From 9c5f09e2f25e4035cb9f91eb6b3163be35f57807 Mon Sep 17 00:00:00 2001
From: Oli <olifer97@gmail.com>
Date: Wed, 22 Dec 2021 11:16:38 -0300
Subject: [PATCH] add memory analisis and overall comparisons

---
 fftma_module/gen/analysis.ipynb | 1672 ++++++++++++++++++-------------
 fftma_module/gen/save_logs.sh   |    2 +-
 2 files changed, 975 insertions(+), 699 deletions(-)

diff --git a/fftma_module/gen/analysis.ipynb b/fftma_module/gen/analysis.ipynb
index e1b2f00..89a3272 100644
--- a/fftma_module/gen/analysis.ipynb
+++ b/fftma_module/gen/analysis.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 74,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -54,12 +54,14 @@
     "    \"generate\": [\"gasdev\"],\n",
     "    \"gasdev\": [\"ran2\"],\n",
     "    \"fftma2\": [\"covariance\", \"fourt\", \"prebuild_gwn\"]\n",
-    "}"
+    "}\n",
+    "overall_time= {}\n",
+    "overall_memory = {}"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -102,7 +104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -114,7 +116,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -125,7 +127,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -162,7 +164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -181,61 +183,66 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def plot_pie(df, function, plt):\n",
+    "def plot_pie(df, function, plt, column):\n",
     "    \n",
     "    labels = relations[function][:]\n",
-    "    total = df.loc[function][('time', 'sum')]\n",
+    "    total = abs(df.loc[function][column])\n",
     "    sizes = []\n",
     "    explode = []\n",
     "\n",
     "    rest = total\n",
     "\n",
     "    for func in labels:\n",
-    "        func_duration = df.loc[func][('time', 'sum')]\n",
+    "        func_duration = abs(df.loc[func][column])\n",
     "        rest -= func_duration\n",
     "        value = func_duration/ total\n",
     "        sizes.append(value)\n",
     "        explode.append(0 if value > 0.01 else 0.1)\n",
     "\n",
-    "    labels.append(\"other\")\n",
-    "    sizes.append(rest/total)\n",
+    "    \n",
+    "    if rest > 0:\n",
+    "        labels.append(\"other\")\n",
+    "        sizes.append(rest/total)\n",
+    "        explode.append(0 if rest/total > 0.01 else 0.1)\n",
     "    sizes = np.array(sizes)\n",
     "    porcent = 100.*sizes/sizes.sum()\n",
-    "    explode.append(0 if rest/total > 0.01 else 0.1)\n",
+    "    \n",
     "\n",
-    "    plt.set_title(function)\n",
+    "    if not np.isnan(sizes).all():\n",
+    "    \n",
+    "        plt.set_title(function)\n",
     "\n",
-    "    patches, texts = plt.pie(sizes, startangle=90, radius=1.2)\n",
-    "    labels_formated = ['{0} - {1:1.2f} %'.format(i,j) for i,j in zip(labels, porcent)]\n",
+    "        patches, texts = plt.pie(sizes, startangle=90, radius=1.2)\n",
+    "        labels_formated = ['{0} - {1:1.2f} %'.format(i,j) for i,j in zip(labels, porcent)]\n",
     "\n",
-    "    sort_legend = True\n",
-    "    if sort_legend:\n",
-    "        patches, labels_formated, dummy =  zip(*sorted(zip(patches, labels_formated, sizes),\n",
-    "                                              key=lambda x: x[2],\n",
-    "                                              reverse=True))\n",
+    "        sort_legend = True\n",
+    "        if sort_legend:\n",
+    "            patches, labels_formated, dummy =  zip(*sorted(zip(patches, labels_formated, sizes),\n",
+    "                                                  key=lambda x: x[2],\n",
+    "                                                  reverse=True))\n",
     "\n",
-    "    plt.legend(patches, labels_formated, loc='upper left', bbox_to_anchor=(-0.1, 1.),\n",
-    "               fontsize=8)\n",
-    "    \n",
-    "    plt.axis('equal')\n",
+    "        plt.legend(patches, labels_formated, loc='upper left', bbox_to_anchor=(-0.1, 1.),\n",
+    "                   fontsize=8)\n",
     "\n",
-    "def plot_analysis(df):\n",
+    "        plt.axis('equal')\n",
+    "\n",
+    "def plot_pie_charts(df, title, column):\n",
     "    fig, axs = plt.subplots(2, 2, dpi=100, figsize=(6, 6))\n",
-    "    fig.suptitle('Time comparisons')\n",
+    "    fig.suptitle(title)\n",
     "    functions = list(relations.keys())\n",
     "    for i in range(2):\n",
     "        for j in range(2):\n",
-    "            plot_pie(df,functions[2*i + j], axs[i, j])\n",
+    "            plot_pie(df,functions[2*i + j], axs[i, j], column)\n",
     "    "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -251,12 +258,12 @@
     "    \"cov_value\": \"covariance\",\n",
     "}\n",
     "\n",
-    "def plot_treemap(df):\n",
+    "def plot_treemap(df, column, name):\n",
     "    df[\"parent\"] = [parents.get(item, \"\") for item in df.index]\n",
     "    df2 = df.reset_index()\n",
-    "    df2[\"time_sum\"] = df2[[(\"time\", \"sum\")]]\n",
-    "    df2 = df2[[\"function\", \"parent\", \"time_sum\"]]\n",
-    "    fig3 = px.treemap(df2, names='function', parents='parent',values='time_sum', color=\"parent\", title=\"Time treemap\")\n",
+    "    df2[name] = df2[[column]]\n",
+    "    df2 = df2[[\"function\", \"parent\", name]]\n",
+    "    fig3 = px.treemap(df2, names='function', parents='parent',values=name, color=\"parent\", title=\"Time treemap\")\n",
     "    fig3.show()"
    ]
   },
@@ -269,7 +276,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [
     {
@@ -297,23 +304,23 @@
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
+       "      <th colspan=\"5\" halign=\"left\">time</th>\n",
        "      <th colspan=\"3\" halign=\"left\">memory</th>\n",
        "      <th colspan=\"3\" halign=\"left\">cpu</th>\n",
-       "      <th colspan=\"5\" halign=\"left\">time</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
-       "      <th>median</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sum</th>\n",
+       "      <th>count</th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
-       "      <th>mean</th>\n",
+       "      <th>median</th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
        "      <th>mean</th>\n",
-       "      <th>sum</th>\n",
-       "      <th>count</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>function</th>\n",
@@ -333,260 +340,262 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Py_kgeneration</th>\n",
-       "      <td>1.2</td>\n",
-       "      <td>1.2</td>\n",
-       "      <td>1.2</td>\n",
-       "      <td>75.100000</td>\n",
-       "      <td>75.100000</td>\n",
-       "      <td>75.100000</td>\n",
-       "      <td>0.633546</td>\n",
-       "      <td>0.633546</td>\n",
-       "      <td>0.633546</td>\n",
-       "      <td>0.633546</td>\n",
+       "      <td>0.544398</td>\n",
+       "      <td>0.544398</td>\n",
+       "      <td>0.544398</td>\n",
+       "      <td>0.544398</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>4.978049</td>\n",
+       "      <td>4.978049</td>\n",
+       "      <td>4.978049</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>generate</th>\n",
-       "      <td>1.3</td>\n",
-       "      <td>1.3</td>\n",
-       "      <td>1.3</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>0.397899</td>\n",
-       "      <td>0.397899</td>\n",
-       "      <td>0.397899</td>\n",
-       "      <td>0.397899</td>\n",
+       "      <td>0.383407</td>\n",
+       "      <td>0.383407</td>\n",
+       "      <td>0.383407</td>\n",
+       "      <td>0.383407</td>\n",
        "      <td>1</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>-0.1</td>\n",
+       "      <td>7.507407</td>\n",
+       "      <td>7.507407</td>\n",
+       "      <td>7.507407</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>gasdev</th>\n",
-       "      <td>-0.2</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.016990</td>\n",
+       "      <td>0.000548</td>\n",
+       "      <td>0.280543</td>\n",
+       "      <td>512</td>\n",
+       "      <td>-0.7</td>\n",
        "      <td>0.2</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>100.100000</td>\n",
-       "      <td>5.669727</td>\n",
-       "      <td>0.000106</td>\n",
-       "      <td>0.007636</td>\n",
-       "      <td>0.000579</td>\n",
-       "      <td>0.296354</td>\n",
-       "      <td>512</td>\n",
+       "      <td>0.393945</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>fftma2</th>\n",
-       "      <td>-0.1</td>\n",
-       "      <td>-0.1</td>\n",
-       "      <td>-0.1</td>\n",
-       "      <td>30.534783</td>\n",
-       "      <td>30.534783</td>\n",
-       "      <td>30.534783</td>\n",
-       "      <td>0.234361</td>\n",
-       "      <td>0.234361</td>\n",
-       "      <td>0.234361</td>\n",
-       "      <td>0.234361</td>\n",
+       "      <td>0.157936</td>\n",
+       "      <td>0.157936</td>\n",
+       "      <td>0.157936</td>\n",
+       "      <td>0.157936</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.100000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>covariance</th>\n",
-       "      <td>-0.1</td>\n",
-       "      <td>-0.1</td>\n",
-       "      <td>-0.1</td>\n",
-       "      <td>31.918182</td>\n",
-       "      <td>31.918182</td>\n",
-       "      <td>31.918182</td>\n",
-       "      <td>0.224350</td>\n",
-       "      <td>0.224350</td>\n",
-       "      <td>0.224350</td>\n",
-       "      <td>0.224350</td>\n",
+       "      <td>0.154748</td>\n",
+       "      <td>0.154748</td>\n",
+       "      <td>0.154748</td>\n",
+       "      <td>0.154748</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.100000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>cov_value</th>\n",
-       "      <td>-0.2</td>\n",
+       "      <th>ran2</th>\n",
+       "      <td>0.000080</td>\n",
+       "      <td>0.001279</td>\n",
+       "      <td>0.000118</td>\n",
+       "      <td>0.082659</td>\n",
+       "      <td>702</td>\n",
+       "      <td>-0.4</td>\n",
        "      <td>0.2</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>100.100000</td>\n",
-       "      <td>0.859143</td>\n",
-       "      <td>0.000103</td>\n",
-       "      <td>0.000966</td>\n",
-       "      <td>0.000134</td>\n",
-       "      <td>0.093502</td>\n",
-       "      <td>700</td>\n",
+       "      <td>0.143162</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>ran2</th>\n",
-       "      <td>-0.2</td>\n",
+       "      <th>cov_value</th>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.000197</td>\n",
+       "      <td>0.000097</td>\n",
+       "      <td>0.067926</td>\n",
+       "      <td>700</td>\n",
+       "      <td>-0.5</td>\n",
        "      <td>0.2</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>0.998148</td>\n",
-       "      <td>0.000101</td>\n",
-       "      <td>0.000583</td>\n",
-       "      <td>0.000133</td>\n",
-       "      <td>0.093435</td>\n",
-       "      <td>702</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.000286</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>fourt</th>\n",
+       "      <th>cgrid</th>\n",
+       "      <td>0.001345</td>\n",
+       "      <td>0.001345</td>\n",
+       "      <td>0.001345</td>\n",
+       "      <td>0.001345</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000553</td>\n",
-       "      <td>0.000795</td>\n",
-       "      <td>0.000664</td>\n",
-       "      <td>0.001993</td>\n",
-       "      <td>3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>cgrid</th>\n",
+       "      <th>length</th>\n",
+       "      <td>0.000287</td>\n",
+       "      <td>0.000294</td>\n",
+       "      <td>0.000292</td>\n",
+       "      <td>0.000875</td>\n",
+       "      <td>3</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.001623</td>\n",
-       "      <td>0.001623</td>\n",
-       "      <td>0.001623</td>\n",
-       "      <td>0.001623</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>length</th>\n",
+       "      <th>fourt</th>\n",
+       "      <td>0.000129</td>\n",
+       "      <td>0.000145</td>\n",
+       "      <td>0.000138</td>\n",
+       "      <td>0.000413</td>\n",
+       "      <td>3</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000355</td>\n",
-       "      <td>0.000359</td>\n",
-       "      <td>0.000358</td>\n",
-       "      <td>0.001073</td>\n",
-       "      <td>3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>clean_real</th>\n",
+       "      <th>maxfactor</th>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.000243</td>\n",
+       "      <td>3</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000463</td>\n",
-       "      <td>0.000463</td>\n",
-       "      <td>0.000463</td>\n",
-       "      <td>0.000463</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>prebuild_gwn</th>\n",
+       "      <th>build_real</th>\n",
+       "      <td>0.000096</td>\n",
+       "      <td>0.000096</td>\n",
+       "      <td>0.000096</td>\n",
+       "      <td>0.000096</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000454</td>\n",
-       "      <td>0.000454</td>\n",
-       "      <td>0.000454</td>\n",
-       "      <td>0.000454</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>build_real</th>\n",
+       "      <th>prebuild_gwn</th>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000410</td>\n",
-       "      <td>0.000410</td>\n",
-       "      <td>0.000410</td>\n",
-       "      <td>0.000410</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>maxfactor</th>\n",
+       "      <th>clean_real</th>\n",
+       "      <td>0.000088</td>\n",
+       "      <td>0.000088</td>\n",
+       "      <td>0.000088</td>\n",
+       "      <td>0.000088</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000105</td>\n",
-       "      <td>0.000106</td>\n",
-       "      <td>0.000105</td>\n",
-       "      <td>0.000316</td>\n",
-       "      <td>3</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "               memory                     cpu                          \\\n",
-       "                  min  max median         min         max        mean   \n",
-       "function                                                                \n",
-       "Py_kgeneration    1.2  1.2    1.2   75.100000   75.100000   75.100000   \n",
-       "generate          1.3  1.3    1.3  100.100000  100.100000  100.100000   \n",
-       "gasdev           -0.2  0.2    0.0    0.000000  100.100000    5.669727   \n",
-       "fftma2           -0.1 -0.1   -0.1   30.534783   30.534783   30.534783   \n",
-       "covariance       -0.1 -0.1   -0.1   31.918182   31.918182   31.918182   \n",
-       "cov_value        -0.2  0.2    0.0    0.000000  100.100000    0.859143   \n",
-       "ran2             -0.2  0.2    0.0    0.000000  100.100000    0.998148   \n",
-       "fourt             0.0  0.0    0.0    0.000000    0.000000    0.000000   \n",
-       "cgrid             0.0  0.0    0.0    0.000000    0.000000    0.000000   \n",
-       "length            0.0  0.0    0.0    0.000000    0.000000    0.000000   \n",
-       "clean_real        0.0  0.0    0.0    0.000000    0.000000    0.000000   \n",
-       "prebuild_gwn      0.0  0.0    0.0    0.000000    0.000000    0.000000   \n",
-       "build_real        0.0  0.0    0.0    0.000000    0.000000    0.000000   \n",
-       "maxfactor         0.0  0.0    0.0    0.000000    0.000000    0.000000   \n",
+       "                    time                                     memory       \\\n",
+       "                     min       max      mean       sum count    min  max   \n",
+       "function                                                                   \n",
+       "Py_kgeneration  0.544398  0.544398  0.544398  0.544398     1    0.2  0.2   \n",
+       "generate        0.383407  0.383407  0.383407  0.383407     1   -0.1 -0.1   \n",
+       "gasdev          0.000081  0.016990  0.000548  0.280543   512   -0.7  0.2   \n",
+       "fftma2          0.157936  0.157936  0.157936  0.157936     1    0.3  0.3   \n",
+       "covariance      0.154748  0.154748  0.154748  0.154748     1    0.3  0.3   \n",
+       "ran2            0.000080  0.001279  0.000118  0.082659   702   -0.4  0.2   \n",
+       "cov_value       0.000081  0.000197  0.000097  0.067926   700   -0.5  0.2   \n",
+       "cgrid           0.001345  0.001345  0.001345  0.001345     1    0.0  0.0   \n",
+       "length          0.000287  0.000294  0.000292  0.000875     3    0.0  0.0   \n",
+       "fourt           0.000129  0.000145  0.000138  0.000413     3    0.0  0.0   \n",
+       "maxfactor       0.000081  0.000081  0.000081  0.000243     3    0.0  0.0   \n",
+       "build_real      0.000096  0.000096  0.000096  0.000096     1    0.0  0.0   \n",
+       "prebuild_gwn    0.000090  0.000090  0.000090  0.000090     1    0.0  0.0   \n",
+       "clean_real      0.000088  0.000088  0.000088  0.000088     1    0.0  0.0   \n",
        "\n",
-       "                    time                                      \n",
-       "                     min       max      mean       sum count  \n",
-       "function                                                      \n",
-       "Py_kgeneration  0.633546  0.633546  0.633546  0.633546     1  \n",
-       "generate        0.397899  0.397899  0.397899  0.397899     1  \n",
-       "gasdev          0.000106  0.007636  0.000579  0.296354   512  \n",
-       "fftma2          0.234361  0.234361  0.234361  0.234361     1  \n",
-       "covariance      0.224350  0.224350  0.224350  0.224350     1  \n",
-       "cov_value       0.000103  0.000966  0.000134  0.093502   700  \n",
-       "ran2            0.000101  0.000583  0.000133  0.093435   702  \n",
-       "fourt           0.000553  0.000795  0.000664  0.001993     3  \n",
-       "cgrid           0.001623  0.001623  0.001623  0.001623     1  \n",
-       "length          0.000355  0.000359  0.000358  0.001073     3  \n",
-       "clean_real      0.000463  0.000463  0.000463  0.000463     1  \n",
-       "prebuild_gwn    0.000454  0.000454  0.000454  0.000454     1  \n",
-       "build_real      0.000410  0.000410  0.000410  0.000410     1  \n",
-       "maxfactor       0.000105  0.000106  0.000105  0.000316     3  "
+       "                            cpu                        \n",
+       "               median       min         max      mean  \n",
+       "function                                               \n",
+       "Py_kgeneration    0.2  4.978049    4.978049  4.978049  \n",
+       "generate         -0.1  7.507407    7.507407  7.507407  \n",
+       "gasdev            0.0  0.000000  100.100000  0.393945  \n",
+       "fftma2            0.3  0.100000    0.100000  0.100000  \n",
+       "covariance        0.3  0.100000    0.100000  0.100000  \n",
+       "ran2              0.0  0.000000  100.100000  0.143162  \n",
+       "cov_value         0.0  0.000000    0.100000  0.000286  \n",
+       "cgrid             0.0  0.000000    0.000000  0.000000  \n",
+       "length            0.0  0.000000    0.000000  0.000000  \n",
+       "fourt             0.0  0.000000    0.000000  0.000000  \n",
+       "maxfactor         0.0  0.000000    0.000000  0.000000  \n",
+       "build_real        0.0  0.000000    0.000000  0.000000  \n",
+       "prebuild_gwn      0.0  0.000000    0.000000  0.000000  \n",
+       "clean_real        0.0  0.000000    0.000000  0.000000  "
       ]
      },
-     "execution_count": 57,
+     "execution_count": 75,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "df = analyze(['log_8-aa'])\n",
+    "overall_time[\"8\"] = df.loc[\"Py_kgeneration\"][(\"time\", \"sum\")]\n",
+    "overall_memory[\"8\"] = abs(df.loc[\"Py_kgeneration\"][(\"memory\", \"median\")])\n",
     "df"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 600x600 with 4 Axes>"
       ]
@@ -596,12 +605,44 @@
     }
    ],
    "source": [
-    "plot_analysis(df)"
+    "plot_pie_charts(df, \"Time comparisons\", (\"time\", \"sum\"))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/oli/.local/lib/python3.6/site-packages/ipykernel_launcher.py:13: RuntimeWarning:\n",
+      "\n",
+      "invalid value encountered in double_scalars\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pie_charts(df, \"Memory comparisons\", (\"memory\", \"median\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -629,15 +670,15 @@
           "gasdev",
           "fftma2",
           "covariance",
-          "cov_value",
           "ran2",
-          "fourt",
+          "cov_value",
           "cgrid",
           "length",
-          "clean_real",
-          "prebuild_gwn",
+          "fourt",
+          "maxfactor",
           "build_real",
-          "maxfactor"
+          "prebuild_gwn",
+          "clean_real"
          ],
          "marker": {
           "colors": [
@@ -648,12 +689,12 @@
            "#ab63fa",
            "#FFA15A",
            "#19d3f3",
-           "#ab63fa",
-           "#636efa",
            "#636efa",
            "#636efa",
            "#ab63fa",
            "#636efa",
+           "#636efa",
+           "#ab63fa",
            "#636efa"
           ]
          },
@@ -664,36 +705,37 @@
           "generate",
           "Py_kgeneration",
           "fftma2",
-          "covariance",
           "gasdev",
-          "fftma2",
-          "",
+          "covariance",
           "",
           "",
           "fftma2",
           "",
+          "",
+          "fftma2",
           ""
          ],
          "type": "treemap",
          "values": [
-          0.633546,
-          0.397899,
-          0.2963540000000001,
-          0.234361,
-          0.22435,
-          0.09350199999999986,
-          0.09343499999999917,
-          0.001993,
-          0.001623,
-          0.001073,
-          0.000463,
-          0.000454,
-          0.00041,
-          0.000316
+          0.544398,
+          0.383407,
+          0.2805429999999995,
+          0.157936,
+          0.154748,
+          0.08265899999999979,
+          0.06792600000000004,
+          0.001345,
+          0.0008749999999999999,
+          0.000413,
+          0.000243,
+          9.6e-05,
+          9e-05,
