* Bug #14271 fixed - conjgrad() displayed an incorrect error message about number of arguments.
+* Bug #14297 fixed - Updated cumsum y=cumsum(x) description. It was just a copy-paste of the help page "sum"
+
* Bug #14347 fixed - plot2d crashed with multiple entries (non regression test).
* Bug #14359 fixed - Black Hole demo updated. Stop and Clear buttons did not have priority tag set. Callback_type property has been added and set to 10.
</refnamediv>
<refsynopsisdiv>
<title>Syntax</title>
- <synopsis>y=cumsum(x)</synopsis>
- <synopsis>y=cumsum(x,orientation)</synopsis>
- <synopsis>y=cumsum(x,outtype)</synopsis>
- <synopsis>y=cumsum(x,orientation,outtype)</synopsis>
+ <synopsis>y=cumsum(x)
+ y=cumsum(x,orientation)
+ y=cumsum(x,outtype)
+ y=cumsum(x,orientation,outtype)
+ </synopsis>
</refsynopsisdiv>
- <refsection>
+
+ <refsection role="parameters">
<title>Arguments</title>
<variablelist>
<varlistentry>
</varlistentry>
</variablelist>
</refsection>
- <refsection>
+
+ <refsection role="description">
<title>Description</title>
<para>
- For an array <literal>x</literal>, <literal>y=cumsum(x)</literal> returns in the scalar <literal>y</literal> the cumulative sum of all the elements of <literal>x</literal>.
+ Returns the cumulative sum of array elements.
+ For an array <term>x</term>, <literal>y=cumsum(x)</literal> a matrix <term>y</term> of the same size as <term>x</term>.
+ The value <literal>y(i)</literal> is the sum of all elements of <literal>x(1:i)</literal> <emphasis role="italic">i.e.</emphasis>:
</para>
<para>
- <literal>y=cumsum(x,orientation)</literal> returns in <literal>y</literal> the cumulative sum of <literal>x</literal> along the dimension given by <literal>orientation</literal>:
+ <latex><![CDATA[ y(i) = \sum_{k=1}^i x(k)]]></latex>
+ </para>
+ <para>
+ <literal>y=cumsum(x,orientation)</literal> returns in <term>y</term> the cumulative sum of <term>x</term> along the dimension given by <term>orientation</term>:
</para>
<itemizedlist>
<listitem>
<para>
- if <literal>orientation</literal> is equal to 1 or "r" then:
+ if <term>orientation</term> is equal to 1 or "r" then:
</para>
<para>
<latex><![CDATA[ y(\mathbf{l},j) = \sum_{\mathbf{i}=1}^l x(\mathbf{i},j)]]></latex>
</listitem>
<listitem>
<para>
- if <literal>orientation</literal> is equal to 2 or "c" then:
+ if <term>orientation</term> is equal to 2 or "c" then:
</para>
<para>
<latex><![CDATA[ y(i,\mathbf{l}) = \sum_{\mathbf{j}=1}^l x(i,{\mathbf{j})]]></latex>
</listitem>
<listitem>
<para>
- if <literal>orientation</literal> is equal to n then:
+ if <term>orientation</term> is equal to n then:
</para>
<para>
<latex><![CDATA[ y(i_1,\ldots,i_{n-1},\mathbf{l},i_{n+1},\ldots) = \sum_{\mathbf{i_n}=1}^l x(i_1,\ldots,i_{n-1},\mathbf{i_n},i_{n+1},\ldots)]]></latex>
</listitem>
<listitem>
<para>
- <literal>y=cumsum(x,"m")</literal> is equivalent to <literal>y=cumsum(x,orientation)</literal> where <literal>orientation</literal> is the index of the first dimension of <literal>x</literal> that is greater than 1. This option is used for Matlab compatibility.
+ <literal>y=cumsum(x,"m")</literal> is equivalent to <literal>y=cumsum(x,orientation)</literal> where <term>orientation</term> is the index of the first dimension of <term>x</term> that is greater than 1. This option is used for Matlab compatibility.
