RECOMB2021.ipynb

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  "metadata": {
    "colab": {
      "name": "RECOMB2021.ipynb",
      "provenance": [],
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      "toc_visible": true,
      "authorship_tag": "ABX9TyOSo8Ivn/NPrD5Reby5yfqb",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/raminass/deep_NMF/blob/master/RECOMB2021.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iiC7qpWBfpsw"
      },
      "source": [
        "# Setup Env"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UKT9Ic0ptEQF"
      },
      "source": [
        "from matplotlib import pyplot as plt\n",
        "from matplotlib.pyplot import text\n",
        "from my_layers import UnsuperNet, SuperNet, UnsuperNetOpt3\n",
        "import utils as util\n",
        "import pandas as pd\n",
        "import sklearn.decomposition as sc\n",
        "import numpy as np\n",
        "import matplotlib.ticker as mticker\n",
        "import joblib\n",
        "import seaborn as sns\n",
        "\n",
        "# This is a bit of magic to make matplotlib figures appear inline in the notebook\n",
        "# rather than in a new window.\n",
        "%matplotlib inline\n",
        "# plt.rcParams['figure.figsize'] = (15.0, 8.0) # set default size of plots\n",
        "# plt.rcParams['image.interpolation'] = 'nearest'\n",
        "# plt.rcParams['image.cmap'] = 'gray'\n",
        "\n",
        "# # use LaTeX fonts in the plot\n",
        "# plt.rc('text', usetex=True)\n",
        "# plt.rc('font', size=30)\n",
        "# plt.rc('legend', fontsize=20)\n",
        "\n",
        "# Some more magic so that the notebook will reload external python modules;\n",
        "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
        "%load_ext autoreload\n",
        "%autoreload 2"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XKLpjZHj4glg"
      },
      "source": [
        "# # latex setting for plots\n",
        "# %%capture\n",
        "! sudo apt-get install texlive-latex-recommended \n",
        "! sudo apt-get install dvipng texlive-latex-extra texlive-fonts-recommended  \n",
        "! wget http://mirrors.ctan.org/macros/latex/contrib/type1cm.zip \n",
        "! unzip type1cm.zip -d /tmp/type1cm \n",
        "! cd /tmp/type1cm/type1cm/ && sudo latex type1cm.ins\n",
        "! sudo mkdir /usr/share/texmf/tex/latex/type1cm \n",
        "! sudo cp /tmp/type1cm/type1cm/type1cm.sty /usr/share/texmf/tex/latex/type1cm \n",
        "! sudo texhash\n",
        "!apt install cm-super ש"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UJHFIIdWVdFL"
      },
      "source": [
        "# Paper Plots"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F4gQOxHFz95i"
      },
      "source": [
        "## Create Data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7iKGkR4s0Bic"
      },
      "source": [
        "### Simulated\n",
        "\n",
        "Run only once"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hUhg4SXu0IoI",
        "outputId": "8dfa6171-c9d6-46b3-da25-2f120a7db1e4"
      },
      "source": [
        "# import all dataset\n",
        "all_mutational = {\n",
        "    1: {\"name\": \"syn.pancreas_sp.sp\", \"sample\": 1000, \"comp\": 11},\n",
        "    2: {\"name\": \"syn.pancreas_sa.sa.96\", \"sample\": 1000, \"comp\": 20},\n",
        "    3: {\"name\": \"syn.many.types_sp.sp\", \"sample\": 2700, \"comp\": 21},\n",
        "    4: {\"name\": \"syn.many.types_sa.sa.96\", \"sample\": 2700, \"comp\": 39},\n",
        "    5: {\"name\": \"syn.3.5.40.rcc.and.ovary_sp.sp\", \"sample\": 1000, \"comp\": 11},\n",
        "    6: {\"name\": \"syn.3.5.40.rcc.and.ovary_sa.sa.96\", \"sample\": 1000, \"comp\": 19},\n",
        "    7: {\"name\": \"syn.3.5.40.abst_sp.sp\", \"sample\": 1000, \"comp\": 3},\n",
        "    8: {\"name\": \"syn.3.5.40.abst_sa.sa.96\", \"sample\": 1000, \"comp\": 3},\n",
        "    9: {\"name\": \"syn.2.7a.7b.bladder.and.melanoma_sp.sp\", \"sample\": 1000, \"comp\": 11},\n",
        "    10: {\"name\": \"syn.2.7a.7b.bladder.and.melanoma_sa.sa.96\", \"sample\": 1000, \"comp\": 26},\n",
        "    11: {\"name\": \"syn.2.7a.7b.abst_sp.sp\", \"sample\": 1000, \"comp\": 3},\n",
        "    12: {\"name\": \"syn.2.7a.7b.abst_sa.sa.96\", \"sample\": 1000, \"comp\": 3},\n",
        "    # # 7.1: {\"name\": \"syn.hyper.low.sa.primary_sp.sp\", \"sample\": 500, \"comp\": 2},\n",
        "    # 7.2: {\"name\": \"syn.hyper.low.sa.primary_sa.sa.96\", \"sample\": 500, \"comp\": 2},\n",
        "}\n",
        "\n",
        "for k, v in all_mutational.items():\n",
        "    sigs_df = pd.read_csv(\n",
        "        f\"data/mutation/{v['name']}/ground.truth.syn.sigs.csv\", sep=\",\"\n",
        "    )\n",
        "    exposures_df = pd.read_csv(\n",
        "        f\"data/mutation/{v['name']}/ground.truth.syn.exposures.csv\", sep=\",\"\n",
        "    )\n",
        "    catalog_df = pd.read_csv(\n",
        "        f\"data/mutation/{v['name']}/ground.truth.syn.catalog.csv\", sep=\",\"\n",
        "    )\n",
        "    all_mutational[k][\"V\"] = catalog_df.iloc[:, 2:].values  # (f,n)\n",
        "    all_mutational[k][\"W\"] = sigs_df.iloc[:, 2:].values  # (f,k)\n",
        "    all_mutational[k][\"H\"] = exposures_df.iloc[:, 1:].values  # (k,n)\n",
        "\n",
        "joblib.dump(all_mutational, 'data/all_mutational.pkl.gz')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['data/all_mutational.pkl.gz']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FKIuZexC3Ycd"
      },
      "source": [
        "### Synthetic"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LqniV__wVZCd",
        "outputId": "26d4110c-cf48-4caf-cfaf-4bf63a1ca62c"
      },
      "source": [
        "synth_comp = [5, 10, 15, 20, 25]\n",
        "all_synt = {}\n",
        "for i, comp in enumerate(synth_comp):\n",
        "    W = abs(np.random.randn(96, comp))  # (f,k) normal\n",
        "    H = abs(np.random.randn(comp, 500))\n",
        "    W = W / W.sum(axis=0)\n",
        "    V = abs(W.dot(H) + 0.3 * np.random.randn(96, 500))  # (f,n) random noise\n",
        "    all_synt[i] = {\n",
        "        \"name\": f\"synthetic_normal_{comp}\",\n",
        "        \"sample\": 500,\n",
        "        \"comp\": comp,\n",
        "        \"V\": V,\n",
        "        \"W\": W,\n",
        "        \"H\": H,\n",
        "    }\n",
        "joblib.dump(all_synt, 'data/all_synt.pkl.gz')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['data/all_synt.pkl.gz']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z30Irp4ESUV0"
      },
      "source": [
        "##Fig.3"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true
        },
        "id": "7RQn0VrxSGWb"
      },
      "source": [
        "from sklearn.model_selection import KFold\n",
        "dataset = joblib.load('data/all_mutational.pkl.gz')\n",
        "n_iter = 500\n",
        "layers = 10\n",
        "fig_3 = pd.DataFrame()\n",
        "lst = {}\n",
        "\n",
        "kf = KFold(n_splits=5, random_state=1, shuffle=True)\n",
        "\n",
        "for k, v in dataset.items():\n",
        "    lst[\"super_no_reg\"] = []\n",
        "    lst[\"super_reg\"] = []\n",
        "    for train_index, test_index in kf.split(v[\"V\"].T):\n",
        "\n",
        "      data, n_components, features, samples = util.build_data(\n",
        "          v[\"V\"], v[\"W\"], v[\"H\"], index = train_index\n",
        "      )\n",
        "\n",
        "      #Supervised\n",
        "      dnmf_model_noreg, super_dnmf_train_loss_noreg, super_dnmf_test_loss_noreg = util.train_supervised(\n",
        "          data, layers, n_iter, L1=False, L2=False\n",
        "      )\n",
        "      dnmf_model_loss_learn_L1_L2, super_dnmf_train_loss_learn_L1_L2 , super_dnmf_test_loss_learn_L1_L2= util.train_supervised(\n",
        "          data, layers, n_iter, L1=True, L2=True\n",
        "      )\n",
        "\n",
        "      lst[\"super_no_reg\"].append(super_dnmf_test_loss_noreg[-1])\n",
        "      lst[\"super_reg\"].append(super_dnmf_test_loss_learn_L1_L2[-1])\n",
        "\n",
        "    fig_3[f\"super_reg_{k}\"] = lst[\"super_reg\"]\n",
        "    fig_3[f\"super_no_reg{k}\"] = lst[\"super_no_reg\"]\n",
        "fig_3.to_csv('data/outputs/fig_3.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "YCitVH0qaSor",
        "outputId": "0968f04c-2d1b-48d7-8ae7-1d2068abc48b"
      },
      "source": [
        "fig_3 = pd.read_csv('data/outputs/fig_3.csv')\n",
        "for x in range(1, 13):\n",
        "  util.plot_box(\n",
        "      [f\"super_reg_{x}\", f\"super_no_reg{x}\"],\n",
        "      [\"Regularized\", \"Not-Regularized\"],\n",
        "      f\"fig3/compare_reg_{x}\",\n",
        "      fig_3,\n",
        "      'Supervised',\n",
        "      None,\n",
        "      '$\\log({MSE})$',\n",
        "  )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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pnrs3O7e7e1vSclpL6u6bo94DAACgaAoRLN29IWk+/dzM0qCYRf0MAl5lSI3kuqQ1SQRLAABwYRSyj+U4hT6ZM0MOy1OjCgAAMBUIlvm9kFQys9UBx8xJag7YDwAAMHUK0RQ+Sdy9bWZNSetmdtnd1zr3hwE865IWx1JAAACAMbkQwTI0Xy91bLqspO9lY8RLLkvak7RqZkuSlt29GULltqSVUUebAwAAFNVFCJaLklruvtG50cz2zOxB9/Ys3L1lZlclPVLS7L1nZukoc0IlAAC4kKa9j2VLUq1PzeRtJc3ZI01oHqYWeiPcQ0pqRDMP2AmTq++a2e6zZ89GKQIAAMBEmepg6e7tfs3dYQ7KlpL+kLmFQLqlpEZ0PlxrTtK+mVUzlG3T3RfcfeHKlSujFAEAAGCiTHWwzKAlaS7vso4hOK64+7K7t9y96e6zktJm9dqQUeMAAABTh2CZyNOEPSdprXMpx1QYIT4vqa2kmZ25LAEAwIUx1cEyQ7Brh/c8AXBdA5rPQxN7ukrQUr/jAAAAps3UBsuwnvd+mA6on1J4f5Hj0hUl6433FUaFb0q6keO6AAAAhTbN0w3NKKmRbA84Jq2pHHU+y0H2h9wbAABgqkxtjaWkp5Lmh0yCXpG0E6YOyqopaSHDcYuS6jmuCwAAUGhFDpalQTvDxOdr/fabWdpP8naf/TUz2w6r6XRK57/se/8wFVHfqY4AAACmUVGDZVk6XJd7kDQcHhucE6YLqiqp0TxRWxmCYVXJ4JubnfvC4JzbSlbbOdF/M0wztKY+gRUAAGBaFaKPZQiGNSX9Jss6qq08MLOmksE3NXff6TwvrN+d1jDOdJzXlHS1XxO4uzfCdSXpYY/9O2bWkHTHzFbC5vRaD9x9caQvFAAAoMAKESzDKOuRwloIjytDDzx53vyQ/W0NaGoHAAC4aIraFA4AAIAJQ7AEAABAFARLAAAAREGwBAAAQBQESwAAAERBsAQAAEAUBEsAAABEQbAEAABAFARLAAAAREGwBAAAQBSnXtLRzF6XVJE0q6N1vNN1uVtK1tB+IWlfUtPd/+q09wQAAMDkGSlYhjD5lqSqpM9J+kBJiGyFj5+HQy8rCZiXJd2Q9Gdm9jlJDUk1d//zU5QdAAAAEyRXsAyBclPSvKQtScvu/ijnNcqS3pD0lpltSVp19x/nuQYAAAAmT+Y+lmb2XUl1JTWNl939nbyhUpLcveXuW+7+ppLm8y+a2VMz+8O81wIAAMDkyBQszeynkj509y+6+3uxbu7ubXd/R9I3JG2Z2ddiXRsAAADna2iwNLN3Ja24+/fPqhChFvNNSbNm9tWzug8AAADOzsBgaWZXJa25+wfnURh3/56kg/O4FwAAAOIaOHjnvAJl1z3fP+97AgAA4PQyjwo3s28pmY+yJanl7r89s1IBAACgcPJMN7QpycPHTTN7oWTy8wfMRwkAAIC8E6Q3JVXc/aNhB5rZ15WsyLPu7r8eoWwAAAAokLzBci1LqJQkd3/PzJqSNsJqO++6+1/kLiEAAAAKIfME6ZI87zrf7v6Bu9+U9KeS7prZczP752b22VylBAAAwMTLEyxt1JuEeSoXJO1I+p6SAUAAAACYInmCZbt7g5l9zsy+bWZ/nOUC7r4i6QNJl3LcFwAAAAWQqyn8xIakv+UjSW+Z2cdm9pcZguZ63kICAABg8uUdvHNCmND8LTNrSfqupBlJXzCzS0oG+/y665QHkn542vsCAABgspw6WHaoKQmWbwyaPN3dPzIbubsmAAAAJlSepvCBQrN4O+OKPJmmLAIAAEBx5AmWl8zsj4Yc8yLjtbIeBwAAgILIW2PZDHNR/tDMvtZjPsoTA3z6yHocAAAACiJvH0tTMlVQNbwUBu3UJTXiFg0AAABFkjdYLkoqS1qWtCCpJGk2bFuRJDP7lZKQWZfUyNjnEgAAAAWXK1i6+yMl81ZuSZKZfUlSRUngrITD0qDZWaPZkLQtaTcEzZkYhQcAAMDkyBMsN7o3hDks31eyTGOeoFkavcgAAACYRJkH77j7OxmOed/dv+fub7r7pyTNS1pTEj4tvGZHLSwAAAAmV7R5LHvpCJoLIWguSnrvLO8JAACA8Yi58s5QaR9NM/v4PO8LAACAs3emNZYDsPIOAADAlBlXsFwb030BAABwRsYSLN19axz3BQAAwNkZV40lAAAApkzmwTtm9lDJGt8/lbTNijoAAADolGcey5uS2pI2JR2Y2a/M7Idm9tUzKx0AAAAKI29T+LuSPpD0TnjtKJn0vCcz++zoRevPzEpmtpfhuLKZ1c2samblru1VM9vu3D5iWcpmVjOzvXCvupmtnuaaAAAARZSnKfyqpE13/8KQ415Xsi74XPi8Lanm7n82ejEPr11SsjTknYynlJQsLVkJ53fua0ladPfWKcpTVTLCfdndVzq2V8xs1d1PLIMJAAAwrfJMkP5dhfW++wlrhe+GTz8KH89IesfMliVV3P1v8xbSzCqS1pWEwVp4z1rTuCPpRTh+JpSp7u47ecvRVaZqKNNVd2937a6Fd4IlAAC4MPIEyzl3f3/IMetKmsb33P1G5w4zW5fUMrNy3nDp7g0l646n10qDYhZ1d9/Mc79hQvN5TUlNZXeolJIAO3JNKAAAQBHFXtKxomTk+O3uHe6+Zmb7SmoQb3TvL5h1Se1+tZ7ufumcywMAADB2eQbv9B2kI0lm9kb4sO3uP+t1TKg5/MDMvpXjvhMl9PNckvRw3GUBAACYJHmCZdPM/mjA/sXw3hhynXuSlnPcd9LcDO9DR6UDAABcJHmawjcl/Uj9m7HTZvD6oIu4+/tmtpDjvqcW+kQudWy6rKTv5bAQ3Eva17PVMUo9xnUBAAAKLXOwdPeGmS2Z2b/tnjooTEU0pyRYZglVB/mKeSqLklrdU/+EeScfjDAlUOegoTvuvtZ13bqZLXZvBwAAmHZ5B++sSdozs3klk6W/ryRQbikJlU13/3XUEp5OS8kcmr3C7m0lX0szZw3jTHhfVvL96LasZGWip6ed0ggAAKBIcq284+4fhQnSfyvpPUn7SiZDv6Rk3sqhfSfDXJfN/EXNz93b/UKjuzeVBM/1nJctdV6/1z2VfH1bgy4SVv7ZNbPdZ8+e5SwCAADA5Mm7pKMkyd2XJb2ppM/le0pq7q5mrK18R0lt5yRoSZrLuaxjGiYH9SXdlVQys7l+B7j7prsvuPvClStXctweAABgMo08j2WoCcw1SMXM7kkyd/+rUe8bWTqJeVnZJzR/0XVuL2n4XNA51c4CAACMW+wJ0o8xs+9K+pKSoFVR0ow8P/CkuPcvD1kLPA2AeWosswTQ5+F9Nsd1AQAACm2kpvCs3P0dJfM+PlTSF/MDJQNmvnaW95UkM6tJ2jezpQGHpf0lXww4pls6f+WgMHo5vD8fcAwAAMBUOdNgKR0O+HnP3d8KA3++qCGr+EQyo6RGstda3qk0HOZp0k+PHbQsZRpYmc8SAABcGGfaFN5LaJrO2p/xNJ5KWhvSFF6RtNNrdHc/7t4ys6aSaZYGXbcVRp4DAABcCJlrLM3sj8+yICMoDdoZJj7vO0m5maXTDN3us79mZtthdZ1ua5IqvUaTh5HgZRV72UoAAIDc8jSFb59ZKfIrS1Kf0NcpDYfHAqCZVZUsxTjfq7bSzCph/5KO1gY/FEbEr0mqd5Yh3OeRpBVqKwEAwEWTpyk8z8jpqEJgqynpN1nWUW3lQWiWfqFkhZ1jK924e9PMbktaN7OZjvOaSubd7NkEHpavTIPhwz7HbIRjtkK4TK/1BqESAABcRHmCpZnZP5e05e6/PasC9RL6SS6OeG5b0soI5w2dFmmUuTwBAACmVd5R4RsK62Cb2T0z++pZFAoAAADFkydYfqRkHkpTMsn5qpI+hh/nDZrnMY8lAAAAzleeYHlVSbPvcnj9SP2D5k/M7NsDRpJvnaLMAAAAmECZ+1iGvopvmdnXlayB/S/c/bdm9jkl8zYuhveypDfD5zIzKQmkdUl1d/+5pEsxvwgAAACMn7l7/pOSMHlH0n929z/vsa+iJFwu62gk9rEbufsroxR4Gi0sLPju7u64iwEAADCUme25+0KvfSMt6RiWaXxH0kdm9kMz+2zXvvfcfcXdZyTNKhmV/Z6SfprnsZwjAAAAztmp1gp390fu/qeS/szMvtXnmA/cfcvdb4ag+eZp7gkAAIDJdKpgmQq1l3uh9vL1Iccy7yMAAMAUihIsJcnd3w+1l8v9ai87fBDrvgAAAJgM0YJlyt2/J+mRmb07YLqhkVbRAQAAwOSKHiylw36Vb0m6YWbf7rX/LO4LAACA8TmTYJly9y1JW0NqLwEAADAFzjRYSofTD70ladbM7p31/QAAADAemVfeySrMabmgZAWe2fCevkpmdlvSsrs/jn1vAAAAjM9IwTI0a6dhsTs8Hju0x+ltSTclESwBAACmSOZgaWZ/qaQmstS9q+vztqRWx+tp+rG7fzR6UQEAADDJ8tRYdk4R1Bkc98N7k9HeAAAAF1fepvCmpHclNdz91/GLAwAAgKLKEyxd0pKkeUnvmNlVJc3edRE0AQAALrw8wfKjEB5/Lek9STKzz0mq6ChotnQUNH/b70Jm9sDdvzFqoQEAADB58gTLte4NYTDOezoZNDeGBM2lkUsMAACAiZQ5WIZVdIYd0yto3pT0o/BxS8nIcgAAAEyZ6BOkdwpBcyu8ZGZfkvSPz/KeAAAAGI8zX9Kxk7u/L2n5PO8JAACA83GuwVKS3L0liYnSAQAApsy5B8vg9pjuCwAAgDMylmDp7u+N474AAAA4O+OqsQQAAMCUIVgCAAAgioHB0syumtm3zqswZvZZM/v2ed0PAAAA8QwMlu7+gaQPzOyHZvb3z7IgZvaGpC13//5Z3gcAAABnY+gE6e7+yMwOJL1vZvfc/ccxC2Bmn5X0I0nPWT8cAACguDL1sXT3ppKlGG+Y2a/M7FshEI7MzP7YzB5K2pP0/7j7n57megAAABivPGuFtyW9ZWZlSauSNs1sT1JD0r6kXUltSS/c/bfpeSGAzkiak1SWdENSRcm64ZvufjPS1wIAAIAxyr1WeFg55y0lIfPrkhYlvaMkNEqSm1n3aemGhqS6pHdC/00AAABMidzBslOY6PxwsnMz+5yS2slSeH8hqU2IBAAAmH6nCpbd3P0jsQ44AADAhcQE6QAAAIgiSrAMI7xfj3EtAAAAFFOsGssNJSO9MwtTFr0ws4/N7Olppy8CAADAeMUKlnV3/1HWg8No8pqkNUlfkLQt6VGksgAAAGAMog7ekSQz+6qSqYd23f1nfQ5bl7Tj7lvh8w0zczP7qrv/VewyAQAA4OzFqrFshPXEnyuZp3JT0p6Z/Wcz+8Mex5eV1FgecvfvSVqOVB4AAACcs5g1lisKgVLJ/JUzkt5UMin6F9ODzOxLklzJSj3dmKoIAACgoGIFy3ckzfaYCH3LzCpm9m13/37YNiNJncs+dvBI5QEAAMA5i9UU/kG/1XXcvaGjJR2jMLNSWKd82HFlM6ubWTWscd65vWpm253bI5VtaLkAAACmUawayw+H7I9SE2lmJUlVSXcynlJSMg1SJZzfua8laTGsfR6Fma1Kmot1PQAAgCKJFSy/YGZ/5O4/795hZt+S1O7YVBpwnUu9NppZRclI8paSQT8tJQOAsthR0uezrKQZflfJ9Eg7Gc/PJNR8Zg28AAAAUydWsNyQ9Ddm9lNJ70t6LumykprCOYXAGCZBX5H0kZl9xd0fpxcI0xT1bEYOzenzHcemQTGLurtv5v6K8ltRMlBp6RzuBQAAMHGiBEt3b5nZgpKJzt/s2NWQtCBpxcxuKAmZdSXTCj0ys6+7+9+G5SBr6giPRWJmS5IeKAmXAAAAF1K06YbcvSlp1syuKqlNbHUM6Hm/+3gze0fSB2a2H45/s89I8YkW+n2W3X2nqw8nAADAhRJ95Z0QJnuOEO86rmFmX5D0JUkNdy/qHJZ33H1t3IUAAAAYt+jBMo8wIjvaqOx+wsCazr6Pl5X0vWyc8rpzkp6e5hoAAADT4izWCv+skimB0j6VLSWDcjbd/dex75fBopJm+Y3OjWa2Z2YPurfn9A1qKwEAABJRg6WZfVvJtEDh0WAAABknSURBVECdnQ1nlYS7NTNbdfd/F/OeQ7Qk1frUTN5Wsp55c5SayzBn5b1RC2ZmVSUBXK+99tqolwEAAJgYsVbekZl9V9Jb4TWrZIqh9DUv6fuS7prZv491z2Hcvd0vNIbBRi0lQTiX0LTedvf20IP7l23T3RfcfeHKlSujXgYAAGBiRAmWZvYlSXPu/gV333L3D9z9o47X++6+5u4zkj4f5qycBC1JcyMs67h2TnNjAgAAFEasGsuqu785/DDJ3W8qmcdyEqQDhzIHy9CEXTub4gAAABRXrGCZdwLHc5laKENNZNqUnSlYhjkrZ0MzOgAAADrEGrzzNzmP90j37cvMapKqZrY8YF3wdN3yFxkvW5FUMbN6n/0L4d576TXdfTHjtQEAAAotVrCcjXSdmGaU1EgOGmCT1lRmGhUeAmq/kKoQOCvuXsilKQEAAE4jVlN408y+leVAM7sn6Xmk+w7yVNL8kKmEKpJ2TjO6GwAAAIkowdLdtyTdNLN/a2av9zrGzP7YzH6opEbv+xFuWxq0M0x83nfycjNLpxm63Wd/zcy2Q79KAAAADBFtHkslI73flLRvZr8ys6dm9pfh/bmS1XcWJN2McK+ydDiYZpA0HB4bnNMxOfl8r9pKM6uE/Us5yzuTsVwAAABTJ9rKO+7+kaSFztDWsbsl6bvu/r1Rrh2CYU1JcCvrqLbywMyaSgbK1LoH6bh708xuS1o3s5mO85qSrvZrAnf3RriuJD0cUraKkknW5zo2H5hZS0kzO0s+AgCAC8Hcz26AtplddfcPzuwGU2JhYcF3d3fHXQwAAIChzGzP3Rd67YvZFH5Cv1CZdaAPAAAAiuNMg+UANA8DAABMmUx9LM3s6wqTf0dQUo4lFAEAAFAMWQfvlBW3lvHMV94BAADA+coaLNuS6u7+T2Lc1MyyLqEIAACAgsjax7Il6f2I92UINAAAwJTJVGPp7o8kPYp1U3d/M9a1AAAAMBnGNSocAAAAU4ZgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiKKQwdLMSma2l+G4spnVzaxqZuWu7VUz2+7cPkI51sP198Nr28zmRr0eAABAkRUqWIZAuSrpA0lZAmFJUkVSTdK+mbmZuaR9SWuS1ty9NWI5tiU9cPdFd5+VNC/phaQ9M6vlvSYAAEDRfXrcBcjCzCqS1iW1lITElrIFS0naURL4ypJmJO1Kqrv7zimKtKWuUOrubUkrZiZJVTPbc/fNU9wDAACgUAoRLN29oaRGUJJkZmlQzKIeM+CFpu6nA2o61yRVJdXM7GEInAAAAFOvUE3hE+IbSmpBewpBshk+rZxLiQAAACYAwTK/OSX9KJcGHJPWZs6cQ3kAAAAmAsEyv7aSQUE3BhxTCu+5BwYBAAAUVSH6WJ5WmFKos4bxspK+l40RLndbUm3IuQvhfXeE6wMAABTSRQiWi5Ja7r7RudHM9szsQff2YUIfyr6hMoxgL0lqMHAHAABcJNPeFN5S/9rF25LWQxCMaS28rww6KEzQvmtmu8+ePYtcBAAAgPM31cHS3dv9mqzdvakkeK7Hul8Y0FORtDxs4nV333T3BXdfuHLlSqwiAAAAjM1UB8sMWpLmTrOsY8rMSjqaOP00k68DAAAUEsEycepgKemRpM28fTYBAACmxVQHyww1kengmlMFSzOrKxmsszb0YAAAgCk1tcHSzGqS9odMZJ7ON/nilPdpEioBAMBFN7XBUsmqN20d1Ur2ktZUjjKfpcxsVVK7V6g0s1JYVxwAAOBCmOZg+VTS/JCJzCuSdkaZbzLUhM4OqKlcEEs6AgCAC6TIwbI0aGcYRNO3edrM0mmGbvfZXzOz7TDau3vfnKQb7j5orspFsfIOAAC4QIq68k5ZSpqbh9Q21sxsW8kUQIfzSppZVVJVSY3mifPDpOnV8Gld0mbHvrKSEeC7YdBOLzOS5uh3CQAALpJCBMsQ5mpKAltZR7WVB2bWVDL4ptY9f6S7N80sXWFnpuO8pqSr/UKpuzfCdSXpYdfuWrjOsBV7mkP2AwAATJVCBMtQ27g44rltDVlesc958322j1QOAACAaVfkPpYAAACYIARLAAAAREGwBAAAQBQESwAAAERBsAQAAEAUBEsAAABEQbAEAABAFARLAAAAREGwBAAAQBQESwAAAERBsAQAAEAUBEsAAABEQbAEAABAFARLAAAAREGwBAAAQBQESwAAAERBsAQAAEAUBEsAAABEQbAEAABAFARLAAAAREGwBAAAQBQES6Ag7t+/r+vXr+uVV17R9evXdf/+/XEXCQCAYz497gIAGO7+/fu6e/eufvzjH+vLX/6ynjx5olu3bkmSvvnNb465dAAAJMzdx12GC29hYcF3d3fHXQxMsOvXr+sHP/iBvvKVrxxue/z4sd5++2394he/GGPJAAAXjZntuftCz30Ey/EjWGKYV155Rb/73e/06quvHm57+fKlPvOZz+jjjz8eY8kAABfNoGBJH0ugAK5du6YnT54c2/bkyRNdu3ZtTCUCAOAkgiVQAHfv3tWtW7f0+PFjvXz5Uo8fP9atW7d09+7dcRcNAIBDDN4BCiAdoPP222/rl7/8pa5du6bvfOc7DNwBAEwU+lhOAPpYAgCAoqCPJQAAAM4cwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEpgCKysr2tjYGHjM4uKiZmdnB75WVlZGLkOj0dDi4qIuXbokM9Pi4qIajcbI1wMAFA/zWAIF1mw2tba2pkajofX19YHHvnjxQq1Wa+gxo1hbWzsMtuVyWVISNBuNhlZXV4eWDQAwHaixBApmZ2dH8/PzunTpkubn53PXCm5vb8vde762t7dzl6fRaByGynq9rv39fR0cHKher0uSNjY2tLOzk/u6AIDiIVgCBdNqtdRsNjUzM6PV1VWVSqWxlmdtbU1SElgrlcrh9kqlolqtduwYAMB0I1gCBbO6uip31/7+vtbX1w+bnseh3W6r2WyqVCppaWnpxP5qtapSqXQYhgEA041gCWBkDx8+lCQtLPRc2evYPgbyAMD0I1gCGFnaj3Jubq7vMem+p0+fnkuZAADjQ7AELphWq6WVlRXNzs7q0qVLWlxcHHlwTbvdliRdvny57zHpvvRYAMD0Yroh4IJJB9KUSiXNzMycalqgdHqiQQOI0n2jTmUEACgOaiyBC6hWq+ng4ED7+/unmhYoTy0kNZYAMP0KGSzNrGRmexmOK5tZ3cyqZlbu2l41s+3O7SOUY8nMama2ambr4ePxDdEFMlhfX1e1Wj38vFKpaHV1VZJ0+/btcRULADAFCtUUbmYlSVVJdzKeUpJUCS+ZWee+lqRFdx+8FEn/stQkyd1XOraVJO2Z2Yq7MwQWE2Vvr///xdIlIdvtthqNxrH5KAdJm7kH1Uam+8Y93yYA4OwVIliaWUXSupIwWAvvWWsGdyS9CMfPSNqVVHf3kZcCMbMlSTfd/VLndndvm9mKpG0zu+rutP2hEDrnwhy27GOnmZmZocc8f/4887EAgGIrRLAMtX/z6edmlgbFLOruvhm5SOuSel7T3RuhfHcksdwICmd/fz/zsWkt5KBz0qBKjSUATL9C9rEcJzObUxJqB03K11TSZA8UQmdT9uzsbObzbty4IUna3d3te0waLNNjAQDTi2CZX9r5bFB7YUtSiYE8mBTtdntgP8jO5u9Bq+h0S/tiNpvNntdPl3zsPBYAML0Ilvml1S6DguXz8N5/ORLgHN2+fVvLy8t996dzW87NzQ1cRafb3NzcYf/Me/fundi/uZn0GCmXy7muCwAopgsRLMP0Qqsdr/UwIGgUWTqKpVU3jFZAVM/+7pn+5Cd/og//54e5zksnQp+fnz+2Zne73dbKysrhtq2trRPntttt7ezs9J3jslarSTo5D2aj0TgMrHknXgcAFJO5+7jLkJuZ1SUtdI/K7nHcnJJBNLXu6X/CPJgP3H0j5733JM25uw04pqpk9PpalusvLCz4oD5qKK6ZmRkdHBxEu94/+L//gf5e+e/pv9X+m37/338f7bpmpp/+9Kc9m6sbjYYWFxclSQcHBz0H4aytrWljI/lR756CaJQVfQAAk8vM9ty9Z7+paa+xbKlHqAxuSxql5jLP0Na+CyiHCdp3zWz32bNnOYuAojg4OJC7R3n95v//jf7hm/9QLz98mSlU9rpGvV7X0tLSYfgrlUqqVqty91P1gVxfX1e9XlelUjkMlJVKRfV6nVAJABfIVNdYZrjOvqS2u88PPfj4OeWMNZYb7j50yiFqLKeXmSnW79i/+X//jf7iV3+hl5+81KufelVf++LX9C//r38Z5doxywkAmG4XucZymJakuZyjt9vS4So7wzwffggw3LO/e6b/+Df/US8/eSlJevnJS/2Hv/kPuftaAgBwlgiWibOaFoiVdxDFu3/9rj7xT45t+8Q/0bs/f3dMJQIA4KSpDpYZaiLT4JcnWKZhdNCI77Q280WO6wJ9/fw3Pz+srUy9/OSlfvabn42pRAAAnFSIJR1HYWY1SVUzWx6wLvgoAfCppCUlYbTfXJbp0iXNHNcF+tr5ZyMvbQ8AwLmZ5hrLGSU1koOao9Oayl6jxvtJjx3Ux7KsZFDQoEnUAQAApso0B8unkub7TDWUqkjacffMfSHdvakkrC4Oue5m1msCAABMgyIHy4GjssPE5H2n+jGzdHK9233218xsu8/o79uSbvbaZ2ZLSoLnyfXtAAAAplhRg2VZyjTlTxoOjw3OCfNMVpXUaJ6orQyTpleV9KW82b0/9Nl8KGmr67ySpHVJy3lqQQEAAKZBIQbvhGBYU9Jvsqyj2soDM2sqGXxT6x6k4+5NM0tX2JnpOK8p6Wq/8OfujXBdKQmQvY5ZMbOlMEgovU5J0iJ9KwEAwEVUyJV3pg0r70yvoqxoU5RyAgDGb9DKO4WosQSKzKzv6p8T49KlU62OCgCAJIIlcKbOohaQ2kUAwKQq6uAdAAAATBiCJQAAAKIgWAIAACAKgiUAAACiIFgCAAAgCkaFAxMg75REWY9n9DgA4DwRLIEJQAAEAEwDmsIBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRmLuPuwwXnpk9k/S34y4HCuPzkj4cdyEATB2eLcjqD939Sq8dBEugYMxs190Xxl0OANOFZwtioCkcAAAAURAsAQAAEAXBEiiezXEXAMBU4tmCU6OPJQAAAKKgxhIAAABRECwBAAAQBcEShWBmS2bmA177ZrZtZtVxl/U0zGwvfD3n+nWY2Wp4Vc7zvll0/BuXx10WnI8ev+/rQ44vT/rPCc+wc7k3z7EJ8OlxFwAYQUNSu+PzkqSypCVJS2a2JmnF3RvjKFxB3VHyfdxQ8v0FJsmqmd1z9/bwQwuBZ9jZ4Dk2AQiWKKLlXn9gzKwkaV1SVVLdzBZ5MAOF11ISuu5IWhtzWWLhGYapRbDE1AgP6hUza0talVSXZOMtVTG4+6VxlwHoY11STcnv9LkGyxD0qpLk7htnfT+eYafDc2wy0McSU8fdD//4TGJfGwDZufumQrOxma2e8+1nlATbgX08Y+MZhiIjWGJapc1Mc2MtBYAY7oX3O2MtxfniGYZCIlhi6oRRd6XwaWucZQFweqEZui2pVPRR01nwDEORESwxjbbDe9vdd3odEKakqIfpHw7MrBb6U/U6thT274fj98LUIZUwPch+uMZSxznplBs9m+46pp7IVRsR7lsP90unKOnbTNdRjqUe55d7HFftOn/fBk+R0vfryPk9Lnccm067stTrWFxY6XKDIzdLm1m142c9/V0+EVTDz65L2u/YdmxqoFHLkBHPsOPn8BwrEAbvoPDCL3lZ0oKSPzrpL/18n2Mf6ah5qR2Or0q6aWbz7t7qOL4saS8c05bUDOemD/6GkhqFtpL+WGfGzPY6yt0KrzklU7FUJV0dMB3LjJltK5nOJI+mjk+L0unwe+juzY5y5v0ez4Xj03+3mXDukpkdXhcX3j0lA1pKZlYNfS8zCT+T25LS/oqdzcw1M1vW8ZHaLSW/2+nPonR8+pqotYg8wzI9wySeY8Xg7rx4TfxLyYPEM772Jc31uc5eOGZPUrljey3d3uf49Y5t5Y57VYbcZ7XP/vT8uT7nVXucs63wh7VjW6njnO0B5Tjo+LpPlHnQffuUv5rha8j6PU7Ltt9Ztq6vzTuvxWu6X52/713b05+h/a7t5UE/J0pGV/f6mSx3/IzVe5xX7lWO035NPMOyP8O6rslzrACvsReAF68sr66H8n74RU1fBxrykAzXSB8iB50Pto79+50PmPBA6PlHRUmtgkuq9blX9IfygK+rMqCcnQ+0ng/tvPft+qO02rUv7/e488HeKxCUBu3nNZ0v9Q+WnT8PSx3b+wbLjmsdDLhf+gypdm0/q2DJM+z4OX2fYV3X5DlWgBd9LFFE8+5++FKP5qI+VsJ7vxU8auE9bS5bCO+9mr3SPlaTsDzXbvrBgP5ObUm3I92vHt4bfnJuv7zf4+XwvukdzUpAL+FnKm9fy3Qk+aA5MNcyHBMTz7DjsjzDJJ5jhUCwROGFX+T0wVAbcGj6AF3v1XFbR3+oZsP7i67zOqXHTMJDJEu/qEafB2QuZlZT8v1o6+hh2inv9zg9fu+0ZcOFkf4MlS3bHI9pUNkdcEy6r9xvYMZZ4hmWuW8nz7ECYPAOpoK7r4XO32UzW+3+H2j4Y5H+wdjR0QO3l71wzaYlK2AcGyxgHatxaPAfgejC/+a/oaRZLU9Nw9MI917S0dd9Ykm6Ub7HOvoaJuGPGwrA3VtmtqPkd2BdA2r7OkcMa/DPWOe+GfUf6NF9/VVJi312N71jovNheIZlwnOsAAiWmCZrSh6S62a22fnAcPd2+oCVtJajuWJTSWfzmpmtKHlwpCMSN7xjFOFZC//LTh+IDSUPvedK/gie6R+H8LDdCp9ueI/1i0f8HqfrQE9CcxyKY03J7+FcCCr9gmBnKFjQ8ZHd6trX65xhFnXUHNptlBHWPMPO9v48x84BTeGYGuF/4+lDcqvHIWlzV54l0qpKHn6bSh40FSUPxMU8tRGdumpRsp6zHsrSlHTJ3Rfdfc3dNzzHtCunkE6jMawWJu/3OH1oZ+1jBqRNx2ko6NvXMgSzLCvYdE45k7mpNfweWp9X7p9pnmFnjufYOSBYYtqkHbuXenQCT/9HvD6oH1W6z45Wv6i7+4q7z7p7+kDsV/ORxShLtKUPuAd9mm7OTPiDkJa5V3+kTrm+xzqaS6/a5/iFHtsA6WigTUWDf6cOl4Ps9TMWtt3pOvaEc+x7yTPsDPAcOz8ES0yV0KyTrlSx1bVvR8n/1EuS9rof2pas5rAv6WbYlDaJrZjZnCWrVxy+hhQlPfdY/6twz141EcOk/yNeseMrTaQTP5+JMDgiXXljeVizUN7vcaipSP/IHDs+fHxmXxuKLfyup7V7g2otN8JxJ34mw8fp5OHNHqODO5vFb4ZzSqFJ90zwDIuP59g5G/d8R7x4ZXnp+BxwJ+YV6zq2c86w7nnp0odYuv9AR3OS9Zofb69rn3edu60eExkreYh1zllX77hP5/0zzQGn5H/a3nXN/Y5yDLtez7noBt03fK8Oetyz12vuFN/j7q/toOO+ndeZ+vnfeB3+TPScx7LHcZWun51B8wjWexybvur9nitdz4C+v2t5vqZ+9+oqL8+wk9fkOVaAFzWWmDqeNLOkNQ/HmjLcve3uy0qaQtJajJnw8YaSvj870rFmpH5KSv5Y7FnXerCe1Hyk/4sth3s0lMxfN6wZptfX1FRSc5DW0KQjV9fc/VLe62XU/fWXB7wOByrk+R6H45tK+ibt6Oh//btKvt5Yc9ZhCnnSnDt08En4mVxUMj9hQ8nPWTt8vOJJ03C/vpW3O+7xQsnP6aKf4aAXnmFR8Rw7ZxaSNoAudrSu7aaSh1+7Y1/6IEr77bTP+OEIALnwDMM4ECyBHkINwYEkubsNOTb9JZp1Vl0AMAF4hmFcaAoHhsg4KlDKN/8dAJwLnmE4TwRLoIfQZJROx/Go17xtYduj8GmUpcYAIAaeYRgXmsKBAcysrqP511o66ng+p6NVFhphYAAATBSeYThvBEtgiDAP2R0lD+F0+bhWeN07y9GhAHBaPMNwngiWAAAAiII+lgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCj+N676oCvAMC30AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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dl1Rx9xfzaIy7f1dSax51AQAAIK6hk3fmFSh76vxg3nUCAABgemPPCjezbypZj7Ipqenu/zGzVgEAACB3siw3dCrJw58bZnajZPHzd1mPEgAAAFkXSG9IKrn7R6NONLOvK9mRp+ruv5ygbQAAAMiRrMGyMk6olCR3f9/MGpKOw247T939/2VuIQAAAHJh7AXSJXnWfb7d/YW7P5T0LUl/Z2YfmtnfmNlnMrUSAAAASy9LsLRJKwnrVO5Kqkn6rpIJQAAAAFghWYJlu/cNM/usmX3bzL40TgHufijphaSNDPUCAAAgBzINhd95I3ne8pmkt83sj2b2T2MEzWrWRgIAAGD5ZZ28c0dY0PxtM2tK+o6kTUlvmNmGksk+v+y55F1J35u2XgAAACyXqYNllxMlwfKrwxZPd/ePzCZ+XBMAAABLKstQ+FBhWLw95o48Yy1ZBAAAgPzIEiw3zOyLI865GbOscc8DAABATmTtsWyEtSi/Z2Z/3Wc9yjsTfAYY9zwAAADkRNZnLE3JUkEH4aUwaedCUj1u0wAAAJAnWYPlnqSipH1Ju5IKkrbCe4eSZGb/qiRkXkiqj/nMJQAAAHIuU7B092dK1q08kyQz+7KkkpLAWQqnpUGzu0ezLulc0mUImpsxGg8AAIDlkSVYHve+Edaw/EDJNo1ZgmZh8iYDAABgGY09ecfd3xnjnA/c/bvu/qa7f0rSjqSKkvBp4bU1aWMBAACwvKKtY9lPV9DcDUFzT9L7s6wTAAAAixFz552R0mc0zeyP86wXAAAAszfTHssh2HkHAABgxSwqWFYWVC8AAABmZCHB0t3PFlEvAAAAZmdRPZYAAABYMWNP3jGz95Ts8f0jSefsqAMAAIBuWdaxfCipLelUUsvM/tXMvmdmX5lZ6wAAAJAbWZcbeirpq5JOJDWVBE0bdLKZfYaeTQAAgPWQZSj8vqRTd39jxHmvK9kXfDv8vS3pxN3/dvJmAgAAYNllmbzzHYX9vgcJe4VfKwmVH0l6JumFpHfC0PkXJm0oAAAAlluWofBtd/9gxDlVJUPjV+7+oPuAmVUlNc2s6O6/ythOAAAALLnYWzqWlMwcf9R7wN0rZnYtqSbpQe9xAAAA5FuWofCBk3Qkycy+Gv7Ydvef9jvH3U8lvTCzb2aoFwAAADmQJVg2zOyLQ47vhY/1EeU8kbSfoV4AAADkQJZgeSrp+0OOp8PgF8MKCc9p7maoFwAAADmQZYH0uqQrM/vfvcfCUkTb4a+jeiwlqTVuvQAAAMiHrJN3KkrC5Y6SxdI/UBIoz5T0Vjbc/ZdRWwgAAIBcyBQs3f0jSW+Y2bmk95WESSmZ2NPWGM9OhrUuGxnbCQAAgCU30XJD7r5vZiUlQXJD0nMlu/J8NMbl7yjp7QQAAMAKmXgdy/DM5TjPU3aY2RNJ5u4/nrReAAAALKfYC6TfYmbfkfRlJcPkJUkFSTuzrBMAAACLMdNg6e7vmNlnlYTKVvh4ZWb77v6DWdYNAACA+ZppsJQ6E37eDy+ZWVFJLyYAAABWyMyDZS93b0pqzrteAAAAzNbYC6Sb2Zdm2RAAAADkW5YtHc9n1goAAADkXpZgWZxZKzIys4KZXU1ZxlTXx24PAABA3mUJlmZmf2Nmn5lZa0Y3oGBmR5JeaIqgG8rYHnninNoDAACwCrIES0k6ltQys+dm9sTMvjKLRvUys1LoETxTsh3kxJN/wqz0x8vSHgAAgFWRZVb4R5I+VNIzt6Okx+/IzKQkXNUlXYyzq46Z/XWWdSzDLj+dhdXN7EaT9xAeKmlrecLrY7cHAABgJWTpsbyvJJDth9f3lQwBm5KQdSTpwsz+aGY/NLNvD5lJfjZFmydmZmVJ70q6WUT9AAAAq2zsYOnubXd/O/x1V9L/cvc3JG0oCZpnehU035RUVbLLzh/N7J9C0PxiuH4j2mcwJjMrSCq6e2PedQMAAKyDzAuku/v7ZlaX9Ldm9i9hSLt7Z510C8c3lQTOgqS98F41DJ17nOZn8tjdKwuoFwAAYC1knbwjKdmm0d3fkfSRmX2ve6Z4OPa+ux+6+6akLSXPNb6v5DlNi9HwLMxsW9LzedcLAACwTiYKlil3f+bu31LSe/nNAee8cPczd38Yguab09Q5obfcvbaAegEAANbGVMEyFXovr0Lv5esjzq3HqHNcYZ3JJ/OscxxmdmBml2Z2+fLly0U3BwAAYGpRgqUkufsHofdyf1DvZZcXseodJqxZ2Xb39jzqy8LdT91919137927t+jmAAAATC1asEy5+3clPTOzp0OWG9qLXe8AFXc/nVNdAAAAay16sJQ6z1W+LemBmX273/FZ1NvNzA4kncy6HgAAACRmEixT7n4m6WxE72V0Yc3KLdasBAAAmJ/M61hm5e4fSXrbzL5uZm+5+1T7dI+pJKlkZhcDju9KUtjv+ya0c17D8wAAACsperAMa1ruKtk7eyt8TF8FM3skad/d/zl23amwtNDA5YVC4Cy5+86gcwAAAJDNRMEyDGunYbE3PN46tc/lbUkPJc0sWAIAAGD+xg6WZvZPSnoiC72Hev7eltTsej1P/xyGxWPpbUdUZnYiaVPSozGXK5ppewAAAJZdlh7L7mcQu4PjdfjYmMds76AoJZN0JlyjcnPY9WZWknQQ/nohadSSRdO2BwAAIPeyDoU3JD2VVHf3X8ZvTn9hofO0B7GoV72DLTNrKJmAczJs28YQFquStrvebplZU1LN3Svpm+5eD+VK0nuzaA8AAMCqMXcf70SzPyp5nnJHSe/lfSXD3heac9BcNbu7u355ebnoZgAAAIxkZlfuvtvvWJYey49CePylpPdDwZ9VsrTPO2Z2X8mQeBo0/2NIg95197cy1A0AAIAllyVYVnrfCJNx3tfdoHk8ImiWJ24xAAAAltLYwTLsojPqnH5B86Gk74c/NxUWJwcAAMBqmenOOyFonoWXzOzLkv7rLOsEAADAYsx0r/Be7v6BpP151gkAAID5mGuwlCR3b0qKuVA6AAAAlsDcg2XwaEH1AgAAYEYWEizd/f1F1AsAAIDZWVSPJQAAAFYMwRIAAABRDA2WZnbfzL45r8aY2WfM7Nvzqg8AAADxDA2W7v5C0gsz+56Z/ZdZNsTMvirpzN3/fpb1AAAAYDZGLpDu7s/MrCXpAzN74u7/ELMBZvYZSd+X9CH7hwMAAOTXWM9YuntDyVaMD8zsX83smyEQTszMvmRm70m6kvR/3f1b05QHAACAxcqyV3hb0ttmVpR0JOnUzK4k1SVdS7qU1JZ04+7/kV4XAuimpG1JRUkPJJWU7Bt+6u4PI30uAAAAWKDMe4WHnXPeVhIyvy5pT9I7SkKjJLmZ9V6WvlGXdCHpnfD8JgAAAFZE5mDZLSx03lns3Mw+q6R3shA+3khqEyIBAABW31TBspe7fyT2AQcAAFhLLJAOAACAKKIEyzDD+/UYZQEAACCfYvVYHiuZ6T22sGTRjZn90cyeT7t8EQAAABYrVrC8cPfvj3tymE1+Iqki6Q1J55KeRWoLAAAAFiDq5B1JMrOvKFl66NLdfzrgtKqkmrufhb8fm5mb2Vfc/cex2wQAAIDZi9VjWQ/7iX+oZJ3KU0lXZvYvZvaFPucXlfRYdrj7dyXtR2oPAAAA5ixmj+WhQqBUsn7lpqQ3lSyK/pfpSWb2ZUmuZKeeXixVBAAAkFOxguU7krb6LIR+ZmYlM/u2u/99eG9Tkrq3fezikdoDAACAOYs1FP5i0O467l7Xqy0dAQAAsKJiBcvfjDhOTyQAAMCKixUs3zCzL/Y7YGbflNTueqswpJyNSO0BAADAnMV6xvJY0r+Z2Y8kfSDpQ0mfU7Jo+rZCYAyLoB9K+sjM/pu7/3NaQFim6CpSewAAADBnUYKluzfNbFfJQudvdh2qS9qVdGhmD5SEzAslywo9M7Ovu/uvwnaQJ5J2YrQHAAAA8xdtuSF3b0jaMrP7StapbHZN6Pmg93wze0fSCzO7Due/OWCmOAAAAHIg+s47IUz2nSHec17dzN6Q9GVJdXdnDUsAAIAcix4ss3D3pqTmItsAAACAOGaxV/hnJB1ISp+pbCqZlHPq7r+MXR8AAACWQ9RgaWbfllTV7QXRtyTtSaqY2ZG7/5+YdQIAAGA5RAuWZvYdSWVJbyuZDX7Tdbgo6X9I+jsz23L3/xmrXgAAACyHKMHSzL4sadvd3xhwygfhVTGz98zsK+7+4xh1AwAAYDnE2nnnwN3fHH2a5O4PlaxjCQAAgBUSK1ja6FNuYWkhAACAFRMrWP5bxvM9Ur0AAABYErGC5VakcgAAAJBTsYJlw8y+Oc6JZvZE0oeR6gUAAMCSiDIr3N3PzOxHZlbUgIXQzexLkg4l7br7gxj1AgAAYHnEXCB9X9IzJUsKNSW1laxlualkHcuCpIakhxHrBAAAwJKINRQud//I3XclfUvJrO8dJTvu7EhqSXrH3R+4+4tYdQIAAGB5RN8r3N1PJZ1KkpndJ0gCAACsh2g9lv0MCpXjTvQBAABAfsw0WA5RWVC9AAAAmJGxhsLN7OuSdiPVWVAymQcAAAArZNxnLIuK28vIzjsAAAArZtxg2ZZ04e7/PUalZnYToxwAAAAsj3GfsWxK+iBivZcRywIAAMASGKvH0t2fKVn8PAp3fzNWWQAAAFgOi5oVDgAAgBVDsAQAAEAUBEsAAABEQbAEAABAFARLAAAAREGwBAAAQBQESwAAAEQx7s47S8XMCpKeufvOFGVcTXN9KKMsaU/StaTPKdkHveruzWnKBQAAyKNcBcsQKA8kPZ6ynCNJ21OWcSJJ7n7Y074rMzt09/o05QMAAORNLobCzaxkZleSziQ1lGwxOWlZRU0fTMuSHnaHSkly97akQ0nnIWQCAACsjVwES3evu/uOu++HnsCbKYo7lDRtb2JV0mm/A13tmyq8AgAA5E0ugmUsoafxXU0RTM1sW1JR0vMhpzWUDNkDAACsjbUJlmFouujujSmLKoWPw4bjm5IKYdgdAABgLaxNsJT02N2PI5TzIHwcFiw/DB+nmiAEAACQJ2sRLMPw9bCh6yzGmZTTDh83I9UJAACw9NYiWEp6y91rkcralDozwEcZGELN7MDMLs3s8uXLl5GaBgAAsDgrHyzDmpVPIhaZZRmhzw064O6n7r7r7rv37t2L0CwAAIDFWulgGSbPtMfsXQQAAMAUVjpYSqq4e9/1JqfQljqzzEf5cPQpAAAAq2Flg6WZHUg6WXAz6CkFAABrYyWDZehN3IqwZmU/6TJDw2Z8p72Z0+wQBAAAkCuvLboBM1KSVDKziwHHdyUp7D9+I0nuvjdm2c8llZXsvjNoLcut8HEWwRYAAGAprWSwDEsLDVxeKATOkrvvTFB8us/4sGcs00lDwxZRBwAAWCkrORQ+S2F4vS1pWA9nSVLsSUMAAABLLc/BMst6kpmZ2YmZnQ+Y/f1I0sN+x8ysrCR4xlw7EwAAYOnlNVgWpbGX/Olnc9j1ZlaSdKDkWcqHvcfDUPt7ks56ritIqkraZ+1MAACwbnLxjGVY6PxESSAs6lVvZcvMGkom4JwM27YxhMWqpO2ut1tm1pRUc/dK+qa710O5UhIg73D3QzMrm9mJXi0rVJC0x7OVAABgHZm7L7oNa293d9cvLy8X3QwAAICRzOzK3Xf7HcvrUDgAAACWDMESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRvLboBgCQzGwm5br7TMoFAKAfgiWwBLIEQDMjMAIAlhJD4QAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKF5bdAOAVba5ualWqxW9XDOLWt7GxoZubm6ilgkAWD8ES2CGWq2W3H3RzRgpdlAFAKwnhsBRUeoAABHXSURBVMIBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLIEVcHh4qOPj47HOPT091c7OjjY2NrSxsaG9vb0obajX69rb27tVbr1ej1I2ACAfCJZAjjUaDe3t7en09HTkuc1mU1tbWzo8PFSj0dDm5qYkdcLf/v7+xO2oVCq3guTm5mYnaI4beAEA+UewBHKmVqt1ehx3dnbG6hVst9va2dlRs9nU0dGRWq2Wrq+v1Wq1dHFx0Sl3khB4enraue7i4qJTdlpupVJRo9HIXC4AIH8IlkDONJvNTo/j0dGRCoXCWNe0222dn5+rWq3euqZUKnX+fHJykqkt7XZbh4eHkqTz8/NbZZVKJR0dHUlKwiUAYPURLIGcOTo6krvr+vpa1WpVxWJx5DXb29s6Pz9XuVweel6z2czUlnQIvlAo9C378ePHkpLh9qxlAwDyh2AJrIlRoVLSWL2f3Z4/fy5Jevjw4cDy0uDLRB4AWH0ESwAdBwcHmc5PeyGHBdI0WF5dXU3eMABALhAsgTXWbDa1s7MjKQmA6dB1TGnoZCgcAFYfwRJYM+kSRVtbW9ra2urM2L64uMg8FJ72Rrbb7YHnpIHy5uZmwhYDAPKCYAmsmZubm76TadJ1LbNIg+V777038Jw0uA4LnwCA1UCwBNZMqVRSq9XqrGGZPld5//79zMPV6VJD7XZbtVrtzvHuZYay9oYCAPKHYAmsoUKhoEKhoFKp1Fm7Ml1EPYtisdiZbb6/v98Jl81mU5VKRcfHx51AOUmPKAAgX3IZLM2sYGZjTzE1syMzOw+vi/Aqjb5yZLnlrnLT1+hFBYEl1W63M+++c3Z21hkS39/fl5lpa2tLx8fHOj8/1+7uriSNtd4mACDfchUsQ6A8kvRC0sjfUuH8c0l1d98Prz1JVUkX4dikbTmXdNhV7r6kJ5KuYoRWYN62t7clqbMV47gKhYKurq50cHCg7e1tlUolVatVtVotlctlXV5eSpL29vaitxkAsFxeW3QDxhGCWlVSU9JJ+DhO98dZCHy3uHvdzI4lHZnZgbufZmxPVVLJ3Td6ym2YWUXSuZndd3dmKyA30qHqSWZvFwqFvttBpltJSre3jgQArKZc9Fi6e93dd0LPYF3SyN98ZlaQVDazQd0v6ft3gueIcrclHUnqG0ZDSC1IyrbSNDBD4+x6k/YspkPXMaSTd8rlMpN3AGAN5CJYTiidKTDot2QaTrM++HUYPg4bL2x0nQdE8/J3L/WNH35Dv/nP32S6rlqtdmZwD5L2LO7vZ/q/1kD1er0zmadarUYpEwCw3FY2WLp7U9KWpPsDTkkDZSNj0WlQHdZr2pRUDL2mQDRPf/5UjX9v6OnPnma67vDwUKenp9ra2rqzLFB3b2a5XL4zZJ0uJdRvOaH0+u5lhSSpVqt1nqk8OTlh4g4ArAlz90W3IbMwvL3b+4xjxjJOlAxX74Xh9XGvu1YSSrdCeJ267N3dXU+HIbFazEyxfsZe/u6lvvaDr6l93davz3+t7T/f1qc/9elOMCwWi7cCXO8knFqtdqs3slgs3lq3slQq6fz8/M6Qdb1e74TEVqt15/je3l6nDemxtPezWq3q6Ohoqs8bALBczOzK3fuOCOdi8k5soSfxQNJpllAZNJQEy3F6I+mmQTRPf/5Un/gn+sPLP+i3v/itfvKLn9w63mw2hy5wXi6X1Wq19OTJE9VqNTWbzc5alrVaLfNs8NTFxYUqlYrq9boajYYKhYLK5bIeP37cmWkOAFgPa9djGULlMyVLEFVGnd/n+qqSyTsDeyND+0qSKu4+clFAeixXV6wey7S38vd//H3nvT/9kz/VD7/+Q33+zz4/dfkxe1YBAKttWI/lyj5j2c3Mts2sGgLfC0lPJgmVQbqmyrBF+dIv9ueGtOnAzC7N7PLly5cTNgXrIu2t7PaJf5L5WUsAAGZpLYKluzfcveLue6GXc9PMridZyDw8V3ksqdzvuJkdSHov/PXDIeWcuvuuu+/eu3cvazOwZn7265/p408+vvXex598rJ/++qcLahEAAHet5TOW7n5qZlKy+85h1gXS3b1iZjKz8+4F2M2srGRG+FZ4iwXSEUXtr/rPyAYAYJmsZbCUOuGyKunEzOqDZngPub4ShtjTKa9tJc9tNs0sDZuZygQAAMiztQ2WwaWSSTZlJcPbmbh7Q/3XwUxngzMjBwAArI2VfcbSzM7NrBW2YBwk7VF8ELn6XUkN9goHAADrZGWDpZJeyIIGb+kovepZfB6r0hBkC3o1exwAAGAtrHKwrEsaNTFnt+vcsZhZ0czczM4HnHIoqZl1QhAAAEDe5TlYjtr5pqpXs7PvCDO4C5Jq4VnJ3uMnYTh9UD13JuaE3soDSft3TwcAAFhteQ2WRamzi05fYVec5yEc3tpaMaxfeaZkFvedEBiOHygZTn/YU25TUk09Q90hqJ4r2ZGn34QeAACAlZaLWeEhGJ5I2tTtfbpbZtaQdCPpxN1vLfbn7jUzq0t63BUu02sf9Z7fdV09lCu9Wuy826NQZjoxqKhkOH2HCTsAAGBd5SJYhl7CYVsoDru2LSnz9o3uvhO7TAAAgFWW16FwAAAALBmCJQAAAKIgWAIAACAKgiUAAACiIFgCAAAgCoIlAAAAoiBYAgAAIIpcrGMJ5JmZLboJI21sbCy6CQCAFUCwBGbI3aOXaWYzKRcAgGkxFA4AAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIjitUU3AIBkZjM5390naQ4AABMhWAJLgAAIAFgFDIUDAAAgCoIlAAAAoiBYAgAAIAqCJQAAAKIgWAIAACAKgiUAAACiIFgCAAAgCoIlAAAAoiBYAgAAIAqCJQAAAKIgWAIAACAKgiUAAACiIFgCAAAgCoIlAAAAoiBYAgAAIAqCJQAAAKIgWAIAACAKgiUAAACiMHdfdBvWnpm9lPSrRbcDufF5Sb9ZdCMArBzuLRjXF9z9Xr8DBEsgZ8zs0t13F90OAKuFewtiYCgcAAAAURAsAQAAEAXBEsif00U3AMBK4t6CqfGMJQAAAKKgxxIAAABRECwBAAAQBcESAAAAURAskQtmVjYzH/K6NrNzMztYdFunYWZX4fOZ6+dhZkfhVZpnvePo+jcuLrotmI8+P+/VEecXl/37hHvYXOrmPrYEXlt0A4AJ1CW1u/5ekFSUVJZUNrOKpEN3ry+icTn1WMnX8VjJ1xdYJkdm9sTd26NPzQXuYbPBfWwJECyRR/v9fsGYWUFSVdKBpAsz2+PGDOReU0noeiypsuC2xMI9DCuLYImVEW7Uh2bWlnQk6UKSLbZV+eDuG4tuAzBAVdKJkp/puQbLEPQOJMndj2ddH/ew6XAfWw48Y4mV4+6dXz7L+KwNgPG5+6nCsLGZHc25+k0lwXboM56xcQ9DnhEssarSYabthbYCQAxPwsfHC23FfHEPQy4RLLFywqy7Qvhrc5FtATC9MAzdllTI+6zpcXAPQ54RLLGKzsPHtrvX+p0QlqS4CMs/tMzsJDxP1e/cQjh+Hc6/CkuHlMLyINehjHLXNemSG32H7rqWnsjUGxHqvQj1pUuUDBym62pHuc/1xT7nHfRcf23Dl0gZ+Hlk/BoXu85Nl10p9zsXayvdx3riYWkzO+j6Xk9/lu8E1fC965Kuu967tTTQpG0YE/ew29dwH8sRJu8g98IPeVHSrpJfOukP/c6Ac5/p1fBSO5x/IOmhme24e7Pr/KKkq3BOW1IjXJve+OtKehTaSp7Hmhkzu+pqdzO8tpUsxXIg6f6Q5Vg2zexcyXImWTR0e1mUbp2vobs3utqZ9Wu8Hc5P/902w7VlM+uUi7X3RMmEloKZHYRnL8cSvifPJaXPK3YPM5+Y2b5uz9RuKvnZTr8XpdvL10TtReQeNtY9TOI+lg/uzovX0r+U3Eh8zNe1pO0B5VyFc64kFbveP0nfH3B+teu9YlddpRH1HA04nl6/PeC6gz7XnCv8Yu16r9B1zfmQdrS6Pu87bR5W74D2H4zxOYz7NU7bdt3dtp7PzbvL4rXar+6f95730++h6573i8O+T5TMru73PVns+h676HNdsV87pv2cuIeNfw/rKZP7WA5eC28AL17jvHpuytfhBzV9tTTiJhnKSG8ire4bW9fx6+4bTLgh9P2loqRXwSWdDKgr+k15yOdVGtLO7hta35t21np7fikd9RzL+jXuvrH3CwSFYcd5reZLg4Nl9/dDuev9gcGyq6zWkPrSe8hBz/uzCpbcw25fM/Ae1lMm97EcvHjGEnm04+6dl/oMFw1wGD4O2sHjJHxMh8t2w8d+w17pM1bLsD3XZfqHIc87tSU9ilTfRfhY97tr+2X9Gu+Hj6feNawE9BO+p7I+a5nOJB+2BmZljHNi4h522zj3MIn7WC4QLJF74Qc5vTGcDDk1vYFW+z24rVe/qLbCx5ue67ql5yzDTWSc56LqA26QmZjZiZKvR1uvbqbdsn6N0/Ovpm0b1kb6PVS08dZ4TIPK5ZBz0mPFQRMzZol72NjPdnIfywEm72AluHslPPxdNLOj3v+Bhl8W6S+Mml7dcPu5CmU2LNkB49ZkAevajUPDfwlEF/43/5aSYbUsPQ3PI9Rd1qvP+86WdJN8jfXqc1iGX27IAXdvmllNyc9AVUN6+7pnDGv491j3sU0NnujRW/6RpL0BhxvetdD5KNzDxsJ9LAcIllglFSU3yaqZnXbfMNy9nd5gJVUyDFecKnnY/MTMDpXcONIZicfeNYtw1sL/stMbYl3JTe9DJb8EZ/rLIdxsz8Jfj73P/sUTfo3TfaCXYTgO+VFR8nO4HYLKoCDYHQp2dXtmt3qO9btmlD29Gg7tNckMa+5hs62f+9gcMBSOlRH+N57eJM/6nJIOd2XZIu1Ayc3vVMmNpqTkhriXpTeiW08vyrjXVENbGpI23H3P3SvufuwZll2ZQrqMxqhemKxf4/SmPe4zZkA6dJyGgoHPWoZgNs4ONt1Lzow91Bp+Dm3AK/P3NPewmeM+NgcES6ya9MHucp+HwNP/EVeHPUeVHrNXu19cuPuhu2+5e3pDHNTzMY5JtmhLb3DvDhi6mZnwCyFtc7/nkbpl+hrr1Vp6BwPO3+3zHiC9mmhT0vCfqc52kP2+x8J7j3vOvWOOz15yD5sB7mPzQ7DESgnDOulOFWc9x2pK/qdekHTVe9O2ZDeHa0kPw1vpkNihmW1bsntF5zWiKem1t56/CnX264kYJf0f8aHd3mkiXfh5JsLkiHTnjf1Rw0JZv8ahpyL9JXPr/PDnmX1uyLfws5727g3rtTwO5935ngx/ThcPb/SZHdw9LP4wXFMIQ7ozwT0sPu5jc7bo9Y548RrnpdtrwN1ZV6zn3O41w3rXpUtvYunxll6tSdZvfbyrnmPec+25+ixkrOQm1r1m3UVXPd31j7UGnJL/aXtPmddd7RhVXt+16IbVG75WrT519nttT/E17v3cWl31dpez8uu/8ep8T/Rdx7LPeaWe751h6whe9Dk3fV0Muq/03AMG/qxl+ZwG1dXTXu5hd8vkPpaDFz2WWDmeDLOkPQ+3hjLcve3u+0qGQtJejM3w52Mlz/7UpFvDSIMUlPyyuLKe/WA96flI/xdbDHXUlaxfN2oYpt/n1FDSc5D20KQzVyvuvpG1vDH1fv7FIa/ORIUsX+NwfkPJs0k1vfpf/6WSzzfWmnVYQZ4M546cfBK+J/eUrE9YV/J91g5/PvRkaHjQs5WPuuq4UfJ9uucznPTCPSwq7mNzZiFpA+hhr/a1PVVy82t3HUtvROlzO+0Z3xwBIBPuYVgEgiXQR+ghaEmSu9uIc9Mfoi1n1wUAS4B7GBaFoXBghDFnBUrZ1r8DgLngHoZ5IlgCfYQho3Q5jmf91m0L7z0Lf42y1RgAxMA9DIvCUDgwhJld6NX6a029evB8W692WaiHiQEAsFS4h2HeCJbACGEdssdKbsLp9nHN8Hoyy9mhADAt7mGYJ4IlAAAAouAZSwAAAERBsAQAAEAUBEsAAABEQbAEAABAFARLAAAARPH/Ab2dDaxez45JAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9aHymu9ckLYTrzZvZnruvRirXlpldkXTV3Y9167t7zcwWJK2b2cvhXgAAAKfeiVssU6FbvNbljjxdLVmUCl3W9+vDYYOl8LFsZoWTluvSipJF45/i7ltKWkTf7fGaAAAAudVLsDxvZn/R4ZxHXV6r2/NSbyiZUd5UaBWshE/ru6D7LddWCKxFSffbnFaRNN/tNQEAAPKu1xbLSliL8u/N7IdN1qPsdiuAXrcMmFQyHvJKm3PSVsmxCOU6SUNou2WTqpIKTOQBAABnRa/B0pQsFTQvaV3SgZn91sz+t5n9MHrtnqhJKki62OactCu7Puz1W66T9HrtynwWPp545jkAAEAe9Dp5Z0ZJF/CspJKSUDYe3luQJDP7raQtSZuStrocc9nJNUnlMHaxlVL4uBuhXCfdjMdMJ+300hIKAACQWz0FS3e/p2TdyjuSZGbfVdItPKMn3cNp0JwP51SVBM11SbshaPYUtsJYyJbhMCztU1ASZGsnLdeFsbrrd9I0hJrZvML36Fvf+lYPtwYAABhNvXSF32p8I6xh+TN3f83d/0zJ+pBLSsKnhde4kgC1qdB1ru5a/HqRzu5eGFK5Xur/fLM33X3V3UvuXnrxxRd7vD0AAMDo6TpYuvs7XZzTKmh+pONBM5owMWda0mybZYWilQMAAEBz0daxbKYuaJZC0JyR9GGs64e1J9MF0FsuKxSrXJ1a3XU6+azzKQAAAPkXc+edjtIxmmb2ONIl70ladfenuukHVK4f7LwDAADOhIG2WLbR0847zZhZOut8qePJEco16Gbty7Q1s9fF4AEAAHIpq2B5klAnMytLqvQRKvsq10S64067xc/TsaSVNucAAACcGpkES3e/029ZM1tUsif5U+HQzAphu8Vo5VpIlzBqN8ayGO7HxCAAAHAmZNVi2Zcwk3u8TYtjSU26p/st14q7V5SMnZxpc9q0pNVurwkAAJB3XQdLM/vAzN43s7kme4QPXGhRvOju7dacnFHDDjr9lgtly2a23mL29zVJV5sdC0G2Julmm3sCAACcKubu3Z+cjFF8K3x6tKOOu//LAOpWf9+ipD2133ZxTNKku9tJy4Wy00oWdZekBXd/qvUxfD/G3H227r1CuOdCh60kj5RKJd/d7WVHSQAAgGyY2Z67l5od63W5oduSLksqKwmWNSWLnre68Tci7RVeVjKecbrDeY0TZfotJ3ffMrP0/Q+aFXL3BTO7EgJmuqxQQdIMYysBAMBZ03WwNLOXlaz9+EqH815Ssi/4ZPi8Jqns7n/bbyXdvd1Yxujl6spPdXHOhqR+FlkHAAA4VXqZvPNTJXt+t2Rm35W0ryRUfq5kIfIHkt4xs9+a2bf7rSgAAABGWy9d4ZPu/lGHc1aUdI3vufvF+gNmtiKpamZFd/+0x3oCAABgxMXe0nFakiuZMX2Muy+Z2b6SbuOLjccBAACQb710hbecpCNJZnY5/LPm7r9qdk6YWf3AzN5qdhwAAAD51UuwrJjZX7Q5nk6U6bTEzk1Jsx3OAQAAQM70EixXJf28zfG0G3yzzTkK4zSbrn0EAACA/Oo6WIbFvvfM7H82HgtLEaV7bXezKPhBt/cFAABAPvQ6eWdJSbicUrJY+kdKAuUdJa2VFXf/XdQaAgAAIBd6Cpbu/rmkV8xsXdKHSsKklEzsqamLsZNhrcundroBAABAvvW13JC7z4a9tGclnZd0X8muPJ93UfwdJa2dAAAAOEX6XscyjLnsZjzlETO7Kcnc/V/6vS8AAABGU+wF0o8xs59K+q6SbvJpSQVJHfffBgAAQP4MNFi6+ztm9k0lofIgfNwzs1l3/8Ug7w0AAIDhGmiwlI4m/HwYXjKzopJWTAAAAJwiAw+Wjdy9Kqk67PsCAABgsLpeIN3MvjPIigAAACDfetnScX1gtQAAAEDu9RIsiwOrBQAAAHKvl2BpZvbXZvaNgdUGAAAAudVLsJSkW5IOzOy+md00s+8PolIAAADIn16C5eeSHijZF3xK0qKkTTN73GvQNLMf9l5VAAAAjLJeguXLSrZwnA2vn6t10Pylmf2kzUzyOyeoMwAAAEZQ1+tYuntN0ttm9rqkkqS/cfc/1u2sMxM+FiW9Fj6XmUlJIN2UtOnuv5Z0PuYXAQAAgOyZu/deKAmT70r618atGeuC5mtKWjYL4dCxG7n7uX4qfBqVSiXf3d3NuhoAAAAdmdmeu5eaHet18o6kZJtGd39H0udm9vf1M8XDsQ/dfcHdxySNS1pQsqXj50q6zgEAAHDK9BUsU+5+z91/LOlvzeytFuc8cPc77n41BM3XTnJPAAAAjKYTBctUaL3cC62XL3U4dyvGPQEAADBaogRLSXL3j0Lr5Wyr1ss6D2LdFwAAAKMhWrBMufvPJN0zs9ttlhuaiX1fAAAAZCt6sJSOxlW+Lemimf2k2fFB3BcAAADZGUiwTLn7HUl3OrReAgAA4BQYaLCUjpYfelvSuJndHPT9AAAAkI2ud97pVljTsqRkB57x8DF9FczsmqRZd9+OfW8AAABkp69gGbq107DYGB6PndqkeE3SVUkESwAAgFOk62BpZv+kpCWy0Hio4fOapGrd6376b3f/vP+qAgAAYJT10mJZv0RQfXDcDx8rzPYGAAA4u3rtCq9Iui1py91/F786AAAAyKtegqVLuiJpStI7Zvaykm7vTRE0AQAAzrxeguXnITz+TtKHkmRm35Q0rSdBs6onQfOPrS5kZu+7+xv9VhoAAACjp5dgudT4RpiM86GeDpq3OgTNK33XGAAAACOp62AZdtHpdE6zoHlV0s/Dv6tKZpYDAADglIm+QHq9EDTvhJfM7LuS/usg7wkAAIBsDHxLx3ru/pGk2WHeEwAAAMMx1GApSe5elcRC6QAAAKfM0INlcC2j+wIAAGBAMgmW7v5hFvcFAADA4GTVYgkAAIBThmAJAACAKNoGSzN72czeGlZlzOwbZvaTYd0PAAAA8bQNlu7+QNIDM/t7M/svg6yImV2WdMfd/26Q9wEAAMBgdFwg3d3vmdmBpI/M7Ka7341ZATP7hqSfS/qM/cMBAADyq6sxlu5eUbIV40Uz+62ZvRUCYd/M7Dtm9oGkPUn/4O4/Psn1AAAAkK1e9gqvSXrbzIqSFiWtmtmepC1J+5J2JdUkPXL3P6blQgAdkzQpqSjpoqRpJfuGr7r71UhfCwAAADLU817hYeect5WEzNclzUh6R0lolCQ3s8Zi6RtbkjYlvRPGbwIAAOCUONFyQ+7+obu/7e6vuPufSTov6RUl3eavhY+vuPufhddr7v4zQiUQx+rqqmZnZzU+Pq6pqSktLCyoWq32dI2FhQXdunUrWp1qtZqWlpY0Pj4uM9P58+c1MzOjjY2NaPcAAIymnlss23H3z8U+4MDA1Wo1TU1NPRUiK5WKVldXVS6XNT8/3/YalUpFS0tL2tra0srKSpR6bWxs6Nq1a6rVapKkYjHpyNja2lKhUNCVK1ei3AcAMJpYIB3IocuXL6tarWpxcVH7+/s6ODjQ5uamJicnJSWtkM1aCDc2NjQ1NaXz589rampKW1tb0eq0tbWl2dlZ1Wo1zc/Py921v79/VL9333032r0AAKMpSrAMM7xfinEtAO1tbW2pUqloZWVFKysrKhaLKhQKmp6e1t7enqanpyVJS0tLT5WtVquqVCoaGxvT4uKiCoVClDrVajXNzs5KkhYXF1Uul48dLxQKR6EXAHB6xWqxvKVkpnfXwpJFj8zssZndP+nyRcBZUS6XVSgUtLi42PK4lITIxhbJxcXFo5bENJTGsLS0pFqtpmKxGK1bHQCQP+buJ7+I2d+4+896OP91SR8omV2+JWlW0qy7XzxxZXKoVCr57u5u1tXAAIyNjeng4CDranT09a9/XV988UXf5dOVILoZ2wkAyDcz23P3UrNj0cdYmtn3Q2vkd9qctiJpw93vuPsDd78l6QMz+37s+gBZOjg4kLtHf3W6btoSmbZQtnql3dP/+Z//2ffXWD+Wk1AJAGdbrGC5FfYT/0zJOpWrkvbM7F/N7NtNzi9KOjYIK7R4zkaqD3CqdRobmc4WHx8fH3hd7t+/f6xO6SSe8+fPy8w0MzOjSqUy8HoAALIXs8VyQdK6ku7t2fDxUyVd3UfM7LuSXMlOPY1Yqgg4ofoQd/Xq4De2Su9XKpW0sLBwtGbl2NiYpCRoXr58mXAJAGdArHUs35E03mTh8ztmNm1mP3H3vwvvjUlS/baPdU4+4BM449LZ4DFnfbfz6NEjSU/Wqtzc3DyamV6tVjUzM6NqtarZ2Vnt7+8PvD4AgOzEarF80Go3HXff0pMtHQEM0K1bt7S1tZXZ7Oz19fWjUCklC6Rvbm5Kaj5LHQBwusQKln/ocJyWSGDANjY2tLS0pGKxqL29vaHfv1gsHguVzd5fX18fdrUAAEMUK1i+YmZ/0eyAmb0lqVb3Vru+ufOR6gOcKZVKRbOzs0ehchhd4Kl0LGW7BdDTWeq97mMOAMiXWGMsb0n6dzP7Z0kfSfpM0vNKFk2fVAiMYRH0BUmfm9kld99OLxCWGhp+MwuQc5VKRVNTU5mESkldLbKe1ikdjwkAOJ2iBEt3r5pZScms8NfqDm1JKklaMLOLSkLmppJZ4/fM7HV3/zRsB1mWNBWjPsBZUa1Wdfny5cxCpSRNTU0d1aWVWi3ptIi10w8AYDTFarGUu1ckjZvZy0rWqazWTej5qPF8M3tH0gMz2w/nv9ZipjiAJqrVqqampjQ2NpZZqJSSJY0WFhZUqVRUq9Wa1iPdWYpgCQCnW/Sdd8JOOvdazRKvO29L0itKlioac/d7sesCnDYPv3ioH/3yR9r9t92RCJVS0s2dTs65efPmU8crlcrRGpYLCwtDrRsAYLiiB8teuHvV3T90dxZGB7pw+ze3db96X9/7y+8NNVTWajVtbGwc276xXrq00a1bt46dU6lUdPnyZUnJupq0WALA6WbucVcCChN05iWlYyqrSiblrLr776Le7JQolUqedhXidDEzxfode/jFQ/3gFz9Q9W5VB//3oKsy8/PzKpef7J5aqVSOFlCXdGxdyfqlgtK1J+vPm5mZkZTsf94szK6urh61SKbH07GV09PTT10TAJBPZrbn7qVmx6KNsQw3+omkFR1fEH1c0oykJTNbdPf/FfOewFlx+ze39ZV/daJrtFuk/KSLl8/Pz6tUKunmzZtH15qentbs7Kzm5+dPdG0AQD5Ea7E0s59KuqIkWG5Jql9XpCjpv0u6Jukf3P1/RLnpKUGL5ekVq8Uyba380+M/Hb33tXNf0y9f/6Ve+PoLJ75+zJZVAMDp1q7FMsoYSzP7rqRJd3/F3e+ECTyf170+cvcldx+T9EJYsxJAl5q1Vn7lX+n2r29nVCMAAJ4Wa/LOvLu/1vk0yd2vKlnHEkCXfv37X+vwq8Nj7x1+dahf/f5XGdUIAICnxRpjaZ1POYZZ4EAPNv6q+WxsAABGSawWy3/v8XwGcwEAAJwysYLleKTrAAAAIKdiBcuKmb3VzYlmdlPSZ5HuCwAAgBERZYylu98xs382s6JaLIRuZt+RtCCp5O4XY9wXAAAAoyPmlo6zkl6TtG9mvzWz+2b2T+HjZ0p23ylJunqSm5jZipltmtl+eK2b2WQP5QtmtneSOoTrFEM95kOgrn9/PtSL/esAAMCZES1YhvUqS5J+rGTW95SSHXemJB1IesfdL7r7g36uHwLhuqT33X3G3cfDtR9J2jOzchflFyU9ULJg+0kVJE1LKisJ025mLmlf0pKkJXevRrgPAABALkTd0lGS3H1V0qokmdnL/QbJJu6oIay5e03SgplJ0nxYCX61vpCZTSvZDaiqJARWFSdYStKGkmBblDQmaVfSpruzNgwAADhzogfLeq1CpZm95e4/7/Y6oav7fpsWwCVJ85LKZvZBCJxpHbaUtGym10qDYAybjUEWAADgrIo5xrIXSz2e/4aS1sGmQpCshE+n+60UAAAA+tdVi6WZva5k4k0MBfXeYjipZBzltTbdzNVw3thJKgcAAID+dNsVXlTvrYzt9LrzTk1JIL2o1i2XhfCRCTMAAHRpbW1NN27c0CeffKKJiQktLy/rzTffzLpayKlug2VNyXjC/xbjprohst8AABMTSURBVGGcYy+uSSqH8ZKtpC2qu/3Vqj9hSaErdW89r+R71a6uAABkbm1tTcvLy7p7965effVV7ezsaG5uTpIIl+hLt8GyKumjiPftKfyFMZQtg1qY+V2QtFU/cWcIZiRV3f1WQ332zOz9xvcBABglN27c0N27d3Xp0iVJ0qVLl3T37l1dv36dYIm+mHuvvdKjx8w2lUzaGe+0dmQ4t+Tu5094z0K4zlOBN8xi35M006rl0szmlcxk17e+9a2pTz/99CTVwYgyM+Xhdywv9QQQ17lz5/Tll1/q2WefPXrv8PBQzz33nB4/fpxhzTDKwvKOTefeZDUrPBozu6IkVM4Oc0Fyd6+1Co3uXlHSyrvSpvyqu5fcvfTiiy8OqpoAALQ0MTGhnZ2dY+/t7OxoYmIioxoh73IdLEOrYbpw+qgtSl6VNMm2jgCAUbW8vKy5uTltb2/r8PBQ29vbmpub0/LyctZVQ04NdIH0IbgnaXVExzKmradFMVMdADCC0nGU169fP5oVfuPGDcZXom+5DZZhrOSWu8dcBqmX+xc7dL2nk4hosQQAjKw333yTIIloctkVbmZlSZUMQ2VZ0n4Y39lKuq5mr0srAQAA5FLugqWZLUqqNQuVZlYIM7IHbUxJi2S7pY3SlkrWswQAAGdCroJlaCEcb9NSWdJwtnS8L2mqwyLo05I2hryuJgAAQGZyEyxDS+RFd19oc9qMult8vdD5lKTL28zWw+zzI2GyUMtueDNLlxm61s19AAAAToNcTN4JS/bck7QbJu00MyZpsotxl8VwzUK71sSwm898+HRT0mrDKWUzW1ey1FG1rly68PkUrZUAAOAsyUWwlFRW0so43eG8SuMbIZSWlQTPop60Vh6YWUXJ5Jpy4zqY7r4VjkvSB43XdfeKmV2TtGJmY3XXrUh6mVAJAADOmlwES3efOUHZqpIu8n7KTnU4XpPUrmseAADgzMjNGEsAAACMNoIlAAAAoiBYAgAAIAqCJQAAAKIgWAIAACAKgiUAAACiIFgCAAAgCoIlAAAAoiBYAgAAIAqCJQAAAKIgWAIAACAKgiUAAACiIFgCAAAgCoIlAAAAoiBYAgAAIAqCJQAAAKIgWAIAACCKZ7KuAHDamVnWVejo/PnzWVcBAHAKECyBAXL3rKsAAMDQ0BUOAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIjimawr0CszW5E0KakY3qpIuunulS7LFyTdc/epSPW5ImlG0r6k5yUVJK24ezXG9QEAAPIiN8EyBMI7SkLkUt17K5L2zGzV3Rc6lJ+X9G7EOpUlqf6+4T57Zrbg7lux7gUAADDqchMslYTKpfqWQHevSVowM0maN7M9d1+tL2Rm00rCZ1VSOXws6oRCS+VVdz9f/76718xsQdK6mb0c6ggAAHDq5WKMpZlNSrrfpnt5KXwshxbDI+6+5e5T7j4bWhAfRarWiqTVZgfq7hOtdRQAAGDU5SJYSnpD0karg6FVMB1jOT3oyoSgW5R0v81pFSVd7wAAAGdCXoLlpJJxi1fanJO2Zo4NoT5peG03QacqqWBmJ+52BwAAyIO8BMuaktnWF9uck3aBD2M2dlqPdvf6LHycHHBdAAAARkJeJu9ck1TuMMu6FD7uDqE+hc6nKJ20M4wWVAAAgMzlosXS3WvtQmWY+V2QtDWkWdhjab26OLdpCDWzeTPbNbPdhw8fRq0cAABAFnIRLLuQzgpvuY5lZN20WKaeb/amu6+6e8ndSy+++GKkagEAAGQn98EyTOiZljTLbjcAAADZyXWwrNuNZ8ndWy5HNAC1uvt38lnnUwAAAPIv18FS0j1Jq+5+K+uKtMHOOwAA4EzIbbA0s00lk3WWOp4cXzdrZqatmbF2+gEAABhpuQyWZlaWVMkoVEpPdtxpt/j5ePhYaXMOAADAqZG7YGlmi5JqzUKlmRXCdouDli591G6MZVFJPZlQBAAAzoRcBcswA3y8TUtlSUNYkNzdK0rGTs60OW1a0uqg6wIAADAqchMsQ0vkRXdvt1bljLrbeaerdSjNrGxm6y1mf1+TdLXZsRCAa5JudnMfAACA0yAXWzqaWVHJDPDdMGmnmTFJk12MuyyGaxba7ZwTdvOZD59uqqH10d03zGxGyXJHs3XlCpJWlKyryYxwAABwZuQiWEoqK2llnO5w3lMTZUIoLSsJnkU9aa08MLOKklnb5