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FAQ
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==========================
FREQUENTLY ASKED QUESTIONS
==========================
==========
Q: I need to store some information into vertices and/or edges
I need several kind of labels on the edges
-----
A: Use one of the functor implementation provided in Persistent or Imperative.
If for instance you want mutable directed graphs with colored vertices,
you may do
type color = Red | Green | Blue | Yellow
module G = Imperative.Digraph.Abstract(struct type t = color end)
(to be able to change the color you would use `type t = color ref' instead)
==========
==========
Q: How to choose between concrete and abstract vertices for my graph
implementation?
-----
A: If you fall into one of the following cases, use abstract vertices:
- you cannot provide efficient comparison/hash functions for vertices; or
- you wish to get two different vertices with the same label.
In other cases, it is certainly easier to use concrete vertices.
==========
==========
Q: Is it possible to serialize graphs?
-----
A: Graphs are serializable data structures: just call [Pervasives.output_value]
on your graph (for example).
But abstract graphs use integer tags to identify vertices;
this tag is made from the global reference [Blocks.cpt_vertex].
There are two related issues.
1) If there are abstract vertices in RAM while unmarshalling some others,
you have to be sure that RAM vertices do not share tags with unmarshalled
ones (except if you really want that).
2) If you need to create new vertices after unserialising an abstract graph,
you have to:
- serialize [!Blocks.cpt_vertex];
- call function [Blocks.after_unserialization] after your unserialisation
process.
There is no issue with concrete graph: it may be easier to use them if
unmarshalling is required.
==========
==========
Q: I need Foobar-Tarjan algorithm and it is not provided
-----
A: Please contribute by sending us the code :-) See next question.
==========
==========
Q: How can I contribute to this library?
-----
A: You can contribute either with a graph data structure or with an algorithm
over graphs. For the former, please follow the signatures given in module
Sig. For the latter, write your algorithm as a functor, following examples
in modules Path, Flow, Components, etc.
==========
==========
Q: Your implementation of algorithm AAA could be greatly improved provided
you add this and this into the graph data structure
-----
A: Of course yes. But the idea behind ocamlgraph is to be as generic as
possible (any algorithm should be useable on any implementation).
When the graph data structure provides additional capabilities
(such as marking, etc.) it is possible to provide a more efficient
implementation into some specialized functor. See module Traverse for
instance (where DFS and cycle detection are optimized for imperative
graphs equipped with marks)
==========
==========
Q: I have a graph implementation with polymorphic types for vertices or edges
and thus I can't apply the algorithms functors
-----
A: Here we bump into Ocaml's type system limitations: the number of type
parameters must be know when the functor is written and the simplest
choice for us was to assume no type parameter at all. (This is exactly the
same for functors Set.Make or Map.Make from Ocaml standard library.)
As a (bad) workaround, you can copy the functor body and substitute your
own functions for the functor arguments.
==========