Functions

Functions#

We have used already used functions (e.g., imread(some_path)) in past lessons. Functions have a name and parameters. Some of them return a result, others don’t. We typically call them like this:

result = function_name(parameters)

Custom functions#

You can DEFine your own functions using the def statement. After the def statement, you should specify your functions’ name and in brackets its parameters. Afterwards follows a colon : and all following lines of code which are indented are part (“inside”) of this function. A final return statement sends the result back to from where the function was called.

def sum_numbers(a, b):
    
    result = a + b
    
    return result

You can then call your function as often as you like

sum_numbers(3, 4)

sum_numbers(5, 6)

Sometimes, you want to save the result of your function in a variable.

c = sum_numbers(4, 5)
print(c)

Simplify code using functions#

Assume you have a complicated algorithm which can tell you if a number if odd or even. Let’s put this algorithm in a function and call it later on. For our algorithm, we will use the modulo operator %.

def print_odd_or_even(number):
    if number % 2 == 0:
        print(number, "is even")
    else:
        print(number, "is odd")

print_odd_or_even(3)

print_odd_or_even(4)

print_odd_or_even(10)

Thus, instead of writing the same if-else block again and again, we can just call our custom print_odd_or_even function.

Documenting functions#

You can document what a function does in its so called doc string. The doc string follows right after the functions header and looks like this:

def square(number):
    '''
    Squares a number by multiplying it with itself and returns its result.
    '''

    return number * number

You can then later read the documentation of the function like this:

print(square.__doc__)

Also try this if you want to have the docstring shown side-by-side in your notebook:

square?

By the way, you can do this with any function:

import math
print(math.sqrt.__doc__)

print(math.exp.__doc__)

Methods#

Methods, as opposed to function are functions that can be executed directly from a variable. They are defined in the same way as functions, but they are called in a different way.

Normal function: function_name(arguments)
Method: variable_name.method_name(optional_arguments)

Every type of variable has its own methods. For example, strings have methods to convert them to uppercase or lowercase, to replace a substring, to split them, etc.

name = 'Johannes'
name.lower()

filename = 'my_image.tif'
filename.endswith('.tif')

Numpy arrays also have a few handy methods you can directly use on them. For example, you can use the mean(), .std() or .sum() methods to calculate the mean, standard deviation and sum of the elements in an array, respectively.

import numpy as np

# create some random data
array = np.random.randint(low=0, high=3, size=[3,3])
array

print(f'Mean: {array.mean()}')
print(f'Standard deviation: {array.std()}')
print(f'Sum of all elements: {array.sum()}')

In some cases, these methods take optional arguments customize the call. For install, the mean, std and sum functions take an optional axis argument that specifies which axis to perform the operation on.

print(f'Sum of all elements along first axis: {array.sum(axis=0)}')
print(f'Sum of all elements along first axis: {array.sum(axis=1)}')

Exercises#

Exercise 1#

Write a function that takes two parameters: number_of_points_achieved and number_of_total_points_in_exam and returns a grade from 1 to 5. Students with > 95% of the points get grade 1, above 80% they get grade 2, above 60% grade 3 and above 50% grade 4. Students with less than 50% get grade 5 and have to repeat the exam. Then, call the function for three students who had 15, 25 and 29 points in an exam with 30 total points.

grade_student_exams(20,30, pass_only=True)

Exercise 2#

write a docstring for your function that describes what it does, the input parameters it expects and the output it returns.

Explore how the jupyter autocompletion and inspecting it with a ? helps you when you use the function.

Exercise 3#

add an optional parameter pass_fail=True to add the possibility to evaluate an exam where students with more than 50% pass the exam.

Exercise 4#

split the complicated function from Exercise 3 into two simpler functions