Lecture05(Zikl01).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Циклический вычислительный процесс в Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAH//2Q==\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"400\"\n",
       "            height=\"300\"\n",
       "            src=\"https://www.youtube.com/embed/Y7wrxzhZLm0\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x6357cd0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import YouTubeVideo\n",
    "YouTubeVideo('Y7wrxzhZLm0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l=[1,2,3,4,5,6]\n",
    "p=1\n",
    "for i in l:\n",
    "    p*=i\n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l=[1,2,3,4,5,6]\n",
    "s=0\n",
    "for i in l:\n",
    "    s+=i\n",
    "print(s)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p=1\n",
    "for i in range(1,10):\n",
    "           p*=i\n",
    "print(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Вычисление факториала   n!    (fac)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "n=10\n",
    "fac=1\n",
    "for i in range(1,n+1):\n",
    "           fac*=i\n",
    "print(fac)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Вложенные циклы  (вычисление факториала)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=4;y=0.2;z=0.07\n",
    "p=1\n",
    "for k in range(2,6,1):\n",
    "    f=1\n",
    "    for j in range(1,k+1):\n",
    "        f*=j\n",
    "    p*=((x+y**2)/(z+f))\n",
    "p"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Выполнение цикла с двумя параметрами"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l=[1,2,3,4,5,6]\n",
    "for i,k in enumerate(l):\n",
    "    l[i]=k+1\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Генерирование списка с помощью цикла"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l=[i**2 for i in range(0,10,1)]\n",
    "l"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Создание списка с помощью цикла и метода append()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l=[]\n",
    "for i in range(10):\n",
    "    l.append(i**2)\n",
    "l\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Пример индивидуального задания"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Так задача решается в Python классическим кодом"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "import math as mt\n",
    "x=4;y=0.2;z=0.07\n",
    "S=0\n",
    "for k in range(2,6,1):\n",
    "    f=1\n",
    "    for j in range(1,k+1):\n",
    "        f*=j\n",
    "    S+=(x+y**2+mt.sin(x))/(z+f)\n",
    "S"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Избавляемся от вложенного цикла "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "import math as mt\n",
    "x=4;y=0.2;z=0.07\n",
    "S=0\n",
    "for k in range(2,6,1):\n",
    "    S+=((x+y**2+mt.sin(x))/(z+mt.factorial(k)))\n",
    "S"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Генерируем список и суммируем его"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math as mt\n",
    "x=4;y=0.2;z=0.07\n",
    "l=[((x+y**2+mt.sin(x))/(z+mt.factorial(k)))for k in range(2,6,1)]\n",
    "print(sum(l)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math as mt\n",
    "x=4;y=0.2;z=0.07\n",
    "l=[]\n",
    "for k in range(2,6,1):\n",
    "    l.append(((x+y**2+mt.sin(x))/(z+mt.factorial(k))))\n",
    "print(sum(l)) "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math as mt\n",
    "x=4;y=0.2;z=0.07\n",
    "p=1\n",
    "for k in range(2,6,1):\n",
    "    p*=((x+y**2+mt.sin(x))/(z+mt.factorial(k)))\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import math as mt\n",
    "x=4;y=0.2;z=0.07\n",
    "l=[]\n",
    "for k in range(2,6,1):\n",
    "    l.append(((x+y**2+mt.sin(x))/(z+mt.factorial(k))))\n",
    "p=np.prod(l)\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=4;y=0.2;z=0.07\n",
    "p=1\n",
    "for k in range(2,6,1):\n",
    "    f=1\n",
    "    for j in range(1,k+1):\n",
    "        f*=j\n",
    "    p*=((x+y**2+mt.sin(x))/(z+f))\n",
    "p"
   ]
  }
 ],
 "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}