+          8.8e-05
          ]
         }
        ],
        "layout": {
+        "autosize": true,
         "legend": {
          "tracegroupgap": 0
         },
@@ -711,6 +753,11 @@
              "line": {
               "color": "#E5ECF6",
               "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
              }
             },
             "type": "bar"
@@ -722,6 +769,11 @@
              "line": {
               "color": "#E5ECF6",
               "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
              }
             },
             "type": "barpolar"
@@ -920,9 +972,10 @@
           "histogram": [
            {
             "marker": {
-             "colorbar": {
-              "outlinewidth": 0,
-              "ticks": ""
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
              }
             },
             "type": "histogram"
@@ -1508,10 +1561,11 @@
         }
        }
       },
+      "image/png": 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        "                            \n",
-       "var gd = document.getElementById('39726ffb-b775-4f55-aac1-aab94725d325');\n",
+       "var gd = document.getElementById('987c1502-aa6c-4db4-b1b7-73f544b3635e');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -1541,7 +1595,7 @@
     }
    ],
    "source": [
-    "plot_treemap(df)"
+    "plot_treemap(df, (\"time\", \"sum\"), \"time_sum\")"
    ]
   },
   {
@@ -1553,7 +1607,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 76,
    "metadata": {},
    "outputs": [
     {
@@ -1581,23 +1635,23 @@
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
+       "      <th colspan=\"5\" halign=\"left\">time</th>\n",
        "      <th colspan=\"3\" halign=\"left\">memory</th>\n",
        "      <th colspan=\"3\" halign=\"left\">cpu</th>\n",
-       "      <th colspan=\"5\" halign=\"left\">time</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
-       "      <th>median</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sum</th>\n",
+       "      <th>count</th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
-       "      <th>mean</th>\n",
+       "      <th>median</th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
        "      <th>mean</th>\n",
-       "      <th>sum</th>\n",
-       "      <th>count</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>function</th>\n",
@@ -1617,260 +1671,262 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Py_kgeneration</th>\n",
-       "      <td>-21.2</td>\n",
-       "      <td>-21.2</td>\n",
-       "      <td>-21.2</td>\n",
-       "      <td>37.944037</td>\n",
-       "      <td>37.944037</td>\n",
-       "      <td>37.944037</td>\n",
-       "      <td>4.518677</td>\n",
-       "      <td>4.518677</td>\n",
-       "      <td>4.518677</td>\n",
-       "      <td>4.518677</td>\n",
+       "      <td>2.908668</td>\n",
+       "      <td>2.908668</td>\n",
+       "      <td>2.908668</td>\n",
+       "      <td>2.908668</td>\n",
        "      <td>1</td>\n",
+       "      <td>-11.1</td>\n",
+       "      <td>-11.1</td>\n",
+       "      <td>-11.1</td>\n",
+       "      <td>6.645455</td>\n",
+       "      <td>6.645455</td>\n",
+       "      <td>6.645455</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>generate</th>\n",
-       "      <td>-20.0</td>\n",
-       "      <td>-20.0</td>\n",
-       "      <td>-20.0</td>\n",
-       "      <td>41.633546</td>\n",
-       "      <td>41.633546</td>\n",
-       "      <td>41.633546</td>\n",
-       "      <td>3.283041</td>\n",
-       "      <td>3.283041</td>\n",
-       "      <td>3.283041</td>\n",
-       "      <td>3.283041</td>\n",
+       "      <td>2.172109</td>\n",
+       "      <td>2.172109</td>\n",
+       "      <td>2.172109</td>\n",
+       "      <td>2.172109</td>\n",
        "      <td>1</td>\n",
+       "      <td>-8.9</td>\n",
+       "      <td>-8.9</td>\n",
+       "      <td>-8.9</td>\n",
+       "      <td>6.535644</td>\n",
+       "      <td>6.535644</td>\n",
+       "      <td>6.535644</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>gasdev</th>\n",
-       "      <td>-23.9</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.023144</td>\n",
+       "      <td>0.000389</td>\n",
+       "      <td>1.593934</td>\n",
+       "      <td>4096</td>\n",
+       "      <td>-5.6</td>\n",
+       "      <td>0.7</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>100.100000</td>\n",
-       "      <td>2.239697</td>\n",
-       "      <td>0.000099</td>\n",
-       "      <td>0.121965</td>\n",
-       "      <td>0.000595</td>\n",
-       "      <td>2.437584</td>\n",
-       "      <td>4096</td>\n",
+       "      <td>0.150024</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>fftma2</th>\n",
-       "      <td>-1.2</td>\n",
-       "      <td>-1.2</td>\n",
-       "      <td>-1.2</td>\n",
-       "      <td>28.555285</td>\n",
-       "      <td>28.555285</td>\n",
-       "      <td>28.555285</td>\n",
-       "      <td>1.231253</td>\n",
-       "      <td>1.231253</td>\n",
-       "      <td>1.231253</td>\n",
-       "      <td>1.231253</td>\n",
+       "      <td>0.733791</td>\n",
+       "      <td>0.733791</td>\n",
+       "      <td>0.733791</td>\n",
+       "      <td>0.733791</td>\n",
        "      <td>1</td>\n",
+       "      <td>-2.2</td>\n",
+       "      <td>-2.2</td>\n",
+       "      <td>-2.2</td>\n",
+       "      <td>6.949315</td>\n",
+       "      <td>6.949315</td>\n",
+       "      <td>6.949315</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>covariance</th>\n",
-       "      <td>-1.2</td>\n",
-       "      <td>-1.2</td>\n",
-       "      <td>-1.2</td>\n",
-       "      <td>28.555285</td>\n",
-       "      <td>28.555285</td>\n",
-       "      <td>28.555285</td>\n",
-       "      <td>1.223604</td>\n",
-       "      <td>1.223604</td>\n",
-       "      <td>1.223604</td>\n",
-       "      <td>1.223604</td>\n",
+       "      <td>0.729820</td>\n",
+       "      <td>0.729820</td>\n",
+       "      <td>0.729820</td>\n",
+       "      <td>0.729820</td>\n",
        "      <td>1</td>\n",
+       "      <td>-2.1</td>\n",
+       "      <td>-2.1</td>\n",
+       "      <td>-2.1</td>\n",
+       "      <td>6.949315</td>\n",
+       "      <td>6.949315</td>\n",
+       "      <td>6.949315</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ran2</th>\n",
-       "      <td>-9.1</td>\n",
-       "      <td>1.3</td>\n",
+       "      <td>0.000079</td>\n",
+       "      <td>0.001632</td>\n",
+       "      <td>0.000092</td>\n",
+       "      <td>0.482296</td>\n",
+       "      <td>5268</td>\n",
+       "      <td>-2.0</td>\n",
+       "      <td>0.5</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>0.456891</td>\n",
-       "      <td>0.000095</td>\n",
-       "      <td>0.001958</td>\n",
-       "      <td>0.000135</td>\n",
-       "      <td>0.710129</td>\n",
-       "      <td>5268</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.000816</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>cov_value</th>\n",
-       "      <td>-3.8</td>\n",
-       "      <td>0.9</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.000274</td>\n",
+       "      <td>0.000089</td>\n",
+       "      <td>0.317795</td>\n",
+       "      <td>3564</td>\n",
+       "      <td>-1.6</td>\n",
+       "      <td>0.5</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>0.365993</td>\n",
-       "      <td>0.000101</td>\n",
-       "      <td>0.001366</td>\n",
-       "      <td>0.000137</td>\n",
-       "      <td>0.488994</td>\n",
-       "      <td>3564</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.000982</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>fourt</th>\n",
+       "      <th>cgrid</th>\n",
+       "      <td>0.001416</td>\n",
+       "      <td>0.001416</td>\n",
+       "      <td>0.001416</td>\n",
+       "      <td>0.001416</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000824</td>\n",
-       "      <td>0.001123</td>\n",
-       "      <td>0.000944</td>\n",
-       "      <td>0.002831</td>\n",
-       "      <td>3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>cgrid</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>fourt</th>\n",
+       "      <td>0.000329</td>\n",
+       "      <td>0.000442</td>\n",
+       "      <td>0.000383</td>\n",
+       "      <td>0.001149</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-0.0</td>\n",
+       "      <td>-0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.001635</td>\n",
-       "      <td>0.001635</td>\n",
-       "      <td>0.001635</td>\n",
-       "      <td>0.001635</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>length</th>\n",
+       "      <td>0.000286</td>\n",
+       "      <td>0.000307</td>\n",
+       "      <td>0.000300</td>\n",
+       "      <td>0.000899</td>\n",
+       "      <td>3</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000352</td>\n",
-       "      <td>0.000360</td>\n",
-       "      <td>0.000356</td>\n",
-       "      <td>0.001069</td>\n",
-       "      <td>3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>maxfactor</th>\n",
+       "      <td>0.000080</td>\n",
+       "      <td>0.000082</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.000242</td>\n",
+       "      <td>3</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000103</td>\n",
-       "      <td>0.000112</td>\n",
-       "      <td>0.000106</td>\n",
-       "      <td>0.000318</td>\n",
-       "      <td>3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>build_real</th>\n",
+       "      <td>0.000140</td>\n",
+       "      <td>0.000140</td>\n",
+       "      <td>0.000140</td>\n",
+       "      <td>0.000140</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000274</td>\n",
-       "      <td>0.000274</td>\n",
-       "      <td>0.000274</td>\n",
-       "      <td>0.000274</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>prebuild_gwn</th>\n",
+       "      <td>0.000103</td>\n",
+       "      <td>0.000103</td>\n",
+       "      <td>0.000103</td>\n",
+       "      <td>0.000103</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000267</td>\n",
-       "      <td>0.000267</td>\n",
-       "      <td>0.000267</td>\n",
-       "      <td>0.000267</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>clean_real</th>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000217</td>\n",
-       "      <td>0.000217</td>\n",
-       "      <td>0.000217</td>\n",
-       "      <td>0.000217</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "               memory                     cpu                         \\\n",
-       "                  min   max median        min         max       mean   \n",
-       "function                                                               \n",
-       "Py_kgeneration  -21.2 -21.2  -21.2  37.944037   37.944037  37.944037   \n",
-       "generate        -20.0 -20.0  -20.0  41.633546   41.633546  41.633546   \n",
-       "gasdev          -23.9   3.0    0.0   0.000000  100.100000   2.239697   \n",
-       "fftma2           -1.2  -1.2   -1.2  28.555285   28.555285  28.555285   \n",
-       "covariance       -1.2  -1.2   -1.2  28.555285   28.555285  28.555285   \n",
-       "ran2             -9.1   1.3    0.0   0.000000  100.100000   0.456891   \n",
-       "cov_value        -3.8   0.9    0.0   0.000000  100.100000   0.365993   \n",
-       "fourt             0.0   0.0    0.0   0.000000    0.000000   0.000000   \n",
-       "cgrid             0.0   0.0    0.0   0.000000    0.000000   0.000000   \n",
-       "length            0.0   0.0    0.0   0.000000    0.000000   0.000000   \n",
-       "maxfactor         0.0   0.0    0.0   0.000000    0.000000   0.000000   \n",
-       "build_real        0.0   0.0    0.0   0.000000    0.000000   0.000000   \n",
-       "prebuild_gwn      0.0   0.0    0.0   0.000000    0.000000   0.000000   \n",
-       "clean_real        0.0   0.0    0.0   0.000000    0.000000   0.000000   \n",
+       "                    time                                     memory        \\\n",
+       "                     min       max      mean       sum count    min   max   \n",
+       "function                                                                    \n",
+       "Py_kgeneration  2.908668  2.908668  2.908668  2.908668     1  -11.1 -11.1   \n",
+       "generate        2.172109  2.172109  2.172109  2.172109     1   -8.9  -8.9   \n",
+       "gasdev          0.000081  0.023144  0.000389  1.593934  4096   -5.6   0.7   \n",
+       "fftma2          0.733791  0.733791  0.733791  0.733791     1   -2.2  -2.2   \n",
+       "covariance      0.729820  0.729820  0.729820  0.729820     1   -2.1  -2.1   \n",
+       "ran2            0.000079  0.001632  0.000092  0.482296  5268   -2.0   0.5   \n",
+       "cov_value       0.000081  0.000274  0.000089  0.317795  3564   -1.6   0.5   \n",
+       "cgrid           0.001416  0.001416  0.001416  0.001416     1    0.0   0.0   \n",
+       "fourt           0.000329  0.000442  0.000383  0.001149     3   -0.0  -0.0   \n",
+       "length          0.000286  0.000307  0.000300  0.000899     3    0.0   0.0   \n",
+       "maxfactor       0.000080  0.000082  0.000081  0.000242     3    0.0   0.0   \n",
+       "build_real      0.000140  0.000140  0.000140  0.000140     1    0.0   0.0   \n",
+       "prebuild_gwn    0.000103  0.000103  0.000103  0.000103     1    0.0   0.0   \n",
+       "clean_real      0.000090  0.000090  0.000090  0.000090     1    0.0   0.0   \n",
        "\n",
-       "                    time                                      \n",
-       "                     min       max      mean       sum count  \n",
-       "function                                                      \n",
-       "Py_kgeneration  4.518677  4.518677  4.518677  4.518677     1  \n",
-       "generate        3.283041  3.283041  3.283041  3.283041     1  \n",
-       "gasdev          0.000099  0.121965  0.000595  2.437584  4096  \n",
-       "fftma2          1.231253  1.231253  1.231253  1.231253     1  \n",
-       "covariance      1.223604  1.223604  1.223604  1.223604     1  \n",
-       "ran2            0.000095  0.001958  0.000135  0.710129  5268  \n",
-       "cov_value       0.000101  0.001366  0.000137  0.488994  3564  \n",
-       "fourt           0.000824  0.001123  0.000944  0.002831     3  \n",
-       "cgrid           0.001635  0.001635  0.001635  0.001635     1  \n",
-       "length          0.000352  0.000360  0.000356  0.001069     3  \n",
-       "maxfactor       0.000103  0.000112  0.000106  0.000318     3  \n",
-       "build_real      0.000274  0.000274  0.000274  0.000274     1  \n",
-       "prebuild_gwn    0.000267  0.000267  0.000267  0.000267     1  \n",
-       "clean_real      0.000217  0.000217  0.000217  0.000217     1  "
+       "                            cpu                        \n",
+       "               median       min         max      mean  \n",
+       "function                                               \n",
+       "Py_kgeneration  -11.1  6.645455    6.645455  6.645455  \n",
+       "generate         -8.9  6.535644    6.535644  6.535644  \n",
+       "gasdev            0.0  0.000000  100.100000  0.150024  \n",
+       "fftma2           -2.2  6.949315    6.949315  6.949315  \n",
+       "covariance       -2.1  6.949315    6.949315  6.949315  \n",
+       "ran2              0.0  0.000000    0.100000  0.000816  \n",
+       "cov_value         0.0  0.000000    0.100000  0.000982  \n",
+       "cgrid             0.0  0.000000    0.000000  0.000000  \n",
+       "fourt             0.0  0.000000    0.000000  0.000000  \n",
+       "length            0.0  0.000000    0.000000  0.000000  \n",
+       "maxfactor         0.0  0.000000    0.000000  0.000000  \n",
+       "build_real        0.0  0.000000    0.000000  0.000000  \n",
+       "prebuild_gwn      0.0  0.000000    0.000000  0.000000  \n",
+       "clean_real        0.0  0.000000    0.000000  0.000000  "
       ]
      },
-     "execution_count": 59,
+     "execution_count": 76,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "df = analyze(['log_16-aa'])\n",
+    "overall_time[\"16\"] = df.loc[\"Py_kgeneration\"][(\"time\", \"sum\")]\n",
+    "overall_memory[\"16\"] = abs(df.loc[\"Py_kgeneration\"][(\"memory\", \"median\")])\n",
     "df"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 600x600 with 4 Axes>"
       ]
@@ -1880,7 +1936,39 @@
     }
    ],
    "source": [
-    "plot_analysis(df)"
+    "plot_pie_charts(df, \"Time comparisons\", (\"time\", \"sum\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/oli/.local/lib/python3.6/site-packages/ipykernel_launcher.py:13: RuntimeWarning:\n",
+      "\n",
+      "invalid value encountered in double_scalars\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pie_charts(df, \"Memory comparisons\", (\"memory\", \"median\"))"
    ]
   },
   {
@@ -1923,6 +2011,7 @@
           "prebuild_gwn",
           "clean_real"
          ],
+         "level": "Py_kgeneration",
          "marker": {
           "colors": [
            "#636efa",
@@ -1978,6 +2067,7 @@
         }
        ],
        "layout": {
+        "autosize": true,
         "legend": {
          "tracegroupgap": 0
         },
@@ -2792,6 +2882,7 @@
         }
        }
       },
+      "image/png": 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\"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Time treemap\"}},                        {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
@@ -2837,7 +2928,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [
     {
@@ -2865,23 +2956,23 @@
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
+       "      <th colspan=\"5\" halign=\"left\">time</th>\n",
        "      <th colspan=\"3\" halign=\"left\">memory</th>\n",
        "      <th colspan=\"3\" halign=\"left\">cpu</th>\n",
-       "      <th colspan=\"5\" halign=\"left\">time</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
-       "      <th>median</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sum</th>\n",
+       "      <th>count</th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
-       "      <th>mean</th>\n",
+       "      <th>median</th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
        "      <th>mean</th>\n",
-       "      <th>sum</th>\n",
-       "      <th>count</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>function</th>\n",
@@ -2901,260 +2992,262 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Py_kgeneration</th>\n",
-       "      <td>240.1</td>\n",
-       "      <td>240.1</td>\n",
-       "      <td>240.1</td>\n",
-       "      <td>24.536011</td>\n",
-       "      <td>24.536011</td>\n",
-       "      <td>24.536011</td>\n",
-       "      <td>47.638534</td>\n",
-       "      <td>47.638534</td>\n",
-       "      <td>47.638534</td>\n",
-       "      <td>47.638534</td>\n",
+       "      <td>22.135483</td>\n",
+       "      <td>22.135483</td>\n",
+       "      <td>22.135483</td>\n",
+       "      <td>22.135483</td>\n",
        "      <td>1</td>\n",
+       "      <td>53.6</td>\n",
+       "      <td>53.6</td>\n",
+       "      <td>53.6</td>\n",
+       "      <td>24.085573</td>\n",
+       "      <td>24.085573</td>\n",
+       "      <td>24.085573</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>generate</th>\n",
-       "      <td>197.0</td>\n",
-       "      <td>197.0</td>\n",
-       "      <td>197.0</td>\n",
-       "      <td>23.163878</td>\n",
-       "      <td>23.163878</td>\n",
-       "      <td>23.163878</td>\n",
-       "      <td>35.573628</td>\n",
-       "      <td>35.573628</td>\n",
-       "      <td>35.573628</td>\n",
-       "      <td>35.573628</td>\n",
+       "      <td>16.686848</td>\n",
+       "      <td>16.686848</td>\n",
+       "      <td>16.686848</td>\n",
+       "      <td>16.686848</td>\n",
        "      <td>1</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>13.146080</td>\n",
+       "      <td>13.146080</td>\n",
+       "      <td>13.146080</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>gasdev</th>\n",
-       "      <td>-14.9</td>\n",
-       "      <td>6.5</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.023022</td>\n",
+       "      <td>0.000377</td>\n",
+       "      <td>12.362677</td>\n",
+       "      <td>32768</td>\n",
+       "      <td>-6.2</td>\n",
+       "      <td>3.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>100.100000</td>\n",
-       "      <td>1.806851</td>\n",
-       "      <td>0.000098</td>\n",
-       "      <td>0.017469</td>\n",
-       "      <td>0.000797</td>\n",
-       "      <td>26.105193</td>\n",
-       "      <td>32768</td>\n",
+       "      <td>0.420267</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>fftma2</th>\n",
-       "      <td>43.1</td>\n",
-       "      <td>43.1</td>\n",
-       "      <td>43.1</td>\n",
-       "      <td>28.564730</td>\n",
-       "      <td>28.564730</td>\n",
-       "      <td>28.564730</td>\n",
-       "      <td>12.060570</td>\n",
-       "      <td>12.060570</td>\n",
-       "      <td>12.060570</td>\n",
-       "      <td>12.060570</td>\n",
+       "      <td>5.445881</td>\n",
+       "      <td>5.445881</td>\n",
+       "      <td>5.445881</td>\n",
+       "      <td>5.445881</td>\n",
        "      <td>1</td>\n",
+       "      <td>5.6</td>\n",
+       "      <td>5.6</td>\n",
+       "      <td>5.6</td>\n",
+       "      <td>57.504022</td>\n",
+       "      <td>57.504022</td>\n",
+       "      <td>57.504022</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>covariance</th>\n",
-       "      <td>42.6</td>\n",
-       "      <td>42.6</td>\n",
-       "      <td>42.6</td>\n",
-       "      <td>28.493006</td>\n",
-       "      <td>28.493006</td>\n",
-       "      <td>28.493006</td>\n",
-       "      <td>12.036319</td>\n",
-       "      <td>12.036319</td>\n",
-       "      <td>12.036319</td>\n",
-       "      <td>12.036319</td>\n",
+       "      <td>5.433282</td>\n",
+       "      <td>5.433282</td>\n",
