Add notebook for keep-alive network.

rt_analyzer/notebooks/keep_alive_measurements/timestamp_notebook.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "439adf9f",
+   "metadata": {},
+   "source": [
+    "## Measurements of keep-alive network between one master coupler and  two slave couplers with cycle time of 5ms"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a19f317d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b9dad676",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f=open(\"coupler0_duration.txt\", \"r\")\n",
+    "lines = f.readlines()\n",
+    "f.close()\n",
+    "lines = [float(x.replace(\"\\n\", \"\")) for x  in lines[:]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d0d49bb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {}\n",
+    "i = 0\n",
+    "for x in lines:\n",
+    "    d[i] = x\n",
+    "    i += 1\n",
+    "s = pd.Series(d, name='duration')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "16a57b80",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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9v//+e9dtoJLUqlUrxcTEaMaMGTp16pQ6dOig9evXa9asWerVq5fbGZXhw4dr1KhR6tOnj7p27aoff/xRycnJqlq1aq51ZGVlqUuXLurfv7/27Nmjt99+W7feeqt69uyZZ+333nuv5s2bp1GjRmnFihVq166dLly4oN27d2vevHlKTk7O9Rbq/Hjqqac0f/58derUSY888ogyMjL06quvqkWLFho2bFiBltWrVy8lJCRoyJAh8vf317vvvquwsDC98MILmjBhgg4ePKhevXqpcuXKOnDggBYuXKiRI0fqiSeeUJkyZfSf//xH0dHRatasmYYNG6ZatWrp119/1YoVK+Tv769Fixa5re/AgQPq2bOnunfvrjVr1ujDDz/U4MGD1apVqyvWefvtt+uNN95Q9+7dNXjwYB0/flzx8fFq0KCBtm7dWuBtKEk33XSTGjRooKefflpOp9PtspL015mm6dOn695779VNN92kgQMHqlq1ajp8+LC++OILtWvXTv/+97/zXP64ceP0wQcfqHv37nrkkUdct19fPMtxqYLuk7m544479MEHH8jhcKhp06Zas2aNvv76awUGBrq1u+GGG1S2bFm98sorSktLk91uV+fOnVW9evUcyxw5cqTeffddDR06VJs2bVLdunX1ySef6LvvvtPUqVPz3RkfuCIP3jEFlIiffvrJGjFihFW3bl2rQoUKVuXKla127dpZ06ZNc7vV+Pz589bkyZOtevXqWeXLl7dCQkKsCRMm5Lgd+cKFC9b48eOtqlWrWhUrVrSioqKsffv25Xmr66pVq6yRI0da1113neXn52fdc8891smTJ92Wefltq5b1122qr7zyitWsWTPLbrdb1113nRUeHm5NnjzZSktLc7WTZMXGxhZom2zfvt3q1q2bVbFiRSsgIMC65557rJSUlKvOd+nt15d6++23LUnWE0884Rr36aefWrfeeqtVqVIlq1KlSlbjxo2t2NhYa8+ePW7zbt682erdu7cVGBho2e12KzQ01Orfv7+1bNkyV5uLt1/v3LnT6tu3r1W5cmXruuuus0aPHm2dPXs2X+/5/ffftxo2bGjZ7XarcePGVkJCgmu5l7ra7deXevrppy1JVoMGDfJc74oVK6yoqCjL4XBYPj4+VlhYmDV06FBr48aNV61569atVocOHSwfHx+