx1G869ceknYB2vEeHUK+JmbErS38Spw0AM1bRcpAcpZe2+mrtK62+unLvVl+tPVOO0scz7YhjTZlEGd2KhufAZa/BtkAnltMCe+8nh/pFBW/stzcn2V8X044mGafyGEtittqzpVlT5o019VFd9ccnVGaNMe+G796mcvNYFVrUKTW2IPSHqrzVvu2is0G1hdTO6tV59sTcmhzFfI5nKN/kdY5nI47iLkVkBW2HLqft87W0fEORVzABfBE214/K59iOoamwHbBnYiFmnXb2EtZ77jtctkKEQ3bnsZ4f0e3OEP/t0N43MKHyHFSPlRO5CtVzUd0nXOdt5EQuxMb6a3iPZ0P+A7FxrlaO0sW/ePDb589f0nn8Rwu7PfPU5B3PCHWdiuoybJyv3hGbqlb8kEi9vwy/W2LaFAXOCmFt43e4ORPC/3fCBDYN+ayPPXBxw2oX7FwCBaakyowHfl4Zfj8Yfp+eqduQCvWenion+7mxQrqB4UYp8NOc/3cOD8Kg8PvCCuWMDXEWhd+7hd/Hh9+vVlHX40KcNqk6DMWEotXAho3dw6Z8KtTDP/7xj3/84x//+Mc//vFPEz7VzsElWZzKR0QOwpYhwSTWrtgy6SfAUFWdJXaA5YGYFncFZg7UCdvvtB/mCekjzGZzFxJtZpTop2EC2mPYRsg9Mc3EVap6hojsiwlmy0JdlmLCX3dVrXpZsBpEZCYEbWI0qTDKqvq8iByHLUtOUNWtctLfiJnLXKWqZ4Swv2F2tVMxc4mDMQ3Itap6Sk4e8aaMjCaRIvIGpolegZ3l0AX4raqemk2/NqTKdhzHcRzHcRxnLVDVSpZKdTTq1UhV7xWRozH73aGYYPQI8P3UPquXMfvZgzGzxBnA+ar6iohMxVbH9sKWl39CyoWlqs4XkQOwJenPY+Yl94W8loc4D4nIIZjd676Y5DkFW6Jc10QPTgNI9m2AmZU83zB6VRyH7QXaI/z9AbY/63tNyOM1zP67I7aMfgm212SdUu2D4ziO4ziO4zjOuqHRlbL/SCVEOqvqgvB3C8zWfShwoqpWcsHsOI7jOI7jOI7zX82nRSi7HTNbnISZN+6ObaAdoarzK6V1HMdxHMdxHMf5b2ZducRfW17Gzvk6Dzvj5M/ALi6QOY7jOI7jOI7zv86nYqXMcRzHcRzHcRzns8qnZaXMcRzHcRzHcRznM4kLZY7jOI7jOI7jOM2IC2WO4ziO4ziO4zjNiAtljuM4juM4juM4zYgLZY7jOI7jOI7jOM2IC2WO4ziO4ziO4zjNyP8DAgP6S0H6mc4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.8833992\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 3.8073559\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.6366525\n"
     ]
    },
    {
     "data": {
      "image/png": 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Tzs0ENlDVpSISO6UfMCPUaxvgWeAd4JtAU2B4+H0esAK4A2gOjAR+qaq3ZbR7R+DJMl2zk6o+Vabf0kJZP1WdViYvx3Ecx3Ecx3G+4jSY+aKqrgC+gwk0mwJnY+aM74nIN0Kct4GTgMmY5mtiSL5zRpbHAIcAKzHB6BJVPRIziZRQRpr7VPVQTFM2C6gCdsnIdxQmkC0Axob3d4EWwHGYVq8xJij9A/ipqg4F/pLT7qdUVcq8nsrpsv8eitKKogylKFIumgjNRBgiQhKvKC0pysYVpG1aK+06RoQmIgwVqeM+KUpjirIBRakrXhOKsglFqb+G2soYRlGa1lFnCXWuJN4QEZrVuy7/IUQYJEKrGoFFGUJR2tSZuCgbUZS2FcTbkKK0W+NKril2vXRcV9mJ0FuETiVl9KMoXUri9RShc0ZYabwqEbqW5NebonTLCOteQf26ibBeSdqeFGX9utJSlPUpSlWd8bLL7SJCzbRF6U5ReleQtpMIvdak3HWNCO1E6FcjsCgdKcoGX3K5rUUYWFJuO4qyYQVpRYSWJWEtRRiUEVZnfuucCueaeuTXPOS3TtZVIjSuaP5ZuzIahTIaVwfaXLNRXfNUag5pkhHWtMKwZP4pSqPQfy1SYUJRBtcIqxRLO5Si1JhDRNhQhDrzy5p/RBiYE9a6grANRGhTEjYgJ6xtSVj/0rB1TlEGUJROdUfMTFtrrskia65xatKgZ8pU9S6gO7AncBkmHHUDLgIQkcMxQehK4AfAgSFp11qZwWRVXQksCt/fCu8Lwnvr0vihDiswLRtAz4x8+4b3tsCZ4TUihG2gqguB72GC3wOYUPkBsF1Wm0VkAxG5tszrS51kv3SK0hwzMX0TuL16whO5C5E3YrQgTI3GBO1LQtqmwIPYGcO7KUojOVE0/UqlvSWkvYok05sQmVb9NStthWGBa0M7birTXgm/vwM8SlGyhZwk3njg2eqJQuRiRD7DNKC16iInioa012Fmsy9VCxsi54e06UXxj0Kd7xehVv+l2ndW6L9/Vk/IImeG/JJrUOR7iHyCaa1j2Mkh3uC8bilTbkXxRChg9/Bz1Qu7opwe6jyZovTNK5uifBe7v9+iGJwGiRwQ6rxLKt5xwBTgbYqhfSJ7hXh75dWv0leZ+h0IvA1MpSgjc+NV3lebhb6aXC1EFGVX7JqcRlG2C/GGh3hvxQW+CMNCH7wlwoAQtnEqbGDIb+tUfruHsC1DO6ZRtP5CpAqRWYj8sLrelu8k4F0Rhoa0I0NdplGUA3P7ryibpOJ9M79zpHX4365Ilbs+ds+8J8LWIb9BoS7vU5Rjsvo1pO2Kbei9J8JOIUNB5A1ErqzzzyqtXqXXRmbTaAs8H+pySGjHetjc+A5FubBe5dri9waKMjFcJ3l90Bx4DHhbhBNC2vahLlMoyq+rCypK6+p7jRrj+7xY57AofxC7rs4KYU2A+4EpIvwgld9+oY6DU2GXU5T3KMoR9em/TGycfgiba+6qjyCV06eNgbtDfg9UCzQiFyDyGJIv+JW5Nq7BxvKbk8hyVbjOm9WRtlJ+Hsq4K7XBeS02fj5HUUrXTWl+jI3H96XS/jCEPZASJr9PMtfEsDND2MMpgfBirP/GpRb4P8Hu19cpStfQB70R2RMpWzdI5sI34+aPCEdjY9uYcH1nIsJh2LjzfJx/RPgmNt69GAWzcG2/DbwUhTAR4vj+ShS4RNgvhL0qQrsQtg82po4VoX0I2zPEGydChxC2e4g3XgTbyCtKD4ryEEX5dVhzrR1F2S+U8T5FU4ogslm41o6uI+1uJHPDtnnRRNgU69MpIvRfm+rWa76tD0XpWn2dNRANJpSJSFMR2VZVl6rqI6p6IRAn1Lgj8O3wfgOm/Yrfswa4VXV8L2VwrAdUXyAfZsSbFt4/BlpEjRbQiuRs2G2qWoWZQp6JCXcX5ZTbk0S4y3plCYZfbWruNJ4OxBvzCBKnLUOAIUj17tuBwKHh8wnh/SQSLejBULIznLAHcGRJWoCNgD7I2ms+RNgKODV8PV7yNXJ7YxpTME3rVjnx9gCODZ+3xLSvAIOALkA5TcD2mOAPtiGwU/g8MKTtGercFzv7CLbRkZln0Bz8KlXnvuHzBiG/tHZgILZRkg6L8erUNqwJYSK7IXwdDowKmpJrQlhPkrGgJqbJuS5860FivtwPq3PfEK8z8PvwWzfgqMx4a9OObAG7JebUSIAO1Lx+15SbMM39esB+YUF4G6bBbw2cHOLdgI1bnUk2uG4IcTphTpfA+qUN0BE4ONzft2HOhloAp4WwW7FxuTnJWNgL2zRLa1euC/m3BQ4LaW8JdWmKnQcu17Y22PnnM8vEq8L+t7QW5pfYNdCcZLz4fWhXI2yxmMdl2PXdFIiLki7Axph5+n+S84Ch2DVzfAj7Bck1ek51TNNi9akjvzOwsXYIcFeZeKeSjGffCe8XhroAnB0EvE7AS8C7FOX34f8tAIdj/ReFxuNIxvd43R+DHUtIwkzY/3uo49NBo/UtTAjoD9xG0Tax1oKTSMbRQ4G6+qwujgT2DZ/3xvoWYEesffWak0TYAptLAY5LCTMbYtdh3RrmussYTPLfHAx0pCg7kNzLm5NtlUTY1Lk0fN0bWF+E3iRruD2AniL0xO5DsH7oEzZL4mbqTkA/irIp5hMAbB7fh6IMBX4WwjYE9gufjwT+hd2L2ZgGOdalH3BwEIbimD8Km1uy2tYauDF83RTYLAhhcXN2GLB50LZFgXkosGUQ9P4YwgYDWwdt4C3Y/bshsG3YoIhhA4HtwwbFLdjYNADYMQisMawfsHO4v/6B9fvZpO//2o1pgUi/sgKsaSFvDXVpB5wYfumDXWv5ApTNNX8mmWu+mxs3e/6pDJEBiCxA5Ef1SlcfijIKU9DMpCjZ64v/AA3m6AObKJ8VkcnYjuRikkXBY+H90/C+Nza4770Oy99fRO7GBrf1gI+wc22lvAa8gE1Or4jI85h2bwfshrgV+FREngp5DAvp5mYVGswT18hcIpyHS2tirhKRhcA5qjp7TfLMxSb2TYHHKejinDjNgCI2gF6DDaoH5+RYhQ0s3bDzewdlxMlLW0pWWkgE2p7Y7traUHvQsMHwAmzSuhPT3h5aK57FPQXTRv2duvslvk/MiVNJ2lexSauSa2tfSJmrZOcX6VnynhdvXbIzUGqiuD/ZdS5lX8g03Syt816QuVP6ZbdtJ0wYWycEQbx0cbE5JYu2sBDavCSsGyWbCMG0pHS3cxgmiKcZApkmZzWul7DA2aMkTj9qm5PXxgTxzeuMZ9T438Ii9oCS/DqQs8hMEzZgssaYL/vayKPmWGTjUO36FaU/8BTQi6L8hoKelZPfSanP5bQNlY7RPycR1E7GhL7DUr9HgSJrIZYVdg7JPdwVc9Z1Yur3xmTf4/WhVjtKd9v1Jq3PPH1ITnj6fphXj/zy5rj0NTitHvmByE7Y/fRrzELogIxY2e2wa6478CkFXY2Nx6X9sz+1N/r3ywjLmn+y2pvXB71S7y/lxMm6rnaDEnN4iNrfY4FxFPQZbIwoNRXcEXM2l2YHao/l2wGlJoDbQC2Tva2gxJzb/ptSz+ObUXu82ZKa42Jn8tkZ0wifSFrjWpPtqV1nqGy82xK7LsoiQg9gi7rilaE3tiaov4bNNo1uJm7EFXRqRhzBhMu47jgVczL4H6chzReXYjvfyzBh6yhMkLmEZGfl55hTjK7YzsbltbNZY/4PW5QNx8xA9lPVJaWRVHU1Nnj9AdtFOBbTVjwEvBiiPYbtnn4Hm5wegpQpxrrjGGz3MXJICKv7jE19sF2rscB9wCtl1OM/DnVoET53x/rzGayvigCItCIZvOINPhIzkegM/DPcFCOxQbY9tjtUY2JMfR4JvIcNdPeGMhqRLESrYvyYptwEmxNvJKYd7Y7drGCTxCWYYHkmNiCNwpzNVBGvWzPvuh7bATsPG6hHYpPoesBPU8XXGPhK6xI+j8QE2fWBc/PShngLQ7m/qCO/xdiO5CVl8qtPWA1yyq003khgNda/UVs5EhszNsUWVHma8JHAcux/2Q87Y5pV55GYc54tMAFtRVa8rPpVGlamfgC7Y5O1mVubNuD7FOXIYApVn74CG3t2DO2NYYeEz3NTYd/DhK4VJGbYp2GLhOWpsDND3yxLpT0WG99mlZQ7mGQDrbSfN8HmmYtC3otSaU/DrtUP62jb97HJeHpWv+SUuwE2Lv46fP481bafYgu6t2J5JeX2xMaW32PaqE9yyqiYCq+NWoQd+o0w07ju2Hnmfth4+kds/HwuRL+OZMH6nXS51Z9tAToY28Q5kLCwL40XhNrhmLOsLphJWUfsf7gHG6MfDkni4nlKquqjMNPRYSQbZCOxDc5OmAlkDHs5hI0J88D22DV7EfAZtvjfPLR9byDTS3JZRLaOJsmpueZFbJ76U32yKjMnjce0sNenokehrOKxMpVfnH/SDsPKjk91VP14bF6I18hI7Cx8bxLrglHY5nJPoubKjhXcHsJfD6aAI7GjIRuQWF2k558rUmGLsQ2cS1NhS7Dr+uepsDnYtR21LaOw62ADam4k9Cp5zyLWbyNMs6YhbBXwDWzDNGqJnsBMNp+mKAeRzD9bkViojAx5bJuqSwzbnkSTHMesHUksY2LYLiQWGTFsNxJrjhi2J4klSAzbh2QDOFrZ/BZbx5ajT/o9x+wvlrFXaPPC8L2S8S6mPYjk/8oijr2nhPovr6PepfROv1c839q9fk+o3wHA73LyH4htNC7C1lrrBBG2EGGPMpZWtWgwTVk4/1XOfARV/YjaO5vXpX6fRslujap2KPm+Y072n6vq6Vk/BPPE9PfPSG7OrPj5Zx3WIaX1+hK5nGTnZAi2U7ksI95h2OD1OKYB2CDEvZqCLqAoJ2P/T7ypPweqgo32RsAPVJkjwnnY4qcDcA0FnR/OD9USBoPafxjwM1U+F6kWUrpgWsTPKWMCGm9eOVE070YON9AI4GZVPhUhno+JA+qroQ7NQ/+cR0E/oijnYwJbNM2YhN3szWOdKehnFOVSoFs4Z1BVts521mF46JePKcpVJLtpPUvSjgDuU+VdEX4OuU48RgAPqfKWCJdB9WH8WJdSAaw0rLTcdc0I4HlVXhLhZey/HQk8SEEnABPIdxAxEniYgo4FxlKUsTl1Hgk8QUFfBqAoE3LirTGZ11pR7gFeoaCPhe/TghD2KImGaiMSs6K6GIEtrG5TZZUIk7GF19sU9J5QxmXYomEh8EdVVojwTghbDNykynIRpmILiaXADaosE2FaqMtM4M8UVCnKTzFtxifArRR0depcU+n1MgIbI36jygIRPsIWRHOBP1DQVRTlvJy2xUXe7yjoCorJObUM4v/WA5HGoHERcI0qH4pwHXb/rgCuoqCLKUqeJimmvVaV6SI1zGa/ADoi0hbVBdnJAZGjgBmoPl2mzpUQhdprw1h0GbYIBLiCgs6hKCdiZ1R3xwTm+8nXMsS2nU1Bx1CUD3LiRaH2t2Gc/RmJRvbKMEYfj20UVQGXU9ALKMolg384qRs2Rp2nypsi/CjslHcDvq/KFyJcKOb4ZX3gxyHsAmzR1RX4LgW9kaI8iS0o24Wwf1GUKSSbKJVyLbAJIq0YTV9MqPx1mKdOZ200b3a+rwq4iILOpSg/ANoFM/o2mIas4vEkNf/cUmP+sccFrceaj0/9U+9TQxl3qfKBCBdsM2iMYv/xVRR0JkW5Avt/jsaOIkAw3Qtp/6HKeyL8FFtLjgDuD/PPxdi8NwJ4QJW3RbgUm2vS88/lmLZ2JFCkoNOAG8P4fjFwBwV9D3iPxNlPT2zzqVwfjAT+TkHfws4WV2Hmh8+o8qoIY7ENjW9hwkSkX6jfC6q8KMJL2PV4FvCSKs+J8HwIOwV4VZVnRRgTwk4AxqrytAjPhLCjgfGqZokVrvtvA2+q8ngq7EBgsiqPpMIuBd5W5Z+psEOxDaU4fuWe4yIxce5bJs5ITEtomyxFmRHCK5kLRwJTKOg/QtpPcuLFDbmbw/zzbtY5sDIbC5UI4oQ1VTNgFSZjDMI0mktC+Xlroqh5PBAYQ2JKu8aIcBRmSdcIO9/4y7IJAg398Gjnq4ZpxXbGLsytMKcdWfG6YovHn1DQPTAAOT+dAAAgAElEQVTtRVwo20K4oAso6Hzspl6IHWDtGeI1xnYWUWUWyU5ITLuYgmY9j60rNthPSKUFmxQV20VdW/OiltiAXV0/HS1gg99fsRt4e8zEoXGqzquw3c3tsAPtw7ABoTU2GMR4qynoxySC5Gtl6twJm9hjWqWgHyHSBluopNP2TtV5qSrzc/JMx1umytxw1q9HyM8GYdM+VpWECfb/lavz2pKun6ryWQgbWx2joB+VSZsVL7Yj1rlPhfHWNVn12x27tuaEV30OGvfGJvdVUH0/ZLWtNzBJ1RazqXtusqrtWqbCpqjaJkwqv3EUwvNTCjozxHs9mDKl+68n1n+dEWkZ4r2vag6XUmWMD/dLuf+yD/AGBV1RRzxI/rfG2OK/NyZAzSxpx5Rqc+zy19BiTDNTOsaMTX1GzIvcYSKcFQ/mI9Ie065fXKa+lRLHxTdK2jGf6KDK2vENbGF8NAU9EbOgyGIgpi14NaQdmxMvlpseo/tgAvaEkPZjEiHv1vB+8dRZ/WuM5arMSOWXHrezyohmkP8OZTyH/Z8QLVMK+j4FzdyRzzz8b2PWIGze6EWiPYhj6iIKOjdHA1YJpfkto6CfkSxmx1E/IaoFNjfEfvlMldUkm3FrOj71K3nvTfJ/LBjz0+1aYeZ96blmJrZQXYyZpd6fShvrtyTc36Xzzzyy5pqaYct1tCyg5r0FtuFTOlZGDUavUO9yC/TSMTCOWbHc1WFe2QUTmrfANFbLqT3/zKpn2IS8sBC+tmGDgTHh/1EK9rzcMv2wiPJnJiudM/Pyr3ReLp1/6kMvbP1YlzfcQdim4i/C97iBtUuowxNg59ZF+LkIl4t5I94M+ICCPk5Bl1LTgqjeBEuDqzAZayX5/hFq4UKZU8pm2KTwIwr6IrYrU8usk2TX9G4ACvogNmGvoLb6twoTVj4On6O99vupOG0ywrKIaUvtgqswU5cZrP2COquMXthEeUcYCF8mselPx1sPm4D/EoSvF0jMerLqDDZp59U59kte2tcw7aOEete2l65NVrxu2HiQHoS7Ygu9dFhnbHHzZQouWfXLbJuYy/PTRdg79EGbWvESjWS6zrXjGV+2UJbVjt0xYWwotqNZ66HzdeRXes9kta3SPs0KqzQ/SPoPTHivNL8sKo0Xyx2PjUFxjJmqSno3ttL82gLTwkI4TU9MUIsbTWCmandgpvhRoxY9Bg5h7WkLzC7ZYLF2RCHZGIYtKO0ZmAV9KCe/dsD0sPCoq9zVQFqT1gaYWZK2K7boey+Uu2L5yuZxzHqvJD+o2f9ZYe0xq4x0WLsQVs58tRxdQ74rsEVbrN+0NcyvlLwxOp4je5f6jSdZ8yMhj+XY2ePy+Zm32SuQ4EreNkh6YEcG+gXnE81K6lz7fzMt/vbAbyjodcDBS5a3GEv+2FFa50rC4rnGdH6tMsLiUYhOwCvkW5c0wdYwlYxZ22Iaupcp6B3Y5sKatiOvjHUd1o6apsLl6IttZvSFXLO/uubCTuH6yaI+Y2qd8cp4VeyNHW1pFza98hha8r45MJGCvkBBlwBXhnXCo5hnzx9jVh9dCQI2AAWtn3mlSEdEpiEStWHDsbXgmeF9XKVZNaSjjwZBVY8lsfV1atMTm7xsYVXQhdW/iFwLdEL1aGxgXI65Qo20ARYGE6ctsIX+i9jN/VF4VZEM/gtTadsCSynoSoqyGbageyXsxqbJShvrHcuo24lAebLKiOacE1JhcfJcEFw39yUxqxmfEW8hRRmCmQZNCnWejS0OSp0hZKXdELPNfyukXRw+H4xNsE2o3S81CN6cWmXES2saj06FgQ0ox4XPcSIcS83D9+uSNjXqZ2cammN9UIWZm8yUI3RWqEcXgCaNVuxQnbYoPTDtwcfYxBkFyR8j0oLRtA3xumG7pJ9yBJOx/n4NG/zLm6itTdvsfM52mDC2OfBPChpNP24P7R6ImdcsAu6moFneYduENqaJbWuLmRUvAM2L93lm/bLza4l5UFuSakcLTKhcSkEfxa6ZSdgiuqpMfjPC/2rn+Qr6r4y2tQWmh4Xh3sAqCvrPjHhg1+WT2Nm2nmXbAdEFtFDQ+6lNVlpCe54jjGNibvNPws7e3k0ihA0N9eiGyHqo1ndXuK66pNuxK3Y/dwXeqWAx0ZbocMIcgzTHBLxS8/Q2wKISwTRd7vaYufl6wKxqjWkSbxW2Y53OT6m5wRfH2UWpMKufmcS2xjSf7YH5YV7pgy3ip1PQeB5TooCqN6nEhVxK2zUwlPtG+DwXWBxMZ7+BCStZc02lxDF6EUUZjm3gxY22j7D7blRO2izKzXEfY5uedTnAOQs713QfqUU5dt67f04Z6blmENZXszEhwMxwC7qqlfAZtoFXnTYIeU1LwqJwlA5rhP1/eeX2x+6f+amwvpinxWkkZ5Fewc5ZZZG0zZ5HOByYHsbA0j7tQdpZSEEXckTmPfdVCmsLzA1WTV2BqJnNog9mtrkTIk2Dg5dS4vjegXie8wieJbF6ALuW3wUQc9+vYaOodK6ZTyHzWbttoKZ2LMu8v4xr+16Yr4ajwuc8pzlDsXEnCmV2HjZS0NUcwTcwK7BfYRugfbDr61MqJDjOaqZavbGzachnx/B9a2wO/EM4GnBTpXl/7YQyp046AJ9T0GXBrrsF8DFHINi5umaInM9o2pNMnntiN3A3TFAAO4eyL7boSmvKhpLsjKUn6Nap7+cC38QcFdxTUr+stJSUsbZeOrPKiLszc8JEvhGJffJiTEA5G3MsEOMNL4m3BNs5+RH2PJcF1NQg1lWXozAXwT/Bdo3jhF+VU+cs4o5X6U55FTZofgB0D+aMUWicji0wm4Z4X2CCThdEmssJtfLKNP8J7oLPxISRWdhZkqwFa/pagGTXdDF2SPivmBOZD7BF2/ZApwHd3luJLRYWY4LWvdhiOR4wNzOLtvTEFqNLsMXSfdgzBqO73fREVOmOZKW0DvUbFMp9DtM+1hQO7LlgT2P9vAybNLLc55f2VTqsKpQxEdMiZ8UrFfRah7hZ+XUK9ZyOTYqLsfHiPuBDRHpTcyFaRfn6tQpp55DtQSzGaxbKXUhtr2iRUm18XrnR7O1e7NrJMlNrTe37A5JF8cfh854h/LhwJirOp0MwL4j7hM/ZQpndT7cCb6P6c8halOgFOe2IYTdgi+w/kAhbJ2IOJ27MMPNrQzJG34+NxxuRPNczq4yssKsxq4rfkzir+TswfOuBY255/p1tFpdoKVsDSzLClmUIflFI+we2CXB9qs43YBtYu4ZzdFcBAyjKa8BuwVy+lEHYLv274fPEVDt+hM0zB4XyaiOyL3ZN3YTWED5rtCPMhWdim75HkVwvH2GeCRGhD/a4haHABNVMM9NK5rh8TZlIY2xDaj7mLOlFzHzq89D2I3PKSIcdiznEidrf6WETpcmmvce1Hz9jONS8R7Lya5UR1jIjLJ12X+A3JM5XlmD30e8wxxb3h7BJwPqINAlnh9Kk89sFcxp2E6XXtAk1LYFPwyZZMHnWuq79hg5rg90jW2LjzBMkj5VIMC1pd2yOaYRdj1mWSLGMAdh4/DK2bmuBXS/LsU2ojzGrgP2A1SJ8W0dXp+0V0r6BnYPNK6MsZc7898YUANExzZs5WQzFjtwcgEg7RtMB2wBshq0Ll4Nuhglg56myOmwUHIKdW2yFbagvpFB9LrkGIvwGe1yFiHCBKpdjgv98YJitnbQrZq4ZjwZU/Bw1N190SmlHMinejpkybI4NAEswu94dsAE3DspnYINeZ7IPUpYuZuKubDruMio7bJ2VFiqdsCojq4w40C/FJrU/kzwnJR0vOidZgh2OvoNkl7S0fek6dw0HufPqkpf2I6DNVfwg1iHvIGsk7jSW5pf+j+K5nHT9BNtVTIcBrF8Pz4NXYy6zb8G8sOWZISyj9rWR1bbdMAcXz6py35SrBr+UE68KGzCnA6tYRA9sJz+rT5eGeFHTs64pbRvYAnouRRlMUV6iKH/EvHY+AwymoMMwQbzS/LLupbx46zKsE3ETp+a9Xkn9sqgVL9O8xTYQulPz/q+0zhWVGyjV+FcB76jyBYBqtafPocSHlyc7tlnsii1wzic8PD7jXFOl7WhBcp/8ELgSwoNma7KSyjZj6/O/xQVHFdC/TYuFmhEvtx0lnslWUXtdsiqjztG77/PYwvuBnLqBCWLvhdegMu2ojf0vf8UO6e+SE8vaVvN5nZBYb3yMPbOrcahnR8zz6Ctl8oPyc9z64cxvFkMxYaNI4oY8ei+dHj7nzcGlYS3C+0JsTFr8r3P3is8xS/dhpfktLxMvnd/KjDCwPp0ZXo2I7thFBiJyMCKdcvKL5aTLTTSciVfPizPiZaVtyLCVVPZ4mPTZzmXknyvLuh/i3PcRdr6vCtO+boFt4vTExrfce6lkg6nSsTcjI2mP/Vfxfy93rmxj4J+YxVJUACwO7/dinkx7AOPiZlB4F2wcE8ySyZziFGVDivJDivJTirKVCNtg690zsDVxtBQbHvJvgY0xnTABst7UKZSJyDQRURE5MBV2bQi7dU0K/SojIjeLyGQRWSgin4vIP0Uk/yGFSbqDROQVEVkiIvNEZIyIdAy/fUtEJoU8F4nIRBE5pSR9SxH5lYjMEJHlIvKRiFwaftsx9HfW69h13AWLSQbiNDtgE+Cz4fMCaj/zYymJ8DKGmm7GFxEWuo1ZGdXx6fQLgdZhYnuB7J3qGK80LdggsSCUsV6OgFMpefUrDYuDf2tsd+WLVFhevAmY9inWeR6Je/csj4Kx3NbYrlVUsffEdv1XA5zOdZ2wQaX2c1hShJ2b5RnxogYsvcCqwrQY6bCeIaxRCK/PAfZvAr9S5V5VblatYfqaZiG1+28V1gcfkAyE65M2nzXHEUtCvJkku/9R47ceMJvV1Y5nWmMLnMmpeJ9hAmn6oP66JJY7h8TEdTVUm/VsjmlXhmELuE7BO9x2ZfIr/S9jGQtIFn5Z8bLu4bx4cafzhZIylpK4N48T+WrsWqqqo34rsPEkjxhvFcF8KmcDoDvWf6tIPN2VaweEA99lyq2Z1hzrtMf6YG5oWwfIdKYzBLv23qL8ubLDsc2dd8n3llhpOxZlxMsinfbVMvHK/W/pchenwj4BaNNi4WKgRRBC0mmbBO+56TChppfddP3ewsaYdBmvY9fXcGwxeAq2eXEZdk9lUSqUpeea58mfa8A0RhMwbd1pOXEWhHa0wLQMaZfin2PXZOdNGL8hdl//WJXnVHPdc5eb4+Zji/Jm1H72VWRLbK54JnwG05RFoazL1Ynj63QZ0VQ7zjWzSISj6gV1l3az47yeTrsE+1/SYctD+uqw4OhhGdlza2tsPP+AZO3QGrs/okfAXtjY/nHqO9hzqP6EefROt2MaiXao9JqOm8+l6528a/+rEraAxKtnuXOWfbH/ZTbWp31z4sX7+gsSU7+eJOu56IFxe+BeVd5S5WNV3kilnU/9x5NKif/xh+GVLZSZ5cEgTIv2DiaUZZXbntomoXHcUaKliB3BGY85M2qJWarsCbyhyu9UeUmVv4X0wzGN9NTwOQp59cY1ZbX5Djbp3oFdaHsBD0s8MJuBiByOmdkNw1S4f8N28uLF0Ae7eW7Hzj0MAa4Xe5gjItXPUjgHG4xuw4Sa+MDWDzGVfnzFJ8ZDsPNdh8wFOgZX7N8lESh2xG66seHzPKB9MGkoYH21GGhFUdpR0CtJFixVmDnjaKDV9jwTy0o/KDFObOtR0GtIBJdS4oBbKsBUYaZxD2bkXV+yyog2zJ0xrcV4ksm8OwW9DVtELEnFuxTrs9iHPShokeS5PVWYoPJq6nteXXpQ0LtJntFThe2yTwRoxoq4AM5zFV+aZ1b/7URy+D0KYDuQHPbvGcK3DWHpxx1UQtyJql/97LzIAqwPXsBsy8Em/dIdwxjvFexejG3pj03kUQMY443