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Boost C++ Libraries

...one of the most highly regarded and expertly designed C++ library projects in the world. — Herb Sutter and Andrei Alexandrescu , C++ Coding Standards

Disjoint Sets

This is class that provides disjoint sets operations with union by rank and path compression . A disjoint-sets data structure maintains a collection S = {S 1 , S 2 , ..., S k } of disjoint sets. Each set is identified by a representative which is some member of of the set. Sets are represented by rooted trees which are encoded in the Parent property map. Two heuristics: "union by rank" and "path compression" are used to speed up the operations [ 1 , 2 ].

Where Defined

Template parameters.

A typical usage pattern for disjoint_sets can be seen in the kruskal_minimum_spanning_tree() algorithm. In this example, we call link() instead of union_set() because u and v were obtained from find_set() and therefore are already the representatives for their sets.

The time complexity is O(m alpha(m,n)) , where alpha is the inverse Ackermann's function, m is the number of disjoint-set operations ( make_set() , find_set() , and link() and n is the number of elements. The alpha function grows very slowly, much more slowly than the log function.

This class manages the storage for the rank and parent properties internally. The storage is in arrays, which are indexed by element ID, hence the requirement for the ID and InverseID functors. The rank and parent properties are initialized during construction so the each element is in a set by itself (so it is not necessary to initialize objects of this class with the initialize_incremental_components() function). This class is especially useful when computing the (dynamic) connected components of an edge_list graph which does not provide a place to store vertex properties.

This class has all of the members in disjoint_sets as well as the following members.

This is a functor which finds the representative vertex for the same component as the element x . While traversing up the representative tree, the functor also applies the path halving technique to shorten the height of the tree.

This is a functor which finds the representative element for the set that element x belongs to.

Revised 01 December, 2006

Distributed under the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt )

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[Solved]-Understanding boost::disjoint_sets-C++

what i can understand from the documentation :

disjoint need to associate a rank and a parent (in the forest tree) to each element. since you might want to work with any kind of data you may,for example, not always want to use a map for the parent: with integer an array is sufficient. you also need a rank foe each element (the rank needed for the union-find).

you'll need two "properties" :

one to associate an integer to each element (first template argument), the rank
one to associate an element to an other one (second template argument), the fathers

on an example :

arrays are used &rank[0], &parent[0] to the type in the template is int*

for a more complex example (using maps) you can look at ugo's answer.

you are just giving to the algorithm two structures to store the data (rank/parent) he needs.

i written a simple implementation a while ago. have a look.

and the usage goes like this. it's simple. isn't it?

loic's answer looks good to me, but i needed to initialize the parent so that each element had itself as parent, so i used the iota function to generate an increasing sequence starting from 0.

using boost, and i imported bits/stdc++.h and used using namespace std for simplicity.

i changed std::vector to std::array because pushing elements to a vector will make it realloc its data, which makes the references the disjoint sets object contains become invalid.

as far as i know, it's not guaranteed that the parent will be a specific number, so that's why i wrote 1 or 2 or 3 or 4 (it can be any of these). maybe the documentation explains with more detail which number will be chosen as leader of the set (i haven't studied it).

in my case, the output is:

seems simple, it can probably be improved to make it more robust (somehow).

note: std::iota fills the range [first, last) with sequentially increasing values, starting with value and repetitively evaluating ++value. more: https://en.cppreference.com/w/cpp/algorithm/iota

for those of you who can't afford the overhead of std::map (or can't use it because you don't have default constructor in your class), but whose data is not as simple as int , i wrote a guide to a solution using std::vector , which is kind of optimal when you know the total number of elements beforehand.

the guide includes a fully-working sample code that you can download and test on your own.

the solution mentioned there assumes you have control of the class' code so that in particular you can add some attributes. if this is still not possible, you can always add a wrapper around it:

moreover, if you know the number of elements to be small, there's no need for size_t , in which case you can add some template for the unsignedint type and decide in runtime to instantiate it with uint8_t , uint16_t , uint32_t or uint64_t , which you can obtain with <cstdint> in c++11 or with boost::cstdint otherwise.

here's the link again in case you missed it: http://janoma.cl/post/using-disjoint-sets-with-a-vector/

rank propertymap used to store the size of a set (element -> std::size_t). see union by rank
parent propertymap used to store the parent of an element (element -> element). see path compression
findcompress optional argument defining the find method. default to find_with_full_path_compression see here (default should be what you need).

note that "the boost property map library contains a few adaptors that convert commonly used data-structures that implement a mapping operation, such as builtin arrays (pointers), iterators, and std::map, to have the property map interface"

this list of these adaptors (like boost::associative_property_map) can be found here .

