{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hierarchical clustering basics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.640838Z",
     "start_time": "2021-03-22T18:45:51.400116Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import numpy as np\n",
    "import pandas as pd                \n",
    "from sklearn import datasets\n",
    "from sklearn.metrics import pairwise_distances\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "from cnnclustering import cluster\n",
    "from cnnclustering import plot\n",
    "from cnnclustering import _types, _fit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook was created using Python 3.8."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.646756Z",
     "start_time": "2021-03-22T18:45:53.643513Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.8.8 (default, Mar 11 2021, 08:58:19) \n",
      "[GCC 8.3.0]\n"
     ]
    }
   ],
   "source": [
    "# Version information\n",
    "print(sys.version)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notebook configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.661235Z",
     "start_time": "2021-03-22T18:45:53.649490Z"
    }
   },
   "outputs": [],
   "source": [
    "# Matplotlib configuration\n",
    "mpl.rc_file(\n",
    "    \"../../matplotlibrc\",\n",
    "    use_default_template=False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.669961Z",
     "start_time": "2021-03-22T18:45:53.664190Z"
    }
   },
   "outputs": [],
   "source": [
    "# Axis property defaults for the plots\n",
    "ax_props = {\n",
    "    \"xlabel\": None,\n",
    "    \"ylabel\": None,\n",
    "    \"xlim\": (-2.5, 2.5),\n",
    "    \"ylim\": (-2.5, 2.5),\n",
    "    \"xticks\": (),\n",
    "    \"yticks\": (),\n",
    "    \"aspect\": \"equal\"\n",
    "}\n",
    "\n",
    "# Line plot property defaults\n",
    "line_props = {\n",
    "    \"linewidth\": 0,\n",
    "    \"marker\": '.',\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.681019Z",
     "start_time": "2021-03-22T18:45:53.672057Z"
    }
   },
   "outputs": [],
   "source": [
    "# Pandas DataFrame print options\n",
    "pd.set_option('display.max_rows', 1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-11T14:38:11.051577Z",
     "start_time": "2019-09-11T14:38:11.034144Z"
    }
   },
   "source": [
    "## Dissimilar blobs showcase"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T13:19:52.308965Z",
     "start_time": "2021-03-22T13:19:52.302030Z"
    }
   },
   "source": [
    "Learn in this tutorial how to use the `cnnclustering` module for step-wise hierarchical clusterings, where\n",
    "one cluster step does not deliver a satisfactory result. We will also show how to use a data set of reduced size for cluster exploration and how we can transfer the result to the original full size data set."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will generate a sample data set of three clusters that have very different point densities and are spatially not very well separated. As we will see,\n",
    "it can be non-trivial (if not impossible) to extract all three clusters with a single set of cluster parameters. We will solve the problem by extracting the clusters in a two step procedure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.743372Z",
     "start_time": "2021-03-22T18:45:53.683330Z"
    }
   },
   "outputs": [],
   "source": [
    "# Generate blobs with quite different point densities\n",
    "dblobs, _ = datasets.make_blobs(\n",
    "    n_samples=int(1e5),\n",
    "    cluster_std=[3.5, 0.32, 1.8],\n",
    "    random_state=1\n",
    "    )\n",
    "\n",
    "dblobs = StandardScaler().fit_transform(dblobs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.762051Z",
     "start_time": "2021-03-22T18:45:53.745265Z"
    }
   },
   "outputs": [],
   "source": [
    "# Initialise clustering\n",
    "clustering = cluster.prepare_clustering(dblobs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:53.772508Z",
     "start_time": "2021-03-22T18:45:53.763802Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hierarchy_level: 0\n",
      "input_data_kind: points\n",
      "points: 100000\n",
      "children: None\n"
     ]
    }
   ],
   "source": [
    "# Get basic information about the clustering instance\n",
    "print(clustering)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:54.450098Z",
     "start_time": "2021-03-22T18:45:53.776491Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the original data\n",
    "_ = clustering.evaluate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at this 2D plot of the generated points above we can already tell that this is probably not the easiest\n",
    "of all clustering problems. One of the three clusters is hardly visible. We also have generated a fairly large amount of data points. If we have a big amount of computer-memory or enough time, we can attempt to cluster the 100,000 points directly. In terms of speed and for data exploration it might be, however, a good idea to perform the clustering on a reduced data set. We can predict the clustering later for the full sized set on the basis of the reduced result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:54.454774Z",
     "start_time": "2021-03-22T18:45:54.452118Z"
    }
   },
   "outputs": [],
   "source": [
    "reduced_dblobs = dblobs[::100]\n",
    "rclustering = cluster.prepare_clustering(reduced_dblobs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We created a cluster object holding a smaller data set by using a point stride of 100, leaving us with only 1000 points that can be clustered very fast. A plot of the reduced set also shows that we made the clustering easier just judging by visual inspection. We can now clearly spot three point clouds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:54.691798Z",
     "start_time": "2021-03-22T18:45:54.456135Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '1000 points')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the reduced data\n",
    "fig, Ax = plt.subplots(1, 2)\n",
    "_ = clustering.evaluate(ax=Ax[0], ax_props=ax_props)\n",
    "_ = rclustering.evaluate(ax=Ax[1], ax_props=ax_props)\n",
    "Ax[0].set_title(f\"{clustering._input_data.n_points} points\", fontsize=10, pad=4)\n",
    "Ax[1].set_title(f\"{rclustering._input_data.n_points} points\", fontsize=10, pad=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we pre-calculate pairwise point distances, we can plot the distribution of distances. This can give us a very basic estimate for a reasonable radius cutoff as one of the cluster parameters. For globular clusters with differing point density, each cluster should be visible as a peak in the distance distribution around a value that is very roughly equivalent to the radius of the point cloud. For more complicated data sets this approximation is not valid, but we can still get a feeling for the value range of meaningful radius cutoffs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:54.827780Z",
     "start_time": "2021-03-22T18:45:54.693221Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "distances = pairwise_distances(rclustering.input_data)\n",
    "distance_rclustering = cluster.prepare_clustering(distances)\n",
    "distance_rclustering._metric = _types.MetricExtPrecomputed()\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "_ = plot.plot_histogram(ax, distances.flatten(), maxima=True, maxima_props={\"order\": 5})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-19T10:35:37.964861Z",
     "start_time": "2019-09-19T10:35:37.962263Z"
    }
   },
   "source": [
    "### Parameter scan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Blindly starting to cluster a data set in a happy-go-lucky attempt may already lead to a satisfactory result in some cases, but let's tackle this problem in a more systematic way to see how different cluster parameters effect the outcome. A scan of a few parameters shows that it is difficult to extract the three clusters at once with one parameter set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:55.739008Z",
     "start_time": "2021-03-22T18:45:54.829140Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for r in [0.05, 0.08, 0.1, 0.125, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.75, 1., 2.]:\n",
    "    for c in [0, 1, 2, 3, 4, 5, 10, 15, 20]:\n",
    "        distance_rclustering.fit(r, c, member_cutoff=5, v=False)  # fit from pre-calculated distances"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-11T10:55:56.099867Z",
     "start_time": "2020-06-11T10:55:56.085610Z"
    }
   },
   "source": [
    "Each cluster result will be added to the `summary` attribute of our cluster object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:55.743696Z",
     "start_time": "2021-03-22T18:45:55.740393Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "#points   r         c         min       max       #clusters %largest  %noise    time     \n",
      "1000      0.050     0         5         None      13        0.329     0.555     00:00:0.004\n",
      "-----------------------------------------------------------------------------------------------\n",
      "\n",
      "-----------------------------------------------------------------------------------------------\n",
      "#points   r         c         min       max       #clusters %largest  %noise    time     \n",
      "1000      0.050     1         5         None      11        0.326     0.607     00:00:0.003\n",
      "-----------------------------------------------------------------------------------------------\n",
      "\n",
      "-----------------------------------------------------------------------------------------------\n",
      "#points   r         c         min       max       #clusters %largest  %noise    time     \n",
      "1000      0.050     2         5         None      5         0.317     0.653     00:00:0.003\n",
      "-----------------------------------------------------------------------------------------------\n",
      "\n",
      "-----------------------------------------------------------------------------------------------\n",
      "#points   r         c         min       max       #clusters %largest  %noise    time     \n",
      "1000      0.050     3         5         None      3         0.315     0.675     00:00:0.003\n",
      "-----------------------------------------------------------------------------------------------\n",
      "\n",