</para>
</listitem>
</itemizedlist>
<para/>
<para>
- The <literal>outtype</literal> argument rules the way the summation is done:
+ The <term>outtype</term> argument rules the way the summation is done:
</para>
<itemizedlist>
<listitem>
<listitem>
<para>For arrays of integers,</para>
<para>
- if <literal>outtype="native"</literal> the evaluation is done using integer computations (modulo 2^b, where b is the number of bits used),
+ if <literal>outtype="native"</literal> the evaluation is done using integer computations (modulo 2^b, where b is the number of bits used),
</para>
<para>
if <literal>outtype="double"</literal> the evaluation is done using floating point computations.
<listitem>
<para>For arrays of booleans,</para>
<para>
- if <literal>outtype="native"</literal> the evaluation is done using boolean computations ( + is replaced by |),
+ if <literal>outtype="native"</literal> the evaluation is done using boolean computations ( + is replaced by |),
</para>
<para>
if <literal>outtype="double"</literal> the evaluation is done using floating point computations (%t values are replaced by 1 and %f values by 0).
</listitem>
</itemizedlist>
</refsection>
- <refsection>
+
+ <refsection role="remark">
<title>Remark</title>
<para>
This function applies, with identical rules to <link linkend="sparse">sparse matrices</link> and <link linkend="hypermat">hypermatrices</link>.
</para>
</refsection>
- <refsection>
+
+ <refsection role="examples">
<title>Examples</title>
<programlisting role="example"><![CDATA[
A=[1,2;3,4];
cumsum(B,"native") //similar to or(B)
]]></programlisting>
</refsection>
+
<refsection role="see also">
<title>See Also</title>
<simplelist type="inline">
y=cumsum(x,orientation,outtype)
</synopsis>
</refsynopsisdiv>
- <refsection>
+
+ <refsection role="parameters">
<title>Paramètres</title>
<variablelist>
<varlistentry>
<term>x</term>
<listitem>
<para>un tableau de réels, de complexes, de booléens, de
- polynômes ou de fractions rationnelles.
+ polynômes ou de fractions rationnelles.
</para>
</listitem>
</varlistentry>
<term>orientation</term>
<listitem>
<para>
- Cet argument peut être
+ Cet argument peut être
</para>
<itemizedlist>
<listitem>
<term>outtype</term>
<listitem>
<para>
- une chaîne de caractères pouvant prendre les valeurs <literal>"native"</literal> ou <literal>"double"</literal>.
+ une chaîne de caractères pouvant prendre les valeurs <literal>"native"</literal> ou <literal>"double"</literal>.
</para>
</listitem>
</varlistentry>
<refsection>
<title>Description</title>
<para>
- Pour un tableau <literal>x</literal>,
- <literal>y=cumsum(x)</literal> renvoie dans <literal>y</literal>
- la somme cumulative de tous les éléments de
- <literal>x</literal>.
+ Renvoie la somme cumulée des éléments d'un tableau.
+ Pour un tableau <term>x</term>,
+ <literal>y=cumsum(x)</literal> renvoie une matrice <term>y</term>
+ de la même taille que <term>x</term>.
+ La valeur <literal>y(i)</literal> est la somme de tous les éléments de <literal>x(1:i)</literal>, <emphasis role="italic">i.e.</emphasis> :
+ </para>
+ <para>
+ <latex><![CDATA[ y(i) = \sum_{k=1}^i x(k)]]></latex>
</para>
<para>
<literal>y=cumsum(x,orientation)</literal> retourne dans
- <literal>y</literal> la somme cumulée des éléments de
- <literal>x</literal> le long de la dimension donnée par le
- paramètre <literal>orientation</literal>:
+ <term>y</term> la somme cumulée des éléments de
+ <term>x</term> le long de la dimension donnée par le
+ paramètre <term>orientation</term>:
</para>
<itemizedlist>
<listitem>
<para>
- Si <literal>orientation</literal> est égal à 1 ou "r" alors :
+ Si <term>orientation</term> est égal à 1 ou "r" alors :
</para>
<para>
<latex><![CDATA[ y(\mathbf{l},j) = \sum_{\mathbf{i}=1}^l x(\mathbf{i},j)]]></latex>
</listitem>
<listitem>
<para>
- Si <literal>orientation</literal> est égal à 2 ou "c" alors :
+ Si <term>orientation</term> est égal à 2 ou "c" alors :
</para>
<para>
<latex><![CDATA[ y(i,\mathbf{l}) = \sum_{\mathbf{j}=1}^l x(i,{\mathbf{j})]]></latex>
</listitem>
<listitem>
<para>
- Si <literal>orientation</literal> est égal à n alors :
+ Si <term>orientation</term> est égal à n alors :
</para>
<para>
<latex><![CDATA[ y(i_1,\ldots,i_{n-1},\mathbf{l},i_{n+1},\ldots) = \sum_{\mathbf{i_n}=1}^l x(i_1,\ldots,i_{n-1},\mathbf{i_n},i_{n+1},\ldots)]]></latex>
</listitem>
<listitem>
<para>
- <literal>y=cumsum(x,"*")</literal> est équivalent à <literal>y=cumsum(x)</literal>
+ <literal>y=cumsum(x,"*")</literal> est équivalent à <literal>y=cumsum(x)</literal>
</para>
</listitem>
<listitem>
<para>
<literal>y=cumsum(x,"m")</literal> est équivalent à
<literal>y=cumsum(x,orientation)</literal> où
- <literal>orientation</literal> est l'index de la première
- dimension de <literal>x</literal> qui est plus grande que
- 1. Cette option est utilisé pour la compatibilité avec Matlab.
