{
 "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",
    "import os\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import scipy.sparse as sp\n",
    "import scipy.io as spio\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from scrambler.models import *\n",
    "from scrambler.utils import OneHotEncoder, get_sequence_masks\n",
    "from scrambler.visualizations import plot_dna_logo, plot_dna_importance_scores\n",
    "\n",
    "from optimus5_utils import load_optimus5_data, load_optimus5_predictor, animate_optimus5_examples\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_train.shape = (15008, 1, 50, 4)\n",
      "x_test.shape = (3200, 1, 50, 4)\n",
      "y_train.shape = (15008, 1)\n",
      "y_test.shape = (3200, 1)\n"
     ]
    }
   ],
   "source": [
    "#Load Optimus-5 data and predictor\n",
    "\n",
    "encoder = OneHotEncoder(seq_length=50, channel_map={'A' : 0, 'C' : 1, 'G' : 2, 'T' : 3})\n",
    "\n",
    "train_data_path = 'bottom5KIFuAUGTop5KIFuAUG.csv'\n",
    "test_data_path = 'randomSampleTestingAllAUGtypes.csv'\n",
    "\n",
    "x_train, y_train, x_test, y_test = load_optimus5_data(train_data_path, test_data_path)\n",
    "\n",
    "predictor_path = 'saved_models/optimusRetrainedMain.hdf5'\n",
    "\n",
    "predictor = load_optimus5_predictor(predictor_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define sequence template and background\n",
    "\n",
    "sequence_template = '$' * 50\n",
    "\n",
    "pseudo_count = 1.0\n",
    "\n",
    "onehot_template = encoder(sequence_template)[None, ...]\n",
    "sequence_mask = get_sequence_masks([sequence_template])[0]\n",
    "\n",
    "x_mean = (np.sum(x_train, axis=(0, 1)) + pseudo_count) / (x_train.shape[0] + 4. * pseudo_count)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualize background sequence distribution\n",
    "\n",
    "plot_dna_logo(np.copy(x_mean), sequence_template=sequence_template, figsize=(10, 1), logo_height=1.0, plot_start=0, plot_end=50)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean KL Div against background (bits) = 1.9679329305814974\n"
     ]
    }
   ],
   "source": [
    "#Calculate mean training set kl-divergence against background\n",
    "\n",
    "x_train_clipped = np.clip(np.copy(x_train[:, 0, :, :]), 1e-8, 1. - 1e-8)\n",
    "\n",
    "kl_divs = np.sum(x_train_clipped * np.log(x_train_clipped / np.tile(np.expand_dims(x_mean, axis=0), (x_train_clipped.shape[0], 1, 1))), axis=-1) / np.log(2.0)\n",
    "\n",
    "x_mean_kl_divs = np.sum(kl_divs * sequence_mask, axis=-1) / np.sum(sequence_mask)\n",
    "x_mean_kl_div = np.mean(x_mean_kl_divs)\n",
    "\n",
    "print(\"Mean KL Div against background (bits) = \" + str(x_mean_kl_div))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
      "For more information, please see:\n",
      "  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
      "  * https://github.com/tensorflow/addons\n",