      "-----------------------------------------------------------------------------------------------\n",
      "#points   r         c         min       max       #clusters %largest  %noise    time     \n",
      "1000      0.050     4         5         None      1         0.312     0.688     00:00:0.003\n",
      "-----------------------------------------------------------------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(*distance_rclustering.summary[:5], sep=\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have `pandas` installed, you can convert the summary to a nice table as a `pandas.DataFrame`. This makes the analysis of the cluster results more convenient."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:55.775205Z",
     "start_time": "2021-03-22T18:45:55.744928Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>n_points</th>\n",
       "      <th>radius_cutoff</th>\n",
       "      <th>cnn_cutoff</th>\n",
       "      <th>member_cutoff</th>\n",
       "      <th>max_clusters</th>\n",
       "      <th>n_clusters</th>\n",
       "      <th>ratio_largest</th>\n",
       "      <th>ratio_noise</th>\n",
       "      <th>execution_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.963</td>\n",
       "      <td>0.026</td>\n",
       "      <td>0.005310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.45</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.661</td>\n",
       "      <td>0.152</td>\n",
       "      <td>0.008084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.40</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.659</td>\n",
       "      <td>0.152</td>\n",
       "      <td>0.007433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.30</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.614</td>\n",
       "      <td>0.326</td>\n",
       "      <td>0.007638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.15</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.333</td>\n",
       "      <td>0.629</td>\n",
       "      <td>0.006231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.30</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.060</td>\n",
       "      <td>0.005462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.35</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.658</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.006439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.30</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.660</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.005740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.30</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.645</td>\n",
       "      <td>0.210</td>\n",
       "      <td>0.006125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.05</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.675</td>\n",
       "      <td>0.003272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.15</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>3</td>\n",
       "      <td>0.334</td>\n",
       "      <td>0.505</td>\n",
       "      <td>0.005417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    n_points  radius_cutoff  cnn_cutoff  member_cutoff  max_clusters  \\\n",
       "54      1000           0.25           0              5          <NA>   \n",
       "98      1000           0.45          20              5          <NA>   \n",
       "88      1000           0.40          15              5          <NA>   \n",
       "71      1000           0.30          20              5          <NA>   \n",
       "44      1000           0.15          20              5          <NA>   \n",
       "66      1000           0.30           3              5          <NA>   \n",
       "78      1000           0.35          10              5          <NA>   \n",
       "68      1000           0.30           5              5          <NA>   \n",
       "69      1000           0.30          10              5          <NA>   \n",
       "3       1000           0.05           3              5          <NA>   \n",
       "42      1000           0.15          10              5          <NA>   \n",
       "\n",
       "    n_clusters  ratio_largest  ratio_noise  execution_time  \n",
       "54           3          0.963        0.026        0.005310  \n",
       "98           3          0.661        0.152        0.008084  \n",
       "88           3          0.659        0.152        0.007433  \n",
       "71           3          0.614        0.326        0.007638  \n",
       "44           3          0.333        0.629        0.006231  \n",
       "66           3          0.667        0.060        0.005462  \n",
       "78           3          0.658        0.134        0.006439  \n",
       "68           3          0.660        0.105        0.005740  \n",
       "69           3          0.645        0.210        0.006125  \n",
       "3            3          0.315        0.675        0.003272  \n",
       "42           3          0.334        0.505        0.005417  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get summary sorted by number of identified clusters\n",
    "df = distance_rclustering.summary.to_DataFrame().sort_values('n_clusters')\n",
    "\n",
    "# Show cluster results where we have 3 clusters\n",
    "df[df.n_clusters == 3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The summary shows indeed that we got 3 clusters (as desired) for a few parameter combinations. Apart from the number of clusters, it is, however often also of interest, how many data points ended up in the clusters and how many are considered outliers (noise). In this case we expect 3 clusters of more or less equal size (member wise) and we may be interested in keeping the outliers-level low. Of the results giving 3 clusters, 3 find the largest cluster to entail one third of the data points (which is good), but the noise level is around 50 % and higher (which is probably not what we want). Let's plot a few results to see what is going on here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:55.986361Z",
     "start_time": "2021-03-22T18:45:55.776471Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Cluster attempts in comparison\n",
    "fig, ax = plt.subplots(2, 2)\n",
    "Ax = ax.flatten()\n",
    "for i, pair in enumerate([(0.050, 4), (0.125, 20), (0.2, 15), (0.450, 10)]):\n",
    "    distance_rclustering.fit(*pair, member_cutoff=5, record=False, v=False)\n",
    "    rclustering._labels = distance_rclustering._labels\n",
    "    \n",
    "    _ = rclustering.evaluate(ax=Ax[i], ax_props=ax_props)\n",
    "    Ax[i].set_title(f'{pair[0]}, {pair[1]}', fontsize=10, pad=4)\n",
    "\n",
    "fig.subplots_adjust(\n",
    "    left=0.2, right=0.8, bottom=0, top=1, wspace=0, hspace=0.3 \n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "None of the above attempts was able to achieve a split into 3 clusters as we wanted it. One could now try to tinker around with the parameters a bit more, or resort to hierarchical clustering. As we see in the plots above (lower left and right), two different parameter pairs are leading to a clean split of different regions of the data, so why not apply both of them, one after the other.\n",
    "\n",
    "Before we do this let's have another close look at the cluster results we obtained. Using the `summarize` method of a cluster object, we can visualize a summary table in a 2D contour plot, to evaluate a few quality measures versus the input parameters *radius cutoff* (*r*) and *similarity criterion* (*c*):\n",
    "\n",
    " - number of identified clusters\n",
    " - members in the largest cluster\n",
    " - points classified as outliers\n",
    " - computational time of the fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:55.990698Z",
     "start_time": "2021-03-22T18:45:55.987644Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['n_points',\n",
       " 'radius_cutoff',\n",
       " 'cnn_cutoff',\n",
       " 'member_cutoff',\n",
       " 'max_clusters',\n",
       " 'n_clusters',\n",
       " 'ratio_largest',\n",
       " 'ratio_noise',\n",
       " 'execution_time']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.Record.__slots__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:56.268665Z",
     "start_time": "2021-03-22T18:45:55.992023Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Computing time\n",
    "fig, ax = plt.subplots()\n",
    "contour = distance_rclustering.summarize(ax=ax, quantity=\"execution_time\")[2][0]\n",
    "colorbar = fig.colorbar(mappable=contour, ax=ax)\n",
    "ax.set_yticks([0, 5, 10, 15, 20])\n",
    "colorbar.set_label(\"time / s\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the *time vs. R/C* plot we can see how the total clustering time depends in particular on the neighbour search radius cutoff. Larger radii result in larger neighbourlists for each point, increasing the processing time so if one has the choice, smaller values for *r* should be preferred."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:56.462354Z",
     "start_time": "2021-03-22T18:45:56.270180Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.05, 1.0)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Noise level\n",
    "fig, ax = plt.subplots()\n",
    "contour = distance_rclustering.summarize(ax=ax, quantity=\"ratio_noise\")[2][0]\n",
    "colorbar = fig.colorbar(mappable=contour, ax=ax, ticks=(0, 0.5, 1))\n",
    "ax.set_yticks([0, 5, 10, 15, 20])\n",
    "colorbar.set_label(\"noise / %\")\n",
    "ax.set_xlim(None, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ratio of outlier-points depends on the search radius *r* as well as on the similarity criterion *c*. We can somewhat denote from this that cluster results with a similar noise-ratio (that are presumably similar qualitatively) are achieved for a variety of *r*/*c* combinations. If we increase *r* and *c* at the same time, the noise-level stays constant. The desired amount of noise depends much on the nature of the underlying data set. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:56.655954Z",
     "start_time": "2021-03-22T18:45:56.463571Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.05, 1.0)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Largest cluster\n",
    "fig, ax = plt.subplots()\n",
    "contour = distance_rclustering.summarize(ax=ax, quantity=\"ratio_largest\")[2][0]\n",
    "colorbar = fig.colorbar(mappable=contour, ax=ax, ticks=(0, 0.5, 1))\n",
    "ax.set_yticks([0, 5, 10, 15, 20])\n",
    "colorbar.set_label(\"largest / %\")\n",