+       "      <td>5.433282</td>\n",
+       "      <td>5.433282</td>\n",
        "      <td>1</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>57.609158</td>\n",
+       "      <td>57.609158</td>\n",
+       "      <td>57.609158</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ran2</th>\n",
-       "      <td>-7.1</td>\n",
-       "      <td>2.6</td>\n",
+       "      <td>0.000078</td>\n",
+       "      <td>0.001366</td>\n",
+       "      <td>0.000094</td>\n",
+       "      <td>3.885548</td>\n",
+       "      <td>41552</td>\n",
+       "      <td>-3.0</td>\n",
+       "      <td>1.7</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>100.100000</td>\n",
-       "      <td>0.449610</td>\n",
-       "      <td>0.000094</td>\n",
-       "      <td>0.001763</td>\n",
-       "      <td>0.000191</td>\n",
-       "      <td>7.933390</td>\n",
-       "      <td>41552</td>\n",
+       "      <td>0.071948</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>cov_value</th>\n",
-       "      <td>-4.1</td>\n",
-       "      <td>2.5</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.000219</td>\n",
+       "      <td>0.000094</td>\n",
+       "      <td>2.323766</td>\n",
+       "      <td>24624</td>\n",
+       "      <td>-2.1</td>\n",
+       "      <td>0.5</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>100.100000</td>\n",
-       "      <td>0.460892</td>\n",
-       "      <td>0.000181</td>\n",
-       "      <td>0.000461</td>\n",
-       "      <td>0.000199</td>\n",
-       "      <td>4.906137</td>\n",
-       "      <td>24624</td>\n",
+       "      <td>0.520748</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>fourt</th>\n",
+       "      <td>0.002485</td>\n",
+       "      <td>0.003625</td>\n",
+       "      <td>0.002885</td>\n",
+       "      <td>0.008655</td>\n",
+       "      <td>3</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>0.5</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>33.400000</td>\n",
-       "      <td>0.004642</td>\n",
-       "      <td>0.006769</td>\n",
-       "      <td>0.005419</td>\n",
-       "      <td>0.016257</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>cgrid</th>\n",
+       "      <td>0.001855</td>\n",
+       "      <td>0.001855</td>\n",
+       "      <td>0.001855</td>\n",
+       "      <td>0.001855</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>0.003691</td>\n",
-       "      <td>0.003691</td>\n",
-       "      <td>0.003691</td>\n",
-       "      <td>0.003691</td>\n",
-       "      <td>1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>length</th>\n",
+       "      <td>0.000294</td>\n",
+       "      <td>0.000552</td>\n",
+       "      <td>0.000456</td>\n",
+       "      <td>0.001369</td>\n",
+       "      <td>3</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>33.366667</td>\n",
-       "      <td>0.000633</td>\n",
-       "      <td>0.001058</td>\n",
-       "      <td>0.000914</td>\n",
-       "      <td>0.002742</td>\n",
-       "      <td>3</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>maxfactor</th>\n",
+       "      <th>build_real</th>\n",
+       "      <td>0.000529</td>\n",
+       "      <td>0.000529</td>\n",
+       "      <td>0.000529</td>\n",
+       "      <td>0.000529</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>20.020000</td>\n",
-       "      <td>0.000179</td>\n",
-       "      <td>0.000185</td>\n",
-       "      <td>0.000182</td>\n",
-       "      <td>0.000910</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>prebuild_gwn</th>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>0.5</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000599</td>\n",
-       "      <td>0.000599</td>\n",
-       "      <td>0.000599</td>\n",
-       "      <td>0.000599</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>build_real</th>\n",
+       "      <th>maxfactor</th>\n",
+       "      <td>0.000089</td>\n",
+       "      <td>0.000093</td>\n",
+       "      <td>0.000091</td>\n",
+       "      <td>0.000455</td>\n",
+       "      <td>5</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000510</td>\n",
-       "      <td>0.000510</td>\n",
-       "      <td>0.000510</td>\n",
-       "      <td>0.000510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prebuild_gwn</th>\n",
+       "      <td>0.000230</td>\n",
+       "      <td>0.000230</td>\n",
+       "      <td>0.000230</td>\n",
+       "      <td>0.000230</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>clean_real</th>\n",
+       "      <td>0.000172</td>\n",
+       "      <td>0.000172</td>\n",
+       "      <td>0.000172</td>\n",
+       "      <td>0.000172</td>\n",
+       "      <td>1</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.000403</td>\n",
-       "      <td>0.000403</td>\n",
-       "      <td>0.000403</td>\n",
-       "      <td>0.000403</td>\n",
-       "      <td>1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "               memory                       cpu                          \\\n",
-       "                  min    max median         min         max        mean   \n",
-       "function                                                                  \n",
-       "Py_kgeneration  240.1  240.1  240.1   24.536011   24.536011   24.536011   \n",
-       "generate        197.0  197.0  197.0   23.163878   23.163878   23.163878   \n",
-       "gasdev          -14.9    6.5    0.0    0.000000  100.100000    1.806851   \n",
-       "fftma2           43.1   43.1   43.1   28.564730   28.564730   28.564730   \n",
-       "covariance       42.6   42.6   42.6   28.493006   28.493006   28.493006   \n",
-       "ran2             -7.1    2.6    0.0    0.000000  100.100000    0.449610   \n",
-       "cov_value        -4.1    2.5    0.0    0.000000  100.100000    0.460892   \n",
-       "fourt             0.0    0.0    0.0    0.000000  100.100000   33.400000   \n",
-       "cgrid             0.0    0.0    0.0  100.100000  100.100000  100.100000   \n",
-       "length            0.0    0.0    0.0    0.000000  100.100000   33.366667   \n",
-       "maxfactor         0.0    0.0    0.0    0.000000  100.100000   20.020000   \n",
-       "prebuild_gwn      0.5    0.5    0.5    0.000000    0.000000    0.000000   \n",
-       "build_real        0.0    0.0    0.0    0.000000    0.000000    0.000000   \n",
-       "clean_real        0.0    0.0    0.0    0.000000    0.000000    0.000000   \n",
+       "                     time                                         memory  \\\n",
+       "                      min        max       mean        sum  count    min   \n",
+       "function                                                                   \n",
+       "Py_kgeneration  22.135483  22.135483  22.135483  22.135483      1   53.6   \n",
+       "generate        16.686848  16.686848  16.686848  16.686848      1   48.0   \n",
+       "gasdev           0.000081   0.023022   0.000377  12.362677  32768   -6.2   \n",
+       "fftma2           5.445881   5.445881   5.445881   5.445881      1    5.6   \n",
+       "covariance       5.433282   5.433282   5.433282   5.433282      1    4.9   \n",
+       "ran2             0.000078   0.001366   0.000094   3.885548  41552   -3.0   \n",
+       "cov_value        0.000081   0.000219   0.000094   2.323766  24624   -2.1   \n",
+       "fourt            0.002485   0.003625   0.002885   0.008655      3    0.0   \n",
+       "cgrid            0.001855   0.001855   0.001855   0.001855      1    0.0   \n",
+       "length           0.000294   0.000552   0.000456   0.001369      3    0.0   \n",
+       "build_real       0.000529   0.000529   0.000529   0.000529      1    0.0   \n",
+       "maxfactor        0.000089   0.000093   0.000091   0.000455      5    0.0   \n",
+       "prebuild_gwn     0.000230   0.000230   0.000230   0.000230      1    0.2   \n",
+       "clean_real       0.000172   0.000172   0.000172   0.000172      1    0.0   \n",
        "\n",
-       "                     time                                          \n",
-       "                      min        max       mean        sum  count  \n",
-       "function                                                           \n",
-       "Py_kgeneration  47.638534  47.638534  47.638534  47.638534      1  \n",
-       "generate        35.573628  35.573628  35.573628  35.573628      1  \n",
-       "gasdev           0.000098   0.017469   0.000797  26.105193  32768  \n",
-       "fftma2          12.060570  12.060570  12.060570  12.060570      1  \n",
-       "covariance      12.036319  12.036319  12.036319  12.036319      1  \n",
-       "ran2             0.000094   0.001763   0.000191   7.933390  41552  \n",
-       "cov_value        0.000181   0.000461   0.000199   4.906137  24624  \n",
-       "fourt            0.004642   0.006769   0.005419   0.016257      3  \n",
-       "cgrid            0.003691   0.003691   0.003691   0.003691      1  \n",
-       "length           0.000633   0.001058   0.000914   0.002742      3  \n",
-       "maxfactor        0.000179   0.000185   0.000182   0.000910      5  \n",
-       "prebuild_gwn     0.000599   0.000599   0.000599   0.000599      1  \n",
-       "build_real       0.000510   0.000510   0.000510   0.000510      1  \n",
-       "clean_real       0.000403   0.000403   0.000403   0.000403      1  "
+       "                                   cpu                         \n",
+       "                 max median        min         max       mean  \n",
+       "function                                                       \n",
+       "Py_kgeneration  53.6   53.6  24.085573   24.085573  24.085573  \n",
+       "generate        48.0   48.0  13.146080   13.146080  13.146080  \n",
+       "gasdev           3.0    0.0   0.000000  100.100000   0.420267  \n",
+       "fftma2           5.6    5.6  57.504022   57.504022  57.504022  \n",
+       "covariance       4.9    4.9  57.609158   57.609158  57.609158  \n",
+       "ran2             1.7    0.0   0.000000  100.100000   0.071948  \n",
+       "cov_value        0.5    0.0   0.000000  100.100000   0.520748  \n",
+       "fourt            0.5    0.0   0.000000    0.000000   0.000000  \n",
+       "cgrid            0.0    0.0   0.000000    0.000000   0.000000  \n",
+       "length           0.0    0.0   0.000000    0.000000   0.000000  \n",
+       "build_real       0.0    0.0   0.000000    0.000000   0.000000  \n",
+       "maxfactor        0.0    0.0   0.000000    0.000000   0.000000  \n",
+       "prebuild_gwn     0.2    0.2   0.000000    0.000000   0.000000  \n",
+       "clean_real       0.0    0.0   0.000000    0.000000   0.000000  "
       ]
      },
-     "execution_count": 50,
+     "execution_count": 77,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "df = analyze(['log_32-aa'])\n",
+    "overall_time[\"32\"] = df.loc[\"Py_kgeneration\"][(\"time\", \"sum\")]\n",
+    "overall_memory[\"32\"] = abs(df.loc[\"Py_kgeneration\"][(\"memory\", \"median\")])\n",
     "df"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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+VCrcfIGV3EZjVX/XB96u4rp+xKo+ng3MEJHzS1z0bqL84x+sDmMAOyt4PFbEOqwmwkWm6o+7VebcZEqZVppNgT97cnCNRc+g+Qp9TC5kBdq+5wHniUi7ouki0h04M6ho0RWqBJVxAVcEr09EmgZ6yQcratuLDfz5GdZF37ig5ZzAjSVi2wnMB64TkbYlYxeRliXKr8S627ko8NmO1XFPqbASSMBTsZ4MGQv8boz57TDWNw/rAvsM4G0RCT4nzwGOF5GjiyYE+r+UvKueg1UN/8/S+teUPB4raDpWB9t7S84QkSgRKfXR2RIqdG4KyOEQj+OWsBjr5ud6ESk6byEiZwK9gLQKrKPO0Dv40ObG6pC2SERewDrgJmD1OC066OdiVXt9KiIvYbXpXYN1EAQn38uB8SIyE+vqvFGgXBZWYgf4FKsX/OTAM7YrsDrHldYZ5gZgIfC7iLyCdVffGqutrQNwVIny04AHsGolXqtilaZSoeAt4CasjmZ3Hu7KjDGzROSKwHqzCDxDDjwKXIrV0e1Z/n5MbjNWb3oTWD4r8Gz528AvIvI+Vi1DJ6xOZ4uwzhuViWlB4HxyV+ACYy7W0zs9sDrg3Qx8UM5qKnpuAqvz3jgRuQereW+nMeagPgXGGI+I3In1mNwCEZnK34/JbeTgRxjrNru78eun7A9Wb/VfsJ59/QO4CqvtOy+ozNnAUqx2sA3AJKyr5OBHafoA72FVYeVjVZV/CqSU2F4zrBNNJlbP+7ewLiYOeEwuULYr1rO327EO5D8D6xxeyn50D6zDAAPt/l31o5/gD38/JnfIx0hLlF+GdYfavgrbig9s6/YS08cFpj8WNO1orNqufKw27FSsGjUDtC6x/CCsJoSMwLngD6xEmBJU5g0gu5SY3AQ9ehs0/Rqsu+ZcrIuP34D/AG2DymwEZh9iX8s9NwXKtcZqqsgKzJsftE/Fj8kFlR8ZOC/mYz02+E7Jf4vK7mskfiSwwyqMiMgsoLcxpke5hZVS1U5EfgX2GmNOs2HbT2Hd5Tc0VlOeUqXSNvgQJyL1SnzvgdULdb4tASlVx4lIX6w767dqYVslj//mWL3lF2pyV+XRO/gQJyLbsaqa1mM9AzoOq1NcH2PMWhtDU6pOEZEjgBSsV522ALqaoEfbAh1Sy+vQlm0q8UiqiCzBuphfiVWNfRXQDjjNGKMdVVWZtJNd6PsCGAW0wWqH/wH4pyZ3pWrdhVhjQawGRpmDn1vvyCFe+BLkX1htwBX1WWC7Ra/J/QW4SpO7qgi9g1dKqWogIkVjyJdlvTFmfTlllKoWmuCVUkqpCKSd7JRSSqkIpAleKaWUikCa4JVSSqkIpAleKaWUikCa4JVSSqkIpAleKaWUikCVetFNenp6Q6y3KOmFQeTzYw1asTslJUVHfqvD9LhXh0nPJTap8HPw6enpxzkcjhcdDoeLoPF9VeQyxnj9fv8CY8x9KSkpW+2OR9U+Pe5VddBziT0qlODT09MbOhyOhU2aNGndqlWrvSKib8cJU36/wes3MT6/ESMIxogxOAwQh4covCACBlPg9Tt27t5bPzcvd7PfyICUlJRCu+NXtUeP+/Dn9xt8xkT5/Mbp85sonx+nzxin328cYMQAseLzNzbZTkQMiEGsj5EoL84oD44oL45oL1K16ztjDIWFhTE7duxonJeXt9nv95+g55LaUdEq+nYOh8PVqlWrvQ0aNMir0YjUYfH6/M4Crz+m0OePLfT6Yzw+f4zHZ2I8Pn+sx+eP8fnNIf/Ne8ZkZMd6sxoWfa8PxNY3bMrY3bLLwluz+XRrBrAXa/z3dUGfP4B1uDMza3bvVC3T4z4MFHr9UfleX1yBxx9X6PXFFnj9cYU+f5zXZ2L8xpTRrGIl7BYxvpx63n0Nyt2QOAMJP7oQR5QHZ7SHqLg8YhrkEhVXUNYFQIMGDfKjo6M969ata+n3+zthnTNUDatogncAolfwoaXQ64/en+9plFPoa5hX6Gvo8fljyz6gK88hAALiiMYaKasl0BMYdFBht2sXkA78HPj8hDtzR3XGo2qVHvchxuvzO7MLvA1yC30Ncwt9DfI9vgZ+Y5y1snHji8Lri4KCegfNE4ePqLhcouvnEF0vl5iGOUTHHXCX7nA4DNZVhQ5yVkv0hw4j+R5fTHaBt1FOgbdRbiCh2x1TCS2BMwIfi9u1BfgJa8jLObgzdRQ8pSqo0OuPysr3uHIKvA3zPL6GhV5/nN0xlcr4nXhyG+HJbVQ8TRw+ourlENMgm3pNMkAvFGtb1RO825VSjXGUWHdm+uEsvnr16piPP/7YNWnSpF1F09q3b588Y8aMPwYMGFCrVY1r166Nue666zqtX78+zul0miuvvHLX3XffvRPg3nvvbf3++++38Pv9dO3aNX/q1KkbW7Ro4StaNt/ji92fbyX0+fPnN378wXuj8vLzwBjcjz3DUSn9WbbkFx51p7J6+TKOP+kUnnrt3VLj8Hg83HH9WLZu2USHzl147IXXiYqKoiA/n+tHX8DTr70HrWrkJ+gY+AwHwO1aB8zBGgb3a9yZOTWyVVUj4lPTauS43zh52GEd86Fg9uzZjfLz8+XCCy/MOpz15BZ662XmeVz7871N8j2+Bovmf8XTj7iL5+/dvZvmrVox7fMFByz3/H8f4aWnHmXaF9+S2Du51HWvXbmcyffdyZ7d1qlxwqR7uPjcIbw+7WOefnVqcbk/t+/kpOP68NGr/z1oHQ8++QrvfzKHRg3qM+3FyXTu0A6AsbfczzWjz2dgv6OtgsbvxJPTGE9OY3J2thOf0xNVmJXfdvmr/fl01h+4M72H8zup8kXkHfzatWtjp0yZ0jI4wVcHj8dDdHR0hcv7/X7OO++8brfddttfV1555T6ALVu2RAHMnDmz8Xvvvddi8eLFK5s2beqfNGlS24kTJ7Z//Y03t+7NKWyWkedpke/x1QfY+dd27p44jufemkHXHj0pLCggP98airpl69bccf8jrFr+G4u+mXfIWL5f8BWNmzTlqdfe5b7bJrBo/jxO/scZvPz0Y1w89hoaN2kC7Kn6j1Nx3YDxgU8hbtdXwLvALE32KpSVd/x//fXXjTIyMpxVSfD78z0NM3I9TbMLvE08Pn9M8LyBg05j4KDTir9PGHsR/Y4/8YDlf/81neVLf6Fdh46H3EZeXi43Xz2ah558gWP6H4/P5yMzYx8AV1x0LldcdG5x2SNOHcHo84cetI6s/dm889FnrJj/Ae9+9DnPTpnG4/dN5Mtvf6R+vbi/k3spxHijHd7c6Ma7098EnsTt+gz4GPgCd2Z2Wb+Pqpqwfq71ww8/bJyUlNQrISEhqV+/fj3T09PjAG688cZOGzdujEtMTEw69dRTuxeVnz59etOjjz46sX379smTJk1qWzR98+bNUUOHDu2anJzcKyEhIemmm25qVzSvffv2yePGjWufnJzca/jw4V0qE98nn3zSKCYmxhQld4COHTt6AX799dd6/fv3z27atKnfGMPgM8/yzZw1q+XK7fuP+isrv1NRcgeY/tZrnHnuhXTt0ROAmNhYGrtcALRu257kPinExJRdWx8VFU1+Xi4A+Xm5REfHsGblMjasW8vpZ59fmd2qTjHAmcA7wA7crndxu4bidkXkhac6fO+8806Trl279u7Zs2fSuHHj2jdt2vSo1atXxwD8/vvvsYMGDep+xBFH9EpISEh6+OGHWxYtJyIpqampbZKTk3u1b98++emnn25eNK+85SZOnNjuiCOO6DVhwoQOP/30U72UlJSeSUlJvbp169a76Dzy/fff13vrrbdazpw5s1liYmLS7bff3hasc1RKSkrP3r1790pOTu716aefFldhF3r90dsz89qs2p51xIbdOT335Ra2KpncS9r513Z+WvgtZw2/qHhaXl4uj9w7iXsnP1nmb/f5rA84sk9fjul/PABOp5NmzVscVO7/fvmdnbv3cs6Qkw6a53Q68fl9eDxecnLziImOIjcvjwefeoXJ/7yxzO2X0Ay4FJgB7Mbt+gi36wzcrrDOSaEmbE+kW7dujbrqqqu6zp07d3X//v3zXnjhhWYjR47stnbt2uXPPvvs5ttvv73jqlWrVgQvk5GR4VyyZMmq7du3RyUkJBwxbty43V26dPFccsklXe66667tw4YNy/Z4PJx66qk9pkyZ0rQoMe/duzdq6dKlKx2Oyv3fW7ZsWb1mzZp5zjrrrK7r1q2L69ChQ8HTTz+9JSkpqbBfv365U15/vfXiFX90inO1aPr21OlROdnZZOzbK66mTQ9Yz7q1q2nXviPXjjqPjL176NP/eG6+637q1y+/42uR4086hXmffcKIISeQfExf+g88ifFjLuTBJ56r1D7VoAbAJYHPLtyud4BncWdusDcsFSq2bt0aNWHChPhvvvlmVZ8+ffKffvrp5hkZGVEAXq+XUaNGdX377bc39OnTJ3///v2OlJSUxIEDB+acfPLJuQCxsbHm999/X/nrr7/GnXDCCb3Gjx+/R0TKXc7pdJply5atBNi3b59j4cKFa+rVq2eys7OlX79+vU4//fSs0047Leeyyy7blZGR4ZwyZcoWgBUrVsQ8+OCD7b7++us1zZo18y9btiz2lFNOSVy6at2mPL+jRW6B11XZRulPZrzHCacOpnmL4msQnvz3/YwccyVt2nUoc9l1a1YTHRPLhLEXsXP7Nnr06s1t9z5Ei7aNDij32vuzGDN8WKm1FQ3q1+PWay7luLMvp02r5rz51APc99iL3HbdGBo3anhQ+QqKBc4PfDbidr0KvIY786+qrlBZwvZqacGCBQ0SEhLy+vfvnwcwbty4vTt37ozesGHDIevQxowZsxegbdu23g4dOhSuWbMmNisry/Hjjz82vu222zolJiYmJScnJ23atCl21apVxZ1Zrrzyyj2VTe4AXq9Xfvzxx8Zut3vbypUrVwwePDhrxMiR3Xdk5bdK6Deow+XX3xx9+cUjWo466x9RTZtbNxTOqIM7xPq8XtJ/+p7HX3iDd2d/TVZmBi/8d3KlYnE4HNz/6NPMmLuQ+yY/xftvvMIppw/F6/WROuFqbr32Mr5asKh2euOWryUwEfgDt2sWbtcpdgek7Dd//vwGPXv2zO3Tp08+wIQJE/ZER0cbgKVLl8b98ccf9UaNGtU1MTExqV+/fok5OTnO3377rbjH91VXXbUHoE+fPvlOp9Ns3rw5uiLLjRs3bnfR33Nzcx2jRo2KT0hISEpJSem1bdu2mPT09PqU4pNPPnFt2rQpdsCAAYmJiYlJF44Y2VOcUVHpK9Z2y6lCcjfGMGvau5x/8aXF03749hu2b93CeReNLnd5n8/L/y2cz72PPMm0L76lVZu2/Puftx1QJic3j/c/nstVo8475HrGjx3Jki/f54t3n+PP7Tv4c/sOzhg0gBv++Qgjrp3EM69NPeSyFRAPPARsxu16p0b7etUBYXsHXxX16tUrfk2i0+k0Ho+n+EU/v/zyy8r69euXesw1atTIV9r09PT0uNGjR3cF6NevX/bbb7+9OXh+586dC3v16pXbt2/ffI/PH3XeqCtiU1NT6/25Z3/H6OhoLrr8ai66/GoAfvvlZ1q3bUfDRo0P2k6b9h3o2Ts50E4OZ547nNeeK7s6rizb/tzMd19/yQvvfMA9E8cxfPRYkpKP4opzTokdOn9GlddbAxzAucC5uF2/Ac8A7+LOzLc3LBVqjDE0btzYW7LWLljw8e10Oo3X65WKLOdyuYrPG7feemv75s2be5cvX74iOjqaIUOGdMvPzy/1AXBjDCeccGL2i2+9n78v19PyUI+zrVuzirtuvAaAo/seyz///XipcSz+cREFBQUMOPnv9vifvv+Wlb//xpnHHwnAju3bmHDZSO6Z/ASDBp95wPJt23Wg34ATad3WaoEcdv5Ixl164QFlZnz6Jb0TupKU0PVQP0cxr9fL7Q88xdTnH+adjz6jZfOmPPfwXZxy4bWc9Y8T6dq57BqFckQDo4HRuF3fAU9i9dPRnviVELZ38IMGDcpZs2ZNvZ9//jkO4OWXX27aunVrT5cuXTxNmjTx7d+/v0J3oy6Xy9+/f/+se+65p7hNfuPGjdHr1q0rtzddSkpK/qpVq1asWrVqRckjKPmwAAAgAElEQVTkDjB8+PDMv/76K+b/fl/dafVf+5M/SUtr3aVHz+Kqr107rBqovLxcnnv8EcaOu7nU7Qw970J+/v47CgsKAFj4zTx69jqiIrtXqkfvv4s77v83DoeDvNxcBEEcDnJz80L5VaRHAq9i3dVfj9tV8d6OKiIMGjQoZ/Xq1fWXLl0aC/DCCy8093g8AnDUUUflN2zY0Bfctr5s2bLYHTt2lHkeqOxyGRkZUR06dCiMjo5m6dKlsYsWLSq+Im/cuLEvKyvLCdYTMMeddmbDRT/80OSHxb+0KUruv/968MMC3RISmT7nO6bP+e6QyR1g5vtvc+6IUTidf4d2c+r9zFu8gs9/+I3Pf/iN1m3b8b+3ph+U3AGGnH0ey5f+SvZ+qw/gwm++pGdS7wPKvPb+rDLv3oP996V3uOT8M2jTqgU5uXlI4EU3IlZNQDU6EfgISMftGlydK450YXsH365dO++rr766/vLLL+/i9XrF5XL5pk2bts7hcHDsscfmJiQk5PXo0aN3x44dC77++usy35o0Y8aMDePHj+/Yo0eP3iJi6tWr53/xxRc3devWzVPV+Lw+vzPLF9X23kefibr84gtbGmNo2Kgxj/7v1eIy14++AL8xeAsLGTb8IkaNvaZ43g2XjWD8bf+k91F9OLrvsQwaciYXnXkyDoeDbgmJ3POIdQe/cd1arrn4PPLzcinIz2dwv95cPWFicc1ASZ/NnEFC0hF079kLgCvH38IDd96Mx+Mh9ZbxhVjtYaGsPfACcAdu17+Ad3Bn6gAWdUD79u29zzzzzMbzzz+/e0xMjDn55JOz6tev72/evLkvOjqaTz/99I8bb7yx43PPPdfa7/dL06ZNvdOnT18PlFoDB1DZ5e67775tY8eO7Tp16tTmnTt3LjjuuOOKe8xffPHF+84///zmiUm9jz5t6LnO626ZxORnX+HB1FvJz8vF4/GQ2DuZyUHngIran5XJV5/P5sMvF1VqOfcdNzFo8BkMGjKUtu07ctWEiVx23uk4HA5atWnLff95qrjs6j82smT5Gj57e0i56123cQvzf1jMZ28/C8ClFwzl/KtvY8bseQzsexTJvXpUbgcrpg8wF7frS2AS7swlNbGRSFLRd9EnRkVFfdGjR4/s+vXra/VoGfx+Izv3F7Tak13Q1ldbb5iqJj1j9hzwqlqAfK9hw9ZddFl0G3HZW+wKrSwrgfuBD7T6rnqF4nG/b98+R9OmTf0Ab7/9dpP777+//fr165fbHZffGNmZld96d3Zh2+p+m2RNaxFTkNPOu63iPXarqJrPJQZ4D7gHd+bGww4uQoXtHXyoMcawJ6ew+c79Be285TzqoqpVL2A6sAi3a4Je1Ue2//znP61mzpzZzO/3S8OGDX1vvfWW7U9Z7MkpaLozq6BDeY+4qWolWG30F+J2PQ88hDtzr80xhRxN8NUgr9AXu2Vfbpd8j6/Gr4LVIQ3EaqN7Ebgbd2aG3QGp6jd58uS/Jk+eHBKPT+UUeOtty8jrnKfHvZ1isZ64uRK36x7gOa3J+1tYVSWFGmMMO7LyW/2xKztJk3tIcGC9IW8Vbtcou4NRkcnvN7J1X1779btyemlyDxku4FlgHm5XJ7uDCRWa4Kso3+OLWbcru+eOrPyOJsza3OqA1sB7uF2f4Xa1sTsYFTn253sarNmxP2lPTkEbgwnlp07qqlOB33G7rrI7kFCgiakKdu0vaPHHzuzeuYW+Kr+6SdWKM7EO9nPLLalUGfzGumvfuDsnsdAXoiO6qSKNgVdxu2bjdrUtt3QE0wRfCYVef/S6ndk9tmfmdQ63nrJ1WAtgFm7Xy7hdWp2qKi2v0Be7dkd2L+uuXYWRYcCyutxcV+VOdjU1bCSE5tCRe7ILmm3PzO90qLdRqZB3DTAIt2s07syf7Q4mbNXUq0MPc4jomrI3p7DJtoy8LnpBH7aaYTXXnQ9cgzsz0+6AapP+p8Ua9S05OblXt27denfv3r339ddf38Hns95x4fMbx4bdOV23Wgd5mcn9z82buHjoIEaefiIXnHY8t18/lqyMvztzL5j3BecO6s/ZJ6Yw8ZoxxW+UKun9N15h+D8GFK/n3SkvFc/bs2snE68Zw4WDB3LeKcfyzqsvlLoOj8fDLVeNZsSQE5h4zRi8Xmvo5YL8fK4YPvSAuOqQHliP011vdyCqaopGk0tMTEz66aef6pX8fuutt7bLzc097LZxYwx/7svt8Oe+3G5+Yxz33noDZ5/UlxFDTuDy809n2ZJfqrTeZyY/wLmD+jNiyAmMGnoKi+Z/VTzvhScmM+io7ow8/URGnn5i8etrS3PdJRdw4eCBjDz9RMZecCYrl/0GWMf3LVeNLo71ukvOZ/OG9aWuY/nSXxl5+omcPPCE+m9O/7R4+tcLf+K6SQ9Vaf9C2AjgR9yu7uWWjCARk+A9niq/dI7mzZt7p02btm7dunXLf/vttxU///xzg+eee655odcftW5Xds/9+Z6m5a8FWrVuwxsffs70Od/x0Vc/0LJ1G1540hoUJjcnG/cdN/HUq+/w6XfptGzdhpeffqzU9Qy7YCQfzvue6XO+461Zc3jrpWeLD+DHH7ibbj168sGXi3gv7Ws+mfFeqSebovHfZ8xdSKPGLhbNt8aKP3D89zopGngBt+tFfd1t+Hn55Zdb3nnnndtXrVq1on///nklvz/55JNtc3NzD+u8Vuj1R/2xK7vn3pzC1kXTTjtjGDO//pEZcxdy5Q0TuWPc2Cqt+5hjj2fa5wuYMXch7sefYdL4K8jNzSmeP/T8EcWvrX3k2VcOuZ7HXnidD75cxPQ53zHmmhu479bxxfOGj76cTxb8zIy5Cxk05Ez+NemmUtcx5fmnuPNfk/lszpzcfz35MgB5efm4n3iJ/9xd+muzw1wi8H+4XYPsDqS2hHWCr+hYzQC33npru2HDhnU99dRTu3fr1q33cccdl1D0vumBAwfmJSUlFYI1IEXv3r3z1m/Y2GDdruxeweOylycmNpa4etYgVD6fz3rPe+D9zAu/mUdi7yPp0j0BgIsuu4rPP/6o1PU0auwq/ntebm7x3TfA6hXLOOFU63XM9es34JhjBzD7o2kHrSNEx38PJdcBX+F2tSy3pAoJY8eO7bh48eKGDzzwQPs+ffoklvx+ySWXdAIYMGBAz8TExKStW7dGDR8+PH7UqFGdBwwYkNC+ffvkESNGxH/zzTf1+/fv37NDhw7JV199dfGIKG63u/URycm9jzzqqCPPH3xyw6XpPxVve9CQoURFWS2aRx7Tj51/bT/guKyoE04ZXHyO6JHYG2Ng3549lV5PY9ff54js/VnF55nYuDhOPHVI8fcj+/Rj258HDZMBQFRUFPl5eRQUFOAMjJbpfuIlbr7qEpq4GpW6TARohvW620NXj0SQsH/RTUXHagZYsmRJg/T09BVt2rTxnXXWWV2feuqplo888sgBL83YvHlz1Geffd7sf29Nx+PzV7q93VNYyOizT2Pb1i0kJPbm6SnvAbB965+07fD36ErtOnZi986/8Hq9xSeOYF+mfczzT0xmy8b13DjpXnodYY0WlXTk0Xw26wOOPKYfGfv28v2Cr4nvenCtUxiM/x4KTgQW43adq2/AC31vvPHGlhUrVtS/8cYbd4wZMyYDoOT3qVOntvz+++9Xt2jRovg98itXrqz3/fffr3Y4HCQkJPTOyMhwfvfdd2sKCgqkS5cuyddff/3uvn375l982ZWe4ddMjDXGyG+//My9t97Ax/N/OiiOd197kRNOGVzqcVsZs6a/S4dOnWnXoWPxtLmzP+bn77/D1bQZ1958B/0HnHjI5e++5Xp+/v47AJ57c3qpZd6d8iKDhgwtdd51t0ziwdSJPJe7v95j997CkmWrWb9pa6TevQeLBl7G7UoCbsedecixCsJd2Cf4kmM1X3HFFR1XrFhRT0T466+/YtLT0+sXJfiTTz45s02bNj6AY489NnvZsmX1gte1d+9ex9BhZyVeMf4WR9KRfarUjhcdE8P0Od/hKSzkkfsm8cG7b3DFIUaJK8vgYecyeNi5bN2ymYnXXMrJ/zid+G49uO3eh3jiwXu56IyTaNaiJX2PH1jqHUDR+O9F3nn1hQPGfy8sLOSiy6/m2IEnVWU3I0knrHb54bgzv7A7GFX9hg4dmlE0VGzPnj3zBg8enBUbG2tiY2NN9+7d81auXBnXuWdywwU/LO78yrP/JWPfXqKioti4bi35eXnFd9wAsz+axtzZs3j9g7TDiun/Fi7gpSf/w0vvzSy+2x5x6RVcfeNtREdH8+vPPzLxmjG8N/sr2nUo/b0t/37qRQA+mTGVpx5x89xbBw71/Oqz/2XLxg3c+37pQ0t37dGT1z/8jBbRBXmtC7c0GDJqPG8/8xBTZ33BB2nzaNywAU/cfxtNmxw8hHWEuAVIwO0ahTuz9A5RYS6sq+jh0GM1r169esWxxx67P3is5ri4uIPGgy76vm/fPsep/xjSe9AZ58SOufaGUpP7ujWrijvAPHz37WXGFR0Tw3kjRzP7Q6v6vG37Dmz/88/i+du2bKZFqzbl3gW079iJ5D4pLJg3B4CmzZrz4JPPM2PuwuKTQ7eExDLXUTT++0WXXc1zj/+b4aPH8uATzzH5vjvLXK4OqQ98gts1wu5AVPWLi4srPkc4nU5T4jtZ+b6mm3dldp547WXces+DfPTVD0wJJPDCwsLi9XzxyUe89OSjvPTeRzRv2arUbU2+787ic8TalaWPgbP4h0Xcd9sNPPP6VOK7/T3qWotWrYuHku7T7zgSex/Jit/Kr1g6Z8Qofv5+IRn7/n4V+5svPstXn8/mubdmUK9e+a2MT73yHiPOGkwTV0MefOoVpr0wmZOOO4anXn