rVq1a1vPPP2+9//77OW6/Lug+uWHDhhzr+uOPP6xhw4ZZVatWtfz8/KyoqChr9+7dOZZhWZb13nvvWfXr17fKli3rtm1y249TU1Ndy61QoYLVokULKyEhwa1NXvuVZeV9azlwkc2y6EUFFIeZM2dq2LBh2rBhQ6HPnuAvkyZN0uTJk3XixIkCnWUAUPrRRwYAABiLIAMAAIxFkAEAAMaijwwAADAWZ2QAAICxCDIAAMBYpf6BeNnZ2Tp69KgqV65cpI96BwAAxceyLJ0+fVrBwcE5/vDopUp9kDl69GiOP7AHAADMcOTIEdWuXTvP6aU+yFx8BPaRI0fk7+/v4WoAAEB+pKenKyQk5Kp/yqLUB5mLl5P8/f0JMgAAGOZq3ULo7AsAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsQgyAADAWAQZAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADCWR4PM9OnT1bJlS/n7+8vf318RERFaunSpa3rHjh1ls9nchlGjRnmwYgAA4E3KeXLltWvX1ssvv6yGDRvKsizNmjVLd911lzZv3qxmzZpJkkaMGKH//u//ds1TsWJFT5ULAAC8jEeDzJ133un2+sUXX9T06dO1du1aV5CpWLGigoKCPFEeAADwcl7TR+bChQuaM2eOMjMzFRER4Rr/0UcfqWrVqmrevLkmTJigM2fOXHE5TqdT6enpbgMAACidPHpGRpK2bdumiIgInTt3Tn5+flq4cKGaNm0qSRo8eLBCQ0MVHBysrVu3avz48dqzZ48WLFiQ5/Li4uI0efLkkiofAAB4kM2yLMuTBWRlZenw4cNKS0vTJ598ov/85z9atWqVK8xcavny5erSpYv27dunsLCwXJfndDrldDpdr9PT0xUSEqK0tDT5+/sX2/sAAABFJz09XQ6H46rHb48HmctFRkYqLCxM7777bo5pmZmZ8vPzU1JSkqKiovK1vPxuCAAA4D3ye/z2mj4yF2VnZ7udUbnUli1bJEk1a9YswYoAAIC38mgfmQkTJig6Olp16tTR6dOnlZiYqJUrVyo5OVn79+9XYmKievToocDAQG3dulWPPfaY2rdvr5YtW3qybAAA4CU8GmSOHz+uIUOG6NixY3I4HGrZsqWSk5PVtWtXHTlyRF9//bWmTp2qzMxMhYSEqE+fPnrmmWc8WTIAAPAiXtdHpqjRRwYAAPMY20cGAAAgvwgyAADAWAQZAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsQgyAADAWAQZAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABjLo0Fm+vTpatmypfz9/eXv76+IiAgtXbrUNf3cuXOKjY1VYGCg/Pz81KdPH6WmpnqwYgAA4E08GmRq166tl19+WZs2bdLGjRvVuXNn3XXXXdqxY4ck6bHHHtOiRYs0f/58rVq1SkePHlXv3r09WTIAAPAiNsuyLE8XcakqVaro1VdfVd++fVWtWjUlJiaqb9++kqTdu3erSZMmWrNmjdq2bZuv5aWnp8vhcCgtLU3+/v7FWToAACgi+T1+e00fmQsXLmjOnDnKzMxURESENm3apPPnzysyMtLVpnHjxqpTp47WrFmT53KcTqfS09PdBgAAUDp5PMhs27ZNfn5+stvtGjVqlBYuXKimTZsqJSVFFSpUUEBAgFv7GjVqKCUlJc/lxcXFyeFwuIaQkJBifgcAAMBTPB5kGjVqpC1btmjdunV68MEHFRMTo507dxZ6eRMmTFBaWpprOHLkSBFWCwAAvEk5TxdQoUIFNWjQQJIUHh6uDRs26M0339SAAQOUlZWlU6dOuZ2VSU1NVVBQUJ7Ls9vtstvtxV02AADwAh4/I3O57OxsOZ1OhYeHq3z58lq2bJlr2p49e3T48GFFRER4sEIAAOAtPHpGZsKECYqOjladOnV0+vRpJSYmauXKlUpOTpbD4dD999+vsWPHqkqVKvL399eYMWMUERGR7zuWAABA6ebRIHP8+HENGTJEx44dk8PhUMuWLZWcnKyuXbtKkv71r3+pTJky6tOnj5xOp6KiovT22297smQAAOBFvO45MkWN58gAAGAe454jAwAAUFAEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsQgyAADAWAQZAