exploration/visualization_experiment.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "from functools import reduce\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(os.path.join('..', 'data.csv'), sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>link</th>\n",
       "      <th>image</th>\n",
       "      <th>inputR1</th>\n",
       "      <th>inputR2</th>\n",
       "      <th>inputR3</th>\n",
       "      <th>inputT1</th>\n",
       "      <th>inputT2</th>\n",
       "      <th>inputT3</th>\n",
       "      <th>outputR1</th>\n",
       "      <th>outputR2</th>\n",
       "      <th>outputR3</th>\n",
       "      <th>outputT1</th>\n",
       "      <th>outputT2</th>\n",
       "      <th>outputT3</th>\n",
       "      <th>comments</th>\n",
       "      <th>created</th>\n",
       "      <th>transmission</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>Bevel gears</td>\n",
       "      <td>https://grabcad.com/library/parametric-bevel-g...</td>\n",
       "      <td>img/0002-bevelgears.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-08 07:25:40.627309</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>Belt drive (quarter turn)</td>\n",
       "      <td>https://www.youtube.com/watch?v=RpVSn_ZZCOI</td>\n",
       "      <td>img/0003-beltdrive-quarterturn.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-08 07:26:13.541636</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>Two stage gearbox</td>\n",
       "      <td>https://grabcad.com/library/2-stage-gear-box</td>\n",
       "      <td>img/0005-twostage-gearbox.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-08 07:27:38.854208</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>Cam follower</td>\n",
       "      <td>https://grabcad.com/library/cam-and-follower-13</td>\n",
       "      <td>img/0010-cam-follower.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-08 07:28:21.610800</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>Belt drive (flat)</td>\n",
       "      <td>http://507movements.com/mm_001.html</td>\n",
       "      <td>img/0014-beltdrive-flat.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018-05-08 07:28:57.759737</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                       name  \\\n",
       "0   3                Bevel gears   \n",
       "1   4  Belt drive (quarter turn)   \n",
       "2   6          Two stage gearbox   \n",
       "3   7               Cam follower   \n",
       "4   8          Belt drive (flat)   \n",
       "\n",
       "                                                link  \\\n",
       "0  https://grabcad.com/library/parametric-bevel-g...   \n",
       "1        https://www.youtube.com/watch?v=RpVSn_ZZCOI   \n",
       "2       https://grabcad.com/library/2-stage-gear-box   \n",
       "3    https://grabcad.com/library/cam-and-follower-13   \n",
       "4                http://507movements.com/mm_001.html   \n",
       "\n",
       "                                image  inputR1  inputR2  inputR3  inputT1  \\\n",
       "0             img/0002-bevelgears.jpg        1        0        0        0   \n",
       "1  img/0003-beltdrive-quarterturn.jpg        1        0        0        0   \n",
       "2       img/0005-twostage-gearbox.jpg        1        0        0        0   \n",
       "3           img/0010-cam-follower.jpg        1        0        0        0   \n",
       "4         img/0014-beltdrive-flat.jpg        1        0        0        0   \n",
       "\n",
       "   inputT2  inputT3  outputR1  outputR2  outputR3  outputT1  outputT2  \\\n",
       "0        0        0         0         1         0         0         0   \n",
       "1        0        0         0         1         0         0         0   \n",
       "2        0        0         1         0         0         0         0   \n",
       "3        0        0         0         0         0         1         0   \n",
       "4        0        0         1         0         0         0         0   \n",
       "\n",
