tutorial1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [
    {
     "data": {
      "text/plain": "array([1, 2, 3, 4, 5, 6, 7, 8, 9])"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x1 = np.arange(1,10)\n",
    "x1"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "data": {
      "text/plain": "array([1. , 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. , 2.1, 2.2,\n       2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1, 3.2, 3.3, 3.4, 3.5,\n       3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8,\n       4.9, 5. , 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 6. , 6.1,\n       6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, 7. , 7.1, 7.2, 7.3, 7.4,\n       7.5, 7.6, 7.7, 7.8, 7.9, 8. , 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7,\n       8.8, 8.9, 9. , 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7, 9.8, 9.9])"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x2 = np.arange(1,10,0.1)\n",
    "x2"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "array([ 1.        ,  1.09090909,  1.18181818,  1.27272727,  1.36363636,\n        1.45454545,  1.54545455,  1.63636364,  1.72727273,  1.81818182,\n        1.90909091,  2.        ,  2.09090909,  2.18181818,  2.27272727,\n        2.36363636,  2.45454545,  2.54545455,  2.63636364,  2.72727273,\n        2.81818182,  2.90909091,  3.        ,  3.09090909,  3.18181818,\n        3.27272727,  3.36363636,  3.45454545,  3.54545455,  3.63636364,\n        3.72727273,  3.81818182,  3.90909091,  4.        ,  4.09090909,\n        4.18181818,  4.27272727,  4.36363636,  4.45454545,  4.54545455,\n        4.63636364,  4.72727273,  4.81818182,  4.90909091,  5.        ,\n        5.09090909,  5.18181818,  5.27272727,  5.36363636,  5.45454545,\n        5.54545455,  5.63636364,  5.72727273,  5.81818182,  5.90909091,\n        6.        ,  6.09090909,  6.18181818,  6.27272727,  6.36363636,\n        6.45454545,  6.54545455,  6.63636364,  6.72727273,  6.81818182,\n        6.90909091,  7.        ,  7.09090909,  7.18181818,  7.27272727,\n        7.36363636,  7.45454545,  7.54545455,  7.63636364,  7.72727273,\n        7.81818182,  7.90909091,  8.        ,  8.09090909,  8.18181818,\n        8.27272727,  8.36363636,  8.45454545,  8.54545455,  8.63636364,\n        8.72727273,  8.81818182,  8.90909091,  9.        ,  9.09090909,\n        9.18181818,  9.27272727,  9.36363636,  9.45454545,  9.54545455,\n        9.63636364,  9.72727273,  9.81818182,  9.90909091, 10.        ])"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x3 = np.linspace(1,10,100)\n",
    "x3"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "array([ 2. ,  2.2,  2.4,  2.6,  2.8,  3. ,  3.2,  3.4,  3.6,  3.8,  4. ,\n        4.2,  4.4,  4.6,  4.8,  5. ,  5.2,  5.4,  5.6,  5.8,  6. ,  6.2,\n        6.4,  6.6,  6.8,  7. ,  7.2,  7.4,  7.6,  7.8,  8. ,  8.2,  8.4,\n        8.6,  8.8,  9. ,  9.2,  9.4,  9.6,  9.8, 10. , 10.2, 10.4, 10.6,\n       10.8, 11. , 11.2, 11.4, 11.6, 11.8, 12. , 12.2, 12.4, 12.6, 12.8,\n       13. , 13.2, 13.4, 13.6, 13.8, 14. , 14.2, 14.4, 14.6, 14.8, 15. ,\n       15.2, 15.4, 15.6, 15.8, 16. , 16.2, 16.4, 16.6, 16.8, 17. , 17.2,\n       17.4, 17.6, 17.8, 18. , 18.2, 18.4, 18.6, 18.8, 19. , 19.2, 19.4,\n       19.6, 19.8])"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = x2*2\n",
    "y"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 1.0, 'y = 2x')"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y1 = x1**2-4*x1+2\n",
    "plt.plot(x1,y1)\n",
    "plt.plot(x2,y)\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.title(\"y = 2x\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 1.0, 'y = x^3+3x-1')"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x4 = np.linspace(1,10,100)\n",
    "y = x4**3+3*x4-1\n",
    "plt.plot(x4,y)\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.title(\"y = x^3+3x-1\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}