    "ax.set_xlim(None, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ratio of points assigned to the largest cluster show a similar trend as the noise-ratio. This view could give a good hint towards reasonable parameter combinations if one already has an idea about the expected cluster size. It also shows for which parameters we do not observe any splitting (about 100 % of the points are in the largest cluster. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:56.951616Z",
     "start_time": "2021-03-22T18:45:56.657181Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.05, 1.0)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Number of clusters\n",
    "fig, ax = plt.subplots()\n",
    "contour = distance_rclustering.summarize(\n",
    "    ax=ax, quantity=\"n_clusters\",\n",
    "    contour_props={\"levels\": 100}\n",
    ")[2][0]\n",
    "colorbar = fig.colorbar(mappable=contour, ax=ax, ticks=range(0, 17, 2))\n",
    "ax.set_yticks([0, 5, 10, 15, 20])\n",
    "colorbar.set_label(\"# clusters\")\n",
    "ax.set_xlim(None, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.159593Z",
     "start_time": "2021-03-22T18:45:56.953025Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.05, 1.0)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NEfH8us9p51GSJKm/3gD8VGYeCRARRwDnA3cA1wHPiIi9M/Nv6jqhncc51Pch66Hx/ViZXUdJWtGxwAcX/ftNFPnukZn5UOCfgBfXeULDoyRJUn/dH7gSICIC+HngnMz8j3L/ucChdZ7Q8ChJktRfVwMbyq9/FtgPOGvR/v2BG+s8oeFR6gCHriVJEzoNeF1E/DNwOvB9iqHqBc8APlfnCQ2PkjrL+Y6StKo/AP4BOAT4PPCUzLweICIOpxiyfledJzQ8dkwT13iUJEntKC+tc1pEbI2I70fExyLikVMc8qHAmzPzEZn5jMz8wsKOzLwsMw/IzE9MX/ndDI+SJEkNiIgjKbqDG4A/At5I0TG8KCIOm/CwZwP/tZ4KqzE8zhnn1nWX7809OWQtaYDeBGwCHpeZf52Zfw8cA+wB/O6ExzwXeG5ENHbtbsOjJElSM/4Q+L3MvGvhjsz8LvBD4KAJj/l64L7AaRGx79QVVuAnzEiSJDUgMy9del9EPAzYB/jShIc9Efgm8GsUnyZzKXANkPc8dT5zwuPvxPAodcjjN24ezOdRS5JWFhH7Af9IcXmdUyY8zDHl9jvldt/ytlhSI8OjpM5xvqOkDtpQdvV2kplHjHOgiHgJ8CLgkRRD1k/LzGsmKSozD57kedNwzqMkSVKzfkgxTH0BcG/guCYXvEyrN4VKkiS1aMu4HcblZOaHgA8BRMSjgM9QfEb1iyY5XkQ8AHgO8FTggcDxmfn5iDia4nJAv5KZtX1EoZ3HDpn1BcK9FEw/zPv75JC1pHmSmV8C3gccHxE/Oe7zywuMbwaeD5wHPBzYrdx9AfATwOvqqbZgeJQkSWrXV8vtJCsm/zvwNeCxwDuBWNiRmT8C3gP8yrQFLmZ4lCRJakB5WZ5RDiy3V05w2J8G/v/MvJPRq6qvWXT8WhgepQ6a96FrSRqaiNgdOCsi/tOS+/ekGHK+imL4eVxXUKzaXs7PAF+e4LjLcsGMpM5wvqOkocrM2yLiLRSfY72J4mMF11J8LvUDgadn5h0THPq9wFsj4jKKjz6EsgMZES8CjgeeN239ixkeNRP7H3cVAFs3rW+5EkmSuiEzT42IrwKvBN5A8ZnWnwOen5lfnvCYfxkRhwPvAv6IIjj+cUQ8EDgE+PPMfH8d9S8wPKp2C8FRkiTdU2b+K/CvNR/zxRHxPoou4xEU1448H3heZn6+znOB4XFuOIeuf+btowodspakyWXmZyiuFzlzLphRrew6SpLUnIg4cblV3BFxr4h4f0Q8tc5zGh47YtYXCG+LYVKSpJk6CTh81I7MvIvi8j+/U+cJDY+qjUGxfk43kCRN6T+Y7OLjy3LOo2phcNQ0nO8oSdVFxDOBZy666+UR8bSlDwMeADwB+GGd5zc8aub2P+4qL9kjSVJ9DgKeVH6dwCOAg0c87hbg48ApdZ7c8KiptdV1vGDzRod1JUlzJzNPBk4GiIi7gN/OzP/d1Pmd8zgHhhyw5uFSNkN+/8Aha0ma0v8AvtPkCe08aiptdh0lSRIvB360+I6I2At4CnAA8InM/GadJ7TzqImNExxnGTINkpKkOfYmYEtE3AsgIu4HbAbeD/wlcGlEPGmF54/N8NgBQ73GY5OGHiCHPnQtSZrYrwIfKK/pCMV1Hx8C/DKwHvg8xWde18bwqIm0eWme5YLi0APkEDnfUZKm9hDga4v+/UvAv2XmxzLzauC9FKuxa9Pr8BgRayPijIg4aMS+iIiXRsQ3IuL2iLg4Io5uoUyVmgicBkhJ0py5BdgDICJ+EvhJ4IxF+3cFdtR5wt6FxzIUri8vhnkexYTQUd4IvBP4V+AE4Ebgk3WP+8+jLnYdx32MJEkD8SngtRHxKuDdwHbgQ4v2/yzw1TpPWEt4jIjdI2K3Oo5VwXqKz2n8KHDIMvU8ADgR+JPMfH5mngo8lWIp+18tTCqdB/M6V26IAXJo76VD1pJUixMoPkHmL4AjgZdl5mUAEfFQ4NeAD9R5wrpC1OuAm8qPy5m1rcBRwP2Aty/zmCdTtGn/auGOzNzO3S/sw2Za4YB1vesoSdI8yczrMnMjsD+wT9kwW7AFOAJ4T53nrCs8Pg34AcVH4IwUEY+KiGMiYo9pTpSZ2zJzc2betMLDjgGuyszrltx/Sbl9zDQ1zKs6gmOT4dOwKUmaF5l5/aIV1wv37cjMr2fmHXWeq66LhG8AzsvMlSZk7gD+BfhvwB/UdN7lHAJ8a8T9C/cdNuPzqyOG9hGGj9+42VAsSfqxiKjSVczMfFFd56wrPK4Bbl/pAZn5lYj4BvCLzD487g18d8T9t5XbVednRsSly+zaMGlRfdbmcDVM10UcWoAcAuc7SlJt/l8gR9x/b4p8toNiTmRt6hq2voJiTH01lwMH13TOlewB3DXi/oXO6K4N1FDJLC8QXldgqjs4th1EJUkaiszcMzP3WnoD7gM8gWLU9RfqPGddncczgVdExBMy8/xVHnvfms65klsZ/b2tLbe3rHaAzBwZhsuO5OGTlyZJkpp027bdphrBum3bFUCt0wZnrpxKeEFEnETxqTO/Utex6+o8/hXFkPD7I+KnRj0gInalWKiydBHLLNwA7DPi/r3L7Y0N1LCqPnws4ay6hOMed5ou6pCGrIcw39Eha0lq1NeA/1znAWsJj5l5FfBCYF+KlPvXEXHUwv6I2B94F3AgcG4d51zFtYyem7iwUGbUfMhBqSMwDWF4eUjBUZKkcZSNu1+k5lHf2i6WnZn/i+JC3N8HXgb8W0Rsi4gfAtcAz6MYLv5vdZ1zBWcC6yJi6dDzY8vt2Q3UsKKudx27GBzHDYIGR0nS0EXEzRFx06gbRe76E+DCOs9Z15xHADLz7Ig4FHgJxdj6Roq0u42i4/iGzPxGnedcxicoFse8CngRFJ+CA/w28IXMvKaBGlozbWhqKjjuf9xVbN20fibHNjhKkubEhxm92hrgTuCbwKnL7J9IreERIDNvp5gD+VcAEbE2M++s8xwR8azyyyPL7bERsRW4LjPPz8xrI+LPgTdExO3AZcDzgYMoLiDeqi53HbvYcVysynUOhxocne8oSVoqM3+r6XPWHh6Xqjs4lk5f8u93ltvzgSeWX/8+xUcZ/i5F9/FLwJMz89MzqKczpglObQTHuruPQw2OkiR1xczD4yxkZlR4TLKoAypJktRnETHqSjKVZOYP6qqjl+Gxz7o6ZN3mcPW43cflhq6H3HV0yFqSBFzP8vMbV7NLXUUYHgdk0vDU9XmOVQw5OEqSVHoLk4fH2hgeG9TFrmNfg+Pi7qPBUZI0DzLzpLZrgBqv86h2TRKguhQcJ63F4NgPDllL0mxExL3Ki4GP2rcuIh5d9zkNj3OqS8FxUvMSHIcw31GSNDMvALYus5jmQODiiDi6zhM6bN1B8xKKlprlRcMlSRqolwKnjVpNnZmXRcSHgNcC59R1QjuPc2gIXUdJkgTATwIrdZ0uBo6q84SGx46Z167jAoPtPQ1hyNr5jpI0UzcCe66w/14UH9lcG8NjQ6qstG4iOBrOJEkalIuA50XEbkt3RMR9gN8qH1Mbw6M6x4ArSVJlJwIHARdExLMi4pCI2BARzwIuBDYAb6zzhC6Y6Qi7jhoih6wlabYy8xsRcSzwd8CHuPsi4gFcBhybmf+nznMaHqWOGsJ8R0nS7GXmxRHxKOBngUdQjCz/O3BRZm6v+3wOW3fAvC+SGcUuqSRpiCLiMRFxTkTcEBGXR8QpEbFu2uNm4YLM/NvMfGdmfmYWwREMj3PDMCZJUrsi4pHAZ4GrgFcDnwReBHwhIvZts7ZxGB4bsNJKa7uOy5vnwDuEIWvnO0rSTk4G/j4zfysz352ZrwSOpVjUcmK7pVVneJwD8xzCJEnqgnJo+ueAP1l8f2aeA5wLPLuFsiZieGyRXcfVGXwlSUOQmTcAx2fm90bs3gzs15eha8NjS5oKjoYvtcEha0naWWa+d5ldB1B8CswtDZYzMcOj1DFDmO8oSaomItYAjwMuyMw72q6nCq/zOGOjFss4XD2e/Y+7iq2b1rddhiRpvm2IiEtH7cjMI6Y47usoOo/OeVT7HLKWJKm7IuLRFKusX5iZU33+dET8xaKv10bEpyPi0GlrHMXOY8PsOk5mXrqPQxiydr6jpIHaMmWH8R4i4hDg48AbM/O0Gg75uEVf706xsvtA4Js1HPse7DwOlF1HSZK6KSIOAM4CTs3Mt43xvDdFxDOX+USaqKu+1RgeG2TXcToGYklS30XEPsCngE3ASWM+/UzgSODDEfHZiPiLiHhqROwFZL2VLs/wOECGrH5yyFqShi0i9gTOAC4EXpOZYwW+zLwkM/8oM48GjgY+AfxniuHvwyPixIj4KWCXmku/B+c8ztBKH0soSZLmziZgX+A84Fcjdhpp/mRm3lrlQJm5rTzOeQARcQnwReAFFIEygeMjYldqvgyQ4VG9Mi8LZyRJg/QL5faDy+w/GKgUHke4MzM/Dny8nBP5A+DrwJOBt0TEzcA5wFmZ+aUJzwEYHgfHIWtJkropM6da1BIRm4DrKTuOmXnNcqcqt5/NzM+Uz92PYqj7ZRGxX2Y+c9I6DI/qnSF2H53vKEmq4FeBjcDPA6dGxP7Av1GEyV1XemJmXgd8oLxNxfDYkCZWWtt1lCRpuDLzLuBL5e1tEbEL8J+AJwGHRMS5wGeAzy08ZRZ1uNpavWRQliTNu8zckZmfy8w/o5jf+FTgYuBp5UNOKS/n84sRcZ+6zmvncUaaXmltmOovh6wlSTXIzLwd+JeIuBj4HeDVwI8oFur8fkTcAZxLsar7y5OeyPAoSZI0LAvD1dvKBTOfBihXYT8R+GXgy5Me3PDYQY10EY97B2w6YfbnmaEhLpyRJGlCq67kzswbgI+Ut4kZHjumseCoueGQsiTNhc8t+vp2irmPy13KZyoumGlA1ZXWjc9bHECI7PtczyHMd5QktS8zX7Ho6x9l5uMy8xuzOJfhsSMaC0EDCIySJKk9hscZGHeldavdswGEyb53H2fJIWtJUt0Mj1JLHLKWJPWR4bFljXbNlusyDqD7KEmSmmF4bJHDrfXxtdyZQ9aSpFkwPM7YciutXVktSZL6yPDYgk52yQYQLjv5ui7D+Y6SpL4yPNZstZXWrQScAQRDjccha0nSrBgedbcBhMw+dR8lSeojw2ODDDYCh6wlSf1meJyhqh9LOFPjdhPtPkqSpBUYHqWBcb6jJGmW1rRdwJCM+7GEMzeALqIkSdO6efsuU/2P9c3bd6mvmAGw86idDSB0dnXo2vmOkqS+Mzw2xIuCqwkOWUuSZs3wqNEGED672n2UJKnPDI8z0omV1uoUh6wlSUNgeByiurqGdh8lSdIShseadG6lteaO8x0lSU0wPA7NALqFkiSpuwyPDej10OkAwmgXXn/nO0qShsLwOCQDCHqajEPWkqSmGB5nYHArrQcQSrvQfZQkaQgMj9KMOWQtSRoSw2MNOrHSetbdQbuPkiQJWNN2AVrGAMKamuF8R0lSkwyPMzZWt8vAWN3Ca7XphHbrkCRpzjhs3bbj3nH3reu6UuPiOsasqemha+c7SpKGxs5jzSqttO5ACNuF57KD09ouY3wdeO26xCFrSVLT7Dw2rQPhZxeeO/mT26y/pnO7cEaSpMkZHqc01krrDgTHxaYKkV3Ssdd1gUPWkqQhMjxqfG2EtZrPafdRkqTJDDY8RsSuEbFumdtuTdTQxYCytNvYi+5jleDY0e7jLDnfUZLUhsGGR+A5wA+Xub28xbqGoamwNoehUJI0fBGxNiLOiIiD2q5lXEMOjwueDTxpye2DszhR1z/TuhddxsXGDY4dumyP8x0lSUtFYX1EPA04D3hK2zVNYh4u1XNxZl7RdhFd1snL9thxXJFD1pLUS+uB7wB3Ad9ruZaJzUPncWb6tNJ6Jl3HWX1P0xy3Q91HSZKW2AocBdwPeHu7pUzO8DgjfQslvRvS7jCHrCVJo2TmtszcnJk3tV3LNOYhPD4nIr4WEd+PiNMj4sC2CxqUuruPLXRo+xb0JUlq0zzMeTwReDfwVeD/Ay6OiEdn5vUrPSkiLl1m14ZRd3Z5sUzVrmLrcx/rCo7HvQM2nVDPsTrI+Y6S1IoNy2WDzDyi6WLaNA+dx+Mz82WZ+bfAUykmq76u5ZrUMXYfJUmqZsjh8YPAAcD7F+7IzMuBL1JcA3JFmXnEqBuwZexKWlwsM+5cxonmPnZxZXQXa5Ik9dmWFbLBXBlseMzM2zPz2szMJbu+AxwYEXvP6txd6WK5CGY8XXnfJEnqssGGxxXcG0hgR9uFdNU8h846AmSX579KkjStwYbHiFg/4r4AHg58MzNvbaSQloZP5zkA/tiEr70dSEmSljfI8BgR+wGXRMSjlux6FnAwcMq05xjrAuGLNBHq6jiH4XM6dh8lSUM11Ev1XA+cCVwUEf8MnAscArwC+DTwN20U1ZfgqKL7uHXTTs1rSZKmEhHPKr88stweGxFbgesy8/yWyhrLIDuP5SKZ/wK8Hngo8Dbgl4A/Bo7JzO11nm9xl+keQ57LDJv2JeCNVWdXVzdPUZfD15KkGTi9vP1m+e93lv/+w9YqGtMgwyNAZt6ZmSdn5qMyc8/M3JiZb6k7OE5qFgGyL6F0Xjh0LUlaKjNjmdsT266tqsGGx66ZdbCb1fHnPZDafZQk6Z4Mj7NSYbh03oNZY6YcUjdASpJ0N8NjjdoKGX3tavbJpO+tQ9eSpKExPDZgpfA1bTAz2FXU1QU9kiT1jOFxFhoKKk0Gx0rnGnhAc/hakiTD49RWG5asErr60j3sS52zNEmAdOhakjQkhseaTNuVGjeYGeQmUFNn1A6kJGmeGR7r1sDQbZvB0dA6GbuPkqShGOrHE3bCJN3EHZw2o2oactw7YNMJ1R4nSZJ6x/A4Qzs4rZYA2bVu30I9ywbdhWC46QRDYumCzRtrOc4ZV6+r5TiSJE3K8DiBvdbsAGY3FNm1sLicVTulXQuOVTqiFWzdtH6sx9cRHA2NkqSucM6jptKXoFsXg6Mkad7ZeazBvK++XXUYWxMxNEqSusjOo2rT6S5kDUPWTXYdDY6SpK6y8zghL70y2lC7kE0FR0OjJKnr7DzO2NBCVFWd7kKOadzgOCmDoySpDwyPmpldeG43QmRNq6yrmqTraHCUJPWFw9aauT4PZc96uNrQKEnqGzuPE9h9t20//nreV1qPo5VO5BRdxzYuyyNJUtcZHtW4zgxnr6CJeY52HSVJfeSwtVrT5+HspRyulqTuuuWu2/jEtoumer7uZuexAUMIR7M0s07khEPWDldLkrQ8w6M6owvD2Q5XS5K0MsOjOqcLIbIqh6slSfPG8DgFV1rP1lQhcoIhay/LI0nS6gyP6rwmOpHOc5QkqRrD44RGdh2Pe0fzhcyRrgxlTxocj33QDfUWIklSCwyPDehK6BmCyq/ljIL8tB1HA6Qkqe+8zuME1uy9fec7lwkrBsf67cJza738UZUha4epJUkq2HlULzUZyusOjnYfJUl9Znisg13HwZpVx9EAKUnqK8PjtAyOrVn1NZ5y3uOsh6oNkJKkPjI8aq418YkykiQNieFxGnYdWzer17qpBTJ2HyVJfWN4rJnBUeM69kE3GCIlSb1heJyUFwTvjKEEdgOkJKkPDI+T2OuBI+8eSogZlAlCfpvXdLQLKUnqOsOjBmGS4N7lxTIGSElSVxkea2LXcRi69EkyBkhJUhf58YQ1MDgO1xlXr/vx122EuYVzLq5DkqQ22XnUYCwb4ivOe1zadVwa2M64et2Pb02zCylJwxARu0fEyRFxbUTcEhEfiYiD265rHIbHKdl17Kdp5zu2ESJdTCNJ/RYRAXwEeAHwPuC1wOHAhRGxf4uljcVh6ykYHIdjta7jctoe1pYk9cozgWOAJ2fmWQARcSbwdeDNwO+2WFtldh4nZHDskU0n3OOfs1pl3UQ30rmPktRrTwcuXQiOAJm5BTgd+PWyM9l5hseJ3LftAjTCDk6b6Hl1r7CeRcBra66lJKlWxwBfHHH/JcB+wIObLWcyhkcNwrLBsaGu41J1hj1DoyT1X0SsBdYD3xqxe+G+w5qraHKGR/Ve1eDYhmmCn91GSRqUvcrtthH7biu3uzVUy1RcMKNhGhEcR3Udm7go+EIAHGdBjaFRkjpnQ0RcOmpHZh5R4fl7lNu7RuzbUW53naSwptl5VK9VnefYhY8irBII7TZK0mDdWm5HNe7WlttbGqplKnYe1VuzGq6eZXhbqQtpaJSkTttSscO4nJvK7T4j9u1dbm+c4viNsfOoXhonOC7XdWzzc6xHfXqNJGm4MnM7cB2wYcTuhYUy1zRX0eTsPKp3Jr0kT9cYGCVp7pwJHB0RazPzzkX3Pxa4PDOvbKmusdh5VK+sGBzH6DpKktSCjwIHAL+xcEdEHAYcC3y8raLGZedRvVFncGxzyFqSNLc2AZ8F3hkRD6ZYef1yYCvw520WNg7Do3ph3OAoSVLXZOaOiHgK8GfAKymu63g28KrMvK7V4sZgeFTnTTLH0a6jJKmLMvNm4GXlrZec86hOWzU42nWUJKlRhkd11qTBcZpFMq6AliRpZYZHddKsgqND1pIkTcfwqM5xqFqSpO4yPKpTpgmOXtNRkqTZMzxqbjhkLUnS9AyP6gy7jpIkdZ/hUZ0wlM+rliRp6AyP6ocpu44OWUuSVA/Do1rXldXVXuNRkqTVGR7VKoerJUnqF8Ojum2VrqND1pIkNcvwqNbYdZQkqX8GHR4jYveIODkiro2IWyLiIxFxcNt1qSK7jpIkdc5gw2NEBPAR4AXA+4DXAocDF0bE/i2WJuw6SpLUV2vaLmCGngkcAzw5M88CiIgzga8DbwZ+t8Xa5lql4FhD11GSJNVvsJ1H4OnApQvBESAztwCnA79ediY1YA5ZS5JUvyGHx2OAL464/xJgP+DBzZYjsOsoSVLfDTI8RsRaYD3wrRG7F+47rLmKBN2e5+gFwiVJqmaocx73KrfbRuy7rdzuttIBIuLSZXY9bMuWLRxxxBGT1jbHblz9ITdfu+Lu7TetAS5f9TC3bdsNuKJSVQA3b9+l8mMlSZO5eceNUDR3GrUj7+CHt311qufrbkMNj3uU27tG7NtRbned8Nh33XHHHbdedtllV034/HmxodxuqfewO1Z/CAD+oJdm9D5oTL4P3eD70L6HAfdp+JxbINmRo/pJ4x5HMNzweGu5HfX9rS23t6x0gMy0tTiFhc6tr2O7fB+6wfehG3wf2rfCqN7MZOYzmj7n0A1yziNwU7ndZ8S+vctthTFUSZIkLTbI8JiZ24HruHuIYrGFhTLXNFeRJEnSMAwyPJbOBH66XHm92GOByzPzyhZqkiRJ6rUhh8ePAgcAv7FwR0QcBhwLfLytoiRJkvpsqAtmADYBnwXeGREPplh5/XJgK/DnbRYmSZLUV5GZbdcwMxGxF/BnwK9RXNfxbOBVmXlFm3VJkiT11aDDoyRJkuo15DmPkiRJqpnhUZIkSZUZHiVJklSZ4VGSJEmVGR4lSZJUmeFRkiRJlRkeNbaI2D0iTo6IayPiloj4SEQcXPG5j4mIcyLihoi4PCJOiYh1My55cKZ5D5Yc53ERcVJEPLH+Kodv2vchIu4TEW+LiP8ofybOjognzbLmIZryd9JPRMQ/RcSVEfGDiDgrIn5m1jUPWUSsjYgzIuKgMZ5Ty+80NcPrPGosEREUnxv+WOBU4NvAK4A9gEdl5tYVnvtI4BLgA8AFwCOAlwJXAT+dmd+fafEDMc17sOQ4a4HNwMOBP8zMk2ZR71BN+z5ExL7APwOHA/8IfAXYAHw5Mz88u8qHZcrfSQ8BvgRcC/w9cBvwK8AvAc/IzI/NtPgBKd+HBwMbgdcDPwMcXOVDOer6naYGZaY3b5VvwC8DCRyz6L4NwHbgr1d57rnAyUvuO7o83sl11zrU2zTvwZLjvLR8TxI4qe3vq2+3ad8HiuD4fWBj299Ln29T/k76H8A1wLpF9wXwL8AVbX9vfboBP1G+DzuA75ZfHzTr99BbOzeHrTWupwOXZuZZC3dk5hbgdODXy/+D3Ek5NP1zwJ8svj8zz6EIMM+eVcEDNNF7sFj50Z0nAXa4Jjfx+xARjymf/9bM3DzzSodtmp+HRwMXZeYNi56bwBnAQyJin9mUPEhbgaOA+wFvH/O5U/9OU7MMjxrXMcAXR9x/CbAfxbDFTspfzsdn5vdG7N4M7FcO42l1E70HS7wWuBP4SH1lzZ1p3odXU7z+fz+DuubNNO/DV4HDImLp38KHA1cDP6ylwjmQmdsyc3Nm3jTB0+v4naYGGR5VWTlHbj3wrRG7F+47bLnnZ+Z7l9l1AMVQxy1TFTgHpn0PymMcSBFe/hK4o9YC50QN78ORwNeB+0XEh8uFGt+IiBfWXOqg1fA+vAHYG3hPRBwREQdFxKuA5wEvLruQmqE6fqepeYZHjWOvcrttxL7byu1u4xwwItYAjwMuyEyDzOrqeA/eAtwAnFJTTfNo4veh7HJtKP/5KeByihBzA0WIeVp9ZQ7eVD8PWSzmeBTwEIou5LeBVwL/T2Z+sr4ytYLa/65o9ta0XYB6ZY9ye9eIfTvK7a5jHvN1FJ1H5zxWM9V7EBGPAF4IvCwzb4uI3Wuub15M8z48gOKP4SOAx2fmhQAR8UGKlb9vAD5eX6mDNu3Pw27Au4EDgeOBW4HfAT4UEcdk5tU11qrRZvF3RTNm51HjuLXcjvqfjrXltvLQc0Q8GjgReGFmXjRlbfNi2vfgrRTdlXfXWdQcmuZ92F5uP78QHOHH84I/ADzOa59WNu3Pwx8Dj6cI8f+YmR+imH93O/A/XajRiFr/rqgZhkeNY2Ei9KgViHuX2xurHCgiDqHorrwxM0+robZ5MfF7UF58+liKAHnviNgT2LPcvWtE7Fl2YrS6aX4WFp77jRH7vl1uvThyNdP8POwC/Dbw0Vx0HcHM3A68h+LqEA+rr1Qto7a/K2qO4VGVlb9Ur+Pu+VqLLUxovma140TEAcBZwKmZ+bb6Khy+Kd+DJ5TbfwBuLm8LYeUN5b//rp5Kh22a96Gc2/ttiukaS+1SbreP2Kclpvx52BfYHbhixL6F+w6avDpVUdffFTXLOY8a15nA0RGxNjPvXHT/Y4HLM/PKlZ5cXjftU8AmiusManyTvgfvAc5ect864GMUn3DyHoprtamaaX4W/hV4ZkSsKf94LljodH17xHM02qTvw3UUi5QeMmLfQeX2/9RVpFY01d8VNc/Oo8b1UYqOyW8s3BERh1EMh644yb8cJj0DuBB4jZfBmNhE70FmXpmZFy6+AReXuxf2+ceyuol/FoD3UiwU+M1Fz92X4hIx78tM53hVN+nPQwL/G3hWORqy8Ny1wEuAL2OIb8o0P0tqgZ9trbGU84TOp7hO3Z9SrJB7OUUX+8jMvK583BOA/TLzfy167lkU/0f/+4xeWffJzLx1xP1aZJr3YMSx7k/RgfGzrcc05c9CAB+i+AzlP6VYoPFiijleP+0q3+qmfB/uD3yBopFyMsXijRdRXCT85zPz8w1+K70XEc8qv3wGxf8YvYxiNOO6zDy/fMyo96HSe6gOafvzEb3170ZxXa53UvxSuIni/94PWvKYT1P+z/2i+3KV20FN1D+E26TvwYjj3B8/27qV94FifuMfAd8Bvgd8EDig7e+pj7cp34d9gFMpuoxbKabUHNb299TH2wq/2z9d4X1Y9T301p2bnUdJkiRV5pxHSZIkVWZ4lCRJUmWGR0mSJFVmeJQkSVJlhkdJkiRVZniUJElSZYZHSZIkVWZ4lCRJUmWGR0mSJFVmeJQkSVJlhkdJkiRVZniUJElSZYZHSZIkVWZ4lCRJUmWGR0mDEBEHRURGxPkRsU9EvD0iroiI7RFxctv1SdJQrGm7AEmqyVHl9lbgKxS/3z4DfA24pKWaJGlwDI+ShmJjuX0KcCpwQmZua7EeSRokw6OkoTiq3F4E/HZm3tViLZI0WM55lDQUR5Xb1xgcJWl2IjPbrkGSphIR9wVuAK4FDkx/sUnSzNh5lDQEC/MdP2NwlKTZMjxKGoKjyu2X2ixCkuaB4VHSECx0Hg2PkjRjhkdJQ3BUuTU8StKMuWBGUq9FxBrgFuD7mfmgtuuRpKGz8yip7x4G3Bu7jpLUCDuPkiRJqszOoyRJkiozPEqSJKkyw6MkSZIqMzxKkiSpMsOjJEmSKjM8SpIkqTLDoyRJkiozPEqSJKkyw6MkSZIqMzxKkiSpMsOjJEmSKjM8SpIkqTLDoyRJkiozPEqSJKkyw6MkSZIqMzxKkiSpMsOjJEmSKjM8SpIkqbL/C6DaVY/kBjxkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 750x450 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# cluster number with adjusted coloring\n",
    "fig, ax = plt.subplots()\n",
    "contour = distance_rclustering.summarize(\n",
    "    ax=ax, quantity=\"n_clusters\",\n",
    "    contour_props={\"levels\": [-0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5],\n",
    "                   \"vmax\": 5}\n",
    "    )[2][0]\n",
    "colorbar = fig.colorbar(mappable=contour, ax=ax, ticks=(0, 1, 2, 3, 4, 5))\n",
    "ax.set_yticks([0, 5, 10, 15, 20])\n",
    "colorbar.set_label(\"# clusters\")\n",
    "ax.set_xlim(None, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The probably most telling view is given by the *number of clusters* plots. The analysis demonstrates nicely that for this data set a splitting into 3 meaningful clusters is hard to achieve."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-19T10:35:00.015683Z",
     "start_time": "2019-09-19T10:34:59.968481Z"
    }
   },
   "source": [
    "### Hierarchical clustering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use the hierarchical approach to clustering this data set, we will apply a pair of cluster parameters that will extract the lesser dense region of the data as an isolated cluster in a first step. That means we choose a comparably large value for the neighbour search radius *r* and a rather low value for the similarity criterion *c*. We can refer to these parameters as *soft* parameters, leaving the more dense regions of the data untouched and in one cluster. Remember that density in terms of common-nearest-neighbour clustering is estimated as the number of common neighbours within the neighbourhood intersection of two points with respect to a radius *r*. More common neighbours (higher similarity cutoff *c*) and/or a smaller neighbourhood radius (smaller *r*) will result in a higher density requirement. To make this more clear let's have a look again at some clusterings. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.407330Z",
     "start_time": "2021-03-22T18:45:57.160847Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Cluster attempts in comparison\n",
    "fig, ax = plt.subplots(2, 2)\n",
    "Ax = ax.flatten()\n",
    "for i, pair in enumerate([(0.18, 6), (0.2, 5), (0.6, 17), (1, 30)]):\n",
    "    distance_rclustering.fit(*pair, member_cutoff=5, record=False, v=False)\n",
    "    rclustering._labels = distance_rclustering._labels\n",
    "    _ = rclustering.evaluate(ax=Ax[i], ax_props=ax_props)\n",
    "    Ax[i].set_title(f'{pair[0]}, {pair[1]}', fontsize=10, pad=4)\n",
    "\n",
    "fig.subplots_adjust(\n",
    "    left=0.2, right=0.8, bottom=0, top=1, wspace=0, hspace=0.3 \n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Lower right__: Choosing a high radius cutoff ($r=1$), i.e. a soft density requirement, results in no cluster splitting. The data set as a whole forms clusters in which the point density is *at least* as high as our density requirement.\n",
    "\n",
    "__Lower left__: When we increase the density requirement ($r=0.6$, $c=17$), we observe a splitting between the broadly distributed lower density cluster and the more dense clusters. Within both the resulting clusters the point density is higher than required by the parameters but they are separated by a low density region and therefore split. This parameter set can be used for the first step of the hierarchical clustering.\n",
    "\n",
    "__Upper right__: Increasing the density requirement further ($r=0.2$, $c=5$), leads to a splitting within the broad cluster first, while the more dense clusters still remain united. Obviously, the point density in the region between the two dense clusters is higher than in parts within the low density cluster.\n",
    "\n",
    "__Upper left__: Choosing parameters hard enough ($r=0.18$, $c=6$) to achieve a splitting of the two dense clusters, does also completely split up the less dense cluster. We could use this parameter set in a second hierarchical clustering step."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The central element of the hierarchical cluster functionality is the `isolate` method of a cluster object. After a clustering (with soft parameters) we can *freeze* the result before we start to re-cluster. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.434164Z",
     "start_time": "2021-03-22T18:45:57.408621Z"
    }
   },
   "outputs": [],
   "source": [
    "# After the first step, we need to isolate the cluster result\n",
    "rclustering.fit(0.6, 17, member_cutoff=5, record=False, v=False)\n",
    "rclustering.isolate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `isolate` method will create a new cluster object (a child cluster) for every cluster of a cluster result.\n",
    "In our case we get two new child clusters (plus one for outliers). The clusters are stored in a dictionary under the `children` attribute of the parent cluster object. The children dictionary of the data after isolation holds a cluster object for each cluster found in the last step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.447427Z",
     "start_time": "2021-03-22T18:45:57.435507Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: cnnclustering.cluster.ClusteringChild,\n",
       " 2: cnnclustering.cluster.ClusteringChild,\n",
       " 0: cnnclustering.cluster.ClusteringChild}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{k: type(v) for k, v in rclustering._children.items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we will use different cluster parameters now for different clusters it would be nice to have something\n",
    "to keep the overview of which cluster has been identified under which parameters. This information is provided by `labels.meta`. A label info tells us three things:\n",
    "\n",
    "  - `origin`: How have these labels been assigned? The entry `\"fit\"` means, they were obtained by a regular clustering.\n",
    "  - `reference`: This is a related clustering object, i.e. the object that is associated to the data for which the labels are valid. For `\"fitted\"` labels this is a reference to the clustering object itself that carries the labels.\n",
    "  - `params`: This is a dictionary stating the cluster parameters (*r*, *c*) that led to each cluster. For `\"fitted\"` labels, each cluster has the same parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.458401Z",
     "start_time": "2021-03-22T18:45:57.448682Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'params': {1: (0.6, 17), 2: (0.6, 17)}, 'reference': <weakproxy at 0x7f3be6647db0 to Clustering at 0x7f3bebfa16a0>, 'origin': 'fit'}\n"
     ]
    }
   ],
   "source": [
    "print(rclustering._labels.meta)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Every single isolated child cluster is a full-fledged, completely functional cluster object itself. When we want to re-cluster a child cluster, this is no different to clustering a parent cluster. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.472579Z",
     "start_time": "2021-03-22T18:45:57.462606Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hierarchy_level: 1\n",
      "input_data_kind: points\n",
      "points: 678\n",
      "children: None\n"
     ]
    }
   ],
   "source": [
    "child1 = rclustering._children[1]\n",
