script.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test Scripts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pylab as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(0, 20, 0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def function_1(x):\n",
    "    return x**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = function_1(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.0000e+00, 1.0000e-02, 4.0000e-02, 9.0000e-02, 1.6000e-01,\n",
       "       2.5000e-01, 3.6000e-01, 4.9000e-01, 6.4000e-01, 8.1000e-01,\n",
       "       1.0000e+00, 1.2100e+00, 1.4400e+00, 1.6900e+00, 1.9600e+00,\n",
       "       2.2500e+00, 2.5600e+00, 2.8900e+00, 3.2400e+00, 3.6100e+00,\n",
       "       4.0000e+00, 4.4100e+00, 4.8400e+00, 5.2900e+00, 5.7600e+00,\n",
       "       6.2500e+00, 6.7600e+00, 7.2900e+00, 7.8400e+00, 8.4100e+00,\n",
       "       9.0000e+00, 9.6100e+00, 1.0240e+01, 1.0890e+01, 1.1560e+01,\n",
       "       1.2250e+01, 1.2960e+01, 1.3690e+01, 1.4440e+01, 1.5210e+01,\n",
       "       1.6000e+01, 1.6810e+01, 1.7640e+01, 1.8490e+01, 1.9360e+01,\n",
       "       2.0250e+01, 2.1160e+01, 2.2090e+01, 2.3040e+01, 2.4010e+01,\n",
       "       2.5000e+01, 2.6010e+01, 2.7040e+01, 2.8090e+01, 2.9160e+01,\n",
       "       3.0250e+01, 3.1360e+01, 3.2490e+01, 3.3640e+01, 3.4810e+01,\n",
       "       3.6000e+01, 3.7210e+01, 3.8440e+01, 3.9690e+01, 4.0960e+01,\n",
       "       4.2250e+01, 4.3560e+01, 4.4890e+01, 4.6240e+01, 4.7610e+01,\n",
       "       4.9000e+01, 5.0410e+01, 5.1840e+01, 5.3290e+01, 5.4760e+01,\n",
       "       5.6250e+01, 5.7760e+01, 5.9290e+01, 6.0840e+01, 6.2410e+01,\n",
       "       6.4000e+01, 6.5610e+01, 6.7240e+01, 6.8890e+01, 7.0560e+01,\n",
       "       7.2250e+01, 7.3960e+01, 7.5690e+01, 7.7440e+01, 7.9210e+01,\n",
       "       8.1000e+01, 8.2810e+01, 8.4640e+01, 8.6490e+01, 8.8360e+01,\n",
       "       9.0250e+01, 9.2160e+01, 9.4090e+01, 9.6040e+01, 9.8010e+01,\n",
       "       1.0000e+02, 1.0201e+02, 1.0404e+02, 1.0609e+02, 1.0816e+02,\n",
       "       1.1025e+02, 1.1236e+02, 1.1449e+02, 1.1664e+02, 1.1881e+02,\n",
       "       1.2100e+02, 1.2321e+02, 1.2544e+02, 1.2769e+02, 1.2996e+02,\n",
       "       1.3225e+02, 1.3456e+02, 1.3689e+02, 1.3924e+02, 1.4161e+02,\n",
       "       1.4400e+02, 1.4641e+02, 1.4884e+02, 1.5129e+02, 1.5376e+02,\n",
       "       1.5625e+02, 1.5876e+02, 1.6129e+02, 1.6384e+02, 1.6641e+02,\n",
       "       1.6900e+02, 1.7161e+02, 1.7424e+02, 1.7689e+02, 1.7956e+02,\n",
       "       1.8225e+02, 1.8496e+02, 1.8769e+02, 1.9044e+02, 1.9321e+02,\n",
       "       1.9600e+02, 1.9881e+02, 2.0164e+02, 2.0449e+02, 2.0736e+02,\n",
       "       2.1025e+02, 2.1316e+02, 2.1609e+02, 2.1904e+02, 2.2201e+02,\n",
       "       2.2500e+02, 2.2801e+02, 2.3104e+02, 2.3409e+02, 2.3716e+02,\n",
       "       2.4025e+02, 2.4336e+02, 2.4649e+02, 2.4964e+02, 2.5281e+02,\n",
       "       2.5600e+02, 2.5921e+02, 2.6244e+02, 2.6569e+02, 2.6896e+02,\n",
       "       2.7225e+02, 2.7556e+02, 2.7889e+02, 2.8224e+02, 2.8561e+02,\n",
       "       2.8900e+02, 2.9241e+02, 2.9584e+02, 2.9929e+02, 3.0276e+02,\n",
       "       3.0625e+02, 3.0976e+02, 3.1329e+02, 3.1684e+02, 3.2041e+02,\n",
       "       3.2400e+02, 3.2761e+02, 3.3124e+02, 3.3489e+02, 3.3856e+02,\n",
       "       3.4225e+02, 3.4596e+02, 3.4969e+02, 3.5344e+02, 3.5721e+02,\n",
       "       3.6100e+02, 3.6481e+02, 3.6864e+02, 3.7249e+02, 3.7636e+02,\n",
       "       3.8025e+02, 3.8416e+02, 3.8809e+02, 3.9204e+02, 3.9601e+02])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph = plt.plot(x ,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "h = 1e-4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0001\n"
     ]
    }
   ],
   "source": [
    "print(h)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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