233GXD3FDgB9yuznYHUhPCPsEHK2us5rLsy8hwnjp4SPKAU4fEXHvzoRN3eeM2b/tzM3mBdm+/38/c2R+T0Msab3ngoNNYuWwpG/5YA8C0t17jjHMuKHU769asKv773j27+WnRd8Xrydi3t7hD4cplv/HNnM+46LKyX9p0qPHf84M69yiigfdxu0ofZ1eFhQYNGvj37t1boaY1Ywx+ccbl+6VZQUE+Hk8hbdtbzWhTX3/5gLJzPp3Jc4/9m5emzqRt+46lrQ6A1Af+U3yO6NGr90Hz039cxN23XMdTr71Hz6TkA+bt2L61+O+bNqxj9Yrf6Z6YdNA6sjIz2fnX9uLvX3+RhqtpM1xNrL7Ab738HJ9/8iEvvTfzgLb6Q9m0caN8+d2PXDdmOB6PF6/Xh4jgEAfZOdU6rnuoSgK+xe3qancg1a3KVfSh+Kx6WWM1H4rX73e4H36s17KlS6Ly8vL5+nPrcZHBw87lmpvKvksvac3K5fzvUevxEr/fT6/ko7jzgf8A0KBhI9yPPs0tV1+Kz+ule89ePPjk88XLjjz9RP735nRatWnLu1Ne5NeffiQ6OhpjDJdedT3Hn3QKAMuWpPOf+1JxRkVRv0FDHnt+Ci1bH/ptrGWN/37NzXdUav/qAAfwCm5XE9yZB1/BqZB9Xr3Idddd99eQIUMS4uLi/F999dWaQ5UzxrBxT25XHM5ogIaNGjPhjrsZffZpNGnW/KCL73/edC3NW7bilqtGF097+f2PadK0WaXic99xE4WFhdx/2w3F0/791Iv06NWbZx99iBW/LSEqKgqH08k/H3qsuH/N/LmfMf/LL3A/9gzZ+zO5/forKMjPw+Fw0LR5C559431EhB3bt/LfB++hQ6d4rr7obACiY2J599N5h4zp3nvuif3fv25HRHA1bsQl559B8mkjadigPtNemFyp/QtjnYD5uF2n4M5cZ3cw1aVOjwfvN0bW78pO0FfOWsJ0PPia8gDuzPvtDsJOkXrcG2PYvDc3PjPP09zuWEJBy+iCnLa+sBsPvqZsBU7BnbnW7kCqQ0RV0VeGMYZNe3K7aHJXh3AfbpdWcUSgLfvyOmlyV4fQHvgGt6uL3YFUhzqb4Lfsy+tU0RfYqDrr0bryvGxd8ee+3A4ZuYX67gNVlvZYw862szuQw1XRBO8H6643EmzPyGurB3nFFP+TR8i/fRW8iNs10u4g1OHblpHXLvjtdEqVoStWkm9hdyCHo6IJPsMY4y0sLIyp0Whqwa79BS12ZReE/ZVZbcn1AL5CovMr/7atCOEA3sHtOsPuQFTV7cjKb7U7u6BODx2qKq0XMCecR6GsaC/63X6/f8GOHTuGRUdHexwOR1jezmXleRvt3J/fKSyDrwX54nMYn/XrGGMl9517M2iy6XOcvjrxuMyhRAMf4nadjDtzsd3BqMrJyC1svCMr/9DPtil1aMcArwNhWYtXoQSfkpLiT09Pvy8vLy953bp1LYHDHq2pthX6TFxmgb9V3a1pLp849zuj/UGdpX2FNNn0OW3WvmdfUKGjPjATt6sv7swddgejKiav0Bf35768iHu+uVqF3dm81o3A7boTd+Z/7A6ksir8HHxKSsrW9PT0E/x+f6fKLBcKZqzI7rFwS947xuh/5bK8HPfs8i5m0zEAGEN0/p66fudeUgesO/lTcWcWlls6AiW/mVwj48H/fvnvh/V8/erVq2M+/vhj16RJk3YVTWvXvn3ys6+/T4+k5EqPKXE4Fsz7giceug+/z0f3xCQefOI5GjY6+J1bfr+f/9yfysKvv0REGH319Ywaey0A3341h+f/+wh/rF7JyDFXMsn9SKnbysrIYOK1Y8jYu4dj+h/P3Q//F7BekHXH9WN58b2ZxW/HU4flYdyuJbgz59gdSGVUKlGnpKQUAn/UUCw1Ij41rQXwJRCxL1SuLs6CTXlxjpB9PjVUDASeA7R3fQhZu3Zt7JQpU1oWJXhjDCKOaN9hXtQfajCoQykaFnrKjNl06Z7Aw/fcwctPP8at9zx4UNm0j6azfu1qPvl2MdlZWVx05kn0O/5EuvfsRacu3fjX48/y5eyPDxhO9qB1zJpOvwEncv0tk7j6onNYu2oFPRKTePyBu7n5rvs1uVcfBzAVt6tfOL0IJ6Ifk4tPTRPgTaw7L6Wqy9W4XTeUX0xVtw8//LBxUlJSr4SEhKR+/fr1TE9PjwO48cYbO23cuDEuMTEx6dRTT+3+5768TojIV59/yphzh3DmgKN4+em/X064e+cO7hh3BZecdRrD/zGg+A2UAGcefyRPPnw/l5x1GvdOHFep+CozLPScTz/iglGX4XQ6cTVtyulnn88XH38IQHzX7vRMSsZZzsVF0bDQfr8fT2EB0TExLPpmHo1dTTjymH6Vil2VqykwK5w63UV0ggduxRpMQKnq9hRu1wC7g6hLtm7dGnXVVVd1feONNzauWbNmxZVXXrlr5MiR3fx+P88+++zm+Pj4/FWrVq348NMvdu8LPAa7PyuTtz+ey3uzv+bNl55hx/ZtANwzcTwXXXY1783+imlffMvy35Ywd/as4m1l7tvHu5/O45FnX6lUjGUNC11a2eChYtt16MT2bX8eVK4swy4YyZaNG7jojJM49oRBtGrTllee/S83TrqnUutRFXYEVqe7sBBWbemVEZ+a1h8oveFKqcMXBbyN23U07sz9dgdTFyxYsKBBQkJCXv/+/fMAxo0bt3fSpEmdNmzYUFwPXej1R2/LzCseGWzoeRcC1iiM7TvFs3XLJhq5XPy0aAF7d+8sXnduTg4b1/3d+njOiFHFw7iGsvr1G/Dfl94s/v6Y+59cMf5mNm/cwGv/ewKAa2667aCBbdRhGYHblYo7M+Rf1B+RCT4+Na0x8D7W401K1ZSuwDPAFXYHoiyb9+bG+/ym+LwWExtXPM/pcOLz+Ypf2vT2x18SGxd38EqA+g1Kf4P1ujWruOtGq/vF0X2PPWhUybbtO/Djd/OLv5c1LHTb9h3Y9ucWjkrpb5X9czNt21W9NfH3X9PZu2cXJ//jDMZecCb/fvoljDHcd+v44uFvVbV5ELdrDu7MX+0OpCyRWkX/DBAR7xJWIW8sbteFdgdRFwwaNChnzZo19X7++ec4gJdffrlp69atPV26dPE0adLEtz87Jya30FtuZ9r6DRrSb8CJTHn+qeJpO//afsBwrYdS3pDRlRkWevCw8/ho6lv4fD4y9+1jzqczOf3s88uNoTQej4enHnFz+33/BiAvLxcRcDikzE56qsqigNdwu0L6Jjmkg6uK+NS0c4DL7Y5D1Skv4Xb9gDuz/Ayhqqxdu3beV199df3ll1/exev1isvl8k2bNm2dw+HgiKNTTPfEJOcFpx1Ph07xPPP61DLX9fAzL/P4A3dzwWnHIyLUq9+Aeyc/Qeu27Q8rxsoMC33W8ItYvvQXzj4pBUEYc80NxWPI/9/CBdwzcTw52fsxxvBl2ifc/e/HGDSk9C5Fb774DGcPv5jmLVsBMP62u7jh8osAuPXuf5UdtL4bpKr6AHcQwk3BFRouNlzEp6Y1B5YD+r7pKvgi5s5FiY4tA+2OI0zNw5052O4gqlO4DBfrN0bW7tjfq8Drr2d3LOFIh4s9LPnA0bgzV9sdSGkirYr+eTS5K3v8A7frUruDqIt2ZhW00uSubBKHVVUfkj0yIybBx6emXUCYvi9YRYzHcbtcdgdRlxR4fdG7dfAoZa+BQEi+FyMiEnx8alo08Kjdcag6rzXwULmlVLXZlpHf0W9MRJzHVFh7BLerc/nFalekHBjXA93sDkIpYBxuVx+7g6gmfsAYY0Ky+jEzz9N4f76nqd1xqIrxGwADfp/dodSEhsBLdgdRUtj3oo9PTWsE3Gt3HEoFOIEXcLuOx50Z7j1Yt/n9/sydO3e2btWq1V4RCZn98RvDn3vyOhu/3+5Qwp4Hj+T7a+6f1hgo9MOuzHwceXuJydtZ/kLh6XTcriG4M+faHUiRsE/wWI8ptLQ7CKWCHAtchjUOQthKSUnJTk9Pvz4jI+PFrKwsFyE0sGiux984u9DE2B1HJMh1Fkbl+DNrdiN+L/V3/UqnVa/jMAe/tjeCPASETIIP68fk4lPT2mCNbhc2L/8PZfqYXLXaBPTEnVlgdyCHKz09vSHQjhBp0luzp7D+c4uzvjLGNLE7lkgwODp9aapj6lE1tgFjcHr2E1WYhdSNh+7Pw535sd1BQPjfwd+PJncVmjoD44CnyisY6lJSUrKBNXbHUWR4atq9gCb3arLXmZEfFx0xz6WHggdwuz4JhSa6kLgir4r41LSewNV2x6FUGe7C7apvdxCRJD41rQnWKJFKhaojCZFHtsM2wQMPE/41ECqytSJEn48NY7eid+8q9Llxu5x2BxGWCT4+Ne04oPQRHJQKLXfgdmkzUjWIT01rBtxsdxyRRkLzKchwlwjY/mbLsEzw6MtEVPhoCVxldxAR4lag3NHiVOXUkY5vdrgPt8vWIcvDLsEH2t5PszsOpSphQqi+qzpcxKem1cPqtKhUuOgKjLIzgLBL8MA1dgegVCX1AEof51NV1Bigmd1BKFVJtvbBCasEH5+aFoOO9a7Ck7YdH56b7A5AqSroj9vV166Nh1WCB84HWtgdhFJVMBi3K8nuIMJRfGrayUBvu+NQqorG27XhcEvw19odgFKH4Ua7AwhT19sdgFKH4WLcLlsGRQqbBB+fmtYNOMXuOJQ6DKNxu+rZHUQ4iU9Na4k+ElvTtBt9zaqHTZ3twibBY3Wu057IKpw1As62O4gwczGgg8rUIEEfhK8FY+3YaFgk+PjUtGhs+oGUqmaj7Q4gzITEKz+VOkz97OiDExYJHjgHaG13EEpVgzPsao8LN/Gpae0AHd1QRYoranuD4ZLg9dl3FSligBF2BxEmRqDNcipyDK/tDYZ8gg+MHvUPu+NQqhppNX3FaPW8iiRdcLt61uYGQz7BY/Wct31UHqWq0Ym4XS3tDiKUxaemdQCOtzsOparZmbW5sXBI8PreeRVpBBhidxAhbjhaPa8ijyb4ErR6XkWi0+0OIMQNtjuAukL0Mqo2nYzbVb+2NhbSCT4+Na09UKttFkrVkiE6wlzp4lPTooCT7I5DqRoQSy2+sC2kEzx6964iV2vgaLuDCFF9sV4KpFQkqrVqek3wStlHq+lLp6+kVpFME3yAdrBTkUz/f5fuVLsDUKoGdcXtSqiNDYVsgo9PTUsC2todh1I1qJ+2wx8oPjUtBn17nYp8tdLHJGQTPFo9ryKfC+hhdxAhJgVr9C1VS0SfRrTDkbWxkVBO8Fp9qeqCfnYHEGK042EtEx0t1g51PsHriU/VBfr//EC1cuJTymZ1N8HHp6a50PZ3VTdogj+QJnhVFzTF7epY0xsJyQQP9LI7AKVqSR/crlA9DmtVfGqaAEfYHYdStaTGL2ZD9cSiCV7VFfWAGr+SDxPxQGO7g1CqlmiCV6oO6GZ3ACFCq+dVXVJnE3yi3QEoVYs0wVt03AkbCEafk7PHUTW9gVBN8F3sDkCpWqQJ3tLe7gCUqkUJNd3/JlQTfCe7A1CqFnW3O4AQoQle1SVOoFlNbiDkEnx8aloTtKONqlv0Dt6iCV7VNS1qcuUhl+DRu3dV92his+jvoOqaOpfgO9sdgFK1rKndAdgt8Ay8vtxK1TUta3LloZjgW9kdgFK1LAq3q6HdQdisFRBldxB1kQ42Y6s6dwcfY3cAStmgRjvbhIHmdgdQV+lgM7aqcwk+2u4AlLJBXa+m1yFiVV1U56roNcGruqiuJ/g4uwNQygZ6B69UHdDE7gBspgle1UU12jSlCV6p0BCKx2Jt0gSv6qIazXeheFLRBK9U3aMJXtVFNdrDMRQfSwnFmCJeHAV5TWV/rN1xqDpLE7xNlvm7NPvel7QgRrwSjfWJwifR+BxReB1R4nc48Tmi8Dud+BwOjNOJ3+nA73RgouTAT7RY5/BoIFokJG8iQ0mdS/B6B19LnPi8Zzt+WDIu6pOCBPnzKBH62h2TqrP0WS2bLDddul/iuadGxkNw4PdH4y2MwueJxuuNweONEZ8nGo83Bq8v1tU/QnwAACAASURBVPrTGyMef+C7PwaPN1Y8/hg8/jg8JgaPPxaPiRGPicVrYik0MXhMjHiJwUssHonBQzReosUnMXgkGp9EWRcqjmjxOaPwiRO/w2ldpAQuUMwBFykOjFMwUVgXKdH8fZFSky8K0ASvqpMxJzl+W3ZT1Mx9x8jaJIcYTeoqFOTaHYCqfn4cjgJi4gqCa2hKS2khfHnnwO+LweOJwldoXaR4vTHi9Ubj9cTg9cXg8cXi8cWI1xuDxxe4IPHHiidwweL1x1JoYiVwoWJdpBCDxxQSvf7SGoxdE3wd0Vs2/DEx6sOtJzuWdosWX7Ld8ShVQo7dAShVGj8OZz6xTmrmImVfXUvw+t7EatJRdm69yfnRH2c5f2xXTwp7oMOShrJ8uwOwmSZ4VRfl1eTKQzHB77Y7gHDWlKy910fNXn6R8xuXi5xkER2hK0xk2h2AzbSKXtVFdS7Bb7M7gHBTn/ycMc4vl46N+iK6DfuOFuFEu2NSlVbXE7zewau6KKMmVx6KCX673QGEgyi8nvOci5Zc7/zU0022HSXCALtjUoelRg/0MKAJXtVFf9XkykMxwesd/CEZc6rj199vjJqVeZSs6+0Q08/uiFS12WV3ADbbg9VNSfvgqLpEE3xdd7T8sebmqA+3nej4PSFK/EfaHY+qdtm4MwvsDsJOGycPK4hPTdsJtLY7FqVqUZ1L8DsAP6H5Gt1aEy/bt9wc9dH6Mx0/tY8TTwKQYHdMqsbstDuAELEFTfCqbqlbCX7j5GHe+NS0XdTBA705mbvHRX2yYqRzQbPGknsE0NHumFStWG93ACFiM+jbFFWdUqN9zkIuwQdso44k+Abk7R/rnPPbZVFz41qRcZQIJ9kdk6p16+wOIERssTsApWqRB9hbkxsI1QS/HehjdxA1JRpv4QXOb5dc55zt6yJ/HS3CQLtjUrb6w+4AQsRmuwNQqhat3zh5WJ17Fz1EYEc7we8f7PjltwlRM/cfIRuSHUJ/u2NSIUPv4C2a4FVdsrymNxCqCX6r3QFUl76yeuXNUR/uHOBYkeAU/9F2x6NCkt7BW9bYHYBStajOJvildgdwOLrJ1k03R3208XTHzx1jxdsL6GV3TCqk6R28ZSVWu6QOOKXqgjqb4H+wO4DKas3eneOiPlk13Pld80aS1xvobHdMKiysx52p72EHNk4e5olPTVsF6GiHqi5YVtMbCMkEv3HysL/iU9M2AvE2h1KmhuRmXen8/LcxUfPqtyBTe8CrqvjJ7gBCzFI0wavI56EWmqRCMsEH/EAIJvgYPAUjnfN/vcaZRifZebQIJ9gdkwprP9sdQIhJB2pyiGylQsHajZOHeWp6I6Gc4H8ERtkdBFg94M9w/Lx0QtSsnCTZlCzCcXbHpCKG3sEfaLHdAShVC2qlGTqUE7zt7fDHyooVt0R9tLu/Y2VPp5iIfS5f2cYH/GJ3ECHmF6zfxWl3IErVoAW1sZFQTvBLgHwgrjY3miBbNtwS9eHmfzh+6Rwj3qTa3Laqc5ZrB7sDbZw8LDc+NW0xcKzdsShVg+p2gg/0qF0MNd/G3ZY9f02Imrn6POei1g2kIBHoUtPbVAr43u4AQtSXaIJXkWvTxsnDauWlTiGb4AN+oIYSfGOyM6+O+uz30c6vGjZj/5EitKmJ7ShVhjl2BxCivgTusTsIpWpIrdy9Q3gk+GoTR0Hexc5vllwd9ZmzPbu1B7yykwf4yu4gQtQPQA7QwO5AlKoBmuADDjvBO/D7hjl+XDI+6uP8RNlypAjHV0dgSh2m73Fn7rc7iFAUaJ5bAAy1OxalasA3tbWhkE7wgRfe/EoVRpYb6Fi27OaoD/f2lTVJDjEpNRCeUofjC7sDCHHz0ASvIs9vGycP21BbGwvpBB8wgwom+F6yad0tUR/8eapjSZdo8R1Rw3EpdTg+tzuAEKf9E1Qk+rA2NxYOCf4D4OFDzewgu7bd6Jy59mzn923rS2EC0K32QlOqSrbizgzrAZX+n707j7Op/h84/vrcO3fGLFz7NugKY4wlvraIImWbZF+yRUrRQgpD4tLittNGKmXJLwqJW0gikZ0iWcK1M9Y7+8xdzu+Pc2eMWZhhZs7cO5/n43EfmnPP8r7TnPs+nz2/2SyRB0xR1v2AfFCXfIlM8OnZLJFHTFHWv4B7UreVJPbqcD/r/sf060uUJK6BEFTWMERJyq3FWgfgJf4PeEPrICQpjxyyWSLzfQW59Ap9gvf4PpDkWgP06/Y+4bfaUInLDYWgtdZBSdJt+kbrALzEt8gEL/mOAi29AwhFUQr6mrm2YFLPGgP16/YKQYjWsUjSHfoXs13OkJhDpijrVuSkN5JvaGyzRBbo1NS6grzY7Rr0+tKjQlCgVRuSlE9k6T13FmkdgCTlgUMFndzBSxK8x3ytA5CkO6QgE1ZuLUFdfEaSvNlsLS7qTQn+WyBR6yAk6Q5sxmwvsDGwvsBmiTyPHFIoebdEYJ4WF/aeBG+2X0FWb0re7ROtA/BSM7UOQJLuwBKbJfKqFhf2ngSv+lDrACTpNp1GndNByiWbJXIdyD44ktfSpHoevC3Bm+37KMB5fCUpD32K2e7UOggvJh/uJW+012aJ3KrVxb0rwavkjS55m0TgM62D8HILgCtaByFJufSplhf3xgT/IyA7KkneZKGnD4l0m2yWyETgc63jkKRcOI1GnetSeV+CN9vdwAdahyFJOaQAM7QOwkd8DKRoHYQk5ZDFZonU9O/V+xK8ag7q05EkFXaLMdsPaB2EL7BZIk8jS/GSdzgLfKF1EN6Z4M32ZOB1rcOQpFtwAVO0DsLHvA4kaB2EJN3CWzZLZLLWQXhnglfNBY5pHYQk3cQ8zPbDWgfhSzwT33ykdRySdBPnUGuZNee9Cd5sdwDTtA5DkrKRgvz7zC9vAXatg5CkbLxts0QmaR0EeHOCVy0EDmkdhCRl4XPM9hNaB+GLPLOCvat1HJKUhSNoPDQuPe9O8Ga7CxirdRiSlEEsso9IfpsBXNA6CEnKYLTWPefT8+4ED2C2rwRWaR2GJKUzGbP9vNZB+DKbJTIOeEnrOCQpnVU2S+RPWgeRnvcneNULyJXmpMLhL2QnsAJhs0R+A6zTOg5JApKB0VoHkZFvJHh1Cc7pWochFXkKMMLTdCQVjJGoX66SpKX3bJbIo1oHkZFvJHjV28B/WgchFWlzMdv/1DqIosRmiTyCfLiXtHUaeFPrILLiOwlenfzmWa3DkIqsy8B4rYMooiyAnG9A0spTNktkvNZBZMV3EjyA2b4WDdfelYq0ZzHbL2sdRFHkmTHsadQmEkkqSF/YLJGrtQ4iO76V4FUvIZ/mpYL1f5jti7UOoiizWSI3AO9oHYdUpJwAxmgdxM34XoI32xOAAYBT61CkIuE0smmosJgE7NA6CKlIcAEDbZbIWK0DuRnfS/AAZvtOYKrWYUg+zw0MxGy/qnUgEtgskQ7gMdSJhiQpP023WSL/0DqIW/HNBK+aDmzWOgjJp72J2b5R6yCk6zxDlUZoHYfk0/7ESwqQvpvg1bHI/ZDTWUr5YwNecpMXNZ4JcBZoHYfkk84BvWyWSK9oAvbdBA9gtp8GeqKu7CVJeeU40Auz3Stu8iJqJPC31kFIPiUZ6GGzRJ7VOpCc8u0ED2C2bwae1zoMyWfEAV3lkLjCzTNXfRdArgkg5ZURNkvkVq2DyA3fT/AAZvsc5Ph46c4pwGDM9n1aByLdms0SeRLoChSKtbklr/aRzRL5ldZB5FbRSPCqF4BNWgchebWpmO3LtQ5CyjmbJXI78DhyEhzp9v1GIR/vnp2ik+DNdgfQDTigdSiSV/oGmKZ1EFLu2SyRSwCz1nFIXmkfXtSpLiOhKEXswdZsDAX+AEwaRyJ5j5VAD9mpzruZoqzzgMFaxyF5jf+A1jZLpNf24yg6JfhUZvsZ4GHk8DkpZ34D+sjk7hOeAJZpHYTkFU4DD3lzcoeiWIJPZTbegzqWuaTGkUiF13agHWZ7nNaBSHnDFGX1B34AOmkdi1RoXUItuR/UOpA7VfRK8KnM9r+AR1CHPUlSRv8AnWRy9y02S2QK0ANYq3UsUqEUA3TwheQORTnBQ+oY+YcBOZe4lN5e4EHM9itaByLlPZslMgl1+NwarWORCpUrQHubJXK31oHklaKd4AHM9q1AG2SbvKT6A2iD2R6tdSBS/vEk+W6AVetYpELhNGq1/DatA8lLMsEDmO1/A61Q1/eViq6fgfaY7XatA5HyX7qS/OdaxyJp6hBwn80S6XNDqItuJ7usmI1VgV+A2lqHIhW4b1FnqXNoHYhU8ExR1knAa1rHIRW4XUAnmyXyotaB5AdZgk/PbD+FWpIv9Ov8SnnqQ2CATO5Fl80S+TrqjHfyb6DoWA+09dXkDrIEnzWz0R+Yg3rDS74rGRiB2e51c0xL+cMUZX0IWAqU0DoWKV99CLzkrTPU5ZRM8DdjNr4MWAC91qFIee4c6ux0XrU6lJT/TFHWusD3QLjWsUh5LhEYbrNELtQ6kIIgE/ytmI0PobbPltE6FCnPbENN7l6zrrNUsExR1hDgM6C/1rFIecaGup77Hq0DKSgyweeE2XgXsAhoqXUo0h2bA7yA2Z6sdSBS4WeKsj4NzAQCtI5FuiO/AP1slsgiNbeFTPA5ZTbqgVeAVwE/jaORcu8S8CRm+wqtA5G8iynK2gj4DqihdSxSrqUAU4G3bJZIl9bBFDSZ4HPLbLwXWIi82b3JamAoZrtXLxwhaccUZTWidsySq9F5j7+AwTZL5N9aB6IVmeBvh9kYAnwEDNE4EunmEoFxmO0fax2I5BtMUdaOqG3z1bSORcqWC3gLmOpZe6DIkgn+TpiNnYGPgepahyJl8hswErPdJxaNkAoPTwc8CzASEBqHI93oEGqpfbvWgRQGMsHfKbMxEJgIjAP8NY5GgvPAS5jti7QORPJtpihrK+AL5MyXhUE86kPXu54piCVkgs87ZmMY8CnQTutQiigXam3KZMz2GK2DkYoGU5Q1ABiF+pBv1DicokhBHeE03maJPKN1MIWNTPB5zWzsA7yJ7IRXkDYAozHb/9I6EKloMkVZy6COsBmBrMkrKDuAUTZL5J9aB1JYyQSfH8xGP+AJ1Bu+isbR+LKtwKuY7eu0DkSSAExR1ruB6UAfrWPxYcdRh77Nt1kiZQK7CZng85PZWAz1iX4CUE7jaHzJXtTEvkrrQCQpK6Yoa3NgCtBJ61h8yEHUh6dFvj6HfF6RCb4gqMPqngWeQ5bo78Qe1OaPpZjt8g9XKvRMUdb6wMvAY4BB43C81d/AG8D3NkukW+tgvIlM8AVJrbrvBYwGmmscjbdQACvwPmb7b1oHI0m3wxRlrYJ63w8HimscjrfYBLwLrJRV8bdHJnitqDPijQZ6Iqe+zcpVYC4wC7P9qNbBSFJe8MyI9wTqJFkNtI2mUIoBFgCzbJbIf7QOxtvJBK81s7EC0A8YCDTROBqtOYC1qMNelmO2J2ocjyTlG1OUtSHwODCAot1HRwE2oj7QL7VZIhM0jsdnyARfmJiNtVFv9gHA3RpHU1AUYDNqUv8Os/2SxvFIUoEyRVn9UDvjPe75N0jbiAqEG9gCLAeW2SyRNm3D8U0ywRdWZmMzoDPqDd8E0GkbUJ5KRH1iX4NaUj+hcTySVCiYoqzFgLao935nfOtBPwlYB/wA/GizRF7UOB6fJxO8NzAbywDtUZN9e6CCtgHdlv2oCX0NsAmzXU4nKUm3YIqyhqMm+o5ACyBE24hyJQXYBfzhea23WSLjtA2paJEJ3huZjTWAZulejYBATWO60UVgJ+pMU+rLbL+gbUiS5N1MUVY9UB9oiXrfNwbqAHot40rnArCb6wl9u5wXXlsywfsCdfhdPdReubU9r1qoq9zl15AcN3AaOAYc9fx7CNgpq9wlqWCYoqxBqEm/Jmp1fo10r0r5cMlk1Pv+X9SJZ/5N/W+bJfJqPlxPugMywfs6s7E0cBdQFiidxSt9yV+k+9cNXEMdrnYVuJLuv88ANsz25AL4BJIk3QZP8q8KlAJKZvEKRl2kye35N/0rCbUmLtrzughE2yyRciEnLyITvCRJkiT5IF/qmS1JkiRJkodM8JIkSZLkg2SClyRJkiQfJBO8JEmSJPkgmeAlSZIkyQfJBC9JkiRJPkgmeEmSJEnyQTLBS5IkSZIPkglekiRJknyQTPCSJEmS5INkgpckSZIkHyQTvCRJkiT5IJngJUmSJMkHyQQvSZIkST5IJnhJkiRJ8kEywUuSJEmSD5IJXpIkSZJ8kEzwkiRJkuSDZIKXJEmSJB8kE7wkSZIk+SCZ4CVJkiTJB8kEL0mSJEk+SCZ4SZIkSfJBMsFLkiRJkg+SCV6SJEmSfJBM8JIkSZLkg2SClyRJkiQfJBO8JElSISWEaCqE2CKEiBdCKEKIhkKIjkKIvUKIJM+2klrHKRVOfloHIBUNQoiJwAFFUX7QOhZJ8gZCCAPwHZAEvAgkAKeA34F/gGeBZCBeCNEfKK8oygyNYtUBg4EeQCOgNHAc+BZ4V1GUJC3iKuqEoihaxyAVAUKIOOB7RVGGaB2LJHkDIUQ48C/wlKIoX3i2dQR+Bh5WFGVdun1XAfUURTFpFGsIEAtsBVYB0UAL4HHUB5IHFZlsCpwswUu55nla95dP5ZKUr8p7/r12i22FQQpwn6IoW9Jt+1wIYQOmAu2AdVkdKOUf2QZfCAgh2gghdnra1I4KIZ4WQpiFEEqG/QYKIXYJIRKFEFeEEN8KIapm2GeDEGK/ECJCCPGbECJBCHFGCDEui+sGCCGmCiH+E0IkCyFOCSHeFkIEZNhPEUJ8LIQYIIT4B7VasKPnvZc9bYSXPXHtEkL0yng8EAw87jmXIoT4Ot37oUKIuUKIC544/hFCPHGHv1ZJ8lqe+2Oj58fvPPfMBmCeZ9uO1PvIsz0SuCvd/WXznKeN5+c+Qogpnu+CWCHE90IIo+c7YIYQIloIESeE+CqL+3+oEGK9Z59kIcQBIcSI9PsoipKSIbmnWu75t05e/F6k3JEleI0JIRoBq4FzwBRAD0wGLmbY7xXgNWAJ8AVQDnge+F0I0UhRlPRP9KU851zm2b8X8JYQYp+iKD97zqcDfgRaAXNQqwLro7b1hQHdMoT6INAH+Bi4BNg820d5zvMN4A/0Q/1CekRRFKtnn0GemLd7rgVw1BNHBdRqPcVz7otAJ+BLIUQJrdoUJUljnwFngInAh8AO4AJwCBiO+h1xHPU+CgGMQBXU+xcgLsP5JgCJgAWoifrd4QDcqN8XZuBeYIjnvNPSHTsCtc3/R8AJdAE+FULoFEX55Bafo6Ln30s5+dBSHlMURb40fKHeNPFA5XTbaqLefKnNVneh3lgTMxxbz7PfxHTbNqAmy0HptvmjPkB8n27bQMAFtMpwzqc9x7dMt03x7BuRRfyBGX42APuAXzNsjwO+zuL4L4CzQJkM2/8PtRoyMOMx8iVfReEFtPHce73SbRvi2dYkw76rANtNzrEPMKTbvgg1uf+UYf8tGc+T1T2IWoA4moPP8AtgB0pq/fssii9ZRa8hIYQeeAj4QVGUs6nbFUX5D7UjTaoeqM0pS4QQZVNfwHngCNA2w6njgIXpzpeCWnq+O90+vVFL7QcznHO95/2M59yoKMqBjJ9BUZTEdJ+nFGpJYhPwvxx8fgH0BFZ6fkwfxxrPuW55HkmSbmm+oiiOdD9vAwQwN8N+24CqQoi02t0M97jRc39uBO4WQhizu6Bn5MxDQJRyYw2jVEBkFb22ygOBwH9ZvJd+Wy3Um/FINudxZPj5tOJ5fE7nKtAgwznrkKEpIENs6R3PaichxCPAJKAhkL7tLic9ZssBJVGrHIfnMA5JknLvZIaf7Z5/T2WxXYf6cH0ZQAhxH2pHuRZAUIb9jenOlUYI0Rd4HfhSUZRZdxS5dNtkgvcOOtSE2Qm1qjyjjO1tWe0D6kNC+nPuA8Zks2/GGz8x4w5CiNaoTQy/AyNRmwEcwFCgfzbnTS+1Bmkh1zsPZfR3Ds4jSdLNZfedcNPvCiFEDeBX4CDqd8Up1B7znVHb+zPVAgshHgbmA1bgmTuKWrojMsFrKxp1EouaWbyXfttR1BvuuKIoh/Po2keBe1Dbym93fGpP1Pg7KIqSnLpRCDE0i32zusZF1LGzeiXdmF5JknItv8aYd0GtmXtUUZS0WgAhRMYmvNTtzVF7zu8E+iiK4synuKQckG3wGlIUxYU6NrSbEKJy6nYhRE3U0nqqZahP2lM87dak21cIIcrcxuWXAKHAUxnfEEIECiGCc3AOF+oXiz7dsSYy98AHtSPhDVNqej7/UqCnEKJeFnGUy0EMkiSp91e27eF3ILWEn/a942l3z/QQL4Sog1pqtwGPpG+7l7QhS/DaMwPtgc1CiFmoyfI5YD9quzaKohwVQkwCpgMmIcQPqCXf6kB31KFn7+byugtQh73N9jyNb/ZcO9yzvQPqU/jNWFGr7VYLIRahtpc/i9p/oEGGfXcBDwkhxqD2mj+uKMo2IAq1Q982IcTnwAHUaS7/h9pBp3QuP5ckFUW7gL5CiPdRh9TFKYqyMg/Ouxa1Sn6lEOIz1CF5T6HWPlZK3UkIURy1Y2wp4B0gMkNZ5KiiKH/mQTxSLsgErzFFUXYJITqhJujXUNu4JqN2gAtPt59FCHEYtd1rimfzKdQb8MfbuK5bCNHNc77BqA8KCcAxYCZwy6YARVHWCyGGoSbpGagd8cYDJjIn+DGoDyKvo3YsnAdsUxTlghCimecz90Bty7+MOu52fG4/lyQVUZ+iFgiGot7TJ1BHp9wRRVEOeSaueh31O+o8MAu1eS19D/wyQOqkW5YsTjUPkAm+gMm56AspTym9rqIotbSORZIkSfI+sg2+EBBCBGb4uRZqL9UNmgQkSZIkeT1Zgi8EhBDngK9Rq8fvQp0aMgBopChKdmPfJUmSJClbsg2+cFgNPIY6b3MyalvVRJncJUmSpNslS/CSJEmS5INkG7wkSZIk+SCZ4CVJkiTJB8kEL0mSJEk+SCZ4SZIkSfJBMsFLkiRJkg+SCV6SJEmSfJBM8JIkSZLkg3I10c2uXbtCgMrIBwPpRm7gbOPGjeO0DkTKe/K+lwoB+R1zG3I80c2uXbvu1el0s3U6nZF0awNLEqC43W672+1+pnHjxlu1DkbKO/K+lwoJ+R1zG3KU4Hft2hWi0+n+KFmyZIXy5ctfEULI6e98kKIoZFjDOafHiejo6NLXrl274Ha7W8mnbN8g73vv53K7hdOFwel2G5xuxc/lVnSAUBSEgiL0iqKUFPHKVYIFQgcCt0CgE7j1OuE06HQOg144dDpt/9/L75jbk9Mq+so6nc5Yvnz5K8HBwYn5GpGUJ1xuRZfkcBVLcroCUpzuAJd6c9/4UhS9241eQREAFQxJ8RVc54IBBQQIoYBwo9M70RlS0Ps50Bkc6A0p6P3T/evvKF++/JWYmBij2+2uTA7Wkpe8grzvCzmXW9ElpDiDElJcQSlOd4DTrRicLrfB6VYMLrdicCvKTZpVBEEoKRV08c5YJSTAoaBXt6fmcgW1Zhx0QrgMepHip9c5DDpdikEvUgx+upQAP11SsL9fQkE8AMjvmNzLaYLXAUI+wRc+brci4lOcwfEpruBkh6tYitNdLMXlLuZyK3eykJAABRRFADpcLj9cKcVwZH+AzqV3+CVfdZh2vP40K3dYgR2Y7bF3EIOkPXnfFyIut6KLT3YGJTpcQYkpruAkpysoxekulhfnVm7R/OJWFH2yUwlMdroDM74nEIq/ny4p0F8fH2TQxwUF6OMDDfqk26kNvBnP36H6nSTliFxNzsskOVwB8cnO4IQUV0iiwxWc7HAHppbAtSQUp0HnSjYEJJ4fA4wB3JiNB4Htntc24G/MdqeWcUqSt3C63bqYRKcxNslhTExxhaS43AH5dCmhcPvZWEERyU5XYLLTFXgNygLohHAXM+gSihn08SEBfrElihlitK7mL4puO8GboqyN8zKQ9GyWyF35de6c2rFjR7Fu3brVOnPmzL6CuN6gQYOq7dixIyT15+PHjxd79dVXT0+c+MrFL+ctqPTOW9PL6/R+OofDIR7sEMlz4yZl2V7+6phn+XffXnQ6HX5+BkZNmELzVg8AsG/PLt6aEkVKSjIpycl07dOfoSNGZTrH8ZNn6DdyAnHxCQzo3omJLwwD4N8jxxj/xof8+PWMnHwkHRDheQ3xbEvCbNwMLAWWY7afz8WvSCoE8uu+Lwz3/K2Eh4dH/PnnnwdLlSrlzq9rJDlc/vZER8nYJGfJxBRXSG4f3vfv3c07UyeQEB+PEIKXJr9B8/vuB+DE8aO8+crLXLl0EafLxdOjxtLj0W4AZOyKtWn9Wj5+5w0Utxun08mQZ17g0d6PAXD50kUmjR7B6RPHMfj788ob79L43vtuON6tKLodO3aGTB33QojD4ajwxIhRSv9Bg6+VKOZ3bdOvq11LFi8uuWjRohO3+3uSckaW4AuJBQsWnEz976PHTwTWrVO7zkNd+xoPnIsJrdeirW7J2kfQ6XQ4UlJ4vEcnIho0ol2nRzKdZ+yUNylhNALw7/6/Gd6vKxv/PopOp+O1qNGMfGkCbdp3xn71Kl3bNuP+dh2oERZ+wzk++XoJzz7ehwE9OhHRphfPP9GPkOAgRk95l9mWV+7kYxYD2nleH2M2bkFN9ssw20/e9EhJ0ojD4cBgMHDw4MEDeX1uRVGIS3YGxyQ6S8YlO4xZVYHn5lwvPjWI197/hHtbt8F27D+efqwbKzbsoFhgIJPHjKRrnwH0eGwwVy5fon9kW1o2bYYp1O+GKnpFUZj4wtN8+d1KwurU48ypk3Rr24x2nR4hOKQ4M6dPpcH/mjBr4ffs37ubF58axE9b9mIwGG6IZ+6nMxg/1UKdBg3p9fB9okvvx0pdvBpT6rU33+LzBYtjomOTypUM9L/m76e7sIReYgAAIABJREFUSeOfdCe8ui1j4cKFJe++++66tWvXjhgxYkRoqVKl7jl06JA/wPDhw6vUq1evTnh4eESTJk1q//XXXwEAcXFxIjIy8u4aNWrUrV27dsR9991XK/V8Y8aMqXzXXXfVq1u3bp0FCxaUTn+tpUuXlmjcuHHtunXr1qlfv36dlStXFgdo2bJlra+++qpU6n6rVq0qXqdOnYjcfha3WxGX45JL/xcdV+ujz7+KaPlAOxFUqlwJt6LogkOKo9Op/6uSk5NwpCRn29s9NbkDxMXG3PimEMTGqNsSE+MxGPwxlixFRgaDHwmJSTgcTtxuNzqdjtnzv6f9/S2oXi00tx8tOzqgFfABcAKzcTtm43jMxpp5dQHJ96xbty64cePGtWvXrh0RFhYWsXDhwpIAv//+e1CjRo3Cw8LCIurXr19n7dq1wQD9+vW7a/LkyRVSjz948KB/2bJl70lOThYrVqwo3rBhw/A6depE1KxZs+4HH3xQNnW/nj17mnr37m1q0qRJ7bCwsLoAQojGly5d0kP23y+p+0VFRVWsX79+ndDQ0PozZ84sk/re7t27i7Vq1apWWO3adcPC69wzxfJBw+OX4sMPHT9Z8YWnHg/s/0g7ej7Uko/ffj3Xv5trV69w9col7m3dBgDT3TUpXsLIHxvWAXDowD+0avswAKXLlCWsTj1W/bhMD9e71aX7DMTa7QDEx8VgLFkaf3/1I65d9QO9Bw4FoF7D/1GuQkV2bd2cKR4/Pz+SEhNJSU5Gr1P77836wMKAYc/gF1S8xHl7UrWD52MaHLkQG34hJqm80+XW5/pDSzfltSX4M2fO+D333HOm33777WCjRo2SZs6cWebatWtpn8dsNp+vXLnyaYA5c+aUeu6556pt2rTpyLJly4x2u11/9OjRfwAuXLigB/j222+NP/74Y6k9e/YcKFmypLt79+7VU8914MAB/9dee63y+vXrD5cuXdq9f//+gLZt29Y+efLkvsGDB1+eP39+maFDh14FmDt3bpmBAwdeyunniEtyBl9JSCkbk+go5VYUPcAPi79hzKRpN+y3d+c2Xot6kZO2Y/QZ+ARtO3TO9pwzppv5ZdUKYuzXeG/O/LSHg2nvfcLoYf35+J3XuXr5Mq9aPqBs+QqZjn/hiX4MeXEKny1cysvPDMIeE8f31nWs/b9Pc/qxbkdTz8uC2bgX+AxYgNken58XlbzHhQsX9H379q35zTffHO3YsWOcy+Xi0qVL+qSkJNG3b98aH3/88YmePXvGrFmzJqR///41jx49um/YsGGXRo4caZo2bdoFgM8++6xs9+7dLwcEBCgtW7ZM2Llz50E/Pz8uXLigb9SoUcSjjz5qr1GjhgPg77//Dtq6dWuWVfLZfb+kvh8QEKDs27fv3z179hRr1apVnZEjR15WFIXuPXqGPT/2FWf7rr2KAVy9chmASS+O5MnnxtCkxX04nU6eH9KPtat+oP0j3XL8+ylVugzlyldgzcrldOjSnf17d2M79h9nT6mVYxH178G6fAlDR4zi9Akbf+3aTtXQKpAhvwshePvTuYwZPpjAoCBi7HbenzMfg78/165ewel03PC9EVq1GufOnM4Uz9Ojx/Fa1IskJibw4ivTOPjPPs6cPMGLE6fesF+iwxWc6HAFR8cmh5Yo5ne1TEhAdEiAX0KOP7iULa9N8Bs2bAiuXbt2QqNGjZIAnnvuuctjx469K/X9H3/8scTs2bPLx8fH691uN3a73Q+gSZMmCePHjy82cODAag888EBsr1697ADr1q0r3rVr1yulS5d2A4wYMeLisGHDQjznMp44cSKgZcuWaXXZQgj+++8//4EDB16dMGFC1RMnThhKlizpWr9+fclPP/301M1id7sVcSk+ueyV+JTyGXvB7t62hYS4OFo/2P6GYxo2ac7SdVu4cvkSLw0fzO5tWzK1e6UaPcHM6Almtm7awIw3pjBv+WoM/v7M/eQDXhg/mc7de3P6hI0nekcS0aBhpir6ShXKsWbR9WTee/g43ps8ht8272TWgu8I8Pdn+oTnuKtK5Zt9zDvREJgFTMds/Br4BLP9v/y6mOQdfvvtt5Dq1asndezYMQ5Ar9dToUIF1/bt2wN1Oh09e/aMAejQoUNcmTJlHFu3bg3q0KFDnNPpZOPGjUGtW7dOWLJkSZkffvjhCMCFCxf8BgwYYDp+/HgxvV6vXLt2zW/Pnj2BqQm+a9euV7Nrb8/u+yXVsGHDLgM0atQoSa/XK3sPHgs9e/Fq2RSHw699115pddmlSpchISGe7Zs3cuVSdNrxCfHx2I7m/k9+xpffMOPNqXz5yQfUCAunUdN70fupob32wSzee20SfTq0plJoVZrd9wB+fpkLzU6nk88/fJf358yn8b33sX/vbkYN68/3v2zO1TwZd9eqzVdLfwLA5XLxzIAevDFjNj//8D2//PQjwSHFGTv5DUqULAmAoig6e6KjjD3RUaaYQZ9QJtj/Qqlg/6s6OYrjtnltgr+ZI0eO+I8fP77ali1b/q1bt27ytm3bAh966KHaABERESkHDx78Z9WqVcV/+eWXElOmTKny119/ZWpbS/+HrCgKrVq1ilm5cuXxrK7XuXPnq59//nnpcuXKOVu0aBFTsWJFV8Z9Jk6cWHHZsmWlEXq/FydN07V4oF2W1VHLv11Il9790Ouzrq0qXaYsrR58mLXWFdkm+FT3tm7D9FfHceTgASpVqcr6NVbe/nQuAFXuMtHgf03Zu3NbpgSf3lLrr9QwVaFhvdrUeaAH260L2PnXASa/M5t5M6dle1weKQmMBkZhNq4C3sJsz1wXKEkZpL9/+/fvf/nzzz8vGxMTc7VUqVLOpk2bJgEMHz78rvbt29tXr159VKfTERERUScxMTGt2TIkJCTTfQw3/35JFRQUpCSmuIpFxyZV0PsZ9Jfikiu6sptUzLN9wYpfCCh281FvLz39OKdsxwCY8+0KSpa6oSWR2hH1mbXw+7Sfu7VtTk3P/R1atRrvz5mf9t6Igb2o2fr+TEEd+mcf0RfOp32/1Gv4PypUrMzB/X/T4v626PV+XIq+kFaKP3PqJJXUmoBsLfxiFg9HdqW40cicD9/lu7V/sGrpYhZ+OYuRL03ItH+SwxV05lpi9QsxyVVKB/tHlw3xv3jTC0hZ8to2+DZt2sQfOnQoKLXta9asWWUcDocAuHr1qt7Pz0+pVq2aw+12M2PGjPKpxx09etQghGDAgAH22bNnn1YUhWPHjvk//PDDsT/++GPpq1ev6txuN7Nnz05rj+vSpUvM5s2bS2zbti2tA8xvv/0WlPrfTz755KVFixaVXbhwYdmhQ4dmqp5Pdrj8R7w8yfD9r9sClvyy2ZBdco+LjeGXn36kW9+BN2w//t9h3G61IBEfF8umX9cSVqdupuMdDgcnjx9L+3nfnl1cuXSRKtVMlDCWJDAwiG2bfwfUqsF9e3ZSs3adbH/H1+yxzPxyEVNeHA5AQmISOp0OnU5HXEKB1qAJoAvwB2bjH5iNj2A2aj40UCpY7dq1iztx4kTA6tWrQ0AtFV64cEHfoEGDJLfbzfLly0sA/PLLL8GXLl0y3HvvvQkATz311GWr1Vpq9uzZ5QYNGpR2f9rtdr3JZErW6XT8/PPPIYcOHQrK+so3utn3S6oz9qSq/0XH1rUnOtK+R0w1alEsMIiff7iegK9euUxQcAhNW7Zm7qfXR6dEnz/HhXNnMl37vc/msWTNJpas2ZQpuQNcvHB9YMrSRfMIDAyimacX/eWL0WnfI5s3/MqxIwfp2r13phqKipVDuRR9gWNHDgFw8vgxTp04jqmG2j2mfWRXvlv4FaD22o8+f+6mhY3TJ0+wddMGeg8citPhwOl0IoRAp9OREH/zFjin222Ijk0KPXg+tsHFuOTyihfnLC14bQk+NDTU+eGHH9q6d+9e09/fX3nggQdigoKC3GXKlHHVrl075dFHH70SHh5et1SpUs7OnTtfSz1u165dgZMnT66iKAoul0v06tXrSvPmzRObN2+euG3btuCGDRtGhISEuNq1a2ffvn07APXq1UueO3fusaeffvquxMREncPhEHXr1k1o27btcYC2bdsm6PV6Tpw4EdCjR4+0nm0pTrfhnD2xckyis0xOhrus/nEZEfXv4a7qNW7YvmblctasXI6fnx8ul4uHI7vS47HBAPzz1x4+fe9NPpn/HU6ng1fHjCA2JgY/Pz8Cg4J497N5aVVg78z6ig/emIzL6cTpdDJg2Ajuadws23jGvzET85inCQxUSxWTRj1Jk04D8DcY+PK9KTn9X5XX7gNWAvswG8ditq/RKhCpYJUrV8717bffHh07dmzVF154QafT6Zg8efKZ/v372xcvXnx01KhR1caPH18lICBA+eabb44ajUY3gMlkctxzzz3xv/76a8l58+alDc16/fXXz4wePbqaxWKpXLdu3YQGDRrkqL9Hs2bNErP6fnG63PrzMUmVAGKTXGVKZBi17ufnx8wvv2H6q+P54uP30el09Bk8jN4Dh/Lmh3N4d9or9GjXAiEEgUHBvGp5nwqVctepdemieViXfweKQvWaYXzwxYK02oyN61Yz95MZ6PR6ylWoyMfzllAsMBBEnLJh7U9s+GU15nc+pEy58ky2fMDYEUPR6XS43W4mvPY2lUKrAjB6opmJo56hS+vG+Pn78+aHn2XqQZ/e21OiGGd+EyEExUsY6dytF70evo/AoOC0GsVbcSuK7lqCo9zlBJd79o6rj+34zvqazRIp59S4hZzORR/u5+e3ulatWnFBQUFJBRBXjly9elWX2ka2YMGCklOmTAk9duzYP1rH5XIrugsxSRWvxKdUuPlUkYVLuqlqcy3JqXD8zEWqb36JYnE37YKQ16zAGMx2OXVlHius931h43IruujYpPKX41IqpnaU9RZBuFNM+ouOA64Kt3XfFyTFmUL02dOYf4vmTKzrEBBls0T+oHVchZnXluAB3nrrrfLLly8v7Xa7RUhIiGv+/PlZtpEXFEVRuBSXUjY6Nin0DqeKlXIuEmiP2fgRMA2zZ2yPJOUzRVG4GJdc7lJsciWnW8m+CCvlh9rAclOUdRMw1maJ3KZ1QIWRVychi8Vy3mKxFIrZ0OyJjuLn7InV8mpuaClXDKjT4w7CbJwEfIHZnm+zjUlSXJIz+PS1BJNv3O9e3Z2lNbDVFGX9DjXRy9nx0vGa6uPCyuFy+9kux5tOXI4P842b3auVQx0/vwuz8QGtg5F8j1tRxJmrCaHHL8WF+8r9rmSe58Yb9Qb2maKsw7QOpDCRCf4OXI5LLn34QmzdmERHmVvvLRWghsAGzMZ5mI3FtQ5G8g1xSc7gwxdiIy7Hp1T0hYyYxqsL8DcoDnxhirKuNEVZK2odTGEgE/xtSHG6/Y5djKtx5lpiddnWXqgNBnZjNjbROhDJe/liqd3HPQLsN0VZe2sdiNZkgs+lawkpxiPRsXXjkp0ltY5FypGawBbMxnFy7LyUWz5bar+BT94WZYAlpijrIlOUNfOCG0XE7Zc+zcZ8Wy4Ws73QLR2pKApnryWFXo5PllU/3scAvAU8hNk4WC5Tewfy674vZPe8oiictydVuhSXXNl3E3uR8BhwvynKOsxmiSxyc2b4ZAn+0KFD/m+//Xa59NtCQ0Prb9my5baWYkxxug3/XYyrndvkfuTffxjaszNd2zSjR7sWTH7pOZISE9Pej7l2jQnPP0WX+5vQvV0LZkw3Z3uunX9upn/kg3Rv14LuD97LX7vUSXh+XrGUPh1a06NdC3q0a8G8zz7O9hzTokbT86GWPNn3UWJj1NFkiqIwclAvTtk0HWFYUB4G/sZszH6lHqlQS11BMjw8PGL79u23vbRqRqtWrSr+/ffflwB1XLvtcnyNi7lI7n/v2Unv9q3ocn8Tnuz7KBfOnc1yv/17dzO4W3ua16rM6GEDbnjv159X0evh++jToTXdH7yXj956jazmKXE4HIweNoDe7Vvx4lODcDrV+V6Sk5IY2rMzMdeuZTrmZhTfLMGnFwqsNkVZp5qirD7/YdPzyQR/5MiRgLlz55a79Z63Zk90FD8SHRuRmOIKSb2Rcsq/WDEmvP42KzZs57u1f5CYkMBXs2amvT/55ecIr9uAlb/vZPmvfzJw2IgszxN9/hyvjhnB6zNmsfzXP1n880aq11Snvq5YOZRPF3zPsl//ZN7y1Xy3YC47/vwj0zmOHDzAyePHWLpuC01atGLVssUALPu/+TRt2ZqqpuqZjvFR5YBVmI0zMBsDbrm3VKjMmTOn3Pjx488dPHjwQLNmzRJvfcStORwO1q9fX/ynn34yJjtc/v9Fx4XHJuW8Cc7tdjPx+eGMNU9n5e87ad32Yd6ZOjHLfctVqMDYKdN5ecobmd67t/UDadPQLln9O39u2sD61dZM+23Z+CslSpbiu7V/ULyEkc2e5WDnzHyHfkOeSpu5MheKSiXFZOD/TFHWPHswLOy8OsEvXbq0RERERJ2wsLCIpk2b1t61a1cxgOeff76azWYrFh4eHvHggw+mrS++ZMmSUg0bNgwPDQ2tP27cuEqp20+ePOnXuXPnu+vXr18nLCws4oUXXqgMcN6eVCEirEbYu69P9uv/SDtefTHrBJydu6rXIKxOPUBd+arePY3Slm48efwYB/7ew6Dhz6btn9XSrQBL5n9Jp669uLuWmtT9AwLS1n1v1PTetOOKlzBiqlkr7RrpGQwGHCnJuN1uEhPUteAvXjjPzyuWMuipZzPt7+MEMApYh9lYZNvnvM2QIUOq7ty5M2TatGmhjRo1CofsvwNWrVpVPDw8PCL12B07dhQLDQ2tD2oNX/HixRuOGDEiNCIios706dPLz58/v9zyH34oc0/DhvVnvjs9VwngwN970fv50axlawB6DRzCxnWrSU7KPPlfhUqh1G/UOG1t9fSCQ4qnLe2cnJyEIyU5y9Xb/PwMJCWqa0EkJSZgMPhz+N/9HD96hA5duucm9KKoL7ChqPSy99oEf+bMGb9hw4bd/fXXX9sOHz584IknnrjYp0+fGm63m48++uikyWRKOnjw4IH169enrbl47do1/d69ew/u3Lnz31mzZlU4fvy4AaB///7Vn3322eh9+/b9+88//xzYs2dP8IdzvqoVHZtUBcB+9SrfrFzH9I8+v+14ExLiWfbtAtq0V2uHjx05SIVKobw+cQz9Orfh6f49+Hf/31kee/TIIZKTkhj+WDf6dGjN9FfHkZCQedrso4cP8veuHdzbOvMQcFONWjRt0Zp+nR7gzMkTRPbowztTJzLmlWn4+RXZgQCtgE2YjTdfCksqFL7++utT9erVS7BYLKf27Nlz8GbfAbcSFxenr1u3btKBAwf+nTx5cvRjg4fER3bvq1+yZhPPjB6Xq7jOnz2dNk87qIk6OKT4DQu/5NTendvo+VBL2jYKo1nL+2nbIXNrUov72xIcUpze7VsRUqIEze67n3enTWL81Om5vl4R1QzYYYqyNtQ6kPzmtQl+48aNwWFhYYmp1XQjRoy4Eh0dbUhN2lkZNGjQFYBKlSo5q1SpknL48OGAmJgY3datW0u89NJL1cLDwyPq168fceLU6ZDDR46WSD3u0d6P5Wod5IwcKSmMG/kELe5vS7tOjwDgdLnYv3cXHR/tybc/bWDQUyN4fkg/HA5HpuNdTie7tm/h3Vlf882q9cTYrzHrPcsN+1w4d4bRwwYwaXr2C1Q8N24SS9Zs4t3ZX7P19w1UrBxK5arVeHXMs4wZPphly5YVxUxfF/gTszHz8nxSoXY73wGp/Pz8lBEjRlx2K4o4eSWhmhM/Y2Foim7YpDlL121hzbb9HNi3l93btmTaR6fTMeXtmXy39g8mW2bw7def07ZDZ5xOF1HPPcmY4YPTVo3MmULwwQteFeAPU5S1m9aB5Kci9YUeGBiY9miv1+sVh8ORttjO7t27/zUEFNMfvxRfK8nhuuHBJyg4JMvzHT18kAnPPwWoN+bEN97NtI/D4WDsyCcoV74i46deT8qVKlehfMVKadV6rdo+jNORwrnTp6hW/e4bzlExtAq169ZPa1vr1LUnX37yQdr70efPMfyx7jz1wsu0f+TWf69xsTHM++wjZn2zlC8//oAm995HZI8+9Gvf0jCkfaO01eOKkCqoJfmumO2btA5GunMGg0FJX5JPv847QLFixdwIne7YxfgaCSnOEplOkE6M3c6TfdQH88pV72LGFwtveL9i5SqcO3N9gaX4uFjiYmMoV+H2a4FLlylLqwcfZq11xU2XYj17+iSb1v/CrIXfM+nFEfQcMISI+vcwsGt7lv/6Z46udet1Ln1WMLDMFGWdYLNEvqV1MPnBa0vwbdq0iT98+HDgjh07igHMmTOnVIUKFRzVq1d3lCxZ0hUbG5ujVZ2MRqO7WbNmMRNfmVTlv+i48CSHKyi7tZgzqhEWntYpJqvk7nQ6Gf/sMIwlSzH5rRk31AJENGhIcEhxDv+7H1DXblcUhYqVM5e+O3frxY4tm0hJTgbgj9/WUdvTtn/xwnmGP9aNoSNG8Wjvx3LykZk5fSpPjx5HYGAQiQkJCCEQQuB0OkRKFjUIRUQpYC1mo2zE9BI3+w6oXbt28tmzZwPOnj3rB/DVV19lmm3y2MW4WqnJPTikOLExMRl3AaCE0Zh2n2dM7qDey06Hg+1b1GfD7xd+zQMPdSSgWO4elI//dzhtvfb4uFg2/bqWsDo3r1h6e8oExk55A51Op97LCIROR1IWTXhSlgRgMUVZP9Q6kPxwB+PgtR23WrlyZecXX3xx7PHHH6/udDqF0Wh0LV68+KhOp6N58+YJYWFhibVq1apbtWrV5PTt8FlZsGjxmVFjxtTu0qa57k7WYs5ozcpl/PrzSsLq1KVvx/uB6yV9IQSvfzCLqeNGk5yUiL9/AO99Nh//ALXzzbODezPypYnUvacRDZs0p037TvTt9AA6nY4aYeFMmq6W4D99bzrnzpxm0dzZLJo7G4D+TzxDt74Dsoxpz46tJCUl0eL+tgD0e/xJxj/3JF/NmkmPHj0dxhLF/e/oQ3u3YsD3mI3PYrbP1jqYQqkQjVe/2XeAyWRyjBw58nzTpk3rlC1b1vHQQw+lrTLocit6IXT6RIcrrWruwY6PsGrZYvp0aM2Dnbrkqh1ep9Px5oef8VrUiyQnJ1O+QkXemHn9zyf9vWw7eoSn+nUjKTGB5KQkHm5alyefe5G+jz/JmpXLWbNyOX5+frhcLh6O7EqPxwZne92fln9HWEQ9atauA8ATI0czbfwoHA4HT40am4vfpCgqvehv5nlTlFUHPG+zRPrM78Or14PPC0kOV8Cxi/G1nW53kV/u0UvXg88vZsz2qVoHoSVfvO+dLrf+6MX42slOV5EZKnUzQbhTqhiuJR12lL5pM0VhkGE9+Py6zCzgWV9J8l5bRZ8XZHKXbsKM2The6yCkvON0ufXHLsaHyeQu3cQI4FOtg8grRTbBJzlc/scuxYfJ5C7dhAWz8Wmtg5DunMut6I5diq+V5HQFaR1L4VN0e9ll4xlTlPUdrYPICzlN8G4gy2kTvVGy02U4fim+ttPlLsrtzXkq7U/DR/5G0vkUs7Gf1kFIt8/lVnTHLsbVSnK4bqv5ydf53B2bN142RVknax3Encppgr+mKIozJSXF6xOi0+3W2S4l1HLI5J6nUtyA24neEat1KHlNB8zHbGyvdSBS7imKwonL8dXTd6iTpByaaoqyjtY6iDuR0170l9xu98YLFy5EGgwGh06n88qHPkVROGNPuispRbbBZcWBQyS5c/+/1q3ARXsSQdG78UvJeqiRlzOg9q5vhdme9XSDUqF0zp5UWS7tfAuyhv5m3jNFWY/YLJGZFwXwAjlK8I0bN3bv2rVrcmJiYv2jR4+Ww0v/JGKT3aUTnYp8ks9Goj7FL9Ztv/WOmSjoEq9Q7dDXCN+t8CsO/ITZeC9m+2mtg5Fu7Up8SqlLccmVbr1n0aYU4ZluckAHfGOKsjazWSIPax1MbuV4HHzjxo3P7Nq1q5Xb7a6Wm+MKizf/uDr4fJxzgtZxFGaPGnYcHKVb3CDXB7pd+CdGo1Nyt9qeFwoFrJiNrTHbfbKq4lb+Da+TL+vB1zn47x2Nrz906JD/ihUrjOPGjbsIEJ/sDKoXXvPuGV98Q3jd+nkTZA5tXLea91+fjNvlomZ4BK+9/wkhxTOPQnO73bw1JYo/1v+CEIIBTz7DY0OGp72/7qcfmfW+Ja3v00dfLya0arUbzhFz7RovDh/EtSuX+V+zFrzy5nsAXLl8ibHPDGH2ouUYDLfoRyzz+60YgR9MUdbmNkukV7VB5ipRN27cOAW46aQxhZEpyvoIIIc83cI1/dWkYgafGMOenxoAXwK9tQ5Eui51iehx48ZdTHG6/U5cTqiZF3nL6XTmajGmhPg4zGNfYO53q6heM4w3J41lzsx3GDPptUz7Wpct4diRQ/z4+07iYmLo2+l+mrZoTc3adfh3/9989PbrfP7tCspXrER8XCw6febJOa0/LKFpy9Y8M3ocT/Z9lCMHD1ArPIJ3p73CqAlTbp3cpZyqAywwRVm7e9MYeZ8fJmeKslYHFlIEPqtUYHphNg6/9W5SXsvJEtHtO3Wulzr89defVzKoa3s6tbyHOTOvTyd9KfoCY0cMpf8j7ej5UEs+fvv1tPc6tWjAB29O4XaWiP7jt3WE121A9ZphAPQdPIyfVyzLct81K5fR47HB6PV6jKVK0aFLd1avWArA/DkfM+ipkZSvqLYwBIcUJzAw8wi/1KVj3W43jpRkDP7+bP5tHSWMJWnwv6Y5ilmRRfic6oq6przX8OmkZ4qyGoBvUatYJCkvzcBsjLj1blJeyckS0Ws270r48Ktv04q6sTF2FqxYy6JV65n32YdcOHcWgEkvjqTv4CdZtOpXFq/+nX/+3svaVT+kXet2l4g+d+Y0lar1yBZEAAAgAElEQVRcX324ctVqXIo+j9OZufnq3JnTVK5yfZnZylWqce6s2r3j2JFDnD9zmid6RdKn4/18/M4buFyZZ2+L7NGHU7bj9O14P81btaF8xUp8/tF7PD9uUq7ilnJsiinK+qjWQeSU17Wl59KbqGv/SlJeCwQWYzY2xWz3iWlcC7uslocdN25ctbTlYYXOz57ouGFRmc7degFQqnQZQquZOHPqBMWNRrZv3siVS9Fp+yXEx2M7er318U6XiL5TLqeTg//8zacLvsetuBn1RH+WLPjyhjZ6gKCgYN77bF7az++YJzJ05ChO2o7z5cfvA/DUCy9RO6Jg+yH4MIFaVd/cZok8qHUwt+KzCd4UZe0IvKR1HJJPqwe8D4zUOpCizuXGD50+U4Ozf8D1Fd30Or1aCvZ0Wluw4pdsV3y73SWiK4VWYeumDWk/nz11krLlK2bZjl8ptApnT5/insZqGeTs6ZNUqqyW/iuGVqFdxy4UC1RH9Lbr+Ah/7d6RKcGnt2/PLq5cvsgDD3VkSI9OvDHzMxRFYfKYkcz9PvtRXrKKPtdKAN+ZoqyNbZbIFK2DuRmfrKI3RVkrAfOR/UOl/DdCLjFbMLJbHtZkMjncxUpUiI3N2cCGoOAQmrZszdxPZ6Rty6slou9r045/9//F8f/UEVWL539Jx0d7ZHmuhyO7sez/5uNyubBfvcqalcvp0EX9U+rctRd//r4et9uN0+nkz99/o3ZEvWzjcjgczJhu5uXJbwCQmJiAEKDTCRLk0rH5oR4wUesgbsVXS/BfA+W0DkIqMr7EbNyJ2S6HIOSj7JaHvZzgKHdXWERwjbBwerRrQZVqJj786v9ueq43P5zDu9NeoUe7FuTlEtHBIcUxvz2T0U8OxOV0UrN2HV774PraJX06tObjeUsoX7ESj/Tsyz9/7abL/Y0RCAY99Sy1POu/d+zak3/3/02Pdi3Q6XT8r1kLBjzxTLbXnTf7Q7r07EeZcuUBGPnSBJ59vC8AY165+aKIXtMlvPCZaIqyLrVZIvdpHUh2crRcrDcxRVkHoZbepVx6TP/r9umGL2WfhdvzB9AGsz3f1rEsaN6wXGySw+X/X3RcXbei+GRtZH4Lwp1SwT8+6XhKFgP1C5kCWi42t3YC99oskYUmoPR86qYwRVnLoLaJSlJBa4Vsiy9QiqJw+mpCdZnc74xvFfEKXBNgjNZBZMfXboz3gLJaByEVWVMxG8vcejcpL0THJpdPSJGLyNwpmeDv2FRTlLWW1kFkxWcSvCnK+iDwuNZxSEVaKSDzlGVSnktyuAIuxibfWYO55CH7It+hQOBLU5S10P0ifSLBm6KsxYDPtI5DkoDhmI25n89fypWz1xKryqp5qRBpTSFsovOVG+QloKbWQUgSoAdmah2EL4tNcoTEJTvl7JR5RJFF+LzyhinKWkrrINLz+gTv6Vg3Tus4JCmdNpiNvbQOwledtydVufVeUs7J/J5HjBSyXOQL4+Anos4sJEmFyTuYjat8bRrb+vPq58tysfse35ej5WKvxqeUTHS4gvMjhqJKdrLLUy+YoqwzbJbIC1oHAl5egjdFWasCz2odhyRlwQS8rHUQvkRRFC7EJsmOdXlMJvg8FQS8onUQqbw6wQNTgQCtg5CkbEzAbKyodRC+4lJcStkUpzvryeNzadb7Ft42T8j1cRvW/sQ7ZnWG0h1//kGfDq2z3C8hPo57qhaq5tibEJw4fpTB3drT5f4m9I98kP8O/Zvt3su+XUCX1o2JvK8RU8eNwuFw5Oi99KZFjabnQy15su+jxMbYAfUBbuSgXpyyHc/bj1fwnjZFWatpHQR4cYI3RVnrAIO1jkOSbiIIeF7rIHyB262Ii7HJlXO6f1bLs+aFNu07M9b8Zr6cWysK8FrUi/TsP4SVv+9k6MhRTB6TdcXo6ZMn+PSdN/lq6U+s+mM3ly9Gs/Sbr2/5XnpHDh7g5PFjLF23hSYtWrFq2WIAlv3ffJq2bE1VU/V8+ZwFyB+YonUQ4MUJHvUXqL/lXpKkrWcwG4O0DsLbRccml3e63YZ7qpbi47dfp0/H++lyfxOsy5ek7XNP1VJ8+t50+kc+yIcWdf71ebM/ov8j7ejb6QFGDOzF2dMn0/Y/f/YMT/Z9lK5tmvH80H5cu3oFyFy6/7+v5/Dqi+oIqBVLFjF62IAsY/xu4Vd0ad2YPh3vZ8Hns275mRwOB29MfIku9zdh4KMP8+60SQzr/QgAUc89yU/LvwNg8bwvaHx3+bRFY57s+yi7tm7mzKmTtKp7F5++N51+ndvwSKv/sWn92hz/TlNFX7yoO/D3XiJ79AHgoc6Pcv7cGU4eP5Zp33U/reCB9h0pW74CQgh6DxrKzz8uveV76RkMBhwpybjdbhIT4jEY/Ll44Tw/r1jKoKd8psX1cVOUNUzrILwywZuirNUB2UtZ8galgSFaB+HNXG5Fdzk+uVLaBiFYsvp3Zi34Hsur4zlz6nrS1un1LLKuZ8yk1/hp+XfYjv3HghVrWfzzRjp378Wbr1zvFrF7+59YPvqcFRu2U7FSKB9apt12jEcOHmDW+xbmfm9lyerfSU5KvOUxS7/5mpO2Yyz79U++WvoTRw7+k/Ze81Zt2PrHRgD+3LSBug0asmvrZhITEzh8YD8NPEvMxsbEEFanLt/+tIEJr73NO1Nz3/x7+vRZUbZ8hbQlbYUQVKxchXNnT2fa99yZ01QOrZr2c+Uq1Th/5vQt30vPVKMWTVu0pl+nBzhz8gSRPfrwztSJjHllWpbL6nopPXD7f1B5xCsTPOq4d1l6l7zFi5iN3nqvae5yfHIZl1tJu997PDYIgCp3mWjcvCW7t21J27d73+ul69/W/sTWPzbwWOc29OnQmq9nfci5dAmn9YPtKVu+AgA9Bwxh6x8bbjvG7Vs2cV+bhyhXQe1y0WfwE7c8Ztvm34ns3geDwYDBYKBLr35p793b+gG2b96Iy+Xi2JFDDHrqWbZu2sjubX9Sr+H/MBgMAAQEFKNdpy4ANGjclNMnct9+rUUnu+fGTWLJmk28O/trtv6+gYqVQ6lctRqvjnmWMcMHs/rHZRpElef6eJqSNeN1j0umKGtpYKjWcUhSLtQEHgV+0DoQb6MoClfiU8rfdKd0w7gDg65PTa8oCsOefZFeA4bk6FrCcyK93g+X6/riYClJyTkPOPVcIvdjy9MfUym0Kgb/AH5a/h0R9e+h+X0P8PlH76HX62h+3wNp+/kH+Kcdp9frb4g7vcHd2pOUmIjBP4BvVq674b3QKqHKpegLOJ1O/Pz8UBSF82dPU6ly5ukGKoVW4VS6h4izp09SMbTKLd/LTlxsDPM++4hZ3yzly48/oMm99/1/e3ceZ0dZ53v8U51OyNodQjohIUsFhwsqmxMElN0rGqirLGIEcUZxA1wYxIUaB7TFcahxHUcERgUccESRYQSmBAYENeKoGBBZdQjUBUm6O52kk066O336nHP/qIo3hk46yzn1q+X7fr36hS9z0vVNOud863nqqafwzlzKW994HCeefAoTJ03a4e/POAf4EIZ3euWu4IH3Ei9eEsmTj1KAgt/Z+9UbZcNgpW3blfO33/JdLrzE58UXnufhX/83H++8ctTfe9IbT+XGb3ydk089jfa996ZSqfDM75/i5QfHOwn//IF7WbO6h306ZnHbzTdy1HFxcc53F7Hs/v+iWq0yPLyZ++66E3f/HW+UeeRrj+P6r3+F3p5uZs6azQ9uumHMP9uRxxzHj354K6ecHl9tvPPW7//Zrx997Alc/aV/4P1/8wnapk+ntXU894a385Vv/duY33tbN/5w+9fmOzo66i8/+FDC227htKVv574f3cHsfeeyYNH+L3nt6095M+868xQu/IjPPh2z+MFNN7DkzWeO+Wvb89UrP8P5F3+CSZMmMzgwgOM4OI7DSKVCpTKc94IH+CvXD/0o8PotDp6rgnf9cBwZ3O9XZCccS2f7q+lc/5B1kDzpHWX0Xq1WWbrkeAYHBrj0ioD95o9+R5J3xlL61q3jvW+Lp7BHqlVOX3runwr+L498Df6H30dP1yoWLNqfz375agBef8qbuDe8ndNPOorZc+Zy0CsPYWhwx9fUDzjoFVzwkUs57y2nMmnKFP73kjeN+Wc769zz+J+nn+TM1x3NtPbpvPLQw1nd3fWnXz/quBO55abrOTo58Tj62BO47eYbOfAVB4/5vXdFHce5PPgKl1/yQb511ZeZOnUaV3zpqj/9eufHL+LEk5dw4htOZd5Clws/6vPOM5YAcMRrjuWsc+MJ1R392mgeeeiXDA0N8ZrjTwLg7He+l0s/9F5uuOar/J8z38a0tkLsRjyN+CFoV431wmZw6vX8bHPg+uFpFGAUlFXnjPvxr68cf92R1jkK7Pt0rj977Jdlw/Llyw9qbW29+4ADDtg4efLk1Hfk21ypTvh9d/8hW/9/h83fm2WPR7S1F+LDn00b+5kydRqVSoVPXvR+Xn7IYbz7AxendvzJ1IanTRiudA9PzPzugPWRYXpW/pHOB3p4sX/0SxEZ9XQUeCbX4vO28Ef3vUuenUVn+/yxXyYAvZuGZ1pnaLb3n3MGS994HGedfAxTpk7j7eedn3qGHI3x8uog1w+PtThwbqbok6f0eNY5RPbAOOAc4PPWQbKuXq+zfqDykoJ/9IV1FnF225re1Vx47kuvQx993IlcctlnX7LgLW11J56iNw1RDu8Gfp72QXNT8MBb0ba0kn95KvgaxGWbtr7ByvSRWm186gdusH1mdnDLPcusYxRKLZ8zDm91/fCiKPA2pnnQPE3Rv8M6gEgDHE5n+4HWIXZSX71eHxkeHp6Q+oEHKjPSPmYZOeTnYTP16gjVWo1NwzXrKLtjKrA07YPmYgTv+uFCwOQahkgTnAN0WofYCb21Wu2n3d3d3vjx4ystLS2pdEGtXqd/00BbnhYA51XVqTqVeq2lPpLxWfp6ncEN6/hd1xD9w7n9d3E2cH2aB8xFwQNv58+2sxDJtbeRg4JfvHhxbfny5Z8aHBw8ZMWKFR2k9B4crtYn9Q3VtFNlCiZQdVpbauMGMn81pM66gRG+93h/bmYcRnGC64dT05ymz0vBn2EdQKSBDqKz/X/Ruf4P1kHGsnjx4heXL19+bK1WW0BKnxeffmDNZes310Z/oos01Jyhtd3zpq7d9NDIX5g/GGVHqjXoHagykuN2J37K3OtJ8VbvzBe864czgcXWOUQa7M3AF61D7IzFixcPA8+kdbwnfxCO/pB1abyBwUprdaDyYi1X95XnmUeKBZ+HRXZvIB85RXbFadYBssj1w8OB0bemk6ao1sfpckh6Tk3zYHkoziXWAUSa4LV0tndYh8igN1sHKBUHp0Kr1jelZ67rh69K62CZLnjXDx3iEbxI0bQAJ1qHyCAVfMqqtGS6BwootQ3bsv6DfRUw2zqESJMcZR0gS1w/3A+tt0ndCOOy3gNFk9o0fdZ/sK+3DiDSRCr4P3fC2C+RhnKgSouuwafrqGTxeNNlveD1AShFtpjO9szfyZKiI6wDlI0D9YpG8GlrAY5P60BZpje8FNkk4FDrEBmi6XkDVRW8hcPTOEhmf7CuH3ag22Wk+DRLBbh+2EK85kbS5OBU65qiN5DKv/XMFjzwausAIilQwccOBKZZhyijEXQfvIFyj+DR9LyUgwo+pul5I1pFb2Ke64f7NPsgWf7BquClDA6ks326dYgM0PvdglbRW2r6KD7LBX+IdQCRFDio3EB/ByYc6nVtdGOm6dfhM/mDdf2wFZhvnUMkJftbB7CULLBL5ZqkbMuhphG8ldKO4BcC+kcnZTHPOoCxhcAU6xCl5NSp0qK9GGyUtuAXWQcQSVHZC34/6wAl5mgVvZkDXT9s6t99Vgu+1FOWUjplL7i51gFKS4vsLLUCTd2yNqsFrxG8lEnZR/AqeEN1LbKzNKuZ3zyrP1gVvJSJCl5MaHreXFOflprVgm/qWY1IxrTR2T7VOoQhFbyRqqPRu7FSFny7dQCRlJV5FK+CN1LT9Lw1FbxICajgJXU1TdFbK+U1eBW8lM2+1gEMqeCNVB2toDemEbxICYy3DmDB9cOJ6ClyZnSLnLlyFbzrh5Mo6YedlJpjHcDIROsAZVbTCN5a6abodTYvUh46mTekEby5vZr5zbNY8GUdyUi5lfXfvQre0AjjtA+9raZ2cBYLvmodoKx66tMnVOrjnq/XGbTOUkIqeEmdpujNNbWDs3j2NmIdoKx+XFt8+AGbbwKgnY3r5zmre12ne/0iZ9XgopaukflOj7Mv6ybs7fRPm8TmvcdR63AcfUA3SFkLXgVjSNvUmitdwWsEnwHrmdq+vj61/Yl6smvwqD+Ven0m63vnO6vXuk7XhkUtq4Zcp7s631ndMstZt1c7m6ZNYvOMFuodjpPJ2aIsKWvB6/0u0iRZLHiN4HPDcXqZPrO3Pn3mI/UDoDb6q1qoVfdlbdd8p2et29K1cX+na/NCp6s2z+kd1+H0TWxjoG0vKvs41Gc4TmmLrqx/br3fpcyGm/nNs1jwOqMvmBot41Yyc9+V9Zn7/qr6iu2+bjwjw3OcNT0Lne6+RU7XxkXOquGFTnd9rrOmdaazfvI0BtsmUOlwHNpSjC/Npfe7lNnmZn7zLBZ8BahT3hFNaVVonfB8ffa85+uz5y3j0O2+bhKbB+Y6vb1bTgT2d1ZWFjg9zHHWjN/H6Z8yhcHp46l2OA6TU4y/p7Yz/1F4GsFLmZWr4KPAq7t+uA6YYZ1FsmmQvSavqO+3YEV9vwU7et00Nm2YF58IrF/krBpY5HSNLGjpYQ5r9trb2Th1MkNbFgpOSCv7DvRaBzCywTqAiKFyFXyiBxW87KF+prQ9VZ/S9lR94Q5fN4MNa+c7q9csdLo27N+yatB1uqrzndXObGfdXtPZOG0SwzNa4hOBZq74Xt3E751ZUeANu364Fr3fpZyaeoKb5YI/yDqElMNa2masrbfNeLT+su1OlDvUarPo61kQLxTsX+R0DblOV22es7qlw+mb2M5A20SGZzjUZ+7mQsGePfpD5NsqVPBSTn9s5jfPcsGLZEadlpZuZszqrs+Y9VB1++eerYxU5jhrVy9weta58ULBza7TXZ/r9LZ2OOsnTWOgbQKVmS0O07f5raUcwSe6gFdahxAx8GIzv7kKXqSBRmgd/0J91twX6rPmPsjB233dXgwPzXV6e1ynu+9lzsq+yz539boUY2ZNl3UAESMawYsUzWYmTHyuPnfBc/W5Cx7gVc9eZh3I1irrACJGmjqCz+ruYk39Q4tkzPPWAYxpBC9l1dQRfFYL/hnrACIpesE6gDEVvJRVKQv+D9YBRFL0tHUAY5qilzLqiwJvoJkHyGTBR4G3EthonUMkJY9ZBzAWWQcQMdDU0TtktOATT1kHEElJ2Qv+OWC9dQiRlP3fZh8gywX/uHUAkRT0k8IbPcuiwKsDv7XOIZKyh5t9ABW8iK3Hk4Iru6Z/2IlkzK+bfYAsF/xy6wAiKSj79PwWKngpm4eafYAsF/yvgWHrECJN9qh1gIxQwUuZvBAFXnezD5LZgo8CbxC96aX4llkHyIingabeMiSSIU2fnocMF3zi59YBRJqoF601ASAKvBqazZDyaPr0PKjgRSz9TAvs/oxm7KQsVPDAg4A+AKWoHrAOkDGpTFuKGKsDv0njQJku+CjwetE2nlJcP7EOkDH3oBN6Kb6no8DbkMaBMl3wiR9ZBxBpgtXAE9YhsiRZVaxRvBRdap2Wh4L/oXUAkSa4V9ffR/Wf1gFEmiy1TstDwf8C6LEOIdJgt1oHyKg7rQOINFEPcaelIvMFn9w+o7N6KZKNwF3WIbIoCrxHgResc4g0yZ1Jp6Ui8wWf0DS9FEkYBd6QdYgM0wm9FFWqXZaXgr8X2GQdQqRBND2/Y5qmlyLaSNxlqclFwSejHb3ppQgG0J0hY7kfndBL8dwdBd7mNA+Yi4JPfMs6gEgDhFHgac/1HUg+BO+xziHSYKlfas5Twd8PPGsdQmQPfdM6QE582zqASAMNA2HaB81NwSf3DF9nnUNkDzwD3GcdIid+BKy0DiHSILdFgdeX9kFzU/CJG4AR6xAiu+labW6zc6LAq6JRvBTHtRYHzVXBR4G3CoNpDpEGGCI+QZWddx3am17y76ko8H5qceBcFXziX6wDiOyG70eBt9Y6RJ5EgfcsWmwn+WfWWXks+LuBx6xDiOyia6wD5NQ/WwcQ2QMbMbzUlLuCT65hXmmdQ2QX/CwKvF9Zh8ipu4E/WIcQ2U3XR4G33urguSv4xC3EK5JF8uAz1gHyKjmhv8o6h8huqAFftQyQy4JPVtj+o3UOkZ2wLAq8+61D5NwNQK91CJFddHuyjsRMLgs+cSPwR+sQImPQ6H0PRYG3EfgH6xwiu8h8EJrbgo8Cbxj4gnUOkR34eRR4P7YOURBXA89bhxDZSf+ehXU3uS34xLXACusQItuh0XuDJPvT6+9T8qAC/K11CMh5wSej+E9Y5xAZxX9FgadtaRvrX4GnrEOIjOEbUeD9j3UIyHnBA0SBdxvwE+scIlupABdZhyiaZHHt5dY5RHagnwzNNOW+4BMfIb4lQSQLvhoF3u+tQxRRFHj/DjxknUNkO74QBd5q6xBbFKLgo8D7LdrnW7JhFXCFdYiC+6R1AJFRrAK+ZB1ia4Uo+MTfARusQ0jpXRoFXr91iCJL1jZoj3rJmk9HgTdgHWJrhSn4KPC6gUusc0ip/QL4jnWIkriAeJ9vkSx4HLjeOsS2ClPwAFHgXQfcZZ1DSmkQeI+e956OKPAi4FLrHCLACPDOZBFophSq4BPvA/qsQ0jp+FHgPW0domSuQXfQiL3PRYH3sHWI0RSu4KPAe5F4Vb1IWu4DvmYdomyS2ZL3AJuss0hpPQz8vXWI7SlcwQNEgfdtILTOIaXQB5ynqXkbycM8tKpeLGwG/joKvBHrINtTyIJPvA/osQ4hhffBKPD00CNbXwOWWYeQ0vlUFHhPWIfYkcIWfBR4q4CzgcwtfJDCuDkKvO9ahyi7ZPbk3cQLHUXS8Avgi9YhxlLYggeIAu8BNH0nzfEE8SyRZEAUeM8AH7POIaUwQLxqPvO7pxa64AGiwPs8cJt1DimUDcCZUeBpcVeGRIF3NXCddQ4pvIuSE8rMK3zBJ84DtDe4NEIN+Kso8P5gHURG9QHi6VORZvinZL+VXChFwUeBtwE4E+18JXvusijw7rAOIaNLHiH9FkALH6XR7iJnl4Gcer08d/e4frgEuBNotc4iufRvUeC9wzqEjM31wyOIV9ZPtM4ihfAk8JpksJgbpRjBbxEF3t3A+dY5JJfuJV6pLTkQBd5v0CJIaYw1wJvyVu5QsoIHiALveuBT1jkkV34JnJFM/0pORIH3HTL2+E7JnQrxgtpnrYPsjtIVPEAUeJ8F/tk6h+TCY8CpWjGfW5eiB1DJ7rswCryfWYfYXaUs+MTFwE3WISTTVgBviAJvnXUQ2T3JE77OQjvdya77Qp5WzI+mVIvstuX64TjiZ/j+tXUWyZyVwLFR4D1nHUT2nOuH04gfCnSkdRbJhauiwPuwdYg9VeYR/Jaz+3cRP3ZSZIvngONV7sURBV4/sAR41DqLZN61wEXWIRqh1CP4rbl++EXgo9Y5xNwTxNPyK62DSOO5fjiTeCR/mHUWyaRvAe8vytMhSz2C31oUeB8DPmudQ0z9injkrnIvqCjweoHXET/HW2Rr11CgcgeN4F/C9cOPAZ8HHOsskqr7gNO1Wr4cXD+cDtyDrslL7AtR4H3COkSjaQS/jSjwvki8ra0+6Mvje4Cnci+PKPD6gJOJT+yk3D5dxHIHjeC3y/XDw4DbgYXWWaRpasAno8D7R+sgYsP1w1bgn4APWmeR1FWAD0WB9w3rIM2igt8B1w87gP8AjrHOIg23DjgnCrx7rIOIPdcPLwC+hp5TURbdwFuiwHvQOkgzqeDH4PrhBOLFF9qHvDgeJ77evsI6iGSH64cnAbcCM6yzSFP9hnjr6cI/cVAFv5NcP3wX8Rn+VOMosmduBc6LAk+PDpaXcP3wZcAdwCuss0hT3ES8Un7IOkgaVPC7IHnzfxetvM2jfuDi5GFDItvl+mEbcDNwqnUWaZgq8PEo8L5iHSRNWkW/C5Ip3WOAzxEv0JJ8WAYcpnKXnZE8FvRNxPtijBjHkT23Fnhj2codNILfba4fHgd8B1hgnUW2axi4DPhSFHg6IZNd5vrhEcC/oin7vLqHeEr+eesgFlTwe8D1w6lAJ/A3aPVt1jwCvCsKvN9ZB5F8c/1wL+LR/EfRrGde9AGXRIF3g3UQSyr4BnD98BDilfa6nc7eGuDvgG9q1C6N5Prha4FvAwcYR5EduwO4IAq8VdZBrKngG8T1Q4f4yXSfB2bapimlKvAvwOVR4K21DiPF5PrhZOBK4MNoO+us6QUuigLvZusgWaGCbzDXD2cQT9ufD0ywTVMay4APR4GnR4FKKlw/PJH4saIHGkeR2C3Eu9Kttg6SJSr4JnH9cAFwOfGoXtfnm+O3wGeiwPuhdRApH9cPxwHvIT6hn2ObprQeA/42CrzQOkgWqeCbLLl3vhN4O1qg0ygPA1dEgXe7dRCRZNr+EuDjQJtxnLJYAXwK+J7W2myfCj4lrh++nHjx11JgvHGcvFpOPGK/0zqIyLZcP5xJPGt3Abo81ywrgSuA66LA0x4FY1DBp8z1wznEHwDnA7ON4+RBlXhV7DVR4N1rHUZkLK4f7g/8PXA2WojXKGuAALiqLNvMNoIK3kjyEJulxKtxtfXtS60Evkl8u9uL1mFEdpXrhwcDFwPnAhON4+RVL/B14MvJDoOyC1TwGZDslvUO4sIv82KdKnA/8erkOzQFJ0WQPHb6AuADwL7GcfJiOXAV8TV2jdh3kwo+Q1w/bAFOIJ7aewuwj22iVNSAB4HvA7dGgddtnEekKZJZu9OJL+AiN04AAAIrSURBVM+dhKbvtzVI/LTHa6PA+4V1mCJQwWeU64etwMnEHwhLKNae90PAA8B/EI/UVepSKq4fHgC8j3j6fq5xHGu/Aa4Dbo4Cb711mCJRwedEsgr/DcRn/scDe9sm2iVDwH8DPwV+AvwyCrzNpolEMiDZAfMI4LTk62DbRKmoAr8E/hO4Mwq8J4zzFJYKPoeSqfxDiT8YDgdeBRwGTLHMlagBzwKPE9+v/lPgVyp0kbEl+2ZsKftjgHG2iRqmD7gbCIG7osBbY5ynFFTwBZGU/l8Ql/0hwELiaf0FwH40/t77NcQr3V8EniQu9MeAJ6PAG2jwsURKJ7mv3gNeB7yaeFvcvGyWVSX+XLiHeKT+oBbNpk8FXwJJ+e9LXPaziUf6W39NTf7rAJuTr6Ft/ncvcaGvBLo0IhdJl+uH04C/JJ65e3Xy35eZhooNEZ/cP7LV1++iwBs0TSUqeBGRvHL9cG/ioj+YeKZu66+5NO7++w1AN9CV/PcF4mdBPAI8pdF5NqngRUQKKnm65ZbCnwNMIt5Gd8vXOOJ1M9Wtvvr5/0XeBXRrNJ5PKngREZECysuCDREREdkFKngREZECUsGLiIgUkApeRESkgFTwIiIiBaSCFxERKSAVvIiISAGp4EVERApIBS8iIlJAKngREZECUsGLiIgUkApeRESkgFTwIiIiBaSCFxERKSAVvIiISAGp4EVERApIBS8iIlJAKngREZECUsGLiIgU0P8DZwTsZ8dN+88AAAAASUVORK5CYII=\n",
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cHLneOwu4zzjOrY3wlPsL4rwe7UqppsAq9EQ7Fb3WIwsYjN6GVxq1RQU5VyG8gQk9QV5N3n+3KbneX+hvW+Xa51b06y8vh3O9z+s67oHeZPAr+uOlx9FvLm5BL9zkJ/s6/wy9n09e/inAfkQeJKFfmmXoyWwcenV2CDC3iPtah14dvBS9g8lQTdM8k+9B9Ha23HIv2+f+Gadp2soixpLbPvRqwjVa0R8/G4J+N3+tpmmHshcqpfJqAijInT7ovxPQO+HlrpFo6fG5EN4iDr2pLr9reR96Mj6gadqeYjr2PqAtelt3Qa+x3Iajxz9I07ScDrlKqVvyWDevY5xC7zRsLsbvJ+EmbeiXwJ1wv0TvCToB2KppWpHvLt1/4Degl9TnunulZlsOdFVKtcteoJSqyvml5uXo1eozlFIBuY+hlKpRhNDmo/fEfSz3B0opi1KqcgH2kV2CyCkxuNvN8/oiSEWvlsvPBvQvyDs9H7tRSl2NXrUYc6ENhTCCpmlO9L451yul6mYvV0o1Qy+NZ/sW/Zp53N3ujMe6SilVrQiHn4/eoff23B8opYKVUuULsA8neqLOedRT6Y/MXp/Huuddx+7zXwAMV0q1ziOOonw/CTcpoV+6T4F70TuUTL/UnWma9p37bvdT9MR8h/ujF9B7qa5QSr3Bf4+tHULv7a65t09S+rPdc4G/lVJfod8VN0TvJLYG/XGzwsS0Win1HvA/9w3Fj+jVbM3RO9rchz4i1MX8iF7FvsS9rwroXyxxQJ1c624EJiulHkVvV4zTNO28PgGaptmVUtPRH1tbrZT6kv8eW4vl/EcKhfAGNmAgsEYp9Q56crwb/emOdgCapu1z//0/B4Qqpb5DL9k2BoaiPwr2UiGPOxe98PGuu2ZsjfvYYe7lg9Bvki8mBr3KfplS6gv09u670K/Ty3KtuxHor5Sait6r/YCmaX8CUejfl38qpd4HdqB/h12OXhNYtZDnJbIZ3c3eG1/899haxwKuvw39zrVeEY4V6j7WQ7mWT3Yvf9FjWTv0tqsM9PauKPTnUjWgVq7te6M3CSSgt4X9i574OnisMwdIySMmG+7HZ3Itvx39gk9Dv9n4B3geqOOxTiyw9ALnOgTY4o7nADANvYSe89ide71a6E0PSe7PfvE4p5zH1jzWH4X++FkG+mN8n+X+vyjsucpLXiX5Qn/G+2/0cST+BSaiJ+j0XOsNQ+9BnuJ+7UR/druFxzq/ANvyOMYcIDbXsgD3dbfNfb2cdV/TM4FKHutpwJsXiP1W9M7CGe54JuR1HaE3e612f19oeDzChn4j8CZ6gSQLvS1+JXC70f83vvxS7l+uuARKqU3AWU3T+hlw7FnopfgKml6dJYTwQe5SeISmac3zW1eIvEgb+iVSSnVELzl/WgrHCs71vhp6b/bfJZkL4TvyuJaboz/x8YshAQm/ICX0InJ36OiAPnRodaCJ5vGomXsAifw6eKRompb78ZOLHXMz+gW/E71aeiJQF+inadqvhYlfCGEcpdRx9Crx/ejjKUxGfwqkvaZpF3r2XIiLkk5xRTcCvd1pNzBGO/+58QZcYGAGD0+gtz0V1Pfu42YPO/s3MFGSuRA+ZxkwBqiN3o7+B/pwrpLMRZFJCb2EKKWy51C/mP2apu0vjXiEEEL4N0noQgghhB+QTnFCCCGEH5CELoQQQvgBSehCCCGEH5CELoQQQvgBSehCCCGEH5CELoQQQviBQg0ss3HjxgroI5PJjYAoKhdwrEOHDgUeIU8YS657cQFyLXuZAj+HvnHjxitMJtO7JpPJisec1kIUkuZyuRJdLtedHTp0WGd0MOLi5LoXFyHXspcpUELfuHFjBZPJ9HvlypVr1axZ86xSSkaj8XJZTpfF7nAFZTm1QIfLFeByYXK6NLNL0yxOTTO7XFicmmZCw6ShKYD6gUmp5R1J5TXQ9O9upaFMTkxmB8rswGR2YApwYLLYNZPFgdlix2TRl6mCfddrmqbi4uKqJiQknHS5XN3l7t57yXXvm1yaht2hBdpdrgCnS7M4XZpZv/bRf6JZXC7NBPr40TXNqVkhrpRA/RpWmr5YuTBbnCiLHbPFoZksdkwBdswWB8riRCm5lr1QQavc65pMJmvNmjXPli9fPr1EIxKFkulwBqRmOitk2J3BmQ5XuSyHq5zd6QpyaZpH9ajK9ZNzKk+zlwYFWFzl9HfuRZoCpwmcAYBewebKKwqlYQlMxxKcRkBIGoEhqQSUT8dkyjMB1KxZ82xSUpLV5XLVRZ9XWXgnue69mMPpMqdmOctn2p3lMh2uoCyHq1yW01XO4XQFnn/h5fEd4BZkxhWsZYWc90H2/I2O8z7RcCf4WuXM9lRXev3qOz4exJL5S7AlZl3KOYlLU9CEbgKU3KEby6VpKi3TGZKa5SifluWskJ7lrOBwuQKMjgs0hSMzBEdmCBkJOQsxB2UQEJxGQHAqgeVTCayQhlK4/44U0ibr7eS69xKappGW5QxOzXJUSM9ylk/PclbIcrqCDApH4XIE4nIEmhwa5qxkKp/84xsgC5v1H2C9x2sntkSZ2rmUFHm2tdComA7FGYin2OjIjSW1b1+TnuUsl5RhtyZnOKzpdmcFTdN8pR1T4cwMxpkZTEZCNX2J2UFQxUQITgWfOQ/hoaSue7nmz5dhdwYmptsrJ2c4rBl2Z4Vza928UiDQ0f2a7F6Wis36J7AYWIgt8ZBRwZUF3v4H4rOWLl1a8ZtvvqlU2O00TSM5w17+SHxa/Z3Hk1rvjUuOOJmUUT8ty1FR0zS15pdVjBrUI+fVv0MrRl/dK2f7tg2qMLx/t5zP//5zbZ7HWfXDUkYMuJJRg3owtO8VvPH8U7jc/SlS09K55YHHadNvFGE9hxH17OtcqK/FHdOepk2/UfQdOYnEpOScc7j6xrvZF3s418k5LWQkVDOlHGsYmBZXP+zXO9/HZr0Lm7VhYX9PQhS39evXl6tXr16b0jre+PHjG4aFhYVnv4KCgi63PfVMgyPxafV3nUiK2HMyuc3Bk/ENBnXvWGnEwO4X/K5OT09j+l0Tuab75Qzp2ZEVMYtyPjt4YB93jB3KyIHdGdqvK8sWf5vnPuITkugzYhJt+o1iyv+ey1l+6kw8vUfcjt1uL+pplgf6ArOAg9isG7FZH8NmbV3UHYoLk/nQi8hutxMQcOHa7p9++qliQkKCecSIEUkF2V96lrPcmdTM6knpjqoXq0a/snc/ruzdL+f93RNG06lrj3PW+XjBD1SyWi96vCt69KLPoMGYTCbsWVncPOxqFi1pah5/dVeeff1DnE4X/6ych8Ph4NpbHuCbpSsZOWTAOfvYtutf9h44xNZV83ny1dnMXRDD3bfcwAdfLKRPt440DW1wkQg0ZXamd0efYvZNbNatwNfAh9gSj100eCH8wNy5cw8BpGQ4yu/cd7BGjw6tg3tGjqh5NvW/ZuhZz9lo17EL27f8fcH9fPLemwQGBrH09785cuggN17bn07delC5SlVmTp3CdaPGMWzMTZw9c5qxkX1o3+kKatWpe84+Pl/4PX2u7MjMBybRd+Qktu36l9ZhzZhqe5no/91z0e+6Qrrc/XoSm/Vf4DtgIbAOW2KePXREwfl0Cf2zzz6r3KRJk4iWLVuGT548uV6VKlXa7t69OxBg69atQb17927WunXrVi1atAh/9tlna2Rvp5TqEBUVVbtNmzat6tWr1+a1116rlv1Zfts98MADdVu3bt3q7rvvrv/XX38Fd+jQoWV4eHirpk2bRkybNq0OwNq1a4M//fTTGgsXLqwaFhYW/tBDD9UBWLBgQaUOHTq0jIiIaNWmTZtWixcvqXQqObP63pPJYXvjkiPOpmbVKkybeNyJ4/z1+69cM3x0oX935StUxGTS//szMzOwZ2ViMuld1bfs2MNVfbqhlCIgIIABPa5g7oKY8/YRYLGQmWXH5XKRmpZOYEAAx0+e4svvljF10o2FDakN8CT6Xfy32KwDsFmlWl6c42LX/KRJk+q3bt26VVhYWHjHjh1bbtmyJQggJSVFRUZGNmnatGlEy5Ytw6+88srm2fubOnVq3UaNGrWOiIhoNXfu3Kqex8p9vS5ZsqQiQLdu3Zp//PHHVbLXW7p0acVWrVqFF+Y8shwuy4nEjFq7TiRF7D+dEvb553OrdevVl+o1a+Wss+63X4g7cZzBQ0dedF/Llyxk5PhbAKjfsBGdunbnp2VLAdi9Yzvd++g34lWrVadFq9YsX7LwvH0EWCykpWfgcrnIzLITGBDAsp/XUKVyJa7ocFlhTq0wmgEPAWuAw9isT2Gz1i+pg5UFPltCP3r0qOXuu+8O/fnnn3e1b98+47XXXquWkJBgAXA4HIwZM6bJ3LlzD7Rv3z4jOTnZ1KFDh7Arr7wytVevXmkAQUFB2tatW3du2rSpXPfu3VtNmTLljFIq3+3MZrO2bdu2nQDx8fGm33//fU9wcLCWkpKiOnXq1GrQoEFJ/fr1S73ppptOJSQkmD/66KPDADt27Ah86qmn6v700097AstXKrd+87Zao669qvkPa7cQGFS0vi2Lv/6C7n0HUK16jXOWTxpzHU6Hg85X9uKuh2cQElI+z+03b/iTp6Ie4FDsfkbdeCtDIq9y4Eigw2Wt+HrpSoYP7ofd4eC75T+T4K5O99SyWSh9unXk8kFjad64IY9PncStU5/gxcfux2Ip8p+WBRjqfv2Lzfoe8DG2xDNF3aHwDxe75gFsNtuJunXrHgGYPXt2lbvvvrvhb7/9tvfbb7+1JiYmmvft27cd4OTJk2aAr776yrp48eIqmzZt2lG5cmXX0KFDG2fvy/N6rVq1qmvbtm1Bffr0aXno0KGtN91005lPP/202i233BIP8NFHH1W78cYbT+cXv6ZpJKbbrWdTs2qkZjoraR79SL6b9zlTH30yZ92kxEReffZx3p77Dfv37r7ofk8cPUKdev/VhtWt34DjR48AEN6mLTEL53PL5Ps4cjCWLRv/om6D81u4bhweyc33zaT9wDFcf1Vv6tWpycSHnuD7uW/kd1rFpS7wKPA/bNalwNvACmyJ0iGzEHy2hP7LL7+Ub9myZVr79u0zAO6+++4zAQEBGsCWLVvK/fvvv8FjxoxpEhYWFt6pU6ew1NRU8z///BOcvf3EiRPPALRv3z7DbDZrhw4dCijIdpMnT865cNPS0kxjxowJbdGiRXiHDh1aHTt2LHDjxo3nP/4BLF682Hrw0KFy3br3bNvx8vatJt86vqpSJo4fO1Kk89c0je/mfc7QG84tCS9b9w9fff8Ln3y3nPizp3n16ZkX3Ee7jl1YsHIty//cxo6tm/l9zTozQNRdt9CwXm26XHMTkTfdS+d2rbGY807QT0+/i80rvuLr2S+w4tc/aVC3FqH163LLA48z/PaHmLdoeZHOz60Z8CJwFJv1M2zWbpeyM+HbLnbNAyxevLhSu3btwpo3bx7x/PPP1925c2cIQMeOHdP27dtX7sYbb2z4/vvvVwkM1J/qWrlyZcXrrrvubNWqVV0mk4nJkyef8tiX9eDBg0HdunULCwsLCx8xYkRTpRT//vtv4I033hi/efPm8gcPHgxITEw0/fTTT5Wzv0/y4tI0dTols9ruk8kRh86mNUvJdFg9k/nff64lLSWFHn0H5mzz3GMPc9vdU8+7WS+sp159h62bNjJqUA9efGIGna/shTmPa7l8SDDfvP8iW1bO44mHJvPo828xfcoE/o09zMhJ0xg5aRpbtpfKE6Zm4DpgObADm/V2bFajevP7HJ8toV+MpmlUqlTJsWvXrh0XWickJCTni8BsNmsOh0MVZDur1ZrTzjN16tR61apVc2zfvn1HQEAAAwcObJqRkXFONbGmaSSk2SunOM21u/bsa45+84OLxr5vzy7+d8/tgJ5wZzzzUp7rbVi3hszMTLr16nfO8uw79ZCQ8oy+aSJPTr//oscDvSque98BLFwcEzC4SxjBweV47cmHcz6PfvNjIlo0ueg+kpJTeOndT1n+xVs898bH9LqiAzcOH0zbATdw7cBeBAeXyzeOiwgCxgHjsFl/AmZgS/zzUnYo/MvevXsDp0+f3nDt2rU7IyIiMv/888/g/v37twQIDw/P2rVr1/alS5dWXLFiRaXHH3+8/pYtW867xpXH4EiaptG9e/ekJUuWHMjreIMHD45///33q9aoUcPRtWvXpNq1a5/3aNb//jejzsLvvquByWy573825dn3xdPCrz5jyMgbMJvNOcs2r1/H5vXreOXpx8jMzCQxIZ5re3Vi8er1521fu159jh89TI1atQE4duQwXXv2AaBeg4a8MvvTnHUn3ziCrr365BlHtr82bSPuTDzXDOhJj6G3Mvf1p9E0jQkPPM7qBRf//ipmYcBs4Gls1reAt7El5lsTUpb5bAm9d+/eqbt37w7Jbid75513qtntdgXQtm3bjAoVKjg928a3bdsWlF3VdiGF3S4hIcFSv379rICAALZs2RK0Zs2anF7tFStWdCYkp4TsPpkccTg+rekVPfsFrvt9NXt2bsvZfuum85/UadoijPnLf2P+8t8umMwBFn41l+tGjjnnSyApIYH09DQAXC4Xy5csJKx13u1fB/7dg8ul35ukpiTz26ofiQhv5QQ9Oael6+OIHDh0lHc+/ZoH7xh/wVgAop59g5kPTCIkOJjUtHSU/rw5druDrKL3kM1LX2AdNusi6Slbtlzsmo+PjzdbLBatYcOGdpfLxaxZs2pmb7dv374ApRTjxo1LfPfdd49omsb+/fsDBwwYkLx48eKq8fHxJpfLxbvvvls9e5shQ4YkrVmzptKff/6ZUzv3888/59S+3Xbbbae/+OKL6p999ln1W2655Zwk43C6zMcS0uveePf0WvNXrA2Yv/y3CybzlOQkVny/mOtHn1vT9sMf/+S8nn/rQ5o2b5lnMgcYGHkdX8/9GIAjhw6y/o/f6TMoEoAzp+JyrvM1v6xi/95dDL5uxAV/x3a7nenPvM4rj08FIDUtA6XAZFKkpKZdcLsSVhN4AtiPzfoINmtwfhuUVUUuoRv93Gi9evUcr7/+euzQoUObBQYGar169UoKCQlxVatWzRkQEMCSJUv+veeeexq89dZbtVwul6pSpYpj/vz5+/lv/KPzFHa7mTNnHpswYUKTL7/8slqjRo0yr7jiiiSAxHR7xR6Dh1eft+DGctf3u5K+Vw/hzvunEf3G+zwVNZWM9DTsdjthEW3Ir8Sel+SkRFb9sJQFK9acs/zAvj08FfUASikcTietWl/GdFt0zud33TSSKQ/OIKJte5YvWcjyJQuxWCw4nU4GRF7HrTePteNIKLf/4FFG3Tkdi8WMxWLmVduDtGvd8oLxrFm/mfSMDAb0vEI/zoRRjLlrBs+/PYfxwyOxVqpY6HMsgGuBa7BZvwRmYkvcXxIHEecy8rq/2DXfsmXLrGuvvfZsWFhYRJUqVRyDBw9OyN5u48aNwTNnzqyvaRpOp1ONGDHibJcuXdK7dOmS/ueff5Zv165deIUKFZz9+vVL/OuvvwBo3bp15kcffbT/jjvuaJSenm6y2+0qIiIirU+fPgcA+vTpk2Y2mzl48GDQsGHDkkAv1Z9KzqxxKiWzrtOlFei7ddnibwlv05ZGjZsW+PcQd+I4d988ivnLfwPg5jvv4fEH7yHyyvaYzGb+99QLVKmql0lWr1zGR2/NwmQ2U6NWbd78ZD7lgi+cD19851NuGhlJrRr69k8+dCeDx9+rf/bo/QWOsYRUBJ4G7sBmfQT4TNrYz1XQsdzDLBbLsubNm6eEhIRklEJcBRIfH2+qUqWKC2Du3LmVH3/88Xr79+/fblQ86XZn0PGE9AYpmY6LPzPmpZoEJSRXsMeXSPb1lOHQOHD0FI3XPEi5lMP5b5A/O/Ah8JQ88lZ8vPG697ZrPieutCzryaSM+lkO1yW1LRmhSWBiSgXH2QpF2bYEruXC2Ag8iC1xdWkf2Fv5dBv6888/X3PhwoVVXS6XqlChgvPTTz/Ns72rpDmcLvOJpIy68an2GpqMgGaEAOBO4GZs1ieBF2W4Sf/kLdd8ttRMR/DxxIwGaVmOEr8RFufpAPyCzboImIYtsczPC+HTJXRvcDols9rJpIz6Ba1i82Y+XELPbQNwK7bErSWx87JCrvsLc7o007GE9HrxaVk181/bu/lwCd2TA3gXeARbYoEG8/JHPtspzmiZdmfgvriU5scS0kP9IZmDX0123RHYiM36BDZroNHBCP+SmJZVac/J5Ah/SOZ+xALcDfyDzdojv5X9lST0IjiVnFl9b1xKRGqWo9BjtYtSEwDMRE/snYwORvg+h8tlOngmtdHBs2nN7U6X3Ch6p0bo1fDRZfFmXhJ6IWQ5XJZ9p1KaHU9Mb+QDMx8JXWvgD2zWF7BZfa7DkvAOien2intPpkQkptur57+2MJgJmA78ic1aqCF5fZ0kpQJKSMuqtDcuOSLVR3uwl3Fm4GFgEzZrK6ODEb5D0zSOJaTXPXgmtYWUyn1OO/QauvvKyrwQRW/7tVlLbD50bIleMzeypmmcSMyocyols27+awsvF4Z+1z4eW+KifNcW5yup696LrvlsdqfLfOhMWhNpWvNp5dCnbo3EZp3g74+1+nQJPXvmpbCwsPC//vorOPf7F1544ZIGQnY4XeYDp1ObeSbzuBPHuXPccK7t1YkRA65k6iR9WsLCyszI4P6J4xjSsyMjB3bnjrFDOXTg/LFR/lzzK+0bVeOzD9654L6SEhL43z23M6RnR4b268qs52w5n/2zaQMjB3ZnSM+O3Db6Wk4ez/vveeFXn3F5t37l2w8cw99bd+Ysn/niO3yx8IdCn58XqwgsdHeYKxN37WXB7t27A3Nf7/Xq1Wuzdu3aIo0qlpLhKL83LiW8sMl8787t3DJ8MNf17sywfl2Z+eDdZLhHXQRo26AKw/t3Y9SgHowa1IO//1yb537S0lJ5bOpdDO/fjet6d2bWczayn0g6evgQE0dew5XhDRk16OL9v56Mup/h/btx2+hrSU5KBPRCypTxIzgca+gTf6VtAHqHuZ5GB1KSfDqhz549u8b06dOP79q1a0fnzp3TPd/HxcVZPvrooyIn9LQsR/DeuJRWuQeJMZvNTLrvIRavXs83K9ZQv2Gji06AcjHDx93M4tXr+frH3+k98GqemHbvOZ8nJyXy2nNP0L3vgAvsQTfzobsJi7iMJb9uYOGqP7hx4mRAH/51xj2TeNj2HEt+3UCPPgN48YkZee5j9usv8uuKxamvPfkQz77+EQDbd+/jn517GTv06iKdnxdT6B3mvsNmldKXH9i7d2/QpVzvnuKSMmocOJ3a0uF0BTocjkJtG1iuHP97+gUW/fIXX//4O+lpaXz8zmvnrPPxgh9yhne+vEve8w19+MYruFxOvlmxhm9WrGHPjm2siNErlSpUqMhdDz/Cc2+8f9FY9u7awaED+1mwci0du3Zn6bfzAPj2y0/p1K0HDUIbX3R7P1QNWIHNOs7oQEqKzyb0CRMmNNiwYUOFJ598sl779u3Dcr+/5557GsbGxpYLCwsL79u3bzPQ79jvvffeuu3btw+rXbv2ZS+88EKN1157rVq7du3C6tWr12b27NlVAM6mZlUZOXpMqxGDegWNGHAld988itNxJwGoVqMml3fumhNHm/YdOXbkUKHjDypXjh59B+ZMCHFZ+07n7ee5x6Yx6d4HqVy5al67AODQgf3s+GcT4yfdlbMse07lHf9sxmyx0Lmbfhc/4sYJrF65jMyM8x8pNpvMZGRkqtS0DAIDA3C5XDxge5nXnnyo0OfmQ65Fr4K/8Li2wqssWLCgUnh4eKsWLVqEd+rUqeXGjRvLAeR1vQPMnz+/Svb1PW3atDrZyw8dOmQZPHhwkzZt2rRq0aJF+L333ltX0zQOnU1r1D6iRcNXnp2pxl7Tj8cemFyo+Bo1bkqLVvoUA2azmdZt23PscOG/H3bv3MaVvfqhlCIgIIArevRh6QI9IVurVOHyzl0JvsC0yNkCAgKwZ2XicrlIT0slICCQUydP8MOiBYy//a6LbuvHAoHPsFmLVgrzcj6b0OfMmXO4devWadHR0Yc3bdq0K/f7N95441BoaGjGrl27dvz000//Zm+Xmppq3rRp066VK1funjlzZoOjR48Gbt68edcXX3yxb/r06Q1PJmXUPBKf1uRh23Pqy+9/5psVa2jfuSvvvBp9XgxOp5Ov5rxP74GDL/l8Pv/o3XP2syJmESaTKd9979+7i1p16vH0jKncMLg3d4wdxs5t/wBw4ti58ySXr1CR8hUqcurkifP2c/8jTzBkxI0h0W99zMwHbuftT+YT2a87jer7fdeBMOAvbNZrjA5EXNzRo0ctEydObDJnzpzYPXv27Lj11ltPjRo1qqnL5eJC13tCQoJ58+bNuzZs2LDznXfeqXXgwIEAgLFjxza+66674rZu3bpz+/btOzZt2lT+9dlzwhLSsqoDJMbH8/mSlfmWgi8mLS2Vb7+ae941PGnMdYwc2J0Xn3iEtLTUPLcNb9OOH2MWkZWZSVpqCj8vjyl0wSG0aXM6de3BDVf34uihg0QOG8WLT8xg6iNPYrH4xdAZl+IJbNY52KwBRgdSnHw2oRfV2LFjz4I++UJgYKBrzJgx8QA9evRIS0pKsuw9fLIBwA/ffcOYwX0Y1q8rC7+cy+7t287Zj6ZpPPPIg1S0VmbcxDsvKaYP3niZw7EHuDdKv2k8HXeS919/iWm2828icnM4nWzbvJGrrh3OV9//wvjbJ3PPhBuwF3KGs/5XD+GPn79PXb3gA8oHB7No+WruvmU0M557g9F3TueR6DeLdG4+ohKwCJv10v4jRYlavXp1+RYtWqR37tw5HWDy5Mln4+LiArKTdF7Gjx9/FqBOnTqO+vXrZ+3ZsycoKSnJtG7dukoPPvhgw7CwsPA2bdpEHDx8pOLef/flFHmvHTnmnOlUC8uelcW0KbfStWcf+l39373isnX/8NX3v/DJd8uJP3v6gs11t065nzr16nPjtf25++bRtG7XAXMRkvDd0x5l/vLfeOndOaz79Rdq161H3QYNeWzqXUyddBPLFn9b5HP0AzcDy7FZKxsdSHEpc7dpwcHBOfOZm81mLSQkxKVpGofj0xsppXA6Hfz91x988dF7fLroR6pVr8EvP37P2y8/d85+omdO5+Sxo8z64HNMprzvi266fiAZ6ekEBAbx+ZKVea7zybtvsOqHpbz35XcEB+uzM+7YuplTcScZfZVeVR5/9iy/rPiB+DOnuWf6Y+dsX6dufWrWrpNTrd69zwAc9iyOHzlM7br6PMnZUlOSSUlOypk3+ULue/xFXnl8Kr+s3cCxk6eZ9+7z3HzfTH5es54+V/rtGC0m4B1s1orYEl80OhhRPHJf73a7PWe467///nunKSAoIPZ0aossp+uc7B1SPu+RUPft2cX/7rkdgHYdu+Q5xbHdbufhKbdSo2Ztpj9x7k15do1ZSEh5Rt80kSen35/nccoFB5+z7YdvvUrTFmH5nu+FpCQn8cl7b/DO5wv48M1X6XjFlUQOG8XIQT24JbIbFfyqnFoofYC12KyR2BJ9vpeg3yb0ypUrO5OTky86/zmAy6WpA6dTm6ZkOipnL0tKTKB8hQpUrlIVe1YW33w+55xtomdO53DsfmZ98DkBgRd+NPXT73686LE/nf0WPyxewOwvvqOS9b++dz37DeLnTf/NM/DYA1NoGdGGG287vz0v/LJ2lK9QkT07t9GiVWu2btqIpmnUrluP+o1Ccdjt/LX2Nzp368E3n82hV/+rCCp3ofFVNOYtWk6rZo1p06o5i39cTXYhxeD5kEvTC9isVmyJjxodiDhX7969U6dMmRK8fv36cp06dcqYPXt2lVq1atkbN25sP378eEBBrncAq9Xq6ty5c9KMRx9tcPtDj1dxujRL3InjaJqLWnXqXXTbpi3CcqYtzYvD4WD6XROxVq7CzOdnnVPKT0pIICAokODgEFwuF8uXLCSs9WV57iclOQmzxUJwcAhHDh3k67kfMevDLwpyenl67bknuOP+aQQHh5CeloZSSp9m2W4nK8uuj6tYdrUC1mGzDsKWuNnoYC7FJTyH7n3PjXrq0qVLWosWLdKbN28e0aBBg0zPdjUP6kSKI7RaRcc5t+NX9u5PzLdfc12vTlirVOWK7r2IO3EcgE3r1/Hlx7Np3KwFN17bH4C6DRox64PPChXfyeNHefmpR6nfMJTbRg8BuGhJ3tP8uR9x6uQJ7npoBkopnn71HZ6Ydj+ZGekEBgbx8nufEhgUBMCzr7/HU1EPkJmZSc1atXnmtXcvuN+z8Qm89cl8fvzibQCu6t2ND75YyGX9R9G4QT2u6pN3j1w/9Ag2azC2xAeNDsTrGHjd161b1/HBBx/sv/nmmxs7HA5ltVqd8+bN22cymQp6veeY+8VXx+6b+lDL6/pcoZRSBIeU57HoV/JN6PlZvuRbVv2whBatIhh9lf6EVHZJ/sC+PTwV9YCeSJ1OWrW+jOkezWp33TSSKQ/OIKJte44cOsjDk2/BYrFgNpt56PFnCYtoA0B6ehrX9uyEPSuT5OQkBnSK4Jrho7gv6vE8Y9q0fh0ZGRl07dkHgBtuvo3pd9/Gx++8xjXDRmO1VgLH2Us6bz9QE1iJzdrHlyd1KrOzrbk0TR04ldpMBo34T9Og+OTy9gR/mG2tuLyELfFho4Mwij9e9wDpdmfQgVMpLR0urWyXS938ZLa14hIH9MaWuDPfNb1QmesUB3qHtoNnUmUEKJGfh7BZ8++ZKHxGht0ZeOBUqiRzcSE1gZ+wWVsYHUhRlLmE7n7WNDQ54782cyEuYjo265NGByEuXabDGXjgdGpLh8slyVxcTG30AWjqGx1IYZW5hH4kPr1hYrq9mtFxCJ/yGDbrzUYHYQAXoGma5vND5NqdLsv+UzLBSnHLabEtQNOtj2mI/kjbhUf18kJ+28s9L8cS0uvGp2UVy/CQosyZjc26H1vihbs4+59jLpcrMS4urlbNmjXPKqV88lvbpWkciU9vnOVwBRkdizfKVA6TxVn4/1pNg1OpTlRmEgEZhZ/PwgeEAzHYrP2wJfrEIz5lJqGfTsmsdjols07+awqRp0D0SV26YEvcZ3QwpaFDhw4pGzduvDMhIeHdpKQkK/oY+D4nKdNVPcOhhRgdh7dymtPMwa68R6zLj8pMov7mlzE7/abPZG5XAPOxWa/FlujKd22DFTmht/mkTYlNn7r15q3F+mhMcoa9/PGEjEbFuU9RJlUDlmCzdsWWmGh0MKWhQ4cO6zZu3Njd5XLVxQeb6J769ewdp9Kc9xsdhzd7POjLf3qysfAjRmkaARmn/TmZZ4tEn8zJZnAc+fLLEvru3bsDFy1aZJ02bdqpTIcz4NDZtGZXdW2jXv3g85xnOUvL6pXLeOXpmbicTpqFhfPUK29RoeL5netdLhfPPx7F7z+tQCnFuNvuZMyESQD8umo5b7/8HP/u3smo8bcyzfbceduDPnDFA5PGk3D2DJd37sojz74MwNkzp3n4zgm8+8VCAgKkP9AlaoV+xx6JLbFwU3H5qA4dOqQAe/Jd0cuERsUMB+4zOg5v58g4llbO7BePnJWkx7BZ/8CWuNzoQC7G5+64CyJ7KkWXpqmDZ9KaOV1asdy4FHYqxbTUFGwP38usDz5jyW8bqVGrNrNfy3tU0Zhv57N/724W/7qBz5es4pN33+Df3fqjkA0bN+WJl95gwh33XPR4Md/Np1O3HixYuZYD+/ayd9cOAF568hHu+9/jksyLz0DgtXzXEoYJjYppD3yKjzYTCK9jAj7HZm2Q75oG8umEnt9UiuERrdtOunFUTtvZqh+WMP66gVzdrS2zX/tvDObTcSd5ePItjL2mH8P7d+PNF57O+ezqrpfx6rOPU5SpFH//eSVhEZfRuJn+SOPomybyw6K8J0NYvuRbho25CbPZjLVKFQYNGcqyRQsACG3SjJbhbfKdnMFiCSAjPQ2Xy4U9K5OAwEDW/LySStbKXHa5347BbpQp2Kxldg5KbxYaFVMBmA9Iu7koTtWAr7FZvfZJCZ9N6PlOpdi4iX3+j2vMr3/8Zc42yUmJzF30I18s/YlP3nudk8ePAfDoA1MYfdNtfLF0FfOW/cr2fzbz49LvcrYr6lSKx48eoU79/x5lrNugIafjTuRZ0j9+9Ah16/9381e3fkOOHztSqONFDhvF4dgDjL6qJ12696Zm7Tq8/8bL3DNNhiUvIS9js0YYHYQ4z1tAs3zXEqLwugAvGx3EhfhsG3peUylOmzat4YEDBwKcLiyYzOfdRQ2+fgQAVapWo17DUI4ePkhFq5W/1qzm7Om4nPXSUlOJ3fffUNCXOpViaQkJKc/L732S8/5F2wxumXIfh2IP8OGbrwBw+70P0jK8dPsR+LEgYK6753vh5qsVJSI0KmYscJPRcQi/djc26+/YEucZHUhuPpvQLybRTp6PpwUG/TfLmNlkxul05gyIMHfRigvOQlbUqRTr1KvPut9+yXl/7PAhqtesjSWPqvM69epz7Mhh2nborK975BB16hZ9oKKtmzZy9swpevW/ignDruaZ195D0zRmTp3CR9/E5LmN99+yeKX2wOOAVIMYLDQqpjHwjtFxiDLhA2zWLdgSdxkdiCefrXLv3bt36p49e4LXr19fDiB7KsXgqnWqBoVUDE5OTirQfkLKV6BTtx589PasnGVxJ45z8vjRfLfNnkpx/vLf8pwX+cre/di5bQsH/tU7CM/79EOuunZYnvsaEHk93375KU6nk8T4eJYvWcigIUMLdA652e12Zj1n46GZzwD67ExK6VOgpqUV7XlTcVFR2KxXGB1EWRYaFWMBvgRkfgZRGioAX2KzFmjK3tJS5BJ6cT8rXlh5TaX46edfHT2Tam/SvFUETVuEMaxfV+o3DMWzHT0vz74+m5eefIRh/bpSnFMplq9QEdsLr3H/bTfidDho1rIVT736ds7nowb14M1P5lOzdh2uGT6a7Vv+ZkjPDigU42+/i+at9ObZP39fzaMPTCE1JRlN01gRs5hHnnmR3gMH53ncT959nSHDb6BajZoATHnwf9x182gApj7yxCWdk8iTGfgUm7Wdr4wo5YceQW/fFKK0tEN/LPIVg+PI4TfTp7o0Te09mdwq0+EKNjoWX9UsKD45RKZPvRRvY0uUnu+lLDQqpiXwD/pofqKQ3g6YtXqw+a9eRsfho1KAVtgSC9eDuYT4bJV7bicTM2pLMhcGm4zNOtDoIMqgt5FkLoxRAXjd6CCy+UVCz7Q7A0+nZtU2Og5R5in0zjJyY1lKQqNibgT6Gh2HKNOGYrMOMToIKHhCd4E+l7g3OpaY3kDTNL+4OSkL/HjKRYAGwINGB1EWhEbFVMaLnwkWZcob2KyGD2RU0CSYoGmaIysry+uqtRLT7ZWSMxyVjY5DFFyWC3A5MNuTjQ6lpEzHZq1ldBBlQDRQ0+gghAAaoT++aqiC9nI/7XK5Vp88eTIyICDAbjKZvKJo5dI0jp5Nb6g5vX5WO5+QaXKaTI6S/a91aXAqMYOQuL+xZBXs0UIfVAF4ArjT6ED8VWhUTDvgdqPjEMLDVGzWudgStxkVQIESeocOHVwbN26cmZ6e3mbfvn018JIxSNLsrkopWVqQ0XH4C82cYg5ypZf0UTCln6Xh7jkovOK+sKTchs36GrbEnUYH4qeexk/6AAm/YUHvIGdYn44CP4feoUOHo+55kRsWZruSsuNUVoX3/k5c5Z/NsMZ4MXj2P2GuPZ1L9CAuJ4HpcZg0v5951Ay8CFxjdCD+JjQqpiv6HNVCeJs+2Kw9sCX+ZsTBC5WYO3TokAX8m++KpWB4VMxMZFSo4pV1ML2c8qvnwo0Wic3aF1viT0YH4meeNToAIS7iUWCQEQf2ySqr0KiYSsD9RschRAG8hM3qFU1U/iA0KqY/0NvoOIS4iIHYrIbMV+2TCR24F6hidBBCFEB7YJTRQfiRZ4wOQIgCMGSyJp9L6KFRMRWBB4yOQ4hCkL/XYhAaFTMYKNk+HkIUjyHYrJeV9kF9LqED9wBVjQ7CHyn8u9u5gbpgs8rEIZfuIaMDEKKAFAaU0n0qoYdGxQQDU42OQ4giuN/oAHyZ+7nzPkbHIUQhDMdmDSvNA/pUQgfGAtWMDkKIIhiBzXpp8/GWbdJsIXyNCZhR2gf0JTI1pfBVFuTvt0hCo2JqAKONjkOIIhhTmsNA+0xCD42K6YbeY1gIXzVJZmIrkomAjAgpfJEFuKm0DuYzCR2YZHQAQlyiasA4o4PwJaFRMSZkTHzh224trQP5REIPjYqxAiONjsPfKTQZAKXk3Wd0AD6mB/pMVkL4qjBs1m6lcSCfSOjoneEMn2tWiGLQ2ojnU33YGKMDEKIY3FIaB/GVhC7VlMKfjDA6AF8QGhVjQX5Xwj+MwGYNLOmDeH1CD42KqQ10NToOIYrRcKMD8BEDkMdUhX+oDFxV0gfx+oQODMU34vR5SsaJKy3hpT3ghI+S6nbhT24o6QP4QqKU0kwpkR5xpUr+ri/CPSrk9UbHIUQxuhabtUT7gnl1Qg+NiqkG9DI6DiFKgLQNX9wAoKLRQQhRjMqj/12XGK9O6MC16A/mC+Fv2mGzNjE6CC820OgAhCgBJTofgbcn9GFGByBECZJq9wvrb3QAQpSA3iW5c69N6KFRMWakur1USRt6qbve6AC8UWhUTH2gpdFxCFECLsNmLbEnN7w2oaOP2y5taKVKRoorZZ2wWcsZHYQXKtF2RiEMpCjBgqo3J3QpnQt/FwBcbnQQXkiq24U/K7F2dG9O6D2NDkCIUiCDJnkIjYpRQD+j4xCiBPUuqR17ZUJ3X9TdjY5DiFIgCf1cTYBSmz9aCANEYLPWKIkde2VCB1oDVY0OoqxRIGPFlT5J6Odqb3QAQpQwRQmV0r01oUvp3ABKOroboS42a0Ojg/AiktBFWVAiTcremtBleklRlkgp/T+S0EVZ0KokduqtCT3c6ACEKEWS0P8jCV2UBS1KYqfemtAjjA5AiFLU2egAvIF7quTaRschRCmoj80aXNw79bqEHhoVUxOZA9kQ0oBumKZGB+Al2hkdgBClRAHNi3unXpfQkdK5gaSTu0FqlsTdug+SGxtRlpSJhC7t56Iskp7u0MDoAIQoRcXeju6NCb1Eev8J4eUaGR2AF5CbGlGWlImELnfpoiwKNToALyAJXZQlZSKh1zM6gLJKOsUZSkroktBF2VIm2tDrGh1AWSUjxRmqTCf00KgYM3Lti7KlBjarpTh36FUJ3T0pS02j4xDCAGU6oaM/f242OgghSln54tyZVyV0oApyUYuyqawn9EpGByCEASoU5868LaFXNzoAIQxS2egADFasJRUhfIRfl9BlylQDKWlCN1KI0QEYTBK6KIv8OqGXMzqAskzJSHFGMmOzBhkdhIGKtepRCB/h11XuxdrjTwgfU5ZLqWX53EXZVax/996WQAOMDkCIC9E0HECmBnYNZddQdhfK4cJkd2FyOPWX04HZ6cTktGNx2jWLy45Zs2NxZRGgZRLgytQCyCKATPcrXQskg0D1r1YvKNrokzSOJHRRFvl1Qve2eEQp0DQ0wA5k6okSu5aTKJXDicnuxOR0YnY6MDsdmJx2zeK0Y9HsWFx2LFoWFlemFqBleiTKTD1RkkGgyiDAlKkFqgwCTekEqgwt0JxJoDmDAP2nFmjOICAgiwBLJgEBWVqAxf0+0I4lMAtLACgLJfs3GlCGE7o0t4myqFir3L0tgXpbPGXKJldzV3WVtN6umZ16idLyX8kyj2SZridLUyYBKkMLNOmJM9CkJ8dAcyYB5gw9WVoysxMlAZZMzRKQSWCAO1EGOrBYgED3qywry49sZhkdQFn1sP2Oy2c5hh+oQnJ6FZWcUV0lZVUlyVFNJTurqiStCinKqlLNFUgzl1cZgcFklQvEHmzBGWJCq6iU1K5cgmLtDOttCdTb4ilTHndM6PW4Y4LRYZRlZTmhZxgdQFmVSnDFPVqDikCRZlA24XJWJC25skpJqUJKalWVlFlVJWdUI8leTSU5q6pkVxWSqaxSTJVIs5RX6ZYQMoOC3DcFZpwVFFRUqkz+/duLc2felkDL4n+oENnKcik10+gARNG4MJkTqVA5UatQ+SAU6aYAIIT0VKt+Y5BaVSVnVCE5o5pKzKqukhxVSXJVUSlaFZJVJZVmrki6JURlBJYjq1wgjhAzzvLu2gJfa7pJK86deVtCL9aTE8LHpBgdgIGkhF7GpRFcPo3g8se1akW+KQjAkVWR1OTKKjWlKslpVVVyZlWVlOmuLXBVUcmuqiRjVanmiqRZyquMgOBzagtcFdBrC0prUI7U4tyZtyX0RKMDEMJAyUYHYCApoYtLZscSeBZrtbOatdp+KNKNgcLlqkB6slWlpVQhObWKSs6oSnJmNZWUVV0lOqqSrFVRyVpllaIqkWap4G5CKEdWuQAcIWZc5RVaJaUK9NSWX5fQk4wOQAiDZMZGRxZre5qPkRK68AoaJlMy5Ssla+UrHaFGkWsLypGZUSmnb0FyelWVnFlNry1wVFVJrqoq2ZWklU8YV4yxe1tClxK6KKvKcukcynZzg/BDGQSVyyCoXJxWpQZwoRuDlOJM6N42UpwkdFFWlfWEdtzoAIQwQHxx7szbErpUuYuyqqyX0OMAh9FBCFHKzhbnzrwqobvbEKWnuyiLThkdgJFioyNdwEmj4xCiFJ2NjY4s1kdVvSqhux0xOgAhDBBrdABe4JjRAQhRivYX9w69MaEX+0kK4QNijQ7AC0hCF2WJJHQh/FSs0QF4AUnooiw5UNw7lIQuhHeINToALxBrdABClCIpoQvhp2KNDsAL7DQ6ACFKUZlI6MVeDSGEl7MDR40OwgvsMDoAIUpRmUjo+4wOQIhStsf92FZZdwB5bFWUDcmUQK2c1yX02OjIZOCg0XEIUYo2Gh2AN3Df1Gw1Og4hSsHfJXET73UJ3e1vowMQohRJQv/PZqMDEKIUrC+JnUpCF8J4ktD/s8noAIQoBWUqoW8wOgAhSokTSWKe/jA6ACFKQYnkOG9N6H9S5FlohfApu2KjI6Uj2H+2AmeMDkKIEnQmNjqyRB7P9sqEHhsdGQ/sNjoOIUqBVLd7iI2O1IDVRschRAkqkep28NKE7iZVb6IsWGN0AF7oZ6MDEKIErSipHXtzQi+xkxbCi6w0OgAv9IvRAQhRgpaV1I69OaEvB2SwDeHPDpRUW5qP204Znx9e+K1DsdGRJTYiotcm9NjoyLPoneOE8FdSC5UHdzu6VLsLf1RipXPw4oTu9r3RAQhRgmKMDsCLLTI6ACFKwA8luXNvT+glevJCGCgTWGV0EF5sMZBhdBBCFCM7JXzNe3tC/xs4aXQQQpSAX2KjI1ONDsJbxUZHplDC1ZNClLKf3XOVlBivTujutjSplhT+aL7RAfiAr40OQIhi9FlJH8CrE7rb50YHIEQxywC+MToIH7AEqXYX/iEV+LakD+ILCf1n4JDRQQhRjJbERkcmGR2Et3NXTy43Og4hisHC0mhi8/qE7q52L/GqCiFKkfw9F5zU0Al/MLc0DuL1Cd3tU6MDEKKYnEae3iiM74DjRgchxCU4Tik90eITCT02OnI3MsiM8A/zY6Mj7UYH4Svcv6sPjI5DiEvweWx0pLM0DuQTCd1NSunCH3xidAA+6D3AYXQQQhSBE3i7tA7mSwn9CyDF6CCEuAR/xEZH/mV0EL4mNjryKHqPdyF8zcLY6MgDpXUwn0nosdGRCUjVm/BtrxgdgA97y+gAhCiCUr3mfSahu81Cqt6EbzoALDQ6CF8VGx25CthpdBxCFMIfsdGRf5TmAX0qocdGRx5ERo8Svun10uoY48eeMToAIQqh1GvkfCqhu71kdABCFFIi8KHRQfiBL4FdRgchRAEYUiPncwk9Njryb+Ano+MQohDeL+lJGcqC2OhIF/CU0XEIUQDPGFEj53MJ3e0FowMQooBSkVql4vQV0pYuvNsOYI4RB/bJhB4bHbkc+M3oOIQogFdioyNlCuBi4i6lP2l0HEJcxAyj+sv4ZEJ3izI6ACHycRp40egg/NB8YLvRQQiRh7Wx0ZGLjDq4zyb02OjItcBio+MQ4iKelrbz4ucupT9gdBxC5GG6kQf32YTuNg15Ll14pwPAO0YH4a9ioyNXAAuMjkMID0tioyN/NzIAn07o7klb3jU6DiHyMDM2OjLL6CD83FQgzegghAAygAeNDsKnE7qbDYg3OgghPPyFzONd4mKjIw8BzxodhxDozWt7jQ7C5xN6bHTkGfSqdyG8gRO4MzY6UjM6kDLiJeBfo4MQZdpWvORRap9P6ACx0ZEfIIPNCO/wemx05CajgygrYqMjM4F7jI5DlFku4PbY6Ei70YGAnyR0t9uR9jRhrIPATKODKGtioyOXAe8bHYcok96OjY780+ggsvlNQo+NjtwPPGZ0HKJMuz02OjLF6CDKqAeQqndRuo4AM4wOwpPfJHS3WYDX3C2JMuUj96NUwgCx0ZGpwHj0PgxClDQXcLO3jTPhVwndPeDEREAeFxKl6QD6I1TCQLHRkeuQKVZF6Xg+NjrS6/pt+VVCB4iNjtyOfLmK0pMFjIqNjkw0OhAB6LOx/WV0EMKvrcNL+8r4XUIHiI2OfAuYZ3QcokyYFhsducHoIIQuNjrSAYwDEgwORfins8Bo99+Z1/HLhO52O7DH6CCEX1sYGx35mtFBiHPFRkf+C4xBb+cUorhowHj3gEZeyW8Turuzwggg3ehYhF+KBW41OgiRN/ejbIZOlCH8zlOx0ZHfGx3ExfhtQgeIjY7cCtxtdBzC79jRq90SjA5EXFhsdORLwGdGxyH8wpfow4x7Nb9O6ACx0ZEfAbONjkP4ldtioyOl45VvuB1Yb3QQwqf9DtziC8M5+31Cd7sL+MHoIIRfsMVGR35qdBCiYGKjIzOAocAxo2MRPmkvcL17iGGvpzTN6286ikVoVEx5YDXQwehYhM+aExsdeYvRQYjCC42KaYN+/VcxOhbhM04DXd2dLH1CWSmhZ48kFYk+CIgQhbUKmGR0EKJo3P1prkHmexAFk45eMveZZA5lKKEDxEZHngSuAs4YHYvwKduA4d4yo5IomtjoyLXAMGQkSXFx6cC1sdGRa4wOpLDKVEIHiI2O3ANcizzOJgpmH3C1jATnH2KjI5cDI9GfVBAit+xkvtLoQIqizCV0yLlTvwZJ6uLi/gV6x0ZHHjE6EFF8YqMjF6OPJueVo30Jw/h0Mocy1CkuL6FRMX2BpUCw0bEIr7MH6BsbHXnU6EBEyQiNiokEvkauf+EHyRzKaAk9m3u2nEhA5rAWnnYDfSSZ+7fY6MgYYAAQb3QswlAp+EEyhzJeQs8WGhXTFfgeqGxwKMJ4u9BL5seNDkSUjtComNbAcqCu0bGIUncMuCY2OnKT0YEUhzJdQs8WGx35B9AXiDM6FmGojeht5pLMy5DY6MhtQDdkMqey5h+gi78kc5CEnsP9n9oZ/RElUfYsBXq5H20UZUxsdORBoDvgc48qiSJZBnT3tw6vktA9uC/qbkCM0bGIUvU2+iASqUYHIowTGx15CugDvGV0LKJEzQaGuGfk9CvShp6H0KgYE/AS8IDRsYgS5QDuj42OlC9wcY7QqJibgHeRHvD+JBN4IDY68h2jAykpktAvIjQqZhLwJhBgdCyi2MWjT4G6wuhAhHcKjYppD3wLhBocirh0e4FRsdGRm40OpCRJlftFxEZHzgb6A37VziJYC7STZC4uxt2vpgMyU6Ov+wK43N+TOUgJvUBCo2KqAh+gT8MofJcLiAYej42OlFHCRIGFRsXcgd4MV8HoWESBpQP3xUZHvm90IKVFEnohuC/qV5F2NV90HBgfGx25yuhAhG8KjYppDMwBehocisjfOuC22OjI7UYHUpqkyr0QYqMj3wM6oj+/KHzHMqCtJHNxKWKjIw8AvdE7y8o8EN4pGbgHuLKsJXOQEnqRhEbFBAFPoV/YFoPDERd2FngY+Dg2OlL+0EWxCY2KaYn++JOU1r3HUmBKbHTkYaMDMYok9EsQGhXTBngHuNLoWMR55gIPup8tFqJEhEbFjAReBBoZHUsZdhK9rXye0YEYTRL6JQqNilHArcDzQDWDwxH64ymTpXpdlJbQqJhywENAFFDe4HDKklTgFeBFfxwkpigkoReT0KiY6sALwARAGRtNmZSBXlJ6JjY6MtPoYETZExoVUw/9KYpxyHdASXIA7wNPyFDN55KEXsxCo2K6oF/UvQ0OpaxwAB8BT8p0p8IbhEbFXAY8AoxAOh4Xt2+AGbHRkXuNDsQbSUIvIaFRMVcBzwLtjY7FT2nAPGCmXNzCG7k7zs0AxiKdZy+FAz2RvxQbHbnR6GC8mST0EuRuX78OsAFtjY3Gr3wPPFIWRn4Svs/9/HoUenNcoLHR+JRk9Kr112KjIw8ZHYwvkIReCjwS+/1AL2Oj8VlOYAH6Xfp6o4MRorBCo2JqAjcDtwPNDQ7Hmx0BXgPej42OTDQ6GF8iCb2UudvX7gZuREacK4gE4GPg9djoyFhjQxHi0rlv8HsDk4BhSKkdwA4sQR+J7wcZmrloJKEbxD0+/ERgCjKbU162oM9T/llsdGSa0cEIURLcT8eMB0YBXSh7veP/QJ885avY6MjTRgfj6yShG8w993p/4Ab0yV8qGxqQsWKBr4AvYqMjtxocixClKjQqpg5609xQoA/+OW2zHfgdfQa7b9zD6YpiIgndi4RGxQQCg4DRwLVARWMjKhVxwNfod+l/yBCtQkBoVIwViASuQa+er2NoQJfmIPp8Cj8Aq2KjI1MMjsdvSUL3Uu7Rpwa7X/3wn2p5DdgErAB+BFbHRkc6jQ1JCO/mfgSuF9DN/fLWTnUOYDuw3v36LTY6cqexIZUdktB9RGhUTBOgL3py7wvUNDaiQjmInsBXot+hS1uZEJfA3fbeHmjl8QoHapRiGKeB/cBuYIP7tSk2OlJmojOIJHQf5O4lGwF0Bi53vy7DO8aRPoJeAs95xUZHHjQ2JCHKhtComGroyb0B+k1/LffP7FcN9KdrzOiD3Xj+NKGPj56YxysevY/LfuAAsF/GT/c+ktD9hDvJhwKt0e/UGwH1gXrunzUovh60Z9ETdyz6xR2LXs22SUrfQghhDEnoZYS7w11d96si+l16MFDO42c59F6oae5XqsfPVPQqtmOx0ZEZpR2/EEKIi5OELoQQQvgBmQlICCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAldCCGE8AOS0IUQQgg/IAld5EspFaqU0pRSE4yORYiyRCnVSSm1VimV6r4G2ymlrlJKbVZKZbiXVTY6TuEdLEYHIIQQ4nxKqQDgayADeABIAw4DvwLbgbuATCBVKTUD2KFp2ncGxVoNuBUYArQCAoBdwKuaps0zIqaySBK6EEJ4p6ZAI+B2TdM+AFBKXQVUBB7TNG1l9oruhP4N8J0BcQJ0BZ4BvgeeBhzAcOArpVS4pmmPGxRXmSIJXQghvFNN98+EfJZ5g+1Ac03TDmYvUEq9DawEpiulXtA0LdWw6MoIaUP3ckqp3kqpDe72sn1KqTuUUjallOaxzi1KqZ+UUnFKqUyl1A6l1OQ89tVRKbVcKXVaKZWulDqglPoo1zqVlVJzlFKJSqkEpdQnQOULxBamlPpGKXXWHd8GpdS1uY6nKaVuzmPbQe7PrrmU348Q/kgpNQdY7X77tfta+QX4xL1svXvZHPd3QXngZvcyzb092d8VSqkWSqnP3Nf1KaXUU0rXQCm1SCmVpJQ6oZR6MFccgUqpJ5VSG93bpiqlflNK9fFcT9O0A57J3L1MQ68xCAKaFOsvSORJSuheTCnVHlgGHAceB8zATOBUrlUno98hL0av6hoCvK2UMmma9pZ7XzWBH93bRqPf4YcCwzyOp4BFQHfgXWAnMJT/vkQ8Y4sA1gBH3ftLBUYB3ymlhmuatlDTtA1Kqf3u5bn3MRqIB5YX8tciRFnwHvq1NQN4HVgPnAR2A5PQvwcOAPvQS8EfAH8Bs93b78u1v3no13MUEAk8CpwF7gB+AqYD44CXlFLrNU371b1dJeA24EvgffTq/onAcqVUZ03TNudzHrXdP08X/NRFkWmaJi8vfaEn6FSgrseyZoAd9w2we1lwHtsuA/Z5vL8e0ICOFznede51HvZYZkbvhKMBEzyWrwT+AYI8lin0JL/HY9mzQBZQxWNZIHoy/9Do37G85OWtL6C3+7ob4bFsQl7XMZACzMljHzb3+u95LDOjd65zAdM9lldG73g3J9e6gbn2WRk4kd/1C1RFvwn51ejfZVl5SZW7l1JKmYH+wHeaph3LXq5p2r/AD57rapqW7rGdVSlVHb26rolSyur+KMH98xp379m8DEYv4b/jsW8n8Eau2KoCfYH5QEWlVHX3Mauhl7ibK6XquVefh97jdZjHLgaifylI71chSscH2f9wX9Mb0G/AP/RYnoBeA9DEc11N07IAlFIm97VvcW9/+YUOppQyAZ+jX+f3FON5iIuQhO69agLBwL95fHbOMqXUlUqplUqpVPTEfQq9ZAyQndBXAwvQq+5Pu9vNblFKBXnsqhFwXNO0lFzH253rfTP0L4On3MfyfD3hET+apm1Bf3xltMf2o9Gr4H7K88yFEMXtUK73iUCGpmm5q8ITgSqeC5RSNyul/kF/fO4M+nUeyX/fLXl5A7gKuM39HSBKgbSh+zilVFNgFXrSnIpelZaFXtp+APdNm6bXgY1QSl2B3sY+CPgIeFApdUUeSfxism8EX+LCbeCeNx3zgEfcpfhk4FrgS03THIU4phCi6JwFXAb6zbr+D6VuBOagd257EYhzb/c/9Mfqzt9YqceBKUCUpmlzixyxKDRJ6N4rDv2OuFken3kuG4Lei/RaTdNy7sJz90LNpmnaOmAdeoIdi14tdgN6ldxBoJ9SqkKuBN8y1272u3/aNY9nYS9iHnrNwHD0NrVKwFcF2E4IUTBa/qsUyQj0632Yu1AAgFLqibxWVkrdhd5uP0vTtOdLKCZxAVLl7qXc7VwrgeuVUnWzlyulmgFXe6yafZfteVdtBW7x3J9Sqoq7F7unze6f2dXu36Pf5E322M5MrjYwTdPigF+AO5RSdXLHrpSqkWv9ncBW9Kr20ei99n/NvZ0QoshSucDjpZcor++XLugDyZxDKTUavUf+5+i1haKUSQndu9nQO5CtUUq9g97j9G5gG9DOvc6P6FXsS5RS7wEVgNvRS/ieyfZmYIpSaiH6Iy0V3esloSdygCXovdSjlVKhwA70zmx5tZXdBfwObFVKvY9+F18L/UKvD7TNtf484En0WocPNU1zFeo3IYS4mI1Af6XUVOAYcEDTtD+LYb9L0b8DFiqlYoDGwJ3o3w0VsldSSnUGPkVvY18FjMtVfliradp+RImShO7FNE3bqJS6Gr2t+in09vGZ6GMlh7nX2a2UGoE+3OJL6I+TvIPeccVz0JjVQGf06vVa6J1f/gLGaZp2wL0vl3tgmFnAjejVeIuBB4FNuWLboZTqiF6VPgG9h3uce70n8zidee4YQ5De7UIUt6noz6A/jd6Z9hOgOBL6HPRnye9A73ezA/27YST6Y3XZwtEfR63Bud872W7hv6Y6UUKUR7OI8BFKqe+ACE3TmhsdixBCCO8gbeheTikVnOt9c/Qe7L8YEpAQQgivJCV0L6eUOo5e7bUf/Tnxyeid2NprmrbXwNCEEEJ4EWlD937LgDHo7ViZwB/ADEnmQgghPEkJXQghhPAD0oYuhBBC+AFJ6EIIIYQfkIQuhBBC+AFJ6EIIIYQfkIQuhBBC+AFJ6EIIIYQfkIQuhBBC+IFCDSyzcePGCkBd5EagrHABxzp06JCS75rCb8l1L7yAfBcVQIEHltm4ceMVJpPpXZPJZMVjblzh1zSXy5Xocrnu7NChwzqjgxGlT6574SXku6gACpTQN27cWMFkMv1euXLlWjVr1jyrlJLh5XyEpmnYnVqA3ekKtDu1ALvLFehwagH6f7tm0kBpGkoDVdOcklXOlRaYs6kyu04lZVqSzxxPabn6jjcCMs+eAOKB48B+bIknjDovUfLkuvctTpfL5HBicbhcAQ6XZnG4NIvTpVkcTs3i1LQAp1OzONHMuK93QJXDaa9LvOOMuZJKdAYGKoVmQmlK4TIpnBaTyW4xK7vFpOwWk8lusSh7gEnZLSblzDXfeYnSNE3FxcVVTUhIOOlyubpLST1vBa1yr2symaw1a9Y8W758+fQSjUgUmt3psqRlOYOzHK4gu9MVmOV0BdodriC7Swt0Ol2B534LKy5U0AoyubRgV0b5nAUa1Cynkaa0EKcl5KmAzLPnbmCzpqJPGrMf2AfsATYC/2BLzCq+MxQGkeveS2XYnUFpWc6Q9CxHSLrdFZLpcJZ3ujTz+Wt6XO95NJiYMFFOmTCZA4AAswY4PT7PcqFXdoPnP1BKaRaTygowmzKDA82pIYHm1PKBltRAi8lRHOeXl5o1a55NSkqyulyuuujfNSKXgiZ0E6DkDt072J0uS3KGo2JKpqNiWpajYpbDVa6kjpVzE5733Xh5oI375SkLm/UfYAOwHvgL2I4tUf5+fItc914g0+4MTMlylE/PcpbPsLtCMuzOEJeWV/IuKg3tAhf4BbfQNGV3akF2pysoLctR6Yx7eYDZlFUuwJwaHGhOLe9O8iZT8fz9uP8OFdKX44KKPtuazdqhGOPIte/EjSW2bx/kTuAVUjMdlVJLOIEXk0Cgo/t1p3vZSWzWlcBy4EdsiSeNCk4UXWhUTIlc97HRkXLNu2maRkqmo3xSuqNycqa9cmlc78V1x6Y37bkCkzPsVQAUSgsKMKVXDLIkWEMC4kMCLRnFdCiRB7+809m9e3fgCy+8UMNzWb169dqsXbs2uLRj2bt3b2Dfvn2bhYaGtm7atGnEM888UzP7s0ceeaR206ZNI8LCwsLbtm0b9vPPP4eAfkEnpGVZD59Na7D7RHJ49Gvvtm1Up3rTAT261Li+35XlJo4akrP/919/iVGDeuS8urVqyItPPJJnLE9G3c/w/t24bfS1JCclkn2sKeNHcDj2QIn+HoBawDjgU+A4NutmbNbnsVk7l/SBhSgOYWFh4fHx8SXynel0aaazqVmVD55JDd1xPKntgdOpYWdSM2sXNplv2/w3Nw8dxMiB3Rk1qAd/rvk157ODB/Zxx9ihjBzYnaH9urJs8bc5n3mW0BPiz57znTKkZ0cuD61OYnw8AOOG9M/5bFi/rrRtUIU9O7edF8uRQwcZO6Sfurpn55Dnnnu27r9xKRG7jie1XrVmQ6O+/fq3lJk+i59fzoe+d+/eoI8++qjGtGnTThXnfu12OwEBAQVe3+Vycf311zd98MEHT9x6663xAIcPH7YArF27Nvjjjz+usXPnzu1Wq9X19ttvV7333vtCf/h1XVJiur2a06Wd83/TqWsPZn34+XnHuP3eh7j93ocAyMrMpH/HVkQOHXneent37eDQgf0sWLmWd2e9wNJv5zFmwiS+/fJTOnXrQYPQxuj93UqFAtq6X9OwWfcBXwJfYEvcWVpBCFEQ2df9rl27dhTnfh0ulyk+1V41Kd1eJc3urKhp2iX1MtM0jQduH89Tr7zFFT16E7v/X+4Ycz2LfllPueBgZk6dwnWjxjFszE2cPXOasZF96NapE6H1AvDMrZWrVGX+8t9y3n/y7hts+HMN1ipVAPh8ycqcz1bELOLdV5+nRavW58Uz75MPuOHm2xg8dCRD+17BmFsmoZWvEPTYjOlBjz73CjuPJ19WsZwlwRocEF+xnCW5NDvZ+SufLqEvWLCgUnh4eKsWLVqEd+rUqeXGjRvLAdxzzz0NY2Njy4WFhYX37du3Wfb68+fPr9KuXbuwevXqtZk2bVqd7OWHDh2yDB48uEmbNm1atWjRIvzee++tm/1ZvXr12kyePLlemzZtWg0fPrxxYeJbvHhxxcDAQC07mQM0aNDAAaCUwuFwqITEJMvplMxqx84m161Zv1Hw2dSsWrmTeUH9tDyG2nXrEX5Zu/M+CwgIwJ6VicvlIj0tlYCAQE6dPMEPixYw/va7inK44tQUeBTY4S65P4zNWjO/jUTZs3LlyvIdOnRo2bJly/AWLVqEf/bZZ5UBfv3115D27duHtWjRIrxNmzatfvzxx/IAN9xwQ6OZM2fWyt5+165dgdWrV2+bmZmpFi1aVLFdu3ZhrVq1Cm/WrFnEq6++Wj17veHDh4eOHDkytGPHji1btGgRAaCU6nD69GkzwKRJk+q3bt26VVhYWHjHjh1bbtmyJSh7W6VUh6ioqNpt2rRpVa9evTavvfZatezP/v7773JX9ugR1iKsVbvwiDbtX3vzrUapWY5Kp06eUA9PvoWx1/RjeP9uvPnC04X+3STEnyX+7Gmu6NEbgNAmzahYycrvv+gJePeO7XTvMwCAqtWq06JVa5YuXmhWgHaRRxIXzvuMoaPH5/3ZV3MZekPen1kCLKSnp+Gw29FcLpTJxNdzP6Jrzz7Ub9gIh8sVEJ+WVSP2TGqLHceT2h6NT6+XaXcG5rkzUSA+m9CPHj1qmThxYpM5c+bE7tmzZ8ett956atSoUU1dLhdvvPHGodDQ0Ixdu3bt+Omnn/7N3iYhIcG8efPmXRs2bNj5zjvv1Dpw4EAAwNixYxvfddddcVu3bt25ffv2HZs2bSr/0UcfVcne7uzZs5YtW7bsXLx4caHqpbdt2xZctWpV+zXXXNOkVatW4QMGDGi6Y8eOQIA2l3dSEyZNyQpr2bJNRPMmoZ+8/25Q1JPPX3Bfm9avY9SgHtx0/UB+XPpdnuss/Oozrr/AxRXatDmduvbghqt7cfTQQSKHjeLFJ2Yw9ZEnsVi8qqKmLfACcBibdS42ayejAxLe4eTJk+bRo0c3e+aZZ47u3r17x86dO3cMGDAgOSMjQ40ePbrpo48+emzPnj07XnrppcNjx45tlpiYaJo4ceLpL7/8MidRv/fee9WHDh16JigoSOvWrVvahg0bdu3cuXPHmjVrdr344ot19u3bl1MF988//4SsWLFi74EDB7bnjsVms53Ytm3bzl27du2YNGlS3N13393Q8/OgoCBt69atO5cuXbp3xowZDTMys0xHzybXGDpiZPi1o28u/83KP8zfrFjDgMjrAHj0gSmMvuk2vli6innLfmX7P5sveJ1fSJWq1ahRsxbLlywE9Or32P3/cuzwIQDC27QlZuF8AI4cjGXLxr846v5Mu0A+37zhT5ISE+jZf9B5n504doSN69YSOWxUntuOveUOfloWw/jrB3LTHXeTkpTEiu8Xc+Ntk89b1+nSLGdSM2vvPpncZv+plGYJaVmVpEq+8Lzqm7wwVq9eXb5FixbpnTt3TgeYPHny2WnTpjXMTtJ5GT9+/FmAOnXqOOrXr5+1Z8+eoGrVqjnXrVtX6cEHHwx48MEHAUhLSzPt2rUrp+3q1ltvPWMyFf7ex+FwqHXr1lVavXr1zo4dO2ZEP/9CzZGjb2j57Yrfnfv2Hwhe/sP3LPltIzVr1+HLObOZdtetfPLtsvP207P/IAYOuZ7g4BD2793NneOGUbtuPS67/L9cd+zIITavX8cLb314wXjunvYod097FICfl39P7br1qNugIY9NvYvUlGTGXdvXcsu1vQp9niUkELgRuBGb9U/gDWA+tkS7sWEJo/z8888VGjdunHHVVVelAJjNZmrVquX866+/gk0mE8OHD08CGDRoUEq1atXs69atCxk0aFCKw+Fg9erVIT169EibP39+te+++24vwMmTJy3jxo0LPXDgQDmz2awlJCRYNm3aFNy0aVM7wHXXXRdfpUoVV16xLF68uNK7775bMzU11exyuUhMTDznu3TixIlnAMJbX+YyWyxqzT//XpaYlGjOyszk6utH5KxXpWo10tJS+WvNas6ejstZnpaaSuy+fymsWR9+zqxnn+DDt16laYsw2ne6ArP7hv2pV9/h5aceZdSgHtSp14DOV/bKuZm/UAl94VefMWT46Dxv+hfN/5Ke/QdRpWq1PLaEGrVq8+7nC3LeP3TnBB587GnWr/2N+XM/IjAwkHujZlK3/jn3QqRkOqwpmQ5roMWUUa180Mlq5QPPFFdPeX/nswm9KIKDg3MuTrPZrNnt9pyBdf7++++dISEhef7RVKxY0ZnX8o0bN5YbN25cE4BOnTqlzJ0795Dn540aNcpq1apVWrv2l9uPxqfX6zvsxpoz/hdlSknPZNX3i2keFk7N2nrN/3WjxhH92HTsWVkEBJ5b6+R5wTRp3pLufQewaf2f5yT0RfO/oPfAq3PauS4mJTmJT957g3c+X8CHb75KxyuuJHLYKMYOvCLwhgFdCA72uk70XdyvF7FZXwTewZYovWXFBXm2x44dO/bM+++/Xz0pKSm+SpUqjk6dOmUATJo0qdHAgQMTly1bts9kMhEeHt4qPT095869QoUKeV73e/fuDZw+fXrDtWvX7oyIiMj8888/g/v379/Scx1zYDlL7JnUBsnp9qpms4Ush+PCj5m5v4PmLlpBULmLX3sP3nEzh2P3AzD7q0VUrlL1nM9bhrfhnc++yXl/fZ8uNGsRBkC9Bg15ZfanOZ9NvnEEzXr01ACVV/N9WmoKPy79ji+WrsojZI1FX3/OI8+8fNF4s638fjH1G4USFtGG6/t04fMlK9n+z2befvk5nn71nTy3yXK4yh1PTG8Ul5xRr0pI4KkKFldCgQ5WhvlslXvv3r1T9+zZE7x+/fpyALNnz65Sq1Yte+PGje2VK1d2JicnF+g5TavV6urcuXPSo48+mtOmHhsbG+BZ9XYhHTp0yNi1a9eOXbt27cidzAGuu35oyomTccGrN+2+7ExqZu1fV/1oaty8JQEBAdRrFMqmDX+SlqoPePTryuU0atLsvGQOcPL4sZx/nzkVx/o1vxHW+rKcZS6Xi0XzP79gW1Zurz33BHfcP43g4BDS09JQSqGUwu5wqCy7VxeA6wCvAPuwWe/GZg3KbwPhP/r165dy8ODBoGXLllUAcDqdnDx50nzZZZdluFwuFi5cWAlgxYoV5U+fPh1wxRVXpAHcfvvtZ2JiYqq8++67NcaPH386e3+JiYnm0NDQTJPJxA8//FBh9+7dIQWJIz4+3myxWLSGDRvaXS4Xs2bNyunvYXe6LACxZ9LDk9LtVT1LCKFNm1MuOIQfvvsv4cafPUNI+Qp06taDj96elbM87sRxTh4/et6xX37vE+Yv/435y387L5kDnDr53+CNC774hODgEDpf2RPQvztcLr1Ms+aXVezfu4vrho5wQd4l9GVLFtIiPILGzVqcd5y/1vyK0+Gga88+F/o15UhKTOTzD9/lzvunA5CRnoYymTApE2mpqflu73RpltMpmXViz6S3SLO7Kp1MdRS8Z3IZcwnPoRv7rHjdunUdH3zwwf6bb765scPhUFar1Tlv3rx9JpOJLl26pLVo0SK9efPmEQ0aNMj0bEfPy9dff31gypQpDZo3bx6hlNKCg4Nd77777sHsqrfCcro0U1xyRs2zaar2o9GzzHfdPApN06hQsRIvvPkBAP2uuobtW/5mTGRfAgMDCQ4JIfqN93P2cddNI5ny4Awi2rZn3icf8POKHwiwWHC5XNx422S6uC9SgHW//YIymejSPf/q8k3r15GRkZFzId5w821Mv/s2Pn7nNW4Yfp3dWqmiL3RKqYteBT8Nm/UZ4COpii8dRj4vXqNGDedXX3217+GHH25w7733mkwmEzNnzjw6duzYxHnz5u277777Gk6fPr1+UFCQ9vnnn++zWq0ugNDQUHvbtm1TV61aVfmTTz45mL2/p59++uj999/fMDo6um5ERETaZZddln92ATp37px+7bXXng0LC4uoUqWKY/DgwQkAxxLS655NzaoFeSdIi8XCax9+znOPTeeDN1/BZDIx6qaJjLzxFp59fTYvPfkIw/p1RSlFcEh5Hot+hVp16hXqd7Tgi0+IWfg1aBqNm7Xg1Q/m5tRWrF65jI/emoXJbKZGrdq8+cl8ygUHAymsWP69WvXjj9hefD1nX999NZdhY27O8zgLv5rLdaPGUZCmyFnPPc6dU6Pcx9KfzBkb2ZeAgABsL75R4HPTNM2ckqVVif49YdmU72OmAV/ERkdKVbyHgo7lHmaxWJY1b948JSQkRKo6L0DTNM6mZlU9mZRZ3+Fy+dxdZLPA+JQQR0IFz2UZDo0DR0/ReM2DlEs5bFRo+dkPPIgt8TujA/Enct3nz6Vp6lRyZo3TKZl1ivp0ipFCcGY1NsU592i1A+2aKsbR54qf5sgi7tgRbD/HcTTZCfow0w/FRkf+Ymxk3sNnq9y9TXKGvcLeuJRWRxPSG/tiMvdxTYCF2KwrsFlbGR2MKBvOpGRW3X0iufXJpIwGvpjMPV3ssTUv1gH4OTQqZkloVIxc90hCv2RZDpflwOnUJgdOp7bMsDsL1AYnSkx/YAs263PYrPJ/IUpElsMVsP9USrOjCemN7U6XLzRR5cvH662vAbaGRsXMCo2KKfXRQL2JJPRLkJCWZd0blxyRPW6x8AoBQBSwHZu1v9HBCP9yJiWz6t6TyREpmQ6r0bEUJ03z+WHazMB9wKbQqJgyO5y0JPQicLk0dehsWsNDZ9Oa+XpVmx8LBX7EZn0dm7VM37WLS+dZKncW60xn3sHlm1XueWkJrA2NinkyNCqmzDV9SkIvpNRMR/CeuOTwhLSsGvmvLQymgHuAv7FZOxodjPBNp1Myq/ljqdyPmYHHgHWhUTHhRgdTmiShF5CmaZxIzKi1/1RqKx+YvlScKwz4A5t1Jjar35WuRMnIcrgs+0+lNDuWkB7qj6XyMuByYGNoVMyDoVExZSLXFbm6uKTmRQbvmxs5y+EKOHQ2rXFalqOi0bGIIrMATwD9sFlHYkuMy28DkQebtWSue4PHtcgtJdMRcuhMWjN5YsXnlQNeAoaERsWMi42OPH+0Hj9SJu5a8rN48eKKbdq0adW0adOIZs2aRdx55531nU591Mf41KzKe+OSIwqSzI8cOsgNg3vnzBP80J0TSEpIAPRhFO8cN5xelzWle0SjAsV15vQp+rRvwf0Tx+UsW/XDUkYMuJJRg3owtO8VvPH8U+Q1loDdbuf+ieMYObA7D9w+HofDAUBmRga3DB+cE1cZ1BPYKPOw+6bPPvuscpMmTSLCwsLC//rrr2LrG7F06dKK33zzTSXQO74dOJ0aVphk/s+mDYwc2J0hPTty2+hrzxnd0dO2zX9z0/UD6dK87jnXdbYNf6xhbGRfhvbrytC+V7Bl41/nrVP813aZGCe9F/BXSRZEvYHfJHT7JQxZWq1aNce8efP27du3b/s///yzY/369eXffPPNaofPpjU4HJ/W1OkqWHVbzVq1mbPgB+Yv/41vV/1BjVq1eefVaAAslgBumXIf7335XYHjeirqAXr2O3eWoyt69MoZ+nH+sl/547df+GlZzHnbrl29ikqVq/D1j79TsZKVNe4pFGe/9iI3TLidSpUrFzgOP1Qf+BWb9VajAxGFM3v27BrTp08/vmvXrh3ZEzNdKrvdzk8//VTx+++/tx6JT6t/NCG9cWHmJne5XMy4ZxIP255jya8b6NFnAC8+MSPPdWvUqsXDjz/HQ48/c95ncSeO89jUyTw96x0WrvqDeT+spnGzluetV9zXdlnI5m51gV9Do2KGGx1ISfHphK6U6vDAAw/Ubd26dau77767/l9//RXcoUOHluHh4a2aNm0a4Tnn+dSpU+tGRkY26du3b7OmTZtGXHHFFS1OnjxpBrjyyivTw8PDswBCQkK0iIiI9D0Hj9aOT8sq1JzcgUFBOcMbOp3OnHHSsz/rcmVPKlYqWL+ab7+aS70Gjbi8c9dzlpevUDFnuMXMzAzsWZnnTESRzWIJICM9DdDHTg4ICGTPzm0c2LeXQUOGFua0/FUQ8CE269vYrFKt6gMmTJjQYMOGDRWefPLJeu3btw8DWLBgQaXw8PBWLVq0CO/UqVPLjRs3lgO9xB0WFpbTIWr9+vXl6tWr1wZg9+7dgRUrVmw3efLkeuHh4a2ee+65mp9++mmN7xYtqtG/e5da7856oVBx7fhnM2aLhc7degAw4sYJrF65jMyM8wfXq1WnHm3adyAw8PxpCOZ/+iFXXzeCJs31JB4YFEQl6/nfF8V+bftL//aCCQG+Do2KyfuOy8f5dEIHfda0bdu27XzvvfeONG/ePPP333/fs2PHjp1btmzZsWTJkiqrVq0qn73u5s2by3/xxRcH9u3bt7169eqOWbNmnddTPfbgocDvf1hWvXu/q4vU8c2elcWoQT3o1bYphw7sY/LUqELv48ihg3wz92PucU91mtvmDX8yvH83+rRvQeduPekzaPB563Tt2YfyFSoycmB3KlSqROcre/LSk48y/YnnCh2Pn5sMLMNmlf4RXm7OnDmHW7dunRYdHX1406ZNu44ePWqZOHFikzlz5sTu2bNnx6233npq1KhRTbMnILmYlJQUc0RERMaOHTt2Pvy/RxJHjZ/I4KGj1Pzlv3Hn/dMKFdeJY0eoU69BzvvyFSpSvkLFcyZKKYh9e3eTmZHBpDHXM2pQD557bBppaecPL1/813aZqHL3pIBnQqNiPgmNivGLgYGy+XxCnzx5cs7sSWlpaaYxY8aEtmjRIrxDhw6tjh07Frhx48acEcN69eqVWLt2bSdAly5dUvbv33/ObXLc6TOB11x7XcSEyfepiLbtixRPQGAg85f/xs9/7yG0WXO++XxOobbXNI3HH7qbqKdfyCnt59auYxcWrFzL8j+3sWPrZv7+c+1565hMJh5/4TW+/vF3ZkbP4qs579Nn0GAcDidRd9/G1Ek38eeaX4tyiv6oL/AzNqs8iuhDVq9eXb5Fixbp2VXvkydPPhsXFxdw4MCBfGtcLBaLNnny5DOJ6fZK++JSWmlKGT6ehNPhYONfa3npnTl8vvQnkhITeOfl6PPWk2u72NwErAqNiqludCDFxecTevaMSgBTp06tV61aNcf27dt37N69e0eXLl2SMzIyciqUypUrl3MnajabNYfDkfPZyVNnyg0cdHXr3gMjTTdNuivPY+3bs4tRg3owalAPnn3koYvGFRAYyPWjxrF0wbxCnU9KchJ7d25n+pRbubrrZbzy9GP88evP3H7DdeetW7Vadbr3HcCPMYsuus9jRw7x208rGH3Tbbz10jMMHzeBp155i+iZ0wsVm5/rAKzBZg01OhBx6QICAjTPkrrnPOcA5cqVcyVlOCsfOpPWzJXPI2lJiYk51/39t9143ue169bn+NH/Ji5KTUkmJTmJGrVqFyrm2vXq06PvQCpVrkxAQABXXzecfzatv+g2cm1fsu7oneXO76zgg3w+oXtKSEiw1K9fPysgIIAtW7YErVmzplJBtjtx+kzIVVcPDu/Wp7+adN+FE3XTFmE5HdJmPPPSeZ8fO3KIdHfblsvl4seli2jRKqJQ51CxkpVft+7nhz/+4Yc//mHqo0/RtWcf3v9KT9oH/t2TM6dxakoyv636Md9jvPD4/3j48WcwmUx6uz4KZTKRkUd1XhnXHD2ptzY6EJG/3r17p+7Zsyd4/fr15QBmz55dpVatWvbGjRvbW7ZsmXns2LGgY8eOWQA+/vjjaudsrJQ6Ep/eREPv/Fa+QkWSk5LyPE4lqzXnup/1wWfnfR5+WTscdjt/rf0NgG8+m0Ov/lcRVK5wrXaDrx/B+rW/kZWZCcDvP6+kZauL/ykWz7VdthrR89AYWO0PE7wUuZrJ254VB5g5c+axCRMmNPnyyy+rNWrUKPOKK67I+wr1kJxhL//sC6+22Lblb5WensZPPywBYEDkddx+78VL4bnt2bmdN194GtATeqs2bZn+5PM5n48YcCXxZ8+QkpzMgE4RdOrWnWdfew+AUYN68OYn86lZu06e+862fMlCli9ZiMViwel0MiDyOoaNuemC63+/8GtahLemWUv9b/XWKffz5PT7sNvt3H7fw4U6vzKiLvAbNusAbIkbjA7G63jR8+J169Z1fPDBB/tvvvnmxg6HQ1mtVue8efP2mUwmQkND7VOmTDnRqVOnVtWrV7f3798/MXu7xHRnFaWUSfPo3933qmtY+u08Rg3qQd+rhxSqHd1kMvHs6+/xVNQDZGZmUrNWbZ557d2cz++6aSRTHpxBRNv2xO7by+03XE9GehqZGRkM6BTBbXc/wOibb6Ndxy70Hng1o6/uhclkommLMB597tULHre4rm1NlaWO7hdUC/glNCqmb2x05HajgymqMj0fekJalvVwfHoTTdP8qqaiqHx4PvSScBbojS1xq9GBGMUfr/vTyZnVjiWmhxodh7cIwZnVyHI2a6ejRoX81zZWHvOhl4Q4oF9sdOS2kjpASSqziSwhLct6+Gx6U0nm4gKqAiuwWVsYHYgoHmdSMqtKMhf5qAmsDI2K8cnrvkwms9RMR7Bn+5kQF1ALWCUd5Xzf2dSsKscS0hsbHYfwCbXQk3pDowMprIImdBegFWb0JG+V5XAFHDyT1twlJfMCyWmRKUDTjJ+qj57U6xkdiCiaxHR7paPx6Y3L7F9wvnz+a70kNEBP6rWMDqQwCtop7pjL5UqMi4urVbNmzbNK+eZABC6Xpg7Hpze2O2XChbxkKqfJ5Pzvv1bT4FSqE5WZREDG6Yts6feaAN9js16JLTHF6GBEwaVnOcsdPpsmtXEX4ZNf5qWjOfBjaFTMlbHRkT5x3RcooXfo0CFl48aNdyYkJLyblJRkxUdv6RIzXDUznVqxTejgbzRzqjnIlXbOMpWZRP3NL2N2+kWfqEtxGfAZNuswbIn5D0UmDOdwuswHz6Tm+5y5kJx+EZcBc4ARBsdRIAV+bK1Dhw7rNm7c2N3lctXFB9veZ/5yJiohw3Wz0XF4s5eDPvonjB2dchZoGgEZpyWZ/+c64DmgzI7asTOsVYnMVtVq185ifRxO0zRiz6Q1yXK6zh80XZxDy2MuCHGO4aFRMTNioyOfNTqQ/BTqOfQOHTqkAHtKKJYSExoVMwWQZJ4PLeNwejlzmXo0rSimYbPuwJb4idGBiP/s3r07cNGiRdZp06adAjgSn96gV4fwSq9+8DlhEW1KNZbVK5fxytMzcTmdNAsL56lX3qJCxfPHuHK5XDz/eBS//7QCpRTjbruTMRMmAfDsIw+xecOfOese2LeX+2c8wbhb7zhnH3a7nYfvnMDRwwep36gxL77zMRaLhcyMDO4cN4zXPvyirM+sWFyeCo2K2RQbHfmD0YFcjM+VtAsrNCrmauB1o+MQfmU2Nmt3o4MQ/9m7d2/QRx99VAPgVHJm9cLOlHgh2XONF1Raagq2h+9l1gefseS3jdSoVZvZr72Y57ox385n/97dLP51A58vWcUn777Bv7t3AjDjmZdyRqd7e+43KBSDrrn+vH3INMmlxgR8ERoV08zoQC7GrxN6aFRMG2AeIG1oojgFAvOxWf1mUgdfcaHpUu+5556GsbGx5cJatWo9ctj1jbLXX/XDEsZfN5Cru7Vl9mv/Ddd8Ou4kD0++hbHX9GN4/245IzwCXN31Ml599nHGXtOPxx6YXKj4fv95JWERl9G4mf4Y8+ibJvLDom/zXHf5km8ZNuYmzGYz1ipVGDRkKMsWLThvvcXffEm3Xn2pXvP8DtfFM5WqVLkXUGXgu9CoGK8dhMdvE3poVExFYBEg02KKklAHvbOMKCUXmy71jTfeOBQaGpq5YNU68+sff5mzTXJSInMX/cgXS3/ik/de5+TxYwA8+sAURt90G18sXcW8Zb+y/Z/N/Lj0u5ztEuPj+XzJSp574/1CxXj86BHq1K+f875ug4acjjuRZ0n/+NEj1K3/37Srdes35PixI+et9928z7n+hvMnhYHimUpVesQVSgRefN0bPmVgCXoVfdB9IUpKJDbrfdgSXzM6kLIgr+lSp02b1jBnulSTJdDpOnd8icHX652Tq1StRr2GoRw9fJCKVit/rVnN2dNxOeulpaYSu+/fnPfXjhyD8oLOYn//uZa0lBR69B2Y5+fZU6lm++yDd86ZSjUrK4vRN99Glyt7llbIZcHw0KiY/8VGRxZ1AvoS45cJPTQqZggw0eg4RJnwPDbramyJm40OpCxLc2BFqfNqHAOD/pvxzGwy43Q6cwZJmrtoxQVnRAspn3et6r49u/jfPbcD0K5jl/NmXaxTrz7rfvsl5/2xw4eoXrM2Fsv5X7V16tXn2JHDtO3QWV/3yCHq1K1/zjoLv/qMISNvwGzOv9UweyrVdz77hkcfmMzwcRMIb9OWG68byMJVf1xwOw3fHFfEYE+GRsV8HxsducXoQDz5XZW7e7L6wtWTCVF0QcBX2KzljQ7E311outS69RsqylWskZyc7+SKgJ6sO3XrwUdvz8pZFnfiOCePH8132/ymUL6ydz92btvCgX/1h4HmffohV107LM99DYi8nm+//BSn00lifDzLlyw8p907JTmJFd8v5vrReVe35ybTJJcqC/BRaFSMVxWKvSqYYvIe+li8QpSWlujPp99rdCAlrbifFy+MvKZL/eqrr/YdTcwMbRYWYWraIoxh/bpSv2Eonu3oeXn29dm89OQjDOvXFaUUwSHleSz6FWrVubQRfstXqIjthde4/7YbcTocNGvZiqdefTvnc89pkq8ZPprtW/5mSM8OKBTjb7+L5q0ictZdtvhbwtu0pVHjpvke95KmUjW+ZcFXXQ48BEQbHUi2Ak2f6itCo2JGA18ZHYev+jLg6V+7mndIY1vRuICu2BL/MjqQ4uIL06fGJWXUOJGU4XOTaHiLEJxZdQOTM/7Nqnz+g/JeppSmTy2sDKBtbHSkV4zP4jdV7qFRMZUB6ZwkjGJCfz7dH2u9vFKG3RkYl5xZP/81xcX4T5HOEOWAD0OjYryinsNvEjrwAlLVLozVFrjf6CDKAk3TOByf1lhmTSwOXpGLfFl3YIrRQYCfJPTQqJgewG1GxyEE8ITMn17yTqVk1kjPcnrtAB++REroxSLaG+ZP9/mEHhoVEwjMRm4zhXcIAd40Ogh/5nRpplPJmXWNjkMIDxWAd40OwucTOnAHEGZ0EEJ4iMRm7W90EP7qZFJGbadLk74KxUSTslBxuTo0KqaPkQH4dEIPjYoJogxPZSm82kvYrD59fXkju9NlOZuaJX1lhLd6xsiD+/pd7m3ApT04KkTJaAvcCHxqdCDFqc0nbUpkPvStN28t0PPtJxIz6khHuOIlJfRi1TU0KiYyNjoyxoiD++yF4W47jzI6DiEu4gls1kCjg/AXGXZnYEKavYbRcQiRj6eNeozNZxM6cCsgz6AKbxYK3G50EP7iRGJGPQ2tWL4oJ468hp+WFb4Q9dZLzxKzcD4A77wSzQu2/+W53uqVy5g48ppLirG0aChWr1zGdb07M6RHBx64fTwpFxhG1+Vy8dxj04i8sj3XdL+cL+fMLtBnnpISEpg4agjD+3fjmRkP5iw/e+Y0E0deg91uL94TLH3tgBFGHNgnE7q7dJ73lSSEd5khpfRLl5rpCE7KsFct6Pp5TVdaHO56aAaRQ0eVyL6NkpKSomwP38usDz5jyW8bqVGrNrNfezHPdWO+nc/+vbtZ/OsGPl+yik/efYN/d+/M97Nz9vHdfDp168GClWs5sG8ve3ftAOClJx/hvv89TkBAQMmdbOl5MjQqJv8ZdYqZTyZ0YAJg+DN/QhRAXWCs0UH4uhOJGfUB2jaowpsvPM2oq3oypGfHnNJy9mdvv/wcYyP78nr0E6SmJPPEtPsYe00/Rgy4kien3489Kytn/T/XrGZsZF+u6X45Lz35KNnDYOcuvT94x80smv8FAI89MIXPPnjnvPjsdjvPzHiQIT06MPaafqxf+3u+53Tq5AnuGDuMoX2v4I6xw5g25VbeeUUfFrx/x3DiThwH4OHJt3DT9fr0qVmZmfRs04SszEwWzf+CSWOuZ/pdExnevxtjBvfhyMHYQv1eAZatWGUJi7iMxs1aADD6pon8sOjbPNddvuRbho25CbPZjLVKFQYNGcqyRQvy/cyTxRJARnoaLpcLe1YmAYGBrPl5JZWslbns8k6Fjt9LhaH3oSlVPpfQQ6NiAoAZRschRCE8mP8q4kJSMx3BqVmO/8YaV4r5y37lnbnfEP3YdI4ePpTzkcls5ouYn5j66FO8/NRjXN65K18sXcXXP/6Oy+Xi84/+e1R4/97dfPLdcr5e8Tsb163hh+++KXKMCz6fQ+z+f/l21R988u0P7NyW/6yazz8eRdsOnVj40zqemfUOG9atyfmsS/ee/Pn7alwuF7t3bCM5OZmU5CQ2rV9HqzbtCAwKAmD7lr+5Z/pMFqxcS5cevfjonVmFjv3w0WOmOvX/a72s26Ahp+NO5FnLcfzoEerWb/DfuvUbcvzYkXw/8xQ5bBSHYw8w+qqedOnem5q16/D+Gy9zz7RHCx27l3vcna9KjS/2cr8JaGR0EEIUQmts1quwJS4zOhBfdDol85zH1IaNGQ9A/UahdOjSjb//XEu9BnqF3dDR43LW+2l5DFs2/sXc998CICMjA5P5vzLMkOE3EBAQQEBAAJHDRrHu99UMHjqySDH+ueZXfX+BeuvK9aPH8d1Xn118m99XM/XRJwGoXrMWPfsNyvnsiu69Wff7LzRtEUbL8NZUrV6DDX/8zpa/19Ol+3/zJ112eWfqN9S/Dtte3vmC7dbeJCSkPC+/90nO+xdtM7hlyn0cij3Ah2++AsDt9z5Iy/A2RoVYXBoDo4GL/yEUI59K6O65Zx8xOg4hiuBhQBJ6IdmdLktShuPibece3eSCQzxGg9U0Xp79KaFNmhXoWErpOzJbLLhc/83mlZlZ+InmsvdV1G26dO/Fa9FP0qR5S7p070W16jVZ9/tq/tm4nkeefTlnvSB3SR3AZDbhzKNUvW/PLv53j943s13HLufN416/Xj3Xil//zHl/7PAhqtesjcVyfnqoU68+x44cpm2Hzvq6Rw5Rp279fD+7kK2bNnL2zCl69b+KCcOu5pnX3kPTNGZOncJH3xjy5FdxuwtJ6Bd0A/pdjxC+pi82a3tsiZuMDuRSFPR58eJyOjmzhqad27N90fwvmDw1iqOHD/H3X3/wsO25PLftMyiSj99+jceiX8VisZCUkEBC/FkaNm4CQMzC+Vx9/QicDgfff/cN42+bDECD0MZs3bSB/oOv5cihg2xev44Bg6+7aJxXdO+Vsz80LafN/WI6X9mTxV9/yZ0PTOfMqTh+XbWcEeMmAFCzdh0qVqrEN599zPtfLaZy1aq8+OQM0lJSaNWmbb779tS0RRjzl/92wc/79+/nmPbI4xz4dw+Nm7Vg3qcfctW1w/Jcd0Dk9Xz75acMvOZ6UpKSWL5kIW98/FW+n+XFbrcz6zkbL7z1IQDp6Wkopd/YpKWlFuocvdgVoVExHWKjI0vluvG1hH6z0QEIcQnuQiYRKjBN04jP47lzp9PJqKt6kp6WxvQno3Oq23N7+PFnmPXcE4wa1AOTyYTZYuGBGU/kJPTGzVpw89CrSEqIp/fAwVx13XAAbrnzPqZNuZXh/bvRtEUYrdt1zDfWYWNv5t/dOxnW9woqWitzeeeu7Ny6+aLbTLM9x2NTpzC07xXUqFWbNu06ULGSNefzLt178euq5dRvFApA9Ro1qR5xGSZT8XZ9qlCxorK98Br333YjToeDZi1b8dSrb+d8PmpQD978ZD41a9fhmuGj2b7lb4b07IBCMf72u2jeKgLgop/l5ZN3X2fI8BuoVqMmAFMe/B933TwagKmPPFGs52iwu9Afsy5xKrtnp7cLjYqpDRwBSv1RgLLiy4Cnf+1q3tEz/zVFESUBdbAlphkdSEFs3LgxzGKxLGvevHlKSEhI4eudL1F8alblw/FpTT2XtW1Qhd+2xVLJar3QZj4jIz0dS0AAFouFhPizjL92AM+8/h6Xtc//BqK4hODMqhyYlXUsK9jrZ67THFnEHTuC7ec4jiY789/Ae2QAdWKjIxNK+kC+VEIfhSRz4dsqAcMoxTY1X3Y2Lau60TGUpEOx+3j0/slomobdbmfUTRNLNZln840inU8rh/7o6tv5rXipfCmhy7O8wh9MQBJ6vjIdzsDUTMd5xfAth+ONCKfIfvvpR954/qnzlt961wNcde2wi7Ztlw6FJlNPl4Zb+H97dx5lR1mncfxbfbsTWS9rABXmioIgwxqQJSLRGRm1RFBBFB2iiAKOzgyKcMGBKQGl0BkHlAEHBxBENgERuYKKkITFI5AQiCEhSCjIwhIIqexL973zR90cM5EknXRV/d6qej7n9AmHA1XPSafz3HrrXVToiUaztStwsHUOkRS8j6C+M0E80zrIILSBzpqT0vIwb9GKbfO+ZxYOf/+RHP7+I61jrEdB+rzTATq0izmkcGCj2do7Cv3JWd6kEIUOfNo6gEhKekj2UjA9ZnGQ5rTb7fiVV17ZYcSIEfM8z8vtr9L5C5ds3Rlo53W7yhqg7a1gpdfpd3yPsU6H/iULWLhsgNeXFvbPxeeBr2V5g6IUuobbpUyOpwCFPnLkyEUTJkw4df78+T9asGBBnZwe5QY69L62ZGCTPO5VdcNoe8Nr/b0LB1w/bqDDwmUDXPHYfJYNFPMRHTiGjAvd+VnujWZrH2D9+yjKkGmWe64aBPHz1iEGY8KECZuT7Emfy2Nc+NDrJ8xZ2H9uHvequp2WvTZ7r81nzb+3f9+1ry9zQLsDry9tF7nMV9kzCv1pWV28CE/oejqXMjoKuMw6xGCMHDlyETA9r/s9+vOW5svkxFu8bOWIgcXLZ7cLtQysyHwgs0J3+sVJ95D4T1nnEMnAUdYBXNRotrYERlvnqJJ+ak73QMl8OMuLu/6NfDc6iEXKaTRBfQvrEA76IOD6C91SWalCz9PhjWYrs59717+RR1gHEMnIMMD19UwWPmodoFI8WEmv6z1QJn3AB7K6uOvfSL1LkzJToa+me5pipkOSsqYOKzt6Qs9ZZn/GXf9GHmIdQCRDo6wDOOZgYGvrEFXieZ7eoeeveoXeaLbeSrJURqSs3kVQ38o6hEM0Imegn16dkZGvnRrN1n5ZXNjZQkdP51J+HnCodQiH5H8ySeV1NCnORib95vI3Up/WpQoOsw7gEBV63jw6A6R8wLoMxr5ZXNTljWX0hC5VoPfoQKPZqgPvsM5RNR3wNMvdxH5ZXNTJb2R3tutI6xwiOTiIoF6Q464ydQCFOfarRDzop6Z36Pnbu9Fspd6/ThY6sA+gwxmkCjYHdrEO4QANtxvwgH4tW7OwGbBb2hd19Rup9+dSJXtaB3CACt1IPz0uv3ots/3SvqCrha7351Ile1gHcIAK3YKnZWuG9kv7gq4WutNH+YmkrNJP6N0Jcbta56giD+inR4VuY7+0L+hqoe9sHUAkR5UudDSHwNSAJsVZ2S/tCzpX6I1maxiwvXUOkRxVfchdO0Ja8ToM6B26lR0bzVaqk7+dK3TgrWj5ilTL9gT1Kh8ZqkI30oNHPzUVup0RaV7M1UIXqZpUf7ALRoVuRevQre2Q5sVU6CJuSPUHu2DeYh2gqvrxesDTiKid0j+hV/kvNqmuKv+51xO6kX5P+7gbK32hb2MdQMSACl1y19Zwu7XSD7mr0KWKVOiSO61BN1f6J/StrQOIGKjkn/vuARVV/jBjqu31aoa7rdIXup7QpYqqumxtU9w+xrnU9IRurvRD7pV8UpHKq2qh91kHqLK2p0I3lmrfuVjoIlWkQpfc6aQ1c6l+oHKx0JdZBxAxoEKX3PWjd+jGUt0DwMVCX2odoIre7s1+fo+eF+rWOSqsqsWmQjGkIXdzqXawiz9MKvTcdDpH9zw84ey+Gzo78PqBnsffWCeqMBd/FvPQsQ5Qbdolzliqv/8u/iWiQs/YZixd+PXenz/+2dq9Ow/z+g+0ziMArLAOYGTAOoCIoXaaF3Ox0PUOPSO7ezOfu6Dvmhfe7U07wPN4r3Ue+X+q+kFWhS5VtjzNi7lY6FX9iy0jnc7Heh6c0Oy7kRHMH+l5vM06kbyhqv65V6FLlanQZf02Z8mCM3pvmXRC7b5dNKxeCAutAxjRiJxUWekLXT/gQ7CH98KMC/qunnWgN13D6sWywDqAhSj0FzaaraXAJtZZRAyUvtD1hL7BOp1ja+MfO7P3pp7tiQ/wPHa1TiQbrJKF3vUy0LAOIWLglTQvpkIvsC1YHJ/Ze/OkT9Xub/R5AwdZ55Ehedk6gKEXUaFLNc1K82IuFvoi6wCu29N7/tkL+66efYD3zAGexxHWeSQVM60DGHrJOoCIkdIX+rPWAVzk0W4fVxv32Jm9N/du5y04AHi7dSZJlQpdpHpKX+hTrQO4ZEsWxWf13jTpk7Vxb+vzBt5tnUcysQINuYtUUbkLPQr9OY1mawGwpXUWS+/yomcv7Lt69v7en0dqWL30ZhPEVd4CVU/oUlXlLvSuaUDlnkY92u3ja2MfPaP3lmHbeQv2R8PqVVHl4XZQoUs1LYtC/9U0L6hCd0CdRfObvTc+cWxt/K593sDB1nkkd5F1AGNzrAOIGJid9gVdLfRKvEff25vxzIV9V7+0jzdDw+rV9qR1AGPTSA6pcPE4Z5GspDrcDu4W+jTrAFnpoT3wqdp9j3699+fDt/UW7g/sZp1JzFW60KPQX9xotqYDe1hnEcnR9LQv6Gqhl+4JfSsWvn527w1PfKL2wDt6vfYh1nnEKU9YB3DARFToUi2PpH1BVwv9WWAl0GcdZKj29f48/YK+a17e23vuQM9jtHUecc7LBHGq2z8W1ETgBOsQIjmqRqFHod/faLb+DOxpnWVj9NAe+Ezt3ke/1nvrJlt7i/YFdrfOJM7S03lionUAkRwtAaakfVEnC71rKgUr9K1ZMO+bfTc8eUzPg7tpWF0GaZJ1AEc8bh1AJEcTo9AfSPuiLs8qfdQ6wGDt7z3z9F3Dznlg4vBTNz22Nn50r9d+i3UmKYwHrQO4IAr9+cBz1jlEcpL6cDu4/YR+N3CRdYi1qTHQ/9navY+d3nvrJlt5i/cF3mmdSQpnABhvHcIhE4G3WYcQyUEmhe7sE3oU+k+QwcL7odqG+LXv910+9unhY+Z+q+/aQ7plLrIxJhHEsXUIh0ywDiCSk0xGoF1+Qge4B/iCdQiAA7zp0y7su/rVPb0XNFtd0nK/dQDHjLUOIJKDV6PQn5HFhV0v9F9jWOg1BvrH1H776L/03rZZ3Vuyj1UOKa2x1gEc80dgLrC9dRCRDGU2b8bZIfeu35GsR8/VtsSvXtJ32bjpw8fMPa/vp4eqzCUDA8AD1iFcEoV+m+RDvEiZ/TKrCztd6FHoLwQeyut+B3nTpt497KyHHht+2hbH1B4+oua1d8rr3lI54wjiBdYhHHSXdQCRDA0Av8rq4q4PuUPyiX10VhfvpX9lMqx++5Zbekv+Nqv7iKzhNusAjvoNsAIYZh1EJAMPRKH/WlYXd/oJvSuTIbjtmD/3B30/HPv08DGvndt3/WEqc8lRG/iFdQgXdUfltJRPyuqOLC/ufKFHoT8FeCGt6x3sPfXUb4ad+dCjw79c/2jtD6NrXmfHtK4tMkgPE8QvWodwmIbdpazuyPLiRRhyh2STmVM29n/upX/lSbV7Hvlq7y+22sJbuleKuUQ2hobb1+1XwCXWIURS9ngU+s9neQPnn9C77tiY/2kH5r1yWd+lY58ePmbeOX03jFKZiyNutw7gsu4a3aesc4ikLPPXbEV5Qv8tybD7LoP5jw/tmTLlW70/mb+bN/sgbQIjjrmfIE7tFVKJ3QhcYB1CJEV3ZH2DQjyhd9en/u+6/ps++lecWrvzocnDvzDlxmHf3mv3ntmjPE8zZcU5V1oHKIhrSJb4iJTB1Cj0J2d9k0IUetdVQP+a/3JH5r18ed8lY6cNHxM3+27SsLq4bC4abh+UKPRnk2z9LFIGP8rjJoUp9Cj057Dagvz39EyefO+wMx7+w/CvbPPh2iOja15H20WK664liFdYhyiQq6wDiKRgCXBdHjcqyjt0ADZh2RUn1e4ZcVrvnVtv7i3b2zqPyAbooOH2DfUrYA7wZusgIkNwcxT68/O4UWGe0AGmvumke7/Rd8t2m3vL3mWdRWQD3U8QP2Mdokii0O8np6FKkQxdkdeNClXoBHEH+IF1DJGN8B/WAQrqSpKtYEWK6OEo9DM5+/yNFKvQE9cCr1uHENkAEwniu61DFFEU+i8Dt1jnENlI38/zZsUr9CBeDPyXdQyRDfAd6wAFd4l1AJGNMIOcz2woXqEnLgEyO7FGJEVT0VK1IYlCfwIZHjkpkpFLu3uo5KaYhR7EC4HvWccQGYSLunM/ZGi+SXJKnUgRzAJ+nPdNi1noicuAV6xDiKzDs8AN1iHKoLvLln4vpSjOi0J/ad43LW6hJ+/SL7aOIbIOZxHE2r40PecBK61DiKzHZJLJ27krbqEnLicZ2hBxzXiCWMekpigK/efQ5jzivrPyfne+SrELPYiXAWdYxxBZQxs43TpESV1IspWmiIt+H4W+2RLVYhc6QBDfDNxnHUNkNdcRxBOtQ5RRFPovAZda5xB5Ax3gTMsAxS/0xFfRuzVxw2LgHOsQJXcx2lxK3HNjFPqmH+TLUehB/BTwQ+sYIsAFBPGL1iHKLAr9GDjLOofIapaTLK00VY5CTwSA/iIVS48D/2kdogqi0P8x8DvrHCJdF0ehH1mHKE+hJ5vNfNk6hlTWAHAyQdxvHaRCvggssg4hlTeRZLKmufIUOkAQ3wH8xDiFVFOoiXD5ikL/eYwnIUnlLQdOjELfiTlc5Sr0xD8DkXUIqZQngfOtQ1TUj4D7rUNIZZ0bhf4U6xCrlK/Qk6H3MWjfZ8nHcuBEglhndhuIQr8DnEyyukAkTw/h2JyZ8hU6QBCPx7HfaCmt0wniJ6xDVFkU+jOAs61zSKUsBsZY7Qi3NuUs9MS/AY9Zh5BSu5EgvsI6hADJYU3jrUNIZXwjCv1nrUOsqbyFngyBfhyYax1FSmka8CXrEJLoDr1/Gi1dlez9Lgp9Jz/Il7fQAYJ4JnAcoKVEkqYlwLEEsZZMOSQK/TnAx0jmNYhk4XngM9Yh1qbchQ4QxOPQAS6SrlMIYmdmtspfRKH/R+BU6xxSSguBo6LQd3bUt/yFDhDElwI/tY4hpXAhQXy9dQhZuyj0fwL8wDqHlEobOCEK/cnWQdalGoWeOAX4g3UIKbTrCOJzrUPIoHwd+L11CCmNM6PQv8s6xPpUp9CDeCnwEeAp6yhSSPeRrHeWAohCvx84HnjOOosU3lVR6BdiGXR1Ch0giOcB/wC8YB1FCmUK8HGC2IntHWVwotB/DTgabTojG28ccJp1iMGqVqEDBPEs4EjgVesoUggzgQ8RxLF1ENlw3XeexwLayU821AzgE67s0z4Y1St0gCB+GvDRJ3dZt5nA6O7yRymoKPTvIVmjPmCdRQrjReBD3VGewqhmoQME8SPAh0mWIoisaVWZz7AOIkMXhf7t6IwHGZyXgfdHoT/dOsiGqm6hw6o93/8eeN06ijhFZV5CUej/jGR3v451FnHWXJIyn2YdZGNUu9Bh1ZP6+9AWsZJQmZdYFPpXASehJ3X5a68AfxeFfmFXQqnQge5pWe8F5lhHEVNTgPeozMutu/HMieiduvzFLOC9rm8csz4q9FWCeBpwOFC49yaSivuBUQSxljRWQHf4/QSgMDOYJTPPAodHof+0dZChUqGvLnkyOwTtMFU11wMf1NK0aolC/xbgA0ChZjJLqqaQlHlkHSQNXqej+SF/Jaj3kuwFXZgNBWSjfZsg/jfrEGKn0WztCtwJ7GWdRXJ1B3BiFPqlWemkQl+XoP4V4BKgZpxE0rcEOI0gvs46iNhrNFtbADeS7E8h5dYBvgWcH4V+qQpQhb4+Qf1I4AZgW+sokpqnSc4z/5N1EHFHo9nqAb5LcrCLlNNC4B+j0P+ldZAsqNAHI6jvTPLpfZR1FBmym4AvEsSLrIOImxrN1ueA/wGGGUeRdD0DHB2F/lTrIFlRoQ9W8l79fOAsNJmwiFYApxPEl1sHEfc1mq1RwG3ADtZZJBW/JjnPvNQTX1XoGyqoHwFcB+xiHUUG7QngcwTxJOsgUhyNZms74AqSw12kmAaAEDgvCv3SbyakQt8YQX0r4PvA542TyLqtBC4ELtLRp7KxGs3Wp4HLgG2ss8gGmQKcFIX+I9ZB8qJCH4qgPprkXdvuxknkr00APk8QF3rnJ3FDo9naCbgS+Ih1FlmvfpKn8gui0K/Usbkq9KEK6sOBc4AmmkTjgiUkT+XfI4j7rcNIuXQnzF0C1G2TyFo8TvJUPsk6iAUVelqC+h4k79tGGyepqg7wM+BsgniWdRgpr0aztTNwFckuc+KG5SSTlr8bhX5lP8ir0NMW1I8CLkK7TuXpYeBfCeJHrYNIdTSarU8C3wHebp2l4h4GTi7zcrTBUqFnIaj3kJzmdD6ws3GaMouAJkF8s3UQqaZGs9UHnAKcB2xvHKdq/gScG4X+HdZBXKFCz1JQfxPwT8DZaKe5ND1H8mR0rWaviwu6W8d+A/gasJlxnLKbAfw7cEMVlqJtCBV6HoL6piRL3E5Hw3NDMZVka87rNeFNXNRotnYkKZuTgV7jOGUzB7gAuCoKfX2QfwMq9DwlQ/EfA84gOaZVBmc8ybr/Owli/YEV5zWarXeSFPtxqNiH6jXgYuCyKPSXWodxmQrdSlAfBXyZpOA3MU7jonnAtcCVBPE06zAiG6M7I/4rwJeArWzTFM4zwH8D10Shv8A6TBGo0K0F9TpwPPA54FDbME54gGSznlsJ4uXWYUTS0Gi2NgPGAKcCexvHcVkbuJtkZ77flO1406yp0F0S1HcnKfbjgHfYhslNB3iE5CCM2wjiGcZ5RDLVaLYOJZkZ/0k0OrfKC8A1JE/jz1uHKSoVuquC+p4k20weBRwG1GwDpaoNPATcCtyujWCkihrN1lbAMd2vI6leucckp6BdA/xeM9aHToVeBEF9W+BDJD/0o4BdbQNtsA4wGbgfGAuMJ4jnmSYScUij2dqUZOe5Y0g+yG9nGig704C7gBbwYJV3dcuCCr2IgvqOJE/th5EU/AG4tY/8POBJYBLJDPVxKnCRwWk0WzWSn+ujSQq+aB/gV7ccGEe3xKPQ1yu1DKnQyyCo95K8c98D2HO1X98JbJnRXdvAS8BMko1enux+PaEhdJH0dGfKHwgc1P0aCWxtGmrtZpEckPI48BhwXxT6i20jVYcKveySWfRv7n6NINmecjuSoh/W/epb7ddeYCmwGFi02q+LgLkkBT4TmKPNXUTy12i2PJINqlYV/IEkZ0fkeV57m2RZ2eOrf0Wh/2qOGWQNKnQRkRJoNFubkHxwf8tavnYkmXg3bLWvGjBAUtDt7j/PB15e7eulN/jnWXrydo8KXUREpAR6rAOIiIjI0KnQRURESkCFLiIiUgIqdBERkRJQoYuIiJSACl1ERKQEVOgiIiIloEIXEREpARW6iIhICajQRURESkCFLiIiUgIqdBERkRJQoYuIiJSACl1ERKQEVOgiIiIloEIXEREpgf8D1YrRPLmILzAAAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 600x600 with 4 Axes>"