       "   outputT3  comments                     created  transmission  \n",
       "0         0       NaN  2018-05-08 07:25:40.627309            10  \n",
       "1         0       NaN  2018-05-08 07:26:13.541636             1  \n",
       "2         0       NaN  2018-05-08 07:27:38.854208            20  \n",
       "3         0       NaN  2018-05-08 07:28:21.610800             1  \n",
       "4         0       NaN  2018-05-08 07:28:57.759737             1  "
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputRotations = ['inputR1', 'inputR2', 'inputR3']\n",
    "inputTranslations = ['inputT1', 'inputT2', 'inputT3']\n",
    "inputs = inputRotations + inputTranslations\n",
    "outputRotations = ['outputR1', 'outputR2', 'outputR3']\n",
    "outputTranslations = ['outputT1', 'outputR2', 'outputT3']\n",
    "outputs = outputRotations + outputTranslations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "inRot = [df[col] for col in inputRotations]\n",
    "inTrans = [df[col] for col in inputTranslations]\n",
    "inAny = inRot + inTrans\n",
    "outRot = [df[col] for col in outputRotations]\n",
    "outTrans = [df[col] for col in outputTranslations]\n",
    "outAny = outRot + outTrans"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total Number of Output Rotations depending on ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JUqvXUEhybJLrkmxIcvoOHn9lkvVJrkzyL0kO7rMeSdL0eguFJIsZrOV8HHAYcHKSw6Z0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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109d84a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputs = reduce((lambda x, y: x + y), inAny)\n",
    "totalOutputRotations = reduce((lambda x, y: x + y), outRot)\n",
    "plt.plot(totalInputs, totalOutputRotations, 'ro')\n",
    "plt.xlabel('totalInputs')\n",
    "plt.ylabel('totalOutputRotations')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7D+iNiH3Jekh/pqp4zMystSrvFA4CVkXE6oh4AbgSmF2sEBGLIuLZtHo3MKHCeMzMrIUq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\nzMws56RgZma5/wHZKEIC5AMpqAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1062e0828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputTranslations = reduce((lambda x, y: x + y), inTrans)\n",
    "totalOutputRotations = reduce((lambda x, y: x + y), outRot)\n",
    "plt.plot(totalInputTranslations, totalOutputRotations, 'ro')\n",
    "plt.xlabel('totalInputTranslations')\n",
    "plt.ylabel('totalOutputRotations')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a6cf240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputRotations = reduce((lambda x, y: x + y), inRot)\n",
    "totalOutputRotations = reduce((lambda x, y: x + y), outRot)\n",
    "plt.plot(totalInputRotations, totalOutputRotations, 'ro')\n",
    "plt.xlabel('totalInputRotations')\n",
    "plt.ylabel('totalOutputRotations')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total Number of Output Translations depending on ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ab3b5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputs = reduce((lambda x, y: x + y), inAny)\n",
    "totalOutputTranslations = reduce((lambda x, y: x + y), outTrans)\n",
    "plt.plot(totalInputs, totalOutputTranslations, 'ro')\n",
    "plt.xlabel('totalInputs')\n",
    "plt.ylabel('totalOutputTranslation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ac6a748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputTranslations = reduce((lambda x, y: x + y), inTrans)\n",
    "totalOutputTranslations = reduce((lambda x, y: x + y), outTrans)\n",
    "plt.plot(totalInputTranslations, totalOutputTranslations, 'ro')\n",
    "plt.xlabel('totalInputTranslations')\n",
    "plt.ylabel('totalOutputTranslation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nA39TKN8BrKkyKDMza49GTzRvBk6Q9Crg2LRoQ0TsakVwZmbWWmWeaH4PcD/wHuC9wH2S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\nYGZmOScFMzPL/X+iz1zWO5sSZwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105f910f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputRotations = reduce((lambda x, y: x + y), inRot)\n",
