EGR 103/Concept List/F21

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Lecture 1 - Course Introduction

  • Main class page: EGR 103L.
  • See information on PDF of slide show on Errata / Notes page.
  • Sakai page: Sakai 103L page; grades, surveys and tests, some assignment submissions
  • Pundit page: EGR 103; reference lists
  • CampusWire page: CampusWire 103L page; message board for questions - you need to be in the class and have the access code 8018 to subscribe.

Lecture 2 - Programs and Programming

  • Almost all languages have input, output, math, conditional execution (decisions), and repetition (loops)
  • Seven steps of programming The Seven Steps Poster
  • Consider how to decide if a number is a prime number
  • To play with Python:
    • Install it on your machine or a public machine: Download
  • Quick tour of Python
    • Editing window, variable explorer, and console
    • Main numerical types: whole numbers (int) and numbers with decimals (float)
    • + - * // (rounded division) and % (remainder / modula) produce in if both sides are an int, float if either or both are floats
    • / (regular division) and // (rounded division) produces float with ints or floats
    • ** to do powers
    • Python doesn't know everything to start with; may need to import things
      • import MODULE means using MODULE.function() to run
      • import MODULE as NAME means using NAME.function() to run
    • VAR = input("prompt: ") will ask the user for a value and stores whatever they type as a string
    • NUM = int(VAR) will convert the item in VAR to an integer if it looks like an integer; error otherwise

Lecture 3 - "Number" Types

  • Finished prime number checker - code is available in the Box drive for the class under Lectures / Lec03
    • Looked at for loops for running code multiple times
    • Looked at if...else trees for making decisions
    • Created a variable to track whether we thought the number was prime
  • Python is a "typed" language - variables have types. We will use several types:
    • Focus of the day: int, float, and array
    • Focus a little later: string, list, tuple
    • Focus later: dictionary, set
    • Focus way later: map, filter, zip
  • int: integers; Python 3 can store these perfectly
  • float: floating point numbers - "numbers with decimal points" - Python sometimes has problems storing floating point items exactly
  • array
    • Requires numpy, usually with import numpy as np
    • Organizational unit for storing rectangular arrays of numbers
    • Generally create with np.array(LIST) where depth of nested LIST is dimensionality of array
      • np.array([1, 2, 3]) is a 1-dimensional array with 3 elements
      • np.array([[1, 2, 3], [4, 5, 6]]) is a 2-dimension array with 2 rows and 3 columns
  • Math with "Number" types works the way you expect
    • ** * / // % + -
    • With arrays, * and / work element by element; *matrix* multiplication is a different character (specifically, @)
  • Relational operators can compare "Number" Types and work the way you expect with True or False as an answer
    • < <= == >= > !=
    • With arrays, either same size or one is a single value; result will be an array of True and False the same size as the array
  • Slices allow us to extract information from a collection or change information in mutable collections
  • a[0] is the element in a at the start
  • a[3] is the element in a three away from the start
  • a[-1] is the last element of a
  • a[-2] is the second-to-last element of a
  • a[:] is all the elements in a because what is really happening is:
    • a[start:until] where start is the first index and until is just *past* the last index;
    • a[3:7] will return a[3] through a[6] in a 4-element array
    • a[start:until:increment] will skip indices by increment instead of 1
    • To go backwards, a[start:until:-increment] will start at an index and then go backwards until getting at or just past until.
  • For 2-D arrays, you can index items with either separate row and column indices or indices separated by commas:
    • a[2][3] is the same as a[2, 3]
    • Only works for arrays!

Lecture 4 - Other Types

  • Lists are set off with [ ] and entries can be any valid type (including other lists!); entries can be of different types from other entries; list items can be changed and mutable items within lists can be changed. Lists can be "grown" by using += with the list.
  • Tuples are indicated by commas without square brackets (and are usually shown with parentheses - which are required if trying to make a tuple an entry in a tuple or a list); tuple items cannot be changed but mutable items within tuples can be
  • Strings are set off with " " or ' ' and contain characters; string items cannot be changed
  • For lists, tuples, and strings:
    • Using + concatenates the two collections
    • Using * with them makes creates a collection with the orignal repeated that many times
    • Using += will create a new item with something appended to the old item; the "something" needs to be the same type (list, tuple, or string); this may seem to break the "can't be changed" rule but really a += b is a = a + b which creates a new a.
  • Characters in strings have "numerical" values based on the ASCII table (https://www.asciitable.com/)
    • Numbers are earlier than lower case letters; lower case letters are earlier than upper case letters
    • Strings are sorted character by character; if one string is shorter than another, it is considered less
      • " Hello" < "Hi" since the "e" comes before the "i"
      • "Zebra" < "apple" since the upper case "Z" is before the lower case "a"
      • "go" < "gone" since the first two characters match and then the word is done
  • To get the numerical value of a single character, use ord("A") or replace the A with the character you want
  • To get the character a number represents, use chr(NUM)
  • To apply either ord or chr to multiple items, use a map; to see the results, make a list out of the map
  • Trinket

