EGR 103/Concept List/S23

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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:
  • 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

Lecture 5 - 9/12 - Fornatted Printing; 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; {:>s} or {:>Xs} where X is a number will right-justify the 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")
  • Lambda functions can have multiple arguments but can perform only one calculation and will return the result of that one calculation: 
    fun_name = lambda in_1, in_2, in_3, in_4: CALCULATION
    • For example:
      hyp = lambda a, b: np.sqrt(a**2 + b**2)
  • Formally defined functions can be multiple lines of code and have multiple outputs.
    • The function can see everything in main, but main cannot see things created in the function.
      • Best bet is to pretend the function cannot see things in main - pass everything in that you need to see!
    •  def FNAME(local1, local2, ...):
     CODE
     return THING1, THING2, ...
    • Four different types of input parameters - we only really talked about the first three kinds:
      • Required (listed first)
      • 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 -more about dictionaries later
    • 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



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