EGR 103/Concept List/S23

Lecture 1 - 1/11 - Course Introduction

• Main class page: EGR 103L
  • Includes links to Sakai, Pundit, and Ed pages
• Sakai page: Sakai 103L page; grades, surveys and tests, some assignment submissions; first day slideshow in Resources section goes over everything else.

Lecture 2 - 1/13 - Programs and Programming

• Almost all languages have input, output, math, conditional execution (decisions), and repetition (loops)
• Seven steps of programming The Seven Steps Poster. Also, for next Friday's class:
  • Watch video on Developing an Algorithm
  • Watch video on A Seven Step Approach to Solving Programming Problems
• Problem: Consider how to decide if a number is a prime number
  • Some "shortcuts" for specific factors (2, 3, and 5, for example) but need to have a generalized approach
  • See if number is evenly divisible by any integer between 2 and the square root of the number - but how do we ask the computer to do that?
• Very quick tour of Python with Spyder
  • Console (with history tab), variable explorer (with other tabs), and editing window

Lecture 3 - 1/13 - "Number" Types

• Google Colab notebook available in the EGR 103 Google Drive folder
• Comments in code:
  • If there is a #, Python ignores everything remaining in that line after the #
  • If there are """ or , Python ignores everything until the closing """ or
  • If you use # %% in Spyder, the editing window will set up a cell and light up the cell your cursor is in. Cells have no impact on how the code runs, just how the code appears in the window
• Python is a "typed" language
  • Focus of the day: int, float, and array
    • int: integers; Python 3 can store these perfectly up to ginormous sizes
    • float: floating point numbers - "numbers with decimal points" - Python sometimes has problems storing floating point items exactly
• Basic operations for ints and floats
  • + - * // (rounded division) and % (remainder / modulo) produce int if both sides are an int, float if either or both are floats
  • / (regular division) produces float with ints or floats
  • ** to do powers
  • Relational operators can compare "Number" Types and work the way you expect with True or False as an answer
    • < <= == >= > !=
  • Logical operators can combine (and, or) booleans or reverse ( not)
• You can convert strings containing characters that "look" like numbers to ints or floats:
  • NUM = int(VAR)
    • If VAR is an int or a float, it will return an int rounded towards 0
    • If VAR is a string, it will return an int only if the string looks exactly like an integer
  • NUM = float(VAR)
    • If VAR is an int or a float, it will return a float with the same value
    • If VAR is a string, it will return a float if the string looks like a float, including scientific notation such as float("1.23e4")
  • This is important because VAR = input("prompt: ") will ask the user for a value and stores whatever they type as a string
• Arrays
  • Python doesn't know everything to start with; may need to import things - must import numpy for arrays
    • import MODULE means using MODULE.function() to run
    • import MODULE as NAME means using NAME.function() to run - this is the most common one for us
    • from MODULE import FUNCTION1, FUNCTION2, ... means using FUNCTION1(), FUNCTION2() as function calls - be careful not to override things
    • from MODULE import * means importing every function and constant from a module into their own name - very dangerous!
  • import numpy as np will be a very common part of code for EGR 103
  • 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 arrays works the way you expect
    • ** * / // % + -
      • With arrays, * and / work element by element; *matrix* multiplication is a different character (specifically, @)
  • Relational operators can compare two arrays that are the same size or an array and a single number
    • < <= == >= > !=
    • With arrays, either same size or one is a single value; the 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 - 1/23 - List, Tuple String

• Google Colab notebook available in the EGR 103 Google Drive folder
• Python script available in the [
• 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 or l.append().
• 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 original 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" is True since the "e" comes before the "i"
    • "Zebra" < "apple" is True since the upper case "Z" is before the lower case "a"
    • "go" < "gone" is True 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