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[project @ 1996-07-24 18:05:43 by jwe]
author | jwe |
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date | Wed, 24 Jul 1996 18:08:39 +0000 |
parents | b1a56412c385 |
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@c Copyright (C) 1996 John W. Eaton @c This is part of the Octave manual. @c For copying conditions, see the file gpl.texi. @node Special Matrices, Matrix Manipulation, Input and Output, Top @chapter Special Matrices Octave provides a number of functions for creating special matrix forms. In nearly all cases, it is best to use the built-in functions for this purpose than to try to use other tricks to achieve the same effect. @menu * Special Utility Matrices:: * Famous Matrices:: @end menu @node Special Utility Matrices, Famous Matrices, Special Matrices, Special Matrices @section Special Utility Matrices @findex eye The function @code{eye} returns an identity matrix. If invoked with a single scalar argument, @code{eye} returns a square matrix with the dimension specified. If you supply two scalar arguments, @code{eye} takes them to be the number of rows and columns. If given a matrix or vector argument, @code{eye} returns an identity matrix with the same dimensions as the given argument. For example, @example eye (3) @end example @noindent creates an identity matrix with three rows and three columns, @example eye (5, 8) @end example @noindent creates an identity matrix with five rows and eight columns, and @example eye ([13, 21; 34, 55]) @end example @noindent creates an identity matrix with two rows and two columns. Normally, @code{eye} expects any scalar arguments you provide to be real and non-negative. The variables @code{ok_to_lose_imaginary_part} and @code{treat_neg_dim_as_zero} control the behavior of @code{eye} for complex and negative arguments. @xref{User Preferences}. Any non-integer arguments are rounded to the nearest integer value. There is an ambiguity when these functions are called with a single argument. You may have intended to create a matrix with the same dimensions as another variable, but ended up with something quite different, because the variable that you used as an argument was a scalar instead of a matrix. For example, if you need to create an identity matrix with the same dimensions as another variable in your program, it is best to use code like this @example eye (rows (a), columns (a)) @end example @noindent instead of just @example eye (a) @end example @noindent unless you know that the variable @var{a} will @emph{always} be a matrix. @findex ones @findex zeros @findex rand The functions @code{ones}, @code{zeros}, and @code{rand} all work like @code{eye}, except that they fill the resulting matrix with all ones, all zeros, or a set of random values. If you need to create a matrix whose values are all the same, you should use an expression like @example val_matrix = val * ones (n, m) @end example The @code{rand} function also takes some additional arguments that allow you to control its behavior. For example, the function call @example rand ("normal") @end example @noindent causes the sequence of numbers to be normally distributed. You may also use an argument of @code{"uniform"} to select a uniform distribution. To find out what the current distribution is, use an argument of @code{"dist"}. Normally, @code{rand} obtains the seed from the system clock, so that the sequence of random numbers is not the same each time you run Octave. If you really do need for to reproduce a sequence of numbers exactly, you can set the seed to a specific value. For example, the function call @example rand ("seed", 13) @end example @noindent sets the seed to the number 13. To see what the current seed is, use the argument @code{"seed"}. If it is invoked without arguments, @code{rand} returns a single element of a random sequence. The @code{rand} function uses Fortran code from RANLIB, a library of fortran routines for random number generation, compiled by Barry W. Brown and James Lovato of the Department of Biomathematics at The University of Texas, M.D. Anderson Cancer Center, Houston, TX 77030. @findex diag To create a diagonal matrix with vector @var{v} on diagonal @var{k}, use the function diag (@var{v}, @var{k}). The second argument is optional. If it is positive, the vector