      "If you depend on functionality not listed there, please file an issue.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Build scrambler\n",
    "\n",
    "#Scrambler network configuration\n",
    "network_config = {\n",
    "    'n_groups' : 5,\n",
    "    'n_resblocks_per_group' : 4,\n",
    "    'n_channels' : 32,\n",
    "    'window_size' : 3,\n",
    "    'dilation_rates' : [1, 2, 4, 2, 1],\n",
    "    'drop_rate' : 0.0,\n",
    "    'norm_mode' : 'instance',\n",
    "    'mask_smoothing' : False,\n",
    "    'mask_smoothing_window_size' : 5,\n",
    "    'mask_smoothing_std' : 1.,\n",
    "    'mask_drop_scales' : [1, 5],\n",
    "    'mask_min_drop_rate' : 0.0,\n",
    "    'mask_max_drop_rate' : 0.5,\n",
    "    'label_input' : False\n",
    "}\n",
    "\n",
    "#Initialize scrambler\n",
    "scrambler = Scrambler(\n",
    "    scrambler_mode='inclusion',\n",
    "    input_size_x=1,\n",
    "    input_size_y=50,\n",
    "    n_out_channels=4,\n",
    "    input_templates=[onehot_template],\n",
    "    input_backgrounds=[x_mean],\n",
    "    batch_size=32,\n",
    "    n_samples=32,\n",
    "    sample_mode='gumbel',\n",
    "    zeropad_input=False,\n",
    "    mask_dropout=False,\n",
    "    network_config=network_config\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded scrambler model from saved_models/optimus5_inclusion_scrambler_bits_0125_epochs_10.h5 \n"
     ]
    }
   ],
   "source": [
    "#Load pre-trained scrambler model\n",
    "save_dir = 'saved_models'\n",
    "\n",
    "model_name = 'optimus5_inclusion_scrambler_bits_0125_epochs_10'\n",
    "\n",
    "if not os.path.isdir(save_dir):\n",
    "    os.makedirs(save_dir)\n",
    "\n",
    "model_path = os.path.join(save_dir, model_name + '.h5')\n",
    "\n",
    "scrambler.load_model(model_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "128/128 [==============================] - 2s 12ms/step\n"
     ]
    }
   ],
   "source": [
    "#Interpret the test set using the trained scrambler\n",
    "pretrained_pwm_test, pretrained_sample_test, pretrained_importance_scores_test = scrambler.interpret(x_test[:128])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating pre-trained scores...\n",
      "128/128 [==============================] - 0s 502us/step\n",
      "Finetuning batch 0...\n",
      "Epoch 1/1\n",
      "500/500 [==============================] - 19s 39ms/step - loss: 45.2304 - ft_nll_loss: 40.9039 - ft_entropy_loss: 4.3265\n",
      "Epoch 1/1\n",
      "500/500 [==============================] - 18s 36ms/step - loss: 31.3552 - ft_nll_loss: 30.4189 - ft_entropy_loss: 0.9364\n",
      "Epoch 1/1\n",
      "500/500 [==============================] - 18s 36ms/step - loss: 26.7862 - ft_nll_loss: 24.6823 - ft_entropy_loss: 2.1039\n",
      "Epoch 1/1\n",
      "500/500 [==============================] - 18s 36ms/step - loss: 31.8888 - ft_nll_loss: 30.6709 - ft_entropy_loss: 1.2179\n"
     ]
    }
   ],
   "source": [
    "#Interpret the test set using the trained scrambler\n",