  • To read more:
    • Note! Many of the tutorials below use Python 2 so instead of print(thing) it shows print thing
    • Lists at tutorialspoint
    • Tuples at tutorialspoint

Lecture 5 - Format and Functions

  • Creating formatted strings using {} and .format() (format strings, standard format specifiers) -- focus was on using s for string and e or f for numerical types, minimumwidth.precision, and possibly a + in front to force printing + for positive numbers.
    • Using {} by themselves will substitute items in order from the format() function into the string that gets created
    • Putting a number in the {} will tell format which thing to get
    • Format specification comes after a : in the {}; if you do not specify a location index, you still have to put a colon in the {}
    • {:s} means string and {:Xs} where X is an integer means reserve at least that much space for a left-formatted string
    • {:f} means floating point (default 6 digits after decimal point) and {:X.Yf} reserves at least X spaces (including + or - and the . if it is there) with Y digits after the decimal point for t right-justified number
    • {:e} means floating point (default 6 digits after decimal point) and {:X.Ye} reserves at least X spaces (including + or - and the . if it is there and the letter e and the + or - after the e and the two or three digit number after that) with Y digits after the decimal point for t right-justified number
  • Aside - Format Specification Mini-Language has all the possibilities; we will cover some but not all of these in later classes
  • You can enter numbers in scientific notation with a number followed by the letter 3 and then a number or negative number for the power of 10; for example, x = 6.02e23 or e = -1.6e-19
    • float can convert scientific notation as well:
float("1e-5")
  • Defined functions can be multiple lines of code and have multiple outputs.
  •  def FNAME(local1, local2, ...):
     CODE
     return THING1, THING2, ...
    • Four different types of input parameters - we only really talked about the first kind:
      • Required (listed first)
    • We will cover the other kinds later
      • Named with defaults (second)
      • Additional positional arguments ("*args") (third)
        • Function will create a tuple containing these items in order
      • Additional keyword arguments ("**kwargs") (last)
        • Function will create a dictionary of keyword and value pairs
    • Function ends when indentation stops or when the function hits a return statement
    • Return returns single item as an item of that type; if there are multiple items returned, they are stored and returned in a tuple
    • If there is a left side to the function call, it either needs to be a single variable name or a tuple with as many entries as the number of items returned

Lecture 6

  • <= < == >= > != work with many types; just be careful about interpreting
  • not can reverse while and and or can combine logical expressions
  • Basics of decisions using if...elif...else
    • Must have logic after if
    • Can have as many elif with logic after
    • Can have an else without logic at the end
    • Flow is solely dependent on indentation!
    • Branches can contain other trees for follow-up questions
  • Movie ratings.
  • Basics of while loops and for loops.
  • The Price Is Right game!

Lecture 7

  • Using a list to keep track of counts
  • Using the enumerate type to provide a collection of indices and values to a loop
  • Basics of Python:Logical Masks

Lecture 8

  • Dictionaries are collections of key : value pairs set off with { }; keys can be any immutable type (int, float, string, tuple) and must be unique; values can be any type and do not need to be unique
  • Storing values in a dictionary
  • Bar chart demo
  • Translation demo with Morse code and NATO phonetic alphabet

Lecture 9

  • Taylor series fundamentals
  • Maclaurin series approximation for exponential uses Chapra 4.2 to compute terms in an infinite sum.
\( y=e^x=\sum_{n=0}^{\infty}\frac{x^n}{n!} \)
so
\( \begin{align} y_{init}&=1\\ y_{new}&=y_{old}+\frac{x^n}{n!} \end{align} \)
  • Newton Method for finding square roots uses Chapra 4.2 to iteratively solve using a mathematical map. To find \(y\) where \(y=\sqrt{x}\):
    \( \begin{align} y_{init}&=1\\ y_{new}&=\frac{y_{old}+\frac{x}{y_{old}}}{2} \end{align} \)
  • See Python version of Fig. 4.2 and modified version of 4.2 in the Resources section of Sakai page under Chapra Pythonified
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