# Generated from unionf-0.1.0.gem by gem2rpm -*- rpm-spec -*-
%global gem_name unionf

Name: rubygem-%{gem_name}
Version: 0.1.0
Release: 1%{?dist}
Summary: Union-find algorithm
License: MIT
URL: http://www.github.com/Schweigert/unionf
Source0: https://rubygems.org/gems/%{gem_name}-%{version}.gem
BuildRequires: ruby(release)
BuildRequires: rubygems-devel
BuildRequires: ruby
BuildArch: noarch

%description
In computer science, a disjoint-set data structure, also called a
union–find data structure or merge–find set, is a data structure that keeps
track of a set of elements partitioned into a number of disjoint
(non-overlapping) subsets. It provides near-constant-time operations (bounded
by the inverse Ackermann function) to add new sets, to merge existing sets,
and to determine whether elements are in the same set. In addition to many
other uses (see the Applications section), disjoint-sets play a key role in
Kruskal's algorithm for finding the minimum spanning tree of a graph.
A disjoint-set forest consists of a number of elements each of which stores an
id, a parent pointer, and, in efficient algorithms, a value called the "rank".
The parent pointers of elements are arranged to form one or more trees, each
representing a set. If an element's parent pointer points to no other element,
then the element is the root of a tree and is the representative member of its
set. A set may consist of only a single element. However, if the element has a
parent, the element is part of whatever set is identified by following the
chain of parents upwards until a representative element (one without a parent)
is reached at the root of the tree.
Forests can be represented compactly in memory as arrays in which parents are
indicated by their array index.
Disjoint-set data structures model the partitioning of a set, for example to
keep track of the connected components of an undirected graph. This model can
then be used to determine whether two vertices belong to the same component,
or whether adding an edge between them would result in a cycle. The Union–Find
algorithm is used in high-performance implementations of unification.
This data structure is used by the Boost Graph Library to implement its
Incremental Connected Components functionality. It is also a key component in
implementing Kruskal's algorithm to find the minimum spanning tree of a graph.
Note that the implementation as disjoint-set forests doesn't allow the
deletion of edges, even without path compression or the rank heuristic.
Sharir and Agarwal report connections between the worst-case behavior of
disjoint-sets and the length of Davenport–Schinzel sequences, a combinatorial
structure from computational geometry.
.


%package doc
Summary: Documentation for %{name}
Requires: %{name} = %{version}-%{release}
BuildArch: noarch

%description doc
Documentation for %{name}.

%prep
%setup -q -n %{gem_name}-%{version}

%build
# Create the gem as gem install only works on a gem file
gem build ../%{gem_name}-%{version}.gemspec

# %%gem_install compiles any C extensions and installs the gem into ./%%gem_dir
# by default, so that we can move it into the buildroot in %%install
%gem_install

%install
mkdir -p %{buildroot}%{gem_dir}
cp -a .%{gem_dir}/* \
        %{buildroot}%{gem_dir}/



%check
pushd .%{gem_instdir}
# Run the test suite.
popd

%files
%dir %{gem_instdir}
%exclude %{gem_instdir}/.gitignore
%license %{gem_instdir}/LICENSE.txt
%{gem_instdir}/bin
%{gem_libdir}
%exclude %{gem_cache}
%{gem_spec}

%files doc
%doc %{gem_docdir}
%{gem_instdir}/Gemfile
%doc %{gem_instdir}/README.md
%{gem_instdir}/Rakefile
%{gem_instdir}/unionf.gemspec

%changelog
* Thu Sep 16 2021 mockbuilder - 0.1.0-1
- Initial package