    "finetuned_pwm_test, finetuned_sample_test, finetuned_importance_scores_test, finetuned_histories = scrambler.finetune(\n",
    "    predictor,\n",
    "    x_test[:128],\n",
    "    y_test[:128],\n",
    "    batch_size=32,\n",
    "    n_iters=500,\n",
    "    norm_mode='instance',\n",
    "    max_score_clip=4.,\n",
    "    adam_lr=0.01,\n",
    "    adam_beta_1=0.5,\n",
    "    adam_beta_2=0.9,\n",
    "    nll_mode='reconstruction',\n",
    "    predictor_task='regression',\n",
    "    entropy_mode='maximization',\n",
    "    entropy_bits=0.125,\n",
    "    entropy_weight=10.\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "def _rolling_average(x, window=1) :\n",
    "    x_avg = []\n",
    "    \n",
    "    for j in range(x.shape[0]) :\n",
    "        j_min = max(j - window + 1, 0)\n",
    "        x_avg.append(np.mean(x[j_min:j+1]))\n",
    "    \n",
    "    return np.array(x_avg)\n",
    "\n",
    "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(2 * 4, 3))\n",
    "\n",
    "n_epochs_actual = len(finetuned_histories[0]['ft_nll'])\n",
    "\n",
    "nll_rolling_window = 25\n",
    "entropy_rolling_window = 25\n",
    "\n",
    "for i in range(len(finetuned_histories)) :\n",
    "    ax1.plot(np.arange(1, n_epochs_actual + 1), _rolling_average(np.array(finetuned_histories[i]['ft_nll']), window=nll_rolling_window), linewidth=3)\n",
    "\n",
    "plt.sca(ax1)\n",
    "plt.xlabel(\"Epochs\", fontsize=14)\n",
    "plt.ylabel(\"NLL\", fontsize=14)\n",
    "plt.xlim(1, n_epochs_actual)\n",
    "plt.xticks([1, n_epochs_actual], [1, n_epochs_actual], fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "\n",
    "for i in range(len(finetuned_histories)) :\n",
    "    ax2.plot(np.arange(1, n_epochs_actual + 1), _rolling_average(np.array(finetuned_histories[i]['ft_entropy']), window=entropy_rolling_window), linewidth=3)\n",
    "\n",
    "plt.sca(ax2)\n",
    "plt.xlabel(\"Epochs\", fontsize=14)\n",
    "plt.ylabel(\"Entropy Loss\", fontsize=14)\n",
    "plt.xlim(1, n_epochs_actual)\n",
    "plt.xticks([1, n_epochs_actual], [1, n_epochs_actual], fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test sequence 0:\n",
      " - Prediction (original) = -1.0\n",
      " - Predictions (scrambled, pretrained) = [-0.9, -0.3, -1.0, -1.5, -0.7, -0.8, -1.2, -0.9, -0.3, -1.1, -1.0, -1.2, -1.2, -1.1, -1.1, -0.6, -0.2, -1.2, -1.3, -0.8, -1.2, -1.4, -1.2, -1.2, -0.6, -0.9, -1.3, -0.9, -0.8, -0.9, -1.5, -0.4]\n",
      " - Predictions (scrambled, finetuned) = [-0.9, -1.0, -1.4, -0.9, -0.2, 0.0, -0.2, -0.7, 0.08, -0.9, -1.1, -0.9, -0.5, -1.2, -1.3, -0.3, -0.7, -0.5, -0.9, -1.3, -0.4, -0.9, -0.0, -1.5, -1.2, -0.0, -1.3, -0.4, -0.4, 