is placed on the @var{k}-th super-diagonal. If it is negative, it is placed on the @var{-k}-th sub-diagonal. The default value of @var{k} is 0, and the vector is placed on the main diagonal. For example, @example octave:13> diag ([1, 2, 3], 1) ans = 0 1 0 0 0 0 2 0 0 0 0 3 0 0 0 0 @end example @findex linspace @findex logspace The functions @code{linspace} and @code{logspace} make it very easy to create vectors with evenly or logarithmically spaced elements. For example, @example linspace (@var{base}, @var{limit}, @var{n}) @end example @noindent creates a row vector with @var{n} (@var{n} greater than 2) linearly spaced elements between @var{base} and @var{limit}. The @var{base} and @var{limit} are always included in the range. If @var{base} is greater than @var{limit}, the elements are stored in decreasing order. If the number of points is not specified, a value of 100 is used. The function @code{logspace} is similar to @code{linspace} except that the values are logarithmically spaced. If @var{limit} is equal to @iftex @tex $\pi$, @end tex @end iftex @ifinfo pi, @end ifinfo the points are between @iftex @tex $10^{base}$ and $\pi$, @end tex @end iftex @ifinfo 10^base and pi, @end ifinfo @emph{not} @iftex @tex $10^{base}$ and $10^{\pi}$, @end tex @end iftex @ifinfo 10^base and 10^pi, @end ifinfo in order to be compatible with the corresponding @sc{Matlab} function. The @code{linspace} and @code{logspace} functions always return row vectors, regardless of the value of @code{prefer_column_vectors}. @xref{Ranges}. @node Famous Matrices, , Special Utility Matrices, Special Matrices @section Famous Matrices The following functions return famous matrix forms. @ftable @code @item hadamard (@var{k}) Return the Hadamard matrix of order n = 2^k. @item hankel (@var{c}, @var{r}) Return the Hankel matrix constructed given the first column @var{c}, and (optionally) the last row @var{r}. If the last element of @var{c} is not the same as the first element of @var{r}, the last element of @var{c} is used. If the second argument is omitted, the last row is taken to be the same as the first column. A Hankel matrix formed from an m-vector @var{c}, and an n-vector @var{r}, has the elements @iftex @tex $$ H (i, j) = \cases{c_{i+j-1},&$i+j-1\le m$;\cr r_{i+j-m},&otherwise.\cr} $$ @end tex @end iftex @ifinfo @example @group H (i, j) = c (i+j-1), i+j-1 <= m; H (i, j) = r (i+j-m), otherwise @end group @end example @end ifinfo @item hilb (@var{n}) Return the Hilbert matrix of order @var{n}. The @iftex @tex $i,\,j$ @end tex @end iftex @ifinfo i, j @end ifinfo element of a Hilbert matrix is defined as @iftex @tex $$ H (i, j) = {1 \over (i + j - 1)} $$ @end tex @end iftex @ifinfo @example H (i, j) = 1 / (i + j - 1) @end example @end ifinfo @item invhilb (@var{n}) Return the inverse of a Hilbert matrix of order @var{n}. This is exact. Compare with the numerical calculation of @code{inverse (hilb (n))}, which suffers from the ill-conditioning of the Hilbert matrix, and the finite precision of your computer's floating point arithmetic. @item toeplitz (@var{c}, @var{r}) Return the Toeplitz matrix constructed given the first column @var{c}, and (optionally) the first row @var{r}. If the first element of @var{c} is not the same as the first element of @var{r}, the first element of @var{c} is used. If the second argument is omitted, the first row is taken to be the same as the first column. A square Toeplitz matrix has the form @iftex @tex $$ \left[\matrix{c_0 & r_1 & r_2 & \ldots & r_n\cr c_1 & c_0 & r_1 & & c_{n-1}\cr c_2 & c_1 & c_0 & & c_{n-2}\cr \vdots & & & & \vdots\cr c_n & c_{n-1} & c_{n-2} & \ldots & c_0}\right]. $$ @end tex @end iftex @ifinfo @example @group c(0) r(1) r(2) ... r(n) c(1) c(0) r(1) r(n-1) c(2) c(1) c(0) r(n-2) . . . . . . c(n) c(n-1) c(n-2) ... c(0) @end group @end example @end ifinfo @item vander (@var{c}) Return the Vandermonde matrix whose next to last column is @var{c}. A Vandermonde matrix has the form @iftex @tex $$ \left[\matrix{c_0^n & \ldots & c_0^2 & c_0 & 1\cr c_1^n & \ldots & c_1^2 & c_1 & 1\cr \vdots & & \vdots & \vdots & \vdots\cr c_n^n & \ldots & c_n^2 & c_n & 1}\right]. $$ @end tex @end iftex @ifinfo @example @group c(0)^n ... c(0)^2 c(0) 1 c(1)^n ... c(1)^2 c(1) 1 . . . . . . . . . . . . c(n)^n ... c(n)^2 c(n) 1 @end group @end example @end ifinfo @end ftable