Inserting elements into Binary Min Heaps - binary-tree

If I am inserting items: 10,12,14,1,6 into a binary min heap one item after another how would the results look like, my problem is with the following
when i start i have:
10
then
10
/
12
then
10
/ \
12 14
then
1
/ \
10 14
/
12
but this is not right, so what is the right way to do that?
Note: this is a homework question, i am trying to understand the concept, if you don't feel comfortable solving the question (it is not the full question anyway) please provide an example with similar issue.

You have to add the new element as a child (or leaf exactly) to the heap (not as root), that means you put it in the first "right" free spot (or in your heap-array, just at the end).
Then you have to re-establish the heap conditions, this is called "heapify". This happens in two phases:
Repeatedly exchange the new element (general: the element that violates the heap conditions) with its parent node as long as it is smaller than the parent and it is not the root.
Repeatedly exchange the new element with the child with the smallest value, until the new element becomes a leave or both child nodes are bigger than the element itself.
That means
10
/ \
12 14
+ 1 leads to
10
/ \
12 14
/
1
And that violates the heap conditions, so you have to heapify
10
/ \
1 14
/
12
But this is still not right, so you have to heapify again
1
/ \
10 14
/
12
And there you are... everything OK now :-)

step1: 10
step2: 10
/
12
step3: 10
/ \
12 14
step4: 1
/ \
10 12
/
14
step5: 1
/ \
6 10
/ \
12 14

Related

Binary Search Tree, How should I rotate this tree to balance

I am trying to rotate a tree to keep it balanced, but I am having hard time with this example. I am not so sure what I am doing wrong here.
I have below tree with L/R height difference 1 at node 30. So, I guess this tree is balanced.
30
/ \
20 60
/ \
10 25
I am adding 22 here and this is what I get after adding 22.
30
/ \
20 60
/ \
10 25
/
22
At node 20, L/R height difference is 1, but at node 30 it is 2. So, I guess it is not balanced any more. I am trying to right rotate the tree to balance it, but I am getting below tree.
20
/ \
10 30
/ \
25 60
/
22
After the rotation, node 20 has L/R height difference of 2 still.
Where am I doing wrong? Can this tree be balanced using rotation?
I can balance the tree using sorted array method like below, but I am really confused about rotation balance in this example.
22 25
/ \ / \
20 30 20 30
/ / \ / \ \
10 25 60 10 22 60
What am I doing wrong here?
Thanks a lot!!
There are basically four type of rotation in the AVL Tree.
Right-left
Left-Right
Left-Left
Right-Right
In your case, Left-Right should be applicable.
Here you need to perform two steps.
1:- Left rotate from 20 node. So your tree should like as below.
30
/ \
25 60
/
20
/ \
10 22
2:- Right rotate from 30 node. So your tree should be like as below.
25
/ \
20 30
/ \ \
10 22 60
You can refer the N website to understand the behavior. Here is one of the best link
This case requires a double rotation: rotate 25 up twice. I'm assuming that you're thinking about AVL trees, but all of the standard balanced binary trees need double rotations in some cases.

AVL Rotation - Which node to rotate

I have read many sources about AVL trees, but did not find anyone addressing this issue: When AVL tree gets unbalanced, which node should be rotated first?
Assuming I have the tree:
10
/ \
5 25
/
20
and I'm trying to add 15, both the root and its child 25 will be unbalanced.
10
/ \
5 25
/
20
/
15
I could do a RR rotation (or single rotation) of 25, resulting in the following tree:
10
/ \
5 20
/\
15 25
or a RL rotation (double rotation) about the root, creating the following tree:
20
/ \
10 25
/ \
5 15
I am confused about which rotation is the most suitable here and in similar cases.
The RR rotation is correct here. The rotation should be done as soon (as low) as the rule is broken. Which is for 25 here.
The higher rotations first don't necessarily break the rule and secondly would become too complex although it doesn't seem so here at the first sight.

How to make a N-level tree in pyramid fashion, such that each child may(doesn't mean has to) have 2 parents?

The question may look very simple, and probably the answer is too, but I always get confused in the tree questions.
Ok so I want to make a tree something like:
3 level 0
/ \
4 5 level 1 ..
/ \ / \
6 7 8
/ \ / \ / \
9 10 11 12
What are such trees called? Sorry, I'm a beginner..
Function can pass an array[] of ints, or function can take input till N = 3 (denoting level 3 with 10 nodes). Also can you give solution in C/C++/Java.
Given your requirements are only for traversal, I would simply implement this using an array a, containing each level as a contiguous sub-array. Level i then occurs in entries L(i-1) up to but not including L(i), where L(n) = n*(n+1)/2. In particular, the jth value on the ith level is in a[L(i-1)+j].
As long as you always keep track of i and j, you can now easily navigate through your pyramid.

Else than backtracking, how do I find longest path in a graph?

