trajectory_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "filename = 'sample_7l.txt'\n",
    "jnt_data = np.loadtxt(filename,delimiter='\\t',unpack=False)\n",
    "\n",
    "jnt_data = np.array(jnt_data.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%config InlineBackend.figure_formats = ['svg']\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.plot(jnt_data)\n",
    "plt.legend(['Jnt1', 'Jnt2', 'Jnt3', 'Jnt4', 'Jnt5' ,'Jnt6', 'Ext1', 'Ext2', 'Ext3'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "jnt_ang = jnt_data\n",
    "jnt_vel = np.gradient(jnt_ang, axis=0)\n",
    "jnt_acc = np.gradient(jnt_vel,axis=0)\n",
    "jnt_jerk = np.gradient(jnt_acc, axis=0)\n",
    "\n",
    "plt.plot(jnt_vel)\n",
    "plt.show()\n",
    "plt.plot(jnt_acc)\n",
    "plt.show()\n",
    "plt.plot(jnt_jerk)\n",
    "plt.show()"
   ]
  }
 ],
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