+ <term>orientation</term> est l'index de la première
+ dimension de <term>x</term> qui est plus grande que
+ 1. Cette option est utilisé pour la compatibilité avec Matlab.
</para>
</listitem>
</itemizedlist>
<para>
- L'argument <literal>outtype</literal> gère la façon dont le produit est réalisé :
+ L'argument <term>outtype</term> gère la façon dont le produit est réalisé :
</para>
<itemizedlist>
<listitem>
- <para>Pour les matrices de doubles, de polynômes, de fractions rationnelles,
+ <para>Pour les matrices de doubles, de polynômes, de fractions rationnelles,
l'évaluation est toujours effetuée sur des nombres à virgule flottante.
- Les options <literal>"double"</literal> ou <literal>"native"</literal> sont équivalentes
+ Les options <literal>"double"</literal> ou <literal>"native"</literal> sont équivalentes
(par défaut, <literal>outtype = "double"</literal>).
</para>
</listitem>
(modulo 2^b, où b est le nombre de bits utilisés).
</para>
<para>
- si <literal>outtype="double"</literal>, le calcul est effectué sur
+ si <literal>outtype="double"</literal>, le calcul est effectué sur
des nombres à virgule flottante.
</para>
<para>
<listitem>
<para>Pour les tableaux de booléens,</para>
<para>
- si <literal>outtype="native"</literal>, le calcul est effectué sur des booléens
+ si <literal>outtype="native"</literal>, le calcul est effectué sur des booléens
(* est remplacée par &),
</para>
<para>
- si <literal>outtype="double"</literal>, le calcul est effectué sur des nombres
+ si <literal>outtype="double"</literal>, le calcul est effectué sur des nombres
à virgule flottante (%t est remplacé par 1 et %f par 0).
</para>
<para>
</refsection>
<refsection>
<title>Exemples</title>
- <programlisting role="example"><![CDATA[
+ <programlisting role="example"><![CDATA[
A=[1,2;3,4];
cumsum(A)
cumsum(A,1)
<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns5="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="cumsum" xml:lang="ja">
<refnamediv>
-
<refname>cumsum</refname>
-
<refpurpose>配列要素の累積和</refpurpose>
-
</refnamediv>
<refsynopsisdiv>
-
<title>呼び出し手順</title>
-
- <synopsis>y=cumsum(x)</synopsis>
-
- <synopsis>y=cumsum(x,orientation)</synopsis>
-
- <synopsis>y=cumsum(x,outtype)</synopsis>
-
- <synopsis>y=cumsum(x,orientation,outtype)</synopsis>
-
+ <synopsis>
+ y=cumsum(x)
+ y=cumsum(x,orientation)
+ y=cumsum(x,outtype)
+ y=cumsum(x,orientation,outtype)
+ </synopsis>
</refsynopsisdiv>
- <refsection>
-
+ <refsection role="parameters">
<title>引数</title>
-
<variablelist>
-
<varlistentry>
-
<term>x</term>
-
<listitem>
-
<para>
-
実数,複素数,論理値,多項式または有理数の配列
-
</para>
-
</listitem>
-
</varlistentry>
-
<varlistentry>
-
<term>orientation</term>
-
<listitem>
-
<para>
-
以下のどちらかを指定します
-
</para>
-
<itemizedlist>
-
<listitem>
-
<para>
-
文字列で,指定可能な値は
-
- <literal>"*"</literal>, <literal>"r"</literal>,
-
+ <literal>"*"</literal>, <literal>"r"</literal>,
<literal>"c"</literal> または <literal>"m"</literal>
-
</para>
-
</listitem>
-
<listitem>
-
<para>正の整数値</para>
-
</listitem>
-
</itemizedlist>
-
</listitem>
-
</varlistentry>
-
<varlistentry>
-
<term>outtype</term>
-
<listitem>
-
<para>
-
文字列で,指定可能な値は
-
<literal>"native"</literal> または
-
- <literal>"double"</literal>.