DHvAd4/Ui0fJ8GZqyWO47JB7r5mA7a+8Tz5OZgBHP05xK/nMPLb/sMmZi5mUxrPQ/z7pe8uL1oKBzSMxzYxlzSR4BEftrCrbznPRzdv0WU/7ZkzHecsp7MozlvoCNRbHc7HYY5R45kHd/gAkjp5JsTtR8eKy5Qe+FTeSdyBPK7OD8gaGsqdR82HJpXbpmCDOl7VhAskjfLSevGC96Mzy9jnjNgmeymmltbojlLgK6ph9o3b7VvGhq2L0kLdTs17ywjhSlOQU9DZtTFmNzTUsKeh7W/vbAF+HwfnQyldfuQZhJ1e5APxazBLu3ulDQX5MnzJkm6lRMs7UtsB8ifTNixgVeDwr6exJHVz2xOelJgD15uFtG2iySMb8mVZhXzWdS37PYEtNwAPRFpDs2/m1McPV9Gr/rjvVZuu/T7fgbNtfE+awTtoHwctPGKxX736vTBvOs9HUZw/Lv/6z22tnS50iEsh4U9BGSzZte2AbV3OrvIptj1ihHAadwMk0wYbAHBX0Se2RPLCfd3qXYHNIZm1PuzKlffcMqGVPXNmw9Cvo6ZracRx9Mw/wMdi/macriODuV8HxY7NpqgV1HI8i/1mLaD+uoS1Y7KiVq/CZha8/eOfEGYhs1LTHBaihhQyS8x3Pxc6htRTAf6BrmpPjcuNMxL7BHYM9MPBkbO2s+RsQUAEMx0803MaGs9txQIetEKBORjiLyNxGZLSJLReR9Ebkh/NZURB4TkU+CBmiuiNwvIr1S6bcVkTeCFul2EbkzaIGuTcXZX0ReFpH5IjJdRK4W88STV6efBI1e1quQlw7YTFW3UtUTsUUq2AWZObkGgerK8HVPVT1MVU9Q1U1UNbhj1l+p6l6q+j1V3Zfg3pjETebOmAQ+BRiqqieq6rdU9bCQ/l1VPSu+SHbYx6pqfTy1VcJnmDA5kIK+C6xmNs0wtfVFxIciT2E1dsMPCQuz1SSCS9JXS2hEycB1Gr9rno4XFhyza6XNJjomSKeF2oPG2iyoF2KCVHUZS5a3iOdshlPQedhgHnfahpakTcdblopX2rZK6vwFtkCvJO3sVJ2lZCGXpjpeiNuU2lqhLKGkKiesUu4EfiTCt0U4RYRB9ahfjbDAB6QO0Afb8Kx4ZfuqjnjrmqxyZwEjKOjnJJqtsZjA/gF2lqKi/Mr01WfAkGgqFuJlhc3Oi1dBO7KuodnARlFrUqZ+dbatDHn/b28RM1Gq0Y7aZmZZ5XYVMSEnpM0qYwYwUMSEj/D8xeh58VxsTM8zX9wrvA8M77sgsl5OXZrEeKl2VIUHQUfmAP3Dgftyzn5mY0JUVlml8SC0J/W/tabmougLzLSoOqxvl2nRbCd3fK8jrDHm0CgyD9vMGZwK+wRYL5x7Po5sjWUUrAZipocFoBEvVmtG6rq2tgNa0IxDGM6ZwL8w0/VS4txQdjy5yLxsvwlcLsJWIpyaU+4iTGCo7pdwP1Y6Pm2Jnbsrhu9bYGuNgdiYQjNW9KPmfNHo7pcPmYfN4+l2LME200ZQ0Okk82/WXFPvMICh5765Grtm0+XG9UTWGNOIZMO7J7aZvQzTkrVjAceTLMrT1Bwrj9AmId6IsIap1bZQ71p1LhP22VqE1afcOq23MM1YU2xDoQ35mrJK58JngINE2EiE9UUYVtqOMmTNK5USZYUemKCYZ74Y++RxbDN541C/4cERUTzbOwPYLJxxR4QWoX7DSvLriilTmoffvwh5lJY/BBujr8Se2zYcu5YGx3ZKPR4eva40ZT/AXKe/g6mQJ2PeR2IZPbDDdzdhu4L7hc+I2Ww/gHXgy5iJUY2HMYvIHtiudz/MbvND7Aa8vkydjsd2qbJeu+clUtXXUl+jyj4+fyqLgdiftAQ4N5govisiNQZcEdlcRH4jIvH5VZNJdvKjrfpCYHzI4ykRqeVFMAiBZ4Sv15b+vg54GRuEzwxasEY8xBBsovwW9j/P5gbaYwPnd8IipxGmZVGSJ88LU+hIyXV2MPeaa2XzGgimFp6M7Y4laTNQZRF2nR0ULvQTUqZFadbY9CzYGL8RymgEnHDlAz+KXq+ODzvFjUme/n5I6AMJYe8DxwXXvE2wCeN94NBUvKw61q6zeUWbEtI2qiPteGCfMMjsS82d6jTjgb1EaCnCHtiCKmsQziqj7jrnsMcmD5+7zaAx923YY8o5m/Z+/YDz978sb/wZD+woQmcRhmOH1scD+4SDuLEP7gGOFOFcEX6BmVeMB/aiKG2ou6/2oCjt6oi3rhkP7BAWxbHcMVidNyEx07oMGxM/Cp8Xl2aUyq+vCCOCVuOgELZF8DwmqXg9gM1F6IiNseOx8Xar4FHrWyGsM7CdCO2wh5yOBzYJHtnS+W0cvI7GsKxraDy2c7mHCK2wXcfxmHOG4eTc56kyelGUzeuIV+t/a8zKuHF1YJgYjw35dcA2weoqF+DgIEwen1FGt5154glszPqrCOdgz8YZggkId2DzWldEsp471xG4ENVDMScQN2IH7cvVxca7JOwQav4fgmlSys3rUdOeTpvFRGzeS4/RsdxDU2mjifC3Y9ipu18/AxMqoknmdzCLjsWpsBOxtcDCVBknlpRByDO60j4kFTYWG1MfwdYCeS67e5F4Xn0RWMldCKZJKTvXMJpnGM1f+BOP8EN+xWiqGM1fMmLGdiT5zacpJeaFbVjUo1mTZft1bTuLdi3n3d6t/Sd7BM+iNciYf47/GT+Lz4xMU3t8svXUYMyByeGYOdoWmKZsJcmZrv5YX+8X7o9vffM3dzfH/s/0fLYCu2ZOCN5X44bqeGDfsLDdHxtH0vPP3th4Mx7YO2xY7EEy9u4lQisRdps0c2ifEHZQmDPT1/SBJWGlC+L+2By7Dao7YuPagJB2/+DMI53fziJ0FGEzTAP0InAYRelCst4bD+wQ5p9NMZPy8cD2InQNwsiWIWxbEdYTYQi25h0PbC1CdxE2wgT78dgY2yNsRO4QwrYQoUqEDTAFwHjgGyL0EqE/ti4cD4wSoY8IfTFt8OvALsE5Sbl7OGrGVpd8L2U8sB1F6U75ufDa0F+TMcFmUEi7JUXpWaMuItvrzbyAyJmpMroDW4o9z7HGGr8OSv/zPKFsKKaRm4CtRYdinjWHUpRtSM6l3o+tF0eLcC4m1I/D5qTNUu14Gbtm25GMWw8Dw0Q4TYQtRPgmyeOhtsH6aXhjVr6IbRwcnpr3KmJdCWVR6n0JE8q+FSuqqstIFgqLSLREOwQBY19sopwK7Kyqe6TiRKIQMg6TVuPAfUyetkxV+6qq5LyOratBYgv96AHo16q57nLjwNsSGyDuwgbP36XP4WGT9RmYJ6HV2J+7oCSPzbAL/mXsxn1IRFpTk30xs8aPsQPI6xbbMXoN87S4AGjOIlrRkhsZzQJG04gB3BcMPsZjKt6Z2IW7FHME8n2K8gTQiWnV5i8DSFS/Vdh/eaAITwMXBROlicApFOVxymspxmE3y9PYgjXGHRHKqPs5LnUzDht4nwV+8/N7fgZx8WwL5ZGpeAdgau6otRmDHeL/iOSg9Ths5/xJYEvm0QwbGPYJdS7X5nHY9fAUsD3LaBTSHBLeHyDp0/6hznfU0bbeoZ5/a25WmNE0pltIG7Vix4ew0amwE0LYn7Ed+44UxQbZopwY3FbXpCjy8I/2un/MT7fbaMpVgy95/YoRf7rs2xdmOSKI9YtumB/Dxqlx2KTyLMlu9U3YJHEltjCbS+KK+lkSc4UqzOS0G7Zwjn3VLcQ7MRXvkhB+CV+Opmwctmv5dKgz2FgQvT5dAUBBx3M5x3AXU3mYv5Dv/jmeAYhes6IL4KbYNXlhSby/Y+N0t1TY30LaHqmwv4aw2Ffx2S6XluT3CIkJYhXmwa4bNun26MicKATcGvIbkEr7IInpY7m2/YO4AVWUgRTlL7oT11OUX1CUs0h2cbthi5ZWt3D8DEyouC6UOyKV352YF788pmAbKVdjfbVlKON1bGGxBcAT7NoKu/a2x9wrt8AWAi+iWsAEFSVrJ1n1j6j+Vk4UlRNYjeopqL6AyBC9mXl6M+8j0kqVT7Gx/iLMrGtfTNuyEtOg3htyfBsTBq8lEbyyiCbWV2MH4jNRZUnohzNFeAZ7TMY07B67lMQk7BNs9/gyrJ/p3GbOKmxh9D0RngK+Fx5uPgE4MYSdEoSP8cBxIez0oC1+HzifojxN8viO94DzwtwQXe7vwnSmM4vdWM3FxIdL12RQiLsVqlsBk1hAf8wU6rSQX56p+46Yc4utsUXVIWQd3rdd+PHAMSG/gbxTbR61OXbNTKATA5bd1uKuWX/otmTezR1+8cn/9XiF/IVyFKaeBa47ld91we7pnbDr/Hmyx6fB2Frqt6jeiXmfHYD12eaoNscWpf1CGUNDGdFsbVwo42mSB+/+O7RjDrahEeMNwOaQ0amwfiHszlRYHLfvSoX1CmF/T4WNCGH7pMI2DfntF8J6YUJ+V2xM6Y7qwahOkRNFUb0XsyYah2lbnyURAMZhmyFPY2OuYHNqb0zIODEVL84/j5PMP21IvB02DmGtQ9iT2KJ/HLYWfDKEx7DmIexpTPgbF97/jY1dzUnG7SdCvVuEsCahHmNC3mMxc9LnKG+C3Bf4OaqNsUd39M2JNw67z57GBBSwa+sP2LV2BlDFCbKQE2R/jm4PR7drzAlyd6odTwHnp/I8H9MW/QRbw8ax925snMjbMM6iNzYfdcA2PnrlOLkZCtyB6qYhXg8mVMsKTxCuU1WmYNfnIdj43TjUCUwbHk3+fwVMVGWmKg+ENjyHjbu/xcabDTBZ5xFsM3NLoOtbbPgRNlbchq0Dt6m0sZUIZdGmOMvDXNy9vTZU6hRsEpsL/FlEGonIdpigcTXmFSo+A6kFduHHgeUt1eqHYcaD95G+4X03TNP1vfBdiF5SSlgL80XEdjafxAbjm0hcZWeRdh99lKoeTzLA7R9/UNVbsT9/IDZpno31RzqPSap6IKbJm4/1TenzTc4K779XrecD7ionPg29OfAFpzCVmylg/b2Ai5nAbTyAHZ4vrZ4AAAZ6SURBVK4Fm9RWY04ongjxbPCeRRei9sie1zMTa1c8KL49yXUYw/K8XEVivO2wPo3X0MRQxges/YI6lrE1yabDTeE9ng34IBVvR5KdmBux/og75DNS8XYAmjKddiV1nlamzun2tuBDohZoUknaGG8zEo1LufxGAm335cG22KA8OZVfb2wij2HvYxNiB2BKdVhLemGLtz66ExtjY0LfjDLbYoL0L7DB+kiSSb+UJ8P7UJINi3SdTdA/QebznUbbcMBmUOjelBNkXCre8FTaKszt+CxscZfuq02wXd4Y750Q7x2+HKHsKWyhHj1YgS2w0jvwdyHSholczX0UuZ0jOYI8c7M3sfGjF8lYOAbbER9AYiL9FonXwGgy9w5mdbA+VJuSTsVMNrqTmJC9gi2M+6TivYpt2vRKxasiuc+nAE3m0FmxBXBXEnOiCdg1kGsWHpiEjSk9SExTfhnezwxt7B7ymRbKnQhwNLd3xvq1PclO5jTioxySsFoEZwRPY4uwOP6auaLqpyTumKs4QS5i7x1hp8Ph2BYnYULK3SGjJdhYUNnmp21SxodQv0uyQHoCm3+3AqL2fAx2j28V4qzGziM2xv7PpWSZMZoznH9ji7u4UMg7kP5EqPt2Ia2GtM2pee8+gI19sa9WUHO8S+dXSdijJI+6iG2Li+NkbjiCrTiffpzNHI5iNQWdHzxxGiJtsWt9Wur5TO+FsErmmraY8Ps5JhS8Tv7zJNP5CTOrhbI3wjUzg00ZhWn9j8HWVcPJWb9QMv+0ZlEci94M1/kMssYn1RdQHYDq0iCkXE6y8TE99d4/VcYWJJrG9FwT13nXhz5ogf0Xr5I918SwUSTPCkuHtS0JG5kRtmVG2i2AtkH72AF4C9XZ2FiVZ80Q036DxIrm3+F9GMkjOEZjmx6x/W9g849Sc/55isS0M87rT4ewwSRzyDPYJsBGJOuEZ7HraEMSYSQ6QhtEsinwHLYZNJDk/FV0erYByf/9eKjf4JA27/7tQ+Ig5QNMmMny2hjbMYjEDLkKeC9ca28BPfRmmuhNKjSbj942PzpZiu1I5hqz8NoDm9OWYhu7b2Nrv/VJ5p94j0I4ziTCtiLcxs16igjHiTACm2OmojoPm7OakfwH1Sgsf4ONJ4kwaiSvtVpO03FcyVLsWmiOXVfvU5RRK/7c5MNTd/vdjcftcMsNn/2hy1hM5piK/d8DgBVyhO4tR2irPmdMP3HDc976jhyhp+loOUJHS89nf7Lt2c9ctN0VOlpmI7SnM68wmk5cxxwaM2UAU/uQbIi2JzhBqghVLfvCdjMVuCZ8b4xJ6gp8P4Q1j+/YImd8+H07TGDTkE8rbMdFw6sDtjhT4O1UmeNC2LXh+0Ph+xkldetfpt7TUuWUvm4tk64PidenyzN+b4/dcH3D92aY7bMC3whh14fvvw3f25bkcUP4/bbwPe6oTgzfm6TyHJlKN4zkAZxd6/rv1uRVps/85S9/+ctf/vKXv/zlL3/V41XpGryS55XchKmTzxKRbTD17wYkdvMA54nI/tguw3KSnfJ5JC68t8RMSXYoyf9BTLM2UEQex3YUSh8+dz1mo3yliGyFCSWbYLsd/chAVftmhVfA85g0PwNolXI2UlTVlzFTzD9hgudwVV0e4vwE0w6+gNlyryJR678mIu9jkngViXr+kfD+d2wHb4iI/APbPWqH7cxNSNUtaslGq+Y+wd1xHMdxHMdxnP8i6hTKVPU+ETkSO/+wEaaOfAw4P3XOaiwmNB2IqbhnABeq6gQRmYppx3bHzBEuIzHvQ1Xnish+mB3nVtjh/ftDXstCnH+KyEGYfffemOT5NuYefl0T1ca9MROZyOskdqelXIJpzI7FtF5vAj9V1fgw28exeu+ImfK9CvyfqhYBVHWliOyJ2anuFuLcCZyj4Wn1ItKFxFXnl+Hgg1CXir3EOI7jOI7jOI6z9khyjKsBKyHSXs1eFLEDfBMxAfAEVf1j2cSO4ziO4ziO4zj/xXxVhLK/YWaLkzHzxp2xQ+lDVXVuubSO4ziO4ziO4zj/zawrl/hry1jsAXcXYB5g/grs4AKZ4ziO4ziO4zj/63wlNGWO4ziO4ziO4zhfV74qmjLHcRzHcRzHcZyvJS6UOY7jOI7jOI7jNCAulDmO4ziO4ziO4zQgLpQ5juM4juM4juM0IC6UOY7jOI7jOI7jNCAulDmO4ziO4ziO4zQg/w/qJMQjJSVN2QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.6763785\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.516525\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.377424\n"
