?? eigen.html,v
字號:
<A NAME="next_i"><!-- --></A><H3>next_i</H3><PRE>public static int <B>next_i</B></PRE><DL><DL></DL></DL><HR><A NAME="next_ip"><!-- --></A><H3>next_ip</H3><PRE>public static int <B>next_ip</B></PRE><DL><DL></DL></DL><!-- ========= CONSTRUCTOR DETAIL ======== --><A NAME="constructor_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TH></TR></TABLE><A NAME="Eigen()"><!-- --></A><H3>Eigen</H3><PRE>public <B>Eigen</B>()</PRE><DL></DL><!-- ============ METHOD DETAIL ========== --><A NAME="method_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Method Detail</B></FONT></TH></TR></TABLE><A NAME="ludcmp(int, int[], double[][], java.lang.Double)"><!-- --></A><H3>ludcmp</H3><PRE>public static void <B>ludcmp</B>(int n, int[] indx, double[][] a, java.lang.Double d)</PRE><DL><DD>given a matrix a[1..n][1..n], this routine replaces it by the LU decomposition of a row wise permutation of itself. this routine is combined with lubksb to solve linear equations to invert a matrix. see numerical recipes, the art of scientific computing, second edition, cambridge university press. pages 46 - 47.<P><DD><DL><DT><B>Parameters:</B><DD><CODE>n</CODE> - dimensions of the input square matrix<DD><CODE>indx</CODE> - row permutations effected by partial pivoting<DD><CODE>a</CODE> - input matrix<DD><CODE>d</CODE> - +/- 1, if row interchanges was even or odd respectively</DL></DD></DL><HR><A NAME="linearSolve(Matrix, double, double[], double[])"><!-- --></A><H3>linearSolve</H3><PRE>public static void <B>linearSolve</B>(<A HREF="Matrix.html" title="class in <Unnamed>">Matrix</A> M, double eigVal, double[] y, double[] x)</PRE><DL><DD>this routine uses the ludcmp and lubksb routines to find eigenvectors corresponding to a given eigen value using the inverse iteration method. see numerical recipes, the art of scientific computing, second edition, cambridge university press. pages 493 - 495<P><DD><DL><DT><B>Parameters:</B><DD><CODE>M</CODE> - input matrix<DD><CODE>eigVal</CODE> - eigen value<DD><CODE>y</CODE> - random vector<DD><CODE>x</CODE> - random vector</DL></DD></DL><HR><A NAME="normEigVec(double, double[])"><!-- --></A><H3>normEigVec</H3><PRE>public static void <B>normEigVec</B>(double eigVal, double[] eigVec)</PRE><DL><DD>an Eigenvalue 'eigVal' and the corresponding Eigenvectors this method normalizes the eigen vectors i.e. divides each Eigenvector with the square root of the corresponding Eigenvalue<P><DD><DL><DT><B>Parameters:</B><DD><CODE>eigVal</CODE> - eigen value<DD><CODE>eigVec</CODE> - eigen vectors</DL></DD></DL><HR><A NAME="calcEigVec(Matrix, double, double[])"><!-- --></A><H3>calcEigVec</H3><PRE>public static void <B>calcEigVec</B>(<A HREF="Matrix.html" title="class in <Unnamed>">Matrix</A> M, double eigVal, double[] eigVec)</PRE><DL><DD>given a matrix 'M', an Eigenvalue 'eigVal', calculate the the Eigenvector 'eigVec'<P><DD><DL><DT><B>Parameters:</B><DD><CODE>M</CODE> - input matrix<DD><CODE>eigVal</CODE> - eigen value<DD><CODE>eigVec</CODE> - eigen vectors</DL></DD></DL><HR><A NAME="random_unit_vector(double[], int)"><!-- --></A><H3>random_unit_vector</H3><PRE>public static void <B>random_unit_vector</B>(double[] x, int dim)</PRE><DL><DD>this routine generates a random vector of length dim with unit size<P><DD><DL><DT><B>Parameters:</B><DD><CODE>x</CODE> - input vector<DD><CODE>dim</CODE> - vector dimension</DL></DD></DL><HR><A NAME="myrandom()"><!