partical_tracking.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2 as cv\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "img = np.zeros([4,6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=(img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for /: 'tuple' and 'int'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-18-92d60c1a447d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'tuple' and 'int'"
     ]
    }
   ],
   "source": [
    "a/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drawing multicolor lines takes awhile. Come back in a minute.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>x</th>\n",
       "      <th>y</th>\n",
       "      <th>frame</th>\n",
       "      <th>particle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.8</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.8</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.8</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>0.8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.8</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2.8</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>0.8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.8</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3.8</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>0.8</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3.8</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      x    y  frame  particle\n",
       "0   0.0  0.0    0.0         0\n",
       "1   0.0  1.0    0.0         1\n",
       "2   0.0  2.0    0.0         2\n",
       "3   0.0  3.0    0.0         3\n",
       "4   1.0  0.0    0.0         4\n",
       "5   1.0  1.0    0.0         5\n",
       "6   1.0  2.0    0.0         6\n",
       "7   1.0  3.0    0.0         7\n",
       "8   2.0  0.0    0.0         8\n",
       "9   2.0  1.0    0.0         9\n",
       "10  2.0  2.0    0.0        10\n",
       "11  2.0  3.0    0.0        11\n",
       "12  3.0  0.0    0.0        12\n",
       "13  3.0  1.0    0.0        13\n",
       "14  3.0  2.0    0.0        14\n",
       "15  3.0  3.0    0.0        15\n",
       "0   0.8 -0.8    0.8         0\n",
       "1   0.8  0.2    0.8         1\n",
       "2   0.8  1.2    0.8         2\n",
       "3   0.8  2.2    0.8         3\n",
       "4   1.8 -0.8    0.8         4\n",
       "5   1.8  0.2    0.8         5\n",
       "6   1.8  1.2    0.8         6\n",
       "7   1.8  2.2    0.8         7\n",
       "8   2.8 -0.8    0.8         8\n",
       "9   2.8  0.2    0.8         9\n",
       "10  2.8  1.2    0.8        10\n",
       "11  2.8  2.2    0.8        11\n",
       "12  3.8 -0.8    0.8        12\n",
       "13  3.8  0.2    0.8        13\n",
       "14  3.8  1.2    0.8        14\n",
       "15  3.8  2.2    0.8        15"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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