Introduction to Functional Programming

Computers are particularly useful when the task requires doing the same thing, many time repeatedly. In this notebook we introduce the use of funtions and loops to let the computer do repeated calculations. And finally demonstrate how to save code in a module that can be imported in your notebook.

Contents:

• Functions
• Loops
• Modules

from numpy import *

A. Functions

In Python we define a function to evaluate a result based on inputs. For example, if you find yourself repeatedly finding the magnitude of a vector, you could define a function to do it. (See the Python Tutorial for much more.)

Define a function with def, then a function name of your choice, then the inputs it needs. End the function with a return statement that provides the result of the computation.

def magnitude_and_direction(vec):                              # define function
    "find the magnitude and direction (in deg) of a 2D vector" # optional documentation line
    mag = sqrt( sum( vec**2 ) )                                
    angle = arctan2(vec[1],vec[0])
    angle = angle * 180/pi                                         # convert to deg
    return mag,angle                                               # return these results

r = array(( 5.5, 3 ))
s = array((-5,  -3 ))
magnitude_and_direction(r)

(6.264982043070834, 28.61045966596522)

magnitude_and_direction( 2*r )

(12.529964086141668, 28.61045966596522)

magnitude_and_direction( r+s )

(0.5, 0.0)

m,d = magnitude_and_direction( s )
print('magnitude of s = {:.3f}, at angle {:.3f} degrees'.format(m,d))

magnitude of s = 5.831, at angle -149.036 degrees

B. Loops

A code loop tells the computer to do something over and over again. There are two basic varieties: the while loop and the for loop.

while loop

A while loop executes over and over, as long as a given condition is true. For example, the Fibonacci sequence is defined such that each element is the sum of the previous two: $\left \{ 0,1,1,2,3,5,8,... \right \}$. The following while loop will continue to print out series elements as long as they're under 20.

a, b = 0, 1
while b < 20:
    print(b)
    c = a+b
    a = b 
    b = c

1
1
2
3
5
8
13

Here's a while loop to find the smallest number that standard Python allows.

small = 1.0
while 1+small > 1:
    small = small/2  # cut 'small' in half
print ('smallest value =',small)

smallest value = 1.1102230246251565e-16

for loop

A for loop will iterate over elements in a list (or array or other sequence).

You could use it to count how many negative values are in a list:

things = [ -1.396,  0.62, -0.57566, -0.66, -1.668, 0.247]
count = 0  # starting value
for t in things:
    if t < 0: count = count + 1
print('there are',count,'negative values')

there are 4 negative values

The range function is often useful in a for statement.

for i in range(5,10):
    print(i)

5
6
7
8
9

Note given end point is never part of the range sequence; range(10) generates 10 values, starting at 0. See more in the tutorial.

C. Modules

Suppose you use a function such as magnitude_and_direction() in many different notebooks. Rather that rewriting the function in each notebook, you could save the code in a "module" which could then be imported when needed.

The physical_constants notebook is convenient to use this way. Take a look at physical_constants.html (the html version of the notebook). The constant deg_per_rad is defined there to convert radians to degrees. To use it here you could import the module:

import physical_constants

The contents of that module are now available here, but they are in their own "namespace". That means that to access them you preceed a variable defined in that module by the module name, followed by a period:

physical_constants.deg_per_rad

57.29577951308232

Note: you can save a lot of this typing with tab completion. Type the first couple of letters and hit Tab to automatically complete it (or to see the possible completions).

If you prefer to dump all the variables defined in that module into this notebook's namespace, import it as follows:

from physical_constants import *

That essentially executes all the code in that module as though it were written here. Now we can write

print('the mass of an electron is',me,'kg')

the mass of an electron is 9.109e-31 kg

If you don't want to compromise your namespace (with from module import * ). You can define a variable to import as, like this:

import physical_constants as pc

Now you have a shortcut to all the stuff in that module.

print('there are exactly', pc.cm_per_in, 'cm in one inch')

there are exactly 2.54 cm in one inch

Creating your own module

The easiest way to create your own module is to create a notebook with the code you will want to import. In the file menu, choose Download as > Python (.py), and put the module in the folder with the notebook that will use it.

Learn more about modules in the Python Tutorial.

Last modified: Thu August 24 2023, 07:41 AM.