EGR 103/Concept List

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This page will be used to keep track of the commands and major concepts for each lecture in EGR 103.

Lecture 1 - Introduction

  • Class web page: EGR 103L; assignments, contact info, readings, etc - see slides on Errata/Notes page
  • Sakai page: Sakai 103L page; grades, surveys and tests, some assignment submissions
  • CampusWire page: CampusWire 103L page; message board for questions - you need to be in the class and have the access code 6393 to subscribe.

Lecture 2 - Programs and Programming

Lecture 3 - "Number" Types

  • Python is a "typed" language - variables have types
  • We will use eight types:
    • Focus of the day: int, float, and array
    • Focus a little later: string, list, tuple
    • Focus later: dictionary, set
  • int: integers; Python can store these perfectly
  • float: floating point numbers - "numbers with decimal points" - Python sometimes has problems
  • array
    • Requires numpy, usually with import numpy as np
    • Organizational unit for storing rectangular arrays of numbers
  • Math with "Number" types works the way you expect
    • ** * / // % + -
  • 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 an array or put information into an array
  • a[0] is the element in a at the start
  • a[3] is the element in a three away from the start
  • 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 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 and Functions

  • 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
  • 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)
  • 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
  • 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
    • Dictionary at tutorialspoint
  • Defined functions can be multiple lines of code and have multiple outputs.
    • Four different types of input parameters:
      • 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
    • 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 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 5 - Format, Logic, Decisions, and Loops