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<html><head><title>dlib C++ Library - modularity_clustering_abstract.h</title></head><body bgcolor='white'><pre> |
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<font color='#009900'>// Copyright (C) 2012 Davis E. King ([email protected]) |
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</font><font color='#009900'>// License: Boost Software License See LICENSE.txt for the full license. |
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</font><font color='#0000FF'>#undef</font> DLIB_MODULARITY_ClUSTERING_ABSTRACT_Hh_ |
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<font color='#0000FF'>#ifdef</font> DLIB_MODULARITY_ClUSTERING_ABSTRACT_Hh_ |
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<font color='#0000FF'>#include</font> <font color='#5555FF'><</font>vector<font color='#5555FF'>></font> |
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<font color='#0000FF'>#include</font> "<a style='text-decoration:none' href='../graph_utils/ordered_sample_pair_abstract.h.html'>../graph_utils/ordered_sample_pair_abstract.h</a>" |
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<font color='#0000FF'>#include</font> "<a style='text-decoration:none' href='../graph_utils/sample_pair_abstract.h.html'>../graph_utils/sample_pair_abstract.h</a>" |
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<font color='#0000FF'>namespace</font> dlib |
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<b>{</b> |
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<font color='#009900'>// ----------------------------------------------------------------------------------------- |
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</font> |
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<font color='#0000FF'><u>double</u></font> <b><a name='modularity'></a>modularity</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'>const</font> std::vector<font color='#5555FF'><</font>sample_pair<font color='#5555FF'>></font><font color='#5555FF'>&</font> edges, |
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<font color='#0000FF'>const</font> std::vector<font color='#5555FF'><</font><font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font><font color='#5555FF'>></font><font color='#5555FF'>&</font> labels |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- labels.size() == max_index_plus_one(edges) |
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- for all valid i: |
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- 0 <= edges[i].distance() < std::numeric_limits<double>::infinity() |
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ensures |
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- Interprets edges as an undirected graph. That is, it contains the edges on |
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the said graph and the sample_pair::distance() values define the edge weights |
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(larger values indicating a stronger edge connection between the nodes). |
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- This function returns the modularity value obtained when the given input |
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graph is broken into subgraphs according to the contents of labels. In |
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particular, we say that two nodes with indices i and j are in the same |
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subgraph or community if and only if labels[i] == labels[j]. |
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- Duplicate edges are interpreted as if there had been just one edge with a |
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distance value equal to the sum of all the duplicate edge's distance values. |
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- See the paper Modularity and community structure in networks by M. E. J. Newman |
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for a detailed definition. |
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!*/</font> |
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<font color='#009900'>// ---------------------------------------------------------------------------------------- |
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</font> |
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<font color='#0000FF'><u>double</u></font> <b><a name='modularity'></a>modularity</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'>const</font> std::vector<font color='#5555FF'><</font>ordered_sample_pair<font color='#5555FF'>></font><font color='#5555FF'>&</font> edges, |
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<font color='#0000FF'>const</font> std::vector<font color='#5555FF'><</font><font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font><font color='#5555FF'>></font><font color='#5555FF'>&</font> labels |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- labels.size() == max_index_plus_one(edges) |
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- for all valid i: |
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- 0 <= edges[i].distance() < std::numeric_limits<double>::infinity() |
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ensures |
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- Interprets edges as a directed graph. That is, it contains the edges on the |
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said graph and the ordered_sample_pair::distance() values define the edge |
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weights (larger values indicating a stronger edge connection between the |
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nodes). Note that, generally, modularity is only really defined for |
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undirected graphs. Therefore, the "directed graph" given to this function |
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should have symmetric edges between all nodes. The reason this function is |
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provided at all is because sometimes a vector of ordered_sample_pair objects |
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is a useful representation of an undirected graph. |
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- This function returns the modularity value obtained when the given input |
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graph is broken into subgraphs according to the contents of labels. In |
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particular, we say that two nodes with indices i and j are in the same |
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subgraph or community if and only if labels[i] == labels[j]. |