-- --></A><H3>myrandom</H3><PRE>public static double <B>myrandom</B>()</PRE><DL><DD>this routine uses knuth's subtractive algorithm to generate uniform random numbers in (0, 1) return random number between 0 and 1<P><DD><DL></DL></DD></DL><HR><A NAME="norm_vector(double[], int)"><!-- --></A><H3>norm_vector</H3><PRE>public static void <B>norm_vector</B>(double[] V, int dim)</PRE><DL><DD>this routine takes in a vector and normalizes the vector<P><DD><DL><DT><B>Parameters:</B><DD><CODE>V</CODE> - input vector<DD><CODE>dim</CODE> - vector dimension</DL></DD></DL><HR><A NAME="vector_len(double[], int)"><!-- --></A><H3>vector_len</H3><PRE>public static double <B>vector_len</B>(double[] V, int dim)</PRE><DL><DD>this routine returns the length of the vector<P><DD><DL><DT><B>Parameters:</B><DD><CODE>V</CODE> - input vector<DD><CODE>dim</CODE> - vector dimension</DL></DD></DL><HR><A NAME="copy_FV(double[], double[], int)"><!-- --></A><H3>copy_FV</H3><PRE>public static void <B>copy_FV</B>(double[] src, double[] dest, int dim)</PRE><DL><DD>this routine copies one vectors contents to another<P><DD><DL><DT><B>Parameters:</B><DD><CODE>src</CODE> - source vector<DD><CODE>dest</CODE> - destination vector<DD><CODE>dim</CODE> - vector dimension</DL></DD></DL><HR><A NAME="Euclidian_Distance(double[], double[], int)"><!-- --></A><H3>Euclidian_Distance</H3><PRE>public static double <B>Euclidian_Distance</B>(double[] S1, double[] S2, int dim)</PRE><DL><DD>this function computes the euclidean distance between two vwctors<P><DD><DL><DT><B>Parameters:</B><DD><CODE>S1</CODE> - first vector<DD><CODE>S2</CODE> - second vector<DD><CODE>dim</CODE> - vector dimension<DT><B>Returns:</B><DD>Euclidian Distance</DL></DD></DL><HR><A NAME="hqr(Matrix, double[], double[])"><!-- --></A><H3>hqr</H3><PRE>public static void <B>hqr</B>(<A HREF="Matrix.html" title="class in <Unnamed>">Matrix</A> M, double[] wr, double[] wi)</PRE><DL><DD>this routine finds all eignvalues of an upper hessenberg matrix. see numerical recipes, the art of scientific computing, second edition, cambridge university press. pages 491 - 493.<P><DD><DL><DT><B>Parameters:</B><DD><CODE>M</CODE> - input matrix<DD><CODE>wr</CODE> - real part of the eigen vectors<DD><CODE>wi</CODE> - immaginary part of the eigen vectors</DL></DD></DL><HR><A NAME="elmhes(Matrix)"><!-- --></A><H3>elmhes</H3><PRE>public static void <B>elmhes</B>(<A HREF="Matrix.html" title="class in <Unnamed>">Matrix</A> M)</PRE><DL><DD>this routine reduces a matrix to hessenberg's form by the elimination method. see numerical recipes, the art of scientific computing, second edition, cambridge university press. pages 484 - 486.<P><DD><DL><DT><B>Parameters:</B><DD><CODE>M</CODE> - input matrix</DL></DD></DL><HR><A NAME="balanc(Matrix)"><!-- --></A><H3>balanc</H3><PRE>public static void <B>balanc</B>(<A HREF="Matrix.html" title="class in <Unnamed>">Matrix</A> M)</PRE><DL><DD>given a matrix this routine replaces it by a balanced matrix with identical eigenvalues. see numerical recipes, the art of scientific computing, second edition, cambridge university press. pages 482 - 484.