cZ1MN19KxyXpA+a3czdF8zsSphMlIbIgqQZxlYCAICzJhfB0t3bjWXsVLaq9mMh25Wd6uKcDUnDXJwdAABgJOVmjCUAAABGG8ESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECyBnFhbW9OFCxd07tw5XbhwQWtra1lXCQCAY57JugIAOltbW9Py8rLu3r2rV199VTs7O5qbm5MkvfnmmxnXDgCAhLl71nU480qlku/u7mZdDYywCxcu6L333tOlS5eO3tve3tb169f18ccfZ1gzAMBZY2Z77l5qeoxgmT2CJTo5d+6cvvzySz377LNH7x0eHuq5557T48ePM6wZAOCsaRcsGWMJ5MDExIR2dnaOvbezs6OJiYmMagQAwNMIlkAOLC8va25uTtvb2zo8PNT29rbm5ua0vLycddUAADjC5B0gB9IJOtevX9cnn3yiiYkJ3bhxg4k7AICRwhjLEcAYSwAAkBeMsQQAAMDAESwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAUZi7Z12HM8/MHkr6NOt6IDdekPSHrCsB4NTh2YJufdvdX2x2gGAJ5IyZ7bp7Ket6ADhdeLYgBrrCAQAAEAXBEgAAAFEQLIH8Wc26AgBOJZ4tODHGWAIAACAKWiwBAAAQBcESAAAAURAsAQAAEAXBErlgZlfMzNu89s1s3czms67rSZjZXvh6hvp1mNlieE0P877dqPtvXMy6LhiOJr/vKx3OL476zwnPsKHcm+fYCHgm6woAfdiSVKv7vCCpKOmKpCtmtiRpwd23sqhcTr2r5Pt4S8n3Fxgli2Z2091rnU/NBZ5hg8FzbAQQLJFHs83+wJhZQdKKpHlJm2Y2w4MZyL2qktD1rqSljOsSC88wnFoES5wa4UG9YGY1SYuSNiVZtrXKB3c/n3UdgBZWJJWV/E4PNViGoDcvSe5+a9D34xl2MjzHRgNjLHHquPvRH59RHGsDoHvuvqrQbWxmi0O+/ZiSYNt2jGdsPMOQZwRLnFZpN9NkprUAEMPN8PHdTGsxXDzDkEsES5w6YdZdIXxazbIuAE4udEPXJBXyPmu6GzzDkGcES5xG6+Fjzd03mp0QlqTYDMs/HJhZOYynanZuIRzfD+fvhaVDpsPyIPvhGlfqyqRLbjTtuqtbeqKn1ohw381wv3SJkpbddHX1uNKkfLHJefMN5fet/RIpLb+OHr/Hxbpz02VXrjQ7F2dWuo91393SZjZf97Oe/i4/FVTDz65L2q9779jSQP3WoUs8w46X4TmWI0zeQe6FX/KipJKSPzrpL/1Ui3Pv6Un3Ui2cPy/pqplNuXu17vyipL1wTk1SJZRNH/xbSloUakrGYw2Mme3V1bsaXpNKlmKZl/Rym+VYxsxsXclyJr2o6PiyKPWOvofuXqmrZ6/f48lwfvrfbSyUvWJmR9fFmXdTyYSWgpnNh7GXXQk/k+uS0vGK9d3MZTOb1fGZ2lUlv9vpz6J0fPmaqK2IPMO6eoZJPMfywd158Rr5l5IHiXf52pc02eI6e+GcPUnFuvfL6fstzl+pe69Yd6/pDvdZbHE8LT/Zotx8kzLrCn9Y694r1JVZb1OPg7qv+6k6t7tvi/rPd/E1dPs9Tuu2X1+3hq/N66/F63S/6n/fG95Pf4b2G94vtvs5UTK7utnPZLHuZ2yzSblis3qc9GviGdb9M6zhmjzHcvDKvAK8eHXzango74df1PR1oA4PyXCN9CFyUP9gqzu+X/+ACQ+Epn9UlLQquKRyi3tFfyi3+bqm29Sz/oHW9KHd630b/igtNhzr9Xtc/2BvFggK7Y7zOp0vtQ6W9T8PV+rebxks66510OZ+6TNkvuH9QQVLnmHHy7R8hjVck+dYDl6MsUQeTbn70UtNuotaWAgfW+3gUQ4f0+6yUvjYrNsrHWM1Cttz7ab/aDPeqSbpWqT7bYaPW/702n69fo9nw8dVr+tWApoJP1O9jrVMZ5K3WwNzqYtzYuIZdlw3zzCJ51guECyRe+EXOX0wlNucmj5AV5oN3NaTP1Tj4eOjhnL10nNG4SHSzbiorRYPyJ6YWVnJ96OmJw/Ter1+j9Pz905aN5wZ6c9Q0bpb4zENKrttzkmPFVtNzBgknmFdj+3kOZYDTN7BqeDuS2Hwd9HMFhv/DzT8sUj/YGzoyQO3mb1wzYolO2AcmyxgdbtxqP0fgejC/82/oaRbrZeWhvsR7n1FT77up7ak6+d7rCdfwyj8cUMOuHvVzDaU/A6sqE1rX/2MYbX/Gas/NqbWEz0ar78oaabF4YrXLXTeCc+wrvAcywGCJU6TJSUPyRUzW61/YLh7LX3ASlrqobtiVclg87KZLSh5cKQzEm953SzCQQv/l50+ELeUPPQ+U/JHcKB/HMLD9k749JY32b+4z+9xug/0KHTHIT+WlPweToag0ioI1oeCko7P7FbDsWZlOpnRk+7QRv3MsOYZNtj78xwbArrCcWqE/xtPH5J3mpySdnf1skXavJKH36qSB820kgfiTC+tEfUaWlG6LbMS6lKRdN7dZ9x9yd1veQ/LrpxAuoxGp1aYXr/H6UO72zFmQNp1nIaClmMtQzDrZgeb+iVnuu5qDb+H1uLV8880z7CB4zk2BARLnDbpwO4rTQaBp/9HvNJuHFV6zJ7sfrHp7gvuPu7u6QOxVctHN/rZoi19wL3foutmYMIfhLTOzcYj1evpe6wna+nNtzi/1OQ9QHoy0WZa7X+njraDbPYzFt57t+Hcpwxx7CXPsAHgOTY8BEucKqFbJ92p4k7DsQ0l/6dekLTX+NC2ZDeHfUlXw1tpl9iCmU1asnvF0atDVdKyx8ZfhXs2a4noJP0/4gU7vtNEuvDzQITJEenOG7OduoV6/R6Hlor0j8yx88O/B/a1Id/C73rauteu1fJWOO+pn8nw73Tx8EqT2cH13eJXQ5lC6NIdCJ5h8fEcG7Ks1zvixaubl46vAffUumIN59avGda4Ll36EEuPH+jJmmTN1sfbazjmDWXX1WQhYyUPsfo16zbr7lN//67WgFPyf9recM39unp0ul7Tteja3Td8rw6a3LPZa/IE3+PGr+2g7r711zn167/xOvqZaLqOZZPzpht+dtqtI7jZ5Nz0tdnqudLwDGj5u9bL19TqXg315Rn29DV5juXgRYslTh1PulnSlodjXRnuXnP3WSVdIWkrxlj49y0lY382pGPdSK0UlPyx2LOG/WA9aflI/y+2GO6xpWT9uk7dMM2+poqSloO0hSadubrk7ud7vV6XGr/+YpvX0USFXr7H4fyKkrFJG3ryf/27Sr7eWGvW4RTypDu34+ST8DM5o2R9wi0lP2e18O8FT7qGW42tvFZ3j0dKfk5nfICTXniGRcVzbMgsJG0ADezJvrarSh5+tbpj6YMoHbdTG/DDEQB6wjMMWSBYAk2EFoIDSXJ363Bu+ks07uy6AGAE8AxDVugKBzroclag1Nv6dwAwFDzDMEwES6CJ0GWULsdxr9m6beG9e+HTKFuNAUAMPMOQFbrCgTbMbFNP1l+r6snA80k92WVhK0wMAICRwjMMw0awBDoI65C9q+QhnG4fVw2vm4OcHQoAJ8UzDMNEsAQAAEAUjLEEAABAFARLAAAAREGwBAAAQBQESwAAAERBsAQAAEAU/x+XS9eI97Gs5QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v_fyrhFDoqdC"
      },
      "source": [
        "fig, axs = plt.subplots(3, 4)\n",
        "for x in range(0, 24, 2):\n",
        "  i = int(x/2)\n",
        "  (axs.flat[i]).boxplot(np.log(fig_3_sim_cv.iloc[:,[x,x+1]].values))\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r_sCOzDtA_0p"
      },
      "source": [
        "## Fig.4"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "background_save": true
        },
        "id": "SO68yD9fkwdQ"
      },
      "source": [
        "from sklearn.model_selection import KFold\n",
        "dataset = joblib.load('data/all_mutational.pkl.gz')\n",
        "n_iter = 500\n",
        "fig_4 = pd.DataFrame()\n",
        "layers_list = [5, 10, 15, 20]\n",
        "lst = {}\n",
        "avg = {}\n",
        "kf = KFold(n_splits=5, random_state=1, shuffle=True)\n",
        "\n",
        "for layers in layers_list:\n",
        "      avg[f\"super_{layers}\"] = []\n",
        "      avg[f\"unsuper_{layers}\"] = []\n",
        "\n",
        "for k, v in dataset.items():\n",
        "\n",
        "    for layers in layers_list:\n",
        "      lst[f\"super_{layers}\"] = []\n",
        "      lst[f\"unsuper_{layers}\"] = []\n",
        "    \n",
        "    for train_index, test_index in kf.split(v[\"V\"].T):\n",
        "\n",
        "      data, n_components, features, samples = util.build_data(\n",
        "          v[\"V\"], v[\"W\"], v[\"H\"], index = train_index\n",
        "      )\n",
        "\n",
        "      for layers in layers_list:\n",
        "        # Supervised\n",
        "        _, super_train, super_test = util.train_supervised(\n",
        "        data, layers, n_iter, L1=True, L2=True )\n",
        "        ##################### unsupervised performance #############################\n",
        "        _, unsuper_train, unsuper_test, _ = util.train_unsupervised(\n",
        "            data, layers, n_iter, n_components\n",
        "        )\n",
        "        \n",
        "        lst[f\"super_{layers}\"].append(super_test[-1])\n",
        "        lst[f\"unsuper_{layers}\"].append(unsuper_test[-1])\n",
        "\n",
        "    for m in layers_list:\n",
        "      avg[f\"super_{m}\"].append(round(np.average(lst[f\"super_{m}\"])))\n",
        "      avg[f\"unsuper_{m}\"].append(round(np.average(lst[f\"unsuper_{m}\"])))\n",
        "\n",
        "fig_4 = pd.DataFrame.from_dict(avg)\n",
        "fig_4.to_csv('data/outputs/fig_4.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t9UksPdku5Bv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "outputId": "35ba0b29-3926-4348-8bb7-224706e3111e"
      },
      "source": [
        "fig_4 = pd.read_csv('data/outputs/fig_4.csv')\n",
        "plt.rcParams['figure.figsize'] = (10.0, 8.0)\n",
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(111)\n",
        "x_axis = ['5', '10', '15', '20']\n",
        "for i in range(fig_4.shape[0]):\n",
        "  data1 = np.log(fig_4[['super_5', 'super_10', 'super_15', 'super_20']].loc[i])\n",
        "  ax.plot(x_axis, data1,'ko-',label='line1')\n",
        "ax.set_xlabel('$\\# layers$')\n",
        "ax.set_ylabel('$\\log({MSE})$')\n",
        "plt.savefig(f\"plots/fig4/supervised.pdf\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "FvAvdFwwxS6I",
        "outputId": "b15c8541-2aea-4c90-ced2-918085522731"
      },
      "source": [
        "fig_4 = pd.read_csv('data/outputs/fig_4.csv')\n",
        "plt.rcParams['figure.figsize'] = (10.0, 8.0)\n",
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(111)\n",
        "x_axis = ['5', '10', '15', '20']\n",
        "for i in range(fig_4.shape[0]):\n",
        "  data1 = np.log(fig_4[['unsuper_5', 'unsuper_10', 'unsuper_15', 'unsuper_20']].loc[i])\n",
        "  ax.plot(x_axis, data1,'ko-',label='line1')\n",
        "ax.set_xlabel('$\\# layers$')\n",
        "ax.set_ylabel('$\\log({MSE})$')\n",
        "plt.savefig(f\"plots/fig4/unsupervised.pdf\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dtxAqrDVeLhR"
      },
      "source": [
        "## Fig.5"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P-y9byChJq3O"
      },
      "source": [
        "from sklearn.model_selection import KFold\n",
        "dataset = joblib.load('data/all_mutational.pkl.gz')\n",
        "n_iter = 500\n",
        "layers = 10\n",
        "fig_5 = pd.DataFrame()\n",
        "lst = {}\n",
        "kf = KFold(n_splits=5, random_state=1, shuffle=True)\n",
        "\n",
        "for k, v in dataset.items():\n",
        "    lst[\"dnmf\"] = []\n",
        "    lst[\"mu_0\"] = []\n",
        "    lst[\"mu_1\"] = []\n",
        "    lst[\"mu_2\"] = []\n",
        "    for train_index, test_index in kf.split(v[\"V\"].T):\n",
        "\n",
        "      data, n_components, features, samples = util.build_data(\n",
        "          v[\"V\"], v[\"W\"], v[\"H\"], index = train_index\n",
        "      )\n",
        "      #Supervised DNMF\n",
        "      _, _ , dnmf_error= util.train_supervised(data, layers, n_iter, L1=True, L2=True)\n",
        "      lst[\"dnmf\"].append(dnmf_error[-1])\n",
        "      #MU\n",
        "      for lam in range(3):\n",
        "        L1 = lam\n",
        "        L2 = lam\n",
        "        #Train\n",
        "        mu_super_iter = 500\n",
        "        w_mu = data.w_init.mat.copy()\n",
        "        for i in range(mu_super_iter):\n",
        "            w_mu, _ = util.mu_update(\n",
        "                data.v_train.mat, data.w.mat, data.h_train.mat,l_1=L1,l_2=L2 ,update_H=False\n",
        "            )\n",
        "        # inference\n",
        "        mu_super_iter = 10\n",
        "        h_mu_test = data.h_0_test.mat.copy()\n",
        "        for i in range(mu_super_iter):\n",
        "            _, h_mu_test = util.mu_update(\n",
        "                data.v_test.mat, w_mu, h_mu_test,l_1=L1,l_2=L2 , update_W=False\n",
        "            )\n",
        "        mu_error = ((data.h_test.mat.T  - h_mu_test.T) ** 2).sum()\n",
        "\n",
        "        lst[f\"mu_{lam}\"].append(mu_error)\n",
        "      \n",
        "    fig_5[f\"dnmf_{k}\"] = lst[\"dnmf\"]\n",
        "    fig_5[f\"mu_0_{k}\"] = lst[\"mu_0\"]\n",
        "    fig_5[f\"mu_1_{k}\"] = lst[\"mu_1\"]\n",
        "    fig_5[f\"mu_2_{k}\"] = lst[\"mu_2\"]\n",
        "fig_5.to_csv('data/outputs/fig_5.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "XsS1y1oj2jyl",
        "outputId": "25381398-5e78-47be-9219-6983870089b1"
      },
      "source": [
        "fig_5 = pd.read_csv('data/outputs/fig_5.csv')\n",
        "for x in range(1, 13):\n",
        "  util.plot_box(\n",
        "      [f\"dnmf_{x}\", f\"mu_0_{x}\", f\"mu_1_{x}\", f\"mu_2_{x}\"],\n",
        "      [\"DNMF\", \"$MU_{\\lambda_1=\\lambda_2=0}$\", \"$MU_{\\lambda_1=\\lambda_2=1}$\", \"$MU_{\\lambda_1=\\lambda_2=2}$\"],\n",
        "      f\"fig5/supervised_performance_{x}\",\n",
        "      fig_5,\n",
        "      'Supervised',\n",
        "      None,\n",
        "      '$\\log({MSE})$',\n",
        "  )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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zRpcvXz5+HQAwWnQCSYFOIAAAYFr06gTCI2AAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHJm6gKgmW2Z2Z6ZHYZl18wWhrUfAADArJmaAGhmBTPblfSWuy+7+7ykRUn3JB2YWSXL/QAAAGbVo+MuQApXJW26eyN+wd2bktbNTJLWzOzA3Xcy2g8AAGAmTUUNYHhUe6s1xLXZDF8rZlY46X4AAACzbCoCoKSXJFW7rQw1evXwbTmD/QAAAGbWtATABUXt9VZ6bBPX8hUz2A8AAGBmTUsAbEoqSDrbY5v4EW7r495B9wMAAJhZ09IJ5IKkirvXemyzFL7uZ7AfAADAzJqKABja6nUNcWZWVlSTVwvbnmg/AACAWTYtj4D7iXvzrme9n5mtmdm+me3fuXNnoMIBAABMkqkPgKGDR1nSao/hXgbez9133H3J3ZdOnz598gIDAACM2VQHwDB2XzzQc9fhXrLaDwAAYBZMdQCUdEPSjrtvj2g/AACAqTe1AdDM9hR13tjsu3EG+wEAAMyKqQyAZlaRVB8g/A20HwAAwCyZugBoZhuSmp1CnJkVwvy/me0HAAAwa6ZiHMBY6Lk77+7dhm1Z6vTioPsBAADMoqmpAQw1dGd7hDhJWlbbjB6D7gcAADCrpqIG0MxKinru7odOHJ0UJS20PuIddD8AAIBZNhUBUFJF0ZRt5T7b1TPaDwAAYGZNRQB09+VR7gcAADDLpqYNIAAAALJBAAQAAMgZAiAAAEDOEAABAAByhgAIAACQMwRAAACAnCEAAgAA5AwBEAAAIGcIgAAAADlDAAQAAMgZAiAAAEDOEAABAAByhgAIAACQMwRAAACAnCEAAgAA5AwBEAAAIGcIgAAAADlDAAQAAMgZAiAAAEDOEAABAAByhgAIAACQMwRAAACAnCEAAgAA5AwBEAAAIGcIgAAAADlDAAQAAMgZAiAAAEDOEAABAAByhgAIAACQMwRAAACAnHn0pAcws6cklSXNSypJKkgqhq8NSU1J9yQdSqq7+++e9JwAAAAY3EABMIS+VyWtSXpM0vuKwl4j/Ptu2PRxRUHwcUlnJf2ymT0mqSap4u7fOkHZAQAAMIBUATAEvx1Ji5KuSlp19xspj1GS9LykV83sqqQNd7+W5hgAAAAYXOI2gGb2NUl7imruHnf319OGP0ly94a7X3X3FxQ9Nv6smd0ys59JeywAAACklygAmtnvSPqBu3/W3d/J6uTu3nT31yW9JOmqmX0pq2MDAACgs74B0MzelLTu7r82rEKEWsEXJM2b2ReHdR4AAAD0CYBm9rSkTXd/fxSFcfc3JB2N4lwAAAB51bMTyKiCX9s53xv1OQEAAPIkcS9gM/uKovH8GpIa7v7DoZUKAAAAQ5NmGJgdSR7+XTeze4oGeX6L8fwAAACmR9qBoOuSyu7+Qb8NzexFRTOEbLn79wYoGwAAAIYgbQDcTBL+JMnd3zGzuqTtMPvHm+7+7dQlBAAAQKYSDwQtydPO4+vu77v7eUm/KOmSmd01s39sZp9OVUoAAABkJk0AtEFPEsb5W5JUlfSGoo4kAAAAGIM0AbDZ/oKZPWZmXzWzn0tyAHdfl/S+pLkU5wUAAECGUj0CfuiFqD3gDUmvmtnHZvbvEgTCrbSFBAAAQHbSdgJ5SBi4+VUza0j6mqSipGfMbE5Rp5Hvte3ylqRvnPS8AAAAGMyJA2CLiqIA+HyvQaLd/QOzgZsTAgAA4ITSPALuKTwObiacISTRUDIAAADIXpoAOGdmP9tnm3sJj5V0OwAAAGQsbQ1gPYzl9w0z+1KH8fwe6ijSRdLtAAAAkLG0bQBN0RAua2FR6PyxJ6mWbdEAAAAwDGkD4LKkkqRVSUuSCpLmw2vrkmRmf6IoDO5JqiVsEwgAAIARSRUA3f2GonH/rkqSmX1eUllRMCyHzeJA2FpDWJO0K2k/BMJiFoUHAABAemkC4Hb7C2EMwPcUTe+WJhAWBi8yAAAATiJxJxB3fz3BNu+5+xvu/oK7f0rSoqRNRSHRwjI/aGEBAABwcpmNA9hJSyBcCoFwWdI7wzwnAAAAestyJpC+4jaEZvbxKM8LAACA+4ZaA9gDM4EAAACMybgC4OaYzgsAAJB7YwmA7n51HOcFAADA+GoAAQAAMCaJO4GY2duK5vD9HUm7zPABAAAwndKMA3heUlPSjqQjM/sTM/uGmX1xaKUDAABA5tIOA/OmpOclVSQ1FAVC67axmX0665pCM9uStKBodhFJqku64u71PvutKBqH8FDS44pmI9ly90aW5QMAAJh0aR4BPy1px92f6bPdU4rm/V0I3zclVdz9lwcvpmRmBUVzEF9x982W17YkHZjZjruvd9m3Ikmt68O+B2a27u61k5QNAABgmqSpAfyawny+3YS5gPfDtx+EfxclvW5mq5LK7v5ngxRUUfjbbK2xc/empHUzk6Q1Mztw9522Mq1IOu/uc62vu3vTzNYl7ZrZ0+FYAAAAMy9NL+AFd3+vzzZbih4J1929GOYEjqeB+5akhpn9TNpCmtmCpFs9HtfG4wpWQs1ee5l21EGo+bsn6WLaMgEAAEyrrIeBKSvqKXyhfUV4bPuLkqoDHPelXvuF2ru4DWA5fj0Ex5KkWz2OXVefmk0AAIBZkiYAdu3sIUlm9nz4Z9Pdf7/TNuHx7Ptm9pUU55Wi9oQH4XFuN3HtYLHltXLbum77Fcys1GMbAACAmZEmANbN7Gd7rF8OX/t1qLgiaTXFeaWot3FB0tke28SPflvD3tkOr7W7G74upCwTAADAVEoTAHckfbPH+vjx716vg4R2hEspzitFj5SX496/XcTH3G95rb09YCdx549iz60AAABmRJqBoGuKHsP+8/Z1YYiYuAYtyZAqR0nPG87d7DVUi5mVFYW9Wltv3mK8f4LTJAmLAAAAUy/tQNCbikLgoqJBod9TFPyuKqr9q7v79zItYfJySVL7OIBpQt3jGZUFAABgoqUKgO7+gaRnzGxX0juKQp8UdRBpKkHbvjBWYM9ZO9IIHUPKklaHMauHma0p9BJ+8sknsz48AADAyA00DIy7r0p6QVGbwHcU1cA9nbD273VFtYcn1jI7yKa7dxomptmyXT93O73o7jthLMOl06dPD15YAACACZH2EfCx0CYv1RRqZnZFkrn77w563jY3FE1Pt53BsZgJBAAA5MLAATAJM/uapM8rCldxR43FjI69p6jTR6+ewQ1FbRSL6h7w4trBe1mUCwAAYNJlPRPIA9z9dUnnJb0taVfS+4o6kXzpJMc1s4qiDie9wp90fwaQXoM8z4evmbVLBAAAmGRDDYBS1HHE3d9x91fd/RlJn1WfWUV6MbMNRbONPBT+zKwQpn+LxY+oe7UBLIXjZd6BBAAAYBINPQC2c/eGu78zyL6hx+98j5q/JbUM6OzudUWPfpe7bC9Fj6Z3BikPAADANEocAM3s54ZZkATnX5B01t3bx/prtawHZwKRollEznfqCRwCZVPR9HQAAAC5kKYTyK6ix7cjZ2YlRT1+90Pnj06KkhbaawfdvWpmy4qGizkepzAEwi1F4wfSAxgAAORGmgDYqyPFsFUUteMr99muY0cOd183s5XQeSQOewVF8wvT9g8AAORKmgBoZvaPJV119x8Oq0CduHuvNnxJj1GV1GmwaAAAgFxJ2wlkW9KRmd0ysytm9sVhFAoAAADDkyYAfqBoHD9TNJjzhqQ9