     ]
    },
    {
     "data": {
      "image/png": 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BCv/7AOfc9JhS5oBHgW7o7NwcoJ9zrlJEQoP0Bmb5cm0PvAzMAA4DGgFD/e9LgDXAfUApMBy41jl3d0q9dwFeKNA0uzrnxhVot7hS1ts5N7PAtQzDMAzDMAzD+C+gXtwXnXNrgBNRhWYL4GzUnfFjEdnSx5kOnAxMQ2e+pvjku6Vc8ljgUGAtqhhd4Zw7GnWJFJ9HnMeccz9CZ8q+AsqA3VOuOwJVyJYCE/zfj4AmwPHorF4Jqij9A7jUOTcYuDej3uOcc1LgMy6jyf4nEaG5CP2LiNdMhE0SYU0zwjYtIqxJRtiARFipCANrrEhOmpKTIeREaoxbBCI0EKF7Io9ScrIZOan1OytCQxEGi8Te95w08tcrqSFtSV7aOkYE8XlEM/c5KfHla1xE2kEiNEoJa5wIGxgPSyUn4u9l0w2vUR2iz1aNz5UI/URokUi7KTlpVUTaPiLUGO+7jgjlInSoFpiTbuSkXY2Jc9KDnHT5tsq20eSkCznpXnPE1LSdyUnPOi7RdwLfb5dXC8xJa3KySUaSb4+ctCAng2p6X9NkTX0hQiPfV0oibHA8rFj5E5M18bSN82RNThr6tioof75LpMkactLAy4vSgokjudKkyHjfDfmTRk4GkJOWNUUToa8I1ePlZBNy0rqItL1FqDHe/yL1tqbMOfcg0AXYB/gtqhx1Bi4BEJEjUUXoGuBc4GCftGPK5aY559YCy/33D/3fpf5v82R8X4Y16CwbkOjYlV7+b0vgLP8Z5sP6OeeWAaeiit8TqFL5ObBjWp1FpJ+I3Fjg0y8t3X892tHcSk4+ICf7gio8wLPAdBFOykrqB9H/Aj4U4TQf1gj4pw87w4c1RO/BByKcHQt7zIed58NKUAPAByKcHwt7BJgmwoU+rAHwEDBVRJ9JH95RhIOqBveqNPwLXRt5/4YoTSn8CZglwpU+jxLgYdR19ilyku12LPInRL5EqpXjD+hM8m3+eg2Av/nrjSUnpXKSuPgnlvb/fNq/VQlakasQmY9IC4Bk2kT6qGjZ8S7yefwjJsyv9+V7q6oTFzkdkemIdItd9mzUYPNPfx9B3ZmnAE/Hwk5DXZWfrab85XMJei/fJSedM8sscrxvg2EFrpWOyJ6IPIfIZgXj5eQAtA97m5x09GkP8vlWGadEOACYDrxTpVzl5DjgA2AGORmQVQ8R9kQ9ACaJ0M5fcDefx8FQJ/f3W0eEzdF+/0MR+gCQk+3Q/n0WOdk5M3FOtkXbbyY52cdfsCEigxHpkJWsNvX1hpbfiXCzCE1i4VJtAJtevgHovZxJTo4uGDc/bV/0XfiUnIzyYY3JyYPk5HVysnmx9fNphZz81qfvU6uyFJlHZpuKTETk0egrpaiXzSwRjvDlawuMBz4kJ1fF0o5F5O8F65ZZSHkekUIeLpCT5sA4tK1vyVLMYvJnmgi/KnjN9As8gMh7VV+z2+peRD5MvUZUFgHu9GW+LhZ2O9of3+DrVoLKwprlD/zRp73Vp22AGqnfBZ71z54Ad/t8n61SaFSuzEZiCo7I1b4vahYL+60Pq1ExqFbfje/HzvVlfipmpLwalRcTajD+XO7jTYr15af4esQNvxf5eO9VGYlETvTxtsgq38Z8atOGvg+ZBkwnJ/19+fZHZB4ie1a1obAvKlcmiNDGpz0K7aM/IieDC8ik3XzayVVGNpGdfBv8KKsNalWPjcAb+h8U4ZZqCnodUS9KmYg0EpEdnHOVzrl/O+cuRh9uoEqzPsL/vRWd/Qrf0zq7dTV8TzIwlAMIgmV2SryZ/u+XQJMwowU0I1obdrdzrgx1hTwLVe4uSV7IU06k3KV90hTD7yy1eClOR2c9NwUe9GE/Q11HQWdNszgJ2CkR70RgF///KP/3eKLZzhD2E2DPRNjRqCEgHnYksF8i7AjggHiYn4l4Bp0Vvcv/dio64wpwOJBtzRbpgkjvzN81j139NQF+HivzSP//Pug6yywGoMaOTv5626FtDVH7HUL0Pu0M/CCjLMPQNZqgrsBhMLkJ0AGdYd4oROgLXOG/7g908YPps3zY5kT3cAjqwtzDpy0Dfud/2wPoKUJXVKED2BXoI0JnwgBDn6V040dOBqLCEx/noAJF74u2QY8aK5nPMPRZ3RQyBExO2gA5dCZ+ONFz2cfn2wuqjBZ/RfvFTYAd/ODgZh+/E3BMWiH8APFOVA70JvJC6OXzKPisbhQ5aUJOfkNOTqsja/mtaL/cDjjEDwbvQWVHc1RRTyuHAKN9vFKifr0POrg8pw7KBjqgOw84Bf9ei9AWeAf4yL8HWdyKrqtuQNQnFMuf0bXQQlSXq1E3/G2I+rFiORu40Kd/qJZpNxw1Mg2het93FipDhKjP/A1UeVD8Ihb3B0QG1doy2H8K8QvUswZU1mUpDEeRL39qwyBgEFJQMQId42xSTcHJZ29UtgBVhtE9UM+jeNhRRLJwH/Q+5CHC9kT3IdTtUPRZAe2PR6AG9opY2Jb+/0GoTIkb3TYlX9bUmfwpFu+5co3/uifQg5yMAH7pwwYB+6YmzslmRGPCTYlkeT/iMkSNL0EW9iWSPxsja4pDPVP2ISe9CsTpiPYnoGOMo/z/vVE50wuqjOF3ou9lP2Bnb1i9zcfvQPSMVcMru3eicq8n+jxCJJM22hDk69KQnJxBTo7YAA+nG9Bn+qdkyNaNoV42+kCF38siMg11MVyBDhRBZ08A5vm/+6FruPaj7jhQRB5GX/5OwBeoxS3JO8DraMf/loi8hj6MO6PCaTQwT0TG+WsEy/fitEy9e+IGubj59XBx16vrRGQZcJ5zbsGGXLOGDPsBlTiXpqzWlvhMWLB4HZIWMYW0eMWGHVzHYaPQtYQQKWI/TImXxWhgR0RakL2Y89CUsPQ81BWiL/ABFS4YIspif+eSXo9iy5yWNplHQWtsERyYEpZVvrLE3wPINyyNBJKD/P0prq/Lqm8xZUGELuig8HnnuN8H7oUOpM/FuWlZaVM4AKq5I4Y6JdNuR773wD5ECnQhRpBuCCqmfMUj0hG9zy/h3Awf+jfgR/7/TsClGpXhwBLn+Dj7crRDlYkl6CCwJapgxNkc0hUdEZoD651jJTrYTnN16574C7pB1V+AR3CuaIXEzz6cFQtq7//+kUhROI00BTAnHYiMUtE1E0Ywd7vLlyvqYrRXIqwh1ZWB6i6vhdDBy9mxkDSvlW+Ljug7HH8mi+srdUa/FdAUkQY4t77oXEUa4w1ciJTi3KqMmBvbpxZLGdrndUbXwheKBzrG+RRAhG1QA+TNzvFBRlk2Rl6kyeC0tMX075+mhM1ICfugyLJtLGmyZmPaBfL72WLkbd2j7/VtwAnAKnKyNxXuxZSY+0Gq+3954u/W6Dg5zt5EY79CDEWVsSR13QY3U93QeXWBuFV4w/xxsaBMF0vf7x+F6jd/d46iZvPqy32xEtU2V6E3+hhUkbkCuNbHuRzdFKMjOni4Kv8yG8xfUMVwKOoieYBzbmUyktPO+yB0t8ZW6M0YBjwFvOGjPYtask9EBfxTqFW0rjkW7VADh/qw4oVq7XgLtdRHiJyKyBHp0TPQgcEQfDsDH3tryDBUEW6PKuZ5+Id6OLrJSjtgfCzsVR8W7sNw/387/1sIG+/DXo6FvePDXoyFTfJhL8TC3vVhz/mwvf3ffwPrvDV+GPAa+nzkbe6SoCfaMbUvEGcEuoFMD9QdM5RlMtAGdW0MbjrjUGv+O35mBfI7r+GowaALOhAOYdN9Oa4BHdSFgV1sgDccmO+vdXusjNXySKZ1tztJm/1Ji+fz+AbtGK+L5TsP7eTjg8Bk5z8c7fA2Be/qqWErUUvxZbGwSvT9/DXZDEcH+v3xHW9GmfPawLsxPIcaIO4TqbKsb4taUOOuisl6pDECnfE/AJ3pDB162v0FtSgeHQtb6/PeG1hdoO1BFdn4ALfG+5tW4ALxtgHuIAw6cjKYSCEDr/iI8FP03Zzqre5Z3I8qeccQ9cmgis12wGqiWYvjfD0X+Tx2QN+H2SKMiLXBCai1OxgD85Uytfoege8Him0X9F0uA15BXfXDDGdog9VkG+tC3S7y18nbnbcAW/jrXunzn4rOpLcCnkafl8iAmJOB5GS7Ai7Y3dFn9h30vVxWi7KkEm+zlP6HlPetBSKtvDV+c9RzoRyY5t29uqGbbrVFN/uKp22EWtuz8kija8b/Ebr+ZxDapq1Q90RF5GeIxGfshqOysB3afxePuvC19d+q3s3wc9X/cUUy6p8Gov3TmajrfyjLx2ibPBoL+xQddz0cC3vP531TgRIORxXFzkTr6oejhrv2RGO74ehz3CkWBun9YtpgfIMG6BvZjw1Hl8dsgn+HfdgCVK4HbxRE6CrCFSJVxpTh6L4DfahuEEnry7/xeRybFS+tfBsThsqJE3wepcD2Ge6Bw9FN7bZEDZ1rCtQDtJ/8cSxsHbADKqtW1SCTDqG6krpBMimVnPSj+n2ozfrToWgbPUTkpZPFxeiY6xGqj90LUi8zZX79V0G3EOfcF+Rv6nFT7PeZJASZc65N4vsuGZdf6Jw7IyPf5DXnE03Jp8U/LOu3uiRZrm8VtQi3IW5pVveRG9DB/AOgL0Ow2BZ4KcLA4Fwq3DhyMsdftwXwR+dYJKJW8hR64AWBc3wtwq/Rl7IDcIYPu8S7rHUGzvNhF4vQ0ce90Idd5C3sPYDLfNiF3t+5N3CyD7vAr8vpB5waCxPUBeYe5zhWhGN8PVoCv6fCLSUnp4H3MRb5IdAV5/7svwuRBagX2pknmp0S315XO8fnIpxDTjqhQupSKtwScnIuap05H7VIhTbujcjHvjwLgTJf5mHAbc4xT4Tz/NqHTYGzqXCLyMlFZFu8hwE55/jCr79bi0gJOvBZSN242w4DHnWOT0W4tF3zhcFd72Yq3Bxy8geiwVAZKtzKYmmfdI7pfv1dUx/2T+f4QISrUde1YcDTzjFVhBlkuxYNBx6kwn2E+r13y4gHWvd4G+yDKn0Ofd5DHr0Tf0Pab0La8O4ExRWAnLwMPEOFe9J/7xdLG893GPCuczoAFaET6ib3PBXuDZ/2/Yw6DANmOMdTsbRpeWwsyTYIs8yX+3yGiC7q/r0Pb4wOuF8lgQi9UPehZaji2cjXYzlwu3OsEeFjdObtc+AeKpwjJ5f792sMVG1qshfab8wFRvt4wc2oO7Ce6kpZ2r0shqAg/tQ/g1v5+jVB5eB9RAp1kuGo8fL3VLhKclIbd8rhaB2u9f3TmUSuwD+lws0i59cd6Vq1u9AxwUPA4aF/jz2TweJ/AhXuXXKSakz7lihDFet2/v8StP1ucI45IlxOpMBeQ4VbTE7CQDO8by38/1/VIt9y1KDj/P8zvQHmWtSF/ko3hs99eUI7n4Qq2qDube0RuU5wbVEZcEWQPxvQBhC9m+Mz4nVF+6D4O3w60dr6tl6p3Qy43DkWivBL/35sDlzlHAtE+IV3WesO/Ma36XmE2QGVcZsBvxG1GQ1FZ+G+8rKmJTrgPTMma8pRw8C5VLj55ORCoCO6lKQzeo/L/PUb+rpE9dBxSF3Kn2IZBjzhHDNEuAJ99oYD91LhZgE3k5NufuzwGirjLxChlxvDcOA+KtynwF9jciXZzwb5MwNdC5wVr64J7rS3Ufic4OGoTHobgJyEY6TKfPnicnmqczwDVXLlNOBFKtyrPu000hmGLht6zDlcTCYl89gYdvV/b0THYbVxiQwGz5+iBq3gORXc0dc6x1I/oxZ/v4vepKk+D482vruEh7QbUrULUDlqIeiHZG9mkWJd6Y8KNBUgFW4ikW/0ZADnMoVkWrwQ9m5KWLHx4mHdU9KWp4R1Q5XBx/1vY2LXm+DrtpwKFyzPlwA3xdqvI6o0rCB9ej4eZ5LP98uUPFZT4eajMyhz0HVs//JxQof1jq9DWGOTrJvErreOCjc3WRAvoMtiab92jjWodbPE55HZQdZyFiHcjxULb+vQABX6oXyOCveFXxvRMZFvj1j5VjnH4kTYauf4OhG2xjmdNSEn/cjJheTkYD870LMqX837i6z6+TLEy7ITqhgMIFpDASqc1xFtGhTSTqCwgOkDvB0rS5ghSeZbVTdfv69qUY+qto+lTctjY+mT+LsN6nZ0