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Worksheets related to Applied Discrete Structures

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An Introduction to Functions using Sage 

Applied Discrete Structures by Alan Doerr & Kenneth Levasseur is licensed under a Creative Commons Attribution - Noncommercial - ShareAlike  3.0 United States License.

This document describes the basic ways in which a function can be represented with Sage.  These topics are introduced in chapter 7 of Applied Discrete Structures.

In any computer program a function defined by a piece of code that will accept inputs and produce outputs. This is a bit more general than the mathematical concept of a function, but close enough to let use study the concept through programming. The function on the set {0,1,2,3,4,5,6}\{0,1,2,3,4,5,6\} defined by the ordered pairs {(0,0),(1,1),(2,4),(3,2),(4,2),(5,4),(6,1)}\{(0,0), (1,1), (2,4), (3,2), (4,2),(5,4), (6,1)\} can be represented as a dictionary:

def f(x): return {0:0,1:1,2:4,3:2,4:2,5:4,6:1}[x]
f(4)
2

Not every function can be easily defined by a formula, but this one can be using the standard synatax for Python/SageMath functions.

def f(x): return x^2 %7
f(4)
2
%html <p> Not every SageMath function is a true function. For example, if the output is governed by a random number generator, the output for a given input will vary. Here is a function that returns 1 with probability $p$ and 0 with probability $1-p$. </p>

Not every SageMath function is a true function. For example, if the output is governed by a random number generator, the output for a given input will vary. Here is a function that returns 1 with probability pp and 0 with probability 1p1-p.

def nonfunction(p): if random()<p: return 1 else: return 0
outputs=[] for k in range(10): outputs=outputs+[nonfunction(0.3)] outputs
[0, 0, 1, 1, 1, 0, 0, 1, 0, 0]