0.47, -0.5, -0.5]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsgAAABACAYAAAAH14HqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAB/5JREFUeJzt3V+MXUUBx/Hv9G+aQin//ENJXUBBiwqm0FbBdjemxhiIJjZFDxqjaEx80fiCJpj44j/eTIgJookaOeqDTYwxQlBbsGJrW2NFjCYCFVAK1TTF1sJCOz7MXXfu2XvdvXtP7z3d+/0kzc7MmTtnHrrZ387OmRNijEiSJElKFg17ApIkSVKTGJAlSZKkjAFZkiRJyhiQJUmSpIwBWZIkScoYkCVJkqSMAVmSJEnKGJAlSZKkjAFZkiRJyiwZ9gSkxihDAD4JfA5Y02rdBdxOEX87rGlJkqTBcgVZmvYF4C6mwzHAOLCbMtw6jAlJkqTBCzHGYc9BGr4y3AT85P/0eBnYShF3DWZCkiRpWFxBlsqwBPjqLL2WAJ8YwGwkSdKQGZAl2A6sG/YkJElSMxiQJfjYsCcgSZKaw4Cs0VaG1cDmYU9DkiQ1hwFZo24CWNyh/ThweMBzkSRJDWBA1qh7Z4e2B4ALgUuALcATA52RJEkaKl8UogUhfDz0dF5hvCeGVnF95dIjwDaKONmqP0QZtgC/6XOKkiTpLOEKskbdWKX+WYr4fFtLEZ8CtgGnBzQnSZI0RK4ga3SVYSVwcdbyHHB/x75F3EMZ/IVSkqQR4A98jbK1lfpOiniqa+8iPnxmpyNJkprAgKxRNlapG4AlSZIBWSNtrFL3tApJkmRA1kgbq9SfHsYkJElSs/iQnhaE7Ng2YOaxb9XrLWOV+t9rnpYkSToLuYKsUfaKrDwJ/HNYE5EkSc1hQNYoW56V/0ERPedYkiS5xUINF8Jq2oPsCWI8XtPoy7Jy+5hluAx4V4fP/IAiHq3p/pIkqYEMyGq6ncC1Wf27wIdrGjsP3pOVa9cAX+8yHwOyJEkLmFss1FwhrATeXGndVOMd8oD8Uo3jSpKks5gBWU22npn/R68khPNrGj/O3kWSJI0at1ioyTZ2ad8A3F/D+Pm2iqU1jCdJkvoVwkXAnZXWLxLjY4OaggFZTdYtIG+knoD8YlY2IEuS1AwTwEcqbb8D7hrUBAzIarI8IB8Fzu/Q3o98BfncmsaUJGlkVV/UNZsuL/Ka6NI2sIDsHmQ1UwhrgEuzlu9k5Y2E0Okbqlf5CvKrKdvGjKQH907VcB9JkjR3nQLyOCEMLLe6gqymyleJJ0kB+dOt+oXAFcBf+7zHs1l5eWvc9Da9Iv4YWEYZ3gg80ud9JEnSXITwKuD1Ha5cALwJONj1s2mhazPwFmA1cBJ4HNhDEZ/qZRoGZDVVHpD/QAqpJ4CV2fV+A/KhSv0SfN20JEnDNJ6VjwFHgNdm12YG5DKsIC2i3UZaQJupDHuBT1HEvXOZhAFZTZUH5APEeIoQfg/ckF2/t897/K1SX0MK45IkaR6qe4qre5K77DnO5dsrfg0cZjogTwBfa+tdhtWkB/c3zDLuRmALYEDWWSqExcB1WcuB7GsekPtVDciX1TCmJEmavzwg7waeAT7aqm8hhMXEmD8f9E3aw/HLwI7WZxcBVwHvBl7TyyQMyGqiq5neSgGwv/X1QNZ2LSEsJ8b8QbteHarUN9H59dKSJOlMSw/ovy5rmQrIU1YD15COfIMyXAW8L7v+GLCVIj7RNm4ZFgHvpYfca0BWE+Wvk54EHm2V92fty0ib8Pf0cZ/qCvIEZVhEEU/3MaYkSZqf8aw8CewjnTj1LPDKVvsEUwEZbql8/rYZ4Rho/Vzf0ctEPOZNTZRvnzhIjFPnFf+F9KBep369K+IJ2h/Ku5T09KskSRq8fHvFPmJ8gRgjaSV5ynhW3p6VDwO/qmsiriCrifLg+zwh3JzVn2F6s35d+5Avyup3UoYtFPFkDWNLkqS5q+4/zstTWyk2E8IS7uUUaX/xlIfa/gJchquBN1TGP00R57SSbEBWs4SwCliXtbyj9a+TOgLyPmB9Vr8e+DZluBU4Ddzc8VOSJKk+IawFLs9a9hLCsv+Vp60ibbH8I+059mhlxFuAz1faXgBWzGU6brFQ01wHzPUteZcTwsV93u/nHdq2k77RjgBf6nN8SZI0u/FKfQdp//GLwMOVaxOksJufZnFunZMxIKtpel0Vnu3cw9n8kvRa6apzSG/tkSRJZ16n10t371vECOQP5L2t9Sa9KT8CPgTcPZ/JGJDVNJtm79JX/3ZFPEqNm/olSdK89BKQbySEpaQQPGWMdARcUsSDFPF7pJeN9Mw9yGqOEALtK8h3A5/p0PM+4O2tch37kL/FfE6vKMMS0n6pK0grzitJe5tOk/7082/gX8CfKOKRGuYpSdLCE8IY7S/y2E062i23CtjaKp9Den7oh8DtWZ9vUIatFPFYv1MyIKtJ1jJ9ziHAHmL8z4xeIexjOiBvIIRFxL7OLv4+cAfth5N38ijwJGW4gbQ3+a2k76GfAruAJ4HnSHuiVpC2aKxrle/rY36SJC1k1dXjDxDj020tIawAjgFLs898BdiZff564HHKcA/p5WJLgW3zmZABWU1SXQ3e37FXe/t5wJXAn+d91yK+RBnuIP0m2s1x0jfZSeBnTD8M8AuKOH3SRRneA7yfFIrPa7XeiAFZkqRu8oB8aEY4BojxJCHsJy1Opc8U8cuU4YPAg0wfAXsB7avK8xLS+ctz7BzC3DtLkiRJDRJjnNNJWT0FZEmSJGmh8xQLSZIkKWNAliRJkjIGZEmSJCljQJYkSZIyBmRJkiQpY0CWJEmSMgZkSZIkKWNAliRJkjIGZEmSJCljQJYkSZIy/wXNKXMiNvrRLAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test sequence 1:\n",
      " - Prediction (original) = -1.0\n",
      " - Predictions (scrambled, pretrained) = [-0.8, -0.4, -0.7, -1.3, -0.8, -1.3, -0.7, -0.8, -0.9, -0.9, -0.5, -0.7, -1.3, -1.2, -1.2, -0.9, -0.7, -1.6, -1.0, -1.3, -1.5, -1.8, -0.1, -1.6, -1.2, -1.1, -1.5, -1.4, -1.3, -1.0, -1.4, -0.9]\n",
