Multidimensional collections

Martin McBride, 2020-02-27
Tags len 2d list
Categories magic methods

In the article on magic methods for collections we saw how to implement collection behaviours for our example matrix class. We implemented support of built-in function len, support for for loops and the in operator. We also saw how to might implement del, although our 2 by 2 matrix doesn't allow it.

For getting and setting elements, we implemented __getitem__ and __setitem__ as if the matrix was a list of 4 elements. In thi sarticle we will see how to improve that.

Supporting two dimensional selection

Our Matrix is a 2D array, so wouldn't it be nice to support (row, column) style selection? It would be nice if we could use a syntax like:

a[0, 1]     #row 0, columns 1

Well we can! The numpy library does exactly this, and we can easily support this with our Matrix class.

If you are familiar with dictionaries, you will know that a dictionary is indexed by keys rather than integers. A key can be an integer, or a string, but it can also be a tuple:

d = dict()
d[0] = 0
d['two'] = 2
d[(0, 1)] = 3

This gives the result:

{0: 0, 'two': 2, (0, 1): 3}

Thanks to the magic of tuple packing we can write d[(0, 1)] as d[0, 1]. So we can do this:

d[0, 1] = 10

which gives:

{0: 0, 'two': 2, (0, 1): 10}

We need to do a similar thing with our matrix class.

Two dimensional getters and setters

Previously our getter and setter accepted and index of the item in list of length 4:

def __getitem__(self, i):

But now instead we want to pass in a tuple (row, col). So we need to modify our code like this:

def __getitem__(self, t):
    row, col = t
    return[row*2 + col]

We can now do this:

m = Matrix(1, 2, 3, 4)
print(m[1, 0])

This prints matrix row 1, column 0, which is the value 3.

We can do a similar thing with the setter:

def __setitem__(self, t, value):
    row, col = t[row*2 + col] = value

which allows us to do this:

m[0, 1] = 5

The matrix has now been updated, with row 0 column 1 set to 5:

[1, 5][3, 4]
If you found this article useful, you might be interested in the book Functional Programming in Python or other books by the same author.


Popular tags

2d arrays abstract data type alignment and animation arc array arrays behavioural pattern bezier curve built-in function callable object chain circle classes close closure cmyk colour combinations comparison operator comprehension context context manager conversion count creational pattern data types design pattern device space dictionary drawing duck typing efficiency ellipse else encryption enumerate fill filter font font style for loop function function composition function plot functools game development generativepy tutorial generator geometry gif gradient greyscale higher order function hsl html image image processing imagesurface immutable object index inner function input installing iter iterable iterator itertools l system lambda function len line linear gradient linspace list list comprehension logical operator lru_cache magic method mandelbrot mandelbrot set map monad mutability named parameter numeric python numpy object open operator optional parameter or partial application path pattern permutations polygon positional parameter print pure function python standard library radial gradient range recipes rectangle recursion reduce repeat rgb rotation scaling sector segment sequence setup shape singleton slice slicing sound spirograph sprite square str stream string stroke structural pattern subpath symmetric encryption template text text metrics tinkerbell fractal transform translation transparency triangle tuple turtle unpacking user space vectorisation webserver website while loop zip