I want to create a tree in Fortran (90) like the one in this picture:
The idea is that I would then be able to follow a path through the tree starting from the root in the following way. At each node perform a check with the value stored there: passing the check move to the left-most child, not passing or having reached a leaf-node move the highest node that the traversal hasn't been to yet. Here is an example of a possible traversal (green indicating passing the test and red not passing):
Importantly, not every node is reached (the ones in black) which is the point of the procedure actually.
So, I think I need is a subroutine that would insert nodes in the tree, in order to build it and another that would allow me to follow paths of the kind described above.
My question is, is this possible? Does this data structure have a name?
Granted that I have virtually no experience with building data structures of this kind, Google has not been much help. An example code would be great but I would be happy to just be referred to some reading where I could learn this.
Related
I would like to use a .natvis file to display all of the elements in a tree structure as a flat list.
I'm aware of the TreeItems expansion described in the .natvis documentation, and have tried to use that, but it seems a bit limited, and difficult to get to work in my situation (Templated node types, nodes which don't contain the actual data, need to cast the nodes to other templated types to get the data, lack of ability to do Exec entries or multiple Items per tree node, etc.)
The CustomListItems expansion is a lot more flexible in terms of being able to assign variables and execute commands which are evaluated in a loop. But I'm struggling to figure out whether there's a way to explore a tree in CustomListItems. Basically there would have to be some way to maintain a stack of some kind so that I could explore the entire left branch and then pop back up and explore the right branch. Is there any way to do this in CustomListItems?
https://learn.microsoft.com/en-ca/previous-versions/visualstudio/visual-studio-2015/debugger/create-custom-views-of-native-objects?view=vs-2015&redirectedfrom=MSDN#natvis-views
I created a doubly-linked list, and the benefits of a sentinel node were clear - no null checks or special cases at list boundaries.
Now I'm writing a red black tree, and trying to figure out if there is any benefit to such a concept.
My implementation is based on the last two functions in this article
(top down insertion/deletion). The author uses a "dummy tree root" or "head" to avoid special cases at the root for his insertion/deletion algorithms. The author's head node is scoped to the functions themselves - seemingly due to it's limited usefulness.
One other article I came across mentioned using a permanent root above the head as an "end" for iteration. This seems interesting, but I tried it and couldn't see any real benefit over using NULL as an end iterator. I also found several articles that used a shared sentinel to represent all empty leaf nodes, but this seems even more pointless than the first case.
Can anyone elaborate on how a sentinel node would be useful in a red black tree?
I am currently trying to create a Barnes-Hut octree, however, I still not fully understand how to do this properly. I have read threads here, this article and some others. I believe I do understand how to make a tree if every node contains the information about the indices of particles inside, and if you keep storing the empty nodes. But if you do not want to? How to make a tree such that at the end you will only have necessary information: say, monopoles and quadrupoles for all non-empty nodes. I made so many different attempts that now I am completely confused, to be honest. What should I contain in each node? What would be the pseudocode for such thing?
P.S. By the way, is it different for monopoles and quadrupoles? I mean I can imagine that you do not need the exact information about the particles inside the node to calculate a monopole (it is just a full mass of node), but for quadruple?
Thank you in advance!
P.S. By the way, I use julia language if it is somehow relevant.
The Zipper data structure is great when one wants to traverse a tree and keep the current position, but what data structure one should use if they want to track more then one position?
Let me explain with examples:
Someone on the #haskell channel has told me that zippers are used in yi editor to represent
the cursor position. This is great, but what if you want to have two
cursors. Like if you want to represent a selection, you need to know the beginning and
the end of the selection.
In the Minotaur example on wikibooks, they use Zipper to represent Minotaur's position inside the labyrinth. If I wanted to add enemy into the labyrinth, representing their position with a Zipper would make as much sense.
Last one is actualy from my mini project where it all started: As part of learning Haskell I'm trying to visualize a tree structure using cairo and gth2hs. This has gone well so far but now I would like to select one or more of the nodes and be able to e.g. move them around. Because there can be more then one of the selected nodes I can't just use
the Zipper as defined in text books.
There is a trivial (naive?) solution, similar to the one they had used in early versions of XMonad which involves finite maps as explained here.