I have a graph shaped as a triangle.
8
/ \
1 4
/ \ / \
4 2 0
/ \ / \ / \
9 1 9 4
In the above graph the longest path is {8, 4, 2, 9}
My current algorithm calculates the max number of the adjacent nodes and add it to the list, then calculates the sum of that list. This works in the above graph but won't work in situations such as this scenario:
8
/ \
0 1
/ \ / \
4 0 4
/ \ / \ / \
9 99 3 4
My algorithm will mistakenly go through {8,1,4,4} where the correct longest path is {8,0,4,99}
The only solution I can think of is Backtracking. Where I have to go through all the paths and calculate the max path, which will be insanely slow in a huge graph. This about a 100k nodes graph.
My question is can I do better than this?
Start at the top.
For each node, pick the maximum of its parents (the nodes above connected to it) and add its own value.
Then, in the last row, pick the maximum.
This will just give you the value of the longest path, but you could easily get the actual path by simply starting at the value picked at the bottom and moving upwards, always picking the greater parent.
The running time would be linear in the number of nodes.
Example:
Original:
First example: Second example:
8 8
/ \ / \
1 4 0 1
/ \ / \ / \ / \
4 2 0 4 0 4
/ \ / \ / \ / \ / \ / \
9 1 9 4 9 99 3 4
Output:
First example: Second example:
8 8
/ \ / \
9 12 8 9
/ \ / \ / \ / \
13 14 12 12 9 13
/ \ / \ / \ / \ / \ / \
22 15 23 16 21 111 16 17
Then you'd pick 23 for the first and 111 for the second.
To get the path, we'd have 23-14-12-8, which corresponds to 9-2-4-8, for the first, and 111-12-8-8, which corresponds to 99-4-0-8, for the second.
I'm of course assuming we have a tree, as stated. For general graphs, this problem is quite a lot more difficult - NP-hard, to be exact.
You do not need backtracking here - you can use breadth-first search to propagate the max for the path that you have found so far to the corresponding node, level by level.
Start at the root, and set its max to its own value.
Go through nodes level-by-level
For each node check the max stored in its parent. There may be one or two of these parents. Pick the max of two max-es, add the value of the node itself, and store it in the current node
When the path through the graph is complete, the result would look like this:
Max graph:
8
/ \
8 9
/ \ / \
12 9 13
/ \ / \ / \
21 111 16 17
To recover a path, find the max value in the bottom layer. This is the final node of your path. You can reconstruct the path from the max graph and the original by starting at the max (111), subtracting the value (99), looking for the result (111-99=12) in the max graph, and continuing to that node until you reach the top:
111 - 99 = 12 -- Take 99
12 - 4 = 8 -- Take 4
8 - 0 = 8 -- Take 0
8 is the root -- Take 8
This gives you the max path in reverse. Note that this may not be the unique path (think of a graph filled with equal values to see how there may be multiple max paths). In this case, however, any path that you would recover will satisfy the max path requirement.

Balanced Binary Search Tree for numbers

I wanted to draw a balanced binary search tree for numbers from 1 to 20.
_______10_______
/ \
___5___ 15
/ \ / \
3 8 13 18
/ \ / \ / \ / \
2 4 7 9 12 14 17 19
/ / / /
1 6 11 16
Is the above tree correct and balanced?
In answer to your original question as to whether or not you need to first calculate the height, no, you don't need to. You just have to understand that a balanced tree is one where the height difference between the tallest and shortest node is zero or one, and the simplest way to achieve this is to ensure that you always pick the midpoint of the possible list, when populating the top node in a sub-tree.
Your sample tree is balanced since all leaf nodes are either at the bottom or next-to-bottom level, hence the difference in heights between any two leaf nodes is at most one.
To create a balanced tree from the numbers 1 through 20 inclusive, you can just make the root entry 10 or 11 (the midpoint being 10.5 for those numbers), so that there's an equal quantity of numbers in either sub-tree.
Then just do that recursively for each sub-tree. On the lower side of 10, 5 is the midpoint:
10
/ \
5 11-thru-19 sub-tree
/ \
1-thru-4 6-thru-9
sub-tree sub-tree
Just expand on that and you'll end up with something like:
_______10_______
/ \
___5___ 15
/ \ / \
2 7 13 17
/ \ / \ / / \
1 3 6 8 11 16 18 <- depth of highest leaf node
\ \ \ \
4 9 12 19 <- depth of lowest leaf node
^
|
Difference is 1
The midpoint can be found at the number where the difference between quantities above and below that numbers is one or zero. For the whole list of numbers 1 through 20 inclusive, there are nine less than 10 and ten greater than 10 (or, if you chose 11 as the midpoint, the quantities are ten and nine).
The difference between your sample and mine is probably to do with the fact that I preferred to pick the midpoint by rounding down where there was a choice (meaning my right sub-trees tend to be "heavier"). Because your left sub-trees are heavier, you appear to have rounded up.
After choosing 10 as the initial midpoint, there's no leeway on the left sub-tree, you have to choose 5 since it has four above and below it. Any other midpoint would result in a difference of at least two between the two halves (for example, choosing 4 as the midpoint would have the two halves of size three and five). This can still give you a balanced sub-tree depending on the data but it's "safer" to choose the midpoint.

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