-
+ <literal>"double"</literal>.
</para>
-
</listitem>
-
</varlistentry>
-
<varlistentry>
-
<term>y</term>
-
<listitem>
-
<para>スカラーまたは配列</para>
-
</listitem>
-
</varlistentry>
-
</variablelist>
-
</refsection>
- <refsection>
-
+ <refsection role="description">
<title>説明</title>
-
<para>
-
- <literal>x</literal>は配列の場合,<literal>y=cumsum(x)</literal> は,
-
- <literal>x</literal>の全要素の累積和を
-
- スカラー<literal>y</literal>に返します.
-
+ <term>x</term>は配列の場合,<literal>y=cumsum(x)</literal> は,
+ <term>x</term>の全要素の累積和を
+ スカラー<term>y</term>に返します:
</para>
-
<para>
-
<literal>y=cumsum(x,orientation)</literal> は
-
- <literal>orientation</literal>により指定された次元方向の
-
- <literal>x</literal> の累積和を<literal>y</literal>に返します:
-
+ <term>orientation</term>により指定された次元方向の
+ <term>x</term> の累積和を<term>y</term>に返します:
+ </para>
+ <para>
+ <latex><![CDATA[ y(i) = \sum_{k=1}^i x(k)]]></latex>
</para>
-
<itemizedlist>
-
<listitem>
-
<para>
-
- <literal>orientation</literal> が 1 または "r" の場合:
-
+ <term>orientation</term> が 1 または "r" の場合:
</para>
-
<para>
-
<latex><![CDATA[ y(\mathbf{l},j) = \sum_{\mathbf{i}=1}^l x(\mathbf{i},j)]]></latex>
-
</para>
-
<para>または </para>
-
<para>
-
<latex><![CDATA[ y(\mathbf{l},j,k,\ldots) = \sum_{\mathbf{i}=1}^l x(\mathbf{i},j,k,\ldots)]]></latex>
-
</para>
-
</listitem>
-
<listitem>
-
<para>
-
- <literal>orientation</literal> が 2 または "c" の場合:
-
+ <term>orientation</term> が 2 または "c" の場合:
</para>
-
<para>
-
<latex><![CDATA[ y(i,\mathbf{l}) = \sum_{\mathbf{j}=1}^l x(i,{\mathbf{j})]]></latex>
-
</para>
-
<para> または </para>
-
<para>
-
<latex><![CDATA[ y(i,\mathbf{l},k,\ldots) = \sum_{\mathbf{j}=1}^l x(i,\mathbf{j},k,\ldots)]]></latex>
-
</para>
-
</listitem>
-
<listitem>
-
<para>
-
- <literal>orientation</literal> が n の場合:
-
+ <term>orientation</term> が n の場合:
</para>
-
<para>
-
<latex><![CDATA[ y(i_1,\ldots,i_{n-1},\mathbf{l},i_{n+1},\ldots) = \sum_{\mathbf{i_n}=1}^l x(i_1,\ldots,i_{n-1},\mathbf{i_n},i_{n+1},\ldots)]]></latex>
-
</para>
-
</listitem>
-
<listitem>
-
<para>
-
<literal>y=cumsum(x,"*")</literal> は
-
<literal>y=cumsum(x)</literal>と等価です.
-
</para>
-
</listitem>
-
<listitem>
-
<para>
-
<literal>y=cumsum(x,"m")</literal> は
-
<literal>y=cumsum(x,orientation)</literal> と等価です.
-
ただし, <literal>orientation</literal> は
-
- <literal>x</literal>の1より大きい最初の次元の添字です.
-
+ <term>x</term>の1より大きい最初の次元の添字です.
このオプションはMatlabとの互換性のために使用されます.
-
</para>
-
</listitem>
-
</itemizedlist>
-
<para/>
-
<para>
-
- <literal>outtype</literal>引数は総和の動作を指定します:
-
+ <term>outtype</term>引数は総和の動作を指定します:
</para>
-
<itemizedlist>
-
<listitem>
-
<para>
-
float, 多項式 有理数の配列の場合, 評価は浮動小数点演算により
-
行われます.
-
<literal>"double"</literal> または <literal>"native"</literal>
-
オプションは等価です.
-
</para>
-
</listitem>
-
<listitem>
-
<para>整数の配列の場合,</para>
-
<para>
-
<literal>outtype="native"</literal>の時,
-
評価は整数演算(モジュロ 2^b, ただし b は使用されるビット数)で行われます,
-
</para>
-
<para>
-
<literal>outtype="double"</literal>の時,評価は浮動小数点演算により
-
行われます.
-
</para>
-
<para>
-
デフォルト値は <literal>outtype="native"</literal>です.
-
</para>
-
</listitem>
-
<listitem>
-
<para>論理値の配列の場合,</para>
-
<para>
-
<literal>outtype="native"</literal>の時,評価は論理値演算
-
(+ は | で置換)により行われます,
-
</para>
-
<para>
-
<literal>outtype="double"</literal>の時,評価は
-
浮動小数点演算(%t は 1, %f は 0で置換)により行われます.
-
</para>
-
<para>
-
デフォルト値は<literal>outtype="double"</literal>です.
-
</para>
-
</listitem>
-
</itemizedlist>
-
</refsection>
- <refsection>
-
+ <refsection role="remark">
<title>注意</title>
-
<para>
-
この関数には,
-
<link linkend="sparse">疎行列</link> および
-
<link linkend="hypermat">ハイパー行列</link>と
-
同じ規則が適用されます.
-
</para>
-
</refsection>
- <refsection>
-
+ <refsection role="examples">
<title>例</title>
-
<programlisting role="example"><![CDATA[
A=[1,2;3,4];
cumsum(A)
cumsum(A,1)
-
I=uint8([2 95 103;254 9 0])
cumsum(I) //native evaluation
cumsum(I,"double")
cumsum(I,2,"double")
-
s=poly(0,"s");
P=[s,%i+s;s^2,1];
cumsum(P),
cumsum(P,2)
-
B=[%t %t %f %f];
cumsum(B) //evaluation in float
cumsum(B,"native") //similar to or(B)
]]></programlisting>
-
</refsection>
<refsection role="see also">
-
<title>参照</title>
-
<simplelist type="inline">
-
<member>
-
<link linkend="sum">sum</link>
-
</member>
-
<member>
-
<link linkend="cumprod">cumprod</link>
-
</member>
-
</simplelist>
-
</refsection>
</refentry>
-
*
-->
<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns4="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="cumsum" xml:lang="en">
+
<refnamediv>
<refname>cumsum</refname>
<refpurpose>soma cumulativa</refpurpose>
</refnamediv>
+
<refsynopsisdiv>
<title>Seqüência de Chamamento</title>
<synopsis>y=cumsum(x)
y=cumsum(x,'c') or y=cumsum(x,2)
</synopsis>
</refsynopsisdiv>
- <refsection>
+
+ <refsection role="parameters">
<title>Parâmetros</title>
<variablelist>
<varlistentry>
</varlistentry>
</variablelist>
</refsection>
- <refsection>
+
+ <refsection role="description">
<title>Descrição</title>
<para>
- Para um vetor ou uma matriz <literal>x</literal>,
- <literal>y=cumsum(x)</literal> retorna em <literal>y</literal> a soma
- cumulativa de todas as entradas de <literal>x</literal> tomadas coluna a
+ Para um vetor ou uma matriz <term>x</term>,
+ <literal>y=cumsum(x)</literal> retorna em <term>y</term> a soma
+ cumulativa de todas as entradas de <term>x</term> tomadas coluna a
coluna.
