Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 6 years ago.
Improve this question
I am trying to find a repository hosting input and output files of large Hamiltonian graphs to test how well my estimation algorithm works. Does anyone know such a place to get sample graphs with their Hamiltonian cycles to test against?
You can have a look at TSPLIB, which is a collection of sample instances for the Traveling Salesman Problem (and related problems) from various sources and of various types. It also has a section for Hamiltonian Cycle problems, with thousands of inputs and output files.
For example, the FHCP Challenge Set is a collection of 1001 instances of the Hamiltonian Cycle Problem, ranging in size from 66 vertices up to 9528 vertices, with an average size of just over 3000 vertices.
Related
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 1 year ago.
Improve this question
The MCMF problem is a standard problem where you have multiple sinks and sources where each source have some supply capacity and each sink node has some demand. Each source and sinks are connected with an edge with some capacity and some cost. You need to maximize the flow with minimum cost. how to solve MCMF problem? Is there any prewritten algo in any library?
Yes there are couple of algorithms like - capacity scaling, cost scaling, network simlex etc. You can find implementations in libraries like - Boost graph library, Networkx, LEMON.
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 3 years ago.
Improve this question
I am trying to train tenserflow U-net, for multi-class segmentation of heart. I have 3 labels and the prediction has 3 probability maps (one probability map for every label). I trained with momentum optimizer which is also the default optimizer of the network. In the very beginning iterations, the probability mapping of label 1 and label 2 are different but after some iterations (or epochs) the probability map of label 1 and label 2 become exactly like each other and technically I have a binary label segmentation. I have seen other networks that have similar architecture like U-net and they have trained on the multi-class dataset. I want to find some multiclass segmentation examples with U-net but all examples are binary.
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 6 years ago.
Improve this question
I am looking for an optimized 4-connectivity or 8-connectivity Connected Component Labelling source code in MATLAB or C++. I saw many implementation of connected component labelling (4-connectivity) in MATLAB.
One of the implementations that works faster is the recursive implementation explained here: http://www.mathworks.com/matlabcentral/fileexchange/38010-connected-component-labeling-like-bwlabel
MATLAB has a built-in bwlabeln or bwlabel, which is far more optimized. They claim to use union-find method from two-pass algorithm described in Sedgewick's Algorithms in C, Addison-Wesley. However, it is hard to find any source code of it. Does anyone have idea about it? An optimized code is really needed.
You can indeed work by scanning the image in scanline order and when you meet a component seed-fill it.
You will find two efficient (and very similar) algorithms in Graphics GEMS 1:
A SEED FILL ALGORITHM, Paul S. Heckbert
FILLING A REGION IN A FRAME BUFFER, Ken Fishkin
and with a little effort some implementations. (The papers give Pascal-like code which is easy to translate.)
They run in linear time, use an explicit stack and don't require union-find.
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 7 years ago.
Improve this question
I've started to work with Neo4j. I know there is an opportunity to extend its API with new functionality. Also, I'm interested in algorithms for large-scale graphs.
My question is: Does anyone know any sites or other resources with the latest improvements for large-scale graphs algorithms? Or maybe you can advise me the most effective solutions for some kind of operations, like: finding the shortest path algorithms, clusterization algorithms, nearest neighbour, radius/diameter computing etc.
Thanks a lot!
Much of modern applied graph theory centers on applying computational linear algebra to graph theoretic algorithms. One prominent group involved in such work is John Gilbert's at UCSB: his group put out a piece of software called Combinatorial BLAS for efficiently executing graph algorithms using methods in computational linear algebra.
Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
We don’t allow questions seeking recommendations for books, tools, software libraries, and more. You can edit the question so it can be answered with facts and citations.
Closed 7 years ago.
Improve this question
I'm having a really hard time visualizing how the Bellman-Ford algorithm works purely through reading code. Does anyone know of an visual example (video, slideshow) that works through an actual graph with that algorithm? Thanks!
I think that this page might be what you are looking for. It does indeed run through the algorithm on a graph, and you may use the UI below to pause the visualization, or run through individual frames one at a time so that you can visualize it at your own pace.