       ]
@@ -3164,7 +3257,39 @@
     }
    ],
    "source": [
-    "plot_analysis(df)"
+    "plot_pie_charts(df, \"Time comparisons\", (\"time\", \"sum\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/oli/.local/lib/python3.6/site-packages/ipykernel_launcher.py:13: RuntimeWarning:\n",
+      "\n",
+      "invalid value encountered in double_scalars\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pie_charts(df, \"Memory comparisons\", (\"memory\", \"median\"))"
    ]
   },
   {
@@ -3262,6 +3387,7 @@
         }
        ],
        "layout": {
+        "autosize": true,
         "legend": {
          "tracegroupgap": 0
         },
@@ -4121,7 +4247,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 78,
    "metadata": {},
    "outputs": [
     {
@@ -4157,23 +4283,23 @@
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
-       "      <th colspan=\"3\" halign=\"left\">cpu</th>\n",
        "      <th colspan=\"3\" halign=\"left\">memory</th>\n",
        "      <th colspan=\"5\" halign=\"left\">time</th>\n",
+       "      <th colspan=\"3\" halign=\"left\">cpu</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
-       "      <th>max</th>\n",
-       "      <th>mean</th>\n",
        "      <th>min</th>\n",
        "      <th>max</th>\n",
        "      <th>median</th>\n",
        "      <th>min</th>\n",
-       "      <th>count</th>\n",
        "      <th>max</th>\n",
        "      <th>mean</th>\n",
-       "      <th>min</th>\n",
        "      <th>sum</th>\n",
+       "      <th>count</th>\n",
+       "      <th>min</th>\n",
+       "      <th>max</th>\n",
+       "      <th>mean</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>function</th>\n",
@@ -4193,260 +4319,262 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Py_kgeneration</th>\n",
-       "      <td>32.278779</td>\n",
-       "      <td>32.278779</td>\n",
-       "      <td>32.278779</td>\n",
-       "      <td>-199.3</td>\n",
-       "      <td>-199.3</td>\n",
-       "      <td>-199.3</td>\n",
+       "      <td>304.2</td>\n",
+       "      <td>304.2</td>\n",
+       "      <td>304.2</td>\n",
+       "      <td>178.629961</td>\n",
+       "      <td>178.629961</td>\n",
+       "      <td>178.629961</td>\n",
+       "      <td>178.629961</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>415.639768</td>\n",
-       "      <td>415.639768</td>\n",
-       "      <td>415.639768</td>\n",
-       "      <td>415.639768</td>\n",
+       "      <td>17.667643</td>\n",
+       "      <td>17.667643</td>\n",
+       "      <td>17.667643</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>generate</th>\n",
-       "      <td>32.749276</td>\n",
-       "      <td>32.749276</td>\n",
-       "      <td>32.749276</td>\n",
-       "      <td>-281.6</td>\n",
-       "      <td>-281.6</td>\n",
-       "      <td>-281.6</td>\n",
+       "      <td>303.8</td>\n",
+       "      <td>303.8</td>\n",
+       "      <td>303.8</td>\n",
+       "      <td>139.743243</td>\n",
+       "      <td>139.743243</td>\n",
+       "      <td>139.743243</td>\n",
+       "      <td>139.743243</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>329.579564</td>\n",
-       "      <td>329.579564</td>\n",
-       "      <td>329.579564</td>\n",
-       "      <td>329.579564</td>\n",
+       "      <td>20.362745</td>\n",
+       "      <td>20.362745</td>\n",
+       "      <td>20.362745</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>fftma2</th>\n",
-       "      <td>30.472359</td>\n",
-       "      <td>30.472359</td>\n",
-       "      <td>30.472359</td>\n",
-       "      <td>85.3</td>\n",
-       "      <td>85.3</td>\n",
-       "      <td>85.3</td>\n",
+       "      <td>2.6</td>\n",
+       "      <td>2.6</td>\n",
+       "      <td>2.6</td>\n",
+       "      <td>38.884135</td>\n",
+       "      <td>38.884135</td>\n",
+       "      <td>38.884135</td>\n",
+       "      <td>38.884135</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>86.059132</td>\n",
-       "      <td>86.059132</td>\n",
-       "      <td>86.059132</td>\n",
-       "      <td>86.059132</td>\n",
+       "      <td>8.035698</td>\n",
+       "      <td>8.035698</td>\n",
+       "      <td>8.035698</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>covariance</th>\n",
-       "      <td>30.505800</td>\n",
-       "      <td>30.505800</td>\n",
-       "      <td>30.505800</td>\n",
-       "      <td>80.9</td>\n",
-       "      <td>80.9</td>\n",
-       "      <td>80.9</td>\n",
+       "      <td>-1.8</td>\n",
+       "      <td>-1.8</td>\n",
+       "      <td>-1.8</td>\n",
+       "      <td>38.781881</td>\n",
+       "      <td>38.781881</td>\n",
+       "      <td>38.781881</td>\n",
+       "      <td>38.781881</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>85.894170</td>\n",
-       "      <td>85.894170</td>\n",
-       "      <td>85.894170</td>\n",
-       "      <td>85.894170</td>\n",
+       "      <td>8.055999</td>\n",
+       "      <td>8.055999</td>\n",
+       "      <td>8.055999</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>gasdev</th>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>2.395994</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>8.0</td>\n",
+       "      <td>-19.3</td>\n",
+       "      <td>4.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>-61.2</td>\n",
+       "      <td>0.000081</td>\n",
+       "      <td>0.023745</td>\n",
+       "      <td>0.000409</td>\n",
+       "      <td>103.849151</td>\n",
        "      <td>262144.0</td>\n",
-       "      <td>0.011277</td>\n",
-       "      <td>0.000909</td>\n",
-       "      <td>0.000193</td>\n",
-       "      <td>242.610944</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>100.100000</td>\n",
+       "      <td>0.567746</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>fourt</th>\n",
-       "      <td>25.100000</td>\n",
-       "      <td>8.433333</td>\n",
-       "      <td>0.100000</td>\n",
-       "      <td>2.3</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>-0.2</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.4</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.025649</td>\n",
+       "      <td>0.041650</td>\n",
+       "      <td>0.031247</td>\n",
+       "      <td>0.093742</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>0.066393</td>\n",
-       "      <td>0.050588</td>\n",
-       "      <td>0.042309</td>\n",
-       "      <td>0.151763</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.100000</td>\n",
+       "      <td>0.100000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>cov_value</th>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>0.572549</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>-9.5</td>\n",
+       "      <td>2.2</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>-7.1</td>\n",
+       "      <td>0.000091</td>\n",
+       "      <td>0.000309</td>\n",
+       "      <td>0.000105</td>\n",
+       "      <td>16.534301</td>\n",
        "      <td>156816.0</td>\n",
-       "      <td>0.000575</td>\n",
-       "      <td>0.000221</td>\n",
-       "      <td>0.000193</td>\n",
-       "      <td>34.674709</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>100.100000</td>\n",
+       "      <td>0.044064</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ran2</th>\n",
-       "      <td>100.100000</td>\n",
-       "      <td>0.527507</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>2.7</td>\n",
+       "      <td>-19.3</td>\n",
+       "      <td>2.4</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>-17.8</td>\n",
+       "      <td>0.000078</td>\n",
+       "      <td>0.002609</td>\n",
+       "      <td>0.000102</td>\n",
+       "      <td>32.804563</td>\n",
        "      <td>333450.0</td>\n",
-       "      <td>0.000691</td>\n",
-       "      <td>0.000218</td>\n",
-       "      <td>0.000190</td>\n",
-       "      <td>74.079918</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>100.100000</td>\n",
+       "      <td>0.118282</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>build_real</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.003262</td>\n",
+       "      <td>0.003262</td>\n",
+       "      <td>0.003262</td>\n",
+       "      <td>0.003262</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.001935</td>\n",
-       "      <td>0.001935</td>\n",
-       "      <td>0.001935</td>\n",
-       "      <td>0.001935</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>prebuild_gwn</th>\n",
+       "      <td>2.1</td>\n",
+       "      <td>2.1</td>\n",
+       "      <td>2.1</td>\n",
+       "      <td>0.001021</td>\n",
+       "      <td>0.001021</td>\n",
+       "      <td>0.001021</td>\n",
+       "      <td>0.001021</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>2.2</td>\n",
-       "      <td>2.2</td>\n",
-       "      <td>2.2</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.002618</td>\n",
-       "      <td>0.002618</td>\n",
-       "      <td>0.002618</td>\n",
-       "      <td>0.002618</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>clean_real</th>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.7</td>\n",
+       "      <td>0.000743</td>\n",
+       "      <td>0.000743</td>\n",
+       "      <td>0.000743</td>\n",
+       "      <td>0.000743</td>\n",
+       "      <td>1.0</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0.001551</td>\n",
-       "      <td>0.001551</td>\n",
-       "      <td>0.001551</td>\n",
-       "      <td>0.001551</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>cgrid</th>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.001870</td>\n",
+       "      <td>0.001870</td>\n",
+       "      <td>0.001870</td>\n",
+       "      <td>0.001870</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>0.003504</td>\n",
-       "      <td>0.003504</td>\n",
-       "      <td>0.003504</td>\n",
-       "      <td>0.003504</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>length</th>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>length</th>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000348</td>\n",
+       "      <td>0.000635</td>\n",
+       "      <td>0.000448</td>\n",
+       "      <td>0.001343</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>0.001141</td>\n",
-       "      <td>0.000827</td>\n",
-       "      <td>0.000668</td>\n",
-       "      <td>0.002481</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>maxfactor</th>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>maxfactor</th>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000104</td>\n",
+       "      <td>0.000123</td>\n",
+       "      <td>0.000112</td>\n",
+       "      <td>0.000447</td>\n",
        "      <td>4.0</td>\n",
-       "      <td>0.000198</td>\n",
-       "      <td>0.000195</td>\n",
-       "      <td>0.000193</td>\n",
-       "      <td>0.000780</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                       cpu                       memory                \\\n",
-       "                       max       mean        min    max median    min   \n",
-       "function                                                                \n",
-       "Py_kgeneration   32.278779  32.278779  32.278779 -199.3 -199.3 -199.3   \n",
-       "generate         32.749276  32.749276  32.749276 -281.6 -281.6 -281.6   \n",
-       "fftma2           30.472359  30.472359  30.472359   85.3   85.3   85.3   \n",
-       "covariance       30.505800  30.505800  30.505800   80.9   80.9   80.9   \n",
-       "gasdev          100.100000   2.395994   0.000000    8.0    0.0  -61.2   \n",
-       "fourt            25.100000   8.433333   0.100000    2.3    0.4   -0.2   \n",
-       "cov_value       100.100000   0.572549   0.000000    3.0    0.0   -7.1   \n",
-       "ran2            100.100000   0.527507   0.000000    2.7    0.0  -17.8   \n",
-       "build_real        0.000000   0.000000   0.000000    0.0    0.0    0.0   \n",
-       "prebuild_gwn      0.000000   0.000000   0.000000    2.2    2.2    2.2   \n",
-       "clean_real        0.000000   0.000000   0.000000    0.4    0.4    0.4   \n",
-       "cgrid             0.000000   0.000000   0.000000    0.0    0.0    0.0   \n",
-       "length            0.000000   0.000000   0.000000    0.0    0.0    0.0   \n",
-       "maxfactor         0.000000   0.000000   0.000000    0.0    0.0    0.0   \n",
-       "\n",
-       "                    time                                                  \n",
-       "                   count         max        mean         min         sum  \n",
+       "               memory                      time                          \\\n",
+       "                  min    max median         min         max        mean   \n",
        "function                                                                  \n",
-       "Py_kgeneration       1.0  415.639768  415.639768  415.639768  415.639768  \n",
-       "generate             1.0  329.579564  329.579564  329.579564  329.579564  \n",
-       "fftma2               1.0   86.059132   86.059132   86.059132   86.059132  \n",
-       "covariance           1.0   85.894170   85.894170   85.894170   85.894170  \n",
-       "gasdev          262144.0    0.011277    0.000909    0.000193  242.610944  \n",
-       "fourt                3.0    0.066393    0.050588    0.042309    0.151763  \n",
-       "cov_value       156816.0    0.000575    0.000221    0.000193   34.674709  \n",
-       "ran2            333450.0    0.000691    0.000218    0.000190   74.079918  \n",
-       "build_real           1.0    0.001935    0.001935    0.001935    0.001935  \n",
-       "prebuild_gwn         1.0    0.002618    0.002618    0.002618    0.002618  \n",
-       "clean_real           1.0    0.001551    0.001551    0.001551    0.001551  \n",
-       "cgrid                1.0    0.003504    0.003504    0.003504    0.003504  \n",
-       "length               3.0    0.001141    0.000827    0.000668    0.002481  \n",
-       "maxfactor            4.0    0.000198    0.000195    0.000193    0.000780  "
+       "Py_kgeneration  304.2  304.2  304.2  178.629961  178.629961  178.629961   \n",
+       "generate        303.8  303.8  303.8  139.743243  139.743243  139.743243   \n",
+       "fftma2            2.6    2.6    2.6   38.884135   38.884135   38.884135   \n",
+       "covariance       -1.8   -1.8   -1.8   38.781881   38.781881   38.781881   \n",
+       "gasdev          -19.3    4.0    0.0    0.000081    0.023745    0.000409   \n",
+       "fourt             0.0    2.4    0.0    0.025649    0.041650    0.031247   \n",
+       "cov_value        -9.5    2.2    0.0    0.000091    0.000309    0.000105   \n",
+       "ran2            -19.3    2.4    0.0    0.000078    0.002609    0.000102   \n",
+       "build_real        0.0    0.0    0.0    0.003262    0.003262    0.003262   \n",
+       "prebuild_gwn      2.1    2.1    2.1    0.001021    0.001021    0.001021   \n",
+       "clean_real        0.7    0.7    0.7    0.000743    0.000743    0.000743   \n",
+       "cgrid             0.0    0.0    0.0    0.001870    0.001870    0.001870   \n",
+       "length            0.0    0.0    0.0    0.000348    0.000635    0.000448   \n",
+       "maxfactor         0.0    0.0    0.0    0.000104    0.000123    0.000112   \n",
+       "\n",
+       "                                            cpu                         \n",
+       "                       sum     count        min         max       mean  \n",
+       "function                                                                \n",
+       "Py_kgeneration  178.629961       1.0  17.667643   17.667643  17.667643  \n",
+       "generate        139.743243       1.0  20.362745   20.362745  20.362745  \n",
+       "fftma2           38.884135       1.0   8.035698    8.035698   8.035698  \n",
+       "covariance       38.781881       1.0   8.055999    8.055999   8.055999  \n",
+       "gasdev          103.849151  262144.0   0.000000  100.100000   0.567746  \n",
+       "fourt             0.093742       3.0   0.100000    0.100000   0.100000  \n",
+       "cov_value        16.534301  156816.0   0.000000  100.100000   0.044064  \n",
+       "ran2             32.804563  333450.0   0.000000  100.100000   0.118282  \n",
+       "build_real        0.003262       1.0   0.000000    0.000000   0.000000  \n",
+       "prebuild_gwn      0.001021       1.0   0.000000    0.000000   0.000000  \n",
+       "clean_real        0.000743       1.0   0.000000    0.000000   0.000000  \n",
+       "cgrid             0.001870       1.0   0.000000    0.000000   0.000000  \n",
+       "length            0.001343       3.0   0.000000    0.000000   0.000000  \n",
+       "maxfactor         0.000447       4.0   0.000000    0.000000   0.000000  "
       ]
      },
-     "execution_count": 60,
+     "execution_count": 78,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "df = analyze(['log_64-aa', 'log_64-ab'])\n",
+    "overall_time[\"64\"] = df.loc[\"Py_kgeneration\"][(\"time\", \"sum\")]\n",
+    "overall_memory[\"64\"] = abs(df.loc[\"Py_kgeneration\"][(\"memory\", \"median\")])\n",
     "df"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 128,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 600x600 with 4 Axes>"
       ]
@@ -4456,7 +4584,39 @@
     }
    ],
    "source": [
-    "plot_analysis(df)"
+    "plot_pie_charts(df, \"Time comparisons\", (\"time\", \"sum\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/oli/.local/lib/python3.6/site-packages/ipykernel_launcher.py:13: RuntimeWarning:\n",
+      "\n",
+      "invalid value encountered in double_scalars\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pie_charts(df, \"Memory comparisons\", (\"memory\", \"median\"))"
    ]
   },
   {
@@ -5750,6 +5910,8 @@
    ],
    "source": [
     "df = analyze(['log_128-aa', 'log_128-ab', 'log_128-ac', 'log_128-ad', 'log_128-ae', 'log_128-af', 'log_128-ag', 'log_128-ah', 'log_128-ai', 'log_128-aj', 'log_128-ak'])\n",
+    "overall_time[\"128\"] = df.loc[\"Py_kgeneration\"][(\"time\", \"sum\")]\n",
+    "overall_memory[\"128\"] = abs(df.loc[\"Py_kgeneration\"][(\"memory\", \"median\")])\n",
     "df"
    ]
   },
@@ -5770,7 +5932,16 @@
     }
    ],
    "source": [
-    "plot_analysis(df)"
+    "plot_pie_charts(df, \"Time comparisons\", (\"time\", \"sum\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_pie_charts(df, \"Memory comparisons\", (\"memory\", \"median\"))"
    ]
   },
   {
@@ -6762,6 +6933,8 @@
    ],
    "source": [
     "df = analyze(['log_256-aa', 'log_256-ab', 'log_256-ac'])\n",
+    "overall_time[\"256\"] = df.loc[\"Py_kgeneration\"][(\"time\", \"sum\")]\n",
+    "overall_memory[\"256\"] = abs(df.loc[\"Py_kgeneration\"][(\"memory\", \"median\")])\n",
     "df"
    ]
   },
@@ -7033,7 +7206,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "plot_analysis(df)"
+    "plot_pie_charts(df, \"Time comparisons\", (\"time\", \"sum\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_pie_charts(df, \"Memory comparisons\", (\"memory\", \"median\"))"
    ]
   },
   {
@@ -7045,6 +7227,88 @@
     "plot_treemap(df)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Comparison between different sizes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_overall_comparison(info, title, unit):\n",
+    "    fig = plt.figure()\n",
+    "    plt.title(title)\n",
+    "    plt.bar(info.keys(),info.values())\n",
+    "    plt.ylabel(unit)\n",
+    "    plt.xlabel(\"sizes\")\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'8': 0.544398, '16': 2.908668, '32': 22.135483, '64': 178.629961}\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(overall_time)\n",
+    "plot_overall_comparison(overall_time, \"Overall Time Comparison\", \"seconds\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'8': 0.2, '16': 11.1, '32': 53.6, '64': 304.2}\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print(overall_memory)\n",
+    "plot_overall_comparison(overall_memory, \"Overall Mermory Comparison\", \"MB\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -7363,6 +7627,18 @@
     "plot_reapeated_data_distribution(data)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TODO\n",
+    "\n",
+    "- Completar analisis de memoria y cpu\n",
+    "- Investigar mas el tema de llamadas a funciones repetidas (gasdev, cov_value, ran2)\n",
+    "- Escribir conclusiones (proximos pasos y cosas que no se consideran importantes)\n",
+    "- Conseguir ayuda en tupac para poder correrlo"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -7373,21 +7649,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.18"
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,
diff --git a/fftma_module/gen/save_logs.sh b/fftma_module/gen/save_logs.sh
index 6a2257b..f12fd6a 100755
--- a/fftma_module/gen/save_logs.sh
+++ b/fftma_module/gen/save_logs.sh
@@ -1,2 +1,2 @@
 python3 setup.py install --user
-ENV=true python3 test.py $1 2>&1 | split -l 5000000 - log_$1-
\ No newline at end of file
+ENV=analysis python3 test.py $1 2>&1 | split -l 5000000 - log_$1-
\ No newline at end of file