</para>
<para>
- <literal>y=cumsum(x,'c')</literal> (ou, equivalentemente,
- <literal>y=cumsum(x,2)</literal>) retorna em <literal>y</literal> a soma
- cumulativa das colunas de <literal>x</literal>: <literal>
- y(i,:)=cumsum(x(i,:))
- </literal>
+ <latex><![CDATA[ y(i) = \sum_{k=1}^i x(k)]]></latex>
</para>
<para>
<literal>y=cumsum(x,'r')</literal> (ou, equivalentemente,
<literal>y=cumsum(x,1)</literal>) retorna em <literal>y</literal> a soma
- cumulativa das linhas de <literal>x</literal>: <literal>
+ cumulativa das linhas de <term>x</term>: <literal>
y(:,i)=cumsum(x(:,i))
</literal>
</para>
<para>
+ <latex><![CDATA[ y(\mathbf{l},j) = \sum_{\mathbf{i}=1}^l x(\mathbf{i},j)]]></latex>
+ </para>
+ <para>or </para>
+ <para>
+ <latex><![CDATA[ y(\mathbf{l},j,k,\ldots) = \sum_{\mathbf{i}=1}^l x(\mathbf{i},j,k,\ldots)]]></latex>
+ </para>
+ <para>
+ <literal>y=cumsum(x,'c')</literal> (ou, equivalentemente,
+ <literal>y=cumsum(x,2)</literal>) retorna em <term>y</term> a soma
+ cumulativa das colunas de <term>x</term>: <literal>
+ y(i,:)=cumsum(x(i,:))
+ </literal>
+ </para>
+ <para>
+ <latex><![CDATA[ y(i,\mathbf{l}) = \sum_{\mathbf{j}=1}^l x(i,{\mathbf{j})]]></latex>
+ </para>
+ <para> or </para>
+ <para>
+ <latex><![CDATA[ y(i,\mathbf{l},k,\ldots) = \sum_{\mathbf{j}=1}^l x(i,\mathbf{j},k,\ldots)]]></latex>
+ </para>
+ <para>
+ if <term>orientation</term> is equal to n then:
+ </para>
+ <para>
+ <latex><![CDATA[ y(i_1,\ldots,i_{n-1},\mathbf{l},i_{n+1},\ldots) = \sum_{\mathbf{i_n}=1}^l x(i_1,\ldots,i_{n-1},\mathbf{i_n},i_{n+1},\ldots)]]></latex>
+ </para>
+ <para>
+ <literal>y=cumsum(x,"*")</literal> is equivalent to <literal>y=cumsum(x)</literal>
+ </para>
+ <para>
<literal>y=cumsum(x,'m')</literal> é a soma cumulativa ao longo da
- primeira dimensão "não-singleton" de <literal>x</literal> (para
+ primeira dimensão "não-singleton" de <term>x</term> (para
compatibilidade com o Matlab).
</para>
+ <para>
+ The <term>outtype</term> argument rules the way the summation is done:
+ </para>
+ <itemizedlist>
+ <listitem>
+ <para>
+ For arrays of floats, of polynomials, of rational fractions, the evaluation is always done using floating points computations. The <literal>"double"</literal> or <literal>"native"</literal> options are equivalent.
+ </para>
+ </listitem>
+ <listitem>
+ <para>For arrays of integers,</para>
+ <para>
+ if <literal>outtype="native"</literal> the evaluation is done using integer computations (modulo 2^b, where b is the number of bits used),
+ </para>
+ <para>
+ if <literal>outtype="double"</literal> the evaluation is done using floating point computations.
+ </para>
+ <para>
+ The default value is <literal>outtype="native"</literal>.
+ </para>
+ </listitem>
+ <listitem>
+ <para>For arrays of booleans,</para>
+ <para>
+ if <literal>outtype="native"</literal> the evaluation is done using boolean computations ( + is replaced by |),
+ </para>
+ <para>
+ if <literal>outtype="double"</literal> the evaluation is done using floating point computations (%t values are replaced by 1 and %f values by 0).
+ </para>
+ <para>
+ The default value is <literal>outtype="double"</literal>.
+ </para>
+ </listitem>
+ </itemizedlist>
+ </refsection>
+
+ <refsection role="remark">
+ <title>Remark</title>
+ <para>
+ This function applies, with identical rules to <link linkend="sparse">sparse matrices</link> and <link linkend="hypermat">hypermatrices</link>.
