lec10_iteration1_template.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Warmup: Slides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "import math\n",
    "import beeper  # doesn't work on Windows, sorry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Warmup: Run this to see how it works\n",
    "# Example 1:  Countdown Timer\n",
    "# delete the repeated code \n",
    "# change the if to while\n",
    "\n",
    "\n",
    "seconds = 2\n",
    "\n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "\n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "    \n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "    \n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "    \n",
    "print(\"DING \" * 5)\n",
    "beeper.beep(8) # Only works on MAC laptops, sorry Windows users :("
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### February 16:  Iteration part 1\n",
    "\n",
    "Learning Objectives: (after this lecture you should be able to...)\n",
    "\n",
    "11.1 Implement an iterative algorithm using a while loop\n",
    "- example: printing / counting\n",
    "- example: validating user input\n",
    "- example: performing an iterative calculation\n",
    "- example: character art\n",
    "\n",
    "11.2 Trace iterative algorithms and determine their output\n",
    "\n",
    "11.3 Recognize common while loop errors\n",
    "- Infinite loops (when unintentional)\n",
    "- Off-by-one mistakes in the loop control variable\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Slides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "1\n",
      "DING DING DING DING DING \n"
     ]
    }
   ],
   "source": [
    "# Example 1:  Countdown Timer\n",
    "# delete the repeated code \n",
    "# change the if to while\n",
    "\n",
    "\n",
    "seconds = 2\n",
    "\n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "\n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "    \n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "    \n",
    "if seconds > 0:\n",
    "    print(seconds)\n",
    "    time.sleep(1)  # 1 second\n",
    "    seconds -= 1   # decrease seconds by 1\n",
    "    \n",
    "print(\"DING \" * 5)\n",
    "beeper.beep(5) # Only works on MAC laptops, sorry Windows users :("
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 1b:  what happens if you remove the line that decreases seconds? \n",
    "# copy/paste the code and try it\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# this is called ......."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 1c: copy/paste the code from 1a but this time start at 1 and count up to 5\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 2:  Put this code into Python Tutor to see how it works\n",
    "\n",
    "n = 0\n",
    "while n < 10:\n",
    "    print(n)\n",
    "    n += 2\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 3: Find the max value of a function on an interval"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![graph.png](attachment:graph.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example 3a: define the function and test it\n",
    "def f(x):\n",
    "    return 5 - (x-2)**2\n",
    "f(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "1 4\n",
      "1.1 4.19\n",
      "1.2000000000000002 4.36\n",
      "1.3000000000000003 4.510000000000001\n",
      "1.4000000000000004 4.640000000000001\n",
      "1.5000000000000004 4.75\n",
      "1.6000000000000005 4.840000000000001\n",
      "1.7000000000000006 4.91\n",
      "1.8000000000000007 4.96\n",
      "1.9000000000000008 4.99\n",
      "2.000000000000001 5.0\n",
      "2.100000000000001 4.99\n",
      "2.200000000000001 4.96\n",
      "2.300000000000001 4.909999999999999\n",
      "2.4000000000000012 4.839999999999999\n",
      "2.5000000000000013 4.749999999999998\n",
      "2.6000000000000014 4.639999999999998\n",
      "2.7000000000000015 4.509999999999998\n",
      "2.8000000000000016 4.359999999999998\n",
      "2.9000000000000017 4.189999999999997\n",
      "3.0000000000000018 3.9999999999999964\n",
      "3.100000000000002 3.7899999999999956\n",
      "3.200000000000002 3.559999999999995\n",
      "3.300000000000002 3.3099999999999947\n",
      "3.400000000000002 3.039999999999994\n",
      "3.500000000000002 2.7499999999999933\n",
      "3.6000000000000023 2.4399999999999924\n",
      "3.7000000000000024 2.109999999999992\n",