      " - Predictions (scrambled, finetuned) = [-1.6, 0.68, -0.7, -0.6, -0.9, 0.66, -0.5, -1.0, -0.8, -0.8, 0.6, -0.6, -1.3, -0.4, -0.5, -0.8, -0.6, -0.7, -0.3, 0.01, 0.12, -1.1, -1.7, -0.7, -0.6, -1.0, -0.4, -1.0, -0.9, -1.0, 0.48, -1.2]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test sequence 2:\n",
      " - Prediction (original) = -0.9\n",
      " - Predictions (scrambled, pretrained) = [-0.6, -0.3, -0.3, -1.0, -0.1, -0.0, -0.9, 0.32, -1.4, -1.0, -0.9, -0.9, -0.1, -0.8, -0.2, -0.1, -0.4, -0.8, -1.1, -1.5, -1.0, -1.0, -0.5, -1.3, -0.7, -0.6, 0.33, -0.2, -0.8, -0.1, -0.8, -0.8]\n",
      " - Predictions (scrambled, finetuned) = [-0.2, -0.3, -0.2, -0.4, -0.8, -0.8, -0.6, -1.0, -0.1, -0.7, -0.7, -0.7, -0.9, -0.8, -0.9, -0.4, -0.5, 0.29, 0.77, -0.8, -0.8, -0.8, -0.8, -1.0, -0.4, -0.7, -0.6, -0.2, -0.5, -0.2, -0.0, -0.7]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsgAAABACAYAAAAH14HqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAACHtJREFUeJzt3V+MXFUBx/Hv6R9abKXYQKgVJaW1thb/YLdAUUBTfSFYjRD/3ERJo00wGnzQBzW0asAEX9SkKtHGxDT2QqMxhtJG1AgWSyUaaVWooG2stIWgWEpFW2g5PtwZ5szd2e7O3Nvddub7SSZ775lzzz0vu/PbM+eeE2KMSJIkSSpMmugOSJIkSacTA7IkSZKUMCBLkiRJCQOyJEmSlDAgS5IkSQkDsiRJkpQwIEuSJEkJA7IkSZKUMCBLkiRJCQOyJEmSlJgy0R2QdHoJq0NX+8/H9TGcqr5IkjQRHEGWJEmSEgZkSZIkKWFAliRJkhIGZEmSJClhQJYkSZISBmRJkiQp4TJvkk6dPMwDlgDPADvJ4v8muEeSJI0qxNjVkqeSBkx5XeQxrXuchwuAjcCKpPQ54NvArQZlSdLpzCkWkuqVhznAfbSHY4BzgC8AD5KH88e9X5IkjZEBWVJ98jAFuBdYfJJabwW+Oj4dkiSpewZkSXVaBbx5DPWmnuqOSJLUKwOypHrkYTKwdqK7IUlSVQZkSXW5GrhwojshSVJVBmRJdflQh7L7gUXAa4FPAAfHs0OSJPXCdZAl1eWa0vkW4AayeLRx/n3ysAXYOr7dkiSpO44gS6ouD1OBBUnJceBTSTguZPEp4Fpg//h1TpKk7jiCLA2KENYC85OSrcS4qabWL6b978nPyeK+jjWz+BR5uK2m+0qSVDsDsjQIQpgEfJZis46m2UBdAXlR6XzLSWtn8VhN95UkqXZOsZAGwwLawzHAECGMvm302JQD8qM1tStJ0rgzIEuDYWmHsjnA3JraLwfkPTW1K0nSuHOKhTQYhkYoXwocqKH9dG7zC7icmySpV8W0wFeXSp8mxhfHqwuOIEuDYaSAPFJ5t2Ykx38niydqaleSNHgupVjtKH29Zzw74Aiy1O+K/8TflpTsp7XjXV0B+ezk+HDbO3lYBqzqcM0asvhMTfeXJPWP8rr6zbJxW0ffgCz1v4XAzOR8A/DFxnHxoF6MseI9pifH5RUqFgCf7HDN1wADsiSp7J1jLBsuD7OAJRQrNT0P/BU4QNbd55wBWep/6SjxEeAntALy+RSjyU9UvEf6t+R4xbYkSWeosDp0FUTj+ti+mlIIk4GrOlRdSgivJMYjHRvKwyLgZuBG4BWld/eQhw3AOrJ4aCz9cg6y1P/SgLwL+DPtIbaOaRbpqPFZNbQnSRpMbwLOTc6bn1eTgSs7XpGHTwO7Kb6tLIdjKB4k/wqweqydMCBL/S8NwDuJ8RjwyAjv9yrdUnpaDe1JkgZTOv94L/DQCO8V8vB+YF2Hdo5SrKrUE6dYSP2s+Krq0qRkZ/LzLY3jugPyBTW0J0k6A5WnTJSnXAybUjFcGoK3A08Cb+/wHuRhKnBH6fqfAbcCOxrn84EbgM+Mct82BmSpvy2i/eumNCDf2Diu40G9fyfHryEP05LtpLcB7wVeD3y9wj0kSf2sWHWpU0BuuowQZhDj843zqyg2vWr6KXA9WXwpKfsbcDt5+A5w8Vi74hQLqb+lo8PHaU2t2JmUzwYuqnifx5Lj0NZeFg+QxXuAByreQ5LU35qrTzRtBx5MzqcAy5PzlaXrP18Kxy1ZfI4s7uz4XgcGZKm/pVtM7ybG5lSIXaV6VadZ/KV0Pq9ie5KkwZOOHj8LPEqM/wIeH6HOdcnxvlK9SpxiIfW39gf0mmI8RAj7aI30DgE/rnCfckC+DLi3QnuSpMGTht8dxJdHg7dTrOnfqpOH9m8r4bdtax3nYXFyTdNLZHHzWDpiQJaKX7IrgHdQLCGzgGLr5BPAIeAfwB+BzWTx4YnqZtdCmEL7A3orCWFvcp7uc191BPmx0vlKiockJEkaXQiB4fOP0+PmjqyXE8LZbATac+yzpRY/AqwplR2lfefXERmQNdjysAT4Ae0B8QXgIMXavhcCy4DrgcUUv3BnijfSvsPdrMark6UVH9Q7CPyH