### Symmetric Generations

I've been trying to work on an implementation of a structure generator algorithm due to Faulon (its a paper in this list somewhere). One problem I have difficulty with is reduction of the number of isomers generated. For example:

It may be hard to read, but the idea is that the full tree of possible ways to attach {Br, Cl, F, I} to c1ccc1 is 4 * 3 * 2 * 1 (you can attach Bromine to all four of the carbons, leaving 3 places to attach chlorine, and so on).

Of course c1(Br)c(Cl)cc1 is the same as c1(Cl)c(Br)cc1 [never mind that C1(Br)=C(Cl)C=C1 is not the same as C1=C(Br)C(Cl)=C1]. Or, in other words, there is a high degree of symmetry in the tree.

There is a way to solve this, perhaps even described in the paper - if I could just understand them...

Symmetry is indeed the main blocker in structure generators. The only way to get performance is to detect symmetry as soon as possible... the deterministic generator we had in CDK 1.0 was doing this, as there is a trick to detect this in the connectivity matrix, but it needs to be normalized. I never had/took the time to fully grasp the math behind it to isolate the bugs in the implementation. But please do look up the literature; it's a must read for your work.
gilleain said…
Finding the eigenvalues of the matrix, perhaps?

Reading the literature is one thing, understanding it is another. I was reading "Isomorphism, Automorphism Partitioning, and Canonical
Labeling Can Be Solved in Polynomial-Time for Molecular Graphs" (Faulon, 1998) and it's heavy going :(

### Generating Dungeons With BSP Trees or Sliceable Rectangles

So, I admit that the original reason for looking at sliceable rectangles was because of this gaming stackoverflow question about generating dungeon maps. The approach described there uses something called a binary split partition tree (BSP Tree) that's usually used in the context of 3D - notably in the rendering engine of the game Doom. Here is a BSP tree, as an example:

In the image, we have a sliced rectangle on the left, with the final rectangles labelled with letters (A-E) and the slices with numbers (1-4). The corresponding tree is on the right, with the slices as internal nodes labelled with 'h' for horizontal and 'v' for vertical. Naturally, only the leaves correspond to rectangles, and each internal node has two children - it's a binary tree.

So what is the connection between such trees and the sliceable dual graphs? Well, the rectangles are related in exactly the expected way:

Here, the same BSP tree is on the left (without some labels), and the slicea…

### Listing Degree Restricted Trees

Although stack overflow is generally just an endless source of questions on the lines of "HALP plz give CODES!? ... NOT homeWORK!! - don't close :(" occasionally you get more interesting ones. For example this one that asks about degree-restricted trees. Also there's some stuff about vertex labelling, but I think I've slightly missed something there.

In any case, lets look at the simpler problem : listing non-isomorphic trees with max degree 3. It's a nice small example of a general approach that I've been thinking about. The idea is to:
Given N vertices, partition 2(N - 1) into N parts of at most 3 -> D = {d0, d1, ... }For each d_i in D, connect the degrees in all possible ways that make trees.Filter out duplicates within each set generated by some d_i. Hmm. Sure would be nice to have maths formatting on blogger....

Anyway, look at this example for partitioning 12 into 7 parts:

At the top are the partitions, in the middle the trees (colored by degree) …

### Common Vertex Matrices of Graphs

There is an interesting set of papers out this year by Milan Randic et al (sorry about the accents - blogger seems to have a problem with accented 'c'...). I've looked at his work before here.

[1] Common vertex matrix: A novel characterization of molecular graphs by counting
[2] On the centrality of vertices of molecular graphs

and one still in publication to do with fullerenes. The central idea here (ho ho) is a graph descriptor a bit like path lengths called 'centrality'. Briefly, it is the count of neighbourhood intersections between pairs of vertices. Roughly this is illustrated here:

For the selected pair of vertices, the common vertices are those at the same distance from each - one at a distance of two and one at a distance of three. The matrix element for this pair will be the sum - 2 - and this is repeated for all pairs in the graph. Naturally, this is symmetric:

At the right of the matrix is the row sum (∑) which can be ordered to provide a graph invarian…