+ </para>
</refsection>
- <refsection>
+
+ <refsection role="examples">
<title>Exemplos</title>
- <programlisting role="example"><![CDATA[
+ <programlisting role="example"><![CDATA[
A=[1,2;3,4];
cumsum(A)
cumsum(A,'r')
for k=2:m;w(k,:)=w(k-1,:)+a(k,:);end;w-cumsum(a,'r')
]]></programlisting>
</refsection>
+
<refsection role="see also">
<title>Ver Também</title>
<simplelist type="inline">
</member>
</simplelist>
</refsection>
+
</refentry>
*
-->
<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns5="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xml:id="cumsum" xml:lang="ru">
+
<refnamediv>
<refname>cumsum</refname>
<refpurpose>суммирование элементов массива с накоплением</refpurpose>
</refnamediv>
+
<refsynopsisdiv>
<title>Последовательность вызова</title>
<synopsis>y=cumsum(x)</synopsis>
<synopsis>y=cumsum(x,outtype)</synopsis>
<synopsis>y=cumsum(x,orientation,outtype)</synopsis>
</refsynopsisdiv>
- <refsection>
+
+ <refsection role="parameters">
<title>Аргументы</title>
<variablelist>
<varlistentry>
<term>x</term>
<listitem>
<para>
- массив вещественных, комплексных, логических значений, а также полиномов или
+ массив вещественных, комплексных, логических значений, а также полиномов или
рациональных дробей.
</para>
</listitem>
<term>outtype</term>
<listitem>
<para>
- тип на выходе: строка с возможными значениями:
- <literal>"native"</literal> или <literal>"double"</literal>.
+ тип на выходе: строка с возможными значениями:
+ <literal>"native"</literal> или <literal>"double"</literal>.
</para>
</listitem>
</varlistentry>
</varlistentry>
</variablelist>
</refsection>
- <refsection>
+
+ <refsection role="description">
<title>Описание</title>
<para>
- Для массива <literal>x</literal>, <literal>y=cumsum(x)</literal> возвращает скаляр
- <literal>y</literal>, представляющий сумму всех элементов <literal>x</literal> с
+ Для массива <term>x</term>, <literal>y=cumsum(x)</literal> возвращает скаляр
+ <term>y</term>, представляющий сумму всех элементов <term>x</term> с
накоплением.
</para>
<para>
- <literal>y=cumsum(x,orientation)</literal> возвращает в <literal>y</literal>
- сумму элементов <literal>x</literal> с накоплением по заданной размерности
- <literal>orientation</literal>:
+ <literal>y=cumsum(x,orientation)</literal> возвращает в <term>y</term>
+ сумму элементов <term>x</term> с накоплением по заданной размерности
+ <term>orientation</term>:
+ </para>
+ <para>
+ <latex><![CDATA[ y(i) = \sum_{k=1}^i x(k)]]></latex>
</para>
<itemizedlist>
<listitem>
<para>
- если <literal>orientation</literal> равна 1 или "r", то:
+ если <term>orientation</term> равна 1 или "r", то:
</para>
<para>
<latex><![CDATA[ y(\mathbf{l},j) = \sum_{\mathbf{i}=1}^l x(\mathbf{i},j)]]></latex>
</listitem>
<listitem>
<para>
- если <literal>orientation</literal> равна 2 или "c", то:
+ если <term>orientation</term> равна 2 или "c", то:
</para>
<para>
<latex><![CDATA[ y(i,\mathbf{l}) = \sum_{\mathbf{j}=1}^l x(i,{\mathbf{j})]]></latex>
</listitem>
<listitem>
<para>
- если <literal>orientation</literal> равна n, то:
+ если <term>orientation</term> равна n, то:
</para>
<para>
<latex><![CDATA[ y(i_1,\ldots,i_{n-1},\mathbf{l},i_{n+1},\ldots) = \sum_{\mathbf{i_n}=1}^l x(i_1,\ldots,i_{n-1},\mathbf{i_n},i_{n+1},\ldots)]]></latex>
</itemizedlist>
<para/>
<para>
- Аргумент <literal>outtype</literal> управляет способом, которым производится суммирование:
+ Аргумент <term>outtype</term> управляет способом, которым производится суммирование:
</para>
<itemizedlist>
<listitem>
<para>
- Для массивов чисел с плавающей запятой, полиномов, рациональных дробей
+ Для массивов чисел с плавающей запятой, полиномов, рациональных дробей
вычисление всегда делается через вычисления с плавающей запятой.