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C++ – Understanding boost::disjoint_sets

boost c++ disjoint-sets

I need to use boost::disjoint_sets, but the documentation is unclear to me. Can someone please explain what each template parameter means, and perhaps give a small example code for creating a disjoint_sets?

As per the request, I am using disjoint_sets to implement Tarjan's off-line least common ancestors algorithm , i.e – the value type should be vertex_descriptor.

Best Solution

What I can understand from the documentation :

Disjoint need to associate a rank and a parent (in the forest tree) to each element. Since you might want to work with any kind of data you may,for example, not always want to use a map for the parent: with integer an array is sufficient. You also need a rank foe each element (the rank needed for the union-find).

You'll need two "properties" :

one to associate an integer to each element (first template argument), the rank
one to associate an element to an other one (second template argument), the fathers

On an example :

Arrays are used &rank[0], &parent[0] to the type in the template is int*

For a more complex example (using maps) you can look at Ugo's answer.

You are just giving to the algorithm two structures to store the data (rank/parent) he needs.

Categorizing smart pointers

scoped_ptr is a smart pointer that is neither transferable nor sharable. It's just usable if you locally need to allocate memory, but be sure it's freed again when it goes out of scope. But it can still be swapped with another scoped_ptr, if you wish to do so.

shared_ptr is a smart pointer that shares ownership (third kind above). It is reference counted so it can see when the last copy of it goes out of scope and then it frees the object managed.

weak_ptr is a non-owning smart pointer. It is used to reference a managed object (managed by a shared_ptr) without adding a reference count. Normally, you would need to get the raw pointer out of the shared_ptr and copy that around. But that would not be safe, as you would not have a way to check when the object was actually deleted. So, weak_ptr provides means by referencing an object managed by shared_ptr. If you need to access the object, you can lock the management of it (to avoid that in another thread a shared_ptr frees it while you use the object) and then use it. If the weak_ptr points to an object already deleted, it will notice you by throwing an exception. Using weak_ptr is most beneficial when you have a cyclic reference: Reference counting cannot easily cope with such a situation.

intrusive_ptr is like a shared_ptr but it does not keep the reference count in a shared_ptr but leaves incrementing/decrementing the count to some helper functions that need to be defined by the object that is managed. This has the advantage that an already referenced object (which has a reference count incremented by an external reference counting mechanism) can be stuffed into an intrusive_ptr - because the reference count is not anymore internal to the smart pointer, but the smart pointer uses an existing reference counting mechanism.

unique_ptr is a transfer of ownership pointer. You cannot copy it, but you can move it by using C++1x's move constructors:

This is the semantic that std::auto_ptr obeys, but because of missing native support for moving, it fails to provide them without pitfalls. unique_ptr will automatically steal resources from a temporary other unique_ptr which is one of the key features of move semantics. auto_ptr will be deprecated in the next C++ Standard release in favor of unique_ptr. C++1x will also allow stuffing objects that are only movable but not copyable into containers. So you can stuff unique_ptr's into a vector for example. I'll stop here and reference you to a fine article about this if you want to read more about this.

C++ – How to use Boost in Visual Studio 2010

While Nate's answer is pretty good already, I'm going to expand on it more specifically for Visual Studio 2010 as requested, and include information on compiling in the various optional components which requires external libraries.

If you are using headers only libraries, then all you need to do is to unarchive the boost download and set up the environment variables. The instruction below set the environment variables for Visual Studio only, and not across the system as a whole. Note you only have to do it once.

