# CSC338. Homework 1¶

Due Date: Wednesday January 15, 9pm

Please see the guidelines at https://www.cs.toronto.edu/~lczhang/338/homework.html

### What to Hand In¶

• Python File containing all your code, named hw1.py.
• PDF file named hw1_written.pdf containing your solutions to the written parts of the assignment. Your solution can be hand-written, but must be legible. Graders may deduct marks for illegible or poorly presented solutions.

If you are using Jupyter Notebook to complete the work, your notebook can be exported as a .py file (File -> Download As -> Python). Your code will be auto-graded using Python 3.6, so please make sure that your code runs. There will be a 20% penalty if you need a remark due to small issues that renders your code untestable.

Make sure to remove or comment out all matplotlib or other expensive code before submitting your code!

Submit the assignment on MarkUs by 9pm on the due date. See the syllabus for the course policy regarding late assignments. All assignments must be done individually.

In [1]:
import math
import numpy as np


## Question 1.¶

For parts (a) and (b), consider the problem of evaluating the function $g(x) = x^2 + x - 4$. Suppose there is a small error, $h$ in the value of $x$.

### Part (a) -- 6pt¶

What is the absolute error and relative error in computing $g(x)$? Implement function and g_abs_err(x, h) and g_rel_err(x, h) to compute those quantities.

In [2]:
def g_abs_err(x, h):
"""Returns the absolute error of computing g at x if x is
perturbed by a small value h.
"""
return None

def g_rel_err(x, h):
"""Returns the relative error of computing g at x if x is
perturbed by a small value h.
"""
return None


### Part (b) -- 3pt¶

Estimate the condition number for the problem. Simplify this answer. For what values of $x$ is this problem well-conditioned? Include your solution in your PDF file.

### Part (c) -- 2pt¶

For parts (c) and (d), consider the problem of finding a root of the function $g(x) = x^2 + x + c$ by using the Quadratic Formula and taking the positive squareroot. Suppose there is a small error, $h$ in the value of $c$.

For what values of $c$ is this problem well-posed? Include your solution in your PDF file.

### Part (d) -- 6pt¶

What is the absolute error and relative error in computing $g(x)$? Implement function and g_root_abs_err(c, h) and g_root_rel_err(c, h) to compute those quantities.

In [3]:
def g_root_abs_err(c, h):
"""Returns the absolute error of finding the (most) positive root of g when
c is perturbed by a small value h.
"""
return None

def g_root_rel_err(c, h):
"""Returns the relative error of finding the (most) positive root of g when
c is perturbed by a small value h.
"""
return None


## Question 2.¶

Consider the function, which is also implemented below. You can run the plot_f python function to see what the graph of $f$ looks like.

$f(x) = \frac{x - sin(x)}{x^3}$

In [4]:
def f(x):
return (x - math.sin(x)) / math.pow(x, 3)

def plot_f():
import matplotlib.pyplot as plt
xs = [x for x in np.arange(-3.0, 3.0, 0.05) if abs(x) > 0.05]
ys = [f(x) for x in xs]
plt.plot(xs, ys, 'bo')

# plot_f() # please comment this out before submitting, or your code might be untestable


### Part (a) -- 2pt¶

What is $f(0.00000001)$? Save the results in the variable q2_est.

Given that $f$ is continuous except at $x = 0$, what should $f(0.00000001)$ be? Save the results in the variable q2_true.

In [5]:
q2_est = None
q2_true = None


### Part (b) -- 2pt¶

Why does the Python statement compute such inaccurate values of $f(0.00000001)$? Include your answer in your PDF File.

### Part (c) -- 5pt¶

Define a Python function f2(x) that uses a different algorithm to compute more accurate values of $f(x)$ for $0 < x \le \frac{\pi}{2}$. More specifically, the relative error should be no more than 1% for those values of $x$.

In [6]:
def f2(x):
return None


## Question 3. -- 4pt¶

The sine function is given by the infinite series

$\sin(x) = x - \frac{x^3}{3!} + \frac{x^5}{5!} - \frac{x^7}{7!} + ...$

Compute the absolute forward and backwards error if we approximate the sine function by the first two terms of the series for elements of the array xs below.

Save your solution in the array q3_forward and q3_backward, so that q3_forward[i] and q3_backward[i] are the absolute forward and backward errors corresponding to the input xs[i].

You may find the functions math.sin and math.asin helpful. You may assume that the true value of $\sin(x)$ can be computed using the function math.sin.

Update (Jan 9th): If the backward error does not exist, please enter "DNE".

In [7]:
xs = [0.1, 0.5, 1.0, 3.0]

q3_forward  = [None, None, None, None]
q3_backward = [None, None, None, None]

# math.sin(0.2)
# math.asin(0.2) # arcsin