M/s4bSA86TiAAAAAGFyaAPi0onH1VsPyTXUPhN8xs6/26Dl89QRlBgAAwAkkbgMYesq+amYvKhpv75+4+w/N7DFFnTOWw9eSpBfC9zIzKQqOe5L23P27kuay/E8AAAAgOXP39DtFoe+ipP/g7t/qsK6sKASu6v4sHA+cyN0fGaTA47S0tOT7++3DDAIAAEweMztw96VO6waaCSRM7/a6pA/M7Btm9um2de+4+7q7FxXNtbsu6R1F7QgHngYOAAAAJ3eiqeDc/Ya7/6KkXzazr3TZ5n13v+ru50MgfOEk5wQAAMDJZDIXcKgNPAi1gU/12baWxTkBAAAwmEwCoCS5+3uhNnC1W21gi/ezOi8AAADSySwAxtz9DUk3zOzNHsPAnHhmDwAAAAwm8wAoHbf7e1XSWTP7aqf1wzgvAAAA+htKAIy5+1VJV/vUBgIAAGCEhhoApeNhYV6VNG9mV4Z9PgAAAPSWeCaQpMKYgEuKZgSZD1/jpWBmFyStuvu7WZ8bAAAA/Q0UAMPj3DjUtYe8BzbtsHtT0nlJBEAAAIAxSBwAzezfKarZK7Svavu+KanRstyK/+3uHwxeVAAAAGQhTQ1g69AtrQHvMHyt07sXAABg8qV9BFyX9Kakmrt/L/viAAAAYNjSBECXtCJpUdLrZva0ose9eyIQAgAATI00AfCDEPK+J+kdSTKzxySVdT8QNnQ/EP6w24HM7C13f2nQQgMAAGBwaQLgZvsLoVPHO3o4EG73CYQrA5cYAAAAJ5I4AIZZPfpt0ykQnpf0zfDvhqKexAAAABiTzAeCbhUC4dWwyMw+L+lvDfOcAAAA6G3oU8G1cvf3JK2O8pwAAAB40EgDoCS5e0MSA0IDAACMycgDYHBhTOcFAADIvbEEQHd/ZxznBQAAwPhqAAEAADAmBEAAAICc6RkAzexpM/vKqApjZp82s6+O6nwAAAB51DMAuvv7kt43s2+Y2f82zIKY2fOSrrr7rw3zPAAAAHnXdyBod79hZkeS3jOzK+5+LcsCmNmnJX1T0l3mBwYAABi+RG0A3b2uaAq3s2b2J2b2lRDcBmZmP2dmb0s6kPRb7v6LJzkeAAAAkkkzF3BT0qtmVpK0IWnHzA4k1SQdStqX1JR0z91/GO8XgmJR0oKkkqSzksqK5gXecffzGf1fAAAAkEDquYDDTB6vKgqDL0palvS6onAnSW5m7bvFL9Qk7Ul6PbQvBAAAwIilDoCtwoDOx4M6m9ljimr7CuHrPUlNwh4AAMDkOFEAbOfuH4h5fgEAACYaA0EDAADkTCYBMPTofSqLYwEAAGC4sqoB3FbUszexMJTMPTP72MxunXRYGQAAACSTVQDcc/dvJt049B6uSNqU9IykXUk3MioLAAAAesi0E4gkmdkXFQ0Js+/uv99lsy1JVXe/Gr7fNjM3sy+6++9mXSYAAADcl1UNYC3MF3xX0Th/O5IOzOw/mNnPdNi+pKgG8Ji7vyFpNaPyAAAAoIssawDXFYKfovH/ipJeUDT482fjjczs85Jc0cwh7RhCBgAAYMiyCoCvS5rvMODzVTMrm9lX3f3XwmtFSWqdLq6FZ1QeAAAAdJHVI+D3u8324e413Z8KDgAAAGOWVQD8QZ/11OwBAABMiKwC4DNm9rOdVpjZVyQ1W14q9DjOXEblAQAAQBdZtQHclvSnZvY7kt6TdFfS44oGh15QCHZhsOd1SR+Y2XPu/m58gDB8zEFG5QEAAEAXmQRAd2+Y2ZKiAZ1faFlVk7Qkad3MzioKg3uKhnu5YWYvuvufhWnkKpIWsygPAAAAustsGBh3r0uaN7OnFY3z12jpGPJe+/Zm9rqk983sMGz/QpeewQAAAMhQ5jOBhNDXsUdw23Y1M3tG0ucl1dydMQABAABGIPMAmIa7NyQ1xlkGAACAvBnGXMCflrQmKW7z11DUuWPH3b+X9fkAAACQTqYB0My+KmlLDw78PC9pWdKmmW24+/+V5TkBAACQTmYB0My+JmlF0quKev/ea1ldkvR3JV0ys3l3/6WszgsAAIB0MgmAZvZ5SQvu/kyXTd4Ly6aZvW1mX3T3383i3AAAAEgnq5lA1tz9hf6bSe5+XtE4gAAAABiDrAKg9d/kAQz5AgAAMCZZBcA/Tbm9Z3ReAAAApJRVAJzP6DgAAAAYsqwCYN3MvpJkQzO7IlOMR4kAABZzSURBVOluRucFAABASpn0Anb3q2b2O2ZWUpcBn83s5yStS1py97NZnBcAAADpZTkQ9KqkG4qGemlIaioaC7CoaBzAgqS6pPMZnhMAAAApZRYA3f0DSUtmtqZoKrjFltUNSV9z9zeyOJeZFSTdcPfFvhtH268pmo1EioKoJG25ey2L8gAAAEyTzOcCdvcdSTuSZGZPu/v7WR07BL81SRdT7LMr6S13X215rSDpqpmtuvt6VuUDAACYBll1AumoW/hL2mGkZfuymR1IuqroMXIj4X4VSVfcvdpWrmYIhKVQOwgAAJAbQw2APWym2djda+6+6O6r4bHtvb47RcruXu+xfkvMSgIAAHIm0SNgM3tR0lJG5ywo6hQyVKFHcrHPZo1RlAUAAGCSJG0DWFLKWrs+RjETyD1JBTPbcPftLtssKHqkDAAAkBtJA2BT0p67/x9ZnNTMkj7CHZi7N82sLmnLzB539wcCbOgIsqX7vYMBAAByIWkbwIak9zI8736Gx+plVVF43TCzQzNbkI7D366kdXdP1KEEAABgViSqAXT3G4oGec6Eu7+Q1bH6nKdhZk8rKvuCpAMzi3sEE/4AAEAujasX8Mi4e1PS87o/dMyK6PgBAABybOYDoJmVFY0fuKxodpKGotrAwyRjAJrZmpntm9n+nTt3hltYAACAEZjpABgC3noYP7Dh7nV3n5cU9wqumNlGr2O4+467L7n70unTp4deZgAAgGGb2QAYOnxstk4BFws9ghcVdRDZCmMGAgAA5MLMBkBFQ7xsdVsZZghZDN+ujKREAAAAE2CWA2BZfYabCb2AdySdHUmJAAAAJkDSgaBn2aGiR8EAAAC5MMs1gHUlm794WdLekMsCAAAwMaY5ABb6rL+gqINH1+3CEDFNd69lWjIAAIAJNq0BsCQdT+nWUejkcUHR7B8PdfIIw79shm0AAAByYyraAIZhWiqSiorCXxz8jsysLumepIq7V1v3c/eqmdUkXTSz9fBy3N7vLXdfHn7pAQAAJstUBMDQW3egsBamgtvMtkQAAADTa1ofAQMAAGBABEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzBEAAAICcIQACAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAzUxkAzaxgZgcp9ymZWcXMDsxsLywbwyojAADApJqqABiC34ak9yWVUuy3JmlPUsXdF9192d2XJdUJgQAAIG+mIgCaWTnU+F2VVJfUSLHvmqQtSYvuXm9bXZG0nllBAQAApsCj4y5AEu5ek7QYf29m95SgBtDMSopC3qq7NztsUlSKMAkAADALpiIAnsCWpKa7VzutdPe5EZcHAABg7KbiEfAgzKwgaUXS2+MuCwAAwCSZ2QAo6Xz4mqq3MAAAwKyb5UfAcZvBRqgNXGtZ97ikvdC2EAAAIFdmOQC2dhK56O6brSvDOIDL7a8DAADMulkOgMXwdVVSp5C3KunIzG516yQiHQ8jsyZJTz75ZOaFBAAAGLVZbgNYiP/RaQiY8Fpd0diCXbn7jrsvufvS6dOnsy8lAADAiM1yAIxD316PbfYlFcxsYQTlAQAAmAizHADvha+9BnqOQ+LSkMsCAAAwMWY5ACaZ4eNu+Do/zIIAAABMklkOgPH4f72mjHs8fL3bYxsAAICZMssBMB7j72yPbeKOIowHCAAAcmNmA6C7NxT18u3VwaMsqeHu9dGUCgAAYPymOQAW+m+iTUllM3voMXDo+VtSNB4gAABAbkxrACxJUpjirasw1dumpL3WbUMgvCFpndo/AACQN1MxE0gIbBVFs3uUdL/278jM6oqGfKl0mtHD3bfDNldDCIyHfnme8AcAAPJoKgJgaM+3fIL9a6KjBwAAgKTpfQQMAACAAREAAQAAcoYACAAAkDMEQAAAgJwhAAIAAOQMARAAACBnCIAAAAA5QwAEAADIGQIgAABAzhAAAQAAcoYACAAAkDMEQAzF+vq6tre3e26zvLys+fn5nsv6+vrAZajValpeXtbc3JzMTMvLy6rVmBIaAIBHx10AzJZ6va7NzU3VajVtbW313PbevXtqNBp9txnE5ubmcQAtlUqSokBYq9W0sbHRt2wAAMwyagBxYtVqVYuLi5qbm9Pi4mLqWrbd3V25e8dld3c3dXlqtdpx+Nvb29Ph4aGOjo60t7cnSdre3la1Wk19XAAAZgUBECfWaDRUr9dVLBa1sbGhQqEw1vJsbm5KioJluVw+fr1cLqtSqTywDQAAeUQAxIltbGzI3XV4eKitra3jR67j0Gw2Va/XVSgUtLKy8tD6tbU1FQqF49AKAEAeEQAxU95++21J0tLSUtdt4nV0CAEA5BUBEDMlbue3sLDQdZt43a1bt0ZSJgAAJg0BEGPXaDS0vr6u+fl5zc3NaXl5eeBOGs1mU5L0+OOPd90mXhdvCwBA3jAMDMYu7pBRKBRULBZPNFxLPGxMr44o8bpBh5gBAGDaUQOIiVCpVHR0dKTDw8MTDdeSplaPGkAAQF4RADF2W1tbWltbO/6+XC5rY2NDknThwoVxFQsAgJlFAMTYHBwcyN2Pw16reAq4ZrOZqrdu/Hi3V+1evG7c4xUCADAuBEBMpNaxBPtNF9eqWCz23ebu3buJtwUAYBYRADGw69ev69lnn9UjjzyiZ599VtevXx/KeQ4PDxNvG9fq9donDpTUAAIA8opewBjI9evXdenSJV27dk3nzp3TzZs39corr2R2/NZHuPPz84n3O3v2rKrVqvb397tuEwfAs2fPDl5AAACmGDWAGMjly5d17do1Pffcczp16pSee+45Xbt2TZcvX060f7PZ7NlOr/Wxb69ZPdrFc//W6/WOx4+nimvdFgCAvCEAYiC3b9/WuXPnHnjt3Llzun37dqL9L1y4oNXV1a7r47EBFxYWes7q0W5hYeG4/eCVK1ceWr+zsyMpamOY5rgAAMwSAiAGcubMGd28eVN3fnRHX/7Ol/WDv/iBbt68qTNnziTaPx7weXFx8YFevs1mU+vr68evXb169aF9m82mqtVq1zECK5WKpIfHEazVasfBMu0A0wAAzBJz93GXYWosLS15r7ZleRK3AXzhjRd0449u6C++9Re6+8d39cwzz+iP/uiPJEW1bK29eeMBnmPr6+vHNXLx9q0dNHZ3dzs+pq3ValpeXpYkHR0ddezMsbm5qe3t7eNjSffbFQ4ywwgAANPGzA7cvWM7KgJgCpMcAIvFoo6OjkZ6zkcfe1Sfe+Nz+vPv/rn+82/+55Geu9Xc3FzHad1qtZq2trZUq9VUKBS0tLSkzc1N2v4BAHKBAJiRSQ6AZqZR/y5/9f/7VX37T76tjz75SKc+dUpf+uyX9E//9j8daRmk8fzfAQCYdL0CIG0AZ4iZjWw5VTil3/rD39JHn3wkSfrok490/Q+v61Th1EjLYWaam5sb808eAIDpQgCcEe5+oiWt079wWrK2Fy28PuLyd3r8CwAAuiMAQlL6APaFlS/oU6cevHw+depT+sLKF0YSQAEAwOCYCQQDqf5C5yFYAADA5KMGEAAAIGcIgAAAADlDAAQAAMgZAiAAAEDOEAABAAByhgAIAACQMwRAAACAnCEAAgAA5AwBEAAAIGcIgAAAADlDAAQAAMgZAiAAAEDOEAABAAByhgAIAACQMwRAAACAnCEAAgAA5AwBEAAAIGfM3cddhqlhZnck/dm4yzGBnpD0g3EXAlOD6wVJca0gDa6Xh/2Mu5/utIIAiBMzs313Xxp3OTAduF6QFNcK0uB6SYdHwAAAADlDAAQAAMgZAiCysDPuAmCqcL0gKa4VpMH1kgJtAAEAAHKGGkBgjMxszcyOzMxblr0BjlPocJxDM1to2aYUXvMOy5GZbXU4brnDcd3MDk/6f0d6XC9IimsF/VADCEwAMytJ2pW0IKnp7nMp969IKksqSdp09+0+2x+GbWvuvpzg+CuhfOvuzmOWMeN6QVJcK+iGGsApYGYrXe6s2u/ItsIfe9rjPXR31rZ9qWXbh44f7uRaj7eS8v/Xehd4kLDM/ZaOx5lgC5Iq4d+FNDuGn/eeojddKVk7mHjbSs+t7qsrekPnDXoycL0gKa4VdEQAnD41SdW2pa7oj25D0qGZbaQ85oaZpXpj6GM96YbhMULaczclNRIs02RZ0e+2IR3/XPoKv7ezLS/V3b3ZZ59yy7e1hOUrK7pLx2TgekFSXCvoiAA4fVbdvX1ZlDQnKa6a3zKzpH9QcVC6mFH5mpLKKQJlHBZ7vrG0WXT3+T7Larpij13J3VuDa9+a3OCipCuK3uSlZG+68bZ939Db9kn6ho7h43pBUlwr6IgAOCPcvenum7r/B7jS79FuEG+Tttawm7fD1/MJt4+3y+0bQAjL8Ztl4jfpcLd9K7zRxnfeSRp5x9um+ZkvhA8RjBnXC5LiWkEvBMAZ4+413a9V2+jXJjC0u2hK0gCPjjuJax77PgYO7UsKit4s7mVw7mlV1v0317gH3HyC/VbdvRre5EvS8e+/q7Bt/AgoUY/A8MgotwF9AnG9ICmuFXRFAJxBIdTFd1RJagGvhK8nfgwc3iSakhYSdEh5KXzNe/uP1kcgie7SQ+3uZvg2vuuuJzjXcRudfm/obfukHj4CQ8P1gqS4VtAVAXB2xcFvpV97vNCtvympYGZrGZw7/uPv1xs4Xv92z61mX6nlEUj8Rtv1TTrcNR+2tLEZqI1OivLRRmeycL0gKa4VdEUAnF2toarcdav74i74SWoM+4m7/3d9DNwSNGspGgvPnBDOj9u/tLxZ97pLbx8va5A2Om8lLqRUzPPvaJJwvSAprhX0QwCcUeGPKv7DOttr2yB+DHziWsCW6v9SjyEH4l66eX/82+kRSNwm86Ga29BOc6vl+7RtdOI3/0R33aExOHfok4PrBUlxraAnAuBsiztW9B2SJQTG+M5vs9e2CVXD14dqAcObRXy3OMjj325TDsVL0gFIJ0GnRyDxnfpS64uhTWWzrcdcml53rW10kj6mWVaPu3+LponanYSf+aSUJQycvhEGSF/JqFlFjOslI5NUFun+dZPhIblWMjIpZQnvKRsWTfqwe9LrhQA429JWrcfBr5R2No8O4j+UTsPBnPTxb73PMk1zSZY6/Ay6ParZ7DBaftzuJskjmjTteWLlXnf/oewXJK1l/OGV2iSUJdzcVNx9291r7l6VdC/D8nC9ZGSSyhIC2J6kxzM8LNdKRiahLPEg2+G9ZTOMdXvWBpjfOUYAnG3xH3mikNVWC3iitoAtvYELbaPDS/d7/w56N7Xq7os9lp5zVU6K9jY6LeLX5lu2XVPnn1eacRTju/6kQzSUlGB4nnDdVJViBphhmYCyrKnt5xtC4MWTzrbD9ZK9cZcl1CxtKeoQl9lYeFwr2ZuAsix0CMwXFE28MFCFDQFwRoU3gPgDJ02NWBz8Sh2CW1rx493jP5jwh78gHX8w5tl5dX7DvBW+lqT7v8v2RyvhZ1mQEj92iW8Ikn7QbCr5jUBFvdt8jtI4y/KSOveCbChZZ6xeuF6GY2xliQfwbxmJIStcK8Mx1veW9qHVQiht6H4NbCoEwNnV+mGTuJ1daAMSB7OT9giO7ypbyxLfqTDxd/chENof02x1qdVMO+p+o+1rV+GNpph0PK+WGt9JuFMfZ1kW1L3mZaA36RZcL0MwSWXJENfKEIy5LK0DbWeCADi74gt0kHZ2cVvAhZPc6YQ7x4YefAzM4M/3Fbr8bo7fpEPVfrdH5Wna6EjSfnzcXhuFWoFdpe8MtKP77TvHbeRlSfCIt3jCU3C9DM8klSULXCvDM5ayhDnuH3hq1tL7eqB2gI9mUTBMlvCHHQeu1LV47t4ws1o4xpZOdrdTVTTP8KqZ7Su6g2mmGCl+JoVg3fFu2d2bZiZFd3xnezwqT3uXvqnojeui7tfytperpOhDYXWA+TnfUjT94Eq3Mof2Tnvtv38z21WC3uotGu7e67rsWpbwphm/gZ+VdKX1MdcJytIr4N1TgjlYu+F6mcnrZSi4VnJ1rayFbQZrTuXuLBO+KHps6mEp9Nl2QdJR2LbS73h9jhOfs/X8pQ7blrsdT9GHnocyrYV/b3XYrhLWHST4GTxUhmlaws/koNv/NWxzKOmox/quP/OE19Ju67UUft8VRXeSA/18Fb2xuaI34U7l3Qj/r/IIfsa9ylJp+XcpXJs9/65S/F67/Y3sdioL10t+r5cu18hD741cK1wrPX7Xh4P+TN2dR8CzJHRPP1B0gdb8BHeZHt21xHcuA7cF9OhOrx7KFFf7j31cp3EIY8IdKfqjXVD0iN3DXWG7mu4Plh3vXzKzQzNztVT5h2McJekJ5tGd4pyiGqkb4XiHiu7cd9192dPfncd3vlcV/Y7L7Y9DPRoSZVsZ9nQcpCyhFuK4U1T4vzaU7SOdTnf4BaVs5M/1kpvr5cS4VnJ5rexqsNrU+4adllkySfqttV+7HZaDlvUda9i6Ha/PduW246auAQzrN1r2P+yyTW5qAGdt0f02KHHPc5e00WXbPQ3xLr1fWRRqttv2Oej3N5Pi/N7p/5flOaZ94XrpWpYT1wDO2sK10rUsFUXDwpzoOLQBnD7d7sTi3rsVP8kdQQt3r5lZXSfvebSj+7WIuaz9m1V2fwDbZQ+Nzs2sqqizT+LxGLNoG5OkLO5eN7PFtmMtqKVR+gnLEtd2tytowIbas4TrpXNZ8DCula5l2VD0Od/atrBbp5/exp3wWVhYpnPR/TYuC22vx7W1nWqLh3KXPkhZwvo1Ddg2r8vxttShhkJDbAs0LQvXS98yUQPItdKvLCud/o+d3nOSLLQBBJBa6Gl4IOmCtw0U61FboJGNlTVoWUL7nVV3P+n4fK2u6P5QR/F51hT1BsxyoN+pwvWCpLhWupalrCiMNkKbzYWwrGjQQcTHnfRZWFimb1F0t73WY/2aOvQ01BDu0k9QloqG05uzpKgmcCWcu2vZ8rJwvfQsz5ai2j9XVNOU65pArpWO54nbHHZbBmoPaOHgADB0Fk1cvuVjHgcytKOpemgva2YLnmzKK4wQ1wuS4lpJj0fAAHIlPDKpS7pnZoXwmGepz27IKa4XJDVt1wq9gAEMXXgjfElhhoFwV5y4J1+G5Sip8zSEtOuaIFwvSIprZXA8AgYAAMgZHgEDAADkDAEQAAAgZwiAAAAAOUMABAAAyBkCIAAAQM4QAAEAAHKGAAgAAJAz/xPXX3LYuLEHRAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d_LUq-xf4ub0"
      },
      "source": [
        "## Fig.6"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nkYu59geNUP4"
      },
      "source": [
        "from sklearn.model_selection import KFold\n",
        "dataset = joblib.load('data/all_mutational.pkl.gz')\n",
        "n_iter = 500\n",
        "layers = 10\n",
        "fig_6 = pd.DataFrame()\n",
        "lst = {}\n",
        "kf = KFold(n_splits=5, random_state=1, shuffle=True)\n",
        "\n",
        "for k, v in dataset.items():\n",
        "    lst[\"dnmf_0\"] = []\n",
        "    lst[\"dnmf_1\"] = []\n",
        "    lst[\"dnmf_2\"] = []\n",
        "    lst[\"mu_0\"] = []\n",
        "    lst[\"mu_1\"] = []\n",
        "    lst[\"mu_2\"] = []\n",
        "    for train_index, test_index in kf.split(v[\"V\"].T):\n",
        "\n",
        "      data, n_components, features, samples = util.build_data(\n",
        "          v[\"V\"], v[\"W\"], v[\"H\"], index = train_index\n",
        "      )\n",
        "\n",
        "      for lam in range(3):\n",
        "        L1 = lam\n",
        "        L2 = lam\n",
        "        ##################### unsupervised performance #############################\n",
        "        _, _, dnmf_error, _ = util.train_unsupervised(\n",
        "            data, layers, n_iter, n_components, l_1=L1, l_2=L2\n",
        "        )\n",
        "        ###### MU ################\n",
        "        # train\n",
        "        h_mu = data.h_0_train.mat.copy()  # k*n\n",
        "        w_mu = data.w_init.mat.copy()  # f*k\n",
        "        for i in range(n_iter):\n",
        "            w_mu, h_mu = util.mu_update(data.v_train.mat, w_mu, h_mu, l_1=L1, l_2=L2)\n",
        "        # test\n",
        "        mu_test_iter = 10\n",
        "        h_mu_test = data.h_0_test.mat.copy()\n",
        "        for i in range(mu_test_iter):\n",
        "            _, h_mu_test = util.mu_update(\n",
        "                data.v_test.mat, w_mu, h_mu_test, update_W=False\n",
        "            )\n",
        "        mu_error = util.cost_mat(data.v_test.mat, w_mu, h_mu_test)\n",
        "\n",
        "        lst[f\"dnmf_{lam}\"].append(dnmf_error[-1])\n",
        "        lst[f\"mu_{lam}\"].append(mu_error)\n",
        "      \n",
        "    fig_6[f\"dnmf_0_{k}\"] = lst[\"dnmf_0\"]\n",
        "    fig_6[f\"dnmf_1_{k}\"] = lst[\"dnmf_1\"]\n",
        "    fig_6[f\"dnmf_2_{k}\"] = lst[\"dnmf_2\"]\n",
        "    fig_6[f\"mu_0_{k}\"] = lst[\"mu_0\"]\n",
        "    fig_6[f\"mu_1_{k}\"] = lst[\"mu_1\"]\n",
        "    fig_6[f\"mu_2_{k}\"] = lst[\"mu_2\"]\n",
        "fig_6.to_csv('data/outputs/fig_6.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Wm5YcSbkzF-Z",
        "outputId": "a1414183-210c-49a0-c2f3-f5c61455ec46"
      },
      "source": [
        "fig_6 = pd.read_csv('data/outputs/fig_6.csv')\n",
        "for x in range(1, 13):\n",
        "  df = fig_6[[f\"dnmf_0_{x}\", f\"mu_0_{x}\", f\"dnmf_1_{x}\", f\"mu_1_{x}\", f\"dnmf_2_{x}\", f\"mu_2_{x}\"]]\n",
        "  df = pd.melt(df)\n",
        "  df['method'] = df.apply(lambda row: 'DNMF 'if row.variable.startswith('dnmf') else 'MU', axis = 1)\n",
        "  if x>9:\n",
        "    df['lambda'] = df.apply(lambda row: row.variable[-4:-3], axis = 1)\n",
        "  else:\n",
        "    df['lambda'] = df.apply(lambda row: row.variable[-3], axis = 1)\n",
        "  df['value'] = np.log(df['value'].values)\n",
        "  plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
        "  sns.boxplot(x='lambda',y='value',data=df,hue='method')\n",
        "  plt.ylabel(\"$\\log({MSE})$\")\n",
        "  plt.xlabel(\"${\\lambda_1,\\lambda_2}$\")\n",
        "  plt.legend([],[], frameon=False)\n",