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsQgyAADAWAQZAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADG8miQiYuL080336zKlSurevXq6tWrl/bs2ePWpmPHjrLZbG7DqFGjPFQxAADwJh4NMqtWrVJsbKzWrl2rr776SufPn1e3bt2UmZnp1m7EiBE6duyYa5gyZYqHKgYAAN6knCdXnpSU5PZ65syZql69ujZt2qT27du7xlesWFFBQUElXR4AAPByXtVHJi0tTZJUpUoVt/EfffSRqlatqubNm2vChAk6c+ZMnstwOp1KT093GwAAQOnk0TMyl8rOztajjz6qdu3aqXnz5q7xgwcPVmhoqIKDg7V161aNHz9ee/bs0YIFC3JdTlxcnCZPnlxSZQMAAA+yWZZleboISXrwwQe1dOlSffvtt6pdu3ae7ZYvX64uXbpo3759CgsLyzHd6XTK6XS6XqenpyskJERpaWny9/cvltoBAEDRSk9Pl8PhuOrx2yvOyIwePVqLFy/W6tWrrxhiJKlNmzaSlGeQsdvtstvtxVInAADwLh4NMpZlacyYMVq4cKFWrlypevXqXXWeLVu2SJJq1qxZzNUBAABv59EgExsbq8TERH3++eeqXLmyUlJSJEkOh0O+vr7av3+/EhMT1aNHDwUGBmrr1q167LHH1L59e7Vs2dKTpQMAAC/g0T4yNpst1/EJCQkaOnSojhw5ov/6r//S9u3blZmZqZCQEN1999165pln8t3fJb/X2AAAgPcwoo/M1TJUSEiIVq1aVULVAAAA03jVc2QAAAAKgiADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsQgyAADAWAQZAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLE8GmTi4uJ08803q3Llyqpevbp69eqlPXv2uLU5d+6cYmNjFRgYKD8/P/Xp00epqakeqhgAAHgTjwaZVatWKTY2VmvXrtVXX32l8+fPq1u3bsrMzHS1eeyxx7Ro0SLNnz9fq1at0tGjR9W7d28PVg0AALyFzbIsy9NFXHTixAlVr15dq1atUvv27ZWWlqZq1aopMTFRffv2lSTt3r1bTZo00Zo1a9S2bdurLjM9PV0Oh0NpaWny9/cv7rcAAACKQH6P317VRyYtLU2SVKVKFUnSpk2bdP78eUVGRrraNG7cWHXq1NGaNWtyXYbT6VR6errbAAAASievCTLZ2dl69NFH1a5dOzVv3lySlJKSogoVKiggIMCtbY0aNZSSkpLrcuLi4uRwOFxDSEhIcZcOAAA8xGuCTGxsrLZv3645c+Zc03ImTJigtLQ013DkyJEiqhAAAHibcp4uQJJGjx6txYsXa/Xq1apdu7ZrfFBQkLKysnTq1Cm3szKpqakKCgrKdVl2u112u724SwYAAF6gUGdkZs2apS+++ML1ety4cQoICNAtt9yiQ4cO5Xs5lmVp9OjRWrhwoZYvX6569eq5TQ8PD1f58uW1bNky17g9e/bo8OHDioiIKEzpAACgFClUkHnppZfk6+srSVqzZo3i4+M1ZcoUVa1aVY899li+lxMbG6sPP/xQiYmJqly5slJSUpSSkqKzZ89KkhwOh+6//36NHTtWK1as0KZNmzRs2DBFRETk644lAABQuhXq9uuKFStq9+7dqlOnjsaPH69jx45p9uzZ2rFjhzp27KgTJ07kb+U2W67jExISNHToUEl/PRDv8ccf18cffyyn06moqCi9/fbbeV5auhy3XwMAYJ78Hr8L1UfGz89PJ0+eVJ06dfTll19q7NixkiQfHx/X2ZT8yE+G8vHxUXx8vOLj4wtTKgAAKMUKFWS6du2q4cOH68Ybb9RPP/2kHj16SJJ27Nih0NDQIi0QAAAgL4XqIxMfH6+IiAidOHFCn376qQIDAyX99QC7wYMHF2mBAAAAeSn0nyg4d+6ctm7dquPHjys7O9ttWs+ePYukuKJAHxkAAMxTrH1kkpKSNGTIEJ08eTJHPxebzaYLFy4UZrEAAAAFUqhLS2PGjFG/fv109OhRZWdnuw2EGAAAUFIKFWRSU1M1duxY1ahRo6jrAQAAyLdCBZm+fftq5cqVRVwKAABAwRSqs++ZM2fUr18/VatWTS1atFD58uXdpj/88MNFVuC1orMvAADmKdbOvh9//LG+/PJL+fj4aOXKlW5P6LXZbF4VZAAAQOlVqCDz9NNPa/LkyfrnP/+pMmUKdXUKAADgmhUqhWRlZWnAgAGEGAAA4FGFSiIxMTGaO3duUdcCAABQIIW6tHThwgVNmTJFycnJatmyZY7Ovm+88UaRFAcAAHAlhQoy27Zt04033ihJ2r59u9u0Szv+AgAAFKdCBZkVK1YUdR0AAAAFRm9dAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsTwaZFavXq0777xTwcHBstls+uyzz9ymDx06VDabzW3o3r27Z4oFAABex6NBJjMzU61atVJ8fHyebbp3765jx465ho8//rgEKwQAAN6snCdXHh0drejo6Cu2sdvtCgoKKqGKAACASby+j8zKlStVvXp1NWrUSA8++KBOnjx5xfZOp1Pp6eluAwAAKJ28Osh0795ds2fP1rJly/TKK69o1apVio6O1oULF/KcJy4uTg6HwzWEhISUYMUAAKAk2SzLsjxdhCTZbDYtXLhQvXr1yrPNzz//rLCwMH399dfq0qVLrm2cTqecTqfrdXp6ukJCQpSWliZ/f/+iLhsAABSD9PR0ORyOqx6/vfqMzOXq16+vqlWrat++fXm2sdvt8vf3dxsAAEDpZFSQ+eWXX3Ty5EnVrFnT06UAAAAv4NG7ljIyMtzOrhw4cEBbtmxRlSpVVKVKFU2ePFl9+vRRUFCQ9u/fr3HjxqlBgwaKioryYNUAAMBbeDTIbNy4UZ06dXK9Hjt2rCQpJiZG06dP19atWzVr1iydOnVKwcHB6tatm55//nnZ7XZPlQwAALyI13T2LS757SwEAAC8R6ns7AsAAHApggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsQgyAADAWAQZAABgLIIMAAAwFkEGAAAYiyADAACMRZABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxvJokFm9erXuvPNOBQcHy2az6bPPPnObblmWnnvuOdWsWVO+vr6KjIzU3r17PVMsAADwOh4NMpmZmWrVqpXi4+NznT5lyhS99dZbeuedd7Ru3TpVqlRJUVFROnfuXAlXCgAAvFE5T648Ojpa0dHRuU6zLEtTp07VM888o7vuukuSNHv2bNWoUUOfffaZBg4cWJKlAgAAL+S1fWQOHDiglJQURUZGusY5HA61adNGa9asyXM+p9Op9PR0twEAAJROXhtkUlJSJEk1atRwG1+jRg3XtNzExcXJ4XC4hpCQkGKtEwAAeI7XBpnCmjBhgtLS0lzDkSNHPF0SAAAoJl4bZIKCgiRJqampbuNTU1Nd03Jjt9vl7+/vNgAAgNLJa4NMvXr1FBQUpGXLlrnGpaena926dYqIiPBgZQAAwFt49K6ljIwM7du3z/X6wIED2rJli6pUqaI6dero0Ucf1QsvvKCGDRuqXr16evbZZxUcHKxevXp5rmgAAOA1PBpkNm7cqE6dOrlejx07VpIUExOjmTNnaty4ccrMzNTIkSN16tQp3XrrrUpKSpKPj4+nSgYAAF7EZlmW5ekiilN6erocDofS0tLoLwMAgCHye/z22j4yAAAAV0OQAQCgGNX95xeeLqFUI8gAAABjEWQAAICxCDIAAMBYBBkAAGAsggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAMARPCc6JIAMAAIxFkAEASOLbPsxEkAFwzTgAAvAUggwAADAWQQYAABiLIAMAAIxFkAEAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAMA1Kq4/mskf48RF7At5I8gAAABjEWRQIHwrAAB4E4IMgCsivJYefJYojQgyAADAaxQ0cBNkAACAsQgyJYxTuwAAFB2CDAAAMBZBBgCAK+BMuncjyFyCnRXehP0RAK6OIGMg0w5w3lhvbjUVZ50Xl33pOkp6u3jj53CtSuN7KmmmbcPL6y3u+j25fUz7bPKjIO+p+cTkfLXz6iAzadIk2Ww2t6Fx48ZFuo7C7ijetoNdSz0lfXAtynWU9KPhCzq+uHnDfugNNVyuMDV5ywGrIHUUV9uiWJ637BclWYe3vOdLFfZzKokve0V17PHqICNJzZo107Fjx1zDt99+6+mSXPK7g+T1DSI/H1xJftvIz/8Lsoxrrclbwpm3/HIqytBd0mek8lpHSa6zoOvy5lDvTbXV/ecXJfIz5i0/h0WlKH5Heds2Key+cK3bwuuDTLly5RQUFOQaqlatWuI1FOXBuTjbeurgVBAlcfnG08u41nXk9pma8ouuNB6QChuACvvFoCjr8Zb9piTO+ubn919JhrPCKq7fYyVx1q8o5y0Irw8ye/fuVXBwsOrXr6977rlHhw8fvmJ7p9Op9PR0tyE3xXV5w1sum5h2sCgJRXlZyJN9XfLDtH4DxRWASiJYeeO+4C11XIk3huyS4C2XMK91Pm/ZnpKXB5k2bdpo5syZSkpK0vTp03XgwAHddtttOn36dJ7zxMXFyeFwuIaQkJASrPjvw5t2YgDA35dXB5no6Gj169dPLVu2VFRUlJYsWaJTp05p3rx5ec4zYcIEpaWluYYjR46UYMUAAFPxBc1M5TxdQEEEBATo+uuv1759+/JsY7fbZbfbS7AqAADgKV59RuZyGRkZ2r9/v2rWrOnpUgAAgBfw6iDzxBNPaNWqVTp48KC+//573X333SpbtqwGDRrk6dIAAJDEJSlP8+og88svv2jQoEFq1KiR+vfvr8DAQK1du1bVqlUr9nWzYxat0vIsFwCAd/HqPjJz5szxdAko5QhIZrj8FueDL9/uwWoAeBOvPiODwinK56UAnuTJR/CjZJWWz6+wT0Uv7DrwNwsyRXGAL8mnUno7Ex5oZeJ29QYmPrSrKNfBflN43vJQ0OJericeClkSdRSVkqzrbxVk4F288YmoJa0o/q7UtS7LE48uL4r5i4O3vn9PPjK/IEyo8Vp4w5feonKlp/V6S0jLL4JMAXj7jultTP5bJYVdT2nfR4ry74ChaBXXJeXi/ByL62eoNAUOE3h6GxJkAMN4+pcGAO/zd/69QJABAADGIsgAAABjEWQAAICxCDIAAMBYBBkAAGAsggyM83funQ8AcEeQAQAAxiLIAMgVZ74AmIAgAwAwCiEblyLIAMDfDEEApQlBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsQgy8GrcXQEAuBKCDAAAMBZBBgAAGIsgAwAAjEWQ+Zui7wkA0/F7DBJBxhj8wAKex88h4H0IMkAx4aBXfNi2AC4iyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxiLIAAAAYxFkAACAsYwIMvHx8apbt658fHzUpk0brV+/3tMlAQAAL+D1QWbu3LkaO3asJk6cqB9++EGtWrVSVFSUjh8/7unSAACAh3l9kHnjjTc0YsQIDRs2TE2bNtU777yjihUr6n/+5388XRoAAPCwcp4u4EqysrK0adMmTZgwwTWuTJkyioyM1Jo1a3Kdx+l0yul0ul6npaVJktLT05XtPKP09HRJcv0/23nmitOv1Lak56O2op+P2kpfbVeaj9pKX21Xmo/azK9NkizL0hVZXuzXX3+1JFnff/+92/gnn3zSat26da7zTJw40ZLEwMDAwMDAUAqGI0eOXDErePUZmcKYMGGCxo4d63qdnZ2t33//XYGBgbLZbB6sDAAA5JdlWTp9+rSCg4Ov2M6rg0zVqlVVtmxZpaamuo1PTU1VUFBQrvPY7XbZ7Xa3cQEBAcVVIgAAKCYOh+Oqbby6s2+FChUUHh6uZcuWucZlZ2dr2bJlioiI8GBlAADAG3j1GRlJGjt2rGJiYvSPf/xDrVu31tSpU5WZmalhw4Z5ujQAAOBhXh9kBgwYoBMnTui5555TSkqKbrjhBiUlJalGjRqeLg0AAHiYzbKudl8TAJjh4MGDqlevnjZv3qwbbrjB0+UAKAFe3UcGQOmTkpKiMWPGqH79+rLb7QoJCdGdd97p1hcOAPLL6y8tASg9Dh48qHbt2ikgIECvvvqqWrRoofPnzys5OVmxsbHavXu3p0sEYBjOyAAoMQ899JBsNpvWr1+vPn366Prrr1ezZs00duxYrV27Vvfdd5/uuOMOt3nOnz+v6tWr6/3335f0152LU6ZMUYMGDWS321WnTh29+OKLea5z+/btio6Olp+fn2rUqKF7771Xv/32m2v6J598ohYtWsjX11eBgYGKjIxUZmZm8WwAAEWOIAOgRPz+++9KSkpSbGysKlWqlGN6QECAhg8frqSkJB07dsw1fvHixTpz5owGDBgg6a+HXr788st69tlntXPnTiUmJubZ+f/UqVPq3LmzbrzxRm3cuFFJSUlKTU1V//79JUnHjh3ToEGDdN9992nXrl1auXKlevfuffVHogPwGnT2BVAi1q9frzZt2mjBggW6++6782zXrFkzxcTEaNy4cZKknj17KjAwUAkJCTp9+rSqVaumf//73xo+fHiOeS/v7PvCCy/om2++UXJysqvNL7/8opCQEO3Zs0cZGRkKDw/XwYMHFRoaWvRvGkCx44wMgBKR3+9Mw4cPV0JCgqS/nuK9dOlS3XfffZKkXbt2yel0qkuXLvla1o8//qgVK1bIz8/PNTRu3FiStH//frVq1UpdunRRixYt1K9fP7333nv6448/CvHuAHgKQQZAiWjYsKFsNttVO/QOGTJEP//8s9asWaMPP/xQ9erV02233SZJ8vX1LdA6MzIydOedd2rLli1uw969e9W+fXuVLVtWX331lZYuXaqmTZtq2rRpatSokQ4cOFDo9wmgZBFkAJSIKlWqKCoqSvHx8bl2pj116pQkKTAwUL169VJCQoJmzpzp9hTvhg0bytfXN9+3at90003asWOH6tatqwYNGrgNF/vp2Gw2tWvXTpMnT9bmzZtVoUIFLVy48NrfMIASQZABUGLi4+N14cIFtW7dWp9++qn27t2rXbt26a233nL7+2nDhw/XrFmztGvXLsXExLjG+/j4aPz48Ro3bpxmz56t/fv3a+3ata47mi4XGxur33//XYMGDdKGDRu0f/9+JScna9iwYbpw4YLWrVunl156SRs3btThw4e1YMECnThxQk2aNCn2bQGgaPAcGQAlpn79+vrhhx/04osv6vHHH9exY8dUrVo1hYeHa/r06a52kZGRqlmzppo1a6bg4GC3ZTz77LMqV66cnnvuOR09elQ1a9bUqFGjcl1fcHCwvvvuO40fP17dunWT0+lUaGiounfvrjJlysjf31+rV6/W1KlTlZ6ertDQUL3++uuKjo4u1u0AoOhw1xIAr5ORkaFatWopISFBvXv39nQ5ALwYZ2QAeI3s7Gz99ttvev311xUQEKCePXt6uiQAXo4gA8BrHD58WPXq1VPt2rU1c+ZMlSvHrygAV8alJQAAYCzuWgIAAMYiyAAAAGMRZAAAgLEIMgAAwFgEGQAAYCyCDAAAMBZBBgAAGIsgAwAAjEWQAQAAxvo/xG6xljBmklkAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.plot.bar()\n",
+    "plt.title(\"Coupler 0 keep-alive duration\")\n",
+    "plt.xlabel('Cycles', fontsize=10)\n",
+    "plt.ylabel('ms', fontsize=10)\n",
+    "plt.xticks([])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "1b5ee5ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f=open(\"coupler1_duration.txt\", \"r\")\n",
+    "lines = f.readlines()\n",
+    "f.close()\n",
+    "lines = [float(x.replace(\"\\n\", \"\")) for x  in lines[:]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "18f16b77",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {}\n",
+    "i = 0\n",
+    "for x in lines:\n",
+    "    d[i] = x\n",
+    "    i += 1\n",
+    "s = pd.Series(d, name='duration')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b44f4d70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s.plot.bar()\n",
+    "plt.title(\"Coupler 1 keep-alive duration\")\n",
+    "plt.xlabel('Cycles', fontsize=10)\n",
+    "plt.ylabel('ms', fontsize=10)\n",
+    "plt.xticks([])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "552fc7b3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}