    "print(child1)  # Child cluster 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note, that the `hierarchy level` in the above overview has increased to 1. We can again plot the distance distribution within this child cluster to see how this changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.589120Z",
     "start_time": "2021-03-22T18:45:57.474998Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "distances_child1 = pairwise_distances(child1.input_data)\n",
    "fig, ax = plt.subplots()\n",
    "_ = plot.plot_histogram(ax, distances_child1, maxima=True, maxima_props={\"order\": 5})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And then we can attempt the second clustering step. Very small clusters may appear in the result. To filter those out because they are irrelevant, we can use the `member_cutoff` keyword argument of the `fit` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:57.793107Z",
     "start_time": "2021-03-22T18:45:57.590587Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------------------------------------\n",
      "#points   r         c         min       max       #clusters %largest  %noise    time     \n",
      "678       0.180     6         None      None      22        0.494     0.090     00:00:0.009\n",
      "-----------------------------------------------------------------------------------------------\n",
      "\n",
      "-----------------------------------------------------------------------------------------------\n",
      "#points   r         c         min       max       #clusters %largest  %noise    time     \n",
      "678       0.180     6         5         None      2         0.494     0.124     00:00:0.009\n",
      "-----------------------------------------------------------------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'member cutoff 5')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now cluster the child cluster\n",
    "fig, Ax = plt.subplots(1, 2)\n",
    "child1.fit(0.18, 6)\n",
    "_ = child1.evaluate(ax=Ax[0], ax_props=ax_props)\n",
    "Ax[0].set_title(f\"member cutoff 1\", fontsize=10, pad=4)\n",
    "\n",
    "# When the result is satisfying, but also a few very small clusters are found,\n",
    "# this can be surpressed\n",
    "child1.fit(0.18, 6, member_cutoff=5)\n",
    "_ = child1.evaluate(ax=Ax[1], ax_props=ax_props)\n",
    "Ax[1].set_title(f\"member cutoff 5\", fontsize=10, pad=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a little extra feature a cluster object has a `pie` method that allows to visualize the current state and splitting on the different hierarchy levels as a pie-diagram (from level 0 in the middle to lower levels to the outside)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:58.006658Z",
     "start_time": "2021-03-22T18:45:57.794535Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.3, 0.3)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The cluster hierarchy can be visualised as pie diagram\n",
    "fig, ax, *plotted = rclustering.pie(\n",
    "    pie_props={\"radius\": 0.2,\n",
    "    \"wedgeprops\": dict(width=0.2, edgecolor='w')}\n",
    ")\n",
    "ax.set_xlim(-0.3, 0.3)\n",
    "ax.set_ylim(-0.3, 0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have isolated one cluster in the first step and two others in a further splitting on a lower hierarchy level, the last step that remains, is to put everything back together. This can be done automatically by calling `reel` on the parent cluster object into which the child cluster results should be integrated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:58.010927Z",
     "start_time": "2021-03-22T18:45:58.008098Z"
    }
   },
   "outputs": [],
   "source": [
    "# Wrap up the hierarchical clustering and integrate the child clusters into\n",
    "# the parent cluster\n",
    "rclustering.reel()\n",
    "\n",
    "# Manually sort clusters by size (make largest be cluster number 1)\n",
    "rclustering._labels.sort_by_size()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:58.115059Z",
     "start_time": "2021-03-22T18:45:58.012124Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.3, 0.3)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rGrjhL1NYsKLe7bpERDJKYZ6fn3x5FIcM6xl96QHgm4C2mMhwClSZL4TTEuHLAG9MX8Gv/vkhjS3t7lYlIpKhjIEvHT+Qy08dgtdpBPoRzhTgfHcrk0RSoMpstcB/gAM6IpZ7JnzKw6/o/2cRkWQYPbicn31lNKWFOVhrNxtjvoqzaF0ykAJV5jq1syVC8Yb6Vn7ywDSmzV3rdk0iIlmlvCjIzy8dzQEDyqIv/R64Dgi7V5UkggJV5vECPwVuAvh4wXp+fP9U1mxUSwQRETd4PYarzhjKxccOiL70GnA2aq2QURSoMksh8BhwIsDjbyzgjifVEkFEJBUcMaIXP/nSKHKDPoCPgZOBJe5WJfGiQJU5egPPAyOaW9v5zb8+4qUpaokgIpJKBvUp5HdXH0RFcRBgOU6oUr+qDKBAlRmGAv8D+q7b3MK1d73PnCUaSRYRSUU9S0Lc9vUDqe1diLW23hhzLvCS23VJbBSo0t+h1tpnjDEli1Y18L0732PFuia3axIRkV3ID/m45cpxjB5UjrW2wxhzJU7PKklTClTp7Sxr7SPGmODHC9bzg3sms6mxze2aRERkD/h9Hm64+ABOGNe1D+DPgf9DmyunJQWq9PUNa+0dxhjz9owV/OSBD2gNd7hdk4iI7KUrTx3CV04aFD38O3AloN+O04wCVfoxwM04fUz479t1/P7fM+mI6N+jiEi6OuPQflz7hf3xej0Ar+B0Vtdi2DSiQJVeAsBfgS8C3Pv0p/z9xXnuViQiInFx0L49+OXlY8jN8QHMxLkDcKm7VcmeUqBKHwU428gc19ER4ZZHPuL599S+REQkkwyqLuLWqw+kvCgIsAw4BbVVSAsKVOmhEngOGNnU2s6Nf53Ke5+sdrsmERFJgF6lIW77+kHUVBZE2yqcA7zsdl2yawpUqW8wTo+p/us3t3Lt3e8xe7Gm1UVEMllByM/NV46NtlVoN8ZcATzodl2ycwpUqe1ga+2zxpjSJaudHlPL1qrHlIhINvD7PNxwyQGcMLarrcKPcW5KkhSkQJW6zrDWPmqMCc6q28AP7n6fjQ26i1ZEJJsYA1eeNoQvn9DVVkG9qlKUAlVq+oK19mFjjHfizJX85IFptLSpx5SISLa6+NgBfOOsfaOHt+CMVukv8BSiQJV6LrTWPmSM8Tz33mJ+/fBH6jElIiKcf1Qt15y7X/TwVuCHKFSlDAWq1HKRtfafxhjPM+8u4tePfIT+9YiISNTZR/Tn2i8Mjx7+CbgGhaqUoECVOi6x1v7dGON5+p1F/OZfClMiIvJ5Zxzajx9dNCJ6eDfwTSDiXkUCClSp4ovW2geNMZ4JE+v47aMzFKZERGSnTjmomusvPgCPxwBMB8YAWmzrIo/bBQhfjo5M/fdthSkREdm9595bwp//Oyt6eAAwDf2d7ir9w3fXl6y1fzPGmCffruPWxxSmRERk93oUBznniJqtXxoB3AUYdyoSBSr3fKErTL21kFs1MiUiInugR3GQO685lKqKPMLhMH/+85+JRCIAXwPuQKHKFT63C8hSZ3b2mfJMmFjHrY/NdLseERFJA9uHqQsvvJCZM2eyZMkSbrnlFjwezzeAduC76O6/pNIIVfKdaK19zBjjfeH9Jfz20Rlu1yMiImlgZ2EK4KmnnuKmm26Kful3gN+hkaqkUqBKrqOstf81xgRe/WAZNz80XdN8IiKyW7sKU1FPPPHE1qHq+zjd1CVJ1DYheQ611r5ojMl7e8ZKbvjLFHVAFxGR3dqTMLW1L37xi9x4443RwyuBvySjzmynEarkGGOtfd4Yk/f+J6u56f6pClMiIrJbexumAP75z39y9913A2CtvQc4M/GVigJV4g3pHJkq/GDuWq67bwpt7WpoKyIiu9adMBV1++238/jjj2OM8VhrHwWOSGy1oim/xKoA3gdqPl64nmvumERTqxrZiojIrsUSpqK8Xi933HEHxxxzDNbaTcaYwwHdVp4gClSJEwJeAw5atqaRK259m40NbW7XJCIiKS4eYSoqJyeHBx54gDFjxgCsAA4B6uJXrURpyi8xPMA/gIM2N7bx/bveU5gSEZHdimeYAmhtbeXqq69m7ty5AJXAi0B5nMqVrShQJcYtwLnh9gjX3TeFxasb3a5HRERSXLzDVNTmzZu57LLLWLZsGcAg4DkgP+YTyzYUqOLvSuCHADc/NJ3p89e5XI6IiKS6RIWpqNWrV3P55ZezYcMGgHHAE4A/bhcQBao4O8FaexfAX5+bzYtTlrpdj4iIpLhEh6moBQsWcOWVV9LU1ARwAvAAygFxo3+Q8TPcWvu4Mcb7/HtLeOD5uW7XIyIiKS5ZYSpqxowZfPvb3yYcDgNcAvwqYRfLMgpU8dEbeM4YUzBt7lp+/ch0t+sREZEUl+wwFfX222/z4x937UpzHXBRwi+aBRSoYpcPPAP0WbSynhvum0J7h1pRiIjIzrkVpqImTJjAPffcA4C19n5gbNIunqEUqGLjBR4BRm2ob+X7d71PfXPY7ZpERCSFuR2mom6//XZee+01jDFB4CmctgrSTQpUsfkDcFprWwc/vGcyy9c1uV2PiIiksFQJUwDWWq699lrmzZsHztKV/wJBV4rJAApU3fdt4FsAP//HB8yq2+ByOSIikspSKUxFNTY2cvXVV7Nx40aAA4H7AONqUWlKgap7TrfW3g5w538/4fUPV7hcjoiIpLJUDFNRS5Ys4Tvf+Q7t7e0AXwS+73JJaUmBau+NsNb+yxhjJkys4+FX5rtdj4iIpLBUDlNR7733HjfffDMA1trfAie7W1H6UaDaO4XAE8aY3MmfrubWx1LrfwgREUkt6RCmoh5++GEee+wxjDHGWvsvYIjbNaUTY61u8d9DBngUOH/l+ia+8us32dyoO/pERGTH0ilMRfn9fh588EHGjBkDMA9nXZUWCe8BjVDtuauB89s7Itx0/zSFKRER2al0DFMA4XCYb33rW9GNlAcCjwE+d6tKDwpUe2a0tfYPAHc99Ynu6BMRkZ1K1zAVtX79er7+9a9H9/w7Dvi5yyWlBQWq3SsC/m2MCbw9YwWPvrbA7XpERCRFpXuYipo9ezY33HADANba63CCleyCAtWuGeB+oHbFuiZ++Y/pLpcjIiKpKlPCVNQLL7zAo48+Gl2k/hDQy+2aUpkC1a59Ezgn3B7hxvunalsZERHZoUwLU1E333wzc+bMwRjTA3gYZ8s12QEFqp0ba629DeDO/87i00UbXS5HRERSUaaGKYDW1lauueaa6Hqqo4HrXS4pZSlQ7VgJzrop/+sfLuffbyx0ux4REUlBmRymohYsWMD//d//AWCt/RlwhKsFpSgFqs8zwN+A/svWNnLLw9NdLkdERFJRNoSpqAkTJvDkk09ijPEA/wLK3a4p1ShQfd41wBlt7R3c+NepNDS3u12PiIikmGwKU1G/+MUvWLBgAUBv4EGUIbahfxjbOrBzDyP+9J9ZzFmyye16REQkxWRjmAJoamrimmuuobW1FeAU4Lsul5RSFKi2KMVZN+V79YNlPPlWndv1iIhIisnWMBU1Z84cfvWrXwFgrf01ztY0ggJVlMEZvuy7ZHUDtzz8kcvliIhIqsn2MBX12GOP8fzzz2OM8eFsTVPidk2pQIHK8W3gtLZwBzfeP5WmFq2bEhGRLRSmtnXTTTexePFigH7A3S6XkxIUqGCAtfYWcNZNzVu62e16REQkhShMfV5DQwPf+973aG9vB/gCcI7LJbku2wOVB/iLMSY0ZfYanny7zu16REQkhShM7dzMmTP5y1/+Ej28G6hwsRzXZXuguhIY39zazq8f0bopERHZQmFq9+68807mzJkDTpj6s8vluCqbA1Vfa+3vAO55+lNWrGtyux4REUkRClN7JhwOc/3110en/s4HznO5JNdka6AywH3GmPyPPlvHE29qaxkREXEoTO2dWbNmcd999wFgrb0L6OFuRe7I1kD1JeCEtnAHtzw0HWvdLkdERFKBwlT33HXXXcyZMwdjTDlwp9v1uCEbA1WltfZ2gL88O4fFqxtdLkdERFKBwlT3hcNhrrvuuujU37k4039ZJdsClQHuMsYUf7poI4++9pnb9YiISApQmIrdJ598wr333guAtfZOsmzqL9sC1XnAmeH2CL966EM6IprrExHJdgpT8XP33Xcze/bs6NTfXTgDGVkhmwJVhbX2zwB/f3EuC5bXu12PiIi4TGEqvqJTf+FwGJxmn1kz9ZdNgeqPxpiK+cs2848X57ldi4iIuExhKjE+/fTT7af+erpbUXJkS6A6HbiwI2K5+aEPae/QVJ+ISDZTmEqse+65h08//RRjTBnwW7frSYZsCFTFwD0Aj7wyn9mLN7lbjYiIuEphKvHC4TA33XQTkUgEnFZFh7lcUsJlQ6C6DahctLKe+5+f43YtIiLiIoWp5Jk5cyZPPPFE9PBOwOdiOQmX6YHqeODSSMRy88Mf0RaOuF2PiIi4RGEq+X7/+9+zceNGgOHA192tJrEyOVAF6OzW+sSbC5m5YL3L5YiIiFsUptyxYcMG/vCHPwBgrf0FGbxAPZMD1TeBAWs3tXDfM5+6XYuIiLhEYcpd//73v/n4448xxhQCv3G7nkTJ1EBVbq39CcB9z8ymqbXD7XpERMQFClPui0Qi/OxnP4sefhk41MVyEiZTA9VPjTFFc5ds4vn3Frtdi4iIuEBhKnXMmDGDxx9/PHqYkQvUMzFQDbXWXg1wx5Oz0O4yIiLZR2Eq9dx2223RBeojgKvdrSb+MjFQ/c4Y4317xgqmzV3rdi0iIpJkClOpacOGDdx+++1AZi5Qz7RAdRxwSntHhD//9xO3axERkSRTmEptjz32WHSBehEZtkA9kwKVD/g9OG0SlqxudLkcERFJJoWp1BeJRPj5z38ePcyoBeqZFKguA/bb3NjG316Y63YtIiKSRApT6eOjjz7auoP6rYBxsZy4yZRAVQj8AuD+5+dQ3xR2uRwREUkWhan088c//pHm5maAg4AzXC4nLjIlUN0AVCxa1cCTb9W5XYuIiCSJwlR6Wr16NX//+9+jhzeTAW0UMiFQ1Vhrvwvw5ydn0aE+CSIiWUFhKr399a9/jbZRGAp80d1qYpcJgerXxpjAlNlreOfjVW7XIiIiSaAwlf7q6+u59957o4c/A4IulhOzdA9UhwLnRyKWO56c5XYtIiKSBApTmeOhhx5ixYoVANXAN1wuJybpHKg8wB8Anp20mPnLNrtcjoiIJJrCVGZpa2vjjjvuAMBaewNQ5G5F3ZfOgepCYGxTSzv3PTvb7VpERCTBFKYy01NPPcX8+fMxxpQCP3S7nu5K10DlB34F8I+X5rF+c6vL5YiISCIpTGWujo4Ofv/73wPQeZNZpbsVdU+6BqpLgH7rNrfw6GufuV2LiIgkkMJU5nv11Vf58MMPMcaEgJ+4XU93pGOg8gLXAzzyyme0hSMulyMiIomiMJU9brvtNgCstVcAA92tZu+lY6A6Dxi4qaGNpybWuV2LiIgkiMJUdpkyZQpvvvkmxhgvnbufpJN0C1Qe4McA/35jAc2tHS6XIyIiiaAwlZ1uu+02IpEIwBeA/VwuZ6+kW6A6DdivsTnME28sdLsWERFJAIWp7DVnzhxeeuml6OF1btayt9IpUBk6R6f+81Yd9c3aAFlEJNMoTMl9990HgLX2AqDG3Wr2XDoFqmOBsS1tHTymO/tERDKOwpQAzJo1i4kTJ0bXUv3A7Xr2VDoFqh8DTJhYx4aGNrdrERGROFKYkq1tNUp1KdDL3Wr2TLoEqsOAI8PtER55VaNTIiKZRGFKtvf+++9H+1LlANe4Xc+eSJdA9WOA599bzJqNLW7XIiIicaIwJTuz1SjV14FiV4vZA+kQqEYDJ3Z0RPjnS/PdrkVEROJEYUp25fXXX2fu3LkYYwqAr7tdz+6kQ6D6McDL05axfF2T27WIiEgcKEzJ7lhr+ctf/hI9vAbIda+a3Uv1QDUMOAvgHy/Oc7kUERGJB4Up2VPPPfccS5cuBagALnW5nF1K9UB1PcDrHy6nbmWD27WIiEiMFKZkb3R0dHD//fdHD38A+F0sZ5dSOVDtY629EODv/5vrdi0iIhIjhSnpjv/85z+sXbsWoC9wocvl7FQqB6rrjDGed2etYu7SzW7XIiIiMVCYku5qbW3lwQcfjB5eR4pml5QsCii31n4J4O//09opEZF0pjAlsfrXv/5FQ0MDwFCcnVNSTqoGqq8YYwKfLtrIzAXr3a5FRES6SWFK4qGhoYEnn3wyevhNN2vZmVQMVAa4EpxtZkREJD0pTEk8PfzwwwBYa08Fat2t5vNSMVAdBQxsbA7z8rRlbtciIiLdoDAl8VZXV8fbb7+NMcYAV7tdz/ZSMVB9DeDFKUtpbu1wuxYREdlLClOSKA899FD06WWkWKPPVAtUPa21ZwM8NXGR27WIiMheUpiSRHrrrbdYvHgxQAlwscvlbCPVAtVXjTG+jxeuZ/4ytUoQEUknClOSaJFIhEceeSR6+A2cddcpIZUClQe4AmCCRqdERNKKwpQky5NPPklrayvACGCcy+V0SaVAdSxQW98U5pVpy92uRURE9pDClCTTpk2beP7556OHX3Ozlq2lUqC6CuB/k5fQGtZidBGRdKAwJW547LHHALDWXgAUu1pMp1QJVL2ttaeDpvtERNKFwpS45cMPP2TOnDkYY0LAF92uB1InUF1qjPF+9Nk6Fqyod7sWERHZDYUpcdujjz4afXoVKbA4PRUClRctRhcRSRsKU5IKnn76aZqamgD2BQ51uZyUCFQnAH03N7bx2odajC4iksoUpiRVNDQ08MILL0QPv+RmLZAageoqgOffX0JbOOJ2LSIishMKU5JqJkyYEH16HpDjYimuB6pqa+0poOk+EZFUpjAlqWjy5MmsXLkSnDv9TnazFrcD1WXGGM+H89ayaFWDy6WIiMiOKExJqrLW8uyzz0YPXd2Kxs1A5QEuBe3bJyKSqhSmJNU9/fTTAFhrT8PFnlRuBqpxQHVjSztvfrTCxTJERGRHFKYkHcyZMyfakyoAnOtWHW4GqnMB3pm5UovRRURSjMKUpJNnnnkm+tS1aT+3ApWhM1C9/qFGp0REUonClKSbrdZRjQeq3ajBrUA1GujX3NrOe5+sdqkEERHZnsKUpKMVK1YwefLk6OGFbtTgVqA6F+DdWau0EbKISIpQmJJ0Fl2cDlzixvXdCFSa7hMRSTEKU5LuXnzxRdra2gD2B4Yn+/puBKoRwD6tbR1MmrXKhcuLiMjWFKYkE2zevJk33ngjepj0xeluBKpzASZ9sprmVk33iYi4SWFKMslW034XkeSMk+xAZXD22+H1D7QRsoiImxSmJNO8+eabNDQ0APQBxiTz2skOVMOAQa3hDt7RdJ+IiGsUpiQTtbW18fbbb0cPT0/mtZMdqM4FmPzpappa2pN8aRERAYUpyWyvv/569OlpybyuK4FKd/eJiLhDYUoy3ZtvvklHRwc4d/r1S9Z1kxmohgLDwu0RJs5cmcTLiogIKExJdti4cSMffPBB9DBpo1TJDFTnAkyZvYaGZk33iYgkk8KUZJPXXnst+jRp66iSHqhe/1B394mIJJPClGSbaKCy1o4HCpNxzWQFqkHA8PaOCG/N0HSfiEiyKExJNqqrq2PhwoUYY/zACcm4ZrIC1TkAU+espb4pnKRLiohkN4UpyWZbTfslZR1VsgLV6QBvaLpPRCQpFKYk220VqE4BfIm+XjICVbG1dhzAe5+sTsLlRESym8KUCHz44Yds2LABoBQ4JNHXS0agOsoY41m0sp7VG1uScDkRkeylMCXi6Ojo4M0334weJnzaLxmB6jiAybPXJOFSIiLZS2FKZFtbdU1PePuEZASqY8HpPyUiIomhMCXyeW+//TbhcBicbgO1ibxWogNVP2Bge0eED+etS/ClRESyk8KUyI41NjZu/f/CkYm8VqID1XEAn9RtpFGbIYuIxJ3ClMiuvf/++9Gn4xN5naQEqilzNN0nIhJvClMiu7ddoDKJuk4iA5UPOBPAY8CXzE1uREQynMKUyJ6ZPn06bW1tAH2BmkRdx1hrE3XuC4B/RQ+stazb3MrMBet5cfJSbUEjItJNClMie+eRRx5h9OjRAJcBDyTiGonsHDoQoL1hPcbnxxssoLwoyFEje3PUyN5EIpbVG5uZPn8dz7+3hKlz1iawFBGRzKAwJbL3Jk+eHA1U40lQoErkCNV/gTPXvvRHNrzzT3IqB5NbO45QzVhC/UbiCYS2+eKOiGXluiamzV3Lc5MWM3PhhkTVJSKSlhSmRLrn4IMP5sEHHwRYgtOBIO7hJ1GBygOsAUoX3/tFWpd+vO27Xh/Bqv2cgFU7lmD1cDy+wDZf0t4RYdmaRibPXsOEdxaxYHl9IuoUEUkLClMi3RcKhZg8eTKBQABgH2BBvK+RqEC1PzAj0trEZzcfCZFdt0wwvhyCfUeQWzuWUM04glX7Yrzbzka2hTtYvLqR92atZsK7dSxb05SIukVEUo7ClEjsEr2OKlFrqI4EaF48fbdhCsC2t9K8YDLNCyYDd2ICuYT6jXICVu1YcioHE/B7GVBVyICqQi4+bh9awxHqVtTzzscrmfDOYtZu0j6BIpJ5FKZE4mOrdVRHkYBAlagRqieAc9a+fAcb3oq9Zk+okFD/0Z1rsMaQ03PANu9ba2lu7WD+8k289dFKnn13MZubwjFfV0TETQpTIvGz1TqqpTgtFOIagBIRqAywCqhY8pev0LL4o3ifH29+GaGaMeTWjCFUO45AWd9t3rfW0tDcztylG3njwxU8995iWtoica9DRCRRFKZE4isYDDJlypToOqoBwGfxPH8iAlUt8FmkvY3PfnkodCR+yxlfUS9CNWOdgLXPOPxFvbZ531rL5sYwny7awKsfLuflKctoa1fAEpHUpDAlkhgPP/wwY8aMAbgcuD+e505EoDoP+HfL0lksufeSeJ97j/hLqwnVjiW3xlmD5csv2+Z9ay0b6lv5eOEGXp66jNenLyeifCUiKUBhSiRxrr32Wq644gqAe4Gr4nnuRCxKHw3QuvzTBJx6z4TXLyG8fgmbpz4JQKBHLaGaceTWjiHUfwze3CJKC4McMaKSI0ZUErGWtRtbmLFgPS+8v4RJs1a7VruIZC+FKZHEmjVrVvTp6HifOxEjVC8Dx6566udsnvbfeJ87dsZDTq9BzhRh7VhC/Ufhycnb5ksiEcvKDc1Mn7eWZyctYfr8dS4VKyLZQmFKJPGqq6t55ZVXANqAgs4/4yLegcoA64CSxXdf5Ooo1R7z+AhW7esscq8dR7DvCDz+4DZf0t4RYcW6JqbOWcsz7y5i9uJNLhUrIplIYUokeSZPnkxRURHASGB6vM4b70DVH1ho28N89stDsR3p17rA+AIE++zftQYrWD38c01Gw+0Rlq5p5P1PV/P0xEXUrWpwqVoRSXcKUyLJ9eCDD3LwwQdDnBemx3sNlbN+atW8tAxTALa9jea6aTTXTWM992D8QUL9RnZNEeb0Horf56WmsoCaygIuOHofWsMdLFrZwKRZq3hqYh2rNqjJqIjsnsKUSPLNmjUrGqhGk/KBKh2m+vaQDbfQNH8STfMnsQ7wBPMJ9RvljGDVjiOn1yBy/F4GVRcxqLqIL50wkJa2DhasqGfizJU8/c4iNtTHbYpWRDKEwpSIOz7+uGt/4bguTI/3lN+LwPGrJvySzVP/E8/zpixvbgmhmtFdI1iBippt3rfW0tTSzrxlm3hz+kqem7SYhpbE9+YSkdSlMCXinn79+vHSSy8BtOIsTI/LlFo8A5UB1gBli++5mNZln8TrvGnFW1DR1cE9t3Ys/pKqbd631lLfFGbOko28+sFy/vf+UjUZFckiClMi7jLGMGXKFAoKCgAOAOKypUs8A1U/oM52hPnsl4dh2zXNBeAr7t21yXNuzTh8hRXbvG+tZWNDG58s2sDLU5bx2gfLUL4SyUwKUyKp4R//+AcHHnggwGXEaaPkeAaqs4H/tKyYzZK7LozXOTOOv7wfuTXjOgPWGLx5Jdu8b61l3eZWZi5Yz4uTl/LWjJUuVSoi8aQwJZI6fvjDH3LZZZcB3AV8Ix7njOei9FEArcsyZ0F6IoTXLmLT2kVsmvI4GEOgx4DOEaxxhPqPwhssoLwoyFEje3PUyN5EIpbVG5uZPn8dL7y/hCmz17r9I4jIXlKYEkktieiYHs8RqheAE1c/fbMTFmTvebzkVA4mt3YcoZqxhPqNxBMIbfMlHRHLynVNTJu7lucmLWbmwg0uFSsie0JhSiT19O/fnxdffBGgBWdhesx3i8UrUBlgFVCx+J5LaF02a3dfL3vC6yNYtZ8TsGqdJqMeX2CbL2nviLBsTSOTZ69hwjuLWLC83qViRWR7ClMiqckYw9SpU8nPzwcYBsR8J128AlUlsNxGOvjsF4di21vjcU7ZjvHlEOw7wpkirBlHsGrfz3Vxbwt3sHh1I+99spoJ79SxbE2TS9WKZDeFKZHU9sQTT7D//vsDnAU8Fev54rWGagBA+8YVClMJZNtbaV4wmeYFk4E7MYFcQv1Gdd1FmFM5mIDfy4CqQgZUFXLxsfvQGo5Qt6Kedz5eyYR3FrN2k7q4iySawpRI6qurq4sGqkHxOF+8AtVAgLZ1i+N0OtkTtq2JpnkTaZo3EQBPqJBQ/9Gda7DGkNNzAMGAlyH9ihnSr5hLTx5Mc2sH85dv4u2PVvLMu4vZ3JSeWwSJpCqFKZH0sHDhwujTlApUAwDC65fE6XTSHZHmzTR++jqNn74OgDe/jFDNGHJrnBGsQFlfcoM+hteWMby2jK+fuS8Nze3MXbqRNz5cwfPvL6G5tcPln0IkfSlMiaSPurq66NO4BKp4raH6N3DemudvZeOkh+NxPkkAX1Gvri1yQrVj8Rf12uZ9ay2bG8N8umgDr364nJenLFMXd5E9pDAlkl6GDRvGk08+Cc5Ndb128+W7Fa9A9QEwcvlD36FxzlvxOJ8kgb+0umuT51DNGHz5Zdu8b61lQ30rs+o28NKUZbw+fTkR5SuRz1GYEkk/eXl5fPDBB9HDYmBTLOeLR6AywGYgv+6PZxFeWxfr+cQlgR61hGrGkVs7hlDNWLyhwm3ej1jL2o0tzFiwnhfeX8KkWatdqlQkdShMiaSvt99+mx49egCMBabGcq54BKqewEobifDZzw/CdmiRc0YwHnJ6DercImcsof6j8OTkbfMlkYhl5YZmps9by7OTljB9/jqXihVxh8KUSHr75z//ybhx4wAuBh6J5VzxWJTutEzYtFJhKpPYCK0rZtO6YjYb3/kneHwEq/btCljBviPw+IP0Lsuld1lfTj6oL+0dEVasa2LqnLU88+4iZi+OafRUJKUpTImkv7q6umiginlhejwC1UCAsFomZLZIOy1LZtCyZAYb3rwf4wsQ7LM/odpx5NaMIVg9HJ/XR3WPfKp75HPW4f0Jt0dYuqaR9z9dzdMTF1G3qsHtn0IkLhSmRDJDPO/0i9sIVZtaJmQV295Gc900muumsR4wgRChvgd03UWY03sofp+XmsoCaioLuODofWgNd7BoZQOTZq3iqYl1rNqgJqOSfhSmRDJHSgaq8DoFqmxm25ppmj+JpvmTWAd4gvmE+o92+mDVjiOn1yBy/F4GVRcxqLqIL50wkJa2DhasqGfizJU8/c4iNtS3uf1jiOySwpRIZtmuuacBur2wPB6L0qcCo5c/fA2Ns9+M9VySoby5JYRqRneNYAUqarZ531pLU0s785Zt4s3pK3lu0mIaWmLe/FskbhSmRDKP3+/no48+wuv1grMv8crunivWQGWAjUDhoj+dQ9uaBbGcS7KIt6Cic5Nnpw+Wv6T3Nu9ba6lvCjNnyUZe/WA5/3t/qZqMimsUpkQy12uvvUZVVRXAIcCk7p4n1kBVAay2kQif/eJgbLumbKR7fMW9uzq459aMw1dYsc371lo2NrTxyaINvDxlGa99sAzlK0kGhSmRzPboo48ycuRIgHOAJ7t7nljXUDktEzavUpiSmLRvXM7mDyaw+YMJAPjL+5FbM64zYI3Bm1dCSUEOh+7Xi0P368VPvzKKdZtbmblgPS9OXsrbM1cSn6b/IlsoTIlkvjVr1kSfVsZynlgDVW9welCJxFN47SI2rV3EpimPgzEEegzoHMEaR6j/KLzBAsqLghw1sjdHjexNJGJZvbGZ6fPX8cL7S5gye63bP4KkOYUpkeywenXXrh+9d/V1uxNroOoB0NG4PsbTiOyCtbStmkfbqnlsnPQIeLzkVA7u3INwLKF+I/EEQvQqzeXEcbmcOK6ajohl5bomps1dy3OTFjNz4Qa3fwpJIwpTItkjVUaonEDVoL+sJIkiHbQu+4TWZZ+w4e0HwesjWLWfE7BqxxKsHo7XF6CqIo+qijxOP7Qf7R0Rlq1pZPLsNUx4ZxELlte7/VNIilKYEskuKRWo2jVCJW7qaKdl8XRaFk+HN+7D+HII9h3ReRfhOIJV++Lz+ujXq4B+vQo4b3wtbeEOFq9u5L1PVjPhnTqWrWly+6eQFKAwJZJ9UipQdTRqhEpSh21vpXnBZJoXTAbuxARyCfUb1XUXYU7lYAJ+LwOqChlQVcjFx+5DazhC3Yp63vl4JRPeWczaTerinm0UpkSy06pVq6JPY1pDFWvbhDeBI1Y89iMaPn4plvOIJI0nVEio/+jONVhjyOk5YJv3rbU0t3bw2fLNvPXRCp55dzGbm7TxdyZTmBLJXqWlpUya1NV+KgB06wM/1kD1KTBk6QNX0LxwaiznEXGNN7/M2SKnxhnBCpT13eZ9ay0Nze3MW7qJN6Yv5/n3ltLUqi7umUJhSiS7GWOYOXMmfr8foBpY2q3zxBio1gGli+44h7bV6pIumcFX1Ktri5xQ7Vj8Rb22ed9ay+bGMJ8u3sCrHyzn5SnL1MU9TSlMiQjAG2+8QWVlJcA4YEp3zhFLoPIDbQALbjmajiato5LM5C+tdhqMdk4R+vLLtnnfWsuG+lZm1W3gpSnLeH36ciLKVylPYUpEoh5//HGGDx8OcAbwdHfOEcui9HIAG+mgo3lTDKcRSW3h9UsIr1/C5qnOjgSBHrWEasaRWzuGUM1YvKFCSguDHD68ksOHVxKxlrWbWpjx2XpeeH8Jk2at3s0VJNkUpkRka1vd6dfthemxBCrnDr+mjWD167hkj7bVC2hbvYBN7z8KxkNOr0GdW+SMJdR/FJ6cPHoUhzh2dBXHjq4iErGs2tDMh/PW8uykJUyfv87tHyGrKUyJyPbi0Toh9kClHlSSzWyE1hWzaV0xm43v/BM8PoJV+3YFrGDfEXj8QSrLcqks68vJB/WlvSPCinVNTJ2zlmfeXcTsxRrhTRaFKRHZkQ0bupYtlXb3HLEHqgYFKpEukXZalsygZckMNrx5P8YXINhnf0K148itGUOwejg+r4/qHvlU98jnrMP7E26PsHRNI+9/upqnJy6iblWD2z9FRlKYEpGdaWxsjD4t6O454jBCpcXoIjtj29torptGc9001gMmECLU94Cuuwhzeg/F7/NSU1lATWUBFxy9D63hDhatbGDSrFU8NbGOVRvUZDRWClMisitbBar87p4j5kClbWdE9pxta6Zp/iSa5k9iHeAJ5hPqP9rpg1U7jpxeg8jxexlUXcSg6iK+dMJAWto6WLCinokzV/L0O4vYUN/m9o+RVhSmRGR33B6hKgOINGn9h0h3RVoaaJz9Jo2z3wTAm1tCqGZ01whWoKKGUI6PYf1LGNa/hCtPHUJTSzvzlm3izekreW7SYhpa1GR0ZxSmRGRPuD1CFQKIhJtjOIWIbK2jaQMNs16hYdYrAHgLKjo3eXb6YPlLepMX8nPAgHIOGFDOt88ZRn1TmDlLNvLqB8v53/tL1WS0k8KUiOwpt0eocsBZIyIiidFRv4b6j56n/qPnAfAV9+7q4J5bMw5fYQWFeQHGDunB2CE9+NGFI9jY0MYnizbwytRlvDptGdmYrxSmRGRvNDU1RZ92O1DF0in9aeC0VU/9nM3T/tvdc4hIDPzl/bv2IMytGYM3r2Sb9621rNvcyscL1vO/yUt5e+ZKYtttKvUpTInI3howYADPPfccwFqgojvniGWEKghg21tjOIWIxCK8to5Na+vYNOVxMIZAz4Hk1owhVDuOUP9ReIMFlBcFGT+yN+NH9iYSsaze2MxHn63n+fcWM2X2Wrd/hLhSmBKR7ojHCFUcApWm/ERSgrW0rZxL28q5bJz0CHi85FQO6VqDFeo3Ek8gRK/SXHqV5nLC2D50RCwr1zXxwby1PPvuYmYuTN82KApTItJdW62hysHZqzi8t+eIZcpvMjB2+T+/TePct7t7DhFJFq+PYNV+zibPtWMJVg/H4wts8yXtHRGWrWlkyuw1THh3EZ8tq3ep2L2jMCUisfD7/Xz88cfRw1Jgr3+7jCVQzQD2X/q3q2he8H53zyEiLjH+IMHq4Z0jWOMIVu2L8W47aN0W7mDx6kbe+2Q1E96pY9mapp2czT0KUyISDzNnziQQCAD0Axbv7ffHEqjmAgOX/PVSWhZ92N1ziEiK8OTkEew7susuwpzKwRjj6XrfWktrOELdynre+XgVEyYuYu0md7u4K0yJSLy89957lJSUAAwDPtnb749D2wQtShfJBJHWRprmTaRp3kQAPKFCQv1Hd00R5vTYh2DAy5C+xQzpW8ylJw2iubWDz5Zv5u0ZThf3zU17veyg2xSmRCSeGhsbo4GqWwvTtShdRHYo0ryZxk9fp/HT1wHw5pc5W+R0tmkIlPUlN+hj/9pS9q8t5eozhtLQ3M68pZt4Y/pynn9vKU2tienirjAlIvHW1taVZwK7+rqdiWXKbxNQWPeHMwiv3+upRhFJc76iXl1b5IRqx+Iv6rXN+9ZaNjeG+XTxBl79YDkvT1kWly7uClMikgjPPfccAwYMABgPvLm33x9LoGoFAgt/dyLtm1d19xwikiH8pdVOg9HacYRqxuLLL93mfWstG+pbmVW3gZemLOP16cuJ7GW+UpgSkUR55plnGDRoEMDRwOt7+/3dnfLz0Dkkpik/EQEIr19CeP0SNk99EoBAj1pCNeM67yIcgzdUSGlhkMOHV3L48Eoi1rJ2UwszPlvPC+8vYdKs1bs8v8KUiCTSVgNMnl193c50N1DlRJ9EtChdRHagbfUC2lYvYNP7j4LxkNNrUOcWOWMJ9R+FJyePHsUhjh1dxbGjq4hELKs2NPPhvLU8N2kJH85f13UuhSkRSbTIliHzpAaqYPSJ7dAIlYjsho3QumI2rStms/Gdf4LHR7Bq366AFew7Ao8/SGVZLpVlfTn5oL60d0RYsa6JuUs2MXyfUiqKQ0QiEf74xz9SUVHB0Ucf7fZPJSIZJC8vr+tpd76/u2uoSoD1APN+OhYiibmTR0Syg/EFCPbZn1DtOHJrxhCsHv65JqMiIknyf8DP9vabuvuJ1TUsZbw+rAKViMTAtrfRXDeN5rpprAdMIESo7wGEasZScvhXMMawuaWeiI39LkERkR3Jz8nH5/ECdCvUxCFQ+bFhd7sli0hmsW3NNM2fRFPdB5Qe8VUALn7kG2xubXC5MhHJVH8991YGVtQCTO3O93dr4RVbpTfj9XfzFCIiu+YrKO963hhudrESEcl0W2211a2h8O4GKovThwrj61ZDURGR3fIVVADQEm6lI9LhcjUiksk8xkSfduvDpruBCjqn/TRCJSKJ4u0MVI3hJpcrEZFMZ7YEqqSOUIEClYgkmDfP6bbe2KZAJSKJ5XFpyg+iC9N1a7OIJIgvrwSApjatnxKRxHJzhEprqEQkoby5xQA0tDW6W4iIZLyAtyvPdKtjuab8RCRleXOLAI1QiUji5fq7NoGp7873K1CJSMryBAsAraESkcTL9YeiTxWoRCSzeILOlloKVCKSSAGvH9+WNeFJD1Sda6gUqEQkMTwBBSoRSbzQltEpgG5tyaARKhFJWSbgfMg1ag2ViCTQVtN9Taixp4hkGk/nItFG3eUnIgmUG4ht/RTEZcovJ4ZTiIjsXPTzRSNUIpJIW93ht7m754glUK0H8IYKYziFiMjORddoag2ViCSS2yNUawG8nZ2MRUTizXicu24UqEQkkXL9udGnrgSqNbClk7GISNx5nI8oBSoRSSSNUIlIhnP21lKgEpFEirVLOsQhUHk0QiUiCeDJKejarFSBSkQSKdYu6RCPKT+NUIlIAvgKewAQsRGawy0uVyMimSyUElN+GqESkQTwFpYDzsbIFutyNSKSyfIDXYvSXWmb4IxQBQvU3FNE4s6X3xmowupBJSKJVZbbNdu2orvniCVQbaSzPbvWUYlIvHnzSwFo0PopEUmwsrzS6NPl3T1HLIEqAqwDTfuJSPx5O39jbFKgEpEEK891N1CBWieISIJ4cosAbTsjIonlNR5KOj9vcD1QaYRKROIsuq2VWiaISCKV5pbgMR6AdjrXh3dHrIFKrRNEJCG8wQJAU34iklhledssSI909zwaoRKRlOTJyQO0KF1EEise66dAI1QikqJMZ18YjVCJSCKVx+EOP4g9UK2ELR2NRUTixdPZuVgjVCKSSFtN+bkaqBYA+EuqYjyNiMi2jD8HcDqli4gkSqpM+X0G4C/pE+NpRES2ZbwBABraGl2uREQyWapM+S0CrCcnF29+WYynEhHZIrqllUaoRCSRtgpUy2I5T6yBqhVYAuAv1SiViMSP8foA9aESkcSKx7YzEHugAk37iUgiOI32aAwrUIlIYgS8AYo6e94Rw8bIEM9ApREqEYkXz5aPpsZWBSoRSYyqol7Rp5uADbGcKx6ByrnTT4FKROLEk1uKMQbQCJWIJE7f4q4uBbMBG8u5NOUnIinH39nbrr2jndb2NperEZFMVV3cO/p0Tqzn0pSfiKQcX0E5AI1h3eEnIomz1QhV6gQqX0E5prOzsYhILKJtWBrVg0pEEmi7Kb+YxCNQbaRzIZc6potIPET3B21UDyoRSaBUm/IDTfuJSBxtCVRakC4iiVGaW0J+Th7W2ggwP9bzxTdQlVTH6XQiks28oSIAmhSoRCRB+naOThljFuI0Ko9JvAKVWieISNx4goUANChQiUiCxHNBOsR7hKpMI1QiEjtPMB/QPn4ikjjVcVyQDvELVLMAcnoOiNPpRCSbeXLyAGjQXX4ikiB947ggHeIXqGZaa62voKJrMamISHd5OluwaIRKRBKlb0lqjlA1GmPmA+T0GhSnU4pItooGKt3lJyKJEPD66VXQI3qYUiNUADMAAj0VqEQkNsYXABSoRCQx+hRV4jEecDZFXh2Pc8YzUH0EkFOpQCUisVGgEpFEGlBeE336MTFuihwV/0ClKT8RiZHx+AAFKhFJjCEVXTfRTYnXOeM/5VdeA15fHE8rIlnH4wUUqEQkMQb32Cf6dGq8zhnPQLUI2GR8fnK2FCoisvectQ3ay09E4s7r8TJwy5RfSo5QWWAaQE7vfeN4WhHJKr4cjDEANKoPlYjEWU1JNTm+HHAWpMe8h19UPAMVdA6d5fQeGufTiki28BWUdz1vDGuESkTia0iPrvVTU4FIvM4b70A1DSCoESoR6SZfQQUALeFWOiIdLlcjIplmcMU2gSpuEjNC1WsQxuuP86lFJBt4OwNVY1gL0kUk/rYaoYrb+imIf6BaCGwwPj8B7esnIt3gzSsFdIefiMRfwOuntrRv9DClA9VWC9O1jkpE9p6vcz9Q7eMnIvE2oLwGn9PaaTWwJJ7njneggs5pv2DVsAScWkQynTe3GIAG3eEnInE2uKKrrdMU4tQhPSoRgep9gGDfAxJwahHJdN7cIkAjVCISf9vd4RdXiQhUb1lrbU6P2q61ECIie8oTLAC0hkpE4i8RW85EJSJQrTfGzAAI1YxOwOlFJJN5gnmAApWIxFfIH6RvSVX0MC0CFcAbAKGasQk6vYhkKk9AgUpE4m//XkPxONtaLcRZlB5XCQ1UuRqhEpG9ZAIhQPv4iUh8jeqzf/Tpa4k4f6IC1VvWWhuoqMWbX5agS4hIJvL4g4D28ROR+BpVlZ6Bass6qv4apRKRPWecTUs1QiUicVOQk8/A8proYVoFKuhaRzUmgZcQkUxjfM62VVpDJSLxckDvYdH1U58AKxNxjUQGqtdB66hEZO8Yjw9QoBKR+BndZ3j06auJukYiA9XbWkclInvN43wsKVCJSLwkev0UJDZQrTfGfARaRyUie8MAClQiEh/leaX0K+mDtTZC53KkREhkoAKtoxKRveDJKcAYBSoRiZ+RvfcDwBjzAbAxUddJSqDSOioR2RO+wh4ARGyE5nCLy9WISCZIxvopSHyg0joqEdlj3sJywNkY2cZ3I3gRyVIjk7B+ChIfqLaso9K0n4jshi+/M1CF1YNKRGJXVdiLXgUVWGvDwMREXivRgQo6E2HegEOScCkRSWfe/FIAGrR+SkTiIHp3nzFmEpDQD5ZkBKpnAPKGHAEebxIuJyLpyptbAkCTApWIxMGoJK2fguQEqonAem9uMaG+ByThciKSrjy5RYDu8BOR2Pk8PsZVHxA9fDnR10tGoGoHngXIGzI+CZcTkXTlDRUC2sdPRGI3smo/8nPywNlq5v1EXy8ZgQpgAkD+0PFJupyIpCNvsACAxrZGlysRkXR3eM2B0acTgEiir5esQPWitbbFX9qHQM8BSbqkiKQbj/PbpEaoRCQmBsNh/cdFD/+bjGsmK1A1GmNeAU37icjOmUAuoDVUIhKbfXsOpCyvBGAz8HoyrpmsQAXwFED+0KOSeEkRSSeeQAhQoBKR2By2ZbrvOaAtGddMZqB61lprg1X7dm0vISKyNePPARSoRCQ2W62fSsp0HyQ3UK3qbKxF3pAjk3hZEUkXxhsAFKhEpPv6l1RTXdwba20r8L9kXTeZgQo6p/3yNO0nIjtgvH7A2ctPRKQ7DqtxFqN3rt2uT9Z1kx2oJgDk1ozFE8xP8qVFJNUZrw/QCJWIdN9W031PJfO6yQ5Uc4FPjddH7sDDknxpEUl5xvlIagwrUInI3uuRX86QHgOw1kaAp5N57WQHKlCTTxHZEc+Wj6PGVgUqEdl70d5Txph3gNXJvLZrgSp34KFd6yVERLx5pRhjAI1QiUj3HF7rznQfuBOoJgPLvcF8cgcf7sLlRSQV+QqcdirtHe20tielbYyIZJCiYCEjKveNHj6V7Ou7EagiwEMAhQec5sLlRSQV+QrKAWgM6w4/Edl7xw48HK/HCzAVWJDs67sRqAD+DpA36DC8uSUulSAiqcSbXwZoY2QR6Z4TB3e1ZPq7G9d3K1B9Akw1Xh8Fw090qQQRSSXevFJAGyOLyN6rLe3HoIparLVh4F9u1OBWoAJ4EKBgpKb9RAS8ecWAelCJyN6Ljk4ZY54B1rlRg5uB6lFrbTjYeyiBngNdLENEUoE3VARAkwKViOwFr/Fw7KCum9xcme4DdwPVus4kSaFGqUSynidYCECDApWI7IWx1SMpc9ZjrwFecKsONwMVdCbJguEngbMyX0SyVHQ7Ku3jJyJ748TB46NPHwHCbtXhdqB6AVjjKygnd8DBLpciIm7y5OQB0KC7/ERkD+UH8ji0czNkXJzuA/cDVRgnUWraTyTLeQIhQCNUIrLnjh5wKAFn15WZwHQ3a3E7UEFnoswfMh5PsMDtWkTEJdFApbv8RGRPbdd7yrpYSkoEqunATOMLULD/CW7XIiIuMb4AoEAlInumurg3w3oNxlrbATzsdj2pEKgs6kklkvUUqERkb2zVe+p/wEp3q0mNQAXwsLW2I1Q9HH95P7drEREXGI8PUKASkd3zGA/HDzoyeujqYvSoVAlUqzoTJoWjznC7FhFxQ2frFAUqEdmdcdUj6ZFfDrABeMblcoDUCVQAfwEoGn02xh90uxYRSTbjfBxpLz8R2Z2z9z8p+vQBoMXFUrqkUqB6FljozS2iYMQpbtciIsnky8EYA0Cj+lCJyC5UFVVyYN9RWGstcLfb9USlUqDqAP4EUHzwRS6XIiLJ5Cso73reGNYIlYjs3JnDTgTAGPM88Jm71WyRSoEK4G/W2oacHrXk7nOQ27WISJL4CnoA0BJupSPS4XI1IpKqgr4cTh5ydPTwz27Wsr1UC1SbjDEPgEapRLKJt3OEqjGsBekisnPHDTyCfGebqvnASy6Xs41UC1QAd1hrbd7gw9VCQSRL+PLLAN3hJyK7dtaWxeh3AREXS/mcVAxU840xzwIUH3iB27WISBJ4c4sB7eMnIjs3qmp/9inrj7W2ic6G4KkkFQMVwB8BCkeejieY73YtIpJg3rxiABp0h5+I7MR5w53dVIwxf8PpP5VSUjVQvQZ87MnJpXDUWW7XIiIJ5g0VARqhEpEdqy7uzSH9x0RbJfzR7Xp2JFUDVdc/sOKDLujqoCwimckTLAC0hkpEduzc/U8FoHNJ0Dx3q9mxVA1U4Owcvc5f0pu8IUfu9otFJH15gnmAApWIfF5BTj4nDB4fPfyDi6XsUioHqmbgXoDig9RCQSSTeQIKVCKyY6ftexwhZ0u6j4A33K1m51I5UAHcZa1tz60ZTU7lYLdrEZEEMYEQoH38RGRbAW+Ac/bv2o7udpwlQSkp1QPVMmPM4wDFh1zidi0ikiCezg3RtY+fiGztlKHHUJ5XCrAEeMTlcnYp1QMVdM6XFgw/EX9ptdu1iEgCGF8OoBEqEdnC7/Fx0cizo4e3AG0ulrNb6RCopgAvGI+P0iMvd7sWEUkA4/MDWkMlIlucPPQYeji7KCwDHnC5nN1Kh0AF8H8ABQecrFEqkQxkPD5AgUpEHD6Pj4u3jE79Bmh1sZw9ki6BajLwnPH4KB1/hdu1iEi8eZyPIgUqEQE4cfB4ehZUAKwA/uJyOXskXQIVwM8ACkacjL+sr9u1iEhcGUCBSkTA6/Fyyahzooe/BVpcLGePpVOgmgI8azxejVKJZBBPTgHGKFCJiOP4gUdSWdgTYDVwn8vl7LF0ClQQXUs1/CT85f1cLkVE4sFX2AOAiI3QHE6LX0RFJEG8xsMlo7tGp34HpM1vWekWqKYBz2iUSiRzeAvLAWdjZJu6PftEJAmOGXg4fYoqAdYCd7tczl5Jt0AF0VGq/U/EX97f3UpEJGa+/M5AFVYPKpFs5jEevjj63OjhrUBadfpNx0D1ATBBo1QimcGbXwpAg9ZPiWS1o/Y5hL7FVQDrgbtcLmevpWOggugdf8NPxF9R43YtIhIDb24JAE0KVCJZy2D40ujzooe/B+pdLKdb0jVQfQg8ZYyHsvFXul2LiMTAk1sE6A4/kWx2/OAj6V9ajbV2I/Bnt+vpjnQNVNA5SpW///EEetS6XYuIdJM3VAhoHz+RbJXjC3D5uIsBMMbcDGxyt6LuSedANR34rzEeSo+6yu1aRKSbvMECABrb0mr9qYjEyfnDT4/u2bcIuMPlcrotnQMVwE+ttbZgv+MI9hvpdi0i0g2enDxAI1Qi2ag0VMzFo86KHl5HmnRF35F0D1QzjTF/Bag46Vro7LYsIunDBHIBraESyUaXjruAkD8E8D7wmMvlxCTdAxXAjdbazcGqfSk84DS3axGRveQJhAAFKpFsU1Pal5OHHBs9/D6kd2ffTAhUq40xvwAoO+6bXb/tikh6MP4cQIFKJNtcffCX8Ho8AP8B3nG5nJhlQqAC+BMw31dQQemRl7ldi4jsBeMNAApUItlkTJ8RHNh3FNbaMPAjt+uJh0wJVG04w4WUHHIJvpIql8sRkT1lvH5AgUokW3iMh68f8mUAjDF/Bj5zt6L4yJRABfAM8IrxBag44btu1yIie8h4fYCzObKIZL6ThhzNPmX9sdZuAH7pdj3xkkmBygLftdZG8ocdQ6j/aLfrEZE9YZyPoQb1oRLJeCFfkMvGXghA5/rn9e5WFD+ZFKgAPjbG3ANQcfIPuj6oRSRFebb8P6oRKpHMd8HIMyjLKwFnmu9Ol8uJq0xMHD+11m7MqRxM4egz3a5FRHbBm1eK6ewf16A1VCIZrSKvjAtGnBk9/BHO+ueMkYmBaq0x5v8Ayo75Bp6cfJfLEZGd8RX0AKC9o522joz6bBWR7Xzn8MsJOm1SJgJPulxO3GVioAK4C5jtyy+ldPzlbtciIjvhKygHNDolkukOrzmQw2sOxFrbDlxFmjfx3JFMDVRh4HsAxQdfhL+0r8vliMiOeJ0NUWkKK1CJZKpcf4hvH+YMbhhjfgvMcreixMjUQAXwAvCC8frpcdr1btciIjvgzSsFtDGySCa7bNyF9HB+efqMDGqTsL1MDlQA37bWtuQOOIjCkae7XYuIbMebVwyoqadIphpSMYCz9z85engVkLG/PWV6oJpvjLkJoPyk7+PNL3e7HhHZijdUBECTApVIxvEaD9ceeRUep4XRQ8ArLpeUUJkeqABuB6Z6Q4Wa+hNJMZ5gIaBF6SKZ6Jz9T2FgRW20I/r33a4n0bIhULUDl1lr2/P3PZr8Yce6XY+IdPIEnbYmauopkll65ldw6biujug/AFa7W1HiZUOgAphhjLkZoOLU6/CECt2uR0QAT04eoG1nRDLNNYdfTsgfBHgLeMDlcpIiWwIVwM3AJ778MipOutbtWkQE8ARCgEaoRDLJ4TUHckj/sVhrw2Roz6kdyaZA1Yoz9WcLR55G7oBD3K5HJOtFA5Xu8hPJDHmBXL6zpefUr4FP3a0oebIpUAG8Z4z5I0CPM27EBHLdrkckqxlfDqBAJZIpLh93ERVOz6l5ODNDWSPbAhXAjcBCf3El5cd9y+1aRLKa8fkBBSqRTDCmz4jte061uFhO0mVjoGoErgAoPugCgv1GulyOSPYyHgUqkUxQkJPPdUd9M3p4J/Cai+W4IhsDFcCrwP0APc/8CcYXcLkckSzlcT6CFKhE0tv3j/hadKpvNvBDl8txRbYGKoBrgRWB8v6Ujr/S7VpEspOJBird5SeSro4fdCRHDTgUa207cAmQlb8hZXOg2ghcDVBy+JcJVg93txqRbOPLwRgDQKP6UImkpZ75FVvf1fd/wDRXC3JRNgcqgAnAw8bjo9d5N+PJyXe7HpGs4Suo6HreGNYIlUi68RgPNxzzbfKdBr3vAr9xuSRXZXugAvgGUOcvqaLitOvcrkUka0QDVUu4lY5Ih8vViMje+sKI0zmg9zCstQ3AF3G2estaClSwCbjIWttROOIUCkacvNtvEJHYeQvKAWgMZ+VyC5G0NqCsP5eNuwgAY8x3gAXuVuQ+BSrHJGPMzwB6nHo9vpIqt+sRyXg+544g3eEnkmYCXj8/PvYa/F4fwFPA39ytKDUoUG1xMzDRE8yn13k3g8fndj0iGc2bVwJoHz+RdHPFgZdQW9oXYBVwJVmyV9/uKFBt0QFcYq3dFKoeTtnRX3O7HpGM5s0tAqBBd/iJpI3RVcM5f8Rp0cNLgTUulpNSFKi2tcgYcyVAyRGXkrvPgW7XI5KxvCEnUGmESiQ9FAULue7ori3b7gaed7GclKNA9Xn/Bu4zxkPPc2/Gm1/udj0iGckTLAC0hkokHXiMh58c9116OGsf5wA/cLmklKNAtWPXADN8+aX0Ou9XXd2cRSR+PME8QIFKJB1cNu5CxvQZgbW2ETgbZ19c2YqSwo41A+dbaxtza8dROv5yt+sRyTieHAUqkXRwaP+xXDLqHACMMZcBn7hbUWpSoNq5OcaYqwBKj/oaoZoxbtcjklGMPwRoHz+RVFZVVMkNR387evhH4DEXy0lpClS79hDwgDEeep13M97OvjkiEjuPPwhoHz+RVBX05fCLE34Q3VrmHbRuapcUqHbvW8AsX0EFlRfcivH63a5HJCMYXw6gESqRVPX9I77GPmX9wek3dT4QdrWgFKdAtXtNwNnW2o2hfgdQcdoNbtcjkhGMz/nlRGuoRFLPmcNO5PjB47HWdgBfAJa7XVOqU6DaM3ONMV+w1kaKRp9J8UEXul2PSNoznbsRKFCJpJZ9ew7im4deCoAx5kfAm+5WlB4UqPbcS8aYawHKT/o+ufsc5HY9IunN43z8KFCJpI7iUBE/O/7a6D59TwC/d7mktKFAtXduBx40Hi+9vvAb/M5eRiLSLQZQoBJJFV7j4SfHfpceTkPrOThby2ifvj2kQLV3LHAVMMkbKqT3JX/Ak5Pvdk0iaccTLMQYBSqRVHLZuIsY3Wf41s07692uKZ0oUO29Vpz/0JYGKmrpdd7N6qQuspd8BRUARGyE5nCLy9WIyEmDj+biUWcDat7ZXUoC3bMSONNa25I3+HDKjvum2/WIpBVvobNHZlNbM1YzCiKuGlW1P9eOvyp6eDNq3tktClTdN80Y81WA0sO/SsGIk92uRyRt+Do3HW8KqweViJv6lfThFyf8EJ9z1+2jwE0ul5S2FKhi8yhOmqfHmT8hp2qYy+WIpAdvfikADVo/JeKa0lAxvzn5xq07oX8ViLhbVfpSoIrdTcAzHl8OvS/6A97OtSEisnPe3BIAmhSoRFyR4wtw80nXU1nYA2A+cCagBY0xUKCKXQS4BJjlK6yg90W/x3TuUSYiO+bJLQJ0h5+IGzzGw43HXMPQngOx1q4DTgbWul1XulOgio/NwBnW2vXBPvvR6/xfQ2cXaBH5PG+oENA+fiJuuOqgL3FE7UFYa9uMMWcC89yuKRMoUMXPZ8aYM6y1LflDjqTnmT+Bzj47IrItb7AAgMa2RpcrEckuZw47kS8ccDoAxpivABNdLSiDKFDF10RjzPnW2o7CkadRfsJ33a5HJCV5nEWwGqESSaKD+o7m24ddHj28EfiXi+VkHAWq+HumsykaJYd+kZLDv+JyOSKpxwRyAa2hEkmWgeU1/N/x38fr7KH5AJ13qEv8KFAlxt8BZyPl479D4agz3a1GJMV4AiFAgUokGXrmV3DLSTcQcm6YehVnCzV11I0zBarEuQ34DUCPM24kb+h4d6sRSSHGnwMoUIkkWlluCb8//f+oyC8DZzuZc4Gwu1VlJgWqxLoeeMB4vPQ6/9eE+o92ux6RlGC8AUCBSiSRioKF3HbaT+lTVAmwEDge2OhqURlMgSqxLPA1YILHl0Pvi28np3Kw2zWJuM54/YAClUii5AdyufXUn1BT2hdgGXBM55+SIApUidcOXAi85Qnm0/tLd+IvrXa7JhFXGa/Tp61Jd/mJxF3IH+S3p9zEoIparLWrccLUQrfrynQKVMnRDJwOTPfll1H15bvwdm4OK5KVjPPR06A+VCJxFfAGuOWk6xnWazDW2g3GmOOAOW7XlQ0UqJJnE3Ai8Jm/tA9VX74TTzDf7ZpEks+z5WNHI1Qi8eP3+PjFCT9gZNX+WGvrjTEnADPcritbKFAl1yqcRYErc3oNovcX78STo1Al2cWbV4rp3EWgQWuoROLCazzcdNx3OajfaKy1zcaYU4ApbteVTRSokm8BcIK1dkOo73CqvnIPns5tOESyga+gBwDtHe20dbS5XI1I+jMYrjv6WxxZe3B0f74zgLfdrivbKFC5Y4Yx5mhr7bpgn2FUXXofntxit2sSSQpfgbN+UKNTIvHxvSO+xvGDjsRa226MOQ942e2aspEClXumG2PGW2tXByuH0Oer9+LNK3G7JpGE8zoNBmkKK1CJxOobh3yF04cdj7XWGmMuAZ52u6ZspUDlro+NMePpXFNVdelfdfefZDxvXikAja0KVCKx+Oahl3L+iNMB6NxD9jF3K8puClTu+xQ4EliW06OWPpf9BW9Bhds1iSSMN68YgMaw7vAT6Q6D4ftHXMV5w0+NvvR14G8uliQoUKWKuTihanGgvD99LvsrvqJebtckkhDeUBGgLuki3eE1Hq4/+ltd03zApcDdbtclClSp5DPgCGBhoKyvE6qKe7tdk0jceYKFgAKVyN7yerzcdOx3OWHweKy1HcaYi9HIVMpQoEoti3BC1Tx/SRV9LvurtqmRjBNtaKtAJbLnAl4/vzjhhxw14FCstWFjzLnAv9yuS7ZQoEo9S4HxwGx/caUTqsr7uVySSPx4cvIABSqRPRXyB/n1yT/m0P5jsda2GGNOB55yuy7ZlgJValqOE6pm+Qp70OfSvxKoqHW5JJH48ARCgAKVyJ4ozMnnD6f9jNF9hmOtbTDGnAz8z+265PMUqFLXKuAo4CNfQTl9Lr+fYN8RbtckErNooNI+fiK7Vp5Xyp/O/CVDew7EWrvOGHM08LrbdcmOKVCltjXA0cBkb24xVV+9l/xhx7pdk0hMjC8HUKd0kV2pKqrkz2feTE1pX4Blxpgj0N58KU2BKvWtxwlVT3t8OfT6wm8oPuQSt2sS6Tbj8wPQpEAlskMDyvrz5zN/SWVhD4D5wKHAJ+5WJbujQJUeGoGzgTuN8VBx0vepOPmHYPSvT9KP8TiBSmuoRD7vwL6juOPMX1GaWwIwHTgM5w5wSXH6Gzl9dADfAq4FKD74QiovvBXjD7pblcje8jgfOwpUIts6a7+TuOWkG8h11hm+gbOOdpWrRckeU6BKLxa4DTjfWtuaP/Qo+nz1Pm2qLOnFRAOVFqWLAHiMh28fehnXHH4FXucXjgeAE4CNrhYme0WBKj09bow51lq7Pli9P32u/Dv+sr5u1ySye74cjDEANLY1ulyMiPtC/iC/OvE6zhl+SvSl64DLgTb3qpLuUKBKXxONMYcACwOl1VRf+Xe1VZCU59tq429tjizZriKvjDvO/BWH9B+DtbYFOA/4Dc5shKQZBar0Ngc4CJiitgqSDqKBqiXcSkekw+VqRNwzqLyWe875DQPLa7DWrjLGHAk84XZd0n0KVOlvNc7CRbVVkJTnLSgHoDGsBemSvQ7rP44/nflLyvNKAWYZYw4EJrtclsRIgSozRNsq/DnaVqHHaT/GeP1u1yWyDV9+GaA7/CR7nT/idH5x4g8JOXdov4jTY0ptETKAAlXm6AC+DVxrrbVF486lz2X34yvs6XZdIl2id6Rq2xnJNl6Pl+8fcRXfOOQreJw7Xe8GTgU2uVuZxIsCVWaxwG3GmFOstRuC1ftT/fV/EaoZ63ZdIgB4c4sAaNAdfpJFSkPF3HbqTzh92PFYay3wXeAbQLvLpUkcKVBlpheMMaOBD315JVR95W5KDvuy2zWJ4A05gUojVJIthlcO5S/n3crIqv2x1jYYY84Abkd38mUcBarMtRBnbv5B4/FSfsI1VF54K56cPLfrkizmCRYAWkMl2eELI87g9tN/vvXi87HAMy6XJQmiQJXZmoFLgaustW35+x5D9VUPEehR63ZdkqU8wXxAgUoyW14gl1+e8CO+fsiX8Xq8AA8DBwKz3a1MEkmBKvNZ4F5jzOHA0kB5f6qv/Cf5+x3vdl2ShTw5uYAClWSufcr6c9+5v+Pw2gOx1rYBVwNfxLkbWzKYAlX2mAyMAl7z5ORS+YXfUH7i98Hjc7suySLGHwK0j59kppMGH83dZ/+aPkWVAIuMMYcB96D1UllBgSq7rMHZcPPXACWHXkKfr96Lt7M3kEiieZzeO9rHTzJKwBvgh+O/znVHf5McXwDgeZxfYKe4W5kkkwJV9mkHrgfOttbWh/qPou/V/yLY9wCXy5JsYHw5gEaoJHP0LuzJXWfdzClDj8VaGwFuBE4D1rtcmiSZAlX2+m/nHSef+Aor6HPZXyk95uuaApSEMj6ne7/WUEkmOLT/WP5y7q0MrKjFWrvGGHM88Csg4nZtknwKVNltDs6dJw8Zj5ey8VdQfcWD+Mv7uV2XZCjTGdgVqCSdhXxBrj3yKm4+6XrynVY07xpjRgKvulyauEiBShpw7kC5wFq7MdhnGH2//ihF4853uy7JRB7nI0eBStLVfr2GcP/5v+e0fbu6nt8GjAeWuVuZuE2BSqIeM8bsB7zi8Qfpcdr19P7Sn/EWVLhdl2QUAyhQSfrxeXxcceDF/OmMX1JV1AtgsTHmaOBaIOxudZIKFKhka8tw7gL8trW2JW/gofT75r/JH3as23VJBvAECzFGgUrST21pX+455zdcMuocvM4o69+B4cAbrhYmKUWBSrYXAe7o3AvwA29uMZUX/I6eZ/8cT06+27VJGvMVOqOdERuhOdzicjUiu+cxHi444AzuPfd3DCyvwVq7Fjgb+Aqwyd3qJNUoUMnOfAIcDPzKWhspHHkafb/xGKH+o92uS9JUdPq4qa0Zqz6HkuJ6FfTg9tN/xtUHf5mA1w/wrDFmf+C/LpcmKUqBSnalDbjRGHMEsMBf0puqS++j7PjvYJwPGJE95itwGsg2hdWDSlLbyUOO5m/n/4ERvYdhrW0ArgBOB1a6XJqkMAUq2RPvAAcAfzXGQ+nhX3E2We41yOWyJJ1485xA1aD1U5KiikNF/OrE6/jRUd8kNxACmGiMGQH8FW0fI7uhQCV7qh7nt7QzrLVrcnoNou/VD1N+wjUY54NHZJe8ucUANClQSYoxGE4ecjT/uOBPHFYzDmttGPgRTjuEBe5WJ+lCbbFlbz3duY7gTuPxnVNy2JfJ3+941jz3Wxpnv+F2bZLCvLlFgO7wk9TSv6Sa7x/5NYZX7ht9aYYx5kvARy6WJWlII1TSHauAc4FTgDp/cSW9L/4DlRf9AZ+zy7rI53hChYD28ZPUkOMLcMWBF3P/+bcxvHJfrLVNOD2lxqAwJd2gESqJxfPAMOBGa+0P8oeO9+XucyDrXruHjZMegUi72/VJCvEGCwBobGt0uRLJdgf1Hc01h19OZWHP6EsTjDHfBha7WJakOY1QSayagBuMMQcAb3sCISpO/C59r36YYPUIl0uTVOJx9jzTCJW4piKvjJ+f8AN+c8qPo2FqCXBm50NhSmKiQCXxMgs4EviqtXZdTq9BVF/5ID1Ov7FrqkeymycQDVRaQyXJ5TUezh1+Kv+44E8cWXsw1toO4HfAvsAEl8uTDKFAJfFkgQeNMYOB+wGKxp5Dv+88RcEBp7pbmbjOBIKAApUk15AeA7j3nN/yrUMvjbZCmGSMGQX8EGdzeJG4UKCSRFgHXA4cDszy5ZXQ65xfUHXpX/BX1LhcmrjF+HMABSpJjqJgId874kruPvvXDKyoxVq7AbgSOAyY4XJ5koG0KF0SaSIwCviutfanuTVjQv2+8W82TXmCda/fS6Rpo8vlSTIZbwBQoJLECngDnDf8VC4aeRb5nev2gH8aY64FVrtYmmQ4BSpJtDbgN8aYx4A/Gq/v9OKDLqDggFPZ8OZf2fjev7DtbW7XKEkQ3a5IgUoSwWM8HDfoCC4fdxE98sujL38IfA94w7XCJGsoUEmy1AFnAEcDt3qD+SPLT7iGogO/wLqX/0T9zBfBameHTGa8zsdNk+7ykzgb02cEVx38JQaWdy0pWAz8GHgEiLhWmGQVBSpJttdwGuddAtzsL66s6nXeLRQffAlrX/wDzXXTXC5PEsY4SzYb1IdK4qS2tB9XH/wlxvUdCYC1dpMx5lfAHUCLq8VJ1lGgEjdEgH8ATwDXWGuvD/YZlt/nsr/SOHcia1++g7aVc10uUeLKs+X+F41QSawq8sq4bNyFnDB4PB7jwVobNsbcaYz5Jc5NMSJJp0AlbmoCbjbG3A/81Fp7Rd6gw3x5gw6jfsYLrHv1bsLrl7hdo8SBN68UYwwADVpDJd2U6w9x0cizOG/4aQQ77xoFHjPG3IA2MRaXKVBJKlgFfN0Y83vg58CFBcNPIn/YcWya+iTr3/gLHQ1rXS5RYuEr6AFAe0c7bR26CUH2To4vwGn7Hs8lo86hJFQUfflt4AfA++5VJrKFApWkkvnARTgdjG82Xt+JxQeeT+HI09n4/qNsfPchOho0mp+OfAXOXVcanZK9kesPccawE/nCAadvHaTmAD8CnsZpJiySEhSoJBV9CJwEjAdu8QSCB5Ue/hWKD7qQzR9MYMPEv9O+cbm7Fcpe8eaXAdAUVqCS3csP5HHO8FM4d/9TKOzcVBtnSu8W4O9A2LXiRHZCgUpS2RvAIcApwI89/pyDig88n6KxZ1M/439sePtvtK3Wsol04M0rBaCxVYFKdq4oWMj5I07jrP1OIi+QG315DvAr4F9Au2vFieyGApWkOgs8CzyHs/ny9cbjO77wgFMpPOBUGj59gw1vPUDL0pnuVim75M0rBqAxrDv85PPKcku44IAzOG3f4wn5g9GXZwK/BP4DdLhWnMgeUqCSdGFxRqzeAEYD11trz84fOt7kDx1P04LJbHjrAZo+0/rUVOTtXP+iLumytZ75FVw48kxOGXIMAV8g+vJU4Bc4v0ipKaekDQUqSUfTgHONMUOAH1lrL8mtHefLrR1Hy9JZrH/rfhpnv6HO6ynEEywEFKjEUV3cmwsPOJMTBo/H5+n6a+gdnCD1ElpsLmlIgUrS2Wzgq8aYnwLft9ZeEewzLNT7ot/TunoBG95+kPoZL0BEyy7c5gnmAwpU2cxjPBzUdxRn738yY6sP2PqtV3Gm9t5EQUrSmAKVZILFwHc6uyR/x1r7zZwetUW9zvk5Zcd+g83TnmTT1P/SUb/G7TqzlicnD1CgykYFOfmcPOQYztzvBHoX9gLAWmuNMc8AvwYmuVqgSJwoUEkmWQPcaIz5LXAV8D1/Uc+eZUdfTen4K2ic/SabJj9B04L3NR2YZJ5ACFCgyia1pf04Z/+TOXbgEVt3Nd8A3G+MuQtY6F51IvGnQCWZaDPwW+CPwNnAVcbjOyJ/32PI3/cY2tYtZtOU/7D5w6eJNG10tdBsEQ1U2scvs3k9Xg7rP46z9z+ZA3oP2/qtGTgbFj+Cs+WUSMZRoJJM1orTu+ZfwDDga9baLwfK+hZWnPhdyo/9BvWzXmbT5CdoWTzd1UIznfE5IxTqlJ6ZikNFnDr0WM4YdiI9Opu4Wms7jDFP4gSpiWh9lGQ4BSrJFrOAbxtjrgcuAK42vsDowhGnUDjiFFpXzWPT5Ceo/+g5Iq2NLpeaeYzPD0CTAlXGMBhGVe3PiUOOYvw+hxDw+qNvrQbuM8bcAyxzr0KR5DJWa0kke40BrrbWXmiMCQFEWpuon/ECm6Y8QeuK2S6XlzkG/HQyxufnW0/dyIwVn7hdjsSgqqiSEweP54RB4+lZULH1W5NxRqMexxkdFskqGqGSbDYVuMwY833gS8BVnpzcoUVjz6Fo7Dm0rppP/cwXaZj5IuH1S1wuNc15PIBGqNJVXiCX8fscwomDj2J45dCt39qIM6X+N2CKG7WJpAqNUIlsYYAjgKustWcbY7paN7cs+4T6Gf+j4eOXaN+8yr0K09SAn3+AMYYvPHQVK+tXu12O7AG/x8eBfUdx3KAjOKTfmK5O5tbaiDHmReBB4GmgxcUyRVKGRqhEtrA4zQXfNMYUA2cBF1hrjwlW7esNVu1LxUnfo7nuA+pn/o+GWa/Q0bjB1YLTgi8HYwygEapUZzAMrxzKcYOOYPw+h1CQk7/1258CDxpjHgKWu1OhSOrSCJXI7vUAzsVZzH549EUbaafps8k0zHyRhk9fI9LS4FqBqcxX0oea7z0DwNH3nkdHRPvcphKvx8vwyqEc2n8cR9QcuP26qOU4U3oPA9PRnXoiO6VAJbJ3qoHzccLVmOiLtr2NxnnvUD/zRRpnv4kNaxYkKth3JNVXPEBLuJUT/nqh2+UIEPIHObB6JIfWjOOgvqMoDBZs/fZm4AmcEPUmoAQssgc05Seyd5YAt3U+BuAEqwuNL7Bv/tCjyB96FJFwC81102ia+w6N894hvG6xqwW7zVtQDqhLutvKcks4tP9YDqsZx8iq/bducwCwFngGmAC8iNZFiew1BSqR7puPs6nrL4H96AxXHn+wNm/goeQNPJQKoG39kq5w1bxwataNXvk6Gz02hhWokq2mtK8TovqPY2jPgdu/PQ8nQE3A2U9PI1EiMVCgEomPj4EbgZuAfYGTgJOstYcHSqv9gYMuoPigC4iEW2le9MGW0au1dW7WnBTevBJA284kQ14gl+GVQxlVNZxD+4+lqqjX9l/yHltC1Gy0JkokbhSoROLL4nRlnwXcaowpAI6iM2B5/Dn98gYcTN6Ag6ngWsIbltE4712a5r1D04LJ2AwMHd7cIgAa2tSBPt5CviD7Vw5lZNV+jOy9H4Mq9sHb2fMLwFrbaox5BSdAPQOsdKtWkUynQCWSWPU4vXqexulzNYQto1dH+EuqAsXjzqN43HlE2ttoWTyd5sUf0bL4I1qWzCDSUu9m7XHhDTmBSiNUscvxBdiv5xAnQFXtx5CKAfi8n/sYnw+8AbxgjHkJ0O2nIkmgQCWSPBanl8+nwO+NMXlsPXrlC9Tk1o4jt3Zc1ze0rl7QGa4+onnxR2k5RejpvINMi9L3XsDrZ9+eg7pGoPbtOQj/tovJAeqA1zsfb+DcOCEiSaZAJeKeRuDZzocBBgFHAod0Pgbm9Kglp0ctRWPOAqCjaSMtS2Y4o1hLZtCy9OOUX+TuCTrNIRWods3n8VFb2pfBFfswqGIfBlXUUlvWb/u78QCWsiVAvY4TqETEZQpUIqnBAnM6H/d1vlYBHMSWgDXOm1sczBt8BHmDj3C+qaOd1pVznXC1ZAatq+YRXrsI2xF24UfYMU9OLqBAtTWfx0dNaV+G7D48gbPuaesA9RlaTC6SchSoRFLXGpyFxM90HgeAEcDBdIYs4/VVB6v2JVi1Lxx0AeCErPD6xbSuXkDb6s+cx6rPaFu3GCLtSf8hjD8EQGOWrqEK+YJUF/dmUEUtgyr2YXDFPrsKTxuAaTgbd0/rfNShACWS8hSoRNJHGzCl8/GnzteqcQLWwcA4YJjx+ooCFbUEKmph2LFd32zbw7StW9QZspyw1br6M8Lrl0ACt4Px+IMANGbwXX4+j4/ehT3pU9yb6qLeVBdX0qeoN9XFvSnPK93Zt0XDU/QxFYUnkbSlQCWS3pZ0Pv7deWyA3sCwrR77Afsan78gp+cAcnoO2OYEkfY2wmvrCK9fSvumVYQ3raR98yraN3U+6tfENLJlfDlA+o9QeT1eKvJK6VPUmz5FlZ3hyfmzsqAHXo93V9++FviIbUeeFqLwJJIxFKhEMosFlnU+XtrqdYMzmvW5oOXxBXJzeg0ip9egHZ8w0kFHw7rOoLWa9k0rO8NW55+bV9FevxZsZIffb3zO1FaqrqEK+YOU5ZZQmltCWW4JZXkllIaKKcsr6Xy9mLLcEoo72z/sQgMwt/Mxb7vnGxL6Q4iI6xSoRLKDBRZ3Pl7Y6nUP0A+nu3s/nNC19aOP8Xj9vsIe+Ap77PzkkQiR1gYiLfV0NG8m0ryZjpZ6Is31GG8AgHF9R1KeV0JzuIWmcAvN4Waawy20tLcSsRasJWItFovd7s+u9ztfo/PPgC9A0JdDyB8i5M8h5A8S8gUJ+oOE/EGCPudP55HT9VphMJ/SzrCU27nGaw+14SwK3z40zcVZPK4RJ5EsZZwPJxGRHfLg3G24Tcja7rgK2OV8VxpoAFZs9Vi5k+frgR0PxYlIVlOgEpFYeYFyoKTzUbzV8xLgDKAQ+ATwAwVAfuejAMjFmZL0bPfnzl7bWgdOGGrA6eu1/fPt/4w+38S2gUndxEUkJgpUIpJuzFaPCJpmE5EUoDVUIpJuLApRIpJiPLv/EhERERHZFQUqERERkRgpUImIiIjESIFKREREJEYKVCIiIiIxUqASERERiZEClYiIiEiMFKhEREREYqRAJSIiIhIjBSoRERGRGClQiYiIiMRIgUpEREQkRv8PUbKpB9WHn9AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 750x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rclustering._children = None\n",
    "fig, ax, *plotted = rclustering.pie()\n",
    "ax.set_xlim(-0.3, 0.3)\n",
    "ax.set_ylim(-0.3, 0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:58.175258Z",
     "start_time": "2021-03-22T18:45:58.116423Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = rclustering.evaluate(ax=ax, ax_props=ax_props)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Label prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T17:46:20.686581Z",
     "start_time": "2021-03-22T17:46:20.680283Z"
    }
   },
   "source": [
    "Now the parameter information becomes useful as they differ for the clusters from different clustering steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:58.179777Z",
     "start_time": "2021-03-22T18:45:58.176613Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'params': {2: (0.6, 17), 3: (0.18, 6), 1: (0.18, 6)},\n",
       " 'reference': <weakproxy at 0x7f3be6647db0 to Clustering at 0x7f3bebfa16a0>,\n",
       " 'origin': 'reel'}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rclustering._labels.meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:45:58.191235Z",
     "start_time": "2021-03-22T18:45:58.180962Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label\tr\tn\n",
      "--------------------\n",
      "1\t0.18\t6\n",
      "2\t0.6\t17\n",
      "3\t0.18\t6\n"
     ]
    }
   ],
   "source": [
    "print(\"Label\", \"r\", \"n\", sep=\"\\t\")\n",
    "print(\"-\" * 20)\n",
    "for k, v in sorted(rclustering._labels.meta[\"params\"].items()):\n",
    "    print(k, *v, sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The cluster result is satisfying. But we have clustered only a reduced set of 1000 points. We would like to predict the cluster label assignment for the full 100,000 points on the basis of the reduced set assignments. This we can do with the `predict` method of a cluster object. We call `predict` with another cluster object for which labels should be predicted as an argument. Similar to a regular `fit` we need to compute neighbourhoods for the points that need assignment, but this time we need relative neighbourhoods between two data sets. We want to compute the neighbouring points in the small set `rclustering` for the points in the big set `clustering`. To allow the fast computation of these neighbourhoods we could calculate a relative pairwise distance matrix for distances from points in `clustering` to points in `rclustering` (a so called map matrix). When we predict labels afterwards we should do the prediction separately for the clusters because the assignment parameters differ. This is where the label info comes in handy showing us the parameters used for the fit as an orientation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:46:03.528898Z",
     "start_time": "2021-03-22T18:45:58.192889Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '3 (0.16, 8)')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x450 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rclustering._predictor = _fit.PredictorFirstmatch()\n",
    "\n",
    "fig, Ax = plt.subplots(1, 3)\n",
    "\n",
    "r = 0.16; c = 8\n",
    "rclustering.predict(clustering, r, c, clusters=[1], purge=True)\n",
    "_ = clustering.evaluate(ax=Ax[0], ax_props=ax_props)\n",
    "Ax[0].set_title(f'1 {(r, c)}', fontsize=10, pad=4)\n",
    "\n",
    "r = 0.35; c = 17\n",
    "rclustering.predict(clustering, r, c, clusters=[2])\n",
    "_ = clustering.evaluate(ax=Ax[1], ax_props=ax_props)\n",
    "Ax[1].set_title(f'2 {(r, c)}', fontsize=10, pad=4)\n",
    "\n",
    "r = 0.16; c = 8\n",
    "rclustering.predict(clustering, r, c, clusters=[3])\n",
    "_ = clustering.evaluate(ax=Ax[2], ax_props=ax_props)\n",
    "Ax[2].set_title(f'3 {(r, c)}', fontsize=10, pad=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-22T18:46:03.534197Z",
     "start_time": "2021-03-22T18:46:03.530471Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label\tr\tn\n",
      "--------------------\n",
      "1\t0.16\t8\n",
      "2\t0.35\t17\n",
      "3\t0.16\t8\n"
     ]
    }
   ],
   "source": [
    "print(\"Label\", \"r\", \"n\", sep=\"\\t\")\n",
    "print(\"-\" * 20)\n",
    "for k, v in sorted(clustering._labels.meta[\"params\"].items()):\n",
    "    print(k, *v, sep=\"\\t\")"
   ]
  }
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