1o59Q+RhOVnccZJrJElqWkyxeVXTYUJofjb/Nyk/i2JQ69dApHjuBWpeYtQ5yBpceZgN3E8rHO8BPgjMJIvzyOIlZHEuxYLl1wFbJqSfvVs6epWXnUsXT/cOU3yt9Uip9E7yMD859++NJGkk5TWO1wG/a7zyYXWLh/HSFZQWl+rspljV4g+9dMYRZA2yLwHnNY4j8D6yWA55kMXDnHnhGLqfNjFE8U9CrzYDlyfnFwG/IQ/folhBY1XHqyRJ6rQJyOh176NY4xhgGXmY1fjMhizeSTFQ81FgQ7edMSBrkL0rOd7VFo7zsBy4pcM1N5HFJ051x2qSBuSnGT5PGIrpI81pGEPApgr3+xFwW6lsTocySZJahs8/Hs0VhDCdjdxNKyBPohiI+WYdXTIga5AdSY7PIw+TyeKJxvlMio0tpgGvS+rNGK/OVRLCVFo75QHcQYxf7lDvl8CKxlk3UzKGy+Lj5GEbcHWldiRJg2Yh7Rt+3A3sL9V5Fa3ngKZTrJa0leKB+smN8tvJwz+Bu5LP854YkDXI1lGsWgHFw3gfB74HQBZ/ASwkD5cAf5qQ3lWzhPYHFkZafeNh0oAcwqRkWZ1e3EKxc95YvFjhPpKk/lEePb6JGJ9sKwlhGvABWp9t15DFbeThG8DnGmXTgB8Ca8jDQxQP9PU0aONDMxpkmygm8Dd9lzxsJQ+ryMMK8nAl8O4J6ltV5fnHIwXkdFehcyiWuOtdFh8A1o+h5s1k8WCle0mS+kUakPcOC8cAMR4Dft/hmrXAr0q13wB8DPgwMLeXDoVuVnUKIfS6BJQkSZI0oWKMYfRaXQZkSZIkqd85xUKSJElKGJAlSZKkhAFZkiRJShiQJUmSpIQBWZIkSUoYkCVJkqSEAVmSJElKGJAlSZKkhAFZkiRJShiQJUmSpMT/AVilnDlP/dskAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsgAAABACAYAAAAH14HqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAACilJREFUeJzt3XvoX3Udx/Hn5+e2n+7Scs52cbl5w5BIqWheKqywNKKLlsSJsEAhwuzyR4VhF8IKhJAoCCq64fECZRFS4Gi0xBSRJLWUxCbb1M3NvKRtc/t9+uP8ftvnnN/5/vY933Pm7HyfD/jC99w/f53z+r6/n8/nhBgjkiRJkgoTR7oBkiRJ0iuJAVmSJElKGJAlSZKkhAFZkiRJShiQJUmSpIQBWZIkSUoYkCVJkqSEAVmSJElKGJAlSZKkxLwj3QBJPZWHFcCVwFuA7cBvgVvJ4tQRbZckSYcQfNW0NCZC2ACsT9Z8lxi/Nmu3K0Kjm0L8UQyzVuZhPbABWFzZsgn4CFnc0eQakqQxEsIkcGll7e+I8ZmXqwlWkKXx8TrKgfXUw3KVPJwK/IHZ4Rjg7cBG8nAOWXzusFxfknTEdFJkgZOAX1TWnQ/8acRmNWYfZGkchLAAWF1Zu/YwXe07wKvn2H4G8I3DdG1J0v+/uufT4Xpm1bKCLI2HE4Dqr/QTO79K0bXikiH2nCtAS5LGW7uAnIclwCrgcbL4n1EaYAVZGg91N5YTCGF+x9f5TMfnkySNn9ECch6OJQ8/A3YADwPPk4cN5OGcpg0wIEvjoa5aPEFRWe5GHiaBD3V2PknSuGoekPOwCLgNuAw4OtnyLuAO8vDZJg0wIEvjYdCNpctuFm8FFnZ4PknSeGoWkPMwAfwaGFQpngCuJw9DF3EMyNJ4GHRj6XLQw7tr1m0FLgLOA34AOK+kJOlQ6p5NJxLCoNx6CfXPoKrThm2Ag/Sk8TCoUjxrfXXKneqUPQOm5AF4W2X5WeBCsvjg9PKd5GEjcMuhmytJGkvF2Ji67n+TwArgidLaonr81a6bYUCWxsPLUUE+ubL8hSQcF7L4K/LwReD1HV5XkvQK0aLIMmMNg3s4rKUakIu3tXb+TLGLhdR3IQTKleLHku/dBOQ8LKT4ZT/jeeDmAXtfD9zZyXUlSX1TfS69OMc2qB8cPgXcDdw7/b0xA7LUf8dTHtH7l+R7V4P0qjetjWTxhdo9s7gf+ElH15Uk9Uv6PNkFPDpg24wPVJb3Ax8ji2eTxTcDZ1IE5UYMyFL/VW8od5W2FRXmttZVljfNuXcWR/pFL0nqvfSZtWX6U7dt5t/L0yvHf4os3nRgKYsPAO+kqCgPzYAs9V9aJd5H+Zf0McBxHVxjXWX54Q7OKUkaP8MHZDi1svwo8NNZZ8zic8CHgZ3DNsKALPVfekPZRrkPcnX7qE6qLG/t4JySpPHTJCBXp227Zbob32xZ3Ar8fNhGGJCl/ksryFsoRgCnXRy6CMjrKssGZEnSKOYOyOVugdWAfPucZx4UnmsYkKX+S282W4lxH+VpcroYqJfOWbmHYmCFJEnDK14EUi3qpAF5CXBsslwNyA911RQDstR/1ZsNlCu8XVSQ01kytpFF35gnSWpqJbAgWa4GZCg/s9KAvAd4squG+KIQqf/KFeTCFmB9zfZRpTe0f5e25GE5cErNMfeRxT0dXFuS1A/V59EWYHvNPn+d/p4+Wx7rcoYkA7LUZyEsojxLRV0FuYsuFpPJ972VbRcAec0x65g9YFCSNL7SgByBbcS4lxB2cfBZlu6zNPm+ucuGGJClfquG37SCPKPrCnI1IEuSNIz0ebSdGGeeJ1uoD8hp976nSmfKw0rKb3gFiGTxb8M0xIAs9Vvd31VQriAvJ4SFxPgio0vHM9j/WJI0iuoMFun3s0r75GEecFSyT7XL3qeBayrrdlPM/39IDtKT+i2tIL8E7Jj+Xp2GrW03i7RqPL/luSRJ42mugFzdJ+3aBx3/e2lAlvqt/JKQeGAAw1yjgkdhQJYktdUkIHc2IK+OAVnqt7oZLGD2y0LaVpDTv7YWtTyXJGncFC8AGSYgL58egF7tUlGtKLdiQJb6rW4OZGpeFtJlBXl1y3NJksbPMmBxsjwoIAOsnZ7S7aVk3dF0yIAs9VsafI8hhIsOfOC/yba2FeR09PCx5CEdBHErxUji97S8hiSpv6qFmglCOI0QTmN2172ZfdMqcqfFGWexkPoqhHmUXwH9welPnbYV5M2V5ROARwDI4m5gN3l4uuU1JEn9VX0O3TjEvk9xsOpcPf77wM3A+4FvNW2MFWSpv1ZTngJnLocjIEuSNKwmz6GZfR9J1q0hDwefeVncQRYfZPasTUMxIEv91aTbxBpCGDZM19lcWe7i5SOSpPExSkD+Z7JuHh12szAgS/3V5GZzFO1uLJsry+e0OJckafy0DcgAb+ioLQZkqceaVnHbDNTbXFl+B3kILc4nSRovXQTkd3fUFgOy1GNNA2+bbhG7gPRV1acDb2pxPknSeGnyDFpNCAso90EG+Ch56GQ+ZAOy1F9NA+/oATmLkdlV5OvIw4KRzylJGg8hLAaOa3IEsAb4F+WXXr0GuKaLJrWe5i0E5lFMsbEYWADsBp6JsVRNkvTySyvIDwC/r9nncuDYmv1HcQ9wRrJ8PvBD8nAFEIH3tjy/JKmfqgWaWynCb+p44OPJ8jqy+Ch5uAdYn6z/CnnYDVwHLAQuGqVBjQNyCKwErgDOBc4ElgL3AU9S/MU6CSwPgWXAVTGyaZSGSWph9is7byPGL9fsdy5w3vRS25knbgcuq6z7JHAxsI9m1QFJ0vioPn+uJcZ7S2tCWEU5IM8c8xvKARngm8DXKXpKjDQeplFADoG1wF3AyulVNwGXx8gLA/Z3kI50ZCwDFiXL1dd0zkjnh2xbQd4wYP3SlueVJPVbNSDXPbO2U7xaeuatemlA/nbN/m2mLm3cB3kK2J8sz2fukG1Alo6MatgdNFF6ehNaO115Hk0Wt1P8gJYkqYk0IO+heENeWYxTwLZZx2TxIYp/MDvVqIIcI1tC4CyKv03PBd4IPBECf6dI9jNdLJYBS4ArgT932mJJwxjm1ziUg/Niiv7IbV4J/WPg7BbHS5LGT/rM2kKMccB+W4B1NcdcC1wwxHUeG7ZBjfsgx8hOio7PwHQ3ik8cPcW+xbB/Adz4+HLg2RjZlx4XAkcBK4BXUTyIJ4G9FFXpSLnafH+M7G3aNkkHVCvIgwJydf2JtAvIvwSuBk4+xH53A0+0uI4kqT/KAXmw8r+eB20CvgdcNcexO4H3DdugZgE5Dwsp5jddQdG/8cV4A7vCRmDeHgDiDWElsIqcCWA/WXxw2eKnVy+aXPCliTB1CrD0uCW7/nH6qofvWDT5wjPAVCBOTcWJEEIML+2fP/9zF16/E/44dMqXNEt649hNcWOoU+16sZZi0O1osriXPFxNMT5hkJ3ApWTRH8GSJBgtIL+WECaIcYosRvLweYoxcpfWHHc/cDFZrM6bPFAYXMWu2TmE4XeWJEmSXkFijEONtWkUkCVJkqS+8016kiRJUsKALEmSJCUMyJIkSVLCgCxJkiQlDMiSJElSwoAsSZIkJQzIkiRJUsKALEmSJCUMyJIkSVLCgCxJkiQl/geB6PfbQB9FEQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test sequence 3:\n",
      " - Prediction (original) = -1.1\n",
      " - Predictions (scrambled, pretrained) = [-0.9, 0.62, -1.0, -0.2, -0.9, -0.0, 0.14, -1.0, 0.11, -0.6, -0.3, 0.86, -0.3, -0.1, -0.2, -0.7, -0.9, -1.1, 0.34, -0.5, -0.5, -0.2, -0.3, -0.5, -0.7, 0.03, 0.57, -1.3, -0.4, -0.5, -0.6, -0.4]\n",
      " - Predictions (scrambled, finetuned) = [0.52, 0.26, -0.5, -0.8, -0.8, -0.8, -0.7, -0.3, -0.8, -0.9, -0.9, -0.7, 0.26, 0.43, 0.1, -0.9, -0.6, 0.56, -0.5, -0.9, 0.42, -0.1, -0.8, -0.6, 0.87, -0.6, 0.24, -0.2, -0.9, -0.8, -0.2, -0.0]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test sequence 4:\n",
      " - Prediction (original) = -1.2\n",
      " - Predictions (scrambled, pretrained) = [-1.6, -1.7, -1.1, -1.5, -0.8, -0.3, -0.5, -0.4, -1.9, -0.6, -1.0, -1.4, -0.6, -0.5, -1.1, -0.3, -1.5, -1.6, -0.9, -1.4, -1.1, -0.9, -1.0, 0.23, -0.7, -1.5, -1.3, 0.04, -1.4, -1.2, -0.0, -0.5]\n",
      " - Predictions (scrambled, finetuned) = [-1.5, -1.6, -0.6, -1.5, -1.3, -0.4, -0.9, -0.6, -1.1, -1.8, 0.01, -1.4, -0.8, -1.3, -1.6, -1.0, -1.0, -0.8, -1.6, -1.0, -1.9, -1.5, -0.4, -2.1, -1.8, -1.7, -0.5, -0.7, -0.6, -1.4, -0.8, -1.7]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualize a few reconstructed sequence patterns\n",
    "\n",
    "plot_examples = np.arange(5).tolist()\n",
    "save_examples = []\n",
    "\n",