ORXuJnSAuyP6vF6JWp2z1gWBZbguAAAgAElEQVTv4P/uhRoX5qD1mOafz+ptUOHdhCvcbFSA9kBnMq5C+6UewMRYvNBW3dFZ6PJYf9cbVXJqq5QNRGdg/QZTjEetzQ5VJOei3htp9ASmUuEq4+Wrxbs1gwq3NJZ2E+ALP5CECve232jhz6hCto7IWp1kEKrcvOfTprk4fVuUo5u2fO3/D31oeK/novVdjc4Ixu9lGbpmfB61f6bL0JnVL2Jpf426JA9FZ+NDWSb6fBdS4SoRaeLL1AJVONJkTW3Lsgw1jBaqRxnaDlNi8XZBZXALdPDdEVUs4rKwPfoOpsnHpPwBdcm9DPXCaIEaUNPkaEi7FjW4NCBqqyB/uqByKd7vdPZx42Gd0Oe0ev8ksjsiF/o2V3LSl5ycSk62KtBWxVJd1oyRSl+WZD97FNrXzwJWt2iytDnahtXjqZG2W1U9clVG27R+u6774yTbobP4p6CzU2lLeShQvjB7Hu53mlypjUyaHFz9Yu9IMo90RLZD5GP0/OAstkVniM+hwv2WyEOnGAYAH/jxkHNOn2MRjkONe3P9RiXbou/XL9EZwxXFZmBKmZFGH1QIQTSY7Id29E2pvhC3JloBn1Ph4g9lS3RAMquGtGG24dOUsE/+w2HB5fB9AOdYjwoiB3xWrdQ6mzQAFTJh6/1eqIVlAtUH6HGCK+onBcN09mwQ8Gsq3EPoVP8stNP+BnUNKcuoR1oehcryaSK8DK3zJDZSSPiZvBZFli88c/GOuWVKvJbklzk/LCdbooLjt+gg/VhU2aypXfC7frWiuqDcFviXc0x3joeJBFBvdADS26cN1t+aBEwLkq5qKsiTAjqtvsk2zSKt/aiWh9R6EXQafVAlLK6cvRZThD5Gldq5wKXOcTN+EwnR3Ql3EGG4f162Aj5yjte9wH4kox5pYbugsx4/cY6LUBerrDYoR124G0PVNvu90ee+RxEbLcRpDXyYWFPQxddjGahBwte3iQg/FeFsP7Nf7L1MIy1tK/LXge7gw0/0Zb0/43qtgGlV9+0/Sxm64daX/v8W6L2MG5RaALOocGsSacuJFKvazjZUy9c/g8egCs9R/m8LYFHMIBfog8qAlahxMq0/3uCyFBHvC1/m1qi8uMU5lqMGw42RhYGBsb9psrqQPEuuGS1H5eN7RPeoDDWCTKa6+1qa/Dkd7ct1I5ic7OKv9RfgTXKyKxmIHidyjndtziLZz2bJqT1RpbkfsP1ug54vyYjXHjVyh768MapsVo8n0srn9W0qZYNQzwpHhVtPhXsjw6ia359ky6RkfetKJnX146ssRqDvXXKNcZz+wKsx+ZM1a5dGK/T+VuG9sm5F9an1qFFre9SA9Hs/Y1j0hkr1tdFHveCcO47qi/SMdPqgVt2S2P/9UYWkP9rhpG4AkufSmJOLUStx2J65tGWTJW2XVrZa7hWbKvwajz/7PG5BO+PVwQLuaYFac1clwhzVrRFBSCxPxIPqayGKDQvXW5AIW06FW++tcV1Qa2Rz1EryBdrhTUItRXPQqfmsmbKQx9KUsOXkZBhqdQuzCLpOrsKtAlZxlJQTCe2da6jHMr8rVG/gXSryDiJPSwsqMOehrmFpZwbWhmbooCWrfP1RgT8dHRivQZ/BH/mZvKbxtH6tYvNEWBAmyXqciw7qfoa6oQbXnmV+B6rNgZlUuHfJJz4jGdygOxOt1cA5VnuXnHJUcdjf/9QF7bzfBs5ARPI2fVGraQtgqd/oYSD63C1Ahfc7wAU6e+jS6tbS16MTKpzmUeHeTKlHy7y01Wckg0IyPy9l7eiDrt88AZESxtCafMHbHRgf+gTv3tUYbdOwq+qxvjxxK+x60bNwkmVsibZfM9RdZQW4vsDEmCI0m5x/NnTTnL2AlVS4Z315nkDXWnRHXd56o+/ccLwrW5H1b0n+5k+tSGzU4J/f54l2pe3l04b+80DAUeGeoDii+5uTkehzF79ef/T92wF9tu5KuHCmXS+kDbMY86hI2ThDy3olOvh8mAp3VlGbk2QTZqya+v/nAcsSim68vrugbfwCkZJSSaGBrT4rFei9fRVdgxUUuuC+2A/tvw9wjidFeBx9RkK+2/s6v+rjfok+m/2JDJ1FrcXzylQf1DK/kuKVy3i87kTryyaC9k0iGyALcxJmmidyFJVoP/E5KuNmp6SN9+Wbo89z01jYEB/2PtHGVHOIBtTlPmw2kctzcD+dRfWzZYfG/k5A12B+g7oHjyD/WCQA/Lqv5/DLDkTo6mdd43EaoQpUVt36oq7rH4PbEhjtxywTyR3cLRavN+ru+QnR2HsCug45fr2e6JKEmaiiCtofn5ZWhzqgNTVt2KUyKciVLqhxbC4qm5v58rXVdY8FZVJHtH+bT4V7PSWn/LRqAOvs8yhBn+cvM0o6BB0npO4Q6mlFkWtz/fhhE6DSOT7z9UguPRmJ3s8R6D0bga49nuCcjtWCzCkGmykz0uiLPlwzidaV9UetW5/4/4ulBZGy9AgwpX+XGT1R62EVfpD9ENr5XYvOjDRPxgthCWHcHH1pkmGrw0sRC1uXUPJCZ70qJSyed1iHsjwRL9TtV+iZaFuiQmouamkPWzj3RAXY58SVMj3EuQc5aZSRb3Ngtd9d8UyfR1hAPJuctCQnHf2gMgxcgiU163r4cp/kr5e2lW9aWijeWlsMhcq3Et0I4TGigVIQ2uVtWRR2cqqMpW1CZJkONEY78ihMBcxI4P+ocKOpcJegi/RDvnv7fH+aUe4yH+8D/MYDqGBLuiP1QPvYl4Fe3g0uWHonUn0WJk5Tn24F6tb3Err+KrR3mIXLf0fUDbOpDxvu65E1yE57v8IgIuSReo+LPidGLam9UaWskb9eK1Rh6kFO7iInl6FrWJMuLYeiCtXxqFL7NdrOC4uoRwjrCDyJblTThuSsdvQOt0Xb6q8+vDva/8VduHqhA4OVZM92h+2WN0EPgW2M9oHLE7FapYTtig5YfozOpj6TqNtjRBsy5CHCNiLcLsL9IuxF9f7pIZ++ZSzfiehgrDMwOWY5zpoJi6d9H71frRFpg8hqRF739e+ObhIxF93lrKbt5Ish2e8UuuegO1s+ht67NBfE6uh7Mw49TmN39NiT4MIdzzc8C69A1WArnu+VPt+B5MvM5ui7X20mL+OsphPQwd+bRG7MtZ0pC/HCWvu44aKmvjcetsa7Hp7h67arr99K1IgwqIjrnezT7hALOwk1fOxPusKZVt/8MJE26Pv4CjCUnLRCDYYXUOFuocKdRLSrd5ILUXfXXqjb+dqUOEHWZNXtIF+3Y9HlAtMy4u3v440iWh/9KdCB2VUbuKxEjUOPoe6EZeg7Nx1o5XcSrTt03NEM+IacDCYnV5KTH6fEbIQqHivRMc5jwAVE9+od/7emd3NznzZrH4G0tMGQGdawFnr2N0Pv9WaIiAilomdDfi3CPBF2R2XIUnJSTk5u9usa8/CGixdROf+pSNXGeklXxK2Bt5xjknMs9uu721B9Fr9oTCkz0uhDpJQFl6N+qHD5hKxzntJZS2JGtlHDNavJ31p1O3TwdrhzXIO60qxKiZcZJtUPYV0FNEoJKxGptmV6UMYapoTF8wkDleT10raIHYQ/yJZIKetFpJT1AiAnJ6OW54+AhQcMfzx0zPEDCVcBjRJnaTRFp8kr0c0RvkIHcnG3lfKMeqSFpZEVLy4Uu/jZoA2lNuWLK5ylf+eQIOzi+YfF9fG0a1LC2qCd/xvkpKm33oX7W0x94u0cvrckv7PujQqYCT7/rkSW3s99nDSLd6hH0pOhDH1eZqH3v4zkM6izFmuKrEfa8xtchmahszupArAWawY7oUJ/vM+vt89zLaoIHYeuj0xTUvYDnnOO0c7xT+d4gnShndUnJNugNfkW3Py06p7aGjUAzAG6e4W6J6rUfUbWujI96+5DdLfJy1C3lbXkH9MQXF3i7ITOijzgHHP9Bixp9chDhC3QQekXqALWMbVuKf0xOpD82pf/cXIy1u8omCStHqBGnUXA1oh0QXca+xoYSYW7kthulSFBLWfJQN+T0O+Evq2Ye56WNo190Y2ctqXC7YjKvfCOxZWA9uj7tSSRb1p/2h+Vlx/7/1eh8qNaGybbxbut3oSuXWtC5N2zoUpZGMjH+6di+94gf5JjxYHoFvUf+P8LXS9+T9amhCXL3C1mwIrLmoaJsM5e/myB9gmPozNlZej79Rp6HmIrUvBjg12AG53jM+d42Ln8DbiKrdvyymYN0L4u+WzUVF8YV6U4Z8WLy5q6JNRpNbrk4iLSt/Bfi8rItPItR/vENaTJJKWofiwjbXhnZ6OGivR3WA2AQ1DjfwdU9pyJKtsHou/4Yn/9NWi/dwrVdwKOczr6bPdF3/u3Se8DO5A/0xg3YNWKGpUyEZkpIk5EDo6F3ejDRm9Ipt9lROQOEZkmIstEZKGI/FNECk2FIiJ3i8gcEVklIgtE5GkRGRb73WV8RvvfR2fFScnryNjvN9Z5AyhBKfuMSCkLAqa2M2VLiaxFbwM0a7xiBflnVvRC3VFmQNWarWVAU+/WE1iGKmANE2ElVH/pl6ICsEkiHkQuFPGwZjWEfZMRL9TtVaIOOE0pqz5Tpi4Kf0bd6JoA265c3TRYMuOuFsti9Rjvv69G391k51CO1nsN0HI/ngrPT1rdmqOWp69JJ60NQh5L0M5JyD+PpDaETiueR3DdbI5aHIObQhk68FsFsDMvdULrWZXWOdaiimo8bL3PJ55HEIDfoLMwXxEdkt0cHUQlZ1TilPuyNEHvRTk64EmeDdbbX2cO0QYRZT6/Br6u+UJWrdKVvixziVz9ylGh1JFIOC0j/x4ti6WdWqAeS1PSpuWxMfRBhfnnqKLXh+p9QmAlOksep4yE/z7p9U2rR2iDFehsA2ibJgV+iFeJ7poG0WxIpJTpDGJjX4dZZG/2cTm6lmUXdPb811TvJwLfpIR1Jd8lMp42awE+6MDiPee41DkecY4xibRhe/h424fZ0PVExqad0VmGtLFBPG3crfdAdB3aFHQGuhc687aanPwauMbvxLcxhMHecqINL7LuOUT1DWlX+N+zBrVD0E1RppKTI1D3ow7o87/Sf8rRPnd9wisj3i7jiAw8SZmZJn/S2NzX7RbnWO8cb/nwcrT+q9ANaLIU29AvrALKSqkMytiGyL14md8i6p+TMq5Q2ubos7aYyLMhKX+CwWk1ajToSLRrZhgIdyZf/nRFFbEp6DM5lDVVs05L0NmcJaQfU9QG7XNmpvwWZxW6ZCCrbtOBOY0argn3vSQj3kdUN8YtQt8zx3tVZW6OPi+fJeIFQ1Zd78C4An1eC58hpsa+5b58XxCdD1eOzsB28n9rkklfofcqi7S0YVaxHSqTst7hHqgy9Iyv12borOODzvGyc0xwjndIlxeQk+Hk5ARycjw52RRdF/a4c3ziN/aYQrrsSjPIVpIvz4rCZsryORHtPO5DO4R9gaclvqtPPj3Rac47UdeavVH3h8AfEp9gSQl+rc8kfg++ttUWw4pIObpwNW2KvW5Qy1MPdKpdF02q1aov2vkGv/piWQp09jM9ZwC0aLJsBTqLFT+vqxJVthok0oJ2xsmwrilh8Q1IlqWEpcWrbVinRFgjctKeCnc9kYAZhCorW6C7VZaiz8jBqCWqNQuqXBBvQ5+xffcb+s/wEqfl25UKdzM6SAwdQHt0F7mZ/nsZ6nL3LMDp/CkMhLKudxf5C67z41WnDLWEvxn7vkF4JWol6fetKxXuH0SuO+VoO8UVlKXkbzqzNKXMybBF/m8bdAA9nWhGrSsV7jkKnyFUhlrVv0CFZRhQtE3E64U+u38n2oGxHBUWS9HOPEvILgO6eL/7R2L59kUV1U7+e3Z9K9wkorOGsvJItl8Zkc9+PzbeMtsH7a9Go+3TB22rDlS4yUTHjSwm35UzqUxTlbY6afUIbTAf7VNB38/kGYEh3teo6xpEStnH6HbR3YmUsJvQ9ztLKQtrDkrRdbFvE/rA/Hw7pYQlBX78/ma5oWYRT3txLCyUJaxRCQOemvKIl1lde9+nEfpezkYNAAdS3do9FB0QF3NwbDrRxjqjidx4lwItY2ujQvm6elmj9V1EWI9yG3quUNb7to5oML0D8AfWVinjN6LPULdGrF4ElIrkGc7ak5PGVLjLiWa6+6MDu72BfiWsTZMraWS5j5b5eo1BlaQ2BeKdj86YNjyIx4JMjT/7tZV7XalwtxCtHRuIPjNbA51+wyUNq+Klp70T7btXxcJGE42ByoGfEBlGyn09KojGQ2X+82Oi4wDK0GdsBfqetuT5KuWzNapIpq5/J90omIdXwJP9bLxuTwKvN1albAnV2zkuz54mOi+1DH3OPgeEL2mP3veuVLixROellqHrt74g//D0jUddlb9B+9R/EPWVaYS+8h2is/jKULk2F31uwruZ1R+/R/ZGQiFemkxqi8qkARQ2rKxCx1pf+u8l5O/kuwTo6NeLnwJATq5Ez+Vdio7hB2SkXUq+IfprouUtgcXkjweKok6UMhFpKyIP+VmiShH5VERu9b81EpFnRWSuiKwWkcUi8riIdI+l30FE3hOR5SLyNxG5PzkTJCIHish4EflGRD4TketFD1PMKtOv/Yxe2qfQdpk/cM5t65w7ieg8gzKiGY88nHO7OOcqnHOnEh0SVy7etcs59/PwQdcstEYfnlv977lEnCDQ/hirj6CHE39BNEj7NuiJPhc/Rn3r+xBth38WakEsuC1+ggXow1nVoXVt82VceQkLaaeg9d7Lh3UhWlAZjzd/I8LSrlfbsCE+rGEyHgBrEFRgHYhOnZegwrkXumBUFzF/Rmv/W6lvn0sO2/qhHmjHnFkPT5i1G+7PPglKWrXOaideaoc+Z5l1y8I5VqMdUEgb3D6THeLGCokFsTzk3HuvW44qSMnypeVbLW2sflVp08IG//L9FWgb7kCFe5lIwC9MyTeNtLIsJHZAtHeN6Y3e25HoLG5v8geFWYPE+eSvxSnYBj7fvPoWYH5K2rq+v33Quh+JCv4+vnybJ+J9RfUzXxqiVvhdRdTi6N265qPGjhCvJNQjuCrH3ptk+80HhsXilZDeVkE2tfZljytlI9F7lqWU/QntI3+NuneFfDf15Yr3HZv6zUxCWaYDP/D1DBs9aD2quy+n8TCwmQiXi/BDEY7yeQxMuJ7pM149bC4wnJyUoJseZLEAGODXoSh3sy2qiJ6Dyss9WcEMYCty0hXdOn5jST6DnduxMGycMhCqPfdtiA+a3qAj1V3OW3olL8kEoC852QaVczCJNlSfWW20J8+GmZ4tY/nOR/vy6BDaeTRGn5s9UVnQ7DT+HJS+eH+cxruownC673e39a57ycFg/rsZ7YZXxSjuiCvI4VlbRL6s+RqdNS1GXgxCxwfnA5zOn7qjymhNaZelhKXVpawWYUNR19/bAfgXndHB9I5eYUrdXc/LuJlEY44mInneDoFqsmbwL99fjRoUk/WYR3QuIXKUW4/KmsL1XUc3n0cxfX5dMx/Y3K9bL2TwT+sri5VJaf1xjXn4tMXKzM3Q8dQrqPFyM9S4+iMRBovQS4QhpMufw1BX89fQtYEHoIbn/UXo7J+NfiTuke/Lv6K6TBLSxwNFUVczZeei7hMz0IpNQ9cIhTy6Av9GX5pP0ArfroWVNuhizyHo4KgT1c/5QUTCwvveqIY+GxUCfy5QphPQzjXts1dWIufcO7GvoTNbR/ZuL6GMp4vIX9AZNoDrncvbmhciITXGH0ydvM6O6Eu9BJ15i6fbAd2GtzKZrg5JHqTXFLXUQGTBq822+OGAwUPxwvGsff7wEdqmP/S/jXKOqeiM4cMivIgqnh+gHX1VPPQZqyTyex6FWrRXxMJOQhfQLk2EfYa26w9jYbNRYRQP+xJ9+eJhc9EONzybo1BFch2RT7IwmQ6otftx4EFfri1JHlj8EAt9vjf5sq4sbzdnNTowO8S/xKNi9TisKg8txwLgDL+RQCkrqtw7qmjOiq7ogvxD/AzkSVS4eT79j2LXy2IycLAX4sd05YvGFN9BFstkYKQfnB78+3+d2xZt1x/6gWMoX1q+k4H9RGiKWqO7+7B9RWgmwh4EVyrYR4TmIuw6dc7gvqhV8Hx/GGroPCcDB/lBZ6F2SSvLWz7ftiIMRTfZ6I0qxUtRYRfcF+NkCdnJwL7oYd81tcG2InQToT/qfjYZ2IuctK6hHpOBESL0FKEn2i8Wf3+D90Dhxee90fd1PjrQ7I0uCt+ZnPSIle91YIAIu4swEH3e70SNRK+LMBa1mr8J9BZhVxG6owrQZPTZ30b0MPjDfNgwf+h2PI9uwEG+vkf7eEPIyQAKt3NvqHKFDWvj8pvkBZ7s8zotjpvGr06YximD3qQN2gc2Qp/VUp/vOz7sID8QPBZ/DADwkgj3oYvhJ6PK7E4UuJfOMfmgEf84fIsek3YcWDb1VxXbjQlnRrVA72tIOwntn+JhL6MK6MVk7wwb0jZC5bemXcTewD9xLljJK7mQ+Wg/OzlWp40h7x25jZPDgP+Hsb4ynNf3o6ryfZY3G5l6PXRm4hl0QPcp4Hg/39L9EIctR/vPy0XYBl3TG88XQHizKo930XZz13NuM9SCHpcrefizFX+G3o/V6CxfZ9Ld1ZN0IOGiuyfPtUblyol+EHm+3xr/IyJZc5Lf4TEuf05ClZal1eo2t2oHzH+jxoAlbVm8KdpvB1kzCpWZ86kua5b68B95Q4P4lZXJe1KeUr+0sJ7oIHk0usnKx8xnAGpcuIqcnEthz567gDNFuB99J9tlxAuypgmwz9Q5g8vQe3uIN2aEd+kl4GgRNhPhTHQ8NRk4mJw0pOa+/CAv0wvFq2ve9uVrQ2GdYDKwj3dFrqkeW4lQLkIfVHmfDOxBTtpSs0waKkIf37/vQ/EyczPUtfwZVAfZDPV+eBHcRHBTUS+wd4Cd/BKSUN/b0Fmzg9C+a0t0UmQhOpu5EHXrngyUibClN5odivYdg0U4RoQtUQPk26ic2tbHC+98jdSVUhYsPm+iD/nheKuMc24VOjCejAq093zcnf3sz0jUuvUJsJtzbu9YnMCZ/m/wQQ6d4LFZs2XOuV7OOcn4HFdThUQHGuFsgd875woqZWjHcypqLZuNrjFKXrMjOrAAdYlIIyhtf3XOLfPphgBXA792zk3KSFdX9CHasjUoElsBn+BcA9QS4SjehfEj1Dp2LdqJM6hs2mr0pTlThJfQAQmvXLr9lSOHPTFuyz7jW15w4FVvujGyFlUqTvWK2kne5e1d4KcijANO8TssTgZG+bDT/FqiycDxPuxM74YwCTjGh53twyYCFT7s3FjYET7slz7sbeAwEd4ALvIHuk4DziQnzwGdmVJ1gOmhOHeEz2/rWNu2AT7kczoA+1LJANbwAHqg7ET/2RN1h73a+3JPBn5CTsYSrecbi7oNrQD68nGVK8s2qAAPhxNPRHd0e4nomZuIKj3PE5udSGEiMAwdtN1yDee3Qgd0e/s8wnbTG8NEX6dX0HOjQtj2vsy7eweCbujsbRfUMBPq1sOnfTCWttyX+ZFYWDcfFtyKf4fOyP0OtXJ95OMN8fGq1tCmUIYuAu6MGpfKfBk6offqFaKZsZNwrhX6/IeZsvN8PW4iW8hOQJXMl/Hvh8/nEp/vNbE2KEXXG72EDsgm+rK8jO56lsVEdKD3HNpfhcHW73weF1P4/l7p7uAbdFOLLPoA1+NcJ1+WPsAbRGtUrvTxxvm/z6KDuzZujEzbbfDY09o1X9isU6t57X+87X3T8bveoQemf+jrGXblehg17HX1YQ389S7zv7+MKsePooacbj6eoH3TVT5ed/TZaY8K3TJf7vtxrgX6fnYjxaXd3e7kk5uc3D0X7rzCydQ/OCFau3Wnr/NgH7beh70PbOYci8razq4obVjZvFHJ6l37dZ4xKVa3B8k+YBpycsQ/zjnk1klXD7t36rWDLx1z2tHLY2nvJdpVMh4WjH5vodbey4gd65BCSHsnwfj4Vy6SUYyUk8TJKFbLKNrwlXto1O23nzR2ym5TXv5ghwajXzr2YuArRJq6O/iNu6NKnhdLGTqQ74y+7xzKo63Rd/Y89Lk/AjXYrUDftX8BsIAu6CCrM/pcrCftnatwrsEL7LXfZEpOmEaP/m8gPEslqoB38elXNmNlN1TR3AlV8nfxLrJzgIvIyQtAY2bSHR3vDMW5YcCshqzrh8qDo71cOQcAkR7uDpa5O1iM+IOOR8ndHNuiMT8c0oDjS4cQvYd9fVk+J/3dDGEDfbyPfdiLqMHma+AXPs5EtC9/ET3jK4TtQXX5Mwk4xsufTZhc5fVyOM4dhvYdA6neb9/oXeMmogrY80SzExPRMeFYYChf0Bztw3bzZQ4zHU3Rd62zL09v1Miwjw97Hh14NwIuwFXtojsU+A26xvc6VHFLrk3Vxmo7+9rOrefmGpWs3qtt80XzT97t1qxDficS7fAYlzVb+vru48OeQg0c7xK5Ak70ZXoZNWiA3pNRvh73EPXlg3y8Q2Lxfubj3cG3M1P2OtrnTSVyJ09jIvoOvYwu8wnlu9yX7yqiejRC7+/L6L2diPanL6H1KZRHA1Sxeg0db5QBN/g8zqew++JNqA5xATDY3SN7uzHSf/mdzf+24q5md7sx0o3q8ue3AHKUe2TERW+PPffe63Y8d8x1DQ698eFfuTHSY83fGk55+KxDn3rivJGPrf1byTqiXSb/7tN382VdhN7H8URjDdDn8UNqseSnGKUs7HQVt76EtS/hAb4RFWo/QxWzxcA9ItLAz/xMQzXWX6B+w6AvTCuiBv7QRef1JKebe/m/e6IzXeHBEfJndvSHDXdfDMrTC+hs3+34KfpCOOd2QW/0wehNeVhEklbHU9B6P++cSyqeiEgvVFNfhw7YAoei7b+ziDxJdD7HgSJydU1lqyV9gE9xbh2qFM5DH3Zdy+PcalQgpG724S3Q4f8hvlMfi9GeumUAAAaQSURBVNY7bIfrfFgDdMtvyMmR22/y2qNPnHfg+eOv2PrMq4646ENUKRyL3uedolyqFnHv/C2ESYGwMGDZOiXe7r5mAtyFc8EN4BG0g1oJzMS5JeiMXS+Oohkn0oXjmMbRjKfCTY9db0eiXdJC2G6xfH+Hvn8lwAreqHIVmYJz4RyXslja7YmMJyFsV9J3U0u2y7ZA6VaMD7OjyTw2hpDHlkS+/fEyN2UuzdG2mIpz81BLdrxuw4kMCPGwVomwYSFMjnLDhpz/3oN3vXjcnSffcetlcpS7NxZva/J9xBV1Se4MfODbIAx6nkBnL7sDzQcyNaxlCQu2w459ZcCHvh4fka2Uxcvc0f+vG19Uz/dlVLnclMi9KaTdjPy1THFeR2ex4mvHyoAZPo/pZN1f7atORdee7lc1mMwnbBoE2gadeYg3UMtjJ9QyvdQ5PkeNYOI/C4HRYy/c4+CFt3U4ad7NXX533+kVbX28J1AZ1BQdNE9HDWHdiPqlN9H3o1cI8zMQNxLtgDefaM1XDyL3s+5oH7gIFagN/W+hHuHQ+0KzSlU4xxJfnnb4WVk/U/EsOsjUY0dyctbsP3W/vPLupuesvqf0/Bm/36Qpep9n+bZKutzEORgY69fuHIkOmub4tmmPPkeg/fkUHxbcrNYCx+JYjhqfrid/4Tr+cOTx6KAzpHUpuwce/tdxo0bvcdXYU3a64uUdjr919N1+gH6Fr/9piBxeRNMFyoDZOPcVzn1OtCvoWPTe7ODLtw6V25GsWUYnYI5PG7wdUp/p9bc7+dciuGsuzPijC26AX+DcPP8+hC31L0Y9IZYQXOaisuwCwALKgY9jZxCGHRjT5M+l/no3A/+HiO5m2mg5tJuCu3NVKMty9Ln8Cr23WUrZGrSP+Qp9L8r8tVdT/XiGuKwpSQlLkz8NWEkp8ADOBTf6J31bFCtr4mENmVVlUAxy5TOio3hqCmu1794gJ/KlnCSu7+GctuNIDpAXeLXHa7Q8eir0f4MG8kLKjG1O2sz+U/d35v6l6+er7yk9dtFt7R+49cRTstySQ5lHEO1mGcK2I1oL+jjRsRWz0T4mxNsGaMFSGqLG2SBDPqG6PNsKaMUqGqDvfTJeXfMw2o92Rd+dRRnxQvm2IF0mzfDfX0WftU2IPKrCJkVDKLw5WOi3+1L9aISPYnnkb3IjIitpMulirlghwv6H8GiLJbR6GuE64P5mpSsvbdq4cjW6nOB59L509N+/AW6aMHNEo+v/ee6R1z917nGPjD/0X8Dohg3WzTx0q0dHjRz21OSSButB5UEwiKhcGSNrTtzljp83L132WaumS2acvNut7zvHHFRBb4XK4DSvuXSccwU/6AvngBv89xLUyueAc3xYafiLCo7J/vcdUSHo/HWaoQ+c8582qCuHA6bH8pzow27035/y389MlK1PgXLPjOWT/IwukK6nb3gHXJXye2t0EWAv/70pUBL7vRTtoBywayy8MdEhlCMz8r7e//5wIvyyAnUZV9M9rM2nQD72sY997GMf+9jHPvaxj31q8Sl2DC6RIScdETmIyOXnLVSz7IdqlwOcc1+KyKXoYtb3UA35CFRD3AK1pF6FWj4fQy1EweIRfLY/RRW0sajVbk90FuUPzrmfi8h+qGJW6csSDqFr75zLsmxsECIyB9XuZxHtMAOQc86NF5HjUIvuZOfcUBHZBd215SXUNWBH1D1lPtDf6cwIInIMOr05A9jUJRreu0vORpW+HZ1zr5CB30r/WHz7bGydE9cu/EAYhmEYhmEYhlEUzhV3NmPyEMm0Cz0mIkej/s8DUMXoWeDC2DqrCehBnwej05+zgIudc++KyCfo7NheqAvab4ltYOGcWywiB6DT69uiU7+P+2ut8nH+KSKHoOe+7IdqntMpvH3nhhKmW3sQdmFSJhHt0hbnC1+WPVEXqvmoz/lvgkLmCdf6Y1Ih8xyHKmTvFFLIvm2KfXAMwzAMwzAMw6gbapwp+48UQqR1bEapAerzPgAY5Zz7a8HEhmEYhmEYhmEY/8V8V5Syh1C3xWmoe+Nu6AzUYOfc4kJpDcMwDMMwDMMw/pupqy3xN5YJ6G5JF6E7tjwA7GwKmWEYhmEYhmEY/+t8J2bKDMMwDMMwDMMwvq98V2bKDMMwDMMwDMMwvpeYUmYYhmEYhmEYhlGPmFJmGIZhGIZhGIZRj5hSZhiGYRiGYRiGUY+YUmYYhmEYhmEYhlGPmFJmGIZhGIZhGIZRj/w/7Ij0nniYIDYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.563277\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 3.5001245\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.6012442\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.5157146\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.5688024\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.742023\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 3.3787544\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.0878575\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "score_pred = 2.968775\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x90 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Load GENESIS models and predict sample sequences\n",