- Опции <literal>"double"</literal> и <literal>"native"</literal> ("естественное")
+ Опции <literal>"double"</literal> и <literal>"native"</literal> ("естественное")
эквивалентны.
</para>
</listitem>
<para>
если <literal>outtype="native"</literal> ("естественное"), то вычисление делается через целочисленные вычисления (по модулю 2^b, где b - число используемых битов);
</para>
- <para>
- если <literal>outtype="double"</literal>, то вычисление делается через вычисления
+ <para>
+ если <literal>outtype="double"</literal>, то вычисление делается через вычисления
с плавающей запятой.
</para>
<para>
</listitem>
<listitem>
<para>Для массивов логических значений:</para>
- <para>
- если <literal>outtype="native"</literal> ("естественное"), то вычисления делаются
+ <para>
+ если <literal>outtype="native"</literal> ("естественное"), то вычисления делаются
с помощью булевой алгебры (+ заменяется на |),
</para>
- <para>
+ <para>
если <literal>outtype="double"</literal>, то вычисление делается через вычисления
с плавающей запятой (значения %t заменяются на 1, а значения %f - на 0).
</para>
</listitem>
</itemizedlist>
</refsection>
- <refsection>
+
+ <refsection role="remark">
<title>Примечание</title>
<para>
- Эта функция применяется с аналогичными правилами к <link linkend="sparse">разряжённым
+ Эта функция применяется с аналогичными правилами к <link linkend="sparse">разряжённым
матрицам
</link>
и <link linkend="hypermat">гиперматрицам</link>.
</para>
</refsection>
- <refsection>
+
+ <refsection role="examples">
<title>Примеры</title>
<programlisting role="example"><![CDATA[
A=[1,2;3,4];
cumsum(A)
cumsum(A,1)
-
+
I=uint8([2 95 103;254 9 0])
cumsum(I) //естественное вычисление
cumsum(I,"double")
cumsum(I,2,"double")
-
+
s=poly(0,"s");
P=[s,%i+s;s^2,1];
cumsum(P),
cumsum(P,2)
-
+
B=[%t %t %f %f];
cumsum(B) //вычисление с плавающей запятой
cumsum(B,"native") //аналогично or(B)
]]></programlisting>
</refsection>
+
<refsection role="see also">
<title>Смотрите также</title>
<simplelist type="inline">
_LaTeX_cumprod.xml_3.png=dac1eef2ec85e26d497e63441494fb62
_LaTeX_cumprod.xml_4.png=d82dfaf597c37928175acc260e516802
_LaTeX_cumprod.xml_5.png=2557e0856332b1a8e4a4328a56e057fd
-_LaTeX_cumsum.xml_1.png=23dfe1e8f3cffd55bfcdf54e31c7c1cc
-_LaTeX_cumsum.xml_2.png=4c76951440e86518a6c419fb7c536c05
-_LaTeX_cumsum.xml_3.png=c9333b61aa171fd3a354f95f095d39eb
-_LaTeX_cumsum.xml_4.png=83945d3c6a18056a1fcd585d40e11705
-_LaTeX_cumsum.xml_5.png=1e00ceeb4652920c0f75ee7c5ee7f525
+_LaTeX_cumsum.xml_1.png=d3b46046b899184c069d6938b393faa2
+_LaTeX_cumsum.xml_2.png=23dfe1e8f3cffd55bfcdf54e31c7c1cc
+_LaTeX_cumsum.xml_3.png=4c76951440e86518a6c419fb7c536c05
+_LaTeX_cumsum.xml_4.png=c9333b61aa171fd3a354f95f095d39eb
+_LaTeX_cumsum.xml_5.png=83945d3c6a18056a1fcd585d40e11705
+_LaTeX_cumsum.xml_6.png=1e00ceeb4652920c0f75ee7c5ee7f525
_LaTeX_damp.xml_1.png=f2c8fd47d5a080d24791f46bc185c706
_LaTeX_damp.xml_2.png=195246810f9bfc228bca491859062b14
_LaTeX_damp.xml_3.png=f2c8fd47d5a080d24791f46bc185c706
projects / scilab.git / commitdiff