      "3.8000000000000025 1.759999999999991\n",
      "3.9000000000000026 1.3899999999999904\n",
      "4.000000000000003 0.9999999999999893\n",
      "4.100000000000002 0.5899999999999901\n",
      "4.200000000000002 0.15999999999999126\n",
      "4.300000000000002 -0.29000000000000714\n",
      "4.400000000000001 -0.760000000000006\n",
      "4.500000000000001 -1.2500000000000044\n",
      "4.6000000000000005 -1.7600000000000025\n",
      "4.7 -2.290000000000001\n",
      "4.8 -2.839999999999999\n",
      "4.8999999999999995 -3.4099999999999966\n",
      "4.999999999999999 -3.9999999999999947\n",
      "max occurred at 2.000000000000001 5.0\n"
     ]
    }
   ],
   "source": [
    "# Example 3b: write code to iterate over values \n",
    "\n",
    "start_x = 1\n",
    "end_x = 5\n",
    "delta_x = 0.1\n",
    "\n",
    "max_y = f(start_x)\n",
    "max_x = start_x\n",
    "print(max_y)\n",
    "\n",
    "current_x = start_x\n",
    "\n",
    "while False:  # change this\n",
    "    y = f(current_x)\n",
    "    print(current_x, y)\n",
    "    if y > max_y:\n",
    "        max_y = 0  # change this\n",
    "        max_x = 0  # change this\n",
    "    current_x += delta_x\n",
    "print(\"max occurred at\", max_x, max_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# can we find a Riemann Sum ?"
   ]
  },
  {
   "attachments": {
    "Riemann%20Sum.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Riemann%20Sum.png](attachment:Riemann%20Sum.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 4: Riemann Sum\n",
    "# copy/paste the code above\n",
    "# change the block inside the while loop to find area under the curve\n",
    "start_x = 1\n",
    "end_x = 5\n",
    "delta_x = 0.1\n",
    "\n",
    "total_area = 0\n",
    "current_x = start_x\n",
    "\n",
    "\n",
    "    \n",
    "print(\"total area is: \", total_area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 4:  write a function to determine if an integer is prime\n",
    "\n",
    "\n",
    "def is_prime(x):\n",
    "    \"\"\" returns True if x is prime, false otherwise. Assumes x is positive\"\"\"\n",
    "\n",
    "    divisor = 2\n",
    "\n",
    "    while divisor <= math.sqrt(x):\n",
    "        if x % divisor == 0: # its divisble\n",
    "            return ???     # not prime\n",
    "        divisor += 1         # try the next number up\n",
    "    return ???\n",
    "\n",
    "is_prime(101)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "is_prime(36)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "is_prime(2) #2 is prime, this should return True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### for loop\n",
    "\n",
    "- does not require initialization of loop control variable outside the loop\n",
    "- loop statement itself creates the loop control variable\n",
    "- keywords `for` and `in`\n",
    "\n",
    "### range() function\n",
    "- range(5) produces the sequence 0, 1, 2, 3, 4, \n",
    "- range(3,5) produces the sequence 3, 4\n",
    "- the ending number is not included\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 5:  Another kind of a loop is a for loop\n",
    "# the loop control variable in this loop is increased by 1 in each iteration\n",
    "\n",
    "for i in range(3,7):\n",
    "    print(i) # don't need to change i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(5): #starts with ___, ends with ____\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write a for loop that prints out the integers from 10 to 20, inclusive\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 6:  Change this `while` loop to a `for` loop \n",
    "\n",
    "print(\"Prime numbers:\")\n",
    "number = 2\n",
    "while number <= 50:\n",
    "    if is_prime(number):\n",
    "        print(number, \"is prime\")\n",
    "    else:\n",
    "        print(number, \"is not prime\")\n",
    "    number += 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example 7: What is an an off-by-one error? \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Practice :  Border by height and width\n",
    "###########\n",
    "#         #\n",
    "#         #\n",
    "###########\n",
    "\n",
    "width = 8\n",
    "height = 4\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "4\n",
      "5\n",
      "6\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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