forked from materialsproject/pymatgen
-
Notifications
You must be signed in to change notification settings - Fork 0
/
pymatgen.optimization.linear_assignment_numpy.html
140 lines (128 loc) · 6.28 KB
/
pymatgen.optimization.linear_assignment_numpy.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8" />
<title>pymatgen.optimization.linear_assignment_numpy module — pymatgen 2019.5.1 documentation</title>
<link rel="stylesheet" href="_static/proBlue.css" type="text/css" />
<link rel="stylesheet" href="_static/pygments.css" type="text/css" />
<script type="text/javascript" id="documentation_options" data-url_root="./" src="_static/documentation_options.js"></script>
<script type="text/javascript" src="_static/jquery.js"></script>
<script type="text/javascript" src="_static/underscore.js"></script>
<script type="text/javascript" src="_static/doctools.js"></script>
<script type="text/javascript" src="_static/language_data.js"></script>
<script async="async" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS-MML_HTMLorMML"></script>
<link rel="shortcut icon" href="_static/favicon.ico"/>
<link rel="index" title="Index" href="genindex.html" />
<link rel="search" title="Search" href="search.html" />
<script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-33990148-1']);
_gaq.push(['_trackPageview']);
</script>
</head><body>
<div class="related" role="navigation" aria-label="related navigation">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="genindex.html" title="General Index"
accesskey="I">index</a></li>
<li class="right" >
<a href="py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="index.html">pymatgen 2019.5.1 documentation</a> »</li>
</ul>
</div>
<div class="document">
<div class="documentwrapper">
<div class="bodywrapper">
<div class="body" role="main">
<div class="section" id="module-pymatgen.optimization.linear_assignment_numpy">
<span id="pymatgen-optimization-linear-assignment-numpy-module"></span><h1>pymatgen.optimization.linear_assignment_numpy module<a class="headerlink" href="#module-pymatgen.optimization.linear_assignment_numpy" title="Permalink to this headline">¶</a></h1>
<p>This module contains an algorithm to solve the Linear Assignment Problem.
It has the same functionality as linear_assignment.pyx, but is much slower
as it is vectorized in numpy rather than cython</p>
<dl class="class">
<dt id="pymatgen.optimization.linear_assignment_numpy.LinearAssignment">
<em class="property">class </em><code class="descname">LinearAssignment</code><span class="sig-paren">(</span><em>costs</em>, <em>epsilon=1e-06</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pymatgen/optimization/linear_assignment_numpy.html#LinearAssignment"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pymatgen.optimization.linear_assignment_numpy.LinearAssignment" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>This class finds the solution to the Linear Assignment Problem.
It finds a minimum cost matching between two sets, given a cost
matrix.</p>
<p>This class is an implementation of the LAPJV algorithm described in:
R. Jonker, A. Volgenant. A Shortest Augmenting Path Algorithm for
Dense and Sparse Linear Assignment Problems. Computing 38, 325-340
(1987)</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>costs</strong> – The cost matrix of the problem. cost[i,j] should be the
cost of matching x[i] to y[j]. The cost matrix may be
rectangular</p></li>
<li><p><strong>epsilon</strong> – Tolerance for determining if solution vector is < 0</p></li>
</ul>
</dd>
</dl>
<dl class="attribute">
<dt id="pymatgen.optimization.linear_assignment_numpy.LinearAssignment.min_cost">
<code class="descname">min_cost</code><a class="headerlink" href="#pymatgen.optimization.linear_assignment_numpy.LinearAssignment.min_cost" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the cost of the best assignment</p>
</dd></dl>
</dd></dl>
</div>
</div>
</div>
</div>
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
<div class="sphinxsidebarwrapper">
<div role="note" aria-label="source link">
<h3>This Page</h3>
<ul class="this-page-menu">
<li><a href="_sources/pymatgen.optimization.linear_assignment_numpy.rst.txt"
rel="nofollow">Show Source</a></li>
</ul>
</div>
<div id="searchbox" style="display: none" role="search">
<h3>Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="search.html" method="get">
<input type="text" name="q" />
<input type="submit" value="Go" />
</form>
</div>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script>
</div>
</div>
<div class="clearer"></div>
</div>
<div class="related" role="navigation" aria-label="related navigation">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="genindex.html" title="General Index"
>index</a></li>
<li class="right" >
<a href="py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="index.html">pymatgen 2019.5.1 documentation</a> »</li>
</ul>
</div>
<div class="footer" role="contentinfo">
© Copyright 2011, Pymatgen Development Team.
Created using <a href="http://sphinx-doc.org/">Sphinx</a> 2.0.1.
</div>
<div class="footer">This page uses <a href="http://analytics.google.com/">
Google Analytics</a> to collect statistics. You can disable it by blocking
the JavaScript coming from www.google-analytics.com.
<script type="text/javascript">
(function() {
var ga = document.createElement('script');
ga.src = ('https:' == document.location.protocol ?
'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
ga.setAttribute('async', 'true');
document.documentElement.firstChild.appendChild(ga);
})();
</script>
</div>
</body>
</html>