    "totalOutputTranslations = reduce((lambda x, y: x + y), outTrans)\n",
    "plt.plot(totalInputRotations, totalOutputTranslations, 'ro')\n",
    "plt.xlabel('totalInputRotations')\n",
    "plt.ylabel('totalOutputTranslation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total Number of Outputs depending on ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ac84e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputs = reduce((lambda x, y: x + y), inAny)\n",
    "totalOutputs = reduce((lambda x, y: x + y), outAny)\n",
    "plt.plot(totalInputs, totalOutputs, 'ro')\n",
    "plt.xlabel('totalInputs')\n",
    "plt.ylabel('totalOutputs')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JM6X584EbI+J1wCl1+3xJbFH0JHso8BOKzjK/Wt5xunX2FeAdEXEoxdXRzsYJ\n8Hx9DGn+L4HzKBLI3ZLG78IxbDfkhGFDyWaKYSih+OX4LkkdkiZS/PV7V10dKG7vPJb+en8vxS2s\nnTVV0lFp/t0Ut2+guHXT2437qX3E24x92d7N9LyBKqd/vyLim8C5FEOJlr0M+B3wG0l7Z8Z4J3Cs\npP1TQ/wciqu4/hwUxYhu/4ui48LBGvDJBokThg0Z6S/p29OtmqMoeui8h2L0vH+IiP9KZdtSw+vZ\nwEXAXEn3UHRv/kzjvWdZDXxI0gMU3UFfnMo/BXxJUjfFX9y9vgu8Y6BG7wY+C3xe0t0UbQ4DmQLc\nKmkFcBnwifLKdN6uAO6n6Oa6PCLbZcClvY3epW3WUfziv4WiB9SlEfGfA8TxxXTrbyVwc0TclxG7\nDSPurdaMF4e//F66TWRmDfgKw8zMsvgKw8zMsvgKw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyL\nE4aZmWX5/wfpR40wvXt5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ac6a710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputTranslations = reduce((lambda x, y: x + y), inTrans)\n",
    "totalOutputs = reduce((lambda x, y: x + y), outAny)\n",
    "plt.plot(totalInputTranslations, totalOutputs, 'ro')\n",
    "plt.xlabel('totalInputTranslations')\n",
    "plt.ylabel('totalOutputs')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Sa4DxwH+WysZL2jeNTwDeSt9tH2Zm1gY5Zxg3SLoRuDpNvwe4fqCFImKHpHOAG4HRwKKI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\nOGGYmVkWJwwzM8vy/wH8xy6enOb4EgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105f910b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputRotations = reduce((lambda x, y: x + y), inRot)\n",
    "totalOutputs = reduce((lambda x, y: x + y), outAny)\n",
    "plt.plot(totalInputRotations, totalOutputs, 'ro')\n",
    "plt.xlabel('totalInputRotations')\n",
    "plt.ylabel('totalOutputs')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Misc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x109d7e7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalOutputs = reduce((lambda x, y: x + y), outAny).sort_values()\n",
    "plt.plot(df['id'], totalOutputs, 'ro')\n",
    "plt.xlabel('Mechanism ID')\n",
    "plt.ylabel('totalOutputs')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IktQYCpKkxlDox45xFzBG07ztMN3b77ZPAM8pSJIajxQkSY2hsIaS3J5kT5Ibk0z8U/uS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\nBUlSYyhIkhpDQZLU/Bd4QLoBSBJ40wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a88b470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "totalInputs = reduce((lambda x, y: x + y), inAny).sort_values()\n",
    "plt.plot(df['id'], totalInputs, 'ro')\n",
    "plt.xlabel('Mechanism ID')\n",
    "plt.ylabel('totalInputs')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x109d83b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#inRot\n",
    "commonRotations = [a * b for a,b in zip(inRot, outRot)]\n",
    "commonRotations\n",
    "\n",
    "#commonRotations\n",
    "\n",
    "plt.plot([\"x\", \"y\", \"z\"], commonRotations, 'ro')\n",
    "plt.xlabel('rotation axis')\n",
    "plt.ylabel('input and output rotation in common')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x105fc2748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df['transmission'].sort_values(), df['id'], 'ro')\n",
    "plt.xlabel('Transmission')\n",
    "plt.ylabel('Mechanism ID')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a954d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df['id'], df['inputR1'], 'ro')\n",
    "plt.xlabel('Mechanism ID')\n",
    "plt.ylabel('Input Rotation on X axis')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Current Dev"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}