<P><DD><DL><DT><B>Parameters:</B><DD><CODE>M</CODE> - input matrix</DL></DD></DL><HR><A NAME="compEigenVal(Matrix)"><!-- --></A><H3>compEigenVal</H3><PRE>public static double[] <B>compEigenVal</B>(<A HREF="Matrix.html" title="class in <Unnamed>">Matrix</A> T)</PRE><DL><DD>this method computes the eigen values of a symmetric matrix<P><DD><DL><DT><B>Parameters:</B><DD><CODE>T</CODE> - input matrix<DT><B>Returns:</B><DD>eigen values of the input matrix</DL></DD></DL><HR><A NAME="sortEigen(double[])"><!-- --></A><H3>sortEigen</H3><PRE>public static double[] <B>sortEigen</B>(double[] wr)</PRE><DL><DD>this method sorts the eigen values in decreasing order of importance<P><DD><DL><DT><B>Parameters:</B><DD><CODE>wr</CODE> - real eigen values<DT><B>Returns:</B><DD>sorted eigen values in increasing order</DL></DD></DL><!-- ========= END OF CLASS DATA ========= --><HR><!-- ======= START OF BOTTOM NAVBAR ====== --><A NAME="navbar_bottom"><!-- --></A><A HREF="#skip-navbar_bottom" title="Skip navigation links"></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0" SUMMARY=""><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_bottom_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3" SUMMARY=""> <TR ALIGN="center" VALIGN="top"> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-summary.html"><FONT CLASS="NavBarFont1"><B>Package</B></FONT></A> </TD> <TD BGCOLOR="#FFFFFF" CLASS="NavBarCell1Rev"> <FONT CLASS="NavBarFont1Rev"><B>Class</B></FONT> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-tree.html"><FONT CLASS="NavBarFont1"><B>Tree</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="deprecated-list.html"><FONT CLASS="NavBarFont1"><B>Deprecated</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="index-all.html"><FONT CLASS="NavBarFont1"><B>Index</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="help-doc.html"><FONT CLASS="NavBarFont1"><B>Help</B></FONT></A> </TD> </TR></TABLE></TD><TD ALIGN="right" VALIGN="top" ROWSPAN=3><EM></EM></TD></TR><TR><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="DisplayScale.html" title="class in <Unnamed>"><B>PREV CLASS</B></A> <A HREF="IFAlgorithm.html" title="interface in <Unnamed>"><B>NEXT CLASS</B></A></FONT></TD><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="index.html?Eigen.html" target="_top"><B>FRAMES</B></A> <A HREF="Eigen.html" target="_top"><B>NO FRAMES</B></A> <SCRIPT type="text/javascript"> <!-- if(window==top) { document.writeln('<A HREF="allclasses-noframe.html"><B>All Classes</B></A>'); } //--></SCRIPT><NOSCRIPT> <A HREF="allclasses-noframe.html"><B>All Classes</B></A></NOSCRIPT></FONT></TD></TR><TR><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2"> SUMMARY: NESTED | <A HREF="#field_summary">FIELD</A> | <A HREF="#constructor_summary">CONSTR</A> | <A HREF="#method_summary">METHOD</A></FONT></TD><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2">DETAIL: <A HREF="#field_detail">FIELD</A> | <A HREF="#constructor_detail">CONSTR</A> | <A HREF="#method_detail">METHOD</A></FONT></TD></TR></TABLE><A NAME="skip-navbar_bottom"></A><!-- ======== END OF BOTTOM NAVBAR ======= --><HR></BODY></HTML>@?? 快捷鍵說明
復制代碼
Ctrl + C
搜索代碼
Ctrl + F
全屏模式
F11
切換主題
Ctrl + Shift + D
顯示快捷鍵
?
增大字號
Ctrl + =
減小字號
Ctrl + -