    "pretrained_importance_scores_test *= sequence_mask[None, None, :, None]\n",
    "finetuned_importance_scores_test *= sequence_mask[None, None, :, None]\n",
    "\n",
    "for test_ix in plot_examples :\n",
    "    \n",
    "    print(\"Test sequence \" + str(test_ix) + \":\")\n",
    "    \n",
    "    y_test_hat_ref = predictor.predict(x=[x_test[test_ix:test_ix+1, ...]], batch_size=1)[0, 0]\n",
    "    y_test_hat_pretrained = predictor.predict(x=[pretrained_sample_test[test_ix, ...]], batch_size=32)[:32, 0].tolist()\n",
    "    y_test_hat_finetuned = predictor.predict(x=[finetuned_sample_test[test_ix, ...]], batch_size=32)[:32, 0].tolist()\n",
    "    \n",
    "    print(\" - Prediction (original) = \" + str(round(y_test_hat_ref, 2))[:4])\n",
    "    print(\" - Predictions (scrambled, pretrained) = \" + str([float(str(round(y_test_hat_pretrained[i], 2))[:4]) for i in range(len(y_test_hat_pretrained))]))\n",
    "    print(\" - Predictions (scrambled, finetuned) = \" + str([float(str(round(y_test_hat_finetuned[i], 2))[:4]) for i in range(len(y_test_hat_finetuned))]))\n",
    "    \n",
    "    save_figs = False\n",
    "    if save_examples is not None and test_ix in save_examples :\n",
    "        save_figs = True\n",
    "    \n",
    "    plot_dna_logo(x_test[test_ix, 0, :, :], sequence_template=sequence_template, figsize=(10, 1), plot_start=0, plot_end=50, plot_sequence_template=True, save_figs=save_figs, fig_name=model_name + \"_test_ix_\" + str(test_ix) + \"_orig_sequence\")\n",
    "    \n",
    "    plot_dna_logo(pretrained_pwm_test[test_ix, 0, :, :], sequence_template=sequence_template, figsize=(10, 1), plot_start=0, plot_end=50, plot_sequence_template=True, save_figs=save_figs, fig_name=model_name + \"_test_ix_\" + str(test_ix) + \"_scrambld_pwm_pretrained\")\n",
    "    plot_dna_importance_scores(pretrained_importance_scores_test[test_ix, 0, :, :].T, encoder.decode(x_test[test_ix, 0, :, :]), figsize=(10, 1), score_clip=None, sequence_template=sequence_template, plot_start=0, plot_end=50, save_figs=save_figs, fig_name=model_name + \"_test_ix_\" + str(test_ix) + \"_scores_pretrained\")\n",
    "    \n",
    "    plot_dna_logo(finetuned_pwm_test[test_ix, 0, :, :], sequence_template=sequence_template, figsize=(10, 1), plot_start=0, plot_end=50, plot_sequence_template=True, save_figs=save_figs, fig_name=model_name + \"_test_ix_\" + str(test_ix) + \"_scrambld_pwm_finetuned\")\n",
    "    plot_dna_importance_scores(finetuned_importance_scores_test[test_ix, 0, :, :].T, encoder.decode(x_test[test_ix, 0, :, :]), figsize=(10, 1), score_clip=None, sequence_template=sequence_template, plot_start=0, plot_end=50, save_figs=save_figs, fig_name=model_name + \"_test_ix_\" + str(test_ix) + \"_scores_finetuned\")\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Environment (conda_tensorflow_p36)",
   "language": "python",
   "name": "conda_tensorflow_p36"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}