Module 2 Assignment¶

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from nose.tools import assert_equal
import numpy as np
import math
import random

Problem 1: Making a tuple¶

In this problem, you will create a tuple containing the values $1, 2, 3$ in that order and save it as a variable called "my_tuple".

### YOUR CODE HERE

assert_equal(type(my_tuple), tuple)
assert_equal(my_tuple[0], 1)
assert_equal(my_tuple[1], 2)
assert_equal(my_tuple[2], 3)

Problem 2: Making a list¶

In this problem, you will create a list containing the values $11, 22, 33$ in that order and save it as a variable called "my_list".

### YOUR CODE HERE

assert_equal(type(my_list), list)
assert_equal(my_list[0], 11)
assert_equal(my_list[1], 22)
assert_equal(my_list[2], 33)

Problem 3: Making a numpy array¶

In this problem, you will create a numpy array containing the values $10, 20, 30$ in that order and save it as a variable called "my_array".

### YOUR CODE HERE

assert_equal(type(my_array), np.ndarray)
assert_equal(my_array[0], 10)
assert_equal(my_array[1], 20)
assert_equal(my_array[2], 30)

Problem 4: Making a dictionary¶

In this problem, you will create a dictionary with keys "first", "second", and "third" with corresponding values 1, 2, and 3 and save it as a variable called "my_dictionary"

### YOUR CODE HERE

assert_equal(type(my_dictionary), dict)
assert_equal(my_dictionary["first"], 1)
assert_equal(my_dictionary["second"], 2)
assert_equal(my_dictionary["third"], 3)

Problem 5: Indexing and slicing a numpy array¶

In this problem, you will practice taking values from the numpy array (which you saved as my_array) in problem 3.

Use indexing or slicing to do the following:

Save the first element of my_array in a variable called "first".

Save the last element of my_array in a variable called "last".

Save the first element and second element of my_array in a variable called "first_and_second".

### YOUR CODE HERE

assert_equal(type(first_and_second), np.ndarray)
assert_equal(first_and_second[0]**2, 100)
assert_equal(first, 10)
assert_equal(last, 30)

Problem 6: Writing a Square Root Function¶

In this problem you will finish writing a function that takes the square root of a number and return it. We have created the function header for you.

def sqrt(n):
    '''
    Computes the square root of a number n
    n: An integer to take the square root of.
    '''
    ### YOUR CODE HERE

assert_equal(3, sqrt(9))
for i in range(1, 10):
    n = random.randint(1, 200)
    assert_equal(math.sqrt(n), sqrt(n))

Problem 7: Taking the square root of each number in a list.¶

For this problem in the sqrt_list function:

Take the square root of each item in the list,
Store each squared item in another list, and
Return this list.

def sqrt_list(m):
    '''
    Computes the square root of each number in list m.
    m: A list full of integers.
    '''
    ### YOUR CODE HERE

perfect_squares = [81,64,49,36,25,16,9,4]  # List containing perfect squares
assert_equal(sqrt_list(perfect_squares), [9, 8, 7, 6, 5, 4, 3, 2])
assert_equal(sqrt_list([100, 121, 144, 169]), [10, 11, 12, 13])

Problem 8: Taking the square root of each number in the list with conditions¶

For this problem in the sqrt_special_case function:

Take the square root of each number in the list if it is odd,
Take cube of each number in this list if it is even,
Store the results of 1 and 2 in another list, and
Return this list.

def sqrt_special_case(m):
    '''
    m: A list full of integers
    '''
    ### YOUR CODE HERE

assert_equal(sqrt_special_case(perfect_squares), [9, 262144, 7, 46656, 5, 4096, 3, 64])
assert_equal(sqrt_special_case([100, 121, 144, 169]), [1000000, 11, 2985984, 13])

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