    "\n",
    "model_prefix = \"genesis_mpradragonn_max_activity_sv40_25000_updates_similarity_margin_03_earthmover_weight_01_target_35\"\n",
    "batch_size = 64\n",
    "\n",
    "sequence_template = sequence_templates[0]\n",
    "\n",
    "save_dir = os.path.join(os.getcwd(), 'saved_models')\n",
    "model_name = model_prefix + '_generator.h5'\n",
    "model_path = os.path.join(save_dir, model_name)\n",
    "\n",
    "generator = load_model(model_path, custom_objects={'st_sampled_softmax': st_sampled_softmax, 'st_hardmax_softmax': st_hardmax_softmax})\n",
    "\n",
    "n = batch_size\n",
    "\n",
    "sequence_class = np.array([0] * n).reshape(-1, 1) #np.random.uniform(-6, 6, (n, 1)) #\n",
    "\n",
    "noise_1 = np.random.uniform(-1, 1, (n, 100))\n",
    "noise_2 = np.random.uniform(-1, 1, (n, 100))\n",
    "\n",
    "pred_outputs = generator.predict([sequence_class, noise_1, noise_2], batch_size=batch_size)\n",
    "\n",
    "_, _, _, optimized_pwm, _, sampled_pwm, _, _, _ = pred_outputs\n",
    "\n",
    "#Make predictions using black box model\n",
    "\n",
    "score_pred = saved_predictor.predict(x=[sampled_pwm[:, 0, :, :, 0]], batch_size=batch_size)\n",
    "\n",
    "for pwm_index in range(16) :\n",
    "\n",
    "    print(\"score_pred = \" + str(score_pred[pwm_index, 5]))\n",
    "    \n",
    "    pwm = np.expand_dims(optimized_pwm[pwm_index, :, :, 0], axis=0)\n",
    "    cut = np.zeros((1, 145))\n",
    "    sco = np.expand_dims(np.expand_dims(score_pred[pwm_index, 5], axis=0), axis=-1)\n",
    "\n",
    "    plot_seqprop_logo(pwm, sco, cut, annotate_peaks='max', sequence_template=sequence_templates[0], figsize=(12, 1.25), width_ratios=[1, 8], logo_height=0.8, usage_unit='fraction', plot_start=0, plot_end=145)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load GENESIS models and predict sample sequences\n",
    "\n",
    "n = 1000\n",
    "n_slack = 0.05 * n\n",
    "\n",
    "n_ceil = int((n + n_slack) / batch_size) * batch_size + batch_size\n",
    "\n",
    "sequence_class = np.array([0] * n_ceil).reshape(-1, 1) #np.random.uniform(-6, 6, (n, 1)) #\n",
    "\n",
    "noise_1 = np.random.uniform(-1, 1, (n_ceil, 100))\n",
    "noise_2 = np.random.uniform(-1, 1, (n_ceil, 100))\n",
    "\n",
    "pred_outputs = generator.predict([sequence_class, noise_1, noise_2], batch_size=batch_size)\n",
    "\n",
    "_, _, _, optimized_pwm, _, sampled_pwm, _, _, _ = pred_outputs\n",
    "\n",
    "pwms = optimized_pwm[:, :, :, 0]\n",
    "onehots = sampled_pwm[:, 0, :, :, 0]\n",
    "\n",
    "#Make predictions using black box model\n",
    "\n",
    "score_pred = saved_predictor.predict(x=[onehots], batch_size=batch_size)\n",
    "\n",
    "score_pred = np.ravel(score_pred[:, 5])\n",
    "\n",
    "sort_index = np.argsort(score_pred)[::-1]\n",
    "\n",
    "pwms = pwms[sort_index][:n]\n",
    "onehots = onehots[sort_index][:n]\n",
    "score_pred = score_pred[sort_index][:n]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean score = 2.8136\n",
      "std score = 0.4097\n",
      "-------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/anaconda3/envs/tensorflow_p36/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "save_figs = False\n",
    "\n",
    "print(\"mean score = \" + str(round(np.mean(score_pred), 4)))\n",
    "print(\"std score = \" + str(round(np.std(score_pred), 4)))\n",
    "print(\"-------------------------\")\n",
    "\n",
    "f = plt.figure(figsize=(6, 4))\n",
    "\n",
    "sns.violinplot(data=[score_pred])\n",
    "\n",
    "plt.xticks([], [])\n",
    "plt.yticks(fontsize=14)\n",
    "\n",
    "plt.ylabel('Fitness Score (log)', fontsize=18)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "if save_figs :\n",
    "    plt.savefig(model_prefix + \"_fitness_score_violin.png\", transparent=True, dpi=150)\n",
    "    plt.savefig(model_prefix + \"_fitness_score_violin.eps\")\n",
    "    plt.savefig(model_prefix + \"_fitness_score_violin.svg\")\n",
    "\n",
    "plt.show()\n",
    "\n",
    "f = plt.figure(figsize=(6, 4))\n",
    "\n",
    "sns.stripplot(data=[score_pred], jitter=1.)\n",
    "\n",
    "plt.xlim(-0.25, 0.25)\n",
    "\n",
    "plt.xticks([], [])\n",
    "plt.yticks(fontsize=14)\n",
    "\n",
    "plt.ylabel('Fitness Score (log)', fontsize=18)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "if save_figs :\n",
    "    plt.savefig(model_prefix + \"_fitness_score_stripplot.png\", transparent=True, dpi=150)\n",
    "    plt.savefig(model_prefix + \"_fitness_score_stripplot.eps\")\n",
    "    plt.savefig(model_prefix + \"_fitness_score_stripplot.svg\")\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean NT Entropy = 1.9801\n",
      "Std NT Entropy = 0.0162\n",
      "Number of unique hexamers = 3254\n",
      "Hexamer Entropy = 9.6264262759959\n",
      "Mean Binary Hexamer Entropy = 0.1576\n",
      "Std Binary Hexamer Entropy = 0.1999\n"
     ]
    }
   ],
   "source": [
    "#Calculate average/std nucleotide entropy\n",
    "\n",
    "nt_entropies = []\n",
    "for j in range(onehots.shape[1]) :\n",
    "    if sequence_templates[0][j] == 'N' :\n",
    "\n",
    "        p_A = np.sum(onehots[:, j, 0]) / n\n",
    "        p_C = np.sum(onehots[:, j, 1]) / n\n",
    "        p_G = np.sum(onehots[:, j, 2]) / n\n",
    "        p_T = np.sum(onehots[:, j, 3]) / n\n",
    "\n",
    "        nt_entropy = 0\n",
    "        if p_A * p_C * p_G * p_T > 0. :\n",
    "            nt_entropy = - (p_A * np.log2(p_A) + p_C * np.log2(p_C) + p_G * np.log2(p_G) + p_T * np.log2(p_T))\n",
    "\n",
    "        nt_entropies.append(nt_entropy)\n",
    "\n",
    "nt_entropies = np.array(nt_entropies)\n",
    "\n",
    "print(\"Mean NT Entropy = \" + str(round(np.mean(nt_entropies), 4)))\n",
    "print(\"Std NT Entropy = \" + str(round(np.std(nt_entropies), 4)))\n",
    "\n",
    "\n",
    "#Calculate hexamer entropies\n",
    "\n",
    "hexamer_encoder = isol.NMerEncoder(n_mer_len=6, count_n_mers=True)\n",
    "\n",
    "hexamers = isol.SparseBatchEncoder(encoder=hexamer_encoder)([\n",
    "    acgt_encoder.decode(onehots[i, :, :]) for i in range(onehots.shape[0])\n",
    "])\n",
    "\n",
    "hexamer_sum = np.ravel(hexamers.sum(axis=0))\n",
    "hexamers_probs = hexamer_sum / np.sum(hexamer_sum)\n",
    "n_nonzero_hexamers = len(np.nonzero(hexamer_sum > 0)[0])\n",
    "\n",
    "print(\"Number of unique hexamers = \" + str(n_nonzero_hexamers))\n",
    "\n",
    "hexamer_entropy = -1. * np.sum(hexamers_probs[hexamer_sum > 0] * np.log2(hexamers_probs[hexamer_sum > 0]))\n",