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- Duplicate edges are interpreted as if there had been just one edge with a |
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distance value equal to the sum of all the duplicate edge's distance values. |
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- See the paper Modularity and community structure in networks by M. E. J. Newman |
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for a detailed definition. |
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!*/</font> |
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<font color='#009900'>// ---------------------------------------------------------------------------------------- |
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</font> |
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<font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font> <b><a name='newman_cluster'></a>newman_cluster</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'>const</font> std::vector<font color='#5555FF'><</font>ordered_sample_pair<font color='#5555FF'>></font><font color='#5555FF'>&</font> edges, |
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std::vector<font color='#5555FF'><</font><font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font><font color='#5555FF'>></font><font color='#5555FF'>&</font> labels, |
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<font color='#0000FF'>const</font> <font color='#0000FF'><u>double</u></font> eps <font color='#5555FF'>=</font> <font color='#979000'>1e</font><font color='#5555FF'>-</font><font color='#979000'>4</font>, |
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<font color='#0000FF'>const</font> <font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font> max_iterations <font color='#5555FF'>=</font> <font color='#979000'>2000</font> |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- is_ordered_by_index(edges) == true |
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- for all valid i: |
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- 0 <= edges[i].distance() < std::numeric_limits<double>::infinity() |
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ensures |
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- This function performs the clustering algorithm described in the paper |
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Modularity and community structure in networks by M. E. J. Newman. |
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- This function interprets edges as a graph and attempts to find the labeling |
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that maximizes modularity(edges, #labels). |
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- returns the number of clusters found. |
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- #labels.size() == max_index_plus_one(edges) |
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- for all valid i: |
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- #labels[i] == the cluster ID of the node with index i in the graph. |
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- 0 <= #labels[i] < the number of clusters found |
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(i.e. cluster IDs are assigned contiguously and start at 0) |
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- The main computation of the algorithm is involved in finding an eigenvector |
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of a certain matrix. To do this, we use the power iteration. In particular, |
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each time we try to find an eigenvector we will let the power iteration loop |
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at most max_iterations times or until it reaches an accuracy of eps. |
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Whichever comes first. |
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!*/</font> |
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<font color='#009900'>// ---------------------------------------------------------------------------------------- |
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</font> |
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<font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font> <b><a name='newman_cluster'></a>newman_cluster</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'>const</font> std::vector<font color='#5555FF'><</font>sample_pair<font color='#5555FF'>></font><font color='#5555FF'>&</font> edges, |
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std::vector<font color='#5555FF'><</font><font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font><font color='#5555FF'>></font><font color='#5555FF'>&</font> labels, |
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<font color='#0000FF'>const</font> <font color='#0000FF'><u>double</u></font> eps <font color='#5555FF'>=</font> <font color='#979000'>1e</font><font color='#5555FF'>-</font><font color='#979000'>4</font>, |
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<font color='#0000FF'>const</font> <font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font> max_iterations <font color='#5555FF'>=</font> <font color='#979000'>2000</font> |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- for all valid i: |
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- 0 <= edges[i].distance() < std::numeric_limits<double>::infinity() |
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ensures |
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- This function is identical to the above newman_cluster() routine except that |
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it operates on a vector of sample_pair objects instead of |
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ordered_sample_pairs. Therefore, this is simply a convenience routine. In |
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particular, it is implemented by transforming the given edges into |
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ordered_sample_pairs and then calling the newman_cluster() routine defined |
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above. |
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!*/</font> |
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<font color='#009900'>// ---------------------------------------------------------------------------------------- |
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</font> |
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<b>}</b> |
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<font color='#0000FF'>#endif</font> <font color='#009900'>// DLIB_MODULARITY_ClUSTERING_ABSTRACT_Hh_ |
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</font> |
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</pre></body></html> |
