Recursive Data Structures

Read this page. In the previous unit of our course we studied recursive algorithms. Recursion is a concept that also applies to data. Here we look at recursive data structures - lists, trees, and sets. A list is a structure that consists of elements linked together. If an element is linked to more than one element, the structure is a tree. If each element is linked to two (sub) elements, it is called a binary tree. Trees can be implemented using lists, as shown in the resource for this unit. Several examples of the wide applicability of lists are presented. A link points to all the remaining links, i.e. the rest of the list or the rest of the tree; thus, a link points to a list or to a tree - this is data recursion.

The efficiency of the programming process includes both running time and size of data. This page discusses the latter for recursive lists and trees.

Lastly, why read the last section on sets? Sets are another recursive data structure and the last section 2.7.6, indicates their connection with trees, namely, a set data type can be implemented in several different ways using a list or a tree data type. Thus, the programming process includes implementation decisions, in addition, to design or algorithm decisions. Each of these types of decisions is constrained by the features of the programming language used. The decision choices, such as which data structure to use, will impact efficiency and effectiveness of the program's satisfaction of the program's requirements.

Note: You will notice an unusual use of C++ here. What the author is doing is showing how to pass a fixed-value data-structure as a calling argument.

6. Separation of concerns

But back to our code. All we've done so far is moved the "faffing about" out of our code and we're doing it by hand. That's bad: we don't want to retrain our eyes to read quadtrees instead of flat arrays, and we don't want to sit at a computer all day manually translating quadtrees to flat arrays and back.

If only we could write some code to do it for us… Some recursive code…

Here's a function that recursively turns a two-dimensional array into a quadtree:

const isOneByOneArray = (something) =>
  Array.isArray(something) && something.length === 1 &&
  Array.isArray(something[0]) && something[0].length === 1;

const contentsOfOneByOneArray = (array) => array[0][0];

const regionsToQuadTree = ([ul, ur, lr, ll]) =>
  ({ ul, ur, lr, ll });

const arrayToQuadTree = multirec({
  indivisible: isOneByOneArray,
  value: contentsOfOneByOneArray,
  divide: divideSquareIntoRegions,
  combine: regionsToQuadTree
});

arrayToQuadTree([
  ['⚪️', '⚪️', '⚪️', '⚪️'],
  ['⚪️', '⚫️', '⚪️', '⚪️'],
  ['⚫️', '⚪️', '⚪️', '⚪️'],
  ['⚫️', '⚫️', '⚫️', '⚪️']
])
  //=>
    ({
      ul:  { ul: "⚪️", ur: "⚪️", lr: "⚫️", ll: "⚪️" },
      ur:  { ul: "⚪️", ur: "⚪️", lr: "⚪️", ll: "⚪️" },
      lr:  { ul: "⚪️", ur: "⚪️", lr: "⚪️", ll: "⚫️" },
      ll:  { ul: "⚫️", ur: "⚪️", lr: "⚫️", ll: "⚫️" }
    })

Naturally, we can also write a function to convert quadtrees back into two-dimensional arrays again:

const isSmallestActualSquare = (square) => isString(square.ul);

const asTwoDimensionalArray = ({ ul, ur, lr, ll }) =>
  [[ul, ur], [ll, lr]];

const regions = ({ ul, ur, lr, ll }) =>
  [ul, ur, lr, ll];

const combineFlatArrays = ([upperLeft, upperRight, lowerRight, lowerLeft]) => {
  const upperHalf = [...zipWith(concat, upperLeft, upperRight)];
  const lowerHalf = [...zipWith(concat, lowerLeft, lowerRight)];

  return concat(upperHalf, lowerHalf);
}

const quadTreeToArray = multirec({
  indivisible: isSmallestActualSquare,
  value: asTwoDimensionalArray,
  divide: regions,
  combine: combineFlatArrays
});

quadTreeToArray(
  arrayToQuadTree([
    ['⚪️', '⚪️', '⚪️', '⚪️'],
    ['⚪️', '⚫️', '⚪️', '⚪️'],
    ['⚫️', '⚪️', '⚪️', '⚪️'],
    ['⚫️', '⚫️', '⚫️', '⚪️']
  ])
)
  //=>
    ([
      ["⚪️", "⚪️", "⚪️", "⚪️"],
      ["⚪️", "⚫️", "⚪️", "⚪️"],
      ["⚫️", "⚪️", "⚪️", "⚪️"],
      ["⚫️", "⚫️", "⚫️", "⚪️"]
    ])

And thus, we can take a two-dimensional array, turn it into a quadtree, rotate the quadtree, and convert it back to a two-dimensional array again:

quadTreeToArray(
  rotateQuadTree(
    arrayToQuadTree([
      ['⚪️', '⚪️', '⚪️', '⚪️'],
      ['⚪️', '⚫️', '⚪️', '⚪️'],
      ['⚫️', '⚪️', '⚪️', '⚪️'],
      ['⚫️', '⚫️', '⚫️', '⚪️']
    ])
  )
)
  //=>
    ([
      ["⚫️", "⚫️", "⚪️", "⚪️"],
      ["⚫️", "⚪️", "⚫️", "⚪️"],
      ["⚫️", "⚪️", "⚪️", "⚪️"],
      ["⚪️", "⚪️", "⚪️", "⚪️"]
    ])