Unarchive the latest version of boost (1.47.0 as of writing) into a directory of your choice (e.g. C:\boost_1_47_0 ).
Create a new empty project in Visual Studio.
Open the Property Manager and expand one of the configuration for the platform of your choice.
Select & right click Microsoft.Cpp.<Platform>.user , and select Properties to open the Property Page for edit.
Select VC++ Directories on the left.
Edit the Include Directories section to include the path to your boost source files.
Repeat steps 3 - 6 for different platform of your choice if needed.

If you want to use the part of boost that require building, but none of the features that requires external dependencies, then building it is fairly simple.

Start the Visual Studio Command Prompt for the platform of your choice and navigate to where boost is.
Run: bootstrap.bat to build b2.exe (previously named bjam).
Win32: b2 --toolset=msvc-10.0 --build-type=complete stage ;
x64: b2 --toolset=msvc-10.0 --build-type=complete architecture=x86 address-model=64 stage

Go for a walk / watch a movie or 2 / ....

Go through steps 2 - 6 from the set of instruction above to set the environment variables.
Edit the Library Directories section to include the path to your boost libraries output. (The default for the example and instructions above would be C:\boost_1_47_0\stage\lib . Rename and move the directory first if you want to have x86 & x64 side by side (such as to <BOOST_PATH>\lib\x86 & <BOOST_PATH>\lib\x64 ).
Repeat steps 2 - 6 for different platform of your choice if needed.

If you want the optional components, then you have more work to do. These are:

Boost.IOStreams Bzip2 filters

Boost.IOStreams Zlib filters

Boost.Python

Boost.Regex ICU support

Boost.IOStreams Bzip2 filters:

Unarchive the latest version of bzip2 library (1.0.6 as of writing) source files into a directory of your choice (e.g. C:\bzip2-1.0.6 ).
Follow the second set of instructions above to build boost, but add in the option -sBZIP2_SOURCE="C:\bzip2-1.0.6" when running b2 in step 5.
Unarchive the latest version of zlib library (1.2.5 as of writing) source files into a directory of your choice (e.g. C:\zlib-1.2.5 ).
Follow the second set of instructions above to build boost, but add in the option -sZLIB_SOURCE="C:\zlib-1.2.5" when running b2 in step 5.
Install a MPI distribution such as Microsoft Compute Cluster Pack.
Follow steps 1 - 3 from the second set of instructions above to build boost.
Edit the file project-config.jam in the directory <BOOST_PATH> that resulted from running bootstrap. Add in a line that read using mpi ; (note the space before the ';').
Follow the rest of the steps from the second set of instructions above to build boost. If auto-detection of the MPI installation fail, then you'll need to look for and modify the appropriate build file to look for MPI in the right place.
Install a Python distribution such as ActiveState's ActivePython. Make sure the Python installation is in your PATH.

To completely built the 32-bits version of the library requires 32-bits Python, and similarly for the 64-bits version. If you have multiple versions installed for such reason, you'll need to tell b2 where to find specific version and when to use which one. One way to do that would be to edit the file project-config.jam in the directory <BOOST_PATH> that resulted from running bootstrap. Add in the following two lines adjusting as appropriate for your Python installation paths & versions (note the space before the ';').

using python : 2.6 : C:\\Python\\Python26\\python ;

using python : 2.6 : C:\\Python\\Python26-x64\\python : : : <address-model>64 ;

Do note that such explicit Python specification currently cause MPI build to fail. So you'll need to do some separate building with and without specification to build everything if you're building MPI as well.

Follow the second set of instructions above to build boost.

Unarchive the latest version of ICU4C library (4.8 as of writing) source file into a directory of your choice (e.g. C:\icu4c-4_8 ).
Open the Visual Studio Solution in <ICU_PATH>\source\allinone .
Build All for both debug & release configuration for the platform of your choice. There can be a problem building recent releases of ICU4C with Visual Studio 2010 when the output for both debug & release build are in the same directory (which is the default behaviour). A possible workaround is to do a Build All (of debug build say) and then do a Rebuild all in the 2nd configuration (e.g. release build).
If building for x64, you'll need to be running x64 OS as there's post build steps that involves running some of the 64-bits application that it's building.
Optionally remove the source directory when you're done.
Follow the second set of instructions above to build boost, but add in the option -sICU_PATH="C:\icu4c-4_8" when running b2 in step 5.