    "\n",
    "print(\"Hexamer Entropy = \" + str(hexamer_entropy))\n",
    "\n",
    "\n",
    "#Calculate average/std hexamer entropy\n",
    "\n",
    "nonzero_index = np.nonzero(hexamer_sum > 0)[0]\n",
    "\n",
    "hexamer_entropies = []\n",
    "for j in range(n_nonzero_hexamers) :\n",
    "    p_on = len(np.nonzero(hexamers[:, nonzero_index[j]] > 0)[0]) / hexamers.shape[0]\n",
    "    p_off = 1. - p_on\n",
    "\n",
    "    hexamer_entropy = 0\n",
    "    if p_on * p_off > 0. :\n",
    "        hexamer_entropy = -(p_on * np.log2(p_on) + p_off * np.log2(p_off))\n",
    "\n",
    "    hexamer_entropies.append(hexamer_entropy)\n",
    "\n",
    "hexamer_entropies = np.array(hexamer_entropies)\n",
    "\n",
    "print(\"Mean Binary Hexamer Entropy = \" + str(round(np.mean(hexamer_entropies), 4)))\n",
    "print(\"Std Binary Hexamer Entropy = \" + str(round(np.std(hexamer_entropies), 4)))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean distance/nt = 0.4961\n",
      "std distance/nt = 0.0347\n",
      "-------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/anaconda3/envs/tensorflow_p36/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import editdistance\n",
    "\n",
    "#Calculate random pair-wise edit distances\n",
    "\n",
    "save_figs = False\n",
    "\n",
    "seqs = [\n",
    "    acgt_encoder.decode(onehots[i, :, :]) for i in range(onehots.shape[0])\n",
    "]\n",
    "\n",
    "shuffle_index = np.arange(len(seqs))\n",
    "np.random.shuffle(shuffle_index)\n",
    "\n",
    "distances = []\n",
    "for i in range(len(seqs)) :\n",
    "    if i == shuffle_index[i] :\n",
    "        continue\n",
    "    \n",
    "    seq_1 = seqs[i]\n",
    "    seq_2 = seqs[shuffle_index[i]]\n",
    "    \n",
    "    dist = editdistance.eval(seq_1, seq_2)\n",
    "\n",
    "    distances.append(dist)\n",
    "\n",
    "    import seaborn as sns\n",
    "\n",
    "distances = np.array(distances) / np.sum([1 if sequence_templates[0][j] == 'N' else 0 for j in range(len(sequence_templates[0]))])\n",
    "\n",
    "print(\"mean distance/nt = \" + str(round(np.mean(distances), 4)))\n",
    "print(\"std distance/nt = \" + str(round(np.std(distances), 4)))\n",
    "print(\"-------------------------\")\n",
    "\n",
    "f = plt.figure(figsize=(6, 4))\n",
    "\n",
    "sns.violinplot(data=[distances])\n",
    "\n",
    "plt.xticks([], [])\n",
    "plt.yticks(fontsize=14)\n",
    "\n",
    "plt.ylabel('Edit distance / nucleotide', fontsize=18)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "if save_figs :\n",
    "    plt.savefig(model_prefix + \"_edit_distance_violin.png\", transparent=True, dpi=150)\n",
    "    plt.savefig(model_prefix + \"_edit_distance_violin.eps\")\n",
    "    plt.savefig(model_prefix + \"_edit_distance_violin.svg\")\n",
    "\n",
    "plt.show()\n",
    "\n",
    "f = plt.figure(figsize=(6, 4))\n",
    "\n",
    "sns.stripplot(data=[distances], jitter=1.)\n",
    "\n",
    "plt.xlim(-0.25, 0.25)\n",
    "\n",
    "plt.xticks([], [])\n",
    "plt.yticks(fontsize=14)\n",
    "\n",
    "plt.ylabel('Edit distance / nucleotide', fontsize=18)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "if save_figs :\n",
    "    plt.savefig(model_prefix + \"_edit_distance_stripplot.png\", transparent=True, dpi=150)\n",
    "    plt.savefig(model_prefix + \"_edit_distance_stripplot.eps\")\n",
    "    plt.savefig(model_prefix + \"_edit_distance_stripplot.svg\")\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plot_n_seqs = 145\n",
    "plot_start = 0\n",
    "plot_end = 145\n",
    "\n",
    "save_figs = False\n",
    "\n",
    "flat_pwms = np.zeros((pwms.shape[0], pwms.shape[1]))\n",
    "for i in range(pwms.shape[0]) :\n",
    "    for j in range(pwms.shape[1]) :\n",
    "        max_nt_ix = np.argmax(pwms[i, j, :])\n",
    "\n",
    "        flat_pwms[i, j] = max_nt_ix + 1\n",
    "\n",
    "flat_pwms = flat_pwms[:plot_n_seqs, plot_start:plot_end]\n",
    "\n",
    "cmap = colors.ListedColormap(['red', 'blue', 'orange', 'darkgreen'])\n",
    "bounds=[0, 1, 2, 3, 4, 5]\n",
    "norm = colors.BoundaryNorm(bounds, cmap.N)\n",
    "\n",
    "f = plt.figure(figsize=(4, 12))\n",
    "\n",
    "plt.imshow(flat_pwms, aspect='equal', interpolation='nearest', origin='lower', cmap=cmap, norm=norm)\n",
    "\n",
    "plt.xticks([], [])\n",
    "plt.yticks([], [])\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "if save_figs :\n",
    "    plt.savefig(model_prefix + \"_diversity_seqs.png\", transparent=True, dpi=150)\n",
    "    plt.savefig(model_prefix + \"_diversity_seqs.svg\")\n",
    "    plt.savefig(model_prefix + \"_diversity_seqs.eps\")\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Get latent space predictor\n",
    "saved_predictor_w_dense = Model(\n",
    "    inputs = saved_predictor.inputs,\n",
    "    outputs = saved_predictor.outputs + [saved_predictor.get_layer('dragonn_dense_1_copy').output]\n",
    ")\n",
    "saved_predictor_w_dense.compile(loss='mse', optimizer=keras.optimizers.SGD(lr=0.1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load GENESIS models and predict sample sequences\n",
    "\n",
    "batch_size = 64\n",
    "\n",
    "n = 4096\n",
    "n_slack = 0\n",
    "\n",
    "n_ceil = int((n + n_slack) / batch_size) * batch_size\n",
    "if n_ceil < n :\n",
    "    n_ceil += batch_size\n",
    "\n",
    "sequence_class = np.array([0] * n_ceil).reshape(-1, 1) #np.random.uniform(-6, 6, (n, 1)) #\n",
    "\n",
    "noise_1 = np.random.uniform(-1, 1, (n_ceil, 100))\n",
    "noise_2 = np.random.uniform(-1, 1, (n_ceil, 100))\n",
    "\n",
    "pred_outputs = generator.predict([sequence_class, noise_1, noise_2], batch_size=batch_size)\n",
    "\n",
    "_, _, _, optimized_pwm, _, sampled_pwm, _, _, _ = pred_outputs\n",
    "\n",
    "pwms = optimized_pwm[:, :, :, 0]\n",
    "onehots = sampled_pwm[:, 0, :, :, 0]\n",
    "\n",
    "#Make predictions using black box model\n",
    "\n",
    "score_pred, dense_pred = saved_predictor_w_dense.predict(x=[onehots], batch_size=batch_size)\n",
    "\n",
    "score_pred = np.ravel(score_pred[:, 5])\n",
    "\n",
    "sort_index = np.argsort(score_pred)[::-1]\n",
    "\n",
    "pwms = pwms[sort_index][:n]\n",
    "onehots = onehots[sort_index][:n]\n",
    "score_pred = score_pred[sort_index][:n]\n",
    "dense_pred = dense_pred[sort_index][:n]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Save sequences to file\n",
    "with open(model_prefix + \"_4096_sequences.txt\", \"wt\") as f:\n",
    "    for i in range(onehots.shape[0]) :\n",
    "        seq = acgt_encoder.decode(onehots[i])\n",
    "        \n",
    "        f.write(seq + \"\\n\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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