distribution.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14180228d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14180228470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x141800d7550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x141809b1780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from numpy import ma\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import animation\n",
    "\n",
    "def plot_distribution_fuction(coefficient):\n",
    "    x = np.arange(0, 10, coefficient)\n",
    "    y = np.sin(0.3*x + 11) * 0.5 + 0.5\n",
    "\n",
    "    plt.step(x, y)\n",
    "    plt.xlim(0, 10)\n",
    "    plt.ylim(0, 1)\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('F(x)')\n",
    "    plt.show()\n",
    "\n",
    "plot_distribution_fuction(0.5)\n",
    "plot_distribution_fuction(0.3)\n",
    "plot_distribution_fuction(0.1)\n",
    "plot_distribution_fuction(0.01)"
   ]
  }
 ],
 "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}