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"""Math.

@see: https://docs.python.org/3/tutorial/stdlib.html#mathematics

Math module is useful as many math functions are already implemented and optimized.

"""

import math

import random

import statistics

def test_math():

"""Math.

The math module gives access to the underlying C library functions for floating point math.

"""

assert math.cos(math.pi / 4) == 0.70710678118654757

assert math.log(1024, 2) == 10.0

def test_random():

"""Random.

The random module provides tools for making random selections.

"""

# Choose from the list randomly.

random_options = ['apple', 'pear', 'banana']

random_choice = random.choice(random_options) # i.e. 'apple'

assert random_choice in random_options

# Sampling without replacement.

random_sample = random.sample(range(100), 10) # i.e. [30, 83, 16, 4, 8, 81, 41, 50, 18, 33]

for sample in random_sample:

assert 0 <= sample <= 100

# Choose random number.

random_float = random.random() # i.e. 0.17970987693706186

assert 0 <= random_float <= 1

# Random integer chosen from range(6)

random_integer = random.randrange(6) # i.e. 4

assert 0 <= random_integer <= 6

def test_statistics():

"""Statistics.

The statistics module calculates basic statistical properties (the mean, median,

variance, etc.) of numeric data.

"""

data = [2.75, 1.75, 1.25, 0.25, 0.5, 1.25, 3.5]

assert statistics.mean(data) == 1.6071428571428572

assert statistics.median(data) == 1.25

assert statistics.variance(data) == 1.3720238095238095