japanese translation updated.
[scilab.git] / scilab / modules / sparse / help / ja_JP / sparseconvert / sparse.xml
1 <?xml version="1.0" encoding="UTF-8"?>
2
3 <!--
4  * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab
5  * Copyright (C) XXXX-2008 - INRIA
6  * 
7  * This file must be used under the terms of the CeCILL.
8  * This source file is licensed as described in the file COPYING, which
9  * you should have received as part of this distribution.  The terms
10  * are also available at    
11  * http://www.cecill.info/licences/Licence_CeCILL_V2.1-en.txt
12  *
13  -->
14
15 <refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="ja" xml:id="sparse">
16     
17     <refnamediv>
18         
19         <refname>sparse</refname>
20         
21         <refpurpose>疎行列を定義</refpurpose>
22         
23     </refnamediv>
24     
25     <refsynopsisdiv>
26         
27         <title>呼び出し手順</title>
28         
29         <synopsis>sp=sparse(X)
30             
31             sp=sparse(ij,v [,mn])
32             
33         </synopsis>
34         
35     </refsynopsisdiv>
36     
37     <refsection>
38         
39         <title>引数</title>
40         
41         <variablelist>
42             
43             <varlistentry>
44                 
45                 <term>X</term>
46                 
47                 <listitem>
48                     
49                     <para>実数または複素数の通常の(または疎)行列</para>
50                     
51                 </listitem>
52                 
53             </varlistentry>
54             
55             <varlistentry>
56                 
57                 <term>ij</term>
58                 
59                 <listitem>
60                     
61                     <para>2列の整数行列 (非ゼロエントリのインデックス)</para>
62                     
63                 </listitem>
64                 
65             </varlistentry>
66             
67             <varlistentry>
68                 
69                 <term>v</term>
70                 
71                 <listitem>
72                     
73                     <para>ベクトル</para>
74                     
75                 </listitem>
76                 
77             </varlistentry>
78             
79             <varlistentry>
80                 
81                 <term>mn</term>
82                 
83                 <listitem>
84                     
85                     <para>2つのエントリ(行の次元, 列の次元c)を有する整数ベクトル</para>
86                     
87                 </listitem>
88                 
89             </varlistentry>
90             
91             <varlistentry>
92                 
93                 <term>sp</term>
94                 
95                 <listitem>
96                     
97                     <para>疎行列</para>
98                     
99                 </listitem>
100                 
101             </varlistentry>
102             
103         </variablelist>
104         
105     </refsection>
106     
107     <refsection>
108         
109         <title>説明</title>
110         
111         <para>
112             
113             <literal>sparse</literal>は疎行列を作成するために使用されます.
114             
115             ゼロでないエントリのみが保存されます.
116             
117         </para>
118         
119         <para>
120             
121             <literal>sp = sparse(X)</literal>  は,
122             
123             0要素を除外することにより,通常の行列を疎行列に変換します.
124             
125             (<literal>X</literal>が既に疎行列の場合,
126             
127             <literal>sp</literal>は<literal>X</literal>となります).
128             
129         </para>
130         
131         <para>
132             
133             <literal>sp=sparse(ij,v [,mn])</literal>は,
134             
135             <literal>sp(ij(k,1),ij(k,2))=v(k)</literal>となる
136             
137             <literal>mn(1)</literal>行<literal>mn(2)</literal>列の疎行列
138             
139             を作成します.
140             
141             <literal>ij</literal> および <literal>v</literal>は列の次元が
142             
143             同じである必要があります.
144             
145             オプションの<literal>mn</literal>パラメータが指定されない場合,
146             
147             行列<literal>sp</literal>の次元は,それぞれ
148             
149             <literal>ij(:,1)</literal> および <literal>ij(:,2)</literal>の
150             
151             最大値となります.
152             
153         </para>
154         
155         <para>
156             
157             疎行列に関する操作(結合,加算,等,)は通常の行列と同じ構文により
158             
159             行ないます.
160             
161         </para>
162         
163         <para>
164             
165             基本的な関数(<literal>abs,maxi,sum,diag,...</literal>)は疎行列でも
166             
167             利用可能です.
168             
169         </para>
170         
171         <para>
172             
173             (通常の行列と疎行列の)混用も可能です.
174             
175             結果は処理に応じて通常または疎行列となります.
176             
177         </para>
178         
179         <para>
180             
181             注意 : 
182             
183             同じ大きさの通常の行列を含む任意の演算は,
184             
185             引数(例: <literal>sp=sparse(d)</literal>),
186             
187             または,結果(例  <literal>d= sp + 1.</literal>) のどちら
188             
189             についても利便性のために提供されていますが,当然避けるべきです.
190             
191             更に,要素(<literal>sp(r,c)</literal>)へのランダムアクセス,
192             
193             特に挿入,は効率的ではありません.
194             
195             このため,性能面の制約があるアクセスでは,
196             
197             読込みアクセスは<link linkend="spget">spget</link>,
198             
199             書込みアクセスは<literal>sp=sparse(ij, v, mn)</literal>による
200             
201             バッチ処理により行う必要があります.
202             
203         </para>
204         
205     </refsection>
206     
207     <refsection>
208         
209         <title>例</title>
210         
211         <programlisting role="example"><![CDATA[
212 sp=sparse([1,2;4,5;3,10],[1,2,3])
213 size(sp)
214 x=rand(2,2);abs(x)-full(abs(sparse(x)))
215 // sparse constructor taking a single dense matrix
216 // removes the zeros.
217 dense=[0., 1., 0., 0., 0.,
218 1., 0., 2., 0., 0.
219 0., 0., 0., 0., 0.
220 0., 0., 0., 0., -0.5];
221 sp=sparse(dense)
222 // complex matrices are also supported
223 sp=sparse(dense*(1+2*%i))
224 // for boolean matrices, the boolean sparse matrix
225 // only stores true values (and removes false values).
226 dense=[%F, %F, %T, %F, %F
227 %T, %F, %F, %F, %F
228 %F, %F, %F, %F, %F
229 %F, %F, %F, %F, %T];
230 sp=sparse(dense)
231
232  ]]></programlisting>
233         
234     </refsection>
235     
236     <refsection role="see also">
237         
238         <title>参照</title>
239         
240         <simplelist type="inline">
241             
242             <member>
243                 
244                 <link linkend="full">full</link>
245                 
246             </member>
247             
248             <member>
249                 
250                 <link linkend="spget">spget</link>
251                 
252             </member>
253             
254             <member>
255                 
256                 <link linkend="sprand">sprand</link>
257                 
258             </member>
259             
260             <member>
261                 
262                 <link linkend="speye">speye</link>
263                 
264             </member>
265             
266             <member>
267                 
268                 <link linkend="lufact">lufact</link>
269                 
270             </member>
271             
272         </simplelist>
273         
274     </refsection>
275     
276 </refentry>
277