That is, e.g. in case of my example project, I would store the selected nodes in an indexed map and replace their representation in the main structure with the indices. But this solution has plenty of disadvantages. Like the ones explained in the link above, or say, again in case of my example, unselecting all the nodes would require searching the whole tree.
Oleg's work on "concurrent" zippers via delimited continuations is the main reference.
See this paper . I seem to recall reading somewhere that the second derivative has two holes, which is probably what you want.
I was thinking today about the best way to store a hierarchical set of nodes, e.g.
(source: www2002.org)
The most obvious way to represent this (to me at least) would be for each node to have nextSibling and childNode pointers, either of which could be null.
This has the following properties:
Requires a small number of changes if you want to add in or remove a node somewhere
Is highly susceptible to corruption. If one node was lost, you could potentially lose a large amount of other nodes that were dependent on being found through that node's pointers.
Another method you might use is to come up with a system of coordinates, e.g. 1.1, 1.2, 1.2.1, 1.2.2. 1.2.3 would be the 3rd node at the 3rd level, with the 2nd node at the prior level as its parent. Unanticipated loss of a node would not affect the ability to resolve any other nodes. However, adding in a node somewhere has the potential effect of changing the coordinates for a large number of other nodes.
What are ways that you could store a hierarchy of nodes that requires few changes to add or delete a node and is resilient to corruption of a few nodes? (not implementation-specific)
When you refer to corruption, are you talking about RAM or some other storage? Perhaps during transmission over some medium?
In any case, when you are dealing with data corruption you are talking about an entire field of computer science that deals with error detection and correction.
When you talk about losing a node, the first thing you have to figure out is 'how do I know I've lost a node?', that's error detection.
As for the problem of protecting data from corruption, pretty much the only way to do this is with redundancy. The amount of redundancy is determined by what limit you want to put on the degree of corruption you would like to be able to recover from. You can't really protect yourself from this with a clever structure design as you are just as likely to suffer corruption to the critical 'clever' part of your structure :)
The ever-wise wikipedia is a good place to start: Error detection and correction
I was thinking today about the best way to store a hierarchical set of nodes
So you are writing a filesystem? ;-)
The most obvious way to represent this (to me at least) would be for each node to have nextSibling and childNode pointers
Why? The sibling information is present at the parent node, so all you need is a pointer back to the parent. A doubly linked-list, so to speak.
What are ways that you could store a hierarchy of nodes that requires few changes to add or delete a node and is resilient to corruption of a few nodes?
There are actually two different questions involved here.
Is the data corrupt?
How do I fix corrupt data (aka self healing systems)?
Answers to these two questions will determine the exact nature of the solution.
Data Corruption
If your only aim is to know if your data is good or not, store a hash digest of child node information with the parent.
Self Healing Structures
Any self healing structure will need the following information:
Is there a corruption? (See above)
Where is the corruption?
Can it be healed?
Different algorithms exist to fix data with varying degree of effectiveness. The root idea is to introduce redundancy. Reconstruction depends on your degree of redundancy. Since the best guarantees are given by the most redundant systems -- you'll have to choose.
I believe there is some scope of narrowing down your question to a point where we can start discussing individual bits and pieces of the puzzle.
A simple option is to store reference to root node in every node - this way it is easy to detect orphan nodes.
Another interesting option is to store hierarchy information as a descendants (transitive closure) table. So for 1.2.3 node you'd have the following relations:
1., 1.2.3. - root node is ascendant of 1.2.3.
1.2., 1.2.3. - 1.2. node is ascendant of 1.2.3.
1., 1.2. - root node is ascendant of 1.2.
etc...
This table can be more resistant to errors as it holds some redundant info.
Goran
The typical method to store a hierarchy, is to have a ParentNode property/field in every node. For root the ParentNode is null, for all other nodes it has a value. This does mean that the tree may lose entire branches, but in memory that seems unlikely, and in a DB you can guard against that using constraints.
This approach doesn't directly support the finding of all siblings, if that is a requirement I'd add another property/field for depth, root has depth 0, all nodes below root have depth 1, and so on. All nodes with the same depth are siblings.