        "  plt.savefig(f\"plots/fig6/unsupervised_performance_{x}.pdf\")\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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tJC90Q8a/vttCN7DlfsLdAs+bLjdTVWvLv3xjhDUBAEy9YQLgqW5rt61cymBIeKW1drTbE3ih2xf4L5KsjigEzidJVW0ZApNcqapXH5wMUlXnMgizp/X+AQB9M+qt4BaTtGzQq9Zau1hVbyW5nuTxYS7aBbgrGTzXN59Pev/eraqVDCZxXGmtXX/gnitVtbbjx9F1560k+YLwBwD00TABcNPJHklSVV/p/nivtfbXG7VprV2tqsWq+npr7c93euPuOb4zOy/1U+feS3J+N+cCABxEwwwBr1TVb27x/lpA225G7XeTnB3ivgAAjNAwAfBqkq167daGf5e2ukj3HOHCEPcFAGCEhlkIejnJzar6owff65aIOdX9upM19d7d6X0BABitYSeBXMwgBJ7OYFHoNzMIftcy6P1baa29M9IKAQAYqaECYGvtvSQnq+rVJD/KIPQlgwki97KDZ/u6tQJXhqwTAIAR2dUyMK21s1W1mEHgeySDXTeudgFxOy9k0HsIAMAE7HodwO6ZwKH20K2q7yap1tpf7fa+AADszagXgv6UqvrjJF/KYHh4MYOFmE+P854AAGxtrAGwtfZCVX02g/D3bne8WVVnW2t/Mc57AwCwsbEGwOTjiSM/6n7WtnX70rjvCwDAxsYeAB/Ubeu2ut/3BQBgYMcLQVfVb42zEAAA9scwW8G9OrYqAADYN8MEwPmxVQEAwL4ZJgBWVf2Hqnp4bNUAADB2wwTAJHkxybtV9UZVfbeqvjyOogAAGJ9hAuB7Sd7OYN/f00meT7JUVR8OGwir6neGLxUAgFEYJgB+IYOt3852P3+ezQPha1X17S1mDl/bQ80AAOzBjtcBbK3dS/LNqvpqkoUk/2tr7efrdvo40x3nkzzR/Z6qSgbBcSnJUmvt/07yyCj/RwAAsHPVWhv+pEHo+06S//Lglm7rAuETGfQUznVvfepGrbVDuyl4khYWFtqNGzcmXQYAwLaq6mZrbWGj94adBJJksL1ba+2FJO9V1Z+unxncvfej1tr51trRJCeSnM9gK7j3MhgyBgBgQnYVANe01l5vrf1ukt+vqq9v0ubt1tq11trTXSB8Yi/3BABgb/YUANd0vYE3u97Az2/TdnkU9wQAYHdGEgCTpLX2ZtcbeHaz3sB13h7VfQEAGM7IAuCa1tr3krxeVX+2xTIwZ0Z9XwAAdmbkATD5+Lm/byZ5vKq+vdH747gvAADbG0sAXNNau5bk2ja9gQAA7KOxBsDk42VhvpnkRFV9d9z3AwBgazveCWSnujUBFzLYEeREd1z7mauqbyQ521r7z6O+NwAA29tVAOyGc9dC3YMh71NNNzj9XpKnkwiAAAATsOMAWFX/KYOevbkH33rg93tJVtf9vLH259bae7svFQCAURimB3D90i3rA95b3XHF7F4AgOk37BDwSpI/S7LcWntn9OUAADBuwwTAluSpJKeTvFBVX8hguHcpAiEAwMwYJgC+14W8d5L8KEmq6rNJFvNJIFzNJ4Hw55tdqKp+0Fr72m6LBgBg94YJgBcffKGb1PGj/GogfHGbQPjUrisGAGBPdhwAu109tmuzUSB8Osmfd39ezWAmMQAAEzLyhaDX6wLhte4nVfWlJP/TOO8JAMDWxr4V3HqttTeTnN3PewIA8Gn7GgCTpLW2msSC0AAAE7LvAbDzjQndFwAOtDt37uRb3/pW7ty5M+lSmGITCYCttR9N4r4AcNC9/PLL+clPfpJXXnll0qUwxSbVAwgAjNidO3fy2muvpbWW1157TS8gmxIAAeCAePnll/PRRx8lST788EO9gGxqywBYVV+oqq/vVzFV9XBVfXu/7gcAB8ny8nLu37+fJLl//36WlpYmXBHTassA2Fp7O8nbVfWnVfU/jrOQqvpKkmuttT8Z530A4KBaXFzM4cODJX4PHz6cM2fOTLgiptW2Q8CttdczWMj5zar696MuoOv1+2GSp+wPDAC79+yzz+ahhwZ/tR86dCjPPPPMhCtiWu3oGcDW2koGW7g9XlV/U1Vfr6qH93LjqvqtLvjdTPJ/ttZ+dy/XA4C+O3bsWJ588slUVZ588skcO3Zs0iUxpYbZC/hekm9W1XyS55NcraqbSZaTvJXkRpJ7Se621n6+dl4XFI8mOZVkPsnjSRYz2Bf4amvt6RH9bwGA3nv22Wfzzjvv6P1jS9Va2/3JVV9NciaDQDffvbzRBas7LidZSnK9e75wpiwsLLQbN25MugwAgG1V1c3W2sJG7+24B3Aj3YLOHy/qXFWfzaC3b6473k1ybxbDHgDAQbWnAPig1tp7sc8vAMBUG2kABBiHy5cv59atW3u+zu3bt5Mkx48f3/O1Tp48mQsXLuz5OgCTMJIAWFW/lcFQ7zujuB7AOHzwwQeTLgFgKoyqB/DFJD9M8uc7PaHbYeTFJJ9NspLkK+tnDwOsGVVP23PPPZckeemll0ZyPYBZNaq9gJdaa8OEv68muZLkYpKTSV5N8vqIagEAYAsjfwawqr6cwZIwN1prf71Js0sZLAVzrfv9xapqVfXl1tpfjbomAAA+MaoewOVuv+A7GazzdzXJzar6L1X16xu0n8+gB/BjrbXvJTk7onoAANjEKHsAz6cLfhms/3c0yRMZLP78xbVGVfWlDBaL3mhFZUvIAACM2agC4AtJTmyw4PO1qlqsqm+31v6ke+1okmwy4WP325IAALAjoxoCfnuz3T5aa8v5ZCs4AAAmbFQB8B+3eV/PHgDAlBhVADxZVb+50Rvden/31r00t8V1HtnJzapqrqpuDlHfRtfY0/kAALNqlAtB36qqv0zyZpI7SY4lWUxyKl2wq6qHM5gs8l5V/c+ttf+8doFu+ZgtQ1lVzSU5l+Q7eym2qp7v6gIA6J2RBMDW2mpVLWSwoPMT695aTrKQ5HxVPZ5B6FrKYLmX16vqq621v62qz2ewLMzpja5fVYsZrB242rVbzWApmaFV1Xz2GCABAGbZyJaBaa2tJDlRVV/IIJytrpsY8uaD7avqhSRvV9VbXfsnNtsKrptIcnrduXezywCYQQ/kcpKndnk+AMBMG/lOIF3o23BG8APtlqvqZJIvJVlurY19DcCqeirJDzIIgQAAvTTyADiM1tpqBsO5Y9c9PzjfWrteZVUaAKC/xrEX8MMZTNRYe+ZvNYPJHVdba++M+n5D+E5r7eIE7w8AMBVGGgCr6tsZTNZY38V2IsmZJBer6vnW2v82ynvusK5TSd7Y7/sCAEyjUa0DmKr64yTf7H5OZLD0y9rP6SR/kuQ/VtX/Pqp7DuFrrbXrE7gvAMDUGUkPYFV9Kcmp1trJTZq82f1crKofVtWXW2t/NYp776C255N8dw/nn8tgSDuPPfbYqMoCAJiYUfUAnmutPbF9s6S19nQG6wCOXbfm373W2r1tG2+itXa1tbbQWlt49NFHR1gdAMBkjCoADjutduxLvnQuttau7tO9AABmwqgC4K0h27cR3XdT3dDtlXHfBwBg1owqAJ4Y0XVGolvz70S3OwkAAOuMahmYlar6emvtz7drWFXfTXJnRPfdzGKSxapa2uT9ha6Wm0nuJklr7cyYawIAmAojCYCttWtV9ZfdpIsNF3yuqt/KYAu2hdba46O47xb1XE+y6bIvXTBcbK2d3qwNAMBBNcqFoM8meT2DpV5Wk9zLoHftaJL5JHNJVpI8PcJ7AgAwpJEtBN1ae6+1tpDkdzOY5Xs6gx1ATid5N8kLrbXHW2tvj+iWcyO6DgBAr4x8L+Bu2ZWrSVJVXxhh4Ftvvrv+3C7X+Du6x/MBAGbWyHoAN7JZ+Kuqrw9znaqar6qlqrpZVe+mC4BJ3u1eW6qqp7a5xmLXtiU5te78t6rq0jD1AADMspH3AO7QxSTbzhhe01pbzWA4eddaa8sZDEcDAPTajgJgVX013dIpIzCXT3rwAADYZzvtAZzPoNduVMa+EwgAABvbaQC8l2Sptfa/jOKmVXV3FNcBAGB4O50EsprkzRHe98YIrwUAwBB21APYWns9g0WeR6K19sSorgUAwHDGugwMAADTRwAEAOgZARAAoGcEQACAnhEAAQB6RgAEAOgZARAAoGcEQACAnhEAAQB6RgAEAOgZARAAoGcEQACAnjk86QKAg+vy5cu5devWpMv42Fotzz333IQr+bSTJ0/mwoULky4D6BEBEBibW7du5a//63/Lh585OulSkiQP/UtLktxc/YcJV/KJQ+/fnXQJQA8JgMBYffiZo/ngN3570mVMrSM//fGkSwB6yDOAAAA9IwACAPSMAAgA0DMCIABAzwiAAAA9IwACAPSMAAgA0DPWAQSAPRjVjje3b9/OBx98MIKKRufIkSM5fvz4SK5lx5vpIgACwB6Masebh/75/dRH/zqiqkbjF//S8ve/3PvOOXa8mT4CIADskR1vtmbHm+njGUAAgJ4RAAEAekYAJEly586dfOtb38qdO3cmXQoAMGYCIEmSl19+OT/5yU/yyiuvTLoUAGDMBEBy586dvPbaa2mt5bXXXtMLCAAHnABIXn755Xz00UdJkg8//FAvIAAccAIgWV5ezv3795Mk9+/fz9LS0oQrAgDGSQAki4uLOXx4sCTk4cOHc+bMmQlXBACMkwBInn322Tz00OCjcOjQoTzzzDMTrggAGCcBkBw7dixPPvlkqipPPvlkjh07NumSAIAxshUcSQa9gO+8847ePwDoAQGQJINewO9///uTLgMA2AcCIDA2t2/fzqH337MR/BYOvX8nt2/fn3QZQM94BhAAoGf0AAJjc/z48fz9Lw/ng9/47UmXMrWO/PTHOX78c5Mugz3Q0709Pd3TRw8gAEDP6AEEgD3Q0709Pd3TRw8gAEDPCIAAAD0jAAIA9IwACADQMwIgAEDPmAUMAHt06P27e14H8KF//nnqo38dUUWj0R767/LRv314z9c59P7dJGYBTxMBEAD24OTJkyO5zu3b9/PBBx+M5FqjcuTIkREt3/K5kf13YjQEQADYgwsXLky6BBiaZwABAHpGAAQA6BkBEACgZwRAAICeEQABAHpGAAQA6BnLwABjNYoFckfloX/+eZKMZGHbUbFALjAJMxkAq2ouyeuttdM7bP98kse7X+e646XW2vI46gMGpm3h11u3fpEkOTk/TYHLArnA/pupANgFv3NJvjNE+2tJvttae3Hd64tJlqrqemvt7FiKBaZugdznnnsuSfLSSy9NuBKAyZqJZwCrarGqbmYQ5laSrO7w1GuttbOttZX1L3Y9fy8meaqqzo22WgCA6TYTAbC1ttxaO92FueUkd7c7p+v9e6qqljZpsva6HkAAoFdmIgDu0tHuuLDJ+2shcn4fagEAmBoz9QzgMFprq1V1Ipv3Fq4Fv5VN3gcAOJAObABMBiFwi7fPdMcr+1ELAMC0OMhDwJtaN5v4qqVgAIC+6V0AXFtDMMmLrbXzk64HAGC/Hegh4DVVdSrJ15KcymBSyDdaa9d3eO65DHoL89hjj42tRgCA/dKLHsDW2kpr7WJr7Uxr7ZEkR6vqrW5B6O3OvdpaW2itLTz66KP7UC0AwHj1ogfwQa21q1WVDHYDOd9auzrpmgAA9ksvegA30oW+e0muVJW1AAGA3uhtAOzc6I5PTbQKAIB9dGADYFW9WlXvdhNANrO2TuDj+1ETAMA0OLABMINevblsvhVc8sluIG+MvxwAgOlwkCeBLCd5dZsJHgvr2gIA9MIs9wDObfP+pSQnNnuzqtZ6CK+31uwHDAD0xqwGwPnk4109NtRt8fZG9yzgp2b5duv/XUuy3Fo7O9ZKAQCmzEwMAXcB7kqSoxmEv7Xg925VrSS5m+TKg7t7tNauV9Vyku+sC4Fr5+54NxAAgINkJgJga201yZldnnsvycXRVgQAMLtmdQgYAIBdEgABAHpmJoaAgX67fPlybt26tefrrF3jueee2/O1Tp48mQsXLuz5OgCTIAACvXHkyJFJlwAwFQRAYOrpaQMYLc8AAgD0jAAIANAzAiAAQM8IgAAAPSMAAgD0jAAIANAzAiAAQM8IgAAAPSMAAgD0jAAIANAzAiAAQM8IgAAAPXN40gX01eXLl3Pr1q09X+f27dv54IMPRlDR6Bw5ciTHjx8fybVOnjyZC6mKTn8AAAsoSURBVBcujORaAH1w586d/OEf/mH+4A/+IMeOHZt0OUwpAXBCbt26lb/+r/8tH37m6J6u89A/v5/66F9HVNVo/OJfWv7+l/+w5+scev/uCKoB6JeXX345P/nJT/LKK6/k937v9yZdDlNKAJygDz9zNB/8xm9PuoypdeSnP550CQAz5c6dO3nttdfSWstrr72WZ555Ri8gG/IMIAAcEC+//HI++uijJMmHH36YV155ZcIVMa0EQAA4IJaXl3P//v0kyf3797O0tDThiphWAiAAHBCLi4s5fHjwdNfhw4dz5syZCVfEtBIAAeCAePbZZ/PQQ4O/2g8dOpRnnnlmwhUxrQRAADggjh07lieffDJVlSeffNIEEDZlFjAAHCDPPvts3nnnHb1/bEkABIAD5NixY/n+978/6TKYcoaAAQB6RgAEAOgZARAAoGcEQACAnhEAAQB6RgAEAOgZy8BMyO3bt3Po/fdy5Kc/nnQpU+vQ+3dy+/b9SZcBAAeOHkAAgJ7RAzghx48fz9//8nA++I3fnnQpU+vIT3+c48c/N+kyAODA0QMIANAzAiAAQM8IgAAAPSMAAgD0jAAIANAzAiAAQM8IgAAAPSMAAgD0jAAIANAzAiAAQM8IgAAAPSMAAgD0jAAIANAzAiAAQM8cnnQBfXbo/bs58tMfT7qMJMlD//zzJMlH//bhCVfyiUPv303yuUmXAQAHjgA4ISdPnpx0CZ9y69YvkiQn56cpcH1u6v47AcBBIABOyIULF0ZyncuXL+fWrVsjudaonDx5cmT/+wCA0RMASZIcOXJk0iUAAPtEAJxxetoAgGGZBQwA0DMCIABAzwiAAAA9IwACAPSMAAgA0DMCIABAzwiAAAA9M5MBsKrmqurmEO0vVdVSVb3V/bxaVafGWSMAwLSaqQDYBb/nk7ydZH6H7V9N8oPW2pnW2okkp5PcTXKzqq6Mt2IAgOkzEwGwqha7Hr9rSVaSrO7w1GtJLrbWVtZeaK3da62dT3I1ybmqOjfyggEApthMBMDW2nJr7XRr7WxrbTmDHrwtdUO8b7TWNguLF7vjlaqaG1WtAADTbiYC4C59Lcn1zd5srd3LoDcxSRb3pSIAgClwkAPgqQye83tqizZrvYNH96EeAICpcJAD4L0kc0ke36LN2tDvTp8pBACYeYcnXcAYfSPJle6Zwc0sdMcb+1APAMBUOLABsHvGb9PwV1WLGfQALndtAQB64SAPAW9nbRbw+a0aVdW5qrpRVTd+9rOf7UNZAADj1csA2E0MWUxydotlYpIkrbWrrbWF1trCo48+uj8FAgCMUbXWJl3D0KpqKclCa+2RXZw7l8FOIt9trb045Lk/S/K3w96TPfm1JP846SJgzHzO6QOf8/336621DXuvDuwzgFt4PcnVYcNfkmz2H5HxqaobrbWF7VvC7PI5pw98zqdLr4aAu57D5dbaxW0bAwAcUL0JgFV1JcmK8AcA9F0vAmBVPZ/k3kbhr6rmun2DmU5XJ10A7AOfc/rA53yKHPhJIN2M3zOttQ2Xe+nWA8w2C0YDABwYs9wDOLddg65n7/HNwl/nTOwEAgD0yKz2AL6VZD7JI5vt4lFV80luZutwdzTJqdZajb5KAIDpNBMBsAtzVzIIbPP5dO/fSpK7Gez7e33dOUsZLPa8nZXW2ukRlssedEPyFzPYp3kug+38Lhmi5yDqJqe9tZtlqWDaVdW5DEbZTiW5l0GHzKXtNmBgf8xEAKQfqupSkue7X1czCPxrYf9FM7g5KLrHUy5l8I/UiwIgB0m34cLNDDpsNnK+tWZCyITN8jOAHCBdz99a+DvTWjvRTfI50732fDehB2ZSVT1VVTer6t0M/nLcyQgFzKLXMwh/LyY5kWTtu3yle/+K7/PJEwCZFpe649n1w73dn88/0AZm0XwGQ2F3M/iLccPnl2GWdf+YP5VBz/bF1tpqa+1ea225e9xq7fvd9/mEGQJm4rrhgnczWKtxw6V9ul6TuSSnW2srG7WBWVJVN/PJX5SGgDkQqurVJItbfJfPJ3mr+/WM57snRw8g0+Dp7rjVjO219wybAUyvHyT54WZvdhNA1nq/bcIwQQIg02DtOb+tevbW3nt8zLUAsEvdahzbTdi72x2PjbkctiAAMg3WZvre2aLN2nvbLgAOwORstj7vOmuzg9/ashVjJQAyDY52x62+NNbeO7pFGwCmWLcE0ppNh4oZPwGQaTBMr54eQIDZtTb798Ud9BQyRgIgADB2VfV8BhP5Vi3sP3kCINNg7V+BW/Xurb3nX4wAM6Zb+PlSBrs82X51CgiATIO72zf5eLbYTtoCMCW65/5eTRf+DP1OBwGQabD2ZXBiizZrs8Z8cQDMiC783YzwN3UEQKbBG91xYYs2awHwjS3aADAlul0/Xo/wN5UEQKbB2lZAp7pt4T6le+3UA20BmFJd+LuZwWM7wt8UEgCZuG5v39Xu1+9s0ORcd1y1DzDAdBP+ZoMAyLQ43x2f72aLJUmqajGfrBtl2QCAKdaN2Ah/M6Baa5OuAZIkVXUpyfPdrw8uDfOidaOYZd3D8JfWvbTYHVfzSQ94WmtnAjOqqq7kk1Gb7VxtrZ3fvhnjcHjSBcCa1trFqlrKoKdvMYMQuJzkUmvNs3/Muvl8EvoefH1+g9cBxkYPIABAz3gGEACgZwRAAICeEQABAHpGAAQA6BkBEACgZwRAAICeEQABAHpGAAQA6Bk7gQCss24v6pXW2uqWjSdg2usDZoMeQIBPW07ytSRvVdXz2zWegGmvD5gBtoID2EBVrX05npjGnrZprw+YbnoAATZ2vTuen2gVm5v2+oAppgcQYANVtZhkKcm91tojk67nQdNeHzDd9AACbKC1tpzkXpK5LmxNlWmvD5huAiDA5q52x2kdZp32+oApZQgYYBNVNZ/krSRprdWEy/kV014fML30AAJsoptdu5p8av29qTHt9QHTSwAE2NqV7jitw6zTXh8whQwBA2yhquaSvNv9+khr7d4k63nQtNcHTCc9gADbWwtV57ZrWFXzE9ihY9v6qmqxqp6vqktV9apdRKDfBECATXS9a6/nk9m2X9um/XwGa/MdG3Npa/fbUX1ry8S01l5srV1srZ1N8nhVLe1HncD0EQABNtCFq5tJvttau9i9fKoLeb/StqouJXkq3aSMaaovyalu3cD1vpFk0eQR6CcBEOAB68LVldba2pZrm66511q71/WsvZhPhmOnpr4kX3swGHbPCq4mOTO2QoGpJQACrLMuXC13gW7Nq91xoj1mu6xvLsmpcdcGzA4BEKCzLlytttY+1ZO2buu1+aqaSJjabX2ttRPregrXX2vtmUWgZwRAgHw8geNmkrTWNhsWndjWa2Oo71wGQfL6ti2BA0cABHpvXbg6muT0Fk3XFl1+eo/3W+p+5iZRX3e98/H8H/SWAAj02rph1bkkX9lqIeVu67WVJHO7nT3bnbfY/XxnQvW9muRs1x7oIQEQ6LuF7nimtbayg/bf6I6Xdnm/5Qxm365m8AzedkZaX1VdSfKNHV4LOKBsBQcwQlX1agbP1l3cQdsrD07mGKdu94/l9eGvquZsHwf9owcQoAe6IeGVDXr+tt3eDjh4Dk+6AIA+6iZivLVP91rMYLj5enfftckn89mHhauB6WMIGGAEuq3g5jNYiPleumf9NhsK7p7Fuzju4dduEsm7WzQ57XlA6B89gAAjsJNn/tZ0CzXf249n77p71LjvA8wWARBg/53fz8kfAA8yBAwA0DNmAQMA9IwACADQMwIgAEDPCIAAAD0jAAIA9IwACADQM/8/KH6AFjHyAgwAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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wYCYmJvTDH/6Q3koApVfoYClJ7r4kaT3svvNU2OKxqoOJPc0m+HSiKmk6vIMJAABQeEV/x1JSEi7NbNrMLoVTNYX9vc1sPpyLvVNOWt9kD+oGAAAYOKUIltLT4emdBpfSHsWtLPWZ2WSLbRvTHlB6LAEAQCl0HSzN7CVJFUmndbC0z3g4pkPN9yTdlrTj7j/v9p6RzSppV9tD4Wa2ImnBzOabbOGYzjJvtjg7AABAYXQULEOYfFPJHtufk3RHSYishu/TiTATSgLWhKRXJH3HzD4naVPJjOq/76LtXQt7iY/pYPZ4u8aVBOZmYTTtqWQ9SwAAUAqZgmUIlKuSZiRdlTTv7jcz1jEp6VVJb5rZVUmX3P3vstSR8V63Ja27+3yDIotK1qFczVj1R5KWWgyFV8J9Y08KAgAAGEhtzwo3s+9L2lDS0zjh7m9nDZVSsgSQu19199eUDJ9/ycw+MrMvZq0rg+cCYOitXJDUKHCmZVbMbO3wPuJh4fOlJp9Llxm60FlzAQAAhk9bwdLMfibpN+7+JXf/MNbNw1qQb0t6XdJVM/t6rLpD/VVJ6zo01B2WGlqTNBcm9TwnLG6+oGQNzHMNiqShc/LQ5xbC52borQQAAGXScijczH4sadHd7/SqESEAvmZmf21mX4s8weeCpHdCD6WUvPu4qRbBz903zSwNndcbXN8xs3SHnXSykpTMPD9FqAQAAGXTNFia2Skl7xI+6Edj3P0HZvZy5DprajJs3eKzM23UvdhJ3QAAAEXTNFj2speyyT0/7vc9AQAA0L22Z4Wb2TeVrMlYVTKT+rc9axUAAACGTpblhlYlefh+x8zuKVnH8YO816MEAABA/rIukL4jqdLOO5dm9g0lazkuu/unHbQNAAAAQyRrsGx7Io+7fxhmVV8Ou+382N3/V+YWAgAAYCi0vUC6JM+6DJC733H3c5L+QtLfmNmemf2Vmb2QqZUAAAAYeFmCpXV6k7DbzqySxcp/oAY74QAAAGC4ZQmWzy34bWafM7Nvm9lX2qnA3Rcl3ZH0Yob7AgAAYAhkGgp/7kTyvuVNSW+a2WMz+8c2guZyk2sAAAAYUlkn7zwnLGj+pplVJX1f0rikKTN7Uclkn08PfeQDST/q9r4AAAAYLF0HyzorSoLlq80WT3f3B2Ydv64JAACAAZVlKLypMCxea3NHnr7sPQ4AAID+yRIsXzSzL7coc6/NutotBwAAgCGRtcdyJ6xF+SMz+3qD9Sifm+BzhHbLAQAAYEhkfcfSlCwVtBC+FCbtbEjajNs0AAAADJOswXJO0qSkeUmzksYknQ7nFiXJzP5NScjckLTZ5juXAAAAGHKZgqW731SybuVVSTKzlyVVlATOSiiWBs36Hs1NSWuStkLQHI/ReAAAAAyOLMHy8uETYQ3Lj5Vs05glaI513mQAAAAMorYn77j7222U+djdf+Dur7n7MUkzkpaUhE8LX6c7bSwAAAAGV7R1LBupC5qzIWjOSfqwl/cEAABAPmLuvNNS+o6mmT3u530BAADQez3tsWyCnXcAAAAKJq9guZTTfQEAANAjuQRLd7+ax30BAADQO3n1WAIAAKBg2p68Y2bXlezx/TNJa+yoAwAAgHpZ1rE8J6kmaVXSfTP7NzP7kZl9rWetAwAAwNDIutzQjyW9KmlFUlVJ0LSjCpvZC/RsAgAAlEOWofBTklbdfapFuZeU7As+HX6uSVpx9+903kwAAAAMuiyTd76vsN/3UcJe4beVhMoHkm5KuiPp7TB0/sVOGwoAAIDBlmUofNrdP25RZlnJ0Pi2u79Sf8HMliVVzWzS3X+VsZ0AAAAYcLG3dKwomTl+4fAFd18ys9uS1iW9cvg6AAAAhluWofAjJ+lIkpm9Gr6tufsvGpVx91VJd8zsmxnuCwAAgCGQJVjumNmXm1yfC8fNFvW8K2k+w30BAAAwBLIEy1VJP2lyPR0G32hWSXhPczbDfQEAADAEsiyQvilp28z+x+FrYSmi6fBjqx5LSbrf7n0BAAAwHLJO3llSEi5nlCyW/rGSQHlVSW/ljrt/GrWFAAAAGAqZgqW7P5A0ZWZrkj5UEialZGJPTW28OxnWutzJ2E4AAAAMuI6WG3L3eTOrKAmSL0r6SMmuPA/a+PjbSno7AQAAUCAdr2MZ3rls533Kp8zsXUnm7j/v9L4AAAAYTLEXSH+GmX1f0stKhskrksYkzfTyngAAAMhHT4Olu79tZp9TEirvh+O2mc27+9/38t4AAADor54GS+nphJ8Pw5fMbFJJLyYAAAAKpOfB8jB3r0qq9vu+AAAMm5GH93T8lz/NuxmSpGO//60k6cmfvJBzSw6MPLwn6Qt5NwN12g6WZvaVo/YABwAAcU1NTeXdhGfcuvU7SdLU5CAFuS8M3P9OZZelx3JN0pd61RAAAHDg4sWLeTfhGW+99ZYk6b333su5JRhkWYLlZM9a0QdmdlbS64dOL4Wh+W7rnZN0W9KEkpnvy93WCwAAMGyyBEszs7+SdNXdf9urBvVC2ClozN3n6s5N62CGeqb1OOvqWJEkd1+sOzcW6l3stF4AAIBhdCxj+cuS7pvZR2b2rpl9rReNisnMliVV6kOlJLn7jpK9z9dCGMxa71lJ5+pDZai3Jmmx03oBAACGVZZg+UDSHSX7gs9IuiRpw8weZw2aZvb17E3NLvRKXpK02ui6u68qGbpe6KD65Sb1bkq6J+mdDuoFAAAYSlmC5SklWzjOh6+f6OigecPMvm1mXzmirqtdtDmLtDdxo0mZnbpybQmBdVLJHunN6u0ksAIAAAyltoOlu9fc/c3w46ykv3b3KUkvKgmaV3UQNF9T0qO3HYLmP4ag+eXw+Rej/Rc0NxuO95qUqUqazDhsXan7bLN6x8KC8AAAAIWX9R1LufuHkr4v6Ttm9nV3f+DuH7r7m4eC5k+UDJ+bklnTy5J2zOyxJI/2X9BcGhZrTcqkoXO2SZnDXgnHZsFyLxynM9QLAAAwtDIHSynZptHd35b0wMx+ZGYvHLr2obsvuvu4pNNKhpo/1EHQ7JedcGynNzJLz2I79aVhdjxDvQAAAEOro2CZcveb7v4XSnovv3lEmTvuftXdz4Wg+Vo398wo7VFsFu7SQJllKHxcejoDvBVmhgMAgFLoKlimQu/ldui9fKlF2X6u7bgSjnNNyqRD4BMZ6s0SFrPUCwAAMLSiBEtJcvePQ+/l/FG9l3XuxLpvizZVlay9ebbRdTNbkHQ9/LjXqEyvmNmCmW2Z2dbdu3f7eWsAAICeiBYsU+7+A0k3zezHTZYbataDGLs9S5LWw+47T4UFzqs6eBeynWHtVC3U0U7PZcPA6u6r7j7r7rMnTpzIcGsAAIDBlGVLx7a5+x1Jb5rZBTOruPvfNrjeN+6+ZGbTZnYpnKpJ2nT3qpnNh3O92ts7S2AFAAAYWj0Jlil3v2pmnzOzH0v6sbv/opf3a9GWHR3MEq+XTt7ZylBdVckyQuM6OjimvZnN1tAE0IErV67o1q1bXdezu7urR48eRWhRPMePH9fJkyej1DU1NaWLFy9GqQsA2tHTYCklyw8p6b38hpm97u6Dts3hrKSdNmd4pz5S8t7mpI7u6Twdjo3CLIAu3Lp1S7/4l3/V4892t5rXsd8/lD35Y6RWxfG7/3D9+x9+3XU9Iw/5mxZA/0UPlmFNy1kloet0OKZfY2Z2QdK8u/9T7HtnFbZmHNPB7PF2pTPbm71jOSmpFiYQAYjs8WfH9ehP/zzvZgys47/8ad5NAFBCHQXLMCknDYuHw+MzRRt8vCbpnKSeB8uwneJtSevuPt+gyKKkqruvZqnX3XfMrKZkEtL6EcUqSmakAwAAlELbwdLM/lFJT+ThXrrD4bGmZHg4/foo/T4Mi+fhuV7D0Fu5IGnmqA+Z2YqS9ygvNBgqvyDpqpktHb4WZpzXJL3bbcMBAACGRZYey/olguqD4+1w3On3bO9WwqzvdR0a6g7Bb1nSXJjU8xwzqygJnpK0IemZXk13XzezOUlXleyNnn5uLNQ9n/G9TQAAgKGWdSh8R9KPlSzV82n85vTEBUnvhB5KKRmu35Q00yz4ufummaWh8/oRZRbN7Gzo2UzrGlMSWHm3EgAAlEqWYOlKZkLPSHrbzE4pCVMbGuCgGcLjUoefPXKYvK7Muo5+zxJAD+zu7mrk4QMmqDQx8nBPu7v7eTcDQMlkCZYPQnj8VNKHkmRmn1MySSUNmlUdBM3fHlWRmX3g7q932mgAAAAMnizB8rlevzAZ50M9HzQvtwiaDffuBoB2nDx5Uv/+h1GWG2ri+C9/qpMnv5B3MwCUTNvB0t2vtlGmUdA8J+kn4fuqkpnlAAAAKJheb+n4QMms6auSZGYvS/ovvbwnAAAA8nGsnzdz949VtzQPAAAAiqOvwVJK1paUlNdC6QAAAOiRvgfL4EJO9wUAAECP5BIs3f3DPO4LAACA3smrxxIAAAAFQ7AEAABAFE2DpZmdMrNv9qsxZvaCmX27X/cDAABAPE3XsXT3O2Z2x8x+JOmSu/+uVw0xs1clLbDVI4B2jDy81/Ve4cd+/1vZkz9GalEcfuw/6cmfvNB1PSMP70li5x0A/dVygXR3v2lm9yV9bGbvuvvfxWyAmb0g6SeS9giVANoxNTUVpZ7d3X09evQoSl2xHD9+PNJWjF+I9r8TALSrrZ133H3HzGYlfd/M3pa0LOn6of2/MzGzr0j6jqSXJS25+993WheAcrl48WLeTQAANJBlr/CapDfNbFLSJUmrZrYtaVPSbUlbkmqS7tUHztAjOS5pWtKkpFckVZTsG77q7uci/bcAAAAgR5n3Cg8757ypJGR+Q9KcpLeVhEZJcjM7/LH0xKakDUlvu/udjloMAACAgZQ5WNYLC50/XezczD6npHdyLBzvSaoRIgEAAIqvq2B5mLs/EPuAAwAAlBILpAMAACCKKMHSzL5iZi/FqAsAAADDKVaP5WUlM73bZmbfNLN7ZvbYzD4Ks8cBAAAwpGIFyw13/0m7hcNs8hVJS5KmJK1JuhmpLQAAAMhB1Mk7kmRmX1Oy9NCWu//iiGLLktbd/Wr4+bKZuZl9zd1/HrtNAAAA6L1YPZabZvYjM9tTsk7lqqRtM/vfZvbFBuUnlfRYPuXuP5A0H6k9AAAA6LOYPZaLCoFSyfqV45JeU7Io+pfSQmb2siRXslPPYSxVBAAAMKRiBcu3JZ1usBD6VTOrmNm33f1vw7lxSTpin3GP1B4AAAD0Wayh8DtH7a7j7ps62NIRAAAABRUrWP6mxXV6IgEAAAouVrCcMrMvN7pgZt+UVKs7NdaknhcjtQcAAAB9Fusdy8uSbpnZzyR9LGlP0oSSRdOnFQJjWAR9UdIDM/uv7v5PaQVhmaLtSO0BAABAn0UJlu5eNbNZJQudv1Z3aVPSrKRFM3tFScjcULKs0E0z+4a7/ypsB7kiaSZGewAAQOLKlSu6detW1/Wkdbz11ltd1zU1NaWLFy92XQ8GT7Tlhtx9R9JpMzulZJ3Kat2Eno8PlzeztyXdMbPbofxrR8wUBwAAOTt+/HjeTcAQMPf85tWY2aSklyVtuntp17CcnZ31ra1Gy3oCAAAMFjPbdvfZRteib+mYhbtXJVXzbAMAAADi6MVe4S9IWpCUvlNZVTIpZ9XdP419PwAAAAyGqMHSzL4taVnPLoh+WtKcpCUzu+Tu/zPmPQEAADAYogVLM/u+pLOS3lQyG/xe3eVJSf9d0t+Y2Wl3/8tY9wUAAMBgiBIszexlSdPuPnVEkY/D15KZXTezr7n7z2PcGwAAAIMh1s47C+7+WutikrufU7KOJQAAAAokVrC01kWeUdqlhQAAAIoqVrDMuqR/fotnAgAAoCdiBcvTkeoBAADAkIoVLHfM7JvtFDSzdyXtRbovAAAABkSUWeHuftXMfha2aGy4ELqZfUXSoqRZd38lxn0BAAAwOGIukD4v6aaSJYWqkmpK1rIcV7KO5ZikHUnnIt4TAAAAAyLWULjc/UHYkPwvlMz6nlGy486MpPuS3nb3V9z9Tqx7AgAAYHBE3yvc3VclrUqSmZ0iSAIAAJRDtB7LRo4Kle1O9InNzBbMbC18bYSvShf1TYY6FsL7pfXn03tNNqsDAACgKBGIi7QAABNGSURBVKL3WLZpSdJP+nlDM1uT9IG7z9edG5N01czm3X2xg2rHJFXCl8yeWSe+KmnO3audtxoAAGB4tBUszewbkmYj3XNMyWSevjGzFUnvuvtO/Xl3r0maT3sdwzB+VutKJilNKpmotCVpw93Xu203AADAMGm3x3JSSS9jLP3eeafSokdyWcl/XyfBcqPDQAoAAFAo7QbLmpIA9d9i3NTM7sWop817pT2JzVTV515UAACAoml38k5V0scR77sVsa5W7kkaM7NLTcpMK1ljEwAAAB1qq8fS3W8qWfw8Cnd/LVZdbdyrZmY7kpbNbMLdnxnSDxN4lpWsuQkAAIAO5TUrvN/mJW1LumRmZyXNu/tOCJVrkha7mb0dhtvP1p2aUPLqwGY3jQYAABgmpQiW7l41s1NKel2nJW2bWTpru6tQqaSns+rul+tPmtm2mX1w+DwAAEBR9XSB9EESlhZ6Vcn7olLSw9jthJ2qpJUjeiYvKBl+b7gAe1hAfcvMtu7evdtlMwAAAPJXmmAZAt5VHexfXlXSe3nbzBY6qdPda0cNd4c1M6tK3t9sdH3V3WfdffbEiROd3B4AAGCglCJYhuC46O7z7l519x13Py0pHaZeaTFrvFNVSdNs6wgAAMqg8MHSzKYlLdVv5ZgKM8RnlKzTudyDAJgOuxMsAQBA4RU+WCoZim44HC09HbKeCT+ePapcI20E0Vo4EiwBAEDhlSFYVtRiQfYwK3xV0ivtVhr2H78dli86ylg49m2nIQAAgLyUYrmhNt3WQQ9jO8ZD+WafSXsqWc8SAAAUXhl6LHckzbZRbk7SRoZ6P5I002IR9Iqk9bDUEQAAQKGVIVim60mOHVUgLEXUcOkgM1sxs7XDnw8Lny8dLl/3ufS9zgudNRsAAGC4FD5Yhsk5F5TstvPc+5BhmaElNQiAIXAuKJnUc65B9WnonDz0uYXwuRl6KwEAQFmU4h1Ld183s01J75jZYjidBr4P3H3uiM9tmtlO+PF6g+s7Zpb2iI7rYLLOjqRThEoAAFAmpQiW0tMtHY8cum7yuZkW12uSFpuVAQAAKIPCD4UDAACgPwiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIhiNO8G9JOZLUiaCz+OheOyu292We/ZUO9tSROh7mV3r3ZTLwAAwDApTbA0szVJH7j7fN25MUlXzWze3Rc7rHdFkuo/H+rdNrPFbkMrAADAsCjFUHgIf++6+3r9eXevhaA5GXozs9Z7VtK5w6HU3WuSFiWthZAJAABQeKUIlpIq7r7T5PqypPkm15t9brXRhdBTeU/SOx3UCwAAMHQKHyzNbFLSeItiVUmTGeudDp/5qEmxHUmZe0IBAACGUeGDpZJewzEzu9SkzLSSEJhFJRybTdCphntnCq0AAADDqPDBMrzvuCNp2cyWD18P70AuS1rKWPUr4dgsWO6F43TGugEAAIZO4YNlMC+pJumSmd0Ow9hpqFyTtNjB0kDtTMqphWOroXgAAIChV4rlhty9amanJN1U0nu4bWbpDPFOQqUUwmLoEW2FmeEAAKDwytJjmQbAV3UwdH1WGSfsHJIlLE4cPmFmC2a2ZWZbd+/e7aIZAAAAg6E0wdLMKpKuKtkhZ0ZJwJyWdLuTNSy75e6r7j7r7rMnTpzo9+0BAACiK0WwDMFx0d3n3b3q7jvuflrS5VBkpcWs8UZqoe52ei73WhcBAAAYboUPlmGizlL9Vo4pd19S0ntZUzJrvFfLArXzHiYAAMBQK3ywVLKU0HPLDKXCjjwz4cezGepN39VsNuM77c28l6FeAACAoVSGYFmRtNWsQJgVvqqDtSnbke6406yX83Q4Zl18HQAAYOiUYrmhNt1WtiHrzXBs9o7lpKRah8sZAQAADJUy9FjuSJpto9ycpI12Kw1D6LXwuaNUlPSEAgAAFF4ZguUFJRNzjuxZDEsR1dx9s8G1FTNbO+LzFySda3TNzM4qCZ7vdt50AACA4VH4YBl6Fi8o2W3nuck5YZmhpVDm8LWKpAUlk3rONah7XdJ1Jetj1n8u3X98vs2deQAAAIZeKd6xdPd1M9uU9I6ZLYbTaeD7wN0bDme7+6aZpRNvrh9RZtHMzprZSl2dY5LmeLcSAACUSSmCpfR0S8elDj4300aZdUnrrcoBKKa9vT1973vf03e/+11NTDy3gysAlEbhh8IBoNeuXbumTz75RO+//37eTQGAXBEsAaALe3t7unHjhtxdN27c0N4eO7gCKC+CJQB04dq1a3ry5Ikk6fHjx/RaAig1giUAdGFzc1P7+/uSpP39fW1stL0cLgAUDsESALpQqVQ0OprMgxwdHdXcXLM9EwCg2AiWANCF8+fP69ix5FfpyMiI3njjjZxbBAD5IVgCQBcmJiZ05swZmZnOnDnDckMASq0061gCQK+cP39en376Kb2VAEqPYAkAXZqYmNAPf/jDvJsBALljKBwAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFwRIAAABRECwBAAAQBcESAAAAURAsAQAAEAXBEgAAAFGM5t0ADKYrV67o1q1bXdezu7srSTp58mTXdU1NTenixYtd1wMAAHqDYImeevToUd5NAAAAfUKwREOxegbfeustSdJ7770XpT4AADC4CJYFE2sIO5a0LWnAHBQMqwMAEB/BsmBu3bqlX/zLv+rxZ8fzbook6dh/uCRpu/rrnFtyYOThvbybAABAIREsC+jxZ8f16E//PO9mDKzjv/xp3k0AAKCQWG4IAAAAURAsAQAAEAXBEgAAAFEQLAEAABAFk3cKZnd3VyMPHzBBpYmRh3va3d3PuxkAABQOwbKIHu9r5OFe3q1IPHmcHI+N5NuOeo8JlQAA9ALBsmC++tWvDuQC6VNTUzm35FmD1h4AAIqAYFkwg7abDFs6AgBQHkzeAQAAQBSF77E0s9uSauHHVnv5rbj7epv1TkpakbQmadPdq3XnK5LmJC2l5wEAAIqu8MFS0mSGsosZyo4pCZAVSTKz+mtVSXOESgAAUCaFDpZmNi3psqR33b3WpFxF0mQHQXBdSS/opKRxSVuSNtrt9RxkV65ciTIJKK0jfdeyG1NTUwP3DikAADhQ6GApaVbJ8HazUDkmadHd5zuof8PdVztuXQkcP3487yYAAIA+KXqwHGujF3JZ0oV+NGaY0DMIAACyKvSscHe/3Oy6mZ2VtN2sRxMAAADtKXqP5ZHCEPjrHQ6BAwAA4JDSBkslQ+BL3VYSlhc6W3dqQsm7l5vd1g0AADBMShksQxhUhOWA5iRVDw+5m9m2mX3QaigeAACgSAr9jmUTK+GrG1UlM84b9UxekLQcljFqyMwWzGzLzLbu3r3bZVMAAADyZ+6edxv6KvRWbrv7iz2+z21JNXefaVV2dnbWt7a2etkcAACAKMxs291nG10rY4/loqR+vP9YlTSdDrsDAAAUXRmD5YKkj/pwn/T9TYIlAAAohVIFy7DF45gOQl83dbUKjOnamARLAABQCqUKlpLSyTRdLYhuZiuSbocF1o8yFo73urkXAADAsChbsJwLx27D3riScNosoKY9laxnCQAASqFswTINe91u4fiRpJkWi6BXJK2zXSQAACiLsgXL8SyFzWzFzNbC9o9PhYXPj9y1x8yWw7cXsjcRAABgOJUtWI61LpIIi5svKNmu8VyDImnonDz0uYXwuRl6KwEAQJmUbUvHTUmT7Wzl6O6bZrYTfrze4PqOmaU77IzrILTuSDpFqAQAAGVTqmDp7nOtSz1TvumuOSE8LnbVKAAAgIIo21A4AAAAeoRgCQAAgCjM3fNuQ+mZ2V1Jv8q7HSXzeUm/ybsRQI/xnKMMeM7774vufqLRBYIlSsnMttx9Nu92AL3Ec44y4DkfLAyFAwAAIAqCJQAAAKIgWKKsVvNuANAHPOcoA57zAcI7lgAAAIiCHksAAABEQbAEAABAFARLlIKZVcxsw8zum5mH7yt5twvoBTNbMbNLebcD6AUzWzCzNTO7bWbb4XmfzLtdSPCOJQrPzJYlpf/IViWNSxoLP19296VcGgZEZmbTkpYlVSQtufvlnJsERGNmY5K2JR0VIhfdnYk8OaPHEoUWeiXTUDnn7qfd/UVJc+HcJTM7m0/rgO6Z2dnQa3NfyT+69MSjqG4qCZWXJZ2WlP4u3wnXV/h9nj+CJYpuORzn3X0zPRm+XzxUBhhGk5KmJd1T8g9uLd/mAPGFToJpJT3xS+5edfeau2+6+4yk9Pc7v89zxlA4CisMm9yXVAu9lI3K3FcyLD7j7juNygDDxMy2dfAPMEPhKAQzW5NUafK7fFLS7fDjXH1HAvqLHksU2blw3GpSJr3G8CEADK4PJF0/6qK7V3XQWz/dlxahIYIliix9j7JZT2R67ZUetwUA0CF3X5fUaqLlvXCc6HFz0ATBEkWWzvzea1ImvTbWpAwAIGfu3ur94XS2+O2mpdBTBEsU2Xg4NvtllF4bb1IGADDAwlJbqSOHzNF7BEsUWZZeSHosAWB4pbPBL7fRs4keIlgCAIChFXaZqkiqsuFF/giWKLL0r9ZmvZHpNf7CBYAhExZEX1ayq9pMzs2BCJYotnutizydPdhOWQDAgAjvVa4phEqGwAcDwRJFlv6SOd2kTDqLkF9IADAkQqjcFqFy4BAsUWQfheNskzJpsPyoSRkAwIAIu+zcFKFyIBEsUWTpll7TYXvHZ4Rz04fKAgAGVAiV20peXyJUDiCCJQor7P1dDT++06DIQjhW2SccAAYboXI4ECxRdIvheCnMHpQkmVlFB+uesTwFAAywMMJEqBwC5u55twHoKTNblnQp/Hh4CaLLrHuGYRYmMSzXnaqEY1UHPfZy97l+tguIycxWdDDK1Mqquy+2LoZeGM27AUCvufuSmW0o6ZmsKAmXm5KW3Z13KzHsJnUQJg+fn2xwHgB6hh5LAAAARME7lgAAAIiCYAkAAIAoCJYAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAo2HkHAPqgbq/6HXevNi2cg0FvH4DhQI8lAPTHpqTXJd02s0utCudg0NsHYAiwpSMA9JGZpb90Tw9iz+Cgtw/AYKPHEgD6az0cF3NtxdEGvX0ABhg9lgDQR2ZWkbQhqebuL+bdnsMGvX0ABhs9lgDQR+6+KakmaSyEuIEy6O0DMNgIlgDQf6vhOKjDzYPePgADiqFwAOgzM5uUdFuS3N1ybs5zBr19AAYXPZYA0GdhtnVVemb9yIEx6O0DMLgIlgCQj5VwHNTh5kFvH4ABxFA4AOTAzMYk3Q8/vujutTzbc9igtw/AYKLHEgDyk4a1hVYFzWwyhx1xWrbPzCpmdsnMls1sjV17gHIjWAJAn4XewJs6mH39eovyk0rWlpzocdPS+7XVvnQ5Ine/7O5L7j4v6RUz2+hHOwEMHoIlAPRRCG3bkt5196VwejqEx+fKmtmypLMKk2kGqX2SpsO6l/UuSKow6QcoJ4IlAPRJXWhbcfd068Qj14x091roCbysg2HpgWmfpNcPB87wLmZV0lzPGgpgYBEsAaAP6kLbZgiKqbVwzLWHr8P2jUma7nXbAAwPgiUA9FhdaKu6+zM9f3VbKE6aWS4hrdP2ufvpup7N+rrSd0IBlAzBEgB6KAwVb0uSux81PJzbFoo9aN+CkoC63rIkgMIhWAJAj9SFtnFJM02KpouRn+vyfhvhayyP9oX6FsX7lUBpESwBoAfqhpfHJL3abIHxsIXijqSxTmdTh89Vwtc7ObVvTdJ8KA+ghAiWANAbs+E45+47bZS/EI7LHd5vU8ls7KqSdxxbido+M1uRdKHNugAUFFs6AsAQMLM1Je8uLrVRduXwJJxeCrvtbNaHSjMbYxtIoHzosQQAdCwMje806KlsuU0lgOIZzbsBAIB4wgSa2326V0XJsPt6uG86aWhSfVjQHcDgYSgcAAZY2NJxUskC5TWFdymPGhIP7zou9XoYOkz+ud+kyAzvWwLlQ48lAAywdt6pTIUFzGv9eLcx3MN6fR8Aw4VgCQDFsdjPSTsAcBhD4QAAAIiCWeEAAACIgmAJAACAKAiWAAAAiIJgCQAAgCgIlgAAAIiCYAkAAIAo/j87Ia/h+aMyGwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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r+tKjP+i/fO6Bvj/Cx+V2flB5Lu8SgK6S5hHwS5Lm3H24SbsXlez7OxK+35A06+7f33mZAAAAyEqanUB+qLCf73bCXsA3lYS/e5KuS7ol6bSZ/cbMvrrTQgEAAJCNNI+AR9z9RpM2M0oeCS+5+6HaE2Y2I2nFzIbc/aOUdQIAUEjseNMaJvEUS9bLwIwpmSn81tYT7j5tZjclXZZ0aOt5AADKiB1vmmPHm+JJEwC3newhSWb2avjjhrv/ul4bd58zszEze9Pdf5ri3gBKquf++q6Xgdnzx09kj/6cUUXZ8D2f06Mv7H5iQs/9dekLn8ugIuSJHW8aYymo4kkTACtm9nV3/6dtzo+H40KT67yrZDwhARDocsPDDeeMtWx1dbNwuxv09vZqcPCFDK70QrJ11+ZGBtdCHljvsrme+2taXd3MuwzUSBMA55SEtu0e31Yf/843uoi73zCz0RT3BVBSjPdpzcmTJ/XZR7/NuwwAEUmzEPSCmR0xsx9sXdIlLBEzoiQANusBlKS76coEAKCYWO+yud4Pr2bUY46spJ0EMi1pycwOKlkU+oaS4HdeSfiruPvtTCsEAABAplIFQHe/J2nYzC5JuqIk9EnJBJENSRPNrhHWCqykrBMAAAAZ2dEyMO4+YWZjSgLfPknvK9kl5F4Lbz+tpPcQAAAAOdjxOoDuvqDWxvs9ZmbvSjJ3/9VO7wsA3WZ1dVX/8Yce9rtt4KM/9OgvVlfzLgPoGlkvBP0UM/uhpFeUPB4ek9Qn6WA77wkAAIDG2hoA3f20mT2vJPzdDcclM5tw979v570BoCwGBwf12eZv9f2RT/IupbB+UHlOnx8czLsMoGu0NQBKjyeOXAlfMrMhJb2CAAAAyEHbA+BW7r4iaWU31zCzPknX3b2lx8lmNqknO5X0heNMGMcIAAAQlT2tNjSzb7SzkBZr6DOzU5JuSRpq8T2XJK27+0T4Glcye3nKzGbbWC4AAEAhpekBvCTp5XYV0khYcmZGSc/hbDg2DYAh4L3r7k+tO+juG5ImzGzezCbdfa4NZQMAItFzf33XewHv+eMnskd/zqiibPiez+nRF3Y/O73n/rokdgIpkjQBsKUet3YIj2ofP+41s/UW6xlz96kG52eU7G5CAAQA7Mjw8HAm11ld3dSDBw8yuVZWent7M9rC7YXM/p6QjTQB0MzsryWdd/fCT1ULk036mzRrqScRAIDtnDhxIu8SgNRaHgMYnJF018zeN7N3zeyb7SgqI+uSqmMGtzMitqUDAACRSRMA7ymZfGFKHseekjRvZg/TBkIz+1b6UtMJ4/wqkmbMbKZODX168ggYAAAgGmkC4EtKtn6bCF8/1faB8JqZfa/BzOHzu6g5jQklu5CcMrObZjYiPQ5/lyRNhWVpAAAAotHyGMDQo3bczL4taVTS/3L3T2p2+hgPxyFJr4XvZWZSEhznJc27+z9J2pflP0SDmlfM7CVJ15U87l0ys8vhNOEPAABEKe0YQLn7FUk/lPR9M/uWu99z9yvuftzdh5WEu2oP4T0lPYTjSh63VszsoSTP7J+geb0bkl7Vk8WnjyjFxA8zmzSzRTNbvHPnTjtKBAAA6KjUAVBKtndz99OS7pnZj83suS3nrrj7lLv3SzogaUrJVnDVQNgxYQ3B80pC6EElQXBE0s2wQ0hD7j7n7qPuPrp///72FgsAANABOwqAVe5+3d2/o6Q38M1t2txy9/PufjQEwtd2c880QsCbCjuArLh7xd0PKJnNLEmzTWYJAwAAdJ1dBcCq0Bu4FHoDX2zStiP774YJH9PuPlGnhmklvYEbSmYJsxYgAACIRiYBUJLc/UboDZzYrjewxq2s7tvATPiqK2wPV91d5EgH6gEAACiEzAJglbv/SNJ1M/tJg2VgxrO+bx1jkhYbNQizgOckHepAPQAAAIWQeQCUHo/7Oy7pkJl9r975dtx3h27qyQxhAACArteWAFjl7uclnW/SG9guFSXrFTYzrmSNQgAAgCi0NQBKj5eFOS7pgJm9m+Gl+5qcf0vJBI9t24UlYjY6NTEFAACgCFreCaRVYU3AUSWLLR8Ix+pXn5m9JWnC3f9xF7cZCvfqCws9P8PdK+FeS2Y27e6Xa8+H5V/GlSxaDQAAEI0dBcDwOLca6raGvKea1nn7hqSjkloOgGGZlllJ/eEe1V69u2ZWkbQuaXZryHP3y2a2IOkdM5uqub8k/czdOzEZBQAAoFBaDoBm9g9Keva2PlLdGvI2lEyqqH69X/2zu9/bSZFhtu6OwlroIZzeyXsBAAC6UZoewNoAVhvwqrNoKwWb3QsAAIA60j4Crkj6iaQFd7+dfTkAAABotzQB0JXsmHFQ0mkze0nJ4955EQgBAABKI00AvBdC3m1JVyTJzJ5XsuNGNRCu6Ekg/GS7C5nZz9z99Z0WDQAAgJ1LEwCfmUgRJnVc0bOB8EyTQMjeuwAAADlpOQCGXT2atakXCI9K+mn484pa250DAAAAbZL5QtC1QiA8H75kZq9I+q/tvCcAAAAaa/tWcLXc/YbYeQMAACBXHQ2A0uNFnXe0IDQAAAB2r+MBMHgrp/sCAABEL5cA6O5X8rgvAAAA8usBBAAAQE4IgAAAAJFpGADN7CUze7NTxZjZc2b2vU7dDwAAIEYNA6C735J0y8x+bGb/uZ2FmNmrks67+9+28z4AAACxa7oQtLtfN7O7km6Y2bvu/ndZFmBmz0n6qaQ19gcGAABov5bGALp7RckWbofM7Ddm9mYIbjtmZt8ws59LWpL0f9z9O7u5HgAAAFqTZi/gDUnHzWxI0ilJc2a2JGlB0k1Ji5I2JK27+yfV94Wg2C9pRNKQpEOSxpTsCzzn7kcz+mcBAABAC1LvBRx28jiuJAx+W9K4pNNKwp0kuZltfVv1hQVJ85JOh/GFAAAA6LDUAbBWWND58aLOZva8kt6+vnBcl7RB2AMAACiOXQXArdz9ntjnFwAAoNBYCBpANNbW1vT2229rbW0t71IAIFeZBMAwo/fFLK4FAO1y4cIFffDBB7p48WLepQBArrLqATyjZGZvy8JSMutm9tDM3t/tsjIA0Mja2pquXbsmd9e1a9foBQQQtawC4Ly7/7TVxmH28KykaUnDki5Jup5RLQDwjAsXLujRo0eSpIcPH9ILCCBqmY8BNLNvht69bzRoNiPpsrufd/db7n5G0s/N7JtZ1wMAkrSwsKDNzU1J0ubmpubn53OuCGgPxrqiFVkFwIWwX/CaknX+5iQtmdn/M7Ov1mk/pKQH8DF3/5GkiYzqAYCnjI2Nae/eZOGDvXv3anx8POeKgPZgrCtakWUP4JSSR7nHlQS545I+UrL482Nm9ookV7JzyFYsIQOgLY4dO6Y9e5KPvJ6eHr3xxhs5VwRkj7GuaFVWAfC0pAPufjw81r0SjhOSvmNm36tp2y9JtdvF1fCM6gGApwwMDOjw4cMyMx0+fFgDAwN5lwRkjrGuaFVWAfDWdrt9uPuCnmwFBwC5OXbsmL72ta/R+4euxVhXtCqrAPj7Jufp2QOQu4GBAb333nv0/qFrMdYVrcoqAA6b2dfrnTCzNyVt1LzU1+A6+zKqBwCA6DDWFa3Kai/gM5KWzeyXkm5IWpM0oGRx6BGFYBcWe56SdM/M/pu7/2P1AmEJmKWM6gEAIDrVsa6/+MUvGOuKhjIJgO6+YmajSmYBv1ZzakHSqKQpMzukJAzOK5klfN3Mvu3uH4Vt5GYlHcyiHgAAYnXs2DHdvn2b3j80lFUPoNy9IumAmb2kZJ2/lZqJITe2tjez05JumdnN0P61bWYGAwCAFlXHugKNZBYAq0LoqzsjeEu7BTMblvSKpAV3Zw1AAACADsg8AKbh7iuSVvKsAQAAIDaZB8Aw0WNSUnXM34qSyR1z7n476/sBAAAgnUwDYNjxY0ZPL/x8QNK4pGkzO+Xu/zvLewIAACCdzAKgmf1Q0hElewAvSFqvOT0k6X9I+hszO+Du/zOr+wIAACCdTAKgmb0iacTdh7dpciN8TZvZz83sm+7+qyzuDQAAgHSy2glk0t1fa95McvejStYBBAAAQA6yCoDWvMlTWPIFAAAgJ1kFwOWU7T2j+wIAACClrALggYyuAwAAgDbLKgBWzOzNVhqa2buS1jK6LwAAAFLKZBawu583s1+a2ZC2WfDZzL4haUrSqLsfyuK+AAAASC/LhaAnJF1XstTLiqQNJWsB9itZB7BPUkXS0QzvCQAAgJSyegQsd7/n7qOSvqNklu9BJTuAHJR0V9Jpdz/k7reyuicAAADSy3wvYHefkzQnSWb2EoEPAACgWDLrAaxnu/DX6oQRAAAAZK+tAbCB6ZzuCwAAEL2WHgGb2bcljWZ0zz4lk0IAAACQg1bHAA4p2147dgIBAADISasBcEPSvLv/9yxuambrWVwHAACUw7lz57S8nHbn2Getrq7qwYMHGVSUrd7eXg0ODu76OsPDwzpx4kQGFTXWagBckXQjw/suZngtAABQcMvLy/rNv9zQV770cFfXeXh/jx49tIyqys7DP3+izzZ/u6trfPxpT0bVNNdSAHT360oWec6Eu7+W1bUAAEA5fOVLD/X9kU/yLqOwflB5rmP3ymsWMAAAAHJCAAQAAIgMARAAACAyBEAAAIDIZL4XMJAllg1oTaeWDQAAdAcCIAqNZQOa6+SyAQCA7kAARKGtrq7KM9g35oUvPtr9RQrKPfl7AoAiW11d1X/8oaejS52UzUd/6NFfdOjznDGAAAAAkaEHEIU2ODiozzZ/y8KhDfyg8pw+n8E4QgBoJz7Pm+vk5zkBEIX38ae7f2Twu/t79McCjgH8Qo/v+vH0x5/26OWM6gEAxIEAiEIbHh7O5Do9q6vaU8BZwD29vbv+be9lZff3BACIAwEQhcbSJgAAZK+UAdDM+iRdd/eDTdrdlLQRvl1vctlZd7+cRX0AAABFVqoAGILfpKR3WnzLUIrLT6WvCAAAoHxKsQyMmY2Z2ZKk85IqklZaeM+IpDOS9rm7bfclaVzSlLs3vSYAAEA3KEUPoLsvSHr8uNfM1tW8d29UyWPdje0ahB7FKXefyKRQAACAEihFD+AO9bXQqzcj6a1OFAMAAFAUXRsA3f1Mo/NmdkTSUqMeQgAAgG5UikfAWQuPfl/n0S8AAIhR1/YANjEjaTrvIgAAAPIQXQA0syFJYtYvAACIVXQBUNJs+GqJmU2a2aKZLd65c6eNZQEAAHRGVAEw9P6Nunul1fe4+5y7j7r76P79+9tYHQAAQGdEFQCV7PaxkHcRAAAAeYotAE5Kej/vIgAAAPIUTQAMW8P1qYVt5AAAALpZNAFQ0lg4svAzAACIWkwBcDwc13OtAgAAIGcxBcChcKQHEAAARK3MAbAvZfv+tlQBAABQMmUNgEPS4z19W5U2MAIAAHSlvXkX0IqwgPOskl68IT0Jc3fNrKJkXN+su19ucJkFSUNsAQegiD7+tEc/qDyXdxmP/e5+0j/wwhcf5VxJ4uNPe/Ry3kVg1/g5b6yTP+elCIAhtI03bdj4Grt6PwC0y/DwcN4lPONPy8uSpM9/tRi1vaxi/j2hdUX89xfzz7m5e0du1A1GR0d9cXEx7zIAoO1OnjwpSTp79mzOlQDt0+0/52a25O6j9c6VdQwgAAAAdogACAAAEBkCIAAAQGQIgAAAAJEhAAIAAESGAAgAABAZAiAAAEBkCIAAAACRIQACAABEhgAIAAAQGQIgAABAZAiAQEpra2t6++23tba2lncpAADsCAEQSOnChQv64IMPdPHixbxLAQBgRwiAQApra2u6du2a3F3Xrl2jFxAAUEp78y4AKJMLFy7o0aNHkqSHDx/q4sWL+u53v5tzVUDi3LlzWl5ezuRa1eucPHly19caHh7WiRMndn0dQOLnPCv0AAIpLCwsaHNzU5K0ubmp+fn5nCsC2qO3t1e9vb15lwG0Vcw/5/QAllxWvwmtrq5KkgYHB3d9rbL9FpTG2NiYrl69qs3NTe3du1fj4+N5lwQ81q3/3QG1+DnPBj2AkCQ9ePBADx48yLuMwjt27Jj27En+s+np6dEbb7yRc0UAAKRHD2DJZfWbUHX8w9mzZzO5XrcaGBjQ4cOH9Ytf/EKHDx/WwMBA3qTf5dwAAAvQSURBVCUBAJAaARBI6dixY7p9+za9fwCA0iIAAikNDAzovffey7sMAAB2jDGAAAAAkSEAAgAARIYACAAAEBkCIAAAQGQIgAAAAJEhAAIAAESGAAgAABAZAiAAAEBkCIAAAACRIQACAABEhgAIAAAQGQIgAABAZAiAAAAAkSEAAgAARIYACAAAEBkCIAAAQGQIgAAAAJEhAAIAAESGAAgAABAZAiAAAEBkCIAAAACRIQACAABEZm/eBcTq3LlzWl5ezruMx6q1nDx5MudKnjY8PKwTJ07kXQYAAF2FAJiT5eVl/fqf/1UPv9ifdymSpD1/cknS0srvcq7kiZ7763mXAABAVyIA5ujhF/v14C//Ku8yCqv3w6t5lwAAQFdiDCAAAEBkCIAAAACRIQACAABEhjGAOVldXVXP/XuMc2ug5/6aVlc38y4DAICuQw8gAABAZOgBzMng4KD+/bO9zAJuoPfDqxocfCHvMgAA6Dr0AAIAAESGAAgAABAZAiAAAEBkCIAAAACRIQACAABEhgAIAAAQGQIgAABAZAiAAAAAkSEAAgAARIYACAAAEBkCIAAAQGQIgAAAAJEhAAIAAESGAAgAABAZAiAAAEBkCIAAAACRKWUANLM+M1tK+Z4hM5s1syUzmw9fp9pVIwAAQFGVKgCG4HdK0i1JQyneNylpXtKsux9093F3H5dUIQQCAIDYlCIAmtlY6PE7L6kiaSXFeyclzUg66O6VLadnJU1lVigAAEAJ7M27gFa4+4Kkg9XvzWxdLfQAmtmQkpA34e4bdZr0K0WYBAAA6AalCIC7MCNpw90v1zvp7vs6XM9Teu6vq/fDq3mW8NieP34iSXr0hedyruSJnvvrkl7IuwwAALpO1wZAM+uTdETSXN611DM8PJx3CU9ZXv6DJGl4qEiB64XC/T0BANANujYASjoajqlmC3fKiRMn8i7hKSdPnpQknT17NudKAABAu3VzAKyOGVwJvYGTNecGJM2HsYUAAABR6eYAWDtJ5B13n649GdYBHN/6OgAAQLfr5gDYH44TkuqFvAlJd83s/e0miUiPl5GZlKSvfOUrmRcJAADQaaVYB3CH+qp/qLcETHitomRtwW25+5y7j7r76P79+7OvEgAAoMO6OQBWQ998gzaLkvrMbKQD9QAAABRCNwfA9XBstNBzNSSOtrkWAACAwujmANjKDh9r4XignYUAAAAUSTcHwOr6f422jBsIx7UGbQAAALpKNwfA6hp/hxq0qU4UYT1AAAAQja4NgO6+omSWb6MJHmOSVty90pmqAAAA8lfmANjXvImmJY2Z2TOPgcPM3yEl6wECAABEo6wBcEiSwhZv2wpbvU1Lmq9tGwLhdUlT9P4BAIDYlGInkBDYZpXs7jGkJ71/d82somTJl9l6O3q4+5nQ5nwIgdWlX14l/AEAgBiVIgCG8Xzju3j/gpjoAQAAIKm8j4ABAACwQwRAAACAyBAAAQAAIkMABAAAiAwBEAAAIDIEQAAAgMgQAAEAACJTinUAsb1z585peXl519epXuPkyZO7vtbw8LBOnDix6+sAAID2IABCktTb25t3CQAAoEMIgCVHTxsAAEiLMYAAAACRIQACAABEhgAIAAAQGQIgAABAZAiAAAAAkSEAAgAARIYACAAAEBkCIAAAQGQIgAAAAJEhAAIAAESGAAgAABAZAiAAAEBkCIAAAACRIQACAABEhgAIAAAQGQIgAABAZAiAAAAAkSEAAgAARMbcPe8aSsPM7kj6KO86IvNlSb/Puwigzfg5Rwz4Oe+8r7r7/nonCIAoNDNbdPfRvOsA2omfc8SAn/Ni4REwAABAZAiAAAAAkSEAoujm8i4A6AB+zhEDfs4LhDGAAAAAkaEHEAAAIDIEQAAAgMgQAFEoZjZmZvNmdtfMPPx5LO+6gHYws1kzO5V3HUA7mNmkmV0ys5tmthR+3ofyrgsJxgCiMMxsRlL1f4Yrkvol9YXvz7j7dC6FARkzsxFJM5LGJE27+5mcSwIyY2Z9kpYkbRf2ptydCSE5owcQhRB6+arhb9zdD7j7Pknj4bVTZnYkn+qA3TOzI6EX5K6S/znSs41udV1J+Dsj6YCk6md5JZyf5fM8fwRAFMVMOE64+0L1xfDnqS1tgDIakjQiaV3J/xg38i0HyF74ZX5ESc/2tLuvuPuGuy+4+0FJ1c93Ps9zxiNg5C48LrgraSP0+tVrc1fJ4+CD7l6p1wYoEzNb0pP/UfIIGF3BzC5JGmvwWT4k6Wb4drz2F350Fj2AKIKj4bjYoE31HI/NAKC4fibp59uddPcVPen9HulIRaiLAIgiqI7za9SzVz13qM21AAB2yN0vS2o2YW89HAfaXA4aIACiCKozfdcatKme62vQBgCQM3dvNr61Ojv4ZsNWaCsCIIqgPxwbfWhUz/U3aAMAKLCwBFLVto+K0X4EQBRBml49egABoLyqs3/PtNBTiDYiAAIAgLYLu96MSVphYf/8EQBRBNXfAhv17lXP8RsjAJRMWPh5RskuTwdzLgciAKIY1ps3eTxbrJW2AICCCOP+LimEPx79FgMBEEVQ/TA40KBNddYYHxwAUBIh/C2J8Fc4BEAUwfvhONqgTTUAvt+gDQCgIMKuH9dF+CskAiCKoLoV0EjYFu4p4bWRLW0BAAUVwt+SkmE7hL8CIgAid2Fv35Xw7Tt1mkyG4wr7AANAsRH+yoEAiKKYCsdTYbaYJMnMxvRk3SiWDQCAAgtPbAh/JWDunncNgCTJzGYknQrfbl0a5gzrRqHMwmD4mZqXxsJxRU96wOXu4wJKysxm9eSpTTNz7j7VvBnaYW/eBQBV7j5tZvNKevrGlITABUkz7s7YP5TdkJ6Evq2vD9V5HQDahh5AAACAyDAGEAAAIDIEQAAAgMgQAAEAACJDAAQAAIgMARAAACAyBEAAAIDIEAABAAAiQwAEAACIDDuBAECNmr2oK+6+0rBxDopeH4ByoAcQAJ62IOl1STfN7FSzxjkoen0ASoCt4ACgDjOrfjgeKGJPW9HrA1Bs9AACQH2Xw3Eq1yq2V/T6ABQYPYAAUIeZjUmal7Th7vvyrmerotcHoNjoAQSAOtx9QdKGpL4Qtgql6PUBKDYCIABsby4ci/qYtej1ASgoHgEDwDbMbEjSTUlyd8u5nGcUvT4AxUUPIABsI8yuXZGeWn+vMIpeH4DiIgACQGOz4VjUx6xFrw9AAfEIGAAaMLM+SXfDt/vcfSPPerYqen0AiokeQABorhqqJps1NLOhHHboaFqfmY2Z2SkzmzGzS+wiAsSNAAgA2wi9a9f1ZLbt603aDylZm2+gzaVV79dSfdVlYtz9jLtPu/uEpENmNt+JOgEUDwEQAOoI4WpJ0rvuPh1eHgkh75m2ZjYj6YjCpIwi1SdpJKwbWOstSWNMHgHiRAAEgC1qwtWsu1e3XNt2zT133wg9a2f05HFsYeqT9PrWYBjGCq5IGm9boQAKiwAIADVqwtVCCHRVl8Ix1x6zHdbXJ2mk3bUBKA8CIAAENeFqxd2f6kmr2XptyMxyCVM7rc/dD9T0FNZeqzpmEUBkCIAAoMcTOJYkyd23eyya29ZrbahvUkmQvNy0JYCuQwAEEL2acNUv6WCDptVFl4/u8n7z4asvj/rC9abE+D8gWgRAAFGreazaJ+nVRgsph63XKpL6djp7NrxvLHy9k1N9lyRNhPYAIkQABBC70XAcd/dKC+3fCseZHd5vQcns2xUlY/CaybQ+M5uV9FaL1wLQpdgKDgAyZGaXlIytm26h7ezWyRztFHb/WKgNf2bWx/ZxQHzoAQSACIRHwpU6PX9Nt7cD0H325l0AAMQoTMS42aF7jSl53Hw53Lc6+WRIHVi4GkDx8AgYADIQtoIbUrIQ84bCWL/tHgWHsXjT7X78GiaR3G3Q5CDjAYH40AMIABloZcxfVVioeaMTY+/CPazd9wFQLgRAAOi8qU5O/gCArXgEDAAAEBlmAQMAAESGAAgAABAZAiAAAEBkCIAAAACRIQACAABEhgAIAAAQmf8Pln74rk2s6dgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AG5r2tQT6FYj"
      },
      "source": [
        "## Fig.7\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HjgsGp1jgSWI"
      },
      "source": [
        "### Fixed"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CJ4_rVZk6EYr"
      },
      "source": [
        "from sklearn.model_selection import KFold\n",
        "brca = np.load('data/BRCA_counts.npy')\n",
        "n_iter = 500\n",
        "layers = 10\n",
        "fig_6_brca_cv = pd.DataFrame()\n",
        "lst = {}\n",
        "kf = KFold(n_splits=5, random_state=1, shuffle=True)\n",
        "\n",
        "for k in range(1,2):\n",
        "    lst[\"dnmf_0\"] = []\n",
        "    lst[\"dnmf_1\"] = []\n",
        "    lst[\"dnmf_2\"] = []\n",
        "    lst[\"mu_0\"] = []\n",
        "    lst[\"mu_1\"] = []\n",
        "    lst[\"mu_2\"] = []\n",
        "    V = brca.T\n",
        "    for train_index, test_index in kf.split(V.T):\n",
        "\n",
        "      data, n_components, features, samples = util.build_data(\n",
        "          V, W, H\n",
        "      )\n",
        "\n",
        "      for lam in range(3):\n",
        "        L1 = lam\n",
        "        L2 = lam\n",
        "        ##################### unsupervised performance #############################\n",
        "        _, _, dnmf_error, _ = util.train_unsupervised(\n",
        "            data, layers, n_iter, n_components, l_1=L1, l_2=L2\n",
        "        )\n",
        "        ###### MU ################\n",
        "        # train\n",
        "        h_mu = data.h_0_train.mat.copy()  # k*n\n",
        "        w_mu = data.w_init.mat.copy()  # f*k\n",
        "        for i in range(n_iter):\n",
        "            w_mu, h_mu = util.mu_update(data.v_train.mat, w_mu, h_mu, l_1=L1, l_2=L2)\n",
        "        # test\n",
        "        mu_test_iter = 10\n",
        "        h_mu_test = data.h_0_test.mat.copy()\n",
        "        for i in range(mu_test_iter):\n",
        "            _, h_mu_test = util.mu_update(\n",
        "                data.v_test.mat, w_mu, h_mu_test, update_W=False\n",
        "            )\n",
        "        mu_error = util.cost_mat(data.v_test.mat, w_mu, h_mu_test)\n",
        "\n",
        "        lst[f\"dnmf_{lam}\"].append(dnmf_error[-1])\n",
        "        lst[f\"mu_{lam}\"].append(mu_error)\n",
        "      \n",
        "    fig_6_brca_cv[f\"dnmf_0_{k}\"] = lst[\"dnmf_0\"]\n",
        "    fig_6_brca_cv[f\"dnmf_1_{k}\"] = lst[\"dnmf_1\"]\n",
        "    fig_6_brca_cv[f\"dnmf_2_{k}\"] = lst[\"dnmf_2\"]\n",
        "    fig_6_brca_cv[f\"mu_0_{k}\"] = lst[\"mu_0\"]\n",
        "    fig_6_brca_cv[f\"mu_1_{k}\"] = lst[\"mu_1\"]\n",
        "    fig_6_brca_cv[f\"mu_2_{k}\"] = lst[\"mu_2\"]\n",
        "fig_6_brca_cv.to_csv('data/outputs/fig_6_brca_cv.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "9iG_NkcS7t3c",
        "outputId": "ef53355d-7a03-4357-fc2f-8750ce912bf6"
      },
      "source": [
        "fig_6_brca_cv = pd.read_csv('data/outputs/fig_6_brca_cv.csv')\n",
        "for x in range(1, 2):\n",
        "  df = fig_6_brca_cv[[f\"dnmf_0_{x}\", f\"mu_0_{x}\", f\"dnmf_1_{x}\", f\"mu_1_{x}\", f\"dnmf_2_{x}\", f\"mu_2_{x}\"]]\n",
        "  df = pd.melt(df)\n",
        "  df['method'] = df.apply(lambda row: 'DNMF 'if row.variable.startswith('dnmf') else 'MU', axis = 1)\n",
        "  if x>9:\n",
        "    df['lambda'] = df.apply(lambda row: row.variable[-4:-3], axis = 1)\n",
        "  else:\n",
        "    df['lambda'] = df.apply(lambda row: row.variable[-3], axis = 1)\n",
        "  df['value'] = np.log(df['value'].values)\n",
        "  # plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
        "  sns.boxplot(x='lambda',y='value',data=df,hue='method')\n",
        "  plt.ylabel(\"$\\log({MSE})$\")\n",
        "  plt.xlabel(\"${\\lambda_1,\\lambda_2}$\")\n",
        "  plt.legend([],[], frameon=False)\n",
        "  # plt.savefig(f\"plots/fig7/unsupervised_performance_brca.pdf\")\n",
        "  plt.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AwynfDPN9Vdf"
      },
      "source": [
        "### RANDOM"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MBPAVKvQ9UNt"
      },
      "source": [
        "from sklearn.model_selection import KFold\n",
        "brca = np.load('data/BRCA_counts.npy')\n",
        "n_iter = 500\n",
        "layers = 10\n",
        "fig_6_brca_random = pd.DataFrame()\n",
        "lst = {}\n",
        "kf = KFold(n_splits=5, random_state=1, shuffle=True)\n",
        "\n",
        "for k in range(1,2):\n",
        "    lst[\"dnmf_0\"] = []\n",
        "    lst[\"dnmf_1\"] = []\n",
        "    lst[\"dnmf_2\"] = []\n",
        "    lst[\"mu_0\"] = []\n",
        "    lst[\"mu_1\"] = []\n",
        "    lst[\"mu_2\"] = []\n",
        "    V = brca.T\n",
        "    \n",
        "    for train_index, test_index in kf.split(V.T):\n",
        "      W = abs(np.random.randn(V.shape[0], 12))  # (f,k) normal\n",
        "      H = abs(np.random.randn(12, V.shape[1]))  # (k,n) normal\n",
        "      data, n_components, features, samples = util.build_data(\n",
        "          V, W, H\n",
        "      )\n",
        "\n",
        "      for lam in range(3):\n",
        "        L1 = lam\n",
        "        L2 = lam\n",
        "        ##################### unsupervised performance #############################\n",
        "        _, _, dnmf_error, _ = util.train_unsupervised(\n",
        "            data, layers, n_iter, n_components, l_1=L1, l_2=L2\n",
        "        )\n",
        "        ###### MU ################\n",
        "        # train\n",
        "        h_mu = H[:, train_index].copy()  # k*n\n",
        "        w_mu = W.copy()  # f*k\n",
        "        for i in range(n_iter):\n",
        "            w_mu, h_mu = util.mu_update(V[:, train_index], w_mu, h_mu, l_1=L1, l_2=L2)\n",
        "        # test\n",
        "        mu_test_iter = 10\n",
        "        h_mu_test = H[:, ~train_index].copy()\n",
        "        for i in range(mu_test_iter):\n",
        "            _, h_mu_test = util.mu_update(\n",
        "                V[:, ~train_index], w_mu, h_mu_test, update_W=False\n",
        "            )\n",
        "        mu_error = util.cost_mat(V[:, ~train_index], w_mu, h_mu_test)\n",
        "\n",
        "        lst[f\"dnmf_{lam}\"].append(dnmf_error[-1])\n",
        "        lst[f\"mu_{lam}\"].append(mu_error)\n",
        "      \n",
        "    fig_6_brca_random[f\"dnmf_0_{k}\"] = lst[\"dnmf_0\"]\n",
        "    fig_6_brca_random[f\"dnmf_1_{k}\"] = lst[\"dnmf_1\"]\n",
        "    fig_6_brca_random[f\"dnmf_2_{k}\"] = lst[\"dnmf_2\"]\n",
        "    fig_6_brca_random[f\"mu_0_{k}\"] = lst[\"mu_0\"]\n",
        "    fig_6_brca_random[f\"mu_1_{k}\"] = lst[\"mu_1\"]\n",
        "    fig_6_brca_random[f\"mu_2_{k}\"] = lst[\"mu_2\"]\n",
        "fig_6_brca_random.to_csv('data/outputs/fig_6_brca_random.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C8-zH0lO_sTe"
      },
      "source": [
        "fig_6_brca_random = pd.read_csv('data/outputs/fig_6_brca_random.csv')\n",
        "for x in range(1, 2):\n",
        "  df = fig_6_brca_random[[f\"dnmf_0_{x}\", f\"mu_0_{x}\", f\"dnmf_1_{x}\", f\"mu_1_{x}\", f\"dnmf_2_{x}\", f\"mu_2_{x}\"]]\n",
        "  df = pd.melt(df)\n",
        "  df['method'] = df.apply(lambda row: 'DNMF 'if row.variable.startswith('dnmf') else 'MU', axis = 1)\n",
        "  if x>9:\n",
        "    df['lambda'] = df.apply(lambda row: row.variable[-4:-3], axis = 1)\n",
        "  else:\n",
        "    df['lambda'] = df.apply(lambda row: row.variable[-3], axis = 1)\n",
        "  df['value'] = np.log(df['value'].values)\n",
        "  plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
        "  sns.boxplot(x='lambda',y='value',data=df,hue='method')\n",
        "  plt.ylabel(\"$\\log({MSE})$\")\n",
        "  plt.xlabel(\"${\\lambda_1,\\lambda_2}$\")\n",
        "  # plt.savefig(f\"plots/fig6/unsupervised_performance_brca_random.pdf\")\n",
        "  plt.show()\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qMrbaol_gSAM"
      },
      "source": [
        "## Fig.8"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lLuI7fuqgUQl"
      },
      "source": [
        "from sklearn.decomposition._nmf import _initialize_nmf\n",
        "n_iter = 1500\n",
        "layers = 10\n",
        "brca = np.load('data/BRCA_counts.npy')\n",
        "V = brca.T\n",
        "W = abs(np.random.randn(V.shape[0], 12))  # (f,k) normal\n",
        "H = abs(np.random.randn(12, V.shape[1]))  # (k,n) normal\n",
        "data, n_components, features, samples = util.build_data(\n",
        "    V, W, H)\n",
        "\n",
        "fig_7_brca = pd.DataFrame()\n",
        "TRAIN_SIZE = 0.80\n",
        "mask = np.random.rand(samples) < TRAIN_SIZE\n",
        "W_init, H_init = _initialize_nmf(V, 12, init='random')\n",
        "for lam in range(3):\n",
        "  L1 = lam\n",
        "  L2 = lam\n",
        "  \n",
        "  ##################### unsupervised performance #############################\n",
        "  _, dnmf_train, dnmf_error, dnmf_w = util.train_unsupervised(data, layers, n_iter, n_components, l_1=L1,l_2=L2, lr=0.001)\n",
        "\n",
        "  ###### MU ################\n",
        "  # train\n",
        "  h_mu = H_init[:, mask]  # k*n\n",
        "  w_mu = W_init\n",
        "  mu_training_cost = []\n",
        "  mu_super_test = []\n",
        "  for i in range(n_iter):\n",
        "      w_mu, h_mu = util.mu_update(V[:, mask], w_mu, h_mu,l_1=L1,l_2=L2)\n",
        "      mu_training_cost.append(util.cost_mat(V[:, mask], w_mu, h_mu,l_1=L1,l_2=L2))\n",
        "      # test\n",
        "      mu_test_iter = 10\n",
        "      h_mu_test = H_init[:,~mask]\n",
        "      for i in range(mu_test_iter):\n",
        "          _, h_mu_test = util.mu_update(\n",
        "              V[:,~mask], w_mu, h_mu_test, update_W=False\n",
        "          )\n",
        "      mu_super_test.append(util.cost_mat(V[:,~mask], w_mu, h_mu_test))\n",
        "\n",
        "  fig_7_brca[f'dnmf_L{L1}'] = dnmf_error\n",
        "  fig_7_brca[f'MU_L{L1}'] = mu_super_test\n",
        "\n",
        "fig_7_brca.to_csv('data/outputs/fig_7_brca.csv', index=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "Ef3PDBYxqVwc",
        "outputId": "9f261883-30c9-4e9d-e540-1b4701269eb1"
      },
      "source": [
        "  plt.rcParams['figure.figsize'] = (10, 8.0)\n",
        "  epochs = range(0, mu_test_iter - 1)\n",
        "  plt.semilogy(np.log(fig_7_brca['MU_L0']), label=\"MU\")\n",
        "  plt.semilogy(np.log(fig_7_brca['dnmf_L0']), label=\"DNMF\")\n",
        "  plt.xlabel(\"Number of Train Iterations\")\n",
        "  plt.ylabel(\"$\\log(MSE)$\")\n",
        "  plt.legend()\n",
        "  ax=plt.gca()\n",
        "  ax.yaxis.set_minor_formatter(mticker.ScalarFormatter())\n",
        "  plt.savefig(f\"plots/fig8/unsupervised_brca_mu_compare_train_L0.pdf\")\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "kV7S2OMewtP5",
        "outputId": "347f2a32-6d4e-49bb-c910-b2bf7d611fe0"
      },
      "source": [
        "  plt.rcParams['figure.figsize'] = (10, 8.0)\n",
        "  epochs = range(0, mu_test_iter - 1)\n",
        "  plt.semilogy(np.log(fig_7_brca['MU_L1']), label=\"MU\")\n",
        "  plt.semilogy(np.log(fig_7_brca['dnmf_L1']), label=\"DNMF\")\n",
        "  plt.xlabel(\"Number of Train Iterations\")\n",
        "  plt.ylabel(\"$\\log(MSE)$\")\n",
        "  plt.legend()\n",
        "  ax=plt.gca()\n",
        "  ax.yaxis.set_minor_formatter(mticker.ScalarFormatter())\n",
        "  plt.savefig(f\"plots/fig8/unsupervised_brca_mu_compare_train_L1.pdf\")\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "n2TtOVmAAIzt",
        "outputId": "42798db6-854b-4882-9adc-fbebc3242bbf"
      },
      "source": [
        "  plt.rcParams['figure.figsize'] = (10, 8.0)\n",
        "  epochs = range(0, mu_test_iter - 1)\n",
        "  plt.semilogy(np.log(fig_7_brca['MU_L2']), label=\"MU\")\n",
        "  plt.semilogy(np.log(fig_7_brca['dnmf_L2']), label=\"DNMF\")\n",
        "  plt.xlabel(\"Number of Train Iterations\")\n",
        "  plt.ylabel(\"$\\log(MSE)$\")\n",
        "  plt.legend()\n",
        "  ax=plt.gca()\n",
        "  ax.yaxis.set_minor_formatter(mticker.ScalarFormatter())\n",
        "  plt.savefig(f\"plots/fig8/unsupervised_brca_mu_compare_train_L2.pdf\")\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}